Multilevel Mixture Factor Models
Varriale, Roberta; Vermunt, Jeroen K.
2012-01-01
Factor analysis is a statistical method for describing the associations among sets of observed variables in terms of a small number of underlying continuous latent variables. Various authors have proposed multilevel extensions of the factor model for the analysis of data sets with a hierarchical structure. These Multilevel Factor Models (MFMs)…
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...... statebased on an idealized mechanical model to be adapted to the original limit state by the model correction factor. Reliable approximations are obtained by iterative use of gradient information on the original limit state function analogously to previous response surface approaches. However, the strength...... 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...
1993-01-01
Jack is an advanced human factors software package that provides a three dimensional model for predicting how a human will interact with a given system or environment. It can be used for a broad range of computer-aided design applications. Jack was developed by the computer Graphics Research Laboratory of the University of Pennsylvania with assistance from NASA's Johnson Space Center, Ames Research Center and the Army. It is the University's first commercial product. Jack is still used for academic purposes at the University of Pennsylvania. Commercial rights were given to Transom Technologies, Inc.
Shell model and spectroscopic factors
Energy Technology Data Exchange (ETDEWEB)
Poves, P. [Madrid Univ. Autonoma and IFT, UAM/CSIC, E-28049 (Spain)
2007-07-01
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)
The cyclical component factor model
DEFF Research Database (Denmark)
Dahl, Christian Møller; Hansen, Henrik; Smidt, John
Forecasting using factor models based on large data sets have received ample attention due to the models' ability to increase forecast accuracy with respect to a range of key macroeconomic variables in the US and the UK. However, forecasts based on such factor models do not uniformly outperform...... the simple autoregressive model when using data from other countries. In this paper we propose to estimate the factors based on the pure cyclical components of the series entering the large data set. Monte Carlo evidence and an empirical illustration using Danish data shows that this procedure can indeed...
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.
Bayesian Estimation of Categorical Dynamic Factor Models
Zhang, Zhiyong; Nesselroade, John R.
2007-01-01
Dynamic factor models have been used to analyze continuous time series behavioral data. We extend 2 main dynamic factor model variations--the direct autoregressive factor score (DAFS) model and the white noise factor score (WNFS) model--to categorical DAFS and WNFS models in the framework of the underlying variable method and illustrate them with…
The Infinite Hierarchical Factor Regression Model
Rai, Piyush
2009-01-01
We propose a nonparametric Bayesian factor regression model that accounts for uncertainty in the number of factors, and the relationship between factors. To accomplish this, we propose a sparse variant of the Indian Buffet Process and couple this with a hierarchical model over factors, based on Kingman's coalescent. We apply this model to two problems (factor analysis and factor regression) in gene-expression data analysis.
A Two-Factor Model of Temperament
Evans, David E.; Rothbart, Mary K.
2009-01-01
The higher order structure of temperament was examined in two studies using the Adult Temperament Questionnaire. Because previous research showed robust levels of convergence between Rothbart’s constructs of temperament and the Big Five factors, we hypothesized a higher order two-factor model of temperament based on Digman’s higher order two-factor model of personality traits derived from factor analysis of the Big Five factors. Study 1 included 258 undergraduates. Digman’s model did not fit ...
Robust and Sparse Factor Modelling
DEFF Research Database (Denmark)
Croux, Christophe; Exterkate, Peter
Factor construction methods are widely used to summarize a large panel of variables by means of a relatively small number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness to outliers and of sparsity; that is, having relatively few...... nonzero factor loadings. Compared to the traditional factor construction method, we find that this procedure leads to a favorable forecasting performance in the presence of outliers and to better interpretable factors. We investigate the performance of the method in a Monte Carlo experiment...
Mackey, Jon; Sehirlioglu, Alp; Dynys, Fred
2014-01-01
A set of convenient thermoelectric device solutions have been derived in order to capture a number of factors which are previously only resolved with numerical techniques. The concise conversion efficiency equations derived from governing equations provide intuitive and straight-forward design guidelines. These guidelines allow for better device design without requiring detailed numerical modeling. The analytical modeling accounts for factors such as i) variable temperature boundary conditions, ii) lateral heat transfer, iii) temperature variable material properties, and iv) transient operation. New dimensionless parameters, similar to the figure of merit, are introduced including the device design factor, fin factor, thermal diffusivity factor, and inductance factor. These new device factors allow for the straight-forward description of phenomenon generally only captured with numerical work otherwise. As an example a device design factor of 0.38, which accounts for thermal resistance of the hot and cold shoes, can be used to calculate a conversion efficiency of 2.28 while the ideal conversion efficiency based on figure of merit alone would be 6.15. Likewise an ideal couple with efficiency of 6.15 will be reduced to 5.33 when lateral heat is accounted for with a fin factor of 1.0.
Shape Factor Modeling and Simulation
2016-06-01
10 3. Shape Factor Distributions for Natural Fragments 12 3.1 Platonic Solids and Uniform Viewing from All Viewpoints 12 3.2 Natural Fragments from...12 Fig. 9 The 5 Platonic solids. ............................................................. 12 Fig. 10 Mean shape factor of...of the 5 Platonic solids............................................ 13 Table 3 Sequence of viewing angles in Icosahedron Gage
Skewed factor models using selection mechanisms
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.
Modeling Ability Differentiation in the Second-Order Factor Model
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,…
Modeling ability differentiation in the second-order factor model
Molenaar, D.; Dolan, C.V.; van der Maas, H.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
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...... features for representing the surface and its dynamics: a general dynamic factor model, restricted factor models designed to capture the key features of the surface along the moneyness and maturity dimensions, and in-between spline-based methods. Key findings are that: (i) the restricted and spline......-based models are both rejected against the general dynamic factor model, (ii) the factors driving the surface are highly persistent, (iii) for the restricted models option Delta is preferred over the more often used strike relative to spot price as measure for moneyness....
Cardinality constrained portfolio selection via factor models
Monge, Juan Francisco
2017-01-01
In this paper we propose and discuss different 0-1 linear models in order to solve the cardinality constrained portfolio problem by using factor models. Factor models are used to build portfolios to track indexes, together with other objectives, also need a smaller number of parameters to estimate than the classical Markowitz model. The addition of the cardinality constraints limits the number of securities in the portfolio. Restricting the number of securities in the portfolio allows us to o...
Comparison of Transcription Factor Binding Site Models
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.
System Identification by Dynamic Factor Models
C. Heij (Christiaan); W. Scherrer; M. Destler
1996-01-01
textabstractThis paper concerns the modelling of stochastic processes by means of dynamic factor models. In such models the observed process is decomposed into a structured part called the latent process, and a remainder that is called noise. The observed variables are treated in a symmetric way, so
Model correction factor method for system analysis
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager; Johannesen, Johannes M.
2000-01-01
The Model Correction Factor Method is an intelligent response surface method based on simplifiedmodeling. MCFM is aimed for reliability analysis in case of a limit state defined by an elaborate model. Herein it isdemonstrated that the method is applicable for elaborate limit state surfaces on which...... severallocally most central points exist without there being a simple geometric definition of the corresponding failuremodes such as is the case for collapse mechanisms in rigid plastic hinge models for frame structures. Taking as simplifiedidealized model a model of similarity with the elaborate model...... surface than existing in the idealized model....
Bayesian Constrained-Model Selection for Factor Analytic Modeling
Peeters, Carel F.W.
2016-01-01
My dissertation revolves around Bayesian approaches towards constrained statistical inference in the factor analysis (FA) model. Two interconnected types of restricted-model selection are considered. These types have a natural connection to selection problems in the exploratory FA (EFA) and confirmatory FA (CFA) model and are termed Type I and Type II model selection. Type I constrained-model selection is taken to mean the determination of the appropriate dimensionality of a model. This type ...
Continuous utility factor in segregation models
Roy, Parna; Sen, Parongama
2016-02-01
We consider the constrained Schelling model of social segregation in which the utility factor of agents strictly increases and nonlocal jumps of the agents are allowed. In the present study, the utility factor u is defined in a way such that it can take continuous values and depends on the tolerance threshold as well as the fraction of unlike neighbors. Two models are proposed: in model A the jump probability is determined by the sign of u only, which makes it equivalent to the discrete model. In model B the actual values of u are considered. Model A and model B are shown to differ drastically as far as segregation behavior and phase transitions are concerned. In model A, although segregation can be achieved, the cluster sizes are rather small. Also, a frozen state is obtained in which steady states comprise many unsatisfied agents. In model B, segregated states with much larger cluster sizes are obtained. The correlation function is calculated to show quantitatively that larger clusters occur in model B. Moreover for model B, no frozen states exist even for very low dilution and small tolerance parameter. This is in contrast to the unconstrained discrete model considered earlier where agents can move even when utility remains the same. In addition, we also consider a few other dynamical aspects which have not been studied in segregation models earlier.
The asset pricing model of musharakah factors
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.
Factor Copula Models for Replicated Spatial Data
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.
Smits, Iris A.M.; Timmerman, Marieke E.; Stegeman, Alwin
Maximum likelihood estimation of the linear factor model for continuous items assumes normally distributed item scores. We consider deviations from normality by means of a skew-normally distributed factor model or a quadratic factor model. We show that the item distributions under a skew-normal
Aging Successfully: A Four-Factor Model
Lee, Pai-Lin; Lan, William; Yen, Tung-Wen
2011-01-01
The study was designed to validate a model for a successful aging process and examine the gender differences in the aging process. Three hundred twelve participants who were 65 or older completed a Taiwan Social Change Survey that measures four factors that define successful aging process: including physical, psychological, social support, and…
Multistructure Statistical Model Applied To Factor Analysis
Bentler, Peter M.
1976-01-01
A general statistical model for the multivariate analysis of mean and covariance structures is described. Matrix calculus is used to develop the statistical aspects of one new special case in detail. This special case separates the confounding of principal components and factor analysis. (DEP)
Aging Successfully: A Four-Factor Model
Lee, Pai-Lin; Lan, William; Yen, Tung-Wen
2011-01-01
The study was designed to validate a model for a successful aging process and examine the gender differences in the aging process. Three hundred twelve participants who were 65 or older completed a Taiwan Social Change Survey that measures four factors that define successful aging process: including physical, psychological, social support, and…
A hierarchical model for ordinal matrix factorization
DEFF Research Database (Denmark)
Paquet, Ulrich; Thomson, Blaise; Winther, Ole
2012-01-01
their ratings for other movies. The Netflix data set is used for evaluation, which consists of around 100 million ratings. Using root mean-squared error (RMSE) as an evaluation metric, results show that the suggested model outperforms alternative factorization techniques. Results also show how Gibbs sampling...
Global Quantitative Modeling of Chromatin Factor Interactions
Zhou, Jian; Troyanskaya, Olga G.
2014-01-01
Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the “chromatin codes”) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles — we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions. PMID:24675896
Connections between Graphical Gaussian Models and Factor Analysis
Salgueiro, M. Fatima; Smith, Peter W. F.; McDonald, John W.
2010-01-01
Connections between graphical Gaussian models and classical single-factor models are obtained by parameterizing the single-factor model as a graphical Gaussian model. Models are represented by independence graphs, and associations between each manifest variable and the latent factor are measured by factor partial correlations. Power calculations…
Smits, Iris A M; Timmerman, Marieke E; Stegeman, Alwin
2016-05-01
Maximum likelihood estimation of the linear factor model for continuous items assumes normally distributed item scores. We consider deviations from normality by means of a skew-normally distributed factor model or a quadratic factor model. We show that the item distributions under a skew-normal factor are equivalent to those under a quadratic model up to third-order moments. The reverse only holds if the quadratic loadings are equal to each other and within certain bounds. We illustrate that observed data which follow any skew-normal factor model can be so well approximated with the quadratic factor model that the models are empirically indistinguishable, and that the reverse does not hold in general. The choice between the two models to account for deviations of normality is illustrated by an empirical example from clinical psychology. © 2015 The British Psychological Society.
Scale Factor Self-Dual Cosmological Models
dS, U Camara; Sotkov, G M
2015-01-01
We implement a conformal time scale factor duality for Friedmann-Robertson-Walker cosmological models, which is consistent with the weak energy condition. The requirement for self-duality determines the equations of state for a broad class of barotropic fluids. We study the example of a universe filled with two interacting fluids, presenting an accelerated and a decelerated period, with manifest UV/IR duality. The associated self-dual scalar field interaction turns out to coincide with the "radiation-like" modified Chaplygin gas models. We present an equivalent realization of them as gauged K\\"ahler sigma models (minimally coupled to gravity) with very specific and interrelated K\\"ahler- and super-potentials. Their applications in the description of hilltop inflation and also as quintessence models for the late universe are discussed.
Modeling Relational Data via Latent Factor Blockmodel
Gao, Sheng; Gallinari, Patrick
2012-01-01
In this paper we address the problem of modeling relational data, which appear in many applications such as social network analysis, recommender systems and bioinformatics. Previous studies either consider latent feature based models but disregarding local structure in the network, or focus exclusively on capturing local structure of objects based on latent blockmodels without coupling with latent characteristics of objects. To combine the benefits of the previous work, we propose a novel model that can simultaneously incorporate the effect of latent features and covariates if any, as well as the effect of latent structure that may exist in the data. To achieve this, we model the relation graph as a function of both latent feature factors and latent cluster memberships of objects to collectively discover globally predictive intrinsic properties of objects and capture latent block structure in the network to improve prediction performance. We also develop an optimization transfer algorithm based on the general...
Human Factors Engineering Program Review Model
2004-02-01
AA NUREG -0711,Rev. 2 Human Factors Engineering Program Review Model 20081009191 I i m To] Bi U.S. Nuclear Regulatory Commission Office of...Material As of November 1999, you may electronically access NUREG -series publications and other NRC records at NRC’s Public Electronic Reading Room at...http://www.nrc.qov/readinq-rm.html. Publicly released records include, to name a few, NUREG -series publications; Federal Register notices; applicant
Space Station crew safety - Human factors model
Cohen, M. M.; Junge, M. K.
1984-01-01
A model of the various human factors issues and interactions that might affect crew safety is developed. The first step addressed systematically the central question: How is this Space Station different from all other spacecraft? A wide range of possible issue was identified and researched. Five major topics of human factors issues that interacted with crew safety resulted: Protocols, Critical Habitability, Work Related Issues, Crew Incapacitation and Personal Choice. Second, an interaction model was developed that would show some degree of cause and effect between objective environmental or operational conditions and the creation of potential safety hazards. The intermediary steps between these two extremes of causality were the effects on human performance and the results of degraded performance. The model contains three milestones: stressor, human performance (degraded) and safety hazard threshold. Between these milestones are two countermeasure intervention points. The first opportunity for intervention is the countermeasure against stress. If this countermeasure fails, performance degrades. The second opportunity for intervention is the countermeasure against error. If this second countermeasure fails, the threshold of a potential safety hazard may be crossed.
Statistical Mechanical Models of Integer Factorization Problem
Nakajima, Chihiro H.; Ohzeki, Masayuki
2017-01-01
We formulate the integer factorization problem via a formulation of the searching problem for the ground state of a statistical mechanical Hamiltonian. The first passage time required to find a correct divisor of a composite number signifies the exponential computational hardness. The analysis of the density of states of two macroscopic quantities, i.e., the energy and the Hamming distance from the correct solutions, leads to the conclusion that the ground state (correct solution) is completely isolated from the other low-energy states, with the distance being proportional to the system size. In addition, the profile of the microcanonical entropy of the model has two peculiar features that are each related to two marked changes in the energy region sampled via Monte Carlo simulation or simulated annealing. Hence, we find a peculiar first-order phase transition in our model.
Human factors engineering program review model
Energy Technology Data Exchange (ETDEWEB)
1994-07-01
The staff of the Nuclear Regulatory Commission is performing nuclear power plant design certification reviews based on a design process plan that describes the human factors engineering (HFE) program elements that are necessary and sufficient to develop an acceptable detailed design specification and an acceptable implemented design. There are two principal reasons for this approach. First, the initial design certification applications submitted for staff review did not include detailed design information. Second, since human performance literature and industry experiences have shown that many significant human factors issues arise early in the design process, review of the design process activities and results is important to the evaluation of an overall design. However, current regulations and guidance documents do not address the criteria for design process review. Therefore, the HFE Program Review Model (HFE PRM) was developed as a basis for performing design certification reviews that include design process evaluations as well as review of the final design. A central tenet of the HFE PRM is that the HFE aspects of the plant should be developed, designed, and evaluated on the basis of a structured top-down system analysis using accepted HFE principles. The HFE PRM consists of ten component elements. Each element in divided into four sections: Background, Objective, Applicant Submittals, and Review Criteria. This report describes the development of the HFE PRM and gives a detailed description of each HFE review element.
Evidence for a General Factor Model of ADHD in Adults
Gibbins, Christopher; Toplak, Maggie E.; Flora, David B.; Weiss, Margaret D.; Tannock, Rosemary
2012-01-01
Objective: To examine factor structures of "Diagnostic and Statistical Manual of Mental Disorders" (4th ed.) symptoms of ADHD in adults. Method: Two sets of models were tested: (a) models with inattention and hyperactivity/impulsivity as separate but correlated latent constructs and (b) hierarchical general factor models with a general factor for…
Taking the Error Term of the Factor Model into Account: The Factor Score Predictor Interval
Beauducel, Andre
2013-01-01
The problem of factor score indeterminacy implies that the factor and the error scores cannot be completely disentangled in the factor model. It is therefore proposed to compute Harman's factor score predictor that contains an additive combination of factor and error variance. This additive combination is discussed in the framework of classical…
Competing Factor Models of Child and Adolescent Psychopathology.
Doyle, Mark M; Murphy, Jamie; Shevlin, Mark
2016-11-01
Co-occurring psychological disorders are highly prevalent among children and adolescents. To date, the most widely utilised factor model used to explain this co-occurrence is the two factor model of internalising and externalising (Achenbach 1966). Several competing models of general psychopathology have since been reported as alternatives, including a recent three factor model of Distress, Fear and Externalising Dimensions (Krueger 1999). Evidence for the three factor model suggests there are advantages to utilising a more complex model. Using the British Child and Adolescent Mental Health Survey 2004 data (B-CAMHS; N = 7997), confirmatory factor analysis was used to test competing factor structure models of child and adolescent psychopathology. The B-CAMHS was an epidemiological survey of children between the ages of 5 and 16 in Great Britain. Child psychological disorders were assessed using the Strength and Difficulties Questionnaire (Goodman 1997), and the Development and Wellbeing Assessment (Goodman et al. 2000). A range of covariates and risk variables including trauma, parent mental health and family functioning where subsequently utilised within a MIMIC model framework to predict each dimension of the 2 and three factor structure models. Two models demonstrated acceptable fit. The first complimented Achenbach's Internalising and Externalising structure. The three factor model was found to have highly comparable fit indices to the two factor model. The second order models did not accurately represent the data nor did an alternative three factor model of Internalising, Externalising and ADHD. The two factor and three factor MIMIC models observed unique profiles of risk for each dimension. The findings suggest that child and adolescent psychopathology may also be accurately conceptualised in terms of distress, fear and externalising dimensions. The MIMIC models demonstrated that the Distress and Fear dimensions have their own unique etiological profile of
Factor Model Forecasts of Exchange Rates
Charles Engel; Nelson C. Mark; Kenneth D. West
2012-01-01
We construct factors from a cross section of exchange rates and use the idiosyncratic deviations from the factors to forecast. In a stylized data generating process, we show that such forecasts can be effective even if there is essentially no serial correlation in the univariate exchange rate processes. We apply the technique to a panel of bilateral U.S. dollar rates against 17 OECD countries. We forecast using factors, and using factors combined with any of fundamentals suggested by Taylor r...
PENGUJIAN FAMA-FRENCH THREE-FACTOR MODEL DI INDONESIA
Directory of Open Access Journals (Sweden)
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.
Quasi Maximum Likelihood Analysis of High Dimensional Constrained Factor Models
Li, Kunpeng; Li,Qi; Lu, Lina
2016-01-01
Factor models have been widely used in practice. However, an undesirable feature of a high dimensional factor model is that the model has too many parameters. An effective way to address this issue, proposed in a seminar work by Tsai and Tsay (2010), is to decompose the loadings matrix by a high-dimensional known matrix multiplying with a low-dimensional unknown matrix, which Tsai and Tsay (2010) name constrained factor models. This paper investigates the estimation and inferential theory ...
Liquidity and Fama-French Three-Factor Model
Institute of Scientific and Technical Information of China (English)
陈政
2012-01-01
The Fama-French three-factor model was proposed to explain the expected return. In this paper,the author takes advantage of the recent data from NYSE, AMEX and NASDAQ stocks to examine whether the Fama-French three-factor model can explain the expected return well on the basis of reviewing the importance of liquidity and criticizing the Fama-French three-factor model. It turns out that the three-factor model can still reflect the factor in asset pricing to a certain degree.
Correlations of MMPI factor scales with measures of the five factor model of personality.
Costa, P T; Busch, C M; Zonderman, A B; McCrae, R R
1986-01-01
Two recent item factor analyses of the Minnesota Multiphasic Personality Inventory (MMPI) classified the resulting factors according to a conceptual scheme offered by Norman's (1963) five factor model. The present article empirically evaluates those classifications by correlating MMPI factor scales with self-report and peer rating measures of the five factor model in a sample of 153 adult men and women. Both sets of predictions were generally supported, although MMPI factors derived in a normal sample showed closer correspondences with the five normal personality dimensions. MMPI factor scales were also correlated with 18 scales measuring specific traits within the broader domains of Neuroticism, Extraversion, and Openness. The nine Costa, Zonderman, McCrae, and Williams (1985) MMPI factor scales appear to give useful global assessments of four of the five factors; other instruments are needed to provide detailed information on more specific aspects of normal personality. The use of the five factor model in routine clinical assessment is discussed.
Stegeman, Alwin
2016-01-01
In the common factor model the observed data is conceptually split into a common covariance producing part and an uncorrelated unique part. The common factor model is fitted to the data itself and a new method is introduced for the simultaneous estimation of loadings, unique variances, factor scores
Stegeman, Alwin
In the common factor model the observed data is conceptually split into a common covariance producing part and an uncorrelated unique part. The common factor model is fitted to the data itself and a new method is introduced for the simultaneous estimation of loadings, unique variances, factor
Heteroscedastic one-factor models and marginal maximum likelihood estimation
Hessen, D.J.; Dolan, C.V.
2009-01-01
In the present paper, a general class of heteroscedastic one-factor models is considered. In these models, the residual variances of the observed scores are explicitly modelled as parametric functions of the one-dimensional factor score. A marginal maximum likelihood procedure for parameter estimati
Factor Model Forecasting of Inflation in Croatia
Directory of Open Access Journals (Sweden)
Davor Kunovac
2007-12-01
Full Text Available This paper tests whether information derived from 144 economic variables (represented by only a few constructed factors can be used for the forecasting of consumer prices in Croatia. The results obtained show that the use of one factor enhances the precision of the benchmark model’s ability to forecast inflation. The methodology used is sufficiently general to be able to be applied directly for the forecasting of other economic variables.
Model correction factor method for system analysis
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager; Johannesen, Johannes M.
2000-01-01
severallocally most central points exist without there being a simple geometric definition of the corresponding failuremodes such as is the case for collapse mechanisms in rigid plastic hinge models for frame structures. Taking as simplifiedidealized model a model of similarity with the elaborate model...... but with clearly defined failure modes, the MCFM can bestarted from each idealized single mode limit state in turn to identify a locally most central point on the elaborate limitstate surface. Typically this procedure leads to a fewer number of locally most central failure points on the elaboratelimit state...... surface than existing in the idealized model....
Supervision in Factor Models Using a Large Number of Predictors
DEFF Research Database (Denmark)
Boldrini, Lorenzo; Hillebrand, Eric Tobias
In this paper we investigate the forecasting performance of a particular factor model (FM) in which the factors are extracted from a large number of predictors. We use a semi-parametric state-space representation of the FM in which the forecast objective, as well as the factors, is included.......g. a standard dynamic factor model with separate forecast and state equations....... in the state vector. The factors are informed of the forecast target (supervised) through the state equation dynamics. We propose a way to assess the contribution of the forecast objective on the extracted factors that exploits the Kalman filter recursions. We forecast one target at a time based...
A model for equivalent axle load factors
Amorim, Sara I.R.; Pais, Jorge; Vale, Aline C.; Minhoto, Manuel
2014-01-01
Most design methods for road pavements require the design traffic, based on the transformation of the traffic spectrum, to be calculated into a number of equivalent passages of a standard axle using the equivalent axle load factors. Generally, these factors only consider the type of axle (single, tandem or tridem), but they do not consider the type of wheel on the axles, i.e., single or dual wheel. The type of wheel has an important influence on the calculation of the design traffic. The exis...
Personalized Predictive Modeling and Risk Factor Identification using Patient Similarity.
Ng, Kenney; Sun, Jimeng; Hu, Jianying; Wang, Fei
2015-01-01
Personalized predictive models are customized for an individual patient and trained using information from similar patients. Compared to global models trained on all patients, they have the potential to produce more accurate risk scores and capture more relevant risk factors for individual patients. This paper presents an approach for building personalized predictive models and generating personalized risk factor profiles. A locally supervised metric learning (LSML) similarity measure is trained for diabetes onset and used to find clinically similar patients. Personalized risk profiles are created by analyzing the parameters of the trained personalized logistic regression models. A 15,000 patient data set, derived from electronic health records, is used to evaluate the approach. The predictive results show that the personalized models can outperform the global model. Cluster analysis of the risk profiles show groups of patients with similar risk factors, differences in the top risk factors for different groups of patients and differences between the individual and global risk factors.
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.
Study on neural network model for calculating subsidence factor
Institute of Scientific and Technical Information of China (English)
GUO Wen-bing; ZHANG Jie
2007-01-01
The major factors influencing subsidence factor were comprehensively analyzed. Then the artificial neural network model for calculating subsidence factor was set up with the theory of artificial neural network (ANN). A large amount of data from observation stations in China was collected and used as learning and training samples to train and test the artificial neural network model. The calculated results of the ANN model and the observed values were compared and analyzed in this paper. The results demonstrate that many factors can be considered in this model and the result is more precise and closer to observed values to calculate the subsidence factor by the ANN model. It can satisfy the need of engineering.
Analysis of effect factors-based stochastic network planning model
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Looking at all the indeterminate factors as a whole and regarding activity durations as independent random variables,the traditional stochastic network planning models ignore the inevitable relationship and dependence among activity durations when more than one activity is possibly affected by the same indeterminate factors.On this basis of analysis of indeterminate effect factors of durations,the effect factors-based stochastic network planning (EFBSNP) model is proposed,which emphasizes on the effects of not only logistic and organizational relationships,but also the dependent relationships,due to indeterminate factors among activity durations on the project period.By virtue of indeterminate factor analysis the model extracts and describes the quantitatively indeterminate effect factors,and then takes into account the indeterminate factors effect schedule by using the Monte Carlo simulation technique.The method is flexible enough to deal with effect factors and is coincident with practice.A software has been developed to simplify the model-based calculation,in VisualStudio.NET language.Finally,a case study is included to demonstrate the applicability of the proposed model and comparison is made with some advantages over the existing models.
Shape Modelling Using Maximum Autocorrelation Factors
DEFF Research Database (Denmark)
Larsen, Rasmus
2001-01-01
of the training set are in reality a time series, e.g.\\$\\backslash\\$ snapshots of a beating heart during the cardiac cycle or when the shapes are slices of a 3D structure, e.g. the spinal cord. Second, in almost all applications a natural order of the landmark points along the contour of the shape is introduced......This paper addresses the problems of generating a low dimensional representation of the shape variation present in a training set after alignment using Procrustes analysis and projection into shape tangent space. We will extend the use of principal components analysis in the original formulation...... of Active Shape Models by Timothy Cootes and Christopher Taylor by building new information into the model. This new information consists of two types of prior knowledge. First, in many situation we will be given an ordering of the shapes of the training set. This situation occurs when the shapes...
Instrumental Variable Bayesian Model Averaging via Conditional Bayes Factors
Karl, Anna; Lenkoski, Alex
2012-01-01
We develop a method to perform model averaging in two-stage linear regression systems subject to endogeneity. Our method extends an existing Gibbs sampler for instrumental variables to incorporate a component of model uncertainty. Direct evaluation of model probabilities is intractable in this setting. We show that by nesting model moves inside the Gibbs sampler, model comparison can be performed via conditional Bayes factors, leading to straightforward calculations. This new Gibbs sampler is...
Nucleon form factors in the canonically quantized Skyrme model
Energy Technology Data Exchange (ETDEWEB)
Acus, A.; Norvaisas, E. [Lithuanian Academy of Sciences, Vilnius (Lithuania). Inst. of Theoretical Physics and Astronomy; Riska, D.O. [Helsinki Univ. (Finland). Dept. of Physics; Helsinki Univ. (Finland). Helsinki Inst. of Physics
2001-08-01
The explicit expressions for the electric, magnetic, axial and induced pseudoscalar form factors of the nucleons are derived in the ab initio quantized Skyrme model. The canonical quantization procedure ensures the existence of stable soliton solutions with good quantum numbers. The form factors are derived for representations of arbitrary dimension of the SU(2) group. After fixing the two parameters of the model, f{sub {pi}} and e, by the empirical mass and electric mean square radius of the proton, the calculated electric and magnetic form factors are fairly close to the empirical ones, whereas the the axial and induced pseudoscalar form factors fall off too slowly with momentum transfer. (orig.)
Nucleon form factors in the canonically quantized Skyrme model
Acus, A; Riska, D O
2001-01-01
The explicit expressions for the electric, magnetic, axial and induced pseudoscalar form factors of the nucleons are derived in the {\\it ab initio} quantized Skyrme model. The canonical quantization procedure ensures the existence of stable soliton solutions with good quantum numbers. The form factors are derived for representations of arbitrary dimension of the SU(2) group. After fixing the two parameters of the model, $f_\\pi$ and $e$, by the empirical mass and electric mean square radius of the proton, the calculated electric and magnetic form factors are fairly close to the empirical ones, whereas the the axial and induced pseudoscalar form factors fall off too slowly with momentum transfer.
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 Drickame...
The determinant factors of open business model
Directory of Open Access Journals (Sweden)
Juan Mejía-Trejo
2017-01-01
Full Text Available Intro ducción : Desde principios del siglo XXI, varios autores afirman que los modelos de negocio abiertos (OBM permiten a una organización ser más eficaz en la creación y la ca p tura de valor siendo un requisito previo para el éxito de las asociaciones de co - des arrollo. Como resultado de las tendencias de: crecientes costos de desarrollo y ciclos de vida de los produ c tos/servicios más cortos, las empresas encuentran cada vez más difícil justificar las inversi o nes en innovación. El OBM resuelve ambas tendencias, s ubrayando los términos: " ecosistema de la industria " y/o " modelo de negocio colaborativo ". No sólo cambia el pr o ceso de innovación, sino que también modifica a las propias organizaciones mediante la r e configuración de sus cadenas de valor y redes. Para las empresas, crea una lógica heurística basada en el actual modelo de negocio y tecnología para extenderlas, con estrategia, al desa r rollo de la innov a ción para crear valor y aumentar los ingresos y beneficios. Enfatiza tanto las relaciones exte r nas así como la gobernabilidad, como valiosos recursos con varios roles que promueven la competitividad corporativa. Por lo tanto, para un sector especializado de alta tecnología como lo es el de las tecnologías de la información de la zona metropolitana de Guadalajar a (IT S MZG, exponemos el siguiente problema de investigación: ¿Cuáles son los factores determinantes de la OBM como modelo empírico que se aplc a do en el ITSMZG? Método: Como se ve, esta investigación tiene como objetivo plantear, los factores determ i nantes de la OBM como un modelo empírico que sea aplicado en el ITSMZG.Se trata de un estudio documental para seleccionar las principales v a riables entre los especialistas de las ITSMZG que practican el proceso OBM mediante el proceso de j e rarquía analítica (AHP y el Panel de Delphi a fin de contrastar los términos académicos con la experiencia de los e s pecialistas. Es un
An alternative method for centrifugal compressor loading factor modelling
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.
Barnes, Jennifer; Prescott, Tim; Muncer, Steven
2012-12-01
The purpose of this investigation was to compare the goodness-of-fit of a one factor model with the four factor model proposed by Fairburn (2008) and the three factor model proposed by Peterson and colleagues (2007) for the Eating Disorder Examination Questionnaire (EDE-Q 6.0) (Fairburn and Beglin, 1994). Using a cross-sectional design, the EDE-Q was completed by 569 adults recruited from universities and eating disorder charities in the UK. Confirmatory factor analysis (CFA) was carried out for both the student and non-student groups. CFA indicated that Peterson et al.'s (2007) three factor model was the best fit for both groups within the current data sample. Acceptable levels of internal reliability were observed and there was clear evidence for a hierarchical factor of eating disorder. The results of this study provide support for the three factor model of the EDE-Q suggested by Peterson and colleagues (2007) in that this model was appropriate for both the student and non-student sample populations. Copyright © 2012 Elsevier Ltd. All rights reserved.
Selection between Linear Factor Models and Latent Profile Models Using Conditional Covariances
Halpin, Peter F.; Maraun, Michael D.
2010-01-01
A method for selecting between K-dimensional linear factor models and (K + 1)-class latent profile models is proposed. In particular, it is shown that the conditional covariances of observed variables are constant under factor models but nonlinear functions of the conditioning variable under latent profile models. The performance of a convenient…
Selection between Linear Factor Models and Latent Profile Models Using Conditional Covariances
Halpin, Peter F.; Maraun, Michael D.
2010-01-01
A method for selecting between K-dimensional linear factor models and (K + 1)-class latent profile models is proposed. In particular, it is shown that the conditional covariances of observed variables are constant under factor models but nonlinear functions of the conditioning variable under latent profile models. The performance of a convenient…
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.
The development of a theoretical model to investigate factors ...
African Journals Online (AJOL)
The development of a theoretical model to investigate factors associated with ... major household appliance market: An integrative conceptual approach. ... disadvantaged consumers gain spending power and access to electricity supply.
Factorized domain wall partition functions in trigonometric vertex models
Foda, O; Zuparic, M
2007-01-01
We obtain factorized domain wall partition functions for two sets of trigonometric vertex models: 1. The N-state Deguchi-Akutsu models, for N = {2, 3, 4} (and conjecture the result for all N >= 5), and 2. The sl(r+1|s+1) Perk-Schultz models, for {r, s = \\N}, where (given the symmetries of these models) the result is independent of {r, s}.
Hidden Markov Models with Factored Gaussian Mixtures Densities
Institute of Scientific and Technical Information of China (English)
LI Hao-zheng; LIU Zhi-qiang; ZHU Xiang-hua
2004-01-01
We present a factorial representation of Gaussian mixture models for observation densities in Hidden Markov Models(HMMs), which uses the factorial learning in the HMM framework. We derive the reestimation formulas for estimating the factorized parameters by the Expectation Maximization (EM) algorithm. We conduct several experiments to compare the performance of this model structure with Factorial Hidden Markov Models(FHMMs) and HMMs, some conclusions and promising empirical results are presented.
Rethinking "Harmonious Parenting" Using a Three-Factor Discipline Model
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…
Form factors in an algebraic model of the nucleon
Bijker, R
1995-01-01
We study the electromagnetic form factors of the nucleon in a collective model of baryons. In an algebraic approach to hadron structure, we derive closed expressions for both elastic and transition form factors, and consequently for the helicity amplitudes that can be measured in electro- and photoproduction.
Relativistic quark model for the Omega- electromagnetic form factors
Energy Technology Data Exchange (ETDEWEB)
G. Ramalho, K. Tsushima, Franz Gross
2009-08-01
We compute the Omega- electromagnetic form factors and the decuplet baryon magnetic moments using a quark model application of the Covariant Spectator Theory. Our predictions for the Omega- electromagnetic form factors can be tested in the future by lattice QCD simulations at the physical strange quark mass.
A relativistic quark model for the Omega- electromagnetic form factors
Ramalho, G; Gross, Franz
2009-01-01
We compute the Omega- electromagnetic form factors and the decuplet baryon magnetic moments using a quark model application of the Covariant Spectator Theory. Our predictions for the Omega- electromagnetic form factors can be tested in the future by lattice QCD simulations at the physical strange quark mass.
Rethinking "Harmonious Parenting" Using a Three-Factor Discipline Model
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…
Detecting Social Desirability Bias Using Factor Mixture Models
Leite, Walter L.; Cooper, Lou Ann
2010-01-01
Based on the conceptualization that social desirable bias (SDB) is a discrete event resulting from an interaction between a scale's items, the testing situation, and the respondent's latent trait on a social desirability factor, we present a method that makes use of factor mixture models to identify which examinees are most likely to provide…
Verification modeling study for the influential factors of secondary clarifier
Gao, Haiwen
2016-01-01
A numerical Quasi 3-D model of secondary clarifier is applied to verify the data obtained through the literature and analyze the influential factors for secondary clarifiers. The data from the papers provide the input parameters for the model. During this study, several influential factors (density waterfall; surface overflow rate; solids loading rate; solids-settling characteristics; mixed liquor suspended solid; clarifier geometry) are tested. The results show that there are some difference...
Is There Really a Global Business Cycle? : A Dynamic Factor Model with Stochastic Factor Selection
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
Testing and modeling non-normality within the one-factor model
Molenaar, D.; Dolan, C.V.; Verhelst, N.D.
2010-01-01
Maximum likelihood estimation in the one-factor model is based on the assumption of multivariate normality for the observed data. This general distributional assumption implies three specific assumptions for the parameters in the one-factor model: the common factor has a normal distribution; the res
Testing and modeling non-normality within the one-factor model
Molenaar, D.; Dolan, C.V.; Verhelst, N.D.
2010-01-01
Maximum likelihood estimation in the one-factor model is based on the assumption of multivariate normality for the observed data. This general distributional assumption implies three specific assumptions for the parameters in the one-factor model: the common factor has a normal distribution; the
Continuous utility factor in segregation models: a few surprises
Roy, Parna
2015-01-01
We consider the constrained Schelling model of social segregation which allows non-local jumps of the agents. In the present study, the utility factor u is defined in a way such that it can take continuous values and depends on the tolerance threshold as well as fraction of unlike neighbours. Two models are proposed: in model A the jump probability is determined by the sign of u only which makes it equivalent to the discrete model. In model B the actual values of u are considered. Model A and model B are shown to differ drastically as far as segregation behaviour and phase transitions are concerned. The constrained model B turns out to be as efficient as the unconstrained discrete model, if not more. In addition, we also consider a few other dynamical aspects which have not been studied in segregation models earlier.
Towards an Accurate Performance Modeling of Parallel SparseFactorization
Energy Technology Data Exchange (ETDEWEB)
Grigori, Laura; Li, Xiaoye S.
2006-05-26
We present a performance model to analyze a parallel sparseLU factorization algorithm on modern cached-based, high-end parallelarchitectures. Our model characterizes the algorithmic behavior bytakingaccount the underlying processor speed, memory system performance, aswell as the interconnect speed. The model is validated using theSuperLU_DIST linear system solver, the sparse matrices from realapplications, and an IBM POWER3 parallel machine. Our modelingmethodology can be easily adapted to study performance of other types ofsparse factorizations, such as Cholesky or QR.
Fuzzy MCDM Model for Risk Factor Selection in Construction Projects
Directory of Open Access Journals (Sweden)
Pejman Rezakhani
2012-11-01
Full Text Available Risk factor selection is an important step in a successful risk management plan. There are many risk factors in a construction project and by an effective and systematic risk selection process the most critical risks can be distinguished to have more attention. In this paper through a comprehensive literature survey, most significant risk factors in a construction project are classified in a hierarchical structure. For an effective risk factor selection, a modified rational multi criteria decision making model (MCDM is developed. This model is a consensus rule based model and has the optimization property of rational models. By applying fuzzy logic to this model, uncertainty factors in group decision making such as experts` influence weights, their preference and judgment for risk selection criteria will be assessed. Also an intelligent checking process to check the logical consistency of experts` preferences will be implemented during the decision making process. The solution inferred from this method is in the highest degree of acceptance of group members. Also consistency of individual preferences is checked by some inference rules. This is an efficient and effective approach to prioritize and select risks based on decisions made by group of experts in construction projects. The applicability of presented method is assessed through a case study.
Uncovering Transcriptional Regulatory Networks by Sparse Bayesian Factor Model
Meng, Jia; Zhang, Jianqiu(Michelle); Qi, Yuan(Alan); Chen, Yidong; Huang, Yufei
2010-12-01
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 ([InlineEquation not available: see fulltext.]) status and Estrogen Receptor negative ([InlineEquation not available: see fulltext.]) status, respectively.
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.
HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.
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.
High-dimensional covariance matrix estimation in approximate factor models
Fan, Jianqing; Mincheva, Martina; 10.1214/11-AOS944
2012-01-01
The variance--covariance matrix plays a central role in the inferential theories of high-dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu [J. Amer. Statist. Assoc. 106 (2011) 672--684], 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 studi...
Matrix Factorizations for Local F-Theory Models
Omer, Harun
2016-01-01
I use matrix factorizations to describe branes at simple singularities as they appear in elliptic fibrations of local F-theory models. Each node of the corresponding Dynkin diagrams of the ADE-type singularities is associated with one indecomposable matrix factorization which can be deformed into one or more factorizations of lower rank. Branes with internal fluxes arise naturally as bound states of the indecomposable factorizations. Describing branes in such a way avoids the need to resolve singularities and encodes information which is neglected in conventional F-theory treatments. This paper aims to show how branes arising in local F-theory models around simple singularities can be described in this framework.
Game Factors and Game-Based Learning Design Model
Directory of Open Access Journals (Sweden)
Yen-Ru Shi
2015-01-01
Full Text Available How to design useful digital game-based learning is a topic worthy of discussion. Past research focused on specific game genres design, but it is difficult to use when the target game genre differs from the default genres used in the research. This study presents macrodesign concepts that elucidates 11 crucial game-design factors, including game goals, game mechanism, game fantasy, game value, interaction, freedom, narrative, sensation, challenges, sociality, and mystery. We clearly define each factor and analyze the relationships among the 11 factors to construct a game-based learning design model. Two application examples are analyzed to verify the usability of the model and the performance of these factors. It can assist educational game designers in developing interesting games.
Supplementary Material for: Factor Copula Models for Replicated Spatial Data
Krupskii, Pavel
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.
Determination of effective loss factors in reduced SEA models
Chimeno Manguán, M.; Fernández de las Heras, M. J.; Roibás Millán, E.; Simón Hidalgo, F.
2017-01-01
The definition of Statistical Energy Analysis (SEA) models for large complex structures is highly conditioned by the classification of the structure elements into a set of coupled subsystems and the subsequent determination of the loss factors representing both the internal damping and the coupling between subsystems. The accurate definition of the complete system can lead to excessively large models as the size and complexity increases. This fact can also rise practical issues for the experimental determination of the loss factors. This work presents a formulation of reduced SEA models for incomplete systems defined by a set of effective loss factors. This reduced SEA model provides a feasible number of subsystems for the application of the Power Injection Method (PIM). For structures of high complexity, their components accessibility can be restricted, for instance internal equipments or panels. For these cases the use of PIM to carry out an experimental SEA analysis is not possible. New methods are presented for this case in combination with the reduced SEA models. These methods allow defining some of the model loss factors that could not be obtained through PIM. The methods are validated with a numerical analysis case and they are also applied to an actual spacecraft structure with accessibility restrictions: a solar wing in folded configuration.
A quality metric for homology modeling: the H-factor
2011-01-01
Background The analysis of protein structures provides fundamental insight into most biochemical functions and consequently into the cause and possible treatment of diseases. As the structures of most known proteins cannot be solved experimentally for technical or sometimes simply for time constraints, in silico protein structure prediction is expected to step in and generate a more complete picture of the protein structure universe. Molecular modeling of protein structures is a fast growing field and tremendous works have been done since the publication of the very first model. The growth of modeling techniques and more specifically of those that rely on the existing experimental knowledge of protein structures is intimately linked to the developments of high resolution, experimental techniques such as NMR, X-ray crystallography and electron microscopy. This strong connection between experimental and in silico methods is however not devoid of criticisms and concerns among modelers as well as among experimentalists. Results In this paper, we focus on homology-modeling and more specifically, we review how it is perceived by the structural biology community and what can be done to impress on the experimentalists that it can be a valuable resource to them. We review the common practices and provide a set of guidelines for building better models. For that purpose, we introduce the H-factor, a new indicator for assessing the quality of homology models, mimicking the R-factor in X-ray crystallography. The methods for computing the H-factor is fully described and validated on a series of test cases. Conclusions We have developed a web service for computing the H-factor for models of a protein structure. This service is freely accessible at http://koehllab.genomecenter.ucdavis.edu/toolkit/h-factor. PMID:21291572
Electromagnetic form factors in a collective model of the nucleon
Bijker, R; Leviatan, A
1995-01-01
We study the electromagnetic form factors of the nucleon in a collective model of baryons. Using the algebraic approach to hadron structure, we derive closed expressions for both elastic and transition form factors, and consequently for the helicity amplitudes that can be measured in electro- and photoproduction. Effects of spin-flavor symmetry breaking and of swelling of hadrons with increasing excitation energy are considered.
Electromagnetic form factors in a collective model of the nucleon
Energy Technology Data Exchange (ETDEWEB)
Bijker, R.; Iachello, F.; Leviatan, A. [Instituto de Ciencias Nucleares, Universidad Nacional Autonoma de Mexico, Apartado Postal 70-543, 04510 (Mexico)]|[Distrito Federale (Mexico)]|[Center for Theoretical Physics, Sloane Laboratory, Yale University, New Haven, Connecticut 06520-8120 (United States)]|[Racah Institute of Physics, The Hebrew University, Jerusalem 91904 (Israel)
1996-10-01
We study the electromagnetic form factors of the nucleon in a collective model of baryons. Using the algebraic approach to hadron structure, we derive closed expressions for both elastic and transition form factors, and consequently for the helicity amplitudes that can be measured in electro- and photoproduction. Effects of spin-flavor symmetry breaking and of swelling of hadrons with increasing excitation energy are considered. {copyright} {ital 1996 The American Physical Society.}
A discrete latent factor model for smoking, cancer and mortality.
Howdon, D.; Jones, A
2013-01-01
This paper investigates the relationships between social circumstances, individual behaviours, and ill-health later in life, with a particular focus on the development of cancer. A discrete latent factor model incorporating individuals' smoking and health outcomes (lifespan and time-to-cancer) is jointly estimated, using the 1984/5 British Health and Lifestyle Survey (HALS) dataset and its July 2009 follow-up, allowing for unobservable factors to affect decisions regarding smoking behaviours ...
Impact of festival factor on electric quantity multiplication forecast model
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
This research aims to improve the forecasting precision of electric quantity. It is discovered that the total electricity consumption considerably increased during the Spring Festival by the analysis of the electric quantity time series from 2002 to 2007 in Shandong province. The festival factor is ascertained to be one of the important seasonal factors affecting the electric quantity fluctuations, and the multiplication model for forecasting is improved by introducing corresponding variables and parameters...
Consumer's Online Shopping Influence Factors and Decision-Making Model
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.
A Bayesian semiparametric factor analysis model for subtype identification.
Sun, Jiehuan; Warren, Joshua L; Zhao, Hongyu
2017-04-25
Disease subtype identification (clustering) is an important problem in biomedical research. Gene expression profiles are commonly utilized to infer disease subtypes, which often lead to biologically meaningful insights into disease. Despite many successes, existing clustering methods may not perform well when genes are highly correlated and many uninformative genes are included for clustering due to the high dimensionality. In this article, we introduce a novel subtype identification method in the Bayesian setting based on gene expression profiles. This method, called BCSub, adopts an innovative semiparametric Bayesian factor analysis model to reduce the dimension of the data to a few factor scores for clustering. Specifically, the factor scores are assumed to follow the Dirichlet process mixture model in order to induce clustering. Through extensive simulation studies, we show that BCSub has improved performance over commonly used clustering methods. When applied to two gene expression datasets, our model is able to identify subtypes that are clinically more relevant than those identified from the existing methods.
Factor selection and structural identification in the interaction ANOVA model.
Post, Justin B; Bondell, Howard D
2013-03-01
When faced with categorical predictors and a continuous response, the objective of an analysis often consists of two tasks: finding which factors are important and determining which levels of the factors differ significantly from one another. Often times, these tasks are done separately using Analysis of Variance (ANOVA) followed by a post hoc hypothesis testing procedure such as Tukey's Honestly Significant Difference test. When interactions between factors are included in the model the collapsing of levels of a factor becomes a more difficult problem. When testing for differences between two levels of a factor, claiming no difference would refer not only to equality of main effects, but also to equality of each interaction involving those levels. This structure between the main effects and interactions in a model is similar to the idea of heredity used in regression models. This article introduces a new method for accomplishing both of the common analysis tasks simultaneously in an interaction model while also adhering to the heredity-type constraint on the model. An appropriate penalization is constructed that encourages levels of factors to collapse and entire factors to be set to zero. It is shown that the procedure has the oracle property implying that asymptotically it performs as well as if the exact structure were known beforehand. We also discuss the application to estimating interactions in the unreplicated case. Simulation studies show the procedure outperforms post hoc hypothesis testing procedures as well as similar methods that do not include a structural constraint. The method is also illustrated using a real data example.
Factor Selection and Structural Identification in the Interaction ANOVA Model
Post, Justin B.; Bondell, Howard D.
2013-01-01
Summary When faced with categorical predictors and a continuous response, the objective of analysis often consists of two tasks: finding which factors are important and determining which levels of the factors differ significantly from one another. Often times these tasks are done separately using Analysis of Variance (ANOVA) followed by a post-hoc hypothesis testing procedure such as Tukey’s Honestly Significant Difference test. When interactions between factors are included in the model the collapsing of levels of a factor becomes a more difficult problem. When testing for differences between two levels of a factor, claiming no difference would refer not only to equality of main effects, but also equality of each interaction involving those levels. This structure between the main effects and interactions in a model is similar to the idea of heredity used in regression models. This paper introduces a new method for accomplishing both of the common analysis tasks simultaneously in an interaction model while also adhering to the heredity-type constraint on the model. An appropriate penalization is constructed that encourages levels of factors to collapse and entire factors to be set to zero. It is shown that the procedure has the oracle property implying that asymptotically it performs as well as if the exact structure were known beforehand. We also discuss the application to estimating interactions in the unreplicated case. Simulation studies show the procedure outperforms post hoc hypothesis testing procedures as well as similar methods that do not include a structural constraint. The method is also illustrated using a real data example. PMID:23323643
K factor estimation in distribution transformers using linear regression models
Directory of Open Access Journals (Sweden)
Juan Miguel Astorga Gómez
2016-06-01
Full Text Available Background: Due to massive incorporation of electronic equipment to distribution systems, distribution transformers are subject to operation conditions other than the design ones, because of the circulation of harmonic currents. It is necessary to quantify the effect produced by these harmonic currents to determine the capacity of the transformer to withstand these new operating conditions. The K-factor is an indicator that estimates the ability of a transformer to withstand the thermal effects caused by harmonic currents. This article presents a linear regression model to estimate the value of the K-factor, from total current harmonic content obtained with low-cost equipment.Method: Two distribution transformers that feed different loads are studied variables, current total harmonic distortion factor K are recorded, and the regression model that best fits the data field is determined. To select the regression model the coefficient of determination R2 and the Akaike Information Criterion (AIC are used. With the selected model, the K-factor is estimated to actual operating conditions.Results: Once determined the model it was found that for both agricultural cargo and industrial mining, present harmonic content (THDi exceeds the values that these transformers can drive (average of 12.54% and minimum 8,90% in the case of agriculture and average value of 18.53% and a minimum of 6.80%, for industrial mining case.Conclusions: When estimating the K factor using polynomial models it was determined that studied transformers can not withstand the current total harmonic distortion of their current loads. The appropriate K factor for studied transformer should be 4; this allows transformers support the current total harmonic distortion of their respective loads.
Probabilistic Multi-Factor Interaction Model for Complex Material Behavior
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
A model for sigma factor competition in bacterial cells.
Mauri, Marco; Klumpp, Stefan
2014-10-01
Sigma factors control global switches of the genetic expression program in bacteria. Different sigma factors compete for binding to a limited pool of RNA polymerase (RNAP) core enzymes, providing a mechanism for cross-talk between genes or gene classes via the sharing of expression machinery. To analyze the contribution of sigma factor competition to global changes in gene expression, we develop a theoretical model that describes binding between sigma factors and core RNAP, transcription, non-specific binding to DNA and the modulation of the availability of the molecular components. The model is validated by comparison with in vitro competition experiments, with which excellent agreement is found. Transcription is affected via the modulation of the concentrations of the different types of holoenzymes, so saturated promoters are only weakly affected by sigma factor competition. However, in case of overlapping promoters or promoters recognized by two types of sigma factors, we find that even saturated promoters are strongly affected. Active transcription effectively lowers the affinity between the sigma factor driving it and the core RNAP, resulting in complex cross-talk effects. Sigma factor competition is not strongly affected by non-specific binding of core RNAPs, sigma factors and holoenzymes to DNA. Finally, we analyze the role of increased core RNAP availability upon the shut-down of ribosomal RNA transcription during the stringent response. We find that passive up-regulation of alternative sigma-dependent transcription is not only possible, but also displays hypersensitivity based on the sigma factor competition. Our theoretical analysis thus provides support for a significant role of passive control during that global switch of the gene expression program.
A Right Coprime Factorization of Neural State Space Models
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon
2007-01-01
In recent years, various methods for identification of nonlinear systems in closed loop using open-loop approaches have received considerable attention. However, these methods rely on differentially coprime factorizations of the nonlinear plants, which can be difficult to compute in practice....... To address this issue, this paper presents various technical results leading up to explicit formulae for right coprime factorizations of neural state space models, i.e., nonlinear system models represented in state space using neural networks, which satisfy a Bezout identity. ...
Electrical tortuosity, Kozeny’s factor and cementation factor modelled for chalk
DEFF Research Database (Denmark)
Katika, Konstantina; Fabricius, Ida Lykke
2015-01-01
Based on the electrical properties of chalk from the North Sea and Stevns Klint and on published data, we explore how klinkenberg corrected permeability from experimental data relate to porosity and electrical resistivity. In the current study we use electrical conductivity data of partially water......, to calculate permeability based on electrical resistivity data. We also calculate the permeability based on a simple porosity model. Finally, we redefine Kozeny’s factor, c, using Carman’s model based on tortuosity and the model based on porosity. This resulted in a third modelled permeability, which describes...
Functional dynamic factor models with application to yield curve forecasting
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.
Solutions of two-factor models with variable interest rates
Li, Jinglu; Clemons, C. B.; Young, G. W.; Zhu, J.
2008-12-01
The focus of this work is on numerical solutions to two-factor option pricing partial differential equations with variable interest rates. Two interest rate models, the Vasicek model and the Cox-Ingersoll-Ross model (CIR), are considered. Emphasis is placed on the definition and implementation of boundary conditions for different portfolio models, and on appropriate truncation of the computational domain. An exact solution to the Vasicek model and an exact solution for the price of bonds convertible to stock at expiration under a stochastic interest rate are derived. The exact solutions are used to evaluate the accuracy of the numerical simulation schemes. For the numerical simulations the pricing solution is analyzed as the market completeness decreases from the ideal complete level to one with higher volatility of the interest rate and a slower mean-reverting environment. Simulations indicate that the CIR model yields more reasonable results than the Vasicek model in a less complete market.
Modeling Image Structure with Factorized Phase-Coupled Boltzmann Machines
Cadieu, Charles F
2010-01-01
We describe a model for capturing the statistical structure of local amplitude and local spatial phase in natural images. The model is based on a recently developed, factorized third-order Boltzmann machine that was shown to be effective at capturing higher-order structure in images by modeling dependencies among squared filter outputs (Ranzato and Hinton, 2010). Here, we extend this model to $L_p$-spherically symmetric subspaces. In order to model local amplitude and phase structure in images, we focus on the case of two dimensional subspaces, and the $L_2$-norm. When trained on natural images the model learns subspaces resembling quadrature-pair Gabor filters. We then introduce an additional set of hidden units that model the dependencies among subspace phases. These hidden units form a combinatorial mixture of phase coupling distributions, concentrated in the sum and difference of phase pairs. When adapted to natural images, these distributions capture local spatial phase structure in natural images.
The structure of musical preferences: a five-factor model.
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.
Modeling wind adjustment factor and midflame wind speed for Rothermel's surface fire spread model
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...
Linear Factor Models and the Estimation of Expected Returns
Sarisoy, Cisil; de Goeij, Peter; Werker, Bas
2015-01-01
Estimating expected returns on individual assets or portfolios is one of the most fundamental problems of finance research. The standard approach, using historical averages,produces noisy estimates. Linear factor models of asset pricing imply a linear relationship between expected returns and exposu
Linear Factor Models and the Estimation of Expected Returns
Sarisoy, Cisil; de Goeij, Peter; Werker, Bas
2016-01-01
Linear factor models of asset pricing imply a linear relationship between expected returns of assets and exposures to one or more sources of risk. We show that exploiting this linear relationship leads to statistical gains of up to 31% in variances when estimating expected returns on individual asse
Reproductive Behavior and Personality Traits of the Five Factor Model
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 se
Tests of risk premia in linear factor models
Kleibergen, F.
2009-01-01
We show that statistical inference on the risk premia in linear factor models that is based on the Fama-MacBeth (FM) and generalized least squares (GLS) two-pass risk premia estimators is misleading when the β’s are small and/or the number of assets is large. We propose novel statistics, that are ba
Tests of risk premia in linear factor models
Kleibergen, F.R.
2005-01-01
We show that inference on risk premia in linear factor models that is based on the Fama-MacBeth and GLS risk premia estimators is misleading when the ß’s are small and/or the number of assets is large. We propose some novel statistics that remain trustworthy in these cases. The inadequacy of Fama-Ma
Tests of risk premia in linear factor models
Kleibergen, F.
2009-01-01
We show that statistical inference on the risk premia in linear factor models that is based on the Fama-MacBeth (FM) and generalized least squares (GLS) two-pass risk premia estimators is misleading when the β’s are small and/or the number of assets is large. We propose novel statistics, that are
Risk factors and prognostic models for perinatal asphyxia at term
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
Bayesian Estimation of Random Coefficient Dynamic Factor Models
Song, Hairong; Ferrer, Emilio
2012-01-01
Dynamic factor models (DFMs) have typically been applied to multivariate time series data collected from a single unit of study, such as a single individual or dyad. The goal of DFMs application is to capture dynamics of multivariate systems. When multiple units are available, however, DFMs are not suited to capture variations in dynamics across…
Bayesian Gaussian Copula Factor Models for Mixed Data.
Murray, Jared S; Dunson, David B; Carin, Lawrence; Lucas, Joseph E
2013-06-01
Gaussian factor models have proven widely useful for parsimoniously characterizing dependence in multivariate data. There is a rich literature on their extension to mixed categorical and continuous variables, using latent Gaussian variables or through generalized latent trait models acommodating measurements in the exponential family. However, when generalizing to non-Gaussian measured variables the latent variables typically influence both the dependence structure and the form of the marginal distributions, complicating interpretation and introducing artifacts. To address this problem we propose a novel class of Bayesian Gaussian copula factor models which decouple the latent factors from the marginal distributions. A semiparametric specification for the marginals based on the extended rank likelihood yields straightforward implementation and substantial computational gains. We provide new theoretical and empirical justifications for using this likelihood in Bayesian inference. We propose new default priors for the factor loadings and develop efficient parameter-expanded Gibbs sampling for posterior computation. The methods are evaluated through simulations and applied to a dataset in political science. The models in this paper are implemented in the R package bfa.
Validation of a Four-Factor Model of Career Indecision
Brown, Steven D.; Hacker, Jason; Abrams, Matthew; Carr, Andrea; Rector, Christopher; Lamp, Kristen; Telander, Kyle; Siena, Anne
2012-01-01
Two studies were designed to explore whether a meta-analytically derived four-factor model of career indecision (Brown & Rector, 2008) could be replicated at the primary and secondary data levels. In the first study, an initial pool of 167 items was written based on 35 different instruments whose scores had loaded saliently on at least one…
Validation of a Four-Factor Model of Career Indecision
Brown, Steven D.; Hacker, Jason; Abrams, Matthew; Carr, Andrea; Rector, Christopher; Lamp, Kristen; Telander, Kyle; Siena, Anne
2012-01-01
Two studies were designed to explore whether a meta-analytically derived four-factor model of career indecision (Brown & Rector, 2008) could be replicated at the primary and secondary data levels. In the first study, an initial pool of 167 items was written based on 35 different instruments whose scores had loaded saliently on at least one…
A novel latent factor model for recommender system
National Research Council Canada - National Science Library
Kumar, Bipul
2016-01-01
... a latent factor model that caters to both accuracy and efficiency by reducing the number of latent features of either users or items making it less complex than Funk-SVD, where latent features of both users and items are equal and often larger. A comprehensive empirical evaluation of accuracy on two publicly available, amazon and ml-100 k datasets rev...
Factorization model for distributions of quarks in hadrons
Energy Technology Data Exchange (ETDEWEB)
Ermolaev, B.I. [Ioffe Physico-Technical Institute, St. Petersburg (Russian Federation); Greco, M. [University Roma Tre, Department of Mathematics and Physics, Rome (Italy); INFN, Rome (Italy); Troyan, S.I. [St. Petersburg Institute of Nuclear Physics, Gatchina (Russian Federation)
2015-07-15
We consider distributions of unpolarized (polarized) quarks in unpolarized (polarized) hadrons. Our approach is based on QCD factorization. We begin with a study of the basic factorization for the parton-hadron scattering amplitudes in the forward kinematics and suggest a model for non-perturbative contributions to such amplitudes. This model is based on this simple observation: after emitting an active quark by the initial hadron, the remaining set of quarks and gluons becomes unstable, so a description of this colored state can approximately be done in terms of resonances, which leads to expressions of the Breit-Wigner type. Then we reduce these formulas to obtain explicit expressions for the quark-hadron scattering amplitudes and quark distributions in K{sub T}- and collinear factorizations. (orig.)
Factorization model for distributions of quarks in hadrons
Ermolaev, B I; Troyan, S I
2015-01-01
We consider distributions of unpolarized (polarized) quarks in unpolarized (polarized) hadrons. Our approach is based on QCD factorization. We begin with study of Basic factorization for the parton-hadron scattering amplitudes in the forward kinematics and suggest a model for non-perturbative contributions to such amplitudes. This model is based on the simple observation: after emitting an active quark by the initial hadron, the remaining set quarks and gluons becomes unstable, so description of this colored state can approximately be done in terms of resonances, which leads to expressions of the Breit-Wigner type. for non-perturbative contributions to the distributions of unpolarized and polarized quarks in the hadrons. Then we reduce these formulae to obtain explicit expressions for the quark-hadron scattering amplitudes and quark distributions in K_T- and Collinear factorizations.
Zero modes method and form factors in quantum integrable models
Directory of Open Access Journals (Sweden)
S. Pakuliak
2015-04-01
Full Text Available We study integrable models solvable by the nested algebraic Bethe ansatz and possessing GL(3-invariant R-matrix. Assuming that the monodromy matrix of the model can be expanded into series with respect to the inverse spectral parameter, we define zero modes of the monodromy matrix entries as the first nontrivial coefficients of this series. Using these zero modes we establish new relations between form factors of the elements of the monodromy matrix. We prove that all of them can be obtained from the form factor of a diagonal matrix element in special limits of Bethe parameters. As a result we obtain determinant representations for form factors of all the entries of the monodromy matrix.
Park, Elisa L.
2009-01-01
The purpose of this study is to understand the dynamics of Korean students' international mobility to study abroad by using the 2-D Model. The first D, "the driving force factor," explains how and what components of the dissatisfaction with domestic higher education perceived by Korean students drives students' outward mobility to seek…
The Interpersonal Style Inventory and the five-factor model.
Lorr, M; Youniss, R P; Kluth, C
1992-03-01
The study examined relations between the 15 scale scores of the Interpersonal Style Inventory (Lorr & Youniss, 1985) and the domain measures of the five-factor model provided by the NEO Personality Inventory (Costa & McCrae, 1985). A sample of 236 college students were administered both inventories. A principal component analysis of the 5 NEO-PI domain scores and the 15 ISI scale scores followed by a Varimax rotation disclosed the expected five higher-order factors. Four factors, Neuroticism, Extraversion, Conscientiousness and Ageeableness, were defined by both NEO and ISI scales. Openness to Experience, however, was represented in the ISI by Independence and Directiveness, which define its Autonomy dimension. Thus, the ISI measures four of the five factors assessed by the NEO-PI.
Two Empirical Models for Land-falling Hurricane Gust Factors
Merceret, Franics J.
2008-01-01
Gaussian and lognormal models for gust factors as a function of height and mean windspeed in land-falling hurricanes are presented. The models were empirically derived using data from 2004 hurricanes Frances and Jeanne and independently verified using data from 2005 hurricane Wilma. The data were collected from three wind towers at Kennedy Space Center and Cape Canaveral Air Force Station with instrumentation at multiple levels from 12 to 500 feet above ground level. An additional 200-foot tower was available for the verification. Mean wind speeds from 15 to 60 knots were included in the data. The models provide formulas for the mean and standard deviation of the gust factor given the mean windspeed and height above ground. These statistics may then be used to assess the probability of exceeding a specified peak wind threshold of operational significance given a specified mean wind speed.
Evaluation of methods for modeling transcription-factor sequence specificity
Weirauch, Matthew T.; Cote, Atina; Norel, Raquel; Annala, Matti; Zhao, Yue; Riley, Todd R.; Saez-Rodriguez, Julio; Cokelaer, Thomas; Vedenko, Anastasia; Talukder, Shaheynoor; Bussemaker, Harmen J.; Morris, Quaid D.; Bulyk, Martha L.; Stolovitzky, Gustavo
2013-01-01
Genomic analyses often involve scanning for potential transcription-factor (TF) binding sites using models of the sequence specificity of DNA binding proteins. Many approaches have been developed to model and learn a protein’s binding specificity, but these methods have not been systematically compared. Here we applied 26 such approaches to in vitro protein binding microarray data for 66 mouse TFs belonging to various families. For 9 TFs, we also scored the resulting motif models on in vivo data, and found that the best in vitro–derived motifs performed similarly to motifs derived from in vivo data. Our results indicate that simple models based on mononucleotide position weight matrices learned by the best methods perform similarly to more complex models for most TFs examined, but fall short in specific cases (<10%). In addition, the best-performing motifs typically have relatively low information content, consistent with widespread degeneracy in eukaryotic TF sequence preferences. PMID:23354101
Higher-order models versus direct hierarchical models: g as superordinate or breadth factor?
Directory of Open Access Journals (Sweden)
GILLES E. GIGNAC
2008-03-01
Full Text Available Intelligence research appears to have overwhelmingly endorsed a superordinate (higher-order model conceptualization of g, in comparison to the relatively less well-known breadth conceptualization of g, as represented by the direct hierarchical model. In this paper, several similarities and distinctions between the indirect and direct hierarchical models are delineated. Based on the re-analysis of five correlation matrices, it was demonstrated via CFA that the conventional conception of g as a higher-order superordinate factor was likely not as plausible as a first-order breadth factor. The results are discussed in light of theoretical advantages of conceptualizing g as a first-order factor. Further, because the associations between group-factors and g are constrained to zero within a direct hierarchical model, previous observations of isomorphic associations between a lower-order group factor and g are questioned.
Self-pathology, the five-factor model, and bloated specific factors: A cautionary tale.
Oltmanns, Joshua R; Widiger, Thomas A
2016-04-01
The five-factor model (FFM) is widely regarded as a useful model for the structure of both normal and maladaptive personality traits. However, recent factor analytic studies have suggested that deficits in the sense of self fall outside the FFM. The current study replicates and extends these findings, illustrating that factors can be situated outside a higher-order domain by including a relatively large number of closely related scales, forming what is known as a bloated specific factor. A total of 1,553 participants (M age = 37.8 years, SD = 13.1) were recruited across 3 studies. One measure of self-pathology (including 15 scales) and 2 measures of the FFM were administered, along with 17 measures of anxiousness and 12 measures of social withdrawal/sociability. Across 2 independent samples and 2 different measures of the FFM, deficits in the sense of self separated from neuroticism when all 15 scales of self-pathology were included. However, self-pathology loaded with FFM neuroticism when only a subset of the self-pathology scales was included. This finding was replicated with measures of social withdrawal/sociability, although only partially replicated with measures of anxiousness. Implications of these findings for past and future factor analytic studies of the structure of psychopathology are discussed.
Chronic gastritis rat model and role of inducing factors
Institute of Scientific and Technical Information of China (English)
Zun Xiang; Jian-Min Si; Huai-De Huang
2004-01-01
AIM: To establish an experimental animal model of chronic gastritis in a short term and to investigate the effects of several potential inflammation-inducing factors on rat gastric mucosa.METHODS: Twenty-four healthy, male SD rats were treated with intragastric administration of 600 mL/L alcohol, 20mmol/L sodium deoxycholate and 0.5 g/L ammonia (factor A), forage containing low levels of vitamins (factor B), and/or indomethacin (factor C), according to an L8(27)orthogonal design. After 12 wk, gastric antral and body mucosae were pathologically examined.RESULTS: Chronic gastritis model was successfully induced in rats treated with factor A for 12 wk. After the treatment of animals, the gastric mucosal inflammation was significantly different from that in controls, and the number of pyloric glands at antrum and parietal cells at body were obviously reduced (P＜0.01). Indomethacin induced gastritis but without atrophy, and short-term vitamin deficiency failed to induce chronic gastritis and gastric atrophy, In addition,indomethacin and vitamin deficiency had no synergistic effect in inducing gastritis with the factor A. No atypical hyperplasia and intestinal metaplasia in the gastric antrum and body were observed in all rats studied.CONCLUSION: Combined intragastric administration of 600 mL/L alcohol, 20 mmol/L sodium deoxycholate and 0.5 g/L ammonia induces chronic gastritis and gastric atrophy in rats. Indomethacin induces chronic gastritis only.The long-term roles of these factors in gastric inflammation and carcinogenesis need to be further elucidated.
Learning Hidden Markov Models using Non-Negative Matrix Factorization
Cybenko, George
2008-01-01
The Baum-Welsh algorithm together with its derivatives and variations has been the main technique for learning Hidden Markov Models (HMM) from observational data. We present an HMM learning algorithm based on the non-negative matrix factorization (NMF) of higher order Markovian statistics that is structurally different from the Baum-Welsh and its associated approaches. The described algorithm supports estimation of the number of recurrent states of an HMM and iterates the non-negative matrix factorization (NMF) algorithm to improve the learned HMM parameters. Numerical examples are provided as well.
Replicating hedge fund returns: A factor model approach
Naser, Omar
2007-01-01
Growth in the Hedge Fund industry mirrors the growth in the Mutual Fund industry. This raises the possibility of creating a passive strategy that replicates Hedge Fund returns at lower cost using liquid, exchange-traded instruments. Using monthly returns for the period 1991-2005 on thirteen Hedge Fund strategies, I build a linear factor models (“clones”) that replicate Hedge Fund returns. I use six common factors to determine the amount of expected return and variation in returns that can be ...
QCD dipole model and $k_{T}$ factorization
Bialas, A; Peschanski, R
2001-01-01
It is shown that the colour dipole approach to hard scattering at high energy is fully compatible with k_T factorization at the leading logarithm approximation (in -log x_Bj). The relations between the dipole amplitudes and unintegrated diagonal and non-diagonal gluon distributions are given. It is also shown that including the exact gluon kinematics in the k_T factorization formula destroys the conservation of transverse position vectors and thus is incompatible with the dipole model for both elastic and diffractive amplitudes.
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...... questionnaires of personality traits (NEO-FFI) and causality orientations (GCOS). To test whether covariance between traits and orientations could be attributed to shared or separate latent variables we conducted joint factor analyses. Results reveal that the Autonomy orientation can be distinguished from...
Probabilistic Usage of the Multi-Factor Interaction Model
Chamis, Christos C.
2008-01-01
A Multi-Factor Interaction Model (MFIM) is used to predict the insulating foam mass expulsion during the ascending of a space vehicle. The exponents in the MFIM are evaluated by an available approach which consists of least squares and an optimization algorithm. These results were subsequently used to probabilistically evaluate the effects of the uncertainties in each participating factor in the mass expulsion. The probabilistic results show that the surface temperature dominates at high probabilities and the pressure which causes the mass expulsion at low probabil
Hayduk, Leslie
2014-01-01
Researchers using factor analysis tend to dismiss the significant ill fit of factor models by presuming that if their factor model is close-to-fitting, it is probably close to being properly causally specified. Close fit may indeed result from a model being close to properly causally specified, but close-fitting factor models can also be seriously…
Hayduk, Leslie
2014-01-01
Researchers using factor analysis tend to dismiss the significant ill fit of factor models by presuming that if their factor model is close-to-fitting, it is probably close to being properly causally specified. Close fit may indeed result from a model being close to properly causally specified, but close-fitting factor models can also be seriously…
On the relation between the linear factor model and the latent profile model
Halpin, P.F.; Dolan, C.V.; Grasman, R.P.P.P.; de Boeck, P.
2011-01-01
The relationship between linear factor models and latent profile models is addressed within the context of maximum likelihood estimation based on the joint distribution of the manifest variables. Although the two models are well known to imply equivalent covariance decompositions, in general they do
On the Relation between the Linear Factor Model and the Latent Profile Model
Halpin, Peter F.; Dolan, Conor V.; Grasman, Raoul P. P. P.; De Boeck, Paul
2011-01-01
The relationship between linear factor models and latent profile models is addressed within the context of maximum likelihood estimation based on the joint distribution of the manifest variables. Although the two models are well known to imply equivalent covariance decompositions, in general they do not yield equivalent estimates of the…
Studying Effective Factors on Corporate Entrepreneurship: Representing a Model
Directory of Open Access Journals (Sweden)
Maryam Soleimani
2013-02-01
Full Text Available Development and advancement of current organizations depends on Corporate Entrepreneurship (CE and its anticipants considerably. Therefore purpose of conducting this survey is to study effective factors on corporate entrepreneurship (personal characteristics of entrepreneurship, human resource practices, organizational culture and employees' satisfaction. This survey was conducted using descriptive-field methodology. Statistical population included managers and experts of Hexa Consulting Engineers Company (Tehran/Iran and the sample consisted of forty seven of them. Questionnaire was tool of data collection. Data was collected in cross-sectional form in July-August 2011. Descriptive and inferential (spearman correlation statistics methods were used for data analysis. According to results, there is a positive significant relationship among all factors (personal characteristics of entrepreneurship, human resource practices, organizational culture and employees' satisfaction and corporate entrepreneurship. In other words, the proposed variables as effective factors on corporate entrepreneurship were confirmed in conceptual model of survey.
Proposition Factor Model of World Class Manufacturing in Brazilian Enterprises
Directory of Open Access Journals (Sweden)
Paulo Sergio Gonçalves de Oliveira
2016-05-01
Full Text Available The present paper aims to develop a model of World Class Manufacturing, to achieve this goal was elaborated a questionnaire with 35 assertive divided in 7 areas suggested by literature review. This questionnaire was send to manufacture specialists, product developers and technician through LinkedIn the participants was select by researchers in discussion groups taking in consideration their experience using the professional profile. About 1000 invite was send to professional from metal-mechanic sector which returned 180 valid questionnaires. The data was analyzed through factor analyses and was obtained 7 constructs, which explained 67% of data variance. The KMO was 0,84, which is considered good for, analyzes purpose. The seventh factor was eliminated because it Cranach’s Alpha was below 0,6 and the remained factor was nominated as: Lean Manufacturing, Human Resources Management to achieve flexibility, Marketing Integration, Costs Reduction and Flexibility.
Octet baryon electromagnetic form factors in a relativistic quark model
Ramalho, G
2011-01-01
We study the octet baryon electromagnetic properties by applying the covariant spectator quark model, and provide covariant parametrization that can be used to study baryon electromagnetic reactions. While we use the lattice QCD data in the large pion mass regime (small pion cloud effects) to determine the parameters of the model in the valence quark sector, we use the nucleon physical and octet baryon magnetic moment data to parameterize the pion cloud contributions. The valence quark contributions for the octet baryon electromagnetic form factors are estimated by extrapolating the lattice parametrization in the large pion mass regime to the physical regime. As for the pion cloud contributions, we parameterize them in a covariant, phenomenological manner, combined with SU(3) symmetry. We also discuss the impact of the pion cloud effects on the octet baryon electromagnetic form factors and their radii.
Octet Baryon Electromagnetic Form Factors in a Relativistic Quark Model
Energy Technology Data Exchange (ETDEWEB)
Gilberto Ramalho, Kazuo Tsushima
2011-09-01
We study the octet baryon electromagnetic properties by applying the covariant spectator quark model, and provide covariant parametrization that can be used to study baryon electromagnetic reactions. While we use the lattice QCD data in the large pion mass regime (small pion cloud effects) to determine the parameters of the model in the valence quark sector, we use the nucleon physical and octet baryon magnetic moment data to parameterize the pion cloud contributions. The valence quark contributions for the octet baryon electromagnetic form factors are estimated by extrapolating the lattice parametrization in the large pion mass regime to the physical regime. As for the pion cloud contributions, we parameterize them in a covariant, phenomenological manner, combined with SU(3) symmetry. We also discuss the impact of the pion cloud effects on the octet baryon electromagnetic form factors and their radii.
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
The FIRO model of family therapy: implications of factor analysis.
Hafner, R J; Ross, M W
1989-11-01
Schutz's FIRO model contains three main elements: inclusion, control, and affection. It is used widely in mental health research and practice, but has received little empirical validation. The present study is based on factor analysis of the resources to FIRO questionnaire of 120 normal couples and 191 couples who were attending a clinic for marital/psychiatric problems. Results confirmed the validity of the FIRO model for women only. The differences between the sexes reflected a considerable degree of sex-role stereotyping, the clinical implications of which are discussed.
Neuroprotective Transcription Factors in Animal Models of Parkinson Disease
François-Xavier Blaudin de Thé; Hocine Rekaik; Alain Prochiantz; Julia Fuchs; Joshi, Rajiv L.
2015-01-01
A number of transcription factors, including En1/2, Foxa1/2, Lmx1a/b, Nurr1, Otx2, and Pitx3, with key roles in midbrain dopaminergic (mDA) neuron development, also regulate adult mDA neuron survival and physiology. Mouse models with targeted disruption of some of these genes display several features reminiscent of Parkinson disease (PD), in particular the selective and progressive loss of mDA neurons in the substantia nigra pars compacta (SNpc). The characterization of these animal models ha...
Factor models on locally tree-like graphs
Dembo, Amir; Sun, Nike
2011-01-01
We consider homogeneous factor models on uniformly sparse graph sequences converging locally to a (unimodular) random tree T, and study the existence of the free energy density phi, the limit of the log-partition function divided by the number of vertices n as n tends to infinity. We provide a new interpolation scheme and use it to prove existence of, and to explicitly compute, the quantity phi subject to uniqueness of a relevant Gibbs measure for the factor model on T. By way of example we compute phi for the independent set (or hard-core) model at low fugacity, for the ferromagnetic Ising model at all parameter values, and for the ferromagnetic Potts model with both weak enough and strong enough interactions. Even beyond uniqueness our interpolation provides useful explicit bounds on phi. In the regimes in which we establish existence of the limit, we show that it coincides with the Bethe free energy functional evaluated at a suitable fixed point of the belief propagation recursions on T. In the special cas...
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.
Gaussian and Lognormal Models of Hurricane Gust Factors
Merceret, Frank
2009-01-01
A document describes a tool that predicts the likelihood of land-falling tropical storms and hurricanes exceeding specified peak speeds, given the mean wind speed at various heights of up to 500 feet (150 meters) above ground level. Empirical models to calculate mean and standard deviation of the gust factor as a function of height and mean wind speed were developed in Excel based on data from previous hurricanes. Separate models were developed for Gaussian and offset lognormal distributions for the gust factor. Rather than forecasting a single, specific peak wind speed, this tool provides a probability of exceeding a specified value. This probability is provided as a function of height, allowing it to be applied at a height appropriate for tall structures. The user inputs the mean wind speed, height, and operational threshold. The tool produces the probability from each model that the given threshold will be exceeded. This application does have its limits. They were tested only in tropical storm conditions associated with the periphery of hurricanes. Winds of similar speed produced by non-tropical system may have different turbulence dynamics and stability, which may change those winds statistical characteristics. These models were developed along the Central Florida seacoast, and their results may not accurately extrapolate to inland areas, or even to coastal sites that are different from those used to build the models. Although this tool cannot be generalized for use in different environments, its methodology could be applied to those locations to develop a similar tool tuned to local conditions.
The DSM-5 dimensional trait model and five-factor models of general personality.
Gore, Whitney L; Widiger, Thomas A
2013-08-01
The current study tests empirically the relationship of the dimensional trait model proposed for the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) with five-factor models of general personality. The DSM-5 maladaptive trait dimensional model proposal included 25 traits organized within five broad domains (i.e., negative affectivity, detachment, antagonism, disinhibition, and psychoticism). Consistent with the authors of the proposal, it was predicted that negative affectivity would align with five-factor model (FFM) neuroticism, detachment with FFM introversion, antagonism with FFM antagonism, disinhibition with low FFM conscientiousness and, contrary to the proposal; psychoticism would align with FFM openness. Three measures of alternative five-factor models of general personality were administered to 445 undergraduates along with the Personality Inventory for DSM-5. The results provided support for the hypothesis that all five domains of the DSM-5 dimensional trait model are maladaptive variants of general personality structure, including the domain of psychoticism.
Models of Labour Services and Estimates of Total Factor Productivity
Robert Dixon; David Shepherd
2007-01-01
This paper examines the manner in which labour services are modelled in the aggregate production function, concentrating on the relationship between numbers employed and average hours worked. It argues that numbers employed and hours worked are not perfect substitutes and that conventional estimates of total factor productivity which, by using total hours worked as the measure of labour services, assume they are perfect substitutes, will be biased when there are marked changes in average hour...
Calculating osmotic pressure according to nonelectrolyte Wilson nonrandom factor model.
Li, Hui; Zhan, Tingting; Zhan, Xiancheng; Wang, Xiaolan; Tan, Xiaoying; Guo, Yiping; Li, Chengrong
2014-08-01
Abstract The osmotic pressure of NaCl solutions was determined by the air humidity in equilibrium (AHE) method. The relationship between the osmotic pressure and the concentration was explored theoretically, and the osmotic pressure was calculated according to the nonelectrolyte Wilson nonrandom factor (N-Wilson-NRF) model from the concentration. The results indicate that the calculated osmotic pressure is comparable to the measured one.
Principal component and factor analytic models in international sire evaluation
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Jakobsen Jette
2011-09-01
Full Text Available Abstract Background Interbull is a non-profit organization that provides internationally comparable breeding values for globalized dairy cattle breeding programmes. Due to different trait definitions and models for genetic evaluation between countries, each biological trait is treated as a different trait in each of the participating countries. This yields a genetic covariance matrix of dimension equal to the number of countries which typically involves high genetic correlations between countries. This gives rise to several problems such as over-parameterized models and increased sampling variances, if genetic (covariance matrices are considered to be unstructured. Methods Principal component (PC and factor analytic (FA models allow highly parsimonious representations of the (covariance matrix compared to the standard multi-trait model and have, therefore, attracted considerable interest for their potential to ease the burden of the estimation process for multiple-trait across country evaluation (MACE. This study evaluated the utility of PC and FA models to estimate variance components and to predict breeding values for MACE for protein yield. This was tested using a dataset comprising Holstein bull evaluations obtained in 2007 from 25 countries. Results In total, 19 principal components or nine factors were needed to explain the genetic variation in the test dataset. Estimates of the genetic parameters under the optimal fit were almost identical for the two approaches. Furthermore, the results were in a good agreement with those obtained from the full rank model and with those provided by Interbull. The estimation time was shortest for models fitting the optimal number of parameters and prolonged when under- or over-parameterized models were applied. Correlations between estimated breeding values (EBV from the PC19 and PC25 were unity. With few exceptions, correlations between EBV obtained using FA and PC approaches under the optimal fit were
The Animal Model Determines the Results of Aeromonas Virulence Factors
Romero, Alejandro; Saraceni, Paolo R.; Merino, Susana; Figueras, Antonio; Tomás, Juan M.; Novoa, Beatriz
2016-01-01
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 Aeromonas 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 analyzed 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-1ΔvapA 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-1ΔrmlB, which lacks the O-antigen lipopolysaccharide (LPS), and the AH-1ΔwahD, 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 demonstrates
CSIR Research Space (South Africa)
Das, Sonali
2010-01-01
Full Text Available This paper uses the dynamic factor model framework, which accommodates a large cross-section of macroeconomic time series, for forecasting regional house price inflation. In this study, the authors forecast house price inflation for five...
National Research Council Canada - National Science Library
Muthen, Bengt; Asparouhov, Tihomir; Rebollo, Irene
2006-01-01
This article discusses new latent variable techniques developed by the authors. As an illustration, a new factor mixture model is applied to the monozygotic-dizygotic twin analysis of binary items measuring alcohol-use disorder...
del Pino Pérez, Antonio; Ibáñez Fernández, Ignacio; Bosa Ojeda, Francisco; Dorta González, Ruth; Gaos Miezoso, María Teresa
2012-02-01
The objective of this study was to validate in a sample of 205 coronary patients a factor model for the BDI-II, especially a model that would allow for modeling of depressive symptoms after explicitly removing bias related to somatic symptoms of depression that would overlap those of heart disease. Exploratory and confirmatory factor analyses for ordinal data were conducted. A one-factor model, six correlated two-factor models and, derivatives thereof, seven models with a single General Depression factor and two uncorrelated factors, were analyzed. Exploratory analysis extracted two factors, Somatic-affective and Cognitive. Confirmatory factor analyses showed the worst fit for the one-factor model. Two-factor models were surpassed in goodness of fit by the models of general-factor and group factors. Among these, the General, Somatic-affective and Cognitive (G-Sa-C) model of Beck with students is noteworthy. The reduced General, Somatic and Cognitive (G-S-C) model of Ward showed the worst goodness of fit. Our model surpasses the cutoff criteria of all fit indexes. We conclude that the inclusion of a general-factor and group factors in all the models surpasses the results of G-S-C model and, therefore, questions it. The G-Sa-C model is strengthened.
Correspondence between five-factor and RIASEC models of personality.
Schinka, J A; Dye, D A; Curtiss, G
1997-04-01
In this study, we examined relationships between the full five-factor (FF; Costa & McCrae, 1985, 1992; Digman, 1990) and Holland's (1985a) RIASEC models of personality in a sample of 1,034 adults. The NEO Personality Inventory-Revised (Costa & McCrae, 1992) and the Self-Directed Search (Holland, 1985c) provided measures of the FF and RIASEC dimensions, respectively. Canonical correlation analyses provided evidence primarily for a pattern of linkages between the FF Extraversion, Openness, and Agreeableness measures and the RIASEC Enterprising, Artistic, and Social scales. Findings from this and previous studies indicated that the FF model appears to ignore the Realistic dimension and provides coverage of the Investigative and Conventional dimensions in women only. In turn, the RIASEC model appears to provide modest coverage of the FF Neuroticism and Conscientiousness domains for women and not at all for men.
Clinical application of the five-factor model.
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.
An Illumination Modeling System for Human Factors Analyses
Huynh, Thong; Maida, James C.; Bond, Robert L. (Technical Monitor)
2002-01-01
Seeing is critical to human performance. Lighting is critical for seeing. Therefore, lighting is critical to human performance. This is common sense, and here on earth, it is easily taken for granted. However, on orbit, because the sun will rise or set every 45 minutes on average, humans working in space must cope with extremely dynamic lighting conditions. Contrast conditions of harsh shadowing and glare is also severe. The prediction of lighting conditions for critical operations is essential. Crew training can factor lighting into the lesson plans when necessary. Mission planners can determine whether low-light video cameras are required or whether additional luminaires need to be flown. The optimization of the quantity and quality of light is needed because of the effects on crew safety, on electrical power and on equipment maintainability. To address all of these issues, an illumination modeling system has been developed by the Graphics Research and Analyses Facility (GRAF) and Lighting Environment Test Facility (LETF) in the Space Human Factors Laboratory at NASA Johnson Space Center. The system uses physically based ray tracing software (Radiance) developed at Lawrence Berkeley Laboratories, a human factors oriented geometric modeling system (PLAID) and an extensive database of humans and environments. Material reflectivity properties of major surfaces and critical surfaces are measured using a gonio-reflectometer. Luminaires (lights) are measured for beam spread distribution, color and intensity. Video camera performances are measured for color and light sensitivity. 3D geometric models of humans and the environment are combined with the material and light models to form a system capable of predicting lighting conditions and visibility conditions in space.
[Diffusion factor calculation for TIP4P model of water].
Zlenko, D V
2012-01-01
A molecular dynamics study has been undertaken for a model of liquid TIP4P water. Thermal dependencies of water density and radial distribution functions were calculated for model verification. Three methods have been used for calculation of diffusion factor thermal dependencies. Their sensitivity to molecular system size and length of used trajectory has been analyzed. It has been shown that Green-Kubo formula-based approach which associates diffusion factor with speed autocorrelation function integral is preferred in case of short MD simulations. The second approach based on Einstein equation which associates mean square displacement of molecule with time is preferred in case of long simulations. It has been also demonstrated that it is possible to modify the second approach to make it more stable and reliable. This modification is to use a slope of the graph of the mean square displacement on time as the estimation of the diffusion factor instead of the ratio of molecule mean square displacement and time.
Cortical factor feedback model for cellular locomotion and cytofission.
Directory of Open Access Journals (Sweden)
Shin I Nishimura
2009-03-01
Full Text Available Eukaryotic cells can move spontaneously without being guided by external cues. For such spontaneous movements, a variety of different modes have been observed, including the amoeboid-like locomotion with protrusion of multiple pseudopods, the keratocyte-like locomotion with a widely spread lamellipodium, cell division with two daughter cells crawling in opposite directions, and fragmentations of a cell to multiple pieces. Mutagenesis studies have revealed that cells exhibit these modes depending on which genes are deficient, suggesting that seemingly different modes are the manifestation of a common mechanism to regulate cell motion. In this paper, we propose a hypothesis that the positive feedback mechanism working through the inhomogeneous distribution of regulatory proteins underlies this variety of cell locomotion and cytofission. In this hypothesis, a set of regulatory proteins, which we call cortical factors, suppress actin polymerization. These suppressing factors are diluted at the extending front and accumulated at the retracting rear of cell, which establishes a cellular polarity and enhances the cell motility, leading to the further accumulation of cortical factors at the rear. Stochastic simulation of cell movement shows that the positive feedback mechanism of cortical factors stabilizes or destabilizes modes of movement and determines the cell migration pattern. The model predicts that the pattern is selected by changing the rate of formation of the actin-filament network or the threshold to initiate the network formation.
Exploring Factor Model Parameters across Continuous Variables with Local Structural Equation Models.
Hildebrandt, Andrea; Lüdtke, Oliver; Robitzsch, Alexander; Sommer, Christopher; Wilhelm, Oliver
2016-01-01
Using an empirical data set, we investigated variation in factor model parameters across a continuous moderator variable and demonstrated three modeling approaches: multiple-group mean and covariance structure (MGMCS) analyses, local structural equation modeling (LSEM), and moderated factor analysis (MFA). We focused on how to study variation in factor model parameters as a function of continuous variables such as age, socioeconomic status, ability levels, acculturation, and so forth. Specifically, we formalized the LSEM approach in detail as compared with previous work and investigated its statistical properties with an analytical derivation and a simulation study. We also provide code for the easy implementation of LSEM. The illustration of methods was based on cross-sectional cognitive ability data from individuals ranging in age from 4 to 23 years. Variations in factor loadings across age were examined with regard to the age differentiation hypothesis. LSEM and MFA converged with respect to the conclusions. When there was a broad age range within groups and varying relations between the indicator variables and the common factor across age, MGMCS produced distorted parameter estimates. We discuss the pros of LSEM compared with MFA and recommend using the two tools as complementary approaches for investigating moderation in factor model parameters.
Strategic Competence as a Fourth-Order Factor Model: A Structural Equation Modeling Approach
Phakiti, Aek
2008-01-01
This article reports on an empirical study that tests a fourth-order factor model of strategic competence through the use of structural equation modeling (SEM). The study examines the hierarchical relationship of strategic competence to (a) strategic knowledge of cognitive and metacognitive strategy use in general (i.e., trait) and (b) strategic…
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.
The Five-Factor Model and Self-Determination Theory
DEFF Research Database (Denmark)
Olesen, Martin Hammershøj; Thomsen, Dorthe Kirkegaard; Schnieber, Anette;
questionnaires of personality traits (NEO-FFI) and causality orientations (GCOS). To test whether covariance between traits and orientations could be attributed to shared or separate latent variables we conducted joint factor analyses. Results reveal that the Autonomy orientation can be distinguished from......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...... related personality traits. The Control orientation shares a latent variable with reversed Agreeableness. The Impersonal orientation shows both overlapping and distinct features with Neuroticism. Results are discussed in relation to an integrative understanding of traits and orientations....
Cosine Based Latent Factor Model for Precision Oriented Recommendation
Directory of Open Access Journals (Sweden)
Bipul Kumar
2016-01-01
Full Text Available Recommender systems suggest a list of interesting items to users based on their prior purchase or browsing behaviour on e-commerce platforms. The continuing research in recommender systems have primarily focused on developing algorithms for rating prediction task. However, most e-commerce platforms provide ‘top-k’ list of interesting items for every user. In line with this idea, the paper proposes a novel machine learning algorithm to predict a list of ‘top-k’ items by optimizing the latent factors of users and items with the mapped scores from ratings. The basic idea is to learn latent factors based on the cosine similarity between the users and items latent features which is then used to predict the scores for unseen items for every user. Comprehensive empirical evaluations on publicly available benchmark datasets reveal that the proposed model outperforms the state-of-the-art algorithms in recommending good items to a user.
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.
Modeling impact of environmental factors on photovoltaic array performance
Directory of Open Access Journals (Sweden)
Jie Yang, Yize Sun, Yang Xu
2013-01-01
Full Text Available 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 m/s, and for irradiance values between 200 and 1000 W/m2. 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.
Nonparametric Bayesian Sparse Factor Models with application to Gene Expression modelling
Knowles, David
2010-01-01
A nonparametric Bayesian extension of Factor Analysis (FA) is proposed where observed data Y is modeled as a linear superposition, G, of a potentially infinite number of hidden factors, X. The Indian Buffet Process (IBP) is used as a prior on G to incorporate sparsity and to allow the number of latent features to be inferred. The model's utility for modeling gene expression data is investigated using randomly generated datasets based on a known sparse connectivity matrix for E. Coli, and on three biological datasets of increasing complexity.
Realistic Models for Filling Factors in HII Regions
Spangler, Steven R.; Costa, Allison H.; Bergerud, Brandon M.; Beauchamp, Kara M.
2017-01-01
One of the parameters used to describe HII regions and other ionized parts of the interstellar medium is the filling factor, defined as the volume fraction of an HII region occupied by matter. The best observational evidence for the existence of a filling factor less than unity is a discrepancy between the electron density derived from density-sensitive line ratios and the root mean square density obtained from emission measure measurements. Following the early, influential study by Osterbrock and Flather (ApJ 129, 26, 1959), most investigations of HII regions envision these objects as a group of isolated cells of high gas density embedded in a vacuum. This picture is at serious odds with more direct measurements of other astrophysical plasmas like the solar wind, where the density follows a less extreme probability distribution function (pdf) such as an exponential or lognormal. We have carried out a set of simulations in which model HII regions are created with different density pdfs such as exponential and lognormal as well as the extreme case of two delta functions. We calculate the electron density as inferred from spectroscopic line ratios and emission measures for all lines of sight through the model nebulas. In the cases of exponential and lognormal pdfs, the spectroscopically derived densities are higher than those obtained by the emission measures by factors of 20 to 100 percent. These are considerably smaller than values often reported in the literature, which can be an order of magnitude or greater. We will discuss possible ways to reconcile realistic density pdfs such as measured in space and laboratory plasmas with the results from astronomical spectroscopic measurements. Finally, we point out that for the Orion Nebula, the density discrepancy is due to geometry, not filling factor (O'Dell, ARAA 39, 99, 2001).
Stochastic contribution to the growth factor in the LCDM model
Energy Technology Data Exchange (ETDEWEB)
Ribeiro, A. L.B.; Andrade, A. P.A.; Letelier, P. S.
2009-01-01
We study the effect of noise on the evolution of the growth factor of density perturbations in the context of the LCDM model. Stochasticity is introduced as a Wiener process amplified by an intensity parameter alpha. By comparing the evolution of deterministic and stochastic cases for different values of alpha we estimate the intensity level necessary to make noise relevant for cosmological tests based on large-scale structure data. Our results indicate that the presence of random forces underlying the fluid description can lead to significant deviations from the nonstochastic solution at late times for alpha>0.001.
Liberal bias and the five-factor model.
Charney, Evan
2015-01-01
Duarte et al. draw attention to the "embedding of liberal values and methods" in social psychological research. They note how these biases are often invisible to the researchers themselves. The authors themselves fall prey to these "invisible biases" by utilizing the five-factor model of personality and the trait of openness to experience as one possible explanation for the under-representation of political conservatives in social psychology. I show that the manner in which the trait of openness to experience is conceptualized and measured is a particularly blatant example of the very liberal bias the authors decry.
Replica Analysis for Portfolio Optimization with Single-Factor Model
Shinzato, Takashi
2017-06-01
In this paper, we use replica analysis to investigate the influence of correlation among the return rates of assets on the solution of the portfolio optimization problem. We consider the behavior of an optimal solution for the case where the return rate is described with a single-factor model and compare the findings obtained from our proposed methods with correlated return rates with those obtained with independent return rates. We then analytically assess the increase in the investment risk when correlation is included. Furthermore, we also compare our approach with analytical procedures for minimizing the investment risk from operations research.
Assessment of the five-factor model of personality.
Widiger, T A; Trull, T J
1997-04-01
The five-factor model (FFM) of personality is obtaining construct validation, recognition, and practical consideration across a broad domain of fields, including clinical psychology, industrial-organizational psychology, and health psychology. As a result, an array of instruments have been developed and existing instruments are being modified to assess the FFM. In this article, we present an overview and critique of five such instruments (the Goldberg Big Five Markers, the revised NEO Personality Inventory, the Interpersonal Adjective Scales-Big Five, the Personality Psychopathology-Five, and the Hogan Personality Inventory), focusing in particular on their representation of the lexical FFM and their practical application.
The proton gyromagnetic g-factor: an electromagnetic model
Sardin, G
2009-01-01
So far, the Standard Model of Elementary Particles has not succeeded getting a trustworthy account of the proton spin, which remains an enigma. This hindrance is known as the proton spin crisis, owing to the experimental evidence already from 1988 suggesting that little or none of the proton spin would come from the spin of the quarks. This prompted theorists to a flood of guessworks about the proton spin. Since it remains unsolved, in the framework of new physics an exploratory approach based on a novel paradigm is proposed, which brings a renewed access to this challenge, through its reciprocal relationship with the g-factor.
Assessment of maladaptive variants of Five-Factor Model traits.
Lynam, Donald R
2012-12-01
Research has shown that the personality disorders (PDs) bear consistent relations to general models of personality functioning, particularly in relation to the Five-Factor Model (FFM). In addition to suggesting that the PDs might be understood as constellations of traits from the FFM, this research also suggests that these constellations might be used to assess the PDs. The present article reviews previous research using the NEO Personality Inventory-Revised (NEO PI-R; Costa & McCrae, ) to assess disordered personality and discusses some shortcomings of this approach. Next, I detail studies that have used what is known about the relations between the FFM and disordered personality to construct new assessments that are grounded in the basic science of personality but designed to assess the more pathological aspects. Finally, the advantages of this approach are outlined. © 2012 The Author. Journal of Personality © 2012, Wiley Periodicals, Inc.
Satisfiers and Dissatisfiers: A Two-Factor Model for Website Design and Evaluation.
Zhang, Ping; von Dran, Gisela M.
2000-01-01
Investigates Web site design factors and their impact from a theoretical perspective. Presents a two-factor model that can guide Web site design and evaluation. According to the model, there are two types of design factors: hygiene and motivator. Results showed that the two-factor model provides a means for Web-user interface studies. Provides…
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Chieh-Chun Chen
Full Text Available Despite explosive growth in genomic datasets, the methods for studying epigenomic mechanisms of gene regulation remain primitive. Here we present a model-based approach to systematically analyze the epigenomic functions in modulating transcription factor-DNA binding. Based on the first principles of statistical mechanics, this model considers the interactions between epigenomic modifications and a cis-regulatory module, which contains multiple binding sites arranged in any configurations. We compiled a comprehensive epigenomic dataset in mouse embryonic stem (mES cells, including DNA methylation (MeDIP-seq and MRE-seq, DNA hydroxymethylation (5-hmC-seq, and histone modifications (ChIP-seq. We discovered correlations of transcription factors (TFs for specific combinations of epigenomic modifications, which we term epigenomic motifs. Epigenomic motifs explained why some TFs appeared to have different DNA binding motifs derived from in vivo (ChIP-seq and in vitro experiments. Theoretical analyses suggested that the epigenome can modulate transcriptional noise and boost the cooperativity of weak TF binding sites. ChIP-seq data suggested that epigenomic boost of binding affinities in weak TF binding sites can function in mES cells. We showed in theory that the epigenome should suppress the TF binding differences on SNP-containing binding sites in two people. Using personal data, we identified strong associations between H3K4me2/H3K9ac and the degree of personal differences in NFκB binding in SNP-containing binding sites, which may explain why some SNPs introduce much smaller personal variations on TF binding than other SNPs. In summary, this model presents a powerful approach to analyze the functions of epigenomic modifications. This model was implemented into an open source program APEG (Affinity Prediction by Epigenome and Genome, http://systemsbio.ucsd.edu/apeg.
Chen, Chieh-Chun; Xiao, Shu; Xie, Dan; Cao, Xiaoyi; Song, Chun-Xiao; Wang, Ting; He, Chuan; Zhong, Sheng
2013-01-01
Despite explosive growth in genomic datasets, the methods for studying epigenomic mechanisms of gene regulation remain primitive. Here we present a model-based approach to systematically analyze the epigenomic functions in modulating transcription factor-DNA binding. Based on the first principles of statistical mechanics, this model considers the interactions between epigenomic modifications and a cis-regulatory module, which contains multiple binding sites arranged in any configurations. We compiled a comprehensive epigenomic dataset in mouse embryonic stem (mES) cells, including DNA methylation (MeDIP-seq and MRE-seq), DNA hydroxymethylation (5-hmC-seq), and histone modifications (ChIP-seq). We discovered correlations of transcription factors (TFs) for specific combinations of epigenomic modifications, which we term epigenomic motifs. Epigenomic motifs explained why some TFs appeared to have different DNA binding motifs derived from in vivo (ChIP-seq) and in vitro experiments. Theoretical analyses suggested that the epigenome can modulate transcriptional noise and boost the cooperativity of weak TF binding sites. ChIP-seq data suggested that epigenomic boost of binding affinities in weak TF binding sites can function in mES cells. We showed in theory that the epigenome should suppress the TF binding differences on SNP-containing binding sites in two people. Using personal data, we identified strong associations between H3K4me2/H3K9ac and the degree of personal differences in NFκB binding in SNP-containing binding sites, which may explain why some SNPs introduce much smaller personal variations on TF binding than other SNPs. In summary, this model presents a powerful approach to analyze the functions of epigenomic modifications. This model was implemented into an open source program APEG (Affinity Prediction by Epigenome and Genome, http://systemsbio.ucsd.edu/apeg).
Neuropathology and Animal Models of Autism: Genetic and Environmental Factors
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Bharathi S. Gadad
2013-01-01
Full Text Available Autism is a heterogeneous behaviorally defined neurodevelopmental disorder. It is defined by the presence of marked social deficits, specific language abnormalities, and stereotyped repetitive patterns of behavior. Because of the variability in the behavioral phenotype of the disorder among patients, the term autism spectrum disorder has been established. In the first part of this review, we provide an overview of neuropathological findings from studies of autism postmortem brains and identify the cerebellum as one of the key brain regions that can play a role in the autism phenotype. We review research findings that indicate possible links between the environment and autism including the role of mercury and immune-related factors. Because both genes and environment can alter the structure of the developing brain in different ways, it is not surprising that there is heterogeneity in the behavioral and neuropathological phenotypes of autism spectrum disorders. Finally, we describe animal models of autism that occur following insertion of different autism-related genes and exposure to environmental factors, highlighting those models which exhibit both autism-like behavior and neuropathology.
Estimating degree day factors from MODIS for snowmelt runoff modeling
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Z. H. He
2014-07-01
Full Text Available Degree-day factors are widely used to estimate snowmelt runoff in operational hydrological models. Usually, they are calibrated on observed runoff, and sometimes on satellite snow cover data. In this paper, we propose a new method for estimating the snowmelt degree-day factor (DDFS directly from MODIS snow covered area (SCA and ground based snow depth data without calibration. Subcatchment snow volume is estimated by combining SCA and snow depths. Snow density is estimated as the ratio of observed precipitation and changes in the snow volume for days with snow accumulation. Finally, DDFS values are estimated as the ratio of changes in the snow water equivalent and degree-day temperatures for days with snow melt. We compare simulations of basin runoff and snow cover patterns using spatially variable DDFS estimated from snow data with those using spatially uniform DDFS calibrated on runoff. The runoff performances using estimated DDFS are slightly improved, and the simulated snow cover patterns are significantly more plausible. The new method may help reduce some of the runoff model parameter uncertainty by reducing the total number of calibration parameters.
Model approach for estimating potato pesticide bioconcentration factor.
Paraíba, Lourival Costa; Kataguiri, Karen
2008-11-01
We presented a model that estimates the bioconcentration factor (BCF) of pesticides in potatoes supposing that the pesticide in the soil solution is absorbed by the potato by passive diffusion, following Fick's second law. The pesticides in the model are nonionic organic substances, traditionally used in potato crops that degrade in the soil according to a first-order kinetic equation. This presents an expression that relates BCF with the pesticide elimination rate by the potato, with the pesticide accumulation rate within the potato, with the rate of growth of the potato and with the pesticide degradation rate in the soil. BCF was estimated supposing steady state equilibrium of the quotient between the pesticide concentration in the potato and the pesticide concentration in the soil solution. It is suggested that a negative correlation exists between the pesticide BCF and the soil sorption partition coefficient. The model was built based on the work of Trapp et al. [Trapp, S., Cammarano, A., Capri, E., Reichenberg, F., Mayer, P., 2007. Diffusion of PAH in potato and carrot slices and application for a potato model. Environ. Sci. Technol. 41 (9), 3103-3108], in which an expression to calculate the diffusivity of persistent organic substances in potatoes is presented. The model consists in adding to the expression of Trapp et al. [Trapp, S., Cammarano, A., Capri, E., Reichenberg, F., Mayer, P., 2007. Diffusion of PAH in potato and carrot slices and application for a potato model. Environ. Sci. Technol. 41 (9), 3103-3108] the hypothesis that the pesticide degrades in the soil. The value of BCF suggests which pesticides should be monitored in potatoes.
Emission factors for passenger cars: application of instantaneous emission modeling
de Haan, Peter; Keller, Mario
This paper discusses the use of 'instantaneous' high-resolution (1 Hz) emission data for the estimation of passenger car emissions during real-world driving. Extensive measurements of 20 EURO-I gasoline passenger cars have been used to predict emission factors for standard (i.e. legislative) as well as non-standard (i.e. real-world) driving patterns. It is shown that emission level predictions based upon chassis dynamometer tests over standard driving cycles significantly underestimate emission levels during real-world driving. The emission characteristics of modern passenger cars equipped with a three-way catalytic converter are a low, basic emission level on the one hand, and frequent emission 'peaks' on the other. For real-world driving, up to one-half of the entire emission can be emitted during these short-lasting peaks. Their frequency depends on various factors, including the level of 'dynamics' (speed variation) of the driving pattern. Because of this, the use of average speed as the only parameter to characterize emissions over a specific driving pattern is not sufficient. The instantaneous emissions approach uses an additional parameter representing engine load in order to resolve the differences between driving patterns with comparable average speeds but different levels of 'dynamics'. The paper includes an investigation of different statistical indicators and discusses methods to further improve the prediction capability of the instantaneous emission approach. The fundamental differences in emission-reduction strategies between different car manufacturers make the task of constructing a model valid for all catalyst passenger cars seemingly impossible, if the model is required to predict both fleet-averaged emission levels and emission factors for driving patterns of short duration for individual vehicles simultaneously.
Samuel, Douglas B.; Mullins-Sweatt, Stephanie N.; Widiger, Thomas A.
2013-01-01
The Five-Factor Model Rating Form (FFMRF) is a one-page measure designed to provide an efficient assessment of the higher order domains of the Five Factor Model (FFM) as well as the more specific, lower order facets proposed by McCrae and Costa. Although previous research has suggested that the FFMRF's assessment of the lower order facets converge…
Salekin, Randall T; Chen, Debra R; Sellbom, Martin; Lester, Whitney S; MacDougall, Emily
2014-07-01
The Levenson, Kiehl, and Fitzpatrick (1995) Self-Report Psychopathy Scale (LSRP) was introduced in the mid-1990s as a brief measure of psychopathy and has since gained considerable popularity. Despite its attractiveness as a brief psychopathy tool, the LSRP has received limited research regarding its factor structure and convergent and discriminant validity. The present study examined the construct validity of the LSRP, testing both its factor structure and the convergent and discriminant validity. Using a community sample of 1,257 undergraduates (869 females; 378 males), we tested whether a 1-, 2-, or 3-factor model best fit the data and examined the links between the resultant factor structures and external correlates. Confirmatory factor analysis (CFA) findings revealed a 3-factor model best matched the data, followed by an adequate-fitting original 2-factor model. Next, comparisons were made regarding the convergent and discriminant validity of the competing 2- and 3-factor models. Findings showed the LSRP traditional primary and secondary factors had meaningful relations with extratest variables such as neuroticism, stress tolerance, and lack of empathy. The 3-factor model showed particular problems with the Callousness scale. These findings underscore the importance of examining not only CFA fit statistics but also convergent and discriminant validity when testing factor structure models. The current findings suggest that the 2-factor model might still be the best way to interpret the LSRP. (c) 2014 APA, all rights reserved.
Muthén, Bengt; Asparouhov, Tihomir; Rebollo, Irene
2006-06-01
This article discusses new latent variable techniques developed by the authors. As an illustration, a new factor mixture model is applied to the monozygotic-dizygotic twin analysis of binary items measuring alcohol-use disorder. In this model, heritability is simultaneously studied with respect to latent class membership and within-class severity dimensions. Different latent classes of individuals are allowed to have different heritability for the severity dimensions. The factor mixture approach appears to have great potential for the genetic analyses of heterogeneous populations. Generalizations for longitudinal data are also outlined.
Factors influencing protein tyrosine nitration--structure-based predictive models.
Bayden, Alexander S; Yakovlev, Vasily A; Graves, Paul R; Mikkelsen, Ross B; Kellogg, Glen E
2011-03-15
Models for exploring tyrosine nitration in proteins have been created based on 3D structural features of 20 proteins for which high-resolution X-ray crystallographic or NMR data are available and for which nitration of 35 total tyrosines has been experimentally proven under oxidative stress. Factors suggested in previous work to enhance nitration were examined with quantitative structural descriptors. The role of neighboring acidic and basic residues is complex: for the majority of tyrosines that are nitrated the distance to the heteroatom of the closest charged side chain corresponds to the distance needed for suspected nitrating species to form hydrogen bond bridges between the tyrosine and that charged amino acid. This suggests that such bridges play a very important role in tyrosine nitration. Nitration is generally hindered for tyrosines that are buried and for those tyrosines for which there is insufficient space for the nitro group. For in vitro nitration, closed environments with nearby heteroatoms or unsaturated centers that can stabilize radicals are somewhat favored. Four quantitative structure-based models, depending on the conditions of nitration, have been developed for predicting site-specific tyrosine nitration. The best model, relevant for both in vitro and in vivo cases, predicts 30 of 35 tyrosine nitrations (positive predictive value) and has a sensitivity of 60/71 (11 false positives). Copyright © 2010 Elsevier Inc. All rights reserved.
Confirmatory Factor Analysis of WAIS-IV in a Clinical Sample: Examining a Bi-Factor Model
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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.
Confirmatory Factor Analysis of WAIS-IV in a Clinical Sample: Examining a Bi-Factor Model
Rachel Collinson; Stephen Evans; Miranda Wheeler; Don Brechin; Jenna Moffitt; Geoff Hill; Steven Muncer
2016-01-01
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.
Gu, Fei; Preacher, Kristopher J; Wu, Wei; Yung, Yiu-Fai
2014-01-01
Although the state space approach for estimating multilevel regression models has been well established for decades in the time series literature, it does not receive much attention from educational and psychological researchers. In this article, we (a) introduce the state space approach for estimating multilevel regression models and (b) extend the state space approach for estimating multilevel factor models. A brief outline of the state space formulation is provided and then state space forms for univariate and multivariate multilevel regression models, and a multilevel confirmatory factor model, are illustrated. The utility of the state space approach is demonstrated with either a simulated or real example for each multilevel model. It is concluded that the results from the state space approach are essentially identical to those from specialized multilevel regression modeling and structural equation modeling software. More importantly, the state space approach offers researchers a computationally more efficient alternative to fit multilevel regression models with a large number of Level 1 units within each Level 2 unit or a large number of observations on each subject in a longitudinal study.
van Schuur, Wyijbrandt H.; Kiers, Henk A.L.
Factor analysis of data that conform to the unfolding model often results in an extra factor. This artificial extra factor is particularly important when data that conform to a bipolar unidimensional unfolding scale are factor analyzed. One bipolar dimension is expected, but two factors are found
Latent Fundamentals Arbitrage with a Mixed Effects Factor Model
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Andrei Salem Gonçalves
2012-09-01
Full Text Available We propose a single-factor mixed effects panel data model to create an arbitrage portfolio that identifies differences in firm-level latent fundamentals. Furthermore, we show that even though the characteristics that affect returns are unknown variables, it is possible to identify the strength of the combination of these latent fundamentals for each stock by following a simple approach using historical data. As a result, a trading strategy that bought the stocks with the best fundamentals (strong fundamentals portfolio and sold the stocks with the worst ones (weak fundamentals portfolio realized significant risk-adjusted returns in the U.S. market for the period between July 1986 and June 2008. To ensure robustness, we performed sub period and seasonal analyses and adjusted for trading costs and we found further empirical evidence that using a simple investment rule, that identified these latent fundamentals from the structure of past returns, can lead to profit.
Logistic regression for risk factor modelling in stuttering research.
Reed, Phil; Wu, Yaqionq
2013-06-01
To outline the uses of logistic regression and other statistical methods for risk factor analysis in the context of research on stuttering. The principles underlying the application of a logistic regression are illustrated, and the types of questions to which such a technique has been applied in the stuttering field are outlined. The assumptions and limitations of the technique are discussed with respect to existing stuttering research, and with respect to formulating appropriate research strategies to accommodate these considerations. Finally, some alternatives to the approach are briefly discussed. The way the statistical procedures are employed are demonstrated with some hypothetical data. Research into several practical issues concerning stuttering could benefit if risk factor modelling were used. Important examples are early diagnosis, prognosis (whether a child will recover or persist) and assessment of treatment outcome. After reading this article you will: (a) Summarize the situations in which logistic regression can be applied to a range of issues about stuttering; (b) Follow the steps in performing a logistic regression analysis; (c) Describe the assumptions of the logistic regression technique and the precautions that need to be checked when it is employed; (d) Be able to summarize its advantages over other techniques like estimation of group differences and simple regression. Copyright © 2012 Elsevier Inc. All rights reserved.
Complement factor B expression profile in a spontaneous uveitis model.
Zipplies, Johanna K; Kirschfink, Michael; Amann, Barbara; Hauck, Stefanie M; Stangassinger, Manfred; Deeg, Cornelia A
2010-12-01
Equine recurrent uveitis serves as a spontaneous model for human autoimmune uveitis. Unpredictable relapses and ongoing inflammation in the eyes of diseased horses as well as in humans lead to destruction of the retina and finally result in blindness. However, the molecular mechanisms leading to inflammation and retinal degeneration are not well understood. An initial screening for differentially regulated proteins in sera of uveitic cases compared to healthy controls revealed an increase of the alternative pathway complement component factor B in ERU cases. To determine the activation status of the complement system, sera were subsequently examined for complement split products. We could demonstrate a significant higher concentration of the activation products B/Ba, B/Bb, Bb neoantigen, iC3b and C3d in uveitic condition compared to healthy controls, whereas for C5b-9 no differences were detected. Additionally, we investigated complement activation directly in the retina by immunohistochemistry, since it is the main target organ of this autoimmune disease. Interestingly, infiltrating cells co-expressed activated factor Bb neoantigen, complement split product C3d as well as CD68, a macrophage marker. In this study, we could demonstrate activation of the complement system both systemically as well as in the eye, the target organ of spontaneous recurrent uveitis. Based on these novel findings, we postulate a novel role for macrophages in connection with complement synthesis at the site of inflammation.
Five-Factor Model personality profiles of drug users
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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.
Dynamic-structure-factor measurements on a model Lorentz gas
Egelstaff, P. A.; Eder, O. J.; Glaser, W.; Polo, J.; Renker, B.; Soper, A. K.
1990-02-01
A model system for the Lorentz gas can be made [Eder, Chen, and Egelstaff, Proc. Phys. Soc. London 89, 833 (1966); McPherson and Egelstaff, Can. J. Phys. 58, 289 (1980)] by mixing small quantities of hydrogen with an argon host. For neutron-scattering experiments the large H-to-Ar cross section ratio (~200) makes the argon relatively invisible. Dynamic-structure-factor [S(Q,ω) for H2] measurements at room temperature have been made on this system using the IN4 spectrometer at the Institute Laue Langevin, Grenoble, France. Argon densities between 1.9 and 10.5 atoms/nm3 were used for 0.4model, but slightly less complicated than a computer simulation so showing the significance of multiple-collision processes.
A comparison of the VAR model and the PC factor model in forecasting inflation in Montenegro
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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.
The Effects of Autocorrelation on the Curve-of-Factors Growth Model
Murphy, Daniel L.; Beretvas, S. Natasha; Pituch, Keenan A.
2011-01-01
This simulation study examined the performance of the curve-of-factors model (COFM) when autocorrelation and growth processes were present in the first-level factor structure. In addition to the standard curve-of factors growth model, 2 new models were examined: one COFM that included a first-order autoregressive autocorrelation parameter, and a…
Yun, Sung Hyun
2011-01-01
The present study investigated the factor structure and reliability of the revised Conflict Tactics Scales' (CTS2) 10-factor model in a community-based female sample (N = 261). The underlying factor structure of the 10-factor model was tested by the confirmatory multiple group factor analysis, which demonstrated complex factor cross-loadings…
Five-factor model personality traits in opioid dependence
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Nordvik Hilmar
2007-08-01
Full Text Available Abstract Background Personality traits may form a part of the aetiology of opioid dependence. For instance, opioid dependence may result from self-medication in emotionally unstable individuals, or from experimenting with drugs in sensation seekers. The five factor model (FFM has obtained a central position in contemporary personality trait theory. The five factors are: Neuroticism, Extraversion, Openness to Experience, Agreeableness and Conscientiousness. Few studies have examined whether there is a distinct personality pattern associated with opioid dependence. Methods We compared FFM personality traits in 65 opioid dependent persons (mean age 27 years, 34% females in outpatient counselling after a minimum of 5 weeks in buprenorphine replacement therapy, with those in a non-clinical, age- and sex-matched sample selected from a national database. Personality traits were assessed by a Norwegian version of the Revised NEO Personality Inventory (NEO PI-R, a 240-item self-report questionnaire. Cohen's d effect sizes were calculated for the differences in personality trait scores. Results The opioid-dependent sample scored higher on Neuroticism, lower on Extraversion and lower on Conscientiousness (d = -1.7, 1.2 and 1.7, respectively than the controls. Effects sizes were small for the difference between the groups in Openness to experience scores and Agreeableness scores. Conclusion We found differences of medium and large effect sizes between the opioid dependent group and the matched comparison group, suggesting that the personality traits of people with opioid dependence are in fact different from those of non-clinical peers.
Comparing factor analytic models of the DSM-IV personality disorders.
Huprich, Steven K; Schmitt, Thomas A; Richard, David C S; Chelminski, Iwona; Zimmerman, Mark A
2010-01-01
There is little agreement about the latent factor structure of the Diagnostic and Statistical Manual of Mental Disorders (DSM) personality disorders (PDs). Factor analytic studies over the past 2 decades have yielded different results, in part reflecting differences in factor analytic technique, the measure used to assess the PDs, and the changing DSM criteria. In this study, we explore the latent factor structure of the DSM (4th ed.; IV) PDs in a sample of 1200 psychiatric outpatients evaluated with the Structured Interview for DSM-IV PDs (B. Pfohl, N. Blum, & M. Zimmerman, 1997). We first evaluated 2 a priori models of the PDs with confirmatory factor analysis (CFA), reflecting their inherent organization in the DSM-IV: a 3-factor model and a 10-factor model. Fit statistics did not suggest that these models yielded an adequate fit. We then evaluated the latent structure with exploratory factor analysis (EFA). Multiple solutions produced more statistically and theoretically reasonable results, as well as providing clinically useful findings. On the basis of fit statistics and theory, 3 models were evaluated further--the 4-, 5-, and 10-factor models. The 10-factor model, which did not resemble the 10-factor model of the CFA, was determined to be the strongest of all 3 models. Future research should use contemporary methods of evaluating factor analytic results in order to more thoroughly compare various factor solutions.
Modeling microRNA-transcription factor networks in cancer.
Aguda, Baltazar D
2013-01-01
An increasing number of transcription factors (TFs) and microRNAs (miRNAs) is known to form feedback loops (FBLs) of interactions where a TF positively or negatively regulates the expression of a miRNA, and the miRNA suppresses the translation of the TF messenger RNA. FBLs are potential sources of instability in a gene regulatory network. Positive FBLs can give rise to switching behaviors while negative FBLs can generate periodic oscillations. This chapter presents documented examples of FBLs and their relevance to stem cell renewal and differentiation in gliomas. Feed-forward loops (FFLs) are only discussed briefly because they do not affect network stability unless they are members of cycles. A primer on qualitative network stability analysis is given and then used to demonstrate the network destabilizing role of FBLs. Steps in model formulation and computer simulations are illustrated using the miR-17-92/Myc/E2F network as an example. This example possesses both negative and positive FBLs.
Multivariate poisson-lognormal model for modeling related factors in crash frequency by severity
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Mehdi Tazhibi
2013-01-01
Full Text Available Aims: Traditionally, roadway safety analyses have used univariate distributions to model crash data for each level of severity separately. This paper uses the multivariate Poisson lognormal (MVPLN models to estimate the expected crash frequency by two levels of severity and then compares those estimates with the univariate Poisson-lognormal (UVPLN and the univariate Poisson (UVP models. Materials and Methods: The parameters estimation is done by Bayesian method for crash data at two levels of severity at the intersection of Isfahan city for 6 months. Results: The results showed that there was over-dispersion issue in data. The UVP model is not able to overcome this problem while the MVPLN model can account for over-dispersion. Also, the estimates of the extra Poisson variation parameters in the MVPLN model were smaller than the UVPLN model that causes improvement in the precision of the MNPLN model. Hence, the MVPLN model is better fitted to the data set. Also, results showed effect of the total Average annual daily traffic (AADT on the property damage only crash was significant in the all of models but effect of the total left turn AADT on the injuries and fatalities crash was significant just in the UVP model. Hence, holding all other factors fixed more property damage only crashes were expected on more the total AADT. For example, under MVPLN model an increase of 1000 vehicles in (average the total AADT was predicted to result in 31% more property damage only crash. Conclusion: Hence, reduction of total AADT was predicted to be highly cost-effective, in terms of the crash cost reductions over the long run.
Factor Analysis of People Rather than Variables: Q and Other Two-Mode Factor Analytic Models.
Frederick, Brigitte N.
Factor analysis attempts to study how different objects group together to form factors with the purposes of: (1) reducing the number of factorable entities (e.g., variables) with which the researcher needs to deal; (2) searching data for qualitative and quantitative differences; and (3) testing hypotheses (R. Gorsuch, 1983). While most factor…
Spectral density of the correlation matrix of factor models: a random matrix theory approach.
Lillo, F; Mantegna, R N
2005-07-01
We studied the eigenvalue spectral density of the correlation matrix of factor models of multivariate time series. By making use of the random matrix theory, we analytically quantified the effect of statistical uncertainty on the spectral density due to the finiteness of the sample. We considered a broad range of models, ranging from one-factor models to hierarchical multifactor models.
Modeling individual subtests of the WAIS IV with multiple latent factors.
Directory of Open Access Journals (Sweden)
Dennis J McFarland
Full Text Available Performance on a cognitive test can be viewed either as measuring a unitary function or as reflecting the operation of multiple factors. Individual subtests in batteries designed to measure human abilities are commonly modeled as a single latent factor. Several latent factors are then used to model groups of subtests. However these latent factors are not independent as they are related through hierarchical or oblique structures. As a result, the simple structure of subtest performance results in complex latent factors. The present study used structural equation modeling to evaluate several multidimensional models of the Wechsler Adult Intelligence Scales-fourth edition (WAIS-IV subtests. Multidimensional models of subtest performance provided better model fit as compared to several previously proposed one dimensional models. These multidimensional models also generalized well to new samples of populations differing in age from that used to estimate the model parameters. Overall these results show that models that describe subtests as multidimensional functions of uncorrelated factors provided a better fit to the WAIS-IV correlations than models that describe subtests as one dimensional functions of correlated factors. There appears to be a trade-off in modeling subtests as one dimensional and modeling with homogeneous latent traits. More consideration should be given to models that include multiple uncorrelated latent factors as determinants of the performance on a given subtest. These results support the view that performance on any given cognitive test is potentially the result of multiple factors. Simple structure may be too simple.
Modeling individual subtests of the WAIS IV with multiple latent factors.
McFarland, Dennis J
2013-01-01
Performance on a cognitive test can be viewed either as measuring a unitary function or as reflecting the operation of multiple factors. Individual subtests in batteries designed to measure human abilities are commonly modeled as a single latent factor. Several latent factors are then used to model groups of subtests. However these latent factors are not independent as they are related through hierarchical or oblique structures. As a result, the simple structure of subtest performance results in complex latent factors. The present study used structural equation modeling to evaluate several multidimensional models of the Wechsler Adult Intelligence Scales-fourth edition (WAIS-IV) subtests. Multidimensional models of subtest performance provided better model fit as compared to several previously proposed one dimensional models. These multidimensional models also generalized well to new samples of populations differing in age from that used to estimate the model parameters. Overall these results show that models that describe subtests as multidimensional functions of uncorrelated factors provided a better fit to the WAIS-IV correlations than models that describe subtests as one dimensional functions of correlated factors. There appears to be a trade-off in modeling subtests as one dimensional and modeling with homogeneous latent traits. More consideration should be given to models that include multiple uncorrelated latent factors as determinants of the performance on a given subtest. These results support the view that performance on any given cognitive test is potentially the result of multiple factors. Simple structure may be too simple.
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.
van der Gaag, Mark; Cuijpers, Anke; Hoffman, Tonko; Remijsen, Mila; Hijman, Ron; de Haan, Lieuwe; van Meijel, Berno; van Harten, Peter N.; Valmaggia, Lucia; de Hert, Marc; Wiersma, Durk
2006-01-01
Objective: The aim of this study was to test the goodness-of-fit of all previously published five-factor models of the Positive and Negative Syndrome Scale (PANSS). Methods: We used confirmatory factor analysis (CFA) with a large data set (N = 5769). Results: The different subsamples were tested for
Testing for time-varying loadings in dynamic factor models
DEFF Research Database (Denmark)
Mikkelsen, Jakob Guldbæk
factors. The squared correlation coefficient times the sample size has a limiting chi-squared distribution. The test can be made robust to serial correlation in the idiosyncratic errors. We find evidence for factor loadings variance in over half of the variables in a dataset for the US economy, while...... there is evidence of time-varying loadings on the risk factors underlying portfolio returns for around 80% of the portfolios....
Integrated traffic conflict model for estimating crash modification factors.
Shahdah, Usama; Saccomanno, Frank; Persaud, Bhagwant
2014-10-01
Crash modification factors (CMFs) for road safety treatments are usually obtained through observational models based on reported crashes. Observational Bayesian before-and-after methods have been applied to obtain more precise estimates of CMFs by accounting for the regression-to-the-mean bias inherent in naive methods. However, sufficient crash data reported over an extended period of time are needed to provide reliable estimates of treatment effects, a requirement that can be a challenge for certain types of treatment. In addition, these studies require that sites analyzed actually receive the treatment to which the CMF pertains. Another key issue with observational approaches is that they are not causal in nature, and as such, cannot provide a sound "behavioral" rationale for the treatment effect. Surrogate safety measures based on high risk vehicle interactions and traffic conflicts have been proposed to address this issue by providing a more "causal perspective" on lack of safety for different road and traffic conditions. The traffic conflict approach has been criticized, however, for lacking a formal link to observed and verified crashes, a difficulty that this paper attempts to resolve by presenting and investigating an alternative approach for estimating CMFs using simulated conflicts that are linked formally to observed crashes. The integrated CMF estimates are compared to estimates from an empirical Bayes (EB) crash-based before-and-after analysis for the same sample of treatment sites. The treatment considered involves changing left turn signal priority at Toronto signalized intersections from permissive to protected-permissive. The results are promising in that the proposed integrated method yields CMFs that closely match those obtained from the crash-based EB before-and-after analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.
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…
40 CFR Table 4 to Subpart Dddd of... - Model Rule-Toxic Equivalency Factors
2010-07-01
... 40 Protection of Environment 6 2010-07-01 2010-07-01 false Model Rule-Toxic Equivalency Factors 4... or Before November 30, 1999 Pt. 60, Subpt. DDDD, Table 4 Table 4 to Subpart DDDD of Part 60—Model Rule—Toxic Equivalency Factors Dioxin/furan congener Toxic equivalency factor 2,3,7,8-tetrachlorinated...
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.
Directory of Open Access Journals (Sweden)
Dilek Teker
2013-01-01
Full Text Available The aim of this research is to compose a new rating methodology and provide credit notches to 23 countries which of 13 are developed and 10 are emerging. There are various literature that explains the determinants of credit ratings. Following the literature, we select 11 variables for our model which of 5 are eliminated by the factor analysis. We use specific dummies to investigate the structural breaks in time and cross section such as pre crises, post crises, BRIC membership, EU membership, OPEC membership, shipbuilder country and platinum reserved country. Then we run an ordered probit model and give credit notches to the countries. We use FITCH ratings as benchmark. Thus, at the end we compare the notches of FITCH with the ones we derive out of our estimated model.
The two-factor model of evaluating mining rights of coal resources based on options
Institute of Scientific and Technical Information of China (English)
ZHANG Jin-suo; ZOU Shao-hui; SHI Xin-min
2008-01-01
MRCR could be regarded as a multi-stage compounding real option, based on option theory, assuming the convenience yield of coal reserves to be constant, built a one-factor model of valuating MRCR with the stochastic value of coal reserves. On the basis of our one-factor model, set up a two-factor model of evaluating MRCR assuming the convenience yield follows the mean-reverting process. When applied to valuate the MRCR of a coalmine, this model gives higher values than the one-factor model and the NPV. This is because the increase of convenience yield can improve the executive opportunity of MRCR.
Modeling the Effects of Person Group Factors on Discrimination
Humphry, Stephen M.
2010-01-01
Discrimination has traditionally been parameterized for items but not other empirical factors. Consequently, if person factors affect discrimination they cause misfit. However, by explicitly formulating the relationship between discrimination and the unit of a metric, it is possible to parameterize discrimination for person groups. This article…
E-Learning and Social Media Motivation Factor Model
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…
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
Specialty choice preference of medical students according to personality traits by Five-Factor Model
National Research Council Canada - National Science Library
Oh Young Kwon; So Youn Park
2016-01-01
Purpose: The purpose of this study was to determine the relationship between personality traits, using the Five-Factor Model, and characteristics and motivational factors affecting specialty choice in Korean medical students. Methods...
Maximum Likelihood Dynamic Factor Modeling for Arbitrary "N" and "T" Using SEM
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…
Moore, Janette; Smith, Gillian W.; Shevlin, Mark; O'Neill, Francis A.
2010-01-01
An alternative models framework was used to test three confirmatory factor analytic models for the Short Leyton Obsessional Inventory-Children's Version (Short LOI-CV) in a general population sample of 517 young adolescent twins (11-16 years). A one-factor model as implicit in current classification systems of Obsessive-Compulsive Disorder (OCD),…
A note on the long rate in factor models of the term structure
de Kort, Jan
2017-01-01
In this paper, we consider factor models of the term structure based on a Brownian filtration. We show that the existence of a nondeterministic long rate in a factor model of the term structure implies, as a consequence of the Dybvig–Ingersoll–Ross theorem, that the model has an equivalent
Moore, Janette; Smith, Gillian W.; Shevlin, Mark; O'Neill, Francis A.
2010-01-01
An alternative models framework was used to test three confirmatory factor analytic models for the Short Leyton Obsessional Inventory-Children's Version (Short LOI-CV) in a general population sample of 517 young adolescent twins (11-16 years). A one-factor model as implicit in current classification systems of Obsessive-Compulsive Disorder (OCD),…
Galkin, A A
2012-01-01
On the basis of graphic models of the human response to environmental factors, two main types of complex quantitative influence as well as interrelation between determined effects at the level of an individual, and stochastic effects on population were revealed. Two main kinds of factors have been suggested to be distinguished. They are essential factors and accidental factors. The essential factors are common for environment. The accidental factors are foreign for environment. The above two kinds are different in approaches of hygienic standardization Accidental factors need a dot-like approach, whereas a two-level range approach is suitable for the essential factors.
Chiu, Weisheng; Rodriguez, Fernando M; Won, Doyeon
2016-10-01
This study examines the factor structure of the shortened version of the Leadership Scale for Sport, through a survey of 201 collegiate swimmers at National Collegiate Athletic Association Division II and III institutions, using both exploratory structural equation modeling and confirmatory factor analysis. Both exploratory structural equation modeling and confirmatory factor analysis showed that a five-factor solution fit the data adequately. The sizes of factor loadings on target factors substantially differed between the confirmatory factor analysis and exploratory structural equation modeling solutions. In addition, the inter-correlations between factors of the Leadership Scale for Sport and the correlations with athletes' satisfaction were found to be inflated in the confirmatory factor analysis solution. Overall, the findings provide evidence of the factorial validity of the shortened Leadership Scale for Sport.
Aleem, Majid; Islam, Md. Shariful
2009-01-01
Individual level factors related to the successor have a central role to play in the succession process of the business. When these factors are viewed in relation to succession planning models, these factors have a direct relation to the succession models in terms of success or failure of the succession process. The major contributing factor to the success or failure of the succession process is that of the leadership provided to the organization by the predecessor. These leadership qualities...
Modeling Individual Subtests of the WAIS IV with Multiple Latent Factors
2013-01-01
Performance on a cognitive test can be viewed either as measuring a unitary function or as reflecting the operation of multiple factors. Individual subtests in batteries designed to measure human abilities are commonly modeled as a single latent factor. Several latent factors are then used to model groups of subtests. However these latent factors are not independent as they are related through hierarchical or oblique structures. As a result, the simple structure of subtest performance results...
Environmental factors in breast cancer invasion: a mathematical modelling review.
Simmons, Alex; Burrage, Pamela M; Nicolau, Dan V; Lakhani, Sunil R; Burrage, Kevin
2017-02-01
This review presents a brief overview of breast cancer, focussing on its heterogeneity and the role of mathematical modelling and simulation in teasing apart the underlying biophysical processes. Following a brief overview of the main known pathophysiological features of ductal carcinoma, attention is paid to differential equation-based models (both deterministic and stochastic), agent-based modelling, multi-scale modelling, lattice-based models and image-driven modelling. A number of vignettes are presented where these modelling approaches have elucidated novel aspects of breast cancer dynamics, and we conclude by offering some perspectives on the role mathematical modelling can play in understanding breast cancer development, invasion and treatment therapies. Copyright © 2016 Royal College of Pathologists of Australasia. Published by Elsevier B.V. All rights reserved.
Conceptual model for assessment of inhalation exposure: Defining modifying factors
Tielemans, E.; Schneider, T.; Goede, H.; Tischer, M.; Warren, N.; Kromhout, H.; Tongeren, M. van; Hemmen, J. van; Cherrie, J.W.
2008-01-01
The present paper proposes a source-receptor model to schematically describe inhalation exposure to help understand the complex processes leading to inhalation of hazardous substances. The model considers a stepwise transfer of a contaminant from the source to the receptor. The conceptual model is c
Varactor Modelling for Power Factor Correction in a Varying Load
Directory of Open Access Journals (Sweden)
Agwu D. D.
2016-06-01
Full Text Available : For efficient system operation, it is desirable to keep the power factor at, or very close to unity. One of the very often used methods is application of suitable power factor correction technology. Capacitors are good candidate for constant load power factor correction due to suitability and cost effectiveness. However for varying loads, synchronous condensers are preferred despite having high initial cost as a result of their being able to supply varying leading or lagging reactive power; according to their field excitation. Due to the high acquisition and operation cost of synchronous condensers, this paper presents varactors as a possible alternative for power factor correction. These are diodes that vary their capacitances and leading reactive power according to supply voltage. Applying this involves looking at variation of power factor with supply voltage; and the option of aggregating and harnessing the junction capacitance of varactors for power factor correction of varying loads at low voltage AC levels. This innovation may lead to great improvement in distribution systems requiring quality power supply
Novel oscillator model with damping factor for plasmon induced transparency in waveguide systems.
Zhao, Mingzhuo; Li, Hongjian; He, Zhihui; Chen, Zhiquan; Xu, Hui; Zheng, Mingfei
2017-09-06
We introduce a novel two-oscillator model with damping factor to describe the plasmon induced transparency (PIT) in a bright-dark model plasmonic waveguide system. The damping factor γ in the model can be calculated from metal conductor damping factor γ c and dielectric damping factor γ d . We investigate the influence of geometry parameters and damping factor γ on transmission spectra as well as slow-light effects in the plasmonic waveguide system. We can find an obvious PIT phenomenon and realize a considerable slow-light effect in the double-cavities system. This work may provide guidance for optical switching and plasmon-based information processing.
Moderating Factors of Video-Modeling with Other as Model: A Meta-Analysis of Single-Case Studies
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…
Moderating Factors of Video-Modeling with Other as Model: A Meta-Analysis of Single-Case Studies
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…
Roesch, Scott C.; Aldridge, Arianna A.; Stocking, Stephanie N.; Villodas, Feion; Leung, Queenie; Bartley, Carrie E.; Black, Lisa J.
2010-01-01
This study used multilevel modeling of daily diary data to model within-person (state) and between-person (trait) components of coping variables. This application included the introduction of multilevel factor analysis (MFA) and a comparison of the predictive ability of these trait/state factors. Daily diary data were collected on a large (n =…
A latent profile analysis of the Five Factor Model of personality: Modeling trait interactions.
Merz, Erin L; Roesch, Scott C
2011-12-01
Interactions among the dimensions of the Five Factor Model (FFM) have not typically been evaluated in mental health research, with the extant literature focusing on bivariate relationships with psychological constructs of interest. This study used latent profile analysis to mimic higher-order interactions to identify homogenous personality profiles using the FFM, and also examined relationships between resultant profiles and affect, self-esteem, depression, anxiety, and coping efficacy. Participants (N = 371) completed self-report and daily diary questionnaires. A 3-profile solution provided the best fit to the data; the profiles were characterized as well-adjusted, reserved, and excitable. The well-adjusted group reported better psychological functioning in validation analyses. The reserved and excitable groups differed on anxiety, with the excitable group reporting generally higher anxiety than the reserved group. Latent profile analysis may be a parsimonious way to model personality heterogeneity.
Exploring key factors in online shopping with a hybrid model.
Chen, Hsiao-Ming; Wu, Chia-Huei; Tsai, Sang-Bing; Yu, Jian; Wang, Jiangtao; Zheng, Yuxiang
2016-01-01
Nowadays, the web increasingly influences retail sales. An in-depth analysis of consumer decision-making in the context of e-business has become an important issue for internet vendors. However, factors affecting e-business are complicated and intertwined. To stimulate online sales, understanding key influential factors and causal relationships among the factors is important. To gain more insights into this issue, this paper introduces a hybrid method, which combines the Decision Making Trial and Evaluation Laboratory (DEMATEL) with the analytic network process, called DANP method, to find out the driving factors that influence the online business mostly. By DEMATEL approach the causal graph showed that "online service" dimension has the highest degree of direct impact on other dimensions; thus, the internet vendor is suggested to made strong efforts on service quality throughout the online shopping process. In addition, the study adopted DANP to measure the importance of key factors, among which "transaction security" proves to be the most important criterion. Hence, transaction security should be treated with top priority to boost the online businesses. From our study with DANP approach, the comprehensive information can be visually detected so that the decision makers can spotlight on the root causes to develop effectual actions.
Assessment of scaling factor in modified dendrite growth model
Institute of Scientific and Technical Information of China (English)
张瑞丰; 沈宁福; 曹文博
2002-01-01
A model for dendrite growth during rapid solidification was established on the basis of BCT model and marginal stability criterion through modified Peclet numbers. Taking into account the interaction of diffusion fields, including solute diffusion field and thermal diffusion field around the dendrite tip, the model obtain a satisfactory results to predict the dendrite velocity and the tip radius, which agrees well with the experimental data from references in Cu-Ni alloy.
Deng, Chaosheng; Wu, Dawen; Yang, Minxia; Chen, Yunfei; Wang, Caiyun; Zhong, Zhanghua; Lian, Ningfang; Chen, Hua; Wu, Shuang
2016-11-01
Few reports have examined tissue factor (TF) and forkhead box transcription factor O-1 (FoxO1) expression in chronic thromboembolic pulmonary hypertension (CTEPH) animal models. To investigate the role of TF and FoxO1 and their interactions during CTEPH pathogenesis in a rat model. Autologous blood clots were repeatedly injected into the pulmonary arteries through right jugular vein to induce a rat model of CTEPH. Hemodynamic parameters, histopathology, and TF and FoxO1expression levels were detected. The mean pulmonary arterial pressure (mPAP), pulmonary vascular resistance and vessel wall area/total area (WA/TA) ratio in the experiment group increased significantly than sham group (P model of CTEPH can be successfully established by the injection of autologous blood clots into the pulmonary artery. TF and FoxO1 may play a key role in vascular remodeling during CTEPH pathogenesis.
Directory of Open Access Journals (Sweden)
Joris Mulder
2012-01-01
Full Text Available This paper discusses a Fortran 90 program referred to asBIEMS (Bayesian inequality and equality constrained model selection that can be used for calculating Bayes factors of multivariate normal linear models with equality and/or inequality constraints betweenthe model parameters versus a model containing no constraints, which is referred to as the unconstrained model. The prior that is used under the unconstrained model is the conjugate expected-constrained posterior prior and the prior under the constrained model is proportional to the unconstrained prior truncated in the constrained space. This results in Bayes factors that appropriately balance between model t and complexity for a broad class of constrained models. When the set of equality and/or inequality constraints in the model represents a hypothesis that applied researchers have in, for instance, (MAN(COVA, (multivariate regression, or repeated measurements, the obtained Bayes factor can be used to determine how much evidence is provided by the data in favor of the hypothesis in comparison to the unconstrained model. If several hypotheses are underinvestigation, the Bayes factors between the constrained models can be calculated using the obtained Bayes factors from BIEMS. Furthermore, posterior model probabilities of constrained models are provided which allows the user to compare the models directlywith each other.
Human Factors of Queuing: A Library Circulation Model.
Mansfield, Jerry W.
1981-01-01
Classical queuing theories and their accompanying service facilities totally disregard the human factors in the name of efficiency. As library managers we need to be more responsive to human needs in the design of service points and make every effort to minimize queuing and queue frustration. Five references are listed. (Author/RAA)
A MATHEMATICAL MODEL FOR ASSESSING THE FACTORING ACTIVITY
Directory of Open Access Journals (Sweden)
Madalina Radoi
2013-11-01
Full Text Available Originally–being over 4,000 years old–factoring was first used in the fertile territory of old Mesopotamia at a time when the famous Code of Hammurabi was drawn up. However, many years passed until the British colonists started to use it on a large scale at a time when the metropolis would pay them sums of money for the merchandise that colonists sent to the old continent until they collected the invoices.In Romania factoring started to play a major role in financial operations for it led to the increase of liquidities on the market.According to the Romanian legislation, factoring is a contract concluded between a party known as “the client”, which supplies merchandise or provides services, and a banking institution or specialized financial institution known as “the factor”, whereby the latter ensures the financing source, collects the receivables and protects credit risks, while the client assigns to the factor the receivables resulting from the sale of goods or the provision of services to third parties.
A Comparison of Imputation Methods for Bayesian Factor Analysis Models
Merkle, Edgar C.
2011-01-01
Imputation methods are popular for the handling of missing data in psychology. The methods generally consist of predicting missing data based on observed data, yielding a complete data set that is amiable to standard statistical analyses. In the context of Bayesian factor analysis, this article compares imputation under an unrestricted…
Wang, Zhe; Li, Lizhi; Ni, Weidou; Li, Zheng
2010-01-01
This paper presents a new approach of applying partial least squares method combined with a physical principle based dominant factor. The characteristic line intensity of the specific element was taken to build up the dominant factor to reflect the major elemental concentration and partial least squares (PLS) approach was then applied to further improve the model accuracy. The deviation evolution of characteristic line intensity from the ideal condition was depicted and according to the deviation understanding, efforts were taken to model the non-linear self-absorption and inter-element interference effects to improve the accuracy of dominant factor model. With a dominant factor to carry the main quantitative information, the novel multivariate model combines advantages of both the conventional univariate and PLS models and partially avoids the overuse of the unrelated noise in the spectrum for PLS application. The dominant factor makes the combination model more robust over a wide concentration range and PLS...
The search for a new model structure of β-Factor XIIa
Henriques, Elsa S.; Floriano, Welly B.; Reuter, Nathalie; Melo, André; Brown, David; Gomes, José A. N. F.; Maigret, Bernard; Nascimento, Marco A. C.; Ramos, Maria João
2001-04-01
We present the search for a new model of β-factor XIIa, a blood coagulation enzyme, with an unknown experimental 3D-structure. We decided to build not one but three different models using different homologous proteins as well as different techniques and different modellers. Additional studies, including extensive molecular dynamics simulations on the solvated state, allowed us to draw several conclusions concerning homology modelling, in general, and β-factor XIIa, in particular.
While short-term studies demonstrate consistent effects of dietary protein, fiber, glycemic index and energy density on energy intake, long-term effectiveness trials typically indicate small or non-significant effects of these dietary factors on long-term weight change. In consequence, most lifestyl...
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.
Saengprom, Narumon; Erawan, Waraporn; Damrongpanit, Suntonrapot; Sakulku, Jaruwan
2015-01-01
The purposes of this study were 1) Compare analytical thinking ability by testing the same sets of students 5 times 2) Develop and verify whether analytical thinking ability of students corresponds to second-order growth curve factors model. Samples were 1,093 eighth-grade students. The results revealed that 1) Analytical thinking ability scores…
Saengprom, Narumon; Erawan, Waraporn; Damrongpanit, Suntonrapot; Sakulku, Jaruwan
2015-01-01
The purposes of this study were 1) Compare analytical thinking ability by testing the same sets of students 5 times 2) Develop and verify whether analytical thinking ability of students corresponds to second-order growth curve factors model. Samples were 1,093 eighth-grade students. The results revealed that 1) Analytical thinking ability scores…
Support for the 7-factor hybrid model of PTSD in a community sample.
Seligowski, Antonia V; Orcutt, Holly K
2016-03-01
Research suggests that 4-factor models of posttraumatic stress disorder (PTSD) may be improved upon by the addition of novel factors, such as Dysphoric Arousal, Externalizing Behaviors, and Anhedonia. However, a novel 7-factor hybrid model has demonstrated superior fit in veteran and undergraduate samples. The current study sought to replicate this finding in a trauma-exposed community sample and examined relations with positive (PA) and negative affect (NA). Participants included 403 adults (M(age) = 37.75) recruited through Amazon's MTurk. PTSD was measured using the PTSD Checklist-5 (PCL-5). Confirmatory factor analyses were conducted in Mplus. The 7-factor hybrid model demonstrated good fit: CFI = .96, TLI = .95, RMSEA = .06 (90% CI [.05, .07]), SRMR = .03. This model was superior to the 5- and 6-factor models. All factors demonstrated significant relations with PA and NA, the largest of which were the Externalizing Behaviors (with NA) and Anhedonia (with PA) factors. Results provide support for the 7-factor hybrid model of PTSD using the PCL-5 in a community sample. Findings replicate previous research suggesting that PTSD is highly related to NA, which has been purported as an underlying dimension of PTSD. It is recommended that future research use clinical measures to further examine the hybrid model. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Adaptation of a 3-factor model for the Pittsburgh Sleep Quality Index in Portuguese older adults.
Becker, Nathália Brandolim; de Neves Jesus, Saul
2017-05-01
The present study examined the factor structure of the Pittsburgh Sleep Quality Index (PSQI) in a sample of older Portuguese adults using a cross-validation approach. Design is a cross-sectional. A convenience sample of 204 community-dwelling older adults (M=70.05, SD=7.15) were included. The global sleep quality (GSQ) score ranged from 0 to 18 with a mean of 5.98 (SD±3.45). The distribution showed that gender and perception of oneself as healthy influences GSQ in this sample. Cronbach's α was 0.69, but increased to 0.70 if the "use of sleep medication" component was deleted. Exploratory factor analysis (EFA) demonstrated two factor model is better than one factor, and a model fit with good indices (chi-square=8.649, df=8, p=0.373). Confirmatory factor analysis (CFA) was performed on the single factor, two factor, and three factor models, with and without the "use of sleep medications" component. The best model was the 3-factor model without the "use of sleep medications" component (chi-square=1.214, df=6, GFI=0.997, AGFI=0.918, CFI=0.986, RMSEA=0.046). The adaptation of the model is similar to the original model, with the only change being the exclusion of the "use of medications to sleep" component. We suggest using that component as a complementary qualitative assessment of health. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.
Factor Analysis of Drawings: Application to College Student Models of the Greenhouse Effect
Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel
2015-01-01
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,…
Realized mixed-frequency factor models for vast dimensional covariance estimation
K. Bannouh (Karim); M.P.E. Martens (Martin); R.C.A. Oomen (Roel); D.J.C. van Dijk (Dick)
2012-01-01
textabstractWe introduce a Mixed-Frequency Factor Model (MFFM) to estimate vast dimensional covari- ance matrices of asset returns. The MFFM uses high-frequency (intraday) data to estimate factor (co)variances and idiosyncratic risk and low-frequency (daily) data to estimate the factor loadings. We
Directory of Open Access Journals (Sweden)
Smederevac Snežana
2006-01-01
Full Text Available The main aim of this study is to estimate the heritability of AFFM and PEN dimensions, including 67 pairs of twins (34 monozygotic and 33 dizygotic of both genders, aged 18 - 44. The heritability has been estimated by the biometric method, two full (ACE and ADE and three reduced (AE, DE and CE models tested for each personality trait. Taking into consideration the AFFM dimensions, additive genetic factors and a non-shared environment contribute the most significantly to the phenotypic variation of activity, sociability and the impulsive sensation seeking; anxiety and aggressiveness are best accounted for by the dominant genetic effects. In the PEN domain, fit indicators suggest that ACE and the reduced AE models provide the best explanation for the phenotypic manifestations of neuroticism, while ACE and CE models account for the variation of L scale. Although the fit indicators calculated for extraversion and psychotic behavior are somewhat problematic, the parameter estimates show that extraversion is best accounted for by the additive genetic variance, shared environmental effects, and the non-shared environment, whereas psychotic behavior is the most adequately explained by both shared and non-shared environmental effects.
Reputation Model with Forgiveness Factor for Semi-Competitive E-Business Agent Societies
Radu Burete; Amelia Badica; Costin Badica
2010-01-01
In this paper we introduce a new reputation model for agents engaged in e-business transactions. Our model enhances classic reputation models by adding forgiveness factor and new sources of reputation information based on agents groups. The model was implemented using JADE multi-agent platform and initially evaluated for e-business scenarios comprising societies of buyer and seller agents.
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...... is then applied to the Nord Pool power market for the analysis of price comovements among different regions within the power grid. We find that the global factor can be interpreted as the system price of the power grid as well as a fractional cointegration relationship between prices and the global factor....
Scale Factor Study for 1:30 Local Scour Model
2016-08-01
Sedimentation engineering : ASCE manuals and reports on engineering practice, No. 54. Reston, VA: American Society of Civil Engineers ...Jeremy A. Sharp, Ronald E. Heath, Howard E. Park, and Tate O. McAlpin PURPOSE: This Coastal and Hydraulics Engineering Technical Note (CHETN... Engineer Research and Development Center, Vicksburg, MS. ERDC/CHL CHETN-VII-15 August 2016 8 For implementation, the scale factor was applied to the
Game Factors and Game-Based Learning Design Model
Yen-Ru Shi; Ju-Ling Shih
2015-01-01
How to design useful digital game-based learning is a topic worthy of discussion. Past research focused on specific game genres design, but it is difficult to use when the target game genre differs from the default genres used in the research. This study presents macrodesign concepts that elucidates 11 crucial game-design factors, including game goals, game mechanism, game fantasy, game value, interaction, freedom, narrative, sensation, challenges, sociality, and mystery. We clearly define ea...
Using a knowledge elicitation method to specify the business model of a human factors organization
Schraagen, J.M.C.; Ven, J. van de; Hoffman, R.R.; Moon, B.M.
2009-01-01
Concept Mapping was used to structure knowledge elicitation interviews with a group of human factors specialists whose goal was to describe the business model of their Department. This novel use of cognitive task analysis to describe the business model of a human factors organization resulted in a n
The effects of motivational factors on car use : a multidisciplinary modelling approach
Steg, L; Geurs, K; Ras, M
2001-01-01
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 mo
Using a knowledge elicitation method to specify the business model of a human factors organization
Schraagen, J.M.C.; Ven, J. van de; Hoffman, R.R.; Moon, B.M.
2009-01-01
Concept Mapping was used to structure knowledge elicitation interviews with a group of human factors specialists whose goal was to describe the business model of their Department. This novel use of cognitive task analysis to describe the business model of a human factors organization resulted in a n
Using a knowledge elicitation method to specify the business model of a human factors organization.
Schraagen, Johannes Martinus Cornelis; van de Ven, Josine; Hoffman, Robert R.; Moon, Brian M.
2009-01-01
Concept Mapping was used to structure knowledge elicitation interviews with a group of human factors specialists whose goal was to describe the business model of their Department. This novel use of cognitive task analysis to describe the business model of a human factors organization resulted in a n
The Manifest Association Structure of the Single-Factor Model: Insights from Partial Correlations
Salgueiro, Maria de Fatima; Smith, Peter W. F.; McDonald, John W.
2008-01-01
The association structure between manifest variables arising from the single-factor model is investigated using partial correlations. The additional insights to the practitioner provided by partial correlations for detecting a single-factor model are discussed. The parameter space for the partial correlations is presented, as are the patterns of…
Joris Mulder; Herbert Hoijtink; Christiaan de Leeuw
2012-01-01
This paper discusses a Fortran 90 program referred to as BIEMS (Bayesian inequality and equality constrained model selection) that can be used for calculating Bayes factors of multivariate normal linear models with equality and/or inequality constraints between the model parameters versus a model containing no constraints, which is referred to as the unconstrained model. The prior that is used under the unconstrained model is the conjugate expected-constrained posterior prior and the prior un...
Form factors of the monodromy matrix entries in gl(2|1)-invariant integrable models
Hutsalyuk, A; Pakuliak, S Z; Ragoucy, E; Slavnov, N A
2016-01-01
We study integrable models solvable by the nested algebraic Bethe ansatz and described by $\\mathfrak{gl}(2|1)$ or $\\mathfrak{gl}(1|2)$ superalgebras. We obtain explicit determinant representations for form factors of the monodromy matrix entries. We show that all form factors are related to each other at special limits of the Bethe parameters. Our results allow one to obtain determinant formulas for form factors of local operators in the supersymmetric t-J model.
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.
Form factors of the monodromy matrix entries in gl (2 | 1)-invariant integrable models
Hutsalyuk, A.; Liashyk, A.; Pakuliak, S. Z.; Ragoucy, E.; Slavnov, N. A.
2016-10-01
We study integrable models solvable by the nested algebraic Bethe ansatz and described by gl (2 | 1) or gl (1 | 2) superalgebras. We obtain explicit determinant representations for form factors of the monodromy matrix entries. We show that all form factors are related to each other at special limits of the Bethe parameters. Our results allow one to obtain determinant formulas for form factors of local operators in the supersymmetric t- J model.
A structural dynamic factor model for the effects of monetary policy estimated by the EM algorithm
DEFF Research Database (Denmark)
Bork, Lasse
This paper applies the maximum likelihood based EM algorithm to a large-dimensional factor analysis of US monetary policy. Specifically, economy-wide effects of shocks to the US federal funds rate are estimated in a structural dynamic factor model in which 100+ US macroeconomic and financial time...... series are driven by the joint dynamics of the federal funds rate and a few correlated dynamic factors. This paper contains a number of methodological contributions to the existing literature on data-rich monetary policy analysis. Firstly, the identification scheme allows for correlated factor dynamics...... as opposed to the orthogonal factors resulting from the popular principal component approach to structural factor models. Correlated factors are economically more sensible and important for a richer monetary policy transmission mechanism. Secondly, I consider both static factor loadings as well as dynamic...
A structural dynamic factor model for the effects of monetary policy estimated by the EM algorithm
DEFF Research Database (Denmark)
Bork, Lasse
This paper applies the maximum likelihood based EM algorithm to a large-dimensional factor analysis of US monetary policy. Specifically, economy-wide effects of shocks to the US federal funds rate are estimated in a structural dynamic factor model in which 100+ US macroeconomic and financial time...... series are driven by the joint dynamics of the federal funds rate and a few correlated dynamic factors. This paper contains a number of methodological contributions to the existing literature on data-rich monetary policy analysis. Firstly, the identification scheme allows for correlated factor dynamics...... as opposed to the orthogonal factors resulting from the popular principal component approach to structural factor models. Correlated factors are economically more sensible and important for a richer monetary policy transmission mechanism. Secondly, I consider both static factor loadings as well as dynamic...
Design of Experiments for Factor Hierarchization in Complex Structure Modelling
Directory of Open Access Journals (Sweden)
C. Kasmi
2013-07-01
Full Text Available Modelling the power-grid network is of fundamental interest to analyse the conducted propagation of unintentional and intentional electromagnetic interferences. The propagation is indeed highly influenced by the channel behaviour. In this paper, we investigate the effects of appliances and the position of cables in a low voltage network. First, the power-grid architecture is described. Then, the principle of Experimental Design is recalled. Next, the methodology is applied to power-grid modelling. Finally, we propose an analysis of the statistical moments of the experimental design results. Several outcomes are provided to describe the effects induced by parameter variability on the conducted propagation of spurious compromising emanations.
Higher-order factors of the big five model of personality: a reanalysis of Digman (1997).
Mutch, Christopher
2005-02-01
Based on the results from factor analyses conducted on 14 different data sets, Digman proposed a model of two higher-order factors, or metatraits, that subsumed the Big Five personality traits. In the current article, problems in Digman's analyses were explicated, and more appropriate analyses were then conducted using the same 14 correlation matrices from Digman's study. The resultant two-factor model produced improper solutions, poor model fit indices, or both, in almost all of the 14 data sets and thus raised serious doubts about the veracity of Digman's proposed model.
Components of Mathematics Anxiety: Factor modelling of the MARS30-brief
Directory of Open Access Journals (Sweden)
Belinda ePletzer
2016-02-01
Full Text Available Mathematics anxiety involves feelings of tension, discomfort, high arousal and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study.The Mathematics Anxiety Rating Scale (MARS is a reliable measure of mathematics anxiety (Richardson & Suinn, 1972, for which several reduced forms have been developed. Most recently, a shortened version of the MARS (MARS30-brief with comparable reliability was published. Different studies suggest that mathematics anxiety involves up to seven different factors. Here we examined the factor structure of the MARS30-brief by means of confirmatory factor analysis. The best model fit was obtained by a six-factor model, dismembering the known two general factors Mathematical Test Anxiety (MTA and Numerical Anxiety (NA in 3 factors each. However, a more parsimonious 5-factor model with 2 sub-factors for MTA and 3 for NA fitted the data comparably well. Factors were differentially susceptible to sex differences and differences between majors. Measurement Invariance for sex was established.
Components of Mathematics Anxiety: Factor Modeling of the MARS30-Brief.
Pletzer, Belinda; Wood, Guilherme; Scherndl, Thomas; Kerschbaum, Hubert H; Nuerk, Hans-Christoph
2016-01-01
Mathematics anxiety involves feelings of tension, discomfort, high arousal, and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study. The Mathematics Anxiety Rating Scale (MARS) is a reliable measure of mathematics anxiety (Richardson and Suinn, 1972), for which several reduced forms have been developed. Most recently, a shortened version of the MARS (MARS30-brief) with comparable reliability was published. Different studies suggest that mathematics anxiety involves up to seven different factors. Here we examined the factor structure of the MARS30-brief by means of confirmatory factor analysis. The best model fit was obtained by a six-factor model, dismembering the known two general factors "Mathematical Test Anxiety" (MTA) and "Numerical Anxiety" (NA) in three factors each. However, a more parsimonious 5-factor model with two sub-factors for MTA and three for NA fitted the data comparably well. Factors were differentially susceptible to sex differences and differences between majors. Measurement invariance for sex was established.
A Mathematical Model on Employment versus Several Factors in Macedonia
Shpresa Syla; Sadri Alija
2013-01-01
In this study is made an attempt to analyze the conjunction of several indicators on the employment of citizens in the Republic of Macedonia. In this regard the logistic regression and odds ratios were used in order to see how certain factors such as gender, age, ethnicity, education, area of residence and the number of family members affect employment at citizens. This study is based on data from a survey organized by the Center for Economic Analyses in December 2011, by 400 citizens of the ...
Efficient sampling of Gaussian graphical models using conditional Bayes factors
Hinne, M.; Lenkoski, A.; Heskes, T.M.; Gerven, M.A.J. van
2014-01-01
Bayesian estimation of Gaussian graphical models has proven to be challenging because the conjugate prior distribution on the Gaussian precision matrix, the G-Wishart distribution, has a doubly intractable partition function. Recent developments provide a direct way to sample from the G-Wishart
A holistic model of advocacy: factors that influence its use.
Kubsch, Sylvia M; Sternard, Marsha J; Hovarter, Rebecca; Matzke, Vicki
2004-02-01
Although advocacy is embraced by nursing as an essential component of holistic philosophy, its scope is often limited in practice. In this article, a research study that examined the use of an expanded definition of advocacy is described. A link to the role of advocacy as a complementary therapy and in relation to facilitating the use of complementary therapies by patients is provided. Fifty-two registered nurses completed a researcher developed advocacy research instrument that assessed the use of moral-ethical, legal, political, spiritual, and substitutive advocacy along with various factors thought to influence the use of advocacy including moral development, perceived assertiveness, and perceived job security. An additional 40 RN-BSN students generated case studies of advocacy enacted in practice that were used as examples of the five categories of advocacy and to support the findings of the survey. Results indicated that moral-ethical advocacy was used more often than the other four categories. Moral stage development had a significant effect on substitutive advocacy but assertiveness and job security were not significant factors influencing any category of advocacy.
Cholesterol, Triglycerides, and the Five-Factor Model of Personality
Sutin, Angelina R.; Terracciano, Antonio; Deiana, Barbara; Uda, Manuela; Schlessinger, David; Lakatta, Edward G.; Costa, Paul T.
2010-01-01
Unhealthy lipid levels are among the leading controllable risk factors for coronary heart disease. To identify the psychological factors associated with dyslipidemia, this study investigates the personality correlates of cholesterol (total, LDL, and HDL) and triglycerides. A community-based sample (N=5,532) from Sardinia, Italy, had their cholesterol and triglyceride levels assessed and completed a comprehensive personality questionnaire, the NEO-PI-R. All analyses controlled for age, sex, BMI, smoking, drinking, hypertension, and diabetes. Low Conscientiousness and traits related to impulsivity were associated with lower HDL cholesterol and higher triglycerides. Compared to the lowest 10%, those who scored in top 10% on Impulsivity had a 2.5 times greater risk of exceeding the clinical threshold for elevated triglycerides (OR=2.51, CI=1.56–4.07). In addition, sex moderated the association between trait depression (a component of Neuroticism) and HDL cholesterol, such that trait depression was associated with lower levels of HDL cholesterol in women but not men. When considering the connection between personality and health, unhealthy lipid profiles may be one intermediate biomarker between personality and morbidity and mortality. PMID:20109519
A Multidimensional Nonnegative Matrix Factorization Model for Retweeting Behavior Prediction
Directory of Open Access Journals (Sweden)
Mengmeng Wang
2015-01-01
Full Text Available Today microblogging has increasingly become a means of information diffusion via user’s retweeting behavior. As a consequence, exploring on retweeting behavior is a better way to understand microblog’s transmissibility in the network. Hence, targeted at online microblogging, a directed social network, along with user-based features, this paper first built content-based features, which consisted of URL, hashtag, emotion difference, and interest similarity, based on time series of text information that user posts. And then we measure relationship-based factor in social network according to frequency of interactions and network structure which blend with temporal information. Finally, we utilize nonnegative matrix factorization to predict user’s retweeting behavior from user-based dimension and content-based dimension, respectively, by employing strength of social relationship to constrain objective function. The results suggest that our proposed method effectively increases retweeting behavior prediction accuracy and provides a new train of thought for retweeting behavior prediction in dynamic social networks.
Cholesterol, triglycerides, and the Five-Factor Model of personality.
Sutin, Angelina R; Terracciano, Antonio; Deiana, Barbara; Uda, Manuela; Schlessinger, David; Lakatta, Edward G; Costa, Paul T
2010-05-01
Unhealthy lipid levels are among the leading controllable risk factors for coronary heart disease. To identify the psychological factors associated with dyslipidemia, this study investigates the personality correlates of cholesterol (total, LDL, and HDL) and triglycerides. A community-based sample (N=5532) from Sardinia, Italy, had their cholesterol and triglyceride levels assessed and completed a comprehensive personality questionnaire, the NEO-PI-R. All analyses controlled for age, sex, BMI, smoking, drinking, hypertension, and diabetes. Low Conscientiousness and traits related to impulsivity were associated with lower HDL cholesterol and higher triglycerides. Compared to the lowest 10%, those who scored in top 10% on Impulsivity had a 2.5 times greater risk of exceeding the clinical threshold for elevated triglycerides (OR=2.51, CI=1.56-4.07). In addition, sex moderated the association between trait depression (a component of Neuroticism) and HDL cholesterol, such that trait depression was associated with lower levels of HDL cholesterol in women but not men. When considering the connection between personality and health, unhealthy lipid profiles may be one intermediate biomarker between personality and morbidity and mortality. Published by Elsevier B.V.
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.
Geiser, Christian; Bishop, Jacob; Lockhart, Ginger
2015-01-01
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) vs. 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. PMID:26283977
Pernot, Pascal
2009-01-01
Bayesian Model Calibration is used to revisit the problem of scaling factor calibration for semi-empirical correction of ab initio calculations. A particular attention is devoted to uncertainty evaluation for scaling factors, and to their effect on prediction of observables involving scaled properties. We argue that linear models used for calibration of scaling factors are generally not statistically valid, in the sense that they are not able to fit calibration data within their uncertainty limits. Uncertainty evaluation and uncertainty propagation by statistical methods from such invalid models are doomed to failure. To relieve this problem, a stochastic function is included in the model to account for model inadequacy, according to the Bayesian Model Calibration approach. In this framework, we demonstrate that standard calibration summary statistics, as optimal scaling factor and root mean square, can be safely used for uncertainty propagation only when large calibration sets of precise data are used. For s...
Parent Ratings of the Strengths and Difficulties Questionnaire: What Is the Optimum Factor Model?
Gomez, Rapson; Stavropoulos, Vasilis
2017-07-01
To date, at least 12 different models have been suggested for the Strengths and Difficulties Questionnaire (SDQ). The current study used confirmatory factor analysis to examine the relative support for these models. In all, 1,407 Malaysian parents completed SDQ ratings of their children (age range = 5-13 years). Although the findings showed some degree of support for all 12 models, there was most support for an oblique six-factor model that included the five SDQ domains (emotional problems, conduct problems, hyperactivity, peer problems, and low prosocial behavior) and a positive construal factor comprising all the 10 SDQ positive worded items. The original proposed five-factor oblique model also showed good fit. The implications of the findings for understanding the results of past studies of the structural models of the parent version of the SDQ, and for clinical and research practice involving the SDQ are discussed.
Finding of Correction Factor and Dimensional Error in Bio-AM Model by FDM Technique
Manmadhachary, Aiamunoori; Ravi Kumar, Yennam; Krishnanand, Lanka
2016-06-01
Additive Manufacturing (AM) is the swift manufacturing process, in which input data can be provided from various sources like 3-Dimensional (3D) Computer Aided Design (CAD), Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and 3D scanner data. From the CT/MRI data can be manufacture Biomedical Additive Manufacturing (Bio-AM) models. The Bio-AM model gives a better lead on preplanning of oral and maxillofacial surgery. However manufacturing of the accurate Bio-AM model is one of the unsolved problems. The current paper demonstrates error between the Standard Triangle Language (STL) model to Bio-AM model of dry mandible and found correction factor in Bio-AM model with Fused Deposition Modelling (FDM) technique. In the present work dry mandible CT images are acquired by CT scanner and supplied into a 3D CAD model in the form of STL model. Further the data is sent to FDM machine for fabrication of Bio-AM model. The difference between Bio-AM to STL model dimensions is considered as dimensional error and the ratio of STL to Bio-AM model dimensions considered as a correction factor. This correction factor helps to fabricate the AM model with accurate dimensions of the patient anatomy. These true dimensional Bio-AM models increasing the safety and accuracy in pre-planning of oral and maxillofacial surgery. The correction factor for Dimension SST 768 FDM AM machine is 1.003 and dimensional error is limited to 0.3 %.
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.
Scrub Typhus Incidence Modeling with Meteorological Factors in South Korea
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Jaewon Kwak
2015-06-01
Full Text Available Since its recurrence in 1986, scrub typhus has been occurring annually and it is considered as one of the most prevalent diseases in Korea. Scrub typhus is a 3rd grade nationally notifiable disease that has greatly increased in Korea since 2000. The objective of this study is to construct a disease incidence model for prediction and quantification of the incidences of scrub typhus. Using data from 2001 to 2010, the incidence Artificial Neural Network (ANN model, which considers the time-lag between scrub typhus and minimum temperature, precipitation and average wind speed based on the Granger causality and spectral analysis, is constructed and tested for 2011 to 2012. Results show reliable simulation of scrub typhus incidences with selected predictors, and indicate that the seasonality in meteorological data should be considered.
Thinning factor distributions viewed through numerical models of continental extension
Svartman Dias, Anna Eliza; Hayman, Nicholas W.; Lavier, Luc L.
2016-12-01
A long-standing question surrounding rifted margins concerns how the observed fault-restored extension in the upper crust is usually less than that calculated from subsidence models or from crustal thickness estimates, the so-called "extension discrepancy." Here we revisit this issue drawing on recently completed numerical results. We extract thinning profiles from four end-member geodynamic model rifts with varying width and asymmetry and propose tectonic models that best explain those results. We then relate the spatial and temporal evolution of upper to lower crustal thinning, or crustal depth-dependent thinning (DDT), and crustal thinning to mantle thinning, or lithospheric DDT, which are difficult to achieve in natural systems due to the lack of observations that constrain thinning at different stages between prerift extension and lithospheric breakup. Our results support the hypothesis that crustal DDT cannot be the main cause of the extension discrepancy, which may be overestimated because of the difficulty in recognizing distributed deformation, and polyphase and detachment faulting in seismic data. More importantly, the results support that lithospheric DDT is likely to dominate at specific stages of rift evolution because crustal and mantle thinning distributions are not always spatially coincident and at times are not even balanced by an equal magnitude of thinning in two dimensions. Moreover, either pure or simple shear models can apply at various points of time and space depending on the type of rift. Both DDT and pure/simple shear variations across space and time can result in observed complex fault geometries, uplift/subsidence, and thermal histories.
Reciprocal burnout model: Interconnectedness of interpersonal and intrapersonal factors
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Andreja Pšeničny
2007-01-01
Full Text Available Burnout can be described as chronic state of extreme psychophysical and emotional exhaustion. Burning out is a stage process consisting of: the stage of exhaustion, the stage of captivity and the final stage – adrenal burnout. Adrenal burnout syndrome (ABS is the final stage of burning out process, resulting in a functional blocade of hypothalamic-pituitary-adrenal axis which causes secondary cortisol insufficiency. Even though they share similar symptoms, burnout and depression are two different types of disorder. They differ mainly in basic cortisol levels and self-esteem. Researchers tend to link the burnout syndrome and environmental stress (interpersonal causes. Recently, some of them found connection between burnout syndrome and personality traits (intrapersonal causes. Reciprocal burnout model links both causes. It shows that in the same circumstances only a few people suffer from adrenal burnout syndrome. It states that personal characteristics are one of the main causes why people suffering from burnout syndrome enroll in nonreciprocal personal and professional relations. Socialization process plays an important role in development of personality traits. The core of the reciprocal burnout model consists of one's attitude towards his or her basic needs' fulfillment, personal system of values, and correlation between fulfillment of basic needs (energy accumulation and burning out process (energy consumption. Reciprocal burnout model is opening a series of questions, concerning the connection between personality traits, life satisfaction and personal values, and burnout syndrome risk behavior, as well as the influence of whole life circumstances on burning out process.
A Mathematical Model on Employment versus Several Factors in Macedonia
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Shpresa Syla
2013-08-01
Full Text Available In this study is made an attempt to analyze the conjunction of several indicators on the employment of citizens in the Republic of Macedonia. In this regard the logistic regression and odds ratios were used in order to see how certain factors such as gender, age, ethnicity, education, area of residence and the number of family members affect employment at citizens. This study is based on data from a survey organized by the Center for Economic Analyses in December 2011, by 400 citizens of the Republic of Macedonia. Results show that young males of Macedonian nationality, those with higher education, ones that live on urban areas and the families that have greater number of members are more likely to be employed. For data processing is used software Med Calc.
A latent factor linear mixed model for high-dimensional longitudinal data analysis.
An, Xinming; Yang, Qing; Bentler, Peter M
2013-10-30
High-dimensional longitudinal data involving latent variables such as depression and anxiety that cannot be quantified directly are often encountered in biomedical and social sciences. Multiple responses are used to characterize these latent quantities, and repeated measures are collected to capture their trends over time. Furthermore, substantive research questions may concern issues such as interrelated trends among latent variables that can only be addressed by modeling them jointly. Although statistical analysis of univariate longitudinal data has been well developed, methods for modeling multivariate high-dimensional longitudinal data are still under development. In this paper, we propose a latent factor linear mixed model (LFLMM) for analyzing this type of data. This model is a combination of the factor analysis and multivariate linear mixed models. Under this modeling framework, we reduced the high-dimensional responses to low-dimensional latent factors by the factor analysis model, and then we used the multivariate linear mixed model to study the longitudinal trends of these latent factors. We developed an expectation-maximization algorithm to estimate the model. We used simulation studies to investigate the computational properties of the expectation-maximization algorithm and compare the LFLMM model with other approaches for high-dimensional longitudinal data analysis. We used a real data example to illustrate the practical usefulness of the model. Copyright © 2013 John Wiley & Sons, Ltd.
Disclosure Factors of Executive Managers Remuneration: A Probit Model
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Themistokles Lazarides
2010-01-01
Full Text Available Problem statement: The study contributes to the literature that argues that the convergence trend of corporate governance systems is either nominal or hasnt the impact that the advocates of this theory hypothesize. Approach: The objective of the study was to test this hypothesis the key issue of remuneration had been chosen to illustrate that the differences of corporate governance systems still exist and they have a substantial impact on business environment. Disclosure or not of information regarding these issues preoccupies regulating, legislative authorities as well as capital market participants. The study, using a probit regression analysis, examined whether these differences are observable in Greece. Greece is a country with the typical characteristics of a Continental Europe corporate governance system. The results were compared with the reported characteristics of Anglo- Saxon countries. The study analyzed data over a period of 6 years (2001-2006. The 60 firms largest, in terms of capitalization and free float, were used. Results: The major factors that affect the remuneration disclosure were the adoption of mergers and acquisitions as the method to expand firms size, the investments risks that the firm is willing to take, stock market capitalization, board of directors size, capital to sales ratio, number of independent board of directors member dismissals and the quality of corporate governance. These differences were significantly different than the ones reported for Anglo-Saxon countries. Conclusion: The study had proven that remuneration disclosure levels in Greece are defined by a different set of factors than the ones in a typical Anglo-Saxon country. Policy and regulation makers should take into account these differences and not adopt isomorphic approaches to different problems and situations.
Proneurogenic Ligands Defined by Modeling Developing Cortex Growth Factor Communication Networks.
Yuzwa, Scott A; Yang, Guang; Borrett, Michael J; Clarke, Geoff; Cancino, Gonzalo I; Zahr, Siraj K; Zandstra, Peter W; Kaplan, David R; Miller, Freda D
2016-09-01
The neural stem cell decision to self-renew or differentiate is tightly regulated by its microenvironment. Here, we have asked about this microenvironment, focusing on growth factors in the embryonic cortex at a time when it is largely comprised of neural precursor cells (NPCs) and newborn neurons. We show that cortical NPCs secrete factors that promote their maintenance, while cortical neurons secrete factors that promote differentiation. To define factors important for these activities, we used transcriptome profiling to identify ligands produced by NPCs and neurons, cell-surface mass spectrometry to identify receptors on these cells, and computational modeling to integrate these data. The resultant model predicts a complex growth factor environment with multiple autocrine and paracrine interactions. We tested this communication model, focusing on neurogenesis, and identified IFNγ, Neurturin (Nrtn), and glial-derived neurotrophic factor (GDNF) as ligands with unexpected roles in promoting neurogenic differentiation of NPCs in vivo.
Skyrme-Model $\\pi NN$ Form Factor and Nucleon-Nucleon Interaction
Holzwarth, G
1997-01-01
We apply the strong $\\pi NN$ 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 possible to use a soft pion form factor in the NN system. As a consequence, the $\\pi N$ and the $NN$ systems can be described using the same soft $\\pi NN$ form factor, which is impossible with the monopole.
Random matrix approach to estimation of high-dimensional factor models
Yeo, Joongyeub
2016-01-01
In dealing with high-dimensional data sets, factor models are often useful for dimension reduction. The estimation of factor models has been actively studied in various fields. In the first part of this paper, we present a new approach to estimate high-dimensional factor models, using the empirical spectral density of residuals. The spectrum of covariance matrices from financial data typically exhibits two characteristic aspects: a few spikes and bulk. The former represent factors that mainly drive the features and the latter arises from idiosyncratic noise. Motivated by these two aspects, we consider a minimum distance between two spectrums; one from a covariance structure model and the other from real residuals of financial data that are obtained by subtracting principal components. Our method simultaneously provides estimators of the number of factors and information about correlation structures in residuals. Using free random variable techniques, the proposed algorithm can be implemented and controlled ef...
Fong, Ted C T; Ho, Rainbow T H; Wan, Adrian H Y; Siu, Pantha Joey C Y; Au-Yeung, Friendly S W
2015-10-01
The Positive and Negative Syndrome Scale (PANSS) is widely used for clinical assessment of symptoms in schizophrenia. Instead of the traditional pyramidal model, recent literature supports the pentagonal model for the dimensionality of the PANSS. The present study aimed to validate the consensus five-factor model of the PANSS and evaluate its convergent validity. Participants were 146 Chinese chronic schizophrenic patients who completed diagnostic interviews and cognitive assessments. Exploratory structural equation modeling (ESEM) was performed to investigate the dimensionality of the PANSS. Covariates (age, sex, and education level) and concurrent outcomes (perceived stress, memory, daily living functions, and motor deficits) were added in the ESEM model. The results supported the consensus 5-factor underlying structure, which comprised 20 items categorized into positive, negative, excitement, depression, and cognitive factors with acceptable reliability (α=.69-.85) and strong factor loadings (λ=.41-.93). The five factors, especially the cognitive factor, showed evident convergent validity with the covariates and concurrent outcomes. The results support the consensus five-factor structure of the PANSS as a robust measure of symptoms in schizophrenia. Future studies could explore the clinical and practical utility of the consensus five-factor model. Copyright © 2015 Elsevier Inc. All rights reserved.
New JLS-Factor Model versus the Standard JLS Model: A Case Study on Chinese Stock Bubbles
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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.
Validation of the five-factor model of personality across instruments and observers.
McCrae, R R; Costa, P T
1987-01-01
Two data sources--self-reports and peer ratings--and two instruments--adjective factors and questionnaire scales--were used to assess the five-factor model of personality. As in a previous study of self-reports (McCrae & Costa, 1985b), adjective factors of neuroticism, extraversion, openness to experience, agreeableness-antagonism, and conscientiousness-undirectedness were identified in an analysis of 738 peer ratings of 275 adult subjects. Intraclass correlations among raters, ranging from .30 to .65, and correlations between mean peer ratings and self-reports, from .25 to .62, showed substantial cross-observer agreement on all five adjective factors. Similar results were seen in analyses of scales from the NEO Personality Inventory. Items from the adjective factors were used as guides in a discussion of the nature of the five factors. These data reinforce recent appeals for the adoption of the five-factor model in personality research and assessment.
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.
Savage, James; Pianosi, Francesca; Bates, Paul; Freer, Jim; Wagener, Thorsten
2015-04-01
Predicting flood inundation extents using hydraulic models is subject to a number of critical uncertainties. For a specific event, these uncertainties are known to have a large influence on model outputs and any subsequent analyses made by risk managers. Hydraulic modellers often approach such problems by applying uncertainty analysis techniques such as the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. However, these methods do not allow one to attribute which source of uncertainty has the most influence on the various model outputs that inform flood risk decision making. Another issue facing modellers is the amount of computational resource that is available to spend on modelling flood inundations that are 'fit for purpose' to the modelling objectives. Therefore a balance needs to be struck between computation time, realism and spatial resolution, and effectively characterising the uncertainty spread of predictions (for example from boundary conditions and model parameterisations). However, it is not fully understood how much of an impact each factor has on model performance, for example how much influence changing the spatial resolution of a model has on inundation predictions in comparison to other uncertainties inherent in the modelling process. Furthermore, when resampling fine scale topographic data in the form of a Digital Elevation Model (DEM) to coarser resolutions, there are a number of possible coarser DEMs that can be produced. Deciding which DEM is then chosen to represent the surface elevations in the model could also influence model performance. In this study we model a flood event using the hydraulic model LISFLOOD-FP and apply Sobol' Sensitivity Analysis to estimate which input factor, among the uncertainty in model boundary conditions, uncertain model parameters, the spatial resolution of the DEM and the choice of resampled DEM, have the most influence on a range of model outputs. These outputs include whole domain maximum
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)
Sensitivity Analysis to Select the Most Influential Risk Factors in a Logistic Regression Model
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Jassim N. Hussain
2008-01-01
Full Text Available The traditional variable selection methods for survival data depend on iteration procedures, and control of this process assumes tuning parameters that are problematic and time consuming, especially if the models are complex and have a large number of risk factors. In this paper, we propose a new method based on the global sensitivity analysis (GSA to select the most influential risk factors. This contributes to simplification of the logistic regression model by excluding the irrelevant risk factors, thus eliminating the need to fit and evaluate a large number of models. Data from medical trials are suggested as a way to test the efficiency and capability of this method and as a way to simplify the model. This leads to construction of an appropriate model. The proposed method ranks the risk factors according to their importance.
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 (Pbehavior. In order to improve construction safety performance, more focus on the workplace condition is required.
Trichotillomania and personality traits from the five-factor model
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Nancy J. Keuthen
2015-01-01
Full Text Available Objective:To examine whether personality traits have predictive validity for trichotillomania (TTM diagnosis, pulling severity and control, and hair pulling style.Methods:In study 1, logistic regression was used with TTM cases (n=54 and controls (n=25 to determine if NEO Five-Factor Inventory (NEO-FFI personality domains predicted TTM case vs. control classification. In study 2, hierarchical multiple regression was used with TTM cases (n=164 to determine whether NEO-FFI personality domains predicted hair pulling severity and control as well as focused and automatic pulling styles.Results:TTM case vs. control status was predicted by NEO-FFI neuroticism. Every 1-point increase in neuroticism scores resulted in a 10% greater chance of TTM diagnosis. Higher neuroticism, higher openness, and lower agreeableness were associated with greater pulling severity. Higher neuroticism was also associated with less control over hair pulling. Higher neuroticism and lower openness were associated with greater focused pulling. None of the personality domains predicted automatic hair pulling.Conclusions:Personality traits, especially neuroticism, can predict TTM diagnosis, hair pulling severity and control, and the focused style of pulling. None of the personality traits predicted automatic pulling. Longitudinal studies are needed to determine whether personality variables predispose to TTM onset, impact disorder course, and/or result from hair pulling behavior.
The HEXACO and Five-Factor Models of Personality in Relation to RIASEC Vocational Interests
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…
A Hierarchical Linear Model with Factor Analysis Structure at Level 2
Miyazaki, Yasuo; Frank, Kenneth A.
2006-01-01
In this article the authors develop a model that employs a factor analysis structure at Level 2 of a two-level hierarchical linear model (HLM). The model (HLM2F) imposes a structure on a deficient rank Level 2 covariance matrix [tau], and facilitates estimation of a relatively large [tau] matrix. Maximum likelihood estimators are derived via the…
Recursive parameter identification for infinite-dimensional factor model by using particle filter
Bagchi, Arunabha; Kamajima, K; Aihara, ShinIchi
2007-01-01
We consider the dynamics of forward rate process which is modeled by the parabolic type infinite-dimensional factor model. The parameters included in this parabolic model are estimated by using the yield curve as the observation data. In this paper, we propose the filtering and identification method
2016-01-01
The purpose of this thesis is to retrace the main steps that were taken in the evolution of the factor models and, in addition, to introduce two examples of how to apply the newest techniques developed in such fields to two different typologies of dataset, one traditional, meaning that it is composed mainly by macroeconomic and financial time series, and the other one 'new' which includes time series relevant to the Italian insurance sector and a set of macroeconomic and financial series r...
Prince-Embury, Sandra; Courville, Troy
2008-01-01
This article examines the scale structure of the Resiliency Scales for Children and Adolescents (RSCA). Confirmatory factor analysis reveals that a three-factor model is a better fit than one- or two-factor models for the normative sample. These findings lend support to the construct validity of the RSCA. The three-factor model is discussed as a…
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.)
Dynamic Factor Method of Computing Dynamic Mathematical Model for System Simulation
Institute of Scientific and Technical Information of China (English)
老大中; 吴娟; 杨策; 蒋滋康
2003-01-01
The computational methods of a typical dynamic mathematical model that can describe the differential element and the inertial element for the system simulation are researched. The stability of numerical solutions of the dynamic mathematical model is researched. By means of theoretical analysis, the error formulas, the error sign criteria and the error relationship criterion of the implicit Euler method and the trapezoidal method are given, the dynamic factor affecting the computational accuracy has been found, the formula and the methods of computing the dynamic factor are given. The computational accuracy of the dynamic mathematical model like this can be improved by use of the dynamic factor.
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.)
Axial form factor of the nucleon in the perturbative chiral quark model
Khosonthongkee, K; Faessler, Amand; Gutsche, T; Lyubovitskij, V E; Pumsa-ard, K; Yan, Y
2004-01-01
We apply the perturbative chiral quark model (PCQM) at one loop to analyze the axial form factor of the nucleon. This chiral quark model is based on an effective Lagrangian, where baryons are described by relativistic valence quarks and a perturbative cloud of Goldstone bosons as dictated by chiral symmetry. We apply the formalism to obtain analytical expressions for the axial form factor of the nucleon, which is given in terms of fundamental parameters of low-energy pion-nucleon physics (weak pion decay constant, strong pion-nucleon form factor) and of only one model parameter (radius of the nucleonic three-quark core).
Modeling the Factors Impacting Pesticide Concentrations in Groundwater Wells
DEFF Research Database (Denmark)
Aisopou, Angeliki; Binning, Philip John; Albrechtsen, Hans-Jørgen
2015-01-01
variability in the concentration at the well, which helps understanding the results of groundwater monitoring programs. The results are used to provide guidance on the design of pumping and regulatory changes for the long-term supply of safe groundwater. The fate of selected pesticides is examined......, for example, if the application of bentazone in a region with a layered aquifer stops today, the concentration at the well can continue to increase for 20 years if a low pumping rate is applied. This study concludes that because of the rapid response of the pesticide concentration at the drinking water well......This study examines the effect of pumping, hydrogeology, and pesticide characteristics on pesticide concentrations in production wells using a reactive transport model in two conceptual hydrogeologic systems; a layered aquifer with and without a stream present. The pumping rate can significantly...
Modeling the Factors Impacting Pesticide Concentrations in Groundwater Wells
DEFF Research Database (Denmark)
Aisopou, Angeliki; Binning, Philip John; Albrechtsen, Hans-Jørgen;
2015-01-01
This study examines the effect of pumping, hydrogeology, and pesticide characteristics on pesticide concentrations in production wells using a reactive transport model in two conceptual hydrogeologic systems; a layered aquifer with and without a stream present. The pumping rate can significantly...... affect the pesticide breakthrough time and maximum concentration at the well. The effect of the pumping rate on the pesticide concentration depends on the hydrogeology of the aquifer; in a layered aquifer, a high pumping rate resulted in a considerably different breakthrough than a low pumping rate......, while in an aquifer with a stream the effect of the pumping rate was insignificant. Pesticide application history and properties have also a great impact on the effect of the pumping rate on the concentration at the well. The findings of the study show that variable pumping rates can generate temporal...
A Model for the Colour Form Factor of the Proton
Dischler, J
2000-01-01
The total cross-section and the jet cross-section differ at a proton-proton collision. The latter is divergent if arbitrarily small transverse momenta are allowed. Even with some fixed lower pt cutoff, increases the jet cross-section much faster than the total cross-section at high energies. We have in this paper studied how the divergence could be tamed by colour screening effects among the partons. To do this we have built a proton model where we assign momenta, positions and colour-charge to all partons in the proton. We find that the relative behaviour of the cross-section can be better understood by the inclusion of this effect.
KADEK MIRA PITRIYANTI; KOMANG DHARMAWAN; G.K. GANDHIADI
2015-01-01
In 1996, Fama and French developed the CAPM in Three Factor Model Fama and French (TFMFF) to analyze the relationship between risk with rate of return by adding firm size factor that is proxied by Small Minus Big (SMB) and value factor at Book to Market Ratio that is proxied by High Minus Low (HML) on the CAPM model. The aim of this research is to compare the ability of CAPM and TFMFF in estimating the returns on six types of portfolios which are formed based on firm size and BE/ME. Selected ...
TEST OF THE FAMA-FRENCH THREE-FACTOR MODEL IN CROATIA
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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.
Macroeconomic factors and oil futures prices. A data-rich model
Energy Technology Data Exchange (ETDEWEB)
Zagaglia, Paolo [Modelling Division, Sveriges Riksbank (Sweden)
2010-03-15
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)
Cognition and the five-factor model of the positive and negative syndrome scale in schizophrenia.
Rodriguez-Jimenez, Roberto; Bagney, Alexandra; Mezquita, Laura; Martinez-Gras, Isabel; Sanchez-Morla, Eva-Maria; Mesa, Natalia; Ibañez, Manuel-Ignacio; Diez-Martin, Justo; Jimenez-Arriero, Miguel-Angel; Lobo, Antonio; Santos, Jose-Luis; Palomo, Tomas
2013-01-01
Different exploratory and confirmatory factorial analyses of the Positive and Negative Syndrome Scale (PANSS) have found a number of factors other than the original positive, negative, and general psychopathology. Based on a review of previous studies and using confirmatory factor analyses (CFA), Wallwork et al. (Schizophr Res 2012; 137: 246-250) have recently proposed a consensus five-factor structure of the PANSS. This solution includes a cognitive factor which could be a useful measure of cognition in schizophrenia. Our objectives were 1) to study the psychometric properties (factorial structure and reliability) of this consensus five-factor model of the PANSS, and 2) to study the relationship between executive performance assessed using the Wisconsin Card Sorting Test (WCST) and the proposed PANSS consensus cognitive factor (composed by items P2-N5-G11). This cross-sectional study included a final sample of 201 Spanish outpatients diagnosed with schizophrenia. For our first objective, CFA was performed and Cronbach's alphas of the five factors were calculated; for the second objective, sequential linear regression analyses were used. The results of the CFA showed acceptable fit indices (NNFI=0.94, CFI=0.95, RMSEA=0.08). Cronbach's alphas of the five factors were adequate. Regression analyses showed that this five-factor model of the PANSS explained more of the WCST variance than the classical three-factor model. Moreover, higher cognitive factor scores were associated with worse WCST performance. These results supporting its factorial structure and reliability provide robustness to this consensus PANSS five-factor model, and indicate some usefulness of the cognitive factor in the clinical assessment of schizophrenic patients. Copyright © 2012 Elsevier B.V. All rights reserved.
Axial form factors of the octet baryons in a covariant quark model
Ramalho, G
2015-01-01
We study the weak interaction axial form factors of the octet baryons, within the covariant spectator quark model, focusing on the dependence of four-momentum transfer squared, Q^2. In our model the axial form factors G_A(Q^2) (axial-vector form factor) and G_P(Q^2) (induced pseudoscalar form factor), are calculated based on the constituent quark axial form factors and the octet baryon wave functions. The quark axial current is parametrized by the two constituent quark form factors, the axial-vector form factor g_A^q(Q^2), and the induced pseudoscalar form factor g_P^q(Q^2). The baryon wave functions are composed of a dominant S-state and a P-state mixture for the relative angular momentum of the quarks. First, we study in detail the nucleon case. We assume that the quark axial-vector form factor g_A^q(Q^2) has the same function form as that of the quark electromagnetic isovector form factor. The remaining parameters of the model, the P-state mixture and the Q^2-dependence of g_P^q(Q^2), are determined by a f...
An information transmission model for transcription factor binding at regulatory DNA sites.
Tan, Mingfeng; Yu, Dong; Jin, Yuan; Dou, Lei; Li, Beiping; Wang, Yuelan; Yue, Junjie; Liang, Long
2012-06-06
Computational identification of transcription factor binding sites (TFBSs) is a rapid, cost-efficient way to locate unknown regulatory elements. With increased potential for high-throughput genome sequencing, the availability of accurate computational methods for TFBS prediction has never been as important as it currently is. To date, identifying TFBSs with high sensitivity and specificity is still an open challenge, necessitating the development of novel models for predicting transcription factor-binding regulatory DNA elements. Based on the information theory, we propose a model for transcription factor binding of regulatory DNA sites. Our model incorporates position interdependencies in effective ways. The model computes the information transferred (TI) between the transcription factor and the TFBS during the binding process and uses TI as the criterion to determine whether the sequence motif is a possible TFBS. Based on this model, we developed a computational method to identify TFBSs. By theoretically proving and testing our model using both real and artificial data, we found that our model provides highly accurate predictive results. In this study, we present a novel model for transcription factor binding regulatory DNA sites. The model can provide an increased ability to detect TFBSs.
Vector interaction model of factors of retailers` competitiveness
Directory of Open Access Journals (Sweden)
T.O. Zagornaya
2013-09-01
Full Text Available The aim of the article. The aim of the article is to develop scientific and methodical approach to the modeling and analysis of complex elements, settings, and the phase trajectories of competition in the market. Development of basic principles of the theory of competition reflects complexity of economic trends in processes at the level of enterprises, industries, markets.The results of the analysis. Despite the large number of methods and computational procedures to situation diagnostic in competitive market there is a need for a dynamic approach as basic element of axiomatic theory of competition. The author adapted such categories as mass, strength, impact, energy in relation to the process of the competitive dynamics of the market. It is possible to reveal the nature of the vector process of interaction between participants of competition, to assess the competitive dynamics of vector in the context of market operators resellers.It is important to note that the dynamic component of competitive analysis will require fundamental review of existing methods and models for assessing the competitiveness of enterprises, investigation of the nature of competition in time. Such a poorly studied category as competitive behavior, which will generate an appropriate analytical tools as part of the competitive dynamics of the theory of competition is analyzed as well. Despite the isolation of selected categories of competition, competitive, competitive advantage, competitive position, they are related to dynamics categories of. The author formed fundamentally new basis vector approach to the study of competition dynamics.Conclusions and directions of further researches. Thus, on theoretical level the author highlighted the dynamic component in the basis of axiomatic theory of competition through comparative analysis of the main elements of dynamic approach to the study of competitive processes. The system of coordinates company's competitiveness
Bridging the gap with the five-factor model.
Costa, Paul T; McCrae, Robert R
2010-04-01
Comments on the original article Personality traits and the classification of mental Disorders: Toward a more complete integration in DSM-5 and an empirical model of psychopathology by Robert F. Krueger and Nicholas R. Eaton (see record 2010-13810-003). Some researchers had hoped the forthcoming Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) would ask psychiatrists (and the clinical psychologists and researchers who are also tied to the DSM) to leap the gap and embrace a trait-based taxonomy of personality pathology (Widiger & Trull, 2007). Krueger and Eaton (pp. 97-118, this issue) take a more pragmatic stance: They hope to coax psychiatrists across by introducing personality dimensions as an adjunct to familiar PD types; they envision that DSM-5 might serve "as a bridge" (p. 110, this issue) to a fully dimensional Diagnostic and Statistical Manual of Mental Disorders, Sixth Edition (DSM-6). We acknowledge the wisdom of this strategy and suggest ways to strengthen it. PsycINFO Database Record (c) 2010 APA, all rights reserved.
Dust from AGBs: relevant factors and modelling uncertainties
Ventura, P; Schneider, R; Di Criscienzo, M; Rossi, C; La Franca, F; Gallerani, S; Valiante, R
2014-01-01
The dust formation process in the winds of Asymptotic Giant Branch stars is discussed, based on full evolutionary models of stars with mass in the range $1$M$_{\\odot} \\leq$M$\\leq 8$M$_{\\odot}$, and metallicities $0.001 < Z <0.008$. Dust grains are assumed to form in an isotropically expanding wind, by growth of pre--existing seed nuclei. Convection, for what concerns the treatment of convective borders and the efficiency of the schematization adopted, turns out to be the physical ingredient used to calculate the evolutionary sequences with the highest impact on the results obtained. Low--mass stars with M$\\leq 3$M$_{\\odot}$ produce carbon type dust with also traces of silicon carbide. The mass of solid carbon formed, fairly independently of metallicity, ranges from a few $10^{-4}$M$_{\\odot}$, for stars of initial mass $1-1.5$M$_{\\odot}$, to $\\sim 10^{-2}$M$_{\\odot}$ for M$\\sim 2-2.5$M$_{\\odot}$; the size of dust particles is in the range $0.1 \\mu$m$\\leq a_C \\leq 0.2\\mu$m. On the contrary, the production...
Modeling the Factors Impacting Pesticide Concentrations in Groundwater Wells.
Aisopou, Angeliki; Binning, Philip J; Albrechtsen, Hans-Jørgen; Bjerg, Poul L
2015-01-01
This study examines the effect of pumping, hydrogeology, and pesticide characteristics on pesticide concentrations in production wells using a reactive transport model in two conceptual hydrogeologic systems; a layered aquifer with and without a stream present. The pumping rate can significantly affect the pesticide breakthrough time and maximum concentration at the well. The effect of the pumping rate on the pesticide concentration depends on the hydrogeology of the aquifer; in a layered aquifer, a high pumping rate resulted in a considerably different breakthrough than a low pumping rate, while in an aquifer with a stream the effect of the pumping rate was insignificant. Pesticide application history and properties have also a great impact on the effect of the pumping rate on the concentration at the well. The findings of the study show that variable pumping rates can generate temporal variability in the concentration at the well, which helps understanding the results of groundwater monitoring programs. The results are used to provide guidance on the design of pumping and regulatory changes for the long-term supply of safe groundwater. The fate of selected pesticides is examined, for example, if the application of bentazone in a region with a layered aquifer stops today, the concentration at the well can continue to increase for 20 years if a low pumping rate is applied. This study concludes that because of the rapid response of the pesticide concentration at the drinking water well due to changes in pumping, wellhead management is important for managing pesticide concentrations.
Genome Scans for Detecting Footprints of Local Adaptation Using a Bayesian Factor Model
Duforet-Frebourg, Nicolas; Bazin, Eric; Blum, Michael G.B.
2014-01-01
There is a considerable impetus in population genomics to pinpoint loci involved in local adaptation. A powerful approach to find genomic regions subject to local adaptation is to genotype numerous molecular markers and look for outlier loci. One of the most common approaches for selection scans is based on statistics that measure population differentiation such as FST. However, there are important caveats with approaches related to FST because they require grouping individuals into populations and they additionally assume a particular model of population structure. Here, we implement a more flexible individual-based approach based on Bayesian factor models. Factor models capture population structure with latent variables called factors, which can describe clustering of individuals into populations or isolation-by-distance patterns. Using hierarchical Bayesian modeling, we both infer population structure and identify outlier loci that are candidates for local adaptation. In order to identify outlier loci, the hierarchical factor model searches for loci that are atypically related to population structure as measured by the latent factors. In a model of population divergence, we show that it can achieve a 2-fold or more reduction of false discovery rate compared with the software BayeScan or with an FST approach. We show that our software can handle large data sets by analyzing the single nucleotide polymorphisms of the Human Genome Diversity Project. The Bayesian factor model is implemented in the open-source PCAdapt software. PMID:24899666
Directory of Open Access Journals (Sweden)
Gianola Daniel
2007-09-01
Full Text Available Abstract Multivariate linear models are increasingly important in quantitative genetics. In high dimensional specifications, factor analysis (FA may provide an avenue for structuring (covariance matrices, thus reducing the number of parameters needed for describing (codispersion. We describe how FA can be used to model genetic effects in the context of a multivariate linear mixed model. An orthogonal common factor structure is used to model genetic effects under Gaussian assumption, so that the marginal likelihood is multivariate normal with a structured genetic (covariance matrix. Under standard prior assumptions, all fully conditional distributions have closed form, and samples from the joint posterior distribution can be obtained via Gibbs sampling. The model and the algorithm developed for its Bayesian implementation were used to describe five repeated records of milk yield in dairy cattle, and a one common FA model was compared with a standard multiple trait model. The Bayesian Information Criterion favored the FA model.
Pia, Maria Grazia; Bell, Zane W.; Dressendorfer, Paul V.
2010-01-01
A scientometric analysis has been performed on selected physics journals to estimate the presence of simulation and modeling in physics literature in the past fifty years. Correlations between the observed trends and several social and economical factors have been evaluated.
The three-factor model of evaluating mining rights of coal resources based on options
Institute of Scientific and Technical Information of China (English)
ZHANG Jin-suo; ZOU Shao-hui
2008-01-01
Since mining rights of coal resources(for short MRCR) could be regarded as amulti-stage compound real option, the evaluation for MRCR can be better solved using op-tion theory than the NPV. In the former research, we developed a two-factor model ofevaluating MRCR when the coal spot price and convenience yield are stochastic based onoption theory. On the basis of this two-factor model, we set up a three-factor model ofevaluating MRCR when the interest rate followed a stochastic process. Through a realexample application, we found the model can get higher values than the two-factor modeland the NPV. This is because considering the volatility of interest rate can improve theexecutive opportunity of MRCR.
Smith, Martin M; Saklofske, Donald H
2016-08-05
Evidence suggests perfectionism is a multidimensional construct composed of 2 higher order factors: perfectionistic strivings and perfectionistic concerns. However, the substantial overlap between perfectionistic strivings and perfectionistic concerns is problematic, as are the unanswered questions regarding the structure of perfectionism following removal of common variance. This research addressed this through bifactor modeling. Three student samples (N = 742) completed Hewitt and Flett's ( 1991 ) Multidimensional Perfectionism Scale, Frost, Marten, Lahart, and Rosenblate's ( 1990 ) Multidimensional Perfectionism Scale, and Slaney, Rice, Mobley, Trippi, and Ashby's ( 2001 ) Almost Perfect Scale-Revised. Greater support was consistently found for the bifactor model, relative to the 2-factor model. Results suggest the bifactor model best represents the structure of perfectionism and provide preliminary support for the use of a general factor score. Researchers are cautioned that removal of general variance may render the reliability of specific factors (i.e., perfectionistic strivings and perfectionistic concerns) suspect.
These model-based estimates use two surveys, the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS). The two surveys are combined using novel statistical methodology.
The relationships between behavioral addictions and the five-factor model of personality
National Research Council Canada - National Science Library
Andreassen, Cecilie Schou; Griffiths, Mark D; Gjertsen, Siri Renate; Krossbakken, Elfrid; Kvam, Siri; Pallesen, Ståle
2013-01-01
..., 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...
Electromagnetic form factors of the baryon octet in the perturbative chiral quark model
Cheedket, S; Gutsche, T; Faessler, A; Pumsa-ard, K; Yan, Y; Gutsche, Th.; Faessler, Amand
2002-01-01
We apply the perturbative chiral quark model at one loop to analyze the electromagnetic form factors of the baryon octet. The analytic expressions for baryon form factors, which are given in terms of fundamental parameters of low-energy pion-nucleon physics(weak pion decay constant, axial nucleon coupling, strong pion-nucleon form factor), and the numerical results for baryon magnetic moments, charge and magnetic radii are presented. Our results are in good agreement with experimental data.
Forecasting Multivariate Volatility using the VARFIMA Model on Realized Covariance Cholesky Factors
DEFF Research Database (Denmark)
Halbleib, Roxana; Voev, Valeri
2011-01-01
This paper analyzes the forecast accuracy of the multivariate realized volatility model introduced by Chiriac and Voev (2010), subject to different degrees of model parametrization and economic evaluation criteria. Bymodelling the Cholesky factors of the covariancematrices, the model generates...... positive definite, but biased covariance forecasts. In this paper, we provide empirical evidence that parsimonious versions of the model generate the best covariance forecasts in the absence of bias correction. Moreover, we show by means of stochastic dominance tests that any risk averse investor...
Alessi, Lucia; Barigozzi, Matteo; Capasso, Marco
2006-01-01
We propose a new model for multivariate forecasting which combines the Generalized Dynamic Factor Model (GDFM)and the GARCH model. The GDFM, applied to a huge number of series, captures the multivariate information and disentangles the common and the idiosyncratic part of each series of returns. In this financial analysis, both these components are modeled as a GARCH. We compare GDFM+GARCH and standard GARCH performance on samples up to 475 series, predicting both levels and volatility of ret...
A receptor model for urban aerosols based on oblique factor analysis
DEFF Research Database (Denmark)
Keiding, Kristian; Sørensen, Morten S.; Pind, Niels
1987-01-01
A procedure is outlined for the construction of receptor models of urban aerosols, based on factor analysis. The advantage of the procedure is that the covariation of source impacts is included in the construction of the models. The results are compared with results obtained by other receptor-modelling...... procedures. It was found that procedures based on correlating sources were physically sound as well as in mutual agreement. Procedures based on non-correlating sources were found to generate physically obscure models....
Modeling of the symmetry factor of electrochemical proton discharge via the Volmer reaction
DEFF Research Database (Denmark)
Björketun, Mårten E.; Tripkovic, Vladimir; Skúlason, Egill
2013-01-01
A scheme for evaluating symmetry factors of elementary electrode reactions using a density functional theory (DFT) based model of the electrochemical double layer is presented. As an illustration, the symmetry factor is determined for hydrogen adsorption via the electrochemical Volmer reaction. T...
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.
A New Look at the Big Five Factor Structure through Exploratory Structural Equation Modeling
Marsh, Herbert W.; Ludtke, Oliver; Muthen, Bengt; Asparouhov, Tihomir; Morin, Alexandre J. S.; Trautwein, Ulrich; Nagengast, Benjamin
2010-01-01
NEO instruments are widely used to assess Big Five personality factors, but confirmatory factor analyses (CFAs) conducted at the item level do not support their a priori structure due, in part, to the overly restrictive CFA assumptions. We demonstrate that exploratory structural equation modeling (ESEM), an integration of CFA and exploratory…
Molenaar, P.C.M.
1987-01-01
Outlines a frequency domain analysis of the dynamic factor model and proposes a solution to the problem of constructing a causal filter of lagged factor loadings. The method is illustrated with applications to simulated and real multivariate time series. The latter applications involve topographic a
Factors Influencing Teachers' Intention to Use Technology: Model Development and Test
Teo, Timothy
2011-01-01
Among the key players in any effective integration of technology in teaching and learning is the teacher. Despite the research that has been conducted to examine the factors that explain teachers' intention to use technology, few have developed a model to statistically explain the interactions among these factors and how they influence teachers'…
The Hierarchical Factor Model of ADHD: Invariant across Age and National Groupings?
Toplak, Maggie E.; Sorge, Geoff B.; Flora, David B.; Chen, Wai; Banaschewski, Tobias; Buitelaar, Jan; Ebstein, Richard; Eisenberg, Jacques; Franke, Barbara; Gill, Michael; Miranda, Ana; Oades, Robert D.; Roeyers, Herbert; Rothenberger, Aribert; Sergeant, Joseph; Sonuga-Barke, Edmund; Steinhausen, Hans-Christoph; Thompson, Margaret; Tannock, Rosemary; Asherson, Philip; Faraone, Stephen V.
2012-01-01
Objective: To examine the factor structure of attention-deficit/hyperactivity disorder (ADHD) in a clinical sample of 1,373 children and adolescents with ADHD and their 1,772 unselected siblings recruited from different countries across a large age range. Hierarchical and correlated factor analytic models were compared separately in the ADHD and…
Factors Affecting Technology Integration in K-12 Classrooms: A Path Model
Inan, Fethi A.; Lowther, Deborah L.
2010-01-01
The purpose of this study was to examine the direct and indirect effects of teachers' individual characteristics and perceptions of environmental factors that influence their technology integration in the classroom. A research-based path model was developed to explain causal relationships between these factors and was tested based on data gathered…
The Five Factor Model of Personality Applied to Adults Who Stutter
Iverach, Lisa; O'Brian, Susan; Jones, Mark; Block, Susan; Lincoln, Michelle; Harrison, Elisabeth; Hewat, Sally; Menzies, Ross G.; Packman, Ann; Onslow, Mark
2010-01-01
Previous research has not explored the Five Factor Model of personality among adults who stutter. Therefore, the present study investigated the five personality domains of Neuroticism, Extraversion, Openness, Agreeableness and Conscientiousness, as measured by the NEO Five Factor Inventory (NEO-FFI), in a sample of 93 adults seeking speech…
Enhancement Factors in Ozone Absorption Based on the Surface Renewal Model and its Application
Institute of Scientific and Technical Information of China (English)
程江; 杨卓如; 陈焕钦; C.H.Kuo; M.E.Zappi
2000-01-01
Based on the Danckwerts surface renewal model, a simple explicit expression of the enhancement factor in ozone absorption with a first order ozone self-decomposition and parallel second order ozonation reactions has been derived. The results are compared with our previous work based on the film theory. The 2,4-dichlorophenol destruction rate by ozonation is predicted using the enhancement factor model in this paper.
A Form Factor Model for Exclusive B- and D-Decays
Stech, B
1996-01-01
An explicit model is presented which gives the momentum transfer-dependent ratios of form factors of hadronic currents. For the unknown Isgur-Wise function and its generalization for transitions to light particles a simple phenomenological Ansatz is added. The model allows a calculation of all form factors in terms of mass parameters only. It is tested by comparison with experimental data, QCD sum rules and lattice calculations.
Quantifying Uncertainty from Computational Factors in Simulations of a Model Ballistic System
2017-08-01
ARL-TR-8074 ● AUG 2017 US Army Research Laboratory Quantifying Uncertainty from Computational Factors in Simulations of a Model...Uncertainty from Computational Factors in Simulations of a Model Ballistic System by Daniel J Hornbaker Weapons and Materials Research...penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM
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...
Presenting a Model to Evaluate the Factors Affecting Export Performance in International Marketing
Directory of Open Access Journals (Sweden)
Hassan Esmailpour
2016-03-01
Full Text Available This study aims to present a model to evaluate the factors affecting export performance of export-oriented business clusters in Western Tehran. For this purpose, export performance was measured by the effectiveness of export, export sales, and export intensity. 83 companies are studied in this research. The statistical population consists of 209 managers and experts associated with the export of the companies. Due to the limited number of the statistical population, the total population is considered as a statistical sample. The data are collected through a questionnaire consisting of two parts: The questionnaire of factor analysis with regard to the factors identified in earlier studies and the questionnaire of export performance. The questionnaire is given to the sampleafter examining its validity and reliability. For statistical data analysis, descriptive and inferential statistical methods are used.Descriptive statistics are used for classifying, summarizing and interpreting statistical data. Inferential statistics are used to assess the export performance based on one sample t testand identify factors affecting export performance. Exploratory and confirmatory factor analysis using SPSS 19 software is usedto provide a model. Structural equation modeling using LISREL software is used toconfirm the proposed model. Four factors (environmental, technical, strategic export marketing capabilities and international management skills are categorized. Finally, the model of the factors affecting the export performance of export-oriented marketing business clusters in Western Tehranis designed and confirmed.
Li, Hongwei; Wang, Weili; Jia, Haixia; Lian, Jianhong; Cao, Jianzhong; Zhang, Xiaqin; Song, Xing; Jia, Sufang; Li, Zhengran; Cao, Xing; Zhou, Wei; Han, Songye; Yang, Weihua; Xi, Yanfen; Lian, Shenming
2017-09-01
Several indices have been developed to predict survival of brain metastases (BM) based on prognostic factors. However, such models were designed for general brain metastases from different kinds of cancers, and prognostic factors vary between cancers and histological subtypes. Recently, studies have indicated that epidermal growth factor receptor (EGFR) mutation status may be a potential prognostic biological factor in BM from lung adenocarcinoma. Thus, we sought to define the role of EGFR mutation in prognoses and introduce a prognostic model specific for BM from lung adenocarcinoma. Data of 256 patients with BM from lung adenocarcinoma identified with EGFR mutations were collected. Independent prognostic factors were confirmed using a Cox regression model. The new prognostic model was developed based on the results of multivariable analyses. The score of each factor was calculated by six-month survival. Prognostic groups were divided into low, medium, and high risk based on the total scores. The prediction ability of the new model was compared to the three existing models. EGFR mutation and Karnofsky performance status were independent prognostic factors and were thus integrated into the new prognostic model. The new model was superior to the three other scoring systems regarding the prediction of three, six, and 12-month survival by pairwise comparison of the area under the curve. Our proposed prognostic model specific for BM from lung adenocarcinoma incorporating EGFR mutation status was valid in predicting patient survival. Further verification is warranted, with prospective testing using large sample sizes. © 2017 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.
Institute of Scientific and Technical Information of China (English)
WU Hao; CHEN Xiaoling; HE Ying; HE Xiaorong; CAI Xiaobin; XU Keyan
2006-01-01
Indicator systems of environmental sustainable development in the Poyang Lake Basin are established from 51 elementary indexes by factor analysis, which is composed of four steps such as the factor model, the parameter estimation, the factor rotation and the factor score. Under the condition that the cumulative proportion is greater than 85%, 5 explicit factors of environmental sustainable development as well as its factor score by region are carried out. The result indicates some impact factors to the basin environmental in descending sort order are volume of water, volume of waste gas discharge, volume of solid wastes, the degree to comprehensive utilization of waste gas, waste water and solid wastes, the emission volume of waste gas, waste water and solid wastes. It is helpful and important to provide decision support for constituting sustainable development strategies and evaluate the sustainable development status of each city.
A Tri-Factor Model for Integrating Ratings Across Multiple Informants
Bauer, Daniel J.; Howard, Andrea L.; Baldasaro, Ruth E.; Curran, Patrick J.; Hussong, Andrea M.; Chassin, Laurie; Zucker, Robert A.
2014-01-01
Psychologists often obtain ratings for target individuals from multiple informants such as parents or peers. In this paper we propose a tri-factor model for multiple informant data that separates target-level variability from informant-level variability and item-level variability. By leveraging item-level data, the tri-factor model allows for examination of a single trait rated on a single target. In contrast to many psychometric models developed for multitrait-multimethod data, the tri-factor model is predominantly a measurement model. It is used to evaluate item quality in scale development, test hypotheses about sources of target variability (e.g., sources of trait differences) versus informant variability (e.g., sources of rater bias), and generate integrative scores that are purged of the subjective biases of single informants. PMID:24079932
Entrance and exit region friction factor models for annular seal analysis. Ph.D. Thesis
Elrod, David Alan
1988-01-01
The Mach number definition and boundary conditions in Nelson's nominally-centered, annular gas seal analysis are revised. A method is described for determining the wall shear stress characteristics of an annular gas seal experimentally. Two friction factor models are developed for annular seal analysis; one model is based on flat-plate flow theory; the other uses empirical entrance and exit region friction factors. The friction factor predictions of the models are compared to experimental results. Each friction model is used in an annular gas seal analysis. The seal characteristics predicted by the two seal analyses are compared to experimental results and to the predictions of Nelson's analysis. The comparisons are for smooth-rotor seals with smooth and honeycomb stators. The comparisons show that the analysis which uses empirical entrance and exit region shear stress models predicts the static and stability characteristics of annular gas seals better than the other analyses. The analyses predict direct stiffness poorly.
MULTIPLE LOGISTIC REGRESSION MODEL TO PREDICT RISK FACTORS OF ORAL HEALTH DISEASES
Directory of Open Access Journals (Sweden)
Parameshwar V. Pandit
2012-06-01
Full Text Available Purpose: To analysis the dependence of oral health diseases i.e. dental caries and periodontal disease on considering the number of risk factors through the applications of logistic regression model. Method: The cross sectional study involves a systematic random sample of 1760 permanent dentition aged between 18-40 years in Dharwad, Karnataka, India. Dharwad is situated in North Karnataka. The mean age was 34.26±7.28. The risk factors of dental caries and periodontal disease were established by multiple logistic regression model using SPSS statistical software. Results: The factors like frequency of brushing, timings of cleaning teeth and type of toothpastes are significant persistent predictors of dental caries and periodontal disease. The log likelihood value of full model is –1013.1364 and Akaike’s Information Criterion (AIC is 1.1752 as compared to reduced regression model are -1019.8106 and 1.1748 respectively for dental caries. But, the log likelihood value of full model is –1085.7876 and AIC is 1.2577 followed by reduced regression model are -1019.8106 and 1.1748 respectively for periodontal disease. The area under Receiver Operating Characteristic (ROC curve for the dental caries is 0.7509 (full model and 0.7447 (reduced model; the ROC for the periodontal disease is 0.6128 (full model and 0.5821 (reduced model. Conclusions: The frequency of brushing, timings of cleaning teeth and type of toothpastes are main signifi cant risk factors of dental caries and periodontal disease. The fitting performance of reduced logistic regression model is slightly a better fit as compared to full logistic regression model in identifying the these risk factors for both dichotomous dental caries and periodontal disease.
Generalized vector form factors of the pion in a chiral quark model
Broniowski, Wojciech
2008-01-01
Generalized vector form factors of the pion, related to the moments of the generalized parton distribution functions, are evaluated in the Nambu--Jona-Lasinio model with the Pauli-Villars regularization. The lowest moments (the electromagnetic and the gravitational form factors) are compared to recent lattice data, with fair agreement. Predictions for higher-order moments are also made. Relevant features of the generalized form factors in the chiral quark models are highlighted and the role of the QCD evolution for the higher-order GFFs is stressed.
Scale-model charge-transfer technique for measuring enhancement factors
Kositsky, J.; Nanevicz, J. E.
1991-01-01
Determination of aircraft electric field enhancement factors is crucial when using airborne field mill (ABFM) systems to accurately measure electric fields aloft. SRI used the scale model charge transfer technique to determine enhancement factors of several canonical shapes and a scale model Learjet 36A. The measured values for the canonical shapes agreed with known analytic solutions within about 6 percent. The laboratory determined enhancement factors for the aircraft were compared with those derived from in-flight data gathered by a Learjet 36A outfitted with eight field mills. The values agreed to within experimental error (approx. 15 percent).
Schirm, Sibylle; Engel, Christoph; Loeffler, Markus; Scholz, Markus
2014-05-26
Haematotoxicity of conventional chemotherapies often results in delays of treatment or reduction of chemotherapy dose. To ameliorate these side-effects, patients are routinely treated with blood transfusions or haematopoietic growth factors such as erythropoietin (EPO) or granulocyte colony-stimulating factor (G-CSF). For the latter ones, pharmaceutical derivatives are available, which differ in absorption kinetics, pharmacokinetic and -dynamic properties. Due to the complex interaction of cytotoxic effects of chemotherapy and the stimulating effects of different growth factor derivatives, optimal treatment is a non-trivial task. In the past, we developed mathematical models of thrombopoiesis, granulopoiesis and erythropoiesis under chemotherapy and growth-factor applications which can be used to perform clinically relevant predictions regarding the feasibility of chemotherapy schedules and cytopenia prophylaxis with haematopoietic growth factors. However, interactions of lineages and growth-factors were ignored so far. To close this gap, we constructed a hybrid model of human granulopoiesis and erythropoiesis under conventional chemotherapy, G-CSF and EPO applications. This was achieved by combining our single lineage models of human erythropoiesis and granulopoiesis with a common stem cell model. G-CSF effects on erythropoiesis were also implemented. Pharmacodynamic models are based on ordinary differential equations describing proliferation and maturation of haematopoietic cells. The system is regulated by feedback loops partly mediated by endogenous and exogenous EPO and G-CSF. Chemotherapy is modelled by depletion of cells. Unknown model parameters were determined by fitting the model predictions to time series data of blood counts and cytokine profiles. Data were extracted from literature or received from cooperating clinical study groups. Our model explains dynamics of mature blood cells and cytokines after growth-factor applications in healthy volunteers
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
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 as i...... that the proposed overall factor of safety is an appropriate and comprehensive measure of factor of safety. The proposed methodology is illustrated for a typical resin transfer moulded (RTM) fume hood. The concept can easily be extended for other applications....
Splett, Joni Williams; Raborn, Anthony; Lane, Kathleen Lynne; Binney, Alexandra J; Chafouleas, Sandra M
2017-03-06
We conducted this study to add to literature of previous conflicting factorial examinations of the BASC-2 Behavioral and Emotional Screening System (BESS), Teacher Form-Child/Adolescent. Data were collected by an urban school district in the southeastern United States including 2,228 students rated by 120 teachers in Fall 2014 and 1,955 students rated by 104 teachers in Spring 2015. In both samples, we replicated and then conceptually and statistically compared factor models to examine the (a) 4-factor structure from which the BESS Teacher Form was developed, and (b) existence of a general factor currently being used. Previous studies examined the 4-factor and bifactor structure of the BESS Teacher Form on separate samples. Our model comparison results support a multidimensional interpretation. We recovered similar fit statistics and standardized factor loadings as previous factor analyses. However, measures of variance accounted for by the general factor were below recommended thresholds of a unidimensional construct. We recommend advancing a factorial model that represents a weighted combination of general and specific factors, but do not support continued use of a unidimensional total T score. Limitations and implications of the study are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Hojka, Vladimir; Stastny, Petr; Rehak, Tomas; Gołas, Artur; Mostowik, Aleksandra; Zawart, Marek; Musálek, Martin
2016-09-01
While tests of basic motor abilities such as speed, maximum strength or endurance are well recognized, testing of complex motor functions such as agility remains unresolved in current literature. Therefore, the aim of this review was to evaluate which main factor or factor structures quantitatively determine agility. In methodological detail, this review focused on research that explained or described the relationships between latent variables in a factorial model of agility using approaches such as principal component analysis, factor analysis and structural equation modeling. Four research studies met the defined inclusion criteria. No quantitative empirical research was found that tried to verify the quality of the whole suggested model of the main factors determining agility through the use of a structural equation modeling (SEM) approach or a confirmatory factor analysis. From the whole structure of agility, only change of direction speed (CODS) and some of its subtests were appropriately analyzed. The combination of common CODS tests is reliable and useful to estimate performance in sub-elite athletes; however, for elite athletes, CODS tests must be specific to the needs of a particular sport discipline. Sprinting and jumping tests are stronger factors for CODS than explosive strength and maximum strength tests. The authors suggest the need to verify the agility factorial model by a second generation data analysis technique such as SEM.
Model reductions for inference: generality of pairwise, binary, and planar factor graphs.
Eaton, Frederik; Ghahramani, Zoubin
2013-05-01
We offer a solution to the problem of efficiently translating algorithms between different types of discrete statistical model. We investigate the expressive power of three classes of model-those with binary variables, with pairwise factors, and with planar topology-as well as their four intersections. We formalize a notion of "simple reduction" for the problem of inferring marginal probabilities and consider whether it is possible to "simply reduce" marginal inference from general discrete factor graphs to factor graphs in each of these seven subclasses. We characterize the reducibility of each class, showing in particular that the class of binary pairwise factor graphs is able to simply reduce only positive models. We also exhibit a continuous "spectral reduction" based on polynomial interpolation, which overcomes this limitation. Experiments assess the performance of standard approximate inference algorithms on the outputs of our reductions.
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.
A Bayesian Multi-Level Factor Analytic Model of Consumer Price Sensitivities across Categories
Duvvuri, Sri Devi; Gruca, Thomas S.
2010-01-01
Identifying price sensitive consumers is an important problem in marketing. We develop a Bayesian multi-level factor analytic model of the covariation among household-level price sensitivities across product categories that are substitutes. Based on a multivariate probit model of category incidence, this framework also allows the researcher to…
A Diquark-Quark Model with Its Use in Nucleon Form Factors
Institute of Scientific and Technical Information of China (English)
WANG Hong-Min; ZHANG Ben-Ai
2005-01-01
The nucleon electromagnetic form factors are investigated within a simple diquark-quark model using the light-front formalism. In this model, baryon is described as a bound state of one quark and one clustering diquark.The calculational results are compared with the experimental ones. We also regard the quarks in a baryon as pointlike constituent quarks.
Factors Affecting Pupils' Noise Annoyance in Schools: The Building and Testing of Models
Boman, Eva; Enmarker, Ingela
2004-01-01
This article reports two studies intended to develop and assess conceptual models of how different factors mediate and moderate the annoyance reaction in school environments. In the first, a survey of 207 pupils was conducted where assumptions about mediators and moderators were formulated and tested. In the best model, general sensitivity and…
Enhancement Factors in Ozone Absorption Based on the Surface Renewal Model and its Application
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Based on the Danckwerts surface renewal model, a simple explicit expression of theenhancement factor in ozone absorption with a first order ozone self-decomposition and parallel secondorder ozonation reactions has been derived. The results are compared with our previous work based onthe film theory. The 2,4-dichlorophenol destruction rate by ozonation is predicted using the enhancementfactor model in this paper.
A Bayesian Multi-Level Factor Analytic Model of Consumer Price Sensitivities across Categories
Duvvuri, Sri Devi; Gruca, Thomas S.
2010-01-01
Identifying price sensitive consumers is an important problem in marketing. We develop a Bayesian multi-level factor analytic model of the covariation among household-level price sensitivities across product categories that are substitutes. Based on a multivariate probit model of category incidence, this framework also allows the researcher to…
Logistic regression models of factors influencing the location of bioenergy and biofuels plants
T.M. Young; R.L. Zaretzki; J.H. Perdue; F.M. Guess; X. Liu
2011-01-01
Logistic regression models were developed to identify significant factors that influence the location of existing wood-using bioenergy/biofuels plants and traditional wood-using facilities. Logistic models provided quantitative insight for variables influencing the location of woody biomass-using facilities. Availability of "thinnings to a basal area of 31.7m2/ha...
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.
Phan, Tran Hong Ha; Saraf, Pritha; Kiparissides, Alexandros; Mantalaris, Athanasios; Song, Hao; Lim, Mayasari
2013-11-01
Stem cell factor (SCF) and erythropoietin (EPO) are two most recognized growth factors that play in concert to control in vitro erythropoiesis. However, exact mechanisms underlying the interplay of these growth factors in vitro remain unclear. We developed a mathematical model to study co-signaling effects of SCF and EPO utilizing the ERK1/2 and GATA-1 pathways (activated by SCF and EPO) that drive the proliferation and differentiation of erythroid progenitors. The model was simplified and formulated based on three key features: synergistic contribution of SCF and EPO on ERK1/2 activation, positive feedback effects on proliferation and differentiation, and cross-inhibition effects of activated ERK1/2 and GATA-1. The model characteristics were developed to correspond with biological observations made known thus far. Our simulation suggested that activated GATA-1 has a more dominant cross-inhibition effect and stronger positive feedback response on differentiation than the proliferation pathway, while SCF contributed more to the activation of ERK1/2 than EPO. A sensitivity analysis performed to gauge the dynamics of the system was able to identify the most sensitive model parameters and illustrated a contribution of transient activity in EPO ligand to growth factor synergism. Based on theoretical arguments, we have successfully developed a model that can simulate growth factor synergism observed in vitro for erythropoiesis. This hypothesized model can be applied to further computational studies in biological systems where synergistic effects of two ligands are seen.
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.
Directory of Open Access Journals (Sweden)
KADEK MIRA PITRIYANTI
2015-11-01
Full Text Available In 1996, Fama and French developed the CAPM in Three Factor Model Fama and French (TFMFF to analyze the relationship between risk with rate of return by adding firm size factor that is proxied by Small Minus Big (SMB and value factor at Book to Market Ratio that is proxied by High Minus Low (HML on the CAPM model. The aim of this research is to compare the ability of CAPM and TFMFF in estimating the returns on six types of portfolios which are formed based on firm size and BE/ME. Selected samples are stocks of LQ-45 in period of February 2014, which have passed the selection of firm profits and ROE Warren Buffett criteria. Simple linear regression and Multiple linear regression with t test and F test statistics are used to demonstrate the influence and significance level of each variable. The results showed that TFMFF was more superior than CAPM. Market risk factor consistently affected each portfolio. SMB and HML is not always significantly effect on each portfolio, such as portfolio B/H, only market risk factor has a significant effect. However, the addition of SMB factors and HML factors could increase the coefficient of determination in each formed portfolio.
Placidi, Luca; Seddik, Hakime; Faria, Sergio H
2009-01-01
A complete theoretical presentation of the CAFFE model (Continuum-mechanical, Anisotropic Flow model, based on an anisotropic Flow Enhancement factor) is given. The CAFFE model is an application of the theory of mixtures with continuous diversity for the case of large ice masses in which the induced anisotropy can not be neglected. The anisotropic response of the material is considered via a simple anisotropic generalization of Glen's flow law based on a scalar anisotropic enhancement factor. Such an enhancement factor depends upon the orientation mass density, that corresponds to the distribution of lattice orientations or simply to the orientation distribution function. The evolution of anisotropy is assumed to be modeled by the evolution of the orientation mass density, that is governed by the balance of mass of the present mixture with continuous diversity and explicitly depends upon four distinct effects interpreted, respectively, with grain rotation, local rigid body rotation, grain boundary migration (...
Followee Recommendation in Microblog Using Matrix Factorization Model with Structural Regularization
Directory of Open Access Journals (Sweden)
Yan Yu
2014-01-01
Full Text Available 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.
DEFF Research Database (Denmark)
Callot, Laurent; Kristensen, Johannes Tang
This paper shows that the parsimoniously time-varying methodology of Callot and Kristensen (2015) can be applied to factor models.We apply this method to study macroeconomic instability in the US from 1959:1 to 2006:4 with a particular focus on the Great Moderation. Models with parsimoniously time...... dimensional by construction and sparse by assumption, is estimated using the Lasso. We apply this method to the estimation of static factor models and factor augmented autoregressions using a set of 190 quarterly observations of 144 US macroeconomic series from Stock and Watson (2009).We find......-varying parameters are models with an unknown number of break points at unknown locations. The parameters are assumed to follow a random walk with a positive probability that an increment is exactly equal to zero so that the parameters do not vary at every point in time. The vector of increments, which is high...
2013-03-22
... AGENCY Draft Guidance for E85 Flexible Fuel Vehicle Weighting Factor for Model Years 2016-2019 Vehicles... determined by weighting the gasoline and E85 values of the model together using the specified factor (see 40... that EPA provide a weighting factor to use for 2016 and later model year vehicles. EPA has assessed the...
Research on Assessment Model of Information System Security Based on Various Security Factors
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
With the rapid development of network technology, the meaning of layers and attributes in respect of information system security must be extended based on the understanding of the concept of information system security. The layering model (LM) of information system security and the five-attribute model (FAM) based on security factors were put forward to perfect the description and modeling of the information system security framework. An effective framework system of risk calculation and assessment was proposed, which is based on FAM.
The pion electromagnetic form-factor in a QCD-inspired model
Pacheco-Bicudo-Cabral de Melo, J; Pace, E; Salmè, G
2004-01-01
We present detailed numerical results for the pion space-like electromagnetic form factor obtained within a recently proposed model of the pion electromagnetic current in a confining light-front QCD-inspired model. The model incorporates the vector meson dominance mechanism at the quark level, where the dressed photon with $q^+>0$ decay in an interacting quark-antiquark pair,wich absorbs the initial pion and produces the pion in the final state.
Directory of Open Access Journals (Sweden)
Feng Dong
Full Text Available China is considered to be the main carbon producer in the world. The per-capita carbon emissions indicator is an important measure of the regional carbon emissions situation. This study used the LMDI factor decomposition model-panel co-integration test two-step method to analyze the factors that affect per-capita carbon emissions. The main results are as follows. (1 During 1997, Eastern China, Central China, and Western China ranked first, second, and third in the per-capita carbon emissions, while in 2009 the pecking order changed to Eastern China, Western China, and Central China. (2 According to the LMDI decomposition results, the key driver boosting the per-capita carbon emissions in the three economic regions of China between 1997 and 2009 was economic development, and the energy efficiency was much greater than the energy structure after considering their effect on restraining increased per-capita carbon emissions. (3 Based on the decomposition, the factors that affected per-capita carbon emissions in the panel co-integration test showed that Central China had the best energy structure elasticity in its regional per-capita carbon emissions. Thus, Central China was ranked first for energy efficiency elasticity, while Western China was ranked first for economic development elasticity.
Dong, Feng; Long, Ruyin; Chen, Hong; Li, Xiaohui; Yang, Qingliang
2013-01-01
China is considered to be the main carbon producer in the world. The per-capita carbon emissions indicator is an important measure of the regional carbon emissions situation. This study used the LMDI factor decomposition model-panel co-integration test two-step method to analyze the factors that affect per-capita carbon emissions. The main results are as follows. (1) During 1997, Eastern China, Central China, and Western China ranked first, second, and third in the per-capita carbon emissions, while in 2009 the pecking order changed to Eastern China, Western China, and Central China. (2) According to the LMDI decomposition results, the key driver boosting the per-capita carbon emissions in the three economic regions of China between 1997 and 2009 was economic development, and the energy efficiency was much greater than the energy structure after considering their effect on restraining increased per-capita carbon emissions. (3) Based on the decomposition, the factors that affected per-capita carbon emissions in the panel co-integration test showed that Central China had the best energy structure elasticity in its regional per-capita carbon emissions. Thus, Central China was ranked first for energy efficiency elasticity, while Western China was ranked first for economic development elasticity.
Forecasting Multivariate Volatility using the VARFIMA Model on Realized Covariance Cholesky Factors
DEFF Research Database (Denmark)
Halbleib, Roxana; Voev, Valeri
2011-01-01
This paper analyzes the forecast accuracy of the multivariate realized volatility model introduced by Chiriac and Voev (2010), subject to different degrees of model parametrization and economic evaluation criteria. Bymodelling the Cholesky factors of the covariancematrices, the model generates...... positive definite, but biased covariance forecasts. In this paper, we provide empirical evidence that parsimonious versions of the model generate the best covariance forecasts in the absence of bias correction. Moreover, we show by means of stochastic dominance tests that any risk averse investor......, regardless of the type of utility function or return distribution, would be better-off from using this model than from using some standard approaches....
Moe, Donald Michael; Lallemand, Michael Scott; McClellan, John Mason; Smith, Joshua Porter; Marko, Shannon T; Eckert, Matthew J; Martin, Matthew J
2017-07-12
Bleeding is a leading cause of preventable death following severe injury. Prothrombin complex concentrates (PCC) treat inborn coagulation disorders and reverse oral anticoagulants, but are proposed for use in "factor-based" resuscitation strategies. Few studies exist for this indication in acidosis, or that compare 3-factor (3PCC) versus 4-factor (4PCC) products. We aimed to assess and compare their safety and efficacy in a porcine model of severe hemorrhagic shock and coagulopathy. Twenty-five adult Yorkshire swine underwent 35% volume hemorrhage, ischemia-reperfusion injury, and protocolized crystalloid resuscitation. Seventeen animals were randomized at 4 hours following model creation to receive a 45-IU/kg dose of either 3PCC or 4PCC. An additional 8 animals received autologous plasma transfusion prior to 4PCC to better characterize response to PCC. Individual factor levels were drawn at 4 and 6 hours. The model created significant acidosis with mean pH 7.21 and lactate of 9.6 mmol/L. Following PCC, 66.7% of 3PCC animals and 25% of 4PCC animals (regardless of plasma administration) developed consumptive coagulopathy. The animals that developed consumptive coagulopathy had manifested the "lethal triad" with lower temperatures (36.3 vs. 37.8°C), increased acidosis (pH 7.14 vs. 7.27, base excess -12.1 vs. -6.5 mEq/L), and worse coagulopathy (prothrombin time 17.1 vs. 14.6 seconds, fibrinogen 87.9 vs. 124.1 mg/dL) (all pfactors with transient improvement of prothrombin time, but there was significant depletion of fibrinogen and platelets with no lasting improvement of coagulopathy. PCC failed to correct coagulopathy and was associated with fibrinogen and platelet depletion. Of greater concern, PCC administration resulted in consumptive coagulopathy in the more severely ill animals. The incidence of consumptive coagulopathy was markedly increased with 3PCC versus 4PCC, and these products should be used with caution in this setting. II, therapeutic.
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.
A dynamic factor model of the evaluation of the financial crisis in Turkey.
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.
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.
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Haftu Hailu
2017-12-01
Full Text Available The purpose of the research is to identify critical success factors and model developing for sustaining kaizen implementation. Peacock shoe is one of the manufacturing industries in Ethiopia facing challenges on sustaining. The methodology followed is factor analysis and empirically testing hypothesis. A database was designed using SPSS version 20. The survey was validated using statistical validation using the Cronbach alpha index; the result is 0.908. The KMO index value was obtained for the 32 items and had a value of 0.642 with Bartlett's Test of Sphericity Approx. Chi-Square 4503.007, degree of freedom 496 and significance value 0.000. A factor analysis by principal components and varimax rotation was applied for finding the critical success factors. Finding designates that 32 items were merged into eight critical success factors. All the eight factors together explain for 76.941 % of the variance. Multiple regression model analysis has indicated that some of the critical success factors had relationship with success indicators. Due to constraint of time, the researcher focused only at peacock shoe manufacturing industry. Other limitation also includes the absence of any local research that shows the critical success factors at the moment.
Modeling and Analysis of Mechanical Quality Factor of the Resonator for Cylinder Vibratory Gyroscope
Institute of Scientific and Technical Information of China (English)
XI Xiang; WU Xuezhong; WU Yulie; ZHANG Yongmeng
2017-01-01
Mechanical Quality factor(Q factor) of the resonator is an important parameter for the cylinder vibratory gyroscope(CVG).Traditional analytical methods mainly focus on a partial energy loss during the vibration process of the CVG resonator,thus are not accurate for the mechanical Q factor prediction.Therefore an integrated model including air damping loss,surface defect loss,support loss,thermoelastic damping loss and internal friction loss is proposed to obtain the mechanical Q factor of the CVG resonator.Based on structural dynamics and energy dissipation analysis,the contribution of each energy loss to the total mechanical Q factor is quantificationally analyzed.For the resonator with radius ranging from 10 mm to 20 mm,its mechanical Q factor is mainly related to the support loss,thermoelastic damping loss and internal friction loss,which are fundamentally determined by the geometric sizes and material properties of the resonator.In addition,resonators made of alloy 3J53 (Ni42CrTiA1),with different sizes,were experimentally fabricated to test the mechanical Q factor.The theoretical model is well verified by the experimental data,thus provides an effective theoretical method to design and predict the mechanical Q factor of the CVG resonator.
Modeling and analysis of mechanical Quality factor of the resonator for cylinder vibratory gyroscope
Xi, Xiang; Wu, Xuezhong; Wu, Yulie; Zhang, Yongmeng
2016-08-01
Mechanical Quality factor(Q factor) of the resonator is an important parameter for the cylinder vibratory gyroscope(CVG). Traditional analytical methods mainly focus on a partial energy loss during the vibration process of the CVG resonator, thus are not accurate for the mechanical Q factor prediction. Therefore an integrated model including air damping loss, surface defect loss, support loss, thermoelastic damping loss and internal friction loss is proposed to obtain the mechanical Q factor of the CVG resonator. Based on structural dynamics and energy dissipation analysis, the contribution of each energy loss to the total mechanical Q factor is quantificationally analyzed. For the resonator with radius ranging from 10 mm to 20 mm, its mechanical Q factor is mainly related to the support loss, thermoelastic damping loss and internal friction loss, which are fundamentally determined by the geometric sizes and material properties of the resonator. In addition, resonators made of alloy 3J53 (Ni42CrTiAl), with different sizes, were experimentally fabricated to test the mechanical Q factor. The theoretical model is well verified by the experimental data, thus provides an effective theoretical method to design and predict the mechanical Q factor of the CVG resonator.
Modeling and projection of dengue fever cases in Guangzhou based on variation of weather factors.
Li, Chenlu; Wang, Xiaofeng; Wu, Xiaoxu; Liu, Jianing; Ji, Duoying; Du, Juan
2017-12-15
Dengue fever is one of the most serious vector-borne infectious diseases, especially in Guangzhou, China. Dengue viruses and their vectors Aedes albopictus are sensitive to climate change primarily in relation to weather factors. Previous research has mainly focused on identifying the relationship between climate factors and dengue cases, or developing dengue case models with some non-climate factors. However, there has been little research addressing the modeling and projection of dengue cases only from the perspective of climate change. This study considered this topic using long time series data (1998-2014). First, sensitive weather factors were identified through meta-analysis that included literature review screening, lagged analysis, and collinear analysis. Then, key factors that included monthly average temperature at a lag of two months, and monthly average relative humidity and monthly average precipitation at lags of three months were determined. Second, time series Poisson analysis was used with the generalized additive model approach to develop a dengue model based on key weather factors for January 1998 to December 2012. Data from January 2013 to July 2014 were used to validate that the model was reliable and reasonable. Finally, future weather data (January 2020 to December 2070) were input into the model to project the occurrence of dengue cases under different climate scenarios (RCP 2.6 and RCP 8.5). Longer time series analysis and scientifically selected weather variables were used to develop a dengue model to ensure reliability. The projections suggested that seasonal disease control (especially in summer and fall) and mitigation of greenhouse gas emissions could help reduce the incidence of dengue fever. The results of this study hope to provide a scientifically theoretical basis for the prevention and control of dengue fever in Guangzhou. Copyright © 2017 Elsevier B.V. All rights reserved.
Villar, Oscar Armando Esparza-Del; Montañez-Alvarado, Priscila; Gutiérrez-Vega, Marisela; Carrillo-Saucedo, Irene Concepción; Gurrola-Peña, Gloria Margarita; Ruvalcaba-Romero, Norma Alicia; García-Sánchez, María Dolores; Ochoa-Alcaraz, Sergio Gabriel
2017-03-01
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. 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. 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 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. The EHBMS is a validated scale that can be used to measure exercise based on the HBM in Mexican populations.
Behavioral analysis of EPA`s MOBILE emission factor model. Discussion paper
Energy Technology Data Exchange (ETDEWEB)
Harrington, W.; McConnell, V.D.; Cannon, M.
1998-06-01
This report provides a review and assessment of several important aspects of the MOBILE model, EPA`s computer model for estimating emission factors for mobile sources. Inventory models like MOBILE have many uses, but the authors focus primarily on the Model`s role for estimation of emission reduction credits from I/M [Inspection/Maintenance] programs. The authors concentrate on how the model incorporates behavioral responses to I/M regulations. The effectiveness of I/M programs in practice are likely to be strongly influenced by the behavior of motorists, mechanics and even state regulatory authorities. In addition to an examination of model structure and assumptions, the authors examine the empirical data used to calibrate the model, much of which is hard coded and not amenable to change by users. Finally, the authors test the sensitivity of MOBILE results to certain assumptions with behavioral content.
Learning a generative model of images by factoring appearance and shape.
Le Roux, Nicolas; Heess, Nicolas; Shotton, Jamie; Winn, John
2011-03-01
Computer vision has grown tremendously in the past two decades. Despite all efforts, existing attempts at matching parts of the human visual system's extraordinary ability to understand visual scenes lack either scope or power. By combining the advantages of general low-level generative models and powerful layer-based and hierarchical models, this work aims at being a first step toward richer, more flexible models of images. After comparing various types of restricted Boltzmann machines (RBMs) able to model continuous-valued data, we introduce our basic model, the masked RBM, which explicitly models occlusion boundaries in image patches by factoring the appearance of any patch region from its shape. We then propose a generative model of larger images using a field of such RBMs. Finally, we discuss how masked RBMs could be stacked to form a deep model able to generate more complicated structures and suitable for various tasks such as segmentation or object recognition.
Reliability Analysis of a Composite Blade Structure Using the Model Correction Factor Method
DEFF Research Database (Denmark)
Dimitrov, Nikolay Krasimiroy; Friis-Hansen, Peter; Berggreen, Christian
2010-01-01
This paper presents a reliability analysis of a composite blade profile. The so-called Model Correction Factor technique is applied as an effective alternate approach to the response surface technique. The structural reliability is determined by use of a simplified idealised analytical model which...... in a probabilistic sense is model corrected so that it, close to the design point, represents the same structural behaviour as a realistic FE model. This approach leads to considerable improvement of computational efficiency over classical response surface methods, because the numerically “cheap” idealistic model...... is used as the response surface, while the time-consuming detailed model is called only a few times until the simplified model is calibrated to the detailed model....
Sparse Probabilistic Parallel Factor Analysis for the Modeling of PET and Task-fMRI Data
DEFF Research Database (Denmark)
Beliveau, Vincent; Papoutsakis, Georgios; Hinrich, Jesper Løve
2017-01-01
interpretability of the results. Here we propose a variational Bayesian parallel factor analysis (VB-PARAFAC) model and an extension with sparse priors (SP-PARAFAC). Notably, our formulation admits time and subject specific noise modeling as well as subject specific offsets (i.e., mean values). We confirmed...... the validity of the models through simulation and performed exploratory analysis of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) data. Although more constrained, the proposed models performed similarly to more flexible models in approximating the PET data, which supports......Modern datasets are often multiway in nature and can contain patterns common to a mode of the data (e.g. space, time, and subjects). Multiway decomposition such as parallel factor analysis (PARAFAC) take into account the intrinsic structure of the data, and sparse versions of these methods improve...
Analysis on influencing factors of clinical teachers’ job satisfaction by structural equation model
Directory of Open Access Journals (Sweden)
Haiyi Jia
2017-02-01
Full Text Available [Research objective] Analyze the influencing factors of clinical teachers’ job satisfaction. [Research method] The ERG theory was used as the framework to design the questionnaires. Data were analyzed by structural equation model for investigating the influencing factors. [Research result] The modified model shows that factors of existence needs and growth needs have direct influence on the job satisfaction of clinical teachers, the influence coefficients are 0.540 and 0.380. The three influencing factors have positive effects on each other, and the correlation coefficients are 0.620, 0.400 and 0.330 respectively. [Research conclusion] Relevant departments should take active measures to improve job satisfaction of clinical teachers from two aspects: existence needs and growth needs, and to improve their work enthusiasm and teaching quality.
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.
Directory of Open Access Journals (Sweden)
J. G. Hemann
2009-01-01
Full Text Available A Positive Matrix Factorization receptor model for aerosol pollution source apportionment was fit to a synthetic dataset simulating one year of daily measurements of ambient PM_{2.5} concentrations, comprised of 39 chemical species from nine pollutant sources. A novel method was developed to estimate model fit uncertainty and bias at the daily time scale, as related to factor contributions. A circular block bootstrap is used to create replicate datasets, with the same receptor model then fit to the data. Neural networks are trained to classify factors based upon chemical profiles, as opposed to correlating contribution time series, and this classification is used to align factor orderings across the model results associated with the replicate datasets. Factor contribution uncertainty is assessed from the distribution of results associated with each factor. Comparing modeled factors with input factors used to create the synthetic data assesses bias. The results indicate that variability in factor contribution estimates does not necessarily encompass model error: contribution estimates can have small associated variability across results yet also be very biased. These findings are likely dependent on characteristics of the data.
Using a factor mixture modeling approach in alcohol dependence in a general population sample.
Kuo, Po-Hsiu; Aggen, Steven H; Prescott, Carol A; Kendler, Kenneth S; Neale, Michael C
2008-11-01
Alcohol dependence (AD) is a complex and heterogeneous disorder. The identification of more homogeneous subgroups of individuals with drinking problems and the refinement of the diagnostic criteria are inter-related research goals. They have the potential to improve our knowledge of etiology and treatment effects, and to assist in the identification of risk factors or specific genetic factors. Mixture modeling has advantages over traditional modeling that focuses on either the dimensional or categorical latent structure. The mixture modeling combines both latent class and latent trait models, but has not been widely applied in substance use research. The goal of the present study is to assess whether the AD criteria in the population could be better characterized by a continuous dimension, a few discrete subgroups, or a combination of the two. More than seven thousand participants were recruited from the population-based Virginia Twin Registry, and were interviewed to obtain DSM-IV (Diagnostic and Statistical Manual of Mental Disorder, version IV) symptoms and diagnosis of AD. We applied factor analysis, latent class analysis, and factor mixture models for symptom items based on the DSM-IV criteria. Our results showed that a mixture model with 1 factor and 3 classes for both genders fit well. The 3 classes were a non-problem drinking group and severe and moderate drinking problem groups. By contrast, models constrained to conform to DSM-IV diagnostic criteria were rejected by model fitting indices providing empirical evidence for heterogeneity in the AD diagnosis. Classification analysis showed different characteristics across subgroups, including alcohol-caused behavioral problems, comorbid disorders, age at onset for alcohol-related milestones, and personality. Clinically, the expanded classification of AD may aid in identifying suitable treatments, interventions and additional sources of comorbidity based on these more homogenous subgroups of alcohol use
$\\pi^0\\to\\gamma^*\\gamma$ transition form factor within Light Front Quark Model
Lih, Chong-Chung
2012-01-01
We study the transition form factor of $\\pi^0\\to\\gamma^* \\gamma$ as a function of the momentum transfer $Q^2$ within the light-front quark model (LFQM). We compare our result with the experimental data by BaBar as well as other calculations based on the LFQM in the literature. We show that our predicted form factor fits well with the experimental data, particularly those at the large $Q^2$ region.
Study of pesudoscalar transition form factors within light front quark model
Geng, Chao-Qiang
2012-01-01
We study the transition form factors of the pesudoscalar mesons ($\\pi,\\eta$ and $\\eta^{\\prime}$) as functions of the momentum transfer $Q^2$ within the light-front quark model. We compare our results with the recent experimental data by CELLO, CLEO, BaBar and Belle. By considering the possible uncertainties from the quark masses, we illustrate that our predicted form factors can fit with all the data, including those at the large $Q^2$ regions.
The relationship between the Five-Factor Model and latent DSM-IV personality disorder dimensions
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...
Components of Mathematics Anxiety: Factor Modeling of the MARS30-Brief
Belinda ePletzer; Guillerme eWood; Thomas eScherndl; Hubert Hannes Kerschbaum; Hans-Christoph eNuerk
2016-01-01
Mathematics anxiety involves feelings of tension, discomfort, high arousal, and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study. The Mathematics Anxiety Rating Scale (MARS) is a reliable meas...
A population pharmacokinetic model for perioperative dosing of factor VIII in hemophilia A patients
Hazendonk, Hendrika; Fijnvandraat, Karin; Lock, Janske; Driessens, Mariëtte; van der Meer, Felix; Meijer, Karina; Kruip, Marieke; Gorkom, Britta Laros-van; Peters, Marjolein; de Wildt, Saskia; Leebeek, Frank; Cnossen, Marjon; Mathôt, Ron
2016-01-01
The role of pharmacokinetic-guided dosing of factor concentrates in hemophilia is currently a subject of debate and focuses on long-term prophylactic treatment. Few data are available on its impact in the perioperative period. In this study, a population pharmacokinetic model for currently registered factor VIII concentrates was developed for severe and moderate adult and pediatric hemophilia A patients (FVIII levels hemophilia A patients by Bayesian adaptive dosing. PMID:27390359
The relationship between the Five-Factor Model and latent DSM-IV personality disorder dimensions
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...
Which psychological factors influence Internet addiction? Evidence through an integrative model
Burnay, Jonathan; Billieux, Joël; Blairy, Sylvie; Laroi, Frank
2015-01-01
Since the appearance of Internet, several preoccupations have appeared as a result, with Internet addiction being one of the most common. The goals of the present study were two-fold. First, to examine which psychological factors are relevant to explain Internet addiction, including impulsivity, passion and social provision. Second, to incorporate all these factors into an integrative model. Based on multiple regressions and path analysis, results revealed a positive relation between Internet...
PWSCC Growth Assessment Model Considering Stress Triaxiality Factor for Primary Alloy 600 Components
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Jong-Sung Kim
2016-08-01
Full Text Available We propose a primary water stress corrosion cracking (PWSCC initiation model of Alloy 600 that considers the stress triaxiality factor to apply to finite element analysis. We investigated the correlation between stress triaxiality effects and PWSCC growth behavior in cold-worked Alloy 600 stream generator tubes, and identified an additional stress triaxiality factor that can be added to Garud's PWSCC initiation model. By applying the proposed PWSCC initiation model considering the stress triaxiality factor, PWSCC growth simulations based on the macroscopic phenomenological damage mechanics approach were carried out on the PWSCC growth tests of various cold-worked Alloy 600 steam generator tubes and compact tension specimens. As a result, PWSCC growth behavior results from the finite element prediction are in good agreement with the experimental results.
Computational two-dimensional modeling of the stress intensity factor in a cracked metallic material
Rolón, J. E.; Cendales, E. D.; Cruz, I. M.
2016-02-01
Cracking of metallic engineering materials is of great importance due cost of replacing mechanical elements cracked and the danger of sudden structural failure of these elements. One of the most important parameters during consideration of the mechanical behavior of machine elements having cracking and that are subject to various stress conditions is the stress intensity factor near the crack tip called factor Kic. In this paper a computational model is developed for the direct assessment of stress concentration factor near to the crack tip and compared with the results obtained in the literature in which other models have been established, which consider continuity of the displacement of the crack tip (XBEM). Based on this numerical approximation can be establish that computational XBEM method has greater accuracy in Kic values obtained than the model implemented by the method of finite elements for the virtual nodal displacement through plateau function.
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.
Bora, Nalini S; Matta, Bharati; Lyzogubov, Valeriy V; Bora, Puran S
2015-02-01
Studies performed over the past decade in humans and experimental animals have been a major source of information and improved our understanding of how dysregulation of the complement system contributes to age-related macular degeneration (AMD) pathology. Drusen, the hall-mark of dry-type AMD are reported to be the by-product of complement mediated inflammatory processes. In wet AMD, unregulated complement activation results in increased production of angiogenic growth factors leading to choroidal neovascularization both in humans and in animal models. In this review article we have linked the complement system with modifiable and non-modifiable AMD risk factors as well as with prediction models of AMD. Understanding the association between the complement system, risk factors and prediction models will help improve our understanding of AMD pathology and management of this disease.
PWSCC growth assessment model considering stress triaxiality factor for primary alloy 600 components
Energy Technology Data Exchange (ETDEWEB)
Kim, Jong Sung [Dept. of Nuclear Engineering, Sejong University, Seoul (Korea, Republic of); Kim, Ji Soo; Jeon, Jun Young; Kim, Yun Jae [Dept. of of Mechanical Engineering, Korea University, Seoul (Korea, Republic of)
2016-08-15
We propose a primary water stress corrosion cracking (PWSCC) initiation model of Alloy 600 that considers the stress triaxiality factor to apply to finite element analysis. We investigated the correlation between stress triaxiality effects and PWSCC growth behavior in cold-worked Alloy 600 stream generator tubes, and identified an additional stress triaxiality factor that can be added to Garud's PWSCC initiation model. By applying the proposed PWSCC initiation model considering the stress triaxiality factor, PWSCC growth simulations based on the macroscopic phenomenological damage mechanics approach were carried out on the PWSCC growth tests of various cold-worked Alloy 600 steam generator tubes and compact tension specimens. As a result, PWSCC growth behavior results from the finite element prediction are in good agreement with the experimental results.
DEFF Research Database (Denmark)
Appelt, Ane L; Vogelius, Ivan R.; Farr, Katherina P.
2014-01-01
Background. Understanding the dose-response of the lung in order to minimize the risk of radiation pneumonitis (RP) is critical for optimization of lung cancer radiotherapy. We propose a method to combine the dose-response relationship for RP in the landmark QUANTEC paper with known clinical risk......-only QUANTEC model and the model including risk factors. Subdistribution cumulative incidence functions were compared for patients with high/low-risk predictions from the two models, and concordance indices (c-indices) for the prediction of RP were calculated. Results. The reference dose- response relationship...... factors, in order to enable individual risk prediction. The approach is validated in an independent dataset. Material and methods. The prevalence of risk factors in the patient populations underlying the QUANTEC analysis was estimated, and a previously published method to adjust dose...
Murphy, Kelly E.
2012-01-13
Fibroblasts and their activated phenotype, myofibroblasts, are the primary cell types involved in the contraction associated with dermal wound healing. Recent experimental evidence indicates that the transformation from fibroblasts to myofibroblasts involves two distinct processes: The cells are stimulated to change phenotype by the combined actions of transforming growth factor β (TGFβ) and mechanical tension. This observation indicates a need for a detailed exploration of the effect of the strong interactions between the mechanical changes and growth factors in dermal wound healing. We review the experimental findings in detail and develop a model of dermal wound healing that incorporates these phenomena. Our model includes the interactions between TGFβ and collagenase, providing a more biologically realistic form for the growth factor kinetics than those included in previous mechanochemical descriptions. A comparison is made between the model predictions and experimental data on human dermal wound healing and all the essential features are well matched. © 2012 Society for Mathematical Biology.
DEFF Research Database (Denmark)
Franchin, P.; Ditlevsen, Ove Dalager; Kiureghian, Armen Der
2002-01-01
The model correction factor method (MCFM) is used in conjunction with the first-order reliability method (FORM) to solve structural reliability problems involving integrals of non-Gaussian random fields. The approach replaces the limit-state function with an idealized one, in which the integrals...... are considered to be Gaussian. Conventional FORM analysis yields the linearization point of the idealized limit-state surface. A model correction factor is then introduced to push the idealized limit-state surface onto the actual limit-state surface. A few iterations yield a good approximation of the reliability...... reliability method; Model correction factor method; Nataf field integration; Non-Gaussion random field; Random field integration; Structural reliability; Pile foundation reliability...
Bühler, Joël; Keller, Ferdinand; Läge, Damian
2014-09-01
An adequate assessment of depression has been of concern to many researchers over the last half-century. These efforts have brought forth a manifold of depression rating scales, of which the Beck Depression Inventory (BDI) is 1 of the most commonly used self-assessment scales. Since its revision, the item structure of the BDI-II has been examined in many factor analytic studies, yet it has not been possible to achieve a consensus about the underlying factor structure. Recent findings from a nonmetric multidimensional scaling (NMDS) analysis (Bühler, Keller, & Läge, 2012) of the German norming sample of the BDI-II emphasized a structure with different qualitative aspects of depression, which suggested that the existing factor models do not adequately represent the data. The NMDS results were reviewed, and on the basis of these findings, a different factor model is proposed. In contrast to the common factor models in the literature, the presented model includes an additional factor, which is associated with the activation level of the BDI-II symptoms. The model was evaluated with a 2nd sample of patients diagnosed with a primary affective disorder (N = 569) and obtained good fit indices that even exceeded the fit of the most reliable factor model (Ward, 2006) described in the literature so far. Furthermore, emphasis is placed on the methodological question of how factor models may be derived from the results of NMDS analyses. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Li, Li; Brumback, Babette A; Weppelmann, Thomas A; Morris, J Glenn; Ali, Afsar
2016-08-15
Motivated by an investigation of the effect of surface water temperature on the presence of Vibrio cholerae in water samples collected from different fixed surface water monitoring sites in Haiti in different months, we investigated methods to adjust for unmeasured confounding due to either of the two crossed factors site and month. In the process, we extended previous methods that adjust for unmeasured confounding due to one nesting factor (such as site, which nests the water samples from different months) to the case of two crossed factors. First, we developed a conditional pseudolikelihood estimator that eliminates fixed effects for the levels of each of the crossed factors from the estimating equation. Using the theory of U-Statistics for independent but non-identically distributed vectors, we show that our estimator is consistent and asymptotically normal, but that its variance depends on the nuisance parameters and thus cannot be easily estimated. Consequently, we apply our estimator in conjunction with a permutation test, and we investigate use of the pigeonhole bootstrap and the jackknife for constructing confidence intervals. We also incorporate our estimator into a diagnostic test for a logistic mixed model with crossed random effects and no unmeasured confounding. For comparison, we investigate between-within models extended to two crossed factors. These generalized linear mixed models include covariate means for each level of each factor in order to adjust for the unmeasured confounding. We conduct simulation studies, and we apply the methods to the Haitian data. Copyright © 2016 John Wiley & Sons, Ltd.
Application of Molecular Modeling to Development of New Factor Xa Inhibitors
Directory of Open Access Journals (Sweden)
Vladimir B. Sulimov
2015-01-01
Full Text Available In consequence of the key role of factor Xa in the clotting cascade and absence of its activity in the processes that do not affect coagulation, this protein is an attractive target for development of new blood coagulation inhibitors. Factor Xa is more effective and convenient target for creation of anticoagulants than thrombin, inhibition of which may cause some side effects. This study is aimed at finding new inhibitors of factor Xa by molecular computer modeling including docking SOL and postdocking optimization DISCORE programs. After validation of molecular modeling methods on well-known factor Xa inhibitors the virtual screening of NCI Diversity and Voronezh State University databases of ready-made low molecular weight species has been carried out. Seventeen compounds selected on the basis of modeling results have been tested experimentally in vitro. It has been found that 12 of them showed activity against factor Xa (IC50 = 1.8–40 μM. Based on analysis of the results, the new original compound was synthesized and experimentally verified. It shows activity against factor Xa with IC50 value of 0.7 μM.
Honesty-humility, the big five, and the five-factor model.
Ashton, Michael C; Lee, Kibeom
2005-10-01
This study investigated the relations of the proposed sixth factor of personality, Honesty-Humility, with the dimensions of the classic English lexical Big Five and the closely related Five-Factor Model (FFM). Results showed that although Honesty-Humility was largely unrelated to markers of the Big Five factors, it was substantially correlated with the FFM Agreeableness domain. This relation was largely due to the Straightforwardness and Modesty facets of FFM Agreeableness, which were only weakly correlated with the Big Five version of Agreeableness. A realignment of FFM facets to produce separate Honesty-Humility and Agreeableness factors provided better prediction of personality variables that involve deceit without hostility, such as Social Adroitness and Self-Monitoring. Results indicate the importance of assessing Honesty-Humility as a separate factor.
Directory of Open Access Journals (Sweden)
Md. Abdul Jalil
2013-01-01
Full Text Available The study explores the critical factors that influence financial planning after retirement among Malaysians, an area which has somewhat been largely overlooked by the extant literature. The study has used a quantitative method to survey a sample of 170 Malaysian citizens, from various places in the Klang Valley area. Exploratory factor analysis, confirmatory factor analysis and structural equation modeling were used to analyze the data. The results suggest that the paths are interrelated to the casual processes significantly. Furthermore, individualâs income or monthly salary is found to be the most important factor influencing financial planning, followed by attitude and culture. The results are mainly favourable to academics and practitioners in Malaysia by contributing an understanding into critical factors that influence people to make financial plan before their retirement. The study provides implications of the findings in the concluding section.
Risk factor selection in rate making: EM adaptive LASSO for zero-inflated poisson regression models.
Tang, Yanlin; Xiang, Liya; Zhu, Zhongyi
2014-06-01
Risk factor selection is very important in the insurance industry, which helps precise rate making and studying the features of high-quality insureds. Zero-inflated data are common in insurance, such as the claim frequency data, and zero-inflation makes the selection of risk factors quite difficult. In this article, we propose a new risk factor selection approach, EM adaptive LASSO, for a zero-inflated Poisson regression model, which combines the EM algorithm and adaptive LASSO penalty. Under some regularity conditions, we show that, with probability approaching 1, important factors are selected and the redundant factors are excluded. We investigate the finite sample performance of the proposed method through a simulation study and the analysis of car insurance data from SAS Enterprise Miner database.
Directory of Open Access Journals (Sweden)
Javali Shivalingappa
2010-01-01
Full Text Available Aim: The study aimed to determine the factors associated with periodontal disease (different levels of severity by using different regression models for ordinal data. Design: A cross-sectional design was employed using clinical examination and ′questionnaire with interview′ method. Materials and Methods: The study was conducted during June 2008 to October 2008 in Dharwad, Karnataka, India. It involved a systematic random sample of 1760 individuals aged 18-40 years. The periodontal disease examination was conducted by using Community Periodontal Index for Treatment Needs (CPITN. Statistical Analysis Used: Regression models for ordinal data with different built-in link functions were used in determination of factors associated with periodontal disease. Results: The study findings indicated that, the ordinal regression models with four built-in link functions (logit, probit, Clog-log and nlog-log displayed similar results with negligible differences in significant factors associated with periodontal disease. The factors such as religion, caste, sources of drinking water, Timings for sweet consumption, Timings for cleaning or brushing the teeth and materials used for brushing teeth were significantly associated with periodontal disease in all ordinal models. Conclusions: The ordinal regression model with Clog-log is a better fit in determination of significant factors associated with periodontal disease as compared to models with logit, probit and nlog-log built-in link functions. The factors such as caste and time for sweet consumption are negatively associated with periodontal disease. But religion, sources of drinking water, Timings for cleaning or brushing the teeth and materials used for brushing teeth are significantly and positively associated with periodontal disease.
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).
A Primary Human Critical Success Factors Model for the ERP System Implementation
Directory of Open Access Journals (Sweden)
Jenko Aleksander
2016-08-01
Full Text Available Background and Purpose: Many researchers have investigated various Critical success factors (CSFs and the different causes of ERP implementation project failures. Despite a detailed literature preview, we were unable to find an appropriate research with a comprehensive overview of the true causes behind CSFs, observed from a human factors perspective. The objective of this research was therefore to develop and evaluate the Primary human factors (PHFs model and to confirm the significant impact of PHFs on traditional CSFs and on the project success.
Pion Form Factor in Chiral Limit of Hard-Wall AdS/QCD Model
Energy Technology Data Exchange (ETDEWEB)
Anatoly Radyushkin; Hovhannes Grigoryan
2007-12-01
We develop a formalism to calculate form factor and charge density distribution of pion in the chiral limit using the holographic dual model of QCD with hard-wall cutoff. We introduce two conjugate pion wave functions and present analytic expressions for these functions and for the pion form factor. They allow to relate such observables as the pion decay constant and the pion charge electric radius to the values of chiral condensate and hard-wall cutoff scale. The evolution of the pion form factor to large values of the momentum transfer is discussed, and results are compared to existing experimental data.
Probabilistic Multi-Factor Interaction Model for Evaluating Continuous Smooth Curves
Chamis, Christos C.
2009-01-01
The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from launch external tanks. The MFIM 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. They are selected so that the MFIM will generate a common curve to fit the individual point data. The results show that the approach used generates the continuous curve.
Latent variable modelling of risk factors associated with childhood diseases: Case study for Nigeria
Directory of Open Access Journals (Sweden)
Khaled Khatab
2011-09-01
Full Text Available Objective: To investigate the impact of various bio-demographic and socio-economic variables on joint childhood diseases in Nigeria with flexible geoadditive probit models. Methods: Geoadditive latent variable model (LVM was applied where the three observable disease (diarrhea, cough, fever variables were modelled as indicators for the latent individual variable "health status" or "frailty" of a child. This modelling approach allowed us to investigate the common influence of risk factors on individual frailties of children, thereby automatically accounting for association between diseases as indicators for health status. The LVM extended to analyze the impact of risk factors and the spatial effects on the unobservable variable “health status ” of a child less than 5 years of age using the 2003 Demographic and Health Surveys (DHS data for Nigeria. Results: The results suggest some strong underlying spatial patterns of the three ailments with a clear southeastern divide of childhood morbidities and this might be the results in the overlapping of the various risk factors. Conclusions: Comorbidity with conditions such as cough, diarrhoea and fever is common in Nigeria. However, little is known about common risk factors and geographical overlaps in these illnesses. The search for overlapping common risk factors and their spatial effects may improve our understanding of the etiology of diseases for efficient and cost-effective control and planning of the three ailments.
Bishop, Malachy; Rumrill, Phillip D; Roessler, Richard T
2015-01-01
This article presents a replication of Rumrill, Roessler, and Fitzgerald's 2004 analysis of a three-factor model of the impact of multiple sclerosis (MS) on quality of life (QOL). The three factors in the original model included illness-related, employment-related, and psychosocial adjustment factors. To test hypothesized relationships between QOL and illness-related, employment-related, and psychosocial variables using data from a survey of the employment concerns of Americans with MS (N = 1,839). An ex post facto, multiple correlational design was employed incorporating correlational and multiple regression analyses. QOL was positively related to educational level, employment status, job satisfaction, and job-match, and negatively related to number of symptoms, severity of symptoms, and perceived stress level. The three-factor model explained approximately 37 percent of the variance in QOL scores. The results of this replication confirm the continuing value of the three-factor model for predicting the QOL of adults with MS, and demonstrate the importance of medical, mental health, and vocational rehabilitation interventions and services in promoting QOL.
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.
Fama and French Three-Factor Model: Evidence from Istanbul Stock Exchange
Directory of Open Access Journals (Sweden)
Veysel Eraslan
2013-04-01
Full Text Available This study tests the validity of the Fama and French three-factor asset pricing model on the Istanbul Stock Exchange (ISE. Monthly excess stock returns over the period from 2003 to 2010 are used in the analysis. Realized returns show that portfolios containing large firms have higher average excess returns than portfolios containing smaller sized firms. Generally, portfolios containing low book-to-market ratio firms perform better than those containing high book-to-market ratio firms. Nine portfolios are constructed according to size and book-to-market ratio of firms in order to explain the variations on excess portfolio returns by using market risk factor, size risk factor and book-to-market ratio risk factors. Size factor has no effect on portfolios having big-size firms but can explain the excess return variations on portfolios having small and medium-sized firms. Book-to-market ratio factor has an effect on portfolios with high book-to-market ratio firms. Fama and French three-factor model has power on explaining variations on excess portfolio returns but this power is not strong throughout the test period on the ISE.
Institute of Scientific and Technical Information of China (English)
ZHANG Xiaodong; LI Yingzi; ZHANG Zhiqiang
2007-01-01
Aiming at the levels of collaborative degree in web-based product development,a collaboration hierarchy model of this product development is developed in this paper.Based on the model,the affecting factors on collaboration levels are analyzed systematically from many aspects,such as technology,organization and business.A gap analysis method is studied in detail,and is applied in a real project.The application shows that it can solve the diverse problems of collaborative product development effectively,and help enterprises find out the critical factors that affect the collaboration.
Bozhalkina, Yana; Timofeeva, Galina
2016-12-01
Mathematical model of loan portfolio in the form of a controlled Markov chain with discrete time is considered. It is assumed that coefficients of migration matrix depend on corrective actions and external factors. Corrective actions include process of receiving applications, interaction with existing solvent and insolvent clients. External factors are macroeconomic indicators, such as inflation and unemployment rates, exchange rates, consumer price indices, etc. Changes in corrective actions adjust the intensity of transitions in the migration matrix. The mathematical model for forecasting the credit portfolio structure taking into account a cumulative impact of internal and external changes is obtained.
Light-Front Model of Transition Form-Factors in Heavy Meson Decay
de Melo, J P B C
2010-01-01
Electroweak transition form factors of heavy meson decays are important ingredients in the extraction of the Cabibbo-Kobayashi-Maskawa (CKM) matrix elements from experimental data. In this work, within a light-front framework, we calculate electroweak transition form factor for the semileptonic decay of $D$ mesons into a pion or a kaon. The model results underestimate in both cases the new data of CLEO for the larger momentum transfers accessible in the experiment. We discuss possible reasons for that in order to improve the model.
Integrals of random fields treated by the model correction factor method
DEFF Research Database (Denmark)
Franchin, P.; Ditlevsen, Ove Dalager; Kiureghian, Armen Der
2002-01-01
The model correction factor method (MCFM) is used in conjunction with the first-order reliability method (FORM) to solve structural reliability problems involving integrals of non-Gaussian random fields. The approach replaces the limit-state function with an idealized one, in which the integrals...... are considered to be Gaussian. Conventional FORM analysis yields the linearization point of the idealized limit-state surface. A model correction factor is then introduced to push the idealized limit-state surface onto the actual limit-state surface. A few iterations yield a good approximation of the reliability...
Maximum Likelihood Estimation of Time-Varying Loadings in High-Dimensional Factor Models
DEFF Research Database (Denmark)
Mikkelsen, Jakob Guldbæk; Hillebrand, Eric; Urga, Giovanni
In this paper, we develop a maximum likelihood estimator of time-varying loadings in high-dimensional factor models. We specify the loadings to evolve as stationary vector autoregressions (VAR) and show that consistent estimates of the loadings parameters can be obtained by a two-step maximum...... likelihood estimation procedure. In the first step, principal components are extracted from the data to form factor estimates. In the second step, the parameters of the loadings VARs are estimated as a set of univariate regression models with time-varying coefficients. We document the finite...
Perry, John L.; Nicholls, Adam R.; Clough, Peter J.; Crust, Lee
2015-01-01
Despite the limitations of overgeneralizing cutoff values for confirmatory factor analysis (CFA; e.g., Marsh, Hau, & Wen, 2004), they are still often employed as golden rules for assessing factorial validity in sport and exercise psychology. The purpose of this study was to investigate the appropriateness of using the CFA approach with these…
Use of pharmacokinetic modelling to individualize FFP dosing in factor V deficiency.
Shakhnovich, V; Daniel, J; Wicklund, B; Kearns, G; Neville, K
2013-03-01
Therapy with fresh frozen plasma (FFP) confers serious risks, such as contraction of blood-borne viruses, allergic reaction, volume overload and development of alloantibodies. The aim of this study was to apply principles of pharmacokinetic (PK) modelling to individual factor content of FFP to optimize individualized dosing, while minimizing potential risks of therapy. We used PK modelling to successfully target individual factor replacement in an 8-month-old patient receiving FFP for treatment of a severe congenital factor V (FV) deficiency. The model fit for the FV activity vs. time data was excellent (r = 0.98) and the model accurately predicted FV activity during the intraoperative and postoperative period. Accurate PK modelling of individual factor activity in FFP has the potential to provide better targeted therapy, enabling clinicians to more precisely dose patients requiring coagulation products, while avoiding wasteful and expensive product overtreatment, minimizing potentially life-threatening complications due to undertreatment and limiting harmful product-associated risks.
HOCOMOCO: A comprehensive collection of human transcription factor binding sites models
Kulakovskiy, Ivan V.
2012-11-21
Transcription factor (TF) binding site (TFBS) models are crucial for computational reconstruction of transcription regulatory networks. In existing repositories, a TF often has several models (also called binding profiles or motifs), obtained from different experimental data. Having a single TFBS model for a TF is more pragmatic for practical applications. We show that integration of TFBS data from various types of experiments into a single model typically results in the improved model quality probably due to partial correction of source specific technique bias. We present the Homo sapiens comprehensive model collection (HOCOMOCO, http://autosome.ru/HOCOMOCO/, http://cbrc.kaust.edu.sa/ hocomoco/) containing carefully hand-curated TFBS models constructed by integration of binding sequences obtained by both low- and high-throughput methods. To construct position weight matrices to represent these TFBS models, we used ChIPMunk software in four computational modes, including newly developed periodic positional prior mode associated with DNA helix pitch. We selected only one TFBS model per TF, unless there was a clear experimental evidence for two rather distinct TFBS models. We assigned a quality rating to each model. HOCOMOCO contains 426 systematically curated TFBS models for 401 human TFs, where 172 models are based on more than one data source. The Author(s) 2012.
HOCOMOCO: a comprehensive collection of human transcription factor binding sites models
Kulakovskiy, Ivan V.; Medvedeva, Yulia A.; Schaefer, Ulf; Kasianov, Artem S.; Vorontsov, Ilya E.; Bajic, Vladimir B.; Makeev, Vsevolod J.
2013-01-01
Transcription factor (TF) binding site (TFBS) models are crucial for computational reconstruction of transcription regulatory networks. In existing repositories, a TF often has several models (also called binding profiles or motifs), obtained from different experimental data. Having a single TFBS model for a TF is more pragmatic for practical applications. We show that integration of TFBS data from various types of experiments into a single model typically results in the improved model quality probably due to partial correction of source specific technique bias. We present the Homo sapiens comprehensive model collection (HOCOMOCO, http://autosome.ru/HOCOMOCO/, http://cbrc.kaust.edu.sa/hocomoco/) containing carefully hand-curated TFBS models constructed by integration of binding sequences obtained by both low- and high-throughput methods. To construct position weight matrices to represent these TFBS models, we used ChIPMunk software in four computational modes, including newly developed periodic positional prior mode associated with DNA helix pitch. We selected only one TFBS model per TF, unless there was a clear experimental evidence for two rather distinct TFBS models. We assigned a quality rating to each model. HOCOMOCO contains 426 systematically curated TFBS models for 401 human TFs, where 172 models are based on more than one data source. PMID:23175603
How Do Various Maize Crop Models Vary in Their Responses to Climate Change Factors?
Bassu, Simona; Brisson, Nadine; Grassini, Patricio; Durand, Jean-Louis; Boote, Kenneth; Lizaso, Jon; Jones, James W.; Rosenzweig, Cynthia; Ruane, Alex C.; Adam, Myriam; Baron, Christian; Basso, Bruno; Biernath, Christian; Boogaard, Hendrik; Conijn, Sjaak; Corbeels, Marc; Deryng, Delphine; DeSanctis, Giacomo; Gayler, Sebastian; Grassini, Patricio; Hatfield, Jerry; Hoek, Steven; Izaurralde, Cesar; Jongschaap, Raymond; Kemanian, Armen R.; Kersebaum, K. Christian
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.
A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas
Directory of Open Access Journals (Sweden)
R. Whitley
2015-12-01
Full Text Available Savanna ecosystems are one of the most dominant and complex terrestrial biomes that derives from a distinct vegetative surface comprised of co-dominant tree and grass populations. While these two vegetation types co-exist functionally, demographically they are not static, but are dynamically changing in response to environmental forces such as annual fire events and rainfall variability. Modelling savanna environments with the current generation of terrestrial biosphere models (TBMs has presented many problems, particularly describing fire frequency and intensity, phenology, leaf biochemistry of C3 and C4 photosynthesis vegetation, and root water uptake. In order to better understand why TBMs perform so poorly in savannas, we conducted a model inter-comparison of 6 TBMs and assessed their performance at simulating latent energy (LE and gross primary productivity (GPP for five savanna sites along a rainfall gradient in northern Australia. Performance in predicting LE and GPP was measured using an empirical benchmarking system, which ranks models by their ability to utilise meteorological driving information to predict the fluxes. On average, the TBMs performed as well as a multi-linear regression of the fluxes against solar radiation, temperature and vapour pressure deficit, but were outperformed by a more complicated nonlinear response model that also included the leaf area index (LAI. This identified that the TBMs are not fully utilising their input information effectively in determining savanna LE and GPP, and highlights that savanna dynamics cannot be calibrated into models and that there are problems in underlying model processes. We identified key weaknesses in a model's ability to simulate savanna fluxes and their seasonal variation, related to the representation of vegetation by the models and root water uptake. We underline these weaknesses in terms of three critical areas for development. First, prescribed tree-rooting depths must be
A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas
Whitley, Rhys; Beringer, Jason; Hutley, Lindsay B.; Abramowitz, Gab; De Kauwe, Martin G.; Duursma, Remko; Evans, Bradley; Haverd, Vanessa; Li, Longhui; Ryu, Youngryel; Smith, Benjamin; Wang, Ying-Ping; Williams, Mathew; Yu, Qiang
2016-06-01
The savanna ecosystem is one of the most dominant and complex terrestrial biomes, deriving from a distinct vegetative surface comprised of co-dominant tree and grass populations. While these two vegetation types co-exist functionally, demographically they are not static but are dynamically changing in response to environmental forces such as annual fire events and rainfall variability. Modelling savanna environments with the current generation of terrestrial biosphere models (TBMs) has presented many problems, particularly describing fire frequency and intensity, phenology, leaf biochemistry of C3 and C4 photosynthesis vegetation, and root-water uptake. In order to better understand why TBMs perform so poorly in savannas, we conducted a model inter-comparison of six TBMs and assessed their performance at simulating latent energy (LE) and gross primary productivity (GPP) for five savanna sites along a rainfall gradient in northern Australia. Performance in predicting LE and GPP was measured using an empirical benchmarking system, which ranks models by their ability to utilise meteorological driving information to predict the fluxes. On average, the TBMs performed as well as a multi-linear regression of the fluxes against solar radiation, temperature and vapour pressure deficit but were outperformed by a more complicated nonlinear response model that also included the leaf area index (LAI). This identified that the TBMs are not fully utilising their input information effectively in determining savanna LE and GPP and highlights that savanna dynamics cannot be calibrated into models and that there are problems in underlying model processes. We identified key weaknesses in a model's ability to simulate savanna fluxes and their seasonal variation, related to the representation of vegetation by the models and root-water uptake. We underline these weaknesses in terms of three critical areas for development. First, prescribed tree-rooting depths must be deep enough
The Five-Factor Model of personality disorder and DSM-5.
Trull, Timothy J
2012-12-01
The Five-Factor Model of personality disorders (FFMPD; Widiger & Mullins-Sweatt, ) developed from the recognition that the popular Five-Factor Model (FFM) of personality could be used to describe and understand the official personality disorder (PD) constructs from the American Psychiatric Association's (APA) diagnostic manuals (e.g., DSM-IV-TR, APA, ). This article provides an overview of the FFM, highlighting its validity and utility in characterizing PDs as well as its ability to provide a comprehensive account of personality pathology in general. In 2013, DSM-5 is scheduled to appear, and the "hybrid" PD proposal will emphasize a 25-personality trait model. I present the current version of this new model, compare it to the FFMPD, and discuss issues related to the implementation of the FFMPD.
Water retention of rigid soils from a two-factor model for clay
Chertkov, V Y
2014-01-01
Water retention is one of the key soil characteristics. Available models of soil water retention relate to the curve-fitting type. The objective of this work is to suggest a physical model of water retention (drying branch) for soils with a rigid matrix. "Physical" means the prediction based on the a priori measured or estimated soil parameters with a clear physical meaning. We rely on the two-factor model of clay that takes into account the factors of capillarity and shrinkage. The key points of the model to be proposed are some weak pseudo shrinkage that the rigid soils demonstrate according to their experimental water retention curves, and some specific properties of the rigid grain matrix. The three input parameters for prediction of soil water retention with the rigid grain matrix include inter-grain porosity, as well as maximum and minimum grain sizes. The comparison between measured and predicted sand water retention curves for four different sands is promising.
English, Sinéad; Bateman, Andrew W; Clutton-Brock, Tim H
2012-05-01
Lifetime records of changes in individual size or mass in wild animals are scarce and, as such, few studies have attempted to model variation in these traits across the lifespan or to assess the factors that affect them. However, quantifying lifetime growth is essential for understanding trade-offs between growth and other life history parameters, such as reproductive performance or survival. Here, we used model selection based on information theory to measure changes in body mass over the lifespan of wild meerkats, and compared the relative fits of several standard growth models (monomolecular, von Bertalanffy, Gompertz, logistic and Richards). We found that meerkats exhibit monomolecular growth, with the best model incorporating separate growth rates before and after nutritional independence, as well as effects of season and total rainfall in the previous nine months. Our study demonstrates how simple growth curves may be improved by considering life history and environmental factors, which may be particularly relevant when quantifying growth patterns in wild populations.
Five-factor model of personality and job satisfaction: a meta-analysis.
Judge, Timothy A; Heller, Daniel; Mount, Michael K
2002-06-01
This study reports results of a meta-analysis linking traits from the 5-factor model of personality to overall job satisfaction. Using the model as an organizing framework, 334 correlations from 163 independent samples were classified according to the model. The estimated true score correlations with job satisfaction were -.29 for Neuroticism, .25 for Extraversion, .02 for Openness to Experience, .17 for Agreeableness, and .26 for Conscientiousness. Results further indicated that only the relations of Neuroticism and Extraversion with job satisfaction generalized across studies. As a set, the Big Five traits had a multiple correlation of .41 with job satisfaction, indicating support for the validity of the dispositional source of job satisfaction when traits are organized according to the 5-factor model.
Stochastic Optimization of Wind Turbine Power Factor Using Stochastic Model of Wind Power
DEFF Research Database (Denmark)
Chen, Peiyuan; Siano, Pierluigi; Bak-Jensen, Birgitte
2010-01-01
. The optimization algorithm utilizes the stochastic models of wind power generation (WPG) and load demand to take into account their stochastic variation. The stochastic model of WPG is developed on the basis of a limited autoregressive integrated moving average (LARIMA) model by introducing a crosscorrelation......This paper proposes a stochastic optimization algorithm that aims to minimize the expectation of the system power losses by controlling wind turbine (WT) power factors. This objective of the optimization is subject to the probability constraints of bus voltage and line current requirements...... structure to the LARIMA model. The proposed stochastic optimization is carried out on a 69-bus distribution system. Simulation results confirm that, under various combinations of WPG and load demand, the system power losses are considerably reduced with the optimal setting of WT power factor as compared...
Dynamic order reduction of thin-film deposition kinetics models: A reaction factorization approach
Energy Technology Data Exchange (ETDEWEB)
Adomaitis, Raymond A., E-mail: adomaiti@umd.edu [Department of Chemical and Biomolecular Engineering, Institute for Systems Research, University of Maryland, College Park, Maryland 20742 (United States)
2016-01-15
A set of numerical tools for the analysis and dynamic dimension reduction of chemical vapor and atomic layer deposition (ALD) surface reaction models is developed in this work. The approach is based on a two-step process where in the first, the chemical species surface balance dynamic equations are factored to effectively decouple the (nonlinear) reaction rates, a process that eliminates redundant dynamic modes and that identifies conserved quantities. If successful, the second phase is implemented to factor out redundant dynamic modes when species relatively minor in concentration are omitted; if unsuccessful, the technique points to potential model structural problems. An alumina ALD process is used for an example consisting of 19 reactions and 23 surface and gas-phase species. Using the approach developed, the model is reduced by nineteen modes to a four-dimensional dynamic system without any knowledge of the reaction rate values. Results are interpreted in the context of potential model validation studies.
Extraction and interpretation of gammaN-->Delta form factors within a dynamical model
Energy Technology Data Exchange (ETDEWEB)
B. Juliá-Díaz, T.-S. H. Lee, T. Sato, and L. C. Smith
2007-01-01
Within the dynamical model of Refs. [Phys. Rev. C54, 2660 (1996); C63, 055201 (2001)], we perform an analysis of recent data of pion electroproduction reactions at energies near the {Delta}(1232) resonance. We discuss possible interpretations of the extracted bare and dressed {gamma} N {yields} {Delta} form factors in terms of relativistic constituent quark models and Lattice QCD calculations. Possible future developments are discussed.
Boundary form factors in the Smirnov--Fateev model with a diagonal boundary $S$ matrix
Lashkevich, Michael
2008-01-01
The boundary conditions with diagonal boundary $S$ matrix and the boundary form factors for the Smirnov--Fateev model on a half line has been considered in the framework of the free field representation. In contrast to the case of the sine-Gordon model, in this case the free field representation is shown to impose severe restrictions on the boundary $S$ matrix, so that a finite number of solutions is only consistent with the free field realization.
Exact solutions of a Flat Full Causal Bulk viscous FRW cosmological model through factorization
Cornejo-Pérez, O
2012-01-01
We study the classical flat full causal bulk viscous FRW cosmological model through the factorization method. The method allows to find some new exact parametric solutions for different values of the viscous parameter $s$. Special attention is given to the well known case $s=1/2$, for which the cosmological model admits scaling symmetries. Also, some exact parametric solutions for $s=1/2$ are obtained through the Lie group method.
De Sanctis, M; Santopinto, E; Vassallo, A
2015-01-01
We briefly describe our relativistic quark-diquark model, developed within the framework of point form dynamics, which is the relativistic extension of the interacting quark-diquark model. In order to do that we have to show the main properties and quantum numbers of the effective degree of freedom of constituent diquark. Our results for the nonstrange baryon spectrum and for the nucleon electromagnetic form factors are discussed.
Antecedents Factors that Influence Soy Consumption: A Structural Equation Modeling Approach
Balasubramanian, Siva K.; Moon, Wanki; Rimal, Arbindra; Coker, Kesha
2009-01-01
We propose a structural model of antecedent factors that affect the frequency of soy consumption. This model, suggests that soy-general knowledge influences perceptions about nutrition concern, health benefits of soy, soy related personal beliefs and personal attitudes toward soy. Health benefits of soy, in turn, impacts soy-related personal beliefs and personal attitudes toward soy. Additionally, soy-related personal beliefs influence personal attitudes toward soy. Finally, both nutrition co...
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.
[Innovative health care models in Germany - success factors, barriers and transferability].
Müller, Beate S; Leiferman, Mareike; Wilke, Dennis; Gerlach, Ferdinand M; Erler, Antje
2016-10-01
Safeguarding country-wide health care in Germany requires innovative ideas: a shortage of skilled staff among medical professionals and in long-term care on the one hand contrasts with an increasing number of multi-morbid elderly patients on the other hand. In the "Innovative Health Care Models" project sponsored by the Robert Bosch Foundation a nationwide status review and systematization of innovative approaches to health care was conducted, along with an analysis of the factors that promote or hinder the implementation of a health care model, and a study of the conditions that must be satisfied if successful concepts are to be transferred to other regions. After identifying innovative and successfully implemented health care models, data on success factors and barriers for implementation as well as data on conditions of their transferability to other regions were collected during structured telephone interviews and entered into a specifically developed database. Content analysis was used to qualitatively evaluate the interviews. Interviews with 65 representatives of successfully implemented models with differing organizational structures and priorities were conducted and evaluated. Success factors and barriers were most obvious in the fields of leadership, readiness to participate, relational aspects, personality traits, cooperation and communication, resources and organizational and structural factors. Various regionally linked health care concepts already exist throughout Germany. The barriers, success factors and conditions influencing the transferability of a model to other regions are largely independent of the type of organization. The success of a model is determined by adequate personal and financial resources, sound organizational structures and external support from political and funding bodies. Copyright © 2016. Published by Elsevier GmbH.
Xu, Lihua; Wubbena, Zane; Stewart, Trae
2016-01-01
Purpose: The purpose of this paper is to investigate the factor structure and the measurement invariance of the Multifactor Leadership Questionnaire (MLQ) across gender of K-12 school principals (n=6,317) in the USA. Design/methodology/approach: Nine first-order factor models and four second-order factor models were tested using confirmatory…
Xu, Lihua; Wubbena, Zane; Stewart, Trae
2016-01-01
Purpose: The purpose of this paper is to investigate the factor structure and the measurement invariance of the Multifactor Leadership Questionnaire (MLQ) across gender of K-12 school principals (n=6,317) in the USA. Design/methodology/approach: Nine first-order factor models and four second-order factor models were tested using confirmatory…
DEFF Research Database (Denmark)
Appelt, Ane L; Vogelius, Ivan R.; Farr, Katherina P.;
2014-01-01
Background. Understanding the dose-response of the lung in order to minimize the risk of radiation pneumonitis (RP) is critical for optimization of lung cancer radiotherapy. We propose a method to combine the dose-response relationship for RP in the landmark QUANTEC paper with known clinical risk...... factors, in order to enable individual risk prediction. The approach is validated in an independent dataset. Material and methods. The prevalence of risk factors in the patient populations underlying the QUANTEC analysis was estimated, and a previously published method to adjust dose......-response relationships for clinical risk factors was employed. Effect size estimates (odds ratios) for risk factors were drawn from a recently published meta-analysis. Baseline values for D50 and γ50 were found. The method was tested in an independent dataset (103 patients), comparing the predictive power of the dose......-only QUANTEC model and the model including risk factors. Subdistribution cumulative incidence functions were compared for patients with high/low-risk predictions from the two models, and concordance indices (c-indices) for the prediction of RP were calculated. Results. The reference dose- response relationship...
Duda, G; Kemper, A; Duda, Gintaras; Gondolo, Paolo; Kemper, Ann
2006-01-01
Theoretical calculations of neutralino cross sections with various nuclei are of great interest to direct dark matter searches such as CDMS, EDELWEISS, ZEPLIN, and other experiments. These cross sections and direct detection rates are generally computed with standard, one or two parameter model-dependent nuclear form factors, which may not exactly mirror the actual form factor for the particular nucleus in question. As is well known, elastic electron scattering can allow for very precise determinations of nuclear form factors and hence nuclear charge densities for spherical or near-spherical nuclei. We use charge densities derived from elastic electron scattering data to calculate model independent form factors for various target nuclei important in dark matter searches, such as Si, Ge, S, Ca and others. We have found that for nuclear recoils in the range of 1-100 keV significant differences in cross sections and rates exist when the model independent form factors are used. DarkSUSY, a publicly-available adva...
A survey of the influencing factors and models for resident's household waste management behavior
Institute of Scientific and Technical Information of China (English)
无
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.
Institute of Scientific and Technical Information of China (English)
Jian-Lan Yu; Jun-Hua Li; Rong-Gui Cheng; Yan-Mei Ma; Xiao-Juan Wang; Jing-Chun Liu
2014-01-01
Objective:To observe the preventive and control effect of matrine on transforming growth factor (TGF-β1) and hepatocyte growth factor(HGF) of liver fibrosis tissue in rats.Methods:A total of 48SD rats were randomly divided intoA,B,C,D groups with12 in each, groupA as the normal control group and groupsB,C,D as liver fibrosis models using composite modulus method with carbon tetrachloride(CCL4).GroupB was the model group, groupC adoptedγ- interferon lavage therapy in the second day of modeling, and groupD adopted matrine lavage treatment, at4 and 8 weeks after treatment.Six rats were executed for detection ofTGF-β1 andHGF, liver tissue histology and comparison fibrosis degree changes of rat liver tissue between groups.Results:GroupsB,C,D showed a more significantly increasedTGF-β1 ateach time point compared with groupA(P<0.05);GroupB showed a more significantly increasedTGF-β1 than groupsC andD at weeks4 and8(P<0.05); groupD showed a lowest level ofTGF-β1, followed by groupsC and B.HGF of groupB decreased more significantly thanA group at weeks4 and8(P<0.05);HGF of groupsC andD was significantly elevated at4 and8 weeks than groupsA andB(P<0.05), in which the groupD showed the highest level ofHGF.According to tissue histologic observation, rat liver tissue structure of groupA was clear and normal, tissue structure of groupB was destroyed with obvious fibrous tissue hyperplasia and fatty change of hepatic cells; groupsC andD showed a slighter liver tissue damage, cell necrosis and connective tissue hyperplasia in collect abbacy than groupB with a trend of obvious improvement.Conclusions:Matrine can reduceTGF-β1 expression and enhance the activity ofHGF, so as to realize the inhibition effect on liver fibrosis in rats.
Directory of Open Access Journals (Sweden)
Marco Innamorati
2014-01-01
Full Text Available Objectives and Methods. The aim of the study was to investigate the construct validity of the ARSQ. Methods. The ARSQ and self-report measures of depression, anxiety, and hopelessness were administered to 774 Italian adults, aged 18 to 64 years. Results. Structural equation modeling indicated that the factor structure of the ARSQ can be represented by a bifactor model: a general rejection sensitivity factor and two group factors, expectancy of rejection and rejection anxiety. Reliability of observed scores was not satisfactory: only 44% of variance in observed total scores was due to the common factors. The analyses also indicated different correlates for the general factor and the group factors. Limitations. We administered an Italian version of the ARSQ to a nonclinical sample of adults, so that studies which use clinical populations or the original version of the ARSQ could obtain different results from those presented here. Conclusion. Our results suggest that the construct validity of the ARSQ is disputable and that rejection anxiety and expectancy could bias individuals to readily perceive and strongly react to cues of rejection in different ways.
Multilevel poisson regression modelling for determining factors of dengue fever cases in bandung
Arundina, Davila Rubianti; Tantular, Bertho; Pontoh, Resa Septiani
2017-03-01
Scralatina or Dengue Fever is a kind of fever caused by serotype virus which Flavivirus genus and be known as Dengue Virus. Dengue Fever caused by Aedes Aegipty Mosquito bites who infected by a dengue virus. The study was conducted in 151 villages in Bandung. Health Analysts believes that there are two factors that affect the dengue cases, Internal factor (individual) and external factor (environment). The data who used in this research is hierarchical data. The method is used for hierarchical data modelling is multilevel method. Which is, the level 1 is village and level 2 is sub-district. According exploration data analysis, the suitable Multilevel Method is Random Intercept Model. Penalized Quasi Likelihood (PQL) approach on multilevel Poisson is a proper analysis to determine factors that affecting dengue cases in the city of Bandung. Clean and Healthy Behavior factor from the village level have an effect on the number of cases of dengue fever in the city of Bandung. Factor from the sub-district level has no effect.
Basset-Mens, Claudine; Anibar, Lamiaa; Durand, Patrick; van der Werf, Hayo M G
2006-08-15
The challenge for environmental assessment tools, such as Life Cycle Assessment (LCA) is to provide a holistic picture of the environmental impacts of a given system, while being relevant both at a global scale, i.e., for global impact categories such as climate change, and at a smaller scale, i.e., for regional impact categories such as aquatic eutrophication. To this end, the environmental mechanisms between emission and impact should be taken into account. For eutrophication in particular, which is one of the main impacts of farming systems, the fate factor of eutrophying pollutants in catchments, and particularly of nitrate, reflects one of these important and complex environmental mechanisms. We define this fate factor as: the ratio of the amount of nitrate at the outlet of the catchment over the nitrate emitted from the catchment's soils. In LCA, this fate factor is most often assumed equal to 1, while the observed fate factor is generally less than 1. A generic approach for estimating the range of variation of nitrate fate factors in a region of intensive agriculture was proposed. This approach was based on the analysis of different catchment scenarios combining different catchment types and different effective rainfalls. The evolution over time of the nitrate fate factor as well as the steady state fate factor for each catchment scenario was obtained using the INCA simulation model. In line with the general LCA model, the implications of the steady state fate factors for nitrate were investigated for the eutrophication impact result in the framework of an LCA of pig production. A sensitivity analysis to the fraction of nitrate lost as N(2)O was presented for the climate change impact category. This study highlighted the difference between the observed fate factor at a given time, which aggregates both storage and transformation processes and a "steady state fate factor", specific to the system considered. The range of steady state fate factors obtained for
The NEO Personality Inventory: Using the Five-Factor Model in Counseling.
McCrae, Robert R.; Costa, Paul T., Jr.
1991-01-01
Reviews NEO Personality Inventory (NEO-PI), which is based on Five-Factor Model taxonomy of personality traits. Summarizes characteristics of test, features for administration and scoring, and studies of reliability, stability, and validity. Claims NEO-PI may be particularly appropriate for use in counseling because it is brief,…
The Five-Factor Model Personality Assessment for Improved Student Design Team Performance
Ogot, Madara; Okudan, Gul E.
2006-01-01
Researchers have long noted the correlation of various personality traits and team performance. Studies relating aggregate team personality traits to team performance are scattered in the literature and may not always be relevant to engineering design teams. This paper synthesizes the results from applicable Five-Factor Model (FFM)-based…
A new model for the computation of the formation factor of core rocks
Beltrán, A.; Chávez, O.; Zaldivar, J.; Godínez, F. A.; García, A.; Zenit, R.
2017-04-01
Among all the rock parameters measured by modern well logging tools, the formation factor is essential because it can be used to calculate the volume of oil- and/or gas in wellsite. A new mathematical model to calculate the formation factor is analytically derived from first principles. Given the electrical properties of both rock and brine (resistivities) and tortuosity (a key parameter of the model), it is possible to calculate the dependence of the formation factor with porosity with good accuracy. When the cementation exponent ceases to remain constant with porosity; the new model is capable of capturing both: the non-linear behavior (for small porosity values) and the typical linear one in log-log plots for the formation factor vs. porosity. Comparisons with experimental data from four different conventional core rock lithologies: sands, sandstone, limestone and volcanic are shown, for all of them a good agreement is observed. This new model is robust, simple and of easy implementation for practical applications. In some cases, it could substitute Archie's law replacing its empirical nature.
Budsankom, Prayoonsri; Sawangboon, Tatsirin; Damrongpanit, Suntorapot; Chuensirimongkol, Jariya
2015-01-01
The purpose of the research is to develop and identify the validity of factors affecting higher order thinking skills (HOTS) of students. The thinking skills can be divided into three types: analytical, critical, and creative thinking. This analysis is done by applying the meta-analytic structural equation modeling (MASEM) based on a database of…
A two-factor, stochastic programming model of Danish mortgage-backed securities
DEFF Research Database (Denmark)
Nielsen, Søren S.; Poulsen, Rolf
2004-01-01
-trivial, both in terms of deciding on an initial mortgage, and in terms of managing (rebalancing) it optimally.We propose a two-factor, arbitrage-free interest-rate model, calibrated to observable security prices, and implement on top of it a multi-stage, stochastic optimization program with the purpose...
Nucleon electromagnetic form factors in a relativistic quark model with chiral symmetry
Energy Technology Data Exchange (ETDEWEB)
Barik, N.; Das, M.
1987-05-01
The nucleon electromagnetic form factors are computed in an independent quark model based on the Dirac equation. Corrections for centre-of-mass motion and pion-cloud effects are incorporated. Results for static quantities are in reasonable agreement with the experimental data.
Raynor, Douglas A.; Levine, Heidi
2009-01-01
Objective: In fall 2006, the authors examined associations between the five-factor model of personality and several key health behaviors. Methods: College students (N = 583) completed the American College Health Association-National College Health Assessment and the International Personality Item Pool Big Five short-form questionnaire. Results:…
Time Use Efficiency and the Five-Factor Model of Personality.
Kelly, William E.; Johnson, Judith L.
2005-01-01
To investigate the relationship between self-perceived time use efficiency and the five-factor model of personality, 105 university students were administered the Time Use Efficiency Scale (TUES; Kelly, 2003) and Saucier's Big-Five Mini-Markers (Saucier, 1994). The results indicated that time use efficiency was strongly, positively related to…
Situational effects of the school factors included in the dynamic model of educational effectiveness
Creerners, Bert; Kyriakides, Leonidas
2009-01-01
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 th
Multilevel Factor Analysis by Model Segregation: New Applications for Robust Test Statistics
Schweig, Jonathan
2014-01-01
Measures of classroom environments have become central to policy efforts that assess school and teacher quality. This has sparked a wide interest in using multilevel factor analysis to test measurement hypotheses about classroom-level variables. One approach partitions the total covariance matrix and tests models separately on the…
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
and systematic approaches to assert usability in modeling and confirm the claims of productivity. This workshop creates a space for discussion being a get together of both MDE, Usability, Human Interfaces and the Experimental Software engineering community. HuFaMo expressly focuses on human factors, in order...
Chiaburu, Dan S.; Oh, In-Sue; Berry, Christopher M.; Li, Ning; Gardner, Richard G.
2011-01-01
Using meta-analytic tests based on 87 statistically independent samples, we investigated the relationships between the five-factor model (FFM) of personality traits and organizational citizenship behaviors in both the aggregate and specific forms, including individual-directed, organization-directed, and change-oriented citizenship. We found that…
The performance of multi-factor term structure models for pricing and hedging caps and swaptions
Driessen, J.J.A.G.; Klaassen, P.; Melenberg, B.
2000-01-01
In this paper we empirically compare a wide range of different term structure models when it comes to the pricing and, in particular, hedging of caps and swaptions. We analyze the influence of the number of factors on the hedging and pricing results, and investigate which type of data "interest rate
The Performance of Multi-Factor Term Structure Models for Pricing and Hedging Caps and Swaptions
Driessen, J.J.A.G.; Klaassen, P.; Melenberg, B.
2000-01-01
In this paper we empirically compare different term structure models when it comes to the pricing and hedging of caps and swaptions.We analyze the influence of the number of factors on the pricing and hedging results, and investigate which type of data -interest rate data or derivative price data-
Light-Front Quark Model Analysis of Meson-Photon Transition Form Factor
Choi, Ho-Meoyng
2016-01-01
We discuss $(\\pi^0,\\eta,\\eta')\\to\\gamma^*\\gamma$ transition form factors using the light-front quark model. Our discussion includes the analysis of the mixing angles for $\\eta-\\eta'$. Our results for $Q^2 F_{(\\pi^0,\\eta,\\eta')\\to\\gamma^*\\gamma}(Q^2)$ show scaling behavior for high $Q^2$ consistent with pQCD predictions.
A simplified model for growth factor induced healing of circular wounds
Vermolen, F.J.; E. van Baaren, E.; Adam, J.A.
2005-01-01
A mathematical model is developed for the rate of healing of a circular wound in a spherical skull. In this paper the regeneration, decay and transport of a generic "growth factor, which induces the healing of the wound, is taken into account. Further, an equation of motion is derived for the actual
Applicability of the Dual-Factor Model of Mental Health for College Students
Eklund, Katie; Dowdy, Erin; Jones, Camille; Furlong, Michael
2011-01-01
This study explores the utility of a dual-factor model of mental health in which the concepts of mental illness and mental wellness are integrated. Life satisfaction, emotional symptoms, personal adjustment, and clinical symptoms were assessed with a sample of 240 college students. Participants were organized into four groups based on levels of…
Lam, Terence Yuk Ping; Lau, Kwok Chi
2014-01-01
This study uses hierarchical linear modeling to examine the influence of a range of factors on the science performances of Hong Kong students in PISA 2006. Hong Kong has been consistently ranked highly in international science assessments, such as Programme for International Student Assessment and Trends in International Mathematics and Science…
Savolainen, Reijo
2015-01-01
Introduction: The article contributes to the conceptual studies of affective factors in information seeking by examining Kuhlthau's information search process model. Method: This random-digit dial telephone survey of 253 people (75% female) living in a rural, medically under-serviced area of Ontario, Canada, follows-up a previous interview study…
Creemers, Bert; Kyriakides, Leonidas
2010-01-01
The dynamic model of educational effectiveness defines school level factors associated with student outcomes. Emphasis is given to the two main aspects of policy, evaluation, and improvement in schools which affect quality of teaching and learning at both the level of teachers and students: a) teach
Verification of Overall Safety Factors In Deterministic Design Of Model Tested Breakwaters
DEFF Research Database (Denmark)
Burcharth, H. F.
2001-01-01
The paper deals with concepts of safety implementation in design. An overall safety factor concept is evaluated on the basis of a reliability analysis of a model tested rubble mound breakwater with monolithic super structure. Also discussed are design load identification and failure mode limit st...
Individual Differences in Response to Automation: The Five Factor Model of Personality
Szalma, James L.; Taylor, Grant S.
2011-01-01
This study examined the relationship of operator personality (Five Factor Model) and characteristics of the task and of adaptive automation (reliability and adaptiveness--whether the automation was well-matched to changes in task demand) to operator performance, workload, stress, and coping. This represents the first investigation of how the Five…
A simplified model for growth factor induced healing of circular wounds
Vermolen, F.J.; E. van Baaren, E.; Adam, J.A.
2005-01-01
A mathematical model is developed for the rate of healing of a circular wound in a spherical skull. In this paper the regeneration, decay and transport of a generic "growth factor, which induces the healing of the wound, is taken into account. Further, an equation of motion is derived for the actual
Creemers, Bert; Kyriakides, Leonidas
2010-01-01
The dynamic model of educational effectiveness defines school level factors associated with student outcomes. Emphasis is given to the two main aspects of policy, evaluation, and improvement in schools which affect quality of teaching and learning at both the level of teachers and students: a) teaching and b) school learning environment. Five…
DEFF Research Database (Denmark)
Jacobsen, Jens Christian Brings; Gustafsson, Finn; Holstein-Rathlou, N.-H.
2003-01-01
hemodynamic stimuli in the individual vessel. Simulated results show emanating microvascular networks with properties similar to those observed in vivo. The model points to an altered endothelial function as a key factor in the development of vascular changes characteristic of hypertension....
Fan, David P.; Elketroussi, Mehdi
1989-01-01
Describes habituation and addiction, both psychological and physiological, using simple equations of mathematical model of ideodynamics, optimized to smoking data from Multiple Risk Factor Intervention Trial (MRFIT) program. With only four constant parameters, it was possible to calculate accurate time trends for recidivism to smoking among…
A Four- and Five-Factor Structural Model for Wechsler Tests: Does It Really Matter Clinically?
Schwartz, David M.
2013-01-01
The purpose of this commentary is to focus on the clinical utility of the four- and five-factor structural models for the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) and Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). It provides a discussion of important considerations when evaluating the clinical utility of the…
A population pharmacokinetic model for perioperative dosing of factor VIII in hemophilia A patients
Hazendonk, Hendrika; Fijnvandraat, Karin; Lock, Janske; Driessens, Mariette; van der Meer, Felix; Meijer, Karina; Kruip, Marieke; Laros-van Gorkom, Britta; Peters, Marjolein; de Wildt, Saskia; Leebeek, Frank; Cnossen, Marjon; Mathot, Ron
2016-01-01
The role of pharmacokinetic-guided dosing of factor concentrates in hemophilia is currently a subject of debate and focuses on long-term prophylactic treatment. Few data are available on its impact in the perioperative period. In this study, a population pharmacokinetic model for currently registere
Conceptualizations of Personality Disorders with the Five Factor Model-Count and Empathy Traits
Kajonius, Petri J.; Dåderman, Anna M.
2017-01-01
Previous research has long advocated that emotional and behavioral disorders are related to general personality traits, such as the Five Factor Model (FFM). The addition of section III in the latest "Diagnostic and Statistical Manual of Mental Disorders" (DSM) recommends that extremity in personality traits together with maladaptive…
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…
A Four- and Five-Factor Structural Model for Wechsler Tests: Does It Really Matter Clinically?
Schwartz, David M.
2013-01-01
The purpose of this commentary is to focus on the clinical utility of the four- and five-factor structural models for the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) and Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). It provides a discussion of important considerations when evaluating the clinical utility of the…
The Performance of Multi-Factor Term Structure Models for Pricing and Hedging Caps and Swaptions
Driessen, J.J.A.G.; Klaassen, P.; Melenberg, B.
2000-01-01
In this paper we empirically compare different term structure models when it comes to the pricing and hedging of caps and swaptions.We analyze the influence of the number of factors on the pricing and hedging results, and investigate which type of data -interest rate data or derivative price data- s
The Five-Factor Model Personality Assessment for Improved Student Design Team Performance
Ogot, Madara; Okudan, Gul E.
2006-01-01
Researchers have long noted the correlation of various personality traits and team performance. Studies relating aggregate team personality traits to team performance are scattered in the literature and may not always be relevant to engineering design teams. This paper synthesizes the results from applicable Five-Factor Model (FFM)-based…
Bayesian Exploratory and Confirmatory Factor Analysis: Perspectives on Constrained-Model Selection
Peeters, C.F.W.
2012-01-01
The dissertation revolves around three aims. The first aim is the construction of a conceptually and computationally simple Bayes factor for Type I constrained-model selection (dimensionality determination) that is determinate under usage of improper priors and the subsequent utilization of this