An alternative method for centrifugal compressor loading factor modelling

Science.gov (United States)

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

2017-08-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-02-15

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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

Science.gov (United States)

Elklit, Ask; Armour, Cherie; Shevlin, Mark

2010-01-01

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

Matrix factorizations, minimal models and Massey products

International Nuclear Information System (INIS)

Knapp, Johanna; Omer, Harun

2006-01-01

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

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

Science.gov (United States)

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

2012-11-01

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

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

Science.gov (United States)

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

2017-01-27

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

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.

Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results.

Science.gov (United States)

Humada, Ali M; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M; Ahmed, Mushtaq N

2016-01-01

A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions.

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

Directory of Open Access Journals (Sweden)

Denis Dolinar

2013-06-01

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

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.

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

Directory of Open Access Journals (Sweden)

Rachel Collinson

2016-12-01

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

Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results

Science.gov (United States)

Humada, Ali M.; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M.; Ahmed, Mushtaq N.

2016-01-01

A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions. PMID:27035575

Value of the distant future: Model-independent results

Science.gov (United States)

Katz, Yuri A.

2017-01-01

This paper shows that the model-independent account of correlations in an interest rate process or a log-consumption growth process leads to declining long-term tails of discount curves. Under the assumption of an exponentially decaying memory in fluctuations of risk-free real interest rates, I derive the analytical expression for an apt value of the long run discount factor and provide a detailed comparison of the obtained result with the outcome of the benchmark risk-free interest rate models. Utilizing the standard consumption-based model with an isoelastic power utility of the representative economic agent, I derive the non-Markovian generalization of the Ramsey discounting formula. Obtained analytical results allowing simple calibration, may augment the rigorous cost-benefit and regulatory impact analysis of long-term environmental and infrastructure projects.

Model Correction Factor Method

DEFF Research Database (Denmark)

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

1997-01-01

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

Shell model and spectroscopic factors

International Nuclear Information System (INIS)

Poves, P.

2007-01-01

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

Functional dynamic factor models with application to yield curve forecasting

KAUST Repository

Hays, Spencer

2012-09-01

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

Modeling Factors with Influence on Sustainable University Management

Directory of Open Access Journals (Sweden)

Oana Dumitrascu

2015-01-01

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

Mutations in zebrafish lrp2 result in adult-onset ocular pathogenesis that models myopia and other risk factors for glaucoma.

Directory of Open Access Journals (Sweden)

Kerry N Veth

2011-02-01

Full Text Available The glaucomas comprise a genetically complex group of retinal neuropathies that typically occur late in life and are characterized by progressive pathology of the optic nerve head and degeneration of retinal ganglion cells. In addition to age and family history, other significant risk factors for glaucoma include elevated intraocular pressure (IOP and myopia. The complexity of glaucoma has made it difficult to model in animals, but also challenging to identify responsible genes. We have used zebrafish to identify a genetically complex, recessive mutant that shows risk factors for glaucoma including adult onset severe myopia, elevated IOP, and progressive retinal ganglion cell pathology. Positional cloning and analysis of a non-complementing allele indicated that non-sense mutations in low density lipoprotein receptor-related protein 2 (lrp2 underlie the mutant phenotype. Lrp2, previously named Megalin, functions as an endocytic receptor for a wide-variety of bioactive molecules including Sonic hedgehog, bone morphogenic protein 4, retinol-binding protein, vitamin D-binding protein, and apolipoprotein E, among others. Detailed phenotype analyses indicated that as lrp2 mutant fish age, many individuals--but not all--develop high IOP and severe myopia with obviously enlarged eye globes. This results in retinal stretch and prolonged stress to retinal ganglion cells, which ultimately show signs of pathogenesis. Our studies implicate altered Lrp2-mediated homeostasis as important for myopia and other risk factors for glaucoma in humans and establish a new genetic model for further study of phenotypes associated with this disease.

Cone Penetrometer N Factor Determination Testing Results

Energy Technology Data Exchange (ETDEWEB)

Follett, Jordan R.

2014-03-05

This document contains the results of testing activities to determine the empirical 'N Factor' for the cone penetrometer in kaolin clay simulant. The N Factor is used to releate resistance measurements taken with the cone penetrometer to shear strength.

The five-factor model in schizotypal personality disorder

OpenAIRE

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

2005-01-01

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

Improved SVR Model for Multi-Layer Buildup Factor Calculation

International Nuclear Information System (INIS)

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

2006-01-01

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

Change management in Iranian hospitals: social factors model

Directory of Open Access Journals (Sweden)

B. Delgoshaei

2012-02-01

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

Linear factor copula models and their properties

KAUST Repository

Krupskii, Pavel; Genton, Marc G.

2018-01-01

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

Linear factor copula models and their properties

KAUST Repository

Krupskii, Pavel

2018-04-25

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

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

Science.gov (United States)

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

2015-03-15

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

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.

Growth factor release by vesicular phospholipid gels: in-vitro results and application for rotator cuff repair in a rat model.

Science.gov (United States)

Buchmann, Stefan; Sandmann, Gunther H; Walz, Lars; Reichel, Thomas; Beitzel, Knut; Wexel, Gabriele; Tian, Weiwei; Battmann, Achim; Vogt, Stephan; Winter, Gerhard; Imhoff, Andreas B

2015-04-10

Biological augmentation of rotator cuff repair is of growing interest to improve biomechanical properties and prevent re-tearing. But intraoperative single shot growth factor application appears not sufficient to provide healing support in the physiologic growth factor expression peaks. The purpose of this study was to establish a sustained release of granulocyte-colony stimulating factor (G-CSF) from injectable vesicular phospholipid gels (VPGs) in vitro and to examine biocompatibility and influence on histology and biomechanical behavior of G-CSF loaded VPGs in a chronic supraspinatus tear rat model. G-CSF loaded VPGs were produced by dual asymmetric centrifugation. In vitro the integrity, stability and release rate were analyzed. In vivo supraspinatus tendons of 60 rats were detached and after 3 weeks a transosseous refixation with G-CSF loaded VPGs augmentation (n = 15; control, placebo, 1 and 10 μg G-CSF/d) was performed. 6 weeks postoperatively the healing site was analyzed histologically (n = 9; H&E by modified MOVIN score/Collagen I/III) and biomechanically (n = 6). In vitro testing revealed stable proteins after centrifugation and a continuous G-CSF release of up to 4 weeks. Placebo VPGs showed histologically no negative side effects on the healing process. Histologically in vivo testing demonstrated significant advantages for G-CSF 1 μg/d but not for G-CSF 10 μg/d in Collagen III content (p = 0.035) and a higher Collagen I/III ratio compared to the other groups. Biomechanically G-CSF 1 μg/d revealed a significant higher load to failure ratio (p = 0.020) compared to control but no significant differences in stiffness. By use of VPGs a continuous growth factor release could be obtained in vitro. The in vivo results demonstrate an improvement of immunohistology and biomechanical properties with a low dose G-CSF application via VPG. The VPG itself was well tolerated and had no negative influence on the healing behavior. Due to the favorable properties

The Five-Factor Model: General Overview

Directory of Open Access Journals (Sweden)

A A Vorobyeva

2011-12-01

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

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.

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

Directory of Open Access Journals (Sweden)

Christian eGeiser

2015-08-01

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

Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

Directory of Open Access Journals (Sweden)

Hong Xue

2018-01-01

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

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

Science.gov (United States)

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

2013-01-01

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

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.

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

Science.gov (United States)

Nikbakht, Roya; Bahrampour, Abbas

2017-01-01

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

Model calculation of the scanned field enhancement factor of CNTs

International Nuclear Information System (INIS)

Ahmad, Amir; Tripathi, V K

2006-01-01

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

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

Science.gov (United States)

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

2015-09-01

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

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.

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

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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.

SHMF: Interest Prediction Model with Social Hub Matrix Factorization

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Chaoyuan Cui

2017-01-01

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

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.

Comparison of Transcription Factor Binding Site Models

KAUST Repository

Bhuyan, Sharifulislam

2012-05-01

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

Common factors and the exchange rate: results from the Brazilian case

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Wilson Rafael de Oliveira Felício

2014-03-01

Full Text Available This paper studies the usefulness of factor models in explaining the dynamics of the exchange rate Real / Dollar from January 1999 to August 2011. The paper verifies that the inclusion of factors embedded on the common movements of exchange rates of a set of countries significantly improves the in-sample and out-of-sample predictive power of the models comprising only macroeconomic fundamentals commonly used in the literature to forecast the exchange rate. The paper also links the information contained in the factors to global shocks like the demand for dollars - a "dollar effect", volatility and liquidity of global financial markets.

Some Results on Mean Square Error for Factor Score Prediction

Science.gov (United States)

Krijnen, Wim P.

2006-01-01

For the confirmatory factor model a series of inequalities is given with respect to the mean square error (MSE) of three main factor score predictors. The eigenvalues of these MSE matrices are a monotonic function of the eigenvalues of the matrix gamma[subscript rho] = theta[superscript 1/2] lambda[subscript rho] 'psi[subscript rho] [superscript…

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

Science.gov (United States)

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

2018-06-01

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

Reformulation of Crop and Management Factor in ANSWERS Model

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Yayat Hidayat

2008-05-01

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

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

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Pablo Sayans-Jiménez

2017-10-01

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

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

Science.gov (United States)

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

2017-01-01

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

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 the thermal absorption factor of photovoltaic/thermal combi-panels

International Nuclear Information System (INIS)

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

2006-01-01

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

Model of separated form factors for unilamellar vesicles

International Nuclear Information System (INIS)

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

2001-01-01

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

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

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Chao Su

2016-01-01

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

Factor Copula Models for Replicated Spatial Data

KAUST Repository

Krupskii, Pavel

2016-12-19

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

Factor Copula Models for Replicated Spatial Data

KAUST Repository

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

2016-01-01

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

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)

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

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Madiha Riaz Bhatti

2014-12-01

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

Success and failure factors in the regional health information system design process--results from a constructive evaluation study.

Science.gov (United States)

Nykänen, P; Karimaa, E

2006-01-01

To identify success and failure factors in the design process of a regional health information system. A constructive evaluation study including interviews, observations, usability study and document analysis. Modelling was found to be a key element for the successful implementation of a health information system. The developed service chain model helped to define use cases and to implement seamless service chains. User participation in the design process was a success factor resulting in good user acceptance and signs of positive impacts on work practices. Evaluation study also helped system developers to guide the system's further development. An important failure factor identified was the lack of semantic interoperability of the system components. The results emphasize the socio-technical nature of health information systems. The starting point for development should be thorough insight into the health care work practices where the information systems are to be used. Successful system design should start from modelling of work processes, data and information flows and definition of concepts and their relations. Health informatics as a scientific discipline provides theories and models for the design and development process.

Carbon dioxide /V2/ radiance results using a new nonequilibrium model

Science.gov (United States)

Sharma, R. D.; Nadile, R. M.

1981-01-01

It was observed during the SPIRE experiment (Spectral Infrared Rocket Experiment) that the 15 micron limb radiance stays constant from 95 to 110 km despite the fact that CO2 concentration over this altitude range decreases by a factor of 20. The results of a 15 micron CO2 radiance model are presented which explain the observed anomaly. It is shown that CO2 deactivation by oxygen is the predominant factor in 15 micron emission above 95 km.

The use of aquatic bioconcentration factors in ecological risk assessments: Confounding issues, laboratory v/s modeled results

International Nuclear Information System (INIS)

Brandt, C.; Blanton, M.L.; Dirkes, R.

1995-01-01

Bioconcentration in aquatic systems is generally taken to refer to contaminant uptake through non-ingestion pathways (i.e., dermal and respiration uptake). Ecological risk assessments performed on aquatic systems often rely on published data on bioconcentration factors to calibrate models of exposure. However, many published BCFs, especially those from in situ studies, are confounded by uptake from ingestion of prey. As part of exposure assessment and risk analysis of the Columbia River's Hanford Reach, the authors tested a methodology to estimate radionuclide BCFs for several aquatic species in the Hanford Reach of the Columbia River. The iterative methodology solves for BCFs from known body burdens and environmental media concentrations. This paper provides BCF methodology description comparisons of BCF from literature and modeled values and how they were used in the exposure assessment and risk analysis of the Columbia River's Hanford Reach

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

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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.

The asset pricing model of musharakah factors

Science.gov (United States)

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

2015-02-01

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

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

African Journals Online (AJOL)

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

Psychological factors related to donation behaviour among Chinese adults: results from a longitudinal investigation.

Science.gov (United States)

Hu, H; Wang, T; Fu, Q

2017-10-01

Little is known about the psychological factors currently influencing blood donation in China. This study investigated the structure of psychological factors and their correlation with donation behaviour of adults in a transforming city in China over a 6-month period. Participants were recruited in Nanjing from May 2013 to April 2014. Preliminary focus group interviews with 102 participants were conducted to generate new items for a Theory of Planned Behaviour (TPB) questionnaire. The questionnaires were completed by 300 participants, and responses were subjected to factor analysis. We confirmed the resulting factorial structure with 861 respondents and examined the associations between these factors and donation behaviour during the next 6 months using structural equation modelling. Factor analysis and structural equation modelling of the data supported an extended TPB model with self-reported past donation behaviour as a covariate. After controlling for past donation behaviour, attitudes towards blood donation (β = 0·288), subjective norm (β = 0·149), self-efficacy (β = 0·199), trust in third-party health professionals (β = 0·237), mistrust towards blood collection agencies (BCAs) (β = -0·085) and traditional Chinese beliefs (β = -0·046) were significantly related to donation intention, whilst donation intention was positively (β = 0·212) associated with donation behaviour. These findings confirm that psychological factors such as attitudes are predictors of blood donation. Recruitment efforts using public information campaigns and interpersonal communications should focus on strengthening positive attitudes, increasing trust in third-party health professionals, elevating self-efficacy, changing traditional Chinese beliefs and relieving mistrust in blood collection agencies (BCAs). © 2017 British Blood Transfusion Society.

Three-dimensional flow analysis and improvement of slip factor model for forward-curved blades centrifugal fan

International Nuclear Information System (INIS)

Guo, En Min; Kim, Kwang Yong

2004-01-01

This work developed improved slip factor model and correction method to predict flow through impeller in forward-curved centrifugal fan. Both steady and unsteady three-dimensional CFD analyses were performed to validate the slip factor model and the correction method. The results show that the improved slip factor model presented in this paper could provide more accurate predictions for forward-curved centrifugal impeller than the other slip factor models since the present model takes into account the effect of blade curvature. The correction method is provided to predict mass-averaged absolute circumferential velocity at the exit of impeller by taking account of blockage effects induced by the large-scale backflow near the front plate and flow separation within blade passage. The comparison with CFD results also shows that the improved slip factor model coupled with the present correction method provides accurate predictions for mass-averaged absolute circumferential velocity at the exit of impeller near and above the flow rate of peak total pressure coefficient

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

Science.gov (United States)

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

2017-01-01

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

Container Throughput Forecasting Using Dynamic Factor Analysis and ARIMAX Model

Directory of Open Access Journals (Sweden)

Marko Intihar

2017-11-01

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

Models of Anaylzing the Influence of Factors on Forming Profit Rate

Directory of Open Access Journals (Sweden)

Klara S. Jakovčević

2014-04-01

Full Text Available The analysis in this paper is focused on identifying the impact of individual factors on the elements of the profit rate. The primary aim of this work is a methodological overview of solutions for understanding the full content of the profit rate as a cause of economic quality as well as indicators of the results of reproduction. Application of model analysis of profit rate factors was performed in an enterprise from Serbia that manufactures construction materials from baked clay. The aim is of application is to test the range in determining elements and factors of economic success of the enterprise, and quantification of changes in its assumptions. The results are useful guideline for the management to take organizational measures to increase the economic success of the enterprise. This means eliminating the negative, emphasizing the positive impact of objectively, and organizational factors to make higher economic success. Based on empirical research, it could be concluded that the proposed quantitative models of analyzing the dynamics of enterprise business quality could be applied in practice.

Analysis of automotive rolling lobe air spring under alternative factors with finite element model

International Nuclear Information System (INIS)

Wong, Pak Kin; Xie, Zhengchao; Zhao, Jing; Xu, Tao; He, Feng

2014-01-01

Air springs are widely used in automotive suspensions for their superior performance in terms of low friction motion, adjustable load carrying capacity and user-friendly ride height control. However, it has posed great difficulties in constructing an accurate model as well as the analysis of the influence of alternative factors, such as cord angle, cord diameter and initial pressure. In this paper, a numerical model of the rolling lobe air spring (RLAS) is built by using finite element method and compared with an existing analytical model. An experiment with respect to the vertical stiffness of the RLAS is carried out to validate the accuracy of the proposed model. Evaluation result reveals that the existing analytical model cannot represent the performance of the RLAS very well, whereas the accuracy of the numerical model is very good. With the verified numerical model, the impacts of many alternative factors on the characteristics of the RLAS are analyzed. Numerical results show that the newly proposed model is reliable to determine the vertical characteristic and physical dimensions of the RLAS under the alternative factors.

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

Czech Academy of Sciences Publication Activity Database

Gapko, Petr; Šmíd, Martin

2012-01-01

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

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

Directory of Open Access Journals (Sweden)

Marilyn Sihuay

2018-05-01

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

Functional dynamic factor models with application to yield curve forecasting

KAUST Repository

Hays, Spencer; Shen, Haipeng; Huang, Jianhua Z.

2012-01-01

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

Factor Analysis of Drawings: Application to College Student Models of the Greenhouse Effect

Science.gov (United States)

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

2015-01-01

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,…

Assessing Heterogeneity for Factor Analysis Model with Continuous and Ordinal Outcomes

Directory of Open Access Journals (Sweden)

Ye-Mao Xia

2016-01-01

Full Text Available Factor analysis models with continuous and ordinal responses are a useful tool for assessing relations between the latent variables and mixed observed responses. These models have been successfully applied to many different fields, including behavioral, educational, and social-psychological sciences. However, within the Bayesian analysis framework, most developments are constrained within parametric families, of which the particular distributions are specified for the parameters of interest. This leads to difficulty in dealing with outliers and/or distribution deviations. In this paper, we propose a Bayesian semiparametric modeling for factor analysis model with continuous and ordinal variables. A truncated stick-breaking prior is used to model the distributions of the intercept and/or covariance structural parameters. Bayesian posterior analysis is carried out through the simulation-based method. Blocked Gibbs sampler is implemented to draw observations from the complicated posterior. For model selection, the logarithm of pseudomarginal likelihood is developed to compare the competing models. Empirical results are presented to illustrate the application of the methodology.

A test of resuspension factor models against Chernobyl data

International Nuclear Information System (INIS)

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

1995-04-01

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

A test of resuspension factor models against Chernobyl data

Energy Technology Data Exchange (ETDEWEB)

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

1995-04-01

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

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

Science.gov (United States)

Clark, D Angus; Bowles, Ryan P

2018-04-23

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

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

Science.gov (United States)

Feng, Yongjiu; Tong, Xiaohua

2017-09-22

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

Monitoring results for the Factor 9 home

International Nuclear Information System (INIS)

Fugler, D.; Dumont, R.

2009-01-01

The Factor 9 home is a new demonstration project that consists of a single family residence located in Regina, Saskatchewan. The home features extremely high levels of energy and water use efficiency. The home was completed in April 2007. Energy and water savings targets were established for the Factor 9 home. In order to assess the extent to which the performance objectives were met, a project was undertaken to monitor energy and water use for a one-year period ending May 31, 2008. Several indoor air quality indicators were also measured. This paper discussed the findings of the project, with particular reference to energy conservation features; water conservation features; performance results; incremental cost of energy and water efficiency features; indoor air quality; and suggested improvements to the Factor 9 home. It was concluded that the demonstration project house showcased high levels of energy efficiency, renewable energy, and water efficiency with proven technologies. 3 refs., 4 figs.

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

Science.gov (United States)

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

2013-06-01

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

A Parametric Factor Model of the Term Structure of Mortality

DEFF Research Database (Denmark)

Haldrup, Niels; Rosenskjold, Carsten Paysen T.

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

Bethe Ansatz and exact form factors of the O(N) Gross Neveu-model

International Nuclear Information System (INIS)

Babujian, Hrachya M.; Foerster, Angela; Karowski, Michael

2016-01-01

We apply previous results on the O(N) Bethe Ansatz http://dx.doi.org/10.1088/1751-8113/45/5/055207, http://arxiv.org/abs/1204.3479, http://dx.doi.org/10.1007/JHEP11(2013)089 to construct a general form factor formula for the O(N) Gross-Neveu model. We examine this formula for several operators, such as the energy momentum, the spin-field and the current. We also compare these results with the 1/N expansion of this model and obtain full agreement. We discuss bound state form factors, in particular for the three particle form factor of the field. In addition for the two particle case we prove a recursion relation for the K-functions of the higher level Bethe Ansatz.

Cardiometabolic risk clustering in spinal cord injury: results of exploratory factor analysis.

Science.gov (United States)

Libin, Alexander; Tinsley, Emily A; Nash, Mark S; Mendez, Armando J; Burns, Patricia; Elrod, Matt; Hamm, Larry F; Groah, Suzanne L

2013-01-01

Evidence suggests an elevated prevalence of cardiometabolic risks among persons with spinal cord injury (SCI); however, the unique clustering of risk factors in this population has not been fully explored. The purpose of this study was to describe unique clustering of cardiometabolic risk factors differentiated by level of injury. One hundred twenty-one subjects (mean 37 ± 12 years; range, 18-73) with chronic C5 to T12 motor complete SCI were studied. Assessments included medical histories, anthropometrics and blood pressure, and fasting serum lipids, glucose, insulin, and hemoglobin A1c (HbA1c). The most common cardiometabolic risk factors were overweight/obesity, high levels of low-density lipoprotein (LDL-C), and low levels of high-density lipoprotein (HDL-C). Risk clustering was found in 76.9% of the population. Exploratory principal component factor analysis using varimax rotation revealed a 3-factor model in persons with paraplegia (65.4% variance) and a 4-factor solution in persons with tetraplegia (73.3% variance). The differences between groups were emphasized by the varied composition of the extracted factors: Lipid Profile A (total cholesterol [TC] and LDL-C), Body Mass-Hypertension Profile (body mass index [BMI], systolic blood pressure [SBP], and fasting insulin [FI]); Glycemic Profile (fasting glucose and HbA1c), and Lipid Profile B (TG and HDL-C). BMI and SBP formed a separate factor only in persons with tetraplegia. Although the majority of the population with SCI has risk clustering, the composition of the risk clusters may be dependent on level of injury, based on a factor analysis group comparison. This is clinically plausible and relevant as tetraplegics tend to be hypo- to normotensive and more sedentary, resulting in lower HDL-C and a greater propensity toward impaired carbohydrate metabolism.

Using a knowledge elicitation method to specify the business model of a human factors organization

NARCIS (Netherlands)

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

Using a knowledge elicitation method to specify the business model of a human factors organization.

NARCIS (Netherlands)

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

Structural equation modeling analysis of factors influencing architects' trust in project design teams

Institute of Scientific and Technical Information of China (English)

DING Zhi-kun; NG Fung-fai; WANG Jia-yuan

2009-01-01

This paper describes a structural equation modeling (SEM) analysis of factors influencing architects' trust in project design teams. We undertook a survey of architects, during which we distributed 193 questionnaires in 29 A-level architectural We used Amos 6.0 for SEM to identify significant personal construct based factors affecting interpersonal trust. The results show that only social interaction between architects significantly affects their interpersonal trust. The explained variance of trust is not very high in the model. Therefore, future research should add more factors into the current model. The practical implication is that team managers should promote the social interactions between team members such that the interpersonal trust level between team members can be improved.

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

Science.gov (United States)

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

2013-01-01

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

Treatments Results and Prognostic Factors in Locally Advanced Hypopharyngeal Cancer

International Nuclear Information System (INIS)

Yoon, Mee-Sun; Chung, Woong-Ki; Ahn, Sung-Ja; Nam, Taek-Keun; Song, Ju-Young; Nah, Byung-Sik; Lim, Sang Cheol; Lee, Joon Kyoo

2007-01-01

The purpose of this study is to present the treatment results and to identify possible prognostic indicators in patients with locally advanced hypopharyngeal carcinoma. Materials and Methods: Between October 1985 to December 2000, 90 patients who had locally advanced stage IV hypopharyngeal carcinoma were studied retrospectively. Twelve patients were treated with radiotherapy alone, 65 patients were treated with a combination of chemotherapy and radiotherapy, and 13 patients were treated with surgery and postoperative radiotherapy with or without neoadjuvant chemotherapy. Total radiation dose ranged from 59.0 to 88.2 Gy (median 70 Gy) for radiotherapy alone. Most patients had ciplatin and 5-fluorouracil, and others had cisplatin and peplomycin or vincristin. Median follow-up period was 15 months. Kaplan-Meier method was used for survival rate and Cox proportional hazard model for multivariate analysis of prognostic factors. Results: Overall 3- and 5-year survival rates were 27% and 17%, respectively. The 2-year locoregional control rates were 33% for radiotherapy alone, 32% for combined chemotherapy and radiotherapy, and 81% for combined surgery and radiotherapy (p=0.006). The prognostic factors affecting overall survival were T stage, concurrent chemo radiation and treatment response. Overall 3- and 5-year laryngeal preservation rates in combined chemotherapy and radiotherapy were 26% and 22%, respectively. Of these, the 5-year laryngeal preservation rates were 52% for concurrent chemo radiation group (n=11), and 16% for neoadjuvant chemotherapy and radiotherapy (n=54, p=0.012). Conclusion: Surgery and postoperative radiotherapy showed better results than radiotherapy alone or with chemotherapy. Radiotherapy combined with concurrent chemotherapy is an effective modality to achieve organ preservation in locally advanced hypopharyngeal cancer. Further prospective randomized studies will be required

Exploring Technostress: Results of a Large Sample Factor Analysis

OpenAIRE

Jonušauskas, Steponas; Raišienė, Agota Giedrė

2016-01-01

With reference to the results of a large sample factor analysis, the article aims to propose the frame examining technostress in a population. The survey and principal component analysis of the sample consisting of 1013 individuals who use ICT in their everyday work was implemented in the research. 13 factors combine 68 questions and explain 59.13 per cent of the answers dispersion. Based on the factor analysis, questionnaire was reframed and prepared to reasonably analyze the respondents’ an...

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

Directory of Open Access Journals (Sweden)

S. Pereira

2012-04-01

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

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

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

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.

Modification of transition's factor in the compact surface-potential-based MOSFET model

Directory of Open Access Journals (Sweden)

Kevkić Tijana

2016-01-01

Full Text Available The modification of an important transition's factor which enables continual behavior of the surface potential in entire useful range of MOSFET operation is presented. The various modifications have been made in order to obtain an accurate and computationally efficient compact MOSFET model. The best results have been achieved by introducing the generalized logistic function (GL in fitting of considered factor. The smoothness and speed of the transition of the surface potential from the depletion to the strong inversion region can be controlled in this way. The results of the explicit model with this GL functional form for transition's factor have been verified extensively with the numerical data. A great agreement was found for a wide range of substrate doping and oxide thickness. Moreover, the proposed approach can be also applied on the case where quantum mechanical effects play important role in inversion mode.

Condensation in models with factorized and pair-factorized stationary states

International Nuclear Information System (INIS)

Evans, M R; Waclaw, B

2015-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

Bayes Factor Covariance Testing in Item Response Models.

Science.gov (United States)

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

2017-12-01

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

Remarks on electromagnetic form factors of hadrons in the quark model

International Nuclear Information System (INIS)

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

1977-01-01

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

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

Directory of Open Access Journals (Sweden)

Zohreh Khayyam Nekouei

2014-01-01

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

1/M corrections to baryonic form factors in the quark model

International Nuclear Information System (INIS)

Cheng, H.; Tseng, B.

1996-01-01

Weak current-induced baryonic form factors at zero recoil are evaluated in the rest frame of the heavy parent baryon using the nonrelativistic quark model. Contrary to previous similar work in the literature, our quark model results do satisfy the constraints imposed by heavy quark symmetry for heavy-heavy baryon transitions at the symmetric point v·v'=1 and are in agreement with the predictions of the heavy quark effective theory for antitriplet-antitriplet heavy baryon form factors at zero recoil evaluated to order 1/m Q . Furthermore, the quark model approach has the merit that it is applicable to any heavy-heavy and heavy-light baryonic transitions at maximum q 2 . Assuming a dipole q 2 behavior, we have applied the quark model form factors to nonleptonic, semileptonic, and weak radiative decays of the heavy baryons. It is emphasized that the flavor suppression factor occurring in many heavy-light baryonic transitions, which is unfortunately overlooked in most literature, is very crucial towards an agreement between theory and experiment for the semileptonic decay Λ c →Λe + ν e . Predictions for the decay modes Λ b →J/ψΛ, Λ c →pφ, Λ b →Λγ, Ξ b →Ξγ, and for the semileptonic decays of Λ b , Ξ b, c, and Ω b are presented. copyright 1996 The American Physical Society

Dependent defaults and losses with factor copula models

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Ackerer Damien

2017-12-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1997-10-01

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

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

Science.gov (United States)

Holschke, Oliver; Rake, Jannis; Levina, Olga

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

A Multinomial Probit Model with Latent Factors

DEFF Research Database (Denmark)

Piatek, Rémi; Gensowski, Miriam

2017-01-01

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

Baryon octet electromagnetic form factors in a confining NJL model

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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

Object recognition in images via a factor graph model

Science.gov (United States)

He, Yong; Wang, Long; Wu, Zhaolin; Zhang, Haisu

2018-04-01

Object recognition in images suffered from huge search space and uncertain object profile. Recently, the Bag-of- Words methods are utilized to solve these problems, especially the 2-dimension CRF(Conditional Random Field) model. In this paper we suggest the method based on a general and flexible fact graph model, which can catch the long-range correlation in Bag-of-Words by constructing a network learning framework contrasted from lattice in CRF. Furthermore, we explore a parameter learning algorithm based on the gradient descent and Loopy Sum-Product algorithms for the factor graph model. Experimental results on Graz 02 dataset show that, the recognition performance of our method in precision and recall is better than a state-of-art method and the original CRF model, demonstrating the effectiveness of the proposed method.

Experiments with a methodology to model the role of R and D expenditures in energy technology learning processes; first results

International Nuclear Information System (INIS)

Miketa, Asami; Schrattenholzer, Leo

2004-01-01

This paper presents the results of using a stylized optimization model of the global electricity supply system to analyze the optimal research and development (R and D) support for an energy technology. The model takes into account the dynamics of technological progress as described by a so-called two-factor learning curve (2FLC). The two factors are cumulative experience ('learning by doing') and accumulated knowledge ('learning by searching'); the formulation is a straightforward expansion of conventional one-factor learning curves, in which only cumulative experience is included as a factor, which aggregates the effects of accumulated knowledge and cumulative experience, among others. The responsiveness of technological progress to the two factors is quantified using learning parameters, which are estimated using empirical data. Sensitivities of the model results to the parameters are also tested. The model results also address the effect of competition between technologies and of CO 2 constraints. The results are mainly methodological; one of the most interesting is that, at least up to a point, competition between technologies - in terms of both market share and R and D support - need not lead to 'lock-in' or 'crowding-out'

Experiments with a methodology to model the role of R and D expenditures in energy technology learning processes: first results

International Nuclear Information System (INIS)

Miketa, A.; Schrattenholzer, L.

2004-01-01

This paper presents the results of using a stylized optimization model of the global electricity supply system to analyze the optimal research and development (R and D) support for an energy technology. The model takes into account the dynamics of technological progress as described by a so-called two-factor learning curve (2FLC). The two factors are cumulative experience (''learning by doing'') and accumulated knowledge (''learning by searching''); the formulation is a straightforward expansion of conventional one-factor learning curves, in which only cumulative experience is included as a factor, which aggregates the effects of accumulated knowledge and cumulative experience, among others. The responsiveness of technological progress to the two factors is quantified using learning parameters, which are estimated using empirical data. Sensitivities of the model results to the parameters are also tested. The model results also address the effect of competition between technologies and of CO 2 constraints. The results are mainly methodological; one of the most interesting is that, at least up to a point, competition between technologies-in terms of both market share and R and D support-need not lead to ''lock-in'' or ''crowding-out''. (author)

Exploring Technostress: Results of a Large Sample Factor Analysis

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Steponas Jonušauskas

2016-06-01

Full Text Available With reference to the results of a large sample factor analysis, the article aims to propose the frame examining technostress in a population. The survey and principal component analysis of the sample consisting of 1013 individuals who use ICT in their everyday work was implemented in the research. 13 factors combine 68 questions and explain 59.13 per cent of the answers dispersion. Based on the factor analysis, questionnaire was reframed and prepared to reasonably analyze the respondents’ answers, revealing technostress causes and consequences as well as technostress prevalence in the population in a statistically validated pattern. A key elements of technostress based on factor analysis can serve for the construction of technostress measurement scales in further research.

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...

Use of model plant hosts to identify Pseudomonas aeruginosa virulence factors

Science.gov (United States)

Rahme, Laurence G.; Tan, Man-Wah; Le, Long; Wong, Sandy M.; Tompkins, Ronald G.; Calderwood, Stephen B.; Ausubel, Frederick M.

1997-01-01

We used plants as an in vivo pathogenesis model for the identification of virulence factors of the human opportunistic pathogen Pseudomonas aeruginosa. Nine of nine TnphoA mutant derivatives of P. aeruginosa strain UCBPP-PA14 that were identified in a plant leaf assay for less pathogenic mutants also exhibited significantly reduced pathogenicity in a burned mouse pathogenicity model, suggesting that P. aeruginosa utilizes common strategies to infect both hosts. Seven of these nine mutants contain TnphoA insertions in previously unknown genes. These results demonstrate that an alternative nonvertebrate host of a human bacterial pathogen can be used in an in vivo high throughput screen to identify novel bacterial virulence factors involved in mammalian pathogenesis. PMID:9371831

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

Science.gov (United States)

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

2012-07-05

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

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

Directory of Open Access Journals (Sweden)

Jeffrey S Bedwell

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

Support vector regression model for the estimation of γ-ray buildup factors for multi-layer shields

International Nuclear Information System (INIS)

Trontl, Kresimir; Smuc, Tomislav; Pevec, Dubravko

2007-01-01

The accuracy of the point-kernel method, which is a widely used practical tool for γ-ray shielding calculations, strongly depends on the quality and accuracy of buildup factors used in the calculations. Although, buildup factors for single-layer shields comprised of a single material are well known, calculation of buildup factors for stratified shields, each layer comprised of different material or a combination of materials, represent a complex physical problem. Recently, a new compact mathematical model for multi-layer shield buildup factor representation has been suggested for embedding into point-kernel codes thus replacing traditionally generated complex mathematical expressions. The new regression model is based on support vector machines learning technique, which is an extension of Statistical Learning Theory. The paper gives complete description of the novel methodology with results pertaining to realistic engineering multi-layer shielding geometries. The results based on support vector regression machine learning confirm that this approach provides a framework for general, accurate and computationally acceptable multi-layer buildup factor model

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

Science.gov (United States)

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

2002-07-01

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

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

International Nuclear Information System (INIS)

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

1995-01-01

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

The Research on Influencing Factors of Medical Logistics Cost Based on ISM Model

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Zhai Yunkai

2017-01-01

Full Text Available The reason why medical logistics cost remains high is a system problem, this paper analyzes the system through the ISM model. The result presents that medical logistics cost factors have four levels of relationship, primary factor is the national policies, secondary factors are the talent construction and pharmaceutical enterprise scale, Intermediate factors are medical information management system and inventory cost, the key factors are transportation cost and distribution center location. Finally, according to the four levels of relationship, this paper put forward specific suggestions to reduce logistics cost.

Monte Carlo Method to Study Properties of Acceleration Factor Estimation Based on the Test Results with Varying Load

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N. D. Tiannikova

2014-01-01

Full Text Available G.D. Kartashov has developed a technique to determine the rapid testing results scaling functions to the normal mode. Its feature is preliminary tests of products of one sample including tests using the alternating modes. Standard procedure of preliminary tests (researches is as follows: n groups of products with m elements in each start being tested in normal mode and, after a failure of one of products in the group, the remained products are tested in accelerated mode. In addition to tests in alternating mode, tests in constantly normal mode are conducted as well. The acceleration factor of rapid tests for this type of products, identical to any lots is determined using such testing results of products from the same lot. A drawback of this technique is that tests are to be conducted in alternating mode till the failure of all products. That is not always is possible. To avoid this shortcoming, the Renyi criterion is offered. It allows us to determine scaling functions using the right-censored data thus giving the opportunity to stop testing prior to all failures of products.In this work a statistical modeling of the acceleration factor estimation owing to Renyi statistics minimization is implemented by the Monte-Carlo method. Results of modeling show that the acceleration factor estimation obtained through Renyi statistics minimization is conceivable for rather large n . But for small sample volumes some systematic bias of acceleration factor estimation, which decreases with growth n is observed for both distributions (exponential and Veybull's distributions. Therefore the paper also presents calculation results of correction factors for a case of exponential distribution and Veybull's distribution.

A hierarchical model for ordinal matrix factorization

DEFF Research Database (Denmark)

Paquet, Ulrich; Thomson, Blaise; Winther, Ole

2012-01-01

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

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

International Nuclear Information System (INIS)

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

2012-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2012-03-01

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

Emotional intelligence is a second-stratum factor of intelligence: evidence from hierarchical and bifactor models.

Science.gov (United States)

MacCann, Carolyn; Joseph, Dana L; Newman, Daniel A; Roberts, Richard D

2014-04-01

This article examines the status of emotional intelligence (EI) within the structure of human cognitive abilities. To evaluate whether EI is a 2nd-stratum factor of intelligence, data were fit to a series of structural models involving 3 indicators each for fluid intelligence, crystallized intelligence, quantitative reasoning, visual processing, and broad retrieval ability, as well as 2 indicators each for emotion perception, emotion understanding, and emotion management. Unidimensional, multidimensional, hierarchical, and bifactor solutions were estimated in a sample of 688 college and community college students. Results suggest adequate fit for 2 models: (a) an oblique 8-factor model (with 5 traditional cognitive ability factors and 3 EI factors) and (b) a hierarchical solution (with cognitive g at the highest level and EI representing a 2nd-stratum factor that loads onto g at λ = .80). The acceptable relative fit of the hierarchical model confirms the notion that EI is a group factor of cognitive ability, marking the expression of intelligence in the emotion domain. The discussion proposes a possible expansion of Cattell-Horn-Carroll theory to include EI as a 2nd-stratum factor of similar standing to factors such as fluid intelligence and visual processing.

Semi-empirical model for the calculation of flow friction factors in wire-wrapped rod bundles

International Nuclear Information System (INIS)

Carajilescov, P.; Fernandez y Fernandez, E.

1981-08-01

LMFBR fuel elements consist of wire-wrapped rod bundles, with triangular array, with the fluid flowing parallel to the rods. A semi-empirical model is developed in order to obtain the average bundle friction factor, as well as the friction factor for each subchannel. The model also calculates the flow distribution factors. The results are compared to experimental data for geometrical parameters in the range: P(div)D = 1.063 - 1.417, H(div)D = 4 - 50, and are considered satisfactory. (Author) [pt

Skyrme-model πNN form factor and nucleon-nucleon interaction

International Nuclear Information System (INIS)

Holzwarth, G.; Machleidt, R.

1997-01-01

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

Atmospheric Deposition Modeling Results

Data.gov (United States)

U.S. Environmental Protection Agency — This asset provides data on model results for dry and total deposition of sulfur, nitrogen and base cation species. Components include deposition velocities, dry...

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...

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.

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.

Talent identification model for sprinter using discriminant factor

Science.gov (United States)

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

2018-01-01

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

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

Science.gov (United States)

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

2004-04-01

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

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

Directory of Open Access Journals (Sweden)

Cosgrave Elizabeth M

2008-09-01

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

Numerical modelling of radon-222 entry into houses: An outline of techniques and results

DEFF Research Database (Denmark)

Andersen, C.E.

2001-01-01

Numerical modelling is a powerful tool for studies of soil gas and radon-222 entry into houses. It is the purpose of this paper to review some main techniques and results. In the past, modelling has focused on Darcy flow of soil gas (driven by indoor–outdoor pressure differences) and combined...... diffusive and advective transport of radon. Models of different complexity have been used. The simpler ones are finite-difference models with one or two spatial dimensions. The more complex models allow for full three-dimensional and time dependency. Advanced features include: soil heterogeneity, anisotropy......, fractures, moisture, non-uniform soil temperature, non-Darcy flow of gas, and flow caused by changes in the atmospheric pressure. Numerical models can be used to estimate the importance of specific factors for radon entry. Models are also helpful when results obtained in special laboratory or test structure...

Strange mesonic transition form factor in the chiral constituent quark model

International Nuclear Information System (INIS)

Ito, H.; Ramsey-Musolf, M.J.

1998-01-01

The form factor g ρπ (S) (Q 2 ) of the strange vector current transition matrix element left-angle ρ|bar sγ μ s|π right-angle is calculated within the chiral quark model. A strange vector current of the constituent U and D quarks is induced by kaon radiative corrections and this mechanism yields the nonvanishing values of g ρπ (S) (0). The numerical result at the photon point is consistent with the one given by the φ-meson dominance model, but the falloff in the Q 2 dependence is faster than the monopole form factor. Mesonic radiative corrections are also examined for the electromagnetic ρ-to-π and K * -to-K transition amplitudes. copyright 1998 The American Physical Society

A Model of Factors Contributing to STEM Learning and Career Orientation

Science.gov (United States)

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

2015-05-01

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

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

Science.gov (United States)

Elklit, Ask; Shevlin, Mark

2007-09-01

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

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

Directory of Open Access Journals (Sweden)

Yunelly Asra

2017-12-01

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

Linear regression metamodeling as a tool to summarize and present simulation model results.

Science.gov (United States)

Jalal, Hawre; Dowd, Bryan; Sainfort, François; Kuntz, Karen M

2013-10-01

Modelers lack a tool to systematically and clearly present complex model results, including those from sensitivity analyses. The objective was to propose linear regression metamodeling as a tool to increase transparency of decision analytic models and better communicate their results. We used a simplified cancer cure model to demonstrate our approach. The model computed the lifetime cost and benefit of 3 treatment options for cancer patients. We simulated 10,000 cohorts in a probabilistic sensitivity analysis (PSA) and regressed the model outcomes on the standardized input parameter values in a set of regression analyses. We used the regression coefficients to describe measures of sensitivity analyses, including threshold and parameter sensitivity analyses. We also compared the results of the PSA to deterministic full-factorial and one-factor-at-a-time designs. The regression intercept represented the estimated base-case outcome, and the other coefficients described the relative parameter uncertainty in the model. We defined simple relationships that compute the average and incremental net benefit of each intervention. Metamodeling produced outputs similar to traditional deterministic 1-way or 2-way sensitivity analyses but was more reliable since it used all parameter values. Linear regression metamodeling is a simple, yet powerful, tool that can assist modelers in communicating model characteristics and sensitivity analyses.

Electromagnetic and Scalar Pion form factor in the Kroll-Lee-Zumino model

International Nuclear Information System (INIS)

Dominguez, C.A.; Jottar, J.I.; Loewe, M.; Willers, B.

2009-01-01

The renormalizable Abelian quantum field theory model of Kroll, Lee, and Zumino is used at the one loop level to compute vertex corrections to the tree-level, Vector Meson Dominance (VMD) electromagnetic pion form factor. These corrections, together with the one-loop vacuum polarization contribution, imply a resulting electromagnetic pion form factor in excellent agreement with data in the whole range of accessible momentum transfers in the space-like region. The time-like form factor, which reproduces the Gounaris-Sakurai formula at and near the rho-meson peak, is unaffected by the vertex correction at order O(g 2 ). The KLZ model is also used to compute the scalar radius of the pion at the one loop level, finding π 2 > S =0.40fm 2 . This value implies for the low energy constant of chiral perturbation theory l-bar 4 =3.4

Results of the naive quark model

International Nuclear Information System (INIS)

Gignoux, C.

1987-10-01

The hypotheses and limits of the naive quark model are recalled and results on nucleon-nucleon scattering and possible multiquark states are presented. Results show that with this model, ropers do not come. For hadron-hadron interactions, the model predicts Van der Waals forces that the resonance group method does not allow. Known many-body forces are not found in the model. The lack of mesons shows up in the absence of a far reaching force. However, the model does have strengths. It is free from spuriousness of center of mass, and allows a democratic handling of flavor. It has few parameters, and its predictions are very good [fr

Generalized Efficient Inference on Factor Models with Long-Range Dependence

DEFF Research Database (Denmark)

Ergemen, Yunus Emre

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

Combination of Gold Nanoparticle-Conjugated Tumor Necrosis Factor-α and Radiation Therapy Results in a Synergistic Antitumor Response in Murine Carcinoma Models

Energy Technology Data Exchange (ETDEWEB)

Koonce, Nathan A. [Department of Radiation Oncology, University of Arkansas for Medical Sciences, Little Rock, Arkansas (United States); Quick, Charles M. [Department of Pathology, University of Arkansas for Medical Sciences, Little Rock, Arkansas (United States); Hardee, Matthew E.; Jamshidi-Parsian, Azemat; Dent, Judith A. [Department of Radiation Oncology, University of Arkansas for Medical Sciences, Little Rock, Arkansas (United States); Paciotti, Giulio F. [CytImmune Sciences, Rockville, Maryland (United States); Nedosekin, Dmitry [Department of Otolaryngology, University of Arkansas for Medical Sciences, Little Rock, Arkansas (United States); Dings, Ruud P.M. [Department of Radiation Oncology, University of Arkansas for Medical Sciences, Little Rock, Arkansas (United States); Griffin, Robert J., E-mail: RJGriffin@uams.edu [Department of Radiation Oncology, University of Arkansas for Medical Sciences, Little Rock, Arkansas (United States)

2015-11-01

Purpose: Although remarkable preclinical antitumor effects have been shown for tumor necrosis factor-α (TNF) alone and combined with radiation, its clinical use has been hindered by systemic dose-limiting toxicities. We investigated the physiological and antitumor effects of radiation therapy combined with the novel nanomedicine CYT-6091, a 27-nm average-diameter polyethylene glycol-TNF-coated gold nanoparticle, which recently passed through phase 1 trials. Methods and Materials: The physiologic and antitumor effects of single and fractionated radiation combined with CYT-6091 were studied in the murine 4T1 breast carcinoma and SCCVII head and neck tumor squamous cell carcinoma models. Results: In the 4T1 murine breast tumor model, we observed a significant reduction in the tumor interstitial fluid pressure (IFP) 24 hours after CYT-6091 alone and combined with a radiation dose of 12 Gy (P<.05 vs control). In contrast, radiation alone (12 Gy) had a negligible effect on the IFP. In the SCCVII head and neck tumor model, the baseline IFP was not markedly elevated, and little additional change occurred in the IFP after single-dose radiation or combined therapy (P>.05 vs control) despite extensive vascular damage observed. The IFP reduction in the 4T1 model was also associated with marked vascular damage and extravasation of red blood cells into the tumor interstitium. A sustained reduction in tumor cell density was observed in the combined therapy group compared with all other groups (P<.05). Finally, we observed a more than twofold delay in tumor growth when CYT-6091 was combined with a single 20-Gy radiation dose—notably, irrespective of the treatment sequence. Moreover, when hypofractionated radiation (12 Gy × 3) was applied with CYT-6091 treatment, a more than five-fold growth delay was observed in the combined treatment group of both tumor models and determined to be synergistic. Conclusions: Our results have demonstrated that TNF-labeled gold

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.

PERBANDINGAN CAPITAL ASSET PRICING MODEL (CAPM DAN THREE FACTORS MODEL FAMA AND FRENCH (TFMFF DALAM MENGESTIMASI RETURN SAHAM

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.

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

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....... 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...... 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...

Innovative supply chain optimization models with multiple uncertainty factors

DEFF Research Database (Denmark)

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

2017-01-01

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

[Monitoring of nursing service context factors: first descriptive results of a cross-sectional Swiss study prior the introduction of SwissDRG].

Science.gov (United States)

Kleinknecht-Dolf, Michael; Spichiger, Elisabeth; Frei, Irena Anna; Müller, Marianne; Martin, Jacqueline S; Spirig, Rebecca

2015-04-01

The adoption of DRG-based payment systems has narrowed hospitals' financial margins, necessitating streamlining and process optimization. The experience of other countries shows that this restructuring can influence context factors essential to the delivery of nursing care. As a result, nursing care quality and patient safety may be impacted. The Sinergia Project aims to develop a monitoring model and related instruments to continuously monitor the impact of DRG-based reimbursement on central nursing service context factors. The descriptive, quantitative results were collected within the framework of a study with a mixed methods design by means of an online survey in which nurses from five hospitals participated. The results show that the nursing service context factors examined (nursing care complexity, quality of the work environment, management, moral distress and job satisfaction), have relevance in all practice areas as regards practice setting and nursing care delivery. Patterns can be recognized that are consistent with those found in the literature and which could be an indication of the relationships between the context factors above, as was hypothesized in the model. The study has provided the participating hospitals with useful data upon which to base discussions on ensuring quality of nursing care and practice development, in addition to information important to the further development of the model and the instruments employed.

A rough multi-factor model of electricity spot prices

International Nuclear Information System (INIS)

Bennedsen, Mikkel

2017-01-01

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

Influence of Various Irradiance Models and Their Combination on Simulation Results of Photovoltaic Systems

Directory of Open Access Journals (Sweden)

Martin Hofmann

2017-09-01

Full Text Available We analyze the output of various state-of-the-art irradiance models for photovoltaic systems. The models include two sun position algorithms, three types of input data time series, nine diffuse fraction models and five transposition models (for tilted surfaces, resulting in 270 different model chains for the photovoltaic (PV system simulation. These model chains are applied to 30 locations worldwide and three different module tracking types, totaling in 24,300 simulations. We show that the simulated PV yearly energy output varies between −5% and +8% for fixed mounted PV modules and between −26% and +14% for modules with two-axis tracking. Model quality varies strongly between locations; sun position algorithms have negligible influence on the simulation results; diffuse fraction models add a lot of variability; and transposition models feature the strongest influence on the simulation results. To highlight the importance of irradiance with high temporal resolution, we present an analysis of the influence of input temporal resolution and simulation models on the inverter clipping losses at varying PV system sizing factors for Lindenberg, Germany. Irradiance in one-minute resolution is essential for accurately calculating inverter clipping losses.

Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

Science.gov (United States)

Abumeri, Galib H.; Chamis, Christos C.

2010-01-01

Complex material behavior is represented by a single equation of product form to account for interaction among the various factors. The factors are selected by the physics of the problem and the environment that the model is to represent. For example, different factors will be required for each to represent temperature, moisture, erosion, corrosion, etc. It is important that the equation represent the physics of the behavior in its entirety accurately. The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the external launch tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points - the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used were obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated. The problem lies in how to represent the divot weight with a single equation. A unique solution to this problem is a multi-factor equation of product form. Each factor is of the following form (1 xi/xf)ei, where xi is the initial value, usually at ambient conditions, xf the final value, and ei the exponent that makes the curve represented unimodal that meets the initial and final values. The exponents are either evaluated by test data or by technical judgment. A minor disadvantage may be the selection of exponents in the absence of any empirical data. This form has been used successfully in describing the foam ejected in simulated space environmental conditions. Seven factors were required

The multi-factor energy input–output model

International Nuclear Information System (INIS)

Guevara, Zeus; Domingos, Tiago

2017-01-01

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

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

KAUST Repository

Ting, Chee-Ming

2017-12-06

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

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.

Nucleon electromagnetic form factors in a relativistic quark model with chiral symmetry

International Nuclear Information System (INIS)

Barik, N.

1987-01-01

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. (author)

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.

Analysis on trust influencing factors and trust model from multiple perspectives of online Auction

Science.gov (United States)

Yu, Wang

2017-10-01

Current reputation models lack the research on online auction trading completely so they cannot entirely reflect the reputation status of users and may cause problems on operability. To evaluate the user trust in online auction correctly, a trust computing model based on multiple influencing factors is established. It aims at overcoming the efficiency of current trust computing methods and the limitations of traditional theoretical trust models. The improved model comprehensively considers the trust degree evaluation factors of three types of participants according to different participation modes of online auctioneers, to improve the accuracy, effectiveness and robustness of the trust degree. The experiments test the efficiency and the performance of our model under different scale of malicious user, under environment like eBay and Sporas model. The experimental results analysis show the model proposed in this paper makes up the deficiency of existing model and it also has better feasibility.

Quantifying credit portfolio losses under multi-factor models

NARCIS (Netherlands)

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

2018-01-01

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

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

Science.gov (United States)

Wan, Gloria W Y; Leung, Patrick W L

2010-10-01

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

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...

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

DEFF Research Database (Denmark)

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

2015-01-01

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

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

DEFF Research Database (Denmark)

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

2013-01-01

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

Assessing a five factor model of PTSD: is dysphoric arousal a unique PTSD construct showing differential relationships with anxiety and depression?

Science.gov (United States)

Armour, Cherie; Elhai, Jon D; Richardson, Don; Ractliffe, Kendra; Wang, Li; Elklit, Ask

2012-03-01

Posttraumatic stress disorder's (PTSD) latent structure has been widely debated. To date, two four-factor models (Numbing and Dysphoria) have received the majority of factor analytic support. Recently, Elhai et al. (2011) proposed and supported a revised (five-factor) Dysphoric Arousal model. Data were gathered from two separate samples; War veterans and Primary Care medical patients. The three models were compared and the resultant factors of the Dysphoric Arousal model were validated against external constructs of depression and anxiety. The Dysphoric Arousal model provided significantly better fit than the Numbing and Dysphoria models across both samples. When differentiating between factors, the current results support the idea that Dysphoric Arousal can be differentiated from Anxious Arousal but not from Emotional Numbing when correlated with depression. In conclusion, the Dysphoria model may be a more parsimonious representation of PTSD's latent structure in these trauma populations despite superior fit of the Dysphoric Arousal model. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

Directory of Open Access Journals (Sweden)

Hossein Bevrani, PhD

2011-09-01

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

Assessment of the five-factor model of personality.

Science.gov (United States)

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.

First results from the International Urban Energy Balance Model Comparison: Model Complexity

Science.gov (United States)

Blackett, M.; Grimmond, S.; Best, M.

2009-04-01

A great variety of urban energy balance models has been developed. These vary in complexity from simple schemes that represent the city as a slab, through those which model various facets (i.e. road, walls and roof) to more complex urban forms (including street canyons with intersections) and features (such as vegetation cover and anthropogenic heat fluxes). Some schemes also incorporate detailed representations of momentum and energy fluxes distributed throughout various layers of the urban canopy layer. The models each differ in the parameters they require to describe the site and the in demands they make on computational processing power. Many of these models have been evaluated using observational datasets but to date, no controlled comparisons have been conducted. Urban surface energy balance models provide a means to predict the energy exchange processes which influence factors such as urban temperature, humidity, atmospheric stability and winds. These all need to be modelled accurately to capture features such as the urban heat island effect and to provide key information for dispersion and air quality modelling. A comparison of the various models available will assist in improving current and future models and will assist in formulating research priorities for future observational campaigns within urban areas. In this presentation we will summarise the initial results of this international urban energy balance model comparison. In particular, the relative performance of the models involved will be compared based on their degree of complexity. These results will inform us on ways in which we can improve the modelling of air quality within, and climate impacts of, global megacities. The methodology employed in conducting this comparison followed that used in PILPS (the Project for Intercomparison of Land-Surface Parameterization Schemes) which is also endorsed by the GEWEX Global Land Atmosphere System Study (GLASS) panel. In all cases, models were run

Trends and determinant factors for population blood pressure with 25 years of follow-up: results from the Copenhagen City Heart Study

DEFF Research Database (Denmark)

Andersen, Ulla Overgaard; Jensen, Gorm B

2010-01-01

) did not receive antihypertensive therapy. METHODS: The BP measurement was fully standardized and measurement method was unchanged throughout the observation period. A questionnaire concerning drinking habits, smoking, medical therapy and physical exercise was completed by the participants and double...... checked by the technicians. RESULTS: After an initial increase, population systolic BP (SBP) decreased. All risk factors were tested in the longitudinal model by means of a residual likelihood ratio test. The final model included sex, age and body mass index as significant factors and covariates. Two...

Modeling Indicator Systems for Evaluating Environmental Sustainable Development Based on Factor Analysis

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.

The Barrett–Crane model: asymptotic measure factor

International Nuclear Information System (INIS)

Kamiński, Wojciech; Steinhaus, Sebastian

2014-01-01

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

The Barrett-Crane model: asymptotic measure factor

Science.gov (United States)

Kamiński, Wojciech; Steinhaus, Sebastian

2014-04-01

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

Supplementary Material for: Factor Copula Models for Replicated Spatial Data

KAUST Repository

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

2016-01-01

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

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

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Tawanda B. Chiyangwa

2017-10-01

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

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

Science.gov (United States)

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

2018-05-04

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

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

Science.gov (United States)

Alboni, Paolo; Alboni, Marco

2006-11-01

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

Testing for time-varying loadings in dynamic factor models

DEFF Research Database (Denmark)

Mikkelsen, Jakob Guldbæk

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

Combination of Gold Nanoparticle-Conjugated Tumor Necrosis Factor-α and Radiation Therapy Results in a Synergistic Antitumor Response in Murine Carcinoma Models.

Science.gov (United States)

Koonce, Nathan A; Quick, Charles M; Hardee, Matthew E; Jamshidi-Parsian, Azemat; Dent, Judith A; Paciotti, Giulio F; Nedosekin, Dmitry; Dings, Ruud P M; Griffin, Robert J

2015-11-01

Although remarkable preclinical antitumor effects have been shown for tumor necrosis factor-α (TNF) alone and combined with radiation, its clinical use has been hindered by systemic dose-limiting toxicities. We investigated the physiological and antitumor effects of radiation therapy combined with the novel nanomedicine CYT-6091, a 27-nm average-diameter polyethylene glycol-TNF-coated gold nanoparticle, which recently passed through phase 1 trials. The physiologic and antitumor effects of single and fractionated radiation combined with CYT-6091 were studied in the murine 4T1 breast carcinoma and SCCVII head and neck tumor squamous cell carcinoma models. In the 4T1 murine breast tumor model, we observed a significant reduction in the tumor interstitial fluid pressure (IFP) 24 hours after CYT-6091 alone and combined with a radiation dose of 12 Gy (P.05 vs control) despite extensive vascular damage observed. The IFP reduction in the 4T1 model was also associated with marked vascular damage and extravasation of red blood cells into the tumor interstitium. A sustained reduction in tumor cell density was observed in the combined therapy group compared with all other groups (P<.05). Finally, we observed a more than twofold delay in tumor growth when CYT-6091 was combined with a single 20-Gy radiation dose-notably, irrespective of the treatment sequence. Moreover, when hypofractionated radiation (12 Gy × 3) was applied with CYT-6091 treatment, a more than five-fold growth delay was observed in the combined treatment group of both tumor models and determined to be synergistic. Our results have demonstrated that TNF-labeled gold nanoparticles combined with single or fractionated high-dose radiation therapy is effective in reducing IFP and tumor growth and shows promise for clinical translation. Copyright © 2015 Elsevier Inc. All rights reserved.

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

Directory of Open Access Journals (Sweden)

Jiun-Yu Wu

2017-09-01

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

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

International Nuclear Information System (INIS)

Zhou, Jian; Qi, Jinyi

2014-01-01

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

Modeling of dengue occurrences early warning involving temperature and rainfall factors

Directory of Open Access Journals (Sweden)

Prama Setia Putra

2017-07-01

Full Text Available Objective: To understand dengue transmission process and its vector dynamics and to develop early warning model of dengue occurrences based on mosquito population and host-vector threshold values considering temperature and rainfall. Methods: To obtain the early warning model, mosquito population and host-vector models are developed initially. Both are developed using differential equations. Basic offspring number (R0m and basic reproductive ratio (R0d which are the threshold values are derived from the models under constant parameters assumption. Temperature and rainfall effects on mosquito and dengue are performed in entomological and disease transmission parameters. Some of parameters are set as functions of temperature or rainfall while other parameters are set to be constant. Hereafter, both threshold values are computed using those parameters. Monthly dengue occurrences data are categorized as zero and one values which one means the outbreak does occur in that month. Logistics regression is chosen to bridge the threshold values and categorized data. Threshold values are considered as the input of early warning model. Semarang city is selected as the sample to develop this early waning model. Results: The derived threshold values which are R 0 m and R 0 d show to have relation that mosquito as dengue vector affects transmission of the disease. Result of the early warning model will be a value between zero and one. It is categorized as outbreak does occur when the value is larger than 0.5 while other is categorized as outbreak does not occur. By using single predictor, the model can perform 68% accuracy approximately. Conclusions: The extinction of mosquitoes will be followed by disease disappearance while mosquitoes existence can lead to disease free or endemic states. Model simulations show that mosquito population are more affected by weather factors than human. Involving weather factors implicitly in the threshold value and linking them

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

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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

Modelling human factor with Petri nets

International Nuclear Information System (INIS)

Bedreaga, Luminita; Constantinescu, Cristina; Guzun, Basarab

2007-01-01

The human contribution to risk and safety of nuclear power plant operation can be best understood, assessed and quantified using tools to evaluate human reliability. Human reliability analysis becomes an important part of every probabilistic safety assessment and it is used to demonstrate that nuclear power plants designed with different safety levels are prepared to cope with severe accidents. Human reliability analysis in context of probabilistic safety assessment consists in: identifying human-system interactions important to safety; quantifying probabilities appropriate with these interactions. Nowadays, the complex system functions can be modelled using special techniques centred either on states space adequate to system or on events appropriate to the system. Knowing that complex system model consists in evaluating the likelihood of success, in other words, in evaluating the possible value for that system being in some state, the inductive methods which are based on the system states can be applied also for human reliability modelling. Thus, switching to the system states taking into account the human interactions, the underlying basis of the Petri nets can be successfully applied and the likelihoods appropriate to these states can also derived. The paper presents the manner to assess the human reliability quantification using Petri nets approach. The example processed in the paper is from human reliability documentation without a detailed human factor analysis (qualitative). The obtained results by these two kinds of methods are in good agreement. (authors)

Large Psub(tr) and quark-quark cross section in the dynamical model of factorizing quarks

International Nuclear Information System (INIS)

Kapshay, V.N.; Sidorov, A.V.; Skachkov, N.B.

1978-01-01

Dynamical model of factorizing quarks containing the quark mass as free model parameter was described. Model calculations were compared with the experimental data on the cross section of the inclusive πsup(o) meson production in the proton-proton interaction. It is shown that the results of the paper are in good agreement with experiments

Comparing statistical and machine learning classifiers: alternatives for predictive modeling in human factors research.

Science.gov (United States)

Carnahan, Brian; Meyer, Gérard; Kuntz, Lois-Ann

2003-01-01

Multivariate classification models play an increasingly important role in human factors research. In the past, these models have been based primarily on discriminant analysis and logistic regression. Models developed from machine learning research offer the human factors professional a viable alternative to these traditional statistical classification methods. To illustrate this point, two machine learning approaches--genetic programming and decision tree induction--were used to construct classification models designed to predict whether or not a student truck driver would pass his or her commercial driver license (CDL) examination. The models were developed and validated using the curriculum scores and CDL exam performances of 37 student truck drivers who had completed a 320-hr driver training course. Results indicated that the machine learning classification models were superior to discriminant analysis and logistic regression in terms of predictive accuracy. Actual or potential applications of this research include the creation of models that more accurately predict human performance outcomes.

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

Directory of Open Access Journals (Sweden)

Budhinath Padhy

2015-02-01

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

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

NARCIS (Netherlands)

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

2016-01-01

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

Bayesian Sensitivity Analysis of a Nonlinear Dynamic Factor Analysis Model with Nonparametric Prior and Possible Nonignorable Missingness.

Science.gov (United States)

Tang, Niansheng; Chow, Sy-Miin; Ibrahim, Joseph G; Zhu, Hongtu

2017-12-01

Many psychological concepts are unobserved and usually represented as latent factors apprehended through multiple observed indicators. When multiple-subject multivariate time series data are available, dynamic factor analysis models with random effects offer one way of modeling patterns of within- and between-person variations by combining factor analysis and time series analysis at the factor level. Using the Dirichlet process (DP) as a nonparametric prior for individual-specific time series parameters further allows the distributional forms of these parameters to deviate from commonly imposed (e.g., normal or other symmetric) functional forms, arising as a result of these parameters' restricted ranges. Given the complexity of such models, a thorough sensitivity analysis is critical but computationally prohibitive. We propose a Bayesian local influence method that allows for simultaneous sensitivity analysis of multiple modeling components within a single fitting of the model of choice. Five illustrations and an empirical example are provided to demonstrate the utility of the proposed approach in facilitating the detection of outlying cases and common sources of misspecification in dynamic factor analysis models, as well as identification of modeling components that are sensitive to changes in the DP prior specification.

Assessment of theoretical and experimental results in the calculation of atmospheric dilution factors in the Atucha I nuclear power plant

International Nuclear Information System (INIS)

Quintana, E.E.; Tossi, M.H.; Telleria, D.M.

1990-01-01

Collective doses produced during the normal working of the Atucha I Nuclear Power Plant are calculated using annual atmospheric factors. This work studies the behaviour of the dilution factors in different periods of the year in order to fit the calculated dose model applying factors from seasonal, monthly or weekly periods. The Radiation Protection Group of the C.N.E.A. have carried out continuous environmental monitoring in the surroundings of the Atucha I Nuclear Power Plant. These studies include the measurement of air tritium concentration, radionuclide that is found principally as tritiated water vapour. This isotope, normally released by the nuclear power plant was used as a tracer to assess the atmospheric dilution factors. Factors were calculated by two methods: an experimental one, based on environmental measurements of the tritium concentration in the surroundings of the nuclear power plant and another one by applying a theoretical model based on information from the micrometeorological tower located in the mentioned place. To carry out the environmental monitoring, four monitoring stations in the surroundings of the power plant were chosen. Three of them are approximately one kilometer from the plant and the fourth is 7.5 km away, near the city of Lima. To condense and collect the atmospheric water vapour, an overcooling system was used. The measurement was performed by liquid scintillation counting, previous alkaline electrolytical enrichment of the samples. The theoretical model uses hourly values of direction and wind intensity, as well as the atmospheric dispersive properties. Values obtained during the period 1976 to 1988 allowed, applying statistical tests, to validate the theoretical model and to observe seasonal variation of the dilution factors throughout the same year and between different years. Finally, results and graphics are presented showing that the behaviour of the dilution factors in different periods of the year. It is recommended to

Identifying the environmental factors that effect within canopy BVOC loss using a multilevel canopy model

Science.gov (United States)

Chan, W. S.; Fuentes, J. D.; Lerdau, M.

2010-12-01

This presentation will provide research findings to evaluate the hypothesis that the loss of biogenic volatile organic compound (BVOC) within plant canopies is dynamic and depends on factors such as plant canopy architecture (height and leaf area distribution), atmospheric turbulence, concentration of oxidants (OH, O3, NO3), and the reactivity of BVOC species. Results will be presented from a new one dimensional, multilevel canopy model that couples algorithms for canopy microclimate, leaf physiology, BVOC emission, turbulent transport, and atmospheric chemistry to investigate the relative importance of factors that impact BVOC loss within a forest canopy. Model sensitivity tests will be presented and discussed to identify factors driving canopy loss. Results show isoprene and monoterpene canopy losses as high as 9 and 18%, respectively, for tall canopies during the daytime. We hypothesize that canopy height and wind speed (i.e. canopy residence time) may be the most important in dictating within-canopy loss. This work will reduce the error in bottom-up flux estimates of BVOCs and ultimately improve parameterizations of BVOC sources in air quality models by accounting for within canopy processes.

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

Science.gov (United States)

Byeon, Haewon

2015-01-01

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

Using Structured Additive Regression Models to Estimate Risk Factors of Malaria: Analysis of 2010 Malawi Malaria Indicator Survey Data

Science.gov (United States)

Chirombo, James; Lowe, Rachel; Kazembe, Lawrence

2014-01-01

Background After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. Methods We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. Results Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. Conclusions The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities. PMID:24991915

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

Directory of Open Access Journals (Sweden)

Naraiana de Oliveira Tavares

2014-12-01

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

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

Science.gov (United States)

Wieske, Joseph

2017-09-01

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

Factors Associated with Asthma ED Visit Rates among Medicaid-enrolled Children: A Structural Equation Modeling Approach

Directory of Open Access Journals (Sweden)

Luceta McRoy

2017-02-01

Full Text Available Background: Asthma is one of the leading causes of emergency department visits and school absenteeism among school-aged children in the United States, but there is significant local-area variation in emergency department visit rates, as well as significant differences across racial-ethnic groups. Analysis: We first calculated emergency department (ED visit rates among Medicaid-enrolled children age 5–12 with asthma using a multi-state dataset. We then performed exploratory factor analysis using over 226 variables to assess whether they clustered around three county-level conceptual factors (socioeconomic status, healthcare capacity, and air quality thought to be associated with variation in asthma ED visit rates. Measured variables (including ED visit rate as the outcome of interest were then standardized and tested in a simple conceptual model through confirmatory factor analysis. Results: County-level (contextual variables did cluster around factors declared a priori in the conceptual model. Structural equation models connecting the ED visit rates to socioeconomic status, air quality, and healthcare system professional capacity factors (consistent with our conceptual framework converged on a solution and achieved a reasonable goodness of fit on confirmatory factor analysis. Conclusion: Confirmatory factor analysis offers an approach for quantitatively testing conceptual models of local-area variation and racial disparities in asthma-related emergency department use.

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

Science.gov (United States)

Maldonado, G; Greenland, S

1998-07-01

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

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

DEFF Research Database (Denmark)

Carstensen, Tina; Kasch, Helge; Frostholm, Lisbeth

2017-01-01

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

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.

Science.gov (United States)

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2011-01-01

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

Testing multi-factor asset pricing models in the Visegrad countries

Czech Academy of Sciences Publication Activity Database

Morgese Borys, Magdalena

2011-01-01

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

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

Science.gov (United States)

Eid, Michael; Koch, Tobias

2014-01-01

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

Changes in diet, cardiovascular risk factors and modelled cardiovascular risk following diagnosis of diabetes: 1-year results from the ADDITION-Cambridge trial cohort.

Science.gov (United States)

Savory, L A; Griffin, S J; Williams, K M; Prevost, A T; Kinmonth, A-L; Wareham, N J; Simmons, R K

2014-02-01

To describe change in self-reported diet and plasma vitamin C, and to examine associations between change in diet and cardiovascular disease risk factors and modelled 10-year cardiovascular disease risk in the year following diagnosis of Type 2 diabetes. Eight hundred and sixty-seven individuals with screen-detected diabetes underwent assessment of self-reported diet, plasma vitamin C, cardiovascular disease risk factors and modelled cardiovascular disease risk at baseline and 1 year (n = 736) in the ADDITION-Cambridge trial. Multivariable linear regression was used to quantify the association between change in diet and cardiovascular disease risk at 1 year, adjusting for change in physical activity and cardio-protective medication. Participants reported significant reductions in energy, fat and sodium intake, and increases in fruit, vegetable and fibre intake over 1 year. The reduction in energy was equivalent to an average-sized chocolate bar; the increase in fruit was equal to one plum per day. There was a small increase in plasma vitamin C levels. Increases in fruit intake and plasma vitamin C were associated with small reductions in anthropometric and metabolic risk factors. Increased vegetable intake was associated with an increase in BMI and waist circumference. Reductions in fat, energy and sodium intake were associated with reduction in HbA1c , waist circumference and total cholesterol/modelled cardiovascular disease risk, respectively. Improvements in dietary behaviour in this screen-detected population were associated with small reductions in cardiovascular disease risk, independently of change in cardio-protective medication and physical activity. Dietary change may have a role to play in the reduction of cardiovascular disease risk following diagnosis of diabetes. © 2013 The Authors. Diabetic Medicine published by John Wiley & Sons Ltd on behalf of Diabetes UK.

The Factors of Forming the National HR-Management Model

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Elena P. Kostenko

2017-12-01

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

Interpreting Results from the Multinomial Logit Model

DEFF Research Database (Denmark)

Wulff, Jesper

2015-01-01

This article provides guidelines and illustrates practical steps necessary for an analysis of results from the multinomial logit model (MLM). The MLM is a popular model in the strategy literature because it allows researchers to examine strategic choices with multiple outcomes. However, there see...... suitable for both interpretation and communication of results. The pratical steps are illustrated through an application of the MLM to the choice of foreign market entry mode.......This article provides guidelines and illustrates practical steps necessary for an analysis of results from the multinomial logit model (MLM). The MLM is a popular model in the strategy literature because it allows researchers to examine strategic choices with multiple outcomes. However, there seem...... to be systematic issues with regard to how researchers interpret their results when using the MLM. In this study, I present a set of guidelines critical to analyzing and interpreting results from the MLM. The procedure involves intuitive graphical representations of predicted probabilities and marginal effects...

Hadron form factors in the constituent quark model

International Nuclear Information System (INIS)

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

1998-01-01

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

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

Science.gov (United States)

Trull, Timothy J.; Widiger, Thomas A.

2013-01-01

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

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

Science.gov (United States)

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

2013-10-01

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

Modeling the factors that influence knowledge transfer in mergers and acquisitions

Institute of Scientific and Technical Information of China (English)

YU Haiyan; LIANG Zhanping

2010-01-01

This paper constructs a model on the factors that influence knowledge transfer in mergers and acquisitions (M&A) and validates it via questionnaire surveys.Using 125 valid collected questionnaires,multiple linear regression analysis and hierarchical regression analysis showed that five out of the ten factors had a positive effect on knowledge transfer effect.The ranking of factor importance,from high to low,was knowledge explicitness,relationship quality,learning intent,advanced transfer activities,and learning capability,which is fairly consistent with positive factors observed in other interorganizational knowledge transfer researches.Our results also showed that one of the control variables (size of acquired firm) had neither a direct or indirect effect on knowledge transfer in M&A.Additionally,our research found that knowledge distance and degree of M&A integration had a positive influence on knowledge transfer effect at the early stage after M&A,but had a negative influence at the late stage.Based on this research,several suggestions for knowledge transfer in M&A are proposed.

Modeling the factors that influence knowledge transfer in mergers and acquisitions

Institute of Scientific and Technical Information of China (English)

YU; Haiyan; LIANG; Zhanping

2010-01-01

This paper constructs a model on the factors that influence knowledge transfer in mergers and acquisitions(M&A)and validates it via questionnaire surveys.Using 125valid collected questionnaires,multiple linear regression analysis and hierarchical regression analysis showed that five out of the ten factors had a positive effect on knowledge transfer effect.The ranking of factor importance,from high to low,was knowledge explicitness,relationship quality,learning intent,advanced transfer activities,and learning capability,which is fairly consistent with positive factors observed in other interorganizational knowledge transfer researches.Our results also showed that one of the control variables(size of acquired firm)had neither a direct or indirect effect on knowledge transfer in M&A.Additionally,our research found that knowledge distance and degree of M&A integration had a positive influence on knowledge transfer effect at the early stage after M&A,but had a negative influence at the late stage.Based on this research,several suggestions for knowledge transfer in M&A are proposed.

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

Directory of Open Access Journals (Sweden)

Francisco José Gondim Pitanga

2014-09-01

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

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

Science.gov (United States)

Yu, Yan; Qiu, Robin G

2014-01-01

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

Evaluation of the Thermodynamic Models for the Thermal Diffusion Factor

DEFF Research Database (Denmark)

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

2003-01-01

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

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

Directory of Open Access Journals (Sweden)

Živanović Marko

2017-01-01

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

Probabilistic safety assessment model in consideration of human factors based on object-oriented bayesian networks

International Nuclear Information System (INIS)

Zhou Zhongbao; Zhou Jinglun; Sun Quan

2007-01-01

Effect of Human factors on system safety is increasingly serious, which is often ignored in traditional probabilistic safety assessment methods however. A new probabilistic safety assessment model based on object-oriented Bayesian networks is proposed in this paper. Human factors are integrated into the existed event sequence diagrams. Then the classes of the object-oriented Bayesian networks are constructed which are converted to latent Bayesian networks for inference. Finally, the inference results are integrated into event sequence diagrams for probabilistic safety assessment. The new method is applied to the accident of loss of coolant in a nuclear power plant. the results show that the model is not only applicable to real-time situation assessment, but also applicable to situation assessment based certain amount of information. The modeling complexity is kept down and the new method is appropriate to large complex systems due to the thoughts of object-oriented. (authors)

Modelling of Safety Factors in the Design of GRP Composite Products

DEFF Research Database (Denmark)

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

2010-01-01

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

Factors influencing creep model equation selection

International Nuclear Information System (INIS)

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

2008-01-01

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

Human factors engineering program review model

International Nuclear Information System (INIS)

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

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

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Vít Maca

2017-06-01

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

INNOVATIVE PRACTICES IN TOURISM. APOSSIBLE MODEL BY FOSTERING SHADOW FACTORS

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Ada Mirela TOMESCU

2015-08-01

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

Influencing Factors and Consequences of Workplace Bullying among Nurses: A Structural Equation Modeling

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Seonyoung Yun, PhD, RN

2018-03-01

Full Text Available Purpose: The purpose of this study was to build and test a model outlining the factors related to workplace bullying among nurses. The hypothesized model included authentic leadership and a relationship-oriented organizational culture as influencing factors, symptom experience and turnover intention as consequences, and positive psychological capital as a mediator of workplace bullying among nurses. Methods: We obtained structured questionnaire data from 301 nurses working at hospitals in South Korea. Based on these data, the developed model was verified via a structural equation modeling analysis using SPSS and AMOS program. Results: The fit indices of the hypothesized model satisfied recommended levels; χ2 = 397.58 (p < .001, normed χ2 (χ2/df = 1.82, RMR = .05, TLI = .93, CFI = .94, RMSEA = .05. A relationship-oriented organizational culture had a direct effect on workplace bullying (β = −.48, p < .001. Furthermore, workplace bullying had a direct effect on symptom experience (β = .36, p < .001, and this relationship was mediated by positive psychological capital (β = .15, p = .003. Workplace bullying also had an indirect effect on turnover intention (β = .20, p = .007. Finally, symptom experience had a direct effect on turnover intention (β = .31, p = .002. Conclusion: These results suggest that workplace bullying among nurses may be prevented by constructing a relationship-oriented organizational culture, as long as employees have sufficient positive psychological capital. In this regard, workplace bullying among nurses should be addressed using a comprehensive strategy that considers both individual and organizational factors. Keywords: bullying, leadership, nurses, organizational culture, personnel turnover

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

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Chandra Shekhar Bhatnagar

2013-07-01

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

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

Science.gov (United States)

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

2018-04-01

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

Incremental validity of positive orientation: predictive efficiency beyond the five-factor model

Directory of Open Access Journals (Sweden)

Łukasz Roland Miciuk

2016-05-01

Full Text Available Background The relation of positive orientation (a basic predisposition to think positively of oneself, one’s life and one’s future and personality traits is still disputable. The purpose of the described research was to verify the hypothesis that positive orientation has predictive efficiency beyond the five-factor model. Participants and procedure One hundred and thirty participants (at the mean age M = 24.84 completed the following questionnaires: the Self-Esteem Scale (SES, the Satisfaction with Life Scale (SWLS, the Life Orientation Test-Revised (LOT-R, the Positivity Scale (P-SCALE, the NEO Five Factor Inventory (NEO-FFI, the Self-Concept Clarity Scale (SCC, the Generalized Self-Efficacy Scale (GSES and the Life Engagement Test (LET. Results The introduction of positive orientation as an additional predictor in the second step of regression analyses led to better prediction of the following variables: purpose in life, self-concept clarity and generalized self-efficacy. This effect was the strongest for predicting purpose in life (i.e. 14% increment of the explained variance. Conclusions The results confirmed our hypothesis that positive orientation can be characterized by incremental validity – its inclusion in the regression model (in addition to the five main factors of personality increases the amount of explained variance. These findings may provide further evidence for the legitimacy of measuring positive orientation and personality traits separately.

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

Science.gov (United States)

Patricia L. Andrews

2012-01-01

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

Analytical results for the Sznajd model of opinion formation

Czech Academy of Sciences Publication Activity Database

Slanina, František; Lavička, H.

2003-01-01

Roč. 35, - (2003), s. 279-288 ISSN 1434-6028 R&D Projects: GA ČR GA202/01/1091 Institutional research plan: CEZ:AV0Z1010914 Keywords : agent models * sociophysics Subject RIV: BE - Theoretical Physics Impact factor: 1.457, year: 2003

Critical success factors model developing for sustainable Kaizen implementation in manufactur-ing industry in Ethiopia

Directory of Open Access Journals (Sweden)

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.

Decision making model design for antivirus software selection using Factor Analysis and Analytical Hierarchy Process

Directory of Open Access Journals (Sweden)

Nurhayati Ai

2018-01-01

Full Text Available Virus spread increase significantly through the internet in 2017. One of the protection method is using antivirus software. The wide variety of antivirus software in the market tends to creating confusion among consumer. Selecting the right antivirus according to their needs has become difficult. This is the reason we conduct our research. We formulate a decision making model for antivirus software consumer. The model is constructed by using factor analysis and AHP method. First we spread questionnaires to consumer, then from those questionnaires we identified 16 variables that needs to be considered on selecting antivirus software. This 16 variables then divided into 5 factors by using factor analysis method in SPSS software. These five factors are security, performance, internal, time and capacity. To rank those factors we spread questionnaires to 6 IT expert then the data is analyzed using AHP method. The result is that performance factors gained the highest rank from all of the other factors. Thus, consumer can select antivirus software by judging the variables in the performance factors. Those variables are software loading speed, user friendly, no excessive memory use, thorough scanning, and scanning virus fast and accurately.

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

Science.gov (United States)

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

2013-02-01

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

[Factors Influencing Participation in Financial Incentive Programmes of Health Insurance Funds. Results of the Study 'German Health Update'].

Science.gov (United States)

Jordan, S; von der Lippe, E; Starker, A; Hoebel, J; Franke, A

2015-11-01

The statutory health insurance can offer their insured incentive programmes that will motivate for healthy behaviour through a financial or material reward. This study will show results about what factors influence financial incentive programme participation (BPT) including all sorts of statutory health insurance funds and taking into account gender differences. For the cross-sectional analysis, data were used from 15,858 participants in the study 'Germany Health Update' (GEDA) from 2009, who were insured in the statutory health insurance. The selection of potential influencing variables for a BPT is based on the "Behavioural Model for Health Service Use" of Andersen. Accordingly, various factors were included in logistic regression models, which were calculated separately by gender: predisposing factors (age, education, social support, and health awareness), enabling factors (income, statutory health insurance fund, and family physician), and need factors (smoking, fruit and vegetable consumption, sports, body mass index, and general health status). In consideration of all factors, for both sexes, BPT is associated with age, health awareness, education, use of a family physician, smoking, and sports activities. In addition, income, body mass index, and diet are significant in women and social support and kind of statutory health insurance fund in men. It is found that predisposing, enabling and need factors are relevant. Financial incentive programmes reach population groups with greatest need less than those groups who already have a health-conscious behaviour, who receive a reward for this. In longitudinal studies, further research on financial incentive programmes should investigate the existence of deadweight effects and whether incentive programmes can contribute to the reduction of the inequity in health. © Georg Thieme Verlag KG Stuttgart · New York.

Factors Affecting the Result of Matches in the One Day Format of Cricket

Directory of Open Access Journals (Sweden)

Ananda Bandulasiri

2016-01-01

Full Text Available Factors contributing to winning games are imperative, as the ultimate objective in a game is victory. The aim of this study was to identify the factors that characterize the game of cricket, and to investigate the factors that truly influence the result of a game using the data collected from the Champions Trophy cricket tournament. According to the results, this cricket tournament can be characterized using the factors of batting, bowling, and decision-making. Further investigation suggests that the rank of the team and the number of runs they score have the most significant influence on the result of games. As far as the effectiveness of assigning bowlers is concerned, the Australian team has done a fabulous job compared to the rest of the teams. (original abstract

Person-fit to the Five Factor Model of personality

Czech Academy of Sciences Publication Activity Database

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

2012-01-01

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

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

International Nuclear Information System (INIS)

Vehvilaeinen, Iivo; Pyykkoenen, Tuomas

2005-01-01

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

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

International Nuclear Information System (INIS)

Vehvilainen, I.; Pyykkoenen, T.

2005-01-01

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

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

Science.gov (United States)

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

2018-04-01

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

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

Directory of Open Access Journals (Sweden)

Oscar Armando Esparza-Del Villar

2017-03-01

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

Factors associated with secondhand smoke exposure in different settings: Results from the German Health Update (GEDA) 2012.

Science.gov (United States)

Fischer, Florian; Kraemer, Alexander

2016-04-14

The ubiquity of secondhand smoke (SHS) exposure at home or in private establishments, workplaces and public areas poses several challenges for the reduction of SHS exposure. This study aimed to describe the prevalence of SHS exposure in Germany and key factors associated with exposure. Results were also differentiated by place of exposure. A secondary data analysis based on the public use file of the German Health Update 2012 was conducted (n = 13,933). Only non-smokers were included in the analysis. In a multivariable logistic regression model the factors associated with SHS exposure were calculated. In addition, a further set of multivariable logistic regressions were calculated for factors associated with the place of SHS exposure (workplace, at home, bars/discotheques, restaurants, at the house of a friend). More than a quarter of non-smoking study participants were exposed to SHS. The main area of exposure was the workplace (40.9 %). The multivariable logistic regression indicated young age as the most important factor associated with SHS exposure. The odds for SHS exposure was higher in men than in women. The likelihood of SHS exposure decreased with higher education. SHS exposure and the associated factors varied between different places of exposure. Despite several actions to protect non-smokers which were implemented in Germany during the past years, SHS exposure still remains a relevant risk factor at a population level. According to the results of this study, particularly the workplace and other public places such as bars and discotheques have to be taken into account for the development of strategies to reduce SHS exposure.

Selection of terrestrial transfer factors for radioecological assessment models and regulatory guides

International Nuclear Information System (INIS)

Ng, Y.C.; Hoffman, F.O.

1983-01-01

A parameter value for a radioecological assessment model is not a single value but a distribution of values about a central value. The sources that contribute to the variability of transfer factors to predict foodchain transport of radionuclides are enumerated. Knowledge of these sources, judgement in interpreting the available data, consideration of collateral information, and established criteria that specify the desired level of conservatism in the resulting predictions are essential elements when selecting appropriate parameter values for radioecological assessment models and regulatory guides. 39 references, 4 figures, 5 tables

Selection of terrestrial transfer factors for radioecological assessment models and regulatory guides

Energy Technology Data Exchange (ETDEWEB)

Ng, Y.C.; Hoffman, F.O.

1983-01-01

A parameter value for a radioecological assessment model is not a single value but a distribution of values about a central value. The sources that contribute to the variability of transfer factors to predict foodchain transport of radionuclides are enumerated. Knowledge of these sources, judgement in interpreting the available data, consideration of collateral information, and established criteria that specify the desired level of conservatism in the resulting predictions are essential elements when selecting appropriate parameter values for radioecological assessment models and regulatory guides. 39 references, 4 figures, 5 tables.

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

KAUST Repository

Kulakovskiy, Ivan V.

2015-11-19

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

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

Science.gov (United States)

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

2013-01-01

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

Size, Value and Business Cycle Variables. The Three-Factor Model and Future Economic Growth: Evidence from an Emerging Market

Directory of Open Access Journals (Sweden)

Fahad Ali

2018-02-01

Full Text Available The paper empirically investigates three different methods to construct factors and identifies some pitfalls that arise in the application of Fama-French’s three-factor model to the Pakistani stock returns. We find that the special features in Pakistan significantly affect size and value factors and also influence the explanatory power of the three-factor model. Additionally, the paper examines the ability of the three factors to predict the future growth of Pakistan’s economy. Using monthly data of both financial and non-financial companies between 2002 and 2016, the article empirically investigates and finds that: (1 size and book-to-market factors exist in the Pakistani stock market, two mimic portfolios SMB and HML generate a return of 9.15% and 12.27% per annum, respectively; (2 adding SMB and HML factors into the model meaningfully increases the explanatory power of the model; and (3 the model’s factors, except for value factor, predict future gross domestic product (GDP growth of Pakistan and remain robust. Our results are robust across sub-periods, risk regimes, and under three different methods of constructing the factors.

Dynamic structure factor for liquid He4 and quantum lattice model

International Nuclear Information System (INIS)

Lee, M.H.

1975-01-01

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

Empiric model for mean generation time adjustment factor for classic point kinetics equations

Energy Technology Data Exchange (ETDEWEB)

Goes, David A.B.V. de; Martinez, Aquilino S.; Goncalves, Alessandro da C., E-mail: david.goes@poli.ufrj.br, E-mail: aquilino@lmp.ufrj.br, E-mail: alessandro@con.ufrj.br [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Departamento de Engenharia Nuclear

2017-11-01

Point reactor kinetics equations are the easiest way to observe the neutron production time behavior in a nuclear reactor. These equations are derived from the neutron transport equation using an approximation called Fick's law leading to a set of first order differential equations. The main objective of this study is to review classic point kinetics equation in order to approximate its results to the case when it is considered the time variation of the neutron currents. The computational modeling used for the calculations is based on the finite difference method. The results obtained with this model are compared with the reference model and then it is determined an empirical adjustment factor that modifies the point reactor kinetics equation to the real scenario. (author)

Empiric model for mean generation time adjustment factor for classic point kinetics equations

International Nuclear Information System (INIS)

Goes, David A.B.V. de; Martinez, Aquilino S.; Goncalves, Alessandro da C.

2017-01-01

Point reactor kinetics equations are the easiest way to observe the neutron production time behavior in a nuclear reactor. These equations are derived from the neutron transport equation using an approximation called Fick's law leading to a set of first order differential equations. The main objective of this study is to review classic point kinetics equation in order to approximate its results to the case when it is considered the time variation of the neutron currents. The computational modeling used for the calculations is based on the finite difference method. The results obtained with this model are compared with the reference model and then it is determined an empirical adjustment factor that modifies the point reactor kinetics equation to the real scenario. (author)

Modeling Shear Induced Von Willebrand Factor Binding to Collagen

Science.gov (United States)

Dong, Chuqiao; Wei, Wei; Morabito, Michael; Webb, Edmund; Oztekin, Alparslan; Zhang, Xiaohui; Cheng, Xuanhong

2017-11-01

Von Willebrand factor (vWF) is a blood glycoprotein that binds with platelets and collagen on injured vessel surfaces to form clots. VWF bioactivity is shear flow induced: at low shear, binding between VWF and other biological entities is suppressed; for high shear rate conditions - as are found near arterial injury sites - VWF elongates, activating its binding with platelets and collagen. Based on parameters derived from single molecule force spectroscopy experiments, we developed a coarse-grain molecular model to simulate bond formation probability as a function of shear rate. By introducing a binding criterion that depends on the conformation of a sub-monomer molecular feature of our model, the model predicts shear-induced binding, even for conditions where binding is highly energetically favorable. We further investigate the influence of various model parameters on the ability to predict shear-induced binding (vWF length, collagen site density and distribution, binding energy landscape, and slip/catch bond length) and demonstrate parameter ranges where the model provides good agreement with existing experimental data. Our results may be important for understanding vWF activity and also for achieving targeted drug therapy via biomimetic synthetic molecules. National Science Foundation (NSF),Division of Mathematical Sciences (DMS).

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

Science.gov (United States)

Greenspan, Stephen

2006-01-01

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

Human Modeling for Ground Processing Human Factors Engineering Analysis

Science.gov (United States)

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

2011-01-01

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

Motivation and personality: relationships between putative motive dimensions and the five factor model of personality.

Science.gov (United States)

Bernard, Larry C

2010-04-01

There are few multidimensional measures of individual differences in motivation available. The Assessment of Individual Motives-Questionnaire assesses 15 putative dimensions of motivation. The dimensions are based on evolutionary theory and preliminary evidence suggests the motive scales have good psychometric properties. The scales are reliable and there is evidence of their consensual validity (convergence of self-other ratings) and behavioral validity (relationships with self-other reported behaviors of social importance). Additional validity research is necessary, however, especially with respect to current models of personality. The present study tested two general and 24 specific hypotheses based on proposed evolutionary advantages/disadvantages and fitness benefits/costs of the five-factor model of personality together with the new motive scales in a sample of 424 participants (M age=28.8 yr., SD=14.6). Results were largely supportive of the hypotheses. These results support the validity of new motive dimensions and increase understanding of the five-factor model of personality.

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

Directory of Open Access Journals (Sweden)

Sayali Shrikrishna Sandbhor

2014-03-01

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

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

OpenAIRE

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

2018-01-01

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

A physiological production model for cacao : results of model simulations

NARCIS (Netherlands)

Zuidema, P.A.; Leffelaar, P.A.

2002-01-01

CASE2 is a physiological model for cocoa (Theobroma cacao L.) growth and yield. This report introduces the CAcao Simulation Engine for water-limited production in a non-technical way and presents simulation results obtained with the model.

Capturing the DSM-5 Alternative Personality Disorder Model Traits in the Five-Factor Model's Nomological Net.

Science.gov (United States)

Suzuki, Takakuni; Griffin, Sarah A; Samuel, Douglas B

2017-04-01

Several studies have shown structural and statistical similarities between the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) alternative personality disorder model and the Five-Factor Model (FFM). However, no study to date has evaluated the nomological network similarities between the two models. The relations of the Revised NEO Personality Inventory (NEO PI-R) and the Personality Inventory for DSM-5 (PID-5) with relevant criterion variables were examined in a sample of 336 undergraduate students (M age  = 19.4; 59.8% female). The resulting profiles for each instrument were statistically compared for similarity. Four of the five domains of the two models have highly similar nomological networks, with the exception being FFM Openness to Experience and PID-5 Psychoticism. Further probing of that pair suggested that the NEO PI-R domain scores obscured meaningful similarity between PID-5 Psychoticism and specific aspects and lower-order facets of Openness. The results support the notion that the DSM-5 alternative personality disorder model trait domains represent variants of the FFM domains. Similarities of Openness and Psychoticism domains were supported when the lower-order aspects and facets of Openness domain were considered. The findings support the view that the DSM-5 trait model represents an instantiation of the FFM. © 2015 Wiley Periodicals, Inc.

An analytical model for backscattered luminance in fog: comparisons with Monte Carlo computations and experimental results

International Nuclear Information System (INIS)

Taillade, Frédéric; Dumont, Eric; Belin, Etienne

2008-01-01

We propose an analytical model for backscattered luminance in fog and derive an expression for the visibility signal-to-noise ratio as a function of meteorological visibility distance. The model uses single scattering processes. It is based on the Mie theory and the geometry of the optical device (emitter and receiver). In particular, we present an overlap function and take the phase function of fog into account. The results of the backscattered luminance obtained with our analytical model are compared to simulations made using the Monte Carlo method based on multiple scattering processes. An excellent agreement is found in that the discrepancy between the results is smaller than the Monte Carlo standard uncertainties. If we take no account of the geometry of the optical device, the results of the model-estimated backscattered luminance differ from the simulations by a factor 20. We also conclude that the signal-to-noise ratio computed with the Monte Carlo method and our analytical model is in good agreement with experimental results since the mean difference between the calculations and experimental measurements is smaller than the experimental uncertainty

The effect of choosing three different C factor formulae derived from NDVI on a fully raster-based erosion modelling

Science.gov (United States)

Sulistyo, Bambang

2016-11-01

The research was aimed at studying the efect of choosing three different C factor formulae derived from NDVI on a fully raster-based erosion modelling of The USLE using remote sensing data and GIS technique. Methods applied was by analysing all factors affecting erosion such that all data were in the form of raster. Those data were R, K, LS, C and P factors. Monthly R factor was evaluated based on formula developed by Abdurachman. K factor was determined using modified formula used by Ministry of Forestry based on soil samples taken in the field. LS factor was derived from Digital Elevation Model. Three C factors used were all derived from NDVI and developed by Suriyaprasit (non-linear) and by Sulistyo (linear and non-linear). P factor was derived from the combination between slope data and landcover classification interpreted from Landsat 7 ETM+. Another analysis was the creation of map of Bulk Density used to convert erosion unit. To know the model accuracy, model validation was done by applying statistical analysis and by comparing Emodel with Eactual. A threshold value of ≥ 0.80 or ≥ 80% was chosen to justify. The research result showed that all Emodel using three formulae of C factors have coeeficient of correlation value of > 0.8. The results of analysis of variance showed that there was significantly difference between Emodel and Eactual when using C factor formula developed by Suriyaprasit and Sulistyo (non-linear). Among the three formulae, only Emodel using C factor formula developed by Sulistyo (linear) reached the accuracy of 81.13% while the other only 56.02% as developed by Sulistyo (nonlinear) and 4.70% as developed by Suriyaprasit, respectively.

Prevalence of Abnormal Papanicolaou Test Results and Related Factors among Women Living in Zanjan, Iran.

Science.gov (United States)

Maleki, Azam; Ahmadnia, Elahe; Avazeh, Azar; Mazloomzadeh, Saeideh; Molaei, Behnaz; Jalilvand, Ahmad

2015-01-01

Currently, a comprehensive program for screening and early detection of cervical cancer does not exist in Iran. This study aimed to determine the prevalence of abnormal Papanicolaou (Pap) smears and some related factors among women living in Zanjan, Iran. This cross-sectional study was conducted in 2012 in Zanjan on 4274 married women aged 20-65 years. The study participants were selected through two-stage cluster sampling. After obtaining written consent, demographic and fertility questionnaires were completed. Samples from cervix were obtained through a standard method using the Rover Cervex- Brush. Evaluation and interpretation of the samples were reported using the Bethesda 2001 method. Data were statistically analyzed using chi-square and logistic regression models. Most inflammatory changes in the samples were mild (37.4%). Abnormal atypical changes in the epithelial cells were found in 4.04%. The highest percentage of abnormal changes in the epithelial cells was atypical squamous cells of undetermined significance (ASCUS) (1.9%). Abnormal results of Pap smear was significantly and independently associated with age, papillomavirus infection, and lack of awareness about Pap smear tests. Given the high prevalence of inflammatory and precancerous changes in this study, compared to other studies in Iran and other Muslim countries, and the effect of demographic variables and individual factors on abnormal results, increasing the awareness of women and their families regarding the risk factors for cervical cancer, preventive measures such as screening, and timely treatment seem necessary.

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

Directory of Open Access Journals (Sweden)

Stevenson Christopher E

2012-01-01

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

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

Science.gov (United States)

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

2012-01-01

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

Development and Initial Validation of the Five-Factor Model Adolescent Personality Questionnaire (FFM-APQ).

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Rogers, Mary E; Glendon, A Ian

2018-01-01

This research reports on the 4-phase development of the 25-item Five-Factor Model Adolescent Personality Questionnaire (FFM-APQ). The purpose was to develop and determine initial evidence for validity of a brief adolescent personality inventory using a vocabulary that could be understood by adolescents up to 18 years old. Phase 1 (N = 48) consisted of item generation and expert (N = 5) review of items; Phase 2 (N = 179) involved item analyses; in Phase 3 (N = 496) exploratory factor analysis assessed the underlying structure; in Phase 4 (N = 405) confirmatory factor analyses resulted in a 25-item inventory with 5 subscales.

Modeling soft factors in computer-based wargames

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

2002-07-01

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

Medulloblastoma in adults: treatment results and prognostic factors

International Nuclear Information System (INIS)

Abacioglu, Ufuk; Uzel, Omer; Sengoz, Meric; Turkan, Sedat; Ober, Ahmet

2002-01-01

Purpose: To investigate the treatment outcome and prognostic factors of adult medulloblastoma patients who received postoperative craniospinal irradiation (RT). Methods and Materials: Between 1983 and 2000, 30 adult patients (17 men and 13 women, age ≥16 years, median 27, range 16-45) underwent postoperative RT. The median duration of symptoms was 2 months (range 1-9). The tumor location was lateral in 16 (53%). A desmoplastic variant was seen in 12 (40%). Tumor resection was complete in 20 (67%) and incomplete in 10 (33%). All patients received craniospinal RT. The median dose to the whole brain was 40 Gy (range 36-51), to the posterior fossa 54 Gy (range 49-56), and to the spinal axis 36 Gy (range 24-40). The median interval between surgery and the start of RT was 31 days (range 12-69), and the median duration of RT was 45 days (range 34-89). Ten patients (33%) received adjuvant chemotherapy. The median follow-up was 51 months (range 5-215). Results: The 5- and 8-year overall survival and disease-free survival rates were 65% and 51% and 63% and 50%, respectively. Twelve patients (40%) developed relapse, with a median follow-up of 51 months. The posterior fossa was the most common site of relapse (6 patients). The median time to relapse was 26 months (range 4-78). Fifty percent of the relapses occurred after 2 years, 17% after 5 years. In univariate analysis, M stage and the interval between surgery and the start of RT were significant prognostic factors for disease-free survival. At 5 years, 70% of M0 patients were estimated to be disease-free, but none of the 3 M3 patients reached 5 years without recurrence (p=0.0002). The 5-year disease-free survival rate for the patients whose interval between surgery and the start of RT was 6 weeks was 0%, 85%, and 75%, respectively (p=0.002). The 5-year posterior fossa control rate for patients who received ≥54 Gy or <54 Gy to the posterior fossa was 91% and 33%, respectively (p=0.05). Conclusion: The survival results

Rotordynamic analysis for stepped-labyrinth gas seals using moody's friction-factor model

International Nuclear Information System (INIS)

Ha, Tae Woong

2001-01-01

The governing equations are derived for the analysis of a stepped labyrinth gas seal generally used in high performance compressors, gas turbines, and steam turbines. The bulk-flow is assumed for a single cavity control volume set up in a stepped labyrinth cavity and the flow is assumed to be completely turbulent in the circumferential direction. The Moody's wall-friction-factor model is used for the calculation of wall shear stresses in the single cavity control volume. For the reaction force developed by the stepped labyrinth gas seal, linearized zeroth-order and first-order perturbation equations are developed for small motion about a centered position. Integration of the resultant first-order pressure distribution along and around the seal defines the rotordynamic coefficients of the stepped labyrinth gas seal. The resulting leakage and rotordynamic characteristics of the stepped labyrinth gas seal are presented and compared with Scharrer's theoretical analysis using Blasius' wall-friction-factor model. The present analysis shows a good qualitative agreement of leakage characteristics with Scharrer's analysis, but underpredicts by about 20 %. For the rotordynamic coefficients, the present analysis generally yields smaller predicted values compared with Scharrer's analysis

Associations between five-factor model of the Positive and Negative Syndrome Scale and plasma levels of monoamine metabolite in patients with schizophrenia.

Science.gov (United States)

Watanabe, Kenya; Miura, Itaru; Kanno-Nozaki, Keiko; Horikoshi, Sho; Mashiko, Hirobumi; Niwa, Shin-Ichi; Yabe, Hirooki

2015-12-15

The five-factor model of the Positive and Negative Syndrome Scale (PANSS) for schizophrenia symptoms is the most common multiple-factor model used in analyses; its use may improve evaluation of symptoms in schizophrenia patients. Plasma monoamine metabolite levels are possible indicators of clinical symptoms or response to antipsychotics in schizophrenia. We investigated the association between five-factor model components and plasma monoamine metabolites levels to explore the model's biological basis. Plasma levels of homovanillic acid (HVA), 3-methoxy-4-hydroxyphenylglycol (MHPG), and 5-hydroxyindoleacetic acid (5-HIAA) were measured using high-performance liquid chromatography in 65 Japanese patients with schizophrenia. Significant negative correlation between plasma 5-HIAA levels and the depression/anxiety component was found. Furthermore, significant positive correlation was found between plasma MHPG levels and the excitement component. Plasma HVA levels were not correlated with any five-factor model component. These results suggest that the five-factor model of the PANSS may have a biological basis, and may be useful for elucidating the psychopathology of schizophrenia. Assessment using the five-factor model may enable understanding of monoaminergic dysfunction, possibly allowing more appropriate medication selection. Further studies of a larger number of first-episode schizophrenia patients are needed to confirm and extend these results. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Clinical application of the five-factor model.

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Widiger, Thomas A; Presnall, Jennifer Ruth

2013-12-01

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

Linear and nonlinear models for predicting fish bioconcentration factors for pesticides.

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Yuan, Jintao; Xie, Chun; Zhang, Ting; Sun, Jinfang; Yuan, Xuejie; Yu, Shuling; Zhang, Yingbiao; Cao, Yunyuan; Yu, Xingchen; Yang, Xuan; Yao, Wu

2016-08-01

This work is devoted to the applications of the multiple linear regression (MLR), multilayer perceptron neural network (MLP NN) and projection pursuit regression (PPR) to quantitative structure-property relationship analysis of bioconcentration factors (BCFs) of pesticides tested on Bluegill (Lepomis macrochirus). Molecular descriptors of a total of 107 pesticides were calculated with the DRAGON Software and selected by inverse enhanced replacement method. Based on the selected DRAGON descriptors, a linear model was built by MLR, nonlinear models were developed using MLP NN and PPR. The robustness of the obtained models was assessed by cross-validation and external validation using test set. Outliers were also examined and deleted to improve predictive power. Comparative results revealed that PPR achieved the most accurate predictions. This study offers useful models and information for BCF prediction, risk assessment, and pesticide formulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analisis Hubungan antara Berbagai Model Gabungan Proksi Investment Opportunity Set dan Real Growth dengan Menggunakan Pendekatan Confirmatory Factor Analysis”

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Muhammad Yusuf

2016-02-01

Full Text Available This study develops and makes composite observed variables from individual Investment Opportunity Set (IOS proxies into one latent variable using structural equation models with a confirmatory factor analysis approach. Six composite investment opportunity set proxies are then created based on some individual proxies, namely price related IOS and investment related IOS. These composite IOS proxies are correlated with the real growth to prove that the model has consistency and ability to predict the real growth. A confirmatory factor analysis results in all observed variables that make latent variables for each model show different result in every model. At model 1, the CFA result show   that every price related IOS proxies at model 1 have significant measurement model fit. At model 2, the Confirmatory Factor Analysis (CFA result show that every price related IOS proxies at model 2 have significant measurement model fit, except for one proxies named Rasio Capital Expenditure to Total Book Asset (RACTE. At model 3, the CFA result show that every price related IOS proxies at model 2 have significant measurement model fit, except for one proxies named Book Value of Property, Plant and Equipment to Book Value of Asset(BVPPEBVA. At model 4, the CFA result show   that every price related IOS proxies at model 1 have significant measurement model fit. At model 5, the CFA result show   that every price related IOS proxies at model 1 have significant measurement model fit. At model 6, the CFA result show that there is no significant measurement model fit for every investment related IOS proxies. Correlation test for all models show almost different result in every models. At model 1, the correlation test show that there is a weak, not significant-positive correlation between price related IOS proxies as latent variable, and real growth proxies. At model 2, the correlation test shows that there is a weak, significant negative correlation between price

Model calculating annual mean atmospheric dispersion factor for coastal site of nuclear power plant

Institute of Scientific and Technical Information of China (English)

无

2001-01-01

This paper describes an atmospheric dispersion field experiment performed on the coastal site of nuclear power plant in the east part of China during 1995 to 1996. The three-dimension joint frequency are obtained by hourly observation of wind and temperature on a 100m high tower; the frequency of the “event day of land and sea breezes” are given by observation of surface wind and land and sea breezes; the diffusion parameters are got from measurements of turbulent and wind tunnel simulation test.A new model calculating the annual mean atmospheric dispersion factor for coastal site of nuclear power plant is developed and established.This model considers not only the effect from mixing release and mixed layer but also the effect from the internal boundary layer and variation of diffusion parameters due to the distance from coast.The comparison between results obtained by the new model and current model shows that the ratio of annual mean atmospheric dispersion factor gained by the new model and the current one is about 2.0.

System Dynamics Modeling of interactive cost factors for small modular reactors

International Nuclear Information System (INIS)

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

2011-01-01

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

HOCOMOCO: a comprehensive collection of human transcription factor binding sites models

Science.gov (United States)

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

HOCOMOCO: A comprehensive collection of human transcription factor binding sites models

KAUST Repository

Kulakovskiy, Ivan V.; Medvedeva, Yulia A.; Schaefer, Ulf; Kasianov, Artem S.; Vorontsov, Ilya E.; Bajic, Vladimir B.; Makeev, Vsevolod J.

2012-01-01

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. The Author(s) 2012.

HOCOMOCO: A comprehensive collection of human transcription factor binding sites models

KAUST Repository

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.

A dual-factor model of mental health: toward a more comprehensive understanding of youth functioning.

Science.gov (United States)

Antaramian, Susan P; Scott Huebner, E; Hills, Kimberly J; Valois, Robert F

2010-10-01

Traditional mental health models focus on psychological problems and distress; accordingly, health is viewed as the absence of illness or disability. In contrast, a dual-factor model of mental health incorporates both indicators of positive subjective well-being (SWB) and measures of psychopathological symptoms to comprehensively determine an individual's psychological adjustment. This study used such a dual-factor model to measure the mental health status of young adolescents. A total of 764 middle school students were classified into one of four distinct groups based on having high or low psychopathology and high or low SWB. Furthermore, group differences in student engagement, academic achievement, and environmental support for learning were investigated. Results demonstrated the existence of a traditionally neglected group of adolescents (low SWB and low psychopathology) who are nonetheless at risk for academic and behavior problems in school and who performed no better than the most troubled group of adolescents. Overall, both the presence of positive well-being and the absence of symptoms were necessary for ensuring the most advantageous school performance. These results highlight the importance of incorporating positive indicators of well-being along with traditional negative factors in more fully understanding relationships between individuals' mental health and educational outcomes. © 2010 American Orthopsychiatric Association.

Generalised Chou-Yang model and recent results

International Nuclear Information System (INIS)

Fazal-e-Aleem; Rashid, H.

1996-01-01

It is shown that most recent results of E710 and UA4/2 collaboration for the total cross section and ρ together with earlier measurements give good agreement with measurements for the differential cross section at 546 and 1800 GeV within the framework of Generalised Chou-Yang model. These results are also compared with the predictions of other models. (author)

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

International Nuclear Information System (INIS)

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

1989-10-01

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

Modeling of human factor Va inactivation by activated protein C

Directory of Open Access Journals (Sweden)

Bravo Maria

2012-05-01

Full Text Available Abstract Background Because understanding of the inventory, connectivity and dynamics of the components characterizing the process of coagulation is relatively mature, it has become an attractive target for physiochemical modeling. Such models can potentially improve the design of therapeutics. The prothrombinase complex (composed of the protease factor (FXa and its cofactor FVa plays a central role in this network as the main producer of thrombin, which catalyses both the activation of platelets and the conversion of fibrinogen to fibrin, the main substances of a clot. A key negative feedback loop that prevents clot propagation beyond the site of injury is the thrombin-dependent generation of activated protein C (APC, an enzyme that inactivates FVa, thus neutralizing the prothrombinase complex. APC inactivation of FVa is complex, involving the production of partially active intermediates and “protection” of FVa from APC by both FXa and prothrombin. An empirically validated mathematical model of this process would be useful in advancing the predictive capacity of comprehensive models of coagulation. Results A model of human APC inactivation of prothrombinase was constructed in a stepwise fashion by analyzing time courses of FVa inactivation in empirical reaction systems with increasing number of interacting components and generating corresponding model constructs of each reaction system. Reaction mechanisms, rate constants and equilibrium constants informing these model constructs were initially derived from various research groups reporting on APC inactivation of FVa in isolation, or in the presence of FXa or prothrombin. Model predictions were assessed against empirical data measuring the appearance and disappearance of multiple FVa degradation intermediates as well as prothrombinase activity changes, with plasma proteins derived from multiple preparations. Our work integrates previously published findings and through the cooperative

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

Directory of Open Access Journals (Sweden)

B. Moeini

2011-10-01

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

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

Science.gov (United States)

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

2013-06-01

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

Uncovering the influence of social skills and psychosociological factors on pain sensitivity using structural equation modeling.

Science.gov (United States)

Tanaka, Yoichi; Nishi, Yuki; Nishi, Yuki; Osumi, Michihiro; Morioka, Shu

2017-01-01

Pain is a subjective emotional experience that is influenced by psychosociological factors such as social skills, which are defined as problem-solving abilities in social interactions. This study aimed to reveal the relationships among pain, social skills, and other psychosociological factors by using structural equation modeling. A total of 101 healthy volunteers (41 men and 60 women; mean age: 36.6±12.7 years) participated in this study. To evoke participants' sense of inner pain, we showed them images of painful scenes on a PC screen and asked them to evaluate the pain intensity by using the visual analog scale (VAS). We examined the correlation between social skills and VAS, constructed a hypothetical model based on results from previous studies and the current correlational analysis results, and verified the model's fit using structural equation modeling. We found significant positive correlations between VAS and total social skills values, as well as between VAS and the "start of relationships" subscales. Structural equation modeling revealed that the values for "start of relationships" had a direct effect on VAS values (path coefficient =0.32, p social support. The results indicated that extroverted people are more sensitive to inner pain and tend to get more social support and maintain a better psychological condition.

A multi-scale model of hepcidin promoter regulation reveals factors controlling systemic iron homeostasis.

Directory of Open Access Journals (Sweden)

Guillem Casanovas

2014-01-01

Full Text Available Systemic iron homeostasis involves a negative feedback circuit in which the expression level of the peptide hormone hepcidin depends on and controls the iron blood levels. Hepcidin expression is regulated by the BMP6/SMAD and IL6/STAT signaling cascades. Deregulation of either pathway causes iron-related diseases such as hemochromatosis or anemia of inflammation. We quantitatively analyzed how BMP6 and IL6 control hepcidin expression. Transcription factor (TF phosphorylation and reporter gene expression were measured under co-stimulation conditions, and the promoter was perturbed by mutagenesis. Using mathematical modeling, we systematically analyzed potential mechanisms of cooperative and competitive promoter regulation by the transcription factors, and experimentally validated the model predictions. Our results reveal that hepcidin cross-regulation primarily occurs by combinatorial transcription factor binding to the promoter, whereas signaling crosstalk is insignificant. We find that the presence of two BMP-responsive elements enhances the steepness of the promoter response towards the iron-sensing BMP signaling axis, which promotes iron homeostasis in vivo. IL6 co-stimulation reduces the promoter sensitivity towards the BMP signal, because the SMAD and STAT transcription factors compete for recruiting RNA polymerase to the transcription start site. This may explain why inflammatory signals disturb iron homeostasis in anemia of inflammation. Taken together, our results reveal why the iron homeostasis circuit is sensitive to perturbations implicated in disease.

Results of steel containment vessel model test

International Nuclear Information System (INIS)

Luk, V.K.; Ludwigsen, J.S.; Hessheimer, M.F.; Komine, Kuniaki; Matsumoto, Tomoyuki; Costello, J.F.

1998-05-01

A series of static overpressurization tests of scale models of nuclear containment structures is being conducted by Sandia National Laboratories for the Nuclear Power Engineering Corporation of Japan and the US Nuclear Regulatory Commission. Two tests are being conducted: (1) a test of a model of a steel containment vessel (SCV) and (2) a test of a model of a prestressed concrete containment vessel (PCCV). This paper summarizes the conduct of the high pressure pneumatic test of the SCV model and the results of that test. Results of this test are summarized and are compared with pretest predictions performed by the sponsoring organizations and others who participated in a blind pretest prediction effort. Questions raised by this comparison are identified and plans for posttest analysis are discussed

Free-free Gaunt factors: comparison of various models

International Nuclear Information System (INIS)

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

1986-01-01

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

Computation of External Quality Factors for RF Structures by Means of Model Order Reduction and a Perturbation Approach

CERN Document Server

Flisgen, Thomas; van Rienen, Ursula

2016-01-01

External quality factors are significant quantities to describe losses via waveguide ports in radio frequency resonators. The current contribution presents a novel approach to determine external quality factors by means of a two-step procedure: First, a state-space model for the lossless radio frequency structure is generated and its model order is reduced. Subsequently, a perturbation method is applied on the reduced model so that external losses are accounted for. The advantage of this approach results from the fact that the challenges in dealing with lossy systems are shifted to the reduced order model. This significantly saves computational costs. The present paper provides a short overview on existing methods to compute external quality factors. Then, the novel approach is introduced and validated in terms of accuracy and computational time by means of commercial software.

Noise and dose modeling for pediatric CT optimization: preliminary results

International Nuclear Information System (INIS)

Miller Clemente, Rafael A.; Perez Diaz, Marlen; Mora Reyes, Yudel; Rodriguez Garlobo, Maikel; Castillo Salazar, Rafael

2008-01-01

Full text: A Multiple Linear Regression Model was developed to predict noise and dose in computed tomography pediatric imaging for head and abdominal examinations. Relative values of Noise and Volumetric Computed Tomography Dose Index was used to estimate de model respectively. 54 images of physical phantoms were performed. Independent variables considered included: phantom diameter, tube current and kilovolts, x ray beam collimation, reconstruction diameter and equipment's post processing filters. Predicted values show good agreement with measurements, which were better in noise model (R 2 adjusted =0.953) than the dose model (R 2 adjusted =0.744). Tube current, object diameter, beam collimation and reconstruction filter were identified as the most influencing factors in models. (author)

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

Science.gov (United States)

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

2018-01-01

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

Generalised Chou-Yang model and recent results

International Nuclear Information System (INIS)

Fazal-e-Aleem; Rashid, H.

1995-09-01

It is shown that most recent results of E710 and UA4/2 collaboration for the total cross section and ρ together with earlier measurements give good agreement with measurements for the differential cross section at 546 and 1800 GeV the framework of Generalised Chou-Yang model. These results are also compared with the predictions of other models. (author). 16 refs, 2 figs

Generalised Chou-Yang model and recent results

Energy Technology Data Exchange (ETDEWEB)

Fazal-e-Aleem [International Centre for Theoretical Physics, Trieste (Italy); Rashid, H. [Punjab Univ., Lahore (Pakistan). Centre for High Energy Physics

1996-12-31

It is shown that most recent results of E710 and UA4/2 collaboration for the total cross section and {rho} together with earlier measurements give good agreement with measurements for the differential cross section at 546 and 1800 GeV within the framework of Generalised Chou-Yang model. These results are also compared with the predictions of other models. (author) 16 refs.

Optimization Scheduling Model for Wind-thermal Power System Considering the Dynamic penalty factor

Science.gov (United States)

PENG, Siyu; LUO, Jianchun; WANG, Yunyu; YANG, Jun; RAN, Hong; PENG, Xiaodong; HUANG, Ming; LIU, Wanyu

2018-03-01

In this paper, a new dynamic economic dispatch model for power system is presented.Objective function of the proposed model presents a major novelty in the dynamic economic dispatch including wind farm: introduced the “Dynamic penalty factor”, This factor could be computed by using fuzzy logic considering both the variable nature of active wind power and power demand, and it could change the wind curtailment cost according to the different state of the power system. Case studies were carried out on the IEEE30 system. Results show that the proposed optimization model could mitigate the wind curtailment and the total cost effectively, demonstrate the validity and effectiveness of the proposed model.

Identification and synthetic modeling of factors affecting American black duck populations

Science.gov (United States)

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

2002-01-01

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

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

Science.gov (United States)

Sezgin, F; Kinay, B

2010-01-01

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

Situational effects of the school factors included in the dynamic model of educational effectiveness

NARCIS (Netherlands)

Creerners, Bert; Kyriakides, Leonidas

We present results of a longitudinal study in which 50 schools, 113 classes and 2,542 Cypriot primary students participated. We tested the validity of the dynamic model of educational effectiveness and especially its assumption that the impact of school factors depends on the current situation of

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

DEFF Research Database (Denmark)

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

2018-01-01

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

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

Science.gov (United States)

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

2014-09-01

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

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

Science.gov (United States)

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

2014-05-23

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

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

Science.gov (United States)

Niedhammer, I; Siegrist, J

1998-11-01

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

DISTANCE AS KEY FACTOR IN MODELLING STUDENTS’ RECRUITMENT BY UNIVERSITIES

Directory of Open Access Journals (Sweden)

SIMONA MĂLĂESCU

2015-10-01

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

Performances of the snow accumulation melting model SAMM: results in the Northern Apennines test area

Science.gov (United States)

Lagomarsino, Daniela; Martelloni, Gianluca; Segoni, Samuele; Catani, Filippo; Fanti, Riccardo

2013-04-01

In this work we propose a snow accumulation-melting model (SAMM) to forecast the snowpack height and we compare the results with a simple temperature index model and an improved version of the latter.For this purpose we used rainfall, temperature and snowpack thickness 5-years data series from 7 weather stations in the Northern Apennines (Emilia Romagna Region, Italy). SAMM is based on two modules modelling the snow accumulation and the snowmelt processes. Each module is composed by two equations: a mass conservation equation is solved to model snowpack thickness and an empirical equation is used for the snow density. The processes linked to the accumulation/depletion of the snowpack (e.g. compression of the snowpack due to newly fallen snow and effects of rainfall) are modelled identifying limiting and inhibitory factors according to a kinetic approach. The model depends on 13 empirical parameters, whose optimal values were defined with an optimization algorithm (simplex flexible) using calibration measures of snowpack thickness. From an operational point of view, SAMM uses as input data only temperature and rainfall measurements, bringing the additional advantage of a relatively easy implementation. In order to verify the improvement of SAMM with respect to a temperature-index model, the latter was applied considering, for the amount of snow melt, the following equation: M = fm(T-T0), where M is hourly melt, fm is the melting factor and T0 is a threshold temperature. In this case the calculation of the depth of the snowpack requires the use of 3 parameters: fm, T0 and ?0 (the mean density of the snowpack). We also performed a simulation by replacing the SAMM melting module with the above equation and leaving unchanged the accumulation module: in this way we obtained a model with 9 parameters. The simulations results suggest that any further extension of the simple temperature index model brings some improvements with a consequent decrease of the mean error

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

Science.gov (United States)

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

Modeling the assessment of the economic factors impact on the development of social entrepreneurship

Science.gov (United States)

Absalyamov, T.; Kundakchyan, R.; Zulfakarova, L.; Zapparova, Z.

2017-12-01

The article deals with the research of modern trends in the development of social entrepreneurship in Russia. The results of the research allow the authors to identify a system of factors that affect the development of entrepreneurship in the modern Russian economy. Moreover, the authors argue the regional specificity of the development of social entrepreneurship. The paper considers specific features and formulates the main limitations of the development of entrepreneurship and the competitive environment in the social sphere. The authors suggest an econometric model for assessing the influence of economic factors on the development of socially-oriented entrepreneurship and present an algorithm for calculating its components. The results of the econometric analysis identify the main factors of the change in the performance indicators of entrepreneurial activity and determine the degree of their impact on social entrepreneurship. The results and conclusions can serve as an estimation of the socioeconomic consequences of the sustainability disruption of the entrepreneurial potential realization in the social sphere.

The Danish national passenger model – Model specification and results

DEFF Research Database (Denmark)

Rich, Jeppe; Hansen, Christian Overgaard

2016-01-01

The paper describes the structure of the new Danish National Passenger model and provides on this basis a general discussion of large-scale model design, cost-damping and model validation. The paper aims at providing three main contributions to the existing literature. Firstly, at the general level......, the paper provides a description of a large-scale forecast model with a discussion of the linkage between population synthesis, demand and assignment. Secondly, the paper gives specific attention to model specification and in particular choice of functional form and cost-damping. Specifically we suggest...... a family of logarithmic spline functions and illustrate how it is applied in the model. Thirdly and finally, we evaluate model sensitivity and performance by evaluating the distance distribution and elasticities. In the paper we present results where the spline-function is compared with more traditional...

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

Science.gov (United States)

Hida, Hirotake; Mouri, Akihiro; Noda, Yukihiro

2013-01-01

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

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

Science.gov (United States)

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

2012-01-01

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

Storm-time ring current: model-dependent results

Directory of Open Access Journals (Sweden)

N. Yu. Ganushkina

2012-01-01

Full Text Available The main point of the paper is to investigate how much the modeled ring current depends on the representations of magnetic and electric fields and boundary conditions used in simulations. Two storm events, one moderate (SymH minimum of −120 nT on 6–7 November 1997 and one intense (SymH minimum of −230 nT on 21–22 October 1999, are modeled. A rather simple ring current model is employed, namely, the Inner Magnetosphere Particle Transport and Acceleration model (IMPTAM, in order to make the results most evident. Four different magnetic field and two electric field representations and four boundary conditions are used. We find that different combinations of the magnetic and electric field configurations and boundary conditions result in very different modeled ring current, and, therefore, the physical conclusions based on simulation results can differ significantly. A time-dependent boundary outside of 6.6 RE gives a possibility to take into account the particles in the transition region (between dipole and stretched field lines forming partial ring current and near-Earth tail current in that region. Calculating the model SymH* by Biot-Savart's law instead of the widely used Dessler-Parker-Sckopke (DPS relation gives larger and more realistic values, since the currents are calculated in the regions with nondipolar magnetic field. Therefore, the boundary location and the method of SymH* calculation are of key importance for ring current data-model comparisons to be correctly interpreted.

Associations between the Five-Factor Model of Personality and Health Behaviors among College Students

Science.gov (United States)

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:…

Thymoma - prognostic factors and treatment results

International Nuclear Information System (INIS)

Gripp, S.; Hilgers, K.; Schmitt, G.

1997-01-01

Purpose/Objective: To assess the prognostic factors and treatment results of thymoma with emphasis on surgery and radiotherapy. Materials and Methods: Thymoma patients treated at Duesseldorf University Hospital from 1954 to 1991 were studied in this retrospective analysis. Depending on stage and residual disease, treatment was surgery (sternotomy or thoracotomy) with and without radiotherapy and chemotherapy (Holoxan, Endoxan, Vinblastin, Adriamycin, Bleomycin, CDDP, Vepesid). 70 patients (38f, 32m) were enrolled in this study. The mean age was 46,5 years. At presentation the median Karnofsky's index was 90%. In 19% thymoma was accidentally diagnosed, 81% presented symptoms at diagnosis. Masaoka's staging system was used (I: intact capsule; II: invasion of the capsule; III: invasion of neighboring organs; IV: dissemination). Stage at presentation was I:21%; II: 26%; III: 43%; IV: 10%. All histologic slices were peer reviewed. Histologic classification according to Lewis (predominantly lymphocytic: 36%; predominantly epithelial: 23%; mixed type: 33%, spindle cell thymoma: 9%) was applied. All available paraffin embedded specimens (36) were studied with DNA cytometric analysis after Feulgen staining. Occasionally thymoma was accompanied by Myasthenia gravis (23%) or other paraneoplastic syndromes (19%). Statistical analysis was performed using the Kaplan-Meier method and logrank-tests. Multivariate analysis was also performed. Results: From 70 patients treated surgically, 68% were radically resected (R0), 26% incompletely resected (R1,2) and 6% had biopsy only. The median cause specific survival (CSS) was 132 months. All patients with localized disease (stage I and II) were completely resected and received no further therapy, whereas only 50% (15 pat) in stage III and 0% in stage IV were amenable to radical resection. 36% (25 pat) received an additional therapy (CMT): 31% (22 pat) postoperative irradiation and 4% (3 pat) combined radio-chemotherapy. The radiation

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

NARCIS (Netherlands)

Steg, L; Geurs, K; Ras, M

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

Critical success factors model developing for sustainable Kaizen implementation in manufactur-ing industry in Ethiopia

OpenAIRE

Haftu Hailu; Abdelkadir Kedir; Getachew Bassa; Kassu Jilcha

2017-01-01

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 th...

Preferences for learning different types of genome sequencing results among young breast cancer patients: Role of psychological and clinical factors.

Science.gov (United States)

Kaphingst, Kimberly A; Ivanovich, Jennifer; Lyons, Sarah; Biesecker, Barbara; Dresser, Rebecca; Elrick, Ashley; Matsen, Cindy; Goodman, Melody

2018-01-29

The growing importance of genome sequencing means that patients will increasingly face decisions regarding what results they would like to learn. The present study examined psychological and clinical factors that might affect these preferences. 1,080 women diagnosed with breast cancer at age 40 or younger completed an online survey. We assessed their interest in learning various types of genome sequencing results: risk of preventable disease or unpreventable disease, cancer treatment response, uncertain meaning, risk to relatives' health, and ancestry/physical traits. Multivariable logistic regression was used to examine whether being "very" interested in each result type was associated with clinical factors: BRCA1/2 mutation status, prior genetic testing, family history of breast cancer, and psychological factors: cancer recurrence worry, genetic risk worry, future orientation, health information orientation, and genome sequencing knowledge. The proportion of respondents who were very interested in learning each type of result ranged from 16% to 77%. In all multivariable models, those who were very interested in learning a result type had significantly higher knowledge about sequencing benefits, greater genetic risks worry, and stronger health information orientation compared to those with less interest (p-values psychological factors. Shared decision-making approaches that increase knowledge about genome sequencing and incorporate patient preferences for health information and learning about genetic risks may help support patients' informed choices about learning different types of sequencing results. © Society of Behavioral Medicine 2018.

Multi-factor energy price models and exotic derivatives pricing

Science.gov (United States)

Hikspoors, Samuel

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

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

International Nuclear Information System (INIS)

Leary, R.A.

1988-01-01

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

Finite-lattice form factors in free-fermion models

International Nuclear Information System (INIS)

Iorgov, N; Lisovyy, O

2011-01-01

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

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

International Nuclear Information System (INIS)

Zagaglia, Paolo

2010-01-01

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

Form factors in the projected linear chiral sigma model

International Nuclear Information System (INIS)

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

1990-01-01

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

INTRAVAL test case 1b - modelling results

International Nuclear Information System (INIS)

Jakob, A.; Hadermann, J.

1991-07-01

This report presents results obtained within Phase I of the INTRAVAL study. Six different models are fitted to the results of four infiltration experiments with 233 U tracer on small samples of crystalline bore cores originating from deep drillings in Northern Switzerland. Four of these are dual porosity media models taking into account advection and dispersion in water conducting zones (either tubelike veins or planar fractures), matrix diffusion out of these into pores of the solid phase, and either non-linear or linear sorption of the tracer onto inner surfaces. The remaining two are equivalent porous media models (excluding matrix diffusion) including either non-linear sorption onto surfaces of a single fissure family or linear sorption onto surfaces of several different fissure families. The fits to the experimental data have been carried out by Marquardt-Levenberg procedure yielding error estimates of the parameters, correlation coefficients and also, as a measure for the goodness of the fits, the minimum values of the χ 2 merit function. The effects of different upstream boundary conditions are demonstrated and the penetration depth for matrix diffusion is discussed briefly for both alternative flow path scenarios. The calculations show that the dual porosity media models are significantly more appropriate to the experimental data than the single porosity media concepts. Moreover, it is matrix diffusion rather than the non-linearity of the sorption isotherm which is responsible for the tailing part of the break-through curves. The extracted parameter values for some models for both the linear and non-linear (Freundlich) sorption isotherms are consistent with the results of independent static batch sorption experiments. From the fits, it is generally not possible to discriminate between the two alternative flow path geometries. On the basis of the modelling results, some proposals for further experiments are presented. (author) 15 refs., 23 figs., 7 tabs

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...

Comparison of analytic source models for head scatter factor calculation and planar dose calculation for IMRT

International Nuclear Information System (INIS)

Yan Guanghua; Liu, Chihray; Lu Bo; Palta, Jatinder R; Li, Jonathan G

2008-01-01

The purpose of this study was to choose an appropriate head scatter source model for the fast and accurate independent planar dose calculation for intensity-modulated radiation therapy (IMRT) with MLC. The performance of three different head scatter source models regarding their ability to model head scatter and facilitate planar dose calculation was evaluated. A three-source model, a two-source model and a single-source model were compared in this study. In the planar dose calculation algorithm, in-air fluence distribution was derived from each of the head scatter source models while considering the combination of Jaw and MLC opening. Fluence perturbations due to tongue-and-groove effect, rounded leaf end and leaf transmission were taken into account explicitly. The dose distribution was calculated by convolving the in-air fluence distribution with an experimentally determined pencil-beam kernel. The results were compared with measurements using a diode array and passing rates with 2%/2 mm and 3%/3 mm criteria were reported. It was found that the two-source model achieved the best agreement on head scatter factor calculation. The three-source model and single-source model underestimated head scatter factors for certain symmetric rectangular fields and asymmetric fields, but similar good agreement could be achieved when monitor back scatter effect was incorporated explicitly. All the three source models resulted in comparable average passing rates (>97%) when the 3%/3 mm criterion was selected. The calculation with the single-source model and two-source model was slightly faster than the three-source model due to their simplicity

Comparison of analytic source models for head scatter factor calculation and planar dose calculation for IMRT

Energy Technology Data Exchange (ETDEWEB)

Yan Guanghua [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611 (United States); Liu, Chihray; Lu Bo; Palta, Jatinder R; Li, Jonathan G [Department of Radiation Oncology, University of Florida, Gainesville, FL 32610-0385 (United States)

2008-04-21

The purpose of this study was to choose an appropriate head scatter source model for the fast and accurate independent planar dose calculation for intensity-modulated radiation therapy (IMRT) with MLC. The performance of three different head scatter source models regarding their ability to model head scatter and facilitate planar dose calculation was evaluated. A three-source model, a two-source model and a single-source model were compared in this study. In the planar dose calculation algorithm, in-air fluence distribution was derived from each of the head scatter source models while considering the combination of Jaw and MLC opening. Fluence perturbations due to tongue-and-groove effect, rounded leaf end and leaf transmission were taken into account explicitly. The dose distribution was calculated by convolving the in-air fluence distribution with an experimentally determined pencil-beam kernel. The results were compared with measurements using a diode array and passing rates with 2%/2 mm and 3%/3 mm criteria were reported. It was found that the two-source model achieved the best agreement on head scatter factor calculation. The three-source model and single-source model underestimated head scatter factors for certain symmetric rectangular fields and asymmetric fields, but similar good agreement could be achieved when monitor back scatter effect was incorporated explicitly. All the three source models resulted in comparable average passing rates (>97%) when the 3%/3 mm criterion was selected. The calculation with the single-source model and two-source model was slightly faster than the three-source model due to their simplicity.

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

OpenAIRE

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

2017-01-01

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

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

International Nuclear Information System (INIS)

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

2011-01-01

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

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

Science.gov (United States)

Wada, Yoshihisa; Tsuji, Hiroshi

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

Does Sluggish Cognitive Tempo Fit within a Bi-factor Model of Attention-Deficit/Hyperactivity Disorder?

Science.gov (United States)

Garner, Annie A.; Peugh, James; Becker, Stephen P.; Kingery, Kathleen M.; Tamm, Leanne; Vaughn, Aaron J.; Ciesielski, Heather; Simon, John O.; Loren, Richard E. A.; Epstein, Jeffery N.

2014-01-01

Objective Studies demonstrate sluggish cognitive tempo (SCT) symptoms to be distinct from inattentive and hyperactive-impulsive dimensions of Attention-Deficit/Hyperactivity Disorder (ADHD). No study has examined SCT within a bi-factor model of ADHD whereby SCT may form a specific factor distinct from inattention and hyperactivity/impulsivity while still fitting within a general ADHD factor, which was the purpose of the current study. Method 168 children were recruited from an ADHD clinic. Most (92%) met diagnostic criteria for ADHD. Parents and teachers completed measures of ADHD and SCT. Results Although SCT symptoms were strongly associated with inattention they loaded onto a factor independent of ADHD ‘g’. Results were consistent across parent and teacher ratings. Conclusions SCT is structurally distinct from inattention as well as from the general ADHD latent symptom structure. Findings support a growing body of research suggesting SCT to be distinct and separate from ADHD. PMID:25005039

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

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Sahar Dalvand

2015-01-01

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

What Factors Lead Companies to Adopt Social Media in their processes: Proposal and Test of a Measurement Model

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Jozé Braz de Araújo

2016-01-01

Full Text Available The objective of this study was to understand which factors lead companies to use social media to achieve results. For that, a theoretical model was proposed and tested. Data was collected using a survey of 237 companies. In the analysis we analysis used the structural eq uation modeling technique. The results show that the social media relative advantage and its observability were important factors to social media organizational adoption. We also found that big companies with more formalized organizational structure (OS t end to adopt social media more than small ones with no formal OS. The companies studied showed strong organizational disposition for innovation adoption.

Chiral-model of weak-interaction form factors and magnetic moments of octet baryons

International Nuclear Information System (INIS)

Kubodera, K.; Kohyama, Y.; Tsushima, K.; Yamaguchi, T.

1989-01-01

For baryon spectroscopy, magnetic moments and weak interaction form factors provide valuable information, and the impressive amount of available experimental data on these quantities for the octet baryons invites detailed investigations. The authors of this paper have made extensive studies of the weak-interaction form factors and magnetic moments of the octet baryons within the framework of the volume-type cloudy-bag model (v-type CBM). The clouds of all octet mesons have been included. Furthermore, we have taken into account in a unified framework various effects that were so far only individually discussed in the literature. Thus, the gluonic effects, center-of-mass (CM0 corrections, and recoil corrections have been included). In this talk, after giving a brief summary of some salient features of the results, we discuss a very interesting application of our model to the problem of the spin content of nucleons

Relativistic form factors for hadrons with quark-model wave functions

International Nuclear Information System (INIS)

Stanley, D.P.; Robson, D.

1982-01-01

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

INTRAVAL Finnsjoen Test - modelling results for some tracer experiments

International Nuclear Information System (INIS)

Jakob, A.; Hadermann, J.

1994-09-01

This report presents the results within Phase II of the INTRAVAL study. Migration experiments performed at the Finnsjoen test site were investigated. The study was done to gain an improved understanding of not only the mechanisms of tracer transport, but also the accuracy and limitations of the model used. The model is based on the concept of a dual porosity medium, taking into account one dimensional advection, longitudinal dispersion, sorption onto the fracture surfaces, diffusion into connected pores of the matrix rock, and sorption onto matrix surfaces. The number of independent water carrying zones, represented either as planar fractures or tubelike veins, may be greater than one, and the sorption processes are described either by linear or non-linear Freundlich isotherms assuming instantaneous sorption equilibrium. The diffusion of the tracer out of the water-carrying zones into connected pore space of the adjacent rock is calculated perpendicular to the direction of the advective/dispersive flow. In the analysis, the fluid flow parameters are calibrated by the measured breakthrough curves for the conservative tracer (iodide). Subsequent fits to the experimental data for the two sorbing tracers strontium and cesium then involve element dependent parameters providing information on the sorption processes and on its representation in the model. The methodology of fixing all parameters except those for sorption with breakthrough curves for non-sorbing tracers generally worked well. The investigation clearly demonstrates the necessity of taking into account pump flow rate variations at both boundaries. If this is not done, reliable conclusions on transport mechanisms or geometrical factors can not be achieved. A two flow path model reproduces the measured data much better than a single flow path concept. (author) figs., tabs., 26 refs

Multiple Statistical Models Based Analysis of Causative Factors and Loess Landslides in Tianshui City, China

Science.gov (United States)

Su, Xing; Meng, Xingmin; Ye, Weilin; Wu, Weijiang; Liu, Xingrong; Wei, Wanhong

2018-03-01

Tianshui City is one of the mountainous cities that are threatened by severe geo-hazards in Gansu Province, China. Statistical probability models have been widely used in analyzing and evaluating geo-hazards such as landslide. In this research, three approaches (Certainty Factor Method, Weight of Evidence Method and Information Quantity Method) were adopted to quantitively analyze the relationship between the causative factors and the landslides, respectively. The source data used in this study are including the SRTM DEM and local geological maps in the scale of 1:200,000. 12 causative factors (i.e., altitude, slope, aspect, curvature, plan curvature, profile curvature, roughness, relief amplitude, and distance to rivers, distance to faults, distance to roads, and the stratum lithology) were selected to do correlation analysis after thorough investigation of geological conditions and historical landslides. The results indicate that the outcomes of the three models are fairly consistent.

Association between anthropometry, cardiometabolic risk factors, & early life factors & adult measures of endothelial function: Results from the New Delhi Birth Cohort

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Mark D Huffman

2015-01-01

Full Text Available Background & objectives: Abnormal endothelial function represents a preclinical marker of atherosclerosis. This study was conducted to evaluate associations between anthropometry, cardiometabolic risk factors, and early life factors and adult measures of endothelial function in a young urban Indian cohort free of clinical cardiovascular disease. Methods: Absolute changes in brachial artery diameter following cuff inflation and sublingual nitroglycerin (400 µg were recorded to evaluate endothelium-dependent and -independent measures of endothelial function in 600 participants (362 men; 238 women from the New Delhi Birth Cohort (2006-2009. Data on anthropometry, cardiometabolic risk factors, medical history, socio-economic position, and lifestyle habits were collected. Height and weight were recorded at birth, two and 11 yr of age. Age- and sex-adjusted linear regression models were developed to evaluate these associations. Results: The mean age of participants was 36±1 yr. Twenty two per cent men and 29 per cent women were obese (BMI th > 30 kg/m [2] . Mean systolic blood pressure (SBP was 131±14 and 119±13 mmHg, and diabetes prevalence was 12 and 8 per cent for men and women, respectively. Brachial artery diameter was higher for men compared with women both before (3.48±0.37 and 2.95±0.35 cm and after hyperaemia (3.87±0.37 vs. 3.37±0.35 cm. A similar difference was seen before and after nitroglycerin. Markers of increased adiposity, smoking, SBP, and metabolic syndrome, but not early life anthropometry, were inversely associated with endothelial function after adjustment for age and sex. Interpretation & conclusions: The analysis of the current prospective data from a young urban Indian cohort showed that cardiometabolic risk factors, but not early life anthropometry, were associated with worse endothelial function.

Application of Delphi method for determining the affecting factors upon audit risk model

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Zohreh Hajiha

2012-01-01

Full Text Available The assessment of risks in an audit work could directly influence the costs, timing, and strategies as well as audit quality. The purpose of this paper is to identify the critical affecting factors on risks proposed in Audit Risk Model (ARM, in Iranian audit environment of Iran. In the present, the Delphi Method consists of 60 audit partners and managers is employed. The panel consists of two equally divided groups, one from audit organization, a governmental organization, and the other from private audit firms. We employ two rounds of Delphi and 58 critical risk factors extracted from auditing literature and Iranian auditing standards and present them to the experts. There are 43 factors categorized as important factors to assess the risks in ARM. The results are considerable in an Iranian audit environment, findings show the most important factors are in inherent risk factors. Finally, we made a comparison with a similar study in Taiwan. Differences indicate that in professional judgment issues like risk assessment, the consideration of particular culture and environment could help enhance the precision of assessments, especially in assessing control risk factors.

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

Science.gov (United States)

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

2014-01-01

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

Towards a taxonomy of common factors in psychotherapy-results of an expert survey.

Science.gov (United States)

Tschacher, Wolfgang; Junghan, Ulrich Martin; Pfammatter, Mario

2014-01-01

How change comes about is hotly debated in psychotherapy research. One camp considers 'non-specific' or 'common factors', shared by different therapy approaches, as essential, whereas researchers of the other camp consider specific techniques as the essential ingredients of change. This controversy, however, suffers from unclear terminology and logical inconsistencies. The Taxonomy Project therefore aims at contributing to the definition and conceptualization of common factors of psychotherapy by analyzing their differential associations to standard techniques. A review identified 22 common factors discussed in psychotherapy research literature. We conducted a survey, in which 68 psychotherapy experts assessed how common factors are implemented by specific techniques. Using hierarchical linear models, we predicted each common factor by techniques and by experts' age, gender and allegiance to a therapy orientation. Common factors differed largely in their relevance for technique implementation. Patient engagement, Affective experiencing and Therapeutic alliance were judged most relevant. Common factors also differed with respect to how well they could be explained by the set of techniques. We present detailed profiles of all common factors by the (positively or negatively) associated techniques. There were indications of a biased taxonomy not covering the embodiment of psychotherapy (expressed by body-centred techniques such as progressive muscle relaxation, biofeedback training and hypnosis). Likewise, common factors did not adequately represent effective psychodynamic and systemic techniques. This taxonomic endeavour is a step towards a clarification of important core constructs of psychotherapy. This article relates standard techniques of psychotherapy (well known to practising therapists) to the change factors/change mechanisms discussed in psychotherapy theory. It gives a short review of the current debate on the mechanisms by which psychotherapy works. We

Correction the Bias of Odds Ratio resulting from the Misclassification of Exposures in the Study of Environmental Risk Factors of Lung Cancer using Bayesian Methods

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Alireza Abadi

2015-07-01

Full Text Available Background & Objective: Inability to measure exact exposure in epidemiological studies is a common problem in many studies, especially cross-sectional studies. Depending on the extent of misclassification, results may be affected. Existing methods for solving this problem require a lot of time and money and it is not practical for some of the exposures. Recently, new methods have been proposed in 1:1 matched case–control studies that have solved these problems to some extent. In the present study we have aimed to extend the existing Bayesian method to adjust for misclassification in matched case–control Studies with 1:2 matching. Methods: Here, the standard Dirichlet prior distribution for a multinomial model was extended to allow the data of exposure–disease (OR parameter to be imported into the model excluding other parameters. Information that exist in literature about association between exposure and disease were used as prior information about OR. In order to correct the misclassification Sensitivity Analysis was accomplished and the results were obtained under three Bayesian Methods. Results: The results of naïve Bayesian model were similar to the classic model. The second Bayesian model by employing prior information about the OR, was heavily affected by these information. The third proposed model provides maximum bias adjustment for the risk of heavy metals, smoking and drug abuse. This model showed that heavy metals are not an important risk factor although raw model (logistic regression Classic detected this exposure as an influencing factor on the incidence of lung cancer. Sensitivity analysis showed that third model is robust regarding to different levels of Sensitivity and Specificity. Conclusion: The present study showed that although in most of exposures the results of the second and third model were similar but the proposed model would be able to correct the misclassification to some extent.

Modeling the potential risk factors of bovine viral diarrhea prevalence in Egypt using univariable and multivariable logistic regression analyses

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Abdelfattah M. Selim

2018-03-01

Full Text Available Aim: The present cross-sectional study was conducted to determine the seroprevalence and potential risk factors associated with Bovine viral diarrhea virus (BVDV disease in cattle and buffaloes in Egypt, to model the potential risk factors associated with the disease using logistic regression (LR models, and to fit the best predictive model for the current data. Materials and Methods: A total of 740 blood samples were collected within November 2012-March 2013 from animals aged between 6 months and 3 years. The potential risk factors studied were species, age, sex, and herd location. All serum samples were examined with indirect ELIZA test for antibody detection. Data were analyzed with different statistical approaches such as Chi-square test, odds ratios (OR, univariable, and multivariable LR models. Results: Results revealed a non-significant association between being seropositive with BVDV and all risk factors, except for species of animal. Seroprevalence percentages were 40% and 23% for cattle and buffaloes, respectively. OR for all categories were close to one with the highest OR for cattle relative to buffaloes, which was 2.237. Likelihood ratio tests showed a significant drop of the -2LL from univariable LR to multivariable LR models. Conclusion: There was an evidence of high seroprevalence of BVDV among cattle as compared with buffaloes with the possibility of infection in different age groups of animals. In addition, multivariable LR model was proved to provide more information for association and prediction purposes relative to univariable LR models and Chi-square tests if we have more than one predictor.

Financial analysis and forecasting of the results of small businesses performance based on regression model

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Svetlana O. Musienko

2017-03-01

Full Text Available Objective to develop the economicmathematical model of the dependence of revenue on other balance sheet items taking into account the sectoral affiliation of the companies. Methods using comparative analysis the article studies the existing approaches to the construction of the company management models. Applying the regression analysis and the least squares method which is widely used for financial management of enterprises in Russia and abroad the author builds a model of the dependence of revenue on other balance sheet items taking into account the sectoral affiliation of the companies which can be used in the financial analysis and prediction of small enterprisesrsquo performance. Results the article states the need to identify factors affecting the financial management efficiency. The author analyzed scientific research and revealed the lack of comprehensive studies on the methodology for assessing the small enterprisesrsquo management while the methods used for large companies are not always suitable for the task. The systematized approaches of various authors to the formation of regression models describe the influence of certain factors on the company activity. It is revealed that the resulting indicators in the studies were revenue profit or the company relative profitability. The main drawback of most models is the mathematical not economic approach to the definition of the dependent and independent variables. Basing on the analysis it was determined that the most correct is the model of dependence between revenues and total assets of the company using the decimal logarithm. The model was built using data on the activities of the 507 small businesses operating in three spheres of economic activity. Using the presented model it was proved that there is direct dependence between the sales proceeds and the main items of the asset balance as well as differences in the degree of this effect depending on the economic activity of small

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

OpenAIRE

Rodney J Scott; Robert Y Cavana; Donald Cameron

2015-01-01

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

[Analysis of dietary pattern and diabetes mellitus influencing factors identified by classification tree model in adults of Fujian].

Science.gov (United States)

Yu, F L; Ye, Y; Yan, Y S

2017-05-10

Objective: To find out the dietary patterns and explore the relationship between environmental factors (especially dietary patterns) and diabetes mellitus in the adults of Fujian. Methods: Multi-stage sampling method were used to survey residents aged ≥18 years by questionnaire, physical examination and laboratory detection in 10 disease surveillance points in Fujian. Factor analysis was used to identify the dietary patterns, while logistic regression model was applied to analyze relationship between dietary patterns and diabetes mellitus, and classification tree model was adopted to identify the influencing factors for diabetes mellitus. Results: There were four dietary patterns in the population, including meat, plant, high-quality protein, and fried food and beverages patterns. The result of logistic analysis showed that plant pattern, which has higher factor loading of fresh fruit-vegetables and cereal-tubers, was a protective factor for non-diabetes mellitus. The risk of diabetes mellitus in the population at T2 and T3 levels of factor score were 0.727 (95 %CI: 0.561-0.943) times and 0.736 (95 %CI : 0.573-0.944) times higher, respectively, than those whose factor score was in lowest quartile. Thirteen influencing factors and eleven group at high-risk for diabetes mellitus were identified by classification tree model. The influencing factors were dyslipidemia, age, family history of diabetes, hypertension, physical activity, career, sex, sedentary time, abdominal adiposity, BMI, marital status, sleep time and high-quality protein pattern. Conclusion: There is a close association between dietary patterns and diabetes mellitus. It is necessary to promote healthy and reasonable diet, strengthen the monitoring and control of blood lipids, blood pressure and body weight, and have good lifestyle for the prevention and control of diabetes mellitus.

The Factors Influencing Satisfaction with Public City Transport: A Structural Equation Modelling Approach

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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.

Type D Personality : a five-factor model perspective

NARCIS (Netherlands)

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

2002-01-01

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

Specific count model for investing the related factors of cost of GERD and functional dyspepsia

Science.gov (United States)

Abadi, Alireza; Chaibakhsh, Samira; Safaee, Azadeh; Moghimi-Dehkordi, Bijan

2013-01-01

Aim The purpose of this study is to analyze the cost of GERD and functional dyspepsia for investing its related factors. Background Gastro-oesophageal reflux disease GERD and dyspepsia are the most common symptoms of gastrointestinal disorders. Recent studies showed high prevalence and variety of clinical presentation of these two symptoms imposed enormous economic burden to the society. Cost data that related to economics burden have specific characteristics. So this kind of data needs to specific models. Poisson regression (PR) and negative binomial regression (NB) are the models that were used for analyzing cost data in this paper. Patients and methods This study designed as a cross-sectional household survey from May 2006 to December 2007 on a random sample of individual in the Tehran province, Iran to find the prevalence of gastrointestinal symptoms and disorders and its related factors. The Cost in each item was counted. PR and NB were carried out to the data respectively. Likelihood ratio test was performed for comparison between models. Also Log likelihood, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used to compare performance of the models. Results According to Likelihood ratio test and all three criterions that we used to compare performance of the models, NB was the best model for analyzing this cost data. Sex, age and insurance statues were being significant. Conclusion PR and NB models were carried out for this data and according the results improved fit of the NB model over PR, it clearly indicates that over-dispersion is involved due to unobserved heterogeneity and/or clustering. NB model in cost data more appropriate fit than PR. PMID:24834282

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

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Afshin Fayyaz-Movaghar

2016-06-01

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

The uncertainty analysis of model results a practical guide

CERN Document Server

Hofer, Eduard

2018-01-01

This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decision-makers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results.

Modelling rainfall erosion resulting from climate change

Science.gov (United States)

Kinnell, Peter

2016-04-01

It is well known that soil erosion leads to agricultural productivity decline and contributes to water quality decline. The current widely used models for determining soil erosion for management purposes in agriculture focus on long term (~20 years) average annual soil loss and are not well suited to determining variations that occur over short timespans and as a result of climate change. Soil loss resulting from rainfall erosion is directly dependent on the product of runoff and sediment concentration both of which are likely to be influenced by climate change. This presentation demonstrates the capacity of models like the USLE, USLE-M and WEPP to predict variations in runoff and erosion associated with rainfall events eroding bare fallow plots in the USA with a view to modelling rainfall erosion in areas subject to climate change.

MODELING POLLINATION FACTORS THAT INFLUENCE ALFALFA SEED YIELD IN NORTH-CENTRAL NEVADA

OpenAIRE

BREAZEALE, Don; FERNANDEZ, George; NARAYANAN, Rangesan

2008-01-01

The relative importance of both environmental and management factors on alfalfa seed yield was investigated on North–Central Nevada farms. Multiple linear regression models using 2002-2003 data revealed that cumulative tripped fl owers increased seed yield in both years. Field location does not appear to make a difference in the observed variation in tripped fl ower production. The results suggest that seed yield can be increased by (a) by placing bee shelters closer and (b) cultural practice...

Collaborative Filtering Recommendation Based on Trust Model with Fused Similar Factor

Directory of Open Access Journals (Sweden)

Ye Li

2017-01-01

Full Text Available Recommended system is beneficial to e-commerce sites, which provides customers with product information and recommendations; the recommendation system is currently widely used in many fields. In an era of information explosion, the key challenges of the recommender system is to obtain valid information from the tremendous amount of information and produce high quality recommendations. However, when facing the large mount of information, the traditional collaborative filtering algorithm usually obtains a high degree of sparseness, which ultimately lead to low accuracy recommendations. To tackle this issue, we propose a novel algorithm named Collaborative Filtering Recommendation Based on Trust Model with Fused Similar Factor, which is based on the trust model and is combined with the user similarity. The novel algorithm takes into account the degree of interest overlap between the two users and results in a superior performance to the recommendation based on Trust Model in criteria of Precision, Recall, Diversity and Coverage. Additionally, the proposed model can effectively improve the efficiency of collaborative filtering algorithm and achieve high performance.

Off-critical statistical models: factorized scattering theories and bootstrap program

International Nuclear Information System (INIS)

Mussardo, G.

1992-01-01

We analyze those integrable statistical systems which originate from some relevant perturbations of the minimal models of conformal field theories. When only massive excitations are present, the systems can be efficiently characterized in terms of the relativistic scattering data. We review the general properties of the factorizable S-matrix in two dimensions with particular emphasis on the bootstrap principle. The classification program of the allowed spins of conserved currents and of the non-degenerate S-matrices is discussed and illustrated by means of some significant examples. The scattering theories of several massive perturbations of the minimal models are fully discussed. Among them are the Ising model, the tricritical Ising model, the Potts models, the series of the non-unitary minimal models M 2,2n+3 , the non-unitary model M 3,5 and the scaling limit of the polymer system. The ultraviolet limit of these massive integrable theories can be exploited by the thermodynamics Bethe ansatz, in particular the central charge of the original conformal theories can be recovered from the scattering data. We also consider the numerical method based on the so-called conformal space truncated approach which confirms the theoretical results and allows a direct measurement of the scattering data, i.e. the masses and the S-matrix of the particles in bootstrap interaction. The problem of computing the off-critical correlation functions is discussed in terms of the form-factor approach

Boolean modelling reveals new regulatory connections between transcription factors orchestrating the development of the ventral spinal cord.

KAUST Repository

Lovrics, Anna

2014-11-14

We have assembled a network of cell-fate determining transcription factors that play a key role in the specification of the ventral neuronal subtypes of the spinal cord on the basis of published transcriptional interactions. Asynchronous Boolean modelling of the network was used to compare simulation results with reported experimental observations. Such comparison highlighted the need to include additional regulatory connections in order to obtain the fixed point attractors of the model associated with the five known progenitor cell types located in the ventral spinal cord. The revised gene regulatory network reproduced previously observed cell state switches between progenitor cells observed in knock-out animal models or in experiments where the transcription factors were overexpressed. Furthermore the network predicted the inhibition of Irx3 by Nkx2.2 and this prediction was tested experimentally. Our results provide evidence for the existence of an as yet undescribed inhibitory connection which could potentially have significance beyond the ventral spinal cord. The work presented in this paper demonstrates the strength of Boolean modelling for identifying gene regulatory networks.

Factor copula models for data with spatio-temporal dependence

KAUST Repository

Krupskii, Pavel

2017-10-13

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

Factor copula models for data with spatio-temporal dependence

KAUST Repository

Krupskii, Pavel; Genton, Marc G.

2017-01-01

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

The Multi-state Latent Factor Intensity Model for Credit Rating Transitions

NARCIS (Netherlands)

Koopman, S.J.; Lucas, A.; Monteiro, A.

2008-01-01

A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic factors. The model has a generalized semi-Markov structure designed to accommodate many of the

A temperature dependent slip factor based thermal model for friction

Indian Academy of Sciences (India)

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

Neutron electromagnetic form factors

International Nuclear Information System (INIS)

Finn, J.M.; Madey, R.; Eden, T.; Markowitz, P.; Rutt, P.M.; Beard, K.; Anderson, B.D.; Baldwin, A.R.; Keane, D.; Manley, D.M.; Watson, J.W.; Zhang, W.M.; Kowalski, S.; Bertozzi, W.; Dodson, G.; Farkhondeh, M.; Dow, K.; Korsch, W.; Tieger, D.; Turchinetz, W.; Weinstein, L.; Gross, F.; Mougey, J.; Ulmer, P.; Whitney, R.; Reichelt, T.; Chang, C.C.; Kelly, J.J.; Payerle, T.; Cameron, J.; Ni, B.; Spraker, M.; Barkhuff, D.; Lourie, R.; Verst, S.V.; Hyde-Wright, C.; Jiang, W.-D.; Flanders, B.; Pella, P.; Arenhoevel, H.

1992-01-01

Nucleon form factors provide fundamental input for nuclear structure and quark models. Current knowledge of neutron form factors, particularly the electric form factor of the neutron, is insufficient to meet these needs. Developments of high-duty-factor accelerators and polarization-transfer techniques permit new experiments that promise results with small sensitivities to nuclear models. We review the current status of the field, our own work at the MIT/Bates linear accelerator, and future experimental efforts

Sequence2Vec: A novel embedding approach for modeling transcription factor binding affinity landscape

KAUST Repository

Dai, Hanjun

2017-07-26

Motivation: An accurate characterization of transcription factor (TF)-DNA affinity landscape is crucial to a quantitative understanding of the molecular mechanisms underpinning endogenous gene regulation. While recent advances in biotechnology have brought the opportunity for building binding affinity prediction methods, the accurate characterization of TF-DNA binding affinity landscape still remains a challenging problem. Results: Here we propose a novel sequence embedding approach for modeling the transcription factor binding affinity landscape. Our method represents DNA binding sequences as a hidden Markov model (HMM) which captures both position specific information and long-range dependency in the sequence. A cornerstone of our method is a novel message passing-like embedding algorithm, called Sequence2Vec, which maps these HMMs into a common nonlinear feature space and uses these embedded features to build a predictive model. Our method is a novel combination of the strength of probabilistic graphical models, feature space embedding and deep learning. We conducted comprehensive experiments on over 90 large-scale TF-DNA data sets which were measured by different high-throughput experimental technologies. Sequence2Vec outperforms alternative machine learning methods as well as the state-of-the-art binding affinity prediction methods.

Treatment results and prognostic factors of pediatric neuroblastoma: a retrospective study

Directory of Open Access Journals (Sweden)

El-Sayed Mohamed I

2010-12-01

Full Text Available Abstract Background We conducted a retrospective analysis to investigate treatment results and prognostic factors of pediatric neuroblastoma patients. Methods This retrospective study was carried out analyzing the medical records of patients with the pathological diagnosis of neuroblastoma seen at South Egypt Cancer Institute, Assiut University during the period from January 2001 and January 2010. After induction chemotherapy, response according to international neuoblastoma response criteria was assessed. Radiotherapy to patients with residual primary tumor was applied. Overall and event free survival (OAS and EFS rates were estimated using Graphed prism program. The Log-rank test was used to examine differences in OAS and EFS rates. Cox-regression multivariate analysis was done to determine the independent prognostic factors affecting survival rates. Results Fifty three cases were analyzed. The median follow-up duration was 32 months and ranged from 2 to 84 months. The 3-year OAS and EFS rates were 39.4% and 29.3% respectively. Poor prognostic factors included age >1 year of age, N-MYC amplification, and high risk group. The majority of patients (68% presented in high risk group, where treatment outcome was poor, as only 21% of patients survived for 3 year. Conclusion Multivariate analysis confirmed only the association between survival and risk group. However, in univariate analysis, local radiation therapy resulted in significant survival improvement. Therefore, radiotherapy should be given to patients with residual tumor evident after induction chemotherapy and surgery. Future attempts to improve OAS in high risk group patients with aggressive chemotherapy and bone marrow transplantation should be considered.

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

Science.gov (United States)

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

2014-05-01

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

Research Results of Bioenergetics Factors Influence on Crop Production Yields Increase

Directory of Open Access Journals (Sweden)