Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

Stevens, Andrew J.; Pu, Yunchen; Sun, Yannan; Spell, Gregory; Carin, Lawrence

2017-04-20

We introduce new dictionary learning methods for tensor-variate data of any order. We represent each data item as a sum of Kruskal decomposed dictionary atoms within the framework of beta-process factor analysis (BPFA). Our model is nonparametric and can infer the tensor-rank of each dictionary atom. This Kruskal-Factor Analysis (KFA) is a natural generalization of BPFA. We also extend KFA to a deep convolutional setting and develop online learning methods. We test our approach on image processing and classification tasks achieving state of the art results for 2D & 3D inpainting and Caltech 101. The experiments also show that atom-rank impacts both overcompleteness and sparsity.

Factors affecting construction performance: exploratory factor analysis

Science.gov (United States)

Soewin, E.; Chinda, T.

2018-04-01

The present work attempts to develop a multidimensional performance evaluation framework for a construction company by considering all relevant measures of performance. Based on the previous studies, this study hypothesizes nine key factors, with a total of 57 associated items. The hypothesized factors, with their associated items, are then used to develop questionnaire survey to gather data. The exploratory factor analysis (EFA) was applied to the collected data which gave rise 10 factors with 57 items affecting construction performance. The findings further reveal that the items constituting ten key performance factors (KPIs) namely; 1) Time, 2) Cost, 3) Quality, 4) Safety & Health, 5) Internal Stakeholder, 6) External Stakeholder, 7) Client Satisfaction, 8) Financial Performance, 9) Environment, and 10) Information, Technology & Innovation. The analysis helps to develop multi-dimensional performance evaluation framework for an effective measurement of the construction performance. The 10 key performance factors can be broadly categorized into economic aspect, social aspect, environmental aspect, and technology aspects. It is important to understand a multi-dimension performance evaluation framework by including all key factors affecting the construction performance of a company, so that the management level can effectively plan to implement an effective performance development plan to match with the mission and vision of the company.

Item-level factor analysis of the Self-Efficacy Scale.

Science.gov (United States)

Bunketorp Käll, Lina

2014-03-01

This study explores the internal structure of the Self-Efficacy Scale (SES) using item response analysis. The SES was previously translated into Swedish and modified to encompass all types of pain, not exclusively back pain. Data on perceived self-efficacy in 47 patients with subacute whiplash-associated disorders were derived from a previously conducted randomized-controlled trial. The item-level factor analysis was carried out using a six-step procedure. To further study the item inter-relationships and to determine the underlying structure empirically, the 20 items of the SES were also subjected to principal component analysis with varimax rotation. The analyses showed two underlying factors, named 'social activities' and 'physical activities', with seven items loading on each factor. The remaining six items of the SES appeared to measure somewhat different constructs and need to be analysed further.

A factor analysis to detect factors influencing building national brand

Directory of Open Access Journals (Sweden)

Naser Azad

Full Text Available Developing a national brand is one of the most important issues for development of a brand. In this study, we present factor analysis to detect the most important factors in building a national brand. The proposed study uses factor analysis to extract the most influencing factors and the sample size has been chosen from two major auto makers in Iran called Iran Khodro and Saipa. The questionnaire was designed in Likert scale and distributed among 235 experts. Cronbach alpha is calculated as 84%, which is well above the minimum desirable limit of 0.70. The implementation of factor analysis provides six factors including “cultural image of customers”, “exciting characteristics”, “competitive pricing strategies”, “perception image” and “previous perceptions”.

Nominal Performance Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M.A. Wasiolek

2003-07-25

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports (BSC 2003 [DIRS 160964]; BSC 2003 [DIRS 160965]; BSC 2003 [DIRS 160976]; BSC 2003 [DIRS 161239]; BSC 2003 [DIRS 161241]) contain detailed description of the model input parameters. This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs and conversion factors for the TSPA. The BDCFs will be used in performance assessment for calculating annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle activity in groundwater and the annual dose from beta- and photon-emitting radionuclides.

Factor analysis of multivariate data

Digital Repository Service at National Institute of Oceanography (India)

Fernandes, A.A.; Mahadevan, R.

A brief introduction to factor analysis is presented. A FORTRAN program, which can perform the Q-mode and R-mode factor analysis and the singular value decomposition of a given data matrix is presented in Appendix B. This computer program, uses...

Factor analysis and scintigraphy

International Nuclear Information System (INIS)

Di Paola, R.; Penel, C.; Bazin, J.P.; Berche, C.

1976-01-01

The goal of factor analysis is usually to achieve reduction of a large set of data, extracting essential features without previous hypothesis. Due to the development of computerized systems, the use of largest sampling, the possibility of sequential data acquisition and the increase of dynamic studies, the problem of data compression can be encountered now in routine. Thus, results obtained for compression of scintigraphic images were first presented. Then possibilities given by factor analysis for scan processing were discussed. At last, use of this analysis for multidimensional studies and specially dynamic studies were considered for compression and processing [fr

Nominal Performance Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M.A. Wasiolek

2005-01-01

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standards. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis'' (Figure 1-1). The objectives of this analysis are to develop BDCFs for the

Scalable group level probabilistic sparse factor analysis

DEFF Research Database (Denmark)

Hinrich, Jesper Løve; Nielsen, Søren Føns Vind; Riis, Nicolai Andre Brogaard

2017-01-01

Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a scalable group level probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component...... pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling...... shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex...

Multiple timescale analysis and factor analysis of energy ecological footprint growth in China 1953-2006

International Nuclear Information System (INIS)

Chen Chengzhong; Lin Zhenshan

2008-01-01

Scientific analysis of energy consumption and its influencing factors is of great importance for energy strategy and policy planning. The energy consumption in China 1953-2006 is estimated by applying the energy ecological footprint (EEF) method, and the fluctuation periods of annual China's per capita EEF (EEF cpc ) growth rate are analyzed with the empirical mode decomposition (EMD) method in this paper. EEF intensity is analyzed to depict energy efficiency in China. The main timescales of the 37 factors that affect the annual growth rate of EEF cpc are also discussed based on EMD and factor analysis methods. Results show three obvious undulation cycles of the annual growth rate of EEF cpc , i.e., 4.6, 14.4 and 34.2 years over the last 53 years. The analysis findings from the common synthesized factors of IMF1, IMF2 and IMF3 timescales of the 37 factors suggest that China's energy policy-makers should attach more importance to stabilizing economic growth, optimizing industrial structure, regulating domestic petroleum exploitation and improving transportation efficiency

An Analysis of Construction Accident Factors Based on Bayesian Network

OpenAIRE

Yunsheng Zhao; Jinyong Pei

2013-01-01

In this study, we have an analysis of construction accident factors based on bayesian network. Firstly, accidents cases are analyzed to build Fault Tree method, which is available to find all the factors causing the accidents, then qualitatively and quantitatively analyzes the factors with Bayesian network method, finally determines the safety management program to guide the safety operations. The results of this study show that bad condition of geological environment has the largest posterio...

A social work study using factor analysis on detecting important factors creating stress: A case study of hydro-power employees

Directory of Open Access Journals (Sweden)

Batoul Aminjafari

2012-08-01

Full Text Available The study performs an empirical study based on the implementation of factor analysis to detect different factors influencing people to have more stress in a hydropower unit located in city of Esfahan, Iran. The study performed the survey among all 81 people who were working for customer service section of this company and consisted of two parts, in the first part; we gather all private information such as age, gender, education, job experience, etc. through seven important questions. In the second part of the survey, there were 66 questions, which included all the relevant factors impacting employees' stress. Cronbach alpha was calculated as 0.946, which is well above the minimum acceptable level. The implementation of factor analysis has detected 16 important groups of factors and each factor is determined by an appropriate name. The results of our factor analysis show that among different factors, difficulty of working condition as well as work pressure are two most important factors increasing stress among employees.

Importance Performance Analysis as a Trade Show Performance Evaluation and Benchmarking Tool

OpenAIRE

Tafesse, Wondwesen; Skallerud, Kåre; Korneliussen, Tor

2010-01-01

Author's accepted version (post-print). The purpose of this study is to introduce importance performance analysis as a trade show performance evaluation and benchmarking tool. Importance performance analysis considers exhibitors’ performance expectation and perceived performance in unison to evaluate and benchmark trade show performance. The present study uses data obtained from exhibitors of an international trade show to demonstrate how importance performance analysis can be used to eval...

Nominal Performance Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2004-09-08

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs for the groundwater exposure scenario for the three climate states considered in the TSPA-LA as well as conversion factors for evaluating compliance with the groundwater protection standard. The BDCFs will be used in performance assessment for calculating all-pathway annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle

Nominal Performance Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs for the groundwater exposure scenario for the three climate states considered in the TSPA-LA as well as conversion factors for evaluating compliance with the groundwater protection standard. The BDCFs will be used in performance assessment for calculating all-pathway annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle activity in groundwater and the annual dose

Nominal Performance Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M.A. Wasiolek

2005-04-28

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standards. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis

Exploratory Bi-Factor Analysis: The Oblique Case

Science.gov (United States)

Jennrich, Robert I.; Bentler, Peter M.

2012-01-01

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford ("Psychometrika" 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler ("Psychometrika" 76:537-549, 2011) introduced an exploratory form of bi-factor…

ANALYSIS OF FACTORS WHICH AFFECTING THE ECONOMIC GROWTH

Directory of Open Access Journals (Sweden)

Suparna Wijaya

2017-03-01

Full Text Available High economic growth and sustainable process are main conditions for sustainability of economic country development. They are also become measures of the success of the country's economy. Factors which tested in this study are economic and non-economic factors which impacting economic development. This study has a goal to explain the factors that influence on macroeconomic Indonesia. It used linear regression modeling approach. The analysis result showed that Tax Amnesty, Exchange Rate, Inflation, and interest rate, they jointly can bring effect which amounted to 77.6% on economic growth whereas the remaining 22.4% is the influenced by other variables which not observed in this study. Keywords: tax amnesty, exchange rates, inflation, SBI and economic growth

Factor analysis of symptom profile in early onset and late onset OCD.

Science.gov (United States)

Grover, Sandeep; Sarkar, Siddharth; Gupta, Gourav; Kate, Natasha; Ghosh, Abhishek; Chakrabarti, Subho; Avasthi, Ajit

2018-04-01

This study aimed to assess the factor structure of early and late onset OCD. Additionally, cluster analysis was conducted in the same sample to assess the applicability of the factors. 345 participants were assessed with Yale Brown Obsessive Compulsive Scale symptom checklist. Patients were classified as early onset (onset of symptoms at age ≤ 18 years) and late onset (onset at age > 18 years) OCD depending upon the age of onset of the symptoms. Factor analysis and cluster analysis of early-onset and late-onset OCD was conducted. The study sample comprised of 91 early onset and 245 late onset OCD subjects. Males were more common in the early onset group. Differences in the frequency of phenomenology related to contamination related, checking, repeating, counting and ordering/arranging compulsions were present across the early and late onset groups. Factor analysis of YBOCS revealed a 3 factor solution for both the groups, which largely concurred with each other. These factors were named as hoarding and symmetry (factor-1), contamination (factor-2) and aggressive, sexual and religious factor (factor-3). To conclude this study shows that factor structure of symptoms of OCD seems to be similar between early-onset and late-onset OCD. Copyright © 2017 Elsevier B.V. All rights reserved.

Factor-cluster analysis and enrichment study of Mangrove sediments - An example from Mengkabong, Sabah

International Nuclear Information System (INIS)

Praveena, S.M.; Ahmed, A.; Radojevic, M.; Mohd Harun Abdullah; Aris, A.Z.

2007-01-01

This paper examines the tidal effects in the sediment of Mengkabong mangrove forest, Sabah. Generally, all the studied parameters showed high value at high tide compared to low tide. Factor-cluster analyses were adopted to allow the identification of controlling factors at high and low tides. Factor analysis extracted six controlling factors at high tide and seven controlling factors at low tide. Cluster analysis extracted two district clusters at high and low tides. The study showed that factor-cluster analysis application is a useful tool to single out the controlling factors at high and low tides. this will provide a basis for describing the tidal effects in the mangrove sediment. The salinity and electrical conductivity clusters as well as component loadings at high and low tide explained the tidal process where there is high contribution of seawater to mangrove sediments that controls the sediment chemistry. The geo accumulation index (T geo ) values suggest the mangrove sediments are having background concentrations for Al, Cu, Fe and Zn and unpolluted for Pb. (author)

Workplace Innovation: Exploratory and Confirmatory Factor Analysis for Construct Validation

Directory of Open Access Journals (Sweden)

Wipulanusat Warit

2017-06-01

Full Text Available Workplace innovation enables the development and improvement of products, processes and services leading simultaneously to improvement in organisational performance. This study has the purpose of examining the factor structure of workplace innovation. Survey data, extracted from the 2014 APS employee census, comprising 3,125 engineering professionals in the Commonwealth of Australia’s departments were analysed using exploratory factor analysis (EFA and confirmatory factor analysis (CFA. EFA returned a two-factor structure explaining 69.1% of the variance of the construct. CFA revealed that a two-factor structure was indicated as a validated model (GFI = 0.98, AGFI = 0.95, RMSEA = 0.08, RMR = 0.02, IFI = 0.98, NFI = 0.98, CFI = 0.98, and TLI = 0.96. Both factors showed good reliability of the scale (Individual creativity: α = 0.83, CR = 0.86, and AVE = 0.62; Team Innovation: α = 0.82, CR = 0.88, and AVE = 0.61. These results confirm that the two factors extracted for characterising workplace innovation included individual creativity and team innovation.

Research on Human-Error Factors of Civil Aircraft Pilots Based On Grey Relational Analysis

Directory of Open Access Journals (Sweden)

Guo Yundong

2018-01-01

Full Text Available In consideration of the situation that civil aviation accidents involve many human-error factors and show the features of typical grey systems, an index system of civil aviation accident human-error factors is built using human factor analysis and classification system model. With the data of accidents happened worldwide between 2008 and 2011, the correlation between human-error factors can be analyzed quantitatively using the method of grey relational analysis. Research results show that the order of main factors affecting pilot human-error factors is preconditions for unsafe acts, unsafe supervision, organization and unsafe acts. The factor related most closely with second-level indexes and pilot human-error factors is the physical/mental limitations of pilots, followed by supervisory violations. The relevancy between the first-level indexes and the corresponding second-level indexes and the relevancy between second-level indexes can also be analyzed quantitatively.

Blood donor show behaviour after an invitation to donate : The influence of collection site factors

NARCIS (Netherlands)

Merz, E.-M.; Zijlstra, B.J.H.; de Kort, W.L.A.M.

2017-01-01

Background and Objectives Show behaviour after invitation to donate varies considerably across donors. More insight into this variation is important for blood banks in achieving stable stocks. This study examined individual factors determining intended show behaviour. Most importantly, however, this

Blood donor show behavior after an invitation to donate: The influence of collection site factors

NARCIS (Netherlands)

Merz, E.M.; Zijlstra, Bonne; De Kort, Wim L.A.M.

2017-01-01

Background and Objectives Show behaviour after invitation to donate varies considerably across donors. More insight into this variation is important for blood banks in achieving stable stocks. This study examined individual factors determining intended show behaviour. Most importantly, however, this

Development Instruments Through Confirmatory Factor Analysis (CFA in Appropriate Intensity Assessment

Directory of Open Access Journals (Sweden)

Ari Saptono

2017-06-01

Full Text Available The research aims to develop the valid and reliable measurement instruments of entrepreneurship intention in vocational secondary school students. Multi stage random sampling was used as the technique to determine sample (300 respondents. The research method used research and development with confirmatory factor analysis (CFA. Result of confirmatory factor analysis (CFA at the second order with robust maximum likelihood method shows that valid and reliable instrument with the acquisition value of loading factor is more than 0.5 (> 0,5 and a significance value of t is more than 1,96 (> 1,96. Reliability test results shows that the value of the combined construct reliability (CR of 0.97and a variance value extract (VE to 0.52 is greater than the limit of acceptance CR ≥ 0.70 and VE ≥ 0.50. The conclusion of the measurement instruments of entrepreneurship intention with three dimensions and 31 items met the standards of validity and reliability in accordance with the instrument development process.

[A factor analysis method for contingency table data with unlimited multiple choice questions].

Science.gov (United States)

Toyoda, Hideki; Haiden, Reina; Kubo, Saori; Ikehara, Kazuya; Isobe, Yurie

2016-02-01

The purpose of this study is to propose a method of factor analysis for analyzing contingency tables developed from the data of unlimited multiple-choice questions. This method assumes that the element of each cell of the contingency table has a binominal distribution and a factor analysis model is applied to the logit of the selection probability. Scree plot and WAIC are used to decide the number of factors, and the standardized residual, the standardized difference between the sample, and the proportion ratio, is used to select items. The proposed method was applied to real product impression research data on advertised chips and energy drinks. Since the results of the analysis showed that this method could be used in conjunction with conventional factor analysis model, and extracted factors were fully interpretable, and suggests the usefulness of the proposed method in the study of psychology using unlimited multiple-choice questions.

The Infinitesimal Jackknife with Exploratory Factor Analysis

Science.gov (United States)

Zhang, Guangjian; Preacher, Kristopher J.; Jennrich, Robert I.

2012-01-01

The infinitesimal jackknife, a nonparametric method for estimating standard errors, has been used to obtain standard error estimates in covariance structure analysis. In this article, we adapt it for obtaining standard errors for rotated factor loadings and factor correlations in exploratory factor analysis with sample correlation matrices. Both…

Confirmatory Factor Analysis of the ISB - Burnout Syndrome Inventory

Directory of Open Access Journals (Sweden)

Ana Maria T. Benevides-Pereira

2017-05-01

Full Text Available AimBurnout is a dysfunctional reaction to chronic occupational stress. The present study analysis the psychometric qualities of the Burnout Syndrome Inventory (ISB through Confirmatory Factor Analysis (CFA.MethodEmpirical study in a multi-centre and multi-occupational sample (n = 701 using the ISB. The Part I assesses antecedent factors: Positive Organizational Conditions (PC and Negative Organizational Conditions (NC. The Part II assesses the syndrome: Emotional Exhaustion (EE, Dehumanization (DE, Emotional Distancing (ED and Personal Accomplishment (PA.ResultsThe highest means occurred in the positive scales CP (M = 23.29, SD = 5.89 and PA (M = 14.84, SD = 4.71. Negative conditions showed the greatest variability (SD = 6.03. Reliability indexes were reasonable, with the lowest rate at .77 for DE and the highest rate .91 for PA. The CFA revealed RMSEA = .057 and CFI = .90 with all scales regressions showing significant values (β = .73 until β = .92.ConclusionThe ISB showed a plausible instrument to evaluate burnout. The two sectors maintained the initial model and confirmed the theoretical presupposition. This instrument makes possible a more comprehensive idea of the labour context, and one or another part may be used separately according to the needs and the aims of the assessor.

Proteome Analysis of the Plant Pathogenic Fungus Monilinia laxa Showing Host Specificity

Directory of Open Access Journals (Sweden)

Olja Bregar

2012-01-01

Full Text Available Brown rot fungus Monilinia laxa (Aderh. & Ruhl. Honey is an important plant pathogen in stone and pome fruits in Europe. We applied a proteomic approach in a study of M. laxa isolates obtained from apples and apricots in order to show the host specifity of the isolates and to analyse differentially expressed proteins in terms of host specifity, fungal pathogenicity and identification of candidate proteins for diagnostic marker development. Extracted mycelium proteins were separated by 2-D electrophoresis (2-DE and visualized by Coomassie staining in a non-linear pH range of 3–11 and Mr of 14–116 kDa. We set up a 2-DE reference map of M. laxa, resolving up to 800 protein spots, and used it for image analysis. The average technical coefficient of variance (13 % demonstrated a high reproducibility of protein extraction and 2-D polyacrylamide gel electrophoresis (2-DE PAGE, and the average biological coefficient of variance (23 % enabled differential proteomic analysis of the isolates. Multivariate statistical analysis (principal component analysis discriminated isolates from two different hosts, providing new data that support the existence of a M. laxa specialized form f. sp. mali, which infects only apples. A total of 50 differentially expressed proteins were further analyzed by LC-MS/MS, yielding 41 positive identifications. The identified mycelial proteins were functionally classified into 6 groups: amino acid and protein metabolism, energy production, carbohydrate metabolism, stress response, fatty acid metabolism and other proteins. Some proteins expressed only in apple isolates have been described as virulence factors in other fungi. The acetolactate synthase was almost 11-fold more abundant in apple-specific isolates than in apricot isolates and it might be implicated in M. laxa host specificity. Ten proteins identified only in apple isolates are potential candidates for the development of M. laxa host-specific diagnostic markers.

Left ventricular wall motion abnormalities evaluated by factor analysis as compared with Fourier analysis

International Nuclear Information System (INIS)

Hirota, Kazuyoshi; Ikuno, Yoshiyasu; Nishikimi, Toshio

1986-01-01

Factor analysis was applied to multigated cardiac pool scintigraphy to evaluate its ability to detect left ventricular wall motion abnormalities in 35 patients with old myocardial infarction (MI), and in 12 control cases with normal left ventriculography. All cases were also evaluated by conventional Fourier analysis. In most cases with normal left ventriculography, the ventricular and atrial factors were extracted by factor analysis. In cases with MI, the third factor was obtained in the left ventricle corresponding to wall motion abnormality. Each case was scored according to the coincidence of findings of ventriculography and those of factor analysis or Fourier analysis. Scores were recorded for three items; the existence, location, and degree of asynergy. In cases of MI, the detection rate of asynergy was 94 % by factor analysis, 83 % by Fourier analysis, and the agreement in respect to location was 71 % and 66 %, respectively. Factor analysis had higher scores than Fourier analysis, but this was not significant. The interobserver error of factor analysis was less than that of Fourier analysis. Factor analysis can display locations and dynamic motion curves of asynergy, and it is regarded as a useful method for detecting and evaluating left ventricular wall motion abnormalities. (author)

Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

Science.gov (United States)

Roberson, Richard B; Elliott, Timothy R; Chang, Jessica E; Hill, Jessica N

2014-11-01

Our objective was to examine the use and quality of exploratory factor analysis (EFA) in articles published in Rehabilitation Psychology. Trained raters examined 66 separate exploratory factor analyses in 47 articles published between 1999 and April 2014. The raters recorded the aim of the EFAs, the distributional statistics, sample size, factor retention method(s), extraction and rotation method(s), and whether the pattern coefficients, structure coefficients, and the matrix of association were reported. The primary use of the EFAs was scale development, but the most widely used extraction and rotation method was principle component analysis, with varimax rotation. When determining how many factors to retain, multiple methods (e.g., scree plot, parallel analysis) were used most often. Many articles did not report enough information to allow for the duplication of their results. EFA relies on authors' choices (e.g., factor retention rules extraction, rotation methods), and few articles adhered to all of the best practices. The current findings are compared to other empirical investigations into the use of EFA in published research. Recommendations for improving EFA reporting practices in rehabilitation psychology research are provided.

Factor analysis and Mokken scaling of the Organizational Commitment Questionnaire in nurses.

Science.gov (United States)

Al-Yami, M; Galdas, P; Watson, R

2018-03-22

To generate an Arabic version of the Organizational Commitment Questionnaire that would be easily understood by Arabic speakers and would be sensitive to Arabic culture. The nursing workforce in Saudi Arabia is undergoing a process of Saudization but there is a need to understand the factors that will help to retain this workforce. No organizational commitment tools exist in Arabic that are specifically designed for health organizations. An Arabic version of the organizational commitment tool could aid Arabic speaking employers to understand their employees' perceptions of their organizations. Translation and back-translation followed by factor analysis (principal components analysis and confirmatory factor analysis) to test the factorial validity and item response theory (Mokken scaling). A two-factor structure was obtained for the Organizational Commitment Questionnaire comprising Factor 1: Value commitment; and Factor 2: Commitment to stay with acceptable reliability measured by internal consistency. A Mokken scale was obtained including items from both factors showing a hierarchy of items running from commitment to the organization and commitment to self. This study shows that the Arabic version of the OCQ retained the established two-factor structure of the original English-language version. Although the two factors - 'value commitment' and 'commitment to stay' - repudiate the original developers' single factor claim. A useful insight into the structure of the Organizational Commitment Questionnaire has been obtained with the novel addition of a hierarchical scale. The Organizational Commitment Questionnaire is now ready to be used with nurses in the Arab speaking world and could be used a tool to measure the contemporary commitment of nursing employees and in future interventions aimed at increasing commitment and retention of valuable nursing staff. © 2018 International Council of Nurses.

An Evaluation on Factors Influencing Decision making for Malaysia Disaster Management: The Confirmatory Factor Analysis Approach

Science.gov (United States)

Zubir, S. N. A.; Thiruchelvam, S.; Mustapha, K. N. M.; Che Muda, Z.; Ghazali, A.; Hakimie, H.

2017-12-01

For the past few years, natural disaster has been the subject of debate in disaster management especially in flood disaster. Each year, natural disaster results in significant loss of life, destruction of homes and public infrastructure, and economic hardship. Hence, an effective and efficient flood disaster management would assure non-futile efforts for life saving. The aim of this article is to examine the relationship between approach, decision maker, influence factor, result, and ethic to decision making for flood disaster management in Malaysia. The key elements of decision making in the disaster management were studied based on the literature. Questionnaire surveys were administered among lead agencies at East Coast of Malaysia in the state of Kelantan and Pahang. A total of 307 valid responses had been obtained for further analysis. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were carried out to analyse the measurement model involved in the study. The CFA for second-order reflective and first-order reflective measurement model indicates that approach, decision maker, influence factor, result, and ethic have a significant and direct effect on decision making during disaster. The results from this study showed that decision- making during disaster is an important element for disaster management to necessitate a successful collaborative decision making. The measurement model is accepted to proceed with further analysis known as Structural Equation Modeling (SEM) and can be assessed for the future research.

Phenotypic factor analysis of psychopathology reveals a new body-related transdiagnostic factor.

Science.gov (United States)

Pezzoli, Patrizia; Antfolk, Jan; Santtila, Pekka

2017-01-01

Comorbidity challenges the notion of mental disorders as discrete categories. An increasing body of literature shows that symptoms cut across traditional diagnostic boundaries and interact in shaping the latent structure of psychopathology. Using exploratory and confirmatory factor analysis, we reveal the latent sources of covariation among nine measures of psychopathological functioning in a population-based sample of 13024 Finnish twins and their siblings. By implementing unidimensional, multidimensional, second-order, and bifactor models, we illustrate the relationships between observed variables, specific, and general latent factors. We also provide the first investigation to date of measurement invariance of the bifactor model of psychopathology across gender and age groups. Our main result is the identification of a distinct "Body" factor, alongside the previously identified Internalizing and Externalizing factors. We also report relevant cross-disorder associations, especially between body-related psychopathology and trait anger, as well as substantial sex and age differences in observed and latent means. The findings expand the meta-structure of psychopathology, with implications for empirical and clinical practice, and demonstrate shared mechanisms underlying attitudes towards nutrition, self-image, sexuality and anger, with gender- and age-specific features.

Analysis on risk factors for post-stroke emotional incontinence

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Xiao-chun ZHANG

2018-01-01

Full Text Available Objective To investigate the occurrence rate and related risk factors for post-stroke emotional incontinence (PSEI. Methods The clinical data [sex, age, body mass index (BMI, education, marital status, medical history (hypertension, heart disease, diabetes, hyperlipemia, smoking and drinking and family history of stroke] of 162 stroke patients were recorded. Serum homocysteine (Hcy level was examined. Head CT and/or MRI were used to indicate stroke subtype, site of lesion and number of lesion. Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-Ⅴ Chinese version and Hamilton Depression Rating Scale-17 Items (HAMD-17 were used to evaluate the degree of depression. House diagnostic standard was used to diagnose PSEI. Univariate and multivariate backward Logistic regression analysis was used to screen related risk factor for PSEI. Spearman rank correlation analysis was used to discuss the correlation between PSEI and post-stroke depression (PSD. Results Among 162 stroke patients, 12 cases were diagnosed as PSEI (7.41% . The ratio of age < 60 years in PSEI group was significantly higher than non-PSEI group (P = 0.045. The ratio of smoking in PSEI group was significantly lower than non-PSEI group (P = 0.036. Univariate and multivariate backward Logistic regression analysis showed age < 60 years was independent risk factor for PSEI (OR = 4.000, 95%CI: 1.149-13.924; P = 0.029. Ten cases were combined with PSD in 12 PSEI patients, and the co-morbidity rate of PSEI and PSD was83.33%. Spearman rank correlation analysis showed PSEI was positively related to PSD (rs = 0.305, P = 0.000. Conclusions PSEI is common affective disorder in stroke patients, which easily happens in patients under 60 years of age. DOI: 10.3969/j.issn.1672-6731.2017.12.010

Tomato Fruits Show Wide Phenomic Diversity but Fruit Developmental Genes Show Low Genomic Diversity.

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Vijee Mohan

Full Text Available Domestication of tomato has resulted in large diversity in fruit phenotypes. An intensive phenotyping of 127 tomato accessions from 20 countries revealed extensive morphological diversity in fruit traits. The diversity in fruit traits clustered the accessions into nine classes and identified certain promising lines having desirable traits pertaining to total soluble salts (TSS, carotenoids, ripening index, weight and shape. Factor analysis of the morphometric data from Tomato Analyzer showed that the fruit shape is a complex trait shared by several factors. The 100% variance between round and flat fruit shapes was explained by one discriminant function having a canonical correlation of 0.874 by stepwise discriminant analysis. A set of 10 genes (ACS2, COP1, CYC-B, RIN, MSH2, NAC-NOR, PHOT1, PHYA, PHYB and PSY1 involved in various plant developmental processes were screened for SNP polymorphism by EcoTILLING. The genetic diversity in these genes revealed a total of 36 non-synonymous and 18 synonymous changes leading to the identification of 28 haplotypes. The average frequency of polymorphism across the genes was 0.038/Kb. Significant negative Tajima'D statistic in two of the genes, ACS2 and PHOT1 indicated the presence of rare alleles in low frequency. Our study indicates that while there is low polymorphic diversity in the genes regulating plant development, the population shows wider phenotype diversity. Nonetheless, morphological and genetic diversity of the present collection can be further exploited as potential resources in future.

The Analysis of Factors Influencing Effectivenes of Property Taxes in Karanganyar Regency

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Endang Brotojoyo

2018-03-01

Full Text Available The purpose of this study was to test empirically Effect of Compensation, Motivation and External Factors To Performance Officer With Property Taxes Voting in the District Effectiveness Matesih Karanganyar. The analysis technique used is using validity and reliability test, linearity test, regression analysis, path analysis, t test, F test, test the coefficient of determination and correlation analysis. Compensation Hypothesis Test Results significantly influence the effectiveness of tax collection. Motivation significantly influences the effectiveness of tax collection. External factors do not significant effect on effectiveness of tax collection. Compensation significant effect on the performance of Officers. Motivation significant effect on the performance of the Property Taxes polling clerk. External factors do not significant effect on the performance of Officers. Effectiveness of tax collection clerk significant effects on performance. F test results can be concluded jointly variable compensation, motivation, and external factors affecting the effectiveness of tax collection performance. The R2 total of 0,974 means that the performance of the Property Taxes in the district polling officer Matesih Karanganyar explained by the variable compensation, motivation, external factors and the effectiveness of tax collection amounted to 97.4%. The results of path analysis showed that the effective compensation and motivation through a direct path, while external factors are not effective for direct and indirect pathways.

Factor Economic Analysis at Forestry Enterprises

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M.Yu. Chik

2018-03-01

Full Text Available The article studies the importance of economic analysis according to the results of research of scientific works of domestic and foreign scientists. The calculation of the influence of factors on the change in the cost of harvesting timber products by cost items has been performed. The results of the calculation of the influence of factors on the change of costs on 1 UAH are determined using the full cost of sold products. The variable and fixed costs and their distribution are allocated that influences the calculation of the impact of factors on cost changes on 1 UAH of sold products. The paper singles out the general results of calculating the influence of factors on cost changes on 1 UAH of sold products. According to the results of the analysis, the list of reserves for reducing the cost of production at forest enterprises was proposed. The main sources of reserves for reducing the prime cost of forest products at forest enterprises are investigated based on the conducted factor analysis.

Students' motivation to study dentistry in Malaysia: an analysis using confirmatory factor analysis.

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Musa, Muhd Firdaus Che; Bernabé, Eduardo; Gallagher, Jennifer E

2015-06-12

Malaysia has experienced a significant expansion of dental schools over the past decade. Research into students' motivation may inform recruitment and retention of the future dental workforce. The objectives of this study were to explore students' motivation to study dentistry and whether that motivation varied by students' and school characteristics. All 530 final-year students in 11 dental schools (6 public and 5 private) in Malaysia were invited to participate at the end of 2013. The self-administered questionnaire, developed at King's College London, collected information on students' motivation to study dentistry and demographic background. Responses on students' motivation were collected using five-point ordinal scales. Confirmatory factor analysis (CFA) was used to evaluate the underlying structure of students' motivation to study dentistry. Multivariate analysis of variance (MANOVA) was used to compare factor scores for overall motivation and sub-domains by students' and school characteristics. Three hundred and fifty-six final-year students in eight schools (all public and two private) participated in the survey, representing an 83% response rate for these schools and 67% of all final-year students nationally. The majority of participants were 24 years old (47%), female (70%), Malay (56%) and from middle-income families (41%) and public schools (78%). CFA supported a model with five first-order factors (professional job, healthcare and people, academic, careers advising and family and friends) which were linked to a single second-order factor representing overall students' motivation. Academic factors and healthcare and people had the highest standardized factor loadings (0.90 and 0.71, respectively), suggesting they were the main motivation to study dentistry. MANOVA showed that students from private schools had higher scores for healthcare and people than those in public schools whereas Malay students had lower scores for family and friends than those

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

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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.

A methodology to incorporate organizational factors into human reliability analysis

International Nuclear Information System (INIS)

Li Pengcheng; Chen Guohua; Zhang Li; Xiao Dongsheng

2010-01-01

A new holistic methodology for Human Reliability Analysis (HRA) is proposed to model the effects of the organizational factors on the human reliability. Firstly, a conceptual framework is built, which is used to analyze the causal relationships between the organizational factors and human reliability. Then, the inference model for Human Reliability Analysis is built by combining the conceptual framework with Bayesian networks, which is used to execute the causal inference and diagnostic inference of human reliability. Finally, a case example is presented to demonstrate the specific application of the proposed methodology. The results show that the proposed methodology of combining the conceptual model with Bayesian Networks can not only easily model the causal relationship between organizational factors and human reliability, but in a given context, people can quantitatively measure the human operational reliability, and identify the most likely root causes or the prioritization of root causes caused human error. (authors)

Comprehensive analysis of the related factors of early hypothyroidism occurring in patients with Graves' disease after 131I treatment

International Nuclear Information System (INIS)

Tan Jian; Wang Peng; Zhang Lijuan; He Yajing; Wang Renfei

2005-01-01

Objective: To make a comprehensive analysis of the related factors of early hypothyroidism occurring in patients with Graves' disease after 131 I treatment. Methods: The information of 131 I treated Graves' disease was collected including general data, clinical observation, laboratory data, thyroid function test, etc. Then a retrospective statistical analysis was carried out, using cluster analysis, factor analysis, discriminant analysis, multivariate regression analysis, etc. Results: 1) Cluster analysis and factor analysis showed that among clinical observation such as clinical course, treatment course, patients' state and disease occurrance, the first three factors correlated highly; among laboratory data such as thyrotrophin receptor antibody (TRAb), thyroid-stimulating immunoglobulins (TSI), thyroglobulin antibody (TgAb) and thyroid microsomal antibody (TMAb), both the first two and the last two correlated highly, each two factors had the similar effect. 2) Fsher discriminant analysis showed that among the thyroid weight, the effective half life, the maximum 131 I uptake percentage, total dose of 131 I and the average dose of 131 I per gram of thyroid, the last one had the most predicting value for incidence of early hypothyroidism. 3) Logistic regression analysis showed that among all the related factors of early hypothyroidism occurred after 131 I treated Graves' disease, thyroid weight, average dose of 131 I per gram of thyroid, the maximum 131 I uptake percentage and the level of TSI were effective factors. Conclusions: The occurrence of early hypothyroidism for 131 I-treated Graves' disease is probably affected by many factors. If more factors are taken into consideration before therapy and the theraputic dose is well adjusted accordingly, it can reduce the incidence of early hypothroidism to a certain extent. (authors)

Influence factors analysis of water environmental quality of main rivers in Tianjin

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Li, Ran; Bao, Jingling; Zou, Di; Shi, Fang

2018-01-01

According to the evaluation results of the water environment quality of main rivers in Tianjin in 1986-2015, this paper analyzed the current situation of water environmental quality of main rivers in Tianjin retrospectively, established the index system and multiple factors analysis through selecting factors influencing the water environmental quality of main rivers from the economy, industry and nature aspects with the combination method of principal component analysis and linear regression. The results showed that water consumption, sewage discharge and water resources were the main factors influencing the pollution of main rivers. Therefore, optimizing the utilization of water resources, improving utilization efficiency and reducing effluent discharge are important measures to reduce the pollution of surface water environment.

First course in factor analysis

CERN Document Server

Comrey, Andrew L

2013-01-01

The goal of this book is to foster a basic understanding of factor analytic techniques so that readers can use them in their own research and critically evaluate their use by other researchers. Both the underlying theory and correct application are emphasized. The theory is presented through the mathematical basis of the most common factor analytic models and several methods used in factor analysis. On the application side, considerable attention is given to the extraction problem, the rotation problem, and the interpretation of factor analytic results. Hence, readers are given a background of

Exploring factors that influence work analysis data: A meta-analysis of design choices, purposes, and organizational context.

Science.gov (United States)

DuVernet, Amy M; Dierdorff, Erich C; Wilson, Mark A

2015-09-01

Work analysis is fundamental to designing effective human resource systems. The current investigation extends previous research by identifying the differential effects of common design decisions, purposes, and organizational contexts on the data generated by work analyses. The effects of 19 distinct factors that span choices of descriptor, collection method, rating scale, and data source, as well as project purpose and organizational features, are explored. Meta-analytic results cumulated from 205 articles indicate that many of these variables hold significant consequences for work analysis data. Factors pertaining to descriptor choice, collection method, rating scale, and the purpose for conducting the work analysis each showed strong associations with work analysis data. The source of the work analysis information and organizational context in which it was conducted displayed fewer relationships. Findings can be used to inform choices work analysts make about methodology and postcollection evaluations of work analysis information. (c) 2015 APA, all rights reserved).

A Confirmatory Factor Analysis of the Structure of Abbreviated Math Anxiety Scale

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Farahman Farrokhi

2011-06-01

Full Text Available "nObjective: The aim of this study is to explore the confirmatory factor analysis results of the Persian adaptation of Abbreviated Math Anxiety Scale (AMAS, proposed by Hopko, Mahadevan, Bare & Hunt. "nMethod: The validity and reliability assessments of the scale were performed on 298 college students chosen randomly from Tabriz University in Iran. The confirmatory factor analysis (CFA was carried out to determine the factor structures of the Persian version of AMAS. "nResults: As expected, the two-factor solution provided a better fit to the data than a single factor. Moreover, multi-group analyses showed that this two-factor structure was invariant across sex. Hence, AMAS provides an equally valid measure for use among college students. "nConclusions:  Brief AMAS demonstrates adequate reliability and validity. The AMAS scores can be used to compare symptoms of math anxiety between male and female students. The study both expands and adds support to the existing body of math anxiety literature.

PATH ANALYSIS OF RECORDING SYSTEM INNOVATION FACTORS AFFECTING ADOPTION OF GOAT FARMERS

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S. Okkyla

2014-09-01

Full Text Available The objective of this study was to evaluate the path analysis of recording system innovation factorsaffecting adoption of goat farmers. This study was conducted from January to February 2014 inPringapus District, Semarang Regency by using survey method. For determining the location, this studyused purposive sampling method. The amount of respondents were determined by quota samplingmethod. Total respondents randomly chosed were 146 farmers. The data were descriptively andquantitatively analyzed by using path analysis of statistical package for the social science (SPSS 16.Independent variables in this study were internal factor, motivation, innovation characteristics,information source, and dependent variable was adoption. Analysis of linear regression showed thatthere was no significant effect of internal factor on adoption, so that it was important to use the trimmingmethod in path analysis. The result of path analysis showed that the influence of motivation, innovationcharacteristics and information source on adoption were 0.168; 0.720 and 0.09, respectively. Innovationcharacteristics were the greatest effect on adoption. In conclusion, by improving innovationcharacteristics of respondent through motivation and information source may significantly increase theadoption of recording system in goat farmers.

Path analysis of risk factors leading to premature birth.

Science.gov (United States)

Fields, S J; Livshits, G; Sirotta, L; Merlob, P

1996-01-01

The present study tested whether various sociodemographic, anthropometric, behavioral, and medical/physiological factors act in a direct or indirect manner on the risk of prematurity using path analysis on a sample of Israeli births. The path model shows that medical complications, primarily toxemia, chorioammionitis, and a previous low birth weight delivery directly and significantly act on the risk of prematurity as do low maternal pregnancy weight gain and ethnicity. Other medical complications, including chronic hypertension, preclampsia, and placental abruption, although significantly correlated with prematurity, act indirectly on prematurity through toxemia. The model further shows that the commonly accepted sociodemographic, anthropometric, and behavioral risk factors act by modifying the development of medical complications that lead to prematurity as opposed to having a direct effect on premature delivery. © 1996 Wiley-Liss, Inc. Copyright © 1996 Wiley-Liss, Inc.

Factor analysis of the contextual fine motor questionnaire in children.

Science.gov (United States)

Lin, Chin-Kai; Meng, Ling-Fu; Yu, Ya-Wen; Chen, Che-Kuo; Li, Kuan-Hua

2014-02-01

Most studies treat fine motor as one subscale in a developmental test, hence, further factor analysis of fine motor has not been conducted. In fact, fine motor has been treated as a multi-dimensional domain from both clinical and theoretical perspectives, and therefore to know its factors would be valuable. The aim of this study is to analyze the internal consistency and factor validity of the Contextual Fine Motor Questionnaire (CFMQ). Based on the ecological observation and literature, the Contextual Fine Motor Questionnaire (CFMQ) was developed and includes 5 subscales: Pen Control, Tool Use During Handicraft Activities, the Use of Dining Utensils, Connecting and Separating during Dressing and Undressing, and Opening Containers. The main purpose of this study is to establish the factorial validity of the CFMQ through conducting this factor analysis study. Among 1208 questionnaires, 904 were successfully completed. Data from the children's CFMQ submitted by primary care providers was analyzed, including 485 females (53.6%) and 419 males (46.4%) from grades 1 to 5, ranging in age from 82 to 167 months (M=113.9, SD=16.3). Cronbach's alpha was used to measure internal consistency and explorative factor analysis was applied to test the five factor structures within the CFMQ. Results showed that Cronbach's alpha coefficient of the CFMQ for 5 subscales ranged from .77 to .92 and all item-total correlations with corresponding subscales were larger than .4 except one item. The factor loading of almost all items classified to their factor was larger than .5 except 3 items. There were five factors, explaining a total of 62.59% variance for the CFMQ. In conclusion, the remaining 24 items in the 5 subscales of the CFMQ had appropriate internal consistency, test-retest reliability and construct validity. Copyright © 2013 Elsevier Ltd. All rights reserved.

Disruptive Event Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2004-09-08

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2004 [DIRS 169671]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis''. The objective of this

Disruptive Event Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2004 [DIRS 169671]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis''. The objective of this analysis was to develop the BDCFs for the volcanic ash

Disruptive Event Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M. A. Wasiolek

2003-07-21

This analysis report, ''Disruptive Event Biosphere Dose Conversion Factor Analysis'', is one of the technical reports containing documentation of the ERMYN (Environmental Radiation Model for Yucca Mountain Nevada) biosphere model for the geologic repository at Yucca Mountain, its input parameters, and the application of the model to perform the dose assessment for the repository. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of the two reports that develop biosphere dose conversion factors (BDCFs), which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the conceptual model as well as the mathematical model and lists its input parameters. Model input parameters are developed and described in detail in five analysis report (BSC 2003 [DIRS 160964], BSC 2003 [DIRS 160965], BSC 2003 [DIRS 160976], BSC 2003 [DIRS 161239], and BSC 2003 [DIRS 161241]). The objective of this analysis was to develop the BDCFs for the volcanic ash exposure scenario and the dose factors (DFs) for calculating inhalation doses during volcanic eruption (eruption phase of the volcanic event). The volcanic ash exposure scenario is hereafter referred to as the volcanic ash scenario. For the volcanic ash scenario, the mode of radionuclide release into the biosphere is a volcanic eruption through the repository with the resulting entrainment of contaminated waste in the tephra and the subsequent atmospheric transport and dispersion of contaminated material in

Disruptive Event Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M. A. Wasiolek

2003-01-01

This analysis report, ''Disruptive Event Biosphere Dose Conversion Factor Analysis'', is one of the technical reports containing documentation of the ERMYN (Environmental Radiation Model for Yucca Mountain Nevada) biosphere model for the geologic repository at Yucca Mountain, its input parameters, and the application of the model to perform the dose assessment for the repository. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of the two reports that develop biosphere dose conversion factors (BDCFs), which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the conceptual model as well as the mathematical model and lists its input parameters. Model input parameters are developed and described in detail in five analysis report (BSC 2003 [DIRS 160964], BSC 2003 [DIRS 160965], BSC 2003 [DIRS 160976], BSC 2003 [DIRS 161239], and BSC 2003 [DIRS 161241]). The objective of this analysis was to develop the BDCFs for the volcanic ash exposure scenario and the dose factors (DFs) for calculating inhalation doses during volcanic eruption (eruption phase of the volcanic event). The volcanic ash exposure scenario is hereafter referred to as the volcanic ash scenario. For the volcanic ash scenario, the mode of radionuclide release into the biosphere is a volcanic eruption through the repository with the resulting entrainment of contaminated waste in the tephra and the subsequent atmospheric transport and dispersion of contaminated material in the biosphere. The biosphere process

Inference algorithms and learning theory for Bayesian sparse factor analysis

International Nuclear Information System (INIS)

Rattray, Magnus; Sharp, Kevin; Stegle, Oliver; Winn, John

2009-01-01

Bayesian sparse factor analysis has many applications; for example, it has been applied to the problem of inferring a sparse regulatory network from gene expression data. We describe a number of inference algorithms for Bayesian sparse factor analysis using a slab and spike mixture prior. These include well-established Markov chain Monte Carlo (MCMC) and variational Bayes (VB) algorithms as well as a novel hybrid of VB and Expectation Propagation (EP). For the case of a single latent factor we derive a theory for learning performance using the replica method. We compare the MCMC and VB/EP algorithm results with simulated data to the theoretical prediction. The results for MCMC agree closely with the theory as expected. Results for VB/EP are slightly sub-optimal but show that the new algorithm is effective for sparse inference. In large-scale problems MCMC is infeasible due to computational limitations and the VB/EP algorithm then provides a very useful computationally efficient alternative.

Inference algorithms and learning theory for Bayesian sparse factor analysis

Energy Technology Data Exchange (ETDEWEB)

Rattray, Magnus; Sharp, Kevin [School of Computer Science, University of Manchester, Manchester M13 9PL (United Kingdom); Stegle, Oliver [Max-Planck-Institute for Biological Cybernetics, Tuebingen (Germany); Winn, John, E-mail: magnus.rattray@manchester.ac.u [Microsoft Research Cambridge, Roger Needham Building, Cambridge, CB3 0FB (United Kingdom)

2009-12-01

Bayesian sparse factor analysis has many applications; for example, it has been applied to the problem of inferring a sparse regulatory network from gene expression data. We describe a number of inference algorithms for Bayesian sparse factor analysis using a slab and spike mixture prior. These include well-established Markov chain Monte Carlo (MCMC) and variational Bayes (VB) algorithms as well as a novel hybrid of VB and Expectation Propagation (EP). For the case of a single latent factor we derive a theory for learning performance using the replica method. We compare the MCMC and VB/EP algorithm results with simulated data to the theoretical prediction. The results for MCMC agree closely with the theory as expected. Results for VB/EP are slightly sub-optimal but show that the new algorithm is effective for sparse inference. In large-scale problems MCMC is infeasible due to computational limitations and the VB/EP algorithm then provides a very useful computationally efficient alternative.

This research is to study the factors which influence the business success of small business ‘processed rotan’. The data employed in the study are primary data within the period of July to August 2013, 30 research observations through census method. Method of analysis used in the study is multiple linear regressions. The results of analysis showed that the factors of labor, innovation and promotion have positive and significant influence on the business success of small business ‘processed rotan’ simultaneously. The analysis also showed that partially labor has positive and significant influence on the business success, yet innovation and promotion have insignificant and positive influence on the business success.

OpenAIRE

Nasution, Inggrita Gusti Sari; Muchtar, Yasmin Chairunnisa

2013-01-01

This research is to study the factors which influence the business success of small business ‘processed rotan’. The data employed in the study are primary data within the period of July to August 2013, 30 research observations through census method. Method of analysis used in the study is multiple linear regressions. The results of analysis showed that the factors of labor, innovation and promotion have positive and significant influence on the business success of small busine...

Multiple factor analysis by example using R

CERN Document Server

Pagès, Jérôme

2014-01-01

Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR).The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The

Multivariate factor analysis of Girgentana goat milk composition

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Pietro Giaccone

2010-01-01

Full Text Available The interpretation of the several variables that contribute to defining milk quality is difficult due to the high degree of  correlation among them. In this case, one of the best methods of statistical processing is factor analysis, which belongs  to the multivariate groups; for our study this particular statistical approach was employed.  A total of 1485 individual goat milk samples from 117 Girgentana goats, were collected fortnightly from January to July,  and analysed for physical and chemical composition, and clotting properties. Milk pH and tritable acidity were within the  normal range for fresh goat milk. Morning milk yield resulted 704 ± 323 g with 3.93 ± 1.23% and 3.48±0.38% for fat  and protein percentages, respectively. The milk urea content was 43.70 ± 8.28 mg/dl. The clotting ability of Girgentana  milk was quite good, with a renneting time equal to 16.96 ± 3.08 minutes, a rate of curd formation of 2.01 ± 1.63 min-  utes and a curd firmness of 25.08 ± 7.67 millimetres.  Factor analysis was performed by applying axis orthogonal rotation (rotation type VARIMAX; the analysis grouped the  milk components into three latent or common factors. The first, which explained 51.2% of the total covariance, was  defined as “slow milks”, because it was linked to r and pH. The second latent factor, which explained 36.2% of the total  covariance, was defined as “milk yield”, because it is positively correlated to the morning milk yield and to the urea con-  tent, whilst negatively correlated to the fat percentage. The third latent factor, which explained 12.6% of the total covari-  ance, was defined as “curd firmness,” because it is linked to protein percentage, a30 and titatrable acidity. With the aim  of evaluating the influence of environmental effects (stage of kidding, parity and type of kidding, factor scores were anal-  ysed with the mixed linear model. Results showed significant effects of the season of

Towards factor analysis exploration applied to positron emission tomography functional imaging for breast cancer characterization

International Nuclear Information System (INIS)

Rekik, W.; Ketata, I.; Sellami, L.; Ben slima, M.; Ben Hamida, A.; Chtourou, K.; Ruan, S.

2011-01-01

This paper aims to explore the factor analysis when applied to a dynamic sequence of medical images obtained using nuclear imaging modality, Positron Emission Tomography (PET). This latter modality allows obtaining information on physiological phenomena, through the examination of radiotracer evolution during time. Factor analysis of dynamic medical images sequence (FADMIS) estimates the underlying fundamental spatial distributions by factor images and the associated so-called fundamental functions (describing the signal variations) by factors. This method is based on an orthogonal analysis followed by an oblique analysis. The results of the FADMIS are physiological curves showing the evolution during time of radiotracer within homogeneous tissues distributions. This functional analysis of dynamic nuclear medical images is considered to be very efficient for cancer diagnostics. In fact, it could be applied for cancer characterization, vascularization as well as possible evaluation of response to therapy.

Analysis of risk factors for non-anastomotic biliary stricture following liver transplantation

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WU Xiaofeng

2013-06-01

Full Text Available ObjectiveTo investigate the risk factors for non-anastomotic biliary stricture (NABS following liver transplantation. MethodsA retrospective analysis was performed on 175 patients who underwent liver transplantation from January 2004 to December 2010 to analyze the risk factors for NABS, which included sex, age, primary disease, blood type, T-tube placement, acute rejection, biliary tract infection, cytomegalovirus infection, Child-Pugh score, cold ischemia time, warm ischemia time, duration of anhepatic phase, and mean hepatic artery blood flow within one week after operation. These patients were divided into early group, who underwent operation from January 2004 to December 2006, and late group, who underwent operation from January 2007 to December 2010; each group was further divided into two subgroups according to whether they developed NABS. The risk factors for NABS were determined by univariate and multivariate logistic regression analyses. ResultsThe univariate logistic regression analysis showed that the risk factors for NABS were biliary tract infection, T-tube placement, and acute rejection in the early group (P＜0.05 and that acute rejection was the risk factor in the late group (P=0003. The multivariate logistic regression analysis showed that acute rejection was significantly associated with NABS in the early group (P=0.014. ConclusionThe risk factors for NABS following liver transplantation from January 2004 to December 2006; biliary tract infection and T-tube placement could be prevented by perioperative interventions, thus reducing the incidence of NABS. The incidence of acute rejection was reduced from January 2007 to December 2010, but it was still significantly associated with NABS.

Analysis of Factors That Affects the Investors in Conducting Business in Indonesia

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Rini Kurnia Sari

2015-10-01

Full Text Available Investment is needed in the development of the economy. With the decentralization of investment is expected to evolve as a whole in every province in Indonesia. Local governments need to improve the quality of economic (GDP / Capita, social (HDI and the infrastructure to attract domestic and foreign investors. Fromthe test results showed that factors affecting investors conducting business in Indonesia is still influenced by GDP/capita, HDI and Infrastructure instead of natural resources.This study uses descriptive analysis and correlation analysis methods to look at the correlation factors that affect investors doing business in Indonesia.

Analysis of mineral phases in coal utilizing factor analysis

International Nuclear Information System (INIS)

Roscoe, B.A.; Hopke, P.K.

1982-01-01

The mineral phase inclusions of coal are discussed. The contribution of these to a coal sample are determined utilizing several techniques. Neutron activation analysis in conjunction with coal washability studies have produced some information on the general trends of elemental variation in the mineral phases. These results have been enhanced by the use of various statistical techniques. The target transformation factor analysis is specifically discussed and shown to be able to produce elemental profiles of the mineral phases in coal. A data set consisting of physically fractionated coal samples was generated. These samples were analyzed by neutron activation analysis and then their elemental concentrations examined using TTFA. Information concerning the mineral phases in coal can thus be acquired from factor analysis even with limited data. Additional data may permit the resolution of additional mineral phases as well as refinement of theose already identified

Perception on obesity among university students: A case study using factor analysis

Science.gov (United States)

Hassan, Suriani; Rahman, Nur Amira Abdol; Ghazali, Khadizah; Ismail, Norlita; Budin, Kamsia

2014-07-01

The purpose of this study was to examine the university students' perceptions on obesity and to compare the difference in mean scores factor based on demographic factors. Data was collected randomly using questionnaires. There were 321 university students participated in this study. Descriptive statistics, factor analysis, normality test, independent t test, one-way ANOVA and non-parametric tests were used in this study. Factor analysis results managed to retrieve three new factors namely impact of the health, impact of the physical appearance and personal factors. The study found that Science students have higher awareness and perceptions than Art students on Factor 1, impact of the health towards overweight problems and obesity. The findings of the study showed students, whose family background has obesity problem have higher awareness and perceptions than students' whose family background has no obesity problem on Factor 1, impact of the health towards overweight problems and obesity. The study also found that students' whose father with primary school level had the lowest awareness and perceptions on Factor 2, impact of the physical appearance towards overweight problems and obesity than other students whose father with higher academic level.

A Pilot Study of Reasons and Risk Factors for "No-Shows" in a Pediatric Neurology Clinic.

Science.gov (United States)

Guzek, Lindsay M; Fadel, William F; Golomb, Meredith R

2015-09-01

Missed clinic appointments lead to decreased patient access, worse patient outcomes, and increased healthcare costs. The goal of this pilot study was to identify reasons for and risk factors associated with missed pediatric neurology outpatient appointments ("no-shows"). This was a prospective cohort study of patients scheduled for 1 week of clinic. Data on patient clinical and demographic information were collected by record review; data on reasons for missed appointments were collected by phone interviews. Univariate and multivariate analyses were conducted using chi-square tests and multiple logistic regression to assess risk factors for missed appointments. Fifty-nine (25%) of 236 scheduled patients were no-shows. Scheduling conflicts (25.9%) and forgetting (20.4%) were the most common reasons for missed appointments. When controlling for confounding factors in the logistic regression, Medicaid (odds ratio 2.36), distance from clinic, and time since appointment was scheduled were associated with missed appointments. Further work in this area is needed. © The Author(s) 2014.

DISRUPTIVE EVENT BIOSPHERE DOSE CONVERSION FACTOR ANALYSIS

International Nuclear Information System (INIS)

M.A. Wasiolek

2005-01-01

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The Biosphere Model Report (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis'' (Figure 1-1). The objective of this analysis was to develop the BDCFs for the volcanic

Application of factor analysis to chemically analyzed data in environmental samples after x-ray fluorescence analysis

International Nuclear Information System (INIS)

El-Sayed, A.A.

2005-01-01

The underlying principle of factorial analysis is frequency distribution and description of reaction in between and through the element series in specific environmental samples. Application of this factor analysis was elaborated to interpret the variance and covariance of certain elements Si, Al, Ca. K, Fe, Ti and Mg in three different types of common materials in environmental sediments, soil, and rock. These evaluations were proceeded after x-ray fluorescence measurements. Results of applications of factorial statistical data analysis show that three factors cause relationship between the above elements in a certain type of environmental samples are mainly recognized. In such cases, these factors represent the main reason for findings and interpret all hidden relationship between the chemical analyzed data. Factor one, the effect of weathering type alteration and oxidation reaction processes as a main one in case of soil and rock where they are characterized by the close covariance of a group of metals, like iron and manganese, commonly derived from weathered and altered igneous rocks. Factor two and three represents other processes. In case of soil, formation of alumino-silicate is revealed in factor two due to the positive covariance of these elements and also the presence of aluminum oxide, titanium oxide and silicon dioxide together is explained by these positive values. The inverse relation between Ca, K, Fe and Mg while indicate the presence of mineral salts which may be due to fertilization and water of irrigation. In case of factor three in that soil, it is the weakest factor that can be used to explain the relationship between the above elements

Personality disorders in substance abusers: Validation of the DIP-Q through principal components factor analysis and canonical correlation analysis

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Hesse Morten

2005-05-01

Full Text Available Abstract Background Personality disorders are common in substance abusers. Self-report questionnaires that can aid in the assessment of personality disorders are commonly used in assessment, but are rarely validated. Methods The Danish DIP-Q as a measure of co-morbid personality disorders in substance abusers was validated through principal components factor analysis and canonical correlation analysis. A 4 components structure was constructed based on 238 protocols, representing antagonism, neuroticism, introversion and conscientiousness. The structure was compared with (a a 4-factor solution from the DIP-Q in a sample of Swedish drug and alcohol abusers (N = 133, and (b a consensus 4-components solution based on a meta-analysis of published correlation matrices of dimensional personality disorder scales. Results It was found that the 4-factor model of personality was congruent across the Danish and Swedish samples, and showed good congruence with the consensus model. A canonical correlation analysis was conducted on a subset of the Danish sample with staff ratings of pathology. Three factors that correlated highly between the two variable sets were found. These variables were highly similar to the three first factors from the principal components analysis, antagonism, neuroticism and introversion. Conclusion The findings support the validity of the DIP-Q as a measure of DSM-IV personality disorders in substance abusers.

Exploratory Factor Analysis as a Construct Validation Tool: (Mis)applications in Applied Linguistics Research

Science.gov (United States)

Karami, Hossein

2015-01-01

Factor analysis has been frequently exploited in applied research to provide evidence about the underlying factors in various measurement instruments. A close inspection of a large number of studies published in leading applied linguistic journals shows that there is a misconception among applied linguists as to the relative merits of exploratory…

Exploratory Factor Analysis With Small Samples and Missing Data.

Science.gov (United States)

McNeish, Daniel

2017-01-01

Exploratory factor analysis (EFA) is an extremely popular method for determining the underlying factor structure for a set of variables. Due to its exploratory nature, EFA is notorious for being conducted with small sample sizes, and recent reviews of psychological research have reported that between 40% and 60% of applied studies have 200 or fewer observations. Recent methodological studies have addressed small size requirements for EFA models; however, these models have only considered complete data, which are the exception rather than the rule in psychology. Furthermore, the extant literature on missing data techniques with small samples is scant, and nearly all existing studies focus on topics that are not of primary interest to EFA models. Therefore, this article presents a simulation to assess the performance of various missing data techniques for EFA models with both small samples and missing data. Results show that deletion methods do not extract the proper number of factors and estimate the factor loadings with severe bias, even when data are missing completely at random. Predictive mean matching is the best method overall when considering extracting the correct number of factors and estimating factor loadings without bias, although 2-stage estimation was a close second.

Ensemble refinement shows conformational flexibility in crystal structures of human complement factor D

International Nuclear Information System (INIS)

Forneris, Federico; Burnley, B. Tom; Gros, Piet

2014-01-01

Ensemble-refinement analysis of native and mutant factor D (FD) crystal structures indicates a dynamical transition in FD from a self-inhibited inactive conformation to a substrate-bound active conformation that is reminiscent of the allostery in thrombin. Comparison with previously observed dynamics in thrombin using NMR data supports the crystallographic ensembles. Human factor D (FD) is a self-inhibited thrombin-like serine proteinase that is critical for amplification of the complement immune response. FD is activated by its substrate through interactions outside the active site. The substrate-binding, or ‘exosite’, region displays a well defined and rigid conformation in FD. In contrast, remarkable flexibility is observed in thrombin and related proteinases, in which Na + and ligand binding is implied in allosteric regulation of enzymatic activity through protein dynamics. Here, ensemble refinement (ER) of FD and thrombin crystal structures is used to evaluate structure and dynamics simultaneously. A comparison with previously published NMR data for thrombin supports the ER analysis. The R202A FD variant has enhanced activity towards artificial peptides and simultaneously displays active and inactive conformations of the active site. ER revealed pronounced disorder in the exosite loops for this FD variant, reminiscent of thrombin in the absence of the stabilizing Na + ion. These data indicate that FD exhibits conformational dynamics like thrombin, but unlike in thrombin a mechanism has evolved in FD that locks the unbound native state into an ordered inactive conformation via the self-inhibitory loop. Thus, ensemble refinement of X-ray crystal structures may represent an approach alternative to spectroscopy to explore protein dynamics in atomic detail

Exploratory Factor Analysis of SCL90-R Symptoms Relevant to Psychosis

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Javad Amini

2011-10-01

Full Text Available "nObjective: Inconsistent results have been reported regarding the symptom dimensions relevant to psychosis in symptoms check list revised (SCL90-R, i.e., "psychoticism" and "paranoid ideation". Therefore, some studies have suggested different factor structures for questions of these two dimensions, and proposed two newly defined dimensions of "schizotypal signs" and "schizophrenia nuclear symptoms". We conducted an exploratory factor analysis on the items of these two dimensions in a general population sample in Iran. "nMethod: A total of 2158 subjects residing in Southern Tehran (capital of Iran were interviewed using the psychoticism and paranoid ideation questions in SCL90-R to assess severity of these symptom dimensions. Factor analysis was done through SAS 9.1.3 PROC FACTOR using Promax rotation (power=3 on the matrix of "polychoric correlations among variables" as the input data. "nResults: Two factors were retained by the proportion criterion. Considering loadings >= 0.5 as minimum criteria for factor loadings, 7 out of 10 questions  from psychoticism ,and 3 out of 6 questions from paranoid ideation were retained, and others were eliminated. The factor labels proposed by the questionnaire suited the extracted factors and were retained. Internal consistency for each of the dimensions was acceptable (Cronbach's alpha 0.7 and 0.74 for paranoid ideation and psychoticism respectively. Composite scores showed a half-normal distribution for both dimensions which is predictable for instruments that detect psychotic symptoms. "nConclusion: Results were in contrast with similar studies, and questioned them by suggesting a different factor structure obtained from a statistically large population. The population in a developing nation (Iran in this study and the socio-cultural differences in developed settings are the potential sources for discrepancies between this analysis and previous reports.

Non-negative factor analysis supporting the interpretation of elemental distribution images acquired by XRF

International Nuclear Information System (INIS)

Alfeld, Matthias; Falkenberg, Gerald; Wahabzada, Mirwaes; Bauckhage, Christian; Kersting, Kristian; Wellenreuther, Gerd

2014-01-01

Stacks of elemental distribution images acquired by XRF can be difficult to interpret, if they contain high degrees of redundancy and components differing in their quantitative but not qualitative elemental composition. Factor analysis, mainly in the form of Principal Component Analysis (PCA), has been used to reduce the level of redundancy and highlight correlations. PCA, however, does not yield physically meaningful representations as they often contain negative values. This limitation can be overcome, by employing factor analysis that is restricted to non-negativity. In this paper we present the first application of the Python Matrix Factorization Module (pymf) on XRF data. This is done in a case study on the painting Saul and David from the studio of Rembrandt van Rijn. We show how the discrimination between two different Co containing compounds with minimum user intervention and a priori knowledge is supported by Non-Negative Matrix Factorization (NMF).

Factor analysis for imperfect maintenance planning at nuclear power plants by cognitive task analysis

International Nuclear Information System (INIS)

Takagawa, Kenichi; Iida, Hiroyasu

2011-01-01

Imperfect maintenance planning was frequently identified in domestic nuclear power plants. To prevent such an event, we analyzed causal factors in maintenance planning stages and showed the directionality of countermeasures in this study. There is a pragmatic limit in finding the causal factors from the items based on report descriptions. Therefore, the idea of the systemic accident model, which is used to monitor the performance variability in normal circumstances, is taken as a new concept instead of investigating negative factors. As an actual method for analyzing usual activities, cognitive task analysis (CTA) was applied. Persons who experienced various maintenance activities at one electric power company were interviewed about sources related to decision making during maintenance planning, and then usual factors affecting planning were extracted as performance variability factors. The tendency of domestic events was analyzed using the classification item of those factors, and the directionality of countermeasures was shown. The following are critical for preventing imperfect maintenance planning: the persons in charge should fully understand the situation of the equipment for which they are responsible in the work planning and maintenance evaluation stages, and they should definitely understand, for example, the maintenance bases of that equipment. (author)

An empirical analysis of macroeconomic and bank-specific factors affecting liquidity of Indian banks

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Anamika Singh

2016-06-01

Full Text Available This paper investigates bank-specific and macroeconomic factors that determine the liquidity of Indian banks. To explore the association, we perform OLS, fixed effect and random effect estimates on a data set of 59 banks from 2000 to 2013. Studied bank-specific factors include bank size, profitability, cost of funding, capital adequacy and deposits. GDP, inflation and unemployment are the macroeconomic factors considered. We also perform liquidity trend analysis of Indian banks based on ownership. Findings reveal that bank ownership affects liquidity of banks. Based on panel data analysis, we suggest that bank-specific (except cost of funding and macroeconomic (except unemployment factors significantly affect bank liquidity. These include bank size, deposits, profitability, capital adequacy, GDP and inflation. Further, bank size and GDP were found to have a negative effect on bank liquidity. On the other hand, deposits, profitability, capital adequacy and inflation showed a positive effect on bank liquidity. Cost of funding and unemployment showed an insignificant effect on bank liquidity. Our paper highlights new facts for enhanced understanding of liquidity in emerging economies like India.

Sea level rise and the geoid: factor analysis approach

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Alexey Sadovski

2013-08-01

Full Text Available Sea levels are rising around the world, and this is a particular concern along most of the coasts of the United States. A 1989 EPA report shows that sea levels rose 5-6 inches more than the global average along the Mid-Atlantic and Gulf Coasts in the last century. The main reason for this is coastal land subsidence. This sea level rise is considered more as relative sea level rise than global sea level rise. Thus, instead of studying sea level rise globally, this paper describes a statistical approach by using factor analysis of regional sea level rates of change. Unlike physical models and semi-empirical models that attempt to approach how much and how fast sea levels are changing, this methodology allows for a discussion of the factor(s that statistically affects sea level rates of change, and seeks patterns to explain spatial correlations.

EXPLORATORY FACTOR ANALYSIS (EFA IN CONSUMER BEHAVIOR AND MARKETING RESEARCH

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Marcos Pascual Soler

2012-06-01

Full Text Available Exploratory Factor Analysis (EFA is one of the most widely used statistical procedures in social research. The main objective of this work is to describe the most common practices used by researchers in the consumer behavior and marketing area. Through a literature review methodology the practices of AFE in five consumer behavior and marketing journals(2000-2010 were analyzed. Then, the choices made by the researchers concerning factor model, retention criteria, rotation, factors interpretation and other relevant issues to factor analysis were analized. The results suggest that researchers routinely conduct analyses using such questionable methods. Suggestions for improving the use of factor analysis and the reporting of results are presented and a checklist (Exploratory Factor Analysis Checklist, EFAC is provided to help editors, reviewers, and authors improve reporting exploratory factor analysis.

A meta-analysis of peripheral blood nerve growth factor levels in patients with schizophrenia.

Science.gov (United States)

Qin, X-Y; Wu, H-T; Cao, C; Loh, Y P; Cheng, Y

2017-09-01

Neurotrophins particularly brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) are crucial modulators in the neurodevelopment and maintenance of central and peripheral nervous systems. Neurotrophin hypothesis of schizophrenia (SCZ) postulated that the changes in the brains of SCZ patients are the result of disturbances of developing processes involving neurotrophic factors. This hypothesis was mainly supported by the abnormal regulation of BDNF in SCZ, especially the decreased peripheral blood BDNF levels in SCZ patients validated by several meta-analyses. However, the regulation of NGF in SCZ remains unclear because of the inconsistent findings from the clinical studies. Therefore, we undertook, to the best of our knowledge, the first systematic review with a meta-analysis to quantitatively summarize the peripheral blood NGF data in SCZ patients compared with healthy control (HC) subjects. A systematic search of Pubmed, PsycINFO and Web of Science identified 13 articles encompassing a sample of 1693 individuals for the meta-analysis. Random-effects meta-analysis showed that patients with SCZ had significantly decreased peripheral blood levels of NGF when compared with the HC subjects (Hedges's g=-0.633, 95% confidence interval (CI)=-0.948 to -0.318, Pmeta-regression analyses showed that age, gender and sample size had no moderating effects on the outcome of the meta-analysis, whereas disease severity might be a confounding factor for the meta-analysis. These results demonstrated that patients with SCZ are accompanied by the decreased peripheral blood NGF levels, strengthening the clinical evidence of an abnormal neurotrophin profile in the patients with SCZ.

Physics Metacognition Inventory Part II: Confirmatory factor analysis and Rasch analysis

Science.gov (United States)

Taasoobshirazi, Gita; Bailey, MarLynn; Farley, John

2015-11-01

The Physics Metacognition Inventory was developed to measure physics students' metacognition for problem solving. In one of our earlier studies, an exploratory factor analysis provided evidence of preliminary construct validity, revealing six components of students' metacognition when solving physics problems including knowledge of cognition, planning, monitoring, evaluation, debugging, and information management. The college students' scores on the inventory were found to be reliable and related to students' physics motivation and physics grade. However, the results of the exploratory factor analysis indicated that the questionnaire could be revised to improve its construct validity. The goal of this study was to revise the questionnaire and establish its construct validity through a confirmatory factor analysis. In addition, a Rasch analysis was applied to the data to better understand the psychometric properties of the inventory and to further evaluate the construct validity. Results indicated that the final, revised inventory is a valid, reliable, and efficient tool for assessing student metacognition for physics problem solving.

Genome wide analysis of stress responsive WRKY transcription factors in Arabidopsis thaliana

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Shaiq Sultan

2016-04-01

Full Text Available WRKY transcription factors are a class of DNA-binding proteins that bind with a specific sequence C/TTGACT/C known as W-Box found in promoters of genes which are regulated by these WRKYs. From previous studies, 43 different stress responsive WRKY transcription factors in Arabidopsis thaliana, identified and then categorized in three groups viz., abiotic, biotic and both of these stresses. A comprehensive genome wide analysis including chromosomal localization, gene structure analysis, multiple sequence alignment, phylogenetic analysis and promoter analysis of these WRKY genes was carried out in this study to determine the functional homology in Arabidopsis. This analysis led to the classification of these WRKY family members into 3 major groups and subgroups and showed evolutionary relationship among these groups on the base of their functional WRKY domain, chromosomal localization and intron/exon structure. The proposed groups of these stress responsive WRKY genes and annotation based on their position on chromosomes can also be explored to determine their functional homology in other plant species in relation to different stresses. The result of the present study provides indispensable genomic information for the stress responsive WRKY transcription factors in Arabidopsis and will pave the way to explain the precise role of various AtWRKYs in plant growth and development under stressed conditions.

The recovery factors analysis of the human errors for research reactors

International Nuclear Information System (INIS)

Farcasiu, M.; Nitoi, M.; Apostol, M.; Turcu, I.; Florescu, Ghe.

2006-01-01

The results of many Probabilistic Safety Assessment (PSA) studies show a very significant contribution of human errors to systems unavailability of the nuclear installations. The treatment of human interactions is considered one of the major limitations in the context of PSA. To identify those human actions that can have an effect on system reliability or availability applying the Human Reliability Analysis (HRA) is necessary. The recovery factors analysis of the human action is an important step in HRA. This paper presents how can be reduced the human errors probabilities (HEP) using those elements that have the capacity to recovery human error. The recovery factors modeling is marked to identify error likelihood situations or situations that conduct at development of the accident. This analysis is realized by THERP method. The necessary information was obtained from the operating experience of the research reactor TRIGA of the INR Pitesti. The required data were obtained from generic databases. (authors)

Classification analysis of organization factors related to system safety

International Nuclear Information System (INIS)

Liu Huizhen; Zhang Li; Zhang Yuling; Guan Shihua

2009-01-01

This paper analyzes the different types of organization factors which influence the system safety. The organization factor can be divided into the interior organization factor and exterior organization factor. The latter includes the factors of political, economical, technical, law, social culture and geographical, and the relationships among different interest groups. The former includes organization culture, communication, decision, training, process, supervision and management and organization structure. This paper focuses on the description of the organization factors. The classification analysis of the organization factors is the early work of quantitative analysis. (authors)

Time Series Factor Analysis with an Application to Measuring Money

NARCIS (Netherlands)

Gilbert, Paul D.; Meijer, Erik

2005-01-01

Time series factor analysis (TSFA) and its associated statistical theory is developed. Unlike dynamic factor analysis (DFA), TSFA obviates the need for explicitly modeling the process dynamics of the underlying phenomena. It also differs from standard factor analysis (FA) in important respects: the

Supervised Cross-Modal Factor Analysis for Multiple Modal Data Classification

KAUST Repository

Wang, Jingbin

2015-10-09

In this paper we study the problem of learning from multiple modal data for purpose of document classification. In this problem, each document is composed two different modals of data, i.e., An image and a text. Cross-modal factor analysis (CFA) has been proposed to project the two different modals of data to a shared data space, so that the classification of a image or a text can be performed directly in this space. A disadvantage of CFA is that it has ignored the supervision information. In this paper, we improve CFA by incorporating the supervision information to represent and classify both image and text modals of documents. We project both image and text data to a shared data space by factor analysis, and then train a class label predictor in the shared space to use the class label information. The factor analysis parameter and the predictor parameter are learned jointly by solving one single objective function. With this objective function, we minimize the distance between the projections of image and text of the same document, and the classification error of the projection measured by hinge loss function. The objective function is optimized by an alternate optimization strategy in an iterative algorithm. Experiments in two different multiple modal document data sets show the advantage of the proposed algorithm over other CFA methods.

A comparison study on detection of key geochemical variables and factors through three different types of factor analysis

Science.gov (United States)

Hoseinzade, Zohre; Mokhtari, Ahmad Reza

2017-10-01

Large numbers of variables have been measured to explain different phenomena. Factor analysis has widely been used in order to reduce the dimension of datasets. Additionally, the technique has been employed to highlight underlying factors hidden in a complex system. As geochemical studies benefit from multivariate assays, application of this method is widespread in geochemistry. However, the conventional protocols in implementing factor analysis have some drawbacks in spite of their advantages. In the present study, a geochemical dataset including 804 soil samples collected from a mining area in central Iran in order to search for MVT type Pb-Zn deposits was considered to outline geochemical analysis through various fractal methods. Routine factor analysis, sequential factor analysis, and staged factor analysis were applied to the dataset after opening the data with (additive logratio) alr-transformation to extract mineralization factor in the dataset. A comparison between these methods indicated that sequential factor analysis has more clearly revealed MVT paragenesis elements in surface samples with nearly 50% variation in F1. In addition, staged factor analysis has given acceptable results while it is easy to practice. It could detect mineralization related elements while larger factor loadings are given to these elements resulting in better pronunciation of mineralization.

Factor analysis of processes of corporate culture formation at industrial enterprises of Ukraine

Directory of Open Access Journals (Sweden)

Illiashenko Sergii

2016-06-01

Full Text Available Authors have analyzed and synthesized the features of formation and development of the corporate culture at industrial enterprises of Ukraine and on this basis developed recommendations for application in the management of strategic development. During the research authors used the following general scientific methods: at research of patterns of interaction national culture, corporate culture and the culture of the individual authors used logical generalization method; for determining factors influencing corporate culture formation with the level of occurrence authors used factor analysis; for trend analysis of the corporate culture development at appropriate levels authors used comparative method. Results of the analysis showed that macro- and microfactors are external and mezofaktors (adaptability of business and corporate governance, corporate ethics, corporate social responsibility and personnel policies, corporate finance are internal for an enterprise. Authors have identified areas for each of the factors, itemized obstacles to the establishment and development of corporate culture at Ukrainian industrial enterprises and proposed recommendations for these processes management.

A new detrended semipartial cross-correlation analysis: Assessing the important meteorological factors affecting API

International Nuclear Information System (INIS)

Shen, Chen-Hua

2015-01-01

To analyze the unique contribution of meteorological factors to the air pollution index (API), a new method, the detrended semipartial cross-correlation analysis (DSPCCA), is proposed. Based on both a detrended cross-correlation analysis and a DFA-based multivariate-linear-regression (DMLR), this method is improved by including a semipartial correlation technique, which is used to indicate the unique contribution of an explanatory variable to multiple correlation coefficients. The advantages of this method in handling nonstationary time series are illustrated by numerical tests. To further demonstrate the utility of this method in environmental systems, new evidence of the primary contribution of meteorological factors to API is provided through DMLR. Results show that the most important meteorological factors affecting API are wind speed and diurnal temperature range, and the explanatory ability of meteorological factors to API gradually strengthens with increasing time scales. The results suggest that DSPCCA is a useful method for addressing environmental systems. - Highlights: • A detrended multiple linear regression is shown. • A detrended semipartial cross correlation analysis is proposed. • The important meteorological factors affecting API are assessed. • The explanatory ability of meteorological factors to API gradually strengthens with increasing time scales.

A new detrended semipartial cross-correlation analysis: Assessing the important meteorological factors affecting API

Energy Technology Data Exchange (ETDEWEB)

Shen, Chen-Hua, E-mail: shenandchen01@163.com [College of Geographical Science, Nanjing Normal University, Nanjing 210046 (China); Jiangsu Center for Collaborative Innovation in Geographical Information Resource, Nanjing 210046 (China); Key Laboratory of Virtual Geographic Environment of Ministry of Education, Nanjing 210046 (China)

2015-12-04

To analyze the unique contribution of meteorological factors to the air pollution index (API), a new method, the detrended semipartial cross-correlation analysis (DSPCCA), is proposed. Based on both a detrended cross-correlation analysis and a DFA-based multivariate-linear-regression (DMLR), this method is improved by including a semipartial correlation technique, which is used to indicate the unique contribution of an explanatory variable to multiple correlation coefficients. The advantages of this method in handling nonstationary time series are illustrated by numerical tests. To further demonstrate the utility of this method in environmental systems, new evidence of the primary contribution of meteorological factors to API is provided through DMLR. Results show that the most important meteorological factors affecting API are wind speed and diurnal temperature range, and the explanatory ability of meteorological factors to API gradually strengthens with increasing time scales. The results suggest that DSPCCA is a useful method for addressing environmental systems. - Highlights: • A detrended multiple linear regression is shown. • A detrended semipartial cross correlation analysis is proposed. • The important meteorological factors affecting API are assessed. • The explanatory ability of meteorological factors to API gradually strengthens with increasing time scales.

Using BMDP and SPSS for a Q factor analysis.

Science.gov (United States)

Tanner, B A; Koning, S M

1980-12-01

While Euclidean distances and Q factor analysis may sometimes be preferred to correlation coefficients and cluster analysis for developing a typology, commercially available software does not always facilitate their use. Commands are provided for using BMDP and SPSS in a Q factor analysis with Euclidean distances.

Exploring Technostress: Results of a Large Sample Factor Analysis

Directory of Open Access Journals (Sweden)

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.

Proteomic Analysis Shows Constitutive Secretion of MIF and p53-associated Activity of COX-2−/− Lung Fibroblasts

Directory of Open Access Journals (Sweden)

Mandar Dave

2017-12-01

Full Text Available The differential expression of two closelyassociated cyclooxygenase isozymes, COX-1 and COX-2, exhibited functions beyond eicosanoid metabolism. We hypothesized that COX-1 or COX-2 knockout lung fibroblasts may display altered protein profiles which may allow us to further differentiate the functional roles of these isozymes at the molecular level. Proteomic analysis shows constitutive production of macrophage migration inhibitory factor (MIF in lung fibroblasts derived from COX-2−/− but not wild-type (WT or COX-1−/− mice. MIF was spontaneously released in high levels into the extracellular milieu of COX2−/− fibroblasts seemingly from the preformed intracellular stores, with no change in the basal gene expression of MIF. The secretion and regulation of MIF in COX-2−/− was “prostaglandin-independent.” GO analysis showed that concurrent with upregulation of MIF, there is a significant surge in expression of genes related to fibroblast growth, FK506 binding proteins, and isomerase activity in COX-2−/− cells. Furthermore, COX-2−/− fibroblasts also exhibit a significant increase in transcriptional activity of various regulators, antagonists, and co-modulators of p53, as well as in the expression of oncogenes and related transcripts. Integrative Oncogenomics Cancer Browser (IntroGen analysis shows downregulation of COX-2 and amplification of MIF and/or p53 activity during development of glioblastomas, ependymoma, and colon adenomas. These data indicate the functional role of the MIF-COX-p53 axis in inflammation and cancer at the genomic and proteomic levels in COX-2-ablated cells. This systematic analysis not only shows the proinflammatory state but also unveils a molecular signature of a pro-oncogenic state of COX-1 in COX-2 ablated cells.

Mortality risk factors show similar trends in modern and historic populations exposed to plague.

Science.gov (United States)

Rubini, Mauro; Gualdi-Russo, Emanuela; Manzon, Vanessa S; Rinaldo, Natascia; Bianucci, Raffaella

2016-05-31

Plague has been responsible for two major historic pandemics (6th-8th century CE; 14th-19th century CE) and a modern one. The recent Malagasy plague outbreaks raised new concerns on the deadly potential of the plague-causing bacteria Yersinia pestis. Between September 2014 and April 2015, outbreaks of bubonic and pneumonic plague hit the Malagasy population. Two hundred and sixty-three cases, including 71 deaths, have been reported in 16 different districts with a case fatality rate of 27%. The scope of our study was to ascertain whether the risk factors for health in modern-day populations exposed to plague and in ancient populations that faced the two historic pandemics varied or remained substantially unaltered. The risk of mortality of the Malagasy population with those obtained from the reconstruction of three samples of European populations exposed to the historic pandemics was contrasted. The evidence shows that the risks of death are not uniform across age neither in modern nor in historic populations exposed to plague and shows precise concentrations in specific age groups (children between five and nine years of age and young adults). Although in the post-antibiotic era, the fatality rates have drastically reduced, both modern and historic populations were exposed to the same risk factors that are essentially represented by a low standard of environmental hygiene, poor nutrition, and weak health systems.

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...

Reliability Analysis and Calibration of Partial Safety Factors for Redundant Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

1998-01-01

Redundancy is important to include in the design and analysis of structural systems. In most codes of practice redundancy is not directly taken into account. In the paper various definitions of a deterministic and reliability based redundancy measure are reviewed. It is described how reundancy can...... be included in the safety system and how partial safety factors can be calibrated. An example is presented illustrating how redundancy is taken into account in the safety system in e.g. the Danish codes. The example shows how partial safety factors can be calibrated to comply with the safety level...

FACTOR ANALYSIS OF A SOCIAL SKILLS SCALE FOR HIGH SCHOOL STUDENTS.

Science.gov (United States)

Wang, H-Y; Lin, C-K

2015-10-01

The objective of this study was to develop a social skills scale for high school students in Taiwan. This study adopted stratified random sampling. A total of 1,729 high school students were included. The students ranged in age from 16 to 18 years. A Social Skills Scale was developed for this study and was designed for classroom teachers to fill out. The test-retest reliability of this scale was tested by Pearson's correlation coefficient. Exploratory factor analysis was used to determine construct validity. The Social Skills Scale had good overall test-retest reliability of .92, and the internal consistency of the five subscales was above .90. The results of the factor analysis showed that the Social Skills Scale covered the five domains of classroom learning skills, communication skills, individual initiative skills, interaction skills, and job-related social skills, and the five factors explained 68.34% of the variance. Thus, the Social Skills Scale had good reliability and validity and would be applicable to and could be promoted for use in schools.

Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors.

Science.gov (United States)

Cho, Gene Young; Moy, Linda; Kim, Sungheon G; Baete, Steven H; Moccaldi, Melanie; Babb, James S; Sodickson, Daniel K; Sigmund, Eric E

2016-08-01

To examine heterogeneous breast cancer through intravoxel incoherent motion (IVIM) histogram analysis. This HIPAA-compliant, IRB-approved retrospective study included 62 patients (age 48.44 ± 11.14 years, 50 malignant lesions and 12 benign) who underwent contrast-enhanced 3 T breast MRI and diffusion-weighted imaging. Apparent diffusion coefficient (ADC) and IVIM biomarkers of tissue diffusivity (Dt), perfusion fraction (fp), and pseudo-diffusivity (Dp) were calculated using voxel-based analysis for the whole lesion volume. Histogram analysis was performed to quantify tumour heterogeneity. Comparisons were made using Mann-Whitney tests between benign/malignant status, histological subtype, and molecular prognostic factor status while Spearman's rank correlation was used to characterize the association between imaging biomarkers and prognostic factor expression. The average values of the ADC and IVIM biomarkers, Dt and fp, showed significant differences between benign and malignant lesions. Additional significant differences were found in the histogram parameters among tumour subtypes and molecular prognostic factor status. IVIM histogram metrics, particularly fp and Dp, showed significant correlation with hormonal factor expression. Advanced diffusion imaging biomarkers show relationships with molecular prognostic factors and breast cancer malignancy. This analysis reveals novel diagnostic metrics that may explain some of the observed variability in treatment response among breast cancer patients. • Novel IVIM biomarkers characterize heterogeneous breast cancer. • Histogram analysis enables quantification of tumour heterogeneity. • IVIM biomarkers show relationships with breast cancer malignancy and molecular prognostic factors.

Factor analysis improves the selection of prescribing indicators

DEFF Research Database (Denmark)

Rasmussen, Hanne Marie Skyggedal; Søndergaard, Jens; Sokolowski, Ineta

2006-01-01

OBJECTIVE: To test a method for improving the selection of indicators of general practitioners' prescribing. METHODS: We conducted a prescription database study including all 180 general practices in the County of Funen, Denmark, approximately 472,000 inhabitants. Principal factor analysis was us...... appropriate and inappropriate prescribing, as revealed by the correlation of the indicators in the first factor. CONCLUSION: Correlation and factor analysis is a feasible method that assists the selection of indicators and gives better insight into prescribing patterns....

Human factors analysis of incident/accident report

International Nuclear Information System (INIS)

Kuroda, Isao

1992-01-01

Human factors analysis of accident/incident has different kinds of difficulties in not only technical, but also psychosocial background. This report introduces some experiments of 'Variation diagram method' which is able to extend to operational and managemental factors. (author)

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

Text mining factor analysis (TFA) in green tea patent data

Science.gov (United States)

Rahmawati, Sela; Suprijadi, Jadi; Zulhanif

2017-03-01

Factor analysis has become one of the most widely used multivariate statistical procedures in applied research endeavors across a multitude of domains. There are two main types of analyses based on factor analysis: Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Both EFA and CFA aim to observed relationships among a group of indicators with a latent variable, but they differ fundamentally, a priori and restrictions made to the factor model. This method will be applied to patent data technology sector green tea to determine the development technology of green tea in the world. Patent analysis is useful in identifying the future technological trends in a specific field of technology. Database patent are obtained from agency European Patent Organization (EPO). In this paper, CFA model will be applied to the nominal data, which obtain from the presence absence matrix. While doing processing, analysis CFA for nominal data analysis was based on Tetrachoric matrix. Meanwhile, EFA model will be applied on a title from sector technology dominant. Title will be pre-processing first using text mining analysis.

Effect of abiotic and biotic stress factors analysis using machine learning methods in zebrafish.

Science.gov (United States)

Gutha, Rajasekar; Yarrappagaari, Suresh; Thopireddy, Lavanya; Reddy, Kesireddy Sathyavelu; Saddala, Rajeswara Reddy

2018-03-01

In order to understand the mechanisms underlying stress responses, meta-analysis of transcriptome is made to identify differentially expressed genes (DEGs) and their biological, molecular and cellular mechanisms in response to stressors. The present study is aimed at identifying the effect of abiotic and biotic stress factors, and it is found that several stress responsive genes are common for both abiotic and biotic stress factors in zebrafish. The meta-analysis of micro-array studies revealed that almost 4.7% i.e., 108 common DEGs are differentially regulated between abiotic and biotic stresses. This shows that there is a global coordination and fine-tuning of gene regulation in response to these two types of challenges. We also performed dimension reduction methods, principal component analysis, and partial least squares discriminant analysis which are able to segregate abiotic and biotic stresses into separate entities. The supervised machine learning model, recursive-support vector machine, could classify abiotic and biotic stresses with 100% accuracy using a subset of DEGs. Beside these methods, the random forests decision tree model classified five out of 8 stress conditions with high accuracy. Finally, Functional enrichment analysis revealed the different gene ontology terms, transcription factors and miRNAs factors in the regulation of stress responses. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis of technological, institutional and socioeconomic factors ...

African Journals Online (AJOL)

Analysis of technological, institutional and socioeconomic factors that influences poor reading culture among secondary school students in Nigeria. ... Proliferation and availability of smart phones, chatting culture and social media were identified as technological factors influencing poor reading culture among secondary ...

Exploratory Analysis of the Factors Affecting Consumer Choice in E-Commerce: Conjoint Analysis

Directory of Open Access Journals (Sweden)

Elena Mazurova

2017-05-01

Full Text Available According to previous studies of online consumer behaviour, three factors are the most influential on purchasing behavior - brand, colour and position of the product on the screen. However, a simultaneous influence of these three factors on the consumer decision making process has not been investigated previously. In this particular work we aim to execute a comprehensive study of the influence of these three factors. In order to answer our main research questions, we conducted an experiment with 96 different combinations of the three attributes, and using statistical analysis, such as conjoint analysis, t-test analysis and Kendall analysis we identified that the most influential factor to the online consumer decision making process is brand, the second most important attribute is the colour, which was estimated half as important as brand, and the least important attribute is the position on the screen. Additionally, we identified the main differences regarding consumers stated and revealed preferences regarding these three attributes.

A factor analysis to find critical success factors in retail brand

Directory of Open Access Journals (Sweden)

Naser Azad

2013-03-01

Full Text Available The present exploratory study aims to find critical components of retail brand among some retail stores. The study seeks to build a brand name in retail level and looks to find important factors affecting it. Customer behavior is largely influenced when the first retail customer experience is formed. These factors have direct impacts on customer experience and satisfaction in retail industry. The proposed study performs an empirical investigation on two well-known retain stores located in city of Tehran, Iran. Using a sample of 265 people from regular customers, the study uses factor analysis and extracts four main factors including related brand, product benefits, customer welfare strategy and corporate profits using the existing 31 factors in the literature.

Show Horse Welfare: Horse Show Competitors' Understanding, Awareness, and Perceptions of Equine Welfare.

Science.gov (United States)

Voigt, Melissa A; Hiney, Kristina; Richardson, Jennifer C; Waite, Karen; Borron, Abigail; Brady, Colleen M

2016-01-01

The purpose of this study was to gain a better understanding of stock-type horse show competitors' understanding of welfare and level of concern for stock-type show horses' welfare. Data were collected through an online questionnaire that included questions relating to (a) interest and general understanding of horse welfare, (b) welfare concerns of the horse show industry and specifically the stock-type horse show industry, (c) decision-making influences, and (d) level of empathic characteristics. The majority of respondents indicated they agree or strongly agree that physical metrics should be a factor when assessing horse welfare, while fewer agreed that behavioral and mental metrics should be a factor. Respondent empathy levels were moderate to high and were positively correlated with the belief that mental and behavioral metrics should be a factor in assessing horse welfare. Respondents indicated the inhumane practices that most often occur at stock-type shows include excessive jerking on reins, excessive spurring, and induced excessive unnatural movement. Additionally, respondents indicated association rules, hired trainers, and hired riding instructors are the most influential regarding the decisions they make related to their horses' care and treatment.

The discriminatory analysis about factors correlative with the early hypothyroidism after 131I therapy for hyperthyroidism

International Nuclear Information System (INIS)

Xiong Lingjing; Liang Changhua; Deng Haoyu; Li Xinhui; Hu Shuo

2002-01-01

Objective: To explore the factors correlative with the early hypothyroidism after 131 I therapy for Graves' hyperthyroidism so as to cure it and decrease the early hypothyroidism occurring and prevent it from becoming irreversible hypothyroidism. Methods: Logistic regression discriminatory analysis by introducing multiple factors from group data and forward stepwise selection of 11 independent variables of 240 hyperthyroidism patients from clinical data and 1 dependent variable from follow-up data after 131 I therapy was conducted. Univariate analysis of each observed factor was performed, too. Results: (1)The results of multivariate analysis showed that the age of patients, the weight of thyroid, the suffering situation, the curve of 131 I absorption rate and the giving 131 I dosage/g thyroid tissue were correlated to early hypothyroidism. The results of univariate analysis showed that the weight of thyroid, the highest absorption of 131 I, the total treatment dosage of 131 I were correlated to early hypothyroidism. (2) The logistic regression equation was statistically significant. (3) The positive and negative predicting accuracy of the early hypothyroidism occurring was 64.08 %, 78.83 %, respectively, the overall predicting accuracy was 72.50%. Conclusions: The dosage of 131 I for treatment of hyperthyroid is the key factor according to the five correlative factors which are relating to the early hypothyroidism and the discriminatory classification. Enhanced follow-up and in time supplement of thyroid hormone are important measures for preventing the early hypothyroidism from becoming irreversible hypothyroidism

The nonenzymatic subunit of pseutarin C, a prothrombin activator from eastern brown snake (Pseudonaja textilis) venom, shows structural similarity to mammalian coagulation factor V.

Science.gov (United States)

Rao, Veena S; Swarup, Sanjay; Kini, R Manjunatha

2003-08-15

Pseutarin C is a group C prothrombin activator from the venom of the eastern brown snake Pseudonaja textilis. It is a multi-subunit protein complex consisting of catalytic and nonenzymatic subunits similar to coagulation factor Xa and factor Va, respectively. Here we describe the complete sequence of the nonenzymatic subunit. Based on the partial amino acid sequence of the nonenzymatic subunit, degenerate primers were designed. Using a "walking" strategy based on sequentially designed primers, we determined the complete cDNA sequence of the nonenzymatic subunit. The cDNA encodes a protein of 1461 amino acid residues, which includes a 30-residue signal peptide, a mature protein of 1430 amino acid residues, and a stop codon. cDNA blot analysis showed a single transcript of approximately 4.6 kb. The deduced amino acid sequence shows approximately 50% identity to mammalian factor V and by homology has a similar domain structure consisting of domains A1-A2-B-A3-C1-C2. Interestingly, the B domain of pseutarin C is shorter than that of mammalian factor V (FV). Although most of the proteolytic activation sites are conserved, 2 of 3 proteolytic sites cleaved by activated protein C are mutated, and thus activated protein C is not able to inactivate this procoagulant toxin. The predicted posttranslational modifications, including disulfide bonds, N-glycosylation, phosphorylation, and sulfation, in pseutarin C are significantly different compared with bovine factor V. Thus, our data demonstrate that the nonenzymatic subunit of group C prothrombin activators is structurally similar to mammalian FV.

Application of classification algorithms for analysis of road safety risk factor dependencies.

Science.gov (United States)

Kwon, Oh Hoon; Rhee, Wonjong; Yoon, Yoonjin

2015-02-01

Transportation continues to be an integral part of modern life, and the importance of road traffic safety cannot be overstated. Consequently, recent road traffic safety studies have focused on analysis of risk factors that impact fatality and injury level (severity) of traffic accidents. While some of the risk factors, such as drug use and drinking, are widely known to affect severity, an accurate modeling of their influences is still an open research topic. Furthermore, there are innumerable risk factors that are waiting to be discovered or analyzed. A promising approach is to investigate historical traffic accident data that have been collected in the past decades. This study inspects traffic accident reports that have been accumulated by the California Highway Patrol (CHP) since 1973 for which each accident report contains around 100 data fields. Among them, we investigate 25 fields between 2004 and 2010 that are most relevant to car accidents. Using two classification methods, the Naive Bayes classifier and the decision tree classifier, the relative importance of the data fields, i.e., risk factors, is revealed with respect to the resulting severity level. Performances of the classifiers are compared to each other and a binary logistic regression model is used as the basis for the comparisons. Some of the high-ranking risk factors are found to be strongly dependent on each other, and their incremental gains on estimating or modeling severity level are evaluated quantitatively. The analysis shows that only a handful of the risk factors in the data dominate the severity level and that dependency among the top risk factors is an imperative trait to consider for an accurate analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

What is hypomania? Tetrachoric factor analysis and kernel estimation of DSM-IV hypomanic symptoms.

Science.gov (United States)

Benazzi, Franco

2009-11-01

The DSM-IV definition of hypomania, which relies on clinical consensus and historical tradition, includes several "nonspecific" symptoms. The aim of this study was to identify the core symptoms of DSM-IV hypomania. In an outpatient private practice, 266 bipolar II disorder (BP-II) and 138 major depressive disorder (MDD) remitted patients were interviewed by a bipolar-trained psychiatrist, for different study goals. Patients were questioned, using the Structured Clinical Interview for DSM-IV, about the most common symptoms and duration of recent threshold and subthreshold hypomanic episodes. Data were recorded between 2002 and 2006. Four different samples, assessed with the same methodology, were pooled for the present analyses. Tetrachoric factor analysis was used to identify core hypomanic symptoms. Distribution of symptoms by kernel estimation was inspected for bimodality. Validity of core hypomania was tested by receiver operating characteristic (ROC) analysis. The distribution of subthreshold and threshold hypomanic episodes did not show bimodality. Tetrachoric factor analysis found 2 uncorrelated factors: factor 1 included the "classic" symptoms elevated mood, inflated self-esteem, decreased need for sleep, talkativeness, and increase in goal-directed activity (overactivity); factor 2 included the "nonspecific" symptoms irritable mood, racing/crowded thoughts, and distractibility. Factor 1 discriminatory accuracy for distinguishing BP-II versus MDD was high (ROC area = 0.94). The distribution of the 5-symptom episodes of factor 1 showed clear-cut bimodality. Similar results were found for episodes limited to 3 behavioral symptoms of factor 1 (decreased need for sleep, talkativeness, and overactivity) and 4 behavioral symptoms of factor 1 (adding elevated mood), with high discriminatory accuracy. A core, categorical DSM-IV hypomania was found that included 3 to 5 symptoms, ie, behavioral symptoms and elevated mood. Behavioral symptoms (overactivity domain

The joint return period analysis of natural disasters based on monitoring and statistical modeling of multidimensional hazard factors

Energy Technology Data Exchange (ETDEWEB)

Liu, Xueqin [State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875 (China); National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023 (China); School of Social Development and Public Policy, Beijing Normal University, Beijing 100875 (China); Li, Ning [State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875 (China); Yuan, Shuai, E-mail: syuan@nmemc.org.cn [National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023 (China); Xu, Ning; Shi, Wenqin; Chen, Weibin [National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023 (China)

2015-12-15

As a random event, a natural disaster has the complex occurrence mechanism. The comprehensive analysis of multiple hazard factors is important in disaster risk assessment. In order to improve the accuracy of risk analysis and forecasting, the formation mechanism of a disaster should be considered in the analysis and calculation of multi-factors. Based on the consideration of the importance and deficiencies of multivariate analysis of dust storm disasters, 91 severe dust storm disasters in Inner Mongolia from 1990 to 2013 were selected as study cases in the paper. Main hazard factors from 500-hPa atmospheric circulation system, near-surface meteorological system, and underlying surface conditions were selected to simulate and calculate the multidimensional joint return periods. After comparing the simulation results with actual dust storm events in 54 years, we found that the two-dimensional Frank Copula function showed the better fitting results at the lower tail of hazard factors and that three-dimensional Frank Copula function displayed the better fitting results at the middle and upper tails of hazard factors. However, for dust storm disasters with the short return period, three-dimensional joint return period simulation shows no obvious advantage. If the return period is longer than 10 years, it shows significant advantages in extreme value fitting. Therefore, we suggest the multivariate analysis method may be adopted in forecasting and risk analysis of serious disasters with the longer return period, such as earthquake and tsunami. Furthermore, the exploration of this method laid the foundation for the prediction and warning of other nature disasters. - Highlights: • A method to estimate the multidimensional joint return periods is presented. • 2D function allows better fitting results at the lower tail of hazard factors. • Three-dimensional simulation has obvious advantages in extreme value fitting. • Joint return periods are closer to the reality

The joint return period analysis of natural disasters based on monitoring and statistical modeling of multidimensional hazard factors

International Nuclear Information System (INIS)

Liu, Xueqin; Li, Ning; Yuan, Shuai; Xu, Ning; Shi, Wenqin; Chen, Weibin

2015-01-01

As a random event, a natural disaster has the complex occurrence mechanism. The comprehensive analysis of multiple hazard factors is important in disaster risk assessment. In order to improve the accuracy of risk analysis and forecasting, the formation mechanism of a disaster should be considered in the analysis and calculation of multi-factors. Based on the consideration of the importance and deficiencies of multivariate analysis of dust storm disasters, 91 severe dust storm disasters in Inner Mongolia from 1990 to 2013 were selected as study cases in the paper. Main hazard factors from 500-hPa atmospheric circulation system, near-surface meteorological system, and underlying surface conditions were selected to simulate and calculate the multidimensional joint return periods. After comparing the simulation results with actual dust storm events in 54 years, we found that the two-dimensional Frank Copula function showed the better fitting results at the lower tail of hazard factors and that three-dimensional Frank Copula function displayed the better fitting results at the middle and upper tails of hazard factors. However, for dust storm disasters with the short return period, three-dimensional joint return period simulation shows no obvious advantage. If the return period is longer than 10 years, it shows significant advantages in extreme value fitting. Therefore, we suggest the multivariate analysis method may be adopted in forecasting and risk analysis of serious disasters with the longer return period, such as earthquake and tsunami. Furthermore, the exploration of this method laid the foundation for the prediction and warning of other nature disasters. - Highlights: • A method to estimate the multidimensional joint return periods is presented. • 2D function allows better fitting results at the lower tail of hazard factors. • Three-dimensional simulation has obvious advantages in extreme value fitting. • Joint return periods are closer to the reality

Statictical Analysis Of The Conditioning Factors Of Urban Electric Consumption

International Nuclear Information System (INIS)

Segura D'Rouville, Juan Joel; Suárez Carreño, Franyelit María

2017-01-01

This research work presents the analysis of the most important factors that condition the urban residential electricity consumption. This study shows the quantitative parameters conditioning the electricity consumption. This sector of analysis has been chosen because there is disaggregated information of which are the main social and technological factors that determine its behavior, growth, with the objective of elaborating policies in the management of the electric consumption. The electrical demand considered as the sum of the powers of all the equipment that are used in each of the instants of a full day, is related to the electrical consumption, which is not but the value of the power demanded by a determined consumer Multiplied by the time in which said demand is maintained. In this report we propose the design of a probabilistic model of prediction of electricity consumption, taking into account mainly influential social and technological factors. The statistical process of this database is done through the Stat Graphics software version 4.1, for its extensive didactic in the accomplishment of calculations and associated methods. Finally, the correlation of the variables was performed to classify the determinants in a specific way and thus to determine the consumption of the dwellings. (author)

Hand function evaluation: a factor analysis study.

Science.gov (United States)

Jarus, T; Poremba, R

1993-05-01

The purpose of this study was to investigate hand function evaluations. Factor analysis with varimax rotation was used to assess the fundamental characteristics of the items included in the Jebsen Hand Function Test and the Smith Hand Function Evaluation. The study sample consisted of 144 subjects without disabilities and 22 subjects with Colles fracture. Results suggest a four factor solution: Factor I--pinch movement; Factor II--grasp; Factor III--target accuracy; and Factor IV--activities of daily living. These categories differentiated the subjects without Colles fracture from the subjects with Colles fracture. A hand function evaluation consisting of these four factors would be useful. Such an evaluation that can be used for current clinical purposes is provided.

A computational intelligent approach to multi-factor analysis of violent crime information system

Science.gov (United States)

Liu, Hongbo; Yang, Chao; Zhang, Meng; McLoone, Seán; Sun, Yeqing

2017-02-01

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

Molecular phylogenetic and expression analysis of the complete WRKY transcription factor family in maize.

Science.gov (United States)

Wei, Kai-Fa; Chen, Juan; Chen, Yan-Feng; Wu, Ling-Juan; Xie, Dao-Xin

2012-04-01

The WRKY transcription factors function in plant growth and development, and response to the biotic and abiotic stresses. Although many studies have focused on the functional identification of the WRKY transcription factors, much less is known about molecular phylogenetic and global expression analysis of the complete WRKY family in maize. In this study, we identified 136 WRKY proteins coded by 119 genes in the B73 inbred line from the complete genome and named them in an orderly manner. Then, a comprehensive phylogenetic analysis of five species was performed to explore the origin and evolutionary patterns of these WRKY genes, and the result showed that gene duplication is the major driving force for the origin of new groups and subgroups and functional divergence during evolution. Chromosomal location analysis of maize WRKY genes indicated that 20 gene clusters are distributed unevenly in the genome. Microarray-based expression analysis has revealed that 131 WRKY transcripts encoded by 116 genes may participate in the regulation of maize growth and development. Among them, 102 transcripts are stably expressed with a coefficient of variation (CV) value of WRKY genes with the CV value of >15% are further analysed to discover new organ- or tissue-specific genes. In addition, microarray analyses of transcriptional responses to drought stress and fungal infection showed that maize WRKY proteins are involved in stress responses. All these results contribute to a deep probing into the roles of WRKY transcription factors in maize growth and development and stress tolerance.

Using exploratory factor analysis in personality research: Best-practice recommendations

Directory of Open Access Journals (Sweden)

Sumaya Laher

2010-11-01

Research purpose: This article presents more objective methods to determine the number of factors, most notably parallel analysis and Velicer’s minimum average partial (MAP. The benefits of rotation are also discussed. The article argues for more consistent use of Procrustes rotation and congruence coefficients in factor analytic studies. Motivation for the study: Exploratory factor analysis is often criticised for not being rigorous and objective enough in terms of the methods used to determine the number of factors, the rotations to be used and ultimately the validity of the factor structure. Research design, approach and method: The article adopts a theoretical stance to discuss the best-practice recommendations for factor analytic research in the field of psychology. Following this, an example located within personality assessment and using the NEO-PI-R specifically is presented. A total of 425 students at the University of the Witwatersrand completed the NEO-PI-R. These responses were subjected to a principal components analysis using varimax rotation. The rotated solution was subjected to a Procrustes rotation with Costa and McCrae’s (1992 matrix as the target matrix. Congruence coefficients were also computed. Main findings: The example indicates the use of the methods recommended in the article and demonstrates an objective way of determining the number of factors. It also provides an example of Procrustes rotation with coefficients of agreement as an indication of how factor analytic results may be presented more rigorously in local research. Practical/managerial implications: It is hoped that the recommendations in this article will have best-practice implications for both researchers and practitioners in the field who employ factor analysis regularly. Contribution/value-add: This article will prove useful to all researchers employing factor analysis and has the potential to set the trend for better use of factor analysis in the South African context.

Cancer risk factors in Korean news media: a content analysis.

Science.gov (United States)

Kye, Su Yeon; Kwon, Jeong Hyun; Kim, Yong-Chan; Shim, Minsun; Kim, Jee Hyun; Cho, Hyunsoon; Jung, Kyu Won; Park, Keeho

2015-01-01

Little is known about the news coverage of cancer risk factors in Korea. This study aimed to examine how the news media encompasses a wide array of content regarding cancer risk factors and related cancer sites, and investigate whether news coverage of cancer risk factors is congruent with the actual prevalence of the disease. A content analysis was conducted on 1,138 news stories covered during a 5-year period between 2008 and 2012. The news stories were selected from nationally representative media in Korea. Information was collected about cancer risk factors and cancer sites. Of various cancer risk factors, occupational and environmental exposures appeared most frequently in the news. Breast cancer was mentioned the most in relation to cancer sites. Breast, cervical, prostate, and skin cancer were overrepresented in the media in comparison to incidence and mortality cases, whereas lung, thyroid, liver, and stomach cancer were underrepresented. To our knowledge, this research is the first investigation dealing with news coverage about cancer risk factors in Korea. The study findings show occupational and environmental exposures are emphasized more than personal lifestyle factors; further, more prevalent cancers in developed countries have greater media coverage, not reflecting the realities of the disease. The findings may help health journalists and other health storytellers to develop effective ways to communicate cancer risk factors.

[Habitat factor analysis for Torreya grandis cv. Merrillii based on spatial information technology].

Science.gov (United States)

Wang, Xiao-ming; Wang, Ke; Ao, Wei-jiu; Deng, Jin-song; Han, Ning; Zhu, Xiao-yun

2008-11-01

Torreya grandis cv. Merrillii, a tertiary survival plant, is a rare tree species of significant economic value and expands rapidly in China. Its special habitat factor analysis has the potential value to provide guide information for its planting, management, and sustainable development, because the suitable growth conditions for this tree species are special and strict. In this paper, the special habitat factors for T. grandis cv. Merrillii in its core region, i.e., in seven villages of Zhuji City, Zhejiang Province were analyzed with Principal Component Analysis (PCA) and a series of data, such as IKONOS image, Digital Elevation Model (DEM), and field survey data supported by the spatial information technology. The results showed that T. grandis cv. Merrillii exhibited high selectivity of environmental factors such as elevation, slope, and aspect. 96.22% of T. grandis cv. Merrillii trees were located at the elevation from 300 to 600 m, 97.52% of them were found to present on the areas whose slope was less than 300, and 74.43% of them distributed on sunny and half-sunny slopes. The results of PCA analysis indicated that the main environmental factors affecting the habitat of T. grandis cv. Merrillii were moisture, heat, and soil nutrients, and moisture might be one of the most important ecological factors for T. grandis cv. Merrillii due to the unique biological and ecological characteristics of the tree species.

Contextual Factors for Establishing Nursing Regulation in Iran: A Qualitative Content Analysis.

Science.gov (United States)

Nejatian, Ahmad; Joulaei, Hassan

2018-04-01

Professional regulation is one of the strategies of the governments which protect the public's right. Nursing practice is not an exception; hence, it is regulated to protect the public against nursing services' adverse effects. Although modern nursing in Iran started from 100 years ago, documents show that there was no regulation mechanism for nursing in Iran till 2016. Hence, this study was conducted to illuminate the contextual factors affecting the nursing regulation process in Iran. To explore the contextual elements of late establishment of nursing registration as an important part of nursing regulation, we applied directed qualitative content analysis. For this purpose, all the historical events and related materials including articles published in scientific journals, gray literature, statements, news articles, and interviews in the period of 2006-2016 were reviewed and analyzed by expert panel and categorized in predetermined groups. Pooled analysis data showed four contributing elements that affected the emerging nursing regulation in Iran. These elements include 1) cultural determinants, 2) structural determinants, 3) situational determinants, and 4) international or exogenous determinants. Nursing regulation is an important health policy issue in Iran which needs to be facilitated by contextual factors. These factors are complicated and country-specific. Political willingness should be accompanied by nursing association willingness to establish and improve nursing regulation. Other researches are recommended to explore actors and process and content of nursing regulation policy in Iran.

Factor Analysis for Clustered Observations.

Science.gov (United States)

Longford, N. T.; Muthen, B. O.

1992-01-01

A two-level model for factor analysis is defined, and formulas for a scoring algorithm for this model are derived. A simple noniterative method based on decomposition of total sums of the squares and cross-products is discussed and illustrated with simulated data and data from the Second International Mathematics Study. (SLD)

Analysis of factors that influencing the interest of Bali State Polytechnic’s students in entrepreneurship

Science.gov (United States)

Ayuni, N. W. D.; Sari, I. G. A. M. K. K.

2018-01-01

The high rate of unemployment results the economic growth to be hampered. To solve this situation, the government try to change the students’ mindset from becoming a job seeker to become a job creator or entrepreneur. One real action that usually been held in Bali State Polytechnic is Student Entrepreneurial Program. The purpose of this research is to identify and analyze the factors that influence the interest of Bali State Polytechnic’s Students in entrepreneurship, especially in the Entrepreneurial Student Program. Method used in this research is Factor Analysis including Bartlett Test, Kaiser-Mayer Olkin (KMO), Measure of Sampling Adequacy (MSA), factor extraction using Principal Component Analysis (PCA), factor selection using eigen value and scree plot, and factor rotation using orthogonal rotation varimax. Result shows that there are four factors that influencing the interest of Bali State Polytechnic’s Students in Entrepreneurship which are Contextual Factor (including Entrepreneurship Training, Academic Support, Perceived Confidence, and Economic Challenge), Self Efficacy Factor (including Leadership, Mental Maturity, Relation with Entrepreneur, and Authority), Subjective Norm Factor (including Support of Important Relative, Support of Friends, and Family Role), and Attitude Factor (including Self Realization).

Analysis and optimization of the TWINKLE factoring device

NARCIS (Netherlands)

Lenstra, A.K.; Shamir, A.; Preneel, B.

2000-01-01

We describe an enhanced version of the TWINKLE factoring device and analyse to what extent it can be expected to speed up the sieving step of the Quadratic Sieve and Number Field Sieve factoring al- gorithms. The bottom line of our analysis is that the TWINKLE-assisted factorization of 768-bit

Analysis of transfer reactions: determination of spectroscopic factors

Energy Technology Data Exchange (ETDEWEB)

Keeley, N. [CEA Saclay, Dept. d' Astrophysique, de Physique des Particules de Physique Nucleaire et de l' Instrumentation Associee (DSM/DAPNIA/SPhN), 91- Gif sur Yvette (France); The Andrzej So an Institute for Nuclear Studies, Dept. of Nuclear Reactions, Warsaw (Poland)

2007-07-01

An overview of the most popular models used for the analysis of direct reaction data is given, concentrating on practical aspects. The 4 following models (in order of increasing sophistication): the distorted wave born approximation (DWBA), the adiabatic model, the coupled channels born approximation, and the coupled reaction channels are briefly described. As a concrete example, the C{sup 12}(d,p)C{sup 13} reaction at an incident deuteron energy of 30 MeV is analysed with progressively more physically sophisticated models. The effect of the choice of the reaction model on the spectroscopic information extracted from the data is investigated and other sources of uncertainty in the derived spectroscopic factors are discussed. We have showed that the choice of the reaction model can significantly influence the nuclear structure information, particularly the spectroscopic factors or amplitudes but occasionally also the spin-parity, that we wish to extract from direct reaction data. We have also demonstrated that the DWBA can fail to give a satisfactory description of transfer data but when the tenets of the theory are fulfilled DWBA can work very well and will yield the same results as most sophisticated models. The use of global rather than fitted optical potentials can also lead to important differences in the extracted spectroscopic factors.

Transforming Rubrics Using Factor Analysis

Science.gov (United States)

Baryla, Ed; Shelley, Gary; Trainor, William

2012-01-01

Student learning and program effectiveness is often assessed using rubrics. While much time and effort may go into their creation, it is equally important to assess how effective and efficient the rubrics actually are in terms of measuring competencies over a number of criteria. This study demonstrates the use of common factor analysis to identify…

Strategic Decision-Making: Research Mapping from Exploratory Factor Analysis and Multidimensional Scaling

Directory of Open Access Journals (Sweden)

Ivano Ribeiro

2017-04-01

Full Text Available To understand the connection between authors, concepts and theories that address strategic decision-making, in this article the citations and co-citations of works published up to 2014 were analyzed. The sample consists of 489 articles published in international periodicals included in the Web of Science-ISI Web of Knowledge database. The search was conducted using key words that enabled the identification of the highest possible number of articles on the subject in question. Through Multidimensional Scaling (MDS and Exploratory Factor Analysis (EFA, the conceptual and theoretical relationships involved in these studies were identified. The results show that from 1980 to 2014 three different factors are highlighted: the first has to do with studies on conflict; the second factor is the Top Management Team (TMT and decision-making; and the third is related to processes. More recently (2013-2014, studies on strategic decision-making are converging towards analysis of conflict and process, composition and control, with Upper Echelon Theory being maintained as the central theory in these studies. This finding is the main contribution of this article.

Genomic analysis of codon usage shows influence of mutation pressure, natural selection, and host features on Marburg virus evolution.

Science.gov (United States)

Nasrullah, Izza; Butt, Azeem M; Tahir, Shifa; Idrees, Muhammad; Tong, Yigang

2015-08-26

The Marburg virus (MARV) has a negative-sense single-stranded RNA genome, belongs to the family Filoviridae, and is responsible for several outbreaks of highly fatal hemorrhagic fever. Codon usage patterns of viruses reflect a series of evolutionary changes that enable viruses to shape their survival rates and fitness toward the external environment and, most importantly, their hosts. To understand the evolution of MARV at the codon level, we report a comprehensive analysis of synonymous codon usage patterns in MARV genomes. Multiple codon analysis approaches and statistical methods were performed to determine overall codon usage patterns, biases in codon usage, and influence of various factors, including mutation pressure, natural selection, and its two hosts, Homo sapiens and Rousettus aegyptiacus. Nucleotide composition and relative synonymous codon usage (RSCU) analysis revealed that MARV shows mutation bias and prefers U- and A-ended codons to code amino acids. Effective number of codons analysis indicated that overall codon usage among MARV genomes is slightly biased. The Parity Rule 2 plot analysis showed that GC and AU nucleotides were not used proportionally which accounts for the presence of natural selection. Codon usage patterns of MARV were also found to be influenced by its hosts. This indicates that MARV have evolved codon usage patterns that are specific to both of its hosts. Moreover, selection pressure from R. aegyptiacus on the MARV RSCU patterns was found to be dominant compared with that from H. sapiens. Overall, mutation pressure was found to be the most important and dominant force that shapes codon usage patterns in MARV. To our knowledge, this is the first detailed codon usage analysis of MARV and extends our understanding of the mechanisms that contribute to codon usage and evolution of MARV.

A Factor Analysis of the BSRI and the PAQ.

Science.gov (United States)

Edwards, Teresa A.; And Others

Factor analysis of the Bem Sex Role Inventory (BSRI) and the Personality Attributes Questionnaire (PAQ) was undertaken to study the independence of the masculine and feminine scales within each instrument. Both instruments were administered to undergraduate education majors. Analysis of primary first and second order factors of the BSRI indicated…

Emotional Intelligence and Nurse Recruitment: Rasch and confirmatory factor analysis of the trait emotional intelligence questionnaire short form.

Science.gov (United States)

Snowden, Austyn; Watson, Roger; Stenhouse, Rosie; Hale, Claire

2015-12-01

To examine the construct validity of the Trait Emotional Intelligence Questionnaire Short form. Emotional intelligence involves the identification and regulation of our own emotions and the emotions of others. It is therefore a potentially useful construct in the investigation of recruitment and retention in nursing and many questionnaires have been constructed to measure it. Secondary analysis of existing dataset of responses to Trait Emotional Intelligence Questionnaire Short form using concurrent application of Rasch analysis and confirmatory factor analysis. First year undergraduate nursing and computing students completed Trait Emotional Intelligence Questionnaire-Short Form in September 2013. Responses were analysed by synthesising results of Rasch analysis and confirmatory factor analysis. Participants (N = 938) completed Trait Emotional Intelligence Questionnaire Short form. Rasch analysis showed the majority of the Trait Emotional Intelligence Questionnaire-Short Form items made a unique contribution to the latent trait of emotional intelligence. Five items did not fit the model and differential item functioning (gender) accounted for this misfit. Confirmatory factor analysis revealed a four-factor structure consisting of: self-confidence, empathy, uncertainty and social connection. All five misfitting items from the Rasch analysis belonged to the 'social connection' factor. The concurrent use of Rasch and factor analysis allowed for novel interpretation of Trait Emotional Intelligence Questionnaire Short form. Much of the response variation in Trait Emotional Intelligence Questionnaire Short form can be accounted for by the social connection factor. Implications for practice are discussed. © 2015 John Wiley & Sons Ltd.

Identification of noise in linear data sets by factor analysis

International Nuclear Information System (INIS)

Roscoe, B.A.; Hopke, Ph.K.

1982-01-01

A technique which has the ability to identify bad data points, after the data has been generated, is classical factor analysis. The ability of classical factor analysis to identify two different types of data errors make it ideally suited for scanning large data sets. Since the results yielded by factor analysis indicate correlations between parameters, one must know something about the nature of the data set and the analytical techniques used to obtain it to confidentially isolate errors. (author)

Analysis of Factors Affecting Inflation in Indonesia: an Islamic Perspective

Directory of Open Access Journals (Sweden)

Elis Ratna Wulan

2015-04-01

Full Text Available This study aims to determine the factors affecting inflation. The research is descriptive quantitative in nature. The data used are reported exchange rates, interest rates, money supply and inflation during 2008-2012. The research data was analyzed using multiple linear regression analysis. The results showed in the year 2008-2012 the condition of each variable are (1 the rate of inflation has a negative trend, (2 the interest rate has a negative trend, (3 the money supply has a positive trend, (4 the value of exchange rate has a positive trend. The test results by using multiple linear regression analysis result that variable interest rates, the money supply and the exchange rate of the rupiah significant effect on the rate of inflation.

"Factor Analysis Using ""R"""

Directory of Open Access Journals (Sweden)

A. Alexander Beaujean

2013-02-01

Full Text Available R (R Development Core Team, 2011 is a very powerful tool to analyze data, that is gaining in popularity due to its costs (its free and flexibility (its open-source. This article gives a general introduction to using R (i.e., loading the program, using functions, importing data. Then, using data from Canivez, Konold, Collins, and Wilson (2009, this article walks the user through how to use the program to conduct factor analysis, from both an exploratory and confirmatory approach.

Whole-tumour diffusion kurtosis MR imaging histogram analysis of rectal adenocarcinoma: Correlation with clinical pathologic prognostic factors.

Science.gov (United States)

Cui, Yanfen; Yang, Xiaotang; Du, Xiaosong; Zhuo, Zhizheng; Xin, Lei; Cheng, Xintao

2018-04-01

To investigate potential relationships between diffusion kurtosis imaging (DKI)-derived parameters using whole-tumour volume histogram analysis and clinicopathological prognostic factors in patients with rectal adenocarcinoma. 79 consecutive patients who underwent MRI examination with rectal adenocarcinoma were retrospectively evaluated. Parameters D, K and conventional ADC were measured using whole-tumour volume histogram analysis. Student's t-test or Mann-Whitney U-test, receiver operating characteristic curves and Spearman's correlation were used for statistical analysis. Almost all the percentile metrics of K were correlated positively with nodal involvement, higher histological grades, the presence of lymphangiovascular invasion (LVI) and circumferential margin (CRM) (phistogram analysis, especially K parameters, were associated with important prognostic factors of rectal cancer. • K correlated positively with some important prognostic factors of rectal cancer. • K mean showed higher AUC and specificity for differentiation of nodal involvement. • DKI metrics with whole-tumour volume histogram analysis depicted tumour heterogeneity.

The Recoverability of P-Technique Factor Analysis

Science.gov (United States)

Molenaar, Peter C. M.; Nesselroade, John R.

2009-01-01

It seems that just when we are about to lay P-technique factor analysis finally to rest as obsolete because of newer, more sophisticated multivariate time-series models using latent variables--dynamic factor models--it rears its head to inform us that an obituary may be premature. We present the results of some simulations demonstrating that even…

Human factor analysis and preventive countermeasures in nuclear power plant

International Nuclear Information System (INIS)

Li Ye

2010-01-01

Based on the human error analysis theory and the characteristics of maintenance in a nuclear power plant, human factors of maintenance in NPP are divided into three different areas: human, technology, and organization. Which is defined as individual factors, including psychological factors, physiological characteristics, health status, level of knowledge and interpersonal skills; The technical factors including technology, equipment, tools, working order, etc.; The organizational factors including management, information exchange, education, working environment, team building and leadership management,etc The analysis found that organizational factors can directly or indirectly affect the behavior of staff and technical factors, is the most basic human error factor. Based on this nuclear power plant to reduce human error and measures the response. (authors)

Retrospective Analysis of Patient Presentations at the Sydney (Australia) Royal Easter Show from 2012 to 2014.

Science.gov (United States)

Crabtree, Nathan; Mo, Shirley; Ong, Leon; Jegathees, Thuvarahan; Wei, Daniel; Fahey, David; Liu, Jia Jenny

2017-04-01

Introduction Comprehensive studies on the relationship between patient demographics and subsequent treatment and disposition at a single mass-gathering event are lacking. The Sydney Royal Easter Show (SRES; Sydney Olympic Park, New South Wales, Australia) is an annual, 14-day, agricultural mass-gathering event occurring around the Easter weekend, attracting more than 800,000 patrons per year. In this study, patient records from the SRES were analyzed to examine relationships between weather, crowd size, day of week, and demographics on treatment and disposition. This information would help to predict factors affecting patient treatment and disposition to guide ongoing training of first responders and to evaluate the appropriateness of staffing skills mix at future events. Hypothesis Patient demographics, environmental factors, and attendance would influence the nature and severity of presentations at the SRES, which would influence staffing requirements. A retrospective analysis of 4,141 patient record forms was performed for patients who presented to St John Ambulance (Australian Capital Territory, Australia) at the SRES between 2012 and 2014 inclusive. Presentation type was classified using a previously published minimum data set. Data on weather and crowd size were obtained from the Australian Bureau of Meteorology (Melbourne, Victoria, Australia) and the SRES, respectively. Statistical analyses were performed using SPSS v22 (IBM; Armonk, New York USA). Between 2012 to 2014, over 2.5 million people attended the SRES with 4,141 patients treated onsite. As expected, the majority of presentations were injuries (49%) and illnesses (46%). Although patient demographics and presentation types did not change over time, the duration of treatment increased. A higher proportion of patients were discharged to hospital or home compared to the proportion of patients discharged back to the event. Patients from rural/regional locations (accounting for 15% of all patients) were

Recruitment Methods and Show Rates to a Prostate Cancer Early Detection Program for High-Risk Men: A Comprehensive Analysis

Science.gov (United States)

Giri, Veda N.; Coups, Elliot J.; Ruth, Karen; Goplerud, Julia; Raysor, Susan; Kim, Taylor Y.; Bagden, Loretta; Mastalski, Kathleen; Zakrzewski, Debra; Leimkuhler, Suzanne; Watkins-Bruner, Deborah

2009-01-01

Purpose Men with a family history (FH) of prostate cancer (PCA) and African American (AA) men are at higher risk for PCA. Recruitment and retention of these high-risk men into early detection programs has been challenging. We report a comprehensive analysis on recruitment methods, show rates, and participant factors from the Prostate Cancer Risk Assessment Program (PRAP), which is a prospective, longitudinal PCA screening study. Materials and Methods Men 35–69 years are eligible if they have a FH of PCA, are AA, or have a BRCA1/2 mutation. Recruitment methods were analyzed with respect to participant demographics and show to the first PRAP appointment using standard statistical methods Results Out of 707 men recruited, 64.9% showed to the initial PRAP appointment. More individuals were recruited via radio than from referral or other methods (χ2 = 298.13, p < .0001). Men recruited via radio were more likely to be AA (p<0.001), less educated (p=0.003), not married or partnered (p=0.007), and have no FH of PCA (p<0.001). Men recruited via referrals had higher incomes (p=0.007). Men recruited via referral were more likely to attend their initial PRAP visit than those recruited by radio or other methods (χ2 = 27.08, p < .0001). Conclusions This comprehensive analysis finds that radio leads to higher recruitment of AA men with lower socioeconomic status. However, these are the high-risk men that have lower show rates for PCA screening. Targeted motivational measures need to be studied to improve show rates for PCA risk assessment for these high-risk men. PMID:19758657

A Second-Order Confirmatory Factor Analysis of the Moral Distress Scale-Revised for Nurses.

Science.gov (United States)

Sharif Nia, Hamid; Shafipour, Vida; Allen, Kelly-Ann; Heidari, Mohammad Reza; Yazdani-Charati, Jamshid; Zareiyan, Armin

2017-01-01

Moral distress is a growing problem for healthcare professionals that may lead to dissatisfaction, resignation, or occupational burnout if left unattended, and nurses experience different levels of this phenomenon. This study aims to investigate the factor structure of the Persian version of the Moral Distress Scale-Revised in intensive care and general nurses. This methodological research was conducted with 771 nurses from eight hospitals in the Mazandaran Province of Iran in 2017. Participants completed the Moral Distress Scale-Revised, data collected, and factor structure assessed using the construct, convergent, and divergent validity methods. The reliability of the scale was assessed using internal consistency (Cronbach's alpha, Theta, and McDonald's omega coefficients) and construct reliability. Ethical considerations: This study was approved by the Ethics Committee of Mazandaran University of Medical Sciences. The exploratory factor analysis ( N = 380) showed that the Moral Distress Scale-Revised has five factors: lack of professional competence at work, ignoring ethical issues and patient conditions, futile care, carrying out the physician's orders without question and unsafe care, and providing care under personal and organizational pressures, which explained 56.62% of the overall variance. The confirmatory factor analysis ( N = 391) supported the five-factor solution and the second-order latent factor model. The first-order model did not show a favorable convergent and divergent validity. Ultimately, the Moral Distress Scale-Revised was found to have a favorable internal consistency and construct reliability. The Moral Distress Scale-Revised was found to be a multidimensional construct. The data obtained confirmed the hypothesis of the factor structure model with a latent second-order variable. Since the convergent and divergent validity of the scale were not confirmed in this study, further assessment is necessary in future studies.

A retrospective analysis to identify the factors affecting infection in patients undergoing chemotherapy.

Science.gov (United States)

Park, Ji Hyun; Kim, Hyeon-Young; Lee, Hanna; Yun, Eun Kyoung

2015-12-01

This study compares the performance of the logistic regression and decision tree analysis methods for assessing the risk factors for infection in cancer patients undergoing chemotherapy. The subjects were 732 cancer patients who were receiving chemotherapy at K university hospital in Seoul, Korea. The data were collected between March 2011 and February 2013 and were processed for descriptive analysis, logistic regression and decision tree analysis using the IBM SPSS Statistics 19 and Modeler 15.1 programs. The most common risk factors for infection in cancer patients receiving chemotherapy were identified as alkylating agents, vinca alkaloid and underlying diabetes mellitus. The logistic regression explained 66.7% of the variation in the data in terms of sensitivity and 88.9% in terms of specificity. The decision tree analysis accounted for 55.0% of the variation in the data in terms of sensitivity and 89.0% in terms of specificity. As for the overall classification accuracy, the logistic regression explained 88.0% and the decision tree analysis explained 87.2%. The logistic regression analysis showed a higher degree of sensitivity and classification accuracy. Therefore, logistic regression analysis is concluded to be the more effective and useful method for establishing an infection prediction model for patients undergoing chemotherapy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fundamental Economic Factors That Affect Housing Prices: Comparative Analysis between Kosovo and Slovenia

Directory of Open Access Journals (Sweden)

Visar Hoxha

2014-12-01

Full Text Available The purpose of this study is to provide strategic implications for real estate appraisers and real estate managers to know the economic determinants of housing price dynamics in Kosovo. The fundamental economic determinants of housing prices, adopted from previous studies, are Gross Domestic Product growth, demographics, real interest rates, and construction costs. The research methodology used is quantitative factor analysis. The main question addressed is, whether the conventional fundamental determinants of housing prices, such as Gross Domestic Product per capita, real interest rates, demographic factors, and construction costs have driven the observed housing prices in Kosovo. By sampling the determinants of housing prices in Kosovo, the study shows their effects on housing price dynamics. The study shows that housing prices in Kosovo are significantly determined by the underlying conventional fundamentals. This is the first research that tries to determine whether the fundamental economic factors influence the housing prices in Kosovo.

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.

U.S. Civil Air Show Crashes, 1993 to 2013: Burden, Fatal Risk Factors, and Evaluation of a Risk Index for Aviation Crashes.

Science.gov (United States)

Ballard, Sarah-Blythe; Osorio, Victor B

2015-01-01

This study provides new public health data about U.S. civil air shows. Risk factors for fatalities in civil air show crashes were analyzed. The value of the FIA score in predicting fatal outcomes was evaluated. With the use of the FAA's General Aviation and Air Taxi Survey and the National Transportation Safety Board's data, the incidence of civil air show crashes from 1993 to 2013 was calculated. Fatality risk factors for crashes were analyzed by means of regression methods. The FIA index was validated to predict fatal outcomes by using the factors of fire, instrument conditions, and away-from-airport location, and was evaluated through receiver operating characteristic (ROC) curves. The civil air show crash rate was 31 crashes per 1,000 civil air events. Of the 174 civil air show crashes that occurred during the study period, 91 (52%) involved at least one fatality; on average, 1.1 people died per fatal crash. Fatalities were associated with four major risk factors: fire [adjusted odds ratio (AOR) = 7.1, 95% confidence interval (CI) = 2.4 to 20.6, P Civil air show crashes were marked by a high risk of fatal outcomes to pilots in aerobatic performances but rare mass casualties. The FIA score was not a valid measurement of fatal risk in civil air show crashes.

Integrating human factors into process hazard analysis

International Nuclear Information System (INIS)

Kariuki, S.G.; Loewe, K.

2007-01-01

A comprehensive process hazard analysis (PHA) needs to address human factors. This paper describes an approach that systematically identifies human error in process design and the human factors that influence its production and propagation. It is deductive in nature and therefore considers human error as a top event. The combinations of different factors that may lead to this top event are analysed. It is qualitative in nature and is used in combination with other PHA methods. The method has an advantage because it does not look at the operator error as the sole contributor to the human failure within a system but a combination of all underlying factors

Study on the factors affecting the quality of public bus transportation service in Bali Province using factor analysis

Science.gov (United States)

Susilawati, M.; Nilakusmawati, D. P. E.

2017-06-01

The volume of mobility flows are increasing day by day and the condition of the number of people using private transport modes contribute to traffic congestion. With the limited capacity of the road, one of the alternatives solution to reduce congestion is to optimize the use of public transport. The purposes of this study are to determine the factors that influence user’s satisfaction on the quality of public bus transportation service and determine variables that became identifier on the dominant factor affecting user’s satisfaction. The study was conducted for the public bus transportation between districts in the province of Bali, which is among the eight regencies and one municipality, using a questionnaire as a data collection instrument. Service variables determinant of user’s satisfaction in this study, described in 25 questions, which were analyzed using factor analysis. The results showed there were six factors that explain the satisfaction of users of public transport in Bali, with a total diversity of data that can be parsed by 61.436%. These factors are: Safety and comfort, Responsiveness, Capacity, Tangible, Safety, Reliability. The dominant factor affecting public transport user satisfaction is the safety and comfort, with the most influential variable is feeling concerned about the personal safety of users when on the bus.

Applications of factor analysis to electron and ion beam surface techniques

International Nuclear Information System (INIS)

Solomon, J.S.

1987-01-01

Factor analysis, a mathematical technique for extracting chemical information from matrices of data, is used to enhance Auger electron spectroscopy (AES), core level electron energy loss spectroscopy (EELS), ion scattering spectroscopy (ISS), and secondary ion mass spectroscopy (SIMS) in studies of interfaces, thin films, and surfaces. Several examples of factor analysis enhancement of chemical bonding variations in thin films and at interfaces studied with AES and SIMS are presented. Factor analysis is also shown to be of great benefit in quantifying electron and ion beam doses required to induce surface damage. Finally, examples are presented of the use of factor analysis to reconstruct elemental profiles when peaks of interest overlap each other during the course of depth profile analysis. (author)

An SPSSR -Menu for Ordinal Factor Analysis

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Mario Basto

2012-01-01

Full Text Available Exploratory factor analysis is a widely used statistical technique in the social sciences. It attempts to identify underlying factors that explain the pattern of correlations within a set of observed variables. A statistical software package is needed to perform the calculations. However, there are some limitations with popular statistical software packages, like SPSS. The R programming language is a free software package for statistical and graphical computing. It offers many packages written by contributors from all over the world and programming resources that allow it to overcome the dialog limitations of SPSS. This paper offers an SPSS dialog written in theR programming language with the help of some packages, so that researchers with little or no knowledge in programming, or those who are accustomed to making their calculations based on statistical dialogs, have more options when applying factor analysis to their data and hence can adopt a better approach when dealing with ordinal, Likert-type data.

Sequence Analysis of Hypothetical Proteins from 26695 to Identify Potential Virulence Factors

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Ahmad Abu Turab Naqvi

2016-09-01

Full Text Available Helicobacter pylori is a Gram-negative bacteria that is responsible for gastritis in human. Its spiral flagellated body helps in locomotion and colonization in the host environment. It is capable of living in the highly acidic environment of the stomach with the help of acid adaptive genes. The genome of H. pylori 26695 strain contains 1,555 coding genes that encode 1,445 proteins. Out of these, 340 proteins are characterized as hypothetical proteins (HP. This study involves extensive analysis of the HPs using an established pipeline which comprises various bioinformatics tools and databases to find out probable functions of the HPs and identification of virulence factors. After extensive analysis of all the 340 HPs, we found that 104 HPs are showing characteristic similarities with the proteins with known functions. Thus, on the basis of such similarities, we assigned probable functions to 104 HPs with high confidence and precision. All the predicted HPs contain representative members of diverse functional classes of proteins such as enzymes, transporters, binding proteins, regulatory proteins, proteins involved in cellular processes and other proteins with miscellaneous functions. Therefore, we classified 104 HPs into aforementioned functional groups. During the virulence factors analysis of the HPs, we found 11 HPs are showing significant virulence. The identification of virulence proteins with the help their predicted functions may pave the way for drug target estimation and development of effective drug to counter the activity of that protein.

In depth analysis of motivational factors at work in the health industry

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Sukhminder Jit Singh Bajwa

2010-01-01

Full Text Available Background: Motivation of health workers is necessary to generate the organizational commitment towards the patients and the hospital and therefore the knowledge about what motivates and satisfies them is very essential.The aim of the project was to investigate and analyze the various factors that help in motivation of the health workers while performing their clinical duties in the hospital. Materials and Methods: A simple random study was conducted among 100 employees of our institute, which included doctors, staff nurses and paramedical staff. One hundred employees from Gian Sagar Institute were chosen randomly for the purpose of our study. All the employees were enquired by the questionnaire method as well as by individual interviews regarding the various motivating and demotivating factors at the work place. Detailed enquiries were performed regarding the various aspects concerning the job factors and work satisfaction. All the answers and findings were observed and recorded. Results: Statistical Analysis Used: Simple non-parametric tests like mean, percentages and chi square tests were employed to analyze the data.The demographic profile of all the employees showed only minor differences which were statistically non-significant. Skills, task identity, task significance, autonomy, feedback, environment, job security and compensation were observed to be the important factors for the motivation of employees. The depth and the extent to which these factors were studied at work in the hospital showed remarkable differences. Conclusion: All the factors studied in this project are essential basis for organizational commitment, but feedback represents the factor with the highest motivation potential especially among the younger population.

Pressure and protective factors influencing nursing students' self-esteem: A content analysis study.

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Valizadeh, Leila; Zamanzadeh, Vahid; Gargari, Rahim Badri; Ghahramanian, Akram; Tabrizi, Faranak Jabbarzadeh; Keogh, Brian

2016-01-01

A review of the literature shows that the range of self-esteem in nursing students ranges from normal to low. It is hypothesized that different contextual factors could affect levels of self-esteem. The main aim of this study was to explore these factors from the viewpoint of Iranian nursing students using a qualitative approach. A qualitative content analysis study. Faculty of Nursing and Midwifery, 2014. Fourteen student nurses and two qualified nurses. This study has been applied to various depths of interpretation. Semi-structured interviews were used to collect the data. Fourteen student nurses and two qualified nurses were interviewed. Two main themes of the "pressure factors" with subthemes: low self-efficacy, sense of triviality, ineffective instructor-student interaction, low self-confidence and "protective factors" with subthemes: knowledge acquisition, mirror of valuability, professional autonomy, religious beliefs, and choosing the nursing field with interest was extracted in this study. Results showed that these themes have interaction with each other like a seesaw, as pressure factors decrease, the effect of protective factors on the self-esteem are increased. Nurse educators not only should try to improve the students' skills and knowledge, but should also try to enhance the protective factors and decrease pressure factors by enhancing the nursing students' feeling of being important, using participatory teaching methods, considering students' feedback, and attempting to improve facilities at the clinics are also recommended. Copyright © 2015. Published by Elsevier Ltd.

Confirmatory factor analysis of the Competitive State Anxiety Inventory-2.

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Lane, A M; Sewell, D F; Terry, P C; Bartram, D; Nesti, M S

1999-06-01

The aim of this study was to evaluate the factor structure of the Competitive State Anxiety Inventory-2 (CSAI-2) using confirmatory factor analysis. Volunteer participants (n = 1213) completed the CSAI-2 approximately 1 h before competition and the data were analysed in two samples. The hypothesized model showed poor fit indices in both samples independently (Robust Comparative Fit Index: sample A = 0.82, sample B = 0.84) and simultaneously (Comparative Fit Index = 0.83), suggesting that the factor structure proposed by Martens et al. is flawed. Our findings suggest that a limitation of the Cognitive Anxiety scale derives from phrasing items around the word 'concerned' rather than 'worried'. We suggest that being concerned about an impending performance does not necessarily mean that an athlete is experiencing negative thoughts, but that the athlete is acknowledging the importance and difficulty of the challenge and is attempting to mobilize resources to cope. The present results question the use of the CSAI-2 as a valid measure of competitive state anxiety.

Correlation Factor Analysis of Retinal Microvascular Changes in Patients With Essential Hypertension

Institute of Scientific and Technical Information of China (English)

Huang Duru; Huang Zhongning

2006-01-01

Objectives To investigate correlation between retinal microvascular signs and essential hypertension classification. Methods The retinal microvascular signs in patients with essential hypertension were assessed with the indirect biomicroscopy lens, the direct and the indirect ophthalmoscopes were used to determine the hypertensive retinopathy grades and retinal arteriosclerosis grades.The rank correlation analysis was used to analysis the correlation these grades with the risk factors concerned with hypertension. Results Of 72 cases with essential hypertension, 28 cases complicated with coronary disease, 20 cases diabetes, 41 cases stroke,17 cases renal malfunction. Varying extent retinal arterioscleroses were found in 71 cases, 1 case with retinal hemorrhage, 2 cases with retina edema, 4 cases with retinal hard exudation, 5 cases with retinal hemorrhage complicated by hard exudation, 2 cases with retinal hemorrhage complicated by hard exudation and cotton wool spot, 1 case with retinal hemorrhage complicated by hard exudation and microaneurysms,1 case with retinal edema and hard exudation, 1 case with retinal microaneurysms, 1 case with branch retinal vein occlusion. The rank correlation analysis showed that either hypertensive retinopathy grades or retinal arteriosclerosis grades were correlated with risk factor lamination of hypertension (r=0.25 or 0.31, P＜0.05), other correlation factors included age and blood high density lipoprotein concerned about hypertensive retinopathy grades or retinal arteriosclerosis grades, but other parameters, namely systolic or diastolic pressure, total cholesterol, triglyceride, low density lipoprotein cholesterol, fasting blood glucose,blood urea nitrogen and blood creatinine were not confirmed in this correlation analysis (P ＞ 0.05).Conclusions Either hypertensive retinopathy grade or retinal arteriosclerosis grade is close with the hypertension risk factor lamination, suggesting that the fundus examination of patients with

A replication of a factor analysis of motivations for trapping

Science.gov (United States)

Schroeder, Susan; Fulton, David C.

2015-01-01

Using a 2013 sample of Minnesota trappers, we employed confirmatory factor analysis to replicate an exploratory factor analysis of trapping motivations conducted by Daigle, Muth, Zwick, and Glass (1998).  We employed the same 25 items used by Daigle et al. and tested the same five-factor structure using a recent sample of Minnesota trappers. We also compared motivations in our sample to those reported by Daigle et el.

A human factor analysis of a radiotherapy accident

International Nuclear Information System (INIS)

Thellier, S.

2009-01-01

Since September 2005, I.R.S.N. studies activities of radiotherapy treatment from the angle of the human and organizational factors to improve the reliability of treatment in radiotherapy. Experienced in nuclear industry incidents analysis, I.R.S.N. analysed and diffused in March 2008, for the first time in France, the detailed study of a radiotherapy accident from the angle of the human and organizational factors. The method used for analysis is based on interviews and documents kept by the hospital. This analysis aimed at identifying the causes of the difference recorded between the dose prescribed by the radiotherapist and the dose effectively received by the patient. Neither verbal nor written communication (intra-service meetings and protocols of treatment) allowed information to be transmitted correctly in order to permit radiographers to adjust the irradiation zones correctly. This analysis highlighted the fact that during the preparation and the carrying out of the treatment, various factors led planned controls to not be performed. Finally, this analysis highlighted the fact that unsolved areas persist in the report over this accident. This is due to a lack of traceability of a certain number of key actions. The article concluded that there must be improvement in three areas: cooperation between the practitioners, control of the actions and traceability of the actions. (author)

Analysis of risk factors of pulmonary embolism in diabetic patients

International Nuclear Information System (INIS)

Xie Changhui; Ma Zhihai; Zhu Lin; Chi Lianxiang

2012-01-01

Objective: To study the related risk factors in diabetic patients with pulmonary embolism (PE). Methods: 58 diabetic cases underwent lower limbs 99m Tc-MAA veins imaging (and/or ultrasonography) and pulmonary perfusion imaging. The related laboratory data [fasting blood glucose (FBG), blood cholesterol, blood long chain triglycerides (LCT)] and clinic information [age, disease courses, chest symptoms (chest pain and short of breathe), lower limbs symptoms (swelling, varicose veins and diabetic foot) and acute complication (diabetic ketoacidosis and hyperosmolar non ketotic diabetic coma)] were collected simultaneously. SPSS was used for χ 2 -test and Logistic regression analysis. Results: (1) 28 patients (48.3%) were showed to be with lower limbs deep vein thrombosis (DVT) and by 99m Tc-MAA imaging, 10 cases (17.2%) with PE. The PE ratios (32.1%) of the patients with DVT was more higher than no DVT (3.3%) (χ 2 =6.53, P 2 ≥4.23, P 2 ≤2.76, P>0.05), respectively. (3) Multiplicity analysis indicated: the related risk factors for PE included chest symptoms (Score=13.316, P=0.000) and lower limbs symptoms (Score=7.780, P=0.005). No significant difference to other factors (Score≤2.494, P>0.114), respectively. Conclusion: The serious DM with chest symptoms, lower limbs symptoms and/or DVT must be controlled as early as possible by all kinds of treatment. It will decrease the PE complication. (authors)

A Sociological Analysis on the Effective factors in Tends to Hijab

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Mahmood Sharepour

2012-12-01

Full Text Available From a sociological perspective. Hjjab is formed in the context of social relations in which the framework. women's issues with cultural. social. political. Economic and religious factors. spiritual. personality and behavior that is different from the paradigms and perspectives is worthy. The purpose of this study is social factors associated with the tendency of female students to wear veil. The statistical population of female students studying at the University make up the number in 1390 was equal to 13,000. 560 of whom have a multi-stage cluster sampling method was selected to the questionnaire with reliability 0.74 responded Results of multivariable regression analysis showed that the most Important variable influencing the direction and lends 10 veil has been the attitudes 10 feminism variable. Other variables affecting status, lifestyle and location. Analytical model explained only 33% of the factors affecting be as two conflicting tendencies. as a moderate 10 strong in university student.

Factors affecting the HIV/AIDS epidemic: An ecological analysis of ...

African Journals Online (AJOL)

Factors affecting the HIV/AIDS epidemic: An ecological analysis of global data. ... Backward multiple linear regression analysis identified the proportion of Muslims, physicians density, and adolescent fertility rate are as the three most prominent factors linked with the national HIV epidemic. Conclusions: The findings support ...

Analysis of Economic Factors Affecting Stock Market

OpenAIRE

Xie, Linyin

2010-01-01

This dissertation concentrates on analysis of economic factors affecting Chinese stock market through examining relationship between stock market index and economic factors. Six economic variables are examined: industrial production, money supply 1, money supply 2, exchange rate, long-term government bond yield and real estate total value. Stock market comprises fixed interest stocks and equities shares. In this dissertation, stock market is restricted to equity market. The stock price in thi...

Deterministic factor analysis: methods of integro-differentiation of non-integral order

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Valentina V. Tarasova

2016-12-01

Full Text Available Objective to summarize the methods of deterministic factor economic analysis namely the differential calculus and the integral method. nbsp Methods mathematical methods for integrodifferentiation of nonintegral order the theory of derivatives and integrals of fractional nonintegral order. Results the basic concepts are formulated and the new methods are developed that take into account the memory and nonlocality effects in the quantitative description of the influence of individual factors on the change in the effective economic indicator. Two methods are proposed for integrodifferentiation of nonintegral order for the deterministic factor analysis of economic processes with memory and nonlocality. It is shown that the method of integrodifferentiation of nonintegral order can give more accurate results compared with standard methods method of differentiation using the first order derivatives and the integral method using the integration of the first order for a wide class of functions describing effective economic indicators. Scientific novelty the new methods of deterministic factor analysis are proposed the method of differential calculus of nonintegral order and the integral method of nonintegral order. Practical significance the basic concepts and formulas of the article can be used in scientific and analytical activity for factor analysis of economic processes. The proposed method for integrodifferentiation of nonintegral order extends the capabilities of the determined factorial economic analysis. The new quantitative method of deterministic factor analysis may become the beginning of quantitative studies of economic agents behavior with memory hereditarity and spatial nonlocality. The proposed methods of deterministic factor analysis can be used in the study of economic processes which follow the exponential law in which the indicators endogenous variables are power functions of the factors exogenous variables including the processes

Ranking insurance firms using AHP and Factor Analysis

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Mohammad Khodaei Valahzaghard

2013-03-01

Full Text Available Insurance industry includes a significant part of economy and it is important to learn more about the capabilities of different firms, which are active in this industry. In this paper, we present an empirical study to rank the insurance firms using analytical hierarchy process as well as factor analysis. The study considers four criteria including capital adequacy, quality of earning, quality of cash flow and quality of firms’ assets. The results of the implementation of factor analysis (FA have been verified using Kaiser-Meyer-Olkin (KMO=0.573 and Bartlett's Chi-Square (443.267 P-value=0.000 tests. According to the results FA, the first important factor, capital adequacy, represents 21.557% of total variance, the second factor, quality of income, represents 20.958% of total variance. In addition, the third factor, quality of cash flow, represents 19.417% of total variance and the last factor, quality of assets, represents 18.641% of total variance. The study has also used analytical hierarchy process (AHP to rank insurance firms. The results of our survey indicate that capital adequacy (0.559 is accounted as the most important factor followed by quality of income (0.235, quality of cash flow (0.144 and quality of assets (0.061. The results of AHP are consistent with the results of FA, which somewhat validates the overall study.

Analysis Of Factors Causing Delays On Harun Nafsi - Hm Rifadin Street In Samarinda East Kalimantan Maintenance Project

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Fadli

2017-12-01

Full Text Available This study aims to identify analyze and describe the factors that affect the project maintenance delay on Harun Nafsi - HM. Rifadin Street in Samarinda East Kalimantan. This research uses qualitative research method by utilizing questionnaires. The 30 participating respondents consist of 14 project implementers and 16 field implementers. The data are analyzed by descriptive statistical technique factor analysis and linear regression analysis. The results show that the factors influencing the delay of maintenance project of Harun Nafis - HM Rifadin Street include 1 time factor and workmanship factor 2 human resources and natural factors 3 geographical conditions late approval plans change and labor strikes and 4 non-optimal working levels and changes in the scope of the project during the work are still ongoing. Based on multiple linear regression analysis coefficient of determination value of 0.824 is obtained. It means that the four factors studied affect 82.4 of project delays and the rest of 27.6 is influenced by other variables out of this study. The results of this study also indicate that the dominant factor for road maintenance project delays is the fourth factor of the factors mentioned. The effort that the contractor needs to undertake is not to expand the employment contract if the project is underway or the contractor does not have the capability to complete another project.

Analysis of risk factors and risk assessment for ischemic stroke recurrence

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Xiu-ying LONG

2016-08-01

Full Text Available Objective To screen the risk factors for recurrence of ischemic stroke and to assess the risk of recurrence. Methods Essen Stroke Risk Score (ESRS was used to evaluate the risk of recurrence in 176 patients with ischemic stroke (96 cases of first onset and 80 cases of recurrence. Univariate and multivariate stepwise Logistic regression analysis was used to screen risk factors for recurrence of ischemic stroke.  Results There were significant differences between first onset group and recurrence group on age, the proportion of > 75 years old, hypertension, diabetes, coronary heart disease, peripheral angiopathy, transient ischemic attack (TIA or ischemic stroke, drinking and ESRS score (P < 0.05, for all. First onset group included one case of ESRS 0 (1.04%, 8 cases of 1 (8.33%, 39 cases of 2 (40.63%, 44 cases of 3 (45.83%, 4 cases of 4 (4.17%. Recurrence group included 2 cases of ESRS 3 (2.50%, 20 cases of 4 (25% , 37 cases of 5 (46.25% , 18 cases of 6 (22.50% , 3 cases of 7 (3.75% . There was significant difference between 2 groups (Z = -11.376, P = 0.000. Logistic regression analysis showed ESRS > 3 score was independent risk factor for recurrence of ischemic stroke (OR = 31.324, 95%CI: 3.934-249.430; P = 0.001.  Conclusions ESRS > 3 score is the independent risk factor for recurrence of ischemic stroke. It is important to strengthen risk assessment of recurrence of ischemic stroke. To screen and control risk factors is the key to secondary prevention of ischemic stroke. DOI: 10.3969/j.issn.1672-6731.2016.07.011

Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

Science.gov (United States)

Stankov, L

1979-07-01

The procedure for hierarchical factoring suggested by Schmid and Leiman (1957) is applied within the framework of image analysis and orthoblique rotational procedures. It is shown that this approach necessarily leads to correlated higher order factors. Also, one can obtain a smaller number of factors than produced by typical hierarchical procedures.

ANALYSIS OF THE FACTORS AFFECTING THE AVERAGE

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Carmen BOGHEAN

2013-12-01

Full Text Available Productivity in agriculture most relevantly and concisely expresses the economic efficiency of using the factors of production. Labour productivity is affected by a considerable number of variables (including the relationship system and interdependence between factors, which differ in each economic sector and influence it, giving rise to a series of technical, economic and organizational idiosyncrasies. The purpose of this paper is to analyse the underlying factors of the average work productivity in agriculture, forestry and fishing. The analysis will take into account the data concerning the economically active population and the gross added value in agriculture, forestry and fishing in Romania during 2008-2011. The distribution of the average work productivity per factors affecting it is conducted by means of the u-substitution method.

Factor Analysis of the Coopersmith Self-Esteem Inventory

OpenAIRE

Güloğlu, Berna; Aydın, Gül

2001-01-01

This study investigated the factor structure of the Turkish version of the Coopersmith Self-Esteem Inventory. The results showed that the inventory had a 21-factor highly complex factor structure. However of the empirically found 21 factors only 10 seemed theoretically meaningful. The results were discussed in comparison to the fndings obtained from the studies that were carried out with the original version of the Coopersmith Self-esteem Inventory.

Nursing students' views of sociocultural factors in clinical learning: a qualitative content analysis.

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Dadgaran, Ideh; Parvizy, Soroor; Peyrovi, Hamid

2013-06-01

The aim of this study is description of nursing students' views of sociocultural factors in clinical learning. A qualitative content analysis was conducted to describe nursing students' views of sociocultural factors in clinical learning. The participants consisted of 21 nursing students. Semi-structured and interactive interviews were used to collect data. All the interviews were recorded and transcribed, and then, they were analyzed using Qualitative Content Analysis and Max Qualitative Data Analysis 2010. From the transcripts, a remarkable number of primary themes, main themes, and sub-themes emerged. The main themes consisted of elements related to "society and culture", "family", "staff", and "classmates". The themes encompassed a spectrum of facilitators of and impediments to clinical learning. The findings showed that the administrators of nursing education should coordinate with faculty and staff by adopting interactive and participatory solutions, including the establishment of clinical learning teams and the transformation of hospitals into suitable sociocultural environments for education. © 2012 The Authors. Japan Journal of Nursing Science © 2012 Japan Academy of Nursing Science.

Evaluation of Parallel Analysis Methods for Determining the Number of Factors

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Crawford, Aaron V.; Green, Samuel B.; Levy, Roy; Lo, Wen-Juo; Scott, Lietta; Svetina, Dubravka; Thompson, Marilyn S.

2010-01-01

Population and sample simulation approaches were used to compare the performance of parallel analysis using principal component analysis (PA-PCA) and parallel analysis using principal axis factoring (PA-PAF) to identify the number of underlying factors. Additionally, the accuracies of the mean eigenvalue and the 95th percentile eigenvalue criteria…

The Five-Factor Model personality traits in schizophrenia: A meta-analysis.

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Ohi, Kazutaka; Shimada, Takamitsu; Nitta, Yusuke; Kihara, Hiroaki; Okubo, Hiroaki; Uehara, Takashi; Kawasaki, Yasuhiro

2016-06-30

Personality is one of important factors in the pathogenesis of schizophrenia because it affects patients' symptoms, cognition and social functioning. Several studies have reported specific personality traits in patients with schizophrenia compared with healthy subjects. However, the results were inconsistent among studies. The NEO Five-Factor Inventory (NEO-FFI) measures five personality traits: Neuroticism (N), Extraversion (E), Openness (O), Agreeableness (A) and Conscientiousness (C). Here, we performed a meta-analysis of these personality traits assessed by the NEO-FFI in 460 patients with schizophrenia and 486 healthy subjects from the published literature and investigated possible associations between schizophrenia and these traits. There was no publication bias for any traits. Because we found evidence of significant heterogeneity in all traits among the studies, we applied a random-effect model to perform the meta-analysis. Patients with schizophrenia showed a higher score for N and lower scores for E, O, A and C compared with healthy subjects. The effect sizes of these personality traits ranged from moderate to large. These differences were not affected by possible moderator factors, such as gender distribution and mean age in each study, expect for gender effect for A. These findings suggest that patients with schizophrenia have a different personality profile compared with healthy subjects. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Factors predicting early postpartum glucose intolerance in Japanese women with gestational diabetes mellitus: decision-curve analysis.

Science.gov (United States)

Kondo, M; Nagao, Y; Mahbub, M H; Tanabe, Tsuyoshi; Tanizawa, Y

2018-04-29

To identify factors predicting early postpartum glucose intolerance in Japanese women with gestational diabetes mellitus, using decision-curve analysis. A retrospective cohort study was performed. The participants were 123 Japanese women with gestational diabetes who underwent 75-g oral glucose tolerance tests at 8-12 weeks after delivery. They were divided into a glucose intolerance and a normal glucose tolerance group based on postpartum oral glucose tolerance test results. Analysis of the pregnancy oral glucose tolerance test results showed predictive factors for postpartum glucose intolerance. We also evaluated the clinical usefulness of the prediction model based on decision-curve analysis. Of 123 women, 78 (63.4%) had normoglycaemia and 45 (36.6%) had glucose intolerance. Multivariable logistic regression analysis showed insulinogenic index/fasting immunoreactive insulin and summation of glucose levels, assessed during pregnancy oral glucose tolerance tests (total glucose), to be independent risk factors for postpartum glucose intolerance. Evaluating the regression models, the best discrimination (area under the curve 0.725) was obtained using the basic model (i.e. age, family history of diabetes, BMI ≥25 kg/m 2 and use of insulin during pregnancy) plus insulinogenic index/fasting immunoreactive insulin intolerance. Insulinogenic index/fasting immunoreactive insulin calculated using oral glucose tolerance test results during pregnancy is potentially useful for predicting early postpartum glucose intolerance in Japanese women with gestational diabetes. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

An inter-battery factor analysis of the comrey personality scales and the 16 personality factor questionnaire

OpenAIRE

Gideon P. de Bruin

2000-01-01

The scores of 700 Afrikaans-speaking university students on the Comrey Personality Scales and the 16 Personality Factor Questionnaire were subjected to an inter-battery factor analysis. This technique uses only the correlations between two sets of variables and reveals only the factors that they have in common. Three of the Big Five personality factors were revealed, namely Extroversion, Neuroticism and Conscientiousness. However, the Conscientiousness factor contained a relatively strong uns...

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming

2017-05-18

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive spatio-temporal data defined over the complex networks into a finite set of regional clusters. To achieve further dimension reduction, we represent the signals in each cluster by a small number of latent factors. The correlation matrix for all nodes in the network are approximated by lower-dimensional sub-structures derived from the cluster-specific factors. To estimate regional connectivity between numerous nodes (within each cluster), we apply principal components analysis (PCA) to produce factors which are derived as the optimal reconstruction of the observed signals under the squared loss. Then, we estimate global connectivity (between clusters or sub-networks) based on the factors across regions using the RV-coefficient as the cross-dependence measure. This gives a reliable and computationally efficient multi-scale analysis of both regional and global dependencies of the large networks. The proposed novel approach is applied to estimate brain connectivity networks using functional magnetic resonance imaging (fMRI) data. Results on resting-state fMRI reveal interesting modular and hierarchical organization of human brain networks during rest.

Intrinsic Risk Factors of Lateral Ankle Sprain: A Systematic Review and Meta-analysis.

Science.gov (United States)

Kobayashi, Takumi; Tanaka, Masashi; Shida, Masahiro

2016-01-01

Lateral ankle ligamentous sprain (LAS) is one of the most common injuries in recreational activities and competitive sports. Many studies have attempted to determine whether there are certain intrinsic factors that can predict LAS. However, no consensus has been reached on the predictive intrinsic factors. To identify the intrinsic risk factors of LAS by meta-analysis from data in randomized control trials and prospective cohort studies. A systematic computerized literature search of MEDLINE, CINAHL, ScienceDirect, SPORTDiscus, and Cochrane Register of Clinical Trials was performed. A computerized literature search from inception to January 2015 resulted in 1133 studies of the LAS intrinsic risk factors written in English. Systematic review. Level 4. The modified quality index was used to assess the quality of the design of the papers and the standardized mean difference was used as an index to pool included study outcomes. Eight articles were included in this systematic review. Meta-analysis results showed that body mass index, slow eccentric inversion strength, fast concentric plantar flexion strength, passive inversion joint position sense, and peroneus brevis reaction time correlated with LAS. Body mass index, slow eccentric inversion strength, fast concentric plantar flexion strength, passive inversion joint position sense, and the reaction time of the peroneus brevis were associated with significantly increased risk of LAS.

Quantitative EDXS analysis of organic materials using the ζ-factor method

International Nuclear Information System (INIS)

Fladischer, Stefanie; Grogger, Werner

2014-01-01

In this study we successfully applied the ζ-factor method to perform quantitative X-ray analysis of organic thin films consisting of light elements. With its ability to intrinsically correct for X-ray absorption, this method significantly improved the quality of the quantification as well as the accuracy of the results compared to conventional techniques in particular regarding the quantification of light elements. We describe in detail the process of determining sensitivity factors (ζ-factors) using a single standard specimen and the involved parameter optimization for the estimation of ζ-factors for elements not contained in the standard. The ζ-factor method was then applied to perform quantitative analysis of organic semiconducting materials frequently used in organic electronics. Finally, the results were verified and discussed concerning validity and accuracy. - Highlights: • The ζ-factor method is used for quantitative EDXS analysis of light elements. • We describe the process of determining ζ-factors from a single standard in detail. • Organic semiconducting materials are successfully quantified

Assessing the Credit Risk of Corporate Bonds Based on Factor Analysis and Logistic Regress Analysis Techniques: Evidence from New Energy Enterprises in China

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Yuanxin Liu

2018-05-01

Full Text Available In recent years, new energy sources have ushered in tremendous opportunities for development. The difficulties to finance new energy enterprises (NEEs can be estimated through issuing corporate bonds. However, there are few scientific and reasonable methods to assess the credit risk of NEE bonds, which is not conducive to the healthy development of NEEs. Based on this, this paper analyzes the advantages and risks of NEEs issuing bonds and the main factors affecting the credit risk of NEE bonds, constructs a hybrid model for assessing the credit risk of NEE bonds based on factor analysis and logistic regress analysis techniques, and verifies the applicability and effectiveness of the model employing relevant data from 46 Chinese NEEs. The results show that the main factors affecting the credit risk of NEE bonds are internal factors involving the company’s profitability, solvency, operational ability, growth potential, asset structure and viability, and external factors including macroeconomic environment and energy policy support. Based on the empirical results and the exact situation of China’s NEE bonds, this article finally puts forward several targeted recommendations.

Cement Leakage in Percutaneous Vertebral Augmentation for Osteoporotic Vertebral Compression Fractures: Analysis of Risk Factors.

Science.gov (United States)

Xie, Weixing; Jin, Daxiang; Ma, Hui; Ding, Jinyong; Xu, Jixi; Zhang, Shuncong; Liang, De

2016-05-01

The risk factors for cement leakage were retrospectively reviewed in 192 patients who underwent percutaneous vertebral augmentation (PVA). To discuss the factors related to the cement leakage in PVA procedure for the treatment of osteoporotic vertebral compression fractures. PVA is widely applied for the treatment of osteoporotic vertebral fractures. Cement leakage is a major complication of this procedure. The risk factors for cement leakage were controversial. A retrospective review of 192 patients who underwent PVA was conducted. The following data were recorded: age, sex, bone density, number of fractured vertebrae before surgery, number of treated vertebrae, severity of the treated vertebrae, operative approach, volume of injected bone cement, preoperative vertebral compression ratio, preoperative local kyphosis angle, intraosseous clefts, preoperative vertebral cortical bone defect, and ratio and type of cement leakage. To study the correlation between each factor and cement leakage ratio, bivariate regression analysis was employed to perform univariate analysis, whereas multivariate linear regression analysis was employed to perform multivariate analysis. The study included 192 patients (282 treated vertebrae), and cement leakage occurred in 100 vertebrae (35.46%). The vertebrae with preoperative cortical bone defects generally exhibited higher cement leakage ratio, and the leakage is typically type C. Vertebrae with intact cortical bones before the procedure tend to experience type S leakage. Univariate analysis showed that patient age, bone density, number of fractured vertebrae before surgery, and vertebral cortical bone were associated with cement leakage ratio (Pcement leakage are bone density and vertebral cortical bone defect, with standardized partial regression coefficients of -0.085 and 0.144, respectively. High bone density and vertebral cortical bone defect are independent risk factors associated with bone cement leakage.

Prognostic factors in pediatric pulmonary arterial hypertension: A systematic review and meta-analysis.

Science.gov (United States)

Ploegstra, Mark-Jan; Zijlstra, Willemijn M H; Douwes, Johannes M; Hillege, Hans L; Berger, Rolf M F

2015-04-01

Despite the introduction of targeted therapies in pediatric pulmonary arterial hypertension (PAH), prognosis remains poor. For the definition of treatment strategies and guidelines, there is a high need for an evidence-based recapitulation of prognostic factors. The aim of this study was to identify and evaluate prognostic factors in pediatric PAH by a systematic review of the literature and to summarize the prognostic value of currently reported prognostic factors using meta-analysis. Medline, EMBASE and Cochrane Library were searched on April 1st 2014 to identify original studies that described predictors of mortality or lung-transplantation exclusively in children with PAH. 1053 citations were identified, of which 25 were included for further analysis. Hazard ratios (HR) and 95% confidence intervals were extracted from the papers. For variables studied in at least three non-overlapping cohorts, a combined HR was calculated using random-effects meta-analysis. WHO functional class (WHO-FC, HR 2.7), (N-terminal pro-) brain natriuretic peptide ([NT-pro]BNP, HR 3.2), mean right atrial pressure (mRAP, HR 1.1), cardiac index (HR 0.7), indexed pulmonary vascular resistance (PVRi, HR 1.3) and acute vasodilator response (HR 0.3) were identified as significant prognostic factors (p ≤ 0.001). This systematic review combined with separate meta-analyses shows that WHO-FC, (NT-pro)BNP, mRAP, PVRi, cardiac index and acute vasodilator response are consistently reported prognostic factors for outcome in pediatric PAH. These variables are useful clinical tools to assess prognosis and should be incorporated in treatment strategies and guidelines for children with PAH. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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.

Familial aggregation and linkage analysis with covariates for metabolic syndrome risk factors.

Science.gov (United States)

Naseri, Parisa; Khodakarim, Soheila; Guity, Kamran; Daneshpour, Maryam S

2018-06-15

Mechanisms of metabolic syndrome (MetS) causation are complex, genetic and environmental factors are important factors for the pathogenesis of MetS In this study, we aimed to evaluate familial and genetic influences on metabolic syndrome risk factor and also assess association between FTO (rs1558902 and rs7202116) and CETP(rs1864163) genes' single nucleotide polymorphisms (SNP) with low HDL_C in the Tehran Lipid and Glucose Study (TLGS). The design was a cross-sectional study of 1776 members of 227 randomly-ascertained families. Selected families contained at least one affected metabolic syndrome and at least two members of the family had suffered a loss of HDL_C according to ATP III criteria. In this study, after confirming the familial aggregation with intra-trait correlation coefficients (ICC) of Metabolic syndrome (MetS) and the quantitative lipid traits, the genetic linkage analysis of HDL_C was performed using conditional logistic method with adjusted sex and age. The results of the aggregation analysis revealed a higher correlation between siblings than between parent-offspring pairs representing the role of genetic factors in MetS. In addition, the conditional logistic model with covariates showed that the linkage results between HDL_C and three marker, rs1558902, rs7202116 and rs1864163 were significant. In summary, a high risk of MetS was found in siblings confirming the genetic influences of metabolic syndrome risk factor. Moreover, the power to detect linkage increases in the one parameter conditional logistic model regarding the use of age and sex as covariates. Copyright © 2018. Published by Elsevier B.V.

Eating Behaviour in the General Population: An Analysis of the Factor Structure of the German Version of the Three-Factor-Eating-Questionnaire (TFEQ and Its Association with the Body Mass Index.

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Antje Löffler

Full Text Available The Three-Factor-Eating-Questionnaire (TFEQ is an established instrument to assess eating behaviour. Analysis of the TFEQ-factor structure was based on selected, convenient and clinical samples so far. Aims of this study were (I to analyse the factor structure of the German version of the TFEQ and (II--based on the refined factor structure--to examine the association between eating behaviour and the body mass index (BMI in a general population sample of 3,144 middle-aged and older participants (40-79 years of the ongoing population based cohort study of the Leipzig Research Center for Civilization Diseases (LIFE Health Study. The factor structure was examined in a split-half analysis with both explorative and confirmatory factor analysis. Associations between TFEQ-scores and BMI values were tested with multiple regression analyses controlled for age, gender, and education. We found a three factor solution for the TFEQ with an 'uncontrolled eating', a 'cognitive restraint' and an 'emotional eating' domain including 29 of the original 51 TFEQ-items. Scores of the 'uncontrolled eating domain' showed the strongest correlation with BMI values (partial r = 0.26. Subjects with scores above the median in both 'uncontrolled eating' and 'emotional eating' showed the highest BMI values (mean = 29.41 kg/m², subjects with scores below the median in all three domains showed the lowest BMI values (mean = 25.68 kg/m²; F = 72.074, p<0.001. Our findings suggest that the TFEQ is suitable to identify subjects with specific patterns of eating behaviour that are associated with higher BMI values. Such information may help health care professionals to develop and implement more tailored interventions for overweight and obese individuals.

Animal and management factors influencing grower and finisher pig performance and efficiency in European systems: a meta-analysis.

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Douglas, S L; Szyszka, O; Stoddart, K; Edwards, S A; Kyriazakis, I

2015-07-01

A meta-analysis on the effects of management and animal-based factors on the performance and feed efficiency of growing pigs can provide information on single factor and interaction effects absent in individual studies. This study analysed the effects of such factors on average daily gain (ADG), feed intake (FI) and feed conversion ratio (FCR) of grower and finisher pigs. The multivariate models identified significant effects of: (1) bedding (Panimals with the least amount of floor space having a higher FI when given a feed with a low metabolisable energy (ME) content, in contrast to all other pigs, which showed a higher FI with increased ME content. The meta-analysis confirmed the significant effect of several well-known factors on the performance and efficiency of grower and finisher pigs, the effects of some less established ones and, importantly, the interactions between such factors.

Two Expectation-Maximization Algorithms for Boolean Factor Analysis

Czech Academy of Sciences Publication Activity Database

Frolov, A. A.; Húsek, Dušan; Polyakov, P.Y.

2014-01-01

Roč. 130, 23 April (2014), s. 83-97 ISSN 0925-2312 R&D Projects: GA ČR GAP202/10/0262 Grant - others:GA MŠk(CZ) ED1.1.00/02.0070; GA MŠk(CZ) EE.2.3.20.0073 Program:ED Institutional research plan: CEZ:AV0Z10300504 Keywords : Boolean Factor analysis * Binary Matrix factorization * Neural networks * Binary data model * Dimension reduction * Bars problem Subject RIV: IN - Informatics, Computer Science Impact factor: 2.083, year: 2014

Causes of liver failure and impact analysis of prognostic risk factors

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WU Xiaoqing

2013-04-01

Full Text Available ObjectiveTo perform a retrospective analysis of patients with liver failure to investigate the causative factors and related risk factors that may affect patient prognosis. MethodsThe clinical, demographic, and laboratory data of 79 consecutive patients diagnosed with liver failure and treated at our hospital between January 2010 and January 2012 (58 males and 21 females; age range: 16-74 years old were collected from the medical records. To identify risk factors of liver failure, the patient variables were assessed by Student’s t-test (continuous variables or Chi-squared test (categorical variables. Multivariate logistic regression analysis was used to investigate the relation between patient outcome and independent risk factors. ResultsThe 79 cases of liver failure were grouped according to disease severity: acute liver failure (n=6; 5 died, subacute liver failure (n=35; 19 died, and chronic liver failure (n=38; 28 died. The overall rate of death was 66%. The majority of cases (81% were related to hepatitis B virus infection. While the three groups of liver failure severity did not show significant differences in sex, mean age, occupation, presence of potassium disorder, total bilirubin (TBil or total cholesterol (CHO at admission, or lowest recorded level of CHO during hospitalization, there were significant intergroup differences in highest recorded TBil level, prothrombin activity (PTA at admission, and highest and lowest recorded PTA, and highest recorded level of CHO. Five independent risk factors were identified: the highest recorded TBil level during hospitalization, presence of infection, hepatorenal syndrome, gastrointestinal bleeding, and hepatic encephalopathy. ConclusionThe major cause of liver failure in this cohort of patients was hepatitis infection, and common biomarkers of liver function, such as TBil, CHO and PTA, may indicate patients with poor prognosis despite clinical intervention. Complications should be addressed as

Confirmatory factor analysis using Microsoft Excel.

Science.gov (United States)

Miles, Jeremy N V

2005-11-01

This article presents a method for using Microsoft (MS) Excel for confirmatory factor analysis (CFA). CFA is often seen as an impenetrable technique, and thus, when it is taught, there is frequently little explanation of the mechanisms or underlying calculations. The aim of this article is to demonstrate that this is not the case; it is relatively straightforward to produce a spreadsheet in MS Excel that can carry out simple CFA. It is possible, with few or no programming skills, to effectively program a CFA analysis and, thus, to gain insight into the workings of the procedure.

Contextual risk factors for low birth weight: a multilevel analysis.

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Gbenga A Kayode

Full Text Available Low birth weight (LBW remains to be a leading cause of neonatal death and a major contributor to infant and under-five mortality. Its prevalence has not declined in the last decade in sub-Saharan Africa (SSA and Asia. Some individual level factors have been identified as risk factors for LBW but knowledge is limited on contextual risk factors for LBW especially in SSA.Contextual risk factors for LBW in Ghana were identified by performing multivariable multilevel logistic regression analysis of 6,900 mothers dwelling in 412 communities that participated in the 2003 and 2008 Demographic and Health Surveys in Ghana.Contextual-level factors were significantly associated with LBW: Being a rural dweller increased the likelihood of having a LBW infant by 43% (OR 1.43; 95% CI 1.01-2.01; P-value <0.05 while living in poverty-concentrated communities increased the risk of having a LBW infant twofold (OR 2.16; 95% CI 1.29-3.61; P-value <0.01. In neighbourhoods with a high coverage of safe water supply the odds of having a LBW infant reduced by 28% (OR 0.74; 95% CI 0.57-0.96; P-value <0.05.This study showed contextual risk factors to have independent effects on the prevalence of LBW infants. Being a rural dweller, living in a community with a high concentration of poverty and a low coverage of safe water supply were found to increase the prevalence of LBW infants. Implementing appropriate community-based intervention programmes will likely reduce the occurrence of LBW infants.

Boolean Factor Analysis by Attractor Neural Network

Czech Academy of Sciences Publication Activity Database

Frolov, A. A.; Húsek, Dušan; Muraviev, I. P.; Polyakov, P.Y.

2007-01-01

Roč. 18, č. 3 (2007), s. 698-707 ISSN 1045-9227 R&D Projects: GA AV ČR 1ET100300419; GA ČR GA201/05/0079 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * dimensionality reduction * features clustering * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.769, year: 2007

MOOC Success Factors: Proposal of an Analysis Framework

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Margarida M. Marques

2017-10-01

Full Text Available Aim/Purpose: From an idea of lifelong-learning-for-all to a phenomenon affecting higher education, Massive Open Online Courses (MOOCs can be the next step to a truly universal education. Indeed, MOOC enrolment rates can be astoundingly high; still, their completion rates are frequently disappointingly low. Nevertheless, as courses, the participants’ enrolment and learning within the MOOCs must be considered when assessing their success. In this paper, the authors’ aim is to reflect on what makes a MOOC successful to propose an analysis framework of MOOC success factors. Background: A literature review was conducted to identify reported MOOC success factors and to propose an analysis framework. Methodology: This literature-based framework was tested against data of a specific MOOC and refined, within a qualitative interpretivist methodology. The data were collected from the ‘As alterações climáticas nos média escolares - Clima@EduMedia’ course, which was developed by the project Clima@EduMedia and was submitted to content analysis. This MOOC aimed to support science and school media teachers in the use of media to teach climate change Contribution: By proposing a MOOC success factors framework the authors are attempting to contribute to fill in a literature gap regarding what concerns criteria to consider a specific MOOC successful. Findings: This work major finding is a literature-based and empirically-refined MOOC success factors analysis framework. Recommendations for Practitioners: The proposed framework is also a set of best practices relevant to MOOC developers, particularly when targeting teachers as potential participants. Recommendation for Researchers: This work’s relevance is also based on its contribution to increasing empirical research on MOOCs. Impact on Society: By providing a proposal of a framework on factors to make a MOOC successful, the authors hope to contribute to the quality of MOOCs. Future Research: Future

Analysis of factors affecting the effect of stope leaching

International Nuclear Information System (INIS)

Xie Wangnan; Dong Chunming

2014-01-01

The industrial test and industrial trial production of stope leaching were carried out at Taoshan orefield of Dabu deposit. The results of test and trial production showed obvious differences in leaching rate and leaching time. Compared with industrial trial production of stope leaching, the leaching rate of industrial test was higher, and leaching time was shorter. It was considered that the blasting method and liquid arrangement were the main factors affecting the leaching rate and leaching time according to analysis. So we put forward the following suggestions: the technique of deep hole slicing tight-face blasting was used to reduce the yield of lump ores, the effective liquid arrangement methods were adopted to make the lixiviant infiltrating throughout whole ore heap, and bacterial leaching was introduced. (authors)

Show me the money: incorporating financial motives into the gambling motives questionnaire.

Science.gov (United States)

Dechant, Kristianne

2014-12-01

Although research has only recently begun to measure what motivates all levels of gambling involvement, motives could offer a theoretically interesting and practical way to subtype gamblers in research and for responsible gambling initiatives. The Gambling Motives Questionnaire (GMQ) is one measure that weaves together much of the gambling motives literature, but it has been criticized for neglecting financial reasons for gambling. This study uses a series of factor analyses to explore the effect of adding nine financial motives to the GMQ in a heterogeneous sample of 1,014 adult past-year gamblers. After trimming trivial financial motives, the penultimate factor analysis of the 15 GMQ items and four financial motives led to a four-factor solution, with factors tapping enhancement, social, coping and financial motives, as predicted. A final factor analysis performed on a modified GMQ-F (i.e., 16 items, including a financial subscale) revealed the same four factors, and hierarchical regression showed that the financial motives improve the GMQ-F's prediction of gambling frequency. This study provides evidence that omitting financial motives is a clear gap in the GMQ, yet suggests that the GMQ is a promising tool that can be conceptually and empirically strengthened with the simple addition of financial items.

Bad splits in bilateral sagittal split osteotomy: systematic review and meta-analysis of reported risk factors.

Science.gov (United States)

Steenen, S A; van Wijk, A J; Becking, A G

2016-08-01

An unfavourable and unanticipated pattern of the bilateral sagittal split osteotomy (BSSO) is generally referred to as a 'bad split'. Patient factors predictive of a bad split reported in the literature are controversial. Suggested risk factors are reviewed in this article. A systematic review was undertaken, yielding a total of 30 studies published between 1971 and 2015 reporting the incidence of bad split and patient age, and/or surgical technique employed, and/or the presence of third molars. These included 22 retrospective cohort studies, six prospective cohort studies, one matched-pair analysis, and one case series. Spearman's rank correlation showed a statistically significant but weak correlation between increasing average age and increasing occurrence of bad splits in 18 studies (ρ=0.229; Pbad split among the different splitting techniques. A meta-analysis pooling the effect sizes of seven cohort studies showed no significant difference in the incidence of bad split between cohorts of patients with third molars present and concomitantly removed during surgery, and patients in whom third molars were removed at least 6 months preoperatively (odds ratio 1.16, 95% confidence interval 0.73-1.85, Z=0.64, P=0.52). In summary, there is no robust evidence to date to show that any risk factor influences the incidence of bad split. Copyright © 2016 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

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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

Testing all six person-oriented principles in dynamic factor analysis.

Science.gov (United States)

Molenaar, Peter C M

2010-05-01

All six person-oriented principles identified by Sterba and Bauer's Keynote Article can be tested by means of dynamic factor analysis in its current form. In particular, it is shown how complex interactions and interindividual differences/intraindividual change can be tested in this way. In addition, the necessity to use single-subject methods in the analysis of developmental processes is emphasized, and attention is drawn to the possibility to optimally treat developmental psychopathology by means of new computational techniques that can be integrated with dynamic factor analysis.

Exploratory factor analysis and reliability analysis with missing data: A simple method for SPSS users

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Bruce Weaver

2014-09-01

Full Text Available Missing data is a frequent problem for researchers conducting exploratory factor analysis (EFA or reliability analysis. The SPSS FACTOR procedure allows users to select listwise deletion, pairwise deletion or mean substitution as a method for dealing with missing data. The shortcomings of these methods are well-known. Graham (2009 argues that a much better way to deal with missing data in this context is to use a matrix of expectation maximization (EM covariances(or correlations as input for the analysis. SPSS users who have the Missing Values Analysis add-on module can obtain vectors ofEM means and standard deviations plus EM correlation and covariance matrices via the MVA procedure. But unfortunately, MVA has no /MATRIX subcommand, and therefore cannot write the EM correlations directly to a matrix dataset of the type needed as input to the FACTOR and RELIABILITY procedures. We describe two macros that (in conjunction with an intervening MVA command carry out the data management steps needed to create two matrix datasets, one containing EM correlations and the other EM covariances. Either of those matrix datasets can then be used asinput to the FACTOR procedure, and the EM correlations can also be used as input to RELIABILITY. We provide an example that illustrates the use of the two macros to generate the matrix datasets and how to use those datasets as input to the FACTOR and RELIABILITY procedures. We hope that this simple method for handling missing data will prove useful to both students andresearchers who are conducting EFA or reliability analysis.

Likelihood-based Dynamic Factor Analysis for Measurement and Forecasting

NARCIS (Netherlands)

Jungbacker, B.M.J.P.; Koopman, S.J.

2015-01-01

We present new results for the likelihood-based analysis of the dynamic factor model. The latent factors are modelled by linear dynamic stochastic processes. The idiosyncratic disturbance series are specified as autoregressive processes with mutually correlated innovations. The new results lead to

Analysis of algae growth mechanism and water bloom prediction under the effect of multi-affecting factor.

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Wang, Li; Wang, Xiaoyi; Jin, Xuebo; Xu, Jiping; Zhang, Huiyan; Yu, Jiabin; Sun, Qian; Gao, Chong; Wang, Lingbin

2017-03-01

The formation process of algae is described inaccurately and water blooms are predicted with a low precision by current methods. In this paper, chemical mechanism of algae growth is analyzed, and a correlation analysis of chlorophyll-a and algal density is conducted by chemical measurement. Taking into account the influence of multi-factors on algae growth and water blooms, the comprehensive prediction method combined with multivariate time series and intelligent model is put forward in this paper. Firstly, through the process of photosynthesis, the main factors that affect the reproduction of the algae are analyzed. A compensation prediction method of multivariate time series analysis based on neural network and Support Vector Machine has been put forward which is combined with Kernel Principal Component Analysis to deal with dimension reduction of the influence factors of blooms. Then, Genetic Algorithm is applied to improve the generalization ability of the BP network and Least Squares Support Vector Machine. Experimental results show that this method could better compensate the prediction model of multivariate time series analysis which is an effective way to improve the description accuracy of algae growth and prediction precision of water blooms.

Structural and functional analysis of coral Hypoxia Inducible Factor.

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Didier Zoccola

Full Text Available Tissues of symbiotic Cnidarians are exposed to wide, rapid and daily variations of oxygen concentration. Indeed, during daytime, intracellular O2 concentration increases due to symbiont photosynthesis, while during night, respiration of both host cells and symbionts leads to intra-tissue hypoxia. The Hypoxia Inducible Factor 1 (HIF-1 is a heterodimeric transcription factor used for maintenance of oxygen homeostasis and adaptation to hypoxia. Here, we carried out a mechanistic study of the response to variations of O2 concentrations of the coral model Stylophora pistillata. In silico analysis showed that homologs of HIF-1 α (SpiHIF-1α and HIF-1β (SpiHIF-1β exist in coral. A specific SpiHIF-1 DNA binding on mammalian Hypoxia Response Element (HRE sequences was shown in extracts from coral exposed to dark conditions. Then, we cloned the coral HIF-1α and β genes and determined their expression and transcriptional activity. Although HIF-1α has an incomplete Oxygen-dependent Degradation Domain (ODD relative to its human homolog, its protein level is increased under hypoxia when tested in mammalian cells. Moreover, co-transfection of SpiHIF-1α and β in mammalian cells stimulated an artificial promoter containing HRE only in hypoxic conditions. This study shows the strong conservation of molecular mechanisms involved in adaptation to O2 concentration between Cnidarians and Mammals whose ancestors diverged about 1,200-1,500 million years ago.

Structural and functional analysis of coral Hypoxia Inducible Factor.

Science.gov (United States)

Zoccola, Didier; Morain, Jonas; Pagès, Gilles; Caminiti-Segonds, Natacha; Giuliano, Sandy; Tambutté, Sylvie; Allemand, Denis

2017-01-01

Tissues of symbiotic Cnidarians are exposed to wide, rapid and daily variations of oxygen concentration. Indeed, during daytime, intracellular O2 concentration increases due to symbiont photosynthesis, while during night, respiration of both host cells and symbionts leads to intra-tissue hypoxia. The Hypoxia Inducible Factor 1 (HIF-1) is a heterodimeric transcription factor used for maintenance of oxygen homeostasis and adaptation to hypoxia. Here, we carried out a mechanistic study of the response to variations of O2 concentrations of the coral model Stylophora pistillata. In silico analysis showed that homologs of HIF-1 α (SpiHIF-1α) and HIF-1β (SpiHIF-1β) exist in coral. A specific SpiHIF-1 DNA binding on mammalian Hypoxia Response Element (HRE) sequences was shown in extracts from coral exposed to dark conditions. Then, we cloned the coral HIF-1α and β genes and determined their expression and transcriptional activity. Although HIF-1α has an incomplete Oxygen-dependent Degradation Domain (ODD) relative to its human homolog, its protein level is increased under hypoxia when tested in mammalian cells. Moreover, co-transfection of SpiHIF-1α and β in mammalian cells stimulated an artificial promoter containing HRE only in hypoxic conditions. This study shows the strong conservation of molecular mechanisms involved in adaptation to O2 concentration between Cnidarians and Mammals whose ancestors diverged about 1,200-1,500 million years ago.

Training department's role in human factor analysis during post-trip reviews

International Nuclear Information System (INIS)

Goodman, D.

1987-01-01

Provide training is a frequent corrective action specified in a post-trip review report. This corrective action is most often decided upon by technical and operational staff, not training staff, without a detailed analysis of whether training can resolve the immediate problem or enhance employees' future performance. A more specific human factor or performance problem analysis would often reveal that training cannot impact or resolve the concern to avoid future occurrences. This human factor analysis is similar to Thomas Gilbert's Behavior Engineering Model (Human Competence, McGraw-Hill, 1978) or Robert Mager's/Peter Pipe's Performance Analysis (Analyzing Performance Problems, Pitman Learning, 1984). At Palo Verde Nuclear Generating Station, training analysts participate in post-trip reviews in order to conduct or provide input to this type of human factor and performance problem analysis. Their goal is to keep provide training out of corrective action statements unless training can in fact impact or resolve the problem. The analysts follow a plant specific logic diagram to identify human factors and to identify whether changes to the environment or to the person would best resolve the concern

Validation of the Malay Version of the Parental Bonding Instrument among Malaysian Youths Using Exploratory Factor Analysis.

Science.gov (United States)

Muhammad, Noor Azimah; Shamsuddin, Khadijah; Omar, Khairani; Shah, Shamsul Azhar; Mohd Amin, Rahmah

2014-01-01

Parenting behaviour is culturally sensitive. The aims of this study were (1) to translate the Parental Bonding Instrument into Malay (PBI-M) and (2) to determine its factorial structure and validity among the Malaysian population. The PBI-M was generated from a standard translation process and comprehension testing. The validation study of the PBI-M was administered to 248 college students aged 18 to 22 years. Participants in the comprehension testing had difficulty understanding negative items. Five translated double negative items were replaced with five positive items with similar meanings. Exploratory factor analysis showed a three-factor model for the PBI-M with acceptable reliability. Four negative items (items 3, 4, 8, and 16) and item 19 were omitted from the final PBI-M list because of incorrect placement or low factor loading (parenting style. Confirmatory factor analysis may further support this finding. Malaysia, parenting, questionnaire, validity.

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,…

Exploring leadership styles for innovation: an exploratory factor analysis

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Wipulanusat Warit

2017-03-01

Full Text Available Leadership plays a vital role in building the process, structures, and climate for an organisation to become innovative and to motivate team expectations toward innovations. This study explores the leadership styles that engineers regard as significant for innovation in the public sector. Exploratory factor analysis (EFA was conducted to identify the principal leadership styles influencing innovation in the Australian Public Service (APS, using survey data extracted from the 2014 APS employee census comprising 3 125 engineering professionals in Commonwealth of Australia departments. EFA returned a two-factor structure explaining 77.6% of the variance of the leadership for innovation construct. In this study, the results from the EFA provided a clear estimation of the factor structure of the measures for leadership for innovation. From the results, the two factors extracted were transformational leadership and consideration leadership. In transformational leadership, a leader values organisational objectives, inspires subordinates to perform, and motivates followers beyond expected levels of work standards. Consideration leadership refers to the degree to which a leader shows concern and expressions of support for subordinates, takes care of their welfare, treats members as equals, and displays warmth and approachability. These findings highlight the role of leadership as the most critical predictor when considering the degree to which subordinates strive for creativity and innovation. Both transformational and consideration leadership styles are recommended to be incorporated into management training and development programs. This study also recommends that Commonwealth departments recruit supervisors who have both of these leadership styles before implementing innovative projects.

Confirmatory factor analysis applied to the Force Concept Inventory

Science.gov (United States)

Eaton, Philip; Willoughby, Shannon D.

2018-06-01

In 1995, Huffman and Heller used exploratory factor analysis to draw into question the factors of the Force Concept Inventory (FCI). Since then several papers have been published examining the factors of the FCI on larger sets of student responses and understandable factors were extracted as a result. However, none of these proposed factor models have been verified to not be unique to their original sample through the use of independent sets of data. This paper seeks to confirm the factor models proposed by Scott et al. in 2012, and Hestenes et al. in 1992, as well as another expert model proposed within this study through the use of confirmatory factor analysis (CFA) and a sample of 20 822 postinstruction student responses to the FCI. Upon application of CFA using the full sample, all three models were found to fit the data with acceptable global fit statistics. However, when CFA was performed using these models on smaller sample sizes the models proposed by Scott et al. and Eaton and Willoughby were found to be far more stable than the model proposed by Hestenes et al. The goodness of fit of these models to the data suggests that the FCI can be scored on factors that are not unique to a single class. These scores could then be used to comment on how instruction methods effect the performance of students along a single factor and more in-depth analyses of curriculum changes may be possible as a result.

Does the Factor Structure of Military Sexual Stressors in Men Correspond to Women's? A Confirmatory Factor Analysis Using the Sexual Harassment Inventory.

Science.gov (United States)

Reddy, Madhavi K; Murdoch, Maureen

2016-02-01

Unwanted sexual stressors experienced by military men and women are associated with a host of negative physical and mental health problems. Government officials are making it a priority to put a stop to these unwanted sexual experiences. However, the measure typically used measures sexual stressors much better for women than for men. The purpose of the present study was to test the factor structure of an alternative measure, the Sexual Harassment Inventory (SHI), to examine whether sexual stressors experienced by men correspond to women's experiences. We used three preexisting datasets in which the SHI was used to assess active and former military members' sexual stressor experiences. We conducted an exploratory factor analysis to identify women's response patterns and a confirmatory factor analysis to determine whether men's response patterns corresponded to women's. Findings showed that the SHI has evidence of factorial validity in female service members and adequate, but not exceptional, factorial fit for male service members. It is imperative that more work be done to better understand how men experience and perceive potential military sexual stressors and how those perceptions and experiences compare to women's. Reprint & Copyright © 2016 Association of Military Surgeons of the U.S.

The combined use of dynamic factor analysis and wavelet analysis to evaluate latent factors controlling complex groundwater level fluctuations in a riverside alluvial aquifer

Science.gov (United States)

Oh, Yun-Yeong; Yun, Seong-Taek; Yu, Soonyoung; Hamm, Se-Yeong

2017-12-01

To identify and quantitatively evaluate complex latent factors controlling groundwater level (GWL) fluctuations in a riverside alluvial aquifer influenced by barrage construction, we developed the combined use of dynamic factor analysis (DFA) and wavelet analysis (WA). Time series data of GWL, river water level and precipitation were collected for 3 years (July 2012 to June 2015) from an alluvial aquifer underneath an agricultural area of the Nakdong river basin, South Korea. Based on the wavelet coefficients of the final approximation, the GWL data was clustered into three groups (WCG1 to WCG3). Two dynamic factors (DFs) were then extracted using DFA for each group; thus, six major factors were extracted. Next, the time-frequency variability of the extracted DFs was examined using multiresolution cross-correlation analysis (MRCCA) with the following steps: 1) major driving forces and their scales in GWL fluctuations were identified by comparing maximum correlation coefficients (rmax) between DFs and the GWL time series and 2) the results were supplemented using the wavelet transformed coherence (WTC) analysis between DFs and the hydrological time series. Finally, relative contributions of six major DFs to the GWL fluctuations could be quantitatively assessed by calculating the effective dynamic efficiency (Def). The characteristics and relevant process of the identified six DFs are: 1) WCG1DF4,1 as an indicative of seasonal agricultural pumping (scales = 64-128 days; rmax = 0.68-0.89; Def ≤ 23.1%); 2) WCG1DF4,4 representing the cycle of regional groundwater recharge (scales = 64-128 days; rmax = 0.98-1.00; Def ≤ 11.1%); 3) WCG2DF4,1 indicating the complex interaction between the episodes of precipitation and direct runoff (scales = 2-8 days; rmax = 0.82-0.91; Def ≤ 35.3%) and seasonal GW-RW interaction (scales = 64-128 days; rmax = 0.76-0.91; Def ≤ 14.2%); 4) WCG2DF4,4 reflecting the complex effects of seasonal pervasive pumping and the local recharge

Seizure Self-Efficacy Scale for Children with Epilepsy: Confirmatory and Exploratory Factor Analysis

Directory of Open Access Journals (Sweden)

Şerife Tutar Güven

2017-12-01

Full Text Available Aim: In the past few years, the concept of self-efficacy in children with epilepsy has become increasingly important. This study aimed to analyze the psychometric aspects of the Turkish version of the Seizure Self-Efficacy Scale for Children. Materials and Methods: This is a cross-sectional survey. The study data were collected using the Seizure Self-Efficacy Scale for Children and Child Introduction Form. The study sample included 166 children who were between 9 and 17 years of age. The authors assessed the reliability and construct validity of the study data using exploratory and confirmatory factor analyses (CFA. Results: The original model was not confirmed by the CFA. The analysis tool included 15 items in two factors. Reliability analysis showed that the two factors were acceptable and valid. The tool was valid and reliable for measuring the self-efficacy of epileptic children. The factor structure was derived from and confirmed by the original tool. It was found that the Turkish version of the modified Seizure Self-Efficacy Scale for Children had excellent satisfactory psychometric aspects for a Turkish population. Conclusion: Health professionals can present a more effective drug process and nursing care by identifying and assessing seizure self-efficacy levels in children with epilepsy, and they can make a positive contribution to disease management and the way the child deals with the disease.

An analysis of predictive factors for concurrent acute-on-chronic liver failure and hepatorenal syndrome

Directory of Open Access Journals (Sweden)

CHEN Yanfang

2015-09-01

Full Text Available ObjectiveTo learn the clinical characteristics of concurrent acute-on-chronic liver failure (ACLF and hepatorenal syndrome (HRS, and to investigate the predictive factors for HRS in patients with ACLF. MethodsA total of 806 patients with ACLF who were admitted to our hospital from January 2012 to May 2014 were selected and divided into two groups according to the incidence of concurrent HRS. Clinical indices and laboratory test results were analyzed in the two groups, and the multivariate logistic regression analysis was used to figure out independent indices for the prediction of HRS in patients with ACLF. A prediction model was established and the receiver operating characteristic curve was drawn to evaluate the accuracy of the prediction model. Comparison of continuous data between the two groups was made by t test, and comparison of categorical data between the two groups was made by χ2 test. ResultsIn all patients with ACLF, 229 had HRS and 577 had no HRS. The univariate logistic regression analysis showed that hepatic encephalopathy, peritonitis, infection, age, cystatin C (Cys-C, serum creatinine (SCr, blood urea nitrogen, albumin, prealbumin, total bilirubin, direct bilirubin, total cholesterol, K+, Na+, phosphorus, Ca2+, prothrombin time, prothrombin activity, international normalized ratio, and hematocrit were significant predictive factors for HRS. The multivariate logistic regression analysis showed that concurrent peritonitis, Cys-C, SCr, and HCO3- were independent predictive factors for HRS in patients with ACLF (OR=3.155, P＜0.01; OR=30.773, P＜0.01; OR=1062, P＜0.01; OR=0.915, P＜0.05. The model was proved of great value in prediction. ConclusionConcurrent peritonitis, Cys-C, SCr, and HCO3- are effective predictive factors for HRS in patients with ACLF.

Prevalence, risk factors and spatial analysis of liver fluke infections in Danish cattle herds

DEFF Research Database (Denmark)

Olsen, Abbey; Frankena, Klaas; Bødker, Rene

2015-01-01

fitted the observed spatial pattern. Results: During the investigated period (2011-2013), an increase in annual herd prevalence was noted (2011-25.6%; 2012-28.4%; 2013-29.3%). The spatial analysis suggested significant clustering of positive and negative herds. Presence of streams, wetlands and pastures...... on farms showed a significant association with the presence of infection in cattle herds. Buying animals from positive herds was a risk factor on conventional farms. Additionally, risk of being infected with Fasciola hepatica was higher in non-dairy herds of medium size (>= 30 and ... to dairy and large (>= 100) cattle herds. The observed spatial pattern could be reproduced by predictions of the risk factor model. Conclusions: This study showed an increase in annual herd level prevalence (2011 to 2013) indicating that an increasing proportion of herds are infected with Fasciola hepatica...

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.

Environmental factor analysis of cholera in China using remote sensing and geographical information systems.

Science.gov (United States)

Xu, M; Cao, C X; Wang, D C; Kan, B; Xu, Y F; Ni, X L; Zhu, Z C

2016-04-01

Cholera is one of a number of infectious diseases that appears to be influenced by climate, geography and other natural environments. This study analysed the environmental factors of the spatial distribution of cholera in China. It shows that temperature, precipitation, elevation, and distance to the coastline have significant impact on the distribution of cholera. It also reveals the oceanic environmental factors associated with cholera in Zhejiang, which is a coastal province of China, using both remote sensing (RS) and geographical information systems (GIS). The analysis has validated the correlation between indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local number of cholera cases based on 8-year monthly data from 2001 to 2008. The results show the number of cholera cases has been strongly affected by the variables of SST, SSH and OCC. Utilizing this information, a cholera prediction model has been established based on the oceanic and climatic environmental factors. The model indicates that RS and GIS have great potential for designing an early warning system for cholera.

College students' drinking motives and social-contextual factors: Comparing associations across levels of analysis.

Science.gov (United States)

O'Hara, Ross E; Armeli, Stephen; Tennen, Howard

2015-06-01

Prior investigations have established between-person associations between drinking motives and both levels of alcohol use and social-contextual factors surrounding that use, but these relations have yet to be examined at the within-person level of analysis. Moreover, exploring previously posited subtypes of coping motives (i.e., coping with depression, anxiety, and anger) may shed light on the within-person processes underlying drinking to cope. In this daily diary study of college student drinking (N = 722; 54% female), students reported each day how many drinks they consumed the previous evening in both social and nonsocial settings along with their motives for each drinking episode. Additionally, they reported whether they attended a party the evening before, the number of people they were with, the gender makeup of that group, and their perceptions of their companions' drinking prevalence and quantity. External reasons for drinking-social and conformity motives-showed patterns largely consistent across levels of analysis and in agreement with motivational models. However, internal reasons for drinking-enhancement and coping motives-demonstrated divergent associations that suggest different processes across levels of analysis. Finally, coping subtypes showed differing associations with drinking levels and social-contextual factors dependent on the predisposing emotion and the level of analysis. These results suggest that internal drinking motives have unique state and trait components, which could have important implications for the application of motivational models to prevention and treatment efforts. We recommend including drinking motives (including coping subtypes) as within-person measures in future microlongitudinal studies. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

College Students’ Drinking Motives and Social-Contextual Factors: Comparing Associations across Levels of Analysis

Science.gov (United States)

O'Hara, Ross E.; Armeli, Stephen; Tennen, Howard

2014-01-01

Prior investigations have established between-person associations between drinking motives and both levels of alcohol use and social-contextual factors surrounding that use, but these relations have yet to be examined at the within-person level of analysis. Moreover, exploring previously posited subtypes of coping motives (i.e., coping with depression, anxiety, and anger) may shed light on the within-person processes underlying drinking to cope. In this daily diary study of college student drinking (N = 722; 54% female), students reported each day how many drinks they consumed the previous evening in both social and nonsocial settings along with their motives for each drinking episode. Additionally, they reported whether they attended a party the evening before, the number of people they were with, the gender makeup of that group, and their perceptions of their companions’ drinking prevalence and quantity. External reasons for drinking—social and conformity motives—showed patterns largely consistent across levels of analysis and in agreement with motivational models. However, internal reasons for drinking—enhancement and coping motives—demonstrated divergent associations that suggest different processes across levels of analysis. Finally, coping subtypes showed differing associations with drinking levels and social-contextual factors dependent on the predisposing emotion and the level of analysis. These results suggest that internal drinking motives have unique state and trait components, which could have important implications for the application of motivational models to prevention and treatment efforts. We recommend including drinking motives (including coping subtypes) as within-person measures in future micro-longitudinal studies. PMID:25546143

Analysis of IFR driver fuel hot channel factors

International Nuclear Information System (INIS)

Ku, J.Y.; Chang, L.K.; Mohr, D.

1994-01-01

Thermal-hydraulic uncertainty factors for Integral Fast Reactor (IFR) driver fuels have been determined based primarily on the database obtained from the predecessor fuels used in the IFR prototype, Experimental Breeder Reactor II. The uncertainty factors were applied to the channel factors (HCFs) analyses to obtain separate overall HCFs for fuel and cladding for steady-state analyses. A ''semistatistical horizontal method'' was used in the HCFs analyses. The uncertainty factor of the fuel thermal conductivity dominates the effects considered in the HCFs analysis; the uncertainty in fuel thermal conductivity will be reduced as more data are obtained to expand the currently limited database for the IFR ternary metal fuel (U-20Pu-10Zr). A set of uncertainty factors to be used for transient analyses has also been derived

Analysis of IFR driver fuel hot channel factors

International Nuclear Information System (INIS)

Ku, J.Y.; Chang, L.K.; Mohr, D.

2004-01-01

Thermal-hydraulic uncertainty factors for Integral Fast Reactor (IFR) driver fuels have been determined based primarily on the database obtained from the predecessor fuels used in the IFR prototype. Experimental Breeder Reactor II. The uncertainty factors were applied to the hot channel factors (HCFs) analyses to obtain separate overall HCFs for fuel and cladding for steady-state analyses. A 'semistatistical horizontal method' was used in the HCFs analyses. The uncertainty factor of the fuel thermal conductivity dominates the effects considered in the HCFs analysis; the uncertainty in fuel thermal conductivity will be reduced as more data are obtained to expand the currently limited database for the IFR ternary metal fuel (U-20Pu-10Zr). A set of uncertainty factors to be used for transient analyses has also been derived. (author)

Quantitative Analysis of the Contributing Factors Affecting Specialty Care No-Show Rates at Brooke Army Medical Center

Science.gov (United States)

2007-03-30

PHYSICAL THERAPY ,TMC 53 9 14.52% AUDIOLOGY,BAMC 133 22 14.19% OPHTH PEDS,BAMC 28 4 12.50% OCCUPATIONAL THERAPY ,BAMC 135 18 11.76% ALLERGY CLINIC,BAMC...for physical therapy and have a total of 4 appointments set up with that clinic. For this study, only the first referral was counted and not the follow...Nephrology. Some of the other low no-show rate clinics were: Pain Management (1.27%), Endocrinology (1.52%), General Surgery (1.83%), Rheumatology (1.89

Economic Analysis of Factors Affecting Technical Efficiency of ...

African Journals Online (AJOL)

Economic Analysis of Factors Affecting Technical Efficiency of Smallholders ... socio-economic characteristics which influence technical efficiency in maize production. ... Ministry of Agriculture and livestock, records, books, reports and internet.

Risk Factors for Child Malnutrition in Bangladesh: A Multilevel Analysis of a Nationwide Population-Based Survey.

Science.gov (United States)

Chowdhury, Mohammad Rocky Khan; Rahman, Mohammad Shafiur; Khan, Mohammad Mubarak Hossain; Mondal, Mohammad Nazrul Islam; Rahman, Mohammad Mosiur; Billah, Baki

2016-05-01

To identify the prevalence and risk factors of child malnutrition in Bangladesh. Data was extracted from the Bangladesh Demographic Health Survey (2011). The outcome measures were stunting, wasting, and underweight. χ(2) analysis was performed to find the association of outcome variables with selected factors. Multilevel logistic regression models with a random intercept at each of the household and community levels were used to identify the risk factors of stunting, wasting, and underweight. From the 2011 survey, 7568 children less than 5 years of age were included in the current analysis. The overall prevalence of stunting, wasting, and underweight was 41.3% (95% CI 39.0-42.9). The χ(2) test and multilevel logistic regression analysis showed that the variables age, sex, mother's body mass index, mother's educational status, father's educational status, place of residence, socioeconomic status, community status, religion, region of residence, and food security are significant factors of child malnutrition. Children with poor socioeconomic and community status were at higher risk of malnutrition. Children from food insecure families were more likely to be malnourished. Significant community- and household-level variations were found. The prevalence of child malnutrition is still high in Bangladesh, and the risk was assessed at several multilevel factors. Therefore, prevention of malnutrition should be given top priority as a major public health intervention. Copyright © 2016 Elsevier Inc. All rights reserved.

Pathway-based factor analysis of gene expression data produces highly heritable phenotypes that associate with age.

Science.gov (United States)

Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

2015-03-09

Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 "pathway phenotypes" that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold ([Formula: see text]). These phenotypes are more heritable ([Formula: see text]) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. Copyright © 2015 Brown et al.

Nationwide analysis on the impact of socioeconomic land use factors and incidence of urothelial carcinoma.

Science.gov (United States)

Brandt, Maximilian P; Gust, Kilian M; Mani, Jens; Vallo, Stefan; Höfner, Thomas; Borgmann, Hendrik; Tsaur, Igor; Thomas, Christian; Haferkamp, Axel; Herrmann, Eva; Bartsch, Georg

2018-02-01

Incidence rates for urothelial carcinoma (UC) have been reported to differ between countries within the European Union (EU). Besides occupational exposure to chemicals, other substances such as tobacco and nitrite in groundwater have been identified as risk factors for UC. We investigated if regional differences in UC incidence rates are associated with agricultural, industrial and residential land use. Newly diagnosed cases of UC between 2003 and 2010 were included. Information within 364 administrative districts of Germany from 2004 for land use factors were obtained and calculated as a proportion of the total area of the respective administrative district and as a smoothed proportion. Furthermore, information on smoking habits was included in our analysis. Kulldorff spatial clustering was used to detect different clusters. A negative binomial model was used to test the spatial association between UC incidence as a ratio of observed versus expected incidence rates, land use and smoking habits. We identified 437,847,834 person years with 171,086 cases of UC. Cluster analysis revealed areas with higher incidence of UC than others (p=0.0002). Multivariate analysis including significant pairwise interactions showed that the environmental factors were independently associated with UC (psocioeconomic factors based on agricultural, industrial and residential land use may be associated with UC incidence rates. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Monte Carlo study comparing PIV, ULS and DWLS in the estimation of dichotomous confirmatory factor analysis.

Science.gov (United States)

Nestler, Steffen

2013-02-01

We conducted a Monte Carlo study to investigate the performance of the polychoric instrumental variable estimator (PIV) in comparison to unweighted least squares (ULS) and diagonally weighted least squares (DWLS) in the estimation of a confirmatory factor analysis model with dichotomous indicators. The simulation involved 144 conditions (1,000 replications per condition) that were defined by a combination of (a) two types of latent factor models, (b) four sample sizes (100, 250, 500, 1,000), (c) three factor loadings (low, moderate, strong), (d) three levels of non-normality (normal, moderately, and extremely non-normal), and (e) whether the factor model was correctly specified or misspecified. The results showed that when the model was correctly specified, PIV produced estimates that were as accurate as ULS and DWLS. Furthermore, the simulation showed that PIV was more robust to structural misspecifications than ULS and DWLS. © 2012 The British Psychological Society.

Analysis on influence factors of China's CO2 emissions based on Path-STIRPAT model

International Nuclear Information System (INIS)

Li Huanan; Mu Hailin; Zhang Ming; Li Nan

2011-01-01

With the intensification of global warming and continued growth in energy consumption, China is facing increasing pressure to cut its CO 2 (carbon dioxide) emissions down. This paper discusses the driving forces influencing China's CO 2 emissions based on Path-STIRPAT model-a method combining Path analysis with STIRPAT (stochastic impacts by regression on population, affluence and technology) model. The analysis shows that GDP per capita (A), industrial structure (IS), population (P), urbanization level (R) and technology level (T) are the main factors influencing China's CO 2 emissions, which exert an influence interactively and collaboratively. The sequence of the size of factors' direct influence on China's CO 2 emission is A>T>P>R>IS, while that of factors' total influence is A>R>P>T>IS. One percent increase in A, IS, P, R and T leads to 0.44, 1.58, 1.31, 1.12 and -1.09 percentage change in CO 2 emission totally, where their direct contribution is 0.45, 0.07, 0.63, 0.08, 0.92, respectively. Improving T is the most important way for CO 2 reduction in China. - Highlights: → We analyze the driving forces influencing China's CO 2 emissions. → Five macro factors like per capita GDP are the main influencing factors. → These factors exert an influence interactively and collaboratively. → Different factors' direct and total influence on China's CO 2 emission is different. → Improving technology level is the most important way for CO 2 reduction in China.

Factor analysis of the Hamilton Depression Rating Scale in Parkinson's disease.

Science.gov (United States)

Broen, M P G; Moonen, A J H; Kuijf, M L; Dujardin, K; Marsh, L; Richard, I H; Starkstein, S E; Martinez-Martin, P; Leentjens, A F G

2015-02-01

Several studies have validated the Hamilton Depression Rating Scale (HAMD) in patients with Parkinson's disease (PD), and reported adequate reliability and construct validity. However, the factorial validity of the HAMD has not yet been investigated. The aim of our analysis was to explore the factor structure of the HAMD in a large sample of PD patients. A principal component analysis of the 17-item HAMD was performed on data of 341 PD patients, available from a previous cross sectional study on anxiety. An eigenvalue ≥1 was used to determine the number of factors. Factor loadings ≥0.4 in combination with oblique rotations were used to identify which variables made up the factors. Kaiser-Meyer-Olkin measure (KMO), Cronbach's alpha, Bartlett's test, communality, percentage of non-redundant residuals and the component correlation matrix were computed to assess factor validity. KMO verified the sample's adequacy for factor analysis and Cronbach's alpha indicated a good internal consistency of the total scale. Six factors had eigenvalues ≥1 and together explained 59.19% of the variance. The number of items per factor varied from 1 to 6. Inter-item correlations within each component were low. There was a high percentage of non-redundant residuals and low communality. This analysis demonstrates that the factorial validity of the HAMD in PD is unsatisfactory. This implies that the scale is not appropriate for studying specific symptom domains of depression based on factorial structure in a PD population. Copyright © 2014 Elsevier Ltd. All rights reserved.

Large-Scale No-Show Patterns and Distributions for Clinic Operational Research

Directory of Open Access Journals (Sweden)

Michael L. Davies

2016-02-01

Full Text Available Patient no-shows for scheduled primary care appointments are common. Unused appointment slots reduce patient quality of care, access to services and provider productivity while increasing loss to follow-up and medical costs. This paper describes patterns of no-show variation by patient age, gender, appointment age, and type of appointment request for six individual service lines in the United States Veterans Health Administration (VHA. This retrospective observational descriptive project examined 25,050,479 VHA appointments contained in individual-level records for eight years (FY07-FY14 for 555,183 patients. Multifactor analysis of variance (ANOVA was performed, with no-show rate as the dependent variable, and gender, age group, appointment age, new patient status, and service line as factors. The analyses revealed that males had higher no-show rates than females to age 65, at which point males and females exhibited similar rates. The average no-show rates decreased with age until 75–79, whereupon rates increased. As appointment age increased, males and new patients had increasing no-show rates. Younger patients are especially prone to no-show as appointment age increases. These findings provide novel information to healthcare practitioners and management scientists to more accurately characterize no-show and attendance rates and the impact of certain patient factors. Future general population data could determine whether findings from VHA data generalize to others.

Large-Scale No-Show Patterns and Distributions for Clinic Operational Research.

Science.gov (United States)

Davies, Michael L; Goffman, Rachel M; May, Jerrold H; Monte, Robert J; Rodriguez, Keri L; Tjader, Youxu C; Vargas, Dominic L

2016-02-16

Patient no-shows for scheduled primary care appointments are common. Unused appointment slots reduce patient quality of care, access to services and provider productivity while increasing loss to follow-up and medical costs. This paper describes patterns of no-show variation by patient age, gender, appointment age, and type of appointment request for six individual service lines in the United States Veterans Health Administration (VHA). This retrospective observational descriptive project examined 25,050,479 VHA appointments contained in individual-level records for eight years (FY07-FY14) for 555,183 patients. Multifactor analysis of variance (ANOVA) was performed, with no-show rate as the dependent variable, and gender, age group, appointment age, new patient status, and service line as factors. The analyses revealed that males had higher no-show rates than females to age 65, at which point males and females exhibited similar rates. The average no-show rates decreased with age until 75-79, whereupon rates increased. As appointment age increased, males and new patients had increasing no-show rates. Younger patients are especially prone to no-show as appointment age increases. These findings provide novel information to healthcare practitioners and management scientists to more accurately characterize no-show and attendance rates and the impact of certain patient factors. Future general population data could determine whether findings from VHA data generalize to others.

[Clinical observation and related factors analysis of neonatal asphyxia complicated with retinal hemorrhage].

Science.gov (United States)

Pu, Q L; Zhou, Q Y; Liu, J; Li, P; Huang, H F; Jiang, H Q

2017-05-11

Objective: To observe and analyze related factors of neonatal asphyxia complicated with retinal hemorrhage. Methods: It was a retrospective case series. Seven hundred and twenty-one cases with neonatal asphyxia after 72 hours of birth were enrolled in this study. Fundus examination was performed on these newborns using the third generation wide-angle digital retina imaging system (RetCamⅢ), and the bleeding level was divided into level I, level Ⅱ and level Ⅲ. The conditions of the newborn and the mother during pregnancy were correlatively analyzed. The other factors were also analyzed including delivery mode, birth weight, gestational age, gender, grade of neonatal asphyxia, scalp hematoma, intracranial hemorrhage, fetal intrauterine distress, mother's age and antenatal complications. Single factor χ(2) test and multivariate logistic regression analysis were used to screen and judge risk factors causing retinal hemorrhage related to neonatal asphyxia. Results: In 721 cases of neonatal asphyxia, retinal hemorrhage was found in 204 newborns (28.29%). The hemorrhage was at level Ⅰ in 77 cases (37.75%) , at level Ⅱ in 38 cases (18.63%) and at level Ⅲ in 89 cases (43.63%) . Four cases also had vitreous hemorrhage. Asphyxia was mild in 673 infants (93.34%) and severe in 48 infants (6.66%). The difference in the degree of retinal hemorrhage between the patients with mild and severe asphyxia was significant (χ(2)=22.336, P= 0.000). When asphyxia was aggravated, the degree of retinal hemorrhage increased. Relative factors analysis showed that delivery mode (χ(2)=158.643, Pneonatal asphyxia (χ(2)=19.809, Phemorrhage. Logistic regression analysis indicated that grade of neonatal asphyxia and delivery mode were risk factors of retinal hemorrhage in neonatal asphyxia ( OR= 0.304, 0.085). Conclusion: The incidence of retinal hemorrhage in neonatal asphyxia was 28.29%. The degree of neonatal asphyxia and delivery mode may play roles in the occurrence of retinal

Prognostic factors of early metastasis and mortality in dogs with appendicular osteosarcoma after receiving surgery : an individual patient data meta-analysis

NARCIS (Netherlands)

Schmidt, A.F.; Nielen, M.; Klungel, O.H.; Hoes, A.W.; de Boer, A.; Groenwold, R.H.H.; Kirpensteijn, J.

2013-01-01

Recently an aggregated data meta-analysis showed that serum alkaline phosphatase (SALP) and proximal humerus location are predictors for shorter survival in canine osteosarcoma. To identify additional prognostic factors of mortality and metastasis an individual patient data meta-analysis (IPDMA) was

Analysis of factors controlling soil phosphorus loss with surface runoff in Huihe National Nature Reserve by principal component and path analysis methods.

Science.gov (United States)

He, Jing; Su, Derong; Lv, Shihai; Diao, Zhaoyan; Bu, He; Wo, Qiang

2018-01-01

Phosphorus (P) loss with surface runoff accounts for the P input to and acceleration of eutrophication of the freshwater. Many studies have focused on factors affecting P loss with surface runoff from soils, but rarely on the relationship among these factors. In the present study, rainfall simulation on P loss with surface runoff was conducted in Huihe National Nature Reserve, in Hulunbeier grassland, China, and the relationships between P loss with surface runoff, soil properties, and rainfall conditions were examined. Principal component analysis and path analysis were used to analyze the direct and indirect effects on P loss with surface runoff. The results showed that P loss with surface runoff was closely correlated with soil electrical conductivity, soil pH, soil Olsen P, soil total nitrogen (TN), soil total phosphorus (TP), and soil organic carbon (SOC). The main driving factors which influenced P loss with surface runoff were soil TN, soil pH, soil Olsen P, and soil water content. Path analysis and determination coefficient analysis indicated that the standard multiple regression equation for P loss with surface runoff and each main factor was Y = 7.429 - 0.439 soil TN - 6.834 soil pH + 1.721 soil Olsen-P + 0.183 soil water content (r = 0.487, p runoff. The effect of physical and chemical properties of undisturbed soils on P loss with surface runoff was discussed, and the soil water content and soil Olsen P were strongly positive influences on the P loss with surface runoff.

Research on the factors of return on equity: empirical analysis in Chinese port industries from 2000-2008

Science.gov (United States)

Li, Wei

2012-01-01

Port industries are the basic industries in the national economy. The industries have become the most modernized departments in every country. The development of the port industry is not only advantageous to promote the optimizing arrangement of social resources, but also to promote the growth of foreign trade volume through enhancing the transportation functions. Return on equity (ROE) is a direct indicator related to the maximization of company's wealth. It makes up the shortcomings of earnings per share (EPS). The aim of this paper is to prove the correlation between ROE and other financial indicators by choosing the listed port companies as the research objectives and selecting the data of these companies from 2000 to 2008 as empirical sample data with statistical analysis of the chartered figure and coefficient. The detailed analysis method used in the paper is the combination of trend analysis, comparative analysis and the ratio of the factor analysis method. This paper analyzes and compares all these factors and draws the conclusions as follows: Firstly, ROE has a positive correlation with total assets turnover, main profit margin and fixed asset ratio, while has a negative correlation with assets liabilities ratio, total assets growth rate and DOL. Secondly, main profit margin has the greatest positive effect on ROE among all these factors. The second greatest factor is total assets turnover, which shows the operation capacity is also an important indicator after the profitability. Thirdly, assets liabilities ratio has the greatest negative effect on ROE among all these factors.

Factors influencing the short-term prognosis of interventional therapy for malignant obstructive jaundice: a multivariate analysis

International Nuclear Information System (INIS)

Zhang Xueqiang; Zhai Renyou

2009-01-01

Objective: To discuss the correlative factors affecting the short-term prognosis in treating malignant obstructive jaundice with percutaneous transhepatic biliary drainage (PTBD) and/or percutaneous transhepatic biliary stenting (PTBS). Methods: During the period of December 2008-June 2009, PTBD and/or PTBS were performed in 67 patients. The clinical date were reviewed and analyzed. According to the reduction degree of serum bilirubin and survival condition in 30 days, the patients were divided into effective group (54 cases) and ineffective group (13 cases). Single factor affecting the short-term prognosis was analyzed by using χ 2 test and multi-factors were analyzed by using non-conditional logistic regression mode. Results: Single variable analysis showed that time of obstruction, way of drainage, preoperative biliary infection, Child-Pugh grade, TBIL, HGB and Cr level were of statistical significance. The logistic regression analysis showed that there were obvious correlation among preoperative biliary infection, Child-grade ≥11 and Cr >115 μmol/L. Conclusion: The infection of the bile duct before operation, Child-grade ≥11 and Cr >115μmol/L carry a close relationship with the short-term prognosis of PTBD and PTBS. Therefore, an overall preoperative evaluation for malignant obstructive jaundice is of great importance. (authors)

Factor and Rasch analysis of the Fonseca anamnestic index for the diagnosis of myogenous temporomandibular disorder.

Science.gov (United States)

Rodrigues-Bigaton, Delaine; de Castro, Ester M; Pires, Paulo F

Rasch analysis has been used in recent studies to test the psychometric properties of a questionnaire. The conditions for use of the Rasch model are one-dimensionality (assessed via prior factor analysis) and local independence (the probability of getting a particular item right or wrong should not be conditioned upon success or failure in another). To evaluate the dimensionality and the psychometric properties of the Fonseca anamnestic index (FAI), such as the fit of the data to the model, the degree of difficulty of the items, and the ability to respond in patients with myogenous temporomandibular disorder (TMD). The sample consisted of 94 women with myogenous TMD, diagnosed by the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD), who answered the FAI. For the factor analysis, we applied the Kaiser-Meyer-Olkin test, Bartlett's sphericity, Spearman's correlation, and the determinant of the correlation matrix. For extraction of the factors/dimensions, an eigenvalue >1.0 was used, followed by oblique oblimin rotation. The Rasch analysis was conducted on the dimension that showed the highest proportion of variance explained. Adequate sample "n" and FAI multidimensionality were observed. Dimension 1 (primary) consisted of items 1, 2, 3, 6, and 7. All items of dimension 1 showed adequate fit to the model, being observed according to the degree of difficulty (from most difficult to easiest), respectively, items 2, 1, 3, 6, and 7. The FAI presented multidimensionality with its main dimension consisting of five reliable items with adequate fit to the composition of its structure. Copyright © 2017 Associação Brasileira de Pesquisa e Pós-Graduação em Fisioterapia. Publicado por Elsevier Editora Ltda. All rights reserved.

FACTORES INDIVIDUALES, FAMILIARES Y SOCIALES ASOCIADOS AL EMBARAZO EN ADOLESCENTES EN EL CENTRO DE SALUD CARLOS SHOWING FERRARI 2014 - 2015

OpenAIRE

Luyo Marcellini, Delci Fiorella

2017-01-01

OBJETIVO: Determinar los factores individuales, familiares y sociales asociados al embarazo en adolescentes en el Centro de Salud Carlos Showing Ferrari del periodo de enero del 2014 a diciembre del 2015. METODOS Y TECNICA: El estudio fue observacional, longitudinal, retrospectivo. Con un diseño caso y control. La técnica utilizada fue el fichaje en base a la recolección de datos de fuentes secundarias. RESULTADOS: Dentro de los Factores individuales de riesgo asociados al embarazo en ...

A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis

Science.gov (United States)

Edwards, Michael C.

2010-01-01

Item factor analysis has a rich tradition in both the structural equation modeling and item response theory frameworks. The goal of this paper is to demonstrate a novel combination of various Markov chain Monte Carlo (MCMC) estimation routines to estimate parameters of a wide variety of confirmatory item factor analysis models. Further, I show…

EMPLOYMENT LEVEL ANALYSIS FROM THE DETERMINANT FACTORS PERSPECTIVE

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Elena Diana ŞERB

2016-02-01

Full Text Available Neglecting the human factor as part of the labor market causes losses for society as any activity that is initiated within it, has as a starting point, and also as a finishing point, the human intervention. The starting point of the article is represented by the projections made by the European    Commission in the Population Ageing Report in 2015 underlying assumptions and projections, and also by the projections of the United Nations report in 2015, and this resulted in many conclusions including the one that for the first time in Romania the average aging in 2015 exceeds the values measured by EU till present day, and this is reflected in the employment level (active aging population. The hypothesis behind the article is that the evolution of the population and migrants has repercussions on employment. Structured in three parts: knowledge status, the analysis of employment indicators and information about the intensity and direction of the link between a number of factors and employment level, this article aims to establish the determinant factors of employment through a research focused on the analysis of secondary sources, and also using the regression model. The most important lesson learned as a result of this research is that the labor market works with a variety of factors with a higher or lower influence, and in turn the labor market influences other factors.

Risk factors for delusion of theft in patients with Alzheimer's disease showing mild dementia in Japan.

Science.gov (United States)

Murayama, N; Iseki, E; Endo, T; Nagashima, K; Yamamoto, R; Ichimiya, Y; Arai, H; Sato, K

2009-07-01

The mechanism underlying delusion in Alzheimer's disease patients has not been fully clarified; however, the occurrence of delusion is a critical issue for dementia patients and their caregivers. In Japan, delusion of theft is the most frequent delusion in AD patients. We examined the risk factors for delusion of theft in AD patients showing mild dementia. Fifty-six AD patients were administered HDS-R, MMSE and COGNISTAT, including the 'speech sample', to assess their neuropsychological and social cognitive functions. The age, years of education, presence of cohabiting family members and premorbid personality traits were obtained from family members. About 25.0% of AD patients showed delusion of theft (D-group), and 75% did not (non-D-group). About 33.3% of female patients and 5.9% of male patients were included in the D-group (p theft in AD patients was related to female gender, absence of cohabiting family members, neurotic personality and retained social cognitive function.

Directional variance adjustment: bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization.

Science.gov (United States)

Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W; Müller, Klaus-Robert; Lemm, Steven

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation.

Correction factor for hair analysis by PIXE

International Nuclear Information System (INIS)

Montenegro, E.C.; Baptista, G.B.; Castro Faria, L.V. de; Paschoa, A.S.

1980-01-01

The application of the Particle Induced X-ray Emission (PIXE) technique to analyse quantitatively the elemental composition of hair specimens brings about some difficulties in the interpretation of the data. The present paper proposes a correction factor to account for the effects of the energy loss of the incident particle with penetration depth, and X-ray self-absorption when a particular geometrical distribution of elements in hair is assumed for calculational purposes. The correction factor has been applied to the analysis of hair contents Zn, Cu and Ca as a function of the energy of the incident particle. (orig.)

Correction factor for hair analysis by PIXE

International Nuclear Information System (INIS)

Montenegro, E.C.; Baptista, G.B.; Castro Faria, L.V. de; Paschoa, A.S.

1979-06-01

The application of the Particle Induced X-ray Emission (PIXE) technique to analyse quantitatively the elemental composition of hair specimens brings about some difficulties in the interpretation of the data. The present paper proposes a correction factor to account for the effects of energy loss of the incident particle with penetration depth, and x-ray self-absorption when a particular geometrical distribution of elements in hair is assumed for calculational purposes. The correction factor has been applied to the analysis of hair contents Zn, Cu and Ca as a function of the energy of the incident particle.(Author) [pt

Investigating product development strategy in beverage industry using factor analysis

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Naser Azad

2013-03-01

Full Text Available Selecting a product development strategy that is associated with the company's current service or product innovation, based on customers’ needs and changing environment, plays an important role in increasing demand, increasing market share, increasing sales and profits. Therefore, it is important to extract effective variables associated with product development to improve performance measurement of firms. This paper investigates important factors influencing product development strategies using factor analysis. The proposed model of this paper investigates 36 factors and, using factor analysis, we extract six most influential factors including information sharing, intelligence information, exposure strategy, differentiation, research and development strategy and market survey. The first strategy, partnership, includes five sub-factor including product development partnership, partnership with foreign firms, customers’ perception from competitors’ products, Customer involvement in product development, inter-agency coordination, customer-oriented approach to innovation and transmission of product development change where inter-agency coordination has been considered the most important factor. Internal strengths are the most influential factors impacting the second strategy, intelligence information. The third factor, introducing strategy, introducing strategy, includes four sub criteria and consumer buying behavior is the most influencing factor. Differentiation is the next important factor with five components where knowledge and expertise in product innovation is the most important one. Research and development strategy with four sub-criteria where reducing product development cycle plays the most influential factor and finally, market survey strategy is the last important factor with three factors and finding new market plays the most important role.

BDNF-Deficient Mice Show Reduced Psychosis-Related Behaviors Following Chronic Methamphetamine.

Science.gov (United States)

Manning, Elizabeth E; Halberstadt, Adam L; van den Buuse, Maarten

2016-04-01

One of the most devastating consequences of methamphetamine abuse is increased risk of psychosis. Brain-derived neurotrophic factor has been implicated in both psychosis and neuronal responses to methamphetamine. We therefore examined persistent psychosis-like behavioral effects of methamphetamine in brain-derived neurotrophic factor heterozygous mice. Mice were chronically treated with methamphetamine from 6 to 9 weeks of age, and locomotor hyperactivity to an acute D-amphetamine challenge was tested in photocell cages after a 2-week withdrawal period. Methamphetamine-treated wild-type mice, but not brain-derived neurotrophic factor heterozygous mice, showed locomotor sensitization to acute 3mg/kg D-amphetamine. Qualitative analysis of exploration revealed tolerance to D-amphetamine effects on entropy in methamphetamine-treated brain-derived neurotrophic factor heterozygous mice, but not wild-type mice. Chronic methamphetamine exposure induces contrasting profiles of behavioral changes in wild-type and brain-derived neurotrophic factor heterozygous mice, with attenuation of behaviors relevant to psychosis in methamphetamine-treated brain-derived neurotrophic factor heterozygous mice. This suggests that brain-derived neurotrophic factor signalling changes may contribute to development of psychosis in methamphetamine users. © The Author 2015. Published by Oxford University Press on behalf of CINP.

Constructing the Japanese version of the Maslach Burnout Inventory-Student Survey: Confirmatory factor analysis.

Science.gov (United States)

Tsubakita, Takashi; Shimazaki, Kazuyo

2016-01-01

To examine the factorial validity of the Maslach Burnout Inventory-Student Survey, using a sample of 2061 Japanese university students majoring in the medical and natural sciences (67.9% male, 31.8% female; Mage  = 19.6 years, standard deviation = 1.5). The back-translated scale used unreversed items to assess inefficacy. The inventory's descriptive properties and Cronbach's alphas were calculated using SPSS software. The present authors compared fit indices of the null, one factor, and default three factor models via confirmatory factor analysis with maximum-likelihood estimation using AMOS software, version 21.0. Intercorrelations between exhaustion, cynicism, and inefficacy were relatively higher than in prior studies. Cronbach's alphas were 0.76, 0.85, and 0.78, respectively. Although fit indices of the hypothesized three factor model did not meet the respective criteria, the model demonstrated better fit than did the null and one factor models. The present authors added four paths between error variables within items, but the modified model did not show satisfactory fit. Subsequent analysis revealed that a bi-factor model fit the data better than did the hypothesized or modified three factor models. The Japanese version of the Maslach Burnout Inventory-Student Survey needs minor changes to improve the fit of its three factor model, but the scale as a whole can be used to adequately assess overall academic burnout in Japanese university students. Although the scale was back-translated, two items measuring exhaustion whose expressions overlapped should be modified, and all items measuring inefficacy should be reversed in order to statistically clarify the factorial difference between the scale's three factors. © 2015 The Authors. Japan Journal of Nursing Science © 2015 Japan Academy of Nursing Science.

Environmental Performance in Countries Worldwide: Determinant Factors and Multivariate Analysis

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Isabel Gallego-Alvarez

2014-11-01

Full Text Available The aim of this study is to analyze the environmental performance of countries and the variables that can influence it. At the same time, we performed a multivariate analysis using the HJ-biplot, an exploratory method that looks for hidden patterns in the data, obtained from the usual singular value decomposition (SVD of the data matrix, to contextualize the countries grouped by geographical areas and the variables relating to environmental indicators included in the environmental performance index. The sample used comprises 149 countries of different geographic areas. The findings obtained from the empirical analysis emphasize that socioeconomic factors, such as economic wealth and education, as well as institutional factors represented by the style of public administration, in particular control of corruption, are determinant factors of environmental performance in the countries analyzed. In contrast, no effect on environmental performance was found for factors relating to the internal characteristics of a country or political factors.

Factors influencing crime rates: an econometric analysis approach

Science.gov (United States)

Bothos, John M. A.; Thomopoulos, Stelios C. A.

2016-05-01

The scope of the present study is to research the dynamics that determine the commission of crimes in the US society. Our study is part of a model we are developing to understand urban crime dynamics and to enhance citizens' "perception of security" in large urban environments. The main targets of our research are to highlight dependence of crime rates on certain social and economic factors and basic elements of state anticrime policies. In conducting our research, we use as guides previous relevant studies on crime dependence, that have been performed with similar quantitative analyses in mind, regarding the dependence of crime on certain social and economic factors using statistics and econometric modelling. Our first approach consists of conceptual state space dynamic cross-sectional econometric models that incorporate a feedback loop that describes crime as a feedback process. In order to define dynamically the model variables, we use statistical analysis on crime records and on records about social and economic conditions and policing characteristics (like police force and policing results - crime arrests), to determine their influence as independent variables on crime, as the dependent variable of our model. The econometric models we apply in this first approach are an exponential log linear model and a logit model. In a second approach, we try to study the evolvement of violent crime through time in the US, independently as an autonomous social phenomenon, using autoregressive and moving average time-series econometric models. Our findings show that there are certain social and economic characteristics that affect the formation of crime rates in the US, either positively or negatively. Furthermore, the results of our time-series econometric modelling show that violent crime, viewed solely and independently as a social phenomenon, correlates with previous years crime rates and depends on the social and economic environment's conditions during previous years.

An Enhanced Factor Analysis of Performance Degradation Assessment on Slurry Pump Impellers

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Shilong Sun

2017-01-01

Full Text Available Slurry pumps, such as oil sand pumps, are widely used in industry to convert electrical energy to slurry potential and kinetic energy. Because of adverse working conditions, slurry pump impellers are prone to suffer wear, which may result in slurry pump breakdowns. To prevent any unexpected breakdowns, slurry pump impeller performance degradation assessment should be immediately conducted to monitor the current health condition and to ensure the safety and reliability of slurry pumps. In this paper, to provide an alternative to the impeller health indicator, an enhanced factor analysis based impeller indicator (EFABII is proposed. Firstly, a low-pass filter is employed to improve the signal to noise ratios of slurry pump vibration signals. Secondly, redundant statistical features are extracted from the filtered vibration signals. To reduce the redundancy of the statistic features, the enhanced factor analysis is performed to generate new statistical features. Moreover, the statistic features can be automatically grouped and developed a new indicator called EFABII. Data collected from industrial oil sand pumps are used to validate the effectiveness of the proposed method. The results show that the proposed method is able to track the current health condition of slurry pump impellers.

A ChIP-Seq benchmark shows that sequence conservation mainly improves detection of strong transcription factor binding sites.

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Tony Håndstad

Full Text Available BACKGROUND: Transcription factors are important controllers of gene expression and mapping transcription factor binding sites (TFBS is key to inferring transcription factor regulatory networks. Several methods for predicting TFBS exist, but there are no standard genome-wide datasets on which to assess the performance of these prediction methods. Also, it is believed that information about sequence conservation across different genomes can generally improve accuracy of motif-based predictors, but it is not clear under what circumstances use of conservation is most beneficial. RESULTS: Here we use published ChIP-seq data and an improved peak detection method to create comprehensive benchmark datasets for prediction methods which use known descriptors or binding motifs to detect TFBS in genomic sequences. We use this benchmark to assess the performance of five different prediction methods and find that the methods that use information about sequence conservation generally perform better than simpler motif-scanning methods. The difference is greater on high-affinity peaks and when using short and information-poor motifs. However, if the motifs are specific and information-rich, we find that simple motif-scanning methods can perform better than conservation-based methods. CONCLUSIONS: Our benchmark provides a comprehensive test that can be used to rank the relative performance of transcription factor binding site prediction methods. Moreover, our results show that, contrary to previous reports, sequence conservation is better suited for predicting strong than weak transcription factor binding sites.

A kernel version of spatial factor analysis

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2009-01-01

. Schölkopf et al. introduce kernel PCA. Shawe-Taylor and Cristianini is an excellent reference for kernel methods in general. Bishop and Press et al. describe kernel methods among many other subjects. Nielsen and Canty use kernel PCA to detect change in univariate airborne digital camera images. The kernel...... version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply kernel versions of PCA, maximum autocorrelation factor (MAF) analysis...

The Analysis Of Factors Affect The Quality Of Competitive Strategy In Industry SME For Embroidery At Padang City

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dahliana kamener dahlia

2016-10-01

Full Text Available The study aimed to analyze the quality factors of competitive strategy on SME for Industrial embroidery in Padang city. With this research is expected to provide benefits to the industry, especially SMEs Industrial embroidery to be able to improve and consider the factors that can affect the quality of competitive strategy in this industry, which the factors influenced such as Quality Strategic Asset, Environment Adabtability and price strategic to the Quality Strategic Competition. The populations of this study were SME industry for the embroidery product in the city of Padang and used census sampling. Data retrieved from the primary data by spreading questionnaires and the measurement by using a Likert scale. Methods of analysis by using descriptive analysis, multiple regression analysis to test the hyphotheses. The result showed that the quality of asset strategik was postively significant effect the Quality Strategic Competition, and enviromental adaptability and price strategy have positively not significant effect on the Quality Strategic Competition.

Impact of neighbourhood land-cover in epiphytic lichen diversity: Analysis of multiple factors working at different spatial scales

Energy Technology Data Exchange (ETDEWEB)

Pinho, P.; Augusto, S.; Maguas, C. [Universidade de Lisboa, Faculdade de Ciencias, Centro de Ecologia e Biologia Vegetal (CEBV), 1749-016 Lisbon (Portugal); Pereira, M.J.; Soares, A. [Universidade Tecnica de Lisboa, Instituto Superior Tecnico, Centro de Recursos Naturais e Ambiente (CERENA) Av. Rovisco Pais, 1049-001 Lisbon (Portugal); Branquinho, C. [Universidade de Lisboa, Faculdade de Ciencias, Centro de Ecologia e Biologia Vegetal (CEBV), 1749-016 Lisbon (Portugal); Universidade Atlantica, Antiga Fabrica da Polvora de Barcarena, 2745-615 Barcarena (Portugal)], E-mail: cmbranquinho@fc.ul.pt

2008-01-15

The objective of this work was to determine the impact of neighbourhood land-cover in epiphytic lichen diversity. We used geostatistics to analyse the spatial structure of lichen-indicators (number of lichen species and Lichen Diversity Value) and correlate them to land-cover considering different distances from the observed data. The results showed that lichen diversity was influenced by different environmental factors that act in the same territory but impact lichens at different distances from the source. The differences in the distance of influence of the several land-cover types seem to be related to the size of pollutants/particles that predominantly are dispersed by each land-cover type. We also showed that a local scale of analysis gives a deeper insight into the understanding of lichen richness and abundance in the region. This work highlighted the importance of a multiple spatial scale of analysis to deeply interpret the relation between lichen diversity and the underling environmental factors. - The interpretation of lichen-biodiversity data was improved by using analysis at different scales.

Impact of neighbourhood land-cover in epiphytic lichen diversity: Analysis of multiple factors working at different spatial scales

International Nuclear Information System (INIS)

Pinho, P.; Augusto, S.; Maguas, C.; Pereira, M.J.; Soares, A.; Branquinho, C.

2008-01-01

The objective of this work was to determine the impact of neighbourhood land-cover in epiphytic lichen diversity. We used geostatistics to analyse the spatial structure of lichen-indicators (number of lichen species and Lichen Diversity Value) and correlate them to land-cover considering different distances from the observed data. The results showed that lichen diversity was influenced by different environmental factors that act in the same territory but impact lichens at different distances from the source. The differences in the distance of influence of the several land-cover types seem to be related to the size of pollutants/particles that predominantly are dispersed by each land-cover type. We also showed that a local scale of analysis gives a deeper insight into the understanding of lichen richness and abundance in the region. This work highlighted the importance of a multiple spatial scale of analysis to deeply interpret the relation between lichen diversity and the underling environmental factors. - The interpretation of lichen-biodiversity data was improved by using analysis at different scales

Analysis of factors for early hypothyroidism after 131I treatment of hyperthyroidism

International Nuclear Information System (INIS)

Zhou Youjun; Quan Xinsheng; Zhang Ling; He Meiqiong

2008-01-01

To explore the factors for the early hypothyroidism following 131 I treatment of hyperthyroidism, clinic data of 120 hyperthyroidism patients including 8 independent and 1 dependent variables after one year 131 I treatment were analyzed by logistic regression analysis method. The results showed that the average 131 I dosage given to one gram thyroid tissue was correlated positively with early hypothyroidism occurrence, and the weight of thyroid was negatively correlated to early hypothyroidism occurrence. The positive and negative prediction accuracy of the early hypothyroidism were 53.3% and 96.1% respectively, and the total prediction accuracy was 46.7%. The results suggest that the 131 I dosage and the weight of thyroid are key factors for early hypothyroidism; the appropriate adjustment of 131 I dosage based on the thyroid mass could prevent the early hypothyroidism occurrence in certain degree. (authors)

Human Resources Management Policies and Practices Scale (HRMPPS: Exploratory and Confirmatory Factor Analysis

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Gisela Demo

2012-10-01

Full Text Available Given the strategic relevance of Human Resources Management (HRM in organizations and the lack of scientific instruments to measure employees’ perceptions about policies and practices of HRM, this study aimed to validate the Human Resources Management Policies and Practices Scale (HRMPPS through exploratory and confirmatory factor analysis using the maximum likelihood method. The study has a quantitative design, but also included qualitative analysis required for the development of a scale. Employees from various organizations composed a sample of 632 people. Scale reliability was assessed by Cronbach’s alpha and Jöreskog’s rho. A sixfactor model was generated showing high-reliability and good fit. Construct validity was provided through convergent and discriminant analyses. The factors were consistent with the literature review and explained about 58% of the construct’s total variance. This study contributes to the scientific production in the area of Human Resources Management since HRMPPS can be used not only in relational studies but also as an evaluation instrument by managers who wish to improve their employees’ well-being as well as organizational outcomes.

Motivational factors influencing the homeowners’ decisions between residential heating systems: An empirical analysis for Germany

International Nuclear Information System (INIS)

Michelsen, Carl Christian; Madlener, Reinhard

2013-01-01

Heating demand accounts for a large fraction of the overall energy demand of private households in Germany. A better understanding of the adoption and diffusion of energy-efficient and renewables-based residential heating systems (RHS) is of high policy relevance, particularly against the background of climate change, security of energy supply and increasing energy prices. In this paper, we explore the multi-dimensionality of the homeowners’ motivation to decide between competing RHS. A questionnaire survey (N=2440) conducted in 2010 among homeowners who had recently installed a RHS provides the empirical foundation. Principal component analysis shows that 25 items capturing different adoption motivations can be grouped around six dimensions: (1) cost aspects, (2) general attitude towards the RHS, (3) government grant, (4) reactions to external threats (i.e., environmental or energy supply security considerations), (5) comfort considerations, and (6) influence of peers. Moreover, a cluster analysis with the identified motivational factors as segmentation variables reveals three adopter types: (1) the convenience-oriented, (2) the consequences-aware, and (3) the multilaterally-motivated RHS adopter. Finally, we show that the influence of the motivational factors on the adoption decision also differs by certain characteristics of the homeowner and features of the home. - Highlights: ► Study of the multi-dimensionality of the motivation to adopt residential heating systems (RHS). ► Principal component and cluster analysis are applied to representative survey data for Germany. ► Motivation has six dimensions, including rational decision-making and emotional factors. ► Adoption motivation differs by certain characteristics of the homeowner and of the home. ► Many adopters are driven by existing habits and perceptions about the convenience of the RHS

Determining The Factors Affecting Fruit Hardness of Different Peach Types with Meta Analysis

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Hande Küçükönder

2014-09-01

Full Text Available The aim of this study is to determine the factor effective in determining the hardness of Caterina, Suidring, Royal Glory and Tirrenia peach types using meta analysis. In the study, the impact force (Fi and the contact time (tc were detected and the impulse values (I that are expressed as independent variable in the area under the curve were calculated in the measurements performed using the technique of a low-mass lateral impactor multiplicated with peach. Using the theory of elasticity, the independent variables were determined as Fmax (maximum impact force, contact time (tmax, Fmax/tmax, 1/tmax, 1/tmax2,5, Fmax/tmax 1.25 and Fmax2.5 parameters. The correlation coefficient values showing the relationship between these parameters and the dependent variable Magness-Taylor force (MT were calculated and were combined with meta-analysis by using the Hunter-Schmid and Fisher’s Z methods. The Cohen’s classification criterion was used in evaluating the resulting mean effect size (combined correlation value and in determining its direction. As a result of the meta-analysis, the mean effect size according to Hunter-Schmid method was found 0.436 (0.371-0.497 positively directed in 95% confidence interval, while it was found 0.468 (0.390-0.545 according to Fisher’s Z method. The effect sizes in both methods were determined “mid-level” according to the Cohen’s classification. When the significance level of the studies was analyzed with the Z test, all of the ones that taken into the meta analysis has been found statistically significant. As a result of the meta analysis in this study evaluating the relationship of peach types with the fruit hardness, the mean effect size has been found to reach “strong level”. Consequently, “maximum shock acceleration” was found to be a more effective factor comparing to the other factors in determining the the fruit hardness according to the results of meta analysis applied in both methods.

Qualitative analysis of factors that increase and reduce involvement in gambling

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Egidijus

2015-12-01

Full Text Available During the rapid development of gambling business, the number of pathological gamblers is increasing as well. The problem of pathological gambling is just as important as alcoholism or drug addiction. However, there is a lack of information and research of this topicin Lithuania. The aim of work: to investigate and analyse the factors that increase or reduce involvement in gambling. Research questions: 1 What factors increase involvement in gambling? 2 What factors reduce involvement in gambling? Critical case sampling was used for selection of the participants. Subjects were required to a have experience of involvement in gambling for at least one year; b have experience of negative impact of gambling on quality of life; c have at least 6 months of gambling abstinence. Five individuals participated in the research; all of them were males who live in Vilnius. Age of the participants varied from 19 to 45. Semi-structured interviews were used to collect data. Interviews were recorded and transcribed verbatim. The matic analysis of the data led to the identification of four major the matic categories: psychological factors; social relations; material well being; quality of life. There search results show that negatyve childhood experience, gambling friends, escaping from various troubles, disputes in family and high financial needs can increase involvement in gambling. Factors that reduce involvement in gambling are: feeling support of social environment, proper evaluation of financial position, awareness of one‘s own addiction to gambling and desire to change life.

[Multiple linear regression and ROC curve analysis of the factors of lumbar spine bone mineral density].

Science.gov (United States)

Zhang, Xiaodong; Zhao, Yinxia; Hu, Shaoyong; Hao, Shuai; Yan, Jiewen; Zhang, Lingyan; Zhao, Jing; Li, Shaolin

2015-09-01

To investigate the correlation between the lumbar vertebra bone mineral density (BMD) and age, gender, height, weight, body mass index, waistline, hipline, bone marrow and abdomen fat, and to explore the key factor affecting the BMD. A total of 72 cases were randomly recruited. All the subjects underwent a spectroscopic examination of the third lumber vertebra with single-voxel method in 1.5T MR. Lipid fractions (FF%) were measured. Quantitative CT were also performed to get the BMD of L3 and the corresponding abdomen subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT). The statistical analysis were performed by SPSS 19.0. Multiple linear regression showed except the age and FF% showed significant difference (P0.05). The correlation of age and FF% with BMD was statistically negatively significant (r=-0.830, -0.521, P<0.05). The ROC curve analysis showed that the sensitivety and specificity of predicting osteoporosis were 81.8% and 86.9%, with a threshold of 58.5 years old. And it showed that the sensitivety and specificity of predicting osteoporosis were 90.9% and 55.7%, with a threshold of 52.8% for FF%. The lumbar vertebra BMD was significantly and negatively correlated with age and bone marrow FF%, but it was not significantly correlated with gender, height, weight, BMI, waistline, hipline, SAT and VAT. And age was the critical factor.

Analysis Of Factors Affecting Demand Red Chili Pepper Capsicum Annum L In Solok And Effort Fulfillment

Directory of Open Access Journals (Sweden)

Zulfitriyana

2015-08-01

Full Text Available Research on the analysis of the factors that influence the demand for red chilli Capsicum annuum L in Solok and compliance efforts implemented in March s.d April 2016. The purpose of this study consisted of 1 analyze the factors affecting the demand for red chili in Solok 2 analyze the elasticity of demand for red chili in Solok 3 know the effort that can be done to meet the demand of red chilli in Solok. To achieve the objectives of the first and second use secondary data for 15 fifteen years and to achieve the objectives the third used primary data. The method used is descriptive analytical method a method that is used to describe phenomena that exist which takes place in the present or past. The variables were observed in this study is the X1 price of red chilli X2 the price of green chili X3 onion prices X4 population X5 income and Y the number of requests red chili which is then analyzed by multiple linear regression elasticity of demand and SWOT. The results of that research addressing the factors that influence the demand for red chili in Solok is the price of red chilli itself the price of green chili as a substitute goods the number of population and income while onion prices affect the amount of red chili demand in Solok. But simultaneously variable X1 red chili prices X2 the price of green chili X3 onion prices X4 population and X5 income strongly influence demand red chili in Solok where the F test results show that F count F table 212.262 3600 with a significance level 0.000 0.010 and the most influential variable is the variable X4 population with the greatest value of beta Coefficients is 1100. Based on analysis of the elasticity of demand is known that red chili pepper is a normal good is inelastic to price elasticity coefficient value amp603p of -0.120. Green chili is substituting goods and shallots are complements of red chili with cross elasticity coefficient amp603px1 and amp603px2 respectively by 0293 and -0.635. While the

Identifying influential factors of business process performance using dependency analysis

Science.gov (United States)

Wetzstein, Branimir; Leitner, Philipp; Rosenberg, Florian; Dustdar, Schahram; Leymann, Frank

2011-02-01

We present a comprehensive framework for identifying influential factors of business process performance. In particular, our approach combines monitoring of process events and Quality of Service (QoS) measurements with dependency analysis to effectively identify influential factors. The framework uses data mining techniques to construct tree structures to represent dependencies of a key performance indicator (KPI) on process and QoS metrics. These dependency trees allow business analysts to determine how process KPIs depend on lower-level process metrics and QoS characteristics of the IT infrastructure. The structure of the dependencies enables a drill-down analysis of single factors of influence to gain a deeper knowledge why certain KPI targets are not met.

Reduced angiogenic factor expression in intrauterine fetal growth restriction using semiquantitative immunohistochemistry and digital image analysis.

Science.gov (United States)

Alahakoon, Thushari I; Zhang, Weiyi; Arbuckle, Susan; Zhang, Kewei; Lee, Vincent

2018-05-01

To localize, quantify and compare angiogenic factors, vascular endothelial growth factor (VEGF), placental growth factor (PlGF), as well as their receptors fms-like tyrosine kinase receptor (Flt-1) and kinase insert domain receptor (KDR) in the placentas of normal pregnancy and complications of preeclampsia (PE), intrauterine fetal growth restriction (IUGR) and PE + IUGR. In a prospective cross-sectional case-control study, 30 pregnant women between 24-40 weeks of gestation, were recruited into four clinical groups. Representative placental samples were stained for VEGF, PlGF, Flt-1 and KDR. Analysis was performed using semiquantitative methods and digital image analysis. The overall VEGF and Flt-1 were strongly expressed and did not show any conclusive difference in the expression between study groups. PlGF and KDR were significantly reduced in expression in the placentas from pregnancies complicated by IUGR compared with normal and preeclamptic pregnancies. The lack of PlGF and KDR may be a cause for the development of IUGR and may explain the loss of vasculature and villous architecture in IUGR. Automated digital image analysis software is a viable alternative method to the manual reading of placental immunohistochemical staining. © 2018 Japan Society of Obstetrics and Gynecology.

Confirmatory Factor Analysis of the WISC-III with Child Psychiatric Inpatients.

Science.gov (United States)

Tupa, David J.; Wright, Margaret O'Dougherty; Fristad, Mary A.

1997-01-01

Factor models of the Wechsler Intelligence Scale for Children-Third Edition (WISC-III) for one, two, three, and four factors were tested using confirmatory factor analysis with a sample of 177 child psychiatric inpatients. The four-factor model proposed in the WISC-III manual provided the best fit to the data. (SLD)

Talking with TV shows

DEFF Research Database (Denmark)

Sandvik, Kjetil; Laursen, Ditte

2014-01-01

User interaction with radio and television programmes is not a new thing. However, with new cross-media production concepts such as X Factor and Voice, this is changing dramatically. The second-screen logic of these productions encourages viewers, along with TV’s traditional one-way communication...... mode, to communicate on interactive (dialogue-enabling) devices such as laptops, smartphones and tablets. Using the TV show Voice as our example, this article shows how the technological and situational set-up of the production invites viewers to engage in new ways of interaction and communication...

Factors that Affect Poverty Areas in North Sumatera Using Discriminant Analysis

Science.gov (United States)

Nasution, D. H.; Bangun, P.; Sitepu, H. R.

2018-04-01

In Indonesia, especially North Sumatera, the problem of poverty is one of the fundamental problems that become the focus of government both central and local government. Although the poverty rate decreased but the fact is there are many people who are poor. Poverty happens covers several aspects such as education, health, demographics, and also structural and cultural. This research will discuss about several factors such as population density, Unemployment Rate, GDP per capita ADHK, ADHB GDP per capita, economic growth and life expectancy that affect poverty in Indonesia. To determine the factors that most influence and differentiate the level of poverty of the Regency/City North Sumatra used discriminant analysis method. Discriminant analysis is one multivariate analysis technique are used to classify the data into a group based on the dependent variable and independent variable. Using discriminant analysis, it is evident that the factor affecting poverty is Unemployment Rate.

Validation of the Malay Version of the Parental Bonding Instrument among Malaysian Youths Using Exploratory Factor Analysis

Science.gov (United States)

MUHAMMAD, Noor Azimah; SHAMSUDDIN, Khadijah; OMAR, Khairani; SHAH, Shamsul Azhar; MOHD AMIN, Rahmah

2014-01-01

Background: Parenting behaviour is culturally sensitive. The aims of this study were (1) to translate the Parental Bonding Instrument into Malay (PBI-M) and (2) to determine its factorial structure and validity among the Malaysian population. Methods: The PBI-M was generated from a standard translation process and comprehension testing. The validation study of the PBI-M was administered to 248 college students aged 18 to 22 years. Results: Participants in the comprehension testing had difficulty understanding negative items. Five translated double negative items were replaced with five positive items with similar meanings. Exploratory factor analysis showed a three-factor model for the PBI-M with acceptable reliability. Four negative items (items 3, 4, 8, and 16) and item 19 were omitted from the final PBI-M list because of incorrect placement or low factor loading (overprotection factor. All the items loaded positively on their respective factors. Conclusion: The Malaysian population favoured positive items in answering questions. The PBI-M confirmed the three-factor model that consisted of care, autonomy and overprotection. The PBI-M is a valid and reliable instrument to assess the Malaysian parenting style. Confirmatory factor analysis may further support this finding. Keywords: Malaysia, parenting, questionnaire, validity PMID:25977634

[Analysis of Prognostic Factors and Clinical Characteristics for Patients with Limited Stage Small Cell Lung Cancer with Pleural Effusion].

Science.gov (United States)

Xu, Kunpeng; Wang, Youyou; Qi, Jing; Zhao, Lujun; Wang, Ping

2018-01-20

Malignant pleural effusion (PE) was generally defined as pleural effusion containing tumors with poor prognosis. Some kinds of undefined pleural effusions due to too small amount of effusion had poor prognosis too. This study aimed to analyze the clinical characteristics and prognostic factors of patients who suffered from limited-stage small cell lung cancer (LS-SCLC) complicated with pleural effusion. A retrospective analysis included 542 patients who were diagnosed with LS-SCLC and had treatment in our hospital from October 2007 to January 2016. We had observed 109 patients who were diagnosed with pleural effusion at their first visit to the doctor. We analyzed the clinical characters, survival time and the prognostic factors of the 109 patients. Our main observation targets were overall survival (OS) and progression free survival (PFS). The median OS and PFS of whole group were 29.4 and 18.2 months. Before treatment, survival time of patients with PE were significantly shorter than patients without PE (median OS: 21.0 vs 31.7 months; median PFS: 14.1 vs 9.1 months; Log-rank, P=0.001, P=0.014). Multi-factor analysis of multivariate Cox shows PE was the independent prognostic factor of LS-SCLC (P=0.04). Single factor analysis showed factors affecting PE patient's survival time included clinical stages, lymph node (LN) stages, KPS scores, pulmonary atelectasis and the state of pleural after treatment. Cox multi-factor analysis reminded that the state of pleural effusion after treatment was the independent prognostic factor of LS-SCLC complicated with pleural effusion (P=0.016). There were three groups was apportioned patients without pleural effusion before treatment (group 1; n=433), patients whose pleural effusion disappeared after treatment (group 2; n=67) and patients whose pleural effusion didn't disappear after treatment (group 3; n=32).The median OS were 31.7, 23.2, 16.8 months in the group 1, 2, 3 and the median PFS were 19.1, 17.9, 11.4 months. Obvious

Seismic analysis response factors and design margins of piping systems

International Nuclear Information System (INIS)

Shieh, L.C.; Tsai, N.C.; Yang, M.S.; Wong, W.L.

1985-01-01

The objective of the simplified methods project of the Seismic Safety Margins Research Program is to develop a simplified seismic risk methodology for general use. The goal is to reduce seismic PRA costs to roughly 60 man-months over a 6 to 8 month period, without compromising the quality of the product. To achieve the goal, it is necessary to simplify the calculational procedure of the seismic response. The response factor approach serves this purpose. The response factor relates the median level response to the design data. Through a literature survey, we identified the various seismic analysis methods adopted in the U.S. nuclear industry for the piping system. A series of seismic response calculations was performed. The response factors and their variabilities for each method of analysis were computed. A sensitivity study of the effect of piping damping, in-structure response spectra envelop method, and analysis method was conducted. In addition, design margins, which relate the best-estimate response to the design data, are also presented

Psychometric properties of the Spanish version of the UPPS-P Impulsive Behavior Scale: A Rasch rating scale analysis and confirmatory factor analysis.

Science.gov (United States)

Pilatti, Angelina; Lozano, Oscar M; Cyders, Melissa A

2015-12-01

The present study was aimed at determining the psychometric properties of the Spanish version of the UPPS-P Impulsive Behavior Scale in a sample of college students. Participants were 318 college students (36.2% men; mean age = 20.9 years, SD = 6.4 years). The psychometric properties of this Spanish version were analyzed using the Rasch model, and the factor structure was examined using confirmatory factor analysis. The verification of the global fit of the data showed adequate indexes for persons and items. The reliability estimates were high for both items and persons. Differential item functioning across gender was found for 23 items, which likely reflects known differences in impulsivity levels between men and women. The factor structure of the Spanish version of the UPPS-P replicates previous work with the original UPPS-P Scale. Overall, results suggest that test scores from the Spanish version of the UPPS-P show adequate psychometric properties to accurately assess the multidimensional model of impulsivity, which represents the most exhaustive measure of this construct. (c) 2015 APA, all rights reserved).

A Third Moment Adjusted Test Statistic for Small Sample Factor Analysis.

Science.gov (United States)

Lin, Johnny; Bentler, Peter M

2012-01-01

Goodness of fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square; but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne's asymptotically distribution-free method and Satorra Bentler's mean scaling statistic were developed under the presumption of non-normality in the factors and errors. This paper finds new application to the case where factors and errors are normally distributed in the population but the skewness of the obtained test statistic is still high due to sampling error in the observed indicators. An extension of Satorra Bentler's statistic is proposed that not only scales the mean but also adjusts the degrees of freedom based on the skewness of the obtained test statistic in order to improve its robustness under small samples. A simple simulation study shows that this third moment adjusted statistic asymptotically performs on par with previously proposed methods, and at a very small sample size offers superior Type I error rates under a properly specified model. Data from Mardia, Kent and Bibby's study of students tested for their ability in five content areas that were either open or closed book were used to illustrate the real-world performance of this statistic.

The human factors and job task analysis in nuclear power plant operation

International Nuclear Information System (INIS)

Stefanescu, Petre; Mihailescu, Nicolae; Dragusin, Octavian

1999-01-01

After a long period of time, during the development of the NPP technology, where the plant hardware has been considered to be the main factor for a safe, reliable and economic operation, the industry is now changing to an adequate responsibility of plant hardware and operation. Since the human factors has been not discussed methodically so far, there is still a lack of improved classification systems for human errors as well as a lack of methods for the systematic approach in designing the operator's working system, as for instance by using the job task analysis (J.T.A.). The J.T.A. appears to be an adequate method to study the human factor in the nuclear power plant operation, enabling an easy conversion to operational improvements. While the results of the analysis of human errors tell 'what' is to be improved, the J.T.A. shows 'how' to improve, for increasing the quality of the work and the safety of the operator's working system. The paper analyses the issue of setting the task and displays four criteria used to select aspects in NPP operation which require special consideration as personal training, design of control room, content and layout of the procedure manual, or organizing the operating personnel. The results are given as three tables giving: 1- Evaluation of deficiencies in the Working System; 2- Evaluation of the Deficiencies of Operator's Disposition; 3- Evaluation of the Mental Structure of Operation

Logistic Regression and Path Analysis Method to Analyze Factors influencing Students’ Achievement

Science.gov (United States)

Noeryanti, N.; Suryowati, K.; Setyawan, Y.; Aulia, R. R.

2018-04-01

Students' academic achievement cannot be separated from the influence of two factors namely internal and external factors. The first factors of the student (internal factors) consist of intelligence (X1), health (X2), interest (X3), and motivation of students (X4). The external factors consist of family environment (X5), school environment (X6), and society environment (X7). The objects of this research are eighth grade students of the school year 2016/2017 at SMPN 1 Jiwan Madiun sampled by using simple random sampling. Primary data are obtained by distributing questionnaires. The method used in this study is binary logistic regression analysis that aims to identify internal and external factors that affect student’s achievement and how the trends of them. Path Analysis was used to determine the factors that influence directly, indirectly or totally on student’s achievement. Based on the results of binary logistic regression, variables that affect student’s achievement are interest and motivation. And based on the results obtained by path analysis, factors that have a direct impact on student’s achievement are students’ interest (59%) and students’ motivation (27%). While the factors that have indirect influences on students’ achievement, are family environment (97%) and school environment (37).

Analysis of Factors Related to Hypopituitarism in Patients with Nonsellar Intracranial Tumor.

Science.gov (United States)

Lu, Song-Song; Gu, Jian-Jun; Luo, Xiao-Hong; Zhang, Jian-He; Wang, Shou-Sen

2017-09-01

Previous studies have suggested that postoperative hypopituitarism in patients with nonsellar intracranial tumors is caused by traumatic surgery. However, with development of minimally invasive and precise neurosurgical techniques, the degree of injury to brain tissue has been reduced significantly, especially for parenchymal tumors. Therefore, understanding preexisting hypopituitarism and related risk factors can improve perioperative management for patients with nonsellar intracranial tumors. Chart data were collected retrospectively from 83 patients with nonsellar intracranial tumors admitted to our hospital from May 2014 to April 2015. Pituitary function of each subject was determined based on results of preoperative serum pituitary hormone analysis. Univariate and multivariate logistic regression methods were used to analyze relationships between preoperative hypopituitarism and factors including age, sex, history of hypertension and secondary epilepsy, course of disease, tumor mass effect, site of tumor, intracranial pressure (ICP), cerebrospinal fluid content, and pituitary morphology. A total of 30 patients (36.14%) presented with preoperative hypopituitarism in either 1 axis or multiple axes; 23 (27.71%) were affected in 1 axis, and 7 (8.43%) were affected in multiple axes. Univariate analysis showed that risk factors for preoperative hypopituitarism in patients with a nonsellar intracranial tumor include an acute or subacute course (≤3 months), intracranial hypertension (ICP >200 mm H 2 O), and mass effect (P hypopituitarism in patients with nonsellar intracranial tumors (P hypopituitarism is high in patients with nonsellar intracranial tumors. The occurrence of hypopituitarism is correlated with factors including an acute or subacute course (≤3 months), intracranial hypertension (ICP >200 mm H 2 O), and mass effect (P hypopituitarism. Copyright © 2017 Elsevier Inc. All rights reserved.

Confirmatory Factor Analysis of the Delirium Rating Scale Revised-98 (DRS-R98).

Science.gov (United States)

Thurber, Steven; Kishi, Yasuhiro; Trzepacz, Paula T; Franco, Jose G; Meagher, David J; Lee, Yanghyun; Kim, Jeong-Lan; Furlanetto, Leticia M; Negreiros, Daniel; Huang, Ming-Chyi; Chen, Chun-Hsin; Kean, Jacob; Leonard, Maeve

2015-01-01

Principal components analysis applied to the Delirium Rating Scale-Revised-98 contributes to understanding the delirium construct. Using a multisite pooled international delirium database, the authors applied confirmatory factor analysis to Delirium Rating Scale-Revised-98 scores from 859 adult patients evaluated by delirium experts (delirium, N=516; nondelirium, N=343). Confirmatory factor analysis found all diagnostic features and core symptoms (cognitive, language, thought process, sleep-wake cycle, motor retardation), except motor agitation, loaded onto factor 1. Motor agitation loaded onto factor 2 with noncore symptoms (delusions, affective lability, and perceptual disturbances). Factor 1 loading supports delirium as a single construct, but when accompanied by psychosis, motor agitation's role may not be solely as a circadian activity indicator.

Towards automatic analysis of dynamic radionuclide studies using principal-components factor analysis

International Nuclear Information System (INIS)

Nigran, K.S.; Barber, D.C.

1985-01-01

A method is proposed for automatic analysis of dynamic radionuclide studies using the mathematical technique of principal-components factor analysis. This method is considered as a possible alternative to the conventional manual regions-of-interest method widely used. The method emphasises the importance of introducing a priori information into the analysis about the physiology of at least one of the functional structures in a study. Information is added by using suitable mathematical models to describe the underlying physiological processes. A single physiological factor is extracted representing the particular dynamic structure of interest. Two spaces 'study space, S' and 'theory space, T' are defined in the formation of the concept of intersection of spaces. A one-dimensional intersection space is computed. An example from a dynamic 99 Tcsup(m) DTPA kidney study is used to demonstrate the principle inherent in the method proposed. The method requires no correction for the blood background activity, necessary when processing by the manual method. The careful isolation of the kidney by means of region of interest is not required. The method is therefore less prone to operator influence and can be automated. (author)

BIOMETRICAL ANALYSIS OF ARABIAN FOALS AND THEIR LATER SUCCESSES IN SHOWS AND ON RACE TRACK

Directory of Open Access Journals (Sweden)

M. PIESZKA

2007-10-01

Full Text Available Arabian horses are one of the most important products of Polish horse breeding.Many of them are International and World champions in shows; others are very wellknown as courageous race horses. To obtain such champions it is necessary to takeunder consideration many factors affecting the final results. The objective of thisstudy was to evaluate the effect of biometrical measurements of the foals at birthaccording to their future successes in shows and on racetrack. The study was carriedout on 143 horses winning in shows and in races. Body weight, height at withers,girth and canon circumferences taken at birth of these horses were analysed.Additionally coat colour was studied. All studied animals were divided into threegroups according to each measurement and the differences between such groupswere evaluated according points obtained for particular place at shows and place inraces. It was stated that horses heavier at birth and with higher girth circumferencegot more successes both at shows and on racetrack. Horses with higher height atwithers at birth were more successful in shows while animals with higher canoncircumference won oftener at race track. It was observed that the most courageousrace horses were bay while most champions were grey.

Interactions between toxic chemicals and natural environmental factors--a meta-analysis and case studies.

Science.gov (United States)

Laskowski, Ryszard; Bednarska, Agnieszka J; Kramarz, Paulina E; Loureiro, Susana; Scheil, Volker; Kudłek, Joanna; Holmstrup, Martin

2010-08-15

The paper addresses problems arising from effects of natural environmental factors on toxicity of pollutants to organisms. Most studies on interactions between toxicants and natural factors, including those completed in the EU project NoMiracle (Novel Methods for Integrated Risk Assessment of Cumulative Stressors in Europe) described herein, showed that effects of toxic chemicals on organisms can differ vastly depending purely on external conditions. We compiled data from 61 studies on effects of temperature, moisture and dissolved oxygen on toxicity of a range of chemicals representing pesticides, polycyclic aromatic hydrocarbons, plant protection products of bacterial origin and trace metals. In 62.3% cases significant interactions (pnatural factors and chemicals were found, reaching 100% for the effect of dissolved oxygen on toxicity of waterborne chemicals. The meta-analysis of the 61 studies showed that the null hypothesis assuming no interactions between toxic chemicals and natural environmental factors should be rejected at p=2.7 x 10(-82) (truncated product method probability). In a few cases of more complex experimental designs, also second-order interactions were found, indicating that natural factors can modify interactions among chemicals. Such data emphasize the necessity of including information on natural factors and their variation in time and across geographic regions in ecological risk assessment. This can be done only if appropriate ecotoxicological test designs are used, in which test organisms are exposed to toxicants at a range of environmental conditions. We advocate designing such tests for the second-tier ecological risk assessment procedures. Copyright 2010 Elsevier B.V. All rights reserved.

Risk Factor Analysis for Mastectomy Skin Flap Necrosis: Implications for Intraoperative Vascular Analysis.

Science.gov (United States)

Reintgen, Christian; Leavitt, Adam; Pace, Elizabeth; Molas-Pierson, Justine; Mast, Bruce A

2016-06-01

Skin flap necrosis after mastectomy can be a devastating complication significantly affecting patient outcomes. Routine vascular analysis (fluorescein or laser angiography) of mastectomy skin flaps in all patients has been advocated but is of questionable cost-effectiveness. The purpose of this study was to identify the incidence and causative risk factors for mastectomy skin flap necrosis and thereby calculate the fiscal reality of intraoperative vascular screening. This is an institutional review board-approved retrospective study of all patients from 2007 to 2013 who underwent mastectomy related to breast cancer. Skin flap necrosis was defined as major if it necessitated return to the operating room. Data analysis was done for determination of causative factors of necrosis, including age, body mass index, smoking, previous irradiation, coronary artery disease, chronic obstructive pulmonary disorder, hypertension, gastroesophageal reflux disease, hyperlipidemia, obstructive sleep apnea, asthma, diabetes, thyroid disease, history of lumpectomy, and breast reduction or augmentation. During this time, intraoperative vascular screening was not done. Five hundred eighty-one patients underwent 616 mastectomies with a total of 34 necrotic events (5.5%)-16 major and 18 minor. Analyses via Student t tests, univariate analyses, χ testing, and logistic regression showed that history of smoking was the only patient factor associated with postoperative necrosis (P = 0.008). More frequently represented in the necrosis group, but without statistical significance, are previous lumpectomy (P = 0.069) and immediate reconstruction (P = 0.078).For the entire study period, the actual cost to the hospital for major necrotic events was $7,123.10 or $445.19 for each of the 16 major necrotic events and $209.50 for all 34 necrotic events. Per-patient cost-effective screening would need to be less than $11.54 for all patients, $100.33 for highest risk patients (smokers), and $21.65 for

Improving Your Exploratory Factor Analysis for Ordinal Data: A Demonstration Using FACTOR

Directory of Open Access Journals (Sweden)

James Baglin

2014-06-01

Full Text Available Exploratory factor analysis (EFA methods are used extensively in the field of assessment and evaluation. Due to EFA's widespread use, common methods and practices have come under close scrutiny. A substantial body of literature has been compiled highlighting problems with many of the methods and practices used in EFA, and, in response, many guidelines have been proposed with the aim to improve application. Unfortunately, implementing recommended EFA practices has been restricted by the range of options available in commercial statistical packages and, perhaps, due to an absence of clear, practical - how-to' demonstrations. Consequently, this article describes the application of methods recommended to get the most out of your EFA. The article focuses on dealing with the common situation of analysing ordinal data as derived from Likert-type scales. These methods are demonstrated using the free, stand-alone, easy-to-use and powerful EFA package FACTOR (http://psico.fcep.urv.es/utilitats/factor/, Lorenzo-Seva & Ferrando, 2006. The demonstration applies the recommended techniques using an accompanying dataset, based on the Big 5 personality test. The outcomes obtained by the EFA using the recommended procedures through FACTOR are compared to the default techniques currently available in SPSS.

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.

The scientific use of factor analysis in behavioral and life sciences

National Research Council Canada - National Science Library

Cattell, Raymond Bernard

1978-01-01

...; the choice of procedures in experimentation; factor interpretation; the relationship of factor analysis to broadened psychometric concepts such as scaling, validity, and reliability, and to higher- strata models...

Bayes factor design analysis: Planning for compelling evidence.

Science.gov (United States)

Schönbrodt, Felix D; Wagenmakers, Eric-Jan

2018-02-01

A sizeable literature exists on the use of frequentist power analysis in the null-hypothesis significance testing (NHST) paradigm to facilitate the design of informative experiments. In contrast, there is almost no literature that discusses the design of experiments when Bayes factors (BFs) are used as a measure of evidence. Here we explore Bayes Factor Design Analysis (BFDA) as a useful tool to design studies for maximum efficiency and informativeness. We elaborate on three possible BF designs, (a) a fixed-n design, (b) an open-ended Sequential Bayes Factor (SBF) design, where researchers can test after each participant and can stop data collection whenever there is strong evidence for either [Formula: see text] or [Formula: see text], and (c) a modified SBF design that defines a maximal sample size where data collection is stopped regardless of the current state of evidence. We demonstrate how the properties of each design (i.e., expected strength of evidence, expected sample size, expected probability of misleading evidence, expected probability of weak evidence) can be evaluated using Monte Carlo simulations and equip researchers with the necessary information to compute their own Bayesian design analyses.

Study of Sesame (Sesame indicum L. Cultivars based on Morphological Characteristics Under Water Deficit Stress Condition Using Factor Analysis

Directory of Open Access Journals (Sweden)

A Asghari

2014-03-01

Full Text Available In order to evaluation sesame cultivars based on morphological characteristics under water deficit stress condition using factor analysis, an experiment was conducted as a split plot based on randomized complete block design with three replications during 2009 in Research Center of Agriculture and Natural Resources in Parsabad. In this experiment, irrigation as the main factor at three levels (50, 75 and 100 percent of crop water requirement and ten sesame cultivars as the sub-factor were studied. The water requirement of sesame was calculated using CROPWAT software (Penman-Monteith method according to FAO-56. Results showed significant differences between the cultivars and the irrigation levels for all studied traits. Interaction between cultivars and irrigation levels was significant for some of traits. Comparisons of means showed that in water deficit condition, yield and all of traits reduced. In all traits the greatest amounts observed in complete irrigation treatment. In 50 percent of water requirement treatment, amount of leaf chlorophyll, root length, root branches and root length/plant height ratio were greater than other treatments. The Karaj1, Ultan, Naze and IS cultivars were better than other cultivars in stress and non stress condition. In factor analysis 5 and 4 first factors in non stress and stress condition explained 91.36 and 89.52 percent of trait variance, respectively. Grouping of sesame cultivars based on first and second factors in non stress conditions showed that Karaj1, Ultan and Naze cultivars were better than other cultivars. Also, in stress conditions Karaj1 and Ultan cultivars grouped as water deficit stress and better cultivars.

Directional Variance Adjustment: Bias Reduction in Covariance Matrices Based on Factor Analysis with an Application to Portfolio Optimization

Science.gov (United States)

Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W.; Müller, Klaus-Robert; Lemm, Steven

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation. PMID:23844016

Directional variance adjustment: bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization.

Directory of Open Access Journals (Sweden)

Daniel Bartz

Full Text Available Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation.

Eastern minds in western cockpits: meta-analysis of human factors in mishaps from three nations.

Science.gov (United States)

Li, Wen-Chin; Harris, Don; Chen, Aurora

2007-04-01

Aviation accident rates vary in different regions; Asia and Africa have higher rates than Europe and America. There has been a great deal of discussion about the role of culture in aviation mishaps; however, culture is rarely mentioned as a contributory factor in accidents. It is hypothesized that different cultures will show different patterns in the underlying causal factors in aircraft accidents. Using a meta-analysis of previously published results, this research examined statistical differences in the 18 categories of the Human Factors Analysis and Classification System (HFACS) across accidents in the Republic of China (Taiwan), India, and the United States. Seven HFACS categories exhibited significant differences between these three regions. These were mostly concerned with contributory factors at the higher organizational levels. The differences were related to organizational processes, organizational climate, resource management, inadequate supervision, physical/mental limitations, adverse mental states, and decision errors. Overall, the evidence from this research supports the observation that national cultures have an impact on aviation safety and adds further explanatory power with regards to why this should be so. The majority of the cultural issues identified seem to be associated with the style of management of the organizations rather than the operation of the aircraft per se.

A Comparative Analysis of Ability of Mimicking Portfolios in Representing the Background Factors

OpenAIRE

Asgharian, Hossein

2004-01-01

Our aim is to give a comparative analysis of ability of different factor mimicking portfolios in representing the background factors. Our analysis contains a cross-sectional regression approach, a time-series regression approach and a portfolio approach for constructing factor mimicking portfolios. The focus of the analysis is the power of mimicking portfolios in the asset pricing models. We conclude that the time series regression approach, with the book-to-market sorted portfolios as the ba...

Methods of selecting factors in the analysis of the real estates market

OpenAIRE

Jasińska, Elżbieta; Preweda, Edward

2006-01-01

In the paper the problem of selecting the method of choosing factors in factorial analysis is presented. For the database of 61 real estates the process of singling out the factors was carried out with the use of all the methods proposed in the STATISTICA 6.0 pack. A particular attention was paid on the number of differentiated factors and the efficiency of subsequent methods for the analysis of the real estates market. Edward Preweda

Liquidity indicator for the Croatian economy – Factor analysis approach

Directory of Open Access Journals (Sweden)

Mirjana Čižmešija

2014-12-01

Full Text Available Croatian business surveys (BS are conducted in the manufacturing industry, retail trade and construction sector. In all of these sectors, manager´s assessments of liquidity are measured. The aim of the paper was to form a new composite liquidity indicator by including business survey liquidity measures from all three covered economic sectors in the Croatian economy mentioned above. In calculating the leading indicator, a factor analysis approach was used. However, this kind of indicator does not exist in a Croatia or in any other European economy. Furthermore, the issue of Croatian companies´ illiquidity is highly neglected in the literature. The empirical analysis consists of two parts. In the first part the new liquidity indicator was formed using factor analysis. One factor (representing the new liquidity indicator; LI was extracted out of the three liquidity variables in three economic sectors. This factor represents the new liquidity indicator. In the second part, econometric models were applied in order to investigate the forecasting properties of the new business survey liquidity indicator, when predicting the direction of changes in Croatian industrial production. The quarterly data used in the research covered the period from January 2000 to April 2013. Based on econometric analysis, it can be concluded that the LI is a leading indicator of Croatia’s industrial production with better forecasting properties then the standard liquidity indicators (formed in a manufacturing industry.

Analysis of nasopharyngeal carcinoma risk factors with Bayesian networks.

Science.gov (United States)

Aussem, Alex; de Morais, Sérgio Rodrigues; Corbex, Marilys

2012-01-01

We propose a new graphical framework for extracting the relevant dietary, social and environmental risk factors that are associated with an increased risk of nasopharyngeal carcinoma (NPC) on a case-control epidemiologic study that consists of 1289 subjects and 150 risk factors. This framework builds on the use of Bayesian networks (BNs) for representing statistical dependencies between the random variables. We discuss a novel constraint-based procedure, called Hybrid Parents and Children (HPC), that builds recursively a local graph that includes all the relevant features statistically associated to the NPC, without having to find the whole BN first. The local graph is afterwards directed by the domain expert according to his knowledge. It provides a statistical profile of the recruited population, and meanwhile helps identify the risk factors associated to NPC. Extensive experiments on synthetic data sampled from known BNs show that the HPC outperforms state-of-the-art algorithms that appeared in the recent literature. From a biological perspective, the present study confirms that chemical products, pesticides and domestic fume intake from incomplete combustion of coal and wood are significantly associated with NPC risk. These results suggest that industrial workers are often exposed to noxious chemicals and poisonous substances that are used in the course of manufacturing. This study also supports previous findings that the consumption of a number of preserved food items, like house made proteins and sheep fat, are a major risk factor for NPC. BNs are valuable data mining tools for the analysis of epidemiologic data. They can explicitly combine both expert knowledge from the field and information inferred from the data. These techniques therefore merit consideration as valuable alternatives to traditional multivariate regression techniques in epidemiologic studies. Copyright © 2011 Elsevier B.V. All rights reserved.

Factor Analysis on the Factors that Influencing Rural Environmental Pollution in the Hilly Area of Sichuan Province,China

Institute of Scientific and Technical Information of China (English)

2011-01-01

By using factor analysis method and establishing analysis indicator system from four aspects including crop production,poultry farming,rural life and township enterprises,the difference,features,and types of factors influencing the rural environmental pollution in the hilly area in Sichuan Province,China.Results prove that the major factor influencing rural environmental pollution in the study area is livestock and poultry breeding,flowed by crop planting,rural life,and township enterprises.Hence future pollution prevention and control should set about from livestock and poultry breeding.Meanwhile,attention should be paid to the prevention and control of rural environmental pollution caused by rural life and township enterprise production.

Absorption correction factor in X-ray fluorescent quantitative analysis

International Nuclear Information System (INIS)

Pimjun, S.

1994-01-01

An experiment on absorption correction factor in X-ray fluorescent quantitative analysis were carried out. Standard samples were prepared from the mixture of Fe 2 O 3 and tapioca flour at various concentration of Fe 2 O 3 ranging from 5% to 25%. Unknown samples were kaolin containing 3.5% to-50% of Fe 2 O 3 Kaolin samples were diluted with tapioca flour in order to reduce the absorption of FeK α and make them easy to prepare. Pressed samples with 0.150 /cm 2 and 2.76 cm in diameter, were used in the experiment. Absorption correction factor is related to total mass absorption coefficient (χ) which varied with sample composition. In known sample, χ can be calculated by conveniently the formula. However in unknown sample, χ can be determined by Emission-Transmission method. It was found that the relationship between corrected FeK α intensity and contents of Fe 2 O 3 in these samples was linear. This result indicate that this correction factor can be used to adjust the accuracy of X-ray intensity. Therefore, this correction factor is essential in quantitative analysis of elements comprising in any sample by X-ray fluorescent technique

Validating the Farsi version of the Pregnancy Worries and Stress Questionnaire (PWSQ): An exploratory factor analysis.

Science.gov (United States)

Navidpour, Fariba; Dolatian, Mahrokh; Shishehgar, Sara; Yaghmaei, Farideh; Majd, Hamid Alavi; Hashemi, Seyed Saeed

2016-10-01

Biological, environmental, inter- and intrapersonal changes during the antenatal period can result in anxiety and stress in pregnant women. It is pivotal to identify potential stressors and prevent their foetal and maternal consequences. The present study was conducted to validate and examine the factor structure of the Farsi version of the Pregnancy Worries and Stress Questionnaire (PWSQ). In 2015, 502 Iranian healthy pregnant women, referred to selected hospitals in Tehran for prenatal care at 8-39 weeks of pregnancy, were recruited through a randomized cluster sampling. The PWSQ was translated into Farsi, and its validity and reliability were examined using exploratory factor analysis by SPSS version 21. The content validity of items on the PWSQ was between 0.63-1. The content validity index for relevance, clarity and simplicity were 0.92, 0.98, and 0.98, respectively, with a mean of 0.94. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.863. Test-retest reliability showed high internal consistency (α=0.89; p<0.0001). The psychometric evaluation and exploratory factor analysis showed that the translated questionnaire is a valid and reliable tool to identify stress in Iranian pregnant women. Application of the questionnaire can facilitate the diagnosis of stress in pregnant women and assist health care providers in providing timely support and minimizing negative outcomes of stress and anxiety in pregnant women and their infants.

Dietary patterns and cardiometabolic risk factors among adolescents: systematic review and meta-analysis.

Science.gov (United States)

Cunha, Carla de Magalhães; Costa, Priscila R F; de Oliveira, Lucivalda P M; Queiroz, Valterlinda A de O; Pitangueira, Jacqueline C D; Oliveira, Ana Marlúcia

2018-04-01

This study systematised and synthesised the results of observational studies that were aimed at supporting the association between dietary patterns and cardiometabolic risk (CMR) factors among adolescents. Relevant scientific articles were searched in PUBMED, EMBASE, SCIENCE DIRECT, LILACS, WEB OF SCIENCE and SCOPUS. Observational studies that included the measurement of any CMR factor in healthy adolescents and dietary patterns were included. The search strategy retained nineteen articles for qualitative analysis. Among retained articles, the effects of dietary pattern on the means of BMI (n 18), waist circumference (WC) (n 9), systolic blood pressure (n 7), diastolic blood pressure (n 6), blood glucose (n 5) and lipid profile (n 5) were examined. Systematised evidence showed that an unhealthy dietary pattern appears to be associated with poor mean values of CMR factors among adolescents. However, evidence of a protective effect of healthier dietary patterns in this group remains unclear. Considering the number of studies with available information, a meta-analysis of anthropometric measures showed that dietary patterns characterised by the highest intake of unhealthy foods resulted in a higher mean BMI (0·57 kg/m²; 95 % CI 0·51, 0·63) and WC (0·57 cm; 95 % CI 0·47, 0·67) compared with low intake of unhealthy foods. Controversially, patterns characterised by a low intake of healthy foods were associated with a lower mean BMI (-0·41 kg/m²; 95 % CI -0·46,-0·36) and WC (-0·43 cm; 95 % CI -0·52,-0·33). An unhealthy dietary pattern may influence markers of CMR among adolescents, but considering the small number and limitations of the studies included, further studies are warranted to strengthen the evidence of this relation.

Meta-Analysis of Selected Maternal and Fetal Factors for Perinatal ...

African Journals Online (AJOL)

BACKGROUND: In several developing countries, achieving Millennium Development Goal 4 is still off track. Multiple maternal and fetal risk factors were inconsistently attributed to the high perinatal mortality in developing countries. However, there was no meta-analysis that assessed the pooled effect of these factors on ...

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

Directory of Open Access Journals (Sweden)

Maryam Kheirollahpour

2014-01-01

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

Risk factor analysis of equine strongyle resistance to anthelmintics

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G. Sallé

2017-12-01

Full Text Available Intestinal strongyles are the most problematic endoparasites of equids as a result of their wide distribution and the spread of resistant isolates throughout the world. While abundant literature can be found on the extent of anthelmintic resistance across continents, empirical knowledge about associated risk factors is missing. This study brought together results from anthelmintic efficacy testing and risk factor analysis to provide evidence-based guidelines in the field. It involved 688 horses from 39 French horse farms and riding schools to both estimate Faecal Egg Count Reduction (FECR after anthelmintic treatment and to interview farm and riding school managers about their practices. Risk factors associated with reduced anthelmintic efficacy in equine strongyles were estimated across drugs using a marginal modelling approach. Results demonstrated ivermectin efficacy (96.3% ± 14.5% FECR, the inefficacy of fenbendazole (42.8% ± 33.4% FECR and an intermediate profile for pyrantel (90.3% ± 19.6% FECR. Risk factor analysis provided support to advocate for FEC-based treatment regimens combined with individual anthelmintic dosage and the enforcement of tighter biosecurity around horse introduction. The combination of these measures resulted in a decreased risk of drug resistance (relative risk of 0.57, p = 0.02. Premises falling under this typology also relied more on their veterinarians suggesting practitionners play an important role in the sustainability of anthelmintic usage. Similarly, drug resistance risk was halved in premises with frequent pasture rotation and with stocking rate below five horses/ha (relative risk of 0.53, p < 0.01. This is the first empirical risk factor analysis for anthelmintic resistance in equids. Our findings should guide the implementation of more sustained strongyle management in the field. Keywords: Horse, Nematode, Anthelmintic resistance, Strongyle, Cyathostomin

Factor analysis for the adoption of nuclear technology in diagnosis and treatment of chronic diseases

International Nuclear Information System (INIS)

Sato, Renato Cesar; Zouain, Desiree Moraes

2012-01-01

To identify and evaluate latent variables (variables that are not directly observed) for adopting and using nuclear technologies in diagnosis and treatment of chronic diseases. The measurement and management of these latent factors are important for health care due to complexities of the sector. Methods: An exploratory factor analysis study was conducted among 52 physicians practicing in the areas of Cardiology, Neurology and Oncology in the State of Sao Paulo who agreed to participate in the study between 2009 and 2010. Data were collected using an attitude measurement questionnaire, and analyzed according to the principal component method with Varimax rotation. Results: The component matrix after factor rotation showed three elucidative groups arranged according to demand for nuclear technology: clinical factors, structural factors, and technological factors. Clinical factors included questionnaire answers referring to medical history, previous interventions, complexity and chronicity of the disease. Structural factors included patient age, physician's practice area, and payment ability. Technological factors included prospective growth in the use of nuclear technology and availability of services. Conclusions: The clinical factors group dimension identified in the study included patient history, prior interventions, and complexity and chronicity of the disease. This dimension is the main motivating for adopting nuclear technology in diagnosis and treatment of chronic diseases. (author)

Phylogenetic Reconstruction Shows Independent Evolutionary Origins of Mitochondrial Transcription Factors from an Ancient Family of RNA Methyltransferase Proteins.

Science.gov (United States)

Aj Harris; Goldman, Aaron David

2018-04-25

Here, we generate a robust phylogenetic framework for the rRNA adenine N(6)-methyltransferase (RAMTase) protein family that shows a more ancient and complex evolutionary history within the family than previously reported. RAMTases occur universally by descent across the three domains of life, and typical orthologs within the family perform methylation of the small subunits of ribosomal RNA (rRNA). However, within the RAMTase family, two different groups of mitochondrial transcription factors, mtTFB1 and mtTFB2, have evolved in eukaryotes through neofunctionalization. Previous phylogenetic analyses have suggested that mtTFB1 and mtTFB2 comprise sister clades that arose via gene duplication, which occurred sometime following the endosymbiosis event that produced the mitochondrion. Through dense and taxonomically broad sampling of RAMTase family members especially within bacteria, we found that these eukaryotic mitochondrial transcription factors, mtTFB1 and mtTFB2, have independent origins in phylogenetically distant clades such that their divergence most likely predates the last universal common ancestor of life. The clade of mtTFB2s comprises orthologs in Opisthokonts and the clade of mtTFB1s includes orthologs in Amoebozoa and Metazoa. Thus, we clearly demonstrate that the neofunctionalization producing the transcription factor function evolved twice independently within the RAMTase family. These results are consistent with and help to elucidate outcomes from prior experimental studies, which found that some members of mtTFB1 still perform the ancestral rRNA methylation function, and the results have broader implications for understanding the evolution of new protein functions. Our phylogenetic reconstruction is also in agreement with prior studies showing two independent origins of plastid RAMTases in Viridiplantae and other photosynthetic autotrophs. We believe that this updated phylogeny of RAMTases should provide a robust evolutionary framework for ongoing

Analysis of risk factors and morphological ultrasound image for gallbladder polyp in adults living in Busan and Gyeongnam provinces

Energy Technology Data Exchange (ETDEWEB)

An, Hyeon [Dept. of Radiology, Inje University Busan Paik Hospital, Busan (Korea, Republic of); Hwang, Chul Hwan [Dept. of Radiation Oncology, Pusan National University Hospital, Busan (Korea, Republic of); Kim, Chang Soo; Ko, Sung Jin [Dept. of Radiological Science, College of Health Sciences, Catholic University of Pusan, Busan (Korea, Republic of)

2016-09-15

This study were to evaluate risk factors of GB polpy in Busan and Gyeongnam area. This study was performed with patients by abdominal ultrasonography among the patients who came to the P hospital from January to May 2016. Among them, risk factors were analyzed on 399 people at the same time when abdominal ultrasonography and hematological test. The statistical analysis of risk factors related to the GB ployp was performed by independent t-test and chi-square test. In consider of difference verification result for calculations odds ratio about independent variables, multiple logistic regression analysis to conduct verify adequacy by calculating forecasting model from variable. As a result, GB polyp risk factors have relevance to male, HBsAg positive, triglyceride. GB polyp risk factors confirmed to male, HBsAg positive, triglyceride were calculated forecasting model and forecasting probability value. Forecasting probability sensitivity 61.0%, specificity 76.8%, ROC area under curve 0.735 showed, it confirmed validity of forecasting model. When analyzing the GB polyps morphologically, among the GB polyp types observed from abdominal ultrasonography, the hyperechoic and homogeneous pattern with neck was the largest as shown from 27.5% and two GB polyps were shown most from 38%, sizes were shown most by maximum diameter, 5 to 10mm from 53%. As a disease accompany with GB polyp showed mild fatty liver(23%), diffuse hepatopathy(21%)

Metabolic and molecular analyses of white mutant Vaccinium berries show down-regulation of MYBPA1-type R2R3 MYB regulatory factor.

Science.gov (United States)

Primetta, Anja K; Karppinen, Katja; Riihinen, Kaisu R; Jaakola, Laura

2015-09-01

MYBPA1-type R2R3 MYB transcription factor shows down-regulation in white mutant berries of Vaccinium uliginosum deficient in anthocyanins but not proanthocyanidins suggesting a role in the regulation of anthocyanin biosynthesis. Berries of the genus Vaccinium are among the best natural sources of flavonoids. In this study, the expression of structural and regulatory flavonoid biosynthetic genes and the accumulation of flavonoids in white mutant and blue-colored wild-type bog bilberry (V. uliginosum) fruits were measured at different stages of berry development. In contrast to high contents of anthocyanins in ripe blue-colored berries, only traces were detected by HPLC-ESI-MS in ripe white mutant berries. However, similar profile and high levels of flavonol glycosides and proanthocyanidins were quantified in both ripe white and ripe wild-type berries. Analysis with qRT-PCR showed strong down-regulation of structural genes chalcone synthase (VuCHS), dihydroflavonol 4-reductase (VuDFR) and anthocyanidin synthase (VuANS) as well as MYBPA1-type transcription factor VuMYBPA1 in white berries during ripening compared to wild-type berries. The profiles of transcript accumulation of chalcone isomerase (VuCHI), anthocyanidin reductase (VuANR), leucoanthocyanidin reductase (VuLAR) and flavonoid 3'5' hydroxylase (VuF3'5'H) were more similar between the white and the wild-type berries during fruit development, while expression of UDP-glucose: flavonoid 3-O-glucosyltransferase (VuUFGT) showed similar trend but fourfold lower level in white mutant. VuMYBPA1, the R2R3 MYB family member, is a homologue of VmMYB2 of V. myrtillus and VcMYBPA1 of V. corymbosum and belongs to MYBPA1-type MYB family which members are shown in some species to be related with proanthocyanidin biosynthesis in fruits. Our results combined with earlier data of the role of VmMYB2 in white mutant berries of V. myrtillus suggest that the regulation of anthocyanin biosynthesis in Vaccinium species could differ

Urinary tract infection in full-term newborn infants: risk factor analysis

Directory of Open Access Journals (Sweden)

Falcão Mário Cícero

2000-01-01

Full Text Available OBJECTIVE: To analyze the correlation of risk factors to the occurrence of urinary tract infection in full-term newborn infants. PATIENTS AND METHODS: Retrospective study (1997 including full-term infants having a positive urine culture by bag specimen. Urine collection was based on: fever, weight loss > 10% of birth weight, nonspecific symptoms (feeding intolerance, failure to thrive, hypoactivity, debilitate suction, irritability, or renal and urinary tract malformations. In these cases, another urine culture by suprapubic bladder aspiration was collected to confirm the diagnosis. To compare and validate the risk factors in each group, the selected cases were divided into two groups: Group I - positive urine culture by bag specimen collection and negative urine culture by suprapubic aspiration, and Group II - positive urine culture by bag specimen collection and positive urine culture by suprapubic aspiration . RESULTS: Sixty one infants were studied, Group I, n = 42 (68.9% and Group II, n = 19 (31.1%. The selected risk factors (associated infectious diseases, use of broad-spectrum antibiotics, renal and urinary tract malformations, mechanical ventilation, parenteral nutrition and intravascular catheter were more frequent in Group II (p<0.05. Through relative risk analysis, risk factors were, in decreasing importance: parenteral nutrition, intravascular catheter, associated infectious diseases, use of broad-spectrum antibiotics, mechanical ventilation, and renal and urinary tract malformations. CONCLUSION: The results showed that parenteral nutrition, intravascular catheter, and associated infectious diseases contributed to increase the frequency of neonatal urinary tract infection, and in the presence of more than one risk factor, the occurrence of urinary tract infection rose up to 11 times.

Investing in systematic factor premiums

NARCIS (Netherlands)

Koedijk, Kees G.; Slager, Alfred M. H.; Stork, P.A.

In this paper we investigate and evaluate factor investing in the US and Europe for equities and bonds. We show that factor-based portfolios generally produce comparable or better portfolios than market indices. We expand the analysis to other asset classes and factors, work with other optimisation

Recurrent-neural-network-based Boolean factor analysis and its application to word clustering.

Science.gov (United States)

Frolov, Alexander A; Husek, Dusan; Polyakov, Pavel Yu

2009-07-01

The objective of this paper is to introduce a neural-network-based algorithm for word clustering as an extension of the neural-network-based Boolean factor analysis algorithm (Frolov , 2007). It is shown that this extended algorithm supports even the more complex model of signals that are supposed to be related to textual documents. It is hypothesized that every topic in textual data is characterized by a set of words which coherently appear in documents dedicated to a given topic. The appearance of each word in a document is coded by the activity of a particular neuron. In accordance with the Hebbian learning rule implemented in the network, sets of coherently appearing words (treated as factors) create tightly connected groups of neurons, hence, revealing them as attractors of the network dynamics. The found factors are eliminated from the network memory by the Hebbian unlearning rule facilitating the search of other factors. Topics related to the found sets of words can be identified based on the words' semantics. To make the method complete, a special technique based on a Bayesian procedure has been developed for the following purposes: first, to provide a complete description of factors in terms of component probability, and second, to enhance the accuracy of classification of signals to determine whether it contains the factor. Since it is assumed that every word may possibly contribute to several topics, the proposed method might be related to the method of fuzzy clustering. In this paper, we show that the results of Boolean factor analysis and fuzzy clustering are not contradictory, but complementary. To demonstrate the capabilities of this attempt, the method is applied to two types of textual data on neural networks in two different languages. The obtained topics and corresponding words are at a good level of agreement despite the fact that identical topics in Russian and English conferences contain different sets of keywords.

Fungal communities in wheat grain show significant co-existence patterns among species

DEFF Research Database (Denmark)

Nicolaisen, M.; Justesen, A. F.; Knorr, K.

2014-01-01

identified as ‘core’ OTUs as they were found in all or almost all samples and accounted for almost 99 % of all sequences. The remaining OTUs were only sporadically found and only in small amounts. Cluster and factor analyses showed patterns of co-existence among the core species. Cluster analysis grouped...... the 21 core OTUs into three clusters: cluster 1 consisting of saprotrophs, cluster 2 consisting mainly of yeasts and saprotrophs and cluster 3 consisting of wheat pathogens. Principal component extraction showed that the Fusarium graminearum group was inversely related to OTUs of clusters 1 and 2....

Risk factors for radiation-induced hypothyroidism: A Literature-Based Meta-Analysis

DEFF Research Database (Denmark)

Vogelius, Ivan R; Bentzen, Søren; Maraldo, Maja V

2011-01-01

BACKGROUND: A systematic overview and meta-analysis of studies reporting data on hypothyroidism (HT) after radiation therapy was conducted to identify risk factors for development of HT. METHODS: Published studies were identified from the PubMed and Embase databases and by hand-searching published...... reviews. Studies allowing the extraction of odds ratios (OR) for HT in 1 or more of several candidate clinical risk groups were included. A meta-analysis of the OR for development of HT with or without each of the candidate risk factors was performed. Furthermore, studies allowing the extraction......% risk of HT at a dose of 45 Gy but with considerable variation in the dose response between studies. Chemotherapy and age were not associated with risk of HT in this analysis. CONCLUSIONS: Several clinical risk factors for HT were identified. The risk of HT increases with increasing radiation dose...

Factor analysis and psychometric properties of the Mother-Adolescent Sexual Communication (MASC) instrument for sexual risk behavior.

Science.gov (United States)

Cox, Mary Foster; Fasolino, Tracy K; Tavakoli, Abbas S

2008-01-01

Sexual risk behavior is a public health problem among adolescents living at or below poverty level. Approximately 1 million pregnancies and 3 million cases of sexually transmitted infections (STIs) are reported yearly. Parenting plays a significant role in adolescent behavior, with mother-adolescent sexual communication correlated with absent or delayed sexual behavior. This study developed an instrument examining constructs of mother-adolescent communication, the Mother-Adolescent Sexual Communication (MASC) instrument. A convenience sample of 99 mothers of middle school children completed the self-administered questionnaires. The original 34-item MASC was reduced to 18 items. Exploratory factor analysis was conducted on the 18-item scale, which resulted in four factors explaining 84.63% of the total variance. Internal consistency analysis produced Cronbach alpha coefficients of .87, .90, .82, and .71 for the four factors, respectively. Convergent validity via hypothesis testing was supported by significant correlations with several subscales of the Parent-Child Relationship Questionnaire (PCRQ) with MASC factors, that is, content and style factors with warmth, personal relationships and disciplinary warmth subscales of the PCRQ, the context factor with personal relationships, and the timing factor with warmth. In light of these findings, the psychometric characteristics and multidimensional perspective of the MASC instrument show evidence of usefulness for measuring and advancing knowledge of mother and adolescent sexual communication techniques.

Understanding Older Adults' Perceptions of Internet Use: An Exploratory Factor Analysis

Science.gov (United States)

Zheng, Robert; Spears, Jeffrey; Luptak, Marilyn; Wilby, Frances

2015-01-01

The current study examined factors related to older adults' perceptions of Internet use. Three hundred ninety five older adults participated in the study. The factor analysis revealed four factors perceived by older adults as critical to their Internet use: social connection, self-efficacy, the need to seek financial information, and the need to…

Lungworm Infections in German dairy cattle herds--seroprevalence and GIS-supported risk factor analysis.

Directory of Open Access Journals (Sweden)

Anne-Marie Schunn

Full Text Available In November 2008, a total of 19,910 bulk tank milk (BTM samples were obtained from dairy farms from all over Germany, corresponding to about 20% of all German dairy herds, and analysed for antibodies against the bovine lungworm Dictyocaulus viviparus by use of the recombinant MSP-ELISA. A total number of 3,397 (17.1%; n = 19,910 BTM samples tested seropositive. The prevalences in individual German federal states varied between 0.0% and 31.2% positive herds. A geospatial map was drawn to show the distribution of seropositive and seronegative herds per postal code area. ELISA results were further analysed for associations with land-use and climate data. Bivariate statistical analysis was used to identify potential spatial risk factors for dictyocaulosis. Statistically significant positive associations were found between lungworm seropositive herds and the proportion of water bodies and grassed area per postal code area. Variables that showed a statistically significant association with a positive BTM test were included in a logistic regression model, which was further refined by controlled stepwise selection of variables. The low Pseudo R(2 values (0.08 for the full model and 0.06 for the final model and further evaluation of the model by ROC analysis indicate that additional, unrecorded factors (e.g. management factors or random effects may substantially contribute to lungworm infections in dairy cows. Veterinarians should include lungworms in the differential diagnosis of respiratory disease in dairy cattle, particularly those at pasture. Monitoring of herds through BTM screening for antibodies can help farmers and veterinarians plan and implement appropriate control measures.

Clinicopathological Analysis of Factors Related to Colorectal Tumor Perforation

OpenAIRE

Medina-Arana, Vicente; Martínez-Riera, Antonio; Delgado-Plasencia, Luciano; Rodríguez-González, Diana; Bravo-Gutiérrez, Alberto; Álvarez-Argüelles, Hugo; Alarcó-Hernández, Antonio; Salido-Ruiz, Eduardo; Fernández-Peralta, Antonia M.; González-Aguilera, Juan J.

2015-01-01

Abstract Colorectal tumor perforation is a life-threatening complication of this disease. However, little is known about the anatomopathological factors or pathophysiologic mechanisms involved. Pathological and immunohistochemical analysis of factors related with tumoral neo-angiogenesis, which could influence tumor perforation are assessed in this study. A retrospective study of patients with perforated colon tumors (Group P) and T4a nonperforated (controls) was conducted between 2001 and 20...

Analysis of risk factors for persistent infection of asymptomatic women with high-risk human papilloma virus.

Science.gov (United States)

Shi, Nianmin; Lu, Qiang; Zhang, Jiao; Li, Li; Zhang, Junnan; Zhang, Fanglei; Dong, Yanhong; Zhang, Xinyue; Zhang, Zheng; Gao, Wenhui

2017-06-03

classification tree. 3000 women participated in the study. The high-risk type HPV infection rate was 8.7%, the persistent infection rate was 7.5%. The persistent infection rates for the 2 age groups (ages 18-26 and 27-30) were 6.9% and 8.7%. The persistent infection rates of Xiangfen county were 7.4% and 7.4% respectively, and those of Quwo county were 7.8% and 11.6% respectively; there was no significant difference between each pair of groups. Single risk-factor analysis showed that first-time sex at age under 20, high school/technical secondary school education or above, multiple sexual partners, having more than 2 sexual partners in the past 6 months, oral sex, and colitis are the risk factors of high-risk type HPV infection. Multivariate analysis showed that the number of sexual partners, smoking and oral sex had an effect on HPV infection. The risk of HPV infection from smoking was 5.0-fold higher, and the risk of HPV infection from oral sex was 6.1-fold higher. Having more than 2 sexual partners increase the risk of HPV infection. By the predicated model analysis, the probability of HPV conveyed by oral sex was 14.8%; if the sexual companion number was zero or more than 2 without oral sex, the probability of HPV infection was 12.1%; if there was one sexual partner who smokes without oral sex, the probability of infection was 18.6%; if there was one sexual partner who does not smoke and without oral sex, the probability of infection was 3.6%. The persistent infection rate of asymptomatic women for high-risk type HPV is lower than those women in all ages. High-risk type HPV infection risk factors include the number of sexual partners, oral sex and smoking. Thus, young women may be able to reduce the risk of infection with high-risk type HPV by reducing the number of sexual partners, forming a correct sexual life habit, and avoiding smoking.

Analysis of soybean production and import trends and its import factors in Indonesia

Science.gov (United States)

Ningrum, I. H.; Irianto, H.; Riptanti, E. W.

2018-03-01

This study aims to analyze the factors affecting soybean imports in Indonesia and to know the trend and projection of Indonesian soybean production as well as the import in 2016-2020. The basic method used in this research is the description analysis method. The data used are secondary data in the form of time series data from 1979-2015. Methods of data analysis using simultaneous equations model with 2SLS (Two Stage Least Square) method and Trend analysis. The results showed that the factors affecting soybean imports in Indonesia are consumption and production. Consumption has positive effect while production is negatively affected. The percentage changed in soybean imports is greater than the percentage change in consumption and production of soybeans. Consumption is positively influenced by imports and production, while production is influenced positively by consumption and negative by imports. The production trend of soybean in 2016-2020 has a tendency to increase with a percentage of 11.18% per year. Production in 2016 is projected at 1.110.537 tons while in 2020 it will increase to 1,721,350 tons. The import trend in 2016-2020 has a tendency to increase with an average percentage of 4.13% per year. Import in 2016 is projected at 2.224.188 tons while in 2020 it will increase to 2.611.270 tons.

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

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

2017-09-15

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

Structural validity of the Pittsburgh Sleep Quality Index in Chinese undergraduate students: A confirmatory factor analysis

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Suran Guo

2016-08-01

Full Text Available The purpose of this study was to examine the structural validity of the Pittsburgh Sleep Quality Index (PSQI in Chinese undergraduate students. A cross-sectional questionnaire survey with 631 Chinese undergraduate students was conducted, and the questionnaire package included a measure of demographic characteristics, Pittsburgh Sleep Quality Index (PSQI, Chinese editions of Center for Epidemiologic Studies-Depression, State- Trait Anxiety Inventory, Rumination Response Scale, and Perceived Social Support Scale. Results showed that the item use of sleep medicine was not suitable for use with this population, that a two-factor model provided the best fit to the data as assessed through confirmatory factor analysis, and that other indices were consistently correlated with the sleep quality but not the sleep efficiency factor.

A factor analysis of Functional Independence and Functional Assessment Measure scores among focal and diffuse brain injury patients: The importance of bi-factor models.

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Gunn, Sarah; Burgess, Gerald H; Maltby, John

2018-04-28

To explore the factor structure of the UK Functional Independence Measure and Functional Assessment Measure (FIM+FAM) among focal and diffuse acquired brain injury patients. Criterion standard. An NHS acute acquired brain injury inpatient rehabilitation hospital. Referred sample of 447 adults (835 cases after exclusions) admitted for inpatient treatment following an acquired brain injury significant enough to justify intensive inpatient neurorehabilitation. Not applicable. Functional Independence Measure and Functional Assessment Measure. Exploratory Factor Analysis suggested a two-factor structure to FIM+FAM scores, among both focal-proximate and diffuse-proximate acquired brain injury aetiologies. Confirmatory Factor Analysis suggested a three-factor bi-factor structure presented the best fit of the FIM+FAM score data across both aetiologies. However, across both analyses, a convergence was found towards a general factor, demonstrated by high correlations between factors in the Exploratory Factor Analysis, and by a general factor explaining the majority of the variance in scores on Confirmatory Factor Analysis. Our findings suggested that although factors describing specific functional domains can be derived from FIM+FAM item scores, there is a convergence towards a single factor describing overall functioning. This single factor informs the specific group factors (e.g. motor, psychosocial and communication function) following brain injury. Further research into the comparative value of the general and group factors as evaluative/prognostic measures is indicated. Copyright © 2018. Published by Elsevier Inc.

Determinants of job stress in chemical process industry: A factor analysis approach.

Science.gov (United States)

Menon, Balagopal G; Praveensal, C J; Madhu, G

2015-01-01

Job stress is one of the active research domains in industrial safety research. The job stress can result in accidents and health related issues in workers in chemical process industries. Hence it is important to measure the level of job stress in workers so as to mitigate the same to avoid the worker's safety related problems in the industries. The objective of this study is to determine the job stress factors in the chemical process industry in Kerala state, India. This study also aims to propose a comprehensive model and an instrument framework for measuring job stress levels in the chemical process industries in Kerala, India. The data is collected through a questionnaire survey conducted in chemical process industries in Kerala. The collected data out of 1197 surveys is subjected to principal component and confirmatory factor analysis to develop the job stress factor structure. The factor analysis revealed 8 factors that influence the job stress in process industries. It is also found that the job stress in employees is most influenced by role ambiguity and the least by work environment. The study has developed an instrument framework towards measuring job stress utilizing exploratory factor analysis and structural equation modeling.

Analysis on the risk factors of bacterial meningitis complicated with subdural effusion

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Zhi JIANG

2015-08-01

Full Text Available Objective To investigate the risk factors of bacterial meningitis complicated with subdural effusion.  Methods The clinical data of children with bacterial meningitis in our hospital were collected and analyzed retrospectively. Logistic regression analysis was used to investigate the risk factors for subdural effusion.  Results A total of 128 cases were divided into control group (N = 64 and subdural effusion group (N = 64. There was no significant difference on serum erythrocyte sedimentation rate (ESR, C-reactive protein (CRP, and white blood cell (WBC between 2 groups (P > 0.05, for all. Compared with control group, cerebrospinal fluid (CSF WBC (Z = 3.126, P = 0.003, CSF protein (Z = 4.928, P = 0.000 and serum procalcitonin (PCT; Z = 2.823, P = 0.007 in subdural effusion group were significantly higher, while CSF glucose (t = 2.166, P = 0.033 was significantly lower. After treatment, CSF WBC (Z = 2.467, P = 0.012 in subdural effusion group was still significantly higher than that of control group, and CSF glucose (t = 4.938, P = 0.000 was still significantly lower. Logistic regression analysis showed that WBC in CSF (P = 0.027, CSF protein (P = 0.002 and serum PCT (P = 0.014 were independent risk factors for bacterial meningitis complicated with subdural effusion.  Conclusions CSF examination of children with bacterial meningitis reveals significant increase of CSF WBC, CSF protein and serum PCT, suggesting concurrent subdural effusion is easily occurred. DOI: 10.3969/j.issn.1672-6731.2015.08.012

Multivariate analysis of risk factors for long-term urethroplasty outcome.

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Breyer, Benjamin N; McAninch, Jack W; Whitson, Jared M; Eisenberg, Michael L; Mehdizadeh, Jennifer F; Myers, Jeremy B; Voelzke, Bryan B

2010-02-01

We studied the patient risk factors that promote urethroplasty failure. Records of patients who underwent urethroplasty at the University of California, San Francisco Medical Center between 1995 and 2004 were reviewed. Cox proportional hazards regression analysis was used to identify multivariate predictors of urethroplasty outcome. Between 1995 and 2004, 443 patients of 495 who underwent urethroplasty had complete comorbidity data and were included in analysis. Median patient age was 41 years (range 18 to 90). Median followup was 5.8 years (range 1 month to 10 years). Stricture recurred in 93 patients (21%). Primary estimated stricture-free survival at 1, 3 and 5 years was 88%, 82% and 79%. After multivariate analysis smoking (HR 1.8, 95% CI 1.0-3.1, p = 0.05), prior direct vision internal urethrotomy (HR 1.7, 95% CI 1.0-3.0, p = 0.04) and prior urethroplasty (HR 1.8, 95% CI 1.1-3.1, p = 0.03) were predictive of treatment failure. On multivariate analysis diabetes mellitus showed a trend toward prediction of urethroplasty failure (HR 2.0, 95% CI 0.8-4.9, p = 0.14). Length of urethral stricture (greater than 4 cm), prior urethroplasty and failed endoscopic therapy are predictive of failure after urethroplasty. Smoking and diabetes mellitus also may predict failure potentially secondary to microvascular damage. Copyright 2010 American Urological Association. Published by Elsevier Inc. All rights reserved.

Analysis of Learning Environment Factors Based on Maslow’s Hierarchy of Needs

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Košir Katja

2013-09-01

Full Text Available This paper provides a new analysis of some learning environment factors from the point of view of one of the most established motivational models, i.e. Maslow’s hierarchy of needs. For a teacher, this model can represent a meaningful tool for the analysis of the potential factors of pupils’ inadequate school adjustment. Some psychological constructs that can be conceptualized as learning environment factors are presented at specific levels of needs. As regards the level of physiological needs, this paper provides an overview of research studies on ergonomic factors of learning environment. As for safety needs, the paper outlines the concepts of classroom management and peer-to-peer violence, and presents some main research findings in both fields. The analysis regarding the level of love and belonging includes aspects of positive classroom climate and the concept of pupils’ social acceptance. Contemporary findings about the development of pupil’s academic self-concept are presented within the self-esteem and achievements needs. Flow is considered to be one of key factors that help teacher satisfy the self-actualization needs and stimulate pupils’ personal development. On the basis of this analysis, some implications and recommendations are given to help teachers efficiently encourage an integrated approach to pupil development.

Analysis of factors influencing decision making of Czech households when purchasing clothes and footwear

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Zuzana Toufarová

2007-01-01

Full Text Available The paper analyses buying behaviour of Czech households on the market with footwear and cloths. It aims at factors influ, encing this behaviour, e.g. price, brand, quality, product attributes, habits, price reductions, advertisement, innovation and word-of-mauth. Primary data were obtained via survey of 727 Czech households by staff of the Department of Marketing and Trade, Mendel University of Agriculture and Forestry Brno. The paper provides results of correlation analysis and factor analysis. When making purchase decisions, households identify attributes and parameters of clothes and footwear as the most important factor. Due to factor analysis, factors were reduced into four comprehensive groups.

48 CFR 1615.404-70 - Profit analysis factors.

Science.gov (United States)

2010-10-01

... CONTRACTING BY NEGOTIATION Contract Pricing 1615.404-70 Profit analysis factors. (a) OPM contracting officers... managerial expertise and effort. Evidence of effective contract performance will receive a plus weight, and... indifference to cost control will generally result in a negative weight. (2) Contract cost risk. In assessing...

A factor analysis of the Kirton Adaption-Innovation Inventory using an alcoholic population.

Science.gov (United States)

Robertson, E D; Fournet, G P; Zelhart, P F; Estes, R E

1988-04-01

The present study reports a factor analysis of the Kirton Adaption-Innovation Inventory using 103 alcoholic men. Kirton in 1976 and we in an unpublished work in 1986 noted identical factor structures when responses from nonalcoholic populations to the inventory were factor analyzed. Recent reviews regarding personality characteristics of alcoholics suggest characteristics similar to the adaption-innovation concepts of Kirton. This factor analysis for an alcoholic sample supports the validity of the inventory as a measure of problem-solving style of alcoholics.

Worry About Caregiving Performance: A Confirmatory Factor Analysis

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Ruijie Li

2018-03-01

Full Text Available Recent studies on the Zarit Burden Interview (ZBI support the existence of a unique factor, worry about caregiving performance (WaP, beyond role and personal strain. Our current study aims to confirm the existence of WaP within the multidimensionality of ZBI and to determine if predictors of WaP differ from the role and personal strain. We performed confirmatory factor analysis (CFA on 466 caregiver-patient dyads to compare between one-factor (total score, two-factor (role/personal strain, three-factor (role/personal strain and WaP, and four-factor models (role strain split into two factors. We conducted linear regression analyses to explore the relationships between different ZBI factors with socio-demographic and disease characteristics, and investigated the stage-dependent differences between WaP with role and personal strain by dyadic relationship. The four-factor structure that incorporated WaP and split role strain into two factors yielded the best fit. Linear regression analyses reveal that different variables significantly predict WaP (adult child caregiver and Neuropsychiatric Inventory Questionnaire (NPI-Q severity from role/personal strain (adult child caregiver, instrumental activities of daily living, and NPI-Q distress. Unlike other factors, WaP was significantly endorsed in early cognitive impairment. Among spouses, WaP remained low across Clinical Dementia Rating (CDR stages until a sharp rise in CDR 3; adult child and sibling caregivers experience a gradual rise throughout the stages. Our results affirm the existence of WaP as a unique factor. Future research should explore the potential of WaP as a possible intervention target to improve self-efficacy in the milder stages of burden.

Using confirmatory factor analysis to explore associated factors of intimate partner violence in a sample of Chinese rural women: a cross-sectional study.

Science.gov (United States)

Hou, Fengsu; Cerulli, Catherine; Wittink, Marsha N; Caine, Eric D; Qiu, Peiyuan

2018-02-02

To estimate the prevalence of intimate partner violence (IPV) among a sample of rural Chinese women and to explore associated factors. Cross-sectional study. Rural areas of Guangyuan City, Sichuan, China. We recruited 1501 women, aged 16 years and older, who had been living locally for at least 2 years and reported being married or in a relationship during the past 12 months. They were among a sample of 1898 potential participants from our larger parent study on the prevalence of depressive-distress symptoms. Participants completed demographic and social economic measures, the Short Form of the Revised Conflict Tactics Scale and the Duke Social Support Index. We applied χ 2 test, analysis of variance and confirmatory factor analysis for analysis. The overall prevalence of IPV in the past 12 months was 29.05%; the prevalence of physical, psychological and sexual violence was 7.66%, 26.58% and 3.20%, respectively. The overall prevalence was highest among women aged 16-29 years, and was more common among those without a high school diploma and who saw their family's financial status as very poor or stagnant. Women who were not victims of IPV had higher levels of social support. Confirmatory factor analysis showed that the total effects of social support on physical, psychological and sexual violence were -0.12, -0.35 and -0.12, respectively. The indirect effects of objective economic status on physical, psychological and sexual violence were -0.047, -0.014 and -0.047, respectively, but the total effect was not significant. The indirect effect of education on psychological violence was -0.056. IPV is common in rural Guangyuan. Our data are comparable with the findings from north-west of China. Social support is an important protective factor. Future work is needed to develop, test and later disseminate potential IPV interventions, with a focus on building actual and perceived supportive social networks. © Article author(s) (or their employer(s) unless otherwise

Parallel factor analysis PARAFAC of process affected water

Energy Technology Data Exchange (ETDEWEB)

Ewanchuk, A.M.; Ulrich, A.C.; Sego, D. [Alberta Univ., Edmonton, AB (Canada). Dept. of Civil and Environmental Engineering; Alostaz, M. [Thurber Engineering Ltd., Calgary, AB (Canada)

2010-07-01

A parallel factor analysis (PARAFAC) of oil sands process-affected water was presented. Naphthenic acids (NA) are traditionally described as monobasic carboxylic acids. Research has indicated that oil sands NA do not fit classical definitions of NA. Oil sands organic acids have toxic and corrosive properties. When analyzed by fluorescence technology, oil sands process-affected water displays a characteristic peak at 290 nm excitation and approximately 346 nm emission. In this study, a parallel factor analysis (PARAFAC) was used to decompose process-affected water multi-way data into components representing analytes, chemical compounds, and groups of compounds. Water samples from various oil sands operations were analyzed in order to obtain EEMs. The EEMs were then arranged into a large matrix in decreasing process-affected water content for PARAFAC. Data were divided into 5 components. A comparison with commercially prepared NA samples suggested that oil sands NA is fundamentally different. Further research is needed to determine what each of the 5 components represent. tabs., figs.

Application of factor analysis to the hydrogeochemical study of a coastal aquifer

OpenAIRE

Ruiz Beviá, Francisco; Gomis Yagües, Vicente; Blasco Alemany, Pilar

1989-01-01

The use of numerical values for the chemical components of waters from an aquifer as input data for factor analysis is shown to be sometimes more convenient than the use of the logarithms of these figures. Factor analysis was applied to the hydrogeochemical study of a coastal aquifer located in Javea, Alicante (Spain). A set of factors was found which explained the source of the ions in the water and even certain chemical processes which accompany the intrusion of seawater, such as the strong...

The factor analysis of the incidence of pneumothorax after CT-guided transthoracic needle aspiration biopsy

International Nuclear Information System (INIS)

Zhong Tao; Yu Hongguang; Wang Yong; Yang Sifu; Wang Xiaoxuan

2007-01-01

Objective: To analyze the impact of multiple factors on the incidence of pneumothorax associated with CT-guided transthoracic needle aspiration biopsy. Methods: The sign of pneumothorax after 162 cases (lesion diameter from 1 cm to 6 cm) CT-guided transthoracic needle aspiration biopsy was observed and its relationship with multivariate factors were analyzed by multivariate logistic regression model. Results: Thirty-two cases presented pneumothorax accounting for 19. 8%. Single variate analysis showed that the sign of pneumothorax related to intercurrent COPD, distance from lesion and chest wall, needle dwelling time and lesion diameter. 67 patients of intercurrent COPD with postoperative pneumothorax occurred in 22 cases (32.8%); With respect to those having lesions close to the chest wall (48 cases), and the cases with the distance between the chest wall and lesions less than 2 cm (55 cases) and greater than 2 cm (59 cases), the postoperative pneumothorax occurred in 0, 14 (25.5%), 18 (30.5%) cases respectively; For those patients with needle in the chest residence time of less than 10 minutes (82 cases), 10-20 minutes (51 cases), more than 20 minutes (28 cases) after the occurrence of pneumothorax were 8 (9.6%), 10(19.6%), 14 (50%) cases respectively; In contrast, those with lesion diameter less than 2 cm (65 cases), 2-4 cm(52 cases), more than 4cm(45 cases) were 19 (29.2%), 8 (15.4%) and 5 (11.1% ) respectively. The multivariate logistic regression analysis showed that the prior three factor's were risk factors of pneumothorax (OR=4.652, 4.030, 2.855 respectively). Conclusions: To avoid the pneumothorax, caution must be taken with respect to CT-guided transthoracic needle aspiration biopsy, patients with intercurrent COPD, long distance between lesion and chest wall, and smaller lesion diameter. For operation the needle dwell time within thorax should be minimized. (authors)

Theory of error for target factor analysis with applications to mass spectrometry and nuclear magnetic resonance spectrometry

International Nuclear Information System (INIS)

Malinowski, E.R.

1978-01-01

Based on the theory of error for abstract factor analysis described earlier, a theory of error for target factor analysis is developed. The theory shows how the error in the data matrix mixes with the error in the target test vector. The apparent error in a target test is found to be a vector sum of the real error in the target vector and the real error in the predicted vector. The theory predicts the magnitudes of these errors without requiring any a priori knowledge of the error in the data matrix or the target vector. A reliability function and a spoil function are developed for the purpose of assessing the validity and the worthiness of a target vector. Examples from model data, mass spectrometry and nuclear magnetic resonance spectrometry are presented. (Auth.)

Confirmatory Factor Analysis of IT-based Competency Questionnaire in Information Science & Knowledge Studies, Based on Job Market Analysis

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Rahim Shahbazi

2016-03-01

Full Text Available The main purpose of the present research is to evaluate the validity of an IT-based competency questionnaire in Information Science & Knowledge Studies. The Survey method has been used in the present research. A data collection tool has been a researcher-made questionnaire. Statistic samples, which are 315 people, have been chosen purposefully from among Iranian faculty members, Ph.D. students, and information center employees. The findings showed that by eliminating 17 items from the whole questionnaire and Confirmatory Factor Analysis of the rest and rotating findings using the Varimax method, 8 Factors were revealed. The resulting components and also the items which had a high load factor with these components were considerably consistent with the classifications in the questionnaire and partly consistent with the findings of other researchers. 76 competency indicators (knowledge, skills, and attitudes were validated and grouped under 8 main categories: 1. “Computer Basics” 2. “Database Operating, Collection Development of Digital Resources, & Digital Library Management” 3. “Basics of Computer Networking” 4. “Basics of Programming & Database Designing” 5. “Web Designing & Web Content Analysis” 6. “Library Software & Computerized Organizing” 7. Archive of Digital Resources and 8. Attitudes.

Preliminary factor analysis of the O’Kelly Women Beliefs Scale in a US sample

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Arturo Heman Contreras

2012-06-01

Full Text Available Using a Rational Emotive Behavior Therapy framework, the O’Kelly Women Beliefs Scale (O’Kelly, in press was originally constructed in Australia to measure sex-role beliefs women may develop through sex-role stereotyping. Factor analysis of the 92 original items showed that 64 items loaded into a single component that accounted for 18.2% of the variance in a sample of 974 Australian women. The present exploratory study examined the psychometric properties of the OWBS in a sample of 202 women born and living in the US. A varimax rotation with cutoff eigenvalues of 3, showed that 37 items loaded into 3 components which accounted for 58.48% of the variance. The items were subsequently grouped into two factors: Ir- rationality, with a total of 27 items was created by merging component 1 and 3 (Pearson’s r = 0.8 between them, and Rationality, with the 10 items from component 2. Analyses indicated a Cronbach’s alpha of 0.91 for Fac- tor 1, and a Cronbach’s alpha 0.74 for Factor 2. Results indicate that this version of the instrument may be used to evaluate both the rational and irrational content of sex-role beliefs of women born in the US.

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

Science.gov (United States)

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Analysis of bus passenger comfort perception based on passenger load factor and in-vehicle time.

Science.gov (United States)

Shen, Xianghao; Feng, Shumin; Li, Zhenning; Hu, Baoyu

2016-01-01

Although bus comfort is a crucial indicator of service quality, existing studies tend to focus on passenger load and ignore in-vehicle time, which can also affect passengers' comfort perception. Therefore, by conducting surveys, this study examines passengers' comfort perception while accounting for both factors. Then, using the survey data, it performs a two-way analysis of variance and shows that both in-vehicle time and passenger load significantly affect passenger comfort. Then, a bus comfort model is proposed to evaluate comfort level, followed by a sensitivity analysis. The method introduced in this study has theoretical implications for bus operators attempting to improve bus service quality.

Understanding clinician attitudes towards implementation of guided self-help cognitive behaviour therapy for those who hear distressing voices: using factor analysis to test normalisation process theory.

Science.gov (United States)

Hazell, Cassie M; Strauss, Clara; Hayward, Mark; Cavanagh, Kate

2017-07-24

The Normalisation Process Theory (NPT) has been used to understand the implementation of physical health care interventions. The current study aims to apply the NPT model to a secondary mental health context, and test the model using exploratory factor analysis. This study will consider the implementation of a brief cognitive behaviour therapy for psychosis (CBTp) intervention. Mental health clinicians were asked to complete a NPT-based questionnaire on the implementation of a brief CBTp intervention. All clinicians had experience of either working with the target client group or were able to deliver psychological therapies. In total, 201 clinicians completed the questionnaire. The results of the exploratory factor analysis found partial support for the NPT model, as three of the NPT factors were extracted: (1) coherence, (2) cognitive participation, and (3) reflexive monitoring. We did not find support for the fourth NPT factor (collective action). All scales showed strong internal consistency. Secondary analysis of these factors showed clinicians to generally support the implementation of the brief CBTp intervention. This study provides strong evidence for the validity of the three NPT factors extracted. Further research is needed to determine whether participants' level of seniority moderates factor extraction, whether this factor structure can be generalised to other healthcare settings, and whether pre-implementation attitudes predict actual implementation outcomes.

Analysis of Factors Affecting Women of Childbearing Age to Screen Using Visual Inspection with Acetic Acid.

Science.gov (United States)

Sidabutar, Sondang; Martini, Santi; Wahyuni, Chatarina Umbul

2017-02-01

The purpose of this study was to evaluate patient factors such as knowledge, attitude, motivation, perception, socio-economic status and travel time to health facilities and assess how these factors affected patients' decision to pursue cervical cancer screening with visual inspection with acetic acid (VIA). A total of 80 women of childbearing age who visited Kenjeran and Balongsari Public Health Centers for health assessments were involved in this study. Patients who agreed to participate in the study underwent a verbal questionnaire to evaluate various factors. Bivariate analysis concluded that knowledge, attitude, motivation, perception, socioeconomic status, and travel time to health facilities were significantly different between women who received VIA screening and women who did not receive VIA screening ( p motivation, perception, socio-economic status, and the travel time to health facilities accounted for 2.920-fold, 2.043-fold, 3.704-fold, 2.965-fold, 3.198-fold and 2.386-fold possibility, respectively, of patients to pursue cervical cancer screening with VIA. Multivariate analysis showed that perception, socio-economic status, and travel time to health facilities were the most important factors influencing whether or not women pursued VIA screening. Knowledge, attitude, motivation, perception, socio-economic status, and travel time to health facilities appears to affect women's' decision to pursue cervical cancer screening with VIA, with the largest intake being the motivational factor.

Periodic tests: a human factors analysis of documentary aspects

International Nuclear Information System (INIS)

Perinet, Romuald; Rousseau, Jean-Marie

2007-01-01

conclusions of this analysis are presented in this paper. The analysis carried out by the IRSN showed that the complexity of the design and implementation process of periodic tests is due to the diversity of.the organizations and participants, the number and the heterogeneity of the documents, and the technical and regulatory complexity of operation. In this context, defects related to the quality of the national reference document updates and to the conditions of their delivery were at the origin of difficulties in CNPEs. These difficulties address the integration of the updates by the participants, the overall vision of the rules to be respected, and the management of the workload to deal with these tasks. The analysis showed that CNPEs made efforts to produce reliable, station-specific updates, but improvements could still be made concerning the organization, the communication and the ergonomics of the operating ranges. More generally, from a human and organizational factors point of view, such an analysis surpasses the search for responsibility for the dysfunctions and allows for a more objective explanation of the encountered difficulties (inapplicable rules, delays of delivery, etc.). It also leads to a consolidated needs analysis in order to improve the global process. On the basis of a preliminary analysis, EDF has identified a plan for improvement. EDF has decided to deal with the improvement of the process within the framework of a thorough study. (authors)

Risk factors for Clonorchis sinensis infection transmission in humans in northern Vietnam: A descriptive and social network analysis study.

Science.gov (United States)

Vinh, Hoang Quang; Phimpraphai, Waraphon; Tangkawattana, Sirikachorn; Smith, John F; Kaewkes, Sasithorn; Dung, Do Trung; Duong, Tran Thanh; Sripa, Banchob

2017-04-01

Clonorchis sinensis is major fish-borne trematode, endemic in North Vietnam. Risk factors described so far include individual eating behaviors and environmental factors. Here, additional to conventional risk factors, we report on socially influenced liver fluke transmission in endemic communities. A cross-sectional study on risk factors and fish sharing networks was conducted in 4 villages of Gia Thinh Commune, Ninh Binh Province. A total of 510 residents in 272 households were recruited for risk factor analysis while 220 households, 28 fishermen and 10 fish-sellers were enrolled for social network study. Fecal examination for C. sinensis eggs was performed. Average C. sinensis infection rate at Gia Thinh commune was 16.5% (range 2% to 34.4%). Higher infection rates were significantly associated with males, lower educational levels, eating raw fish, and location of the villages. Social network analysis (SNA) showed a strong positive correlation between ego network size (number of households in fish sharing network) and quantity of raw fish consumed (r=0.603, Psinensis infection transmission in northern Vietnam. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

An analysis of main factors in electron beam flue gas purification

International Nuclear Information System (INIS)

Zhang Ming; Xu Guang

2003-01-01

Electron beam flue gas purification method is developing very quickly in recent years. Based on the experiment setting for electron beam flue gas purification in Institute of Nuclear Energy and Technology, Tsinghua University, how the technique factors affect the ratio of desulphurization and denitrogenation are described. Radiation dose (D), temperature (T), humidity (H), pour ammonia quantity (α) and initial concentration of SO 2 (C SO 2 ) and NO x (C NO x ) are main factors influencing flue gas purification. Using the methods of correlation analysis and regression analysis, the primary effect factors are found out and the regression equations are set to optimize the system process, predigest the system structure and to forecast the experimental results. (authors)

Assessment of children with suspected auditory processing disorder: a factor analysis study.

Science.gov (United States)

Ahmmed, Ansar U; Ahmmed, Afsara A; Bath, Julie R; Ferguson, Melanie A; Plack, Christopher J; Moore, David R

2014-01-01

To identify the factors that may underlie the deficits in children with listening difficulties, despite normal pure-tone audiograms. These children may have auditory processing disorder (APD), but there is no universally agreed consensus as to what constitutes APD. The authors therefore refer to these children as children with suspected APD (susAPD) and aim to clarify the role of attention, cognition, memory, sensorimotor processing speed, speech, and nonspeech auditory processing in susAPD. It was expected that a factor analysis would show how nonauditory and supramodal factors relate to auditory behavioral measures in such children with susAPD. This would facilitate greater understanding of the nature of listening difficulties, thus further helping with characterizing APD and designing multimodal test batteries to diagnose APD. Factor analysis of outcomes from 110 children (68 male, 42 female; aged 6 to 11 years) with susAPD on a widely used clinical test battery (SCAN-C) and a research test battery (MRC Institute of Hearing Research Multi-center Auditory Processing "IMAP"), that have age-based normative data. The IMAP included backward masking, simultaneous masking, frequency discrimination, nonverbal intelligence, working memory, reading, alerting attention and motor reaction times to auditory and visual stimuli. SCAN-C included monaural low-redundancy speech (auditory closure and speech in noise) and dichotic listening tests (competing words and competing sentences) that assess divided auditory attention and hence executive attention. Three factors were extracted: "general auditory processing," "working memory and executive attention," and "processing speed and alerting attention." Frequency discrimination, backward masking, simultaneous masking, and monaural low-redundancy speech tests represented the "general auditory processing" factor. Dichotic listening and the IMAP cognitive tests (apart from nonverbal intelligence) were represented in the "working

Kernel parameter dependence in spatial factor analysis

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2010-01-01

kernel PCA. Shawe-Taylor and Cristianini [4] is an excellent reference for kernel methods in general. Bishop [5] and Press et al. [6] describe kernel methods among many other subjects. The kernel version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional...... feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply a kernel version of maximum autocorrelation factor (MAF) [7, 8] analysis to irregularly sampled stream sediment geochemistry data from South Greenland and illustrate the dependence...... of the kernel width. The 2,097 samples each covering on average 5 km2 are analyzed chemically for the content of 41 elements....

Delineation of geochemical anomalies based on stream sediment data utilizing fractal modeling and staged factor analysis

Science.gov (United States)

Afzal, Peyman; Mirzaei, Misagh; Yousefi, Mahyar; Adib, Ahmad; Khalajmasoumi, Masoumeh; Zarifi, Afshar Zia; Foster, Patrick; Yasrebi, Amir Bijan

2016-07-01

Recognition of significant geochemical signatures and separation of geochemical anomalies from background are critical issues in interpretation of stream sediment data to define exploration targets. In this paper, we used staged factor analysis in conjunction with the concentration-number (C-N) fractal model to generate exploration targets for prospecting Cr and Fe mineralization in Balvard area, SE Iran. The results show coexistence of derived multi-element geochemical signatures of the deposit-type sought and ultramafic-mafic rocks in the NE and northern parts of the study area indicating significant chromite and iron ore prospects. In this regard, application of staged factor analysis and fractal modeling resulted in recognition of significant multi-element signatures that have a high spatial association with host lithological units of the deposit-type sought, and therefore, the generated targets are reliable for further prospecting of the deposit in the study area.

Potential risk factors associated with human alveolar echinococcosis: Systematic review and meta-analysis.

Science.gov (United States)

Conraths, Franz J; Probst, Carolina; Possenti, Alessia; Boufana, Belgees; Saulle, Rosella; La Torre, Giuseppe; Busani, Luca; Casulli, Adriano

2017-07-01

Human alveolar echinococcosis (AE) is a severe zoonotic disease caused by the metacestode stage of Echinococcus multilocularis. AE is commonly associated with a long incubation period that may last for more than ten years. The objective of this systematic literature review was to identify and summarize the current knowledge on statistically relevant potential risk factors (PRFs) associated with AE in humans. Six bibliographic databases were searched, generating a total of 1,009 publications. Following the removal of duplicate records and the exclusion of papers that failed to meet the criteria of a previously agreed a priori protocol, 23 publications were retained; however, 6 of these did not contain data in a format that allowed their inclusion in the meta-analysis. The remaining 17 publications (6 case-control and 11 cross-sectional studies) were meta-analysed to investigate associations between AE and PRFs. Pooled odds ratios (OR) were used as a measure of effect and separately analysed for case-control and cross-sectional studies. In the case-control studies, the following PRFs for human AE showed higher odds of outcome: "dog ownership", "cat ownership", "have a kitchen garden", "occupation: farmer", "haymaking in meadows not adjacent to water", "went to forests for vocational reasons", "chewed grass" and "hunting / handling foxes". In the cross-sectional studies, the following PRFs showed higher odds of outcome: "dog ownership", "play with dogs", "gender: female", "age over 20 years", "ethnic group: Tibetan", "low income", "source of drinking water other than well or tap", "occupation: herding" and "low education". Our meta-analysis confirmed that the chance of AE transmission through ingestion of food and water contaminated with E. multilocularis eggs exists, but showed also that food- and water-borne PRFs do not significantly increase the risk of infection. This systematic review analysed international peer-reviewed articles that have over the years

Potential risk factors associated with human alveolar echinococcosis: Systematic review and meta-analysis.

Directory of Open Access Journals (Sweden)

Franz J Conraths

2017-07-01

Full Text Available Human alveolar echinococcosis (AE is a severe zoonotic disease caused by the metacestode stage of Echinococcus multilocularis. AE is commonly associated with a long incubation period that may last for more than ten years. The objective of this systematic literature review was to identify and summarize the current knowledge on statistically relevant potential risk factors (PRFs associated with AE in humans.Six bibliographic databases were searched, generating a total of 1,009 publications. Following the removal of duplicate records and the exclusion of papers that failed to meet the criteria of a previously agreed a priori protocol, 23 publications were retained; however, 6 of these did not contain data in a format that allowed their inclusion in the meta-analysis. The remaining 17 publications (6 case-control and 11 cross-sectional studies were meta-analysed to investigate associations between AE and PRFs. Pooled odds ratios (OR were used as a measure of effect and separately analysed for case-control and cross-sectional studies. In the case-control studies, the following PRFs for human AE showed higher odds of outcome: "dog ownership", "cat ownership", "have a kitchen garden", "occupation: farmer", "haymaking in meadows not adjacent to water", "went to forests for vocational reasons", "chewed grass" and "hunting / handling foxes". In the cross-sectional studies, the following PRFs showed higher odds of outcome: "dog ownership", "play with dogs", "gender: female", "age over 20 years", "ethnic group: Tibetan", "low income", "source of drinking water other than well or tap", "occupation: herding" and "low education". Our meta-analysis confirmed that the chance of AE transmission through ingestion of food and water contaminated with E. multilocularis eggs exists, but showed also that food- and water-borne PRFs do not significantly increase the risk of infection.This systematic review analysed international peer-reviewed articles that have over the

Biosphere dose conversion Factor Importance and Sensitivity Analysis

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

This report presents importance and sensitivity analysis for the environmental radiation model for Yucca Mountain, Nevada (ERMYN). ERMYN is a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis concerns the output of the model, biosphere dose conversion factors (BDCFs) for the groundwater, and the volcanic ash exposure scenarios. It identifies important processes and parameters that influence the BDCF values and distributions, enhances understanding of the relative importance of the physical and environmental processes on the outcome of the biosphere model, includes a detailed pathway analysis for key radionuclides, and evaluates the appropriateness of selected parameter values that are not site-specific or have large uncertainty

Paediatric lower limb deformity correction using the Ilizarov technique: a statistical analysis of factors affecting the complication rate.

Science.gov (United States)

Oostenbroek, Hubert J; Brand, Ronald; van Roermund, Peter M; Castelein, René M

2014-01-01

Limb length discrepancy (LLD) and other patient factors are thought to influence the complication rate in (paediatric) limb deformity correction. In the literature, information is conflicting. This study was performed to identify clinical factors that affect the complication rate in paediatric lower-limb lengthening. A consecutive group of 37 children was analysed. The median proportionate LLD was 15 (4-42)%. An analysis was carried out on several patient factors that may complicate the treatment or end result using logistic regression in a polytomous logistic regression model. The factors analysed were proportionate LLD, cause of deformity, location of corrected bone, and the classification of the deformity according to an overall classification that includes the LLD and all concomitant deformity factors. The median age at the start of the treatment was 11 (6-17) years. The median lengthening index was 1.5 (0.8-3.8) months per centimetre lengthening. The obstacle and complication rate was 69% per lengthened bone. Proportionate LLD was the only statistically significant predictor for the occurrence of complications. Concomitant deformities did not influence the complication rate. From these data we constructed a simple graph that shows the relationship between proportionate LLD and risk for complications. This study shows that only relative LLD is a predictor of the risk for complications. The additional value of this analysis is the production of a simple graph. Construction of this graph using data of a patient group (for example, your own) may allow a more realistic comparison with results in the literature than has been possible before.

Common Factor Analysis Versus Principal Component Analysis: Choice for Symptom Cluster Research

Directory of Open Access Journals (Sweden)

Hee-Ju Kim, PhD, RN

2008-03-01

Conclusion: If the study purpose is to explain correlations among variables and to examine the structure of the data (this is usual for most cases in symptom cluster research, CFA provides a more accurate result. If the purpose of a study is to summarize data with a smaller number of variables, PCA is the choice. PCA can also be used as an initial step in CFA because it provides information regarding the maximum number and nature of factors. In using factor analysis for symptom cluster research, several issues need to be considered, including subjectivity of solution, sample size, symptom selection, and level of measure.

Different anthropometric adiposity measures and their association with cardiovascular disease risk factors: a meta-analysis.

Science.gov (United States)

van Dijk, S B; Takken, T; Prinsen, E C; Wittink, H

2012-05-01

To investigate which anthropometric adiposity measure has the strongest association with cardiovascular disease (CVD) risk factors in Caucasian men and women without a history of CVD. Systematic review and meta-analysis. We searched databases for studies reporting correlations between anthropometric adiposity measures and CVD risk factors in Caucasian subjects without a history of CVD. Body mass index (BMI), waist circumference, waist-to-hip ratio, waist-to-height ratio and body fat percentage were considered the anthropometric adiposity measures. Primary CVD risk factors were: systolic blood pressure, diastolic blood pressure, high density lipoprotein (HDL) cholesterol, triglycerides and fasting glucose. Two independent reviewers performed abstract, full text and data selection. Twenty articles were included describing 21,618 males and 24,139 females. Waist circumference had the strongest correlation with all CVD risk factors for both men and women, except for HDL and LDL in men. When comparing BMI with waist circumference, the latter showed significantly better correlations to CVD risk factors, except for diastolic blood pressure in women and HDL and total cholesterol in men. We recommend the use of waist circumference in clinical and research studies above other anthropometric adiposity measures, especially compared with BMI, when evaluating CVD risk factors.

Experimental Analysis for Factors Affecting the Repeatability of Plastics Injection Molding Tests on the Self-developed Apparatus

Directory of Open Access Journals (Sweden)

Yugang Huang

2013-06-01

Full Text Available Normal 0 false false false IN X-NONE X-NONE MicrosoftInternetExplorer4 To improve the repeatability of the injection molding test result, the affecting factors were investigated by means of experiments. Besides the traditional processing parameter, the factors of test conditions were also considered. In order to focus on the molding process rather than the molded part, the curve measurement of the melt pressure at the entrance to the nozzle was used as the output characteristic. Experiments for polypropylene (PP showed that the injected volume was the key processing parameter. Within the test conditions, the injection number is the most important factor. According to the analysis the operating procedure was improved effectively. Normal 0 false false false IN X-NONE X-NONE MicrosoftInternetExplorer4 Doi: 10.12777/ijse.5.1.6-11 [How to cite this article: Huang, Y., Li, D., Liu, Y. (2013. Experimental Analysis for Factors Affecting the Repeatability of Plastics Injection Molding Tests on the Self-developed Apparatus. International Journal of Science and Engineering, 5(1,6-11. Doi: 10.12777/ijse.5.1.6-11]

[Analysis of prognostic factors after radical resection in 628 patients with stage II or III colon cancer].

Science.gov (United States)

Qin, Qiong; Yang, Lin; Zhou, Ai-ping; Sun, Yong-kun; Song, Yan; DU, Feng; Wang, Jin-wan

2013-03-01

To analyze the clinicopathologic factors related to recurrence and metastasis of stage II or III colon cancer after radical resection. The clinical and pathological data of 628 patients with stage II or III colon cancer after radical resection from Jan. 2005 to Dec. 2008 in our hospital were retrospectively reviewed and analyzed. The overall recurrence and metastasis rate was 28.5% (179/628). The 5-year disease-free survival (DFS) rate was 70.3% and 5-year overall survival (OS) rate was 78.5%. Univariate analysis showed that age, smoking intensity, depth of tumor invasion, lymph node metastasis, TNM stage, gross classification, histological differentiation, blood vessel tumor embolus, tumor gross pathology, multiple primary tumors, preoperative and postoperative serum concentration of CEA and CA19-9, and the regimen of adjuvant chemotherapy were correlated to recurrence and metastasis of colon cancer after radical resection. Multivariate analysis showed that regional lymph node metastasis, TNM stage, the regimen of postoperative adjuvant chemotherapy, and preoperative serum concentration of CEA and CA19-9 were independent factors affecting the prognosis of colon cancer patients. Regional lymph node metastasis, TNM stage, elevated preoperative serum concentration of CEA and CA19-9, the regimen of postoperative adjuvant chemotherapy with single fluorouracil type drug are independent risk factors of recurrence and metastasis in patients with stage II-III colon cancer after radical resection.

Using Factor Analysis to Identify Topic Preferences Within MBA Courses

Directory of Open Access Journals (Sweden)

Earl Chrysler

2003-02-01

Full Text Available This study demonstrates the role of a principal components factor analysis in conducting a gap analysis as to the desired characteristics of business alumni. Typically, gap analyses merely compare the emphases that should be given to areas of inquiry with perceptions of actual emphases. As a result, the focus is upon depth of coverage. A neglected area in need of investigation is the breadth of topic dimensions and their differences between the normative (should offer and the descriptive (actually offer. The implications of factor structures, as well as traditional gap analyses, are developed and discussed in the context of outcomes assessment.

Factor analysis of combined organic and inorganic aerosol mass spectra from high resolution aerosol mass spectrometer measurements

Directory of Open Access Journals (Sweden)

Y. L. Sun

2012-09-01

Full Text Available Positive matrix factorization (PMF was applied to the merged high resolution mass spectra of organic and inorganic aerosols from aerosol mass spectrometer (AMS measurements to investigate the sources and evolution processes of submicron aerosols in New York City in summer 2009. This new approach is able to study the distribution of organic and inorganic species in different types of aerosols, the acidity of organic aerosol (OA factors, and the fragment ion patterns related to photochemical processing. In this study, PMF analysis of the unified AMS spectral matrix resolved 8 factors. The hydrocarbon-like OA (HOA and cooking OA (COA factors contain negligible amounts of inorganic species. The two factors that are primarily ammonium sulfate (SO₄-OA and ammonium nitrate (NO₃-OA, respectively, are overall neutralized. Among all OA factors the organic fraction of SO₄-OA shows the highest degree of oxidation (O/C = 0.69. Two semi-volatile oxygenated OA (OOA factors, i.e., a less oxidized (LO-OOA and a more oxidized (MO-OOA, were also identified. MO-OOA represents local photochemical products with a diurnal profile exhibiting a pronounced noon peak, consistent with those of formaldehyde (HCHO and O_x(= O₃ + NO₂. The NO⁺/NO₂⁺ ion ratio in MO-OOA is much higher than that in NO₃-OA and in pure ammonium nitrate, indicating the formation of organic nitrates. The nitrogen-enriched OA (NOA factor contains ~25% of acidic inorganic salts, suggesting the formation of secondary OA via acid-base reactions of amines. The size distributions of OA factors derived from the size-resolved mass spectra show distinct diurnal evolving behaviors but overall a progressing evolution from smaller to larger particle mode as the oxidation degree of OA increases. Our results demonstrate that PMF analysis of the unified aerosol mass spectral matrix which contains both

Risk Factors for Acquired Rifamycin and Isoniazid Resistance: A Systematic Review and Meta-Analysis.

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Neesha Rockwood

Full Text Available Studies looking at acquired drug resistance (ADR are diverse with respect to geographical distribution, HIV co-infection rates, retreatment status and programmatic factors such as regimens administered and directly observed therapy. Our objective was to examine and consolidate evidence from clinical studies of the multifactorial aetiology of acquired rifamycin and/or isoniazid resistance within the scope of a single systematic review. This is important to inform policy and identify key areas for further studies.Case-control and cohort studies and randomised controlled trials that reported ADR as an outcome during antitubercular treatment regimens including a rifamycin and examined the association of at least 1 risk factor were included. Post hoc, we carried out random effects Mantel-Haenszel weighted meta-analyses of the impact of 2 key risk factors 1 HIV and 2 baseline drug resistance on the binary outcome of ADR. Heterogeneity was assessed used I2 statistic. As a secondary outcome, we calculated median cumulative incidence of ADR, weighted by the sample size of the studies.Meta-analysis of 15 studies showed increased risk of ADR with baseline mono- or polyresistance (RR 4.85 95% CI 3.26 to 7.23, heterogeneity I2 58%, 95% CI 26 to 76%. Meta-analysis of 8 studies showed that HIV co-infection was associated with increased risk of ADR (RR 3.02, 95% CI 1.28 to 7.11; there was considerable heterogeneity amongst these studies (I2 81%, 95% CI 64 to 90%. Non-adherence, extrapulmonary/disseminated disease and advanced immunosuppression in HIV co-infection were other risk factors noted. The weighted median cumulative incidence of acquired multi drug resistance calculated in 24 studies (assuming whole cohort as denominator, regardless of follow up DST was 0.1% (5th to 95th percentile 0.07 to 3.2%.Baseline drug resistance and HIV co-infection were significant risk factors for ADR. There was a trend of positive association with non-adherence which is likely

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

Directory of Open Access Journals (Sweden)

Dugwon Seo

2010-05-01

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

Analysis of corrosive environmental factors of seabed sediment

Indian Academy of Sciences (India)

Unknown

Seabed sediment; corrosion; environmental factors. 1. Introduction. The corrosion ... plays an important role in the corrosion behaviour of steel in sediment. Figure 2b shows the change in oxidation-reduction po- tential, Eh with distance from ...

[Analysis of lifestyle and risk factors of atherosclerosis in students of selected universities in Krakow].

Science.gov (United States)

Skrzypek, Agnieszka; Szeliga, Marta; Stalmach-Przygoda, Agata; Kowalska, Bogumila; Jabłoński, Konrad; Nowakowski, Michal

Reduction of risk factors of atherosclerosis, lifestyle modification significantly cause the reduction in the incidence, morbidity and mortality of cardiovascular diseases (CVDs). Objective: To evaluate cardiovascular risk factors and analyze the lifestyle of students finishing the first year of studies at selected universities in Krakow. The study was performed in 2015roku. 566 students finishing the first year of study, including 319 (56.4%) men and 247 (43.6%) women were examined. The students were in age from 18 to 27 years, an average of 20.11± 1.15 years. They represented 6 different universities in Cracow. In order to assess eating habits, lifestyle and analysis of risk factors of cardiovascular disease was used method of diagnostic survey using the survey technique. BMI was calculated from anthropometric measurements. The program Statistica 12.0 were used in statistical analysis. The analysis showed that most fruits and vegetables consume UR students and AWF, least of AGH. Only 34.8% of students regularly consume fish of the sea, there were no significant differences between universities. Sports frequently cultivate the students of AWF (93% of the students of this university). Academy of Fine Arts students drink the most coffee. Students of AGH frequently consume alcohol. 60% of all students never tried drugs, but only 25.7% of student of Fine Arts never tried drugs. Overweight occurs in 12.6% of students, and obesity in 1.1%. The most risk factors of atherosclerosis occur in students of AGH and ASP. The results of the study clearly indicate on the necessity of implementation of prevention and improvement of health behaviors in students of AGH and ASP universities.

Analysis on Developmental Factors of the Liver Diseases in Ultrasound Diagnosis of Healthcare

Energy Technology Data Exchange (ETDEWEB)

Lee, Mi Yeon [Dept. of Radiology of Healthcare Center Kyobo Life Insurance Science, Seoul (Korea, Republic of); Jung, Hong Ryang; Lim, Chang Hwan [Dept. of Radiological Science, Hanseo University, Seosan (Korea, Republic of)

2009-03-15

The study found out developmental factors of the liver diseases in 29, 531 cases of the healthy adults who were diagnosed by using ultrasound at domestic healthcare centers in 6 cities. The results are as follows. Based on the result of the study, the liver diseases diagnosed by using ultrasound was revealed to show 43.1% of prevalence, and the occurrence was significantly higher in male (23.3%) than in female (19.8%). The prevalence of hepatic diseases related to the BMI was revealed to show highest prevalence of the fatty liver in obese group (BMI 25) by recording 44.3%. Smoking contributed to the high prevalence of all liver diseases. Although the fatty liver was the most frequently occurred form of liver diseases by recording the prevalence of 49.1% (22.2% in male, 26.9% in female), the significant difference was found only in female (p < 0.05), but male group did not show significant difference (p > 0.05). The prevalence of hepatic diseases related to the hypertension was revealed to show highest prevalence of the fatty liver in hypertension group by recording 67.7%. The prevalence of hepatic diseases related to the diabetes was revealed to show highest prevalence of the fatty liver in diabetes group by recording 66.2%. The high prevalence of all hepatic diseases was related to diabetes mellitus with statistical significance (p < 0.001). The multiple regression analysis for the related factors which affect the prevalence of the liver diseases showed the higher prevalence by age. Sex, obesity and diabetes mellitus were positively related to the prevalence (p < 0.05) while hypertension and smoking showed no significant relationship to the prevalence of the disease (p > 0.05).

Confirmatory Factor Analysis of the French Version of the Anticipatory and Consummatory Interpersonal Pleasure Scale

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Joséphine Chaix

2017-07-01

Full Text Available The Anticipatory and Consummatory Interpersonal Pleasure Scale (ACIPS, a measure specifically designed to assess hedonic capacity for social and interpersonal pleasure, was used to evaluate the presence of social anhedonia in patients as well as the general population. The first goal of this study was to validate the structure of the French version of the ACIPS. The second objective was to verify whether a one, two or three factor solution is most appropriate for the ACIPS scale. The French version of the ACIPS was tested on 263 French-speaking pre-graduate students or professional volunteers. For the confirmatory factor analysis, data were treated as categorical ordinal and all the models were estimated using a robust weighted least squares estimator with adjustments for the mean and variance. Three models were estimated. A one-factor model representing a general undifferentiated “pleasure” latent construct was first tested on the 17 ACIPS items. A two-factor model distinguishing anticipatory-pleasure and consummatory-pleasure was tested next. Finally, a three-factor model including subdomains of intimate social interactions, group social interactions, and social bonding was tested. The one and two-factor models showed a somewhat poor fit to the data. However, the goodness of fit of the three factor model was adequate. These results suggest that individuals who enjoyed interaction in one of these three subdomains were more likely to enjoy doing so in the two other domains. However, on the basis of the comparison between the one and three factor models, these three types of interactions may not be considered as indistinguishable. Rather, they represent distinct and theoretically meaningful dimensions. These results show the French version of the ACIPS is a useful and valid scale to measure the capacity of savoring different kinds of social relationships.

Analysis of clinical factors for pathological complete response after preoperative neoadjuvant chemoradiotherapy for rectal cancer

International Nuclear Information System (INIS)

Ayiguli Hare; Palida Apizi; Iskandar Abulimiti; Zhang Jinrong; Tian Hanhan

2014-01-01

Objective: To evaluate the clinical factors associated with pathological complete response (pCR) after preoperative neoadjuvant chemoradiotherapy for rectal cancer. Methods: A retrospective analysis was performed on the clinical data of 116 patients with rectal cancer, who underwent neoadjuvant chemoradiotherapy followed by radical surgery from January 2009 to December 2012. All patients received pelvic intensity-modulated radiotherapy (50 Gy/25 fractions) with concurrent fluorouracil based chemotherapy and then underwent radical surgery 4-8 weeks later. The clinical factors associated with pCR or non-pCR were analyzed by Logistic regression. Results: Of the 116 patients, 20 (17.2%) achieved a pCR after neoadjuvant chemoradiotherapy. The univariate analysis showed that percentage of circumference of the rectal tube invaded by the tumor, preoperative serum carcinoembryonic antigen (CEA) level, T stage, N stage, distance from the anal verge, degree of tumor differentiation, and maximum tumor diameter were associated with pCR or non-pCR after neoadjuvant chemoradiotherapy for rectal cancer. The multivariate analysis revealed that percentage of circumference of the rectal tube invaded by the tumor, preoperative serum CEA level,and T stage were predictive factors for pCR or non-pCR after neoadjuvant chemoradiotherapy for rectal cancer. Conclusions: Non-circumferential tumor (percentage of circumference of the rectal tube invaded by the tumor <75 %), low CEA level, and early T stage before treatment may be associated with pCR after neoadjuvant chemoradiotherapy for rectal cancer. (authors)

Modular Open-Source Software for Item Factor Analysis

Science.gov (United States)

Pritikin, Joshua N.; Hunter, Micheal D.; Boker, Steven M.

2015-01-01

This article introduces an item factor analysis (IFA) module for "OpenMx," a free, open-source, and modular statistical modeling package that runs within the R programming environment on GNU/Linux, Mac OS X, and Microsoft Windows. The IFA module offers a novel model specification language that is well suited to programmatic generation…

Which factors enhance positive drug reimbursement recommendation in Scotland? A retrospective analysis 2006-2013.

Science.gov (United States)

Charokopou, Mata; Majer, Istvan M; Raad, Johan de; Broekhuizen, Stefan; Postma, Maarten; Heeg, Bart

2015-03-01

To identify the factors that influence the Scottish Medicines Consortium (SMC) in deciding whether to accept pharmaceutical technologies for use within the Scottish health care system. A database of SMC submissions between 2006 and 2013 was created, containing a range of clinical, economic, and other factors extracted from published health technology assessment reports. A binomial outcome variable was used, defined as the decision to "accept for use" or "not recommend" a technology. Univariate and multivariate analyses were conducted to assess the impact by means of odds ratios (ORs) of the submitted evidence on the recommendation decision. Out of 463 applications, 265 were accepted for use (57%) and 198 (43%) were not recommended for use within National Health Service Scotland. Univariate analyses showed that 13 variables significantly affected the SMC decision. Of these 13 variables, 7 variables were shown to have a meaningful impact in the multivariate analysis. Four of these concerned the outcome of cost-effectiveness analyses; the fact that a submission was supported by a cost-minimization analysis was the strongest positive variable (OR = 10.30) and a submission showing a product not being cost-effective (i.e., incremental cost-effectiveness ratio above £30,000/quality-adjusted life-year gained) was the strongest negative predictor (OR = 0.47). The other variables concerned whether the submission was related to a product indicated for a nervous system disease (OR = 0.41), whether it was indicated for nonchronic use (OR = 1.66), and whether the submission was performed by a big company (OR = 2.83). This study demonstrated that the outcome of cost-effectiveness analyses is an important factor affecting the SMC's reimbursement recommendation decision. Copyright © 2015. Published by Elsevier Inc.

Analysis of the Survival of Children Under Five in Indonesia and Associated Factors

Science.gov (United States)

Nur Islami Warrohmah, Annisa; Maniar Berliana, Sarni; Nursalam, Nursalam; Efendi, Ferry; Haryanto, Joni; Has, Eka Misbahatul M.; Ulfiana, Elida; Dwi Wahyuni, Sylvia

2018-02-01

The under-five mortality rate (U5MR) remains a challenge for developing nations, including Indonesia. This study aims to assess the key factors associated with mortality of Indonesian infants using survival analysis. Data taken from 14,727 live-born infants (2007-2012) was examined from the nationally representative Indonesian Demographic Health Survey. The Weibull hazard model was performed to analyse the socioeconomic status and related determinants of infant mortality. The findings indicated that mother factors (education, working status, autonomy, economic status, maternal age at birth, birth interval, type of births, complications, history of previous mortality, breastfeeding, antenatal care and place of delivery); infant factors (birth size); residence; and environmental conditions were associated with the childhood mortality. Rural or urban residence was an important determining factor of infant mortality. For example, considering the factor of a mother’s education, rural educated mothers had a significant association with the survival of their infants. In contrast, there was no significant association between urban educated mothers and their infants’ mortality. The results showed obvious contextual differences which determine the childhood mortality. Socio-demographic and economic factors remain critical in determining the death of infants. This study provides evidence for designing targeted interventions, as well as suggesting specific needs based on the population’s place of residence, in the issue of U5MR. Further interventions should also consider other identified variables while developing programmes to address infant’s needs.

Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.

Science.gov (United States)

Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod

2017-07-15

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal

Dual-Tracer PET Using Generalized Factor Analysis of Dynamic Sequences

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Fakhri, Georges El; Trott, Cathryn M.; Sitek, Arkadiusz; Bonab, Ali; Alpert, Nathaniel M.

2013-01-01

Purpose With single-photon emission computed tomography, simultaneous imaging of two physiological processes relies on discrimination of the energy of the emitted gamma rays, whereas the application of dual-tracer imaging to positron emission tomography (PET) imaging has been limited by the characteristic 511-keV emissions. Procedures To address this limitation, we developed a novel approach based on generalized factor analysis of dynamic sequences (GFADS) that exploits spatio-temporal differences between radiotracers and applied it to near-simultaneous imaging of 2-deoxy-2-[18F]fluoro-D-glucose (FDG) (brain metabolism) and 11C-raclopride (D2) with simulated human data and experimental rhesus monkey data. We show theoretically and verify by simulation and measurement that GFADS can separate FDG and raclopride measurements that are made nearly simultaneously. Results The theoretical development shows that GFADS can decompose the studies at several levels: (1) It decomposes the FDG and raclopride study so that they can be analyzed as though they were obtained separately. (2) If additional physiologic/anatomic constraints can be imposed, further decomposition is possible. (3) For the example of raclopride, specific and nonspecific binding can be determined on a pixel-by-pixel basis. We found good agreement between the estimated GFADS factors and the simulated ground truth time activity curves (TACs), and between the GFADS factor images and the corresponding ground truth activity distributions with errors less than 7.3±1.3 %. Biases in estimation of specific D2 binding and relative metabolism activity were within 5.9±3.6 % compared to the ground truth values. We also evaluated our approach in simultaneous dual-isotope brain PET studies in a rhesus monkey and obtained accuracy of better than 6 % in a mid-striatal volume, for striatal activity estimation. Conclusions Dynamic image sequences acquired following near-simultaneous injection of two PET radiopharmaceuticals

Identification of advanced human factors engineering analysis, design and evaluation methods

International Nuclear Information System (INIS)

Plott, C.; Ronan, A. M.; Laux, L.; Bzostek, J.; Milanski, J.; Scheff, S.

2006-01-01

NUREG-0711 Rev.2, 'Human Factors Engineering Program Review Model,' provides comprehensive guidance to the Nuclear Regulatory Commission (NRC) in assessing the human factors practices employed by license applicants for Nuclear Power Plant control room designs. As software based human-system interface (HSI) technologies supplant traditional hardware-based technologies, the NRC may encounter new HSI technologies or seemingly unconventional approaches to human factors design, analysis, and evaluation methods which NUREG-0711 does not anticipate. A comprehensive survey was performed to identify advanced human factors engineering analysis, design and evaluation methods, tools, and technologies that the NRC may encounter in near term future licensee applications. A review was conducted to identify human factors methods, tools, and technologies relevant to each review element of NUREG-0711. Additionally emerging trends in technology which have the potential to impact review elements, such as Augmented Cognition, and various wireless tools and technologies were identified. The purpose of this paper is to provide an overview of the survey results and to highlight issues that could be revised or adapted to meet with emerging trends. (authors)

Meta-analysis Number of Plants Drugs Used by Characteristics Socioeconomic Factors, Environmental and Geographic

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Febiola Diah Pratiwi

2017-09-01

Full Text Available Ethnobotany is the study of public relations with the use of plants. Use of plants by people influenced by several factors, such as social, cultural, socioeconomic, and geographic. Most of the ethnicities in Indonesia has a high dependence on plants medicine for survival. However, the factors that influence the use of medicinal plants by people in Indonesia have not been studied, so that research is needed to optimize the use of medicinal plants to sustainability benefits. The purpose of this study is to analyze the number of species of plants medicine used by the influence of socio-economic, environmental, and geographic factors using principal component analysis and analyzing patterns of use of plants medicine. The results showed that the economy and infrastructure components (access to electricity, means of education, income level, health facilities, distance from the highway, remoteness, and the fastest time toward the road and the number of people graduating from elementary school affect the number of medicinal plant species used. Based on the results of the study of literature and field observations, the pattern of use of plants medicine in addition to be used as medicine, the plant is used for food, building materials, plant ornamental, ceremonial, wood, wicker and crafts, coloring agents, animal feed, ingredients aromatic, and pesticide. The usage patterns in each region or village has the distinction of which is influenced by the remoteness factor due to the differences in the social, economic, environmental, and geographic.  Keywords: ethnobotany, plants medicine, principal component analysis

Molecular cloning, characterization and expression analysis of coagulation factor VII gene in grass carp (Ctenopharyngodon idella).

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Liu, Qiaolin; Xu, Baohong; Xiao, Tiaoyi; Su, Jianming; Zhong, Lei

2013-08-01

Coagulation factor VII has been studied in several species but, to date, not in grass carp (Ctenopharyngodon idella), a commercially important freshwater fish found in China. In this study, the full-length cDNA of grass carp coagulation factor VII (GcCFVII) was cloned using a RACE-Ready cDNA Kit, grass carp were challenged with a hemorrhagic virus, and temporal expression profiles of GcCFVII in the thymus, gills, liver, spleen, and head kidney were examined at 0 h, 24 h, 48 h, 72 h, 96 h, and 138 h using fluorescence quantitative PCR. The results showed the 1480 bp GcCFVII to contain three conservative motifs: Gla, EGF-CA, and Tryp-SPc, similar to other species. Phylogenetic analysis showed the evolution of GcCFVII gene to be consistent with the evolution of the species. After viral challenge, GcCFVII expression in five tissues of grass carp showed different patterns of fluctuation. These results provide a solid basis for further investigation of GcCFVII and its relationship with grass carp hemorrhage. Copyright © 2013 Elsevier Ltd. All rights reserved.

Analysis of risk factors in the development of retinopathy of prematurity.

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Knezević, Sanja; Stojanović, Nadezda; Oros, Ana; Savić, Dragana; Simović, Aleksandra; Knezević, Jasmina

2011-01-01

Retinopathy of prematurity (ROP) is a multifactorial disease that occurs most frequently in very small and very sick preterm infants, and it has been identified as the major cause of childhood blindness. The aim of this study was to evaluate ROP incidence and risk factors associated with varying degrees of illness. The study was conducted at the Centre for Neonatology, Paediatric Clinic of the Clinical Centre Kragujevac, Serbia, in the period from June 2006 to December 2008. Ophthalmologic screening was performed in all children with body weight lower than 2000 g or gestational age lower than 36 weeks. We analyzed eighteen postnatal and six perinatal risk factors and the group correlations for each of the risk factors. Out of 317 children that were screened, 56 (17.7%) developed a mild form of ROP, while 68 (21.5%) developed a severe form. Univariate analysis revealed a large number of statistically significant risk factors for the development of ROP, especially the severe form. Multivariate logistical analysis further separated two independent risk factors: small birth weight (p = 0.001) and damage of central nervous system (p = 0.01). Independent risk factors for transition from mild to severe forms of ROP were identified as: small birth weight (p = 0.05) and perinatal risk factors (p = 0.02). Small birth weight and central nervous system damage were risk factors for the development of ROP, perinatal risk factors were identified as significant for transition from mild to severe form of ROP.

Breast Cancer Risk From Modifiable and Non-Modifiable Risk Factors among Women in Southeast Asia: A Meta-Analysis

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Nindrea, Ricvan Dana; Aryandono, Teguh; Lazuardi, Lutfan

2017-12-28

Objective: The aim of this study was to determine breast cancer risk from modifiable and non-modifiable factors among women in Southeast Asia. Methods: This meta-analysis was performed on research articles on breast cancer risk factors in PubMed, ProQuest and EBSCO databases published between 1997 and October 2017. Pooled odds ratios (OR) are calculated using fixed and random-effect models. Data were processed using Review Manager 5.3 (RevMan 5.3). Results: From a total of 1,211 articles, 15 studies (1 cohort and 14 case control studies) met the criteria for systematic review. Meta-analysis results showed that of the known modifiable risk factors for breast cancer, parity (nulipara) had the highest odd ratio (OR = 1.85 [95% CI 1.47-2.32]) followed by body mass index (overweight) (OR = 1.61 [95% CI 1.43-1.80]) and use of oral contraceptives (OR = 1.27 [95% CI 1.07-1.51]). Of non-modifiable risk factors, family history of breast cancer had the highest odd ratio (OR = 2.53 [95% CI 1.25-5.09]), followed by age (≥ 40 years) (OR = 1.53 [95% CI 1.34-1.76]) and menopausal status (OR = 1.44 [95% CI 1.26-1.65]). Conclusion: This analysis confirmed associations between both modifiable risk factors (parity, body mass index and use of oral contraceptives) and non-modifiable risk factors (family history of breast cancer, age and menopausal status) with breast cancer. Creative Commons Attribution License

Analysis of Prognostic Factors in 541 Female Patients with Advanced Non-small Cell Lung Cancer

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Meina WU

2011-03-01

Full Text Available Background and objective As there is a sharp increase in the incidence of lung cancer in women in recent years, it has brought broad concerns with its unique clinical and epidemiological characteristics and better prognosis. The aim of this study is to analyze the clinical data of women with advanced non-small cell lung cancer (NSCLC retrospectively to explore the prognostic factors. Methods Clinical data of 541 female patients with advanced NSCLC were collected and followed up till death. The primary endpoint is overall survival (OS. SPSS 11.0 statistical analysis software was used for univariate and multivariate analysis. Results The mean age is 59 years (20 years-86 years, adenocarcinoma account for 80.2% (434/541. The median OS was 15 months (95%CI: 13.87-16.13, and 1, 2, 5-year survival rates were 58.8%, 23.7% and 3.20% respectively. Univariate analysis showed that clinical stage, ECOG score, weight loss, clinical symptoms, liver/bone/brain metastasis and received more than one chemotherapy regimen, good response to the first-line chemotherapy, EGFR-TKI targeted therapy and radiotherapy treatment were significantly correlated with the OS and survival rate (P < 0.05. Combined with multivariate analysis, weight loss before treatment, ECOG score, received EGFR-TKI targeted therapy and response to first-line chemotherapy were independent prognostic factor for survival (P < 0.05. Conclusion There is a higher percentage of adenocarcinoma in female NSCLC. Weight loss before treatment, ECOG score, EGFR-TKI targeted therapy and response to first-line chemotherapy may become independent prognostic factors for survival of female patients with advanced NSCLC.

Singaporean Adolescents' Perceptions of Online Social Communication: An Exploratory Factor Analysis

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Zheng, Robert Z.; Cheok, Angeline; Khoo, Eng

2011-01-01

The current study investigated adolescents' perceptions in online social communication. Three factors were perceived by adolescents as critical to online social communication. These included self-identity, self-confidence, and self-social factors. Results showed significant differences between the factors derived from the current study and those…

Factors Affecting Green Residential Building Development: Social Network Analysis

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Xiaodong Yang

2018-05-01

Full Text Available Green residential buildings (GRBs are one of the effective practices of energy saving and emission reduction in the construction industry. However, many real estate developers in China are less willing to develop GRBs, because of the factors affecting green residential building development (GRBD. In order to promote the sustainable development of GRBs in China, this paper, based on the perspective of real estate developers, identifies the influential and critical factors affecting GRBD, using the method of social network analysis (SNA. Firstly, 14 factors affecting GRBD are determined from 64 preliminary factors of three main elements, and the framework is established. Secondly, the relationships between the 14 factors are analyzed by SNA. Finally, four critical factors for GRBD, which are on the local economy development level, development strategy and innovation orientation, developer’s acknowledgement and positioning for GRBD, and experience and ability for GRBD, are identified by the social network centrality test. The findings illustrate the key issues that affect the development of GRBs, and provide references for policy making by the government and strategy formulation by real estate developers.

Genomic identification of WRKY transcription factors in carrot (Daucus carota) and analysis of evolution and homologous groups for plants.

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Li, Meng-Yao; Xu, Zhi-Sheng; Tian, Chang; Huang, Ying; Wang, Feng; Xiong, Ai-Sheng

2016-03-15

WRKY transcription factors belong to one of the largest transcription factor families. These factors possess functions in plant growth and development, signal transduction, and stress response. Here, we identified 95 DcWRKY genes in carrot based on the carrot genomic and transcriptomic data, and divided them into three groups. Phylogenetic analysis of WRKY proteins from carrot and Arabidopsis divided these proteins into seven subgroups. To elucidate the evolution and distribution of WRKY transcription factors in different species, we constructed a schematic of the phylogenetic tree and compared the WRKY family factors among 22 species, which including plants, slime mold and protozoan. An in-depth study was performed to clarify the homologous factor groups of nine divergent taxa in lower and higher plants. Based on the orthologous factors between carrot and Arabidopsis, 38 DcWRKY proteins were calculated to interact with other proteins in the carrot genome. Yeast two-hybrid assay showed that DcWRKY20 can interact with DcMAPK1 and DcMAPK4. The expression patterns of the selected DcWRKY genes based on transcriptome data and qRT-PCR suggested that those selected DcWRKY genes are involved in root development, biotic and abiotic stress response. This comprehensive analysis provides a basis for investigating the evolution and function of WRKY genes.

A Comparison of Distribution Free and Non-Distribution Free Factor Analysis Methods

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Ritter, Nicola L.

2012-01-01

Many researchers recognize that factor analysis can be conducted on both correlation matrices and variance-covariance matrices. Although most researchers extract factors from non-distribution free or parametric methods, researchers can also extract factors from distribution free or non-parametric methods. The nature of the data dictates the method…

Application of factor analysis in psychological diagnostics (sample: study of students’ social safety

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Pavel Aleksandrovich Kislyakov

2015-10-01

Our recommendations for the use of factor analysis, with necessary restrictions and clear reasons of a possible ambiguity of solutions, will be useful to everyone interested in mastering an adequate mathematical tool for solving problems pertaining to the humanities, in particular, those of practical psychology. As a practical example is presented the research of the psychological factors which provide students’ social safety. With the help of the factor analysis relevant personal and professional qualities of a teacher were revealed which are the subjective factors of students’ social safety, namely: social anticipation, socio-psychological stress resistance, social tolerance, professional orientation, responsibility, communication skills.

Sensitivity Analysis of the USLE Soil Erodibility Factor to Its Determining Parameters

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Mitova, Milena; Rousseva, Svetla

2014-05-01

Soil erosion is recognized as one of the most serious soil threats worldwide. Soil erosion prediction is the first step in soil conservation planning. The Universal Soil Loss Equation (USLE) is one of the most widely used models for soil erosion predictions. One of the five USLE predictors is the soil erodibility factor (K-factor), which evaluates the impact of soil characteristics on soil erosion rates. Soil erodibility nomograph defines K-factor depending on soil characteristics, such as: particle size distribution (fractions finer that 0.002 mm and from 0.1 to 0.002 mm), organic matter content, soil structure and soil profile water permeability. Identifying the soil characteristics, which mostly influence the K-factor would give an opportunity to control the soil loss through erosion by controlling the parameters, which reduce the K-factor value. The aim of the report is to present the results of analysis of the relative weight of these soil characteristics in the K-factor values. The relative impact of the soil characteristics on K-factor was studied through a series of statistical analyses of data from the geographic database for soil erosion risk assessments in Bulgaria. Degree of correlation between K-factor values and the parameters that determine it was studied by correlation analysis. The sensitivity of the K-factor was determined by studying the variance of each parameter within the range between minimum and maximum possible values considering average value of the other factors. Normalizing transformation of data sets was applied because of the different dimensions and the orders of variation of the values of the various parameters. The results show that the content of particles finer than 0.002 mm has the most significant relative impact on the soil erodibility, followed by the content of particles with size from 0.1 mm to 0.002 mm, the class of the water permeability of the soil profile, the content of organic matter and the aggregation class. The

Landslides geotechnical analysis. Qualitative assessment by valuation factors

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Cuanalo Oscar, Sc D.; Oliva Aldo, Sc D.; Polanco Gabriel, M. E.

2012-04-01

In general, a landslide can cause a disaster when it is combined a number of factors such as an extreme event related to a geological phenomenon, vulnerable elements exposed in a specific geographic area, and the probability of loss and damage evaluated in terms of lives and economic assets, in a certain period of time. This paper presents the qualitative evaluation of slope stability through of Valuation Factors, obtained from the characterization of the determinants and triggers factors that influence the instability; for the first the morphology and topography, geology, soil mechanics, hydrogeology and vegetation to the second, the rain, earthquakes, erosion and scour, human activity, and ultimately dependent factors of the stability analysis, and its influence ranges which greatly facilitate the selection of construction processes best suited to improve the behavior of a slope or hillside. The Valuation Factors are a set of parameters for assessing the influence of conditioning and triggering factors that influence the stability of slopes and hillsides. The characteristics of each factor must be properly categorized to involve its effect on behavior; a way to do this is by assigning a weighted value range indicating its effect on the stability of a slope. It is proposed to use Valuation Factors with weighted values between 0 and 1 (arbitrarily selected but common sense and logic), the first corresponds to no or minimal effect on stability (no effect or very little influence) and the second, the greatest impact on it (has a significant influence). The meddle effects are evaluated with intermediate values.

Multi-Scale Factor Analysis of High-Dimensional Brain Signals