Effects of growing location on the production of main active components and antioxidant activity of Dasiphora fruticosa (L.) Rydb. by chemometric methods.

PubMed

Liu, Wei; Wang, Dongmei; Hou, Xiaogai; Yang, Yueqin; Xue, Xian; Jia, Qishi; Zhang, Lixia; Zhao, Wei; Yin, Dongxue

2018-05-17

Traditional Chinese medicine (TCM) plays a very important role in the health system of China. The content and activity of active component are main indexes that evaluate the quality of TCM, however they may vary with environmental factors in their growing locations. In this study, effects of environmental factors on the contents of active components and antioxidant activity of Dasiphora fruticosa from the five main production areas of China were investigated. The contents of tannin, total flavonoid and rutin were determined and varied within the range of 7.65-10.69%, 2.30-5.39% and 0.18-0.81%, respectively. Antioxidant activity was determined by DPPH assay, with the DPPH IC 50 values ranged from 8.791 to 32.534μg mL -1 . In order to further explore the cause of these significant geographical variations, the chemometric methods including correlation analysis, principal component analysis, gray correlation analysis, and path analysis were conducted. The results showed environmental factors had significant effect on the active component contents and antioxidant activity. Rapidly available phosphorus (RAP) and rapidly available nitrogen (RAN) were common dominant factors, and a significant positive correlation was observed between RAP and active components and antioxidant activity (P<0.05). Contributed by their high active components and strong antioxidant activity, Bange in Tibet and Geermu in Qinghai Province was selected as a favorable growing location, respectively. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Psychometric properties of Connor-Davidson Resilience Scale in a Spanish sample of entrepreneurs.

PubMed

Manzano-García, Guadalupe; Ayala Calvo, Juan Carlos

2013-01-01

The literature regarding entrepreneurship suggests that the resilience of entrepreneurs may help to explain entrepreneurial success, but there is no resilience measure widely accepted by researchers. This study analyzes the psychometric properties of the Connor and Davidson Resilience Scale (CD-RISC) in a sample of Spanish entrepreneurs. A telephone survey research method was used. The participants were entrepreneurs operating in the business services sector. Interviewers telephoned a total of 900 entrepreneurs of whom 783 produced usable questionnaires. The CD-RISC was used as data collection instrument. We used principal component analysis factor and confirmatory factor analysis to determine the factor structure of the CD-RISC. Confirmatory factor analysis failed to verify the original five-factor structure of the CD-RISC, whereas principal component analysis factor yielded a 3-factor structure of resilience (hardiness, resourcefulness and optimism). In this research, 47.48% of the total variance was accounted for by three factors, and the obtained factor structure was verified through confirmatory factor analysis. The CD-RISC has been shown to be a reliable and valid tool for measuring entrepreneurs' resilience.

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

PubMed

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

2014-08-01

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

Measuring self-rated productivity: factor structure and variance component analysis of the Health and Work Questionnaire.

PubMed

von Thiele Schwarz, Ulrica; Sjöberg, Anders; Hasson, Henna; Tafvelin, Susanne

2014-12-01

To test the factor structure and variance components of the productivity subscales of the Health and Work Questionnaire (HWQ). A total of 272 individuals from one company answered the HWQ scale, including three dimensions (efficiency, quality, and quantity) that the respondent rated from three perspectives: their own, their supervisor's, and their coworkers'. A confirmatory factor analysis was performed, and common and unique variance components evaluated. A common factor explained 81% of the variance (reliability 0.95). All dimensions and rater perspectives contributed with unique variance. The final model provided a perfect fit to the data. Efficiency, quality, and quantity and three rater perspectives are valid parts of the self-rated productivity measurement model, but with a large common factor. Thus, the HWQ can be analyzed either as one factor or by extracting the unique variance for each subdimension.

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

PubMed

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

2018-01-01

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

Evaluation of Parallel Analysis Methods for Determining the Number of Factors

ERIC Educational Resources Information Center

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…

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

PubMed

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.

Critical Factors Explaining the Leadership Performance of High-Performing Principals

ERIC Educational Resources Information Center

Hutton, Disraeli M.

2018-01-01

The study explored critical factors that explain leadership performance of high-performing principals and examined the relationship between these factors based on the ratings of school constituents in the public school system. The principal component analysis with the use of Varimax Rotation revealed that four components explain 51.1% of the…

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

PubMed

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

2010-10-01

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

Generalized Structured Component Analysis with Uniqueness Terms for Accommodating Measurement Error

PubMed Central

Hwang, Heungsun; Takane, Yoshio; Jung, Kwanghee

2017-01-01

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

Analyzing the development of Indonesia shrimp industry

NASA Astrophysics Data System (ADS)

Wati, L. A.

2018-04-01

This research aimed to analyze the development of shrimp industry in Indonesia. Porter’s Diamond Theory was used for analysis. The Porter’s Diamond theory is one of framework for industry analysis and business strategy development. The Porter’s Diamond theory has five forces that determine the competitive intensity in an industry, namely (1) the threat of substitute products, (2) the threat of competition, (3) the threat of new entrants, (4) bargaining power of suppliers, and (5) bargaining power of consumers. The development of Indonesian shrimp industry pretty good, explained by Porter Diamond Theory analysis. Analysis of Porter Diamond Theory through four main components namely factor conditions; demand condition; related and supporting industries; and firm strategy, structure and rivalry coupled with a two-component supporting (regulatory the government and the factor of chance). Based on the result of this research show that two-component supporting (regulatory the government and the factor of chance) have positive. Related and supporting industries have negative, firm and structure strategy have negative, rivalry has positive, factor condition have positive (except science and technology resources).

Intelligent data analysis to interpret major risk factors for diabetic patients with and without ischemic stroke in a small population

PubMed Central

Gürgen, Fikret; Gürgen, Nurgül

2003-01-01

This study proposes an intelligent data analysis approach to investigate and interpret the distinctive factors of diabetes mellitus patients with and without ischemic (non-embolic type) stroke in a small population. The database consists of a total of 16 features collected from 44 diabetic patients. Features include age, gender, duration of diabetes, cholesterol, high density lipoprotein, triglyceride levels, neuropathy, nephropathy, retinopathy, peripheral vascular disease, myocardial infarction rate, glucose level, medication and blood pressure. Metric and non-metric features are distinguished. First, the mean and covariance of the data are estimated and the correlated components are observed. Second, major components are extracted by principal component analysis. Finally, as common examples of local and global classification approach, a k-nearest neighbor and a high-degree polynomial classifier such as multilayer perceptron are employed for classification with all the components and major components case. Macrovascular changes emerged as the principal distinctive factors of ischemic-stroke in diabetes mellitus. Microvascular changes were generally ineffective discriminators. Recommendations were made according to the rules of evidence-based medicine. Briefly, this case study, based on a small population, supports theories of stroke in diabetes mellitus patients and also concludes that the use of intelligent data analysis improves personalized preventive intervention. PMID:12685939

Identification of atmospheric organic sources using the carbon hollow tube-gas chromatography method and factor analysis

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

Cobb, G.P.; Braman, R.S.; Gilbert, R.A.

Atmospheric organics were sampled and analyzed by using the carbon hollow tube-gas chromatography method. Chromatograms from spice mixtures, cigarettes, and ambient air were analyzed. Principal factor analysis of row order chromatographic data produces factors which are eigenchromatograms of the components in the samples. Component sources are identified from the eigenchromatograms in all experiments and the individual eigenchromatogram corresponding to a particular source is determined in most cases. Organic sources in ambient air and in cigaretts are identified with 87% certainty. Analysis of clove cigarettes allows the determination of the relative amount of clove in different cigarettes. A new nondestructive qualitymore » control method using the hollow tube-gas chromatography analysis is discussed.« less

A mixture model with a reference-based automatic selection of components for disease classification from protein and/or gene expression levels

PubMed Central

2011-01-01

Background Bioinformatics data analysis is often using linear mixture model representing samples as additive mixture of components. Properly constrained blind matrix factorization methods extract those components using mixture samples only. However, automatic selection of extracted components to be retained for classification analysis remains an open issue. Results The method proposed here is applied to well-studied protein and genomic datasets of ovarian, prostate and colon cancers to extract components for disease prediction. It achieves average sensitivities of: 96.2 (sd = 2.7%), 97.6% (sd = 2.8%) and 90.8% (sd = 5.5%) and average specificities of: 93.6% (sd = 4.1%), 99% (sd = 2.2%) and 79.4% (sd = 9.8%) in 100 independent two-fold cross-validations. Conclusions We propose an additive mixture model of a sample for feature extraction using, in principle, sparseness constrained factorization on a sample-by-sample basis. As opposed to that, existing methods factorize complete dataset simultaneously. The sample model is composed of a reference sample representing control and/or case (disease) groups and a test sample. Each sample is decomposed into two or more components that are selected automatically (without using label information) as control specific, case specific and not differentially expressed (neutral). The number of components is determined by cross-validation. Automatic assignment of features (m/z ratios or genes) to particular component is based on thresholds estimated from each sample directly. Due to the locality of decomposition, the strength of the expression of each feature across the samples can vary. Yet, they will still be allocated to the related disease and/or control specific component. Since label information is not used in the selection process, case and control specific components can be used for classification. That is not the case with standard factorization methods. Moreover, the component selected by proposed method as disease specific can be interpreted as a sub-mode and retained for further analysis to identify potential biomarkers. As opposed to standard matrix factorization methods this can be achieved on a sample (experiment)-by-sample basis. Postulating one or more components with indifferent features enables their removal from disease and control specific components on a sample-by-sample basis. This yields selected components with reduced complexity and generally, it increases prediction accuracy. PMID:22208882

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

PubMed

Park, Gi-Pyo

2014-08-01

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

A feasibility study on age-related factors of wrist pulse using principal component analysis.

PubMed

Jang-Han Bae; Young Ju Jeon; Sanghun Lee; Jaeuk U Kim

2016-08-01

Various analysis methods for examining wrist pulse characteristics are needed for accurate pulse diagnosis. In this feasibility study, principal component analysis (PCA) was performed to observe age-related factors of wrist pulse from various analysis parameters. Forty subjects in the age group of 20s and 40s were participated, and their wrist pulse signal and respiration signal were acquired with the pulse tonometric device. After pre-processing of the signals, twenty analysis parameters which have been regarded as values reflecting pulse characteristics were calculated and PCA was performed. As a results, we could reduce complex parameters to lower dimension and age-related factors of wrist pulse were observed by combining-new analysis parameter derived from PCA. These results demonstrate that PCA can be useful tool for analyzing wrist pulse signal.

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

ERIC Educational Resources Information Center

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

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

Accuracy of the Parallel Analysis Procedure with Polychoric Correlations

ERIC Educational Resources Information Center

Cho, Sun-Joo; Li, Feiming; Bandalos, Deborah

2009-01-01

The purpose of this study was to investigate the application of the parallel analysis (PA) method for choosing the number of factors in component analysis for situations in which data are dichotomous or ordinal. Although polychoric correlations are sometimes used as input for component analyses, the random data matrices generated for use in PA…

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

PubMed

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

1998-07-01

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

CLUSFAVOR 5.0: hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles

PubMed Central

Peterson, Leif E

2002-01-01

CLUSFAVOR (CLUSter and Factor Analysis with Varimax Orthogonal Rotation) 5.0 is a Windows-based computer program for hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles. CLUSFAVOR 5.0 standardizes input data; sorts data according to gene-specific coefficient of variation, standard deviation, average and total expression, and Shannon entropy; performs hierarchical cluster analysis using nearest-neighbor, unweighted pair-group method using arithmetic averages (UPGMA), or furthest-neighbor joining methods, and Euclidean, correlation, or jack-knife distances; and performs principal-component analysis. PMID:12184816

DREEM on: validation of the Dundee Ready Education Environment Measure in Pakistan.

PubMed

Khan, Junaid Sarfraz; Tabasum, Saima; Yousafzai, Usman Khalil; Fatima, Mehreen

2011-09-01

To validate DREEM in medical education environment of Punjab, Pakistan. The DREEM questionnaire was anonymously collected from Final year Baccalaureate of Medicine; Baccalaureate of Surgery students in the private and public medical colleges affiliated with the University of Health Sciences, Lahore. Data was analyzed using Principal Component Analysis with Varimax Rotation. The response rate was 84.14 %. The average DREEM score was 125. Confirmatory and Exploratory Factor Analysis was applied under the conditions of eigenvalues >1 and loadings > or = 0.3. In CONFIRMATORY FACTOR ANALYSIS, Five components were extracted accounting for 40.10% of variance and in EXPLORATORY FACTOR ANALYSIS, Ten components were extracted accounting for 52.33% of variance. Total 50 items had internal consistency reliability of 0.91 (Cronbach's Alpha). The value of Spearman-Brown was 0.868 showing the reliability of the analysis. In both analyses the subscales produced were sensible but the mismatch from the original was largely due to the English-Pakistan contextual and cultural differences. DREEM is a generic instrument that will do well with regional modifications to suit individual, contextual and cultural settings.

Function Invariant and Parameter Scale-Free Transformation Methods

ERIC Educational Resources Information Center

Bentler, P. M.; Wingard, Joseph A.

1977-01-01

A scale-invariant simple structure function of previously studied function components for principal component analysis and factor analysis is defined. First and second partial derivatives are obtained, and Newton-Raphson iterations are utilized. The resulting solutions are locally optimal and subjectively pleasing. (Author/JKS)

Psychometric analysis of the Brisbane Practice Environment Measure (B-PEM).

PubMed

Flint, Anndrea; Farrugia, Charles; Courtney, Mary; Webster, Joan

2010-03-01

To undertake rigorous psychometric testing of the newly developed contemporary work environment measure (the Brisbane Practice Environment Measure [B-PEM]) using exploratory factor analysis and confirmatory factor analysis. Content validity of the 33-item measure was established by a panel of experts. Initial testing involved 195 nursing staff using principal component factor analysis with varimax rotation (orthogonal) and Cronbach's alpha coefficients. Confirmatory factor analysis was conducted using data from a further 983 nursing staff. Principal component factor analysis yielded a four-factor solution with eigenvalues greater than 1 that explained 52.53% of the variance. These factors were then verified using confirmatory factor analysis. Goodness-of-fit indices showed an acceptable fit overall with the full model, explaining 21% to 73% of the variance. Deletion of items took place throughout the evolution of the instrument, resulting in a 26-item, four-factor measure called the Brisbane Practice Environment Measure-Tested. The B-PEM has undergone rigorous psychometric testing, providing evidence of internal consistency and goodness-of-fit indices within acceptable ranges. The measure can be utilised as a subscale or total score reflective of a contemporary nursing work environment. An up-to-date instrument to measure practice environment may be useful for nursing leaders to monitor the workplace and to assist in identifying areas for improvement, facilitating greater job satisfaction and retention.

Influential Observations in Principal Factor Analysis.

ERIC Educational Resources Information Center

Tanaka, Yutaka; Odaka, Yoshimasa

1989-01-01

A method is proposed for detecting influential observations in iterative principal factor analysis. Theoretical influence functions are derived for two components of the common variance decomposition. The major mathematical tool is the influence function derived by Tanaka (1988). (SLD)

The Mediating Effects of Generative Cognition on Imagination Stimulation

ERIC Educational Resources Information Center

Hsu, Yuling; Liang, Chaoyun; Chang, Chi-Cheng

2014-01-01

This study, based in Taiwan, aims to explore what psychological factors influence imagination stimulation of education major students, and what the relationship is between these factors and imagination. Both principal component analysis and confirmatory factor analysis were employed to determine the most appropriate structure of the developed…

Authoritarianism Revisited: Evidence for an Aggression Factor.

ERIC Educational Resources Information Center

Raden, David

1981-01-01

Performed a principal components factor analysis on scores of 245 undergraduates to a short version of the F Scale and measures of prejudice, attitude toward welfare, toleration of political deviance, punitiveness toward criminals, and support of the Vietnam War. Analysis produced two factors: authoritarian aggression and attitude toward welfare.…

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

PubMed

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

2010-08-06

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

On the Factor Structure of a Reading Comprehension Test

ERIC Educational Resources Information Center

Salehi, Mohammad

2011-01-01

To investigate the construct validly of a section of a high stakes test, an exploratory factor analysis using principal components analysis was employed. The rotation used was varimax with the suppression level of 0.30. Eleven factors were extracted out of 35 reading comprehension items. The fact that these factors emerged speak to the construct…

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

PubMed

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

2017-08-01

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

Comparison of three-dimensional fluorescence analysis methods for predicting formation of trihalomethanes and haloacetic acids.

PubMed

Peleato, Nicolás M; Andrews, Robert C

2015-01-01

This work investigated the application of several fluorescence excitation-emission matrix analysis methods as natural organic matter (NOM) indicators for use in predicting the formation of trihalomethanes (THMs) and haloacetic acids (HAAs). Waters from four different sources (two rivers and two lakes) were subjected to jar testing followed by 24hr disinfection by-product formation tests using chlorine. NOM was quantified using three common measures: dissolved organic carbon, ultraviolet absorbance at 254 nm, and specific ultraviolet absorbance as well as by principal component analysis, peak picking, and parallel factor analysis of fluorescence spectra. Based on multi-linear modeling of THMs and HAAs, principle component (PC) scores resulted in the lowest mean squared prediction error of cross-folded test sets (THMs: 43.7 (μg/L)(2), HAAs: 233.3 (μg/L)(2)). Inclusion of principle components representative of protein-like material significantly decreased prediction error for both THMs and HAAs. Parallel factor analysis did not identify a protein-like component and resulted in prediction errors similar to traditional NOM surrogates as well as fluorescence peak picking. These results support the value of fluorescence excitation-emission matrix-principal component analysis as a suitable NOM indicator in predicting the formation of THMs and HAAs for the water sources studied. Copyright © 2014. Published by Elsevier B.V.

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

NASA Astrophysics Data System (ADS)

Tsakiri, Katerina G.

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

Physics Metacognition Inventory Part Ii: Confirmatory Factor Analysis and Rasch Analysis

ERIC Educational Resources Information Center

Taasoobshirazi, Gita; Bailey, MarLynn; Farley, John

2015-01-01

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,…

Human factors analysis of workstation design: Earth Radiation Budget Satellite Mission Operations Room

NASA Technical Reports Server (NTRS)

Stewart, L. J.; Murphy, E. D.; Mitchell, C. M.

1982-01-01

A human factors analysis addressed three related yet distinct issues within the area of workstation design for the Earth Radiation Budget Satellite (ERBS) mission operation room (MOR). The first issue, physical layout of the MOR, received the most intensive effort. It involved the positioning of clusters of equipment within the physical dimensions of the ERBS MOR. The second issue for analysis was comprised of several environmental concerns, such as lighting, furniture, and heating and ventilation systems. The third issue was component arrangement, involving the physical arrangement of individual components within clusters of consoles, e.g., a communications panel.

A Component Analysis of Positive Behaviour Support Plans

ERIC Educational Resources Information Center

McClean, Brian; Grey, Ian

2012-01-01

Background: Positive behaviour support (PBS) emphasises multi-component interventions by natural intervention agents to help people overcome challenging behaviours. This paper investigates which components are most effective and which factors might mediate effectiveness. Method: Sixty-one staff working with individuals with intellectual disability…

Wavelet decomposition based principal component analysis for face recognition using MATLAB

NASA Astrophysics Data System (ADS)

Sharma, Mahesh Kumar; Sharma, Shashikant; Leeprechanon, Nopbhorn; Ranjan, Aashish

2016-03-01

For the realization of face recognition systems in the static as well as in the real time frame, algorithms such as principal component analysis, independent component analysis, linear discriminate analysis, neural networks and genetic algorithms are used for decades. This paper discusses an approach which is a wavelet decomposition based principal component analysis for face recognition. Principal component analysis is chosen over other algorithms due to its relative simplicity, efficiency, and robustness features. The term face recognition stands for identifying a person from his facial gestures and having resemblance with factor analysis in some sense, i.e. extraction of the principal component of an image. Principal component analysis is subjected to some drawbacks, mainly the poor discriminatory power and the large computational load in finding eigenvectors, in particular. These drawbacks can be greatly reduced by combining both wavelet transform decomposition for feature extraction and principal component analysis for pattern representation and classification together, by analyzing the facial gestures into space and time domain, where, frequency and time are used interchangeably. From the experimental results, it is envisaged that this face recognition method has made a significant percentage improvement in recognition rate as well as having a better computational efficiency.

Semantic evaluations of noise with tonal components in Japan, France, and Germany: a cross-cultural comparison.

PubMed

Hansen, Hans; Weber, Reinhard

2009-02-01

An evaluation of tonal components in noise using a semantic differential approach yields several perceptual and connotative factors. This study investigates the effect of culture on these factors with the aid of equivalent listening tests carried out in Japan (n=20), France (n=23), and Germany (n=20). The data's equivalence level is determined by a bias analysis. This analysis gives insight in the cross-cultural validity of the scales used for sound character determination. Three factors were extracted by factor analysis in all cultural subsamples: pleasant, metallic, and power. By employing appropriate target rotations of the factor spaces, the rotated factors were compared and they yield high similarities between the different cultural subsamples. To check cross-cultural differences in means, an item bias analysis was conducted. The a priori assumption of unbiased scales is rejected; the differences obtained are partially linked to bias effects. Acoustical sound descriptors were additionally tested for the semantic dimensions. The high agreement in judgments between the different cultural subsamples contrast the moderate success of the signal parameters to describe the dimensions.

Patterns in longitudinal growth of refraction in Southern Chinese children: cluster and principal component analysis.

PubMed

Chen, Yanxian; Chang, Billy Heung Wing; Ding, Xiaohu; He, Mingguang

2016-11-22

In the present study we attempt to use hypothesis-independent analysis in investigating the patterns in refraction growth in Chinese children, and to explore the possible risk factors affecting the different components of progression, as defined by Principal Component Analysis (PCA). A total of 637 first-born twins in Guangzhou Twin Eye Study with 6-year annual visits (baseline age 7-15 years) were available in the analysis. Cluster 1 to 3 were classified after a partitioning clustering, representing stable, slow and fast progressing groups of refraction respectively. Baseline age and refraction, paternal refraction, maternal refraction and proportion of two myopic parents showed significant differences across the three groups. Three major components of progression were extracted using PCA: "Average refraction", "Acceleration" and the combination of "Myopia stabilization" and "Late onset of refraction progress". In regression models, younger children with more severe myopia were associated with larger "Acceleration". The risk factors of "Acceleration" included change of height and weight, near work, and parental myopia, while female gender, change of height and weight were associated with "Stabilization", and increased outdoor time was related to "Late onset of refraction progress". We therefore concluded that genetic and environmental risk factors have different impacts on patterns of refraction progression.

Patterns in longitudinal growth of refraction in Southern Chinese children: cluster and principal component analysis

PubMed Central

Chen, Yanxian; Chang, Billy Heung Wing; Ding, Xiaohu; He, Mingguang

2016-01-01

In the present study we attempt to use hypothesis-independent analysis in investigating the patterns in refraction growth in Chinese children, and to explore the possible risk factors affecting the different components of progression, as defined by Principal Component Analysis (PCA). A total of 637 first-born twins in Guangzhou Twin Eye Study with 6-year annual visits (baseline age 7–15 years) were available in the analysis. Cluster 1 to 3 were classified after a partitioning clustering, representing stable, slow and fast progressing groups of refraction respectively. Baseline age and refraction, paternal refraction, maternal refraction and proportion of two myopic parents showed significant differences across the three groups. Three major components of progression were extracted using PCA: “Average refraction”, “Acceleration” and the combination of “Myopia stabilization” and “Late onset of refraction progress”. In regression models, younger children with more severe myopia were associated with larger “Acceleration”. The risk factors of “Acceleration” included change of height and weight, near work, and parental myopia, while female gender, change of height and weight were associated with “Stabilization”, and increased outdoor time was related to “Late onset of refraction progress”. We therefore concluded that genetic and environmental risk factors have different impacts on patterns of refraction progression. PMID:27874105

Characterization of extracellular polymeric substances in biofilms under long-term exposure to ciprofloxacin antibiotic using fluorescence excitation-emission matrix and parallel factor analysis.

PubMed

Gu, Chaochao; Gao, Pin; Yang, Fan; An, Dongxuan; Munir, Mariya; Jia, Hanzhong; Xue, Gang; Ma, Chunyan

2017-05-01

The presence of antibiotic residues in the environment has been regarded as an emerging concern due to their potential adverse environmental consequences such as antibiotic resistance. However, the interaction between antibiotics and extracellular polymeric substances (EPSs) of biofilms in wastewater treatment systems is not entirely clear. In this study, the effect of ciprofloxacin (CIP) antibiotic on biofilm EPS matrix was investigated and characterized using fluorescence excitation-emission matrix (EEM) and parallel factor (PARAFAC) analysis. Physicochemical analysis showed that the proteins were the major EPS fraction, and their contents increased gradually with an increase in CIP concentration (0-300 μg/L). Based on the characterization of biofilm tightly bound EPS (TB-EPS) by EEM, three fluorescent components were identified by PARAFAC analysis. Component C1 was associated with protein-like substances, and components C2 and C3 belonged to humic-like substances. Component C1 exhibited an increasing trend as the CIP addition increased. Pearson's correlation results showed that CIP correlated significantly with the protein contents and component C1, while strong correlations were also found among UV 254 , dissolved organic carbon, humic acids, and component C3. A combined use of EEM-PARAFAC analysis and chemical measurements was demonstrated as a favorable approach for the characterization of variations in biofilm EPS in the presence of CIP antibiotic.

Multiple Component Event-Related Potential (mcERP) Estimation

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

In Spite of Indeterminacy Many Common Factor Score Estimates Yield an Identical Reproduced Covariance Matrix

ERIC Educational Resources Information Center

Beauducel, Andre

2007-01-01

It was investigated whether commonly used factor score estimates lead to the same reproduced covariance matrix of observed variables. This was achieved by means of Schonemann and Steiger's (1976) regression component analysis, since it is possible to compute the reproduced covariance matrices of the regression components corresponding to different…

Does the Assessment of Recovery Capital scale reflect a single or multiple domains?

PubMed

Arndt, Stephan; Sahker, Ethan; Hedden, Suzy

2017-01-01

The goal of this study was to determine whether the 50-item Assessment of Recovery Capital scale represents a single general measure or whether multiple domains might be psychometrically useful for research or clinical applications. Data are from a cross-sectional de-identified existing program evaluation information data set with 1,138 clients entering substance use disorder treatment. Principal components and iterated factor analysis were used on the domain scores. Multiple group factor analysis provided a quasi-confirmatory factor analysis. The solution accounted for 75.24% of the total variance, suggesting that 10 factors provide a reasonably good fit. However, Tucker's congruence coefficients between the factor structure and defining weights (0.41-0.52) suggested a poor fit to the hypothesized 10-domain structure. Principal components of the 10-domain scores yielded one factor whose eigenvalue was greater than one (5.93), accounting for 75.8% of the common variance. A few domains had perceptible but small unique variance components suggesting that a few of the domains may warrant enrichment. Our findings suggest that there is one general factor, with a caveat. Using the 10 measures inflates the chance for Type I errors. Using one general measure avoids this issue, is simple to interpret, and could reduce the number of items. However, those seeking to maximally predict later recovery success may need to use the full instrument and all 10 domains.

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

PubMed

Baka, Łukasz; Basińska, Beata A

2016-01-01

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

Harmonic analysis of the precipitation in Greece

NASA Astrophysics Data System (ADS)

Nastos, P. T.; Zerefos, C. S.

2009-04-01

Greece is a country with a big variety of climates due to its geographical position, to the many mountain ranges and also to the multifarious and long coastline. The mountainous volumes are of such orientation that influences the distribution of the precipitation, having as a result, Western Greece to present great differentiations from Central and Eastern Greece. The application of harmonic analysis to the annual variability of precipitation is the goal of this study, so that the components, which compose the annual variability, be elicited. For this purpose, the mean monthly precipitation data from 30 meteorological stations of National Meteorological Service were used for the time period 1950-2000. The initial target is to reduce the number of variables and to detect structure in the relationships between variables. The most commonly used technique for this purpose is the application of Factor Analysis to a table having as columns the meteorological stations-variables and rows the monthly mean precipitation, so that 2 main factors were calculated, which explain the 98% of total variability of precipitation in Greece. Factor 1, representing the so-called uniform field and interpreting the most of the total variance, refers in fact to the Mediterranean depressions, affecting mainly the West of Greece and also the East Aegean and the Asia Minor coasts. In the process, the Fourier Analysis was applied to the factor scores extracted from the Factor Analysis, so that 2 harmonic components are resulted, which explain above the 98% of the total variability of each main factor, and are due to different synoptic and thermodynamic processes associated with Greece's precipitation construction. Finally, the calculation of the time of occurrence of the maximum precipitation, for each harmonic component of each one of the two main factors, gives the spatial distribution of appearance of the maximum precipitation in the Hellenic region.

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

PubMed

Batchelder, Laurie; Brosnan, Mark; Ashwin, Chris

2017-01-01

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

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

PubMed Central

Batchelder, Laurie; Brosnan, Mark; Ashwin, Chris

2017-01-01

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

Chemical information obtained from Auger depth profiles by means of advanced factor analysis (MLCFA)

NASA Astrophysics Data System (ADS)

De Volder, P.; Hoogewijs, R.; De Gryse, R.; Fiermans, L.; Vennik, J.

1993-01-01

The advanced multivariate statistical technique "maximum likelihood common factor analysis (MLCFA)" is shown to be superior to "principal component analysis (PCA)" for decomposing overlapping peaks into their individual component spectra of which neither the number of components nor the peak shape of the component spectra is known. An examination of the maximum resolving power of both techniques, MLCFA and PCA, by means of artificially created series of multicomponent spectra confirms this finding unambiguously. Substantial progress in the use of AES as a chemical-analysis technique is accomplished through the implementation of MLCFA. Chemical information from Auger depth profiles is extracted by investigating the variation of the line shape of the Auger signal as a function of the changing chemical state of the element. In particular, MLCFA combined with Auger depth profiling has been applied to problems related to steelcord-rubber tyre adhesion. MLCFA allows one to elucidate the precise nature of the interfacial layer of reaction products between natural rubber vulcanized on a thin brass layer. This study reveals many interesting chemical aspects of the oxi-sulfidation of brass undetectable with classical AES.

Spectral compression algorithms for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R.

2007-10-16

A method for spectrally compressing data sets enables the efficient analysis of very large multivariate images. The spectral compression algorithm uses a factored representation of the data that can be obtained from Principal Components Analysis or other factorization technique. Furthermore, a block algorithm can be used for performing common operations more efficiently. An image analysis can be performed on the factored representation of the data, using only the most significant factors. The spectral compression algorithm can be combined with a spatial compression algorithm to provide further computational efficiencies.

[Methods of a posteriori identification of food patterns in Brazilian children: a systematic review].

PubMed

Carvalho, Carolina Abreu de; Fonsêca, Poliana Cristina de Almeida; Nobre, Luciana Neri; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2016-01-01

The objective of this study is to provide guidance for identifying dietary patterns using the a posteriori approach, and analyze the methodological aspects of the studies conducted in Brazil that identified the dietary patterns of children. Articles were selected from the Latin American and Caribbean Literature on Health Sciences, Scientific Electronic Library Online and Pubmed databases. The key words were: Dietary pattern; Food pattern; Principal Components Analysis; Factor analysis; Cluster analysis; Reduced rank regression. We included studies that identified dietary patterns of children using the a posteriori approach. Seven studies published between 2007 and 2014 were selected, six of which were cross-sectional and one cohort, Five studies used the food frequency questionnaire for dietary assessment; one used a 24-hour dietary recall and the other a food list. The method of exploratory approach used in most publications was principal components factor analysis, followed by cluster analysis. The sample size of the studies ranged from 232 to 4231, the values of the Kaiser-Meyer-Olkin test from 0.524 to 0.873, and Cronbach's alpha from 0.51 to 0.69. Few Brazilian studies identified dietary patterns of children using the a posteriori approach and principal components factor analysis was the technique most used.

Multidimensional change in psychotherapy.

PubMed

Jones, E E

1980-04-01

Assessed psychotherapy outcome for 177 patients who were seen for an average of 31 therapy hours with the Rating Scales for Outcome of Therapy and a Therapist Questionnaire. Results of a components analysis did not support Storrow's rational groupings of the Rating Scales into five dimensions and suggested that two general areas of psychological adjustment underlie the 11 scales. A second components analysis that included both outcome measures supports only in part the contention that when results from diverse outcome measures are factor analyzed, the factors necessarily are associated with method of measurement rather than substantive dimensions of change.

Treatment Components and Their Relationships with Drug and Alcohol Abstinence.

ERIC Educational Resources Information Center

Orwin, Rob; Ellis, Bruce

This study evaluates the effect of treatment components through a secondary analysis of data from the National Treatment Improvement Evaluation Study (NTIES). The study examines the relationship between treatment components, client-level factors, and treatment outcomes, and how these relationships vary by treatment modality. It seeks to understand…

Impacts of a flash flood on drinking water quality: case study of areas most affected by the 2012 Beijing flood.

PubMed

Sun, Rubao; An, Daizhi; Lu, Wei; Shi, Yun; Wang, Lili; Zhang, Can; Zhang, Ping; Qi, Hongjuan; Wang, Qiang

2016-02-01

In this study, we present a method for identifying sources of water pollution and their relative contributions in pollution disasters. The method uses a combination of principal component analysis and factor analysis. We carried out a case study in three rural villages close to Beijing after torrential rain on July 21, 2012. Nine water samples were analyzed for eight parameters, namely turbidity, total hardness, total dissolved solids, sulfates, chlorides, nitrates, total bacterial count, and total coliform groups. All of the samples showed different degrees of pollution, and most were unsuitable for drinking water as concentrations of various parameters exceeded recommended thresholds. Principal component analysis and factor analysis showed that two factors, the degree of mineralization and agricultural runoff, and flood entrainment, explained 82.50% of the total variance. The case study demonstrates that this method is useful for evaluating and interpreting large, complex water-quality data sets.

Psychometric evaluation of the Persian version of the Templer's Death Anxiety Scale in cancer patients.

PubMed

Soleimani, Mohammad Ali; Yaghoobzadeh, Ameneh; Bahrami, Nasim; Sharif, Saeed Pahlevan; Sharif Nia, Hamid

2016-10-01

In this study, 398 Iranian cancer patients completed the 15-item Templer's Death Anxiety Scale (TDAS). Tests of internal consistency, principal components analysis, and confirmatory factor analysis were conducted to assess the internal consistency and factorial validity of the Persian TDAS. The construct reliability statistic and average variance extracted were also calculated to measure construct reliability, convergent validity, and discriminant validity. Principal components analysis indicated a 3-component solution, which was generally supported in the confirmatory analysis. However, acceptable cutoffs for construct reliability, convergent validity, and discriminant validity were not fulfilled for the three subscales that were derived from the principal component analysis. This study demonstrated both the advantages and potential limitations of using the TDAS with Persian-speaking cancer patients.

A New Approach for Quantitative Evaluation of Ultrasonic Wave Attenuation in Composites

NASA Astrophysics Data System (ADS)

Ni, Qing-Qing; Li, Ran; Xia, Hong

2017-02-01

When ultrasonic waves propagate in composite materials, the propagation behaviors result from the combination effects of various factors, such as material anisotropy and viscoelastic property, internal microstructure and defects, incident wave characteristics and interface condition between composite components. It is essential to make it clear how these factors affect the ultrasonic wave propagation and attenuation characteristics, and how they mutually interact on each other. In the present paper, based on a newly developed time-domain finite element analysis code, PZflex, a unique approach for clarifying the detailed influence mechanism of aforementioned factors is proposed, in which each attenuation component can be extracted from the overall attenuation and analyzed respectively. By taking into consideration the interrelation between each individual attenuation component, the variation behaviors of each component and internal dynamic stress distribution against material anisotropy and matrix viscosity are separately and quantitatively evaluated. From the detailed analysis results of each attenuation component, the energy dissipation at interface is a major component in ultrasonic wave attenuation characteristics, which can provide a maximum contribution rate of 68.2 % to the overall attenuation, and each attenuation component is closely related to the material anisotropy and viscoelasticity. The results clarify the correlation between ultrasonic wave propagation characteristics and material viscoelastic properties, which will be useful in the further development of ultrasonic technology in defect detection.

Factor analysis of an instrument to measure the impact of disease on daily life.

PubMed

Pedrosa, Rafaela Batista Dos Santos; Rodrigues, Roberta Cunha Matheus; Padilha, Kátia Melissa; Gallani, Maria Cecília Bueno Jayme; Alexandre, Neusa Maria Costa

2016-01-01

to verify the structure of factors of an instrument to measure the Heart Valve Disease Impact on Daily Life (IDCV) when applied to coronary artery disease patients. the study included 153 coronary artery disease patients undergoing outpatient follow-up care. The IDCV structure of factors was initially assessed by means of confirmatory factor analysis and, subsequently, by exploratory factor analysis. The Varimax rotation method was used to estimate the main components of analysis, eigenvalues greater than one for extraction of factors, and factor loading greater than 0.40 for selection of items. Internal consistency was estimated using Cronbach's alpha coefficient. confirmatory factor analysis did not confirm the original structure of factors of the IDCV. Exploratory factor analysis showed three dimensions, which together explained 78% of the measurement variance. future studies with expansion of case selection are necessary to confirm the IDCV new structure of factors.

Psychometric Evaluation of a Triage Decision Making Inventory

DTIC Science & Technology

2011-06-27

the correlation matrix and inter-item correlations were reviewed. The Bartlett’s test of sphericity and the Kaiser - Meyer Olkin (KMO) were examined to...nursing experience. Principal component factor analysis with Varimax rotation was conducted using SPSS version 16. The Kaiser - Meyer - Olkin Measure of...Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 7 iterations

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

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

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

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

Meta-analysis of the Brief Psychiatric Rating Scale Factor Structure

ERIC Educational Resources Information Center

Shafer, Alan

2005-01-01

A meta-analysis (N=17,620; k=26) of factor analyses of the Brief Psychiatric Rating Scale (BPRS) was conducted. Analysis of the 12 items from Overall et al.'s (J. E. Overall, L. E. Hollister, & P. Pichot, 1974) 4 subscales found support for his 4 subscales. Analysis of all 18 BPRS items found 4 components similar to those of Overall et al. In a…

Enhanced Component Performance Study. Emergency Diesel Generators 1998–2013

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

Schroeder, John Alton

2014-11-01

This report presents an enhanced performance evaluation of emergency diesel generators (EDGs) at U.S. commercial nuclear power plants. This report evaluates component performance over time using Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES) data from 1998 through 2013 and maintenance unavailability (UA) performance data using Mitigating Systems Performance Index (MSPI) Basis Document data from 2002 through 2013. The objective is to present an analysis of factors that could influence the system and component trends in addition to annual performance trends of failure rates and probabilities. The factors analyzed for the EDG component are the differences in failuresmore » between all demands and actual unplanned engineered safety feature (ESF) demands, differences among manufacturers, and differences among EDG ratings. Statistical analyses of these differences are performed and results showing whether pooling is acceptable across these factors. In addition, engineering analyses were performed with respect to time period and failure mode. The factors analyzed are: sub-component, failure cause, detection method, recovery, manufacturer, and EDG rating.« less

[Study on ecological suitability regionalization of Eucommia ulmoides in Guizhou].

PubMed

Kang, Chuan-Zhi; Wang, Qing-Qing; Zhou, Tao; Jiang, Wei-Ke; Xiao, Cheng-Hong; Xie, Yu

2014-05-01

To study the ecological suitability regionalization of Eucommia ulmoides, for selecting artificial planting base and high-quality industrial raw material purchase area of the herb in Guizhou. Based on the investigation of 14 Eucommia ulmoides producing areas, pinoresinol diglucoside content and ecological factors were obtained. Using spatial analysis method to carry on ecological suitability regionalization. Meanwhile, combining pinoresinol diglucoside content, the correlation of major active components and environmental factors were analyzed by statistical analysis. The most suitability planting area of Eucommia ulmoides was the northwest of Guizhou. The distribution of Eucommia ulmoides was mainly affected by the type and pH value of soil, and monthly precipitation. The spatial structure of major active components in Eucommia ulmoides were randomly distributed in global space, but had only one aggregation point which had a high positive correlation in local space. The major active components of Eucommia ulmoides had no correlation with altitude, longitude or latitude. Using the spatial analysis method and statistical analysis method, based on environmental factor and pinoresinol diglucoside content, the ecological suitability regionalization of Eucommia ulmoides can provide reference for the selection of suitable planting area, artificial planting base and directing production layout.

Principal Component and Linkage Analysis of Cardiovascular Risk Traits in the Norfolk Isolate

PubMed Central

Cox, Hannah C.; Bellis, Claire; Lea, Rod A.; Quinlan, Sharon; Hughes, Roger; Dyer, Thomas; Charlesworth, Jac; Blangero, John; Griffiths, Lyn R.

2009-01-01

Objective(s) An individual's risk of developing cardiovascular disease (CVD) is influenced by genetic factors. This study focussed on mapping genetic loci for CVD-risk traits in a unique population isolate derived from Norfolk Island. Methods This investigation focussed on 377 individuals descended from the population founders. Principal component analysis was used to extract orthogonal components from 11 cardiovascular risk traits. Multipoint variance component methods were used to assess genome-wide linkage using SOLAR to the derived factors. A total of 285 of the 377 related individuals were informative for linkage analysis. Results A total of 4 principal components accounting for 83% of the total variance were derived. Principal component 1 was loaded with body size indicators; principal component 2 with body size, cholesterol and triglyceride levels; principal component 3 with the blood pressures; and principal component 4 with LDL-cholesterol and total cholesterol levels. Suggestive evidence of linkage for principal component 2 (h2 = 0.35) was observed on chromosome 5q35 (LOD = 1.85; p = 0.0008). While peak regions on chromosome 10p11.2 (LOD = 1.27; p = 0.005) and 12q13 (LOD = 1.63; p = 0.003) were observed to segregate with principal components 1 (h2 = 0.33) and 4 (h2 = 0.42), respectively. Conclusion(s): This study investigated a number of CVD risk traits in a unique isolated population. Findings support the clustering of CVD risk traits and provide interesting evidence of a region on chromosome 5q35 segregating with weight, waist circumference, HDL-c and total triglyceride levels. PMID:19339786

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

PubMed

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

2002-12-30

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

Analysis of exergy efficiency of a super-critical compressed carbon dioxide energy-storage system based on the orthogonal method.

PubMed

He, Qing; Hao, Yinping; Liu, Hui; Liu, Wenyi

2018-01-01

Super-critical carbon dioxide energy-storage (SC-CCES) technology is a new type of gas energy-storage technology. This paper used orthogonal method and variance analysis to make significant analysis on the factors which would affect the thermodynamics characteristics of the SC-CCES system and obtained the significant factors and interactions in the energy-storage process, the energy-release process and the whole energy-storage system. Results have shown that the interactions in the components have little influence on the energy-storage process, the energy-release process and the whole energy-storage process of the SC-CCES system, the significant factors are mainly on the characteristics of the system component itself, which will provide reference for the optimization of the thermal properties of the energy-storage system.

Analysis of exergy efficiency of a super-critical compressed carbon dioxide energy-storage system based on the orthogonal method

PubMed Central

He, Qing; Liu, Hui; Liu, Wenyi

2018-01-01

Super-critical carbon dioxide energy-storage (SC-CCES) technology is a new type of gas energy-storage technology. This paper used orthogonal method and variance analysis to make significant analysis on the factors which would affect the thermodynamics characteristics of the SC-CCES system and obtained the significant factors and interactions in the energy-storage process, the energy-release process and the whole energy-storage system. Results have shown that the interactions in the components have little influence on the energy-storage process, the energy-release process and the whole energy-storage process of the SC-CCES system, the significant factors are mainly on the characteristics of the system component itself, which will provide reference for the optimization of the thermal properties of the energy-storage system. PMID:29634742

Psychometric evaluation of the canine brief pain inventory in a Swedish sample of dogs with pain related to osteoarthritis.

PubMed

Essner, Ann; Zetterberg, Lena; Hellström, Karin; Gustås, Pia; Högberg, Hans; Sjöström, Rita

2017-07-01

To evaluate intervention, implement evidence-based practice and enhance the welfare of dogs with naturally occurring osteoarthritis (OA), access to valid, reliable and clinically relevant outcome measures is crucial for researchers, veterinarians and rehabilitation practitioners. The objectives of the present study were to translate and evaluate psychometric properties, in terms of internal consistency and construct validity, of the owner-reported measure canine brief pain inventory (CBPI) in a Swedish sample of dogs with pain related to OA. Twenty-one owners of clinically sound dogs and 58 owners of dogs with pain related to OA were included in this observational and cross-sectional study. After being translated according to the guidelines for patient-reported outcome measures, the CBPI was completed by the canine owners. Construct validity was assessed by confirmatory factor analysis, by repeating the principal component analysis and by assessing for differences between clinically sound dogs and dogs with pain related to OA. Internal consistency was estimated by Cronbach's α. Confirmatory factor analysis was not able to confirm the factor-structure models tested in our sample. Principal component analysis showed a two-component structure, pain severity and pain interference of function. Two components accounted for 76.8% of the total variance, suggesting an acceptable fit of a two-component structure. The ratings from the clinically sound dogs differed from OA dogs and showed significantly lower CBPI total sum. Cronbach's α was 0.94 for the total CBPI, 0.91 for the pain severity and 0.91 for the pain interference of function. The results indicate that the translated version of the CBPI is valid for use in the Swedish language. The findings suggest satisfying psychometric properties in terms of high internal consistencies and ability to discriminate clinically sound dogs from OA dogs. However, based on the confirmatory factor analysis, the original factor structure in the CBPI is not ideally suited to measure pain related to OA in our sample and the hypothesis of the presented two-factor structure was rejected. Further research needs to be conducted to determine whether the original psychometric results from CBPI can be replicated across different target groups and particularly with larger sample size.

A Profile-Based Framework for Factorial Similarity and the Congruence Coefficient.

PubMed

Hartley, Anselma G; Furr, R Michael

2017-01-01

We present a novel profile-based framework for understanding factorial similarity in the context of exploratory factor analysis in general, and for understanding the congruence coefficient (a commonly used index of factor similarity) specifically. First, we introduce the profile-based framework articulating factorial similarity in terms of 3 intuitive components: general saturation similarity, differential saturation similarity, and configural similarity. We then articulate the congruence coefficient in terms of these components, along with 2 additional profile-based components, and we explain how these components resolve ambiguities that can be-and are-found when using the congruence coefficient. Finally, we present secondary analyses revealing that profile-based components of factorial are indeed linked to experts' actual evaluations of factorial similarity. Overall, the profile-based approach we present offers new insights into the ways in which researchers can examine factor similarity and holds the potential to enhance researchers' ability to understand the congruence coefficient.

The eudaimonic component of satisfaction with life and psychological well-being in Spanish cultures.

PubMed

Díaz, Darío; Stavraki, María; Blanco, Amalio; Gandarillas, Beatriz

2015-01-01

In the study of well-being there are two partially overlapping traditions that have been developed in parallel. Subjective well-being (SWB) has been associated with the hedonistic approach of well-being, and psychological well-being (PWB) with the eudaimonistic one. However, satisfaction with life, the most common SWB indicator, is not strictly a hedonic concept and contains many eudaimonic components. The objective of this research is to examine whether a Eudaimonic Well-being G-Factor of Satisfaction with Life (SWLS) and Psychological Well-being Scales (PWBS) emerges. 400 people from the general population of Colombia (Study 1) and 401 from Spain (Study 2), recruited via advertisement, voluntarily participated and filled in a booklet containing, in order of appearance, the PWBS and the SWLS. According to our hypothesis, parallel analysis, eigenvalues, scree plot graphs and exploratory factor analysis (Study 1) suggested the existence of a one-factor structure. Confirmatory factor analysis (Study 2) indicated that this one-factor model provided excellent data fit. Results of a multi-group confirmatory factor analysis confirmed cross-cultural factor invariance. These results question the view that the satisfaction with life indicator is uniquely hedonic and point to the need for a greater integration between hedonic and eudaimonic traditions.

Common factor analysis versus principal component analysis: choice for symptom cluster research.

PubMed

Kim, Hee-Ju

2008-03-01

The purpose of this paper is to examine differences between two factor analytical methods and their relevance for symptom cluster research: common factor analysis (CFA) versus principal component analysis (PCA). Literature was critically reviewed to elucidate the differences between CFA and PCA. A secondary analysis (N = 84) was utilized to show the actual result differences from the two methods. CFA analyzes only the reliable common variance of data, while PCA analyzes all the variance of data. An underlying hypothetical process or construct is involved in CFA but not in PCA. PCA tends to increase factor loadings especially in a study with a small number of variables and/or low estimated communality. Thus, PCA is not appropriate for examining the structure of data. 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.

Principal component analysis to assess the efficiency and mechanism for enhanced coagulation of natural algae-laden water using a novel dual coagulant system.

PubMed

Ou, Hua-Se; Wei, Chao-Hai; Deng, Yang; Gao, Nai-Yun; Ren, Yuan; Hu, Yun

2014-02-01

A novel dual coagulant system of polyaluminum chloride sulfate (PACS) and polydiallyldimethylammonium chloride (PDADMAC) was used to treat natural algae-laden water from Meiliang Gulf, Lake Taihu. PACS (Aln(OH)mCl3n-m-2k(SO4)k) has a mass ratio of 10 %, a SO4 (2-)/Al3 (+) mole ratio of 0.0664, and an OH/Al mole ratio of 2. The PDADMAC ([C8H16NCl]m) has a MW which ranges from 5 × 10(5) to 20 × 10(5) Da. The variations of contaminants in water samples during treatments were estimated in the form of principal component analysis (PCA) factor scores and conventional variables (turbidity, DOC, etc.). Parallel factor analysis determined four chromophoric dissolved organic matters (CDOM) components, and PCA identified four integrated principle factors. PCA factor 1 had significant correlations with chlorophyll-a (r=0.718), protein-like CDOM C1 (0.689), and C2 (0.756). Factor 2 correlated with UV254 (0.672), humic-like CDOM component C3 (0.716), and C4 (0.758). Factors 3 and 4 had correlations with NH3-N (0.748) and T-P (0.769), respectively. The variations of PCA factors scores revealed that PACS contributed less aluminum dissolution than PAC to obtain equivalent removal efficiency of contaminants. This might be due to the high cationic charge and pre-hydrolyzation of PACS. Compared with PACS coagulation (20 mg L(-1)), the removal of PCA factors 1, 2, and 4 increased 45, 33, and 12 %, respectively, in combined PACS-PDADMAC treatment (0.8 mg L(-1) +20 mg L(-1)). Since PAC contained more Al (0.053 g/1 g) than PACS (0.028 g/1 g), the results indicated that PACS contributed less Al dissolution into the water to obtain equivalent removal efficiency.

The Baptist Health Nurse Retention Questionnaire: A Methodological Study, Part 1.

PubMed

Lengerich, Alexander; Bugajski, Andrew; Marchese, Matthew; Hall, Brittany; Yackzan, Susan; Davies, Claire; Brockopp, Dorothy

2017-05-01

The purposes of this study were to develop and test the Baptist Health Nurse Retention Questionnaire (BHNRQ) and examine the importance of nurse retention factors. Multiple factors, including increasing patient acuity levels, have led to concerns regarding nurse retention. An understanding of current factors related to retention is limited. To establish the psychometric properties of the BHNRQ, data were collected from 279 bedside nurses at a 391-bed, Magnet® redesignated community hospital. A principal component analysis was conducted to determine the subscale structure of the BHNRQ. Additional analyses were conducted related to content validity and test-retest reliability. The results of the principal components analysis revealed 3 subscales: nursing practice, management, and staffing. Analyses demonstrate that the BHNRQ is a reliable and valid instrument for measuring nurse retention factors. The BHNRQ was found to be a clinically useful instrument for measuring important factors related to nurse retention.

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

PubMed

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

2016-09-01

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

Determining the optimal number of independent components for reproducible transcriptomic data analysis.

PubMed

Kairov, Ulykbek; Cantini, Laura; Greco, Alessandro; Molkenov, Askhat; Czerwinska, Urszula; Barillot, Emmanuel; Zinovyev, Andrei

2017-09-11

Independent Component Analysis (ICA) is a method that models gene expression data as an action of a set of statistically independent hidden factors. The output of ICA depends on a fundamental parameter: the number of components (factors) to compute. The optimal choice of this parameter, related to determining the effective data dimension, remains an open question in the application of blind source separation techniques to transcriptomic data. Here we address the question of optimizing the number of statistically independent components in the analysis of transcriptomic data for reproducibility of the components in multiple runs of ICA (within the same or within varying effective dimensions) and in multiple independent datasets. To this end, we introduce ranking of independent components based on their stability in multiple ICA computation runs and define a distinguished number of components (Most Stable Transcriptome Dimension, MSTD) corresponding to the point of the qualitative change of the stability profile. Based on a large body of data, we demonstrate that a sufficient number of dimensions is required for biological interpretability of the ICA decomposition and that the most stable components with ranks below MSTD have more chances to be reproduced in independent studies compared to the less stable ones. At the same time, we show that a transcriptomics dataset can be reduced to a relatively high number of dimensions without losing the interpretability of ICA, even though higher dimensions give rise to components driven by small gene sets. We suggest a protocol of ICA application to transcriptomics data with a possibility of prioritizing components with respect to their reproducibility that strengthens the biological interpretation. Computing too few components (much less than MSTD) is not optimal for interpretability of the results. The components ranked within MSTD range have more chances to be reproduced in independent studies.

Chemometric expertise of the quality of groundwater sources for domestic use.

PubMed

Spanos, Thomas; Ene, Antoaneta; Simeonova, Pavlina

2015-01-01

In the present study 49 representative sites have been selected for the collection of water samples from central water supplies with different geographical locations in the region of Kavala, Northern Greece. Ten physicochemical parameters (pH, electric conductivity, nitrate, chloride, sodium, potassium, total alkalinity, total hardness, bicarbonate and calcium) were analyzed monthly, in the period from January 2010 to December 2010. Chemometric methods were used for monitoring data mining and interpretation (cluster analysis, principal components analysis and source apportioning by principal components regression). The clustering of the chemical indicators delivers two major clusters related to the water hardness and the mineral components (impacted by sea, bedrock and acidity factors). The sampling locations are separated into three major clusters corresponding to the spatial distribution of the sites - coastal, lowland and semi-mountainous. The principal components analysis reveals two latent factors responsible for the data structures, which are also an indication for the sources determining the groundwater quality of the region (conditionally named "mineral" factor and "water hardness" factor). By the apportionment approach it is shown what the contribution is of each of the identified sources to the formation of the total concentration of each one of the chemical parameters. The mean values of the studied physicochemical parameters were found to be within the limits given in the 98/83/EC Directive. The water samples are appropriate for human consumption. The results of this study provide an overview of the hydrogeological profile of water supply system for the studied area.

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

EPA Science Inventory

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

Analysis and improvement measures of flight delay in China

NASA Astrophysics Data System (ADS)

Zang, Yuhang

2017-03-01

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

The rate of change in declining steroid hormones: a new parameter of healthy aging in men?

PubMed

Walther, Andreas; Philipp, Michel; Lozza, Niclà; Ehlert, Ulrike

2016-09-20

Research on healthy aging in men has increasingly focused on age-related hormonal changes. Testosterone (T) decline is primarily investigated, while age-related changes in other sex steroids (dehydroepiandrosterone [DHEA], estradiol [E2], progesterone [P]) are mostly neglected. An integrated hormone parameter reflecting aging processes in men has yet to be identified. 271 self-reporting healthy men between 40 and 75 provided both psychometric data and saliva samples for hormone analysis. Correlation analysis between age and sex steroids revealed negative associations for the four sex steroids (T, DHEA, E2, and P). Principal component analysis including ten salivary analytes identified a principal component mainly unifying the variance of the four sex steroid hormones. Subsequent principal component analysis including the four sex steroids extracted the principal component of declining steroid hormones (DSH). Moderation analysis of the association between age and DSH revealed significant moderation effects for psychosocial factors such as depression, chronic stress and perceived general health. In conclusion, these results provide further evidence that sex steroids decline in aging men and that the integrated hormone parameter DSH and its rate of change can be used as biomarkers for healthy aging in men. Furthermore, the negative association of age and DSH is moderated by psychosocial factors.

The rate of change in declining steroid hormones: a new parameter of healthy aging in men?

PubMed Central

Walther, Andreas; Philipp, Michel; Lozza, Niclà; Ehlert, Ulrike

2016-01-01

Research on healthy aging in men has increasingly focused on age-related hormonal changes. Testosterone (T) decline is primarily investigated, while age-related changes in other sex steroids (dehydroepiandrosterone [DHEA], estradiol [E2], progesterone [P]) are mostly neglected. An integrated hormone parameter reflecting aging processes in men has yet to be identified. 271 self-reporting healthy men between 40 and 75 provided both psychometric data and saliva samples for hormone analysis. Correlation analysis between age and sex steroids revealed negative associations for the four sex steroids (T, DHEA, E2, and P). Principal component analysis including ten salivary analytes identified a principal component mainly unifying the variance of the four sex steroid hormones. Subsequent principal component analysis including the four sex steroids extracted the principal component of declining steroid hormones (DSH). Moderation analysis of the association between age and DSH revealed significant moderation effects for psychosocial factors such as depression, chronic stress and perceived general health. In conclusion, these results provide further evidence that sex steroids decline in aging men and that the integrated hormone parameter DSH and its rate of change can be used as biomarkers for healthy aging in men. Furthermore, the negative association of age and DSH is moderated by psychosocial factors. PMID:27589836

Identification and apportionment of hazardous elements in the sediments in the Yangtze River estuary.

PubMed

Wang, Jiawei; Liu, Ruimin; Wang, Haotian; Yu, Wenwen; Xu, Fei; Shen, Zhenyao

2015-12-01

In this study, positive matrix factorization (PMF) and principal components analysis (PCA) were combined to identify and apportion pollution-based sources of hazardous elements in the surface sediments in the Yangtze River estuary (YRE). Source identification analysis indicated that PC1, including Al, Fe, Mn, Cr, Ni, As, Cu, and Zn, can be defined as a sewage component; PC2, including Pb and Sb, can be considered as an atmospheric deposition component; and PC3, containing Cd and Hg, can be considered as an agricultural nonpoint component. To better identify the sources and quantitatively apportion the concentrations to their sources, eight sources were identified with PMF: agricultural/industrial sewage mixed (18.6 %), mining wastewater (15.9 %), agricultural fertilizer (14.5 %), atmospheric deposition (12.8 %), agricultural nonpoint (10.6 %), industrial wastewater (9.8 %), marine activity (9.0 %), and nickel plating industry (8.8 %). Overall, the hazardous element content seems to be more connected to anthropogenic activity instead of natural sources. The PCA results laid the foundation for the PMF analysis by providing a general classification of sources. PMF resolves more factors with a higher explained variance than PCA; PMF provided both the internal analysis and the quantitative analysis. The combination of the two methods can provide more reasonable and reliable results.

Genetic variant for behavioral regulation factor of executive function and its possible brain mechanism in attention deficit hyperactivity disorder.

PubMed

Sun, Xiao; Wu, Zhaomin; Cao, Qingjiu; Qian, Ying; Liu, Yong; Yang, Binrang; Chang, Suhua; Yang, Li; Wang, Yufeng

2018-05-16

As a childhood-onset psychiatric disorder, attention deficit hyperactivity disorder (ADHD) is complicated by phenotypic and genetic heterogeneity. Lifelong executive function deficits in ADHD are described in many literatures and have been proposed as endophenotypes of ADHD. However, its genetic basis is still elusive. In this study, we performed a genome-wide association study of executive function, rated with Behavioral Rating Inventory of Executive Function (BRIEF), in ADHD children. We identified one significant variant (rs852004, P = 2.51e-08) for the overall score of BRIEF. The association analyses for each component of executive function found this locus was more associated with inhibit and monitor components. Further principle component analysis and confirmatory factor analysis provided an ADHD-specific executive function pattern including inhibit and monitor factors. SNP rs852004 was mainly associated with the Behavioral Regulation factor. Meanwhile, we found the significant locus was associated with ADHD symptom. The Behavioral Regulation factor mediated its effect on ADHD symptom. Functional magnetic resonance imaging (fMRI) analyses further showed evidence that this variant affected the activity of inhibition control related brain regions. It provided new insights for the genetic basis of executive function in ADHD.

Factor Structure and Reliability of the 2008 and 2009 SERU/UCUES Questionnaire Core. SERU Project Technical Report

ERIC Educational Resources Information Center

Chatman, Steve

2009-01-01

This technical report summarizes the third independent factor analysis of the SERU/UCUES questionnaire responses of students with majors. The 2009 solution employed the same quantitative analysis used in the prior solutions--varimax orthogonal rotation to determine principal components followed by promax oblique rotation to identify…

Career Interests of Students in Psychology Specialties Degrees: Psychometric Evidence and Correlations with the RIASEC Dimensions

ERIC Educational Resources Information Center

Ferreira, Aristides I.; Rodrigues, Rosa I.; da Costa Ferreira, Paula

2016-01-01

In this study, we present the development of a vocational interest scale for university students studying psychology. Three dimensions were extracted through principal component analysis, namely, organizational, educational, and clinical psychology. A second study with confirmatory factor analysis replicated the same three factors obtained in the…

Factor analysis as a tool for spectral line component separation 21cm emission in the direction of L1780

NASA Technical Reports Server (NTRS)

Toth, L. V.; Mattila, K.; Haikala, L.; Balazs, L. G.

1992-01-01

The spectra of the 21cm HI radiation from the direction of L1780, a small high-galactic latitude dark/molecular cloud, were analyzed by multivariate methods. Factor analysis was performed on HI (21cm) spectra in order to separate the different components responsible for the spectral features. The rotated, orthogonal factors explain the spectra as a sum of radiation from the background (an extended HI emission layer), and from the L1780 dark cloud. The coefficients of the cloud-indicator factors were used to locate the HI 'halo' of the molecular cloud. Our statistically derived 'background' and 'cloud' spectral profiles, as well as the spatial distribution of the HI halo emission distribution were compared to the results of a previous study which used conventional methods analyzing nearly the same data set.

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

PubMed Central

Hao, Guozhu

2016-01-01

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

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

PubMed

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

2016-01-01

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

Inequalities in the spiritual health of young Canadians: a national, cross-sectional study.

PubMed

Michaelson, Valerie; Freeman, John; King, Nathan; Ascough, Hannah; Davison, Colleen; Trothen, Tracy; Phillips, Sian; Pickett, William

2016-11-28

Spiritual health, along with physical, emotional, and social aspects, is one of four domains of health. Assessment in this field of research is challenging methodologically. No contemporary population-based studies have profiled the spiritual health of adolescent Canadians with a focus on health inequalities. In a 2014 nationally representative sample of Canadians aged 11-15 years we therefore: (1) psychometrically evaluated a series of items used to assess the perceived importance of spiritual health and its four potential sub-domains (connections with: self, others, nature and the natural environment, and the transcendent) to adolescents; (2) described potential inequalities in spiritual health within adolescent populations, overall and by spiritual health sub-domain, by key socio-demographic factors. Cross-sectional analysis of survey reports from the 2014 (Cycle 7) of the Canadian Health Behaviour in School-aged Children study (weighted n = 25,036). Principal components analysis followed by confirmatory factor analysis were used to explore the psychometric properties of the spiritual health items and the associated composite scale describing perceived importance of spiritual health. Associations among this composite scale, its individual sub-domains, and key socio-demographic factors were then explored. The principal components analysis best supported a four-factor structure where the eight scale items loaded highly according to the original four domains. This was also supported in confirmatory factor analyses. We then combined the eight items into composite spiritual health score as supported by theory, principal components analysis findings, and acceptable tests of reliability. Further confirmatory factor analysis suggested the need for additional refinements to this scale. Based upon exploratory cross-sectional analyses, strong socio-demographic inequalities were observed in the spiritual health measures by age, gender, relative material wealth, immigration status, and province/territory. Study findings highlight potential inequalities in the spiritual health of young Canadians, as well as opportunities for methodological advances in the assessment of adolescent spiritual health in our population.

Exploratory factor analysis of the 12-item Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale in people newly diagnosed with advanced cancer.

PubMed

Bai, Mei; Dixon, Jane K

2014-01-01

The purpose of this study was to reexamine the factor pattern of the 12-item Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale (FACIT-Sp-12) using exploratory factor analysis in people newly diagnosed with advanced cancer. Principal components analysis (PCA) and 3 common factor analysis methods were used to explore the factor pattern of the FACIT-Sp-12. Factorial validity was assessed in association with quality of life (QOL). Principal factor analysis (PFA), iterative PFA, and maximum likelihood suggested retrieving 3 factors: Peace, Meaning, and Faith. Both Peace and Meaning positively related to QOL, whereas only Peace uniquely contributed to QOL. This study supported the 3-factor model of the FACIT-Sp-12. Suggestions for revision of items and further validation of the identified factor pattern were provided.

Classification Techniques for Multivariate Data Analysis.

DTIC Science & Technology

1980-03-28

analysis among biologists, botanists, and ecologists, while some social scientists may refer "typology". Other frequently encountered terms are pattern...the determinantal equation: lB -XW 0 (42) 49 The solutions X. are the eigenvalues of the matrix W-1 B 1 as in discriminant analysis. There are t non...Statistical Package for Social Sciences (SPSS) (14) subprogram FACTOR was used for the principal components analysis. It is designed both for the factor

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

PubMed Central

Ju, Jin Hyun; Crystal, Ronald G.

2017-01-01

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

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

PubMed

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

2017-05-01

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

Determination of Parachute Joint Factors using Seam and Joint Testing

NASA Technical Reports Server (NTRS)

Mollmann, Catherine

2015-01-01

This paper details the methodology for determining the joint factor for all parachute components. This method has been successfully implemented on the Capsule Parachute Assembly System (CPAS) for the NASA Orion crew module for use in determining the margin of safety for each component under peak loads. Also discussed are concepts behind the joint factor and what drives the loss of material strength at joints. The joint factor is defined as a "loss in joint strength...relative to the basic material strength" that occurs when "textiles are connected to each other or to metals." During the CPAS engineering development phase, a conservative joint factor of 0.80 was assumed for each parachute component. In order to refine this factor and eliminate excess conservatism, a seam and joint testing program was implemented as part of the structural validation. This method split each of the parachute structural joints into discrete tensile tests designed to duplicate the loading of each joint. Breaking strength data collected from destructive pull testing was then used to calculate the joint factor in the form of an efficiency. Joint efficiency is the percentage of the base material strength that remains after degradation due to sewing or interaction with other components; it is used interchangeably with joint factor in this paper. Parachute materials vary in type-mainly cord, tape, webbing, and cloth -which require different test fixtures and joint sample construction methods. This paper defines guidelines for designing and testing samples based on materials and test goals. Using the test methodology and analysis approach detailed in this paper, the minimum joint factor for each parachute component can be formulated. The joint factors can then be used to calculate the design factor and margin of safety for that component, a critical part of the design verification process.

The Psychometric Assessment of Children with Learning Disabilities: An Index Derived from a Principal Components Analysis of the WISC-R.

ERIC Educational Resources Information Center

Lawson, J. S.; Inglis, James

1984-01-01

A learning disability index (LDI) for the assessment of intellectual deficits on the Wechsler Intelligence Scale for Children-Revised (WISC-R) is described. The Factor II score coefficients derived from an unrotated principal components analysis of the WISC-R normative data, in combination with the individual's scaled scores, are used for this…

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

PubMed

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.

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

PubMed

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

2016-04-01

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

Psychosocial factors and tooth wear with a significant component of attrition.

PubMed

da Silva, A M; Oakley, D A; Hemmings, K W; Newman, H N; Watkins, S

1997-06-01

Pathological tooth wear is often associated with bruxism, which appears in turn to be influenced by psychosocial factors. This study investigated putative relationships between psychosocial factors (total and average perceived stress, state and trait anxiety) and tooth wear, comparing 45 patients exhibiting tooth wear with a significant component of attrition to 45 controls. Groups were matched for gender and age. Subjects completed the Modified and Perceived Stress Scale and the State-Trait Anxiety Inventory. A between-groups multivariate analysis of variance indicated that the two groups did not differ significantly on the combined psychosocial factors, F(4,85) = 1.16, P > 0.05. However, a univariate F-test showed that tooth-wear patients presented significantly more trait anxiety than controls, F(1,88) = 4.15, P < 0.05. Further research is indicated to clarify the importance of trait anxiety and other psychosocial factors in the progression of tooth wear with a significant component of attrition.

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

PubMed Central

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

2010-01-01

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

The development of summary components for the Disablement in the Physically Active scale in collegiate athletes.

PubMed

Houston, Megan N; Hoch, Johanna M; Van Lunen, Bonnie L; Hoch, Matthew C

2015-11-01

The Disablement in the Physically Active scale (DPA) is a generic patient-reported outcome designed to evaluate constructs of disability in physically active populations. The purpose of this study was to analyze the DPA scale structure for summary components. Four hundred and fifty-six collegiate athletes completed a demographic form and the DPA. A principal component analysis (PCA) was conducted with oblique rotation. Factors with eigenvalues >1 that explained >5 % of the variance were retained. The PCA revealed a two-factor structure consistent with paradigms used to develop the original DPA. Items 1-12 loaded on Factors 1 and Items 13-16 loaded on Factor 2. Items 1-12 pertain to impairment, activity limitations, and participation restrictions. Items 13-16 address psychosocial and emotional well-being. Consideration of item content suggested Factor 1 concerned physical function, while Factor 2 concerned mental well-being. Thus, items clustered around Factor 1 and 2 were identified as physical (DPA-PSC) and mental (DPA-MSC) summary components, respectively. Together, the factors accounted for 65.1 % of the variance. The PCA revealed a two-factor structure for the DPA that resulted in DPA-PSC and DPA-MSC. Analyzing the DPA as separate constructs may provide distinct information that could help to prescribe treatment and rehabilitation strategies.

Spatiotemporal Distribution, Sources, and Photobleaching Imprint of Dissolved Organic Matter in the Yangtze Estuary and Its Adjacent Sea Using Fluorescence and Parallel Factor Analysis

PubMed Central

Li, Penghui; Chen, Ling; Zhang, Wen; Huang, Qinghui

2015-01-01

To investigate the seasonal and interannual dynamics of dissolved organic matter (DOM) in the Yangtze Estuary, surface and bottom water samples in the Yangtze Estuary and its adjacent sea were collected and characterized using fluorescence excitation-emission matrices (EEMs) and parallel factor analysis (PARAFAC) in both dry and wet seasons in 2012 and 2013. Two protein-like components and three humic-like components were identified. Three humic-like components decreased linearly with increasing salinity (r>0.90, p<0.001), suggesting their distribution could primarily be controlled by physical mixing. By contrast, two protein-like components fell below the theoretical mixing line, largely due to microbial degradation and removal during mixing. Higher concentrations of humic-like components found in 2012 could be attributed to higher freshwater discharge relative to 2013. There was a lack of systematic patterns for three humic-like components between seasons and years, probably due to variations of other factors such as sources and characteristics. Highest concentrations of fluorescent components, observed in estuarine turbidity maximum (ETM) region, could be attributed to sediment resuspension and subsequent release of DOM, supported by higher concentrations of fluorescent components in bottom water than in surface water at two stations where sediments probably resuspended. Meanwhile, photobleaching could be reflected from the changes in the ratios between fluorescence intensity (Fmax) of humic-like components and chromophoric DOM (CDOM) absorption coefficient (a355) along the salinity gradient. This study demonstrates the abundance and composition of DOM in estuaries are controlled not only by hydrological conditions, but also by its sources, characteristics and related estuarine biogeochemical processes. PMID:26107640

An Analysis of Construction Contractor Performance Evaluation System

DTIC Science & Technology

2009-03-01

65 8. Summary of Determinant and KMO Values for Finalized...principle component analysis output is the KMO and Bartlett‘s Test. KMO or Kaiser-Meyer-Olkin measure of sampling adequacy is used to identify if a...set of variables, when factored together, yield distinct and reliable factors (Field, 2005). KMO statistics vary between values of 0 to 1. Kaiser

Chromophoric dissolved organic matter (CDOM) variability in Barataria Basin using excitation-emission matrix (EEM) fluorescence and parallel factor analysis (PARAFAC).

PubMed

Singh, Shatrughan; D'Sa, Eurico J; Swenson, Erick M

2010-07-15

Chromophoric dissolved organic matter (CDOM) variability in Barataria Basin, Louisiana, USA,was examined by excitation emission matrix (EEM) fluorescence combined with parallel factor analysis (PARAFAC). CDOM optical properties of absorption and fluorescence at 355nm along an axial transect (36 stations) during March, April, and May 2008 showed an increasing trend from the marine end member to the upper basin with mean CDOM absorption of 11.06 + or - 5.01, 10.05 + or - 4.23, 11.67 + or - 6.03 (m(-)(1)) and fluorescence 0.80 + or - 0.37, 0.78 + or - 0.39, 0.75 + or - 0.51 (RU), respectively. PARAFAC analysis identified two terrestrial humic-like (component 1 and 2), one non-humic like (component 3), and one soil derived humic acid like (component 4) components. The spatial variation of the components showed an increasing trend from station 1 (near the mouth of basin) to station 36 (end member of bay; upper basin). Deviations from this increasing trend were observed at a bayou channel with very high chlorophyll-a concentrations especially for component 3 in May 2008 that suggested autochthonous production of CDOM. The variability of components with salinity indicated conservative mixing along the middle part of the transect. Component 1 and 4 were found to be relatively constant, while components 2 and 3 revealed an inverse relationship for the sampling period. Total organic carbon showed increasing trend for each of the components. An increase in humification and a decrease in fluorescence indices along the transect indicated an increase in terrestrial derived organic matter and reduced microbial activity from lower to upper basin. The use of these indices along with PARAFAC results improved dissolved organic matter characterization in the Barataria Basin. Copyright 2010 Elsevier B.V. All rights reserved.

Factors Affecting Turkish Students' Achievement in Mathematics

ERIC Educational Resources Information Center

Demir, Ibrahim; Kilic, Serpil; Depren, Ozer

2009-01-01

Following past researches, student background, learning strategies, self-related cognitions in mathematics and school climate variables were important for achievement. The purpose of this study was to identify a number of factors that represent the relationship among sets of interrelated variables using principal component factor analysis and…

Insights into the interaction between carbamazepine and natural dissolved organic matter in the Yangtze Estuary using fluorescence excitation-emission matrix spectra coupled with parallel factor analysis.

PubMed

Wang, Ying; Zhang, Manman; Fu, Jun; Li, Tingting; Wang, Jinggang; Fu, Yingyu

2016-10-01

The interaction between carbamazepine (CBZ) and dissolved organic matter (DOM) from three zones (the nearshore, the river channel, and the coastal areas) in the Yangtze Estuary was investigated using fluorescence quenching titration combined with excitation emission matrix spectra and parallel factor analysis (PARAFAC). The complexation between CBZ and DOM was demonstrated by the increase in hydrogen bonding and the disappearance of the C=O stretch obtained from the Fourier transform infrared spectroscopy analysis. The results indicated that two protein-like substances (component 2 and component3) and two humic-like substances (component 1 and 4) were identified in the DOM from the Yangtze Estuary. The fluorescence quenching curves of each component with the addition of CBZ and the Ryan and Weber model calculation results both demonstrated that the different components exhibited different complexation activities with CBZ. The protein-like components had a stronger affinity with CBZ than did the humic-like substances. On the other hand, the autochthonous tyrosine-like C2 played an important role in the complexation with DOM from the river channel and coastal areas, while C3 influenced by anthropogenic activities showed an obvious effect in the nearshore area. DOMs from the river channel have the highest binding capacity for CBZ, which may ascribe to the relatively high phenol content group in the DOM.

A symmetrical subtraction combined with interpolated values for eliminating scattering from fluorescence EEM data

NASA Astrophysics Data System (ADS)

Xu, Jing; Liu, Xiaofei; Wang, Yutian

2016-08-01

Parallel factor analysis is a widely used method to extract qualitative and quantitative information of the analyte of interest from fluorescence emission-excitation matrix containing unknown components. Big amplitude of scattering will influence the results of parallel factor analysis. Many methods of eliminating scattering have been proposed. Each of these methods has its advantages and disadvantages. The combination of symmetrical subtraction and interpolated values has been discussed. The combination refers to both the combination of results and the combination of methods. Nine methods were used for comparison. The results show the combination of results can make a better concentration prediction for all the components.

Component Selection for Sterile Compounding.

PubMed

Dilzer, Richard H

2017-01-01

This article describes the factors to consider, as well as the process of proper component selection, for use in preparing compounded sterile preparations. Special emphasis is placed on individual chemical factors that may impact a preparation's accuracy and potency. Values reported in a typical certificate of analysis are discussed, including methods of identifying any required adjustments to a master formulation or compounding record during the compounding of sterile preparations. Proper screening of the certificate of analysis, the Safety Data Sheet, procedural documentation, and the filing of all certificates of conformance are crucial to the operation of a sterile compounding facility. Copyright© by International Journal of Pharmaceutical Compounding, Inc.

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

ERIC Educational Resources Information Center

Montri, Paitoon; Sirisuth, Chaiyuth; Lammana, Preeda

2015-01-01

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

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

PubMed

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

2018-02-01

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

Principal-component analysis of two-particle azimuthal correlations in PbPb and $$p\\text{Pb}$$ collisions at CMS

DOE PAGES

Sirunyan, A.M.; et al.

2017-12-05

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from sNN=2.76TeV PbPb and sNN=5.02TeV pPb collisions collected by the CMS experiment at the CERN Large Hadron Collider. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it was shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on the breakdown of flow factorization in heavymore » ion collisions. The first two modes (“leading” and “subleading”) of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and pPb collisions as a function of pT over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique was also applied to multiplicity fluctuations. These also show a subleading mode. The connection of these new results to previous studies of factorization is discussed.« less

Principal-component analysis of two-particle azimuthal correlations in PbPb and pPb collisions at CMS

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

Sirunyan, Albert M; et al.

2017-08-23

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from sqrt(s[NN]) = 2.76 TeV PbPb and sqrt(s[NN]) = 5.02 TeV pPb collisions collected by the CMS experiment at the LHC. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it has been shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on the breakdown ofmore » flow factorization in heavy ion collisions. The first two modes ("leading" and "subleading") of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and pPb collisions as a function of pt over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique has also been applied to multiplicity fluctuations. These also show a subleading mode. The connection of these new results to previous studies of factorization is discussed.« less

Principal-component analysis of two-particle azimuthal correlations in PbPb and p Pb collisions at CMS

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

Sirunyan, A. M.; Tumasyan, A.; Adam, W.

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from √ sNN = 2.76TeV PbPb and √ sNN = 5.02TeV pPb collisions collected by the CMS experiment at the CERN Large Hadron Collider. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it was shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on themore » breakdown of flow factorization in heavy ion collisions. The first two modes (“leading” and “subleading”) of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and pPb collisions as a function of p T over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique was also applied to multiplicity fluctuations. These also show a subleading mode. As a result, the connection of these new results to previous studies of factorization is discussed.« less

Principal-component analysis of two-particle azimuthal correlations in PbPb and p Pb collisions at CMS

NASA Astrophysics Data System (ADS)

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Grossmann, J.; Hrubec, J.; Jeitler, M.; König, A.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Pree, E.; Rabady, D.; Rad, N.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Spanring, M.; Spitzbart, D.; Strauss, J.; Waltenberger, W.; Wittmann, J.; Wulz, C.-E.; Zarucki, M.; Chekhovsky, V.; Mossolov, V.; Suarez Gonzalez, J.; De Wolf, E. A.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; De Bruyn, I.; De Clercq, J.; Deroover, K.; Flouris, G.; Lowette, S.; Moortgat, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Vannerom, D.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Roskas, C.; Salva, S.; Tytgat, M.; Verbeke, W.; Zaganidis, N.; Bakhshiansohi, H.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Jafari, A.; Komm, M.; Krintiras, G.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Piotrzkowski, K.; Quertenmont, L.; Vidal Marono, M.; Wertz, S.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Melo De Almeida, M.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Torres Da Silva De Araujo, F.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Tomei, T. R. Fernandez Perez; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Misheva, M.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Gao, X.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Jiang, C. H.; Leggat, D.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Yazgan, E.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Courbon, B.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Susa, T.; Ather, M. W.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; Abdelalim, A. A.; Mohammed, Y.; Salama, E.; Dewanjee, R. 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T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Rossini, M.; Schönenberger, M.; Shchutska, L.; Starodumov, A.; Tavolaro, V. R.; Theofilatos, K.; Vesterbacka Olsson, M. L.; Wallny, R.; Zagozdzinska, A.; Zhu, D. H.; Aarrestad, T. K.; Amsler, C.; Caminada, L.; Canelli, M. F.; De Cosa, A.; Donato, S.; Galloni, C.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Ngadiuba, J.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Seitz, C.; Zucchetta, A.; Candelise, V.; Doan, T. H.; Jain, Sh.; Khurana, R.; Konyushikhin, M.; Kuo, C. M.; Lin, W.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chao, Y.; Chen, K. F.; Chen, P. H.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Miñano Moya, M.; Paganis, E.; Psallidas, A.; Tsai, J. f.; Asavapibhop, B.; Kovitanggoon, K.; Singh, G.; Srimanobhas, N.; Adiguzel, A.; Bakirci, M. N.; Boran, F.; Cerci, S.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Dumanoglu, I.; Girgis, S.; Gokbulut, G.; Guler, Y.; Hos, I.; Kangal, E. E.; Kara, O.; Kayis Topaksu, A.; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Tali, B.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Bilin, B.; Karapinar, G.; Ocalan, K.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Tekten, S.; Yetkin, E. A.; Agaras, M. N.; Atay, S.; Cakir, A.; Cankocak, K.; Grynyov, B.; Levchuk, L.; Sorokin, P.; Aggleton, R.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Seif El Nasr-storey, S.; Smith, D.; Smith, V. J.; Belyaev, A.; Brew, C.; Brown, R. M.; Calligaris, L.; Cieri, D.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Baber, M.; Bainbridge, R.; Breeze, S.; Buchmuller, O.; Bundock, A.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; De Wit, A.; Della Negra, M.; Di Maria, R.; Dunne, P.; Elwood, A.; Futyan, D.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Lane, R.; Laner, C.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Matsushita, T.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Scott, E.; Seez, C.; Shtipliyski, A.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Winterbottom, D.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Bartek, R.; Dominguez, A.; Buccilli, A.; Cooper, S. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Cutts, D.; Garabedian, A.; Hakala, J.; Heintz, U.; Hogan, J. M.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Pazzini, J.; Piperov, S.; Sagir, S.; Syarif, R.; Yu, D.; Band, R.; Brainerd, C.; Burns, D.; Calderon De La Barca Sanchez, M.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; Smith, J.; Squires, M.; Stolp, D.; Tos, K.; Tripathi, M.; Wang, Z.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Saltzberg, D.; Schnaible, C.; Valuev, V.; Bouvier, E.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Ghiasi Shirazi, S. M. A.; Hanson, G.; Heilman, J.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Olmedo Negrete, M.; Paneva, M. I.; Shrinivas, A.; Si, W.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Hashemi, B.; Holzner, A.; Klein, D.; Kole, G.; Krutelyov, V.; Letts, J.; Macneill, I.; Masciovecchio, M.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Amin, N.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Franco Sevilla, M.; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Heller, R.; Incandela, J.; Mullin, S. D.; Ovcharova, A.; Qu, H.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Bendavid, J.; Bornheim, A.; Lawhorn, J. M.; Newman, H. B.; Nguyen, T.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhang, Z.; Zhu, R. Y.; Andrews, M. B.; Ferguson, T.; Mudholkar, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Weinberg, M.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Leontsinis, S.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Abdullin, S.; Albrow, M.; Apollinari, G.; Apresyan, A.; Apyan, A.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Canepa, A.; Cheung, H. W. K.; Chlebana, F.; Cremonesi, M.; Duarte, J.; Elvira, V. D.; Freeman, J.; Gecse, Z.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Lincoln, D.; Lipton, R.; Liu, M.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Schneider, B.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strait, J.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Acosta, D.; Avery, P.; Bortignon, P.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Das, S.; Field, R. D.; Furic, I. K.; Konigsberg, J.; Korytov, A.; Kotov, K.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Rank, D.; Sperka, D.; Terentyev, N.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Joshi, Y. R.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, T.; Askew, A.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Kolberg, T.; Perry, T.; Prosper, H.; Santra, A.; Yohay, R.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Cavanaugh, R.; Chen, X.; Evdokimov, O.; Gerber, C. E.; Hangal, D. A.; Hofman, D. J.; Jung, K.; Kamin, J.; Sandoval Gonzalez, I. D.; Tonjes, M. B.; Trauger, H.; Varelas, N.; Wang, H.; Wu, Z.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Castle, J.; Khalil, S.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Royon, C.; Sanders, S.; Schmitz, E.; Stringer, R.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Azzolini, V.; Barbieri, R.; Baty, A.; Bi, R.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Tatar, K.; Velicanu, D.; Wang, J.; Wang, T. W.; Wyslouch, B.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Hansen, P.; Kalafut, S.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Alyari, M.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wang, R.-J.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Loukas, N.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; Wayne, M.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Ji, W.; Liu, B.; Luo, W.; Puigh, D.; Winer, B. L.; Wulsin, H. W.; Benaglia, A.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Lange, D.; Luo, J.; Marlow, D.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Svyatkovskiy, A.; Tully, C.; Malik, S.; Norberg, S.; Barker, A.; Barnes, V. E.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; Schulte, J. F.; Sun, J.; Wang, F.; Xie, W.; Cheng, T.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Ciesielski, R.; Goulianos, K.; Mesropian, C.; Agapitos, A.; Chou, J. P.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Montalvo, R.; Nash, K.; Osherson, M.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Castaneda Hernandez, A.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Sturdy, J.; Zaleski, S.; Buchanan, J.; Caillol, C.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.; CMS Collaboration

2017-12-01

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from √{sNN}=2.76 TeV PbPb and √{sNN}=5.02 TeV p Pb collisions collected by the CMS experiment at the CERN Large Hadron Collider. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it was shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on the breakdown of flow factorization in heavy ion collisions. The first two modes ("leading" and "subleading") of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and p Pb collisions as a function of pT over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique was also applied to multiplicity fluctuations. These also show a subleading mode. The connection of these new results to previous studies of factorization is discussed.

Principal-component analysis of two-particle azimuthal correlations in PbPb and p Pb collisions at CMS

DOE PAGES

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; ...

2017-12-05

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from √ sNN = 2.76TeV PbPb and √ sNN = 5.02TeV pPb collisions collected by the CMS experiment at the CERN Large Hadron Collider. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it was shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on themore » breakdown of flow factorization in heavy ion collisions. The first two modes (“leading” and “subleading”) of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and pPb collisions as a function of p T over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique was also applied to multiplicity fluctuations. These also show a subleading mode. As a result, the connection of these new results to previous studies of factorization is discussed.« less

Multivariate Analysis of Remains of Molluscan Foods Consumed by Latest Pleistocene and Holocene Humans in Nerja Cave, Málaga, Spain

NASA Astrophysics Data System (ADS)

Serrano, Francisco; Guerra-Merchán, Antonio; Lozano-Francisco, Carmen; Vera-Peláez, José Luis

1997-09-01

Nerja Cave is a karstic cavity used by humans from Late Paleolithic to post-Chalcolithic times. Remains of molluscan foods in the uppermost Pleistocene and Holocene sediments were studied with cluster analysis and principal components analysis, in both Qand Rmodes. The results from cluster analysis distinguished interval groups mainly in accordance with chronology and distinguished assemblages of species mainly according to habitat. Significant changes in the shellfish diet through time were revealed. In the Late Magdalenian, most molluscs consumed consisted of pulmonate gastropods and species from sandy sea bottoms. The Epipaleolithic diet was more varied and included species from rocky shorelines. From the Neolithic onward most molluscs consumed were from rocky shorelines. From the principal components analysis in Qmode, the first factor reflected mainly changes in the predominant capture environment, probably because of major paleogeographic changes. The second factor may reflect selective capture along rocky coastlines during certain times. The third factor correlated well with the sea-surface temperature curve in the western Mediterranean (Alboran Sea) during the late Quaternary.

An Analysis of Turnover Intentions: A Reexamination of Air Force Civil Engineering Company Grade Officers

DTIC Science & Technology

2012-03-01

edu 75 Appendix C Factor Analysis of Measurement Items Interrole conflict Factor Analysis (FA): Table: KMO and Bartlett’s Test Kaiser-Meyer...Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. 77 POS FA: Table: KMO and Bartlett’s...Tempo FA: Table: KMO and Bartlett’s Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .733 Bartlett’s Test of Sphericity Approx. Chi-Square

The Factor Structure of Some Piagetian Tasks

ERIC Educational Resources Information Center

Lawson, Anton E.; Nordland, Floyd H.

1976-01-01

Investigated was the hypothesis that conservation tasks are unifactor by administering eight different conservation tasks to 96 seventh-grade science students and performing a principal component analysis on the data. Results indicated that conservation tasks may measure up to three different components of cognitive thought. (SL)

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Battle Damage Modeling

DTIC Science & Technology

2010-05-01

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

Assessment on the leakage hazard of landfill leachate using three-dimensional excitation-emission fluorescence and parallel factor analysis method.

PubMed

Pan, Hongwei; Lei, Hongjun; Liu, Xin; Wei, Huaibin; Liu, Shufang

2017-09-01

A large number of simple and informal landfills exist in developing countries, which pose as tremendous soil and groundwater pollution threats. Early warning and monitoring of landfill leachate pollution status is of great importance. However, there is a shortage of affordable and effective tools and methods. In this study, a soil column experiment was performed to simulate the pollution status of leachate using three-dimensional excitation-emission fluorescence (3D-EEMF) and parallel factor analysis (PARAFAC) models. Sum of squared residuals (SSR) and principal component analysis (PCA) were used to determine the optimal components for PARAFAC. A one-way analysis of variance showed that the component scores of the soil column leachate were significant influenced by landfill leachate (p<0.05). Therefore, the ratio of the component scores of the soil under the landfill to that of natural soil could be used to evaluate the leakage status of landfill leachate. Furthermore, a hazard index (HI) and a hazard evaluation standard were established. A case study of Kaifeng landfill indicated a low hazard (level 5) by the use of HI. In summation, HI is presented as a tool to evaluate landfill pollution status and for the guidance of municipal solid waste management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Seasonality of suicides: environmental, sociological and biological covariations.

PubMed

Souêtre, E; Salvati, E; Belugou, J L; Douillet, P; Braccini, T; Darcourt, G

1987-01-01

The monthly rates of completed suicides in France from 1978 until 1982 were analyzed. The seasonal variations of environmental (daylight and sunlight durations, mean temperature, geomagnetism), sociological (unemployment, deaths of all causes, birth and conception rates), and biological (melatonin, cortisol and serotonin circannual rhythms) factors were compared to the seasonal patterns of suicides. A clear seasonal variation (with peaks in May and September) in suicidal behavior was detected. These patterns tended to differ as a function of age (bimodal in young, unimodal in old people). The component analysis clearly pointed out that seasonal patterns of suicides may be considered as the sum of two components, unimodal and bimodal. Almost similar covariations were found between the main seasonal (unimodal) component of suicides and environmental (daylight duration and mean monthly temperature) or sociological factors whereas the secondary component was more correlated to variations in environmental factors and, to some extent, to biological parameters.

Using Interactive Graphics to Teach Multivariate Data Analysis to Psychology Students

ERIC Educational Resources Information Center

Valero-Mora, Pedro M.; Ledesma, Ruben D.

2011-01-01

This paper discusses the use of interactive graphics to teach multivariate data analysis to Psychology students. Three techniques are explored through separate activities: parallel coordinates/boxplots; principal components/exploratory factor analysis; and cluster analysis. With interactive graphics, students may perform important parts of the…

Scale for positive aspects of caregiving experience: development, reliability, and factor structure.

PubMed

Kate, N; Grover, S; Kulhara, P; Nehra, R

2012-06-01

OBJECTIVE. To develop an instrument (Scale for Positive Aspects of Caregiving Experience [SPACE]) that evaluates positive caregiving experience and assess its psychometric properties. METHODS. Available scales which assess some aspects of positive caregiving experience were reviewed and a 50-item questionnaire with a 5-point rating was constructed. In all, 203 primary caregivers of patients with severe mental disorders were asked to complete the questionnaire. Internal consistency, test-retest reliability, cross-language reliability, split-half reliability, and face validity were evaluated. Principal component factor analysis was run to assess the factorial validity of the scale. RESULTS. The scale developed as part of the study was found to have good internal consistency, test-retest reliability, cross-language reliability, split-half reliability, and face validity. Principal component factor analysis yielded a 4-factor structure, which also had good test-retest reliability and cross-language reliability. There was a strong correlation between the 4 factors obtained. CONCLUSION. The SPACE developed as part of this study has good psychometric properties.

Discovering Hematopoietic Mechanisms Through Genome-Wide Analysis of GATA Factor Chromatin Occupancy

PubMed Central

Fujiwara, Tohru; O'Geen, Henriette; Keles, Sunduz; Blahnik, Kimberly; Linnemann, Amelia K.; Kang, Yoon-A; Choi, Kyunghee; Farnham, Peggy J.; Bresnick, Emery H.

2009-01-01

SUMMARY GATA factors interact with simple DNA motifs (WGATAR) to regulate critical processes, including hematopoiesis, but very few WGATAR motifs are occupied in genomes. Given the rudimentary knowledge of mechanisms underlying this restriction, and how GATA factors establish genetic networks, we used ChIP-seq to define GATA-1 and GATA-2 occupancy genome-wide in erythroid cells. Coupled with genetic complementation analysis and transcriptional profiling, these studies revealed a rich collection of targets containing a characteristic binding motif of greater complexity than WGATAR. GATA factors occupied loci encoding multiple components of the Scl/TAL1 complex, a master regulator of hematopoiesis and leukemogenic target. Mechanistic analyses provided evidence for cross-regulatory and autoregulatory interactions among components of this complex, including GATA-2 induction of the hematopoietic corepressor ETO-2 and an ETO-2 negative autoregulatory loop. These results establish fundamental principles underlying GATA factor mechanisms in chromatin and illustrate a complex network of considerable importance for the control of hematopoiesis. PMID:19941826

An investigation of the critical components of a land ethic: An application of Q methodology

NASA Astrophysics Data System (ADS)

Spradling, Suzanne Shaw

Scope and method of study. The purpose of this study was to reveal the underlying structure of the beliefs of a sample of environmental educators regarding the critical components of a land or environmental ethic. Participants in the study were 30 environmental educators from seven states. All had been trained in one or more of the following national environmental education programs: Project WILD, Project WET, Project Learning Tree, Leopold Education Project, or Leave No Trace. Ages of the participants ranged from 18--63 years. Q methodology directed the study. Each participant completed a Q-sort of 54 statements related to environmental ethics. The data were analyzed using a computer program PQMethod 2.06. This program performed a correlation matrix as input data for factor analysis, and a VARIMAX rotation. Participant demographic data were collected in order to provide a more complete picture of the revealed structure of beliefs. Findings and conclusions. A three-factor solution was revealed from the analysis of the data. These factors represent the groupings of the participants with like beliefs in reference to the critical components of environmental ethics. Factor one was named Nature's Advocates. These individuals believe in equal rights for all parts of the environment. Factor two was named Nature's Stewards because of the revealed belief that humans were to have dominion over the earth given to them by the creator and that natural resources should be used responsibly. Factor three was named Nature's Romantics because of their belief that nature should be preserved for its aesthetic value and because of their naive approach to conservation. The demographic data added detail to the portrait created from the Q-sort data analysis. It is important then, to take into consideration what environmental educators believe about environmental ethics in designing meaningful curriculum that seeks to foster the development of those ethics. This study reveals the beliefs of a sample of environmental educators relating to environmental ethics critical components.

Comparative Analysis of the Volatile Components of Agrimonia eupatoria from Leaves and Roots by Gas Chromatography-Mass Spectrometry and Multivariate Curve Resolution

PubMed Central

Feng, Xiao-Liang; He, Yun-biao; Liang, Yi-Zeng; Wang, Yu-Lin; Huang, Lan-Fang; Xie, Jian-Wei

2013-01-01

Gas chromatography-mass spectrometry and multivariate curve resolution were applied to the differential analysis of the volatile components in Agrimonia eupatoria specimens from different plant parts. After extracted with water distillation method, the volatile components in Agrimonia eupatoria from leaves and roots were detected by GC-MS. Then the qualitative and quantitative analysis of the volatile components in the main root of Agrimonia eupatoria was completed with the help of subwindow factor analysis resolving two-dimensional original data into mass spectra and chromatograms. 68 of 87 separated constituents in the total ion chromatogram of the volatile components were identified and quantified, accounting for about 87.03% of the total content. Then, the common peaks in leaf were extracted with orthogonal projection resolution method. Among the components determined, there were 52 components coexisting in the studied samples although the relative content of each component showed difference to some extent. The results showed a fair consistency in their GC-MS fingerprint. It was the first time to apply orthogonal projection method to compare different plant parts of Agrimonia eupatoria, and it reduced the burden of qualitative analysis as well as the subjectivity. The obtained results proved the combined approach powerful for the analysis of complex Agrimonia eupatoria samples. The developed method can be used to further study and quality control of Agrimonia eupatoria. PMID:24286016

Comparative Analysis of the Volatile Components of Agrimonia eupatoria from Leaves and Roots by Gas Chromatography-Mass Spectrometry and Multivariate Curve Resolution.

PubMed

Feng, Xiao-Liang; He, Yun-Biao; Liang, Yi-Zeng; Wang, Yu-Lin; Huang, Lan-Fang; Xie, Jian-Wei

2013-01-01

Gas chromatography-mass spectrometry and multivariate curve resolution were applied to the differential analysis of the volatile components in Agrimonia eupatoria specimens from different plant parts. After extracted with water distillation method, the volatile components in Agrimonia eupatoria from leaves and roots were detected by GC-MS. Then the qualitative and quantitative analysis of the volatile components in the main root of Agrimonia eupatoria was completed with the help of subwindow factor analysis resolving two-dimensional original data into mass spectra and chromatograms. 68 of 87 separated constituents in the total ion chromatogram of the volatile components were identified and quantified, accounting for about 87.03% of the total content. Then, the common peaks in leaf were extracted with orthogonal projection resolution method. Among the components determined, there were 52 components coexisting in the studied samples although the relative content of each component showed difference to some extent. The results showed a fair consistency in their GC-MS fingerprint. It was the first time to apply orthogonal projection method to compare different plant parts of Agrimonia eupatoria, and it reduced the burden of qualitative analysis as well as the subjectivity. The obtained results proved the combined approach powerful for the analysis of complex Agrimonia eupatoria samples. The developed method can be used to further study and quality control of Agrimonia eupatoria.

Assessment and quantification of post-weaning multi-systemic wasting syndrome severity at farm level.

PubMed

Alarcon, Pablo; Velasova, Martina; Werling, Dirk; Stärk, Katharina D C; Chang, Yu-Mei; Nevel, Amanda; Pfeiffer, Dirk U; Wieland, Barbara

2011-01-01

Post-weaning multi-systemic wasting syndrome (PMWS) causes major economic losses for the English pig industry and severity of clinical signs and economic impact vary considerably between affected farms. We present here a novel approach to quantify severity of PMWS based on morbidity and mortality data and presence of porcine circovirus type 2 (PCV2). In 2008-2009, 147 pig farms across England, non-vaccinating for PCV2, were enrolled in a cross-sectional study. Factor analysis was used to generate variables representing biologically meaningful aspects of variation among qualitative and quantitative morbidity variables. Together with other known variables linked to PMWS, the resulting factors were included in a principal component analysis (PCA) to derive an algorithm for PMWS severity. Factor analysis resulted in two factors: Morbidity Factor 1 (MF1) representing mainly weaner and grower morbidity, and Morbidity Factor 2 (MF2) which mainly reflects variation in finisher morbidity. This indicates that farms either had high morbidity mainly in weaners/growers or mainly in finishers. Subsequent PCA resulted in the extraction of one component representing variation in MF1, post-weaning mortality and percentage of PCV2 PCR positive animals. Component scores were normalised to a value range from 0 to 10 and farms classified into: non or slightly affected farms with a score <4, moderately affected farms with scores 4-6.5 and highly affected farms with a score >6.5. The identified farm level PMWS severities will be used to identify risk factors related to these, to assess the efficacy of PCV2 vaccination and investigating the economic impact of potential control measures. Copyright © 2010 Elsevier B.V. All rights reserved.

Identifying Items to Assess Methodological Quality in Physical Therapy Trials: A Factor Analysis

PubMed Central

Cummings, Greta G.; Fuentes, Jorge; Saltaji, Humam; Ha, Christine; Chisholm, Annabritt; Pasichnyk, Dion; Rogers, Todd

2014-01-01

Background Numerous tools and individual items have been proposed to assess the methodological quality of randomized controlled trials (RCTs). The frequency of use of these items varies according to health area, which suggests a lack of agreement regarding their relevance to trial quality or risk of bias. Objective The objectives of this study were: (1) to identify the underlying component structure of items and (2) to determine relevant items to evaluate the quality and risk of bias of trials in physical therapy by using an exploratory factor analysis (EFA). Design A methodological research design was used, and an EFA was performed. Methods Randomized controlled trials used for this study were randomly selected from searches of the Cochrane Database of Systematic Reviews. Two reviewers used 45 items gathered from 7 different quality tools to assess the methodological quality of the RCTs. An exploratory factor analysis was conducted using the principal axis factoring (PAF) method followed by varimax rotation. Results Principal axis factoring identified 34 items loaded on 9 common factors: (1) selection bias; (2) performance and detection bias; (3) eligibility, intervention details, and description of outcome measures; (4) psychometric properties of the main outcome; (5) contamination and adherence to treatment; (6) attrition bias; (7) data analysis; (8) sample size; and (9) control and placebo adequacy. Limitation Because of the exploratory nature of the results, a confirmatory factor analysis is needed to validate this model. Conclusions To the authors' knowledge, this is the first factor analysis to explore the underlying component items used to evaluate the methodological quality or risk of bias of RCTs in physical therapy. The items and factors represent a starting point for evaluating the methodological quality and risk of bias in physical therapy trials. Empirical evidence of the association among these items with treatment effects and a confirmatory factor analysis of these results are needed to validate these items. PMID:24786942

Identifying items to assess methodological quality in physical therapy trials: a factor analysis.

PubMed

Armijo-Olivo, Susan; Cummings, Greta G; Fuentes, Jorge; Saltaji, Humam; Ha, Christine; Chisholm, Annabritt; Pasichnyk, Dion; Rogers, Todd

2014-09-01

Numerous tools and individual items have been proposed to assess the methodological quality of randomized controlled trials (RCTs). The frequency of use of these items varies according to health area, which suggests a lack of agreement regarding their relevance to trial quality or risk of bias. The objectives of this study were: (1) to identify the underlying component structure of items and (2) to determine relevant items to evaluate the quality and risk of bias of trials in physical therapy by using an exploratory factor analysis (EFA). A methodological research design was used, and an EFA was performed. Randomized controlled trials used for this study were randomly selected from searches of the Cochrane Database of Systematic Reviews. Two reviewers used 45 items gathered from 7 different quality tools to assess the methodological quality of the RCTs. An exploratory factor analysis was conducted using the principal axis factoring (PAF) method followed by varimax rotation. Principal axis factoring identified 34 items loaded on 9 common factors: (1) selection bias; (2) performance and detection bias; (3) eligibility, intervention details, and description of outcome measures; (4) psychometric properties of the main outcome; (5) contamination and adherence to treatment; (6) attrition bias; (7) data analysis; (8) sample size; and (9) control and placebo adequacy. Because of the exploratory nature of the results, a confirmatory factor analysis is needed to validate this model. To the authors' knowledge, this is the first factor analysis to explore the underlying component items used to evaluate the methodological quality or risk of bias of RCTs in physical therapy. The items and factors represent a starting point for evaluating the methodological quality and risk of bias in physical therapy trials. Empirical evidence of the association among these items with treatment effects and a confirmatory factor analysis of these results are needed to validate these items. © 2014 American Physical Therapy Association.

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

ERIC Educational Resources Information Center

Ho, Esther Sui Chu; Sum, Kwok Wing

2018-01-01

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

Risk factors associated with liver steatosis and fibrosis in chronic hepatitis B patient with component of metabolic syndrome.

PubMed

Cai, Shaohang; Ou, Zejin; Liu, Duan; Liu, Lili; Liu, Ying; Wu, Xiaolu; Yu, Tao; Peng, Jie

2018-05-01

We investigated whether metabolic syndrome exacerbated the risk of liver fibrosis among chronic hepatitis B patients and risk factors associated with liver steatosis and fibrosis in chronic hepatitis B patients with components of metabolic syndrome. This study included 1236 chronic hepatitis B patients with at least one component of metabolic syndrome. The controlled attenuation parameter and liver stiffness, patient information and relevant laboratory data were recorded. Controlled attenuation parameter was increased progressively with the number of metabolic syndrome components ( p  < 0.001). Multivariate analysis indicated younger age, high gamma-glutamyltransferase level, high waist-hip ratio, and high body mass index were independent risk factors associated with nonalcoholic fatty liver disease among chronic hepatitis B patients with metabolic syndrome. In the fibrosis and non-fibrosis groups, most of blood lipid was relatively lower in fibrosis group. An increased proportion of chronic hepatitis B patients with liver fibrosis was found concomitant with an increasing number of components of metabolic syndrome. Male gender, older age, smoking, aspartate aminotransferase levels, high body mass index, and low platelet level were identified as independent risk factors associated with liver fibrosis. For chronic hepatitis B patients with coexisting components of metabolic syndrome, stratification by independent risk factors for nonalcoholic fatty liver disease and fibrosis can help with management of their disease.

The factorial reliability of the Middlesex Hospital Questionnaire in normal subjects.

PubMed

Bagley, C

1980-03-01

The internal reliability of the Middlesex Hospital Questionnaire and its component subscales has been checked by means of principal components analyses of data on 256 normal subjects. The subscales (with the possible exception of Hysteria) were found to contribute to the general underlying factor of psychoneurosis. In general, the principal components analysis points to the reliability of the subscales, despite some item overlap.

Procedures and models for estimating preconstruction costs of highway projects.

DOT National Transportation Integrated Search

2012-07-01

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

Generalizability of dietary patterns of the inverse association between alcohol consumption and type 2 diabetes risk

USDA-ARS?s Scientific Manuscript database

Epidemiology of dietary components and disease risk limits interpretability due to potential residual confounding by correlated dietary components. Dietary pattern analyses by factor analysis or partial least squares may overcome this limitation. To examine confounding by dietary pattern as well as ...

Confounding by dietary pattern of the inverse association between alcohol consumption and type 2 diabetes risk

USDA-ARS?s Scientific Manuscript database

Epidemiology of dietary components and disease risk limits interpretability due to potential residual confounding by correlated dietary components. Dietary pattern analyses by factor analysis or partial least squares may overcome the limitation. To examine confounding by dietary pattern as well as ...

Confounding by dietary patterns of the inverse association between alcohol consumption and type 2 diabetes risk

USDA-ARS?s Scientific Manuscript database

Epidemiology of dietary components and disease risk limits interpretability due to potential residual confounding by correlated dietary components. Dietary pattern analyses by factor analysis or partial least squares may overcome this limitation. To examine confounding by dietary pattern as well as ...

The Individual Regulation Component of Group Emotional Intelligence: Measure Development and Validation

ERIC Educational Resources Information Center

Peterson, Christina Hamme

2012-01-01

Counseling work is increasingly conducted in team format. The methods counseling teams use to manage the emotional component of their group life, or their group emotional intelligence, have been proposed as significantly contributing to group member trust, cooperation, and ultimate performance. Item development, exploratory factor analysis, and…

[Assessment of the strength of tobacco control on creating smoke-free hospitals using principal components analysis].

PubMed

Liu, Hui-lin; Wan, Xia; Yang, Gong-huan

2013-02-01

To explore the relationship between the strength of tobacco control and the effectiveness of creating smoke-free hospital, and summarize the main factors that affect the program of creating smoke-free hospitals. A total of 210 hospitals from 7 provinces/municipalities directly under the central government were enrolled in this study using stratified random sampling method. Principle component analysis and regression analysis were conducted to analyze the strength of tobacco control and the effectiveness of creating smoke-free hospitals. Two principal components were extracted in the strength of tobacco control index, which respectively reflected the tobacco control policies and efforts, and the willingness and leadership of hospital managers regarding tobacco control. The regression analysis indicated that only the first principal component was significantly correlated with the progression in creating smoke-free hospital (P<0.001), i.e. hospitals with higher scores on the first principal component had better achievements in smoke-free environment creation. Tobacco control policies and efforts are critical in creating smoke-free hospitals. The principal component analysis provides a comprehensive and objective tool for evaluating the creation of smoke-free hospitals.

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

PubMed

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

2007-01-01

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

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

PubMed Central

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

2007-01-01

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

Research on distributed heterogeneous data PCA algorithm based on cloud platform

NASA Astrophysics Data System (ADS)

Zhang, Jin; Huang, Gang

2018-05-01

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

The Influence Of Component Alignment On The Life Of Total Knee Prostheses

NASA Astrophysics Data System (ADS)

Bugariu, Delia; Bereteu, Liviu

2012-12-01

An arthritic knee affects the patient's life by causing pain and limiting movement. If the cartilage and the bone surfaces are severely affected, the natural joint is replaced with an artificial joint. The procedure is called total knee arthroplasty (TKA). Lately, the numbers of implanted total knee prostheses grow steadily. An important factor in TKA is the perfect alignment of the total knee prosthesis (TKP) components. Component misalignment can lead to the prosthesis loss by producing wear particles. The paper proposes a study on mechanical behaviors of a TKP based on numerical analysis, using ANSYS software. The numerical analysis is based on both the normal and the changed angle of the components alignment.

[Determination of five naphthaquinones in Arnebia euchroma by quantitative analysis multi-components with single-marker].

PubMed

Zhao, Wen-Wen; Wu, Zhi-Min; Wu, Xia; Zhao, Hai-Yu; Chen, Xiao-Qing

2016-10-01

This study is to determine five naphthaquinones (acetylshikonin, β-acetoxyisovalerylalkannin, isobutylshikonin, β,β'-dimethylacrylalkannin,α-methyl-n-butylshikonin） by quantitative analysis of multi-components with a single marker (QAMS). β,β'-Dimethylacrylalkannin was selected as the internal reference substance, and the relative correlation factors (RCFs) of acetylshikonin, β-acetoxyisovalerylalkannin, isobutylshikonin and α-methyl-n-butylshikonin were calculated. Then the ruggedness of relative correction factors was tested on different instruments and columns. Meanwhile, 16 batches of Arnebia euchroma were analyzed by external standard method (ESM) and QAMS, respectively. The peaks were identifited by LC-MS. The ruggedness of relative correction factors was good. And the analytical results calculated by ESM and QAMS showed no difference. The quantitative method established was feasible and suitable for the quality evaluation of A. euchroma. Copyright© by the Chinese Pharmaceutical Association.

Dimensions of professional labor support for intrapartum practice.

PubMed

Sauls, Donna J

2006-01-01

To define and describe the dimensions of Professional Labor Support (PLS). A factor-analytic study was conducted with a random sample of 146 intrapartum nurses in Texas. Nurses' responses to the Labor Support Questionnaire (LSQ) were subjected to principal components analysis and descriptive analysis. A six-factor solution indicated the dimensions of PLS: Tangible Support, Advocacy, Emotional Support-Reassurance, Emotional Support-Creating Control, Security and Comfort, Emotional Support-Nurse Caring Behavior, and Informational Support. Although the presence of four dimensions was theorized, six dimensions were found. The emotional support dimension was identified by nurses as being an important component of labor support as indicated by the identification of three separate emotional support dimensions.

A symmetrical subtraction combined with interpolated values for eliminating scattering from fluorescence EEM data.

PubMed

Xu, Jing; Liu, Xiaofei; Wang, Yutian

2016-08-05

Parallel factor analysis is a widely used method to extract qualitative and quantitative information of the analyte of interest from fluorescence emission-excitation matrix containing unknown components. Big amplitude of scattering will influence the results of parallel factor analysis. Many methods of eliminating scattering have been proposed. Each of these methods has its advantages and disadvantages. The combination of symmetrical subtraction and interpolated values has been discussed. The combination refers to both the combination of results and the combination of methods. Nine methods were used for comparison. The results show the combination of results can make a better concentration prediction for all the components. Copyright © 2016 Elsevier B.V. All rights reserved.

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

ERIC Educational Resources Information Center

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

2008-01-01

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

The Three Domains of Disgust Scale: Factor Structure, Psychometric Properties, and Conceptual Limitations

ERIC Educational Resources Information Center

Olatunji, Bunmi O.; Adams, Thomas; Ciesielski, Bethany; David, Bieke; Sarawgi, Shivali; Broman-Fulks, Joshua

2012-01-01

This investigation examined the measurement properties of the Three Domains of Disgust Scale (TDDS). Principal components analysis in Study 1 (n = 206) revealed three factors of Pathogen, Sexual, and Moral Disgust that demonstrated excellent reliability, including test-retest over 12 weeks. Confirmatory factor analyses in Study 2 (n = 406)…

Factors Related to the Recruitment and Retention of Professionals from Specialized Disciplines.

ERIC Educational Resources Information Center

Harrington, Deborah; And Others

A survey was developed to identify critical factors in job selection and retention for speech/language pathologists, physical therapists, and occupational therapists. The survey was completed by 455 New Mexico professionals in these disciplines. A principal-components analysis identified six factors that were important in career decisions: (1)…

Use of multivariate analysis for determining sources of solutes found in wet atmospheric deposition in the United States

USGS Publications Warehouse

Hooper, R.P.; Peters, N.E.

1989-01-01

A principal-components analysis was performed on the major solutes in wet deposition collected from 194 stations in the United States and its territories. Approximately 90% of the components derived could be interpreted as falling into one of three categories - acid, salt, or an agricultural/soil association. The total mass, or the mass of any one solute, was apportioned among these components by multiple linear regression techniques. The use of multisolute components for determining trends or spatial distribution represents a substantial improvement over single-solute analysis in that these components are more directly related to the sources of the deposition. The geographic patterns displayed by the components in this analysis indicate a far more important role for acid deposition in the Southeast and intermountain regions of the United States than would be indicated by maps of sulfate or nitrate deposition alone. In the Northeast and Midwest, the acid component is not declining at most stations, as would be expected from trends in sulfate deposition, but is holding constant or increasing. This is due, in part, to a decline in the agriculture/soil factor throughout this region, which would help to neutralize the acidity.

Climate drivers on malaria transmission in Arunachal Pradesh, India.

PubMed

Upadhyayula, Suryanaryana Murty; Mutheneni, Srinivasa Rao; Chenna, Sumana; Parasaram, Vaideesh; Kadiri, Madhusudhan Rao

2015-01-01

The present study was conducted during the years 2006 to 2012 and provides information on prevalence of malaria and its regulation with effect to various climatic factors in East Siang district of Arunachal Pradesh, India. Correlation analysis, Principal Component Analysis and Hotelling's T² statistics models are adopted to understand the effect of weather variables on malaria transmission. The epidemiological study shows that the prevalence of malaria is mostly caused by the parasite Plasmodium vivax followed by Plasmodium falciparum. It is noted that, the intensity of malaria cases declined gradually from the year 2006 to 2012. The transmission of malaria observed was more during the rainy season, as compared to summer and winter seasons. Further, the data analysis study with Principal Component Analysis and Hotelling's T² statistic has revealed that the climatic variables such as temperature and rainfall are the most influencing factors for the high rate of malaria transmission in East Siang district of Arunachal Pradesh.

Work-related musculoskeletal disorders (WMDs) risk assessment at core assembly production of electronic components manufacturing company

NASA Astrophysics Data System (ADS)

Yahya, N. M.; Zahid, M. N. O.

2018-03-01

This study conducted to assess the work-related musculoskeletal disorders (WMDs) among the workers at core assembly production in an electronic components manufacturing company located in Pekan, Pahang, Malaysia. The study is to identify the WMDs risk factor and risk level. A set of questionnaires survey based on modified Nordic Musculoskeletal Disorder Questionnaires have been distributed to respective workers to acquire the WMDs risk factor identification. Then, postural analysis was conducted in order to measure the respective WMDs risk level. The analysis were based on two ergonomics assessment tools; Rapid Upper Limb Assessment (RULA) and Rapid Entire Body Assessment (REBA). The study found that 30 respondents out of 36 respondents suffered from WMDs especially at shoulder, wrists and lower back. The WMDs risk have been identified from unloading process, pressing process and winding process. In term of the WMDs risk level, REBA and RULA assessment tools have indicated high risk level to unloading and pressing process. Thus, this study had established the WMDs risk factor and risk level of core assembly production in an electronic components manufacturing company at Malaysia environment.

Analysis of metabolic syndrome components in >15 000 african americans identifies pleiotropic variants: results from the population architecture using genomics and epidemiology study.

PubMed

Carty, Cara L; Bhattacharjee, Samsiddhi; Haessler, Jeff; Cheng, Iona; Hindorff, Lucia A; Aroda, Vanita; Carlson, Christopher S; Hsu, Chun-Nan; Wilkens, Lynne; Liu, Simin; Selvin, Elizabeth; Jackson, Rebecca; North, Kari E; Peters, Ulrike; Pankow, James S; Chatterjee, Nilanjan; Kooperberg, Charles

2014-08-01

Metabolic syndrome (MetS) refers to the clustering of cardiometabolic risk factors, including dyslipidemia, central adiposity, hypertension, and hyperglycemia, in individuals. Identification of pleiotropic genetic factors associated with MetS traits may shed light on key pathways or mediators underlying MetS. Using the Metabochip array in 15 148 African Americans from the Population Architecture using Genomics and Epidemiology (PAGE) study, we identify susceptibility loci and investigate pleiotropy among genetic variants using a subset-based meta-analysis method, ASsociation-analysis-based-on-subSETs (ASSET). Unlike conventional models that lack power when associations for MetS components are null or have opposite effects, Association-analysis-based-on-subsets uses 1-sided tests to detect positive and negative associations for components separately and combines tests accounting for correlations among components. With Association-analysis-based-on-subsets, we identify 27 single nucleotide polymorphisms in 1 glucose and 4 lipids loci (TCF7L2, LPL, APOA5, CETP, and APOC1/APOE/TOMM40) significantly associated with MetS components overall, all P<2.5e-7, the Bonferroni adjusted P value. Three loci replicate in a Hispanic population, n=5172. A novel African American-specific variant, rs12721054/APOC1, and rs10096633/LPL are associated with ≥3 MetS components. We find additional evidence of pleiotropy for APOE, TOMM40, TCF7L2, and CETP variants, many with opposing effects (eg, the same rs7901695/TCF7L2 allele is associated with increased odds of high glucose and decreased odds of central adiposity). We highlight a method to increase power in large-scale genomic association analyses and report a novel variant associated with all MetS components in African Americans. We also identify pleiotropic associations that may be clinically useful in patient risk profiling and for informing translational research of potential gene targets and medications. © 2014 American Heart Association, Inc.

Quality assurance of the clinical learning environment in Austria: Construct validity of the Clinical Learning Environment, Supervision and Nurse Teacher Scale (CLES+T scale).

PubMed

Mueller, Gerhard; Mylonas, Demetrius; Schumacher, Petra

2018-07-01

Within nursing education, the clinical learning environment is of a high importance in regards to the development of competencies and abilities. The organization, atmosphere, and supervision in the clinical learning environment are only a few factors that influence this development. In Austria there is currently no valid instrument available for the evaluation of influencing factors. The aim of the study was to test the construct validity with principal component analysis as well as the internal consistency of the German Clinical Learning Environment, Supervision and Teacher Scale (CLES+T scale) in Austria. The present validation study has a descriptive-quantitative cross-sectional design. The sample consisted of 385 nursing students from thirteen training institutions in Austria. The data collection was carried out online between March and April 2016. Starting with a polychoric correlation matrix, a parallel analysis with principal component extraction and promax rotation was carried out due to the ordinal data. The exploratory ordinal factor analysis supported a four-component solution and explained 73% of the total variance. The internal consistency of all 25 items reached a Cronbach's α of 0.95 and the four components ranged between 0.83 and 0.95. The German version of the CLES+T scale seems to be a useful instrument for identifying potential areas of improvement in clinical practice in order to derive specific quality measures for the practical learning environment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Polytopic vector analysis in igneous petrology: Application to lunar petrogenesis

NASA Technical Reports Server (NTRS)

Shervais, John W.; Ehrlich, R.

1993-01-01

Lunar samples represent a heterogeneous assemblage of rocks with complex inter-relationships that are difficult to decipher using standard petrogenetic approaches. These inter-relationships reflect several distinct petrogenetic trends as well as thermomechanical mixing of distinct components. Additional complications arise from the unequal quality of chemical analyses and from the fact that many samples (e.g., breccia clasts) are too small to be representative of the system from which they derived. Polytopic vector analysis (PVA) is a multi-variate procedure used as a tool for exploratory data analysis. PVA allows the analyst to classify samples and clarifies relationships among heterogenous samples with complex petrogenetic histories. It differs from orthogonal factor analysis in that it uses non-orthogonal multivariate sample vectors to extract sample endmember compositions. The output from a Q-mode (sample based) factor analysis is the initial step in PVA. The Q-mode analysis, using criteria established by Miesch and Klovan and Miesch, is used to determine the number of endmembers in the data system. The second step involves determination of endmembers and mixing proportions with all output expressed in the same geochemical variable as the input. The composition of endmembers is derived by analysis of the variability of the data set. Endmembers need not be present in the data set, nor is it necessary for their composition to be known a priori. A set of any endmembers defines a 'polytope' or classification figure (triangle for a three component system, tetrahedron for a four component system, a 'five-tope' in four dimensions for five component system, et cetera).

The Specific Level of Functioning Scale: construct validity, internal consistency and factor structure in a large Italian sample of people with schizophrenia living in the community.

PubMed

Mucci, Armida; Rucci, Paola; Rocca, Paola; Bucci, Paola; Gibertoni, Dino; Merlotti, Eleonora; Galderisi, Silvana; Maj, Mario

2014-10-01

The study aimed to assess the construct validity, internal consistency and factor structure of the Specific Levels of Functioning Scale (SLOF), a multidimensional instrument assessing real life functioning. The study was carried out in 895 Italian people with schizophrenia, all living in the community and attending the outpatient units of 26 university psychiatric clinics and/or community mental health departments. The construct validity of the SLOF was analyzed by means of the multitrait-multimethod approach, using the Personal and Social Performance (PSP) Scale as the gold standard. The factor structure of the SLOF was examined using both an exploratory principal component analysis and a confirmatory factor analysis. The six factors identified using exploratory principal component analysis explained 57.1% of the item variance. The examination of the multitrait-multimethod matrix revealed that the SLOF factors had high correlations with PSP factors measuring the same constructs and low correlations with PSP factors measuring different constructs. The confirmatory factor analysis (CFA) corroborated the 6-factor structure reported in the original validation study. Loadings were all significant and ranged from a minimum of 0.299 to a maximum of 0.803. The CFA model was adequately powered and had satisfactory goodness of fit indices (comparative fit index=0.927, Tucker-Lewis index=0.920 and root mean square error of approximation=0.047, 95% CI 0.045-0.049). The present study confirms, in a large sample of Italian people with schizophrenia living in the community, that the SLOF is a reliable and valid instrument for the assessment of social functioning. It has good construct validity and internal consistency, and a well-defined factor structure. Copyright © 2014 Elsevier B.V. All rights reserved.

Wind Tunnel Strain-Gage Balance Calibration Data Analysis Using a Weighted Least Squares Approach

NASA Technical Reports Server (NTRS)

Ulbrich, N.; Volden, T.

2017-01-01

A new approach is presented that uses a weighted least squares fit to analyze wind tunnel strain-gage balance calibration data. The weighted least squares fit is specifically designed to increase the influence of single-component loadings during the regression analysis. The weighted least squares fit also reduces the impact of calibration load schedule asymmetries on the predicted primary sensitivities of the balance gages. A weighting factor between zero and one is assigned to each calibration data point that depends on a simple count of its intentionally loaded load components or gages. The greater the number of a data point's intentionally loaded load components or gages is, the smaller its weighting factor becomes. The proposed approach is applicable to both the Iterative and Non-Iterative Methods that are used for the analysis of strain-gage balance calibration data in the aerospace testing community. The Iterative Method uses a reasonable estimate of the tare corrected load set as input for the determination of the weighting factors. The Non-Iterative Method, on the other hand, uses gage output differences relative to the natural zeros as input for the determination of the weighting factors. Machine calibration data of a six-component force balance is used to illustrate benefits of the proposed weighted least squares fit. In addition, a detailed derivation of the PRESS residuals associated with a weighted least squares fit is given in the appendices of the paper as this information could not be found in the literature. These PRESS residuals may be needed to evaluate the predictive capabilities of the final regression models that result from a weighted least squares fit of the balance calibration data.

Phases of female sexual response cycle among Malaysian women with infertility: a factor analysis study.

PubMed

Seen Heng, Yeoh; Sidi, Hatta; Nik Jaafar, Nik Ruzyanei; Razali, Rosdinom; Ram, Hari

2013-04-01

This cross-sectional study aimed to determine the construct of the phases of the female sexual response cycle (SRC) among women attending an infertility clinic in a Malaysian tertiary center. The sexual response phases were measured with a validated Malay version of the Female Sexual Function Index (FSFI). The correlation structure of the items of the SRC phases (i.e. desire, arousal, orgasm, satisfaction and pain) was determined using principal component analysis (PCA), with varimax rotation method. The number of factors obtained was decided using Kaiser's criteria. A total of 150 married women with a mean age of 32 years participated in this study. Factor loadings using PCA with varimax rotation divided the sexual domains into three components. The first construct comprised sexual arousal, lubrication and pain (suggesting a mechanical component). The second construct were orgasm and sexual satisfaction (suggesting a physical achievement). Sexual desire, suggesting a psychological component, stood on its own as the third. The findings suggest that three constructs could be identified and in favor of the Basson model (a non-linear concept of SRC) for Malaysian women's sexual functioning. Understanding this would help clinicians to strategize the treatment approach of sexual dysfunction in women with infertility. Copyright © 2013 Wiley Publishing Asia Pty Ltd.

Success-Factors in Transition to University Mathematics

ERIC Educational Resources Information Center

Bengmark, S.; Thunberg, H.; Winberg, T. M.

2017-01-01

This study examines different factors' relative importance for students' performance in the transition to university mathematics. Students' characteristics (motivation, actions and beliefs) were measured when entering the university and at the end of the first year. Principal component analysis revealed four important constructs:…

Characterization of Aroma-Active Components and Antioxidant Activity Analysis of E-jiao (Colla Corii Asini) from Different Geographical Origins.

PubMed

Zhang, Shan; Xu, Lu; Liu, Yang-Xi; Fu, Hai-Yan; Xiao, Zuo-Bing; She, Yuan-Bin

2018-04-01

E-jiao (Colla Corii Asini, CCA) has been widely used as a healthy food and Chinese medicine. Although authentic CCA is characterized by its typical sweet and neutral fragrance, its aroma components have been rarely investigated. This work investigated the aroma-active components and antioxidant activity of 19 CCAs from different geographical origins. CCA extracts obtained by simultaneous distillation and extraction were analyzed by gas chromatography-mass spectrometry (GC-MS), gas chromatography-olfactometry (GC-O) and sensory analysis. The antioxidant activity of CCAs was determined by ABTS and DPPH assays. A total of 65 volatile compounds were identified and quantified by GC-MS and 23 aroma-active compounds were identified by GC-O and aroma extract dilution analysis. The most powerful aroma-active compounds were identified based on the flavor dilution factor and their contents were compared among the 19 CCAs. Principal component analysis of the 23 aroma-active components showed 3 significant clusters. Canonical correlation analysis between antioxidant assays and the 23 aroma-active compounds indicates strong correlation (r = 0.9776, p = 0.0281). Analysis of aroma-active components shows potential for quality evaluation and discrimination of CCAs from different geographical origins.

Principal component analysis of cardiovascular risk traits in three generations cohort among Indian Punjabi population.

PubMed

Badaruddoza; Kumar, Raman; Kaur, Manpreet

2015-09-01

The current study focused to determine significant cardiovascular risk factors through principal component factor analysis (PCFA) among three generations on 1827 individuals in three generations including 911 males (378 from offspring, 439 from parental and 94 from grand-parental generations) and 916 females (261 from offspring, 515 from parental and 140 from grandparental generations). The study performed PCFA with orthogonal rotation to reduce 12 inter-correlated variables into groups of independent factors. The factors have been identified as 2 for male grandparents, 3 for male offspring, female parents and female grandparents each, 4 for male parents and 5 for female offspring. This data reduction method identified these factors that explained 72%, 84%, 79%, 69%, 70% and 73% for male and female offspring, male and female parents and male and female grandparents respectively, of the variations in original quantitative traits. The factor 1 accounting for the largest portion of variations was strongly loaded with factors related to obesity (body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR), and thickness of skinfolds) among all generations with both sexes, which has been known to be an independent predictor for cardiovascular morbidity and mortality. The second largest components, factor 2 and factor 3 for almost all generations reflected traits of blood pressure phenotypes loaded, however, in male offspring generation it was observed that factor 2 was loaded with blood pressure phenotypes as well as obesity. This study not only confirmed but also extended prior work by developing a cumulative risk scale from factor scores. Till today, such a cumulative and extensive scale has not been used in any Indian studies with individuals of three generations. These findings and study highlight the importance of global approach for assessing the risk and need for studies that elucidate how these different cardiovascular risk factors interact with each other over the time to create clinical disease. The findings also added depth to the negligible amount of literature of factor analysis of cardiovascular risk in any Indian ethnic population.

Factors affecting the views and attitudes of Scottish pharmacists to continuing professional development.

PubMed

Power, Ailsa; Grammatiki, Aikaterini; Bates, Ian; Mc Kellar, Susan; Johnson, B Julienne; Diack, H Lesley; Stewart, Derek; Hudson, Steve A

2011-12-01

To explore factors associated with Scottish pharmacists' views and attitudes to continuing professional development (CPD). A retrospective principal component analysis of 552 (22.8%) questionnaires returned from a sample of 2420 Scottish pharmacists randomly selected from the 4300 pharmacists registered with the Royal Pharmaceutical Society of Great Britain and with a Scottish address. Principal component analysis of questionnaire items (n = 19) revealed four factors associated with Scottish pharmacists' views and attitudes to CPD: having positive support in the workplace, having access to resources and meeting learning needs, having confidence in the CPD process and motivation to participate in the CPD process. Community pharmacists were identified as the subgroup of pharmacists that needed most support for CPD regarding all four factors, while pharmacists working in primary care felt that they had most support in the workplace in comparison to other sectors (P < 0.05) and better access to resources and meeting learning needs when compared to community (P < 0.001) and hospital (P = 0.008) colleagues. Pharmacists working in primary care also felt more motivated to participate in the CPD process than those in the community (P < 0.001), and hospital pharmacists reported having more confidence in the CPD process compared to community pharmacists (P < 0.05). Using principal component analysis has identified four factors associated with Scottish pharmacists' views and attitudes to CPD. This may provide an approach to facilitate comparison of CPD views and attitudes with intra and inter professional groupings. Further study may allow identification of good practice and solutions to common CPD issues. © 2011 The Authors. IJPP © 2011 Royal Pharmaceutical Society.

Research on Air Quality Evaluation based on Principal Component Analysis

NASA Astrophysics Data System (ADS)

Wang, Xing; Wang, Zilin; Guo, Min; Chen, Wei; Zhang, Huan

2018-01-01

Economic growth has led to environmental capacity decline and the deterioration of air quality. Air quality evaluation as a fundamental of environmental monitoring and air pollution control has become increasingly important. Based on the principal component analysis (PCA), this paper evaluates the air quality of a large city in Beijing-Tianjin-Hebei Area in recent 10 years and identifies influencing factors, in order to provide reference to air quality management and air pollution control.

HFE (Human Factors Engineering) Technology for Navy Weapon System Acquisition.

DTIC Science & Technology

1979-07-01

requirements 2-31 to electrical components using: Failure Modes and Effects Analysis ( FMEA ) and LOR data, component design requirements and a selected...3- 60 * ,.- .- I; L , , _ m m _ --- : " I. I ._ . - I- The use of SAINT can specify various outputs of the simulation, histograms, plots, summary...Electro Safety . 60 .98 .95 .65 .92 .70 .42 .62 Personnel Relationships .74 .70 .79 .63 .40 .77 .85 .80 Electro Circuit Analysis .63 .90 .95 .58 .40

Resolving and quantifying overlapped chromatographic bands by transmutation

PubMed

Malinowski

2000-09-15

A new chemometric technique called "transmutation" is developed for the purpose of sharpening overlapped chromatographic bands in order to quantify the components. The "transmutation function" is created from the chromatogram of the pure component of interest, obtained from the same instrument, operating under the same experimental conditions used to record the unresolved chromatogram of the sample mixture. The method is used to quantify mixtures containing toluene, ethylbenzene, m-xylene, naphthalene, and biphenyl from unresolved chromatograms previously reported. The results are compared to those obtained using window factor analysis, rank annihilation factor analysis, and matrix regression analysis. Unlike the latter methods, the transmutation method is not restricted to two-dimensional arrays of data, such as those obtained from HPLC/DAD, but is also applicable to chromatograms obtained from single detector experiments. Limitations of the method are discussed.

Principal variance component analysis of crop composition data: a case study on herbicide-tolerant cotton.

PubMed

Harrison, Jay M; Howard, Delia; Malven, Marianne; Halls, Steven C; Culler, Angela H; Harrigan, George G; Wolfinger, Russell D

2013-07-03

Compositional studies on genetically modified (GM) and non-GM crops have consistently demonstrated that their respective levels of key nutrients and antinutrients are remarkably similar and that other factors such as germplasm and environment contribute more to compositional variability than transgenic breeding. We propose that graphical and statistical approaches that can provide meaningful evaluations of the relative impact of different factors to compositional variability may offer advantages over traditional frequentist testing. A case study on the novel application of principal variance component analysis (PVCA) in a compositional assessment of herbicide-tolerant GM cotton is presented. Results of the traditional analysis of variance approach confirmed the compositional equivalence of the GM and non-GM cotton. The multivariate approach of PVCA provided further information on the impact of location and germplasm on compositional variability relative to GM.

Psychometric properties of the Spanish version of the Cocaine Selective Severity Assessment to evaluate cocaine withdrawal in treatment-seeking individuals.

PubMed

Pérez de los Cobos, José; Trujols, Joan; Siñol, Núria; Vasconcelos e Rego, Lisiane; Iraurgi, Ioseba; Batlle, Francesca

2014-09-01

Reliable and valid assessment of cocaine withdrawal is relevant for treating cocaine-dependent patients. This study examined the psychometric properties of the Spanish version of the Cocaine Selective Severity Assessment (CSSA), an instrument that measures cocaine withdrawal. Participants were 170 cocaine-dependent inpatients receiving detoxification treatment. Principal component analysis revealed a 4-factor structure for CSSA that included the following components: 'Cocaine Craving and Psychological Distress', 'Lethargy', 'Carbohydrate Craving and Irritability', and 'Somatic Depressive Symptoms'. These 4 components accounted for 56.0% of total variance. Internal reliability for these components ranged from unacceptable to good (Chronbach's alpha: 0.87, 0.65, 0.55, and 0.22, respectively). All components except Somatic Depressive Symptoms presented concurrent validity with cocaine use. In summary, while some properties of the Spanish version of the CSSA are satisfactory, such as interpretability of factor structure and test-retest reliability, other properties, such as internal reliability and concurrent validity of some factors, are inadequate. Copyright © 2014 Elsevier Inc. All rights reserved.

Components of Spatial Thinking: Evidence from a Spatial Thinking Ability Test

ERIC Educational Resources Information Center

Lee, Jongwon; Bednarz, Robert

2012-01-01

This article introduces the development and validation of the spatial thinking ability test (STAT). The STAT consists of sixteen multiple-choice questions of eight types. The STAT was validated by administering it to a sample of 532 junior high, high school, and university students. Factor analysis using principal components extraction was applied…

Investigating Predictors of Listening Comprehension in Third-, Seventh-, and Tenth-Grade Students: A Dominance Analysis Approach

ERIC Educational Resources Information Center

Tighe, Elizabeth L.; Spencer, Mercedes; Schatschneider, Christopher

2015-01-01

This study rank ordered the contributive importance of several predictors of listening comprehension for third, seventh, and tenth graders. Principal components analyses revealed that a three-factor solution with fluency, reasoning, and working memory components provided the best fit across grade levels. Dominance analyses indicated that fluency…

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

PubMed

Luce, Robert; Hildebrandt, Peter; Kuhlmann, Uwe; Liesen, Jörg

2016-09-01

The key challenge of time-resolved Raman spectroscopy is the identification of the constituent species and the analysis of the kinetics of the underlying reaction network. In this work we present an integral approach that allows for determining both the component spectra and the rate constants simultaneously from a series of vibrational spectra. It is based on an algorithm for nonnegative matrix factorization that is applied to the experimental data set following a few pre-processing steps. As a prerequisite for physically unambiguous solutions, each component spectrum must include one vibrational band that does not significantly interfere with the vibrational bands of other species. The approach is applied to synthetic "experimental" spectra derived from model systems comprising a set of species with component spectra differing with respect to their degree of spectral interferences and signal-to-noise ratios. In each case, the species involved are connected via monomolecular reaction pathways. The potential and limitations of the approach for recovering the respective rate constants and component spectra are discussed. © The Author(s) 2016.

Structural factors of jointed plain concrete pavements : SPS-2--initial evaluation and analysis

DOT National Transportation Integrated Search

2005-04-01

The SPS-2 experiment, "Strategic Study of Structural Factors for Jointed Plain Concrete Pavements (JPCP)," is one of the key components of the Long Term Pavement Performance (LTPP) program. The main objective of this experiment is to determine the re...

The Development and Validation of the Online Shopping Addiction Scale.

PubMed

Zhao, Haiyan; Tian, Wei; Xin, Tao

2017-01-01

We report the development and validation of a scale to measure online shopping addiction. Inspired by previous theories and research on behavioral addiction, the Griffiths's widely accepted six-factor component model was referred to and an 18-item scale was constructed, with each component measured by three items. The results of exploratory factor analysis, based on Sample 1 (999 college students) and confirmatory factor analysis, based on Sample 2 (854 college students) showed the Griffiths's substantive six-factor structure underlay the online shopping addiction scale. Cronbach's alpha suggested that the resulting scale was highly reliable. Concurrent validity, based on Sample 3 (328 college students), was also satisfactory as indicated by correlations between the scale and measures of similar constructs. Finally, self-perceived online shopping addiction can be predicted to a relatively high degree. The present 18-item scale is a solid theory-based instrument to empirically measure online shopping addiction and can be used for understanding the phenomena among young adults.

The Development and Validation of the Online Shopping Addiction Scale

PubMed Central

Zhao, Haiyan; Tian, Wei; Xin, Tao

2017-01-01

We report the development and validation of a scale to measure online shopping addiction. Inspired by previous theories and research on behavioral addiction, the Griffiths's widely accepted six-factor component model was referred to and an 18-item scale was constructed, with each component measured by three items. The results of exploratory factor analysis, based on Sample 1 (999 college students) and confirmatory factor analysis, based on Sample 2 (854 college students) showed the Griffiths's substantive six-factor structure underlay the online shopping addiction scale. Cronbach's alpha suggested that the resulting scale was highly reliable. Concurrent validity, based on Sample 3 (328 college students), was also satisfactory as indicated by correlations between the scale and measures of similar constructs. Finally, self-perceived online shopping addiction can be predicted to a relatively high degree. The present 18-item scale is a solid theory-based instrument to empirically measure online shopping addiction and can be used for understanding the phenomena among young adults. PMID:28559864

Survivorship analysis of failure pattern after revision total hip arthroplasty.

PubMed

Retpen, J B; Varmarken, J E; Jensen, J S

1989-12-01

Failure, defined as established indication for or performed re-revision of one or both components, was analyzed using survivorship methods in 306 revision total hip arthroplasties. The longevity of revision total hip arthroplasties was inferior to that of previously reported primary total hip arthroplasties. The overall survival curve was two-phased, with a late failure period associated with aseptic loosening of one or both components and an early failure period associated with causes of failure other than loosening. Separate survival curves for aseptic loosening of femoral and acetabular components showed late and almost simultaneous decline, but with a tendency toward a higher rate of failure for the femoral component. No differences in survival could be found between the Stanmore, Lubinus standard, and Lubinus long-stemmed femoral components. A short interval between the index operation and the revision and intraoperative and postoperative complications were risk factors for early failure. Young age was a risk factor for aseptic loosening of the femoral component. Intraoperative fracture of the femoral shaft was not a risk factor for secondary loosening. No difference in survival was found between primary cemented total arthroplasty and primary noncemented hemiarthroplasty.

Factor Structure and Psychometric Properties of the Injection Phobia Scale-Anxiety

ERIC Educational Resources Information Center

Olatunji, Bunmi O.; Sawchuk, Craig N.; Moretz, Melanie W.; David, Bieke; Armstrong, Thomas; Ciesielski, Bethany G.

2010-01-01

The present investigation examined the factor structure and psychometric properties of the Injection Phobia Scale-Anxiety (IPS-Anx). Principal components analysis of IPS-Anx items in Study 1 (n = 498) revealed a 2-factor structure consisting of Distal Fear and Contact Fear. However, CFA results in Study 2 (n = 567) suggest that a 1-factor…

Using host-pathogen protein interactions to identify and characterize Francisella tularensis virulence factors.

PubMed

Wallqvist, Anders; Memišević, Vesna; Zavaljevski, Nela; Pieper, Rembert; Rajagopala, Seesandra V; Kwon, Keehwan; Yu, Chenggang; Hoover, Timothy A; Reifman, Jaques

2015-12-29

Francisella tularensis is a select bio-threat agent and one of the most virulent intracellular pathogens known, requiring just a few organisms to establish an infection. Although several virulence factors are known, we lack an understanding of virulence factors that act through host-pathogen protein interactions to promote infection. To address these issues in the highly infectious F. tularensis subsp. tularensis Schu S4 strain, we deployed a combined in silico, in vitro, and in vivo analysis to identify virulence factors and their interactions with host proteins to characterize bacterial infection mechanisms. We initially used comparative genomics and literature to identify and select a set of 49 putative and known virulence factors for analysis. Each protein was then subjected to proteome-scale yeast two-hybrid (Y2H) screens with human and murine cDNA libraries to identify potential host-pathogen protein-protein interactions. Based on the bacterial protein interaction profile with both hosts, we selected seven novel putative virulence factors for mutant construction and animal validation experiments. We were able to create five transposon insertion mutants and used them in an intranasal BALB/c mouse challenge model to establish 50 % lethal dose estimates. Three of these, ΔFTT0482c, ΔFTT1538c, and ΔFTT1597, showed attenuation in lethality and can thus be considered novel F. tularensis virulence factors. The analysis of the accompanying Y2H data identified intracellular protein trafficking between the early endosome to the late endosome as an important component in virulence attenuation for these virulence factors. Furthermore, we also used the Y2H data to investigate host protein binding of two known virulence factors, showing that direct protein binding was a component in the modulation of the inflammatory response via activation of mitogen-activated protein kinases and in the oxidative stress response. Direct interactions with specific host proteins and the ability to influence interactions among host proteins are important components for F. tularensis to avoid host-cell defense mechanisms and successfully establish an infection. Although direct host-pathogen protein-protein binding is only one aspect of Francisella virulence, it is a critical component in directly manipulating and interfering with cellular processes in the host cell.

Development and Factor Analysis of the Protective Factors Index: A Report Card Section Related to the Work of School Counselors

ERIC Educational Resources Information Center

Bass, Gwen; Lee, Ji Hee; Wells, Craig; Carey, John C.; Lee, Sangmin

2015-01-01

The scale development and exploratory and confirmatory factor analyses of the Protective Factor Index (PFI) is described. The PFI is a 13-item component of elementary students' report cards that replaces typical items associated with student behavior. The PFI is based on the Construct-Based Approach (CBA) to school counseling, which proposes that…

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

PubMed

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

2012-10-01

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

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

NASA Technical Reports Server (NTRS)

1991-01-01

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

Seasonal characterization of CDOM for lakes in semiarid regions of Northeast China using excitation-emission matrix fluorescence and parallel factor analysis (EEM-PARAFAC)

NASA Astrophysics Data System (ADS)

Zhao, Ying; Song, Kaishan; Wen, Zhidan; Li, Lin; Zang, Shuying; Shao, Tiantian; Li, Sijia; Du, Jia

2016-03-01

The seasonal characteristics of fluorescent components in chromophoric dissolved organic matter (CDOM) for lakes in the semiarid region of Northeast China were examined by excitation-emission matrix (EEM) spectra and parallel factor analysis (PARAFAC). Two humic-like (C1 and C2) and protein-like (C3 and C4) components were identified using PARAFAC. The average fluorescence intensity of the four components differed under seasonal variation from June and August 2013 to February and April 2014. Components 1 and 2 exhibited a strong linear correlation (R2 = 0.628). Significantly positive linear relationships between CDOM absorption coefficients a(254) (R2 = 0.72, 0.46, p < 0.01), a(280) (R2 = 0.77, 0.47, p < 0.01), a(350) (R2 = 0.76, 0.78, p < 0.01) and Fmax for two humic-like components (C1 and C2) were exhibited, respectively. A significant relationship (R2 = 0.930) was found between salinity and dissolved organic carbon (DOC). However, almost no obvious correlation was found between salinity and EEM-PARAFAC-extracted components except for C3 (R2 = 0.469). Results from this investigation demonstrate that the EEM-PARAFAC technique can be used to evaluate the seasonal dynamics of CDOM fluorescent components for inland waters in the semiarid regions of Northeast China, and to quantify CDOM components for other waters with similar environmental conditions.

Multivariate analysis of selected metals in tannery effluents and related soil.

PubMed

Tariq, Saadia R; Shah, Munir H; Shaheen, N; Khalique, A; Manzoor, S; Jaffar, M

2005-06-30

Effluent and relevant soil samples from 38 tanning units housed in Kasur, Pakistan, were obtained for metal analysis by flame atomic absorption spectrophotometric method. The levels of 12 metals, Na, Ca, K, Mg, Fe, Mn, Cr, Co, Cd, Ni, Pb and Zn were determined in the two media. The data were evaluated towards metal distribution and metal-to-metal correlations. The study evidenced enhanced levels of Cr (391, 16.7 mg/L) and Na (25,519, 9369 mg/L) in tannery effluents and relevant soil samples, respectively. The effluent versus soil trace metal content relationship confirmed that the effluent Cr was strongly correlated with soil Cr. For metal source identification the techniques of principal component analysis, and cluster analysis were applied. The principal component analysis yielded two factors for effluents: factor 1 (49.6% variance) showed significant loading for Ca, Fe, Mn, Cr, Cd, Ni, Pb and Zn, referring to a tanning related source for these metals, and factor 2 (12.6% variance) with higher loadings of Na, K, Mg and Co, was associated with the processes during the skin/hide treatment. Similarly, two factors with a cumulative variance of 34.8% were obtained for soil samples: factor 1 manifested the contribution from Mg, Mn, Co, Cd, Ni and Pb, which though soil-based is basically effluent-derived, while factor 2 was found associated with Na, K, Ca, Cr and Zn which referred to a tannery-based source. The dendograms obtained from cluster analysis, also support the observed results. The study exhibits a gross pollution of soils with Cr at levels far exceeding the stipulated safe limit laid down for tannery effluents.

SPSS and SAS programs for determining the number of components using parallel analysis and velicer's MAP test.

PubMed

O'Connor, B P

2000-08-01

Popular statistical software packages do not have the proper procedures for determining the number of components in factor and principal components analyses. Parallel analysis and Velicer's minimum average partial (MAP) test are validated procedures, recommended widely by statisticians. However, many researchers continue to use alternative, simpler, but flawed procedures, such as the eigenvalues-greater-than-one rule. Use of the proper procedures might be increased if these procedures could be conducted within familiar software environments. This paper describes brief and efficient programs for using SPSS and SAS to conduct parallel analyses and the MAP test.

Relationships between Social Cognition and Sibling Constellations.

ERIC Educational Resources Information Center

Goebel, Barbara L.

1985-01-01

First and second born college students (N=178) responded to measures of four social cognition factors. Multivariate analysis of variance identified relationships of social cognition factors with five sibling constellation components: subject's sex, subject's birth order (first or second), adjacent first or second born sibling's sex, spacing…

Factor Structure of Psychoeducational and Neuropsychological Measures of Learning-Disabled Children.

ERIC Educational Resources Information Center

Chittooran, Mary Mathai; And Others

1993-01-01

Administered Wechsler Intelligence Scale for Children-Revised, Halstead-Reitan Neuropsychological Battery, Peabody Picture Vocabulary Test, and Wide Range Achievement Test to 934 learning-disabled students between ages 8 and 16. Principal-components analysis with varimax rotation indicated existence of seven factors: Verbal Reasoning, Academic…

Characterization of DOM adsorption of CNTs by using excitation-emission matrix fluorescence spectroscopy and multiway analysis.

PubMed

Peng, Mingguo; Li, Huajie; Li, Dongdong; Du, Erdeng; Li, Zhihong

2017-06-01

Carbon nanotubes (CNTs) were utilized to adsorb DOM in micro-polluted water. The characteristics of DOM adsorption on CNTs were investigated based on UV 254 , TOC, and fluorescence spectrum measurements. Based on PARAFAC (parallel factor) analysis, four fluorescent components were extracted, including one protein-like component (C4) and three humic acid-like components (C1, C2, and C3). The adsorption isotherms, kinetics, and thermodynamics of DOM adsorption on CNTs were further investigated. A Freundlich isotherm model fit the adsorption data well with high values of correlation. As a type of macro-porous and meso-porous adsorbent, CNTs preferably adsorb humic acid-like substances rather than protein-like substances. The increasing temperature will speed up the adsorption process. The self-organizing map (SOM) analysis further explains the fluorescent properties of water samples. The results provide a new insight into the adsorption behaviour of DOM fluorescent components on CNTs.

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

Kravtsov, A.I.

To determine the effect of geologic factors on the composition of abyssal derivates (complementing existing information on the geochemistry of volcanic gases) isotopic analysis of carbon was used to obtain physicochemical criteria of the origin of gases, independent of geologic-petrographic data. The investigations include component analysis of all the gases, particularly hydrocarbon compounds, repeatedly found in the fumarole emanations of pyroclastic streams. Volcanic carbon dioxide which is the principal component of gases of active volcanoes and hot springs in the Kuril-Kamchatka volcanic arc and of other volcanoes was investigated.

Characterization of selected volatile organic compounds, polycyclic aromatic hydrocarbons and carbonyl compounds at a roadside monitoring station

NASA Astrophysics Data System (ADS)

Ho, K. F.; Lee, S. C.; Chiu, Gloria M. Y.

Volatile organic compounds (VOCs), PAHs and carbonyl compounds are the major toxic components in Hong Kong. Emissions from motor vehicles have been one of the primary pollution sources in the metropolitan areas throughout Hong Kong for a long time. A 1-yr monitoring program for VOCs, PAHs and carbonyl compounds had been performed at a roadside urban station at Hong Kong Polytechnic University in order to determine the variations and correlations of each selected species (VOCs, PAHs and carbonyl compounds). This study is aimed to analyze toxic volatile organic compounds (benzene, toluene, ethylbenzene and xylene), two carbonyl compounds (formaldehyde, acetaldehyde), and selective polycyclic aromatic hydrocarbons. The monitoring program started from 16 April 1999 to 30 March 2000. Ambient VOC concentrations, many of which originate from the same sources as particulate PAHs and carbonyls compounds, show significant quantities of benzene, toluene and xylenes. Correlations and multivariate analysis of selected gaseous and particulate phase organic pollutants were performed. Source identification by principle component analysis and hierarchical cluster analysis allowed the identification of four sources (factors) for the roadside monitoring station. Factor 1 represents the effect of diesel vehicle exhaust. Factor 2 shows the contribution of aromatic compounds. Factor 3 explains photochemical products—formaldehyde and acetaldehyde. Factor 4 explains the effect of gasoline vehicle exhaust.

Drug target identification using network analysis: Taking active components in Sini decoction as an example

NASA Astrophysics Data System (ADS)

Chen, Si; Jiang, Hailong; Cao, Yan; Wang, Yun; Hu, Ziheng; Zhu, Zhenyu; Chai, Yifeng

2016-04-01

Identifying the molecular targets for the beneficial effects of active small-molecule compounds simultaneously is an important and currently unmet challenge. In this study, we firstly proposed network analysis by integrating data from network pharmacology and metabolomics to identify targets of active components in sini decoction (SND) simultaneously against heart failure. To begin with, 48 potential active components in SND against heart failure were predicted by serum pharmacochemistry, text mining and similarity match. Then, we employed network pharmacology including text mining and molecular docking to identify the potential targets of these components. The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database. At last, network analysis was conducted to identify most possible targets of components in SND. Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level. Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects. We envisage that network analysis will also be useful in target identification of a bioactive compound.

Drug target identification using network analysis: Taking active components in Sini decoction as an example

PubMed Central

Chen, Si; Jiang, Hailong; Cao, Yan; Wang, Yun; Hu, Ziheng; Zhu, Zhenyu; Chai, Yifeng

2016-01-01

Identifying the molecular targets for the beneficial effects of active small-molecule compounds simultaneously is an important and currently unmet challenge. In this study, we firstly proposed network analysis by integrating data from network pharmacology and metabolomics to identify targets of active components in sini decoction (SND) simultaneously against heart failure. To begin with, 48 potential active components in SND against heart failure were predicted by serum pharmacochemistry, text mining and similarity match. Then, we employed network pharmacology including text mining and molecular docking to identify the potential targets of these components. The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database. At last, network analysis was conducted to identify most possible targets of components in SND. Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level. Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects. We envisage that network analysis will also be useful in target identification of a bioactive compound. PMID:27095146

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

PubMed

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

2018-05-19

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

Factors supporting dentist leaders' retention in leadership.

PubMed

Tuononen, T; Lammintakanen, J; Suominen, A L

2017-12-01

The aim was to study factors associated with staying in a dentist leadership position. We used an electronic questionnaire to gather data from 156 current or former Finnish dentist leaders in 2014. Principal component analysis categorized statements regarding time usage and opportunities in managerial work into five main components. Associations between these main component scores and the tendency to stay as a leader were analyzed with logistic regression. Out of the five main components, two were significantly associated with staying as a leader: 'career intentions', which represented intent to continue or to leave the leadership position; and 'work time control opportunities', which represented how leaders could control their own work time. Other factors that supported staying were leadership education, more work time available for leadership work, and lower age. The main component 'work pressure' decreased, although not significantly, the odds of continuing; it included lack of leadership work time, and pressure from superiors or subordinates. Leaders have important roles in health care, ensuring everyday operations as well as developing their organizations to meet future challenges. Knowledge of these supporting factors will enable dentist leaders and their organizations to improve working conditions in order to recruit and retain motivated and competent persons. In addition, well-designed education is important to inspire and encourage future leaders. Copyright© 2017 Dennis Barber Ltd.

Psychometric Research in Reading.

ERIC Educational Resources Information Center

Davis, Frederick B.

This review of psychometric research in reading analyzes the factors which seem related to reading comprehension skills. Experimental analysis of reading comprehension by L. E. Thorndike revealed two major components: knowledge of word meanings and verbal reasoning abilities. Subsequent analysis of experimental studies of reading comprehension…

RECENT APPLICATIONS OF SOURCE APPORTIONMENT METHODS AND RELATED NEEDS

EPA Science Inventory

Traditional receptor modeling studies have utilized factor analysis (like principal component analysis, PCA) and/or Chemical Mass Balance (CMB) to assess source influences. The limitations with these approaches is that PCA is qualitative and CMB requires the input of source pr...

Subgroups of Adult Basic Education Learners with Different Profiles of Reading Skills

ERIC Educational Resources Information Center

MacArthur, Charles A.; Konold, Timothy R.; Glutting, Joseph J.; Alamprese, Judith A.

2012-01-01

The purpose of this study was to identify subgroups of adult basic education (ABE) learners with different profiles of skills in the core reading components of decoding, word recognition, spelling, fluency, and comprehension. The analysis uses factor scores of those 5 reading components from on a prior investigation of the reliability and…

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

ERIC Educational Resources Information Center

Park, Elisa L.

2009-01-01

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

Screening Protocol for Early Identification of Brazilian Children at Risk for Dyslexia

PubMed Central

Germano, Giseli D.; César, Alexandra B. P. de C.; Capellini, Simone A.

2017-01-01

Early identification of students at risk of dyslexia has been an educational challenge in the past years. This research had two main goals. First, we aimed to develop a screening protocol for early identification of Brazilian children at risk for dyslexia; second, we aimed to identify the predictive variables of this protocol using Principal Component Analysis. The major step involved in developing this protocol was the selection of variables, which were chosen based on the literature review and linguistic criteria. The screening protocol was composed of seven cognitive-linguistic skills: Letter naming; Phonological Awareness (which comprises the following subtests: Rhyme production, Rhyme identification, Syllabic segmentation, Production of words from a given phoneme, Phonemic Synthesis, and Phonemic analysis); Phonological Working memory, Rapid naming Speed; Silent reading; Reading of words and non-words; and Auditory Comprehension of sentences from pictures. A total of 149 children, aged from 6 years to 6 and 11, of both genders who were enrolled in the 1st grade of elementary public schools were submitted to the screening protocol. Principal Component Analysis revealed four factors, accounting for 64.45% of the variance of the Protocol variables: first factor (“pre-reading”), second factor (“decoding”), third factor (“Reading”), and fourth factor “Auditory processing.” The factors found corroborate those reported in the National and International literature and have been described as early signs of dyslexia and reading problems. PMID:29163246

A Comprehensive Needs Assessment To Facilitate Prevention of School Drop Out and Violence.

ERIC Educational Resources Information Center

Hunt, Mary Ellen; Meyers, Joel; Davies, Gwen; Meyers, Barbara; Grogg, Kathryn Rogers; Neel, John

2002-01-01

Study addresses school violence and dropout and proposes that the underlying factor of school connectedness/school climate should guide preventive and intervention efforts. Principal components analysis revealed five distinct factors: school connectedness/positive school climate, causes of violence, causes of school dropout, interventions for drop…

Assessing Underreporting Response Bias on the MMPI-2

ERIC Educational Resources Information Center

Bagby, R. Michael; Marshall, Margarita B.

2004-01-01

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

Non-Cognitive Factor Relationships to Hybrid Doctoral Student Self-Efficacy

ERIC Educational Resources Information Center

Egbert, Jessica Dalby; Gomez, Frank; Li, Wenling; Pennington, Sandra L.

2015-01-01

Statistical analysis of data gathered from 139 healthcare doctoral students revealed three key findings regarding non-cognitive factor relationships to hybrid doctoral student self-efficacy between online (web-based) and on-campus course components. First, student experiences significantly differed between online and on-campus course components…

Learning Style Scales: a valid and reliable questionnaire.

PubMed

Abdollahimohammad, Abdolghani; Ja'afar, Rogayah

2014-01-01

Learning-style instruments assist students in developing their own learning strategies and outcomes, in eliminating learning barriers, and in acknowledging peer diversity. Only a few psychometrically validated learning-style instruments are available. This study aimed to develop a valid and reliable learning-style instrument for nursing students. A cross-sectional survey study was conducted in two nursing schools in two countries. A purposive sample of 156 undergraduate nursing students participated in the study. Face and content validity was obtained from an expert panel. The LSS construct was established using principal axis factoring (PAF) with oblimin rotation, a scree plot test, and parallel analysis (PA). The reliability of LSS was tested using Cronbach's α, corrected item-total correlation, and test-retest. Factor analysis revealed five components, confirmed by PA and a relatively clear curve on the scree plot. Component strength and interpretability were also confirmed. The factors were labeled as perceptive, solitary, analytic, competitive, and imaginative learning styles. Cronbach's α was >0.70 for all subscales in both study populations. The corrected item-total correlations were >0.30 for the items in each component. The LSS is a valid and reliable inventory for evaluating learning style preferences in nursing students in various multicultural environments.

Extrinsic Factors as Component Positions to Bone and Intrinsic Factors Affecting Postoperative Rotational Limb Alignment in Total Knee Arthroplasty.

PubMed

Mochizuki, Tomoharu; Sato, Takashi; Tanifuji, Osamu; Watanabe, Satoshi; Kobayashi, Koichi; Endo, Naoto

2018-02-13

This study aimed to identify the factors affecting postoperative rotational limb alignment of the tibia relative to the femur. We hypothesized that not only component positions but also several intrinsic factors were associated with postoperative rotational limb alignment. This study included 99 knees (90 women and 9 men) with a mean age of 77 ± 6 years. A three-dimensional (3D) assessment system was applied under weight-bearing conditions to biplanar long-leg radiographs using 3D-to-2D image registration technique. The evaluation parameters were (1) component position; (2) preoperative and postoperative coronal, sagittal, and rotational limb alignment; (3) preoperative bony deformity, including femoral torsion, condylar twist angle, and tibial torsion; and (4) preoperative and postoperative range of motion (ROM). In multiple linear regression analysis using a stepwise procedure, postoperative rotational limb alignment was associated with the following: (1) rotation of the component position (tibia: β = 0.371, P < .0001; femur: β = -0.327, P < .0001), (2) preoperative rotational limb alignment (β = 0.253, P = .001), (3) postoperative flexion angle (β = 0.195, P = .007), and (4) tibial torsion (β = 0.193, P = .010). In addition to component positions, the intrinsic factors, such as preoperative rotational limb alignment, ROM, and tibial torsion, affected postoperative rotational limb alignment. On a premise of correct component positions, the intrinsic factors that can be controlled by surgeons should be taken care. In particular, ROM is necessary to be improved within the possible range to acquire better postoperative rotational limb alignment. Copyright © 2018 Elsevier Inc. All rights reserved.

Structure of the Nucleon and its Excitations

NASA Astrophysics Data System (ADS)

Kamleh, Waseem; Leinweber, Derek; Liu, Zhan-wei; Stokes, Finn; Thomas, Anthony; Thomas, Samuel; Wu, Jia-jun

2018-03-01

The structure of the ground state nucleon and its finite-volume excitations are examined from three different perspectives. Using new techniques to extract the relativistic components of the nucleon wave function, the node structure of both the upper and lower components of the nucleon wave function are illustrated. A non-trivial role for gluonic components is manifest. In the second approach, the parity-expanded variational analysis (PEVA) technique is utilised to isolate states at finite momenta, enabling a novel examination of the electric and magnetic form factors of nucleon excitations. Here the magnetic form factors of low-lying odd-parity nucleons are particularly interesting. Finally, the structure of the nucleon spectrum is examined in a Hamiltonian effective field theory analysis incorporating recent lattice-QCD determinations of low-lying two-particle scattering-state energies in the finite volume. The Roper resonance of Nature is observed to originate from multi-particle coupled-channel interactions while the first radial excitation of the nucleon sits much higher at approximately 1.9 GeV.

[Balanced scorecard for performance measurement of a nursing organization in a Korean hospital].

PubMed

Hong, Yoonmi; Hwang, Kyung Ja; Kim, Mi Ja; Park, Chang Gi

2008-02-01

The purpose of this study was to develop a balanced scorecard (BSC) for performance measurement of a Korean hospital nursing organization and to evaluate the validity and reliability of performance measurement indicators. Two hundred fifty-nine nurses in a Korean hospital participated in a survey questionnaire that included 29-item performance evaluation indicators developed by investigators of this study based on the Kaplan and Norton's BSC (1992). Cronbach's alpha was used to test the reliability of the BSC. Exploratory and confirmatory factor analysis with a structure equation model (SEM) was applied to assess the construct validity of the BSC. Cronbach's alpha of 29 items was .948. Factor analysis of the BSC showed 5 principal components (eigen value >1.0) which explained 62.7% of the total variance, and it included a new one, community service. The SEM analysis results showed that 5 components were significant for the hospital BSC tool. High degree of reliability and validity of this BSC suggests that it may be used for performance measurements of a Korean hospital nursing organization. Future studies may consider including a balanced number of nurse managers and staff nurses in the study. Further data analysis on the relationships among factors is recommended.

Testicular Lumicrine Factors Regulate ERK, STAT, and NFKB Pathways in the Initial Segment of the Rat Epididymis to Prevent Apoptosis1

PubMed Central

Xu, Bingfang; Abdel-Fattah, Rana; Yang, Ling; Crenshaw, Sallie A.; Black, Michael B.; Hinton, Barry T.

2011-01-01

The initial segment of the epididymis is vital for male fertility; therefore, it is important to understand the mechanisms that regulate this important region. Deprival of testicular luminal fluid factors/lumicrine factors from the epididymis results in a wave of apoptosis in the initial segment. In this study, a combination of protein array and microarray analyses was used to examine the early changes in downstream signal transduction pathways following loss of lumicrine factors. We discovered the following cascade of events leading to the loss of protection and eventual apoptosis: in the first 6 h after loss of lumicrine factors, down-regulation of the ERK pathway components was observed at the mRNA expression and protein activity levels. Microarray analysis revealed that mRNA levels of several key components of the ERK pathway, Dusp6, Dusp5, and Etv5, decreased sharply, while the analysis from the protein array revealed a decline in the activities of MAP2K1/2 and MAPK1. Immunostaining of phospho-MAPK3/1 indicated that down-regulation of the ERK pathway was specific to the epithelial cells of the initial segment. Subsequently, after 12 h of loss of lumicrine factors, levels of mRNA expression of STAT and NFKB pathway components increased, mRNA levels of several genes encoding cell cycle inhibitors increased, and levels of protein expression of several proapoptotic phosphatases increased. Finally, after 18 h of loss of protection from lumicrine factors, apoptosis was observed. In conclusion, testicular lumicrine factors protect the cells of the initial segment by activating the ERK pathway, repressing STAT and NFKB pathways, and thereby preventing apoptosis. PMID:21311037

Perspectives in Individualized Learning.

ERIC Educational Resources Information Center

Weisgerber, Robert A.

The readings presented here are an analysis of selected factors underlying the process of individualized learning. The book is organized topically and moves from theoretical considerations toward an analysis of important educational components. The readings come from a cross section of experts representing the areas of learning theory, individual…

Characterization of CDOM from urban waters in Northern-Northeastern China using excitation-emission matrix fluorescence and parallel factor analysis.

PubMed

Zhao, Ying; Song, Kaishan; Li, Sijia; Ma, Jianhang; Wen, Zhidan

2016-08-01

Chromophoric dissolved organic matter (CDOM) plays an important role in aquatic systems, but high concentrations of organic materials are considered pollutants. The fluorescent component characteristics of CDOM in urban waters sampled from Northern and Northeastern China were examined by excitation-emission matrix fluorescence and parallel factor analysis (EEM-PARAFAC) to investigate the source and compositional changes of CDOM on both space and pollution levels. One humic-like (C1), one tryptophan-like component (C2), and one tyrosine-like component (C3) were identified by PARAFAC. Mean fluorescence intensities of the three CDOM components varied spatially and by pollution level in cities of Northern and Northeastern China during July-August, 2013 and 2014. Principal components analysis (PCA) was conducted to identify the relative distribution of all water samples. Cluster analysis (CA) was also used to categorize the samples into groups of similar pollution levels within a study area. Strong positive linear relationships were revealed between the CDOM absorption coefficients a(254) (R (2) = 0.89, p < 0.01); a(355) (R (2) = 0.94, p < 0.01); and the fluorescence intensity (F max) for the humic-like C1 component. A positive linear relationship (R (2) = 0.77) was also exhibited between dissolved organic carbon (DOC) and the F max for the humic-like C1 component, but a relatively weak correlation (R (2) = 0.56) was detected between DOC and the F max for the tryptophan-like component (C2). A strong positive correlation was observed between the F max for the tryptophan-like component (C2) and total nitrogen (TN) (R (2) = 0.78), but moderate correlations were observed with ammonium-N (NH4-N) (R (2) = 0.68), and chemical oxygen demand (CODMn) (R (2) = 0.52). Therefore, the fluorescence intensities of CDOM components can be applied to monitor water quality in real time compared to that of traditional approaches. These results demonstrate that EEM-PARAFAC is useful to evaluate the dynamics of CDOM fluorescent components in urban waters from Northern and Northeastern China and this method has potential applications for monitoring urban water quality in different regions with various hydrological conditions and pollution levels.

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

NASA Astrophysics Data System (ADS)

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

2015-08-01

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

Validation and factor structure of the Thai version of the EURO-D scale for depression among older psychiatric patients.

PubMed

Jirapramukpitak, Tawanchai; Darawuttimaprakorn, Niphon; Punpuing, Sureeporn; Abas, Melanie

2009-11-01

To assess the concurrent and the construct validity of the Euro-D in older Thai persons. Eight local psychiatrists used the major depressive episode section of the Mini International Neuropsychiatric Interview to interview 150 consecutive psychiatric clinic attendees. A trained interviewer administered the Euro-D. We used receiver operating characteristic (ROC) analysis to assess the overall discriminability of the Euro-D scale and principal components factor analysis to assess its construct validity. The area under the ROC curve for the Euro-D with respect to major depressive episode was 0.78 [95% confidence interval (CI) 0.70-0.90] indicating moderately good discriminability. At a cut-point of 5/6 the sensitivity for major depressive episodes is 84.3%, specificity 58.6%, and kappa 0.37 (95% CI 0.22-0.52) indicating fair concordance. However, at the 3/4 cut-point recommended from European studies there is high sensitivity (94%) but poor specificity (34%). The principal components analysis suggested four factors. The first two factors conformed to affective suffering (depression, suicidality and tearfulness) and motivation (interest, concentration and enjoyment). Sleep and appetite constituted a separate factor, whereas pessimism loaded on its own factor. Among Thai psychiatric clinic attendees Euro-D is moderately valid for major depression. A much higher cut-point may be required than that which is usually advocated. The Thai version also shares two common factors as reported from most of previous studies.

High performance semantic factoring of giga-scale semantic graph databases.

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

al-Saffar, Sinan; Adolf, Bob; Haglin, David

2010-10-01

As semantic graph database technology grows to address components ranging from extant large triple stores to SPARQL endpoints over SQL-structured relational databases, it will become increasingly important to be able to bring high performance computational resources to bear on their analysis, interpretation, and visualization, especially with respect to their innate semantic structure. Our research group built a novel high performance hybrid system comprising computational capability for semantic graph database processing utilizing the large multithreaded architecture of the Cray XMT platform, conventional clusters, and large data stores. In this paper we describe that architecture, and present the results of our deployingmore » that for the analysis of the Billion Triple dataset with respect to its semantic factors, including basic properties, connected components, namespace interaction, and typed paths.« less

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

PubMed

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

2018-02-01

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

Associations between Caries among Children and Household Sugar Procurement, Exposure to Fluoridated Water and Socioeconomic Indicators in the Brazilian Capital Cities

PubMed Central

Gonçalves, Michele Martins; Leles, Cláudio Rodrigues; Freire, Maria do Carmo Matias

2013-01-01

The objective of this ecological study was to investigate the association between caries experience in 5- and 12-year-old Brazilian children in 2010 and household sugar procurement in 2003 and the effects of exposure to water fluoridation and socioeconomic indicators. Sample units were all 27 Brazilian capital cities. Data were obtained from the National Surveys of Oral Health; the National Household Food Budget Survey; and the United Nations Program for Development. Data analysis included correlation coefficients, exploratory factor analysis, and linear regression. There were significant negative associations between caries experience and procurement of confectionery, fluoridated water, HDI, and per capita income. Procurement of confectionery and soft drinks was positively associated with HDI and per capita income. Exploratory factor analysis grouped the independent variables by reducing highly correlated variables into two uncorrelated component variables that explained 86.1% of total variance. The first component included income, HDI, water fluoridation, and procurement of confectionery, while the second included free sugar and procurement of soft drinks. Multiple regression analysis showed that caries is associated with the first component. Caries experience was associated with better socioeconomic indicators of a city and exposure to fluoridated water, which may affect the impact of sugars on the disease. PMID:24307900

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-05-25

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-11-23

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

A novel approach combining self-organizing map and parallel factor analysis for monitoring water quality of watersheds under non-point source pollution

PubMed Central

Zhang, Yixiang; Liang, Xinqiang; Wang, Zhibo; Xu, Lixian

2015-01-01

High content of organic matter in the downstream of watersheds underscored the severity of non-point source (NPS) pollution. The major objectives of this study were to characterize and quantify dissolved organic matter (DOM) in watersheds affected by NPS pollution, and to apply self-organizing map (SOM) and parallel factor analysis (PARAFAC) to assess fluorescence properties as proxy indicators for NPS pollution and labor-intensive routine water quality indicators. Water from upstreams and downstreams was sampled to measure dissolved organic carbon (DOC) concentrations and excitation-emission matrix (EEM). Five fluorescence components were modeled with PARAFAC. The regression analysis between PARAFAC intensities (Fmax) and raw EEM measurements indicated that several raw fluorescence measurements at target excitation-emission wavelength region could provide similar DOM information to massive EEM measurements combined with PARAFAC. Regression analysis between DOC concentration and raw EEM measurements suggested that some regions in raw EEM could be used as surrogates for labor-intensive routine indicators. SOM can be used to visualize the occurrence of pollution. Relationship between DOC concentration and PARAFAC components analyzed with SOM suggested that PARAFAC component 2 might be the major part of bulk DOC and could be recognized as a proxy indicator to predict the DOC concentration. PMID:26526140

Reexamining the Validity and Dimensionality of the Moorong Self-Efficacy Scale: Improving Its Clinical Utility.

PubMed

Middleton, James W; Tran, Yvonne; Lo, Charles; Craig, Ashley

2016-12-01

To improve the clinical utility of the Moorong Self-Efficacy Scale (MSES) by reexamining its factor structure and comparing its performance against a measure of general self-efficacy in persons with spinal cord injury (SCI). Cross-sectional survey design. Community. Adults with SCI (N=161; 118 men and 43 women) recruited from Australia (n=82) and the United States (n=79), including 86 with paraplegia and 75 with tetraplegia. None. Confirmatory factor analysis deriving fit indices on reported 1-, 2-, and 3-factor structures for the MSES. Exploratory factor analysis of MSES using principal component analysis with promax oblique rotation and structure validation, with correlations and multiple regression using cross-sectional data from the Sherer General Self-Efficacy Scale and Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36). The MSES was confirmed to have a 3-factor structure, explaining 61% of variance. Two of the factors, labeled social function self-efficacy and personal function self-efficacy, were SCI condition-specific, whereas the other factor (accounting for 9.7% of variance) represented general self-efficacy, correlating most strongly with the Sherer General Self-Efficacy Scale. Correlations and multiple regression analyses between MSES factors, Sherer General Self-Efficacy Scale total score, SF-36 Physical and Mental Component Summary scores, and SF-36 domain scores support validity of this MSES factor structure. No significant cross-cultural differences existed between Australia and the United States in total MSES or factor scores. The findings support a 3-factor structure encompassing general and SCI domain-specific self-efficacy beliefs and better position the MSES to assist SCI rehabilitation assessment, planning, and research. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Sparse modeling of spatial environmental variables associated with asthma

PubMed Central

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

2014-01-01

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

Sparse modeling of spatial environmental variables associated with asthma.

PubMed

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

2015-02-01

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

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale.

PubMed

Sediyama, Cristina Y N; Moura, Ricardo; Garcia, Marina S; da Silva, Antonio G; Soraggi, Carolina; Neves, Fernando S; Albuquerque, Maicon R; Whiteside, Setephen P; Malloy-Diniz, Leandro F

2017-01-01

Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale. Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a) urgency, (b) lack of premeditation; (c) lack of perseverance; (d) sensation seeking. In the present study 384 participants (278 women and 106 men), who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis. Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years) scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach's alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory. Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS.

Exploratory and Confirmatory Factor Analyses in Reading-Related Cognitive Component among Grade Four Students in Thailand

ERIC Educational Resources Information Center

Liao, Chen-Huei; Kuo, Bor-Chen; Deenang, Exkarach; Mok, Magdalena Mo Ching

2016-01-01

This study aimed to investigate the structure and the validity of the cognitive components of reading in Thai, which is a language with a high degree of grapheme-phoneme correspondence. The participants were 1181 fourth-grade students in 29 schools in Thailand, divided into two subsamples for data analysis. Phoneme isolation, rapid colour naming,…

Subjective Well-Being in a Multicultural Urban Population: Structural, and Multivariate Analyses of the Ontario Health Survey Well-Being Scale

ERIC Educational Resources Information Center

John, Lindsay Herbert

2004-01-01

The validity of a scale, from the Ontario Health Survey, measuring the subjective sense of well-being, for a large multicultural population in Metropolitan Toronto, is examined through principal components analysis with oblique rotation. Four factors are extracted. Factor 1, is a stress and strain factor, and consists of health worries, feeling…

Morphological, motor and situation-motor characteristics of elite female handball players according to playing performance and position.

PubMed

Cavala, Marijana; Katić, Ratko

2010-12-01

The aim of the study was to define biomotor characteristics that determine playing performance and position in female handball. A battery of 13 variables consisting of somatotype components (3 variables), basic motor abilities (5 variables) and specific motor abilities (5 variables) were applied in a sample of 52 elite female handball players. Differences in biomotor characteristics according to playing performance and position of female handball players were determined by use of the analysis of variance (ANOVA) and discriminative analysis. Study results showed the high-quality female handball players to predominantly differ from the less successful ones in the specific factor of throw strength and basic dash factor, followed by the specific abilities of movement without and with ball, basic coordination/agility and specific ability of ball manipulation, and a more pronounced mesomorphic component. Results also revealed the wing players to be superior in the speed of movement frequency (psychomotor speed), run (explosive strength) and speed of movement with ball as compared with players at other playing positions. Also, endomorphic component was less pronounced in players at the wing and back player positions as compared with goalkeeper and pivot positions, where endomorphic component was considerably more pronounced.

Reading component skills of learners in adult basic education.

PubMed

MacArthur, Charles A; Konold, Timothy R; Glutting, Joseph J; Alamprese, Judith A

2010-01-01

The purposes of this study were to investigate the reliability and construct validity of measures of reading component skills with a sample of adult basic education (ABE) learners, including both native and nonnative English speakers, and to describe the performance of those learners on the measures. Investigation of measures of reading components is needed because available measures were neither developed for nor normed on ABE populations or with nonnative speakers of English. The study included 486 students, 334 born or educated in the United States (native) and 152 not born or educated in the United States (nonnative) but who spoke English well enough to participate in English reading classes. All students had scores on 11 measures covering five constructs: decoding, word recognition, spelling, fluency, and comprehension. Confirmatory factor analysis (CFA) was used to test three models: a two-factor model with print and meaning factors; a three-factor model that separated out a fluency factor; and a five-factor model based on the hypothesized constructs. The five-factor model fit best. In addition, the CFA model fit both native and nonnative populations equally well without modification, showing that the tests measure the same constructs with the same accuracy for both groups. Group comparisons found no difference between the native and nonnative samples on word recognition, but the native sample scored higher on fluency and comprehension and lower on decoding than did the nonnative sample. Students with self-reported learning disabilities scored lower on all reading components. Differences by age and gender were also analyzed.

Principal component analysis to assess the composition and fate of impurities in a large river-embedded reservoir: Qingcaosha Reservoir.

PubMed

Ou, Hua-Se; Wei, Chao-Hai; Deng, Yang; Gao, Nai-Yun

2013-08-01

Qingcaosha Reservoir (QR) is the largest river-embedded reservoir in east China, which receives its source water from the Yangtze River (YR). The temporal and spatial variations in dissolved organic matter (DOM), chromophoric DOM (CDOM), nitrogen, phosphorus and phytoplankton biomass were investigated from June to September in 2012 and were integrated by principal component analysis (PCA). Three PCA factors were identified: (1) phytoplankton related factor 1, (2) total DOM related factor 2, and (3) eutrophication related factor 3. Factor 1 was a lake-type parameter which correlated with chlorophyll-a and protein-like CDOM (r = 0.793 and r = 0.831, respectively). Factor 2 was a river-type parameter which correlated with total DOC and humic-like CDOM (r = 0.668 and r = 0.726, respectively). Factor 3 correlated with total nitrogen and phosphorus (r = 0.864 and r = 0.621, respectively). The low flow speed, self-sedimentation and nutrient accumulation in QR resulted in increases in PCA factor 1 scores (phytoplankton biomass and derived CDOM) in the spatial scale, indicating a change of river-type water (YR) to lake-type water (QR). In summer, the water temperature variation induced a growth-bloom-decay process of phytoplankton combined with the increase of PCA factor 2 (humic-like CDOM) in the QR, which was absent in the YR.

On the stability analysis of approximate factorization methods for 3D Euler and Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Demuren, A. O.; Ibraheem, S. O.

1993-01-01

The convergence characteristics of various approximate factorizations for the 3D Euler and Navier-Stokes equations are examined using the von-Neumann stability analysis method. Three upwind-difference based factorizations and several central-difference based factorizations are considered for the Euler equations. In the upwind factorizations both the flux-vector splitting methods of Steger and Warming and van Leer are considered. Analysis of the Navier-Stokes equations is performed only on the Beam and Warming central-difference scheme. The range of CFL numbers over which each factorization is stable is presented for one-, two-, and three-dimensional flow. Also presented for each factorization is the CFL number at which the maximum eigenvalue is minimized, for all Fourier components, as well as for the high frequency range only. The latter is useful for predicting the effectiveness of multigrid procedures with these schemes as smoothers. Further, local mode analysis is performed to test the suitability of using a uniform flow field in the stability analysis. Some inconsistencies in the results from previous analyses are resolved.

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

PubMed

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

2015-04-01

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

Identification of Reliable Components in Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS): a Data-Driven Approach across Metabolic Processes.

PubMed

Motegi, Hiromi; Tsuboi, Yuuri; Saga, Ayako; Kagami, Tomoko; Inoue, Maki; Toki, Hideaki; Minowa, Osamu; Noda, Tetsuo; Kikuchi, Jun

2015-11-04

There is an increasing need to use multivariate statistical methods for understanding biological functions, identifying the mechanisms of diseases, and exploring biomarkers. In addition to classical analyses such as hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis, various multivariate strategies, including independent component analysis, non-negative matrix factorization, and multivariate curve resolution, have recently been proposed. However, determining the number of components is problematic. Despite the proposal of several different methods, no satisfactory approach has yet been reported. To resolve this problem, we implemented a new idea: classifying a component as "reliable" or "unreliable" based on the reproducibility of its appearance, regardless of the number of components in the calculation. Using the clustering method for classification, we applied this idea to multivariate curve resolution-alternating least squares (MCR-ALS). Comparisons between conventional and modified methods applied to proton nuclear magnetic resonance ((1)H-NMR) spectral datasets derived from known standard mixtures and biological mixtures (urine and feces of mice) revealed that more plausible results are obtained by the modified method. In particular, clusters containing little information were detected with reliability. This strategy, named "cluster-aided MCR-ALS," will facilitate the attainment of more reliable results in the metabolomics datasets.

Metabolic syndrome in menopause and associated factors: a meta-analysis.

PubMed

Pu, D; Tan, R; Yu, Q; Wu, J

2017-12-01

Metabolic syndrome (MetS) is a cluster of risk factors for cardiovascular disease and diabetes. Menopause is associated with an increased risk for MetS. The purpose of this meta-analysis is to better understand the relationship between MetS and menopause. MEDLINE and EMBASE were searched for all the associated articles on (1) MetS components in postmenopausal women vs. premenopausal women, (2) comparison of MetS incidence between surgical menopause and natural menopause, (3) the effect of hormone therapy (HT) with 17β-estradiol (E2) compared to conjugated equine estrogen (CEE) on MetS components among postmenopausal women. A meta-analysis was applied by Review Manager 5.3 software. All comparable indicators were significantly unfavorably changed in postmenopausal women compared to premenopausal women except for high density lipoprotein cholesterol. Women who underwent surgical menopause suffered a 1.51-fold higher risk for MetS compared to those with natural menopause. HT with E2 provided more benefits for levels of triglyceride and diastolic blood, while CEE showed a better effect on both high and low density lipoprotein cholesterol levels. Menopause nearly adversely affects all components of MetS, and surgical menopause may lead to a higher incidence of MetS compared to natural menopause. HT with various preparations may have different effects on MetS components. These results may clarify the management of menopause-related MetS in clinical practice.

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

ERIC Educational Resources Information Center

Anderson, Carolyn J.

1996-01-01

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

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

PubMed

Úbeda, Yulán; Llorente, Miquel

2015-02-18

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

Heritability of somatotype components from early adolescence into young adulthood: a multivariate analysis on a longitudinal twin study.

PubMed

Peeters, M W; Thomis, M A; Claessens, A L; Loos, R J F; Maes, H H M; Lysens, R; Vanden Eynde, B; Vlietinck, R; Beunen, G

2003-01-01

Several studies with different designs have attempted to estimate the heritability of somatotype components. However they often ignore the covariation between the three components as well as possible sex and age effects. Shared environmental factors are not always controlled for. This study explores the pattern of genetic and environmental determination of the variation in Heath-Carter somatotype components from early adolescence into young adulthood. Data from the Leuven Longitudinal Twin Study, a longitudinal sample of Belgian same-aged twins followed from 10 to 18 years (n = 105 pairs, equally divided over five zygosity groups), is entered into a multivariate path analysis. Thus the covariation between the somatotype components is taken into account, gender heterogeneity can be tested, common environmental influences can be distinguished from genetic effects and age effects are controlled for. Heritability estimates from 10 to 18 years range from 0.21 to 0.88, 0.46 to 0.76 and 0.16 to 0.73 for endomorphy, mesomorphy and ectomorphy in boys. In girls, heritability estimates range from 0.76 to 0.89, 0.36 to 0.57 and 0.57 to 0.76 for the respective somatotype components. Sex differences are significant from 14 years onwards. More than half of the variance in all somatotype components for both sexes at all time points is explained by factors the three components have in common. The finding of substantial genetic influence on the variability of somatotype components is further supported. The need to consider somatotype as a whole is stressed as well as the need for sex- and perhaps age-specific analyses. Further multivariate analyses are needed to confirm the present findings.

Psychosocial factors of caregiver burden in child caregivers: results from the new national study of caregiving.

PubMed

Cohen, Steven A; Cook, Sarah; Kelley, Lauren; Sando, Trisha; Bell, Allison E

2015-08-07

Over 50 million informal caregivers in the United States provide care to an aging adult, saving the economy hundreds of billions of dollars annually from costly hospitalization or institutionalization. Despite the benefits associated with caregiving, caregiver stress can lead to negative physical and mental health consequences, or "caregiver burden". Given these potential negative consequences of caregiver burden, it is important not only to understand the multidimensional components of burden but to also understand the experience from the perspective of the caregiver themselves. Therefore, the objectives of our study are to use exploratory factor analysis to obtain a set of latent factors among a subset of caregiver burden questions identified in previous studies and assess their reliability. All data was obtained from the 2011 National Study of Caregiving (NSOC). Exploratory factor analysis (EFA) was performed to identify a set of latent factors assessing four domains of caregiver burden in "child caregivers": those informal caregivers who provide care to a parent or stepparent. Sensitivity analysis was also conducted by repeating the EFA on demographic subsets of caregivers. After multiple factor analyses, four consistent caregiver burden factors emerged from the 23 questions analyzed: Negative emotional, positive emotional, social, and financial. Reliability of each factor varied, and was strongest for the positive emotional domain for caregiver burden. These domains were generally consistent across demographic subsets of informal caregivers. These results provide researchers a more comprehensive understanding of caregiver burden to target interventions to protect caregiver health and maintain this vital component of the US health care system.

Reliability, factor analysis and internal consistency calculation of the Insomnia Severity Index (ISI) in French and in English among Lebanese adolescents.

PubMed

Chahoud, M; Chahine, R; Salameh, P; Sauleau, E A

2017-06-01

Our goal is to validate and to verify the reliability of the French and English versions of the Insomnia Severity Index (ISI) in Lebanese adolescents. A cross-sectional study was implemented. 104 Lebanese students aged between 14 and 19 years participated in the study. The English version of the questionnaire was distributed to English-speaking students and the French version was administered to French-speaking students. A scale (1 to 7 with 1 = very well understood and 7 = not at all) was used to identify the level of the students' understanding of each instruction, question and answer of the ISI. The scale's structural validity was assessed. The factor structure of ISI was evaluated by principal component analysis. The internal consistency of this scale was evaluated by Cronbach's alpha. To assess test-retest reliability the intraclass correlation coefficient (ICC) was used. The principal component analysis confirmed the presence of a two-component factor structure in the English version and a three-component factor structure in the French version with eigenvalues > 1. The English version of the ISI had an excellent internal consistency (α = 0.90), while the French version had a good internal consistency (α = 0.70). The ICC presented an excellent agreement in the French version (ICC = 0.914, CI = 0.856-0.949) and a good agreement in the English one (ICC = 0.762, CI = 0.481-890). The Bland-Altman plots of the two versions of the ISI showed that the responses over two weeks' were comparable and very few outliers were detected. The results of our analyses reveal that both English and French versions of the ISI scale have good internal consistency and are reproducible and reliable. Therefore, it can be used to assess the prevalence of insomnia in Lebanese adolescents.

Differential distribution of amino acids in plants.

PubMed

Kumar, Vinod; Sharma, Anket; Kaur, Ravdeep; Thukral, Ashwani Kumar; Bhardwaj, Renu; Ahmad, Parvaiz

2017-05-01

Plants are a rich source of amino acids and their individual abundance in plants is of great significance especially in terms of food. Therefore, it is of utmost necessity to create a database of the relative amino acid contents in plants as reported in literature. Since in most of the cases complete analysis of profiles of amino acids in plants was not reported, the units used and the methods applied and the plant parts used were different, amino acid contents were converted into relative units with respect to lysine for statistical analysis. The most abundant amino acids in plants are glutamic acid and aspartic acid. Pearson's correlation analysis among different amino acids showed that there were no negative correlations between the amino acids. Cluster analysis (CA) applied to relative amino acid contents of different families. Alismataceae, Cyperaceae, Capparaceae and Cactaceae families had close proximity with each other on the basis of their relative amino acid contents. First three components of principal component analysis (PCA) explained 79.5% of the total variance. Factor analysis (FA) explained four main underlying factors for amino acid analysis. Factor-1 accounted for 29.4% of the total variance and had maximum loadings on glycine, isoleucine, leucine, threonine and valine. Factor-2 explained 25.8% of the total variance and had maximum loadings on alanine, aspartic acid, serine and tyrosine. 14.2% of the total variance was explained by factor-3 and had maximum loadings on arginine and histidine. Factor-4 accounted 8.3% of the total variance and had maximum loading on the proline amino acid. The relative content of different amino acids presented in this paper is alanine (1.4), arginine (1.8), asparagine (0.7), aspartic acid (2.4), cysteine (0.5), glutamic acid (2.8), glutamine (0.6), glycine (1.0), histidine (0.5), isoleucine (0.9), leucine (1.7), lysine (1.0), methionine (0.4), phenylalanine (0.9), proline (1.1), serine (1.0), threonine (1.0), tryptophan (0.3), tyrosine (0.7) and valine (1.2).

Principal component analysis of the Norwegian version of the quality of life in late-stage dementia scale.

PubMed

Mjørud, Marit; Kirkevold, Marit; Røsvik, Janne; Engedal, Knut

2014-01-01

To investigate which factors the Quality of Life in Late-Stage Dementia (QUALID) scale holds when used among people with dementia (pwd) in nursing homes and to find out how the symptom load varies across the different severity levels of dementia. We included 661 pwd [mean age ± SD, 85.3 ± 8.6 years; 71.4% women]. The QUALID and the Clinical Dementia Rating (CDR) scale were applied. A principal component analysis (PCA) with varimax rotation and Kaiser normalization was applied to test the factor structure. Nonparametric analyses were applied to examine differences of symptom load across the three CDR groups. The mean QUALID score was 21.5 (±7.1), and the CDR scores of the three groups were 1 in 22.5%, 2 in 33.6% and 3 in 43.9%. The results of the statistical measures employed were the following: Crohnbach's α of QUALID, 0.74; Bartlett's test of sphericity, p <0.001; the Kaiser-Meyer-Olkin measure, 0.77. The PCA analysis resulted in three components accounting for 53% of the variance. The first component was 'tension' ('facial expression of discomfort', 'appears physically uncomfortable', 'verbalization suggests discomfort', 'being irritable and aggressive', 'appears calm', Crohnbach's α = 0.69), the second was 'well-being' ('smiles', 'enjoys eating', 'enjoys touching/being touched', 'enjoys social interaction', Crohnbach's α = 0.62) and the third was 'sadness' ('appears sad', 'cries', 'facial expression of discomfort', Crohnbach's α 0.65). The mean score on the components 'tension' and 'well-being' increased significantly with increasing severity levels of dementia. Three components of quality of life (qol) were identified. Qol decreased with increasing severity of dementia. © 2013 S. Karger AG, Basel.

[Geographical distribution of left ventricular Tei index based on principal component analysis].

PubMed

Xu, Jinhui; Ge, Miao; He, Jinwei; Xue, Ranyin; Yang, Shaofang; Jiang, Jilin

2014-11-01

To provide a scientific standard of left ventricular Tei index for healthy people from various region of China, and to lay a reliable foundation for the evaluation of left ventricular diastolic and systolic function. The correlation and principal component analysis were used to explore the left ventricular Tei index, which based on the data of 3 562 samples from 50 regions of China by means of literature retrieval. Th e nine geographical factors were longitude(X₁), latitude(X₂), altitude(X₃), annual sunshine hours (X₄), the annual average temperature (X₅), annual average relative humidity (X₆), annual precipitation (X₇), annual temperature range (X₈) and annual average wind speed (X₉). ArcGIS soft ware was applied to calculate the spatial distribution regularities of left ventricular Tei index. There is a significant correlation between the healthy people's left ventricular Tei index and geographical factors, and the correlation coefficients were -0.107 (r₁), -0.301 (r₂), -0.029 (r₃), -0.277 (r₄), -0.256(r₅), -0.289(r₆), -0.320(r₇), -0.310 (r₈) and -0.117 (r₉), respectively. A linear equation between the Tei index and the geographical factor was obtained by regression analysis based on the three extracting principal components. The geographical distribution tendency chart for healthy people's left Tei index was fitted out by the ArcGIS spatial interpolation analysis. The geographical distribution for left ventricular Tei index in China follows certain pattern. The reference value in North is higher than that in South, while the value in East is higher than that in West.

The structural basis for the functional comparability of factor VIII and the long-acting variant recombinant factor VIII Fc fusion protein

DOE PAGES

Leksa, N. C.; Chiu, P. -L.; Bou-Assaf, G. M.; ...

2017-05-03

Fusion of the human IgG 1 Fc domain to the C-terminal C2 domain of B-domain-deleted (BDD) factor VIII (FVIII) results in the recombinant FVIII Fc (rFVIIIFc) fusion protein, which has a 1.5-fold longer half-life in humans. To assess the structural properties of rFVIIIFc by comparing its constituent FVIII and Fc elements with their respective isolated components, and evaluating their structural independence within rFVIIIFc. rFVIIIFc and its isolated FVIII and Fc components were compared by the use of hydrogen–deuterium exchange mass spectrometry (HDX-MS). The structure of rFVIIIFc was also evaluated by the use of X-ray crystallography, small-angle X-ray scattering (SAXS), andmore » electron microscopy (EM). The degree of steric interference by the appended Fc domain was assessed by EM and surface plasmon resonance (SPR). HDX-MS analysis of rFVIIIFc revealed that fusion caused no structural perturbations in FVIII or Fc. The rFVIIIFc crystal structure showed that the FVIII component is indistinguishable from published BDD FVIII structures. The Fc domain was not observed, indicating high mobility. SAXS analysis was consistent with an ensemble of rigid-body models in which the Fc domain exists in a largely extended orientation relative to FVIII. Binding of Fab fragments of anti-C2 domain antibodies to BDD FVIII was visualized by EM, and the affinities of the corresponding intact antibodies for BDD FVIII and rFVIIIFc were comparable by SPR analysis. Thus, the FVIII and Fc components of rFVIIIFc are structurally indistinguishable from their isolated constituents, and show a high degree of structural independence, consistent with the functional comparability of rFVIIIFc and unmodified FVIII.« less

The structural basis for the functional comparability of Factor VIII and the long-acting variant recombinant Factor VIII Fc fusion protein

PubMed Central

Leksa, N.C.; Chiu, P.-L.; Bou-Assaf, G.M.; Quan, C.; Liu, Z.; Goodman, A.B.; Chambers, M.G.; Tsutakawa, S.E.; Hammel, M.; Peters, R.T.; Walz, T.; Kulman, J.D.

2017-01-01

SUMMARY Background Fusion of the human IgG1 Fc domain to the C-terminal C2 domain of B domain-deleted (BDD) factor VIII (FVIII) results in the rFVIIIFc fusion protein that has a 1.5-fold longer half-life in humans. Objective To assess the structural properties of rFVIIIFc by comparing its constituent FVIII and Fc elements with their respective isolated components and evaluating their structural independence within rFVIIIFc. Methods rFVIIIFc and its isolated FVIII and Fc components were compared by hydrogen-deuterium exchange mass spectrometry (HDX-MS). The structure of rFVIIIFc was also evaluated by X-ray crystallography, small-angle X-ray scattering (SAXS), and electron microscopy (EM). The degree of steric interference by the appended Fc domain was assessed by EM and surface plasmon resonance (SPR). Results HDX-MS analysis of rFVIIIFc revealed that fusion caused no structural perturbations in FVIII or Fc. The rFVIIIFc crystal structure showed that the FVIII component is indistinguishable from published BDD FVIII structures. The Fc domain was not observed, indicating high mobility. SAXS analysis was consistent with an ensemble of rigid-body models in which the Fc domain exists in a largely extended orientation relative to FVIII. Binding of Fab fragments of anti-C2 domain antibodies to BDD FVIII was visualized by EM, and the affinities of the corresponding intact antibodies for BDD FVIII and rFVIIIFc were comparable by SPR analysis. Conclusions The FVIII and Fc components of rFVIIIFc are structurally indistinguishable from their isolated constituents and exhibit a high degree of structural independence, consistent with the functional comparability of rFVIIIFc and unmodified FVIII. PMID:28397397

The structural basis for the functional comparability of factor VIII and the long-acting variant recombinant factor VIII Fc fusion protein

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

Leksa, N. C.; Chiu, P. -L.; Bou-Assaf, G. M.

Fusion of the human IgG 1 Fc domain to the C-terminal C2 domain of B-domain-deleted (BDD) factor VIII (FVIII) results in the recombinant FVIII Fc (rFVIIIFc) fusion protein, which has a 1.5-fold longer half-life in humans. To assess the structural properties of rFVIIIFc by comparing its constituent FVIII and Fc elements with their respective isolated components, and evaluating their structural independence within rFVIIIFc. rFVIIIFc and its isolated FVIII and Fc components were compared by the use of hydrogen–deuterium exchange mass spectrometry (HDX-MS). The structure of rFVIIIFc was also evaluated by the use of X-ray crystallography, small-angle X-ray scattering (SAXS), andmore » electron microscopy (EM). The degree of steric interference by the appended Fc domain was assessed by EM and surface plasmon resonance (SPR). HDX-MS analysis of rFVIIIFc revealed that fusion caused no structural perturbations in FVIII or Fc. The rFVIIIFc crystal structure showed that the FVIII component is indistinguishable from published BDD FVIII structures. The Fc domain was not observed, indicating high mobility. SAXS analysis was consistent with an ensemble of rigid-body models in which the Fc domain exists in a largely extended orientation relative to FVIII. Binding of Fab fragments of anti-C2 domain antibodies to BDD FVIII was visualized by EM, and the affinities of the corresponding intact antibodies for BDD FVIII and rFVIIIFc were comparable by SPR analysis. Thus, the FVIII and Fc components of rFVIIIFc are structurally indistinguishable from their isolated constituents, and show a high degree of structural independence, consistent with the functional comparability of rFVIIIFc and unmodified FVIII.« less

Steam automobile analysis

NASA Technical Reports Server (NTRS)

Peoples, J. A.

1975-01-01

Report includes many charts that present graphically the effects of design parameters on performance. Equations and data are given which can assist designer in selecting among such factors as working medium, horsepower, and engine components.

40 CFR 89.118 - Deterioration factors and service accumulation.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., subsystems, or components selected by the manufacturer under § 89.117(d). The manufacturer shall describe the... must be based on good engineering judgment. (iii) Engineering analysis for established technologies. (A) In the case where an engine family uses established technology, an analysis based on good engineering...

40 CFR 89.118 - Deterioration factors and service accumulation.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., subsystems, or components selected by the manufacturer under § 89.117(d). The manufacturer shall describe the... must be based on good engineering judgment. (iii) Engineering analysis for established technologies. (A) In the case where an engine family uses established technology, an analysis based on good engineering...

49 CFR 236.907 - Product Safety Plan (PSP).

Code of Federal Regulations, 2012 CFR

2012-10-01

... product components and their physical relationship in the subsystem or system; (2) A description of the... in § 236.909 and appendix B to this part; (8) A hazard mitigation analysis, including a complete and... principles and assumptions; (11) A human factors analysis, including a complete description of all human...

40 CFR 89.118 - Deterioration factors and service accumulation.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., subsystems, or components selected by the manufacturer under § 89.117(d). The manufacturer shall describe the... must be based on good engineering judgment. (iii) Engineering analysis for established technologies. (A) In the case where an engine family uses established technology, an analysis based on good engineering...

40 CFR 89.118 - Deterioration factors and service accumulation.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., subsystems, or components selected by the manufacturer under § 89.117(d). The manufacturer shall describe the... must be based on good engineering judgment. (iii) Engineering analysis for established technologies. (A) In the case where an engine family uses established technology, an analysis based on good engineering...

49 CFR 236.907 - Product Safety Plan (PSP).

Code of Federal Regulations, 2011 CFR

2011-10-01

... product components and their physical relationship in the subsystem or system; (2) A description of the... in § 236.909 and appendix B to this part; (8) A hazard mitigation analysis, including a complete and... principles and assumptions; (11) A human factors analysis, including a complete description of all human...

40 CFR 89.118 - Deterioration factors and service accumulation.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., subsystems, or components selected by the manufacturer under § 89.117(d). The manufacturer shall describe the... must be based on good engineering judgment. (iii) Engineering analysis for established technologies. (A) In the case where an engine family uses established technology, an analysis based on good engineering...

Outdoor Leader Career Development: Exploration of a Career Path

ERIC Educational Resources Information Center

Wagstaff, Mark

2016-01-01

The purpose of this study was to assess the efficacy of the proposed Outdoor Leader Career Development Model (OLCDM) through the development of the Outdoor Leader Career Development Inventory (OLCDI). I assessed the reliability and validity of the OLCDI through exploratory factor analysis, principal component analysis, and varimax rotation, based…

The Circumplex Pattern of the Life Styles Inventory: A Reanalysis.

ERIC Educational Resources Information Center

Levin, Joseph

1991-01-01

A reanalysis of the intercorrelation matrix from a principal components analysis of the Life Styles Inventory was conducted using a Canadian sample. Using nonmetric multidimensional scaling, analyses show an almost perfect circumplex pattern. Results illustrate the inadequacy of factor analytic procedures for the analysis and representation of a…

A Principal Components Analysis of the Rathus Assertiveness Schedule.

ERIC Educational Resources Information Center

Law, H. G.; And Others

1979-01-01

Investigated the adequacy of the Rathus Assertiveness Schedule (RAS) as a global measure of assertiveness. Analysis indicated that the RAS does not provide a unidimensional index of assertiveness, but rather measures a number of factors including situation-specific assertive behavior, aggressiveness, and a more general assertiveness. (Author)

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

PubMed

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

2012-01-01

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

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

PubMed Central

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

2012-01-01

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

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

NASA Technical Reports Server (NTRS)

Ling, Lisa

2014-01-01

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

Pyrolysis-mass spectrometry/pattern recognition on a well-characterized suite of humic samples

USGS Publications Warehouse

MacCarthy, P.; DeLuca, S.J.; Voorhees, K.J.; Malcolm, R.L.; Thurman, E.M.

1985-01-01

A suite of well-characterized humic and fulvic acids of freshwater, soil and plant origin was subjected to pyrolysis-mass spectrometry and the resulting data were analyzed by pattern recognition and factor analysis. A factor analysis plot of the data shows that the humic acids and fulvic acids can be segregated into two distinct classes. Carbohydrate and phenolic components are more pronounced in the pyrolysis products of the fulvic acids, and saturated and unsaturated hydrocarbons contribute more to the humic acid pyrolysis products. A second factor analysis plot shows a separation which appears to be based primarily on whether the samples are of aquatic or soil origin. ?? 1985.

Unsupervised Discovery of Demixed, Low-Dimensional Neural Dynamics across Multiple Timescales through Tensor Component Analysis.

PubMed

Williams, Alex H; Kim, Tony Hyun; Wang, Forea; Vyas, Saurabh; Ryu, Stephen I; Shenoy, Krishna V; Schnitzer, Mark; Kolda, Tamara G; Ganguli, Surya

2018-06-27

Perceptions, thoughts, and actions unfold over millisecond timescales, while learned behaviors can require many days to mature. While recent experimental advances enable large-scale and long-term neural recordings with high temporal fidelity, it remains a formidable challenge to extract unbiased and interpretable descriptions of how rapid single-trial circuit dynamics change slowly over many trials to mediate learning. We demonstrate a simple tensor component analysis (TCA) can meet this challenge by extracting three interconnected, low-dimensional descriptions of neural data: neuron factors, reflecting cell assemblies; temporal factors, reflecting rapid circuit dynamics mediating perceptions, thoughts, and actions within each trial; and trial factors, describing both long-term learning and trial-to-trial changes in cognitive state. We demonstrate the broad applicability of TCA by revealing insights into diverse datasets derived from artificial neural networks, large-scale calcium imaging of rodent prefrontal cortex during maze navigation, and multielectrode recordings of macaque motor cortex during brain machine interface learning. Copyright © 2018 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

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

Design of experiments and principal component analysis as approaches for enhancing performance of gas-diffusional air-breathing bilirubin oxidase cathode

NASA Astrophysics Data System (ADS)

Babanova, Sofia; Artyushkova, Kateryna; Ulyanova, Yevgenia; Singhal, Sameer; Atanassov, Plamen

2014-01-01

Two statistical methods, design of experiments (DOE) and principal component analysis (PCA) are employed to investigate and improve performance of air-breathing gas-diffusional enzymatic electrodes. DOE is utilized as a tool for systematic organization and evaluation of various factors affecting the performance of the composite system. Based on the results from the DOE, an improved cathode is constructed. The current density generated utilizing the improved cathode (755 ± 39 μA cm-2 at 0.3 V vs. Ag/AgCl) is 2-5 times higher than the highest current density previously achieved. Three major factors contributing to the cathode performance are identified: the amount of enzyme, the volume of phosphate buffer used to immobilize the enzyme, and the thickness of the gas-diffusion layer (GDL). PCA is applied as an independent confirmation tool to support conclusions made by DOE and to visualize the contribution of factors in individual cathode configurations.

[Resolving excitation emission matrix spectroscopy of estuarine CDOM with parallel factor analysis and its application in organic pollution monitoring].

PubMed

Guo, Wei-Dong; Huang, Jian-Ping; Hong, Hua-Sheng; Xu, Jing; Deng, Xun

2010-06-01

The distribution and estuarine behavior of fluorescent components of chromophoric dissolved organic matter (CDOM) from Jiulong Estuary were determined by fluorescence excitation emission matrix spectroscopy (EEMs) combined with parallel factor analysis (PARAFAC). The feasibility of these components as tracers for organic pollution in estuarine environments was also evaluated. Four separate fluorescent components were identified by PARAFAC, including three humic-like components (C1: 240, 310/382 nm; C2: 230, 250, 340/422 nm; C4: 260, 390/482 nm) and one protein-like components (C3: 225, 275/342 nm). These results indicated that UV humic-like peak A area designated by traditional "peak-picking method" was not a single peak but actually a combination of several fluorescent components, and it also had inherent links to so-called marine humic-like peak M or terrestrial humic-like peak C. Component C2 which include peak M decreased with increase of salinity in Jiulong Estuary, demonstrating that peak M can not be thought as the specific indicator of the "marine" humic-like component. Two humic-like components C1 and C2 showed additional behavior in the turbidity maximum region (salinity < 6) and then conservative mixing behavior for the rest estuarine region, while humic-like components C4 showed conservative mixing behavior for the whole estuarine region. However, the protein-like component C3 showed nonconservative mixing behavior, suggesting it had autochthonous estuarine origin. EEMs-PARAFAC can provide fluorescent fingerprint to differentiate the DOM features for three tributaries of Jiulong River. The observed linear relationships between humic-like components and absorption coefficient a (280) with chemical oxygen demand (COD) and biological oxygen demand (BOD5) suggest that the optical properties of CDOM may provide a fast in-situ way to monitor the variation of the degree of organic pollution in estuarine environments.

Performance assessment and optimisation of a large information system by combined customer relationship management and resilience engineering: a mathematical programming approach

NASA Astrophysics Data System (ADS)

Azadeh, A.; Foroozan, H.; Ashjari, B.; Motevali Haghighi, S.; Yazdanparast, R.; Saberi, M.; Torki Nejad, M.

2017-10-01

ISs and ITs play a critical role in large complex gas corporations. Many factors such as human, organisational and environmental factors affect IS in an organisation. Therefore, investigating ISs success is considered to be a complex problem. Also, because of the competitive business environment and the high amount of information flow in organisations, new issues like resilient ISs and successful customer relationship management (CRM) have emerged. A resilient IS will provide sustainable delivery of information to internal and external customers. This paper presents an integrated approach to enhance and optimise the performance of each component of a large IS based on CRM and resilience engineering (RE) in a gas company. The enhancement of the performance can help ISs to perform business tasks efficiently. The data are collected from standard questionnaires. It is then analysed by data envelopment analysis by selecting the optimal mathematical programming approach. The selected model is validated and verified by principle component analysis method. Finally, CRM and RE factors are identified as influential factors through sensitivity analysis for this particular case study. To the best of our knowledge, this is the first study for performance assessment and optimisation of large IS by combined RE and CRM.

Selected sperm traits are simultaneously altered after scrotal heat stress and play specific roles in in vitro fertilization and embryonic development.

PubMed

Lucio, Aline C; Alves, Benner G; Alves, Kele A; Martins, Muller C; Braga, Lucas S; Miglio, Luisa; Alves, Bruna G; Silva, Thiago H; Jacomini, José O; Beletti, Marcelo E

2016-09-01

Improvements in the estimation of male fertility indicators require advances in laboratory tests for sperm assessment. The aims of the present work were (1) to apply a multivariate analysis to examine sperm set of alterations and interactions and (2) to evaluate the importance of sperm parameters on the outcome of standard IVF and embryonic development. Bulls (n = 3) were subjected to scrotal insulation, and ejaculates were collected before (preinsulation = Day 0) and through 56 days (Days 7, 14, 21, 28, 35, 42, 49, and 56) of the experimental period. Sperm head morphometry and chromatin variables were assessed by a computational image analysis, and IVF was performed. Scrotal heat stress induced alterations in all evaluated sperm head features, as well as cleavage and blastocyst rates. A principal component analysis revealed three main components (factors) that represented almost 89% of the cumulative variance. In addition, an association of factor scores with cleavage (factor 1) and blastocyst (factor 3) rates was observed. In conclusion, several sperm traits were simultaneously altered as a result of a thermal insult. These sperm traits likely play specific roles in IVF and embryonic development. Copyright © 2016 Elsevier Inc. All rights reserved.

The DASS-14: Improving the Construct Validity and Reliability of the Depression, Anxiety, and Stress Scale in a Cohort of Health Professionals.

PubMed

Wise, Frances M; Harris, Darren W; Olver, John H

2017-01-01

Considerable research has been undertaken in evaluating the DASS-21 in a variety of clinical populations, but studies of the instrument's psychometric adequacy in healthcare professionals is lacking. This study aimed to establish and improve the construct validity and reliability of the DASS-21 in a cohort of Australian health professionals. 343 rehabilitation health professionals completed the DASS-21, along with a demographic questionnaire. Principal components analysis was performed to identify potential factors in the DASS-21. Factors were interpreted against theoretical constructs underlying the instrument. Items loading on separate factors were then subjected to reliability analysis to determine internal consistency of subscales. Items that demonstrated poor fit, or loaded onto more than one factor, were deleted to maximise the reliability of each subscale. Principal components analysis identified three dimensions (depression, anxiety, stress) in a modified version of the DASS-21 (renamed DASS-14), with appropriate construct validity and good reliability (a=0.73 to 0.88). The three dimensions accounted for over 62% of variance between items. The modified DASS-14 scale is a more parsimonious measure of depression, anxiety, and stress, with acceptable reliability and construct validity, in rehabilitation health professionals and is appropriate for use in studies of similar populations.

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

PubMed

Allegre, B; Therme, P

2008-10-01

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

Dimensions of patient satisfaction with comprehensive abortion care in Addis Ababa, Ethiopia.

PubMed

Mossie Chekol, Bekalu; Abera Abdi, Dame; Andualem Adal, Tamirie

2016-12-07

Patient satisfaction is a measure of the extent to which a patient is content with the health care received from health care providers. It has been recognized as one of the most vital indicators of quality. Hence, it has been studied and measured extensively as part of service quality and as a standalone construct. In spite of this, there has been limited or no studies in Ethiopia that describe factors of abortion care contributed to women's satisfaction. This study aimed to identifying the underlying factors that contribute to patient satisfaction with comprehensive abortion care and at exploring relationships between total satisfaction scores and socio-demographic and care-related variables in Addis Ababa, Ethiopia. At the beginning of the study in-depth interviews with 16 participants and a focus group discussion of 8 participants were conducted consecutively at the time of discharge to generate questions used to evaluate women's satisfaction with abortion care. Following generation of the perceived indicators, expert review, pilot study, and item analysis were performed in order to produce the reduced and better 26 items used to measure abortion care satisfaction. A total sample size of 450 participants from eight health facilities completed the survey. Principal component exploratory factor analysis and confirmatory factor analysis were conducted respectively to identify and confirm the factors of abortion care contributing to women's satisfaction. Mean satisfaction scores were compared across socio demographic and care-related variables such as age, educational level, gestational age (first trimester and second trimester), and facility type using analysis of variance. Exploratory factor analysis of the 26 items indicated that satisfaction with abortion care consisted of five main components accounting for 60.48% of the variance in total satisfaction scores. Factor loadings of all items were found to be greater than 0.4. These factors are named as follows: "art of care" which means interpersonal relationships with the care-provider, "physical environment" which means the perceived quality of physical surroundings in which care is delivered, including cleanliness of facilities and equipment, "information" which means the information received related to abortion procedures, "privacy and confidentiality", "quality of care" which refers to technical quality of the care provider. Furthermore, analysis of variance showed that overall satisfaction is found to be related to facility type, relationship status, gestational age, and procedural type. The findings provided support that women's satisfaction with comprehensive abortion care has five major factors. Therefore, to improve the overall quality of comprehensive abortion care, attention should be given to the advancement of these components namely, positive interpersonal communication with care-receiver, pleasantness of physical environment, offering enough information related to the procedure, securing clients' privacy during counseling and treatment, and technical quality of the providers.

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

PubMed

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

2007-07-01

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

Independent component analysis-based algorithm for automatic identification of Raman spectra applied to artistic pigments and pigment mixtures.

PubMed

González-Vidal, Juan José; Pérez-Pueyo, Rosanna; Soneira, María José; Ruiz-Moreno, Sergio

2015-03-01

A new method has been developed to automatically identify Raman spectra, whether they correspond to single- or multicomponent spectra. The method requires no user input or judgment. There are thus no parameters to be tweaked. Furthermore, it provides a reliability factor on the resulting identification, with the aim of becoming a useful support tool for the analyst in the decision-making process. The method relies on the multivariate techniques of principal component analysis (PCA) and independent component analysis (ICA), and on some metrics. It has been developed for the application of automated spectral analysis, where the analyzed spectrum is provided by a spectrometer that has no previous knowledge of the analyzed sample, meaning that the number of components in the sample is unknown. We describe the details of this method and demonstrate its efficiency by identifying both simulated spectra and real spectra. The method has been applied to artistic pigment identification. The reliable and consistent results that were obtained make the methodology a helpful tool suitable for the identification of pigments in artwork or in paint in general.

Effects of biotic and abiotic indices on long term soil moisture data in a grassland biodiversity experiment

NASA Astrophysics Data System (ADS)

Fischer, Christine; Hohenbrink, Tobias; Leimer, Sophia; Roscher, Christiane; Ravenek, Janneke; de Kroon, Hans; Kreutziger, Yvonne; Wirth, Christian; Eisenhauer, Nico; Gleixner, Gerd; Weigelt, Alexandra; Mommer, Liesje; Beßler, Holger; Schröder, Boris; Hildebrandt, Anke

2015-04-01

Soil moisture is the dynamic link between climate, soil and vegetation and the dynamics and variation are affected by several often interrelated factors such as soil texture, soil structural parameters (soil organic carbon) and vegetation parameters (belowground- and aboveground biomass). For the characterization and estimation of soil moisture and its variability and the resulting water fluxes and solute transports, the knowledge of the relative importance of these factors is of major challenge for hydrology and bioclimatology. Because of the heterogeneity of these factors, soil moisture varies strongly over time and space. Our objective was to assess the spatio-temporal variability of soil moisture and factors which could explain that variability, like soil properties and vegetation cover, in in a long term biodiversity experiment (Jena Experiment). The Jena Experiment consist 86 plots on which plant species richness (0, 1, 2, 4, 8, 16, and 60) and functional groups (legumes, grasses, tall herbs, and small herbs) were manipulated in a factorial design Soil moisture measurements were performed weekly April to September 2003-2005 and 2008-2013 using Delta T theta probe. Measurements were integrated to three depth intervals: 0.0 - 0.20, 0.20 - 0.40 and 0.40 - 0.70 m. We analyze the spatio-temporal patterns of soil water content on (i) the normalized time series and (ii) the first components obtained from a principal component analysis (PCA). Both were correlated with the design variables of the Jena Experiment (plant species richness and plant functional groups) and other influencing factors such as soil texture, soil structural variables and vegetation parameters. For the time stability of soil water content, the analysis showed that plots containing grasses was consistently drier than average at the soil surface in all observed years while plots containing legumes comparatively moister, but only up to the year 2008. In 0.40 - 0.70 m soil deep plots presence of small herbs led to higher than average soil moisture in some years (2008, 2012, 2013). Interestingly, plant species richness led to moister than average subsoil at the beginning of the experiment (2003 and 2004), which changed to lower than average up to the year 2010 in all depths. There was no effect of species diversity in the years since 2010, although species diversity generally increases leaf area index and aboveground biomass. The first component from the PCA analysis described the mean behavior in time of all soil moisture time series. The second component reflected the impact of soil depth. The first two components explained 76% of the data set total variance. The third component is linked to plant species richness and explained about 4 % of the total variance of soil moisture data. The fourth component, which explained 2.4 %, showed a high correlation to soil texture. Within this study we investigate the dominant factors controlling spatio-temporal patterns of soil moisture at several soil depths. Although climate and soil depths were the most important drivers, other factors like plant species richness and soil texture affected the temporal variation while certain plant functional groups were important for the spatial variability.

Identification of regional activation by factorization of high-density surface EMG signals: A comparison of Principal Component Analysis and Non-negative Matrix factorization.

PubMed

Gallina, Alessio; Garland, S Jayne; Wakeling, James M

2018-05-22

In this study, we investigated whether principal component analysis (PCA) and non-negative matrix factorization (NMF) perform similarly for the identification of regional activation within the human vastus medialis. EMG signals from 64 locations over the VM were collected from twelve participants while performing a low-force isometric knee extension. The envelope of the EMG signal of each channel was calculated by low-pass filtering (8 Hz) the monopolar EMG signal after rectification. The data matrix was factorized using PCA and NMF, and up to 5 factors were considered for each algorithm. Association between explained variance, spatial weights and temporal scores between the two algorithms were compared using Pearson correlation. For both PCA and NMF, a single factor explained approximately 70% of the variance of the signal, while two and three factors explained just over 85% or 90%. The variance explained by PCA and NMF was highly comparable (R > 0.99). Spatial weights and temporal scores extracted with non-negative reconstruction of PCA and NMF were highly associated (all p < 0.001, mean R > 0.97). Regional VM activation can be identified using high-density surface EMG and factorization algorithms. Regional activation explains up to 30% of the variance of the signal, as identified through both PCA and NMF. Copyright © 2018 Elsevier Ltd. All rights reserved.

Resolving the variability of CDOM fluorescence to differentiate the sources and fate of DOM in Lake Taihu and its tributaries.

PubMed

Yao, Xin; Zhang, Yunlin; Zhu, Guangwei; Qin, Boqiang; Feng, Longqing; Cai, Linlin; Gao, Guang

2011-01-01

Taihu Basin is the most developed area in China, which economic development has resulted in pollutants being produced and discharged into rivers and the lake. Lake Taihu is located in the center of the basin, which is characterized by a complex network of rivers and channels. To assess the sources and fate of dissolved organic matter (DOM) in surface waters, we determined the components and abundance of chromophoric dissolved organic matter (CDOM) within Lake Taihu and 66 of its tributaries, and 22 sites along transects from two main rivers. In Lake Taihu, there was a relative less spatial variation in CDOM absorption a(CDOM)(355) with a mean of 2.46 ± 0.69 m⁻¹ compared to the mean of 3.36 ± 1.77 m⁻¹ in the rivers. Two autochthonous tryptophan-like components (C1 and C5), two humic-like components (C2 and C3), and one autochthonous tyrosine-like component (C4) were identified using the parallel factor analysis (PARAFAC) model. The C2 and C3 had a direct relationship with a(CDOM)(355), dissolved organic carbon (DOC), and chemical oxygen demand (COD). The separation of lake samples from river samples, on both axes of the Principal Component Analysis (PCA), showed the difference in DOM fluorophores between these various environments. Components C1 and C5 concurrently showed positive factor 1 loadings, while C4 was close to the negative factor 1 axis. Components C2 and C3 showed positive second factor loadings. The major contribution of autochthonous tryptophan-like components to lake samples is due to the autochthonous production of CDOM in the lake ecosystems. The results also showed that the differences in geology and associated land use control CDOM dynamics, such as the high levels of CDOM with terrestrial characteristics in the northwestern upstream rivers and low levels of CDOM with increased microbial characteristics in the southwestern upstream rivers. Most of river samples from the downstream regions in the eastern and southeastern plains had a similar relative abundance of humic-like fluorescence, with less of the tryptophan-like and more of the tyrosine-like contributions than did samples from upstream regions. Copyright © 2010 Elsevier Ltd. All rights reserved.

Method for exploiting bias in factor analysis using constrained alternating least squares algorithms

DOEpatents

Keenan, Michael R.

2008-12-30

Bias plays an important role in factor analysis and is often implicitly made use of, for example, to constrain solutions to factors that conform to physical reality. However, when components are collinear, a large range of solutions may exist that satisfy the basic constraints and fit the data equally well. In such cases, the introduction of mathematical bias through the application of constraints may select solutions that are less than optimal. The biased alternating least squares algorithm of the present invention can offset mathematical bias introduced by constraints in the standard alternating least squares analysis to achieve factor solutions that are most consistent with physical reality. In addition, these methods can be used to explicitly exploit bias to provide alternative views and provide additional insights into spectral data sets.

In vitro analysis of allogeneic lymphocyte interaction. V. Identification and characterization of two components of allogeneic effect factor, one of which displays H-2-restricted helper activity and the other, T cell-growth factor activity.

PubMed

Delovitch, T L; Watson, J; Battistella, R; Harris, J F; Shaw, J; Paetkau, V

1981-01-01

An allogeneic effect factor (AEF) derived from mixed lymphocyte reaction (MLR) cultures of alloactivated A.SW (H-2s) responder T cells and irradiated A/WySn (H-2a) stimulator spleen cells helps an in vitro primary anti-erythrocyte plaque-forming cell PFC response of BALB/c nude spleen cels and also A/WySn but not A.SW T cell-depleted spleen cells. AEF activity is adsorbed by anti-Ik and anti-I-Ak but not by anti-I-Jk, anti-I-ECk, and anti-Is. Gel filtration of ACA 54 resolves AEF into two main components that which appear in the 50,000- to 70,000-mol wt (component I) and 30,000- to 35,000-mol wt (component II) regions, respectively. Component I has a mol wt of 68,000, elutes from DEAE-Sephacel at 0.05-0.1 M NaCl, and has an isoelectric point (pI) of 5.8. It helps A/WySn but not A.SW B cells and, therefore, is H-2 restricted. Component II is not H-2 restricted, because it helps both A.SW and A/WySn B cells. It also stimulates (a) the growth of a long-term cytotoxic cell line in vitro, (b) Con A-induced thymocyte mitogenesis, and (c) the generation of cytotoxic T cells. The latter three properties of component II are not shared by component I. In addition, component II elutes from DEAE-Sephacel at 0.15-0.2 M NaCl and has a pI of 4.3 and 4.9. Ia determinants and Ig VH, CH, L-chain, and idiotypic determinants are not present on either component I or component II. The properties of component II are identical to that of a T cell growth factor produced by Con A-stimulated spleen cells. It is suggested that the H-2-restricted component I of AEF might be an MLR-activated responder T cell-derived Ia alloantigen receptor.

Phenotypic and genetic structure of traits delineating personality disorder.

PubMed

Livesley, W J; Jang, K L; Vernon, P A

1998-10-01

The evidence suggests that personality traits are hierarchically organized with more specific or lower-order traits combining to form more generalized higher-order traits. Agreement exists across studies regarding the lower-order traits that delineate personality disorder but not the higher-order traits. This study seeks to identify the higher-order structure of personality disorder by examining the phenotypic and genetic structures underlying lower-order traits. Eighteen lower-order traits were assessed using the Dimensional Assessment of Personality Disorder-Basic Questionnaire in samples of 656 personality disordered patients, 939 general population subjects, and a volunteer sample of 686 twin pairs. Principal components analysis yielded 4 components, labeled Emotional Dysregulation, Dissocial Behavior, Inhibitedness, and Compulsivity, that were similar across the 3 samples. Multivariate genetic analyses also yielded 4 genetic and environmental factors that were remarkably similar to the phenotypic factors. Analysis of the residual heritability of the lower-order traits when the effects of the higher-order factors were removed revealed a substantial residual heritable component for 12 of the 18 traits. The results support the following conclusions. First, the stable structure of traits across clinical and nonclinical samples is consistent with dimensional representations of personality disorders. Second, the higher-order traits of personality disorder strongly resemble dimensions of normal personality. This implies that a dimensional classification should be compatible with normative personality. Third, the residual heritability of the lower-order traits suggests that the personality phenotypes are based on a large number of specific genetic components.

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

Fast, J; Zhang, Q; Tilp, A

Significantly improved returns in their aerosol chemistry data can be achieved via the development of a value-added product (VAP) of deriving OA components, called Organic Aerosol Components (OACOMP). OACOMP is primarily based on multivariate analysis of the measured organic mass spectral matrix. The key outputs of OACOMP are the concentration time series and the mass spectra of OA factors that are associated with distinct sources, formation and evolution processes, and physicochemical properties.

16S rRNA analysis provides evidence of biofilms on all components of three infected periprosthetic knees including permanent braided suture.

PubMed

Swearingen, Matthew C; DiBartola, Alex C; Dusane, Devendra; Granger, Jeffrey; Stoodley, Paul

2016-10-01

Bacterial biofilms are the main etiological agent of periprosthetic joint infections (PJI); however, it is unclear if biofilms colonize one or multiple components. Because biofilms can colonize a variety of surfaces, we hypothesized that biofilms would be present on all components. 16S ribosomal RNA (rRNA) gene sequencing analysis was used to identify bacteria recovered from individual components and non-absorbable suture material recovered from three PJI total knee revision cases. Bray-Curtis non-metric multidimensional scaling analysis revealed no significant differences in similarity when factoring component, material type, or suture versus non-suture material, but did reveal significant differences in organism profile between patients (P < 0.001) and negative controls (P < 0.001). Confocal microscopy and a novel agar encasement culturing method also confirmed biofilm growth on a subset of components. While 16S sequencing suggested that the microbiology was more complex than revealed by culture contaminating, bacterial DNA generates a risk of false positives. This report highlights that biofilm bacteria may colonize all infected prosthetic components including braided suture material, and provides further evidence that clinical culture can fail to sufficiently identify the full pathogen profile in PJI cases. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Metabolic Profiles Predict Adverse Events Following Coronary Artery Bypass Grafting

PubMed Central

Shah, Asad A.; Craig, Damian M.; Sebek, Jacqueline K.; Haynes, Carol; Stevens, Robert C.; Muehlbauer, Michael J.; Granger, Christopher B.; Hauser, Elizabeth R.; Newby, L. Kristin; Newgard, Christopher B.; Kraus, William E.; Hughes, G. Chad; Shah, Svati H.

2012-01-01

Objectives Clinical models incompletely predict outcomes following coronary artery bypass grafting. Novel molecular technologies may identify biomarkers to improve risk stratification. We examined whether metabolic profiles can predict adverse events in patients undergoing coronary artery bypass grafting. Methods The study population comprised 478 subjects from the CATHGEN biorepository of patients referred for cardiac catheterization who underwent coronary artery bypass grafting after enrollment. Targeted mass spectrometry-based profiling of 69 metabolites was performed in frozen, fasting plasma samples collected prior to surgery. Principal-components analysis and Cox proportional hazards regression modeling were used to assess the relation between metabolite factor levels and a composite outcome of post-coronary artery bypass grafting myocardial infarction, need for percutaneous coronary intervention, repeat coronary artery bypass grafting, or death. Results Over a mean follow-up of 4.3 ± 2.4 years, 126 subjects (26.4%) suffered an adverse event. Three principal-components analysis-derived factors were significantly associated with adverse outcome in univariable analysis: short-chain dicarboxylacylcarnitines (factor 2, P=0.001); ketone-related metabolites (factor 5, P=0.02); and short-chain acylcarnitines (factor 6, P=0.004). These three factors remained independently predictive of adverse outcome after multivariable adjustment: factor 2 (adjusted hazard ratio 1.23; 95% confidence interval [1.10-1.38]; P<0.001), factor 5 (1.17 [1.01-1.37], P=0.04), and factor 6 (1.14 [1.02-1.27], P=0.03). Conclusions Metabolic profiles are independently associated with adverse outcomes following coronary artery bypass grafting. These profiles may represent novel biomarkers of risk that augment existing tools for risk stratification of coronary artery bypass grafting patients and may elucidate novel biochemical pathways that mediate risk. PMID:22306227

Tracking variations in fluorescent-dissolved organic matter in an aerobic submerged membrane bioreactor using excitation-emission matrix spectra combined with parallel factor analysis.

PubMed

Hur, Jin; Shin, Jaewon; Kang, Minsun; Cho, Jinwoo

2014-08-01

In this study, the variations in the fluorescent components of dissolved organic matter (DOM) were tracked for an aerobic submerged membrane bioreactor (MBR) at three different operation stages (cake layer formation, condensation, and after cleaning). The fluorescent DOM was characterized using excitation-emission matrix (EEM) spectroscopy combined with parallel factor analysis (PARAFAC). Non-aromatic carbon structures appear to be actively involved in the membrane fouling for the cake layer formation stage as revealed by much higher UV-absorbing DOM per organic carbon found in the effluent versus those inside the reactor. Four fluorescent components were successfully identified from the reactor and the effluent DOMs by EEM-PARAFAC modeling. Among those in the reactor, microbial humic-like fluorescence was the most abundant component at the cake layer formation stage and tryptophan-like fluorescence at the condensation stage. In contrast to the reactor, relatively similar composition of the PARAFAC components was exhibited for the effluent at all three stages. Tryptophan-like fluorescence displayed the largest difference between the reactor and the effluent, suggesting that this component could be a good tracer for membrane fouling. It appears that the fluorescent DOM was involved in membrane fouling by cake layer formation rather than by internal pore adsorption because its difference between the reactor and the effluent was the highest among all the four components, even after the membrane cleaning. Our study provided an insight into the fate and the behavior fluorescent DOM components for an MBR system, which could be an indicator of the membrane fouling.

Rank estimation and the multivariate analysis of in vivo fast-scan cyclic voltammetric data

PubMed Central

Keithley, Richard B.; Carelli, Regina M.; Wightman, R. Mark

2010-01-01

Principal component regression has been used in the past to separate current contributions from different neuromodulators measured with in vivo fast-scan cyclic voltammetry. Traditionally, a percent cumulative variance approach has been used to determine the rank of the training set voltammetric matrix during model development, however this approach suffers from several disadvantages including the use of arbitrary percentages and the requirement of extreme precision of training sets. Here we propose that Malinowski’s F-test, a method based on a statistical analysis of the variance contained within the training set, can be used to improve factor selection for the analysis of in vivo fast-scan cyclic voltammetric data. These two methods of rank estimation were compared at all steps in the calibration protocol including the number of principal components retained, overall noise levels, model validation as determined using a residual analysis procedure, and predicted concentration information. By analyzing 119 training sets from two different laboratories amassed over several years, we were able to gain insight into the heterogeneity of in vivo fast-scan cyclic voltammetric data and study how differences in factor selection propagate throughout the entire principal component regression analysis procedure. Visualizing cyclic voltammetric representations of the data contained in the retained and discarded principal components showed that using Malinowski’s F-test for rank estimation of in vivo training sets allowed for noise to be more accurately removed. Malinowski’s F-test also improved the robustness of our criterion for judging multivariate model validity, even though signal-to-noise ratios of the data varied. In addition, pH change was the majority noise carrier of in vivo training sets while dopamine prediction was more sensitive to noise. PMID:20527815

The engine fuel system fault analysis

NASA Astrophysics Data System (ADS)

Zhang, Yong; Song, Hanqiang; Yang, Changsheng; Zhao, Wei

2017-05-01

For improving the reliability of the engine fuel system, the typical fault factor of the engine fuel system was analyzed from the point view of structure and functional. The fault character was gotten by building the fuel system fault tree. According the utilizing of fault mode effect analysis method (FMEA), several factors of key component fuel regulator was obtained, which include the fault mode, the fault cause, and the fault influences. All of this made foundation for next development of fault diagnosis system.

Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

PubMed

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.

ROBNCA: robust network component analysis for recovering transcription factor activities.

PubMed

Noor, Amina; Ahmad, Aitzaz; Serpedin, Erchin; Nounou, Mohamed; Nounou, Hazem

2013-10-01

Network component analysis (NCA) is an efficient method of reconstructing the transcription factor activity (TFA), which makes use of the gene expression data and prior information available about transcription factor (TF)-gene regulations. Most of the contemporary algorithms either exhibit the drawback of inconsistency and poor reliability, or suffer from prohibitive computational complexity. In addition, the existing algorithms do not possess the ability to counteract the presence of outliers in the microarray data. Hence, robust and computationally efficient algorithms are needed to enable practical applications. We propose ROBust Network Component Analysis (ROBNCA), a novel iterative algorithm that explicitly models the possible outliers in the microarray data. An attractive feature of the ROBNCA algorithm is the derivation of a closed form solution for estimating the connectivity matrix, which was not available in prior contributions. The ROBNCA algorithm is compared with FastNCA and the non-iterative NCA (NI-NCA). ROBNCA estimates the TF activity profiles as well as the TF-gene control strength matrix with a much higher degree of accuracy than FastNCA and NI-NCA, irrespective of varying noise, correlation and/or amount of outliers in case of synthetic data. The ROBNCA algorithm is also tested on Saccharomyces cerevisiae data and Escherichia coli data, and it is observed to outperform the existing algorithms. The run time of the ROBNCA algorithm is comparable with that of FastNCA, and is hundreds of times faster than NI-NCA. The ROBNCA software is available at http://people.tamu.edu/∼amina/ROBNCA

Finding Imaging Patterns of Structural Covariance via Non-Negative Matrix Factorization

PubMed Central

Sotiras, Aristeidis; Resnick, Susan M.; Davatzikos, Christos

2015-01-01

In this paper, we investigate the use of Non-Negative Matrix Factorization (NNMF) for the analysis of structural neuroimaging data. The goal is to identify the brain regions that co-vary across individuals in a consistent way, hence potentially being part of underlying brain networks or otherwise influenced by underlying common mechanisms such as genetics and pathologies. NNMF offers a directly data-driven way of extracting relatively localized co-varying structural regions, thereby transcending limitations of Principal Component Analysis (PCA), Independent Component Analysis (ICA) and other related methods that tend to produce dispersed components of positive and negative loadings. In particular, leveraging upon the well known ability of NNMF to produce parts-based representations of image data, we derive decompositions that partition the brain into regions that vary in consistent ways across individuals. Importantly, these decompositions achieve dimensionality reduction via highly interpretable ways and generalize well to new data as shown via split-sample experiments. We empirically validate NNMF in two data sets: i) a Diffusion Tensor (DT) mouse brain development study, and ii) a structural Magnetic Resonance (sMR) study of human brain aging. We demonstrate the ability of NNMF to produce sparse parts-based representations of the data at various resolutions. These representations seem to follow what we know about the underlying functional organization of the brain and also capture some pathological processes. Moreover, we show that these low dimensional representations favorably compare to descriptions obtained with more commonly used matrix factorization methods like PCA and ICA. PMID:25497684

Whole-body patterns of the range of joint motion in young adults: masculine type and feminine type.

PubMed

Moromizato, Keiichi; Kimura, Ryosuke; Fukase, Hitoshi; Yamaguchi, Kyoko; Ishida, Hajime

2016-10-01

Understanding the whole-body patterns of joint flexibility and their related biological and physical factors contributes not only to clinical assessments but also to the fields of human factors and ergonomics. In this study, ranges of motion (ROMs) at limb and trunk joints of young adults were analysed to understand covariation patterns of different joint motions and to identify factors associated with the variation in ROM. Seventy-eight healthy volunteers (42 males and 36 females) living on Okinawa Island, Japan, were recruited. Passive ROM was measured at multiple joints through the whole body (31 measurements) including the left and right side limbs and trunk. Comparisons between males and females, dominant and non-dominant sides, and antagonistic motions indicated that body structures influence ROMs. In principal component analysis (PCA) on the ROM data, the first principal component (PC1) represented the sex difference and a similar covariation pattern appeared in the analysis within each sex. Multiple regression analysis showed that this component was associated with sex, age, body fat %, iliospinale height, and leg extension strength. The present study identified that there is a spectrum of "masculine" and "feminine" types in the whole-body patterns of joint flexibility. This study also suggested that body proportion and composition, muscle mass and strength, and possibly skeletal structures partly explain such patterns. These results would be important to understand individual variation in susceptibility to joint injuries and diseases and in one's suitable and effective postures and motions.

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

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

An Analysis of Digital Inclusion Projects: Three Crucial Factors and Four Key Components

ERIC Educational Resources Information Center

Smith, Chris

2015-01-01

This paper provides an in-depth analysis into two case studies aimed at addressing the digital divide in two developing countries. A detailed description is provided for each case study along with an analysis of how successful the two projects were at addressing the digital divide in Siyabuswa, South Africa and Ennis, Ireland. The two case studies…

The Shock and Vibration Digest. Volume 16, Number 1

DTIC Science & Technology

1984-01-01

investigation of the measure- ment of frequency band average loss factors of structural components for use in the statistical energy analysis method of...stiffness. Matrix methods Key Words: Finite element technique. Statistical energy analysis . Experimental techniques. Framed structures, Com- puter...programs In order to further understand the practical application of the statistical energy analysis , a two section plate-like frame structure is

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

NASA Astrophysics Data System (ADS)

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.

Public knowledge and beliefs about depression among urban and rural Malays in Malaysia.

PubMed

Swami, Viren; Loo, Phik-Wern; Furnham, Adrian

2010-09-01

This study examined knowledge and beliefs about depression among Malaysian Malays varying in socioeconomic status. A total of 153 urban and 189 rural participants completed a questionnaire in which they had to identify two cases of depression and rate a series of items about the causes and best treatments for depression. Results showed that urban participants were more likely to use psychiatric labels ('depression') for the two vignettes, whereas rural participants tended to use more generic terms ('emotional stress'). Principal components analysis (PCA) showed that beliefs about the causes of depression factored into five components, of which stressful life events was most strongly endorsed by both groups. PCA of treatment items revealed four stable components, of which religious factors were most strongly endorsed. There were also a number of significant between-group differences in the endorsement of these factors (eta(p) (2) = .03-.11), with rural participants generally rating supernatural and religious factors more strongly than urban Malays. These results are discussed in relation to mental health literacy programmes in Malaysia.

Quantitative descriptive analysis and principal component analysis for sensory characterization of Indian milk product cham-cham.

PubMed

Puri, Ritika; Khamrui, Kaushik; Khetra, Yogesh; Malhotra, Ravinder; Devraja, H C

2016-02-01

Promising development and expansion in the market of cham-cham, a traditional Indian dairy product is expected in the coming future with the organized production of this milk product by some large dairies. The objective of this study was to document the extent of variation in sensory properties of market samples of cham-cham collected from four different locations known for their excellence in cham-cham production and to find out the attributes that govern much of variation in sensory scores of this product using quantitative descriptive analysis (QDA) and principal component analysis (PCA). QDA revealed significant (p < 0.05) difference in sensory attributes of cham-cham among the market samples. PCA identified four significant principal components that accounted for 72.4 % of the variation in the sensory data. Factor scores of each of the four principal components which primarily correspond to sweetness/shape/dryness of interior, surface appearance/surface dryness, rancid and firmness attributes specify the location of each market sample along each of the axes in 3-D graphs. These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring attributes of cham-cham that contribute most to its sensory acceptability.

Self-efficacy difference among patients with cancer with different socioeconomic status: application of latent class analysis and standardization and decomposition analysis.

PubMed

Yuan, Changrong; Wei, Chunlan; Wang, Jichuan; Qian, Huijuan; Ye, Xianghong; Liu, Yingyan; Hinds, Pamela S

2014-06-01

Although the relationship between partial socioeconomic status (SES) and self-efficacy has been studied in previous studies, few research have examined self-efficacy difference among patients with cancer with different SES. A cross-sectional survey involving 764 patients with cancer was completed. Latent class analysis (LCA) was applied to identify distinct groups of patients with cancer using four SES indicators (education, income, employment status and health insurance status). Standardization and decomposition analysis (SDA) was then used to examine differences in patients' self-efficacy among SES groups and the components of the differences attributed to confounding factors, such as gender, age, anxiety, depression and social support. Participants were classified into four distinctive SES groups via using LCA method, and the observed self-efficacy level significantly varied by SES groups; as theorized, higher self-efficacy was associated with higher SES. The self-efficacy differences by SES groups were decomposed into "real" group differences and factor component effects that are attributed to group differences in confounding factor compositions. Self-efficacy significantly varies by SES. Social support significantly confounded the observed differences in self-efficacy between different SES groups among Chinese patients with cancer. Copyright © 2014 Elsevier Ltd. All rights reserved.

Psychometric Properties of a Screening Instrument for Domestic Violence in a Sample of Iranian Women

PubMed Central

Azadarmaki, Taghi; Kassani, Aziz; Menati, Rostam; Hassanzadeh, Jafar; Menati, Walieh

2016-01-01

Background Domestic violence against women is regarded as an important health problem among women and a serious concern in issues related to human rights. To date, a few screening tools for domestic violence exist for Iranian married women, but they assess only some of the domestic violence components. Objectives The present study aimed to design and determine the validity and reliability of a screening instrument for domestic violence in a sample of Iranian women. Materials and Methods The present study was a cross-sectional psychometric evaluation conducted on 350 married women in Ilam, Iran, in 2014. The samples were selected through multistage sampling and the main method was cluster sampling. A 20-item, self-administered questionnaire was validated by exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). An Eigen value > 1 and a loading factor > 0.3 for each component were considered as indices for extracting domestic violence components. Reliability was calculated by test-retest and Cronbach’s alpha. Also, the content validity index (CVI) and content validity ratio (CVR) were used to measure content validity. The data were analyzed using SPSS-13 and LISREL 8.8 software programs. Results The self-administered instrument was completed by 334 women. The CFA and EFA methods confirmed embedding items and the three-factor structure of the instrument including psychological, physical, and sexual violence, which explained 66% of the total variance of the domestic violence. The ICC and Cronbach’s alpha coefficients were > 0.7 for the components of the questionnaire. The test-retest also revealed strong correlations for each of the domestic violence components (r > 0.6). Conclusions The used instrument for measuring domestic violence had desirable validity and reliability and can be used as a suitable instrument in health and social researches in the local population. PMID:27331052

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

ERIC Educational Resources Information Center

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

2001-01-01

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

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

ERIC Educational Resources Information Center

Buchanan, Tom; Sainter, Phillip; Saunders, Gunter

2013-01-01

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

A Network Pharmacology Approach to Determine the Active Components and Potential Targets of Curculigo Orchioides in the Treatment of Osteoporosis.

PubMed

Wang, Nani; Zhao, Guizhi; Zhang, Yang; Wang, Xuping; Zhao, Lisha; Xu, Pingcui; Shou, Dan

2017-10-27

BACKGROUND Osteoporosis is a complex bone disorder with a genetic predisposition, and is a cause of health problems worldwide. In China, Curculigo orchioides (CO) has been widely used as a herbal medicine in the prevention and treatment of osteoporosis. However, research on the mechanism of action of CO is still lacking. The aim of this study was to identify the absorbable components, potential targets, and associated treatment pathways of CO using a network pharmacology approach. MATERIAL AND METHODS We explored the chemical components of CO and used the five main principles of drug absorption to identify absorbable components. Targets for the therapeutic actions of CO were obtained from the PharmMapper server database. Pathway enrichment analysis was performed using the Comparative Toxicogenomics Database (CTD). Cytoscape was used to visualize the multiple components-multiple target-multiple pathways-multiple disease network for CO. RESULTS We identified 77 chemical components of CO, of which 32 components could be absorbed in the blood. These potential active components of CO regulated 83 targets and affected 58 pathways. Data analysis showed that the genes for estrogen receptor alpha (ESR1) and beta (ESR2), and the gene for 11 beta-hydroxysteroid dehydrogenase type 1, or cortisone reductase (HSD11B1) were the main targets of CO. Endocrine regulatory factors and factors regulating calcium reabsorption, steroid hormone biosynthesis, and metabolic pathways were related to these main targets and to ten corresponding compounds. CONCLUSIONS The network pharmacology approach used in our study has attempted to explain the mechanisms for the effects of CO in the prevention and treatment of osteoporosis, and provides an alternative approach to the investigation of the effects of this complex compound.

Relationship between soluble microbial products (SMP) and effluent organic matter (EfOM): characterized by fluorescence excitation emission matrix coupled with parallel factor analysis.

PubMed

Yu, Huarong; Qu, Fangshu; Sun, Lianpeng; Liang, Heng; Han, Zhengshuang; Chang, Haiqing; Shao, Senlin; Li, Guibai

2015-02-01

Effluent organic matter (EfOM) originating from wastewater treatment plant (WWTP) is of significant concern, as it not only influences the discharge quality of WWTP but also exerts a significant effect on the efficiency of the downstream advanced treatment facilities. Soluble microbial products (SMP) is a major part of EfOM. In order to further understand the relationship between soluble microbial products (SMP) and EfOM, and in turn, to propose measures for EfOM control, the formation of SMP and EfOM in identical activated sludge sequencing batch reactors (SBR) with different feed water was investigated using fluorescence excitation and emission spectroscopy matrix coupled with parallel factor analysis (EEM-PARAFAC) as well as other organic matter quantification tools. Results showed that EfOM contained not only SMP but also a considerable amount of allochthonous organic matter that derived not merely from natural organic matter (NOM). Four components in EfOM/SMP were identified by EEM-PARAFAC. Tyrosine-like substances in EfOM (Component 3, λex/em=270/316 nm) were mainly originated from utilization associated products (UAP) of SMP. Tryptophan-like substances (Component 2, λex/em=280/336 nm) as well as fulvic-like and humic-like substances in EfOM (Component 1, λex/em=240(290)/392 nm and Component 4, λex/em=260(365)/444 nm) were majorly derived from the refractory substances introduced along with the influent, among which Component 2 was stemmed from sources other than NOM. As solid retention time (SRT) increased, Component 2 and polysaccharides in SMP/EfOM decreased, while Component 4 in SMP increased. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

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 < 0.01, n = 180). Soil TN, soil pH, soil Olsen P, and soil water content and the interactions between them were the main factors affecting P loss with surface 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.

Fast characterization of cheeses by dynamic headspace-mass spectrometry.

PubMed

Pérès, Christophe; Denoyer, Christian; Tournayre, Pascal; Berdagué, Jean-Louis

2002-03-15

This study describes a rapid method to characterize cheeses by analysis of their volatile fraction using dynamic headspace-mass spectrometry. Major factors governing the extraction and concentration of the volatile components were first studied. These components were extracted from the headspace of the cheeses in a stream of helium and concentrated on a Tenax TA trap. They were then desorbed by heating and injected directly into the source of a mass spectrometer via a short deactivated silica transfer line. The mass spectra of the mixture of volatile components were considered as fingerprints of the analyzed substances. Forward stepwise factorial discriminant analysis afforded a limited number of characteristic mass fragments that allowed a good classification of the batches of cheeses studied.

Tissue and cell-type co-expression networks of transcription factors and wood component genes in Populus trichocarpa.

PubMed

Shi, Rui; Wang, Jack P; Lin, Ying-Chung; Li, Quanzi; Sun, Ying-Hsuan; Chen, Hao; Sederoff, Ronald R; Chiang, Vincent L

2017-05-01

Co-expression networks based on transcriptomes of Populus trichocarpa major tissues and specific cell types suggest redundant control of cell wall component biosynthetic genes by transcription factors in wood formation. We analyzed the transcriptomes of five tissues (xylem, phloem, shoot, leaf, and root) and two wood forming cell types (fiber and vessel) of Populus trichocarpa to assemble gene co-expression subnetworks associated with wood formation. We identified 165 transcription factors (TFs) that showed xylem-, fiber-, and vessel-specific expression. Of these 165 TFs, 101 co-expressed (correlation coefficient, r > 0.7) with the 45 secondary cell wall cellulose, hemicellulose, and lignin biosynthetic genes. Each cell wall component gene co-expressed on average with 34 TFs, suggesting redundant control of the cell wall component gene expression. Co-expression analysis showed that the 101 TFs and the 45 cell wall component genes each has two distinct groups (groups 1 and 2), based on their co-expression patterns. The group 1 TFs (44 members) are predominantly xylem and fiber specific, and are all highly positively co-expressed with the group 1 cell wall component genes (30 members), suggesting their roles as major wood formation regulators. Group 1 TFs include a lateral organ boundary domain gene (LBD) that has the highest number of positively correlated cell wall component genes (36) and TFs (47). The group 2 TFs have 57 members, including 14 vessel-specific TFs, and are generally less correlated with the cell wall component genes. An exception is a vessel-specific basic helix-loop-helix (bHLH) gene that negatively correlates with 20 cell wall component genes, and may function as a key transcriptional suppressor. The co-expression networks revealed here suggest a well-structured transcriptional homeostasis for cell wall component biosynthesis during wood formation.

Metabolic syndrome: An independent risk factor for erectile dysfunction

PubMed Central

Sanjay, Saran; Bharti, Gupta Sona; Manish, Gutch; Rajeev, Philip; Pankaj, Agrawal; Puspalata, Agroiya; Keshavkumar, Gupta

2015-01-01

Objective: The objective was to determine the role of various components of metabolic syndrome (MetS) as independent risk factor for erectile dysfunction (ED). Materials and Methods: A total of 113 subjects of MetS, as recommended by recent IDF and AHA/NHLBI joint interim statement were selected for study who presented for ED. After doing Anthropometric examination, fasting laboratory assay for fasting plasma glucose (FPG), fasting insulin, hemoglobin A1c, triglyceride (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and 2 h oral glucose tolerance test (OGTT) was done. Erectile function was assessed by completing questions one through five of the International Index of Erectile Function (IIEF-5). A multiple linear regression analysis was carried out on 66 subjects with IIEF-5 score as dependent variable and components of MetS FPG, 2 h OGTT, TG, HDL, and waist circumference as independent variables. Results: Using a multiple linear regression analysis, we observed that presence of the various components of MetS was associated with ED and a decrease IIEF-5 score and this effect was greater than the effect associated with any of the individual components. Of the individual components of the MetS, HDL (B = 0.136; P = 0.004) and FPG (B = −0.069; P = 0.007) conferred the strongest effect on IIEF-5 score. However, overall age had most significant effect on IIEF-5 score. Conclusion: It is crucial to formulate strategies and implement them to prevent or control the epidemic of the MetS and its consequences. The early identification and treatment of risk factors might be helpful to prevent ED and secondary cardiovascular disease, including diet and lifestyle interventions. PMID:25729692

Metabolic syndrome: An independent risk factor for erectile dysfunction.

PubMed

Sanjay, Saran; Bharti, Gupta Sona; Manish, Gutch; Rajeev, Philip; Pankaj, Agrawal; Puspalata, Agroiya; Keshavkumar, Gupta

2015-01-01

The objective was to determine the role of various components of metabolic syndrome (MetS) as independent risk factor for erectile dysfunction (ED). A total of 113 subjects of MetS, as recommended by recent IDF and AHA/NHLBI joint interim statement were selected for study who presented for ED. After doing Anthropometric examination, fasting laboratory assay for fasting plasma glucose (FPG), fasting insulin, hemoglobin A1c, triglyceride (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and 2 h oral glucose tolerance test (OGTT) was done. Erectile function was assessed by completing questions one through five of the International Index of Erectile Function (IIEF-5). A multiple linear regression analysis was carried out on 66 subjects with IIEF-5 score as dependent variable and components of MetS FPG, 2 h OGTT, TG, HDL, and waist circumference as independent variables. Using a multiple linear regression analysis, we observed that presence of the various components of MetS was associated with ED and a decrease IIEF-5 score and this effect was greater than the effect associated with any of the individual components. Of the individual components of the MetS, HDL (B = 0.136; P = 0.004) and FPG (B = -0.069; P = 0.007) conferred the strongest effect on IIEF-5 score. However, overall age had most significant effect on IIEF-5 score. It is crucial to formulate strategies and implement them to prevent or control the epidemic of the MetS and its consequences. The early identification and treatment of risk factors might be helpful to prevent ED and secondary cardiovascular disease, including diet and lifestyle interventions.

Motivations and self-presentation strategies on Korean-based "Cyworld" weblog format personal homepages.

PubMed

Jung, Taejin; Youn, Hyunsook; McClung, Steven

2007-02-01

The main purposes of this study are to find out individuals' motives and interpersonal self-presentation strategies on constructing Korean weblog format personal homepage (e.g., "Cyworld mini-homepage"). The study also attempts to find predictor motives that lead to the activities of posting and maintaining a homepage and compare the self-presentation strategies used on the Web with those commonly used in interpersonal situations. By using a principal component factor analysis, four salient self-presentation strategy factors and five interpretable mini-homepage hosting motive factors were identified. Accompanying multiple regression analysis shows that entertainment and personal income factors are major predictors in explaining homepage maintenance expenditures and frequencies of updating.

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

NASA Technical Reports Server (NTRS)

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

1974-01-01

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

Local and regional components of aerosol in a heavily trafficked street canyon in central London derived from PMF and cluster analysis of single-particle ATOFMS spectra.

PubMed

Giorio, Chiara; Tapparo, Andrea; Dall'Osto, Manuel; Beddows, David C S; Esser-Gietl, Johanna K; Healy, Robert M; Harrison, Roy M

2015-03-17

Positive matrix factorization (PMF) has been applied to single particle ATOFMS spectra collected on a six lane heavily trafficked road in central London (Marylebone Road), which well represents an urban street canyon. PMF analysis successfully extracted 11 factors from mass spectra of about 700,000 particles as a complement to information on particle types (from K-means cluster analysis). The factors were associated with specific sources and represent the contribution of different traffic related components (i.e., lubricating oils, fresh elemental carbon, organonitrogen and aromatic compounds), secondary aerosol locally produced (i.e., nitrate, oxidized organic aerosol and oxidized organonitrogen compounds), urban background together with regional transport (aged elemental carbon and ammonium) and fresh sea spray. An important result from this study is the evidence that rapid chemical processes occur in the street canyon with production of secondary particles from road traffic emissions. These locally generated particles, together with aging processes, dramatically affected aerosol composition producing internally mixed particles. These processes may become important with stagnant air conditions and in countries where gasoline vehicles are predominant and need to be considered when quantifying the impact of traffic emissions.

Characterization of dissolved organic matter in Dongjianghu Lake by UV-visible absorption spectroscopy with multivariate analysis.

PubMed

Zhu, Yanzhong; Song, Yonghui; Yu, Huibin; Liu, Ruixia; Liu, Lusan; Lv, Chunjian

2017-08-08

UV-visible absorption spectroscopy coupled with principal component analysis (PCA) and hierarchical cluster analysis (HCA) was applied to characterize spectroscopic components, detect latent factors, and investigate spatial variations of dissolved organic matter (DOM) in a large-scale lake. Twelve surface water samples were collected from Dongjianghu Lake in China. DOM contained lignin and quinine moieties, carboxylic acid, microbial products, and aromatic and alkyl groups, which in the northern part of the lake was largely different from the southern part. Fifteen spectroscopic indices were deduced from the absorption spectra to indicate molecular weight or humification degree of DOM. The northern part of the lake presented the smaller molecular weight or the lower humification degree of DOM than the southern part. E 2/4 , E 3/4 , E 2/3 , and S 2 were latent factors of characterizing the molecular weight of DOM, while E 2/5 , E 3/5 , E 2/6 , E 4/5 , E 3/6 , and A 2/1 were latent factors of evaluating the humification degree of DOM. The UV-visible absorption spectroscopy combined with PCA and HCA may not only characterize DOM fractions of lakes, but may be transferred to other types of waterscape.

Factor analytic reduction of the carotid-cardiac baroreflex parameters

NASA Technical Reports Server (NTRS)

Ludwig, David A.

1989-01-01

An accepted method for measuring the responsiveness of the carotid-cardiac baroreflex to arterial pressure changes is to artificially stimulate the baroreceptors in the neck. This is accomplished by using a pressurized neck cuff which constricts and distends the carotid artery and subsequently stimulates the baroreceptors. Nine physiological responses to this type of stimulation are quantified and used as indicators of the baroreflex. Thirty male humans between the ages 27 and 46 underwent the carotid-cardiac baroreflex test. The data for the nine response parameters were analyzed by principle component factor analysis. The results of this analysis indicated that 93 percent of the total variance across all nine parameters could be explained in four dimensions. Examination of the factor loadings following an orthogonal rotation of the principle components indicated four well defined dimensions. The first two dimensions reflected location points for R-R interval and carotid distending pressure respectively. The third dimension was composed of measures reflecting the gain of the reflex. The fourth dimension was the ratio of the resting R-R interval to R-R interval during simulated hypertension. The data suggests that the analysis of all nine baroreflex parameters is redundant.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-12-01

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

Finite element analysis of 2-Station hip himulator

NASA Astrophysics Data System (ADS)

Fazli, M. I. M.; Yahya, A.; Shahrom, A.; Nawawi, S. W.; Zainudin, M. R.; Nazarudin, M. S.

2017-10-01

This paper presented the analysis of materials and design architecture of 2-station hip simulator. Hip simulator is a machine used to conduct the joint and wear test of hip prosthetic. In earlier work, the hip simulator was modified and some improvement were made by using SolidWorks software. The simulator consists of 3DOF which controlled by separate stepper motor and a static load that set up by manual method in each station. In this work, finite element analysis (FEA) of hip simulator was implemented to analyse the structure of the design and selected materials used for simulator component. The analysis is completed based on two categories which are safety factor and stress tests. Both design drawing and FEA was done using SolidWorks software. The study of the two categories is performed by applying the peak load up to 4000N on the main frame that is embedded with metal-on-metal hip prosthesis. From FEA, the value of safety factor and degree of stress formation are successfully obtained. All the components exceed the value of 2 for safety factor analysis while the degree of stress formation shows higher value compare to the yield strength of the material. With this results, it provides information regarding part of simulator which are susceptible to destruct. Besides, the results could be used for design improvement and certify the stability of the hip simulator in real application.

Characterizing fluorescent dissolved organic matter in a membrane bioreactor via excitation-emission matrix combined with parallel factor analysis.

PubMed

Maqbool, Tahir; Quang, Viet Ly; Cho, Jinwoo; Hur, Jin

2016-06-01

In this study, we successfully tracked the dynamic changes in different constitutes of bound extracellular polymeric substances (bEPS), soluble microbial products (SMP), and permeate during the operation of bench scale membrane bioreactors (MBRs) via fluorescence excitation-emission matrix (EEM) combined with parallel factor analysis (PARAFAC). Three fluorescent groups were identified, including two protein-like (tryptophan-like C1 and tyrosine-like C2) and one microbial humic-like components (C3). In bEPS, protein-like components were consistently more dominant than C3 during the MBR operation, while their relative abundance in SMP depended on aeration intensities. C1 of bEPS exhibited a linear correlation (R(2)=0.738; p<0.01) with bEPS amounts in sludge, and C2 was closely related to the stability of sludge. The protein-like components were more greatly responsible for membrane fouling. Our study suggests that EEM-PARAFAC can be a promising monitoring tool to provide further insight into process evaluation and membrane fouling during MBR operation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparative Analysis of Metabolic Syndrome Components in over 15,000 African Americans Identifies Pleiotropic Variants: Results from the PAGE Study

PubMed Central

Carty, Cara L.; Bhattacharjee, Samsiddhi; Haessler, Jeff; Cheng, Iona; Hindorff, Lucia A.; Aroda, Vanita; Carlson, Christopher S.; Hsu, Chun-Nan; Wilkens, Lynne; Liu, Simin; Selvin, Elizabeth; Jackson, Rebecca; North, Kari E.; Peters, Ulrike; Pankow, James S.; Chatterjee, Nilanjan; Kooperberg, Charles

2014-01-01

Background Metabolic syndrome (MetS) refers to the clustering of cardio-metabolic risk factors including dyslipidemia, central adiposity, hypertension and hyperglycemia in individuals. Identification of pleiotropic genetic factors associated with MetS traits may shed light on key pathways or mediators underlying MetS. Methods and Results Using the Metabochip array in 15,148 African Americans (AA) from the PAGE Study, we identify susceptibility loci and investigate pleiotropy among genetic variants using a subset-based meta-analysis method, ASsociation-analysis-based-on-subSETs (ASSET). Unlike conventional models which lack power when associations for MetS components are null or have opposite effects, ASSET uses one-sided tests to detect positive and negative associations for components separately and combines tests accounting for correlations among components. With ASSET, we identify 27 SNPs in 1 glucose and 4 lipids loci (TCF7L2, LPL, APOA5, CETP, LPL, APOC1/APOE/TOMM40) significantly associated with MetS components overall, all P< 2.5e-7, the Bonferroni adjusted P-value. Three loci replicate in a Hispanic population, n=5172. A novel AA-specific variant, rs12721054/APOC1, and rs10096633/LPL are associated with ≥3 MetS components. We find additional evidence of pleiotropy for APOE, TOMM40, TCF7L2 and CETP variants, many with opposing effects; e.g. the same rs7901695/TCF7L2 allele is associated with increased odds of high glucose and decreased odds of central adiposity. Conclusions We highlight a method to increase power in large-scale genomic association analyses, and report a novel variant associated with all MetS components in AA. We also identify pleiotropic associations that may be clinically useful in patient risk profiling and for informing translational research of potential gene targets and medications. PMID:25023634

Validating a Cantonese short version of the Zarit Burden Interview (CZBI-Short) for dementia caregivers.

PubMed

Tang, Jennifer Yee-Man; Ho, Andy Hau-Yan; Luo, Hao; Wong, Gloria Hoi-Yan; Lau, Bobo Hi-Po; Lum, Terry Yat-Sang; Cheung, Karen Siu-Lan

2016-09-01

The present study aimed to develop and validate a Cantonese short version of the Zarit Burden Interview (CZBI-Short) for Hong Kong Chinese dementia caregivers. The 12-item Zarit Burden Interview (ZBI) was translated into spoken Cantonese and back-translated by two bilingual research assistants and face validated by a panel of experts. Five hundred Chinese dementia caregivers showing signs of stress reported their burden using the translated ZBI and rated their depressive symptoms, overall health, and care recipients' physical functioning and behavioral problems. The factor structure of the translated scale was identified using principal component analysis and confirmatory factor analysis; internal consistency and item-total correlations were assessed; and concurrent validity was tested by correlating the ZBI with depressive symptoms, self-rated health, and care recipients' physical functioning and behavioral problems. The principal component analysis resulted in 11 items loading on a three-factor model comprised role strain, self-criticism, and negative emotion, which accounted for 59% of the variance. The confirmatory factor analysis supported the three-factor model (CZBI-Short) that explained 61% of the total variance. Cronbach's alpha (0.84) and item-total correlations (rho = 0.39-0.71) indicated CZBI-Short had good reliability. CZBI-Short showed correlations with depressive symptoms (r = 0.50), self-rated health (r = -0.26) and care recipients' physical functioning (r = 0.18-0.26) and disruptive behaviors (r = 0.36). The 12-item CZBI-Short is a concise, reliable, and valid instrument to assess burden in Chinese dementia caregivers in clinical and social care settings.

Attitudes of French-Canadian university students toward use of condoms: a structural analysis.

PubMed

Bernard, J; Hébert, Y; de Man, A; Farrar, D

1989-12-01

164 French-Canadian university students took part in a study analyzing the factorial pattern of attitudes toward the use of condoms. A principal component analysis identified 7 factors, namely, positive general attitude toward use of condoms, contraceptive security, inhibition of sexual pleasure, inconvenience, embarrassment, responsibility, and lessening of physical pleasure.

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale

PubMed Central

Sediyama, Cristina Y. N.; Moura, Ricardo; Garcia, Marina S.; da Silva, Antonio G.; Soraggi, Carolina; Neves, Fernando S.; Albuquerque, Maicon R.; Whiteside, Setephen P.; Malloy-Diniz, Leandro F.

2017-01-01

Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale. Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a) urgency, (b) lack of premeditation; (c) lack of perseverance; (d) sensation seeking. In the present study 384 participants (278 women and 106 men), who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis. Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years) scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach’s alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory. Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS. PMID:28484414

Public health laboratory quality management in a developing country.

PubMed

Wangkahat, Khwanjai; Nookhai, Somboon; Pobkeeree, Vallerut

2012-01-01

The article aims to give an overview of the system of public health laboratory quality management in Thailand and to produce a strengths, weaknesses, opportunities and threats (SWOT) analysis that is relevant to public health laboratories in the country. The systems for managing laboratory quality that are currently employed were described in the first component. The second component was a SWOT analysis, which used the opinions of laboratory professionals to identify any areas that could be improved to meet quality management systems. Various quality management systems were identified and the number of laboratories that met both international and national quality management requirements was different. The SWOT analysis found the opportunities and strengths factors offered the best chance to improve laboratory quality management in the country. The results are based on observations and brainstorming with medical laboratory professionals who can assist laboratories in accomplishing quality management. The factors derived from the analysis can help improve laboratory quality management in the country. This paper provides viewpoints and evidence-based approaches for the development of best possible practice of services in public health laboratories.

Assessment of sediment quality in the Mediterranean Sea-Boughrara lagoon exchange areas (southeastern Tunisia): GIS approach-based chemometric methods.

PubMed

Kharroubi, Adel; Gargouri, Dorra; Baati, Houda; Azri, Chafai

2012-06-01

Concentrations of selected heavy metals (Cd, Pb, Zn, Cu, Mn, and Fe) in surface sediments from 66 sites in both northern and eastern Mediterranean Sea-Boughrara lagoon exchange areas (southeastern Tunisia) were studied in order to understand current metal contamination due to the urbanization and economic development of nearby several coastal regions of the Gulf of Gabès. Multiple approaches were applied for the sediment quality assessment. These approaches were based on GIS coupled with chemometric methods (enrichment factors, geoaccumulation index, principal component analysis, and cluster analysis). Enrichment factors and principal component analysis revealed two distinct groups of metals. The first group corresponded to Fe and Mn derived from natural sources, and the second group contained Cd, Pb, Zn, and Cu originated from man-made sources. For these latter metals, cluster analysis showed two distinct distributions in the selected areas. They were attributed to temporal and spatial variations of contaminant sources input. The geoaccumulation index (I (geo)) values explained that only Cd, Pb, and Cu can be considered as moderate to extreme pollutants in the studied sediments.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-06-01

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

Analysis of Tourists Preferences on Smart Tourism in Yogyakarta (Case: Vredeburg Fort Museum)

NASA Astrophysics Data System (ADS)

Amanda, Rima; Santosa, PInsap; Nur Rizal, M.

2018-04-01

Smart tourism is a supporting system of an individual tourism in the terms of a comprehensive and integrated information and technology service. An educational tourist destination such as a museum is expected to present an informative and interactive atmosphere. Vredeburg Fort Museum as one of the tourist destinations in Yogyakarta begins to lose its visitors. The lack of interest of public towards the museum and the assumption that the museum is an ancient, less well maintained, and boring place become main obstacles in attracting tourists. This research aims to find the important factors becoming the preferences of tourists to visit the Vredeburg Museum in Yogyakarta. The research method used is the Principal Component Analysis. The analysis shows there are four main factors with eigenvalue more than 1, i.e. the first factor of 8,623, the second factor of 1,920, the third factor of 1,175, and the fourth factor of 1.082. Those four factors are the result of the grouping of 20 preference determinant variables.

Sufficient Forecasting Using Factor Models

PubMed Central

Fan, Jianqing; Xue, Lingzhou; Yao, Jiawei

2017-01-01

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

Measuring Alexithymia via Trait Approach-I: A Alexithymia Scale Item Selection and Formation of Factor Structure

PubMed Central

TATAR, Arkun; SALTUKOĞLU, Gaye; ALİOĞLU, Seda; ÇİMEN, Sümeyye; GÜVEN, Hülya; AY, Çağla Ebru

2017-01-01

Introduction It is not clear in the literature whether available instruments are sufficient to measure alexithymia because of its theoretical structure. Moreover, it has been reported that several measuring instruments are needed to measure this construct, and all the instruments have different error sources. The old and the new forms of Toronto Alexithymia Scale are the only instruments available in Turkish. Thus, the purpose of this study was to develop a new scale to measure alexithymia, selecting items and constructing the factor structure. Methods A total of 1117 patients aged from 19 to 82 years (mean = 35.05 years) were included. A 100-item pool was prepared and applied to 628 women and 489 men. Data were analyzed using Explanatory Factor Analysis, Confirmatory Factor Analysis, and Item Response Theory and 28 items were selected. The new form of 28 items was applied to 415 university students, including 271 women and 144 men aged from 18 to 30 (mean=21.44). Results The results of Explanatory Factor Analysis revealed a five-factor construct of “Solving and Expressing Affective Experiences,” “External Locused Cognitive Style,” “Tendency to Somatize Affections,” “Imaginary Life and Visualization,” and “Acting Impulsively,” along with a two-factor construct representing the “Affective” and “Cognitive” components. All the components of the construct showed good model fit and high internal consistency. The new form was tested in terms of internal consistency, test-retest reliability, and concurrent validity using Toronto Alexithymia Scale as criteria and discriminative validity using Five-Factor Personality Inventory Short Form. Conclusion The results showed that the new scale met the basic psychometric requirements. Results have been discussed in line with related studies. PMID:29033633

Measuring Filial Piety in the 21st Century: Development, Factor Structure, and Reliability of the 10-Item Contemporary Filial Piety Scale.

PubMed

Lum, Terry Y S; Yan, Elsie C W; Ho, Andy H Y; Shum, Michelle H Y; Wong, Gloria H Y; Lau, Mandy M Y; Wang, Junfang

2016-11-01

The experience and practice of filial piety have evolved in modern Chinese societies, and existing measures fail to capture these important changes. Based on a conceptual analysis on current literature, 42 items were initially compiled to form a Contemporary Filial Piety Scale (CFPS), and 1,080 individuals from a representative sample in Hong Kong were surveyed. Principal component analysis generated a 16-item three-factor model: Pragmatic Obligations (Factor 1; 10 items), Compassionate Reverence (Factor 2; 4 items), and Family Continuity (Factor 3; 2 items). Confirmatory factor analysis revealed strong factor loadings for Factors 1 and 2, while removing Factor 3 and conceptually duplicated items increased total variance explained from 58.02% to 60.09% and internal consistency from .84 to .88. A final 10-item two-factor structure model was adopted with a goodness of fit of 0.95. The CFPS-10 is a data-driven, simple, and efficient instrument with strong psychometric properties for assessing contemporary filial piety. © The Author(s) 2015.

Examining the factor structure of MUIS-C scale among baby boomers with hepatitis C.

PubMed

Reinoso, Humberto; Türegün, Mehmet

2016-11-01

Baby boomers account for two out of every three cases of hepatitis C infection in the U.S. To conduct an exploratory factor analysis directed at supporting the use of the MUIS-C as a reliable instrument in measuring illness uncertainty among baby boomers with hepatitis C. The steps of conducting a typical principal component analysis (PCA) with an oblique rotation were used on a sample of 146 participants, the sampling adequacy of items was examined via the Kaiser-Meyer-Olkin (KMO) measure, and the Bartlett's sphericity test was used for appropriateness of conducting a factor analysis. A two-factor structure was obtained by using Horn's parallel analysis method. The two factors explained a cumulative total of 45.8% of the variance. The results of the analyses indicated that the MUIS-C was a valid and reliable instrument and potentially suitable for use in baby boomer population diagnosed with hepatitis C. Published by Elsevier Inc.

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

Pain sensitivity profiles in patients with advanced knee osteoarthritis

PubMed Central

Frey-Law, Laura A.; Bohr, Nicole L.; Sluka, Kathleen A.; Herr, Keela; Clark, Charles R.; Noiseux, Nicolas O.; Callaghan, John J; Zimmerman, M Bridget; Rakel, Barbara A.

2016-01-01

The development of patient profiles to subgroup individuals on a variety of variables has gained attention as a potential means to better inform clinical decision-making. Patterns of pain sensitivity response specific to quantitative sensory testing (QST) modality have been demonstrated in healthy subjects. It has not been determined if these patterns persist in a knee osteoarthritis population. In a sample of 218 participants, 19 QST measures along with pain, psychological factors, self-reported function, and quality of life were assessed prior to total knee arthroplasty. Component analysis was used to identify commonalities across the 19 QST assessments to produce standardized pain sensitivity factors. Cluster analysis then grouped individuals that exhibited similar patterns of standardized pain sensitivity component scores. The QST resulted in four pain sensitivity components: heat, punctate, temporal summation, and pressure. Cluster analysis resulted in five pain sensitivity profiles: a “low pressure pain” group, an “average pain” group, and three “high pain” sensitivity groups who were sensitive to different modalities (punctate, heat, and temporal summation). Pain and function differed between pain sensitivity profiles, along with sex distribution; however no differences in OA grade, medication use, or psychological traits were found. Residualizing QST data by age and sex resulted in similar components and pain sensitivity profiles. Further, these profiles are surprisingly similar to those reported in healthy populations suggesting that individual differences in pain sensitivity are a robust finding even in an older population with significant disease. PMID:27152688

Principle of maximum entropy for reliability analysis in the design of machine components

NASA Astrophysics Data System (ADS)

Zhang, Yimin

2018-03-01

We studied the reliability of machine components with parameters that follow an arbitrary statistical distribution using the principle of maximum entropy (PME). We used PME to select the statistical distribution that best fits the available information. We also established a probability density function (PDF) and a failure probability model for the parameters of mechanical components using the concept of entropy and the PME. We obtained the first four moments of the state function for reliability analysis and design. Furthermore, we attained an estimate of the PDF with the fewest human bias factors using the PME. This function was used to calculate the reliability of the machine components, including a connecting rod, a vehicle half-shaft, a front axle, a rear axle housing, and a leaf spring, which have parameters that typically follow a non-normal distribution. Simulations were conducted for comparison. This study provides a design methodology for the reliability of mechanical components for practical engineering projects.

Evolution of the symbiotic binary system AG Pegasi - The slowest classical nova eruption ever recorded

NASA Technical Reports Server (NTRS)

Kenyon, Scott J.; Mikolajewska, Joanna; Mikolajewski, Maciej; Polidan, Ronald S.; Slovak, Mark H.

1993-01-01

We present an analysis of new and existing photometric and spectroscopic observations of the ongoing eruption in the symbiotic star AG Pegasi, showing that this binary has evolved considerably since the turn of the century. Recent dramatic changes in both the UV continuum and the wind from the hot component allow a more detailed analysis than in previous papers. AG Peg is composed of a normal M3 giant and a hot, compact star embedded in a dense, ionized nebula. The hot component powers the activity observed in this system, including a dense wind and a photoionized region within the outer atmosphere of the red giant. The hot component contracted in radius at roughly constant luminosity from 1850 to 1985. Its bolometric luminosity declined by a factor of about 4 during the past 5 yr. Both the mass loss rate from the hot component and the emission activity decreased in step with the hot component's total luminosity, while photospheric radiation from the red giant companion remained essentially constant.

Measuring Acceptance of Sleep Difficulties: The Development of the Sleep Problem Acceptance Questionnaire.

PubMed

Bothelius, Kristoffer; Jernelöv, Susanna; Fredrikson, Mats; McCracken, Lance M; Kaldo, Viktor

2015-11-01

Acceptance may be an important therapeutic process in sleep medicine, but valid psychometric instruments measuring acceptance related to sleep difficulties are lacking. The purpose of this study was to develop a measure of acceptance in insomnia, and to examine its factor structure as well as construct validity. In a cross-sectional design, a principal component analysis for item reduction was conducted on a first sample (A) and a confirmatory factor analysis on a second sample (B). Construct validity was tested on a combined sample (C). Questionnaire items were derived from a measure of acceptance in chronic pain, and data were gathered through screening or available from pretreatment assessments in four insomnia treatment trials, administered online, via bibliotherapy and in primary care. Adults with insomnia: 372 in sample A and 215 in sample B. Sample C (n = 820) included sample A and B with another 233 participants added. Construct validity was assessed through relations with established acceptance and sleep scales. The principal component analysis presented a two-factor solution with eight items, explaining 65.9% of the total variance. The confirmatory factor analysis supported the solution. Acceptance of sleep problems was more closely related to subjective symptoms and consequences of insomnia than to diary description of sleep, or to acceptance of general private events. The Sleep Problem Acceptance Questionnaire (SPAQ), containing the subscales "Activity Engagement" and "Willingness", is a valid tool to assess acceptance of insomnia. © 2015 Associated Professional Sleep Societies, LLC.

Systems genetic analysis of multivariate response to iron deficiency in mice

PubMed Central

Yin, Lina; Unger, Erica L.; Jellen, Leslie C.; Earley, Christopher J.; Allen, Richard P.; Tomaszewicz, Ann; Fleet, James C.

2012-01-01

The aim of this study was to identify genes that influence iron regulation under varying dietary iron availability. Male and female mice from 20+ BXD recombinant inbred strains were fed iron-poor or iron-adequate diets from weaning until 4 mo of age. At death, the spleen, liver, and blood were harvested for the measurement of hemoglobin, hematocrit, total iron binding capacity, transferrin saturation, and liver, spleen and plasma iron concentration. For each measure and diet, we found large, strain-related variability. A principal-components analysis (PCA) was performed on the strain means for the seven parameters under each dietary condition for each sex, followed by quantitative trait loci (QTL) analysis on the factors. Compared with the iron-adequate diet, iron deficiency altered the factor structure of the principal components. QTL analysis, combined with PosMed (a candidate gene searching system) published gene expression data and literature citations, identified seven candidate genes, Ptprd, Mdm1, Picalm, lip1, Tcerg1, Skp2, and Frzb based on PCA factor, diet, and sex. Expression of each of these is cis-regulated, significantly correlated with the corresponding PCA factor, and previously reported to regulate iron, directly or indirectly. We propose that polymorphisms in multiple genes underlie individual differences in iron regulation, especially in response to dietary iron challenge. This research shows that iron management is a highly complex trait, influenced by multiple genes. Systems genetics analysis of iron homeostasis holds promise for developing new methods for prevention and treatment of iron deficiency anemia and related diseases. PMID:22461179

Readers' opinions of romantic poetry are consistent with emotional measures based on the Dictionary of Affect in Language.

PubMed

Whissell, Cynthia

2003-06-01

A principal components analysis of 68 volunteers' subjective ratings of 20 excerpts of Romantic poetry and of Dictionary of Affect scores for the same excerpts produced four components representing Pleasantness, Activation, Romanticism, and Nature. Dictionary measures and subjective ratings of the same constructs loaded on the same factor. Results are interpreted as providing construct validity for the Dictionary of Affect.

Piping benchmark problems. Volume 1. Dynamic analysis uniform support motion response spectrum method

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

Bezler, P.; Hartzman, M.; Reich, M.

1980-08-01

A set of benchmark problems and solutions have been developed for verifying the adequacy of computer programs used for dynamic analysis and design of nuclear piping systems by the Response Spectrum Method. The problems range from simple to complex configurations which are assumed to experience linear elastic behavior. The dynamic loading is represented by uniform support motion, assumed to be induced by seismic excitation in three spatial directions. The solutions consist of frequencies, participation factors, nodal displacement components and internal force and moment components. Solutions to associated anchor point motion static problems are not included.

Conducting financial due diligence of medical practices.

PubMed

Louiselle, P

1995-12-01

Many healthcare organizations are acquiring medical practices in an effort to build more integrated systems of healthcare products and services. This acquisition activity must be approached cautiously to ensure that medical practices being acquired do not have deficiencies that would jeopardize integration efforts. Conducting a thorough due diligence analysis of medical practices before finalizing the transaction can limit the acquiring organizations' legal and financial exposure and is a necessary component to the acquisition process. The author discusses the components of a successful financial due diligence analysis and addresses some of the risk factors in a practice acquisition.

Assessing trihalomethanes (THMs) and N-nitrosodimethylamine (NDMA) formation potentials in drinking water treatment plants using fluorescence spectroscopy and parallel factor analysis.

PubMed

Yang, Liyang; Kim, Daekyun; Uzun, Habibullah; Karanfil, Tanju; Hur, Jin

2015-02-01

The formation of disinfection byproducts (DBPs) is a major challenge in drinking water treatments. This study explored the applicability of fluorescence excitation-emission matrices and parallel factor analysis (EEM-PARAFAC) for assessing the formation potentials (FPs) of trihalomethanes (THMs) and N-nitrosodimethylamine (NDMA), and the treatability of THM and NDMA precursors in nine drinking water treatment plants. Two humic-like and one tryptophan-like components were identified for the samples using PARAFAC. The total THM FP (TTHM FP) correlated strongly with humic-like component C2 (r=0.874), while NDMA FP showed a moderate and significant correlation with the tryptophan-like component C3 (r=0.628). The reduction by conventional treatment was more effective for C2 than C3, and for TTHM FP than NDMA FP. The treatability of DOM and TTHM FP correlated negatively with the absorption spectral slope (S275-295) and biological index (BIX) of the raw water, but it correlated positively with humification index (HIX). Our results demonstrated that PARAFAC components were valuable for assessing DBPs FP in drinking water treatments, and also that the raw water quality could affect the treatment efficiency. Copyright © 2014 Elsevier Ltd. All rights reserved.

An Exploratory Study on Using Principal-Component Analysis and Confirmatory Factor Analysis to Identify Bolt-On Dimensions: The EQ-5D Case Study.

PubMed

Finch, Aureliano Paolo; Brazier, John Edward; Mukuria, Clara; Bjorner, Jakob Bue

2017-12-01

Generic preference-based measures such as the EuroQol five-dimensional questionnaire (EQ-5D) are used in economic evaluation, but may not be appropriate for all conditions. When this happens, a possible solution is adding bolt-ons to expand their descriptive systems. Using review-based methods, studies published to date claimed the relevance of bolt-ons in the presence of poor psychometric results. This approach does not identify the specific dimensions missing from the Generic preference-based measure core descriptive system, and is inappropriate for identifying dimensions that might improve the measure generically. This study explores the use of principal-component analysis (PCA) and confirmatory factor analysis (CFA) for bolt-on identification in the EQ-5D. Data were drawn from the international Multi-Instrument Comparison study, which is an online survey on health and well-being measures in five countries. Analysis was based on a pool of 92 items from nine instruments. Initial content analysis provided a theoretical framework for PCA results interpretation and CFA model development. PCA was used to investigate the underlining dimensional structure and whether EQ-5D items were represented in the identified constructs. CFA was used to confirm the structure. CFA was cross-validated in random halves of the sample. PCA suggested a nine-component solution, which was confirmed by CFA. This included psychological symptoms, physical functioning, and pain, which were covered by the EQ-5D, and satisfaction, speech/cognition,relationships, hearing, vision, and energy/sleep which were not. These latter factors may represent relevant candidate bolt-ons. PCA and CFA appear useful methods for identifying potential bolt-ons dimensions for an instrument such as the EQ-5D. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

New predictor of aortic enlargement in uncomplicated type B aortic dissection based on elliptic Fourier analysis.

PubMed

Sato, Hiroshi; Ito, Toshiro; Kuroda, Yosuke; Uchiyama, Hiroki; Watanabe, Toshitaka; Yasuda, Naomi; Nakazawa, Junji; Harada, Ryo; Kawaharada, Nobuyoshi

2017-12-01

This study aimed to re-examine the conventional predictive factors for dissected aortic enlargement, such as the aortic and false lumen diameter and to consider whether the morphological elements of the dissected aorta could be predictors by quantifying the 'shape' of the true lumen based on elliptic Fourier analysis. A total of 80 patients with uncomplicated type B aortic dissection were included. The patients were divided into 'Enlargement group' and 'No Change group.' Between the 2 groups, the mean systolic blood pressure during follow-up, aortic and false lumen maximum diameters, and analysed morphological data were compared using each statistical method. The maximum aortic and false lumen diameters were significantly larger in the Enlargement group than in the No Change group (39.3 vs 35.9 mm; P = 0.0058) (23.5 vs 18.2 mm; P = 0.000095). The principal component 1, which is the data calculated by elliptic Fourier analysis, was significantly lower in the Enlargement group than in the No Change group (0.020 vs - 0.072; P = 0.000049). The mean systolic blood pressure ≥130 mmHg, aortic diameter, false lumen diameter and principal component 1 were included in the Cox proportional hazard model as covariates to determine the significant predictive variable. Principal component 1 demonstrated the only significance with aortic enlargement on multivariate analysis (odds ratio = 0.32; P = 0.048). The analysed and calculated morphological data of the shape of the true lumen can be more effective predictive factors of aortic enlargement of type B dissection than the conventional factors. © The Author 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Anthropometric and Somatotype Characteristics of Young Soccer Players: Differences Among Categories, Subcategories, and Playing Position.

PubMed

Perroni, Fabrizio; Vetrano, Mario; Camolese, Giancarlo; Guidetti, Laura; Baldari, Carlo

2015-08-01

Considering that anthropometric parameters are important factors in the performance of the soccer players, the aim of this study was to explore the differences in anthropometric and somatotype characteristics of Italian young soccer players. Weight, height, body mass index, and somatotype of 112 young soccer players, grouped in Giovanissimi "A" (14 years), "B" (13 years), and "C" (12 years) as well as Allievi "B" (15 years) and "A" (16 years) and "Juniores" (older than 17 years), were evaluated. Statistical analysis tests were computed at p ≤ 0.05, and an analysis of variance for each somatotype was calculated to analyze the main effects and interactions of the factors: categories, subcategories, and playing position. Bonferroni's post hoc analysis was used to identify differences among mean values. Considering all subjects, we have found significant differences in categories, subcategories, and playing position between anthropometric values and a somatotype value of 2.8-3.8-2.9. Significant differences have found among goalkeepers and the others playing position in endomorphy (p ≤ 0.001) and with defenders and midfielders in ectomorphy (p < 0.01) components, whereas no differences in mesomorphy. Analyzing the interaction between subcategories and playing position factors, a significant effect was found only in the endomorphy component (p = 0.05). The analysis of anthropometric characteristic of Italian young soccer players indicates that players have high muscularity value and low adiposity. This study showed the presence of somatotype differences for playing position within categories also in the youngest categories and subcategories, in particular, in the endomorphy component. Young soccer players should be trained with more appropriate and specific training load to avoid the increased injury risk during adolescence.

Supercritical Fluid Chromatography of Drugs: Parallel Factor Analysis for Column Testing in a Wide Range of Operational Conditions

PubMed Central

Al-Degs, Yahya; Andri, Bertyl; Thiébaut, Didier; Vial, Jérôme

2017-01-01

Retention mechanisms involved in supercritical fluid chromatography (SFC) are influenced by interdependent parameters (temperature, pressure, chemistry of the mobile phase, and nature of the stationary phase), a complexity which makes the selection of a proper stationary phase for a given separation a challenging step. For the first time in SFC studies, Parallel Factor Analysis (PARAFAC) was employed to evaluate the chromatographic behavior of eight different stationary phases in a wide range of chromatographic conditions (temperature, pressure, and gradient elution composition). Design of Experiment was used to optimize experiments involving 14 pharmaceutical compounds present in biological and/or environmental samples and with dissimilar physicochemical properties. The results showed the superiority of PARAFAC for the analysis of the three-way (column × drug × condition) data array over unfolding the multiway array to matrices and performing several classical principal component analyses. Thanks to the PARAFAC components, similarity in columns' function, chromatographic trend of drugs, and correlation between separation conditions could be simply depicted: columns were grouped according to their H-bonding forces, while gradient composition was dominating for condition classification. Also, the number of drugs could be efficiently reduced for columns classification as some of them exhibited a similar behavior, as shown by hierarchical clustering based on PARAFAC components. PMID:28695040

Components of self-esteem in affective patients and non-psychiatric controls.

PubMed

Serretti, Alessandro; Olgiati, Paolo; Colombo, Cristina

2005-09-01

Decrease in self-esteem (SE) is found in all mood disorders during inter-episode phases. This trait was associated with relapse and suicidality but its genetic basis is still undefined, probably because SE has multiple components. The aim of the current study was to ascertain which of those components were altered in a sample of affective patients. Three hundred and thirty-one outpatients with bipolar (N=199) and major depressive MD (N=132) disorders in remission for at least three months and one hundred controls completed the Rosenberg Self-esteem Scale (RSE; [Rosenberg, M., 1965. The measurement of self-esteem, Society and the Adolescent Self-Image. Princeton University Press, pp.16-36]). Principal component analysis was performed to identify RSE factor structure. Extracted factors were compared across case and control groups in the whole sample (N=431) and in a sub-sample (N=301) with low self-esteem (RSE <20). PCA yielded a two-factor solution with self-confidence (SC) and self-deprecation (SD) that was largely consistent with the existing literature. Such factors were both associated with lower scores in affective patients than controls (SC: F=52, p<0.01; SD: F=43, p<0.01). However in the low RSE group only self-confidence was found to be decreased in subjects with mood disorders (SC: F=13.8, p<0.01; SD: F=0.05, p=0.9). These findings suggest that self-esteem deficit in affective disorders might involve specific components. Implications for research and clinical practice are discussed.

Instruments measuring perceived racism/racial discrimination: review and critique of factor analytic techniques.

PubMed

Atkins, Rahshida

2014-01-01

Several compendiums of instruments that measure perceived racism and/or discrimination are present in the literature. Other works have reviewed the psychometric properties of these instruments in terms of validity and reliability and have indicated if the instrument was factor analyzed. However, little attention has been given to the quality of the factor analysis performed. The aim of this study was to evaluate the exploratory factor analyses done on instruments measuring perceived racism/racial discrimination using guidelines from experts in psychometric theory. The techniques used for factor analysis were reviewed and critiqued and the adequacy of reporting was evaluated. Internet search engines and four electronic abstract databases were used to identify 16 relevant instruments that met the inclusion/exclusion criteria. Principal component analysis was the most frequent method of extraction (81%). Sample sizes were adequate for factor analysis in 81 percent of studies. The majority of studies reported appropriate criteria for the acceptance of un-rotated factors (81%) and justified the rotation method (75%). Exactly 94 percent of studies reported partially acceptable criteria for the acceptance of rotated factors. The majority of articles (69%) reported adequate coefficient alphas for the resultant subscales. In 81 percent of the studies, the conceptualized dimensions were supported by factor analysis.

INSTRUMENTS MEASURING PERCEIVED RACISM/RACIAL DISCRIMINATION: REVIEW AND CRITIQUE OF FACTOR ANALYTIC TECHNIQUES

PubMed Central

Atkins, Rahshida

2015-01-01

Several compendiums of instruments that measure perceived racism and/or discrimination are present in the literature. Other works have reviewed the psychometric properties of these instruments in terms of validity and reliability and have indicated if the instrument was factor analyzed. However, little attention has been given to the quality of the factor analysis performed. The aim of this study was to evaluate the exploratory factor analyses done on instruments measuring perceived racism/racial discrimination using guidelines from experts in psychometric theory. The techniques used for factor analysis were reviewed and critiqued and the adequacy of reporting was evaluated. Internet search engines and four electronic abstract databases were used to identify 16 relevant instruments that met the inclusion/exclusion criteria. Principal component analysis was the most frequent method of extraction (81%). Sample sizes were adequate for factor analysis in 81 percent of studies. The majority of studies reported appropriate criteria for the acceptance of un-rotated factors (81%) and justified the rotation method (75%). Exactly 94 percent of studies reported partially acceptable criteria for the acceptance of rotated factors. The majority of articles (69%) reported adequate coefficient alphas for the resultant subscales. In 81 percent of the studies, the conceptualized dimensions were supported by factor analysis. PMID:25626225

Study on nondestructive discrimination of genuine and counterfeit wild ginsengs using NIRS

NASA Astrophysics Data System (ADS)

Lu, Q.; Fan, Y.; Peng, Z.; Ding, H.; Gao, H.

2012-07-01

A new approach for the nondestructive discrimination between genuine wild ginsengs and the counterfeit ones by near infrared spectroscopy (NIRS) was developed. Both discriminant analysis and back propagation artificial neural network (BP-ANN) were applied to the model establishment for discrimination. Optimal modeling wavelengths were determined based on the anomalous spectral information of counterfeit samples. Through principal component analysis (PCA) of various wild ginseng samples, genuine and counterfeit, the cumulative percentages of variance of the principal components were obtained, serving as a reference for principal component (PC) factor determination. Discriminant analysis achieved an identification ratio of 88.46%. With sample' truth values as its outputs, a three-layer BP-ANN model was built, which yielded a higher discrimination accuracy of 100%. The overall results sufficiently demonstrate that NIRS combined with BP-ANN classification algorithm performs better on ginseng discrimination than discriminant analysis, and can be used as a rapid and nondestructive method for the detection of counterfeit wild ginsengs in food and pharmaceutical industry.

Principal components analysis of an evaluation of the hemiplegic subject based on the Bobath approach.

PubMed

Corriveau, H; Arsenault, A B; Dutil, E; Lepage, Y

1992-01-01

An evaluation based on the Bobath approach to treatment has previously been developed and partially validated. The purpose of the present study was to verify the content validity of this evaluation with the use of a statistical approach known as principal components analysis. Thirty-eight hemiplegic subjects participated in the study. Analysis of the scores on each of six parameters (sensorium, active movements, muscle tone, reflex activity, postural reactions, and pain) was evaluated on three occasions across a 2-month period. Each time this produced three factors that contained 70% of the variation in the data set. The first component mainly reflected variations in mobility, the second mainly variations in muscle tone, and the third mainly variations in sensorium and pain. The results of such exploratory analysis highlight the fact that some of the parameters are not only important but also interrelated. These results seem to partially support the conceptual framework substantiating the Bobath approach to treatment.

Simulation of multispectral multisource for device of consumer and medicine products analysis

NASA Astrophysics Data System (ADS)

Korolev, Timofey K.; Peretyagin, Vladimir S.

2017-06-01

One of the results of intensive development of led technology was the creation of a multi-component, managed devices and illumination/irradiation used in various fields of production (e.g., food industry analysis, food quality). The use of LEDs has become possible due to their structure determining spatial, energy, electrical, thermal and other characteristics. However, the development of the devices for illumination/irradiation require closer attention in the case if you want to provide precise illumination to the area of analysis, located at a specified distance from the radiation source. The present work is devoted to the development and modelling of a specialized source of radiation intended for solving problems of analysis of food products, medicines and water for suitability in drinking. In this work, we provided a mathematical model of spatial and spectral distribution of irridation from the source of infrared radiation ring structure. When you create this kind of source, you address factors such spectral component, the power settings, the spatial and energy components of the diodes.

Temporal trend and climate factors of hemorrhagic fever with renal syndrome epidemic in Shenyang City, China

PubMed Central

2011-01-01

Background Hemorrhagic fever with renal syndrome (HFRS) is an important infectious disease caused by different species of hantaviruses. As a rodent-borne disease with a seasonal distribution, external environmental factors including climate factors may play a significant role in its transmission. The city of Shenyang is one of the most seriously endemic areas for HFRS. Here, we characterized the dynamic temporal trend of HFRS, and identified climate-related risk factors and their roles in HFRS transmission in Shenyang, China. Methods The annual and monthly cumulative numbers of HFRS cases from 2004 to 2009 were calculated and plotted to show the annual and seasonal fluctuation in Shenyang. Cross-correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on HFRS transmission and the autocorrelation of monthly HFRS cases. Principal component analysis was constructed by using climate data from 2004 to 2009 to extract principal components of climate factors to reduce co-linearity. The extracted principal components and autocorrelation terms of monthly HFRS cases were added into a multiple regression model called principal components regression model (PCR) to quantify the relationship between climate factors, autocorrelation terms and transmission of HFRS. The PCR model was compared to a general multiple regression model conducted only with climate factors as independent variables. Results A distinctly declining temporal trend of annual HFRS incidence was identified. HFRS cases were reported every month, and the two peak periods occurred in spring (March to May) and winter (November to January), during which, nearly 75% of the HFRS cases were reported. Three principal components were extracted with a cumulative contribution rate of 86.06%. Component 1 represented MinRH0, MT1, RH1, and MWV1; component 2 represented RH2, MaxT3, and MAP3; and component 3 represented MaxT2, MAP2, and MWV2. The PCR model was composed of three principal components and two autocorrelation terms. The association between HFRS epidemics and climate factors was better explained in the PCR model (F = 446.452, P < 0.001, adjusted R2 = 0.75) than in the general multiple regression model (F = 223.670, P < 0.000, adjusted R2 = 0.51). Conclusion The temporal distribution of HFRS in Shenyang varied in different years with a distinctly declining trend. The monthly trends of HFRS were significantly associated with local temperature, relative humidity, precipitation, air pressure, and wind velocity of the different previous months. The model conducted in this study will make HFRS surveillance simpler and the control of HFRS more targeted in Shenyang. PMID:22133347

Sleep spindle and K-complex detection using tunable Q-factor wavelet transform and morphological component analysis

PubMed Central

Lajnef, Tarek; Chaibi, Sahbi; Eichenlaub, Jean-Baptiste; Ruby, Perrine M.; Aguera, Pierre-Emmanuel; Samet, Mounir; Kachouri, Abdennaceur; Jerbi, Karim

2015-01-01

A novel framework for joint detection of sleep spindles and K-complex events, two hallmarks of sleep stage S2, is proposed. Sleep electroencephalography (EEG) signals are split into oscillatory (spindles) and transient (K-complex) components. This decomposition is conveniently achieved by applying morphological component analysis (MCA) to a sparse representation of EEG segments obtained by the recently introduced discrete tunable Q-factor wavelet transform (TQWT). Tuning the Q-factor provides a convenient and elegant tool to naturally decompose the signal into an oscillatory and a transient component. The actual detection step relies on thresholding (i) the transient component to reveal K-complexes and (ii) the time-frequency representation of the oscillatory component to identify sleep spindles. Optimal thresholds are derived from ROC-like curves (sensitivity vs. FDR) on training sets and the performance of the method is assessed on test data sets. We assessed the performance of our method using full-night sleep EEG data we collected from 14 participants. In comparison to visual scoring (Expert 1), the proposed method detected spindles with a sensitivity of 83.18% and false discovery rate (FDR) of 39%, while K-complexes were detected with a sensitivity of 81.57% and an FDR of 29.54%. Similar performances were obtained when using a second expert as benchmark. In addition, when the TQWT and MCA steps were excluded from the pipeline the detection sensitivities dropped down to 70% for spindles and to 76.97% for K-complexes, while the FDR rose up to 43.62 and 49.09%, respectively. Finally, we also evaluated the performance of the proposed method on a set of publicly available sleep EEG recordings. Overall, the results we obtained suggest that the TQWT-MCA method may be a valuable alternative to existing spindle and K-complex detection methods. Paths for improvements and further validations with large-scale standard open-access benchmarking data sets are discussed. PMID:26283943

[Complexity and its integrative effects of the time lags of environment factors affecting Larix gmelinii stem sap flow].

PubMed

Wang, Hui-Mei; Sun, Wei; Zu, Yuan-Gang; Wang, Wen-Jie

2011-12-01

Based on the one-year (2005) observations with a frequency of half hour on the stem sap flow of Larix gmelinii plantation trees planted in 1969 and the related environmental factors air humidity (RH), air temperature (T(air)), photosynthetic components active radiation (PAR), soil temperature (T(soil)), and soil moisture (TDR), principal analysis (PCA) and correction analysis were made on the time lag effect of the stem flow in different seasons (26 days of each season) and in a year via dislocation analysis, with the complexity and its integrative effects of the time lags of environment factors affecting the stem sap flow approached. The results showed that in different seasons and for different environmental factors, the time lag effect varied obviously. In general, the time lag of PAR was 0.5-1 hour ahead of sap flow, that of T(air) and RH was 0-2 hours ahead of or behind the sap flow, and the time lags of T(soil) and TDR were much longer or sometimes undetectable. Because of the complexity of the time lags, no evident improvements were observed in the linear correlations (R2, slope, and intercept) when the time lags based on short-term (20 days) data were used to correct the time lags based on whole year data. However, obvious improvements were found in the standardized and non-standardized correlation coefficients in stepwise multiple regressions, i.e., the time lag corrections could improve the effects of RH, but decreased the effects of PAR, T(air), and T(soil). PCA could be used to simplify the complexity. The first and the second principal components could stand for over 75% information of all the environmental factors in different seasons and in whole year. The time lags of both the first and the second principal components were 1-1.5 hours in advance of the sap flow, except in winter (no time lag effect).

Cooked carrots volatiles. AEDA and odor activity comparisons. Identification of Linden Ether as an important aroma component

USDA-ARS?s Scientific Manuscript database

MS with GC-RI evidence was found for the presence of Linden ether in cooked carrot. Evaluation of the GC effluent from cooked carrot volatiles using Aroma Extract Dilution Analysis (AEDA) found Linden ether with the highest Flavor Dilution (FD) factor. Others with 10 fold lower FD factors were B-i...

Further Validation of the Inventory of Mental Toughness Factors in Sport (IMTF-S)

ERIC Educational Resources Information Center

Stonkus, Mark A.; Royal, Kenneth D.

2015-01-01

The purpose of this study was to provide further validation a new measure of mental toughness in sport. The Inventory of Mental Toughness Factors in Sport (IMTF-S) was originally developed and validated using principal component analysis. For the present study, the psychometric properties of the IMTF-S were again evaluated, but by way of the Rasch…

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

DTIC Science & Technology

2010-06-01

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

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

PubMed

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

2008-09-01

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

The Relationship of Social Engagement and Social Support With Sense of Community.

PubMed

Tang, Fengyan; Chi, Iris; Dong, Xinqi

2017-07-01

We aimed to investigate the relationship of engagement in social and cognitive activities and social support with the sense of community (SOC) and its components among older Chinese Americans. The Sense of Community Index (SCI) was used to measure SOC and its four component factors: membership, influence, needs fulfillment, and emotional connection. Social engagement was assessed with 16 questions. Social support included positive support and negative strain. Principal component analysis was used to identify the SCI components. Linear regression analysis was used to detect the contribution of social engagement and social support to SOC and its components. After controlling for sociodemographics and self-rated health, social activity engagement and positive social support were positively related to SOC and its components. This study points to the importance of social activity engagement and positive support from family and friends in increasing the sense of community. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Psychometric Evaluation of the Team Member Perspectives of Person-Centered Care (TM-PCC) Survey for Long-Term Care Homes.

PubMed

Boscart, Veronique M; Davey, Meaghan; Ploeg, Jenny; Heckman, George; Dupuis, Sherry; Sheiban, Linda; Luh Kim, Jessica; Brown, Paul; Sidani, Souraya

2018-06-06

Person-centered care (PCC) is fundamental for providing high-quality care in long-term care homes. This study aimed to evaluate the psychometric properties of an 11-item Team Member Perspectives of Person-Centered Care (TM-PCC) survey, adapted from White and colleagues (2008). In a cross-sectional study, 461 staff from four long-term care homes in Ontario, Canada, completed the TM-PCC. Construct validity and internal consistency of the TM-PCC were examined with a principal component analysis and Cronbach’s alpha coefficient. Findings revealed a three-component structure with factor 1, Supporting Social Relationships; factor 2, Familiarity with Residents’ Preferences; and factor 3, Meaningful Resident⁻Staff Relationships. The TM-PCC, as compared to the original survey, presented with less components (i.e., did not address Resident Autonomy, Personhood, Comfort, Work with Residents, Personal Environment, and Management Structure), yet included one new component (Meaningful Resident⁻Staff Relationships). The TM-PCC has a similar internal consistency (Cronbach’s alpha coefficient 0.82 vs. White et al. 0.74⁻0.91). The TM-PCC can be used to assess PCC from the staff’s perspective in long-term care homes.

How are population-based funding formulae for healthcare composed? A comparative analysis of seven models.

PubMed

Penno, Erin; Gauld, Robin; Audas, Rick

2013-11-08

Population-based funding formulae act as an important means of promoting equitable health funding structures. To evaluate how policy makers in different jurisdictions construct health funding formulae and build an understanding of contextual influences underpinning formula construction we carried out a comparative analysis of key components of funding formulae across seven high-income and predominantly publically financed health systems: New Zealand, England, Scotland, the Netherlands, the state of New South Wales in Australia, the Canadian province of Ontario, and the city of Stockholm, Sweden. Core components from each formula were summarised and key similarities and differences evaluated from a compositional perspective. We categorised approaches to constructing funding formulae under three main themes: identifying factors which predict differential need amongst populations; adjusting for cost factors outside of needs factors; and engaging in normative correction of allocations for 'unmet' need. We found significant congruence in the factors used to guide need and cost adjustments. However, there is considerable variation in interpretation and implementation of these factors. Despite broadly similar frameworks, there are distinct differences in the composition of the formulae across the seven health systems. Ultimately, the development of funding formulae is a dynamic process, subject to availability of data reflecting health needs, the influence of wider socio-political objectives and health system determinants.

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

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

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

2014-11-01

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

A Multivariate Analysis of the Early Dropout Process

ERIC Educational Resources Information Center

Fiester, Alan R.; Rudestam, Kjell E.

1975-01-01

Principal-component factor analyses were performed on patient input (demographic and pretherapy expectations), therapist input (demographic), and patient perspective therapy process variables that significantly differentiated early dropout from nondropout outpatients at two community mental health centers. (Author)

Influence of running stride frequency in heart rate variability analysis during treadmill exercise testing.

PubMed

Bailón, Raquel; Garatachea, Nuria; de la Iglesia, Ignacio; Casajús, Jose Antonio; Laguna, Pablo

2013-07-01

The analysis and interpretation of heart rate variability (HRV) during exercise is challenging not only because of the nonstationary nature of exercise, the time-varying mean heart rate, and the fact that respiratory frequency exceeds 0.4 Hz, but there are also other factors, such as the component centered at the pedaling frequency observed in maximal cycling tests, which may confuse the interpretation of HRV analysis. The objectives of this study are to test the hypothesis that a component centered at the running stride frequency (SF) appears in the HRV of subjects during maximal treadmill exercise testing, and to study its influence in the interpretation of the low-frequency (LF) and high-frequency (HF) components of HRV during exercise. The HRV of 23 subjects during maximal treadmill exercise testing is analyzed. The instantaneous power of different HRV components is computed from the smoothed pseudo-Wigner-Ville distribution of the modulating signal assumed to carry information from the autonomic nervous system, which is estimated based on the time-varying integral pulse frequency modulation model. Besides the LF and HF components, the appearance is revealed of a component centered at the running SF as well as its aliases. The power associated with the SF component and its aliases represents 22±7% (median±median absolute deviation) of the total HRV power in all the subjects. Normalized LF power decreases as the exercise intensity increases, while normalized HF power increases. The power associated with the SF does not change significantly with exercise intensity. Consideration of the running SF component and its aliases is very important in HRV analysis since stride frequency aliases may overlap with LF and HF components.

Time series analysis of collective motions in proteins

NASA Astrophysics Data System (ADS)

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

2004-01-01

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

Source Evaluation and Trace Metal Contamination in Benthic Sediments from Equatorial Ecosystems Using Multivariate Statistical Techniques

PubMed Central

Benson, Nsikak U.; Asuquo, Francis E.; Williams, Akan B.; Essien, Joseph P.; Ekong, Cyril I.; Akpabio, Otobong; Olajire, Abaas A.

2016-01-01

Trace metals (Cd, Cr, Cu, Ni and Pb) concentrations in benthic sediments were analyzed through multi-step fractionation scheme to assess the levels and sources of contamination in estuarine, riverine and freshwater ecosystems in Niger Delta (Nigeria). The degree of contamination was assessed using the individual contamination factors (ICF) and global contamination factor (GCF). Multivariate statistical approaches including principal component analysis (PCA), cluster analysis and correlation test were employed to evaluate the interrelationships and associated sources of contamination. The spatial distribution of metal concentrations followed the pattern Pb>Cu>Cr>Cd>Ni. Ecological risk index by ICF showed significant potential mobility and bioavailability for Cu, Cu and Ni. The ICF contamination trend in the benthic sediments at all studied sites was Cu>Cr>Ni>Cd>Pb. The principal component and agglomerative clustering analyses indicate that trace metals contamination in the ecosystems was influenced by multiple pollution sources. PMID:27257934

SCA with rotation to distinguish common and distinctive information in linked data.

PubMed

Schouteden, Martijn; Van Deun, Katrijn; Pattyn, Sven; Van Mechelen, Iven

2013-09-01

Often data are collected that consist of different blocks that all contain information about the same entities (e.g., items, persons, or situations). In order to unveil both information that is common to all data blocks and information that is distinctive for one or a few of them, an integrated analysis of the whole of all data blocks may be most useful. Interesting classes of methods for such an approach are simultaneous-component and multigroup factor analysis methods. These methods yield dimensions underlying the data at hand. Unfortunately, however, in the results from such analyses, common and distinctive types of information are mixed up. This article proposes a novel method to disentangle the two kinds of information, by making use of the rotational freedom of component and factor models. We illustrate this method with data from a cross-cultural study of emotions.

Morphological instability of a thermophoretically growing deposit

NASA Technical Reports Server (NTRS)

Castillo, Jose L.; Garcia-Ybarra, Pedro L.; Rosner, Daniel E.

1992-01-01

The stability of the planar interface of a structureless solid growing from a depositing component dilute in a carrier fluid is studied when the main solute transport mechanism is thermal (Soret) diffusion. A linear stability analysis, carried out in the limit of low growth Peclet number, leads to a dispersion relation which shows that the planar front is unstable either when the thermal diffusion factor of the condensing component is positive and the latent heat release is small or when the thermal diffusion factor is negative and the solid grows over a thermally-insulating substrate. Furthermore, the influence of interfacial energy effects and constitutional supersaturation in the vicinity of the moving interface is analyzed in the limit of very small Schmidt numbers (small solute Fickian diffusion). The analysis is relevant to physical vapor deposition of very massive species on cold surfaces, as in recent experiments of organic solid film growth under microgravity conditions.

Inversion of gravity gradient tensor data: does it provide better resolution?

NASA Astrophysics Data System (ADS)

Paoletti, V.; Fedi, M.; Italiano, F.; Florio, G.; Ialongo, S.

2016-04-01

The gravity gradient tensor (GGT) has been increasingly used in practical applications, but the advantages and the disadvantages of the analysis of GGT components versus the analysis of the vertical component of the gravity field are still debated. We analyse the performance of joint inversion of GGT components versus separate inversion of the gravity field alone, or of one tensor component. We perform our analysis by inspection of the Picard Plot, a Singular Value Decomposition tool, and analyse both synthetic data and gradiometer measurements carried out at the Vredefort structure, South Africa. We show that the main factors controlling the reliability of the inversion are algebraic ambiguity (the difference between the number of unknowns and the number of available data points) and signal-to-noise ratio. Provided that algebraic ambiguity is kept low and the noise level is small enough so that a sufficient number of SVD components can be included in the regularized solution, we find that: (i) the choice of tensor components involved in the inversion is not crucial to the overall reliability of the reconstructions; (ii) GGT inversion can yield the same resolution as inversion with a denser distribution of gravity data points, but with the advantage of using fewer measurement stations.

The Iranian version of 12-item Short Form Health Survey (SF-12): factor structure, internal consistency and construct validity

PubMed Central

Montazeri, Ali; Vahdaninia, Mariam; Mousavi, Sayed Javad; Omidvari, Speideh

2009-01-01

Background The 12-item Short Form Health Survey (SF-12) as a shorter alternative of the SF-36 is largely used in health outcomes surveys. The aim of this study was to validate the SF-12 in Iran. Methods A random sample of the general population aged 15 years and over living in Tehran, Iran completed the SF-12. Reliability was estimated using internal consistency and validity was assessed using known groups comparison and convergent validity. In addition, the factor structure of the questionnaire was extracted by performing both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Results: In all, 5587 individuals were studied (2721 male and 2866 female). The mean age and formal education of the respondents were 35.1 (SD = 15.4) and 10.2 (SD = 4.4) years respectively. The results showed satisfactory internal consistency for both summary measures, that are the Physical Component Summary (PCS) and the Mental Component Summary (MCS); Cronbach's α for PCS-12 and MCS-12 was 0.73 and 0.72, respectively. Known-groups comparison showed that the SF-12 discriminated well between men and women and those who differed in age and educational status (P < 0.001). In addition, correlations between the SF-12 scales and single items showed that the physical functioning, role physical, bodily pain and general health subscales correlated higher with the PCS-12 score, while the vitality, social functioning, role emotional and mental health subscales more correlated with the MCS-12 score lending support to its good convergent validity. Finally the principal component analysis indicated a two-factor structure (physical and mental health) that jointly accounted for 57.8% of the variance. The confirmatory factory analysis also indicated a good fit to the data for the two-latent structure (physical and mental health). Conclusion In general the findings suggest that the SF-12 is a reliable and valid measure of health related quality of life among Iranian population. However, further studies are needed to establish stronger psychometric properties for this alternative form of the SF-36 Health Survey in Iran. PMID:19758427

The Iranian version of 12-item Short Form Health Survey (SF-12): factor structure, internal consistency and construct validity.

PubMed

Montazeri, Ali; Vahdaninia, Mariam; Mousavi, Sayed Javad; Omidvari, Speideh

2009-09-16

The 12-item Short Form Health Survey (SF-12) as a shorter alternative of the SF-36 is largely used in health outcomes surveys. The aim of this study was to validate the SF-12 in Iran. A random sample of the general population aged 15 years and over living in Tehran, Iran completed the SF-12. Reliability was estimated using internal consistency and validity was assessed using known groups comparison and convergent validity. In addition, the factor structure of the questionnaire was extracted by performing both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). In all, 5587 individuals were studied (2721 male and 2866 female). The mean age and formal education of the respondents were 35.1 (SD = 15.4) and 10.2 (SD = 4.4) years respectively. The results showed satisfactory internal consistency for both summary measures, that are the Physical Component Summary (PCS) and the Mental Component Summary (MCS); Cronbach's alpha for PCS-12 and MCS-12 was 0.73 and 0.72, respectively. Known-groups comparison showed that the SF-12 discriminated well between men and women and those who differed in age and educational status (P < 0.001). In addition, correlations between the SF-12 scales and single items showed that the physical functioning, role physical, bodily pain and general health subscales correlated higher with the PCS-12 score, while the vitality, social functioning, role emotional and mental health subscales more correlated with the MCS-12 score lending support to its good convergent validity. Finally the principal component analysis indicated a two-factor structure (physical and mental health) that jointly accounted for 57.8% of the variance. The confirmatory factory analysis also indicated a good fit to the data for the two-latent structure (physical and mental health). In general the findings suggest that the SF-12 is a reliable and valid measure of health related quality of life among Iranian population. However, further studies are needed to establish stronger psychometric properties for this alternative form of the SF-36 Health Survey in Iran.

Development and validation of a tool to assess the physical and social environment associated with physical activity among adults in Sri Lanka.

PubMed

De Silva Weliange, Shreenika H; Fernando, Dulitha; Gunatilake, Jagath

2014-05-03

Environmental characteristics are known to be associated with patterns of physical activity (PA). Although several validated tools exist, to measure the environment characteristics, these instruments are not necessarily suitable for application in all settings especially in a developing country. This study was carried out to develop and validate an instrument named the "Physical And Social Environment Scale--PASES" to assess the physical and social environmental factors associated with PA. This will enable identification of various physical and social environmental factors affecting PA in Sri Lanka, which will help in the development of more tailored intervention strategies for promoting higher PA levels in Sri Lanka. The PASES was developed using a scientific approach of defining the construct, item generation, analysis of content of items and item reduction. Both qualitative and quantitative methods of key informant interviews, in-depth interviews and rating of the items generated by experts were conducted. A cross sectional survey among 180 adults was carried out to assess the factor structure through principal component analysis. Another cross sectional survey among a different group of 180 adults was carried out to assess the construct validity through confirmatory factor analysis. Reliability was assessed with test re-test reliability and internal consistency using Spearman r and Cronbach's alpha respectively. Thirty six items were selected after the expert ratings and were developed into interviewer administered questions. Exploration of factor structure of the 34 items which were factorable through principal component analysis with Quartimax rotation extracted 8 factors. The 34 item instrument was assessed for construct validity with confirmatory factor analysis which confirmed an 8 factor model (x2 = 339.9, GFI = 0.90). The identified factors were infrastructure for walking, aesthetics and facilities for cycling, vehicular traffic safety, access and connectivity, recreational facilities for PA, safety, social cohesion and social acceptance of PA with the two non-factorable factors, residential density and land use mix. The PASES also showed good test re-test reliability and a moderate level of internal consistency. The PASES is a valid and reliable tool which could be used to assess the physical and social environment associated with PA in Sri Lanka.

Helium Mass Spectrometer Leak Detection: A Method to Quantify Total Measurement Uncertainty

NASA Technical Reports Server (NTRS)

Mather, Janice L.; Taylor, Shawn C.

2015-01-01

In applications where leak rates of components or systems are evaluated against a leak rate requirement, the uncertainty of the measured leak rate must be included in the reported result. However, in the helium mass spectrometer leak detection method, the sensitivity, or resolution, of the instrument is often the only component of the total measurement uncertainty noted when reporting results. To address this shortfall, a measurement uncertainty analysis method was developed that includes the leak detector unit's resolution, repeatability, hysteresis, and drift, along with the uncertainty associated with the calibration standard. In a step-wise process, the method identifies the bias and precision components of the calibration standard, the measurement correction factor (K-factor), and the leak detector unit. Together these individual contributions to error are combined and the total measurement uncertainty is determined using the root-sum-square method. It was found that the precision component contributes more to the total uncertainty than the bias component, but the bias component is not insignificant. For helium mass spectrometer leak rate tests where unit sensitivity alone is not enough, a thorough evaluation of the measurement uncertainty such as the one presented herein should be performed and reported along with the leak rate value.

Factor analysis of Wechsler Adult Intelligence Scale-Revised in developmentally disabled persons.

PubMed

Di Nuovo, Santo F; Buono, Serafino

2006-12-01

The results of previous studies on the factorial structure of Wechsler Intelligence Scales are somewhat inconsistent across normal and pathological samples. To study specific clinical groups, such as developmentally disabled persons, it is useful to examine the factor structure in appropriate samples. A factor analysis was carried out using the principal component method and the Varimax orthogonal rotation on the Wechsler Adult Intelligence Scale (WAIS-R) in a sample of 203 developmentally disabled persons, with a mean age of 25 years 4 months. Developmental disability ranged from mild to moderate. Partially contrasting with previous studies on normal samples, results found a two-factor solution. Wechsler's traditional Verbal and Performance scales seems to be more appropriate for this sample than the alternative three-factor solution.

Body Mass Index, Waist Circumference, and the Clustering of Cardiometabolic Risk Factors in Early Childhood.

PubMed

Anderson, Laura N; Lebovic, Gerald; Hamilton, Jill; Hanley, Anthony J; McCrindle, Brian W; Maguire, Jonathon L; Parkin, Patricia C; Birken, Catherine S

2016-03-01

Obesity has its origins in early childhood; however, there is limited evidence of the association between anthropometric indicators and cardiometabolic risk factors in young children. Our aim was to evaluate the associations between body mass index (BMI) and waist circumference (WC) in relation to cardiometabolic risk factors and to explore the clustering of these factors. A cross-sectional study was conducted in children aged 1-5 years through TARGet Kids! (n = 2917). Logistic regression was used to evaluate associations between BMI and WC z-scores and individual traditional and possible non-traditional cardiometabolic risk factors. The underlying clustering of these measures was evaluated using principal components analysis (PCA). Child obesity (BMI z-score >2) was associated with high (>90th percentile) leptin [odds ratio (OR) 8.15, 95% confidence interval (CI) 4.56, 14.58] and insulin (OR = 1.76; 95% CI 1.05, 2.94). WC z-score >1 was associated with high insulin (OR 1.59, 95% CI 1.11, 2.28), leptin (OR 5.48, 95% CI 3.48, 8.63) and 25-hydroxyvitamin D < 75 nmol/L (OR 1.39, 95% CI 1.08, 1.79). BMI and WC were not associated with other traditional cardiometabolic risk factors, including non-High Density Lipoprotein (HDL) cholesterol, and glucose. Among children 3-5 years (n = 1035) the PCA of traditional risk factors identified three components: adiposity/blood pressure, metabolic, and lipids. The inclusion of non-traditional risk factors identified four additional components but contributed minimally to the total variation explained. Anthropometric indicators are associated with selected cardiometabolic risk factors in early childhood, although the clustering of risk factors suggests that adiposity is only one distinct component of cardiometabolic risk. The measurement of other risk factors beyond BMI and WC may be important in defining cardiometabolic risk in early childhood. © 2015 John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Analysis of metastasis associated signal regulatory network in colorectal cancer.

PubMed

Qi, Lu; Ding, Yanqing

2018-06-18

Metastasis is a key factor that affects the survival and prognosis of colorectal cancer patients. To elucidate molecular mechanism associated with the metastasis of colorectal cancer, genes related to the metastasis time of colorectal cancer were screened. Then, a network was constructed with this genes. Data was obtained from colorectal cancer expression profile. Molecular mechanism elucidated the time of tumor metastasis and the expression of genes related to colorectal cancer. We found that metastasis-promoting and metastasis-inhibiting networks included protein hubs of high connectivity. These protein hubs were components of organelles. Some ribosomal proteins promoted the metastasis of colorectal cancer. In some components of organelles, such as proteasomes, mitochondrial ribosome, ATP synthase, and splicing factors, the metastasis of colorectal cancer was inhibited by some sections of these organelles. After performing survival analysis of proteins in organelles, joint survival curve of proteins was constructed in ribosomal network. This joint survival curve showed metastasis was promoted in patients with colorectal cancer (P = 0.0022939). Joint survival curve of proteins was plotted against proteasomes (P = 7 e-07), mitochondrial ribosome (P = 0.0001157), ATP synthase (P = 0.0001936), and splicing factors (P = 1.35e-05). These curves indicate that metastasis of colorectal cancer can be inhibited. After analyzing proteins that bind with organelle components, we also found that some proteins were associated with the time of colorectal cancer metastasis. Hence, different cellular components play different roles in the metastasis of colorectal cancer. Copyright © 2018 Elsevier Inc. All rights reserved.

[Validation of a questionnaire to evaluate patient safety in clinical laboratories].

PubMed

Giménez Marín, Ángeles; Rivas-Ruiz, Francisco

2012-01-01

The aim of this study was to prepare, pilot and validate a questionnaire to evaluate patient safety in the specific context of clinical laboratories. A specific questionnaire on patient safety in the laboratory, with 62 items grouped into six areas, was developed, taking into consideration the diverse human and laboratory contextual factors which may contribute to producing errors. A pilot study of 30 interviews was carried out, including validity and reliability analyses using principal components factor analysis and Cronbach's alpha. Subsequently, 240 questionnaires were sent to 21 hospitals, followed by a test-retest of 41 questionnaires with the definitive version. The sample analyzed was composed of 225 questionnaires (an overall response rate of 80%). Of the 62 items initially assessed, 17 were eliminated due to non-compliance with the criteria established before the principal components factor analysis was performed. For the 45 remaining items, 12 components were identified, with an cumulative variance of 69.5%. In seven of the 10 components with two or more items, Cronbach's alpha was higher than 0.7. The questionnaire items assessed in the test-retest were found to be stable. We present the first questionnaire with sufficiently proven validity and reliability for evaluating patient safety in the specific context of clinical laboratories. This questionnaire provides a useful instrument to perform a subsequent macrostudy of hospital clinical laboratories in Spain. The questionnaire can also be used to monitor and promote commitment to patient safety within the search for continuous quality improvement. Copyright © 2011 SESPAS. Published by Elsevier Espana. All rights reserved.

An efficient classification method based on principal component and sparse representation.

PubMed

Zhai, Lin; Fu, Shujun; Zhang, Caiming; Liu, Yunxian; Wang, Lu; Liu, Guohua; Yang, Mingqiang

2016-01-01

As an important application in optical imaging, palmprint recognition is interfered by many unfavorable factors. An effective fusion of blockwise bi-directional two-dimensional principal component analysis and grouping sparse classification is presented. The dimension reduction and normalizing are implemented by the blockwise bi-directional two-dimensional principal component analysis for palmprint images to extract feature matrixes, which are assembled into an overcomplete dictionary in sparse classification. A subspace orthogonal matching pursuit algorithm is designed to solve the grouping sparse representation. Finally, the classification result is gained by comparing the residual between testing and reconstructed images. Experiments are carried out on a palmprint database, and the results show that this method has better robustness against position and illumination changes of palmprint images, and can get higher rate of palmprint recognition.

A stable systemic risk ranking in China's banking sector: Based on principal component analysis

NASA Astrophysics Data System (ADS)

Fang, Libing; Xiao, Binqing; Yu, Honghai; You, Qixing

2018-02-01

In this paper, we compare five popular systemic risk rankings, and apply principal component analysis (PCA) model to provide a stable systemic risk ranking for the Chinese banking sector. Our empirical results indicate that five methods suggest vastly different systemic risk rankings for the same bank, while the combined systemic risk measure based on PCA provides a reliable ranking. Furthermore, according to factor loadings of the first component, PCA combined ranking is mainly based on fundamentals instead of market price data. We clearly find that price-based rankings are not as practical a method as fundamentals-based ones. This PCA combined ranking directly shows systemic risk contributions of each bank for banking supervision purpose and reminds banks to prevent and cope with the financial crisis in advance.

A Multilevel Analysis of the Impact of a Professional Learning Community, Faculty Trust in Colleagues and Collective Efficacy on Teacher Commitment to Students

ERIC Educational Resources Information Center

Lee, John Chi-kin; Zhang, Zhonghua; Yin, Hongbiao

2011-01-01

This study investigated the relationships between a professional learning community (PLC), faculty trust in colleagues, teachers' collective efficacy, and their commitment to students. The findings from exploratory factor analysis indicated that three clear components could be extracted from the scale of Professional Learning Communities…

A proposed biophysical approach to Visual absorption capability (VAC)

Treesearch

W. C. Yeomans

1979-01-01

In British Columbia, visual analysis is in its formative stages and has only recently been accepted by Government as a resource component, notably within the Resource Analysis Branch, Ministry of Environment. Visual absorption capability (VAC), is an integral factor in visual resource assessment. VAC is examined by the author in the degree to which it relates to...

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

ERIC Educational Resources Information Center

Bray-Clark, Nikki; Bates, Reid

2005-01-01

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

Examination of Trends and Evidence-Based Elements in State Physical Education Legislation: A Content Analysis

ERIC Educational Resources Information Center

Eyler, Amy A.; Brownson, Ross C.; Aytur, Semra A.; Cradock, Angie L.; Doescher, Mark; Evenson, Kelly R.; Kerr, Jacqueline; Maddock, Jay; Pluto, Delores L.; Steinman, Lesley; Tompkins, Nancy O'Hara; Troped, Philip; Schmid, Thomas L.

2010-01-01

Objectives: To develop a comprehensive inventory of state physical education (PE) legislation, examine trends in bill introduction, and compare bill factors. Methods: State PE legislation from January 2001 to July 2007 was identified using a legislative database. Analysis included components of evidence-based school PE from the Community Guide and…

Designers' models of the human-computer interface

NASA Technical Reports Server (NTRS)

Gillan, Douglas J.; Breedin, Sarah D.

1993-01-01

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

Finding imaging patterns of structural covariance via Non-Negative Matrix Factorization.

PubMed

Sotiras, Aristeidis; Resnick, Susan M; Davatzikos, Christos

2015-03-01

In this paper, we investigate the use of Non-Negative Matrix Factorization (NNMF) for the analysis of structural neuroimaging data. The goal is to identify the brain regions that co-vary across individuals in a consistent way, hence potentially being part of underlying brain networks or otherwise influenced by underlying common mechanisms such as genetics and pathologies. NNMF offers a directly data-driven way of extracting relatively localized co-varying structural regions, thereby transcending limitations of Principal Component Analysis (PCA), Independent Component Analysis (ICA) and other related methods that tend to produce dispersed components of positive and negative loadings. In particular, leveraging upon the well known ability of NNMF to produce parts-based representations of image data, we derive decompositions that partition the brain into regions that vary in consistent ways across individuals. Importantly, these decompositions achieve dimensionality reduction via highly interpretable ways and generalize well to new data as shown via split-sample experiments. We empirically validate NNMF in two data sets: i) a Diffusion Tensor (DT) mouse brain development study, and ii) a structural Magnetic Resonance (sMR) study of human brain aging. We demonstrate the ability of NNMF to produce sparse parts-based representations of the data at various resolutions. These representations seem to follow what we know about the underlying functional organization of the brain and also capture some pathological processes. Moreover, we show that these low dimensional representations favorably compare to descriptions obtained with more commonly used matrix factorization methods like PCA and ICA. Copyright © 2014 Elsevier Inc. All rights reserved.

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

PubMed

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

2018-01-01

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

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

PubMed

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

2015-08-30

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

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

PubMed Central

2012-01-01

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

Centrality Evolution of pt and yt Spectra from Au-Au Collisions at √ {sNN} = 200 GeV

NASA Astrophysics Data System (ADS)

Trainor, Thomas A.

A two-component analysis of spectra to pt = 12 GeV/c for identified pions and protons from 200 GeV Au-Au collisions is presented. The method is similar to an analysis of the nch dependence of pt spectra from p-p collisions at 200 GeV, but applied to Au-Au centrality dependence. The soft-component reference is a Lévy distribution on transverse mass mt. The hard-component reference is a Gaussian on transverse rapidity yt with exponential (pt power-law) tail. Deviations of data from the reference are described by hard-component ratio rAA, which generalizes nuclear modification factor RAA. The analysis suggests that centrality evolution of pion and proton spectra is dominated by changes in parton fragmentation. The structure of rAA suggests that parton energy loss produces a negative boost Δyt of a large fraction (but not all) of the minimum-bias fragment distribution, and that lower-energy partons suffer relatively less energy loss, possibly due to color screening. The analysis also suggests that the anomalous p/π ratio may be due to differences in the parton energy-loss process experienced by the two hadron species. This analysis provides no evidence for radial flow.

Factors associated with generic health-related quality of life (HRQOL) in patients with chronic obstructive pulmonary disease (COPD): a cross-sectional study.

PubMed

Brandl, Magdalena; Böhmer, Merle M; Brandstetter, Susanne; Finger, Tamara; Fischer, Wiebke; Pfeifer, Michael; Apfelbacher, Christian

2018-02-01

Health-related quality of life (HRQOL) is impaired in chronic obstructive pulmonary disease (COPD) patients, but determining factors for HRQOL are still not unequivocal. This study measures HRQOL among patients with COPD and aims to determine factors associated with HRQOL. Data for cross-sectional analyses were obtained from the baseline of a cohort study. The study population includes adult COPD patients (disease duration ≥3 months), recruited from primary and secondary care settings in Germany, without acute psychiatric/neurologic disease (exception: affective/ anxiety disorders). HRQOL was assessed using the Short-Form 12 (SF-12) Health Survey Questionnaire, comprising a physical and mental component. Independent variables encompass socio-demographic, disease-specific, treatment-related and psychological factors. Multivariable linear regression analyses were conducted. In total, 206 COPD patients (60.7% male; mean age: 65.3 years) took part in the study. In multivariable analysis, the physical component score showed a significant negative association with the COPD Assessment Test (CAT) (P<0.001) and a higher total number of prescribed medications (P=0.001). A higher forced expiratory volume in 1 second (FEV1) value in percent predicted was significantly related to the physical component score in a positive manner (P=0.006). The mental component score was significantly associated with elevated patient-reported symptoms of anxiety (P=0.002) or depression (P<0.001), measured by the hospital anxiety and depression scale (HADS) in a negative way. Like for the physical component score (P<0.001), a worse CAT score was significantly associated with a lower mental component score (P=0.033). Focusing on patient reported outcomes and screening for depression and anxiety with potential successive treatment might be promising approaches to improve HRQOL in patients with COPD.

THz spectral data analysis and components unmixing based on non-negative matrix factorization methods

NASA Astrophysics Data System (ADS)

Ma, Yehao; Li, Xian; Huang, Pingjie; Hou, Dibo; Wang, Qiang; Zhang, Guangxin

2017-04-01

In many situations the THz spectroscopic data observed from complex samples represent the integrated result of several interrelated variables or feature components acting together. The actual information contained in the original data might be overlapping and there is a necessity to investigate various approaches for model reduction and data unmixing. The development and use of low-rank approximate nonnegative matrix factorization (NMF) and smooth constraint NMF (CNMF) algorithms for feature components extraction and identification in the fields of terahertz time domain spectroscopy (THz-TDS) data analysis are presented. The evolution and convergence properties of NMF and CNMF methods based on sparseness, independence and smoothness constraints for the resulting nonnegative matrix factors are discussed. For general NMF, its cost function is nonconvex and the result is usually susceptible to initialization and noise corruption, and may fall into local minima and lead to unstable decomposition. To reduce these drawbacks, smoothness constraint is introduced to enhance the performance of NMF. The proposed algorithms are evaluated by several THz-TDS data decomposition experiments including a binary system and a ternary system simulating some applications such as medicine tablet inspection. Results show that CNMF is more capable of finding optimal solutions and more robust for random initialization in contrast to NMF. The investigated method is promising for THz data resolution contributing to unknown mixture identification.

THz spectral data analysis and components unmixing based on non-negative matrix factorization methods.

PubMed

Ma, Yehao; Li, Xian; Huang, Pingjie; Hou, Dibo; Wang, Qiang; Zhang, Guangxin

2017-04-15

In many situations the THz spectroscopic data observed from complex samples represent the integrated result of several interrelated variables or feature components acting together. The actual information contained in the original data might be overlapping and there is a necessity to investigate various approaches for model reduction and data unmixing. The development and use of low-rank approximate nonnegative matrix factorization (NMF) and smooth constraint NMF (CNMF) algorithms for feature components extraction and identification in the fields of terahertz time domain spectroscopy (THz-TDS) data analysis are presented. The evolution and convergence properties of NMF and CNMF methods based on sparseness, independence and smoothness constraints for the resulting nonnegative matrix factors are discussed. For general NMF, its cost function is nonconvex and the result is usually susceptible to initialization and noise corruption, and may fall into local minima and lead to unstable decomposition. To reduce these drawbacks, smoothness constraint is introduced to enhance the performance of NMF. The proposed algorithms are evaluated by several THz-TDS data decomposition experiments including a binary system and a ternary system simulating some applications such as medicine tablet inspection. Results show that CNMF is more capable of finding optimal solutions and more robust for random initialization in contrast to NMF. The investigated method is promising for THz data resolution contributing to unknown mixture identification. Copyright © 2017 Elsevier B.V. All rights reserved.

Localization of functional receptor epitopes on the structure of ciliary neurotrophic factor indicates a conserved, function-related epitope topography among helical cytokines.

PubMed

Panayotatos, N; Radziejewska, E; Acheson, A; Somogyi, R; Thadani, A; Hendrickson, W A; McDonald, N Q

1995-06-09

By rational mutagenesis, receptor-specific functional analysis, and visualization of complex formation in solution, we identified individual amino acid side chains involved specifically in the interaction of ciliary neurotrophic factor (CNTF) with CNTFR alpha and not with the beta-components, gp130 and LIFR. In the crystal structure, the side chains of these residues, which are located in helix A, the AB loop, helix B, and helix D, are surface accessible and are clustered in space, thus constituting an epitope for CNTFR alpha. By the same analysis, a partial epitope for gp130 was also identified on the surface of helix A that faces away from the alpha-epitope. Superposition of the CNTF and growth hormone structures showed that the location of these epitopes on CNTF is analogous to the location of the first and second receptor epitopes on the surface of growth hormone. Further comparison with proposed binding sites for alpha- and beta-receptors on interleukin-6 and leukemia inhibitory factor indicated that this epitope topology is conserved among helical cytokines. In each case, epitope I is utilized by the specificity-conferring component, whereas epitopes II and III are used by accessory components. Thus, in addition to a common fold, helical cytokines share a conserved order of receptor epitopes that is function related.

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

PubMed

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

2016-01-23

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

Investigation of carbon dioxide emission in China by primary component analysis.

PubMed

Zhang, Jing; Wang, Cheng-Ming; Liu, Lian; Guo, Hang; Liu, Guo-Dong; Li, Yuan-Wei; Deng, Shi-Huai

2014-02-15

Principal component analysis (PCA) is employed to investigate the relationship between CO2 emissions (COEs) stemming from fossil fuel burning and cement manufacturing and their affecting factors. Eight affecting factors, namely, Population (P), Urban Population (UP); the Output Values of Primary Industry (PIOV), Secondary Industry (SIOV), and Tertiary Industry (TIOV); and the Proportions of Primary Industry's Output Value (PPIOV), Secondary Industry's Output Value (PSIOV), and Tertiary Industry's Output Value (PTIOV), are chosen. PCA is employed to eliminate the multicollinearity of the affecting factors. Two principal components, which can explain 92.86% of the variance of the eight affecting factors, are chosen as variables in the regression analysis. Ordinary least square regression is used to estimate multiple linear regression models, in which COEs and the principal components serve as dependent and independent variables, respectively. The results are given in the following. (1) Theoretically, the carbon intensities of PIOV, SIOV, and TIOV are 2573.4693, 552.7036, and 606.0791 kt per one billion $, respectively. The incomplete statistical data, the different statistical standards, and the ideology of self sufficiency and peasantry appear to show that the carbon intensity of PIOV is higher than those of SIOV and TIOV in China. (2) PPIOV, PSIOV, and PTIOV influence the fluctuations of COE. The parameters of PPIOV, PSIOV, and PTIOV are -2706946.7564, 2557300.5450, and 3924767.9807 kt, respectively. As the economic structure of China is strongly tied to technology level, the period when PIOV plays the leading position is characterized by lagging technology and economic developing. Thus, the influence of PPIOV has a negative value. As the increase of PSIOV and PTIOV is always followed by technological innovation and economic development, PSIOV and PTIOV have the opposite influence. (3) The carbon intensities of P and UP are 1.1029 and 1.7862 kt per thousand people, respectively. The carbon intensity of the rural population can be inferred to be lower than 1.1029 kt per thousand people. The characteristics of poverty and the use of bio-energy in rural areas result in a carbon intensity of the rural population that is lower than that of P. Copyright © 2013 Elsevier B.V. All rights reserved.

A Second Look at Dwyer's Studies by Means of Meta-Analysis: The Effects of Pictorial Realism on Text Comprehension and Vocabulary.

ERIC Educational Resources Information Center

Reinwein, Joachim; Huberdeau, Lucie

A meta-analysis examined a series of studies by F.M. Dwyer on the effect of illustrations on text comprehension. Principal component analysis was used to reduce the four posttests used by Dwyer to more fundamental factors of learning, followed by analyses of variance. All nine studies (involving secondary-school and college students) in which…

Proceedings: Economic and Social Analysis Workshop Held at St. Louis, Missouri on 25-29 October 1982,

DTIC Science & Technology

1983-10-01

institutional factors for determining the discount rate. For instance tax impact analysis is particularly troublesome. According to one recent study ...STAND-ALONE TECHNICAL REPORT. THE FOLLOWING COMPONENT PART NUMBERS COMPRISE THE COMPILATION REPORT: AW: TIILE: AD-P002 631 National Waterways Study ...for Military Programs: The Fort -;1uchanan, Puerto Rico, Realignment Study . AD-P002 646 Economic Analysis of Alternative Military Housing

Validation of a questionnaire to measure sexual health knowledge and understanding (Sexual Health Questionnaire) in Nepalese secondary school: A psychometric process.

PubMed

Acharya, Dev Raj; Thomas, Malcolm; Cann, Rosemary

2016-01-01

School-based sex education has the potential to prevent unwanted pregnancy and to promote positive sexual health at the individual, family and community level. To develop and validate a sexual health questionnaire to measure young peoples' sexual health knowledge and understanding (SHQ) in Nepalese secondary school. Secondary school students (n = 259, male = 43.63%, female = 56.37%) and local experts (n = 9, male = 90%, female = 10%) were participated in this study. Evaluation processes were; content validity (>0.89), plausibility check (>95), item-total correlation (>0.3), factor loading (>0.4), principal component analysis (4 factors Kaiser's criterion), Chronbach's alpha (>0.65), face validity and internal consistency using test-retest reliability (P > 0.05). The principal component analysis revealed four factors to be extracted; sexual health norms and beliefs, source of sexual health information, sexual health knowledge and understanding, and level of sexual awareness. Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy demonstrated that the patterns of correlations are relatively compact (>0.80). Chronbach's alpha for each factors were above the cut-off point (0.65). Face validity indicated that the questions were clear to the majority of the respondent. Moreover, there were no significant differences (P > 0.05) in the responses to the items at two time points at seven weeks later. The finding suggests that SHQ is a valid and reliable instrument to be used in schools to measure sexual health knowledge and understanding. Further analysis such as structured equation modelling (SEM) and confirmatory factor analysis could make the questionnaire more robust and applicable to the wider school population.

Validation of a questionnaire to measure sexual health knowledge and understanding (Sexual Health Questionnaire) in Nepalese secondary school: A psychometric process

PubMed Central

Acharya, Dev Raj; Thomas, Malcolm; Cann, Rosemary

2016-01-01

Background: School-based sex education has the potential to prevent unwanted pregnancy and to promote positive sexual health at the individual, family and community level. Objectives: To develop and validate a sexual health questionnaire to measure young peoples’ sexual health knowledge and understanding (SHQ) in Nepalese secondary school. Materials and Methods: Secondary school students (n = 259, male = 43.63%, female = 56.37%) and local experts (n = 9, male = 90%, female = 10%) were participated in this study. Evaluation processes were; content validity (>0.89), plausibility check (>95), item-total correlation (>0.3), factor loading (>0.4), principal component analysis (4 factors Kaiser's criterion), Chronbach's alpha (>0.65), face validity and internal consistency using test-retest reliability (P > 0.05). Results: The principal component analysis revealed four factors to be extracted; sexual health norms and beliefs, source of sexual health information, sexual health knowledge and understanding, and level of sexual awareness. Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy demonstrated that the patterns of correlations are relatively compact (>0.80). Chronbach's alpha for each factors were above the cut-off point (0.65). Face validity indicated that the questions were clear to the majority of the respondent. Moreover, there were no significant differences (P > 0.05) in the responses to the items at two time points at seven weeks later. Conclusions: The finding suggests that SHQ is a valid and reliable instrument to be used in schools to measure sexual health knowledge and understanding. Further analysis such as structured equation modelling (SEM) and confirmatory factor analysis could make the questionnaire more robust and applicable to the wider school population. PMID:27500171

Measuring trust in nurses - Psychometric properties of the Trust in Nurses Scale in four countries.

PubMed

Stolt, Minna; Charalambous, Andreas; Radwin, Laurel; Adam, Christina; Katajisto, Jouko; Lemonidou, Chryssoula; Patiraki, Elisabeth; Sjövall, Katarina; Suhonen, Riitta

2016-12-01

The purpose of this study was to examine psychometric properties of three translated versions of the Trust in Nurses Scale (TNS) and cancer patients' perceptions of trust in nurses in a sample of cancer patients from four European countries. A cross-sectional, cross-cultural, multi-site survey design was used. The data were collected with the Trust in Nurses Scale from patients with different types of malignancies in 17 units within five clinical sites (n = 599) between 09/2012 and 06/2014. Data were analyzed using descriptive and inferential statistics, multivariate methods and psychometrics using exploratory factor analysis, Cronbach's alpha coefficients, item analysis and Rasch analysis. The psychometric properties of the data were consistent in all countries. Within the exploratory factor analysis the principal component analysis supported the one component structure (unidimensionality) of the TNS. The internal consistency reliability was acceptable. The Rasch analysis supported the unidimensionality of the TNS cross-culturally. All items of the TNS demonstrated acceptable goodness-of-fit to the Rasch model. Cancer patients trusted nurses to a great extent although between-country differences were found. The Trust in Nurses Scale proved to be a valid and reliable tool for measuring patients' trust in nurses in oncological settings in international contexts. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimization of a Three-Component Green Corrosion Inhibitor Mixture for Using in Cooling Water by Experimental Design

NASA Astrophysics Data System (ADS)

Asghari, E.; Ashassi-Sorkhabi, H.; Ahangari, M.; Bagheri, R.

2016-04-01

Factors such as inhibitor concentration, solution hydrodynamics, and temperature influence the performance of corrosion inhibitor mixtures. The simultaneous studying of the impact of different factors is a time- and cost-consuming process. The use of experimental design methods can be useful in minimizing the number of experiments and finding local optimized conditions for factors under the investigation. In the present work, the inhibition performance of a three-component inhibitor mixture against corrosion of St37 steel rotating disk electrode, RDE, was studied. The mixture was composed of citric acid, lanthanum(III) nitrate, and tetrabutylammonium perchlorate. In order to decrease the number of experiments, the L16 Taguchi orthogonal array was used. The "control factors" were the concentration of each component and the rotation rate of RDE and the "response factor" was the inhibition efficiency. The scanning electron microscopy and energy dispersive x-ray spectroscopy techniques verified the formation of islands of adsorbed citrate complexes with lanthanum ions and insoluble lanthanum(III) hydroxide. From the Taguchi analysis results the mixture of 0.50 mM lanthanum(III) nitrate, 0.50 mM citric acid, and 2.0 mM tetrabutylammonium perchlorate under the electrode rotation rate of 1000 rpm was found as optimum conditions.

Diffuse nutrient losses and the impact factors determining their regional differences in four catchments from North to South China

NASA Astrophysics Data System (ADS)

Zhang, Yongyong; Zhou, Yujian; Shao, Quanxi; Liu, Hongbin; Lei, Qiuliang; Zhai, Xiaoyan; Wang, Xuelei

2016-12-01

Diffuse nutrient loss mechanism is complicated and shows remarkably regional differences due to spatial heterogeneities of underlying surface conditions, climate and agricultural practices. Moreover, current available observations are still hard to support the identification of impact factors due to different time or space steps. In this study, an integrated water system model (HEQM) was adopted to obtain the simulated loads of diffuse components (carriers: runoff and sediment; nutrient: total nitrogen (TN) and total phosphorous (TP)) with synchronous scales. Multivariable statistical analysis approaches (Analysis of Similarity and redundancy analysis) were used to assess the regional differences, and to identify impact factors as well as their contributions. Four catchments were selected as our study areas, i.e., Xiahui and Zhangjiafen Catchments of Miyun Basin in North China, Yuliang and Tunxi Catchments of Xin'anjiang Basin in South China. Results showed that the model performances of monthly processes were very good for runoff and good for sediment, TN and TP. The annual average coefficients of all the diffuse components in Xin'anjiang Basin were much greater than those in Miyun Basin, and showed significantly regional differences. All the selected impact factors interpreted 72.87-82.16% of the regional differences of carriers, and 62.72-71.62% of those of nutrient coefficients, respectively. For individual impact factor categories, the critical category was geography, followed by land-use/cover, carriers, climate, as well as soil and agricultural practices in Miyun Basin, or agricultural practices and soil in Xin'anjiang Basin. For individual factors, the critical factors were locations for the carrier regional differences, and carriers or chemical fertilizer for the nutrient regional differences. This study is expected to promote further applications of integrated water system model and multivariable statistical analysis in the diffuse nutrient studies, and provide a scientific support for the diffuse pollution control and management in China.

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

NASA Astrophysics Data System (ADS)

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).

The Malay Version of the Perceived Stress Scale (PSS)-10 is a Reliable and Valid Measure for Stress among Nurses in Malaysia.

PubMed

Sandhu, Sukhvinder Singh; Ismail, Noor Hassim; Rampal, Krishna Gopal

2015-11-01

The Perceived Stress Scale-10 (PSS-10) is widely used to assess stress perception. The aim of this study was to translate the original PSS-10 into Malay and assess the reliability and validity of the Malay version among nurses. The Malay version of the PSS-10 was distributed among 229 nurses from four government hospitals in Selangor State. Test-retest reliability and concurrent validity was conducted with 25 nurses with the Malay version of the Depression Anxiety Stress Scales (DASS) 21. Cronbach's alpha, confirmatory factor analysis (CFA), intraclass correlation coefficient and Pearson's r correlation coefficient were used to determine the psychometric properties of the Malay PSS-10. Two factor components were yielded through exploratory factor analysis with eigenvalues of 3.37 and 2.10, respectively. Both of the factors accounted for 54.6% of the variance. CFA yielded a two-factor structure with satisfactory goodness-of-fit indices [x 2 /df = 2.43; comparative fit index (CFI) = 0.92, goodness-of-fit Index (GFI) = 0.94; standardised root mean square residual (SRMR) = 0.07 and root mean square error of approximation (RMSEA) = 0.08 (90% CI = 0.07-0.09)]. The Cronbach's alpha coefficient for the total items was 0.63 (0.82 for factor 1 and 0.72 for factor 2). The intraclass correlation coefficient (ICC) was 0.81 (95% CI: 0.62-0.91) for test-retest reliability testing after seven days. The total score and the negative component of the PSS-10 correlated significantly with the stress component of the DASS-21: (r = 0.61, P < 0.001) and (r = 0.56, P < 0.004), respectively. The Malay version of the PSS-10 demonstrated a satisfactory level of validity and reliability to assess stress perception. Therefore, this questionnaire is valid in assessing stress perception among nurses in Malaysia.

Multivariate Genetic Correlates of the Auditory Paired Stimuli-Based P2 Event-Related Potential in the Psychosis Dimension From the BSNIP Study.

PubMed

Mokhtari, Mohammadreza; Narayanan, Balaji; Hamm, Jordan P; Soh, Pauline; Calhoun, Vince D; Ruaño, Gualberto; Kocherla, Mohan; Windemuth, Andreas; Clementz, Brett A; Tamminga, Carol A; Sweeney, John A; Keshavan, Matcheri S; Pearlson, Godfrey D

2016-05-01

The complex molecular etiology of psychosis in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is not well defined, presumably due to their multifactorial genetic architecture. Neurobiological correlates of psychosis can be identified through genetic associations of intermediate phenotypes such as event-related potential (ERP) from auditory paired stimulus processing (APSP). Various ERP components of APSP are heritable and aberrant in SZ, PBP and their relatives, but their multivariate genetic factors are less explored. We investigated the multivariate polygenic association of ERP from 64-sensor auditory paired stimulus data in 149 SZ, 209 PBP probands, and 99 healthy individuals from the multisite Bipolar-Schizophrenia Network on Intermediate Phenotypes study. Multivariate association of 64-channel APSP waveforms with a subset of 16 999 single nucleotide polymorphisms (SNPs) (reduced from 1 million SNP array) was examined using parallel independent component analysis (Para-ICA). Biological pathways associated with the genes were assessed using enrichment-based analysis tools. Para-ICA identified 2 ERP components, of which one was significantly correlated with a genetic network comprising multiple linearly coupled gene variants that explained ~4% of the ERP phenotype variance. Enrichment analysis revealed epidermal growth factor, endocannabinoid signaling, glutamatergic synapse and maltohexaose transport associated with P2 component of the N1-P2 ERP waveform. This ERP component also showed deficits in SZ and PBP. Aberrant P2 component in psychosis was associated with gene networks regulating several fundamental biologic functions, either general or specific to nervous system development. The pathways and processes underlying the gene clusters play a crucial role in brain function, plausibly implicated in psychosis. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Identification of factors most important for ammonia emission from fertilized soils for potato production using principal component analysis

Treesearch

Guodoong Liu; Yuncong Li; Kati W. Migliaccio; Ying Ouyang; Ashok K. Alva

2011-01-01

Ammonia (NH3) emissions from fertilized soils are a costly problem that is undermining agricultural and ecological sustainability worldwide. Ammonia emissions from crop production have been reliably documented in recent years. However, insufficient efforts have been made to determine the factors most influential in facilitating NH3 emissions. The goal of this study was...

An Investigation of Psychometric Properties of Coping Styles Scale Brief Form: A Study of Validity and Reliability

ERIC Educational Resources Information Center

Bacanli, Hasan; Surucu, Mustafa; Ilhan, Tahsin

2013-01-01

The aim of the current study was to develop a short form of Coping Styles Scale based on COPE Inventory. A total of 275 undergraduate students (114 female, and 74 male) were administered in the first study. In order to test factors structure of Coping Styles Scale Brief Form, principal components factor analysis and direct oblique rotation was…

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

PubMed Central

de Paiva, Anderson Paulo

2018-01-01

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

Spectroscopic and Chemometric Analysis of Binary and Ternary Edible Oil Mixtures: Qualitative and Quantitative Study.

PubMed

Jović, Ozren; Smolić, Tomislav; Primožič, Ines; Hrenar, Tomica

2016-04-19

The aim of this study was to investigate the feasibility of FTIR-ATR spectroscopy coupled with the multivariate numerical methodology for qualitative and quantitative analysis of binary and ternary edible oil mixtures. Four pure oils (extra virgin olive oil, high oleic sunflower oil, rapeseed oil, and sunflower oil), as well as their 54 binary and 108 ternary mixtures, were analyzed using FTIR-ATR spectroscopy in combination with principal component and discriminant analysis, partial least-squares, and principal component regression. It was found that the composition of all 166 samples can be excellently represented using only the first three principal components describing 98.29% of total variance in the selected spectral range (3035-2989, 1170-1140, 1120-1100, 1093-1047, and 930-890 cm(-1)). Factor scores in 3D space spanned by these three principal components form a tetrahedral-like arrangement: pure oils being at the vertices, binary mixtures at the edges, and ternary mixtures on the faces of a tetrahedron. To confirm the validity of results, we applied several cross-validation methods. Quantitative analysis was performed by minimization of root-mean-square error of cross-validation values regarding the spectral range, derivative order, and choice of method (partial least-squares or principal component regression), which resulted in excellent predictions for test sets (R(2) > 0.99 in all cases). Additionally, experimentally more demanding gas chromatography analysis of fatty acid content was carried out for all specimens, confirming the results obtained by FTIR-ATR coupled with principal component analysis. However, FTIR-ATR provided a considerably better model for prediction of mixture composition than gas chromatography, especially for high oleic sunflower oil.

Development of a scale for attitude toward condom use for migrant workers in India.

PubMed

Talukdar, Arunansu; Bal, Runa; Sanyal, Debasis; Roy, Krishnendu; Talukdar, Payel Sengupta

2008-02-01

The propaganda for the use of condoms remains one of the mainstay for prevention of human immunodeficiency virus (HIV) transmission. In spite of the proven efficacy of condom, some moral, social and psychological obstacles are still prevalent, hindering the use of condoms. The study tried to construct a short condom-attitude scale for use among the migrant workers, a major bridge population in India. The study was conducted among the male migrant workers who were 18-49 years old, sexually active and had heard about condoms and were engaged in nonformal jobs. We recruited 234 and 280 candidates for Phase 1 and Phase 2 respectively. Ten items from the original 40-item Brown's ATC (attitude towards condom) scale were selected in Phase 1. After analysis of Phase 1 results, using principal component analysis six items were found appropriate for measuring attitude towards condom use. These six items were then administered in another group in Phase 2. Utilizing Pearson's correlations, scale items were examined in terms of their mean response scores and the correlation matrix between items. Cornbach's alpha and construct validity were also assessed for the entire sample. Study subjects were categorized as condom users and nonusers. The scale structure was explored by analyzing response scores with respect to the items, using principal component analysis followed by varimax rotation analysis. Principal component analysis revealed that the first factor accounted for 71% of the variance, with eigenvalue greater than one. Eigenvalues of the second factor was less than one. Application of screen test suggests only one factor was dominant. Mean score of six items among condom users was 20.45 and that among nonusers was 16.67, which was statistically significant (P<0.01). Cornbach's alpha coefficient was 0.92. This tailor-made attitude-toward-condom-use scale, targeted for most vulnerable people in India, can be included in any rapid survey for assessing the existing beliefs and attitudes toward condoms and also for evaluating efficacy of an intervention program.

Mapping Common Aphasia Assessments to Underlying Cognitive Processes and Their Neural Substrates.

PubMed

Lacey, Elizabeth H; Skipper-Kallal, Laura M; Xing, Shihui; Fama, Mackenzie E; Turkeltaub, Peter E

2017-05-01

Understanding the relationships between clinical tests, the processes they measure, and the brain networks underlying them, is critical in order for clinicians to move beyond aphasia syndrome classification toward specification of individual language process impairments. To understand the cognitive, language, and neuroanatomical factors underlying scores of commonly used aphasia tests. Twenty-five behavioral tests were administered to a group of 38 chronic left hemisphere stroke survivors and a high-resolution magnetic resonance image was obtained. Test scores were entered into a principal components analysis to extract the latent variables (factors) measured by the tests. Multivariate lesion-symptom mapping was used to localize lesions associated with the factor scores. The principal components analysis yielded 4 dissociable factors, which we labeled Word Finding/Fluency, Comprehension, Phonology/Working Memory Capacity, and Executive Function. While many tests loaded onto the factors in predictable ways, some relied heavily on factors not commonly associated with the tests. Lesion symptom mapping demonstrated discrete brain structures associated with each factor, including frontal, temporal, and parietal areas extending beyond the classical language network. Specific functions mapped onto brain anatomy largely in correspondence with modern neural models of language processing. An extensive clinical aphasia assessment identifies 4 independent language functions, relying on discrete parts of the left middle cerebral artery territory. A better understanding of the processes underlying cognitive tests and the link between lesion and behavior may lead to improved aphasia diagnosis, and may yield treatments better targeted to an individual's specific pattern of deficits and preserved abilities.

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

PubMed

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.

Thermal Analysis of Fermilab Mu2e Beamstop and Structural Analysis of Beamline Components

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

Narug, Colin S.

The Mu2e project at Fermilab National Accelerator Laboratory aims to observe the unique conversion of muons to electrons. The success or failure of the experiment to observe this conversion will further the understanding of the standard model of physics. Using the particle accelerator, protons will be accelerated and sent to the Mu2e experiment, which will separate the muons from the beam. The muons will then be observed to determine their momentum and the particle interactions occur. At the end of the Detector Solenoid, the internal components will need to absorb the remaining particles of the experiment using polymer absorbers. Becausemore » the internal structure of the beamline is in a vacuum, the heat transfer mechanisms that can disperse the energy generated by the particle absorption is limited to conduction and radiation. To determine the extent that the absorbers will heat up over one year of operation, a transient thermal finite element analysis has been performed on the Muon Beam Stop. The levels of energy absorption were adjusted to determine the thermal limit for the current design. Structural finite element analysis has also been performed to determine the safety factors of the Axial Coupler, which connect and move segments of the beamline. The safety factor of the trunnion of the Instrument Feed Through Bulk Head has also been determined for when it is supporting the Muon Beam Stop. The results of the analysis further refine the design of the beamline components prior to testing, fabrication, and installation.« less

Identification of Ginger (Zingiber officinale Roscoe) Volatiles and Localization of Aroma-Active Constituents by GC-Olfactometry.

PubMed

Pang, Xueli; Cao, Jianmin; Wang, Dabin; Qiu, Jun; Kong, Fanyu

2017-05-24

For the characterization of chemical components contributing to the aroma of ginger, which could benefit the development of deep-processed ginger products, volatile extracts were isolated by a combination of direct solvent extraction-solvent-assisted flavor evaporation and static headspace analysis. Aroma-impact components were identified by gas chromatography-olfactometry-mass spectrometry, and the most potent odorants were further screened by aroma extract dilution analysis (AEDA) and static headspace dilution analysis (SHDA). The AEDA results revealed that geranial, eucalyptol, β-linalool, and bornyl acetate were the most potent odorants, exhibiting the highest flavor dilution factor (FD factor) of 2187. SHDA indicated that the predominant headspace odorants were α-pinene and eucalyptol. In addition, odorants exhibiting a high FD factor in SHDA were estimated to be potent aroma contributors in AEDA. The predominant odorants were found to be monoterpenes and sesquiterpenes, as along with their oxygenated derivatives, providing minty, lemon-like, herbal, and woody aromas. On the other hand, three highly volatile compounds detected by SHDA were not detected by AEDA, whereas 34 high-polarity, low-volatility compounds were identified only by AEDA, demonstrating the complementary natures of SHDA and AEDA and the necessity of utilizing both techniques to accurately characterize the aroma of ginger.

Genetic diversity analysis of fruit characteristics of hawthorn germplasm.

PubMed

Su, K; Guo, Y S; Wang, G; Zhao, Y H; Dong, W X

2015-12-07

One hundred and six accessions of hawthorn intraspecific resources, from the National Germplasm Repository at Shenyang, were subjected to genetic diversity and principal component analysis based on evaluation data of 15 fruit traits. Results showed that the genetic diversity of hawthorn fruit traits varied. Among the 15 traits, the fruit shape variable coefficient had the most obvious evaluation, followed by fruit surface state, dot color, taste, weight of single fruit, sepal posture, peduncle form, and metula traits. These are the primary traits by which hawthorn could be classified in the future. The principal component demonstrated that these traits are the most influential factors of hawthorn fruit characteristics.

A Component-Centered Meta-Analysis of Family-Based Prevention Programs for Adolescent Substance Use

PubMed Central

Roseth, Cary J.; Fosco, Gregory M.; Lee, You-kyung; Chen, I-Chien

2016-01-01

Although research has documented the positive effects of family-based prevention programs, the field lacks specific information regarding why these programs are effective. The current study summarized the effects of family-based programs on adolescent substance use using a component-based approach to meta-analysis in which we decomposed programs into a set of key topics or components that were specifically addressed by program curricula (e.g., parental monitoring/behavior management, problem solving, positive family relations, etc.). Components were coded according to the amount of time spent on program services that targeted youth, parents, and the whole family; we also coded effect sizes across studies for each substance-related outcome. Given the nested nature of the data, we used hierarchical linear modeling to link program components (Level 2) with effect sizes (Level 1). The overall effect size across programs was .31, which did not differ by type of substance. Youth-focused components designed to encourage more positive family relationships and a positive orientation toward the future emerged as key factors predicting larger than average effect sizes. Our results suggest that, within the universe of family-based prevention, where components such as parental monitoring/behavior management are almost universal, adding or expanding certain youth-focused components may be able to enhance program efficacy. PMID:27064553

Psychometric Properties of the Persian Version of the Social Anxiety - Acceptance and Action Questionnaire.

PubMed

Soltani, Esmail; Bahrainian, Seyed Abdolmajid; Masjedi Arani, Abbas; Farhoudian, Ali; Gachkar, Latif

2016-06-01

Social anxiety disorder is often related to specific impairment or distress in different areas of life, including occupational, social and family settings. The purpose of the present study was to examine the psychometric properties of the persian version of the social anxiety-acceptance and action questionnaire (SA-AAQ) in university students. In this descriptive cross-sectional study, 324 students from Shahid Beheshti University of Medical Sciences participated via the cluster sampling method during year 2015. Factor analysis by the principle component analysis method, internal consistency analysis, and convergent and divergent validity were conducted to examine the validity of the SA-AAQ. To calculate the reliability of the SA-AAQ, Cronbach's alpha and test-retest reliability were used. The results from factor analysis by principle component analysis method yielded three factors that were named acceptance, action and non-judging of experience. The three-factor solution explained 51.82% of the variance. Evidence for the internal consistency of SA-AAQ was obtained via calculating correlations between SA-AAQ and its subscales. Support for convergent and discriminant validity of the SA-AAQ via its correlations with the acceptance and action questionnaire - II, social interaction anxiety scale, cognitive fusion questionnaire, believability of anxious feelings and thoughts questionnaire, valued living questionnaire and WHOQOL- BREF was obtained. The reliability of the SA-AAQ via calculating Cronbach's alpha and test-retest coefficients yielded values of 0.84 and 0.84, respectively. The Iranian version of the SA-AAQ has acceptable levels of psychometric properties in university students. The SA-AAQ is a valid and reliable measure to be utilized in research investigations and therapeutic interventions.

Psychometric Properties of the Persian Version of the Social Anxiety - Acceptance and Action Questionnaire

PubMed Central

Soltani, Esmail; Bahrainian, Seyed Abdolmajid; Masjedi Arani, Abbas; Farhoudian, Ali; Gachkar, Latif

2016-01-01

Background Social anxiety disorder is often related to specific impairment or distress in different areas of life, including occupational, social and family settings. Objective The purpose of the present study was to examine the psychometric properties of the persian version of the social anxiety-acceptance and action questionnaire (SA-AAQ) in university students. Materials and Methods In this descriptive cross-sectional study, 324 students from Shahid Beheshti University of Medical Sciences participated via the cluster sampling method during year 2015. Factor analysis by the principle component analysis method, internal consistency analysis, and convergent and divergent validity were conducted to examine the validity of the SA-AAQ. To calculate the reliability of the SA-AAQ, Cronbach’s alpha and test-retest reliability were used. Results The results from factor analysis by principle component analysis method yielded three factors that were named acceptance, action and non-judging of experience. The three-factor solution explained 51.82% of the variance. Evidence for the internal consistency of SA-AAQ was obtained via calculating correlations between SA-AAQ and its subscales. Support for convergent and discriminant validity of the SA-AAQ via its correlations with the acceptance and action questionnaire - II, social interaction anxiety scale, cognitive fusion questionnaire, believability of anxious feelings and thoughts questionnaire, valued living questionnaire and WHOQOL- BREF was obtained. The reliability of the SA-AAQ via calculating Cronbach’s alpha and test-retest coefficients yielded values of 0.84 and 0.84, respectively. Conclusions The Iranian version of the SA-AAQ has acceptable levels of psychometric properties in university students. The SA-AAQ is a valid and reliable measure to be utilized in research investigations and therapeutic interventions. PMID:27803719

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

PubMed

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

2011-01-01

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

The dimensions of responsiveness of a health system: a Taiwanese perspective.

PubMed

Hsu, Chih-Cheng; Chen, Likwang; Hu, Yu-Whuei; Yip, Winnie; Shu, Chen-Chun

2006-03-17

Responsiveness is an indicator used to measure how well a health system performs relative to non-health aspects. This study assessed whether seven dimensions proposed by the World Health Organization (WHO) to measure responsiveness (dignity, autonomy, confidentiality, prompt attention, social support, basic amenities, and choices of providers) are applicable in evaluating the health system of Taiwan. A key informant survey and focus group research were used in this study. The translated WHO proposed questionnaire was sent to 205 nominated key informants by mail, and 132 (64.4%) were returned. We used principal component analysis to extract factors. Linear regression analysis was used to assess the relationship between the total score and the extracted factors. A qualitative content analysis was also carried out in focus group research. Principal component analysis produced five factors (respect, access, confidentiality, basic amenities, and social support) that explained 63.5% of the total variances. These five factors demonstrated acceptable internal consistency and four of them (except social support) were significantly correlated with the total responsiveness score. The focus group interviews revealed health providers' communication ability and medical ethics were also highly appraised by Taiwanese. When the performance of a health system is to be evaluated, elements of responsiveness proposed by WHO may have to be tailored to fit different cultural backgrounds. Four key features illustrate the uniqueness of Taiwanese perspectives: the idea of autonomy may not be conceptualized, prompt attention and choice of providers are on the same track, social support during care is trivially correlated to the total responsiveness score, and accountability of health providers is deemed essential to a health system.

Psychometric analysis of the Swedish version of the General Medical Council's multi source feedback questionnaires.

PubMed

Olsson, Jan-Eric; Wallentin, Fan Yang; Toth-Pal, Eva; Ekblad, Solvig; Bertilson, Bo Christer

2017-07-10

To determine the internal consistency and the underlying components of our translated and adapted Swedish version of the General Medical Council's multisource feedback questionnaires (GMC questionnaires) for physicians and to confirm which aspects of good medical practice the latent variable structure reflected. From October 2015 to March 2016, residents in family medicine in Sweden were invited to participate in the study and to use the Swedish version to perform self-evaluations and acquire feedback from both their patients and colleagues. The validation focused on internal consistency and construct validity. Main outcome measures were Cronbach's alpha coefficients, Principal Component Analysis, and Confirmatory Factor Analysis indices. A total of 752 completed questionnaires from patients, colleagues, and residents were analysed. Of these, 213 comprised resident self-evaluations, 336 were feedback from residents' patients, and 203 were feedback from residents' colleagues. Cronbach's alpha coefficients of the scores were 0.88 from patients, 0.93 from colleagues, and 0.84 in the self-evaluations. The Confirmatory Factor Analysis validated two models that fit the data reasonably well and reflected important aspects of good medical practice. The first model had two latent factors for patient-related items concerning empathy and consultation management, and the second model had five latent factors for colleague-related items, including knowledge and skills, attitude and approach, reflection and development, teaching, and trust. The current Swedish version seems to be a reliable and valid tool for formative assessment for resident physicians and their supervisors. This needs to be verified in larger samples.

Psychometric analysis of the Swedish version of the General Medical Council's multi source feedback questionnaires

PubMed Central

Wallentin, Fan Yang; Toth-Pal, Eva; Ekblad, Solvig; Bertilson, Bo Christer

2017-01-01

Objectives To determine the internal consistency and the underlying components of our translated and adapted Swedish version of the General Medical Council's multisource feedback questionnaires (GMC questionnaires) for physicians and to confirm which aspects of good medical practice the latent variable structure reflected. Methods From October 2015 to March 2016, residents in family medicine in Sweden were invited to participate in the study and to use the Swedish version to perform self-evaluations and acquire feedback from both their patients and colleagues. The validation focused on internal consistency and construct validity. Main outcome measures were Cronbach’s alpha coefficients, Principal Component Analysis, and Confirmatory Factor Analysis indices. Results A total of 752 completed questionnaires from patients, colleagues, and residents were analysed. Of these, 213 comprised resident self-evaluations, 336 were feedback from residents’ patients, and 203 were feedback from residents’ colleagues. Cronbach’s alpha coefficients of the scores were 0.88 from patients, 0.93 from colleagues, and 0.84 in the self-evaluations. The Confirmatory Factor Analysis validated two models that fit the data reasonably well and reflected important aspects of good medical practice. The first model had two latent factors for patient-related items concerning empathy and consultation management, and the second model had five latent factors for colleague-related items, including knowledge and skills, attitude and approach, reflection and development, teaching, and trust. Conclusions The current Swedish version seems to be a reliable and valid tool for formative assessment for resident physicians and their supervisors. This needs to be verified in larger samples. PMID:28704204

Urbanization and human health in urban India: institutional analysis of water-borne diseases in Ahmedabad.

PubMed

Saravanan, V S; Ayessa Idenal, Marissa; Saiyed, Shahin; Saxena, Deepak; Gerke, Solvay

2016-10-01

Diseases are rapidly urbanizing. Ageing infrastructures, high levels of inequality, poor urban governance, rapidly growing economies and highly dense and mobile populations all create environments rife for water-borne diseases. This article analyzes the role of institutions as crosscutting entities among a myriad of factors that breed water-borne diseases in the city of Ahmedabad, India. It applies 'path dependency' and a 'rational choice' perspective to understand the factors facilitating the breeding of diseases. This study is based on household surveys of approximately 327 households in two case study wards and intermittent interviews with key informants over a period of 2 years. Principle component analysis is applied to reduce the data and convert a set of observations, which potentially correlate with each other, into components. Institutional analyses behind these components reveal the role of social actors in exploiting the deeply rooted inefficiencies affecting urban health. This has led to a vicious cycle; breaking this cycle requires understanding the political dynamics that underlie the exposure and prevalence of diseases to improve urban health. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Development of AMSTAR: a measurement tool to assess the methodological quality of systematic reviews.

PubMed

Shea, Beverley J; Grimshaw, Jeremy M; Wells, George A; Boers, Maarten; Andersson, Neil; Hamel, Candyce; Porter, Ashley C; Tugwell, Peter; Moher, David; Bouter, Lex M

2007-02-15

Our objective was to develop an instrument to assess the methodological quality of systematic reviews, building upon previous tools, empirical evidence and expert consensus. A 37-item assessment tool was formed by combining 1) the enhanced Overview Quality Assessment Questionnaire (OQAQ), 2) a checklist created by Sacks, and 3) three additional items recently judged to be of methodological importance. This tool was applied to 99 paper-based and 52 electronic systematic reviews. Exploratory factor analysis was used to identify underlying components. The results were considered by methodological experts using a nominal group technique aimed at item reduction and design of an assessment tool with face and content validity. The factor analysis identified 11 components. From each component, one item was selected by the nominal group. The resulting instrument was judged to have face and content validity. A measurement tool for the 'assessment of multiple systematic reviews' (AMSTAR) was developed. The tool consists of 11 items and has good face and content validity for measuring the methodological quality of systematic reviews. Additional studies are needed with a focus on the reproducibility and construct validity of AMSTAR, before strong recommendations can be made on its use.

Exploring the Sensitivity of Horn's Parallel Analysis to the Distributional Form of Random Data

ERIC Educational Resources Information Center

Dinno, Alexis

2009-01-01

Horn's parallel analysis (PA) is the method of consensus in the literature on empirical methods for deciding how many components/factors to retain. Different authors have proposed various implementations of PA. Horn's seminal 1965 article, a 1996 article by Thompson and Daniel, and a 2004 article by Hayton, Allen, and Scarpello all make assertions…

Medical University admission test: a confirmatory factor analysis of the results.

PubMed

Luschin-Ebengreuth, Marion; Dimai, Hans P; Ithaler, Daniel; Neges, Heide M; Reibnegger, Gilbert

2016-05-01

The Graz Admission Test has been applied since the academic year 2006/2007. The validity of the Test was demonstrated by a significant improvement of study success and a significant reduction of dropout rate. The purpose of this study was a detailed analysis of the internal correlation structure of the various components of the Graz Admission Test. In particular, the question investigated was whether or not the various test parts constitute a suitable construct which might be designated as "Basic Knowledge in Natural Science." This study is an observational investigation, analyzing the results of the Graz Admission Test for the study of human medicine and dentistry. A total of 4741 applicants were included in the analysis. Principal component factor analysis (PCFA) as well as techniques from structural equation modeling, specifically confirmatory factor analysis (CFA), were employed to detect potential underlying latent variables governing the behavior of the measured variables. PCFA showed good clustering of the science test parts, including also text comprehension. A putative latent variable "Basic Knowledge in Natural Science," investigated by CFA, was indeed shown to govern the response behavior of the applicants in biology, chemistry, physics, and mathematics as well as text comprehension. The analysis of the correlation structure of the various test parts confirmed that the science test parts together with text comprehension constitute a satisfactory instrument for measuring a latent construct variable "Basic Knowledge in Natural Science." The present results suggest the fundamental importance of basic science knowledge for results obtained in the framework of the admission process for medical universities.

Size distributions of ambient air particles and enrichment factor analyses of metallic elements at Taichung Harbor near the Taiwan Strait

NASA Astrophysics Data System (ADS)

Fang, Guor-Cheng; Wu, Yuh-Shen; Chang, Shih-Yu; Huang, Shih-Han; Rau, Jui-Yeh

2006-10-01

This work attempts to characterize metallic elements associated with atmospheric particulate matter on a dry deposition plate, a TE-PUF high-volume air sampler and a universal air sampler. Dry deposition fluxes of particulates and concentrations of total suspended particulate, fine (PM 2.5) and coarse (PM 2.5-10) particulate matters were collected at Taichung harbor sampling sites from August 2004 to January 2005. Chemical analyses of metallic elements were made using a flame atomic absorption spectrophotometer coupled with hollow cathode lamps. Concentrations of metal elements in the forms of coarse particles and fine particles as well as the coarse/fine particulate ratios were presented. Statistical methods such as correlation analysis, principal component analysis and enrichment factor analysis were performed to compare the chemical components and identify possible emission sources at the sampling sites. Metallic elements of Cu, Zn, Pb, Cr, Ni and Mg had higher EF crust ratios in winter and spring than in summer and autumn. Diurnal and nocturnal variations of metallic element concentrations in fine and coarse particles were also discussed.

Psychometric properties of the Exercise Benefits/Barriers Scale in Mexican elderly women

PubMed Central

Enríquez-Reyna, María Cristina; Cruz-Castruita, Rosa María; Ceballos-Gurrola, Oswaldo; García-Cadena, Cirilo Humberto; Hernández-Cortés, Perla Lizeth; Guevara-Valtier, Milton Carlos

2017-01-01

ABSTRACT Objective: analyze and assess the psychometric properties of the subscales in the Spanish version of the Exercise Benefits/Barriers Scale in an elderly population in the Northeast of Mexico. Method: methodological study. The sample consisted of 329 elderly associated with one of the five public centers for senior citizens in the metropolitan area of Northeast Mexico. The psychometric properties included the assessment of the Cronbach's alpha coefficient, the Kaiser Meyer Olkin coefficient, the inter-item correlation, exploratory and confirmatory factor analysis. Results: in the principal components analysis, two components were identified based on the 43 items in the scale. The item-total correlation coefficient of the exercise benefits subscale was good. Nevertheless, the coefficient for the exercise barriers subscale revealed inconsistencies. The reliability and validity were acceptable. The confirmatory factor analysis revealed that the elimination of items improved the goodness of fit of the baseline scale, without affecting its validity or reliability. Conclusion: the Exercise Benefits/Barriers subscale presented satisfactory psychometric properties for the Mexican context. A 15-item short version is presented with factorial structure, validity and reliability similar to the complete scale. PMID:28591306

Helicopter Drive System on-Condition Maintenance Capability (UH-1/AH-1)

DTIC Science & Technology

1976-07-01

Capability 17 2.2 FACTORS LIMITING THE PERFORMANCE OF THE STUDY . . 18 2.3 ASSUMPTIONS USED IN THE ANALYSIS 20 2.3.1 Assembly Operability 20 2.3.2...DRIVE SYSTEM COMPONENTS AND THEIR EFFECTIVITY 64 2 AIRCRAFT TECHNICAL MANUALS USED DURING THE STUDY 66 3 DRIVE SYSTEM COMPONENTS DA2410 RECORDS...the federal stock number, and current effectivity of these assemblies. The general approach used was to examine the overhaul and acci- dent records

Quantization of Motor Activity into Primitives and Time-Frequency Atoms Using Independent Component Analysis and Matching Pursuit Algorithms

DTIC Science & Technology

2001-10-25

form: (1) A is a scaling factor, t is time and r a coordinate vector describing the limb configuration. We...combination of limb state and EMG. In our early examination of EMG we detected underlying groups of muscles and phases of activity by inspection and...representations of EEG or other biological signals has been thoroughly explored. Such components might be used as a basis for neuroprosthetic control

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

Influence of soil conditions on dissolved organic matter leached from forest and wetland soils: a controlled growth chamber study.

PubMed

Kim, Eun-Ah; Nguyen, Hang Vo-Minh; Oh, Hae Sung; Hur, Jin; Choi, Jung Hyun

2016-03-01

This study investigated the effects of various soil conditions, including drying-rewetting, nitrogen deposition, and temperature rise, on the quantities and the composition of dissolved organic matter leached from forest and wetland soils. A set of forest and wetland soils with and without the nitrogen deposition were incubated in the growth chambers under three different temperatures. The moisture contents were kept constant, except for two-week drying intervals. Comparisons between the original and the treated samples revealed that drying-rewetting was a crucial environmental factor driving changes in the amount of dissolved organic carbon (DOC). The DOC was also notably increased by the nitrogen deposition to the dry forest soil and was affected by the temperature of the dry wetland soil. A parallel factor (PARAFAC) analysis identified three sub-fractions of the fluorescent dissolved organic matter (FDOM) from the fluorescence excitation-emission matrices (EEMs), and their compositions depended on drying-rewetting. The data as a whole, including the DOC and PARAFAC components and other optical indices, were possibly explained by the two main variables, which were closely related with the PARAFAC components and DOC based on principal component analysis (PCA). Our results suggested that the DOC and PARAFAC component information could provide a comprehensive interpretation of the changes in the soil-leached DOM in response to the different environmental conditions.

Analysis of factors controlling sediment phosphorus flux potential of wetlands in Hulun Buir grassland by principal component and path analysis method.

PubMed

He, Jing; Su, Derong; Lv, Shihai; Diao, Zhaoyan; Ye, Shengxing; Zheng, Zhirong

2017-11-08

Phosphorus (P) flux potential can predict the trend of phosphorus release from wetland sediments to water and provide scientific parameters for further monitoring and management for phosphorus flux from wetland sediments to overlying water. Many studies have focused on factors affecting sediment P flux potential in sediment-water interface, but rarely on the relationship among these factors. In the present study, experiment on sediment P flux potential in sediment-water interface was conducted in six wetlands in Hulun Buir grassland, China and the relationships among sediment P flux potential in sediment-water interface, sediment physical properties, and sediment chemical characteristics were examined. Principal component analysis and path analysis were used to discuss these data in correlation coefficient, direct, and indirect effects on sediment P flux potential in sediment-water interface. Results indicated that the major factors affecting sediment P flux potential in sediment-water interface were amount of organophosphate-degradation bacterium in sediment, Ca-P content, and total phosphorus concentrations. The factors of direct influence sediment P flux potential were sediment Ca-P content, Olsen-P content, SOC content, and sediment Al-P content. The indirect influence sediment P flux potential in sediment-water interface was sediment Olsen-P content, sediment SOC content, sediment Ca-P content, and sediment Al-P content. And the standard multiple regression describing the relationship between sediment P flux potential in sediment-water interface and its major effect factors was Y = 5.849 - 1.025X 1  - 1.995X 2  + 0.188X 3  - 0.282X 4 (r = 0.9298, p < 0.01, n = 96), where Y is sediment P flux potential in sediment-water interface, X 1 is sediment Ca-P content, X 2 is sediment Olsen-P content, X 3 is sediment SOC content, and X 4 is sediment Al-P content. Therefore, future research will focus on these sediment properties to analyze the interrelation among sediment properties factors, main vegetable factors, and environment factors which influence the sediment P flux potential in sediment-water interface.

Temporal dynamic of malaria in a suburban area along the Niger River.

PubMed

Sissoko, Mahamadou Soumana; Sissoko, Kourane; Kamate, Bourama; Samake, Yacouba; Goita, Siaka; Dabo, Abdoulaye; Yena, Mama; Dessay, Nadine; Piarroux, Renaud; Doumbo, Ogobara K; Gaudart, Jean

2017-10-23

Even if rainfall and temperature are factors classically associated to malaria, little is known about other meteorological factors, their variability and combinations related to malaria, in association with river height variations. Furthermore, in suburban area, urbanization and growing population density should be assessed in relation to these environmental factors. The aim of this study was to assess the impact of combined environmental, meteorological and hydrological factors on malaria incidence through time in the context of urbanization. Population observational data were prospectively collected. Clinical malaria was defined as the presence of parasites in addition to clinical symptoms. Meteorological and hydrological factors were measured daily. For each factors variation indices were estimated. Urbanization was yearly estimated assessing satellite imaging and field investigations. Principal component analysis was used for dimension reduction and factors combination. Lags between malaria incidences and the main components were assessed by cross-correlation functions. Generalized additive model was used to assess relative impact of different environmental components, taking into account lags, and modelling non-linear relationships. Change-point analysis was used to determine transmission periods within years. Malaria incidences were dominated by annual periodicity and varied through time without modification of the dynamic, with no impact of the urbanization. The main meteorological factor associated with malaria was a combination of evaporation, humidity and rainfall, with a lag of 3 months. The relationship between combined temperature factors showed a linear impact until reaching high temperatures limiting malaria incidence, with a lag 3.25 months. Height and variation of the river were related to malaria incidence (respectively 6 week lag and no lag). The study emphasizes no decreasing trend of malaria incidence despite accurate access to care and control strategies in accordance to international recommendations. Furthermore, no decreasing trend was showed despite the urbanization of the area. Malaria transmission remain increase 3 months after the beginning of the dry season. Addition to evaporation versus humidity/rainfall, nonlinear relationship for temperature and river height and variations have to be taken into account when implementing malaria control programmes.

Differential principal component analysis of ChIP-seq.

PubMed

Ji, Hongkai; Li, Xia; Wang, Qian-fei; Ning, Yang

2013-04-23

We propose differential principal component analysis (dPCA) for analyzing multiple ChIP-sequencing datasets to identify differential protein-DNA interactions between two biological conditions. dPCA integrates unsupervised pattern discovery, dimension reduction, and statistical inference into a single framework. It uses a small number of principal components to summarize concisely the major multiprotein synergistic differential patterns between the two conditions. For each pattern, it detects and prioritizes differential genomic loci by comparing the between-condition differences with the within-condition variation among replicate samples. dPCA provides a unique tool for efficiently analyzing large amounts of ChIP-sequencing data to study dynamic changes of gene regulation across different biological conditions. We demonstrate this approach through analyses of differential chromatin patterns at transcription factor binding sites and promoters as well as allele-specific protein-DNA interactions.

Comparison of gray matter volume and thickness for analysis of cortical changes in Alzheimer's disease

NASA Astrophysics Data System (ADS)

Liu, Jiachao; Li, Ziyi; Chen, Kewei; Yao, Li; Wang, Zhiqun; Li, Kunchen; Guo, Xiaojuan

2011-03-01

Gray matter volume and cortical thickness are two indices of concern in brain structure magnetic resonance imaging research. Gray matter volume reflects mixed-measurement information of cerebral cortex, while cortical thickness reflects only the information of distance between inner surface and outer surface of cerebral cortex. Using Scaled Subprofile Modeling based on Principal Component Analysis (SSM_PCA) and Pearson's Correlation Analysis, this study further provided quantitative comparisons and depicted both global relevance and local relevance to comprehensively investigate morphometrical abnormalities in cerebral cortex in Alzheimer's disease (AD). Thirteen patients with AD and thirteen age- and gender-matched healthy controls were included in this study. Results showed that factor scores from the first 8 principal components accounted for ~53.38% of the total variance for gray matter volume, and ~50.18% for cortical thickness. Factor scores from the fifth principal component showed significant correlation. In addition, gray matter voxel-based volume was closely related to cortical thickness alterations in most cortical cortex, especially, in some typical abnormal brain regions such as insula and the parahippocampal gyrus in AD. These findings suggest that these two measurements are effective indices for understanding the neuropathology in AD. Studies using both gray matter volume and cortical thickness can separate the causes of the discrepancy, provide complementary information and carry out a comprehensive description of the morphological changes of brain structure.

Environmental Quality Assessment of Built Areas with High Vacancy

NASA Astrophysics Data System (ADS)

Jiang, Y.; Yuan, Y.; Neale, A. C.

2015-12-01

Around the world, many urban areas are challenged by vacant and abandoned residential and business property. High vacancy areas have often been associated with increasing public safety problems and declining property values and subsequent tax base. High vacancy can lead to visible signs of city decline and significant barriers to the revitalization of cities. Addressing the problem of vacancy requires knowledge of vacancy patterns and their possible contributing factors. In this study, we evaluated the ten year (2005-2015) urban environmental changes for some high vacancy areas. Social and economic variables derived from U.S. census data such as non-white population, employment rate, housing price, and environmental variables derived from National Land Cover Data such as land cover and impervious area, were used as the basis for analysis. Correlation analysis and principle components analysis were performed at the Census Block Group level. Three components were identified and interpreted as economic status, urbanness, and greenness. A synthetic Urban Environmental Quality (UEQ) index was developed by integrating the three principle components according to their weights. Comparisons of the UEQ indices between the 2005 and 2015 in the increasingly high vacancy area provided useful information for investigating the possible associations between social, economic, and environmental factors, and the vacancy status. This study could provide useful information for understanding the complex issues leading to vacancy and facilitating future rehabilitation of vacant urban area.

Comprehensive Analysis of Two Downburst-Related Aircraft Accidents

NASA Technical Reports Server (NTRS)

Shen, J.; Parks, E. K.; Bach, R. E.

1996-01-01

Although downbursts have been identified as the major cause of a number of aircraft takeoff and landing accidents, only the 1985 Dallas/Fort Worth (DFW) and the more recent (July 1994) Charlotte, North Carolina, landing accidents provided sufficient onboard recorded data to perform a comprehensive analysis of the downburst phenomenon. The first step in the present analysis was the determination of the downburst wind components. Once the wind components and their gradients were determined, the degrading effect of the wind environment on the airplane's performance was calculated. This wind-shear-induced aircraft performance degradation, sometimes called the F-factor, was broken down into two components F(sub 1) and F(sub 2), representing the effect of the horizontal wind gradient and the vertical wind velocity, respectively. In both the DFW and Charlotte cases, F(sub 1) was found to be the dominant causal factor of the accident. Next, the aircraft in the two cases were mathematically modeled using the longitudinal equations of motion and the appropriate aerodynamic parameters. Based on the aircraft model and the determined winds, the aircraft response to the recorded pilot inputs showed good agreement with the onboard recordings. Finally, various landing abort strategies were studied. It was concluded that the most acceptable landing abort strategy from both an analytical and pilot's standpoint was to hold constant nose-up pitch attitude while operating at maximum engine thrust.

Serum NGF, BDNF and IL-6 Levels in Postpartum Mothers As Predictors of Infant Development: The Influence of Affective Disorders

PubMed Central

Pinheiro, Karen Amaral Tavares; Pinheiro, Ricardo Tavares; Coelho, Fábio Monteiro da Cunha; da Silva, Ricardo Azevedo; Quevedo, Luciana Ávila; Schwanz, Cristina Carvalhal; Wiener, Carolina David; Manfro, Gisele Gus; Giovenardi, Márcia; Lucion, Aldo Bolten; de Souza, Diogo Onofre; Portela, Luis Valmor; Oses, Jean Pierre

2014-01-01

Background Early adverse experiences are associated with increased risk of developing psychiatric disorders, although little is known about the neurobiological mediators involved. The mechanisms by which early environmental influences may mediate vulnerability in the development of offspring await further investigation. The present study correlated the NGF, BDNF, IL-6 and cortisol levels of mothers with postpartum affective disorders (PPAD) with infant development. Methods A longitudinal study was performed with 152 pregnant women and their infants. Between 60 and 120 days after delivery, women were interviewed and provided biological samples for biochemical analysis, and the infants were examined for neurobiological-motor development. Results Overall, the mothers' history of affective disorders, PPAD and anxiety disorder were associated with infant motor development. Using an adjusted linear regression analysis, PPAD (p = 0.049), maternal anxiety disorder (p = 0.043), NGF level (p = 0.034) and infant cortisol level (p = 0.013) were associated with infant motor development. Using a factorial analysis of primary components, two components were retained. The psychological factor was characterized by a positive loading of a history of affective disorder, PPAD and anxiety disorder. For the biological factor, infant cortisol adhered negatively with infant motor development, but NGF was positively associated. The psychological factor had a negative association, but the biological factor had a positive association with infant motor development. Conclusions There are few studies that have focused on the relationship of biomarkers and infant neurodevelopment. Our study points that psychological and biological factors are associated with infant motor development, however the causal relationship between these factors is still to be defined. PMID:24733087

Genetics of Variation in Serum Uric Acid and Cardiovascular Risk Factors in Mexican Americans

PubMed Central

Voruganti, V. Saroja; Nath, Subrata D.; Cole, Shelley A.; Thameem, Farook; Jowett, Jeremy B.; Bauer, Richard; MacCluer, Jean W.; Blangero, John; Comuzzie, Anthony G.; Abboud, Hanna E.; Arar, Nedal H.

2009-01-01

Background: Elevated serum uric acid is associated with several cardiovascular disease (CVD) risk factors such as hypertension, inflammation, endothelial dysfunction, insulin resistance, dyslipidemia, and obesity. However, the role of uric acid as an independent risk factor for CVD is not yet clear. Objective: The aim of the study was to localize quantitative trait loci regulating variation in serum uric acid and also establish the relationship between serum uric acid and other CVD risk factors in Mexican Americans (n = 848; men = 310, women = 538) participating in the San Antonio Family Heart Study. Methods: Quantitative genetic analysis was conducted using variance components decomposition method, implemented in the software program SOLAR. Results: Mean ± sd of serum uric acid was 5.35 ± 1.38 mg/dl. Univariate genetic analysis showed serum uric acid and other CVD risk markers to be significantly heritable (P < 0.005). Bivariate analysis showed significant correlation of serum uric acid with body mass index, waist circumference, waist/hip ratio, total body fat, plasma insulin, serum triglycerides, high-density lipoprotein cholesterol, C-reactive protein, and granulocyte macrophage-colony stimulating factor (P < 0.05). A genome-wide scan for detecting quantitative trait loci regulating serum uric acid variation showed a significant logarithm of odds (LOD) score of 4.72 (empirical LOD score = 4.62; P < 0.00001) on chromosome 3p26. One LOD support interval contains 25 genes, of which an interesting candidate gene is chemokine receptor 2. Summary: There is a significant genetic component in the variation in serum uric acid and evidence of pleiotropy between serum uric acid and other cardiovascular risk factors. PMID:19001525

Serum NGF, BDNF and IL-6 levels in postpartum mothers as predictors of infant development: the influence of affective disorders.

PubMed

Pinheiro, Karen Amaral Tavares; Pinheiro, Ricardo Tavares; Coelho, Fábio Monteiro da Cunha; da Silva, Ricardo Azevedo; Quevedo, Luciana Ávila; Schwanz, Cristina Carvalhal; Wiener, Carolina David; Manfro, Gisele Gus; Giovenardi, Márcia; Lucion, Aldo Bolten; de Souza, Diogo Onofre; Portela, Luis Valmor; Oses, Jean Pierre

2014-01-01

Early adverse experiences are associated with increased risk of developing psychiatric disorders, although little is known about the neurobiological mediators involved. The mechanisms by which early environmental influences may mediate vulnerability in the development of offspring await further investigation. The present study correlated the NGF, BDNF, IL-6 and cortisol levels of mothers with postpartum affective disorders (PPAD) with infant development. A longitudinal study was performed with 152 pregnant women and their infants. Between 60 and 120 days after delivery, women were interviewed and provided biological samples for biochemical analysis, and the infants were examined for neurobiological-motor development. Overall, the mothers' history of affective disorders, PPAD and anxiety disorder were associated with infant motor development. Using an adjusted linear regression analysis, PPAD (p = 0.049), maternal anxiety disorder (p = 0.043), NGF level (p = 0.034) and infant cortisol level (p = 0.013) were associated with infant motor development. Using a factorial analysis of primary components, two components were retained. The psychological factor was characterized by a positive loading of a history of affective disorder, PPAD and anxiety disorder. For the biological factor, infant cortisol adhered negatively with infant motor development, but NGF was positively associated. The psychological factor had a negative association, but the biological factor had a positive association with infant motor development. There are few studies that have focused on the relationship of biomarkers and infant neurodevelopment. Our study points that psychological and biological factors are associated with infant motor development, however the causal relationship between these factors is still to be defined.

Trace elements in lake sediments measured by the PIXE technique

NASA Astrophysics Data System (ADS)

Gatti, Luciana V.; Mozeto, Antônio A.; Artaxo, Paulo

1999-04-01

Lakes are ecosystems where there is a great potential of metal accumulation in sediments due to their depositional characteristics. Total concentration of trace elements was measured on a 50 cm long sediment core from the Infernão Lake, that is an oxbow lake of the Moji-Guaçu River basin, in the state of São Paulo, Brazil. Dating of the core shows up to 180 yrs old sediment layers. The use of the PIXE technique for elemental analysis avoids the traditional acid digestion procedure common in other techniques. The multielemental characteristic of PIXE allows a simultaneous determination of about 20 elements in the sediment samples, such as, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Rb, Sr, Zr, Ba, and Pb. Average values for the elemental composition were found to be similar to the bulk crustal composition. The lake flooding pattern strongly influences the time series of the elemental profiles. Factor analysis of the elemental variability shows five factors. Two of the factors represent the mineralogical matrix, and others represent the organic component, a factor with lead, and another loaded with chromium. The mineralogical component consists of elements such as, Fe, Al, V, Ti, Mn, Ni, K, Zr, Sr, Cu and Zn. The variability of Si is explained by two distinct factors, because it is influenced by two different sources, aluminum-silicates and quartz, and the effect of inundation are different for each other. The organic matter is strongly associated with calcium, and also bounded with S, Zn, Cu and P. Lead and chromium appears as separated factors, although it is not clear the evidences for their anthropogenic origin. The techniques developed for sample preparation and PIXE analysis was proven as advantageous and provided very good reproducibility and accuracy.

Item response theory and factor analysis as a mean to characterize occurrence of response shift in a longitudinal quality of life study in breast cancer patients

PubMed Central

2014-01-01

Background The occurrence of response shift (RS) in longitudinal health-related quality of life (HRQoL) studies, reflecting patient adaptation to disease, has already been demonstrated. Several methods have been developed to detect the three different types of response shift (RS), i.e. recalibration RS, 2) reprioritization RS, and 3) reconceptualization RS. We investigated two complementary methods that characterize the occurrence of RS: factor analysis, comprising Principal Component Analysis (PCA) and Multiple Correspondence Analysis (MCA), and a method of Item Response Theory (IRT). Methods Breast cancer patients (n = 381) completed the EORTC QLQ-C30 and EORTC QLQ-BR23 questionnaires at baseline, immediately following surgery, and three and six months after surgery, according to the “then-test/post-test” design. Recalibration was explored using MCA and a model of IRT, called the Linear Logistic Model with Relaxed Assumptions (LLRA) using the then-test method. Principal Component Analysis (PCA) was used to explore reconceptualization and reprioritization. Results MCA highlighted the main profiles of recalibration: patients with high HRQoL level report a slightly worse HRQoL level retrospectively and vice versa. The LLRA model indicated a downward or upward recalibration for each dimension. At six months, the recalibration effect was statistically significant for 11/22 dimensions of the QLQ-C30 and BR23 according to the LLRA model (p ≤ 0.001). Regarding the QLQ-C30, PCA indicated a reprioritization of symptom scales and reconceptualization via an increased correlation between functional scales. Conclusions Our findings demonstrate the usefulness of these analyses in characterizing the occurrence of RS. MCA and IRT model had convergent results with then-test method to characterize recalibration component of RS. PCA is an indirect method in investigating the reprioritization and reconceptualization components of RS. PMID:24606836

A component analysis of positive behaviour support plans.

PubMed

McClean, Brian; Grey, Ian

2012-09-01

Positive behaviour support (PBS) emphasises multi-component interventions by natural intervention agents to help people overcome challenging behaviours. This paper investigates which components are most effective and which factors might mediate effectiveness. Sixty-one staff working with individuals with intellectual disability and challenging behaviours completed longitudinal competency-based training in PBS. Each staff participant conducted a functional assessment and developed and implemented a PBS plan for one prioritised individual. A total of 1,272 interventions were available for analysis. Measures of challenging behaviour were taken at baseline, after 6 months, and at an average of 26 months follow-up. There was a significant reduction in the frequency, management difficulty, and episodic severity of challenging behaviour over the duration of the study. Escape was identified by staff as the most common function, accounting for 77% of challenging behaviours. The most commonly implemented components of intervention were setting event changes and quality-of-life-based interventions. Only treatment acceptability was found to be related to decreases in behavioural frequency. No single intervention component was found to have a greater association with reductions in challenging behaviour.

Extracting factors for interest rate scenarios

NASA Astrophysics Data System (ADS)

Molgedey, L.; Galic, E.

2001-04-01

Factor based interest rate models are widely used for risk managing purposes, for option pricing and for identifying and capturing yield curve anomalies. The movements of a term structure of interest rates are commonly assumed to be driven by a small number of orthogonal factors such as SHIFT, TWIST and BUTTERFLY (BOW). These factors are usually obtained by a Principal Component Analysis (PCA) of historical bond prices (interest rates). Although PCA diagonalizes the covariance matrix of either the interest rates or the interest rate changes, it does not use both covariance matrices simultaneously. Furthermore higher linear and nonlinear correlations are neglected. These correlations as well as the mean reverting properties of the interest rates become crucial, if one is interested in a longer time horizon (infrequent hedging or trading). We will show that Independent Component Analysis (ICA) is a more appropriate tool than PCA, since ICA uses the covariance matrix of the interest rates as well as the covariance matrix of the interest rate changes simultaneously. Additionally higher linear and nonlinear correlations may be easily incorporated. The resulting factors are uncorrelated for various time delays, approximately independent but nonorthogonal. This is in contrast to the factors obtained from the PCA, which are orthogonal and uncorrelated for identical times only. Although factors from the ICA are nonorthogonal, it is sufficient to consider only a few factors in order to explain most of the variation in the original data. Finally we will present examples that ICA based hedges outperforms PCA based hedges specifically if the portfolio is sensitive to structural changes of the yield curve.

Evaluation of non-negative matrix factorization of grey matter in age prediction.

PubMed

Varikuti, Deepthi P; Genon, Sarah; Sotiras, Aristeidis; Schwender, Holger; Hoffstaedter, Felix; Patil, Kaustubh R; Jockwitz, Christiane; Caspers, Svenja; Moebus, Susanne; Amunts, Katrin; Davatzikos, Christos; Eickhoff, Simon B

2018-06-01

The relationship between grey matter volume (GMV) patterns and age can be captured by multivariate pattern analysis, allowing prediction of individuals' age based on structural imaging. Raw data, voxel-wise GMV and non-sparse factorization (with Principal Component Analysis, PCA) show good performance but do not promote relatively localized brain components for post-hoc examinations. Here we evaluated a non-negative matrix factorization (NNMF) approach to provide a reduced, but also interpretable representation of GMV data in age prediction frameworks in healthy and clinical populations. This examination was performed using three datasets: a multi-site cohort of life-span healthy adults, a single site cohort of older adults and clinical samples from the ADNI dataset with healthy subjects, participants with Mild Cognitive Impairment and patients with Alzheimer's disease (AD) subsamples. T1-weighted images were preprocessed with VBM8 standard settings to compute GMV values after normalization, segmentation and modulation for non-linear transformations only. Non-negative matrix factorization was computed on the GM voxel-wise values for a range of granularities (50-690 components) and LASSO (Least Absolute Shrinkage and Selection Operator) regression were used for age prediction. First, we compared the performance of our data compression procedure (i.e., NNMF) to various other approaches (i.e., uncompressed VBM data, PCA-based factorization and parcellation-based compression). We then investigated the impact of the granularity on the accuracy of age prediction, as well as the transferability of the factorization and model generalization across datasets. We finally validated our framework by examining age prediction in ADNI samples. Our results showed that our framework favorably compares with other approaches. They also demonstrated that the NNMF based factorization derived from one dataset could be efficiently applied to compress VBM data of another dataset and that granularities between 300 and 500 components give an optimal representation for age prediction. In addition to the good performance in healthy subjects our framework provided relatively localized brain regions as the features contributing to the prediction, thereby offering further insights into structural changes due to brain aging. Finally, our validation in clinical populations showed that our framework is sensitive to deviance from normal structural variations in pathological aging. Copyright © 2018 Elsevier Inc. All rights reserved.

Incipient fault detection study for advanced spacecraft systems

NASA Technical Reports Server (NTRS)

Milner, G. Martin; Black, Michael C.; Hovenga, J. Mike; Mcclure, Paul F.

1986-01-01

A feasibility study to investigate the application of vibration monitoring to the rotating machinery of planned NASA advanced spacecraft components is described. Factors investigated include: (1) special problems associated with small, high RPM machines; (2) application across multiple component types; (3) microgravity; (4) multiple fault types; (5) eight different analysis techniques including signature analysis, high frequency demodulation, cepstrum, clustering, amplitude analysis, and pattern recognition are compared; and (6) small sample statistical analysis is used to compare performance by computation of probability of detection and false alarm for an ensemble of repeated baseline and faulted tests. Both detection and classification performance are quantified. Vibration monitoring is shown to be an effective means of detecting the most important problem types for small, high RPM fans and pumps typical of those planned for the advanced spacecraft. A preliminary monitoring system design and implementation plan is presented.

Reliability and Validity of the Sexual Pressure Scale for Women-Revised

PubMed Central

Jones, Rachel; Gulick, Elsie

2008-01-01

Sexual pressure among young urban women represents adherence to gender stereotypical expectations to engage in sex. Revision of the original 5-factor Sexual Pressure Scale was undertaken in two studies to improve reliabilities in two of the five factors. In Study 1 the reliability of the Sexual Pressure Scale for Women-Revised (SPSW-R) was tested, and principal components analysis was performed in a sample of 325 young, urban women. A parsimonious 18-item, 4-factor model explained 61% of the variance. In Study 2 the theory underlying sexual pressure was supported by confirmatory factor analysis using structural equation modeling in a sample of 181 women. Reliabilities of the SPSW-R total and subscales were very satisfactory, suggesting it may be used in intervention research. PMID:18666222

Comparison of Subjective Health Complaints between Chinese and German University Students: A Cross-Sectional Study

PubMed Central

Chu, Janet Junqing; Khan, Mobarak Hossain; Jahn, Heiko J.; Kraemer, Alexander

2015-01-01

High rates of health complaints (HCs) with substantial variation are reported in different university populations, which can be linked to socio-demographic, lifestyle-related factors, and cultural differences. HCs can be categorized into distinct components. This study aimed to identify and compare underlying dimensions of HCs (HC components); to access and compare HC prevalence, and the associations between HC components, socio-demographic, lifestyle-related factors, and perceived stress in German and Chinese university students. Two health surveys were conducted among 5159 university students (1853 Chinese, 3306 German). Factor analysis and logistic regression were applied. The prevalence of HC ranged from 4.6% to 40.2% over the two countries. Germans reported at least three HCs more often (47.2% vs. 35.8%). Chinese students more often reported gastrointestinal complaints. Perceived stress was positively associated with all three HC components in both countries (OR = 1.03–1.50) with stronger associations among Germans. Women more often reported HCs (OR = 1.32–2.43) with stronger associations among the Germans. Having a father with a low educational level was associated with high psychological symptoms among the Chinese (OR = 1.51), but with low gastrointestinal complaints among the Germans (OR = 0.79). The high prevalence of HCs in students requires country-specific interventions. PMID:26690463

Purification and some properties of the protein component of tissue thromboplastin from human brain.

PubMed Central

Bjorklid, E; Storm, E

1977-01-01

The protein component of tissue thromboplastib (Factor III) from human brain was purified by extraction of a microsomal fraction with sodium deoxycholate, gel filtration of the extract on Sephadex G-100 and preparative polyacrylamide-gel electrophoresis in the presence of sodium dodecyl sulphate. The product, apoprotein III, was homogeneous by anayltical polyacrylamide-gel electrophoresis, and it induced monospecific antibodies in rabbits and goat as shown by immunodiffusion and immunoelectrophoresis. Amino acid- and carbohydrate-analysis data for apoprotein III are presented. The carbohydrate moiety of the protein consists of fucose, mannose, galactose, N-acetylglucosamine and N-acetylneuraminate, amounting to a total content of 6.3g/100g. The apoprotein alone had no procoagulant activity. When Factor III was reconstituted by combining the pure apoprotein with a purified lipid fraction from the deoxycholate extract of crude Factor III, a high and optimal procoagulant activity was obtained at a phospholipid/protein ratio of 1.1g/g. Phosphatidylethanolamine alone had a weak but significant ability to restore activity, whereas phosphatidylcholine and phosphatidylserine separately had almost none. Two-component mixtures were on average more effective, and three-component mixtures far more effective, than the single phospholipids. The inclusion of a small amount of phosphatidylserine was very important for high activity. Images Fig. 2. PLATE 1 PMID:889578

Behavioral lifestyle and mental health status of Japanese factory workers.

PubMed

Ezoe, S; Morimoto, K

1994-01-01

Lifestyle factors, sometimes associated with physical health and mortality, have also been known to be associated with mental health status. This study seeks to correlate behavioral lifestyles with major components of mental health among Japanese factory workers. We administered the 28-item version of the General Health Questionnaire (GHQ-28) and a questionnaire concerning eight personal health practices to 2,132 male and 668 female factory workers at a camera-manufacturing company in Japan. There were strong negative relationships of a higher total number of favorable lifestyles as indicated by the Health Practice Index (HPI) to psychological distress and its components: somatic symptoms, anxiety-insomnia, and social dysfunction. After controlling for the effects of confounding factors that included age, marital status, and somatic condition, multiple logistic regression analysis indicated that five of the eight health factors among male workers--mental stress, nutritional balance, eating breakfast regularly, physical exercise, and working hours--were significantly related to the grade of psychological distress or its three components. Among female workers, five health practices, i.e., mental stress, physical exercise, sleeping hours, working hours, and cigarette smoking, were significantly associated with the grade of psychological distress or its three components. Good health practices might be individually and as a whole associated with better mental health status in factory workers.

Proteomic and transcriptomic analyses to explain the pleiotropic effects of Ankaferd blood stopper

PubMed Central

Simsek, Cem; Selek, Sebnem; Koca, Meltem; Haznedaroglu, Ibrahim Celal

2017-01-01

Ankaferd blood stopper is a standardized mixture of the plants Thymus vulgaris, Glycyrrhiza glabra, Vitis vinifera, Alpinia officinarum, and Urtica dioica and has been used as a topical hemostatic agent and with its clinical application established in randomized controlled trials and case reports. Ankaferd has been successfully used in gastrointestinal endobronchial mucosal and cutaneous bleedings and also in abdominal, thoracic, dental and oropharyngeal, and pelvic surgeries. Ankaferd’s hemostatic action is thought to form a protein complex with coagulation factors that facilitate adhesion of blood components. Besides its hemostatic action, Ankaferd has demonstrated pleiotropic effects, including anti-neoplastic and anti-microbial activities and tissue-healing properties; the underlying mechanisms for these have not been well studied. Ankaferd’s individual components were determined by proteomic and chemical analyses. Ankaferd also augments transcription of some transcription factors which is shown with transcriptomic analysis. The independent effects of these ingredients and augmented transcription factors are not known precisely. Here, we review what is known of Ankaferd blood stopper components from chemical, proteomic, and transcriptomic analyses and propose that individual components can explain some pleiotropic effects of Ankaferd. Certainly more research is needed focusing on individual ingredients of Ankaferd to elucidate their precise and effects. PMID:28839937

Principal component analysis of normalized full spectrum mass spectrometry data in multiMS-toolbox: An effective tool to identify important factors for classification of different metabolic patterns and bacterial strains.

PubMed

Cejnar, Pavel; Kuckova, Stepanka; Prochazka, Ales; Karamonova, Ludmila; Svobodova, Barbora

2018-06-15

Explorative statistical analysis of mass spectrometry data is still a time-consuming step. We analyzed critical factors for application of principal component analysis (PCA) in mass spectrometry and focused on two whole spectrum based normalization techniques and their application in the analysis of registered peak data and, in comparison, in full spectrum data analysis. We used this technique to identify different metabolic patterns in the bacterial culture of Cronobacter sakazakii, an important foodborne pathogen. Two software utilities, the ms-alone, a python-based utility for mass spectrometry data preprocessing and peak extraction, and the multiMS-toolbox, an R software tool for advanced peak registration and detailed explorative statistical analysis, were implemented. The bacterial culture of Cronobacter sakazakii was cultivated on Enterobacter sakazakii Isolation Agar, Blood Agar Base and Tryptone Soya Agar for 24 h and 48 h and applied by the smear method on an Autoflex speed MALDI-TOF mass spectrometer. For three tested cultivation media only two different metabolic patterns of Cronobacter sakazakii were identified using PCA applied on data normalized by two different normalization techniques. Results from matched peak data and subsequent detailed full spectrum analysis identified only two different metabolic patterns - a cultivation on Enterobacter sakazakii Isolation Agar showed significant differences to the cultivation on the other two tested media. The metabolic patterns for all tested cultivation media also proved the dependence on cultivation time. Both whole spectrum based normalization techniques together with the full spectrum PCA allow identification of important discriminative factors in experiments with several variable condition factors avoiding any problems with improper identification of peaks or emphasis on bellow threshold peak data. The amounts of processed data remain still manageable. Both implemented software utilities are available free of charge from http://uprt.vscht.cz/ms. Copyright © 2018 John Wiley & Sons, Ltd.

Improved application of independent component analysis to functional magnetic resonance imaging study via linear projection techniques.

PubMed

Long, Zhiying; Chen, Kewei; Wu, Xia; Reiman, Eric; Peng, Danling; Yao, Li

2009-02-01

Spatial Independent component analysis (sICA) has been widely used to analyze functional magnetic resonance imaging (fMRI) data. The well accepted implicit assumption is the spatially statistical independency of intrinsic sources identified by sICA, making the sICA applications difficult for data in which there exist interdependent sources and confounding factors. This interdependency can arise, for instance, from fMRI studies investigating two tasks in a single session. In this study, we introduced a linear projection approach and considered its utilization as a tool to separate task-related components from two-task fMRI data. The robustness and feasibility of the method are substantiated through simulation on computer data and fMRI real rest data. Both simulated and real two-task fMRI experiments demonstrated that sICA in combination with the projection method succeeded in separating spatially dependent components and had better detection power than pure model-based method when estimating activation induced by each task as well as both tasks.

Using independent component analysis for electrical impedance tomography

NASA Astrophysics Data System (ADS)

Yan, Peimin; Mo, Yulong

2004-05-01

Independent component analysis (ICA) is a way to resolve signals into independent components based on the statistical characteristics of the signals. It is a method for factoring probability densities of measured signals into a set of densities that are as statistically independent as possible under the assumptions of a linear model. Electrical impedance tomography (EIT) is used to detect variations of the electric conductivity of the human body. Because there are variations of the conductivity distributions inside the body, EIT presents multi-channel data. In order to get all information contained in different location of tissue it is necessary to image the individual conductivity distribution. In this paper we consider to apply ICA to EIT on the signal subspace (individual conductivity distribution). Using ICA the signal subspace will then be decomposed into statistically independent components. The individual conductivity distribution can be reconstructed by the sensitivity theorem in this paper. Compute simulations show that the full information contained in the multi-conductivity distribution will be obtained by this method.

Performance analysis and prediction in triathlon.

PubMed

Ofoghi, Bahadorreza; Zeleznikow, John; Macmahon, Clare; Rehula, Jan; Dwyer, Dan B

2016-01-01

Performance in triathlon is dependent upon factors that include somatotype, physiological capacity, technical proficiency and race strategy. Given the multidisciplinary nature of triathlon and the interaction between each of the three race components, the identification of target split times that can be used to inform the design of training plans and race pacing strategies is a complex task. The present study uses machine learning techniques to analyse a large database of performances in Olympic distance triathlons (2008-2012). The analysis reveals patterns of performance in five components of triathlon (three race "legs" and two transitions) and the complex relationships between performance in each component and overall performance in a race. The results provide three perspectives on the relationship between performance in each component of triathlon and the final placing in a race. These perspectives allow the identification of target split times that are required to achieve a certain final place in a race and the opportunity to make evidence-based decisions about race tactics in order to optimise performance.

Polymeric proanthocyanidins from Sicilian pistachio (Pistacia vera L.) nut extract inhibit lipopolysaccharide-induced inflammatory response in RAW 264.7 cells.

PubMed

Gentile, C; Allegra, M; Angileri, F; Pintaudi, A M; Livrea, M A; Tesoriere, L

2012-04-01

Positive effects of pistachio nut consumption on plasma inflammatory biomarkers have been described; however, little is known about molecular events associated with these effects. We studied the anti-inflammatory activity of a hydrophilic extract from Sicilian Pistacia L. (HPE) in a macrophage model and investigated bioactive components relevant to the observed effects. HPE oligomer/polymer proanthocyanidin fractions were isolated by adsorbance chromatography, and components quantified as anthocyanidins after acidic hydrolysis. Isoflavones were measured by gradient elution HPLC analysis. RAW 264.7 murine macrophages were pre-incubated with either HPE (1- to 20-mg fresh nut equivalents) or its isolated components for 1 h, then washed before stimulating with lipopolysaccharide (LPS) for 24 h. Cell viability and parameters associated with Nuclear Factor-κB (NF-κB) activation were assayed according to established methods including ELISA, Western blot, or cytofluorimetric analysis. HPE suppressed nitric oxide (NO) and tumor necrosis factor-α (TNF-α) production and inducible NO-synthase levels dose dependently, whereas inhibited prostaglandin E2 (PGE2) release and decreased cyclo-oxygenase-2 content, the lower the HPE amount the higher the effect. Cytotoxic effects were not observed. HPE also caused a dose-dependent decrease in intracellular reactive oxygen species and interfered with the NF-κB activation. Polymeric proanthocyanidins, but not isoflavones, at a concentration comparable with their content in HPE, inhibited NO, PGE2, and TNF-α formation, as well as activation of IκB-α. Oligomeric proanthocyanidins showed only minor effects. Our results provide molecular evidence of anti-inflammatory activity of pistachio nut and indicate polymeric proanthocyanidins as the bioactive components. The mechanism may involve the redox-sensitive transcription factor NF-κB. Potential effects associated with pistachio nut consumption are discussed in terms of the proanthocyanidin bioavailability.

An Analysis of Viable Financial Negotiations Processes and Related Internal Controls for Procurement in Pakistan

DTIC Science & Technology

2016-06-01

regulations are in accordance with UNCITRAL Model Law and are based on principles of “ accountability , transparency, fairness, efficiency and value for... account certain factors about the firm(s) for pre-qualification. These factors include past performance and experience; financial health; managerial...internal control components, along with associated principles , were discussed in detail to develop a suitable internal control system for the financial

A Confirmatory Factor Analysis of Home Environment and Home Social Behavior Data from the Elementary School Success Profile for Families

ERIC Educational Resources Information Center

Wegmann, Kate M.; Thompson, Aaron M.; Bowen, Natasha K.

2011-01-01

The purpose of the current study was to test the factor structure and scale quality of data provided by caregivers about the home environment and child behavior at home using the Elementary School Success Profile (ESSP) for Families. The ESSP for Families is one component of the ESSP, an online social-environmental assessment that also collects…

Enhancing Public Helicopter Safety as a Component of Homeland Security

DTIC Science & Technology

2016-12-01

Risk Assessment Tool GPS Global Positioning System IFR instrument flight rules ILS instrument landing system IMC instrument meteorological...flight rules ( IFR ) flying and the lack of a pre-flight risk assessment. Pilot fatigue is a factor that appeared in two of the accident reports (New...three common factors that emerged from the qualitative analysis of coding: inadequate proficiency of IFR flying, lack of a pre- flight risk assessment

Temperament and problem solving in a population of adolescent guide dogs.

PubMed

Bray, Emily E; Sammel, Mary D; Seyfarth, Robert M; Serpell, James A; Cheney, Dorothy L

2017-09-01

It is often assumed that measures of temperament within individuals are more correlated to one another than to measures of problem solving. However, the exact relationship between temperament and problem-solving tasks remains unclear because large-scale studies have typically focused on each independently. To explore this relationship, we tested 119 prospective adolescent guide dogs on a battery of 11 temperament and problem-solving tasks. We then summarized the data using both confirmatory factor analysis and exploratory principal components analysis. Results of confirmatory analysis revealed that a priori separation of tests as measuring either temperament or problem solving led to weak results, poor model fit, some construct validity, and no predictive validity. In contrast, results of exploratory analysis were best summarized by principal components that mixed temperament and problem-solving traits. These components had both construct and predictive validity (i.e., association with success in the guide dog training program). We conclude that there is complex interplay between tasks of "temperament" and "problem solving" and that the study of both together will be more informative than approaches that consider either in isolation.

Robust demarcation of basal cell carcinoma by dependent component analysis-based segmentation of multi-spectral fluorescence images.

PubMed

Kopriva, Ivica; Persin, Antun; Puizina-Ivić, Neira; Mirić, Lina

2010-07-02

This study was designed to demonstrate robust performance of the novel dependent component analysis (DCA)-based approach to demarcation of the basal cell carcinoma (BCC) through unsupervised decomposition of the red-green-blue (RGB) fluorescent image of the BCC. Robustness to intensity fluctuation is due to the scale invariance property of DCA algorithms, which exploit spectral and spatial diversities between the BCC and the surrounding tissue. Used filtering-based DCA approach represents an extension of the independent component analysis (ICA) and is necessary in order to account for statistical dependence that is induced by spectral similarity between the BCC and surrounding tissue. This generates weak edges what represents a challenge for other segmentation methods as well. By comparative performance analysis with state-of-the-art image segmentation methods such as active contours (level set), K-means clustering, non-negative matrix factorization, ICA and ratio imaging we experimentally demonstrate good performance of DCA-based BCC demarcation in two demanding scenarios where intensity of the fluorescent image has been varied almost two orders of magnitude. Copyright 2010 Elsevier B.V. All rights reserved.

Factor Structure and Item Level Psychometrics of the Social Problem Solving Inventory Revised-Short Form in Traumatic Brain Injury

PubMed Central

Li, Chih-Ying; Waid-Ebbs, Julia; Velozo, Craig A.; Heaton, Shelley C.

2016-01-01

Primary Objective Social problem solving deficits characterize individuals with traumatic brain injury (TBI). Poor social problem solving interferes with daily functioning and productive lifestyles. Therefore, it is of vital importance to use the appropriate instrument to identify deficits in social problem solving for individuals with TBI. This study investigates factor structure and item-level psychometrics of the Social Problem Solving Inventory-Revised Short Form (SPSI-R:S), for adults with moderate and severe TBI. Research Design Secondary analysis of 90 adults with moderate and severe TBI who completed the SPSI-R:S. Methods and Procedures An exploratory factor analysis (EFA), principal components analysis (PCA) and Rasch analysis examined the factor structure and item-level psychometrics of the SPSI-R:S. Main Outcomes and Results The EFA showed three dominant factors, with positively worded items represented as the most definite factor. The other two factors are negative problem solving orientation and skills; and negative problem solving emotion. Rasch analyses confirmed the three factors are each unidimensional constructs. Conclusions The total score interpretability of the SPSI-R:S may be challenging due to the multidimensional structure of the total measure. Instead, we propose using three separate SPSI-R:S subscores to measure social problem solving for the TBI population. PMID:26052731

Factor structure and item level psychometrics of the Social Problem Solving Inventory-Revised: Short Form in traumatic brain injury.

PubMed

Li, Chih-Ying; Waid-Ebbs, Julia; Velozo, Craig A; Heaton, Shelley C

2016-01-01

Social problem-solving deficits characterise individuals with traumatic brain injury (TBI), and poor social problem solving interferes with daily functioning and productive lifestyles. Therefore, it is of vital importance to use the appropriate instrument to identify deficits in social problem solving for individuals with TBI. This study investigates factor structure and item-level psychometrics of the Social Problem Solving Inventory-Revised: Short Form (SPSI-R:S), for adults with moderate and severe TBI. Secondary analysis of 90 adults with moderate and severe TBI who completed the SPSI-R:S was performed. An exploratory factor analysis (EFA), principal components analysis (PCA) and Rasch analysis examined the factor structure and item-level psychometrics of the SPSI-R:S. The EFA showed three dominant factors, with positively worded items represented as the most definite factor. The other two factors are negative problem-solving orientation and skills; and negative problem-solving emotion. Rasch analyses confirmed the three factors are each unidimensional constructs. It was concluded that the total score interpretability of the SPSI-R:S may be challenging due to the multidimensional structure of the total measure. Instead, we propose using three separate SPSI-R:S subscores to measure social problem solving for the TBI population.

Overlap and distinction between measures of insight and self-stigma.

PubMed

Hasson-Ohayon, Ilanit

2018-05-24

Multiple studies on insight into one's illness and self-stigma among patients with serious mental illness and their relatives have shown that these constructs are related to one another and that they affect outcome. However, a critical exploration of the items used to assess both constructs raises questions with regard to the possible overlapping and centrality of items. The current study used five different samples to explore the possible overlap and distinction between insight and self-stigma, and to identify central items, via network analyses and principal component factor analysis. Findings from the network analyses showed overlap between insight and self-stigma exist with a relatively clearer observational distinction between the constructs among the two parent samples in comparison to the patient samples. Principal component factor analysis constrained to two factors showed that a relatively high percentage of items were not loaded on either factor, and in a few datasets, several insight items were loaded on the self-stigma scale and vice versa. The author discusses implications for research and calls for rethinking the way insight is assessed. Clinical implications are also discussed in reference to central items of social isolation, future worries and stereotype endorsement among the different study groups. Copyright © 2018 Elsevier B.V. All rights reserved.

Research on energy conversion mechanism of rotodynamic pump and design of non-overload centrifugal pump

NASA Astrophysics Data System (ADS)

Zhang, X. L.; Hu, S. B.; Shen, Z. Z.; Wu, S. P.; Li, K.

2016-05-01

In this paper, an attempt has been made for the calculation of an expression for the intrinsic law of input power which has not yet been given by current theory of Rotodynamic pump. By adequate recognition of the characteristics of non-inertial system within the rotating impeller, it is concluded that the input power consists of two power components, the first power component, whose magnitude increases with the increase of the flow rate, corresponds to radial velocity component, and the second power component, whose magnitude decreases with the increase of the flow rate, corresponds to tangential velocity component, therefore, the law of rise, basic levelness and drop of input power curves of centrifugal pump, mixed-flow pump and axial-flow pump can be explained reasonably. Through further analysis, the main ways for realizing non-overload of centrifugal pump are obtained, and its equivalent design factor is found out, the factor correlates with the outlet angle of leading face and back face of the blade, wrap angle, number of blades, outlet width, area ratio, and the ratio of operating flow rate to specified flow rate and so on. These are verified with actual example.

Evolution of Abscisic Acid Synthesis and Signaling Mechanisms

PubMed Central

Hauser, Felix; Waadt, Rainer; Schroeder, Julian I.

2011-01-01

The plant hormone abscisic acid (ABA) mediates seed dormancy, controls seedling development and triggers tolerance to abiotic stresses, including drought. Core ABA signaling components consist of a recently identified group of ABA receptor proteins of the PYRABACTIN RESISTANCE (PYR)/REGULATORY COMPONENT OF ABA RECEPTOR (RCAR) family that act as negative regulators of members of the PROTEIN PHOSPHATASE 2C (PP2C) family. Inhibition of PP2C activity enables activation of SNF1-RELATED KINASE 2 (SnRK2) protein kinases, which target downstream components, including transcription factors, ion channels and NADPH oxidases. These and other components form a complex ABA signaling network. Here, an in depth analysis of the evolution of components in this ABA signaling network shows that (i) PYR/RCAR ABA receptor and ABF-type transcription factor families arose during land colonization of plants and are not found in algae and other species, (ii) ABA biosynthesis enzymes have evolved to plant- and fungal-specific forms, leading to different ABA synthesis pathways, (iii) existing stress signaling components, including PP2C phosphatases and SnRK kinases, were adapted for novel roles in this plant-specific network to respond to water limitation. In addition, evolutionarily conserved secondary structures in the PYR/RCAR ABA receptor family are visualized. PMID:21549957

Human Factors Analysis to Improve the Processing of Ares-1 Launch Vehicle

NASA Technical Reports Server (NTRS)

Dippolito, Gregory M.; Stambolian, Damon B.

2011-01-01

The Constellation Program (CxP) is composed of an array of vehicles used to go to the Moon and Mars. The Ares vehicle one of the components of CxP, goes through several stages of processing before it is launched at the Kennedy Space Center. In order to have efficient and effective ground processing inside and outside the vehicle, all of the ground processing activities should be analyzed. The analysis for this program was performed, by engineers, technicians, and human factors experts with spacecraft processing experience. The procedure used to gather data was accomplished by observing human activities within physical mockups. The paper will focus on the procedures, analysis and results from these observations.

Solar array electrical performance assessment for Space Station Freedom

NASA Technical Reports Server (NTRS)

Smith, Bryan K.; Brisco, Holly

1993-01-01

Electrical power for Space Station Freedom will be generated by large Photovoltaic arrays with a beginning of life power requirement of 30.8 kW per array. The solar arrays will operate in a Low Earth Orbit (LEO) over a design life of fifteen years. This paper provides an analysis of the predicted solar array electrical performance over the design life and presents a summary of supporting analysis and test data for the assigned model parameters and performance loss factors. Each model parameter and loss factor is assessed based upon program requirements, component analysis, and test data to date. A description of the LMSC performance model, future test plans, and predicted performance ranges are also given.

Solar array electrical performance assessment for Space Station Freedom

NASA Technical Reports Server (NTRS)

Smith, Bryan K.; Brisco, Holly

1993-01-01

Electrical power for Space Station Freedom will be generated by large photovoltaic arrays with a beginning of life power requirement of 30.8 kW per array. The solar arrays will operate in a Low Earth Orbit (LEO) over a design life of fifteen years. This paper provides an analysis of the predicted solar array electrical performance over the design life and presents a summary of supporting analysis and test data for the assigned model parameters and performance loss factors. Each model parameter and loss factor is assessed based upon program requirements, component analysis and test data to date. A description of the LMSC performance model future test plans and predicted performance ranges are also given.

Methods of Collection of Biological Information for Fatigue Evaluation during Visual Display Terminals (VDT) Operation

NASA Astrophysics Data System (ADS)

Hachiya, Yuriko; Ogai, Harutoshi; Okazaki, Hiroko; Fujisaki, Takeshi; Uchida, Kazuhiko; Oda, Susumu; Wada, Futoshi; Mori, Koji

A method for the analysis of fatigue parameters has been rarely researched in VDT operation. Up to now, fatigue was evaluated by changing of biological information. If signals regarding fatigue are detected, fatigue can be measured. The purpose of this study proposed experiment and analysis method to extract parameters related to fatigue from the biological information during VDT operation using the Independent Component Analysis (ICA). An experiment had 11 subjects. As for the experiment were light loaded VDT operation and heavy loaded VDT operation. A measurement item were amount of work, a mistake number, subjective symptom, surface skin temperature (forehead and apex nasi), heart rate, skin blood flow of forearm and respiratory rate. In the heavy loaded operation group, mistake number and subjective symptom score were increased to compare with the other. And Two-factor ANOVA was used for analysis. The result of mistake number was confirmed that heavy loaded. After the moving averages of waveshape were calculated, it was made to extract independent components by using the ICA. The results of the ICA suggest that the independent components increase according to accumulation of fatigue. Thus, the independent components would be a possible parameter of fatigue. However, further experiments should continue in order to obtain the conclusive finding of our research.

Effects of changes along the risk chain on flood risk

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Factor Structure of Hospital Anxiety and Depression Scale in Malaysian patients with coronary artery disease.

PubMed

Kaur, Satpal; Zainal, Nor Zuraida; Low, Wah Yun; Ramasamy, Ravindran; Sidhu, Jaideep Singh

2015-05-01

The Hospital Anxiety and Depression Scale (HADS) is a common screening instrument used to determine the levels of anxiety and depression experienced by a patient and has been extensively used in patients with coronary artery disease (CAD). This study aimed to establish the factor structure of HADS in a Malaysian sample of 189 patients with CAD. Factor analysis of HADS using principal component analysis with varimax rotation yielded 3 factors. Confirmatory factor analysis supported the use of HADS in assessing 3 distinct dimensions of psychological distress--namely, anxiety, anhedonia, and psychomotor retardation. The HADS showed good internal consistency and was found to be a valid measure of psychological distress among Malaysian patients with CAD. However, low mean scores on the original 2 factors--that is, anxiety and depression--and also on the 2 depression subscales--anhedonia and psychomotor retardation--suggests that the recommended cutoff score to screen for psychological distress among CAD patients be reevaluated. Further research to determine the generalizability and consistency for the tridimensional structure of the HADS in Malaysia is recommended. © 2014 APJPH.

Single-trial event-related potentials to significant stimuli.

PubMed

Rushby, Jacqueline A; Barry, Robert J

2009-11-01

The stimulus-response pattern of the skin conductance response (SCR) was used as a model of the Orienting Reflex (OR) to assess the P1, N1, P2, N2 and late positive complex (LPC/P300) components of the ERP in a simple habituation paradigm, in which a single series of 12 innocuous tones were presented at a very long interstimulus interval (2 min). To maintain their waking state during this boring task, participants were instructed to alternately close or open their eyes to each stimulus. None of the baseline-to-peak ERP measures showed trials effects comparable with the marked habituation over trials shown by the SCRs. Principal Components Analysis was used to decompose the ERP, yielding factors identified as the N1, N2, P3a, P3b and Novelty P3 components. An additional factor represented later eye-movement activity. No trial effects were apparent for the N1, N2, P3a or P3b components. The Novelty P3 showed marked response decrement over trials. These results are discussed in relation to current conceptualisations of the OR.

Optimizing protection efforts for amphibian conservation in Mediterranean landscapes

NASA Astrophysics Data System (ADS)

García-Muñoz, Enrique; Ceacero, Francisco; Carretero, Miguel A.; Pedrajas-Pulido, Luis; Parra, Gema; Guerrero, Francisco

2013-05-01

Amphibians epitomize the modern biodiversity crisis, and attract great attention from the scientific community since a complex puzzle of factors has influence on their disappearance. However, these factors are multiple and spatially variable, and declining in each locality is due to a particular combination of causes. This study shows a suitable statistical procedure to determine threats to amphibian species in medium size administrative areas. For our study case, ten biological and ecological variables feasible to affect the survival of 15 amphibian species were categorized and reduced through Principal Component Analysis. The principal components extracted were related to ecological plasticity, reproductive potential, and specificity of breeding habitats. Finally, the factor scores of species were joined in a presence-absence matrix that gives us information to identify where and why conservation management are requires. In summary, this methodology provides the necessary information to maximize benefits of conservation measures in small areas by identifying which ecological factors need management efforts and where should we focus them on.

Factors Associated With Reflection Among Students After an Advanced Pharmacy Practice Experience (APPE) in Sweden

PubMed Central

Lindblad, Åsa Kettis; Gustavsson, Maria; Ring, Lena

2009-01-01

Objective To identify individual and social factors associated with pharmacy students' level of reflection in an advanced pharmacy practice experience (APPE). Methods A postal questionnaire, including a reflective assignment, was sent to all pharmacy interns (n=262) at Uppsala University, Sweden, for 4 semesters in 2005-2007. Results In a univariate analysis, 7 factors were found to be associated with students' level of reflection. After controlling for covariates, 3 social factors were found to be independently associated with reflection: having a formal preceptor (OR=5.3), being at a small pharmacy (OR=19.8), and students' perception of the importance of discussing critical thinking with the preceptor (OR=1.2). No correlation could be observed between level of reflection and critical thinking, nor learning style. Conclusion Social components seem to be of higher importance than individual components in students' reflective levels after pharmacy internship experience. Trained preceptors are important to foster reflection skills. PMID:19885076

Navier-Stokes Entropy Controlled Combustion Instability Analysis for Liquid Propellants

NASA Technical Reports Server (NTRS)

Chung, T. J.; Yoon, W. S.

1990-01-01

Navier-Stokes solutions are used to calculate oscillatory components of pressure, velocity, and density, which in turn provide necessary data to compute energy growth factors to determine combustion instability. It is shown that wave instabilities are associated with changes in entropy and the space and time averages of oscillatory components of pressure, velocity and density, together with the mean flow field in the energy equation. Compressible laminar and turbulent flows and reacting flows with hydrogen/oxygen combustion are considered. The SSME combustion/thrust chamber is used for illustration of the theory. The analysis shows that the increase of mean pressure and disturbances consistently results in the increase of instability. It is shown that adequate combustion instability analysis requires at least third order nonlinearity in energy growth or decay.

Transforming Graph Data for Statistical Relational Learning

DTIC Science & Technology

2012-10-01

Jordan, 2003), PLSA (Hofmann, 1999), ? Classification via RMN (Taskar et al., 2003) or SVM (Hasan, Chaoji, Salem , & Zaki, 2006) ? Hierarchical...dimensionality reduction methods such as Principal 407 Rossi, McDowell, Aha, & Neville Component Analysis (PCA), Principal Factor Analysis ( PFA ), and...clustering algorithm. Journal of the Royal Statistical Society. Series C, Applied statistics, 28, 100–108. Hasan, M. A., Chaoji, V., Salem , S., & Zaki, M

Pathways to the Bachelor's Degree for Latino Students. Latino Students & the Educational Pipeline, Part III

ERIC Educational Resources Information Center

Swail, Watson Scott; Cabrera, Alberto F.; Lee, Chul; Williams, Adriane

2005-01-01

The third component of our three-part series focuses on students who attained a bachelor's degree and what it took to get there. We used multiple regression analysis to determine the factors that seemed to matter on the pathway to the BA. The appendix of this report provides methodological details to this analysis. (Contains 2 footnotes and 7…

Kottamia 74-inch telescope discovery of the new eclipsing binary KAO-EGYPT J225702.44+523222.1.: First CCD photometry and light curve analysis

NASA Astrophysics Data System (ADS)

Shokry, A.; Darwish, M. S.; Saad, S. M.; Eldepsy, M.; Zead, I.

2017-08-01

We present the first multicolor CCD photometry for the newly discovered binary system KAO-EGYPT J225702.44+523222.1. New times of light minimum and new ephemeris were obtained. The VR I light curves were analyzed using WD code, the difference in maximum light at phase 0.25 is modeled with a cool spot on the secondary component. The solution show that the system is A-subtype, overcontact binary with fill-out factor = 42% and low mass ratio, q = 0.275. The two components of spectral types K0 and K1 and the primary component is the massive one. The position of both components on the M-L and M-R relations revealed that the primary component is a main sequence star while the secondary is an evolved component.

Estimating the number of pure chemical components in a mixture by X-ray absorption spectroscopy.

PubMed

Manceau, Alain; Marcus, Matthew; Lenoir, Thomas

2014-09-01

Principal component analysis (PCA) is a multivariate data analysis approach commonly used in X-ray absorption spectroscopy to estimate the number of pure compounds in multicomponent mixtures. This approach seeks to describe a large number of multicomponent spectra as weighted sums of a smaller number of component spectra. These component spectra are in turn considered to be linear combinations of the spectra from the actual species present in the system from which the experimental spectra were taken. The dimension of the experimental dataset is given by the number of meaningful abstract components, as estimated by the cascade or variance of the eigenvalues (EVs), the factor indicator function (IND), or the F-test on reduced EVs. It is shown on synthetic and real spectral mixtures that the performance of the IND and F-test critically depends on the amount of noise in the data, and may result in considerable underestimation or overestimation of the number of components even for a signal-to-noise (s/n) ratio of the order of 80 (σ = 20) in a XANES dataset. For a given s/n ratio, the accuracy of the component recovery from a random mixture depends on the size of the dataset and number of components, which is not known in advance, and deteriorates for larger datasets because the analysis picks up more noise components. The scree plot of the EVs for the components yields one or two values close to the significant number of components, but the result can be ambiguous and its uncertainty is unknown. A new estimator, NSS-stat, which includes the experimental error to XANES data analysis, is introduced and tested. It is shown that NSS-stat produces superior results compared with the three traditional forms of PCA-based component-number estimation. A graphical user-friendly interface for the calculation of EVs, IND, F-test and NSS-stat from a XANES dataset has been developed under LabVIEW for Windows and is supplied in the supporting information. Its possible application to EXAFS data is discussed, and several XANES and EXAFS datasets are also included for download.

Reliability and validity of the Malay Version of the Breast- Impact of Treatment Scale (MVBITS) in breast cancer women undergoing chemotherapy.

PubMed

Zainal, Nor Zuraida; Shuib, Norley; Bustam, Anita Zarina; Sabki, Zuraida Ahmad; Guan, Ng Chong

2013-01-01

Body image dissatisfaction among breast cancer survivors has been associated with psychological stress resultant from breast cancer and resultant surgery. This study aimed to examine the psychometric properties of the Malay Version of the Breast-Impact of Treatment Scale (MVBITS) and to investigate the associations of retained factors with the Hospital Anxiety and Depression Scale (HADS) and the Rosenberg Self-Esteem Scale (RSES). The MVBITS was 'forward-backward' translated from English to Malay and then administered to 70 female breast cancer patients who came to the Oncology Clinic of University Malaya Medical Centre, Kuala Lumpur, Malaysia to undergo chemotherapy. Principal component analysis (PCA) with varimax rotation was performed to explore the factor structure of the MVBITS. Associations of retained factors were estimated with reference to Spearman correlation coefficients. The internal consistency reliability of MVBITS was good (Cronbach's alpha 0.945) and showed temporal stability over a 3-week period. Principal component analysis suggested two factors termed as 'Intrusion' and 'Avoidance' domains. These factors explained 70.3% of the variance. Factor 1 comprised the effects of breast cancer treatment on the emotion and thought, while Factor 2 informed attempts to limit exposure of the body to self or others. The Factor 1 of MVBITS was positively correlated with total, depression and anxiety sub-scores of HADS. Factor 2 was positively correlated with total and anxiety sub-scores of HADS. MVBITS was also positively correlated with the RSES scores. The results showed that the Malay Version of Breast-Impact of Treatment Scale possesses satisfactory psychometric properties suggesting that this instrument is appropriate for assessment of body change stress among female breast cancer patients in Malaysia.

Bidding factors-the reduction of the data dimension with the use of PCA

NASA Astrophysics Data System (ADS)

Leśniak, Agnieszka

2017-07-01

Making the decision to participate in the tender is subject to a number of factors, affects the health of the company and is an important aspect in its quest for success. Efforts to select bidding factors have been repeatedly undertaken in various countries and in numerous construction markets. Researchers usually give a long list of factors, also called criteria, which in their opinion may significantly influence the bidding decision. The paper presents an attempt to reduce a proposed set of bidding factorsdefined in Poland with the use of thePrincipal Component Analysis.

Accounting of fundamental components of the rotation parameters of the Earth in the formation of a high-accuracy orbit of navigation satellites

NASA Astrophysics Data System (ADS)

Markov, Yu. G.; Mikhailov, M. V.; Pochukaev, V. N.

2012-07-01

An analysis of perturbing factors influencing the motion of a navigation satellite (NS) is carried out, and the degree of influence of each factor on the GLONASS orbit is estimated. It is found that fundamental components of the Earth's rotation parameters (ERP) are one substantial factor commensurable with maximum perturbations. Algorithms for the calculation of orbital perturbations caused by these parameters are given; these algorithms can be implemented in a consumer's equipment. The daily prediction of NS coordinates is performed on the basis of real GLONASS satellite ephemerides transmitted to a consumer, using the developed prediction algorithms taking the ERP into account. The obtained accuracy of the daily prediction of GLONASS ephemerides exceeds by tens of times the accuracy of the daily prediction performed using algorithms recommended in interface control documents.

Small Town Insurgency: The Struggle for Information Dominance to Reduce Gang Violence

DTIC Science & Technology

2010-12-01

focuses on the importance of information dominance , there has been little research into component factors that might either promote, or inhibit, the... information dominance with respect to a counter-gang strategy. Through comparative analysis, our research suggests that improving relationships between

Polychlorinated biphenyl sources, environmental levels, and exposures in school buildings

EPA Science Inventory

Background: Building materials and components containing polychlorinated biphenyls (PCBs) were used in some U.S. school buildings until the late 1970s and may be present today. There is limited information on source factors and occupant exposures. Methods: Analysis of PCBs in mat...

Children's Perceptions of the Qualities of Sibling Relationships.

ERIC Educational Resources Information Center

Furman, Wyndol; Buhrmester, Duane

1985-01-01

Developed a framework for describing and assessing the qualities of sibling relationships by interviewing upper elementary school children and administering a self-report questionnaire to fifth- and sixth-grade children. Component analysis yielded four underlying factors: warmth/closeness, relative status/power, conflict, and rivalry. Relative…

Construct Validation of the Physics Metacognition Inventory

NASA Astrophysics Data System (ADS)

Taasoobshirazi, Gita; Farley, John

2013-02-01

The 24-item Physics Metacognition Inventory was developed to measure physics students' metacognition for problem solving. Items were classified into eight subcomponents subsumed under two broader components: knowledge of cognition and regulation of cognition. The students' scores on the inventory were found to be reliable and related to students' physics motivation and physics grade. An exploratory factor analysis provided evidence of construct validity, revealing six components of students' metacognition when solving physics problems including: knowledge of cognition, planning, monitoring, evaluation, debugging, and information management. Although women and men differed on the components, they had equivalent overall metacognition for problem solving. The implications of these findings for future research are discussed.

Modeling longitudinal data, I: principles of multivariate analysis.

PubMed

Ravani, Pietro; Barrett, Brendan; Parfrey, Patrick

2009-01-01

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

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

NASA Astrophysics Data System (ADS)

Kolodezhnov, V. N.

2018-03-01

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

Face Aging Effect Simulation Using Hidden Factor Analysis Joint Sparse Representation.

PubMed

Yang, Hongyu; Huang, Di; Wang, Yunhong; Wang, Heng; Tang, Yuanyan

2016-06-01

Face aging simulation has received rising investigations nowadays, whereas it still remains a challenge to generate convincing and natural age-progressed face images. In this paper, we present a novel approach to such an issue using hidden factor analysis joint sparse representation. In contrast to the majority of tasks in the literature that integrally handle the facial texture, the proposed aging approach separately models the person-specific facial properties that tend to be stable in a relatively long period and the age-specific clues that gradually change over time. It then transforms the age component to a target age group via sparse reconstruction, yielding aging effects, which is finally combined with the identity component to achieve the aged face. Experiments are carried out on three face aging databases, and the results achieved clearly demonstrate the effectiveness and robustness of the proposed method in rendering a face with aging effects. In addition, a series of evaluations prove its validity with respect to identity preservation and aging effect generation.

Sex differences in event-related potential components during the solution of complex mental rotation tasks.

PubMed

Jaušovec, Norbert

2012-04-18

The objective of the study was to evaluate the factor of sex in terms of its influence on event-related potential components during the solution of a complex mental rotation task. To evaluate the factor of sex, independent of differences in ability levels and hormonal changes, women and men were equalized with respect to general intelligence and spatial ability. In addition, all women were tested during the low-estrogen phase of the menstrual cycle. The event-related potential analysis indicated that men showed shorter P3 and longer P1 latencies, as well as lower N1 amplitudes. These results suggest that men devoted more time to the analysis of irrelevant information presented in the rotation tasks, which resulted in mental rotation taking place earlier in men than in women. It can be concluded that, even though men and women showed similar performances on complex rotation tasks, they differed in their solution processes.

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

PubMed

Beautemps, D; Badin, P; Bailly, G

2001-05-01

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

Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis

NASA Astrophysics Data System (ADS)

E, Jianwei; Bao, Yanling; Ye, Jimin

2017-10-01

As one of the most vital energy resources in the world, crude oil plays a significant role in international economic market. The fluctuation of crude oil price has attracted academic and commercial attention. There exist many methods in forecasting the trend of crude oil price. However, traditional models failed in predicting accurately. Based on this, a hybrid method will be proposed in this paper, which combines variational mode decomposition (VMD), independent component analysis (ICA) and autoregressive integrated moving average (ARIMA), called VMD-ICA-ARIMA. The purpose of this study is to analyze the influence factors of crude oil price and predict the future crude oil price. Major steps can be concluded as follows: Firstly, applying the VMD model on the original signal (crude oil price), the modes function can be decomposed adaptively. Secondly, independent components are separated by the ICA, and how the independent components affect the crude oil price is analyzed. Finally, forecasting the price of crude oil price by the ARIMA model, the forecasting trend demonstrates that crude oil price declines periodically. Comparing with benchmark ARIMA and EEMD-ICA-ARIMA, VMD-ICA-ARIMA can forecast the crude oil price more accurately.