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Sample records for factor analysis parafac

  1. Application of Parallel Factor Analysis (PARAFAC to Electrophysiological Data

    Directory of Open Access Journals (Sweden)

    Sarah Katharina eSchmitz

    2015-01-01

    Full Text Available The identification of important features in multi-electrode recordings requires the decomposition of data in order to disclose relevant features and to offer a clear graphical representation. This can be a demanding task. Parallel Factor Analysis (PARAFAC; Hitchcock, 1927; Carrol & Chang, 1970; Harshman, 1970 is a method to decompose multi-dimensional arrays in order to focus on the features of interest, and provides a distinct illustration of the results. We applied PARAFAC to analyse spatio-temporal patterns in the functional connectivity between neurons, as revealed in their spike trains recorded in cat primary visual cortex (area 18. During these recordings we reversibly deactivated feedback connections from higher visual areas in the pMS (posterior middle suprasylvian cortex in order to study the impact of these top-down signals. Cross correlation was computed for every possible pair of the electrodes in the electrode array. PARAFAC was then used to reveal the effects of time, stimulus, and deactivation condition on the correlation patterns. Our results show that PARAFAC is able to reliably extract changes in correlation strength for different experimental conditions and display the relevant features. Thus, PARAFAC proves to be well-suited for the use in the context of electrophysiological (action potential recordings.

  2. Application of Parallel Factor Analysis (PARAFAC) to electrophysiological data.

    Science.gov (United States)

    Schmitz, S Katharina; Hasselbach, Philipp P; Ebisch, Boris; Klein, Anja; Pipa, Gordon; Galuske, Ralf A W

    2014-01-01

    The identification of important features in multi-electrode recordings requires the decomposition of data in order to disclose relevant features and to offer a clear graphical representation. This can be a demanding task. Parallel Factor Analysis (PARAFAC; Hitchcock, 1927; Carrol and Chang, 1970; Harshman, 1970) is a method to decompose multi-dimensional arrays in order to focus on the features of interest, and provides a distinct illustration of the results. We applied PARAFAC to analyse spatio-temporal patterns in the functional connectivity between neurons, as revealed in their spike trains recorded in cat primary visual cortex (area 18). During these recordings we reversibly deactivated feedback connections from higher visual areas in the pMS (posterior middle suprasylvian) cortex in order to study the impact of these top-down signals. Cross correlation was computed for every possible pair of the 16 electrodes in the electrode array. PARAFAC was then used to reveal the effects of time, stimulus, and deactivation condition on the correlation patterns. Our results show that PARAFAC is able to reliably extract changes in correlation strength for different experimental conditions and display the relevant features. Thus, PARAFAC proves to be well-suited for the use in the context of electrophysiological (action potential) recordings.

  3. Three-Mode Factor Analysis by Means of Candecomp/Parafac

    NARCIS (Netherlands)

    Stegeman, Alwin; Lam, Tam T T

    2014-01-01

    A three-mode covariance matrix contains covariances of N observations (e.g., subject scores) on J variables for K different occasions or conditions. We model such an JK×JK covariance matrix as the sum of a (common) covariance matrix having Candecomp/Parafac form, and a diagonal matrix of unique vari

  4. Heterogeneous adsorption behavior of landfill leachate on granular activated carbon revealed by fluorescence excitation emission matrix (EEM)-parallel factor analysis (PARAFAC).

    Science.gov (United States)

    Lee, Sonmin; Hur, Jin

    2016-04-01

    Heterogeneous adsorption behavior of landfill leachate on granular activated carbon (GAC) was investigated by fluorescence excitation-emission matrix (EEM) combined with parallel factor analysis (PARAFAC). The equilibrium adsorption of two leachates on GAC was well described by simple Langmuir and Freundlich isotherm models. More nonlinear isotherm and a slower adsorption rate were found for the leachate with the higher values of specific UV absorbance and humification index, suggesting that the leachate containing more aromatic content and condensed structures might have less accessible sites of GAC surface and a lower degree of diffusive adsorption. Such differences in the adsorption behavior were found even within the bulk leachate as revealed by the dissimilarity in the isotherm and kinetic model parameters between two identified PARAFAC components. For both leachates, terrestrial humic-like fluorescence (C1) component, which is likely associated with relatively large sized and condensed aromatic structures, exhibited a higher isotherm nonlinearity and a slower kinetic rate for GAC adsorption than microbial humic-like (C2) component. Our results were consistent with size exclusion effects, a well-known GAC adsorption mechanism. This study demonstrated the promising benefit of using EEM-PARAFAC for GAC adsorption processes of landfill leachate through fast monitoring of the influent and treated leachate, which can provide valuable information on optimizing treatment processes and predicting further environmental impacts of the treated effluent.

  5. Surface speciation of Eu3+ adsorbed on kaolinite by time-resolved laser fluorescence spectroscopy (TRLFS) and parallel factor analysis (PARAFAC).

    Science.gov (United States)

    Ishida, Keisuke; Saito, Takumi; Aoyagi, Noboru; Kimura, Takaumi; Nagaishi, Ryuji; Nagasaki, Shinya; Tanaka, Satoru

    2012-05-15

    Time-resolved laser fluorescence spectroscopy (TRLFS) is an effective speciation technique for fluorescent metal ions and can be further extended by the parallel factor analysis (PARAFAC). The adsorption of Eu(3+) on kaolinite as well as gibbsite as a reference mineral was investigated by TRLFS together with batch adsorption measurements. The PAFAFAC modeling provided the fluorescence spectra, decay lifetimes, and relative intensity profiles of three Eu(3+) surface complexes with kaolinite; an outer-sphere (factor A) complex and two inner-sphere (factors B and C) complexes. Their intensity profiles qualitatively explained the measured adsorption of Eu(3+). Based on the TRLFS results in varied H(2)O/D(2)O media, it was shown that the outer-sphere complex exhibited more rapid fluorescence decay than Eu(3+) aquo ion, because of the energy transfer to the surface. Factor B was an inner-sphere complex, which became dominant at relatively high pH, high salt concentration and low Eu(3+) concentration. Its spectrum and lifetime were similar to those of Eu(3+) adsorbed on gibbsite, suggesting its occurrence on the edge face of the gibbsite layer of kaolinite. From the comparison with the spectra and lifetimes of crystalline or aqueous Eu(OH)(3), factor C was considered as a poly-nuclear surface complex of Eu(3+) formed at relatively high Eu(3+) concentration.

  6. Advanced Residuals Analysis for Determining the Number of PARAFAC Components in Dissolved Organic Matter.

    Science.gov (United States)

    Cuss, Chad W; Guéguen, Céline; Andersson, Per; Porcelli, Don; Maximov, Trofim; Kutscher, Liselott

    2016-02-01

    Parallel factor analysis (PARAFAC) has facilitated an explosion in research connecting the fluorescence properties of dissolved organic matter (DOM) to its functions and biogeochemical cycling in natural and engineered systems. However, the validation of robust PARAFAC models using split-half analysis requires an oft unrealistically large number (hundreds to thousands) of excitation-emission matrices (EEMs), and models with too few components may not adequately describe differences between DOM. This study used self-organizing maps (SOM) and comparing changes in residuals with the effects of adding components to estimate the number of PARAFAC components in DOM from two data sets: MS (110 EEMs from nine leaf leachates and headwaters) and LR (64 EEMs from the Lena River). Clustering by SOM demonstrated that peaks clearly persisted in model residuals after validation by split-half analysis. Plotting the changes to residuals was an effective method for visualizing the removal of fluorophore-like fluorescence caused by increasing the number of PARAFAC components. Extracting additional PARAFAC components via residuals analysis increased the proportion of correctly identified size-fractionated leaf leachates from 56.0 ± 0.8 to 75.2 ± 0.9%, and from 51.7 ± 1.4 to 92.9 ± 0.0% for whole leachates. Model overfitting was assessed by considering the correlations between components, and their distributions amongst samples. Advanced residuals analysis improved the ability of PARAFAC to resolve the variation in DOM fluorescence, and presents an enhanced validation approach for assessing the number of components that can be used to supplement the potentially misleading results of split-half analysis.

  7. [Application of PARAFAC method and 3-D fluorescence spectra in petroleum pollutant measurement and analysis].

    Science.gov (United States)

    Pan, Zhao; Wang, Yu-tian; Shao, Xiao-qing; Wu, Xi-jun; Yang, Li-li

    2012-03-01

    A method for identification and concentration measurement of petroleum pollutant by combining three-dimensional (3-D) fluorescence spectra with parallel factor analysis (PARAFAC) was proposed. The main emphasis of research was the measurement of coexisting different kinds of petroleum. The CCl4 solutions of a 0# diesel sample, a 97# gasoline sample, and a kerosene sample were used as measurement objects. The condition of multiple petroleum coexistence was simulated by petroleum solutions with different mixed ratios. The character of PARAFAC in complex mixture coexisting system analysis was studied. The spectra of three kinds of solutions and the spectra of gasoline-diesel mixed samples, diesel-kerosene mixed samples, and gas oline-diesel mixed with small counts of kerosene interference samples were analyzed respectively. The core consistency diagnostic method and residual sum of squares method were applied to calculate the number of factors in PARAFAC. In gasoline-diesel experiment, gasoline or diesel can be identified and measured as a whole respectively by 2-factors parallel factors analysis. In diesel-kerosene experiment, 2-factors parallel factors analysis can only obtain the characters of diesel, and the 3rd factor is needed to separate the kerosene spectral character from the mixture spectrum. When small counts of kerosene exist in gasoline-diesel solution, gasoline and diesel still can be identified and measured as principal components by a 2-factors parallel factor analysis, and the effect of interference on qualitative analysis is not significant. The experiment verified that the PARAFAC method can obtain characteristic spectrum of each kind of petroleum, and the concentration of petroleum in solutions can be predicted simultaneously, with recoveries shown in the paper. The results showed the possibility of petroleum pollutant identification and concentration measurement based on the 3-D fluorescence spectra and PARAFAC.

  8. Monitoring organic loading to swimming pools by fluorescence excitation–emission matrix with parallel factor analysis (PARAFAC)

    DEFF Research Database (Denmark)

    Seredynska-Sobecka, Bozena; Stedmon, Colin; Boe-Hansen, Rasmus

    2011-01-01

    Fluorescence Excitation–Emission Matrix spectroscopy combined with parallel factor analysis was employed to monitor water quality and organic contamination in swimming pools. The fluorescence signal of the swimming pool organic matter was low but increased slightly through the day. The analysis...... loading in swimming pool water. The fluorescence at 420nm gradually increased during opening hours and represented material accumulating through the day....

  9. Towards understanding the stabilization process in vermicomposting using PARAFAC analysis of fluorescence spectra.

    Science.gov (United States)

    Lv, Baoyi; Xing, Meiyan; Zhao, Chunhui; Yang, Jian; Xiang, Liang

    2014-12-01

    In this study, fluorescence excitation-emission matrix (EEM) combined with parallel factor analysis (PARAFAC) was employed to trace the behavior of water extractable organic matter and assess the stabilization process during vermicomposting of sewage sludge and cattle dung. Experiments using different mixing ratios of sewage sludge and cattle dung were conducted using Eisenia fetida. The results showed that vermicomposting reduced the DOC, DOC/DON ratio and ammonia, while increased the nitrate content. A three-component model containing two humic-like materials (components 1 and 2) and a protein-like material (component 3) was successfully developed using PARAFAC analysis. Moreover, the initial waste composition had a significant effect on the distribution of each component and the addition of cattle dung improved the stability of sewage sludge in vermicomposting. The PARAFAC results also indicated that protein-like materials were degraded and humic acid-like compounds were evolved during vermicomposting. Pearson correlation analysis showed that components 2 and 3 are more suitable to assess vermicompost maturity than component 1. In all, EEM-PARAFAC can be used to track organic transformation and assess biological stability during the vermicomposting process.

  10. Characterisation of dissolved organic matter fluorescence properties by PARAFAC analysis and thermal quenching.

    Science.gov (United States)

    Carstea, Elfrida M; Baker, Andy; Bieroza, Magdalena; Reynolds, Darren M; Bridgeman, John

    2014-09-15

    The fluorescence intensity of dissolved organic matter (DOM) in aqueous samples is known to be highly influenced by temperature. Although several studies have demonstrated the effect of thermal quenching on the fluorescence of DOM, no research has been undertaken to assess the effects of temperature by combining fluorescence excitation - emission matrices (EEM) and parallel factor analysis (PARAFAC) modelling. This study further extends previous research on thermal quenching by evaluating the impact of temperature on the fluorescence of DOM from a wide range of environmental samples, in the range 20 °C - 0 °C. Fluorescence intensity increased linearly with respect to temperature decrease at all temperatures down to 0 °C. Results showed that temperature affected the PARAFAC components associated with humic-like and tryptophan-like components of DOM differently, depending on the water type. The terrestrial humic-like components, C1 and C2 presented the highest thermal quenching in rural water samples and the lowest in urban water samples, while C3, the tryptophan-like component, and C4, a reprocessed humic-like component, showed opposite results. These results were attributed to the availability and abundance of the components or to the degree of exposure to the heat source. The variable thermal quenching of the humic-like components also indicated that although the PARAFAC model generated the same components across sites, the DOM composition of each component differed between them. This study has shown that thermal quenching can provide additional information on the characteristics and composition of DOM and highlighted the importance of correcting fluorescence data collected in situ.

  11. A fully robust PARAFAC method for analyzing fluorescence data

    DEFF Research Database (Denmark)

    Engelen, Sanne; Frosch, Stina; Jørgensen, Bo

    2009-01-01

    Parallel factor analysis (PARAFAC) is a widespread method for modeling fluorescence data by means of an alternating least squares procedure. Consequently, the PARAFAC estimates are highly influenced by outlying excitation–emission landscapes (EEM) and element-wise outliers, like for example Raman......, there still exists no robust method for handling fluorescence data encountering both outlying EEM landscapes and scatter. In this paper, we present an iterative algorithm where the robust PARAFAC method and the scatter identification tool are alternately performed. A fully automated robust PARAFAC method...

  12. Source analysis of organic matter in swine wastewater after anaerobic digestion with EEM-PARAFAC.

    Science.gov (United States)

    Zeng, Zhuo; Zheng, Ping; Ding, Aqiang; Zhang, Meng; Abbas, Ghulam; Li, Wei

    2017-03-01

    Swine wastewater is one of the most serious pollution sources, and it has attracted a great public concern in China. Anaerobic digestion technology is extensively used in swine wastewater treatment. However, the anaerobic digestion effluents are difficult to meet the discharge standard. The results from batch experiments showed that plenty of refractory organic matter remained in the effluents after mesophilic anaerobic digestion for 30 days. The effluent total COD (tCOD) and soluble COD (sCOD) were 483 and 324 mg/L, respectively, with the sCOD/tCOD ratio of 0.671. Fluorescence excitation-emission matrix (EEM) coupled with parallel factor analysis (PARAFAC) revealed that the dissolved organic matter in the effluents was tryptophan-like substance, humic acid substance, and fulvic acid substance. Based on the appearance time during anaerobic digestion, tryptophan-like substance and humic acid substance were inferred to originate from the raw swine wastewater, and the fulvic acid substance was inferred to be formed in the anaerobic digestion. This work has revealed the source of residual organic matter in anaerobic digestion of swine wastewater and has provided some valuable information for the post-treatment.

  13. Fluorescence spectroscopy and multi-way techniques. PARAFAC

    DEFF Research Database (Denmark)

    Murphy, Kathleen R.; Stedmon, Colin A.; Graeber, Daniel;

    2013-01-01

    PARAllel FACtor analysis (PARAFAC) is increasingly used to decompose fluorescence excitation emission matrices (EEMs) into their underlying chemical components. In the ideal case where fluorescence conforms to Beers Law, this process can lead to the mathematical identification and quantification...... of independently varying fluorophores. However, many practical and analytical hurdles stand between EEM datasets and their chemical interpretation. This article provides a tutorial in the practical application of PARAFAC to fluorescence datasets, demonstrated using a dissolved organic matter (DOM) fluorescence...... dataset. A new toolbox for MATLAB is presented to support improved visualisation and sensitivity analyses of PARAFAC models in fluorescence spectroscopy. © 2013 The Royal Society of Chemistry....

  14. A three-step algorithm for CANDECOMP/PARAFAC analysis of large data sets with multicollinearity

    NARCIS (Netherlands)

    Kiers, H.A.L.

    1998-01-01

    Fitting the CANDECOMP/PARAFAC model by the standard alternating least squares algorithm often requires very many iterations. One case in point is that of analysing data with mild to severe multicollinearity. If, in addition, the size of the data is large, the computation of one CANDECOMP/PARAFAC sol

  15. The Implementation by PARAFAC Decompose Components Analysis in the Three-Dimensional Fluorescence Spectroscopy Data%平行因子法分解成分分析在三维荧光光谱数据中的实现

    Institute of Scientific and Technical Information of China (English)

    祝鹏; 刘成林; 祝飞

    2015-01-01

    The paper systematically analyzes the implementation process of the parallel factor analysis (PARAFAC) method de‐compose matrix data .As example ,The three dimensional fluorescence spectra of the water samples taken from the lake were an‐alyzed by PARAFAC .According to the distribution of the core matrix elements ,the core consistency ,the degree of similarity between the model spectra and the original spectra ,the physical meaning of the proposed decomposition components ,the number of components was determined .Then the corresponding PARAFAC model was established .The components of the fluorescence material components dissolved in water samples can be decomposed by this PARAFAC model .%系统分析了PARAFAC法解析立方阵数据的实现过程。以建立PARAFAC模型对湖泊水样三维荧光光谱数据进行荧光物质成分分解为例,通过对核心阵元素分布、核一致函数、模型谱图与原始谱图拟合程度以及拟分解成分物理意义的分析,确定 PARAFAC 法分解样品荧光物质成分的合理成分数,实现PARAFAC法对荧光物质成分的合理分解与识别。

  16. PARAFAC modeling of fluorescence excitation - Emission spectra of fish bile for rapid en route screening of PAC exposure

    DEFF Research Database (Denmark)

    Christensen, Jan H.; Tomasi, Giorgio; Strand, Jakob

    2009-01-01

    with parallel factor analysis (PARAFAC) and may constitute an alternative to fixed wavelength fluorescence and synchronous fluorescence spectroscopy (M). PARAFAC was applied to excitation-emission matrices (EEMs) of bile samples of shorthorn sculpins and European eels collected in Greenland and Denmark...

  17. Behavior of reoccurring PARAFAC components in fluorescent dissolved organic matter in natural and engineered systems: a critical review.

    Science.gov (United States)

    Ishii, Stephanie K L; Boyer, Treavor H

    2012-02-21

    Fluorescence spectroscopy coupled with parallel factor analysis (PARAFAC) has been widely used to characterize dissolved organic matter (DOM). Characterization is based on the intensity and location of independent fluorescent components identified in models constructed from excitation-emission matrices (EEMs). Similar fluorescent components have been identified in PARAFAC studies across a wide range of systems; however, there is a lack of discussion regarding the consistency with which these similar components behave. The overall goal of this critical review is to compare results for PARAFAC studies published since the year 2000 which include one or more of three reoccurring humic-like components. Components are compared and characterized based on EEM location, characteristic ecosystems, and behavior in natural and engineered systems. This synthesis allows PARAFAC users to more confidently infer DOM characteristics based on identified components. Additionally, behavioral inconsistencies between similar components help elucidate DOM properties for which fluorescence spectroscopy with PARAFAC may be a weak predictive tool.

  18. Screening for dioxin contamination in fish oil by PARAFAC and N-PLSR analysis of fluorescence landscapes

    DEFF Research Database (Denmark)

    Pedersen, Dorthe Kjær; Engelsen, Søren Balling

    2002-01-01

    A preliminary investigation of fish oils demonstrates that fluorescence excitation-emission landscapes evaluated by 3-way chemometric methods may be a candidate for an inexpensive screening method to indicate the level of contamination by dioxins and PCB’s which are normally analysed with expensive...... and time-consuming physicochemical separation techniques such as GC-MS. Fluorescence landscapes of 88 fish oils have been investigated and showed great variation due to species, season and treatment, depicting a variation in natural fluorescent components. The fluorescence landscapes were analysed...... by PARAFAC. Samples with similar fluorescence fingerprints were selected from a PARAFAC score plot and local significant prediction models with PARAFAC/MLR, N-PLSR and PLSR were established with correlation coefficients in the range from r=0.69 (n=10) to r=0.97 (n=75) for dioxin and r=0.92 (n=12) for PCB...

  19. The PARAFAC-MUSIC Algorithm for DOA Estimation with Doppler Frequency in a MIMO Radar System

    Directory of Open Access Journals (Sweden)

    Nan Wang

    2014-01-01

    Full Text Available The PARAFAC-MUSIC algorithm is proposed to estimate the direction-of-arrival (DOA of the targets with Doppler frequency in a monostatic MIMO radar system in this paper. To estimate the Doppler frequency, the PARAFAC (parallel factor algorithm is firstly utilized in the proposed algorithm, and after the compensation of Doppler frequency, MUSIC (multiple signal classification algorithm is applied to estimate the DOA. By these two steps, the DOA of moving targets can be estimated successfully. Simulation results show that the proposed PARAFAC-MUSIC algorithm has a higher accuracy than the PARAFAC algorithm and the MUSIC algorithm in DOA estimation.

  20. Spectroscopic characterisation of dissolved organic matter changes in drinking water treatment: From PARAFAC analysis to online monitoring wavelengths.

    Science.gov (United States)

    Shutova, Yulia; Baker, Andy; Bridgeman, John; Henderson, Rita K

    2014-05-01

    Organic matter (OM) causes many problems in drinking water treatment. It is difficult to monitor OM concentrations and character during treatment processes due to its complexity. Fluorescence spectroscopy is a promising tool for online monitoring. In this study, a unique dataset of fluorescence excitation emission matrixes (EEMs) (n = 867) was collected from all treatment stages of five drinking water treatment plants (WTPs) situated in diverse locations from subtropical to temperate climate. The WTPs incorporated various water sources, treatment processes and OM removal efficiencies (DOC removal 0%-68%). Despite these differences, four common fluorescence PARAFAC components were identified for characterisation of OM concentration and treatability. Moreover, fluorescence component ratios showed site-specific statistically significant correlations with OM removal, which contrasted with correlations between specific UV absorbance at 254 nm (SUVA) and OM removal that were not statistically significant. This indicates that use of fluorescence spectroscopy may be a more robust alternative for predicting DOC removal than UV spectroscopy. Based on the identified fluorescence components, four optical locations were selected in order to move towards single wavelength online OM monitoring. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Stabilizing the PARAFAC decomposition of fluorescence spectra by insertion of zeros outside the data area

    DEFF Research Database (Denmark)

    Thygesen, Lisbeth Garbrecht; Rinnan, Åsmund; Barsberg, Søren

    2004-01-01

    The use of fluorescence spectroscopy for recording multiple excitation and corresponding emission wavelengths and the subsequent technique of analyzing the resulting fluorescence landscapes is a rather new method as opposed to the use of just a single excitation wavelength. In a fluorescence...... landscape, several light-scatter effects are usually present, and often the part of the landscape containing information on the chemical and/or physical characteristics of the sample is surrounded by two Rayleigh scatter lines. When such landscapes are decomposed using parallel factor analysis (PARAFAC...... by PARAFAC. In this paper, we introduce a novel pretreatment method applicable for two-dimensional fluorescence landscapes, where instead of inserting only missing values a mixture of zeros and missing values are inserted close to and outside the Rayleigh scatter lines. It is shown that, by the use...

  2. Estimating latent trends in multivariate longitudinal data via Parafac2 with functional and structural constraints.

    Science.gov (United States)

    Helwig, Nathaniel E

    2017-07-01

    Longitudinal data are inherently multimode in the sense that such data are often collected across multiple modes of variation, for example, time × variables × subjects. In many longitudinal studies, multiple variables are collected to measure some latent construct(s) of interest. In such cases, the goal is to understand temporal trends in the latent variables, as well as individual differences in the trends. Multimode component analysis models provide a powerful framework for discovering latent trends in longitudinal data. However, classic implementations of multimode models do not take into consideration functional information (i.e., the temporal sequence of the collected data) or structural information (i.e., which variables load onto which latent factors) about the study design. In this paper, we reveal how functional and structural constraints can be imposed in multimode models (Parafac and Parafac2) in order to elucidate trends in longitudinal data. As a motivating example, we consider a longitudinal study on per capita alcohol consumption trends conducted from 1970 to 2013 by the U.S. National Institute on Alcohol Abuse and Alcoholism. We demonstrate how functional and structural information about the study design can be incorporated into the Parafac and Parafac2 alternating least squares algorithms to understand temporal and regional trends in three latent constructs: beer consumption, spirits consumption, and wine consumption. Our results reveal that Americans consume more than the recommended amount of alcohol, and total alcohol consumption trends show no signs of decreasing in the last decade. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Functional Parallel Factor Analysis for Functions of One- and Two-dimensional Arguments.

    Science.gov (United States)

    Choi, Ji Yeh; Hwang, Heungsun; Timmerman, Marieke E

    2017-02-14

    Parallel factor analysis (PARAFAC) is a useful multivariate method for decomposing three-way data that consist of three different types of entities simultaneously. This method estimates trilinear components, each of which is a low-dimensional representation of a set of entities, often called a mode, to explain the maximum variance of the data. Functional PARAFAC permits the entities in different modes to be smooth functions or curves, varying over a continuum, rather than a collection of unconnected responses. The existing functional PARAFAC methods handle functions of a one-dimensional argument (e.g., time) only. In this paper, we propose a new extension of functional PARAFAC for handling three-way data whose responses are sequenced along both a two-dimensional domain (e.g., a plane with x- and y-axis coordinates) and a one-dimensional argument. Technically, the proposed method combines PARAFAC with basis function expansion approximations, using a set of piecewise quadratic finite element basis functions for estimating two-dimensional smooth functions and a set of one-dimensional basis functions for estimating one-dimensional smooth functions. In a simulation study, the proposed method appeared to outperform the conventional PARAFAC. We apply the method to EEG data to demonstrate its empirical usefulness.

  4. Analysis of the three-dimensional tongue shape using a three-index factor analysis model

    Science.gov (United States)

    Zheng, Yanli; Hasegawa-Johnson, Mark; Pizza, Shamala

    2003-01-01

    Three-dimensional tongue shape during vowel production is analyzed using the three-mode PARAFAC (parallel factors) model. Three-dimensional MRI images of five speakers (9 vowels) are analyzed. Sixty-five virtual fleshpoints (13 segments along the rostral-caudal dimension and 5 segments along the right-left direction) are chosen based on the interpolated tongue shape images. Methods used to adjust the alignment of MRI images, to set up the fleshpoints, and to measure the position of the fleshpoints are presented. PARAFAC analysis of this 3D coordinate data results in a stable two-factor solution that explains about 70% of the variance.

  5. Parafac and go/no-go: disentangling CNV return from the P3 complex by trilinear component analysis.

    Science.gov (United States)

    Verleger, Rolf; Paulick, Claudia; Möcks, Joachim; Smith, Janette L; Keller, Karsten

    2013-03-01

    It has been proposed that the fronto-central difference between go-P3 and no-go P3 is due to motor-related negativity overlapping P3 in the go case and positive relaxation of such negativity overlapping P3 in the no-go case, and that this motor-related activation may be identified by its having the same topography as the preceding CNV. Testing these suggestions meets with the problem of how to validly distinguish between P3 and the assumed overlapping continuing or downsweeping CNV. Distinguishing between overlapping components is a major reason why principal component analysis (PCA) has been applied, but the major criterion of conventional rotations (Varimax and Promax) is avoiding overlap. Trilinear component analysis (TCA) defines components independently of overlap, by their having stable topographies across time and observations. By applying TCA, we expected to obtain equal P3 components in go and no-go, and a preceding CNV component that would continue and overlap P3 with negative polarity in the go case and with positive polarity in the no-go case. We analyzed data from warned go/no-go tasks, separately for blocks with hand movements and eye movements. Different from expectation, TCA of the Hand task yielded three relevant components: parietal P3, only slightly affected by go vs. no-go, an overlapping CNV downturn unaffected by go vs. no-go, and an anterior-positive/posterior-negative bipolar N2-P3 that modeled the go/no-go effect. No convincing TCA solution was obtained in the Eye task. Possibilities and limitations of the TCA method are discussed.

  6. Multivariate curve resolution based chromatographic peak alignment combined with parallel factor analysis to exploit second-order advantage in complex chromatographic measurements.

    Science.gov (United States)

    Parastar, Hadi; Akvan, Nadia

    2014-03-13

    In the present contribution, a new combination of multivariate curve resolution-correlation optimized warping (MCR-COW) with trilinear parallel factor analysis (PARAFAC) is developed to exploit second-order advantage in complex chromatographic measurements. In MCR-COW, the complexity of the chromatographic data is reduced by arranging the data in a column-wise augmented matrix, analyzing using MCR bilinear model and aligning the resolved elution profiles using COW in a component-wise manner. The aligned chromatographic data is then decomposed using trilinear model of PARAFAC in order to exploit pure chromatographic and spectroscopic information. The performance of this strategy is evaluated using simulated and real high-performance liquid chromatography-diode array detection (HPLC-DAD) datasets. The obtained results showed that the MCR-COW can efficiently correct elution time shifts of target compounds that are completely overlapped by coeluted interferences in complex chromatographic data. In addition, the PARAFAC analysis of aligned chromatographic data has the advantage of unique decomposition of overlapped chromatographic peaks to identify and quantify the target compounds in the presence of interferences. Finally, to confirm the reliability of the proposed strategy, the performance of the MCR-COW-PARAFAC is compared with the frequently used methods of PARAFAC, COW-PARAFAC, multivariate curve resolution-alternating least squares (MCR-ALS), and MCR-COW-MCR. In general, in most of the cases the MCR-COW-PARAFAC showed an improvement in terms of lack of fit (LOF), relative error (RE) and spectral correlation coefficients in comparison to the PARAFAC, COW-PARAFAC, MCR-ALS and MCR-COW-MCR results.

  7. Sparse Probabilistic Parallel Factor Analysis for the Modeling of PET and Task-fMRI Data

    DEFF Research Database (Denmark)

    Beliveau, Vincent; Papoutsakis, Georgios; Hinrich, Jesper Løve

    2017-01-01

    interpretability of the results. Here we propose a variational Bayesian parallel factor analysis (VB-PARAFAC) model and an extension with sparse priors (SP-PARAFAC). Notably, our formulation admits time and subject specific noise modeling as well as subject specific offsets (i.e., mean values). We confirmed...... the validity of the models through simulation and performed exploratory analysis of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) data. Although more constrained, the proposed models performed similarly to more flexible models in approximating the PET data, which supports......Modern datasets are often multiway in nature and can contain patterns common to a mode of the data (e.g. space, time, and subjects). Multiway decomposition such as parallel factor analysis (PARAFAC) take into account the intrinsic structure of the data, and sparse versions of these methods improve...

  8. Usefulness of a PARAFAC decomposition in the fiber selection procedure to determine chlorophenols by means SPME-GC-MS

    Energy Technology Data Exchange (ETDEWEB)

    Morales, Rocio; Ortiz, M.C. [University of Burgos, Department of Chemistry, Faculty of Sciences, Burgos (Spain); Sarabia, Luis A. [University of Burgos, Department of Mathematics and Computation, Faculty of Sciences, Burgos (Spain)

    2012-05-15

    In this work, a procedure based on solid-phase microextraction and gas chromatography coupled with mass spectrometry is proposed to determine chlorophenols in water without derivatization. The following chlorophenols are studied: 2,4-dichlorophenol; 2,4,6-trichlorophenol; 2,3,4,6-tetrachlorophenol and pentachlorophenol. Three kinds of SPME fibers, polyacrylate, polydimethylsiloxane, and polydimethylsiloxane/divinylbenzene are compared to identify the most suitable one for the extraction process on the basis of two criteria: (a) to select the equilibrium time studying the kinetics of the extraction, and (b) to obtain the best values of the figures of merit. In both cases, a three-way PARAllel FACtor analysis decomposition is used. For the first step, the three-way experimental data are arranged as follows: if I extraction times are considered, the tensor of data, X, of dimensions I x J x K is generated by concatenating the I matrices formed by the abundances of the J m/z ions recorded in K elution times around the retention time for each chlorophenol. The second-order property of PARAFAC (or PARAFAC2) assesses the unequivocal identification of each chlorophenol, as consequence, the loadings in the first mode estimated by the PARAFAC decomposition are the kinetic profile. For the second step, a calibration based on a PARAFAC decomposition is used for each fiber. The best figures of merit were obtained with PDMS/DVB fiber. The values of decision limit, CC{alpha}, achieved are between 0.29 and 0.67 {mu}g L{sup -1} for the four chlorophenols. The accuracy (trueness and precision) of the procedure was assessed. This procedure has been applied to river water samples. (orig.)

  9. Cross-language information retrieval using PARAFAC2.

    Energy Technology Data Exchange (ETDEWEB)

    Bader, Brett William; Chew, Peter; Abdelali, Ahmed (New Mexico State University, Las Cruces, NM); Kolda, Tamara Gibson

    2007-05-01

    A standard approach to cross-language information retrieval (CLIR) uses Latent Semantic Analysis (LSA) in conjunction with a multilingual parallel aligned corpus. This approach has been shown to be successful in identifying similar documents across languages - or more precisely, retrieving the most similar document in one language to a query in another language. However, the approach has severe drawbacks when applied to a related task, that of clustering documents 'language-independently', so that documents about similar topics end up closest to one another in the semantic space regardless of their language. The problem is that documents are generally more similar to other documents in the same language than they are to documents in a different language, but on the same topic. As a result, when using multilingual LSA, documents will in practice cluster by language, not by topic. We propose a novel application of PARAFAC2 (which is a variant of PARAFAC, a multi-way generalization of the singular value decomposition [SVD]) to overcome this problem. Instead of forming a single multilingual term-by-document matrix which, under LSA, is subjected to SVD, we form an irregular three-way array, each slice of which is a separate term-by-document matrix for a single language in the parallel corpus. The goal is to compute an SVD for each language such that V (the matrix of right singular vectors) is the same across all languages. Effectively, PARAFAC2 imposes the constraint, not present in standard LSA, that the 'concepts' in all documents in the parallel corpus are the same regardless of language. Intuitively, this constraint makes sense, since the whole purpose of using a parallel corpus is that exactly the same concepts are expressed in the translations. We tested this approach by comparing the performance of PARAFAC2 with standard LSA in solving a particular CLIR problem. From our results, we conclude that PARAFAC2 offers a very promising alternative to

  10. High Accuracy 2D-DOA Estimation for Conformal Array Using PARAFAC

    Directory of Open Access Journals (Sweden)

    Liangtian Wan

    2014-01-01

    Full Text Available Due to the polarization diversity (PD of element patterns caused by the varying curvature of the conformal carrier, the conventional direction-of-arrival (DOA estimation algorithms could not be applied to the conformal array. In order to describe the PD of conformal array, the polarization parameter is considered in the snapshot data model. The paramount difficulty for DOA estimation is the coupling between the angle information and polarization parameter. Based on the characteristic of the cylindrical conformal array, the decoupling between the polarization parameter and DOA can be realized with a specially designed array structure. 2D-DOA estimation of the cylindrical conformal array is accomplished via parallel factor analysis (PARAFAC theory. To avoid parameter pairing problem, the algorithm forms a PARAFAC model of the covariance matrices in the covariance domain. The proposed algorithm can also be generalized to other conformal array structures and nonuniform noise scenario. Cramer-Rao bound (CRB is derived and simulation results with the cylindrical conformal array are presented to verify the performance of the proposed algorithm.

  11. PARAFAC Decomposition for Ultrasonic Wave Sensing of Fiber Bragg Grating Sensors: Procedure and Evaluation

    Directory of Open Access Journals (Sweden)

    Rencheng Zheng

    2015-07-01

    Full Text Available Ultrasonic wave-sensing technology has been applied for the health monitoring of composite structures, using normal fiber Bragg grating (FBG sensors with a high-speed wavelength interrogation system of arrayed waveguide grating (AWG filters; however, researchers are required to average thousands of repeated measurements to distinguish significant signals. To resolve this bottleneck problem, this study established a signal-processing strategy that improves the signal-to-noise ratio for the one-time measured signal of ultrasonic waves, by application of parallel factor analysis (PARAFAC technology that produces unique multiway decomposition without additional orthogonal or independent constraints. Through bandpass processing of the AWG filter and complex wavelet transforms, ultrasonic wave signals are preprocessed as time, phase, and frequency profiles, and then decomposed into a series of conceptual three-way atoms by PARAFAC. While an ultrasonic wave results in a Bragg wavelength shift, antiphase fluctuations can be observed at two adjacent AWG ports. Thereby, concentrating on antiphase features among the three-way atoms, a fitting atom can be chosen and then restored to three-way profiles as a final result. An experimental study has revealed that the final result is consistent with the conventional 1024-data averaging signal, and relative error evaluation has indicated that the signal-to-noise ratio of ultrasonic waves can be significantly improved.

  12. 2D-DOA estimation of noncircular signals for uniform rectangular array via NC-PARAFAC method

    Science.gov (United States)

    Zhang, Licen; Lv, Weihua; Zhang, Xiaofei; Li, Shu

    2016-11-01

    In this paper, we propose a two-dimensional direction of arrival (2D-DOA) estimation algorithm for uniform rectangular array via noncircular-parallel factor (NC-PARAFAC) method. Compared to the conventional parallel factor (PARAFAC) algorithm, the proposed algorithm exploits the property of noncircular signals to double the array aperture. Therefore, the angle estimation performance of the proposed algorithm is better than the conventional PARAFAC method. The proposed algorithm achieves automatically paired two-dimensional angle estimates, and has better 2D-DOA estimation performance than some conventional algorithms, which include estimation of signal parameters via rotational invariance technique (ESPRIT), propagator method (PM), PARAFAC algorithm, noncircular-ESPRIT (NC-ESPRIT) and noncircular-PM (NC-PM). We also derive the Cramér-Rao bound for the 2D-DOA estimation of noncircular signals with uniform rectangular array. Simulation results verify the effectiveness and improvement of the proposed algorithm.

  13. Prediction of BOD, COD, and Total Nitrogen Concentrations in a Typical Urban River Using a Fluorescence Excitation-Emission Matrix with PARAFAC and UV Absorption Indices

    Directory of Open Access Journals (Sweden)

    Jin Hur

    2012-01-01

    Full Text Available The development of a real-time monitoring tool for the estimation of water quality is essential for efficient management of river pollution in urban areas. The Gap River in Korea is a typical urban river, which is affected by the effluent of a wastewater treatment plant (WWTP and various anthropogenic activities. In this study, fluorescence excitation-emission matrices (EEM with parallel factor analysis (PARAFAC and UV absorption values at 220 nm and 254 nm were applied to evaluate the estimation capabilities for biochemical oxygen demand (BOD, chemical oxygen demand (COD, and total nitrogen (TN concentrations of the river samples. Three components were successfully identified by the PARAFAC modeling from the fluorescence EEM data, in which each fluorophore group represents microbial humic-like (C1, terrestrial humic-like organic substances (C2, and protein-like organic substances (C3, and UV absorption indices (UV220 and UV254, and the score values of the three PARAFAC components were selected as the estimation parameters for the nitrogen and the organic pollution of the river samples. Among the selected indices, UV220, C3 and C1 exhibited the highest correlation coefficients with BOD, COD, and TN concentrations, respectively. Multiple regression analysis using UV220 and C3 demonstrated the enhancement of the prediction capability for TN.

  14. Prediction of BOD, COD, and total nitrogen concentrations in a typical urban river using a fluorescence excitation-emission matrix with PARAFAC and UV absorption indices.

    Science.gov (United States)

    Hur, Jin; Cho, Jinwoo

    2012-01-01

    The development of a real-time monitoring tool for the estimation of water quality is essential for efficient management of river pollution in urban areas. The Gap River in Korea is a typical urban river, which is affected by the effluent of a wastewater treatment plant (WWTP) and various anthropogenic activities. In this study, fluorescence excitation-emission matrices (EEM) with parallel factor analysis (PARAFAC) and UV absorption values at 220 nm and 254 nm were applied to evaluate the estimation capabilities for biochemical oxygen demand (BOD), chemical oxygen demand (COD), and total nitrogen (TN) concentrations of the river samples. Three components were successfully identified by the PARAFAC modeling from the fluorescence EEM data, in which each fluorophore group represents microbial humic-like (C1), terrestrial humic-like organic substances (C2), and protein-like organic substances (C3), and UV absorption indices (UV(220) and UV(254)), and the score values of the three PARAFAC components were selected as the estimation parameters for the nitrogen and the organic pollution of the river samples. Among the selected indices, UV(220), C3 and C1 exhibited the highest correlation coefficients with BOD, COD, and TN concentrations, respectively. Multiple regression analysis using UV(220) and C3 demonstrated the enhancement of the prediction capability for TN.

  15. Prebiotic Low Sugar Chocolate Dairy Desserts: Physical and Optical Characteristics and Performance of PARAFAC and PCA Preference Map.

    Science.gov (United States)

    Morais, E C; Esmerino, E A; Monteiro, R A; Pinheiro, C M; Nunes, C A; Cruz, A G; Bolini, Helena M A

    2016-01-01

    The addition of prebiotic and sweeteners in chocolate dairy desserts opens up new opportunities to develop dairy desserts that besides having a lower calorie intake still has functional properties. In this study, prebiotic low sugar dairy desserts were evaluated by 120 consumers using a 9-point hedonic scale, in relation to the attributes of appearance, aroma, flavor, texture, and overall liking. Internal preference map using parallel factor analysis (PARAFAC) and principal component analysis (PCA) was performed using the consumer data. In addition, physical (texture profile) and optical (instrumental color) analyses were also performed. Prebiotic dairy desserts containing sucrose and sucralose were equally liked by the consumers. These samples were characterized by firmness and gumminess, which can be considered drivers of liking by the consumers. Optimization of the prebiotic low sugar dessert formulation should take in account the choice of ingredients that contribute in a positive manner for these parameters. PARAFAC allowed the extraction of more relevant information in relation to PCA, demonstrating that consumer acceptance analysis can be evaluated by simultaneously considering several attributes. Multiple factor analysis reported Rv value of 0.964, suggesting excellent concordance for both methods.

  16. Insight into photocatalytic degradation of dissolved organic matter in UVA/TiO₂ systems revealed by fluorescence EEM-PARAFAC.

    Science.gov (United States)

    Phong, Diep Dinh; Hur, Jin

    2015-12-15

    Photocatalytic degradation of dissolved organic matter (DOM) using TiO2 as a catalyst and UVA as a light source was examined under various experimental settings with different TiO2 doses, solution pH, and the light intensities. The changes in UV absorbance and fluorescence with the irradiation time followed a pseudo-first order model much better than those of dissolved organic carbon. In general, the degradation rates were increased by higher TiO2 doses and light intensities. However, the exact photocatalytic responses of DOM to the irradiation were affected by many other factors such as aggregation of TiO2, light scattering, hydroxyl radicals produced, and DOM sorption on TiO2. Fluorescence excitation-emission matrix (EEM) coupled with parallel factor analysis (PARAFAC) revealed that the DOM changes in fluorescence could be described by the combinations of four dissimilar components including one protein-like, two humic-like, and one terrestrial humic-like components, each of which followed well the pseudo-first order model. The photocatalytic degradation rates were higher for protein-like versus humic-like component, whereas the opposite order was displayed for the degradation rates in the absence of TiO2, suggesting different dominant mechanisms operating between the systems with and without TiO2. Our results based on EEM-PARAFAC provided new insights into the underlying mechanisms associated with the photocatalytic degradation of DOM as well as the potential environmental impact of the treated water. This study demonstrated a successful application of EEM-PARAFAC for photocatalytic systems via directly comparing the kinetic rates of the individual DOM components with different compositions.

  17. Occurrence and behaviors of fluorescence EEM-PARAFAC components in drinking water and wastewater treatment systems and their applications: a review.

    Science.gov (United States)

    Yang, Liyang; Hur, Jin; Zhuang, Wane

    2015-05-01

    Fluorescence excitation emission matrices-parallel factor analysis (EEM-PARAFAC) is a powerful tool for characterizing dissolved organic matter (DOM), and it is applied in a rapidly growing number of studies on drinking water and wastewater treatments. This paper presents an overview of recent findings about the occurrence and behavior of PARAFAC components in drinking water and wastewater treatments, as well as their feasibility for assessing the treatment performance and water quality including disinfection by-product formation potentials (DBPs FPs). A variety of humic-like, protein-like, and unique (e.g., pyrene-like) fluorescent components have been identified, providing valuable insights into the chemical composition of DOM and the effects of various treatment processes in engineered systems. Coagulation/flocculation-clarification preferentially removes humic-like components, and additional treatments such as biological activated carbon filtration, anion exchange, and UV irradiation can further remove DOM from drinking water. In contrast, biological treatments are more effective for protein-like components in wastewater treatments. PARAFAC components have been proven to be valuable as surrogates for conventional water quality parameter, to track the changes of organic matter quantity and quality in drinking water and wastewater treatments. They are also feasible for assessing formations of trihalomethanes and other DBPs and evaluating treatment system performance. Further studies of EEM-PARAFAC for assessing the effects of the raw water quality and variable treatment conditions on the removal of DOM, and the formation potentials of various emerging DBPs, are essential for optimizing the treatment processes to ensure treated water quality.

  18. Humic-like substances from urban waste as auxiliaries for photo-Fenton treatment: a fluorescence EEM-PARAFAC study.

    Science.gov (United States)

    Ballesteros, S García; Costante, M; Vicente, R; Mora, M; Amat, A M; Arques, A; Carlos, L; Einschlag, F S García

    2017-01-18

    In this work, analysis of excitation-emission-matrices (EEM) has been employed to gain further insight into the characterization of humic like substances (HLS) obtained from urban wastes (soluble bio-organic substances, SBOs). In particular, complexation of these substances with iron and changes along a photo-Fenton process have been studied. Recorded EEMs were decomposed by using parallel factor analysis (PARAFAC). Three fluorescent components were identified by PARAFAC modeling of the entire set of SBO solutions studied. The EEM peak locations (λex/λem) of these components were 310-330 nm/400-420 nm (C1), 340-360 nm/450-500 nm (C2), and 285 nm/335-380 nm (C3). Slight variations of the maximum position of each component with the solution pH were observed. The interaction of SBO with Fe(iii) was characterized by determining the stability constants of the components with Fe(iii) at different pH values, which were in the order of magnitude of the ones reported for humic substances and reached their highest values at pH = 5. Photochemical experiments employing SBO and Fe(iii), with and without H2O2, showed pH-dependent trends for the evolution of the modeled components, which exhibited a strong correlation with the efficiency reported for the photo-Fenton processes in the presence of SBO at different pH values.

  19. Fluorescence spectroscopy and multi-way techniques. PARAFAC

    DEFF Research Database (Denmark)

    Murphy, Kathleen R.; Stedmon, Colin A.; Graeber, Daniel;

    2013-01-01

    of independently varying fluorophores. However, many practical and analytical hurdles stand between EEM datasets and their chemical interpretation. This article provides a tutorial in the practical application of PARAFAC to fluorescence datasets, demonstrated using a dissolved organic matter (DOM) fluorescence...... dataset. A new toolbox for MATLAB is presented to support improved visualisation and sensitivity analyses of PARAFAC models in fluorescence spectroscopy. © 2013 The Royal Society of Chemistry....

  20. Chromatographic background drift correction coupled with parallel factor analysis to resolve coelution problems in three-dimensional chromatographic data: quantification of eleven antibiotics in tap water samples by high-performance liquid chromatography coupled with a diode array detector.

    Science.gov (United States)

    Yu, Yong-Jie; Wu, Hai-Long; Fu, Hai-Yan; Zhao, Juan; Li, Yuan-Na; Li, Shu-Fang; Kang, Chao; Yu, Ru-Qin

    2013-08-01

    Chromatographic background drift correction has been an important field of research in chromatographic analysis. In the present work, orthogonal spectral space projection for background drift correction of three-dimensional chromatographic data was described in detail and combined with parallel factor analysis (PARAFAC) to resolve overlapped chromatographic peaks and obtain the second-order advantage. This strategy was verified by simulated chromatographic data and afforded significant improvement in quantitative results. Finally, this strategy was successfully utilized to quantify eleven antibiotics in tap water samples. Compared with the traditional methodology of introducing excessive factors for the PARAFAC model to eliminate the effect of background drift, clear improvement in the quantitative performance of PARAFAC was observed after background drift correction by orthogonal spectral space projection.

  1. Application of fluorescence and PARAFAC to assess vertical distribution of subsurface hydrocarbons and dispersant during the Deepwater Horizon oil spill.

    Science.gov (United States)

    Mendoza, Wilson G; Riemer, Daniel D; Zika, Rod G

    2013-05-01

    We evaluated the use of excitation and emission matrix (EEM) fluorescence and parallel factorial analysis (PARAFAC) modeling techniques for monitoring crude oil components in the water column. Four of the seven derived PARAFAC loadings were associated with the Macondo crude oil components. The other three components were associated with the dispersant, an unresolved component and colored dissolved organic matter (CDOM). The fluorescence of the associated benzene and naphthalene-like components of crude oil exhibited a maximum at ∼1200 m. The maximum fluorescence of the component associated with the dispersant (i.e., Corexit EC9500A) was observed at the same depth. The plume observed at this depth was attributed to the dispersed crude oil from the Deepwater Horizon oil spill. Results demonstrate the application of EEM and PARAFAC to simultaneously monitor selected PAH, dispersant-containing and humic-like fluorescence components in the oil spill region in the Gulf of Mexico.

  2. Degenerate solutions obtained from several variants of factor analysis

    NARCIS (Netherlands)

    Zijlstra, Bonne J.H.; Kiers, Henk A.L.

    2002-01-01

    Considerable research has been performed concerning degenerate solutions from the Parafac model. However, degenerate solutions have also been reported to occur with the shifted multiplicative model and a model for component analysis of multitrait multimethod matrices. Furthermore, we obtained

  3. Analyzing individual and group differences in multijoint multiwaveform gait data using the Parafac2 model.

    Science.gov (United States)

    Helwig, Nathaniel E; Hong, Sungjin; Bokhari, Ehsan

    2013-01-01

    Locomotion research often involves analyzing multiwaveform data (e.g., velocities, accelerations, etc.) from various body locations (e.g., knees, ankles, etc.) of several subjects. Therefore, some multivariate technique such as principal component analysis is often used to examine interrelationships between the many correlated waveforms. Despite its extensive use in locomotion research, principal component analysis is for two-mode data, whereas locomotion data are typically collected in higher mode form. In this paper, we present the benefits of analyzing four-mode locomotion data (subjects × time × joints × waveforms) using the Parafac2 model, which is a component model designed for analyzing variation in multimode data. Using bilateral hip, knee, and ankle angular displacement, velocity, and acceleration waveforms, we demonstrate Parafac2's ability to produce interpretable components describing (i) the fundamental patterns of variation in lower limb angular kinematics during healthy walking and (ii) the fundamental differences between normal and atypical subjects' multijoint multiwaveform locomotive patterns. Also, we illustrate how Parafac2 makes it possible to determine which waveforms best characterize the individual and/or group differences captured by each component. Our results indicate that different waveforms should be used for different purposes, confirming the need for the holistic analysis of multijoint multiwaveform locomotion data, particularly when investigating atypical motion patterns.

  4. Practical aspects of PARAFAC modeling of fluorescence excitation-emission data

    DEFF Research Database (Denmark)

    Andersen, Charlotte Møller; Bro, R.

    2003-01-01

    . These steps include choosing the right number of components, handling problems with missing values and scatter, detecting variables influenced by noise and identifying outliers. Various validation methods are applied in order to ensure that the optimal model has been found and several common data......This paper presents a dedicated investigation and practical description of how to apply PARAFAC modeling to complicated fluorescence excitation-emission measurements. The steps involved in finding the optimal PARAFAC model are described in detail based on the characteristics of fluorescence data......-specific problems and their solutions are explained. Finally, interpretations of the specific models are given. The paper can be used as a tutorial for investigating fluorescence landscapes with multi-way analysis. Copyright (C) 2003 John Wiley Sons, Ltd....

  5. Identification and quantification of known polycyclic aromatic hydrocarbons and pesticides in complex mixtures using fluorescence excitation-emission matrices and parallel factor analysis.

    Science.gov (United States)

    Ferretto, Nicolas; Tedetti, Marc; Guigue, Catherine; Mounier, Stéphane; Redon, Roland; Goutx, Madeleine

    2014-07-01

    Polycyclic aromatic hydrocarbons (PAHs) and pesticides are among the most widespread organic contaminants in aquatic environments. Because of their aromatic structure, PAHs and pesticides have intrinsic fluorescence properties in the ultraviolet/blue spectral range. In this study, excitation-emission matrix (EEM) fluorescence spectroscopy and parallel factor (PARAFAC) analysis were used to characterise and discriminate fluorescence signatures of nine PAHs and three pesticides at the μg L(-1) level in the presence of humic substances (0.1-10 mgCL(-1)). These contaminants displayed a diversity of fluorescence signatures regarding spectral position (λEx: 220-335 nm, λEm: 310-414 nm), Stokes shift (39-169 nm) and number of peaks (1-8), with detection limits ranging from 0.02 to 1.29μgL(-1). The EEM/PARAFAC method applied to mixtures of PAHs with humic substances validated a seven-component model that included one humic-like fluorophore and six PAH-like fluorophores. The EEM/PARAFAC method applied to mixtures of pesticides with humic substances validated a six-component model that included one humic-like fluorophore and three pesticide-like fluorophores. The EEM/PARAFAC method adequately quantified most of the contaminants for humic substance concentrations not exceeding 2.5 mg CL(-1). The application of this method to natural (marine) samples was demonstrated through (1) the match between the Ex and Em spectra of PARAFAC components and the Ex and Em spectra of standard PAHs, and (2) the good linear correlations between the fluorescence intensities of PARAFAC components and the PAH concentrations determined by GC-MS.

  6. A New Approach of Oil Spill Detection Using Time-Resolved LIF Combined with Parallel Factors Analysis for Laser Remote Sensing

    Directory of Open Access Journals (Sweden)

    Deqing Liu

    2016-08-01

    Full Text Available In hope of developing a method for oil spill detection in laser remote sensing, a series of refined and crude oil samples were investigated using time-resolved fluorescence in conjunction with parallel factors analysis (PARAFAC. The time resolved emission spectra of those investigated samples were taken by a laser remote sensing system on a laboratory basis with a detection distance of 5 m. Based on the intensity-normalized spectra, both refined and crude oil samples were well classified without overlapping, by the approach of PARAFAC with four parallel factors. Principle component analysis (PCA has also been operated as a comparison. It turned out that PCA operated well in classification of broad oil type categories, but with severe overlapping among the crude oil samples from different oil wells. Apart from the high correct identification rate, PARAFAC has also real-time capabilities, which is an obvious advantage especially in field applications. The obtained results suggested that the approach of time-resolved fluorescence combined with PARAFAC would be potentially applicable in oil spill field detection and identification.

  7. A New Approach of Oil Spill Detection Using Time-Resolved LIF Combined with Parallel Factors Analysis for Laser Remote Sensing.

    Science.gov (United States)

    Liu, Deqing; Luan, Xiaoning; Guo, Jinjia; Cui, Tingwei; An, Jubai; Zheng, Ronger

    2016-08-23

    In hope of developing a method for oil spill detection in laser remote sensing, a series of refined and crude oil samples were investigated using time-resolved fluorescence in conjunction with parallel factors analysis (PARAFAC). The time resolved emission spectra of those investigated samples were taken by a laser remote sensing system on a laboratory basis with a detection distance of 5 m. Based on the intensity-normalized spectra, both refined and crude oil samples were well classified without overlapping, by the approach of PARAFAC with four parallel factors. Principle component analysis (PCA) has also been operated as a comparison. It turned out that PCA operated well in classification of broad oil type categories, but with severe overlapping among the crude oil samples from different oil wells. Apart from the high correct identification rate, PARAFAC has also real-time capabilities, which is an obvious advantage especially in field applications. The obtained results suggested that the approach of time-resolved fluorescence combined with PARAFAC would be potentially applicable in oil spill field detection and identification.

  8. PARAFAC2 - Part II. Modeling chromatographic data with retention time shifts

    NARCIS (Netherlands)

    Bro, Rasmus; Andersson, Claus A.; Kiers, Henk A.L.

    1999-01-01

    This paper offers an approach for handling retention time shifts in resolving chromatographic data using the PARAFAC2 model. In Part I of this series an algorithm for PARAFAC2 was developed and extended to N-way arrays. It was discussed that the PARAFAC2 model has a number of attractive features. It

  9. The LMPCA program: a graphical user interface for fitting the linked-mode PARAFAC-PCA model to coupled real-valued data.

    Science.gov (United States)

    Wilderjans, Tom F; Ceulemans, Eva; Kiers, Henk A L; Meers, Kristof

    2009-11-01

    In behavioral research, PARAFAC analysis, a three-mode generalization of standard principal component analysis (PCA), is often used to disclose the structure of three-way three-mode data. To get insight into the underlying mechanisms, one often wants to relate the component matrices resulting from such a PARAFAC analysis to external (two-way two-mode) information, regarding one of the modes of the three-way data. To this end, linked-mode PARAFAC-PCA analysis can be used, in which the three-way and the two-way data set, which have one mode in common, are simultaneously analyzed. More specifically, a PARAFAC and a PCA model are fitted to the three-way and the two-way data, respectively, restricting the component matrix for the common mode to be equal in both models. Until now, however, no software program has been publicly available to perform such an analysis. Therefore, in this article, the LMPCA program, a free and easy-to-use MATLAB graphical user interface, is presented to perform a linked-mode PARAFAC-PCA analysis. The LMPCA software can be obtained from the authors at http://ppw.kuleuven.be/okp/software/LMPCA. For users who do not have access to MATLAB, a stand-alone version is provided.

  10. Fluorescent quantification of terazosin hydrochloride content in human plasma and tablets using second-order calibration based on both parallel factor analysis and alternating penalty trilinear decomposition.

    Science.gov (United States)

    Zou, Hong-Yan; Wu, Hai-Long; OuYang, Li-Qun; Zhang, Yan; Nie, Jin-Fang; Fu, Hai-Yan; Yu, Ru-Qin

    2009-09-14

    Two second-order calibration methods based on the parallel factor analysis (PARAFAC) and the alternating penalty trilinear decomposition (APTLD) method, have been utilized for the direct determination of terazosin hydrochloride (THD) in human plasma samples, coupled with the excitation-emission matrix fluorescence spectroscopy. Meanwhile, the two algorithms combing with the standard addition procedures have been applied for the determination of terazosin hydrochloride in tablets and the results were validated by the high-performance liquid chromatography with fluorescence detection. These second-order calibrations all adequately exploited the second-order advantages. For human plasma samples, the average recoveries by the PARAFAC and APTLD algorithms with the factor number of 2 (N=2) were 100.4+/-2.7% and 99.2+/-2.4%, respectively. The accuracy of two algorithms was also evaluated through elliptical joint confidence region (EJCR) tests and t-test. It was found that both algorithms could give accurate results, and only the performance of APTLD was slightly better than that of PARAFAC. Figures of merit, such as sensitivity (SEN), selectivity (SEL) and limit of detection (LOD) were also calculated to compare the performances of the two strategies. For tablets, the average concentrations of THD in tablet were 63.5 and 63.2 ng mL(-1) by using the PARAFAC and APTLD algorithms, respectively. The accuracy was evaluated by t-test and both algorithms could give accurate results, too.

  11. Noncircular-PARAFAC for 2D-DOA estimation of noncircular signals in arbitrarily spaced acoustic vector-sensor array subjected to unknown locations

    Science.gov (United States)

    Zhang, Xiaofei; Cao, Renzheng; Zhou, Ming

    2013-12-01

    In this paper, we propose a noncircular-parallel factor (NC-PARAFAC) algorithm for two-dimensional direction of arrival (DOA) estimation of noncircular signals for acoustic vector-sensor array. The proposed algorithm enhances the angle estimation performance via utilizing the noncircularity of the signals, and it can be suitable for arbitrary array subjected to unknown locations and achieve automatically paired two-dimensional angle estimation. The proposed algorithm has better angle estimation performance than estimation of signal parameters via rotational invariance technique, PARAFAC algorithm, and propagator method. Furthermore, the proposed algorithm has a lower computational complexity than the PARAFAC algorithm. We also derive the Crámer-Rao bound of DOA estimation of noncircular signal in acoustic vector-sensor array. The simulation results verify the effectiveness of the algorithm.

  12. Simultaneous determination of aflatoxins B2 and G2 in peanuts using spectrofluorescence coupled with parallel factor analysis.

    Science.gov (United States)

    Luna, A S; Luiz, R A; Lima, I C A; Março, P H; Valderrama, P; Boqué, R; Ferré, J

    2013-05-17

    In the present study a method for the simultaneous determination of aflatoxins B2 and G2 in peanuts has been developed. The method uses second order standard addition method and excitation-emission fluorescence data together with parallel factor analysis (PARAFAC). The aflatoxin analysis was based on extraction with methanol-water and carried out using immunoaffinity clean-up. The results of PARAFAC on a set of spiked and naturally contaminated peanuts indicated that the two aflatoxins could be successfully determined. The method was validated and analytical figures of merit were obtained for both analytes. The limits of detection (LOD) were 0.05 and 0.04 μg kg(-1) for aflatoxins B2 and G2, respectively. The limits of quantification (LOQ) were 0.16 and 0.12 μg kg(-1) for aflatoxins B2 and G2, respectively. Coupling of spectrofluorimetry with PARAFAC can be considered as an alternative method for quantification of aflatoxins in the presence of unknown interferences obtained through analysis of highly complex matrix of peanuts samples at a reduced cost per analysis.

  13. Factor analysis

    CERN Document Server

    Gorsuch, Richard L

    2013-01-01

    Comprehensive and comprehensible, this classic covers the basic and advanced topics essential for using factor analysis as a scientific tool in psychology, education, sociology, and related areas. Emphasizing the usefulness of the techniques, it presents sufficient mathematical background for understanding and sufficient discussion of applications for effective use. This includes not only theory but also the empirical evaluations of the importance of mathematical distinctions for applied scientific analysis.

  14. Two cross-linguistic factors underlying tongue shapes for vowels

    Energy Technology Data Exchange (ETDEWEB)

    Nix, D.A.; Papcun, G.; Hogden, J.; Zlokarnik, I. [Los Alamos National Lab., NM (United States)

    1996-06-01

    Desirable characteristics of a vocal-tract parametrization include accuracy, low dimensionality, and generalizability across speakers and languages. A low-dimensional, speaker-independent linear parametrization of vowel tongue shapes can be obtained using the PARAFAC three-mode factor analysis procedure. Harshman et al. applied PARAFAC to midsagittal x-ray vowel data from five English speakers, reporting that two speaker-independent factors are required to accurately represent the tongue shape measured along anatomically normalized vocal-tract diameter grid lines. Subsequently, the cross-linguistic generality of this parametrization was brought into question by the application of PARAFAC to Icelandic vowel data, where three nonorthogonal factors were reported. This solution is shown to be degenerate; a reanalysis of Jackson`s Icelandic data produces two factors that match Harshman et al.`s factors for English vowels, contradicting Jackson`s distinction between English and Icelandic language-specific `articulatory primes.` To obtain vowel factors not constrained by artificial measurement grid lines, x-ray tongue shape traces of six English speakers were marked with 13 equally spaced points. PARAFAC analysis of this unconstranied (x,y) coordinate data results in two factors that are clearly interpretable in terms of the traditional vowel quality dimensions front/back, high/low. 14 refs., 8 figs., 2 tabs.

  15. Three-way analysis of the UPLC-PDA dataset for the multicomponent quantitation of hydrochlorothiazide and olmesartan medoxomil in tablets by parallel factor analysis and three-way partial least squares.

    Science.gov (United States)

    Dinç, Erdal; Ertekin, Zehra Ceren

    2016-01-01

    An application of parallel factor analysis (PARAFAC) and three-way partial least squares (3W-PLS1) regression models to ultra-performance liquid chromatography-photodiode array detection (UPLC-PDA) data with co-eluted peaks in the same wavelength and time regions was described for the multicomponent quantitation of hydrochlorothiazide (HCT) and olmesartan medoxomil (OLM) in tablets. Three-way dataset of HCT and OLM in their binary mixtures containing telmisartan (IS) as an internal standard was recorded with a UPLC-PDA instrument. Firstly, the PARAFAC algorithm was applied for the decomposition of three-way UPLC-PDA data into the chromatographic, spectral and concentration profiles to quantify the concerned compounds. Secondly, 3W-PLS1 approach was subjected to the decomposition of a tensor consisting of three-way UPLC-PDA data into a set of triads to build 3W-PLS1 regression for the analysis of the same compounds in samples. For the proposed three-way analysis methods in the regression and prediction steps, the applicability and validity of PARAFAC and 3W-PLS1 models were checked by analyzing the synthetic mixture samples, inter-day and intra-day samples, and standard addition samples containing HCT and OLM. Two different three-way analysis methods, PARAFAC and 3W-PLS1, were successfully applied to the quantitative estimation of the solid dosage form containing HCT and OLM. Regression and prediction results provided from three-way analysis were compared with those obtained by traditional UPLC method.

  16. Investigation of the interaction between As and Sb species and dissolved organic matter in the Yangtze Estuary, China, using excitation-emission matrices with parallel factor analysis.

    Science.gov (United States)

    Wang, Ying; Zhang, Di; Shen, Zhen-Yao; Feng, Cheng-Hong; Zhang, Xiao

    2015-02-01

    The interactions between trivalent or pentavalent As/Sb and dissolved organic matter (DOM) in four regions (the river channel, the adjacent coastal area, and the northern and southern nearshore areas) of the Yangtze Estuary, China, were studied using fluorescence quenching titration combined with excitation-emission matrix spectroscopy and parallel factor analysis (PARAFAC). The As/Sb-DOM complexation characteristics were investigated using FTIR and UV absorbance spectroscopy and zeta potential analysis. Four protein-like components and one humic-like component were identified in the DOM from the Yangtze Estuary, China, by PARAFAC analysis. The tryptophan-like substance represented by component 2 was the dominant component and played an important role in the complexation between DOM and As/Sb. The results of complexation modeling demonstrated that the binding capacity of trivalent As/Sb with DOM was higher than that of pentavalent As/Sb with DOM. The DOM from the north nearshore area with the most acidic functional groups and greatest aromaticity possessed the highest binding capacity for trivalent and pentavalent As/Sb. The increase in the UV absorbance and the charge neutralization further indicated the interaction between As/Sb and DOM. The higher binding capacity of Sb(III) with DOM was mainly due to the hydroxyl and carboxyl groups. Our study demonstrates that the use of the advanced EEM-PARAFAC method in fluorescence quenching studies is very useful for evaluating the properties of DOM-pollutant interactions.

  17. Discrimination of three typical amino acids using PARAFAC

    Science.gov (United States)

    Yang, Hui; Xiao, Xue; Zhao, Xuesong; Wu, Yan; Zong, Junjun; Ye, Jiesong

    2016-10-01

    The intrinsic fluorescence characteristics of tryptophan, tyrosine and phenyloalanine were presented in this paper. The excitation/emission wavelength of tryptophan, tyrosine and phenyloalanine locate at λex/λem=280/350nm, 275nm/303 and 260/280nm respectively. The excitation and emission bands of these bio-fluorophores are quite overlapped within the EEM area whose excitation wavelength/emission wavelength scope is 230-270nm/260-340nm. Using the PARAFAC algorithm, 10 tryptophan, tyrosine and phenyloalanine mixed solutions and three compound amino acids samples were successfully decomposed, the emission profiles, excitation profiles, central wavelengths and the concentration of the three components were retrieved with high precision, and finally, the tyrosine and taurine were detected from 1st and 2nd sample respectively.

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

    Science.gov (United States)

    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.

  19. Changes in the fluorescence composition of multiple DOM sources over pH gradients assessed by combining parallel factor analysis and self-organizing maps

    Science.gov (United States)

    Cuss, C. W.; Shi, Y. X.; McConnell, S. M.; Guéguen, C.

    2014-09-01

    Dissolved organic matter is a ubiquitous constituent of natural waters that plays key roles in several important processes. The fluorescence properties of DOM have been linked to its functionality, but these properties may vary with pH. In this study Kohonen's self-organizing maps (SOMs) were applied to excitation-emission matrices (EEMs) of fresh dissolved organic matter (DOM) from three sources: senescent sugar-maple leaves and white spruce needles, and humified white spruce needles, over a pH range of ~4.5 - 12.5. SOMs were applied to raw EEMs, EEMs reduced in dimensionality by pre-processing using parallel factor analysis (PARAFAC), and PARAFAC loading proportions normalized to values at initial pH. Some separation of EEMs into source-based clusters was achieved in the SOM of raw EEMs, but commingling was apparent and evidence of changes over pH gradients was overshadowed. SOMs of PARAFAC component proportions demonstrated clear source-based clustering, and pH-based gradients were visible for DOM from senescent and humified spruce needles. Changes in optical properties were obvious over pH gradients in the SOM of components normalized to starting condition. Component proportions decreased to values as low as 5% of the initial values for microbial humic-like peak M and increased to as high as 278% for a humic-like component. Tyrosine-like fluorescence increased to 112% of initial over increasing pH in humified spruce leachates but decreased to as low as 45% in the other leachates. The combination of PARAFAC and SOM drastically enhanced visualization and interpretability of pH-induced changes in DOM compared to either method alone.

  20. Uniqueness of three-mode factor models with sparse cores : The 3x3x3 case

    NARCIS (Netherlands)

    Kiers, H.A.L.; ten Berge, J.M.F.; Rocci, R

    1997-01-01

    Three-Mode Factor Analysis (3MFA) and PARAFAC are methods to describe three-way data. Both methods employ models with components for the three modes of a three-way array; the 3MFA model also uses a three-way core array for linking all components to each other. The use of the core array makes the 3MF

  1. Parallel Factor Analysis as an exploratory tool for wavelet transformed event-related EEG

    DEFF Research Database (Denmark)

    Mørup, Morten; Hansen, Lars Kai; Hermann, Cristoph S.

    2006-01-01

    to extract the expected features of a previously reported ERP paradigm: namely, a quantitative difference of coherent occipital gamma activity between conditions of a visual paradigm. Furthermore, the method revealed a qualitative difference which has not previously been reported. The PARAFAC decomposition...... of the 3-way array of ANOVA F test values clearly showed the difference of regions of interest across modalities, while the 5-way analysis enabled visualization of both quantitative and qualitative differences. Consequently, PARAFAC is a promising data exploratory tool in the analysis of the wavelets...

  2. Foundations of factor analysis

    CERN Document Server

    Mulaik, Stanley A

    2009-01-01

    Introduction Factor Analysis and Structural Theories Brief History of Factor Analysis as a Linear Model Example of Factor AnalysisMathematical Foundations for Factor Analysis Introduction Scalar AlgebraVectorsMatrix AlgebraDeterminants Treatment of Variables as Vectors Maxima and Minima of FunctionsComposite Variables and Linear Transformations Introduction Composite Variables Unweighted Composite VariablesDifferentially Weighted Composites Matrix EquationsMulti

  3. "Parallel factor analysis of multi-excitation ultraviolet resonance Raman spectra for protein secondary structure determination".

    Science.gov (United States)

    Oshokoya, Olayinka O; JiJi, Renee D

    2015-09-10

    Protein secondary structural analysis is important for understanding the relationship between protein structure and function, or more importantly how changes in structure relate to loss of function. The structurally sensitive protein vibrational modes (amide I, II, III and S) in deep-ultraviolet resonance Raman (DUVRR) spectra resulting from the backbone C-O and N-H vibrations make DUVRR a potentially powerful tool for studying secondary structure changes. Experimental studies reveal that the position and intensity of the four amide modes in DUVRR spectra of proteins are largely correlated with the varying fractions of α-helix, β-sheet and disordered structural content of proteins. Employing multivariate calibration methods and DUVRR spectra of globular proteins with varying structural compositions, the secondary structure of a protein with unknown structure can be predicted. A disadvantage of multivariate calibration methods is the requirement of known concentration or spectral profiles. Second-order curve resolution methods, such as parallel factor analysis (PARAFAC), do not have such a requirement due to the "second-order advantage." An exceptional feature of DUVRR spectroscopy is that DUVRR spectra are linearly dependent on both excitation wavelength and secondary structure composition. Thus, higher order data can be created by combining protein DUVRR spectra of several proteins collected at multiple excitation wavelengths to give multi-excitation ultraviolet resonance Raman data (ME-UVRR). PARAFAC has been used to analyze ME-UVRR data of nine proteins to resolve the pure spectral, excitation and compositional profiles. A three factor model with non-negativity constraints produced three unique factors that were correlated with the relative abundance of helical, β-sheet and poly-proline II dihedral angles. This is the first empirical evidence that the typically resolved "disordered" spectrum represents the better defined poly-proline II type structure.

  4. SIMPLE VALIDATORY TOOLS FOR JUDGING THE PREDICTIVE PERFORMANCE OF PARAFAC AND 3-WAY PLS

    NARCIS (Netherlands)

    SMILDE, AK; DOORNBOS, DA

    1992-01-01

    The methods PARAFAC and three-way PLS are compared with respect to their ability to predict reversed-phase retention values. Special attention is paid to simple validatory tools, the meaning and use of which are explained. The simple validatory tools consist of percentages of explained variation in

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

    Science.gov (United States)

    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; pbEPS 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.

  6. Jammer Suppression in DS-CDMA Communications using Parafac-based Blind Separation

    Directory of Open Access Journals (Sweden)

    Xu Lingyun

    2016-01-01

    Full Text Available In this paper we propose to apply parafac-based source separation techniques for jammer suppression in direct spread spectrum communication systems. The jammer excision is formulated as an optimization problem and a new algorithm is presented which is based on the parafac tri-iterative least square algorithm. By jointly diagonalizing the time delay correlation matrix of the observed signals and using the new proposed method, a better solution is achieved. The proposed algorithm can successfully separate communication signals and jamming signals. Simulation results reveal that our proposed algorithm has the better blind signal separation performance than joint diagonalization method. Our proposed algorithm doesn’t require whitening processing. Moreover our proposed algorithm works well in the underdetermined condition, where the number of sources exceeds than the number of antennas.

  7. Bayesian Exploratory Factor Analysis

    DEFF Research Database (Denmark)

    Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.;

    2014-01-01

    This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corr......This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor......, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates...

  8. Chemometric processing of second-order liquid chromatographic data with UV-vis and fluorescence detection. A comparison of multivariate curve resolution and parallel factor analysis 2.

    Science.gov (United States)

    Bortolato, Santiago A; Olivieri, Alejandro C

    2014-09-01

    Second-order liquid chromatographic data with multivariate spectral (UV-vis or fluorescence) detection usually show changes in elution time profiles from sample to sample, causing a loss of trilinearity in the data. In order to analyze them with an appropriate model, the latter should permit a given component to have different time profiles in different samples. Two popular models in this regard are multivariate curve resolution-alternating least-squares (MCR-ALS) and parallel factor analysis 2 (PARAFAC2). The conditions to be fulfilled for successful application of the latter model are discussed on the basis of simple chromatographic concepts. An exhaustive analysis of the multivariate calibration models is carried out, employing both simulated and experimental chromatographic data sets. The latter involve the quantitation of benzimidazolic and carbamate pesticides in fruit and juice samples using liquid chromatography with diode array detection, and of polycyclic aromatic hydrocarbons in water samples, in both cases in the presence of potential interferents using liquid chromatography with fluorescence spectral detection, thereby achieving the second-order advantage. The overall results seem to favor MCR-ALS over PARAFAC2, especially in the presence of potential interferents.

  9. Bayesian Exploratory Factor Analysis

    DEFF Research Database (Denmark)

    Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.

    2014-01-01

    This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor......, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates...

  10. Enzyme activity measurement via spectral evolution profiling and PARAFAC

    DEFF Research Database (Denmark)

    Baum, Andreas; Meyer, Anne S.; Garcia, Javier Lopez

    2013-01-01

    The recent advances in multi-way analysis provide new solutions to traditional enzyme activity assessment. In the present study enzyme activity has been determined by monitoring spectral changes of substrates and products in real time. The method relies on measurement of distinct spectral...... fingerprints of the reaction mixture at specific time points during the course of the whole enzyme catalyzed reaction and employs multi-way analysis to detect the spectral changes. The methodology is demonstrated by spectral evolution profiling of Fourier Transform Infrared (FTIR) spectral fingerprints using...

  11. Discrimination of marine algal taxonomic groups based on fluorescence excitation emission matrix, parallel factor analysis and CHEMTAX

    Institute of Scientific and Technical Information of China (English)

    CHEN Xiaona; SURongguo; BAIYing; SHI Xiaoyong; YANG Rujun

    2014-01-01

    An in vivo three-dimensional fluorescence method for the determination of algae community structure was developed by parallel factor analysis (PARAFAC) and CHEMTAX. The PARAFAC model was applied to fluo-rescence excitation-emission matrix (EEM) of 60 algae species belonging to five divisions and 11 fluorescent components were identified according to the residual sum of squares and specificity of the composition profiles of fluorescent. By the 11 fluorescent components, the algae species at different growth stages were classified correctly at the division level using Bayesian discriminant analysis (BDA). Then the reference fluo-rescent component ratio matrix was constructed for CHEMTAX, and the EEM–PARAFAC–CHEMTAX method was developed to differentiate algae taxonomic groups. The correct discrimination ratios (CDRs) when the fluorometric method was used for single-species samples were 100% at the division level, except for Bacil-lariophyta with a CDR of 95.6%. The CDRs for the mixtures were above 94.0% for the dominant algae species and above 87.0% for the subdominant algae species. However, the CDRs of the subdominant algae species were too low to be unreliable when the relative abundance estimated was less than 15.0%. The fluorometric method was tested using the samples from the Jiaozhou Bay and the mesocosm experiments in the Xiaomai Island Bay in August 2007. The discrimination results of the dominant algae groups agreed with microscopy cell counts, as well as the subdominant algae groups of which the estimated relative abundance was above 15.0%. This technique would be of great aid when low-cost and rapid analysis is needed for samples in a large batch. The fluorometric technique has the ability to correctly identify dominant species with proper abundance both in vivo and in situ.

  12. Uniqueness conditions for constrained three-way factor decompositions with linearly dependent loadings

    NARCIS (Netherlands)

    Stegeman, Alwin; De Almeida, Andre L. F.

    2009-01-01

    In this paper, we derive uniqueness conditions for a constrained version of the parallel factor (Parafac) decomposition, also known as canonical decomposition (Candecomp). Candecomp/Parafac (CP) decomposes a three-way array into a prespecified number of outer product arrays. The constraint is that

  13. Factor Analysis and AIC.

    Science.gov (United States)

    Akaike, Hirotugu

    1987-01-01

    The Akaike Information Criterion (AIC) was introduced to extend the method of maximum likelihood to the multimodel situation. Use of the AIC in factor analysis is interesting when it is viewed as the choice of a Bayesian model; thus, wider applications of AIC are possible. (Author/GDC)

  14. Using the simultaneous generalized Schur decomposition as a Candecomp/Parafac algorithm for ill-conditioned data

    NARCIS (Netherlands)

    Stegeman, A.

    2009-01-01

    The Candecomp/Parafac (CP) method decomposes a three-way array into a prespecified number R of outer product arrays, by minimizing the sum-of-squares of the residual array. The practical use of CP is sometimes complicated by the occurrence of so-called 'degenerate' sequences of solutions, in which s

  15. Convergence Properties of an Iterative Procedure of Ipsatizing and Standardizing a Data Matrix, with Applications to Parafac/Candecomp Preprocessing.

    Science.gov (United States)

    ten Berge, Jos M. F.; Kiers, Henk A. L.

    1989-01-01

    Centering a matrix row-wise and rescaling it column-wise to a unit sum of squares requires an iterative procedure. It is shown that this procedure converges to a stable solution that need not be centered row-wise. The results bear directly on several types of preprocessing methods in Parafac/Candecomp. (Author/TJH)

  16. Estimating the Concentration and Biodegradability of Organic Matter in 22 Wastewater Treatment Plants Using Fluorescence Excitation Emission Matrices and Parallel Factor Analysis

    Directory of Open Access Journals (Sweden)

    Liyang Yang

    2014-01-01

    Full Text Available This study aimed at monitoring the changes of fluorescent components in wastewater samples from 22 Korean biological wastewater treatment plants and exploring their prediction capabilities for total organic carbon (TOC, dissolved organic carbon (DOC, biochemical oxygen demand (BOD, chemical oxygen demand (COD, and the biodegradability of the wastewater using an optical sensing technique based on fluorescence excitation emission matrices and parallel factor analysis (EEM-PARAFAC. Three fluorescent components were identified from the samples by using EEM-PARAFAC, including protein-like (C1, fulvic-like (C2 and humic-like (C3 components. C1 showed the highest removal efficiencies for all the treatment types investigated here (69% ± 26%–81% ± 8%, followed by C2 (37% ± 27%–65% ± 35%, while humic-like component (i.e., C3 tended to be accumulated during the biological treatment processes. The percentage of C1 in total fluorescence (%C1 decreased from 54% ± 8% in the influents to 28% ± 8% in the effluents, while those of C2 and C3 (%C2 and %C3 increased from 43% ± 6% to 62% ± 9% and from 3% ± 7% to 10% ± 8%, respectively. The concentrations of TOC, DOC, BOD, and COD were the most correlated with the fluorescence intensity (Fmax of C1 (r = 0.790–0.817, as compared with the other two fluorescent components. The prediction capability of C1 for TOC, BOD, and COD were improved by using multiple regression based on Fmax of C1 and suspended solids (SS (r = 0.856–0.865, both of which can be easily monitored in situ. The biodegradability of organic matter in BOD/COD were significantly correlated with each PARAFAC component and their combinations (r = −0.598–0.613, p < 0.001, with the highest correlation coefficient shown for %C1. The estimation capability was further enhanced by using multiple regressions based on %C1, %C2 and C3/C2 (r = −0.691.

  17. Identification and quantification of carbamate pesticides in dried lime tree flowers by means of excitation-emission molecular fluorescence and parallel factor analysis when quenching effect exists.

    Science.gov (United States)

    Rubio, L; Ortiz, M C; Sarabia, L A

    2014-04-11

    A non-separative, fast and inexpensive spectrofluorimetric method based on the second order calibration of excitation-emission fluorescence matrices (EEMs) was proposed for the determination of carbaryl, carbendazim and 1-naphthol in dried lime tree flowers. The trilinearity property of three-way data was used to handle the intrinsic fluorescence of lime flowers and the difference in the fluorescence intensity of each analyte. It also made possible to identify unequivocally each analyte. Trilinearity of the data tensor guarantees the uniqueness of the solution obtained through parallel factor analysis (PARAFAC), so the factors of the decomposition match up with the analytes. In addition, an experimental procedure was proposed to identify, with three-way data, the quenching effect produced by the fluorophores of the lime flowers. This procedure also enabled the selection of the adequate dilution of the lime flowers extract to minimize the quenching effect so the three analytes can be quantified. Finally, the analytes were determined using the standard addition method for a calibration whose standards were chosen with a D-optimal design. The three analytes were unequivocally identified by the correlation between the pure spectra and the PARAFAC excitation and emission spectral loadings. The trueness was established by the accuracy line "calculated concentration versus added concentration" in all cases. Better decision limit values (CCα), in x0=0 with the probability of false positive fixed at 0.05, were obtained for the calibration performed in pure solvent: 2.97 μg L(-1) for 1-naphthol, 3.74 μg L(-1) for carbaryl and 23.25 μg L(-1) for carbendazim. The CCα values for the second calibration carried out in matrix were 1.61, 4.34 and 51.75 μg L(-1) respectively; while the values obtained considering only the pure samples as calibration set were: 2.65, 8.61 and 28.7 μg L(-1), respectively.

  18. A chemometric analysis of ligand-induced changes in intrinsic fluorescence of folate binding protein indicates a link between altered conformational structure and physico-chemical characteristics

    DEFF Research Database (Denmark)

    Bruun, Susanne W; Holm, Jan; Hansen, Steen Ingemann

    2009-01-01

    Ligand binding alters the conformational structure and physico-chemical characteristics of bovine folate binding protein (FBP). For the purpose of achieving further information we analyzed ligand (folate and methotrexate)-induced changes in the fluorescence landscape of FBP. Fluorescence excitation...... and emission two-dimensional (2D) spectra were recorded over a wide range of wavelengths on a Perkin-Elmer LS 55 spectrofluorometer at varying pH in different buffers, and the resulting three-dimensional data were subjected to a chemometric analysis, parallel factor analysis (PARAFAC). The most important...... of folate accords fairly well with the disappearance of strongly hydrophobic tryptophan residues from the solvent-exposed surface of FBP. The PARAFAC has thus proven useful to establish a hitherto unexplained link between parallel changes in conformational structure and physico-chemical characteristics...

  19. Determination of polycyclic aromatic hydrocarbons by four-way parallel factor analysis in presence of humic acid

    Science.gov (United States)

    Yang, Ruifang; Zhao, Nanjing; Xiao, Xue; Yu, Shaohui; Liu, Jianguo; Liu, Wenqing

    2016-01-01

    There is not effective method to solve the quenching effect of quencher in fluorescence spectra measurement and recognition of polycyclic aromatic hydrocarbons in aquatic environment. In this work, a four-way dataset combined with four-way parallel factor analysis is used to identify and quantify polycyclic aromatic hydrocarbons in the presence of humic acid, a fluorescent quencher and an ubiquitous substance in aquatic system, through modeling the quenching effect of humic acid by decomposing the four-way dataset into four loading matrices corresponding to relative concentration, excitation spectra, emission spectra and fluorescence quantum yield, respectively. It is found that Phenanthrene, pyrene, anthracene and fluorene can be recognized simultaneously with the similarities all above 0.980 between resolved spectra and reference spectra. Moreover, the concentrations of them ranging from 0 to 8 μg L-1 in the test samples prepared with river water could also be predicted successfully with recovery rate of each polycyclic aromatic hydrocarbon between 100% and 120%, which were higher than those of three-way PARAFAC. These results demonstrate that the combination of four-way dataset with four-way parallel factor analysis could be a promising method to recognize the fluorescence spectra of polycyclic aromatic hydrocarbons in the presence of fluorescent quencher from both qualitative and quantitative perspective.

  20. Factor analysis of multivariate data

    Digital Repository Service at National Institute of Oceanography (India)

    Fernandes, A.A.; Mahadevan, R.

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

  1. Factor Analysis of Intern Effectiveness

    Science.gov (United States)

    Womack, Sid T.; Hannah, Shellie Louise; Bell, Columbus David

    2012-01-01

    Four factors in teaching intern effectiveness, as measured by a Praxis III-similar instrument, were found among observational data of teaching interns during the 2010 spring semester. Those factors were lesson planning, teacher/student reflection, fairness & safe environment, and professionalism/efficacy. This factor analysis was as much of a…

  2. Factor analysis and missing data

    NARCIS (Netherlands)

    Kamakura, WA; Wedel, M

    2000-01-01

    The authors study the estimation of factor models and the imputation of missing data and propose an approach that provides direct estimates of factor weights without the replacement of missing data with imputed values. First, the approach is useful in applications of factor analysis in the presence

  3. First course in factor analysis

    CERN Document Server

    Comrey, Andrew L

    2013-01-01

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

  4. Fluorescence spectroscopy of soil pellets : The use of CP/PARAFAC.

    Science.gov (United States)

    Mounier, Stéphane; Nicolodeli, Gustavo; Redon, Roland; Hacherouf, Kalhed; Milori, Debora M. B. P.

    2014-05-01

    performed in pellets (boric and humic acids mixture) using a portable system built by Embrapa Instrumentation. It comprises a diode laser (Coherent - CUBE) emitting at 405 nm (50 mW), and the detection of emission by a high sensitivity mini-spectrometer (USB4000 - Ocean Optics) using a range from 440 to 800 nm. In first step, the 3D tensors were then treated by the CP/PARAFAC algorithm to decompose the signal response after removing the diffusion signal : three components were extracted with a CORCONDIA over 60%. The first component can be associate an artefact of the measurement or boric acid fluorescence, the second and third component could the related to the two different fluorescence contributions of tryptophan molecule, one with central excitation/emission in 290/360 nm and other in 350/465 nm. The presence of a small quantity (i.e. few percent in mass) of humic acid (HA) is quenching drastically the TRP fluorescence. Complementary, measurements will be performed to understand this behaviour taking in account the absorption wavelength by the surface (colour) and by measuring the time life fluorescence of the samples. Humic acid fluorescence in pellets (BA and HA) cannot be observed using lamp + monochromator excitation due to low intensity of source. The same pellets were measure using LIFS system, and fluorescence intensity increased as a function of concentration of HA until occur the inner filter effect from 300 ppm, similar to the behaviour of HA in solution. Even whether solid surface measurements are easier, understanding is not yet clear. More investigation needs to be done. Moreover, it should be important to know if the use of CP/PARAFAC decomposition for such data is relevant with the trilinear model. References Milori, D.M.B.P., Galeti, H.V.A., Martin-Neto, L., Dieckow, J., González-Pérez, M., Bayer, C., Salton, J., 2006. Organic Matter Study of Whole Soil Samples Using Laser-Induced Fluorescence Spectroscopy. Soil Science Society of America Journal 70

  5. Scalable Tensor Factorizations with Missing Data

    DEFF Research Database (Denmark)

    Acar, Evrim; Dunlavy, Daniel M.; Kolda, Tamara G.

    2010-01-01

    The problem of missing data is ubiquitous in domains such as biomedical signal processing, network trac analysis, bibliometrics, social network analysis, chemometrics, computer vision, and communication networks|all domains in which data collection is subject to occasional errors. Moreover......, these data sets can be quite large and have more than two axes of variation, e.g., sender, receiver, time. Many applications in those domains aim to capture the underlying latent structure of the data; in other words, they need to factorize data sets with missing entries. If we cannot address the problem...... of missing data, many important data sets will be discarded or improperly analyzed. Therefore, we need a robust and scalable approach for factorizing multi-way arrays (i.e., tensors) in the presence of missing data. We focus on one of the most well-known tensor factorizations, CANDECOMP/PARAFAC (CP...

  6. Scalable Tensor Factorizations with Missing Data

    DEFF Research Database (Denmark)

    Acar, Evrim; Dunlavy, Daniel M.; Kolda, Tamara G.

    2010-01-01

    The problem of missing data is ubiquitous in domains such as biomedical signal processing, network trac analysis, bibliometrics, social network analysis, chemometrics, computer vision, and communication networks|all domains in which data collection is subject to occasional errors. Moreover......, these data sets can be quite large and have more than two axes of variation, e.g., sender, receiver, time. Many applications in those domains aim to capture the underlying latent structure of the data; in other words, they need to factorize data sets with missing entries. If we cannot address the problem...... of missing data, many important data sets will be discarded or improperly analyzed. Therefore, we need a robust and scalable approach for factorizing multi-way arrays (i.e., tensors) in the presence of missing data. We focus on one of the most well-known tensor factorizations, CANDECOMP/PARAFAC (CP...

  7. An efficient algorithm for Parafac with uncorrelated mode-A components applied to large I x J x K data sets with I >> JK

    NARCIS (Netherlands)

    Kiers, Henk A. L.; Harshman, Richard A.

    2009-01-01

    Harshman and Lundy (Comput Stat. Data AnaL 1994; 18: 39-72) described an option in the Parafac algorithm for constraining one or more component matrices to have uncorrelated columns. In cases where an algorithm using this constraint is to be applied to a three-way array that has too many entries in

  8. Quantification of source impact to PM using three-dimensional weighted factor model analysis on multi-site data

    Science.gov (United States)

    Shi, Guoliang; Peng, Xing; Huangfu, Yanqi; Wang, Wei; Xu, Jiao; Tian, Yingze; Feng, Yinchang; Ivey, Cesunica E.; Russell, Armistead G.

    2017-07-01

    Source apportionment technologies are used to understand the impacts of important sources of particulate matter (PM) air quality, and are widely used for both scientific studies and air quality management. Generally, receptor models apportion speciated PM data from a single sampling site. With the development of large scale monitoring networks, PM speciation are observed at multiple sites in an urban area. For these situations, the models should account for three factors, or dimensions, of the PM, including the chemical species concentrations, sampling periods and sampling site information, suggesting the potential power of a three-dimensional source apportionment approach. However, the principle of three-dimensional Parallel Factor Analysis (Ordinary PARAFAC) model does not always work well in real environmental situations for multi-site receptor datasets. In this work, a new three-way receptor model, called ;multi-site three way factor analysis; model is proposed to deal with the multi-site receptor datasets. Synthetic datasets were developed and introduced into the new model to test its performance. Average absolute error (AAE, between estimated and true contributions) for extracted sources were all less than 50%. Additionally, three-dimensional ambient datasets from a Chinese mega-city, Chengdu, were analyzed using this new model to assess the application. Four factors are extracted by the multi-site WFA3 model: secondary source have the highest contributions (64.73 and 56.24 μg/m3), followed by vehicular exhaust (30.13 and 33.60 μg/m3), crustal dust (26.12 and 29.99 μg/m3) and coal combustion (10.73 and 14.83 μg/m3). The model was also compared to PMF, with general agreement, though PMF suggested a lower crustal contribution.

  9. Transforming Rubrics Using Factor Analysis

    Science.gov (United States)

    Baryla, Ed; Shelley, Gary; Trainor, William

    2012-01-01

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

  10. Dealing with the ubiquity of phthalates in the laboratory when determining plasticizers by gas chromatography/mass spectrometry and PARAFAC.

    Science.gov (United States)

    Oca, M L; Rubio, L; Sarabia, L A; Ortiz, M C

    2016-09-16

    Determining plasticizers and other additives migrated from plastic materials becomes a hard task when these substances are already present in the laboratory environment. This work dealt with this drawback in the multiresidue determination of four plasticizers (2,6-di-tert-butyl-4-methyl-phenol (BHT), diisobutyl phthalate (DiBP), bis(2-ethylhexyl) adipate (DEHA) and diisononyl phthalate (DiNP)) and a UV stabilizer (benzophenone (BP)) by gas chromatography/mass spectrometry (GC/MS) using DiBP-d4 as internal standard. The ubiquity of DiBP by a non-constant leaching process in the laboratory was detected, which could not guarantee the achievement of a trustworthy quantification. To handle this, the assessment of the level of DiBP in solvent blanks having fixed the probabilities of false non-compliance (α) and false compliance (β) at 0.01 was performed. On the other hand, another special case was that of DiNP, in whose chromatogram finger peaks appear because of an array of possible C9 isomers. PARAFAC, used for the identification and quantification of all the substances, is a useful chemometric tool that enabled a more reliable determination of this analyte since no peak areas were considered but chromatographic and spectral loadings. Since phthalates may migrate from rubber latex items, an evaluation of the existence of matrix effects on the determination of the five analytes was conducted prior to an extraction with hexane from a dummy for infants. As matrix effects were present, the quantification of the compounds under study was performed following the standard addition method using PARAFAC sample loadings as response variable. As a result, the presence of BHT was confirmed, being its concentration equal to 37.87μgL(-1). Calibrations based on PARAFAC yielded the following values for the decision limit (CCα): 1.16μgL(-1) for BHT, 1.34μgL(-1) for BP, 1.84μgL(-1) for DEHA and 51.42μgL(-1) for DiNP(for α=0.05 and two replicates).

  11. Simultaneous measurement of two enzyme activities using infrared spectroscopy: A comparative evaluation of PARAFAC, TUCKER and N-PLS modeling

    DEFF Research Database (Denmark)

    Baum, Andreas; Hansen, Per Waaben; Meyer, Anne S.;

    2013-01-01

    Enzymes are used in many processes to release fermentable sugars for green production of biofuel, or the refinery of biomass for extraction of functional food ingredients such as pectin or prebiotic oligosaccharides. The complex biomasses may, however, require a multitude of specific enzymes which...... are active on specific substrates generating a multitude of products. In this paper we use the plant polymer, pectin, to present a method to quantify enzyme activity of two pectolytic enzymes by monitoring their superimposed spectral evolutions simultaneously. The data is analyzed by three chemometric...... multiway methods, namely PARAFAC, TUCKER3 and N-PLS, to establish simultaneous enzyme activity assays for pectin lyase and pectin methyl esterase. Correlation coefficients Rpred2 for prediction test sets are 0.48, 0.96 and 0.96 for pectin lyase and 0.70, 0.89 and 0.89 for pectin methyl esterase...

  12. Scalable tensor factorizations for incomplete data

    DEFF Research Database (Denmark)

    Acar, Evrim; Dunlavy, Daniel M.; KOlda, Tamara G.

    2011-01-01

    The problem of incomplete data—i.e., data with missing or unknown values—in multi-way arrays is ubiquitous in biomedical signal processing, network traffic analysis, bibliometrics, social network analysis, chemometrics, computer vision, communication networks, etc. We consider the problem of how...... to factorize data sets with missing values with the goal of capturing the underlying latent structure of the data and possibly reconstructing missing values (i.e., tensor completion). We focus on one of the most well-known tensor factorizations that captures multi-linear structure, CANDECOMP/PARAFAC (CP......-WOPT on two real-world applications: a novel EEG (electroencephalogram) application where missing data is frequently encountered due to disconnections of electrodes and the problem of modeling computer network traffic where data may be absent due to the expense of the data collection process....

  13. PARAFAC: uma ferramenta quimiométrica para tratamento de dados multidimensionais. Aplicações na determinação direta de fármacos em plasma humano por espectrofluorimetria

    OpenAIRE

    Sena Marcelo M.; Trevisan Marcello G.; Poppi Ronei J.

    2005-01-01

    Since the last decade, the combined use of chemometrics and molecular spectroscopic techniques has become a new alternative for direct drug determination, without the need of physical separation. Among the new methodologies developed, the application of PARAFAC in the decomposition of spectrofluorimetric data should be highlighted. The first objective of this article is to describe the theoretical basis of PARAFAC. For this purpose, a discussion about the order of chemometric methods used in ...

  14. An easy guide to factor analysis

    CERN Document Server

    Kline, Paul

    2014-01-01

    Factor analysis is a statistical technique widely used in psychology and the social sciences. With the advent of powerful computers, factor analysis and other multivariate methods are now available to many more people. An Easy Guide to Factor Analysis presents and explains factor analysis as clearly and simply as possible. The author, Paul Kline, carefully defines all statistical terms and demonstrates step-by-step how to work out a simple example of principal components analysis and rotation. He further explains other methods of factor analysis, including confirmatory and path analysis, a

  15. Fluorescence spectroscopy and parallel factor analysis as a dissolved organic monitoring tool to assess treatment performance in drinking water trains.

    Science.gov (United States)

    Vera, M; Cruz, S; Boleda, M R; Mesa, J; Martín-Alonso, J; Casas, S; Gibert, O; Cortina, J L

    2017-04-15

    Fluorescence excitation emission matrix (FEEM) spectroscopy was used to evaluate its applicability as a tool to track dissolved organic matter (DOM) in a drinking water treatment plant (DWTP) that incorporates a conventional line (consisting in ozonation and GAC filtration) and a membrane-based line (consisting in ultrafiltration, reverse osmosis and mineralization) working in parallel. Seven sampling points within the different process stages were characterized monthly during 2014. A global Parallel Factor Analysis (PARAFAC) was used to pull out underlying organic fractions from the fluorescence spectra. Accordingly a five components model was selected to describe the system and the pros and cons of the model were discussed by analysis of the residuals. Among the five fluorescent components, those associated to humic-like matter (C1, C3 and C4) showed a similar season variability in the river water feeding the DWTP (which resembled that of UV254 and TOC), whereas the two components associated to protein-like matter (C2 and C5) exhibited a different behavior. The maximum fluorescence intensity values (Fmax) were used to quantify DOM removals across the plant. Compared to the conventional line, water from the UF/RO membrane-based line showed between 6 and 14 times lower fluorescence intensity signal for the humic-like components and between 1 and 3 for the protein-like components as compared to the conventional line. The differences in DOM composition due to seasonal variations and along the treatment trains point out the suitability of using fluorescence measurements over other parameters such as UV254 as a monitoring tool to help optimize operation conditions of each treatment stage and improve produced water quality in a DWTP.

  16. Second-order Data by Flow Injection Analysis with Spectrophotometric Diode-array Detection and Incorporated Gel-filtration Chromatographic Column

    DEFF Research Database (Denmark)

    Bechmann, Iben Ellegaard

    1997-01-01

    A flow injection analysis (FIA) system furnished with a gel-filtration chromatographic column and with photodiode-array detection was used for the generation of second-order data. The system presented is a model system in which the analytes are blue dextran, potassium hexacyanoferrate......(III) and heparin. It is shown that the rank of the involved sample data matrices corresponds to the number of chemical components present in the sample. The PARAFAC (parallel factor analysis) algorithm combined with multiple linear regression and the tri-PLS (tri-linear partial least-squares regression), which...

  17. Human Factors Analysis in Software Engineering

    Institute of Scientific and Technical Information of China (English)

    Xu Ren-zuo; Ma Ruo-feng; Liu Li-na; Xiong Zhong-wei

    2004-01-01

    The general human factors analysis analyzes human functions, effects and influence in a system. But in a narrow sense, it analyzes human influence upon the reliability of a system, it includes traditional human reliability analysis, human error analysis, man-machine interface analysis, human character analysis, and others. A software development project in software engineering is successful or not to be completely determined by human factors. In this paper, we discuss the human factors intensions, declare the importance of human factors analysis for software engineering by listed some instances. At last, we probe preliminarily into the mentality that a practitioner in software engineering should possess.

  18. A factor analysis to detect factors influencing building national brand

    Directory of Open Access Journals (Sweden)

    Naser Azad

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

  19. Measurement Bias Detection through Factor Analysis

    Science.gov (United States)

    Barendse, M. T.; Oort, F. J.; Werner, C. S.; Ligtvoet, R.; Schermelleh-Engel, K.

    2012-01-01

    Measurement bias is defined as a violation of measurement invariance, which can be investigated through multigroup factor analysis (MGFA), by testing across-group differences in intercepts (uniform bias) and factor loadings (nonuniform bias). Restricted factor analysis (RFA) can also be used to detect measurement bias. To also enable nonuniform…

  20. 激发-发射矩阵荧光结合二阶校正法测定人体血浆样和牛蒡子药材中的牛蒡苷含量%Determination of arctiin in plasma samples and arctium lappa L. by using excitation-emission matrix fluorescence and second-order calibration based on parallel factor analysis/alternating normalization-weighted error algorithms

    Institute of Scientific and Technical Information of China (English)

    张燕; 吴海龙; 欧阳立群; 万瑶; 俞汝勤

    2009-01-01

    本文利用激发-发射矩阵荧光与二阶校正算法相结合,实现快速测定人体血浆样和牛蒡子对照药材中的牛蒡苷含量.采用二阶校正方法的平行因子分析(PARAFAC)和交替归一加权残差(ANWE)两种算法进行解析,所得血浆基体干扰下牛蒡苷的回收率分别为(98.7±1.4)%和(99.7±1.6)%,实现了对血浆样中的牛蒡苷含茸的直接快速定量测定.此外,用上述两种方法对牛蒡子药材中的牛蒡苷含量进行快速测定,所得结果与液相色谱方法结果进行比较,结果令人满意.实验结果表明,此方法方便快捷,可用于复杂试样中未知干扰共存下牛蒡苷含量的测定.%This paper proposed a new approach for direct determination of arctiin in plasma samples as well as a Chinese medicine (Arctium lappa L.) by the combination of excitation-emission matrix fluorescence and second-order calibration methods based on paral-lel factor analysis(PARAFAC) and alternating normalization-weighted error(ANWE) algorithms. The average recoveries of actiin in plasma samples obtained by using PARAFAC and ANWE with the estimated component number of two were 98.7 ± 1.4% and 99. 7 ± 1.6%, respectively. The methodology was used to estimate the content of arctiin in Aretium lappa L. , and the obtained results were also satisfactory compared with that of the HPLC method. It can be seen that the suggested methods can be employed to directly deter-mine arctiin, even in the presence of unknown and un-calibrated interferences, only with a simple pretreatment procedure.

  1. Statistical inference of Minimum Rank Factor Analysis

    NARCIS (Netherlands)

    Shapiro, A; Ten Berge, JMF

    2002-01-01

    For any given number of factors, Minimum Rank Factor Analysis yields optimal communalities for an observed covariance matrix in the sense that the unexplained common variance with that number of factors is minimized, subject to the constraint that both the diagonal matrix of unique variances and the

  2. Statistical inference of Minimum Rank Factor Analysis

    NARCIS (Netherlands)

    Shapiro, A; Ten Berge, JMF

    For any given number of factors, Minimum Rank Factor Analysis yields optimal communalities for an observed covariance matrix in the sense that the unexplained common variance with that number of factors is minimized, subject to the constraint that both the diagonal matrix of unique variances and the

  3. PROGNOSTIC FACTORS ANALYSIS FOR STAGEⅠ RECTAL CANCER

    Institute of Scientific and Technical Information of China (English)

    武爱文; 顾晋; 薛钟麒; 王怡; 徐光炜

    2001-01-01

    To explore the death-related factors of stageⅠrectal cancer patients. Methods: 89 cases of stage I rectal cancer patients between 1985 and 2000 were retrospectively studied for prognostic factors. Factors including age, gender, tumor size, circumferential occupation, gross type, pathological type, depth of tumor invasion, surgical procedure, adjuvant chemotherapy and postoperative complication were chosen for cox multivariate analysis (forward procedure) using Spss software (10.0 version). Results: multivariate analysis demonstrated that muscular invasion was an independent negative prognostic factor for stageⅠrectal cancer patients (P=0.003). Conclusion: Muscular invasion is a negative prognostic factor for stage I rectal cancer patients.

  4. Kernel Factor Analysis Algorithm with Varimax

    Institute of Scientific and Technical Information of China (English)

    Xia Guoen; Jin Weidong; Zhang Gexiang

    2006-01-01

    Kernal factor analysis (KFA) with varimax was proposed by using Mercer kernel function which can map the data in the original space to a high-dimensional feature space, and was compared with the kernel principle component analysis (KPCA). The results show that the best error rate in handwritten digit recognition by kernel factor analysis with varimax (4.2%) was superior to KPCA (4.4%). The KFA with varimax could more accurately image handwritten digit recognition.

  5. Multiple factor analysis by example using R

    CERN Document Server

    Pagès, Jérôme

    2014-01-01

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

  6. Kernel parameter dependence in spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2010-01-01

    feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply a kernel version of maximum autocorrelation factor (MAF) [7, 8] analysis to irregularly sampled stream sediment geochemistry data from South Greenland and illustrate the dependence...

  7. Multistructure Statistical Model Applied To Factor Analysis

    Science.gov (United States)

    Bentler, Peter M.

    1976-01-01

    A general statistical model for the multivariate analysis of mean and covariance structures is described. Matrix calculus is used to develop the statistical aspects of one new special case in detail. This special case separates the confounding of principal components and factor analysis. (DEP)

  8. Analysis of Economic Factors Affecting Stock Market

    OpenAIRE

    Xie, Linyin

    2010-01-01

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

  9. What Is Rotating in Exploratory Factor Analysis?

    Science.gov (United States)

    Osborne, Jason W.

    2015-01-01

    Exploratory factor analysis (EFA) is one of the most commonly-reported quantitative methodology in the social sciences, yet much of the detail regarding what happens during an EFA remains unclear. The goal of this brief technical note is to explore what "rotation" is, what exactly is rotating, and why we use rotation when performing…

  10. Stepwise Variable Selection in Factor Analysis.

    Science.gov (United States)

    Kano, Yutaka; Harada, Akira

    2000-01-01

    Takes several goodness-of-fit statistics as measures of variable selection and develops backward elimination and forward selection procedures in exploratory factor analysis. A newly developed variable selection program, SEFA, can print several fit measures for a current model and models obtained by removing an internal variable or adding an…

  11. Multilevel exploratory factor analysis of discrete data

    NARCIS (Netherlands)

    Barendse, M.T.; Oort, F.J.; Jak, S.; Timmerman, M.E.

    2013-01-01

    Exploratory factor analysis (EFA) can be used to determine the dimensionality of a set of items. When data come from clustered subjects, such as pupils within schools or children within families, the hierarchical structure of the data should be taken into account. Standard multilevel EFA is only sui

  12. An SPSSR -Menu for Ordinal Factor Analysis

    Directory of Open Access Journals (Sweden)

    Mario Basto

    2012-01-01

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

  13. ANALYSIS OF THE FACTORS AFFECTING THE AVERAGE

    Directory of Open Access Journals (Sweden)

    Carmen BOGHEAN

    2013-12-01

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

  14. Nominal Performance Biosphere Dose Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M.A. Wasiolek

    2005-04-28

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

  15. A kernel version of spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2009-01-01

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

  16. What Is Rotating in Exploratory Factor Analysis?

    Directory of Open Access Journals (Sweden)

    Jason W. Osborne

    2015-01-01

    Full Text Available Exploratory factor analysis (EFA is one of the most commonly-reported quantitative methodology in the social sciences, yet much of the detail regarding what happens during an EFA remains unclear. The goal of this brief technical note is to explore what - rotation- is, what exactly is rotating, and why we use rotation when performing EFAs. Some commentary about the relative utility and desirability of different rotation methods concludes the narrative.

  17. A Beginner’s Guide to Factor Analysis: Focusing on Exploratory Factor Analysis

    Directory of Open Access Journals (Sweden)

    An Gie Yong

    2013-10-01

    Full Text Available The following paper discusses exploratory factor analysis and gives an overview of the statistical technique and how it is used in various research designs and applications. A basic outline of how the technique works and its criteria, including its main assumptions are discussed as well as when it should be used. Mathematical theories are explored to enlighten students on how exploratory factor analysis works, an example of how to run an exploratory factor analysis on SPSS is given, and finally a section on how to write up the results is provided. This will allow readers to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output.

  18. Factor analysis identifies subgroups of constipation

    Institute of Scientific and Technical Information of China (English)

    Philip G Dinning; Mike Jones; Linda Hunt; Sergio E Fuentealba; Jamshid Kalanter; Denis W King; David Z Lubowski; Nicholas J Talley; Ian J Cook

    2011-01-01

    AIM: To determine whether distinct symptom groupings exist in a constipated population and whether such grouping might correlate with quantifiable pathophysiological measures of colonic dysfunction. METHODS: One hundred and ninety-one patients presenting to a Gastroenterology clinic with constipation and 32 constipated patients responding to a newspaper advertisement completed a 53-item, wide-ranging selfreport questionnaire. One hundred of these patients had colonic transit measured scintigraphically. Factor analysis determined whether constipation-related symptoms grouped into distinct aspects of symptomatology. Cluster analysis was used to determine whether individual patients naturally group into distinct subtypes. RESULTS: Cluster analysis yielded a 4 cluster solution with the presence or absence of pain and laxative unresponsiveness providing the main descriptors. Amongst all clusters there was a considerable proportion of patients with demonstrable delayed colon transit, irritable bowel syndrome positive criteria and regular stool frequency. The majority of patients with these characteristics also reported regular laxative use. CONCLUSION: Factor analysis identified four constipation subgroups, based on severity and laxative unresponsiveness, in a constipated population. However, clear stratification into clinically identifiable groups remains imprecise.

  19. A kernel version of spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2009-01-01

    of PCA and related techniques. An interesting dilemma in reduction of dimensionality of data is the desire to obtain simplicity for better understanding, visualization and interpretation of the data on the one hand, and the desire to retain sufficient detail for adequate representation on the other hand......Based on work by Pearson in 1901, Hotelling in 1933 introduced principal component analysis (PCA). PCA is often used for general feature generation and linear orthogonalization or compression by dimensionality reduction of correlated multivariate data, see Jolliffe for a comprehensive description...... version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply kernel versions of PCA, maximum autocorrelation factor (MAF) analysis...

  20. Nominal Performance Biosphere Dose Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M. Wasiolek

    2004-09-08

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

  1. Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

    Science.gov (United States)

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

    2014-11-01

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

  2. Scalable tensor factorizations with incomplete data.

    Energy Technology Data Exchange (ETDEWEB)

    Morup, Morten (Technical University of Denmark); Dunlavy, Daniel M. (Sandia National Laboratories, Albuquerque, NM); Acar, Evrim (Information Technologies Institute, Turkey); Kolda, Tamara Gibson

    2010-07-01

    The problem of incomplete data - i.e., data with missing or unknown values - in multi-way arrays is ubiquitous in biomedical signal processing, network traffic analysis, bibliometrics, social network analysis, chemometrics, computer vision, communication networks, etc. We consider the problem of how to factorize data sets with missing values with the goal of capturing the underlying latent structure of the data and possibly reconstructing missing values (i.e., tensor completion). We focus on one of the most well-known tensor factorizations that captures multi-linear structure, CANDECOMP/PARAFAC (CP). In the presence of missing data, CP can be formulated as a weighted least squares problem that models only the known entries. We develop an algorithm called CP-WOPT (CP Weighted OPTimization) that uses a first-order optimization approach to solve the weighted least squares problem. Based on extensive numerical experiments, our algorithm is shown to successfully factorize tensors with noise and up to 99% missing data. A unique aspect of our approach is that it scales to sparse large-scale data, e.g., 1000 x 1000 x 1000 with five million known entries (0.5% dense). We further demonstrate the usefulness of CP-WOPT on two real-world applications: a novel EEG (electroencephalogram) application where missing data is frequently encountered due to disconnections of electrodes and the problem of modeling computer network traffic where data may be absent due to the expense of the data collection process.

  3. Three-way principal component analysis as a tool to evaluate the chemical stability of metal bearing residues from wastewater treatment by the ferrite process.

    Science.gov (United States)

    Pardo, Rafael; Vega, Marisol; Barrado, Enrique; Castrillejo, Yolanda; Sánchez, Isabel

    2013-11-15

    The chemical fractionation patterns of eight metals (Cd, Co, Cu, Cr, Mn, Ni, Pb and Zn) have been determined in 27 metal-bearing residues by using the BCR sequential extraction procedure. The residues were generated as by-products during the optimization of a semi-continuous reactor for metal removal from wastewater based on ferrite synthesis by co-precipitation. The three-dimensional X dataset (samples×metals×fractions) obtained by applying the BCR procedure has been analyzed by multivariate methods: matrix augmentation (MA-PCA) and three-way principal component analysis, 3-PCA (PARAFAC and Tucker3 models). MA-PCA and PARAFAC methods led to two-factor models giving a satisfactory but incomplete picture of the metal fractionation patterns, but the Tucker3 [2,1,2] model allowed to simultaneously describe both the 'pseudo-total' (acid-soluble) contents and the chemical fractionation by means of two non-null interactions g111 and g212 which explain 53.5% and 18.0% of the total variance, respectively. The A-mode loadings of the g212 interaction showed the close relationship between the magnetic character of the solid residues, i.e. the crystalline structure, and the chemical fractionation patterns of the metals resulting from the application of the BCR sequential extraction procedure.

  4. Analysis of Ultra Linguistic Factors in Interpretation

    Institute of Scientific and Technical Information of China (English)

    姚嘉

    2015-01-01

    The quality of interpretation is a dynamic conception, involving a good deal of variables, such as the participants, the situations, working conditions, cultures etc.. Therefore, in interpretation, those static elements, such as traditional grammars and certain linguistic rules can not be counted as the only criteria for the quality of interpretation. That is, there are many other non-language elements—Ultra-linguistic factors that play an important role in interpretation. Ultra-linguistic factors get rid of the bounding of traditional grammar and parole, and reveal the facts in an indirect way. This paper gives a brief analysis of Ultra Lin⁃guistic elements in interpretation in order to achieve better result in interpretation practice.

  5. Factor Rotation and Standard Errors in Exploratory Factor Analysis

    Science.gov (United States)

    Zhang, Guangjian; Preacher, Kristopher J.

    2015-01-01

    In this article, we report a surprising phenomenon: Oblique CF-varimax and oblique CF-quartimax rotation produced similar point estimates for rotated factor loadings and factor correlations but different standard error estimates in an empirical example. Influences of factor rotation on asymptotic standard errors are investigated using a numerical…

  6. Model correction factor method for system analysis

    DEFF Research Database (Denmark)

    Ditlevsen, Ove Dalager; Johannesen, Johannes M.

    2000-01-01

    The Model Correction Factor Method is an intelligent response surface method based on simplifiedmodeling. MCFM is aimed for reliability analysis in case of a limit state defined by an elaborate model. Herein it isdemonstrated that the method is applicable for elaborate limit state surfaces on which...... severallocally most central points exist without there being a simple geometric definition of the corresponding failuremodes such as is the case for collapse mechanisms in rigid plastic hinge models for frame structures. Taking as simplifiedidealized model a model of similarity with the elaborate model...... surface than existing in the idealized model....

  7. Scalable group level probabilistic sparse factor analysis

    DEFF Research Database (Denmark)

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

    2017-01-01

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

  8. Disruptive Event Biosphere Dose Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M. Wasiolek

    2004-09-08

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

  9. Three-way partial least-squares/residual bilinearization study of second-order lanthanide-sensitized luminescence excitation-time decay data: analysis of benzoic acid in beverage samples.

    Science.gov (United States)

    Lozano, Valeria A; Ibañez, Gabriela A; Olivieri, Alejandro C

    2008-03-10

    Lanthanide-sensitized luminescence excitation-time decay matrices were employed for achieving the second-order advantage using as chemometric algorithms parallel factor analysis (PARAFAC) and multidimensional partial least-squares with residual bilinearization (N-PLS/RBL). The second-order data were measured for a calibration set of samples containing the analyte benzoic acid in the concentration range from 0.00 to 5.00 mg L(-1), for a validation set containing the analyte and the potential interferent saccharin (in the range 0.00-6.00 mg L(-1)), and for real samples of beverages containing benzoic acid as preservant, saccharin, and other potentially interfering compounds. All samples were treated with terbium(III), trioctylphosphine oxide as a synergistic ligand, and contained a suitable imidazol buffer, in order to ensure maximum intensity of the luminescence signals. The results indicate a slightly better predictive ability of the newly introduced N-PLS/RBL procedure over standard PARAFAC, both in what concerns the comparison with nominal analyte concentrations in the validation sample set and with results provided by the reference high-performance liquid chromatographic technique for the real sample set.

  10. Attitude Exploration Using Factor Analysis Technique

    Directory of Open Access Journals (Sweden)

    Monika Raghuvanshi

    2016-12-01

    Full Text Available Attitude is a psychological variable that contains positive or negative evaluation about people or an environment. The growing generation possesses learning skills, so if positive attitude is inculcated at the right age, it might therefore become habitual. Students in the age group 14-20 years from the city of Bikaner, India, are the target population for this study. An inventory of 30Likert-type scale statements was prepared in order to measure attitude towards the environment and matters related to conservation. The primary data is collected though a structured questionnaire, using cluster sampling technique and analyzed using the IBM SPSS 23 statistical tool. Factor analysis is used to reduce 30 variables to a smaller number of more identifiable groups of variables. Results show that students “need more regulation and voluntary participation to protect the environment”, “need conservation of water and electricity”, “are concerned for undue wastage of water”, “need visible actions to protect the environment”, “need strengthening of the public transport system”, “are a little bit ignorant about the consequences of global warming”, “want prevention of water pollution by industries”, “need changing of personal habits to protect the environment”, and “don’t have firsthand experience of global warming”. Analysis revealed that nine factors obtained could explain about 58.5% variance in the attitude of secondary school students towards the environment in the city of Bikaner, India. The remaining 39.6% variance is attributed to other elements not explained by this analysis. A global campaign for improvement in attitude about environmental issues and its utility in daily lives may boost positive youth attitudes, potentially impacting worldwide. A cross-disciplinary approach may be developed by teaching along with other related disciplines such as science, economics, and social studies etc.

  11. Factorized molecular wave functions: Analysis of the nuclear factor

    Energy Technology Data Exchange (ETDEWEB)

    Lefebvre, R., E-mail: roland.lefebvre@u-psud.fr [Institut des Sciences Moléculaires d’ Orsay, Bâtiment 350, UMR8214, CNRS- Université. Paris-Sud, 91405 Orsay, France and Sorbonne Universités, UPMC Univ Paris 06, UFR925, F-75005 Paris (France)

    2015-06-07

    The exact factorization of molecular wave functions leads to nuclear factors which should be nodeless functions. We reconsider the case of vibrational perturbations in a diatomic species, a situation usually treated by combining Born-Oppenheimer products. It was shown [R. Lefebvre, J. Chem. Phys. 142, 074106 (2015)] that it is possible to derive, from the solutions of coupled equations, the form of the factorized function. By increasing artificially the interstate coupling in the usual approach, the adiabatic regime can be reached, whereby the wave function can be reduced to a single product. The nuclear factor of this product is determined by the lowest of the two potentials obtained by diagonalization of the potential matrix. By comparison with the nuclear wave function of the factorized scheme, it is shown that by a simple rectification, an agreement is obtained between the modified nodeless function and that of the adiabatic scheme.

  12. Correspondence factor analysis of steroid libraries.

    Science.gov (United States)

    Ojasoo, T; Raynaud, J P; Doré, J C

    1995-06-01

    The receptor binding of a library of 187 steroids to five steroid hormone receptors (estrogen, progestin, androgen, mineralocorticoid, and glucocorticoid) has been analyzed by correspondence factor analysis (CFA) in order to illustrate how the method could be used to derive structure-activity-relationships from much larger libraries. CFA is a cartographic multivariate technique that provides objective distribution maps of the data after reduction and filtering of redundant information and noise. The key to the analysis of very complex data tables is the formation of barycenters (steroids with one or more common structural fragments) that can be introduced into CFA analyses used as mathematical models. This is possible in CFA because the method uses X2-metrics and is based on the distributional equivalence of the rows and columns of the transformed data matrix. We have thus demonstrated, in purely objective statistical terms, the general conclusions on the specificity of various functional and other groups derived from prior analyses by expert intuition and reasoning. A finer analysis was made of a series of A-ring phenols showing the high degree of glucocorticoid receptor and progesterone receptor binding that can be generated by certain C-11-substitutions despite the presence of the phenolic A-ring characteristic of estrogen receptor-specific binding.

  13. Factorial invariance in multilevel confirmatory factor analysis.

    Science.gov (United States)

    Ryu, Ehri

    2014-02-01

    This paper presents a procedure to test factorial invariance in multilevel confirmatory factor analysis. When the group membership is at level 2, multilevel factorial invariance can be tested by a simple extension of the standard procedure. However level-1 group membership raises problems which cannot be appropriately handled by the standard procedure, because the dependency between members of different level-1 groups is not appropriately taken into account. The procedure presented in this article provides a solution to this problem. This paper also shows Muthén's maximum likelihood (MUML) estimation for testing multilevel factorial invariance across level-1 groups as a viable alternative to maximum likelihood estimation. Testing multilevel factorial invariance across level-2 groups and testing multilevel factorial invariance across level-1 groups are illustrated using empirical examples. SAS macro and Mplus syntax are provided.

  14. Physiological Factors Analysis in Unpressurized Aircraft Cabins

    Science.gov (United States)

    Patrao, Luis; Zorro, Sara; Silva, Jorge

    2016-11-01

    Amateur and sports flight is an activity with growing numbers worldwide. However, the main cause of flight incidents and accidents is increasingly pilot error, for a number of reasons. Fatigue, sleep issues and hypoxia, among many others, are some that can be avoided, or, at least, mitigated. This article describes the analysis of psychological and physiological parameters during flight in unpressurized aircraft cabins. It relates cerebral oximetry and heart rate with altitude, as well as with flight phase. The study of those parameters might give clues on which variations represent a warning sign to the pilot, thus preventing incidents and accidents due to human factors. Results show that both cerebral oximetry and heart rate change along the flight and altitude in the alert pilot. The impaired pilot might not reveal these variations and, if this is detected, he can be warned in time.

  15. Practical Considerations for Using Exploratory Factor Analysis in Educational Research

    Science.gov (United States)

    Beavers, Amy S.; Lounsbury, John W.; Richards, Jennifer K.; Huck, Schuyler W.; Skolits, Gary J.; Esquivel, Shelley L.

    2013-01-01

    The uses and methodology of factor analysis are widely debated and discussed, especially the issues of rotational use, methods of confirmatory factor analysis, and adequate sample size. The variety of perspectives and often conflicting opinions can lead to confusion among researchers about best practices for using factor analysis. The focus of the…

  16. Comprehensive two-dimensional gas chromatography combined to multivariate data analysis for detection of disease-resistant clones of Eucalyptus.

    Science.gov (United States)

    Hantao, Leandro Wang; Toledo, Bruna Regina; Ribeiro, Fabiana Alves de Lima; Pizetta, Marilia; Pierozzi, Caroline Geraldi; Furtado, Edson Luiz; Augusto, Fabio

    2013-11-15

    In this paper it is reported the use of the chromatographic profiles from volatile fractions of plant clones - in this case, hybrids of Eucalyptus grandis×Eucalyptus urophylla - to determine specimens susceptible to rust disease. The analytes were isolated by headspace solid phase microextraction (HS-SPME) and analyzed by comprehensive two-dimensional gas chromatography combined to fast quadrupole mass spectrometry (GC×GC-qMS). Parallel Factor Analysis (PARAFAC) was employed for estimate the correlation between the chromatographic profiles and resistance against Eucalyptus rust, after preliminary variable selection performed by Fisher ratio analysis. The proposed method allowed the differentiation between susceptible and non-susceptible clones and determination of three resistance biomarkers. This approach can be a valuable alternative for the otherwise time-consuming and labor-intensive methods commonly used.

  17. Fluorescence spectral analysis for the discrimination of complex, similar mixtures with the aid of chemometrics.

    Science.gov (United States)

    Ni, Yongnian; Lai, Yanhua; Kokot, Serge

    2012-07-01

    An analytical method for the classification of complex real-world samples was researched and developed with the use of excitation-emission fluorescence matrix (EEFM) spectroscopy, using the medicinal herbs, Rhizoma corydalis decumbentis (RCD) and Rhizoma corydalis (RC) as example samples. The data set was obtained from various authentic RCD-A and RC-A, adulterated AD, and commercial RCD-C and RC-C samples. The spectra (range: λ(ex) = 215∼395 nm and λ(em) = 290∼560 nm), arranged in two- and three-way data matrix formats, were processed using principal component analysis (PCA) and parallel factor analysis (PARAFAC) to produce two-dimensional component-by-component plots for qualitative data classification. The RCD-A and RC-A object groups were clearly discriminated, but the AD and the RCD-C as well as RC-C samples were less well separated. PARAFAC analysis produced somewhat better discrimination, and loadings plots revealed the presence of the marker compound Protopine-a strongly fluorescing substance-as well as at least two other unidentified fluorescent components. Classification performance of the common K-nearest neighbors (KNN) and linear discrimination analysis (LDA) methods was relatively poor when compared with that of the back propagation- and radial basis function-artificial neural networks (BP-ANN and RBF-ANN) models on the basis of two- and three-way formatted data. The best results were obtained with the three-way fingerprints and the RBF-ANN model. Subsequently, the quality of the commercial samples (RCD-C and RC-C) was classified on the best optimized RBF-ANN model. Thus, EEFM spectroscopy, which provides three-way measured data, is potentially a powerful analytical technique for the analysis of complex real-world substances provided the classification is performed by the RBF-ANN or similar ANN methods.

  18. Housing price forecastability: A factor analysis

    DEFF Research Database (Denmark)

    Bork, Lasse; Møller, Stig Vinther

    of the model stays high at longer horizons. The estimated factors are strongly statistically signi…cant according to a bootstrap resampling method which takes into account that the factors are estimated regressors. The simple three-factor model also contains substantial out-of-sample predictive power...

  19. A Second Generation Nonlinear Factor Analysis.

    Science.gov (United States)

    Etezadi-Amoli, Jamshid; McDonald, Roderick P.

    1983-01-01

    Nonlinear common factor models with polynomial regression functions, including interaction terms, are fitted by simultaneously estimating the factor loadings and common factor scores, using maximum likelihood and least squares methods. A Monte Carlo study gives support to a conjecture about the form of the distribution of the likelihood ratio…

  20. Disruptive Event Biosphere Doser Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M. Wasiolek

    2000-12-28

    The purpose of this report was to document the process leading to, and the results of, development of radionuclide-, exposure scenario-, and ash thickness-specific Biosphere Dose Conversion Factors (BDCFs) for the postulated postclosure extrusive igneous event (volcanic eruption) at Yucca Mountain. BDCF calculations were done for seventeen radionuclides. The selection of radionuclides included those that may be significant dose contributors during the compliance period of up to 10,000 years, as well as radionuclides of importance for up to 1 million years postclosure. The approach documented in this report takes into account human exposure during three different phases at the time of, and after, volcanic eruption. Calculations of disruptive event BDCFs used the GENII-S computer code in a series of probabilistic realizations to propagate the uncertainties of input parameters into the output. The pathway analysis included consideration of different exposure pathway's contribution to the BDCFs. BDCFs for volcanic eruption, when combined with the concentration of radioactivity deposited by eruption on the soil surface, allow calculation of potential radiation doses to the receptor of interest. Calculation of radioactivity deposition is outside the scope of this report and so is the transport of contaminated ash from the volcano to the location of the receptor. The integration of the biosphere modeling results (BDCFs) with the outcomes of the other component models is accomplished in the Total System Performance Assessment (TSPA), in which doses are calculated to the receptor of interest from radionuclides postulated to be released to the environment from the potential repository at Yucca Mountain.

  1. Nominal Performance Biosphere Dose Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M. Wasiolek

    2000-12-21

    The purpose of this report was to document the process leading to development of the Biosphere Dose Conversion Factors (BDCFs) for the postclosure nominal performance of the potential repository at Yucca Mountain. BDCF calculations concerned twenty-four radionuclides. This selection included sixteen radionuclides that may be significant nominal performance dose contributors during the compliance period of up to 10,000 years, five additional radionuclides of importance for up to 1 million years postclosure, and three relatively short-lived radionuclides important for the human intrusion scenario. Consideration of radionuclide buildup in soil caused by previous irrigation with contaminated groundwater was taken into account in the BDCF development. The effect of climate evolution, from the current arid conditions to a wetter and cooler climate, on the BDCF values was evaluated. The analysis included consideration of different exposure pathway's contribution to the BDCFs. Calculations of nominal performance BDCFs used the GENII-S computer code in a series of probabilistic realizations to propagate the uncertainties of input parameters into the output. BDCFs for the nominal performance, when combined with the concentrations of radionuclides in groundwater allow calculation of potential radiation doses to the receptor of interest. Calculated estimates of radionuclide concentration in groundwater result from the saturated zone modeling. The integration of the biosphere modeling results (BDCFs) with the outcomes of the other component models is accomplished in the Total System Performance Assessment (TSPA) to calculate doses to the receptor of interest from radionuclides postulated to be released to the environment from the potential repository at Yucca Mountain.

  2. EXPLORATORY FACTOR ANALYSIS (EFA IN CONSUMER BEHAVIOR AND MARKETING RESEARCH

    Directory of Open Access Journals (Sweden)

    Marcos Pascual Soler

    2012-06-01

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

  3. Factor analysis of serogroups botanica and aurisina of Leptospira biflexa.

    Science.gov (United States)

    Cinco, M

    1977-11-01

    Factor analysis is performed on serovars of Botanica and Aurisina serogroup of Leptospira biflexa. The results show the arrangement of main factors serovar and serogroup specific, as well as the antigens common with serovars of heterologous serogroups.

  4. An Item Factor Analysis of the Mooney Problem Check List

    Science.gov (United States)

    Stewart, David W.; Deiker, Thomas

    1976-01-01

    Explores the factor structure of the Mooney Problem Check List (MPCL) at the junior and senior high school level by undertaking a large obverse factor analysis of item responses in three adolescent criterion groups. (Author/DEP)

  5. Full Information Item Factor Analysis of the FCI

    Science.gov (United States)

    Hagedorn, Eric

    2010-02-01

    Traditional factor analytical methods, principal factors or principal components analysis, are inappropriate techniques for analyzing dichotomously scored responses to standardized tests or concept inventories because they lead to artifactual factors often referred to as ``difficulty factors.'' Full information item factor analysis (Bock, Gibbons and Muraki, 1988) based on Thurstone's multiple factor model and calculated using marginal maximum likelihood estimation, is an appropriate technique for such analyses. Force Concept Inventory (Hestenes, Wells and Swackhamer, 1992) data from 1582 university students completing an introductory physics course, was analyzed using the full information item factor analysis software TESTFACT v. 4. Analyzing the statistical significance of successive factors added to the model, using chi-squared statistics, led to a six factor model interpretable in terms of the conceptual dimensions of the FCI. )

  6. Exploratory matrix factorization for PET image analysis.

    Science.gov (United States)

    Kodewitz, A; Keck, I R; Tomé, A M; Lang, E W

    2010-01-01

    Features are extracted from PET images employing exploratory matrix factorization techniques such as nonnegative matrix factorization (NMF). Appropriate features are fed into classifiers such as a support vector machine or a random forest tree classifier. An automatic feature extraction and classification is achieved with high classification rate which is robust and reliable and can help in an early diagnosis of Alzheimer's disease.

  7. Analysis of Factors Affecting the Quality of an E-commerce Website Using Factor Analysis

    Directory of Open Access Journals (Sweden)

    Saurabh Mishra

    2014-12-01

    Full Text Available The purpose of this study is to identify factors which affect the quality and effectiveness of an e commerce website which also majorly affect customer satisfaction and ultimately customer retention and loyalty. This research paper examines a set of 23 variables and integrates them into 4 factors which affect the quality of a website. An online questionnaire survey was conducted to generate statistics regarding the preferences of the e-commerce website users.The 23 variables taken from customer survey are generalized into 4 major factors using exploratory factor analysis which are content, navigation, services and interface design. The research majorly consists of the responses of students between the age group of 18-25 years and considers different B2C commercial websites. Identified variables are important with respect to the current competition in the market as service of an e-commerce website also play a major role in ensuring customer satisfaction. Further research in this domain can be done for websites’ version for mobile devices.

  8. Exploring Technostress: Results of a Large Sample Factor Analysis

    OpenAIRE

    Steponas Jonušauskas; Agota Giedre Raisiene

    2016-01-01

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

  9. Identification of noise in linear data sets by factor analysis

    Energy Technology Data Exchange (ETDEWEB)

    Roscoe, B.A.; Hopke, Ph.K. (Illinois Univ., Urbana (USA))

    1982-01-01

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

  10. Effect Factors of Liquid Scintillation Analysis

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    <正>Over the past decades, the liquid scintillation analysis (LSA) technique remains one of the most popular experimental tools used for the quantitative analysis of radionuclide, especially low-energy β

  11. FACTOR ANALYSIS OF THE ELKINS HYPNOTIZABILITY SCALE

    Science.gov (United States)

    Elkins, Gary; Johnson, Aimee K.; Johnson, Alisa J.; Sliwinski, Jim

    2015-01-01

    Assessment of hypnotizability can provide important information for hypnosis research and practice. The Elkins Hypnotizability Scale (EHS) consists of 12 items and was developed to provide a time-efficient measure for use in both clinical and laboratory settings. The EHS has been shown to be a reliable measure with support for convergent validity with the Stanford Hypnotic Susceptibility Scale, Form C (r = .821, p < .001). The current study examined the factor structure of the EHS, which was administered to 252 adults (51.3% male; 48.7% female). Average time of administration was 25.8 minutes. Four factors selected on the basis of the best theoretical fit accounted for 63.37% of the variance. The results of this study provide an initial factor structure for the EHS. PMID:25978085

  12. ANALYSIS OF EXTERNAL FACTORS AFFECTING THE PRICING

    Directory of Open Access Journals (Sweden)

    Irina A. Kiseleva

    2013-01-01

    Full Text Available The external factors influencing the process of formation of tariffs of commercial services are considered in the article. External environment is known to be very diverse and changeable. Currently, pricing has become one of the key processes of strategic development of a company. Pricing in the service sector, in turn, is highly susceptible to changes in the external environment. Its components directly or indirectly affect the market of services, changing it adopted economic processes. As a rule, firms providing services can’t influence the changes in external factors. However, the service market is very flexible, which enables businesses to reshape pricing strategy, to adapt it to the new environment.

  13. Factor Analysis for Spectral Reconnaissance and Situational Understanding

    Science.gov (United States)

    2016-07-11

    reviewed journals: Final Report: Factor Analysis for Spectral Reconnaissance and Situational Understanding Report Title The Army has a critical need for...based NP-hard design problems, by associating them with corresponding estimation problems. 1 Factor Analysis for Spectral Reconnaissance and Situational ...SECURITY CLASSIFICATION OF: The Army has a critical need for enhancing situational understanding for dismounted soldiers and rapidly deployed tactical

  14. A Factor Analysis of the BSRI and the PAQ.

    Science.gov (United States)

    Edwards, Teresa A.; And Others

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

  15. Exploratory Factor Analysis of African Self-Consciousness Scale Scores

    Science.gov (United States)

    Bhagwat, Ranjit; Kelly, Shalonda; Lambert, Michael C.

    2012-01-01

    This study replicates and extends prior studies of the dimensionality, convergent, and external validity of African Self-Consciousness Scale scores with appropriate exploratory factor analysis methods and a large gender balanced sample (N = 348). Viable one- and two-factor solutions were cross-validated. Both first factors overlapped significantly…

  16. Multigroup Confirmatory Factor Analysis: Locating the Invariant Referent Sets

    Science.gov (United States)

    French, Brian F.; Finch, W. Holmes

    2008-01-01

    Multigroup confirmatory factor analysis (MCFA) is a popular method for the examination of measurement invariance and specifically, factor invariance. Recent research has begun to focus on using MCFA to detect invariance for test items. MCFA requires certain parameters (e.g., factor loadings) to be constrained for model identification, which are…

  17. Factor Analysis of People Rather than Variables: Q and Other Two-Mode Factor Analytic Models.

    Science.gov (United States)

    Frederick, Brigitte N.

    Factor analysis attempts to study how different objects group together to form factors with the purposes of: (1) reducing the number of factorable entities (e.g., variables) with which the researcher needs to deal; (2) searching data for qualitative and quantitative differences; and (3) testing hypotheses (R. Gorsuch, 1983). While most factor…

  18. Chiral analysis of baryon form factors

    Energy Technology Data Exchange (ETDEWEB)

    Gail, T.A.

    2007-11-08

    This work presents an extensive theoretical investigation of the structure of the nucleon within the standard model of elementary particle physics. In particular, the long range contributions to a number of various form factors parametrizing the interactions of the nucleon with an electromagnetic probe are calculated. The theoretical framework for those calculations is chiral perturbation theory, the exact low energy limit of Quantum Chromo Dynamics, which describes such long range contributions in terms of a pion-cloud. In this theory, a nonrelativistic leading one loop order calculation of the form factors parametrizing the vector transition of a nucleon to its lowest lying resonance, the {delta}, a covariant calculation of the isovector and isoscalar vector form factors of the nucleon at next to leading one loop order and a covariant calculation of the isoscalar and isovector generalized vector form factors of the nucleon at leading one loop order are performed. In order to perform consistent loop calculations in the covariant formulation of chiral perturbation theory an appropriate renormalization scheme is defined in this work. All theoretical predictions are compared to phenomenology and results from lattice QCD simulations. These comparisons allow for a determination of the low energy constants of the theory. Furthermore, the possibility of chiral extrapolation, i.e. the extrapolation of lattice data from simulations at large pion masses down to the small physical pion mass is studied in detail. Statistical as well as systematic uncertainties are estimated for all results throughout this work. (orig.)

  19. Analytic standard errors for exploratory process factor analysis.

    Science.gov (United States)

    Zhang, Guangjian; Browne, Michael W; Ong, Anthony D; Chow, Sy Miin

    2014-07-01

    Exploratory process factor analysis (EPFA) is a data-driven latent variable model for multivariate time series. This article presents analytic standard errors for EPFA. Unlike standard errors for exploratory factor analysis with independent data, the analytic standard errors for EPFA take into account the time dependency in time series data. In addition, factor rotation is treated as the imposition of equality constraints on model parameters. Properties of the analytic standard errors are demonstrated using empirical and simulated data.

  20. A replication of a factor analysis of motivations for trapping

    Science.gov (United States)

    Schroeder, Susan; Fulton, David C.

    2015-01-01

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

  1. Analysis of Interaction Factors Between Two Piles

    Institute of Scientific and Technical Information of China (English)

    CAO Ming; CHEN Long-zhu

    2008-01-01

    A rigorous analytical method is presented for calculating the interaction factor between two identical piles subjected to vertical loads. Following the technique proposed by Muki and Sternberg, the problem is decomposed into an extended soil mass and two fictitious piles characterized respectively by Young's modulus of the soil and that of the difference between the pile and soil. The unknown axial forces along fictitious piles are determined by solving a Fredholm integral equation of the second kind, which imposes the compatibility condition that the axial strains of the fictitious piles are equal to those corresponding to the centroidal axes of the extended soil. The real pile forces and displacements can subequally be calculated based on the determined fictitious pile forces, and finally, the desired pile interaction factors may be obtained. Results confirm the validity of the proposed approach and portray the influence of the governing parameters on the pile interaction.

  2. Analysis of factors affecting fattening of chickens

    OpenAIRE

    OBERMAJEROVÁ, Barbora

    2013-01-01

    Poultry meat belongs to the basic assortment of human nutrition. The meat of an intensively fattened poultry is a source of easily digestible proteins, lipids, mineral substances and vitamins. The aim of this bachelor´s thesis was to write out a literature review, which is focused on the intensity of growth, carcass yield, quality and composition of broiler chickens meat. The following describes the internal and external factors that affect them, i.e. genetic foundation, hybrid combination, s...

  3. Investigating product development strategy in beverage industry using factor analysis

    Directory of Open Access Journals (Sweden)

    Naser Azad

    2013-03-01

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

  4. Housing Price Forecastability: A Factor Analysis

    DEFF Research Database (Denmark)

    Bork, Lasse; Møller, Stig Vinther

    2016-01-01

    We examine U.S. housing price forecastability using principal component analysis (PCA), partial least squares (PLS), and sparse PLS (SPLS). We incorporate information from a large panel of 128 economic time series and show that macroeconomic fundamentals have strong predictive power for future...

  5. Housing price forecastability: A factor analysis

    DEFF Research Database (Denmark)

    Møller, Stig Vinther; Bork, Lasse

    2017-01-01

    We examine U.S. housing price forecastability using principal component analysis (PCA), partial least squares (PLS), and sparse PLS (SPLS). We incorporate information from a large panel of 128 economic time series and show that macroeconomic fundamentals have strong predictive power for future...

  6. Scalable tensor factorizations with missing data.

    Energy Technology Data Exchange (ETDEWEB)

    Morup, Morten (Technical University of Denmark); Dunlavy, Daniel M.; Acar, Evrim (Turkish National Research Institute of Electronics and Cryptology); Kolda, Tamara Gibson

    2010-04-01

    The problem of missing data is ubiquitous in domains such as biomedical signal processing, network traffic analysis, bibliometrics, social network analysis, chemometrics, computer vision, and communication networks|all domains in which data collection is subject to occasional errors. Moreover, these data sets can be quite large and have more than two axes of variation, e.g., sender, receiver, time. Many applications in those domains aim to capture the underlying latent structure of the data; in other words, they need to factorize data sets with missing entries. If we cannot address the problem of missing data, many important data sets will be discarded or improperly analyzed. Therefore, we need a robust and scalable approach for factorizing multi-way arrays (i.e., tensors) in the presence of missing data. We focus on one of the most well-known tensor factorizations, CANDECOMP/PARAFAC (CP), and formulate the CP model as a weighted least squares problem that models only the known entries. We develop an algorithm called CP-WOPT (CP Weighted OPTimization) using a first-order optimization approach to solve the weighted least squares problem. Based on extensive numerical experiments, our algorithm is shown to successfully factor tensors with noise and up to 70% missing data. Moreover, our approach is significantly faster than the leading alternative and scales to larger problems. To show the real-world usefulness of CP-WOPT, we illustrate its applicability on a novel EEG (electroencephalogram) application where missing data is frequently encountered due to disconnections of electrodes.

  7. Signs and symptoms of acute mania: a factor analysis

    Directory of Open Access Journals (Sweden)

    de Silva Varuni A

    2011-08-01

    Full Text Available Abstract Background The major diagnostic classifications consider mania as a uni-dimensional illness. Factor analytic studies of acute mania are fewer compared to schizophrenia and depression. Evidence from factor analysis suggests more categories or subtypes than what is included in the classification systems. Studies have found that these factors can predict differences in treatment response and prognosis. Methods The sample included 131 patients consecutively admitted to an acute psychiatry unit over a period of one year. It included 76 (58% males. The mean age was 44.05 years (SD = 15.6. Patients met International Classification of Diseases-10 (ICD-10 clinical diagnostic criteria for a manic episode. Patients with a diagnosis of mixed bipolar affective disorder were excluded. Participants were evaluated using the Young Mania Rating Scale (YMRS. Exploratory factor analysis (principal component analysis was carried out and factors with an eigenvalue > 1 were retained. The significance level for interpretation of factor loadings was 0.40. The unrotated component matrix identified five factors. Oblique rotation was then carried out to identify three factors which were clinically meaningful. Results Unrotated principal component analysis extracted five factors. These five factors explained 65.36% of the total variance. Oblique rotation extracted 3 factors. Factor 1 corresponding to 'irritable mania' had significant loadings of irritability, increased motor activity/energy and disruptive aggressive behaviour. Factor 2 corresponding to 'elated mania' had significant loadings of elevated mood, language abnormalities/thought disorder, increased sexual interest and poor insight. Factor 3 corresponding to 'psychotic mania' had significant loadings of abnormalities in thought content, appearance, poor sleep and speech abnormalities. Conclusions Our findings identified three clinically meaningful factors corresponding to 'elated mania', 'irritable mania

  8. Factors Effecting Unemployment: A Cross Country Analysis

    Directory of Open Access Journals (Sweden)

    Aurangzeb

    2013-01-01

    Full Text Available This paper investigates macroeconomic determinants of the unemployment for India, China and Pakistan for the period 1980 to 2009. The investigation was conducted through co integration, granger causality and regression analysis. The variables selected for the study are unemployment, inflation, gross domestic product, exchange rate and the increasing rate of population. The results of regression analysis showed significant impact of all the variables for all three countries. GDP of Pakistan showed positive relation with the unemployment rate and the reason of that is the poverty level and underutilization of foreign investment. The result of granger causality showed that bidirectional causality does not exist between any of the variable for all three countries. Co integration result explored that long term relationship do exist among the variables for all the models. It is recommended that distribution of income needs to be improved for Pakistan in order to have positive impact of growth on the employment rate.

  9. ANALYSIS OF RISK FACTORS ECTOPIC PREGNANCY

    Directory of Open Access Journals (Sweden)

    Budi Santoso

    2017-04-01

    Full Text Available Introduction: Ectopic pregnancy is a pregnancy with extrauterine implantation. This situation is gynecologic emergency that contributes to maternal mortality. Therefore, early recognition, based on identification of the causes of ectopic pregnancy risk factors, is needed. Methods: The design descriptive observational. The samples were pregnant women who had ectopic pregnancy at Maternity Room, Emergency Unit, Dr. Soetomo Hospital, Surabaya, from 1 July 2008 to 1 July 2010. Sampling technique was total sampling using medical records. Result: Patients with ectopic pregnancy were 99 individuals out of 2090 pregnant women who searched for treatment in Dr. Soetomo Hospital. However, only 29 patients were accompanied with traceable risk factors. Discussion:. Most ectopic pregnancies were in the age group of 26-30 years, comprising 32 patients (32.32%, then in age groups of 31–35 years as many as 25 patients (25.25%, 18 patients in age group 21–25 years (18.18%, 17 patients in age group 36–40 years (17.17%, 4 patients in age group 41 years and more (4.04%, and the least was in age group of 16–20 years with 3 patients (3.03%. A total of 12 patients with ectopic pregnancy (41.38% had experience of abortion and 6 patients (20.69% each in groups of patients with ectopic pregnancy who used family planning, in those who used family planning as well as ectopic pregnancy patients with history of surgery. There were 2 patients (6.90% of the group of patients ectopic pregnancy who had history of surgery and history of abortion. The incidence rate of ectopic pregnancy was 4.73%, mostly in the second gravidity (34.34%, whereas the nulliparous have the highest prevalence of 39.39%. Acquired risk factors, i.e. history of operations was 10.34%, patients with family planning 20.69%, patients with history of abortion 41.38%, patients with history of abortion and operation 6.90% patients with family and history of abortion was 20.69%.

  10. Analysis of Socio-Economic Factors Influencing Farmers' Adoption ...

    African Journals Online (AJOL)

    Analysis of Socio-Economic Factors Influencing Farmers' Adoption of Rice ... Farming experience, household size, farm size and extension contact ... gender, market availability, education, extension contact, labour availability and farm size.

  11. Exploring Technostress: Results of a Large Sample Factor Analysis

    Directory of Open Access Journals (Sweden)

    Steponas Jonušauskas

    2016-06-01

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

  12. Risk Factor Analysis for Oral Precancer among Slum Dwellers in ...

    African Journals Online (AJOL)

    Rajasthan Dental College, Jaipur, Rajasthan, 1Dental Wing, All India Institute of Medical Sciences (AIIMS), Bhopal,. 4Department of Public ... Keywords: Oral cancer, Risk factor analysis, Slum dwellers. Access this .... hygiene aid used in India.

  13. Meta analysis of risk factors for colorectal cancer

    Institute of Scientific and Technical Information of China (English)

    Kun Chen; Jiong-Liang Qiu; Yang Zhang; Yu-Wan Zhao

    2003-01-01

    AIM: To study the risk factors for colorectal cancer in China.METHODS: A meta-analysis of the risk factors of colorectal cancer was conducted for 14 case-control studies, and reviewed 14 reports within 13 years which included 5034cases and 5205 controls. Dersimonian and Laird random effective models were used to process the results.RESULTS: Meta analysis of the 14 studies demonstrated that proper physical activites and dietary fibers were protective factors (pooled OR<0.8), while fecal mucohemorrhage,chronic diarrhea and polyposis were highly associated with colorectal cancer (all pooled OR>4). The stratified results showed that different OR values of some factors were due to geographic factors or different resourses.CONCLUSION: Risks of colorectal cancer are significantly associated with the histories of intestinal diseases or relative symptoms, high lipid diet, emotional trauma and family history of cancers. The suitable physical activities and dietary fibers are protective factors.

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

    Science.gov (United States)

    Rahmawati, Sela; Suprijadi, Jadi; Zulhanif

    2017-03-01

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

  15. The Pain Behaviour Checklist: factor analysis and validation.

    Science.gov (United States)

    Anciano, D

    1986-11-01

    A factor analysis was performed on Philips & Hunter's (1981) Pain Behaviour Checklist for headache sufferers. Three intuitively meaningful factors emerged. All were similarly associated with overall intensity; pain severity does not determine type of pain behaviour. Differences in pain behaviour emerged between migraine and tension headache groups.

  16. Determining Dimensionality of Exercise Readiness Using Exploratory Factor Analysis

    Directory of Open Access Journals (Sweden)

    Kelley Strohacker, Rebecca A. Zakrajsek

    2016-06-01

    Full Text Available Assessment of “exercise readiness” is a central component to the flexible non-linear periodization (FNLP method of organizing training workloads, but the underlying factor structure of this construct has not been empirically determined. The purpose of this study was to assess construct dimensionality of exercise readiness using exploratory factor analysis. The result of which serve as initial steps of developing a brief measure of exercise readiness. Participants consisted of students recruited from undergraduate Kinesiology courses at a racially diverse, southern University. Independent, anonymous online survey data were collected across three stages: 1 generation of item pool (n = 290, 2 assessment of face validity and refinement of item pool (n = 168, and 3 exploratory factor analysis (n = 684. A principal axis factor analysis was conducted with 41 items using oblique rotation (promax. Four statistically significant factors, as determined through parallel analysis, explained 61.5% of the variance in exercise readiness. Factor 1 contained items that represented vitality (e.g., lively, revived. Factor 2 items related to physical fatigue (e.g. tired, drained. Factors 3 and 4 were descriptive of, discomfort (e.g. pain, sick and health (i.e. healthy, fit, respectively. This inductive approach indicates that exercise readiness is comprised of four dimensions: vitality, physical fatigue, discomfort, and health. This finding supports readiness assessment techniques currently recommended for practitioners according to the FNLP model. These results serve as a theoretical foundation upon which to further develop and refine a brief survey instrument to measure exercise readiness.

  17. 48 CFR 2115.404-71 - Profit analysis factors.

    Science.gov (United States)

    2010-10-01

    ... account in assigning a plus weight. (5) Cost control. This factor is based on the Contractor's previously... TYPES CONTRACTING BY NEGOTIATION Contract Pricing 2115.404-71 Profit analysis factors. (a) The OPM... receive a plus weight, and poor performance or failure to comply with contract terms and conditions a zero...

  18. Analysis on Family Factor in Construction of New Socialist Countryside

    Institute of Scientific and Technical Information of China (English)

    2012-01-01

    This paper analyzes the family factor in the construction of new socialist countryside. It is believed that the family plays both the positive role and negative role in new socialist countryside construction. Based on this analysis,it puts forward corresponding countermeasures,including bringing into play the effect of family in promoting production and carrying forward excellent factors of family culture.

  19. Exploratory Tobit factor analysis for multivariate censored data

    NARCIS (Netherlands)

    Kamakura, WA; Wedel, M

    2001-01-01

    We propose Multivariate Tobit models with a factor structure on the covariance matrix. Such models are particularly useful in the exploratory analysis of multivariate censored data and the identification of latent variables from behavioral data. The factor structure provides a parsimonious

  20. Connectivism in Postsecondary Online Courses: An Exploratory Factor Analysis

    Science.gov (United States)

    Hogg, Nanette; Lomicky, Carol S.

    2012-01-01

    This study explores 465 postsecondary students' experiences in online classes through the lens of connectivism. Downes' 4 properties of connectivism (diversity, autonomy, interactivity, and openness) were used as the study design. An exploratory factor analysis was performed. This study found a 4-factor solution. Subjects indicated that autonomy…

  1. Confirmatory Factor Analysis of the Career Factors Inventory on a Community College Sample

    Science.gov (United States)

    Simon, Merril A.; Tovar, Esau

    2004-01-01

    A confirmatory factor analysis was conducted using AMOS 4.0 to validate the 21-item Career Factors Inventory on a community college student sample. The multidimensional inventory assesses types and levels of career indecision antecedents. The sample consisted of 512 ethnically diverse freshmen students; 46% were men and 54% were women.…

  2. Conditioning Analysis of Incomplete Cholesky Factorizations with Orthogonal Dropping

    Energy Technology Data Exchange (ETDEWEB)

    Napov, Artem [Free Univ. of Brussels (Belgium)

    2013-08-01

    The analysis of preconditioners based on incomplete Cholesky factorization in which the neglected (dropped) components are orthogonal to the approximations being kept is presented. General estimate for the condition number of the preconditioned system is given which only depends on the accuracy of individual approximations. The estimate is further improved if, for instance, only the newly computed rows of the factor are modified during each approximation step. In this latter case it is further shown to be sharp. The analysis is illustrated with some existing factorizations in the context of discretized elliptic partial differential equations.

  3. Conditioning Analysis of Incomplete Cholesky Factorizations with Orthogonal Dropping

    Energy Technology Data Exchange (ETDEWEB)

    Napov, Artem [Free Univ. of Brussels (Belgium)

    2013-08-01

    The analysis of preconditioners based on incomplete Cholesky factorization in which the neglected (dropped) components are orthogonal to the approximations being kept is presented. General estimate for the condition number of the preconditioned system is given which only depends on the accuracy of individual approximations. The estimate is further improved if, for instance, only the newly computed rows of the factor are modified during each approximation step. In this latter case it is further shown to be sharp. The analysis is illustrated with some existing factorizations in the context of discretized elliptic partial differential equations.

  4. Risk Factors Analysis on Traumatic Brain Injury Prognosis

    Institute of Scientific and Technical Information of China (English)

    Xiao-dong Qu; Resha Shrestha; Mao-de Wang

    2011-01-01

    To investigate the independent risk factors of traumatic brain injury (TBI) prognosis.Methods A retrospective analysis was performed in 885 hospitalized TEl patients from January 1,2003 to January 1, 2010 in the First Affiliated Hospital of Medical College of Xi' an Jiaotong University. Single-factor and logistic regression analysis were conducted to evaluate the association of different variables with TBI outcome.Results The single-factor analysis revealed significant association between several variables and TEl outcome, including age (P=0.044 for the age group 40-60, P<0.001 for the age group ≥60), complications (P<0.001), cerebrospinal fluid leakage (P<0.001), Glasgow Coma Scale (GCS) (P<0.001), pupillary light reflex (P<0.001), shock (P<0.001), associated extra-cranial lesions (P=0.01), subdural hematoma (P<0.001), cerebral contusion (P<0.001), diffuse axonal injury (P<0.001), and subarachnoid hemorrhage (P<0.001), suggesting the influence of those factors on the prognosis of TBI. Furthermore, logistic regression analysis identified age, GCS score, pupillary light reflex, subdural hematoma, and subarachnoid hemorrhage as independent risk factors of TEl prognosis.Conclusion Age, GCS score, papillary light reflex, subdural hematoma, and subarachnoid hemorrhage may be risk factors influencing the prognosis of TEl. Paying attention to those factors might improve the outcome of TBI in clinical treatment.

  5. Analysis on total factor productivity of Chinese provincial economy

    Institute of Scientific and Technical Information of China (English)

    GUO Qingwang; ZHAO Zhiyun; JIA Junxue

    2006-01-01

    This paper applies the nonparametric DEA-Malmquist index approach to estimate total factor productivity growth,efficiency change and the rate of technological progress from 1979 to 2003.This is done to conduct analysis on the total factor productivity of China's provincial economy.Analysis on the evolution of distribution dynamics of relative labor productivity,relative total factor productivity,relative efficiency and relative technological progress is done by using kernel density estimation flor the period from 1979 to 2003 in 29 provinces of China.Our analysis indicates that disparities of provincial economic growth are large and have been increasing owing to the relatively large and increasing disparities of total factor productivity growth especially the rate of technological progress.

  6. Analysis of related risk factors for pancreatic fistula after pancreaticoduodenectomy

    Institute of Scientific and Technical Information of China (English)

    Qi-Song Yu; He-Chao Huang; Feng Ding; Xin-Bo Wang

    2016-01-01

    Objective:To explore the related risk factors for pancreatic fistula after pancreaticoduodenectomy to provide a theoretical evidence for effectively preventing the occurrence of pancreatic fistula.Methods:A total of 100 patients who were admitted in our hospital from January, 2012 to January, 2015 and had performed pancreaticoduodenectomy were included in the study. The related risk factors for developing pancreatic fistula were collected for single factor and Logistic multi-factor analysis.Results:Among the included patients, 16 had pancreatic fistula, and the total occurrence rate was 16% (16/100). The single-factor analysis showed that the upper abdominal operation history, preoperative bilirubin, pancreatic texture, pancreatic duct diameter, intraoperative amount of bleeding, postoperative hemoglobin, and application of somatostatin after operation were the risk factors for developing pancreatic fistula (P<0.05). The multi-factor analysis showed that the upper abdominal operation history, the soft pancreatic texture, small pancreatic duct diameter, and low postoperative hemoglobin were the dependent risk factors for developing pancreatic fistula (OR=4.162, 6.104, 5.613, 4.034,P<0.05).Conclusions:The occurrence of pancreatic fistula after pancreaticoduodenectomy is closely associated with the upper abdominal operation history, the soft pancreatic texture, small pancreatic duct diameter, and low postoperative hemoglobin; therefore, effective measures should be taken to reduce the occurrence of pancreatic fistula according to the patients’own conditions.

  7. Environmental Performance in Countries Worldwide: Determinant Factors and Multivariate Analysis

    Directory of Open Access Journals (Sweden)

    Isabel Gallego-Alvarez

    2014-11-01

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

  8. Determining Dimensionality of Exercise Readiness Using Exploratory Factor Analysis.

    Science.gov (United States)

    Strohacker, Kelley; Zakrajsek, Rebecca A

    2016-06-01

    Assessment of "exercise readiness" is a central component to the flexible non-linear periodization (FNLP) method of organizing training workloads, but the underlying factor structure of this construct has not been empirically determined. The purpose of this study was to assess construct dimensionality of exercise readiness using exploratory factor analysis. The result of which serve as initial steps of developing a brief measure of exercise readiness. Participants consisted of students recruited from undergraduate Kinesiology courses at a racially diverse, southern University. Independent, anonymous online survey data were collected across three stages: 1) generation of item pool (n = 290), 2) assessment of face validity and refinement of item pool (n = 168), and 3) exploratory factor analysis (n = 684). A principal axis factor analysis was conducted with 41 items using oblique rotation (promax). Four statistically significant factors, as determined through parallel analysis, explained 61.5% of the variance in exercise readiness. Factor 1 contained items that represented vitality (e.g., lively, revived). Factor 2 items related to physical fatigue (e.g. tired, drained). Factors 3 and 4 were descriptive of, discomfort (e.g. pain, sick) and health (i.e. healthy, fit), respectively. This inductive approach indicates that exercise readiness is comprised of four dimensions: vitality, physical fatigue, discomfort, and health. This finding supports readiness assessment techniques currently recommended for practitioners according to the FNLP model. These results serve as a theoretical foundation upon which to further develop and refine a brief survey instrument to measure exercise readiness. Key pointsAssessment of exercise readiness is a key component in implementing an exercise program based on flexible nonlinear periodization, but the dimensionality of this concept has not been empirically determined.Based on a series of surveys and a robust exploratory factor analysis

  9. ANALYSIS OF RISK FACTORS IN 3901 PATIENTS WITH STROKE

    Institute of Scientific and Technical Information of China (English)

    Xin-Feng Liu; Guy van Melle; Julien Bogousslavsky

    2005-01-01

    Objective To estimate the frequency of various risk factors for overall stroke and to identify risk factors for cerebral infarction (CI) versus intracerebral hemorrhage (ICH) in a large hospital-based stroke registry.Methods Data from a total of 3901 patients, consisting of 3525 patients with CI and 376 patients with ICH were prospectively coded and entered into a computerized data bank.Results Hypertension and smoking were the most prominent factors affecting overall stroke followed by mild internal carotid artery stenosis (< 50%), hypercholesterolemia, transient ischemic attacks (TIAs), diabetes mellitus, and cardiac ischemia. Univariate analysis showed that factors in male significantly associated with CI versus ICH were old age, a family history of stroke, and intermittent claudication; whereas in female the factors were oral contraception and migraine. By multivariate analysis, in all patients, the factors significantly associated with CI as opposed to ICH were smoking, hypercholesterolemia, migraine, TIAs, atrial fibrillation, structural heart disease, and arterial disease. Hypertension was the only significant factor related with ICH versus CI.Conclusions The factors for ischemic and hemorrhagic stroke are not exactly the same. Cardiac and arterial disease are the most powerful factors associated with CI rather than ICH.

  10. Analysis of effect factors-based stochastic network planning model

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Looking at all the indeterminate factors as a whole and regarding activity durations as independent random variables,the traditional stochastic network planning models ignore the inevitable relationship and dependence among activity durations when more than one activity is possibly affected by the same indeterminate factors.On this basis of analysis of indeterminate effect factors of durations,the effect factors-based stochastic network planning (EFBSNP) model is proposed,which emphasizes on the effects of not only logistic and organizational relationships,but also the dependent relationships,due to indeterminate factors among activity durations on the project period.By virtue of indeterminate factor analysis the model extracts and describes the quantitatively indeterminate effect factors,and then takes into account the indeterminate factors effect schedule by using the Monte Carlo simulation technique.The method is flexible enough to deal with effect factors and is coincident with practice.A software has been developed to simplify the model-based calculation,in VisualStudio.NET language.Finally,a case study is included to demonstrate the applicability of the proposed model and comparison is made with some advantages over the existing models.

  11. Identification of noise in linear data sets by factor analysis

    Energy Technology Data Exchange (ETDEWEB)

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

    1981-01-01

    The approach to classical factor analysis described in this paper, i.e. doing the analysis for varying numbers of factors without prior assumptions to the number of factors, prevents one from getting eroneous results by inherent computer code assumptions. Identification of a factor containing most of the variance of one variable with little variance of other variables, pinpoints a possible difficulty in the data, if the singularity has no obvious physical significance. Examination of the factor scores will determine whether the problem is isolated to a few samples or over all the samples. Having this information, one may then go back to the raw data and take the appropriate corrective action. Classical factor analysis has the ability to identify several types of errors in data after it has been generated. It is then ideally suited for scanning large data sets. The ease of the identification technique makes it a beneficial tool to use before reduction and analysis of large data sets and should, in the long run, save time and effort.

  12. Biological risk factors for suicidal behaviors: a meta-analysis.

    Science.gov (United States)

    Chang, B P; Franklin, J C; Ribeiro, J D; Fox, K R; Bentley, K H; Kleiman, E M; Nock, M K

    2016-09-13

    Prior studies have proposed a wide range of potential biological risk factors for future suicidal behaviors. Although strong evidence exists for biological correlates of suicidal behaviors, it remains unclear if these correlates are also risk factors for suicidal behaviors. We performed a meta-analysis to integrate the existing literature on biological risk factors for suicidal behaviors and to determine their statistical significance. We conducted a systematic search of PubMed, PsycInfo and Google Scholar for studies that used a biological factor to predict either suicide attempt or death by suicide. Inclusion criteria included studies with at least one longitudinal analysis using a biological factor to predict either of these outcomes in any population through 2015. From an initial screen of 2541 studies we identified 94 cases. Random effects models were used for both meta-analyses and meta-regression. The combined effect of biological factors produced statistically significant but relatively weak prediction of suicide attempts (weighted mean odds ratio (wOR)=1.41; CI: 1.09-1.81) and suicide death (wOR=1.28; CI: 1.13-1.45). After accounting for publication bias, prediction was nonsignificant for both suicide attempts and suicide death. Only two factors remained significant after accounting for publication bias-cytokines (wOR=2.87; CI: 1.40-5.93) and low levels of fish oil nutrients (wOR=1.09; CI: 1.01-1.19). Our meta-analysis revealed that currently known biological factors are weak predictors of future suicidal behaviors. This conclusion should be interpreted within the context of the limitations of the existing literature, including long follow-up intervals and a lack of tests of interactions with other risk factors. Future studies addressing these limitations may more effectively test for potential biological risk factors.

  13. Retinopathy risk factors in type II diabetic patients using factor analysis and discriminant analysis

    OpenAIRE

    Tazhibi, Mahdi; Sarrafzade, Sheida; Amini, Masoud

    2014-01-01

    Introduction: Diabetes is one of the most common chronic diseases in the world. Incidence and prevalence of diabetes are increasing in developing countries as well as in Iran. Retinopathy is the most common chronic disorder in diabetic patients. Materials and Methods: In this study, we used the information of diabetic patients’ reports that refer to endocrine and metabolism research center of Isfahan University of Medical Sciences to determine diabetic retinopathy risk factors. We used factor...

  14. Identification of noise in linear data sets by factor analysis

    Energy Technology Data Exchange (ETDEWEB)

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

    1982-01-01

    With the use of atomic and nuclear methods to analyze samples for a multitude of elements, very large data sets have been generated. Due to the ease of obtaining these results with computerized systems, the elemental data acquired are not always as thoroughly checked as they should be leading to some, if not many, bad data points. It is advantageous to have some feeling for the trouble spots in a data set before it is used for further studies. A technique which has the ability to identify bad data points, after the data has been generated, is classical factor analysis. The ability of classical factor analysis to identify two different types of data errors make it ideally suited for scanning large data sets. Since the results yielded by factor analysis indicate correlations between parameters, one must know something about the nature of the data set and the analytical techniques used to obtain it to confidentially isolate errors.

  15. Personality and coping traits: A joint factor analysis.

    Science.gov (United States)

    Ferguson, Eamonn

    2001-11-01

    OBJECTIVES: The main objective of this paper is to explore the structural similarities between Eysenck's model of personality and the dimensions of the dispositional COPE. Costa et al. {Costa P., Somerfield, M., & McCrae, R. (1996). Personality and coping: A reconceptualisation. In (pp. 44-61) Handbook of coping: Theory, research and applications. New York: Wiley} suggest that personality and coping behaviour are part of a continuum based on adaptation. If this is the case, there should be structural similarities between measures of personality and coping behaviour. This is tested using a joint factor analysis of personality and coping measures. DESIGN: Cross-sectional survey. METHODS: The EPQ-R and the dispositional COPE were administered to 154 participants, and the data were analysed using joint factor analysis and bivariate associations. RESULTS: The joint factor analysis indicated that these data were best explained by a four-factor model. One factor was primarily unrelated to personality. There was a COPE-neurotic-introvert factor (NI-COPE) containing coping behaviours such as denial, a COPE-extroversion (E-COPE) factor containing behaviours such as seeking social support and a COPE-psychoticism factor (P-COPE) containing behaviours such as alcohol use. This factor pattern, especially for NI- and E-COPE, was interpreted in terms of Gray's model of personality {Gray, J. A. (1987) The psychology of fear and stress. Cambridge: Cambridge University Press}. NI-, E-, and P-COPE were shown to be related, in a theoretically consistent manner, to perceived coping success and perceived coping functions. CONCLUSIONS: The results indicate that there are indeed conceptual links between models of personality and coping. It is argued that future research should focus on identifying coping 'trait complexes'. Implications for practice are discussed.

  16. Emotional experiences and motivating factors associated with fingerprint analysis.

    Science.gov (United States)

    Charlton, David; Fraser-Mackenzie, Peter A F; Dror, Itiel E

    2010-03-01

    In this study, we investigated the emotional and motivational factors involved in fingerprint analysis in day-to-day routine case work and in significant and harrowing criminal investigations. Thematic analysis was performed on interviews with 13 experienced fingerprint examiners from a variety of law enforcement agencies. The data revealed factors relating to job satisfaction and the use of skill. Individual satisfaction related to catching criminals was observed; this was most notable in solving high profile, serious, or long-running cases. There were positive emotional effects associated with matching fingerprints and apparent fear of making errors. Finally, we found evidence for a need of cognitive closure in fingerprint examiner decision-making.

  17. Unascertained Factor Method of Dynamic Characteristic Analysis for Antenna Structures

    Institute of Scientific and Technical Information of China (English)

    ZHU Zeng-qing; LIANG Zhen-tao; CHEN Jian-jun

    2008-01-01

    The dynamic characteristic analysis model of antenna structures is built, in which the structural physical parameters and geometrical dimensions are all considered as unascertained variables, And a structure dynamic characteristic analysis method based on the unascertained factor method is given. The computational expression of structural characteristic is developed by the mathematics expression of unascertained factor and the principles of unascertained rational numbers arithmetic. An example is given, in which the possible values and confidence degrees of the unascertained structure characteristics are obtained. The calculated results show that the method is feasible and effective.

  18. Using Factor Analysis to Identify Topic Preferences Within MBA Courses

    Directory of Open Access Journals (Sweden)

    Earl Chrysler

    2003-02-01

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

  19. Confirmatory Factor Analysis of the Procrastination Assessment Scale for Students

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    Ronald D. Yockey

    2015-10-01

    Full Text Available The relative fit of one- and two-factor models of the Procrastination Assessment Scale for Students (PASS was investigated using confirmatory factor analysis on an ethnically diverse sample of 345 participants. The results indicated that although the two-factor model provided better fit to the data than the one-factor model, neither model provided optimal fit. However, a two-factor model which accounted for common item theme pairs used by Solomon and Rothblum in the creation of the scale provided good fit to the data. In addition, a significant difference by ethnicity was also found on the fear of failure subscale of the PASS, with Whites having significantly lower scores than Asian Americans or Latino/as. Implications of the results are discussed and recommendations made for future work with the scale.

  20. Analysis of Factors Influencing Farmers’ Identification of Entrepreneurial Opportunity

    Institute of Scientific and Technical Information of China (English)

    Jing; GAO; Fang; YANG

    2013-01-01

    Based on the survey data of entrepreneurship concerning farmers in China,this article uses the multivariate adjustment regression analysis method,to analyze the factors influencing farmers’ identification of entrepreneurial opportunity and the mechanism. The results show that demographic characteristics are still an important factor influencing farmers’ identification of entrepreneurial opportunity,but the extent of its influence is weaker than entrepreneurs’ trait. The new trait theory is verified in farmers’ entrepreneurship opportunity behavior; entrepreneurship environment is becoming an important factor influencing entrepreneurial opportunity identification,whose regulation effect on entrepreneurs’ social network and previous experience is stronger than the regulation effect on entrepreneurs’ psychological trait.

  1. A factor analysis to find critical success factors in retail brand

    Directory of Open Access Journals (Sweden)

    Naser Azad

    2013-03-01

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

  2. Ranking insurance firms using AHP and Factor Analysis

    Directory of Open Access Journals (Sweden)

    Mohammad Khodaei Valahzaghard

    2013-03-01

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

  3. Workplace Innovation: Exploratory and Confirmatory Factor Analysis for Construct Validation

    Directory of Open Access Journals (Sweden)

    Wipulanusat Warit

    2017-06-01

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

  4. Analysis of plug-in hybrid electric vehicle utility factors

    Science.gov (United States)

    Bradley, Thomas H.; Quinn, Casey W.

    Plug-in hybrid electric vehicles (PHEVs) are hybrid electric vehicles that can be fueled from both conventional liquid fuels and grid electricity. To represent the total contribution of both of these fuels to the operation, energy use, and environmental impacts of PHEVs, researchers have developed the concept of the utility factor. As standardized in documents such as SAE J1711 and SAE J2841, the utility factor represents the proportion of vehicle distance travelled that can be allocated to a vehicle test condition so as to represent the real-world driving habits of a vehicle fleet. These standards must be used with care so that the results are understood within the context of the assumptions implicit in the standardized utility factors. This study analyzes and derives alternatives to the standard utility factors from the 2001 National Highway Transportation Survey, so as to understand the sensitivity of PHEV performance to assumptions regarding charging frequency, vehicle characteristics, driver characteristics, and means of defining the utility factor. Through analysis of these alternative utility factors, this study identifies areas where analysis, design, and policy development for PHEVs can be improved by alternative utility factor calculations.

  5. Bone dynamic study. Evaluation for factor analysis of hip joint

    Energy Technology Data Exchange (ETDEWEB)

    Nakajima, Kotaro; Toyama, Hinako; Ishikawa, Nobuyoshi; Hatakeyama, Rokuro; Akisada, Masayoshi; Miyagawa, Shunpei

    1989-02-01

    Factor analysis was applied to dynamic study of Tc-99m MDP for the evaluation of hip joint disorders. Fifteen patients were examined; eight were normal, six was osteoarthritis in which one accompanied synovitis was included, and one was aseptic necrosis on the head of the femur. In normals, according to the Tc-99m MDP kinetics, three factor images and time-activity curves were obtained which were named as blood vessel, soft tissue, and bone factor images and curves. In the patient with osteoarthritis, increased accumulation of the hip joint was shown in bone factor image only. But in one patient, who took osteoarthritis with synovitis, marked accumulations of the Tc-99m MDP appeared not only on the bone factor image but also on the soft tissue. Operation revealed thickening synovial tissue around the hip joint, caused by inflammatory process. In follow-up studies of the patient with aseptic necrosis on the head of the left femur, exessive accumulations, which were seemed in his left hip joint on both bone and soft tissue factor images at first, were decreased respondently to the treatment of this lesion. In conclusion, the factor analysis was useful for differential diagnosis of the hip joint disorders and observation of the clinical course of the hip joint disorders.

  6. A Brief History of the Philosophical Foundations of Exploratory Factor Analysis.

    Science.gov (United States)

    Mulaik, Stanley A.

    1987-01-01

    Exploratory factor analysis derives its key ideas from many sources, including Aristotle, Francis Bacon, Descartes, Pearson and Yule, and Kant. The conclusions of exploratory factor analysis are never complete without subsequent confirmatory factor analysis. (Author/GDC)

  7. Heterogeneity of Capital Stocks in Japan: Classification by Factor Analysis

    Directory of Open Access Journals (Sweden)

    Konomi Tonogi

    2014-04-01

    Full Text Available This paper examines the heterogeneity of capital stocks using financial statement data of publicly listed Japanese firms. We conduct factor analysis on investment rates among various capital goods and estimate factor loadings of each as its reactions to common factors like total factor productivity (TFP shocks. Then we estimate the uniqueness for each investment rate, which is the percentage of its variance that is not explained by the common factors. If the estimated factor loadings are similar between some of the heterogeneous capital goods, it may well imply that the adjustment cost structure of these investments is also similar. Further, if some of the estimated values of uniqueness are small, it suggests that certain theoretical models may track the dynamics of the investment rates well. Our estimation results show that Building and Structure have similar factor loadings as do Machinery & Equipment, Vehicles & Delivery Equipment, and Tools, Furniture, & Fixture. This suggests that we could remedy the Curse of Dimensionality by bundling the investments that have similar factor loadings together and that identifying the functional structures of each group of capital goods can greatly improve the performance of empirical investment equations.

  8. Landslides geotechnical analysis. Qualitative assessment by valuation factors

    Science.gov (United States)

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

    2012-04-01

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

  9. Exploratory factor analysis of the Brazilian OHIP for edentulous subjects.

    Science.gov (United States)

    Souza, R F; Leles, C R; Guyatt, G H; Pontes, C B; Della Vecchia, M P; Neves, F D

    2010-03-01

    The use of seven domains for the Oral Health Impact Profile (OHIP)-EDENT was not supported for its Brazilian version, making data interpretation in clinical settings difficult. Thus, the aim of this study was to assess patients' responses for the translated OHIP-EDENT in a group of edentulous subjects and to develop factor scales for application in future studies. Data from 103 conventional and implant-retained complete denture wearers (36 men, mean age of 69.1 +/- 10.3 years) were assessed using the Brazilian version of the OHIP-EDENT. Oral health-related quality of life domains were identified by factor analysis using principal component analysis as the extraction method, followed by varimax rotation. Factor analysis identified four factors that accounted for 63% of the 19 items total variance, named masticatory discomfort and disability (four items), psychological discomfort and disability (five items), social disability (five items) and oral pain and discomfort (five items). Four factors/domains of the Brazilian OHIP-EDENT version represent patient-important aspects of oral health-related quality of life.

  10. Using Confirmatory Factor Analysis for Construct Validation: An Empirical Review

    Science.gov (United States)

    DiStefano, Christine; Hess, Brian

    2005-01-01

    This study investigated the psychological assessment literature to determine what applied researchers are using and reporting from confirmatory factor analysis (CFA) studies for evidence of construct validation. One hundred and one articles published in four major psychological assessment journals between 1990 and 2002 were systematically…

  11. Modular Open-Source Software for Item Factor Analysis

    Science.gov (United States)

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

    2015-01-01

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

  12. Modular Open-Source Software for Item Factor Analysis

    Science.gov (United States)

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

    2015-01-01

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

  13. A Factor Analysis of Barriers to Effective Listening.

    Science.gov (United States)

    Golen, Steven

    1990-01-01

    Conducts a factor analysis to determine listening barriers perceived as most frequently affecting the listening effectiveness among business college students. Finds the presence of six listening barriers, with the barrier "listen primarily for details or facts" as the most frequently encountered barrier perceived by students. (MM)

  14. A Comparison of Imputation Methods for Bayesian Factor Analysis Models

    Science.gov (United States)

    Merkle, Edgar C.

    2011-01-01

    Imputation methods are popular for the handling of missing data in psychology. The methods generally consist of predicting missing data based on observed data, yielding a complete data set that is amiable to standard statistical analyses. In the context of Bayesian factor analysis, this article compares imputation under an unrestricted…

  15. The Effects of Overextraction on Factor and Component Analysis.

    Science.gov (United States)

    Fava, J L; Velicer, W F

    1992-07-01

    The effects of overextracting factors and components within and between the methods of maximum likelihood factor analysis (MLFA) and principal component analysis (PCA) were examined. Computer-simulated data sets were generated to represent a range of factor and component patterns. Saturation (aij = .8, .6 & .4), sample size (N = 75, 150,225,450), and variable-to-component (factor) ratio (p:m = 12:1,6:1, & 4:1) were conditions manipulated. In Study 1, scores based on the incorrect patterns were correlated with correct scores within each method after each overextraction. In Study 2, scores were correlated between the methods of PCAand MLFA after each overextraction. Overextraction had a negative effect, but scores based on strong component and factor patterns displayed robustness to the effects of overextraction. Low item saturation and low sample size resulted in degraded score reproduction. Degradation was strongest for patterns that combined low saturation and low sample size. Component and factor scores were highly correlated even at maximal levels of overextraction. Dissimilarity between score methods was the greatest in conditions that combined low saturation and low sample size. Some guidelines for researchers concerning the effects of overextraction are noted, as well as some cautions in the interpretation of results.

  16. Exploratory factor analysis of the Oral Health Impact Profile.

    Science.gov (United States)

    John, M T; Reissmann, D R; Feuerstahler, L; Waller, N; Baba, K; Larsson, P; Celebić, A; Szabo, G; Rener-Sitar, K

    2014-09-01

    Although oral health-related quality of life (OHRQoL) as measured by the Oral Health Impact Profile (OHIP) is thought to be multidimensional, the nature of these dimensions is not known. The aim of this report was to explore the dimensionality of the OHIP using the Dimensions of OHRQoL (DOQ) Project, an international study of general population subjects and prosthodontic patients. Using the project's Learning Sample (n = 5173), we conducted an exploratory factor analysis on the 46 OHIP items not specifically referring to dentures for 5146 subjects with sufficiently complete data. The first eigenvalue (27·0) of the polychoric correlation matrix was more than ten times larger than the second eigenvalue (2·6), suggesting the presence of a dominant, higher-order general factor. Follow-up analyses with Horn's parallel analysis revealed a viable second-order, four-factor solution. An oblique rotation of this solution revealed four highly correlated factors that we named Oral Function, Oro-facial Pain, Oro-facial Appearance and Psychosocial Impact. These four dimensions and the strong general factor are two viable hypotheses for the factor structure of the OHIP.

  17. Evaluating Exploratory Factor Analysis: Which Initial-Extraction Techniques Provide the Best Factor Fidelity?

    Science.gov (United States)

    Buley, Jerry L.

    1995-01-01

    States that attacks by communication scholars have cast doubt on the validity of exploratory factor analysis (EFA). Tests EFA's ability to produce results that replicate known dimensions in a data set. Concludes that EFA should be viewed with cautious optimism and be evaluated according to the findings of this and similar studies. (PA)

  18. Factor analysis improves the selection of prescribing indicators

    DEFF Research Database (Denmark)

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

    2006-01-01

    OBJECTIVE: To test a method for improving the selection of indicators of general practitioners' prescribing. METHODS: We conducted a prescription database study including all 180 general practices in the County of Funen, Denmark, approximately 472,000 inhabitants. Principal factor analysis was used...... indicators directly quantifying choice of coxibs, indicators measuring expenditure per Defined Daily Dose, and indicators taking risk aspects into account, (2) "Frequent NSAID prescribing", comprising indicators quantifying prevalence or amount of NSAID prescribing, and (3) "Diverse NSAID choice", comprising...... appropriate and inappropriate prescribing, as revealed by the correlation of the indicators in the first factor. CONCLUSION: Correlation and factor analysis is a feasible method that assists the selection of indicators and gives better insight into prescribing patterns....

  19. Identifying influential factors of business process performance using dependency analysis

    Science.gov (United States)

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

    2011-02-01

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

  20. Developmental Coordination Disorder: Validation of a Qualitative Analysis Using Statistical Factor Analysis

    Directory of Open Access Journals (Sweden)

    Kathy Ahern

    2002-09-01

    Full Text Available This study investigates triangulation of the findings of a qualitative analysis by applying an exploratory factor analysis to themes identified in a phenomenological study. A questionnaire was developed from a phenomenological analysis of parents' experiences of parenting a child with Developmental Coordination Disorder (DCD. The questionnaire was administered to 114 parents of DCD children and data were analyzed using an exploratory factor analysis. The extracted factors provided support for the validity of the original qualitative analysis, and a commentary on the validity of the process is provided. The emerging description is of the compromises that were necessary to translate qualitative themes into statistical factors, and of the ways in which the statistical analysis suggests further qualitative study.

  1. Analysis of Recurrence Factor of Postoperative Papillary Thyroid Cancer

    Directory of Open Access Journals (Sweden)

    XING Lan-lan;CHEN Song;LI Ya-ming

    2014-02-01

    Full Text Available To investigate the factors that influences the recurrence of papillary thyroid cancer,69 patients with papillary thyroid cancer since January 1, 2011 to march 30, 2013 were analyzed respectively. They meet the inclusion criteria and complete clinical data, 18 males and 51 females,average age: 40.17±12.97.Thyroid ultrasonography, thyroid function test, thyroglobulin and antibody measurement were performed on all patients and thyroid function were checked three or more times on the premise of continuously levothyroxine. Single factor analysis were performed using SPSS17.0 in these respects including patients' gender, age, tumor size, type of opetation, the inhibition degree of TSH with taking levothyroxine postoperative and whether to perform 131I thyroid remnant ablation. Binary Logistic regression analysis were used for studying recurrence factors in multivariate analysis. The ROC curve were drawn, and then determine the threshold of TSH to evaluate tumor recurrence using Youden index method. Unvaried analysis showed that there was no statistically significance between papillary thyroid cancer recurrence and patients' age, surgical approach (P =0.373, P = 0.226,but were related to patient's gender, tumor size, postoperative TSH suppression degree and the removal of residual thyroid tissue postoperative(P= 0.031, P = 0.004, P = 0.000 01, P = 0.000 05. Males, large tumors, high postoperative TSH values and patients who didn't remove the residual thyroid tissue after surgery had higher recurrence rate. Logistic regression analysis showed that tumor size, postoperative TSH suppression degree and whether to remove the residual thyroid tissue were the influencing factors of tumor recurrence. The postoperative TSH supressive degree evaluation of critical point of tumor recurrence was determined by 0.223 5 mU/L using the Yueden index method. Large tumors, high postoperative TSH values,and no removal of the residual thyroid tissue had more influence

  2. Confirmatory factor analysis of the WAIS-IV/WMS-IV.

    Science.gov (United States)

    Holdnack, James A; Xiaobin Zhou; Larrabee, Glenn J; Millis, Scott R; Salthouse, Timothy A

    2011-06-01

    The Wechsler Adult Intelligence Scale-fourth edition (WAIS-IV) and the Wechsler Memory Scale-fourth edition (WMS-IV) were co-developed to be used individually or as a combined battery of tests. The independent factor structure of each of the tests has been identified; however, the combined factor structure has yet to be determined. Confirmatory factor analysis was applied to the WAIS-IV/WMS-IV Adult battery (i.e., age 16-69 years) co-norming sample (n = 900) to test 13 measurement models. The results indicated that two models fit the data equally well. One model is a seven-factor solution without a hierarchical general ability factor: Verbal Comprehension, Perceptual Reasoning, Processing Speed, Auditory Working Memory, Visual Working Memory, Auditory Memory, and Visual Memory. The second model is a five-factor model composed of Verbal Comprehension, Perceptual Reasoning, Processing Speed, Working Memory, and Memory with a hierarchical general ability factor. Interpretative implications for each model are discussed.

  3. An exploratory analysis of personality factors contributed to suicide attempts

    Directory of Open Access Journals (Sweden)

    P. N. Suresh Kumar

    2013-01-01

    Full Text Available Background: People who attempt suicide have certain individual predispositions, part of which is contributed by personality traits. Aims: The present study was conducted to identify the psycho-sociodemographic and personality related factors contributing to suicide attempts. Materials and Methods: 104 suicide attempters admitted in various departments and referred to the department of psychiatry of IQRAA Hospital formed the study sample. They were evaluated with a self designed socio-demographic proforma, Eysenck′s Personality Questionnaire Revised, Albert Einstein College of Medicine-Impulsivity Coping Scale, and Past Feelings and Acts of Violence Scale. Statistics Analysis: The data was initially analyzed by percentage of frequencies. Association between socio-demographic and selected psychological factors was analyzed using t-test and Chi-square test. Intercorrelation among psychological factors was calculated by Pearson′s correlation coefficient "r". Results and Conclusion: Factors such as young age, being married, nuclear family, feeling lonely and burden to family, inability to solve the problems of day to day life, and presence of psychiatric diagnosis and personality traits such as neuroticism, impulsivity, and violence were contributed to suicide attempt. A significant positive relationship between these factors was also identified. Findings of the present study call the attention of mental health professionals to identify these high risk factors in susceptible individuals and to modify these factors to prevent them from attempting suicide.

  4. Confirmatory factor analysis for the Eating Disorder Examination Questionnaire: Evidence supporting a three-factor model.

    Science.gov (United States)

    Barnes, Jennifer; Prescott, Tim; Muncer, Steven

    2012-12-01

    The purpose of this investigation was to compare the goodness-of-fit of a one factor model with the four factor model proposed by Fairburn (2008) and the three factor model proposed by Peterson and colleagues (2007) for the Eating Disorder Examination Questionnaire (EDE-Q 6.0) (Fairburn and Beglin, 1994). Using a cross-sectional design, the EDE-Q was completed by 569 adults recruited from universities and eating disorder charities in the UK. Confirmatory factor analysis (CFA) was carried out for both the student and non-student groups. CFA indicated that Peterson et al.'s (2007) three factor model was the best fit for both groups within the current data sample. Acceptable levels of internal reliability were observed and there was clear evidence for a hierarchical factor of eating disorder. The results of this study provide support for the three factor model of the EDE-Q suggested by Peterson and colleagues (2007) in that this model was appropriate for both the student and non-student sample populations. Copyright © 2012 Elsevier Ltd. All rights reserved.

  5. Replication Analysis in Exploratory Factor Analysis: What It Is and Why It Makes Your Analysis Better

    Directory of Open Access Journals (Sweden)

    Jason W. Osborne

    2012-11-01

    Full Text Available Exploratory Factor Analysis (EFA is a powerful and commonly-used tool for investigating the underlying variable structure of a psychometric instrument. However, there is much controversy in the social sciences with regard to the techniques used in EFA (Ford, MacCallum, & Tait, 1986; Henson & Roberts, 2006 and the reliability of the outcome. Simulations by Costello and Osborne (2005, for example, demonstrate how poorly some EFA analyses replicate, even with clear underlying factor structures and large samples. Thus, we argue that researchers should routinely examine the stability or volatility of their EFA solutions to gain more insight into the robustness of their solutions and insight into how to improve their instruments while still at the exploratory stage of development.

  6. Testing the number of required dimensions in exploratory factor analysis

    Directory of Open Access Journals (Sweden)

    Achim, Andr\\'e

    2017-01-01

    Full Text Available While maximum likelihood exploratory factor analysis (EFA provides a statistical test that $k$ dimensions are sufficient to account for the observed correlations among a set of variables, determining the required number of factors in least-squares based EFA has essentially relied on heuristic procedures. Two methods, Revised Parallel Analysis (R-PA and Comparison Data (CD, were recently proposed that generate surrogate data based on an increasing number of principal axis factors in order to compare their sequence of eigenvalues with that from the data. The latter should be unremarkable among the former if enough dimensions are included. While CD looks for a balance between efficiency and parsimony, R-PA strictly test that $k$ dimensions are sufficient by ranking the next eigenvalue, i.e. at rank $k+1$, of the actual data among those from the surrogate data. Importing two features of CD into R-PA defines four variants that are here collectively termed Next Eigenvalue Sufficiency Tests (NESTs. Simulations implementing 144 sets of parameters, including correlated factors and presence of a doublet factor, show that all four NESTs largely outperform CD, the standard Parallel Analysis, the Mean Average Partial method and even the maximum likelihood approach, in identifying the correct number of common factors. The recommended, most successful NEST variant is also the only one that never overestimates the correct number of dimensions beyond its nominal $\\alpha$ level. This variant is made available as R and MATLAB code as well as a complement incorporated in a Microsoft Excel file.

  7. Analysis of the determinative factors for energy efficiency

    Directory of Open Access Journals (Sweden)

    Antonio Vanderley Herrero Sola

    2007-10-01

    Full Text Available The aim of this paper is to study energy efficiency in productive sector. The main objective is to analyze determinative factors to Energy Efficiency, identifying how external forces influence those factors as weel as energy efficiency, in order to subsidize a future scenery planning in energy management. The result of this analysis, based on scientific works, case study in universities, research in companies, studies by Brazilian Federal Government and studies by specialists, shows that energy efficiency depends on: effectiveness governmental actions for the technological development; technological development; initiative by universities for technology transfer to the companies; the relationship between individuals and small companies to create a corporative structure.

  8. Performance analysis of parallel supernodal sparse LU factorization

    Energy Technology Data Exchange (ETDEWEB)

    Grigori, Laura; Li, Xiaoye S.

    2004-02-05

    We investigate performance characteristics for the LU factorization of large matrices with various sparsity patterns. We consider supernodal right-looking parallel factorization on a bi-dimensional grid of processors, making use of static pivoting. We develop a performance model and we validate it using the implementation in SuperLU-DIST, the real matrices and the IBM Power3 machine at NERSC. We use this model to obtain performance bounds on parallel computers, to perform scalability analysis and to identify performance bottlenecks. We also discuss the role of load balance and data distribution in this approach.

  9. Arabidopsis transcription factors: genome-wide comparative analysis among eukaryotes.

    Science.gov (United States)

    Riechmann, J L; Heard, J; Martin, G; Reuber, L; Jiang, C; Keddie, J; Adam, L; Pineda, O; Ratcliffe, O J; Samaha, R R; Creelman, R; Pilgrim, M; Broun, P; Zhang, J Z; Ghandehari, D; Sherman, B K; Yu, G

    2000-12-15

    The completion of the Arabidopsis thaliana genome sequence allows a comparative analysis of transcriptional regulators across the three eukaryotic kingdoms. Arabidopsis dedicates over 5% of its genome to code for more than 1500 transcription factors, about 45% of which are from families specific to plants. Arabidopsis transcription factors that belong to families common to all eukaryotes do not share significant similarity with those of the other kingdoms beyond the conserved DNA binding domains, many of which have been arranged in combinations specific to each lineage. The genome-wide comparison reveals the evolutionary generation of diversity in the regulation of transcription.

  10. Factor analysis and predictive validity of microcomputer-based tests

    Science.gov (United States)

    Kennedy, R. S.; Baltzley, D. R.; Turnage, J. J.; Jones, M. B.

    1989-01-01

    11 tests were selected from two microcomputer-based performance test batteries because previously these tests exhibited rapid stability (less than 10 min, of practice) and high retest reliability efficiencies (r greater than 0.707 for each 3 min. of testing). The battery was administered three times to each of 108 college students (48 men and 60 women) and a factor analysis was performed. Two of the three identified factors appear to be related to information processing ("encoding" and "throughput/decoding"), and the third named an "output/speed" factor. The spatial, memory, and verbal tests loaded on the "encoding" factor and included Grammatical Reasoning, Pattern Comparison, Continuous Recall, and Matrix Rotation. The "throughput/decoding" tests included perceptual/numerical tests like Math Processing, Code Substitution, and Pattern Comparison. The output speed factor was identified by Tapping and Reaction Time tests. The Wonderlic Personnel Test was group administered before the first and after the last administration of the performance tests. The multiple Rs in the total sample between combined Wonderlic as a criterion and less than 5 min. of microcomputer testing on Grammatical Reasoning and Math Processing as predictors ranged between 0.41 and 0.52 on the three test administrations. Based on these results, the authors recommend a core battery which, if time permits, would consist of two tests from each factor. Such a battery is now known to permit stable, reliable, and efficient assessment.

  11. Human Factors in Financial Trading: An Analysis of Trading Incidents.

    Science.gov (United States)

    Leaver, Meghan; Reader, Tom W

    2016-09-01

    This study tests the reliability of a system (FINANS) to collect and analyze incident reports in the financial trading domain and is guided by a human factors taxonomy used to describe error in the trading domain. Research indicates the utility of applying human factors theory to understand error in finance, yet empirical research is lacking. We report on the development of the first system for capturing and analyzing human factors-related issues in operational trading incidents. In the first study, 20 incidents are analyzed by an expert user group against a referent standard to establish the reliability of FINANS. In the second study, 750 incidents are analyzed using distribution, mean, pathway, and associative analysis to describe the data. Kappa scores indicate that categories within FINANS can be reliably used to identify and extract data on human factors-related problems underlying trading incidents. Approximately 1% of trades (n = 750) lead to an incident. Slip/lapse (61%), situation awareness (51%), and teamwork (40%) were found to be the most common problems underlying incidents. For the most serious incidents, problems in situation awareness and teamwork were most common. We show that (a) experts in the trading domain can reliably and accurately code human factors in incidents, (b) 1% of trades incur error, and (c) poor teamwork skills and situation awareness underpin the most critical incidents. This research provides data crucial for ameliorating risk within financial trading organizations, with implications for regulation and policy. © 2016, Human Factors and Ergonomics Society.

  12. Impact factors of fractal analysis of porous structure

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Characterization of pore structure is one of the key problems for fabrication and application research on porous materials. But, complexity of pore structure makes it difficult to characterize pore structure by Euclidean geometry and traditional experimental methods. Fractal theory has been proved effective to characterize the complex pore structure. The box dimension method based on fractal theory was applied to characterizing the pore structure of fiber porous materials by analyzing the electronic scanning microscope (SEM) images of the porous materials in this paper. The influences of image resolution, threshold value, and image magnification on fractal analysis were investigated. The results indicate that such factors greatly affect fractal analysis process and results. The appropriate magnification threshold and fractal analysis are necessary for fractal analysis.

  13. Exploratory factor analysis of the Dizziness Handicap Inventory (German version

    Directory of Open Access Journals (Sweden)

    de Bruin Eling D

    2010-03-01

    Full Text Available Abstract Background The Dizziness Handicap Inventory (DHI is a validated, self-report questionnaire which is widely used as an outcome measure. Previous studies supported the multidimensionality of the DHI, but not the original subscale structure. The objectives of this survey were to explore the dimensions of the Dizziness Handicap Inventory - German version, and to investigate the associations of the retained factors with items assessing functional disability and the Hospital Anxiety and Depression Scale (HADS. Secondly we aimed to explore the retained factors according to the International Classification of Functioning, Disability and Health (ICF. Methods Patients were recruited from a tertiary centre for vertigo, dizziness or balance disorders. They filled in two questionnaires: (1 The DHI assesses precipitating physical factors associated with dizziness/unsteadiness and functional/emotional consequences of symptoms. (2 The HADS assesses non-somatic symptoms of anxiety and depression. In addition, patients answered the third question of the University of California Los Angeles-Dizziness Questionnaire which covers the impact of dizziness and unsteadiness on everyday activities. Principal component analysis (PCA was performed to explore the dimensions of the DHI. Associations were estimated by Spearman correlation coefficients. Results One hundred ninety-four patients with dizziness or unsteadiness associated with a vestibular disorder, mean age (standard deviation of 50.6 (13.6 years, participated. Based on eigenvalues greater one respectively the scree plot we analysed diverse factor solutions. The 3-factor solution seems to be reliable, clinically relevant and can partly be explained with the ICF. It explains 49.2% of the variance. Factor 1 comprises the effect of dizziness and unsteadiness on emotion and participation, factor 2 informs about specific activities or effort provoking dizziness and unsteadiness, and factor 3 focuses on self

  14. Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-04-20

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

  15. Risk factors for progressive ischemic stroke A retrospective analysis

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    BACKGROUND: Progressive ischemic stroke has higher fatality rate and disability rate than common cerebral infarction, thus it is very significant to investigate the early predicting factors related to the occurrence of progressive ischemic stroke, thc potential pathological mechanism and the risk factors of early intervention for preventing the occurrence of progressive ischemic stroke and ameliorating its outcome.OBJECTIVE: To analyze the possible related risk factors in patients with progressive ishcemic stroke, so as to provide reference for the prevention and treatment of progressive ishcemic stroke.DESIGN: A retrospective analysis.SETTING: Department of Neurology, General Hospital of Beijing Coal Mining Group.PARTICIPANTS: Totally 280 patients with progressive ischemic stroke were selected from the Department of Neurology, General Hospital of Beijing Coal Mining Group from March 2002 to June 2006, including 192 males and 88 females, with a mean age of (62±7) years old. They were all accorded with the diagnostic standards for cerebral infarction set by the Fourth National Academic Meeting for Cerebrovascular Disease in 1995, and confired by CT or MRI, admitted within 24 hours after attack, and the neurological defect progressed gradually or aggravated in gradients within 72 hours after attack, and the aggravation of neurological defect was defined as the neurological deficit score decreased by more than 2 points. Meanwhile,200 inpatients with non-progressive ischemic stroke (135 males and 65 females) were selected as the control group.METHODS: After admission, a univariate analysis of variance was conducted using the factors of blood pressure, history of diabetes mellitus, fever, leukocytosis, levels of blood lipids, fibrinogen, blood glucose and plasma homocysteine, cerebral arterial stenosis, and CT symptoms of early infarction, and the significant factors were involved in the multivariate non-conditional Logistic regression analysis.MAIN OUTCOME MEASURES

  16. Analysis of risk factors for postoperative pancreatic fistula following pancreaticoduodenectomy.

    Science.gov (United States)

    Liu, Qi-Yu; Zhang, Wen-Zhi; Xia, Hong-Tian; Leng, Jian-Jun; Wan, Tao; Liang, Bin; Yang, Tao; Dong, Jia-Hong

    2014-12-14

    To explore the morbidity and risk factors of postoperative pancreatic fistula (POPF) following pancreaticoduodenectomy. The data from 196 consecutive patients who underwent pancreaticoduodenectomy, performed by different surgeons, in the General Hospital of the People's Liberation Army between January 1(st), 2013 and December 31(st), 2013 were retrospectively collected for analysis. The diagnoses of POPF and clinically relevant (CR)-POPF following pancreaticoduodenectomy were judged strictly by the International Study Group on Pancreatic Fistula Definition. Univariate analysis was performed to analyze the following factors: patient age, sex, body mass index (BMI), hypertension, diabetes mellitus, serum CA19-9 level, history of jaundice, serum albumin level, blood loss volume, pancreatic duct diameter, pylorus preserving pancreaticoduodenectomy, pancreatic drainage and pancreaticojejunostomy. Multivariate logistic regression analysis was used to determine the main independent risk factors for POPF. POPF occurred in 126 (64.3%) of the patients, and the incidence of CR-POPF was 32.7% (64/196). Patient characteristics of age, sex, BMI, hypertension, diabetes mellitus, serum CA19-9 level, history of jaundice, serum albumin level, blood loss volume, pylorus preserving pancreaticoduodenectomy and pancreaticojejunostomy showed no statistical difference related to the morbidity of POPF or CR-POPF. Pancreatic duct diameter was found to be significantly correlated with POPF rates by univariate analysis and multivariate regression analysis, with a pancreatic duct diameter ≤ 3 mm being an independent risk factor for POPF (OR = 0.291; P = 0.000) and CR-POPF (OR = 0.399; P = 0.004). The CR-POPF rate was higher in patients without external pancreatic stenting, which was found to be an independent risk factor for CR-POPF (OR = 0.394; P = 0.012). Among the entire patient series, there were three postoperative deaths, giving a total mortality rate of 1.5% (3/196), and the mortality

  17. ANALYSIS OF FACTORS WHICH AFFECTING THE ECONOMIC GROWTH

    Directory of Open Access Journals (Sweden)

    Suparna Wijaya

    2017-03-01

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

  18. Empirical Analysis on Factors Influencing Distribution of Vegetal Production

    Institute of Scientific and Technical Information of China (English)

    Wenjie; WU

    2015-01-01

    Since the reform and opening-up,there has been a great change in spatial pattern of China’s vegetable production. This paper studied vegetable production in provinces of China in 1978- 2013. From the sequential characteristics,China’s vegetable production area is constantly growing and takes on stage characteristic. From the spatial distribution,China’s vegetable production takes on the trend of " going down the south" and " marching the west". In order to grasp rules of changes of vegetable production and the influence factors,this paper made theoretical and empirical analysis on factors possibly influencing distribution of vegetable production. Results show that major factors influencing distribution of China’s vegetable production include irrigation condition,non-agricultural employment,market demand,knowledge spillover,comparative effectiveness,rural road and government policies.

  19. A Bayesian semiparametric factor analysis model for subtype identification.

    Science.gov (United States)

    Sun, Jiehuan; Warren, Joshua L; Zhao, Hongyu

    2017-04-25

    Disease subtype identification (clustering) is an important problem in biomedical research. Gene expression profiles are commonly utilized to infer disease subtypes, which often lead to biologically meaningful insights into disease. Despite many successes, existing clustering methods may not perform well when genes are highly correlated and many uninformative genes are included for clustering due to the high dimensionality. In this article, we introduce a novel subtype identification method in the Bayesian setting based on gene expression profiles. This method, called BCSub, adopts an innovative semiparametric Bayesian factor analysis model to reduce the dimension of the data to a few factor scores for clustering. Specifically, the factor scores are assumed to follow the Dirichlet process mixture model in order to induce clustering. Through extensive simulation studies, we show that BCSub has improved performance over commonly used clustering methods. When applied to two gene expression datasets, our model is able to identify subtypes that are clinically more relevant than those identified from the existing methods.

  20. Analysis of Factors Influencing English Listening Teaching and the Countermeasures

    Institute of Scientific and Technical Information of China (English)

    TIAN Tian

    2013-01-01

    English teaching focuses on cultivating and improving students’listening, speaking, reading, writing and translating skills, which are complementary to each other. Among these five skills, listening, as an important basic skill, should be put into top priority in English teaching. Mainly based on the analysis of factors influencing English listening teaching, the paper puts for-ward some effective countermeasures in improving teaching effectiveness.

  1. Analysis on some factors affecting MIMO in tunnel

    Science.gov (United States)

    Zheng, Hong-dang; Nie, Xiao-Yan; Xu, Zhao

    2009-07-01

    Based on the 3D-GBSB (three-dimensional Geometrically Based Single-Bounce) model and MIMO channel capacity function, by geometric analysis, it is analyzed that transceiver antenna arrays, antenna spacing, antenna array angle, SNR and Rician K-factor and so on impact on the frequency-nonselective fading MIMO channel capacity. Monte Carlo method can be applied to stimulate the wireless fading channel and demonstrate Cumulative Distribution Function of above.

  2. Creative Uses of Factor Analysis in Psychotherapy Research: Past Examples and Future Possibilities.

    Science.gov (United States)

    Adams, James M.

    Factor analysis is a statistical method of reducing a set number of variables by finding similarities between them. This paper reviews the potential of factor analysis, focusing on exploratory factor analysis, in research on psychotherapy. Within the field of psychotherapy, the use of factor analysis can be classified into three groups. The first…

  3. Design of financial results on the basis of factor analysis

    Directory of Open Access Journals (Sweden)

    V. M. Sidorov

    2016-01-01

    Full Text Available Approaches are presented in the article, qualificatory the design of financial results on the basis of factor analysis. Connection marks between development of enterprises and scientific and technical progress. It is shown that potential of enterprises can be based on the design of financial results. Actuality of this direction of research marks on a background the entered approvals against Russia. A control role is indicated at the effective use of resources. It is well-proven that a key moment in forming of profit of enterprise is a design of financial results. A factor analysis is reasonable at the estimation of activity of organization, which exposed an application of this determined model domain. is sent to capital augmentation. The role of the financial system and separate elements is shown in to financially-economic activity. Connection is set between a design and structure of the investigated object. A design cannot come true without determination of structure of the investigated object, because a structure characterizes steady connections between elements. The components of elements are able in totality to counteract to external influences. For expansion of the system to distinguish the most meaningful factors. To distinguish integrating connections from appropriate. Distinguished, that factors due to co-operating with each other can create a synergistically or extinguishing effect or neutralize each other. Factors will organize or will disorganize work of organization. The design of objects is built on the certain terms, and separate parties of object are examined at abandonment from the less meaningful elements of the system. The role of empiric and theoretical level of research in the design of activity of organization is shown. An author suggested to use the determined model for determination of functional connections between a resulting index and factor signs. Exposed an application of this determined model domain.

  4. An analysis of risk factors for asymptomatic cerebral infarction.

    Science.gov (United States)

    Shiga, Tomoko; Owada, Kiyoshi; Hoshino, Tatsuo; Nagahara, Hikaru; Shiratori, Keiko

    2008-01-01

    The aim of this study is to identify risk factors for asymptomatic cerebral infarction (ACI) in the general Japanese population. A total of 634 subjects (272 men aged 55.4+/-8.8 years and 362 women aged 55.2+/-8.5 years) who visited the Health Management Center at Aoyama Hospital (Tokyo, Japan) from January 2004 through January 2005 for an annual brain dry dock examination were analyzed. We evaluated 21 risk factors for ACI by multivariate logistic regression analysis. Abnormal or potentially abnormal conditions were detected in 258 subjects (40.7% of all subjects who had an annual check-up program for brain disease). The most frequent abnormal finding was ACI, which was observed in 208 subjects. The significant risk factors for ACI, as determined by multivariate logistic analysis, were age (P <0.01), hypertension (P <0.01), and hypertensive vascular changes in the fundus (P <0.05). The hypertensive vascular abnormalities in the fundus might be a risk factor for ACI independent of age and hypertension.

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

    Directory of Open Access Journals (Sweden)

    Elena Mazurova

    2017-05-01

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

  6. Menstrual Factors, Reproductive Factors 
and Lung Cancer Risk: A Meta-analysis

    Directory of Open Access Journals (Sweden)

    Yue ZHANG

    2012-12-01

    Full Text Available Background and objective Epidemiological studies have suggested that menstrual and reproductive factors may influence lung cancer risk, but the results are controversial. We therefore carried out a meta-analysis aiming to examine the associations of lung cancer in women with menstrual and reproductive factors. 
Methods Relevant studies were searched from PubMed database, CNKI, WANFANG DATA and VIP INFORMATION up to January 2012, with no language restrictions. References listed from selected papers were also reviewed. We included studies that reported the estimates of relative risks (RRs with 95% confidence intervals (CIs for the association between menstrual and reproductive factors and lung cancer risk. The pooled RRs were calculated after the heterogeneity test with the software Stata 11, and publication bias and sensitivity were evaluated at the same time. 
Results Twenty-five articles, representing 24 independent studies, were included in this meta-analysis. Older age at menarche in North America women (RR=0.83; 95%CI: 0.73-0.94 was associated with a significant decreased risk of lung cancer. Longer length of menstrual cycle was also associated with decreased lung cancer risk (RR=0.72; 95%CI: 0.57-0.90. Other exposures were not significantly associated. 
Conclusions Our analysis provides evidence of the hypothesis that female sex hormones influence the risk of lung cancer in women, yet additional studies are warranted to extend this finding and to clarify the underlying mechanisms.

  7. Dispersion-theoretical analysis of the nucleon electromagnetic form factors

    Energy Technology Data Exchange (ETDEWEB)

    Belushkin, M.

    2007-09-29

    The structure of the proton and the neutron is of fundamental importance for the study of the strong interaction dynamics over a wide range of momentum transfers. The nucleon form factors encode information on the internal structure of the nucleon as probed by the electromagnetic interaction, and, to a certain extent, reflect the charge and magnetisation distributions within the proton and the neutron. In this thesis we report on our investigation of the electromagnetic form factors of the proton and the neutron with dispersion relation techniques, including known experimental input on the {pi}{pi}, K anti K and the {rho}{pi} continua and perturbative QCD constraints. We include new experimental data on the pion form factor and the nucleon form factors in our simultaneous analysis of all four form factors in both the space- and the timelike regions for all momentum transfers, and perform Monte- Carlo sampling in order to obtain theoretical uncertainty bands. Finally, we discuss the implications of our results on the pion cloud of the nucleon, the nucleon radii and the Okubo-Zweig-Iizuka rule, and present our results of a model-independent approach to estimating two-photon effects in elastic electron-proton scattering. (orig.)

  8. Dispersion-theoretical analysis of the nucleon electromagnetic form factors

    Energy Technology Data Exchange (ETDEWEB)

    Belushkin, M.

    2007-09-29

    The structure of the proton and the neutron is of fundamental importance for the study of the strong interaction dynamics over a wide range of momentum transfers. The nucleon form factors encode information on the internal structure of the nucleon as probed by the electromagnetic interaction, and, to a certain extent, reflect the charge and magnetisation distributions within the proton and the neutron. In this thesis we report on our investigation of the electromagnetic form factors of the proton and the neutron with dispersion relation techniques, including known experimental input on the {pi}{pi}, K anti K and the {rho}{pi} continua and perturbative QCD constraints. We include new experimental data on the pion form factor and the nucleon form factors in our simultaneous analysis of all four form factors in both the space- and the timelike regions for all momentum transfers, and perform Monte- Carlo sampling in order to obtain theoretical uncertainty bands. Finally, we discuss the implications of our results on the pion cloud of the nucleon, the nucleon radii and the Okubo-Zweig-Iizuka rule, and present our results of a model-independent approach to estimating two-photon effects in elastic electron-proton scattering. (orig.)

  9. A Bayes factor meta-analysis of Bem's ESP claim.

    Science.gov (United States)

    Rouder, Jeffrey N; Morey, Richard D

    2011-08-01

    In recent years, statisticians and psychologists have provided the critique that p-values do not capture the evidence afforded by data and are, consequently, ill suited for analysis in scientific endeavors. The issue is particular salient in the assessment of the recent evidence provided for ESP by Bem (2011) in the mainstream Journal of Personality and Social Psychology. Wagenmakers, Wetzels, Borsboom, and van der Maas (Journal of Personality and Social Psychology, 100, 426-432, 2011) have provided an alternative Bayes factor assessment of Bem's data, but their assessment was limited to examining each experiment in isolation. We show here that the variant of the Bayes factor employed by Wagenmakers et al. is inappropriate for making assessments across multiple experiments, and cannot be used to gain an accurate assessment of the total evidence in Bem's data. We develop a meta-analytic Bayes factor that describes how researchers should update their prior beliefs about the odds of hypotheses in light of data across several experiments. We find that the evidence that people can feel the future with neutral and erotic stimuli to be slight, with Bayes factors of 3.23 and 1.57, respectively. There is some evidence, however, for the hypothesis that people can feel the future with emotionally valenced nonerotic stimuli, with a Bayes factor of about 40. Although this value is certainly noteworthy, we believe it is orders of magnitude lower than what is required to overcome appropriate skepticism of ESP.

  10. [Morbidity, mortality and analysis of prognostic factors for colorectal cancer].

    Science.gov (United States)

    Clauer, U; Schäfer, J; Roder, J

    2015-06-01

    This study analyzed morbidity, mortality and prognostic factors for patient survival in a single center collective of patients with colorectal cancer and a high follow-up rate. A total of 698 consecutive patients were included in this study. Data were collected prospectively. Descriptive and survival analyses as well as Cox regression analyses were performed to identify factors for morbidity, mortality and prognostic factors for survival. At presentation 78.8 % of the colon cancer patients and 83.5 % of rectal cancer patients showed symptomatic disease and 6.5 % of patients underwent an emergency procedure. Mortality was 3.6 %, morbidity was 42.7 % and 4.3 % of patients developed an anastomotic leakage with the need of reoperation. In spite of the regular application of a fast-track program, 10 % of patients had a prolonged duration of bowel paralysis. In patients with colon cancer there were no differences between overall survival (OAS) and disease-free survival, whereas there was a significant difference in patients with rectal cancer. The mean survival of all patients was 65.39 ± 1.722 months. The ASA score, cardiovascular disease, number of metastatic lymph nodes, lymph node ratio, residual tumor and general or surgery-associated complications were strongly independent influencing factors on OAS. A Cox analysis revealed age at diagnosis and microscopic residual tumor (TNM R1) as highly significant influencing factors on OAS. Other significant factors of influence on OAS were development of general or surgery-associated complications and the presence of cardiovascular diseases. Cardiovascular disease leads to a higher morbidity rate whereas age, International Union Against Cancer (UICC) stage, R-status, lymphatic spread and occurrence of complications are important prognostic factors for survival.

  11. Phasor analysis of binary diffraction gratings with different fill factors

    Energy Technology Data Exchange (ETDEWEB)

    MartInez, Antonio [Departamento de Ciencia de Materiales, Optica y TecnologIa Electronica, Universidad Miguel Hernandez, 03202 Elche (Spain); Sanchez-Lopez, Ma del Mar [Instituto de BioingenierIa y Departamento de Fisica y Arquitectura de Computadores, Universidad Miguel Hernandez, 03202 Elche (Spain); Moreno, Ignacio [Departamento de Ciencia de Materiales, Optica y TecnologIa Electronica, Universidad Miguel Hernandez, 03202 Elche (Spain)

    2007-09-11

    In this work, we present a simple analysis of binary diffraction gratings with different slit widths relative to the grating period. The analysis is based on a simple phasor technique directly derived from the Huygens principle. By introducing a slit phasor and a grating phasor, the intensity of the diffracted orders and the grating's resolving power can be easily obtained without applying the usual Fourier transform operations required for these calculations. The proposed phasor technique is mathematically equivalent to the Fourier transform calculation of the diffraction order amplitude, and it can be useful to explain binary diffraction gratings in a simple manner in introductory physics courses. This theoretical analysis is illustrated with experimental results using a liquid crystal device to display diffraction gratings with different fill factors.

  12. Biosphere dose conversion Factor Importance and Sensitivity Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M. Wasiolek

    2004-10-15

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

  13. Making Tensor Factorizations Robust to Non-Gaussian Noise

    CERN Document Server

    Chi, Eric C

    2010-01-01

    Tensors are multi-way arrays, and the Candecomp/Parafac (CP) tensor factorization has found application in many different domains. The CP model is typically fit using a least squares objective function, which is a maximum likelihood estimate under the assumption of i.i.d. Gaussian noise. We demonstrate that this loss function can actually be highly sensitive to non-Gaussian noise. Therefore, we propose a loss function based on the 1-norm because it can accommodate both Gaussian and grossly non-Gaussian perturbations. We also present an alternating majorization-minimization algorithm for fitting a CP model using our proposed loss function.

  14. Association factor analysis between osteoporosis with cerebral artery disease

    Science.gov (United States)

    Jin, Eun-Sun; Jeong, Je Hoon; Lee, Bora; Im, Soo Bin

    2017-01-01

    Abstract The purpose of this study was to determine the clinical association factors between osteoporosis and cerebral artery disease in Korean population. Two hundred nineteen postmenopausal women and men undergoing cerebral computed tomography angiography were enrolled in this study to evaluate the cerebral artery disease by cross-sectional study. Cerebral artery disease was diagnosed if there was narrowing of 50% higher diameter in one or more cerebral vessel artery or presence of vascular calcification. History of osteoporotic fracture was assessed using medical record, and radiographic data such as simple radiography, MRI, and bone scan. Bone mineral density was checked by dual-energy x-ray absorptiometry. We reviewed clinical characteristics in all patients and also performed subgroup analysis for total or extracranial/ intracranial cerebral artery disease group retrospectively. We performed statistical analysis by means of chi-square test or Fisher's exact test for categorical variables and Student's t-test or Wilcoxon's rank sum test for continuous variables. We also used univariate and multivariate logistic regression analyses were conducted to assess the factors associated with the prevalence of cerebral artery disease. A two-tailed p-value of less than 0.05 was considered as statistically significant. All statistical analyses were performed using R (version 3.1.3; The R Foundation for Statistical Computing, Vienna, Austria) and SPSS (version 14.0; SPSS, Inc, Chicago, Ill, USA). Of the 219 patients, 142 had cerebral artery disease. All vertebral fracture was observed in 29 (13.24%) patients. There was significant difference in hip fracture according to the presence or absence of cerebral artery disease. In logistic regression analysis, osteoporotic hip fracture was significantly associated with extracranial cerebral artery disease after adjusting for multiple risk factors. Females with osteoporotic hip fracture were associated with total calcified

  15. Factor analysis of nursing students' perception of patient safety education.

    Science.gov (United States)

    Mansour, Mansour

    2015-01-01

    The aim of this study is to investigate the factor structure of the Health Care Professionals Patient Safety Assessment Curriculum Survey (HPPSACS) when completed by a group of nursing students from one University in the UK. The quality, content and delivery of nursing education can have a significant impact on the future students' safety behaviours in clinical settings. The Health Care Professionals Patient Safety Assessment Curriculum Survey HPPSACS has been developed in the US to establish undergraduate nursing students' perceived awareness, skills, and attitudes toward patient safety education. The instrument has not been reported to be used elsewhere; therefore, some psychometric properties remain untested. Pre-registration nursing students (n=272) from three campuses of a university in East of England completed the HPPSACS in 2012. Principal component analysis was conducted to explore the factors emerging from the students' responses. 222 students (82%) returned the questionnaires. Constraining data to a 4-factor solution explained 52% of the variance. Factors identified were: "Willingness to disclose errors", "Recognition and management of medical errors", "The Perceived interprofessional context of patient safety" and "The perceived support and understanding for improving patient safety". The overall Cronbach's alpha was 0.64, indicating moderate internal consistency of the instrument. Some demographical and descriptive questions on the HPPSACS instrument were modified to accommodate the participants' educational context. However, all items in the HPPSACS which were included in the factor analysis remain identical to the original tool. The study offers empirical findings of how patient safety education is contextualised in the undergraduate, pre-registration nursing curriculum. Further research is required to refine and improve the overall reliability of the Health Care Professionals Patient Safety Assessment Curriculum Survey (HPPSACS' instrument

  16. Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis.

    Directory of Open Access Journals (Sweden)

    Anna B. Costello

    2005-07-01

    Full Text Available Exploratory factor analysis (EFA is a complex, multi-step process. The goal of this paper is..to collect, in one article, information that will allow researchers and practitioners to..understand the various choices available through popular software packages, and to make..decisions about - best practices- in exploratory factor analysis. In particular, this paper..provides practical information on making decisions regarding (a extraction, (b rotation, (c..the number of factors to interpret, and (d sample size.

  17. Analysis of random factors of the self-education process

    Directory of Open Access Journals (Sweden)

    A. A. Solodov

    2016-01-01

    Full Text Available The aim of the study is the statistical description of the random factors of the self-educationт process, namely that stage of the process of continuous education, in which there is no meaningful impact on the student’s educational organization and the development of algorithms for estimating these factors. It is assumed that motivations of self-education are intrinsic factors that characterize the individual learner and external, associated with the changing environment and emerging challenges. Phenomena available for analysis a self-learning process (observed data are events relevant to this process, which are modeled by points on the time axis, the number and position of which is assumed to be random. Each point can be mapped with the unknown and unobserved random or nonrandom factor (parameter which affects the intensity of formation of dots. The purpose is to describe observable and unobservable data and developing algorithms for optimal evaluation. Further, such evaluations can be used for the individual characteristics of the process of self-study or for comparison of different students. For the analysis of statistical characteristics of the process of selfeducation applied mathematical apparatus of the theory of point random processes, which allows to determine the key statistical characteristics of unknown random factors of the process of self-education. The work consists of a logically complete model including the following components.• Study the basic statistical model of the appearance of points in the process of self-education in the form of a Poisson process, the only characteristic is the intensity of occurrence of events• Methods of testing the hypothesis about Poisson distribution of observed events.• Generalization of the basic model to the case where the intensity function depends on the time and unknown factor (variable can be both random and not random. Such factors are interpreted as

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

    Science.gov (United States)

    Hoseinzade, Zohre; Mokhtari, Ahmad Reza

    2017-10-01

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

  19. Dimensionality of an Early Childhood Scale Using Rasch Analysis and Confirmatory Factor Analysis.

    Science.gov (United States)

    Banerji, Madhabi; Smith, Richard M.; Dedrick, Robert F.

    1997-01-01

    This paper explores the use of Rasch analysis and linear confirmatory factor analysis to investigate the dimensionality of an early childhood test, the Gesell School Readiness Screening Test (F. Ilg and others, 1978). Discusses empirical analyses of results from 523 kindergarten students using both methods. (SLD)

  20. Analysis of Social Cohesion in Health Data by Factor Analysis Method: The Ghanaian Perspective

    Science.gov (United States)

    Saeed, Bashiru I. I.; Xicang, Zhao; Musah, A. A. I.; Abdul-Aziz, A. R.; Yawson, Alfred; Karim, Azumah

    2013-01-01

    We investigated the study of the overall social cohesion of Ghanaians. In this study, we considered the paramount interest of the involvement of Ghanaians in their communities, their views of other people and institutions, and their level of interest in both local and national politics. The factor analysis method was employed for analysis using R…

  1. Learning From Hidden Traits: Joint Factor Analysis and Latent Clustering

    Science.gov (United States)

    Yang, Bo; Fu, Xiao; Sidiropoulos, Nicholas D.

    2017-01-01

    Dimensionality reduction techniques play an essential role in data analytics, signal processing and machine learning. Dimensionality reduction is usually performed in a preprocessing stage that is separate from subsequent data analysis, such as clustering or classification. Finding reduced-dimension representations that are well-suited for the intended task is more appealing. This paper proposes a joint factor analysis and latent clustering framework, which aims at learning cluster-aware low-dimensional representations of matrix and tensor data. The proposed approach leverages matrix and tensor factorization models that produce essentially unique latent representations of the data to unravel latent cluster structure -- which is otherwise obscured because of the freedom to apply an oblique transformation in latent space. At the same time, latent cluster structure is used as prior information to enhance the performance of factorization. Specific contributions include several custom-built problem formulations, corresponding algorithms, and discussion of associated convergence properties. Besides extensive simulations, real-world datasets such as Reuters document data and MNIST image data are also employed to showcase the effectiveness of the proposed approaches.

  2. Dietary Factors Affecting Thyroid Cancer Risk: A Meta-Analysis.

    Science.gov (United States)

    Cho, Young Ae; Kim, Jeongseon

    2015-01-01

    Some dietary factors are proposed to affect thyroid carcinogenesis, but previous studies have reported inconsistent findings. Therefore, we performed a meta-analysis, including 18 eligible studies, to clarify the role of dietary factors in the risk of thyroid cancer. The relative risks (RRs) with 95% confidence intervals (95% CIs) were estimated to assess the association and heterogeneity tests and subgroup and sensitivity analyses, and bias assessments were performed. When the results from all studies were combined, dietary iodine, fish, and cruciferous vegetable intake were not associated with thyroid cancer. However, when the data were divided by geographic location based on iodine availability, a slight increase in the risk of thyroid cancer was observed among those consuming a high total amount of fish in iodine nondeficient areas (RR: 1.18; 95% CI: 1.03-1.35; P for heterogeneity = 0.282). When excluding the studies examining a single food item and hospital-based controls, a high intake of cruciferous vegetables was associated with an increased risk of thyroid cancer in iodine-deficient areas (RR: 1.43; 95% CI: 1.18-1.74; P for heterogeneity = 0.426). This meta-analysis implies that the role of dietary factors, such as fish and cruciferous vegetables, in thyroid cancer risk can differ based on iodine availability.

  3. Bayes factor design analysis: Planning for compelling evidence.

    Science.gov (United States)

    Schönbrodt, Felix D; Wagenmakers, Eric-Jan

    2017-03-01

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

  4. IDENTIFICATION OF CRITICAL SSCM ACTIVITIES THROUGH CONFIRMATORY FACTOR ANALYSIS

    Directory of Open Access Journals (Sweden)

    V. Narasimham

    2013-06-01

    Full Text Available As a developing country, economic and environmental performance has to be balanced in India. Green supply chain management (GSCM is emerging as an important proactive approach for Indian enterprises for improving environmental performance of processes and products in accordance with the requirements of environmental regulations. This study examines the consistency approaches by confirmatory factor analysis that determines the construct validity, convergent validity,construct reliability and internal consistency of the items of Sustainable supply chain management (SSCM requirements. This study examines the consistency approaches by Confirmatory factor analysis that determines the adoption and implementation of Sustainable supply chain management activities in small & medium scale industries. The requirements include Management commitment, customer coordination, sustainable design & production, green procurement and eco logistics for sustainable supply chains. This study suggested that the five factor model with eighteen items of the sustainable supply chain design had a good fit. Further, the study showed a valid and reliable measurement to identify critical items among the requirements of sustainable supply chains.

  5. Medical and psychosocial factors associated with antibiotic prescribing in primary care: survey questionnaire and factor analysis.

    Science.gov (United States)

    Lee, Tau-Hong; Wong, Joshua Gx; Lye, David Cb; Chen, Mark Ic; Loh, Victor Wk; Leo, Yee-Sin; Lee, Linda K; Chow, Angela Lp

    2017-03-01

    Acute upper respiratory infections (AURI) are the leading causes of antibiotic prescribing in primary care although antibiotics are often not indicated. To gain an understanding of the knowledge, attitudes, and practices (KAP) of GPs in Singapore and the associated latent factors to guide the implementation of an effective programme to reduce antibiotic use in primary care. An anonymous survey on the KAP of antibiotic use in AURI of GPs in Singapore. KAP survey questionnaires were posted to all GPs from a database. To ascertain the latent factors affecting prescribing patterns, exploratory factor analysis was performed. Among 427 responses, 351 (82.2%) were from GPs working in private practice. It was found that 58.4% of GPs in the private versus 72.4% of those in the public sector recognised that >80% of AURIs were caused by viruses (P = 0.02). The majority of GPs (353/427; 82.7%) felt that antibiotics were overprescribed in primary care. Significant factors associated with low antibiotic prescribing were good medical knowledge and clinical competency (adjusted odds ratio [aOR] 3.2, 95% confidence interval [CI] = 2.4 to 4.3), good clinical practice (aOR 2.7 [95% CI = 2.0 to 3.6]), availability of diagnostic tests (aOR 1.4 [95% CI = 1.1 to 1.8]), and desire to improve clinical practice (aOR 1.5 [95% CI = 1.2 to 1.9]). The conservative practice of giving antibiotics 'to be on the safe side' is significantly less likely to be associated with low antibiotic prescribing (aOR 0.7 [95% CI = 0.5 to 0.9]). This is the first KAP survey on antibiotic prescribing for AURI among GPs in Singapore. With the latent factors identified, future interventions should be directed at addressing these factors to reduce inappropriate antibiotic prescribing. © British Journal of General Practice 2017.

  6. Factors influencing societal response of nanotechnology: an expert stakeholder analysis

    Energy Technology Data Exchange (ETDEWEB)

    Gupta, Nidhi, E-mail: nidhi.gupta@wur.nl; Fischer, Arnout R. H., E-mail: arnout.fischer@wur.nl; Lans, Ivo A. van der, E-mail: Ivo.vanderLans@wur.nl [Wageningen University, Marketing and Consumer Behaviour Group (Netherlands); Frewer, Lynn J., E-mail: lynn.frewer@newcastle.ac.uk [Newcastle University, School of Agriculture, Food and Rural Development (United Kingdom)

    2012-05-15

    Nanotechnology can be described as an emerging technology and, as has been the case with other emerging technologies such as genetic modification, different socio-psychological factors will potentially influence societal responses to its development and application. These factors will play an important role in how nanotechnology is developed and commercialised. This article aims to identify expert opinion on factors influencing societal response to applications of nanotechnology. Structured interviews with experts on nanotechnology from North West Europe were conducted using repertory grid methodology in conjunction with generalized Procrustes analysis to examine the psychological constructs underlying societal uptake of 15 key applications of nanotechnology drawn from different areas (e.g. medicine, agriculture and environment, chemical, food, military, sports, and cosmetics). Based on expert judgement, the main factors influencing societal response to different applications of nanotechnology will be the extent to which applications are perceived to be beneficial, useful, and necessary, and how 'real' and physically close to the end-user these applications are perceived to be by the public.

  7. Exploring leadership styles for innovation: an exploratory factor analysis

    Directory of Open Access Journals (Sweden)

    Wipulanusat Warit

    2017-03-01

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

  8. Factors influencing societal response of nanotechnology: an expert stakeholder analysis.

    Science.gov (United States)

    Gupta, Nidhi; Fischer, Arnout R H; van der Lans, Ivo A; Frewer, Lynn J

    2012-05-01

    Nanotechnology can be described as an emerging technology and, as has been the case with other emerging technologies such as genetic modification, different socio-psychological factors will potentially influence societal responses to its development and application. These factors will play an important role in how nanotechnology is developed and commercialised. This article aims to identify expert opinion on factors influencing societal response to applications of nanotechnology. Structured interviews with experts on nanotechnology from North West Europe were conducted using repertory grid methodology in conjunction with generalized Procrustes analysis to examine the psychological constructs underlying societal uptake of 15 key applications of nanotechnology drawn from different areas (e.g. medicine, agriculture and environment, chemical, food, military, sports, and cosmetics). Based on expert judgement, the main factors influencing societal response to different applications of nanotechnology will be the extent to which applications are perceived to be beneficial, useful, and necessary, and how 'real' and physically close to the end-user these applications are perceived to be by the public. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11051-012-0857-x) contains supplementary material, which is available to authorized users.

  9. [Analysis of risk factors for perinatal brachial plexus palsy].

    Science.gov (United States)

    Gosk, Jerzy; Rutowski, Roman

    2005-04-01

    Risk factors of obstetrical brachial plexus palsy include: (1) large birth weight, (2) shoulder dystocia and prolonged second stage of labour, (3) instrumental vaginal delivery (forceps delivery, vacuum extraction), (4) diabetes mellitus and mother's obesity, (5) breech presentation, (6) delivery and infant with obstetrical brachial plexus palsy in antecedent delivery. The purpose was analysis of the classical risk factors for brachial plexus palsy based on our own clinical material. Clinical material consists of 83 children with obstetrical brachial plexus palsy treated at the Department of Trauma and Hand Surgery (surgically--54, conservatively--29). Control group consists of 56 healthy newborns. Data recorded included: birth weight, body length, head and chest circumference, Apgar test at 1 min., type of brachial palsy and side affected, type of birth, presentation, duration of delivery (II stage), age of mother, mother's diseases, parity. The infants treated surgically have had a significantly higher birth weight, body height, head and chest circumference, in compression with control group and group treated conservatively. The differences were statistically important. Shoulder dystocia occurred in 32.9% of all vaginal delivery. Instrumental vaginal delivery was observed in 11.3% and breech presentation in 4.9% cases. There were no incidences of obstetrical brachial plexus palsy recurrence. Diabetes mellitus and mother's obesity was found in 3 cases. (1) Fetal macrosomia is the important risk factor of the obstetrical brachial plexus palsy. (2) Obstetrical brachial plexus palsy may occur also in the absence of the classical risk factors.

  10. Factors influencing societal response of nanotechnology: an expert stakeholder analysis

    Science.gov (United States)

    Gupta, Nidhi; Fischer, Arnout R. H.; van der Lans, Ivo A.; Frewer, Lynn J.

    2012-05-01

    Nanotechnology can be described as an emerging technology and, as has been the case with other emerging technologies such as genetic modification, different socio-psychological factors will potentially influence societal responses to its development and application. These factors will play an important role in how nanotechnology is developed and commercialised. This article aims to identify expert opinion on factors influencing societal response to applications of nanotechnology. Structured interviews with experts on nanotechnology from North West Europe were conducted using repertory grid methodology in conjunction with generalized Procrustes analysis to examine the psychological constructs underlying societal uptake of 15 key applications of nanotechnology drawn from different areas (e.g. medicine, agriculture and environment, chemical, food, military, sports, and cosmetics). Based on expert judgement, the main factors influencing societal response to different applications of nanotechnology will be the extent to which applications are perceived to be beneficial, useful, and necessary, and how 'real' and physically close to the end-user these applications are perceived to be by the public.

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

    Directory of Open Access Journals (Sweden)

    James Baglin

    2014-06-01

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

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

    Science.gov (United States)

    Pezzoli, Patrizia; Antfolk, Jan; Santtila, Pekka

    2017-01-01

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

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

    Science.gov (United States)

    Taasoobshirazi, Gita; Bailey, MarLynn; Farley, John

    2015-11-01

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

  14. Econometric Analysis of Factors Affecting Special Purpose Forests in China

    Institute of Scientific and Technical Information of China (English)

    Wang Lanhui; Cai Fei

    2003-01-01

    The forest estate is one of our most important natural resources. It is also the material foundation for sustainable forestry development in China. It is a timely topic of concern within the forestry community and touches the entire society. From a social economic point of view, the sustainable development has been promoted by the efficient use of the forest resources in a continuing improvement of the environment. The objective of the present analysis is to measure the effect of various factors, such as population, economic development and related policies on the use of the forest resources. The 29 provinces of Mainland China are classified in three regions, based largely on their level of economic development. For each region, the factors which affect the area of special purpose forests (SPF) are analyzed. Some recommendations are made for further improvement.

  15. Pareto analysis of critical factors affecting technical institution evaluation

    Directory of Open Access Journals (Sweden)

    Victor Gambhir

    2012-08-01

    Full Text Available With the change of education policy in 1991, more and more technical institutions are being set up in India. Some of these institutions provide quality education, but others are merely concentrating on quantity. These stakeholders are in a state of confusion about decision to select the best institute for their higher educational studies. Although various agencies including print media provide ranking of these institutions every year, but their results are controversial and biased. In this paper, the authors have made an endeavor to find the critical factors for technical institution evaluation from literature survey. A Pareto analysis has also been performed to find the intensity of these critical factors in evaluation. This will not only help the stake holders in taking right decisions but will also help the management of institutions in benchmarking for identifying the most important critical areas to improve the existing system. This will in turn help Indian economy.

  16. Flavor Analysis of Nucleon, Δ , and Hyperon Electromagnetic Form Factors

    Science.gov (United States)

    Rohrmoser, Martin; Choi, Ki-Seok; Plessas, Willibald

    2017-03-01

    By the analysis of the world data base of elastic electron scattering on the proton and the neutron (for the latter, in fact, on ^2H and ^3He) important experimental insights have recently been gained into the flavor compositions of nucleon electromagnetic form factors. We report on testing the Graz Goldstone-boson-exchange relativistic constituent-quark model in comparison to the flavor contents in low-energy nucleons, as revealed from electron-scattering phenomenology. It is found that a satisfactory agreement is achieved between theory and experiment for momentum transfers up to Q^2˜ 4 GeV^2, relying on three-quark configurations only. Analogous studies have been extended to the Δ and the hyperon electromagnetic form factors. For them we here show only some sample results in comparison to data from lattice quantum chromodynamics.

  17. Confirmatory factor analysis of the Sport Organizational Effectiveness Scale.

    Science.gov (United States)

    Karteroliotis, Konstantinos; Papadimitriou, Dimitra

    2004-08-01

    The purpose of this study was to examine the factorial validity of the 5-factor model of sport organizational effectiveness developed by Papadimitriou and Taylor. This questionnaire has 33 items which assess five composite effectiveness dimensions pertinent to the operation of sport organizations: calibre of the board and external liaisons, interest in athletes, internal procedures, long term planning, and sport science support. The multiple constituency approach was used as a theoretical framework for developing this scale. Data were obtained from respondents affiliated with 20 Greek national sport organizations with a questionnaire. Analysis indicated that the 5-factor model of effectiveness is workable in assessing the organizational performance of nonprofit sport organizations. The application of the multiple constituency approach in studying sport organizational effectiveness was also suggested.

  18. Confirmatory Factor Analysis of the Social Interest Index

    Directory of Open Access Journals (Sweden)

    Gary K. Leak

    2011-10-01

    Full Text Available Social interest was Alfred Adler’s most important personality trait, and it reflects one’s genuine concern for the welfare of all individuals. Several measures of social interest are available, and the Social Interest Index (SII is one of the most popular in current use. This study is the first to report the results of a confirmatory factor analysis of the SII. Using college students, three models were tested in an effort to find support for the factorial validity of this scale. All analyses showed a poor fit between the theoretical model and scale items. The results paint a fairly negative picture of the factor structure of this important scale.

  19. Multivariate factor analysis of Girgentana goat milk composition

    Directory of Open Access Journals (Sweden)

    Pietro Giaccone

    2010-01-01

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

  20. Reliability estimation in a multilevel confirmatory factor analysis framework.

    Science.gov (United States)

    Geldhof, G John; Preacher, Kristopher J; Zyphur, Michael J

    2014-03-01

    Scales with varying degrees of measurement reliability are often used in the context of multistage sampling, where variance exists at multiple levels of analysis (e.g., individual and group). Because methodological guidance on assessing and reporting reliability at multiple levels of analysis is currently lacking, we discuss the importance of examining level-specific reliability. We present a simulation study and an applied example showing different methods for estimating multilevel reliability using multilevel confirmatory factor analysis and provide supporting Mplus program code. We conclude that (a) single-level estimates will not reflect a scale's actual reliability unless reliability is identical at each level of analysis, (b) 2-level alpha and composite reliability (omega) perform relatively well in most settings, (c) estimates of maximal reliability (H) were more biased when estimated using multilevel data than either alpha or omega, and (d) small cluster size can lead to overestimates of reliability at the between level of analysis. We also show that Monte Carlo confidence intervals and Bayesian credible intervals closely reflect the sampling distribution of reliability estimates under most conditions. We discuss the estimation of credible intervals using Mplus and provide R code for computing Monte Carlo confidence intervals.

  1. Spinal appearance questionnaire: factor analysis, scoring, reliability, and validity testing.

    Science.gov (United States)

    Carreon, Leah Y; Sanders, James O; Polly, David W; Sucato, Daniel J; Parent, Stefan; Roy-Beaudry, Marjolaine; Hopkins, Jeffrey; McClung, Anna; Bratcher, Kelly R; Diamond, Beverly E

    2011-08-15

    Cross sectional. This study presents the factor analysis of the Spinal Appearance Questionnaire (SAQ) and its psychometric properties. Although the SAQ has been administered to a large sample of patients with adolescent idiopathic scoliosis (AIS) treated surgically, its psychometric properties have not been fully evaluated. This study presents the factor analysis and scoring of the SAQ and evaluates its psychometric properties. The SAQ and the Scoliosis Research Society-22 (SRS-22) were administered to AIS patients who were being observed, braced or scheduled for surgery. Standard demographic data and radiographic measures including Lenke type and curve magnitude were also collected. Of the 1802 patients, 83% were female; with a mean age of 14.8 years and mean initial Cobb angle of 55.8° (range, 0°-123°). From the 32 items of the SAQ, 15 loaded on two factors with consistent and significant correlations across all Lenke types. There is an Appearance (items 1-10) and an Expectations factor (items 12-15). Responses are summed giving a range of 5 to 50 for the Appearance domain and 5 to 20 for the Expectations domain. The Cronbach's α was 0.88 for both domains and Total score with a test-retest reliability of 0.81 for Appearance and 0.91 for Expectations. Correlations with major curve magnitude were higher for the SAQ Appearance and SAQ Total scores compared to correlations between the SRS Appearance and SRS Total scores. The SAQ and SRS-22 Scores were statistically significantly different in patients who were scheduled for surgery compared to those who were observed or braced. The SAQ is a valid measure of self-image in patients with AIS with greater correlation to curve magnitude than SRS Appearance and Total score. It also discriminates between patients who require surgery from those who do not.

  2. Menstrual Factors,Reproductive Factors and Lung Cancer Risk:A Meta-analysis

    Institute of Scientific and Technical Information of China (English)

    Yue ZHANG; Zhihua YIN; Li SHEN; Yan WAN; Baosen ZHOU

    2012-01-01

    Background and objective Epidemiological studies have suggested that menstrual and reproductive factors may influence lung cancer risk,but the results are controversial.We therefore carried out a meta-analysis aiming to examine the associations of lung cancer in women with menstrual and reproductive factors.Methods Relevant studies were searched from PubMed database,CNKI,WANFANG DATA and VIP INFORMATION up to January 2012,with no language restrictions.References listed from selected papers were also reviewed.We included studies that reported the estimates of relative risks(RRs)with 95% confidence intervals(CIs)for the association between menstrual and reproductive factors and lung cancer risk.The pooled RRs were calculated after the heterogeneity test with the software Stata 11,and publication bias and sensitivity were evaluated at the same time.Results Twenty-five articles,representing 24 independent studies,were included in this meta-analysis.Older age at menarche in North America women(RR=0.83;95%CI:0.73-0.94)was associated with a significant decreased risk of lung cancer.Longer length of menstrual cycle was also associated with decreased lung cancer risk(RR=0.72;95%CI:0.57-0.90).Other exposures were not significantly associated.Conclusions Our analysis provides evidence of the hypothesis that female sex hormones influence the risk of lung cancer in women,yet additional studies are warranted to extend this finding and to clarify the underlying mechanisms.

  3. Replica Analysis for Portfolio Optimization with Single-Factor Model

    Science.gov (United States)

    Shinzato, Takashi

    2017-06-01

    In this paper, we use replica analysis to investigate the influence of correlation among the return rates of assets on the solution of the portfolio optimization problem. We consider the behavior of an optimal solution for the case where the return rate is described with a single-factor model and compare the findings obtained from our proposed methods with correlated return rates with those obtained with independent return rates. We then analytically assess the increase in the investment risk when correlation is included. Furthermore, we also compare our approach with analytical procedures for minimizing the investment risk from operations research.

  4. Determination of selectivity of HPLC systems by correspondence factor analysis

    Institute of Scientific and Technical Information of China (English)

    Yuan Wang; Jun Yang; Xin Lu; Guo Wang Xu

    2007-01-01

    Correspondence factor analysis (CFA) was employed to study the selectivity of 14 HPLC systems, The tested LC systems were classified as reversed-phase (RP), ion-exchange (IE) and hydrophilic interaction chromatography (HILIC) modes. It was found that the retentions of the hydrophilic solutes on HILIC column were significantly influenced by the second-order effects besides their hydrophilic properties. Organic modifiers and residue silanol groups on silica surface both participated in retention. HypersilTM amino column performed separation in the HILIC mode at appropriate conditions, and its retention mechanism was more similar to that of HILIC silica column than that of HILIC column coating poly(aspartamide) groups.

  5. The FIRO model of family therapy: implications of factor analysis.

    Science.gov (United States)

    Hafner, R J; Ross, M W

    1989-11-01

    Schutz's FIRO model contains three main elements: inclusion, control, and affection. It is used widely in mental health research and practice, but has received little empirical validation. The present study is based on factor analysis of the resources to FIRO questionnaire of 120 normal couples and 191 couples who were attending a clinic for marital/psychiatric problems. Results confirmed the validity of the FIRO model for women only. The differences between the sexes reflected a considerable degree of sex-role stereotyping, the clinical implications of which are discussed.

  6. Critical Analysis of Factors Contributing to the Formation of Interlanguage

    Institute of Scientific and Technical Information of China (English)

    赵栩

    2015-01-01

    Interlanguage is a common phenomenon in foreign language learning process.It refers to the language system which is formed in a certain period in learners' second language or foreign language learning process.In the past,behaviorist learning theory and mentalist learning theory has dominated language learning for a long period of time,but both of them have some deficiencies.This paper is to make a critical analysis on the factors contributing to the formation of interlanguage,which reflects the practical importance of interlanguage to language teaching and learning.

  7. Critical Analysis of Factors Contributing to the Formation of Interlanguage

    Institute of Scientific and Technical Information of China (English)

    赵栩

    2015-01-01

    Interlanguage is a common phenomenon in foreign language learning process.It refers to the language system which is formed in a certain period in learners’ second language or foreign language learning process.In the past,behaviorist learning theory and mentalist learning theory has dominated language learning for a long period of time,but both of them have some deficiencies.This paper is to make a critical analysis on the factors contributing to the formation of interlanguage,which reflects the practical importance of interlanguage to language teaching and learning.

  8. Metabolomics

    DEFF Research Database (Denmark)

    Pedersen, Hans

    ) spectroscopy (Paper II), fluorescence spectroscopy (Paper III) and gas chromatography coupled to mass spectrometry (GC-MS). The principles of the three data acquisition techniques have been briefly described and the methods have been compared. The techniques complement each other, which makes room for data...... analysis (PCA), parallel factor analysis (PARAFAC), PARAFAC2 and partial least squares discriminant analysis (PLS-DA) all being described in depth. It can be a challenge to determine the appropriate number of components in PARAFAC2, since no specific tools have been developed for this purpose. Paper I...

  9. Analysis of significant factors for dengue fever incidence prediction.

    Science.gov (United States)

    Siriyasatien, Padet; Phumee, Atchara; Ongruk, Phatsavee; Jampachaisri, Katechan; Kesorn, Kraisak

    2016-04-16

    Many popular dengue forecasting techniques have been used by several researchers to extrapolate dengue incidence rates, including the K-H model, support vector machines (SVM), and artificial neural networks (ANN). The time series analysis methodology, particularly ARIMA and SARIMA, has been increasingly applied to the field of epidemiological research for dengue fever, dengue hemorrhagic fever, and other infectious diseases. The main drawback of these methods is that they do not consider other variables that are associated with the dependent variable. Additionally, new factors correlated to the disease are needed to enhance the prediction accuracy of the model when it is applied to areas of similar climates, where weather factors such as temperature, total rainfall, and humidity are not substantially different. Such drawbacks may consequently lower the predictive power for the outbreak. The predictive power of the forecasting model-assessed by Akaike's information criterion (AIC), Bayesian information criterion (BIC), and the mean absolute percentage error (MAPE)-is improved by including the new parameters for dengue outbreak prediction. This study's selected model outperforms all three other competing models with the lowest AIC, the lowest BIC, and a small MAPE value. The exclusive use of climate factors from similar locations decreases a model's prediction power. The multivariate Poisson regression, however, effectively forecasts even when climate variables are slightly different. Female mosquitoes and seasons were strongly correlated with dengue cases. Therefore, the dengue incidence trends provided by this model will assist the optimization of dengue prevention. The present work demonstrates the important roles of female mosquito infection rates from the previous season and climate factors (represented as seasons) in dengue outbreaks. Incorporating these two factors in the model significantly improves the predictive power of dengue hemorrhagic fever forecasting

  10. Information technology portfolio in supply chain management using factor analysis

    Directory of Open Access Journals (Sweden)

    Ahmad Jaafarnejad

    2013-11-01

    Full Text Available The adoption of information technology (IT along with supply chain management (SCM has become increasingly a necessity among most businesses. This enhances supply chain (SC performance and helps companies achieve the organizational competitiveness. IT systems capture and analyze information and enable management to make decisions by considering a global scope across the entire SC. This paper reviews the existing literature on IT in SCM and considers pertinent criteria. Using principal component analysis (PCA of factor analysis (FA, a number of related criteria are divided into smaller groups. Finally, SC managers can develop an IT portfolio in SCM using mean values of few extracted components on the relevance –emergency matrix. A numerical example is provided to explain details of the proposed method.

  11. Analysis of Factors Affecting Inflation in Indonesia: an Islamic Perspective

    Directory of Open Access Journals (Sweden)

    Elis Ratna Wulan

    2015-04-01

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

  12. Comprehensive analysis of plant rapid alkalization factor (RALF) genes.

    Science.gov (United States)

    Sharma, Arti; Hussain, Adil; Mun, Bong-Gyu; Imran, Qari Muhammad; Falak, Noreen; Lee, Sang-Uk; Kim, Jae Young; Hong, Jeum Kyu; Loake, Gary John; Ali, Asad; Yun, Byung-Wook

    2016-09-01

    Receptor mediated signal carriers play a critical role in the regulation of plant defense and development. Rapid alkalization factor (RALF) proteins potentially comprise important signaling components which may have a key role in plant biology. The RALF gene family contains large number of genes in several plant species, however, only a few RALF genes have been characterized to date. In this study, an extensive database search identified 39, 43, 34 and 18 RALF genes in Arabidopsis, rice, maize and soybean, respectively. These RALF genes were found to be highly conserved across the 4 plant species. A comprehensive analysis including the chromosomal location, gene structure, subcellular location, conserved motifs, protein structure, protein-ligand interaction and promoter analysis was performed. RALF genes from four plant species were divided into 7 groups based on phylogenetic analysis. In silico expression analysis of these genes, using microarray and EST data, revealed that these genes exhibit a variety of expression patterns. Furthermore, RALF genes showed distinct expression patterns of transcript accumulation in vivo following nitrosative and oxidative stresses in Arabidopsis. Predicted interaction between RALF and heme ligand also showed that RALF proteins may contribute towards transporting or scavenging oxygen moieties. This suggests a possible role for RALF genes during changes in cellular redox status. Collectively, our data provides a valuable resource to prime future research in the role of RALF genes in plant growth and development.

  13. Confirmatory Factor Analysis of the ISB - Burnout Syndrome Inventory

    Directory of Open Access Journals (Sweden)

    Ana Maria T. Benevides-Pereira

    2017-05-01

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

  14. Difficult mask ventilation in obese patients: analysis of predictive factors.

    Science.gov (United States)

    Leoni, A; Arlati, S; Ghisi, D; Verwej, M; Lugani, D; Ghisi, P; Cappelleri, G; Cedrati, V; El Tantawi Ali Alsheraei, A; Pocar, M; Ceriani, V; Aldegheri, G

    2014-02-01

    This study aimed to determine the accuracy of commonly used preoperative difficult airway indices as predictors of difficult mask ventilation (DMV) in obese patients (BMI >30 kg/m2). In 309 consecutive obese patients undergoing general surgery, the modified Mallampati test, patient's Height/Thyromental distance ratio, Inter-Incisor Distance, Protruding Mandible (PM), history of Obstructive Sleep Apnea and Neck Circumference (NC) were recorded preoperatively. DMV was defined as Grade 3 mask ventilation (MV) by the Han's scale (MV inadequate, unstable or requiring two practitioners). Data are shown as means±SD or number and proportions. Independent DMV predictors were identified by multivariate analysis. The discriminating capacity of the model (ROC curve area) and adjusted weights for the risk factors (odds ratios) were also determined. BMI averaged 42.5±8.3 kg/m2. DMV was reported in 27 out of 309 patients (8.8%; 95%CI 5.6-11.9%). The multivariate analysis retained NC (OR 1.17; P2 associated factors as the best discriminating point for DMV. Obese patients show increased incidence of DMV with respect to the undifferentiated surgical population. Limited PM, Mallampati test and NC are important DMV predictors.

  15. Determining the Number of Factors to Retain in an Exploratory Factor Analysis Using Comparison Data of Known Factorial Structure

    Science.gov (United States)

    Ruscio, John; Roche, Brendan

    2012-01-01

    Exploratory factor analysis (EFA) is used routinely in the development and validation of assessment instruments. One of the most significant challenges when one is performing EFA is determining how many factors to retain. Parallel analysis (PA) is an effective stopping rule that compares the eigenvalues of randomly generated data with those for…

  16. Analysis of transfer reactions: determination of spectroscopic factors

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-07-01

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

  17. A Demonstration of the Impact of Outliers on the Decisions about the Number of Factors in Exploratory Factor Analysis

    Science.gov (United States)

    Liu, Yan; Zumbo, Bruno D.; Wu, Amery D.

    2012-01-01

    Previous studies have rarely examined the impact of outliers on the decisions about the number of factors to extract in an exploratory factor analysis. The few studies that have investigated this issue have arrived at contradictory conclusions regarding whether outliers inflated or deflated the number of factors extracted. By systematically…

  18. Factor Structure of the Student-Teacher Relationship Scale for Norwegian School-Age Children Explored with Confirmatory Factor Analysis

    Science.gov (United States)

    Drugli, May Britt; Hjemdal, Odin

    2013-01-01

    The validity of the Student-Teacher Relationship Scale (STRS) was examined in a national sample of 863 Norwegian schoolchildren in grades 1-7 (aged 6-13). The original factor structure of the STRS was tested by confirmatory factor analysis (CFA). The CFA results did not support the original three-factor structure of the STRS. Subsequent CFA of the…

  19. [Analysis of predisposing factors for pancreatic fistula after pancreaticoduodenectomy].

    Science.gov (United States)

    Chen, You-yi; Sun, Bei; Jiang, Hong-chi

    2013-08-01

    To analyze the predisposing factors for pancreatic fistula after pancreaticoduodenectomy. The clinical data of 323 patients undergoing pancreaticoduodenectomy from January 2007 to March 2012 were analyzed retrospectively. There were 185 male and 138 female patients, aging from 27 to 82 years. All the patients were devided into pancreatic fistula group (n = 52) and non-pancreatic fistula group (n = 271). Twenty variables, such as age, sex, primary disease, alcohol abuse, cholangitis, bilirubin, albumin, hemoglobin, operating time, blood loss, transfusion, texture of the remnant pancreas, diameter of wirsung, drainages of pancreatic duct, specialized group which potentially affect the incidence, were analyzed by t test for continuous variables and χ(2) test for discrete variables. The variables with significance (P fistula rate was 16.1% (52/323), 7 patients died for pancreatic fistula PF. In univariate analysis, primary disease, preoperative high bilirubin level, intraoperative blood loss and transfusion, texture of the remnant pancreas, diameter of wirsung, drainages of pancreatic duct, specialized group had significant difference between two groups (χ(2) = 4.072 to 9.008, P analysis revealed that primary disease (OR = 2.091, P = 0.001), texture of the remnant pancreas (OR = 7.715, P = 0.040), diameter of wirsung (OR = 5.405, P = 0.006), pancreatic duct stent (OR = 4.313, P = 0.001) and specialized group (OR = 6.404, P = 0.006) were independent risk factors in pancreatic fistula. Primary disease, texture of the remnant pancreas, diameter of wirsung, pancreatic duct stent and specialized group are independent risk factors in pancreatic fistula. With the purpose of decreasing pancreatic fistula rate after PD, it is necessary to operate meticulously and precisely, place external pancreatic duct stent and establish pancreatic center or specialized group.

  20. Factors affecting the concentrations of heavy metals in precipitation of Tehran using factor analysis method

    Directory of Open Access Journals (Sweden)

    H Kamani

    2016-03-01

    Full Text Available Backgrounds and Objectives: Quantity of trace metals in the wet precipitation can illustrate the environmental pollution of different urban areas. Up to now, there is no study regarding the chemistry of wet precipitation in Tehran .The objectives of this study are: measurement of heavy metal concentrations and identification of the main factors affecting the heavy metal concentrations in wet precipitation using factor analysis method. Materials and Methods: This was a cross-sectional study in which measurements of heavy metals were performed in 53 wet precipitation samples collected from a central site of Tehran City, capital of Iran. The samples were collected during November to May in 2010, 2011 and 2012 on the roof of the student’s dormitory building of Tehran University of Medical Sciences and then the concentration of heavy metals in each sample was measured with ICP-MS. Results: pH ranged from 4.2 to 7.1 with a mean value of 5.1 indicating in acidic range. Result of EF calculations revealed that samples were not enriched with Fe and Cr but were enriched with Zn, Cd, Ni, Pb and Cu. Factor Component Analysis with Varimax normalized rotation showed Al, Fe and Cr are originated from crustal source and Zn, Cd, Ni, Pb and Cu are originated from anthropogenic sources.  Conclusion: EF and acidic pH values indicate Tehran is under the influence of extremely anthropogenic activities. Large number of vehicles and industrial activity in the city are undoubtedly responsible for the emission of a wide range of pollution.

  1. Determination of volatile organic compounds pollution sources in malaysian drinking water using multivariate analysis.

    Science.gov (United States)

    Soh, Shiau-Chian; Abdullah, Md Pauzi

    2007-01-01

    A field investigation was conducted at all water treatment plants throughout 11 states and Federal Territory in Peninsular Malaysia. The sampling points in this study include treatment plant operation, service reservoir outlet and auxiliary outlet point at the water pipelines. Analysis was performed by solid phase micro-extraction technique with a 100 microm polydimethylsiloxane fibre using gas chromatography with mass spectrometry detection to analyse 54 volatile organic compounds (VOCs) of different chemical families in drinking water. The concentration of VOCs ranged from undetectable to 230.2 microg/l. Among all of the VOCs species, chloroform has the highest concentration and was detected in all drinking water samples. Average concentrations of total trihalomethanes (THMs) were almost similar among all states which were in the range of 28.4--33.0 microg/l. Apart from THMs, other abundant compounds detected were cis and trans-1,2-dichloroethylene, trichloroethylene, 1,2-dibromoethane, benzene, toluene, ethylbenzene, chlorobenzene, 1,4-dichlorobenzene and 1,2-dichloro - benzene. Principal component analysis (PCA) with the aid of varimax rotation, and parallel factor analysis (PARAFAC) method were used to statistically verify the correlation between VOCs and the source of pollution. The multivariate analysis pointed out that the maintenance of auxiliary pipelines in the distribution systems is vital as it can become significant point source pollution to Malaysian drinking water.

  2. Multivariate Analysis of Clinical Factors in Restenosis after Coronary Stenting

    Institute of Scientific and Technical Information of China (English)

    Wen Shangyu; Mao Jieming; Guo Liiun; Zhao Yiming; Zhang Fuchun; Guo Jingxlan; Cheng Mingzhe

    2000-01-01

    Ojbective To find the independent predictors for restenosis after coronary stenting.Methods Quantitative angiography was performed on 60 cases (67 successfully dilated lesions) after angioplasty over 6-months follow-up, and both univariate and multivariate logistic regression analysis were done to identify the correlations of restenosis with clinical factors. Results The total restenosis rate was 31.3%(21 of 67 lesions), and according to univariate analysis the patients who underwent coronary stenting ≥3.5mm had a lower rate of restenosis ( P < 0. 01).Collateral circulation to the obstruction site, high maximal inflation pressure, smoking and the less minimal lumen diameter after PTCA made the rate of restenosis higherower ( P < 0.05) . Multivariate logistic regression analysis showed that coronary stenting ≥ 3.5mm had a low rate of restenosis, but high maximal inflation pressure and smoking made the restenosis rate higher. Conclusion Coronary stent size, maximal inflation pressure and. smoking were independent predictors for restenosis.

  3. Analysis of Entrepreneurship barriers in Moravia-Silesian Region by VRIO and Factor analysis application

    OpenAIRE

    Šebestová, Jarmila

    2007-01-01

    The small and medium sized entrepreneurship is often considered to be as a phenomenon of our times. Why many authors dedicated their work on this field? The main reason is that SME make influence on society life and contribute to economic development of the region, where they establish their business. The same situation is in Moravia-Silesian region, where the fac-tor analysis being applied. VRIO and Porter's analysis were used to interpret clearly research findings.

  4. Spatial Dependence and Heterogeneity in Bayesian Factor Analysis : A Cross-National Investigation of Schwartz Values

    NARCIS (Netherlands)

    Stakhovych, Stanislav; Bijmolt, Tammo H. A.; Wedel, Michel

    2012-01-01

    In this article, we present a Bayesian spatial factor analysis model. We extend previous work on confirmatory factor analysis by including geographically distributed latent variables and accounting for heterogeneity and spatial autocorrelation. The simulation study shows excellent recovery of the

  5. Dispersive analysis of the scalar form factor of the nucleon

    CERN Document Server

    Hoferichter, M; Kubis, B; Meißner, U -G

    2012-01-01

    Based on the recently proposed Roy-Steiner equations for pion-nucleon scattering, we derive a system of coupled integral equations for the pi pi --> N-bar N and K-bar K --> N-bar N S-waves. These equations take the form of a two-channel Muskhelishvili-Omnes problem, whose solution in the presence of a finite matching point is discussed. We use these results to update the dispersive analysis of the scalar form factor of the nucleon fully including K-bar K intermediate states. In particular, we determine the correction Delta_sigma=sigma(2M_pi^2)-sigma_{pi N}, which is needed for the extraction of the pion-nucleon sigma term from pi N scattering, as a function of pion-nucleon subthreshold parameters and the pi N coupling constant.

  6. Theory of sampling: four critical success factors before analysis.

    Science.gov (United States)

    Wagner, Claas; Esbensen, Kim H

    2015-01-01

    Food and feed materials characterization, risk assessment, and safety evaluations can only be ensured if QC measures are based on valid analytical data, stemming from representative samples. The Theory of Sampling (TOS) is the only comprehensive theoretical framework that fully defines all requirements to ensure sampling correctness and representativity, and to provide the guiding principles for sampling in practice. TOS also defines the concept of material heterogeneity and its impact on the sampling process, including the effects from all potential sampling errors. TOS's primary task is to eliminate bias-generating errors and to minimize sampling variability. Quantitative measures are provided to characterize material heterogeneity, on which an optimal sampling strategy should be based. Four critical success factors preceding analysis to ensure a representative sampling process are presented here.

  7. MULTIDIMENSIONAL RELIABILITY OF INSTRUMENT STUDENTS’ SATISFACTION USING CONFIRMATORY FACTOR ANALYSIS

    Directory of Open Access Journals (Sweden)

    Gaguk Margono

    2014-11-01

    Full Text Available The purpose of this paper is to compare unidimensional reliability and multidimensional reliability of instrument students’ satisfaction as an internal costumer. Multidimensional reliability measurement is rarely used in the field of research. Multidimensional reliability is estimated by using Confirmatory Factor Analysis (CFA on the Structural Equation Model (SEM. Measurements and calculations are described in this article using instrument students’ satisfaction as an internal costumer. Survey method used in this study and sampling used simple random sampling. This instrument has been tried out to 173 students. The result is concluded that the measuringinstrument of students’ satisfaction as an internal costumer by using multidimensional reliability coefficient has higher accuracy when compared with a unidimensional reliability coefficient. Expected in advanced research used another formula multidimensional reliability, including when using SEM.

  8. Bayesian analysis of factors associated with fibromyalgia syndrome subjects

    Science.gov (United States)

    Jayawardana, Veroni; Mondal, Sumona; Russek, Leslie

    2015-01-01

    Factors contributing to movement-related fear were assessed by Russek, et al. 2014 for subjects with Fibromyalgia (FM) based on the collected data by a national internet survey of community-based individuals. The study focused on the variables, Activities-Specific Balance Confidence scale (ABC), Primary Care Post-Traumatic Stress Disorder screen (PC-PTSD), Tampa Scale of Kinesiophobia (TSK), a Joint Hypermobility Syndrome screen (JHS), Vertigo Symptom Scale (VSS-SF), Obsessive-Compulsive Personality Disorder (OCPD), Pain, work status and physical activity dependent from the "Revised Fibromyalgia Impact Questionnaire" (FIQR). The study presented in this paper revisits same data with a Bayesian analysis where appropriate priors were introduced for variables selected in the Russek's paper.

  9. Statistical Analysis of Factors Affecting Child Mortality in Pakistan.

    Science.gov (United States)

    Ahmed, Zoya; Kamal, Asifa; Kamal, Asma

    2016-06-01

    Child mortality is a composite indicator reflecting economic, social, environmental, healthcare services, and their delivery situation in a country. Globally, Pakistan has the third highest burden of fetal, maternal, and child mortality. Factors affecting child mortality in Pakistan are investigated by using Binary Logistic Regression Analysis. Region, education of mother, birth order, preceding birth interval (the period between the previous child birth and the index child birth), size of child at birth, and breastfeeding and family size were found to be significantly important with child mortality in Pakistan. Child mortality decreased as level of mother's education, preceding birth interval, size of child at birth, and family size increased. Child mortality was found to be significantly higher in Balochistan as compared to other regions. Child mortality was low for low birth orders. Child survival was significantly higher for children who were breastfed as compared to those who were not.

  10. Accelerated Gibbs Sampling for Infinite Sparse Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Andrzejewski, D M

    2011-09-12

    The Indian Buffet Process (IBP) gives a probabilistic model of sparse binary matrices with an unbounded number of columns. This construct can be used, for example, to model a fixed numer of observed data points (rows) associated with an unknown number of latent features (columns). Markov Chain Monte Carlo (MCMC) methods are often used for IBP inference, and in this technical note, we provide a detailed review of the derivations of collapsed and accelerated Gibbs samplers for the linear-Gaussian infinite latent feature model. We also discuss and explain update equations for hyperparameter resampling in a 'full Bayesian' treatment and present a novel slice sampler capable of extending the accelerated Gibbs sampler to the case of infinite sparse factor analysis by allowing the use of real-valued latent features.

  11. [Rhabdomyolysis in a Bipolar Adolescent. Analysis of Associated Factors].

    Science.gov (United States)

    Restrepo, Diana; Montoya, Pablo; Giraldo, Laura; Gaviria, Génesis; Mejía, Catalina

    2015-01-01

    To describe a case of rhabdomyolysis associated with the use of quetiapine and lamotrigine in an adolescent treated for bipolar disorder. Description of the clinical case, analysis of the associated factors and a non-systematic review of the relevant literature. An 18 year old male, with bipolar disorder and treated pharmacologically with quetiapine and lamotrigine, after two weeks of physical activity presents with rhabdomyolysis. Quetiapine and exercise have been associated with rhabdomyolysis. The mediator mechanism of this association has not been found, although it has been established that there is neuromuscular dysfunction and an increase in sarcomere permeability. This clinical case allowed the complex interaction between antipsychotic agents and increased physical activity to be observed in a psychiatric adolescent patient, as well as the appearance of a potentially lethal medical complication. Copyright © 2014 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

  12. [Cephalometric standards of adult Greeks (Ricketts' ten factor analysis)].

    Science.gov (United States)

    Kavadia, S; Topouzelis, N; Sidiropoulou, S; Markovitsi, H; Kolokythas, G

    1989-09-01

    In this study the ten factors which compose the Ricketts' summary analysis were measured on 81 lateral skull radiographs of adult Greeks (41 males and 40 females) with normal occlusion and harmonious face to establish cephalometric standards. The mean value, standard deviation, standard error of the mean, minimum and maximum values as well as the range of each variable were found and discussed for each sex separately as well as for the whole sample. The main conclusion of the study is that adult Greeks with normal occlusion and harmonious face present: a tendency to the brachy facial vertical type, a small retroposition of the maxilla and of the lower lip and prominent and labialy proclined lower incisors.

  13. Expression analysis of TALE family transcription factors during avian development.

    Science.gov (United States)

    Coy, Sarah E; Borycki, Anne-Gaëlle

    2010-04-01

    The TALE family of homeodomain containing transcription factors consists of the Meis, Prep and Tgif, and the Pbx subfamily of proteins. Several TALE orthologues have been identified in amniotes, but no comprehensive analysis of their expression pattern during embryogenesis has been performed. Here, we report on TALE gene expression in the avian embryo. During embryonic development, Pbx genes are predominantly expressed in the neural ectoderm and paraxial mesoderm, although Pbx3 is restricted to the intermediate and lateral mesoderm, and anterior central nervous system. Members of the Meis, Prep, and Tgif subfamilies are expressed at high levels in the paraxial mesoderm, and display differential expression along the anterior-posterior and dorsoventral axes of the developing neural tube. Overall the expression patterns reported in this study are consistent with the known function of the TALE gene family in controlling early patterning of limb, neural tube and paraxial mesoderm tissues during embryogenesis.

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

    Science.gov (United States)

    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,…

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

    Science.gov (United States)

    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,…

  16. Dynamic factor analysis for estimating ground water arsenic trends.

    Science.gov (United States)

    Kuo, Yi-Ming; Chang, Fi-John

    2010-01-01

    Drinking ground water containing high arsenic (As) concentrations has been associated with blackfoot disease and the occurrence of cancer along the southwestern coast of Taiwan. As a result, 28 ground water observation wells were installed to monitor the ground water quality in this area. Dynamic factor analysis (DFA) is used to identify common trends that represent unexplained variability in ground water As concentrations of decommissioned wells and to investigate whether explanatory variables (total organic carbon [TOC], As, alkalinity, ground water elevation, and rainfall) affect the temporal variation in ground water As concentration. The results of the DFA show that rainfall dilutes As concentration in areas under aquacultural and agricultural use. Different combinations of geochemical variables (As, alkalinity, and TOC) of nearby monitoring wells affected the As concentrations of the most decommissioned wells. Model performance was acceptable for 11 wells (coefficient of efficiency >0.50), which represents 52% (11/21) of the decommissioned wells. Based on DFA results, we infer that surface water recharge may be effective for diluting the As concentration, especially in the areas that are relatively far from the coastline. We demonstrate that DFA can effectively identify the important factors and common effects representing unexplained variability common to decommissioned wells on As variation in ground water and extrapolate information from existing monitoring wells to the nearby decommissioned wells.

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

    Science.gov (United States)

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

    2015-01-01

    Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance,…

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

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    Bruce Weaver

    2014-09-01

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

  19. Weightlifter Lumbar Physiology Health Influence Factor Analysis of Sports Medicine.

    Science.gov (United States)

    Zhang, Xiangyang

    2015-01-01

    Chinese women's weightlifting project has been in the advanced world level, suggests that the Chinese coaches and athletes have many successful experience in the weight lifting training. Little weight lifting belongs to high-risk sports, however, to the lumbar spine injury, some young good athletes often due to lumbar trauma had to retire, and the national investment and athletes toil is regret things. This article from the perspective of sports medicine, weightlifting athletes training situation analysis and put forward Suggestions, aimed at avoiding lumbar injury, guarantee the health of athletes. In this paper, first of all to 50 professional women's weightlifting athletes doing investigation, found that 82% of the athletes suffer from lumbar disease symptoms, the reason is mainly composed of lumbar strain, intensity is too large, motion error caused by three factors. From the Angle of sports medicine and combined with the characteristics of the structure of human body skeleton athletes lumbar structural mechanics analysis, find out the lumbar force's two biggest technical movement, study, and regulate the action standard, so as to minimize lumbar force, for athletes to contribute to the health of the lumbar spine.

  20. Efficiency limit factor analysis for the Francis-99 hydraulic turbine

    Science.gov (United States)

    Zeng, Y.; Zhang, L. X.; Guo, J. P.; Guo, Y. K.; Pan, Q. L.; Qian, J.

    2017-01-01

    The energy loss in hydraulic turbine is the most direct factor that affects the efficiency of the hydraulic turbine. Based on the analysis theory of inner energy loss of hydraulic turbine, combining the measurement data of the Francis-99, this paper calculates characteristic parameters of inner energy loss of the hydraulic turbine, and establishes the calculation model of the hydraulic turbine power. Taken the start-up test conditions given by Francis-99 as case, characteristics of the inner energy of the hydraulic turbine in transient and transformation law are researched. Further, analyzing mechanical friction in hydraulic turbine, we think that main ingredients of mechanical friction loss is the rotation friction loss between rotating runner and water body, and defined as the inner mechanical friction loss. The calculation method of the inner mechanical friction loss is given roughly. Our purpose is that explore and research the method and way increasing transformation efficiency of water flow by means of analysis energy losses in hydraulic turbine.

  1. Characterizing the interaction between uranyl ion and fulvic acid using regional integration analysis (RIA) and fluorescence quenching.

    Science.gov (United States)

    Zhu, Bingqi; Ryan, David K

    2016-03-01

    The development of chemometric methods has substantially improved the quantitative usefulness of the fluorescence excitation-emission matrix (EEM) in the analysis of dissolved organic matter (DOM). In this study, Regional Integration Analysis (RIA) was used to quantitatively interpret EEMs and assess fluorescence quenching behavior in order to study the binding between uranyl ion and fulvic acid. Three fulvic acids including soil fulvic acid (SFA), Oyster River fulvic acid (ORFA) and Suwannee River fulvic acid (SRFA) were used and investigated by the spectroscopic techniques. The EEM spectra obtained were divided into five regions according to fluorescence structural features and two distinct peaks were observed in region III and region V. Fluorescence quenching analysis was conducted for these two regions with the stability constants, ligand concentrations and residual fluorescence values calculated using the Ryan-Weber model. Results indicated a relatively strong binding ability between uranyl ion and fulvic acid samples at low pH (log K value varies from 4.11 to 4.67 at pH 3.50). Fluorophores in region III showed a higher binding ability with fewer binding sites than in region V. Stability constants followed the order, SFA > ORFA > SRFA, while ligand concentrations followed the reverse order, SRFA > ORFA > SFA. A comparison between RIA and Parallel Factor Analysis (PARAFAC) data treatment methods was also performed and good agreement between these two methods (less than 4% difference in log K values) demonstrates the reliability of the RIA method in this study.

  2. Selection of Variables in Exploratory Factor Analysis: An Empirical Comparison of a Stepwise and Traditional Approach

    Science.gov (United States)

    Hogarty, Kristine Y.; Kromrey, Jeffrey D.; Ferron, John M.; Hines, Constance V.

    2004-01-01

    The purpose of this study was to investigate and compare the performance of a stepwise variable selection algorithm to traditional exploratory factor analysis. The Monte Carlo study included six factors in the design; the number of common factors; the number of variables explained by the common factors; the magnitude of factor loadings; the number…

  3. Connections between Graphical Gaussian Models and Factor Analysis

    Science.gov (United States)

    Salgueiro, M. Fatima; Smith, Peter W. F.; McDonald, John W.

    2010-01-01

    Connections between graphical Gaussian models and classical single-factor models are obtained by parameterizing the single-factor model as a graphical Gaussian model. Models are represented by independence graphs, and associations between each manifest variable and the latent factor are measured by factor partial correlations. Power calculations…

  4. Recovery of weak factor loadings when adding the mean structure in confirmatory factor analysis: A simulation study

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    Carmen eXiménez

    2016-01-01

    Full Text Available This article extends previous research on the recovery of weak factor loadings in confirmatory factor analysis by exploring the effects of adding the mean structure. This issue has not been examined in previous research. This study is based on the framework of Yung and Bentler (1999 and aims to examine the conditions that affect the recovery of weak factor loadings when the model includes the mean structure, compared to analyzing the covariance structure alone. A simulation study was conducted in which several constraints were defined for one-, two-, and three-factor models. Results show that adding the mean structure improves the recovery of weak factor loadings and reduces the asymptotic variances for the factor loadings, particularly for the models with a smaller number of factors and a small sample size. Therefore, under certain circumstances, modeling the means should be seriously considered for covariance models containing weak factor loadings.

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

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    Hee-Ju Kim, PhD, RN

    2008-03-01

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

  6. Hypersensitivity reactions to fluoroquinolones: analysis of the factors involved.

    Science.gov (United States)

    Blanca-López, N; Ariza, A; Doña, I; Mayorga, C; Montañez, M I; Garcia-Campos, J; Gomez, F; Rondón, C; Blanca, M; Torres, M J

    2013-05-01

    Hypersensitivity reactions to fluoroquinolones seem to be on the increase, especially immediate type reactions. The aim of this study was to determine whether several conditions, including gender, age, type of reaction, time interval between the reaction and the study, type of symptoms, the specific fluoroquinolone involved in the reaction and previous confirmed hypersensitivity to betalactams or to other drugs were factors contributing to the development of hypersensitivity to fluoroquinolones. We analysed retrospectively all patients attending our allergy department between January 2005 and December 2010 because of a reaction associated with fluoroquinolone administration. The diagnosis was confirmed by basophil activation test or drug provocation tests. In accordance with the results, patients were then classified as having hypersensitivity or non-hypersensitivity to fluoroquinolones. A group of 218 patients was evaluated; 69 were confirmed as having hypersensitivity, 146 as non-hypersensitivity and 3 were excluded. Comparisons between groups showed that the allergic patients more often had a previous confirmed hypersensitivity to betalactams (P = 0.029), immediate reactions (P = 0.001) and anaphylaxis (P = 0.000), and moxifloxacin was the fluoroquinolone most frequently involved (P = 0.027). The logistic regression analysis showed three factors associated with the diagnosis of hypersensitivity reactions to fluoroquinolones: previous hypersensitivity to betalactams (OR: 4.571; 95% CI: 0.987-21.171; adjusted OR: 23.654; 95% CI: 1.529-365.853), immediate reactions (OR: 17.333; 95% CI: 4.374-68.691; adjusted OR: 52.493; 95% CI: 6.621-416.200) and reactions induced by moxifloxacin (OR: 3.091; 95% CI: 1.160-8.239; adjusted OR: 13.610; 95% CI: 2.419-76.565). In patients who develop reactions to fluoroquinolones, hypersensitivity is more often confirmed in those with immediate reactions and when moxifloxacin is involved. Moreover, patients with hypersensitivity to

  7. Comprehensive Behavioral Analysis of Activating Transcription Factor 5-Deficient Mice.

    Science.gov (United States)

    Umemura, Mariko; Ogura, Tae; Matsuzaki, Ayako; Nakano, Haruo; Takao, Keizo; Miyakawa, Tsuyoshi; Takahashi, Yuji

    2017-01-01

    Activating transcription factor 5 (ATF5) is a member of the CREB/ATF family of basic leucine zipper transcription factors. We previously reported that ATF5-deficient (ATF5(-/-)) mice demonstrated abnormal olfactory bulb development due to impaired interneuron supply. Furthermore, ATF5(-/-) mice were less aggressive than ATF5(+/+) mice. Although ATF5 is widely expressed in the brain, and involved in the regulation of proliferation and development of neurons, the physiological role of ATF5 in the higher brain remains unknown. Our objective was to investigate the physiological role of ATF5 in the higher brain. We performed a comprehensive behavioral analysis using ATF5(-/-) mice and wild type littermates. ATF5(-/-) mice exhibited abnormal locomotor activity in the open field test. They also exhibited abnormal anxiety-like behavior in the light/dark transition test and open field test. Furthermore, ATF5(-/-) mice displayed reduced social interaction in the Crawley's social interaction test and increased pain sensitivity in the hot plate test compared with wild type. Finally, behavioral flexibility was reduced in the T-maze test in ATF5(-/-) mice compared with wild type. In addition, we demonstrated that ATF5(-/-) mice display disturbances of monoamine neurotransmitter levels in several brain regions. These results indicate that ATF5 deficiency elicits abnormal behaviors and the disturbance of monoamine neurotransmitter levels in the brain. The behavioral abnormalities of ATF5(-/-) mice may be due to the disturbance of monoamine levels. Taken together, these findings suggest that ATF5(-/-) mice may be a unique animal model of some psychiatric disorders.

  8. Analysis of factors associated with excess weight in school children

    Science.gov (United States)

    Pinto, Renata Paulino; Nunes, Altacílio Aparecido; de Mello, Luane Marques

    2016-01-01

    Abstract Objective: To determine the prevalence of overweight and obesity in schoolchildren aged 10 to 16 years and its association with dietary and behavioral factors. Methods: Cross-sectional study that evaluated 505 adolescents using a structured questionnaire and anthropometric data. The data was analyzed through the T Test for independent samples and Mann-Whitney Test to compare means and medians, respectively, and Chi2 Test for proportions. Prevalence ratio (RP) and the 95% confidence interval was used to estimate the degree of association between variables. The logistic regression was employed to adjust the estimates to confounding factors. The significance level of 5% was considered for all analysis. Results: Excess weight was observed in 30.9% of the schoolchildren: 18.2% of overweight and 12.7% of obesity. There was no association between weight alterations and dietary/behavioral habits in the bivariate and multivariate analyses. However, associations were observed in relation to gender. Daily consumption of sweets [PR=0.75 (0.64-0.88)] and soft drinks [PR=0.82 (0.70-0.97)] was less frequent among boys; having lunch daily was slightly more often reported by boys [OR=1.11 (1.02-1.22)]. Physical activity practice of (≥3 times/week) was more often mentioned by boys and the association measures disclosed two-fold more physical activity in this group [PR=2.04 (1.56-2.67)] when compared to girls. Approximately 30% of boys and 40% of girls stated they did not perform activities requiring energy expenditure during free periods, with boys being 32% less idle than girls [PR=0.68 (0.60-0.76)]. Conclusions: A high prevalence of both overweight and obesity was observed, as well as unhealthy habits in the study population, regardless of the presence of weight alterations. Health promotion strategies in schools should be encouraged, in order to promote healthy habits and behaviors among all students. PMID:27321919

  9. Factors influencing crime rates: an econometric analysis approach

    Science.gov (United States)

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

    2016-05-01

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

  10. FACTOR 9.2: A Comprehensive Program for Fitting Exploratory and Semiconfirmatory Factor Analysis and IRT Models

    Science.gov (United States)

    Lorenzo-Seva, Urbano; Ferrando, Pere J.

    2013-01-01

    FACTOR 9.2 was developed for three reasons. First, exploratory factor analysis (FA) is still an active field of research although most recent developments have not been incorporated into available programs. Second, there is now renewed interest in semiconfirmatory (SC) solutions as suitable approaches to the complex structures are commonly found…

  11. Analysis of nomofobic behaviors of adolescents regarding various factors

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    Deniz Mertkan Gezgin

    2016-05-01

    Full Text Available Although the developments in technology have made our lives and daily activities easier, it is believed that problematic and excessive use of technology could have some negative effects on people. One of these negative effects is the prevalence of nomophobia, which is considered as a new phobia in recent years. Nomophobia is defined as the fear and anxiety when an individual cannot access his or her mobile/smart phone or cannot have the chance to communicate online and offline via mobile devices. Nomophobic tendencies can change individuals’ daily habits. Negative emotions due to nomophobic tendencies like fear and anxiety especially in young people is thought to affect their school lives and academic achievements. The purpose of this research is to analyze the prevalence of nomophobia among high school students regarding various factors. The Nomophobia Scale (NMP-Q, which was used in this study, was developed by Yildirim and Correia (2015, and adapted into Turkish by Yildirim, Sumuer, Adnan and Yildirim (2015. The study group consists of 475 high school students attending six different schools situated in diverse socio-economic areas in Izmir and Edirne in 2015-2016 education year. The study was conducted in survey model and descriptive statistics. T-test for independent samples and one-way analysis of variance (ANOVA techniques were used at the analysis stage. According to the findings, mean scores obtained from the scale demonstrated that the levels of nomophobic behaviors of high school students were above the average. Besides, female students have higher nomophobia levels compared to male students in terms of gender variable and a significant difference was found in terms of the duration of mobile internet usage. A significant difference could not be found in terms of the variables such as grade, parents’ education levels, and the duration of smartphone usage. Furthermore, the study has revealed that high school students use their

  12. Analysis of cultural development of Isfahan city Using Factor analysis method

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    J.Mohammadi

    2013-01-01

    Full Text Available Extended abstract1-IntroductionCultural spaces are consideredas one of the main factors for development. Cultural development is a qualitative and valuable process that for assessing it, quantitative indicators in cultural planning are used to obtain development objectives in the pattern of goods and services. The aim of the study is to determine and analyze cultural development level and regional inequality of different districts of Isfahan using factor analysis technique. The statistical population of the study is 14 districts of Isfahan municipality. The dominant approach ofthis study is quantitative – description and analytical. In this study, 35 indices have been summarized by factor analysis method and have been reduced to 5 factors and combined in significant ones and delivered.2 – Theoretical basesThe most important objectives of spatial planning, considering limitation of resources, are optimum distributions of facilities and services among different locations in which people live. To do this,there is a need to identify different locations in terms of having different facilities and services, so that developed locations are specified and planners can proceed to do something for spatial equilibrium and reducing privileged distance between districts.The present study has been conducted to reach to an equal development in Isfahan urban districts following identifying the situation and the manner of distributing development facilities cultural selected indices in different districts.3 – DiscussionCultural development of societies is evaluated by considering the changes and improvement of its indices and measured by quantitative frames. Cultural development indices are the most important tools for cultural planning in a special district in a society. In this study, cultural development indices have been used to determine the levels of districts. By using factor analysis model, the share of influential factors in the cultural

  13. Prognostic Factor Analysis of Intraocular Pressure with Neovascular Glaucoma.

    Science.gov (United States)

    Nakano, Satoko; Nakamuro, Takako; Yokoyama, Katsuhiko; Kiyosaki, Kunihiro; Kubota, Toshiaki

    2016-01-01

    Purpose. To perform multivariate analysis for identifying independent predictors of elevated intraocular pressure (IOP) with neovascular glaucoma (NVG), including antivascular endothelial growth factor (VEGF) intravitreal injections. Methods. We retrospectively reviewed 142 NVG patients (181 eyes) with ischemic retinal diseases [proliferative diabetic retinopathy (PDR) in 134 eyes, retinal vein occlusion (RVO) in 29, and ocular ischemic syndrome in 18]. We analyzed age, gender, initial/final LogMAR VA, initial/final IOP, extent of iris and/or angle neovascularization, treatments, preexisting complications, concurrent medications, and follow-up duration. Results. The mean follow-up duration was 23.8 ± 18.8 months. At the final follow-up, 125 (72.3%) eyes had IOP ≤ 21 mmHg. NVG patients with RVO had a higher degree of angle closure and higher IOP. NVG with PDR had better IOP and LogMAR VA. Angle closure had the greatest impact on final IOP. Greater than 90% of patients treated with trabeculectomy with mitomycin C (LEC) had persistent declines in IOP (≤21 mmHg). Stand-alone and combination anti-VEGF therapies were not associated with improved long-term prognosis of IOP. Conclusions. Angle closure was found to have the greatest effect on NVG-IOP prognosis. When target IOP values are not obtained after adequate PRP with or without anti-VEGF, early LEC may improve the prognosis of IOP.

  14. Prognostic Factor Analysis of Intraocular Pressure with Neovascular Glaucoma

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    Satoko Nakano

    2016-01-01

    Full Text Available Purpose. To perform multivariate analysis for identifying independent predictors of elevated intraocular pressure (IOP with neovascular glaucoma (NVG, including antivascular endothelial growth factor (VEGF intravitreal injections. Methods. We retrospectively reviewed 142 NVG patients (181 eyes with ischemic retinal diseases [proliferative diabetic retinopathy (PDR in 134 eyes, retinal vein occlusion (RVO in 29, and ocular ischemic syndrome in 18]. We analyzed age, gender, initial/final LogMAR VA, initial/final IOP, extent of iris and/or angle neovascularization, treatments, preexisting complications, concurrent medications, and follow-up duration. Results. The mean follow-up duration was 23.8 ± 18.8 months. At the final follow-up, 125 (72.3% eyes had IOP ≤ 21 mmHg. NVG patients with RVO had a higher degree of angle closure and higher IOP. NVG with PDR had better IOP and LogMAR VA. Angle closure had the greatest impact on final IOP. Greater than 90% of patients treated with trabeculectomy with mitomycin C (LEC had persistent declines in IOP (≤21 mmHg. Stand-alone and combination anti-VEGF therapies were not associated with improved long-term prognosis of IOP. Conclusions. Angle closure was found to have the greatest effect on NVG-IOP prognosis. When target IOP values are not obtained after adequate PRP with or without anti-VEGF, early LEC may improve the prognosis of IOP.

  15. A Sensitivity Analysis Approach to Identify Key Environmental Performance Factors

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    Xi Yu

    2014-01-01

    Full Text Available Life cycle assessment (LCA is widely used in design phase to reduce the product’s environmental impacts through the whole product life cycle (PLC during the last two decades. The traditional LCA is restricted to assessing the environmental impacts of a product and the results cannot reflect the effects of changes within the life cycle. In order to improve the quality of ecodesign, it is a growing need to develop an approach which can reflect the changes between the design parameters and product’s environmental impacts. A sensitivity analysis approach based on LCA and ecodesign is proposed in this paper. The key environmental performance factors which have significant influence on the products’ environmental impacts can be identified by analyzing the relationship between environmental impacts and the design parameters. Users without much environmental knowledge can use this approach to determine which design parameter should be first considered when (redesigning a product. A printed circuit board (PCB case study is conducted; eight design parameters are chosen to be analyzed by our approach. The result shows that the carbon dioxide emission during the PCB manufacture is highly sensitive to the area of PCB panel.

  16. Distal wound complications following pedal bypass: analysis of risk factors.

    Science.gov (United States)

    Robison, J G; Ross, J P; Brothers, T E; Elliott, B M

    1995-01-01

    Wound complications of the pedal incision continue to compromise successful limb salvage following aggressive revascularization. Significant distal wound disruption occurred in 14 of 142 (9.8%) patients undergoing pedal bypass with autogenous vein for limb salvage between 1986 and 1993. One hundred forty-two pedal bypass procedures were performed for rest pain in 66 patients and tissue necrosis in 76. Among the 86 men and 56 women, 76% were diabetic and 73% were black. All but eight patients had a history of diabetes and/or tobacco use. Eight wounds were successfully managed with maintenance of patent grafts from 5 to 57 months. Exposure of a patent graft precipitated amputation in three patients, as did graft occlusion in an additional patient. One graft was salvaged by revision to the peroneal artery and one was covered by a local bipedicled flap. Multiple regression analysis identified three factors associated with wound complications at the pedal incision site: diabetes mellitus (p = 0.03), age > 70 years (p = 0.03), and rest pain (p = 0.05). Ancillary techniques ("pie-crusting") to reduce skin tension resulted in no distal wound problems among 15 patients considered to be at greatest risk for wound breakdown. Attention to technique of distal graft tunneling, a wound closure that reduces tension, and control of swelling by avoiding dependency on and use of gentle elastic compression assume crucial importance in minimizing pedal wound complications following pedal bypass.

  17. Regression and kriging analysis for grid power factor estimation

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    Rajesh Guntaka

    2014-12-01

    Full Text Available The measurement of power factor (PF in electrical utility grids is a mainstay of load balancing and is also a critical element of transmission and distribution efficiency. The measurement of PF dates back to the earliest periods of electrical power distribution to public grids. In the wide-area distribution grid, measurement of current waveforms is trivial and may be accomplished at any point in the grid using a current tap transformer. However, voltage measurement requires reference to ground and so is more problematic and measurements are normally constrained to points that have ready and easy access to a ground source. We present two mathematical analysis methods based on kriging and linear least square estimation (LLSE (regression to derive PF at nodes with unknown voltages that are within a perimeter of sample nodes with ground reference across a selected power grid. Our results indicate an error average of 1.884% that is within acceptable tolerances for PF measurements that are used in load balancing tasks.

  18. Rorschach assessment of traumatized refugees: an exploratory factor analysis.

    Science.gov (United States)

    Opaas, Marianne; Hartmann, Ellen

    2013-01-01

    Fifty-one multitraumatized mental health patients with refugee backgrounds completed the Rorschach (Meyer & Viglione, 2008), Harvard Trauma Questionnaire, and Hopkins Symptom Checklist-25 (Mollica, McDonald, Massagli, & Silove, 2004), and the World Health Organization Quality of Life-BREF questionnaire (WHOQOL Group, 1998) before the start of treatment. The purpose was to gain more in-depth knowledge of an understudied patient group and to provide a prospective basis for later analyses of treatment outcome. Factor analysis of trauma-related Rorschach variables gave 2 components explaining 60% of the variance; the first was interpreted as trauma-related flooding versus constriction and the second as adequate versus impaired reality testing. Component 1 correlated positively with self-reported reexperiencing symptoms of posttraumatic stress (r = .32, p < .05). Component 2 correlated positively with self-reported quality of life in the physical, psychological, and social relationships domains (r = .34, .32, and .35, p < .05), and negatively with anxiety (r = -.33, p < .05). Each component also correlated significantly with resources like work experience, education, and language skills.

  19. Investigation of Arctic and Antarctic spatial and depth patterns of sea water in CTD profiles using chemometric data analysis

    Science.gov (United States)

    Kotwa, Ewelina; Lacorte, Silvia; Duarte, Carlos; Tauler, Roma

    2014-09-01

    In this paper we examine 2- and 3-way chemometric methods for analysis of Arctic and Antarctic water samples. Standard CTD (conductivity-temperature-depth) sensor devices were used during two oceanographic expeditions (July 2007 in the Arctic; February 2009 in the Antarctic) covering a total of 174 locations. The output from these devices can be arranged in a 3-way data structure (according to sea water depth, measured variables, and geographical location). We used and compared 2- and 3-way statistical tools including PCA, PARAFAC, PLS, and N-PLS for exploratory analysis, spatial patterns discovery and calibration. Particular importance was given to the correlation and possible prediction of fluorescence from other physical variables. MATLAB's mapping toolbox was used for geo-referencing and visualization of the results. We conclude that: 1) PCA and PARAFAC models were able to describe data in a satisfactory way, but PARAFAC results were easier to interpret; 2) applying a 2-way model to 3-way data raises the risk of flattening the covariance structure of the data and losing information; 3) the distinction between Arctic and Antarctic seas was revealed mostly by PC1, relating to the physico-chemical properties of the water samples; and 4) we confirm the ability to predict fluorescence values from physical measurements when the 3-way data structure is used in N-way PLS regression.

  20. The five-factor model of the Positive and Negative Syndrome Scale - I : Confirmatory factor analysis fails to confirm 25 published five-factor solutions

    NARCIS (Netherlands)

    van der Gaag, Mark; Cuijpers, Anke; Hoffman, Tonko; Remijsen, Mila; Hijman, Ron; de Haan, Lieuwe; van Meijel, Berno; van Harten, Peter N.; Valmaggia, Lucia; de Hert, Marc; Wiersma, Durk

    2006-01-01

    Objective: The aim of this study was to test the goodness-of-fit of all previously published five-factor models of the Positive and Negative Syndrome Scale (PANSS). Methods: We used confirmatory factor analysis (CFA) with a large data set (N = 5769). Results: The different subsamples were tested for

  1. Factor Analysis of the Aberrant Behavior Checklist in Individuals with Autism Spectrum Disorders

    Science.gov (United States)

    Brinkley, Jason; Nations, Laura; Abramson, Ruth K.; Hall, Alicia; Wright, Harry H.; Gabriels, Robin; Gilbert, John R.; Pericak-Vance, Margaret A. O.; Cuccaro, Michael L.

    2007-01-01

    Exploratory factor analysis (varimax and promax rotations) of the aberrant behavior checklist-community version (ABC) in 275 individuals with Autism spectrum disorder (ASD) identified four- and five-factor solutions which accounted for greater than 70% of the variance. Confirmatory factor analysis (Lisrel 8.7) revealed indices of moderate fit for…

  2. Network based transcription factor analysis of regenerating axolotl limbs

    Directory of Open Access Journals (Sweden)

    Cameron Jo Ann

    2011-03-01

    Full Text Available Abstract Background Studies on amphibian limb regeneration began in the early 1700's but we still do not completely understand the cellular and molecular events of this unique process. Understanding a complex biological process such as limb regeneration is more complicated than the knowledge of the individual genes or proteins involved. Here we followed a systems biology approach in an effort to construct the networks and pathways of protein interactions involved in formation of the accumulation blastema in regenerating axolotl limbs. Results We used the human orthologs of proteins previously identified by our research team as bait to identify the transcription factor (TF pathways and networks that regulate blastema formation in amputated axolotl limbs. The five most connected factors, c-Myc, SP1, HNF4A, ESR1 and p53 regulate ~50% of the proteins in our data. Among these, c-Myc and SP1 regulate 36.2% of the proteins. c-Myc was the most highly connected TF (71 targets. Network analysis showed that TGF-β1 and fibronectin (FN lead to the activation of these TFs. We found that other TFs known to be involved in epigenetic reprogramming, such as Klf4, Oct4, and Lin28 are also connected to c-Myc and SP1. Conclusions Our study provides a systems biology approach to how different molecular entities inter-connect with each other during the formation of an accumulation blastema in regenerating axolotl limbs. This approach provides an in silico methodology to identify proteins that are not detected by experimental methods such as proteomics but are potentially important to blastema formation. We found that the TFs, c-Myc and SP1 and their target genes could potentially play a central role in limb regeneration. Systems biology has the potential to map out numerous other pathways that are crucial to blastema formation in regeneration-competent limbs, to compare these to the pathways that characterize regeneration-deficient limbs and finally, to identify stem

  3. Analysis of factors associated with excess weight in school children

    Directory of Open Access Journals (Sweden)

    Renata Paulino Pinto

    Full Text Available Abstract Objective: To determine the prevalence of overweight and obesity in schoolchildren aged 10 to 16 years and its association with dietary and behavioral factors. Methods: Cross-sectional study that evaluated 505 adolescents using a structured questionnaire and anthropometric data. The data was analyzed through the T Test for independent samples and Mann-Whitney Test to compare means and medians, respectively, and Chi2 Test for proportions. Prevalence ratio (RP and the 95% confidence interval was used to estimate the degree of association between variables. The logistic regression was employed to adjust the estimates to confounding factors. The significance level of 5% was considered for all analysis. Results: Excess weight was observed in 30.9% of the schoolchildren: 18.2% of overweight and 12.7% of obesity. There was no association between weight alterations and dietary/behavioral habits in the bivariate and multivariate analyses. However, associations were observed in relation to gender. Daily consumption of sweets [PR=0.75 (0.64-0.88] and soft drinks [PR=0.82 (0.70-0.97] was less frequent among boys; having lunch daily was slightly more often reported by boys [OR=1.11 (1.02-1.22]. Physical activity practice of (≥3 times/week was more often mentioned by boys and the association measures disclosed two-fold more physical activity in this group [PR=2.04 (1.56-2.67] when compared to girls. Approximately 30% of boys and 40% of girls stated they did not perform activities requiring energy expenditure during free periods, with boys being 32% less idle than girls [PR=0.68 (0.60-0.76]. Conclusions: A high prevalence of both overweight and obesity was observed, as well as unhealthy habits in the study population, regardless of the presence of weight alterations. Health promotion strategies in schools should be encouraged, in order to promote healthy habits and behaviors among all students.

  4. Analysis of factors associated with excess weight in school children.

    Science.gov (United States)

    Pinto, Renata Paulino; Nunes, Altacílio Aparecido; de Mello, Luane Marques

    2016-12-01

    To determine the prevalence of overweight and obesity in schoolchildren aged 10 to 16 years and its association with dietary and behavioral factors. Cross-sectional study that evaluated 505 adolescents using a structured questionnaire and anthropometric data. The data was analyzed through the T Test for independent samples and Mann-Whitney Test to compare means and medians, respectively, and Chi(2) Test for proportions. Prevalence Ratio (RP) and the 95% confidence interval was used to estimate the degree of association between variables. The logistic regression was employed to adjust the estimates to confounding factors. The significance level of 5% was considered for all analysis. Excess weight was observed in 30.9% of the schoolchildren: 18.2% of overweight and 12.7% of obesity. There was no association between weight alterations and dietary/behavioral habits in the bivariate and multivariate analyses. However, associations were observed in relation to gender. Daily consumption of sweets [PR=0.75 (0.64-0.88)] and soft drinks [PR=0.82 (0.70-0.97)] was less frequent among boys; having lunch daily was slightly more often reported by boys [OR=1.11 (1.02-1.22)]. Physical activity practice of (≥3 times/week) was more often mentioned by boys and the association measures disclosed two-fold more physical activity in this group [PR=2.04 (1.56-2.67)] when compared to girls. Approximately 30% of boys and 40% of girls stated they did not perform activities requiring energy expenditure during free periods, with boys being 32% less idle than girls [PR=0.68 (0.60-0.76)]. A high prevalence of both overweight and obesity was observed, as well as unhealthy habits in the study population, regardless of the presence of weight alterations. Health promotion strategies in schools should be encouraged, in order to promote healthy habits and behaviors among all students. Copyright © 2016 Sociedade de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.

  5. Immunohistochemistry profiles of breast ductal carcinoma: factor analysis of digital image analysis data

    Directory of Open Access Journals (Sweden)

    Laurinavicius Arvydas

    2012-03-01

    Full Text Available Abstract Background Molecular studies of breast cancer revealed biological heterogeneity of the disease and opened new perspectives for personalized therapy. While multiple gene expression-based systems have been developed, current clinical practice is largely based upon conventional clinical and pathologic criteria. This gap may be filled by development of combined multi-IHC indices to characterize biological and clinical behaviour of the tumours. Digital image analysis (DA with multivariate statistics of the data opens new opportunities in this field. Methods Tissue microarrays of 109 patients with breast ductal carcinoma were stained for a set of 10 IHC markers (ER, PR, HER2, Ki67, AR, BCL2, HIF-1α, SATB1, p53, and p16. Aperio imaging platform with the Genie, Nuclear and Membrane algorithms were used for the DA. Factor analysis of the DA data was performed in the whole group and hormone receptor (HR positive subgroup of the patients (n = 85. Results Major factor potentially reflecting aggressive disease behaviour (i-Grade was extracted, characterized by opposite loadings of ER/PR/AR/BCL2 and Ki67/HIF-1α. The i-Grade factor scores revealed bimodal distribution and were strongly associated with higher Nottingham histological grade (G and more aggressive intrinsic subtypes. In HR-positive tumours, the aggressiveness of the tumour was best defined by positive Ki67 and negative ER loadings. High Ki67/ER factor scores were strongly associated with the higher G and Luminal B types, but also were detected in a set of G1 and Luminal A cases, potentially indicating high risk patients in these categories. Inverse relation between HER2 and PR expression was found in the HR-positive tumours pointing at differential information conveyed by the ER and PR expression. SATB1 along with HIF-1α reflected the second major factor of variation in our patients; in the HR-positive group they were inversely associated with the HR and BCL2 expression and represented

  6. Immunohistochemistry profiles of breast ductal carcinoma: factor analysis of digital image analysis data.

    Science.gov (United States)

    Laurinavicius, Arvydas; Laurinaviciene, Aida; Ostapenko, Valerijus; Dasevicius, Darius; Jarmalaite, Sonata; Lazutka, Juozas

    2012-03-16

    Molecular studies of breast cancer revealed biological heterogeneity of the disease and opened new perspectives for personalized therapy. While multiple gene expression-based systems have been developed, current clinical practice is largely based upon conventional clinical and pathologic criteria. This gap may be filled by development of combined multi-IHC indices to characterize biological and clinical behaviour of the tumours. Digital image analysis (DA) with multivariate statistics of the data opens new opportunities in this field. Tissue microarrays of 109 patients with breast ductal carcinoma were stained for a set of 10 IHC markers (ER, PR, HER2, Ki67, AR, BCL2, HIF-1α, SATB1, p53, and p16). Aperio imaging platform with the Genie, Nuclear and Membrane algorithms were used for the DA. Factor analysis of the DA data was performed in the whole group and hormone receptor (HR) positive subgroup of the patients (n = 85). Major factor potentially reflecting aggressive disease behaviour (i-Grade) was extracted, characterized by opposite loadings of ER/PR/AR/BCL2 and Ki67/HIF-1α. The i-Grade factor scores revealed bimodal distribution and were strongly associated with higher Nottingham histological grade (G) and more aggressive intrinsic subtypes. In HR-positive tumours, the aggressiveness of the tumour was best defined by positive Ki67 and negative ER loadings. High Ki67/ER factor scores were strongly associated with the higher G and Luminal B types, but also were detected in a set of G1 and Luminal A cases, potentially indicating high risk patients in these categories. Inverse relation between HER2 and PR expression was found in the HR-positive tumours pointing at differential information conveyed by the ER and PR expression. SATB1 along with HIF-1α reflected the second major factor of variation in our patients; in the HR-positive group they were inversely associated with the HR and BCL2 expression and represented the major factor of variation. Finally, we

  7. Epigenetic clock analysis of diet, exercise, education, and lifestyle factors.

    Science.gov (United States)

    Quach, Austin; Levine, Morgan E; Tanaka, Toshiko; Lu, Ake T; Chen, Brian H; Ferrucci, Luigi; Ritz, Beate; Bandinelli, Stefania; Neuhouser, Marian L; Beasley, Jeannette M; Snetselaar, Linda; Wallace, Robert B; Tsao, Philip S; Absher, Devin; Assimes, Themistocles L; Stewart, James D; Li, Yun; Hou, Lifang; Baccarelli, Andrea A; Whitsel, Eric A; Horvath, Steve

    2017-02-14

    Behavioral and lifestyle factors have been shown to relate to a number of health-related outcomes, yet there is a need for studies that examine their relationship to molecular aging rates. Toward this end, we use recent epigenetic biomarkers of age that have previously been shown to predict all-cause mortality, chronic conditions, and age-related functional decline. We analyze cross-sectional data from 4,173 postmenopausal female participants from the Women's Health Initiative, as well as 402 male and female participants from the Italian cohort study, Invecchiare nel Chianti.Extrinsic epigenetic age acceleration (EEAA) exhibits significant associations with fish intake (p=0.02), moderate alcohol consumption (p=0.01), education (p=3x10(-5)), BMI (p=0.01), and blood carotenoid levels (p=1x10(-5))-an indicator of fruit and vegetable consumption, whereas intrinsic epigenetic age acceleration (IEAA) is associated with poultry intake (p=0.03) and BMI (p=0.05). Both EEAA and IEAA were also found to relate to indicators of metabolic syndrome, which appear to mediate their associations with BMI. Metformin-the first-line medication for the treatment of type 2 diabetes-does not delay epigenetic aging in this observational study. Finally, longitudinal data suggests that an increase in BMI is associated with increase in both EEAA and IEAA.Overall, the epigenetic age analysis of blood confirms the conventional wisdom regarding the benefits of eating a high plant diet with lean meats, moderate alcohol consumption, physical activity, and education, as well as the health risks of obesity and metabolic syndrome.

  8. Human Factors Considerations in New Nuclear Power Plants: Detailed Analysis.

    Energy Technology Data Exchange (ETDEWEB)

    OHara,J.; Higgins, J.; Brown, W.; Fink, R.

    2008-02-14

    This Nuclear Regulatory Commission (NRC) sponsored study has identified human-performance issues in new and advanced nuclear power plants. To identify the issues, current industry developments and trends were evaluated in the areas of reactor technology, instrumentation and control technology, human-system integration technology, and human factors engineering (HFE) methods and tools. The issues were organized into seven high-level HFE topic areas: Role of Personnel and Automation, Staffing and Training, Normal Operations Management, Disturbance and Emergency Management, Maintenance and Change Management, Plant Design and Construction, and HFE Methods and Tools. The issues where then prioritized into four categories using a 'Phenomena Identification and Ranking Table' methodology based on evaluations provided by 14 independent subject matter experts. The subject matter experts were knowledgeable in a variety of disciplines. Vendors, utilities, research organizations and regulators all participated. Twenty issues were categorized into the top priority category. This Brookhaven National Laboratory (BNL) technical report provides the detailed methodology, issue analysis, and results. A summary of the results of this study can be found in NUREG/CR-6947. The research performed for this project has identified a large number of human-performance issues for new control stations and new nuclear power plant designs. The information gathered in this project can serve as input to the development of a long-term strategy and plan for addressing human performance in these areas through regulatory research. Addressing human-performance issues will provide the technical basis from which regulatory review guidance can be developed to meet these challenges. The availability of this review guidance will help set clear expectations for how the NRC staff will evaluate new designs, reduce regulatory uncertainty, and provide a well-defined path to new nuclear power plant

  9. Risk analysis-based food safety policy: scientific factors versus socio-cultural factors.

    Science.gov (United States)

    De Rosa, Mauro; van Knapen, Frans; Brom, Frans W A

    2008-09-15

    The purpose of this article is to illustrate the importance of socio-cultural factors in risk management and the need to incorporate these factors in a standard, internationally recognized (WTO) framework. This was achieved by analysing the relevance of these factors in three cases. It can be concluded that the pre-eminent role of science in food-related regulatory decisions is debatable. At a risk management level, other factors, such as cultural, social, or economic issues, are often more important than scientific advice in determining policy. There is a need for transparency at an international level as trade barriers are gradually being removed and these other factors are becoming more apparent. Therefore it is important that all the factors implicated in the food safety policy-making process are recognized in a standard framework.

  10. Factors influencing societal response of nanotechnology : an expert stakeholder analysis

    OpenAIRE

    2012-01-01

    Nanotechnology can be described as an emerging technology and, as has been the case with other emerging technologies such as genetic modification, different socio-psychological factors will potentially influence societal responses to its development and application. These factors will play an important role in how nanotechnology is developed and commercialised. This article aims to identify expert opinion on factors influencing societal response to applications of nanotechnology. Structured i...

  11. Quasi Maximum Likelihood Analysis of High Dimensional Constrained Factor Models

    OpenAIRE

    Li, Kunpeng; Li,Qi; Lu, Lina

    2016-01-01

    Factor models have been widely used in practice. However, an undesirable feature of a high dimensional factor model is that the model has too many parameters. An effective way to address this issue, proposed in a seminar work by Tsai and Tsay (2010), is to decompose the loadings matrix by a high-dimensional known matrix multiplying with a low-dimensional unknown matrix, which Tsai and Tsay (2010) name constrained factor models. This paper investigates the estimation and inferential theory ...

  12. Confirmatory factor analysis of the Oral Health Impact Profile.

    Science.gov (United States)

    John, M T; Feuerstahler, L; Waller, N; Baba, K; Larsson, P; Celebić, A; Kende, D; Rener-Sitar, K; Reissmann, D R

    2014-09-01

    Previous exploratory analyses suggest that the Oral Health Impact Profile (OHIP) consists of four correlated dimensions and that individual differences in OHIP total scores reflect an underlying higher-order factor. The aim of this report is to corroborate these findings in the Dimensions of Oral Health-Related Quality of Life (DOQ) Project, an international study of general population subjects and prosthodontic patients. Using the project's Validation Sample (n = 5022), we conducted confirmatory factor analyses in a sample of 4993 subjects with sufficiently complete data. In particular, we compared the psychometric performance of three models: a unidimensional model, a four-factor model and a bifactor model that included one general factor and four group factors. Using model-fit criteria and factor interpretability as guides, the four-factor model was deemed best in terms of strong item loadings, model fit (RMSEA = 0·05, CFI = 0·99) and interpretability. These results corroborate our previous findings that four highly correlated factors - which we have named Oral Function, Oro-facial Pain, Oro-facial Appearance and Psychosocial Impact - can be reliably extracted from the OHIP item pool. However, the good fit of the unidimensional model and the high interfactor correlations in the four-factor solution suggest that OHRQoL can also be sufficiently described with one score.

  13. An Analysis of Key Factors Affecting Chinese ESL Students’ Listening

    Institute of Scientific and Technical Information of China (English)

    苏君; 郭润玉

    2012-01-01

      With the proposal of Internet-based CET, more emphasis need be attached to listening skill. In order to improve stu⁃dents’ listening skill, linguistic knowledge, psychological factors and cultural background knowledge, as three key factors affect⁃ing Chinese ESL students, have been analyzed and the improving solutions have been suggested.

  14. Factors influencing societal response of nanotechnology : an expert stakeholder analysis

    NARCIS (Netherlands)

    Gupta, N.; Fischer, A.R.H.; Lans, van der I.A.; Frewer, L.J.

    2012-01-01

    Nanotechnology can be described as an emerging technology and, as has been the case with other emerging technologies such as genetic modification, different socio-psychological factors will potentially influence societal responses to its development and application. These factors will play an import

  15. Confirmatory Factor Analysis of the WAIS-IV/WMS-IV

    Science.gov (United States)

    Holdnack, James A.; Zhou, Xiaobin; Larrabee, Glenn J.; Millis, Scott R.; Salthouse, Timothy A.

    2011-01-01

    The Wechsler Adult Intelligence Scale-fourth edition (WAIS-IV) and the Wechsler Memory Scale-fourth edition (WMS-IV) were co-developed to be used individually or as a combined battery of tests. The independent factor structure of each of the tests has been identified; however, the combined factor structure has yet to be determined. Confirmatory…

  16. Confirmatory Factor Analysis of the WAIS-IV/WMS-IV

    Science.gov (United States)

    Holdnack, James A.; Zhou, Xiaobin; Larrabee, Glenn J.; Millis, Scott R.; Salthouse, Timothy A.

    2011-01-01

    The Wechsler Adult Intelligence Scale-fourth edition (WAIS-IV) and the Wechsler Memory Scale-fourth edition (WMS-IV) were co-developed to be used individually or as a combined battery of tests. The independent factor structure of each of the tests has been identified; however, the combined factor structure has yet to be determined. Confirmatory…

  17. Using Multilevel Factor Analysis with Clustered Data: Investigating the Factor Structure of the Positive Values Scale

    Science.gov (United States)

    Huang, Francis L.; Cornell, Dewey G.

    2016-01-01

    Advances in multilevel modeling techniques now make it possible to investigate the psychometric properties of instruments using clustered data. Factor models that overlook the clustering effect can lead to underestimated standard errors, incorrect parameter estimates, and model fit indices. In addition, factor structures may differ depending on…

  18. Enhanced Phosphoproteomic Profiling Workflow For Growth Factor Signaling Analysis

    DEFF Research Database (Denmark)

    Sylvester, Marc; Burbridge, Mike; Leclerc, Gregory

    2010-01-01

    understanding of pathological processes. In our study we create and integrate data on phosphorylations that are initiated by several growth factor receptors. We present an approach for quantitative, time-resolved phosphoproteomic profiling that integrates the important contributions by phosphotyrosines. Methods...... A549 lung carcinoma cells were used as a model and stimulated with hepatocyte growth factor, epidermal growth factor or fibroblast growth factor. We employed a quick protein digestion workflow with spin filters without using urea. Phosphopeptides in general were enriched by sequential elution from...... in order to maximize identification of peptides as well as localization of phosphorylation sites. Results and Conclusions The combination of SIMAC with phosphotyrosine enrichment leads to a significant increase in identification of potential signaling events in growth factor receptor signaling networks...

  19. FACTOR ANALYSIS OF THE ROLLING PROCESS TECHNOLOGY (Part2

    Directory of Open Access Journals (Sweden)

    A. N. Chichko

    2011-01-01

    Full Text Available The mathematical model of the multivariate regression analysis carrying out is presented. Its practical application for rolled production is examined. Analysis of the model adequacy is carried out.

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

    Directory of Open Access Journals (Sweden)

    Zuzana Toufarová

    2007-01-01

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

  1. Factor analysis is more appropriate to identify overall dietary patterns associated with diabetes when compared with treelet transform analysis

    NARCIS (Netherlands)

    Schoenaker, D.A.J.M.; Dobson, A.; Soedamah-Muthu, S.S.; Mishra, G.D.

    2013-01-01

    Treelet transform (TT) is a proposed alternative to factor analysis for deriving dietary patterns. Before applying this method to nutrition data, further analyses are required to assess its validity in nutritional epidemiology. We aimed to compare dietary patterns from factor analysis and TT and the

  2. Application of Factor Analysis on the Financial Ratios of Indian Cement Industry and Validation of the Results by Cluster Analysis

    Science.gov (United States)

    De, Anupam; Bandyopadhyay, Gautam; Chakraborty, B. N.

    2010-10-01

    Financial ratio analysis is an important and commonly used tool in analyzing financial health of a firm. Quite a large number of financial ratios, which can be categorized in different groups, are used for this analysis. However, to reduce number of ratios to be used for financial analysis and regrouping them into different groups on basis of empirical evidence, Factor Analysis technique is being used successfully by different researches during the last three decades. In this study Factor Analysis has been applied over audited financial data of Indian cement companies for a period of 10 years. The sample companies are listed on the Stock Exchange India (BSE and NSE). Factor Analysis, conducted over 44 variables (financial ratios) grouped in 7 categories, resulted in 11 underlying categories (factors). Each factor is named in an appropriate manner considering the factor loads and constituent variables (ratios). Representative ratios are identified for each such factor. To validate the results of Factor Analysis and to reach final conclusion regarding the representative ratios, Cluster Analysis had been performed.

  3. Drivers of fluorescent dissolved organic matter in the global epipelagic ocean

    DEFF Research Database (Denmark)

    Catalá, T.S.; Álvarez-Salgado, X. A.; Otero, J.

    2016-01-01

    Fluorescent dissolved organic matter (FDOM) in open surface waters (oceans was analysed by excitation-emission matrix (EEM) spectroscopy and parallel factor analysis (PARAFAC). A four-component PARAFAC model was fit to the EEMs, which included two humic......- (C1 and C2) and two amino acid-like (C3 and C4) components previously identified in ocean waters. Generalizedadditive models (GAMs) were used to explore the environmental factors that drive the global distribution of these PARAFAC components. The explained variance for the humic-like components...... and the two humic-like PARAFAC components suggest that their distribution are biologically controlled. Compared with the dark ocean (> 200 m), the relationships of C1 and C2 with AOU indicate a higher C1/AOU and C2/AOU ratios of the humic-like substances in the dark ocean than in the surface ocean where a net...

  4. Factors influencing first childbearing timing decisions among men: Path analysis

    Science.gov (United States)

    Kariman, Nourossadat; Amerian, Maliheh; Jannati, Padideh; Salmani, Fatemeh

    2016-01-01

    Background: Factors that influence men’s childbearing intentions have been relatively unexplored in the literature. Objective: This study aimed to determine the influencing factors about the first childbearing timing decisions of men. Materials and Methods: In this cross-sectional study, 300 men who were referred to private and governmental healthcare centers in Shahrood, Iran were randomly recruited from April to September 2014. Data were collected using a demographic questionnaire, the Quality of Life Questionnaire; ENRICH Marital Satisfaction Questionnaire, Synder’s Hope Scale, and the Multidimensional Scale of Perceived Social Support. Results: After removing the statistically insignificant paths, men’s age at marriage had the highest direct effect (β=0.86) on their first childbearing decision. Marital satisfaction (β=-0.09), social support (β=0.06), economic status (β=0.06), and quality of life (β=-0.08) were other effective factors on men’s first childbearing decisions. Moreover, marital satisfaction and social support had significant indirect effects on men’s childbearing decisions (β=-0.04 and -0.01, respectively). Conclusion: Many factors, including personal factors (age at marriage and quality of life), family factors (marital satisfaction), and social factors (social support), can affect men’s decision to have a child. Policymakers are hence required to develop strategies to promote the socioeconomic and family conditions of the couples and to encourage them to have as many children as they desire at an appropriate time. PMID:27738661

  5. Impact Factors of Energy Productivity in China: An Empirical Analysis

    Institute of Scientific and Technical Information of China (English)

    Wei Chu; Shen Manhong

    2007-01-01

    This article developed a decomposition model of energy productivity on the basis of the economic growth model. Four factors were considered which may influence China's energy productivity according to this model: technology improvement, resource allocation structure, industrial structure and institute arrangement. Then, an econometric model was employed to test the four factors empirically on the basis of China's statistical data from 1978 to 2004. Results indicated that capital deepening contributes the most (207%) to energy efficiency improvement, and impact from labor forces (13%) is the weakest one in resource factor; industrial structure (7%) and institute innovation (9.5%) positively improve the energy productivity.

  6. Convergence analysis of the alternating RGLS algorithm for the identification of the reduced complexity Volterra model.

    Science.gov (United States)

    Laamiri, Imen; Khouaja, Anis; Messaoud, Hassani

    2015-03-01

    In this paper we provide a convergence analysis of the alternating RGLS (Recursive Generalized Least Square) algorithm used for the identification of the reduced complexity Volterra model describing stochastic non-linear systems. The reduced Volterra model used is the 3rd order SVD-PARAFC-Volterra model provided using the Singular Value Decomposition (SVD) and the Parallel Factor (PARAFAC) tensor decomposition of the quadratic and the cubic kernels respectively of the classical Volterra model. The Alternating RGLS (ARGLS) algorithm consists on the execution of the classical RGLS algorithm in alternating way. The ARGLS convergence was proved using the Ordinary Differential Equation (ODE) method. It is noted that the algorithm convergence canno׳t be ensured when the disturbance acting on the system to be identified has specific features. The ARGLS algorithm is tested in simulations on a numerical example by satisfying the determined convergence conditions. To raise the elegies of the proposed algorithm, we proceed to its comparison with the classical Alternating Recursive Least Squares (ARLS) presented in the literature. The comparison has been built on a non-linear satellite channel and a benchmark system CSTR (Continuous Stirred Tank Reactor). Moreover the efficiency of the proposed identification approach is proved on an experimental Communicating Two Tank system (CTTS).

  7. Conversion factors in carnivore scat analysis: sources of bias

    National Research Council Canada - National Science Library

    Ferdinand Rühe; Michael Ksinsik; Christian Kiffner

    2008-01-01

    .... In our study, we aimed at: 1) presenting conversion factors (CFs) of roe deer Capreolus capreolus, European hare Lepus europaeus and house mice Mus musculus digested by wolf Canis lupus, Eurasian lynx Lynx lynx and red fox Vulpes vulpes, 2...

  8. TMFA: A FORTRAN Program for Three-Mode Factor Analysis and Individual Differences Multidimensional Scaling.

    Science.gov (United States)

    Redfield, Joel

    1978-01-01

    TMFA, a FORTRAN program for three-mode factor analysis and individual-differences multidimensional scaling, is described. Program features include a variety of input options, extensive preprocessing of input data, and several alternative methods of analysis. (Author)

  9. Low energy analysis of the nucleon electromagnetic form factors

    CERN Document Server

    Kubis, B; Kubis, Bastian; Meissner, Ulf-G.

    2001-01-01

    We analyze the electromagnetic form factors of the nucleon to fourth order in relativistic baryon chiral perturbation theory. We employ the recently proposed infrared regularization scheme and show that the convergence of the chiral expansion is improved as compared to the heavy fermion approach. We also discuss the inclusion of vector mesons and obtain an accurate description of all four nucleon form factors for momentum transfer squared up to Q^2 \\simeq 0.4 GeV^2.

  10. An Analysis of the Factors Impacting Employee's Specific Investment

    Institute of Scientific and Technical Information of China (English)

    WU Ai-hua; GE Wen-lei

    2008-01-01

    The amount of specific investment from employees is limited, and the reasons of the under-investment from employees are analyzed in this paper. Based on the relationship of the specific investment and the employee demission, an empirical study has been conducted focusing on the factors influencing the employee turnover and the specific investment. A theoretical model of the factors influencing employee's specific investment is given.

  11. A Multivariate Analysis of Risk Factors for Diabetic Nephropathy

    Directory of Open Access Journals (Sweden)

    Anthony Shannon

    2007-03-01

    Full Text Available This paper uses multivariate methods on actual data from 267 patients with noninsulin- dependent (Type 2 diabetes mellitus in order to see how the various risk factors can affect the progression of diabetic nephropathy. The approach succeeds in identifying preliminary risk factors such as smoking for males, although the females had higher fasting blood glucose at diagnosis. Not surprisingly, hypertension is common among patients of both sexes and it has an association with proteinuria in female patients in the sample.

  12. Quantitative risk analysis offshore-Human and organizational factors

    Energy Technology Data Exchange (ETDEWEB)

    Espen Skogdalen, Jon, E-mail: jon.espen.skogdalen@gmail.co [Department of Industrial Economics, Risk Management and Planning, University of Stavanger, 4036 Stavanger (Norway); Vinnem, Jan Erik, E-mail: jev@preventor.n [Department of Industrial Economics, Risk Management and Planning, University of Stavanger, 4036 Stavanger (Norway)

    2011-04-15

    Quantitative Risk Analyses (QRAs) are one of the main tools for risk management within the Norwegian and UK oil and gas industry. Much criticism has been given to the limitations related to the QRA-models and that the QRAs do not include human and organizational factors (HOF-factors). Norway and UK offshore legislation and guidelines require that the HOF-factors are included in the QRAs. A study of 15 QRAs shows that the factors are to some extent included, and there are large differences between the QRAs. The QRAs are categorized into four levels according to the findings. Level 1 QRAs do not describe or comment on the HOF-factors at all. Relevant research projects have been conducted to fulfill the requirements of Level 3 analyses. At this level, there is a systematic collection of data related to HOF. The methods are systematic and documented, and the QRAs are adjusted. None of the QRAs fulfill the Level 4 requirements. Level 4 QRAs include the model and describe the HOF-factors as well as explain how the results should be followed up in the overall risk management. Safety audits by regulatory authorities are probably necessary to point out the direction for QRA and speed up the development.

  13. A Unified Factors Analysis Framework for Discriminative Feature Extraction and Object Recognition

    Directory of Open Access Journals (Sweden)

    Ningbo Hao

    2016-01-01

    Full Text Available Various methods for feature extraction and dimensionality reduction have been proposed in recent decades, including supervised and unsupervised methods and linear and nonlinear methods. Despite the different motivations of these methods, we present in this paper a general formulation known as factor analysis to unify them within a common framework. During factor analysis, an object can be seen as being comprised of content and style factors, and the objective of feature extraction and dimensionality reduction is to obtain the content factor without style factor. There are two vital steps in factor analysis framework; one is the design of factor separating objective function, including the design of partition and weight matrix, and the other is the design of space mapping function. In this paper, classical Linear Discriminant Analysis (LDA and Locality Preserving Projection (LPP algorithms are improved based on factor analysis framework, and LDA based on factor analysis (FA-LDA and LPP based on factor analysis (FA-LPP are proposed. Experimental results show the superiority of our proposed approach in classification performance compared to classical LDA and LPP algorithms.

  14. Old and new ideas for data screening and assumption testing for exploratory and confirmatory factor analysis

    Directory of Open Access Journals (Sweden)

    David B. Flora

    2012-03-01

    Full Text Available We provide a basic review of the data screening and assumption testing issues relevant to exploratory and confirmatory factor analysis along with practical advice for conducting analyses that are sensitive to these concerns. Historically, factor analysis was developed for explaining the relationships among many continuous test scores, which led to the expression of the common factor model as a multivariate linear regression model with observed, continuous variables serving as dependent variables and unobserved factors as the independent, explanatory variables. Thus, we begin our paper with a review of the assumptions for the common factor model and data screening issues as they pertain to the factor analysis of continuous observed variables. In particular, we describe how principles from regression diagnostics also apply to factor analysis. Next, because modern applications of factor analysis frequently involve the analysis of the individual items from a single test or questionnaire, an important focus of this paper is the factor analysis of items. Although the traditional linear factor model is well-suited to the analysis of continuously distributed variables, commonly used item types, including Likert-type items, almost always produce dichotomous or ordered categorical variables. We describe how relationships among such items are often not well described by product-moment correlations, which has clear ramifications for the traditional linear factor analysis. An alternative, non-linear factor analysis using polychoric correlations has become more readily available to applied researchers and thus more popular. Consequently, we also review the assumptions and data-screening issues involved in this method. Throughout the paper, we demonstrate these procedures using an historic data set of nine cognitive ability variables.

  15. Old and new ideas for data screening and assumption testing for exploratory and confirmatory factor analysis.

    Science.gov (United States)

    Flora, David B; Labrish, Cathy; Chalmers, R Philip

    2012-01-01

    We provide a basic review of the data screening and assumption testing issues relevant to exploratory and confirmatory factor analysis along with practical advice for conducting analyses that are sensitive to these concerns. Historically, factor analysis was developed for explaining the relationships among many continuous test scores, which led to the expression of the common factor model as a multivariate linear regression model with observed, continuous variables serving as dependent variables, and unobserved factors as the independent, explanatory variables. Thus, we begin our paper with a review of the assumptions for the common factor model and data screening issues as they pertain to the factor analysis of continuous observed variables. In particular, we describe how principles from regression diagnostics also apply to factor analysis. Next, because modern applications of factor analysis frequently involve the analysis of the individual items from a single test or questionnaire, an important focus of this paper is the factor analysis of items. Although the traditional linear factor model is well-suited to the analysis of continuously distributed variables, commonly used item types, including Likert-type items, almost always produce dichotomous or ordered categorical variables. We describe how relationships among such items are often not well described by product-moment correlations, which has clear ramifications for the traditional linear factor analysis. An alternative, non-linear factor analysis using polychoric correlations has become more readily available to applied researchers and thus more popular. Consequently, we also review the assumptions and data-screening issues involved in this method. Throughout the paper, we demonstrate these procedures using an historic data set of nine cognitive ability variables.

  16. An improvement of window factor analysis for resolution of noisy HPLC-DAD data

    Institute of Scientific and Technical Information of China (English)

    邵学广; 林祥钦; 邵利民; 李梅青

    2002-01-01

    Window factor analysis (WFA) is a powerful tool in analyzing evolutionary process. However, it was found that window factor analysis is much sensitive to the noise involved in original data matrix. An error analysis was done with the fact that the concentration profiles resolved by the conventional window factor analysis are easily distorted by the noise reserved by the abstract factor analysis (AFA), and a modified algorithm for window factor analysis was proposed. Both simulated and experimental HPLC-DAD data were investigated by the conventional and the improved methods. Results show that the improved method can yield less noise-distorted concentration profiles than the conventional method, and the ability for resolution of noisy data sets can be greatly enhanced.

  17. FACTOR ANALYSIS OF THE ROLLING PROCESS TECHNOLOGY (part 1

    Directory of Open Access Journals (Sweden)

    A. N. Chichko

    2011-01-01

    Full Text Available The mathematical model of multidimensional regression analysis is presented. Its practical application for rolling production is examined. The algorithm of special characteristics determination is developed.

  18. Functional pathway mapping analysis for hypoxia-inducible factors.

    Science.gov (United States)

    Chuang, Chia-Sheng; Pai, Tun-Wen; Hu, Chin-Hua; Tzou, Wen-Shyong; Dah-Tsyr Chang, Margaret; Chang, Hao-Teng; Chen, Chih-Chia

    2011-06-20

    Hypoxia-inducible factors (HIFs) are transcription factors that play a crucial role in response to hypoxic stress in living organisms. The HIF pathway is activated by changes in cellular oxygen levels and has significant impacts on the regulation of gene expression patterns in cancer cells. Identifying functional conservation across species and discovering conserved regulatory motifs can facilitate the selection of reference species for empirical tests. This paper describes a cross-species functional pathway mapping strategy based on evidence of homologous relationships that employs matrix-based searching techniques for identifying transcription factor-binding sites on all retrieved HIF target genes. HIF-related orthologous and paralogous genes were mapped onto the conserved pathways to indicate functional conservation across species. Quantitatively measured HIF pathways are depicted in order to illustrate the extent of functional conservation. The results show that in spite of the evolutionary process of speciation, distantly related species may exhibit functional conservation owing to conservative pathways. The novel terms OrthRate and ParaRate are proposed to quantitatively indicate the flexibility of a homologous pathway and reveal the alternative regulation of functional genes. The developed functional pathway mapping strategy provides a bioinformatics approach for constructing biological pathways by highlighting the homologous relationships between various model species. The mapped HIF pathways were quantitatively illustrated and evaluated by statistically analyzing their conserved transcription factor-binding elements. hypoxia-inducible factor (HIF), hypoxia-response element (HRE), transcription factor (TF), transcription factor binding site (TFBS), KEGG (Kyoto Encyclopedia of Genes and Genomes), cross-species comparison, orthology, paralogy, functional pathway.

  19. Analysis of genetics and risk factors of Alzheimer's Disease.

    Science.gov (United States)

    Panpalli Ates, M; Karaman, Y; Guntekin, S; Ergun, M A

    2016-06-14

    Alzheimer's Disease is the leading neurodegenerative cause of dementia. The pathogenesis is not clearly understood yet, is believed to be the complex interaction between genetic and environmental factors. Consequently vascular risk factors and Apolipoprotein E genotyping are increasingly gaining importance. This study aimed at assessing the relationships between Alzheimer's Disease and Apolipoprotein E phenotype and vascular risk factors. Patients diagnosed with "possible Alzheimer's Disease" in the Gazi University, Department of Neurology, were included in the study and age-matched volunteer patients who attended the polyclinic were included as a control group. In this study, the risk factors including low education level, smoking, hyperlipidemia, higher serum total cholesterol levels, and hyperhomocysteinemia were found to be statistically significantly more common in the Alzheimer's Disease group in comparison to the Control Group, while all Apolipoprotein E ε4/ε4 genotypes were found in the Alzheimer's Disease group. The presence of the Apolipoprotein E ε4 allele is believed to increase vascular risk factors as well as to affect Alzheimer's Disease directly. The biological indicators which are used in identifying the patients' genes will be probably used in the treatment plan of the patients in the future.

  20. Enhanced Phosphoproteomic Profiling Workflow For Growth Factor Signaling Analysis

    DEFF Research Database (Denmark)

    Sylvester, Marc; Burbridge, Mike; Leclerc, Gregory;

    2010-01-01

    Background Our understanding of complex signaling networks is still fragmentary. Isolated processes have been studied extensively but cross-talk is omnipresent and precludes intuitive predictions of signaling outcomes. The need for quantitative data on dynamic systems is apparent especially for our...... A549 lung carcinoma cells were used as a model and stimulated with hepatocyte growth factor, epidermal growth factor or fibroblast growth factor. We employed a quick protein digestion workflow with spin filters without using urea. Phosphopeptides in general were enriched by sequential elution from...... transfer dissociation adds confidence in modification site assignment. The workflow is relatively simple but the integration of complementary techniques leads to a deeper insight into cellular signaling networks and the potential pharmacological intervention thereof....

  1. Sacrococcygeal pilonidal disease: analysis of previously proposed risk factors

    Directory of Open Access Journals (Sweden)

    Ali Harlak

    2010-01-01

    Full Text Available PURPOSE: Sacrococcygeal pilonidal disease is a source of one of the most common surgical problems among young adults. While male gender, obesity, occupations requiring sitting, deep natal clefts, excessive body hair, poor body hygiene and excessive sweating are described as the main risk factors for this disease, most of these need to be verified with a clinical trial. The present study aimed to evaluate the value and effect of these factors on pilonidal disease. METHOD: Previously proposed main risk factors were evaluated in a prospective case control study that included 587 patients with pilonidal disease and 2,780 healthy control patients. RESULTS: Stiffness of body hair, number of baths and time spent seated per day were the three most predictive risk factors. Adjusted odds ratios were 9.23, 6.33 and 4.03, respectively (p<0.001. With an adjusted odds ratio of 1.3 (p<.001, body mass index was another risk factor. Family history was not statistically different between the groups and there was no specific occupation associated with the disease. CONCLUSIONS: Hairy people who sit down for more than six hours a day and those who take a bath two or less times per week are at a 219-fold increased risk for sacrococcygeal pilonidal disease than those without these risk factors. For people with a great deal of hair, there is a greater need for them to clean their intergluteal sulcus. People who engage in work that requires sitting in a seat for long periods of time should choose more comfortable seats and should also try to stand whenever possible.

  2. Anticoagulation duration in heterozygous factor V Leiden: a decision analysis.

    Science.gov (United States)

    Donovan, Anna K; Smith, Kenneth J; Ragni, Margaret V

    2013-01-01

    Current anticoagulation guidelines suggest that optimal anticoagulation duration for unprovoked venous thromboembolism is determined by an individual risk assessment, balancing risks of anticoagulation bleeding with venous thromboembolism recurrence. Among individuals heterozygous for the factor V Leiden mutation, while venous thromboembolism recurrence risk is greater, the risk for bleeding is recognized to be lower, suggesting longer duration anticoagulation could be considered. The objective of this study was to compare standard vs. lifelong anticoagulation in 20-year-old factor V Leiden heterozygotes with unprovoked venous thromboembolism. A Markov state-transition model was used, incorporating risks of major, minor, and fatal anticoagulation bleeding, bleeding and thromboembolism morbidity and mortality, and quality of life utilities. Model parameter values favoring lifelong anticoagulation in factor V Leiden heterozygotes were determined in sensitivity analyses. Outcomes were in quality-adjusted life years, discounted at 3% per year. In general population groups with odds ratios for venous thromboembolism recurrence and anticoagulation bleeding of 1.0, a short-term anticoagulation strategy gained 0.09 quality-adjusted life years more than a lifelong anticoagulation strategy. By contrast, in factor V Leiden heterozygotes, lifetime anticoagulation was favored if their relative risk of venous thromboembolism was greater than 1.07 or their relative risk for bleeding was less than 0.91. Results were relatively insensitive to individual variation in other parameter values. Lifelong anticoagulation may benefit individuals heterozygous for factor V Leiden and previous idiopathic venous thromboembolism. Studies assessing bleeding risk with anticoagulation in factor V Leiden heterozygotes and the costs of indefinite anticoagulation are needed to determine if lifelong anticoagulation is the optimal strategy. © 2013 Elsevier Ltd. All rights reserved.

  3. Sacrococcygeal pilonidal disease: analysis of previously proposed risk factors

    Science.gov (United States)

    Harlak, Ali; Mentes, Oner; Kilic, Selim; Coskun, Kagan; Duman, Kazim; Yilmaz, Fahri

    2010-01-01

    PURPOSE Sacrococcygeal pilonidal disease is a source of one of the most common surgical problems among young adults. While male gender, obesity, occupations requiring sitting, deep natal clefts, excessive body hair, poor body hygiene and excessive sweating are described as the main risk factors for this disease, most of these need to be verified with a clinical trial. The present study aimed to evaluate the value and effect of these factors on pilonidal disease. METHOD Previously proposed main risk factors were evaluated in a prospective case control study that included 587 patients with pilonidal disease and 2,780 healthy control patients. RESULTS Stiffness of body hair, number of baths and time spent seated per day were the three most predictive risk factors. Adjusted odds ratios were 9.23, 6.33 and 4.03, respectively (p<0.001). With an adjusted odds ratio of 1.3 (p<.001), body mass index was another risk factor. Family history was not statistically different between the groups and there was no specific occupation associated with the disease. CONCLUSIONS Hairy people who sit down for more than six hours a day and those who take a bath two or less times per week are at a 219-fold increased risk for sacrococcygeal pilonidal disease than those without these risk factors. For people with a great deal of hair, there is a greater need for them to clean their intergluteal sulcus. People who engage in work that requires sitting in a seat for long periods of time should choose more comfortable seats and should also try to stand whenever possible. PMID:20186294

  4. Stability Analysis of Train Movement with Uncertain Factors

    Directory of Open Access Journals (Sweden)

    JingJing Ye

    2015-01-01

    Full Text Available We propose a new traffic model which is based on the traditional OV (optimal velocity car-following model. Here, some realistic factors are regarded as uncertain quantity, such as the headway distance. Our aim is to analyze and discuss the stability of car-following model under the constraint of uncertain factors. Then, according to the principle of expected value in fuzzy theory, an improved OV traffic model is constructed. Simulation results show that our proposed model can avoid collisions effectively under uncertain environment, and its stability can also be improved. Moreover, we discuss its stability as some parameters change, such as the relaxation time.

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

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

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

  6. Spatial Dependence and Heterogeneity in Bayesian Factor Analysis: A Cross-National Investigation of Schwartz Values

    Science.gov (United States)

    Stakhovych, Stanislav; Bijmolt, Tammo H. A.; Wedel, Michel

    2012-01-01

    In this article, we present a Bayesian spatial factor analysis model. We extend previous work on confirmatory factor analysis by including geographically distributed latent variables and accounting for heterogeneity and spatial autocorrelation. The simulation study shows excellent recovery of the model parameters and demonstrates the consequences…

  7. Spatial Dependence and Heterogeneity in Bayesian Factor Analysis: A Cross-National Investigation of Schwartz Values

    Science.gov (United States)

    Stakhovych, Stanislav; Bijmolt, Tammo H. A.; Wedel, Michel

    2012-01-01

    In this article, we present a Bayesian spatial factor analysis model. We extend previous work on confirmatory factor analysis by including geographically distributed latent variables and accounting for heterogeneity and spatial autocorrelation. The simulation study shows excellent recovery of the model parameters and demonstrates the consequences…

  8. Spatial Dependence and Heterogeneity in Bayesian Factor Analysis : A Cross-National Investigation of Schwartz Values

    NARCIS (Netherlands)

    Stakhovych, Stanislav; Bijmolt, Tammo H. A.; Wedel, Michel

    2012-01-01

    In this article, we present a Bayesian spatial factor analysis model. We extend previous work on confirmatory factor analysis by including geographically distributed latent variables and accounting for heterogeneity and spatial autocorrelation. The simulation study shows excellent recovery of the mo

  9. Developing Multidimensional Likert Scales Using Item Factor Analysis: The Case of Four-Point Items

    Science.gov (United States)

    Asún, Rodrigo A.; Rdz-Navarro, Karina; Alvarado, Jesús M.

    2016-01-01

    This study compares the performance of two approaches in analysing four-point Likert rating scales with a factorial model: the classical factor analysis (FA) and the item factor analysis (IFA). For FA, maximum likelihood and weighted least squares estimations using Pearson correlation matrices among items are compared. For IFA, diagonally weighted…

  10. A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis

    Science.gov (United States)

    Edwards, Michael C.

    2010-01-01

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

  11. The determinants of the bias in Minimum Rank Factor Analysis (MRFA)

    NARCIS (Netherlands)

    Socan, G; ten Berge, JMF; Yanai, H; Okada, A; Shigemasu, K; Kano, Y; Meulman, JJ

    2003-01-01

    Minimum Rank Factor Analysis (MRFA), see Ten Berge (1998), and Ten Berge and Kiers (1991), is a method of common factor analysis which yields, for any given covariance matrix Sigma, a diagonal matrix Psi of unique variances which are nonnegative and which entail a reduced covariance matrix Sigma-Psi

  12. A Primer on Bootstrap Factor Analysis as Applied to Health Studies Research

    Science.gov (United States)

    Lu, Wenhua; Miao, Jingang; McKyer, E. Lisako J.

    2014-01-01

    Objectives: To demonstrate how the bootstrap method could be conducted in exploratory factor analysis (EFA) with a syntax written in SPSS. Methods: The data obtained from the Texas Childhood Obesity Prevention Policy Evaluation project (T-COPPE project) were used for illustration. A 5-step procedure to conduct bootstrap factor analysis (BFA) was…

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

    Ritter, Nicola L.

    2012-01-01

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

  15. Factors Affecting Online Groupwork Interest: A Multilevel Analysis

    Science.gov (United States)

    Du, Jianxia; Xu, Jianzhong; Fan, Xitao

    2013-01-01

    The purpose of the present study is to examine the personal and contextual factors that may affect students' online groupwork interest. Using the data obtained from graduate students in an online course, both student- and group-level predictors for online groupwork interest were analyzed within the framework of hierarchical linear modeling…

  16. Dispersive analysis of the pion transition form factor

    CERN Document Server

    Hoferichter, Martin; Leupold, Stefan; Niecknig, Franz; Schneider, Sebastian P

    2014-01-01

    We analyze the pion transition form factor using dispersion theory. We calculate the singly-virtual form factor in the time-like region based on data for the $e^+e^-\\to 3\\pi$ cross section, generalizing previous studies on $\\omega,\\phi\\to3\\pi$ decays and $\\gamma\\pi\\to\\pi\\pi$ scattering, and verify our result by comparing to $e^+e^-\\to\\pi^0\\gamma$ data. We perform the analytic continuation to the space-like region, predicting the poorly-constrained space-like transition form factor below 1 GeV, and extract the slope of the form factor at vanishing momentum transfer $a_\\pi=(30.7\\pm0.6)\\times 10^{-3}$. We derive the dispersive formalism necessary for the extension of these results to the doubly-virtual case, as required for the pion-pole contribution to hadronic light-by-light scattering in the anomalous magnetic moment of the muon.

  17. Sexual Opinion Survey: An Exploratory Factor Analysis with Helping Professionals

    Science.gov (United States)

    Bloom, Zachary D.; Gutierrez, Daniel; Lambie, Glenn W.

    2015-01-01

    Counselors and marriage and family therapists work with individuals, couples, and families on issues related to sexuality. However, clinicians may be underserving their clients by "not" having adequate training and preparation to work with clients with these presenting issues. One mitigating factor in the treatment of sexual problems is…

  18. Confirmatory Factor Analysis of the Work Locus of Control Scale

    Science.gov (United States)

    Oliver, Joseph E.; Jose, Paul E.; Brough, Paula

    2006-01-01

    Original formulations of the Work Locus of Control Scale (WLCS) proposed a unidimensional structure of this measure; however, more recently, evidence for a two-dimensional structure has been reported, with separate subscales for internal and external loci of control. The current study evaluates the one- and two-factor models with confirmatory…

  19. Expression analysis of OsbZIP transcription factors in resistance ...

    African Journals Online (AJOL)

    zino

    2013-08-21

    Aug 21, 2013 ... Plant basic leucine zipper (bZIP) proteins play an essential role in the genes ... Key words: OsbZIP transcription factors, rice blast, resistance ... quantitative reverse transcriptions polymerase chain reaction. ... eukaryotes, which shared two common structures: a .... RNA extration and reverse transcription.

  20. A Content Analysis of Protective Factors within States' Antibullying Laws

    Science.gov (United States)

    Weaver, Lori M.; Brown, James R.; Weddle, Daniel B.; Aalsma, Matthew C.

    2013-01-01

    State lawmakers have responded to school bullying by crafting antibullying legislation. By July 2011, 47 states enacted such laws, though varied widely in content and scope. This study systematically evaluated each state's antibullying legislation by focusing on the inclusion of individual, parental, and systemic protective factors through…

  1. Factors Associated with Sexual Behavior among Adolescents: A Multivariate Analysis.

    Science.gov (United States)

    Harvey, S. Marie; Spigner, Clarence

    1995-01-01

    A self-administered survey examining multiple factors associated with engaging in sexual intercourse was completed by 1,026 high school students in a classroom setting. Findings suggest that effective interventions to address teenage pregnancy need to utilize a multifaceted approach to the prevention of high-risk behaviors. (JPS)

  2. A Content Analysis of Factors Affecting New Product Development Process

    Directory of Open Access Journals (Sweden)

    Eda Atilgan-Inan

    2010-07-01

    Full Text Available The objective of this study is to review the international marketing literature on new product development process and compare the changes in the important factors in the process with the changes in the management approaches. For this purpose, the articles in three international marketing journals were selected and “new product development” and “new product performance” were searched for in the abstracts. After grouping the variables in the process, they were compared with the perspectives of management in the related periods. The results indicated that organizational factors have always been important for new product development process, which is in line with the nature of the innovation process. But the emphasis on internal factors has increased in the 21st century which is congruent with the change in management perspective foregrounding resource based view. The study differs from the similar literature review studies on the point that it deals with the topic from international marketing perspective. Therefore, R&D and other marketing studies are not included in the review and the study proposes the important factors from international firms’ point of view.

  3. [Analysis of risk factors for bleeding after thyroid surgery].

    Science.gov (United States)

    Qiu, Xiaoping; Li, Zhengjiang; Liu, Jie; An, Changming; Yin, Yulin; Tang, Pingzhang; Xu, Zhengang

    2016-01-01

    To identify risk factors for bleeding after thyroid surgery, and discuss the potential relevance between the bleeding timing and sources. A total of 2568 cases that underwent thyroid operation from June 2012 to June 2013 were collected and analysed retrospectively the risk factors for postoperative bleeding by Cox and the potential relevance between the bleeding timing and sources. Among 2568 patients, 40 patients occurred postoperative bleeding Indentified risk factors were extent resection (P=0.0435) and surgeon (P=0.0071). Thyroid bed and strap muscles/sternocleidomastoid were the most common sources of bleeding after surgery within 6 hours; while thyroid bed was the most common source of bleeding after surgery between 6 and 8 h; wound errhysis was the most common source during 8-24 h after the operation; thyroid bed and strap muscles/sternocleidomastoid were the most common sources within 24 h after thgroid surgery. Bleeding after thyroid surgery is a rare but potentially life-threatening complication, and the extent of resection and the surgeon are risk factors. Thyroid bed and strap muscles/sternocleidomastoid are the most common sources of bleeding after surgery within 24 hours.

  4. Phantom pain and risk factors : A multivariate analysis

    NARCIS (Netherlands)

    Dijkstra, PU; Geertzen, JHB; Stewart, R; van der Schans, CP

    2002-01-01

    Phantom pain has been given considerable attention in literature. Phantom Pain reduces quality of life, and patients suffering from phantom pain make heavy use of the medical system. Many risk factors have been identified for phantom Pain in univariate analyses, including phantom sensations, stump P

  5. An Analysis of the Social Distance Factor Affecting Language Use

    Institute of Scientific and Technical Information of China (English)

    闫宇

    2015-01-01

    The social distance is the main social factor that influences language use.This paper explores how the social distance affects language use in different ways based on solidarity,status and formality,in order to achieve a better understanding of language use.

  6. An Analysis of Factors Influencing Attitudes Toward Death.

    Science.gov (United States)

    Cox, Gerry R.

    This article assesses the affects of several factors; sex, age, occupation, size of residence, anomie, marital status, class, and world view, on attitudes towards death. The author's attitudes model is based upon the four-part basic Durkheimian typology, varying in degree and nature of an individual's integration in societal groups. Included in…

  7. Analysis of risk factors of cord blood transplantation for children.

    Science.gov (United States)

    Goldstein, Gal; Bielorai, Bella; Stein, Jerry; Stepensky, Polina; Elhasid, Ronit; Zaidman, Irena; Chetrit, Angela; Yaniv, Isaac; Nagler, Arnon; Toren, Amos

    2013-12-01

    As cord blood (CB) is being used frequently as a source for heamtopoetic stem cell transplantation defining risk factors for transplantation outcome is an important issue. The data of all single unit CB transplantation preformed in Israel from 1992 to 2011 were collected. The risk factors for myeloid engraftment, event free survival (EFS) and overall survival (OS) were studied in 87 children. There were 49 children with hematological malignancies and 38 with non-malignant diseases. Cumulative rate of neutrophil recovery was 78.3%, while median time to myeloid recovery was 26 days. The incidence of platelet engraftment at 150 days was 53%, and the median time to platelet recovery was 36 days. ABO blood group matching between CB unit and recipient was associated with superior myeloid engraftment. Acute graft versus host disease of grades II-IV occurred in 33% of the patients. Chronic graft versus host disease occurred in 16% of patients. Probabilities of EFS and OS at 1 year were 45% and 57%, respectively. Factors associated with inferior OS were Rh major mismatch versus matched Rh and transplantation from unrelated donor versus related donor. These results indicate that matching of ABO blood groups is an important factor that affects engraftment, and also that Rh matching seem to have an impact on OS, which was not previously described in the setting of CB transplantation. © 2013 Wiley Periodicals, Inc.

  8. Analysis of The Factors Influencing the Private Cost of Teacher ...

    African Journals Online (AJOL)

    info

    was to determine the actual private unit cost of teacher education as well as the factors ... education was higher in state tertiary institutions than their federal ... project/assignment, teaching practice, study tow/excursion, textbook, stationary ... However, in order to ease the estimation process, the popular methods is to use unit.

  9. Confirmatory Factor Analysis of the Geriatric Depression Scale

    Science.gov (United States)

    Adams, Kathryn Betts; Matto, Holly C.; Sanders, Sara

    2004-01-01

    Purpose: The Geriatric Depression Scale (GDS) is widely used in clinical and research settings to screen older adults for depressive symptoms. Although several exploratory factor analytic structures have been proposed for the scale, no independent confirmation has been made available that would enable investigators to confidently identify scores…

  10. An Analysis of Factors Influencing Attitudes Toward Death.

    Science.gov (United States)

    Cox, Gerry R.

    This article assesses the affects of several factors; sex, age, occupation, size of residence, anomie, marital status, class, and world view, on attitudes towards death. The author's attitudes model is based upon the four-part basic Durkheimian typology, varying in degree and nature of an individual's integration in societal groups. Included in…

  11. INFLUENCE FACTOR ANALYSIS OF CHINESE STUDENTS' LERANING STYLES

    Institute of Scientific and Technical Information of China (English)

    周平

    2009-01-01

    Learning style, aiming at language learner, is a hot issue of second language acquisition. The article first reviews the various definitions of learning style. From the perspective of cognition, three influence factors of Chinese students' learning styles are analyzed. Suggestions are proposed for teachers to help students develop learning styles.

  12. Phantom pain and risk factors : A multivariate analysis

    NARCIS (Netherlands)

    Dijkstra, PU; Geertzen, JHB; Stewart, R; van der Schans, CP

    2002-01-01

    Phantom pain has been given considerable attention in literature. Phantom Pain reduces quality of life, and patients suffering from phantom pain make heavy use of the medical system. Many risk factors have been identified for phantom Pain in univariate analyses, including phantom sensations, stump P

  13. A Content Analysis of Protective Factors within States' Antibullying Laws

    Science.gov (United States)

    Weaver, Lori M.; Brown, James R.; Weddle, Daniel B.; Aalsma, Matthew C.

    2013-01-01

    State lawmakers have responded to school bullying by crafting antibullying legislation. By July 2011, 47 states enacted such laws, though varied widely in content and scope. This study systematically evaluated each state's antibullying legislation by focusing on the inclusion of individual, parental, and systemic protective factors through…

  14. Algorithms for unweighted least-squares factor analysis

    NARCIS (Netherlands)

    Krijnen, WP

    Estimation of the factor model by unweighted least squares (ULS) is distribution free, yields consistent estimates, and is computationally fast if the Minimum Residuals (MinRes) algorithm is employed, MinRes algorithms produce a converging sequence of monotonically decreasing ULS function values.

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

    Science.gov (United States)

    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…

  16. Confirmatory factor analysis of the Child Oral Health Impact Profile (Korean version).

    Science.gov (United States)

    Cho, Young Il; Lee, Soonmook; Patton, Lauren L; Kim, Hae-Young

    2016-04-01

    Empirical support for the factor structure of the Child Oral Health Impact Profile (COHIP) has not been fully established. The purposes of this study were to evaluate the factor structure of the Korean version of the COHIP (COHIP-K) empirically using confirmatory factor analysis (CFA) based on the theoretical framework and then to assess whether any of the factors in the structure could be grouped into a simpler single second-order factor. Data were collected through self-reported COHIP-K responses from a representative community sample of 2,236 Korean children, 8-15 yr of age. Because a large inter-factor correlation of 0.92 was estimated in the original five-factor structure, the two strongly correlated factors were combined into one factor, resulting in a four-factor structure. The revised four-factor model showed a reasonable fit with appropriate inter-factor correlations. Additionally, the second-order model with four sub-factors was reasonable with sufficient fit and showed equal fit to the revised four-factor model. A cross-validation procedure confirmed the appropriateness of the findings. Our analysis empirically supported a four-factor structure of COHIP-K, a summarized second-order model, and the use of an integrated summary COHIP score.

  17. DYNAMIC CHARACTERISTIC ANALYSIS OF FUZZY- STOCHASTIC TRUSS STRUCTURES BASED ON FUZZY FACTOR METHOD AND RANDOM FACTOR METHOD

    Institute of Scientific and Technical Information of China (English)

    MA Juan; CHEN Jian-jun; XU Ya-lan; JIANG Tao

    2006-01-01

    A new fuzzy stochastic finite element method based on the fuzzy factor method and random factor method is given and the analysis of structural dynamic characteristic for fuzzy stochastic truss structures is presented. Considering the fuzzy randomness of the structural physical parameters and geometric dimensions simultaneously, the structural stiffness and mass matrices are constructed based on the fuzzy factor method and random factor method; from the Rayleigh's quotient of structural vibration, the structural fuzzy random dynamic characteristic is obtained by means of the interval arithmetic;the fuzzy numeric characteristics of dynamic characteristic are then derived by using the random variable's moment function method and algebra synthesis method. Two examples are used to illustrate the validity and rationality of the method given. The advantage of this method is that the effect of the fuzzy randomness of one of the structural parameters on the fuzzy randomness of the dynamic characteristic can be reflected expediently and objectively.

  18. Unveiling multiple solid-state transitions in pharmaceutical solid dosage forms using multi-series hyperspectral imaging and different curve resolution approaches

    DEFF Research Database (Denmark)

    Alexandrino, Guilherme L; Amigo Rubio, Jose Manuel; Khorasani, Milad Rouhi

    2017-01-01

    Solid-state transitions at the surface of pharmaceutical solid dosage forms (SDF) were monitored using multi-series hyperspectral imaging (HSI) along with Multivariate Curve Resolution – Alternating Least Squares (MCR-ALS) and Parallel Factor Analysis (PARAFAC and PARAFAC2). First, the solid...... with polyvinylpyrrolidone using time series MIR-HSI. MCR-ALS properly resolved the known solid-state forms of the drug in the pixels of the series MIR-images, while PARAFAC and PARAFAC2 failed to properly resolve all the drug forms in the series MIR-images due to i) strict trilinearity leak in the three-way array and ii......) the mandatory constant cross-product AkTAk over the k series MIR-images (A is the loadings of the shift mode), respectively. The highlighting of the advantages and limitation of the corresponding curve resolution methods stressed their potential applicability when handling multi-series HSI to study solid...

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

    Directory of Open Access Journals (Sweden)

    Gideon P. de Bruin

    2000-06-01

    Full Text Available The scores of 700 Afrikaans-speaking university students on the Comrey Personality Scales and the 16 Personality Factor Questionnaire were subjected to an inter-battery factor analysis. This technique uses only the correlations between two sets of variables and reveals only the factors that they have in common. Three of the Big Five personality factors were revealed, namely Extroversion, Neuroticism and Conscientiousness. However, the Conscientiousness factor contained a relatively strong unsocialised component and in this regard it is similar to Eysencks Psychoticism factor. The results support the construct validity of the Comrey Personality Scales and the 16 Personality Factor Questionnaire. Implications for personality questionnaire design and validation are discussed. OpsommingDie tellings van 700 Afrikaanssprekende universiteitstudente vir die Comrey Persoonlikheidskale en die 16 Per- soonlikheidsfaktorvraelys is aan 'n interbattery-faktorontleding onderwerp. Hierdie tegniek gebruik slegs die korrelasies tussen twee stelle veranderlikes en ontbloot slegs faktore wat die twee stelle veranderlikes gemeen het. Drie van die faktore van die vyfFaktormodel is blootgele, naamlik Ekstroversie, Neurotisisme en Konsensieusheid. Die Konsensieusheidsfaktor het ook n relatief sterk ongesosialiseerdheidskomponent ingesluit en in hierdie sin is dit soortgelyk aan Eysenck se Psigotisisme faktor. Die resultate ondersteun die konstrukgeldigheid van die Comrey Persoonlikheidskale en die 16 Persoonlikheidsfaktorvraelys. Implikasies vir die ontwerp en validering van persoonlikheidstoetse word bespreek.

  20. ANALYSIS OF DEATH FACTORS FOR ACUTE HEMORRHAGIC NECROTIZING PANCREATITIS

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    Objective:To analyse the factors affecting the mortality of acute hemorrhagic necrotizing pancreatitis (AHNP). Methods:One hundred and twelve patients with AHNP were retrospectively divided into two groups--the dead and survivors. Some parameters were analysed statistically.Results:The average age,sex ratio and onset of illness were similar between two groups. The difference of early shock, early ARDS, high body temperature, leukocytosis and high blood glucose between two groups were not significant. The important factors affecting the mortality were: severe pancreatic necrosis; incorrect therapeutic surgery;improper surgical methods.Conclusion: The patients with mild or moderate AHNP should mainly receive conservative treatment for 48~72 hours. The early shock and ARDS should be corrected before surgical intervention, the swelling pancreas should be dissected fully and duodenostomy should be performed in operation.

  1. Factors Influencing Renewable Energy Production & Supply - A Global Analysis

    Science.gov (United States)

    Ali, Anika; Saqlawi, Juman Al

    2016-04-01

    Renewable energy is one of the key technologies through which the energy needs of the future can be met in a sustainable and carbon-neutral manner. Increasing the share of renewable energy in the total energy mix of each country is therefore a critical need. While different countries have approached this in different ways, there are some common aspects which influence the pace and effectiveness of renewable energy incorporation. This presentation looks at data and information from 34 selected countries, analyses the patterns, compares the different parameters and identifies the common factors which positively influence renewable energy incorporation. The most successful countries are analysed for their renewable energy performance against their GDP, policy/regulatory initiatives in the field of renewables, landmass, climatic conditions and population to identify the most influencing factors to bring about positive change in renewable energy share.

  2. A Univariate Analysis of Risk Factors for Diabetic Nephropathy

    Directory of Open Access Journals (Sweden)

    Yee Hung Choy

    2006-12-01

    Full Text Available This paper uses actual data from 267 patients with non-insulin-dependent (Type 2 diabetes mellitus in order to see how the various risk factors can affect the progression of diabetic nephropathy. Examination of each independent variable individually can only provide a preliminary idea of how important each variable is by itself. The relative importance of all the variables has to be examined simultaneously by multivariate methods. The approach succeeds in identifying preliminary risk factors such as smoking for males, although the females had higher fasting blood glucose at diagnosis. Not surprisingly, hypertension is common among patients of both sexes and it has an association with proteinuria in female patients in the sample.

  3. Factor Analysis of Enterprise Internet+ Impetus Based on System Dynamics

    Directory of Open Access Journals (Sweden)

    Cao Haiwang

    2017-01-01

    Full Text Available Internet+ plays an important role in the transition and upgrading of enterprises in this era. To promote enterprise Internet+ implementation, this paper studies the influencing factors in enterprise Internet+ impetus. First, based on system dynamics, the influencing factors of enterprise Internet+ impetus are analyzed as well as their relationships. Then, a system dynamics model is established and Vensim PLE is utilized to simulate the model. Finally, some suggestions about the Internet+ implementation are given. The simulation results show that technological environment, government policy and information asymmetry all have different influence on the enterprise Internet+ impetus and different strategies can be taken to change their influence. This study is helpful for enterprises to understand the Internet+ impetus mechanism thus promote Internet+ implementation.

  4. Computational Fluid Dynamics Analysis of Butterfly Valve Performance Factors

    OpenAIRE

    Del Toro, Adam

    2012-01-01

    Butterfly valves are commonly used in industrial applications to control the internal flow of both compressible and incompressible fluids. A butterfly valve typically consists of a metal disc formed around a central shaft, which acts as its axis of rotation. As the valve's opening angle is increased from 0 degrees (fully closed) to 90 degrees (fully open), fluid is able to more readily flow past the valve. Characterizing a valve's performance factors, such as pressure drop, hydrodynamic torqu...

  5. Investigating product development strategy in beverage industry using factor analysis

    OpenAIRE

    Naser Azad; Seyed Mohsen Seyed Aliakbar; Seyed Foad Zarifi; Somayeh Hozouri

    2013-01-01

    Selecting a product development strategy that is associated with the company's current service or product innovation, based on customers’ needs and changing environment, plays an important role in increasing demand, increasing market share, increasing sales and profits. Therefore, it is important to extract effective variables associated with product development to improve performance measurement of firms. This paper investigates important factors influencing product development strategies us...

  6. Risk Factors for Gambling Problems: An Analysis by Gender.

    Science.gov (United States)

    Hing, Nerilee; Russell, Alex; Tolchard, Barry; Nower, Lia

    2016-06-01

    Differences in problem gambling rates between males and females suggest that associated risk factors vary by gender. Previous combined analyses of male and female gambling may have obscured these distinctions. This study aimed to develop separate risk factor models for gambling problems for males and for females, and identify gender-based similarities and differences. It analysed data from the largest prevalence study in Victoria Australia (N = 15,000). Analyses determined factors differentiating non-problem from at-risk gamblers separately for women and men, then compared genders using interaction terms. Separate multivariate analyses determined significant results when controlling for all others. Variables included demographics, gambling behaviour, gambling motivations, money management, and mental and physical health. Significant predictors of at-risk status amongst female gamblers included: 18-24 years old, not speaking English at home, living in a group household, unemployed or not in the workforce, gambling on private betting, electronic gaming machines (EGMs), scratch tickets or bingo, and gambling for reasons other than social reasons, to win money or for general entertainment. For males, risk factors included: 18-24 years old, not speaking English at home, low education, living in a group household, unemployed or not in the workforce, gambling on EGMs, table games, races, sports or lotteries, and gambling for reasons other than social reasons, to win money or for general entertainment. High risk groups requiring appropriate interventions comprise young adults, especially males; middle-aged female EGM gamblers; non-English speaking populations; frequent EGM, table games, race and sports gamblers; and gamblers motivated by escape.

  7. Analysis of Affective Factors and Corresponding Solution in English Teaching

    Institute of Scientific and Technical Information of China (English)

    张劲松

    2009-01-01

    Affect is the related issues that influence the students' learning progress and result, including one's interest, emotion, self-confidence and so on. Affective factors are the motivation for the students' learning. In the past few decades, people have always been pursuing the effective methods of teaching, from the Grammar Translation Method, to Communicative Language Teaching. Now people start to focus on affective teaching and have got some good result.

  8. Classification tree analysis of factors affecting parking choices in Qatar

    OpenAIRE

    Shaaban, K.; Pande, A

    2015-01-01

    Qatar has experienced a significant population growth in the past decade. The growth has been accompanied by an increase in automobile ownership rates leading to parking problems especially in the capital city of Doha. The objective of this study was to find the factors affecting people's choice of parking in this rich developing country when different parking options are available. Two commercial centers located in the city of Doha, Qatar were selected for this study; the City Center mall an...

  9. ANALYSIS FACTORS THAT AFFECTING THE WORK COMMITMENT OF TEACHERS

    Directory of Open Access Journals (Sweden)

    Marsofiyati

    2015-10-01

    Full Text Available The purpose of this research is to analyze the factors that affecting the work commitment of teachers.The research use descriptive quantitative method. The problem are the teachers who work without commitment, just to teach according to what was ordered by the principal. By having a high work commitment that is evident in the behavior of painstaking work, passionate, integrity of the work, responsibility, and maintain morale as educators. The results are: commitment to working both seen from the achievement an average score of 71.61, completion of the task is the highest factor in teachers' work commitment with an average score of 79.67, and development of self-efficacy is the lowest factor in teachers' work commitment with an average score of 73.00.Suggestions are: schools should give rewards to the teachers who complete the task on time and to sanction teachers who did not complete the task on time, provide education and training to the teachers continuously and sustainably as efforts to develop self-efficacy ofteachers, the teacher involvement in school activities further improved, so that the visible concern for the fate of school teachers and Teacher work program should be set up and executed in accordance with a predetermined plan.

  10. Analysis of psychological factors which interfere in soccer athletes’ behaviour

    Directory of Open Access Journals (Sweden)

    Constanza Pujals

    2008-06-01

    Full Text Available The aim of this study is to analyze the psychological factors which interfere in soccer athletes’s behaviour, juvenile and infant categories. 40 athletes from a soccer school in Maringá – PR were studied and the instruments used were: inventories, interviews, questionnaires and research diary. Data were collected individually and in group. Intervention occurred for 12 months through observation, evaluation and showed the following factors: motivation, anxiety, aggression and self confidence. Results pointed out that the positive emotions expressed by the athletes were good mood, happiness, relaxation, interest in improving and hope while negative emotions were anxiety, rage, aggressiveness, low self-confidence, lack of motivation, insecurity, feeling of failure, pessimism and group instability. Relatives and coach were also generating factors of stress and anxiety. Thus, this sporting context shows that the sports psychology seems to be highly efficient to reduce anxiety and agression indexes as well as to increase motivation and self-confidence, demonstrating the importance of psychological preparation for sporting training.

  11. Factor Analysis of the DePaul Symptom Questionnaire: Identifying Core Domains

    OpenAIRE

    Jason, Leonard A.; Sunnquist, Madison; Brown, Abigail; Furst, Jacob; Cid, Marjoe; Farietta, Jillianna; Kot, Bobby; Bloomer, Craig; Nicholson, Laura; Williams, Yolonda; Jantke, Rachel; Newton, Julia L.; Strand, Elin Bolle

    2015-01-01

    The present study attempted to identify critical symptom domains of individuals with Myalgic Encephalomyelitis (ME) and chronic fatigue syndrome (CFS). Using patient and control samples collected in the United States, Great Britain, and Norway, exploratory factor analysis (EFA) was used to establish the underlying factor structure of ME and CFS symptoms. The EFA suggested a four-factor solution: post-exertional malaise, cognitive dysfunction, sleep difficulties, and a combined factor consisti...

  12. Bayesian non-negative factor analysis for reconstructing transcription factor mediated regulatory networks

    Directory of Open Access Journals (Sweden)

    Chen Yidong

    2011-10-01

    Full Text Available Abstract Background Transcriptional regulation by transcription factor (TF controls the time and abundance of mRNA transcription. Due to the limitation of current proteomics technologies, large scale measurements of protein level activities of TFs is usually infeasible, making computational reconstruction of transcriptional regulatory network a difficult task. Results We proposed here a novel Bayesian non-negative factor model for TF mediated regulatory networks. Particularly, the non-negative TF activities and sample clustering effect are modeled as the factors from a Dirichlet process mixture of rectified Gaussian distributions, and the sparse regulatory coefficients are modeled as the loadings from a sparse distribution that constrains its sparsity using knowledge from database; meantime, a Gibbs sampling solution was developed to infer the underlying network structure and the unknown TF activities simultaneously. The developed approach has been applied to simulated system and breast cancer gene expression data. Result shows that, the proposed method was able to systematically uncover TF mediated transcriptional regulatory network structure, the regulatory coefficients, the TF protein level activities and the sample clustering effect. The regulation target prediction result is highly coordinated with the prior knowledge, and sample clustering result shows superior performance over previous molecular based clustering method. Conclusions The results demonstrated the validity and effectiveness of the proposed approach in reconstructing transcriptional networks mediated by TFs through simulated systems and real data.

  13. Confirmatory factor analysis, latent profile analysis, and factor mixture modeling of the syndromes of the Child Behavior Checklist and Teacher Report Form.

    Science.gov (United States)

    Gomez, Rapson; Vance, Alasdair

    2014-12-01

    The current study used confirmatory factor analysis (CFA), latent profile analysis (LPA), and factor mixture modeling (FMM) to examine the co-occurrence of the childhood syndromes using the Child Behavior Checklist (CBCL) and Teacher Report Form (TRF). Parents and teachers completed the CBCL and TRF, respectively, for a clinic-referred sample of 720 children, ages 7-12 years. For the CBCL, the analyses indicated most support a 2-class 2-factor FMM, and for the TRF, there was most support for a 2-class 3-factor model. The classes were all syndromes at average levels and all syndromes at high levels. The findings indicate high syndrome co-occurrence. The implications of the findings for understanding syndrome co-occurrence in the CBCL and TRF, theories of syndrome co-occurrence, and the clinical use of the CBCL and TRF are discussed. (c) 2014 APA, all rights reserved.

  14. The Factors Analysis on Food Safety Accidents Statistics

    Directory of Open Access Journals (Sweden)

    Boyi Xiang

    2015-05-01

    Full Text Available The study uses SPSS17.0 analysis of validity and reliability of the food enterprises questionnaire. Using AMOS17. 0 software for structural equation model test of goodness of fit and analysis of on the path. From the “melamine” to “Sudanred” and “steroid-tainted pork” events that have been exposed recently, series of typical food safety incidents resulted in the emergence of food safety issues become the focus of attention. A series of food processing can be contaminated by harmful substances, resulting in harmful food, thus constituting food safety issues and poses a serious threat to public and person’s health.

  15. Análisis del fracaso empresarial por sectores: factores diferenciadores = Cross-industry analysis of business failure: differential factors

    Directory of Open Access Journals (Sweden)

    María Jesús Mures Quintana

    2012-03-01

    Full Text Available El objetivo de este trabajo se centra en el análisis del fracaso empresarial por sectores, a fin de identificar los factores explicativos y predictivos de este fenómeno que son diferentes en tres de los principales sectores que se distinguen en toda economía: industria, construcción y servicios.Para cada uno de estos sectores, seguimos el mismo procedimiento. En primer lugar, aplicamos un análisis de componentes principales con el que identificamos los factores explicativos del fracaso empresarial en los tres sectores. A continuación, consideramos dichos factores como variables independientes en un análisis discriminante, que aplicamos para predecir el fracaso de una muestra de empresas, utilizando no sólo información financiera en forma de ratios, sino también otras variables no financieras relativas a las empresas, así como información externa a las mismas que refleja las condiciones macroeconómicas bajo las que desarrollan su actividad.This paper focuses on a cross-industry analysis of business failure, in order to identify the explanatory and predictor factors of this event that are different in three of the main industries in every economy: manufacturing, building and service. For each one of these industries, the same procedure is followed. First, a principal components analysis is applied in order to identify the explanatory factors of business failure in the three industries. Next, these factors are considered as independent variables in a discriminant analysis, so as to predict the firms’ failure, using not only financial information expressed by ratios, but also other non-financial variables related to the firms, as well as external information that reflects macroeconomic conditions under which they develop their activity.

  16. Análisis del fracaso empresarial por sectores: factores diferenciadores = Cross-industry analysis of business failure: differential factors

    Directory of Open Access Journals (Sweden)

    María Jesús Mures Quintana

    2012-12-01

    Full Text Available El objetivo de este trabajo se centra en el análisis del fracaso empresarial por sectores, a fin de identificar los factores explicativos y predictivos de este fenómeno que son diferentes en tres de los principales sectores que se distinguen en toda economía: industria, construcción y servicios. Para cada uno de estos sectores, seguimos el mismo procedimiento. En primer lugar, aplicamos un análisis de componentes principales con el que identificamos los factores explicativos del fracaso empresarial en los tres sectores. A continuación, consideramos dichos factores como variables independientes en un análisis discriminante, que aplicamos para predecir el fracaso de una muestra de empresas, utilizando no sólo información financiera en forma de ratios, sino también otras variables no financieras relativas a las empresas, así como información externa a las mismas que refleja las condiciones macroeconómicas bajo las que desarrollan su actividad. This paper focuses on a cross-industry analysis of business failure, in order to identify the explanatory and predictor factors of this event that are different in three of the main industries in every economy: manufacturing, building and service. For each one of these industries, the same procedure is followed. First, a principal components analysis is applied in order to identify the explanatory factors of business failure in the three industries. Next, these factors are considered as independent variables in a discriminant analysis, so as to predict the firms’ failure, using not only financial information expressed by ratios, but also other non-financial variables related to the firms, as well as external information that reflects macroeconomic conditions under which they develop their activity.

  17. A Bayes factor meta-analysis of Bem's ESP claim

    NARCIS (Netherlands)

    Rouder, Jeffrey N.; Morey, Richard D.

    In recent years, statisticians and psychologists have provided the critique that p-values do not capture the evidence afforded by data and are, consequently, ill suited for analysis in scientific endeavors. The issue is particular salient in the assessment of the recent evidence provided for ESP by

  18. Confirmatory Factor Analysis on the Big 5 Personality Test Inventory

    Science.gov (United States)

    Kamarulzaman, Wirawani; Nordin, Mohamad Sahari

    2012-01-01

    This paper is intended to examine the validity of Big 5 Personality test inventory of 44 questions with 5-Likert Scale measurement. Confirmatory factory analysis (CFA) was conducted to determine the good fit indices of the 5 personality types. Those types are 1) extraversion, 2) agreeableness, 3) conscientiousness, 4) openness and 5) neuroticism.…

  19. Exploratory Factor Analysis of Reading, Spelling, and Math Errors

    Science.gov (United States)

    O'Brien, Rebecca; Pan, Xingyu; Courville, Troy; Bray, Melissa A.; Breaux, Kristina; Avitia, Maria; Choi, Dowon

    2017-01-01

    Norm-referenced error analysis is useful for understanding individual differences in students' academic skill development and for identifying areas of skill strength and weakness. The purpose of the present study was to identify underlying connections between error categories across five language and math subtests of the Kaufman Test of…

  20. A Bayes factor meta-analysis of Bem's ESP claim

    NARCIS (Netherlands)

    Rouder, Jeffrey N.; Morey, Richard D.

    2011-01-01

    In recent years, statisticians and psychologists have provided the critique that p-values do not capture the evidence afforded by data and are, consequently, ill suited for analysis in scientific endeavors. The issue is particular salient in the assessment of the recent evidence provided for ESP by

  1. [Determination and analysis of protein profile of different transfer factors].

    Science.gov (United States)

    Guidos-Fogelbach, Guillermo Arturo; Paredes-Aguilar, Jorge Antonio; Colín-Martínez, Nayeli Montserrat; Rojo-Gutiérrez, María Isabel; López-Hidalgo, Marisol; Reyes-López, César Augusto Sandino

    2016-01-01

    Introducción: El factor de transferencia (FT) es el extracto dializable de leucocitos con propiedades de transferencia de inmunidad celular. Su uso se ha extendido en el tratamiento de una amplia gama de padecimientos inmunológicos, infecciosos y como coadyuvante de padecimientos oncológicos. A pesar de ello, no se conocen completamente aspectos importantes de su perfil proteico, concentraciones de componentes y mecanismos de acción. Objetivos: Analizar los perfiles proteicos de diferentes factores de transferencia comercializados en México. Métodos: Se obtuvieron y analizaron 6 FT comercializados en México. Se realizó la cuantificación de proteínas por el método de Bradford, cromatografía líquida de alta resolución (HPLC) y electroforesis en geles de poliacrilamida (SDS-PAGE). Todas las muestras fueron analizadas por duplicado. Resultados: Las concentraciones de proteínas totales de todos los FT analizados fueron menores de 0.2 mg/mL. Los perfiles cromatográficos mostraron diferencias en algunos FT. La concentración de proteínas resultó de 6 hasta casi mil veces más baja en comparación con lo informado por algunos fabricantes. Conclusión: Casi la totalidad de los factores de transferencia comercializados en México carecen de un etiquetado y registro sanitario que cumpla con las normas oficiales vigentes.

  2. Modern Integration Units: Comparative Analysis Of The Growth Factors

    Directory of Open Access Journals (Sweden)

    Bulat Doskalievich Khusainov

    2015-03-01

    Full Text Available In the article, the results of the research, which purpose is to ground and assess the factors of economic growth of regional integration communities and national economies of member countries that develop them, are presented. The foreign trade, mutual trade turnover, and domestic demand are allocated as such factors. The authors has applied the novelty in their methodology which in contrast to the traditional assessment method of growth factors of integration communities and their participants, is based on comparison of two components — external and domestic demand, based on dividing the external demand on two components: the first one is pure export (the difference between export and import is a component of cumulative demand of goods in integration community, i.e. the pure export of mutual trade; the second one is a pure export of foreign trade of goods outside of the integration association. Scope of the research is seven most known regional integrated units arose at different times and being at different stages of development — the European Union, North American Free Trade Area, Association of Southeast Asian Nations, Southern American Common Market, Asia-Pacific Economic Cooperation, and also member countries of the Eurasian integration — the Customs Union and Common Free Market Zone developed into the Eurasian Economic Union in January 1, 2015. In conclusion, it is noted that the integration develops successfully only in the conditions of the rise in national economies of the participating countries. Crisis economies have to deal more with internal problems than to resolve integration issues.

  3. Analysis and Comparison of Factors Influencing University Choice

    Directory of Open Access Journals (Sweden)

    Navratilova Tereza

    2013-09-01

    Full Text Available This study applies the theory of planned behaviour to a university’s selection process. Within the structural equation modelling a measurement model is defined for two types of universities - economic and technical. Furthermore, it is examined whether the designed manifest variables determine the latent variables featured in the theory of planned behaviour, namely the attitudes toward the behaviour, subjective norm, and perceived behavioural control. Based on the values of standardized regression coefficients for each of the factors, comparison between the students of economic and technical faculties was carried out.

  4. Analysis on the risk factors of second fracture in osteoporosis-

    Directory of Open Access Journals (Sweden)

    RUAN Wen-dong

    2011-04-01

    Full Text Available 【Abstract】 Objective: To explore the clinical characteristics and risk factors of refracture in patients suffering from osteoporosis-related fractures as well as effective interventions. Methods: From January 2006 to January 2008, both out-patients and in-patients in our hospital who were over 50 years old and suffered from osteoporosis-related fractures were selected for this research. They were divided into fracture group and refracture group. The refracture rate was followed up for 2 years, during which 11 patients developed refracture, thus were included in the refracture group. Therefore, 273 patients, 225 first-fracture cases, aged (67.7± 8.5 years, and 48 refracture cases, aged (72.7±9.5 years, were included in this study. General data including age and sex, fracture types, femoral neck bone mineral density (BMD T-scores tested by dual-energy X-rays absorptiometry (DEXA, Charlson index, time-frame between two fractures as well as mobility skill assessment were collected and analyzed by single-factor and multivariate statistical methods. Results: Females accounted for 70.2% of the fracture group and 77.1% of the refracture group. The most common refracture type was vertebral fracture for the first time and femoral neck fracture for the second time during the followup. The second fracture happened 3.7 years after the first one on average. The refracture rate was 2.12% within one year, and 4.66% within two years. Risk factors for a second fracture in osteoporotic fracture patients included age (>75 years, HR=1.23, 95%CI 1.18-1.29; >85 years, HR=1.68, 95% CI 1.60-1.76, female sex (HR=1.36, 95%CI 1.32-1.40, prior vertebral fractures (HR=1.62, 95%CI 1.01-2.07, prior hip fractures (HR=1.27, 95%CI 0.89-2.42, BMD T-score<-3.5 (HR=1.38, 95%CI 1.17-1.72 and weakened motor skills (HR=1.27, 95%CI 1.09-1.40. Conclusions: The risks of second fracture among patients with initial brittle fracture are substantial. There is adequate time between the

  5. Analysis of related factors affecting prognosis of shunt surgery in patients with secondary normal pressure hydrocephalus

    Institute of Scientific and Technical Information of China (English)

    WANG Cheng; DU Hang-gen; YIN Li-chun; HE Min; ZHANG Guo-jun; TIAN Yong; HAO Bi-lie

    2013-01-01

    Objective:The management of secondary normal pressure hydrocephalus (sNPH) is controversial.Many factors may affect the surgery effect.The purpose of this study was to identify the possible factors influencing prognosis and provide theoretical basis for clinical treatment of sNPH.Methods:A retrospective study was carried out to investigate the results of 31 patients with sNPH who underwent ventriculoperitoneal shunt surgery from January 2007 to December 2011.We processed the potential influencing factors by univariate analysis and the result further by multivariate logistic regression analysis.Results:Factors including age,disease duration and Glasgow coma scale (GCS) score before surgery significantly influenced the prognosis of sNPH (P<0.05).Further logistic regression analysis showed that all the three factors are independent influencing factors.Conclusion:Age,disease duration and GCS score before surgery have positive predictive value in estimating favorable response to surgical treatment for sNPH.

  6. A confirmatory factor analysis of the Self-Directed Learning Readiness Scale.

    Science.gov (United States)

    Williams, Brett; Brown, Ted

    2013-12-01

    The Self-Directed Learning Readiness Scale measures readiness for self-directed learning among undergraduate healthcare students. While several exploratory factor analyses and one confirmatory factor analysis have examined the psychometric properties of the Self-Directed Learning Readiness Scale, questions have been raised regarding the underlying latent constructs being measured. The objective of this study was to determine the best-fitting Self-Directed Learning Readiness Scale factorial structure among three models published in the literature. Data from the three-factor 40-item Self-Directed Learning Readiness Scale completed by 233 undergraduate paramedic students from four Australian universities (response rate of 26%) were analyzed using maximum likelihood confirmatory factor analysis. Comparison of model fit from the 40-item version was undertaken with the previously documented four-factor 36-item and three-factor 29-item Self-Directed Learning Readiness Scales. The model fit indices of the three one-factor congeneric models with maximum likelihood analysis demonstrate that the 40-item Self-Directed Learning Readiness Scale does not fit the data well. The best fitting model was the four-factor 36-item Self-Directed Learning Readiness Scale followed by the three-factor 29-item models. The confirmatory factor analysis results did not support the overall construct validity of the original 40-item Self-Directed Learning Readiness Scale. © 2013 Wiley Publishing Asia Pty Ltd.

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

    Science.gov (United States)

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

    2017-06-01

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

  8. A Keyword Analysis for Human Resource Management Factors

    Directory of Open Access Journals (Sweden)

    Muhammed Kürşad ÖZLEN

    2014-05-01

    Full Text Available With the constant increasing in technology and education, with development of multinational corporations and frequent changes in economic status and structures, Human Resources become the most crucial, the most reliable and necessary department. Moreover, in many companies, Human Resource Department is the most important department. The main purpose of this research is to mark off top rated factors related with Human Resource Management by analyzing all the abstracts of the published papers of a Human Resource Management journal for the period between the first issue of 2005 and the first issue of 2013. We identified the most frequent categories of the articles during this analyzed period. The literature is reviewed according to the identified factors related to Human Resource Management. If the keywords about Human Resources (35,7 % is not considered, it is observed that the researches, for the selected period, have organizational approach (39,2 % (Management, organizational strategy, organizational performance, organizational culture, contextual issues, technical issues and location and from the individual approach (24,4 % (Individual performance, training and education, employee rights, and behavioral issues. Furthermore, it is also observed that the researchers (a mainly give importance to the practice more than the theory and (b consider the organization more than the individual.

  9. An intergrative factor analysis of leadership measures and theories.

    Science.gov (United States)

    Sweney, A B; Fiechtner, L A; Samores, R J

    1975-05-01

    Since the instruments for measuring most of the current leadership models have never been reconciled, it is important that the relationships between them be clearly understood before assumptions of similarity are made. A sample of 103 male working students were given a battery of tests measuring leadership orientations. The tests included role preference and role pressure measures from Sweney's Response to Power Model, the California F Scale, Fiedler's Least Preferred Co-Worker Scale and Assumed Similarity Between Opposites Scale, Costley and Downey's six scales to measure McGregor's "Theory X" and "Theory Y" constructs, modified scales for the Blake and Mouton Managerial Grid, and relevant scales from the 16 PF. The results were intercorrelated and yielded 11 varimax factors based upon a Guttman criterion, as follows: Authoritarian Role Preferance, Authoritarian Role Pressure, Equalitarian Role Preferance, Equalitarian Role Pressure, Balanced Manager, People Oriented Manager, Assumed Similarity Between Opposites, Contemptuous Indulgence, Supportive Values, People Tolerance, and Organizational Tolerance. The instruments measuring authoritarianism loaded the first factor in the right direction, but most of them had their primary loadings elsewhere, suggesting greater conceptual complexity to this area than previously recognized.

  10. Affinity purification strategies for proteomic analysis of transcription factor complexes.

    Science.gov (United States)

    Giambruno, Roberto; Grebien, Florian; Stukalov, Alexey; Knoll, Christian; Planyavsky, Melanie; Rudashevskaya, Elena L; Colinge, Jacques; Superti-Furga, Giulio; Bennett, Keiryn L

    2013-09-06

    Affinity purification (AP) coupled to mass spectrometry (MS) has been successful in elucidating protein molecular networks of mammalian cells. These approaches have dramatically increased the knowledge of the interconnectivity present among proteins and highlighted biological functions within different protein complexes. Despite significant technical improvements reached in the past years, it is still challenging to identify the interaction networks and the subsequent associated functions of nuclear proteins such as transcription factors (TFs). A straightforward and robust methodology is therefore required to obtain unbiased and reproducible interaction data. Here we present a new approach for TF AP-MS, exemplified with the CCAAT/enhancer binding protein alpha (C/EBPalpha). Utilizing the advantages of a double tag and three different MS strategies, we conducted a total of six independent AP-MS strategies to analyze the protein-protein interactions of C/EBPalpha. The resultant data were combined to produce a cohesive C/EBPalpha interactome. Our study describes a new methodology that robustly identifies specific molecular complexes associated with transcription factors. Moreover, it emphasizes the existence of TFs as protein complexes essential for cellular biological functions and not as single, static entities.

  11. Analysis of factors influencing prognosis in foals with septic arthritis

    Directory of Open Access Journals (Sweden)

    Vos Nicolas J

    2008-02-01

    Full Text Available Abstract The purpose of this paper was to identify factors that would positively or negatively affect the short-term survival rate of foals with septic arthritis. Medical records of 81 foals (≤seven months of age with a clinical diagnosis of septic arthritis, referred to the equine hospital at Cornell University Hospital for Animals, between 1994 and 2003 were reviewed. Signalment, age at presentation, number of affected joints, joint fluid parameters, bacterial agents, treatment modalities and year of treatment were compared between survivors and nonsurvivors. Sixty-two of 81 foals (77% were discharged from the hospital and classified as 'survivors'. Multiple joint involvement and detection of intra-articular Gram-negative, mixed bacterial infection and degenerate neutrophils were negatively associated with short-term survival. Initiation of treatment within 24 hrs of onset of clinical signs and combination of treatment modalities were positively correlated with survival. Further investigation is needed to determine if these two factors have a similar influence on athletic performance.

  12. [Analysis of related factors of slope plant hyperspectral remote sensing].

    Science.gov (United States)

    Sun, Wei-Qi; Zhao, Yun-Sheng; Tu, Lin-Ling

    2014-09-01

    In the present paper, the slope gradient, aspect, detection zenith angle and plant types were analyzed. In order to strengthen the theoretical discussion, the research was under laboratory condition, and modeled uniform slope for slope plant. Through experiments we found that these factors indeed have influence on plant hyperspectral remote sensing. When choosing slope gradient as the variate, the blade reflection first increases and then decreases as the slope gradient changes from 0° to 36°; When keeping other factors constant, and only detection zenith angle increasing from 0° to 60°, the spectral characteristic of slope plants do not change significantly in visible light band, but decreases gradually in near infrared band; With only slope aspect changing, when the dome meets the light direction, the blade reflectance gets maximum, and when the dome meets the backlit direction, the blade reflectance gets minimum, furthermore, setting the line of vertical intersection of incidence plane and the dome as an axis, the reflectance on the axis's both sides shows symmetric distribution; In addition, spectral curves of different plant types have a lot differences between each other, which means that the plant types also affect hyperspectral remote sensing results of slope plants. This research breaks through the limitations of the traditional vertical remote sensing data collection and uses the multi-angle and hyperspectral information to analyze spectral characteristics of slope plants. So this research has theoretical significance to the development of quantitative remote sensing, and has application value to the plant remote sensing monitoring.

  13. Total Factor Evaluation and Influencing Factor Analysis about Arable Land Productivity In Kaifeng City

    Institute of Scientific and Technical Information of China (English)

    Yongying HUANG; Liutao LIANG

    2016-01-01

    This paper uses DEA and Malmquist index to analyze the changes in arable land productivity in Kaifeng City during 2003- 2012.The results show that during 2003- 2011,Kaifeng’s arable land productivity was inefficient in DEA-terms,indicating that the production resources were not rationally used; in 2012,Kaifeng’s arable land productivity was efficient in DEA-terms,indicating that the ratio of input to output in 2012 was optimal; with the lapse of time,the Malmquist total factor productivity showed a trend of " increase-decrease-increase-decrease-increase",and the average technical efficiency was greater than 1,indicating that the agricultural production technology continues to advance. Using Tobit model,we analyze the factors that affect arable land productivity,and results show that the number of large and medium tractors and policy dummy variable have a significantly positive impact,while grain sown area has a significantly negative impact. Therefore,in order to improve arable land productivity in Kaifeng City,it is necessary to adhere to long-term stable agricultural support policy,improve the technological level of new agricultural modernization,increase investment in agricultural science and technology,and expand the sown area of cash crops.

  14. Legitimacy as an Operational Factor: An Alternative Analysis

    Science.gov (United States)

    2006-10-23

    Stephen E. O’Rear Lieutenant Colonel, United States Air Force A paper submitted to the Faculty of the Naval War College in partial... Nietzsche , are but a few of those who have sought simple answers to complex questions regarding the nature of life, religion, and morality among other...failure to achieve the desired end state .”8 This paper presents a dissenting opinion, offering an alternative analysis that legitimacy is best viewed as

  15. The Italian version of the Junior Eysenck Personality Questionnaire: a confirmatory factor analysis.

    Science.gov (United States)

    Vidotto, Giulio; Cioffi, Raffaele; Saggino, Aristide; Wilson, Glenn

    2008-12-01

    An experimental version of the Italian Junior Eysenck Personality Questionnaire with a 5-point scale was administered to a group of 1,000 high school students, 200 within each age group from 11 to 15 years. Following a previous exploratory factor analysis, which yielded a fourth factor in addition to the original three, the aim of the present research was to study the factor structure of the Italian version using confirmatory factor analysis. Three models were tested, a three-factor orthogonal model, a three-factor oblique model, and a four-factor model based on an a priori separation of extraversion items into two sets. None of the considered models converged satisfactorily. An interpretation of the results was proposed.

  16. Factor analysis of the interrelationships between clinical variables in horses with colic.

    Science.gov (United States)

    Thoefner, M B; Ersbøll, A K; Jensen, A L; Hesselholt, M

    2001-02-16

    A prospective survey of horses with colic referred to the Large Animal Hospital at the Royal Veterinary and Agricultural University of Copenhagen, Denmark, was undertaken between August 1994 and December 1997. The interrelationships between 17 clinical variables were analysed using factor analysis. Factor analysis uncovers the structure of the variability in data and therefore detects multicollinearity. A total of 528 horses were admitted in the study period. Of these, 16 were excluded from the analysis as a result of miscellaneous conditions. Only 205 horses had observations for all 17 variables. Because no major change occurred in the main diagnostic categories, this population was considered as a representative subset. Factor analysis confirmed the clinical impression of correlation between variables, but the multicollinearity turned out not to be strong. Four factors were extracted, and these accounted for 51% of the total variance. The retained factors were interpreted by integrating previously reported clinical research. The first factor, which was interpreted as endotoxaemia, had high loadings on capillary refill time, mucous-membrane colour, degree of pain, heart rate, packed-cell volume and abdominal sounds. In the second factor, cecal decompression, admission month and gastric reflux had the predominant influence, and this factor was explained as cecal tympany. The third factor was simply interpreted as age because it had high loadings on gender, age and temperature. In the fourth factor, the interpretation was not straightforward, although breed had the greatest influence in the formation of this factor. Subsequently, the extracted factors were used in a logistic-regression analysis to determine their association with outcome (survival/death). The two factors interpreted as endotoxaemia and age were related to the outcome.

  17. Analysis of GSCM Practices Factors and Sub Factors for Implementation of GSCM in Manufacturing Industries

    Directory of Open Access Journals (Sweden)

    Rituraj Chandraker; Rajesh Kumar ; Apoorv Tiwari

    2013-10-01

    Full Text Available The manufacturing activities are the major contributions to world’s environmental degradation. But it has been very difficult to understand and analyse the effect of individual activities and its corresponding contribution in the act of environmental degradation. Effects have been made of the analysis to understand the drivers and barriers of the green supply chain. Methodology has been evolving to analyse the existing scenario in an organisation and to suggest possible remedial measures.

  18. Factors Controlling Nanoparticle Pharmacokinetics: An Integrated Analysis and Perspective

    DEFF Research Database (Denmark)

    Moghimi, Seyed Moien; Hunter, A.C.; Andresen, T.L.

    2012-01-01

    of interrelated core and interfacial physicochemical and biological factors. Pertinent to realizing therapeutic goals, definitive maps that establish the interdependency of nanoparticle size, shape, and surface characteristics in relation to interfacial forces, biodistribution, controlled drug release, excretion......, and adverse effects must be outlined. These concepts are critically evaluated and an integrated perspective is provided on the basis of the recent application of nanoscience approaches to nanocarrier design and engineering. The future of this exciting field is bright; some regulatory-approved products...... are already on the market and many are in late-phase clinical trials. With concomitant advances in extensive computational knowledge of the genomics and epigenomics of interindividual variations in drug responses, the boundaries toward development of personalized nanomedicines can be pushed further....

  19. Sensitivity Factor Analysis For Unit Commitment In Loaded Lines

    Directory of Open Access Journals (Sweden)

    Lata Chaudhary

    2016-05-01

    Full Text Available In today’s competitive electricity market, it is not possible to settle all contracted transactions of power because of congestion in transmission lines. Usually, the independent system operator seeks to eliminate congestion by rescheduling output power of the generators. But all generators may not have the same effect (sensitivity on the power flow of the congested lines, so this is not an economical way to reschedule output power of all generators for managing congestion. Therefore, in this paper, active power generator sensitivity factor of the generators to the congested lines have been utilized to ascertain the number of generators participating in congestion management. The effectiveness and feasibility of the proposed algorithm have been tested on IEEE 30 bus system

  20. An Analysis on the Contextual Factors Affecting Motivation in SLA

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    <正>For us Chinese,a foreign language is something to be acquired as a kind of communicative tool,so we can infer that an effective way in SLA(Second Language Acquisition) must be learning the target language in a communicative context.A communicative context certainly concerns not only the interactional classroom activities designed in accordance with some stated curriculum tasks to lead the L2 students to learning swimming by swimming,but also other relevant elements which have a lot to do with all the situational,interactional and cultural contexts.In order to lessen some potential sources of conflict between L2 teacher and L2 learner,this article is an attempt to urge a careful study on the contextual factors affecting motivation in SLA.

  1. ANALYSIS OF POPULATION MIGRATION AS A CRIMINOGENIC FACTOR

    Directory of Open Access Journals (Sweden)

    Mariana MITRA-NIŢĂ

    2016-07-01

    Full Text Available Migration is a voluntary movement of population from one geographic location to another. This movement can be of several types, depending on the cause determining the respective migration. Population movements or its mobility is not a new phenomenon but has deep roots in ancient history. We can even say that in the beginning man was migratory, nomadic and later it became steadfast, linked in some way to certain geographic locations. Population migration has multiple consequences, both positive and negative. Among the negative we can mention overpopulation or underpopulation of certain areas, heterogeneity of traditions and cultures of immigrants, inability of migratory population to adapt to the area they migrated to, not finding a job, marginalization, etc. All these are genuine and objective criminological factors that could actually cause committing crimes in the migratory population. We cannot and do not want to stop the mobility of people, but we can be careful to avoid harmful consequences caused by this phenomenon.

  2. [Risk Factor Analysis of Pneumonia after Cardiovascular Surgery].

    Science.gov (United States)

    Maekawa, Yoshiyuki; Abe, Shuichi; Nakamura, Ken; Uchida, Tetsuro; Sadahiro, Mitsuaki; Morikane, Keita

    2016-08-01

    Pneumonia is a major and life-threatening complication after cardiovascular surgery. The objective of our study was to describe epidemiology, clinical characteristics, and risk factors of pneumonia after cardiovascular surgery. From January 2007 to December 2011, 511 consecutive patients (age 67.3±11.9;336 men, 175 women) were enrolled in this study. Pneumonia was diagnosed according to Centers of Disease Control and Prevention surveillance criteria for healthcare associated infection. Data collection included preoperative, intraoperative, and post-operative variables. The overall incidence of pneumonia was 72 cases(14.0%). The mortality in pneumonia group was significantly higher than that in non-pneumonia group (16.6% vs 4.3%, Odds ratio 4.4 ppneumonia after cardiovascular surgery.

  3. Obesity-associated Breast Cancer: Analysis of risk factors.

    Science.gov (United States)

    Engin, Atilla

    2017-01-01

    Several studies show that a significantly stronger association is obvious between increased body mass index (BMI) and higher breast cancer incidence. Furthermore, obese women are at higher risk of all-cause and breast cancer specific mortality when compared to non-obese women with breast cancer. In this context, increased levels of estrogens due to excessive aromatization activity of the adipose tissue, overexpression of pro-inflammatory cytokines, insulin resistance, hyperactivation of insulin-like growth factors (IGFs) pathways, adipocyte-derived adipokines, hypercholesterolemia and excessive oxidative stress contribute to the development of breast cancer in obese women. While higher breast cancer risk with hormone replacement therapy is particularly evident among lean women, in postmenopausal women who are not taking exogenous hormones, general obesity is a significant predictor for breast cancer. Moreover, increased plasma cholesterol leads to accelerated tumor formation and exacerbates their aggressiveness. In contrast to postmenopausal women, premenopausal women with high BMI are inversely associated with breast cancer risk. Nevertheless, life-style of women for breast cancer risk is regulated by avoiding the overweight and a high-fat diet. Estrogen-plus-progestin hormone therapy users for more than 5 years have elevated risks of both invasive ductal and lobular breast cancer. Additionally, these cases are more commonly node-positive and have a higher cancer-related mortality. Collectively, in this chapter, the impacts of obesity-related estrogen, cholesterol, saturated fatty acid, leptin and adiponectin concentrations, aromatase activity, leptin and insulin resistance on breast cancer patients are evaluated. Obesity-related prognostic factors of breast cancer also are discussed at molecular basis.

  4. Risk factor analysis for metaplastic gastritis in Koreans

    Institute of Scientific and Technical Information of China (English)

    Soonami Choi; Yun Jeong Lim; Sue Kyung Park

    2006-01-01

    AIM: To conduct a retrospective study to determine the risk factors for development of metaplastic gastritis in Korean population.METHODS: The database of 113449 subjects who underwent a gastroscopy for the purpose of a regular check-up at center for health promotion, Samsung medical center during 5 years was collected and retrospectively analyzed. Among them, 5847 subjects who had endoscopically diagnosed as a metaplastic gastritis or 10076 normal as well as answered to questionnaire were included for present study. The subjects were divided into 2 groups; Group Ⅰ, normal and Group Ⅱ, metaplastic gastritis. Age, gender, Helicobacter pylori(H pylori) seropositivity, body mass index (BMI),family history of cancer, smoking, alcohol consumption,total daily calories, folate and salt intake and dietary habit (out-eating, overeating, irregular eating) were retrieved from questionnaire or electronic medical record and compared between group Ⅰ and group Ⅱ.RESULTS: The prevalence of group Ⅱ was 11%(13578/113449) increasing its prevalence with age(P= 0.000). But, there was no significant association between 2 groups in BMI, family history of cancer,alcohol consumption, total daily calories, folate and salt intake and dietary habit (out-eating, overeating, irregular eating). Old age (P=0.000), male gender (P=0.000),H pylori seropositivity (P= 0.010) and current smoker (P= 0.000) were significantly more common in group Ⅱ at multiple logistic regression model.CONCLUSION: Our data suggested that old age, male gender,Hpyloriseropositivity and smoking were risk factors for metaplastic gastritis, precancerous lesion of gastric cancer.

  5. Analysis of factors that determine hospitalization of emergency department patients

    Directory of Open Access Journals (Sweden)

    Katarzyna Szwamel

    2016-09-01

    Full Text Available Background. Optimization of health care financing under current standards of treatment can be achieved by determining the factors that affect the number of hospital admissions at emergency departments (ED, and their significance. Objectives . Identification of factors determining hospitalizations at emergency department. Material and methods . The study involved 150 emergency department patients in Kedzierzyn-Kozle. An original questionnaire, the Health Behaviors Inventory, and a modified version of the Camberwell Assessment of Need Short Appraisal Schedule (CANSAS were used. Results. At greatest risk of hospitalization are those patients who: take more than 4 drugs (OR 12.17, 95% CI 2.97–73.67; are being treated for chronic diseases (OR 5.37, 95% CI 2.56–11.62; are above 44.5 years of age (OR 3.14, 95% CI 1.54–6.51; are being treated at an outpatient specialist clinic (OR 3.87, 95% CI 1.85–8.32; have a BMI above 27.1 (OR 2.84, 95% CI 1.39–5.88; have at most average material status (OR 0.42, 95% CI 0.20–0.87; have symptoms of severity greater than 5 (OR 2.23, 95% CI 1.11–4.55; and have a low index of unsatisfied needs (a Camberwell index lower than 0.825: OR 0.36, 95% CI 0.17–0.72. Conclusions . Any program to prevent hospitalization should be based on the measurement of health behavior, should focus on promoting knowledge of chronic diseases and the means of preventing them, and should involve patient education on the purpose of emergency departments. It is necessary to strive for increase responsiveness of healthcare to patients’ needs and to support the area of primary-care-oriented services in the field of ‘small surgery’.

  6. Factor Analysis: An Instrument for Selection of Social Performance Factors || Análisis factorial: un instrumento de selección de factores sociales de rendimiento

    Directory of Open Access Journals (Sweden)

    Hornungová, Jana

    2014-06-01

    Full Text Available This article is focused on the identification of social performance factors. For this purpose, a multidimensional statistical method -factor analysis- was used. The basic set for the selection of indicators was the concept (and the social tool of Corporate Social Responsibility, subsequently, the questionnaire was constructed. Empirical research was attended by 32 companies, from the Area of Information and Communication Activities (CZ-NACE, section J, with the number of employees over 250. The aim of the factor analysis was selection of significant indicators and performance factors for selected area from the input database. On the basis of the paper, there were evaluated: three social factors from the area of working environment and two social factors from the area of local community. The understanding of their application into the internal management shall be necessary prior to company's decision regarding the measures of key performance indicators. || Este artículo se centra en la identificación de factores de rendimiento social. Para este propósito, se utilizó el método estadístico multidimensional del análisis factorial. El conjunto básico para la selección de indicadores fue el concepto (y el instrumento social de la Responsabilidad Social Corporativa; posteriormente, se construyó un cuestionario. En la investigación empírica participaron 32 empresas, desde el Área de Actividades de la Información y la Comunicación (sección J, CZ-NACE, con un número de empleados superior a 250. El objetivo del análisis de los factores fue la selección de indicadores relevantes y factores de rendimiento para el área seleccionada de la base de datos de partida. Basándose en el trabajo, se evaluaron tres factores sociales del área del ambiente de trabajo y dos factores sociales del ámbito de la comunidad local. El entendimiento de su aplicación en la gestión interna se considera necesaria antes de la decisión de la empresa en cuanto

  7. Vibration factors impact analysis on aerial film camera imaging quality

    Science.gov (United States)

    Xie, Jun; Han, Wei; Xu, Zhonglin; Tan, Haifeng; Yang, Mingquan

    2017-08-01

    Aerial film camera can acquire ground target image information advantageous, but meanwhile the change of aircraft attitude, the film features and the work of camera inside system could result in a vibration which could depress the image quality greatly. This paper presented a design basis of vibration mitigation stabilized platform based on the vibration characteristic of the aerial film camera and indicated the application analysis that stabilized platform could support aerial camera to realize the shoot demand of multi-angle and large scale. According to the technique characteristics of stabilized platform, the development direction are high precision, more agility, miniaturization and low power.

  8. Factor analysis of small business conditions of boundary region

    Directory of Open Access Journals (Sweden)

    Леся Михайлівна Газуда

    2015-05-01

    Full Text Available In terms of border-zone and capabilities of direct implementation of foreign economic cooperation with the Member States of the European Union is necessary to intensify the development of priority economic activities in Zakarpattia region. Background and specific characteristics of small business development in the region are considered in the article. It is conducted the multivariate correlation and regression analysis of conditions of regional small business development for the main indicators, including the volume of sales, the gross regional product, the economically active population, capital investment, exports and imports

  9. Determination of Some Factors Affecting Honey Yield by Path Analysis

    Directory of Open Access Journals (Sweden)

    Melis Çelik Güney

    2016-10-01

    Full Text Available Path analysis is determinate that relationships among variables by using correlation coefficient, partial correlation coefficient and path coefficient. In this study, direct and indirect effects of honey yield between brood rearing area, flight activity, pollen collection, nectar collection and cleaning power were examined with these coefficients. Data which taken from C.U. Faculty of Agriculture, Department of Animal Science, Beekeeping Business were used. In the end of this research, the effect of brood rearing area on honey yield was found significant. In the colonies, brood rearing area has the highest direct effect of honey yield. Nectar collection has the highest indirect effect.

  10. An Analysis of Key Factors in Developing a Smart City

    Directory of Open Access Journals (Sweden)

    Aidana Šiurytė

    2016-06-01

    Full Text Available The concept Smart City is used widely but it is perceived differently as well. Literature review reveals key elements of the Smart City – Information and Communication Technologies and Smart Citizens. Nevertheless, raising public awareness is not a priority of local municipalities which are trying to develop cities. Focus group discussion aims to analyse citizens’ insights in regards to the Smart City and their contribution to creation of it. Case study of Vilnius examines a position of mu-nicipality in developing city as smart. Study contains suggestions for the improvement of communication in the city. Methods employed: comparative literature analysis, focus group investigation, case study.

  11. Factor analysis of fatal road traffic crashes with massive casualties in China

    Directory of Open Access Journals (Sweden)

    Tao Chen

    2016-04-01

    Full Text Available Factor analysis refers to a collection of statistical methods for reducing correlational data into a smaller number of dimensions or factors. In this study, factor analysis theory was used to determine the main influential factors of road traffic crashes with massive casualties. Twenty variables related to personnel, vehicles, roads, and environment were collected, and the significance of their correlations was tested for validity. A correlation coefficient matrix R was calculated, and its latent root λ was obtained based on the characteristic equation. A number of common factors were determined according to the value of latent root λ . Factor loading was used to express the relationship of each variable to the underlying main influential factors. An index system of accident factors was developed based on the results of factor loading, and the weight of each factor was calculated to classify the factor influence. The main influential factors of accidents were determined to be fault behavior, driving experience, condition of vehicle safety, purpose of vehicle, road lighting, driver, road surface condition, roadside protection facilities, and road terrain.

  12. Analysis of the Factors Influencing the Therapeutic Effects of Onychomycosis

    Institute of Scientific and Technical Information of China (English)

    ZHENG; Yuechen; WU; Yanqing; CHEN; Hui; ZHU; Zhaoru; LIU; Ling; ZENG; Jingsi

    2001-01-01

    In order to improve the curative effect of onychomycosis, the factors influencing the therapeutic effects were investigated. 545 cases including 245 males and 300 females, who were diagnosed both clinically and mycologically, were treated by Intraconazole with intermittent pulse therapy. The therapeutic effects were judged by the following observations regularly and analyzed from the factors as follows: age; growing speed of nails; accompanied diseases; family history; trauma of nails; infection ways of the pathogens; manifestation of the injury; pathogens; duration of the treatment. The results showed that the recovery rate was higher in younger patients (P<0.01) with a quicker recovery rate (P<0. 001), and a lower recurrent rate (P<0. 01), as well as in those with quicker growing speed of new-born nail. Also the patients with WSO and DLSO manifestation had a higher recovery rate. The patients with onychomycosis caused by T. rubrum had a higher recovery rate (P<0. 01 to 0. 001) no matter whether to prolong the treatment duration. The patients with diabetes mellitus or hyperhidrosis, as well as with positive family history or basic nail diseases such as trauma and paronychia, had a lower recovery rate and the curative effects were not satisfactory. It was concluded that although the single and some DLSO-manifestation nail injury could be cured by internal and external treatments with the help of removing the sick nail and the duration of the treatment could be shortened. The treatment duration should be prolonged in order to increase the curative effects and decrease the recurrence under such conditions as following: old patients above 60 years; patients with low-growing-speed new-borne nails; patients with thumb and big toel injury and ingrowing nail; patients with diabetes mellitus, hyperhidrosis or Renauld's phenomenon; patients with nail trauma before or during the treatment ; patients with PSO or TDO manifestation ; patients with onychomycosis caused

  13. Analysis of the Relevant Factors of Retaining Women in Judo

    Directory of Open Access Journals (Sweden)

    Joško Sindik

    2014-09-01

    Full Text Available This study aimed to determine the latent dimensions of all relevant factors about engagement of women in judo, to determine the intercorrelations among these latent dimensions, as well as the correlations with three relevant variables. Final goal was to determine the differences in revealed latent dimensions, in relation to several independent variables: educational level, marital status, impulses to engage in judo, then depending are the women athletes (competitors or not, members of the Board or not, trainers or not. A total of 50 female judokas from a larger number of Croatian clubs were examined, by specially composed the survey. The results showed that all seven questionnaires showed medium to high satisfactory reliability, together with good con¬struct validity, in 15 latent dimensions that are revealed. It can be noticed that relatively older women have more obligations and more barriers that oppose to their engagement in judo. Only small number of differences are found among women engaged in judo, mainly among participants who are members of the Board in the club or Croatian Judo Federation, as compared with those who are not. Small number of statistically significant differences (as well as the correlations can be also observed as the fact that all women partially share similar problems, while the media strategies are perceived as the most powerful to increase women’s persistence in judo, in any type of engagement.

  14. Factors influencing ERP implementation in Indian SMEs: An empirical analysis

    Directory of Open Access Journals (Sweden)

    Rana Basu

    2011-04-01

    Full Text Available Enterprise Resource Planning (ERP is essentially a commercial software package that enables the integration of transaction - oriented data and business processes throughout an organization. In order to remain competitive in this global business scenario, the small and medium scale enterprises (SMEs are opting for ERP implementation. In Indian SME sector, the adoption of ERP is rapidly increasing. Literature shows many instances where organizations, even after implementing such novel information systems like ERP, are unable to derive the benefits of integration. It is, therefore, not surprising that implementation of enterprise information systems in general is quite difficult due to their size, scope and complexity. Therefore, there is a need to identify some issues that would lead to positive outcome for the implementation of ERP systems in the context of Indian SME sector. This paper thus attempts to identify and to prioritize the factors influencing proper implementation of ERP systems in a business organization particularly for Indian small and medium businesses (SMBs. The research presented here is specifically targeted the Indian SMEs, which have already completed the process of implementing ERP system.

  15. Analysis of surgical and MRI factors associated with cerebellar mutism.

    Science.gov (United States)

    Sergeant, Anjali; Kameda-Smith, Michelle Masayo; Manoranjan, Branavan; Karmur, Brij; Duckworth, JoAnn; Petrelli, Tina; Savage, Katey; Ajani, Olufemi; Yarascavitch, Blake; Samaan, M Constantine; Scheinemann, Katrin; Alyman, Cheryl; Almenawer, Saleh; Farrokhyar, Forough; Fleming, Adam J; Singh, Sheila Kumari; Stein, Nina

    2017-07-01

    The surgical risk factors and neuro-imaging characteristics associated with cerebellar mutism (CM) remain unclear and require further investigation. Therefore, we aimed to examine surgical and MRI findings associated with CM in children following posterior fossa tumor resection. Using our data registry, we retrospectively collected data from pediatric patients who acquired CM and were matched based on age and pathology type with individuals who did not acquire CM after posterior fossa surgery. The strength of association between surgical and MRI variables and CM were examined using odds ratios (ORs) and corresponding 95% confidence intervals (CIs). A total of 22 patients (11 with and 11 without CM) were included. Medulloblastoma was the most common pathology among CM patients (91%); the remaining 9% were diagnosed with a pilocytic astrocytoma. Tumor attachment to the floor of the fourth ventricle (OR 6; 95% CI 0.7-276), calcification/hemosiderin deposition (OR 7; 95% CI 0.9-315.5), and post-operative peri-ventricular ischemia on MRI (OR 5; 95% CI 0.5-236.5) were found to have the highest measures of association with CM. Our results may suggest that tumor attachment to the floor of the fourth ventricle, pathological calcification, and post-operative ischemia have a relatively higher prevalence in patients with CM. Collectively, our work calls for a larger multi-institutional cohort study of CM patients to encourage further investigation of the determinants and management of CM in order to potentially minimize its development and predict onset.

  16. Analysis of factors influencing the accuracy of CRDInSAR

    Science.gov (United States)

    Fu, Wenxue; Guo, Huadong; Tian, Qingjiu; Guo, Xiaofang

    2010-11-01

    In recent years, the method of Corner Reflectors Differential Interferometric Synthetic Aperture Radar (CRDInSAR) was proposed for overcoming the limitations of decorrelations of the conventional differential interferometric synthetic aperture radar (DInSAR) technique. In general, the corner reflector has very high RCS (Radar Cross Section) for a small size, and the maximum RCS occurs when it points directly along the boresight of the SAR antenna. The beam width of a trihedral corner reflector is rather broad (having a 3dB beam width of 40° in both elevation and azimuth), so it is fairly tolerant to installation errors. It can be made available as artificial PS (Permanent Scatterers) points by installing them on a study area due to the stable amplitude and phase performance. However, some errors of CRDInSAR system will still affect the results of measurement. In this paper, the factors influence the accuracy of CRDInSAR are discussed, which include the errors of baseline and its angle, look angle and height of corner reflector respectively.

  17. Complicated appendicitis: Analysis of risk factors in children

    Directory of Open Access Journals (Sweden)

    Mahavir Singh

    2014-01-01

    Full Text Available Background: Acute appendicitis (AA is the most common surgical emergency in childhood. The risk of rupture is negligible within the first 24 h, climbing to 6% after 36 h from the onset of symptoms. Because of difficulty in accurate diagnosis of AA a significant number of children still are being managed when it is already perforated. There is always a need to make an early diagnosis of AA and to find out the risk factors associated with development of complication in this condition. Patients and Methods: A total of 102 patients with a clinical diagnosis of AA were admitted during the study period. On admission, a good clinical history and proper physical examination was performed. All the eligible patients who finally diagnosed clinically as having AA were planned for emergency open appendectomy. The removed appendix was sent for histopathological examination in all the study subjects. Results: Out of 102 cases, 93 cases were histopathologically appendicitis, rest nine cases showed no evidence of inflammation so the rate of negative appendectomy was around 9%. On histopathology normal appendix was found in nine patients (8.9%, AA in 71 patients (69.6%, complicated appendicitis (CA which includes perforated and gangrenous appendicitis was present in 22 patients (21.5%. Perforations were more common in patients who were younger than 5 years. >60% patients presented with CA when the duration of pain was >72 h. Presence of appendicolith increased the probability of CA.

  18. Factor Analysis on Subsidy Preference of Private Forest Owners

    Institute of Scientific and Technical Information of China (English)

    Niandong; CHEN; Chunxia; ZHANG; Senwei; HUANG

    2013-01-01

    Forest farmers are the basic micro-subjects in southern collectively owned forest, and their willingness towards forest management directly influences forestry development. Thus, to provide subsidies to forest farmers is an important means to encourage the farmers’ enthusiasm to manage the forest and promote the healthy and sustainable development of private forest. In order to reduce the supply-demand contradictions and improve the implementation effects of the subsidies system, the design of the system should be based on the real needs of forest farmers. On this basis, a questionnaire survey was designed in this paper to study the preferences of forest farmers to different types of subsidies in the southern collectively owned forest and the influencing factors were analysed by the Logistic Model to search for the reasonable design of the system. It was concluded that the forest farmers with different backgrounds show different preference to the subsidies, which, to a certain extent, reflects the development bottlenecks of forestry, and lays a foundation for the design of subsidies system.

  19. Stress Intensity Factor Analysis and the Stability of Overhanging Rock

    Science.gov (United States)

    Huang, R. Q.; Wu, L. Z.; He, Q.; Li, J. H.

    2017-08-01

    The collapse of overhanging rock is a common geological hazard in mountainous areas. The stability of overhanging rock is usually determined by the growth of a crack along a main structural plane. On the basis of linear fracture mechanics combined with the stress concentration coefficient, an analytical method to determine the stress intensity factor (SIF) of overhanging rock is developed to evaluate its stability. Experiments on pre-cracked sandstone were carried out to simulate failure of overhanging rock and verify the analytical solution to fracturing and failure of overhanging rocks. Additionally, numerical solutions using the finite element method are derived to compare with the experimental results. The J-integral and displacement extrapolation methods are used to determine stress changes at the crack tip in the overhanging rocks, and the results confirm that the analytical solutions are consistent with the results of the numerical solutions, including the displacement extrapolation used to analyze the SIF of the overhanging rock. The ratio of fracture toughness to effective SIF at the crack tip can be considered useful when examining the stability of overhanging rock.

  20. Optical factors in the rapid analysis of captive bubbles.

    Science.gov (United States)

    Khoojinian, Hamed; Goodarzi, Jim P; Hall, Stephen B

    2012-10-01

    Bubbles and droplets offer multiple advantages over Langmuir troughs for compressing interfacial films. Experiments, however, that manipulate films to maintain constant surface tension (γ) present problems because they require feedback. Measurements of bubbles and droplets calculate γ from the shape of the interface, and calculations in real time based on finding the Laplacian shape that best fits the interface can be difficult. Faster methods obtain γ from only the height and diameter, but the bubbles and droplets rest against a solid support, which obscures one section of the interface and complicates measurements of the height. The experiments here investigated a series of optical variables that affect the visualized location of the different surfaces for captive bubbles. The pitch of the support and camera as well as the collimation of illuminating light affected the accuracy of the measured dimensions. The wavelength of illumination altered the opacity of turbid subphases and hydrated gel used to form the solid support. The width of all visualized edges depended on the spectral width and collimation of the illuminating light. The intensity of illumination had little effect on the images as long as the grayscale remained within the dynamic range of the camera. With optimization of these optical factors, the width of all edges narrowed significantly. The surfaces away from the solid support approached the infinite sharpness of the physical interface. With these changes, the grayscale at the upper interface provided the basis for locating all surfaces, which improved real-time measurements based on the height and diameter.

  1. Analysis on Factors Affecting Seedling Establishment in Rice

    Directory of Open Access Journals (Sweden)

    Ju LUO

    2007-03-01

    Full Text Available Elongations of coleoptile and mesocotyl are related directly to rice seedling establishment in soil and height of plant is related to lodging in rice production. Twelve typical rice cultivars with different lengths of coleoptile and mesocotyl (long, medium and short were selected by screening the lengths of coleoptile and mesocotyl in 1500 accessions. The seedling establishments of these typical cultivars were compared under the combinations of different sowing depths and flooding durations, and two semi-dwarf varieties (G140, Zhong 96–21 with good seedling establishments and optimum mesocotyl lengths were found. The length of mesocotyl was completely fitted negative binomial distribution and the length of coleoptile was nearly fitted lognormal distribution. Analysis of the relationships among mesocotyl, coleoptile, seeding depth, flooding duration, and their interactions to seedling establishment percentage showed that there existed significant relations among mesocotyl, coleoptile, mesocotyl × coleoptile, seeding depth, flooding duration and mesocotyl × sowing depth in the experiment for seedling establishment.

  2. Analysis on Factors Affecting Seedling Establishment in Rice

    Institute of Scientific and Technical Information of China (English)

    LUO Ju; TANG Shao-qing; HU Pei-song; Aleman LOUIS; JIAO Gui-ai; TANG Jian

    2007-01-01

    Elongations of coleoptile and mesocotyl are related directly to rice seedling establishment in soil and height of plant is related to lodging in rice production. Twelve typical rice cultivars with different lengths of coleoptile and mesocotyl (long, medium and short) were selected by screening the lengths of coleoptile and mesocotyl in 1500 accessions. The seedling establishments of these typical cultivars were compared under the combinations of different sowing depths and flooding durations, and two semi-dwarf varieties (G140, Zhong 96-21) with good seedling establishments and optimum mesocotyl lengths were found. The length of mesocotyl was completely fitted negative binomial distribution and the length of coleoptile was nearly fitted Iognormal distribution.Analysis of the relationships among mesocotyl, coleoptile, seeding depth, flooding duration, and their interactions to seedling establishment percentage showed that there existed significant relations among mesocotyl, coleoptile, mesocotyl × coleoptile,seeding depth, flooding duration and mesocotyl × sowing depth in the experiment for seedling establishment.

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

    Science.gov (United States)

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

    2015-09-01

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

  4. Prognostic factors for relapse in stage I seminoma managed by surveillance: a pooled analysis

    DEFF Research Database (Denmark)

    Warde, Padraig; Specht, Lena; Horwich, Alan

    2002-01-01

    Several management options are available to patients with stage I seminoma, including adjuvant radiotherapy, surveillance, and adjuvant chemotherapy. We performed a pooled analysis of patients from the four largest surveillance studies to better delineate prognostic factors associated with disease...

  5. Risk factors for postoperative pancreatic fistula: Analysis of 539 successive cases of pancreaticoduodenectomy

    National Research Council Canada - National Science Library

    Bing-Yang Hu Tao Wan Wen-Zhi Zhang Jia-Hong Dong

    2016-01-01

    AIM To analyze the risk factors for pancreatic fistula after pancreaticoduodenectomy.METHODS We conducted a retrospective analysis of 539 successive cases of pancreaticoduodenectomy performed at our hospital from March 2012 to October 2015...

  6. Analysis of factors that affect DQE in digital mammography

    Science.gov (United States)

    Takamura, Miho; Higaki, Akiko; Kodera, Yoshie

    2005-04-01

    The international standard IEC 62220-1 about DQE measurement of digital X-ray equipment was published in 2003, but mammography systems aren"t applied to this IEC standard because the factor affect measurement is complicated. Especially, the influence to the pre-sampling MTF by edge method when X-ray beam is oblique to detector. The influence of nonuniformity of x-ray intensity by the heel effect on digital Wiener spectrum (WS) doesn"t become clear. A 0.1mm-thick tungsten edge was imaged in the position where X-ray beam was perpendicular to detector plane and in 6cm from chest wall, respectively. And the pre-sampling MTFs were obtained from these edge images. The calculation area of the digital WS within irradiation area was moved in parallel direction to X-ray tube axis, and the digital WS were calculated. The pre-sampling MTFs and the digital WS are calculated by the method based on the IEC proposal. We used MAMMOMAT3000(SIEMENS), MGU-100B(TOSHIBA), M-IV(LORAD) and Senographe DMR+(GE) as X-ray generator. Images were obtained by FCR PROFECT CS (Fujifilm medical). In all equipments and both arrangement directions of the edge test device, pre-sampling MTFs are almost the same, even if the arrangement places of the edge test device varied. In all equipments, when the calculation area was moved about 10cm, the digital WS of the anode side was higher 7.2-17.9% than those of the cathode side. It was found that the dose of anode side was lower about 20% than cathode side from the profile of an exposure image. We think that digital WS modified the nonuniformity of the dose by the heel effect is obtained by multiplying the digital WS by the compensation coefficient obtained by the dose profile, in low spatial frequency.

  7. Confirmatory factor analysis of a Spanish version of the sex fantasy questionnaire: assessing gender differences.

    Science.gov (United States)

    Sierra, Juan Carlos; Ortega, Virgilio; Zubeidat, Ihab

    2006-01-01

    The objective of this study was to validate the factor structure of Wilson's Sex Fantasy Questionnaire (SFQ; Wilson, 1978; Wilson & Lang, 1981) using a Spanish version. In order to do this, we conducted confirmatory factor analysis on two nonclinical samples containing 195 men and 315 women. Both groups were tested for the structure proposed by Wilson and also for some alternative models. Confirmatory factor analysis showed that four factors were reasonably distinct, especially for the men. We proposed shortened version of the instrument that would have sufficient psychometric guarantees for assessing sexual fantasies in both genders. This abridged version improved the fit of the four-factor oblique factor equally for both the samples of men and women. In the light of the results of the validation hypothesis established with some criterion variables (dyadic sexual desire, unconventional sex, homophobia), we discuss discrepancies between both versions.

  8. The application of spectral distribution of product of two random matrices in the factor analysis

    Institute of Scientific and Technical Information of China (English)

    Bai-suo JIN; Bai-qi MIAO; Wu-yi YE; Zhen-xiang WU

    2007-01-01

    In the factor analysis model with large cross-section and time-series dimensions, we propose a new method to estimate the number of factors. Specially if the idiosyncratic terms satisfy a linear time series model, the estimators of the parameters can be obtained in the time series model.The theoretical properties of the estimators are also explored. A simulation study and an empirical analysis are conducted.

  9. The application of spectral distribution of product of two random matrices in the factor analysis

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In the factor analysis model with large cross-section and time-series dimensions,we pro- pose a new method to estimate the number of factors.Specially if the idiosyncratic terms satisfy a linear time series model,the estimators of the parameters can be obtained in the time series model. The theoretical properties of the estimators are also explored.A simulation study and an empirical analysis are conducted.

  10. Human Reliability Analysis for Design: Using Reliability Methods for Human Factors Issues

    Energy Technology Data Exchange (ETDEWEB)

    Ronald Laurids Boring

    2010-11-01

    This paper reviews the application of human reliability analysis methods to human factors design issues. An application framework is sketched in which aspects of modeling typically found in human reliability analysis are used in a complementary fashion to the existing human factors phases of design and testing. The paper provides best achievable practices for design, testing, and modeling. Such best achievable practices may be used to evaluate and human system interface in the context of design safety certifications.

  11. Analysis on Pollution Factors in Asparagus Production and Research on Safety Production Technology

    OpenAIRE

    Ma, Liping; Hao, Bianqing; Qiao, Xiongwu

    2013-01-01

    Based on the analysis on the infection degree, infection law and influencing factors of the main diseases on asparagus and the analysis on the pollution factors in asparagus production such as blind pesticide use, atmospheric pollution and acid rain, the pollution of soil and fertilizer, this article proposes asparagus safety production technologies which include the selection of disease-resistant variety and suitable planting field, scientific and reasonable disease control, balanced fertili...

  12. Analysis of Factors Affecting Testing in Object oriented systems

    Directory of Open Access Journals (Sweden)

    Mrs. Sujata Khatri,

    2011-03-01

    Full Text Available Software testing is an important software quality assurance activity to ensure that the benefits of Object oriented programming will be realized. Testing object oriented systems is little bit challenging ascomplexity shifted from functions and procedures as in traditional procedural systems to the interconnections among its components. Object oriented development has presented a numerous variety of new challenges due to its features like encapsulation, inheritance, polymorphism and dynamic binding. Earlier the faults used to bein the software units, whereas the problem now is primarily in the way in which we connect the software. Development is writing the code, testing is finding out whether or not the code runs the way you expect it to. A major challenge to the software developers remains how to reduce the cost while improving the quality of software testing. Software testing is difficult and expensive, and testing object oriented system is even more difficult. A tester often needs to spend significant time in developing lengthy testing code to ensure that system under test is reasonably well tested. Substantial research has been carried out in object oriented analysis, design.However relatively less attention has been paid to testing of object oriented programs. This paper describes the various features of object oriented programming and how they effect testing of object oriented systems.

  13. Mayo Older Americans Normative Studies: Factor Analysis of an Expanded Neuropsychological Battery

    OpenAIRE

    Greenaway, Melanie C.; Smith, Glenn E.; Tangalos, Eric G.; Geda, Yonas E.; Ivnik, Robert J.

    2008-01-01

    The Mayo Cognitive Factor Scores were derived from a “core battery” consisting of the WAIS-R, WMS-R, and Auditory Verbal Learning Test. The present study sought to clarify the factor structure of an expanded neuropsychological battery in normal elderly controls. Confirmatory factor analysis was performed on the WAIS-III, WRAT-3 Reading, Boston Naming Test, Controlled Oral Word Association Test, Category Fluency, Rey-Osterrieth Complex Figure, Visual Form Discrimination, and Trail Making Test ...

  14. Confirmatory factor analysis of the Multidimensional Inventory of Perfectionism in Sport

    OpenAIRE

    Madigan, Daniel J.

    2016-01-01

    Objectives and Method: The Multidimensional Inventory of Perfectionism in Sport (MIPS; Stoeber, Otto, & Stoll, 2006) is a commonly used measure of perfectionism in sport. However, there is limited empirical evidence supporting its subscale structure and composition. Therefore, the present study investigated the factor structure of the MIPS in a sample of 470 athletes (mean age 20.0 years).\\ud \\ud Results: Confirmatory factor analysis showed that the data supported the hypothesized four-factor...

  15. Risk factors for PTSD after birth in a normal population: A meta-analysis

    OpenAIRE

    Ayers, S; Bond, R.; Wijma, K

    2013-01-01

    Evidence suggests that a proportion of women report posttraumatic stress disorder (PTSD) after childbirth, with between 1 and 3% of women developing the disorder as a direct result of birth (Alcorn, O'Donovan, Patrick, Creedy, & Devilly). A range of factors are associated with postpartum PTSD, including prepartum, birth and postpartum factors. This meta-analysis synthesizes research on posttraumatic stress symptoms after childbirth in order to identify key vulnerability and risk factors. ...

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

    Directory of Open Access Journals (Sweden)

    Leandro F. Malloy-Diniz

    2017-04-01

    Full Text Available 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.

  17. Examining evolving performance on the Force Concept Inventory using factor analysis

    Science.gov (United States)

    Semak, M. R.; Dietz, R. D.; Pearson, R. H.; Willis, C. W.

    2017-06-01

    The application of factor analysis to the Force Concept Inventory (FCI) has proven to be problematic. Some studies have suggested that factor analysis of test results serves as a helpful tool in assessing the recognition of Newtonian concepts by students. Other work has produced at best ambiguous results. For the FCI administered as a pre- and post-test, we see factor analysis as a tool by which the changes in conceptual associations made by our students may be gauged given the evolution of their response patterns. This analysis allows us to identify and track conceptual linkages, affording us insight as to how our students have matured due to instruction. We report on our analysis of 427 pre- and post-tests. The factor models for the pre- and post-tests are explored and compared along with the methodology by which these models were fit to the data. The post-test factor pattern is more aligned with an expert's interpretation of the questions' content, as it allows for a more readily identifiable relationship between factors and physical concepts. We discuss this evolution in the context of approaching the characteristics of an expert with force concepts. Also, we find that certain test items do not significantly contribute to the pre- or post-test factor models and attempt explanations as to why this is so. This may suggest that such questions may not be effective in probing the conceptual understanding of our students.

  18. Dynamic factor analysis in the frequency domain: causal modeling of multivariate psychophysiological time series

    NARCIS (Netherlands)

    Molenaar, P.C.M.

    1987-01-01

    Outlines a frequency domain analysis of the dynamic factor model and proposes a solution to the problem of constructing a causal filter of lagged factor loadings. The method is illustrated with applications to simulated and real multivariate time series. The latter applications involve topographic a

  19. Multivariate statistical study with a factor analysis of foraminiferal fauna from the Chilka Lake, India

    Digital Repository Service at National Institute of Oceanography (India)

    Jayalakshmy, K.V.; Rao, K.K.

    Foraminiferal fauna from the surface sediments of the Chilka Lake along the east coast of India has been studied as regards distribution of its assemblages. From Q-mode factor analysis of the data, eight significant factor groups for species have...

  20. Validation of the Adolescent Concerns Measure (ACM): Evidence from Exploratory and Confirmatory Factor Analysis

    Science.gov (United States)

    Ang, Rebecca P.; Chong, Wan Har; Huan, Vivien S.; Yeo, Lay See

    2007-01-01

    This article reports the development and initial validation of scores obtained from the Adolescent Concerns Measure (ACM), a scale which assesses concerns of Asian adolescent students. In Study 1, findings from exploratory factor analysis using 619 adolescents suggested a 24-item scale with four correlated factors--Family Concerns (9 items), Peer…