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

Science.gov (United States)

Morales, Rocío; Cruz Ortiz, M; Sarabia, Luis A

2012-05-01

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 × J × 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, CCα, achieved are between 0.29 and 0.67 μg L(-1) for the four chlorophenols. The accuracy (trueness and precision) of the procedure was assessed. This procedure has been applied to river water samples.

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.

[Characterizing chromophoric dissolved organic matter (CDOM) in Lake Honghu, Lake Donghu and Lake Liangzihu using excitation-emission matrices (EEMs) fluorescence and parallel factor analysis (PARAFAC)].

Science.gov (United States)

Zhou, Yong-Qiang; Zhang, Yun-Lin; Niu, Cheng; Wang, Ming-Zhu

2013-12-01

Little is known about DOM characteristics in medium to large sized lakes located in the middle and lower reaches of Yangtze River, like Lake Honghu, Lake Donghu and Lake Liangzihu. Absorption, fluorescence and composition characteristics of chromophoric dissolved organic matter (CDOM) are presented using the absorption spectroscopy, the excitation-emission ma trices (EEMs) fluorescence and parallel factor analysis (PARAFAC) model based on the data collected in Sep-Oct. 2007 including 15, 9 and 10 samplings in Lake Honghu, Lake Donghu and Lake Liangzihu, respectively. CDOM absorption coefficient at 350 nm a(350) coefficient in Lake Honghu was significantly higher than those in Lake Donghu and Lake Liangzihu (t-test, pCDOM spectral slope in the wavelength range of 280-500 nm (S280-500) and a(350) (R2 =0. 781, p<0. 001). The mean value of S280-500 in Lake Honghu was significantly lower than those in Lake Donghu (t-test, pPARAFAC model, among which significant positive correlations were found between C1 and C2 (R2 =0. 884, p<0. 001), C3 and C4 (R2 =0. 677, p<0.001), respectively, suggesting that the sources of the two humic-like components as well as the two protein-like components were similar. However, no significant correlation has been found between those 4 fluorescent components and DOC concentration. Th e fluorescenceindices of FI255 (HIX), Fl265, FI310 (BIX) and Fl370 in Lake Donghu were all significantly higher than those in Lake Liangzihu (t-test, p <0.05) and Lake Honghu (t-test, p<0. 01), indicating that the eutrophication status in Lake Donghu was higher than Lake Honghu and Lake Liangzihu.

Unveiling the transformation and bioavailability of dissolved organic matter in contrasting hydrothermal vents using fluorescence EEM-PARAFAC.

Science.gov (United States)

Yang, Liyang; Zhuang, Wan-E; Chen, Chen-Tung Arthur; Wang, Bing-Jye; Kuo, Fu-Wen

2017-03-15

The submarine hydrothermal systems are extreme environments where active cycling of dissolved organic matter (DOM) may occur. However, little is known about the optical properties and bioavailability of hydrothermal DOM, which could provide valuable insights into its transformation processes and biogeochemical reactivity. The quantity, quality, and bioavailability of DOM were investigated for four very different hydrothermal vents east of Taiwan, using dissolved organic carbon (DOC), absorption spectroscopy, and fluorescence excitation-emission matrices-parallel factor analysis (EEM-PARAFAC). The DOC and absorption coefficient a 280 were both lower in the two hydrothermal vents off the Orchid Island and on the Green Island than in the surrounding seawater and the two vents off the Kueishantao Island, indicating effective removals of DOM in the former two hydrothermal systems owing to possible adsorption/co-precipitation and thermal degradation respectively. The four hydrothermal DOM showed notable differences in the absorption spectral slope S 275-295 , humification index HIX, biological index BIX, EEM spectra, and the relative distributions of seven PARAFAC components. The results demonstrated a high diversity of chemical composition and transformation history of DOM under contrasting hydrothermal conditions. The little change in the hydrothermal DOC after 28-day microbial incubations indicated a low bioavailability of the bulk DOM, and different PARAFAC components showed contrasting bioavailability. The results have profound implications for understanding the biogeochemical cycling and environmental effects of hydrothermal DOM in the marine environments. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

NARCIS (Netherlands)

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

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,

[Characterization of Chromophoric dissolved organic matter (CDOM) in Zhoushan fishery using excitation-emission matrix spectroscopy (EEMs) and parallel factor analysis (PARAFAC)].

Science.gov (United States)

Zhou, Qian-qian; Su, Rong-guo; Bai, Ying; Zhang, Chuan-song; Shi, Xiao-yong

2015-01-01

The composition, distribution characteristics and sources of chromophoric dissolved organic matter(CDOM) in Zhoushan Fishery in spring were evaluated by fluorescence excitation-emission matrix (EEM) combined with parallel factor analysis (EEMs-PARAFAC). Three humic-like components [C1 (330/420 nm)], C2 [(290) 365/440 nm] and C3 [(260) 370/490 nm)] and two protein-like components [C4(285/340 nm) and C5 (270/310 nm)] were identified by EEMs-PARAFAC. The horizontal distribution patterns of the five components were almost the same with only slight differences, showing decreasing trends with increasing distance from shore. In the surface and middle layers, the high value areas were located in the north of Hangzhou Bay estuary and the outlet of Xiazhimen channel, and the former's was higher in the surface layer while the latter's was higher in the middle layer. In the bottom layer, CDOM decreased gradiently from the inshore to offshore, with higher CDOM near Zhoushan Island. The distributions of fluorescence components showed an opposite trend with salinity, and no significant linear relationship with Chl-a concentration was found, which indicated that CDOM in the surface and middle layers were dominated by terrestrial input and human activities of Zhoushan Island and that of the bottom layer was attribute to human activities of Zhoushan Island. The vertical distribution of five fluorescent components along 30.5 degrees N transect showed a decreasing trend from the surface and middle layers to bottom layer with high values in inshore and offshore areas, which were correlated with the lower salinity and higher Chl-a concentration, respectively. On this transect, CDOM was mainly affected by Yangtze River input in coastal area but by bioactivities in offshore waters. Along the 30 degrees N transect, the vertical distribution patterns of CDOM were similar to those of 30.5 degrees N transect but there was a high value area in the bottom layer near the shore, attributing to

Finding the limit of diverging components in three-way Candecomp/Parafac : A demonstration of its practical merits

NARCIS (Netherlands)

Stegeman, Alwin

Three-way Candecomp/Parafac (CP) is a three-way generalization of principal component analysis (PCA) for matrices. Contrary to PCA, a CP decomposition is rotationally unique under mild conditions. However, a CP analysis may be hampered by the non-existence of a best-fitting CP decomposition with R≤2

Metabolic profiling based on two-dimensional J-resolved 1H NMR data and parallel factor analysis

DEFF Research Database (Denmark)

Yilmaz, Ali; Nyberg, Nils T; Jaroszewski, Jerzy W.

2011-01-01

the intensity variances along the chemical shift axis are taken into account. Here, we describe the use of parallel factor analysis (PARAFAC) as a tool to preprocess a set of two-dimensional J-resolved spectra with the aim of keeping the J-coupling information intact. PARAFAC is a mathematical decomposition......-model was done automatically by evaluating amount of explained variance and core consistency values. Score plots showing the distribution of objects in relation to each other, and loading plots in the form of two-dimensional pseudo-spectra with the same appearance as the original J-resolved spectra...

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

Science.gov (United States)

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

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

Ramia Z. Al Bakain

2017-01-01

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

Characterisation of landfill leachate by EEM-PARAFAC-SOM during physical-chemical treatment by coagulation-flocculation, activated carbon adsorption and ion exchange.

Science.gov (United States)

Oloibiri, Violet; De Coninck, Sam; Chys, Michael; Demeestere, Kristof; Van Hulle, Stijn W H

2017-11-01

The combination of fluorescence excitation-emission matrices (EEM), parallel factor analysis (PARAFAC) and self-organizing maps (SOM) is shown to be a powerful tool in the follow up of dissolved organic matter (DOM) removal from landfill leachate by physical-chemical treatment consisting of coagulation, granular activated carbon (GAC) and ion exchange. Using PARAFAC, three DOM components were identified: C1 representing humic/fulvic-like compounds; C2 representing tryptophan-like compounds; and C3 representing humic-like compounds. Coagulation with ferric chloride (FeCl 3 ) at a dose of 7 g/L reduced the maximum fluorescence of C1, C2 and C3 by 52%, 17% and 15% respectively, while polyaluminium chloride (PACl) reduced C1 only by 7% at the same dose. DOM removal during GAC and ion exchange treatment of raw and coagulated leachate exhibited different profiles. At less than 2 bed volumes (BV) of treatment, the humic components C1 and C3 were rapidly removed, whereas at BV ≥ 2 the tryptophan-like component C2 was preferentially removed. Overall, leachate treated with coagulation +10.6 BV GAC +10.6 BV ion exchange showed the highest removal of C1 (39% - FeCl 3 , 8% - PACl), C2 (74% - FeCl 3 , 68% - PACl) and no C3 removal; whereas only 52% C2 and no C1 and C3 removal was observed in raw leachate treated with 10.6 BV GAC + 10.6 BV ion exchange only. Analysis of PARAFAC-derived components with SOM revealed that coagulation, GAC and ion exchange can treat leachate at least 50% longer than only GAC and ion exchange before the fluorescence composition of leachate remains unchanged. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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

by the inter-trial phase coherence (ITPC) encompassing ANOVA analysis of differences between conditions and 5-way analysis of channel x frequency x time x subject x condition. A flow chart is presented on how to perform data exploration using the PARAFAC decomposition on multi-way arrays. This includes (A......) channel x frequency x time 3-way arrays of F test values from a repeated measures analysis of variance (ANOVA) between two stimulus conditions; (B) subject-specific 3-way analyses; and (C) an overall 5-way analysis of channel x frequency x time x subject x condition. The PARAFAC decompositions were able...... 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...

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

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 improv...

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

2013-08-09

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. Copyright © 2013 Elsevier B.V. All rights reserved.

Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data.

Science.gov (United States)

Liu, Yuanyuan; Shang, Fanhua; Jiao, Licheng; Cheng, James; Cheng, Hong

2015-11-01

In recent years, low-rank tensor completion (LRTC) problems have received a significant amount of attention in computer vision, data mining, and signal processing. The existing trace norm minimization algorithms for iteratively solving LRTC problems involve multiple singular value decompositions of very large matrices at each iteration. Therefore, they suffer from high computational cost. In this paper, we propose a novel trace norm regularized CANDECOMP/PARAFAC decomposition (TNCP) method for simultaneous tensor decomposition and completion. We first formulate a factor matrix rank minimization model by deducing the relation between the rank of each factor matrix and the mode- n rank of a tensor. Then, we introduce a tractable relaxation of our rank function, and then achieve a convex combination problem of much smaller-scale matrix trace norm minimization. Finally, we develop an efficient algorithm based on alternating direction method of multipliers to solve our problem. The promising experimental results on synthetic and real-world data validate the effectiveness of our TNCP method. Moreover, TNCP is significantly faster than the state-of-the-art methods and scales to larger problems.

Ethanol- and trifluoroethanol-induced changes in phase states of DPPC membranes. Prodan emission-excitation fluorescence spectroscopy supported by PARAFAC analysis

Science.gov (United States)

Horochowska, Martyna; Cieślik-Boczula, Katarzyna; Rospenk, Maria

2018-03-01

It has been shown that Prodan emission-excitation fluorescence spectroscopy supported by Parallel Factor (PARAFAC) analysis is a fast, simple and sensitive method used in the study of the phase transition from the noninterdigitated gel (Lβ‧) state to the interdigitated gel (LβI) phase, triggered by ethanol and 2,2,2-trifluoroethanol (TFE) molecules in dipalmitoylphosphatidylcholines (DPPC) membranes. The relative contribution of lipid phases with spectral characteristics of each pure phase component has been presented as a function of an increase in alcohol concentration. It has been stated that both alcohol molecules can induce a formation of the LβI phase, but TFE is over six times stronger inducer of the interdigitated phase in DPPC membranes than ethanol molecules. Moreover, in the TFE-mixed DPPC membranes, the transition from the Lβ‧ to LβI phase is accompanied by a formation of the fluid phase, which most probably serves as a boundary phase between the Lβ‧ and LβI regions. Contrary to the three phase-state model of TFE-mixed DPPC membranes, in ethanol-mixed DPPC membranes only the two phase-state model has been detected.

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

Science.gov (United States)

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

2016-08-01

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

PARAFAC: uma ferramenta quimiométrica para tratamento de dados multidimensionais. Aplicações na determinação direta de fármacos em plasma humano por espectrofluorimetria PARAFAC: a chemometric tool for multi-dimensional data treatment. Applications in direct determination of drugs in human plasma by spectrofluorimetry

Directory of Open Access Journals (Sweden)

Marcelo M. Sena

2005-10-01

Full Text Available 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 multivariate calibration and the development of multi-dimensional methods is presented first. The other objective of this article is to divulge for the Brazilian chemical community the potential of the combination PARAFAC/spectrofluorimetry for the determination of drugs in complex biological matrices. For this purpose, two applications aiming at determining, respectively, doxorrubicine and salicylate in human plasma are presented.

[Application of excitation-emission matrix spectrum combined with parallel factor analysis in dissolved organic matter in East China Sea].

Science.gov (United States)

Lü, Li-Sha; Zhao, Wei-Hong; Miao, Hui

2013-03-01

Using excitation-emission matrix spectrum(EEMs) combined with parallel factor analysis (PARAFAC) examine the fluorescent components feature of dissolved organic matter (DOM) sampled from East China Sea in the summer and autumn was examined. The type, distribution and origin of the fluorescence dissolved organic matter were also discussed. Three fluorescent components were identified by PARAFAC, including protein-like component C1 (235, 280/330), terrestrial or marine humic-like component C2 (255, 330/400) and terrestrial humic-like component C3 (275, 360/480). The good linearity of the two humic-like components showed the same source or some relationship between the chemical constitutions. As a whole, the level of the fluorescence intensity in coastal ocean was higher than that of the open ocean in different water layers in two seasons. The relationship of three components with chlorophyll-a and salinity showed the DOM in the study area is almost not influenced by the living algal matter, but the fresh water outflow of the Yangtze River might be the source of them in the Yangtze River estuary in Summer. From what has been discussed above, we can draw the conclusion that the application of EEM-PARAFAC modeling will exert a profound influence upon the research of the dissolved organic matter.

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

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

Science.gov (United States)

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

2017-09-01

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

Optimization of headspace experimental factors to determine chlorophenols in water by means of headspace solid-phase microextraction and gas chromatography coupled with mass spectrometry and parallel factor analysis.

Science.gov (United States)

Morales, Rocío; Cruz Ortiz, M; Sarabia, Luis A

2012-11-19

In this work an analytical procedure based on headspace solid-phase microextraction and gas chromatography coupled with mass spectrometry (HS-SPME-GC/MS) is proposed to determine chlorophenols with prior derivatization step to improve analyte volatility and therefore the decision limit (CCα). After optimization, the analytical procedure was applied to analyze river water samples. The following analytes are studied: 2,4-dichlorophenol (2,4-DCP), 2,4,6-trichlorophenol (2,4,6-TrCP), 2,3,4,6-tetrachlorophenol (2,4,6-TeCP) and pentachlorophenol (PCP). A D-optimal design is used to study the parameters affecting the HS-SPME process and the derivatization step. Four experimental factors at two levels and one factor at three levels were considered: (i) equilibrium/extraction temperature, (ii) extraction time, (iii) sample volume, (iv) agitation time and (v) equilibrium time. In addition two interactions between four of them were considered. The D-optimal design enables the reduction of the number of experiments from 48 to 18 while maintaining enough precision in the estimation of the effects. As every analysis took 1h, the design is blocked in 2 days. The second-order property of the PARAFAC (parallel factor analysis) decomposition avoids the need of fitting a new calibration model each time that the experimental conditions change. In consequence, the standardized loadings in the sample mode estimated by a PARAFAC decomposition are the response used in the design because they are proportional to the amount of analyte extracted. It has been found that block effect is significant and that 60°C equilibrium temperature together with 25min extraction time are necessary to achieve the best extraction for the chlorophenols analyzed. The other factors and interactions were not significant. After that, a calibration based in a PARAFAC2 decomposition provided the following values of CCα: 120, 208, 86, 39ngL(-1) for 2,4-DCP, 2,4,6-TrCP, 2,3,4,5-TeCP and PCP respectively for a

The Carroll and Chang conjecture of equal Indscal components when Candecomp/Parafac gives perfect fit

NARCIS (Netherlands)

Ten Berge, J.M.F.; Stegeman, A.; Bennani-Dosse, M.

2009-01-01

The Candecomp/Parafac algorithm approximates a set of matrices X(1),...,X(I), by products of the form AC(i)B', with C(i) diagonal, i = 1,...,I. Carroll and Chang have conjectured that, when the matrices are symmetric, the resulting A and B will be column wise proportional. For cases of perfect fit,

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

The relationship of chromophoric dissolved organic matter parallel factor analysis fluorescence and polycyclic aromatic hydrocarbons in natural surface waters.

Science.gov (United States)

Li, Sijia; Chen, Ya'nan; Zhang, Jiquan; Song, Kaishan; Mu, Guangyi; Sun, Caiyun; Ju, Hanyu; Ji, Meichen

2018-01-01

Polycyclic aromatic hydrocarbons (PAHs), a large group of persistent organic pollutants (POPs), have caused wide environmental pollution and ecological effects. Chromophoric dissolved organic matter (CDOM), which consists of complex compounds, was seen as a proxy of water quality. An attempt was made to understand the relationships of CDOM absorption parameters and parallel factor analysis (PARAFAC) components with PAHs under seasonal variation in the riverine, reservoir, and urban waters of the Yinma River watershed in 2016. These different types of water bodies provided wide CDOM and PAHs concentration ranges with CDOM absorption coefficients at a wavelength of 350 nm (a CDOM (350)) of 1.17-20.74 m -1 and total PAHs of 0-1829 ng/L. CDOM excitation-emission matrix (EEM) presented two fluorescent components, e.g., terrestrial humic-like (C1) and tryptophan-like (C2) were identified using PARAFAC. Tryptophan-like associated protein-like fluorescence often dominates the EEM signatures of sewage samples. Our finding is that seasonal CDOM EEM-PARAFAC and PAHs concentration showed consistent tendency indicated that PAHs were un-ignorable pollutants. However, the disparities in seasonal CDOM-PAH relationships relate to the similar sources of CDOM and PAHs, and the proportion of PAHs in CDOM. Overlooked and poorly appreciated, quantifying the relationship between CDOM and PAHs has important implications, because these results simplify ecological and health-based risk assessment of pollutants compared to the traditional chemical measurements.

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. Copyright © 2016 Elsevier Ltd. All rights reserved.

Fluorescence, electrophoretic and chromatographic fingerprints of herbal medicines and their comparative chemometric analysis.

Science.gov (United States)

Mazina, Jekaterina; Vaher, Merike; Kuhtinskaja, Maria; Poryvkina, Larisa; Kaljurand, Mihkel

2015-07-01

The aim of the present study was to compare the polyphenolic compositions of 47 medicinal herbs (HM) and four herbal tea mixtures from Central Estonia by rapid, reliable and sensitive Spectral Fluorescence Signature (SFS) method in a front face mode. The SFS method was validated for the main identified HM representatives including detection limits (0.037mgL(-1) for catechin, 0.052mgL(-1) for protocatechuic acid, 0.136mgL(-1) for chlorogenic acid, 0.058mgL(-1) for syringic acid and 0.256mgL(-1) for ferulic acid), linearity (up to 5.0-15mgL(-1)), intra-day precision (RSDs=6.6-10.6%), inter-day precision (RSDs=6.4-13.8%), matrix effect (-15.8 to +5.5) and recovery (85-107%). The phytochemical fingerprints were differentiated by parallel factor analysis (PARAFAC) combined with hierarchical cluster analysis (CA) and principal component analysis (PCA). HM were clustered into four main clusters (catechin-like, hydroxycinnamic acid-like, dihydrobenzoic acid-like derivatives containing HM and HM with low/very low content of fluorescent constituents) and 14 subclusters (rich, medium, low/very low contents). The average accuracy and precision of CA for validation HM set were 97.4% (within 85.2-100%) and 89.6%, (within 66.7-100%), respectively. PARAFAC-PCA/CA has improved the analysis of HM by the SFS method. The results were verified by two separation methods CE-DAD and HPLC-DAD-MS also combined with PARAFAC-PCA/CA. The SFS-PARAFAC-PCA/CA method has potential as a rapid and reliable tool for investigating the fingerprints and predicting the composition of HM or evaluating the quality and authenticity of different standardised formulas. Moreover, SFS-PARAFAC-PCA/CA can be implemented as a laboratory and/or an onsite method. Copyright © 2015 Elsevier B.V. All rights reserved.

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...... revealed that the organic matter fluorescence was characterised by five different components, one of which was unique to swimming pool organic matter and one which was specific to organic contamination. The latter component had emission peaks at 420nm and was found to be a sensitive indicator of organic...... loading in swimming pool water. The fluorescence at 420nm gradually increased during opening hours and represented material accumulating through the day....

Drivers of fluorescent dissolved organic matter in the global epipelagic ocean

KAUST Repository

Catalá , T. S.; Á lvarez-Salgado, X. A.; Otero, J.; Iuculano, F.; Companys, B.; Horstkotte, B.; Romera-Castillo, C.; Nieto-Cid, M.; Latasa, M.; Moran, Xose Anxelu G.; Gasol, J. M.; Marrasé , C.; Stedmon, C. A.; Reche, I.

2016-01-01

Fluorescent dissolved organic matter (FDOM) in open surface waters (< 200 m) of the Atlantic, Pacific, and Indian oceans was analysed by excitation-emission matrix (EEM) spectroscopy and parallel factor analysis (PARAFAC). A four-component PARAFAC

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

Science.gov (United States)

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

2010-06-01

The distribution and estuarine behavior of fluorescent components of chromophoric dissolved organic matter (CDOM) from Jiulong Estuary were determined by fluorescence excitation emission matrix spectroscopy (EEMs) combined with parallel factor analysis (PARAFAC). The feasibility of these components as tracers for organic pollution in estuarine environments was also evaluated. Four separate fluorescent components were identified by PARAFAC, including three humic-like components (C1: 240, 310/382 nm; C2: 230, 250, 340/422 nm; C4: 260, 390/482 nm) and one protein-like components (C3: 225, 275/342 nm). These results indicated that UV humic-like peak A area designated by traditional "peak-picking method" was not a single peak but actually a combination of several fluorescent components, and it also had inherent links to so-called marine humic-like peak M or terrestrial humic-like peak C. Component C2 which include peak M decreased with increase of salinity in Jiulong Estuary, demonstrating that peak M can not be thought as the specific indicator of the "marine" humic-like component. Two humic-like components C1 and C2 showed additional behavior in the turbidity maximum region (salinity CDOM may provide a fast in-situ way to monitor the variation of the degree of organic pollution in estuarine environments.

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach

Science.gov (United States)

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions. PMID:29033978

Linking groundwater dissolved organic matter to sedimentary organic matter from a fluvio-lacustrine aquifer at Jianghan Plain, China by EEM-PARAFAC and hydrochemical analyses.

Science.gov (United States)

Huang, Shuang-bing; Wang, Yan-xin; Ma, Teng; Tong, Lei; Wang, Yan-yan; Liu, Chang-rong; Zhao, Long

2015-10-01

The sources of dissolved organic matter (DOM) in groundwater are important to groundwater chemistry and quality. This study examined similarities in the nature of DOM and investigated the link between groundwater DOM (GDOM) and sedimentary organic matter (SOM) from a lacustrine-alluvial aquifer at Jianghan Plain. Sediment, groundwater and surface water samples were employed for SOM extraction, optical and/or chemical characterization, and subsequent fluorescence excitation-emission matrix (EEM) and parallel factor analyses (PARAFAC). Spectroscopic properties of bulk DOM pools showed that indices indicative of GDOM (e.g., biological source properties, humification level, aromaticity and molecule mobility) varied within the ranges of those of two extracted end-members of SOM: humic-like materials and microbe-associated materials. The coexistence of PARAFAC compositions and the sustaining internal relationship between GDOM and extracted SOM indicate a similar source. The results from principal component analyses with selected spectroscopic indices showed that GDOM exhibited a transition trend regarding its nature: from refractory high-humification DOM to intermediate humification DOM and then to microbe-associated DOM, with decreasing molecular weight. Correlations of spectroscopic indices with physicochemical parameters of the groundwater suggested that GDOM was released from SOM and was modified by microbial diagenetic processes. The current study demonstrated the associations of GDOM with SOM from a spectroscopic viewpoint and provided new evidence supporting SOM as the source of GDOM. Copyright © 2015 Elsevier B.V. All rights reserved.

Characterizing chromophoric dissolved organic matter in Lake Tianmuhu and its catchment basin using excitation-emission matrix fluorescence and parallel factor analysis.

Science.gov (United States)

Zhang, Yunlin; Yin, Yan; Feng, Longqing; Zhu, Guangwei; Shi, Zhiqiang; Liu, Xiaohan; Zhang, Yuanzhi

2011-10-15

Chromophoric dissolved organic matter (CDOM) is an important optically active substance that transports nutrients, heavy metals, and other pollutants from terrestrial to aquatic systems and is used as a measure of water quality. To investigate how the source and composition of CDOM changes in both space and time, we used chemical, spectroscopic, and fluorescence analyses to characterize CDOM in Lake Tianmuhu (a drinking water source) and its catchment in China. Parallel factor analysis (PARAFAC) identified three individual fluorophore moieties that were attributed to humic-like and protein-like materials in 224 water samples collected between December 2008 and September 2009. The upstream rivers contained significantly higher concentrations of CDOM than did the lake water (a(350) of 4.27±2.51 and 2.32±0.59 m(-1), respectively), indicating that the rivers carried a substantial load of organic matter to the lake. Of the three main rivers that flow into Lake Tianmuhu, the Pingqiao River brought in the most CDOM from the catchment to the lake. CDOM absorption and the microbial and terrestrial humic-like components, but not the protein-like component, were significantly higher in the wet season than in other seasons, indicating that the frequency of rainfall and runoff could significantly impact the quantity and quality of CDOM collected from the catchment. The different relationships between the maximum fluorescence intensities of the three PARAFAC components, CDOM absorption, and chemical oxygen demand (COD) concentration in riverine and lake water indicated the difference in the composition of CDOM between Lake Tianmuhu and the rivers that feed it. This study demonstrates the utility of combining excitation-emission matrix fluorescence and PARAFAC to study CDOM dynamics in inland waters. Copyright © 2011 Elsevier Ltd. All rights reserved.

Interactions between stepwise-eluted sub-fractions of fulvic acids and protons revealed by fluorescence titration combined with EEM-PARAFAC.

Science.gov (United States)

Song, Fanhao; Wu, Fengchang; Guo, Fei; Wang, Hao; Feng, Weiying; Zhou, Min; Deng, Yanghui; Bai, Yingchen; Xing, Baoshan; Giesy, John P

2017-12-15

In aquatic environments, pH can control environmental behaviors of fulvic acid (FA) via regulating hydrolysis of functional groups. Sub-fractions of FA, eluted using pyrophosphate buffers with initial pHs of 3.0 (FA 3 ), 5.0 (FA 5 ), 7.0 (FA 7 ), 9.0 (FA 9 ) and 13.0 (FA 13 ), were used to explore interactions between the various, operationally defined, FA fractions and protons, by use of EEM-PARAFAC analysis. Splitting of peaks (FA 3 and FA 13 ), merging of peaks (FA 7 ), disappearance of peaks (FA 9 and FA 13 ), and red/blue-shifting of peaks were observed during fluorescence titration. Fulvic-like components were identified from FA 3 -FA 13 , and protein-like components were observed in fractions FA 9 and FA 13 . There primary compounds (carboxylic-like, phenolic-like, and protein-like chromophores) in PARAFAC components were distinguished based on acid-base properties. Dissociation constants (pK a ) for fulvic-like components with proton ranged from 2.43 to 4.13 in an acidic pH and from 9.95 to 11.27 at basic pH. These results might be due to protonation of di-carboxylate and phenolic functional groups. At basic pH, pK a values of protein-like components (9.77-10.13) were similar to those of amino acids. However, at acidic pH, pK a values of protein-like components, which ranged from 3.33 to 4.22, were 1-2units greater than those of amino acids. Results presented here, will benefit understanding of environmental behaviors of FA, as well as interactions of FA with environmental contaminants. Copyright © 2017 Elsevier B.V. All rights reserved.

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-stat...

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 (< 200 m) of the Atlantic, Pacific, and Indian 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 hum...

Simultaneous and Direct Determination of Vancomycin and Cephalexin in Human Plasma by Using HPLC-DAD Coupled with Second-Order Calibration Algorithms

Directory of Open Access Journals (Sweden)

Le-Qian Hu

2012-01-01

Full Text Available A simple, rapid, and sensitive method for the simultaneous determination of vancomycin and cephalexin in human plasma was developed by using HPLC-DAD with second-order calibration algorithms. Instead of a completely chromatographic separation, mathematical separation was performed by using two trilinear decomposition algorithms, that is, PARAFAC-alternative least squares (PARAFAC-ALSs and self-weight-alternative-trilinear-decomposition- (SWATLD- coupled high-performance liquid chromatography with DAD detection. The average recoveries attained from PARAFAC-ALS and SWATLD with the factor number of 4 (N=4 were 101±5% and 102±4% for vancomycin, and 96±3% and 97±3% for cephalexininde in real human samples, respectively. The statistical comparison between PARAFAC-ALS and SWATLD is demonstrated to be similar. The results indicated that the combination of HPLC-DAD detection with second-order calibration algorithms is a powerful tool to quantify the analytes of interest from overlapped chromatographic profiles for complex analysis of drugs in plasma.

Development and validation of a method for the determination of regulated fragrance allergens by High-Performance Liquid Chromatography and Parallel Factor Analysis 2.

Science.gov (United States)

Pérez-Outeiral, Jessica; Elcoroaristizabal, Saioa; Amigo, Jose Manuel; Vidal, Maider

2017-12-01

This work presents the development and validation of a multivariate method for quantitation of 6 potentially allergenic substances (PAS) related to fragrances by ultrasound-assisted emulsification microextraction coupled with HPLC-DAD and PARAFAC2 in the presence of other 18 PAS. The objective is the extension of a previously proposed univariate method to be able to determine the 24 PAS currently considered as allergens. The suitability of the multivariate approach for the qualitative and quantitative analysis of the analytes is discussed through datasets of increasing complexity, comprising the assessment and validation of the method performance. PARAFAC2 showed to adequately model the data facing up different instrumental and chemical issues, such as co-elution profiles, overlapping spectra, unknown interfering compounds, retention time shifts and baseline drifts. Satisfactory quality parameters of the model performance were obtained (R 2 ≥0.94), as well as meaningful chromatographic and spectral profiles (r≥0.97). Moreover, low errors of prediction in external validation standards (below 15% in most cases) as well as acceptable quantification errors in real spiked samples (recoveries from 82 to 119%) confirmed the suitability of PARAFAC2 for resolution and quantification of the PAS. The combination of the previously proposed univariate approach, for the well-resolved peaks, with the developed multivariate method allows the determination of the 24 regulated PAS. Copyright © 2017 Elsevier B.V. All rights reserved.

Tensor Deflation for CANDECOMP/PARAFAC - Part II: Initialization and Error Analysis

Czech Academy of Sciences Publication Activity Database

Phan, A. H.; Tichavský, Petr; Cichocki, A.

2015-01-01

Roč. 63, č. 22 (2015), s. 5939-5950 ISSN 1053-587X R&D Projects: GA ČR(CZ) GA14-13713S Institutional support: RVO:67985556 Keywords : Canonical polyadic decomposition * tensor deflation * performance analysis Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.624, year: 2015 http://library.utia.cas.cz/separaty/2015/SI/tichavsky-0448266.pdf

Scalable Tensor Factorizations with Missing Data

DEFF Research Database (Denmark)

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

2010-01-01

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...... 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...

Scalable tensor factorizations for incomplete data

DEFF Research Database (Denmark)

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

2011-01-01

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...... 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 × 1000 × 1000 with five million known entries (0.5% dense). We further demonstrate the usefulness of CP...

Comprehensive analysis of yeast metabolite GC x GC-TOFMS data: combining discovery-mode and deconvolution chemometric software.

Science.gov (United States)

Mohler, Rachel E; Dombek, Kenneth M; Hoggard, Jamin C; Pierce, Karisa M; Young, Elton T; Synovec, Robert E

2007-08-01

The first extensive study of yeast metabolite GC x GC-TOFMS data from cells grown under fermenting, R, and respiring, DR, conditions is reported. In this study, recently developed chemometric software for use with three-dimensional instrumentation data was implemented, using a statistically-based Fisher ratio method. The Fisher ratio method is fully automated and will rapidly reduce the data to pinpoint two-dimensional chromatographic peaks differentiating sample types while utilizing all the mass channels. The effect of lowering the Fisher ratio threshold on peak identification was studied. At the lowest threshold (just above the noise level), 73 metabolite peaks were identified, nearly three-fold greater than the number of previously reported metabolite peaks identified (26). In addition to the 73 identified metabolites, 81 unknown metabolites were also located. A Parallel Factor Analysis graphical user interface (PARAFAC GUI) was applied to selected mass channels to obtain a concentration ratio, for each metabolite under the two growth conditions. Of the 73 known metabolites identified by the Fisher ratio method, 54 were statistically changing to the 95% confidence limit between the DR and R conditions according to the rigorous Student's t-test. PARAFAC determined the concentration ratio and provided a fully-deconvoluted (i.e. mathematically resolved) mass spectrum for each of the metabolites. The combination of the Fisher ratio method with the PARAFAC GUI provides high-throughput software for discovery-based metabolomics research, and is novel for GC x GC-TOFMS data due to the use of the entire data set in the analysis (640 MB x 70 runs, double precision floating point).

Modelling spatial and temporal variations in the water quality of an artificial water reservoir in the semiarid Midwest of Argentina

Energy Technology Data Exchange (ETDEWEB)

Cid, Fabricio D., E-mail: fabricio.cid@gmail.com [Laboratory of Biology ' Prof. E. Caviedes Codelia' , Facultad de Ciencias Humanas, Universidad Nacional de San Luis, San Luis (Argentina); Laboratory of Integrative Biology, Institute for Multidisciplinary Research in Biology (IMIBIO-SL), Consejo Nacional de Investigaciones Cientificas y Tecnicas, San Luis (Argentina); Department of Biochemistry and Biological Sciences, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina); Anton, Rosa I. [Department of Analytical Chemistry, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina); Pardo, Rafael; Vega, Marisol [Department of Analytical Chemistry, Facultad de Ciencias, Universidad de Valladolid, Valladolid (Spain); Caviedes-Vidal, Enrique [Laboratory of Biology ' Prof. E. Caviedes Codelia' , Facultad de Ciencias Humanas, Universidad Nacional de San Luis, San Luis (Argentina); Laboratory of Integrative Biology, Institute for Multidisciplinary Research in Biology (IMIBIO-SL), Consejo Nacional de Investigaciones Cientificas y Tecnicas, San Luis (Argentina); Department of Biochemistry and Biological Sciences, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina)

2011-10-31

Highlights: {yields} Water quality of an Argentinean reservoir has been investigated by N-way PCA. {yields} PARAFAC mode modelled spatial and seasonal variations of water composition. {yields} Two factors related with organic and lead pollution have been identified. {yields} The most polluted areas of the reservoir were located, and polluting sources identified. - Abstract: Temporal and spatial patterns of water quality of an important artificial water reservoir located in the semiarid Midwest of Argentina were investigated using chemometric techniques. Surface water samples were collected at 38 points of the water reservoir during eleven sampling campaigns between October 1998 and June 2000, covering the warm wet season and the cold dry season, and analyzed for dissolved oxygen (DO), conductivity, pH, ammonium, nitrate, nitrite, total dissolved solids (TDS), alkalinity, hardness, bicarbonate, chloride, sulfate, calcium, magnesium, fluoride, sodium, potassium, iron, aluminum, silica, phosphate, sulfide, arsenic, chromium, lead, cadmium, chemical oxygen demand (COD), biochemical oxygen demand (BOD), viable aerobic bacteria (VAB) and total coliform bacteria (TC). Concentrations of lead, ammonium, nitrite and coliforms were higher than the maximum allowable limits for drinking water in a large proportion of the water samples. To obtain a general representation of the spatial and temporal trends of the water quality parameters at the reservoir, the three-dimensional dataset (sampling sites x parameters x sampling campaigns) has been analyzed by matrix augmentation principal component analysis (MA-PCA) and N-way principal component analysis (N-PCA) using Tucker3 and PARAFAC (Parallel Factor Analysis) models. MA-PCA produced a component accounting for the general behavior of parameters associated with organic pollution. The Tucker3 models were not appropriate for modelling the water quality dataset. The two-factor PARAFAC model provided the best picture to understand the

Modelling spatial and temporal variations in the water quality of an artificial water reservoir in the semiarid Midwest of Argentina

International Nuclear Information System (INIS)

Cid, Fabricio D.; Anton, Rosa I.; Pardo, Rafael; Vega, Marisol; Caviedes-Vidal, Enrique

2011-01-01

Highlights: → Water quality of an Argentinean reservoir has been investigated by N-way PCA. → PARAFAC mode modelled spatial and seasonal variations of water composition. → Two factors related with organic and lead pollution have been identified. → The most polluted areas of the reservoir were located, and polluting sources identified. - Abstract: Temporal and spatial patterns of water quality of an important artificial water reservoir located in the semiarid Midwest of Argentina were investigated using chemometric techniques. Surface water samples were collected at 38 points of the water reservoir during eleven sampling campaigns between October 1998 and June 2000, covering the warm wet season and the cold dry season, and analyzed for dissolved oxygen (DO), conductivity, pH, ammonium, nitrate, nitrite, total dissolved solids (TDS), alkalinity, hardness, bicarbonate, chloride, sulfate, calcium, magnesium, fluoride, sodium, potassium, iron, aluminum, silica, phosphate, sulfide, arsenic, chromium, lead, cadmium, chemical oxygen demand (COD), biochemical oxygen demand (BOD), viable aerobic bacteria (VAB) and total coliform bacteria (TC). Concentrations of lead, ammonium, nitrite and coliforms were higher than the maximum allowable limits for drinking water in a large proportion of the water samples. To obtain a general representation of the spatial and temporal trends of the water quality parameters at the reservoir, the three-dimensional dataset (sampling sites x parameters x sampling campaigns) has been analyzed by matrix augmentation principal component analysis (MA-PCA) and N-way principal component analysis (N-PCA) using Tucker3 and PARAFAC (Parallel Factor Analysis) models. MA-PCA produced a component accounting for the general behavior of parameters associated with organic pollution. The Tucker3 models were not appropriate for modelling the water quality dataset. The two-factor PARAFAC model provided the best picture to understand the spatial and

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

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......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...

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

Fast Alternating LS Algorithms for High Order CANDECOMP/PARAFAC Tensor Factorizations

Czech Academy of Sciences Publication Activity Database

Phan, A. H.; Tichavský, Petr; Cichocki, A.

2013-01-01

Roč. 61, č. 19 (2013), s. 4834-4846 ISSN 1053-587X R&D Projects: GA ČR GA102/09/1278 Institutional support: RVO:67985556 Keywords : Canonical polyadic decomposition * tensor decomposition Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 3.198, year: 2013 http://library.utia.cas.cz/separaty/2013/SI/tichavsky-0396774.pdf

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.

Chemical structure of the Chromophoric Dissolved Organic Matter (CDOM) fluorescent matter.

Science.gov (United States)

Blough, N. V.; Del Vecchio, R.; Cartisano, C. M.; Bianca, M.

2017-12-01

The structure(s), distribution and dynamics of CDOM have been investigated over the last several decades largely through optical spectroscopy (including both absorption and fluorescence) due to the fairly inexpensive instrumentation and the easy-to-gather data (over thousands published papers from 1990-2016). Yet, the chemical structure(s) of the light absorbing and emitting species or constituents within CDOM has only recently being proposed and tested through chemical manipulation of selected functional groups (such as carbonyl and carboxylic/phenolic containing molecules) naturally occurring within the organic matter pool. Similarly, fitting models (among which the PArallel FACtor analysis, PARAFAC) have been developed to better understand the nature of a subset of DOM, the CDOM fluorescent matter (FDOM). Fluorescence spectroscopy coupled with chemical tests and PARAFAC analyses could potentially provide valuable insights on CDOM sources and chemical nature of the FDOM pool. However, despite that applications (and publications) of PARAFAC model to FDOM have grown exponentially since its first application/publication (2003), a large fraction of such publications has misinterpreted the chemical meaning of the delivered PARAFAC `components' leading to more confusion than clarification on the nature, distribution and dynamics of the FDOM pool. In this context, we employed chemical manipulation of selected functional groups to gain further insights on the chemical structure of the FDOM and we tested to what extent the PARAFAC `components' represent true fluorophores through a controlled chemical approach with the ultimate goal to provide insights on the chemical nature of such `components' (as well as on the chemical nature of the FDOM) along with the advantages and limitations of the PARAFAC application.

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

Science.gov (United States)

Baum, Andreas; Hansen, Per Waaben; Meyer, Anne S; Mikkelsen, Jørn Dalgaard

2013-08-06

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 Rpred(2) 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, respectively. The retrieved models are compared and prediction test sets show that especially TUCKER3 performs well, even in comparison to the supervised regression method N-PLS. Copyright © 2013 Elsevier B.V. All rights reserved.

[Research on optimal modeling strategy for licorice extraction process based on near-infrared spectroscopy technology].

Science.gov (United States)

Wang, Hai-Xia; Suo, Tong-Chuan; Yu, He-Shui; Li, Zheng

2016-10-01

The manufacture of traditional Chinese medicine (TCM) products is always accompanied by processing complex raw materials and real-time monitoring of the manufacturing process. In this study, we investigated different modeling strategies for the extraction process of licorice. Near-infrared spectra associate with the extraction time was used to detemine the states of the extraction processes. Three modeling approaches, i.e., principal component analysis (PCA), partial least squares regression (PLSR) and parallel factor analysis-PLSR (PARAFAC-PLSR), were adopted for the prediction of the real-time status of the process. The overall results indicated that PCA, PLSR and PARAFAC-PLSR can effectively detect the errors in the extraction procedure and predict the process trajectories, which has important significance for the monitoring and controlling of the extraction processes. Copyright© by the Chinese Pharmaceutical Association.

New light on a dark subject: On the use of fluorescence data to deduce redox states of natural organic matter (NOM)

Science.gov (United States)

Macalady, Donald L.; Walton-Day, Katherine

2009-01-01

This paper reports the use of excitation-emission matrix fluorescence spectroscopy (EEMS), parallel factor statistical analysis (PARAFAC), and oxidation-reduction experiments to examine the effect of redox conditions on PARAFAC model results for aqueous samples rich in natural organic matter. Fifty-four aqueous samples from 11 different geographic locations and two plant extracts were analyzed untreated and after chemical treatments or irradiation were used in attempts to change the redox status of the natural organic matter. The EEMS spectra were generated and modeled using a PARAFAC package developed by Cory and McKnight (2005). The PARAFAC model output was examined for consistency with previously reported relations and with changes expected to occur upon experimental oxidation and reduction of aqueous samples. Results indicate the implied fraction of total sample fluorescence attributed to quinone-like moieties was consistent (0.64 to 0.78) and greater than that observed by Cory and McKnight (2005). The fraction of the quinone-like moieties that was reduced (the reducing index, RI) showed relatively little variation (0.46 to 0.71) despite attempts to alter the redox status of the natural organic matter. The RI changed little after reducing samples using zinc metal, oxidizing at high pH with air, or irradiating with a Xenon lamp. Our results, however, are consistent with the correlations between the fluorescence indices (FI) of samples and the ratio of PARAFAC fitting parameters suggested by Cory and McKnight (2005), though we used samples with a much narrower range of FI values.

Drivers of fluorescent dissolved organic matter in the global epipelagic ocean

KAUST Repository

Catalá, T. S.

2016-03-24

Fluorescent dissolved organic matter (FDOM) in open surface waters (< 200 m) of the Atlantic, Pacific, and Indian 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. Generalized-additive 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 was substantially larger (> 70%) than for the amino acid-like components (< 35%). The environmental variables exhibiting the largest effect on the global distribution of C1 and C2 were apparent oxygen utilisation followed by chlorophyll a. Positive non-linear relationships between both predictor variables 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 effect of photobleaching is also detected. C3 (tryptophan-like) and C4 (tyrosine-like) variability was mostly dictated by salinity (S), by means of positive non-linear relationships, suggesting a primary physical control of their distributions at the global surface ocean scale that could be related to the changing evaporation-precipitation regime. Remarkably, bacterial biomass (BB) only contributed to explain a minor part of the variability of C1 and C4.

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...... 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...... of FBP induced by folate binding. Parameters for ligand binding derived from PARAFAC analysis of the fluorescence data were qualitatively and quantitatively similar to those obtained from binding of radiofolate to FBP. Herein, methotrexate exhibited a higher affinity for FBP than in competition...

Detection and quantification of extra virgin olive oil adulteration by means of autofluorescence excitation-emission profiles combined with multi-way classification.

Science.gov (United States)

Durán Merás, Isabel; Domínguez Manzano, Jaime; Airado Rodríguez, Diego; Muñoz de la Peña, Arsenio

2018-02-01

Within olive oils, extra virgin olive oil is the highest quality and, in consequence, the most expensive one. Because of that, it is common that some merchants attempt to take economic advantage by mixing it up with other less expensive oils, like olive oil or olive pomace oil. In consequence, the characterization and authentication of extra virgin olive oils is a subject of great interest, both for industry and consumers. This paper reports the potential of front-face total fluorescence spectroscopy combined with second-order chemometric methods for the detection of extra virgin olive oils adulteration with other olive oils. Excitation-emission matrices (EEMs) of extra virgin olive oils and extra virgin olive oils adulterated with olive oils or with olive pomace oils were recorded using front-face fluorescence spectroscopy. The full information content in these fluorescence images was analyzed with the aid of unsupervised parallel factor analysis (PARAFAC), PARAFAC supervised by linear discriminant analysis (LDA-PARAFAC), and discriminant unfolded partial least-squares (DA-UPLS). The discriminant ability of LDA-PARAFAC was studied through the tridimensional plots of the canonical vectors, defining a surface separating the established categories. For DA-UPLS, the discriminant ability was established through the bidimensional plots of predicted values of calibration and validation samples, in order to assign each sample to a given class. The models demonstrated the possibility of detecting adulterations of extra virgin olive oils with percentages of around 15% and 3% of olive and olive pomace oils, respectively. Also, UPLS regression was used to quantify the adulteration level of extra virgin olive oils with olive oils or with olive pomace oils. Copyright © 2017 Elsevier B.V. All rights reserved.

Photo- and bio-reactivity patterns of dissolved organic matter from biomass and soil leachates and surface waters in a subtropical wetland.

Science.gov (United States)

Chen, Meilian; Jaffé, Rudolf

2014-09-15

Dissolved organic carbon (DOC) measurements and optical properties were applied to assess the photo- and bio-reactivity of dissolved organic matter (DOM) from different sources, including biomass leaching, soil leaching and surface waters in a subtropical wetland ecosystem. Samples were exposed to light and/or dark incubated through controlled laboratory experiments. Changes in DOC, ultraviolet (UV-Vis) visible absorbance, and excitation-emission matrix (EEM) fluorescence combined with parallel factor analysis (PARAFAC) were performed to assess sample degradation. Degradation experiments showed that while significant amounts of DOC were consumed during bio-incubation for biomass leachates, a higher degree of bio-recalcitrance for soil leachate and particularly surface waters was displayed. Photo- and bio-humification transformations were suggested for sawgrass, mangrove, and seagrass leachates, as compared to substantial photo-degradation and very little to almost no change after bio-incubation for the other samples. During photo-degradation in most cases the EEM-PARAFAC components displayed photo-decay as compared to a few cases which featured photo-production. In contrast during bio-incubation most EEM-PARAFAC components proved to be mostly bio-refractory although some increases and decreases in abundance were also observed. Furthermore, the sequential photo- followed by bio-degradation showed, with some exceptions, a "priming effect" of light exposure on the bio-degradation of DOM, and the combination of these two processes resulted in a DOM composition more similar to that of the natural surface water for the different sub-environments. In addition, for leachate samples there was a general enrichment of one of the EEM-PARAFAC humic-like component (Ex/Em: bio-degradation process. This study exemplifies the effectiveness of optical property and EEM-PARAFAC in the assessment of DOM reactivity and highlights the importance of the coupling of photo- and bio

PARAFASCA: ASCA combined with PARAFAC for the analysis of metabolic fingerprinting data

NARCIS (Netherlands)

Jansen, J.J.; Bro, R.; Hoefsloot, H.C.J.; Berg, F.W.J. van den; Westerhuis, J.A.; Smilde, A.K.

2008-01-01

Novel post-genomics experiments such as metabolomics provide datasets that are highly multivariate and often reflect an underlying experimental design, developed with a specific experimental question in mind. ANOVA-simultaneous component analysis (ASCA) can be used for the analysis of multivariate

A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection. Quantitation of fluoroquinolones in water samples.

Science.gov (United States)

Alcaráz, Mirta R; Bortolato, Santiago A; Goicoechea, Héctor C; Olivieri, Alejandro C

2015-03-01

Matrix augmentation is regularly employed in extended multivariate curve resolution-alternating least-squares (MCR-ALS), as applied to analytical calibration based on second- and third-order data. However, this highly useful concept has almost no correspondence in parallel factor analysis (PARAFAC) of third-order data. In the present work, we propose a strategy to process third-order chromatographic data with matrix fluorescence detection, based on an Augmented PARAFAC model. The latter involves decomposition of a three-way data array augmented along the elution time mode with data for the calibration samples and for each of the test samples. A set of excitation-emission fluorescence matrices, measured at different chromatographic elution times for drinking water samples, containing three fluoroquinolones and uncalibrated interferences, were evaluated using this approach. Augmented PARAFAC exploits the second-order advantage, even in the presence of significant changes in chromatographic profiles from run to run. The obtained relative errors of prediction were ca. 10 % for ofloxacin, ciprofloxacin, and danofloxacin, with a significant enhancement in analytical figures of merit in comparison with previous reports. The results are compared with those furnished by MCR-ALS.

Fast-freezing with liquid nitrogen preserves bulk dissolved organic matter concentrations, but not its composition

DEFF Research Database (Denmark)

Thieme, Lisa; Graeber, Daniel; Kaupenjohann, Martin

2016-01-01

-freezing with liquid nitrogen) on DOM concentrations measured as organic carbon (DOC) concentrations and on spectroscopic properties of DOM from different terrestrial ecosystems (forest and grassland). Fresh and differently frozen throughfall, stemflow, litter leachate and soil solution samples were analyzed for DOC...... concentrations, UV-vis absorption and fluorescence excitation–emission matrices combined with parallel factor analysis (PARAFAC). Fast-freezing with liquid nitrogen prevented a significant decrease of DOC concentrations observed after freezing at −18 °C. Nonetheless, the share of PARAFAC components 1 (EXmax...... component 4 (EXmax: 280 nm, EXmax: 328 nm) to total fluorescence was not affected by freezing. We recommend fast-freezing with liquid nitrogen for preservation of bulk DOC concentrations of samples from terrestrial sources, whereas immediate measuring is preferable to preserve spectroscopic properties...

Making tensor factorizations robust to non-gaussian noise.

Energy Technology Data Exchange (ETDEWEB)

Chi, Eric C. (Rice University, Houston, TX); Kolda, Tamara Gibson

2011-03-01

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 independent and identically distributed (i.i.d.) Gaussian noise. We demonstrate that this loss function can 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 (MM) algorithm for fitting a CP model using our proposed loss function (CPAL1) and compare its performance to the workhorse algorithm for fitting CP models, CP alternating least squares (CPALS).

Decomposing the time-frequency representation of EEG using non-negative matrix and multi-way factorization

DEFF Research Database (Denmark)

Mørup, Morten; Hansen, Lars Kai; Parnas, Josef

2006-01-01

We demonstrate how non-negative matrix factorization (NMF) can be used to decompose the inter trial phase coherence (ITPC) of multi-channel EEG to yield a unique decomposition of time-frequency signatures present in various degrees in the recording channels. The NMF optimization is easily...... generalized to a parallel factor (PARAFAC) model to form a non-negative multi-way factorization (NMWF). While the NMF can examine subject specific activities the NMWF can effectively extract the most similar activities across subjects and or conditions. The methods are tested on a proprioceptive stimulus...... consisting of a weight change in a handheld load. While somatosensory gamma oscillations have previously only been evoked by electrical stimuli we hypothesized that a natural proprioceptive stimulus also would be able to evoke gamma oscillations. ITPC maxima were determined by visual inspection...

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

Science.gov (United States)

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

2017-06-01

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

Anthropogenic signature of sediment organic matter probed by UV-Visible and fluorescence spectroscopy and the association with heavy metal enrichment.

Science.gov (United States)

He, Wei; Lee, Jong-Hyun; Hur, Jin

2016-05-01

Sediment organic matter (SOM) was extracted in an alkaline solution from 43 stream sediments in order to explore the anthropogenic signatures. The SOM spectroscopic characteristics including excitation-emission matrix (EEM)-parallel factor analysis (PARAFAC) were compared for five sampling site groups classified by the anthropogenic variables of land use, population density, the loadings of organics and nutrients, and metal enrichment. The conventional spectroscopic characteristics including specific UV absorbance, absorbance ratio, and humification index did not properly discriminate among the different cluster groups except in the case of metal enrichment. Of the four decomposed PARAFAC components, humic-like and tryptophan-like fluorescence responded negatively and positively, respectively, to increasing degrees of the anthropogenic variables except for land use. The anthropogenic enrichment of heavy metals was positively associated with the abundance of tryptophan-like component. In contrast, humic-like component, known to be mostly responsible for metal binding, exhibited a decreasing trend corresponding with metal enrichment. These conflicting trends can be attributed to the overwhelmed effects of the coupled discharges of heavy metals and organic pollutants into sediments. Our study suggests that the PARAFAC components can be used as functional signatures to probe the anthropogenic influences on sediments. Copyright © 2016 Elsevier Ltd. All rights reserved.

Removal of NOM-constituents as characterized by LC-OCD and F-EEM during drinking water treatment

KAUST Repository

Baghoth, S. A.

2011-11-01

Natural organic matter (NOM) is of concern in drinking water because it causes adverse aesthetic qualities such as taste, odour, and colour; impedes the performance of treatment processes; and decreases the effectiveness of oxidants and disinfectants while contributing to undesirable disinfection by-products. The effective removal of NOM during drinking water treatment requires a good understanding of its character. Because of its heterogeneity, NOM characterization necessitates the use of multiple analytical techniques. In this study, NOM in water samples from two drinking water treatment trains was characterized using liquid chromatography with organic carbon detection (LC-OCD), and fluorescence excitation-emission matrices (F-EEMs) with parallel factor analysis (PARAFAC). These characterization methods indicate that the raw and treated waters are dominated by humic substances. The results show that whereas the coagulation process for both plants may be optimized for the removal of bulk DOC, it is not likewise optimized for the removal of specific NOM fractions. A five component PARAFAC model was developed for the F-EEMs, three of which are humic-like, while two are protein-like. These PARAFAC components and the LC-OCD fractions represented effective tools for the performance evaluation of the two water treatment plants in terms of the removal of NOM fractions. © IWA Publishing 2011.

Two and three way spectrophotometric-assisted multivariate determination of linezolid in the presence of its alkaline and oxidative degradation products and application to pharmaceutical formulation

Science.gov (United States)

Hegazy, Maha Abd El-Monem; Eissa, Maya Shaaban; Abd El-Sattar, Osama Ibrahim; Abd El-Kawy, Mohammad

2014-07-01

Linezolid (LIN) is determined in the presence of its alkaline (ALK) and oxidative (OXD) degradation products without preliminary separation based on ultraviolet spectrophotometry using two-way chemometric methods; principal component regression (PCR) and partial least-squares (PLS), and three-way chemometric methods; parallel factor analysis (PARAFAC) and multi-way partial least squares (N-PLS). A training set of mixtures containing LIN, ALK and OXD; was prepared in the concentration ranges of 12-18, 2.4-3.6 and 1.2-1.8 μg mL-1, respectively according to a multilevel multifactor experimental design. The multivariate calibrations were obtained by measuring the zero-order absorbance from 220 to 320 nm using the training set. The validation of the multivariate methods was realized by analyzing their synthetic mixtures. The capabilities of the chemometric analysis methods for the analysis of real samples were evaluated by determination of LIN in its pharmaceutical preparation with satisfactory results. The accuracy of the methods, evaluated through the root mean square error of prediction (RMSEP), was 0.058, 0.026, 0.101 and 0.026 for LIN using PCR, PLS, PARAFAC and N-PLS, respectively. Protolytic equilibria of LIN and its degradation products were evaluated using the corresponding absorption spectra-pH data obtained with PARAFAC. The obtained pKa values of LIN, ALK and OXD are 5.70, 8.90 and 6.15, respectively. The results obtained were statistically compared to that of a reported HPLC method, and there was no significant difference between the proposed methods and the reported method regarding both accuracy and precision.

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

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

Science.gov (United States)

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

2018-02-01

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

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

Science.gov (United States)

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

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Penghui Li

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

Unsupervised classification of petroleum Certified Reference Materials and other fuels by chemometric analysis of gas chromatography-mass spectrometry data.

Science.gov (United States)

de Carvalho Rocha, Werickson Fortunato; Schantz, Michele M; Sheen, David A; Chu, Pamela M; Lippa, Katrice A

2017-06-01

As feedstocks transition from conventional oil to unconventional petroleum sources and biomass, it will be necessary to determine whether a particular fuel or fuel blend is suitable for use in engines. Certifying a fuel as safe for use is time-consuming and expensive and must be performed for each new fuel. In principle, suitability of a fuel should be completely determined by its chemical composition. This composition can be probed through use of detailed analytical techniques such as gas chromatography-mass spectroscopy (GC-MS). In traditional analysis, chromatograms would be used to determine the details of the composition. In the approach taken in this paper, the chromatogram is assumed to be entirely representative of the composition of a fuel, and is used directly as the input to an algorithm in order to develop a model that is predictive of a fuel's suitability. When a new fuel is proposed for service, its suitability for any application could then be ascertained by using this model to compare its chromatogram with those of the fuels already known to be suitable for that application. In this paper, we lay the mathematical and informatics groundwork for a predictive model of hydrocarbon properties. The objective of this work was to develop a reliable model for unsupervised classification of the hydrocarbons as a prelude to developing a predictive model of their engine-relevant physical and chemical properties. A set of hydrocarbons including biodiesel fuels, gasoline, highway and marine diesel fuels, and crude oils was collected and GC-MS profiles obtained. These profiles were then analyzed using multi-way principal components analysis (MPCA), principal factors analysis (PARAFAC), and a self-organizing map (SOM), which is a kind of artificial neural network. It was found that, while MPCA and PARAFAC were able to recover descriptive models of the fuels, their linear nature obscured some of the finer physical details due to the widely varying composition of the

Determining the Number of Factors in P-Technique Factor Analysis

Science.gov (United States)

Lo, Lawrence L.; Molenaar, Peter C. M.; Rovine, Michael

2017-01-01

Determining the number of factors is a critical first step in exploratory factor analysis. Although various criteria and methods for determining the number of factors have been evaluated in the usual between-subjects R-technique factor analysis, there is still question of how these methods perform in within-subjects P-technique factor analysis. A…

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.

Comparison between HPSEC-OCD and F-EEMs for assessing DBPs formation in water.

Science.gov (United States)

Hidayah, Euis Nurul; Chou, Yung-Chen; Yeh, Hsuan-Hsien

2017-03-21

In this study, natural organic matter (NOM) in source water, as well as the treated water after coagulation with or without potassium permanganate (KMnO 4 ) preoxidation, was characterized by using high performance size exclusion chromatography with organic carbon detector (HPSEC-OCD) and fluorescence excitation emission matrices (F-EEMs) with parallel factor (PARAFAC) analysis. Bulk parameters, such as dissolved organic carbon (DOC) and ultraviolet light absorbance at 254 nm (UV 254 ), were also analyzed. The results show that KMnO 4 preoxidation caused the breakdown of high molecular weight (MW) organics into low MW organics. All organics, whether those that existed in the source water or those generated by KMnO 4 preoxidation, could be partly removed by coagulation. Combining the derived organic fractions obtained from HPSEC-OCD with peak-fitting and from F-EEMs with PARAFAC on the same sample, humic substances have been specified as the main organic composition. Further, the predictive models for trihalomethanes formation potential (THMFP) and haloacetic acids formation potential (HAAFP) based on organic fractions from HPSEC-OCD have higher accuracy than those based on the components from PARAFAC modeling. These models provide useful tools to specify the organic fractions from HPSEC-OCD and F-EEMs that constitute active precursors towards trihalomethanes (THMs) or haloacetic acids (HAAs) formation in water. Further, by knowing the major organic precursors, it would facilitate choosing the appropriate water treatment process for disinfection by-products (DBPs) control.

Evaluation of CDOM sources and their links with water quality in the lakes of Northeast China using fluorescence spectroscopy

Science.gov (United States)

Zhao, Ying; Song, Kaishan; Wen, Zhidan; Fang, Chong; Shang, Yingxin; Lv, Lili

2017-07-01

The spatial distributions of the fluorescence intensities Fmax for chromophoric dissolved organic matter (CDOM) components, the fluorescence indices (FI370 and FI310) and their correlations with water quality of 19 lakes in the Songhua River Basin (SHRB) across semiarid regions of Northeast China were examined with the data collected in September 2012 and 2015. The 19 lakes were divided into two groups according to EC (threshold value = 800 μS cm-1): fresh water (N = 13) and brackish water lakes (N = 6). The fluorescent characteristics of CDOM in the 19 lakes were investigated using excitation-emission matrix fluorescence spectroscopy (EEM) coupled with parallel factor (PARAFAC) and multivariate analysis. Two humic-like components (C1 and C3), one tryptophan-like component (C2), and one tyrosine-like component (C4) were identified by PARAFAC. The component C4 was not included in subsequent analyses due to the strong scatter in some colloidal water samples from brackish water lakes. The correlations between Fmax for the three EEM-PARAFAC extracted CDOM components C1-C3, the fluorescence indices (FI370 and FI310) and the water quality parameters (i.e., TN, TP, Chl-a, pH, EC, turbidity (Turb) and dissolved organic carbon (DOC)) were determined by redundancy analysis (RDA). The results of RDA analysis showed that spatial variation in land cover, pollution sources, and salinity/EC gradients in water quality affected Fmax for the fluorescent components C1-C3 and the fluorescence indices (FI370 and FI310). Further examination indicated that the CDOM fluorescent components and the fluorescence indices (FI370 and FI310) did not significantly differ (t-test, p > 0.05) in fresh water (N = 13) and brackish water lakes (N = 6). There was a difference in the distribution of the average Fmax for the CDOM fluorescent components between C1 to C3 from agricultural sources and urban wastewater sources in hypereutrophic brackish water lakes. The Fmax for humic-like components C1 and

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

Enhanced Measurements of Chromophoric Dissolved Organic Matter (CDOM) for Water Quality Analysis using a New Simultaneous Absorbance and Fluorescence Instrument

Science.gov (United States)

Gilmore, A. M.

2009-12-01

Water quality, with respect to suspended particles and dissolved organic and inorganic compounds, is now recognized as one of the top global environmental concerns. Contemporary research indicates fluorescence spectral analyses coupled with UV-VIS absorbance assays have the potential, especially when combined and coordinated, to facilitate rapid, robust quantification of a wide range of compounds, including interactions among them. Fluorescence excitation-emission matrices (EEMs) collected over the UV-VIS region provide a wealth of information on chromophoric dissolved organic matter (CDOM). CDOM includes humic and fulvic acid, chlorophyll, petroleum, protein, amino acid, quinone, fertilizer, pesticide, sewage and numerous other compound classes. Analysis of the EEMs using conventional and multivariate techniques, including primarily parallel factor analysis (PARAFAC), provides information about many types of CDOM relevant to carbon cycling and pollution of fresh, marine and drinking water sources. Of critical concern also are the CDOM interactions with, and optical activities of, dissolved inorganic compounds. Many of the inorganic compounds and oxygen demand parameters can be analyzed with a wide range of UV-VIS absorbance assays. The instrument is designed and optimized for high UV throughput and low stray light performance. The sampling optics are optimized for both fluorescence and absorbance detection with the same sample. Both EEM and absorbance measurements implement NIST traceable instrument correction and calibration routines. The fluorescence detection utilizes a high dynamic range CCD coupled to a high-resolution spectrograph while absorbance utilizes diode based detection with a high dynamic range and extremely low-stray light specifications. The CDOM analysis is facilitated by a transfer of the data and model information with the PARAFAC routine. The EEM analysis software package facilitates coordinated correction of and correlation with the

Linkage between the temporal and spatial variability of dissolved organic matter and whole-stream metabolism

Directory of Open Access Journals (Sweden)

S. Halbedel

2013-08-01

Full Text Available Dissolved organic matter (DOM is an important resource for microbes, thus affecting whole-stream metabolism. However, the factors influencing its chemical composition and thereby also its bio-availability are complex and not thoroughly understood. It was hypothesized that whole-stream metabolism is linked to DOM composition and that the coupling of both is influenced by seasonality and different land-use types. We tested this hypothesis in a comparative study on two pristine forestry streams and two non-forestry streams. The investigated streams were located in the Harz Mountains (central Europe, Germany. The metabolic rate was measured with a classical two-station oxygen change technique and the variability of DOM with fluorescence spectroscopy. All streams were clearly net heterotrophic, whereby non-forestry streams showed a higher primary production, which was correlated to irradiance and phosphorus concentration. We detected three CDOM components (C1, C2, C3 using parallel factor (PARAFAC analysis. We compared the excitation and emission maxima of these components with the literature and correlated the PARAFAC components with each other and with fluorescence indices. The correlations suggest that two PARAFAC components are derived from allochthonous sources (C1, C3 and one is derived autochthonously (C2. The chromophoric DOM matrix was dominated by signals of humic-like substances with a highly complex structure, followed by humic-like, fulfic acids, low-molecular-weight substances, and with minor amounts of amino acids and proteins. The ratios of these PARAFAC components (C1 : C2, C1 : C3, C3 : C2 differed with respect to stream types (forestry versus non-forestry. We demonstrated a significant correlation between gross primary production (GPP and signals of autochthonously derived, low-molecular-weight humic-like substances. A positive correlation between P / R (i.e. GPP/daily community respiration and the fluorescence index FI suggests

Detection of Copper (II) and Cadmium (II) binding to dissolved organic matter from macrophyte decomposition by fluorescence excitation-emission matrix spectra combined with parallel factor analysis

International Nuclear Information System (INIS)

Yuan, Dong-hai; Guo, Xu-jing; Wen, Li; He, Lian-sheng; Wang, Jing-gang; Li, Jun-qi

2015-01-01

Fluorescence excitation-emission matrix (EEM) spectra coupled with parallel factor analysis (PARAFAC) was used to characterize dissolved organic matter (DOM) derived from macrophyte decomposition, and to study its complexation with Cu (II) and Cd (II). Both the protein-like and the humic-like components showed a marked quenching effect by Cu (II). Negligible quenching effects were found for Cd (II) by components 1, 5 and 6. The stability constants and the fraction of the binding fluorophores for humic-like components and Cu (II) can be influenced by macrophyte decomposition of various weight gradients in aquatic plants. Macrophyte decomposition within the scope of the appropriate aquatic phytomass can maximize the stability constant of DOM-metal complexes. A large amount of organic matter was introduced into the aquatic environment by macrophyte decomposition, suggesting that the potential risk of DOM as a carrier of heavy metal contamination in macrophytic lakes should not be ignored. - Highlights: • Macrophyte decomposition increases fluorescent DOM components in the upper sediment. • Protein-like components are quenched or enhanced by adding Cu (II) and Cd (II). • Macrophyte decomposition DOM can impact the affinity of Cu (II) and Cd (II). • The log K M and f values showed a marked change due to macrophyte decomposition. • Macrophyte decomposition can maximize the stability constant of DOM-Cu (II) complexes. - Macrophyte decomposition DOM can influence on the binding affinity of metal ions in macrophytic lakes

Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination.

Science.gov (United States)

Zhao, Qibin; Zhang, Liqing; Cichocki, Andrzej

2015-09-01

CANDECOMP/PARAFAC (CP) tensor factorization of incomplete data is a powerful technique for tensor completion through explicitly capturing the multilinear latent factors. The existing CP algorithms require the tensor rank to be manually specified, however, the determination of tensor rank remains a challenging problem especially for CP rank . In addition, existing approaches do not take into account uncertainty information of latent factors, as well as missing entries. To address these issues, we formulate CP factorization using a hierarchical probabilistic model and employ a fully Bayesian treatment by incorporating a sparsity-inducing prior over multiple latent factors and the appropriate hyperpriors over all hyperparameters, resulting in automatic rank determination. To learn the model, we develop an efficient deterministic Bayesian inference algorithm, which scales linearly with data size. Our method is characterized as a tuning parameter-free approach, which can effectively infer underlying multilinear factors with a low-rank constraint, while also providing predictive distributions over missing entries. Extensive simulations on synthetic data illustrate the intrinsic capability of our method to recover the ground-truth of CP rank and prevent the overfitting problem, even when a large amount of entries are missing. Moreover, the results from real-world applications, including image inpainting and facial image synthesis, demonstrate that our method outperforms state-of-the-art approaches for both tensor factorization and tensor completion in terms of predictive performance.

Distinct optical chemistry of dissolved organic matter in urban pond ecosystems

Czech Academy of Sciences Publication Activity Database

McEnroe, N. A.; Williams, C. J.; Xenopoulos, M. A.; Porcal, Petr; Frost, P. C.

2013-01-01

Roč. 8, č. 11 (2013), e80334 E-ISSN 1932-6203 Institutional support: RVO:60077344 Keywords : dissolved organic matter * photodegradation * fluorescence * PARAFAC Subject RIV: DA - Hydrology ; Limnology Impact factor: 3.534, year: 2013

Experimental and theoretical investigation of interaction between bovine serum albumin and the mixture of caffeic acid and salicylic acid as the antioxidants

International Nuclear Information System (INIS)

Benvidi, Ali; Rezaeinasab, Masoud; Gharaghani, Sajjad; Abbasi, Saleheh; Zare, Hamid R.

2017-01-01

In the present work, interaction between bovine serum albumin (BSA) with caffeic acid (CA), salicylic acid (SA) and the mixture of these components were studied by experimental and computational methods In the experimental measurements, differential pulse voltammetry (DPV) and UV–vis spectrophotometry (UV–Vis) were separately used to investigate the nature of interactions. Also, some of the thermodynamics parameters were obtained from these measurements. At the second step, the chemometric methods including multivariate curve resolution–alternating least squares (MCR–ALS) and parallel factor analysis (PARAFAC) were used since the results of the experimental measurements have a strongly overlapping signals. For this purpose, a three-way array was resolved by PARAFAC and a row- and column-wise augmented matrix, which built with DPV and UV–vis sub-matrices, were analyzed using MCR-ALS. The interesting results for stoichiometry and electrochemical behaviors of these components were obtained by using the proposed algorithms. Finally, molecular docking were applied to compare experimentally determined binding parameters with molecular modelling. According to the obtained results an excellent agreement was found between experimental and computational results.

Organic characterisation of cave drip water by LC-OCD and fluorescence analysis

Science.gov (United States)

Rutlidge, Helen; Andersen, Martin S.; Baker, Andy; Chinu, Khorshed J.; Cuthbert, Mark O.; Jex, Catherine N.; Marjo, Christopher E.; Markowska, Monika; Rau, Gabriel C.

2015-10-01

Cathedral Cave, Wellington, Australia, is a natural laboratory for studying water movement and geochemical processes in the unsaturated zone by using artificial irrigation to activate drip sites within the cave. Water sampled from two drip sites activated by irrigations carried out in summer 2014 was analysed for dissolved inorganic ions and fluorescent organic matter. The analysis allowed the development of a conceptual flow path model for each drip site. DOM analysis was further complemented by liquid chromatography with organic carbon detection (LC-OCD), applied for the first time to karst drip waters, allowing the characterisation of six organic matter fractions. The differences in organic matter fractions at each drip site are interpreted as a signature of the proposed flow paths. LC-OCD was also compared with parallel factor analysis (PARAFAC) of the fluorescence and good correlations were observed for high molecular weight organic matter. Strong positive correlations were also observed for high molecular weight matter and Cu and Ni. This is suggestive of colloidal transport of Cu and Ni by organic matter with high molecular weight, while small molecular weight colloids were not efficient transporters. LC-OCD uniquely provides information on non-fluorescent organic matter and can be used to further quantify drip water organic matter composition.

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.

Exploratory Bi-factor Analysis: The Oblique Case

OpenAIRE

Jennrich, Robert L.; Bentler, Peter M.

2011-01-01

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford (1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler (2011) introduced an exploratory form of bi-factor analysis that does not require one to provide an explicit bi-factor structure a priori. They use exploratory factor analysis and a bi-factor rotation criterion designed to produce a rotated loading mat...

Attempt to separate the fluorescence spectra of adrenaline and noradrenaline using chemometrics

DEFF Research Database (Denmark)

Nikolajsen, Rikke P; Hansen, Åse Marie; Bro, R

2000-01-01

An investigation was conducted on whether the fluorescence spectra of the very similar catecholamines adrenaline and noradrenaline could be separated using chemometric methods. The fluorescence landscapes (several excitation and emission spectra were measured) of two data sets with respectively 16...... regression (Unfold-PLSR) on the larger data set and parallel factor analysis (PARAFAC) of the six samples of the smaller set showed that there was no difference between the fluorescence landscapes of adrenaline and noradrenaline. It can be concluded that chemometric separation of adrenaline and noradrenaline...

Factors affecting construction performance: exploratory factor analysis

Science.gov (United States)

Soewin, E.; Chinda, T.

2018-04-01

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

Seasonal Variation in the Quality of Dissolved and Particulate Organic Matter Exchanged Between a Salt Marsh and Its Adjacent Estuary

Science.gov (United States)

Osburn, C. L.; Mikan, M.; Etheridge, J. R.; Burchell, M. R.; Birgand, F.

2015-12-01

Salt marshes are transitional ecosystems between terrestrial and marine environments. Along with mangroves and other vegetated coastal habitats, salt marshes rank among the most productive ecosystems on Earth, with critical global importance for the planet's carbon cycle. Fluorescence was used to examine the quality of dissolved and particulate organic matter (DOM and POM) exchanging between a tidal creek in a created salt marsh and its adjacent estuary in eastern North Carolina, USA. Samples from the creek were collected hourly over four tidal cycles in May, July, August, and October of 2011. Absorbance and fluorescence of chromophoric DOM (CDOM) and of base-extracted POM (BEPOM) served as the tracers for organic matter quality while dissolved organic carbon (DOC) and base-extracted particulate organic carbon (BEPOC) were used to compute fluxes. Fluorescence was modeled using parallel factor analysis (PARAFAC) and principle components analysis (PCA) of the PARAFAC results. Of nine PARAFAC components modeled, we used multiple linear regression to identify tracers for recalcitrant DOM; labile soil-derived source DOM; detrital POM; and planktonic POM. Based on mass balance, recalcitrant DOC export was 86 g C m-2 yr-1 and labile DOC export was 49 g C m-2 yr-1. The marsh also exported 41 g C m-2 yr-1 of detrital terrestrial POC, which likely originated from lands adjacent to the North River estuary. Planktonic POC export from the marsh was 6 g C m-2 yr-1. Using the DOM and POM quality results obtained via fluorescence measurements and scaling up to global salt marsh area, we estimated that the potential release of CO2 from the respiration of salt marsh DOC and POC transported to estuaries could be 11 Tg C yr-1, roughly 4% of the recently estimated CO2 release for marshes and estuaries globally.

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”.

Factor analysis of multivariate data

Digital Repository Service at National Institute of Oceanography (India)

Fernandes, A.A.; Mahadevan, R.

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

Factor analysis and scintigraphy

International Nuclear Information System (INIS)

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

1976-01-01

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

Bootstrap confidence intervals for three-way methods

NARCIS (Netherlands)

Kiers, Henk A.L.

Results from exploratory three-way analysis techniques such as CANDECOMP/PARAFAC and Tucker3 analysis are usually presented without giving insight into uncertainties due to sampling. Here a bootstrap procedure is proposed that produces percentile intervals for all output parameters. Special

New approach for rapid assessment of trophic status of Yellow Sea and East China Sea using easy-to-measure parameters

Science.gov (United States)

Kong, Xianyu; Liu, Yanfang; Jian, Huimin; Su, Rongguo; Yao, Qingzhen; Shi, Xiaoyong

2017-10-01

To realize potential cost savings in coastal monitoring programs and provide timely advice for marine management, there is an urgent need for efficient evaluation tools based on easily measured variables for the rapid and timely assessment of estuarine and offshore eutrophication. In this study, using parallel factor analysis (PARAFAC), principal component analysis (PCA), and discriminant function analysis (DFA) with the trophic index (TRIX) for reference, we developed an approach for rapidly assessing the eutrophication status of coastal waters using easy-to-measure parameters, including chromophoric dissolved organic matter (CDOM), fluorescence excitation-emission matrices, CDOM UV-Vis absorbance, and other water-quality parameters (turbidity, chlorophyll a, and dissolved oxygen). First, we decomposed CDOM excitation-emission matrices (EEMs) by PARAFAC to identify three components. Then, we applied PCA to simplify the complexity of the relationships between the water-quality parameters. Finally, we used the PCA score values as independent variables in DFA to develop a eutrophication assessment model. The developed model yielded classification accuracy rates of 97.1%, 80.5%, 90.3%, and 89.1% for good, moderate, and poor water qualities, and for the overall data sets, respectively. Our results suggest that these easy-to-measure parameters could be used to develop a simple approach for rapid in-situ assessment and monitoring of the eutrophication of estuarine and offshore areas.

Low Complexity Damped Gauss-Newton algorithms for CANDECOMP/PARAFAC

Czech Academy of Sciences Publication Activity Database

Phan, A. H.; Tichavský, Petr; Cichocki, A.

2013-01-01

Roč. 34, č. 1 (2013), s. 126-147 ISSN 0895-4798 R&D Projects: GA MŠk 1M0572; GA ČR GA102/09/1278 Institutional support: RVO:67985556 Keywords : tensor factorization * canonical polyadic decomposition * alternating least squares Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.806, year: 2013 http://library.utia.cas.cz/separaty/2014/SI/tichavsky-0391019.pdf

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.

Exploratory Bi-Factor Analysis: The Oblique Case

Science.gov (United States)

Jennrich, Robert I.; Bentler, Peter M.

2012-01-01

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

Revealing Sources and Distribution Changes of Dissolved Organic Matter (DOM) in Pore Water of Sediment from the Yangtze Estuary

Science.gov (United States)

Wang, Ying; Zhang, Di; Shen, Zhenyao; Feng, Chenghong; Chen, Jing

2013-01-01

Dissolved organic matter (DOM) in sediment pore waters from Yangtze estuary of China based on abundance, UV absorbance, molecular weight distribution and fluorescence were investigated using a combination of various parameters of DOM as well as 3D fluorescence excitation emission matrix spectra (F-EEMS) with the parallel factor and principal component analysis (PARAFAC-PCA). The results indicated that DOM in pore water of Yangtze estuary was very variable which mainly composed of low aromaticity and molecular weight materials. Three humic-like substances (C1, C2, C4) and one protein-like substance (C3) were identified by PARAFAC model. C1, C2 and C4 exhibited same trends and were very similar. The separation of samples on both axes of the PCA showed the difference in DOM properties. C1, C2 and C4 concurrently showed higher positive factor 1 loadings, while C3 showed highly positive factor 2 loadings. The PCA analysis showed a combination contribution of microbial DOM signal and terrestrial DOM signal in the Yangtze estuary. Higher and more variable DOM abundance, aromaticity and molecular weight of surface sediment pore water DOM can be found in the southern nearshore than the other regions primarily due to the influence of frequent and intensive human activities and tributaries inflow in this area. The DOM abundance, aromaticity, molecular weight and fluorescence intensity in core of different depth were relative constant and increased gradually with depth. DOM in core was mainly composed of humic-like material, which was due to higher release of the sedimentary organic material into the porewater during early diagenesis. PMID:24155904

The Infinitesimal Jackknife with Exploratory Factor Analysis

Science.gov (United States)

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

2012-01-01

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

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

International Nuclear Information System (INIS)

Hirota, Kazuyoshi; Ikuno, Yoshiyasu; Nishikimi, Toshio

1986-01-01

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

Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

Science.gov (United States)

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

2014-11-01

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

Lithuanian Population Aging Factors Analysis

Directory of Open Access Journals (Sweden)

Agnė Garlauskaitė

2015-05-01

Full Text Available The aim of this article is to identify the factors that determine aging of Lithuania’s population and to assess the influence of these factors. The article shows Lithuanian population aging factors analysis, which consists of two main parts: the first describes the aging of the population and its characteristics in theoretical terms. Second part is dedicated to the assessment of trends that influence the aging population and demographic factors and also to analyse the determinants of the aging of the population of Lithuania. After analysis it is concluded in the article that the decline in the birth rate and increase in the number of emigrants compared to immigrants have the greatest impact on aging of the population, so in order to show the aging of the population, a lot of attention should be paid to management of these demographic processes.

Factor Economic Analysis at Forestry Enterprises

Directory of Open Access Journals (Sweden)

M.Yu. Chik

2018-03-01

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

Characterization and spacial distribution variability of chromophoric dissolved organic matter (CDOM) in the Yangtze Estuary.

Science.gov (United States)

Wang, Ying; Zhang, Di; Shen, Zhenyao; Chen, Jing; Feng, Chenghong

2014-01-01

The spatial characteristics and the quantity and quality of the chromophoric dissolved organic matter (CDOM) in the Yangtze Estuary, based on the abundance, degree of humification and sources, were studied using 3D fluorescence excitation emission matrix spectra (F-EEMs) with parallel factor and principal component analysis (PARAFAC-PCA). The results indicated that the CDOM abundance decreased and the aromaticity increased from the upstream to the downstream areas of the estuary. Higher CDOM abundance and degrees of humification were observed in the pore water than that in the surface and bottom waters. Two humic-like components (C1 and C3) and one tryptophan-like component (C2) were identified using the PARAFAC model. The separation of the samples by PCA highlighted the differences in the DOM properties. Components C1 and C3 concurrently displayed positive factor 1 loadings with nearly zero factor 2 loadings, while C2 showed highly positive factor 2 loadings. The C1 and C3 were very similar and exhibited a direct relationship with A355 and DOC. The CDOM in the pore water increased along the river to the coastal area, which was mainly influenced by C1 and C3 and was significantly derived from sediment remineralization and deposition from the inflow of the Yangtze River. The CDOM in the surface and bottom waters was dominated by C2, especially in the inflows of multiple tributaries that were affected by intensive anthropogenic activities. The microbial degradation of exogenous wastes from the tributary inputs and shoreside discharges were dominant sources of the CDOM in the surface and bottom waters. Copyright © 2013 Elsevier Ltd. All rights reserved.

Time-resolved laser fluorescence spectroscopy of organic ligands by europium: Fluorescence quenching and lifetime properties

Science.gov (United States)

Nouhi, A.; Hajjoul, H.; Redon, R.; Gagné, J. P.; Mounier, S.

2018-03-01

Time-resolved Laser Fluorescence Spectroscopy (TRLFS) has proved its usefulness in the fields of biophysics, life science and geochemistry to characterize the fluorescence probe molecule with its chemical environment. The purpose of this study is to demonstrate the applicability of this powerful technique combined with Steady-State (S-S) measurements. A multi-mode factor analysis, in particular CP/PARAFAC, was used to analyze the interaction between Europium (Eu) and Humic substances (HSs) extracted from Saint Lawrence Estuary in Canada. The Saint Lawrence system is a semi-enclosed water stream with connections to the Atlantic Ocean and is an excellent natural laboratory. CP/PARAFAC applied to fluorescence S-S data allows introspecting ligands-metal interactions and the one-site 1:1 modeling gives information about the stability constants. From the spectral signatures and decay lifetimes data given by TRLFS, one can deduce the fluorescence quenching which modifies the fluorescence and discuss its mechanisms. Results indicated a relatively strong binding ability between europium and humic substances samples (Log K value varies from 3.38 to 5.08 at pH 7.00). Using the Stern-Volmer plot, it has been concluded that static and dynamic quenching takes places in the case of salicylic acid and europium interaction while for HSs interaction only a static quenching is observed.

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

Fluorescence spectrometric studies on the binding of puerarin to human serum albumin using warfarin, ibuprofen and digitoxin as site markers with the aid of chemometrics

International Nuclear Information System (INIS)

Zhang Guowen; Zhao Nan; Wang Lin

2011-01-01

The interaction of puerarin with human serum albumin (HSA) in pH 7.4 Tris-HCl buffer has been investigated by fluorescence, Fourier transform infrared (FT-IR) and circular dichroism (CD) spectroscopy. The results revealed the presence of static type of quenching mechanism in the binding of puerarin to HSA. The association constants (K a ) between puerarin and HSA were obtained according to Modified Stern-Volmer equation. The calculated thermodynamic parameters indicated that the binding of puerarin to HSA was driven mainly by hydrophobic interaction. The competitive experiments of site markers suggested that the binding site of puerarin to HSA was located in the region of subdomain IIA (sudlow site I). Further, a chemometrics approach, parallel factor analysis (PARAFAC), was applied to resolve the measured three-way synchronous fluorescence spectra data of the competitive interaction between puerarin and warfarin with HSA. The concentration information for the three reaction components, warfarin, puerarin and puerarin-HSA, in the system at equilibrium was obtained simultaneously. The PARAFAC analysis indicated that puerarin in the puerarin-HSA complex was displaced by warfarin, which confirmed the binding site of puerarin to HSA was located in site I. Moreover, the results of CD and FT-IR spectra demonstrated that the secondary structure of HSA was changed in the presence of puerarin. - Highlights: → Puerarin can quench the fluorescence of human serum albumin (HSA). → The HSA fluorescence is quenched by puerarin through a static quenching mechanism. → The binding of puerarin to HSA is driven mainly by hydrophobic interaction. → The parallel factor analysis confirms that puerarin is located in site I of HSA. → The binding of puerarin to HSA induces changes in the secondary structure of HSA.

Automatically identifying scatter in fluorescence data using robust techniques

DEFF Research Database (Denmark)

Engelen, S.; Frosch, Stina; Hubert, M.

2007-01-01

as input data for three different PARAFAC methods. Firstly inserting missing values in the scatter regions are tested, secondly an interpolation of the scatter regions is performed and finally the scatter regions are down-weighted. These results show that the PARAFAC method to choose after scatter...

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

Parallel Factor-Based Model for Two-Dimensional Direction Estimation

Directory of Open Access Journals (Sweden)

Nizar Tayem

2017-01-01

Full Text Available Two-dimensional (2D Direction-of-Arrivals (DOA estimation for elevation and azimuth angles assuming noncoherent, mixture of coherent and noncoherent, and coherent sources using extended three parallel uniform linear arrays (ULAs is proposed. Most of the existing schemes have drawbacks in estimating 2D DOA for multiple narrowband incident sources as follows: use of large number of snapshots, estimation failure problem for elevation and azimuth angles in the range of typical mobile communication, and estimation of coherent sources. Moreover, the DOA estimation for multiple sources requires complex pair-matching methods. The algorithm proposed in this paper is based on first-order data matrix to overcome these problems. The main contributions of the proposed method are as follows: (1 it avoids estimation failure problem using a new antenna configuration and estimates elevation and azimuth angles for coherent sources; (2 it reduces the estimation complexity by constructing Toeplitz data matrices, which are based on a single or few snapshots; (3 it derives parallel factor (PARAFAC model to avoid pair-matching problems between multiple sources. Simulation results demonstrate the effectiveness of the proposed algorithm.

Improved Tensor-Based Singular Spectrum Analysis Based on Single Channel Blind Source Separation Algorithm and Its Application to Fault Diagnosis

Directory of Open Access Journals (Sweden)

Dan Yang

2017-04-01

Full Text Available To solve the problem of multi-fault blind source separation (BSS in the case that the observed signals are under-determined, a novel approach for single channel blind source separation (SCBSS based on the improved tensor-based singular spectrum analysis (TSSA is proposed. As the most natural representation of high-dimensional data, tensor can preserve the intrinsic structure of the data to the maximum extent. Thus, TSSA method can be employed to extract the multi-fault features from the measured single-channel vibration signal. However, SCBSS based on TSSA still has some limitations, mainly including unsatisfactory convergence of TSSA in many cases and the number of source signals is hard to accurately estimate. Therefore, the improved TSSA algorithm based on canonical decomposition and parallel factors (CANDECOMP/PARAFAC weighted optimization, namely CP-WOPT, is proposed in this paper. CP-WOPT algorithm is applied to process the factor matrix using a first-order optimization approach instead of the original least square method in TSSA, so as to improve the convergence of this algorithm. In order to accurately estimate the number of the source signals in BSS, EMD-SVD-BIC (empirical mode decomposition—singular value decomposition—Bayesian information criterion method, instead of the SVD in the conventional TSSA, is introduced. To validate the proposed method, we applied it to the analysis of the numerical simulation signal and the multi-fault rolling bearing signals.

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...

Analysis of mineral phases in coal utilizing factor analysis

International Nuclear Information System (INIS)

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

1982-01-01

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

Uptake of allochthonous dissolved organic matter from soil and salmon in coastal temperate rainforest streams

Science.gov (United States)

Jason B. Fellman; Eran Hood; Richard T. Edwards; Jeremy B. Jones

2009-01-01

Dissolved organic matter (DOM) is an important component of aquatic food webs. We compare the uptake kinetics for NH4-N and different fractions of DOM during soil and salmon leachate additions by evaluating the uptake of organic forms of carbon (DOC) and nitrogen (DON), and proteinaceous DOM, as measured by parallel factor (PARAFAC) modeling of...

Partitioned Alternating Least Squares Technique for Canonical Polyadic Tensor Decomposition

Czech Academy of Sciences Publication Activity Database

Tichavský, Petr; Phan, A. H.; Cichocki, A.

2016-01-01

Roč. 23, č. 7 (2016), s. 993-997 ISSN 1070-9908 R&D Projects: GA ČR(CZ) GA14-13713S Institutional support: RVO:67985556 Keywords : canonical polyadic decomposition * PARAFAC * tensor decomposition Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.528, year: 2016 http://library.utia.cas.cz/separaty/2016/SI/tichavsky-0460710.pdf

Iodine mobilization in groundwater system at Datong basin, China: Evidence from hydrochemistry and fluorescence characteristics

Energy Technology Data Exchange (ETDEWEB)

Li, Junxia; Wang, Yanxin, E-mail: yx.wang@cug.edu.cn; Guo, Wei; Xie, Xianjun; Zhang, Liping; Liu, Yaqing; Kong, Shuqiong

2014-01-01

Characterizing the speciation of iodine in groundwater is essential for understanding its hydrogeochemical behavior in aquifer systems. To quantify the variations in iodine speciation and assess factors controlling the distribution and transformation of iodine, 82 groundwater samples and 1 rain water were collected from the Datong basin, northern China in this study. Factor analysis (FA) and excitation emission matrix with parallel factor analysis (EEM–PARAFAC) were used to clarify the potential relationships among iodine species and other hydrochemical parameters. The iodine concentrations of groundwater range from 6.23 to 1380 μg L{sup −1} with 47% of samples exceeding its drinking water level of 150 μg L{sup −1} as recommended by the Chinese government. 57% of samples have ratios of iodate to total iodine greater than 60%, while iodide as the major species in 22% of the samples. Significant amounts of organic iodine with concentrations higher than 100 μg L{sup −1} were observed in 9 groundwater samples. Redox conditions of groundwater system strongly affect iodine concentration and speciation of inorganic iodine in groundwater, and extremely reducing condition restricts the iodine release from sediments into groundwater. The results of FA show that iodine mobilization in groundwater is related to the nature of dissolved organic matter. EEM-PARAFAC model demonstrates the dominance of terrestrial DOM sources and the presence of microbial activities in groundwater system of the Datong basin. It is proposed that degradation of organic matter and reductive dissolution of iron oxyhydroxides are major hydrogeochemical processes responsible for the mobilization of iodine release and the genesis of organic iodine. - Highlights: • Iodine species in groundwater was studied from Datong basin, northern China. • Weakly alkaline environment favors the accumulation of iodine in groundwater. • Iodate is the major species of iodine in groundwater from Datong

Differences in chewing sounds of dry-crisp snacks by multivariate data analysis

Science.gov (United States)

De Belie, N.; Sivertsvik, M.; De Baerdemaeker, J.

2003-09-01

Chewing sounds of different types of dry-crisp snacks (two types of potato chips, prawn crackers, cornflakes and low calorie snacks from extruded starch) were analysed to assess differences in sound emission patterns. The emitted sounds were recorded by a microphone placed over the ear canal. The first bite and the first subsequent chew were selected from the time signal and a fast Fourier transformation provided the power spectra. Different multivariate analysis techniques were used for classification of the snack groups. This included principal component analysis (PCA) and unfold partial least-squares (PLS) algorithms, as well as multi-way techniques such as three-way PLS, three-way PCA (Tucker3), and parallel factor analysis (PARAFAC) on the first bite and subsequent chew. The models were evaluated by calculating the classification errors and the root mean square error of prediction (RMSEP) for independent validation sets. It appeared that the logarithm of the power spectra obtained from the chewing sounds could be used successfully to distinguish the different snack groups. When different chewers were used, recalibration of the models was necessary. Multi-way models distinguished better between chewing sounds of different snack groups than PCA on bite or chew separately and than unfold PLS. From all three-way models applied, N-PLS with three components showed the best classification capabilities, resulting in classification errors of 14-18%. The major amount of incorrect classifications was due to one type of potato chips that had a very irregular shape, resulting in a wide variation of the emitted sounds.

Logistic regression analysis of risk factors for postoperative recurrence of spinal tumors and analysis of prognostic factors.

Science.gov (United States)

Zhang, Shanyong; Yang, Lili; Peng, Chuangang; Wu, Minfei

2018-02-01

The aim of the present study was to investigate the risk factors for postoperative recurrence of spinal tumors by logistic regression analysis and analysis of prognostic factors. In total, 77 male and 48 female patients with spinal tumor were selected in our hospital from January, 2010 to December, 2015 and divided into the benign (n=76) and malignant groups (n=49). All the patients underwent microsurgical resection of spinal tumors and were reviewed regularly 3 months after operation. The McCormick grading system was used to evaluate the postoperative spinal cord function. Data were subjected to statistical analysis. Of the 125 cases, 63 cases showed improvement after operation, 50 cases were stable, and deterioration was found in 12 cases. The improvement rate of patients with cervical spine tumor, which reached 56.3%, was the highest. Fifty-two cases of sensory disturbance, 34 cases of pain, 30 cases of inability to exercise, 26 cases of ataxia, and 12 cases of sphincter disorders were found after operation. Seventy-two cases (57.6%) underwent total resection, 18 cases (14.4%) received subtotal resection, 23 cases (18.4%) received partial resection, and 12 cases (9.6%) were only treated with biopsy/decompression. Postoperative recurrence was found in 57 cases (45.6%). The mean recurrence time of patients in the malignant group was 27.49±6.09 months, and the mean recurrence time of patients in the benign group was 40.62±4.34. The results were significantly different (Pregression analysis of total resection-related factors showed that total resection should be the preferred treatment for patients with benign tumors, thoracic and lumbosacral tumors, and lower McCormick grade, as well as patients without syringomyelia and intramedullary tumors. Logistic regression analysis of recurrence-related factors revealed that the recurrence rate was relatively higher in patients with malignant, cervical, thoracic and lumbosacral, intramedullary tumors, and higher Mc

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.

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.

Classification analysis of organization factors related to system safety

International Nuclear Information System (INIS)

Liu Huizhen; Zhang Li; Zhang Yuling; Guan Shihua

2009-01-01

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

Time Series Factor Analysis with an Application to Measuring Money

NARCIS (Netherlands)

Gilbert, Paul D.; Meijer, Erik

2005-01-01

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

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.

Fluorescence excitation-emission matrix (EEM) spectroscopy and cavity ring-down (CRD) absorption spectroscopy of oil-contaminated jet fuel using fiber-optic probes.

Science.gov (United States)

Omrani, Hengameh; Barnes, Jack A; Dudelzak, Alexander E; Loock, Hans-Peter; Waechter, Helen

2012-06-21

Excitation emission matrix (EEM) and cavity ring-down (CRD) spectral signatures have been used to detect and quantitatively assess contamination of jet fuels with aero-turbine lubricating oil. The EEM spectrometer has been fiber-coupled to permit in situ measurements of jet turbine oil contamination of jet fuel. Parallel Factor (PARAFAC) analysis as well as Principal Component Analysis and Regression (PCA/PCR) were used to quantify oil contamination in a range from the limit of detection (10 ppm) to 1000 ppm. Fiber-loop cavity ring-down spectroscopy using a pulsed 355 nm laser was used to quantify the oil contamination in the range of 400 ppm to 100,000 ppm. Both methods in combination therefore permit the detection of oil contamination with a linear dynamic range of about 10,000.

TENSOR DECOMPOSITIONS AND SPARSE LOG-LINEAR MODELS

Science.gov (United States)

Johndrow, James E.; Bhattacharya, Anirban; Dunson, David B.

2017-01-01

Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. We derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions. PMID:29332971

Using BMDP and SPSS for a Q factor analysis.

Science.gov (United States)

Tanner, B A; Koning, S M

1980-12-01

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

Exploring Technostress: Results of a Large Sample Factor Analysis

Directory of Open Access Journals (Sweden)

Steponas Jonušauskas

2016-06-01

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

Exploring Technostress: Results of a Large Sample Factor Analysis

OpenAIRE

Jonušauskas, Steponas; Raišienė, Agota Giedrė

2016-01-01

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

Multilinear analysis of Time-Resolved Laser-Induced Fluorescence Spectra of U(VI containing natural water samples

Directory of Open Access Journals (Sweden)

Višňák Jakub

2017-01-01

Full Text Available Natural waters’ uranium level monitoring is of great importance for health and environmental protection. One possible detection method is the Time-Resolved Laser-Induced Fluorescence Spectroscopy (TRLFS, which offers the possibility to distinguish different uranium species. The analytical identification of aqueous uranium species in natural water samples is of distinct importance since individual species differ significantly in sorption properties and mobility in the environment. Samples originate from former uranium mine sites and have been provided by Wismut GmbH, Germany. They have been characterized by total elemental concentrations and TRLFS spectra. Uranium in the samples is supposed to be in form of uranyl(VI complexes mostly with carbonate (CO32− and bicarbonate (HCO3− and to lesser extend with sulphate (SO42− , arsenate (AsO43− , hydroxo (OH− , nitrate (NO3− and other ligands. Presence of alkaline earth metal dications (M = Ca2+ , Mg2+ , Sr2+ will cause most of uranyl to prefer ternary complex species, e.g. Mn(UO2(CO332n-4 (n ∊ {1; 2}. From species quenching the luminescence, Cl− and Fe2+ should be mentioned. Measurement has been done under cryogenic conditions to increase the luminescence signal. Data analysis has been based on Singular Value Decomposition and monoexponential fit of corresponding loadings (for separate TRLFS spectra, the “Factor analysis of Time Series” (FATS method and Parallel Factor Analysis (PARAFAC, all data analysed simultaneously. From individual component spectra, excitation energies T00, uranyl symmetric mode vibrational frequencies ωgs and excitation driven U-Oyl bond elongation ΔR have been determined and compared with quasirelativistic (TDDFT/B3LYP theoretical predictions to cross -check experimental data interpretation.

Multilinear analysis of Time-Resolved Laser-Induced Fluorescence Spectra of U(VI) containing natural water samples

Science.gov (United States)

Višňák, Jakub; Steudtner, Robin; Kassahun, Andrea; Hoth, Nils

2017-09-01

Natural waters' uranium level monitoring is of great importance for health and environmental protection. One possible detection method is the Time-Resolved Laser-Induced Fluorescence Spectroscopy (TRLFS), which offers the possibility to distinguish different uranium species. The analytical identification of aqueous uranium species in natural water samples is of distinct importance since individual species differ significantly in sorption properties and mobility in the environment. Samples originate from former uranium mine sites and have been provided by Wismut GmbH, Germany. They have been characterized by total elemental concentrations and TRLFS spectra. Uranium in the samples is supposed to be in form of uranyl(VI) complexes mostly with carbonate (CO32- ) and bicarbonate (HCO3- ) and to lesser extend with sulphate (SO42- ), arsenate (AsO43- ), hydroxo (OH- ), nitrate (NO3- ) and other ligands. Presence of alkaline earth metal dications (M = Ca2+ , Mg2+ , Sr2+ ) will cause most of uranyl to prefer ternary complex species, e.g. Mn(UO2)(CO3)32n-4 (n ɛ {1; 2}). From species quenching the luminescence, Cl- and Fe2+ should be mentioned. Measurement has been done under cryogenic conditions to increase the luminescence signal. Data analysis has been based on Singular Value Decomposition and monoexponential fit of corresponding loadings (for separate TRLFS spectra, the "Factor analysis of Time Series" (FATS) method) and Parallel Factor Analysis (PARAFAC, all data analysed simultaneously). From individual component spectra, excitation energies T00, uranyl symmetric mode vibrational frequencies ωgs and excitation driven U-Oyl bond elongation ΔR have been determined and compared with quasirelativistic (TD)DFT/B3LYP theoretical predictions to cross -check experimental data interpretation. Note to the reader: Several errors have been produced in the initial version of this article. This new version published on 23 October 2017 contains all the corrections.

[Resolving characteristic of CDOM by excitation-emission matrix spectroscopy combined with parallel factor analysis in the seawater of outer Yangtze Estuary in Autumn in 2010].

Science.gov (United States)

Yan, Li-Hong; Chen, Xue-Jun; Su, Rong-Guo; Han, Xiu-Rong; Zhang, Chuan-Song; Shi, Xiao-Yong

2013-01-01

The distribution and estuarine behavior of fluorescent components of chromophoric dissolved organic matter in the seawater of outer Yangtze Estuary were determined by fluorescence excitation emission matrix spectra combined with parallel factor analysis. Six individual fluorescent components were identified by PARAFAC models, including three terrestrial humic-like components C1 [330 nm/390(430) nm], C2 (390 nm/480 nm), C3 (360 nm/440 nm), marine biological production component C5 (300 nm/400 nm) and protein-like components C4 (290 nm/350 nm) and C6 (275 nm/300 nm). The results indicated that C1, C2, and C3 showed a conservative mixing behavior in the whole estuarine region, especially in high-salinity region. And the fluorescence intensity proportion of C1 and C3 decreased with increase of salinity and fluorescence intensity proportion of C2 kept constant with increase of salinity in the whole estuarine region. While C4 showed conservative mixing behavior in low-salinity region and non-conservative mixing behavior in high-salinity region, and fluorescence intensity proportion of C4 increased with increase of salinity. However, C5 and C6 showed a non-conservative mixing behavior and fluorescence intensity proportion increased with increase of salinity in high-salinity region. Significantly spatial difference was recorded for CDOM absorption coefficient in the coastal region and in the open water areas with the highest value in coastal region and the lowest value in the open water areas. The scope of absorption coefficient and absorption slope was higher in coastal region than that in the open water areas. Significantly positive correlations were found between CDOM absorption coefficient and the fluorescence intensities of C1, C2, C3, and C4, but no significant correlation was found between C5 and C6, suggesting that the river inputs contributed to the coastal areas, while CDOM in the open water areas was affected by terrestrial inputs and phytoplankton degradation.

2D-DOA and Mutual Coupling Estimation in Vehicle Communication System via Conformal Array

Directory of Open Access Journals (Sweden)

Yan Zou

2015-01-01

Full Text Available Many direction-of-arrival (DOA estimation algorithms have been proposed recently. However, the effect of mutual coupling among antenna elements has not been taken into consideration. In this paper, a novel DOA and mutual coupling coefficient estimation algorithm is proposed in intelligent transportation systems (ITS via conformal array. By constructing the spectial mutual coupling matrix (MCM, the effect of mutual coupling can be eliminated via instrumental element method. Then the DOA of incident signals can be estimated based on parallel factor (PARAFAC theory. The PARAFAC model is constructed in cumulant domain using covariance matrices. The mutual coupling coefficients are estimated based on the former DOA estimation and the matrix transformation between MCM and the steering vector. Finally, due to the drawback of the parameter pairing method in Wan et al., 2014, a novel method is given to improve the performance of parameter pairing. The computer simulation verifies the effectiveness of the proposed algorithm.

Factor analysis improves the selection of prescribing indicators

DEFF Research Database (Denmark)

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

2006-01-01

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

Dissolved organic matter dynamics in the oligo/meso-haline zone of wetland-influenced coastal rivers

Science.gov (United States)

Maie, Nagamitsu; Sekiguchi, Satoshi; Watanabe, Akira; Tsutsuki, Kiyoshi; Yamashita, Youhei; Melling, Lulie; Cawley, Kaelin M.; Shima, Eikichi; Jaffé, Rudolf

2014-08-01

Wetlands are key components in the global carbon cycle and export significant amounts of terrestrial carbon to the coastal oceans in the form of dissolved organic carbon (DOC). Conservative behavior along the salinity gradient of DOC and chromophoric dissolved organic matter (CDOM) has often been observed in estuaries from their freshwater end-member (salinity = 0) to the ocean (salinity = 35). While the oligo/meso-haline (salinity DOC and CDOM optical properties determined by UV absorbance at 254 nm (A254) and excitation-emission matrix (EEM) fluorescence coupled with parallel factor analysis (PARAFAC) along the lower salinity range (salinity DOC and A254 was observed, while these parameters showed similar conservative behavior for the third. Three distinct EEM-PARAFAC models established for each of the rivers provided similar spectroscopic characteristics except for some unique fluorescence features observed for the Judan River. The distribution patterns of PARAFAC components suggested that the inputs from plankton and/or submerged aquatic vegetation can be important in the Bekanbeushi River. Further, DOM photo-products formed in the estuarine lake were also found to be transported upstream. In the Harney River, whereas upriver-derived terrestrial humic-like components were mostly distributed conservatively, some of these components were also derived from mangrove inputs in the oligo/meso-haline zone. Interestingly, fluorescence intensities of some terrestrial humic-like components increased with salinity for the Judan River possibly due to changes in the dissociation state of acidic functional groups and/or increase in the fluorescence quantum yield along the salinity gradient. The protein-like and microbial humic-like components were distributed differently between three wetland rivers, implying that interplay between loss to microbial degradation and inputs from diverse sources are different for the three wetland-influenced rivers. The results presented here

A 21 000-year record of fluorescent organic matter markers in the WAIS Divide ice core

Science.gov (United States)

D'Andrilli, Juliana; Foreman, Christine M.; Sigl, Michael; Priscu, John C.; McConnell, Joseph R.

2017-05-01

Englacial ice contains a significant reservoir of organic material (OM), preserving a chronological record of materials from Earth's past. Here, we investigate if OM composition surveys in ice core research can provide paleoecological information on the dynamic nature of our Earth through time. Temporal trends in OM composition from the early Holocene extending back to the Last Glacial Maximum (LGM) of the West Antarctic Ice Sheet Divide (WD) ice core were measured by fluorescence spectroscopy. Multivariate parallel factor (PARAFAC) analysis is widely used to isolate the chemical components that best describe the observed variation across three-dimensional fluorescence spectroscopy (excitation-emission matrices; EEMs) assays. Fluorescent OM markers identified by PARAFAC modeling of the EEMs from the LGM (27.0-18.0 kyr BP; before present 1950) through the last deglaciation (LD; 18.0-11.5 kyr BP), to the mid-Holocene (11.5-6.0 kyr BP) provided evidence of different types of fluorescent OM composition and origin in the WD ice core over 21.0 kyr. Low excitation-emission wavelength fluorescent PARAFAC component one (C1), associated with chemical species similar to simple lignin phenols was the greatest contributor throughout the ice core, suggesting a strong signature of terrestrial OM in all climate periods. The component two (C2) OM marker, encompassed distinct variability in the ice core describing chemical species similar to tannin- and phenylalanine-like material. Component three (C3), associated with humic-like terrestrial material further resistant to biodegradation, was only characteristic of the Holocene, suggesting that more complex organic polymers such as lignins or tannins may be an ecological marker of warmer climates. We suggest that fluorescent OM markers observed during the LGM were the result of greater continental dust loading of lignin precursor (monolignol) material in a drier climate, with lower marine influences when sea ice extent was higher and

Human factors analysis of incident/accident report

International Nuclear Information System (INIS)

Kuroda, Isao

1992-01-01

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

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.

Nominal Performance Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M.A. Wasiolek

2005-01-01

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

Analysis of technological, institutional and socioeconomic factors ...

African Journals Online (AJOL)

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

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

Directory of Open Access Journals (Sweden)

Elena Mazurova

2017-05-01

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

A factor analysis to find critical success factors in retail brand

Directory of Open Access Journals (Sweden)

Naser Azad

2013-03-01

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

Factor analysis for exercise stress radionuclide ventriculography

International Nuclear Information System (INIS)

Hirota, Kazuyoshi; Yasuda, Mitsutaka; Oku, Hisao; Ikuno, Yoshiyasu; Takeuchi, Kazuhide; Takeda, Tadanao; Ochi, Hironobu

1987-01-01

Using factor analysis, a new image processing in exercise stress radionuclide ventriculography, changes in factors associated with exercise were evaluated in 14 patients with angina pectoris or old myocardial infarction. The patients were imaged in the left anterior oblique projection, and three factor images were presented on a color coded scale. Abnormal factors (AF) were observed in 6 patients before exercise, 13 during exercise, and 4 after exercise. In 7 patients, the occurrence of AF was associated with exercise. Five of them became free from AF after exercise. Three patients showing AF before exercise had aggravation of AF during exercise. Overall, the occurrence or aggravation of AF was associated with exercise in ten (71 %) of the patients. The other three patients, however, had disappearance of AF during exercise. In the last patient, none of the AF was observed throughout the study. In view of a high incidence of AF associated with exercise, the factor analysis may have the potential in evaluating cardiac reverse from the viewpoint of left ventricular wall motion abnormality. (Namekawa, K.)

Nominal Performance Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M.A. Wasiolek

2003-07-25

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

Hand function evaluation: a factor analysis study.

Science.gov (United States)

Jarus, T; Poremba, R

1993-05-01

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

Salivary SPECT and factor analysis in Sjoegren's syndrome

International Nuclear Information System (INIS)

Nakamura, T.; Oshiumi, Y.; Yonetsu, K.; Muranaka, T.; Sakai, K.; Kanda, S.; National Fukuoka Central Hospital

1991-01-01

Salivary SPECT and factor analysis in Sjoegren's syndrome were performed in 17 patients and 6 volunteers as controls. The ability of SPECT to detect small differences in the level of uptake can be used to separate glands from background even when uptake is reduced as in the patients with Sjoegren's syndrome. In control and probable Sjoegren's syndrome groups the uptake ratio of the submandibular gland to parotid gland on salivary SPECT (S/P ratio) was less than 1.0. However, in the definite Sjoergren's syndrome group, the ratio was more than 1.0. Moreover, the ratio in all patients with sialectasia, which is characteristic of Sjoegren's syndrome, was more than 1.0. Salivary factor analysis of normal parotid glands showed slowly increasing patterns of uptake and normal submandibular glands had rapidly increasing patterns of uptake. However, in the definite Sjoegren's syndrome group, the factor analysis patterns were altered, with slowly increasing patterns dominating both in the parotid and submandibular glands. These results suggest that the S/P ratio in salivary SPECT and salivary factor analysis provide additional radiologic criteria in diagnosing Sjoegren's syndrome. (orig.)

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

Directory of Open Access Journals (Sweden)

Sumaya Laher

2010-11-01

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

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

Factor Analysis for Clustered Observations.

Science.gov (United States)

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

1992-01-01

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

Analysis and optimization of the TWINKLE factoring device

NARCIS (Netherlands)

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

2000-01-01

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

Nominal Performance Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2004-09-08

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

Nominal Performance Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

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

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…

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…

Identification of noise in linear data sets by factor analysis

International Nuclear Information System (INIS)

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

1982-01-01

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

"Factor Analysis Using ""R"""

Directory of Open Access Journals (Sweden)

A. Alexander Beaujean

2013-02-01

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

Probabilistic inference with noisy-threshold models based on a CP tensor decomposition

Czech Academy of Sciences Publication Activity Database

Vomlel, Jiří; Tichavský, Petr

2014-01-01

Roč. 55, č. 4 (2014), s. 1072-1092 ISSN 0888-613X R&D Projects: GA ČR GA13-20012S; GA ČR GA102/09/1278 Institutional support: RVO:67985556 Keywords : Bayesian networks * Probabilistic inference * Candecomp-Parafac tensor decomposition * Symmetric tensor rank Subject RIV: JD - Computer Applications, Robotics Impact factor: 2.451, year: 2014 http://library.utia.cas.cz/separaty/2014/MTR/vomlel-0427059.pdf

Dissolved organic matter dynamics in surface waters affected by oil spill pollution: Results from the Serious Game exercise

Science.gov (United States)

Gonnelli, M.; Galletti, Y.; Marchetti, E.; Mercadante, L.; Retelletti Brogi, S.; Ribotti, A.; Sorgente, R.; Vestri, S.; Santinelli, C.

2016-11-01

Dissolved organic carbon (DOC), chromophoric and fluorescent dissolved organic matter (CDOM and FDOM, respectively) surface distribution was studied during the Serious Game exercise carried out in the Eastern Ligurian Sea, where an oil spill was localized by using satellite images and models. This paper reports the first DOC, CDOM and FDOM data for this area together with an evaluation of fluorescence as a fast and inexpensive tool for early oil spill detection in marine waters. The samples collected in the oil spill showed a fluorescence intensity markedly higher ( 5 fold) than all the other samples. The excitation-emission matrixes, coupled with parallel factor analysis (PARAFAC), allowed for the identification in the FDOM pool of a mixture of polycyclic aromatic hydrocarbons, humic-like and protein-like fluorophores.

Simultaneous Fault Detection and Sensor Selection for Condition Monitoring of Wind Turbines

Directory of Open Access Journals (Sweden)

Wenna Zhang

2016-04-01

Full Text Available Data collected from the supervisory control and data acquisition (SCADA system are used widely in wind farms to obtain operation and performance information about wind turbines. The paper presents a three-way model by means of parallel factor analysis (PARAFAC for wind turbine fault detection and sensor selection, and evaluates the method with SCADA data obtained from an operational farm. The main characteristic of this new approach is that it can be used to simultaneously explore measurement sample profiles and sensors profiles to avoid discarding potentially relevant information for feature extraction. With K-means clustering method, the measurement data indicating normal, fault and alarm conditions of the wind turbines can be identified, and the sensor array can be optimised for effective condition monitoring.

The Recoverability of P-Technique Factor Analysis

Science.gov (United States)

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

2009-01-01

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

Human factor analysis and preventive countermeasures in nuclear power plant

International Nuclear Information System (INIS)

Li Ye

2010-01-01

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

Effects of sampling methods on the quantity and quality of dissolved organic matter in sediment pore waters as revealed by absorption and fluorescence spectroscopy.

Science.gov (United States)

Chen, Meilian; Lee, Jong-Hyeon; Hur, Jin

2015-10-01

Despite literature evidence suggesting the importance of sampling methods on the properties of sediment pore waters, their effects on the dissolved organic matter (PW-DOM) have been unexplored to date. Here, we compared the effects of two commonly used sampling methods (i.e., centrifuge and Rhizon sampler) on the characteristics of PW-DOM for the first time. The bulk dissolved organic carbon (DOC), ultraviolet-visible (UV-Vis) absorption, and excitation-emission matrixes coupled with parallel factor analysis (EEM-PARAFAC) of the PW-DOM samples were compared for the two sampling methods with the sediments from minimal to severely contaminated sites. The centrifuged samples were found to have higher average values of DOC, UV absorption, and protein-like EEM-PARAFAC components. The samples collected with the Rhizon sampler, however, exhibited generally more humified characteristics than the centrifuged ones, implying a preferential collection of PW-DOM with respect to the sampling methods. Furthermore, the differences between the two sampling methods seem more pronounced in relatively more polluted sites. Our observations were possibly explained by either the filtration effect resulting from the smaller pore size of the Rhizon sampler or the desorption of DOM molecules loosely bound to minerals during centrifugation, or both. Our study suggests that consistent use of one sampling method is crucial for PW-DOM studies and also that caution should be taken in the comparison of data collected with different sampling methods.

Integrating human factors into process hazard analysis

International Nuclear Information System (INIS)

Kariuki, S.G.; Loewe, K.

2007-01-01

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

Tensor Deflation for CANDECOMP/PARAFAC - Part I: Alternating Subspace Update Algorithm

Czech Academy of Sciences Publication Activity Database

Phan, A. H.; Tichavský, Petr; Cichocki, A.

2015-01-01

Roč. 63, č. 22 (2015), s. 5924-5938 ISSN 1053-587X R&D Projects: GA ČR(CZ) GA14-13713S Institutional support: RVO:67985556 Keywords : Canonical polyadic decomposition * tensor deflation * tensor tracking Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.624, year: 2015 http://library.utia.cas.cz/separaty/2015/SI/tichavsky-0448255.pdf

Applications of factor analysis to electron and ion beam surface techniques

International Nuclear Information System (INIS)

Solomon, J.S.

1987-01-01

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

An SPSSR -Menu for Ordinal Factor Analysis

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.

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). Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Multiway modeling and analysis in stem cell systems biology

Directory of Open Access Journals (Sweden)

Vandenberg Scott L

2008-07-01

Full Text Available Abstract Background Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.. A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. Results We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a

Disruptive Event Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M. A. Wasiolek

2003-07-21

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

Disruptive Event Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M. A. Wasiolek

2003-01-01

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

A replication of a factor analysis of motivations for trapping

Science.gov (United States)

Schroeder, Susan; Fulton, David C.

2015-01-01

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

A human factor analysis of a radiotherapy accident

International Nuclear Information System (INIS)

Thellier, S.

2009-01-01

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

Cramér-Rao-Induced Bounds for CANDECOMP/ PARAFAC Tensor Decomposition

Czech Academy of Sciences Publication Activity Database

Tichavský, Petr; Phan, A. H.; Koldovský, Zbyněk

2013-01-01

Roč. 61, č. 8 (2013), s. 1986-1997 ISSN 1053-587X R&D Projects: GA ČR GA102/09/1278 Grant - others:GA ČR(CZ) GAP103/11/1947 Program:GA Institutional support: RVO:67985556 Keywords : Canonical polyadic decomposition * multilinear models * stability Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 3.198, year: 2013 http://library.utia.cas.cz/separaty/2013/SI/tichavsky-0391438.pdf

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale

Science.gov (United States)

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

2017-01-01

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

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.

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

Science.gov (United States)

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

2017-01-01

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

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

African Journals Online (AJOL)

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

Analysis of Economic Factors Affecting Stock Market

OpenAIRE

Xie, Linyin

2010-01-01

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

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

Directory of Open Access Journals (Sweden)

Valentina V. Tarasova

2016-12-01

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

Modification and analysis of engineering hot spot factor of HFETR

International Nuclear Information System (INIS)

Hu Yuechun; Deng Caiyu; Li Haitao; Xu Taozhong; Mo Zhengyu

2014-01-01

This paper presents the modification and analysis of engineering hot spot factors of HFETR. The new factors are applied in the fuel temperature analysis and the estimated value of the safety allowable operating power of HFETR. The result shows the maximum cladding temperature of the fuel is lower when the new factor are in utilization, and the safety allowable operating power of HFETR if higher, thus providing the economical efficiency of HFETR. (authors)

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.

Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

Science.gov (United States)

Stankov, L

1979-07-01

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

ANALYSIS OF THE FACTORS AFFECTING THE AVERAGE

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.

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

Science.gov (United States)

Bunketorp Käll, Lina

2014-03-01

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

Evaluation of Parallel Analysis Methods for Determining the Number of Factors

Science.gov (United States)

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

2010-01-01

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

Disruptive Event Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2004-09-08

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

Disruptive Event Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

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

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

OpenAIRE

Gideon P. de Bruin

2000-01-01

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

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming

2017-05-18

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

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

International Nuclear Information System (INIS)

Fladischer, Stefanie; Grogger, Werner

2014-01-01

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

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

Science.gov (United States)

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

2017-12-01

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

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

International Nuclear Information System (INIS)

Chen Chengzhong; Lin Zhenshan

2008-01-01

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

Analysis of related risk factors for pancreatic fistula after pancreaticoduodenectomy

Directory of Open Access Journals (Sweden)

Qi-Song Yu

2016-08-01

Full Text Available 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.

Space time frequency (STF) code tensor for the characterization of the epileptic preictal stage.

Science.gov (United States)

Direito, Bruno; Teixeira, César; Ribeiro, Bernardete; Castelo-Branco, Miguel; Dourado, António

2012-01-01

We evaluate the ability of multiway models to characterize the epileptic preictal period. The understanding of the characteristics of the period prior to the seizure onset is a decisive step towards the development of seizure prediction frameworks. Multiway models of EEG segments already demonstrated that hidden structures may be unveiled using tensor decomposition techniques. We propose a novel approach using a multiway model, Parallel Factor Analysis (PARAFAC), to identify spatial, temporal and spectral signatures of the preictal period. The results obtained, from a dataset of 4 patients, with a total of 30 seizures, suggest that a common structure may be involved in seizure generation. Furthermore, the spatial signature may be related to the ictal onset region and that determined frequency sub-bands may be more relevant in preictal stages.

Two Expectation-Maximization Algorithms for Boolean Factor Analysis

Czech Academy of Sciences Publication Activity Database

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

2014-01-01

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

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

Science.gov (United States)

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

2018-04-01

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

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.

Study of influencing factors to chromophoric dissolved organic matter absorption properties from fluorescence features in Taihu lake in autumn

Directory of Open Access Journals (Sweden)

Chuang-Chun Huang

2013-04-01

Full Text Available In order to identify the components of chromophoric dissolved organic matter (CDOM, confirm the influence of components to the absorption coefficient of CDOM (aCDOM, and estimate aCDOM from fluorescence spectra, fluorescence and optical measurements of CDOM were carried out in November 2008. The results indicate that, the primary component of CDOM is humic-like. The secondary component is tryptophan-like, which is the product of phytoplankton and aquatic debris rather than the wastewater treatment drainaged from city. In this study, six fluorophores with multiple excitation-emission matrices (EEMs peaks (A, B, C, N, M, T were identified according to the parallel factor analysis (PARAFAC. The average contribution of each component to the CDOM is 19.93, 18.82, 16.88, 16.39, 12.26, and 15.72%, respectively. Red Shifted phenomenon will happen with the increase of fluorescence intensity for ultraviolet and terrestrially humic-like. Conversely, marine humic-like will appear Reverse Red Shifted with the increase of fluorescence intensity. The primary contributor to the shoulder value of CDOM’s absorption coefficient at 275 nm is phytoplankton productivity, followed by marine humic-like. The main contributors to the shoulder shape are UV humic-like and phytoplankton productivity, followed by marine humic-like and tryptophan-like. A strong correlation between CDOM absorption and fluorescence intensity at emission wavelength of 424 nm and excitation wavelength ranging from 280 to 360 nm was found. The absorption coefficient can be retrieved successfully from the same excitation wavelength’s fluorescence intensity by an exponential model.

Multivariate factor analysis of Girgentana goat milk composition

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Pietro Giaccone

2010-01-01

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

Confirmatory factor analysis using Microsoft Excel.

Science.gov (United States)

Miles, Jeremy N V

2005-11-01

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

Boolean Factor Analysis by Attractor Neural Network

Czech Academy of Sciences Publication Activity Database

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

2007-01-01

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

MOOC Success Factors: Proposal of an Analysis Framework

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Margarida M. Marques

2017-10-01

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

DISRUPTIVE EVENT BIOSPHERE DOSE CONVERSION FACTOR ANALYSIS

International Nuclear Information System (INIS)

M.A. Wasiolek

2005-01-01

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

Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

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Hong Xue

2018-01-01

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

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

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Batoul Aminjafari

2012-08-01

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

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

Science.gov (United States)

Molenaar, Peter C M

2010-05-01

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

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

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Bruce Weaver

2014-09-01

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

Likelihood-based Dynamic Factor Analysis for Measurement and Forecasting

NARCIS (Netherlands)

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

2015-01-01

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

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

International Nuclear Information System (INIS)

Goodman, D.

1987-01-01

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

Sustainable Manufacturing Practices in Malaysian Automotive Industry: Confirmatory Factor Analysis

OpenAIRE

Habidin, Nurul Fadly; Zubir, Anis Fadzlin Mohd; Fuz, Nursyazwani Mohd; Latip, Nor Azrin Md; Azman, Mohamed Nor Azhari

2015-01-01

Sustainable manufacturing practices (SMPs) have received enormous attention in current years as an effective solution to support the continuous growth and expansion of the automotive manufacturing industry. This reported study was conducted to examine confirmatory factor analysis for SMP such as manufacturing process, supply chain management, social responsibility, and environmental management based on automotive manufacturing industry. The results of confirmatory factor analysis show that fo...

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,…

Confirmatory factor analysis applied to the Force Concept Inventory

Science.gov (United States)

Eaton, Philip; Willoughby, Shannon D.

2018-06-01

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

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

Science.gov (United States)

Wada, Yoshihisa; Tsuji, Hiroshi

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

Workplace Innovation: Exploratory and Confirmatory Factor Analysis for Construct Validation

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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.

Analysis of IFR driver fuel hot channel factors

International Nuclear Information System (INIS)

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

1994-01-01

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

Analysis of IFR driver fuel hot channel factors

International Nuclear Information System (INIS)

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

2004-01-01

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

Economic Analysis of Factors Affecting Technical Efficiency of ...

African Journals Online (AJOL)

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

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

Science.gov (United States)

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

2017-01-01

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

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

Science.gov (United States)

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

2015-02-01

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

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

Science.gov (United States)

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

2017-12-01

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

A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis

Science.gov (United States)

Edwards, Michael C.

2010-01-01

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

EMPLOYMENT LEVEL ANALYSIS FROM THE DETERMINANT FACTORS PERSPECTIVE

Directory of Open Access Journals (Sweden)

Elena Diana ŞERB

2016-02-01

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

Factor analysis of the contextual fine motor questionnaire in children.

Science.gov (United States)

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

2014-02-01

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

Correction factor for hair analysis by PIXE

International Nuclear Information System (INIS)

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

1980-01-01

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

Correction factor for hair analysis by PIXE

International Nuclear Information System (INIS)

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

1979-06-01

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

Investigating product development strategy in beverage industry using factor analysis

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.

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.

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...

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.

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

Directory of Open Access Journals (Sweden)

Endang Brotojoyo

2018-03-01

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

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.

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

Science.gov (United States)

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

1997-01-01

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

Factors that Affect Poverty Areas in North Sumatera Using Discriminant Analysis

Science.gov (United States)

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

2018-04-01

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

Seismic analysis response factors and design margins of piping systems

International Nuclear Information System (INIS)

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

1985-01-01

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

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

Science.gov (United States)

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

2018-04-01

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

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

Science.gov (United States)

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

2015-01-01

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

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

International Nuclear Information System (INIS)

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

1985-01-01

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

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.

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.

The scientific use of factor analysis in behavioral and life sciences

National Research Council Canada - National Science Library

Cattell, Raymond Bernard

1978-01-01

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

Bayes factor design analysis: Planning for compelling evidence.

Science.gov (United States)

Schönbrodt, Felix D; Wagenmakers, Eric-Jan

2018-02-01

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

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

OpenAIRE

Asgharian, Hossein

2004-01-01

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

Front-face fluorescence spectroscopy combined with second-order multivariate algorithms for the quantification of polyphenols in red wine samples.

Science.gov (United States)

Cabrera-Bañegil, Manuel; Hurtado-Sánchez, María Del Carmen; Galeano-Díaz, Teresa; Durán-Merás, Isabel

2017-04-01

The potential of front-face fluorescence spectroscopy combined with second-order chemometric methods was investigated for the quantification of the main polyphenols present in wine samples. Parallel factor analysis (PARAFAC) and unfolded-partial least squares coupled to residual bilinearization (U-PLS/RBL) were assessed for the quantification of catechin, epicatechin, quercetin, resveratrol, caffeic acid, gallic acid, p-coumaric acid, and vanillic acid in red wines. Excitation-emission matrices of different red wine samples, without pretreatment, were obtained in front-face mode, recording emission between 290 and 450 nm, exciting between 240 and 290 nm, for the analysis of epicatechin, catechin, caffeic acid, gallic acid, and vanillic acid; and excitation and emission between 300-360 and 330-400nm, respectively, for the analysis of resveratrol. U-PLS/RBL algorithm provided the best results and this methodology was validated by an optimized liquid chromatographic coupled to diode array and fluorimetric detectors procedure, obtaining a very good correlation for vanillic acid, caffeic acid, epicatechin and resveratrol. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

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

Science.gov (United States)

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

2016-02-01

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

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

OpenAIRE

Jasińska, Elżbieta; Preweda, Edward

2006-01-01

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

Liquidity indicator for the Croatian economy – Factor analysis approach

Directory of Open Access Journals (Sweden)

Mirjana Čižmešija

2014-12-01

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

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

Institute of Scientific and Technical Information of China (English)

2011-01-01

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

Absorption correction factor in X-ray fluorescent quantitative analysis

International Nuclear Information System (INIS)

Pimjun, S.

1994-01-01

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

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

International Nuclear Information System (INIS)

El-Sayed, A.A.

2005-01-01

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

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

African Journals Online (AJOL)

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

Risk factor analysis of equine strongyle resistance to anthelmintics

Directory of Open Access Journals (Sweden)

G. Sallé

2017-12-01

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

Comparing the Spectroscopic and Molecular Characteristics of Different Dissolved Organic Matter Fractions Isolated by Hydrophobic and Anionic Exchange Resins Using Fluorescence Spectroscopy and FT-ICR-MS

Directory of Open Access Journals (Sweden)

Morgane Derrien

2017-07-01

Full Text Available Despite the environmental significance of dissolved organic matter (DOM, characterizing DOM is still challenging due to its structural complexity and heterogeneity. In this study, three different chemical fractions, including hydrophobic acid (HPOA, transphilic acid (TPIA, and hydrophilic neutral and base (HPIN/B fractions, were separated from bulk aquatic DOM samples, and their spectral features and the chemical composition at the molecular level were compared using both fluorescence excitation emission matrix-parallel factor analysis (EEM-PARAFAC and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS. The HPIN/B fraction was distinguished from the two acidic fractions (i.e., HPOA and TPIA by the EEM-PARAFAC, while the TPIA fraction was discriminated by using the molecular parameters derived from the FT-ICR MS analyses. Statistical comparison suggests that the spectral dissimilarity among the three chemical fractions might result from the acido-basic properties of DOM samples, while the differences in molecular composition were more likely to be affected by the hydrophobicity of the DOM fractions. The non-metric multidimensional scaling map further revealed that the HPOA was the most heterogeneous among the three fractions. The number of overlapping formulas among the three chemical fractions constituted only <5% of all identified formulas, and those between two different fractions ranged from 2.0% to 24.1%, implying relatively homogeneous properties of the individual chemical fractions with respect to molecular composition. Although employing chemical fractionation achieved a lowering of the DOM heterogeneity, prevalent signatures of either acido-basic property or the hydrophobic nature of DOM on the characteristics of three chemical isolated fractions were not found for this study.

Tensor hypercontraction. II. Least-squares renormalization

Science.gov (United States)

Parrish, Robert M.; Hohenstein, Edward G.; Martínez, Todd J.; Sherrill, C. David

2012-12-01

The least-squares tensor hypercontraction (LS-THC) representation for the electron repulsion integral (ERI) tensor is presented. Recently, we developed the generic tensor hypercontraction (THC) ansatz, which represents the fourth-order ERI tensor as a product of five second-order tensors [E. G. Hohenstein, R. M. Parrish, and T. J. Martínez, J. Chem. Phys. 137, 044103 (2012)], 10.1063/1.4732310. Our initial algorithm for the generation of the THC factors involved a two-sided invocation of overlap-metric density fitting, followed by a PARAFAC decomposition, and is denoted PARAFAC tensor hypercontraction (PF-THC). LS-THC supersedes PF-THC by producing the THC factors through a least-squares renormalization of a spatial quadrature over the otherwise singular 1/r12 operator. Remarkably, an analytical and simple formula for the LS-THC factors exists. Using this formula, the factors may be generated with O(N^5) effort if exact integrals are decomposed, or O(N^4) effort if the decomposition is applied to density-fitted integrals, using any choice of density fitting metric. The accuracy of LS-THC is explored for a range of systems using both conventional and density-fitted integrals in the context of MP2. The grid fitting error is found to be negligible even for extremely sparse spatial quadrature grids. For the case of density-fitted integrals, the additional error incurred by the grid fitting step is generally markedly smaller than the underlying Coulomb-metric density fitting error. The present results, coupled with our previously published factorizations of MP2 and MP3, provide an efficient, robust O(N^4) approach to both methods. Moreover, LS-THC is generally applicable to many other methods in quantum chemistry.

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

DEFF Research Database (Denmark)

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

2011-01-01

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

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…

Clinicopathological Analysis of Factors Related to Colorectal Tumor Perforation

OpenAIRE

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

2015-01-01

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

An Analysis of Construction Accident Factors Based on Bayesian Network

OpenAIRE

Yunsheng Zhao; Jinyong Pei

2013-01-01

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

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

Science.gov (United States)

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

2018-04-28

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

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

Science.gov (United States)

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

2015-01-01

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

Exploratory Factor Analysis of SCL90-R Symptoms Relevant to Psychosis

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Javad Amini

2011-10-01

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

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

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Košir Katja

2013-09-01

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

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

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Zuzana Toufarová

2007-01-01

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

48 CFR 1615.404-70 - Profit analysis factors.

Science.gov (United States)

2010-10-01

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

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

Science.gov (United States)

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

1988-04-01

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

Worry About Caregiving Performance: A Confirmatory Factor Analysis

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Ruijie Li

2018-03-01

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

Development and validation of mathematical methods for the evaluation of spectroscopic data of uranyl (VI) hxdrolysis; Entwicklung und Validierung mathematischer Methoden zur Auswertung spektroskopischer Daten der Uranyl(VI)-Hydrolyse

Energy Technology Data Exchange (ETDEWEB)

Drobot, Bjoern

2016-08-18

The availability of metals in the biosphere is determined by the chemical state. Spectroscopic methods are appropriate for the analysis of speciation - the problem is the data processing. In the frame of the thesis the use of the software PARAFAC was used to analyze the excitation spectra of uranyl (VI) hydrolysis. It was shown that modern mathematical tools are essential for the data processing. The range of applicability covers deprotonation processes up to complex biochemical processes.

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

OpenAIRE

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

1989-01-01

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

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

Science.gov (United States)

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

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

An analysis of main factors in electron beam flue gas purification

International Nuclear Information System (INIS)

Zhang Ming; Xu Guang

2003-01-01

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

Kernel parameter dependence in spatial factor analysis

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2010-01-01

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

Decomposition and classification of electroencephalography data

DEFF Research Database (Denmark)

Frølich, Laura

. To enforce orthonormality of projection matrices, objective functions quantifying class discrimination were optimised on a cross-product of Stiefel (orthonormal matrix) manifolds. Supervised feature extraction outperformed unsupervised methods, but the choice of supervised method mattered less. We suggested......_MARC was also used to inspect effects of artefacts on motor imagery based Brain-Computer Interfaces (BCIs) in two studies, where removing artefactual ICs had little performance impact. Finally, we investigated multi-linear classification on single trials of EEG data, proposing a rigorous optimisation approach...... completions of methods to include both PARAFAC and Tucker structures. The two structures provided similar performances, making the more interpretable PARAFAC models appealing....

Biosphere dose conversion Factor Importance and Sensitivity Analysis

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

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

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

Directory of Open Access Journals (Sweden)

Hee-Ju Kim, PhD, RN

2008-03-01

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

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

Science.gov (United States)

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

2015-06-12

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

Using Factor Analysis to Identify Topic Preferences Within MBA Courses

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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.

A methodology to incorporate organizational factors into human reliability analysis

International Nuclear Information System (INIS)

Li Pengcheng; Chen Guohua; Zhang Li; Xiao Dongsheng

2010-01-01

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

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

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Hesse Morten

2005-05-01

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

Characterising Event-Based DOM Inputs to an Urban Watershed

Science.gov (United States)

Croghan, D.; Bradley, C.; Hannah, D. M.; Van Loon, A.; Sadler, J. P.

2017-12-01

Dissolved Organic Matter (DOM) composition in urban streams is dominated by terrestrial inputs after rainfall events. Urban streams have particularly strong terrestrial-riverine connections due to direct input from terrestrial drainage systems. Event driven DOM inputs can have substantial adverse effects on water quality. Despite this, DOM from important catchment sources such as road drains and Combined Sewage Overflows (CSO's) remains poorly characterised within urban watersheds. We studied DOM sources within an urbanised, headwater watershed in Birmingham, UK. Samples from terrestrial sources (roads, roofs and a CSO), were collected manually after the onset of rainfall events of varying magnitude, and again within 24-hrs of the event ending. Terrestrial samples were analysed for fluorescence, absorbance and Dissolved Organic Carbon (DOC) concentration. Fluorescence and absorbance indices were calculated, and Parallel Factor Analysis (PARAFAC) was undertaken to aid sample characterization. Substantial differences in fluorescence, absorbance, and DOC were observed between source types. PARAFAC-derived components linked to organic pollutants were generally highest within road derived samples, whilst humic-like components tended to be highest within roof samples. Samples taken from the CSO generally contained low fluorescence, however this likely represents a dilution effect. Variation within source groups was particularly high, and local land use seemed to be the driving factor for road and roof drain DOM character and DOC quantity. Furthermore, high variation in fluorescence, absorbance and DOC was apparent between all sources depending on event type. Drier antecedent conditions in particular were linked to greater presence of terrestrially-derived components and higher DOC content. Our study indicates that high variations in DOM character occur between source types, and over small spatial scales. Road drains located on main roads appear to contain the poorest

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…

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

Science.gov (United States)

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

2014-07-01

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

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

Science.gov (United States)

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

2015-09-01

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

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

International Nuclear Information System (INIS)

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

2006-01-01

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

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

Directory of Open Access Journals (Sweden)

Farahman Farrokhi

2011-06-01

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

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

Science.gov (United States)

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

2011-01-01

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

Factors Affecting Green Residential Building Development: Social Network Analysis

Directory of Open Access Journals (Sweden)

Xiaodong Yang

2018-05-01

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

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…

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

Directory of Open Access Journals (Sweden)

Pavel Aleksandrovich Kislyakov

2015-10-01

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

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.

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming; Ombao, Hernando; Salleh, Sh-Hussain

2017-01-01

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive

Comparing 3 dietary pattern methods--cluster analysis, factor analysis, and index analysis--With colorectal cancer risk: The NIH-AARP Diet and Health Study.

Science.gov (United States)

Reedy, Jill; Wirfält, Elisabet; Flood, Andrew; Mitrou, Panagiota N; Krebs-Smith, Susan M; Kipnis, Victor; Midthune, Douglas; Leitzmann, Michael; Hollenbeck, Albert; Schatzkin, Arthur; Subar, Amy F

2010-02-15

The authors compared dietary pattern methods-cluster analysis, factor analysis, and index analysis-with colorectal cancer risk in the National Institutes of Health (NIH)-AARP Diet and Health Study (n = 492,306). Data from a 124-item food frequency questionnaire (1995-1996) were used to identify 4 clusters for men (3 clusters for women), 3 factors, and 4 indexes. Comparisons were made with adjusted relative risks and 95% confidence intervals, distributions of individuals in clusters by quintile of factor and index scores, and health behavior characteristics. During 5 years of follow-up through 2000, 3,110 colorectal cancer cases were ascertained. In men, the vegetables and fruits cluster, the fruits and vegetables factor, the fat-reduced/diet foods factor, and all indexes were associated with reduced risk; the meat and potatoes factor was associated with increased risk. In women, reduced risk was found with the Healthy Eating Index-2005 and increased risk with the meat and potatoes factor. For men, beneficial health characteristics were seen with all fruit/vegetable patterns, diet foods patterns, and indexes, while poorer health characteristics were found with meat patterns. For women, findings were similar except that poorer health characteristics were seen with diet foods patterns. Similarities were found across methods, suggesting basic qualities of healthy diets. Nonetheless, findings vary because each method answers a different question.

Scale-Free Nonparametric Factor Analysis: A User-Friendly Introduction with Concrete Heuristic Examples.

Science.gov (United States)

Mittag, Kathleen Cage

Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that…

Inference algorithms and learning theory for Bayesian sparse factor analysis

International Nuclear Information System (INIS)

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

2009-01-01

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

Inference algorithms and learning theory for Bayesian sparse factor analysis

Energy Technology Data Exchange (ETDEWEB)

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

2009-12-01

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

the use of the dynamic magnification factor in the dynamic analysis

African Journals Online (AJOL)

Uncle Greg 4 Real

bridges and some country's codes of practice made specifications in respect of the dynamic magnification factor for the analysis and design of various types of structures subjected to ... span. For example the United kingdom code. [10] presented dynamic magnification factors, related ... For SDOF (Single Degree of Freedom).

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

Science.gov (United States)

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

2018-03-22

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

Qualitative analysis of factors leading to clinical incidents.

Science.gov (United States)

Smith, Matthew D; Birch, Julian D; Renshaw, Mark; Ottewill, Melanie

2013-01-01

The purpose of this paper is to evaluate the common themes leading or contributing to clinical incidents in a UK teaching hospital. A root-cause analysis was conducted on patient safety incidents. Commonly occurring root causes and contributing factors were collected and correlated with incident timing and severity. In total, 65 root-cause analyses were reviewed, highlighting 202 factors implicated in the clinical incidents and 69 categories were identified. The 14 most commonly occurring causes (encountered in four incidents or more) were examined as a key-root or contributory cause. Incident timing was also analysed; common factors were encountered more frequently during out-hours--occurring as contributory rather than a key-root cause. In total, 14 commonly occurring factors were identified to direct interventions that could prevent many clinical incidents. From these, an "Organisational Safety Checklist" was developed to involve departmental level clinicians to monitor practice. This study demonstrates that comprehensively investigating incidents highlights common factors that can be addressed at a local level. Resilience against clinical incidents is low during out-of-hours periods, where factors such as lower staffing levels and poor service provision allows problems to escalate and become clinical incidents, which adds to the literature regarding out-of-hours care provision and should prove useful to those organising hospital services at departmental and management levels.

The mathematical pathogenetic factors analysis of acute inflammatory diseases development of bronchopulmonary system among infants

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G. O. Lezhenko

2017-10-01

Full Text Available The purpose. To study the factor structure and to establish the associative interaction of pathogenetic links of acute diseases development of the bronchopulmonary system in infants.Materials and methods. The examination group consisted of 59 infants (average age 13.8 ± 1.4 months sick with acute inflammatory bronchopulmonary diseases. Also we tested the level of 25-hydroxyvitamin D (25(ОНD, vitamin D-binding protein, hBPI, cathelicidin LL-37, ß1-defensins, lactoferrin in blood serum with the help of immunoenzymometric analysis. Selection of prognostically important pathogenetic factors of acute bronchopulmonary disease among infants was conducted using ROC-analysis. The procedure for classifying objects was carried out using Hierarchical Cluster Analysis by the method of Centroid-based clustering. Results. Based on the results of the ROC-analysis were selected 15 potential predictors of the development of acute inflammatory diseases of the bronchopulmonary system among infants. The factor analysis made it possible to determine the 6 main components . The biggest influence in the development of the disease was made by "the anemia factor", "the factor of inflammation", "the maternal factor", "the vitamin D supply factor", "the immune factor" and "the phosphorus-calcium exchange factor” with a factor load of more than 0.6. The performed procedure of hierarchical cluster analysis confirmed the initial role of immuno-inflammatory components. The conclusions. The highlighted factors allowed to define a group of parameters, that must be influenced to achieve a maximum effect in carrying out preventive and therapeutic measures. First of all, it is necessary to influence the "the anemia factor" and "the calcium exchange factor", as well as the "the vitamin D supply factor". In other words, to correct vitamin D deficiency and carry out measures aimed at preventing the development of anemia. The prevention and treatment of the pathological course of

Analysis on risk factors for post-stroke emotional incontinence

Directory of Open Access Journals (Sweden)

Xiao-chun ZHANG

2018-01-01

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

Ranking factors of an investment in cogeneration: sensitivity analysis ranking the technical and economical factors

International Nuclear Information System (INIS)

Sundberg, Gunnel

2001-01-01

A deregulation of the electricity market in Europe will result in increased competition among the power-producing companies. They will therefore carefully estimate the financial risk in an investment in new power-producing capability. One part of the risk assessment is to perform a sensitivity analysis. This paper presents a sensitivity analysis using factorial design, resulting in an assessment of the most important technical and economical factors affecting an investment in gas turbine combined cycle and a steam cycle fired by wood chips. The study is performed using a simulation model that optimises the operation of existing power plants and potential new investments to fulfil the desired heat demand. The local utility system analysed is a Swedish district heating system with 655 GWh y -1 heat demand. The conclusion is that to understand which of the technical and economical factors affect the investment, it is not sufficient to investigate the parameters of the studied plant, but also the parameters related to the competing plants. Both the individual effects of the factors and the effect of their interaction should be investigated. For the energy system studied the price of natural gas, price of wood chips and investment cost have the major influence on the profitability of the investment. (Author)

Meta-Analysis of Comparing Personal and Environmental Factors Effective in Addiction Relapse (Iran, 2004 -2012

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s Safari

2014-12-01

Full Text Available Objective: This As a meta-analysis, this study aimed to integrate different studies and investigate the impact of individual and environmental factors on the reappearance of addiction in quitted people. Method: This study is a meta-analysis which uses Hunter and Schmidt approach. For this purpose, 28 out of 42 studies enjoying acceptable methodologies were selected, upon which the meta-analysis was conducted. A meta-analysis checklist was the research instrument. Using summary of the study results, the researcher manually calculated effect size and interpreted it based on the meta-analysis approach and Cohen’s table. Findings: Results revealed that the effect size of environmental factors on addiction relapse was 0.64 while it was obtained 0.41 for individual factors on addiction relapse. Conclusion: According to Cohen’s table, the effect sizes are evaluated as moderate and high for individual factors and environmental factors on addiction relapse, respectively.

Análisis del fracaso empresarial por sectores: factores diferenciadores = Cross-industry analysis of business failure: differential factors

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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.

Human factors review for Severe Accident Sequence Analysis (SASA)

International Nuclear Information System (INIS)

Krois, P.A.; Haas, P.M.; Manning, J.J.; Bovell, C.R.

1984-01-01

The paper will discuss work being conducted during this human factors review including: (1) support of the Severe Accident Sequence Analysis (SASA) Program based on an assessment of operator actions, and (2) development of a descriptive model of operator severe accident management. Research by SASA analysts on the Browns Ferry Unit One (BF1) anticipated transient without scram (ATWS) was supported through a concurrent assessment of operator performance to demonstrate contributions to SASA analyses from human factors data and methods. A descriptive model was developed called the Function Oriented Accident Management (FOAM) model, which serves as a structure for bridging human factors, operations, and engineering expertise and which is useful for identifying needs/deficiencies in the area of accident management. The assessment of human factors issues related to ATWS required extensive coordination with SASA analysts. The analysis was consolidated primarily to six operator actions identified in the Emergency Procedure Guidelines (EPGs) as being the most critical to the accident sequence. These actions were assessed through simulator exercises, qualitative reviews, and quantitative human reliability analyses. The FOAM descriptive model assumes as a starting point that multiple operator/system failures exceed the scope of procedures and necessitates a knowledge-based emergency response by the operators. The FOAM model provides a functionally-oriented structure for assembling human factors, operations, and engineering data and expertise into operator guidance for unconventional emergency responses to mitigate severe accident progression and avoid/minimize core degradation. Operators must also respond to potential radiological release beyond plant protective barriers. Research needs in accident management and potential uses of the FOAM model are described. 11 references, 1 figure

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.

Analysis of risk factors in the development of retinopathy of prematurity

Directory of Open Access Journals (Sweden)

Knežević Sanja

2011-01-01

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

Analysis of Factors Influencing Labour Supplied to Non-Farm Sub ...

African Journals Online (AJOL)

acer

regression analysis reveal that educational level had negative coefficient, while occupation had positive coefficient ... component of the rural economy, its role in ... economic factors influencing labour ... Textbooks, Government publications,.

Confirmatory factor analysis of the female sexual function index.

Science.gov (United States)

Opperman, Emily A; Benson, Lindsay E; Milhausen, Robin R

2013-01-01

The Female Sexual Functioning Index (Rosen et al., 2000 ) was designed to assess the key dimensions of female sexual functioning using six domains: desire, arousal, lubrication, orgasm, satisfaction, and pain. A full-scale score was proposed to represent women's overall sexual function. The fifth revision to the Diagnostic and Statistical Manual (DSM) is currently underway and includes a proposal to combine desire and arousal problems. The objective of this article was to evaluate and compare four models of the Female Sexual Functioning Index: (a) single-factor model, (b) six-factor model, (c) second-order factor model, and (4) five-factor model combining the desire and arousal subscales. Cross-sectional and observational data from 85 women were used to conduct a confirmatory factor analysis on the Female Sexual Functioning Index. Local and global goodness-of-fit measures, the chi-square test of differences, squared multiple correlations, and regression weights were used. The single-factor model fit was not acceptable. The original six-factor model was confirmed, and good model fit was found for the second-order and five-factor models. Delta chi-square tests of differences supported best fit for the six-factor model validating usage of the six domains. However, when revisions are made to the DSM-5, the Female Sexual Functioning Index can adapt to reflect these changes and remain a valid assessment tool for women's sexual functioning, as the five-factor structure was also supported.

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

International Nuclear Information System (INIS)

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

2007-01-01

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

Fatigue Analysis of Tubesheet/Shell Juncture Applying the Mitigation Factor for Over-conservatism

International Nuclear Information System (INIS)

Kang, Deog Ji; Kim, Kyu Hyoung; Lee, Jae Gon

2009-01-01

If the environmental fatigue requirements are applied to the primary components of a nuclear power plant, to which the present ASME Code fatigue curves are applied, some locations with high level CUF (Cumulative Usage Factor) are anticipated not to meet the code criteria. The application of environmental fatigue damage is still particularly controversial for plants with 60-year design lives. Therefore, it is need to develop a detailed fatigue analysis procedure to identify the conservatisms in the procedure and to lower the cumulative usage factor. Several factors are being considered to mitigate the conservatism such as three-dimensional finite element modeling. In the present analysis, actual pressure transient data instead of conservative maximum and minimum pressure data was applied as one of mitigation factors. Unlike in the general method, individual transient events were considered instead of the grouped transient events. The tubesheet/shell juncture in the steam generator assembly is the one of the weak locations and was, therefore, selected as a target to evaluate the mitigation factor in the present analysis

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...

A Retrospective Analysis of Factors Affecting Early Stoma Complications.

Science.gov (United States)

Koc, Umit; Karaman, Kerem; Gomceli, Ismail; Dalgic, Tahsin; Ozer, Ilter; Ulas, Murat; Ercan, Metin; Bostanci, Erdal; Akoglu, Musa

2017-01-01

Despite advances in surgical techniques and products for stoma care, stoma-related complications are still common. A retrospective analysis was performed of the medical records of 462 consecutive patients (295 [63.9%] female, 167 [36.1 %] male, mean age 55.5 ± 15.1 years, mean body mass index [BMI] 25.1 ± 5.2) who had undergone stoma creation at the Gastroenterological Surgery Clinic of Turkiye Yuksek İhtisas Teaching and Research Hospital between January 2008 and December 2012 to examine the incidence of early (ie, within 30 days after surgery) stoma complications and identify potential risk factors. Variables abstracted included gender, age, and BMI; existence of malignant disease; comorbidities (diabetes mellitus, hypertension, coronary artery disease, chronic respiratory disease); use of neoadjuvant chemoradiotherapy; permanent or temporary stoma; type of stoma (loop/end stoma); stoma localization; and the use of preoperative marking of the stoma site. Data were entered and analyzed using statistical software. Descriptive statistics, chi-squared, and Mann-Whitney U tests were used to describe and analyze all variables, and logistic regression analysis was used to determine independent risk factors for stoma complications. Ostomy-related complications developed in 131 patients (28.4%) Of these, superficial mucocutaneous separation was the most frequent complication (90 patients, 19.5%), followed by stoma retraction (15 patients, 3.2%). In univariate analysis, malignant disease (P = .025), creation of a colostomy (P = .002), and left lower quadrant stoma location (P toma complication. Only stoma location was an independent risk factor for the development of a stoma complication (P = .044). The rate of stoma complications was not significantly different between patients who underwent nonemergent surgery (30% in patients preoperatively sited versus 28.4% not sited) and patients who underwent emergency surgery (27.1%). Early stoma complication rates were higher

Analysis of Key Factors Driving Japan’s Military Normalization

Science.gov (United States)

2017-09-01

no change to our policy of not giving in to terrorism.”40 Though the prime minister was democratically supported, Koizumi’s leadership style took...of the key driving factors of Japan’s normalization. The areas of prime ministerial leadership , regional security threats, alliance issues, and...analysis of the key driving factors of Japan’s normalization. The areas of prime ministerial leadership , regional security threats, alliance issues, and

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.

Adjusting for multiple prognostic factors in the analysis of randomised trials

Science.gov (United States)

2013-01-01

Background When multiple prognostic factors are adjusted for in the analysis of a randomised trial, it is unclear (1) whether it is necessary to account for each of the strata, formed by all combinations of the prognostic factors (stratified analysis), when randomisation has been balanced within each stratum (stratified randomisation), or whether adjusting for the main effects alone will suffice, and (2) the best method of adjustment in terms of type I error rate and power, irrespective of the randomisation method. Methods We used simulation to (1) determine if a stratified analysis is necessary after stratified randomisation, and (2) to compare different methods of adjustment in terms of power and type I error rate. We considered the following methods of analysis: adjusting for covariates in a regression model, adjusting for each stratum using either fixed or random effects, and Mantel-Haenszel or a stratified Cox model depending on outcome. Results Stratified analysis is required after stratified randomisation to maintain correct type I error rates when (a) there are strong interactions between prognostic factors, and (b) there are approximately equal number of patients in each stratum. However, simulations based on real trial data found that type I error rates were unaffected by the method of analysis (stratified vs unstratified), indicating these conditions were not met in real datasets. Comparison of different analysis methods found that with small sample sizes and a binary or time-to-event outcome, most analysis methods lead to either inflated type I error rates or a reduction in power; the lone exception was a stratified analysis using random effects for strata, which gave nominal type I error rates and adequate power. Conclusions It is unlikely that a stratified analysis is necessary after stratified randomisation except in extreme scenarios. Therefore, the method of analysis (accounting for the strata, or adjusting only for the covariates) will not

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.

Human Reliability Analysis for Design: Using Reliability Methods for Human Factors Issues

International Nuclear Information System (INIS)

Boring, Ronald Laurids

2010-01-01

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.

Exploratory Factor Analysis With Small Samples and Missing Data.

Science.gov (United States)

McNeish, Daniel

2017-01-01

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

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

International Nuclear Information System (INIS)

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

2011-01-01

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

The Columbia Impairment Scale: Factor Analysis Using a Community Mental Health Sample

Science.gov (United States)

Singer, Jonathan B.; Eack, Shaun M.; Greeno, Catherine M.

2011-01-01

Objective: The objective of this study was to test the factor structure of the parent version of the Columbia Impairment Scale (CIS) in a sample of mothers who brought their children for community mental health (CMH) services (n = 280). Method: Confirmatory factor analysis (CFA) was used to test the fit of the hypothesized four-factor structure…

Spatio-Temporal Multiway Data Decomposition Using Principal Tensor Analysis on k-Modes: The R Package PTAk

Directory of Open Access Journals (Sweden)

Didier G. Leibovici

2010-10-01

Full Text Available The purpose of this paper is to describe the R package {PTAk and how the spatio-temporal context can be taken into account in the analyses. Essentially PTAk( is a multiway multidimensional method to decompose a multi-entries data-array, seen mathematically as a tensor of any order. This PTAk-modes method proposes a way of generalizing SVD (singular value decomposition, as well as some other well known methods included in the R package, such as PARAFAC or CANDECOMP and the PCAn-modes or Tucker-n model. The example datasets cover different domains with various spatio-temporal characteristics and issues: (i~medical imaging in neuropsychology with a functional MRI (magnetic resonance imaging study, (ii~pharmaceutical research with a pharmacodynamic study with EEG (electro-encephaloegraphic data for a central nervous system (CNS drug, and (iii~geographical information system (GIS with a climatic dataset that characterizes arid and semi-arid variations. All the methods implemented in the R package PTAk also support non-identity metrics, as well as penalizations during the optimization process. As a result of these flexibilities, together with pre-processing facilities, PTAk constitutes a framework for devising extensions of multidimensional methods such ascorrespondence analysis, discriminant analysis, and multidimensional scaling, also enabling spatio-temporal constraints.

Human Factors Engineering and Ergonomics Analysis for the Canister Storage Building (CSB) Results and Findings

International Nuclear Information System (INIS)

GARVIN, L.J.

1999-01-01

The purpose for this supplemental report is to follow-up and update the information in SNF-3907, Human Factors Engineering (HFE) Analysis: Results and Findings. This supplemental report responds to applicable U.S. Department of Energy Safety Analysis Report review team comments and questions. This Human Factors Engineering and Ergonomics (HFE/Erg) analysis was conducted from April 1999 to July 1999; SNF-3907 was based on analyses accomplished in October 1998. The HFE/Erg findings presented in this report and SNF-3907, along with the results of HNF-3553, Spent Nuclear Fuel Project, Final Safety Analysis Report. Annex A, ''Canister Storage Building Final Safety Analysis Report,'' Chapter A3.0, ''Hazards and Accidents Analyses,'' provide the technical basis for preparing or updating HNF-3553, Annex A, Chapter A13.0, ''Human Factors Engineering.'' The findings presented in this report allow the HNF-3553 Chapter 13.0, ''Human Factors,'' to respond fully to the HFE requirements established in DOE Order 5480.23, Nuclear Safety Analysis Reports

Human Factors Engineering and Ergonomics Analysis for the Canister Storage Building (CSB): Results and Findings

International Nuclear Information System (INIS)

GARVIN, L.J.

1999-01-01

The purpose for this supplemental report is to follow-up and update the information in SNF-3907, Human Factors Engineering (HFE) Analysis: Results and Findings. This supplemental report responds to applicable U.S. Department of Energy Safety Analysis Report review team comments and questions. This Human Factors Engineering and Ergonomics (HFE/Erg) analysis was conducted from April 1999 to July 1999; SNF-3907 was based on analyses accomplished in October 1998. The HFE/Erg findings presented in this report and SNF-3907, along with the results of HNF-3553, Spent Nuclear Fuel Project, Final Safety Analysis Report, Annex A, ''Canister Storage Building Final Safety Analysis Report,'' Chapter A3.0, ''Hazards and Accidents Analyses,'' provide the technical basis for preparing or updating HNF-3553. Annex A, Chaptex A13.0, ''Human Factors Engineering.'' The findings presented in this report allow the HNF-3553 Chapter 13.0, ''Human Factors,'' to respond fully to the HFE requirements established in DOE Order 5480.23, Nuclear Safety Analysis Reports

Analysis of Performance Factors for Accounting and Finance Related Business Courses in a Distance Education Environment

Science.gov (United States)

Benligiray, Serdar; Onay, Ahmet

2017-01-01

The objective of this study is to explore business courses performance factors with a focus on accounting and finance. Course score interrelations are assumed to represent interpretable constructs of these factors. Factor analysis is proposed to identify the constructs that explain the correlations. Factor analysis results identify three…

Characteristics and fate of natural organic matter during UV oxidation processes.

Science.gov (United States)

Ahn, Yongtae; Lee, Doorae; Kwon, Minhwan; Choi, Il-Hwan; Nam, Seong-Nam; Kang, Joon-Wun

2017-10-01

Advanced oxidation processes (AOPs) are widely used in water treatments. During oxidation processes, natural organic matter (NOM) is modified and broken down into smaller compounds that affect the characteristics of the oxidized NOM by AOPs. In this study, NOM was characterized and monitored in the UV/hydrogen peroxide (H 2 O 2 ) and UV/persulfate (PS) processes using a liquid chromatography-organic carbon detector (LC-OCD) technique, and a combination of excitation-emission matrices (EEM) and parallel factor analysis (PARAFAC). The percentages of mineralization of NOM in the UV/H 2 O 2 and UV/PS processes were 20.5 and 83.3%, respectively, with a 10 mM oxidant dose and a contact time of 174 s (UV dose: approximately 30,000 mJ). Low-pressure, Hg UV lamp (254 nm) was applied in this experiment. The steady-state concentration of SO 4 - was 38-fold higher than that of OH at an oxidant dose of 10 mM. With para-chlorobenzoic acid (pCBA) as a radical probe compound, we experimentally determined the rate constants of Suwannee River NOM (SRNOM) with OH (k OH/NOM  = 3.3 × 10 8  M -1 s -1 ) and SO 4 - (k SO4-/NOM  = 4.55 × 10 6  M -1 s -1 ). The hydroxyl radical and sulfate radical showed different mineralization pathways of NOM, which have been verified by the use of LC-OCD and EEM/PARAFAC. Consequently, higher steady-state concentrations of SO 4 - , and different reaction preferences of OH and SO 4 - with the NOM constituent had an effect on the mineralization efficiency. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hydrological Controls on Dissolved Organic Matter Quality and Export in a Coastal River System in Southeastern USA

Science.gov (United States)

Bhattacharya, R.; Osburn, C. L.

2017-12-01

Dissolved organic matter (DOM) exported from river catchments can influence the biogeochemical processes in coastal environments with implications for water quality and carbon budget. High flow conditions are responsible for most DOM export ("pulses") from watersheds, and these events reduce DOM transformation and production by "shunting" DOM from river networks into coastal waters: the Pulse-Shunt Concept (PSC). Subsequently, the source and quality of DOM is also expected to change as a function of river flow. Here, we used stream dissolved organic carbon concentrations ([DOC]) along with DOM optical properties, such as absorbance at 350 nm (a350) and fluorescence excitation and emission matrices modeled by parallel factor analysis (PARAFAC), to characterize DOM source, quality and fluxes under variable flow conditions for the Neuse River, a coastal river system in the southeastern US. Observations were made at a flow gauged station above head of tide periodically between Aug 2011 and Feb 2013, which captured low flow periods in summer and several high flow events including Hurricane Irene. [DOC] and a350 were correlated and varied positively with river flow, implying that a large portion of the DOM was colored, humic and flow-mobilized. During high flow conditions, PARAFAC results demonstrated the higher influx of terrestrial humic DOM, and lower in-stream phytoplankton production or microbial degradation. However, during low flow, DOM transformation and production increased in response to higher residence times and elevated productivity. Further, 70% of the DOC was exported by above average flows, where 3-4 fold increases in DOC fluxes were observed during episodic events, consistent with PSC. These results imply that storms dramatically affects DOM export to coastal waters, whereby high river flow caused by episodic events primarily shunt terrestrial DOM to coastal waters, whereas low flow promotes in-stream DOM transformation and amendment with microbial DOM.

Factoral analysis of the cost of preparing oil

Energy Technology Data Exchange (ETDEWEB)

Avdeyeva, L A; Kudoyarov, G Sh; Shmatova, M F

1979-01-01

Mathematical statistics methods (basically correlational and regression analysis) are used to study the factors which form the level of cost of preparing oil with consideration of the mutual influence of the factors. Selected as the claims for inclusion into a mathematical model was a group of five a priori justified factors: the water level of the oil being extracted (%); the specific expenditure of deemulsifiers; the volume of oil preparation; the quality of oil preparation (the salt content) and the level of use of the installations' capacities (%). To construct an economic and mathematical model of the cost of the technical preparation (SPP) of the oil, all the unions which make up the Ministry of the Oil Industry were divided into two comparable totalities. The first group included unions in which the oil SPP was lower than the branch average and the second, unions in which the SPP was higher than the branch wide cost. Using the coefficients of regression, special elasticity coefficients and the fluctuation indicators, the basic factors were finally identified which have the greatest influence on the formation of the oil SPP level separately for the first and second groups of unions.

Assessing Heterogeneity for Factor Analysis Model with Continuous and Ordinal Outcomes

Directory of Open Access Journals (Sweden)

Ye-Mao Xia

2016-01-01

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

Analysis of Human Error Types and Performance Shaping Factors in the Next Generation Main Control Room

International Nuclear Information System (INIS)

Sin, Y. C.; Jung, Y. S.; Kim, K. H.; Kim, J. H.

2008-04-01

Main control room of nuclear power plants has been computerized and digitalized in new and modernized plants, as information and digital technologies make great progresses and become mature. Survey on human factors engineering issues in advanced MCRs: Model-based approach, Literature survey-based approach. Analysis of human error types and performance shaping factors is analysis of three human errors. The results of project can be used for task analysis, evaluation of human error probabilities, and analysis of performance shaping factors in the HRA analysis

Minerals sampling: sensibility analysis and correction factors for Pierre Gy's equation

International Nuclear Information System (INIS)

Vallebuona, G.; Niedbalski, F.

2005-01-01

Pierre Gy's equation is widely used in ore sampling. This equation is based in four parameters: shape factor, size distribution factor, mineralogical factor and liberation factor. The usual practice is to consider fixed values for the shape and size distribution factors. This practice does not represent well several important ores. The mineralogical factor considers only one specie of interest and the gangue, leaving out other cases such as polymetallic ores where there are more than one species of interest. A sensibility analysis to the Gy's equation factors was done and a procedure to determine specific values for them was developed and presented in this work. mean ore characteristics, associated with an insecure use of the actual procedure, were determined. finally, for a case study, the effects of using each alternative were evaluated. (Author) 4 refs

Interactive analysis of human error factors in NPP operation events

International Nuclear Information System (INIS)

Zhang Li; Zou Yanhua; Huang Weigang

2010-01-01

Interactive of human error factors in NPP operation events were introduced, and 645 WANO operation event reports from 1999 to 2008 were analyzed, among which 432 were found relative to human errors. After classifying these errors with the Root Causes or Causal Factors, and then applying SPSS for correlation analysis,we concluded: (1) Personnel work practices are restricted by many factors. Forming a good personnel work practices is a systematic work which need supports in many aspects. (2)Verbal communications,personnel work practices, man-machine interface and written procedures and documents play great roles. They are four interaction factors which often come in bundle. If some improvements need to be made on one of them,synchronous measures are also necessary for the others.(3) Management direction and decision process, which are related to management,have a significant interaction with personnel factors. (authors)

Risk factors for chronic and recurrent otitis media-a meta-analysis.

Science.gov (United States)

Zhang, Yan; Xu, Min; Zhang, Jin; Zeng, Lingxia; Wang, Yanfei; Zheng, Qing Yin

2014-01-01

Risk factors associated with chronic otitis media (COM) and recurrent otitis media (ROM) have been investigated in previous studies. The objective of this study was to integrate the findings and determine the possible risk factors for COM/ROM based on our meta-analysis. A comprehensive search of electronic bibliographic databases (PubMed, Embase, CNKI and Wanfang database) from 1964 to Dec 2012, as well as a manual search of references of articles, was performed. A total of 2971 articles were searched, and 198 full-text articles were assessed for eligibility; 24 studies were eligible for this meta-analysis. Regarding risk factors for COM/ROM, there were two to nine different studies from which the odds ratios (ORs) could be pooled. The presence of allergy or atopy increased the risk of COM/ROM (OR, 1.36; 95% CI, 1.13-1.64; P = 0.001). An upper respiratory tract infection (URTI) significantly increased the risk of COM/ROM (OR, 6.59; 95% CI, 3.13-13.89; Pmedia (AOM)/ROM increased the risk of COM/ROM (OR, 11.13; 95% CI, 1.06-116.44; P = 0.04). Passive smoke significantly increased the risk of COM/ROM (OR, 1.39; 95% CI, 1.02-1.89 P = 0.04). Low social status appeared to be a risk factor for COM/ROM (OR, 3.82; 95% CI, 1.11-13.15; P = 0.03). Our meta-analysis identified reliable conclusions that allergy/atopy, URTI, snoring, previous history of AOM/ROM, Second-hand smoke and low social status are important risk factors for COM/ROM. Other unidentified risk factors need to be identified in further studies with critical criteria.

A RECOGNITION OF HEALTH AND NUTRITION FACTORS IN FOOD DEMAND ANALYSIS

OpenAIRE

Capps, Oral, Jr.; Schmitz, John D.

1991-01-01

A theoretical framework in which to formally consider health and nutrition factors in demand analyses is developed. The framework is employed to empirically identify and assess the impacts of information pertaining to cholesterol on the demands for beef, pork, poultry, and fish. Issues in considering health and nutrition factors in food demand analysis are documented.

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

Science.gov (United States)

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

2018-01-01

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

A meta-analysis of factors affecting trust in human-robot interaction.

Science.gov (United States)

Hancock, Peter A; Billings, Deborah R; Schaefer, Kristin E; Chen, Jessie Y C; de Visser, Ewart J; Parasuraman, Raja

2011-10-01

We evaluate and quantify the effects of human, robot, and environmental factors on perceived trust in human-robot interaction (HRI). To date, reviews of trust in HRI have been qualitative or descriptive. Our quantitative review provides a fundamental empirical foundation to advance both theory and practice. Meta-analytic methods were applied to the available literature on trust and HRI. A total of 29 empirical studies were collected, of which 10 met the selection criteria for correlational analysis and 11 for experimental analysis. These studies provided 69 correlational and 47 experimental effect sizes. The overall correlational effect size for trust was r = +0.26,with an experimental effect size of d = +0.71. The effects of human, robot, and environmental characteristics were examined with an especial evaluation of the robot dimensions of performance and attribute-based factors. The robot performance and attributes were the largest contributors to the development of trust in HRI. Environmental factors played only a moderate role. Factors related to the robot itself, specifically, its performance, had the greatest current association with trust, and environmental factors were moderately associated. There was little evidence for effects of human-related factors. The findings provide quantitative estimates of human, robot, and environmental factors influencing HRI trust. Specifically, the current summary provides effect size estimates that are useful in establishing design and training guidelines with reference to robot-related factors of HRI trust. Furthermore, results indicate that improper trust calibration may be mitigated by the manipulation of robot design. However, many future research needs are identified.

Supervised Cross-Modal Factor Analysis for Multiple Modal Data Classification

KAUST Repository

Wang, Jingbin

2015-10-09

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

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

Directory of Open Access Journals (Sweden)

Shaiq Sultan

2016-04-01

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

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

International Nuclear Information System (INIS)

Takagawa, Kenichi; Iida, Hiroyasu

2011-01-01

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

Human Factors Analysis of Pipeline Monitoring and Control Operations: Final Technical Report

Science.gov (United States)

2008-11-26

The purpose of the Human Factors Analysis of Pipeline Monitoring and Control Operations project was to develop procedures that could be used by liquid pipeline operators to assess and manage the human factors risks in their control rooms that may adv...

Confirmatory factor analysis of the neck disability index in a whiplash population indicates a one-factor model is viable

OpenAIRE

Gabel, Charles P.; Cuesta-Vargas, Antonio I.; Barr, Sebastian; Winkeljohn Black, Stephanie; Osborne, Jason W.; Melloh, Markus

2016-01-01

Purpose The neck disability index (NDI) as a 10-item patient reported outcome (PRO) measure is the most commonly used whiplash associated disorders (WAD) assessment tool. However, statistical rigor and factor structure are not definitive. To date, confirmatory factor analysis (CFA) has not examined whether the factor structure generalizes across different groups (e.g., WAD versus non-WAD). This study aimed to determine the psychometric properties of the NDI in these population groups.

Meta-analysis of greenhouse gas displacement factors of wood product substitution

International Nuclear Information System (INIS)

Sathre, Roger; O'Connor, Jennifer

2010-01-01

A displacement factor can express the efficiency of using biomass to reduce net greenhouse gas (GHG) emission, by quantifying the amount of emission reduction achieved per unit of wood use. Here we integrate data from 21 different international studies in a meta-analysis of the displacement factors of wood products substituted in place of non-wood materials. We calculate the displacement factors in consistent units of tons of carbon (tC) of emission reduction per tC in wood product. The displacement factors range from a low of -2.3 to a high of 15, with most lying in the range of 1.0 to 3.0. The average displacement factor value is 2.1, meaning that for each tC in wood products substituted in place of non-wood products, there occurs an average GHG emission reduction of approximately 2.1 tC. Expressed in other units, this value corresponds to roughly 3.9 t CO 2 eq emission reduction per ton of dry wood used. The few cases of negative displacement factors are the result of worst-case scenarios that are unrealistic in current practice. This meta-analysis quantifies the range of GHG benefits of wood substitution, and provides a clear climate rationale for increasing wood substitution in place of other products, provided that forests are sustainably managed and that wood residues are used responsibly.

Meta-analysis of greenhouse gas displacement factors of wood product substitution

Energy Technology Data Exchange (ETDEWEB)

Sathre, Roger [Ecotechnology, Mid Sweden University, 83125 Ostersund (Sweden); O' Connor, Jennifer [FPInnovations-Forintek, Vancouver, BC, Canada V6T 1W5 (Canada)

2010-04-15

A displacement factor can express the efficiency of using biomass to reduce net greenhouse gas (GHG) emission, by quantifying the amount of emission reduction achieved per unit of wood use. Here we integrate data from 21 different international studies in a meta-analysis of the displacement factors of wood products substituted in place of non-wood materials. We calculate the displacement factors in consistent units of tons of carbon (tC) of emission reduction per tC in wood product. The displacement factors range from a low of -2.3 to a high of 15, with most lying in the range of 1.0 to 3.0. The average displacement factor value is 2.1, meaning that for each tC in wood products substituted in place of non-wood products, there occurs an average GHG emission reduction of approximately 2.1 tC. Expressed in other units, this value corresponds to roughly 3.9 t CO{sub 2} eq emission reduction per ton of dry wood used. The few cases of negative displacement factors are the result of worst-case scenarios that are unrealistic in current practice. This meta-analysis quantifies the range of GHG benefits of wood substitution, and provides a clear climate rationale for increasing wood substitution in place of other products, provided that forests are sustainably managed and that wood residues are used responsibly.

Financial consumer protection and customer satisfaction. A relationship study by using factor analysis and discriminant analysis

Directory of Open Access Journals (Sweden)

Marimuthu SELVAKUMAR

2015-11-01

Full Text Available This paper tries to make an attempt to study the relationship between the financial consumer protection and customer satisfaction by using factor analysis and discriminant analysis. The main objectives of the study are to analyze the financial consumer protection in commercial banks, to examine the customer satisfaction of commercial banks and to identify the factors of financial consumer protection lead customer satisfaction. There are many research work carried out on financial consumer protection in financial literacy, but the identification of factors which lead the financial consumer protection and the relationship between financial consumer protection and the customer satisfaction is very important, Particularly for banks to improve its quality and increase the customer satisfaction. Therefore this study is carried out with the aim of identifying the factors of financial consumer protection and its influence on customer satisfaction. This study is both descriptive and analytical in nature. It covers both primary and secondary data. The primary data has been collected from the customers of commercial banks using pre-tested interview schedule and the secondary data has been collected from standard books, journals, magazines, websites and so on.

PRINCIPAL COMPONENT ANALYSIS OF FACTORS DETERMINING PHOSPHATE ROCK DISSOLUTION ON ACID SOILS

Directory of Open Access Journals (Sweden)

Yusdar Hilman

2016-10-01

Full Text Available Many of the agricultural soils in Indonesia are acidic and low in both total and available phosphorus which severely limits their potential for crops production. These problems can be corrected by application of chemical fertilizers. However, these fertilizers are expensive, and cheaper alternatives such as phosphate rock (PR have been considered. Several soil factors may influence the dissolution of PR in soils, including both chemical and physical properties. The study aimed to identify PR dissolution factors and evaluate their relative magnitude. The experiment was conducted in Soil Chemical Laboratory, Universiti Putra Malaysia and Indonesian Center for Agricultural Land Resources Research and Development from January to April 2002. The principal component analysis (PCA was used to characterize acid soils in an incubation system into a number of factors that may affect PR dissolution. Three major factors selected were soil texture, soil acidity, and fertilization. Using the scores of individual factors as independent variables, stepwise regression analysis was performed to derive a PR dissolution function. The factors influencing PR dissolution in order of importance were soil texture, soil acidity, then fertilization. Soil texture factors including clay content and organic C, and soil acidity factor such as P retention capacity interacted positively with P dissolution and promoted PR dissolution effectively. Soil texture factors, such as sand and silt content, soil acidity factors such as pH, and exchangeable Ca decreased PR dissolution.

Risk factors for chronic and recurrent otitis media-a meta-analysis.

Directory of Open Access Journals (Sweden)

Yan Zhang

Full Text Available Risk factors associated with chronic otitis media (COM and recurrent otitis media (ROM have been investigated in previous studies. The objective of this study was to integrate the findings and determine the possible risk factors for COM/ROM based on our meta-analysis. A comprehensive search of electronic bibliographic databases (PubMed, Embase, CNKI and Wanfang database from 1964 to Dec 2012, as well as a manual search of references of articles, was performed. A total of 2971 articles were searched, and 198 full-text articles were assessed for eligibility; 24 studies were eligible for this meta-analysis. Regarding risk factors for COM/ROM, there were two to nine different studies from which the odds ratios (ORs could be pooled. The presence of allergy or atopy increased the risk of COM/ROM (OR, 1.36; 95% CI, 1.13-1.64; P = 0.001. An upper respiratory tract infection (URTI significantly increased the risk of COM/ROM (OR, 6.59; 95% CI, 3.13-13.89; P<0.00001. Snoring appeared to be a significant risk factor for COM/ROM (OR, 1.96; 95% CI, 1.78-2.16; P<0.00001. A patient history of acute otitis media (AOM/ROM increased the risk of COM/ROM (OR, 11.13; 95% CI, 1.06-116.44; P = 0.04. Passive smoke significantly increased the risk of COM/ROM (OR, 1.39; 95% CI, 1.02-1.89 P = 0.04. Low social status appeared to be a risk factor for COM/ROM (OR, 3.82; 95% CI, 1.11-13.15; P = 0.03. Our meta-analysis identified reliable conclusions that allergy/atopy, URTI, snoring, previous history of AOM/ROM, Second-hand smoke and low social status are important risk factors for COM/ROM. Other unidentified risk factors need to be identified in further studies with critical criteria.

Gene expression meta-analysis identifies metastatic pathways and transcription factors in breast cancer

International Nuclear Information System (INIS)

Thomassen, Mads; Tan, Qihua; Kruse, Torben A

2008-01-01

Metastasis is believed to progress in several steps including different pathways but the determination and understanding of these mechanisms is still fragmentary. Microarray analysis of gene expression patterns in breast tumors has been used to predict outcome in recent studies. Besides classification of outcome, these global expression patterns may reflect biological mechanisms involved in metastasis of breast cancer. Our purpose has been to investigate pathways and transcription factors involved in metastasis by use of gene expression data sets. We have analyzed 8 publicly available gene expression data sets. A global approach, 'gene set enrichment analysis' as well as an approach focusing on a subset of significantly differently regulated genes, GenMAPP, has been applied to rank pathway gene sets according to differential regulation in metastasizing tumors compared to non-metastasizing tumors. Meta-analysis has been used to determine overrepresentation of pathways and transcription factors targets, concordant deregulated in metastasizing breast tumors, in several data sets. The major findings are up-regulation of cell cycle pathways and a metabolic shift towards glucose metabolism reflected in several pathways in metastasizing tumors. Growth factor pathways seem to play dual roles; EGF and PDGF pathways are decreased, while VEGF and sex-hormone pathways are increased in tumors that metastasize. Furthermore, migration, proteasome, immune system, angiogenesis, DNA repair and several signal transduction pathways are associated to metastasis. Finally several transcription factors e.g. E2F, NFY, and YY1 are identified as being involved in metastasis. By pathway meta-analysis many biological mechanisms beyond major characteristics such as proliferation are identified. Transcription factor analysis identifies a number of key factors that support central pathways. Several previously proposed treatment targets are identified and several new pathways that may

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

Science.gov (United States)

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

2015-02-01

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

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.

Confirmatory factor analysis of posttraumatic stress symptoms in sexually harassed women.

Science.gov (United States)

Palmieri, Patrick A; Fitzgerald, Louise F

2005-12-01

Posttraumatic stress disorder (PTSD) factor analytic research to date has not provided a clear consensus on the structure of posttraumatic stress symptoms. Seven hypothesized factor structures were evaluated using confirmatory factor analysis of the Posttraumatic Stress Disorder Checklist, a paper-and-pencil measure of posttraumatic stress symptom severity, in a sample of 1,218 women who experienced a broad range of workplace sexual harassment. The model specifying correlated re-experiencing, effortful avoidance, emotional numbing, and hyperarousal factors provided the best fit to the data. Virtually no support was obtained for the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV; American Psychiatric Association, 1994) three-factor model of re-experiencing, avoidance, and hyperarousal factors. Different patterns of correlations with external variables were found for the avoidance and emotional numbing factors, providing further validation of the supported model.

A pragmatic approach to estimate alpha factors for common cause failure analysis

International Nuclear Information System (INIS)

Hassija, Varun; Senthil Kumar, C.; Velusamy, K.

2014-01-01

Highlights: • Estimation of coefficients in alpha factor model for common cause analysis. • A derivation of plant specific alpha factors is demonstrated. • We examine sensitivity of common cause contribution to total system failure. • We compare beta factor and alpha factor models for various redundant configurations. • The use of alpha factors is preferable, especially for large redundant systems. - Abstract: Most of the modern technological systems are deployed with high redundancy but still they fail mainly on account of common cause failures (CCF). Various models such as Beta Factor, Multiple Greek Letter, Binomial Failure Rate and Alpha Factor exists for estimation of risk from common cause failures. Amongst all, alpha factor model is considered most suitable for high redundant systems as it arrives at common cause failure probabilities from a set of ratios of failures and the total component failure probability Q T . In the present study, alpha factor model is applied for the assessment of CCF of safety systems deployed at two nuclear power plants. A method to overcome the difficulties in estimation of the coefficients viz., alpha factors in the model, importance of deriving plant specific alpha factors and sensitivity of common cause contribution to the total system failure probability with respect to hazard imposed by various CCF events is highlighted. An approach described in NUREG/CR-5500 is extended in this study to provide more explicit guidance for a statistical approach to derive plant specific coefficients for CCF analysis especially for high redundant systems. The procedure is expected to aid regulators for independent safety assessment

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

Directory of Open Access Journals (Sweden)

Guo Yundong

2018-01-01

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

Analysis of employee benefits in Factoring KB, a.s.v

OpenAIRE

Vachoušek, Stanislav

2011-01-01

The main objective of this work is to analyze employee benefits - benefits of Factoring KB, a.s. The theoretical part of the generally specifies the basic concepts related to employee benefits needed to cope with the analytical part. The content of this section is primarily a system of employee benefits, classification of employee benefits, tax savings and marginally trends in providing benefits. The analytical part is devoted exclusively to Factoring KB, there is an analysis of employee bene...

WHY DO SOME NATIONS SUCCEED AND OTHERS FAIL IN INTERNATIONAL COMPETITION? FACTOR ANALYSIS AND CLUSTER ANALYSIS AT EUROPEAN LEVEL

Directory of Open Access Journals (Sweden)

Popa Ion

2015-07-01

Full Text Available As stated by Michael Porter (1998: 57, 'this is perhaps the most frequently asked economic question of our times.' However, a widely accepted answer is still missing. The aim of this paper is not to provide the BIG answer for such a BIG question, but rather to provide a different perspective on the competitiveness at the national level. In this respect, we followed a two step procedure, called “tandem analysis”. (OECD, 2008. First we employed a Factor Analysis in order to reveal the underlying factors of the initial dataset followed by a Cluster Analysis which aims classifying the 35 countries according to the main characteristics of competitiveness resulting from Factor Analysis. The findings revealed that clustering the 35 states after the first two factors: Smart Growth and Market Development, which recovers almost 76% of common variability of the twelve original variables, are highlighted four clusters as well as a series of useful information in order to analyze the characteristics of the four clusters and discussions on them.

Genomewide analysis of TCP transcription factor gene family in ...

Indian Academy of Sciences (India)

Home; Journals; Journal of Genetics; Volume 93; Issue 3. Genomewide ... Teosinte branched1/cycloidea/proliferating cell factor1 (TCP) proteins are a large family of transcriptional regulators in angiosperms. They are ... To the best of our knowledge, this is the first study of a genomewide analysis of apple TCP gene family.

Human Factors Engineering and Ergonomics Analysis for the Canister Storage Building (CSB) Results and Findings

Energy Technology Data Exchange (ETDEWEB)

GARVIN, L.J.

1999-09-20

The purpose for this supplemental report is to follow-up and update the information in SNF-3907, Human Factors Engineering (HFE) Analysis: Results and Findings. This supplemental report responds to applicable U.S. Department of Energy Safety Analysis Report review team comments and questions. This Human Factors Engineering and Ergonomics (HFE/Erg) analysis was conducted from April 1999 to July 1999; SNF-3907 was based on analyses accomplished in October 1998. The HFE/Erg findings presented in this report and SNF-3907, along with the results of HNF-3553, Spent Nuclear Fuel Project, Final Safety Analysis Report, Annex A, ''Canister Storage Building Final Safety Analysis Report,'' Chapter A3.0, ''Hazards and Accidents Analyses,'' provide the technical basis for preparing or updating HNF-3553. Annex A, Chaptex A13.0, ''Human Factors Engineering.'' The findings presented in this report allow the HNF-3553 Chapter 13.0, ''Human Factors,'' to respond fully to the HFE requirements established in DOE Order 5480.23, Nuclear Safety Analysis Reports.

Human factor analysis and preventive countermeasures of maintenance in nuclear power plant

International Nuclear Information System (INIS)

Zhang Li; Hu Chao

2008-01-01

Based on the human error analysis theory and the characteristics of maintenance in a nuclear power plant, human factors of maintenance in NPP are divided into three different areas: human, technology, and organization, in which human refers to the individual factors, mainly including psychological quality, physiological characteristic, state of health, knowledge, skill level, and interpersonal relationship. Technology includes the maintenance technology, maintenance strategy, maintenance tool, maintenance interface, maintenance regulation, and work environment. Organization includes task arrangement, information communication, training, personnel external environment, team construction, and leadership. The analysis also reveals that the organization factors, which can indirectly influence personnel performance, are the primary initiators of human error. Based on these, some countermeasures are brought forward in order to reduce human errors. (authors)

Sulfites and the wine metabolome.

Science.gov (United States)

Roullier-Gall, Chloé; Hemmler, Daniel; Gonsior, Michael; Li, Yan; Nikolantonaki, Maria; Aron, Alissa; Coelho, Christian; Gougeon, Régis D; Schmitt-Kopplin, Philippe

2017-12-15

In a context of societal concern about food preservation, the reduction of sulfite input plays a major role in the wine industry. To improve the understanding of the chemistry involved in the SO 2 protection, a series of bottle aged Chardonnay wines made from the same must, but with different concentrations of SO 2 added at pressing were analyzed by ultrahigh resolution mass spectrometry (FT-ICR-MS) and excitation emission matrix fluorescence (EEMF). Metabolic fingerprints from FT-ICR-MS data could discriminate wines according to the added concentration to the must but they also revealed chemistry-related differences according to the type of stopper, providing a wine metabolomics picture of the impact of distinct stopping strategies. Spearman rank correlation was applied to link the statistically modeled EEMF components (parallel factor analysis (PARAFAC)) and the exact mass information from FT-ICR-MS, and thus revealing the extent of sulfur-containing compounds which could show some correlation with fluorescence fingerprints. Copyright © 2017 Elsevier Ltd. All rights reserved.

Risk Factors for Post-stroke Depression: A Meta-analysis

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Yu Shi

2017-07-01

Full Text Available Background: Stroke not only impacts patients physically but also economically. Post-stroke depression (PSD, as a common complication of stroke, always obstructs the process of stroke rehabilitation. Accordingly, defining the risk factors associated with PSD has extraordinary importance. Although there have been many studies investigating the risk factors for PSD, the results are inconsistent.Objectives: The objectives of this study were to identify the risk factors for PSD by evidence-based medicine.Data sources: A systematic and comprehensive database search was performed of PubMed, Medline, CENTRAL, EMBASE.com, the Cochrane library and Web of Science for Literature, covering publications from January 1, 1998 to November 19, 2016.Study Selection: Studies on risk factors for PSD were identified, according to inclusion and exclusion criteria. The risk of bias tool, described in the Cochrane Handbook version 5.1.0, was used to assess the quality of each study. Meta-analysis was performed using RevMan 5.3 software.Results: Thirty-six studies were included for review. A history of mental illness was the highest ranking modifiable risk factor; other risk factors for PSD were female gender, age (<70 years, neuroticism, family history, severity of stroke, and level of handicap. Social support was a protective factor for PSD.Conclusion: There are many factors that have effects on PSD. The severity of stroke is an important factor in the occurrence of PSD. Mental history is a possible predictor of PSD. Prevention of PSD requires social and family participation.

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...

Final Technical Report: Advanced Measurement and Analysis of PV Derate Factors.

Energy Technology Data Exchange (ETDEWEB)

King, Bruce Hardison [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Burton, Patrick D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hansen, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Christian Birk [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-12-01

The Advanced Measurement and Analysis of PV Derate Factors project focuses on improving the accuracy and reducing the uncertainty of PV performance model predictions by addressing a common element of all PV performance models referred to as “derates”. Widespread use of “rules of thumb”, combined with significant uncertainty regarding appropriate values for these factors contribute to uncertainty in projected energy production.

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.)

Dispersion-theoretical analysis of the nucleon electromagnetic form factors

International Nuclear Information System (INIS)

Belushkin, M.

2007-01-01

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 ππ, K anti K and the ρπ 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.)

Using the deterministic factor systems in the analysis of return on ...

African Journals Online (AJOL)

Using the deterministic factor systems in the analysis of return on equity. ... or equal the profitability of bank deposits, the business of the organization is not efficient. ... Application of quantitative and qualitative indicators in the analysis allows to ... By Country · List All Titles · Free To Read Titles This Journal is Open Access.

A Confirmatory Factor Analysis of the Academic Motivation Scale with Black College Students

Science.gov (United States)

Cokley, Kevin

2015-01-01

The factor structure of the Academic Motivation Scale (AMS) was examined with a sample of 578 Black college students. A confirmatory factor analysis of the AMS was conducted. Results indicated that the hypothesized seven-factor model did not fit the data. Implications for future research with the AMS are discussed.

Analysis on the factors affecting seafarers fatigue based on European Navigation Inc

DEFF Research Database (Denmark)

Zhao, Zhi Wei; Zhu, Yun Qi; Zheng, En Xi

2017-01-01

In order to analyze the main factors associated with fatigue and analyze the main factors which contribute to fatigue of different types of seafarers. SPSS software was used to carry out optimal scale multiple regression and variance analysis based on the questionnaire surveys of 454 employees...

Human factors and fuzzy set theory for safety analysis

International Nuclear Information System (INIS)

Nishiwaki, Y.

1987-01-01

Human reliability and performance is affected by many factors: medical, physiological and psychological, etc. The uncertainty involved in human factors may not necessarily be probabilistic, but fuzzy. Therefore, it is important to develop a theory by which both the non-probabilistic uncertainties, or fuzziness, of human factors and the probabilistic properties of machines can be treated consistently. In reality, randomness and fuzziness are sometimes mixed. From the mathematical point of view, probabilistic measures may be considered a special case of fuzzy measures. Therefore, fuzzy set theory seems to be an effective tool for analysing man-machine systems. The concept 'failure possibility' based on fuzzy sets is suggested as an approach to safety analysis and fault diagnosis of a large complex system. Fuzzy measures and fuzzy integrals are introduced and their possible applications are also discussed. (author)

Analysis of the financial factors governing the profitability of lunar helium-3

Science.gov (United States)

Kulcinski, G. L.; Thompson, H.; Ott, S.

1989-01-01

Financial factors influencing the profitability of the mining and utilization of lunar helium-3 are examined. The analysis addressed the following questions: (1) which financial factors have the greatest leverage on the profitability of He-3; (2) over what range can these factors be varied to keep the He-3 option profitable; and (3) what ultimate effect could this energy source have on the price of electricity for U.S. consumers. Two complementary methods of analysis were used in the assessment: rate of return on incremental investment required and reduction revenue requirements (total cost to customers) achieved. Some of the factors addressed include energy demand, power generation costs with and without fusion, profitability for D-He(3) fusion, annual capital and operating costs, launch mass and costs, He-3 price, and government funding. Specific conclusions are made with respect to each of the companies considered: utilities, lunar mining company, and integrated energy company.

Validity of a four-factor modelunderlying the physical fitness in adults with intellectual disabilities a confirmatory factor analysis

OpenAIRE

Cuesta-Vargas, Antonio; Solera Martinez, M; Rodriguez Moya, Alejandro; Perez, Y; Martinez Vizcaino, V

2011-01-01

Purpose: To use confirmatory factor analysis to test whether a four factor might explain the clustering of the components of the physical fitness in adults with intellectual disabilities (FID). Relevance: Individuals with intellectual disabilities (ID) are significantly weaker than individuals without ID at all stages of life. These subjects might be particularly susceptible to loss of basic function because of poor physical fitness. Participants: We studied 267 adults with intellectual...

Analysis on factors affecting consumers decision on purchasing simple-type houses

Science.gov (United States)

Rumintang, A.; Sholichin, I.

2018-01-01

In line with the increase of the population and the need of comfortable houses, as affected by modernization era, the house demand is getting higher. Hence, conducting a research on consumers need and want in buying a house should be seriously attempted to succeed marketing activity. Using an analysis consumers’ behavior, the researcher will know few affecting factors related to consumers’ satisfaction in buying a house. Among other, the factors in question include: house price, house condition, facilities, location and accessability. The sample of this research was drawn from the residents of Graha Asri Housing, Taman Bulang Permai, and Sukodono Permai. Based on the analysis and discussion, some conclusions are made as follow: the factors and variables affecting the consumers’ decision on each choice of house is different and also the same variables on three sources of data include housing atmosphere, cleaning service, ease of access to shopping center, health clinics or hospitals, tourism spot, schools, and the bus station.

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

Directory of Open Access Journals (Sweden)

Ari Saptono

2017-06-01

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

A Rasch and factor analysis of the Functional Assessment of Cancer Therapy-General (FACT-G

Directory of Open Access Journals (Sweden)

Selby Peter J

2007-04-01

Full Text Available Abstract Background Although the Functional Assessment of Cancer Therapy – General questionnaire (FACT-G has been validated few studies have explored the factor structure of the instrument, in particular using non-sample dependent measurement techniques, such as Rasch Models. Furthermore, few studies have explored the relationship between item fit to the Rasch Model and clinical utility. The aim of this study was to investigate the dimensionality and measurement properties of the FACT-G with Rasch Models and Factor analysis. Methods A factor analysis and Rasch analysis (Partial Credit Model was carried out on the FACT-G completed by a heterogeneous sample of cancer patients (n = 465. For the Rasch analysis item fit (infit mean squares ≥ 1.30, dimensionality and item invariance were assessed. The impact of removing misfitting items on the clinical utility of the subscales and FACT-G total scale was also assessed. Results The factor analysis demonstrated a four factor structure of the FACT-G which broadly corresponded to the four subscales of the instrument. Internal consistency for these four scales was very good (Cronbach's alpha 0.72 – 0.85. The Rasch analysis demonstrated that each of the subscales and the FACT-G total scale had misfitting items (infit means square ≥ 1.30. All these scales with the exception of the Social & Family Well-being Scale (SFWB were unidimensional. When misfitting items were removed, the effect sizes and the clinical utility of the instrument were maintained for the subscales and the total FACT-G scores. Conclusion The results of the traditional factor analysis and Rasch analysis of the FACT-G broadly agreed. Caution should be exercised when utilising the Social & Family Well-being scale and further work is required to determine whether this scale is best represented by two factors. Additionally, removing misfitting items from scales should be performed alongside an assessment of the impact on clinical utility.

Influencing Factors of Catering and Food Service Industry Based on Principal Component Analysis

OpenAIRE

Zi Tang

2014-01-01

Scientific analysis of influencing factors is of great importance for the healthy development of catering and food service industry. This study attempts to present a set of critical indicators for evaluating the contribution of influencing factors to catering and food service industry in the particular context of Harbin City, Northeast China. Ten indicators that correlate closely with catering and food service industry were identified and performed by the principal component analysis method u...

Driven Factors Analysis of China’s Irrigation Water Use Efficiency by Stepwise Regression and Principal Component Analysis

Directory of Open Access Journals (Sweden)

Renfu Jia

2016-01-01

Full Text Available This paper introduces an integrated approach to find out the major factors influencing efficiency of irrigation water use in China. It combines multiple stepwise regression (MSR and principal component analysis (PCA to obtain more realistic results. In real world case studies, classical linear regression model often involves too many explanatory variables and the linear correlation issue among variables cannot be eliminated. Linearly correlated variables will cause the invalidity of the factor analysis results. To overcome this issue and reduce the number of the variables, PCA technique has been used combining with MSR. As such, the irrigation water use status in China was analyzed to find out the five major factors that have significant impacts on irrigation water use efficiency. To illustrate the performance of the proposed approach, the calculation based on real data was conducted and the results were shown in this paper.

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

International Nuclear Information System (INIS)

Shen, Chen-Hua

2015-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-12-04

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

Evaluation of the reliability concerning the identification of human factors as contributing factors by a computer supported event analysis (CEA)

International Nuclear Information System (INIS)

Wilpert, B.; Maimer, H.; Loroff, C.

2000-01-01

The project's objectives are the evaluation of the reliability concerning the identification of Human Factors as contributing factors by a computer supported event analysis (CEA). CEA is a computer version of SOL (Safety through Organizational Learning). Parts of the first step were interviews with experts from the nuclear power industry and the evaluation of existing computer supported event analysis methods. This information was combined to a requirement profile for the CEA software. The next step contained the implementation of the software in an iterative process of evaluation. The completion of this project was the testing of the CEA software. As a result the testing demonstrated that it is possible to identify contributing factors with CEA validly. In addition, CEA received a very positive feedback from the experts. (orig.) [de

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

Directory of Open Access Journals (Sweden)

WU Xiaofeng

2013-06-01

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

Risk Factors for Premature Births: A Cross-Sectional Analysis of ...

African Journals Online (AJOL)

Risk Factors for Premature Births: A Cross-Sectional Analysis of Hospital Records in a Cameroonian Health Facility. Andreas Chiabi, Evelyn M Mah, Nicole Mvondo, Seraphin Nguefack, Lawrence Mbuagbaw, Karen K Kamga, Shiyuan Zhang, Emile Mboudou, Pierre F Tchokoteu, Elie Mbonda ...

Analysis Of The Social-Economic Factors Affecting Output Of Nihort ...

African Journals Online (AJOL)

Analysis Of The Social-Economic Factors Affecting Output Of Nihort Fruit Adoptors And ... A moderate family size of 6-7 family members are in adopters and ... Extension agents presence is necessary in the study area so as to organise training ...

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Science.gov (United States)

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

2018-03-01

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

Confirmatory Factor Analysis of the WISC-IV in a Hospital Referral Sample

Science.gov (United States)

Devena, Sarah E.; Gay, Catherine E.; Watkins, Marley W.

2013-01-01

Confirmatory factor analysis was used to determine the factor structure of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) scores of 297 children referred to a children's hospital in the Southwestern United States. Results support previous findings that indicate the WISC-IV is best represented by a direct hierarchical…

A Confirmatory Factor Analysis of Reilly's Role Overload Scale

Science.gov (United States)

Thiagarajan, Palaniappan; Chakrabarty, Subhra; Taylor, Ronald D.

2006-01-01

In 1982, Reilly developed a 13-item scale to measure role overload. This scale has been widely used, but most studies did not assess the unidimensionality of the scale. Given the significance of unidimensionality in scale development, the current study reports a confirmatory factor analysis of the 13-item scale in two samples. Based on the…

Beyond factor analysis: Multidimensionality and the Parkinson's Disease Sleep Scale-Revised.

Directory of Open Access Journals (Sweden)

Maria E Pushpanathan

Full Text Available Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinson's disease (PD. The Parkinson's Disease Sleep Scale (PDSS and its variants (the Parkinson's disease Sleep Scale-Revised; PDSS-R, and the Parkinson's Disease Sleep Scale-2; PDSS-2 quantify a range of symptoms impacting sleep in only 15 items. However, data from these scales may be problematic as included items have considerable conceptual breadth, and there may be overlap in the constructs assessed. Multidimensional measurement models, accounting for the tendency for items to measure multiple constructs, may be useful more accurately to model variance than traditional confirmatory factor analysis. In the present study, we tested the hypothesis that a multidimensional model (a bifactor model is more appropriate than traditional factor analysis for data generated by these types of scales, using data collected using the PDSS-R as an exemplar. 166 participants diagnosed with idiopathic PD participated in this study. Using PDSS-R data, we compared three models: a unidimensional model; a 3-factor model consisting of sub-factors measuring insomnia, motor symptoms and obstructive sleep apnoea (OSA and REM sleep behaviour disorder (RBD symptoms; and, a confirmatory bifactor model with both a general factor and the same three sub-factors. Only the confirmatory bifactor model achieved satisfactory model fit, suggesting that PDSS-R data are multidimensional. There were differential associations between factor scores and patient characteristics, suggesting that some PDSS-R items, but not others, are influenced by mood and personality in addition to sleep symptoms. Multidimensional measurement models may also be a helpful tool in the PDSS and the PDSS-2 scales and may improve the sensitivity of these instruments.

Scintigraphic measurement of the contractile activity of the gastric antrum using factor analysis

International Nuclear Information System (INIS)

Bergmann, H.; Hoebart, J.; Kugi, A.; Stacher, G.; Granser, G.V.

1990-01-01

The motor activity of the gastric antrum is difficult to record by manometric means and scintigraphic methods have proved unsatisfactory so far as no consistent relationship between antral contractile activity and gastric emptying rate could be detected. We investigated, using data recorded in 16 healthy human subjects after the ingestion of a semisolid standard meal, whether a newly developed method employing factor analysis would yield more meaningful and reproducible results. Factor analysis was applied to sequential scintigraphic images (3-s frame time) of gastric antrum. The computed factor images and the respective factor curves are representative of distinct dynamic structures of the antrum. From the more or less sinusoidal excursions of the factor curves, which exhibited the 3 cycles per minute frequency characteristic for the stomach, amplitude, frequency and propagation velocity of antral contractions can be calculated. The amplitudes of the factor curves were used to calculate a contraction index. This contraction index was found to be correlated significantly negatively with the gastric half-emptying time of the ingested meal. The employed factor analytical approach thus seems a promising tool to further investigate the role of antral contractility in the process of gastric emptying. (Authors)

Sea level rise and the geoid: factor analysis approach

Directory of Open Access Journals (Sweden)

Alexey Sadovski

2013-08-01

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

The recovery factors analysis of the human errors for research reactors

International Nuclear Information System (INIS)

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

2006-01-01

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

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

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Rini Kurnia Sari

2015-10-01

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

The effects of common risk factors on stock returns: A detrended cross-correlation analysis

Science.gov (United States)

Ruan, Qingsong; Yang, Bingchan

2017-10-01

In this paper, we investigate the cross-correlations between Fama and French three factors and the return of American industries on the basis of cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). Qualitatively, we find that the return series of Fama and French three factors and American industries were overall significantly cross-correlated based on the analysis of a statistic. Quantitatively, we find that the cross-correlations between three factors and the return of American industries were strongly multifractal, and applying MF-DCCA we also investigate the cross-correlation of industry returns and residuals. We find that there exists multifractality of industry returns and residuals. The result of correlation coefficients we can verify that there exist other factors which influence the industry returns except Fama three factors.

In-depth analysis of the causal factors of incidents reported in the Greek petrochemical industry

Energy Technology Data Exchange (ETDEWEB)

Konstandinidou, Myrto [Institute of Nuclear Technology-Radiation Protection, National Center for Scientific Research ' Demokritos' , Aghia Paraskevi 15310 (Greece); Nivolianitou, Zoe, E-mail: zoe@ipta.demokritos.gr [Institute of Nuclear Technology-Radiation Protection, National Center for Scientific Research ' Demokritos' , Aghia Paraskevi 15310 (Greece); Kefalogianni, Eirini; Caroni, Chrys [School of Applied Mathematical and Physical Sciences, National Technical University of Athens, 9 Iroon Polytexneiou Str., Zografou Campus, 157 80 Athens (Greece)

2011-11-15

This paper presents a statistical analysis of all reported incidents in the Greek petrochemical industry from 1997 to 2003. A comprehensive database has been developed to include industrial accidents (fires, explosions and substance releases), occupational accidents, incidents without significant consequences and near misses. The study concentrates on identifying and analyzing the causal factors related to different consequences of incidents, in particular, injury, absence from work and material damage. Methods of analysis include logistic regression with one of these consequences as dependent variable. The causal factors that are considered cover four major categories related to organizational issues, equipment malfunctions, human errors (of commission or omission) and external causes. Further analyses aim to confirm the value of recording near misses by comparing their causal factors with those of more serious incidents. The statistical analysis highlights the connection between the human factor and the underlying causes of accidents or incidents. - Highlights: > The research work is original, based on field data collected directly from the petrochemical industry. > It deals with the in-depth statistical analysis of accident data on human-organizational causes. > It researches underlying causes of accidents and the parameters affecting them. > The causal factors that are considered cover four big taxonomies. > Near misses are worth recording for comparing their causal factors with more serious incidents.

Research on the relationship between the elements and pharmacological activities in velvet antler using factor analysis and cluster analysis

Science.gov (United States)

Zhou, Libing

2017-04-01

Velvet antler has certain effect on improving the body's immune cells and the regulation of immune system function, nervous system, anti-stress, anti-aging and osteoporosis. It has medicinal applications to treat a wide range of diseases such as tissue wound healing, anti-tumor, cardiovascular disease, et al. Therefore, the research on the relationship between pharmacological activities and elements in velvet antler is of great significance. The objective of this study was to comprehensively evaluate 15 kinds of elements in different varieties of velvet antlers and study on the relationship between the elements and traditional Chinese medicine efficacy for the human. The factor analysis and the factor cluster analysis methods were used to analyze the data of elements in the sika velvet antler, cervus elaphus linnaeus, flower horse hybrid velvet antler, apiti (elk) velvet antler, male reindeer velvet antler and find out the relationship between 15 kinds of elements including Ca, P, Mg, Na, K, Fe, Cu, Mn, Al, Ba, Co, Sr, Cr, Zn and Ni. Combining with MATLAB2010 and SPSS software, the chemometrics methods were made on the relationship between the elements in velvet antler and the pharmacological activities. The first commonality factor F1 had greater load on the indexes of Ca, P, Mg, Co, Sr and Ni, and the second commonality factor F2 had greater load on the indexes of K, Mn, Zn and Cr, and the third commonality factor F3 had greater load on the indexes of Na, Cu and Ba, and the fourth commonality factor F4 had greater load on the indexes of Fe and Al. 15 kinds of elements in velvet antler in the order were elk velvet antler>flower horse hybrid velvet antler>cervus elaphus linnaeus>sika velvet antler>male reindeer velvet antler. Based on the factor analysis and the factor cluster analysis, a model for evaluating traditional Chinese medicine quality was constructed. These studies provide the scientific base and theoretical foundation for the future large-scale rational

Problems with the factor analysis of items: Solutions based on item response theory and item parcelling

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Gideon P. De Bruin

2004-10-01

Full Text Available The factor analysis of items often produces spurious results in the sense that unidimensional scales appear multidimensional. This may be ascribed to failure in meeting the assumptions of linearity and normality on which factor analysis is based. Item response theory is explicitly designed for the modelling of the non-linear relations between ordinal variables and provides a strong alternative to the factor analysis of items. Items may also be combined in parcels that are more likely to satisfy the assumptions of factor analysis than do the items. The use of the Rasch rating scale model and the factor analysis of parcels is illustrated with data obtained with the Locus of Control Inventory. The results of these analyses are compared with the results obtained through the factor analysis of items. It is shown that the Rasch rating scale model and the factoring of parcels produce superior results to the factor analysis of items. Recommendations for the analysis of scales are made. Opsomming Die faktorontleding van items lewer dikwels misleidende resultate op, veral in die opsig dat eendimensionele skale as meerdimensioneel voorkom. Hierdie resultate kan dikwels daaraan toegeskryf word dat daar nie aan die aannames van lineariteit en normaliteit waarop faktorontleding berus, voldoen word nie. Itemresponsteorie, wat eksplisiet vir die modellering van die nie-liniêre verbande tussen ordinale items ontwerp is, bied ’n aantreklike alternatief vir die faktorontleding van items. Items kan ook in pakkies gegroepeer word wat meer waarskynlik aan die aannames van faktorontleding voldoen as individuele items. Die gebruik van die Rasch beoordelingskaalmodel en die faktorontleding van pakkies word aan die hand van data wat met die Lokus van Beheervraelys verkry is, gedemonstreer. Die resultate van hierdie ontledings word vergelyk met die resultate wat deur ‘n faktorontleding van die individuele items verkry is. Die resultate dui daarop dat die Rasch

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

International Nuclear Information System (INIS)

Ha, Tae Woong

2001-01-01

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

Analysis of Performance Factors for Accounting and Finance Related Business Courses in A Distance Education Environment

OpenAIRE

BENLIGIRAY, Serdar; ONAY, Ahmet

2017-01-01

The objective of this study is to explore business courses performance factors with a focus on accounting and finance. Course score interrelations are assumed to represent interpretable constructs of these factors. Factor analysis is proposed to identify the constructs that explain the correlations. Factor analysis results identify three sub-groups of business core courses. The first group is labeled as management-oriented courses. Accounting, finance and economics courses are separated in tw...

Memory systems, processes, and tasks: taxonomic clarification via factor analysis.

Science.gov (United States)

Bruss, Peter J; Mitchell, David B

2009-01-01

The nature of various memory systems was examined using factor analysis. We reanalyzed data from 11 memory tasks previously reported in Mitchell and Bruss (2003). Four well-defined factors emerged, closely resembling episodic and semantic memory and conceptual and perceptual implicit memory, in line with both memory systems and transfer-appropriate processing accounts. To explore taxonomic issues, we ran separate analyses on the implicit tasks. Using a cross-format manipulation (pictures vs. words), we identified 3 prototypical tasks. Word fragment completion and picture fragment identification tasks were "factor pure," tapping perceptual processes uniquely. Category exemplar generation revealed its conceptual nature, yielding both cross-format priming and a picture superiority effect. In contrast, word stem completion and picture naming were more complex, revealing attributes of both processes.

Supervised Cross-Modal Factor Analysis for Multiple Modal Data Classification

KAUST Repository

Wang, Jingbin; Zhou, Yihua; Duan, Kanghong; Wang, Jim Jing-Yan; Bensmail, Halima

2015-01-01

. In this paper, we improve CFA by incorporating the supervision information to represent and classify both image and text modals of documents. We project both image and text data to a shared data space by factor analysis, and then train a class label predictor

A Confirmatory Factor Analysis on the Attitude Scale of Constructivist Approach for Science Teachers

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E. Evrekli

2010-11-01

Full Text Available Underlining the importance of teachers for the constructivist approach, the present study attempts to develop “Attitude Scale of Construc¬tivist Approach for Science Teachers (ASCAST”. The pre-applications of the scale were administered to a total of 210 science teachers; however, the data obtained from 5 teachers were excluded from the analysis. As a result of the analysis of the data obtained from the pre-applications, it was found that the scale could have a single factor structure, which was tested using the confir¬matory factor analysis. As a result of the initial confirmatory factor analysis, the values of fit were examined and found to be low. Subsequently, by exam¬ining the modification indices, error covariance was added between items 23 and 24 and the model was tested once again. The added error covariance led to a significant improvement in the model, producing values of fit suitable for limit values. Thus, it was concluded that the scale could be employed with a single factor. The explained variance value for the scale developed with a sin¬gle factor structure was calculated to be 50.43% and its reliability was found to be .93. The results obtained suggest that the scale possesses reliable-valid characteristics and could be used in further studies.

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

Science.gov (United States)

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

2015-09-01

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

Qualitative and quantitative methods for human factor analysis and assessment in NPP. Investigations and results

International Nuclear Information System (INIS)

Hristova, R.; Kalchev, B.; Atanasov, D.

2005-01-01

We consider here two basic groups of methods for analysis and assessment of the human factor in the NPP area and give some results from performed analyses as well. The human factor is the human interaction with the design equipment, with the working environment and takes into account the human capabilities and limits. In the frame of the qualitative methods for analysis of the human factor are considered concepts and structural methods for classifying of the information, connected with the human factor. Emphasize is given to the HPES method for human factor analysis in NPP. Methods for quantitative assessment of the human reliability are considered. These methods allow assigning of probabilities to the elements of the already structured information about human performance. This part includes overview of classical methods for human reliability assessment (HRA, THERP), and methods taking into account specific information about human capabilities and limits and about the man-machine interface (CHR, HEART, ATHEANA). Quantitative and qualitative results concerning human factor influence in the initiating events occurrences in the Kozloduy NPP are presented. (authors)

Analysis of operational events by ATHEANA framework for human factor modelling

International Nuclear Information System (INIS)

Bedreaga, Luminita; Constntinescu, Cristina; Doca, Cezar; Guzun, Basarab

2007-01-01

In the area of human reliability assessment, the experts recognise the fact that the current methods have not represented correctly the role of human in prevention, initiating and mitigating the accidents in nuclear power plants. The nature of this deficiency appears because the current methods used in modelling of human factor have not taken into account the human performance and reliability such as it has been observed in the operational events. ATHEANA - A Technique for Human Error ANAlysis - is a new methodology for human analysis that has included the specific data of operational events and also psychological models for human behaviour. This method has included new elements such as the unsafe action and error mechanisms. In this paper we present the application of ATHEANA framework in the analysis of operational events that appeared in different nuclear power plants during 1979-2002. The analysis of operational events has consisted of: - identification of the unsafe actions; - including the unsafe actions into a category, omission ar commission; - establishing the type of error corresponding to the unsafe action: slip, lapse, mistake and circumvention; - establishing the influence of performance by shaping the factors and some corrective actions. (authors)

Estimation of physiological parameters using knowledge-based factor analysis of dynamic nuclear medicine image sequences

International Nuclear Information System (INIS)

Yap, J.T.; Chen, C.T.; Cooper, M.

1995-01-01

The authors have previously developed a knowledge-based method of factor analysis to analyze dynamic nuclear medicine image sequences. In this paper, the authors analyze dynamic PET cerebral glucose metabolism and neuroreceptor binding studies. These methods have shown the ability to reduce the dimensionality of the data, enhance the image quality of the sequence, and generate meaningful functional images and their corresponding physiological time functions. The new information produced by the factor analysis has now been used to improve the estimation of various physiological parameters. A principal component analysis (PCA) is first performed to identify statistically significant temporal variations and remove the uncorrelated variations (noise) due to Poisson counting statistics. The statistically significant principal components are then used to reconstruct a noise-reduced image sequence as well as provide an initial solution for the factor analysis. Prior knowledge such as the compartmental models or the requirement of positivity and simple structure can be used to constrain the analysis. These constraints are used to rotate the factors to the most physically and physiologically realistic solution. The final result is a small number of time functions (factors) representing the underlying physiological processes and their associated weighting images representing the spatial localization of these functions. Estimation of physiological parameters can then be performed using the noise-reduced image sequence generated from the statistically significant PCs and/or the final factor images and time functions. These results are compared to the parameter estimation using standard methods and the original raw image sequences. Graphical analysis was performed at the pixel level to generate comparable parametric images of the slope and intercept (influx constant and distribution volume)

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

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Illiashenko Sergii

2016-06-01

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

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

Science.gov (United States)

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

2015-01-01

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

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

Science.gov (United States)

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

2008-11-01

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