WorldWideScience

Sample records for variables factor analysis

  1. Amplification factor variable amplifier

    NARCIS (Netherlands)

    Akitsugu, Oshita; Nauta, Bram

    2007-01-01

    PROBLEM TO BE SOLVED: To provide an amplification factor variable amplifier capable of achieving temperature compensation of an amplification factor over a wide variable amplification factor range. ; SOLUTION: A Gilbert type amplification factor variable amplifier 11 amplifies an input signal and

  2. Amplification factor variable amplifier

    NARCIS (Netherlands)

    Akitsugu, Oshita; Nauta, Bram

    2010-01-01

    PROBLEM TO BE SOLVED: To provide an amplification factor variable amplifier capable of achieving temperature compensation of an amplification factor over a wide variable amplification factor range. ;SOLUTION: A Gilbert type amplification factor variable amplifier 11 amplifies an input signal and can

  3. 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.

  4. Collinear Latent Variables in Multilevel Confirmatory Factor Analysis : A Comparison of Maximum Likelihood and Bayesian Estimation

    NARCIS (Netherlands)

    Can, Seda; van de Schoot, Rens|info:eu-repo/dai/nl/304833207; Hox, Joop|info:eu-repo/dai/nl/073351431

    2015-01-01

    Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the

  5. Exploratory factor analysis for differentiating sensory and mechanical variables related to muscle-tendon unit elongation

    Directory of Open Access Journals (Sweden)

    Mauro H. Chagas

    2016-01-01

    Full Text Available ABSTRACT Background Stretching exercises are able to promote adaptations in the muscle-tendon unit (MTU, which can be tested through physiological and biomechanical variables. Identifying the key variables in MTU adaptations is crucial to improvements in training. Objective To perform an exploratory factor analysis (EFA involving the variables often used to evaluate the response of the MTU to stretching exercises. Method Maximum joint range of motion (ROMMAX, ROM at first sensation of stretching (FSTROM, peak torque (torqueMAX, passive stiffness, normalized stiffness, passive energy, and normalized energy were investigated in 36 participants during passive knee extension on an isokinetic dynamometer. Stiffness and energy values were normalized by the muscle cross-sectional area and their passive mode assured by monitoring the EMG activity. Results EFA revealed two major factors that explained 89.68% of the total variance: 53.13% was explained by the variables torqueMAX, passive stiffness, normalized stiffness, passive energy, and normalized energy, whereas the remaining 36.55% was explained by the variables ROMMAX and FSTROM. Conclusion This result supports the literature wherein two main hypotheses (mechanical and sensory theories have been suggested to describe the adaptations of the MTU to stretching exercises. Contrary to some studies, in the present investigation torqueMAX was significantly correlated with the variables of the mechanical theory rather than those of the sensory theory. Therefore, a new approach was proposed to explain the behavior of the torqueMAX during stretching exercises.

  6. Analysis of spatio-temporal variability of C-factor derived from remote sensing data

    Science.gov (United States)

    Pechanec, Vilem; Benc, Antonin; Purkyt, Jan; Cudlin, Pavel

    2016-04-01

    In some risk areas water erosion as the present task has got the strong influence on agriculture and can threaten inhabitants. In our country combination of USLE and RUSLE models has been used for water erosion assessment (Krása et al., 2013). Role of vegetation cover is characterized by the help of vegetation protection factor, so-called C- factor. Value of C-factor is given by the ratio of washing-off on a plot with arable crops to standard plot which is kept as fallow regularly spud after any rain (Janeček et al., 2012). Under conditions we cannot identify crop structure and its turn, determination of C-factor can be problem in large areas. In such case we only determine C-factor according to the average crop representation. New technologies open possibilities for acceleration and specification of the approach. Present-day approach for the C-factor determination is based on the analysis of multispectral image data. Red and infrared spectrum is extracted and these parts of image are used for computation of vegetation index series (NDVI, TSAVI). Acquired values for fractional time sections (during vegetation period) are averaged out. At the same time values of vegetation indices for a forest and cleared area are determined. Also regressive coefficients are computed. Final calculation is done by the help of regressive equations expressing relation between values of NDVI and C-factor (De Jong, 1994; Van der Knijff, 1999; Karaburun, 2010). Up-to-date land use layer is used for the determination of erosion threatened areas on the base of selection of individual landscape segments of erosion susceptible categories of land use. By means of Landsat 7 data C-factor has been determined for the whole area of the Czech Republic in every month of the year of 2014. At the model area in a small watershed C-factor has been determined by the conventional (tabular) procedure. Analysis was focused on: i) variability assessment of C-factor values while using the conventional

  7. Mixture simultaneous factor analysis for capturing differences in latent variables between higher level units of multilevel data

    NARCIS (Netherlands)

    De Roover, K.; Vermunt, J.K.; Timmerman, Marieke E.; Ceulemans, Eva

    2017-01-01

    Given multivariate data, many research questions pertain to the covariance structure: whether and how the variables (for example, personality measures) covary. Exploratory factor analysis (EFA) is often used to look for latent variables that may explain the covariances among variables; for example,

  8. 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

  9. Glucose variability for cardiovascular risk factors in type 2 diabetes: a meta-analysis

    OpenAIRE

    Liang, Shuang; Yin, Hang; Wei, Chunxiang; Xie, Linjun; He, Hua; Liu, Xiaoquan

    2017-01-01

    Aims It is consensus that glucose variability (GV) plays an important role in maccomplications of type 2 diabetes, but whether GV has a causal role is not yet clear for cardiovascular disease (CVD). This study sought to explore the effect on GV for CVD risk factors with type 2 diabetes. Methods The systematic literature search was performed to identify all GV and CVD risk factors, including total cholesterol (TC), LDL cholesterol (LDL-C), triglyceride (TG), HDL cholesterol (HDL-C), Body Mass ...

  10. Identification and analysis of explanatory variables for a multi-factor productivity model of passenger airlines

    Directory of Open Access Journals (Sweden)

    Antonio Henriques de Araújo Jr

    2011-05-01

    Full Text Available The paper aimed to identify and analyze the explanatory variables for airlines productivity during 2000 2005, by testing the Pearson correlation between the single factor productivity capital, energy and labor of a sample of 45 selected international airlines (4 Brazilian carriers among them and their productivity explanatory variables like medium stage length, aircraft load factor, hours flown and cruise speed for selected routes besides aircraft seat configuration and airlines number of employees. The research demonstrated, that a set of variables can explain differences in productivity for passenger airlines, such as: investment in personnel training processes, automation, airplane seat density, occupation of aircraft, average flight stage length, density and extension of routes, among others.

  11. Derivation and application of mathematical model for well test analysis with variable skin factor in hydrocarbon reservoirs

    Directory of Open Access Journals (Sweden)

    Pengcheng Liu

    2016-06-01

    Full Text Available Skin factor is often regarded as a constant in most of the mathematical model for well test analysis in oilfields, but this is only a kind of simplified treatment with the actual skin factor changeable. This paper defined the average permeability of a damaged area as a function of time by using the definition of skin factor. Therefore a relationship between a variable skin factor and time was established. The variable skin factor derived was introduced into existing traditional models rather than using a constant skin factor, then, this newly derived mathematical model for well test analysis considering variable skin factor was solved by Laplace transform. The dimensionless wellbore pressure and its derivative changed with dimensionless time were plotted with double logarithm and these plots can be used for type curve fitting. The effects of all the parameters in the expression of variable skin factor were analyzed based on the dimensionless wellbore pressure and its derivative. Finally, actual well testing data were used to fit the type curves developed which validates the applicability of the mathematical model from Sheng-2 Block, Shengli Oilfield, China.

  12. Analysis of spatiotemporal variability of C-factor derived from remote sensing data

    Science.gov (United States)

    Pechanec, Vilém; Mráz, Alexander; Benc, Antonín; Cudlín, Pavel

    2018-01-01

    Soil erosion is an important phenomenon that contributes to the degradation of agricultural land. Even though it is a natural process, human activities can significantly increase its impact on land degradation and present serious limitation on sustainable agricultural land use. Nowadays, the risk of soil erosion is assessed either qualitatively by expert assessment or quantitatively using model-based approach. One of the primary factors affecting the soil erosion assessment is a cover-management factor, C-factor. In the Czech Republic, several models are used to assess the C-factor on a long-term basis based on data collected using traditional tabular methods. This paper presents work to investigate the estimation of both long-term and short-term cover-management factors using remote sensing data. The results demonstrate a successful development of C-factor maps for each month of 2014, growing season average, and annual average for the Czech Republic. C-factor values calculated from remote sensing data confirmed expected trend in their temporal variability for selected crops. The results presented in this paper can be used for enhancing existing methods for estimating C-factor, planning future agricultural activities, and designing technical remediations and improvement activities of land use in the Czech Republic, which are also financially supported by the European Union funds.

  13. An Exploratory Factor Analysis of the Sexual Orientation Counselor Competency Scale: Examining the Variable of Experience

    Science.gov (United States)

    Ali, Shainna; Lambie, Glenn; Bloom, Zachary D.

    2017-01-01

    The Sexual Orientation Counselor Competency Scale (SOCCS), developed by Bidell in 2005, measures counselors' levels of skills, awareness, and knowledge in assisting lesbian, gay, or bisexual (LGB) clients. In an effort to gain an increased understanding of the construct validity of the SOCCS, researchers performed an exploratory factor analysis on…

  14. Ideal, nonideal, and no-marker variables: The confirmatory factor analysis (CFA) marker technique works when it matters.

    Science.gov (United States)

    Williams, Larry J; O'Boyle, Ernest H

    2015-09-01

    A persistent concern in the management and applied psychology literature is the effect of common method variance on observed relations among variables. Recent work (i.e., Richardson, Simmering, & Sturman, 2009) evaluated 3 analytical approaches to controlling for common method variance, including the confirmatory factor analysis (CFA) marker technique. Their findings indicated significant problems with this technique, especially with nonideal marker variables (those with theoretical relations with substantive variables). Based on their simulation results, Richardson et al. concluded that not correcting for method variance provides more accurate estimates than using the CFA marker technique. We reexamined the effects of using marker variables in a simulation study and found the degree of error in estimates of a substantive factor correlation was relatively small in most cases, and much smaller than error associated with making no correction. Further, in instances in which the error was large, the correlations between the marker and substantive scales were higher than that found in organizational research with marker variables. We conclude that in most practical settings, the CFA marker technique yields parameter estimates close to their true values, and the criticisms made by Richardson et al. are overstated. (c) 2015 APA, all rights reserved).

  15. Job demands and job strain as risk factors for employee wellbeing in elderly care: an instrumental-variables analysis.

    Science.gov (United States)

    Elovainio, Marko; Heponiemi, Tarja; Kuusio, Hannamaria; Jokela, Markus; Aalto, Anna-Mari; Pekkarinen, Laura; Noro, Anja; Finne-Soveri, Harriet; Kivimäki, Mika; Sinervo, Timo

    2015-02-01

    The association between psychosocial work environment and employee wellbeing has repeatedly been shown. However, as environmental evaluations have typically been self-reported, the observed associations may be attributable to reporting bias. Applying instrumental-variable regression, we used staffing level (the ratio of staff to residents) as an unconfounded instrument for self-reported job demands and job strain to predict various indicators of wellbeing (perceived stress, psychological distress and sleeping problems) among 1525 registered nurses, practical nurses and nursing assistants working in elderly care wards. In ordinary regression, higher self-reported job demands and job strain were associated with increased risk of perceived stress, psychological distress and sleeping problems. The effect estimates for the associations of these psychosocial factors with perceived stress and psychological distress were greater, but less precisely estimated, in an instrumental-variables analysis which took into account only the variation in self-reported job demands and job strain that was explained by staffing level. No association between psychosocial factors and sleeping problems was observed with the instrumental-variable analysis. These results support a causal interpretation of high self-reported job demands and job strain being risk factors for employee wellbeing. © The Author 2014. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

  16. Latent variable models an introduction to factor, path, and structural equation analysis

    CERN Document Server

    Loehlin, John C

    2004-01-01

    This fourth edition introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. The book is intended for advanced students and researchers in the areas of social, educational, clinical, ind

  17. Analysis of spatiotemporal variability of C-factor derived from remote sensing data

    Czech Academy of Sciences Publication Activity Database

    Pechanec, V.; Mráz, A.; Benc, A.; Cudlín, Pavel

    2018-01-01

    Roč. 12, č. 1 (2018), č. článku 016022. ISSN 1931-3195 R&D Projects: GA MŠk(CZ) LO1415 Grant - others:EHP,MF ČR(CZ) EHP-CZ02-OV-1-014-2014 Program:CZ02 Institutional support: RVO:86652079 Keywords : leaf-area index * soil-erosion * water erosion * ecosystem * model * vegetation * europe * fluxes * scale * ndvi * C-factor * soil erosion * erosion models * remote sensing * vegetation Subject RIV: EH - Ecology, Behaviour OBOR OECD: Environmental sciences (social aspects to be 5.7) Impact factor: 1.107, year: 2016

  18. Environmental life cycle assessment of grain maize production: An analysis of factors causing variability.

    Science.gov (United States)

    Boone, Lieselot; Van Linden, Veerle; De Meester, Steven; Vandecasteele, Bart; Muylle, Hilde; Roldán-Ruiz, Isabel; Nemecek, Thomas; Dewulf, Jo

    2016-05-15

    To meet the growing demand, high yielding, but environmentally sustainable agricultural plant production systems are desired. Today, life cycle assessment (LCA) is increasingly used to assess the environmental impact of these agricultural systems. However, the impact results are very diverse due to management decisions or local natural conditions. The impact of grain maize is often generalized and an average is taken. Therefore, we studied variation in production systems. Four types of drivers for variability are distinguished: policy, farm management, year-to-year weather variation and innovation. For each driver, scenarios are elaborated using ReCiPe and CEENE (Cumulative Exergy Extraction from the Natural Environment) to assess the environmental footprint. Policy limits fertilisation levels in a soil-specific way. The resource consumption is lower for non-sandy soils than for sandy soils, but entails however more eutrophication. Farm management seems to have less influence on the environmental impact when considering the CEENE only. But farm management choices such as fertiliser type have a large effect on emission-related problems (e.g. eutrophication and acidification). In contrast, year-to-year weather variation results in large differences in the environmental footprint. The difference in impact results between favourable and poor environmental conditions amounts to 19% and 17% in terms of resources and emissions respectively, and irrigation clearly is an unfavourable environmental process. The best environmental performance is obtained by innovation as plant breeding results in a steadily increasing yield over 25 years. Finally, a comparison is made between grain maize production in Flanders and a generically applied dataset, based on Swiss practices. These very different results endorse the importance of using local data to conduct LCA of plant production systems. The results of this study show decision makers and farmers how they can improve the

  19. INTRINSIC FACTORS AND FIRM FINANCIAL ANALYSIS WITH TRIPPLE BOTTOM LINES AS INTERVENING VARIABLE AGAINST FIRM VALUE Empirical Studies on Property and Real Estate Companies Year 2010-2013

    Directory of Open Access Journals (Sweden)

    Mia Andika Sari

    2016-09-01

    Full Text Available This research conducted to examine the influence of intrinsic factors which being peroxided with Capital Structure, Firm Size, Firm Age and Financial factors that being peroxided with liquidity, profitability also with another activities using triple bottom lines as Intervening Variable against Firm Value of Property Industries. The data that being used in this study were obtained from published financial statements during the period 2010 to 2013, as well as annual reports that can be accessed through the IDX website. Data analysis technique used in this study is a regression with panel data and path analysis. The results of this research showed that intrinsic factors and financial variables have a significant influence on the firm value, as well as intrinsic factors and financial variables have a significant influence on the triple bottom lines. From the results of path analysis demonstrated that the indirect effect using the triple bottom lines as a intervening variable was greater than the direct effect.

  20. Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis

    Science.gov (United States)

    Szabo, J.K.; Fedriani, E.M.; Segovia-Gonzalez, M. M.; Astheimer, L.B.; Hooper, M.J.

    2010-01-01

    This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 19982004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types. ?? 2010 World Scientific Publishing Company.

  1. 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.

  2. Analysis of source regions and meteorological factors for the variability of spring PM10 concentrations in Seoul, Korea

    Science.gov (United States)

    Lee, Jangho; Kim, Kwang-Yul

    2018-02-01

    CSEOF analysis is applied for the springtime (March, April, May) daily PM10 concentrations measured at 23 Ministry of Environment stations in Seoul, Korea for the period of 2003-2012. Six meteorological variables at 12 pressure levels are also acquired from the ERA Interim reanalysis datasets. CSEOF analysis is conducted for each meteorological variable over East Asia. Regression analysis is conducted in CSEOF space between the PM10 concentrations and individual meteorological variables to identify associated atmospheric conditions for each CSEOF mode. By adding the regressed loading vectors with the mean meteorological fields, the daily atmospheric conditions are obtained for the first five CSEOF modes. Then, HYSPLIT model is run with the atmospheric conditions for each CSEOF mode in order to back trace the air parcels and dust reaching Seoul. The K-means clustering algorithm is applied to identify major source regions for each CSEOF mode of the PM10 concentrations in Seoul. Three main source regions identified based on the mean fields are: (1) northern Taklamakan Desert (NTD), (2) Gobi Desert and (GD), and (3) East China industrial area (ECI). The main source regions for the mean meteorological fields are consistent with those of previous study; 41% of the source locations are located in GD followed by ECI (37%) and NTD (21%). Back trajectory calculations based on CSEOF analysis of meteorological variables identify distinct source characteristics associated with each CSEOF mode and greatly facilitate the interpretation of the PM10 variability in Seoul in terms of transportation route and meteorological conditions including the source area.

  3. Characterization factors for terrestrial acidification at the global scale: a systematic analysis of spatial variability and uncertainty.

    Science.gov (United States)

    Roy, Pierre-Olivier; Azevedo, Ligia B; Margni, Manuele; van Zelm, Rosalie; Deschênes, Louise; Huijbregts, Mark A J

    2014-12-01

    Characterization factors (CFs) are used in life cycle assessment (LCA) to quantify the potential impact per unit of emission. CFs are obtained from a characterization model which assess the environmental mechanisms along the cause-effect chain linking an emission to its potential damage on a given area of protection, such as loss in ecosystem quality. Up to now, CFs for acidifying emissions did not cover the global scale and were only representative of their characterization model geographical scope. Consequently, current LCA practices implicitly assume that all emissions from a global supply chain occur within the continent referring to the characterization method geographical scope. This paper provides worldwide 2°×2.5° spatially-explicit CFs, representing the change in relative loss of terrestrial vascular plant species due to an emission change of nitrogen oxides (NOx), ammonia (NH3) and sulfur dioxide (SO2). We found that spatial variability in the CFs is much larger compared to statistical uncertainty (six orders of magnitude vs. two orders of magnitude). Spatial variability is mainly caused by the atmospheric fate factor and soil sensitivity factor, while the ecological effect factor is the dominant contributor to the statistical uncertainty. The CFs provided in our study allow the worldwide spatially explicit evaluation of life cycle impacts related to acidifying emissions. This opens the door to evaluate regional life cycle emissions of different products in a global economy. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. Absence of prognostic value of nuclear shape factor analysis in colorectal carcinoma: relevance of interobserver and intraobserver variability.

    Science.gov (United States)

    Di Fabio, Francesco; Shrier, Ian; Bégin, Louis R; Gordon, Philip H

    2008-12-01

    Several retrospective studies, including our previous investigation, have shown a prognostic value of nuclear shape factor in colorectal carcinomas. This prospective study was designed to assess the reliability of nuclear shape factor determined by nuclear morphometry and to confirm its prognostic value. Ninety-eight patients who underwent colorectal carcinoma resection were prospectively enrolled. Measurement of nuclear shape factor was performed by using a computer-based image analysis system. Nuclear shape factor was defined as the degree of circularity of the nucleus (1.0 for a perfect circle and values by American Joint Committee on Cancer stage were: 0.73 (0.07) in Stage I, 0.74 (0.06) in Stage II, and 0.75 (0.05) in Stage III carcinomas (P = 0.78, ANOVA). The intraobserver agreement was poor for observer A (r = 0.28) and practically nonexistent for observer B (r = -0.004, Pearson correlation). The intraclass coefficient for interobserver agreement was practically nonexistent. No significant association between nuclear shape factor and ten-year survival was found. Our prospective results, as opposed to our previous retrospective results, suggest that the reliability for nuclear shape factor morphometric analysis is very poor. We failed to confirm a prognostic value for nuclear shape factor in colorectal carcinoma.

  5. Meta-Analysis of the Effects of Foods and Derived Products Containing Ellagitannins and Anthocyanins on Cardiometabolic Biomarkers: Analysis of Factors Influencing Variability of the Individual Responses

    Science.gov (United States)

    Chambers, Karen; Andrés-Lacueva, Cristina; Konic Ristic, Aleksandra; Hollands, Wendy J.; Kroon, Paul A.; Rodríguez-Mateos, Ana; Istas, Geoffrey; Kontogiorgis, Christos A.; Morand, Christine; Espín, Juan Carlos

    2018-01-01

    Understanding interindividual variability in response to dietary polyphenols remains essential to elucidate their effects on cardiometabolic disease development. A meta-analysis of 128 randomized clinical trials was conducted to investigate the effects of berries and red grapes/wine as sources of anthocyanins and of nuts and pomegranate as sources of ellagitannins on a range of cardiometabolic risk biomarkers. The potential influence of various demographic and lifestyle factors on the variability in the response to these products were explored. Both anthocyanin- and ellagitannin-containing products reduced total-cholesterol with nuts and berries yielding more significant effects than pomegranate and grapes. Blood pressure was significantly reduced by the two main sources of anthocyanins, berries and red grapes/wine, whereas waist circumference, LDL-cholesterol, triglycerides, and glucose were most significantly lowered by the ellagitannin-products, particularly nuts. Additionally, we found an indication of a small increase in HDL-cholesterol most significant with nuts and, in flow-mediated dilation by nuts and berries. Most of these effects were detected in obese/overweight people but we found limited or non-evidence in normoweight individuals or of the influence of sex or smoking status. The effects of other factors, i.e., habitual diet, health status or country where the study was conducted, were inconsistent and require further investigation. PMID:29495642

  6. Meta-Analysis of the Effects of Foods and Derived Products Containing Ellagitannins and Anthocyanins on Cardiometabolic Biomarkers: Analysis of Factors Influencing Variability of the Individual Responses

    Directory of Open Access Journals (Sweden)

    María-Teresa García-Conesa

    2018-02-01

    Full Text Available Understanding interindividual variability in response to dietary polyphenols remains essential to elucidate their effects on cardiometabolic disease development. A meta-analysis of 128 randomized clinical trials was conducted to investigate the effects of berries and red grapes/wine as sources of anthocyanins and of nuts and pomegranate as sources of ellagitannins on a range of cardiometabolic risk biomarkers. The potential influence of various demographic and lifestyle factors on the variability in the response to these products were explored. Both anthocyanin- and ellagitannin-containing products reduced total-cholesterol with nuts and berries yielding more significant effects than pomegranate and grapes. Blood pressure was significantly reduced by the two main sources of anthocyanins, berries and red grapes/wine, whereas waist circumference, LDL-cholesterol, triglycerides, and glucose were most significantly lowered by the ellagitannin-products, particularly nuts. Additionally, we found an indication of a small increase in HDL-cholesterol most significant with nuts and, in flow-mediated dilation by nuts and berries. Most of these effects were detected in obese/overweight people but we found limited or non-evidence in normoweight individuals or of the influence of sex or smoking status. The effects of other factors, i.e., habitual diet, health status or country where the study was conducted, were inconsistent and require further investigation.

  7. Unbiased proteomics analysis demonstrates significant variability in mucosal immune factor expression depending on the site and method of collection.

    Directory of Open Access Journals (Sweden)

    Kenzie M Birse

    Full Text Available Female genital tract secretions are commonly sampled by lavage of the ectocervix and vaginal vault or via a sponge inserted into the endocervix for evaluating inflammation status and immune factors critical for HIV microbicide and vaccine studies. This study uses a proteomics approach to comprehensively compare the efficacy of these methods, which sample from different compartments of the female genital tract, for the collection of immune factors. Matching sponge and lavage samples were collected from 10 healthy women and were analyzed by tandem mass spectrometry. Data was analyzed by a combination of differential protein expression analysis, hierarchical clustering and pathway analysis. Of the 385 proteins identified, endocervical sponge samples collected nearly twice as many unique proteins as cervicovaginal lavage (111 vs. 61 with 55% of proteins common to both (213. Each method/site identified 73 unique proteins that have roles in host immunity according to their gene ontology. Sponge samples enriched for specific inflammation pathways including acute phase response proteins (p = 3.37×10(-24 and LXR/RXR immune activation pathways (p = 8.82×10(-22 while the role IL-17A in psoriasis pathway (p = 5.98×10(-4 and the complement system pathway (p = 3.91×10(-3 were enriched in lavage samples. Many host defense factors were differentially enriched (p<0.05 between sites including known/potential antimicrobial factors (n = 21, S100 proteins (n = 9, and immune regulatory factors such as serpins (n = 7. Immunoglobulins (n = 6 were collected at comparable levels in abundance in each site although 25% of those identified were unique to sponge samples. This study demonstrates significant differences in types and quantities of immune factors and inflammation pathways collected by each sampling technique. Therefore, clinical studies that measure mucosal immune activation or factors assessing HIV transmission should utilize

  8. The influence of biological and technical factors on quantitative analysis of amyloid PET: Points to consider and recommendations for controlling variability in longitudinal data.

    Science.gov (United States)

    Schmidt, Mark E; Chiao, Ping; Klein, Gregory; Matthews, Dawn; Thurfjell, Lennart; Cole, Patricia E; Margolin, Richard; Landau, Susan; Foster, Norman L; Mason, N Scott; De Santi, Susan; Suhy, Joyce; Koeppe, Robert A; Jagust, William

    2015-09-01

    In vivo imaging of amyloid burden with positron emission tomography (PET) provides a means for studying the pathophysiology of Alzheimer's and related diseases. Measurement of subtle changes in amyloid burden requires quantitative analysis of image data. Reliable quantitative analysis of amyloid PET scans acquired at multiple sites and over time requires rigorous standardization of acquisition protocols, subject management, tracer administration, image quality control, and image processing and analysis methods. We review critical points in the acquisition and analysis of amyloid PET, identify ways in which technical factors can contribute to measurement variability, and suggest methods for mitigating these sources of noise. Improved quantitative accuracy could reduce the sample size necessary to detect intervention effects when amyloid PET is used as a treatment end point and allow more reliable interpretation of change in amyloid burden and its relationship to clinical course. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  9. Analysis of acoustic cardiac signals for heart rate variability and murmur detection using nonnegative matrix factorization-based hierarchical decomposition

    DEFF Research Database (Denmark)

    Shah, Ghafoor; Koch, Peter; Papadias, Constantinos B.

    2014-01-01

    The detection of heart rate variability (HRV) via cardiac auscultation examination can be a useful and inexpensive tool which, however, is challenging in the presence of pathological signals and murmurs. The aim of this research is to analyze acoustic cardiac signals for HRV and murmur detection...

  10. Variable Eddington factors and flux-limiting diffusion coefficients

    International Nuclear Information System (INIS)

    Whalen, P.P.

    1982-01-01

    Variable Eddington factors and flux limiting diffusion coefficients arise in two common techniques of closing the moment equations of transport. The first two moment equations of the full transport equation are still frequently used to solve many problems of radiative or particle transport. An approximate analysis, developed by Levermore, exhibits the relation between the coefficients of the two different techniques. This analysis is described and then used to test the validity of several commonly used flux limiters and Eddington factors. All of the ad-hoc flux limiters have limited validity. All of the variable Eddington factors derived from some underlying description of the angular distribution function are generally valid. The use of coefficients from Minerbo's elegant maximum entropy Eddington factor analysis is suggested for use in either flux limited diffusion or variable Eddington factor equations

  11. An analysis of factors associated with influenza, pneumoccocal, Tdap, and herpes zoster vaccine uptake in the US adult population and corresponding inter-state variability.

    Science.gov (United States)

    La, Elizabeth M; Trantham, Laurel; Kurosky, Samantha K; Odom, Dawn; Aris, Emmanuel; Hogea, Cosmina

    2018-02-01

    Despite longstanding recommendations for routine vaccination against influenza; pneumococcal; tetanus, diphtheria, acellular pertussis (Tdap); and herpes zoster (HZ) among the United States general adult population, vaccine uptake remains low. Understanding factors that influence adult vaccination and coverage variability beyond the national level are important steps toward developing targeted strategies for increasing vaccination coverage. A retrospective analysis was conducted using data from the Behavioral Risk Factor Surveillance System (2011-2014). Multivariable logistic regression modeling was employed to identify individual factors associated with vaccination (socio-demographics, health status, healthcare utilization, state of residence) and generate adjusted vaccination coverage and compliance estimates nationally and by state. Results indicated that multiple characteristics were consistently associated with a higher likelihood of vaccination across all four vaccines, including female sex, increased educational attainment, and annual household income. Model-adjusted vaccination coverage estimates varied widely by state, with inter-state variability for the most recent year of data as follows: influenza (aged ≥18 years) 30.2-49.5%; pneumococcal (aged ≥65 years) 64.0-74.7%; Tdap (aged ≥18 years) 18.7-46.6%; and HZ (aged ≥60 years) 21.3-42.9%. Model-adjusted compliance with age-appropriate recommendations across vaccines was low and also varied by state: influenza+Tdap (aged 18-59 years) 7.9-24.7%; influenza+Tdap+HZ (aged 60-64 years) 4.1-14.4%; and influenza+Tdap+HZ+pneumococcal (aged ≥65 years) 3.0-18.3%. In summary, after adjusting for individual characteristics associated with vaccination, substantial heterogeneity across states remained, suggesting that other local factors (e.g. state policies) may be impacting adult vaccines uptake. Further research is needed to understand such factors, focusing on differences between states with high versus

  12. An Instrumental Variable Probit (IVP Analysis on Depressed Mood in Korea: The Impact of Gender Differences and Other Socio-Economic Factors

    Directory of Open Access Journals (Sweden)

    Lara Gitto

    2015-08-01

    Full Text Available Background Depression is a mental health state whose frequency has been increasing in modern societies. It imposes a great burden, because of the strong impact on people’s quality of life and happiness. Depression can be reliably diagnosed and treated in primary care: if more people could get effective treatments earlier, the costs related to depression would be reversed. The aim of this study was to examine the influence of socio-economic factors and gender on depressed mood, focusing on Korea. In fact, in spite of the great amount of empirical studies carried out for other countries, few epidemiological studies have examined the socio-economic determinants of depression in Korea and they were either limited to samples of employed women or did not control for individual health status. Moreover, as the likely data endogeneity (i.e. the possibility of correlation between the dependent variable and the error term as a result of autocorrelation or simultaneity, such as, in this case, the depressed mood due to health factors that, in turn might be caused by depression, might bias the results, the present study proposes an empirical approach, based on instrumental variables, to deal with this problem. Methods Data for the year 2008 from the Korea National Health and Nutrition Examination Survey (KNHANES were employed. About seven thousands of people (N= 6,751, of which 43% were males and 57% females, aged from 19 to 75 years old, were included in the sample considered in the analysis. In order to take into account the possible endogeneity of some explanatory variables, two Instrumental Variables Probit (IVP regressions were estimated; the variables for which instrumental equations were estimated were related to the participation of women to the workforce and to good health, as reported by people in the sample. Explanatory variables were related to age, gender, family factors (such as the number of family members and marital status and socio

  13. An Instrumental Variable Probit (IVP) analysis on depressed mood in Korea: the impact of gender differences and other socio-economic factors.

    Science.gov (United States)

    Gitto, Lara; Noh, Yong-Hwan; Andrés, Antonio Rodríguez

    2015-04-16

    Depression is a mental health state whose frequency has been increasing in modern societies. It imposes a great burden, because of the strong impact on people's quality of life and happiness. Depression can be reliably diagnosed and treated in primary care: if more people could get effective treatments earlier, the costs related to depression would be reversed. The aim of this study was to examine the influence of socio-economic factors and gender on depressed mood, focusing on Korea. In fact, in spite of the great amount of empirical studies carried out for other countries, few epidemiological studies have examined the socio-economic determinants of depression in Korea and they were either limited to samples of employed women or did not control for individual health status. Moreover, as the likely data endogeneity (i.e. the possibility of correlation between the dependent variable and the error term as a result of autocorrelation or simultaneity, such as, in this case, the depressed mood due to health factors that, in turn might be caused by depression), might bias the results, the present study proposes an empirical approach, based on instrumental variables, to deal with this problem. Data for the year 2008 from the Korea National Health and Nutrition Examination Survey (KNHANES) were employed. About seven thousands of people (N= 6,751, of which 43% were males and 57% females), aged from 19 to 75 years old, were included in the sample considered in the analysis. In order to take into account the possible endogeneity of some explanatory variables, two Instrumental Variables Probit (IVP) regressions were estimated; the variables for which instrumental equations were estimated were related to the participation of women to the workforce and to good health, as reported by people in the sample. Explanatory variables were related to age, gender, family factors (such as the number of family members and marital status) and socio-economic factors (such as education

  14. Impact of socio-demographic factors on the mitigating actions for climate change: a path analysis with mediating effects of attitudinal variables.

    Science.gov (United States)

    Masud, Muhammad Mehedi; Akhatr, Rulia; Nasrin, Shamima; Adamu, Ibrahim Mohammed

    2017-12-01

    Socio-demographic factors play a significant role in increasing the individual's climate change awareness and in setting a favorable individual attitude towards its mitigation. To better understand how the adversative effects of climate change can be mitigated, this study attempts to investigate the impact of socio-demographic factors on the mitigating actions of the individuals (MAOI) on climate change. Qualitative data were collected from a face-to-face survey of 360 respondents in the Kuala Lumpur region of Malaysia through a close-ended questionnaire. Analysis was conducted on the mediating effects of attitudinal variables through the path model by using the SEM. Findings indicate that the socio-demographic factors such as gender, age, education, income, and ethnicity can greatly influence the individual's awareness, attitude, risk perception, and knowledge of climate change issues. The results drawn from this study also revealed that the attitudinal factors act as a mediating effect between the socio-demographic factors and the MAOI, thereby, indicating that both the socio-demographic factors and the attitudinal factors have significant effects on the MAOI towards climate change. The outcome of this study can help policy makers and other private organizations to decide on the appropriate actions to take in managing climate change effects. These actions which encompass improving basic climate change education and making the public more aware of the local dimensions of climate change are important for harnessing public engagement and support that can also stimulate climate change awareness and promote mitigating actions to n protect the environment from the impact of climate change.

  15. Interplay Among Psychopathologic Variables, Personal Resources, Context-Related Factors, and Real-life Functioning in Individuals With Schizophrenia: A Network Analysis.

    Science.gov (United States)

    Galderisi, Silvana; Rucci, Paola; Kirkpatrick, Brian; Mucci, Armida; Gibertoni, Dino; Rocca, Paola; Rossi, Alessandro; Bertolino, Alessandro; Strauss, Gregory P; Aguglia, Eugenio; Bellomo, Antonello; Murri, Martino Belvederi; Bucci, Paola; Carpiniello, Bernardo; Comparelli, Anna; Cuomo, Alessandro; De Berardis, Domenico; Dell'Osso, Liliana; Di Fabio, Fabio; Gelao, Barbara; Marchesi, Carlo; Monteleone, Palmiero; Montemagni, Cristiana; Orsenigo, Giulia; Pacitti, Francesca; Roncone, Rita; Santonastaso, Paolo; Siracusano, Alberto; Vignapiano, Annarita; Vita, Antonio; Zeppegno, Patrizia; Maj, Mario

    2018-04-01

    Enhanced understanding of factors associated with symptomatic and functional recovery is instrumental to designing personalized treatment plans for people with schizophrenia. To date, this is the first study using network analysis to investigate the associations among cognitive, psychopathologic, and psychosocial variables in a large sample of community-dwelling individuals with schizophrenia. To assess the interplay among psychopathologic variables, cognitive dysfunctions, functional capacity, personal resources, perceived stigma, and real-life functioning in individuals with schizophrenia, using a data-driven approach. This multicenter, cross-sectional study involved 26 university psychiatric clinics and/or mental health departments. A total of 921 community-dwelling individuals with a DSM-IV diagnosis of schizophrenia who were stabilized on antipsychotic treatment were recruited from those consecutively presenting to the outpatient units of the sites between March 1, 2012, and September 30, 2013. Statistical analysis was conducted between July 1 and September 30, 2017. Measures covered psychopathologic variables, neurocognition, social cognition, functional capacity, real-life functioning, resilience, perceived stigma, incentives, and service engagement. Of 740 patients (221 women and 519 men; mean [SD] age, 40.0 [10.9] years) with complete data on the 27 study measures, 163 (22.0%) were remitted (with a score of mild or better on 8 core symptoms). The network analysis showed that functional capacity and everyday life skills were the most central and highly interconnected nodes in the network. Psychopathologic variables split in 2 domains, with positive symptoms being one of the most peripheral and least connected nodes. Functional capacity bridged cognition with everyday life skills; the everyday life skills node was connected to disorganization and expressive deficits. Interpersonal relationships and work skills were connected to avolition; the interpersonal

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

    Science.gov (United States)

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

    2010-07-15

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

  17. El Análisis de Covarianza como Mecanismo de Control de Factores de Confusión / Analysis of Covariance as a Methodology to Control Confounding Variables

    Directory of Open Access Journals (Sweden)

    Correa Londoño Guillermo

    2013-08-01

    Full Text Available Resumen. Parte de la variabilidad total en un estudio experimental puede explicarse por factores que son asignados y/o controlados por el investigador y que son de interés primario para este. Asimismo, los experimentos suelen involucrar factores que a pesar de su carácter secundario también afectan la respuesta. El mecanismo más comúnmente usado para controlar el efecto de factores secundarios es el bloqueo. Existen, sin embargo, situaciones en las que la fuente de variación secundaria solamente se reconoce tras haberse iniciado el experimento y/o en las que sus niveles no configuran categorías que permitan agrupar unidades experimentales homogéneas; en tales casos, podría considerarse la utilización de covariables para satisfacer los mismos objetivos que el bloqueo. Para aplicar una adecuada corrección mediante análisis de covarianza deben satisfacerse dos condiciones: la viabilidad y la pertinencia. La viabilidad se refiere a la posibilidad de explicar parte de la variabilidad de la respuesta en función de la covariable, mediante un modelo de regresión. La pertinencia tiene que ver con la adecuación de la corrección aplicada, considerando que al eliminar el efecto de la covariable no se arrastre parte del efecto de los tratamientos. La viabilidad suele evaluarse con apoyo de algún programa estadístico; la pertinencia, por su parte, exige una aproximación conceptual. / Abstract. Some portion of the total variability in an experimental study can be explained by factors that are controlled and/or assigned by the researcher, and that are of his primary interest. Likewise, experiments usually involve factors that, despite their ancillary nature, also affect the response. Blocking is the most widely used mechanism to control the effect of ancillary factors. There are, however, situations in which the secondary source of variation is recognized only after the experiment has been started and/or in which its levels don’t allow to

  18. Phytoscreening with SPME: Variability Analysis.

    Science.gov (United States)

    Limmer, Matt A; Burken, Joel G

    2015-01-01

    Phytoscreening has been demonstrated at a variety of sites over the past 15 years as a low-impact, sustainable tool in delineation of shallow groundwater contaminated with chlorinated solvents. Collection of tree cores is rapid and straightforward, but low concentrations in tree tissues requires sensitive analytics. Solid-phase microextraction (SPME) is amenable to the complex matrix while allowing for solvent-less extraction. Accurate quantification requires the absence of competitive sorption, examined here both in laboratory experiments and through comprehensive examination of field data. Analysis of approximately 2,000 trees at numerous field sites also allowed testing of the tree genus and diameter effects on measured tree contaminant concentrations. Collectively, while these variables were found to significantly affect site-adjusted perchloroethylene (PCE) concentrations, the explanatory power of these effects was small (adjusted R(2) = 0.031). 90th quantile chemical concentrations in trees were significantly reduced by increasing Henry's constant and increasing hydrophobicity. Analysis of replicate tree core data showed no correlation between replicate relative standard deviation (RSD) and wood type or tree diameter, with an overall median RSD of 30%. Collectively, these findings indicate SPME is an appropriate technique for sampling and analyzing chlorinated solvents in wood and that phytoscreening is robust against changes in tree type and diameter.

  19. Operant Variability: A Conceptual Analysis

    Science.gov (United States)

    Barba, Lourenco de Souza

    2012-01-01

    Some researchers claim that variability is an operant dimension of behavior. The present paper reviews the concept of operant behavior and emphasizes that differentiation is the behavioral process that demonstrates an operant relation. Differentiation is conceived as change in the overlap between two probability distributions: the distribution of…

  20. Elimination of chromatographic and mass spectrometric problems in GC-MS analysis of Lavender essential oil by multivariate curve resolution techniques: Improving the peak purity assessment by variable size moving window-evolving factor analysis.

    Science.gov (United States)

    Jalali-Heravi, Mehdi; Moazeni-Pourasil, Roudabeh Sadat; Sereshti, Hassan

    2015-03-01

    In analysis of complex natural matrices by gas chromatography-mass spectrometry (GC-MS), many disturbing factors such as baseline drift, spectral background, homoscedastic and heteroscedastic noise, peak shape deformation (non-Gaussian peaks), low S/N ratio and co-elution (overlapped and/or embedded peaks) lead the researchers to handle them to serve time, money and experimental efforts. This study aimed to improve the GC-MS analysis of complex natural matrices utilizing multivariate curve resolution (MCR) methods. In addition, to assess the peak purity of the two-dimensional data, a method called variable size moving window-evolving factor analysis (VSMW-EFA) is introduced and examined. The proposed methodology was applied to the GC-MS analysis of Iranian Lavender essential oil, which resulted in extending the number of identified constituents from 56 to 143 components. It was found that the most abundant constituents of the Iranian Lavender essential oil are α-pinene (16.51%), camphor (10.20%), 1,8-cineole (9.50%), bornyl acetate (8.11%) and camphene (6.50%). This indicates that the Iranian type Lavender contains a relatively high percentage of α-pinene. Comparison of different types of Lavender essential oils showed the composition similarity between Iranian and Italian (Sardinia Island) Lavenders. Published by Elsevier B.V.

  1. Omitted variable bias in crash reduction factors.

    Science.gov (United States)

    2015-09-01

    Transportation planners and traffic engineers are increasingly turning to crash reduction factors to evaluate changes in road : geometric and design features in order to reduce crashes. Crash reduction factors are typically estimated based on segment...

  2. Harmonic and complex analysis in several variables

    CERN Document Server

    Krantz, Steven G

    2017-01-01

    Authored by a ranking authority in harmonic analysis of several complex variables, this book embodies a state-of-the-art entrée at the intersection of two important fields of research: complex analysis and harmonic analysis. Written with the graduate student in mind, it is assumed that the reader has familiarity with the basics of complex analysis of one and several complex variables as well as with real and functional analysis. The monograph is largely self-contained and develops the harmonic analysis of several complex variables from the first principles. The text includes copious examples, explanations, an exhaustive bibliography for further reading, and figures that illustrate the geometric nature of the subject. Each chapter ends with an exercise set. Additionally, each chapter begins with a prologue, introducing the reader to the subject matter that follows; capsules presented in each section give perspective and a spirited launch to the segment; preludes help put ideas into context. Mathematicians and...

  3. 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

  4. Multiple-locus variable number of tandem repeats fingerprinting (MLVF) and virulence factor analysis of methicillin resistant Staphylococcus aureus SCCmec type III.

    Science.gov (United States)

    Emaneini, Mohammad; Jabalameli, Leila; Iman-Eini, Hossein; Aligholi, Marzieh; Ghasemi, Amir; Nakhjavani, Farrokh Akbari; Taherikalani, Morovat; Khoramian, Babak; Asadollahi, Parisa; Jabalameli, Fereshteh

    2011-01-01

    Methicillin resistant Staphylococcus aureus (MRSA), particularly strains with type III staphylococcal cassette chromosome mec (SCCmec), represent a serious human pathogen in Tehran, Iran. The disease-causing capability depends on their ability to produce a wide variety of virulent factors. The prevalence of exotoxin genes and multiple-locus variable number of tandem repeats fingerprinting (MLVF) profile among MRSA isolates, from patients in Tehran, was evaluated by PCR and Multiplex-PCR. The MLVF typing of 144 MRSA isolates with type III SCCmec produced 5 different MLVF types. Generally, 97.2% (140/144) of all the isolates were positive for at least one of the tested exotoxin genes. The most prevalent genes were hld, found in 87.5% (126/144) of the isolates followed by lukE-lukD and hla found in 72.9% (105/144) and 70.1% (101/144) of the isolates, respectively. The tst gene, belonging to MLVF types I, IV and V, was found among three of the isolates from blood and wound samples. The sea gene was detected in 58.3% (84/144) of the isolates and the sed and see genes were found in one isolate with MLVF type V. The coexistence of genes was observed in the 87.5% (126/144) of the isolates. The rate of coexistence of hld with lukE-lukD, hla with lukE-lukD and sea with lukE-lukD were 66.7% (96/144), 44.4% (64/144) and 44.4% (64/144), respectively. The present study demonstrated that MRSA strains with type III SCCmec show different MLVF patterns and exotoxin profiles.

  5. Influence of environmental factors on birth weight variability of ...

    African Journals Online (AJOL)

    Administrator

    2011-05-30

    May 30, 2011 ... significant (P < 0.05). Type of birth also had effect on the body weight of lambs at birth in both Pirot and ... Key words: Environmental factors, birth weight variability, indigenous sheep. ... breeding plans to improve production.

  6. 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

  7. Robust cluster analysis and variable selection

    CERN Document Server

    Ritter, Gunter

    2014-01-01

    Clustering remains a vibrant area of research in statistics. Although there are many books on this topic, there are relatively few that are well founded in the theoretical aspects. In Robust Cluster Analysis and Variable Selection, Gunter Ritter presents an overview of the theory and applications of probabilistic clustering and variable selection, synthesizing the key research results of the last 50 years. The author focuses on the robust clustering methods he found to be the most useful on simulated data and real-time applications. The book provides clear guidance for the varying needs of bot

  8. Scalable conditional induction variables (CIV) analysis

    DEFF Research Database (Denmark)

    Oancea, Cosmin Eugen; Rauchwerger, Lawrence

    2015-01-01

    parallelizing compiler and evaluated its impact on five Fortran benchmarks. We have found that that there are many important loops using CIV subscripts and that our analysis can lead to their scalable parallelization. This in turn has led to the parallelization of the benchmark programs they appear in.......Subscripts using induction variables that cannot be expressed as a formula in terms of the enclosing-loop indices appear in the low-level implementation of common programming abstractions such as filter, or stack operations and pose significant challenges to automatic parallelization. Because...... the complexity of such induction variables is often due to their conditional evaluation across the iteration space of loops we name them Conditional Induction Variables (CIV). This paper presents a flow-sensitive technique that summarizes both such CIV-based and affine subscripts to program level, using the same...

  9. Prognostic factors in metastatic spinal cord compression: a prospective study using multivariate analysis of variables influencing survival and gait function in 153 patients

    International Nuclear Information System (INIS)

    Helweg-Larsen, Susanne; Soerensen, Per Soelberg; Kreiner, Svend

    2000-01-01

    Purpose: Based on a very large patient cohort followed prospectively for at least a year or until death, we analyzed the prognostic significance of various clinical and radiological variables on posttreatment ambulatory function and survival. Methods and Materials: During a 3((1)/(2))-year period we prospectively included 153 consecutive patients with a diagnosis of spinal cord compression due to metastatic disease. The patients were followed with regular neurological examinations by the same neurologist for a minimum period of 11 months or until death. The prognostic significance of five variables on gait function and survival time after treatment was analyzed. Results: The type of the primary tumor had a direct influence on the interval between the diagnosis of the primary malignancy and the occurrence of spinal cord compression (p < 0.0005), and on the ambulatory function at time of diagnosis (p = 0.016). There was a clear correlation between the degree of myelographic blockage and gait function (p = 0.000) and between gait function and sensory disturbances (p = 0.000). The final gait was dependent on the gait function at time of diagnosis (p < 0.0005). Survival time after diagnosis depended directly on the time from primary tumor diagnosis until spinal cord compression (p = 0.002), on the ambulatory function at the time of diagnosis (p = 0.018), and on the ambulatory function after treatment. Conclusions: The pretreatment ambulatory function is the main determinant for posttreatment gait function. Survival time is rather short, especially in nonambulatory patients, and can only be improved by restoration of gait function in nonambulatory patients by immediate treatment

  10. Evaluating the underlying factors behind variable rate debt.

    Science.gov (United States)

    McCue, Michael J; Kim, Tae Hyun Tanny

    2007-01-01

    Recent trends show a greater usage of variable rate debt among health care bond issues. In 2004, 63.4% of the total health care bonds issued were variable rate compared with 30.6% in 1995 (Fitch Ratings, 2005). The purpose of this study is to gain a better understanding of the underlying factors, credit spread, issue characteristics, and issuer factors behind why hospitals and health system borrowers select variable rate debt compared with fixed rate debt. From 2000 to 2004, this study sampled 230 newly issued tax-exempt bonds issued by acute care hospitals and health care systems that included both variable and fixed rate debt issues. Using a logistic regression model, hospitals with variable rate debt issues were assigned a value of 1, whereas hospitals with fixed rate debt issues were assigned a value of 0. This study found a positive association between bond insurance and variable rate debt and a negative association between callable feature and variable rate debt. Facilities located in certificate-of-need states that possessed higher case mix acuity, earned higher profit margins, generated higher debt service coverage, and held less debt were more likely to issue variable rate debt. Overall, hospital managers and board members of hospitals possessing a strong financial performance have an interest in utilizing variable rate debt to lower their cost of capital. In addition, this outcome may also reflect that investment bankers are doing a better job in educating senior hospital management about the interest rate savings benefit of variable rate compared with fixed rate debt.

  11. "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.

  12. Influence of environmental factors on birth weight variability of ...

    African Journals Online (AJOL)

    The present investigation was carried out to study the influence of environmental factors on the birth weight variability of two breeds of sheep. Animals used in this research were taken from the Pirot and Svrljig indigenous sheep breeds. The data were collected from 1999 to 2009 and were analyzed to determine the effect of ...

  13. Variability in wheat: factors affecting its nutritional value

    NARCIS (Netherlands)

    Gutierrez del Alamo Oms, A.; Verstegen, M.W.A.; Hartog, den L.A.; Villamide, M.J.

    2008-01-01

    Wheat is a common raw material used to provide energy in broiler diets. Its apparent metabolisable energy and its influence on broiler performance varies between wheat samples. Reasons for that variability can be classified as intrinsic (variety, chemical composition) and extrinsic factors (growing

  14. Scalable conditional induction variables (CIV) analysis

    KAUST Repository

    Oancea, Cosmin E.

    2015-02-01

    Subscripts using induction variables that cannot be expressed as a formula in terms of the enclosing-loop indices appear in the low-level implementation of common programming abstractions such as Alter, or stack operations and pose significant challenges to automatic parallelization. Because the complexity of such induction variables is often due to their conditional evaluation across the iteration space of loops we name them Conditional Induction Variables (CIV). This paper presents a flow-sensitive technique that summarizes both such CIV-based and affine subscripts to program level, using the same representation. Our technique requires no modifications of our dependence tests, which is agnostic to the original shape of the subscripts, and is more powerful than previously reported dependence tests that rely on the pairwise disambiguation of read-write references. We have implemented the CIV analysis in our parallelizing compiler and evaluated its impact on five Fortran benchmarks. We have found that that there are many important loops using CIV subscripts and that our analysis can lead to their scalable parallelization. This in turn has led to the parallelization of the benchmark programs they appear in.

  15. An improved and explicit surrogate variable analysis procedure by coefficient adjustment.

    Science.gov (United States)

    Lee, Seunggeun; Sun, Wei; Wright, Fred A; Zou, Fei

    2017-06-01

    Unobserved environmental, demographic, and technical factors can negatively affect the estimation and testing of the effects of primary variables. Surrogate variable analysis, proposed to tackle this problem, has been widely used in genomic studies. To estimate hidden factors that are correlated with the primary variables, surrogate variable analysis performs principal component analysis either on a subset of features or on all features, but weighting each differently. However, existing approaches may fail to identify hidden factors that are strongly correlated with the primary variables, and the extra step of feature selection and weight calculation makes the theoretical investigation of surrogate variable analysis challenging. In this paper, we propose an improved surrogate variable analysis using all measured features that has a natural connection with restricted least squares, which allows us to study its theoretical properties. Simulation studies and real data analysis show that the method is competitive to state-of-the-art methods.

  16. Capturing heterogeneity in gene expression studies by surrogate variable analysis.

    Directory of Open Access Journals (Sweden)

    Jeffrey T Leek

    2007-09-01

    Full Text Available It has unambiguously been shown that genetic, environmental, demographic, and technical factors may have substantial effects on gene expression levels. In addition to the measured variable(s of interest, there will tend to be sources of signal due to factors that are unknown, unmeasured, or too complicated to capture through simple models. We show that failing to incorporate these sources of heterogeneity into an analysis can have widespread and detrimental effects on the study. Not only can this reduce power or induce unwanted dependence across genes, but it can also introduce sources of spurious signal to many genes. This phenomenon is true even for well-designed, randomized studies. We introduce "surrogate variable analysis" (SVA to overcome the problems caused by heterogeneity in expression studies. SVA can be applied in conjunction with standard analysis techniques to accurately capture the relationship between expression and any modeled variables of interest. We apply SVA to disease class, time course, and genetics of gene expression studies. We show that SVA increases the biological accuracy and reproducibility of analyses in genome-wide expression studies.

  17. A Systematic Review and Meta-Analysis of the Effects of Flavanol-Containing Tea, Cocoa and Apple Products on Body Composition and Blood Lipids: Exploring the Factors Responsible for Variability in Their Efficacy

    Science.gov (United States)

    González-Sarrías, Antonio; Pinto, Paula; Dall’Asta, Margherita; Rodríguez-Mateos, Ana; Dumont, Julie; Massaro, Marika; Sánchez-Meca, Julio; Morand, Christine

    2017-01-01

    Several randomized controlled trials (RCTs) and meta-analyses support the benefits of flavanols on cardiometabolic health, but the factors affecting variability in the responses to these compounds have not been properly assessed. The objectives of this meta-analysis were to systematically collect the RCTs-based-evidence of the effects of flavanol-containing tea, cocoa and apple products on selected biomarkers of cardiometabolic risk and to explore the influence of various factors on the variability in the responses to the consumption of these products. A total of 120 RCTs were selected. Despite a high heterogeneity, the intake of the flavanol-containing products was associated using a random model with changes (reported as standardized difference in means (SDM)) in body mass index (−0.15, p < 0.001), waist circumference (−0.29, p < 0.001), total-cholesterol (−0.21, p < 0.001), LDL-cholesterol (−0.23, p < 0.001), and triacylglycerides (−0.11, p = 0.027), and with an increase of HDL-cholesterol (0.15, p = 0.005). Through subgroup analyses, we showed the influence of baseline-BMI, sex, source/form of administration, medication and country of investigation on some of the outcome measures and suggest that flavanols may be more effective in specific subgroups such as those with a BMI ≥ 25.0 kg/m2, non-medicated individuals or by specifically using tea products. This meta-analysis provides the first robust evidence of the effects induced by the consumption of flavanol-containing tea, cocoa and apple products on weight and lipid biomarkers and shows the influence of various factors that can affect their bioefficacy in humans. Of note, some of these effects are quantitatively comparable to those produced by drugs, life-style changes or other natural products. Further, RCTs in well-characterized populations are required to fully comprehend the factors affecting inter-individual responses to flavanol and thereby improve flavanols efficacy in the prevention of

  18. A Systematic Review and Meta-Analysis of the Effects of Flavanol-Containing Tea, Cocoa and Apple Products on Body Composition and Blood Lipids: Exploring the Factors Responsible for Variability in Their Efficacy

    Directory of Open Access Journals (Sweden)

    Antonio González-Sarrías

    2017-07-01

    Full Text Available Several randomized controlled trials (RCTs and meta-analyses support the benefits of flavanols on cardiometabolic health, but the factors affecting variability in the responses to these compounds have not been properly assessed. The objectives of this meta-analysis were to systematically collect the RCTs-based-evidence of the effects of flavanol-containing tea, cocoa and apple products on selected biomarkers of cardiometabolic risk and to explore the influence of various factors on the variability in the responses to the consumption of these products. A total of 120 RCTs were selected. Despite a high heterogeneity, the intake of the flavanol-containing products was associated using a random model with changes (reported as standardized difference in means (SDM in body mass index (−0.15, p < 0.001, waist circumference (−0.29, p < 0.001, total-cholesterol (−0.21, p < 0.001, LDL-cholesterol (−0.23, p < 0.001, and triacylglycerides (−0.11, p = 0.027, and with an increase of HDL-cholesterol (0.15, p = 0.005. Through subgroup analyses, we showed the influence of baseline-BMI, sex, source/form of administration, medication and country of investigation on some of the outcome measures and suggest that flavanols may be more effective in specific subgroups such as those with a BMI ≥ 25.0 kg/m2, non-medicated individuals or by specifically using tea products. This meta-analysis provides the first robust evidence of the effects induced by the consumption of flavanol-containing tea, cocoa and apple products on weight and lipid biomarkers and shows the influence of various factors that can affect their bioefficacy in humans. Of note, some of these effects are quantitatively comparable to those produced by drugs, life-style changes or other natural products. Further, RCTs in well-characterized populations are required to fully comprehend the factors affecting inter-individual responses to flavanol and thereby improve flavanols efficacy in the

  19. 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.

  20. 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...

  1. Scalable conditional induction variables (CIV) analysis

    KAUST Repository

    Oancea, Cosmin E.; Rauchwerger, Lawrence

    2015-01-01

    challenges to automatic parallelization. Because the complexity of such induction variables is often due to their conditional evaluation across the iteration space of loops we name them Conditional Induction Variables (CIV). This paper presents a flow

  2. Variability, Predictability, and Race Factors Affecting Performance in Elite Biathlon.

    Science.gov (United States)

    Skattebo, Øyvind; Losnegard, Thomas

    2018-03-01

    To investigate variability, predictability, and smallest worthwhile performance enhancement in elite biathlon sprint events. In addition, the effects of race factors on performance were assessed. Data from 2005 to 2015 including >10,000 and >1000 observations for each sex for all athletes and annual top-10 athletes, respectively, were included. Generalized linear mixed models were constructed based on total race time, skiing time, shooting time, and proportions of targets hit. Within-athlete race-to-race variability was expressed as coefficient of variation of performance times and standard deviation (SD) in proportion units (%) of targets hit. The models were adjusted for random and fixed effects of subject identity, season, event identity, and race factors. The within-athlete variability was independent of sex and performance standard of athletes: 2.5-3.2% for total race time, 1.5-1.8% for skiing time, and 11-15% for shooting times. The SD of the proportion of hits was ∼10% in both shootings combined (meaning ±1 hit in 10 shots). The predictability in total race time was very high to extremely high for all athletes (ICC .78-.84) but trivial for top-10 athletes (ICC .05). Race times during World Championships and Olympics were ∼2-3% faster than in World Cups. Moreover, race time increased by ∼2% per 1000 m of altitude, by ∼5% per 1% of gradient, by 1-2% per 1 m/s of wind speed, and by ∼2-4% on soft vs hard tracks. Researchers and practitioners should focus on strategies that improve biathletes' performance by at least 0.8-0.9%, corresponding to the smallest worthwhile enhancement (0.3 × within-athlete variability).

  3. Multiwavelength Variability Analysis of 3C 279

    Energy Technology Data Exchange (ETDEWEB)

    Patiño-Álvarez, Víctor M. [Max-Planck-Institut für Radioastronomie, Bonn (Germany); Fernandes, Sunil [Department of Physics and Astronomy, University of Texas at San Antonio, San Antonio, TX (United States); Chavushyan, Vahram [Instituto Nacional de Astrofísica Óptica y Electrónica, Puebla (Mexico); López-Rodríguez, Erique [SOFIA Science Center, NASA Ames Center, Mountain View, CA (United States); León-Tavares, Jonathan [Centre for Remote Sensing and Earth Observation Processes (TAP), Flemish Institute for Technological Research (VITO), Mol (Belgium); Schlegel, Eric M. [Department of Physics and Astronomy, University of Texas at San Antonio, San Antonio, TX (United States); Carrasco, Luis; Valdés, José R.; Carramiñana, Alberto, E-mail: patinoavm@mpifr-bonn.mpg.de [Instituto Nacional de Astrofísica Óptica y Electrónica, Puebla (Mexico)

    2017-11-23

    We present a multifrequency analysis of the variability in the flat-spectrum radio quasar 3C 279 from 2008 to 2014. Our multiwavelength datasets range from 1 mm to gamma-rays, with additional optical polarimetry. Cross-correlation analysis shows a significant correlation between the UV continuum emission, the optical and NIR bands, at a delay consistent with zero, implying co-spatial emission regions. We also find a correlation between the UV continuum and the 1 mm data, which implies that the dominant process in producing the UV continuum is synchrotron emission. Based on the behavior of the gamma-ray light curve with respect to other bands, we identified three different activity periods. During period A we find a significant correlation at zero delay between the UV continuum and the gamma-rays, implying co-spatial emission regions which points toward synchrotron self-Compton as dominant gamma-ray emission mechanism. During period C we find a delay between the UV continuum and the gamma-rays, as well as a correlation at zero delay between X-rays and gamma-rays, both results implying that external inverse Compton is the dominant gamma-ray emission mechanism. During period B there are multiple flares in the bands from 1 mm to UV, however, none of these show a counterpart in the gamma-rays band. We propose that this is caused by an increase in the gamma-ray opacity due to electron-positron pair production.

  4. 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...

  5. Multiwavelength Variability Analysis of 3C 279

    Directory of Open Access Journals (Sweden)

    Víctor M. Patiño-Álvarez

    2017-11-01

    Full Text Available We present a multifrequency analysis of the variability in the flat-spectrum radio quasar 3C 279 from 2008 to 2014. Our multiwavelength datasets range from 1 mm to gamma-rays, with additional optical polarimetry. Cross-correlation analysis shows a significant correlation between the UV continuum emission, the optical and NIR bands, at a delay consistent with zero, implying co-spatial emission regions. We also find a correlation between the UV continuum and the 1 mm data, which implies that the dominant process in producing the UV continuum is synchrotron emission. Based on the behavior of the gamma-ray light curve with respect to other bands, we identified three different activity periods. During period A we find a significant correlation at zero delay between the UV continuum and the gamma-rays, implying co-spatial emission regions which points toward synchrotron self-Compton as dominant gamma-ray emission mechanism. During period C we find a delay between the UV continuum and the gamma-rays, as well as a correlation at zero delay between X-rays and gamma-rays, both results implying that external inverse Compton is the dominant gamma-ray emission mechanism. During period B there are multiple flares in the bands from 1 mm to UV, however, none of these show a counterpart in the gamma-rays band. We propose that this is caused by an increase in the gamma-ray opacity due to electron-positron pair production.

  6. Psychobiological Factors Affecting Cortisol Variability in Human-Dog Dyads.

    Directory of Open Access Journals (Sweden)

    Iris Schöberl

    Full Text Available Stress responses within dyads are modulated by interactions such as mutual emotional support and conflict. We investigated dyadic psychobiological factors influencing intra-individual cortisol variability in response to different challenging situations by testing 132 owners and their dogs in a laboratory setting. Salivary cortisol was measured and questionnaires were used to assess owner and dog personality as well as owners' social attitudes towards the dog and towards other humans. We calculated the individual coefficient of variance of cortisol (iCV = sd/mean*100 over the different test situations as a parameter representing individual variability of cortisol concentration. We hypothesized that high cortisol variability indicates efficient and adaptive coping and a balanced individual and dyadic social performance. Female owners of male dogs had lower iCV than all other owner gender-dog sex combinations (F = 14.194, p<0.001, whereas owner Agreeableness (NEO-FFI scaled positively with owner iCV (F = 4.981, p = 0.028. Dogs of owners high in Neuroticism (NEO-FFI and of owners who were insecure-ambivalently attached to their dogs (FERT, had low iCV (F = 4.290, p = 0.041 and F = 5.948, p = 0.016, as had dogs of owners with human-directed separation anxiety (RSQ or dogs of owners with a strong desire of independence (RSQ (F = 7.661, p = 0.007 and F = 9.192, p = 0.003. We suggest that both owner and dog social characteristics influence dyadic cortisol variability, with the human partner being more influential than the dog. Our results support systemic approaches (i.e. considering the social context in science and in counselling.

  7. Detailed heart rate variability analysis in athletes.

    Science.gov (United States)

    Kiss, Orsolya; Sydó, Nóra; Vargha, Péter; Vágó, Hajnalka; Czimbalmos, Csilla; Édes, Eszter; Zima, Endre; Apponyi, Györgyi; Merkely, Gergő; Sydó, Tibor; Becker, Dávid; Allison, Thomas G; Merkely, Béla

    2016-08-01

    Heart rate variability (HRV) analysis has been used to evaluate patients with various cardiovascular diseases. While the vast majority of HRV studies have focused on pathological states, our study focuses on the less explored area of HRV analysis across different training intensity and sports. We aimed to measure HRV in healthy elite and masters athletes and compare to healthy, but non-athletic controls. Time-domain HRV analysis was applied in 138 athletes (male 110, age 28.4 ± 8.3) and 100 controls (male 56, age 28.3 ± 6.9) during Holter monitoring (21.3 ± 3.0 h). All studied parameters were higher in elite athletes compared to controls [SDNN (CI) 225.3 (216.2-234.5) vs 158.6 (150.2-167.1) ms; SDNN Index (CI) 99.6 (95.6-103.7) vs 72.4 (68.7-76.2) ms; pNN50 (CI) 24.2 (22.2-26.3) vs 14.4 (12.7-16.3) %; RMSSD (CI) 71.8 (67.6-76.2) vs 50.8 (46.9-54.8) ms; p HRV values than controls, but no significant differences were found between elite athletes and masters athletes. Some parameters were higher in canoeists-kayakers and bicyclists than runners. Lower cut-off values in elite athletes were SDNN: 147.4 ms, SDNN Index: 66.6 ms, pNN50: 9.7 %, RMSSD: 37.9 ms. Autonomic regulation in elite athletes described with HRV is significantly different than in healthy controls. Sports modality and level of performance, but not age- or sex-influenced HRV. Our study provides athletic normal HRV values. Further investigations are needed to determine its role in risk stratification, optimization of training, or identifying overtraining.

  8. Deciphering factors controlling groundwater arsenic spatial variability in Bangladesh

    Science.gov (United States)

    Tan, Z.; Yang, Q.; Zheng, C.; Zheng, Y.

    2017-12-01

    Elevated concentrations of geogenic arsenic in groundwater have been found in many countries to exceed 10 μg/L, the WHO's guideline value for drinking water. A common yet unexplained characteristic of groundwater arsenic spatial distribution is the extensive variability at various spatial scales. This study investigates factors influencing the spatial variability of groundwater arsenic in Bangladesh to improve the accuracy of models predicting arsenic exceedance rate spatially. A novel boosted regression tree method is used to establish a weak-learning ensemble model, which is compared to a linear model using a conventional stepwise logistic regression method. The boosted regression tree models offer the advantage of parametric interaction when big datasets are analyzed in comparison to the logistic regression. The point data set (n=3,538) of groundwater hydrochemistry with 19 parameters was obtained by the British Geological Survey in 2001. The spatial data sets of geological parameters (n=13) were from the Consortium for Spatial Information, Technical University of Denmark, University of East Anglia and the FAO, while the soil parameters (n=42) were from the Harmonized World Soil Database. The aforementioned parameters were regressed to categorical groundwater arsenic concentrations below or above three thresholds: 5 μg/L, 10 μg/L and 50 μg/L to identify respective controlling factors. Boosted regression tree method outperformed logistic regression methods in all three threshold levels in terms of accuracy, specificity and sensitivity, resulting in an improvement of spatial distribution map of probability of groundwater arsenic exceeding all three thresholds when compared to disjunctive-kriging interpolated spatial arsenic map using the same groundwater arsenic dataset. Boosted regression tree models also show that the most important controlling factors of groundwater arsenic distribution include groundwater iron content and well depth for all three

  9. Using variable combination population analysis for variable selection in multivariate calibration.

    Science.gov (United States)

    Yun, Yong-Huan; Wang, Wei-Ting; Deng, Bai-Chuan; Lai, Guang-Bi; Liu, Xin-bo; Ren, Da-Bing; Liang, Yi-Zeng; Fan, Wei; Xu, Qing-Song

    2015-03-03

    Variable (wavelength or feature) selection techniques have become a critical step for the analysis of datasets with high number of variables and relatively few samples. In this study, a novel variable selection strategy, variable combination population analysis (VCPA), was proposed. This strategy consists of two crucial procedures. First, the exponentially decreasing function (EDF), which is the simple and effective principle of 'survival of the fittest' from Darwin's natural evolution theory, is employed to determine the number of variables to keep and continuously shrink the variable space. Second, in each EDF run, binary matrix sampling (BMS) strategy that gives each variable the same chance to be selected and generates different variable combinations, is used to produce a population of subsets to construct a population of sub-models. Then, model population analysis (MPA) is employed to find the variable subsets with the lower root mean squares error of cross validation (RMSECV). The frequency of each variable appearing in the best 10% sub-models is computed. The higher the frequency is, the more important the variable is. The performance of the proposed procedure was investigated using three real NIR datasets. The results indicate that VCPA is a good variable selection strategy when compared with four high performing variable selection methods: genetic algorithm-partial least squares (GA-PLS), Monte Carlo uninformative variable elimination by PLS (MC-UVE-PLS), competitive adaptive reweighted sampling (CARS) and iteratively retains informative variables (IRIV). The MATLAB source code of VCPA is available for academic research on the website: http://www.mathworks.com/matlabcentral/fileexchange/authors/498750. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Variability and uncertainty in Swedish exposure factors for use in quantitative exposure assessments.

    Science.gov (United States)

    Filipsson, Monika; Öberg, Tomas; Bergbäck, Bo

    2011-01-01

    Information of exposure factors used in quantitative risk assessments has previously been compiled and reported for U.S. and European populations. However, due to the advancement of science and knowledge, these reports are in continuous need of updating with new data. Equally important is the change over time of many exposure factors related to both physiological characteristics and human behavior. Body weight, skin surface, time use, and dietary habits are some of the most obvious examples covered here. A wealth of data is available from literature not primarily gathered for the purpose of risk assessment. Here we review a number of key exposure factors and compare these factors between northern Europe--here represented by Sweden--and the United States. Many previous compilations of exposure factor data focus on interindividual variability and variability between sexes and age groups, while uncertainty is mainly dealt with in a qualitative way. In this article variability is assessed along with uncertainty. As estimates of central tendency and interindividual variability, mean, standard deviation, skewness, kurtosis, and multiple percentiles were calculated, while uncertainty was characterized using 95% confidence intervals for these parameters. The presented statistics are appropriate for use in deterministic analyses using point estimates for each input parameter as well as in probabilistic assessments. © 2010 Society for Risk Analysis.

  11. 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

  12. Clinical Trials With Large Numbers of Variables: Important Advantages of Canonical Analysis.

    Science.gov (United States)

    Cleophas, Ton J

    2016-01-01

    Canonical analysis assesses the combined effects of a set of predictor variables on a set of outcome variables, but it is little used in clinical trials despite the omnipresence of multiple variables. The aim of this study was to assess the performance of canonical analysis as compared with traditional multivariate methods using multivariate analysis of covariance (MANCOVA). As an example, a simulated data file with 12 gene expression levels and 4 drug efficacy scores was used. The correlation coefficient between the 12 predictor and 4 outcome variables was 0.87 (P = 0.0001) meaning that 76% of the variability in the outcome variables was explained by the 12 covariates. Repeated testing after the removal of 5 unimportant predictor and 1 outcome variable produced virtually the same overall result. The MANCOVA identified identical unimportant variables, but it was unable to provide overall statistics. (1) Canonical analysis is remarkable, because it can handle many more variables than traditional multivariate methods such as MANCOVA can. (2) At the same time, it accounts for the relative importance of the separate variables, their interactions and differences in units. (3) Canonical analysis provides overall statistics of the effects of sets of variables, whereas traditional multivariate methods only provide the statistics of the separate variables. (4) Unlike other methods for combining the effects of multiple variables such as factor analysis/partial least squares, canonical analysis is scientifically entirely rigorous. (5) Limitations include that it is less flexible than factor analysis/partial least squares, because only 2 sets of variables are used and because multiple solutions instead of one is offered. We do hope that this article will stimulate clinical investigators to start using this remarkable method.

  13. 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.

  14. 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.

  15. 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.

  16. Continuous variable polarization entanglement, experiment and analysis

    International Nuclear Information System (INIS)

    Bowen, Warwick P; Treps, Nicolas; Schnabel, Roman; Ralph, Timothy C; Lam, Ping Koy

    2003-01-01

    We generate and characterize continuous variable polarization entanglement between two optical beams. We first produce quadrature entanglement, and by performing local operations we transform it into a polarization basis. We extend two entanglement criteria, the inseparability criteria proposed by Duan et al (2000 Phys. Rev. Lett. 84 2722) and the Einstein-Podolsky-Rosen (EPR) paradox criteria proposed by Reid and Drummond (1988 Phys. Rev. Lett. 60 2731), to Stokes operators; and use them to characterize the entanglement. Our results for the EPR paradox criteria are visualized in terms of uncertainty balls on the Poincare sphere. We demonstrate theoretically that using two quadrature entangled pairs it is possible to entangle three orthogonal Stokes operators between a pair of beams, although with a bound √3 times more stringent than for the quadrature entanglement

  17. Continuous variable polarization entanglement, experiment and analysis

    Energy Technology Data Exchange (ETDEWEB)

    Bowen, Warwick P [Department of Physics, Faculty of Science, Australian National University, ACT 0200 (Australia); Treps, Nicolas [Department of Physics, Faculty of Science, Australian National University, ACT 0200 (Australia); Schnabel, Roman [Department of Physics, Faculty of Science, Australian National University, ACT 0200 (Australia); Ralph, Timothy C [Department of Physics, Centre for Quantum Computer Technology, University of Queensland, St Lucia, QLD 4072 (Australia); Lam, Ping Koy [Department of Physics, Faculty of Science, Australian National University, ACT 0200 (Australia)

    2003-08-01

    We generate and characterize continuous variable polarization entanglement between two optical beams. We first produce quadrature entanglement, and by performing local operations we transform it into a polarization basis. We extend two entanglement criteria, the inseparability criteria proposed by Duan et al (2000 Phys. Rev. Lett. 84 2722) and the Einstein-Podolsky-Rosen (EPR) paradox criteria proposed by Reid and Drummond (1988 Phys. Rev. Lett. 60 2731), to Stokes operators; and use them to characterize the entanglement. Our results for the EPR paradox criteria are visualized in terms of uncertainty balls on the Poincare sphere. We demonstrate theoretically that using two quadrature entangled pairs it is possible to entangle three orthogonal Stokes operators between a pair of beams, although with a bound {radical}3 times more stringent than for the quadrature entanglement.

  18. Partitioning the variability of fasting plasma glucose levels in pedigrees. Genetic and environmental factors.

    Science.gov (United States)

    Boehnke, M; Moll, P P; Kottke, B A; Weidman, W H

    1987-04-01

    Fasting plasma glucose measurements made in 1972-1977 on normoglycemic individuals in three-generation Caucasian pedigrees from Rochester, Minnesota were analyzed. The authors determined the contributions of polygenic loci and environmental factors to fasting plasma glucose variability in these pedigrees. To that end, fasting plasma glucose measurements were normalized by an inverse normal scores transformation and then regressed separately for males and females on measured concomitants including age, body mass index (weight/height2), season of measurement, sex hormone use, and diuretic use. The authors found that 27.7% of the variability in normalized fasting plasma glucose in these pedigrees is explained by these measured concomitants. Subsequent variance components analysis suggested that unmeasured polygenic loci and unmeasured shared environmental factors together account for at least an additional 36.7% of the variability in normalized fasting plasma glucose, with genes alone accounting for at least 27.3%. These results are consistent with the known familiality of diabetes, for which fasting plasma glucose level is an important predictor. Further, these familial factors provide an explanation for at least half the variability in normalized fasting plasma glucose which remains after regression on known concomitants.

  19. 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)

  20. 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…

  1. Fourier analysis in several complex variables

    CERN Document Server

    Ehrenpreis, Leon

    2006-01-01

    Suitable for advanced undergraduates and graduate students, this text develops comparison theorems to establish the fundamentals of Fourier analysis and to illustrate their applications to partial differential equations.The three-part treatment begins by establishing the quotient structure theorem or fundamental principle of Fourier analysis. Topics include the geometric structure of ideals and modules, quantitative estimates, and examples in which the theory can be applied. The second part focuses on applications to partial differential equations and covers the solution of homogeneous and inh

  2. 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.

  3. Conserved variable analysis of the marine boundary layer and air

    Indian Academy of Sciences (India)

    The present study is based on the observed features of the MBL (Marine Boundary Layer) during the Bay of Bengal and Monsoon Experiment (BOBMEX) - Pilot phase. Conserved Variable Analysis (CVA) of the conserved variables such as potential temperature, virtual potential temperature, equivalent potential temperature ...

  4. Analysis of Design Variables of Annular Linear Induction Electromagnetic Pump using an MHD Model

    Energy Technology Data Exchange (ETDEWEB)

    Kwak, Jae Sik; Kim, Hee Reyoung [Ulsan National Institute of Science and Technology, Ulsan (Korea, Republic of)

    2015-05-15

    The generated force is affected by lots of factors including electrical input, hydrodynamic flow, geometrical shape, and so on. These factors, which are the design variables of an ALIP, should be suitably analyzed to optimally design an ALIP. Analysis on the developed pressure and efficiency of the ALIP according to the change of design variables is required for the ALIP satisfying requirements. In this study, the design variables of the ALIP are analyzed by using ideal MHD analysis model. Electromagnetic force and efficiency are derived by analyzing the main design variables such as pump core length, inner core diameter, flow gap and turns of coils. The developed pressure and efficiency of the ALIP were derived and analyzed on the change of the main variables such as pump core length, inner core diameter, flow gap, and turns of coils of the ALIP.

  5. Analysis of Dynamic Characteristics of Portal Frame with Variable Section

    OpenAIRE

    Hao Jianing

    2016-01-01

    Combined with a portal frame design, by the use of finite element software ANSYS, the finite element model of single specimens of portal rigid frame and the overall portal rigid frame building are established. portal rigid frame’s beam and column is variable cross section. Through the modal analysis, comparative analysis of the frequency and vibration type of the radiolabeling specimens and finite element model of the whole, for the further development of variable cross-section portal rigid f...

  6. Review and classification of variability analysis techniques with clinical applications.

    Science.gov (United States)

    Bravi, Andrea; Longtin, André; Seely, Andrew J E

    2011-10-10

    Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis.

  7. Review and classification of variability analysis techniques with clinical applications

    Science.gov (United States)

    2011-01-01

    Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis. PMID:21985357

  8. Variations of Histone Modification Patterns: Contributions of Inter-plant Variability and Technical Factors

    Directory of Open Access Journals (Sweden)

    Sylva Brabencová

    2017-12-01

    Full Text Available Inter-individual variability of conspecific plants is governed by differences in their genetically determined growth and development traits, environmental conditions, and adaptive responses under epigenetic control involving histone post-translational modifications. The apparent variability in histone modifications among plants might be increased by technical variation introduced in sample processing during epigenetic analyses. Thus, to detect true variations in epigenetic histone patterns associated with given factors, the basal variability among samples that is not associated with them must be estimated. To improve knowledge of relative contribution of biological and technical variation, mass spectrometry was used to examine histone modification patterns (acetylation and methylation among Arabidopsis thaliana plants of ecotypes Columbia 0 (Col-0 and Wassilewskija (Ws homogenized by two techniques (grinding in a cryomill or with a mortar and pestle. We found little difference in histone modification profiles between the ecotypes. However, in comparison of the biological and technical components of variability, we found consistently higher inter-individual variability in histone mark levels among Ws plants than among Col-0 plants (grown from seeds collected either from single plants or sets of plants. Thus, more replicates of Ws would be needed for rigorous analysis of epigenetic marks. Regarding technical variability, the cryomill introduced detectably more heterogeneity in the data than the mortar and pestle treatment, but mass spectrometric analyses had minor apparent effects. Our study shows that it is essential to consider inter-sample variance and estimate suitable numbers of biological replicates for statistical analysis for each studied organism when investigating changes in epigenetic histone profiles.

  9. Variations of Histone Modification Patterns: Contributions of Inter-plant Variability and Technical Factors.

    Science.gov (United States)

    Brabencová, Sylva; Ihnatová, Ivana; Potěšil, David; Fojtová, Miloslava; Fajkus, Jiří; Zdráhal, Zbyněk; Lochmanová, Gabriela

    2017-01-01

    Inter-individual variability of conspecific plants is governed by differences in their genetically determined growth and development traits, environmental conditions, and adaptive responses under epigenetic control involving histone post-translational modifications. The apparent variability in histone modifications among plants might be increased by technical variation introduced in sample processing during epigenetic analyses. Thus, to detect true variations in epigenetic histone patterns associated with given factors, the basal variability among samples that is not associated with them must be estimated. To improve knowledge of relative contribution of biological and technical variation, mass spectrometry was used to examine histone modification patterns (acetylation and methylation) among Arabidopsis thaliana plants of ecotypes Columbia 0 (Col-0) and Wassilewskija (Ws) homogenized by two techniques (grinding in a cryomill or with a mortar and pestle). We found little difference in histone modification profiles between the ecotypes. However, in comparison of the biological and technical components of variability, we found consistently higher inter-individual variability in histone mark levels among Ws plants than among Col-0 plants (grown from seeds collected either from single plants or sets of plants). Thus, more replicates of Ws would be needed for rigorous analysis of epigenetic marks. Regarding technical variability, the cryomill introduced detectably more heterogeneity in the data than the mortar and pestle treatment, but mass spectrometric analyses had minor apparent effects. Our study shows that it is essential to consider inter-sample variance and estimate suitable numbers of biological replicates for statistical analysis for each studied organism when investigating changes in epigenetic histone profiles.

  10. Variability of soil-to-crop transfer factor

    International Nuclear Information System (INIS)

    Uchida, Shigeo; Kamada, Hiroshi; Yokosuka, Setsuko; Ohmomo, Yoichiro

    1987-01-01

    Many European countries have nuclear facilities in inland areas, where extremely low level radioactive waste liquid is discharged to rivers. In those nations, therefore, many studies have been made oncerning the transfer of radioisotopes into plants. In Japan, greater attention has been attracted to such radioisotope transfer into plants and then into human bodies. Thus the present report reviews various studies on this issue. The key parameter for this process is the transfer factor (also called concentration factor, coefficient or ratio). The factor largely depends on various other factors including the characteristics of different nuclides, properties of soil (pH, oxidation-reduction potential, grain size distribution, contents of clay minerals, contents of organic matters, water content, etc.), characteristics of crops and cultivation conditions. It has been reported that I is absorbed by plants more rapidly than IO 3 . Of the various soil parameters, the pH of soil has the greatest effect on the transfer factor. Soil is mostly alkaline in Europe and America while acid soil account for a great part in Japan, suggesting that the transfer factor would be greater in Japan. The total potassium content in soil has the second largest effect on the factor. Radioactive iodine has shown to be transferred into soy beans and spinach 30 times more rapidly than into fruit vegetables. The oxidation-reduction potential also has a significant influence on the transfer factor. (Nogami, K.)

  11. Visuospatial ability factors and performance variables in laparoscopic simulator training

    NARCIS (Netherlands)

    Luursema, J.M.; Verwey, Willem B.; Burie, Remke

    2012-01-01

    Visuospatial ability has been shown to be important to several aspects of laparoscopic performance, including simulator training. Only a limited subset of visuospatial ability factors however has been investigated in such studies. Tests for different visuospatial ability factors differ in stimulus

  12. Real analysis series, functions of several variables, and applications

    CERN Document Server

    Laczkovich, Miklós

    2017-01-01

    This book develops the theory of multivariable analysis, building on the single variable foundations established in the companion volume, Real Analysis: Foundations and Functions of One Variable. Together, these volumes form the first English edition of the popular Hungarian original, Valós Analízis I & II, based on courses taught by the authors at Eötvös Loránd University, Hungary, for more than 30 years. Numerous exercises are included throughout, offering ample opportunities to master topics by progressing from routine to difficult problems. Hints or solutions to many of the more challenging exercises make this book ideal for independent study, or further reading. Intended as a sequel to a course in single variable analysis, this book builds upon and expands these ideas into higher dimensions. The modular organization makes this text adaptable for either a semester or year-long introductory course. Topics include: differentiation and integration of functions of several variables; infinite numerica...

  13. An Analysis of Social Class Classification Based on Linguistic Variables

    Institute of Scientific and Technical Information of China (English)

    QU Xia-sha

    2016-01-01

    Since language is an influential tool in social interaction, the relationship of speech and social factors, such as social class, gender, even age is worth studying. People employ different linguistic variables to imply their social class, status and iden-tity in the social interaction. Thus the linguistic variation involves vocabulary, sounds, grammatical constructions, dialects and so on. As a result, a classification of social class draws people’s attention. Linguistic variable in speech interactions indicate the social relationship between people. This paper attempts to illustrate three main linguistic variables which influence the social class, and further sociolinguistic studies need to be more concerned about.

  14. Minimizing inter-microscope variability in dental microwear texture analysis

    Science.gov (United States)

    Arman, Samuel D.; Ungar, Peter S.; Brown, Christopher A.; DeSantis, Larisa R. G.; Schmidt, Christopher; Prideaux, Gavin J.

    2016-06-01

    A common approach to dental microwear texture analysis (DMTA) uses confocal profilometry in concert with scale-sensitive fractal analysis to help understand the diets of extinct mammals. One of the main benefits of DMTA over other methods is the repeatable, objective manner of data collection. This repeatability, however, is threatened by variation in results of DMTA of the same dental surfaces yielded by different microscopes. Here we compare DMTA data of five species of kangaroos measured on seven profilers of varying specifications. Comparison between microscopes confirms that inter-microscope differences are present, but we show that deployment of a number of automated treatments to remove measurement noise can help minimize inter-microscope differences. Applying these same treatments to a published hominin DMTA dataset shows that they alter some significant differences between dietary groups. Minimising microscope variability while maintaining interspecific dietary differences requires then that these factors are balanced in determining appropriate treatments. The process outlined here offers a solution for allowing comparison of data between microscopes, which is essential for ongoing DMTA research. In addition, the process undertaken, including considerations of other elements of DMTA protocols also promises to streamline methodology, remove measurement noise and in doing so, optimize recovery of a reliable dietary signature.

  15. 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…

  16. Analysis of Dynamic Characteristics of Portal Frame with Variable Section

    Directory of Open Access Journals (Sweden)

    Hao Jianing

    2016-01-01

    Full Text Available Combined with a portal frame design, by the use of finite element software ANSYS, the finite element model of single specimens of portal rigid frame and the overall portal rigid frame building are established. portal rigid frame’s beam and column is variable cross section. Through the modal analysis, comparative analysis of the frequency and vibration type of the radiolabeling specimens and finite element model of the whole, for the further development of variable cross-section portal rigid frame of earthquake and wind vibration analysis lay the foundation.

  17. A meta analysis of the variability in firm performance attributable to human resource variables

    Directory of Open Access Journals (Sweden)

    Lloyd Kapondoro

    2015-01-01

    Full Text Available The contribution of Human Resource Management (HRM practices to organisation-wide performance is a critical aspect of the Human Resource (HR value proposition. The purpose of the study was to describe the strength of HRM practices and systems in influencing overall organisational performance. While research has concluded that there is a significant positive relationship between HRM practices or systems and an organisation’s market performance, the strength of this relationship has relatively not received much analysis in order to explain the degree to which HRM practices explain variance in firm performance. The study undertook a meta-analysis of published researches in international journals. The study established that HRM variables accounted for an average of 31% of the variability in firm performance. Cohen’s f2 calculated for this study as a meta effect size calculation yielded an average of 0.681, implying that HRM variables account for 68% of variability in firm performance. A one sample Kolmogorov-Smirnov test showed that the distribution of R2 is not normal. A major managerial implication of this study is that effective HRM practices have a significant business case. The study provides, quantitatively, the average variability in firm success that HRM accounts for.

  18. Variability Bugs in Highly Configurable Systems: A Qualitative Analysis

    DEFF Research Database (Denmark)

    Abal, Iago; Melo, Jean; Stanciulescu, Stefan

    2018-01-01

    Variability-sensitive verification pursues effective analysis of the exponentially many variants in number of features of a program family. Several variability-aware techniques have been proposed, but researchers still lack examples of concrete bugs induced by variability, occurring in real large......-scale systems. A collection of real world bugs is needed to evaluate tool implementations of variability-sensitive analyses by testing them on real bugs. We present a qualitative study of 98 diverse variability bugs collected from bug-fixing commits in the Apache, BusyBox, Linux kernel and Marlin repositories....... We analyze each of the bugs, and record the results in a database. For each bug, we create a self-contained simplified C99 version and a simplified patch, in order to help researchers who are not experts on these subject studies to understand them, so that they can use it for evaluation...

  19. Power calculator for instrumental variable analysis in pharmacoepidemiology.

    Science.gov (United States)

    Walker, Venexia M; Davies, Neil M; Windmeijer, Frank; Burgess, Stephen; Martin, Richard M

    2017-10-01

    Instrumental variable analysis, for example with physicians' prescribing preferences as an instrument for medications issued in primary care, is an increasingly popular method in the field of pharmacoepidemiology. Existing power calculators for studies using instrumental variable analysis, such as Mendelian randomization power calculators, do not allow for the structure of research questions in this field. This is because the analysis in pharmacoepidemiology will typically have stronger instruments and detect larger causal effects than in other fields. Consequently, there is a need for dedicated power calculators for pharmacoepidemiological research. The formula for calculating the power of a study using instrumental variable analysis in the context of pharmacoepidemiology is derived before being validated by a simulation study. The formula is applicable for studies using a single binary instrument to analyse the causal effect of a binary exposure on a continuous outcome. An online calculator, as well as packages in both R and Stata, are provided for the implementation of the formula by others. The statistical power of instrumental variable analysis in pharmacoepidemiological studies to detect a clinically meaningful treatment effect is an important consideration. Research questions in this field have distinct structures that must be accounted for when calculating power. The formula presented differs from existing instrumental variable power formulae due to its parametrization, which is designed specifically for ease of use by pharmacoepidemiologists. © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association

  20. [Relations between biomedical variables: mathematical analysis or linear algebra?].

    Science.gov (United States)

    Hucher, M; Berlie, J; Brunet, M

    1977-01-01

    The authors, after a short reminder of one pattern's structure, stress on the possible double approach of relations uniting the variables of this pattern: use of fonctions, what is within the mathematical analysis sphere, use of linear algebra profiting by matricial calculation's development and automatiosation. They precise the respective interests on these methods, their bounds and the imperatives for utilization, according to the kind of variables, of data, and the objective for work, understanding phenomenons or helping towards decision.

  1. [Quantitative analysis of drug expenditures variability in dermatology units].

    Science.gov (United States)

    Moreno-Ramírez, David; Ferrándiz, Lara; Ramírez-Soto, Gabriel; Muñoyerro, M Dolores

    2013-01-01

    Variability in adjusted drug expenditures among clinical departments raises the possibility of difficult access to certain therapies at the time that avoidable expenditures may also exist. Nevertheless, drug expenditures are not usually applied to clinical practice variability analysis. To identify and quantify variability in drug expenditures in comparable dermatology department of the Servicio Andaluz de Salud. Comparative economic analysis regarding the drug expenditures adjusted to population and health care production in 18 dermatology departments of the Servicio Andaluz de Salud. The 2012 cost and production data (homogeneous production units -HPU-)were provided by Inforcoan, the cost accounting information system of the Servicio Andaluz de Salud. The observed drug expenditure ratio ranged from 0.97?/inh to 8.90?/inh and from 208.45?/HPU to 1,471.95?/ HPU. The Pearson correlation between drug expenditure and population was 0.25 and 0.35 for the correlation between expenditure and homogeneous production (p=0.32 and p=0,15, respectively), both Pearson coefficients confirming the lack of correlation and arelevant degree of variability in drug expenditures. The quantitative analysis of variability performed through Pearson correlation has confirmed the existence of drug expenditure variability among comparable dermatology departments. Copyright © 2013 SEFH. Published by AULA MEDICA. All rights reserved.

  2. Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

    Science.gov (United States)

    Hassanzadeh, S.; Hosseinibalam, F.; Omidvari, M.

    2008-04-01

    Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

  3. 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

  4. Effective Analysis of C Programs by Rewriting Variability

    DEFF Research Database (Denmark)

    Iosif-Lazar, Alexandru Florin; Melo, Jean; Dimovski, Aleksandar

    2017-01-01

    and effective analysis and verification of real-world C program families. Importance. We report some interesting variability-related bugs that we discovered using various state-of-the-art single-program C verification tools, such as Frama-C, Clang, LLBMC.......Context. Variability-intensive programs (program families) appear in many application areas and for many reasons today. Different family members, called variants, are derived by switching statically configurable options (features) on and off, while reuse of the common code is maximized. Inquiry....... Verification of program families is challenging since the number of variants is exponential in the number of features. Existing single-program analysis and verification tools cannot be applied directly to program families, and designing and implementing the corresponding variability-aware versions is tedious...

  5. GIS and correlation analysis of geo-environmental variables ...

    African Journals Online (AJOL)

    GIS and correlation analysis of geo-environmental variables influencing malaria prevalence in the Saboba district of Northern Ghana. ... The study also applied spline interpolation technique to map malaria prevalence in the district using standardised malaria incidence. The result indicates that distance to marshy areas is ...

  6. Variability, correlation and path coefficient analysis of seedling traits ...

    African Journals Online (AJOL)

    Indirect selection is a useful means for improving yield in cotton crop. The objective of the present study was to determine the genetic variability, broad sense heritability, genetic advance and correlation among the six seedling traits and their direct and indirect effects on cotton yield by using path coefficient analysis.

  7. Omitted Variable Sensitivity Analysis with the Annotated Love Plot

    Science.gov (United States)

    Hansen, Ben B.; Fredrickson, Mark M.

    2014-01-01

    The goal of this research is to make sensitivity analysis accessible not only to empirical researchers but also to the various stakeholders for whom educational evaluations are conducted. To do this it derives anchors for the omitted variable (OV)-program participation association intrinsically, using the Love plot to present a wide range of…

  8. Nonlinear canonical correlation analysis with k sets of variables

    NARCIS (Netherlands)

    van der Burg, Eeke; de Leeuw, Jan

    1987-01-01

    The multivariate technique OVERALS is introduced as a non-linear generalization of canonical correlation analysis (CCA). First, two sets CCA is introduced. Two sets CCA is a technique that computes linear combinations of sets of variables that correlate in an optimal way. Two sets CCA is then

  9. Variable precision rough set for multiple decision attribute analysis

    Institute of Scientific and Technical Information of China (English)

    Lai; Kin; Keung

    2008-01-01

    A variable precision rough set (VPRS) model is used to solve the multi-attribute decision analysis (MADA) problem with multiple conflicting decision attributes and multiple condition attributes. By introducing confidence measures and a β-reduct, the VPRS model can rationally solve the conflicting decision analysis problem with multiple decision attributes and multiple condition attributes. For illustration, a medical diagnosis example is utilized to show the feasibility of the VPRS model in solving the MADA...

  10. Lifestyle factors and socioeconomic variables associated with abdominal obesity in Brazilian adolescents.

    Science.gov (United States)

    Moraes, Augusto César Ferreira de; Falcão, Mário Cícero

    2013-01-01

    Lifestyle variables have a key role in the development of abdominal obesity (AO). The objective of this study was to identify lifestyle factors and socioeconomic variables associated with AO in adolescents. This study carried out a school-based survey in the Brazilian city of Maringá in Paraná. The representative sample was of 991 adolescents (54.5% girls) from both public and private high schools selected through multi-stage random sampling. AO was classified according to waist circumference value. The independent variables studied were: gender, age, socioeconomic level, parental and household characteristics, smoking, alcohol use, physical inactivity, sedentary behaviour and nutrition-related habits. Poisson regression was used with robust variance adjustment to analyse the associations. The analysis was stratified by sexes. The prevalence of AO was 32.7% (girls = 36.3%, boys = 28.4%). In girls, excessive intake of fried foods was inversely associated with AO and excessive consumption of soda was positively associated. In boys, the results demonstrated a negative association with excessive consumption of sweets and soda. It is concluded that the prevalence of AO among adolescents was higher in both sexes. AO is associated with different eating habits in females and males and these relationships are mediated by familial contexts.

  11. 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.

  12. Attribute Analysis of Aridity Variability in North Xinjiang, China

    Directory of Open Access Journals (Sweden)

    Yanfeng Wu

    2016-01-01

    Full Text Available Identifying the dominant meteorological factors affecting aridity variability can improve our understanding of climate change and its future trend in arid and semiarid regions. This study investigated the spatiotemporal aridity variability in North Xinjiang, China, from 1961 to 2013, based on the UNESCO aridity index (precipitation/potential evapotranspiration, and analyzed its association with meteorological factors. The results suggest that North Xinjiang is becoming more humid with an increasing trend in aridity index. Precipitation, temperature, and relative humidity have positive correlation with aridity, and evapotranspiration, sunshine hours, and wind speed have negative correlation with aridity. Wind speed and sunshine hours have a higher sensitivity and more contribution to aridity. This study provides an understanding of the effect of recent climate change on drought in northwest China.

  13. Analysis models for variables associated with breastfeeding duration

    Directory of Open Access Journals (Sweden)

    Edson Theodoro dos S. Neto

    2013-09-01

    Full Text Available OBJECTIVE To analyze the factors associated with breastfeeding duration by two statistical models. METHODS A population-based cohort study was conducted with 86 mothers and newborns from two areas primary covered by the National Health System, with high rates of infant mortality in Vitória, Espírito Santo, Brazil. During 30 months, 67 (78% children and mothers were visited seven times at home by trained interviewers, who filled out survey forms. Data on food and sucking habits, socioeconomic and maternal characteristics were collected. Variables were analyzed by Cox regression models, considering duration of breastfeeding as the dependent variable, and logistic regression (dependent variables, was the presence of a breastfeeding child in different post-natal ages. RESULTS In the logistic regression model, the pacifier sucking (adjusted Odds Ratio: 3.4; 95%CI 1.2-9.55 and bottle feeding (adjusted Odds Ratio: 4.4; 95%CI 1.6-12.1 increased the chance of weaning a child before one year of age. Variables associated to breastfeeding duration in the Cox regression model were: pacifier sucking (adjusted Hazard Ratio 2.0; 95%CI 1.2-3.3 and bottle feeding (adjusted Hazard Ratio 2.0; 95%CI 1.2-3.5. However, protective factors (maternal age and family income differed between both models. CONCLUSIONS Risk and protective factors associated with cessation of breastfeeding may be analyzed by different models of statistical regression. Cox Regression Models are adequate to analyze such factors in longitudinal studies.

  14. A Statistical Analysis of Cointegration for I(2) Variables

    DEFF Research Database (Denmark)

    Johansen, Søren

    1995-01-01

    be conducted using the ¿ sup2/sup distribution. It is shown to what extent inference on the cointegration ranks can be conducted using the tables already prepared for the analysis of cointegration of I(1) variables. New tables are needed for the test statistics to control the size of the tests. This paper...... contains a multivariate test for the existence of I(2) variables. This test is illustrated using a data set consisting of U.K. and foreign prices and interest rates as well as the exchange rate....

  15. Frequency spectrum analysis of finger photoplethysmographic waveform variability during haemodialysis.

    Science.gov (United States)

    Javed, Faizan; Middleton, Paul M; Malouf, Philip; Chan, Gregory S H; Savkin, Andrey V; Lovell, Nigel H; Steel, Elizabeth; Mackie, James

    2010-09-01

    This study investigates the peripheral circulatory and autonomic response to volume withdrawal in haemodialysis based on spectral analysis of photoplethysmographic waveform variability (PPGV). Frequency spectrum analysis was performed on the baseline and pulse amplitude variabilities of the finger infrared photoplethysmographic (PPG) waveform and on heart rate variability extracted from the ECG signal collected from 18 kidney failure patients undergoing haemodialysis. Spectral powers were calculated from the low frequency (LF, 0.04-0.145 Hz) and high frequency (HF, 0.145-0.45 Hz) bands. In eight stable fluid overloaded patients (fluid removal of >2 L) not on alpha blockers, progressive reduction in relative blood volume during haemodialysis resulted in significant increase in LF and HF powers of PPG baseline and amplitude variability (P analysis of finger PPGV may provide valuable information on the autonomic vascular response to blood volume reduction in haemodialysis, and can be potentially utilized as a non-invasive tool for assessing peripheral circulatory control during routine dialysis procedure.

  16. ZnO crystals obtained by electrodeposition: Statistical analysis of most important process variables

    International Nuclear Information System (INIS)

    Cembrero, Jesus; Busquets-Mataix, David

    2009-01-01

    In this paper a comparative study by means of a statistical analysis of the main process variables affecting ZnO crystal electrodeposition is presented. ZnO crystals were deposited on two different substrates, silicon wafer and indium tin oxide. The control variables were substrate types, electrolyte concentration, temperature, exposition time and current density. The morphologies of the different substrates were observed using scanning electron microscopy. The percentage of substrate area covered by ZnO deposit was calculated by computational image analysis. The design of the applied experiments was based on a two-level factorial analysis involving a series of 32 experiments and an analysis of variance. Statistical results reveal that variables exerting a significant influence on the area covered by ZnO deposit are electrolyte concentration, substrate type and time of deposition, together with a combined two-factor interaction between temperature and current density. However, morphology is also influenced by surface roughness of the substrates

  17. Multivariate analysis between air pollutants and meteorological variables in Seoul

    International Nuclear Information System (INIS)

    Kim, J.; Lim, J.

    2005-01-01

    Multivariate analysis was conducted to analyze the relationship between air pollutants and meteorological variables measured in Seoul from January 1 to December 31, 1999. The first principal component showed the contrast effect between O 3 and the other pollutants. The second principal component showed the contrast effect between CO, SO 2 , NO 2 , and O 3 , PM 10 , TSP. Based on the cluster analysis, three clusters represented different air pollution levels, seasonal characteristics of air pollutants, and meteorological conditions. Discriminant analysis with air environment index (AEI) was carried out to develop an air pollution index function. (orig.)

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

    Directory of Open Access Journals (Sweden)

    Naser Azad

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

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

    OpenAIRE

    Dalvand, Sahar; Koohpayehzadeh, Jalil; Karimlou, Masoud; Asgari, Fereshteh; Rafei, Ali; Seifi, Behjat; Niksima, Seyed Hassan; Bakhshi, Enayatollah

    2015-01-01

    Background. Because the use of BMI (Body Mass Index) alone as a measure of adiposity has been criticized, in the present study our aim was to fit a latent variable model to simultaneously examine the factors that affect waist circumference (continuous outcome) and obesity (binary outcome) among Iranian adults. Methods. Data included 18,990 Iranian individuals aged 20–65 years that are derived from the third National Survey of Noncommunicable Diseases Risk Factors in Iran. Using latent variabl...

  20. Causality and cointegration analysis between macroeconomic variables and the Bovespa.

    Directory of Open Access Journals (Sweden)

    Fabiano Mello da Silva

    Full Text Available The aim of this study is to analyze the causality relationship among a set of macroeconomic variables, represented by the exchange rate, interest rate, inflation (CPI, industrial production index as a proxy for gross domestic product in relation to the index of the São Paulo Stock Exchange (Bovespa. The period of analysis corresponded to the months from January 1995 to December 2010, making a total of 192 observations for each variable. Johansen tests, through the statistics of the trace and of the maximum eigenvalue, indicated the existence of at least one cointegration vector. In the analysis of Granger (1988 causality tests via error correction, it was found that a short-term causality existed between the CPI and the Bovespa. Regarding the Granger (1988 long-term causality, the results indicated a long-term behaviour among the macroeconomic variables with the BOVESPA. The results of the long-term normalized vector for the Bovespa variable showed that most signals of the cointegration equation parameters are in accordance with what is suggested by the economic theory. In other words, there was a positive behaviour of the GDP and a negative behaviour of the inflation and of the exchange rate (expected to be a positive relationship in relation to the Bovespa, with the exception of the Selic rate, which was not significant with that index. The variance of the Bovespa was explained by itself in over 90% at the twelfth month, followed by the country risk, with less than 5%.

  1. Causality and cointegration analysis between macroeconomic variables and the Bovespa.

    Science.gov (United States)

    da Silva, Fabiano Mello; Coronel, Daniel Arruda; Vieira, Kelmara Mendes

    2014-01-01

    The aim of this study is to analyze the causality relationship among a set of macroeconomic variables, represented by the exchange rate, interest rate, inflation (CPI), industrial production index as a proxy for gross domestic product in relation to the index of the São Paulo Stock Exchange (Bovespa). The period of analysis corresponded to the months from January 1995 to December 2010, making a total of 192 observations for each variable. Johansen tests, through the statistics of the trace and of the maximum eigenvalue, indicated the existence of at least one cointegration vector. In the analysis of Granger (1988) causality tests via error correction, it was found that a short-term causality existed between the CPI and the Bovespa. Regarding the Granger (1988) long-term causality, the results indicated a long-term behaviour among the macroeconomic variables with the BOVESPA. The results of the long-term normalized vector for the Bovespa variable showed that most signals of the cointegration equation parameters are in accordance with what is suggested by the economic theory. In other words, there was a positive behaviour of the GDP and a negative behaviour of the inflation and of the exchange rate (expected to be a positive relationship) in relation to the Bovespa, with the exception of the Selic rate, which was not significant with that index. The variance of the Bovespa was explained by itself in over 90% at the twelfth month, followed by the country risk, with less than 5%.

  2. 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…

  3. Variables relacionadas con los factores protectores en estudiantes de una universidad pública colombiana, 2016

    OpenAIRE

    Jaramillo, C.P.; Vélez, C.; Hoyos, M.; Escobar, M.P.; Pico, M.E.

    2017-01-01

    Introducción: Los factores protectores se definen como aquellos que fomentan los comportamientos favorables y positivos y desestimulan e inhiben los comportamientos de riesgo, limitando los efectos de los riesgos a los cuales se exponen los individuos. El fomento de factores protectores facilita el desarrollo de comportamientos y hábitos saludables así como la prevención de factores de riesgo. Objetivo: Analizar las variables relacionadas con los factores protectores en estudiantes de una uni...

  4. Predictor variables of happiness and its connection with risk and protective factors for health

    Directory of Open Access Journals (Sweden)

    Maite eGaraigordobil

    2015-08-01

    Full Text Available Great thinkers, philosophers, scientists, and artists from History have often been concerned about one of the most important elements of life: happiness. The study had four goals: 1 To analyze possible differences in feelings of happiness as a function of sex and age; 2 To explore the relations of happiness with risk factors (psychopathological symptoms, behavior problems and protective factors (self-concept-self-esteem, cooperative behavior, social skills for health; 3 To identify predictor variables of happiness; and 4 To explore whether self-esteem mediates the relationship between happiness and psychopathological symptoms. The sample comprised 286 adolescents (14-16 years old. The study used a descriptive, correlational, and cross-sectional methodology. Seven assessment instruments were administered. The ANOVAs confirm that there are no sex differences, but happiness decreases as age increases. Pearson coefficients show that adolescents with more feelings of happiness had fewer psychopathological symptoms (somatization, obsession-compulsion, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, psychoticism…, fewer behavioral problems (school-academic, antisocial behavior, shyness-withdrawal, psychopathological, psychosomatic, high social adaptation, high self-concept/self-esteem, many cooperative behaviors, many appropriate social skills, and few negative social skills (inappropriate assertiveness, impulsiveness, jealousy-withdrawal. Multiple regression analysis identified five variables predicting happiness: high self-concept, few symptoms of depression, many cooperative behaviors, high self-esteem, and low psychoticism. Results showed a partial mediational effect of self-esteem in the relation between happiness and psychopathological symptoms. The discussion focuses on the importance of implementing programs to promote feelings of happiness, as well as protective factors for health (self

  5. Predictor variables of happiness and its connection with risk and protective factors for health

    Science.gov (United States)

    Garaigordobil, Maite

    2015-01-01

    Great thinkers, philosophers, scientists, and artists from History have often been concerned about one of the most important elements of life: happiness. The study had four goals: (1) To analyze possible differences in feelings of happiness as a function of sex and age; (2) To explore the relations of happiness with risk factors (psychopathological symptoms, behavior problems) and protective factors (self-concept-self-esteem, cooperative behavior, social skills) for health; (3) To identify predictor variables of happiness; and (4) To explore whether self-esteem mediates the relationship between happiness and psychopathological symptoms. The sample comprised 286 adolescents (14–16 years old). The study used a descriptive, correlational, and cross-sectional methodology. Seven assessment instruments were administered. The ANOVAs confirm that there are no sex differences, but happiness decreases as age increases. Pearson coefficients show that adolescents with more feelings of happiness had fewer psychopathological symptoms (somatization, obsession–compulsion, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, psychoticism…), fewer behavioral problems (school-academic, antisocial behavior, shyness-withdrawal, psychopathological, psychosomatic), high social adaptation, high self-concept/self-esteem, many cooperative behaviors, many appropriate social skills, and few negative social skills (inappropriate assertiveness, impulsiveness, jealousy-withdrawal). Multiple regression analysis identified five variables predicting happiness: high self-concept, few symptoms of depression, many cooperative behaviors, high self-esteem, and low psychoticism. Results showed a partial mediational effect of self-esteem in the relation between happiness and psychopathological symptoms. The discussion focuses on the importance of implementing programs to promote feelings of happiness, as well as protective factors for health (self

  6. The Use of Categorical Variables in Data Envelopment Analysis

    OpenAIRE

    Rajiv D. Banker; Richard C. Morey

    1986-01-01

    Data Envelopment Analysis has now been extensively applied in a range of empirical settings to identify relative inefficiencies, and provide targets for improvements. It accomplishes this by developing peer groups for each unit being operated. The use of categorical variables is an important extension which can improve the peer group construction process and incorporate "on-off" characteristics, e.g., presence of drive-in window or not in a banking network. It relaxes the stringent need for f...

  7. Stability analysis for cellular neural networks with variable delays

    International Nuclear Information System (INIS)

    Zhang Qiang; Wei Xiaopeng; Xu Jin

    2006-01-01

    Some sufficient conditions for the global exponential stability of cellular neural networks with variable delay are obtained by means of a method based on delay differential inequality. The method, which does not make use of Lyapunov functionals, is simple and effective for the stability analysis of neural networks with delay. Some previously established results in the literature are shown to be special cases of the presented result

  8. An analysis of prediction skill of monthly mean climate variability

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Arun; Chen, Mingyue; Wang, Wanqiu [Climate Prediction Center, National Centers for Environmental Prediction (CPC/NCEP), Camp Springs, MD (United States)

    2011-09-15

    In this paper, lead-time and spatial dependence in skill for prediction of monthly mean climate variability is analyzed. The analysis is based on a set of extensive hindcasts from the Climate Forecast System at the National Centers for Environmental Prediction. The skill characteristics of initialized predictions is also compared with the AMIP simulations forced with the observed sea surface temperature (SST) to quantify the role of initial versus boundary conditions in the prediction of monthly means. The analysis is for prediction of monthly mean SST, precipitation, and 200-hPa height. The results show a rapid decay in skill with lead time for the atmospheric variables in the extratropical latitudes. Further, after a lead-time of approximately 30-40 days, the skill of monthly mean prediction is essentially a boundary forced problem, with SST anomalies in the tropical central/eastern Pacific playing a dominant role. Because of the larger contribution from the atmospheric internal variability to monthly time-averages (compared to seasonal averages), skill for monthly mean prediction associated with boundary forcing is also lower. The analysis indicates that the prospects of skillful prediction of monthly means may remain a challenging problem, and may be limited by inherent limits in predictability. (orig.)

  9. Joint effects of climate variability and socioecological factors on dengue transmission: epidemiological evidence.

    Science.gov (United States)

    Akter, Rokeya; Hu, Wenbiao; Naish, Suchithra; Banu, Shahera; Tong, Shilu

    2017-06-01

    To assess the epidemiological evidence on the joint effects of climate variability and socioecological factors on dengue transmission. Following PRISMA guidelines, a detailed literature search was conducted in PubMed, Web of Science and Scopus. Peer-reviewed, freely available and full-text articles, considering both climate and socioecological factors in relation to dengue, published in English from January 1993 to October 2015 were included in this review. Twenty studies have met the inclusion criteria and assessed the impact of both climatic and socioecological factors on dengue dynamics. Among those, four studies have further investigated the relative importance of climate variability and socioecological factors on dengue transmission. A few studies also developed predictive models including both climatic and socioecological factors. Due to insufficient data, methodological issues and contextual variability of the studies, it is hard to draw conclusion on the joint effects of climate variability and socioecological factors on dengue transmission. Future research should take into account socioecological factors in combination with climate variables for a better understanding of the complex nature of dengue transmission as well as for improving the predictive capability of dengue forecasting models, to develop effective and reliable early warning systems. © 2017 John Wiley & Sons Ltd.

  10. Wavelet and receiver operating characteristic analysis of heart rate variability

    Science.gov (United States)

    McCaffery, G.; Griffith, T. M.; Naka, K.; Frennaux, M. P.; Matthai, C. C.

    2002-02-01

    Multiresolution wavelet analysis has been used to study the heart rate variability in two classes of patients with different pathological conditions. The scale dependent measure of Thurner et al. was found to be statistically significant in discriminating patients suffering from hypercardiomyopathy from a control set of normal subjects. We have performed Receiver Operating Characteristc (ROC) analysis and found the ROC area to be a useful measure by which to label the significance of the discrimination, as well as to describe the severity of heart dysfunction.

  11. Load flow analysis for variable speed offshore wind farms

    DEFF Research Database (Denmark)

    Chen, Zhe; Zhao, Menghua; Blaabjerg, Frede

    2009-01-01

    factors such as the different wind farm configurations, the control of wind turbines and the power losses of pulse width modulation converters are considered. The DC/DC converter model is proposed and integrated into load flow algorithm by modifying the Jacobian matrix. Two iterative methods are proposed...... and integrated into the load flow algorithm: one takes into account the control strategy of converters and the other considers the power losses of converters. In addition, different types of variable speed wind turbine systems with different control methods are investigated. Finally, the method is demonstrated......A serial AC-DC integrated load flow algorithm for variable speed offshore wind farms is proposed. It divides the electrical system of a wind farm into several local networks, and different load flow methods are used for these local networks sequentially. This method is fast, more accurate, and many...

  12. Genetic distance estimates and variable factors distinguishing between goat Kacang, Muara and Samosir

    Science.gov (United States)

    Hamdan; Saputra, H.; Mirwandhono, E.; Hasnudi; Sembiring, I.; Umar, S.; Ginting, N.; Alwiyah

    2018-02-01

    The purpose of this research was to look the genetic distance and factors distinguishing variable betwen types of goats in North Sumatera. This research have been conducted in PayaBakung, Hamparan Perak and Klambir Lima village, Deli Serdang district, Batu Binumbun, Aritonang, HutaGinjang village, Muarasubdistrict, North Tapanuli district and ParbabaDolok, Siopat Sosor, Sinabulan village, Ronggur Nihuta Pangururan village, Sitonggi-tonggi village in the subdistrict RonggurNihuta, Samosir district of the month of July 2016. The data was analyzed using descriptive, discriminants, canonical, Principal Component Analysis, Distance genetic and Tree Phylogenetic. The result showed that the nearest genetic distance goat found in Kacang and Samosir (1.973), and the farthest genetic distnace find in Samosir and Muara (8.671). The variables made it difference was goat race Base Rim Horn (0.856) and Long Horn (0.878). Genetic distance values most far between Muaragoat with Samosir goat was (8.671). The conclude that the crossing superior result, must be cross between two goat types with value genetics most distance. It will have a better chance heterosis in cross result.

  13. 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.

  14. Analysis of Factors in Technological and Vocational School Teachers' Perceived Organizational Innovative Climate and Continuous Use of E-Teaching: Using Computer Self-Efficacy as an Intervening Variable

    Science.gov (United States)

    Chou, Chun-Mei; Hsiao, His-Chi; Shen, Chien-Hua; Chen, Su-Chang

    2010-01-01

    This study aims to analyze the correlation (N = 335) among technological and vocational school teachers' perceived organizational innovative climate, computer self-efficacy, and continuous use of e-teaching in Taiwan. Teachers' perceived organizational innovative climate includes five factors, namely, job autonomy, innovative leadership, resource…

  15. Expanded flux variability analysis on metabolic network of Escherichia coli

    Institute of Scientific and Technical Information of China (English)

    CHEN Tong; XIE ZhengWei; OUYANG Qi

    2009-01-01

    Flux balance analysis,based on the mass conservation law in a cellular organism,has been extensively employed to study the interplay between structures and functions of cellular metabolic networks.Consequently,the phenotypes of the metabolism can be well elucidated.In this paper,we introduce the Expanded Flux Variability Analysis (EFVA) to characterize the intrinsic nature of metabolic reactions,such as flexibility,modularity and essentiality,by exploring the trend of the range,the maximum and the minimum flux of reactions.We took the metabolic network of Escherichia coli as an example and analyzed the variability of reaction fluxes under different growth rate constraints.The average variability of all reactions decreases dramatically when the growth rate increases.Consider the noise effect on the metabolic system,we thus argue that the microorganism may practically grow under a suboptimal state.Besides,under the EFVA framework,the reactions are easily to be grouped into catabolic and anabolic groups.And the anabolic groups can be further assigned to specific biomass constitute.We also discovered the growth rate dependent essentiality of reactions.

  16. Analysis of Bernstein's factorization circuit

    NARCIS (Netherlands)

    Lenstra, A.K.; Shamir, A.; Tomlinson, J.; Tromer, E.; Zheng, Y.

    2002-01-01

    In [1], Bernstein proposed a circuit-based implementation of the matrix step of the number field sieve factorization algorithm. These circuits offer an asymptotic cost reduction under the measure "construction cost x run time". We evaluate the cost of these circuits, in agreement with [1], but argue

  17. gHRV: Heart rate variability analysis made easy.

    Science.gov (United States)

    Rodríguez-Liñares, L; Lado, M J; Vila, X A; Méndez, A J; Cuesta, P

    2014-08-01

    In this paper, the gHRV software tool is presented. It is a simple, free and portable tool developed in python for analysing heart rate variability. It includes a graphical user interface and it can import files in multiple formats, analyse time intervals in the signal, test statistical significance and export the results. This paper also contains, as an example of use, a clinical analysis performed with the gHRV tool, namely to determine whether the heart rate variability indexes change across different stages of sleep. Results from tests completed by researchers who have tried gHRV are also explained: in general the application was positively valued and results reflect a high level of satisfaction. gHRV is in continuous development and new versions will include suggestions made by testers. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  18. Quantitative analysis of spatial variability of geotechnical parameters

    Science.gov (United States)

    Fang, Xing

    2018-04-01

    Geotechnical parameters are the basic parameters of geotechnical engineering design, while the geotechnical parameters have strong regional characteristics. At the same time, the spatial variability of geotechnical parameters has been recognized. It is gradually introduced into the reliability analysis of geotechnical engineering. Based on the statistical theory of geostatistical spatial information, the spatial variability of geotechnical parameters is quantitatively analyzed. At the same time, the evaluation of geotechnical parameters and the correlation coefficient between geotechnical parameters are calculated. A residential district of Tianjin Survey Institute was selected as the research object. There are 68 boreholes in this area and 9 layers of mechanical stratification. The parameters are water content, natural gravity, void ratio, liquid limit, plasticity index, liquidity index, compressibility coefficient, compressive modulus, internal friction angle, cohesion and SP index. According to the principle of statistical correlation, the correlation coefficient of geotechnical parameters is calculated. According to the correlation coefficient, the law of geotechnical parameters is obtained.

  19. Exploratory Analysis of Dengue Fever Niche Variables within the Río Magdalena Watershed

    Directory of Open Access Journals (Sweden)

    Austin Stanforth

    2016-09-01

    Full Text Available Previous research on Dengue Fever have involved laboratory tests or study areas with less diverse temperature and elevation ranges than is found in Colombia; therefore, preliminary research was needed to identify location specific attributes of Dengue Fever transmission. Environmental variables derived from the Moderate Resolution Imaging Spectroradiometer (MODIS and Tropical Rainfall Measuring Mission (TRMM satellites were combined with population variables to be statistically compared against reported cases of Dengue Fever in the Río Magdalena watershed, Colombia. Three-factor analysis models were investigated to analyze variable patterns, including a population, population density, and empirical Bayesian estimation model. Results identified varying levels of Dengue Fever transmission risk, and environmental characteristics which support, and advance, the research literature. Multiple temperature metrics, elevation, and vegetation composition were among the more contributory variables found to identify future potential outbreak locations.

  20. Radiograph and passive data analysis using mixed variable optimization

    Science.gov (United States)

    Temple, Brian A.; Armstrong, Jerawan C.; Buescher, Kevin L.; Favorite, Jeffrey A.

    2015-06-02

    Disclosed herein are representative embodiments of methods, apparatus, and systems for performing radiography analysis. For example, certain embodiments perform radiographic analysis using mixed variable computation techniques. One exemplary system comprises a radiation source, a two-dimensional detector for detecting radiation transmitted through a object between the radiation source and detector, and a computer. In this embodiment, the computer is configured to input the radiographic image data from the two-dimensional detector and to determine one or more materials that form the object by using an iterative analysis technique that selects the one or more materials from hierarchically arranged solution spaces of discrete material possibilities and selects the layer interfaces from the optimization of the continuous interface data.

  1. Statistical analysis of nuclear power plant pump failure rate variability: some preliminary results

    International Nuclear Information System (INIS)

    Martz, H.F.; Whiteman, D.E.

    1984-02-01

    In-Plant Reliability Data System (IPRDS) pump failure data on over 60 selected pumps in four nuclear power plants are statistically analyzed using the Failure Rate Analysis Code (FRAC). A major purpose of the analysis is to determine which environmental, system, and operating factors adequately explain the variability in the failure data. Catastrophic, degraded, and incipient failure severity categories are considered for both demand-related and time-dependent failures. For catastrophic demand-related pump failures, the variability is explained by the following factors listed in their order of importance: system application, pump driver, operating mode, reactor type, pump type, and unidentified plant-specific influences. Quantitative failure rate adjustments are provided for the effects of these factors. In the case of catastrophic time-dependent pump failures, the failure rate variability is explained by three factors: reactor type, pump driver, and unidentified plant-specific influences. Finally, point and confidence interval failure rate estimates are provided for each selected pump by considering the influential factors. Both types of estimates represent an improvement over the estimates computed exclusively from the data on each pump

  2. Analysis and Prediction of Micromilling Stability with Variable Tool Geometry

    Directory of Open Access Journals (Sweden)

    Ziyang Cao

    2014-11-01

    Full Text Available Micromilling can fabricate miniaturized components using micro-end mill at high rotational speeds. The analysis of machining stability in micromilling plays an important role in characterizing the cutting process, estimating the tool life, and optimizing the process. A numerical analysis and experimental method are presented to investigate the chatter stability in micro-end milling process with variable milling tool geometry. The schematic model of micromilling process is constructed and the calculation formula to predict cutting force and displacements is derived. This is followed by a detailed numerical analysis on micromilling forces between helical ball and square end mills through time domain and frequency domain method and the results are compared. Furthermore, a detailed time domain simulation for micro end milling with straight teeth and helical teeth end mill is conducted based on the machine-tool system frequency response function obtained through modal experiment. The forces and displacements are predicted and the simulation result between variable cutter geometry is deeply compared. The simulation results have important significance for the actual milling process.

  3. 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...

  4. Electromagnetic fields from mobile phone base station - variability analysis.

    Science.gov (United States)

    Bienkowski, Pawel; Zubrzak, Bartlomiej

    2015-09-01

    The article describes the character of electromagnetic field (EMF) in mobile phone base station (BS) surroundings and its variability in time with an emphasis on the measurement difficulties related to its pulse and multi-frequency nature. Work also presents long-term monitoring measurements performed recently in different locations in Poland - small city with dispersed building development and in major polish city - dense urban area. Authors tried to determine the trends in changing of EMF spectrum analyzing daily changes of measured EMF levels in those locations. Research was performed using selective electromagnetic meters and also EMF meter with spectrum analysis.

  5. An analysis of the variable radial velocity of alpha cygni

    International Nuclear Information System (INIS)

    Lucy, L.B.

    1976-01-01

    On the basis of 447 radial velocities obtained at the Lick Observatory by Paddock in the years 1927--1935, an attempt is made to discover the nature of the semiregular variability of α Cygni (A2 Ia). Harmonic analysis of the 144 velocities obtained in 1931 suggests that this variability is due to the simultaneous excitation of many discrete pulsation modes. The amplitudes and periods of these modes are then determined by least-squares fitting to all the data, and a final solution is obtained that comprises 16 terms with periods from 6.9 to 100.8 days. All terms are found to have highly significant amplitudes, and most terms also pass a test of the stability of their amplitudes and phases. Reasons are given for believing that most terms represent nonradial oscillations, and this leads to the suggestion that the resulting surface motions are to be identified with macroturbulence. An argument is also given for believing that the pulsational instability persists down to periods at which atmospheric oscillations become progressive, and this leads to the suggestion that such waves are observed as microturbulence and give rise to the observed mass loss. The importance of further monitoring of the variability of supergiants is stressed

  6. PATH ANALYSIS WITH LOGISTIC REGRESSION MODELS : EFFECT ANALYSIS OF FULLY RECURSIVE CAUSAL SYSTEMS OF CATEGORICAL VARIABLES

    OpenAIRE

    Nobuoki, Eshima; Minoru, Tabata; Geng, Zhi; Department of Medical Information Analysis, Faculty of Medicine, Oita Medical University; Department of Applied Mathematics, Faculty of Engineering, Kobe University; Department of Probability and Statistics, Peking University

    2001-01-01

    This paper discusses path analysis of categorical variables with logistic regression models. The total, direct and indirect effects in fully recursive causal systems are considered by using model parameters. These effects can be explained in terms of log odds ratios, uncertainty differences, and an inner product of explanatory variables and a response variable. A study on food choice of alligators as a numerical exampleis reanalysed to illustrate the present approach.

  7. 24-Hour Blood Pressure Variability Assessed by Average Real Variability: A Systematic Review and Meta-Analysis.

    Science.gov (United States)

    Mena, Luis J; Felix, Vanessa G; Melgarejo, Jesus D; Maestre, Gladys E

    2017-10-19

    Although 24-hour blood pressure (BP) variability (BPV) is predictive of cardiovascular outcomes independent of absolute BP levels, it is not regularly assessed in clinical practice. One possible limitation to routine BPV assessment is the lack of standardized methods for accurately estimating 24-hour BPV. We conducted a systematic review to assess the predictive power of reported BPV indexes to address appropriate quantification of 24-hour BPV, including the average real variability (ARV) index. Studies chosen for review were those that presented data for 24-hour BPV in adults from meta-analysis, longitudinal or cross-sectional design, and examined BPV in terms of the following issues: (1) methods used to calculate and evaluate ARV; (2) assessment of 24-hour BPV determined using noninvasive ambulatory BP monitoring; (3) multivariate analysis adjusted for covariates, including some measure of BP; (4) association of 24-hour BPV with subclinical organ damage; and (5) the predictive value of 24-hour BPV on target organ damage and rate of cardiovascular events. Of the 19 assessed studies, 17 reported significant associations between high ARV and the presence and progression of subclinical organ damage, as well as the incidence of hard end points, such as cardiovascular events. In all these cases, ARV remained a significant independent predictor ( P <0.05) after adjustment for BP and other clinical factors. In addition, increased ARV in systolic BP was associated with risk of all cardiovascular events (hazard ratio, 1.18; 95% confidence interval, 1.09-1.27). Only 2 cross-sectional studies did not find that high ARV was a significant risk factor. Current evidence suggests that ARV index adds significant prognostic information to 24-hour ambulatory BP monitoring and is a useful approach for studying the clinical value of BPV. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

  8. Variability of African Farming Systems from Phenological Analysis of NDVI Time Series

    Science.gov (United States)

    Vrieling, Anton; deBeurs, K. M.; Brown, Molly E.

    2011-01-01

    Food security exists when people have access to sufficient, safe and nutritious food at all times to meet their dietary needs. The natural resource base is one of the many factors affecting food security. Its variability and decline creates problems for local food production. In this study we characterize for sub-Saharan Africa vegetation phenology and assess variability and trends of phenological indicators based on NDVI time series from 1982 to 2006. We focus on cumulated NDVI over the season (cumNDVI) which is a proxy for net primary productivity. Results are aggregated at the level of major farming systems, while determining also spatial variability within farming systems. High temporal variability of cumNDVI occurs in semiarid and subhumid regions. The results show a large area of positive cumNDVI trends between Senegal and South Sudan. These correspond to positive CRU rainfall trends found and relate to recovery after the 1980's droughts. We find significant negative cumNDVI trends near the south-coast of West Africa (Guinea coast) and in Tanzania. For each farming system, causes of change and variability are discussed based on available literature (Appendix A). Although food security comprises more than the local natural resource base, our results can perform an input for food security analysis by identifying zones of high variability or downward trends. Farming systems are found to be a useful level of analysis. Diversity and trends found within farming system boundaries underline that farming systems are dynamic.

  9. Fixed capacity and variable member grouping assignment of orthogonal variable spreading factor code tree for code division multiple access networks

    Directory of Open Access Journals (Sweden)

    Vipin Balyan

    2014-08-01

    Full Text Available Orthogonal variable spreading factor codes are used in the downlink to maintain the orthogonality between different channels and are used to handle new calls arriving in the system. A period of operation leads to fragmentation of vacant codes. This leads to code blocking problem. The assignment scheme proposed in this paper is not affected by fragmentation, as the fragmentation is generated by the scheme itself. In this scheme, the code tree is divided into groups whose capacity is fixed and numbers of members (codes are variable. A group with maximum number of busy members is used for assignment, this leads to fragmentation of busy groups around code tree and compactness within group. The proposed scheme is well evaluated and compared with other schemes using parameters like code blocking probability and call establishment delay. Through simulations it has been demonstrated that the proposed scheme not only adequately reduces code blocking probability, but also requires significantly less time before assignment to locate a vacant code for assignment, which makes it suitable for the real-time calls.

  10. Heart rate variability analysis with the R package RHRV

    CERN Document Server

    García Martínez, Constantino Antonio; Vila, Xosé A; Lado Touriño, María José; Rodríguez-Liñares, Leandro; Rodríguez Presedo, Jesús María; Méndez Penín, Arturo José

    2017-01-01

    This book introduces readers to the basic concepts of Heart Rate Variability (HRV) and its most important analysis algorithms using a hands-on approach based on the open-source RHRV software. HRV refers to the variation over time of the intervals between consecutive heartbeats. Despite its apparent simplicity, HRV is one of the most important markers of the autonomic nervous system activity and it has been recognized as a useful predictor of several pathologies. The book discusses all the basic HRV topics, including the physiological contributions to HRV, clinical applications, HRV data acquisition, HRV data manipulation and HRV analysis using time-domain, frequency-domain, time-frequency, nonlinear and fractal techniques. Detailed examples based on real data sets are provided throughout the book to illustrate the algorithms and discuss the physiological implications of the results. Offering a comprehensive guide to analyzing beat information with RHRV, the book is intended for masters and Ph.D. students in v...

  11. Design of ideal cascades of gas centrifuges with variable separation factors

    International Nuclear Information System (INIS)

    Olander, D.R.

    1976-01-01

    A method of designing ideal cascades in which the separation factor varies with stage number is presented and applied to centrifuges as separating units. The centrifuge is characterized by a performance function, which gives the separative power, optimized with respect to all internal variables, as a function of cut and throughput. For centrifuges with certain types of performance functions, variable-α ideal cascades can provide a product at a lower cost than the conventional ideal cascade in which the separation factor is independent of stage number

  12. Analysis of the Variables that Affect Bookstore Customer Satisfaction

    Directory of Open Access Journals (Sweden)

    Elis Ratna Wulan

    2016-02-01

    Full Text Available Competition, which becomes more widespread, complex, and intense, drives companies to must be able to see the various opportunities that exist and to identify strategies for creating customer satisfaction. As an example of a company must be able to produce products with good quality, reasonable price, facilities, and companies are able to create a positive image in the eyes of consumers. This strategy is quite important in facing the competitive level of competition with rival firms. This research is aimed to analysis simultaneously or partially positive effect of the facilities, prices and corporate image on customer satisfaction, as well as analyzing the most dominant variable in effecting bookstore customer satisfaction. Data used in this research are primary data from Tmbookstore customer in Cianjur city, West Java Indonesia, which were collected from respondents using valid and reliable questionnaire. A total of 100 respondents were selected from Tmbookstore visitors by accidental sampling. Data were analyzed using multiple regression analysis. Results of the research indicate that product, price, location, and simultaneously affect to bookstore consumer satisfaction. Partially, only two of the three variables that affect bookstore consumer satisfaction namely price and company image. Image of the company is the most a dominant impact on bookstore customer satisfaction.

  13. Sensitivity analysis and power for instrumental variable studies.

    Science.gov (United States)

    Wang, Xuran; Jiang, Yang; Zhang, Nancy R; Small, Dylan S

    2018-03-31

    In observational studies to estimate treatment effects, unmeasured confounding is often a concern. The instrumental variable (IV) method can control for unmeasured confounding when there is a valid IV. To be a valid IV, a variable needs to be independent of unmeasured confounders and only affect the outcome through affecting the treatment. When applying the IV method, there is often concern that a putative IV is invalid to some degree. We present an approach to sensitivity analysis for the IV method which examines the sensitivity of inferences to violations of IV validity. Specifically, we consider sensitivity when the magnitude of association between the putative IV and the unmeasured confounders and the direct effect of the IV on the outcome are limited in magnitude by a sensitivity parameter. Our approach is based on extending the Anderson-Rubin test and is valid regardless of the strength of the instrument. A power formula for this sensitivity analysis is presented. We illustrate its usage via examples about Mendelian randomization studies and its implications via a comparison of using rare versus common genetic variants as instruments. © 2018, The International Biometric Society.

  14. Analysis of the Variables that Affect Bookstore Customer Satisfaction

    Directory of Open Access Journals (Sweden)

    Elis Ratna Wulan

    2015-06-01

    Full Text Available Competition, which becomes more widespread, complex, and intense, drives companies to must be able to see the various opportunities that exist and to identify strategies for creating customer satisfaction. As an example of a company must be able to produce products with good quality, reasonable price, facilities, and companies are able to create a positive image in the eyes of consumers. This strategy is quite important in facing the competitive level of competition with rival firms. This research is aimed to analysis simultaneously or partially positive effect of the facilities, prices and corporate image on customer satisfaction, as well as analyzing the most dominant variable in effecting bookstore customer satisfaction.  Data used in this research are primary data from Tmbookstore customer in Cianjur city, West Java Indonesia, which were collected from respondents using valid and reliable questionnaire. A total of 100 respondents were selected from Tmbookstore visitors by accidental sampling. Data were analyzed using multiple regression analysis. Results of the research indicate that product, price, location, and simultaneously affect to bookstore consumer satisfaction. Partially, only two of the three variables that affect bookstore consumer satisfaction namely price and company image. Image of the company is the most a dominant impact on bookstore customer satisfaction.

  15. Factors affecting the inter-annual to centennial timescale variability of Indian summer monsoon rainfall

    Science.gov (United States)

    Malik, Abdul; Brönnimann, Stefan

    2018-06-01

    The Modes of Ocean Variability (MOV) namely Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), and El Niño Southern Oscillation (ENSO) can have significant impacts on Indian Summer Monsoon Rainfall (ISMR) on different timescales. The timescales at which these MOV interacts with ISMR and the factors which may perturb their relationship with ISMR need to be investigated. We employ De-trended Cross-Correlation Analysis (DCCA), and De-trended Partial-Cross-Correlation Analysis (DPCCA) to study the timescales of interaction of ISMR with AMO, PDO, and ENSO using observational dataset (AD 1854-1999), and atmosphere-ocean-chemistry climate model simulations with SOCOL-MPIOM (AD 1600-1999). Further, this study uses De-trended Semi-Partial Cross-Correlation Analysis (DSPCCA) to address the relation between solar variability and the ISMR. We find statistically significant evidence of intrinsic correlations of ISMR with AMO, PDO, and ENSO on different timescales, consistent between model simulations and observations. However, the model fails to capture modulation in intrinsic relationship between ISRM and MOV due to external signals. Our analysis indicates that AMO is a potential source of non-stationary relationship between ISMR and ENSO. Furthermore, the pattern of correlation between ISMR and Total Solar Irradiance (TSI) is inconsistent between observations and model simulations. The observational dataset indicates statistically insignificant negative intrinsic correlation between ISMR and TSI on decadal-to-centennial timescales. This statistically insignificant negative intrinsic correlation is transformed to statistically significant positive extrinsic by AMO on 61-86-year timescale. We propose a new mechanism for Sun-monsoon connection which operates through AMO by changes in summer (June-September; JJAS) meridional gradient of tropospheric temperatures (ΔTTJJAS). There is a negative (positive) intrinsic correlation between ΔTTJJAS (AMO) and

  16. Nonalcoholic steatohepatitis in precision medicine: Unraveling the factors that contribute to individual variability.

    Science.gov (United States)

    Clarke, John D; Cherrington, Nathan J

    2015-07-01

    There are numerous factors in individual variability that make the development and implementation of precision medicine a challenge in the clinic. One of the main goals of precision medicine is to identify the correct dose for each individual in order to maximize therapeutic effect and minimize the occurrence of adverse drug reactions. Many promising advances have been made in identifying and understanding how factors such as genetic polymorphisms can influence drug pharmacokinetics (PK) and contribute to variable drug response (VDR), but it is clear that there remain many unidentified variables. Underlying liver diseases such as nonalcoholic steatohepatitis (NASH) alter absorption, distribution, metabolism, and excretion (ADME) processes and must be considered in the implementation of precision medicine. There is still a profound need for clinical investigation into how NASH-associated changes in ADME mediators, such as metabolism enzymes and transporters, affect the pharmacokinetics of individual drugs known to rely on these pathways for elimination. This review summarizes the key PK factors in individual variability and VDR and highlights NASH as an essential underlying factor that must be considered as the development of precision medicine advances. A multifactorial approach to precision medicine that considers the combination of two or more risk factors (e.g. genetics and NASH) will be required in our effort to provide a new era of benefit for patients. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. Internet Gamblers Differ on Social Variables: A Latent Class Analysis.

    Science.gov (United States)

    Khazaal, Yasser; Chatton, Anne; Achab, Sophia; Monney, Gregoire; Thorens, Gabriel; Dufour, Magali; Zullino, Daniele; Rothen, Stephane

    2017-09-01

    Online gambling has gained popularity in the last decade, leading to an important shift in how consumers engage in gambling and in the factors related to problem gambling and prevention. Indebtedness and loneliness have previously been associated with problem gambling. The current study aimed to characterize online gamblers in relation to indebtedness, loneliness, and several in-game social behaviors. The data set was obtained from 584 Internet gamblers recruited online through gambling websites and forums. Of these gamblers, 372 participants completed all study assessments and were included in the analyses. Questionnaires included those on sociodemographics and social variables (indebtedness, loneliness, in-game social behaviors), as well as the Gambling Motives Questionnaire, Gambling Related Cognitions Scale, Internet Addiction Test, Problem Gambling Severity Index, Short Depression-Happiness Scale, and UPPS-P Impulsive Behavior Scale. Social variables were explored with a latent class model. The clusters obtained were compared for psychological measures and three clusters were found: lonely indebted gamblers (cluster 1: 6.5%), not lonely not indebted gamblers (cluster 2: 75.4%), and not lonely indebted gamblers (cluster 3: 18%). Participants in clusters 1 and 3 (particularly in cluster 1) were at higher risk of problem gambling than were those in cluster 2. The three groups differed on most assessed variables, including the Problem Gambling Severity Index, the Short Depression-Happiness Scale, and the UPPS-P subscales (except the sensation seeking subscore). Results highlight significant between-group differences, suggesting that Internet gamblers are not a homogeneous group. Specific intervention strategies could be implemented for groups at risk.

  18. 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.

  19. Real analysis foundations and functions of one variable

    CERN Document Server

    Laczkovich, Miklós

    2015-01-01

    Based on courses given at Eötvös Loránd University (Hungary) over the past 30 years, this introductory textbook develops the central concepts of the analysis of functions of one variable - systematically, with many examples and illustrations, and in a manner that builds upon, and sharpens, the students' mathematical intuition. The modular organization of the book makes it adaptable for either semester or year-long introductory courses, while the wealth of material allows for it to be used at various levels of student sophistication in all programs where analysis is a part of the curriculum, including teachers' education. In the spirit of learning-by-doing, Real Analysis includes more than 500 engaging exercises for the student keen on mastering the basics of analysis. There are frequent hints and occasional complete solutions provided for the more challenging exercises making it an ideal choice for independent study. The book includes a solid grounding in the basics of logic and proofs, sets, and real numb...

  20. Structural Analysis of Correlated Factors: Lessons from the Verbal-Performance Dichotomy of the Wechsler Scales.

    Science.gov (United States)

    Macmann, Gregg M.; Barnett, David W.

    1994-01-01

    Describes exploratory and confirmatory analyses of verbal-performance procedures to illustrate concepts and procedures for analysis of correlated factors. Argues that, based on convergent and discriminant validity criteria, factors should have higher correlations with variables that they purport to measure than with other variables. Discusses…

  1. A review of factors explaining variability in fentanyl pharmacokinetics; focus on implications for cancer patients

    NARCIS (Netherlands)

    Kuip, E.J.M.; Zandvliet, M.L.; Koolen, S.L.; Mathijssen, R.H.; Rijt, C.C. van der

    2017-01-01

    Fentanyl is a strong opioid that is available for various administration routes, and which is widely used to treat cancer-related pain. Many factors influence the fentanyl pharmacokinetics leading to a wide inter- and intrapatient variability. This systematic review summarizes multiple studied

  2. Assessing factors related to waist circumference and obesity: application of a latent variable model.

    Science.gov (United States)

    Dalvand, Sahar; Koohpayehzadeh, Jalil; Karimlou, Masoud; Asgari, Fereshteh; Rafei, Ali; Seifi, Behjat; Niksima, Seyed Hassan; Bakhshi, Enayatollah

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Sahar Dalvand

    2015-01-01

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

  4. The cross wavelet analysis of dengue fever variability influenced by meteorological conditions

    Science.gov (United States)

    Lin, Yuan-Chien; Yu, Hwa-Lung; Lee, Chieh-Han

    2015-04-01

    The multiyear variation of meteorological conditions induced by climate change causes the changing diffusion pattern of infectious disease and serious epidemic situation. Among them, dengue fever is one of the most serious vector-borne diseases distributed in tropical and sub-tropical regions. Dengue virus is transmitted by several species of mosquito and causing lots amount of human deaths every year around the world. The objective of this study is to investigate the impact of meteorological variables to the temporal variation of dengue fever epidemic in southern Taiwan. Several extreme and average indices of meteorological variables, i.e. temperature and humidity, were used for this analysis, including averaged, maximum and minimum temperature, and average rainfall, maximum 1-hr rainfall, and maximum 24-hr rainfall. This study plans to identify and quantify the nonlinear relationship of meteorological variables and dengue fever epidemic, finding the non-stationary time-frequency relationship and phase lag effects of those time series from 1998-2011 by using cross wavelet method. Results show that meteorological variables all have a significant time-frequency correlation region to dengue fever epidemic in frequency about one year (52 weeks). The associated phases can range from 0 to 90 degrees (0-13 weeks lag from meteorological factors to dengue incidences). Keywords: dengue fever, cross wavelet analysis, meteorological factor

  5. Regression analysis of nuclear plant capacity factors

    International Nuclear Information System (INIS)

    Stocks, K.J.; Faulkner, J.I.

    1980-07-01

    Operating data on all commercial nuclear power plants of the PWR, HWR, BWR and GCR types in the Western World are analysed statistically to determine whether the explanatory variables size, year of operation, vintage and reactor supplier are significant in accounting for the variation in capacity factor. The results are compared with a number of previous studies which analysed only United States reactors. The possibility of specification errors affecting the results is also examined. Although, in general, the variables considered are statistically significant, they explain only a small portion of the variation in the capacity factor. The equations thus obtained should certainly not be used to predict the lifetime performance of future large reactors

  6. On the Analysis of Recurrence Characteristics at Variable Actions

    Directory of Open Access Journals (Sweden)

    Horea SANDI

    2011-07-01

    Full Text Available The paper is devoted to some methodological problems raised by the analysis of hazards due to variable actions having implications for the risk of damage to structures. The basic recurrence model used is that of Poissonian stochastic processes. The techniques of calibration of specific recurrence characteristics are discussed, adopting a critical point of view versus statistical analyses relying exclusively on data like annual maxima. The adoption of some types of distributions is critically discussed, from the point of view of their compatibility with the Poissonian model referred to. Only the Gumbel and Fréchet distributions are accepted as adequate for the purpose adopted. Starting from their common properties an unbounded family of distributions is proposed. This family makes it possible to adopt calibrations providing an approximation of unlimited closeness to observation samples. The case of a pluri-dimensional characterization of the randomness of observation data is then tackled, considering as an illustrative case the directional statistical analysis of sequences of wind events. Some specific expressions are proposed for the directional analysis, leading to a good approximation of observation samples. A case study relying on the expressions is then presented.

  7. Standardizing effect size from linear regression models with log-transformed variables for meta-analysis.

    Science.gov (United States)

    Rodríguez-Barranco, Miguel; Tobías, Aurelio; Redondo, Daniel; Molina-Portillo, Elena; Sánchez, María José

    2017-03-17

    Meta-analysis is very useful to summarize the effect of a treatment or a risk factor for a given disease. Often studies report results based on log-transformed variables in order to achieve the principal assumptions of a linear regression model. If this is the case for some, but not all studies, the effects need to be homogenized. We derived a set of formulae to transform absolute changes into relative ones, and vice versa, to allow including all results in a meta-analysis. We applied our procedure to all possible combinations of log-transformed independent or dependent variables. We also evaluated it in a simulation based on two variables either normally or asymmetrically distributed. In all the scenarios, and based on different change criteria, the effect size estimated by the derived set of formulae was equivalent to the real effect size. To avoid biased estimates of the effect, this procedure should be used with caution in the case of independent variables with asymmetric distributions that significantly differ from the normal distribution. We illustrate an application of this procedure by an application to a meta-analysis on the potential effects on neurodevelopment in children exposed to arsenic and manganese. The procedure proposed has been shown to be valid and capable of expressing the effect size of a linear regression model based on different change criteria in the variables. Homogenizing the results from different studies beforehand allows them to be combined in a meta-analysis, independently of whether the transformations had been performed on the dependent and/or independent variables.

  8. Identifying Factors Causing Variability in Greenhouse Gas (GHG) Fluxes in a Polygonal Tundra Landscape

    Science.gov (United States)

    Arora, B.; Wainwright, H. M.; Vaughn, L. S.; Curtis, J. B.; Torn, M. S.; Dafflon, B.; Hubbard, S. S.

    2017-12-01

    Greenhouse gas (GHG) flux variations in Arctic tundra environments are important to understand because of the vast amount of soil carbon stored in these regions and the potential of these regions to convert from a global carbon sink to a source under warmer conditions. Multiple factors potentially contribute to GHG flux variations observed in these environments, including snowmelt timing, growing season length, active layer thickness, water table variations, and temperature fluctuations. The objectives of this study are to investigate temporal variability in CO2 and CH4 fluxes at Barrow, AK over three successive growing seasons (2012-14) and to determine the factors influencing this variability using a novel entropy-based classification scheme. We analyzed soil, vegetation, and climate parameters as well as GHG fluxes at multiple locations within low-, flat- and high-centered polygons at Barrow, AK as part of the Next Generation Ecosystem Experiment (NGEE) Arctic project. Entropy results indicate that different environmental factors govern variability in GHG fluxes under different spatiotemporal settings. In particular, flat-centered polygons are more likely to become significant sources of CO2 during warm and dry years as opposed to high-centered polygons that contribute considerably to CO2 emissions during cold and wet years. In contrast, the highest CH4 emissions were always associated with low-centered polygons. Temporal variability in CO2 fluxes was primarily associated with factors affecting soil temperature and/or vegetation dynamics during early and late season periods. Temporal variability in CH4 fluxes was primarily associated with changes in vegetation cover and its covariability with primary controls such as seasonal thaw—rather than direct response to changes in soil moisture. Overall, entropy results document which factors became important under different spatiotemporal settings, thus providing clues concerning the manner in which ecosystem

  9. 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 ...

  10. Virulence factors and genetic variability of Staphylococcus aureus strains isolated from raw sheep's milk cheese.

    Science.gov (United States)

    Spanu, Vincenzo; Spanu, Carlo; Virdis, Salvatore; Cossu, Francesca; Scarano, Christian; De Santis, Enrico Pietro Luigi

    2012-02-01

    Contamination of dairy products with Staphylococcus aureus can be of animal or human origin. The host pathogen relationship is an important factor determining genetic polymorphism of the strains and their potential virulence. The aim of the present study was to carry out an extensive characterization of virulence factors and to study the genetic variability of S. aureus strains isolated from raw ewe's milk cheese. A total of 100 S. aureus strains isolated from cheese samples produced in 10 artisan cheese factories were analyzed for the presence of enterotoxins (sea-see) and enterotoxins-like genes (seh, sek, sel, sem, seo, sep), leukocidins, exfoliatins, haemolysins, toxic shock syndrome toxin 1 (TSST-1) and the accessory gene regulator alleles (agr). Strains were also typed using pulsed-field gel electrophoresis (PFGE). AMOVA analysis carried out on PFGE and PCR data showed that the major component explaining genetic distance between strains was the dairy of origin. Of the total isolates 81% had a pathogenicity profile ascribable to "animal" biovar while 16% could be related to "human" biovar. The biovar allowed to estimate the most likely origin of the contamination. Minimum inhibitory concentrations (MICs) of nine antimicrobial agents and the presence of the corresponding genes coding for antibiotic resistance was also investigated. 18 strains carrying blaZ gene showed resistance to ampicillin and penicillin and 6 strains carrying tetM gene were resistant to tetracycline. The presence of mecA gene and methicillin resistance, typical of strains of human origin, was never detected. The results obtained in the present study confirm that S. aureus contamination in artisan cheese production is mainly of animal origin. Copyright © 2011. Published by Elsevier B.V.

  11. Brand Loyalty Factors Affecting the Hotel Elections of Tourists investigation with Respect to the Demographic Variables

    Directory of Open Access Journals (Sweden)

    Ahmet Tayfun

    2015-12-01

    Full Text Available The purpose of this research is to investigate the factors affecting hotel guests’s brand loyalty and these factors is to determine whether there is a difference or not according to the demographic variables. Within this purpose, a survey research was conducted on the guests staying in the five star hotels of Ankara, Turkey. The research was carried out in two stages, namely the pilot study and the main study. As a result of study, while the factors affecting brand loyalty differs based on the gender and the age of the participants (p0,05

  12. Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

    Directory of Open Access Journals (Sweden)

    Hong Xue

    2018-01-01

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

  13. Within and between Individual Variability of Exposure to Work-Related Musculoskeletal Disorder Risk Factors

    Directory of Open Access Journals (Sweden)

    Mohsen Zare

    2018-05-01

    Full Text Available Industrial companies indicate a tendency to eliminate variations in operator strategies, particularly following implementation of the lean principle. Companies believe when the operators perform the same prescribed tasks, they have to execute them in the same manner (completing the same gestures and being exposed to the same risk factors. They attempt to achieve better product quality by standardizing and reducing operational leeway. However, operators adjust and modify ways of performing tasks to balance between their abilities and the requirements of the job. This study aims to investigate the variability of exposure to physical risk factors within and between operators when executing the same prescribed tasks. The Ergonomic Standard method was used to evaluate two workstations. Seven operators were observed thirty times between repeated cycle times at those workstations. The results revealed the variability of exposure to risk factors between and within operators in the repeated execution of the same tasks. Individual characteristics and operators’ strategies might generate the variability of exposure to risk factors that may be an opportunity to reduce the risks of work-related musculoskeletal disorders (WR-MSDs. However, sometimes operators’ strategies may cause overexposure to risk factors; operators most often adopt such strategies to undertake their tasks while reducing the workload.

  14. The use of cognitive ability measures as explanatory variables in regression analysis.

    Science.gov (United States)

    Junker, Brian; Schofield, Lynne Steuerle; Taylor, Lowell J

    2012-12-01

    Cognitive ability measures are often taken as explanatory variables in regression analysis, e.g., as a factor affecting a market outcome such as an individual's wage, or a decision such as an individual's education acquisition. Cognitive ability is a latent construct; its true value is unobserved. Nonetheless, researchers often assume that a test score , constructed via standard psychometric practice from individuals' responses to test items, can be safely used in regression analysis. We examine problems that can arise, and suggest that an alternative approach, a "mixed effects structural equations" (MESE) model, may be more appropriate in many circumstances.

  15. Summer U.S. Surface Air Temperature Variability: Controlling Factors and AMIP Simulation Biases

    Science.gov (United States)

    Merrifield, A.; Xie, S. P.

    2016-02-01

    This study documents and investigates biases in simulating summer surface air temperature (SAT) variability over the continental U.S. in the Coupled Model Intercomparison Project (CMIP5) Atmospheric Model Intercomparison Project (AMIP). Empirical orthogonal function (EOF) and multivariate regression analyses are used to assess the relative importance of circulation and the land surface feedback at setting summer SAT over a 30-year period (1979-2008). In observations, regions of high SAT variability are closely associated with midtropospheric highs and subsidence, consistent with adiabatic theory (Meehl and Tebaldi 2004, Lau and Nath 2012). Preliminary analysis shows the majority of the AMIP models feature high SAT variability over the central U.S., displaced south and/or west of observed centers of action (COAs). SAT COAs in models tend to be concomitant with regions of high sensible heat flux variability, suggesting an excessive land surface feedback in these models modulate U.S. summer SAT. Additionally, tropical sea surface temperatures (SSTs) play a role in forcing the leading EOF mode for summer SAT, in concert with internal atmospheric variability. There is evidence that models respond to different SST patterns than observed. Addressing issues with the bulk land surface feedback and the SST-forced component of atmospheric variability may be key to improving model skill in simulating summer SAT variability over the U.S.

  16. 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.

  17. Sensitivity analysis on uncertainty variables affecting the NPP's LUEC with probabilistic approach

    International Nuclear Information System (INIS)

    Nuryanti; Akhmad Hidayatno; Erlinda Muslim

    2013-01-01

    One thing that is quite crucial to be reviewed prior to any investment decision on the nuclear power plant (NPP) project is the calculation of project economic, including calculation of Levelized Unit Electricity Cost (LUEC). Infrastructure projects such as NPP’s project are vulnerable to a number of uncertainty variables. Information on the uncertainty variables which makes LUEC’s value quite sensitive due to the changes of them is necessary in order the cost overrun can be avoided. Therefore this study aimed to do the sensitivity analysis on variables that affect LUEC with probabilistic approaches. This analysis was done by using Monte Carlo technique that simulate the relationship between the uncertainty variables and visible impact on LUEC. The sensitivity analysis result shows the significant changes on LUEC value of AP1000 and OPR due to the sensitivity of investment cost and capacity factors. While LUEC changes due to sensitivity of U 3 O 8 ’s price looks not quite significant. (author)

  18. Quantification of variability and uncertainty in lawn and garden equipment NOx and total hydrocarbon emission factors.

    Science.gov (United States)

    Frey, H Christopher; Bammi, Sachin

    2002-04-01

    Variability refers to real differences in emissions among multiple emission sources at any given time or over time for any individual emission source. Variability in emissions can be attributed to variation in fuel or feedstock composition, ambient temperature, design, maintenance, or operation. Uncertainty refers to lack of knowledge regarding the true value of emissions. Sources of uncertainty include small sample sizes, bias or imprecision in measurements, nonrepresentativeness, or lack of data. Quantitative methods for characterizing both variability and uncertainty are demonstrated and applied to case studies of emission factors for lawn and garden (L&G) equipment engines. Variability was quantified using empirical and parametric distributions. Bootstrap simulation was used to characterize confidence intervals for the fitted distributions. The 95% confidence intervals for the mean grams per brake horsepower/hour (g/hp-hr) emission factors for two-stroke engine total hydrocarbon (THC) and NOx emissions were from -30 to +41% and from -45 to +75%, respectively. The confidence intervals for four-stroke engines were from -33 to +46% for THCs and from -27 to +35% for NOx. These quantitative measures of uncertainty convey information regarding the quality of the emission factors and serve as a basis for calculation of uncertainty in emission inventories (EIs).

  19. Heart Rate Variability Analysis in Patients with Allergic Rhinitis

    Directory of Open Access Journals (Sweden)

    Ming-Ying Lan

    2013-01-01

    Full Text Available Background. Very few studies investigate the role of the autonomic nervous system in allergic rhinitis. In this study, we evaluated the autonomic nervous system in allergic rhinitis patients using heart rate variability (HRV analysis. Methods. Eleven patients with allergic rhinitis and 13 healthy controls, aged between 19 and 40 years old, were enrolled in the study. Diagnosis of allergic rhinitis was based on clinical history, symptoms, and positive Phadiatop test. Electrocardiographic recordings on the sitting and supine positions were obtained for HRV analysis. Results. In the supine position, there were no significant statistical differences in very-low-frequency power (VLF, ≤0.04 Hz, low-frequency power (LF, 0.04–0.15 Hz, high-frequency power (HF, 0.15–0.40 Hz, and the ratio of LF to HF (LF/HF between the patient and control groups. The mean RR intervals significantly increased, while LF% and LF/HF significantly decreased in the patient group in the sitting position. Moreover, mean RR intervals, LF, and LF/HF, which were significantly different between the two positions in the control group, did not show a significant change with the posture change in the patient group. Conclusion. These suggest that patients with allergic rhinitis may have poor sympathetic modulation in the sitting position. Autonomic dysfunction may therefore play a role in the pathophysiology of allergic rhinitis.

  20. 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

  1. Climate Variability, Social and Environmental Factors, and Ross River Virus Transmission: Research Development and Future Research Needs

    Science.gov (United States)

    Tong, Shilu; Dale, Pat; Nicholls, Neville; Mackenzie, John S.; Wolff, Rodney; McMichael, Anthony J.

    2008-01-01

    Background Arbovirus diseases have emerged as a global public health concern. However, the impact of climatic, social, and environmental variability on the transmission of arbovirus diseases remains to be determined. Objective Our goal for this study was to provide an overview of research development and future research directions about the interrelationship between climate variability, social and environmental factors, and the transmission of Ross River virus (RRV), the most common and widespread arbovirus disease in Australia. Methods We conducted a systematic literature search on climatic, social, and environmental factors and RRV disease. Potentially relevant studies were identified from a series of electronic searches. Results The body of evidence revealed that the transmission cycles of RRV disease appear to be sensitive to climate and tidal variability. Rainfall, temperature, and high tides were among major determinants of the transmission of RRV disease at the macro level. However, the nature and magnitude of the interrelationship between climate variability, mosquito density, and the transmission of RRV disease varied with geographic area and socioenvironmental condition. Projected anthropogenic global climatic change may result in an increase in RRV infections, and the key determinants of RRV transmission we have identified here may be useful in the development of an early warning system. Conclusions The analysis indicates that there is a complex relationship between climate variability, social and environmental factors, and RRV transmission. Different strategies may be needed for the control and prevention of RRV disease at different levels. These research findings could be used as an additional tool to support decision making in disease control/surveillance and risk management. PMID:19079707

  2. 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.

  3. Variability in connectivity patterns of fish with ontogenetic migrations: Modelling effects of abiotic and biotic factors

    Directory of Open Access Journals (Sweden)

    Susanne Eva Tanner

    2015-10-01

    Full Text Available Connectivity is a critical property of marine fish populations as it drives population replenishment, determines colonization patterns and the resilience of populations to harvest. Understanding connectivity patterns is particularly important in species that present ontogenetic migrations and segregated habitat use during their life history, such as marine species with estuarine nursery areas. Albeit challenging, fish movement can be estimated and quantified using different methodologies depending on the life history stages of interest (e.g. biophysical modelling, otolith chemistry, genetic markers. Relative contributions from estuarine nursery areas to the adult coastal populations were determined using otolith elemental composition and maximum likelihood estimation for four commercially important species (Dicentrarchus labrax, Plathichtys flesus, Solea senegalensis and Solea solea and showed high interannual variability. Here, the effects of abiotic and biotic factors on the observed variability in connectivity rates and extent between estuarine juvenile and coastal adult subpopulations are investigated using generalized linear models (GLM and generalized mixed models (GMM. Abiotic factors impacting both larval and juvenile life history stages are included in the models (e.g. wind force and direction, NAO, water temperature while biotic factors relative to the estuarine residency of juvenile fish are evaluated (e.g. juvenile density, food availability. Factors contributing most to the observed variability in connectivity rates are singled out and compared among species. General trends are identified and results area discussed in the general context of identifying potential management frameworks applicable to different life stages and which may prove useful for ontogenetically migrating species.

  4. The role of climate and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria

    Science.gov (United States)

    Abdussalam, Auwal; Thornes, John; Leckebusch, Gregor

    2015-04-01

    Nigeria has a number of climate-sensitive infectious diseases; one of the most important of these diseases that remains a threat to public health is cholera. This study investigates the influences of both meteorological and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria. A stepwise multiple regression models are used to estimate the influence of the year-to-year variations of cholera cases and deaths for individual states in the country and as well for three groups of states that are classified based on annual rainfall amount. Specifically, seasonal mean maximum and minimum temperatures and annual rainfall totals were analysed with annual aggregate count of cholera cases and deaths, taking into account of the socioeconomic factors that are potentially enhancing vulnerability such as: absolute poverty, adult literacy, access to pipe borne water and population density. Result reveals that the most important explanatory meteorological and socioeconomic variables in explaining the spatiotemporal variability of the disease are rainfall totals, seasonal mean maximum temperature, absolute poverty, and accessibility to pipe borne water. The influences of socioeconomic factors appeared to be more pronounced in the northern part of the country, and vice-versa in the case of meteorological factors. Also, cross validated models output suggests a strong possibility of disease prediction, which will help authorities to put effective control measures in place which depend on prevention, and or efficient response.

  5. The effects of exposure to environmental factors on Heart Rate Variability: An ecological perspective

    International Nuclear Information System (INIS)

    Schnell, Izhak; Potchter, Oded; Epstein, Yoram; Yaakov, Yaron; Hermesh, Hagai; Brenner, Shmuel; Tirosh, Emanuel

    2013-01-01

    The impact of human exposure to environmental factors on Heart Rate Variability (HRV) was examined in the urban space of Tel-Aviv-Jaffa. Four environmental factors were investigated: thermal and social loads; CO concentrations and noise. Levels of HRV are explained mainly by subjective social stresses, noise and CO. The most interesting result is the fact that while subjective social stress and noise increase HRV, low levels of CO are reducing HRV to some extent moderating the impact of subjective social stress and noise. Beyond the poisoning effect of CO and the fact that extremely low levels of HRV associated with high dozes of CO increase risk for life, low levels of CO may have a narcotic effect, as it is measured by HRV. The effects of thermal loads on HRV are negligible probably due to the use of behavioral means in order to neutralize heat and cold effects. -- Highlights: ► The impact of human exposure to environmental factors on Heart Rate Variability (HRV) was examined. ► Previous studies measured human exposure to pollution by fixed monitoring stations. ► This study measured actual personal exposure by mini sensors. ► High level of subjective social load and noise increase HRV. ► Low levels of CO may have a narcotic effect, as it is measured by HRV. -- The research focuses on the effects of environmental factors; noise, subjective social stress, thermal load and CO on Heart Rate Variability

  6. Variability of in vivo recovery of factor IX after infusion of monoclonal antibody purified factor IX concentrates in patients with hemophilia B. The Mononine Study Group.

    Science.gov (United States)

    White, G C; Shapiro, A D; Kurczynski, E M; Kim, H C; Bergman, G E

    1995-05-01

    Monoclonal antibody purified factor IX concentrate, Mononine (Armour Pharmaceutical Company, Kankakee, Illinois, USA), is a recently developed replacement factor concentrate for the treatment of patients with hemophilia B. The pharmacokinetic properties of monoclonal antibody purified factor IX concentrate (MAb Factor IX concentrate) have been evaluated in only small samples of patients, and little is known about those factors that might influenced in vivo recovery of factor IX after infusion is a larger patient population. In vivo recovery of factor IX was therefore evaluated for 80 different indications in 72 patients who received MAb Factor IX concentrate for the management of spontaneous or trauma-induced bleeding, or as prophylaxis with surgery. The average recovery after infusions for presurgical pharmacokinetic analysis (mean +/- standard deviation) was 1.28 +/- 0.56 U/dl rise per U/kg infused (range 0.41-2.80), and the average recovery after all infusions for treatment was 1.23 +/- 0.49 U/dl rise per U/kg infused (range - 0.35-2.92). Recovery values for multiple MAb Factor IX doses in a given patient were also variable; the average recovery was 1.22 +/- 0.53 U/dl rise per U/kg given, and standard deviations ranged from 0.03 to 1.26. Patient age, weight, and MAb Factor IX concentrate dose minimally but significantly influenced factor IX recovery. There was no significant effect of either race, history of previous thrombotic complications during treatment with other replacement factor concentrates, or bleeding state on recovery. All of the patients treated with this preparation experienced excellent hemostasis, and no thrombotic complications were observed.

  7. Stress Intensity Factor for Interface Cracks in Bimaterials Using Complex Variable Meshless Manifold Method

    Directory of Open Access Journals (Sweden)

    Hongfen Gao

    2014-01-01

    Full Text Available This paper describes the application of the complex variable meshless manifold method (CVMMM to stress intensity factor analyses of structures containing interface cracks between dissimilar materials. A discontinuous function and the near-tip asymptotic displacement functions are added to the CVMMM approximation using the framework of complex variable moving least-squares (CVMLS approximation. This enables the domain to be modeled by CVMMM without explicitly meshing the crack surfaces. The enriched crack-tip functions are chosen as those that span the asymptotic displacement fields for an interfacial crack. The complex stress intensity factors for bimaterial interfacial cracks were numerically evaluated using the method. Good agreement between the numerical results and the reference solutions for benchmark interfacial crack problems is realized.

  8. Research on Open-Closed-Loop Iterative Learning Control with Variable Forgetting Factor of Mobile Robots

    Directory of Open Access Journals (Sweden)

    Hongbin Wang

    2016-01-01

    Full Text Available We propose an iterative learning control algorithm (ILC that is developed using a variable forgetting factor to control a mobile robot. The proposed algorithm can be categorized as an open-closed-loop iterative learning control, which produces control instructions by using both previous and current data. However, introducing a variable forgetting factor can weaken the former control output and its variance in the control law while strengthening the robustness of the iterative learning control. If it is applied to the mobile robot, this will reduce position errors in robot trajectory tracking control effectively. In this work, we show that the proposed algorithm guarantees tracking error bound convergence to a small neighborhood of the origin under the condition of state disturbances, output measurement noises, and fluctuation of system dynamics. By using simulation, we demonstrate that the controller is effective in realizing the prefect tracking.

  9. Pre-analytical and analytical factors influencing Alzheimer's disease cerebrospinal fluid biomarker variability.

    Science.gov (United States)

    Fourier, Anthony; Portelius, Erik; Zetterberg, Henrik; Blennow, Kaj; Quadrio, Isabelle; Perret-Liaudet, Armand

    2015-09-20

    A panel of cerebrospinal fluid (CSF) biomarkers including total Tau (t-Tau), phosphorylated Tau protein at residue 181 (p-Tau) and β-amyloid peptides (Aβ42 and Aβ40), is frequently used as an aid in Alzheimer's disease (AD) diagnosis for young patients with cognitive impairment, for predicting prodromal AD in mild cognitive impairment (MCI) subjects, for AD discrimination in atypical clinical phenotypes and for inclusion/exclusion and stratification of patients in clinical trials. Due to variability in absolute levels between laboratories, there is no consensus on medical cut-off value for the CSF AD signature. Thus, for full implementation of this core AD biomarker panel in clinical routine, this issue has to be solved. Variability can be explained both by pre-analytical and analytical factors. For example, the plastic tubes used for CSF collection and storage, the lack of reference material and the variability of the analytical protocols were identified as important sources of variability. The aim of this review is to highlight these pre-analytical and analytical factors and describe efforts done to counteract them in order to establish cut-off values for core CSF AD biomarkers. This review will give the current state of recommendations. Copyright © 2015. Published by Elsevier B.V.

  10. Analysis of the spatial variability of crop yield and soil properties in small agricultural plots

    Directory of Open Access Journals (Sweden)

    Vieira Sidney Rosa

    2003-01-01

    Full Text Available The objective of this study was to assess spatial variability of soil properties and crop yield under no tillage as a function of time, in two soil/climate conditions in São Paulo State, Brazil. The two sites measured approximately one hectare each and were cultivated with crop sequences which included corn, soybean, cotton, oats, black oats, wheat, rye, rice and green manure. Soil fertility, soil physical properties and crop yield were measured in a 10-m grid. The soils were a Dusky Red Latossol (Oxisol and a Red Yellow Latossol (Ultisol. Soil sampling was performed in each field every two years after harvesting of the summer crop. Crop yield was measured at the end of each crop cycle, in 2 x 2.5 m sub plots. Data were analysed using semivariogram analysis and kriging interpolation for contour map generation. Yield maps were constructed in order to visually compare the variability of yields, the variability of the yield components and related soil properties. The results show that the factors affecting the variability of crop yield varies from one crop to another. The changes in yield from one year to another suggest that the causes of variability may change with time. The changes with time for the cross semivariogram between phosphorus in leaves and soybean yield is another evidence of this result.

  11. Epigenetic variability in conversion to psychosis: novel findings from an innovative longitudinal methylomic analysis.

    Science.gov (United States)

    Kebir, Oussama; Chaumette, Boris; Krebs, Marie-Odile

    2018-04-26

    Conversion to psychosis is a longitudinal process during which several epigenetic changes have been described. We tested the hypothesis that epigenetic variability in the methylomes of ultra-high risk (UHR) individuals may contribute to the risk of conversion. We studied a longitudinal cohort of UHR individuals (n = 39) and compared two groups (converters, n = 14 vs. non-converters, n = 25). A longitudinal methylomic study was conducted using Infinium HumanMethylation450 BeadChip covering half a million cytosine-phosphate-guanine (CpG) sites across the human genome from whole-blood samples. We used two statistical methods to investigate the variability of methylation probes. (i) The search for longitudinal variable methylation probes (VMPs) based on median comparisons identified two VMPs in converters only. The first CpG was located in the MACROD2 gene and the second CpG was in an intergenic region at 8q24.21. (ii) The detection of outliers using variance analysis related to private epimutations identified a dozen CpGs in converters only and highlighted two genes (RAC1 and SPHK1) from the sphingolipid signaling pathway. Our study is the first to support increased methylome variability during conversion to psychosis. We speculate that stochastic factors could increase DNA methylation variability and have a role in the complex pathophysiology of conversion to psychosis as well as in other psychiatric diseases.

  12. Utility of Childhood Glucose Homeostasis Variables in Predicting Adult Diabetes and Related Cardiometabolic Risk Factors

    OpenAIRE

    Nguyen, Quoc Manh; Srinivasan, Sathanur R.; Xu, Ji-Hua; Chen, Wei; Kieltyka, Lyn; Berenson, Gerald S.

    2009-01-01

    OBJECTIVE This study examines the usefulness of childhood glucose homeostasis variables (glucose, insulin, and insulin resistance index [homeostasis model assessment of insulin resistance {HOMA-IR}]) in predicting pre-diabetes and type 2 diabetes and related cardiometabolic risk factors in adulthood. RESEARCH DESIGN AND METHODS This retrospective cohort study consisted of normoglycemic (n = 1,058), pre-diabetic (n = 37), and type 2 diabetic (n = 25) adults aged 19–39 years who were followed o...

  13. Risk factors for Type 2 Diabetes Mellitus in college students: association with sociodemographic variables

    Directory of Open Access Journals (Sweden)

    Adman Câmara Soares Lima

    2014-06-01

    Full Text Available OBJECTIVE: identify the modifiable risk factors for type 2 diabetes mellitus in college students and associate these factors with their sociodemographic variables.METHOD: cross-sectional study, involving 702 college students from Fortaleza-CE, Brazil. Sociodemographic, anthropometric, physical exercise data and blood pressure and fasting plasma glucose levels were collected.RESULTS: the most prevalent risk factor was sedentariness, followed by overweight, central obesity, high fasting plasma glucose and arterial hypertension. A statistically significant association was found between overweight and sex (p=0.000, age (p=0.004 and marital status (p=0.012, as well as between central obesity and age (p=0.018 and marital status (p=0.007 and between high fasting plasma glucose and sex (p=0.033.CONCLUSION: distinct risk factors were present in the study population, particularly sedentariness and overweight.

  14. Longitudinal intra- and inter-individual variability in young swimmers' performance and determinant competition factors

    Directory of Open Access Journals (Sweden)

    Jorge Estrela Morais

    2014-09-01

    Full Text Available The main purpose of this study was to follow-up the intra- and inter-individual variability of young swimmers' performance and determinant factors over two competitive seasons. Thirty young swimmers (14 boys: 12.33±0.65 years-old; 16 girls: 11.15±0.55 years-old were followed-up throughout two consecutive seasons (seven evaluation moments. Performance (100m freestyle, anthropometric, kinematic, hydrodynamic and efficiency features were evaluated. A gender and skill-level effect was observed. Boys improved in a higher amount (% comparing to girls. Overall, swimmers in skill-level 2 (both genders presented a higher intra-individual variability. Performance and anthropometrics showed a significant inter-individual variability in most moments, but hydrodynamics, kinematics and efficiency did not. Within each skill-level hydrodynamics, kinematics and efficiency were the variables that showed a high inter-individual variability. As a gender and skill-level effect was noticed in an age-group of young swimmers, coaches and practitioners should put the focus in specific and customized training plans for each skill-level of swimmers.

  15. Interannual and spatial variability of maple syrup yield as related to climatic factors

    Science.gov (United States)

    Houle, Daniel

    2014-01-01

    Sugar maple syrup production is an important economic activity for eastern Canada and the northeastern United States. Since annual variations in syrup yield have been related to climate, there are concerns about the impacts of climatic change on the industry in the upcoming decades. Although the temporal variability of syrup yield has been studied for specific sites on different time scales or for large regions, a model capable of accounting for both temporal and regional differences in yield is still lacking. In the present study, we studied the factors responsible for interregional and interannual variability in maple syrup yield over the 2001–2012 period, by combining the data from 8 Quebec regions (Canada) and 10 U.S. states. The resulting model explained 44.5% of the variability in yield. It includes the effect of climatic conditions that precede the sapflow season (variables from the previous growing season and winter), the effect of climatic conditions during the current sapflow season, and terms accounting for intercountry and temporal variability. Optimal conditions for maple syrup production appear to be spatially restricted by less favourable climate conditions occurring during the growing season in the north, and in the south, by the warmer winter and earlier spring conditions. This suggests that climate change may favor maple syrup production northwards, while southern regions are more likely to be negatively affected by adverse spring conditions. PMID:24949244

  16. Analysis of Program Obfuscation Schemes with Variable Encoding Technique

    Science.gov (United States)

    Fukushima, Kazuhide; Kiyomoto, Shinsaku; Tanaka, Toshiaki; Sakurai, Kouichi

    Program analysis techniques have improved steadily over the past several decades, and software obfuscation schemes have come to be used in many commercial programs. A software obfuscation scheme transforms an original program or a binary file into an obfuscated program that is more complicated and difficult to analyze, while preserving its functionality. However, the security of obfuscation schemes has not been properly evaluated. In this paper, we analyze obfuscation schemes in order to clarify the advantages of our scheme, the XOR-encoding scheme. First, we more clearly define five types of attack models that we defined previously, and define quantitative resistance to these attacks. Then, we compare the security, functionality and efficiency of three obfuscation schemes with encoding variables: (1) Sato et al.'s scheme with linear transformation, (2) our previous scheme with affine transformation, and (3) the XOR-encoding scheme. We show that the XOR-encoding scheme is superior with regard to the following two points: (1) the XOR-encoding scheme is more secure against a data-dependency attack and a brute force attack than our previous scheme, and is as secure against an information-collecting attack and an inverse transformation attack as our previous scheme, (2) the XOR-encoding scheme does not restrict the calculable ranges of programs and the loss of efficiency is less than in our previous scheme.

  17. Profile and Risk Factor Analysis of Unintentional Injuries in Children.

    Science.gov (United States)

    Bhamkar, Rahul; Seth, Bageshree; Setia, Maninder Singh

    2016-10-01

    To study the profile and various risk factors associated with unintentional injuries in children. The study is a cross sectional analysis of data collected from 351 children presenting with unintentional injury to a tertiary care hospital in Navi Mumbai, India. Data were collected about variables based on Haddon Phase Factor Matrix - host, environment and agent factors. Proportions for categorical variables across various groups were compared using Chi square test or Fisher's exact test. Logistic regression model was used to evaluate the factors. Falls (36 %) were the most common injuries followed by bites (23 %). Majority of children were school going children (38 %) followed by preschool children (29 %). Forty-seven percent were from lower socioeconomic class. Commonest place of injury was home (48 %) and the commonest time was evening (49 %). Though there was male predominance in injuries, the difference across gender did not vary significantly (p = 0.15). Poisonings were significantly more common in infants and toddlers and in rural population (p risk of bites compared to urban (p Profile of injuries varies widely as per the variations in agent, host and environmental factors. Socio-environmental, economic conditions and infancy-toddler age groups are predisposing risk factors for bites and poisoning. Although rural areas and lower socioeconomic class population are more vulnerable to serious types of injuries, they still lack essential basic medical care.

  18. Analysis of suspension with variable stiffness and variable damping force for automotive applications

    Directory of Open Access Journals (Sweden)

    Lalitkumar Maikulal Jugulkar

    2016-05-01

    Full Text Available Passive shock absorbers are designed for standard load condition. These give better vibration isolation performance only for the standard load condition. However, if the sprung mass is lesser than the standard mass, comfort and road holding ability is affected. It is demonstrated that sprung mass acceleration increases by 50%, when the vehicle mass varies by 100 kg. In order to obtain consistent damping performance from the shock absorber, it is essential to vary its stiffness and damping properties. In this article, a variable stiffness system is presented, which comprises of two helical springs and a variable fluid damper. Fluid damper intensity is changed in four discrete levels to achieve variable stiffness of the prototype. Numerical simulations have been performed with MATLAB Simscape and Simulink which have been with experimentation on a prototype. Furthermore, the numerical model of the prototype is used in design of real size shock absorber with variable stiffness and damping. Numerical simulation results on the real size model indicate that the peak acceleration will improve by 15% in comparison to the conventional passive solution, without significant deterioration of road holding ability. Arrangement of sensors and actuators for incorporating the system in a vehicle suspension has also been discussed.

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

    Directory of Open Access Journals (Sweden)

    Elis Ratna Wulan

    2015-04-01

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

  20. Atmospheric forcing of decadal Baltic Sea level variability in the last 200 years. A statistical analysis

    Energy Technology Data Exchange (ETDEWEB)

    Huenicke, B. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Kuestenforschung

    2008-11-06

    This study aims at the estimation of the impact of different atmospheric factors on the past sealevel variations (up to 200 years) in the Baltic Sea by statistically analysing the relationship between Baltic Sea level records and observational and proxy-based reconstructed climatic data sets. The focus lies on the identification and possible quantification of the contribution of sealevel pressure (wind), air-temperature and precipitation to the low-frequency (decadal and multi-decadal) variability of Baltic Sea level. It is known that the wind forcing is the main factor explaining average Baltic Sea level variability at inter-annual to decadal timescales, especially in wintertime. In this thesis it is statistically estimated to what extent other regional climate factors contribute to the spatially heterogeneous Baltic Sea level variations around the isostatic trend at multi-decadal timescales. Although the statistical analysis cannot be completely conclusive, as the potential climate drivers are all statistically interrelated to some degree, the results indicate that precipitation should be taken into account as an explanatory variable for sea-level variations. On the one hand it has been detected that the amplitude of the annual cycle of Baltic Sea level has increased throughout the 20th century and precipitation seems to be the only factor among those analysed (wind through SLP field, barometric effect, temperature and precipitation) that can account for this evolution. On the other hand, precipitation increases the ability to hindcast inter-annual variations of sea level in some regions and seasons, especially in the Southern Baltic in summertime. The mechanism by which precipitation exerts its influence on Baltic Sea level is not ascertained in this statistical analysis due to the lack of long salinity time series. This result, however, represents a working hypothesis that can be confirmed or disproved by long simulations of the Baltic Sea system - ocean

  1. Influence diagram of physiological and environmental factors affecting heart rate variability: an extended literature overview

    Directory of Open Access Journals (Sweden)

    Julien Fatisson

    2016-09-01

    Full Text Available Heart rate variability (HRV corresponds to the adaptation of the heart to any stimulus. In fact, among the pathologies affecting HRV the most, there are the cardiovascular diseases and depressive disorders, which are associated with high medical cost in Western societies. Consequently, HRV is now widely used as an index of health.In order to better understand how this adaptation takes place, it is necessary to examine which factors directly influence HRV, whether they have a physiological or environmental origin. The primary objective of this research is therefore to conduct a literature review in order to get a comprehensive overview of the subject.The system of these factors affecting HRV can be divided into the following five categories: physiological and pathological factors, environmental factors, lifestyle factors, non-modifiable factors and effects. The direct interrelationships between these factors and HRV can be regrouped into an influence diagram. This diagram can therefore serve as a basis to improve daily clinical practice as well as help design even more precise research protocols.

  2. Variables and risk factors associated with child abuse in daycare settings.

    Science.gov (United States)

    Schumacher, R B; Carlson, R S

    1999-09-01

    This article was developed to identify the variables associated with abuse of children in daycare centers and homes, and to specify risk factors to guide professionals and parents. The literature regarding child abuse (physical [PA], sexual [SA], and ritual [RA]) was reviewed, with emphasis on identification of variables associated with victims, perpetrators, and settings. Three factors increased the complexity of the review: (1) differences in definition and categorization complicated study comparison; (2) emotional tone affected some reviewers' definitions, methodology, and conclusions; and (3) some aspects of child abuse in daycare homes and centers have not been well researched. PA most frequently occurred in the form of over discipline, was a response to prior conflict with the child, and may have been inadvertently supported by parental permission for corporal punishment. Although SA occurred less frequently in centers than in homes, effects on the victim seemed worse in centers. SA often included PA. A Satanic overtone was frequently associated with RA, and RA coupled with SA was most devastating. Unfortunately, effects were not temporary. Males predominated the perpetrator profile. Multiple perpetrator abuse was worse (e.g., severity of intrusion). Failure of center staff to report suspicion of abuse by fellow staff or parents was cited as a worry by several researchers. Although research regarding abuse in daycare settings is sparse, one cannot wait for more or better research in order to identify risk factors. Based on literature reviewed, the authors provide risk factors for faculty, caregivers, parents, children, and professionals.

  3. Analysis of time variable gravity data over Africa

    International Nuclear Information System (INIS)

    Barletta, Valentina R.; Aoudia, Abdelkarim

    2010-01-01

    phenomena, climate and even to human activities. The time analysis approach proposed in this work is used to discriminate signals from different possible geographical sources mostly in the low latitude regions, where hydrology is strongest, as for example Africa. By applying our approach to hydrological models we can show similarities and differences with GRACE data. The similarities lie almost all in the geographical signatures of the periodic component even if there are differences in amplitudes and phase. While differences in the non-periodic component can be explained with the presence of other phenomena, the differences in the periodic component can be explained with missing groundwater or other defects in the hydrological models. In this way we tested the adequacy of some hydrological models commonly combined with gravity data to retrieve solid Earth geophysical signatures. Thus we show that analysis of time variable gravity data over Africa strongly requires a correct and reliable hydrological model. (author)

  4. Comparison of Two- and Three-Dimensional Methods for Analysis of Trunk Kinematic Variables in the Golf Swing.

    Science.gov (United States)

    Smith, Aimée C; Roberts, Jonathan R; Wallace, Eric S; Kong, Pui; Forrester, Stephanie E

    2016-02-01

    Two-dimensional methods have been used to compute trunk kinematic variables (flexion/extension, lateral bend, axial rotation) and X-factor (difference in axial rotation between trunk and pelvis) during the golf swing. Recent X-factor studies advocated three-dimensional (3D) analysis due to the errors associated with two-dimensional (2D) methods, but this has not been investigated for all trunk kinematic variables. The purpose of this study was to compare trunk kinematic variables and X-factor calculated by 2D and 3D methods to examine how different approaches influenced their profiles during the swing. Trunk kinematic variables and X-factor were calculated for golfers from vectors projected onto the global laboratory planes and from 3D segment angles. Trunk kinematic variable profiles were similar in shape; however, there were statistically significant differences in trunk flexion (-6.5 ± 3.6°) at top of backswing and trunk right-side lateral bend (8.7 ± 2.9°) at impact. Differences between 2D and 3D X-factor (approximately 16°) could largely be explained by projection errors introduced to the 2D analysis through flexion and lateral bend of the trunk and pelvis segments. The results support the need to use a 3D method for kinematic data calculation to accurately analyze the golf swing.

  5. Analysis of cataclysmic variable GSC02197-00886 evolution

    Science.gov (United States)

    Mitrofanova, A. A.; Borisov, N. V.; Shimansky, V. V.

    2014-01-01

    We present the spectral analysis of the physical state and evolution of the WZSge-type cataclysmic variable GSC02197-00886. The spectra of the system, covering the total orbital period at the time of the outburst on May 8, 2010, at the late relaxation stage, and in the quiescent state, were obtained at the SAO RAS 6-m BTA telescope in 2010-2012. From the absorption and emission HI, He I, and Fe II lines, we have determined the radial velocities for all the nights of observations and constructed the maps of Doppler tomography for the quiescent state. It was found that during the outburst the spectra of the object were formed in an optically thick accretion disk with an effective temperature of T eff ≈ 45 000 K and in a hotter boundary layer. During the relaxation of the system, the accretion disk gradually became optically thinner in the continuum and in the emission lines. In the quiescent state (July 2012), the continuous spectrum was dominated by the radiation of the cooling white dwarf with T eff = 18 000 K. The emission lines are formed on the surface of the cool star by the X-ray irradiation of the 1RXSJ213807.1+261958 source. We propose a method for determining the parameters of the white dwarf, based on the numerical modeling of the system spectra in the quiescent state and their comparison with the observed spectra. It is shown that the effective temperature of white dwarf has decreased by Δ T eff = 6000 K during the relaxation from August 2010 to July 2012. We have obtained a set of parameters for GSC02197-00886 and shown their good agreement with the average parameters of the W Z Sge-type systems, presented in the literature.

  6. Variable forgetting factor mechanisms for diffusion recursive least squares algorithm in sensor networks

    Science.gov (United States)

    Zhang, Ling; Cai, Yunlong; Li, Chunguang; de Lamare, Rodrigo C.

    2017-12-01

    In this work, we present low-complexity variable forgetting factor (VFF) techniques for diffusion recursive least squares (DRLS) algorithms. Particularly, we propose low-complexity VFF-DRLS algorithms for distributed parameter and spectrum estimation in sensor networks. For the proposed algorithms, they can adjust the forgetting factor automatically according to the posteriori error signal. We develop detailed analyses in terms of mean and mean square performance for the proposed algorithms and derive mathematical expressions for the mean square deviation (MSD) and the excess mean square error (EMSE). The simulation results show that the proposed low-complexity VFF-DRLS algorithms achieve superior performance to the existing DRLS algorithm with fixed forgetting factor when applied to scenarios of distributed parameter and spectrum estimation. Besides, the simulation results also demonstrate a good match for our proposed analytical expressions.

  7. Factors contributing to radiocaesium variability in upland sheep flocks in west Cumbria (United Kingdom)

    International Nuclear Information System (INIS)

    Beresford, N.A.; Barnett, C.L.; Wright, S.M.; Howard, B.J.; Crout, N.M.J.

    2007-01-01

    Following the Chernobyl accident in 1986, restrictions were placed on the movement and slaughter of sheep within upland areas of the UK because radiocaesium activity concentrations in their meat exceeded 1000 Bq kg -1 fresh weight. Some farms remain under restriction in 2007. From 1991 to 1993 detailed studies were conducted on three sheep farms within the restricted area of west Cumbria to systematically assess the various parameters which may contribute to the observed variability in radiocaesium activity concentrations within sheep flocks. This paper reports the spatial variation in soil and vegetation activity concentrations across the grazed areas at these farms and determines the influence of grazing behaviour on variability in 137 Cs activity concentrations between individual sheep within the flocks. Together with previously reported results, these new data are used to draw conclusions on the factors determining variability within the three flocks. However, the factors are too site specific to be able to generalise the findings to other farms within the restricted areas of the UK

  8. Antiretroviral treatment adherence as a mediating factor between psychosocial variables and HIV viral load.

    Science.gov (United States)

    Attonito, Jennifer; Dévieux, Jessy G; Lerner, Brenda D G; Hospital, Michelle M; Rosenberg, Rhonda

    2014-01-01

    Psychosocial factors may directly impact HIV health measures such as viral load (VL) whether or not patients are taking antiretroviral treatment (ART) consistently. Structural equation modeling plus Baron and Kenny's (1986) four-step approach were used to test a mediated model predicting VL among 246 HIV-infected adults who were on ART. Exogenous variables were social support, barriers to adherence, and stress. Moderators were alcohol use, marijuana use, and neurocognitive impairment. A small positive association between marijuana use and ART adherence approached significance. Only barriers to adherence predicted a decrease in adherence rates and an increase in VL. No other factors were significantly associated with either VL or adherence, and no interaction effects between exogenous variables and moderators were identified. The association between barriers to adherence and VL was partially mediated by ART adherence. Findings provide modest support for a direct link between psychosocial variables and a virologic response to ART. Copyright © 2014 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.

  9. Development of variable LRFD \\0x03C6 factors for deep foundation design due to site variability [summary].

    Science.gov (United States)

    2012-01-01

    Both the Florida Department of Transportation : (FDOT) and the Federal Highway Administration : (FHWA) specify use of fixed resistance factors () : for Load and Resistance Factored Design (LRFD) of : deep foundations, depending on design approach :...

  10. Economic analysis of variables affecting the plantain ( Musa sp ...

    African Journals Online (AJOL)

    Journal of Agriculture, Forestry and the Social Sciences ... The study examined variables affecting plantain (Musa sp) mono cropping system of production by ... land fragmentation, wrong application of fertilizer, high cost of fertilizers, lack of ...

  11. 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

  12. Lake variability: Key factors controlling mercury concentrations in New York State fish

    International Nuclear Information System (INIS)

    Simonin, Howard A.; Loukmas, Jefferey J.; Skinner, Lawrence C.; Roy, Karen M.

    2008-01-01

    A 4 year study surveyed 131 lakes across New York State beginning in 2003 to improve our understanding of mercury and gather information from previously untested waters. Our study focused on largemouth and smallmouth bass, walleye and yellow perch, common piscivorous fish shown to accumulate high mercury concentrations and species important to local fisheries. Fish from Adirondack and Catskill Forest Preserve lakes generally had higher mercury concentrations than those from lakes in other areas of the state. Variability between nearby individual lakes was observed, and could be due to differences in water chemistry, lake productivity or the abundance of wetlands in the watershed. We found the following factors impact mercury bioaccumulation: fish length, lake pH, specific conductivity, chlorophyll a, mercury concentration in the water, presence of an outlet dam and amount of contiguous wetlands. - Lake water chemistry variables, dams, and wetlands play major roles in determining fish mercury concentrations

  13. Form factors and complete spectrum of XXX antiperiodic higher spin chains by quantum separation of variables

    Energy Technology Data Exchange (ETDEWEB)

    Niccoli, G. [YITP, Stony Brook University, New York 11794-3840 (United States)

    2013-05-15

    The antiperiodic transfer matrices associated to higher spin representations of the rational 6-vertex Yang-Baxter algebra are analyzed by generalizing the approach introduced recently in the framework of Sklyanin's quantum separation of variables (SOV) for cyclic representations, spin-1/2 highest weight representations, and also for spin-1/2 representations of the 6-vertex reflection algebra. Such SOV approach allow us to derive exactly results which represent complicate tasks for more traditional methods based on Bethe ansatz and Baxter Q-operator. In particular, we both prove the completeness of the SOV characterization of the transfer matrix spectrum and its simplicity. Then, the derived characterization of local operators by Sklyanin's quantum separate variables and the expression of the scalar products of separate states by determinant formulae allow us to compute the form factors of the local spin operators by one determinant formulae similar to those of the scalar products.

  14. Impact analysis of flow variability in sizing kanbans

    Directory of Open Access Journals (Sweden)

    Isaac Pergher

    2014-02-01

    Full Text Available The aim of this paper is to analyze the effects of variability flow, advocated by Factory Physics, in sizing Kanban production systems. The variability of flow presupposes that the variability of activities performed by a process is dissipated throughout the productive flow system, causing variations in the lead time, the work-in-process levels and the equipment availability, among others. To conduct the research, we created a didactic model of discrete event computer simulation. The proposed model aims to present the possible impacts caused by the variability flow in a production system regarding the sizing of the number of Kanbans cards, by using the results supplied by two different investigated scenarios. The main results of the research allow concluding that, by comparing the two scenarios developed in the model, the presence of variability in the production system caused an average increase of 32% in the number of Kanban cards (p=0,000. This implies that, in real productive systems, the study of Kanban sizing should consider the variability of individual operations, a fact often relegated as an assumption in the formulation from classical literature on the definition of the number of Kanbans, thus providing opportunities for the development of future research.

  15. Variables As Currency: Linking Meta-Analysis Research and Data Paths in Sciences

    Directory of Open Access Journals (Sweden)

    Hua Qin

    2014-11-01

    Full Text Available Meta-analyses are studies that bring together data or results from multiple independent studies to produce new and over-arching findings. Current data curation systems only partially support meta-analytic research. Some important meta-analytic tasks, such as the selection of relevant studies for review and the integration of research datasets or findings, are not well supported in current data curation systems. To design tools and services that more fully support meta-analyses, we need a better understanding of meta-analytic research. This includes an understanding of both the practices of researchers who perform the analyses and the characteristics of the individual studies that are brought together. In this study, we make an initial contribution to filling this gap by developing a conceptual framework linking meta-analyses with data paths represented in published articles selected for the analysis. The framework focuses on key variables that represent primary/secondary datasets or derived socio-ecological data, contexts of use, and the data transformations that are applied. We introduce the notion of using variables and their relevant information (e.g., metadata and variable relationships as a type of currency to facilitate synthesis of findings across individual studies and leverage larger bodies of relevant source data produced in small science research. Handling variables in this manner provides an equalizing factor between data from otherwise disparate data-producing communities. We conclude with implications for exploring data integration and synthesis issues as well as system development.

  16. 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.

  17. 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.)

  18. Worry About Caregiving Performance: A Confirmatory Factor Analysis

    Directory of Open Access Journals (Sweden)

    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.

  19. 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

  20. Análisis cualitativo comparativo difuso para determinar influencias entre variables socio-económicas y el rendimiento académico de los universitarios || Fuzzy-Set Qualitative Comparative Analysis to Determine Effects from Socio-Economical Factors and University Students Performance

    Directory of Open Access Journals (Sweden)

    Fedriani Martel, Eugenio M.

    2018-01-01

    Full Text Available El objetivo de este artículo es explicar el rendimiento académico con la ayuda de una técnica novedosa: el análisis cualitativo comparativo difuso. Para hacerlo posible, se consideran diferentes variables que afectan a la educación superior, así como el rendimiento académico de los estudiantes universitarios. Los datos utilizados provienen de los diferentes grados impartidos en la Facultad de Ciencias Empresariales de la Universidad Pablo de Olavide, de Sevilla (España, desde el año 2009, aunque la técnica utilizada puede ser fácilmente adaptada a otros colectivos y situaciones. || The objective of this paper is to explain academic performance with the aid of an innovative technique: Fuzzy-set Qualitative Comparative Analysis (fsQCA. To do so, different objective factors, which affect higher education, are analyzed and the academic performance of university students is also considered. Specifically, data of students on different degrees in the Faculty of Business Sciences of the Pablo de Olavide University of Seville since 2009 was used, but it is believed that the methodology described can be easily extrapolated.

  1. 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.)

  2. 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

  3. 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

  4. 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.

  5. Spacesuit Glove-Induced Hand Trauma and Analysis of Potentially Related Risk Variables

    Science.gov (United States)

    Charvat, Chacqueline M.; Norcross, Jason; Reid, Christopher R.; McFarland, Shane M.

    2015-01-01

    Injuries to the hands are common among astronauts who train for extravehicular activity (EVA). When the gloves are pressurized, they restrict movement and create pressure points during tasks, sometimes resulting in pain, muscle fatigue, abrasions, and occasionally more severe injuries such as onycholysis. Glove injuries, both anecdotal and recorded, have been reported during EVA training and flight persistently through NASA's history regardless of mission or glove model. Theories as to causation such as glove-hand fit are common but often lacking in supporting evidence. Previous statistical analysis has evaluated onycholysis in the context of crew anthropometry only. The purpose of this study was to analyze all injuries (as documented in the medical records) and available risk factor variables with the goal to determine engineering and operational controls that may reduce hand injuries due to the EVA glove in the future. A literature review and data mining study were conducted between 2012 and 2014. This study included 179 US NASA crew who trained or completed an EVA between 1981 and 2010 (crossing both Shuttle and ISS eras) and wore either the 4000 Series or Phase VI glove during Extravehicular Mobility Unit (EMU) spacesuit EVA training and flight. All injuries recorded in medical records were analyzed in their association to candidate risk factor variables. Those risk factor variables included demographic characteristics, hand anthropometry, glove fit characteristics, and training/EVA characteristics. Utilizing literature, medical records and anecdotal causation comments recorded in crewmember injury data, investigators were able to identify several risk factors associated with increased risk of glove related injuries. Prime among them were smaller hand anthropometry, duration of individual suited exposures, and improper glove-hand fit as calculated by the difference in the anthropometry middle finger length compared to the baseline EVA glove middle finger length.

  6. Statistical analysis of corn yields responding to climate variability at various spatio-temporal resolutions

    Science.gov (United States)

    Jiang, H.; Lin, T.

    2017-12-01

    Rain-fed corn production systems are subject to sub-seasonal variations of precipitation and temperature during the growing season. As each growth phase has varied inherent physiological process, plants necessitate different optimal environmental conditions during each phase. However, this temporal heterogeneity towards climate variability alongside the lifecycle of crops is often simplified and fixed as constant responses in large scale statistical modeling analysis. To capture the time-variant growing requirements in large scale statistical analysis, we develop and compare statistical models at various spatial and temporal resolutions to quantify the relationship between corn yield and weather factors for 12 corn belt states from 1981 to 2016. The study compares three spatial resolutions (county, agricultural district, and state scale) and three temporal resolutions (crop growth phase, monthly, and growing season) to characterize the effects of spatial and temporal variability. Our results show that the agricultural district model together with growth phase resolution can explain 52% variations of corn yield caused by temperature and precipitation variability. It provides a practical model structure balancing the overfitting problem in county specific model and weak explanation power in state specific model. In US corn belt, precipitation has positive impact on corn yield in growing season except for vegetative stage while extreme heat attains highest sensitivity from silking to dough phase. The results show the northern counties in corn belt area are less interfered by extreme heat but are more vulnerable to water deficiency.

  7. Stepwise data envelopment analysis (DEA); choosing variables for measuring technical efficiency in Norwegian electricity distribution

    International Nuclear Information System (INIS)

    Kittelsen, S.A.C.

    1993-04-01

    Electric power distribution is an activity that in principle delivers a separate product to each customer. A specification of products for a utility as a whole leads potentially to a large number of product aspects including topographic and climatic conditions, and the level of disaggregation of factors and products may give the production and cost functions a high dimensionality. Some aggregation is therefore necessary. Non-parametric methods like Data Envelopment Analysis (DEA) have the advantage that they may give meaningful results when parametric methods would not have enough degrees of freedom, but will have related problems if the variables are collinear or are irrelevant. Although aggregate efficiency measures will not be much affected, rates of transformation will be corrupted and observations with extreme values may be measured as efficient by default. Little work has been done so far on the statistical properties of the non-parametric efficiency measure. This paper utilizes a suggestion by Rajiv Banker to measure the significance of the change in results when disaggregating or introducing an extra variable, and shows how one can let the data participate in deciding which variables should be included in the analysis. 32 refs., 7 figs., 4 tabs

  8. Real Exchange Rate Variability: An Empirical Analysis of the Developing Countries Case

    OpenAIRE

    Sebastian Edwards

    1986-01-01

    The purpose of this paper is to investigate the potential role of monetary and real factors in explaining real exchange rate variability in developing countries. For this purpose two indexes of real effective exchange rate variability that measure short-term and long-term variability were constructed for 30 countries. The results obtained, using a generalized least squares procedures on cross section data, indicate that real exchange rate variability has been affected both by real and monetar...

  9. 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

  10. 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

  11. 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.

  12. 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...

  13. Variability search in M 31 using principal component analysis and the Hubble Source Catalogue

    Science.gov (United States)

    Moretti, M. I.; Hatzidimitriou, D.; Karampelas, A.; Sokolovsky, K. V.; Bonanos, A. Z.; Gavras, P.; Yang, M.

    2018-06-01

    Principal component analysis (PCA) is being extensively used in Astronomy but not yet exhaustively exploited for variability search. The aim of this work is to investigate the effectiveness of using the PCA as a method to search for variable stars in large photometric data sets. We apply PCA to variability indices computed for light curves of 18 152 stars in three fields in M 31 extracted from the Hubble Source Catalogue. The projection of the data into the principal components is used as a stellar variability detection and classification tool, capable of distinguishing between RR Lyrae stars, long-period variables (LPVs) and non-variables. This projection recovered more than 90 per cent of the known variables and revealed 38 previously unknown variable stars (about 30 per cent more), all LPVs except for one object of uncertain variability type. We conclude that this methodology can indeed successfully identify candidate variable stars.

  14. Bayesian analysis of factors associated with fibromyalgia syndrome subjects

    Science.gov (United States)

    Jayawardana, Veroni; Mondal, Sumona; Russek, Leslie

    2015-01-01

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

  15. Glycemic variability is an independent predictive factor for development of hepatic fibrosis in nonalcoholic fatty liver disease.

    Directory of Open Access Journals (Sweden)

    Motoi Hashiba

    Full Text Available Patients with nonalcoholic fatty liver disease (NAFLD and nonalcoholic steatohepatitis (NASH often have metabolic disorders including insulin resistance and type 2 diabetes mellitus (T2DM. We clarified the predictive factors in glucose metabolism for progression of hepatic fibrosis in patients with NAFLD by the 75-g oral glucose tolerance test (75gOGTT and a continuous glucose monitoring system (CGMS. One hundred sixty-nine patients (68 female and 101 male patients with biopsy-proven NAFLD with performance with 75gOGTT were enrolled and divided into four groups according to the stage of hepatic fibrosis (F0-3. The proportion of patients with T2DM significantly gradually increased, HbA1c and the homeostasis model assessment of insulin resistance were significantly elevated, and 1,5-anhydroglucitol (1,5-AG was remarkably decreased with the progression of fibrosis. In the 75gOGTT, both plasma glucose and insulin secretion were remarkably increased with the progression of fibrosis. The only factor significantly associated with advanced fibrosis was 1,5-AG (P = 0.008 as determined by multivariate logistic regression analysis. We next evaluated the changes in blood glucose during 24 hours by monitoring with the CGMS to confirm the relationship between glycemic variability and progression of fibrosis. Variability of median glucose, standard deviation of median glucose (P = 0.0022, maximum blood glucose (P = 0.0019, and ΔMin-max blood glucose (P = 0.0029 were remarkably higher in severe fibrosis than in mild fibrosis.Hyperinsulinemia and hyperglycemia, especially glycemic variability, are important predictive factors in glucose impairment for the progression of hepatic fibrosis in NAFLD.

  16. Las variables emocionales como factores de riesgo de los trastornos de la conducta alimentaria

    Directory of Open Access Journals (Sweden)

    Aitziber Pascual

    2011-01-01

    Full Text Available Este estudio ex post facto analizó si determinadas variables emocionales pueden considerarse factores de riesgo de los trastornos de la conducta alimentaria (TCA. Se analizaron las siguientes variables: ansiedad-rasgo, dificultad para identificar y expresar las emociones (alexitimia, autoestima, actitud negativa hacia la expresión emocional, percepción negativa de las emociones, influuencia de la alimentación, el peso y la figura corporal en el estado de ánimo, necesidad de control y estrategias de afrontamiento. Participaron 368 mujeres: 78 con TCA, 145 en riesgo de TCA y 145 de un grupo de control normativo. La variable que mostró mayor capacidad discriminante de todos los tipos de riesgo frente al grupo de control fue la relativa a la influencia en el estado de ánimo. Asimismo, la baja autoestima mostró buena capacidad para discriminar el riesgo de purga/atracón, y el riesgo de anorexia y purga/atracón frente al grupo control; a su vez, las formas de afrontamiento acción impulsiva y expresión emocional mostraron buena capacidad para discriminar el riesgo de anorexia del grupo control. Estos resultados tienen implicaciones importantes tanto en el área de la evaluación como en el de la prevención de estos trastornos.

  17. Experimental Analysis of Linear Induction Motor under Variable Voltage Variable Frequency (VVVF Power Supply

    Directory of Open Access Journals (Sweden)

    Prasenjit D. Wakode

    2016-07-01

    Full Text Available This paper presents the complete analysis of Linear Induction Motor (LIM under VVVF. The complete variation of LIM air gap flux under ‘blocked Linor’ condition and starting force is analyzed and presented when LIM is given VVVF supply. The analysis of this data is important in further understanding of the equivalent circuit parameters of LIM and to study the magnetic circuit of LIM. The variation of these parameters is important to know the LIM response at different frequencies. The simulation and application of different control strategies such as vector control thus becomes quite easy to apply and understand motor’s response under such strategy of control.

  18. CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability

    Science.gov (United States)

    Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

  19. CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability: SSD Plot Diagrams

    Science.gov (United States)

    Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

  20. Variability, correlation and path coefficient analysis of seedling traits ...

    African Journals Online (AJOL)

    use

    2011-12-12

    Dec 12, 2011 ... Indirect selection is a useful means for improving yield in cotton crop. The objective of the present study was to determine the genetic variability, broad sense heritability, genetic advance and correlation among the six seedling traits and their direct and indirect effects on cotton yield by using path coefficient ...

  1. Genetic variability, correlation and path analysis in sponge gourd ...

    African Journals Online (AJOL)

    Windows-7

    2013-02-06

    Feb 6, 2013 ... fiber used in industries for filter and cleaning the motor car, glass wares, kitchen ... The fibrous vascular system inside the fruit after been separated from the skin, ... was carried out to gather information on genetic variability ...

  2. Heart rate variability analysis in acute poisoning by cholinesterase inhibitors

    OpenAIRE

    JEONG, JINWOO; KIM, YONGIN

    2017-01-01

    Heart rate variability (HRV) has been associated with a variety of clinical situations. However, few studies have examined the association between HRV and acute poisoning. Organophosphate (OP) and carbamate inhibit esterase enzymes, particularly acetylcholinesterase, resulting in an accumulation of acetylcholine and thereby promoting excessive activation of corresponding receptors. Because diagnosis and treatment of OP and carbamate poisoning greatly depend on...

  3. Analysis of North Sea Offshore Wind Power Variability

    NARCIS (Netherlands)

    Buatois, A.; Gibescu, M.; Rawn, B.G.; Van der Meijden, M.A.M.M.

    2014-01-01

    This paper evaluates, for a 2030 scenario, the impact on onshore power systems in terms of the variability of the power generated by 81 GW of offshore wind farms installed in the North Sea. Meso-scale reanalysis data are used as input for computing the hourly power production for offshore wind

  4. An Analysis of the Interactive Effects of Demographic Variables on ...

    African Journals Online (AJOL)

    This study investigated the influence of two environmental variables (social density and overcrowding) on students' learning and academic performance in selected Nigerian Universities. 150 undergraduates drawn from two universities within the middle belt region of Nigeria made up of 90 males and 60 females responded ...

  5. Predicting travel time variability for cost-benefit analysis

    NARCIS (Netherlands)

    Peer, S.; Koopmans, C.; Verhoef, E.T.

    2010-01-01

    Unreliable travel times cause substantial costs to travelers. Nevertheless, they are not taken into account in many cost-benefit-analyses (CBA), or only in very rough ways. This paper aims at providing simple rules on how variability can be predicted, based on travel time data from Dutch highways.

  6. Perceptual mapping of mulitiple variable batteries by plotting supplementary variables in correspondence analysis of rating data

    NARCIS (Netherlands)

    A. Torres (Antoni); M. van de Velden (Michel)

    2005-01-01

    textabstractIn this paper we consider the use of correspondence analysis (CA) of rating data. CA of rating data allows a joint representation of the rated items (e.g. attributes or products) and individuals. However, as the number of individuals increases, the interpretation of the CA map becomes

  7. 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

  8. Using variable transformations to perform common event analysis

    International Nuclear Information System (INIS)

    Worrell, R.B.

    1977-01-01

    Any analytical method for studying the effect of common events on the behavior of a system is considered as being a form of common event analysis. The particular common events that are involved often represent quite different phenomena, and this has led to the development of different kinds of common event analysis. For example, common mode failure analysis, common cause analysis, critical location analysis, etc., are all different kinds of common event analysis for which the common events involved represent different phenomena. However, the problem that must be solved for each of these different kinds of common event analysis is essentially the same: Determine the effect of common events on the behavior of a system. Thus, a technique that is useful in achieving one kind of common event analysis is often useful in achieving other kinds of common event analysis

  9. 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

  10. 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.

  11. Bias and Bias Correction in Multi-Site Instrumental Variables Analysis of Heterogeneous Mediator Effects

    Science.gov (United States)

    Reardon, Sean F.; Unlu, Faith; Zhu, Pei; Bloom, Howard

    2013-01-01

    We explore the use of instrumental variables (IV) analysis with a multi-site randomized trial to estimate the effect of a mediating variable on an outcome in cases where it can be assumed that the observed mediator is the only mechanism linking treatment assignment to outcomes, as assumption known in the instrumental variables literature as the…

  12. Development of variable LRFD \\0x03C6 factors for deep foundation design due to site variability.

    Science.gov (United States)

    2012-04-01

    The current design guidelines of Load and Resistance Factor Design (LRFD) specifies constant values : for deep foundation design, based on analytical method selected and degree of redundancy of the pier. : However, investigation of multiple sites in ...

  13. 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

  14. Genetic analysis of glucosinolate variability in broccoli florets using genome-anchored single nucleotide polymorphisms.

    Science.gov (United States)

    Brown, Allan F; Yousef, Gad G; Reid, Robert W; Chebrolu, Kranthi K; Thomas, Aswathy; Krueger, Christopher; Jeffery, Elizabeth; Jackson, Eric; Juvik, John A

    2015-07-01

    The identification of genetic factors influencing the accumulation of individual glucosinolates in broccoli florets provides novel insight into the regulation of glucosinolate levels in Brassica vegetables and will accelerate the development of vegetables with glucosinolate profiles tailored to promote human health. Quantitative trait loci analysis of glucosinolate (GSL) variability was conducted with a B. oleracea (broccoli) mapping population, saturated with single nucleotide polymorphism markers from a high-density array designed for rapeseed (Brassica napus). In 4 years of analysis, 14 QTLs were associated with the accumulation of aliphatic, indolic, or aromatic GSLs in floret tissue. The accumulation of 3-carbon aliphatic GSLs (2-propenyl and 3-methylsulfinylpropyl) was primarily associated with a single QTL on C05, but common regulation of 4-carbon aliphatic GSLs was not observed. A single locus on C09, associated with up to 40 % of the phenotypic variability of 2-hydroxy-3-butenyl GSL over multiple years, was not associated with the variability of precursor compounds. Similarly, QTLs on C02, C04, and C09 were associated with 4-methylsulfinylbutyl GSL concentration over multiple years but were not significantly associated with downstream compounds. Genome-specific SNP markers were used to identify candidate genes that co-localized to marker intervals and previously sequenced Brassica oleracea BAC clones containing known GSL genes (GSL-ALK, GSL-PRO, and GSL-ELONG) were aligned to the genomic sequence, providing support that at least three of our 14 QTLs likely correspond to previously identified GSL loci. The results demonstrate that previously identified loci do not fully explain GSL variation in broccoli. The identification of additional genetic factors influencing the accumulation of GSL in broccoli florets provides novel insight into the regulation of GSL levels in Brassicaceae and will accelerate development of vegetables with modified or enhanced GSL

  15. 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…

  16. 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

  17. 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

  18. 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.

  19. Variable structure control of complex systems analysis and design

    CERN Document Server

    Yan, Xing-Gang; Edwards, Christopher

    2017-01-01

    This book systematizes recent research work on variable-structure control. It is self-contained, presenting necessary mathematical preliminaries so that the theoretical developments can be easily understood by a broad readership. The text begins with an introduction to the fundamental ideas of variable-structure control pertinent to their application in complex nonlinear systems. In the core of the book, the authors lay out an approach, suitable for a large class of systems, that deals with system uncertainties with nonlinear bounds. Its treatment of complex systems in which limited measurement information is available makes the results developed convenient to implement. Various case-study applications are described, from aerospace, through power systems to river pollution control with supporting simulations to aid the transition from mathematical theory to engineering practicalities. The book addresses systems with nonlinearities, time delays and interconnections and considers issues such as stabilization, o...

  20. 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.

  1. 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…

  2. Effects of wetland vs. landscape variables on parasite communities of Rana pipiens: links to anthropogenic factors

    Science.gov (United States)

    Schotthoefer, Anna M.; Rohr, Jason R.; Cole, Rebecca A.; Koehler, Anson V.; Johnson, Catherine M.; Johnson, Lucinda B.; Beasley, Val R.

    2011-01-01

    The emergence of several diseases affecting amphibian populations worldwide has prompted investigations into determinants of the occurrence and abundance of parasites in frogs. To understand the spatial scales and identify specific environmental factors that determine risks of parasitism in frogs, helminth communities in metamorphic frogs of the northern leopard frog (Rana pipiens) were examined in relation to wetland and landscape factors at local (1 km) and regional (10 km) spatial extents in an agricultural region of Minnesota (USA) using regression analyses, ordination, and variance partitioning techniques. Greater amounts of forested and woody wetland habitats, shorter distances between woody wetlands, and smaller-sized open water patches in surrounding landscapes were the most consistently positive correlates with the abundances, richness, and diversity of helminths found in the frogs. Wetland and local landscape variables were suggested as most important for larval trematode abundances, whereas local and regional landscape variables appeared most important for adult helminths. As previously reported, the sum concentration of atrazine and its metabolite desethylatrazine, was the strongest predictor of larval trematode communities. In this report, we highlight the additional influences of landscape factors. In particular, our data suggest that anthropogenic activities that have resulted in the loss of the availability and connectivity of suitable habitats in the surrounding landscapes of wetlands are associated with declines in helminth richness and abundance, but that alteration of wetland water quality through eutrophication or pesticide contamination may facilitate the transmission of certain parasite taxa when they are present at wetlands. Although additional research is needed to quantify the negative effects of parasitism on frog populations, efforts to reduce inputs of agrochemicals into wetlands to limit larval trematode infections may be warranted

  3. 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.

  4. Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis.

    Science.gov (United States)

    Adeola, Abiodun M; Botai, Joel O; Rautenbach, Hannes; Adisa, Omolola M; Ncongwane, Katlego P; Botai, Christina M; Adebayo-Ojo, Temitope C

    2017-11-08

    The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease's transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998-2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables' and malaria cases' time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature ( R ² = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in

  5. Analysis on electronic control unit of continuously variable transmission

    Science.gov (United States)

    Cao, Shuanggui

    Continuously variable transmission system can ensure that the engine work along the line of best fuel economy, improve fuel economy, save fuel and reduce harmful gas emissions. At the same time, continuously variable transmission allows the vehicle speed is more smooth and improves the ride comfort. Although the CVT technology has made great development, but there are many shortcomings in the CVT. The CVT system of ordinary vehicles now is still low efficiency, poor starting performance, low transmission power, and is not ideal controlling, high cost and other issues. Therefore, many scholars began to study some new type of continuously variable transmission. The transmission system with electronic systems control can achieve automatic control of power transmission, give full play to the characteristics of the engine to achieve optimal control of powertrain, so the vehicle is always traveling around the best condition. Electronic control unit is composed of the core processor, input and output circuit module and other auxiliary circuit module. Input module collects and process many signals sent by sensor and , such as throttle angle, brake signals, engine speed signal, speed signal of input and output shaft of transmission, manual shift signals, mode selection signals, gear position signal and the speed ratio signal, so as to provide its corresponding processing for the controller core.

  6. 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...

  7. Physical activity as a health factor modifying heart rate variability (HRV

    Directory of Open Access Journals (Sweden)

    Nowosielska-Swadzba Danuta

    2015-03-01

    Full Text Available Purpose: The aim of the research was the evaluation of the selected HRV factors of the training volleyball players in two training periods and non-training people. Materials and methods : The study involved 8 leading volleyball players aged 20-23 and 13 non-training persons aged 19-26. The study of the training players was conducted twice: in the pre-competition and in the competition period. The study for the non-training persons was conducted once. The selected factors of the spectral analysis have been evaluated: TP [ms 2], share of LF and HF power [n.u], LF/HF indicator and time analysis factors: RR [ms], HR [1/min], RMSSD [ms]. Results : Statistically significant differences appeared only in the selected time analysis factors (RR, HR, between the group of the training and non-training persons. Other differences in the evaluated parameters were not statistically significant. Conclusions : Physical activity influences on the HRV growth. HRV measurement may serve for the control of the changes taking place in the AUN under the influence of the physical activity.

  8. Universal analytical scattering form factor for shell-, core-shell, or homogeneous particles with continuously variable density profile shape.

    Science.gov (United States)

    Foster, Tobias

    2011-09-01

    A novel analytical and continuous density distribution function with a widely variable shape is reported and used to derive an analytical scattering form factor that allows us to universally describe the scattering from particles with the radial density profile of homogeneous spheres, shells, or core-shell particles. Composed by the sum of two Fermi-Dirac distribution functions, the shape of the density profile can be altered continuously from step-like via Gaussian-like or parabolic to asymptotically hyperbolic by varying a single "shape parameter", d. Using this density profile, the scattering form factor can be calculated numerically. An analytical form factor can be derived using an approximate expression for the original Fermi-Dirac distribution function. This approximation is accurate for sufficiently small rescaled shape parameters, d/R (R being the particle radius), up to values of d/R ≈ 0.1, and thus captures step-like, Gaussian-like, and parabolic as well as asymptotically hyperbolic profile shapes. It is expected that this form factor is particularly useful in a model-dependent analysis of small-angle scattering data since the applied continuous and analytical function for the particle density profile can be compared directly with the density profile extracted from the data by model-free approaches like the generalized inverse Fourier transform method. © 2011 American Chemical Society

  9. Analysis of variables affecting drug compliance in schizophrenia

    Directory of Open Access Journals (Sweden)

    Shakeel Ansari

    2014-01-01

    Full Text Available Context: As compliance of the patient during management of schizophrenia is crucial, the current study was conducted to find out the factors that affected compliance. Aims: The aim of the study was to analyze the prevalence of noncompliance and to find out different factors affecting compliance in schizophrenic patients. Materials and Methods: Observational cross-sectional study was conducted on 100 adult schizophrenic patients. Noncompliance was assessed using the rating of medication influence (ROMI scale. Severity of illness was measured using positive and negative syndrome scale (PANSS. Results: Prevalence of noncompliance was 37%. Using ROMI scale; positive relationship with psychiatrist, family pressure for taking medications, stigma, and substance abuse were found to be significant factors. Severity of illness was also found as determining factor. Conclusion: To improve the compliance in schizophrenia patients, roles of both psychiatrists and family members are crucial.

  10. Early variability in the conceptualisation of "sustainable development and human factors".

    Science.gov (United States)

    Thatcher, Andrew

    2012-01-01

    The sub-discipline of "sustainable development and human factors" is relatively new, first being used in 2006 with a Technical Committee of the IEA being established only in 2009 and a similar special interest group on "green ergonomics" at the Institute of Ergonomics and Human Factors being established in 2010. In general though, the definitions and practice of "sustainable development" is highly contentious and ambiguous across a range of disciplines. This paper examines the diversity of definitions and approaches to sustainable development and human factors in the early papers in this sub-discipline. An examination of 45 chapters and papers (from 2008 to 2011) reveals a surprising consistency in the definitions used for sustainable development but also a large proportion of the papers where no definitions are given at all. The majority of papers were, however, biased towards an economic capital and social capital emphasis, which is to be expected of work traditionally in the ergonomics paradigm. Further, most papers were theoretical in nature demonstrating a great opportunity for empirical work. The variability in definitions is discussed in relation to the future challenges facing the growth of this emergent sub-discipline and opportunities for further theoretical and empirical work.

  11. Microsatellite marker analysis of the genetic variability in Hanoverian Hounds.

    Science.gov (United States)

    Lüpke, L; Distl, O

    2005-04-01

    Genetic variability of the dog breed Hanoverian Hound was analysed using a set of 16 microsatellites. The sample of 92 dogs was representative for the total current population [n=334, inbreeding coefficient 9.2%, relationship coefficient 11.2%] with respect to the level and distribution of the inbreeding and relationship coefficients. All microsatellites used were in Hardy-Weinberg equilibrium. The average number of alleles was 6.4. The average observed heterozygosity (H(O)) was slightly higher than the expected heterozygosity (H(E)). Dinucleotide microsatellites exhibited lower polymorphism information content (PIC) than tetranucleotide microsatellites (0.52 versus 0.66). The average PIC was 0.61. The individual inbreeding coefficient was negatively related to the average H(O) of all microsatellites, whereas the proportion of genes from introducing of Hanoverian Hounds from abroad showed no relationships to H(O). We found that the genetic variability in the Hanoverian Hounds analysed here was unexpectedly higher than that previously published for dog breeds of similar population size. Even in dog breeds of larger population size heterogyzosity was seldom higher than that observed here. The rather high genetic variability as quantified by polymorphic microsatellites in Hanoverian Hounds may be due to a large genetic variation in the founder animals of this breed and to the fact that this genetic diversity could be maintained despite genetic bottlenecks experienced by this breed in the 1920s and 1950s and despite the presence of high inbreeding and relationship coefficients for more than 50 years.

  12. 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

  13. Homogeneity analysis with k sets of variables: An alternating least squares method with optimal scaling features

    NARCIS (Netherlands)

    van der Burg, Eeke; de Leeuw, Jan; Verdegaal, Renée

    1988-01-01

    Homogeneity analysis, or multiple correspondence analysis, is usually applied tok separate variables. In this paper we apply it to sets of variables by using sums within sets. The resulting technique is called OVERALS. It uses the notion of optimal scaling, with transformations that can be multiple

  14. Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

    DEFF Research Database (Denmark)

    Dechesne, Arnaud; Badawi, N.; Aamand, Jens

    2014-01-01

    across pesticide classes: they include some soil characteristics (pH) and some agricultural management practices (pesticide application, tillage), while other potential controlling factors have more conflicting effects depending on the site or the pesticide. Evidence demonstrating the importance......Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we...... critically examine the literature on spatial variability of pesticide biodegradation in agricultural soil. We discuss the motivations, methods, and main findings of the primary literature. We found significant diversity in the approaches used to describe and quantify spatial heterogeneity, which complicates...

  15. 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

  16. 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...

  17. 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

  18. 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....

  19. Transient analysis of a variable speed rotary compressor

    International Nuclear Information System (INIS)

    Park, Youn Cheol

    2010-01-01

    A transient simulation model of a rolling piston type rotary compressor is developed to predict the dynamic characteristics of a variable speed compressor. The model is based on the principles of conservation, real gas equations, kinematics of the crankshaft and roller, mass flow loss due to leakage, and heat transfer. For the computer simulation of the compressor, the experimental data were obtained from motor performance tests at various operating frequencies. Using the developed model, re-expansion loss, friction loss, mass flow loss and heat transfer loss is estimated as a function of the crankshaft speed in a variable speed compressor. In addition, the compressor efficiency and energy losses are predicted at various compressor-operating frequencies. Since the transient state of the compressor strongly depends on the system, the developed model is combined with a transient system simulation program to get transient variations of the compression process in the system. Motor efficiency, mechanical efficiency, motor torque and volumetric efficiency are calculated with respect to variation of the driving frequency in a rotary compressor.

  20. Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

    Directory of Open Access Journals (Sweden)

    Arnaud eDechesne

    2014-12-01

    Full Text Available Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we critically examine the literature on spatial variability of pesticide biodegradation in agricultural soil. We discuss the motivations, methods, and main findings of the primary literature. We found significant diversity in the approaches used to describe and quantify spatial heterogeneity, which complicates inter-studies comparisons. However, it is clear that the presence and activity of pesticide degraders is often highly spatially variable with coefficients of variation often exceeding 50% and frequently displays nonrandom spatial patterns. A few controlling factors have tentatively been identified across pesticide classes: they include some soil characteristics (pH and some agricultural management practices (pesticide application, tillage, while other potential controlling factors have more conflicting effects depending on the site or the pesticide. Evidence demonstrating the importance of spatial heterogeneity on the fate of pesticides in soil has been difficult to obtain but modelling and experimental systems that do not include soil’s full complexity reveal that this heterogeneity must be considered to improve prediction of pesticide biodegradation rates or of leaching risks. Overall, studying the spatial heterogeneity of pesticide biodegradation is a relatively new field at the interface of agronomy, microbial ecology, and geosciences and a wealth of novel data is being collected from these different disciplinary perspectives. We make suggestions on possible avenues to take full advantage of these investigations for a better understanding and prediction of the fate of pesticides in soil.

  1. Approaches for modeling within subject variability in pharmacometric count data analysis: dynamic inter-occasion variability and stochastic differential equations.

    Science.gov (United States)

    Deng, Chenhui; Plan, Elodie L; Karlsson, Mats O

    2016-06-01

    Parameter variation in pharmacometric analysis studies can be characterized as within subject parameter variability (WSV) in pharmacometric models. WSV has previously been successfully modeled using inter-occasion variability (IOV), but also stochastic differential equations (SDEs). In this study, two approaches, dynamic inter-occasion variability (dIOV) and adapted stochastic differential equations, were proposed to investigate WSV in pharmacometric count data analysis. These approaches were applied to published count models for seizure counts and Likert pain scores. Both approaches improved the model fits significantly. In addition, stochastic simulation and estimation were used to explore further the capability of the two approaches to diagnose and improve models where existing WSV is not recognized. The results of simulations confirmed the gain in introducing WSV as dIOV and SDEs when parameters vary randomly over time. Further, the approaches were also informative as diagnostics of model misspecification, when parameters changed systematically over time but this was not recognized in the structural model. The proposed approaches in this study offer strategies to characterize WSV and are not restricted to count data.

  2. Initiating an ergonomic analysis. A process for jobs with highly variable tasks.

    Science.gov (United States)

    Conrad, K M; Lavender, S A; Reichelt, P A; Meyer, F T

    2000-09-01

    Occupational health nurses play a vital role in addressing ergonomic problems in the workplace. Describing and documenting exposure to ergonomic risk factors is a relatively straightforward process in jobs in which the work is repetitive. In other types of work, the analysis becomes much more challenging because tasks may be repeated infrequently, or at irregular time intervals, or under different environmental and temporal conditions, thereby making it difficult to observe a "representative" sample of the work performed. This article describes a process used to identify highly variable job tasks for ergonomic analyses. The identification of tasks for ergonomic analysis was a two step process involving interviews and a survey of firefighters and paramedics from a consortium of 14 suburban fire departments. The interviews were used to generate a list of frequently performed, physically strenuous job tasks and to capture clear descriptions of those tasks and associated roles. The goals of the survey were to confirm the interview findings across the entire target population and to quantify the frequency and degree of strenuousness of each task. In turn, the quantitative results from the survey were used to prioritize job tasks for simulation. Although this process was used to study firefighters and paramedics, the approach is likely to be suitable for many other types of occupations in which the tasks are highly variable in content and irregular in frequency.

  3. Dimensional analysis of heart rate variability in heart transplant recipients

    Energy Technology Data Exchange (ETDEWEB)

    Zbilut, J.P.; Mayer-Kress, G.; Geist, K.

    1987-01-01

    We discuss periodicities in the heart rate in normal and transplanted hearts. We then consider the possibility of dimensional analysis of these periodicities in transplanted hearts and problems associated with the record.

  4. GIS and correlation analysis of geo-environmental variables ...

    African Journals Online (AJOL)

    Key words: Correlation, GIS, malaria geography, malaria incidence ... problems, as it has created the possibility for geocoding, extracting and spatial analysis of health ...... Bulletin of the World Health Organization, 78(12), 1438–1444. Carter ...

  5. A Generalized Stability Analysis of the AMOC in Earth System Models: Implication for Decadal Variability and Abrupt Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Fedorov, Alexey V. [Yale Univ., New Haven, CT (United States)

    2015-01-14

    The central goal of this research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) as related to climate variability and abrupt climate change within a hierarchy of climate models ranging from realistic ocean models to comprehensive Earth system models. Generalized Stability Analysis, a method that quantifies the transient and asymptotic growth of perturbations in the system, is one of the main approaches used throughout this project. The topics we have explored range from physical mechanisms that control AMOC variability to the factors that determine AMOC predictability in the Earth system models, to the stability and variability of the AMOC in past climates.

  6. Factors in Variability of Serial Gabapentin Concentrations in Elderly Patients with Epilepsy.

    Science.gov (United States)

    Conway, Jeannine M; Eberly, Lynn E; Collins, Joseph F; Macias, Flavia M; Ramsay, R Eugene; Leppik, Ilo E; Birnbaum, Angela K

    2017-10-01

    To characterize and quantify the variability of serial gabapentin concentrations in elderly patients with epilepsy. This study included 83 patients (age ≥ 60 yrs) from an 18-center randomized double-blind double-dummy parallel study from the Veterans Affairs Cooperative 428 Study. All patients were taking 1500 mg/day gabapentin. Within-person coefficient of variation (CV) in gabapentin concentrations, measured weekly to bimonthly for up to 52 weeks, then quarterly, was computed. Impact of patient characteristics on gabapentin concentrations (linear mixed model) and CV (linear regression) were estimated. A total of 482 gabapentin concentration measurements were available for analysis. Gabapentin concentrations and intrapatient CVs ranged from 0.5 to 22.6 μg/ml (mean 7.9 μg/ml, standard deviation [SD] 4.1 μg/ml) and 2% to 79% (mean 27.9%, SD 15.3%), respectively, across all visits. Intrapatient CV was higher by 7.3% for those with a body mass index of ≥ 30 kg/m 2 (coefficient = 7.3, p=0.04). CVs were on average 0.5% higher for each 1-unit higher CV in creatinine clearance (coefficient = 0.5, p=0.03) and 1.2% higher for each 1-hour longer mean time after dose (coefficient = 1.2, p=0.04). Substantial intrapatient variability in serial gabapentin concentration was noted in elderly patients with epilepsy. Creatinine clearance, time of sampling relative to dose, and obesity were found to be positively associated with variability. © 2017 Pharmacotherapy Publications, Inc.

  7. Latent vs. Observed Variables : Analysis of Irrigation Water Efficiency Using SEM and SUR

    NARCIS (Netherlands)

    Tang, Jianjun; Folmer, Henk

    In this paper we compare conceptualising single factor technical and allocative efficiency as indicators of a single latent variable, or as separate observed variables. In the former case, the impacts on both efficiency types are analysed by means of structural equationmodeling (SEM), in the latter

  8. 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)

  9. A MAD Explanation for the Correlation between Bulk Lorentz Factor and Minimum Variability Timescale

    Science.gov (United States)

    Lloyd-Ronning, Nicole; Lei, Wei-hua; Xie, Wei

    2018-04-01

    We offer an explanation for the anti-correlation between the minimum variability timescale (MTS) in the prompt emission light curve of gamma-ray bursts (GRBs) and the estimated bulk Lorentz factor of these GRBs, in the context of a magnetically arrested disk (MAD) model. In particular, we show that previously derived limits on the maximum available energy per baryon in a Blandford-Znajek jet leads to a relationship between the characteristic MAD timescale in GRBs and the maximum bulk Lorentz factor: tMAD∝Γ-6, somewhat steeper than (although within the error bars of) the fitted relationship found in the GRB data. Similarly, the MAD model also naturally accounts for the observed anti-correlation between MTS and gamma-ray luminosity L in the GRB data, and we estimate the accretion rates of the GRB disk (given these luminosities) in the context of this model. Both of these correlations (MTS - Γ and MTS - L) are also observed in the AGN data, and we discuss the implications of our results in the context of both GRB and blazar systems.

  10. On variable geometric factor systems for top-hat electrostatic space plasma analyzers

    International Nuclear Information System (INIS)

    Collinson, Glyn A; Kataria, Dhiren O

    2010-01-01

    Even in the relatively small region of space that is the Earth's magnetosphere, ion and electron fluxes can vary by several orders of magnitude. Top-hat electrostatic analyzers currently do not possess the dynamic range required to sample plasma under all conditions. The purpose of this study was to compare, through computer simulation, three new electrostatic methods that would allow the sensitivity of a sensor to be varied through control of its geometric factor (GF) (much like an aperture on a camera). The methods studied were inner filter plates, split hemispherical analyzer (SHA) and top-cap electrode. This is the first discussion of the filter plate concept and also the first study where all three systems are studied within a common analyzer design, so that their relative merits could be fairly compared. Filter plates were found to have the important advantage that they facilitate the reduction in instrument sensitivity whilst keeping all other instrument parameters constant. However, it was discovered that filter plates have numerous disadvantages that make such a system impracticable for a top-hat electrostatic analyzer. It was found that both the top-cap electrode and SHA are promising variable geometric factor system (VGFS) concepts for implementation into a top-hat electrostatic analyzer, each with distinct advantages over the other

  11. The Effect of Birth Weight on Academic Performance: Instrumental Variable Analysis.

    Science.gov (United States)

    Lin, Shi Lin; Leung, Gabriel Matthew; Schooling, C Mary

    2017-05-01

    Observationally, lower birth weight is usually associated with poorer academic performance; whether this association is causal or the result of confounding is unknown. To investigate this question, we obtained an effect estimate, which can have a causal interpretation under specific assumptions, of birth weight on educational attainment using instrumental variable analysis based on single nucleotide polymorphisms determining birth weight combined with results from the Social Science Genetic Association Consortium study of 126,559 Caucasians. We similarly obtained an estimate of the effect of birth weight on academic performance in 4,067 adolescents from Hong Kong's (Chinese) Children of 1997 birth cohort (1997-2016), using twin status as an instrumental variable. Birth weight was not associated with years of schooling (per 100-g increase in birth weight, -0.006 years, 95% confidence interval (CI): -0.02, 0.01) or college completion (odds ratio = 1.00, 95% CI: 0.96, 1.03). Birth weight was also unrelated to academic performance in adolescents (per 100-g increase in birth weight, -0.004 grade, 95% CI: -0.04, 0.04) using instrumental variable analysis, although conventional regression gave a small positive association (0.02 higher grade, 95% CI: 0.01, 0.03). Observed associations of birth weight with academic performance may not be causal, suggesting that interventions should focus on the contextual factors generating this correlation. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  12. Multivariate factor analysis of Girgentana goat milk composition

    Directory of Open Access Journals (Sweden)

    Pietro Giaccone

    2010-01-01

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

  13. Variability in microbiological degradation experiments, analysis and case study

    DEFF Research Database (Denmark)

    Sommer, Helle Mølgaard

    1997-01-01

    and describes analysis techniques for testing the reproducibility of a given experiment. The parameter estimation method employed for the experiments in this study is based on an iterative maximum likelihood method and the test statistic is an approximated likelihood ratio test. The estimations were carried out...

  14. Analysis of Secret Key Randomness Exploiting the Radio Channel Variability

    Directory of Open Access Journals (Sweden)

    Taghrid Mazloum

    2015-01-01

    Full Text Available A few years ago, physical layer based techniques have started to be considered as a way to improve security in wireless communications. A well known problem is the management of ciphering keys, both regarding the generation and distribution of these keys. A way to alleviate such difficulties is to use a common source of randomness for the legitimate terminals, not accessible to an eavesdropper. This is the case of the fading propagation channel, when exact or approximate reciprocity applies. Although this principle has been known for long, not so many works have evaluated the effect of radio channel properties in practical environments on the degree of randomness of the generated keys. To this end, we here investigate indoor radio channel measurements in different environments and settings at either 2.4625 GHz or 5.4 GHz band, of particular interest for WIFI related standards. Key bits are extracted by quantizing the complex channel coefficients and their randomness is evaluated using the NIST test suite. We then look at the impact of the carrier frequency, the channel variability in the space, time, and frequency degrees of freedom used to construct a long secret key, in relation to the nature of the radio environment such as the LOS/NLOS character.

  15. Analysis of North Sea Offshore Wind Power Variability

    Directory of Open Access Journals (Sweden)

    Aymeric Buatois

    2014-05-01

    Full Text Available This paper evaluates, for a 2030 scenario, the impact on onshore power systems in terms of the variability of the power generated by 81 GW of offshore wind farms installed in the North Sea. Meso-scale reanalysis data are used as input for computing the hourly power production for offshore wind farms, and this total production is analyzed to identify the largest aggregated hourly power variations. Based on publicly available information, a simplified representation of the coastal power grid is built for the countries bordering the North Sea. Wind farms less than 60 km from shore are connected radially to the mainland, while the rest are connected to a hypothetical offshore HVDC (High-Voltage Direct Current power grid, designed such that wind curtailment does not exceed 1% of production. Loads and conventional power plants by technology and associated cost curves are computed for the various national power systems, based on 2030 projections. Using the MATLAB-based MATPOWER toolbox, the hourly optimal power flow for this regional hybrid AC/DC grid is computed for high, low and medium years from the meso-scale database. The largest net load variations are evaluated per market area and related to the extra load-following reserves that may be needed from conventional generators.

  16. VAM2D: Variably saturated analysis model in two dimensions

    International Nuclear Information System (INIS)

    Huyakorn, P.S.; Kool, J.B.; Wu, Y.S.

    1991-10-01

    This report documents a two-dimensional finite element model, VAM2D, developed to simulate water flow and solute transport in variably saturated porous media. Both flow and transport simulation can be handled concurrently or sequentially. The formulation of the governing equations and the numerical procedures used in the code are presented. The flow equation is approximated using the Galerkin finite element method. Nonlinear soil moisture characteristics and atmospheric boundary conditions (e.g., infiltration, evaporation and seepage face), are treated using Picard and Newton-Raphson iterations. Hysteresis effects and anisotropy in the unsaturated hydraulic conductivity can be taken into account if needed. The contaminant transport simulation can account for advection, hydrodynamic dispersion, linear equilibrium sorption, and first-order degradation. Transport of a single component or a multi-component decay chain can be handled. The transport equation is approximated using an upstream weighted residual method. Several test problems are presented to verify the code and demonstrate its utility. These problems range from simple one-dimensional to complex two-dimensional and axisymmetric problems. This document has been produced as a user's manual. It contains detailed information on the code structure along with instructions for input data preparation and sample input and printed output for selected test problems. Also included are instructions for job set up and restarting procedures. 44 refs., 54 figs., 24 tabs

  17. Statictical Analysis Of The Conditioning Factors Of Urban Electric Consumption

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  18. Comparative study of the effect of chemical and physical factors on the variability of almond

    International Nuclear Information System (INIS)

    Imamaliev, G.N.; Akhund-Zade, I.M.; Brazhnikova, G.B.

    1975-01-01

    Six vareties of almond: Texas, Krymskij, Nek-ultra, Logindok, Drejk and Myagkoskorlupyj have been studied. It is shown that gamma-irradiation at a dose up to 16 kr induces 16 to 43 % changes in plants. A dose of 32 kr induces 33 to 60 % changes, 40 t0 50 kr - 65 to 90 % changes, but with a less percentage of survived plants. High doses of gamma-radiation induces a broad spectrum of variability, is not observed under the treatment of seeds with chemical mutagens. A dose of 32 to 40 kr has been found to be critical for the varieties studied, a dose of 50 kr - to be lethal. At a dose of 50 kr the seedlings either do not survive to the end of the vegetative period, or only 3 to 5 plants survie. A chemical mutagen, ethylmethanesulphonate (EMS) at a concentration of 0.1 to 0.2 % produc 12 to 13 % morphological changes, the percentage of survived plants being higher as compared with gamma-radiation. The mutagen concentration of 0.4% produces 90 to 93 % changed plants, the plant survival being 50 to 57 %. The 0.4% concentration can be taken as a critical one for the varieties studied. Comparative evaluations of gamma-radiation and chemical mutagens reveale that EMS at concentrations studied produces 3 to 4 times more changes than gamma-rays, the percentage of survived plants being also 3 to 4 times higher. However, EMS produces monotypic changes, while gamma-radiation induces a broad spectrum of variability. Thus, EMS can be used as a factor inducing dwarf varieties of almond and other fruit cultures

  19. A method for calorimetric analysis in variable conditions heating

    International Nuclear Information System (INIS)

    Berthier, G.

    1965-01-01

    By the analysis of the thermal transition conditions given by the quenching of a sample in a furnace maintained at a high temperature, it is possible to study the thermal diffusivity of some materials and those of solid state structure transformation on a qualitative as well as a quantitative standpoint. For instance the transformation energy of α-quartz into β-quartz and the Wigner energy stored within neutron-irradiated beryllium oxide have been measured. (author) [fr

  20. 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

  1. Iterative Strain-Gage Balance Calibration Data Analysis for Extended Independent Variable Sets

    Science.gov (United States)

    Ulbrich, Norbert Manfred

    2011-01-01

    A new method was developed that makes it possible to use an extended set of independent calibration variables for an iterative analysis of wind tunnel strain gage balance calibration data. The new method permits the application of the iterative analysis method whenever the total number of balance loads and other independent calibration variables is greater than the total number of measured strain gage outputs. Iteration equations used by the iterative analysis method have the limitation that the number of independent and dependent variables must match. The new method circumvents this limitation. It simply adds a missing dependent variable to the original data set by using an additional independent variable also as an additional dependent variable. Then, the desired solution of the regression analysis problem can be obtained that fits each gage output as a function of both the original and additional independent calibration variables. The final regression coefficients can be converted to data reduction matrix coefficients because the missing dependent variables were added to the data set without changing the regression analysis result for each gage output. Therefore, the new method still supports the application of the two load iteration equation choices that the iterative method traditionally uses for the prediction of balance loads during a wind tunnel test. An example is discussed in the paper that illustrates the application of the new method to a realistic simulation of temperature dependent calibration data set of a six component balance.

  2. Patterns in the Physical, Chemical, and Biological Composition of Icelandic Lakes and the Dominant Factors Controlling Variability Across Watersheds

    Science.gov (United States)

    Greco, A.; Strock, K.; Edwards, B. R.

    2017-12-01

    Fourteen lakes were sampled in the southern and western area of Iceland in June of 2017. The southern systems, within the Eastern Volcanic Zone, have minimal soil development and active volcanoes that produce ash input to lakes. Lakes in the Western Volcanic Zone were more diverse and located in older bedrock with more extensively weathered soil. Physical variables (temperature, oxygen concentration, and water clarity), chemical variables (pH, conductivity, dissolved and total nitrogen and phosphorus concentrations, and dissolved organic carbon concentration), and biological variables (algal biomass) were compared across the lakes sampled in these geographic regions. There was a large range in lake characteristics, including five to eighteen times higher algal biomass in the southern systems that experience active ash input to lakes. The lakes located in the Eastern Volcanic Zone also had higher conductivity and lower pH, especially in systems receiving substantial geothermal input. These results were analyzed in the context of more extensive lake sampling efforts across Iceland (46 lakes) to determine defining characteristics of lakes in each region and to identify variables that drive heterogeneous patterns in physical, chemical, and biological lake features within each region. Coastal systems, characterized by high conductivity, and glacially-fed systems, characterized by high iron concentrations, were unique from lakes in all other regions. Clustering and principal component analyses revealed that lake type (plateau, valley, spring-fed, and direct-runoff) was not the primary factor explaining variability in lake chemistry outside of the coastal and glacial lake types. Instead, lakes differentiated along a gradient of iron concentration and total nitrogen concentration. The physical and chemical properties of subarctic lakes are especially susceptible to both natural and human-induced environmental impacts. However, relatively little is known about the

  3. Ischemic risk stratification by means of multivariate analysis of the heart rate variability

    International Nuclear Information System (INIS)

    Valencia, José F; Vallverdú, Montserrat; Caminal, Pere; Porta, Alberto; Voss, Andreas; Schroeder, Rico; Vázquez, Rafael; Bayés de Luna, Antonio

    2013-01-01

    In this work, a univariate and multivariate statistical analysis of indexes derived from heart rate variability (HRV) was conducted to stratify patients with ischemic dilated cardiomyopathy (IDC) in cardiac risk groups. Indexes conditional entropy, refined multiscale entropy (RMSE), detrended fluctuation analysis, time and frequency analysis, were applied to the RR interval series (beat-to-beat series), for single and multiscale complexity analysis of the HRV in IDC patients. Also, clinical parameters were considered. Two different end-points after a follow-up of three years were considered: (i) analysis A, with 151 survivor patients as a low risk group and 13 patients that suffered sudden cardiac death as a high risk group; (ii) analysis B, with 192 survivor patients as a low risk group and 30 patients that suffered cardiac mortality as a high risk group. A univariate and multivariate linear discriminant analysis was used as a statistical technique for classifying patients in risk groups. Sensitivity (Sen) and specificity (Spe) were calculated as diagnostic criteria in order to evaluate the performance of the indexes and their linear combinations. Sen and Spe values of 80.0% and 72.9%, respectively, were obtained during daytime by combining one clinical parameter and one index from RMSE, and during nighttime Sen = 80% and Spe = 73.4% were attained by combining one clinical factor and two indexes from RMSE. In particular, relatively long time scales were more relevant for classifying patients into risk groups during nighttime, while during daytime shorter scales performed better. The results suggest that the left atrial size, indexed to body surface and RMSE indexes are those that allow enhanced classification of ischemic patients in their respective risk groups, confirming that a single measurement is not enough to fully characterize ischemic risk patients and the clinical relevance of HRV complexity measures. (paper)

  4. 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.

  5. Partial differential equations with variable exponents variational methods and qualitative analysis

    CERN Document Server

    Radulescu, Vicentiu D

    2015-01-01

    Partial Differential Equations with Variable Exponents: Variational Methods and Qualitative Analysis provides researchers and graduate students with a thorough introduction to the theory of nonlinear partial differential equations (PDEs) with a variable exponent, particularly those of elliptic type. The book presents the most important variational methods for elliptic PDEs described by nonhomogeneous differential operators and containing one or more power-type nonlinearities with a variable exponent. The authors give a systematic treatment of the basic mathematical theory and constructive meth

  6. Application of factor analysis in identification of dominant hydrogeochemical processes of some nitrogenous groundwater of Serbia

    Directory of Open Access Journals (Sweden)

    Stojković Jana

    2013-01-01

    Full Text Available Multivariate statistical analyses are used for reducing large datasets to a smaller number of variables, which explain main hydrogeochemical processes that control water geochemistry. Factor analysis (FA allows discovering intercorrelations inside the data matrix and grouping of similar variables, i.e. chemical parameters. In this way new variables are extracted, which are called factors, and each factor is explained by some hydrogeochemical process. Applying FA to a dataset that consists of 15 chemical parameters measured on 40 groundwater samples from Serbia, four factors were extracted, which explain 73.9% of total variance in the analyzed dataset. Interpretation of obtained factors indicated several hydrogeochemical processes: the impact of sea water intrusions and volatiles in previous geological periods, solutes diffusion from the marine clay, cation exchange and dissolution of carbonate and silicate minerals. [Projekat Ministarstva nauke Republike Srbije, br. 43004

  7. DNA flow cytometric analysis in variable types of hydropic placentas

    Directory of Open Access Journals (Sweden)

    Fatemeh Atabaki pasdar

    2015-05-01

    Full Text Available Background: Differential diagnosis between complete hydatidiform mole, partial hydatidiform mole and hydropic abortion, known as hydropic placentas is still a challenge for pathologists but it is very important for patient management. Objective: We analyzed the nuclear DNA content of various types of hydropic placentas by flowcytometry. Materials and Methods: DNA ploidy analysis was performed in 20 non-molar (hydropic and non-hydropic spontaneous abortions and 20 molar (complete and partial moles, formalin-fixed, paraffin-embedded tissue samples by flow cytometry. The criteria for selection were based on the histopathologic diagnosis. Results: Of 10 cases histologically diagnosed as complete hydatiform mole, 9 cases yielded diploid histograms, and 1 case was tetraploid. Of 10 partial hydatidiform moles, 8 were triploid and 2 were diploid. All of 20 cases diagnosed as spontaneous abortions (hydropic and non-hydropic yielded diploid histograms. Conclusion: These findings signify the importance of the combined use of conventional histology and ploidy analysis in the differential diagnosis of complete hydatidiform mole, partial hydatidiform mole and hydropic abortion.

  8. Factors influencing crime rates: an econometric analysis approach

    Science.gov (United States)

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

    2016-05-01

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

  9. Levey-Jennings Analysis Uncovers Unsuspected Causes of Immunohistochemistry Stain Variability.

    Science.gov (United States)

    Vani, Kodela; Sompuram, Seshi R; Naber, Stephen P; Goldsmith, Jeffrey D; Fulton, Regan; Bogen, Steven A

    Almost all clinical laboratory tests use objective, quantitative measures of quality control (QC), incorporating Levey-Jennings analysis and Westgard rules. Clinical immunohistochemistry (IHC) testing, in contrast, relies on subjective, qualitative QC review. The consequences of using Levey-Jennings analysis for QC assessment in clinical IHC testing are not known. To investigate this question, we conducted a 1- to 2-month pilot test wherein the QC for either human epidermal growth factor receptor 2 (HER-2) or progesterone receptor (PR) in 3 clinical IHC laboratories was quantified and analyzed with Levey-Jennings graphs. Moreover, conventional tissue controls were supplemented with a new QC comprised of HER-2 or PR peptide antigens coupled onto 8 μm glass beads. At institution 1, this more stringent analysis identified a decrease in the HER-2 tissue control that had escaped notice by subjective evaluation. The decrement was due to heterogeneity in the tissue control itself. At institution 2, we identified a 1-day sudden drop in the PR tissue control, also undetected by subjective evaluation, due to counterstain variability. At institution 3, a QC shift was identified, but only with 1 of 2 controls mounted on each slide. The QC shift was due to use of the instrument's selective reagent drop zones dispense feature. None of these events affected patient diagnoses. These case examples illustrate that subjective QC evaluation of tissue controls can detect gross assay failure but not subtle changes. The fact that QC issues arose from each site, and in only a pilot study, suggests that immunohistochemical stain variability may be an underappreciated problem.

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

    Directory of Open Access Journals (Sweden)

    María Jesús Mures Quintana

    2012-12-01

    Full Text Available El objetivo de este trabajo se centra en el análisis del fracaso empresarial por sectores, a fin de identificar los factores explicativos y predictivos de este fenómeno que son diferentes en tres de los principales sectores que se distinguen en toda economía: industria, construcción y servicios. Para cada uno de estos sectores, seguimos el mismo procedimiento. En primer lugar, aplicamos un análisis de componentes principales con el que identificamos los factores explicativos del fracaso empresarial en los tres sectores. A continuación, consideramos dichos factores como variables independientes en un análisis discriminante, que aplicamos para predecir el fracaso de una muestra de empresas, utilizando no sólo información financiera en forma de ratios, sino también otras variables no financieras relativas a las empresas, así como información externa a las mismas que refleja las condiciones macroeconómicas bajo las que desarrollan su actividad. This paper focuses on a cross-industry analysis of business failure, in order to identify the explanatory and predictor factors of this event that are different in three of the main industries in every economy: manufacturing, building and service. For each one of these industries, the same procedure is followed. First, a principal components analysis is applied in order to identify the explanatory factors of business failure in the three industries. Next, these factors are considered as independent variables in a discriminant analysis, so as to predict the firms’ failure, using not only financial information expressed by ratios, but also other non-financial variables related to the firms, as well as external information that reflects macroeconomic conditions under which they develop their activity.

  11. Improved Variable Selection Algorithm Using a LASSO-Type Penalty, with an Application to Assessing Hepatitis B Infection Relevant Factors in Community Residents

    Science.gov (United States)

    Guo, Pi; Zeng, Fangfang; Hu, Xiaomin; Zhang, Dingmei; Zhu, Shuming; Deng, Yu; Hao, Yuantao

    2015-01-01

    Objectives In epidemiological studies, it is important to identify independent associations between collective exposures and a health outcome. The current stepwise selection technique ignores stochastic errors and suffers from a lack of stability. The alternative LASSO-penalized regression model can be applied to detect significant predictors from a pool of candidate variables. However, this technique is prone to false positives and tends to create excessive biases. It remains challenging to develop robust variable selection methods and enhance predictability. Material and methods Two improved algorithms denoted the two-stage hybrid and bootstrap ranking procedures, both using a LASSO-type penalty, were developed for epidemiological association analysis. The performance of the proposed procedures and other methods including conventional LASSO, Bolasso, stepwise and stability selection models were evaluated using intensive simulation. In addition, methods were compared by using an empirical analysis based on large-scale survey data of hepatitis B infection-relevant factors among Guangdong residents. Results The proposed procedures produced comparable or less biased selection results when compared to conventional variable selection models. In total, the two newly proposed procedures were stable with respect to various scenarios of simulation, demonstrating a higher power and a lower false positive rate during variable selection than the compared methods. In empirical analysis, the proposed procedures yielding a sparse set of hepatitis B infection-relevant factors gave the best predictive performance and showed that the procedures were able to select a more stringent set of factors. The individual history of hepatitis B vaccination, family and individual history of hepatitis B infection were associated with hepatitis B infection in the studied residents according to the proposed procedures. Conclusions The newly proposed procedures improve the identification of

  12. Didymosphenia geminata in the Upper Esopus Creek: Current Status, Variability, and Controlling Factors.

    Science.gov (United States)

    George, Scott Daniel; Baldigo, Barry Paul

    2015-01-01

    In May of 2009, the bloom-forming diatom Didymosphenia geminata was first identified in the Upper Esopus Creek, a key tributary to the New York City water-supply and a popular recreational stream. The Upper Esopus receives supplemental flows from the Shandaken Portal, an underground aqueduct delivering waters from a nearby basin. The presence of D. geminata is a concern for the local economy, water supply, and aquatic ecosystem because nuisance blooms have been linked to degraded stream condition in other regions. Here we ascertain the extent and severity of the D. geminata invasion, determine the impact of supplemental flows from the Portal on D. geminata, and identify potential factors that may limit D. geminata in the watershed. Stream temperature, discharge, and water quality were characterized at select sites and periphyton samples were collected five times at 6 to 20 study sites between 2009 and 2010 to assess standing crop, diatom community structure, and density of D. geminata and all diatoms. Density of D. geminata ranged from 0-12 cells cm(-2) at tributary sites, 0-781 cells cm(-2) at sites upstream of the Portal, and 0-2,574 cells cm(-2) at sites downstream of the Portal. Survey period and Portal (upstream or downstream) each significantly affected D. geminata cell density. In general, D. geminata was most abundant during the November 2009 and June 2010 surveys and at sites immediately downstream of the Portal. We found that D. geminata did not reach nuisance levels or strongly affect the periphyton community. Similarly, companion studies showed that local macroinvertebrate and fish communities were generally unaffected. A number of abiotic factors including variable flows and moderate levels of phosphorous and suspended sediment may limit blooms of D. geminata in this watershed.

  13. Didymosphenia geminata in the Upper Esopus Creek: Current Status, Variability, and Controlling Factors.

    Directory of Open Access Journals (Sweden)

    Scott Daniel George

    Full Text Available In May of 2009, the bloom-forming diatom Didymosphenia geminata was first identified in the Upper Esopus Creek, a key tributary to the New York City water-supply and a popular recreational stream. The Upper Esopus receives supplemental flows from the Shandaken Portal, an underground aqueduct delivering waters from a nearby basin. The presence of D. geminata is a concern for the local economy, water supply, and aquatic ecosystem because nuisance blooms have been linked to degraded stream condition in other regions. Here we ascertain the extent and severity of the D. geminata invasion, determine the impact of supplemental flows from the Portal on D. geminata, and identify potential factors that may limit D. geminata in the watershed. Stream temperature, discharge, and water quality were characterized at select sites and periphyton samples were collected five times at 6 to 20 study sites between 2009 and 2010 to assess standing crop, diatom community structure, and density of D. geminata and all diatoms. Density of D. geminata ranged from 0-12 cells cm(-2 at tributary sites, 0-781 cells cm(-2 at sites upstream of the Portal, and 0-2,574 cells cm(-2 at sites downstream of the Portal. Survey period and Portal (upstream or downstream each significantly affected D. geminata cell density. In general, D. geminata was most abundant during the November 2009 and June 2010 surveys and at sites immediately downstream of the Portal. We found that D. geminata did not reach nuisance levels or strongly affect the periphyton community. Similarly, companion studies showed that local macroinvertebrate and fish communities were generally unaffected. A number of abiotic factors including variable flows and moderate levels of phosphorous and suspended sediment may limit blooms of D. geminata in this watershed.

  14. Periodic radio variability in NRAO 530: phase dispersion minimization analysis

    International Nuclear Information System (INIS)

    Lu Junchao; Lin Jiming; Qiu Hongbing; Wang Junyi; An Tao

    2012-01-01

    A periodicity analysis of the radio light curves of the blazar NRAO 530 at 14.5, 8.0, and 4.8 GHz is presented employing an improved phase dispersion minimization technique. The result, which shows two persistent periodic components of ∼ 6 and ∼ 10 yr at all three frequencies, is consistent with the results obtained with the Lomb-Scargle periodogram and weighted wavelet Z-transform algorithms. The reliability of the derived periodicities is confirmed by the Monte Carlo numerical simulations which show a high statistical confidence. (Quasi-)Periodic fluctuations of the radio luminosity of NRAO 530 might be associated with the oscillations of the accretion disk triggered by hydrodynamic instabilities of the accreted flow. (research papers)

  15. Bias and Bias Correction in Multisite Instrumental Variables Analysis of Heterogeneous Mediator Effects

    Science.gov (United States)

    Reardon, Sean F.; Unlu, Fatih; Zhu, Pei; Bloom, Howard S.

    2014-01-01

    We explore the use of instrumental variables (IV) analysis with a multisite randomized trial to estimate the effect of a mediating variable on an outcome in cases where it can be assumed that the observed mediator is the only mechanism linking treatment assignment to outcomes, an assumption known in the IV literature as the exclusion restriction.…

  16. Variables predicting elevated portal pressure in alcoholic liver disease. Results of a multivariate analysis

    DEFF Research Database (Denmark)

    Krogsgaard, K; Christensen, E; Gluud, C

    1987-01-01

    In 46 alcoholic patients the association of wedged-to-free hepatic-vein pressure with other variables (clinical, histologic, hemodynamic, and liver function data) was studied by means of multiple regression analysis, taking the wedged-to-free hepatic-vein pressure as the dependent variable. Four ...

  17. Methods for the Quasi-Periodic Variability Analysis in Blazars Y. Liu ...

    Indian Academy of Sciences (India)

    the variability analysis in blazars in optical and radio bands, to search for possible quasi-periodic signals. 2. Power spectral density (PSD). In statistical signal processing and physics, the power spectral density (PSD) is a positive real function of a frequency variable associated with a stationary stochas- tic process. Intuitively ...

  18. Analysis, Test and Verification in The Presence of Variability (Dagstuhl Seminar 13091)

    DEFF Research Database (Denmark)

    2014-01-01

    -aware tool chains. We brought together 46 key researchers from three continents, working on quality assurance challenges that arise from introducing variability, and some who do not work with variability, but that are experts in their respective areas in the broader domain of software analysis or testing...

  19. Dispositional Variables and Work-Family Conflict: A Meta-Analysis

    Science.gov (United States)

    Allen, Tammy D.; Johnson, Ryan C.; Saboe, Kristin N.; Cho, Eunae; Dumani, Soner; Evans, Sarah

    2012-01-01

    Meta-analysis was used to comprehensively summarize the relationship between dispositional variables and both directions of work-family conflict. The largest effects detected were those associated with negative affect, neuroticism, and self-efficacy; all were in expected directions. In general, negative trait-based variables (e.g., negative affect…

  20. [Variability in smoking experimentation and risk factors in 4 secondary schools in Murcia (Spain)].

    Science.gov (United States)

    García, Pedro; Carrillo, Andrés; Sánchez, Joseph; Hurtado, Ascensión; Sánchez, Irene; Martínez, Rafaela; Cuevas, María Dolores

    2007-01-01

    To identify patterns of tobacco experimentation and consumption in 4 geographically close groups of students in the first year of secondary education, as well as attitudes and consumption in their social environments. To identify the factors associated with tobacco experimentation and consumption in each of the student groups. An observational, descriptive, cross-sectional, multicenter study was conducted in 4 secondary schools in the region of Murcia (Spain). The study population consisted of first graders in secondary education, recruited in January 2005. The study variables were collected using a modified version of the FRISC questionnaire. The study population was composed of 377 students (190 boys) with a mean age of 12.6 years (standard deviation [SD] = 0.6). Between 15.3% and 42.1% of the students had smoked at some time. Between 2% and 6.9% smoked regularly. These differences were related to socioeconomic characteristics ("living with the mother", p = 0.049; "living with the father", p = 0.015) and consumption in the environment ("mother", p = 0.013; "friends", p pocket money, consumption among friends, experimenting with alcohol and not living in one of the towns studied. Significant differences were found among the towns studied. Application of standard preventive programs may prove ineffective unless they are adapted to the characteristics of the specific school.

  1. Regional precipitation variability in East Asia related to climate and environmental factors during 1979-2012

    Science.gov (United States)

    Deng, Yinyin; Gao, Tao; Gao, Huiwang; Yao, Xiaohong; Xie, Lian

    2014-01-01

    This paper studies the inter-annual precipitation variations in different regions of East Asia from oceans to interior areas in China during 1979 – 2012. The results computed by Empirical Orthogonal Functions (EOF) demonstrate that the annual precipitation changes are mainly related to the El Niño-Southern Oscillation, East Asian summer monsoon and aerosols. We also found that the increased Sea surface temperature (SST) could explain the precipitation changes over the Northwest Pacific in the dry season (Oct. – May) and the East China Sea and the South China Sea in the rainy season (Jun. – Sep.). The precipitation changes over the ocean unexplained by SST were likely due to the water vapor transport dominated by dynamic factors. With the increased SST, the moisture transported from oceans to interior land was likely redistributed and caused the complicated regional variability of precipitation. Moreover, the impacts of aerosols on cloud and precipitation varied with different pollution levels and different seasons. PMID:25033387

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

    Directory of Open Access Journals (Sweden)

    Nurhayati Ai

    2018-01-01

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

  3. Variability of indoor and outdoor VOC measurements: An analysis using variance components

    International Nuclear Information System (INIS)

    Jia, Chunrong; Batterman, Stuart A.; Relyea, George E.

    2012-01-01

    This study examines concentrations of volatile organic compounds (VOCs) measured inside and outside of 162 residences in southeast Michigan, U.S.A. Nested analyses apportioned four sources of variation: city, residence, season, and measurement uncertainty. Indoor measurements were dominated by seasonal and residence effects, accounting for 50 and 31%, respectively, of the total variance. Contributions from measurement uncertainty (<20%) and city effects (<10%) were small. For outdoor measurements, season, city and measurement variation accounted for 43, 29 and 27% of variance, respectively, while residence location had negligible impact (<2%). These results show that, to obtain representative estimates of indoor concentrations, measurements in multiple seasons are required. In contrast, outdoor VOC concentrations can use multi-seasonal measurements at centralized locations. Error models showed that uncertainties at low concentrations might obscure effects of other factors. Variance component analyses can be used to interpret existing measurements, design effective exposure studies, and determine whether the instrumentation and protocols are satisfactory. - Highlights: ► The variability of VOC measurements was partitioned using nested analysis. ► Indoor VOCs were primarily controlled by seasonal and residence effects. ► Outdoor VOC levels were homogeneous within neighborhoods. ► Measurement uncertainty was high for many outdoor VOCs. ► Variance component analysis is useful for designing effective sampling programs. - Indoor VOC concentrations were primarily controlled by seasonal and residence effects; and outdoor concentrations were homogeneous within neighborhoods. Variance component analysis is a useful tool for designing effective sampling programs.

  4. Topex-Poseidon analysis of sea level variability over the Atlantic Ocean

    Science.gov (United States)

    Catalan P-U, M.; Villares, P.; Catalan, M.; Gomez-Enri, J.

    2003-04-01

    The variability of sea level and surface geostrophic currents in Atlantic Ocean is investigated using 333 cycles of altimeter information obtained by TOPEX-POSEIDON satellite. After the improvements of orbit accuracy, the most important concern to studies of sea level variability from altimeter height data are related with the formalism used for modelling the altimetric measurement corrections. Presently, one of the main sources of potential error is the correction for atmospheric pressure loading, the so-called ‘inverse barometer effect’. As is well known, this correction is intended to adjust the sea surface elevation for the static effects of the downward force of the mass of the atmosphere on the sea surface, adjusted, in this oversimplified model in 1cm/mbar. The exact response of the sea surface to atmospheric pressure loading depends on the space and time scales of the pressure field and must be specially a concern at high latitudes where atmospheric pressure fluctuations are large due to the intensity of low pressure fields at these latitudes and the additional uncertainty in the model estimates of the local sea level pressure. To study these effects over the whole Atlantic Ocean we compute a linear regression adjustment and an Empirical Orthogonal Functions Decomposition (EOFD), between sea level variation without inverse barometer correction and the atmospheric pressure, in all the Topex-Poseidon cross points over the whole Atlantic, including both the Artic and Antarctic Oceans. We use the barometric factor computed from the linear regression to correct the satellite mean sea level variation, comparing the correlation with the pressure. Our results show an important improvement in the decorrelation between sea level and atmospheric pressure time series, compared with the use of Inverse Barometer model, at most of the satellite cross points. The complicated nature of sea level variability at high latitudes justify that EOFD analysis conclusions

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

    Science.gov (United States)

    Wagner, Claas; Esbensen, Kim H

    2015-01-01

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

  6. 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

  7. Fourier analysis of the light curves of eclipsing variables, XXIV

    International Nuclear Information System (INIS)

    Edalati, M.T.

    1978-01-01

    The aim of the present paper will be to evaluate numerically Jacobian and other functions which have been discussed in more detail in a previous paper of this series, and also choose the most convenient moments to obtain a good determination for the unknown eclipse parameters a and c 0 . More than 12 different pairs of g-functions for real values of m have been investigated numerically and diagrammatically. The behaviour of g-functions depends but very little on different combination of the moments, and related diagrams are approximately the same as g 2 and g 4 . The behaviour of the vanishing Jacobian, arising from different pairs of g-functions for real values of m>= 0 . Accordingly, the author obtains the optimum combination of the moments (i.e., A 6 , A 7 , A 8 and A 9 ) in g-functions g 7 and g 8 . It has been noted that the behaviour of the g-functions which depend on the combinations of the higher order moments (i.e., m>= 5) have been ruled out, because the proportional error of the moments Asub(2m) increases with increasing values of real m. The automated method has been tested successfully on the light curve of RT Per. Finally, a comparison is given of the elements of RT Per arising from two different pairs of g-functions, i.e. g 2 , g 4 and g 7 , g 8 for the light curves analysis. (Auth.)

  8. Variability of photosynthetic parameters of Pinus sibirica Du Tour needles under changing climatic factors

    Directory of Open Access Journals (Sweden)

    A.P. Zotikova

    2013-12-01

    Full Text Available The air temperature and relative humidity and the intensity of photosynthetically active radiation are the basic ecological factors determining geographical distribution of a species. Wood plant adaptation depends on the intensity of physiological and biochemicalprocesses of plants as a response to changing environmental factors. Investigations to reveal (detect the variability of modification andgenetic components of the photosynthetic parameters in needles of the Siberian cedar (Pinus sibirica Du Tour mountain ecotypes, distributed in central part of the Altai Mountains, were carried out. Also, the survey was extended to some experiments with these ecotypes introduced to mild climate and flat regions from south-western of Siberia. The length and thickness of needles, the size of chloroplasts, content of the photosynthetic pigments, and the functional activity of chloroplastsat the level of photo system II were the evaluated traits. Growing under mountainous conditions (at about 2000m elevation, the two-year-old needles were shorter and thicker and contained very large in size chloroplasts while the content of chlorophylls and carotinoids was twice lower than that in the local ecotype growing in the lowlands. On the other hand, more green and yellow pigments were found in needles of mountain ecotypes planted in the lowlands compared to the local lowland ectype trees. A decrease in pool of the photosynthetic pigments in the highlands ecotypes is probably due to decreased biosynthesis andincreased photo-destruction caused by severe light and temperature conditions. These parameters are likely to be associated withmodifications due to intense insolation, low temperature, ozone concentration, UV radiation, and other negative factors that are morepronounced at high elevation. Despite the large pool of accumulated photosynthetic pigments, the functional activity of chloroplasts in themountain ecotype at the level

  9. 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.

  10. Integrating factors and conservation theorems for Hamilton's canonical equations of motion of variable mass nonholonomic nonconservative dynamical systems

    Institute of Scientific and Technical Information of China (English)

    李仁杰; 乔永芬; 刘洋

    2002-01-01

    We present a general approach to the construction of conservation laws for variable mass nonholonomic noncon-servative systems. First, we give the definition of integrating factors, and we study in detail the necessary conditionsfor the existence of the conserved quantities. Then, we establish the conservation theorem and its inverse theorem forHamilton's canonical equations of motion of variable mass nonholonomic nonconservative dynamical systems. Finally,we give an example to illustrate the application of the results.

  11. Integrating factors and conservation theorems for Hamilton‘s canonical equations of motion of variable mass nonholonmic nonconservative dynamical systems

    Institute of Scientific and Technical Information of China (English)

    李仁杰; 刘洋; 等

    2002-01-01

    We present a general approach to the construction of conservation laws for variable mass noholonmic nonconservative systems.First,we give the definition of integrating factors,and we study in detail the necessary conditions for the existence of the conserved quantities,Then,we establish the conservatioin theorem and its inverse theorem for Hamilton's canonical equations of motion of variable mass nonholonomic nonocnservative dynamical systems.Finally,we give an example to illustrate the application of the results.

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

    Science.gov (United States)

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

    2017-06-01

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

  13. Farmers' Perceptions of Climate Variability and Factors Influencing Adaptation: Evidence from Anhui and Jiangsu, China.

    Science.gov (United States)

    Kibue, Grace Wanjiru; Liu, Xiaoyu; Zheng, Jufeng; Zhang, Xuhui; Pan, Genxing; Li, Lianqing; Han, Xiaojun

    2016-05-01

    Impacts of climate variability and climate change are on the rise in China posing great threat to agriculture and rural livelihoods. Consequently, China is undertaking research to find solutions of confronting climate change and variability. However, most studies of climate change and variability in China largely fail to address farmers' perceptions of climate variability and adaptation. Yet, without an understanding of farmers' perceptions, strategies are unlikely to be effective. We conducted questionnaire surveys of farmers in two farming regions, Yifeng, Jiangsu and Qinxi, Anhui achieving 280 and 293 responses, respectively. Additionally, we used climatological data to corroborate the farmers' perceptions of climate variability. We found that farmers' were aware of climate variability such that were consistent with climate records. However, perceived impacts of climate variability differed between the two regions and were influenced by farmers' characteristics. In addition, the vast majorities of farmers were yet to make adjustments in their farming practices as a result of numerous challenges. These challenges included socioeconomic and socio-cultural barriers. Results of logit modeling showed that farmers are more likely to adapt to climate variability if contact with extension services, frequency of seeking information, household heads' education, and climate variability perceptions are improved. These results suggest the need for policy makers to understand farmers' perceptions of climate variability and change in order to formulate policies that foster adaptation, and ultimately protect China's agricultural assets.

  14. Hydrological and environmental variables outperform spatial factors in structuring species, trait composition, and beta diversity of pelagic algae.

    Science.gov (United States)

    Wu, Naicheng; Qu, Yueming; Guse, Björn; Makarevičiūtė, Kristė; To, Szewing; Riis, Tenna; Fohrer, Nicola

    2018-03-01

    There has been increasing interest in algae-based bioassessment, particularly, trait-based approaches are increasingly suggested. However, the main drivers, especially the contribution of hydrological variables, of species composition, trait composition, and beta diversity of algae communities are less studied. To link species and trait composition to multiple factors (i.e., hydrological variables, local environmental variables, and spatial factors) that potentially control species occurrence/abundance and to determine their relative roles in shaping species composition, trait composition, and beta diversities of pelagic algae communities, samples were collected from a German lowland catchment, where a well-proven ecohydrological modeling enabled to predict long-term discharges at each sampling site. Both trait and species composition showed significant correlations with hydrological, environmental, and spatial variables, and variation partitioning revealed that the hydrological and local environmental variables outperformed spatial variables. A higher variation of trait composition (57.0%) than species composition (37.5%) could be explained by abiotic factors. Mantel tests showed that both species and trait-based beta diversities were mostly related to hydrological and environmental heterogeneity with hydrological contributing more than environmental variables, while purely spatial impact was less important. Our findings revealed the relative importance of hydrological variables in shaping pelagic algae community and their spatial patterns of beta diversities, emphasizing the need to include hydrological variables in long-term biomonitoring campaigns and biodiversity conservation or restoration. A key implication for biodiversity conservation was that maintaining the instream flow regime and keeping various habitats among rivers are of vital importance. However, further investigations at multispatial and temporal scales are greatly needed.

  15. Radon in indoor air of primary schools: determinant factors, their variability and effective dose.

    Science.gov (United States)

    Madureira, Joana; Paciência, Inês; Rufo, João; Moreira, André; de Oliveira Fernandes, Eduardo; Pereira, Alcides

    2016-04-01

    Radon is a radioactive gas, abundant in granitic areas, such as in the city of Porto at the north-east of Portugal. This gas is a recognized carcinogenic agent, being appointed by the World Health Organization as the leading cause of lung cancer after smoking. The aim of this preliminary survey was to determine indoor radon concentrations in public primary schools, to analyse the main factors influencing their indoor concentration levels and to estimate the effective dose in students and teachers in primary schools. Radon concentrations were measured in 45 classrooms from 13 public primary schools located in Porto, using CR-39 passive radon detectors for about 2-month period. In all schools, radon concentrations ranged from 56 to 889 Bq/m(3) (mean = 197 Bq/m(3)). The results showed that the limit of 100 Bq/m(3) established by WHO IAQ guidelines was exceeded in 92 % of the measurements, as well as 8 % of the measurements exceeded the limit of 400 Bq/m(3) established by the national legislation. Moreover, the mean annual effective dose was calculated as 1.25 mSv/y (ranging between 0.58 and 3.07 mSv/y), which is below the action level (3-10 mSv). The considerable variability of radon concentration observed between and within floors indicates a need to monitor concentrations in several rooms for each floor. A single radon detector for each room can be used, provided that the measurement error is considerably lower than variability of radon concentration between rooms. The results of the present survey will provide useful baseline data for adopting safety measures and dealing effectively with radiation emergencies. In particular, radon remediation techniques should be used in buildings located in the highest radon risk areas of Portugal. The results obtained in the current study concerning radon levels and their variations will be useful to optimize the design of future research surveys.

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

    Directory of Open Access Journals (Sweden)

    Ana Maria T. Benevides-Pereira

    2017-05-01

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

  17. PISA 2012 Analysis of School Variables Affecting Problem-Solving Competency: Turkey-Serbia Comparison

    Directory of Open Access Journals (Sweden)

    Emine YAVUZ

    2017-12-01

    Full Text Available According to the OECD's PISA 2012 Turkey problem-solving report, Turkey and Serbia are at the same mathematical literacy level. However, Serbia's average of problem-solving competency is said to be higher than Turkey's. In this study, school variables that affect problem-solving competency of the two countries were examined and compared. The method of the study was causal comparison method, and HLM analysis was performed on data of 4494 students from 147 schools in Turkey sample and 4059 students from 132 schools in Serbia sample separately. As a result of HLM analysis, "obstacle and family donation" variable for Serbia and "abandon, teacher morale and mathematics competition" variable for Turkey were statistically significant. Although it was found that for each countries different variables influence the problem-solving competency, it was quite remarkable that these variables are in common in that they are components of the school climate concept.

  18. Evaluating measurement models in clinical research: covariance structure analysis of latent variable models of self-conception.

    Science.gov (United States)

    Hoyle, R H

    1991-02-01

    Indirect measures of psychological constructs are vital to clinical research. On occasion, however, the meaning of indirect measures of psychological constructs is obfuscated by statistical procedures that do not account for the complex relations between items and latent variables and among latent variables. Covariance structure analysis (CSA) is a statistical procedure for testing hypotheses about the relations among items that indirectly measure a psychological construct and relations among psychological constructs. This article introduces clinical researchers to the strengths and limitations of CSA as a statistical procedure for conceiving and testing structural hypotheses that are not tested adequately with other statistical procedures. The article is organized around two empirical examples that illustrate the use of CSA for evaluating measurement models with correlated error terms, higher-order factors, and measured and latent variables.

  19. 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.

  20. Modeling Psychological Attributes in Psychology – An Epistemological Discussion: Network Analysis vs. Latent Variables

    Science.gov (United States)

    Guyon, Hervé; Falissard, Bruno; Kop, Jean-Luc

    2017-01-01

    Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes. PMID:28572780

  1. Analysis on the public acceptance of nuclear energy using structural equation model with latent variables

    International Nuclear Information System (INIS)

    Lee, Young Eal

    1996-02-01

    Comparison of the effect of education and public information on the public acceptance of nuclear energy is carried out. For the increase of public acceptance, the correct understanding on the nuclear energy via proper regular school education would be the first basis and the appropriate public information services by utility and unbiased mass media would be the second basis. Subjects that which is more effect in education or information and how much effective quantitatively to improve the public acceptance are derived. Structural Equation Model (SEM) with Latent Variables (LVs) in social science to public attitudes towards nuclear energy is developed. Questionnaire is conducted to respondents who took part in the program of visiting the nuclear power plant opened by OKAEA in 1995. As a result of the analysis, effect of education for correct awareness of nuclear energy is more sensitive to public acceptance than that of information. It is shown that the susceptibility in education factor in influence of radiation on human body and that in information factor persons consider nuclear power plant as an environmental polluter. It is concluded that radiation treatment should be a 'Hand on Experience' and general principle of nuclear power generation should be contained in the educational text book. Education and information should not been independently performed but been carried out simultaneously and mutually aided. It is shown that this modeling approach is useful to make the decision for the long-term nuclear energy policy transparent and successful

  2. Housing price forecastability: A factor analysis

    DEFF Research Database (Denmark)

    Bork, Lasse; Møller, Stig Vinther

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

  3. Erikson Psychosocial Stage Inventory: A Factor Analysis

    Science.gov (United States)

    Gray, Mary McPhail; And Others

    1986-01-01

    The 72-item Erikson Psychosocial Stage Inventory (EPSI) was factor analyzed for a group of 534 university freshmen and sophomore students. Seven factors emerged, which were labeled Initiative, Industry, Identity, Friendship, Dating, Goal Clarity, and Self-Confidence. Item's representing Erikson's factors, Trust and Autonomy, were dispersed across…

  4. Meta-analysis of the predictive factors of postpartum fatigue.

    Science.gov (United States)

    Badr, Hanan A; Zauszniewski, Jaclene A

    2017-08-01

    Nearly 64% of new mothers are affected by fatigue during the postpartum period, making it the most common problem that a woman faces as she adapts to motherhood. Postpartum fatigue can lead to serious negative effects on the mother's health and the newborn's development and interfere with mother-infant interaction. The aim of this meta-analysis was to identify predictive factors of postpartum fatigue and to document the magnitude of their effects using effect sizes. We used two search engines, PubMed and Google Scholar, to identify studies that met three inclusion criteria: (a) the article was written in English, (b) the article studied the predictive factors of postpartum fatigue, and (c) the article included information about the validity and reliability of the instruments used in the research. Nine articles met these inclusion criteria. The direction and strength of correlation coefficients between predictive factors and postpartum fatigue were examined across the studies to determine their effect sizes. Measurement of predictor variables occurred from 3days to 6months postpartum. Correlations reported between predictive factors and postpartum fatigue were as follows: small effect size (r range =0.10 to 0.29) for education level, age, postpartum hemorrhage, infection, and child care difficulties; medium effect size (r range =0.30 to 0.49) for physiological illness, low ferritin level, low hemoglobin level, sleeping problems, stress and anxiety, and breastfeeding problems; and large effect size (r range =0.50+) for depression. Postpartum fatigue is a common condition that can lead to serious health problems for a new mother and her newborn. Therefore, increased knowledge concerning factors that influence the onset of postpartum fatigue is needed for early identification of new mothers who may be at risk. Appropriate treatments, interventions, information, and support can then be initiated to prevent or minimize the postpartum fatigue. Copyright © 2017 Elsevier

  5. Multi-scale approach to the environmental factors effects on spatio-temporal variability of Chironomus salinarius (Diptera: Chironomidae) in a French coastal lagoon

    Science.gov (United States)

    Cartier, V.; Claret, C.; Garnier, R.; Fayolle, S.; Franquet, E.

    2010-03-01

    The complexity of the relationships between environmental factors and organisms can be revealed by sampling designs which consider the contribution to variability of different temporal and spatial scales, compared to total variability. From a management perspective, a multi-scale approach can lead to time-saving. Identifying environmental patterns that help maintain patchy distribution is fundamental in studying coastal lagoons, transition zones between continental and marine waters characterised by great environmental variability on spatial and temporal scales. They often present organic enrichment inducing decreased species richness and increased densities of opportunist species like C hironomus salinarius, a common species that tends to swarm and thus constitutes a nuisance for human populations. This species is dominant in the Bolmon lagoon, a French Mediterranean coastal lagoon under eutrophication. Our objective was to quantify variability due to both spatial and temporal scales and identify the contribution of different environmental factors to this variability. The population of C. salinarius was sampled from June 2007 to June 2008 every two months at 12 sites located in two areas of the Bolmon lagoon, at two different depths, with three sites per area-depth combination. Environmental factors (temperature, dissolved oxygen both in sediment and under water surface, sediment organic matter content and grain size) and microbial activities (i.e. hydrolase activities) were also considered as explanatory factors of chironomid densities and distribution. ANOVA analysis reveals significant spatial differences regarding the distribution of chironomid larvae for the area and the depth scales and their interaction. The spatial effect is also revealed for dissolved oxygen (water), salinity and fine particles (area scale), and for water column depth. All factors but water column depth show a temporal effect. Spearman's correlations highlight the seasonal effect

  6. Alaskan soil carbon stocks: spatial variability and dependence on environmental factors

    Directory of Open Access Journals (Sweden)

    U. Mishra

    2012-09-01

    Full Text Available The direction and magnitude of soil organic carbon (SOC changes in response to climate change depend on the spatial and vertical distributions of SOC. We estimated spatially resolved SOC stocks from surface to C horizon, distinguishing active-layer and permafrost-layer stocks, based on geospatial analysis of 472 soil profiles and spatially referenced environmental variables for Alaska. Total Alaska state-wide SOC stock was estimated to be 77 Pg, with 61% in the active-layer, 27% in permafrost, and 12% in non-permafrost soils. Prediction accuracy was highest for the active-layer as demonstrated by highest ratio of performance to deviation (1.5. Large spatial variability was predicted, with whole-profile, active-layer, and permafrost-layer stocks ranging from 1–296 kg C m−2, 2–166 kg m−2, and 0–232 kg m−2, respectively. Temperature and soil wetness were found to be primary controllers of whole-profile, active-layer, and permafrost-layer SOC stocks. Secondary controllers, in order of importance, were found to be land cover type, topographic attributes, and bedrock geology. The observed importance of soil wetness rather than precipitation on SOC stocks implies that the poor representation of high-latitude soil wetness in Earth system models may lead to large uncertainty in predicted SOC stocks under future climate change scenarios. Under strict caveats described in the text and assuming temperature changes from the A1B Intergovernmental Panel on Climate Change emissions scenario, our geospatial model indicates that the equilibrium average 2100 Alaska active-layer depth could deepen by 11 cm, resulting in a thawing of 13 Pg C currently in permafrost. The equilibrium SOC loss associated with this warming would be highest under continuous permafrost (31%, followed by discontinuous (28%, isolated (24.3%, and sporadic (23.6% permafrost areas. Our high-resolution mapping of soil carbon stock reveals the

  7. Material variability and repetitive member factors for the allowable properties of engineered wood products

    Science.gov (United States)

    Steve Verrill; David E. Kretschmann

    2009-01-01

    It has been argued that repetitive member allowable property adjustments should be larger for high-variability materials than for low-variability materials. We report analytic calculations and simulations that suggest that the order of such adjustments should be reversed, that is, given the manner in which allowable properties are currently calculated, as the...

  8. Variability of perfluoroalkyl substance concentrations in pregnant women by socio-demographic and dietary factors in a Spanish birth cohort.

    Science.gov (United States)

    Manzano-Salgado, Cyntia B; Casas, Maribel; Lopez-Espinosa, Maria-Jose; Ballester, Ferran; Martinez, David; Ibarluzea, Jesus; Santa-Marina, Loreto; Schettgen, Thomas; Vioque, Jesus; Sunyer, Jordi; Vrijheid, Martine

    2016-01-01

    Prenatal exposure to perfluoroalkyl substances (PFAS) might affect child health; but maternal determinants of PFAS exposure are unclear. We evaluated the socio-demographic and dietary factors of prenatal PFAS concentrations in a Spanish birth cohort. We analyzed perfluorohexanesulfonic acid (PFHxS), perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and perfluorononanoic acid (PFNA) in 1216 plasma samples collected during the 1(ST) trimester of pregnancy (2003-2008). We used multivariable linear regressions to assess the geometric mean (GM) ratios of PFAS concentrations by socio-demographic and dietary factors. We used analysis of variance (ANOVA) to assess the variability of PFAS concentrations by maternal factors. GM PFAS concentrations ranged from 0.55ng/mL for PFHxS to 5.77ng/mL for PFOS. Women born outside of Spain had lower PFAS concentrations (e.g. GM ratio for PFHxS 0.53[95%CI: 0.46, 0.60] than Spanish women. PFHxS and PFOA concentrations were higher in mothers from the regions of Sabadell (2.13[1.93, 2.35] and 1.73[1.60, 1.88], respectively) and Valencia (1.40[1.28, 1.54] and 1.42[1.31, 1.53], respectively) than Gipuzkoa. PFOA and PFNA concentrations decreased with parity (≥2 children: 0.79[0.67, 0.94] and 0.82[0.68, 0.99], respectively). Younger women (i.e. 6months compared to those who never breastfed (0.79[0.67, 0.94] and 0.82[0.71, 0.95], respectively). High intake of fish and shellfish during pregnancy (i.e. ≥5.6 servings/week) was associated with 11% (1.11[1.04, 1.18]) higher PFOS concentrations than the lowest intake group. Our ANOVA models explained 26% to 40% of PFAS concentrations variability. Prenatal PFAS concentrations were mainly determined by maternal country of birth, region of residence, previous breastfeeding and age. Fish and shellfish intake also contributed to PFOS and PFOA concentrations. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. No rationale for 1 variable per 10 events criterion for binary logistic regression analysis

    Directory of Open Access Journals (Sweden)

    Maarten van Smeden

    2016-11-01

    Full Text Available Abstract Background Ten events per variable (EPV is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. Methods The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth’s correction, are compared. Results The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect (‘separation’. We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth’s correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. Conclusions The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

  10. Multiscale Entropy Analysis of Heart Rate Variability for Assessing the Severity of Sleep Disordered Breathing

    Directory of Open Access Journals (Sweden)

    Wen-Yao Pan

    2015-01-01

    Full Text Available Obstructive sleep apnea (OSA is an independent cardiovascular risk factor to which autonomic nervous dysfunction has been reported to be an important contributor. Ninety subjects recruited from the sleep center of a single medical center were divided into four groups: normal snoring subjects without OSA (apnea hypopnea index, AHI < 5, n = 11, mild OSA (5 ≤ AHI < 15, n = 10, moderate OSA (15 ≤ AHI < 30, n = 24, and severe OSA (AHI ≥ 30, n = 45. Demographic (i.e., age, gender, anthropometric (i.e., body mass index, neck circumference, and polysomnographic (PSG data were recorded and compared among the different groups. For each subject, R-R intervals (RRI from 10 segments of 10-minute electrocardiogram recordings during non-rapid eye movement sleep at stage N2 were acquired and analyzed for heart rate variability (HRV and sample entropy using multiscale entropy index (MEI that was divided into small scale (MEISS, scale 1–5 and large scale (MEILS, scale 6–10. Our results not only demonstrated that MEISS could successfully distinguish normal snoring subjects and those with mild OSA from those with moderate and severe disease, but also revealed good correlation between MEISS and AHI with Spearman correlation analysis (r = −0.684, p < 0.001. Therefore, using the two parameters of EEG and ECG, MEISS may serve as a simple preliminary screening tool for assessing the severity of OSA before proceeding to PSG analysis.

  11. No rationale for 1 variable per 10 events criterion for binary logistic regression analysis.

    Science.gov (United States)

    van Smeden, Maarten; de Groot, Joris A H; Moons, Karel G M; Collins, Gary S; Altman, Douglas G; Eijkemans, Marinus J C; Reitsma, Johannes B

    2016-11-24

    Ten events per variable (EPV) is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth's correction, are compared. The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect ('separation'). We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth's correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

  12. Analysis of temporal and spatial trends of hydro-climatic variables in the Wei River Basin.

    Science.gov (United States)

    Zhao, Jing; Huang, Qiang; Chang, Jianxia; Liu, Dengfeng; Huang, Shengzhi; Shi, Xiaoyu

    2015-05-01

    The Wei River is the largest tributary of the Yellow River in China. The relationship between runoff and precipitation in the Wei River Basin has been changed due to the changing climate and increasingly intensified human activities. In this paper, we determine abrupt changes in hydro-climatic variables and identify the main driving factors for the changes in the Wei River Basin. The nature of the changes is analysed based on data collected at twenty-one weather stations and five hydrological stations in the period of 1960-2010. The sequential Mann-Kendall test analysis is used to capture temporal trends and abrupt changes in the five sub-catchments of the Wei River Basin. A non-parametric trend test at the basin scale for annual data shows a decreasing trend of precipitation and runoff over the past fifty-one years. The temperature exhibits an increase trend in the entire period. The potential evaporation was calculated based on the Penman-Monteith equation, presenting an increasing trend of evaporation since 1990. The stations with a significant decreasing trend in annual runoff mainly are located in the west of the Wei River primarily interfered by human activities. Regression analysis indicates that human activity was possibly the main cause of the decline of runoff after 1970. Copyright © 2015. Published by Elsevier Inc.

  13. Seasonal and Spatial Variability of Anthropogenic and Natural Factors Influencing Groundwater Quality Based on Source Apportionment

    Directory of Open Access Journals (Sweden)

    Xueru Guo

    2018-02-01

    Full Text Available Globally, groundwater resources are being deteriorated by rapid social development. Thus, there is an urgent need to assess the combined impacts of natural and enhanced anthropogenic sources on groundwater chemistry. The aim of this study was to identify seasonal characteristics and spatial variations in anthropogenic and natural effects, to improve the understanding of major hydrogeochemical processes based on source apportionment. 34 groundwater points located in a riverside groundwater resource area in northeast China were sampled during the wet and dry seasons in 2015. Using principal component analysis and factor analysis, 4 principal components (PCs were extracted from 16 groundwater parameters. Three of the PCs were water-rock interaction (PC1, geogenic Fe and Mn (PC2, and agricultural pollution (PC3. A remarkable difference (PC4 was organic pollution originating from negative anthropogenic effects during the wet season, and geogenic F enrichment during the dry season. Groundwater exploitation resulted in dramatic depression cone with higher hydraulic gradient around the water source area. It not only intensified dissolution of calcite, dolomite, gypsum, Fe, Mn and fluorine minerals, but also induced more surface water recharge for the water source area. The spatial distribution of the PCs also suggested the center of the study area was extremely vulnerable to contamination by Fe, Mn, COD, and F−.

  14. Nominal Performance Biosphere Dose Conversion Factor Analysis

    International Nuclear Information System (INIS)

    Wasiolek, M.

    2000-01-01

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

  15. Disruptive Event Biosphere Doser Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M. Wasiolek

    2000-12-28

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

  16. Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis.

    Science.gov (United States)

    Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

    2018-06-04

    A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c  = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

  17. analysis of the factors influencing farmers' adoption of alley farming ...

    African Journals Online (AJOL)

    p2333147

    The variables in equation (2) are defined and explained in Table 1. ..... varieties in Guinea – Bissau. ... productivity of agricultural systems in the West African Savanna. ... for soil fertility improvement in South and Central Benin: Analysis of.

  18. Lactose intolerance : analysis of underlying factors

    NARCIS (Netherlands)

    Vonk, RJ; Priebe, MG; Koetse, HA; Stellaard, F; Lenoir-Wijnkoop, [No Value; Antoine, JM; Zhong, Y; Huang, CY

    Background We studied the degree of lactose digestion and orocecal transit time (OCTT) as possible causes for the variability of symptoms of lactose intolerance (LI) in a sample of a population with genetically determined low lactase activity. Methods Lactose digestion index (LDI) was measured by

  19. Quantitative effects of composting state variables on C/N ratio through GA-aided multivariate analysis

    International Nuclear Information System (INIS)

    Sun Wei; Huang, Guo H.; Zeng Guangming; Qin Xiaosheng; Yu Hui

    2011-01-01

    It is widely known that variation of the C/N ratio is dependent on many state variables during composting processes. This study attempted to develop a genetic algorithm aided stepwise cluster analysis (GASCA) method to describe the nonlinear relationships between the selected state variables and the C/N ratio in food waste composting. The experimental data from six bench-scale composting reactors were used to demonstrate the applicability of GASCA. Within the GASCA framework, GA searched optimal sets of both specified state variables and SCA's internal parameters; SCA established statistical nonlinear relationships between state variables and the C/N ratio; to avoid unnecessary and time-consuming calculation, a proxy table was introduced to save around 70% computational efforts. The obtained GASCA cluster trees had smaller sizes and higher prediction accuracy than the conventional SCA trees. Based on the optimal GASCA tree, the effects of the GA-selected state variables on the C/N ratio were ranged in a descending order as: NH 4 + -N concentration > Moisture content > Ash Content > Mean Temperature > Mesophilic bacteria biomass. Such a rank implied that the variation of ammonium nitrogen concentration, the associated temperature and the moisture conditions, the total loss of both organic matters and available mineral constituents, and the mesophilic bacteria activity, were critical factors affecting the C/N ratio during the investigated food waste composting. This first application of GASCA to composting modelling indicated that more direct search algorithms could be coupled with SCA or other multivariate analysis methods to analyze complicated relationships during composting and many other environmental processes. - Research Highlights: → A genetic algorithm aided stepwise cluster analysis method in food waste composting. → Nonlinear relationships between the selected state variables and the C/N ratio. → Introduced proxy tables save around 70% computational

  20. Quantitative effects of composting state variables on C/N ratio through GA-aided multivariate analysis

    Energy Technology Data Exchange (ETDEWEB)

    Sun Wei [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan, S4S 0A2 (Canada); Huang, Guo H., E-mail: huangg@iseis.org [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan, S4S 0A2 (Canada); MOE Key Laboratory of Regional Energy Systems Optimization, Sino-Canada Energy and Environmental Research Academy, North China Electric Power University, Beijing, 102206 (China); Zeng Guangming [MOE Key Laboratory of Environmental Biology and Pollution Control, College of Environmental Science and Engineering, Hunan University, Changsha, Hunan, 410082 (China); Qin Xiaosheng [School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798 (Singapore); Yu Hui [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan, S4S 0A2 (Canada)

    2011-03-01

    It is widely known that variation of the C/N ratio is dependent on many state variables during composting processes. This study attempted to develop a genetic algorithm aided stepwise cluster analysis (GASCA) method to describe the nonlinear relationships between the selected state variables and the C/N ratio in food waste composting. The experimental data from six bench-scale composting reactors were used to demonstrate the applicability of GASCA. Within the GASCA framework, GA searched optimal sets of both specified state variables and SCA's internal parameters; SCA established statistical nonlinear relationships between state variables and the C/N ratio; to avoid unnecessary and time-consuming calculation, a proxy table was introduced to save around 70% computational efforts. The obtained GASCA cluster trees had smaller sizes and higher prediction accuracy than the conventional SCA trees. Based on the optimal GASCA tree, the effects of the GA-selected state variables on the C/N ratio were ranged in a descending order as: NH{sub 4}{sup +}-N concentration > Moisture content > Ash Content > Mean Temperature > Mesophilic bacteria biomass. Such a rank implied that the variation of ammonium nitrogen concentration, the associated temperature and the moisture conditions, the total loss of both organic matters and available mineral constituents, and the mesophilic bacteria activity, were critical factors affecting the C/N ratio during the investigated food waste composting. This first application of GASCA to composting modelling indicated that more direct search algorithms could be coupled with SCA or other multivariate analysis methods to analyze complicated relationships during composting and many other environmental processes. - Research Highlights: {yields} A genetic algorithm aided stepwise cluster analysis method in food waste composting. {yields} Nonlinear relationships between the selected state variables and the C/N ratio. {yields} Introduced proxy tables

  1. Individual and Work-Related Factors Influencing Burnout of Mental Health Professionals: A Meta-Analysis

    Science.gov (United States)

    Lim, Nayoung; Kim, Eun Kyoung; Kim, Hyunjung; Yang, Eunjoo; Lee, Sang Min

    2010-01-01

    The current study identifies and assesses individual and work-related factors as correlates of burnout among mental health professionals. Results of a meta-analysis indicate that age and work setting variables are the most significant indicators of emotional exhaustion and depersonalization. In terms of level of personal accomplishment, the age…

  2. Foot-and-Mouth Disease Virus Serotype O Phylodynamics: Genetic Variability Associated with Epidemiological Factors in Pakistan

    DEFF Research Database (Denmark)

    Brito, B. P.; Perez, A. M.; Jamal, S. M.

    2013-01-01

    One of the most challenging aspects of foot-and-mouth disease (FMD) control is the high genetic variability of the FMD virus (FMDV). In endemic settings such as the Indian subcontinent, this variability has resulted in the emergence of pandemic strains that have spread widely and caused devastating...... outbreaks in disease-free areas. In countries trying to control and eradicate FMD using vaccination strategies, the constantly evolving and wide diversity of field FMDV strains is an obstacle for identifying vaccine strains that are successful in conferring protection against infection with field viruses....... Consequently, quantitative knowledge on the factors that are associated with variability of the FMDV is prerequisite for preventing and controlling FMD in the Indian subcontinent. A hierarchical linear model was used to assess the association between time, space, host species and the genetic variability...

  3. The Effects of Variability and Risk in Selection Utility Analysis: An Empirical Comparison.

    Science.gov (United States)

    Rich, Joseph R.; Boudreau, John W.

    1987-01-01

    Investigated utility estimate variability for the selection utility of using the Programmer Aptitude Test to select computer programmers. Comparison of Monte Carlo results to other risk assessment approaches (sensitivity analysis, break-even analysis, algebraic derivation of the distribtion) suggests that distribution information provided by Monte…

  4. Analysis of nasopharyngeal carcinoma risk factors with Bayesian networks.

    Science.gov (United States)

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

    2012-01-01

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

  5. A Bayesian Nonparametric Approach to Factor Analysis

    DEFF Research Database (Denmark)

    Piatek, Rémi; Papaspiliopoulos, Omiros

    2018-01-01

    This paper introduces a new approach for the inference of non-Gaussian factor models based on Bayesian nonparametric methods. It relaxes the usual normality assumption on the latent factors, widely used in practice, which is too restrictive in many settings. Our approach, on the contrary, does no...

  6. 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)

  7. Determining the spatial variability of wetland soil bulk density, organic matter, and the conversion factor between organic matter and organic carbon across coastal Louisiana, U.S.A.

    Science.gov (United States)

    Wang, Hongqing; Piazza, Sarai C.; Sharp, Leigh A.; Stagg, Camille L.; Couvillion, Brady R.; Steyer, Gregory D.; McGinnis, Thomas E.

    2016-01-01

    Soil bulk density (BD), soil organic matter (SOM) content, and a conversion factor between SOM and soil organic carbon (SOC) are often used in estimating SOC sequestration and storage. Spatial variability in BD, SOM, and the SOM–SOC conversion factor affects the ability to accurately estimate SOC sequestration, storage, and the benefits (e.g., land building area and vertical accretion) associated with wetland restoration efforts, such as marsh creation and sediment diversions. There are, however, only a few studies that have examined large-scale spatial variability in BD, SOM, and SOM–SOC conversion factors in coastal wetlands. In this study, soil cores, distributed across the entire coastal Louisiana (approximately 14,667 km2) were used to examine the regional-scale spatial variability in BD, SOM, and the SOM–SOC conversion factor. Soil cores for BD and SOM analyses were collected during 2006–09 from 331 spatially well-distributed sites in the Coastwide Reference Monitoring System network. Soil cores for the SOM–SOC conversion factor analysis were collected from 15 sites across coastal Louisiana during 2006–07. Results of a split-plot analysis of variance with incomplete block design indicated that BD and SOM varied significantly at a landscape level, defined by both hydrologic basins and vegetation types. Vertically, BD and SOM varied significantly among different vegetation types. The SOM–SOC conversion factor also varied significantly at the landscape level. This study provides critical information for the assessment of the role of coastal wetlands in large regional carbon budgets and the estimation of carbon credits from coastal restoration.

  8. Factors that affect the variability in heart rate during endoscopic retrograde cholangiopancreatography

    DEFF Research Database (Denmark)

    Christensen, Merete; Reinert, Rebekka; Rasmussen, Verner

    2002-01-01

    OBJECTIVE: To find out if drugs, position, and endoscopic manipulation during endoscopic retrograde cholangiopancreatography (ERCP) influence the changes in the variability of heart rate. DESIGN: Single-blind randomised trial. SUBJECTS: 10 volunteers given butyscopolamine, glucagon, or saline...

  9. A Variable Stiffness Analysis Model for Large Complex Thin-Walled Guide Rail

    Directory of Open Access Journals (Sweden)

    Wang Xiaolong

    2016-01-01

    Full Text Available Large complex thin-walled guide rail has complicated structure and no uniform low rigidity. The traditional cutting simulations are time consuming due to huge computation especially in large workpiece. To solve these problems, a more efficient variable stiffness analysis model has been propose, which can obtain quantitative stiffness value of the machining surface. Applying simulate cutting force in sampling points using finite element analysis software ABAQUS, the single direction variable stiffness rule can be obtained. The variable stiffness matrix has been propose by analyzing multi-directions coupling variable stiffness rule. Combining with the three direction cutting force value, the reasonability of existing processing parameters can be verified and the optimized cutting parameters can be designed.

  10. Clinical Variability in Cardiovascular Disease Risk Factor Screening and Management in Adolescent and Young Adult Women with Polycystic Ovary Syndrome.

    Science.gov (United States)

    Baer, Tamara E; Milliren, Carly E; Walls, Courtney; DiVasta, Amy D

    2015-10-01

    To review the clinical presentation, evaluation, and management of normal-weight (NW), overweight (OW), and obese (OB) adolescent and young adult women with polycystic ovary syndrome (PCOS) during a 2-year follow-up. Retrospective chart review. One hundred seventy-three adolescent and young adult women, aged 12-22 years, diagnosed with PCOS. Demographic, health data, and laboratory measures were abstracted from 3 clinic visits: baseline and 1- and 2-year follow-up. Subjects were classified as NW, OW, or OB. Longitudinal data were analyzed using repeated-measures analysis of variance. Body mass index, self-reported concerns, and lifestyle changes. Most patients (73%) were OW or OB. Family history of type 2 diabetes was greater in OW (38%) and OB (53%) patients compared with NW (22%) patients (P = .002). Acanthosis nigricans was identified in OW (62%) and OB (21%) patients but not in NW patients (0%; P insulin (P PCOS were OW or OB. Substantial clinical variability existed in cardiovascular disease (CVD) screening; among those screened, OW and OB patients had greater CVD risk factors. Despite self-reported concerns about weight and diabetes risk among OW and OB patients, no clinically significant change in body mass index percentile occurred. Evidence-based interventions and recommendations for screening tests are needed to address CVD risk in adolescents and young adults with PCOS. Copyright © 2015 North American Society for Pediatric and Adolescent Gynecology. Published by Elsevier Inc. All rights reserved.

  11. 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.

  12. A Geographic Information-Assisted Temporal Mixture Analysis for Addressing the Issue of Endmember Class and Endmember Spectra Variability

    Directory of Open Access Journals (Sweden)

    Wenliang Li

    2017-03-01

    Full Text Available Spectral mixture analysis (SMA is a common approach for parameterizing biophysical fractions of urban environment and widely applied in many fields. For successful SMA, the selection of endmember class and corresponding spectra has been assumed as the most important step. Thanks to the spatial heterogeneity of natural and urban landscapes, the variability of endmember class and corresponding spectra has been widely considered as the profound error source in SMA. To address the challenging problems, we proposed a geographic information-assisted temporal mixture analysis (GATMA. Specifically, a logistic regression analysis was applied to analyze the relationship between land use/land covers and surrounding socio-economic factors, and a classification tree method was used to identify the present status of endmember classes throughout the whole study area. Furthermore, an ordinary kriging analysis was employed to generate a spatially varying endmember spectra at all pixels in the remote sensing image. As a consequence, a fully constrained temporal mixture analysis was conducted for examining the fractional land use land covers. Results show that the proposed GATMA achieved a promising accuracy with an RMSE of 6.81%, SE of 1.29% and MAE of 2.6%. In addition, comparative analysis result illustrates that a significant accuracy improvement has been found in the whole study area and both developed and less developed areas, and this demonstrates that the variability of endmember class and endmember spectra is essential for unmixing analysis.

  13. Short-term variability of Johor River discharge based on wavelet analysis

    Science.gov (United States)

    Ahmad, N.; Kamaruddin, S. A.; Heryansyah, A.

    2015-02-01

    River discharge provides a direct measure of water quantity and availability of water for specific uses. It also provides the basis for understanding river basin processes and is essential for interpreting and understanding river flow characteristics. This study investigates the temporal variability of river discharge records of Johor River. Wavelet analysis of discharge records for 30 years was carried out to characterize the river flow variability. Our results indicate that Johor River discharge data shows a significant short-term variability of between 0.6 to 2.5 years.

  14. Factors driving the spatiotemporal variability in phytoplankton in the Northern South China Sea

    Science.gov (United States)

    Wei, Na; Satheeswaran, Thangaraj; Jenkinson, Ian R.; Xue, Bing; Wei, Yuqiu; Liu, Haijiao; Sun, Jun

    2018-06-01

    The influence of oceanographic processes on phytoplankton diversity and community structure was examined during a cruise conducted from July to August 2012 in the northern South China Sea (nSCS). One hundred ninety seven seawater samples were collected and analyzed from 41 stations in the nSCS. A total of 215 species were identified belonging to 67 genera, mostly dominated by diatoms (67.36%) followed by dinoflagellates (28.16%). The mean cell abundance of diatoms and dinoflagellates were 1.954 × 103 cells L-1 and 0.817 × 103 cells L-1, respectively. Diatoms mainly distributed in coastal region whereas dianoflaglletes in the open sea. Margalaf's species richness (dMa) was maximum (3.96) at SQD1 station (Depth 15 m), whereas it was minimum (0.07) at SS1 (Depth 200 m). Further, Box-Whisker plot displayed that dissolved inorganic nutrients incresed with depth. Nevertheless, redundacy analysis reveled that phytoplankton density has a negative relationship with nutrients. Overall the presesant study provides latest in-depth information about how the factors influencing the phytoplankton density and diversity in the (nSCS) during summer based on the cruise data which could serve as a reference for the similar study.

  15. 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.

  16. 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.

  17. 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)

  18. Discrete factor approximations in simultaneous equation models: estimating the impact of a dummy endogenous variable on a continuous outcome.

    Science.gov (United States)

    Mroz, T A

    1999-10-01

    This paper contains a Monte Carlo evaluation of estimators used to control for endogeneity of dummy explanatory variables in continuous outcome regression models. When the true model has bivariate normal disturbances, estimators using discrete factor approximations compare favorably to efficient estimators in terms of precision and bias; these approximation estimators dominate all the other estimators examined when the disturbances are non-normal. The experiments also indicate that one should liberally add points of support to the discrete factor distribution. The paper concludes with an application of the discrete factor approximation to the estimation of the impact of marriage on wages.

  19. Sensitivity Analysis of Weather Variables on Offsite Consequence Analysis Tools in South Korea and the United States.

    Science.gov (United States)

    Kim, Min-Uk; Moon, Kyong Whan; Sohn, Jong-Ryeul; Byeon, Sang-Hoon

    2018-05-18

    We studied sensitive weather variables for consequence analysis, in the case of chemical leaks on the user side of offsite consequence analysis (OCA) tools. We used OCA tools Korea Offsite Risk Assessment (KORA) and Areal Location of Hazardous Atmospheres (ALOHA) in South Korea and the United States, respectively. The chemicals used for this analysis were 28% ammonia (NH₃), 35% hydrogen chloride (HCl), 50% hydrofluoric acid (HF), and 69% nitric acid (HNO₃). The accident scenarios were based on leakage accidents in storage tanks. The weather variables were air temperature, wind speed, humidity, and atmospheric stability. Sensitivity analysis was performed using the Statistical Package for the Social Sciences (SPSS) program for dummy regression analysis. Sensitivity analysis showed that impact distance was not sensitive to humidity. Impact distance was most sensitive to atmospheric stability, and was also more sensitive to air temperature than wind speed, according to both the KORA and ALOHA tools. Moreover, the weather variables were more sensitive in rural conditions than in urban conditions, with the ALOHA tool being more influenced by weather variables than the KORA tool. Therefore, if using the ALOHA tool instead of the KORA tool in rural conditions, users should be careful not to cause any differences in impact distance due to input errors of weather variables, with the most sensitive one being atmospheric stability.

  20. Sensitivity Analysis of Weather Variables on Offsite Consequence Analysis Tools in South Korea and the United States

    Directory of Open Access Journals (Sweden)

    Min-Uk Kim

    2018-05-01

    Full Text Available We studied sensitive weather variables for consequence analysis, in the case of chemical leaks on the user side of offsite consequence analysis (OCA tools. We used OCA tools Korea Offsite Risk Assessment (KORA and Areal Location of Hazardous Atmospheres (ALOHA in South Korea and the United States, respectively. The chemicals used for this analysis were 28% ammonia (NH3, 35% hydrogen chloride (HCl, 50% hydrofluoric acid (HF, and 69% nitric acid (HNO3. The accident scenarios were based on leakage accidents in storage tanks. The weather variables were air temperature, wind speed, humidity, and atmospheric stability. Sensitivity analysis was performed using the Statistical Package for the Social Sciences (SPSS program for dummy regression analysis. Sensitivity analysis showed that impact distance was not sensitive to humidity. Impact distance was most sensitive to atmospheric stability, and was also more sensitive to air temperature than wind speed, according to both the KORA and ALOHA tools. Moreover, the weather variables were more sensitive in rural conditions than in urban conditions, with the ALOHA tool being more influenced by weather variables than the KORA tool. Therefore, if using the ALOHA tool instead of the KORA tool in rural conditions, users should be careful not to cause any differences in impact distance due to input errors of weather variables, with the most sensitive one being atmospheric stability.

  1. Importance analysis for models with correlated variables and its sparse grid solution

    International Nuclear Information System (INIS)

    Li, Luyi; Lu, Zhenzhou

    2013-01-01

    For structural models involving correlated input variables, a novel interpretation for variance-based importance measures is proposed based on the contribution of the correlated input variables to the variance of the model output. After the novel interpretation of the variance-based importance measures is compared with the existing ones, two solutions of the variance-based importance measures of the correlated input variables are built on the sparse grid numerical integration (SGI): double-loop nested sparse grid integration (DSGI) method and single loop sparse grid integration (SSGI) method. The DSGI method solves the importance measure by decreasing the dimensionality of the input variables procedurally, while SSGI method performs importance analysis through extending the dimensionality of the inputs. Both of them can make full use of the advantages of the SGI, and are well tailored for different situations. By analyzing the results of several numerical and engineering examples, it is found that the novel proposed interpretation about the importance measures of the correlated input variables is reasonable, and the proposed methods for solving importance measures are efficient and accurate. -- Highlights: •The contribution of correlated variables to the variance of the output is analyzed. •A novel interpretation for variance-based indices of correlated variables is proposed. •Two solutions for variance-based importance measures of correlated variables are built

  2. Nonparametric factor analysis of time series

    OpenAIRE

    Rodríguez-Poo, Juan M.; Linton, Oliver Bruce

    1998-01-01

    We introduce a nonparametric smoothing procedure for nonparametric factor analaysis of multivariate time series. The asymptotic properties of the proposed procedures are derived. We present an application based on the residuals from the Fair macromodel.

  3. Analysis of success factors in advertising

    OpenAIRE

    Fedorchak, Oleksiy; Kedebecz, Kristina

    2017-01-01

    The essence of factors of the success of advertising campaigns is investigated. The stages of conducting and stages of evaluation of the effectiveness of advertising campaigns are determined. Also defined goals and objectives of advertising campaigns.

  4. 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

  5. Holographic analysis of diffraction structure factors

    International Nuclear Information System (INIS)

    Marchesini, S.; Bucher, J.J.; Shuh, D.K.; Fabris, L.; Press, M.J.; West, M.W.; Hussain, Z.; Mannella, N.; Fadley, C.S.; Van Hove, M.A.; Stolte, W.C.

    2002-01-01

    We combine the theory of inside-source/inside-detector x-ray fluorescence holography and Kossel lines/ x ray standing waves in kinematic approximation to directly obtain the phases of the diffraction structure factors. The influence of Kossel lines and standing waves on holography is also discussed. We obtain partial phase determination from experimental data obtaining the sign of the real part of the structure factor for several reciprocal lattice vectors of a vanadium crystal

  6. A preliminary analysis of the variability of ionospheric characteristics from ionosonde data

    International Nuclear Information System (INIS)

    Mosert, M.; Ezquer, R.; Miro, G.; Corbella, R.; Zerda, L. de la

    2003-01-01

    We use ionosonde data obtained at El Arenosillo (37.1, 353.2), Tucuman (-26.9, 294.6), San Juan (-31.5, 294.5), Buenos Aires (-34.6, 301.7), Ushuaia (-54.8, 291.7) and Puerto Belgrano (-77.9, 321.4) to study the variability of the critical frequencies foE, foF1, foF2 and the propagation factor M(3000)F2 as a function of local time, season, latitude and solar cycle. Two variability indexes were introduced: Clo= Qlo/ median and Cup= Qup/ median, in order to quantify the variability of the parameters. The results indicate that these parameters are helpful to the development of a quantitative model of the variability of the different ionospheric parameters. (author)

  7. Analysis of genetic variability in the Czech Dachshund population using microsatellite markers

    Czech Academy of Sciences Publication Activity Database

    Přibáňová, M.; Horák, Pavel; Schröffelová, D.; Urban, T.; Bechyňová, Renata; Musilová, L.

    2009-01-01

    Roč. 126, - (2009), s. 311-318 ISSN 0931-2668 R&D Projects: GA AV ČR 1QS500450578; GA ČR GD523/03/H076 Institutional research plan: CEZ:AV0Z50450515 Keywords : dachshund * dog * genetic variability * microsatellite Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 1.706, year: 2009

  8. Analysis of Autonomic Nervous System Functional Age and Heart Rate Variability in Mine Workers

    Directory of Open Access Journals (Sweden)

    Vasicko T

    2016-04-01

    Full Text Available Introduction: Heavy working conditions and many unpropitious factors influencing workers health participate in development of various health disorders, among other autonomic cardiovascular regulation malfunction. The aim of this study is to draw a comparison of autonomic nervous system functional age and heart rate variability changes between workers with and without mining occupational exposure.

  9. A Sociological Analysis on the Effective factors in Tends to Hijab

    Directory of Open Access Journals (Sweden)

    Mahmood Sharepour

    2012-12-01

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

  10. Identification of Variables and Factors Impacting Consumer Behavior in On-line Shopping in India: An Empirical Study

    Science.gov (United States)

    Chhikara, Sudesh

    On-line shopping is a recent phenomenon in the field of E-Business and is definitely going to be the future of shopping in the world. Most of the companies are running their on-line portals to sell their products/services. Though online shopping is very common outside India, its growth in Indian Market, which is a large and strategic consumer market, is still not in line with the global market. The potential growth of on-line shopping has triggered the idea of conducting a study on on-line shopping in India. The present research paper has used exploratory study to depict and highlight the various categories of factors and variables impacting the behavior of consumers towards on-line shopping in India. The data was collected through in-depth interviews on a sample of 41 respondents from Delhi, Mumbai, Chennai and Bangalore. The results of the study show that on-line shopping in India is basically impacted by five categories of factors like demographics factor, Psychographics factor, Online shopping feature and policies, Technological factor, Security factor. The results of the study are used to present a comprehensive model of on-line shopping which could be further used by the researchers and practitioners for conducting future studies in the similar area. A brief operational definition of all the factors and variables impacting on-line shopping in India is also described. And finally practical implications of the study are also elucidated.

  11. 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)

  12. 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...

  13. Analysis of input variables of an artificial neural network using bivariate correlation and canonical correlation

    International Nuclear Information System (INIS)

    Costa, Valter Magalhaes

    2011-01-01

    was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables using neural networks. (author)

  14. Joint variable frame rate and length analysis for speech recognition under adverse conditions

    DEFF Research Database (Denmark)

    Tan, Zheng-Hua; Kraljevski, Ivan

    2014-01-01

    This paper presents a method that combines variable frame length and rate analysis for speech recognition in noisy environments, together with an investigation of the effect of different frame lengths on speech recognition performance. The method adopts frame selection using an a posteriori signal......-to-noise (SNR) ratio weighted energy distance and increases the length of the selected frames, according to the number of non-selected preceding frames. It assigns a higher frame rate and a normal frame length to a rapidly changing and high SNR region of a speech signal, and a lower frame rate and an increased...... frame length to a steady or low SNR region. The speech recognition results show that the proposed variable frame rate and length method outperforms fixed frame rate and length analysis, as well as standalone variable frame rate analysis in terms of noise-robustness....

  15. Insights into gait disorders: walking variability using phase plot analysis, Huntington's disease.

    Science.gov (United States)

    Collett, Johnny; Esser, Patrick; Khalil, Hanan; Busse, Monica; Quinn, Lori; DeBono, Katy; Rosser, Anne; Nemeth, Andrea H; Dawes, Helen

    2014-09-01

    Huntington's disease (HD) is a progressive inherited neurodegenerative disorder. Identifying sensitive methodologies to quantitatively measure early motor changes have been difficult to develop. This exploratory observational study investigated gait variability and symmetry in HD using phase plot analysis. We measured the walking of 22 controls and 35 HD gene carriers (7 premanifest (PreHD)), 16 early/mid (HD1) and 12 late stage (HD2) in Oxford and Cardiff, UK. The unified Huntington's disease rating scale-total motor scores (UHDRS-TMS) and disease burden scores (DBS) were used to quantify disease severity. Data was collected during a clinical walk test (8.8 or 10 m) using an inertial measurement unit attached to the trunk. The 6 middle strides were used to calculate gait variability determined by spatiotemporal parameters (co-efficient of variation (CoV)) and phase plot analysis. Phase plots considered the variability in consecutive wave forms from vertical movement and were quantified by SDA (spatiotemporal variability), SDB (temporal variability), ratio ∀ (ratio SDA:SDB) and Δangleβ (symmetry). Step time CoV was greater in manifest HD (p0.05). Phase plot analysis identified differences between manifest HD and controls for SDB, Ratio ∀ and Δangle (all pplot analysis may be a sensitive method of detecting gait changes in HD and can be performed quickly during clinical walking tests. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Blood pressure variability predicts cardiovascular events independently of traditional cardiovascular risk factors and target organ damage

    DEFF Research Database (Denmark)

    Vishram, Julie K K; Dahlöf, Björn; Devereux, Richard B

    2015-01-01

    ). METHODS: In 8505 patients randomized to losartan vs. atenolol-based treatment in the LIFE study, we tested whether BP variability assessed as SD and range for BP6-24months measured at 6, 12, 18 and 24 months of treatment was associated with target organ damage (TOD) defined by LVH on ECG and urine albumin......BACKGROUND: Assessment of antihypertensive treatment is normally based on the mean value of a number of blood pressure (BP) measurements. However, it is uncertain whether high in-treatment visit-to-visit BP variability may be harmful in hypertensive patients with left ventricular hypertrophy (LVH.......05), but MI was not. CONCLUSION: In LIFE patients, higher in-treatment BP6-24months variability was independently of mean BP6-24months associated with later CEP and stroke, but not with MI or TOD after 24 months....

  17. Variable-flavor-number scheme in analysis of heavy-quark electro-production data

    International Nuclear Information System (INIS)

    Alekhin, S.; Bluemlein, J.; Klein, S.; Moch, S.

    2009-08-01

    We check the impact of the factorization scheme employed in the calculation of the heavy-quark deep-inelastic scattering (DIS) electro-production on the PDFs determined in the NNLO QCD analysis of the world inclusive neutral-current DIS data combined with the ones on the neutrino-nucleon DIS di-muon production and the fixed-target Drell-Yan process. The charm-quark DIS contribution is calculated in the general-mass variable-flavor-number (GMVFN) scheme: At asymptotically large values of the momentum transfer Q it is given by the zero-mass 4-flavor scheme and at the value of Q equal to the charm-quark mass it is smoothly matched with the 3-flavor scheme using the Buza-Matiounine-Smith-van Neerven prescription. The PDFs obtained in this variant of the fit are very similar to the ones obtained in the fit with a 3-flavor scheme employed. Our 5-flavor PDFs derived from the 3-flavor ones using the NNLO matching conditions are used to calculate the rates of W ± /Z and t anti t production at the Tevatron collider and the LHC at NNLO. (orig.)

  18. Comparative analysis of female physicists in the physical sciences: Motivation and background variables

    Science.gov (United States)

    Dabney, Katherine P.; Tai, Robert H.

    2014-06-01

    The majority of existing science, technology, engineering, and mathematics (STEM) research studies compare women to men, yet a paucity of research exists that examines what differentiates female career choice within the physical sciences. In light of these research trends and recommendations, this study examines the following question: On average, do females who select physics as compared to chemistry doctoral programs differ in their reported personal motivations and background factors prior to entering the field? This question is analyzed using variables from the Project Crossover Survey data set through a subset of female physical science doctoral students and scientists (n =1137). A logistic regression analysis and prototypical odds ratio uncover what differentiates women in the physical sciences based on their academic achievement and experiences ranging from high school through undergraduate education. Results indicate that females who have negative undergraduate chemistry experiences as well as higher grades and positive experiences in undergraduate physics are more likely to pursue a career in physics as opposed to chemistry. Conclusions suggest that a greater emphasis should be placed on the classroom experiences that are provided to females in gateway physics courses. Analyses show that women are not a single entity that should only be examined as a whole group or in comparison to men. Instead women can be compared to one another to see what influences their differences in educational experiences and career choice in STEM-based fields as well as other academic areas of study.

  19. Pressure and pressure derivative analysis for injection tests with variable temperature without type-curve matching

    International Nuclear Information System (INIS)

    Escobar, Freddy Humberto; Martinez, Javier Andres; Montealegre Matilde

    2008-01-01

    The analysis of injection tests under nonisothermic conditions is important for the accurate estimation of the reservoir permeability and the well's skin factor; since previously an isothermical system was assumed without taking into account a moving temperature front which expands with time plus the consequent changes in both viscosity and mobility between the cold and the hot zone of the reservoir which leads to unreliable estimation of the reservoir and well parameters. To construct the solution an analytical approach presented by Boughrara and Peres (2007) was used. That solution was initially introduced for the calculation of the injection pressure in an isothermic system. It was later modified by Boughrara and Reynolds (2007) to consider a system with variable temperature in vertical wells. In this work, the pressure response was obtained by numerical solution of the anisothermical model using the Gauss Quadrature method to solve the integrals, and assuming that both injection and reservoir temperatures were kept constant during the injection process and the water saturation is uniform throughout the reservoir. For interpretation purposes, a technique based upon the unique features of the pressure and pressure derivative curves were used without employing type-curve matching (TDS technique). The formulation was verified by its application to field and synthetic examples. As expected, increasing reservoir temperature causes a decrement in the mobility ratio, then estimation of reservoir permeability is some less accurate from the second radial flow, especially, as the mobility ratio increases

  20. Implementation of a variable-step integration technique for nonlinear structural dynamic analysis

    International Nuclear Information System (INIS)

    Underwood, P.; Park, K.C.

    1977-01-01

    The paper presents the implementation of a recently developed unconditionally stable implicit time integration method into a production computer code for the transient response analysis of nonlinear structural dynamic systems. The time integrator is packaged with two significant features; a variable step size that is automatically determined and this is accomplished without additional matrix refactorizations. The equations of motion solved by the time integrator must be cast in the pseudo-force form, and this provides the mechanism for controlling the step size. Step size control is accomplished by extrapolating the pseudo-force to the next time (the predicted pseudo-force), then performing the integration step and then recomputing the pseudo-force based on the current solution (the correct pseudo-force); from this data an error norm is constructed, the value of which determines the step size for the next step. To avoid refactoring the required matrix with each step size change a matrix scaling technique is employed, which allows step sizes to change by a factor of 100 without refactoring. If during a computer run the integrator determines it can run with a step size larger than 100 times the original minimum step size, the matrix is refactored to take advantage of the larger step size. The strategy for effecting these features are discussed in detail. (Auth.)

  1. Comparative analysis of female physicists in the physical sciences: Motivation and background variables

    Directory of Open Access Journals (Sweden)

    Katherine P. Dabney

    2014-02-01

    Full Text Available The majority of existing science, technology, engineering, and mathematics (STEM research studies compare women to men, yet a paucity of research exists that examines what differentiates female career choice within the physical sciences. In light of these research trends and recommendations, this study examines the following question: On average, do females who select physics as compared to chemistry doctoral programs differ in their reported personal motivations and background factors prior to entering the field? This question is analyzed using variables from the Project Crossover Survey data set through a subset of female physical science doctoral students and scientists (n=1137. A logistic regression analysis and prototypical odds ratio uncover what differentiates women in the physical sciences based on their academic achievement and experiences ranging from high school through undergraduate education. Results indicate that females who have negative undergraduate chemistry experiences as well as higher grades and positive experiences in undergraduate physics are more likely to pursue a career in physics as opposed to chemistry. Conclusions suggest that a greater emphasis should be placed on the classroom experiences that are provided to females in gateway physics courses. Analyses show that women are not a single entity that should only be examined as a whole group or in comparison to men. Instead women can be compared to one another to see what influences their differences in educational experiences and career choice in STEM-based fields as well as other academic areas of study.

  2. Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

    Science.gov (United States)

    Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

    2016-03-10

    Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    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.

  4. Variables associated with olfactory disorders in adults: A U.S. population-based analysis

    Directory of Open Access Journals (Sweden)

    Julia Noel

    2017-03-01

    Full Text Available Objective: Olfactory dysfunction is known to have significant social, psychological, and safety implications. Despite increasingly recognized prevalence, potential risk factors for olfactory loss have been arbitrarily documented and knowledge is limited in scale. The aim of this study is to identify potential demographic and exposure variables correlating with olfactory dysfunction. Methods: Cross-sectional analysis of the 2011–2012 and 2013–2014 editions of the National Health Examination and Nutrition Survey was performed. The utilized survey reports from a nationally representative sample of about 5000 persons each year located in counties across the United States. There is an interview and physical examination component which includes demographic, socioeconomic, dietary, and health-related questions as well as medical, dental, physiologic measurements, and laboratory tests. 3594 adult respondents from 2011 to 2012 and 3708 respondents from 2013 to 2014 were identified from the above population-based database. The frequency of self-reported disorders as well as performance on odor identification testing was determined in relation to demographic factors, occupational or environmental exposures, and urinary levels of environmental and industrial compounds. Results: In both subjective and objective analysis, smell disorders were significantly more common with increasing age. While the non-Hispanic Black and non-Hispanic Asian populations were less likely to report subjective olfactory loss, they, along with Hispanics, performed more poorly on odor identification than Caucasians. Those with limited education had a decreased prevalence of hyposmia. Women outperformed men on smell testing. Those reporting exposure to vapors were more likely to experience olfactory dysfunction, and urinary levels of manganese, 2-Thioxothiazolidine-4-carboxylic acid, and 2-Aminothiazoline-4-carboxylic acid were lower among respondents with subjective smell

  5. Analysis of Increased Information Technology Outsourcing Factors

    Directory of Open Access Journals (Sweden)

    Brcar Franc

    2013-01-01

    Full Text Available The study explores the field of IT outsourcing. The narrow field of research is to build a model of IT outsourcing based on influential factors. The purpose of this research is to determine the influential factors on IT outsourcing expansion. A survey was conducted with 141 large-sized Slovenian companies. Data were statistically analyzed using binary logistic regression. The final model contains five factors: (1 management’s support; (2 knowledge on IT outsourcing; (3 improvement of efficiency and effectiveness; (4 quality improvement of IT services; and (5 innovation improvement of IT. Managers immediately can use the results of this research in their decision-making. Increased performance of each individual organization is to the benefit of the entire society. The examination of IT outsourcing with the methods used is the first such research in Slovenia.

  6. 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.

  7. Postpartum Depression in Women: A Risk Factor Analysis.

    Science.gov (United States)

    Zaidi, Farheen; Nigam, Aruna; Anjum, Ruby; Agarwalla, Rashmi

    2017-08-01

    Postpartum Depression (PPD) is a known entity affecting not only the women but the whole family. It affects women more harshly and chronically due to their increased stress sensitivity, maladaptive coping strategies and multiple social roles in the community. To estimate the commonly associated risk factors of PPD among the women coming to a tertiary hospital in New Delhi, India. It was a longitudinal study conducted at the antenatal clinic for a period of one year. Total 260 women were screened at > 36 weeks of gestation, of which 149 postnatal women completed the questionnaire for PPD at six weeks of their delivery. The inform consent, demographical data and obstetrical details from each participant was taken before commencing the screening. Various risk factors and their association were determined by odds-ratio and significant association was accepted at order to identify the most important confounding variables, logistic regression analysis was used. PPD is a common mental health problem seen among the postnatal women as it was found in 12.75% (19 out of 149) of subjects at six weeks of their delivery. Moreover, it has significant association with the young maternal age (p-value=0.040), birth of the female child (p-value=0.015), previous stressful life events (p-value= 0.003), low self-esteem and feeling of loneliness (p-value=0.007). This study provides important information regarding the risk factors associated with development of PPD in this region of India. Female sex of the new born and the younger age play an important role in the development of PPD.

  8. Time series analysis of embodied interaction: Movement variability and complexity matching as dyadic properties

    Directory of Open Access Journals (Sweden)

    Leonardo Zapata-Fonseca

    2016-12-01

    Full Text Available There is a growing consensus that a fuller understanding of social cognition depends on more systematic studies of real-time social interaction. Such studies require methods that can deal with the complex dynamics taking place at multiple interdependent temporal and spatial scales, spanning sub-personal, personal, and dyadic levels of analysis. We demonstrate the value of adopting an extended multi-scale approach by re-analyzing movement time series generated in a study of embodied dyadic interaction in a minimal virtual reality environment (a perceptual crossing experiment. Reduced movement variability revealed an interdependence between social awareness and social coordination that cannot be accounted for by either subjective or objective factors alone: it picks out interactions in which subjective and objective conditions are convergent (i.e. elevated coordination is perceived as clearly social, and impaired coordination is perceived as socially ambiguous. This finding is consistent with the claim that interpersonal interaction can be partially constitutive of direct social perception. Clustering statistics (Allan Factor of salient events revealed fractal scaling. Complexity matching defined as the similarity between these scaling laws was significantly more pronounced in pairs of participants as compared to surrogate dyads. This further highlights the multi-scale and distributed character of social interaction and extends previous complexity matching results from dyadic conversation to nonverbal social interaction dynamics. Trials with successful joint interaction were also associated with an increase in local coordination. Consequently, a local coordination pattern emerges on the background of complex dyadic interactions in the PCE task and makes joint successful performance possible.

  9. Comparative Analysis of Upper Ocean Heat Content Variability from Ensemble Operational Ocean Analyses

    Science.gov (United States)

    Xue, Yan; Balmaseda, Magdalena A.; Boyer, Tim; Ferry, Nicolas; Good, Simon; Ishikawa, Ichiro; Rienecker, Michele; Rosati, Tony; Yin, Yonghong; Kumar, Arun

    2012-01-01

    Upper ocean heat content (HC) is one of the key indicators of climate variability on many time-scales extending from seasonal to interannual to long-term climate trends. For example, HC in the tropical Pacific provides information on thermocline anomalies that is critical for the longlead forecast skill of ENSO. Since HC variability is also associated with SST variability, a better understanding and monitoring of HC variability can help us understand and forecast SST variability associated with ENSO and other modes such as Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO), Tropical Atlantic Variability (TAV) and Atlantic Multidecadal Oscillation (AMO). An accurate ocean initialization of HC anomalies in coupled climate models could also contribute to skill in decadal climate prediction. Errors, and/or uncertainties, in the estimation of HC variability can be affected by many factors including uncertainties in surface forcings, ocean model biases, and deficiencies in data assimilation schemes. Changes in observing systems can also leave an imprint on the estimated variability. The availability of multiple operational ocean analyses (ORA) that are routinely produced by operational and research centers around the world provides an opportunity to assess uncertainties in HC analyses, to help identify gaps in observing systems as they impact the quality of ORAs and therefore climate model forecasts. A comparison of ORAs also gives an opportunity to identify deficiencies in data assimilation schemes, and can be used as a basis for development of real-time multi-model ensemble HC monitoring products. The OceanObs09 Conference called for an intercomparison of ORAs and use of ORAs for global ocean monitoring. As a follow up, we intercompared HC variations from ten ORAs -- two objective analyses based on in-situ data only and eight model analyses based on ocean data assimilation systems. The mean, annual cycle, interannual variability and longterm trend of HC have

  10. a Latent Variable Path Analysis Model of Secondary Physics Enrollments in New York State.

    Science.gov (United States)

    Sobolewski, Stanley John

    The Percentage of Enrollment in Physics (PEP) at the secondary level nationally has been approximately 20% for the past few decades. For a more scientifically literate citizenry as well as specialists to continue scientific research and development, it is desirable that more students enroll in physics. Some of the predictor variables for physics enrollment and physics achievement that have been identified previously includes a community's socioeconomic status, the availability of physics, the sex of the student, the curriculum, as well as teacher and student data. This study isolated and identified predictor variables for PEP of secondary schools in New York. Data gathered by the State Education Department for the 1990-1991 school year was used. The source of this data included surveys completed by teachers and administrators on student characteristics and school facilities. A data analysis similar to that done by Bryant (1974) was conducted to determine if the relationships between a set of predictor variables related to physics enrollment had changed in the past 20 years. Variables which were isolated included: community, facilities, teacher experience, number of type of science courses, school size and school science facilities. When these variables were isolated, latent variable path diagrams were proposed and verified by the Linear Structural Relations computer modeling program (LISREL). These diagrams differed from those developed by Bryant in that there were more manifest variables used which included achievement scores in the form of Regents exam results. Two criterion variables were used, percentage of students enrolled in physics (PEP) and percent of students enrolled passing the Regents physics exam (PPP). The first model treated school and community level variables as exogenous while the second model treated only the community level variables as exogenous. The goodness of fit indices for the models was 0.77 for the first model and 0.83 for the second

  11. A Novel Method for Lithium-Ion Battery Online Parameter Identification Based on Variable Forgetting Factor Recursive Least Squares

    Directory of Open Access Journals (Sweden)

    Zizhou Lao

    2018-05-01

    Full Text Available For model-based state of charge (SOC estimation methods, the battery model parameters change with temperature, SOC, and so forth, causing the estimation error to increase. Constantly updating model parameters during battery operation, also known as online parameter identification, can effectively solve this problem. In this paper, a lithium-ion battery is modeled using the Thevenin model. A variable forgetting factor (VFF strategy is introduced to improve forgetting factor recursive least squares (FFRLS to variable forgetting factor recursive least squares (VFF-RLS. A novel method based on VFF-RLS for the online identification of the Thevenin model is proposed. Experiments verified that VFF-RLS gives more stable online parameter identification results than FFRLS. Combined with an unscented Kalman filter (UKF algorithm, a joint algorithm named VFF-RLS-UKF is proposed for SOC estimation. In a variable-temperature environment, a battery SOC estimation experiment was performed using the joint algorithm. The average error of the SOC estimation was as low as 0.595% in some experiments. Experiments showed that VFF-RLS can effectively track the changes in model parameters. The joint algorithm improved the SOC estimation accuracy compared to the method with the fixed forgetting factor.

  12. Factors Associated with Success in a Calculus Course: An Examination of Personal Variables

    Science.gov (United States)

    Ubuz, Behiye

    2011-01-01

    This study examined relationships between students' personal variables (gender, prior achievements, age and academic major) and their success in the first year undergraduate calculus course. The study sample consisted of 59 first year undergraduate students taking Math 154 Calculus II course. A written test about integral, sequence and series…

  13. Incorporation of gene-specific variability improves expression analysis using high-density DNA microarrays

    Directory of Open Access Journals (Sweden)

    Spitznagel Edward

    2003-11-01

    Full Text Available Abstract Background The assessment of data reproducibility is essential for application of microarray technology to exploration of biological pathways and disease states. Technical variability in data analysis largely depends on signal intensity. Within that context, the reproducibility of individual probe sets has not been hitherto addressed. Results We used an extraordinarily large replicate data set derived from human placental trophoblast to analyze probe-specific contribution to variability of gene expression. We found that signal variability, in addition to being signal-intensity dependant, is probe set-specific. Importantly, we developed a novel method to quantify the contribution of this probe set-specific variability. Furthermore, we devised a formula that incorporates a priori-computed, replicate-based information on probe set- and intensity-specific variability in determination of expression changes even without technical replicates. Conclusion The strategy of incorporating probe set-specific variability is superior to analysis based on arbitrary fold-change thresholds. We recommend its incorporation to any computation of gene expression changes using high-density DNA microarrays. A Java application implementing our T-score is available at http://www.sadovsky.wustl.edu/tscore.html.

  14. Warranty claim analysis considering human factors

    International Nuclear Information System (INIS)

    Wu Shaomin

    2011-01-01

    Warranty claims are not always due to product failures. They can also be caused by two types of human factors. On the one hand, consumers might claim warranty due to misuse and/or failures caused by various human factors. Such claims might account for more than 10% of all reported claims. On the other hand, consumers might not be bothered to claim warranty for failed items that are still under warranty, or they may claim warranty after they have experienced several intermittent failures. These two types of human factors can affect warranty claim costs. However, research in this area has received rather little attention. In this paper, we propose three models to estimate the expected warranty cost when the two types of human factors are included. We consider two types of failures: intermittent and fatal failures, which might result in different claim patterns. Consumers might report claims after a fatal failure has occurred, and upon intermittent failures they might report claims after a number of failures have occurred. Numerical examples are given to validate the results derived.

  15. Chiral analysis of baryon form factors

    Energy Technology Data Exchange (ETDEWEB)

    Gail, T.A.

    2007-11-08

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

  16. 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).

  17. Using a latent variable model with non-constant factor loadings to examine PM2.5 constituents related to secondary inorganic aerosols.

    Science.gov (United States)

    Zhang, Zhenzhen; O'Neill, Marie S; Sánchez, Brisa N

    2016-04-01

    Factor analysis is a commonly used method of modelling correlated multivariate exposure data. Typically, the measurement model is assumed to have constant factor loadings. However, from our preliminary analyses of the Environmental Protection Agency's (EPA's) PM 2.5 fine speciation data, we have observed that the factor loadings for four constituents change considerably in stratified analyses. Since invariance of factor loadings is a prerequisite for valid comparison of the underlying latent variables, we propose a factor model that includes non-constant factor loadings that change over time and space using P-spline penalized with the generalized cross-validation (GCV) criterion. The model is implemented using the Expectation-Maximization (EM) algorithm and we select the multiple spline smoothing parameters by minimizing the GCV criterion with Newton's method during each iteration of the EM algorithm. The algorithm is applied to a one-factor model that includes four constituents. Through bootstrap confidence bands, we find that the factor loading for total nitrate changes across seasons and geographic regions.

  18. Directional semivariogram analysis to identify and rank controls on the spatial variability of fracture networks

    Science.gov (United States)

    Hanke, John R.; Fischer, Mark P.; Pollyea, Ryan M.

    2018-03-01

    In this study, the directional semivariogram is deployed to investigate the spatial variability of map-scale fracture network attributes in the Paradox Basin, Utah. The relative variability ratio (R) is introduced as the ratio of integrated anisotropic semivariogram models, and R is shown to be an effective metric for quantifying the magnitude of spatial variability for any two azimuthal directions. R is applied to a GIS-based data set comprising roughly 1200 fractures, in an area which is bounded by a map-scale anticline and a km-scale normal fault. This analysis reveals that proximity to the fault strongly influences the magnitude of spatial variability for both fracture intensity and intersection density within 1-2 km. Additionally, there is significant anisotropy in the spatial variability, which is correlated with trends of the anticline and fault. The direction of minimum spatial correlation is normal to the fault at proximal distances, and gradually rotates and becomes subparallel to the fold axis over the same 1-2 km distance away from the fault. We interpret these changes to reflect varying scales of influence of the fault and the fold on fracture network development: the fault locally influences the magnitude and variability of fracture network attributes, whereas the fold sets the background level and structure of directional variability.

  19. Multivariate statistical analysis of radioactive variables in two phosphate ores from Sudan

    International Nuclear Information System (INIS)

    Adam, Abdel Majid A.; Eltayeb, Mohamed Ahmed H.

    2012-01-01

    Multivariate statistical techniques are efficient ways to display complex relationships among many objects. An attempt was made to study the radioactive data in two types of Sudanese phosphate deposits; Kurun and Uro phosphate, using several multivariate statistical methods. Pearson correlation coefficient revealed that a U-238 distribution in Kurun phosphate is controlled by the variation of K-40 concentration, whereas in Uro phosphate it is controlled by the variation of U-235 and U-234 concentration. Histograms and normal Q–Q plots clearly show that the radioactive variables did not follow a normal distribution. This non-normality feature observed may be attributed to complicating influence of geological factors. The principal components analysis (PCA) gives a model of five components for representing the acquired data from Kurun phosphate, where 89.5% of the total variance is explained. A model of four components was sufficient to represent the acquired data from Uro phosphate, where 87.5% of the total data variance is explained. The hierarchical cluster analysis (HCA) indicates that U-238 behaves in the same manner in the two types of phosphates; it associated with a group of four radionuclides; U-234, Po-210, Ra-226, Th-230, which the most abundant radionuclides, and all belong to the uranium-238 decay series. Two parameters have been adapted for the direct differentiate between the two phosphates. Firstly, U-238 in Uro phosphate have shown higher degree of mobility (CV% = 82.6) than that in Kurun phosphate (CV% = 64.7), and secondly, the activity ratio of Th-230/Th-232 in Uro phosphate is nine times than that in Kurun phosphate. - Highlights: ► Multivariate statistical techniques were used to characterize radioactive data. ► U-238 in Uro phosphate shows higher degree of mobility (CV% = 82.6). ► U-238 in Kurun phosphate shows lower degree of mobility (CV% = 64.7). ► The radioactive variables did not follow a normal distribution. ► The ratio of Th

  20. Variable selection based near infrared spectroscopy quantitative and qualitative analysis on wheat wet gluten

    Science.gov (United States)

    Lü, Chengxu; Jiang, Xunpeng; Zhou, Xingfan; Zhang, Yinqiao; Zhang, Naiqian; Wei, Chongfeng; Mao, Wenhua

    2017-10-01

    Wet gluten is a useful quality indicator for wheat, and short wave near infrared spectroscopy (NIRS) is a high performance technique with the advantage of economic rapid and nondestructive test. To study the feasibility of short wave NIRS analyzing wet gluten directly from wheat seed, 54 representative wheat seed samples were collected and scanned by spectrometer. 8 spectral pretreatment method and genetic algorithm (GA) variable selection method were used to optimize analysis. Both quantitative and qualitative model of wet gluten were built by partial least squares regression and discriminate analysis. For quantitative analysis, normalization is the optimized pretreatment method, 17 wet gluten sensitive variables are selected by GA, and GA model performs a better result than that of all variable model, with R2V=0.88, and RMSEV=1.47. For qualitative analysis, automatic weighted least squares baseline is the optimized pretreatment method, all variable models perform better results than those of GA models. The correct classification rates of 3 class of 30% wet gluten content are 95.45, 84.52, and 90.00%, respectively. The short wave NIRS technique shows potential for both quantitative and qualitative analysis of wet gluten for wheat seed.

  1. Elsaesser variable analysis of fluctuations in the ion foreshock and undisturbed solar wind

    Science.gov (United States)

    Labelle, James; Treumann, Rudolf A.; Marsch, Eckart

    1994-01-01

    Magnetohydrodynamics (MHD) fluctuations in the solar wind have been investigated previously by use of Elsaesser variables. In this paper, we present a comparison of the spectra of Elsaesser variables in the undisturbed solar wind at 1 AU and in the ion foreshock in front of the Earth. Both observations take place under relatively strong solar wind flow speed conditions (approximately equal 600 km/s). In the undisturbed solar wind we find that outward propagating Alfven waves dominate, as reported by other observers. In the ion foreshock the situation is more complex, with neither outward nor inward propagation dominating over the entire range investigated (1-10 mHz). Measurements of the Poynting vectors associated with the fluctuations are consistent with the Elsaesser variable analysis. These results generally support interpretations of the Elsaesser variables which have been made based strictly on solar wind data and provide additional insight into the nature of the ion foreshock turbulence.

  2. Fractal analysis of heart rate variability and mortality after an acute myocardial infarction

    DEFF Research Database (Denmark)

    Tapanainen, Jari M; Thomsen, Poul Erik Bloch; Køber, Lars

    2002-01-01

    The recently developed fractal analysis of heart rate (HR) variability has been suggested to provide prognostic information about patients with heart failure. This prospective multicenter study was designed to assess the prognostic significance of fractal and traditional HR variability parameters...... in a large, consecutive series of survivors of an acute myocardial infarction (AMI). A consecutive series of 697 patients were recruited to participate 2 to 7 days after an AMI in 3 Nordic university hospitals. The conventional time-domain and spectral parameters and the newer fractal scaling indexes of HR...... variability were analyzed from 24-hour RR interval recordings. During the mean follow-up of 18.4 +/- 6.5 months, 49 patients (7.0%) died. Of all the risk variables, a reduced short-term fractal scaling exponent (alpha(1)

  3. 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.

  4. The knowledge conversion SECI process as innovation indicator analysis factor

    OpenAIRE

    Silva, Elaine da [UNESP; Valentim, Marta Lígia Pomim [UNESP

    2013-01-01

    It highlights the innovation importance in the current society and presents innovation indicators applied in 125 countries. We made an analysis in the 80 variables distributed through seven GII pillars, trying to identify the direct, indirect or null incidences of the knowledge conversion way described by the SECI Process. The researched revealed the fact that knowledge management, in this case specifically the knowledge conversion SECI Process, is present in the variables that, according to ...

  5. Variability of radon and thoron equilibrium factors in indoor environment of Garhwal Himalaya

    International Nuclear Information System (INIS)

    Prasad, Mukesh; Rawat, Mukesh; Dangwal, Anoop; Kandari, Tushar; Gusain, G.S.; Mishra, Rosaline; Ramola, R.C.

    2016-01-01

    The measurements of radon, thoron and their progeny concentrations have been carried out in the dwellings of Uttarkashi and Tehri districts of Garhwal Himalaya, India using LR-115 detector based pin-hole dosimeter and DRPS/DTPS techniques. The equilibrium factors for radon, thoron and their progeny were calculated by using the values measured with these techniques. The average values of equilibrium factor between radon and its progeny have been found to be 0.44, 0.39, 0.39 and 0.28 for rainy, autumn, winter and summer seasons, respectively. For thoron and its progeny, the average values of equilibrium factor have been found to be 0.04, 0.04, 0.04 and 0.03 for rainy, autumn, winter and summer seasons, respectively. The equilibrium factor between radon and its progeny has been found to be dependent on the seasonal changes. However, the equilibrium factor for thoron and progeny has been found to be same for rainy, autumn and winter seasons but slightly different for summer season. The annual average equilibrium factors for radon and thoron have been found to vary from 0.23 to 0.80 with an average of 0.42 and from 0.01 to 0.29 with an average of 0.07, respectively. The detailed discussion of the measurement techniques and the explanation for the results obtained is given in the paper. - Highlights: • Equilibrium factors for indoor radon, thoron and their progeny were measured. • Recently developed passive detector techniques were used for measurements. • The values of equilibrium factors are comparable with world's average values. • Equilibrium factor should be measured separately for individual dwelling. • Separate values of equilibrium factors are useful to produce actual radiation dose.

  6. An Empirical Analysis of Job Satisfaction Factors.

    Science.gov (United States)

    1987-09-01

    have acknowledged the importance of factors which make the Air Force attractive to its members or conversely, make other employees consider...Maslow’s need hierarchy theory attempts to show that man has five basic categories of needs: physiological, safety, belongingness , esteem, and self...attained until lower-level basic needs are attained. This implies a sort of growth process where optional job environments for given employees are

  7. Soil structure interaction model and variability of parameters in seismic analysis of nuclear island connected building

    International Nuclear Information System (INIS)

    Subramanian, K.V.; Palekar, S.M.; Bavare, M.S.; Mapari, H.A.; Patel, S.C.; Pillai, C.S.

    2005-01-01

    This paper provides salient features of the Soil Structure Interaction analysis of Nuclear Island Connected Building (NICB). The dynamic analysis of NICB is performed on a full 3D model accounting for the probable variation in the stiffness of the founding medium. A range analyses was performed to establish the effect of variability of subgrade parameters on the results of seismic analyses of NICB. This paper presents details of various analyses with respect to the subgrade model, uncertainties in subgrade properties, results of seismic analyses and a study of effect of the variability of parameters on the results of these analyses. The results of this study indicate that the variability of soil parameters beyond a certain value of shear wave velocity does not influence the response and in fact the response marginally diminishes. (authors)

  8. Analysis of input variables of an artificial neural network using bivariate correlation and canonical correlation

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Valter Magalhaes; Pereira, Iraci Martinez, E-mail: valter.costa@usp.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2011-07-01

    The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because a previous diagnosis allows the correction of the fault and, like this, to prevent the production stopped, improving operator's security and it's not provoking economics losses. The objective of this work is to build a set, using bivariate correlation and canonical correlation, which will be the set of input variables of an artificial neural network to monitor the greater number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. Initially, for the input set of neural network we selected the variables: nuclear power, primary circuit flow rate, control/safety rod position and difference in pressure in the core of the reactor, because almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The nuclear power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures; the primary circuit flow rate has the function of energy transport by removing the nucleus heat. An artificial neural network was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables. (author)

  9. Analysis of input variables of an artificial neural network using bivariate correlation and canonical correlation

    International Nuclear Information System (INIS)

    Costa, Valter Magalhaes; Pereira, Iraci Martinez

    2011-01-01

    The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because a previous diagnosis allows the correction of the fault and, like this, to prevent the production stopped, improving operator's security and it's not provoking economics losses. The objective of this work is to build a set, using bivariate correlation and canonical correlation, which will be the set of input variables of an artificial neural network to monitor the greater number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. Initially, for the input set of neural network we selected the variables: nuclear power, primary circuit flow rate, control/safety rod position and difference in pressure in the core of the reactor, because almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The nuclear power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures; the primary circuit flow rate has the function of energy transport by removing the nucleus heat. An artificial neural network was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables. (author)

  10. Factors controlling temporal variability of near-ground atmospheric 222Rn concentration over central Europe

    Science.gov (United States)

    Zimnoch, M.; Wach, P.; Chmura, L.; Gorczyca, Z.; Rozanski, K.; Godlowska, J.; Mazur, J.; Kozak, K.; Jeričević, A.

    2014-09-01

    Concentration of radon (222Rn) in the near-ground atmosphere has been measured quasi-continuously from January 2005 to December 2009 at two continental sites in Europe: Heidelberg (south-west Germany) and Krakow (southern Poland). The atmosphere was sampled at ca. 30 and 20 m above the local ground. Both stations were equipped with identical instruments. Regular observations of 222Rn were supplemented by measurements of surface fluxes of this gas in the Krakow urban area, using two different approaches. The measured concentrations of 222Rn varied at both sites in a wide range, from less than 2.0 Bq m-3 to approximately 40 Bq m-3 in Krakow and 35 Bq m-3 in Heidelberg. The mean 222Rn content in Krakow, when averaged over the entire observation period, was 30% higher than in Heidelberg (5.86 ± 0.09 and 4.50 ± 0.07 Bq m-3, respectively). Distinct seasonality of 222Rn signal is visible in the obtained time series of 222Rn concentration, with higher values recorded generally during late summer and autumn. The surface 222Rn fluxes measured in Krakow also revealed a distinct seasonality, with broad maximum observed during summer and early autumn and minimum during the winter. When averaged over a 5-year observation period, the night-time surface 222Rn flux was equal to 46.8 ± 2.4 Bq m-2 h-1. Although the atmospheric 222Rn levels at Heidelberg and Krakow appeared to be controlled primarily by local factors, it was possible to evaluate the "continental effect" in atmospheric 222Rn content between both sites, related to gradual build-up of 222Rn concentration in the air masses travelling between Heidelberg and Krakow. The mean value of this build-up was equal to 0.78 ± 0.12 Bq m-3. The measured minimum 222Rn concentrations at both sites and the difference between them was interpreted in the framework of a simple box model coupled with HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) analysis of air mass trajectories. The best fit of experimental data was

  11. Phytoplankton variability in relation to some environmental factors in the eastern coast of Suez Gulf, Egypt.

    Science.gov (United States)

    Nassar, Mohamed Z; El-Din, Nihal G Shams; Gharib, Samiha M

    2015-10-01

    Water samples were seasonally collected from 12 stations of the eastern coast of Suez Gulf during autumn of 2012 and winter, spring, and summer of 2013 in order to investigate phytoplankton community structure in relation to some physicochemical parameters. The study area harbored a diversified phytoplankton community (138 species), belonging to 67 genera. Four algal groups were represented and classified as Bacillariophyceae (90 species), Dinophyceae (28 species), Cyanophyceae (16 species), and Chlorophyceae (4 species). The results indicated a relative high occurrence of some species namely.; Pleurotaenium trabecula of green algae; Chaetoceros lorenzianus, Proboscia alata var. gracillima, Pseudosolenia calcar-avis, and Pseudo-nitzschia pungens of diatoms; Trichodesmium erythraeum and Pseudoanabaena limnetica of cyanophytes. Most of other algal species were fairly distributed at the selected stations of the study area. The total abundance of phytoplankton was relatively low (average of 2989 unit/L) in the eastern coast of Suez Gulf, as compared its western coast and the northern part of the Red Sea. The diversity of phytoplankton species was relatively high (2.35-3.82 nats) with an annual average of 3.22 nats in the present study. The results concluded that most of eastern coast of Suez Gulf is still healthy, relatively unpolluted, and oligotrophic area, which is clearly achieved by the low values of dissolved phosphate (0.025-0.3 μM), nitrate (0.18-1.26 μM), and dissolved ammonium (0.81-5.36 μM). Even if the occurrence of potentially harmful algae species was low, the study area should be monitored continuously. The dissolved oxygen ranged between 1.77 and 8.41 mg/L and pH values between 7.6 and 8.41. The multiple regression analysis showed that the dissolved nitrate and pH values were the most effective factors that controlled the seasonal fluctuations of phytoplankton along the eastern coast of Suez Gulf during 2012-2013.

  12. Risk and protective factors of internet addiction: a meta-analysis of empirical studies in Korea.

    Science.gov (United States)

    Koo, Hoon Jung; Kwon, Jung-Hye

    2014-11-01

    A meta-analysis of empirical studies performed in Korea was conducted to systematically investigate the associations between the indices of Internet addiction (IA) and psychosocial variables. Systematic literature searches were carried out using the Korean Studies Information Service System, Research Information Sharing Service, Science Direct, Google Scholar, and references in review articles. The key words were Internet addiction, (Internet) game addiction, and pathological, problematic, and excessive Internet use. Only original research papers using Korean samples published from 1999 to 2012 and officially reviewed by peers were included for analysis. Ninety-five studies meeting the inclusion criteria were identified. The magnitude of the overall effect size of the intrapersonal variables associated with internet addiction was significantly higher than that of interpersonal variables. Specifically, IA demonstrated a medium to strong association with "escape from self" and "self-identity" as self-related variables. "Attention problem", "self-control", and "emotional regulation" as control and regulation-relation variables; "addiction and absorption traits" as temperament variables; "anger" and "aggression" as emotion and mood and variables; "negative stress coping" as coping variables were also associated with comparably larger effect sizes. Contrary to our expectation, the magnitude of the correlations between relational ability and quality, parental relationships and family functionality, and IA were found to be small. The strength of the association between IA and the risk and protective factors was found to be higher in younger age groups. The findings highlight a need for closer examination of psychosocial factors, especially intrapersonal variables when assessing high-risk individuals and designing intervention strategies for both general IA and Internet game addiction.

  13. Risk and Protective Factors of Internet Addiction: A Meta-Analysis of Empirical Studies in Korea

    Science.gov (United States)

    Koo, Hoon Jung

    2014-01-01

    Purpose A meta-analysis of empirical studies performed in Korea was conducted to systematically investigate the associations between the indices of Internet addiction (IA) and psychosocial variables. Materials and Methods Systematic literature searches were carried out using the Korean Studies Information Service System, Research Information Sharing Service, Science Direct, Google Scholar, and references in review articles. The key words were Internet addiction, (Internet) game addiction, and pathological, problematic, and excessive Internet use. Only original research papers using Korean samples published from 1999 to 2012 and officially reviewed by peers were included for analysis. Ninety-five studies meeting the inclusion criteria were identified. Results The magnitude of the overall effect size of the intrapersonal variables associated with internet addiction was significantly higher than that of interpersonal variables. Specifically, IA demonstrated a medium to strong association with "escape from self" and "self-identity" as self-related variables. "Attention problem", "self-control", and "emotional regulation" as control and regulation-relation variables; "addiction and absorption traits" as temperament variables; "anger" and "aggression" as emotion and mood and variables; "negative stress coping" as coping variables were also associated with comparably larger effect sizes. Contrary to our expectation, the magnitude of the correlations between relational ability and quality, parental relationships and family functionality, and IA were found to be small. The strength of the association between IA and the risk and protective factors was found to be higher in younger age groups. Conclusion The findings highlight a need for closer examination of psychosocial factors, especially intrapersonal variables when assessing high-risk individuals and designing intervention strategies for both general IA and Internet game addiction. PMID:25323910

  14. 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.

  15. 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…

  16. 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

  17. 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.

  18. Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection

    DEFF Research Database (Denmark)

    Sharifzadeh, Sara; Ghodsi, Ali; Clemmensen, Line H.

    2017-01-01

    Principal component analysis (PCA) is one of the main unsupervised pre-processing methods for dimension reduction. When the training labels are available, it is worth using a supervised PCA strategy. In cases that both dimension reduction and variable selection are required, sparse PCA (SPCA...

  19. Analysis and minimization of Torque Ripple for variable Flux reluctance machines

    NARCIS (Netherlands)

    Bao, J.; Gysen, B.L.J.; Boynov, K.; Paulides, J.J.H.; Lomonova, E.A.

    2017-01-01

    Variable flux reluctance machines (VFRMs) are permanent-magnet-free three-phase machines and are promising candidates for applications requiring low cost and robustness. This paper studies the torque ripple and minimization methods for 12-stator VFRMs. Starting with the analysis of harmonics in the

  20. Urban vs. Rural CLIL: An Analysis of Input-Related Variables, Motivation and Language Attainment

    Science.gov (United States)

    Alejo, Rafael; Piquer-Píriz, Ana

    2016-01-01

    The present article carries out an in-depth analysis of the differences in motivation, input-related variables and linguistic attainment of the students at two content and language integrated learning (CLIL) schools operating within the same institutional and educational context, the Spanish region of Extremadura, and differing only in terms of…

  1. Variability and budget of CO2 in Europe: analysis of the CAATER airborne campaigns - Part 1: Observed variability

    International Nuclear Information System (INIS)

    Xueref-Remy, I.; Messager, C.; Ramonet, M.; Paris, J.D.; Ciais, P.; Filippi, D.; Pastel, M.; Nedelec, P.

    2011-01-01

    help to identify the origin of fossil fuel emissions in the PBL even when distanced by several days/hundreds of kms from their sources. We have compared airborne CO 2 observations to nearby ground station measurements and thereby, confirmed that measurements taken in the lower few meters of the PBL (low-level ground stations) are representative of the local scale, while those located in the free troposphere (FT) (mountain stations) are representative of atmospheric CO 2 regionally on a scale of a few hundred kilometers. Stations located several 100 km away from each other differ from a few ppm in their measurements indicating the existence of a gradient within the free troposphere. Observations at stations located on top of small mountains may match the airborne data if the sampled air comes from the FT rather than coming up from the valley. Finally, the analysis of the CO 2 vertical variability conducted on the 14 profiles recorded in each campaign shows a variability at least 5 to 8 times higher in the PBL (the 1- standard deviation associated to the CO 2 mean of all profiles within the PBL is 4.0 ppm and 5.7 ppm for CAATER-1 and CAATER-2, respectively) than in the FT (within the FT, 1-σ is 0.5 ppm and 1.1 ppm for CAATER-1 and CAATER-2, respectively). The CO 2 jump between the PBL and the FT equals 3.7 ppm for the first campaign and -0.3 ppm for the second campaign. A very striking zonal CO 2 gradient of about 11 ppm was observed in the mid-PBL during CAATER-2, with higher concentrations in the west than in the east. This gradient may originate from differences in atmospheric mixing, ground emission rates or Autumn's earlier start in the west. More airborne campaigns are currently under analysis in the framework of the CARBOEUROPE-IP project to better assess the likelihood of these different hypotheses. In a companion paper (Xueref-Remy et al., 2011, Part 2), a comparison of vertical profiles from observations and several modeling frameworks was conducted for both

  2. Variability and budget of CO2 in Europe: analysis of the CAATER airborne campaigns – Part 1: Observed variability

    Directory of Open Access Journals (Sweden)

    J. D. Paris

    2011-06-01

    fossil fuel emissions in the PBL even when distanced by several days/hundreds of kms from their sources. We have compared airborne CO2 observations to nearby ground station measurements and thereby, confirmed that measurements taken in the lower few meters of the PBL (low-level ground stations are representative of the local scale, while those located in the free troposphere (FT (moutain stations are representative of atmospheric CO2 regionally on a scale of a few hundred kilometers. Stations located several 100 km away from each other differ from a few ppm in their measurements indicating the existence of a gradient within the free troposphere. Observations at stations located on top of small mountains may match the airborne data if the sampled air comes from the FT rather than coming up from the valley. Finally, the analysis of the CO2 vertical variability conducted on the 14 profiles recorded in each campaign shows a variability at least 5 to 8 times higher in the PBL (the 1-σ standard deviation associated to the CO2 mean of all profiles within the PBL is 4.0 ppm and 5.7 ppm for CAATER-1 and CAATER-2, respectively than in the FT (within the FT, 1-σ is 0.5 ppm and 1.1 ppm for CAATER-1 and CAATER-2, respectively. The CO2 jump between the PBL and the FT equals 3.7 ppm for the first campaign and −0.3 ppm for the second campaign. A very striking zonal CO2 gradient of about 11 ppm was observed in the mid-PBL during CAATER-2, with higher concentrations in the west than in the east. This gradient may originate from differences in atmospheric mixing, ground emission rates or Autumn's earlier start in the west. More airborne campaigns are currently under analysis in the framework of the CARBOEUROPE-IP project to better assess the likelihood of these different hypotheses. In a companion paper (Xueref-Remy et al., 2011, Part 2, a comparison of vertical profiles from observations and several modeling frameworks was conducted for both campaigns.

  3. Factors affecting temporal variability of arsenic in groundwater used for drinking water supply in the United States.

    Science.gov (United States)

    Ayotte, Joseph D; Belaval, Marcel; Olson, Scott A; Burow, Karen R; Flanagan, Sarah M; Hinkle, Stephen R; Lindsey, Bruce D

    2015-02-01

    The occurrence of arsenic in groundwater is a recognized environmental hazard with worldwide importance and much effort has been focused on surveying and predicting where arsenic occurs. Temporal variability is one aspect of this environmental hazard that has until recently received less attention than other aspects. For this study, we analyzed 1245 wells with two samples per well. We suggest that temporal variability, often reported as affecting very few wells, is perhaps a larger issue than it appears and has been overshadowed by datasets with large numbers of non-detect data. Although there was only a slight difference in arsenic concentration variability among samples from public and private wells (p=0.0452), the range of variability was larger for public than for private wells. Further, we relate the variability we see to geochemical factors-primarily variability in redox-but also variability in major-ion chemistry. We also show that in New England there is a weak but statistically significant indication that seasonality may have an effect on concentrations, whereby concentrations in the first two quarters of the year (January-June) are significantly lower than in the second two quarters (July-December) (pgroundwater levels. It is possible that this difference in arsenic concentrations is related to groundwater level changes, pumping stresses, evapotranspiration effects, or perhaps mixing of more oxidizing, lower pH recharge water in wetter months. Focusing on the understanding the geochemical conditions in aquifers where arsenic concentrations are concerns and causes of geochemical changes in the groundwater environment may lead to a better understanding of where and by how much arsenic will vary over time. Published by Elsevier B.V.

  4. Heart rate variability analysis in postural orthostatic tachycardia syndrome: a case report

    Directory of Open Access Journals (Sweden)

    Raffaele Calabrò

    2006-09-01

    Full Text Available The authors present a case of 36 year old male patient with idiopathic postural orthostatic tachycardia syndrome (POTS diagnosed during head-up tilt testing. Power spectral analysis of heart rate variability (HRV during the tilt test revealed that the ratio of low and high frequency powers (LF/HF increased with the onset of orthostatic intolerance. This analysis confirmed in our patient a strong activation in sympathetic tone.

  5. Factors that contribute to physician variability in decisions to limit life support in the ICU: a qualitative study.

    Science.gov (United States)

    Wilson, Michael E; Rhudy, Lori M; Ballinger, Beth A; Tescher, Ann N; Pickering, Brian W; Gajic, Ognjen

    2013-06-01

    Our aim was to explore reasons for physician variability in decisions to limit life support in the intensive care unit (ICU) utilizing qualitative methodology. Single center study consisting of semi-structured interviews with experienced physicians and nurses. Seventeen intensivists from medical (n = 7), surgical (n = 5), and anesthesia (n = 5) critical care backgrounds, and ten nurses from medical (n = 5) and surgical (n = 5) ICU backgrounds were interviewed. Principles of grounded theory were used to analyze the interview transcripts. Eleven factors within four categories were identified that influenced physician variability in decisions to limit life support: (1) physician work environment-workload and competing priorities, shift changes and handoffs, and incorporation of nursing input; (2) physician experiences-of unexpected patient survival, and of limiting life support in physician's family; (3) physician attitudes-investment in a good surgical outcome, specialty perspective, values and beliefs; and (4) physician relationship with patient and family-hearing the patient's wishes firsthand, engagement in family communication, and family negotiation. We identified several factors which physicians and nurses perceived were important sources of physician variability in decisions to limit life support. Ways to raise awareness and ameliorate the potentially adverse effects of factors such as workload, competing priorities, shift changes, and handoffs should be explored. Exposing intensivists to long term patient outcomes, formalizing nursing input, providing additional training, and emphasizing firsthand knowledge of patient wishes may improve decision making.

  6. 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)

  7. 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.

  8. 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....

  9. Factor Analysis for Finding Invariant Neural Descriptors of Human Emotions

    Directory of Open Access Journals (Sweden)

    Vitor Pereira

    2018-01-01

    Full Text Available A major challenge in decoding human emotions from electroencephalogram (EEG data is finding representations that are invariant to inter- and intrasubject differences. Most of the previous studies are focused in building an individual discrimination model for every subject (subject dependent model. Building subject-independent models is a harder problem due to the high data variability between different subjects and different experiments with the same subject. This paper explores, for the first time, the Factor Analysis as an efficient technique to extract temporal and spatial EEG features suitable to build brain-computer interface for decoding human emotions across various subjects. Our findings show that early waves (temporal window of 200–400 ms after the stimulus onset carry more information about the valence of the emotion. Also, spatial location of features, with a stronger impact on the emotional valence, occurs in the parietal and occipital regions of the brain. All discrimination models (NN, SVM, kNN, and RF demonstrate better discrimination rate of the positive valence. These results match closely experimental psychology hypothesis that, during early periods after the stimulus presentation, the brain response—to images with highly positive valence—is stronger.

  10. Variability of radon and thoron equilibrium factors in indoor environment of Garhwal Himalaya.

    Science.gov (United States)

    Prasad, Mukesh; Rawat, Mukesh; Dangwal, Anoop; Kandari, Tushar; Gusain, G S; Mishra, Rosaline; Ramola, R C

    2016-01-01

    The measurements of radon, thoron and their progeny concentrations have been carried out in the dwellings of Uttarkashi and Tehri districts of Garhwal Himalaya, India using LR-115 detector based pin-hole dosimeter and DRPS/DTPS techniques. The equilibrium factors for radon, thoron and their progeny were calculated by using the values measured with these techniques. The average values of equilibrium factor between radon and its progeny have been found to be 0.44, 0.39, 0.39 and 0.28 for rainy, autumn, winter and summer seasons, respectively. For thoron and its progeny, the average values of equilibrium factor have been found to be 0.04, 0.04, 0.04 and 0.03 for rainy, autumn, winter and summer seasons, respectively. The equilibrium factor between radon and its progeny has been found to be dependent on the seasonal changes. However, the equilibrium factor for thoron and progeny has been found to be same for rainy, autumn and winter seasons but slightly different for summer season. The annual average equilibrium factors for radon and thoron have been found to vary from 0.23 to 0.80 with an average of 0.42 and from 0.01 to 0.29 with an average of 0.07, respectively. The detailed discussion of the measurement techniques and the explanation for the results obtained is given in the paper. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Quantitative effects of composting state variables on C/N ratio through GA-aided multivariate analysis.

    Science.gov (United States)

    Sun, Wei; Huang, Guo H; Zeng, Guangming; Qin, Xiaosheng; Yu, Hui

    2011-03-01

    It is widely known that variation of the C/N ratio is dependent on many state variables during composting processes. This study attempted to develop a genetic algorithm aided stepwise cluster analysis (GASCA) method to describe the nonlinear relationships between the selected state variables and the C/N ratio in food waste composting. The experimental data from six bench-scale composting reactors were used to demonstrate the applicability of GASCA. Within the GASCA framework, GA searched optimal sets of both specified state variables and SCA's internal parameters; SCA established statistical nonlinear relationships between state variables and the C/N ratio; to avoid unnecessary and time-consuming calculation, a proxy table was introduced to save around 70% computational efforts. The obtained GASCA cluster trees had smaller sizes and higher prediction accuracy than the conventional SCA trees. Based on the optimal GASCA tree, the effects of the GA-selected state variables on the C/N ratio were ranged in a descending order as: NH₄+-N concentration>Moisture content>Ash Content>Mean Temperature>Mesophilic bacteria biomass. Such a rank implied that the variation of ammonium nitrogen concentration, the associated temperature and the moisture conditions, the total loss of both organic matters and available mineral constituents, and the mesophilic bacteria activity, were critical factors affecting the C/N ratio during the investigated food waste composting. This first application of GASCA to composting modelling indicated that more direct search algorithms could be coupled with SCA or other multivariate analysis methods to analyze complicated relationships during composting and many other environmental processes. Copyright © 2010 Elsevier B.V. All rights reserved.

  12. Decoupling Solar Variability and Instrument Trends Using the Multiple Same-Irradiance-Level (MuSIL) Analysis Technique

    Science.gov (United States)

    Woods, Thomas N.; Eparvier, Francis G.; Harder, Jerald; Snow, Martin

    2018-05-01

    The solar spectral irradiance (SSI) dataset is a key record for studying and understanding the energetics and radiation balance in Earth's environment. Understanding the long-term variations of the SSI over timescales of the 11-year solar activity cycle and longer is critical for many Sun-Earth research topics. Satellite measurements of the SSI have been made since the 1970s, most of them in the ultraviolet, but recently also in the visible and near-infrared. A limiting factor for the accuracy of previous solar variability results is the uncertainties for the instrument degradation corrections, which need fairly large corrections relative to the amount of solar cycle variability at some wavelengths. The primary objective of this investigation has been to separate out solar cycle variability and any residual uncorrected instrumental trends in the SSI measurements from the Solar Radiation and Climate Experiment (SORCE) mission and the Thermosphere, Mesosphere, Ionosphere, Energetic, and Dynamics (TIMED) mission. A new technique called the Multiple Same-Irradiance-Level (MuSIL) analysis has been developed, which examines an SSI time series at different levels of solar activity to provide long-term trends in an SSI record, and the most common result is a downward trend that most likely stems from uncorrected instrument degradation. This technique has been applied to each wavelength in the SSI records from SORCE (2003 - present) and TIMED (2002 - present) to provide new solar cycle variability results between 27 nm and 1600 nm with a resolution of about 1 nm at most wavelengths. This technique, which was validated with the highly accurate total solar irradiance (TSI) record, has an estimated relative uncertainty of about 5% of the measured solar cycle variability. The MuSIL results are further validated with the comparison of the new solar cycle variability results from different solar cycles.

  13. Sympathetic Activity, Assessed by Power Spectral Analysis of Heart Rate Variability, in White-Coat, Masked and Sustained Hypertension Versus True Normotension

    Czech Academy of Sciences Publication Activity Database

    Fagard, R.H.; Stolarz, K.; Kuznetsova, T.; Seidlerová, J.; Tikhonoff, V.; Grodzicki, T.; Nikitin, Y.; Filipovský, J.; Peleška, Jan; Casiglia, E.; Thijs, L.; Staessen, J.A.; Kawecka-Jaszcz, K.

    2007-01-01

    Roč. 25, č. 11 (2007), s. 2280-2285 ISSN 0263-6352 Institutional research plan: CEZ:AV0Z10300504 Keywords : heart rate variability * masked hypertension * power spectral analysis * sympathetic activity * white-coat hypertension Subject RIV: FA - Cardiovascular Diseases incl. Cardiotharic Surgery Impact factor: 4.364, year: 2007

  14. 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)

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

    International Nuclear Information System (INIS)

    Sato, Renato Cesar; Zouain, Desiree Moraes

    2012-01-01

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

  16. Variability of the western Galician upwelling system (NW Spain) during an intensively sampled annual cycle. An EOF analysis approach

    Science.gov (United States)

    Herrera, J. L.; Rosón, G.; Varela, R. A.; Piedracoba, S.

    2008-07-01

    The key features of the western Galician shelf hydrography and dynamics are analyzed on a solid statistical and experimental basis. The results allowed us to gather together information dispersed in previous oceanographic works of the region. Empirical orthogonal functions analysis and a canonical correlation analysis were applied to a high-resolution dataset collected from 47 surveys done on a weekly frequency from May 2001 to May 2002. The main results of these analyses are summarized bellow. Salinity, temperature and the meridional component of the residual current are correlated with the relevant local forcings (the meridional coastal wind component and the continental run-off) and with a remote forcing (the meridional temperature gradient at latitude 37°N). About 80% of the salinity and temperature total variability over the shelf, and 37% of the residual meridional current total variability are explained by two EOFs for each variable. Up to 22% of the temperature total variability and 14% of the residual meridional current total variability is devoted to the set up of cross-shore gradients of the thermohaline properties caused by the wind-induced Ekman transport. Up to 11% and 10%, respectively, is related to the variability of the meridional temperature gradient at the Western Iberian Winter Front. About 30% of the temperature total variability can be explained by the development and erosion of the seasonal thermocline and by the seasonal variability of the thermohaline properties of the central waters. This thermocline presented unexpected low salinity values due to the trapping during spring and summer of the high continental inputs from the River Miño recorded in 2001. The low salinity plumes can be traced on the Galician shelf during almost all the annual cycle; they tend to be extended throughout the entire water column under downwelling conditions and concentrate in the surface layer when upwelling favourable winds blow. Our evidences point to the

  17. Measurement-Device Independency Analysis of Continuous-Variable Quantum Digital Signature

    Directory of Open Access Journals (Sweden)

    Tao Shang

    2018-04-01

    Full Text Available With the practical implementation of continuous-variable quantum cryptographic protocols, security problems resulting from measurement-device loopholes are being given increasing attention. At present, research on measurement-device independency analysis is limited in quantum key distribution protocols, while there exist different security problems for different protocols. Considering the importance of quantum digital signature in quantum cryptography, in this paper, we attempt to analyze the measurement-device independency of continuous-variable quantum digital signature, especially continuous-variable quantum homomorphic signature. Firstly, we calculate the upper bound of the error rate of a protocol. If it is negligible on condition that all measurement devices are untrusted, the protocol is deemed to be measurement-device-independent. Then, we simplify the calculation by using the characteristics of continuous variables and prove the measurement-device independency of the protocol according to the calculation result. In addition, the proposed analysis method can be extended to other quantum cryptographic protocols besides continuous-variable quantum homomorphic signature.

  18. Using principal component analysis to understand the variability of PDS 456

    Science.gov (United States)

    Parker, M. L.; Reeves, J. N.; Matzeu, G. A.; Buisson, D. J. K.; Fabian, A. C.

    2018-02-01

    We present a spectral-variability analysis of the low-redshift quasar PDS 456 using principal component analysis. In the XMM-Newton data, we find a strong peak in the first principal component at the energy of the Fe absorption line from the highly blueshifted outflow. This indicates that the absorption feature is more variable than the continuum, and that it is responding to the continuum. We find qualitatively different behaviour in the Suzaku data, which is dominated by changes in the column density of neutral absorption. In this case, we find no evidence of the absorption produced by the highly ionized gas being correlated with this variability. Additionally, we perform simulations of the source variability, and demonstrate that PCA can trivially distinguish between outflow variability correlated, anticorrelated and un-correlated with the continuum flux. Here, the observed anticorrelation between the absorption line equivalent width and the continuum flux may be due to the ionization of the wind responding to the continuum. Finally, we compare our results with those found in the narrow-line Seyfert 1 IRAS 13224-3809. We find that the Fe K UFO feature is sharper and more prominent in PDS 456, but that it lacks the lower energy features from lighter elements found in IRAS 13224-3809, presumably due to differences in ionization.

  19. Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

    Science.gov (United States)

    Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

    2017-09-01

    In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Robust best linear estimation for regression analysis using surrogate and instrumental variables.

    Science.gov (United States)

    Wang, C Y

    2012-04-01

    We investigate methods for regression analysis when covariates are measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies the classical measurement error model, but it may not have repeated measurements. In addition to the surrogate variables that are available among the subjects in the calibration sample, we assume that there is an instrumental variable (IV) that is available for all study subjects. An IV is correlated with the unobserved true exposure variable and hence can be useful in the estimation of the regression coefficients. We propose a robust best linear estimator that uses all the available data, which is the most efficient among a class of consistent estimators. The proposed estimator is shown to be consistent and asymptotically normal under very weak distributional assumptions. For Poisson or linear regression, the proposed estimator is consistent even if the measurement error from the surrogate or IV is heteroscedastic. Finite-sample performance of the proposed estimator is examined and compared with other estimators via intensive simulation studies. The proposed method and other methods are applied to a bladder cancer case-control study.

  1. ANALYSIS OF RISK FACTORS ECTOPIC PREGNANCY

    Directory of Open Access Journals (Sweden)

    Budi Santoso

    2017-04-01

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

  2. Do climate variables and human density affect Achatina fulica (Bowditch) (Gastropoda: Pulmonata) shell length, total weight and condition factor?

    Science.gov (United States)

    Albuquerque, F S; Peso-Aguiar, M C; Assunção-Albuquerque, M J T; Gálvez, L

    2009-08-01

    The length-weight relationship and condition factor have been broadly investigated in snails to obtain the index of physical condition of populations and evaluate habitat quality. Herein, our goal was to describe the best predictors that explain Achatina fulica biometrical parameters and well being in a recently introduced population. From November 2001 to November 2002, monthly snail samples were collected in Lauro de Freitas City, Bahia, Brazil. Shell length and total weight were measured in the laboratory and the potential curve and condition factor were calculated. Five environmental variables were considered: temperature range, mean temperature, humidity, precipitation and human density. Multiple regressions were used to generate models including multiple predictors, via model selection approach, and then ranked with AIC criteria. Partial regressions were used to obtain the separated coefficients of determination of climate and human density models. A total of 1.460 individuals were collected, presenting a shell length range between 4.8 to 102.5 mm (mean: 42.18 mm). The relationship between total length and total weight revealed that Achatina fulica presented a negative allometric growth. Simple regression indicated that humidity has a significant influence on A. fulica total length and weight. Temperature range was the main variable that influenced the condition factor. Multiple regressions showed that climatic and human variables explain a small proportion of the variance in shell length and total weight, but may explain up to 55.7% of the condition factor variance. Consequently, we believe that the well being and biometric parameters of A. fulica can be influenced by climatic and human density factors.

  3. Do climate variables and human density affect Achatina fulica (Bowditch (Gastropoda: Pulmonata shell length, total weight and condition factor?

    Directory of Open Access Journals (Sweden)

    FS. Albuquerque

    Full Text Available The length-weight relationship and condition factor have been broadly investigated in snails to obtain the index of physical condition of populations and evaluate habitat quality. Herein, our goal was to describe the best predictors that explain Achatina fulica biometrical parameters and well being in a recently introduced population. From November 2001 to November 2002, monthly snail samples were collected in Lauro de Freitas City, Bahia, Brazil. Shell length and total weight were measured in the laboratory and the potential curve and condition factor were calculated. Five environmental variables were considered: temperature range, mean temperature, humidity, precipitation and human density. Multiple regressions were used to generate models including multiple predictors, via model selection approach, and then ranked with AIC criteria. Partial regressions were used to obtain the separated coefficients of determination of climate and human density models. A total of 1.460 individuals were collected, presenting a shell length range between 4.8 to 102.5 mm (mean: 42.18 mm. The relationship between total length and total weight revealed that Achatina fulica presented a negative allometric growth. Simple regression indicated that humidity has a significant influence on A. fulica total length and weight. Temperature range was the main variable that influenced the condition factor. Multiple regressions showed that climatic and human variables explain a small proportion of the variance in shell length and total weight, but may explain up to 55.7% of the condition factor variance. Consequently, we believe that the well being and biometric parameters of A. fulica can be influenced by climatic and human density factors.

  4. Three-Factor Market-Timing Models with Fama and French's Spread Variables

    Directory of Open Access Journals (Sweden)

    Joanna Olbryś

    2010-01-01

    Full Text Available The traditional performance measurement literature has attempted to distinguish security selection, or stock-picking ability, from market-timing, or the ability to predict overall market returns. However, the literature finds that it is not easy to separate ability into such dichotomous categories. Some researchers have developed models that allow the decomposition of manager performance into market-timing and selectivity skills. The main goal of this paper is to present modified versions of classical market-timing models with Fama and French’s spread variables SMB and HML, in the case of Polish equity mutual funds. (original abstract

  5. Housing price forecastability: A factor analysis

    DEFF Research Database (Denmark)

    Møller, Stig Vinther; Bork, Lasse

    2017-01-01

    We examine U.S. housing price forecastability using principal component analysis (PCA), partial least squares (PLS), and sparse PLS (SPLS). We incorporate information from a large panel of 128 economic time series and show that macroeconomic fundamentals have strong predictive power for future...... movements in housing prices. We find that (S)PLS models systematically dominate PCA models. (S)PLS models also generate significant out-of-sample predictive power over and above the predictive power contained by the price-rent ratio, autoregressive benchmarks, and regression models based on small datasets....

  6. Analysis of Parking Reliability Guidance of Urban Parking Variable Message Sign System

    OpenAIRE

    Zhenyu Mei; Ye Tian; Dongping Li

    2012-01-01

    Operators of parking guidance and information systems (PGIS) often encounter difficulty in determining when and how to provide reliable car park availability information to drivers. Reliability has become a key factor to ensure the benefits of urban PGIS. The present paper is the first to define the guiding parking reliability of urban parking variable message signs (VMSs). By analyzing the parking choice under guiding and optional parking lots, a guiding parking reliability model was constru...

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

    Science.gov (United States)

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

    2018-04-01

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

  8. Adaptability and variability of the cell functions to the environmental factors

    Energy Technology Data Exchange (ETDEWEB)

    Kikuchi, Tadatoshi [Kyoto Univ., Kumatori, Osaka (Japan). Research Reactor Inst.

    1995-02-01

    Adaptive phenomenon of the cells to the environmental factors is one of the most important functions of cells. In the initial research program, yeast, Saccharomyces cerevisiae, as model species of eukaryote was selected to use for the experiments and copper sulfate was adopted as one of the ideal environmental factors, and then adaptation mechanisms of yeast cells in the environment surrounded by copper ions were analyzed metabolically and morphologically. Furthermore, in the relationships between environmental factors and the cells, the researches performed were as follows: (1) Induced mutation in the extranuclear-inheritable system: Mutagenic effect of ethidium bromide on mitochondria and plastids. (2) Induction of gene expression by light exposure in the early development of chloroplast in Chlamydomonas reinhardi. (3) Some features of RNA and protein syntheses in thermophilic alga Cyanidium caldarium. (4) Satellite DNA of Ochromonas danica. (5) Analyses of cell functions using various kinds of radiations. (6) Novel methionine requirement of radiation resistant bacterium, Deinococcus radiodurans. (author).

  9. Vulnerability analysis of power systems considering uncertainty in variables using fuzzy logic type 2

    Directory of Open Access Journals (Sweden)

    Julian Alexander Melo Rodriguez

    2016-09-01

    Full Text Available Objectives: This paper presents a new methodology for analyzing the vulnerability of power systems including uncertainty in some variables. Method: The methodology optimizes a Bi-level mixed integer model. Costs associated with power generation and load shedding are minimized at the lowest level whereas at the higher level the damage in the power system, represented by the load shedding, is maximized. Fuzzy logic type 2 is used to model the uncertainty in both linguistic variables and numeric variables. The linguistic variables model the factors of the geographical environment while numeric variables model parameters of the power system. Results: The methodology was validated by using a modified IEEE RTS-96 test system. The results show that by including particularities of the geographical environment different vulnerabilities are detected in the power system. Moreover, it was possible to identify that the most critical component is the line 112-123 because it had 16 attacks in 18 scenarios, and that the maximum load shedding of the system varies from 145 to 1258 MW. Conclusions: This methodology can be used to coordinate and refine protection plans of the power system infrastructure. Funding: EMC-UN research group.

  10. Selection of variables for neural network analysis. Comparisons of several methods with high energy physics data

    International Nuclear Information System (INIS)

    Proriol, J.

    1994-01-01

    Five different methods are compared for selecting the most important variables with a view to classifying high energy physics events with neural networks. The different methods are: the F-test, Principal Component Analysis (PCA), a decision tree method: CART, weight evaluation, and Optimal Cell Damage (OCD). The neural networks use the variables selected with the different methods. We compare the percentages of events properly classified by each neural network. The learning set and the test set are the same for all the neural networks. (author)

  11. VALUE OF HEART RATE VARIABILITY ANALYSIS IN DIAGNOSTICS OF THE EMOTIONAL STATE

    Directory of Open Access Journals (Sweden)

    І. Chaykovskyi

    2012-11-01

    Full Text Available The is presented the development of method for evaluation of emotional state of man, what suitable for use at the workplace based on analysis of heart rate (HR variability. 28 healthy volunteers were examined. 3 audiovisual clips were consistently presented on the display of the personal computer for each of them. One clip contained information originating the positive emotions, the second one – negative emotions, the third one – neutral. All possible pairs of the emotional states were analysed with help of one- and multi-dimensional linear discriminant analysis based on HR variability. Showing the emotional video-clips (of both signs causes reliable slowing of HR frequency and also some decreasing of HR variability. In addition, negative emotions cause regularizing and simplification of structural organization of heart rhythm. Accuracy of discrimination for pair “emotional – neutral” video clips was 98 %, for pair “rest – neutral” was 74 %, for pair “positive – negative” was 91 %. Analysis of HR variability enables to determine the emotional state of observed person at the workplace with high reliability.

  12. Rose bush leaf and internode expansion dynamics: analysis and development of a model capturing interplant variability

    Directory of Open Access Journals (Sweden)

    Sabine eDemotes-Mainard

    2013-10-01

    Full Text Available Bush rose architecture, among other factors, such as plant health, determines plant visual quality. The commercial product is the individual plant and interplant variability may be high within a crop. Thus, both mean plant architecture and interplant variability should be studied. Expansion is an important feature of architecture, but it has been little studied at the level of individual organs in bush roses. We investigated the expansion kinetics of primary shoot organs, to develop a model reproducing the organ expansion of real crops from non destructive input variables. We took interplant variability in expansion kinetics and the model’s ability to simulate this variability into account. Changes in leaflet and internode dimensions over thermal time were recorded for primary shoot expansion, on 83 plants from three crops grown in different climatic conditions and densities. An empirical model was developed, to reproduce organ expansion kinetics for individual plants of a real crop of bush rose primary shoots. Leaflet or internode length was simulated as a logistic function of thermal time. The model was evaluated by cross-validation. We found that differences in leaflet or internode expansion kinetics between phytomer positions and between plants at a given phytomer position were due mostly to large differences in time of organ expansion and expansion rate, rather than differences in expansion duration. Thus, in the model, the parameters linked to expansion duration were predicted by values common to all plants, whereas variability in final size and organ expansion time was captured by input data. The model accurately simulated leaflet and internode expansion for individual plants (RMSEP = 7.3% and 10.2% of final length, respectively. Thus, this study defines the measurements required to simulate expansion and provides the first model simulating organ expansion in rosebush to capture interplant variability.

  13. Stochastic Analysis of the Efficiency of a Wireless Power Transfer System Subject to Antenna Variability and Position Uncertainties.

    Science.gov (United States)

    Rossi, Marco; Stockman, Gert-Jan; Rogier, Hendrik; Vande Ginste, Dries

    2016-07-19

    The efficiency of a wireless power transfer (WPT) system in the radiative near-field is inevitably affected by the variability in the design parameters of the deployed antennas and by uncertainties in their mutual position. Therefore, we propose a stochastic analysis that combines the generalized polynomial chaos (gPC) theory with an efficient model for the interaction between devices in the radiative near-field. This framework enables us to investigate the impact of random effects on the power transfer efficiency (PTE) of a WPT system. More specifically, the WPT system under study consists of a transmitting horn antenna and a receiving textile antenna operating in the Industrial, Scientific and Medical (ISM) band at 2.45 GHz. First, we model the impact of the textile antenna's variability on the WPT system. Next, we include the position uncertainties of the antennas in the analysis in order to quantify the overall variations in the PTE. The analysis is carried out by means of polynomial-chaos-based macromodels, whereas a Monte Carlo simulation validates the complete technique. It is shown that the proposed approach is very accurate, more flexible and more efficient than a straightforward Monte Carlo analysis, with demonstrated speedup factors up to 2500.

  14. Stochastic Analysis of the Efficiency of a Wireless Power Transfer System Subject to Antenna Variability and Position Uncertainties

    Directory of Open Access Journals (Sweden)

    Marco Rossi

    2016-07-01

    Full Text Available The efficiency of a wireless power transfer (WPT system in the radiative near-field is inevitably affected by the variability in the design parameters of the deployed antennas and by uncertainties in their mutual position. Therefore, we propose a stochastic analysis that combines the generalized polynomial chaos (gPC theory with an efficient model for the interaction between devices in the radiative near-field. This framework enables us to investigate the impact of random effects on the power transfer efficiency (PTE of a WPT system. More specifically, the WPT system under study consists of a transmitting horn antenna and a receiving textile antenna operating in the Industrial, Scientific and Medical (ISM band at 2.45 GHz. First, we model the impact of the textile antenna’s variability on the WPT system. Next, we include the position uncertainties of the antennas in the analysis in order to quantify the overall variations in the PTE. The analysis is carried out by means of polynomial-chaos-based macromodels, whereas a Monte Carlo simulation validates the complete technique. It is shown that the proposed approach is very accurate, more flexible and more efficient than a straightforward Monte Carlo analysis, with demonstrated speedup factors up to 2500.

  15. Stochastic Analysis of the Efficiency of a Wireless Power Transfer System Subject to Antenna Variability and Position Uncertainties

    Science.gov (United States)

    Rossi, Marco; Stockman, Gert-Jan; Rogier, Hendrik; Vande Ginste, Dries

    2016-01-01

    The efficiency of a wireless power transfer (WPT) system in the radiative near-field is inevitably affected by the variability in the design parameters of the deployed antennas and by uncertainties in their mutual position. Therefore, we propose a stochastic analysis that combines the generalized polynomial chaos (gPC) theory with an efficient model for the interaction between devices in the radiative near-field. This framework enables us to investigate the impact of random effects on the power transfer efficiency (PTE) of a WPT system. More specifically, the WPT system under study consists of a transmitting horn antenna and a receiving textile antenna operating in the Industrial, Scientific and Medical (ISM) band at 2.45 GHz. First, we model the impact of the textile antenna’s variability on the WPT system. Next, we include the position uncertainties of the antennas in the analysis in order to quantify the overall variations in the PTE. The analysis is carried out by means of polynomial-chaos-based macromodels, whereas a Monte Carlo simulation validates the complete technique. It is shown that the proposed approach is very accurate, more flexible and more efficient than a straightforward Monte Carlo analysis, with demonstrated speedup factors up to 2500. PMID:27447632

  16. Data analysis as a source of variability of the HLA-peptide multimer assay

    DEFF Research Database (Denmark)

    Gouttefangeas, Cécile; Chan, Cliburn; Attig, Sebastian

    2015-01-01

    by laboratories performing ex vivo T cell immune monitoring. In particular, analysis currently relies on a manual, step-by-step strategy employing serial gating decisions based on visual inspection of one- or two-dimensional plots. It is therefore operator dependent and subjective. In the context of continuing......Multiparameter flow cytometry is an indispensable method for assessing antigen-specific T cells in basic research and cancer immunotherapy. Proficiency panels have shown that cell sample processing, test protocols and data analysis may all contribute to the variability of the results obtained...... efforts to support inter-laboratory T cell assay harmonization, the CIMT Immunoguiding Program organized its third proficiency panel dedicated to the detection of antigen-specific CD8(+) T cells by HLA-peptide multimer staining. We first assessed the contribution of manual data analysis to the variability...

  17. High interpatient variability of raltegravir CSF concentrations in HIV-positive patients: a pharmacogenetic analysis.

    Science.gov (United States)

    Calcagno, Andrea; Cusato, Jessica; Simiele, Marco; Motta, Ilaria; Audagnotto, Sabrina; Bracchi, Margherita; D'Avolio, Antonio; Di Perri, Giovanni; Bonora, Stefano

    2014-01-01

    To analyse the determinants of raltegravir CSF penetration, including the pharmacogenetics of drug transporters located at the blood-brain barrier or blood-CSF barrier. Plasma and CSF raltegravir concentrations were determined by a validated HPLC coupled with mass spectrometry method in adults on raltegravir-based combination antiretroviral therapy undergoing a lumbar puncture. Single nucleotide polymorphisms in the genes encoding drugs transporters (ABCB1 3435, SLCO1A2, ABCC2 and SLC22A6) and the gene encoding hepatocyte nuclear factor 4 α (HNF4α) were determined by real-time PCR. In 41 patients (73.2% male, 95.1% Caucasians), the median raltegravir plasma and CSF concentrations were 165 ng/mL (83-552) and 31 ng/mL (21-56), respectively. CSF-to-plasma ratios (CPRs) ranged from 0.005 to 1.33 (median 0.20, IQR 0.04-0.36). Raltegravir trough CSF concentrations (n = 35) correlated with raltegravir plasma levels (ρ = 0.395, P = 0.019); CPRs were higher in patients with blood-brain barrier damage (0.47 versus 0.18, P = 0.02). HNF4α 613 CG genotype carriers had lower trough CSF concentrations (20 versus 37 ng/mL, P = 0.03) and CPRs (0.12 versus 0.27, P = 0.02). Following multivariate linear regression analysis, the CSF-to-serum albumin ratio was the only independent predictor of raltegravir penetration into the CSF. Raltegravir penetration into the CSF shows a large interpatient variability, although CSF concentrations were above the wild-type IC50 in all patients (and above IC95 in 28.6%). In this cohort, blood-brain barrier permeability is the only independent predictor of raltegravir CPR. The impact of single nucleotide polymorphisms in selected genes on raltegravir penetration warrants further studies.

  18. Achieving success in intervention studies: an analysis of variable staff engagement across three midwifery settings.

    Science.gov (United States)

    Henderson, Amanda; Schoonbeek, Sue; Ossenberg, Christine; Caddick, Alison; Wing, Diane; Capell, Lorna; Gould, Karen

    2014-06-01

    To critically analyse the success of staff's behaviour changes in the practice setting. Facilitators were employed to initiate and facilitate a four-step process (optimism, overcoming obstacles, oversight and reinforcing outcomes) that fostered development of behaviours consistent with learning in everyday practice. Many studies seek to engage staff in workplace behaviour improvement. The success of such studies is highly variable. Little is known about the work of the facilitator in ensuring success. Understanding the contextual factors that contribute to effective facilitation of workplace improvement is essential to ensure best use of resources. Mixed methods Facilitators employed a four-step process - optimism, overcoming obstacles, oversight and reinforcing outcomes - to stage behaviour change implementation. The analysis of staff engagement in behaviour changes was assessed through weekly observation of workplaces, informal discussions with staff and facilitator diaries. The impact of behaviour change was informed through pre- and postsurveys on staff's perception across three midwifery sites. Surveys measured (1) midwives' perception of support for their role in facilitating learning (Support Instrument for Nurses Facilitating the Learning of Others) and (2) development of a learning culture in midwifery practice settings (Clinical Learning Organisational Culture Survey). Midwives across three sites completed the presurvey (n = 216) and postsurvey (n = 90). Impact varied according to the degree that facilitators were able to progress teams through four stages necessary for change (OOORO). Statistically significant results were apparent in two subscales important for supporting staff, namely teamwork and acknowledgement; in the two areas, facilitators worked through 'obstacles' and coached staff in performing the desired behaviours and rewarded them for their success. Elements of the learning culture also statistically improved in one site. Findings suggest

  19. Principal Component Analysis to Explore Climatic Variability and Dengue Outbreak in Lahore

    Directory of Open Access Journals (Sweden)

    Syed Afrozuddin Ahmed

    2014-08-01

    Full Text Available Normal 0 false false false EN-US X-NONE X-NONE Various studies have reported that global warming causes unstable climate and many serious impact to physical environment and public health. The increasing incidence of dengue incidence is now a priority health issue and become a health burden of Pakistan.  In this study it has been investigated that spatial pattern of environment causes the emergence or increasing rate of dengue fever incidence that effects the population and its health. Principal component analysis is performed for the purpose of finding if there is/are any general environmental factor/structure which could be affected in the emergence of dengue fever cases in Pakistani climate. Principal component is applied to find structure in data for all four periods i.e. 1980 to 2012, 1980 to 1995 and 1996 to 2012.  The first three PCs for the period (1980-2012, 1980-1994, 1995-2012 are almost the same and it represent hot and windy weather. The PC1s of all dengue periods are different to each other. PC2 for all period are same and it is wetness in weather. PC3s are different and it is the combination of wetness and windy weather. PC4s for all period show humid but no rain in weather. For climatic variable only minimum temperature and maximum temperature are significantly correlated with daily dengue cases.  PC1, PC3 and PC4 are highly significantly correlated with daily dengue cases 

  20. Factoring handedness data: I. Item analysis.

    Science.gov (United States)

    Messinger, H B; Messinger, M I

    1995-12-01

    Recently in this journal Peters and Murphy challenged the validity of factor analyses done on bimodal handedness data, suggesting instead that right- and left-handers be studied separately. But bimodality may be avoidable if attention is paid to Oldfield's questionnaire format and instructions for the subjects. Two characteristics appear crucial: a two-column LEFT-RIGHT format for the body of the instrument and what we call Oldfield's Admonition: not to indicate strong preference for handedness item, such as write, unless "... the preference is so strong that you would never try to use the other hand unless absolutely forced to...". Attaining unimodality of an item distribution would seem to overcome the objections of Peters and Murphy. In a 1984 survey in Boston we used Oldfield's ten-item questionnaire exactly as published. This produced unimodal item distributions. With reflection of the five-point item scale and a logarithmic transformation, we achieved a degree of normalization for the items. Two surveys elsewhere based on Oldfield's 20-item list but with changes in the questionnaire format and the instructions, yielded markedly different item distributions with peaks at each extreme and sometimes in the middle as well.

  1. Young Mothers' Play with Their Toddlers: Individual Variability as a Function of Psychosocial Factors

    Science.gov (United States)

    Driscoll, Joan Riley; Easterbrooks, M. Ann

    2007-01-01

    There is no one style of parenting which characterizes young mothers as a group. In addition, life circumstances play an important role in shaping maternal behaviour. The aim of this study was to identify patterns of maternal play behaviour and contextual (social and personal) factors associated with these different patterns. In this study, 107…

  2. Fishery discards: Factors affecting their variability within a demersal trawl fishery

    DEFF Research Database (Denmark)

    Feekings, Jordan P.; Bartolino, Valerio; Madsen, Niels

    2012-01-01

    the factors that influence discarding within the Danish Kattegat demersal fleet over the period 1997 to 2008. Generalised additive models were used to assess how discards of the 3 main target species, Norway lobster, cod and plaice, and their subcomponents (under and over minimum landings size) are influenced...

  3. Jordanian Mothers' Perceptions of Their Children's Social Competence: An Examination of Family Factors and Demographic Variables

    Science.gov (United States)

    Abu Taleb, Tagreed Fathi; AlZoubi, Rifa Rafe

    2015-01-01

    Children's social competence is an area of research that receives minimal attention from Jordanian researchers. It is important to investigate this area of development so as to provide parents with information about the nature of social competence and possible factors affecting its development. This research study examined Jordanian mothers'…

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

    International Nuclear Information System (INIS)

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

    2002-01-01

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

  5. Design study and performance analysis of a high-speed multistage variable-geometry fan for a variable cycle engine

    Science.gov (United States)

    Sullivan, T. J.; Parker, D. E.

    1979-01-01

    A design technology study was performed to identify a high speed, multistage, variable geometry fan configuration capable of achieving wide flow modulation with near optimum efficiency at the important operating condition. A parametric screening study of the front and rear block fans was conducted in which the influence of major fan design features on weight and efficiency was determined. Key design parameters were varied systematically to determine the fan configuration most suited for a double bypass, variable cycle engine. Two and three stage fans were considered for the front block. A single stage, core driven fan was studied for the rear block. Variable geometry concepts were evaluated to provide near optimum off design performance. A detailed aerodynamic design and a preliminary mechanical design were carried out for the selected fan configuration. Performance predictions were made for the front and rear block fans.

  6. Geostatistical Analysis of Mesoscale Spatial Variability and Error in SeaWiFS and MODIS/Aqua Global Ocean Color Data

    Science.gov (United States)

    Glover, David M.; Doney, Scott C.; Oestreich, William K.; Tullo, Alisdair W.

    2018-01-01

    Mesoscale (10-300 km, weeks to months) physical variability strongly modulates the structure and dynamics of planktonic marine ecosystems via both turbulent advection and environmental impacts upon biological rates. Using structure function analysis (geostatistics), we quantify the mesoscale biological signals within global 13 year SeaWiFS (1998-2010) and 8 year MODIS/Aqua (2003-2010) chlorophyll a ocean color data (Level-3, 9 km resolution). We present geographical distributions, seasonality, and interannual variability of key geostatistical parameters: unresolved variability or noise, resolved variability, and spatial range. Resolved variability is nearly identical for both instruments, indicating that geostatistical techniques isolate a robust measure of biophysical mesoscale variability largely independent of measurement platform. In contrast, unresolved variability in MODIS/Aqua is substantially lower than in SeaWiFS, especially in oligotrophic waters where previous analysis identified a problem for the SeaWiFS instrument likely due to sensor noise characteristics. Both records exhibit a statistically significant relationship between resolved mesoscale variability and the low-pass filtered chlorophyll field horizontal gradient magnitude, consistent with physical stirring acting on large-scale gradient as an important factor supporting observed mesoscale variability. Comparable horizontal length scales for variability are found from tracer-based scaling arguments and geostatistical decorrelation. Regional variations between these length scales may reflect scale dependence of biological mechanisms that also create variability directly at the mesoscale, for example, enhanced net phytoplankton growth in coastal and frontal upwelling and convective mixing regions. Global estimates of mesoscale biophysical variability provide an improved basis for evaluating higher resolution, coupled ecosystem-ocean general circulation models, and data assimilation.

  7. Variable selection in the explorative analysis of several data blocks in metabolomics

    DEFF Research Database (Denmark)

    Karaman, İbrahim; Nørskov, Natalja; Yde, Christian Clement

    highly correlated data sets in one integrated approach. Due to the high number of variables in data sets from metabolomics (both raw data and after peak picking) the selection of important variables in an explorative analysis is difficult, especially when different data sets of metabolomics data need...... to be related. Tools for the handling of mental overflow minimising false discovery rates both by using statistical and biological validation in an integrative approach are needed. In this paper different strategies for variable selection were considered with respect to false discovery and the possibility...... for biological validation. The data set used in this study is metabolomics data from an animal intervention study. The aim of the metabolomics study was to investigate the metabolic profile in pigs fed various cereal fractions with special attention to the metabolism of lignans using NMR and LC-MS based...

  8. Read margin analysis of crossbar arrays using the cell-variability-aware simulation method

    Science.gov (United States)

    Sun, Wookyung; Choi, Sujin; Shin, Hyungsoon

    2018-02-01

    This paper proposes a new concept of read margin analysis of crossbar arrays using cell-variability-aware simulation. The size of the crossbar array should be considered to predict the read margin characteristic of the crossbar array because the read margin depends on the number of word lines and bit lines. However, an excessively high-CPU time is required to simulate large arrays using a commercial circuit simulator. A variability-aware MATLAB simulator that considers independent variability sources is developed to analyze the characteristics of the read margin according to the array size. The developed MATLAB simulator provides an effective method for reducing the simulation time while maintaining the accuracy of the read margin estimation in the crossbar array. The simulation is also highly efficient in analyzing the characteristic of the crossbar memory array considering the statistical variations in the cell characteristics.

  9. The interface between research on individual difference variables and teaching practice: The case of cognitive factors and personality

    Directory of Open Access Journals (Sweden)

    Adriana Biedroń

    2016-09-01

    Full Text Available While a substantial body of empirical evidence has been accrued about the role of individual differences in second language acquisition, relatively little is still known about how factors of this kind can mediate the effects of instructional practices as well as how empirically-derived insights can inform foreign language pedagogy, both with respect to shaping certain variables and adjusting instruction to individual learner profiles. The present paper is an attempt to shed light on the interface between research on individual difference factors and teaching practice, focusing upon variables which do not easily lend themselves to external manipulation, namely intelligence, foreign language aptitude, working memory and personality, with the role of the last of these in language learning being admittedly the least obvious. In each case, the main research findings will briefly be outlined, their potential for informing instruction will be considered, and, in the final part, the caveats concerning practical applications of research on the variables in question will be spelled out.

  10. Natural variability of biochemical biomarkers in the macro-zoobenthos: Dependence on life stage and environmental factors.

    Science.gov (United States)

    Scarduelli, Lucia; Giacchini, Roberto; Parenti, Paolo; Migliorati, Sonia; Di Brisco, Agnese Maria; Vighi, Marco

    2017-11-01

    Biomarkers are widely used in ecotoxicology as indicators of exposure to toxicants. However, their ability to provide ecologically relevant information remains controversial. One of the major problems is understanding whether the measured responses are determined by stress factors or lie within the natural variability range. In a previous work, the natural variability of enzymatic levels in invertebrates sampled in pristine rivers was proven to be relevant across both space and time. In the present study, the experimental design was improved by considering different life stages of the selected taxa and by measuring more environmental parameters. The experimental design considered sampling sites in 2 different rivers, 8 sampling dates covering the whole seasonal cycle, 4 species from 3 different taxonomic groups (Plecoptera, Perla grandis; Ephemeroptera, Baetis alpinus and Epeorus alpicula; Tricoptera, Hydropsyche pellucidula), different life stages for each species, and 4 enzymes (acetylcholinesterase, glutathione S-transferase, alkaline phosphatase, and catalase). Biomarker levels were related to environmental (physicochemical) parameters to verify any kind of dependence. Data were statistically elaborated using hierarchical multilevel Bayesian models. Natural variability was found to be relevant across both space and time. The results of the present study proved that care should be paid when interpreting biomarker results. Further research is needed to better understand the dependence of the natural variability on environmental parameters. Environ Toxicol Chem 2017;36:3158-3167. © 2017 SETAC. © 2017 SETAC.

  11. 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.

  12. Why do lifespan variability trends for the young and old diverge? A perturbation analysis

    Directory of Open Access Journals (Sweden)

    Michal Engelman

    2014-05-01

    Full Text Available Background: Variation in lifespan has followed strikingly different trends for the young and old: while overall lifespan variability has decreased as life expectancy at birth has risen, the variability conditional on survival to older ages has increased. These diverging trends reflect changes in the underlying demographic parameters determining age-specific mortality. Objective: We ask why the variation in the adult ages at death has followed a different trend than the variation at younger ages, and aim to explain the diverging patterns in terms of historical changes in the age schedule of mortality. Methods: Using simulations, we show that the empirical trends in lifespan variation are well characterized using the Siler model, which describes the mortality hazard across the full lifespan using functions representing early-life, later-life, and background mortality. We then obtain maximum likelihood estimates of the Siler parameters over time. Finally, we express lifespan variation in terms of a Markov chain model, and apply matrix calculus perturbation analysis to compute the sensitivity of age-specific lifespan variance trends to the changing Siler model parameters. Results: Our analysis produces a detailed quantification of the impact of changing demographic parameters on the pattern of lifespan variability at all ages, highlighting the impact of declining childhood mortality on the reduction of lifespan variability and the impact of improved survival in adulthood on the rising variability of lifespans at older ages. Conclusions: These findings provide insight into the dynamic relationship between the age pattern of survival improvements and time trends in lifespan variability.

  13. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    Directory of Open Access Journals (Sweden)

    Reinders Marcel JT

    2009-11-01

    Full Text Available Abstract Background Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical

  14. A comprehensive analysis of coherent rainfall patterns in China and potential drivers. Part I: Interannual variability

    Science.gov (United States)

    Stephan, Claudia Christine; Klingaman, Nicholas Pappas; Vidale, Pier Luigi; Turner, Andrew George; Demory, Marie-Estelle; Guo, Liang

    2018-06-01

    Interannual rainfall variability in China affects agriculture, infrastructure and water resource management. To improve its understanding and prediction, many studies have associated precipitation variability with particular causes for specific seasons and regions. Here, a consistent and objective method, Empirical Orthogonal Teleconnection (EOT) analysis, is applied to 1951-2007 high-resolution precipitation observations over China in all seasons. Instead of maximizing the explained space-time variance, the method identifies regions in China that best explain the temporal variability in domain-averaged rainfall. The EOT method is validated by the reproduction of known relationships to the El Niño Southern Oscillation (ENSO): high positive correlations with ENSO are found in eastern China in winter, along the Yangtze River in summer, and in southeast China during spring. New findings include that wintertime rainfall variability along the southeast coast is associated with anomalous convection over the tropical eastern Atlantic and communicated to China through a zonal wavenumber-three Rossby wave. Furthermore, spring rainfall variability in the Yangtze valley is related to upper-tropospheric midlatitude perturbations that are part of a Rossby wave pattern with its origin in the North Atlantic. A circumglobal wave pattern in the northern hemisphere is also associated with autumn precipitation variability in eastern areas. The analysis is objective, comprehensive, and produces timeseries that are tied to specific locations in China. This facilitates the interpretation of associated dynamical processes, is useful for understanding the regional hydrological cycle, and allows the results to serve as a benchmark for assessing general circulation models.

  15. Simultaneous analysis of climatic trends in multiple variables: an example of application of multivariate statistical methods

    Czech Academy of Sciences Publication Activity Database

    Huth, Radan; Pokorná, Lucie

    2005-01-01

    Roč. 25, - (2005), s. 469-484 ISSN 0899-8418 R&D Projects: GA AV ČR(CZ) IAA3017301 Institutional research plan: CEZ:AV0Z30420517 Keywords : climatic trends * trend consistency * principal component analysis * cluster analysis * Czech Republic Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.622, year: 2005

  16. 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).

  17. Study and evaluation of the Siemens virtual wedge factor: dosimetric monitor system and variable field effects

    Energy Technology Data Exchange (ETDEWEB)

    Sendon Rio, J R Sendon; Martinez, C Otero; GarcIa, M Sanchez; Busto, R Lobato; Vega, V Luna; Sueiro, J Mosquera; Camean, M Pombar [Servizo de Radiofisica e Proteccion Radioloxica, Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Santiago de Compostela (Spain)], E-mail: jose.ramon.sendon.del.rio@sergas.es

    2008-03-07

    In the year 1997 Siemens introduced the virtual wedge in its accelerators. The idea was that a dose profile similar to that of a physical wedge can be obtained by moving one of the accelerator jaws at a constant speed while the dose rate is changing. This work explores the observed behaviour of virtual wedge factors. A model is suggested which takes into account that at any point in time, when the jaw moves, the dose at a point of interest in the phantom is not only due to the direct beam. It also depends on the scattered radiation in the phantom, the head scatter and the behaviour of the monitoring system of the accelerator. Measurements are performed in a Siemens Primus accelerator and compared to the model predictions. It is shown that the model agrees reasonably well with measurements spanning a wide range of conditions. A strong dependence of virtual wedge factors on the dosimetric board has been confirmed and an explanation has been given on how the balance between different contributions is responsible for virtual wedge factors values.

  18. Aggressive and unsportsmanlike behaviours in competitive sports: an analysis of related personal and environmental variables

    Directory of Open Access Journals (Sweden)

    Antonia Pelegrín

    2013-10-01

    Full Text Available This paper gives an analysis of personal and environmental variables related to aggressive and unsportsmanlike behaviours in a sample of Spanish sports competitors. We aim to: 1 ascertain how personality and expression variables relate to trait anger control and unsportsmanlike behaviors, in relation to men and women, age groups and type of sport, 2 identify and analyze the most maladjusted and the most adjusted profiles in a sample of sportsmen and women; 3 identify personality variables as predictors of aggressive and unsportsmanlike behaviours. Differences in gender, age and type of sport were appreciated in personality variables and in aggressive and unsportsmanlike behaviours. Men have better emotional adjustment (more behaviours of emotional stability, better self-esteem, self-confidence and leadership, and have worse social adjustment (fewer behaviours of tolerance, social skills and responsibility; more aggressive and unsportsmanlike behaviours. Women have better social adjustment (more behaviours of tolerance, understanding, adaptation, responsibility, discipline and sociability, and have worse emotional adjustment (greater anxiety. More aggressive and unsportsmanlike behaviours and greater emotional maladjustment were found in the youngest sportsmen and women. Aggressive and unsportsmanlike behaviours were more frequent in team sports. This study highlights personality variables as predictors of aggressive and unsportsmanlike behaviours.

  19. Correlation Analysis of Water Demand and Predictive Variables for Short-Term Forecasting Models

    Directory of Open Access Journals (Sweden)

    B. M. Brentan

    2017-01-01

    Full Text Available Operational and economic aspects of water distribution make water demand forecasting paramount for water distribution systems (WDSs management. However, water demand introduces high levels of uncertainty in WDS hydraulic models. As a result, there is growing interest in developing accurate methodologies for water demand forecasting. Several mathematical models can serve this purpose. One crucial aspect is the use of suitable predictive variables. The most used predictive variables involve weather and social aspects. To improve the interrelation knowledge between water demand and various predictive variables, this study applies three algorithms, namely, classical Principal Component Analysis (PCA and machine learning powerful algorithms such as Self-Organizing Maps (SOMs and Random Forest (RF. We show that these last algorithms help corroborate the results found by PCA, while they are able to unveil hidden features for PCA, due to their ability to cope with nonlinearities. This paper presents a correlation study of three district metered areas (DMAs from Franca, a Brazilian city, exploring weather and social variables to improve the knowledge of residential demand for water. For the three DMAs, temperature, relative humidity, and hour of the day appear to be the most important predictive variables to build an accurate regression model.

  20. Measuring Instrument Constructs of Return Factors for Green Office Building Investments Variables Using Rasch Measurement Model

    Directory of Open Access Journals (Sweden)

    Isa Mona

    2016-01-01

    Full Text Available This paper is a preliminary study on rationalising green office building investments in Malaysia. The aim of this paper is attempt to introduce the application of Rasch measurement model analysis to determine the validity and reliability of each construct in the questionnaire. In achieving this objective, a questionnaire survey was developed consists of 6 sections and a total of 106 responses were received from various investors who own and lease office buildings in Kuala Lumpur. The Rasch Measurement analysis is used to measure the quality control of item constructs in the instrument by measuring the specific objectivity within the same dimension, to reduce ambiguous measures, and a realistic estimation of precision and implicit quality. The Rasch analysis consists of the summary statistics, item unidimensionality and item measures. A result shows the items and respondent (person reliability is at 0.91 and 0.95 respectively.