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Sample records for regression identified factors

  1. Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change.

    Science.gov (United States)

    Feng, Yongjiu; Tong, Xiaohua

    2017-09-22

    Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.

  2. Identifying the Safety Factors over Traffic Signs in State Roads using a Panel Quantile Regression Approach.

    Science.gov (United States)

    Šarić, Željko; Xu, Xuecai; Duan, Li; Babić, Darko

    2018-06-20

    This study intended to investigate the interactions between accident rate and traffic signs in state roads located in Croatia, and accommodate the heterogeneity attributed to unobserved factors. The data from 130 state roads between 2012 and 2016 were collected from Traffic Accident Database System maintained by the Republic of Croatia Ministry of the Interior. To address the heterogeneity, a panel quantile regression model was proposed, in which quantile regression model offers a more complete view and a highly comprehensive analysis of the relationship between accident rate and traffic signs, while the panel data model accommodates the heterogeneity attributed to unobserved factors. Results revealed that (1) low visibility of material damage (MD) and death or injured (DI) increased the accident rate; (2) the number of mandatory signs and the number of warning signs were more likely to reduce the accident rate; (3)average speed limit and the number of invalid traffic signs per km exhibited a high accident rate. To our knowledge, it's the first attempt to analyze the interactions between accident consequences and traffic signs by employing a panel quantile regression model; by involving the visibility, the present study demonstrates that the low visibility causes a relatively higher risk of MD and DI; It is noteworthy that average speed limit corresponds with accident rate positively; The number of mandatory signs and the number of warning signs are more likely to reduce the accident rate; The number of invalid traffic signs per km are significant for accident rate, thus regular maintenance should be kept for a safer roadway environment.

  3. Identifying the Factors That Influence Change in SEBD Using Logistic Regression Analysis

    Science.gov (United States)

    Camilleri, Liberato; Cefai, Carmel

    2013-01-01

    Multiple linear regression and ANOVA models are widely used in applications since they provide effective statistical tools for assessing the relationship between a continuous dependent variable and several predictors. However these models rely heavily on linearity and normality assumptions and they do not accommodate categorical dependent…

  4. Identifying Environmental and Social Factors Predisposing to Pathological Gambling Combining Standard Logistic Regression and Logic Learning Machine.

    Science.gov (United States)

    Parodi, Stefano; Dosi, Corrado; Zambon, Antonella; Ferrari, Enrico; Muselli, Marco

    2017-12-01

    Identifying potential risk factors for problem gambling (PG) is of primary importance for planning preventive and therapeutic interventions. We illustrate a new approach based on the combination of standard logistic regression and an innovative method of supervised data mining (Logic Learning Machine or LLM). Data were taken from a pilot cross-sectional study to identify subjects with PG behaviour, assessed by two internationally validated scales (SOGS and Lie/Bet). Information was obtained from 251 gamblers recruited in six betting establishments. Data on socio-demographic characteristics, lifestyle and cognitive-related factors, and type, place and frequency of preferred gambling were obtained by a self-administered questionnaire. The following variables associated with PG were identified: instant gratification games, alcohol abuse, cognitive distortion, illegal behaviours and having started gambling with a relative or a friend. Furthermore, the combination of LLM and LR indicated the presence of two different types of PG, namely: (a) daily gamblers, more prone to illegal behaviour, with poor money management skills and who started gambling at an early age, and (b) non-daily gamblers, characterised by superstitious beliefs and a higher preference for immediate reward games. Finally, instant gratification games were strongly associated with the number of games usually played. Studies on gamblers habitually frequently betting shops are rare. The finding of different types of PG by habitual gamblers deserves further analysis in larger studies. Advanced data mining algorithms, like LLM, are powerful tools and potentially useful in identifying risk factors for PG.

  5. Identifying the critical success factors in the coverage of low vision services using the classification analysis and regression tree methodology.

    Science.gov (United States)

    Chiang, Peggy Pei-Chia; Xie, Jing; Keeffe, Jill Elizabeth

    2011-04-25

    To identify the critical success factors (CSF) associated with coverage of low vision services. Data were collected from a survey distributed to Vision 2020 contacts, government, and non-government organizations (NGOs) in 195 countries. The Classification and Regression Tree Analysis (CART) was used to identify the critical success factors of low vision service coverage. Independent variables were sourced from the survey: policies, epidemiology, provision of services, equipment and infrastructure, barriers to services, human resources, and monitoring and evaluation. Socioeconomic and demographic independent variables: health expenditure, population statistics, development status, and human resources in general, were sourced from the World Health Organization (WHO), World Bank, and the United Nations (UN). The findings identified that having >50% of children obtaining devices when prescribed (χ(2) = 44; P 3 rehabilitation workers per 10 million of population (χ(2) = 4.50; P = 0.034), higher percentage of population urbanized (χ(2) = 14.54; P = 0.002), a level of private investment (χ(2) = 14.55; P = 0.015), and being fully funded by government (χ(2) = 6.02; P = 0.014), are critical success factors associated with coverage of low vision services. This study identified the most important predictors for countries with better low vision coverage. The CART is a useful and suitable methodology in survey research and is a novel way to simplify a complex global public health issue in eye care.

  6. APPLICATION OF MULTIPLE LOGISTIC REGRESSION, BAYESIAN LOGISTIC AND CLASSIFICATION TREE TO IDENTIFY THE SIGNIFICANT FACTORS INFLUENCING CRASH SEVERITY

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    MILAD TAZIK

    2017-11-01

    Full Text Available Identifying cases in which road crashes result in fatality or injury of drivers may help improve their safety. In this study, datasets of crashes happened in TehranQom freeway, Iran, were examined by three models (multiple logistic regression, Bayesian logistic and classification tree to analyse the contribution of several variables to fatal accidents. For multiple logistic regression and Bayesian logistic models, the odds ratio was calculated for each variable. The model which best suited the identification of accident severity was determined based on AIC and DIC criteria. Based on the results of these two models, rollover crashes (OR = 14.58, %95 CI: 6.8-28.6, not using of seat belt (OR = 5.79, %95 CI: 3.1-9.9, exceeding speed limits (OR = 4.02, %95 CI: 1.8-7.9 and being female (OR = 2.91, %95 CI: 1.1-6.1 were the most important factors in fatalities of drivers. In addition, the results of the classification tree model have verified the findings of the other models.

  7. A regression tree for identifying combinations of fall risk factors associated to recurrent falling: a cross-sectional elderly population-based study.

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    Kabeshova, A; Annweiler, C; Fantino, B; Philip, T; Gromov, V A; Launay, C P; Beauchet, O

    2014-06-01

    Regression tree (RT) analyses are particularly adapted to explore the risk of recurrent falling according to various combinations of fall risk factors compared to logistic regression models. The aims of this study were (1) to determine which combinations of fall risk factors were associated with the occurrence of recurrent falls in older community-dwellers, and (2) to compare the efficacy of RT and multiple logistic regression model for the identification of recurrent falls. A total of 1,760 community-dwelling volunteers (mean age ± standard deviation, 71.0 ± 5.1 years; 49.4 % female) were recruited prospectively in this cross-sectional study. Age, gender, polypharmacy, use of psychoactive drugs, fear of falling (FOF), cognitive disorders and sad mood were recorded. In addition, the history of falls within the past year was recorded using a standardized questionnaire. Among 1,760 participants, 19.7 % (n = 346) were recurrent fallers. The RT identified 14 nodes groups and 8 end nodes with FOF as the first major split. Among participants with FOF, those who had sad mood and polypharmacy formed the end node with the greatest OR for recurrent falls (OR = 6.06 with p falls (OR = 0.25 with p factors for recurrent falls, the combination most associated with recurrent falls involving FOF, sad mood and polypharmacy. The FOF emerged as the risk factor strongly associated with recurrent falls. In addition, RT and multiple logistic regression were not sensitive enough to identify the majority of recurrent fallers but appeared efficient in detecting individuals not at risk of recurrent falls.

  8. Regression Analysis to Identify Factors Associated with Urinary Iodine Concentration at the Sub-National Level in India, Ghana, and Senegal

    Science.gov (United States)

    Knowles, Jacky; Kupka, Roland; Dumble, Sam; Garrett, Greg S.; Pandav, Chandrakant S.; Yadav, Kapil; Touré, Ndeye Khady; Foriwa Amoaful, Esi; Gorstein, Jonathan

    2018-01-01

    Single and multiple variable regression analyses were conducted using data from stratified, cluster sample design, iodine surveys in India, Ghana, and Senegal to identify factors associated with urinary iodine concentration (UIC) among women of reproductive age (WRA) at the national and sub-national level. Subjects were survey household respondents, typically WRA. For all three countries, UIC was significantly different (p regression analysis, UIC was significantly associated with strata and household salt iodine category in India and Ghana (p < 0.001). Estimated UIC was 1.6 (95% confidence intervals (CI) 1.3, 2.0) times higher (India) and 1.4 (95% CI 1.2, 1.6) times higher (Ghana) among WRA from households using adequately iodised salt than among WRA from households using non-iodised salt. Other significant associations with UIC were found in India, with having heard of iodine deficiency (1.2 times higher; CI 1.1, 1.3; p < 0.001) and having improved dietary diversity (1.1 times higher, CI 1.0, 1.2; p = 0.015); and in Ghana, with the level of tomato paste consumption the previous week (p = 0.029) (UIC for highest consumption level was 1.2 times lowest level; CI 1.1, 1.4). No significant associations were found in Senegal. Sub-national data on iodine status are required to assess equity of access to optimal iodine intake and to develop strategic responses as needed. PMID:29690505

  9. Regression Analysis to Identify Factors Associated with Urinary Iodine Concentration at the Sub-National Level in India, Ghana, and Senegal

    Directory of Open Access Journals (Sweden)

    Jacky Knowles

    2018-04-01

    Full Text Available Single and multiple variable regression analyses were conducted using data from stratified, cluster sample design, iodine surveys in India, Ghana, and Senegal to identify factors associated with urinary iodine concentration (UIC among women of reproductive age (WRA at the national and sub-national level. Subjects were survey household respondents, typically WRA. For all three countries, UIC was significantly different (p < 0.05 by household salt iodine category. Other significant differences were by strata and by household vulnerability to poverty in India and Ghana. In multiple variable regression analysis, UIC was significantly associated with strata and household salt iodine category in India and Ghana (p < 0.001. Estimated UIC was 1.6 (95% confidence intervals (CI 1.3, 2.0 times higher (India and 1.4 (95% CI 1.2, 1.6 times higher (Ghana among WRA from households using adequately iodised salt than among WRA from households using non-iodised salt. Other significant associations with UIC were found in India, with having heard of iodine deficiency (1.2 times higher; CI 1.1, 1.3; p < 0.001 and having improved dietary diversity (1.1 times higher, CI 1.0, 1.2; p = 0.015; and in Ghana, with the level of tomato paste consumption the previous week (p = 0.029 (UIC for highest consumption level was 1.2 times lowest level; CI 1.1, 1.4. No significant associations were found in Senegal. Sub-national data on iodine status are required to assess equity of access to optimal iodine intake and to develop strategic responses as needed.

  10. Regression Analysis to Identify Factors Associated with Household Salt Iodine Content at the Sub-National Level in Bangladesh, India, Ghana and Senegal

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    Knowles, Jacky; Kupka, Roland; Dumble, Sam; Garrett, Greg S.; Pandav, Chandrakant S.; Yadav, Kapil; Nahar, Baitun; Touré, Ndeye Khady; Amoaful, Esi Foriwa; Gorstein, Jonathan

    2018-01-01

    Regression analyses of data from stratified, cluster sample, household iodine surveys in Bangladesh, India, Ghana and Senegal were conducted to identify factors associated with household access to adequately iodised salt. For all countries, in single variable analyses, household salt iodine was significantly different (p < 0.05) between strata (geographic areas with representative data, defined by survey design), and significantly higher (p < 0.05) among households: with better living standard scores, where the respondent knew about iodised salt and/or looked for iodised salt at purchase, using salt bought in a sealed package, or using refined grain salt. Other country-level associations were also found. Multiple variable analyses showed a significant association between salt iodine and strata (p < 0.001) in India, Ghana and Senegal and that salt grain type was significantly associated with estimated iodine content in all countries (p < 0.001). Salt iodine relative to the reference (coarse salt) ranged from 1.3 (95% CI 1.2, 1.5) times higher for fine salt in Senegal to 3.6 (95% CI 2.6, 4.9) times higher for washed and 6.5 (95% CI 4.9, 8.8) times higher for refined salt in India. Sub-national data are required to monitor equity of access to adequately iodised salt. Improving household access to refined iodised salt in sealed packaging, would improve iodine intake from household salt in all four countries in this analysis, particularly in areas where there is significant small-scale salt production. PMID:29671774

  11. Regression Analysis to Identify Factors Associated with Household Salt Iodine Content at the Sub-National Level in Bangladesh, India, Ghana and Senegal

    Directory of Open Access Journals (Sweden)

    Jacky Knowles

    2018-04-01

    Full Text Available Regression analyses of data from stratified, cluster sample, household iodine surveys in Bangladesh, India, Ghana and Senegal were conducted to identify factors associated with household access to adequately iodised salt. For all countries, in single variable analyses, household salt iodine was significantly different (p < 0.05 between strata (geographic areas with representative data, defined by survey design, and significantly higher (p < 0.05 among households: with better living standard scores, where the respondent knew about iodised salt and/or looked for iodised salt at purchase, using salt bought in a sealed package, or using refined grain salt. Other country-level associations were also found. Multiple variable analyses showed a significant association between salt iodine and strata (p < 0.001 in India, Ghana and Senegal and that salt grain type was significantly associated with estimated iodine content in all countries (p < 0.001. Salt iodine relative to the reference (coarse salt ranged from 1.3 (95% CI 1.2, 1.5 times higher for fine salt in Senegal to 3.6 (95% CI 2.6, 4.9 times higher for washed and 6.5 (95% CI 4.9, 8.8 times higher for refined salt in India. Sub-national data are required to monitor equity of access to adequately iodised salt. Improving household access to refined iodised salt in sealed packaging, would improve iodine intake from household salt in all four countries in this analysis, particularly in areas where there is significant small-scale salt production.

  12. Binary Logistic Regression Analysis in Assessment and Identifying Factors That Influence Students' Academic Achievement: The Case of College of Natural and Computational Science, Wolaita Sodo University, Ethiopia

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    Zewude, Bereket Tessema; Ashine, Kidus Meskele

    2016-01-01

    An attempt has been made to assess and identify the major variables that influence student academic achievement at college of natural and computational science of Wolaita Sodo University in Ethiopia. Study time, peer influence, securing first choice of department, arranging study time outside class, amount of money received from family, good life…

  13. Assessing risk factors for periodontitis using regression

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    Lobo Pereira, J. A.; Ferreira, Maria Cristina; Oliveira, Teresa

    2013-10-01

    Multivariate statistical analysis is indispensable to assess the associations and interactions between different factors and the risk of periodontitis. Among others, regression analysis is a statistical technique widely used in healthcare to investigate and model the relationship between variables. In our work we study the impact of socio-demographic, medical and behavioral factors on periodontal health. Using regression, linear and logistic models, we can assess the relevance, as risk factors for periodontitis disease, of the following independent variables (IVs): Age, Gender, Diabetic Status, Education, Smoking status and Plaque Index. The multiple linear regression analysis model was built to evaluate the influence of IVs on mean Attachment Loss (AL). Thus, the regression coefficients along with respective p-values will be obtained as well as the respective p-values from the significance tests. The classification of a case (individual) adopted in the logistic model was the extent of the destruction of periodontal tissues defined by an Attachment Loss greater than or equal to 4 mm in 25% (AL≥4mm/≥25%) of sites surveyed. The association measures include the Odds Ratios together with the correspondent 95% confidence intervals.

  14. Identifying Interacting Genetic Variations by Fish-Swarm Logic Regression

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    Yang, Aiyuan; Yan, Chunxia; Zhu, Feng; Zhao, Zhongmeng; Cao, Zhi

    2013-01-01

    Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR) is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR), which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds. PMID:23984382

  15. Identifying Interacting Genetic Variations by Fish-Swarm Logic Regression

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    Xuanping Zhang

    2013-01-01

    Full Text Available Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR, which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds.

  16. Identifying predictors of physics item difficulty: A linear regression approach

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    Mesic, Vanes; Muratovic, Hasnija

    2011-06-01

    Large-scale assessments of student achievement in physics are often approached with an intention to discriminate students based on the attained level of their physics competencies. Therefore, for purposes of test design, it is important that items display an acceptable discriminatory behavior. To that end, it is recommended to avoid extraordinary difficult and very easy items. Knowing the factors that influence physics item difficulty makes it possible to model the item difficulty even before the first pilot study is conducted. Thus, by identifying predictors of physics item difficulty, we can improve the test-design process. Furthermore, we get additional qualitative feedback regarding the basic aspects of student cognitive achievement in physics that are directly responsible for the obtained, quantitative test results. In this study, we conducted a secondary analysis of data that came from two large-scale assessments of student physics achievement at the end of compulsory education in Bosnia and Herzegovina. Foremost, we explored the concept of “physics competence” and performed a content analysis of 123 physics items that were included within the above-mentioned assessments. Thereafter, an item database was created. Items were described by variables which reflect some basic cognitive aspects of physics competence. For each of the assessments, Rasch item difficulties were calculated in separate analyses. In order to make the item difficulties from different assessments comparable, a virtual test equating procedure had to be implemented. Finally, a regression model of physics item difficulty was created. It has been shown that 61.2% of item difficulty variance can be explained by factors which reflect the automaticity, complexity, and modality of the knowledge structure that is relevant for generating the most probable correct solution, as well as by the divergence of required thinking and interference effects between intuitive and formal physics knowledge

  17. Identifying predictors of physics item difficulty: A linear regression approach

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    Hasnija Muratovic

    2011-06-01

    Full Text Available Large-scale assessments of student achievement in physics are often approached with an intention to discriminate students based on the attained level of their physics competencies. Therefore, for purposes of test design, it is important that items display an acceptable discriminatory behavior. To that end, it is recommended to avoid extraordinary difficult and very easy items. Knowing the factors that influence physics item difficulty makes it possible to model the item difficulty even before the first pilot study is conducted. Thus, by identifying predictors of physics item difficulty, we can improve the test-design process. Furthermore, we get additional qualitative feedback regarding the basic aspects of student cognitive achievement in physics that are directly responsible for the obtained, quantitative test results. In this study, we conducted a secondary analysis of data that came from two large-scale assessments of student physics achievement at the end of compulsory education in Bosnia and Herzegovina. Foremost, we explored the concept of “physics competence” and performed a content analysis of 123 physics items that were included within the above-mentioned assessments. Thereafter, an item database was created. Items were described by variables which reflect some basic cognitive aspects of physics competence. For each of the assessments, Rasch item difficulties were calculated in separate analyses. In order to make the item difficulties from different assessments comparable, a virtual test equating procedure had to be implemented. Finally, a regression model of physics item difficulty was created. It has been shown that 61.2% of item difficulty variance can be explained by factors which reflect the automaticity, complexity, and modality of the knowledge structure that is relevant for generating the most probable correct solution, as well as by the divergence of required thinking and interference effects between intuitive and formal

  18. Efficient logistic regression designs under an imperfect population identifier.

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    Albert, Paul S; Liu, Aiyi; Nansel, Tonja

    2014-03-01

    Motivated by actual study designs, this article considers efficient logistic regression designs where the population is identified with a binary test that is subject to diagnostic error. We consider the case where the imperfect test is obtained on all participants, while the gold standard test is measured on a small chosen subsample. Under maximum-likelihood estimation, we evaluate the optimal design in terms of sample selection as well as verification. We show that there may be substantial efficiency gains by choosing a small percentage of individuals who test negative on the imperfect test for inclusion in the sample (e.g., verifying 90% test-positive cases). We also show that a two-stage design may be a good practical alternative to a fixed design in some situations. Under optimal and nearly optimal designs, we compare maximum-likelihood and semi-parametric efficient estimators under correct and misspecified models with simulations. The methodology is illustrated with an analysis from a diabetes behavioral intervention trial. © 2013, The International Biometric Society.

  19. 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

  20. Quasi-Poisson versus negative binomial regression models in identifying factors affecting initial CD4 cell count change due to antiretroviral therapy administered to HIV-positive adults in North-West Ethiopia (Amhara region).

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    Seyoum, Awoke; Ndlovu, Principal; Zewotir, Temesgen

    2016-01-01

    CD4 cells are a type of white blood cells that plays a significant role in protecting humans from infectious diseases. Lack of information on associated factors on CD4 cell count reduction is an obstacle for improvement of cells in HIV positive adults. Therefore, the main objective of this study was to investigate baseline factors that could affect initial CD4 cell count change after highly active antiretroviral therapy had been given to adult patients in North West Ethiopia. A retrospective cross-sectional study was conducted among 792 HIV positive adult patients who already started antiretroviral therapy for 1 month of therapy. A Chi square test of association was used to assess of predictor covariates on the variable of interest. Data was secondary source and modeled using generalized linear models, especially Quasi-Poisson regression. The patients' CD4 cell count changed within a month ranged from 0 to 109 cells/mm 3 with a mean of 15.9 cells/mm 3 and standard deviation 18.44 cells/mm 3 . The first month CD4 cell count change was significantly affected by poor adherence to highly active antiretroviral therapy (aRR = 0.506, P value = 2e -16 ), fair adherence (aRR = 0.592, P value = 0.0120), initial CD4 cell count (aRR = 1.0212, P value = 1.54e -15 ), low household income (aRR = 0.63, P value = 0.671e -14 ), middle income (aRR = 0.74, P value = 0.629e -12 ), patients without cell phone (aRR = 0.67, P value = 0.615e -16 ), WHO stage 2 (aRR = 0.91, P value = 0.0078), WHO stage 3 (aRR = 0.91, P value = 0.0058), WHO stage 4 (0876, P value = 0.0214), age (aRR = 0.987, P value = 0.000) and weight (aRR = 1.0216, P value = 3.98e -14 ). Adherence to antiretroviral therapy, initial CD4 cell count, household income, WHO stages, age, weight and owner of cell phone played a major role for the variation of CD4 cell count in our data. Hence, we recommend a close follow-up of patients to adhere the prescribed medication for

  1. Antibiotic Resistances in Livestock: A Comparative Approach to Identify an Appropriate Regression Model for Count Data

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    Anke Hüls

    2017-05-01

    Full Text Available Antimicrobial resistance in livestock is a matter of general concern. To develop hygiene measures and methods for resistance prevention and control, epidemiological studies on a population level are needed to detect factors associated with antimicrobial resistance in livestock holdings. In general, regression models are used to describe these relationships between environmental factors and resistance outcome. Besides the study design, the correlation structures of the different outcomes of antibiotic resistance and structural zero measurements on the resistance outcome as well as on the exposure side are challenges for the epidemiological model building process. The use of appropriate regression models that acknowledge these complexities is essential to assure valid epidemiological interpretations. The aims of this paper are (i to explain the model building process comparing several competing models for count data (negative binomial model, quasi-Poisson model, zero-inflated model, and hurdle model and (ii to compare these models using data from a cross-sectional study on antibiotic resistance in animal husbandry. These goals are essential to evaluate which model is most suitable to identify potential prevention measures. The dataset used as an example in our analyses was generated initially to study the prevalence and associated factors for the appearance of cefotaxime-resistant Escherichia coli in 48 German fattening pig farms. For each farm, the outcome was the count of samples with resistant bacteria. There was almost no overdispersion and only moderate evidence of excess zeros in the data. Our analyses show that it is essential to evaluate regression models in studies analyzing the relationship between environmental factors and antibiotic resistances in livestock. After model comparison based on evaluation of model predictions, Akaike information criterion, and Pearson residuals, here the hurdle model was judged to be the most appropriate

  2. Methods for identifying SNP interactions: a review on variations of Logic Regression, Random Forest and Bayesian logistic regression.

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    Chen, Carla Chia-Ming; Schwender, Holger; Keith, Jonathan; Nunkesser, Robin; Mengersen, Kerrie; Macrossan, Paula

    2011-01-01

    Due to advancements in computational ability, enhanced technology and a reduction in the price of genotyping, more data are being generated for understanding genetic associations with diseases and disorders. However, with the availability of large data sets comes the inherent challenges of new methods of statistical analysis and modeling. Considering a complex phenotype may be the effect of a combination of multiple loci, various statistical methods have been developed for identifying genetic epistasis effects. Among these methods, logic regression (LR) is an intriguing approach incorporating tree-like structures. Various methods have built on the original LR to improve different aspects of the model. In this study, we review four variations of LR, namely Logic Feature Selection, Monte Carlo Logic Regression, Genetic Programming for Association Studies, and Modified Logic Regression-Gene Expression Programming, and investigate the performance of each method using simulated and real genotype data. We contrast these with another tree-like approach, namely Random Forests, and a Bayesian logistic regression with stochastic search variable selection.

  3. Logistic regression for risk factor modelling in stuttering research.

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    Reed, Phil; Wu, Yaqionq

    2013-06-01

    To outline the uses of logistic regression and other statistical methods for risk factor analysis in the context of research on stuttering. The principles underlying the application of a logistic regression are illustrated, and the types of questions to which such a technique has been applied in the stuttering field are outlined. The assumptions and limitations of the technique are discussed with respect to existing stuttering research, and with respect to formulating appropriate research strategies to accommodate these considerations. Finally, some alternatives to the approach are briefly discussed. The way the statistical procedures are employed are demonstrated with some hypothetical data. Research into several practical issues concerning stuttering could benefit if risk factor modelling were used. Important examples are early diagnosis, prognosis (whether a child will recover or persist) and assessment of treatment outcome. After reading this article you will: (a) Summarize the situations in which logistic regression can be applied to a range of issues about stuttering; (b) Follow the steps in performing a logistic regression analysis; (c) Describe the assumptions of the logistic regression technique and the precautions that need to be checked when it is employed; (d) Be able to summarize its advantages over other techniques like estimation of group differences and simple regression. Copyright © 2012 Elsevier Inc. All rights reserved.

  4. Sexual harassment: identifying risk factors.

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    O'Hare, E A; O'Donohue, W

    1998-12-01

    A new model of the etiology of sexual harassment, the four-factor model, is presented and compared with several models of sexual harassment including the biological model, the organizational model, the sociocultural model, and the sex role spillover model. A number of risk factors associated with sexually harassing behavior are examined within the framework of the four-factor model of sexual harassment. These include characteristics of the work environment (e.g., sexist attitudes among co-workers, unprofessional work environment, skewed sex ratios in the workplace, knowledge of grievance procedures for sexual harassment incidents) as well as personal characteristics of the subject (e.g., physical attractiveness, job status, sex-role). Subjects were 266 university female faculty, staff, and students who completed the Sexual Experience Questionnaire to assess the experience of sexual harassment and a questionnaire designed to assess the risk factors stated above. Results indicated that the four-factor model is a better predictor of sexual harassment than the alternative models. The risk factors most strongly associated with sexual harassment were an unprofessional environment in the workplace, sexist atmosphere, and lack of knowledge about the organization's formal grievance procedures.

  5. On the null distribution of Bayes factors in linear regression

    Science.gov (United States)

    We show that under the null, the 2 log (Bayes factor) is asymptotically distributed as a weighted sum of chi-squared random variables with a shifted mean. This claim holds for Bayesian multi-linear regression with a family of conjugate priors, namely, the normal-inverse-gamma prior, the g-prior, and...

  6. Two-factor logistic regression in pediatric liver transplantation

    Science.gov (United States)

    Uzunova, Yordanka; Prodanova, Krasimira; Spasov, Lyubomir

    2017-12-01

    Using a two-factor logistic regression analysis an estimate is derived for the probability of absence of infections in the early postoperative period after pediatric liver transplantation. The influence of both the bilirubin level and the international normalized ratio of prothrombin time of blood coagulation at the 5th postoperative day is studied.

  7. Risk Factors of Falls in Community-Dwelling Older Adults: Logistic Regression Tree Analysis

    Science.gov (United States)

    Yamashita, Takashi; Noe, Douglas A.; Bailer, A. John

    2012-01-01

    Purpose of the Study: A novel logistic regression tree-based method was applied to identify fall risk factors and possible interaction effects of those risk factors. Design and Methods: A nationally representative sample of American older adults aged 65 years and older (N = 9,592) in the Health and Retirement Study 2004 and 2006 modules was used.…

  8. [Application of negative binomial regression and modified Poisson regression in the research of risk factors for injury frequency].

    Science.gov (United States)

    Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan

    2011-11-01

    To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.

  9. Logistic regression models of factors influencing the location of bioenergy and biofuels plants

    Science.gov (United States)

    T.M. Young; R.L. Zaretzki; J.H. Perdue; F.M. Guess; X. Liu

    2011-01-01

    Logistic regression models were developed to identify significant factors that influence the location of existing wood-using bioenergy/biofuels plants and traditional wood-using facilities. Logistic models provided quantitative insight for variables influencing the location of woody biomass-using facilities. Availability of "thinnings to a basal area of 31.7m2/ha...

  10. Identifying the factors underlying discontinuation of triptans.

    Science.gov (United States)

    Wells, Rebecca E; Markowitz, Shira Y; Baron, Eric P; Hentz, Joseph G; Kalidas, Kavita; Mathew, Paul G; Halker, Rashmi; Dodick, David W; Schwedt, Todd J

    2014-02-01

    To identify factors associated with triptan discontinuation among migraine patients. It is unclear why many migraine patients who are prescribed triptans discontinue this treatment. This study investigated correlates of triptan discontinuation with a focus on potentially modifiable factors to improve compliance. This multicenter cross-sectional survey (n = 276) was performed at US tertiary care headache clinics. Headache fellows who were members of the American Headache Society Headache Fellows Research Consortium recruited episodic and chronic migraine patients who were current triptan users (use within prior 3 months and for ≥1 year) or past triptan users (no use within 6 months; prior use within 2 years). Univariate analyses were first completed to compare current triptan users to past users for: migraine characteristics, other migraine treatments, triptan education, triptan efficacy, triptan side effects, type of prescribing provider, Migraine Disability Assessment (MIDAS) scores and Beck Depression Inventory (BDI) scores. Then, a multivariable logistic regression model was selected from all possible combinations of predictor variables to determine the factors that best correlated with triptan discontinuation. Compared with those still using triptans (n = 207), those who had discontinued use (n = 69) had higher rates of medication overuse (30 vs. 18%, P = .04) and were more likely to have ever used opioids for migraine treatment (57 vs. 38%, P = .006) as well as higher MIDAS (mean 63 vs. 37, P = .001) and BDI scores (mean 10.4 vs. 7.4, P = .009). Compared with discontinued users, current triptan users were more likely to have had their triptan prescribed by a specialist (neurologist, headache specialist, or pain specialist) (74 vs. 54%, P = .002) and were more likely to report headache resolution (53 vs. 14%, P  24 (2.6, [1.5, 4.6]), BDI >4 (2.5, [1.4, 4.5]), and a history of ever using opioids for migraine therapy (2.2, [1

  11. Regression and kriging analysis for grid power factor estimation

    Directory of Open Access Journals (Sweden)

    Rajesh Guntaka

    2014-12-01

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

  12. Identifying the important factors in simulation models with many factors

    NARCIS (Netherlands)

    Bettonvil, B.; Kleijnen, J.P.C.

    1994-01-01

    Simulation models may have many parameters and input variables (together called factors), while only a few factors are really important (parsimony principle). For such models this paper presents an effective and efficient screening technique to identify and estimate those important factors. The

  13. Identifying motivational factors within a multinational company

    Directory of Open Access Journals (Sweden)

    Daniela Bradutanu

    2011-08-01

    Full Text Available The aim of the study is to identify the main motivational factors within a multinational company. The first objective is to identify work functions, formulated on Abraham Maslow’s pyramid, following the identification of the key characteristics that motivate an employee at the work place and last, but not least, the type of motivation that employees focus, intrinsic or extrinsic. The research method targeted a questionnaire based survey, including various company employees and an interview with the manager. The results confirmed that in Romania, employees put great emphasis on extrinsic motivation, a certain income and job security being primary. These results have implications for managers that in order to effectively motivate staff, first, must know their needs and expectations. To identify the main needs and motivational factors we had as a starting point Maslow's pyramid.

  14. 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).

  15. Spontaneous regression of retinopathy of prematurity:incidence and predictive factors

    Directory of Open Access Journals (Sweden)

    Rui-Hong Ju

    2013-08-01

    Full Text Available AIM:To evaluate the incidence of spontaneous regression of changes in the retina and vitreous in active stage of retinopathy of prematurity(ROP and identify the possible relative factors during the regression.METHODS: This was a retrospective, hospital-based study. The study consisted of 39 premature infants with mild ROP showed spontaneous regression (Group A and 17 with severe ROP who had been treated before naturally involuting (Group B from August 2008 through May 2011. Data on gender, single or multiple pregnancy, gestational age, birth weight, weight gain from birth to the sixth week of life, use of oxygen in mechanical ventilation, total duration of oxygen inhalation, surfactant given or not, need for and times of blood transfusion, 1,5,10-min Apgar score, presence of bacterial or fungal or combined infection, hyaline membrane disease (HMD, patent ductus arteriosus (PDA, duration of stay in the neonatal intensive care unit (NICU and duration of ROP were recorded.RESULTS: The incidence of spontaneous regression of ROP with stage 1 was 86.7%, and with stage 2, stage 3 was 57.1%, 5.9%, respectively. With changes in zone Ⅲ regression was detected 100%, in zoneⅡ 46.2% and in zoneⅠ 0%. The mean duration of ROP in spontaneous regression group was 5.65±3.14 weeks, lower than that of the treated ROP group (7.34±4.33 weeks, but this difference was not statistically significant (P=0.201. GA, 1min Apgar score, 5min Apgar score, duration of NICU stay, postnatal age of initial screening and oxygen therapy longer than 10 days were significant predictive factors for the spontaneous regression of ROP (P<0.05. Retinal hemorrhage was the only independent predictive factor the spontaneous regression of ROP (OR 0.030, 95%CI 0.001-0.775, P=0.035.CONCLUSION:This study showed most stage 1 and 2 ROP and changes in zone Ⅲ can spontaneously regression in the end. Retinal hemorrhage is weakly inversely associated with the spontaneous regression.

  16. Lagged kernel machine regression for identifying time windows of susceptibility to exposures of complex mixtures.

    Science.gov (United States)

    Liu, Shelley H; Bobb, Jennifer F; Lee, Kyu Ha; Gennings, Chris; Claus Henn, Birgit; Bellinger, David; Austin, Christine; Schnaas, Lourdes; Tellez-Rojo, Martha M; Hu, Howard; Wright, Robert O; Arora, Manish; Coull, Brent A

    2018-07-01

    The impact of neurotoxic chemical mixtures on children's health is a critical public health concern. It is well known that during early life, toxic exposures may impact cognitive function during critical time intervals of increased vulnerability, known as windows of susceptibility. Knowledge on time windows of susceptibility can help inform treatment and prevention strategies, as chemical mixtures may affect a developmental process that is operating at a specific life phase. There are several statistical challenges in estimating the health effects of time-varying exposures to multi-pollutant mixtures, such as: multi-collinearity among the exposures both within time points and across time points, and complex exposure-response relationships. To address these concerns, we develop a flexible statistical method, called lagged kernel machine regression (LKMR). LKMR identifies critical exposure windows of chemical mixtures, and accounts for complex non-linear and non-additive effects of the mixture at any given exposure window. Specifically, LKMR estimates how the effects of a mixture of exposures change with the exposure time window using a Bayesian formulation of a grouped, fused lasso penalty within a kernel machine regression (KMR) framework. A simulation study demonstrates the performance of LKMR under realistic exposure-response scenarios, and demonstrates large gains over approaches that consider each time window separately, particularly when serial correlation among the time-varying exposures is high. Furthermore, LKMR demonstrates gains over another approach that inputs all time-specific chemical concentrations together into a single KMR. We apply LKMR to estimate associations between neurodevelopment and metal mixtures in Early Life Exposures in Mexico and Neurotoxicology, a prospective cohort study of child health in Mexico City.

  17. SU-E-J-212: Identifying Bones From MRI: A Dictionary Learnign and Sparse Regression Approach

    International Nuclear Information System (INIS)

    Ruan, D; Yang, Y; Cao, M; Hu, P; Low, D

    2014-01-01

    Purpose: To develop an efficient and robust scheme to identify bony anatomy based on MRI-only simulation images. Methods: MRI offers important soft tissue contrast and functional information, yet its lack of correlation to electron-density has placed it as an auxiliary modality to CT in radiotherapy simulation and adaptation. An effective scheme to identify bony anatomy is an important first step towards MR-only simulation/treatment paradigm and would satisfy most practical purposes. We utilize a UTE acquisition sequence to achieve visibility of the bone. By contrast to manual + bulk or registration-to identify bones, we propose a novel learning-based approach for improved robustness to MR artefacts and environmental changes. Specifically, local information is encoded with MR image patch, and the corresponding label is extracted (during training) from simulation CT aligned to the UTE. Within each class (bone vs. nonbone), an overcomplete dictionary is learned so that typical patches within the proper class can be represented as a sparse combination of the dictionary entries. For testing, an acquired UTE-MRI is divided to patches using a sliding scheme, where each patch is sparsely regressed against both bone and nonbone dictionaries, and subsequently claimed to be associated with the class with the smaller residual. Results: The proposed method has been applied to the pilot site of brain imaging and it has showed general good performance, with dice similarity coefficient of greater than 0.9 in a crossvalidation study using 4 datasets. Importantly, it is robust towards consistent foreign objects (e.g., headset) and the artefacts relates to Gibbs and field heterogeneity. Conclusion: A learning perspective has been developed for inferring bone structures based on UTE MRI. The imaging setting is subject to minimal motion effects and the post-processing is efficient. The improved efficiency and robustness enables a first translation to MR-only routine. The scheme

  18. SU-E-J-212: Identifying Bones From MRI: A Dictionary Learnign and Sparse Regression Approach

    Energy Technology Data Exchange (ETDEWEB)

    Ruan, D; Yang, Y; Cao, M; Hu, P; Low, D [UCLA, Los Angeles, CA (United States)

    2014-06-01

    Purpose: To develop an efficient and robust scheme to identify bony anatomy based on MRI-only simulation images. Methods: MRI offers important soft tissue contrast and functional information, yet its lack of correlation to electron-density has placed it as an auxiliary modality to CT in radiotherapy simulation and adaptation. An effective scheme to identify bony anatomy is an important first step towards MR-only simulation/treatment paradigm and would satisfy most practical purposes. We utilize a UTE acquisition sequence to achieve visibility of the bone. By contrast to manual + bulk or registration-to identify bones, we propose a novel learning-based approach for improved robustness to MR artefacts and environmental changes. Specifically, local information is encoded with MR image patch, and the corresponding label is extracted (during training) from simulation CT aligned to the UTE. Within each class (bone vs. nonbone), an overcomplete dictionary is learned so that typical patches within the proper class can be represented as a sparse combination of the dictionary entries. For testing, an acquired UTE-MRI is divided to patches using a sliding scheme, where each patch is sparsely regressed against both bone and nonbone dictionaries, and subsequently claimed to be associated with the class with the smaller residual. Results: The proposed method has been applied to the pilot site of brain imaging and it has showed general good performance, with dice similarity coefficient of greater than 0.9 in a crossvalidation study using 4 datasets. Importantly, it is robust towards consistent foreign objects (e.g., headset) and the artefacts relates to Gibbs and field heterogeneity. Conclusion: A learning perspective has been developed for inferring bone structures based on UTE MRI. The imaging setting is subject to minimal motion effects and the post-processing is efficient. The improved efficiency and robustness enables a first translation to MR-only routine. The scheme

  19. Identifying Dietary Patterns Associated with Mild Cognitive Impairment in Older Korean Adults Using Reduced Rank Regression

    Directory of Open Access Journals (Sweden)

    Dayeon Shin

    2018-01-01

    Full Text Available Diet plays a crucial role in cognitive function. Few studies have examined the relationship between dietary patterns and cognitive functions of older adults in the Korean population. This study aimed to identify the effect of dietary patterns on the risk of mild cognitive impairment. A total of 239 participants, including 88 men and 151 women, aged 65 years and older were selected from health centers in the district of Seoul, Gyeonggi province, and Incheon, in Korea. Dietary patterns were determined using Reduced Rank Regression (RRR methods with responses regarding vitamin B6, vitamin C, and iron intakes, based on both a one-day 24-h recall and a food frequency questionnaire. Cognitive function was assessed using the Korean-Mini Mental State Examination (K-MMSE. Multivariable logistic regression models were used to estimate the association between dietary pattern score and the risk of mild cognitive impairment. A total of 20 (8% out of the 239 participants had mild cognitive impairment. Three dietary patterns were identified: seafood and vegetables, high meat, and bread, ham, and alcohol. Among the three dietary patterns, the older adult population who adhered to the seafood and vegetables pattern, characterized by high intake of seafood, vegetables, fruits, bread, snacks, soy products, beans, chicken, pork, ham, egg, and milk had a decreased risk of mild cognitive impairment compared to those who did not (adjusted odds ratios 0.06, 95% confidence interval 0.01–0.72 after controlling for gender, supplementation, education, history of dementia, physical activity, body mass index (BMI, and duration of sleep. The other two dietary patterns were not significantly associated with the risk of mild cognitive impairment. In conclusion, high consumption of fruits, vegetables, seafood, and protein foods was significantly associated with reduced mild cognitive impairment in older Korean adults. These results can contribute to the establishment of

  20. Risk factors for pedicled flap necrosis in hand soft tissue reconstruction: a multivariate logistic regression analysis.

    Science.gov (United States)

    Gong, Xu; Cui, Jianli; Jiang, Ziping; Lu, Laijin; Li, Xiucun

    2018-03-01

    Few clinical retrospective studies have reported the risk factors of pedicled flap necrosis in hand soft tissue reconstruction. The aim of this study was to identify non-technical risk factors associated with pedicled flap perioperative necrosis in hand soft tissue reconstruction via a multivariate logistic regression analysis. For patients with hand soft tissue reconstruction, we carefully reviewed hospital records and identified 163 patients who met the inclusion criteria. The characteristics of these patients, flap transfer procedures and postoperative complications were recorded. Eleven predictors were identified. The correlations between pedicled flap necrosis and risk factors were analysed using a logistic regression model. Of 163 skin flaps, 125 flaps survived completely without any complications. The pedicled flap necrosis rate in hands was 11.04%, which included partial flap necrosis (7.36%) and total flap necrosis (3.68%). Soft tissue defects in fingers were noted in 68.10% of all cases. The logistic regression analysis indicated that the soft tissue defect site (P = 0.046, odds ratio (OR) = 0.079, confidence interval (CI) (0.006, 0.959)), flap size (P = 0.020, OR = 1.024, CI (1.004, 1.045)) and postoperative wound infection (P < 0.001, OR = 17.407, CI (3.821, 79.303)) were statistically significant risk factors for pedicled flap necrosis of the hand. Soft tissue defect site, flap size and postoperative wound infection were risk factors associated with pedicled flap necrosis in hand soft tissue defect reconstruction. © 2017 Royal Australasian College of Surgeons.

  1. Use of multilevel logistic regression to identify the causes of differential item functioning.

    Science.gov (United States)

    Balluerka, Nekane; Gorostiaga, Arantxa; Gómez-Benito, Juana; Hidalgo, María Dolores

    2010-11-01

    Given that a key function of tests is to serve as evaluation instruments and for decision making in the fields of psychology and education, the possibility that some of their items may show differential behaviour is a major concern for psychometricians. In recent decades, important progress has been made as regards the efficacy of techniques designed to detect this differential item functioning (DIF). However, the findings are scant when it comes to explaining its causes. The present study addresses this problem from the perspective of multilevel analysis. Starting from a case study in the area of transcultural comparisons, multilevel logistic regression is used: 1) to identify the item characteristics associated with the presence of DIF; 2) to estimate the proportion of variation in the DIF coefficients that is explained by these characteristics; and 3) to evaluate alternative explanations of the DIF by comparing the explanatory power or fit of different sequential models. The comparison of these models confirmed one of the two alternatives (familiarity with the stimulus) and rejected the other (the topic area) as being a cause of differential functioning with respect to the compared groups.

  2. Identifying Domain-General and Domain-Specific Predictors of Low Mathematics Performance: A Classification and Regression Tree Analysis

    Directory of Open Access Journals (Sweden)

    David J. Purpura

    2017-12-01

    Full Text Available Many children struggle to successfully acquire early mathematics skills. Theoretical and empirical evidence has pointed to deficits in domain-specific skills (e.g., non-symbolic mathematics skills or domain-general skills (e.g., executive functioning and language as underlying low mathematical performance. In the current study, we assessed a sample of 113 three- to five-year old preschool children on a battery of domain-specific and domain-general factors in the fall and spring of their preschool year to identify Time 1 (fall factors associated with low performance in mathematics knowledge at Time 2 (spring. We used the exploratory approach of classification and regression tree analyses, a strategy that uses step-wise partitioning to create subgroups from a larger sample using multiple predictors, to identify the factors that were the strongest classifiers of low performance for younger and older preschool children. Results indicated that the most consistent classifier of low mathematics performance at Time 2 was children’s Time 1 mathematical language skills. Further, other distinct classifiers of low performance emerged for younger and older children. These findings suggest that risk classification for low mathematics performance may differ depending on children’s age.

  3. Extralobar pulmonary sequestration in neonates: The natural course and predictive factors associated with spontaneous regression

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Hee Mang; Jung, Ah Young; Cho, Young Ah; Yoon, Chong Hyun; Lee, Jin Seong [Asan Medical Center Children' s Hospital, University of Ulsan College of Medicine, Department of Radiology and Research Institute of Radiology, Songpa-gu, Seoul (Korea, Republic of); Kim, Ellen Ai-Rhan [University of Ulsan College of Medicine, Division of Neonatology, Asan Medical Center Children' s Hospital, Seoul (Korea, Republic of); Chung, Sung-Hoon [Kyung Hee University School of Medicine, Department of Pediatrics, Seoul (Korea, Republic of); Kim, Seon-Ok [Asan Medical Center, Department of Clinical Epidemiology and Biostatistics, Seoul (Korea, Republic of)

    2017-06-15

    To describe the natural course of extralobar pulmonary sequestration (EPS) and identify factors associated with spontaneous regression of EPS. We retrospectively searched for patients diagnosed with EPS on initial contrast CT scan within 1 month after birth and had a follow-up CT scan without treatment. Spontaneous regression of EPS was assessed by percentage decrease in volume (PDV) and percentage decrease in sum of the diameter of systemic feeding arteries (PDD) by comparing initial and follow-up CT scans. Clinical and CT features were analysed to determine factors associated with PDV and PDD rates. Fifty-one neonates were included. The cumulative proportions of patients reaching PDV > 50 % and PDD > 50 % were 93.0 % and 73.3 % at 4 years, respectively. Tissue attenuation was significantly associated with PDV rate (B = -21.78, P <.001). The tissue attenuation (B = -22.62, P =.001) and diameter of the largest systemic feeding arteries (B = -48.31, P =.011) were significant factors associated with PDD rate. The volume and diameter of systemic feeding arteries of EPS spontaneously decreased within 4 years without treatment. EPSs showing a low tissue attenuation and small diameter of the largest systemic feeding arteries on initial contrast-enhanced CT scans were likely to regress spontaneously. (orig.)

  4. BENCHMARKING - PRACTICAL TOOLS IDENTIFY KEY SUCCESS FACTORS

    Directory of Open Access Journals (Sweden)

    Olga Ju. Malinina

    2016-01-01

    Full Text Available The article gives a practical example of the application of benchmarking techniques. The object of study selected fashion store Company «HLB & M Hennes & Mauritz», located in the shopping center «Gallery», Krasnodar. Hennes & Mauritz. The purpose of this article is to identify the best ways to develop a fashionable brand clothing store Hennes & Mauritz on the basis of benchmarking techniques. On the basis of conducted market research is a comparative analysis of the data from different perspectives. The result of the author’s study is a generalization of the ndings, the development of the key success factors that will allow to plan a successful trading activities in the future, based on the best experience of competitors.

  5. Observed to expected or logistic regression to identify hospitals with high or low 30-day mortality?

    Science.gov (United States)

    Helgeland, Jon; Clench-Aas, Jocelyne; Laake, Petter; Veierød, Marit B.

    2018-01-01

    Introduction A common quality indicator for monitoring and comparing hospitals is based on death within 30 days of admission. An important use is to determine whether a hospital has higher or lower mortality than other hospitals. Thus, the ability to identify such outliers correctly is essential. Two approaches for detection are: 1) calculating the ratio of observed to expected number of deaths (OE) per hospital and 2) including all hospitals in a logistic regression (LR) comparing each hospital to a form of average over all hospitals. The aim of this study was to compare OE and LR with respect to correctly identifying 30-day mortality outliers. Modifications of the methods, i.e., variance corrected approach of OE (OE-Faris), bias corrected LR (LR-Firth), and trimmed mean variants of LR and LR-Firth were also studied. Materials and methods To study the properties of OE and LR and their variants, we performed a simulation study by generating patient data from hospitals with known outlier status (low mortality, high mortality, non-outlier). Data from simulated scenarios with varying number of hospitals, hospital volume, and mortality outlier status, were analysed by the different methods and compared by level of significance (ability to falsely claim an outlier) and power (ability to reveal an outlier). Moreover, administrative data for patients with acute myocardial infarction (AMI), stroke, and hip fracture from Norwegian hospitals for 2012–2014 were analysed. Results None of the methods achieved the nominal (test) level of significance for both low and high mortality outliers. For low mortality outliers, the levels of significance were increased four- to fivefold for OE and OE-Faris. For high mortality outliers, OE and OE-Faris, LR 25% trimmed and LR-Firth 10% and 25% trimmed maintained approximately the nominal level. The methods agreed with respect to outlier status for 94.1% of the AMI hospitals, 98.0% of the stroke, and 97.8% of the hip fracture hospitals

  6. Regression and kriging analysis for grid power factor estimation

    OpenAIRE

    Rajesh Guntaka; Harley R. Myler

    2014-01-01

    The measurement of power factor (PF) in electrical utility grids is a mainstay of load balancing and is also a critical element of transmission and distribution efficiency. The measurement of PF dates back to the earliest periods of electrical power distribution to public grids. In the wide-area distribution grid, measurement of current waveforms is trivial and may be accomplished at any point in the grid using a current tap transformer. However, voltage measurement requires reference to grou...

  7. Identifying perinatal risk factors for infant maltreatment: an ecological approach

    Directory of Open Access Journals (Sweden)

    Hallisey Elaine J

    2006-12-01

    Full Text Available Abstract Background Child maltreatment and its consequences are a persistent problem throughout the world. Public health workers, human services officials, and others are interested in new and efficient ways to determine which geographic areas to target for intervention programs and resources. To improve assessment efforts, selected perinatal factors were examined, both individually and in various combinations, to determine if they are associated with increased risk of infant maltreatment. State of Georgia birth records and abuse and neglect data were analyzed using an area-based, ecological approach with the census tract as a surrogate for the community. Cartographic visualization suggested some correlation exists between risk factors and child maltreatment, so bivariate and multivariate regression were performed. The presence of spatial autocorrelation precluded the use of traditional ordinary least squares regression, therefore a spatial regression model coupled with maximum likelihood estimation was employed. Results Results indicate that all individual factors or their combinations are significantly associated with increased risk of infant maltreatment. The set of perinatal risk factors that best predicts infant maltreatment rates are: mother smoked during pregnancy, families with three or more siblings, maternal age less than 20 years, births to unmarried mothers, Medicaid beneficiaries, and inadequate prenatal care. Conclusion This model enables public health to take a proactive stance, to reasonably predict areas where poor outcomes are likely to occur, and to therefore more efficiently allocate resources. U.S. states that routinely collect the variables the National Center for Health Statistics (NCHS defines for birth certificates can easily identify areas that are at high risk for infant maltreatment. The authors recommend that agencies charged with reducing child maltreatment target communities that demonstrate the perinatal risks

  8. Regression Trees Identify Relevant Interactions: Can This Improve the Predictive Performance of Risk Adjustment?

    Science.gov (United States)

    Buchner, Florian; Wasem, Jürgen; Schillo, Sonja

    2017-01-01

    Risk equalization formulas have been refined since their introduction about two decades ago. Because of the complexity and the abundance of possible interactions between the variables used, hardly any interactions are considered. A regression tree is used to systematically search for interactions, a methodologically new approach in risk equalization. Analyses are based on a data set of nearly 2.9 million individuals from a major German social health insurer. A two-step approach is applied: In the first step a regression tree is built on the basis of the learning data set. Terminal nodes characterized by more than one morbidity-group-split represent interaction effects of different morbidity groups. In the second step the 'traditional' weighted least squares regression equation is expanded by adding interaction terms for all interactions detected by the tree, and regression coefficients are recalculated. The resulting risk adjustment formula shows an improvement in the adjusted R 2 from 25.43% to 25.81% on the evaluation data set. Predictive ratios are calculated for subgroups affected by the interactions. The R 2 improvement detected is only marginal. According to the sample level performance measures used, not involving a considerable number of morbidity interactions forms no relevant loss in accuracy. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

  9. Identifying individual changes in performance with composite quality indicators while accounting for regression to the mean.

    Science.gov (United States)

    Gajewski, Byron J; Dunton, Nancy

    2013-04-01

    Almost a decade ago Morton and Torgerson indicated that perceived medical benefits could be due to "regression to the mean." Despite this caution, the regression to the mean "effects on the identification of changes in institutional performance do not seem to have been considered previously in any depth" (Jones and Spiegelhalter). As a response, Jones and Spiegelhalter provide a methodology to adjust for regression to the mean when modeling recent changes in institutional performance for one-variable quality indicators. Therefore, in our view, Jones and Spiegelhalter provide a breakthrough methodology for performance measures. At the same time, in the interests of parsimony, it is useful to aggregate individual quality indicators into a composite score. Our question is, can we develop and demonstrate a methodology that extends the "regression to the mean" literature to allow for composite quality indicators? Using a latent variable modeling approach, we extend the methodology to the composite indicator case. We demonstrate the approach on 4 indicators collected by the National Database of Nursing Quality Indicators. A simulation study further demonstrates its "proof of concept."

  10. Risk factors identified for certain lymphoma subtypes

    Science.gov (United States)

    In a large international collaborative analysis of risk factors for non-Hodgkin lymphoma (NHL), scientists were able to quantify risk associated with medical history, lifestyle factors, family history of blood or lymph-borne cancers, and occupation for 11

  11. Key factors contributing to accident severity rate in construction industry in Iran: a regression modelling approach.

    Science.gov (United States)

    Soltanzadeh, Ahmad; Mohammadfam, Iraj; Moghimbeigi, Abbas; Ghiasvand, Reza

    2016-03-01

    Construction industry involves the highest risk of occupational accidents and bodily injuries, which range from mild to very severe. The aim of this cross-sectional study was to identify the factors associated with accident severity rate (ASR) in the largest Iranian construction companies based on data about 500 occupational accidents recorded from 2009 to 2013. We also gathered data on safety and health risk management and training systems. Data were analysed using Pearson's chi-squared coefficient and multiple regression analysis. Median ASR (and the interquartile range) was 107.50 (57.24- 381.25). Fourteen of the 24 studied factors stood out as most affecting construction accident severity (p<0.05). These findings can be applied in the design and implementation of a comprehensive safety and health risk management system to reduce ASR.

  12. Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications.

    Science.gov (United States)

    Tao, Chenyang; Nichols, Thomas E; Hua, Xue; Ching, Christopher R K; Rolls, Edmund T; Thompson, Paul M; Feng, Jianfeng

    2017-01-01

    We propose a generalized reduced rank latent factor regression model (GRRLF) for the analysis of tensor field responses and high dimensional covariates. The model is motivated by the need from imaging-genetic studies to identify genetic variants that are associated with brain imaging phenotypes, often in the form of high dimensional tensor fields. GRRLF identifies from the structure in the data the effective dimensionality of the data, and then jointly performs dimension reduction of the covariates, dynamic identification of latent factors, and nonparametric estimation of both covariate and latent response fields. After accounting for the latent and covariate effects, GRLLF performs a nonparametric test on the remaining factor of interest. GRRLF provides a better factorization of the signals compared with common solutions, and is less susceptible to overfitting because it exploits the effective dimensionality. The generality and the flexibility of GRRLF also allow various statistical models to be handled in a unified framework and solutions can be efficiently computed. Within the field of neuroimaging, it improves the sensitivity for weak signals and is a promising alternative to existing approaches. The operation of the framework is demonstrated with both synthetic datasets and a real-world neuroimaging example in which the effects of a set of genes on the structure of the brain at the voxel level were measured, and the results compared favorably with those from existing approaches. Copyright © 2016. Published by Elsevier Inc.

  13. 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.

  14. Pathways-driven sparse regression identifies pathways and genes associated with high-density lipoprotein cholesterol in two Asian cohorts.

    Directory of Open Access Journals (Sweden)

    Matt Silver

    2013-11-01

    Full Text Available Standard approaches to data analysis in genome-wide association studies (GWAS ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait's genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK

  15. Pathways-Driven Sparse Regression Identifies Pathways and Genes Associated with High-Density Lipoprotein Cholesterol in Two Asian Cohorts

    Science.gov (United States)

    Silver, Matt; Chen, Peng; Li, Ruoying; Cheng, Ching-Yu; Wong, Tien-Yin; Tai, E-Shyong; Teo, Yik-Ying; Montana, Giovanni

    2013-01-01

    Standard approaches to data analysis in genome-wide association studies (GWAS) ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs) or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait's genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK signalling and immune

  16. BRAVO identifies critical success factors for logistics

    NARCIS (Netherlands)

    Kokke, C.J.T.M.; Donselaar, van K.H.; Allessie, M.

    1997-01-01

    Good operational performance depends on knowing which operational factors are critical to success. Bravo, a research project involving 150 transport and distribution companies in The Netherlands, has developed a tool now being adopted nationally by all companies in the sector to find opportunities

  17. Using multiobjective tradeoff sets and Multivariate Regression Trees to identify critical and robust decisions for long term water utility planning

    Science.gov (United States)

    Smith, R.; Kasprzyk, J. R.; Balaji, R.

    2017-12-01

    In light of deeply uncertain factors like future climate change and population shifts, responsible resource management will require new types of information and strategies. For water utilities, this entails potential expansion and efficient management of water supply infrastructure systems for changes in overall supply; changes in frequency and severity of climate extremes such as droughts and floods; and variable demands, all while accounting for conflicting long and short term performance objectives. Multiobjective Evolutionary Algorithms (MOEAs) are emerging decision support tools that have been used by researchers and, more recently, water utilities to efficiently generate and evaluate thousands of planning portfolios. The tradeoffs between conflicting objectives are explored in an automated way to produce (often large) suites of portfolios that strike different balances of performance. Once generated, the sets of optimized portfolios are used to support relatively subjective assertions of priorities and human reasoning, leading to adoption of a plan. These large tradeoff sets contain information about complex relationships between decisions and between groups of decisions and performance that, until now, has not been quantitatively described. We present a novel use of Multivariate Regression Trees (MRTs) to analyze tradeoff sets to reveal these relationships and critical decisions. Additionally, when MRTs are applied to tradeoff sets developed for different realizations of an uncertain future, they can identify decisions that are robust across a wide range of conditions and produce fundamental insights about the system being optimized.

  18. Identifying keystone species in the human gut microbiome from metagenomic timeseries using sparse linear regression.

    Directory of Open Access Journals (Sweden)

    Charles K Fisher

    Full Text Available Human associated microbial communities exert tremendous influence over human health and disease. With modern metagenomic sequencing methods it is now possible to follow the relative abundance of microbes in a community over time. These microbial communities exhibit rich ecological dynamics and an important goal of microbial ecology is to infer the ecological interactions between species directly from sequence data. Any algorithm for inferring ecological interactions must overcome three major obstacles: 1 a correlation between the abundances of two species does not imply that those species are interacting, 2 the sum constraint on the relative abundances obtained from metagenomic studies makes it difficult to infer the parameters in timeseries models, and 3 errors due to experimental uncertainty, or mis-assignment of sequencing reads into operational taxonomic units, bias inferences of species interactions due to a statistical problem called "errors-in-variables". Here we introduce an approach, Learning Interactions from MIcrobial Time Series (LIMITS, that overcomes these obstacles. LIMITS uses sparse linear regression with boostrap aggregation to infer a discrete-time Lotka-Volterra model for microbial dynamics. We tested LIMITS on synthetic data and showed that it could reliably infer the topology of the inter-species ecological interactions. We then used LIMITS to characterize the species interactions in the gut microbiomes of two individuals and found that the interaction networks varied significantly between individuals. Furthermore, we found that the interaction networks of the two individuals are dominated by distinct "keystone species", Bacteroides fragilis and Bacteroided stercosis, that have a disproportionate influence on the structure of the gut microbiome even though they are only found in moderate abundance. Based on our results, we hypothesize that the abundances of certain keystone species may be responsible for individuality in

  19. Predictive factors in patients eligible for pegfilgrastim prophylaxis focusing on RDI using ordered logistic regression analysis.

    Science.gov (United States)

    Kanbayashi, Yuko; Ishikawa, Takeshi; Kanazawa, Motohiro; Nakajima, Yuki; Kawano, Rumi; Tabuchi, Yusuke; Yoshioka, Tomoko; Ihara, Norihiko; Hosokawa, Toyoshi; Takayama, Koichi; Shikata, Keisuke; Taguchi, Tetsuya

    2018-03-16

    Although pegfilgrastim prophylaxis is expected to maintain the relative dose intensity (RDI) of chemotherapy and improve safety, information is limited. However, the optimal selection of patients eligible for pegfilgrastim prophylaxis is an important issue from a medical economics viewpoint. Therefore, this retrospective study identified factors that could predict these eligible patients to maintain the RDI. The participants included 166 cancer patients undergoing pegfilgrastim prophylaxis combined with chemotherapy in our outpatient chemotherapy center between March 2015 and April 2017. Variables were extracted from clinical records for regression analysis of factors related to maintenance of the RDI. RDI was classified into four categories: 100% = 0, 85% or predictive factors in patients eligible for pegfilgrastim prophylaxis to maintain the RDI. Threshold measures were examined using a receiver operating characteristic (ROC) analysis curve. Age [odds ratio (OR) 1.07, 95% confidence interval (CI) 1.04-1.11; P maintenance. ROC curve analysis of the group that failed to maintain the RDI indicated that the threshold for age was 70 years and above, with a sensitivity of 60.0% and specificity of 80.2% (area under the curve: 0.74). In conclusion, younger age, anemia (less), and administration of pegfilgrastim 24-72 h after chemotherapy were significant factors for RDI maintenance.

  20. Schistosoma mansoni reinfection: Analysis of risk factors by classification and regression tree (CART modeling.

    Directory of Open Access Journals (Sweden)

    Andréa Gazzinelli

    Full Text Available Praziquantel (PZQ is an effective chemotherapy for schistosomiasis mansoni and a mainstay for its control and potential elimination. However, it does not prevent against reinfection, which can occur rapidly in areas with active transmission. A guide to ranking the risk factors for Schistosoma mansoni reinfection would greatly contribute to prioritizing resources and focusing prevention and control measures to prevent rapid reinfection. The objective of the current study was to explore the relationship among the socioeconomic, demographic, and epidemiological factors that can influence reinfection by S. mansoni one year after successful treatment with PZQ in school-aged children in Northeastern Minas Gerais state Brazil. Parasitological, socioeconomic, demographic, and water contact information were surveyed in 506 S. mansoni-infected individuals, aged 6 to 15 years, resident in these endemic areas. Eligible individuals were treated with PZQ until they were determined to be negative by the absence of S. mansoni eggs in the feces on two consecutive days of Kato-Katz fecal thick smear. These individuals were surveyed again 12 months from the date of successful treatment with PZQ. A classification and regression tree modeling (CART was then used to explore the relationship between socioeconomic, demographic, and epidemiological variables and their reinfection status. The most important risk factor identified for S. mansoni reinfection was their "heavy" infection at baseline. Additional analyses, excluding heavy infection status, showed that lower socioeconomic status and a lower level of education of the household head were also most important risk factors for S. mansoni reinfection. Our results provide an important contribution toward the control and possible elimination of schistosomiasis by identifying three major risk factors that can be used for targeted treatment and monitoring of reinfection. We suggest that control measures that target

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

    Science.gov (United States)

    Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

    2012-05-01

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

  2. [Socioeconomic factors conditioning obesity in adults. Evidence based on quantile regression and panel data].

    Science.gov (United States)

    Temporelli, Karina L; Viego, Valentina N

    2016-08-01

    Objective To measure the effect of socioeconomic variables on the prevalence of obesity. Factors such as income level, urbanization, incorporation of women into the labor market and access to unhealthy foods are considered in this paper. Method Econometric estimates of the proportion of obese men and women by country were calculated using models based on panel data and quantile regressions, with data from 192 countries for the period 2002-2005.Levels of per capita income, urbanization, income/big mac ratio price and labor indicators for female population were considered as explanatory variables. Results Factors that have influence over obesity in adults differ between men and women; accessibility to fast food is related to male obesity, while the employment mode causes higher rates in women. The underlying socioeconomic factors for obesity are also different depending on the magnitude of this problem in each country; in countries with low prevalence, a greater level of income favor the transition to obesogenic habits, while a higher income level mitigates the problem in those countries with high rates of obesity. Discussion Identifying the socio-economic causes of the significant increase in the prevalence of obesity is essential for the implementation of effective strategies for prevention, since this condition not only affects the quality of life of those who suffer from it but also puts pressure on health systems due to the treatment costs of associated diseases.

  3. An application in identifying high-risk populations in alternative tobacco product use utilizing logistic regression and CART: a heuristic comparison.

    Science.gov (United States)

    Lei, Yang; Nollen, Nikki; Ahluwahlia, Jasjit S; Yu, Qing; Mayo, Matthew S

    2015-04-09

    Other forms of tobacco use are increasing in prevalence, yet most tobacco control efforts are aimed at cigarettes. In light of this, it is important to identify individuals who are using both cigarettes and alternative tobacco products (ATPs). Most previous studies have used regression models. We conducted a traditional logistic regression model and a classification and regression tree (CART) model to illustrate and discuss the added advantages of using CART in the setting of identifying high-risk subgroups of ATP users among cigarettes smokers. The data were collected from an online cross-sectional survey administered by Survey Sampling International between July 5, 2012 and August 15, 2012. Eligible participants self-identified as current smokers, African American, White, or Latino (of any race), were English-speaking, and were at least 25 years old. The study sample included 2,376 participants and was divided into independent training and validation samples for a hold out validation. Logistic regression and CART models were used to examine the important predictors of cigarettes + ATP users. The logistic regression model identified nine important factors: gender, age, race, nicotine dependence, buying cigarettes or borrowing, whether the price of cigarettes influences the brand purchased, whether the participants set limits on cigarettes per day, alcohol use scores, and discrimination frequencies. The C-index of the logistic regression model was 0.74, indicating good discriminatory capability. The model performed well in the validation cohort also with good discrimination (c-index = 0.73) and excellent calibration (R-square = 0.96 in the calibration regression). The parsimonious CART model identified gender, age, alcohol use score, race, and discrimination frequencies to be the most important factors. It also revealed interesting partial interactions. The c-index is 0.70 for the training sample and 0.69 for the validation sample. The misclassification

  4. DETERMINATION OF FACTORS AFFECTING LENGTH OF STAY WITH MULTINOMIAL LOGISTIC REGRESSION IN TURKEY

    Directory of Open Access Journals (Sweden)

    Öğr. Gör. Rukiye NUMAN TEKİN

    2016-08-01

    Full Text Available Length of stay (LOS has important implications in various aspects of health services, can vary according to a wide range of factors. It is noticed that LOS has been neglected mostly in both theoratical studies and practice of health care management in Turkey. The main purpose of this study is to identify factors related to LOS in Turkey. A retrospective analysis of 2.255.836 patients hospitalized to private, university, foundation university and other (municipality, association and foreigners/minority hospitals hospitals which have an agreement with Social Security Institution (SSI in Turkey, from January 1, 2010, until the December 31, 2010, was examined. Patient’s data were taken from MEDULA (National Electronic Invoice System and SPSS 18.0 was used to perform statistical analysis. In this study t-test, one way anova and multinomial logistic regression are used to determine variables that may affect to LOS. The average LOS of patients was 3,93 days (SD = 5,882. LOS showed a statistically significant difference according to all independent variables used in the study (age, gender, disease class, type of hospitalization, presence of comorbidity, type and number of surgery, season of hospitalization, hospital ownership/bed capacity/ geographical region/residential area/type of service. According to the results of the multinomial lojistic regression analysis, LOS was negatively affected in terms of gender, presence of comorbidity, geographical region of hospital and was positively affected in terms of age, season of hospitalization, hospital bed capacity/ ownership/type of service/residential area.

  5. Identifying factors affecting optimal management of agricultural water

    Directory of Open Access Journals (Sweden)

    Masoud Samian

    2015-01-01

    In addition to quantitative methodology such as descriptive statistics and factor analysis a qualitative methodology was employed for dynamic simulation among variables through Vensim software. In this study, the factor analysis technique was used through the Kaiser-Meyer-Olkin (KMO and Bartlett tests. From the results, four key elements were identified as factors affecting the optimal management of agricultural water in Hamedan area. These factors were institutional and legal factors, technical and knowledge factors, economic factors and social factors.

  6. Risk factors for violence in psychosis: systematic review and meta-regression analysis of 110 studies.

    Directory of Open Access Journals (Sweden)

    Katrina Witt

    Full Text Available Previous reviews on risk and protective factors for violence in psychosis have produced contrasting findings. There is therefore a need to clarify the direction and strength of association of risk and protective factors for violent outcomes in individuals with psychosis.We conducted a systematic review and meta-analysis using 6 electronic databases (CINAHL, EBSCO, EMBASE, Global Health, PsycINFO, PUBMED and Google Scholar. Studies were identified that reported factors associated with violence in adults diagnosed, using DSM or ICD criteria, with schizophrenia and other psychoses. We considered non-English language studies and dissertations. Risk and protective factors were meta-analysed if reported in three or more primary studies. Meta-regression examined sources of heterogeneity. A novel meta-epidemiological approach was used to group similar risk factors into one of 10 domains. Sub-group analyses were then used to investigate whether risk domains differed for studies reporting severe violence (rather than aggression or hostility and studies based in inpatient (rather than outpatient settings.There were 110 eligible studies reporting on 45,533 individuals, 8,439 (18.5% of whom were violent. A total of 39,995 (87.8% were diagnosed with schizophrenia, 209 (0.4% were diagnosed with bipolar disorder, and 5,329 (11.8% were diagnosed with other psychoses. Dynamic (or modifiable risk factors included hostile behaviour, recent drug misuse, non-adherence with psychological therapies (p values<0.001, higher poor impulse control scores, recent substance misuse, recent alcohol misuse (p values<0.01, and non-adherence with medication (p value <0.05. We also examined a number of static factors, the strongest of which were criminal history factors. When restricting outcomes to severe violence, these associations did not change materially. In studies investigating inpatient violence, associations differed in strength but not direction.Certain dynamic risk

  7. Logistic regression and multiple classification analyses to explore risk factors of under-5 mortality in bangladesh

    International Nuclear Information System (INIS)

    Bhowmik, K.R.; Islam, S.

    2016-01-01

    Logistic regression (LR) analysis is the most common statistical methodology to find out the determinants of childhood mortality. However, the significant predictors cannot be ranked according to their influence on the response variable. Multiple classification (MC) analysis can be applied to identify the significant predictors with a priority index which helps to rank the predictors. The main objective of the study is to find the socio-demographic determinants of childhood mortality at neonatal, post-neonatal, and post-infant period by fitting LR model as well as to rank those through MC analysis. The study is conducted using the data of Bangladesh Demographic and Health Survey 2007 where birth and death information of children were collected from their mothers. Three dichotomous response variables are constructed from children age at death to fit the LR and MC models. Socio-economic and demographic variables significantly associated with the response variables separately are considered in LR and MC analyses. Both the LR and MC models identified the same significant predictors for specific childhood mortality. For both the neonatal and child mortality, biological factors of children, regional settings, and parents socio-economic status are found as 1st, 2nd, and 3rd significant groups of predictors respectively. Mother education and household environment are detected as major significant predictors of post-neonatal mortality. This study shows that MC analysis with or without LR analysis can be applied to detect determinants with rank which help the policy makers taking initiatives on a priority basis. (author)

  8. The study of logistic regression of risk factor on the death cause of uranium miners

    International Nuclear Information System (INIS)

    Wen Jinai; Yuan Liyun; Jiang Ruyi

    1999-01-01

    Logistic regression model has widely been used in the field of medicine. The computer software on this model is popular, but it is worth to discuss how to use this model correctly. Using SPSS (Statistical Package for the Social Science) software, unconditional logistic regression method was adopted to carry out multi-factor analyses on the cause of total death, cancer death and lung cancer death of uranium miners. The data is from radioepidemiological database of one uranium mine. The result show that attained age is a risk factor in the logistic regression analyses of total death, cancer death and lung cancer death. In the logistic regression analysis of cancer death, there is a negative correlation between the age of exposure and cancer death. This shows that the younger the age at exposure, the bigger the risk of cancer death. In the logistic regression analysis of lung cancer death, there is a positive correlation between the cumulated exposure and lung cancer death, this show that cumulated exposure is a most important risk factor of lung cancer death on uranium miners. It has been documented by many foreign reports that the lung cancer death rate is higher in uranium miners

  9. Determining factors influencing survival of breast cancer by fuzzy logistic regression model.

    Science.gov (United States)

    Nikbakht, Roya; Bahrampour, Abbas

    2017-01-01

    Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM). The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86). Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.

  10. Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

    Science.gov (United States)

    Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

    2018-03-01

    Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

  11. Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

    Science.gov (United States)

    Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

    2017-01-01

    Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

  12. Identifying the Prognosis Factors in Death after Liver Transplantation via Adaptive LASSO in Iran

    Directory of Open Access Journals (Sweden)

    Hadi Raeisi Shahraki

    2016-01-01

    Full Text Available Despite the widespread use of liver transplantation as a routine therapy in liver diseases, the effective factors on its outcomes are still controversial. This study attempted to identify the most effective factors on death after liver transplantation. For this purpose, modified least absolute shrinkage and selection operator (LASSO, called Adaptive LASSO, was utilized. One of the best advantages of this method is considering high number of factors. Therefore, in a historical cohort study from 2008 to 2013, the clinical findings of 680 patients undergoing liver transplant surgery were considered. Ridge and Adaptive LASSO regression methods were then implemented to identify the most effective factors on death. To compare the performance of these two models, receiver operating characteristic (ROC curve was used. According to the results, 12 factors in Ridge regression and 9 ones in Adaptive LASSO regression were significant. The area under the ROC curve (AUC of Adaptive LASSO was equal to 89% (95% CI: 86%–91%, which was significantly greater than Ridge regression (64%, 95% CI: 61%–68% (p<0.001. As a conclusion, the significant factors and the performance criteria revealed the superiority of Adaptive LASSO method as a penalized model versus traditional regression model in the present study.

  13. Identifying Factors for Worker Motivation in Zambia's Rural Health Facilities.

    Science.gov (United States)

    Cross, Samuel S; Baernholdt, Dr Marianne

    2017-01-01

    Within Zambia there is a shortage of health workers in rural areas. This study aims to identify motivating factors for retaining rural health workers. Sixty rural health workers completed surveys and 46 were interviewed. They rated the importance of six motivating factors and discussed these and other factors in interviews. An interview was conducted with a Government Human Resources Manager (HR Manager) to elicit contextual information. All six factors were identified as being very important motivators, as were two additional factors. Additional career training was identified by many as the most important factor. Comparison of results and the HR Manager interview revealed that workers lacked knowledge about opportunities and that the HR manager was aware of barriers to career development. The Zambian government might better motivate and retain rural health workers by offering them any combination of identified factors, and by addressing the barriers to career development.

  14. Differentiating regressed melanoma from regressed lichenoid keratosis.

    Science.gov (United States)

    Chan, Aegean H; Shulman, Kenneth J; Lee, Bonnie A

    2017-04-01

    Distinguishing regressed lichen planus-like keratosis (LPLK) from regressed melanoma can be difficult on histopathologic examination, potentially resulting in mismanagement of patients. We aimed to identify histopathologic features by which regressed melanoma can be differentiated from regressed LPLK. Twenty actively inflamed LPLK, 12 LPLK with regression and 15 melanomas with regression were compared and evaluated by hematoxylin and eosin staining as well as Melan-A, microphthalmia transcription factor (MiTF) and cytokeratin (AE1/AE3) immunostaining. (1) A total of 40% of regressed melanomas showed complete or near complete loss of melanocytes within the epidermis with Melan-A and MiTF immunostaining, while 8% of regressed LPLK exhibited this finding. (2) Necrotic keratinocytes were seen in the epidermis in 33% regressed melanomas as opposed to all of the regressed LPLK. (3) A dense infiltrate of melanophages in the papillary dermis was seen in 40% of regressed melanomas, a feature not seen in regressed LPLK. In summary, our findings suggest that a complete or near complete loss of melanocytes within the epidermis strongly favors a regressed melanoma over a regressed LPLK. In addition, necrotic epidermal keratinocytes and the presence of a dense band-like distribution of dermal melanophages can be helpful in differentiating these lesions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  15. Identifying influential factors on integrated marketing planning using information technology

    Directory of Open Access Journals (Sweden)

    Karim Hamdi

    2014-07-01

    Full Text Available This paper presents an empirical investigation to identify important factors influencing integrated marketing planning using information technology. The proposed study designs a questionnaire for measuring integrated marketing planning, which consists of three categories of structural factors, behavioral factors and background factors. There are 40 questions associated with the proposed study in Likert scale. Cronbach alphas have been calculated for structural factors, behavioral factors and background factors as 0.89, 0.86 and 0.83, respectively. Using some statistical test, the study has confirmed the effects of three factors on integrated marketing. In addition, the implementation of Freedman test has revealed that structural factors were the most important factor followed by background factors and behavioral factors.

  16. Retrieving relevant factors with exploratory SEM and principal-covariate regression: A comparison.

    Science.gov (United States)

    Vervloet, Marlies; Van den Noortgate, Wim; Ceulemans, Eva

    2018-02-12

    Behavioral researchers often linearly regress a criterion on multiple predictors, aiming to gain insight into the relations between the criterion and predictors. Obtaining this insight from the ordinary least squares (OLS) regression solution may be troublesome, because OLS regression weights show only the effect of a predictor on top of the effects of other predictors. Moreover, when the number of predictors grows larger, it becomes likely that the predictors will be highly collinear, which makes the regression weights' estimates unstable (i.e., the "bouncing beta" problem). Among other procedures, dimension-reduction-based methods have been proposed for dealing with these problems. These methods yield insight into the data by reducing the predictors to a smaller number of summarizing variables and regressing the criterion on these summarizing variables. Two promising methods are principal-covariate regression (PCovR) and exploratory structural equation modeling (ESEM). Both simultaneously optimize reduction and prediction, but they are based on different frameworks. The resulting solutions have not yet been compared; it is thus unclear what the strengths and weaknesses are of both methods. In this article, we focus on the extents to which PCovR and ESEM are able to extract the factors that truly underlie the predictor scores and can predict a single criterion. The results of two simulation studies showed that for a typical behavioral dataset, ESEM (using the BIC for model selection) in this regard is successful more often than PCovR. Yet, in 93% of the datasets PCovR performed equally well, and in the case of 48 predictors, 100 observations, and large differences in the strengths of the factors, PCovR even outperformed ESEM.

  17. Exploring factors associated with traumatic dental injuries in preschool children: a Poisson regression analysis.

    Science.gov (United States)

    Feldens, Carlos Alberto; Kramer, Paulo Floriani; Ferreira, Simone Helena; Spiguel, Mônica Hermann; Marquezan, Marcela

    2010-04-01

    This cross-sectional study aimed to investigate the factors associated with dental trauma in preschool children using Poisson regression analysis with robust variance. The study population comprised 888 children aged 3- to 5-year-old attending public nurseries in Canoas, southern Brazil. Questionnaires assessing information related to the independent variables (age, gender, race, mother's educational level and family income) were completed by the parents. Clinical examinations were carried out by five trained examiners in order to assess traumatic dental injuries (TDI) according to Andreasen's classification. One of the five examiners was calibrated to assess orthodontic characteristics (open bite and overjet). Multivariable Poisson regression analysis with robust variance was used to determine the factors associated with dental trauma as well as the strengths of association. Traditional logistic regression was also performed in order to compare the estimates obtained by both methods of statistical analysis. 36.4% (323/888) of the children suffered dental trauma and there was no difference in prevalence rates from 3 to 5 years of age. Poisson regression analysis showed that the probability of the outcome was almost 30% higher for children whose mothers had more than 8 years of education (Prevalence Ratio = 1.28; 95% CI = 1.03-1.60) and 63% higher for children with an overjet greater than 2 mm (Prevalence Ratio = 1.63; 95% CI = 1.31-2.03). Odds ratios clearly overestimated the size of the effect when compared with prevalence ratios. These findings indicate the need for preventive orientation regarding TDI, in order to educate parents and caregivers about supervising infants, particularly those with increased overjet and whose mothers have a higher level of education. Poisson regression with robust variance represents a better alternative than logistic regression to estimate the risk of dental trauma in preschool children.

  18. Multiple Linear Regression Analysis of Factors Affecting Real Property Price Index From Case Study Research In Istanbul/Turkey

    Science.gov (United States)

    Denli, H. H.; Koc, Z.

    2015-12-01

    Estimation of real properties depending on standards is difficult to apply in time and location. Regression analysis construct mathematical models which describe or explain relationships that may exist between variables. The problem of identifying price differences of properties to obtain a price index can be converted into a regression problem, and standard techniques of regression analysis can be used to estimate the index. Considering regression analysis for real estate valuation, which are presented in real marketing process with its current characteristics and quantifiers, the method will help us to find the effective factors or variables in the formation of the value. In this study, prices of housing for sale in Zeytinburnu, a district in Istanbul, are associated with its characteristics to find a price index, based on information received from a real estate web page. The associated variables used for the analysis are age, size in m2, number of floors having the house, floor number of the estate and number of rooms. The price of the estate represents the dependent variable, whereas the rest are independent variables. Prices from 60 real estates have been used for the analysis. Same price valued locations have been found and plotted on the map and equivalence curves have been drawn identifying the same valued zones as lines.

  19. Modelling long-term fire occurrence factors in Spain by accounting for local variations with geographically weighted regression

    Science.gov (United States)

    Martínez-Fernández, J.; Chuvieco, E.; Koutsias, N.

    2013-02-01

    Humans are responsible for most forest fires in Europe, but anthropogenic factors behind these events are still poorly understood. We tried to identify the driving factors of human-caused fire occurrence in Spain by applying two different statistical approaches. Firstly, assuming stationary processes for the whole country, we created models based on multiple linear regression and binary logistic regression to find factors associated with fire density and fire presence, respectively. Secondly, we used geographically weighted regression (GWR) to better understand and explore the local and regional variations of those factors behind human-caused fire occurrence. The number of human-caused fires occurring within a 25-yr period (1983-2007) was computed for each of the 7638 Spanish mainland municipalities, creating a binary variable (fire/no fire) to develop logistic models, and a continuous variable (fire density) to build standard linear regression models. A total of 383 657 fires were registered in the study dataset. The binary logistic model, which estimates the probability of having/not having a fire, successfully classified 76.4% of the total observations, while the ordinary least squares (OLS) regression model explained 53% of the variation of the fire density patterns (adjusted R2 = 0.53). Both approaches confirmed, in addition to forest and climatic variables, the importance of variables related with agrarian activities, land abandonment, rural population exodus and developmental processes as underlying factors of fire occurrence. For the GWR approach, the explanatory power of the GW linear model for fire density using an adaptive bandwidth increased from 53% to 67%, while for the GW logistic model the correctly classified observations improved only slightly, from 76.4% to 78.4%, but significantly according to the corrected Akaike Information Criterion (AICc), from 3451.19 to 3321.19. The results from GWR indicated a significant spatial variation in the local

  20. Fuzzy Regression Prediction and Application Based on Multi-Dimensional Factors of Freight Volume

    Science.gov (United States)

    Xiao, Mengting; Li, Cheng

    2018-01-01

    Based on the reality of the development of air cargo, the multi-dimensional fuzzy regression method is used to determine the influencing factors, and the three most important influencing factors of GDP, total fixed assets investment and regular flight route mileage are determined. The system’s viewpoints and analogy methods, the use of fuzzy numbers and multiple regression methods to predict the civil aviation cargo volume. In comparison with the 13th Five-Year Plan for China’s Civil Aviation Development (2016-2020), it is proved that this method can effectively improve the accuracy of forecasting and reduce the risk of forecasting. It is proved that this model predicts civil aviation freight volume of the feasibility, has a high practical significance and practical operation.

  1. The Research of Regression Method for Forecasting Monthly Electricity Sales Considering Coupled Multi-factor

    Science.gov (United States)

    Wang, Jiangbo; Liu, Junhui; Li, Tiantian; Yin, Shuo; He, Xinhui

    2018-01-01

    The monthly electricity sales forecasting is a basic work to ensure the safety of the power system. This paper presented a monthly electricity sales forecasting method which comprehensively considers the coupled multi-factors of temperature, economic growth, electric power replacement and business expansion. The mathematical model is constructed by using regression method. The simulation results show that the proposed method is accurate and effective.

  2. Influential factors of red-light running at signalized intersection and prediction using a rare events logistic regression model.

    Science.gov (United States)

    Ren, Yilong; Wang, Yunpeng; Wu, Xinkai; Yu, Guizhen; Ding, Chuan

    2016-10-01

    Red light running (RLR) has become a major safety concern at signalized intersection. To prevent RLR related crashes, it is critical to identify the factors that significantly impact the drivers' behaviors of RLR, and to predict potential RLR in real time. In this research, 9-month's RLR events extracted from high-resolution traffic data collected by loop detectors from three signalized intersections were applied to identify the factors that significantly affect RLR behaviors. The data analysis indicated that occupancy time, time gap, used yellow time, time left to yellow start, whether the preceding vehicle runs through the intersection during yellow, and whether there is a vehicle passing through the intersection on the adjacent lane were significantly factors for RLR behaviors. Furthermore, due to the rare events nature of RLR, a modified rare events logistic regression model was developed for RLR prediction. The rare events logistic regression method has been applied in many fields for rare events studies and shows impressive performance, but so far none of previous research has applied this method to study RLR. The results showed that the rare events logistic regression model performed significantly better than the standard logistic regression model. More importantly, the proposed RLR prediction method is purely based on loop detector data collected from a single advance loop detector located 400 feet away from stop-bar. This brings great potential for future field applications of the proposed method since loops have been widely implemented in many intersections and can collect data in real time. This research is expected to contribute to the improvement of intersection safety significantly. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Identifying factors affecting destination choice of medical tourists: a ...

    African Journals Online (AJOL)

    medical tourism”, has emerged as a new source of competitive advantage all over the world. The present study seeks to identify the factors that affect destination choice of medical tourists. Methods: We systematically searched relevant databases ...

  4. Predicting Factors of INSURE Failure in Low Birth Weight Neonates with RDS; A Logistic Regression Model

    Directory of Open Access Journals (Sweden)

    Bita Najafian

    2015-02-01

    Full Text Available Background:Respiratory Distress syndrome is the most common respiratory disease in premature neonate and the most important cause of death among them. We aimed to investigate factors to predict successful or failure of INSURE method as a therapeutic method of RDS.Methods:In a cohort study,45 neonates with diagnosed RDS and birth weight lower than 1500g were included and they underwent INSURE followed by NCPAP(Nasal Continuous Positive Airway Pressure. The patients were divided into failure or successful groups and factors which can predict success of INSURE were investigated by logistic regression in SPSS 16th version.Results:29 and16 neonates were observed in successful and failure groups, respectively. Birth weight was the only variable with significant difference between two groups (P=0.002. Finally logistic regression test showed that birth weight is only predicting factor for success (P: 0.001, EXP[β]: 0.009, CI [95%]: 1.003-0.014 and mortality (P: 0.029, EXP[β]: 0.993, CI [95%]: 0.987-0.999 of neonates treated with INSURE method.Conclusion:Predicting factors which affect on success rate of INSURE can be useful for treating and reducing charge of neonate with RDS and the birth weight is one of the effective factor on INSURE Success in this study.

  5. Predicting Factors of INSURE Failure in Low Birth Weight Neonates with RDS; A Logistic Regression Model

    Directory of Open Access Journals (Sweden)

    Bita Najafian

    2015-02-01

    Full Text Available Background:Respiratory Distress syndrome is the most common respiratory disease in premature neonate and the most important cause of death among them. We aimed to investigate factors to predict successful or failure of INSURE method as a therapeutic method of RDS. Methods:In a cohort study,45 neonates with diagnosed RDS and birth weight lower than 1500g were included and they underwent INSURE followed by NCPAP(Nasal Continuous Positive Airway Pressure. The patients were divided into failure or successful groups and factors which can predict success of INSURE were investigated by logistic regression in SPSS 16th version. Results:29 and16 neonates were observed in successful and failure groups, respectively. Birth weight was the only variable with significant difference between two groups (P=0.002. Finally logistic regression test showed that birth weight is only predicting factor for success (P: 0.001, EXP[β]: 0.009, CI [95%]: 1.003-0.014 and mortality (P: 0.029, EXP[β]: 0.993, CI [95%]: 0.987-0.999 of neonates treated with INSURE method. Conclusion:Predicting factors which affect on success rate of INSURE can be useful for treating and reducing charge of neonate with RDS and the birth weight is one of the effective factor on INSURE Success in this study.

  6. Determination of osteoporosis risk factors using a multiple logistic regression model in postmenopausal Turkish women.

    Science.gov (United States)

    Akkus, Zeki; Camdeviren, Handan; Celik, Fatma; Gur, Ali; Nas, Kemal

    2005-09-01

    To determine the risk factors of osteoporosis using a multiple binary logistic regression method and to assess the risk variables for osteoporosis, which is a major and growing health problem in many countries. We presented a case-control study, consisting of 126 postmenopausal healthy women as control group and 225 postmenopausal osteoporotic women as the case group. The study was carried out in the Department of Physical Medicine and Rehabilitation, Dicle University, Diyarbakir, Turkey between 1999-2002. The data from the 351 participants were collected using a standard questionnaire that contains 43 variables. A multiple logistic regression model was then used to evaluate the data and to find the best regression model. We classified 80.1% (281/351) of the participants using the regression model. Furthermore, the specificity value of the model was 67% (84/126) of the control group while the sensitivity value was 88% (197/225) of the case group. We found the distribution of residual values standardized for final model to be exponential using the Kolmogorow-Smirnow test (p=0.193). The receiver operating characteristic curve was found successful to predict patients with risk for osteoporosis. This study suggests that low levels of dietary calcium intake, physical activity, education, and longer duration of menopause are independent predictors of the risk of low bone density in our population. Adequate dietary calcium intake in combination with maintaining a daily physical activity, increasing educational level, decreasing birth rate, and duration of breast-feeding may contribute to healthy bones and play a role in practical prevention of osteoporosis in Southeast Anatolia. In addition, the findings of the present study indicate that the use of multivariate statistical method as a multiple logistic regression in osteoporosis, which maybe influenced by many variables, is better than univariate statistical evaluation.

  7. Investigating the Effect of Complexity Factors in Stoichiometry Problems Using Logistic Regression and Eye Tracking

    Science.gov (United States)

    Tang, Hui; Kirk, John; Pienta, Norbert J.

    2014-01-01

    This paper includes two experiments, one investigating complexity factors in stoichiometry word problems, and the other identifying students' problem-solving protocols by using eye-tracking technology. The word problems used in this study had five different complexity factors, which were randomly assigned by a Web-based tool that we developed. The…

  8. Trait Mindfulness as a Limiting Factor for Residual Depressive Symptoms: An Explorative Study Using Quantile Regression

    Science.gov (United States)

    Radford, Sholto; Eames, Catrin; Brennan, Kate; Lambert, Gwladys; Crane, Catherine; Williams, J. Mark G.; Duggan, Danielle S.; Barnhofer, Thorsten

    2014-01-01

    Mindfulness has been suggested to be an important protective factor for emotional health. However, this effect might vary with regard to context. This study applied a novel statistical approach, quantile regression, in order to investigate the relation between trait mindfulness and residual depressive symptoms in individuals with a history of recurrent depression, while taking into account symptom severity and number of episodes as contextual factors. Rather than fitting to a single indicator of central tendency, quantile regression allows exploration of relations across the entire range of the response variable. Analysis of self-report data from 274 participants with a history of three or more previous episodes of depression showed that relatively higher levels of mindfulness were associated with relatively lower levels of residual depressive symptoms. This relationship was most pronounced near the upper end of the response distribution and moderated by the number of previous episodes of depression at the higher quantiles. The findings suggest that with lower levels of mindfulness, residual symptoms are less constrained and more likely to be influenced by other factors. Further, the limiting effect of mindfulness on residual symptoms is most salient in those with higher numbers of episodes. PMID:24988072

  9. Identifying Generalizable Image Segmentation Parameters for Urban Land Cover Mapping through Meta-Analysis and Regression Tree Modeling

    Directory of Open Access Journals (Sweden)

    Brian A. Johnson

    2018-01-01

    Full Text Available The advent of very high resolution (VHR satellite imagery and the development of Geographic Object-Based Image Analysis (GEOBIA have led to many new opportunities for fine-scale land cover mapping, especially in urban areas. Image segmentation is an important step in the GEOBIA framework, so great time/effort is often spent to ensure that computer-generated image segments closely match real-world objects of interest. In the remote sensing community, segmentation is frequently performed using the multiresolution segmentation (MRS algorithm, which is tuned through three user-defined parameters (the scale, shape/color, and compactness/smoothness parameters. The scale parameter (SP is the most important parameter and governs the average size of generated image segments. Existing automatic methods to determine suitable SPs for segmentation are scene-specific and often computationally intensive, so an approach to estimating appropriate SPs that is generalizable (i.e., not scene-specific could speed up the GEOBIA workflow considerably. In this study, we attempted to identify generalizable SPs for five common urban land cover types (buildings, vegetation, roads, bare soil, and water through meta-analysis and nonlinear regression tree (RT modeling. First, we performed a literature search of recent studies that employed GEOBIA for urban land cover mapping and extracted the MRS parameters used, the image properties (i.e., spatial and radiometric resolutions, and the land cover classes mapped. Using this data extracted from the literature, we constructed RT models for each land cover class to predict suitable SP values based on the: image spatial resolution, image radiometric resolution, shape/color parameter, and compactness/smoothness parameter. Based on a visual and quantitative analysis of results, we found that for all land cover classes except water, relatively accurate SPs could be identified using our RT modeling results. The main advantage of our

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

    Science.gov (United States)

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

    2015-12-01

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

  11. Risk factors of regression and undercorrection in photorefractive keratectomy:a case-control study

    Directory of Open Access Journals (Sweden)

    Seyed-Farzad Mohammadi

    2015-10-01

    Full Text Available AIM:To determine risk factors of regression and undercorrection following photorefractive keratectomy (PRK in myopia or myopic astigmatism.METHODS: A case-control study was designed in which eyes with an indication for re-treatment (RT were defined as cases; primary criteria for RT indication, as assessed at least 9mo postoperatively, included an uncorrected distance visual acuity (UDVA of 20/30 or worse and a stable refraction for more than 3mo. Additional considerations included optical quality symptoms and significant higher order aberrations (HOAs. Controls were chosen from the same cohort of operated eyes which had complete post-operative follow up data beyond 9mo and did not need RT. The cohort included patients who had undergone PRK by the Tissue-Saving (TS ablation profile of Technolas 217z100 excimer laser (Bausch & Lomb, Rochester, NY, USA. Mitomycin C had been used in all of the primary procedures.RESULTS:We had 70 case eyes and 158 control eyes, and they were comparable in terms of age, sex and follow-up time (P values:0.58, 1.00 and 0.89, respectively. Pre-operative spherical equivalent of more than -5.00 diopter (D, intended optical zone (OZ diameter of less than 6.00 mm and ocular fixation instability during laser ablation were associated with RT indications (all P values <0.001. These factors maintained their significance in the multiple logistic regression model with odd ratios of 6.12, 6.71 and 7.89, respectively.CONCLUSION:Higher refractive correction (>-5.00 D, smaller OZ (<6.00 mm and unstable fixation during laser ablation of PRK for myopia and myopic astigmatism were found to be strong predictors of undercorrection and regression.

  12. Estimation of a Reactor Core Power Peaking Factor Using Support Vector Regression and Uncertainty Analysis

    International Nuclear Information System (INIS)

    Bae, In Ho; Naa, Man Gyun; Lee, Yoon Joon; Park, Goon Cherl

    2009-01-01

    The monitoring of detailed 3-dimensional (3D) reactor core power distribution is a prerequisite in the operation of nuclear power reactors to ensure that various safety limits imposed on the LPD and DNBR, are not violated during nuclear power reactor operation. The LPD and DNBR should be calculated in order to perform the two major functions of the core protection calculator system (CPCS) and the core operation limit supervisory system (COLSS). The LPD at the hottest part of a hot fuel rod, which is related to the power peaking factor (PPF, F q ), is more important than the LPD at any other position in a reactor core. The LPD needs to be estimated accurately to prevent nuclear fuel rods from melting. In this study, support vector regression (SVR) and uncertainty analysis have been applied to estimation of reactor core power peaking factor

  13. Logistic Regression Analysis on Factors Affecting Adoption of Rice-Fish Farming in North Iran

    Directory of Open Access Journals (Sweden)

    Seyyed Ali NOORHOSSEINI-NIYAKI

    2012-06-01

    Full Text Available We evaluated the factors influencing the adoption of rice-fish farming in the Tavalesh region near the Caspian Sea in northern Iran. We conducted a survey with open-ended questions. Data were collected from 184 respondents (61 adopters and 123 non-adopters randomly sampled from selected villages and analyzed using logistic regression and multi-response analysis. Family size, number of contacts with an extension agent, participation in extension-education activities, membership in social institutions and the presence of farm workers were the most important socio-economic factors for the adoption of rice-fish farming system. In addition, economic problems were the most common issue reported by adopters. Other issues such as lack of access to appropriate fish food, losses of fish, lack of access to high quality fish fingerlings and dehydration and poor water quality were also important to a number of farmers.

  14. Managing more than the mean: Using quantile regression to identify factors related to large elk groups

    Science.gov (United States)

    Brennan, Angela K.; Cross, Paul C.; Creely, Scott

    2015-01-01

    Summary Animal group size distributions are often right-skewed, whereby most groups are small, but most individuals occur in larger groups that may also disproportionately affect ecology and policy. In this case, examining covariates associated with upper quantiles of the group size distribution could facilitate better understanding and management of large animal groups.

  15. Identifying factors affecting about outsourcing in paraclinical services

    African Journals Online (AJOL)

    Objective: Outsourcing refers to the transfer of services or functions to an outsider supplier, which controls them through a contract or cooperative. The main problem of senior managers in health organizations is determining the services which should be outsourced. The present study seeks to identify the factors that affect ...

  16. Identifying risk factors that contribute to acute mountain sickness ...

    African Journals Online (AJOL)

    This study is a questionnaire-based study conducted in London and at Everest Base Camp, in which 116 lowlanders were invited to participate and fill in a questionnaire to identify potential risk factors in their history that may have contributed to development of or protection against AMS. Results. A total of 89 lowlanders ...

  17. What Makes Sports Fans Interactive? Identifying Factors Affecting Chat Interactions in Online Sports Viewing.

    Science.gov (United States)

    Ko, Minsam; Yeo, Jaeryong; Lee, Juyeong; Lee, Uichin; Jang, Young Jae

    2016-01-01

    Sports fans are able to watch games from many locations using TV services while interacting with other fans online. In this paper, we identify the factors that affect sports viewers' online interactions. Using a large-scale dataset of more than 25 million chat messages from a popular social TV site for baseball, we extract various game-related factors, and investigate the relationships between these factors and fans' interactions using a series of multiple regression analyses. As a result, we identify several factors that are significantly related to viewer interactions. In addition, we determine that the influence of these factors varies according to the user group; i.e., active vs. less active users, and loyal vs. non-loyal users.

  18. What Makes Sports Fans Interactive? Identifying Factors Affecting Chat Interactions in Online Sports Viewing.

    Directory of Open Access Journals (Sweden)

    Minsam Ko

    Full Text Available Sports fans are able to watch games from many locations using TV services while interacting with other fans online. In this paper, we identify the factors that affect sports viewers' online interactions. Using a large-scale dataset of more than 25 million chat messages from a popular social TV site for baseball, we extract various game-related factors, and investigate the relationships between these factors and fans' interactions using a series of multiple regression analyses. As a result, we identify several factors that are significantly related to viewer interactions. In addition, we determine that the influence of these factors varies according to the user group; i.e., active vs. less active users, and loyal vs. non-loyal users.

  19. What Makes Sports Fans Interactive? Identifying Factors Affecting Chat Interactions in Online Sports Viewing

    Science.gov (United States)

    Yeo, Jaeryong; Lee, Juyeong

    2016-01-01

    Sports fans are able to watch games from many locations using TV services while interacting with other fans online. In this paper, we identify the factors that affect sports viewers’ online interactions. Using a large-scale dataset of more than 25 million chat messages from a popular social TV site for baseball, we extract various game-related factors, and investigate the relationships between these factors and fans’ interactions using a series of multiple regression analyses. As a result, we identify several factors that are significantly related to viewer interactions. In addition, we determine that the influence of these factors varies according to the user group; i.e., active vs. less active users, and loyal vs. non-loyal users. PMID:26849568

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

    Science.gov (United States)

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

    2011-02-01

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

  1. Lung cancer and risk factors: how to identify phenotypic markers?

    International Nuclear Information System (INIS)

    Clement-Duchene, Christelle

    2009-01-01

    Lung cancer is the leading cause of death in the world. Most lung cancer are diagnosed at an advanced stage (IIIB and IV), with a poor prognosis. The main risk factors are well known like active smoking, and occupational exposure (asbestos), but 10 a 20% occur in never smokers. In this population, various studies have been conducted in order to identify possible risk factors, and although many have been identified, none seem to explain more than a small percentage of the cases. According to the histological types, adenocarcinoma is now the more frequent type, and its association with the main risk factors (tobacco exposure, asbestos exposure) is still studied. The tumoral location is associated with the exposure to the risk factors. Finally, the survival seems to be different between gender, and between smokers, and never smokers. All these characteristics are perhaps associated with different pathways of carcinogenesis. In this context, we have analyzed a cohort of 1493 patients with lung cancer in order to identify phenotypic markers, and to understand the mechanisms of the lung carcinogenesis. (author) [fr

  2. Children exposed to intimate partner violence: Identifying differential effects of family environment on children's trauma and psychopathology symptoms through regression mixture models.

    Science.gov (United States)

    McDonald, Shelby Elaine; Shin, Sunny; Corona, Rosalie; Maternick, Anna; Graham-Bermann, Sandra A; Ascione, Frank R; Herbert Williams, James

    2016-08-01

    The majority of analytic approaches aimed at understanding the influence of environmental context on children's socioemotional adjustment assume comparable effects of contextual risk and protective factors for all children. Using self-reported data from 289 maternal caregiver-child dyads, we examined the degree to which there are differential effects of severity of intimate partner violence (IPV) exposure, yearly household income, and number of children in the family on posttraumatic stress symptoms (PTS) and psychopathology symptoms (i.e., internalizing and externalizing problems) among school-age children between the ages of 7-12 years. A regression mixture model identified three latent classes that were primarily distinguished by differential effects of IPV exposure severity on PTS and psychopathology symptoms: (1) asymptomatic with low sensitivity to environmental factors (66% of children), (2) maladjusted with moderate sensitivity (24%), and (3) highly maladjusted with high sensitivity (10%). Children with mothers who had higher levels of education were more likely to be in the maladjusted with moderate sensitivity group than the asymptomatic with low sensitivity group. Latino children were less likely to be in both maladjusted groups compared to the asymptomatic group. Overall, the findings suggest differential effects of family environmental factors on PTS and psychopathology symptoms among children exposed to IPV. Implications for research and practice are discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Neutron Buildup Factors Calculation for Support Vector Regression Application in Shielding Analysis

    International Nuclear Information System (INIS)

    Duckic, P.; Matijevic, M.; Grgic, D.

    2016-01-01

    In this paper initial set of data for neutron buildup factors determination using Support Vector Regression (SVR) method is prepared. The performance of SVR technique strongly depends on the quality of information used for model training. Thus it is very important to provide representable data to the SVR. SVR is a supervised type of learning so it demands data in the input/output form. In the case of neutron buildup factors estimation, the input parameters are the incident neutron energy, shielding thickness and shielding material and the output parameter is the neutron buildup factor value. So far the initial sets of data for different shielding configurations have been obtained using SCALE4.4 sequence SAS3. However, this results were obtained using group constants, thus the incident neutron energy was determined as the average value for each energy group. Obtained this way, the data provided to the SVR are fewer and therefore insufficient. More valuable information is obtained using SCALE6.2beta5 sequence MAVRIC which can perform calculations for the explicit incident neutron energy, which leads to greater maneuvering possibilities when active learning measures are employed, and consequently improves the quality of the developed SVR model.(author).

  4. Changes of platelet GMP-140 in diabetic nephropathy and its multi-factor regression analysis

    International Nuclear Information System (INIS)

    Wang Zizheng; Du Tongxin; Wang Shukui

    2001-01-01

    The relation of platelet GMP-140 and its related factors with diabetic nephropathy was studied. 144 patients of diabetic mellitus without nephropathy (group without DN, mean suffering duration of 25.5 +- 18.6 months); 80 with diabetic nephropathy (group DN, mean suffering duration of 58.7 +- 31.6 months) and 50 normal controls were chosen in the research. Platelet GMP-140, plasma α 1 -MG, β 2 -MG, and 24 hour urine albumin (ALB), IgG, α 1 -MG, β 2 -MG were detected by RIA, while HBA 1 C via chromatographic separation and FBG, PBG, Ch, TG, HDL, FG via biochemical methods. All the data had been processed with software on computer with t-test and linear regression, and multi-factor analysis were done also. The levels of platelet GMP-140, FG, DBP, TG, HBA 1 C and PBG in group DN were significantly higher than those of group without DN and normal control (P 0.05), while they were higher than those of normal controls. Multi-factor analysis of platelet GMP-140 with TG, DBP and HBA 1 C were performed in 80 patients with DN (P 1 C are the independent factors enhancing the activation of platelets. The disturbance of lipid metabolism in type II diabetic mellitus may also enhance the activation of platelets. Elevation of blood pressure may accelerate the initiation and deterioration of DN in which change of platelet GMP-140 is an independent factor. Elevation of HBA 1 C and blood glucose are related closely to the diabetic nephropathy

  5. Identifiable risk factors in hepatitis b and c

    International Nuclear Information System (INIS)

    Rehman, F.U.; Pervez, A.; Rafiq, A.

    2011-01-01

    Background: Both hepatitis B and C are common infections affecting masses and are leading causes of Chronic Liver Disease in Pakistan as well as worldwide. In majority of cases both viral diseases spread by factors that are preventable. The present study is conducted to determine the identifiable risk factors in patients admitted with Chronic Hepatitis B and C. Methods: An observational study was carried out for a period of 6 months. All age groups and both sexes were included. The patients were interviewed and the identifiable risk factors were looked for. The standard methods for detection of Hepatitis B and C were used. Results: One-hundred and ten patients were studied from January to July 2009. Sixty-five patients had Hepatitis C, 35 had Hepatitis B, and 10 had both Hepatitis B and C. Ninety-three patients had a history of injections and transfusions etc., and 38 had surgical scars. Tattoos were present in 42 patients and nose and/or ear piercing marks were present in 28 patients. The number of risk factors increased in co-infection. Conclusion: There is a role of unhygienic health delivery practices, lack of awareness and resources for standard screening protocol for spread of Hepatitis B and C. (author)

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

    Science.gov (United States)

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

    2018-02-01

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

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

    Science.gov (United States)

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

    2015-09-01

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

  8. Identifying Nonprovider Factors Affecting Pediatric Emergency Medicine Provider Efficiency.

    Science.gov (United States)

    Saleh, Fareed; Breslin, Kristen; Mullan, Paul C; Tillett, Zachary; Chamberlain, James M

    2017-10-31

    The aim of this study was to create a multivariable model of standardized relative value units per hour by adjusting for nonprovider factors that influence efficiency. We obtained productivity data based on billing records measured in emergency relative value units for (1) both evaluation and management of visits and (2) procedures for 16 pediatric emergency medicine providers with more than 750 hours worked per year. Eligible shifts were in an urban, academic pediatric emergency department (ED) with 2 sites: a tertiary care main campus and a satellite community site. We used multivariable linear regression to adjust for the impact of shift and pediatric ED characteristics on individual-provider efficiency and then removed variables from the model with minimal effect on productivity. There were 2998 eligible shifts for the 16 providers during a 3-year period. The resulting model included 4 variables when looking at both ED sites combined. These variables include the following: (1) number of procedures billed by provider, (2) season of the year, (3) shift start time, and (4) day of week. Results were improved when we separately modeled each ED location. A 3-variable model using procedures billed by provider, shift start time, and season explained 23% of the variation in provider efficiency at the academic ED site. A 3-variable model using procedures billed by provider, patient arrivals per hour, and shift start time explained 45% of the variation in provider efficiency at the satellite ED site. Several nonprovider factors affect provider efficiency. These factors should be considered when designing productivity-based incentives.

  9. Partial Least Squares Regression for Determining the Control Factors for Runoff and Suspended Sediment Yield during Rainfall Events

    Directory of Open Access Journals (Sweden)

    Nufang Fang

    2015-07-01

    Full Text Available Multivariate statistics are commonly used to identify the factors that control the dynamics of runoff or sediment yields during hydrological processes. However, one issue with the use of conventional statistical methods to address relationships between variables and runoff or sediment yield is multicollinearity. The main objectives of this study were to apply a method for effectively identifying runoff and sediment control factors during hydrological processes and apply that method to a case study. The method combines the clustering approach and partial least squares regression (PLSR models. The case study was conducted in a mountainous watershed in the Three Gorges Area. A total of 29 flood events in three hydrological years in areas with different land uses were obtained. In total, fourteen related variables were separated from hydrographs using the classical hydrograph separation method. Twenty-nine rainfall events were classified into two rainfall regimes (heavy Rainfall Regime I and moderate Rainfall Regime II based on rainfall characteristics and K-means clustering. Four separate PLSR models were constructed to identify the main variables that control runoff and sediment yield for the two rainfall regimes. For Rainfall Regime I, the dominant first-order factors affecting the changes in sediment yield in our study were all of the four rainfall-related variables, flood peak discharge, maximum flood suspended sediment concentration, runoff, and the percentages of forest and farmland. For Rainfall Regime II, antecedent condition-related variables have more effects on both runoff and sediment yield than in Rainfall Regime I. The results suggest that the different control factors of the two rainfall regimes are determined by the rainfall characteristics and thus different runoff mechanisms.

  10. Identifying important motivational factors for professionals in Greek hospitals

    Science.gov (United States)

    Kontodimopoulos, Nick; Paleologou, Victoria; Niakas, Dimitris

    2009-01-01

    Background The purpose of this study was to identify important motivational factors according to the views of health-care professionals in Greek hospitals and particularly to determine if these might differ in the public and private sectors. Methods A previously developed -and validated- instrument addressing four work-related motivators (job attributes, remuneration, co-workers and achievements) was used. Three categories of health care professionals, doctors (N = 354), nurses (N = 581) and office workers (N = 418), working in public and private hospitals, participated and motivation was compared across socio-demographic and occupational variables. Results The range of reported motivational factors was mixed and Maslow's conclusions that lower level motivational factors must be met before ascending to the next level were not confirmed. The highest ranked motivator for the entire sample, and by professional subgroup, was achievements (P motivators were similar, and only one significant difference was observed, namely between doctors and nurses in respect to co-workers (P motivated by all factors significantly more than their public-hospital counterparts. Conclusion The results are in agreement with the literature which focuses attention to management approaches employing both monetary and non-monetary incentives to motivate health care workers. This study showed that intrinsic factors are particularly important and should become a target for effective employee motivation. PMID:19754968

  11. Identifying key hospital service quality factors in online health communities.

    Science.gov (United States)

    Jung, Yuchul; Hur, Cinyoung; Jung, Dain; Kim, Minki

    2015-04-07

    The volume of health-related user-created content, especially hospital-related questions and answers in online health communities, has rapidly increased. Patients and caregivers participate in online community activities to share their experiences, exchange information, and ask about recommended or discredited hospitals. However, there is little research on how to identify hospital service quality automatically from the online communities. In the past, in-depth analysis of hospitals has used random sampling surveys. However, such surveys are becoming impractical owing to the rapidly increasing volume of online data and the diverse analysis requirements of related stakeholders. As a solution for utilizing large-scale health-related information, we propose a novel approach to identify hospital service quality factors and overtime trends automatically from online health communities, especially hospital-related questions and answers. We defined social media-based key quality factors for hospitals. In addition, we developed text mining techniques to detect such factors that frequently occur in online health communities. After detecting these factors that represent qualitative aspects of hospitals, we applied a sentiment analysis to recognize the types of recommendations in messages posted within online health communities. Korea's two biggest online portals were used to test the effectiveness of detection of social media-based key quality factors for hospitals. To evaluate the proposed text mining techniques, we performed manual evaluations on the extraction and classification results, such as hospital name, service quality factors, and recommendation types using a random sample of messages (ie, 5.44% (9450/173,748) of the total messages). Service quality factor detection and hospital name extraction achieved average F1 scores of 91% and 78%, respectively. In terms of recommendation classification, performance (ie, precision) is 78% on average. Extraction and

  12. IDENTIFYING MOTIVATION FACTOR INVOLVEMENT OF SARAWAK MALAY WOMEN ENTREPRENEUR

    Directory of Open Access Journals (Sweden)

    Masyantie Mohamad

    2016-03-01

    Full Text Available Sarawak multilayered cake among Sarawak product signature famous among the local as well as international tourist visiting Sarawak. In fact, Sarawak Malay women entrepreneurs have become very necessary players in the entrepreneurial field specifically in this cottage industries from the early introduction of this business, they have facing various problem in this businesses. Thus, this research aims to build an understanding of motivational factor that encourage Sarawak Malay women entrepreneurial experiences especially in multilayered cake businesses. Using qualitative methods, this research aims to identify the entrepreneurial motivations factors; with regards to start-up motivation by Sarawak Malay women. The finding shows that the motivations that influence Malay women within Kuching, Sarawak areas to start and grow their business are involve self-driven and context driven that motivate them involve in multilayered cakes businesses.

  13. Identifying the customer satisfaction factors in furniture market

    Directory of Open Access Journals (Sweden)

    Majid Azizi

    2017-05-01

    Full Text Available Purpose – the purpose of this research is to identify the influential factors on customer satisfaction in the Iranian furniture market in order to get acquainted with the fundamental items for planning future sales programs with the purposes of extolling competitive advantages. Design/methodology/approach – A commixture of 6 items and 31 factors were educed from interviewing with 20 experts in furniture designing and manufacturing industry. The collected data from customer need indexes in previous research were also used. Findings – results showed that such factors as economic factors weighting 0.32, product specifications weighting 0.21 and credibility weighting 0.19 were the most important indexes and price weighting 0.195, fame weighting 0.131, quality, durability and resistance weighting 0.116, paying conditions weighting 0.095, designing and decorating in virtual softwares before ordering weighting 0.074, updatedness weighting 0.064 and interaction approach with the weight of 0.42 were the most considerable influential sub-indexes on the satisfaction of the Iranian furniture market customers. Research limitations/implications – by the enhancement of competition throughout the world markets and the inevitable presence of Iran in it, the market activists’ concentration should shift towards paying comprehensive attention to desires and needs of furniture market customers. Practical implications – some important issues on planning suitable manufacturing and marketing programs in furniture market are introduce so that the activists be aware of considering the growing knowledge and awareness of end-users which increases the pressure on the manufacturer side. There are also some solutions in terms of internal and external organizational factors with regard to the complex nature of competitive environment in furniture market. Originality/value – the paper provides an examination of effective factors on customer satisfaction with a

  14. Assessing vulnerability to drought: identifying underlying factors across Europe

    Science.gov (United States)

    Urquijo, Julia; Gonzalez Tánago, Itziar; Ballesteros, Mario; De Stefano, Lucia

    2015-04-01

    Drought is considered one of the most severe and damaging natural hazards in terms of people and sectors affected and associated losses. Drought is a normal and recurrent climatic phenomenon that occurs worldwide, although its spatial and temporal characteristics vary significantly among climates. In the case of Europe, in the last thirty years, the region has suffered several drought events that have caused estimated economic damages over a €100 billion and have affected almost 20% of its territory and population. In recent years, there has been a growing awareness among experts and authorities of the need to shift from a reactive crisis approach to a drought risk management approach, as well as of the importance of designing and implementing policies, strategies and plans at country and river basin levels to deal with drought. The identification of whom and what is vulnerable to drought is a central aspect of drought risk mitigation and planning and several authors agree that societal vulnerability often determines drought risk more than the actual precipitation shortfalls. The final aim of a drought vulnerability assessment is to identify the underlying sources of drought impact, in order to develop policy options that help to enhance coping capacity and therefore to prevent drought impact. This study identifies and maps factors underlying vulnerability to drought across Europe. The identification of factors influencing vulnerability starts from the analysis of past drought impacts in four European socioeconomic sectors. This analysis, along with an extensive literature review, led to the selection of vulnerability factors that are both relevant and adequate for the European context. Adopting the IPCC model, vulnerability factors were grouped to describe exposure, sensitivity and adaptive capacity. The aggregation of these components has resulted in the mapping of vulnerability to drought across Europe at NUTS02 level. Final results have been compared with

  15. The likelihood of achieving quantified road safety targets: a binary logistic regression model for possible factors.

    Science.gov (United States)

    Sze, N N; Wong, S C; Lee, C Y

    2014-12-01

    In past several decades, many countries have set quantified road safety targets to motivate transport authorities to develop systematic road safety strategies and measures and facilitate the achievement of continuous road safety improvement. Studies have been conducted to evaluate the association between the setting of quantified road safety targets and road fatality reduction, in both the short and long run, by comparing road fatalities before and after the implementation of a quantified road safety target. However, not much work has been done to evaluate whether the quantified road safety targets are actually achieved. In this study, we used a binary logistic regression model to examine the factors - including vehicle ownership, fatality rate, and national income, in addition to level of ambition and duration of target - that contribute to a target's success. We analyzed 55 quantified road safety targets set by 29 countries from 1981 to 2009, and the results indicate that targets that are in progress and with lower level of ambitions had a higher likelihood of eventually being achieved. Moreover, possible interaction effects on the association between level of ambition and the likelihood of success are also revealed. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Effective factors contraceptive use by logistic regression model in Tehran, 1996

    Directory of Open Access Journals (Sweden)

    Ramezani F

    1999-07-01

    Full Text Available Despite unwillingness to fertility, about 30% of couples do not use any kind of contraception and this will lead to unwanted pregnancy. In this clinical trial study, 4177 subjects who had at least one alive child, and delivered in one of the 12 university hospitals in Tehran were recruited. This study was conducted in 1996. The questionnaire included some questions about contraceptive use, their attitudes about unwantedness or wantedness of their current pregnancies. Data were analysed using a Logistic Regrassion Model. Results showed that 20.3% of those who had no fertility intention, did not use any kind of contraception methods, 41.1% of the subjects who were using a contraception method before pregnancy, had got pregnant unwantedly. Based on Logistic Regression Model; age, education, previous familiarity of women with contraception methods and husband's education were the most significant factors in contraceptive use. Subjects who were 20 years old and less or 35 years old and more and illeterate subjects were at higher risk for unuse of contraception methods. This risk was not related to the gender of their children that suggests a positive change in their perspectives towards sex and the number of children. It is suggested that health politicians choose an appropriate model to enhance the literacy, education and counseling for the correct usage of contraceptives and prevention of unwanted pregnancy.

  17. Perioperative factors predicting poor outcome in elderly patients following emergency general surgery: a multivariate regression analysis

    Science.gov (United States)

    Lees, Mackenzie C.; Merani, Shaheed; Tauh, Keerit; Khadaroo, Rachel G.

    2015-01-01

    Background Older adults (≥ 65 yr) are the fastest growing population and are presenting in increasing numbers for acute surgical care. Emergency surgery is frequently life threatening for older patients. Our objective was to identify predictors of mortality and poor outcome among elderly patients undergoing emergency general surgery. Methods We conducted a retrospective cohort study of patients aged 65–80 years undergoing emergency general surgery between 2009 and 2010 at a tertiary care centre. Demographics, comorbidities, in-hospital complications, mortality and disposition characteristics of patients were collected. Logistic regression analysis was used to identify covariate-adjusted predictors of in-hospital mortality and discharge of patients home. Results Our analysis included 257 patients with a mean age of 72 years; 52% were men. In-hospital mortality was 12%. Mortality was associated with patients who had higher American Society of Anesthesiologists (ASA) class (odds ratio [OR] 3.85, 95% confidence interval [CI] 1.43–10.33, p = 0.008) and in-hospital complications (OR 1.93, 95% CI 1.32–2.83, p = 0.001). Nearly two-thirds of patients discharged home were younger (OR 0.92, 95% CI 0.85–0.99, p = 0.036), had lower ASA class (OR 0.45, 95% CI 0.27–0.74, p = 0.002) and fewer in-hospital complications (OR 0.69, 95% CI 0.53–0.90, p = 0.007). Conclusion American Society of Anesthesiologists class and in-hospital complications are perioperative predictors of mortality and disposition in the older surgical population. Understanding the predictors of poor outcome and the importance of preventing in-hospital complications in older patients will have important clinical utility in terms of preoperative counselling, improving health care and discharging patients home. PMID:26204143

  18. Exploratory Network Meta Regression Analysis of Stroke Prevention in Atrial Fibrillation Fails to Identify Any Interactions with Treatment Effect.

    Science.gov (United States)

    Batson, Sarah; Sutton, Alex; Abrams, Keith

    2016-01-01

    Patients with atrial fibrillation are at a greater risk of stroke and therefore the main goal for treatment of patients with atrial fibrillation is to prevent stroke from occurring. There are a number of different stroke prevention treatments available to include warfarin and novel oral anticoagulants. Previous network meta-analyses of novel oral anticoagulants for stroke prevention in atrial fibrillation acknowledge the limitation of heterogeneity across the included trials but have not explored the impact of potentially important treatment modifying covariates. To explore potentially important treatment modifying covariates using network meta-regression analyses for stroke prevention in atrial fibrillation. We performed a network meta-analysis for the outcome of ischaemic stroke and conducted an exploratory regression analysis considering potentially important treatment modifying covariates. These covariates included the proportion of patients with a previous stroke, proportion of males, mean age, the duration of study follow-up and the patients underlying risk of ischaemic stroke. None of the covariates explored impacted relative treatment effects relative to placebo. Notably, the exploration of 'study follow-up' as a covariate supported the assumption that difference in trial durations is unimportant in this indication despite the variation across trials in the network. This study is limited by the quantity of data available. Further investigation is warranted, and, as justifying further trials may be difficult, it would be desirable to obtain individual patient level data (IPD) to facilitate an effort to relate treatment effects to IPD covariates in order to investigate heterogeneity. Observational data could also be examined to establish if there are potential trends elsewhere. The approach and methods presented have potentially wide applications within any indication as to highlight the potential benefit of extending decision problems to include additional

  19. Exploratory Network Meta Regression Analysis of Stroke Prevention in Atrial Fibrillation Fails to Identify Any Interactions with Treatment Effect.

    Directory of Open Access Journals (Sweden)

    Sarah Batson

    Full Text Available Patients with atrial fibrillation are at a greater risk of stroke and therefore the main goal for treatment of patients with atrial fibrillation is to prevent stroke from occurring. There are a number of different stroke prevention treatments available to include warfarin and novel oral anticoagulants. Previous network meta-analyses of novel oral anticoagulants for stroke prevention in atrial fibrillation acknowledge the limitation of heterogeneity across the included trials but have not explored the impact of potentially important treatment modifying covariates.To explore potentially important treatment modifying covariates using network meta-regression analyses for stroke prevention in atrial fibrillation.We performed a network meta-analysis for the outcome of ischaemic stroke and conducted an exploratory regression analysis considering potentially important treatment modifying covariates. These covariates included the proportion of patients with a previous stroke, proportion of males, mean age, the duration of study follow-up and the patients underlying risk of ischaemic stroke.None of the covariates explored impacted relative treatment effects relative to placebo. Notably, the exploration of 'study follow-up' as a covariate supported the assumption that difference in trial durations is unimportant in this indication despite the variation across trials in the network.This study is limited by the quantity of data available. Further investigation is warranted, and, as justifying further trials may be difficult, it would be desirable to obtain individual patient level data (IPD to facilitate an effort to relate treatment effects to IPD covariates in order to investigate heterogeneity. Observational data could also be examined to establish if there are potential trends elsewhere. The approach and methods presented have potentially wide applications within any indication as to highlight the potential benefit of extending decision problems to

  20. Identifying Human Factors Issues in Aircraft Maintenance Operations

    Science.gov (United States)

    Veinott, Elizabeth S.; Kanki, Barbara G.; Shafto, Michael G. (Technical Monitor)

    1995-01-01

    Maintenance operations incidents submitted to the Aviation Safety Reporting System (ASRS) between 1986-1992 were systematically analyzed in order to identify issues relevant to human factors and crew coordination. This exploratory analysis involved 95 ASRS reports which represented a wide range of maintenance incidents. The reports were coded and analyzed according to the type of error (e.g, wrong part, procedural error, non-procedural error), contributing factors (e.g., individual, within-team, cross-team, procedure, tools), result of the error (e.g., aircraft damage or not) as well as the operational impact (e.g., aircraft flown to destination, air return, delay at gate). The main findings indicate that procedural errors were most common (48.4%) and that individual and team actions contributed to the errors in more than 50% of the cases. As for operational results, most errors were either corrected after landing at the destination (51.6%) or required the flight crew to stop enroute (29.5%). Interactions among these variables are also discussed. This analysis is a first step toward developing a taxonomy of crew coordination problems in maintenance. By understanding what variables are important and how they are interrelated, we may develop intervention strategies that are better tailored to the human factor issues involved.

  1. Novel Application of Statistical Methods to Identify New Urinary Incontinence Risk Factors

    Directory of Open Access Journals (Sweden)

    Theophilus O. Ogunyemi

    2012-01-01

    Full Text Available Longitudinal data for studying urinary incontinence (UI risk factors are rare. Data from one study, the hallmark Medical, Epidemiological, and Social Aspects of Aging (MESA, have been analyzed in the past; however, repeated measures analyses that are crucial for analyzing longitudinal data have not been applied. We tested a novel application of statistical methods to identify UI risk factors in older women. MESA data were collected at baseline and yearly from a sample of 1955 men and women in the community. Only women responding to the 762 baseline and 559 follow-up questions at one year in each respective survey were examined. To test their utility in mining large data sets, and as a preliminary step to creating a predictive index for developing UI, logistic regression, generalized estimating equations (GEEs, and proportional hazard regression (PHREG methods were used on the existing MESA data. The GEE and PHREG combination identified 15 significant risk factors associated with developing UI out of which six of them, namely, urinary frequency, urgency, any urine loss, urine loss after emptying, subject’s anticipation, and doctor’s proactivity, are found most highly significant by both methods. These six factors are potential candidates for constructing a future UI predictive index.

  2. Deriving amplification factors from simple site parameters using generalized regression neural networks: implications for relevant site proxies

    Science.gov (United States)

    Boudghene Stambouli, Ahmed; Zendagui, Djawad; Bard, Pierre-Yves; Derras, Boumédiène

    2017-07-01

    Most modern seismic codes account for site effects using an amplification factor (AF) that modifies the rock acceleration response spectra in relation to a "site condition proxy," i.e., a parameter related to the velocity profile at the site under consideration. Therefore, for practical purposes, it is interesting to identify the site parameters that best control the frequency-dependent shape of the AF. The goal of the present study is to provide a quantitative assessment of the performance of various site condition proxies to predict the main AF features, including the often used short- and mid-period amplification factors, Fa and Fv, proposed by Borcherdt (in Earthq Spectra 10:617-653, 1994). In this context, the linear, viscoelastic responses of a set of 858 actual soil columns from Japan, the USA, and Europe are computed for a set of 14 real accelerograms with varying frequency contents. The correlation between the corresponding site-specific average amplification factors and several site proxies (considered alone or as multiple combinations) is analyzed using the generalized regression neural network (GRNN). The performance of each site proxy combination is assessed through the variance reduction with respect to the initial amplification factor variability of the 858 profiles. Both the whole period range and specific short- and mid-period ranges associated with the Borcherdt factors Fa and Fv are considered. The actual amplification factor of an arbitrary soil profile is found to be satisfactorily approximated with a limited number of site proxies (4-6). As the usual code practice implies a lower number of site proxies (generally one, sometimes two), a sensitivity analysis is conducted to identify the "best performing" site parameters. The best one is the overall velocity contrast between underlying bedrock and minimum velocity in the soil column. Because these are the most difficult and expensive parameters to measure, especially for thick deposits, other

  3. Identifying risk factors for victimization among male prisoners in Taiwan.

    Science.gov (United States)

    Kuo, Shih-Ya; Cuvelier, Steven J; Huang, Yung-Shun

    2014-02-01

    This study identified risk factors for prison victimization in Taiwan with an application of Western literature and assessed the extent of its applicability in an Eastern context. The sample was drawn from four male prisons located in Northern, Central, Southern, and Eastern Taiwan; a total of 1,181 valid surveys were collected. The results generally support the major findings of the extant Western studies. Crowding, however, was not significantly associated with the risk of victimization in any of the statistical models, which might be related to the different experiences and living conditions in the free community between Taiwanese and American inmates. This study generated clear policy implications, which may reduce prison victimization and engender a greater sense of well-being in the prison environment.

  4. Anterior cruciate ligament injury: Identifying information sources and risk factor awareness among the general population.

    Directory of Open Access Journals (Sweden)

    Yasuharu Nagano

    Full Text Available Raising awareness on a disorder is important for its prevention and for promoting public health. However, for sports injuries like the anterior cruciate ligament (ACL injury no studies have investigated the awareness on risk factors for injury and possible preventative measures in the general population. The sources of information among the population are also unclear. The purpose of the present study was to identify these aspects of public awareness about the ACL injury.A questionnaire was randomly distributed among the general population registered with a web based questionnaire supplier, to recruit 900 participants who were aware about the ACL injury. The questionnaire consisted of two parts: Question 1 asked them about their sources of information regarding the ACL injury; Question 2 asked them about the risk factors for ACL injury. Multivariate logistic regression was used to determine the information sources that provide a good understanding of the risk factors.The leading source of information for ACL injury was television (57.0%. However, the results of logistic regression analysis revealed that television was not an effective medium to create awareness about the risk factors, among the general population. Instead "Lecture by a coach", "Classroom session on Health", and "Newspaper" were significantly more effective in creating a good awareness of the risk factors (p < 0.001.

  5. Total-Factor Energy Efficiency (TFEE Evaluation on Thermal Power Industry with DEA, Malmquist and Multiple Regression Techniques

    Directory of Open Access Journals (Sweden)

    Jin-Peng Liu

    2017-07-01

    Full Text Available Under the background of a new round of power market reform, realizing the goals of energy saving and emission reduction, reducing the coal consumption and ensuring the sustainable development are the key issues for thermal power industry. With the biggest economy and energy consumption scales in the world, China should promote the energy efficiency of thermal power industry to solve these problems. Therefore, from multiple perspectives, the factors influential to the energy efficiency of thermal power industry were identified. Based on the economic, social and environmental factors, a combination model with Data Envelopment Analysis (DEA and Malmquist index was constructed to evaluate the total-factor energy efficiency (TFEE in thermal power industry. With the empirical studies from national and provincial levels, the TFEE index can be factorized into the technical efficiency index (TECH, the technical progress index (TPCH, the pure efficiency index (PECH and the scale efficiency index (SECH. The analysis showed that the TFEE was mainly determined by TECH and PECH. Meanwhile, by panel data regression model, unit coal consumption, talents and government supervision were selected as important indexes to have positive effects on TFEE in thermal power industry. In addition, the negative indexes, such as energy price and installed capacity, were also analyzed to control their undesired effects. Finally, considering the analysis results, measures for improving energy efficiency of thermal power industry were discussed widely, such as strengthening technology research and design (R&D, enforcing pollutant and emission reduction, distributing capital and labor rationally and improving the government supervision. Relative study results and suggestions can provide references for Chinese government and enterprises to enhance the energy efficiency level.

  6. A new multiple regression model to identify multi-family houses with a high prevalence of sick building symptoms "SBS", within the healthy sustainable house study in Stockholm (3H).

    Science.gov (United States)

    Engvall, Karin; Hult, M; Corner, R; Lampa, E; Norbäck, D; Emenius, G

    2010-01-01

    The aim was to develop a new model to identify residential buildings with higher frequencies of "SBS" than expected, "risk buildings". In 2005, 481 multi-family buildings with 10,506 dwellings in Stockholm were studied by a new stratified random sampling. A standardised self-administered questionnaire was used to assess "SBS", atopy and personal factors. The response rate was 73%. Statistical analysis was performed by multiple logistic regressions. Dwellers owning their building reported less "SBS" than those renting. There was a strong relationship between socio-economic factors and ownership. The regression model, ended up with high explanatory values for age, gender, atopy and ownership. Applying our model, 9% of all residential buildings in Stockholm were classified as "risk buildings" with the highest proportion in houses built 1961-1975 (26%) and lowest in houses built 1985-1990 (4%). To identify "risk buildings", it is necessary to adjust for ownership and population characteristics.

  7. Factor Analysis of Therapist-Identified Treatment Targets in Community-Based Children's Mental Health.

    Science.gov (United States)

    Love, Allison R; Okado, Izumi; Orimoto, Trina E; Mueller, Charles W

    2018-01-01

    The present study used exploratory and confirmatory factor analyses to identify underlying latent factors affecting variation in community therapists' endorsement of treatment targets. As part of a statewide practice management program, therapist completed monthly reports of treatment targets (up to 10 per month) for a sample of youth (n = 790) receiving intensive in-home therapy. Nearly 75 % of youth were diagnosed with multiple co-occurring disorders. Five factors emerged: Disinhibition, Societal Rules Evasion, Social Engagement Deficits, Emotional Distress, and Management of Biodevelopmental Outcomes. Using logistic regression, primary diagnosis predicted therapist selection of Disinhibition and Emotional Distress targets. Client age predicted endorsement of Societal Rules Evasion targets. Practice-to-research implications are discussed.

  8. The mechanical properties of high speed GTAW weld and factors of nonlinear multiple regression model under external transverse magnetic field

    Science.gov (United States)

    Lu, Lin; Chang, Yunlong; Li, Yingmin; He, Youyou

    2013-05-01

    A transverse magnetic field was introduced to the arc plasma in the process of welding stainless steel tubes by high-speed Tungsten Inert Gas Arc Welding (TIG for short) without filler wire. The influence of external magnetic field on welding quality was investigated. 9 sets of parameters were designed by the means of orthogonal experiment. The welding joint tensile strength and form factor of weld were regarded as the main standards of welding quality. A binary quadratic nonlinear regression equation was established with the conditions of magnetic induction and flow rate of Ar gas. The residual standard deviation was calculated to adjust the accuracy of regression model. The results showed that, the regression model was correct and effective in calculating the tensile strength and aspect ratio of weld. Two 3D regression models were designed respectively, and then the impact law of magnetic induction on welding quality was researched.

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

    Directory of Open Access Journals (Sweden)

    Xi Yu

    2014-01-01

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

  10. Regression Levels of Selected Affective Factors on Science Achievement: A Structural Equation Model with TIMSS 2011 Data

    Science.gov (United States)

    Akilli, Mustafa

    2015-01-01

    The aim of this study is to demonstrate the science success regression levels of chosen emotional features of 8th grade students using Structural Equation Model. The study was conducted by the analysis of students' questionnaires and science success in TIMSS 2011 data using SEM. Initially, the factors that are thought to have an effect on science…

  11. Evaluating risk factors for endemic human Salmonella Enteritidis infections with different phage types in Ontario, Canada using multinomial logistic regression and a case-case study approach

    Directory of Open Access Journals (Sweden)

    Varga Csaba

    2012-10-01

    Full Text Available Abstract Background Identifying risk factors for Salmonella Enteritidis (SE infections in Ontario will assist public health authorities to design effective control and prevention programs to reduce the burden of SE infections. Our research objective was to identify risk factors for acquiring SE infections with various phage types (PT in Ontario, Canada. We hypothesized that certain PTs (e.g., PT8 and PT13a have specific risk factors for infection. Methods Our study included endemic SE cases with various PTs whose isolates were submitted to the Public Health Laboratory-Toronto from January 20th to August 12th, 2011. Cases were interviewed using a standardized questionnaire that included questions pertaining to demographics, travel history, clinical symptoms, contact with animals, and food exposures. A multinomial logistic regression method using the Generalized Linear Latent and Mixed Model procedure and a case-case study design were used to identify risk factors for acquiring SE infections with various PTs in Ontario, Canada. In the multinomial logistic regression model, the outcome variable had three categories representing human infections caused by SE PT8, PT13a, and all other SE PTs (i.e., non-PT8/non-PT13a as a referent category to which the other two categories were compared. Results In the multivariable model, SE PT8 was positively associated with contact with dogs (OR=2.17, 95% CI 1.01-4.68 and negatively associated with pepper consumption (OR=0.35, 95% CI 0.13-0.94, after adjusting for age categories and gender, and using exposure periods and health regions as random effects to account for clustering. Conclusions Our study findings offer interesting hypotheses about the role of phage type-specific risk factors. Multinomial logistic regression analysis and the case-case study approach are novel methodologies to evaluate associations among SE infections with different PTs and various risk factors.

  12. Identifying Sociological Factors for the Success of Space Exploration

    Science.gov (United States)

    Lundquist, C. A.; Tarter, D.; Coleman, A.

    Astrosociology factors relevant to success of future space exploration may best be identified through studies of sociological circumstances of past successful explorations, such as the Apollo-Lunar Missions. These studies benefit from access to primary records of the past programs. The Archives and Special Collections Division of the Salmon Library at the University of Alabama Huntsville (UAH) houses large collections of material from the early periods of the space age. The Huntsville campus of the University of Alabama System had its birth in the mid-1950s at the time when the von Braun rocket team was relocated from Texas to Huntsville. The University, the City of Huntsville and the US Government rocket organizations developed in parallel over subsequent years. As a result, the University has a significant space heritage and focus. This is true not only for the engineering and science disciplines, but also for the social sciences. The life of the University spans the period when Huntsville government and industrial organizations were responsible for producing the rocket vehicles to first take mankind to the Moon. That endeavor was surely as significant sociologically as technologically. In the 1980s, Donald E. Tarter, conducted a series of video interviews with some leading members of the original von Braun team. Although the interviews ranged over many engineering subjects, they also recorded personal features of people involved in the Apollo lunar exploration program and the interactions between these people. Such knowledge was of course an objective. These interviews are now in the collections of the UAH Library Archives, along with extensive documentation from the same period. Under sponsorship of the Archives and the NASA-Marshall Retiree Association, the interview series was restarted in 2006 to obtain comparable oral-history interviews with more than fifty US born members of the rocket team from the 1960s. Again these video interviews are rich with

  13. 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.

  14. Identifying factors causing cost overrun of the construction projects ...

    Indian Academy of Sciences (India)

    Swapnil P Wanjari

    Cost overrun in India; ANOVA; factor analysis; construction projects. 1. Introduction ... gramme Implementation in India [2], projects of public .... case if a respondent never came across of such factor. ..... The co-relation matrix for variables of cost overruns was ..... There are various problems observed due to communication.

  15. Sensitivity of Microstructural Factors Influencing the Impact Toughness of Hypoeutectoid Steels with Ferrite-Pearlite Structure using Multiple Regression Analysis

    International Nuclear Information System (INIS)

    Lee, Seung-Yong; Lee, Sang-In; Hwang, Byoung-chul

    2016-01-01

    In this study, the effect of microstructural factors on the impact toughness of hypoeutectoid steels with ferrite-pearlite structure was quantitatively investigated using multiple regression analysis. Microstructural analysis results showed that the pearlite fraction increased with increasing austenitizing temperature and decreasing transformation temperature which substantially decreased the pearlite interlamellar spacing and cementite thickness depending on carbon content. The impact toughness of hypoeutectoid steels usually increased as interlamellar spacing or cementite thickness decreased, although the impact toughness was largely associated with pearlite fraction. Based on these results, multiple regression analysis was performed to understand the individual effect of pearlite fraction, interlamellar spacing, and cementite thickness on the impact toughness. The regression analysis results revealed that pearlite fraction significantly affected impact toughness at room temperature, while cementite thickness did at low temperature.

  16. Identifying risk factors that contribute to acute mountain sickness

    African Journals Online (AJOL)

    Acute mountain sickness (AMS) is an ever-increasing burden on the health sector. With reported incidences .... schedule to reduce the likelihood of AMS. The data ... of Health and. Multidisciplinary Board on Exercise to identify individuals who.

  17. Clinicopathologic factors identify sporadic mismatch repair-defective colon cancers

    DEFF Research Database (Denmark)

    Halvarsson, Britta; Anderson, Harald; Domanska, Katarina

    2008-01-01

    Identification of sporadic mismatch repair (MMR)-defective colon cancers is increasingly demanded for decisions on adjuvant therapies. We evaluated clinicopathologic factors for the identification of these prognostically favorable tumors. Histopathologic features in 238 consecutive colon cancers...

  18. Identifying and ranking the factors affecting the adoption of biofuels

    OpenAIRE

    Saeed Azizi; Fattaneh Alizadeh Meshkani; Reza Agha Mousa

    2016-01-01

    This paper presents an empirical investigation to determine the important factors influencing on adoption of biofuels from consumer’s perspective. The study designs a questionnaire in Likert scale and distributes it among 211 randomly selected people who use green products in city of Tehran, Iran. Cronbach alpha is calculated as 0.812, which is well above the acceptable level. Using principle component with Varimax rotation, the study has determined five important factors including social com...

  19. Identifying the bleeding trauma patient: predictive factors for massive transfusion in an Australasian trauma population.

    Science.gov (United States)

    Hsu, Jeremy Ming; Hitos, Kerry; Fletcher, John P

    2013-09-01

    Military and civilian data would suggest that hemostatic resuscitation results in improved outcomes for exsanguinating patients. However, identification of those patients who are at risk of significant hemorrhage is not clearly defined. We attempted to identify factors that would predict the need for massive transfusion (MT) in an Australasian trauma population, by comparing those trauma patients who did receive massive transfusion with those who did not. Between 1985 and 2010, 1,686 trauma patients receiving at least 1 U of packed red blood cells were identified from our prospectively maintained trauma registry. Demographic, physiologic, laboratory, injury, and outcome variables were reviewed. Univariate analysis determined significant factors between those who received MT and those who did not. A predictive multivariate logistic regression model with backward conditional stepwise elimination was used for MT risk. Statistical analysis was performed using SPSS PASW. MT patients had a higher pulse rate, lower Glasgow Coma Scale (GCS) score, lower systolic blood pressure, lower hemoglobin level, higher Injury Severity Score (ISS), higher international normalized ratio (INR), and longer stay. Initial logistic regression identified base deficit (BD), INR, and hemoperitoneum at laparotomy as independent predictive variables. After assigning cutoff points of BD being greater than 5 and an INR of 1.5 or greater, a further model was created. A BD greater than 5 and either INR of 1.5 or greater or hemoperitoneum was associated with 51 times increase in MT risk (odds ratio, 51.6; 95% confidence interval, 24.9-95.8). The area under the receiver operating characteristic curve for the model was 0.859. From this study, a combination of BD, INR, and hemoperitoneum has demonstrated good predictability for MT. This tool may assist in the determination of those patients who might benefit from hemostatic resuscitation. Prognostic study, level III.

  20. Identifying risk factors associated with smear positivity of pulmonary tuberculosis in Kazakhstan.

    Directory of Open Access Journals (Sweden)

    Sabrina Hermosilla

    Full Text Available Sputum smear-positive tuberculosis (TB patients have a high risk of transmission and are of great epidemiological and infection control significance. Little is known about the smear-positive populations in high TB burden regions, such as Kazakhstan. The objective of this study is to characterize the smear-positive population in Kazakhstan and identify associated modifiable risk factors.Data on incident TB cases' (identified between April 2012 and March 2014 socio-demographic, risk behavior, and comorbidity characteristics were collected in four regions of Kazakhstan through structured survey and medical record review. We used multivariable logistic regression to determine factors associated with smear positivity.Of the total sample, 193 (34.3% of the 562 study participants tested smear-positive. In the final adjusted multivariable logistic regression model, sex (adjusted odds ratio (aOR = 2.0, 95% CI:1.3-3.1, p < 0.01, incarceration (aOR = 3.6, 95% CI:1.2-11.1, p = 0.03, alcohol dependence (aOR = 2.6, 95% CI:1.2-5.7, p = 0.02, diabetes (aOR = 5.0, 95% CI:2.4-10.7, p < 0.01, and physician access (aOR = 2.7, 95% CI:1.3-5.5p < 0.01 were associated with smear-positivity.Incarceration, alcohol dependence, diabetes, and physician access are associated with smear positivity among incident TB cases in Kazakhstan. To stem the TB epidemic, screening, treatment and prevention policies should address these factors.

  1. Ultrasound-enhanced bioscouring of greige cotton: regression analysis of process factors

    Science.gov (United States)

    Ultrasound-enhanced bioscouring process factors for greige cotton fabric are examined using custom experimental design utilizing statistical principles. An equation is presented which predicts bioscouring performance based upon percent reflectance values obtained from UV-Vis measurements of rutheniu...

  2. Using Structured Additive Regression Models to Estimate Risk Factors of Malaria: Analysis of 2010 Malawi Malaria Indicator Survey Data

    Science.gov (United States)

    Chirombo, James; Lowe, Rachel; Kazembe, Lawrence

    2014-01-01

    Background After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. Methods We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. Results Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. Conclusions The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities. PMID:24991915

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

    Directory of Open Access Journals (Sweden)

    Earl Chrysler

    2003-02-01

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

  4. Identifying and ranking the factors affecting the adoption of biofuels

    Directory of Open Access Journals (Sweden)

    Saeed Azizi

    2016-09-01

    Full Text Available This paper presents an empirical investigation to determine the important factors influencing on adoption of biofuels from consumer’s perspective. The study designs a questionnaire in Likert scale and distributes it among 211 randomly selected people who use green products in city of Tehran, Iran. Cronbach alpha is calculated as 0.812, which is well above the acceptable level. Using principle component with Varimax rotation, the study has determined five important factors including social commitment, product usefulness, infrastructure, management approach and customer oriented, which influence the most on adaptation of biofuels.

  5. X-factor for innovation: identifying future excellent professionals

    NARCIS (Netherlands)

    den Hertog, J.H.

    2016-01-01

    In this study we wanted to identify which type of individual is capable of achieving professional excellence. Our main question therefore read: which individual antecedents predict professional excellence? We chose to focus on personality traits and specifically on proactive personality - the

  6. Clinicopathologic factors identify sporadic mismatch repair-defective colon cancers

    DEFF Research Database (Denmark)

    Halvarsson, Britta; Anderson, Harald; Domanska, Katarina

    2008-01-01

    Identification of sporadic mismatch repair (MMR)-defective colon cancers is increasingly demanded for decisions on adjuvant therapies. We evaluated clinicopathologic factors for the identification of these prognostically favorable tumors. Histopathologic features in 238 consecutive colon cancers...... and excluded 61.5% of the tumors from MMR testing. This clinicopathologic index thus successfully selects MMR-defective colon cancers. Udgivelsesdato: 2008-Feb...

  7. Determining the Factors of Social Phobia Levels of University Students: A Logistic Regression Analysis

    Science.gov (United States)

    Ozen, Hamit

    2016-01-01

    Experiencing social phobia is an important factor which can hinder academic success during university years. In this study, research of social phobia with several variables is conducted among university students. The research group of the study consists of total 736 students studying at various departments at universities in Turkey. Students are…

  8. Factors Affecting University Entrants' Performance in High-Stakes Tests: A Multiple Regression Analysis

    Science.gov (United States)

    Uy, Chin; Manalo, Ronaldo A.; Cabauatan, Ronaldo R.

    2015-01-01

    In the Philippines, students seeking admission to a university are usually required to meet certain entrance requirements, including passing the entrance examinations with questions on IQ and English, mathematics, and science. This paper aims to determine the factors that affect the performance of entrants into business programmes in high-stakes…

  9. Factors Associated with Increased Pain in Primary Dysmenorrhea: Analysis Using a Multivariate Ordered Logistic Regression Model.

    Science.gov (United States)

    Tomás-Rodríguez, María I; Palazón-Bru, Antonio; Martínez-St John, Damian R J; Navarro-Cremades, Felipe; Toledo-Marhuenda, José V; Gil-Guillén, Vicente F

    2017-04-01

    In the literature about primary dysmenorrhea (PD), either a pain gradient has been studied just in women with PD or pain was assessed as a binary variable (presence or absence). Accordingly, we decided to carry out a study in young women to determine possible factors associated with intense pain. A cross-sectional observational study. A Spanish University in 2016. A total of 306 women, aged 18-30 years. A questionnaire was filled in by the participants to assess associated factors with dysmenorrhoea. Our outcome measure was the Andersch and Milsom scale (grade from 0 to 3). grade 0 (menstruation is not painful and daily activity is unaffected), grade 1 (menstruation is painful but seldom inhibits normal activity, analgesics are seldom required, and mild pain), grade 2 (daily activity affected, analgesics required and give relief so that absence from work or school is unusual, and moderate pain), and grade 3 (activity clearly inhibited, poor effect of analgesics, vegetative symptoms and severe pain). Factors significantly associated with more extreme pain: a higher menstrual flow (odds ratio [OR], 2.11; P < .001), a worse quality of life (OR, 0.97; P < .001) and use of medication for PD (OR, 8.22; P < .001). We determined factors associated with extreme pain in PD in a novel way. Further studies are required to corroborate our results. Copyright © 2016 North American Society for Pediatric and Adolescent Gynecology. Published by Elsevier Inc. All rights reserved.

  10. Identifying landscape factors affecting tiger decline in the Bangladesh Sundarbans

    Directory of Open Access Journals (Sweden)

    Abu Naser Mohsin Hossain

    2018-01-01

    Full Text Available The Sundarbans Forest (∼10,000 km2 represents the only mangrove ecosystem inhabited by tigers Panthera tigris. However, in the Bangladesh portion of the Sundarbans (∼6,000 km2 tigers appear to have declined. The aim of this study was to examine the influence of a range of environmental and landscape variables in possible changes in the relative abundance of tigers in the Bangladesh Sundarbans over a five-year period (2007–2011. In 2007, 2011 tiger relative abundance was assessed using sign surveys. Using regression models we investigated changes in relative abundance versus multiple landscape variables (human disturbance associated with villages and commercial shipping lanes, distance to the international border with India where there is enhanced patrolling, presence of forest guard stations, number of criminal prosecutions and forest protection status. Tiger relative abundance was higher in 2007 and declined by 2011 with changes best explained by the proximity to international boundaries. This result might have been affected by the high levels of security patrols at the India-Bangladesh border along with cross border tiger movement between India and Bangladesh. Neighboring tiger range countries could strengthen cross-border law enforcement, increasing protection of dispersing animals. Particularly alarming was the absence of a positive effect of protected areas relative to those outside the protected area system or forest guard stations, implying a lack of management effectiveness suggesting an urgent need for an improved strategy for managing tigers and their habitats. Keywords: Wildlife poaching, Population declines, Transboundary protection, Joint patrolling, Protected area effectiveness

  11. Human-automation collaboration in manufacturing: identifying key implementation factors

    OpenAIRE

    Charalambous, George; Fletcher, Sarah; Webb, Philip

    2013-01-01

    Human-automation collaboration refers to the concept of human operators and intelligent automation working together interactively within the same workspace without conventional physical separation. This concept has commanded significant attention in manufacturing because of the potential applications, such as the installation of large sub-assemblies. However, the key human factors relevant to human-automation collaboration have not yet been fully investigated. To maximise effective implement...

  12. Support vector regression model for the estimation of γ-ray buildup factors for multi-layer shields

    International Nuclear Information System (INIS)

    Trontl, Kresimir; Smuc, Tomislav; Pevec, Dubravko

    2007-01-01

    The accuracy of the point-kernel method, which is a widely used practical tool for γ-ray shielding calculations, strongly depends on the quality and accuracy of buildup factors used in the calculations. Although, buildup factors for single-layer shields comprised of a single material are well known, calculation of buildup factors for stratified shields, each layer comprised of different material or a combination of materials, represent a complex physical problem. Recently, a new compact mathematical model for multi-layer shield buildup factor representation has been suggested for embedding into point-kernel codes thus replacing traditionally generated complex mathematical expressions. The new regression model is based on support vector machines learning technique, which is an extension of Statistical Learning Theory. The paper gives complete description of the novel methodology with results pertaining to realistic engineering multi-layer shielding geometries. The results based on support vector regression machine learning confirm that this approach provides a framework for general, accurate and computationally acceptable multi-layer buildup factor model

  13. Predicting Factors of INSURE Failure in Low Birth Weight Neonates with RDS; A Logistic Regression Model

    OpenAIRE

    Bita Najafian; Aminsaburi Aminsaburi; Seyyed Hassan Fakhraei; Abolfazl afjeh; Fatemeh Eghbal; Reza Noroozian

    2015-01-01

    Background:Respiratory Distress syndrome is the most common respiratory disease in premature neonate and the most important cause of death among them. We aimed to investigate factors to predict successful or failure of INSURE method as a therapeutic method of RDS. Methods:In a cohort study,45 neonates with diagnosed RDS and birth weight lower than 1500g were included and they underwent INSURE followed by NCPAP(Nasal Continuous Positive Airway Pressure). The patients were divided into failu...

  14. Use of clinical risk factors to identify postmenopausal women with vertebral fractures.

    Science.gov (United States)

    Tobias, J H; Hutchinson, A P; Hunt, L P; McCloskey, E V; Stone, M D; Martin, J C; Thompson, P W; Palferman, T G; Bhalla, A K

    2007-01-01

    Previous studies have been unable to identify risk factors for prevalent vertebral fractures (VF), which are suitable for use in selection strategies intended to target high-risk sub-groups for diagnostic assessment. However, these studies generally consisted of large epidemiology surveys based on questionnaires and were only able to evaluate a limited number of risk factors. Here, we investigated whether a stronger relationship exists with prevalent VF when conventional risk factors are combined with additional information obtained from detailed one-to-one assessment. Women aged 65-75 registered at four geographically distinct GP practices were invited to participate (n=1,518), of whom 540 attended for assessment as follows: a questionnaire asking about risk factors for osteoporosis such as height loss compared to age 25 and history of non-vertebral fracture (NVF), the get-up-and-go test, Margolis back pain score, measurement of wall-tragus and rib-pelvis distances, and BMD as measured by the distal forearm BMD. A lateral thoraco-lumbar spine X-ray was obtained, which was subsequently scored for the presence of significant vertebral deformities. Of the 509 subjects who underwent spinal radiographs, 37 (7.3%) were found to have one or more VF. Following logistic regression analysis, the four most predictive clinical risk factors for prevalent VF were: height loss (P=0.006), past NVF (P=0.004), history of back pain (P=0.075) and age (P=0.05). BMD was also significantly associated with prevalent VF (P=0.002), but its inclusion did not affect associations with other variables. Factors elicited from detailed one-to-one assessment were not related to the risk of one or more prevalent VFs. The area under ROC curves derived from these regressions, which suggested that models for prevalent VF had modest predictive accuracy, were as follows: 0.68 (BMD), 0.74 (four clinical risk factors above) and 0.78 (clinical risk factors + BMD). Analyses were repeated in relation to the

  15. [Identifying clinical risk factors in recurrent idiopathic deep venous thrombosis].

    Science.gov (United States)

    Del Río Solá, M Lourdes; González Fajardo, José Antonio; Vaquero Puerta, Carlos

    2016-03-18

    Oral anticoagulant therapy for more than 6 months in patients with an episode of idiopathic thromboembolic disease is controversial. The objective was to determine predictive clinical signs that identify patients at increased risk of thromboembolic recurrence after stopping anticoagulant therapy for 6 months after an episode of idiopathic deep vein thrombosis (DVT). A prospective study which included 306 consecutive patients with a first episode of idiopathic DVT from June 2012 to June 2014. Predictor variables of recurrent thromboembolic disease and episodes of recurrence during follow-up of the patients (28.42 months) were collected. We performed a multivariate analysis to analyze possible predictors (Pthrombus (P=.001) in males, and persistence of residual thrombus in women (P=.046). The mean recurrence-free survival was shorter in both groups. The presence of echogenic thrombus in men and the existence of residual DVT in women were 2 clinical signs associated with increased risk of thromboembolic recurrence after stopping anticoagulant therapy for 6 months after an episode of idiopathic DVT in our study. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

  16. Identifying factors contributing to slow growth in pigs.

    Science.gov (United States)

    He, Y; Deen, J; Shurson, G C; Wang, L; Chen, C; Keisler, D H; Li, Y Z

    2016-05-01

    Pigs that grow slower than their contemporaries can cause complications for animal welfare and profitability. This study was conducted to investigate factors that may contribute to slow growth of pigs. Pigs ( = 440) farrowed by 65 sows were monitored from birth to market. Pigs were categorized as slow, average, and fast growers based on market weight adjusted to 170 d of age (slow growers were 125 kg). Blood samples were collected from 48 focal pigs at 9 and 21 wk of age and analyzed for hormone and free AA concentrations. Data were analyzed using the Mixed and Logistic procedures of SAS. Slow-growing pigs accounted for 10% of pigs marketed, average growers accounted for 49% of pigs marketed, and fast growers accounted for 41% of pigs marketed. Compared with fast growers, slow growers were lighter at birth ( ratio = 2.17, 95% confidence interval = 1.19 to 3.96, = 0.01). Litter size and parity of the pigs' dam were not associated with slow growth. These results suggest that low concentrations of IGF-1, insulin, leptin, and AA may contribute to or be associated with slow growth in pigs.

  17. Identifying the Relevant Factors in Newspaper Advertising Effectiveness

    Directory of Open Access Journals (Sweden)

    Cristóbal Benavides

    2014-01-01

    Full Text Available Este estudio explora varios factores con el fin de establecer cuáles son losmás importantes en motivar a los lectores de periódicos locales a comprar,visitar tiendas y buscar información adicional acerca de los productos oservicios promovidos en los anuncios. El comportamiento durante el pro-ceso de compra es consecuencia de una compleja interacción de dimen-siones culturales, sociales, personales y psicológicas. Este proceso –el cualse produce antes de la acción– tiene implicaciones relevantes y los depar-tamentos de mercadeo deben prestar atención a ello. Una serie de hipóte-sis basadas en la forma como la publicidad atrae a los consumidores y encómo afecta la toma de decisiones al momento de la compra fueron puestasa prueba usando una encuesta que fue administrada a una muestra de 1.333personas encuestadas en Chile. También se realizó un análisis discriminan-te para averiguar por qué algunos lectores de periódicos se ven motivadosa comprar bienes o servicios, visitar una tienda o buscar más información.Los resultados muestran que el atractivo de la oferta anunciada es el factormás importante para explicar el comportamiento posterior del consumidor.

  18. Using reduced rank regression methods to identify dietary patterns associated with obesity: a cross-country study among European and Australian adolescents.

    Science.gov (United States)

    Huybrechts, Inge; Lioret, Sandrine; Mouratidou, Theodora; Gunter, Marc J; Manios, Yannis; Kersting, Mathilde; Gottrand, Frederic; Kafatos, Anthony; De Henauw, Stefaan; Cuenca-García, Magdalena; Widhalm, Kurt; Gonzales-Gross, Marcela; Molnar, Denes; Moreno, Luis A; McNaughton, Sarah A

    2017-01-01

    This study aims to examine repeatability of reduced rank regression (RRR) methods in calculating dietary patterns (DP) and cross-sectional associations with overweight (OW)/obesity across European and Australian samples of adolescents. Data from two cross-sectional surveys in Europe (2006/2007 Healthy Lifestyle in Europe by Nutrition in Adolescence study, including 1954 adolescents, 12-17 years) and Australia (2007 National Children's Nutrition and Physical Activity Survey, including 1498 adolescents, 12-16 years) were used. Dietary intake was measured using two non-consecutive, 24-h recalls. RRR was used to identify DP using dietary energy density, fibre density and percentage of energy intake from fat as the intermediate variables. Associations between DP scores and body mass/fat were examined using multivariable linear and logistic regression as appropriate, stratified by sex. The first DP extracted (labelled 'energy dense, high fat, low fibre') explained 47 and 31 % of the response variation in Australian and European adolescents, respectively. It was similar for European and Australian adolescents and characterised by higher consumption of biscuits/cakes, chocolate/confectionery, crisps/savoury snacks, sugar-sweetened beverages, and lower consumption of yogurt, high-fibre bread, vegetables and fresh fruit. DP scores were inversely associated with BMI z-scores in Australian adolescent boys and borderline inverse in European adolescent boys (so as with %BF). Similarly, a lower likelihood for OW in boys was observed with higher DP scores in both surveys. No such relationships were observed in adolescent girls. In conclusion, the DP identified in this cross-country study was comparable for European and Australian adolescents, demonstrating robustness of the RRR method in calculating DP among populations. However, longitudinal designs are more relevant when studying diet-obesity associations, to prevent reverse causality.

  19. Dual Regression

    OpenAIRE

    Spady, Richard; Stouli, Sami

    2012-01-01

    We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution f...

  20. Determining the Relationship between U.S. County-Level Adult Obesity Rate and Multiple Risk Factors by PLS Regression and SVM Modeling Approaches

    Directory of Open Access Journals (Sweden)

    Chau-Kuang Chen

    2015-02-01

    Full Text Available Data from the Center for Disease Control (CDC has shown that the obesity rate doubled among adults within the past two decades. This upsurge was the result of changes in human behavior and environment. Partial least squares (PLS regression and support vector machine (SVM models were conducted to determine the relationship between U.S. county-level adult obesity rate and multiple risk factors. The outcome variable was the adult obesity rate. The 23 risk factors were categorized into four domains of the social ecological model including biological/behavioral factor, socioeconomic status, food environment, and physical environment. Of the 23 risk factors related to adult obesity, the top eight significant risk factors with high normalized importance were identified including physical inactivity, natural amenity, percent of households receiving SNAP benefits, and percent of all restaurants being fast food. The study results were consistent with those in the literature. The study showed that adult obesity rate was influenced by biological/behavioral factor, socioeconomic status, food environment, and physical environment embedded in the social ecological theory. By analyzing multiple risk factors of obesity in the communities, may lead to the proposal of more comprehensive and integrated policies and intervention programs to solve the population-based problem.

  1. EMPIRICAL STUDY OF DIFFERENT FACTORS EFFECTS ON ARTICLES PUBLICATION REGARDING SURVEY INTERVIEWER CHARACTERISTICS USING MULTILEVEL REGRESSION MODEL

    Directory of Open Access Journals (Sweden)

    Alina MOROŞANU

    2013-06-01

    Full Text Available The purpose of this research work is to evaluate the effects which some factors could have on articles publication regarding survey interviewer characteristics. For this, the author studied the existing literature from the various fields in which articles on survey interviewer characteristics has been published and which can be found in online articles database. The analysis was performed on 243 articles achieved by researchers in the time period 1949-2012. Using statistical software R and applying multilevel regression model, the results showed that the time period when the studied articles are made and the interaction between the number of authors and the number of pages affect the most their publication in journals with a certain level of impact factor.

  2. Estimating the Influence of Accident Related Factors on Motorcycle Fatal Accidents using Logistic Regression (Case Study: Denpasar-Bali

    Directory of Open Access Journals (Sweden)

    Wedagama D.M.P.

    2010-01-01

    Full Text Available In Denpasar the capital of Bali Province, motorcycle accident contributes to about 80% of total road accidents. Out of those motorcycle accidents, 32% are fatal accidents. This study investigates the influence of accident related factors on motorcycle fatal accidents in the city of Denpasar during period 2006-2008 using a logistic regression model. The study found that the fatality of collision with pedestrians and right angle accidents were respectively about 0.44 and 0.40 times lower than collision with other vehicles and accidents due to other factors. In contrast, the odds that a motorcycle accident will be fatal due to collision with heavy and light vehicles were 1.67 times more likely than with other motorcycles. Collision with pedestrians, right angle accidents, and heavy and light vehicles were respectively accounted for 31%, 29%, and 63% of motorcycle fatal accidents.

  3. A logistic regression analysis of factors related to the treatment compliance of infertile patients with polycystic ovary syndrome.

    Science.gov (United States)

    Li, Saijiao; He, Aiyan; Yang, Jing; Yin, TaiLang; Xu, Wangming

    2011-01-01

    To investigate factors that can affect compliance with treatment of polycystic ovary syndrome (PCOS) in infertile patients and to provide a basis for clinical treatment, specialist consultation and health education. Patient compliance was assessed via a questionnaire based on the Morisky-Green test and the treatment principles of PCOS. Then interviews were conducted with 99 infertile patients diagnosed with PCOS at Renmin Hospital of Wuhan University in China, from March to September 2009. Finally, these data were analyzed using logistic regression analysis. Logistic regression analysis revealed that a total of 23 (25.6%) of the participants showed good compliance. Factors that significantly (p < 0.05) affected compliance with treatment were the patient's body mass index, convenience of medical treatment and concerns about adverse drug reactions. Patients who are obese, experience inconvenient medical treatment or are concerned about adverse drug reactions are more likely to exhibit noncompliance. Treatment education and intervention aimed at these patients should be strengthened in the clinic to improve treatment compliance. Further research is needed to better elucidate the compliance behavior of patients with PCOS.

  4. Logistic regression analysis of the risk factors of anastomotic fistula after radical resection of esophageal‐cardiac cancer

    Science.gov (United States)

    Huang, Jinxi; Wang, Chenghu; Yuan, Weiwei; Zhang, Zhandong; Chen, Beibei; Zhang, Xiefu

    2017-01-01

    Background This study was conducted to investigate the risk factors of anastomotic fistula after the radical resection of esophageal‐cardiac cancer. Methods Five hundred and forty‐four esophageal‐cardiac cancer patients who underwent surgery and had complete clinical data were included in the study. Fifty patients diagnosed with postoperative anastomotic fistula were considered the case group and the remaining 494 subjects who did not develop postoperative anastomotic fistula were considered the control. The potential risk factors for anastomotic fistula, such as age, gender, diabetes history, smoking history, were collected and compared between the groups. Statistically significant variables were substituted into logistic regression to further evaluate the independent risk factors for postoperative anastomotic fistulas in esophageal‐cardiac cancer. Results The incidence of anastomotic fistulas was 9.2% (50/544). Logistic regression analysis revealed that female gender (P < 0.05), laparoscopic surgery (P < 0.05), decreased postoperative albumin (P < 0.05), and postoperative renal dysfunction (P < 0.05) were independent risk factors for anastomotic fistulas in patients who received surgery for esophageal‐cardiac cancer. Of the 50 anastomotic fistulas, 16 cases were small fistulas, which were only discovered by conventional imaging examination and not presenting clinical symptoms. All of the anastomotic fistulas occurred within seven days after surgery. Five of the patients with anastomotic fistulas underwent a second surgery and three died. Conclusion Female patients with esophageal‐cardiac cancer treated with endoscopic surgery and suffering from postoperative hypoproteinemia and renal dysfunction were susceptible to postoperative anastomotic fistula. PMID:28940985

  5. Logistic regression analysis of prognostic factors in 106 acute-on-chronic liver failure patients with hepatic encephalopathy

    Directory of Open Access Journals (Sweden)

    CUI Yanping

    2014-10-01

    Full Text Available ObjectiveTo analyze the prognostic factors in acute-on-chronic liver failure (ACLF patients with hepatic encephalopathy (HE and to explore the risk factors for prognosis. MethodsA retrospective analysis was performed on 106 ACLF patients with HE who were hospitalized in our hospital from January 2010 to July 2013. The patients were divided into improved group and deteriorated group. The univariate indicators including age, sex, laboratory indicators [total bilirubin (TBil, albumin (Alb, alanine aminotransferase (ALT, aspartate amino-transferase (AST, and prothrombin time activity (PTA], the stage of HE, complications [persistent hyponatremia, digestive tract bleeding, hepatorenal syndrome (HRS, ascites, infection, and spontaneous bacterial peritonitis (SBP], and plasma exchange were analyzed by chi-square test or t-test. Indicators with statistical significance were subsequently analyzed by binary logistic regression. ResultsUnivariate analysis showed that ALT (P=0.009, PTA (P=0.043, the stage of HE (P=0.000, and HRS (P=0.003 were significantly different between the two groups, whereas differences in age, sex, TBil, Alb, AST, persistent hyponatremia, digestive tract bleeding, ascites, infection, SBP, and plasma exchange were not statistically significant (P>0.05. Binary logistic regression demonstrated that PTA (b=-0097, P=0.025, OR=0.908, HRS (b=2.279, P=0.007, OR=9.764, and the stage of HE (b=1873, P=0.000, OR=6.510 were prognostic factors in ACLF patients with HE. ConclusionThe stage of HE, HRS, and PTA are independent influential factors for the prognosis in ACLF patients with HE. Reduced PTA, advanced HE stage, and the presence of HRS indicate worse prognosis.

  6. Pre-Analytical Parameters Affecting Vascular Endothelial Growth Factor Measurement in Plasma: Identifying Confounders.

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    Johanna M Walz

    Full Text Available Vascular endothelial growth factor-A (VEGF-A is intensively investigated in various medical fields. However, comparing VEGF-A measurements is difficult because sample acquisition and pre-analytic procedures differ between studies. We therefore investigated which variables act as confounders of VEGF-A measurements.Following a standardized protocol, blood was taken at three clinical sites from six healthy participants (one male and one female participant at each center twice one week apart. The following pre-analytical parameters were varied in order to analyze their impact on VEGF-A measurements: analyzing center, anticoagulant (EDTA vs. PECT / CTAD, cannula (butterfly vs. neonatal, type of centrifuge (swing-out vs. fixed-angle, time before and after centrifugation, filling level (completely filled vs. half-filled tubes and analyzing method (ELISA vs. multiplex bead array. Additionally, intrapersonal variations over time and sex differences were explored. Statistical analysis was performed using a linear regression model.The following parameters were identified as statistically significant independent confounders of VEGF-A measurements: analyzing center, anticoagulant, centrifuge, analyzing method and sex of the proband. The following parameters were no significant confounders in our data set: intrapersonal variation over one week, cannula, time before and after centrifugation and filling level of collection tubes.VEGF-A measurement results can be affected significantly by the identified pre-analytical parameters. We recommend the use of CTAD anticoagulant, a standardized type of centrifuge and one central laboratory using the same analyzing method for all samples.

  7. Pre-Analytical Parameters Affecting Vascular Endothelial Growth Factor Measurement in Plasma: Identifying Confounders.

    Science.gov (United States)

    Walz, Johanna M; Boehringer, Daniel; Deissler, Heidrun L; Faerber, Lothar; Goepfert, Jens C; Heiduschka, Peter; Kleeberger, Susannah M; Klettner, Alexa; Krohne, Tim U; Schneiderhan-Marra, Nicole; Ziemssen, Focke; Stahl, Andreas

    2016-01-01

    Vascular endothelial growth factor-A (VEGF-A) is intensively investigated in various medical fields. However, comparing VEGF-A measurements is difficult because sample acquisition and pre-analytic procedures differ between studies. We therefore investigated which variables act as confounders of VEGF-A measurements. Following a standardized protocol, blood was taken at three clinical sites from six healthy participants (one male and one female participant at each center) twice one week apart. The following pre-analytical parameters were varied in order to analyze their impact on VEGF-A measurements: analyzing center, anticoagulant (EDTA vs. PECT / CTAD), cannula (butterfly vs. neonatal), type of centrifuge (swing-out vs. fixed-angle), time before and after centrifugation, filling level (completely filled vs. half-filled tubes) and analyzing method (ELISA vs. multiplex bead array). Additionally, intrapersonal variations over time and sex differences were explored. Statistical analysis was performed using a linear regression model. The following parameters were identified as statistically significant independent confounders of VEGF-A measurements: analyzing center, anticoagulant, centrifuge, analyzing method and sex of the proband. The following parameters were no significant confounders in our data set: intrapersonal variation over one week, cannula, time before and after centrifugation and filling level of collection tubes. VEGF-A measurement results can be affected significantly by the identified pre-analytical parameters. We recommend the use of CTAD anticoagulant, a standardized type of centrifuge and one central laboratory using the same analyzing method for all samples.

  8. 儿童情绪障碍相关因素的LOGISTIC回归分析%Logistic Regression Analysis of Related Risk Factors of Emotional Disorders in Children

    Institute of Scientific and Technical Information of China (English)

    高鸿云; 冯金英; 徐俊冕; 郑士俊

    2001-01-01

    Objective: To identify the related psychosocial risk factors of emotional disorders in children. Methods:To use case-control approach in which. Diagnosis was made by clinical interview according to ICD-10 criteria. Eighty eight cases and controls separately filled out general condition inventory. The results were put into Logistic regression model for analysis. Results: The children with timid personality, without kindergarten education, or with parents who were administrative or technical personnel, were apt to have emotional disorders. The children who were usually counseled by their mothers had less emotional disorders than those were beaten. Conclusion: The emotional disorders were the results of multiple factors. Prevention of children's emotional disorders should be focused on the children's personality and family education.

  9. Reproductive risk factors assessment for anaemia among pregnant women in India using a multinomial logistic regression model.

    Science.gov (United States)

    Perumal, Vanamail

    2014-07-01

    To assess reproductive risk factors for anaemia among pregnant women in urban and rural areas of India. The International Institute of Population Sciences, India, carried out third National Family Health Survey in 2005-2006 to estimate a key indicator from a sample of ever-married women in the reproductive age group 15-49 years. Data on various dimensions were collected using a structured questionnaire, and anaemia was measured using a portable HemoCue instrument. Anaemia prevalence among pregnant women was compared between rural and urban areas using chi-square test and odds ratio. Multinomial logistic regression analysis was used to determine risk factors. Anaemia prevalence was assessed among 3355 pregnant women from rural areas and 1962 pregnant women from urban areas. Moderate-to-severe anaemia in rural areas (32.4%) is significantly more common than in urban areas (27.3%) with an excess risk of 30%. Gestational age specific prevalence of anaemia significantly increases in rural areas after 6 months. Pregnancy duration is a significant risk factor in both urban and rural areas. In rural areas, increasing age at marriage and mass media exposure are significant protective factors of anaemia. However, more births in the last five years, alcohol consumption and smoking habits are significant risk factors. In rural areas, various reproductive factors and lifestyle characteristics constitute significant risk factors for moderate-to-severe anaemia. Therefore, intensive health education on reproductive practices and the impact of lifestyle characteristics are warranted to reduce anaemia prevalence. © 2014 John Wiley & Sons Ltd.

  10. Risk factors for subclinical intramammary infection in dairy goats in two longitudinal field studies evaluated by Bayesian logistic regression

    DEFF Research Database (Denmark)

    Koop, Gerrit; Collar, Carol A.; Toft, Nils

    2013-01-01

    Identification of risk factors for subclinical intramammary infections (IMI) in dairy goats should contribute to improved udder health. Intramammary infection may be diagnosed by bacteriological culture or by somatic cell count (SCC) of a milk sample. Both bacteriological culture and SCC are impe......Identification of risk factors for subclinical intramammary infections (IMI) in dairy goats should contribute to improved udder health. Intramammary infection may be diagnosed by bacteriological culture or by somatic cell count (SCC) of a milk sample. Both bacteriological culture and SCC...... are imperfect tests, particularly lacking sensitivity, which leads to misclassification and thus to biased estimates of odds ratios in risk factor studies. The objective of this study was to evaluate risk factors for the true (latent) IMI status of major pathogens in dairy goats. We used Bayesian logistic...... regression models that accounted for imperfect measurement of IMI by both culture and SCC. Udder half milk samples were collected from 530 Dutch and 438 California dairy goats in 10 herds on 3 occasions during lactation. Udder halves were classified as positive or negative for isolation of a major pathogen...

  11. Factors associated with trait anger level of juvenile offenders in Hubei province: A binary logistic regression analysis.

    Science.gov (United States)

    Tang, Li-Na; Ye, Xiao-Zhou; Yan, Qiu-Ge; Chang, Hong-Juan; Ma, Yu-Qiao; Liu, De-Bin; Li, Zhi-Gen; Yu, Yi-Zhen

    2017-02-01

    The risk factors of high trait anger of juvenile offenders were explored through questionnaire study in a youth correctional facility of Hubei province, China. A total of 1090 juvenile offenders in Hubei province were investigated by self-compiled social-demographic questionnaire, Childhood Trauma Questionnaire (CTQ), and State-Trait Anger Expression Inventory-II (STAXI-II). The risk factors were analyzed by chi-square tests, correlation analysis, and binary logistic regression analysis with SPSS 19.0. A total of 1082 copies of valid questionnaires were collected. High trait anger group (n=316) was defined as those who scored in the upper 27th percentile of STAXI-II trait anger scale (TAS), and the rest were defined as low trait anger group (n=766). The risk factors associated with high level of trait anger included: childhood emotional abuse, childhood sexual abuse, step family, frequent drug abuse, and frequent internet using (P0.05). It was suggested that traumatic experience in childhood and unhealthy life style may significantly increase the level of trait anger in adulthood. The risk factors of high trait anger and their effects should be taken into consideration seriously.

  12. Identifying Predictive Factors for Incident Reports in Patients Receiving Radiation Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Elnahal, Shereef M., E-mail: selnaha1@jhmi.edu [Department of Radiation Oncology and Molecular Radiation Sciences, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland (United States); Blackford, Amanda [Department of Oncology Biostatistics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland (United States); Smith, Koren; Souranis, Annette N.; Briner, Valerie; McNutt, Todd R.; DeWeese, Theodore L.; Wright, Jean L.; Terezakis, Stephanie A. [Department of Radiation Oncology and Molecular Radiation Sciences, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland (United States)

    2016-04-01

    Purpose: To describe radiation therapy cases during which voluntary incident reporting occurred; and identify patient- or treatment-specific factors that place patients at higher risk for incidents. Methods and Materials: We used our institution's incident learning system to build a database of patients with incident reports filed between January 2011 and December 2013. Patient- and treatment-specific data were reviewed for all patients with reported incidents, which were classified by step in the process and root cause. A control group of patients without events was generated for comparison. Summary statistics, likelihood ratios, and mixed-effect logistic regression models were used for group comparisons. Results: The incident and control groups comprised 794 and 499 patients, respectively. Common root causes included documentation errors (26.5%), communication (22.5%), technical treatment planning (37.5%), and technical treatment delivery (13.5%). Incidents were more frequently reported in minors (age <18 years) than in adult patients (37.7% vs 0.4%, P<.001). Patients with head and neck (16% vs 8%, P<.001) and breast (20% vs 15%, P=.03) primaries more frequently had incidents, whereas brain (18% vs 24%, P=.008) primaries were less frequent. Larger tumors (17% vs 10% had T4 lesions, P=.02), and cases on protocol (9% vs 5%, P=.005) or with intensity modulated radiation therapy/image guided intensity modulated radiation therapy (52% vs 43%, P=.001) were more likely to have incidents. Conclusions: We found several treatment- and patient-specific variables associated with incidents. These factors should be considered by treatment teams at the time of peer review to identify patients at higher risk. Larger datasets are required to recommend changes in care process standards, to minimize safety risks.

  13. Identifying Predictive Factors for Incident Reports in Patients Receiving Radiation Therapy

    International Nuclear Information System (INIS)

    Elnahal, Shereef M.; Blackford, Amanda; Smith, Koren; Souranis, Annette N.; Briner, Valerie; McNutt, Todd R.; DeWeese, Theodore L.; Wright, Jean L.; Terezakis, Stephanie A.

    2016-01-01

    Purpose: To describe radiation therapy cases during which voluntary incident reporting occurred; and identify patient- or treatment-specific factors that place patients at higher risk for incidents. Methods and Materials: We used our institution's incident learning system to build a database of patients with incident reports filed between January 2011 and December 2013. Patient- and treatment-specific data were reviewed for all patients with reported incidents, which were classified by step in the process and root cause. A control group of patients without events was generated for comparison. Summary statistics, likelihood ratios, and mixed-effect logistic regression models were used for group comparisons. Results: The incident and control groups comprised 794 and 499 patients, respectively. Common root causes included documentation errors (26.5%), communication (22.5%), technical treatment planning (37.5%), and technical treatment delivery (13.5%). Incidents were more frequently reported in minors (age <18 years) than in adult patients (37.7% vs 0.4%, P<.001). Patients with head and neck (16% vs 8%, P<.001) and breast (20% vs 15%, P=.03) primaries more frequently had incidents, whereas brain (18% vs 24%, P=.008) primaries were less frequent. Larger tumors (17% vs 10% had T4 lesions, P=.02), and cases on protocol (9% vs 5%, P=.005) or with intensity modulated radiation therapy/image guided intensity modulated radiation therapy (52% vs 43%, P=.001) were more likely to have incidents. Conclusions: We found several treatment- and patient-specific variables associated with incidents. These factors should be considered by treatment teams at the time of peer review to identify patients at higher risk. Larger datasets are required to recommend changes in care process standards, to minimize safety risks.

  14. IPF-LASSO: Integrative L1-Penalized Regression with Penalty Factors for Prediction Based on Multi-Omics Data

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    Anne-Laure Boulesteix

    2017-01-01

    Full Text Available As modern biotechnologies advance, it has become increasingly frequent that different modalities of high-dimensional molecular data (termed “omics” data in this paper, such as gene expression, methylation, and copy number, are collected from the same patient cohort to predict the clinical outcome. While prediction based on omics data has been widely studied in the last fifteen years, little has been done in the statistical literature on the integration of multiple omics modalities to select a subset of variables for prediction, which is a critical task in personalized medicine. In this paper, we propose a simple penalized regression method to address this problem by assigning different penalty factors to different data modalities for feature selection and prediction. The penalty factors can be chosen in a fully data-driven fashion by cross-validation or by taking practical considerations into account. In simulation studies, we compare the prediction performance of our approach, called IPF-LASSO (Integrative LASSO with Penalty Factors and implemented in the R package ipflasso, with the standard LASSO and sparse group LASSO. The use of IPF-LASSO is also illustrated through applications to two real-life cancer datasets. All data and codes are available on the companion website to ensure reproducibility.

  15. Predictive factors of esophageal stenosis associated with tumor regression in radiation therapy for locally advanced esophageal cancer

    International Nuclear Information System (INIS)

    Atsumi, Kazushige; Shioyama, Yoshiyuki; Nakamura, Katsumasa

    2010-01-01

    The purpose of this retrospective study was to clarify the predictive factors correlated with esophageal stenosis within three months after radiation therapy for locally advanced esophageal cancer. We enrolled 47 patients with advanced esophageal cancer with T2-4 and stage II-III who were treated with definitive radiation therapy and achieving complete response of primary lesion at Kyushu University Hospital between January 1998 and December 2005. Esophagography was performed for all patients before treatment and within three months after completion of the radiation therapy, the esophageal stenotic ratio was evaluated. The stenotic ratio was used to define four levels of stenosis: stenosis level 1, stenotic ratio of 0-25%; 2, 25-50%; 3, 50-75%; 4, 75-100%. We then estimated the correlation between the esophageal stenosis level after radiation therapy and each of numerous factors. The numbers and total percentages of patients at each stenosis level were as follows: level 1: n=14 (30%); level 2: 8 (17%); level 3: 14 (30%); and level 4: 11 (23%). Esophageal stenosis in the case of full circumference involvement tended to be more severe and more frequent. Increases in wall thickness tended to be associated with increases in esophageal stenosis severity and frequency. The extent of involved circumference and wall thickness of tumor region were significantly correlated with esophageal stenosis associated with tumor regression in radiation therapy (p=0.0006, p=0.005). For predicting the possibility of esophageal stenosis with tumor regression within three months in radiation therapy, the extent of involved circumference and esophageal wall thickness of the tumor region may be useful. (author)

  16. Identifying work ability promoting factors for home care aides and assistant nurses

    Directory of Open Access Journals (Sweden)

    Larsson Agneta

    2012-01-01

    Full Text Available Abstract Background In workplace health promotion, all potential resources needs to be taken into consideration, not only factors relating to the absence of injury and the physical health of the workers, but also psychological aspects. A dynamic balance between the resources of the individual employees and the demands of work is an important prerequisite. In the home care services, there is a noticeable trend towards increased psychosocial strain on employees at work. There are a high frequency of work-related musculoskeletal disorders and injuries, and a low prevalence of sustainable work ability. The aim of this research was to identify factors promoting work ability and self-efficacy in care aides and assistant nurses within home care services. Methods This study is based on cross-sectional data collected in a municipality in northern Sweden. Care aides (n = 58 and assistant nurses (n = 79 replied to a self-administered questionnaire (response rate 46%. Hierarchical multiple regression analyses were performed to assess the influence of several independent variables on self-efficacy (model 1 and work ability (model 2 for care aides and assistant nurses separately. Results Perceptions of personal safety, self-efficacy and musculoskeletal wellbeing contributed to work ability for assistant nurses (R2adj of 0.36, p 2adj of 0.29, p = 0.001. Self-efficacy was associated with the safety climate and the physical demands of the job in both professions (R2adj of 0.24, p = 0.003 for care aides, and also by sex and age for the assistant nurses (R2adj of 0.31, p Conclusions The intermediate factors contributed differently to work ability in the two professions. Self-efficacy, personal safety and musculoskeletal wellbeing were important for the assistant nurses, while the work ability of the care aides was associated with the safety climate, but also with the non-changeable factors age and seniority. All these factors are important to acknowledge in

  17. Study of risk factors affecting both hypertension and obesity outcome by using multivariate multilevel logistic regression models

    Directory of Open Access Journals (Sweden)

    Sepedeh Gholizadeh

    2016-07-01

    Full Text Available Background:Obesity and hypertension are the most important non-communicable diseases thatin many studies, the prevalence and their risk factors have been performedin each geographic region univariately.Study of factors affecting both obesity and hypertension may have an important role which to be adrressed in this study. Materials &Methods:This cross-sectional study was conducted on 1000 men aged 20-70 living in Bushehr province. Blood pressure was measured three times and the average of them was considered as one of the response variables. Hypertension was defined as systolic blood pressure ≥140 (and-or diastolic blood pressure ≥90 and obesity was defined as body mass index ≥25. Data was analyzed by using multilevel, multivariate logistic regression model by MlwiNsoftware. Results:Intra class correlations in cluster level obtained 33% for high blood pressure and 37% for obesity, so two level model was fitted to data. The prevalence of obesity and hypertension obtained 43.6% (0.95%CI; 40.6-46.5, 29.4% (0.95%CI; 26.6-32.1 respectively. Age, gender, smoking, hyperlipidemia, diabetes, fruit and vegetable consumption and physical activity were the factors affecting blood pressure (p≤0.05. Age, gender, hyperlipidemia, diabetes, fruit and vegetable consumption, physical activity and place of residence are effective on obesity (p≤0.05. Conclusion: The multilevel models with considering levels distribution provide more precise estimates. As regards obesity and hypertension are the major risk factors for cardiovascular disease, by knowing the high-risk groups we can d careful planning to prevention of non-communicable diseases and promotion of society health.

  18. Applying spatial regression to evaluate risk factors for microbiological contamination of urban groundwater sources in Juba, South Sudan

    Science.gov (United States)

    Engström, Emma; Mörtberg, Ulla; Karlström, Anders; Mangold, Mikael

    2017-06-01

    This study developed methodology for statistically assessing groundwater contamination mechanisms. It focused on microbial water pollution in low-income regions. Risk factors for faecal contamination of groundwater-fed drinking-water sources were evaluated in a case study in Juba, South Sudan. The study was based on counts of thermotolerant coliforms in water samples from 129 sources, collected by the humanitarian aid organisation Médecins Sans Frontières in 2010. The factors included hydrogeological settings, land use and socio-economic characteristics. The results showed that the residuals of a conventional probit regression model had a significant positive spatial autocorrelation (Moran's I = 3.05, I-stat = 9.28); therefore, a spatial model was developed that had better goodness-of-fit to the observations. The most significant factor in this model ( p-value 0.005) was the distance from a water source to the nearest Tukul area, an area with informal settlements that lack sanitation services. It is thus recommended that future remediation and monitoring efforts in the city be concentrated in such low-income regions. The spatial model differed from the conventional approach: in contrast with the latter case, lowland topography was not significant at the 5% level, as the p-value was 0.074 in the spatial model and 0.040 in the traditional model. This study showed that statistical risk-factor assessments of groundwater contamination need to consider spatial interactions when the water sources are located close to each other. Future studies might further investigate the cut-off distance that reflects spatial autocorrelation. Particularly, these results advise research on urban groundwater quality.

  19. Modeling the potential risk factors of bovine viral diarrhea prevalence in Egypt using univariable and multivariable logistic regression analyses

    Directory of Open Access Journals (Sweden)

    Abdelfattah M. Selim

    2018-03-01

    Full Text Available Aim: The present cross-sectional study was conducted to determine the seroprevalence and potential risk factors associated with Bovine viral diarrhea virus (BVDV disease in cattle and buffaloes in Egypt, to model the potential risk factors associated with the disease using logistic regression (LR models, and to fit the best predictive model for the current data. Materials and Methods: A total of 740 blood samples were collected within November 2012-March 2013 from animals aged between 6 months and 3 years. The potential risk factors studied were species, age, sex, and herd location. All serum samples were examined with indirect ELIZA test for antibody detection. Data were analyzed with different statistical approaches such as Chi-square test, odds ratios (OR, univariable, and multivariable LR models. Results: Results revealed a non-significant association between being seropositive with BVDV and all risk factors, except for species of animal. Seroprevalence percentages were 40% and 23% for cattle and buffaloes, respectively. OR for all categories were close to one with the highest OR for cattle relative to buffaloes, which was 2.237. Likelihood ratio tests showed a significant drop of the -2LL from univariable LR to multivariable LR models. Conclusion: There was an evidence of high seroprevalence of BVDV among cattle as compared with buffaloes with the possibility of infection in different age groups of animals. In addition, multivariable LR model was proved to provide more information for association and prediction purposes relative to univariable LR models and Chi-square tests if we have more than one predictor.

  20. Análise de fatores e regressão bissegmentada em estudos de estratificação ambiental e adaptabilidade em milho Factor analysis and bissegmented regression for studies about environmental stratification and maize adaptability

    Directory of Open Access Journals (Sweden)

    Deoclécio Domingos Garbuglio

    2007-02-01

    Full Text Available O objetivo deste trabalho foi verificar possíveis divergências entre os resultados obtidos nas avaliações da adaptabilidade de 27 genótipos de milho (Zea mays L., e na estratificação de 22 ambientes no Estado do Paraná, por meio de técnicas baseadas na análise de fatores e regressão bissegmentada. As estratificações ambientais foram feitas por meio do método tradicional e por análise de fatores, aliada ao porcentual da porção simples da interação GxA (PS%. As análises de adaptabilidade foram realizadas por meio de regressão bissegmentada e análise de fatores. Pela análise de regressão bissegmentada, os genótipos estudados apresentaram alta performance produtiva; no entanto, não foi constatado o genótipo considerado como ideal. A adaptabilidade dos genótipos, analisada por meio de plotagens gráficas, apresentou respostas diferenciadas quando comparada à regressão bissegmentada. A análise de fatores mostrou-se eficiente nos processos de estratificação ambiental e adaptabilidade dos genótipos de milho.The objective of this work was to verify possible divergences among results obtained on adaptability evaluations of 27 maize genotypes (Zea mays L., and on stratification of 22 environments on Paraná State, Brazil, through techniques of factor analysis and bissegmented regression. The environmental stratifications were made through the traditional methodology and by factor analysis, allied to the percentage of the simple portion of GxE interaction (PS%. Adaptability analyses were carried out through bissegmented regression and factor analysis. By the analysis of bissegmented regression, studied genotypes had presented high productive performance; however, it was not evidenced the genotype considered as ideal. The adaptability of the genotypes, analyzed through graphs, presented different answers when compared to bissegmented regression. Factor analysis was efficient in the processes of environment stratification and

  1. Identifying Trajectories of Borderline Personality Features in Adolescence: Antecedent and Interactive Risk Factors.

    Science.gov (United States)

    Haltigan, John D; Vaillancourt, Tracy

    2016-03-01

    To examine trajectories of adolescent borderline personality (BP) features in a normative-risk cohort (n = 566) of Canadian children assessed at ages 13, 14, 15, and 16 and childhood predictors of trajectory group membership assessed at ages 8, 10, 11, and 12. Data were drawn from the McMaster Teen Study, an on-going study examining relations among bullying, mental health, and academic achievement. Participants and their parents completed a battery of mental health and peer relations questionnaires at each wave of the study. Academic competence was assessed at age 8 (Grade 3). Latent class growth analysis, analysis of variance, and logistic regression were used to analyze the data. Three distinct BP features trajectory groups were identified: elevated or rising, intermediate or stable, and low or stable. Parent- and child-reported mental health symptoms, peer relations risk factors, and intra-individual risk factors were significant predictors of elevated or rising and intermediate or stable trajectory groups. Child-reported attention-deficit hyperactivity disorder (ADHD) and somatization symptoms uniquely predicted elevated or rising trajectory group membership, whereas parent-reported anxiety and child-reported ADHD symptoms uniquely predicted intermediate or stable trajectory group membership. Child-reported somatization symptoms was the only predictor to differentiate the intermediate or stable and elevated or rising trajectory groups (OR 1.15, 95% CI 1.04 to 1.28). Associations between child-reported reactive temperament and elevated BP features trajectory group membership were 10.23 times higher among children who were bullied, supporting a diathesis-stress pathway in the development of BP features for these youth. Findings demonstrate the heterogeneous course of BP features in early adolescence and shed light on the potential prodromal course of later borderline personality disorder. © The Author(s) 2015.

  2. A study of the dengue epidemic and meteorological factors in Guangzhou, China, by using a zero-inflated Poisson regression model.

    Science.gov (United States)

    Wang, Chenggang; Jiang, Baofa; Fan, Jingchun; Wang, Furong; Liu, Qiyong

    2014-01-01

    The aim of this study is to develop a model that correctly identifies and quantifies the relationship between dengue and meteorological factors in Guangzhou, China. By cross-correlation analysis, meteorological variables and their lag effects were determined. According to the epidemic characteristics of dengue in Guangzhou, those statistically significant variables were modeled by a zero-inflated Poisson regression model. The number of dengue cases and minimum temperature at 1-month lag, along with average relative humidity at 0- to 1-month lag were all positively correlated with the prevalence of dengue fever, whereas wind velocity and temperature in the same month along with rainfall at 2 months' lag showed negative association with dengue incidence. Minimum temperature at 1-month lag and wind velocity in the same month had a greater impact on the dengue epidemic than other variables in Guangzhou.

  3. Personality, Driving Behavior and Mental Disorders Factors as Predictors of Road Traffic Accidents Based on Logistic Regression

    Science.gov (United States)

    Alavi, Seyyed Salman; Mohammadi, Mohammad Reza; Souri, Hamid; Mohammadi Kalhori, Soroush; Jannatifard, Fereshteh; Sepahbodi, Ghazal

    2017-01-01

    Background: The aim of this study was to evaluate the effect of variables such as personality traits, driving behavior and mental illness on road traffic accidents among the drivers with accidents and those without road crash. Methods: In this cohort study, 800 bus and truck drivers were recruited. Participants were selected among drivers who referred to Imam Sajjad Hospital (Tehran, Iran) during 2013-2015. The Manchester driving behavior questionnaire (MDBQ), big five personality test (NEO personality inventory) and semi-structured interview (schizophrenia and affective disorders scale) were used. After two years, we surveyed all accidents due to human factors that involved the recruited drivers. The data were analyzed using the SPSS software by performing the descriptive statistics, t-test, and multiple logistic regression analysis methods. P values less than 0.05 were considered statistically significant. Results: In terms of controlling the effective and demographic variables, the findings revealed significant differences between the two groups of drivers that were and were not involved in road accidents. In addition, it was found that depression and anxiety could increase the odds ratio (OR) of road accidents by 2.4- and 2.7-folds, respectively (P=0.04, P=0.004). It is noteworthy to mention that neuroticism alone can increase the odds of road accidents by 1.1-fold (P=0.009), but other personality factors did not have a significant effect on the equation. Conclusion: The results revealed that some mental disorders affect the incidence of road collisions. Considering the importance and sensitivity of driving behavior, it is necessary to evaluate multiple psychological factors influencing drivers before and after receiving or renewing their driver’s license. PMID:28293047

  4. Personality, Driving Behavior and Mental Disorders Factors as Predictors of Road Traffic Accidents Based on Logistic Regression.

    Science.gov (United States)

    Alavi, Seyyed Salman; Mohammadi, Mohammad Reza; Souri, Hamid; Mohammadi Kalhori, Soroush; Jannatifard, Fereshteh; Sepahbodi, Ghazal

    2017-01-01

    The aim of this study was to evaluate the effect of variables such as personality traits, driving behavior and mental illness on road traffic accidents among the drivers with accidents and those without road crash. In this cohort study, 800 bus and truck drivers were recruited. Participants were selected among drivers who referred to Imam Sajjad Hospital (Tehran, Iran) during 2013-2015. The Manchester driving behavior questionnaire (MDBQ), big five personality test (NEO personality inventory) and semi-structured interview (schizophrenia and affective disorders scale) were used. After two years, we surveyed all accidents due to human factors that involved the recruited drivers. The data were analyzed using the SPSS software by performing the descriptive statistics, t-test, and multiple logistic regression analysis methods. P values less than 0.05 were considered statistically significant. In terms of controlling the effective and demographic variables, the findings revealed significant differences between the two groups of drivers that were and were not involved in road accidents. In addition, it was found that depression and anxiety could increase the odds ratio (OR) of road accidents by 2.4- and 2.7-folds, respectively (P=0.04, P=0.004). It is noteworthy to mention that neuroticism alone can increase the odds of road accidents by 1.1-fold (P=0.009), but other personality factors did not have a significant effect on the equation. The results revealed that some mental disorders affect the incidence of road collisions. Considering the importance and sensitivity of driving behavior, it is necessary to evaluate multiple psychological factors influencing drivers before and after receiving or renewing their driver's license.

  5. Comparison of linear and zero-inflated negative binomial regression models for appraisal of risk factors associated with dental caries.

    Science.gov (United States)

    Batra, Manu; Shah, Aasim Farooq; Rajput, Prashant; Shah, Ishrat Aasim

    2016-01-01

    Dental caries among children has been described as a pandemic disease with a multifactorial nature. Various sociodemographic factors and oral hygiene practices are commonly tested for their influence on dental caries. In recent years, a recent statistical model that allows for covariate adjustment has been developed and is commonly referred zero-inflated negative binomial (ZINB) models. To compare the fit of the two models, the conventional linear regression (LR) model and ZINB model to assess the risk factors associated with dental caries. A cross-sectional survey was conducted on 1138 12-year-old school children in Moradabad Town, Uttar Pradesh during months of February-August 2014. Selected participants were interviewed using a questionnaire. Dental caries was assessed by recording decayed, missing, or filled teeth (DMFT) index. To assess the risk factor associated with dental caries in children, two approaches have been applied - LR model and ZINB model. The prevalence of caries-free subjects was 24.1%, and mean DMFT was 3.4 ± 1.8. In LR model, all the variables were statistically significant. Whereas in ZINB model, negative binomial part showed place of residence, father's education level, tooth brushing frequency, and dental visit statistically significant implying that the degree of being caries-free (DMFT = 0) increases for group of children who are living in urban, whose father is university pass out, who brushes twice a day and if have ever visited a dentist. The current study report that the LR model is a poorly fitted model and may lead to spurious conclusions whereas ZINB model has shown better goodness of fit (Akaike information criterion values - LR: 3.94; ZINB: 2.39) and can be preferred if high variance and number of an excess of zeroes are present.

  6. Personality, Driving Behavior and Mental Disorders Factors as Predictors of Road Traffic Accidents Based on Logistic Regression

    Directory of Open Access Journals (Sweden)

    Seyyed Salman Alavi

    2017-01-01

    Full Text Available Background: The aim of this study was to evaluate the effect of variables such as personality traits, driving behavior and mental illness on road traffic accidents among the drivers with accidents and those without road crash. Methods: In this cohort study, 800 bus and truck drivers were recruited. Participants were selected among drivers who referred to Imam Sajjad Hospital (Tehran, Iran during 2013-2015. The Manchester driving behavior questionnaire (MDBQ, big five personality test (NEO personality inventory and semi-structured interview (SADS were used. After two years, we surveyed all accidents due to human factors that involved the recruited drivers. The data were analyzed using the SPSS software by performing the descriptive statistics, t-test, and multiple logistic regression analysis methods. P values less than 0.05 were considered statistically significant. Results: In terms of controlling the effective and demographic variables, the findings revealed significant differences between the two groups of drivers that were and were not involved in road accidents. In addition, it was found that depression and anxiety could increase the odds ratio (OR of road accidents by 2.4- and 2.7-folds, respectively (P=0.04, P=0.004. It is noteworthy to mention that neuroticism alone can increase the odds of road accidents by 1.1-fold (P=0.009, but other personality factors did not have a significant effect on the equation. Conclusion: The results revealed that some mental disorders affect the incidence of road collisions. Considering the importance and sensitivity of driving behavior, it is necessary to evaluate multiple psychological factors influencing drivers before and after receiving or renewing their driver’s license.

  7. Evaluation of an inpatient fall risk screening tool to identify the most critical fall risk factors in inpatients.

    Science.gov (United States)

    Hou, Wen-Hsuan; Kang, Chun-Mei; Ho, Mu-Hsing; Kuo, Jessie Ming-Chuan; Chen, Hsiao-Lien; Chang, Wen-Yin

    2017-03-01

    To evaluate the accuracy of the inpatient fall risk screening tool and to identify the most critical fall risk factors in inpatients. Variations exist in several screening tools applied in acute care hospitals for examining risk factors for falls and identifying high-risk inpatients. Secondary data analysis. A subset of inpatient data for the period from June 2011-June 2014 was extracted from the nursing information system and adverse event reporting system of an 818-bed teaching medical centre in Taipei. Data were analysed using descriptive statistics, receiver operating characteristic curve analysis and logistic regression analysis. During the study period, 205 fallers and 37,232 nonfallers were identified. The results revealed that the inpatient fall risk screening tool (cut-off point of ≥3) had a low sensitivity level (60%), satisfactory specificity (87%), a positive predictive value of 2·0% and a negative predictive value of 99%. The receiver operating characteristic curve analysis revealed an area under the curve of 0·805 (sensitivity, 71·8%; specificity, 78%). To increase the sensitivity values, the Youden index suggests at least 1·5 points to be the most suitable cut-off point for the inpatient fall risk screening tool. Multivariate logistic regression analysis revealed a considerably increased fall risk in patients with impaired balance and impaired elimination. The fall risk factor was also significantly associated with days of hospital stay and with admission to surgical wards. The findings can raise awareness about the two most critical risk factors for falls among future clinical nurses and other healthcare professionals and thus facilitate the development of fall prevention interventions. This study highlights the needs for redefining the cut-off points of the inpatient fall risk screening tool to effectively identify inpatients at a high risk of falls. Furthermore, inpatients with impaired balance and impaired elimination should be closely

  8. Sequences of Regressions Distinguish Nonmechanical from Mechanical Associations between Metabolic Factors, Body Composition, and Bone in Healthy Postmenopausal Women.

    Science.gov (United States)

    Solis-Trapala, Ivonne; Schoenmakers, Inez; Goldberg, Gail R; Prentice, Ann; Ward, Kate A

    2016-03-09

    There is increasing recognition of complex interrelations between the endocrine functions of bone and fat tissues or organs. The objective was to describe nonmechanical and mechanical links between metabolic factors, body composition, and bone with the use of graphical Markov models. Seventy postmenopausal women with a mean ± SD age of 62.3 ± 3.7 y and body mass index (in kg/m 2 ) of 24.9 ± 3.8 were recruited. Bone outcomes were peripheral quantitative computed tomography measures of the distal and diaphyseal tibia, cross-sectional area (CSA), volumetric bone mineral density (vBMD), and cortical CSA. Biomarkers of osteoblast and adipocyte function were plasma concentrations of leptin, adiponectin, osteocalcin, undercarboxylated osteocalcin (UCOC), and phylloquinone. Body composition measurements were lean and percent fat mass, which were derived with the use of a 4-compartment model. Sequences of Regressions, a subclass of graphical Markov models, were used to describe the direct (nonmechanical) and indirect (mechanical) interrelations between metabolic factors and bone by simultaneously modeling multiple bone outcomes and their relation with biomarker outcomes with lean mass, percent fat mass, and height as intermediate explanatory variables. The graphical Markov models showed both direct and indirect associations linking plasma leptin and adiponectin concentrations with CSA and vBMD. At the distal tibia, lean mass, height, and adiponectin-UCOC interaction were directly explanatory of CSA (R 2 = 0.45); at the diaphysis, lean mass, percent fat mass, leptin, osteocalcin, and age-adiponectin interaction were directly explanatory of CSA (R 2 = 0.49). The regression models exploring direct associations for vBMD were much weaker, with R 2 = 0.15 and 0.18 at the distal and diaphyseal sites, respectively. Lean mass and UCOC were associated, and the global Markov property of the graph indicated that this association was explained by osteocalcin. This study, to our

  9. [Analysis of dietary pattern and diabetes mellitus influencing factors identified by classification tree model in adults of Fujian].

    Science.gov (United States)

    Yu, F L; Ye, Y; Yan, Y S

    2017-05-10

    Objective: To find out the dietary patterns and explore the relationship between environmental factors (especially dietary patterns) and diabetes mellitus in the adults of Fujian. Methods: Multi-stage sampling method were used to survey residents aged ≥18 years by questionnaire, physical examination and laboratory detection in 10 disease surveillance points in Fujian. Factor analysis was used to identify the dietary patterns, while logistic regression model was applied to analyze relationship between dietary patterns and diabetes mellitus, and classification tree model was adopted to identify the influencing factors for diabetes mellitus. Results: There were four dietary patterns in the population, including meat, plant, high-quality protein, and fried food and beverages patterns. The result of logistic analysis showed that plant pattern, which has higher factor loading of fresh fruit-vegetables and cereal-tubers, was a protective factor for non-diabetes mellitus. The risk of diabetes mellitus in the population at T2 and T3 levels of factor score were 0.727 (95 %CI: 0.561-0.943) times and 0.736 (95 %CI : 0.573-0.944) times higher, respectively, than those whose factor score was in lowest quartile. Thirteen influencing factors and eleven group at high-risk for diabetes mellitus were identified by classification tree model. The influencing factors were dyslipidemia, age, family history of diabetes, hypertension, physical activity, career, sex, sedentary time, abdominal adiposity, BMI, marital status, sleep time and high-quality protein pattern. Conclusion: There is a close association between dietary patterns and diabetes mellitus. It is necessary to promote healthy and reasonable diet, strengthen the monitoring and control of blood lipids, blood pressure and body weight, and have good lifestyle for the prevention and control of diabetes mellitus.

  10. Latinos in science: Identifying factors that influence the low percentage of Latino representation in the sciences

    Science.gov (United States)

    Miranda, Susan Jennifer

    A mixed methods approach was used to identify factors that influence the underrepresentation of Latinos in the domain of science. The researcher investigated the role of family influences, academic preparation, and personal motivations to determine science-related career choices by Latinos. Binary logistic regression analyses were conducted using information from Latinos gathered from the National Education Longitudinal Study of 1988 (NELS: 88) administered by the National Center for Education Statistics. For the present study, data were analyzed using participants' responses as high school seniors, college students, and post-baccalaureates. Students responded to questions on school, work, parental academic influences, personal aspirations, and self-perception. To provide more insight into the experiences of Latinos in science and support the statistical analyses, nine students majoring in science in a private, urban university located in the northeastern part of the country were interviewed. Eleven variables related to parents' academic support and students' perceptions of parental support were taken together as predictors for two separate criteria from the survey. These results identified parents' level of education and the importance of academics to parents in their teen's college choice as significant predictors in determining college major in science. When the criterion was degree in science, the significant predictor was the frequency parents contacted high school as volunteers. Student interviews supported this information, demonstrating the importance of parental support in attaining a degree in science. Academic preparation was also analyzed. Students' reasons for taking science classes in high school was a significant predictor for science major; significant predictors for science degree were the emphasis placed on objectives in math and science classes and number of courses in biology and physics. Student interviews supported this information and

  11. Identifying at-risk profiles and protective factors for problem gambling: A longitudinal study across adolescence and early adulthood.

    Science.gov (United States)

    Allami, Youssef; Vitaro, Frank; Brendgen, Mara; Carbonneau, René; Tremblay, Richard E

    2018-05-01

    Past studies have identified various risk and protective factors for problem gambling (PG). However, no study has examined the interplay between these factors using a combination of person-centered and variable-centered approaches embedded within a longitudinal design. The present study aimed to (a) identify distinct profiles in early adolescence based on a set of risk factors commonly associated with PG (impulsivity, depression, anxiety, drug-alcohol use, aggressiveness, and antisociality), (b) explore the difference in reported gambling problems between these profiles during midadolescence and early adulthood, and (c) identify family- and peer-related variables that could operate as protective or compensatory factors in this context. Two samples were used: (a) a population sample (N = 1,033) living in low socioeconomic-status neighborhoods and (b) a population sample (N = 3,017) representative of students attending Quebec schools. Latent profile analyses were conducted to identify at-risk profiles based on individual risk factors measured at age 12 years. Negative binomial regression models were estimated to compare profiles in terms of their reported gambling problems at ages 16 and 23. Finally, family- and peer-related variables measured at age 14 were included to test their protective or compensatory role with respect to the link between at-risk profiles and gambling problems. Four profiles were identified: well-adjusted, internalizing, externalizing, and comorbid. Compared to the well-adjusted profile, the externalizing and comorbid profiles reported more gambling problems at ages 16 and 23, but the internalizing profile did not differ significantly. Various protective and compensatory factors emerged for each profile at both time points. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  12. Regression Phalanxes

    OpenAIRE

    Zhang, Hongyang; Welch, William J.; Zamar, Ruben H.

    2017-01-01

    Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work well for classification tasks. In this paper, we propose a different class of phalanxes for application in regression settings. We define a "Regression Phalanx" - a subset of features that work well together for prediction. We propose a novel algorithm which automatically chooses Regression Phalanxes from high-dimensi...

  13. Identifying patients with therapy-resistant depression by using factor analysis

    DEFF Research Database (Denmark)

    Andreasson, K; Liest, V; Lunde, M

    2010-01-01

    with transcranial pulsed electromagnetic fields (T-PEMF)], in which the relative effect as percentage of improvement during the treatment period was analysed. RESULTS: We identified 2 major factors, the first of which was a general factor. The second was a dual factor consisting of a depression subscale comprising...

  14. Identifying and assessing the factors affecting skill gap in digital marketing in communication industry companies

    Directory of Open Access Journals (Sweden)

    Fereshteh Ghotbifar

    2017-03-01

    Full Text Available As far as new communication channels are concerned, there have been extensive developments in communications and marketing in digital era. Today, therefore, companies try to take advantage of digital marketing channels to provide suitable services to customers to improve their satisfaction level. However, this study aimed to identify and assess factors affecting skill gap in digital marketing. This was descriptive correlation study. The population consisted of experts in communications industry to identify most important skill gaps in digital marketing and factors affecting them; also, managers and specialists of these companies were investigated to determine the role of identified factors in reducing skills gaps. Using localized questionnaire and interviewing with ten experts who were selected by Delphi snowball method, the skill gaps in marketing and factors affecting them were identified. Also, a researcher made questionnaire with 32 questions was distributed among 226 employees to investigate the identified factors role in reducing skills gap in digital marketing. The results showed that from four identified factors, the components including operational strategic factors and environmental factors had direct and positive impact on creating skill gap in digital marketing of studied companies. The environmental factors such as social and cultural conditions, religion, technology, and economy had more proactive impact on skills gap in digital marketing. Also, the results showed that among skills gaps in digital marketing of studied companies, the skills (Principles of Communication and (Predicting Future had the highest and lowest gaps, respectively.

  15. Study of depression influencing factors with zero-inflated regression models in a large-scale population survey

    OpenAIRE

    Xu, Tao; Zhu, Guangjin; Han, Shaomei

    2017-01-01

    Objectives The number of depression symptoms can be considered as count data in order to get complete and accurate analyses findings in studies of depression. This study aims to compare the goodness of fit of four count outcomes models by a large survey sample to identify the optimum model for a risk factor study of the number of depression symptoms. Methods 15 820 subjects, aged 10 to 80 years old, who were not suffering from serious chronic diseases and had not run a high fever in the past ...

  16. Identifying environmental risk factors and mapping the risk of human West Nile virus in South Dakota.

    Science.gov (United States)

    Hess, A.; Davis, J. K.; Wimberly, M. C.

    2017-12-01

    Human West Nile virus (WNV) first arrived in the USA in 1999 and has since then spread across the country. Today, the highest incidence rates are found in the state of South Dakota. The disease occurrence depends on the complex interaction between the mosquito vector, the bird host and the dead-end human host. Understanding the spatial domain of this interaction and being able to identify disease transmission hotspots is crucial for effective disease prevention and mosquito control. In this study we use geospatial environmental information to understand what drives the spatial distribution of cases of human West Nile virus in South Dakota and to map relative infection risk across the state. To map the risk of human West Nile virus in South Dakota, we used geocoded human case data from the years 2004-2016. Satellite data from the Landsat ETM+ and MODIS for the years 2003 to 2016 were used to characterize environmental patterns. From these datasets we calculated indices, such as the normalized differenced vegetation index (NDVI) and the normalized differenced water index (NDWI). In addition, datasets such as the National Land Data Assimilation System (NLDAS), National Land Cover Dataset (NLCD), National Wetland inventory (NWI), National Elevation Dataset (NED) and Soil Survey Geographic Database (SSURGO) were utilized. Environmental variables were summarized for a buffer zone around the case and control points. We used a boosted regression tree model to identify the most important variables describing the risk of WNV infection. We generated a risk map by applying this model across the entire state. We found that the highest relative risk is present in the James River valley in northeastern South Dakota. Factors that were identified as influencing the transmission risk include inter-annual variability of vegetation cover, water availability and temperature. Land covers such as grasslands, low developed areas and wetlands were also found to be good predictors for human

  17. Identifying factors influencing contraceptive use in Bangladesh: evidence from BDHS 2014 data.

    Science.gov (United States)

    Hossain, M B; Khan, M H R; Ababneh, F; Shaw, J E H

    2018-01-30

    Birth control is the conscious control of the birth rate by methods which temporarily prevent conception by interfering with the normal process of ovulation, fertilization, and implantation. High contraceptive prevalence rate is always expected for controlling births for those countries that are experiencing high population growth rate. The factors that influence contraceptive prevalence are also important to know for policy implication purposes in Bangladesh. This study aims to explore the socio-economic, demographic and others key factors that influence the use of contraception in Bangladesh. The contraception data are extracted from the 2014 Bangladesh Demographic and Health Survey (BDHS) data which were collected by using a two stage stratified random sampling technique that is a source of nested variability. The nested sources of variability must be incorporated in the model using random effects in order to model the actual parameter effects on contraceptive prevalence. A mixed effect logistic regression model has been implemented for the binary contraceptive data, where parameters are estimated through generalized estimating equation by assuming exchangeable correlation structure to explore and identify the factors that truly affect the use of contraception in Bangladesh. The prevalence of contraception use by currently married 15-49 years aged women or their husbands is 62.4%. Our study finds that administrative division, place of residence, religion, number of household members, woman's age, occupation, body mass index, breastfeeding practice, husband's education, wish for children, living status with wife, sexual activity in past year, women amenorrheic status, abstaining status, number of children born in last five years and total children ever died were significantly associated with contraception use in Bangladesh. The odds of women experiencing the outcome of interest are not independent due to the nested structure of the data. As a result, a mixed

  18. Identify and Classify Critical Success Factor of Agile Software Development Methodology Using Mind Map

    OpenAIRE

    Tasneem Abd El Hameed; Mahmoud Abd EL Latif; Sherif Kholief

    2016-01-01

    Selecting the right method, right personnel and right practices, and applying them adequately, determine the success of software development. In this paper, a qualitative study is carried out among the critical factors of success from previous studies. The factors of success match with their relative principles to illustrate the most valuable factor for agile approach success, this paper also prove that the twelve principles poorly identified for few factors resulting from qualitative and qua...

  19. Regression-Based Norms for a Bi-factor Model for Scoring the Brief Test of Adult Cognition by Telephone (BTACT).

    Science.gov (United States)

    Gurnani, Ashita S; John, Samantha E; Gavett, Brandon E

    2015-05-01

    The current study developed regression-based normative adjustments for a bi-factor model of the The Brief Test of Adult Cognition by Telephone (BTACT). Archival data from the Midlife Development in the United States-II Cognitive Project were used to develop eight separate linear regression models that predicted bi-factor BTACT scores, accounting for age, education, gender, and occupation-alone and in various combinations. All regression models provided statistically significant fit to the data. A three-predictor regression model fit best and accounted for 32.8% of the variance in the global bi-factor BTACT score. The fit of the regression models was not improved by gender. Eight different regression models are presented to allow the user flexibility in applying demographic corrections to the bi-factor BTACT scores. Occupation corrections, while not widely used, may provide useful demographic adjustments for adult populations or for those individuals who have attained an occupational status not commensurate with expected educational attainment. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  20. A multiple linear regression analysis of factors affecting the simulated Basic Life Support (BLS) performance with Automated External Defibrillator (AED) in Flemish lifeguards.

    Science.gov (United States)

    Iserbyt, Peter; Schouppe, Gilles; Charlier, Nathalie

    2015-04-01

    Research investigating lifeguards' performance of Basic Life Support (BLS) with Automated External Defibrillator (AED) is limited. Assessing simulated BLS/AED performance in Flemish lifeguards and identifying factors affecting this performance. Six hundred and sixteen (217 female and 399 male) certified Flemish lifeguards (aged 16-71 years) performed BLS with an AED on a Laerdal ResusciAnne manikin simulating an adult victim of drowning. Stepwise multiple linear regression analysis was conducted with BLS/AED performance as outcome variable and demographic data as explanatory variables. Mean BLS/AED performance for all lifeguards was 66.5%. Compression rate and depth adhered closely to ERC 2010 guidelines. Ventilation volume and flow rate exceeded the guidelines. A significant regression model, F(6, 415)=25.61, p<.001, ES=.38, explained 27% of the variance in BLS performance (R2=.27). Significant predictors were age (beta=-.31, p<.001), years of certification (beta=-.41, p<.001), time on duty per year (beta=-.25, p<.001), practising BLS skills (beta=.11, p=.011), and being a professional lifeguard (beta=-.13, p=.029). 71% of lifeguards reported not practising BLS/AED. Being young, recently certified, few days of employment per year, practising BLS skills and not being a professional lifeguard are factors associated with higher BLS/AED performance. Measures should be taken to prevent BLS/AED performances from decaying with age and longer certification. Refresher courses could include a formal skills test and lifeguards should be encouraged to practise their BLS/AED skills. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  1. Identify and rank key factors influencing the adoption of cloud computing for a healthy Electronics

    Directory of Open Access Journals (Sweden)

    Javad Shukuhy

    2015-02-01

    Full Text Available Cloud computing as a new technology with Internet infrastructure and new approaches can be significant benefits in providing medical services electronically. Aplying this technology in E-Health requires consideration of various factors. The main objective of this study is to identify and rank the factors influencing the adoption of e-health cloud. Based on the Technology-Organization-Environment (TOE framework and Human-Organization-Technology fit (HOT-fit model, 16 sub-factors were identified in four major factors. With survey of 60 experts, academics and experts in health information technology and with the help of fuzzy analytic hierarchy process had ranked these sub-factors and factors. In the literature, considering newness this study, no internal or external study, have not alluded these number of criteria. The results show that when deciding to adopt cloud computing in E-Health, respectively, must be considered technological, human, organizational and environmental factors.

  2. Using association rule mining to identify risk factors for early childhood caries.

    Science.gov (United States)

    Ivančević, Vladimir; Tušek, Ivan; Tušek, Jasmina; Knežević, Marko; Elheshk, Salaheddin; Luković, Ivan

    2015-11-01

    Early childhood caries (ECC) is a potentially severe disease affecting children all over the world. The available findings are mostly based on a logistic regression model, but data mining, in particular association rule mining, could be used to extract more information from the same data set. ECC data was collected in a cross-sectional analytical study of the 10% sample of preschool children in the South Bačka area (Vojvodina, Serbia). Association rules were extracted from the data by association rule mining. Risk factors were extracted from the highly ranked association rules. Discovered dominant risk factors include male gender, frequent breastfeeding (with other risk factors), high birth order, language, and low body weight at birth. Low health awareness of parents was significantly associated to ECC only in male children. The discovered risk factors are mostly confirmed by the literature, which corroborates the value of the methods. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  3. Identifying risk factors of avian infectious diseases at household level in Poyang Lake region, China.

    Science.gov (United States)

    Jiang, Qian; Zhou, Jieting; Jiang, Zhiben; Xu, Bing

    2014-09-01

    Poultry kept in backyard farms are susceptible to acquiring and spreading infectious diseases because of free ranging and poor biosecurity measures. Since some of these diseases are zoonoses, this is also a significant health concern to breeders and their families. Backyard farms are common in rural regions of China. However, there is lack of knowledge of backyard poultry in the country. To obtain first-hand information of backyard poultry and identify risk factors of avian infectious diseases, a cross-sectional study was carried out at household level in rural regions around Poyang Lake. A door-to-door survey was conducted to collect data on husbandry practices, trading practices of backyard farmers, and surrounding environments of backyard farms. Farms were categorized into cases and controls based on their history of poultry death. Data were collected for 137 farms, and the association with occurrence of poultry death event was explored by chi-square tests. Results showed that vaccination implementation was a protective factor (odds ratio OR=0.40, 95% confidence interval CI: 0.20-0.80, p=0.01), while contact with other backyard flocks increased risk (OR=1.72, 95% CI: 0.79-3.74, p=0.16). A concept of "farm connectivity" characterized by the density of particular land-use types in the vicinity of the farm was proposed to characterize the degree of contact between poultry in one household farm and those in other household farms. It was found that housing density in a 20-m buffer zone of the farmhouse was most significantly associated with poultry death occurrence (OR=1.08, 95% CI: 1.02-1.17, p=0.03), and was in agreement with observation of villagers. Binary logistic regression was applied to evaluate the relationship between poultry death event and density of land-use types in all buffer zones. When integrated with vaccination implementation for poultry, prediction accuracy of poultry death event reached 72.0%. Results combining questionnaire survey with

  4. Human chorionic gonadotrophin regression rate as a predictive factor of postmolar gestational trophoblastic neoplasm in high-risk hydatidiform mole: a case-control study.

    Science.gov (United States)

    Kim, Bo Wook; Cho, Hanbyoul; Kim, Hyunki; Nam, Eun Ji; Kim, Sang Wun; Kim, Sunghoon; Kim, Young Tae; Kim, Jae-Hoon

    2012-01-01

    The aim of this study was early prediction of postmolar gestational trophoblastic neoplasm (GTN) after evacuation of high-risk mole, by comparison of human chorionic gonadotrophin (hCG) regression rates. Fifty patients with a high-risk mole initially and spontaneously regressing after molar evacuation were selected from January 1, 1996 to May 31, 2010 (spontaneous regression group). Fifty patients with a high-risk mole initially and progressing to postmolar GTN after molar evacuation were selected (postmolar GTN group). hCG regression rates represented as hCG/initial hCG were compared between the two groups. The sensitivity and specificity of these rates for prediction of postmolar GTN were assessed using receiver operating characteristic curves. Multivariate analyses of associations between risk factors and postmolar GTN progression were performed. The mean regression rate of hCG between the two groups was compared. hCG regression rates represented as hCG/initial hCG (%) were 0.36% in the spontaneous regression group and 1.45% in the postmolar GTN group in the second week (p=0.003). Prediction of postmolar GTN by hCG regression rate revealed a sensitivity of 48.0% and specificity of 89.5% with a cut-off value of 0.716% and area under the curve (AUC) of 0.759 in the 2nd week (pfactor for postmolar GTN. Crown Copyright © 2011. Published by Elsevier Ireland Ltd. All rights reserved.

  5. Identifying Risk Factors for Drug Use in an Iranian Treatment Sample: A Prediction Approach Using Decision Trees.

    Science.gov (United States)

    Amirabadizadeh, Alireza; Nezami, Hossein; Vaughn, Michael G; Nakhaee, Samaneh; Mehrpour, Omid

    2018-05-12

    Substance abuse exacts considerable social and health care burdens throughout the world. The aim of this study was to create a prediction model to better identify risk factors for drug use. A prospective cross-sectional study was conducted in South Khorasan Province, Iran. Of the total of 678 eligible subjects, 70% (n: 474) were randomly selected to provide a training set for constructing decision tree and multiple logistic regression (MLR) models. The remaining 30% (n: 204) were employed in a holdout sample to test the performance of the decision tree and MLR models. Predictive performance of different models was analyzed by the receiver operating characteristic (ROC) curve using the testing set. Independent variables were selected from demographic characteristics and history of drug use. For the decision tree model, the sensitivity and specificity for identifying people at risk for drug abuse were 66% and 75%, respectively, while the MLR model was somewhat less effective at 60% and 73%. Key independent variables in the analyses included first substance experience, age at first drug use, age, place of residence, history of cigarette use, and occupational and marital status. While study findings are exploratory and lack generalizability they do suggest that the decision tree model holds promise as an effective classification approach for identifying risk factors for drug use. Convergent with prior research in Western contexts is that age of drug use initiation was a critical factor predicting a substance use disorder.

  6. Logistic regression analysis of factors associated with avascular necrosis of the femoral head following femoral neck fractures in middle-aged and elderly patients.

    Science.gov (United States)

    Ai, Zi-Sheng; Gao, You-Shui; Sun, Yuan; Liu, Yue; Zhang, Chang-Qing; Jiang, Cheng-Hua

    2013-03-01

    Risk factors for femoral neck fracture-induced avascular necrosis of the femoral head have not been elucidated clearly in middle-aged and elderly patients. Moreover, the high incidence of screw removal in China and its effect on the fate of the involved femoral head require statistical methods to reflect their intrinsic relationship. Ninety-nine patients older than 45 years with femoral neck fracture were treated by internal fixation between May 1999 and April 2004. Descriptive analysis, interaction analysis between associated factors, single factor logistic regression, multivariate logistic regression, and detailed interaction analysis were employed to explore potential relationships among associated factors. Avascular necrosis of the femoral head was found in 15 cases (15.2 %). Age × the status of implants (removal vs. maintenance) and gender × the timing of reduction were interactive according to two-factor interactive analysis. Age, the displacement of fractures, the quality of reduction, and the status of implants were found to be significant factors in single factor logistic regression analysis. Age, age × the status of implants, and the quality of reduction were found to be significant factors in multivariate logistic regression analysis. In fine interaction analysis after multivariate logistic regression analysis, implant removal was the most important risk factor for avascular necrosis in 56-to-85-year-old patients, with a risk ratio of 26.00 (95 % CI = 3.076-219.747). The middle-aged and elderly have less incidence of avascular necrosis of the femoral head following femoral neck fractures treated by cannulated screws. The removal of cannulated screws can induce a significantly high incidence of avascular necrosis of the femoral head in elderly patients, while a high-quality reduction is helpful to reduce avascular necrosis.

  7. The Promise of Virtual Teams: Identifying Key Factors in Effectiveness and Failure

    Science.gov (United States)

    Horwitz, Frank M.; Bravington, Desmond; Silvis, Ulrik

    2006-01-01

    Purpose: The aim of the investigation is to identify enabling and disenabling factors in the development and operation of virtual teams; to evaluate the importance of factors such as team development, cross-cultural variables, leadership, communication and social cohesion as contributors to virtual team effectiveness. Design/methodology/approach:…

  8. Risk factors for atherosclerosis - can they be used to identify the ...

    African Journals Online (AJOL)

    Risk factors are often used in preventive care programmes to identify the patient at particular risk for developing atherosclerosis. Risk factors for atherosclerosis have also been shown to be linked to the presence of the disease at a given time, a fact that may be helpful when screening for additional atherosclerotic disease in ...

  9. Combined and interactive effects of environmental and GWAS-identified risk factors in ovarian cancer

    DEFF Research Database (Denmark)

    Pearce, Celeste Leigh; Rossing, Mary Anne; Lee, Alice W

    2013-01-01

    There are several well-established environmental risk factors for ovarian cancer, and recent genome-wide association studies have also identified six variants that influence disease risk. However, the interplay between such risk factors and susceptibility loci has not been studied....

  10. Patient and carer identified factors which contribute to safety incidents in primary care: a qualitative study.

    Science.gov (United States)

    Hernan, Andrea L; Giles, Sally J; Fuller, Jeffrey; Johnson, Julie K; Walker, Christine; Dunbar, James A

    2015-09-01

    Patients can have an important role in reducing harm in primary-care settings. Learning from patient experience and feedback could improve patient safety. Evidence that captures patients' views of the various contributory factors to creating safe primary care is largely absent. The aim of this study was to address this evidence gap. Four focus groups and eight semistructured interviews were conducted with 34 patients and carers from south-east Australia. Participants were asked to describe their experiences of primary care. Audio recordings were transcribed verbatim and specific factors that contribute to safety incidents were identified in the analysis using the Yorkshire Contributory Factors Framework (YCFF). Other factors emerging from the data were also ascertained and added to the analytical framework. Thirteen factors that contribute to safety incidents in primary care were ascertained. Five unique factors for the primary-care setting were discovered in conjunction with eight factors present in the YCFF from hospital settings. The five unique primary care contributing factors to safety incidents represented a range of levels within the primary-care system from local working conditions to the upstream organisational level and the external policy context. The 13 factors included communication, access, patient factors, external policy context, dignity and respect, primary-secondary interface, continuity of care, task performance, task characteristics, time in the consultation, safety culture, team factors and the physical environment. Patient and carer feedback of this type could help primary-care professionals better understand and identify potential safety concerns and make appropriate service improvements. The comprehensive range of factors identified provides the groundwork for developing tools that systematically capture the multiple contributory factors to patient safety. Published by the BMJ Publishing Group Limited. For permission to use (where not

  11. Predictive factors on the efficacy and risk/intensity of tooth sensitivity of dental bleaching: A multi regression and logistic analysis.

    Science.gov (United States)

    Rezende, Márcia; Loguercio, Alessandro D; Kossatz, Stella; Reis, Alessandra

    2016-02-01

    The aim of this study was to identify predictor factors associated with the whitening outcome and risk and intensity of bleaching-induced tooth sensitivity from pooled data of 11 clinical trials of dental bleaching performed by the same research group. The individual patient data of several published and ongoing studies about dental bleaching was collected and retrospectively analyzed. At the patient-level, independent variables (bleaching techniques [at-home and in-office protocols], sex, age and baseline tooth color in shade guide unit [SGU]) as well as dependent variables (color change in shade guide units (ΔSGU), color change in the CIEL*a*b* system (ΔE), risk and intensity of TS in a visual analog scale) were collected. Multivariable linear regression and multivariable logistic regression models were carried out using backward elimination whenever the p-values were higher than 0.05. A significant relationship between baseline color and age on color change estimates was detected (pwhitening degree of 0.07 for the final ΔSGU and 0.69 for the ΔE. The bleaching technique was shown to be a significant predictor of ΔSGU (prisk of TS for at-home bleaching was 51% (95% CI 41.4-60.6) and for the in-office 62.9% (95% CI 56.9-67.3). Younger patients with darker teeth reach a higher degree of whitening. Patient with darker teeth and submitted to at-home bleaching presents lower risk and intensity of TS. The baseline color of the teeth and the patient's age is directly related to the effectiveness of dental bleaching and TS. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Pediatric malignant hyperthermia: risk factors, morbidity, and mortality identified from the Nationwide Inpatient Sample and Kids' Inpatient Database.

    Science.gov (United States)

    Salazar, Jose H; Yang, Jingyan; Shen, Liang; Abdullah, Fizan; Kim, Tae W

    2014-12-01

    Malignant Hyperthermia (MH) is a potentially fatal metabolic disorder. Due to its rarity, limited evidence exists about risk factors, morbidity, and mortality especially in children. Using the Nationwide Inpatient Sample and the Kid's Inpatient Database (KID), admissions with the ICD-9 code for MH (995.86) were extracted for patients 0-17 years of age. Demographic characteristics were analyzed. Logistic regression was performed to identify patient and hospital characteristics associated with mortality. A subset of patients with a surgical ICD-9 code in the KID was studied to calculate the prevalence of MH in the dataset. A total of 310 pediatric admissions were seen in 13 nonoverlapping years of data. Patients had a mortality of 2.9%. Male sex was predominant (64.8%), and 40.5% of the admissions were treated at centers not identified as children's hospitals. The most common associated diagnosis was rhabdomyolysis, which was present in 26 cases. Regression with the outcome of mortality did not yield significant differences between demographic factors, age, sex race, or hospital type, pediatric vs nonpediatric. Within a surgical subset of 530,449 admissions, MH was coded in 55, giving a rate of 1.04 cases per 10,000 cases. This study is the first to combine two large databases to study MH in the pediatric population. The analysis provides an insight into the risk factors, comorbidities, mortality, and prevalence of MH in the United States population. Until more methodologically rigorous, large-scale studies are done, the use of databases will continue to be the optimal method to study rare diseases. © 2014 John Wiley & Sons Ltd.

  13. Identifying factors which enhance capacity to engage in clinical education among podiatry practitioners: an action research project.

    Science.gov (United States)

    Abey, Sally; Lea, Susan; Callaghan, Lynne; Shaw, Steve; Cotton, Debbie

    2015-01-01

    Health profession students develop practical skills whilst integrating theory with practice in a real world environment as an important component of their training. Research in the area of practice placements has identified challenges and barriers to the delivery of effective placement learning. However, there has been little research in podiatry and the question of which factors impact upon clinical educators' capacity to engage with the role remains an under-researched area. This paper presents the second phase of an action research project designed to determine the factors that impact upon clinical educators' capacity to engage with the mentorship role. An online survey was developed and podiatry clinical educators recruited through National Health Service (NHS) Trusts. The survey included socio-demographic items, and questions relating to the factors identified as possible variables influencing clinical educator capacity; the latter was assessed using the 'Clinical Educator Capacity to Engage' scale (CECE). Descriptive statistics were used to explore demographic data whilst the relationship between the CECE and socio-demographic factors were examined using inferential statistics in relation to academic profile, career profile and organisation of the placement. The survey response rate was 42 % (n = 66). Multiple linear regression identified four independent variables which explain a significant proportion of the variability of the dependent variable, 'capacity to engage with clinical education', with an adjusted R2 of 0.428. The four variables were: protected mentorship time, clinical educator relationship with university, sign-off responsibility, and volunteer status. The identification of factors that impact upon clinical educators' capacity to engage in mentoring of students has relevance for strategic planning and policy-making with the emphasis upon capacity-building at an individual level, so that the key attitudes and characteristics that are linked

  14. Factors affecting CO_2 emissions in China’s agriculture sector: Evidence from geographically weighted regression model

    International Nuclear Information System (INIS)

    Xu, Bin; Lin, Boqiang

    2017-01-01

    China is currently the world's largest emitter of carbon dioxide. Considered as a large agricultural country, carbon emission in China’s agriculture sector keeps on growing rapidly. It is, therefore, of great importance to investigate the driving forces of carbon dioxide emissions in this sector. The traditional regression estimation can only get “average” and “global” parameter estimates; it excludes the “local” parameter estimates which vary across space in some spatial systems. Geographically weighted regression embeds the latitude and longitude of the sample data into the regression parameters, and uses the local weighted least squares method to estimate the parameters point–by–point. To reveal the nonstationary spatial effects of driving forces, geographically weighted regression model is employed in this paper. The results show that economic growth is positively correlated with emissions, with the impact in the western region being less than that in the central and eastern regions. Urbanization is positively related to emissions but produces opposite effects pattern. Energy intensity is also correlated with emissions, with a decreasing trend from the eastern region to the central and western regions. Therefore, policymakers should take full account of the spatial nonstationarity of driving forces in designing emission reduction policies. - Highlights: • We explore the driving forces of CO_2 emissions in the agriculture sector. • Urbanization is positively related to emissions but produces opposite effect pattern. • The effect of energy intensity declines from the eastern region to western region.

  15. Familial Autoimmune Thyroid Disease as a Risk Factor for Regression in Children with Autism Spectrum Disorder: A CPEA Study

    Science.gov (United States)

    Molloy, Cynthia A.; Morrow, Ardythe L.; Meinzen-Derr, Jareen; Dawson, Geraldine; Bernier, Raphael; Dunn, Michelle; Hyman, Susan L.; McMahon, William M.; Goudie-Nice, Julie; Hepburn, Susan; Minshew, Nancy; Rogers, Sally; Sigman, Marian; Spence, M. Anne; Tager-Flusberg, Helen; Volkmar, Fred R.; Lord, Catherine

    2006-01-01

    A multicenter study of 308 children with Autism Spectrum Disorder (ASD) was conducted through the Collaborative Programs of Excellence in Autism (CPEA), sponsored by the National Institute of Child Health and Human Development, to compare the family history of autoimmune disorders in children with ASD with and without a history of regression. A…

  16. Risk factors identified for owner-reported feline obesity at around one year of age: Dry diet and indoor lifestyle.

    Science.gov (United States)

    Rowe, Elizabeth; Browne, William; Casey, Rachel; Gruffydd-Jones, Tim; Murray, Jane

    2015-10-01

    Obesity is considered the second most common health problem in pet cats in developed countries. Previous studies investigating risk factors for feline obesity have been cross-sectional, where reverse causality cannot be ruled out. This study is the first to use prospective data from a large scale longitudinal study of pet cats ('Bristol Cats') to identify early-life risk factors for feline overweight/obesity at around one year of age. Data analysed were collected via three owner-completed questionnaires (for cats aged 2-4 months, 6.5-7 months and 12.5-13 months) completed between May 2010 and August 2013. Owner-reported body condition scores (BCS) of cats at age 12.5-13 months, using the 5-point system, were categorised into a dichotomous variable: overweight/obese (BCS 4-5) and not overweight (BCS 1-3) and used as the dependent variable. Cat breed, neuter status, outdoor access, type of diet, frequency of wet and dry food fed and frequency of treats fed were analysed as potential risk factors. Of the 966 cats for which data were available, 7.0% were reported by their owners to be overweight/obese at 12.5-13 months of age. Descriptive data on type of diet fed at different cat ages suggest that a dry diet is the most popular choice for UK domestic cats. Significant potential explanatory variables from univariable logistic regression models were included in multivariable logistic regression models built using stepwise forward-selection. To account for potential hierarchical clustering of data due to multi-cat households these were extended to two-level random intercept models. Models were compared using Wald test p- values. Clustering had no impact on the analysis. The final multivariable logistic regression model identified two risk factors that were independently associated with an increased risk of feline obesity developing at 12.5-13 months of age: restricted or no outdoor access and feeding dry food as the only or major (>50%) type of food in the diet at age 12

  17. Autistic Regression

    Science.gov (United States)

    Matson, Johnny L.; Kozlowski, Alison M.

    2010-01-01

    Autistic regression is one of the many mysteries in the developmental course of autism and pervasive developmental disorders not otherwise specified (PDD-NOS). Various definitions of this phenomenon have been used, further clouding the study of the topic. Despite this problem, some efforts at establishing prevalence have been made. The purpose of…

  18. Identifying changes in dissolved organic matter content and characteristics by fluorescence spectroscopy coupled with self-organizing map and classification and regression tree analysis during wastewater treatment.

    Science.gov (United States)

    Yu, Huibin; Song, Yonghui; Liu, Ruixia; Pan, Hongwei; Xiang, Liancheng; Qian, Feng

    2014-10-01

    The stabilization of latent tracers of dissolved organic matter (DOM) of wastewater was analyzed by three-dimensional excitation-emission matrix (EEM) fluorescence spectroscopy coupled with self-organizing map and classification and regression tree analysis (CART) in wastewater treatment performance. DOM of water samples collected from primary sedimentation, anaerobic, anoxic, oxic and secondary sedimentation tanks in a large-scale wastewater treatment plant contained four fluorescence components: tryptophan-like (C1), tyrosine-like (C2), microbial humic-like (C3) and fulvic-like (C4) materials extracted by self-organizing map. These components showed good positive linear correlations with dissolved organic carbon of DOM. C1 and C2 were representative components in the wastewater, and they were removed to a higher extent than those of C3 and C4 in the treatment process. C2 was a latent parameter determined by CART to differentiate water samples of oxic and secondary sedimentation tanks from the successive treatment units, indirectly proving that most of tyrosine-like material was degraded by anaerobic microorganisms. C1 was an accurate parameter to comprehensively separate the samples of the five treatment units from each other, indirectly indicating that tryptophan-like material was decomposed by anaerobic and aerobic bacteria. EEM fluorescence spectroscopy in combination with self-organizing map and CART analysis can be a nondestructive effective method for characterizing structural component of DOM fractions and monitoring organic matter removal in wastewater treatment process. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Identifying risk factors for first-episode neck pain: A systematic review.

    Science.gov (United States)

    Kim, Rebecca; Wiest, Colin; Clark, Kelly; Cook, Chad; Horn, Maggie

    2018-02-01

    Neck pain affects 15.1% of the United States' general population every 3 months, and ranks fourth in global disability. Because of the tendency for neck pain to become a chronic issue, it is important to identify risk factors that could encourage prevention and early diagnosis. The purpose of this systematic review was to identify risk factors for a first episode of neck pain. Three databases were searched with key words such as "neck pain" and "first incidence." Risk factors from the resulting articles were reported as either a physical or psychosocial risk factor and ranked by the strength of their odds/risk/hazard ratio: empowering leadership, high perceived social climate, leisure physical activity, and cervical extensor endurance. Most risk factors found for neck pain were related to psychosocial characteristics, rather than physical characteristics. A number of these risk factors were mediating factors, suggesting that a prevention-based program may be useful in modifying the existence of the risk factors before the occurrence of neck pain. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Identifying risk factors for PTSD in women seeking medical help after rape

    OpenAIRE

    Möller, Anna Tiihonen; Bäckström, Torbjörn; Söndergaard, Hans Peter; Helström, Lotti

    2014-01-01

    Objectives: Rape has been found to be the trauma most commonly associated with Posttraumatic Stress Disorder (PTSD) among women. It is therefore important to be able to identify those women at greatest risk of developing PTSD. The aims of the present study were to analyze the PTSD prevalence six months after sexual assaults and identify the major risk factors for developing PTSD. Methods: Participants were 317 female victims of rape who sought help at the Emergency Clinic for Raped Women at S...

  1. [Application of regression tree in analyzing the effects of climate factors on NDVI in loess hilly area of Shaanxi Province].

    Science.gov (United States)

    Liu, Yang; Lü, Yi-he; Zheng, Hai-feng; Chen, Li-ding

    2010-05-01

    Based on the 10-day SPOT VEGETATION NDVI data and the daily meteorological data from 1998 to 2007 in Yan' an City, the main meteorological variables affecting the annual and interannual variations of NDVI were determined by using regression tree. It was found that the effects of test meteorological variables on the variability of NDVI differed with seasons and time lags. Temperature and precipitation were the most important meteorological variables affecting the annual variation of NDVI, and the average highest temperature was the most important meteorological variable affecting the inter-annual variation of NDVI. Regression tree was very powerful in determining the key meteorological variables affecting NDVI variation, but could not build quantitative relations between NDVI and meteorological variables, which limited its further and wider application.

  2. Risk Factors for Chronic Subdural Hematoma Recurrence Identified Using Quantitative Computed Tomography Analysis of Hematoma Volume and Density.

    Science.gov (United States)

    Stavrinou, Pantelis; Katsigiannis, Sotirios; Lee, Jong Hun; Hamisch, Christina; Krischek, Boris; Mpotsaris, Anastasios; Timmer, Marco; Goldbrunner, Roland

    2017-03-01

    Chronic subdural hematoma (CSDH), a common condition in elderly patients, presents a therapeutic challenge with recurrence rates of 33%. We aimed to identify specific prognostic factors for recurrence using quantitative analysis of hematoma volume and density. We retrospectively reviewed radiographic and clinical data of 227 CSDHs in 195 consecutive patients who underwent evacuation of the hematoma through a single burr hole, 2 burr holes, or a mini-craniotomy. To examine the relationship between hematoma recurrence and various clinical, radiologic, and surgical factors, we used quantitative image-based analysis to measure the hematoma and trapped air volumes and the hematoma densities. Recurrence of CSDH occurred in 35 patients (17.9%). Multivariate logistic regression analysis revealed that the percentage of hematoma drained and postoperative CSDH density were independent risk factors for recurrence. All 3 evacuation methods were equally effective in draining the hematoma (71.7% vs. 73.7% vs. 71.9%) without observable differences in postoperative air volume captured in the subdural space. Quantitative image analysis provided evidence that percentage of hematoma drained and postoperative CSDH density are independent prognostic factors for subdural hematoma recurrence. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Linear regression

    CERN Document Server

    Olive, David J

    2017-01-01

    This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...

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

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  5. An exploratory study to identify critical factors of innovation culture in organizations

    Directory of Open Access Journals (Sweden)

    Hamed Asgari

    2013-07-01

    Full Text Available During the past two decades, there has been a growing trend on knowledge-based organizations. Innovation, on the other hand, plays essential role on building competitive business units. In this paper, we present an exploratory study to identify critical factors of innovation culture in organizations. We detect important factors influencing innovation culture in construction industry based on the implementation of factor analysis. The proposed study designs a questionnaire and distributes it among 400 experts who are involved in construction industry. Cronbach alpha has been calculated as 0.779, which validates the overall questionnaire. The results of factor analysis have indicated that six factors of building cultural infrastructures, education, organizational vision, established culture, strategic culture and flexible culture are the most important items influencing innovation culture.

  6. Organisational Issues for E-Learning: Critical Success Factors as Identified by HE Practitioners

    Science.gov (United States)

    McPherson, Maggie; Nunes, Miguel Baptista

    2006-01-01

    Purpose: The purpose of this paper is to report on a research project that identified organisational critical success factors (CSFs) for e-learning implementation in higher education (HE). These CSFs can be used as a theoretical foundation upon which to base decision-making and strategic thinking about e-learning. Design/methodology/approach: The…

  7. Using exploratory factor analysis of FFQ data to identify dietary patterns among Yup'ik people.

    Science.gov (United States)

    Ryman, Tove K; Austin, Melissa A; Hopkins, Scarlett; Philip, Jacques; O'Brien, Diane; Thummel, Kenneth; Boyer, Bert B

    2014-03-01

    An FFQ developed by the Center for Alaska Native Health Research for studies in Yup'ik people includes market foods and subsistence foods such as moose, seal, waterfowl and salmon that may be related to disease risk. Because the FFQ contains >100 food items, we sought to characterize dietary patterns more simply for use in ongoing pharmacogenomics studies. Exploratory factor analysis was used to derive a small number of 'factors' that explain a substantial amount of the variation in the Yup'ik diet. We estimated factor scores and measured associations with demographic characteristics and biomarkers. South-west Alaska, USA. Yup'ik people (n 358) aged ≥18 years. We identified three factors that each accounted for ≥10 % of the common variance: the first characterized by 'processed foods' (e.g. salty snacks, sweetened cereals); the second by 'fruits and vegetables' (e.g. fresh citrus, potato salad); and the third by 'subsistence foods' (seal or walrus soup, non-oily fish). Participants from coastal communities had higher values for the 'subsistence' factor, whereas participants from inland communities had higher values for the 'fruits and vegetables' factor. A biomarker of marine intake, δ 15N, was correlated with the 'subsistence' factor, whereas a biomarker of corn- and sugarcane-based market food intake, δ 13C, was correlated with 'processed foods'. The exploratory factor analysis identified three factors that appeared to reflect dietary patterns among Yup'ik based on associations with participant characteristics and biomarkers. These factors will be useful for chronic disease studies in this population.

  8. Robust Nonnegative Matrix Factorization via Joint Graph Laplacian and Discriminative Information for Identifying Differentially Expressed Genes

    Directory of Open Access Journals (Sweden)

    Ling-Yun Dai

    2017-01-01

    Full Text Available Differential expression plays an important role in cancer diagnosis and classification. In recent years, many methods have been used to identify differentially expressed genes. However, the recognition rate and reliability of gene selection still need to be improved. In this paper, a novel constrained method named robust nonnegative matrix factorization via joint graph Laplacian and discriminative information (GLD-RNMF is proposed for identifying differentially expressed genes, in which manifold learning and the discriminative label information are incorporated into the traditional nonnegative matrix factorization model to train the objective matrix. Specifically, L2,1-norm minimization is enforced on both the error function and the regularization term which is robust to outliers and noise in gene data. Furthermore, the multiplicative update rules and the details of convergence proof are shown for the new model. The experimental results on two publicly available cancer datasets demonstrate that GLD-RNMF is an effective method for identifying differentially expressed genes.

  9. Depression in Intimate Partner Violence Victims in Slovenia: A Crippling Pattern of Factors Identified in Family Practice Attendees

    Directory of Open Access Journals (Sweden)

    Nena Kopčavar Guček

    2018-01-01

    Full Text Available This multi-centre cross-sectional study explored associations between prevalence of depression and exposure to intimate partner violence (IPV at any time in patients’ adult life in 471 participants of a previous IPV study. In 2016, 174 interviews were performed, using the Short Form Domestic Violence Exposure Questionnaire, the Zung Scale and questions about behavioural patterns of exposure to IPV. Family doctors reviewed patients’ medical charts for period from 2012 to 2016, using the Domestic Violence Exposure Medical Chart Check List, for conditions which persisted for at least three years. Depression was found to be associated with any exposure to IPV in adult life and was more likely to affect women. In multivariable logistic regression modelling, factors associated with self-rated depression were identified (p < 0.05. Exposure to emotional and physical violence was identified as a risk factor in the first model, explaining 23% of the variance. The second model explained 66% of the variance; past divorce, dysfunctional family relationships and a history of incapacity to work increased the likelihood of depression in patients. Family doctors should consider IPV exposure when detecting depression, since lifetime IPV exposure was found to be 40.4% and 36.9% of depressed revealed it.

  10. Depression in Intimate Partner Violence Victims in Slovenia: A Crippling Pattern of Factors Identified in Family Practice Attendees.

    Science.gov (United States)

    Guček, Nena Kopčavar; Selič, Polona

    2018-01-26

    This multi-centre cross-sectional study explored associations between prevalence of depression and exposure to intimate partner violence (IPV) at any time in patients' adult life in 471 participants of a previous IPV study. In 2016, 174 interviews were performed, using the Short Form Domestic Violence Exposure Questionnaire, the Zung Scale and questions about behavioural patterns of exposure to IPV. Family doctors reviewed patients' medical charts for period from 2012 to 2016, using the Domestic Violence Exposure Medical Chart Check List, for conditions which persisted for at least three years. Depression was found to be associated with any exposure to IPV in adult life and was more likely to affect women. In multivariable logistic regression modelling, factors associated with self-rated depression were identified (p < 0.05). Exposure to emotional and physical violence was identified as a risk factor in the first model, explaining 23% of the variance. The second model explained 66% of the variance; past divorce, dysfunctional family relationships and a history of incapacity to work increased the likelihood of depression in patients. Family doctors should consider IPV exposure when detecting depression, since lifetime IPV exposure was found to be 40.4% and 36.9% of depressed revealed it.

  11. Identifying the necessary and sufficient number of risk factors for predicting academic failure.

    Science.gov (United States)

    Lucio, Robert; Hunt, Elizabeth; Bornovalova, Marina

    2012-03-01

    Identifying the point at which individuals become at risk for academic failure (grade point average [GPA] academic success or failure. This study focused on 12 school-related factors. Using a thorough 5-step process, we identified which unique risk factors place one at risk for academic failure. Academic engagement, academic expectations, academic self-efficacy, homework completion, school relevance, school safety, teacher relationships (positive relationship), grade retention, school mobility, and school misbehaviors (negative relationship) were uniquely related to GPA even after controlling for all relevant covariates. Next, a receiver operating characteristic curve was used to determine a cutoff point for determining how many risk factors predict academic failure (GPA academic failure, which provides a way for early identification of individuals who are at risk. Further implications of these findings are discussed. PsycINFO Database Record (c) 2012 APA, all rights reserved.

  12. Prediction of Foreign Object Debris/Damage type based in human factors for aeronautics using logistic regression model

    Science.gov (United States)

    Romo, David Ricardo

    Foreign Object Debris/Damage (FOD) has been an issue for military and commercial aircraft manufacturers since the early ages of aviation and aerospace. Currently, aerospace is growing rapidly and the chances of FOD presence are growing as well. One of the principal causes in manufacturing is the human error. The cost associated with human error in commercial and military aircrafts is approximately accountable for 4 billion dollars per year. This problem is currently addressed with prevention programs, elimination techniques, and designation of FOD areas, controlled access, restrictions of personal items entering designated areas, tool accountability, and the use of technology such as Radio Frequency Identification (RFID) tags, etc. All of the efforts mentioned before, have not show a significant occurrence reduction in terms of manufacturing processes. On the contrary, a repetitive path of occurrence is present, and the cost associated has not declined in a significant manner. In order to address the problem, this thesis proposes a new approach using statistical analysis. The effort of this thesis is to create a predictive model using historical categorical data from an aircraft manufacturer only focusing in human error causes. The use of contingency tables, natural logarithm of the odds and probability transformation is used in order to provide the predicted probabilities of each aircraft. A case of study is shown in this thesis in order to show the applied methodology. As a result, this approach is able to predict the possible outcomes of FOD by the workstation/area needed, and monthly predictions per workstation. This thesis is intended to be the starting point of statistical data analysis regarding FOD in human factors. The purpose of this thesis is to identify the areas where human error is the primary cause of FOD occurrence in order to design and implement accurate solutions. The advantages of the proposed methodology can go from the reduction of cost

  13. Identifying Contextual Factors of Employee Satisfaction of Performance Management at a Thai State Enterprise

    Directory of Open Access Journals (Sweden)

    Molraudee Saratun

    2013-11-01

    Full Text Available Normal 0 false false false IN X-NONE X-NONE MicrosoftInternetExplorer4 Although there has been an increase in Performance Management (PM literature over the years arguing that PM perceptions are likely to be a function of PM process components and contextual factors, the actual relationship between the contextual factors and employee satisfaction of PM remains little explored.  Extending previous research, this study examines relationships between contextual factors and employees’ PM satisfaction.  Derived from the literature, these contextual factors are motivation and empowerment of employees, role conflict, role ambiguity, perceived organisational support, procedural justice and distributive justice.  Seven directional hypotheses are tested accordingly through a series of regression analyses.  This article finds that these contextual factors, with the exception of role conflict, are directly predictive of enhanced employees’ PM satisfaction at the Thai state enterprise. Keywords: Performance management, contextual factors, performance management satisfaction, public organisations, Thailand. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

  14. Identifying Watershed, Landscape, and Engineering Design Factors that Influence the Biotic Condition of Restored Streams

    Directory of Open Access Journals (Sweden)

    Barbara Doll

    2016-04-01

    Full Text Available Restored stream reaches at 79 sites across North Carolina were sampled for aquatic macroinvertebrates using a rapid bioassessment protocol. Morphological design parameters and geographic factors, including watershed and landscape parameters (e.g., valley slope, substrate, were also compiled for these streams. Principal component regression analyses revealed correlations between design and landscape variables with macroinvertebrate metrics. The correlations were strengthened by adding watershed variables. Ridge regression was used to find the best-fit model for predicting dominant taxa from the “pollution sensitive” orders of Ephemeroptera (mayflies, Plecoptera (stoneflies, and Trichoptera (caddisflies, or EPT taxa, resulting in coefficient weights that were most interpretable relative to site selection and design parameters. Results indicate that larger (wider streams located in the mountains and foothills where there are steeper valleys, larger substrate, and undeveloped watersheds are expected to have higher numbers of dominant EPT taxa. In addition, EPT taxa numbers are positively correlated with accessible floodplain width and negatively correlated with width-to-depth ratio and sinuosity. This study indicates that both site selection and design should be carefully considered in order to maximize the resulting biotic condition and associated potential ecological uplift of the stream.

  15. Identifying Factors Reinforcing Robotization: Interactive Forces of Employment, Working Hour and Wage

    Directory of Open Access Journals (Sweden)

    Joonmo Cho

    2018-02-01

    Full Text Available Unlike previous studies on robotization approaching the future based on the cutting-edge technologies and adopting a framework where robotization is considered as an exogenous variable, this study considers that robotization occurs endogenously and uses it as a dependent variable for an objective examination of the effect of robotization on the labor market. To this end, a robotization indicator is created based on the actual number of industrial robots currently deployed in workplaces, and a multiple regression analysis is performed using the robotization indicator and labor variables such as employment, working hours, and wage. The results using the multiple regression considering the triangular relationship of employment–working-hours–wages show that job destruction due to robotization is not too remarkable yet that use. Our results show the complementary relation between employment and robotization, but the substituting relation between working hour and robotization. The results also demonstrate the effects of union, the size of the company and the proportion of production workers and simple labor workers etc. These findings indicate that the degree of robotization may vary with many factors of the labor market. Limitations of this study and implications for future research are also discussed.

  16. A method to identify dependencies between organizational factors using statistical independence test

    International Nuclear Information System (INIS)

    Kim, Y.; Chung, C.H.; Kim, C.; Jae, M.; Jung, J.H.

    2004-01-01

    A considerable number of studies on organizational factors in nuclear power plants have been made especially in recent years, most of which have assumed organizational factors to be independent. However, since organizational factors characterize the organization in terms of safety and efficiency etc. and there would be some factors that have close relations between them. Therefore, from whatever point of view, if we want to identify the characteristics of an organization, the dependence relationships should be considered to get an accurate result. In this study the organization of a reference nuclear power plant in Korea was analyzed for the trip cases of that plant using 20 organizational factors that Jacobs and Haber had suggested: 1) coordination of work, 2) formalization, 3) organizational knowledge, 4) roles and responsibilities, 5) external communication, 6) inter-department communications, 7) intra-departmental communications, 8) organizational culture, 9) ownership, 10) safety culture, 11) time urgency, 12) centralization, 13) goal prioritization, 14) organizational learning, 15) problem identification, 16) resource allocation, 17) performance evaluation, 18) personnel selection, 19) technical knowledge, and 20) training. By utilizing the results of the analysis, a method to identify the dependence relationships between organizational factors is presented. The statistical independence test for the analysis result of the trip cases is adopted to reveal dependencies. This method is geared to the needs to utilize many kinds of data that has been obtained as the operating years of nuclear power plants increase, and more reliable dependence relations may be obtained by using these abundant data

  17. Identifying Key Drivers of Return Reversal with Dynamical Bayesian Factor Graph.

    Directory of Open Access Journals (Sweden)

    Shuai Zhao

    Full Text Available In the stock market, return reversal occurs when investors sell overbought stocks and buy oversold stocks, reversing the stocks' price trends. In this paper, we develop a new method to identify key drivers of return reversal by incorporating a comprehensive set of factors derived from different economic theories into one unified dynamical Bayesian factor graph. We then use the model to depict factor relationships and their dynamics, from which we make some interesting discoveries about the mechanism behind return reversals. Through extensive experiments on the US stock market, we conclude that among the various factors, the liquidity factors consistently emerge as key drivers of return reversal, which is in support of the theory of liquidity effect. Specifically, we find that stocks with high turnover rates or high Amihud illiquidity measures have a greater probability of experiencing return reversals. Apart from the consistent drivers, we find other drivers of return reversal that generally change from year to year, and they serve as important characteristics for evaluating the trends of stock returns. Besides, we also identify some seldom discussed yet enlightening inter-factor relationships, one of which shows that stocks in Finance and Insurance industry are more likely to have high Amihud illiquidity measures in comparison with those in other industries. These conclusions are robust for return reversals under different thresholds.

  18. Identify the Important Decision Factors of Online Shopping Adoption in Indonesia

    Directory of Open Access Journals (Sweden)

    Lailatul HIJRAH

    2017-12-01

    Full Text Available The objective of this study is to identify factors encouraging a consumer to engage in online shopping activities. The expected contribution of this study is for online entrepreneurs, in order to develop the most suitable business strategy, so that it will be clearly identified and sorted out which factors are the most important and the main motivation of Indonesian consumers to shop via online by using responses from respondents who usually shop online and offline in 3 cities in Indonesia, Jakarta, Surabaya and Samarinda. The research instruments were developed by conducting FGDs on relevant groups, either academics, online shopping activists, suppliers and courier businessmen in Jakarta, Surabaya and Samarinda Cities in effort to extract any information that encourages consumers to online shopping. After conducting FGD, the researcher produced 48 items proposed for factor analysis and after extracted to form eleven constructs, some items were removed because they had less loading factors. The eleven constructs or dimensions are trust, risk, consumer factors, website factors, price, service quality, convenience, subjective norm, product guarantee, variety of products and lifestyle. The implications of this study provide valuable insights about consumer decisions to online shopping or not online shopping.

  19. Identifying and ranking the factors affecting entrepreneurial marketing to facilitate exports

    Directory of Open Access Journals (Sweden)

    Mehdi Habibzadeh

    2016-04-01

    Full Text Available Small and medium enterprises (SMEs are believed the most important components of today’s businesses and they can boost the growth of economy. This paper presents an empirical investigation to identify and rank important factors influencing on entrepreneurial marketing to facilitate exports of SMEs. The study designs a questionnaire in Likert scale and distributes it among 387 randomly selected entrepreneurs who act as managers of some SMEs in city of Tehran, Iran. Cronbach alpha is calculated as 0.873, which is well above the acceptable level. Using principle component analysis, the study has determined four factors including competitive intelligence, competitive advantage, external factors and internal factors to facilitate the export of SMEs.

  20. Linking demand and supply factors in identifying cultural ecosystem services of urban green infrastructures

    DEFF Research Database (Denmark)

    Hegetschweiler, K. Tessa; de Vries, Sjerp; Arnberger, Arne

    2017-01-01

    and supply factors together. The aim was to provide an overview of this highly interdisciplinary research, to describe how these linkages are being made and to identify which factors significantly influence dependent variables such as levels of use, activities or health and well-being benefits. Commonly used......Urban green infrastructure provides a number of cultural ecosystem services that are greatly appreciated by the public. In order to benefit from these services, actual contact with the respective ecosystem is often required. Furthermore, the type of services offered depend on the physical...... characteristics of the ecosystem. We conducted a review of publications dealing with demand or social factors such as user needs, preferences and values as well as spatially explicit supply or physical factors such as amount of green space, (bio)diversity, recreational infrastructure, etc. and linking demand...

  1. Local acceptance of wind energy: Factors of success identified in French and German case studies

    International Nuclear Information System (INIS)

    Jobert, Arthur; Laborgne, Pia; Mimler, Solveig

    2007-01-01

    The objective of this paper is to identify and analyse factors that are important for winning acceptance of wind-energy parks on the local level. The developers of wind-energy parks need to know how to manage 'social acceptance' at the different stages of planning, realisation and operation. Five case studies in France and Germany focused on factors of success in developing a wind-energy project on a given site and illuminated how policy frameworks influence local acceptance. Our hypothesis is that these factors fall into two categories: institutional conditions, such as economic incentives and regulations; and site-specific conditions (territorial factors), such as the local economy, the local geography, local actors, and the actual on-site planning process (project management)

  2. Identifying context factors explaining physician's low performance in communication assessment: an explorative study in general practice.

    Science.gov (United States)

    Essers, Geurt; van Dulmen, Sandra; van Weel, Chris; van der Vleuten, Cees; Kramer, Anneke

    2011-12-13

    Communication is a key competence for health care professionals. Analysis of registrar and GP communication performance in daily practice, however, suggests a suboptimal application of communication skills. The influence of context factors could reveal why communication performance levels, on average, do not appear adequate. The context of daily practice may require different skills or specific ways of handling these skills, whereas communication skills are mostly treated as generic. So far no empirical analysis of the context has been made. Our aim was to identify context factors that could be related to GP communication. A purposive sample of real-life videotaped GP consultations was analyzed (N = 17). As a frame of reference we chose the MAAS-Global, a widely used assessment instrument for medical communication. By inductive reasoning, we analyzed the GP behaviour in the consultation leading to poor item scores on the MAAS-Global. In these cases we looked for the presence of an intervening context factor, and how this might explain the actual GP communication behaviour. We reached saturation after having viewed 17 consultations. We identified 19 context factors that could potentially explain the deviation from generic recommendations on communication skills. These context factors can be categorized into doctor-related, patient-related, and consultation-related factors. Several context factors seem to influence doctor-patient communication, requiring the GP to apply communication skills differently from recommendations on communication. From this study we conclude that there is a need to explicitly account for context factors in the assessment of GP (and GP registrar) communication performance. The next step is to validate our findings.

  3. Sensitized mutagenesis screen in Factor V Leiden mice identifies thrombosis suppressor loci.

    Science.gov (United States)

    Westrick, Randal J; Tomberg, Kärt; Siebert, Amy E; Zhu, Guojing; Winn, Mary E; Dobies, Sarah L; Manning, Sara L; Brake, Marisa A; Cleuren, Audrey C; Hobbs, Linzi M; Mishack, Lena M; Johnston, Alexander J; Kotnik, Emilee; Siemieniak, David R; Xu, Jishu; Li, Jun Z; Saunders, Thomas L; Ginsburg, David

    2017-09-05

    Factor V Leiden ( F5 L ) is a common genetic risk factor for venous thromboembolism in humans. We conducted a sensitized N -ethyl- N -nitrosourea (ENU) mutagenesis screen for dominant thrombosuppressor genes based on perinatal lethal thrombosis in mice homozygous for F5 L ( F5 L/L ) and haploinsufficient for tissue factor pathway inhibitor ( Tfpi +/- ). F8 deficiency enhanced the survival of F5 L/L Tfpi +/- mice, demonstrating that F5 L/L Tfpi +/- lethality is genetically suppressible. ENU-mutagenized F5 L/L males and F5 L/+ Tfpi +/- females were crossed to generate 6,729 progeny, with 98 F5 L/L Tfpi +/- offspring surviving until weaning. Sixteen lines, referred to as "modifier of Factor 5 Leiden ( MF5L1-16 )," exhibited transmission of a putative thrombosuppressor to subsequent generations. Linkage analysis in MF5L6 identified a chromosome 3 locus containing the tissue factor gene ( F3 ). Although no ENU-induced F3 mutation was identified, haploinsufficiency for F3 ( F3 +/- ) suppressed F5 L/L Tfpi +/- lethality. Whole-exome sequencing in MF5L12 identified an Actr2 gene point mutation (p.R258G) as the sole candidate. Inheritance of this variant is associated with suppression of F5 L/L Tfpi +/- lethality ( P = 1.7 × 10 -6 ), suggesting that Actr2 p.R258G is thrombosuppressive. CRISPR/Cas9 experiments to generate an independent Actr2 knockin/knockout demonstrated that Actr2 haploinsufficiency is lethal, supporting a hypomorphic or gain-of-function mechanism of action for Actr2 p.R258G Our findings identify F8 and the Tfpi/F3 axis as key regulators in determining thrombosis balance in the setting of F5 L and also suggest a role for Actr2 in this process.

  4. Regression of L-NAME−Induced Hypertension: The Role of Nitric Oxide and Endothelium-Derived Constricting Factor

    Czech Academy of Sciences Publication Activity Database

    Paulis, Ĺudovít; Zicha, Josef; Kuneš, Jaroslav; Hojná, Silvie; Behuliak, M.; Celec, P.; Kojšová, S.; Pecháňová, O.; Šimko, F.

    2008-01-01

    Roč. 31, č. 4 (2008), s. 793-803 ISSN 0916-9636 R&D Projects: GA MŠk(CZ) 1M0510 Grant - others:VEGA(SK) 1/3429/06; VEGA(SK) 2/6148/26; APVT(SK) 51-027404 Institutional research plan: CEZ:AV0Z50110509 Keywords : nitric oxide * endothelial factors * cyclooxygenase Subject RIV: ED - Physiology Impact factor: 3.146, year: 2008

  5. Identifying main factors of capacity fading in lithium ion cells using orthogonal design of experiments

    International Nuclear Information System (INIS)

    Su, Laisuo; Zhang, Jianbo; Wang, Caijuan; Zhang, Yakun; Li, Zhe; Song, Yang; Jin, Ting; Ma, Zhao

    2016-01-01

    Highlights: • The effect of seven principal factors on the aging behavior of lithium ion cells is studied. • Orthogonal design of experiments is used to reduce the experiment units. • Capacity fades linearly during the initial 10% capacity fading period. • Statistical methods are used to compare the significance of each principal factor. • A multi-factor statistical model is developed to predict the aging rate of cells. - Abstract: The aging rate under cycling conditions for lithium-ion cells is affected by many factors. Seven principal factors are systematically examined using orthogonal design of experiments, and statistical analysis was used to identify the order of principal factors in terms of strength in causing capacity fade. These seven principal factors are: the charge and discharge currents (i_1, i_2) during the constant current regime, the charge and discharge cut-off voltages (V_1, V_2) and the corresponding durations (t_1, t_2) during the constant voltage regime, and the ambient temperature (T). An orthogonal array with 18 test units was selected for the experiments. The test results show that (1) during the initial 10% capacity fading period, the capacity faded linearly with Wh-throughput for all the test conditions; (2) after the initial period, certain cycling conditions exacerbated aging rates, while the others remain the same. The statistical results show that: (1) except for t_1, the other six principal factors significantly affect the aging rate; (2) the strength of the principal factors was ranked as: i_1 > V_1 > T > t_2 > V_2 > i_2 > t_1. Finally, a multi-factor statistical aging model is developed to predict the aging rate, and the accuracy of the model is validated.

  6. Risk factors for exclusive breastfeeding lasting less than two months-Identifying women in need of targeted breastfeeding support.

    Directory of Open Access Journals (Sweden)

    Karin Cato

    Full Text Available Breastfeeding rates in Sweden are declining, and it is important to identify women at risk for early cessation of exclusive breastfeeding.The aim of this study was to investigate factors associated with exclusive breastfeeding lasting less than two months postpartum.A population-based longitudinal study was conducted at Uppsala University Hospital, Sweden. Six hundred and seventy-nine women were included in this sub-study. Questionnaires were sent at five days, six weeks and six months postpartum, including questions on breastfeeding initiation and duration as well as several other background variables. The main outcome measure was exclusive breastfeeding lasting less than two months postpartum. Multivariable logistic regression analysis was used in order to calculate adjusted Odds Ratios (AOR and 95% Confidence Intervals (95% CI.Seventy-seven percent of the women reported exclusive breastfeeding at two months postpartum. The following variables in the multivariate regression analysis were independently associated with exclusive breastfeeding lasting less than two months postpartum: being a first time mother (AOR 2.15, 95% CI 1.32-3.49, reporting emotional distress during pregnancy (AOR 2.21, 95% CI 1.35-3.62 and giving birth by cesarean section (AOR 2.63, 95% CI 1.34-5.17.Factors associated with shorter exclusive breastfeeding duration were determined. Identification of women experiencing emotional distress during pregnancy, as well as scrutiny of caregiving routines on cesarean section need to be addressed, in order to give individual targeted breastfeeding support and promote longer breastfeeding duration.

  7. Resident Workflow and Psychiatric Emergency Consultation: Identifying Factors for Quality Improvement in a Training Environment.

    Science.gov (United States)

    Blair, Thomas; Wiener, Zev; Seroussi, Ariel; Tang, Lingqi; O'Hora, Jennifer; Cheung, Erick

    2017-06-01

    Quality improvement to optimize workflow has the potential to mitigate resident burnout and enhance patient care. This study applied mixed methods to identify factors that enhance or impede workflow for residents performing emergency psychiatric consultations. The study population consisted of all psychiatry program residents (55 eligible, 42 participating) at the Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles. The authors developed a survey through iterative piloting, surveyed all residents, and then conducted a focus group. The survey included elements hypothesized to enhance or impede workflow, and measures pertaining to self-rated efficiency and stress. Distributional and bivariate analyses were performed. Survey findings were clarified in focus group discussion. This study identified several factors subjectively associated with enhanced or impeded workflow, including difficulty with documentation, the value of personal organization systems, and struggles to communicate with patients' families. Implications for resident education are discussed.

  8. Use of model plant hosts to identify Pseudomonas aeruginosa virulence factors

    Science.gov (United States)

    Rahme, Laurence G.; Tan, Man-Wah; Le, Long; Wong, Sandy M.; Tompkins, Ronald G.; Calderwood, Stephen B.; Ausubel, Frederick M.

    1997-01-01

    We used plants as an in vivo pathogenesis model for the identification of virulence factors of the human opportunistic pathogen Pseudomonas aeruginosa. Nine of nine TnphoA mutant derivatives of P. aeruginosa strain UCBPP-PA14 that were identified in a plant leaf assay for less pathogenic mutants also exhibited significantly reduced pathogenicity in a burned mouse pathogenicity model, suggesting that P. aeruginosa utilizes common strategies to infect both hosts. Seven of these nine mutants contain TnphoA insertions in previously unknown genes. These results demonstrate that an alternative nonvertebrate host of a human bacterial pathogen can be used in an in vivo high throughput screen to identify novel bacterial virulence factors involved in mammalian pathogenesis. PMID:9371831

  9. Job satisfaction of nurses and identifying factors of job satisfaction in Slovenian Hospitals.

    Science.gov (United States)

    Lorber, Mateja; Skela Savič, Brigita

    2012-06-01

    To determine the level of job satisfaction of nursing professionals in Slovenian hospitals and factors influencing job satisfaction in nursing. The study included 4 hospitals selected from the hospital list comprising 26 hospitals in Slovenia. The employees of these hospitals represent 29.8% and 509 employees included in the study represent 6% of all employees in nursing in Slovenian hospitals. One structured survey questionnaire was administered to the leaders and the other to employees, both consisting 154 items evaluated on a 5 point Likert-type scale. We examined the correlation between independent variables (age, number of years of employment, behavior of leaders, personal characteristics of leaders, and managerial competencies of leaders) and the dependent variable (job satisfaction - satisfaction with the work, coworkers, management, pay, etc) by applying correlation analysis and multivariate regression analysis. In addition, factor analysis was used to establish characteristic components of the variables measured. We found a medium level of job satisfaction in both leaders (3.49±0.5) and employees (3.19±0.6), however, there was a significant difference between their estimates (t=3.237; P=lt;0.001). Job satisfaction was explained by age (Plt;0.05; β=0.091), years of employment (Plt;0.05; β=0.193), personal characteristics of leaders (Plt;0.001; β=0.158), and managerial competencies of leaders (Plt;0.000; β=0.634) in 46% of cases. The factor analysis yielded four factors explaining 64% of the total job satisfaction variance. Satisfied employees play a crucial role in an organization's success, so health care organizations must be aware of the importance of employees' job satisfaction. It is recommended to monitor employees' job satisfaction levels on an annual basis.

  10. STUDY OF IDENTIFYING AND PRIORITIZING THE AFFECTING FACTORS ON BANK BRAND CUSTOMER LOYALTY

    OpenAIRE

    Zahra Aliyari; Yosef Beygzadeh

    2017-01-01

    Today, customer loyalty is the key to business success. By increased customers’ loyalty, market share and profitability level of enterprises will rise. Market perception along with planning and adopting appropriate strategies for making customers loyal and enhancing their rate of loyalty leads to long-term benefits for the enterprises. Given the importance of the issue, the goal of this study was to identify and prioritize the factors affecting loyalty to a banking brand from perspective of K...

  11. Identifying and assessing the factors affecting skill gap in digital marketing in communication industry companies

    OpenAIRE

    Ghotbifar, Fereshteh; Marjani, Mohammad Reza; Ramazani, Abbas

    2017-01-01

    As far as new communication channels are concerned, there have been extensive developments in communications and marketing in digital era. Today, therefore, companies try to take advantage of digital marketing channels to provide suitable services to customers to improve their satisfaction level. However, this study aimed to identify and assess factors affecting skill gap in digital marketing. This was descriptive correlation study. The population consisted of experts in communications indust...

  12. Transcription factor expression uniquely identifies most postembryonic neuronal lineages in the Drosophila thoracic central nervous system.

    Science.gov (United States)

    Lacin, Haluk; Zhu, Yi; Wilson, Beth A; Skeath, James B

    2014-03-01

    Most neurons of the adult Drosophila ventral nerve cord arise from a burst of neurogenesis during the third larval instar stage. Most of this growth occurs in thoracic neuromeres, which contain 25 individually identifiable postembryonic neuronal lineages. Initially, each lineage consists of two hemilineages--'A' (Notch(On)) and 'B' (Notch(Off))--that exhibit distinct axonal trajectories or fates. No reliable method presently exists to identify these lineages or hemilineages unambiguously other than labor-intensive lineage-tracing methods. By combining mosaic analysis with a repressible cell marker (MARCM) analysis with gene expression studies, we constructed a gene expression map that enables the rapid, unambiguous identification of 23 of the 25 postembryonic lineages based on the expression of 15 transcription factors. Pilot genetic studies reveal that these transcription factors regulate the specification and differentiation of postembryonic neurons: for example, Nkx6 is necessary and sufficient to direct axonal pathway selection in lineage 3. The gene expression map thus provides a descriptive foundation for the genetic and molecular dissection of adult-specific neurogenesis and identifies many transcription factors that are likely to regulate the development and differentiation of discrete subsets of postembryonic neurons.

  13. Which sociodemographic factors are important on smoking behaviour of high school students? The contribution of classification and regression tree methodology in a broad epidemiological survey.

    Science.gov (United States)

    Ozge, C; Toros, F; Bayramkaya, E; Camdeviren, H; Sasmaz, T

    2006-08-01

    The purpose of this study is to evaluate the most important sociodemographic factors on smoking status of high school students using a broad randomised epidemiological survey. Using in-class, self administered questionnaire about their sociodemographic variables and smoking behaviour, a representative sample of total 3304 students of preparatory, 9th, 10th, and 11th grades, from 22 randomly selected schools of Mersin, were evaluated and discriminative factors have been determined using appropriate statistics. In addition to binary logistic regression analysis, the study evaluated combined effects of these factors using classification and regression tree methodology, as a new statistical method. The data showed that 38% of the students reported lifetime smoking and 16.9% of them reported current smoking with a male predominancy and increasing prevalence by age. Second hand smoking was reported at a 74.3% frequency with father predominance (56.6%). The significantly important factors that affect current smoking in these age groups were increased by household size, late birth rank, certain school types, low academic performance, increased second hand smoking, and stress (especially reported as separation from a close friend or because of violence at home). Classification and regression tree methodology showed the importance of some neglected sociodemographic factors with a good classification capacity. It was concluded that, as closely related with sociocultural factors, smoking was a common problem in this young population, generating important academic and social burden in youth life and with increasing data about this behaviour and using new statistical methods, effective coping strategies could be composed.

  14. Identifying Critical Factors in the Eco-Efficiency of Remanufacturing Based on the Fuzzy DEMATEL Method

    Directory of Open Access Journals (Sweden)

    Qianwang Deng

    2015-11-01

    Full Text Available Remanufacturing can bring considerable economic and environmental benefits such as cost saving, conservation of energy and resources, and reduction of emissions. With the increasing awareness of sustainable manufacturing, remanufacturing gradually becomes the research priority. Most studies concentrate on the analysis of influencing factors, or the evaluation of the economic and environmental performance in remanufacturing, while little effort has been devoted to investigating the critical factors influencing the eco-efficiency of remanufacturing. Considering the current development of the remanufacturing industry in China, this paper proposes a set of factors influencing the eco-efficiency of remanufacturing and then utilizes a fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL method to establish relation matrixes reflecting the interdependent relationships among these factors. Finally, the contributions of each factor to eco-efficiency and mutual influence values among them are obtained, and critical factors in eco-efficiency of remanufacturing are identified. The results of the present work can provide theoretical supports for the government to make appropriate policies to improve the eco-efficiency of remanufacturing.

  15. A retrospective chart review to identify perinatal factors associated with food allergies.

    Science.gov (United States)

    Dowhower Karpa, Kelly; Paul, Ian M; Leckie, J Alexander; Shung, Sharon; Carkaci-Salli, Nurgul; Vrana, Kent E; Mauger, David; Fausnight, Tracy; Poger, Jennifer

    2012-10-19

    Gut flora are important immunomodulators that may be disrupted in individuals with atopic conditions. Probiotic bacteria have been suggested as therapeutic modalities to mitigate or prevent food allergic manifestations. We wished to investigate whether perinatal factors known to disrupt gut flora increase the risk of IgE-mediated food allergies. Birth records obtained from 192 healthy children and 99 children diagnosed with food allergies were reviewed retrospectively. Data pertaining to delivery method, perinatal antibiotic exposure, neonatal nursery environment, and maternal variables were recorded. Logistic regression analysis was used to assess the association between variables of interest and subsequent food allergy diagnosis. Retrospective investigation did not find perinatal antibiotics, NICU admission, or cesarean section to be associated with increased risk of food allergy diagnosis. However, associations between food allergy diagnosis and male gender (66 vs. 33; p=0.02) were apparent in this cohort. Additionally, increasing maternal age at delivery was significantly associated with food allergy diagnosis during childhood (OR, 1.05; 95% CI, 1.017 to 1.105; p=0.005). Gut flora are potent immunomodulators, but their overall contribution to immune maturation remains to be elucidated. Additional understanding of the interplay between immunologic, genetic, and environmental factors underlying food allergy development need to be clarified before probiotic therapeutic interventions can routinely be recommended for prevention or mitigation of food allergies. Such interventions may be well-suited in male infants and in infants born to older mothers.

  16. Assessing the Factors Predicting Work-Related Musculoskeletal Disorders Among Iranian Port’s Personnel Using Regression Model

    Directory of Open Access Journals (Sweden)

    Mohammad Khandan

    2017-11-01

    Discussion: Psychological factors of workplaces include job burnout, employees’ attitude and safety climate that negatively affect ergonomic disorders. Since psychological and psycho-social issues are neglected in developing countries such as Iran, the researchers anticipate that the obtained results can be used as a guideline for policymakers as well as in the supportive and preventive arena for managing safety and health issues.

  17. Gestational diabetes mellitus in sub-Saharan Africa: systematic review and meta-regression on prevalence and risk factors

    NARCIS (Netherlands)

    Mwanri, A.W.; Kinabo, J.L.; Ramaiya, K.; Feskens, E.J.M.

    2015-01-01

    Objective We systematically reviewed publications on prevalence and risk factors for gestational diabetes mellitus (GDM) in the 47 countries of sub-Saharan Africa. Methods We conducted a systematic search in PUBMED and reviewed articles published until June 2014 and searched the references of

  18. Application of positive matrix factorization to identify potential sources of PAHs in soil of Dalian, China

    International Nuclear Information System (INIS)

    Wang Degao; Tian Fulin; Yang Meng; Liu Chenlin; Li Yifan

    2009-01-01

    Soil derived sources of polycyclic aromatic hydrocarbons (PAHs) in the region of Dalian, China were investigated using positive matrix factorization (PMF). Three factors were separated based on PMF for the statistical investigation of the datasets both in summer and winter. These factors were dominated by the pattern of single sources or groups of similar sources, showing seasonal and regional variations. The main sources of PAHs in Dalian soil in summer were the emissions from coal combustion average (46%), diesel engine (30%), and gasoline engine (24%). In winter, the main sources were the emissions from coal-fired boiler (72%), traffic average (20%), and gasoline engine (8%). These factors with strong seasonality indicated that coal combustion in winter and traffic exhaust in summer dominated the sources of PAHs in soil. These results suggested that PMF model was a proper approach to identify the sources of PAHs in soil. - PMF model is a proper approach to identify potential sources of PAHs in soil based on the PAH profiles measured in the field and those published in the literature.

  19. A Matlab program for stepwise regression

    Directory of Open Access Journals (Sweden)

    Yanhong Qi

    2016-03-01

    Full Text Available The stepwise linear regression is a multi-variable regression for identifying statistically significant variables in the linear regression equation. In present study, we presented the Matlab program of stepwise regression.

  20. Identifying factors affecting the safety of mid-block bicycle lanes considering mixed 2-wheeled traffic flow.

    Science.gov (United States)

    Bai, Lu; Chan, Ching-Yao; Liu, Pan; Xu, Chengcheng

    2017-10-03

    Electric bikes (e-bikes) have been one of the fastest growing trip modes in Southeast Asia over the past 2 decades. The increasing popularity of e-bikes raised some safety concerns regarding urban transport systems. The primary objective of this study was to identify whether and how the generalized linear regression model (GLM) could be used to relate cyclists' safety with various contributing factors when riding in a mid-block bike lane. The types of 2-wheeled vehicles in the study included bicycle-style electric bicycles (BSEBs), scooter-style electric bicycles (SSEBs), and regular bicycles (RBs). Traffic conflict technology was applied as a surrogate measure to evaluate the safety of 2-wheeled vehicles. The safety performance model was developed by adopting a generalized linear regression model for relating the frequency of rear-end conflicts between e-bikes and regular bikes to the operating speeds of BSEBs, SSEBs, and RBs in mid-block bike lanes. The frequency of rear-end conflicts between e-bikes and bikes increased with an increase in the operating speeds of e-bikes and the volume of e-bikes and bikes and decreased with an increase in the width of bike lanes. The large speed difference between e-bikes and bikes increased the frequency of rear-end conflicts between e-bikes and bikes in mid-block bike lanes. A 1% increase in the average operating speed of e-bikes would increase the expected number of rear-end conflicts between e-bikes and bikes by 1.48%. A 1% increase in the speed difference between e-bikes and bikes would increase the expected number of rear-end conflicts between e-bikes/bikes by 0.16%. The conflict frequency in mid-block bike lanes can be modeled using generalized linear regression models. The factors that significantly affected the frequency of rear-end conflicts included the operating speeds of e-bikes, the speed difference between e-bikes and regular bikes, the volume of e-bikes, the volume of bikes, and the width of bike lanes. The

  1. A combined structural dynamics approach identifies a putative switch in factor VIIa employed by tissue factor to initiate blood coagulation

    DEFF Research Database (Denmark)

    Olsen, Ole H; Rand, Kasper D; Østergaard, Henrik

    2007-01-01

    Coagulation factor VIIa (FVIIa) requires tissue factor (TF) to attain full catalytic competency and to initiate blood coagulation. In this study, the mechanism by which TF allosterically activates FVIIa is investigated by a structural dynamics approach that combines molecular dynamics (MD......) simulations and hydrogen/deuterium exchange (HX) mass spectrometry on free and TF-bound FVIIa. The differences in conformational dynamics from MD simulations are shown to be confined to regions of FVIIa observed to undergo structural stabilization as judged by HX experiments, especially implicating activation...... in the presence of TF or an active-site inhibitor. Based on MD simulations, a key switch of the TF-induced structural changes is identified as the interacting pair Leu305{163} and Phe374{225} in FVIIa, whose mutual conformations are guided by the presence of TF and observed to be closely linked to the structural...

  2. Prevalence of HIV in pregnant women identified with a risk factor at a tertiary care hospital.

    Science.gov (United States)

    Mahmud, Ghazala; Abbas, Shazra

    2009-01-01

    HIV is an epidemic quite unlike any other, combining the problems of a lifelong medical disease with immense social, psychological, economic and public health consequences. Since we are living in a global village where human interactions has become fast and frequent, diseases like HIV are no more alien to us. HIV/AIDS in Pakistan is slowly gaining recognition as a public health issue of great importance. Objectives of this study were to determine the prevalence of HIV in pregnant women identified with a high risk factor/behaviour at a tertiary care hospital. It is a Descriptive study. All pregnant women attending antenatal booking clinic were assessed via a pre-designed 'Risk assessment questionnaire'. Women identified with a risk factor were offered HIV Rapid screening test (Capillus HIV1/2). Positive (reactive) results on screening test were confirmed with ELISA. During the study period (March 2007-May 2008), out of 5263 antenatal bookings 785 (14%) women were identified with a risk factor. HIV screening test was done in 779 (99%), and 6 women refused testing. Three women (0.3%) were found positive (reactive) on screening. Two out of 3 women were confirmed positive (0.2%) on ELISA. Husbands of both women were tested and one found positive (migrant from Dubai). Second women had history of blood transfusion. Her husband was HIV negative. During the study period, in addition to 2 pregnant women diagnosed as HIV positive through ANC risk screening, 6 confirmed HIV positive women, found pregnant were referred from 'HIV Treatment Centre', Pakistan Institute of Medical Sciences (PIMS) to Prevention of Parent to Child Transmission (PPTCT) centre for obstetric care. Spouses of 5 out of 6 had history of working abroad and extramarital sexual relationships. All positive (8) women were referred to PPTCT centre for further management. A simple 'Risk Assessment Questionnaire' can help us in identifying women who need HIV screening. Sexual transmission still remains the

  3. Identifying risk profiles for childhood obesity using recursive partitioning based on individual, familial, and neighborhood environment factors.

    Science.gov (United States)

    Van Hulst, Andraea; Roy-Gagnon, Marie-Hélène; Gauvin, Lise; Kestens, Yan; Henderson, Mélanie; Barnett, Tracie A

    2015-02-15

    Few studies consider how risk factors within multiple levels of influence operate synergistically to determine childhood obesity. We used recursive partitioning analysis to identify unique combinations of individual, familial, and neighborhood factors that best predict obesity in children, and tested whether these predict 2-year changes in body mass index (BMI). Data were collected in 2005-2008 and in 2008-2011 for 512 Quebec youth (8-10 years at baseline) with a history of parental obesity (QUALITY study). CDC age- and sex-specific BMI percentiles were computed and children were considered obese if their BMI was ≥95th percentile. Individual (physical activity and sugar-sweetened beverage intake), familial (household socioeconomic status and measures of parental obesity including both BMI and waist circumference), and neighborhood (disadvantage, prestige, and presence of parks, convenience stores, and fast food restaurants) factors were examined. Recursive partitioning, a method that generates a classification tree predicting obesity based on combined exposure to a series of variables, was used. Associations between resulting varying risk group membership and BMI percentile at baseline and 2-year follow up were examined using linear regression. Recursive partitioning yielded 7 subgroups with a prevalence of obesity equal to 8%, 11%, 26%, 28%, 41%, 60%, and 63%, respectively. The 2 highest risk subgroups comprised i) children not meeting physical activity guidelines, with at least one BMI-defined obese parent and 2 abdominally obese parents, living in disadvantaged neighborhoods without parks and, ii) children with these characteristics, except with access to ≥1 park and with access to ≥1 convenience store. Group membership was strongly associated with BMI at baseline, but did not systematically predict change in BMI. Findings support the notion that obesity is predicted by multiple factors in different settings and provide some indications of potentially

  4. Identifying risk factors of highly pathogenic avian influenza (H5N1 subtype) in Indonesia.

    Science.gov (United States)

    Loth, Leo; Gilbert, Marius; Wu, Jianmei; Czarnecki, Christina; Hidayat, Muhammad; Xiao, Xiangming

    2011-10-01

    Highly pathogenic avian influenza (HPAI), subtype H5N1, was first officially reported in Indonesia in 2004. Since then the disease has spread and is now endemic in large parts of the country. This study investigated the statistical relationship between a set of risk factors and the presence or absence of HPAI in Indonesia during 2006 and 2007. HPAI was evaluated through participatory disease surveillance (PDS) in backyard village chickens (the study population), and risk factors included descriptors of people and poultry distribution (separating chickens, ducks and production sectors), poultry movement patterns and agro-ecological conditions. The study showed that the risk factors "elevation", "human population density" and "rice cropping" were significant in accounting for the spatial variation of the PDS-defined HPAI cases. These findings were consistent with earlier studies in Thailand and Vietnam. In addition "commercial poultry population", and two indicators of market locations and transport; "human settlements" and "road length", were identified as significant risk factors in the models. In contrast to several previous studies carried out in Southeast Asia, domestic backyard ducks were not found to be a significant risk factor in Indonesia. The study used surrogate estimates of market locations and marketing chains and further work should focus on the actual location of the live bird markets, and on the flow of live poultry and poultry products between them, so that patterns of possible transmission, and regions of particular risk could be better inferred. Copyright © 2011 Elsevier B.V. All rights reserved.

  5. Dietary patterns as identified by factor analysis and colorectal cancer among middle-aged Americans.

    Science.gov (United States)

    Flood, Andrew; Rastogi, Tanuja; Wirfält, Elisabet; Mitrou, Panagiota N; Reedy, Jill; Subar, Amy F; Kipnis, Victor; Mouw, Traci; Hollenbeck, Albert R; Leitzmann, Michael; Schatzkin, Arthur

    2008-07-01

    Although diet has long been suspected as an etiological factor for colorectal cancer, studies of single foods and nutrients have provided inconsistent results. We used factor analysis methods to study associations between dietary patterns and colorectal cancer in middle-aged Americans. Diet was assessed among 293,615 men and 198,767 women in the National Institutes of Health-AARP Diet and Health Study. Principal components factor analysis identified 3 primary dietary patterns: a fruit and vegetables, a diet foods, and a red meat and potatoes pattern. State cancer registries identified 2151 incident cases of colorectal cancer in men and 959 in women between 1995 and 2000. Men with high scores on the fruit and vegetable pattern were at decreased risk [relative risk (RR) for quintile (Q) 5 versus Q1: 0.81; 95% CI: 0.70, 0.93; P for trend = 0.004]. Both men and women had a similar risk reduction with high scores on the diet food factor: men (RR: 0.82; 95% CI: 0.72, 0.94; P for trend = 0.001) and women (RR: 0.87; 95% CI: 0.71, 1.07; P for trend = 0.06). High scores on the red meat factor were associated with increased risk: men (RR: 1.17; 95% CI: 1.02, 1.35; P for trend = 0.14) and women (RR: 1.48; 95% CI: 1.20, 1.83; P for trend = 0.0002). These results suggest that dietary patterns characterized by a low frequency of meat and potato consumption and frequent consumption of fruit and vegetables and fat-reduced foods are consistent with a decreased risk of colorectal cancer.

  6. Identifying risk factors for PTSD in women seeking medical help after rape.

    Directory of Open Access Journals (Sweden)

    Anna Tiihonen Möller

    Full Text Available Rape has been found to be the trauma most commonly associated with Posttraumatic Stress Disorder (PTSD among women. It is therefore important to be able to identify those women at greatest risk of developing PTSD. The aims of the present study were to analyze the PTSD prevalence six months after sexual assaults and identify the major risk factors for developing PTSD.Participants were 317 female victims of rape who sought help at the Emergency Clinic for Raped Women at Stockholm South Hospital, Sweden. Baseline assessments of mental health were carried out and followed up after six months.Thirty-nine percent of the women had developed PTSD at the six month assessment, and 47% suffered from moderate or severe depression. The major risk factors for PTSD were having been sexually assaulted by more than one person, suffering from acute stress disorder (ASD shortly after the assault, having been exposed to several acts during the assault, having been injured, having co-morbid depression, and having a history of more than two earlier traumas. Further, ASD on its own was found to be a poor predictor of PTSD because of the substantial ceiling effect after sexual assaults.Development of PTSD is common in the aftermath of sexual assaults. Increased risk of developing PTSD is caused by a combination of victim vulnerability and the extent of the dramatic nature of the current assault. By identifying those women at greatest risk of developing PTSD appropriate therapeutic resources can be directed.

  7. Identifying risk factors for PTSD in women seeking medical help after rape.

    Science.gov (United States)

    Tiihonen Möller, Anna; Bäckström, Torbjörn; Söndergaard, Hans Peter; Helström, Lotti

    2014-01-01

    Rape has been found to be the trauma most commonly associated with Posttraumatic Stress Disorder (PTSD) among women. It is therefore important to be able to identify those women at greatest risk of developing PTSD. The aims of the present study were to analyze the PTSD prevalence six months after sexual assaults and identify the major risk factors for developing PTSD. Participants were 317 female victims of rape who sought help at the Emergency Clinic for Raped Women at Stockholm South Hospital, Sweden. Baseline assessments of mental health were carried out and followed up after six months. Thirty-nine percent of the women had developed PTSD at the six month assessment, and 47% suffered from moderate or severe depression. The major risk factors for PTSD were having been sexually assaulted by more than one person, suffering from acute stress disorder (ASD) shortly after the assault, having been exposed to several acts during the assault, having been injured, having co-morbid depression, and having a history of more than two earlier traumas. Further, ASD on its own was found to be a poor predictor of PTSD because of the substantial ceiling effect after sexual assaults. Development of PTSD is common in the aftermath of sexual assaults. Increased risk of developing PTSD is caused by a combination of victim vulnerability and the extent of the dramatic nature of the current assault. By identifying those women at greatest risk of developing PTSD appropriate therapeutic resources can be directed.

  8. Application of Geomorphologic Factors for Identifying Soil Loss in Vulnerable Regions of the Cameron Highlands

    Directory of Open Access Journals (Sweden)

    Kahhoong Kok

    2018-03-01

    Full Text Available The main purpose of this study is to propose a methodology for identifying vulnerable regions in the Cameron Highlands that are susceptible to soil loss, based on runoff aggregation structure and the energy expenditure pattern of the natural river basin, within the framework of power law distribution. To this end, three geomorphologic factors, namely shear stress and stream power, as well as the drainage area of every point in the basin of interest, have been extracted using GIS, and then their complementary cumulative distributions are graphically analyzed by fitting them to power law distribution, with the purpose of identifying the sensitive points within the basin that are susceptible to soil loss with respect to scaling regimes of shear stress and stream power. It is observed that the range of vulnerable regions by the scaling regime of shear stress is much narrower than by the scaling regime of stream power. This result seems to suggest that shear stress is a scale-dependent factor, which does not follow power law distribution and does not adequately reflect the energy expenditure pattern of a river basin. Therefore, stream power is preferred as a more reasonable factor for the evaluation of soil loss. The methodology proposed in this study can be validated by visualizing the path of soil loss, which is generated from the hillslope process (characterized by the local slope to the valley through a fluvial process (characterized by the drainage area as well as the local slope.

  9. Using a Delphi Method to Identify Human Factors Contributing to Nursing Errors.

    Science.gov (United States)

    Roth, Cheryl; Brewer, Melanie; Wieck, K Lynn

    2017-07-01

    The purpose of this study was to identify human factors associated with nursing errors. Using a Delphi technique, this study used feedback from a panel of nurse experts (n = 25) on an initial qualitative survey questionnaire followed by summarizing the results with feedback and confirmation. Synthesized factors regarding causes of errors were incorporated into a quantitative Likert-type scale, and the original expert panel participants were queried a second time to validate responses. The list identified 24 items as most common causes of nursing errors, including swamping and errors made by others that nurses are expected to recognize and fix. The responses provided a consensus top 10 errors list based on means with heavy workload and fatigue at the top of the list. The use of the Delphi survey established consensus and developed a platform upon which future study of nursing errors can evolve as a link to future solutions. This list of human factors in nursing errors should serve to stimulate dialogue among nurses about how to prevent errors and improve outcomes. Human and system failures have been the subject of an abundance of research, yet nursing errors continue to occur. © 2016 Wiley Periodicals, Inc.

  10. Return to Work: A Cut-Off of FIM Gain with Montebello Rehabilitation Factor Score in Order to Identify Predictive Factors in Subjects with Acquired Brain Injury.

    Science.gov (United States)

    Franceschini, Marco; Massimiani, Maria Pia; Paravati, Stefano; Agosti, Maurizio

    2016-01-01

    Return to work (RTW) for people with acquired brain injury (ABI) represents a main objective of rehabilitation: this work presents a strong correlation between personal well-being and quality of life. The aim of this study is to investigate the prognostic factors that can predict RTW after ABI (traumatic or non- traumatic aetiology) in patients without disorders of consciousness (e.g. coma, vegetative or minimally conscious state) at the beginning of their admission to rehabilitation. At the end of a 6-month follow-up after discharge, data were successfully collected in 69 patients. The rehabilitation effectiveness (functional Recovery) between admission and discharge was assessed by Functional Independent Measure (FIM) gain, through the Montebello Rehabilitation Factor Score (MRFS), which was obtained as follows: (discharge FIM-admission FIM)/(Maximum possible FIM-Admission FIM) x 100. The cut-off value (criterion) deriving from MRFS, which helped identify RTW patients, resulted in .659 (sn 88.9%; sp 52.4%). Considering the Mini Mental State Examination (MMSE) and the MRFS data, the multivariable binary logistic regression analysis presented 62.96% of correct RTW classification cases, 80.95% of non-RTW leading to an overall satisfactory predictability of 73.91%. The results of the present study suggest that occupational therapy intervention could modify cut-off in patients with an MFRS close to target at the end of an in-hospital rehabilitative program thus developing their capabilities and consequently surpassing cut-off itself.

  11. Return to Work: A Cut-Off of FIM Gain with Montebello Rehabilitation Factor Score in Order to Identify Predictive Factors in Subjects with Acquired Brain Injury.

    Directory of Open Access Journals (Sweden)

    Marco Franceschini

    Full Text Available Return to work (RTW for people with acquired brain injury (ABI represents a main objective of rehabilitation: this work presents a strong correlation between personal well-being and quality of life. The aim of this study is to investigate the prognostic factors that can predict RTW after ABI (traumatic or non- traumatic aetiology in patients without disorders of consciousness (e.g. coma, vegetative or minimally conscious state at the beginning of their admission to rehabilitation. At the end of a 6-month follow-up after discharge, data were successfully collected in 69 patients. The rehabilitation effectiveness (functional Recovery between admission and discharge was assessed by Functional Independent Measure (FIM gain, through the Montebello Rehabilitation Factor Score (MRFS, which was obtained as follows: (discharge FIM-admission FIM/(Maximum possible FIM-Admission FIM x 100. The cut-off value (criterion deriving from MRFS, which helped identify RTW patients, resulted in .659 (sn 88.9%; sp 52.4%. Considering the Mini Mental State Examination (MMSE and the MRFS data, the multivariable binary logistic regression analysis presented 62.96% of correct RTW classification cases, 80.95% of non-RTW leading to an overall satisfactory predictability of 73.91%. The results of the present study suggest that occupational therapy intervention could modify cut-off in patients with an MFRS close to target at the end of an in-hospital rehabilitative program thus developing their capabilities and consequently surpassing cut-off itself.

  12. Pilot Critical Incident Reports as a Means to Identify Human Factors of Remotely Piloted Aircraft

    Science.gov (United States)

    Hobbs, Alan; Cardoza, Colleen; Null, Cynthia

    2016-01-01

    It has been estimated that aviation accidents are typically preceded by numerous minor incidents arising from the same causal factors that ultimately produced the accident. Accident databases provide in-depth information on a relatively small number of occurrences, however incident databases have the potential to provide insights into the human factors of Remotely Piloted Aircraft System (RPAS) operations based on a larger volume of less-detailed reports. Currently, there is a lack of incident data dealing with the human factors of unmanned aircraft systems. An exploratory study is being conducted to examine the feasibility of collecting voluntary critical incident reports from RPAS pilots. Twenty-three experienced RPAS pilots volunteered to participate in focus groups in which they described critical incidents from their own experience. Participants were asked to recall (1) incidents that revealed a system flaw, or (2) highlighted a case where the human operator contributed to system resilience or mission success. Participants were asked to only report incidents that could be included in a public document. During each focus group session, a note taker produced a de-identified written record of the incident narratives. At the end of the session, participants reviewed each written incident report, and made edits and corrections as necessary. The incidents were later analyzed to identify contributing factors, with a focus on design issues that either hindered or assisted the pilot during the events. A total of 90 incidents were reported. Human factor issues included the impact of reduced sensory cues, traffic separation in the absence of an out-the-window view, control latencies, vigilance during monotonous and ultra-long endurance flights, control station design considerations, transfer of control between control stations, the management of lost link procedures, and decision-making during emergencies. Pilots participated willingly and enthusiastically in the study

  13. Screening for violence risk factors identifies young adults at risk for return emergency department visit for injury.

    Science.gov (United States)

    Hankin, Abigail; Wei, Stanley; Foreman, Juron; Houry, Debra

    2014-08-01

    Homicide is the second leading cause of death among youth aged 15-24. Prior cross-sectional studies, in non-healthcare settings, have reported exposure to community violence, peer behavior, and delinquency as risk factors for violent injury. However, longitudinal cohort studies have not been performed to evaluate the temporal or predictive relationship between these risk factors and emergency department (ED) visits for injuries among at-risk youth. The objective was to assess whether self-reported exposure to violence risk factors in young adults can be used to predict future ED visits for injuries over a 1-year period. This prospective cohort study was performed in the ED of a Southeastern US Level I trauma center. Eligible participants were patients aged 18-24, presenting for any chief complaint. We excluded patients if they were critically ill, incarcerated, or could not read English. Initial recruitment occurred over a 6-month period, by a research assistant in the ED for 3-5 days per week, with shifts scheduled such that they included weekends and weekdays, over the hours from 8AM-8PM. At the time of initial contact in the ED, patients were asked to complete a written questionnaire, consisting of previously validated instruments measuring the following risk factors: a) aggression, b) perceived likelihood of violence, c) recent violent behavior, d) peer behavior, e) community exposure to violence, and f) positive future outlook. At 12 months following the initial ED visit, the participants' medical records were reviewed to identify any subsequent ED visits for injury-related complaints. We analyzed data with chi-square and logistic regression analyses. Three hundred thirty-two patients were approached, of whom 300 patients consented. Participants' average age was 21.1 years, with 60.1% female, 86.0% African American. After controlling for participant gender, ethnicity, or injury complaint at time of first visit, return visits for injuries were significantly

  14. Osteoporosis among Fallers without Concomitant Fracture Identified in an Emergency Department: Frequencies and Risk Factors

    DEFF Research Database (Denmark)

    Glintborg, Bente; Hesse, Ulrik; Houe, Thomas

    2011-01-01

    aged 50-80 years sustaining a low-energy fall without fracture were identified from an ED (n = 199). Patients answered a questionnaire on risk factors and underwent osteodensitometry. Data was compared to a group of patients routinely referred to osteodensitometry from general practice (n = 201......). Results. Among the 199 included fallers, 41 (21%) had osteoporosis. Among these, 35 (85%) reported either previous fracture or reduced body height (>3¿cm). These two risk factors were more frequent among fallers with osteoporosis compared to fallers with normal bone mineral density or osteopenia (previous...... if the patient has a prior fracture or declined body height. Since fallers generally have higher fracture risk, the ED might serve as an additional entrance to osteodensitometry compared to referral from primary care....

  15. Identifying sources of atmospheric fine particles in Havana City using Positive Matrix Factorization technique

    International Nuclear Information System (INIS)

    Pinnera, I.; Perez, G.; Ramos, M.; Guibert, R.; Aldape, F.; Flores M, J.; Martinez, M.; Molina, E.; Fernandez, A.

    2011-01-01

    In previous study a set of samples of fine and coarse airborne particulate matter collected in a urban area of Havana City were analyzed by Particle-Induced X-ray Emission (PIXE) technique. The concentrations of 14 elements (S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br and Pb) were consistently determined in both particle sizes. The analytical database provided by PIXE was statistically analyzed in order to determine the local pollution sources. The Positive Matrix Factorization (PMF) technique was applied to fine particle data in order to identify possible pollution sources. These sources were further verified by enrichment factor (EF) calculation. A general discussion about these results is presented in this work. (Author)

  16. Job satisfaction of nurses and identifying factors of job satisfaction in Slovenian Hospitals

    Science.gov (United States)

    Lorber, Mateja; Skela Savič, Brigita

    2012-01-01

    Aim To determine the level of job satisfaction of nursing professionals in Slovenian hospitals and factors influencing job satisfaction in nursing. Methods The study included 4 hospitals selected from the hospital list comprising 26 hospitals in Slovenia. The employees of these hospitals represent 29.8% and 509 employees included in the study represent 6% of all employees in nursing in Slovenian hospitals. One structured survey questionnaire was administered to the leaders and the other to employees, both consisting 154 items evaluated on a 5 point Likert-type scale. We examined the correlation between independent variables (age, number of years of employment, behavior of leaders, personal characteristics of leaders, and managerial competencies of leaders) and the dependent variable (job satisfaction – satisfaction with the work, coworkers, management, pay, etc) by applying correlation analysis and multivariate regression analysis. In addition, factor analysis was used to establish characteristic components of the variables measured. Results We found a medium level of job satisfaction in both leaders (3.49 ± 0.5) and employees (3.19 ± 0.6), however, there was a significant difference between their estimates (t = 3.237; P = Job satisfaction was explained by age (P job satisfaction variance. Conclusion Satisfied employees play a crucial role in an organization’s success, so health care organizations must be aware of the importance of employees’ job satisfaction. It is recommended to monitor employees’ job satisfaction levels on an annual basis. PMID:22661140

  17. Identifying practice-related factors for high-volume prescribers of antibiotics in Danish general practice

    DEFF Research Database (Denmark)

    Aabenhus, Rune; Siersma, Volkert Dirk; Sandholdt, Håkon

    2017-01-01

    practice-related factors driving high antibiotic prescribing rates. Results: We included 98% of general practices in Denmark (n = 1962) and identified a 10% group of high prescribers who accounted for 15% of total antibiotic prescriptions and 18% of critically important antibiotic prescriptions. Once case...... prescriptions issued over the phone compared with all antibiotic prescriptions; and a high number of consultations per 1000 patients. We also found that a low number of consultations per 1000 patients was associated with a reduced likelihood of being a high prescriber of antibiotics. Conclusions: An apparent...

  18. Genome-wide strategies identify downstream target genes of chick connective tissue-associated transcription factors.

    Science.gov (United States)

    Orgeur, Mickael; Martens, Marvin; Leonte, Georgeta; Nassari, Sonya; Bonnin, Marie-Ange; Börno, Stefan T; Timmermann, Bernd; Hecht, Jochen; Duprez, Delphine; Stricker, Sigmar

    2018-03-29

    Connective tissues support organs and play crucial roles in development, homeostasis and fibrosis, yet our understanding of their formation is still limited. To gain insight into the molecular mechanisms of connective tissue specification, we selected five zinc-finger transcription factors - OSR1, OSR2, EGR1, KLF2 and KLF4 - based on their expression patterns and/or known involvement in connective tissue subtype differentiation. RNA-seq and ChIP-seq profiling of chick limb micromass cultures revealed a set of common genes regulated by all five transcription factors, which we describe as a connective tissue core expression set. This common core was enriched with genes associated with axon guidance and myofibroblast signature, including fibrosis-related genes. In addition, each transcription factor regulated a specific set of signalling molecules and extracellular matrix components. This suggests a concept whereby local molecular niches can be created by the expression of specific transcription factors impinging on the specification of local microenvironments. The regulatory network established here identifies common and distinct molecular signatures of limb connective tissue subtypes, provides novel insight into the signalling pathways governing connective tissue specification, and serves as a resource for connective tissue development. © 2018. Published by The Company of Biologists Ltd.

  19. The use of human factors methods to identify and mitigate safety issues in radiation therapy

    International Nuclear Information System (INIS)

    Chan, Alvita J.; Islam, Mohammad K.; Rosewall, Tara; Jaffray, David A.; Easty, Anthony C.; Cafazzo, Joseph A.

    2010-01-01

    Background and purpose: New radiation therapy technologies can enhance the quality of treatment and reduce error. However, the treatment process has become more complex, and radiation dose is not always delivered as intended. Using human factors methods, a radiotherapy treatment delivery process was evaluated, and a redesign was undertaken to determine the effect on system safety. Material and methods: An ethnographic field study and workflow analysis was conducted to identify human factors issues of the treatment delivery process. To address specific issues, components of the user interface were redesigned through a user-centered approach. Sixteen radiation therapy students were then used to experimentally evaluate the redesigned system through a usability test to determine the effectiveness in mitigating use errors. Results: According to findings from the usability test, the redesigned system successfully reduced the error rates of two common errors (p < .04 and p < .01). It also improved the mean task completion time by 5.5% (p < .02) and achieved a higher level of user satisfaction. Conclusions: These findings demonstrated the importance and benefits of applying human factors methods in the design of radiation therapy systems. Many other opportunities still exist to improve patient safety in this area using human factors methods.

  20. Identifying and prioritizing different factors influencing the success of advertisement during the economic depression

    Directory of Open Access Journals (Sweden)

    Aram Rashidi

    2014-04-01

    Full Text Available During the financial crisis of 2007, many businesses and banks faced unexpected circumstances and declared bankruptcy. Market mortgage crisis and the collapse of the economic system in United States created a substantial amount of damage in world economy. Within a few years, the economic downturn was transferred to developing countries such as Iran. The recession has created conditions for Iranian companies that have led them to focus more on the subject of advertising since this is the primary tool of communication and business customers business. Success and failure of many organizations and companies depend on their advertisement planning. In this study, the factors contributing to the success and effectiveness of advertising during the recession time are identified. This survey has been accomplished on investigating an Iranian dairy firm named “Kalle”. Using a questionnaire in Likert scale, the study determines the effects of various factors of advertisement on sales improvement in this firm using Pearson correlation ratio and rank them based on Freedman test. Cronbach alpha has been calculated as 0.93. According to the results, factors that contribute to the success of advertising during a recession include: Responsiveness to customers’ needs, advertising tools, content factors, the amount of money spent and availability.

  1. Identifying and prioritizing the factors effective in customer satisfaction using the TOPSIS method

    Directory of Open Access Journals (Sweden)

    H Forougozar

    2014-01-01

    Full Text Available Introduction: Customer satisfaction has been suggested as one of the interesting and challenging issues of management in the new millennium. In addition, oral and dental health and the quality of the services the health centers delivered to the patients directly affect the customer satisfaction. Therefore, the present study aimed to identify, investigate, and rank the factors affecting the customer satisfaction in the department of dentistry of Shiraz Farhangiyan health center. Method: The present descriptive study was conducted on the specialists and patients of the department of dentistry of Shiraz Farhangiyan health center. The validity of the questionnaire utilized in the study was confirmed by expert professors and its reliability was approved using the Cronbach’s alpha formula. Finally, the study data were analyzed in SPSS statistical software (v. 16, using inferential statistics. Results: All the hypotheses were confirmed by the results of the statistical analyses and quality, services, and expenditures revealed to affect the customer satisfaction in the department of dentistry of Shiraz Farhangiyan health center. Moreover, these factors were ranked using the TOPSIS method and the results showed quality and expenditures as the most and the least effective factors in customer satisfaction, respectively. Conclusion: Since restoring and arranging the organization based on the customer needs is among the main priorities of designing an organization, managers are suggested to take measures for organizational reformation based on the customers’ priorities. Of course, conducting such programs is of utmost importance in health and treatment environments, leading to provision of better services and facilitation of learning, education, and research. Thus, identifying the effective factors in customer satisfaction and ranking them are highly important.

  2. A structured elicitation method to identify key direct risk factors for the management of natural resources

    Directory of Open Access Journals (Sweden)

    Michael Smith

    2015-11-01

    Full Text Available The high level of uncertainty inherent in natural resource management requires planners to apply comprehensive risk analyses, often in situations where there are few resources. In this paper, we demonstrate a broadly applicable, novel and structured elicitation approach to identify important direct risk factors. This new approach combines expert calibration and fuzzy based mathematics to capture and aggregate subjective expert estimates of the likelihood that a set of direct risk factors will cause management failure. A specific case study is used to demonstrate the approach; however, the described methods are widely applicable in risk analysis. For the case study, the management target was to retain all species that characterise a set of natural biological elements. The analysis was bounded by the spatial distribution of the biological elements under consideration and a 20-year time frame. Fourteen biological elements were expected to be at risk. Eleven important direct risk factors were identified that related to surrounding land use practices, climate change, problem species (e.g., feral predators, fire and hydrological change. In terms of their overall influence, the two most important risk factors were salinisation and a lack of water which together pose a considerable threat to the survival of nine biological elements. The described approach successfully overcame two concerns arising from previous risk analysis work: (1 the lack of an intuitive, yet comprehensive scoring method enabling the detection and clarification of expert agreement and associated levels of uncertainty; and (2 the ease with which results can be interpreted and communicated while preserving a rich level of detail essential for informed decision making.

  3. Application of geographically-weighted regression analysis to assess risk factors for malaria hotspots in Keur Soce health and demographic surveillance site.

    Science.gov (United States)

    Ndiath, Mansour M; Cisse, Badara; Ndiaye, Jean Louis; Gomis, Jules F; Bathiery, Ousmane; Dia, Anta Tal; Gaye, Oumar; Faye, Babacar

    2015-11-18

    In Senegal, considerable efforts have been made to reduce malaria morbidity and mortality during the last decade. This resulted in a marked decrease of malaria cases. With the decline of malaria cases, transmission has become sparse in most Senegalese health districts. This study investigated malaria hotspots in Keur Soce sites by using geographically-weighted regression. Because of the occurrence of hotspots, spatial modelling of malaria cases could have a considerable effect in disease surveillance. This study explored and analysed the spatial relationships between malaria occurrence and socio-economic and environmental factors in small communities in Keur Soce, Senegal, using 6 months passive surveillance. Geographically-weighted regression was used to explore the spatial variability of relationships between malaria incidence or persistence and the selected socio-economic, and human predictors. A model comparison of between ordinary least square and geographically-weighted regression was also explored. Vector dataset (spatial) of the study area by village levels and statistical data (non-spatial) on malaria confirmed cases, socio-economic status (bed net use), population data (size of the household) and environmental factors (temperature, rain fall) were used in this exploratory analysis. ArcMap 10.2 and Stata 11 were used to perform malaria hotspots analysis. From Jun to December, a total of 408 confirmed malaria cases were notified. The explanatory variables-household size, housing materials, sleeping rooms, sheep and distance to breeding site returned significant t values of -0.25, 2.3, 4.39, 1.25 and 2.36, respectively. The OLS global model revealed that it explained about 70 % (adjusted R(2) = 0.70) of the variation in malaria occurrence with AIC = 756.23. The geographically-weighted regression of malaria hotspots resulted in coefficient intercept ranging from 1.89 to 6.22 with a median of 3.5. Large positive values are distributed mainly in the southeast

  4. Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

    Science.gov (United States)

    Liu, Yan; Salvendy, Gavriel

    2009-05-01

    This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.

  5. Identifying Contextual and Emotional Factors to Explore Weight Disparities between Obese Black and White Women

    Directory of Open Access Journals (Sweden)

    NiCole R. Keith

    2016-01-01

    Full Text Available Background Obese black women enrolled in weight loss interventions experience 50% less weight reduction than obese white women. This suggests that current weight loss strategies may increase health disparities. Objective We evaluated the feasibility of identifying daily contextual factors that may influence obesity. Methods In-home interviews with 16 obese (body mass index ≥ 30 black and white urban poor women were performed. For 14 days, ecological momentary assessment (EMA was used to capture emotion and social interactions every other day, and day reconstruction method surveys were used the following day to reconstruct the context of the prior day's EMA. Results Factors included percentage of participants without weight scales (43.8% or fitness equipment (68.8% in the home and exposed to food at work (55.6%. The most frequently reported location, activity, and emotion were home (19.4 ± 8.53, working (7.1 ± 8.80, and happy (6.9 ± 10.03, respectively. Conclusion Identifying individual contexts may lead to valuable insights about obesogenic behaviors and new interventions to improve weight management.

  6. Testing job typologies and identifying at-risk subpopulations using factor mixture models.

    Science.gov (United States)

    Keller, Anita C; Igic, Ivana; Meier, Laurenz L; Semmer, Norbert K; Schaubroeck, John M; Brunner, Beatrice; Elfering, Achim

    2017-10-01

    Research in occupational health psychology has tended to focus on the effects of single job characteristics or various job characteristics combined into 1 factor. However, such a variable-centered approach does not account for the clustering of job attributes among groups of employees. We addressed this issue by using a person-centered approach to (a) investigate the occurrence of different empirical constellations of perceived job stressors and resources and (b) validate the meaningfulness of profiles by analyzing their association with employee well-being and performance. We applied factor mixture modeling to identify profiles in 4 large samples consisting of employees in Switzerland (Studies 1 and 2) and the United States (Studies 3 and 4). We identified 2 profiles that spanned the 4 samples, with 1 reflecting a combination of relatively low stressors and high resources (P1) and the other relatively high stressors and low resources (P3). The profiles differed mainly in terms of their organizational and social aspects. Employees in P1 reported significantly higher mean levels of job satisfaction, performance, and general health, and lower means in exhaustion compared with P3. Additional analyses showed differential relationships between job attributes and outcomes depending on profile membership. These findings may benefit organizational interventions as they show that perceived work stressors and resources more strongly influence satisfaction and well-being in particular profiles. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  7. Design considerations for identifying breast cancer risk factors in a population-based study in Africa.

    Science.gov (United States)

    Brinton, Louise A; Awuah, Baffour; Nat Clegg-Lamptey, Joe; Wiafe-Addai, Beatrice; Ansong, Daniel; Nyarko, Kofi M; Wiafe, Seth; Yarney, Joel; Biritwum, Richard; Brotzman, Michelle; Adjei, Andrew A; Adjei, Ernest; Aitpillah, Francis; Edusei, Lawrence; Dedey, Florence; Nyante, Sarah J; Oppong, Joseph; Osei-Bonsu, Ernest; Titiloye, Nicholas; Vanderpuye, Verna; Brew Abaidoo, Emma; Arhin, Bernard; Boakye, Isaac; Frempong, Margaret; Ohene Oti, Naomi; Okyne, Victoria; Figueroa, Jonine D

    2017-06-15

    Although breast cancer is becoming more prevalent in Africa, few epidemiologic studies have been undertaken and appropriate methodologic approaches remain uncertain. We therefore conducted a population-based case-control study in Accra and Kumasi, Ghana, enrolling 2,202 women with lesions suspicious for breast cancer and 2,161 population controls. Biopsy tissue for cases prior to neoadjuvant therapy (if given), blood, saliva and fecal samples were sought for study subjects. Response rates, risk factor prevalences and odds ratios for established breast cancer risk factors were calculated. A total of 54.5% of the recruited cases were diagnosed with malignancies, 36.0% with benign conditions and 9.5% with indeterminate diagnoses. Response rates to interviews were 99.2% in cases and 91.9% in controls, with the vast majority of interviewed subjects providing saliva (97.9% in cases vs. 98.8% in controls) and blood (91.8% vs. 82.5%) samples; lower proportions (58.1% vs. 46.1%) provided fecal samples. While risk factor prevalences were unique as compared to women in other countries (e.g., less education, higher parity), cancer risk factors resembled patterns identified elsewhere (elevated risks associated with higher levels of education, familial histories of breast cancer, low parity and larger body sizes). Subjects with benign conditions were younger and exhibited higher socioeconomic profiles (e.g., higher education and lower parity) than those with malignancies, suggesting selective referral influences. While further defining breast cancer risk factors in Africa, this study showed that successful population-based interdisciplinary studies of cancer in Africa are possible but require close attention to diagnostic referral biases and standardized and documented approaches for high-quality data collection, including biospecimens. © 2017 UICC.

  8. Identifying factors associated with the discharge of male State patients from Weskoppies Hospital

    Directory of Open Access Journals (Sweden)

    Riaan G. Prinsloo

    2017-12-01

    Full Text Available Background: Designated psychiatric facilities are responsible for the care, treatment and reintegration of State patients. The necessary long-term care places a considerable strain on health-care resources. Resource use should be optimised while managing the risks that patients pose to themselves and the community. Identifying unique factors associated with earlier discharge may decrease the length of stay. Factors associated with protracted inpatient care without discharge could identify patients who require early and urgent intervention. Aim: We identify socio-economic, demographic, psychiatric and charge-related factors associated with the discharge of male State patients. Methods: We reviewed the files of discharged and admitted forensic State patients at Weskoppies Psychiatric Hospital. Data were captured in an electronic recording sheet. The association between factors and the outcome measure (discharged vs. admitted was determined using chi-squared tests and Fischer’s exact tests. Results: Discharged State patients were associated with being a primary caregiver (p = 0.031 having good insight into illness (p = 0.025 or offence (p = 0.005 and having had multiple successful leaves of absences. A lack of substance abuse during admission (p = 0.027, an absence of a diagnosis of substance use disorder (p = 0.013 and the absence of verbal and physical aggression (p = 0.002 and p = 0.016 were associated with being discharged. Prolonged total length of stay (9–12 years, p = 0.031 and prolonged length of stay in open wards (6–9 years, p = 0.000 were associated with being discharged. A history of previous offences (p = 0.022, a diagnosis of substance use disorder (p = 0.023, recent substance abuse (p = 0.018 and a history of physical aggression since admission (p = 0.017 were associated with continued admission. Conclusion: Discharge of State patients is associated with an absence of substance abuse, lack of aggression

  9. Identifying protective and risk factors for injurious falls in patients hospitalized for acute care: a retrospective case-control study

    Directory of Open Access Journals (Sweden)

    Emmanuel Aryee

    2017-11-01

    Full Text Available Abstract Background Admitted patients who fall and injure themselves during an acute hospitalization incur increased costs, morbidity, and mortality, but little research has been conducted on identifying inpatients at high risk to injure themselves in a fall. Falls risk assessment tools have been unsuccessful due to their low positive predictive value when applied broadly to entire hospital populations. We aimed to identify variables associated with the risk of or protection against injurious fall in the inpatient setting. We also aimed to test the variables in the ABCs mnemonic (Age > 85, Bones-orthopedic conditions, anti-Coagulation and recent surgery for correlation with injurious fall. Methods We performed a retrospective case-control study at an academic tertiary care center comparing admitted patients with injurious fall to admitted patients without fall. We collected data on the demographics, medical and fall history, outcomes, and discharge disposition of injured fallers and control patients. We performed multivariate analysis of potential risk factors for injurious fall with logistic regression to calculate adjusted odds ratios. Results We identified 117 injured fallers and 320 controls. There were no differences in age, anti-coagulation use or fragility fractures between cases and controls. In multivariate analysis, recent surgery (OR 0.46, p = 0.003 was protective; joint replacement (OR 5.58, P = 0.002, psychotropic agents (OR 2.23, p = 0.001, the male sex (OR 2.08, p = 0.003 and history of fall (OR 2.08, p = 0.02 were significantly associated with injurious fall. Conclusion In this study, the variables in the ABCs parameters were among the variables not useful for identifying inpatients at risk of injuring themselves in a fall, while other non-ABCs variables demonstrated a significant association with injurious fall. Recent surgery was a protective factor, and practices around the care of surgical patients could be

  10. Using a Systematic Approach to Identifying Organizational Factors in Root Cause Analysis

    International Nuclear Information System (INIS)

    Gallogly, Kay Wilde

    2011-01-01

    This presentation set the scene for the second discussion session. In her presentation, the author observed that: - Investigators do not see the connection between the analysis tools available and the identification of HOF. Most investigators use the tools in a cursory manner and so do not derive the full benefits of the tools. Some tools are used for presentation purposes as opposed to being used for analytical purposes e.g. event and causal factors charts. In some cases, the report will indicate that specific analytical tools were used in the investigation but the analysis is not in the body of the report. - Some investigators are documenting HOF causes but do not recognize them as such. This indicates a lack of understanding of HOF. - Others investigators focus on technical issues because of their own comfort level. - The culture of the Organisation will affect the depth of the investigation and therefore the use of the analytical tools to pursue HOF issues. - The author contends that if analysis tools are applied systematically to gather factually based data, then HOF issues can be identified. The use of factual information (without judgement and subjectivity) is important to maintain the credibility of the investigation especially when HOF issues are identified. - Systematic use of tools assists in better communication of the issues to foster greater understanding and acceptance by senior management. - Barrier Analysis, Change Analysis, and TWIN (Task Demands, Work Environment, Individual Capabilities, and Human Nature) all offer the opportunity to identify HOF issues if the analyst pursues this line of investigation. It was illustrated that many elements of the TWIN Error Precursors are themselves Organisational in nature. - The TWIN model applied to the Anatomy of an Event will help to distinguish those which are Organisational issues (Latent Organisational Weaknesses, Error Precursors and Flawed Defences) and those which are human factors (Active Errors

  11. Tombusvirus-yeast interactions identify conserved cell-intrinsic viral restriction factors

    Directory of Open Access Journals (Sweden)

    Zsuzsanna eSasvari

    2014-08-01

    Full Text Available To combat viral infections, plants possess innate and adaptive immune pathways, such as RNA silencing, R gene and recessive gene-mediated resistance mechanisms. However, it is likely that additional cell-intrinsic restriction factors (CIRF are also involved in limiting plant virus replication. This review discusses novel CIRFs with antiviral functions, many of them RNA-binding proteins or affecting the RNA binding activities of viral replication proteins. The CIRFs against tombusviruses have been identified in yeast (Saccharomyces cerevisiae, which is developed as an advanced model organism. Grouping of the identified CIRFs based on their known cellular functions and subcellular localization in yeast reveals that TBSV replication is limited by a wide variety of host gene functions. Yeast proteins with the highest connectivity in the network map include the well-characterized Xrn1p 5’-3’ exoribonuclease, Act1p actin protein and Cse4p centromere protein. The protein network map also reveals an important interplay between the pro-viral Hsp70 cellular chaperone and the antiviral co-chaperones, and possibly key roles for the ribosomal or ribosome-associated factors. We discuss the antiviral functions of selected CIRFs, such as the RNA binding nucleolin, ribonucleases, WW-domain proteins, single- and multi-domain cyclophilins, TPR-domain co-chaperones and cellular ion pumps. These restriction factors frequently target the RNA-binding region in the viral replication proteins, thus interfering with the recruitment of the viral RNA for replication and the assembly of the membrane-bound viral replicase. Although many of the characterized CIRFs act directly against TBSV, we propose that the TPR-domain co-chaperones function as guardians of the cellular Hsp70 chaperone system, which is subverted efficiently by TBSV for viral replicase assembly in the absence of the TPR-domain co-chaperones.

  12. Proteinuria in adult Saudi patients with sickle cell disease is not associated with identifiable risk factors

    Directory of Open Access Journals (Sweden)

    Aleem Aamer

    2010-01-01

    Full Text Available Renal involvement in patients with sickle cell disease (SCD is associated with signi-ficant morbidity and mortality. Proteinuria is common in patients with SCD and is a risk factor for future development of renal failure. We sought to identify risk factors, if any, associated with pro-teinuria in adult Saudi patients with SCD. We studied 67 patients with SCD followed-up at the King Khalid University Hospital, Riyadh, Saudi Arabia. All patients underwent 24-hour urine collection to measure creatinine clearance and to quantify proteinuria. In addition, blood was examined for evaluation of hematological and biochemical parameters. Clinical information was gathered from review of the patients′ charts. A urine protein level of more than 0.150 grams/24 hours was consi-dered abnormal. Urine protein was correlated with various clinical and laboratory parameters. Thirty-one males and 36 females were evaluated. The mean age of the cohort was 23.8 (± 7.2 years. Twenty-seven patients (40.3% had proteinuria of more than 0.150 grams/24 hours. The study group had a mean hemoglobin level of 8.5 (± 2.8 g/dL and mean fetal hemoglobin (HbF level of 14.4% (± 7.3%. Majority of the patients (61 had hemoglobin SS genotype and six patients had S-β0 thala-ssemia. None of the parameters evaluated correlated with proteinuria although there was a border-line association with older age and higher systolic blood pressure (P = 0.073 and 0.061 respec-tively. Hydroxyurea use for more than a year was not beneficial. In conclusion, our study suggests that proteinuria in adult Saudi patients is not associated with any clear identifiable risk factors.

  13. Physiologically-based toxicokinetic models help identifying the key factors affecting contaminant uptake during flood events

    Energy Technology Data Exchange (ETDEWEB)

    Brinkmann, Markus; Eichbaum, Kathrin [Department of Ecosystem Analysis, Institute for Environmental Research,ABBt – Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); Kammann, Ulrike [Thünen-Institute of Fisheries Ecology, Palmaille 9, 22767 Hamburg (Germany); Hudjetz, Sebastian [Department of Ecosystem Analysis, Institute for Environmental Research,ABBt – Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Cofalla, Catrina [Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Buchinger, Sebastian; Reifferscheid, Georg [Federal Institute of Hydrology (BFG), Department G3: Biochemistry, Ecotoxicology, Am Mainzer Tor 1, 56068 Koblenz (Germany); Schüttrumpf, Holger [Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Preuss, Thomas [Department of Environmental Biology and Chemodynamics, Institute for Environmental Research,ABBt- Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); and others

    2014-07-01

    Highlights: • A PBTK model for trout was coupled with a sediment equilibrium partitioning model. • The influence of physical exercise on pollutant uptake was studies using the model. • Physical exercise during flood events can increase the level of biliary metabolites. • Cardiac output and effective respiratory volume were identified as relevant factors. • These confounding factors need to be considered also for bioconcentration studies. - Abstract: As a consequence of global climate change, we will be likely facing an increasing frequency and intensity of flood events. Thus, the ecotoxicological relevance of sediment re-suspension is of growing concern. It is vital to understand contaminant uptake from suspended sediments and relate it to effects in aquatic biota. Here we report on a computational study that utilizes a physiologically based toxicokinetic model to predict uptake, metabolism and excretion of sediment-borne pyrene in rainbow trout (Oncorhynchus mykiss). To this end, data from two experimental studies were compared with the model predictions: (a) batch re-suspension experiments with constant concentration of suspended particulate matter at two different temperatures (12 and 24 °C), and (b) simulated flood events in an annular flume. The model predicted both the final concentrations and the kinetics of 1-hydroxypyrene secretion into the gall bladder of exposed rainbow trout well. We were able to show that exhaustive exercise during exposure in simulated flood events can lead to increased levels of biliary metabolites and identified cardiac output and effective respiratory volume as the two most important factors for contaminant uptake. The results of our study clearly demonstrate the relevance and the necessity to investigate uptake of contaminants from suspended sediments under realistic exposure scenarios.

  14. Physiologically-based toxicokinetic models help identifying the key factors affecting contaminant uptake during flood events

    International Nuclear Information System (INIS)

    Brinkmann, Markus; Eichbaum, Kathrin; Kammann, Ulrike; Hudjetz, Sebastian; Cofalla, Catrina; Buchinger, Sebastian; Reifferscheid, Georg; Schüttrumpf, Holger; Preuss, Thomas

    2014-01-01

    Highlights: • A PBTK model for trout was coupled with a sediment equilibrium partitioning model. • The influence of physical exercise on pollutant uptake was studies using the model. • Physical exercise during flood events can increase the level of biliary metabolites. • Cardiac output and effective respiratory volume were identified as relevant factors. • These confounding factors need to be considered also for bioconcentration studies. - Abstract: As a consequence of global climate change, we will be likely facing an increasing frequency and intensity of flood events. Thus, the ecotoxicological relevance of sediment re-suspension is of growing concern. It is vital to understand contaminant uptake from suspended sediments and relate it to effects in aquatic biota. Here we report on a computational study that utilizes a physiologically based toxicokinetic model to predict uptake, metabolism and excretion of sediment-borne pyrene in rainbow trout (Oncorhynchus mykiss). To this end, data from two experimental studies were compared with the model predictions: (a) batch re-suspension experiments with constant concentration of suspended particulate matter at two different temperatures (12 and 24 °C), and (b) simulated flood events in an annular flume. The model predicted both the final concentrations and the kinetics of 1-hydroxypyrene secretion into the gall bladder of exposed rainbow trout well. We were able to show that exhaustive exercise during exposure in simulated flood events can lead to increased levels of biliary metabolites and identified cardiac output and effective respiratory volume as the two most important factors for contaminant uptake. The results of our study clearly demonstrate the relevance and the necessity to investigate uptake of contaminants from suspended sediments under realistic exposure scenarios

  15. Genome-wide CRISPR/Cas9 Screen Identifies Host Factors Essential for Influenza Virus Replication

    Directory of Open Access Journals (Sweden)

    Julianna Han

    2018-04-01

    Full Text Available Summary: The emergence of influenza A viruses (IAVs from zoonotic reservoirs poses a great threat to human health. As seasonal vaccines are ineffective against zoonotic strains, and newly transmitted viruses can quickly acquire drug resistance, there remains a need for host-directed therapeutics against IAVs. Here, we performed a genome-scale CRISPR/Cas9 knockout screen in human lung epithelial cells with a human isolate of an avian H5N1 strain. Several genes involved in sialic acid biosynthesis and related glycosylation pathways were highly enriched post-H5N1 selection, including SLC35A1, a sialic acid transporter essential for IAV receptor expression and thus viral entry. Importantly, we have identified capicua (CIC as a negative regulator of cell-intrinsic immunity, as loss of CIC resulted in heightened antiviral responses and restricted replication of multiple viruses. Therefore, our study demonstrates that the CRISPR/Cas9 system can be utilized for the discovery of host factors critical for the replication of intracellular pathogens. : Using a genome-wide CRISPR/Cas9 screen, Han et al. demonstrate that the major hit, the sialic acid transporter SLC35A1, is an essential host factor for IAV entry. In addition, they identify the DNA-binding transcriptional repressor CIC as a negative regulator of cell-intrinsic immunity. Keywords: CRISPR/Cas9 screen, GeCKO, influenza virus, host factors, sialic acid pathway, SLC35A1, Capicua, CIC, cell-intrinsic immunity, H5N1

  16. Burden of liver disease in Europe: epidemiology and analysis of risk factors to identify prevention policies.

    Science.gov (United States)

    Pimpin, Laura; Cortez-Pinto, Helena; Negro, Francesco; Corbould, Emily; Lazarus, Jeffrey V; Webber, Laura; Sheron, Nick

    2018-05-16

    The burden of liver disease in Europe continues to grow. We aimed to describe the epidemiology of liver diseases and their risk factors in European countries, and identify public health interventions that could impact on these risk factors to reduce the burden of liver disease. As part of the HEPAHEALTH project, commissioned by EASL, we extracted information on historical and current prevalence and mortality from national and international literature and databases on liver disease in 35 countries in the WHO European region, as well as historical and recent prevalence data on their main determinants; alcohol consumption, obesity and hepatitis B and C virus infections. We extracted information from peer-reviewed and grey literature to identify public health interventions targeting these risk factors. The epidemiology of liver disease is diverse and countries cluster with similar pictures, although the exact composition of diseases and the trends in risk factors which drive them is varied. Prevalence and mortality data indicate that increasing cirrhosis and liver cancer may be linked to dramatic increases in harmful alcohol consumption in Northern European countries, and viral hepatitis epidemics in Eastern and Southern European countries. Countries with historically low levels of liver disease may experience an increase in non-alcoholic fatty liver disease in the future, given the rise of obesity across the majority of European countries. Interventions exist for curbing harmful alcohol use, reducing obesity, preventing or treating viral hepatitis, and screening for liver disease at an early stage. Liver disease in Europe is a serious issue, with increasing cirrhosis and liver cancer. The public health and hepatology communities are uniquely placed to implement measures aimed at reducing their causes: harmful alcohol consumption, child and adult obesity prevalence and chronic infection with hepatitis viruses, which will in turn reduce the burden of liver disease. The

  17. Identifying the environmental factors that effect within canopy BVOC loss using a multilevel canopy model

    Science.gov (United States)

    Chan, W. S.; Fuentes, J. D.; Lerdau, M.

    2010-12-01

    This presentation will provide research findings to evaluate the hypothesis that the loss of biogenic volatile organic compound (BVOC) within plant canopies is dynamic and depends on factors such as plant canopy architecture (height and leaf area distribution), atmospheric turbulence, concentration of oxidants (OH, O3, NO3), and the reactivity of BVOC species. Results will be presented from a new one dimensional, multilevel canopy model that couples algorithms for canopy microclimate, leaf physiology, BVOC emission, turbulent transport, and atmospheric chemistry to investigate the relative importance of factors that impact BVOC loss within a forest canopy. Model sensitivity tests will be presented and discussed to identify factors driving canopy loss. Results show isoprene and monoterpene canopy losses as high as 9 and 18%, respectively, for tall canopies during the daytime. We hypothesize that canopy height and wind speed (i.e. canopy residence time) may be the most important in dictating within-canopy loss. This work will reduce the error in bottom-up flux estimates of BVOCs and ultimately improve parameterizations of BVOC sources in air quality models by accounting for within canopy processes.

  18. Genome-wide screen of Pseudomonas aeruginosa In Saccharomyces cerevisiae identifies new virulence factors

    Directory of Open Access Journals (Sweden)

    Rafat eZrieq

    2015-11-01

    Full Text Available Pseudomonas aeruginosa is a human opportunistic pathogen that causes mortality in cystic fibrosis and immunocompromised patients. While many virulence factors of this pathogen have already been identified, several remain to be discovered. In this respect we set an unprecedented genome-wide screen of a P. aeruginosa expression library based on a yeast growth phenotype. 51 candidates were selected in a three-round screening process. The robustness of the screen was validated by the selection of three well known secreted proteins including one demonstrated virulence factor, the protease LepA. Further in silico sorting of the 51 candidates highlighted three potential new Pseudomonas effector candidates (Pec. By testing the cytotoxicity of wild type P. aeruginosa vs pec mutants towards macrophages and the virulence in the Caenorhabditis elegans model, we demonstrated that the three selected Pecs are novel virulence factors of P. aeruginosa. Additional cellular localization experiments in the host revealed specific localization for Pec1 and Pec2 that could inform about their respective functions.

  19. Use of a twin dataset to identify AMD-related visual patterns controlled by genetic factors

    Science.gov (United States)

    Quellec, Gwénolé; Abràmoff, Michael D.; Russell, Stephen R.

    2010-03-01

    The mapping of genotype to the phenotype of age-related macular degeneration (AMD) is expected to improve the diagnosis and treatment of the disease in a near future. In this study, we focused on the first step to discover this mapping: we identified visual patterns related to AMD which seem to be controlled by genetic factors, without explicitly relating them to the genes. For this purpose, we used a dataset of eye fundus photographs from 74 twin pairs, either monozygotic twins, who have the same genotype, or dizygotic twins, whose genes responsible for AMD are less likely to be identical. If we are able to differentiate monozygotic twins from dizygotic twins, based on a given visual pattern, then this pattern is likely to be controlled by genetic factors. The main visible consequence of AMD is the apparition of drusen between the retinal pigment epithelium and Bruch's membrane. We developed two automated drusen detectors based on the wavelet transform: a shape-based detector for hard drusen, and a texture- and color- based detector for soft drusen. Forty visual features were evaluated at the location of the automatically detected drusen. These features characterize the texture, the shape, the color, the spatial distribution, or the amount of drusen. A distance measure between twin pairs was defined for each visual feature; a smaller distance should be measured between monozygotic twins for visual features controlled by genetic factors. The predictions of several visual features (75.7% accuracy) are comparable or better than the predictions of human experts.

  20. Identifying factors associated with perceived success in the transition from hospital to home after brain injury.

    Science.gov (United States)

    Nalder, Emily; Fleming, Jennifer; Foster, Michele; Cornwell, Petrea; Shields, Cassandra; Khan, Asad

    2012-01-01

    : To identify the factors associated with perceived success of the transition from hospital to home after traumatic brain injury (TBI). : Prospective longitudinal cohort design with data collection at discharge and 1, 3, and 6 months postdischarge. : A total of 127 individuals with TBI discharged to the community and 83 significant others. : An analog scale (0-100) of perceived success of the transition from hospital to home rated by individuals and significant others; Sentinel Events Questionnaire; EuroQol Group Quality-of-Life measure visual analog scale; Sydney Psychosocial Reintegration Scale; Mayo-Portland Adaptability Inventory-4; short form of the Depression, Anxiety, Stress Scales; Craig Hospital Inventory of Environmental Factors; and Caregiver Strain Index. : Greater perceived success of transition for individuals with a TBI was associated with higher levels of health-related quality of life, level of community integration, and more severe injury. Among survivors, sentinel events such as returning to work and independent community access and changing living situation were associated with greater perceived success; financial strain and difficulty accessing therapy services were associated with less success. Among significant others, lower ratings of transition success were associated with higher significant other stress levels as well as lower levels of community integration and changes in the living situation of the individual with TBI. : A combination of sentinel events and personal and environmental factors influences the perceptions of individuals and their families regarding the success of the transition from hospital to home.

  1. Impact of identifying factors which trigger bothersome tinnitus on the treatment outcome in tinnitus retraining therapy.

    Science.gov (United States)

    Molini, Egisto; Faralli, Mario; Calzolaro, Lucia; Ricci, Giampietro

    2014-01-01

    The aim of this work was to ascertain any differences in the effectiveness of rehabilitation therapy in relation to the presence or absence of a known negative reinforcement responsible for the tinnitus-related pathology. Between 1 January 2001 and 31 December 2008, we recruited 294 subjects suffering from incapacitating tinnitus and/or hyperacusis. The patients underwent tinnitus retraining therapy (TRT) according to the methods described by Jastreboff and Hazell [Tinnitus Retraining Therapy: Implementing the Neurophysiological Model. Cambridge, Cambridge University Press, 2004, pp 121-133]. We clinically assessed the presence or absence of known phenomena of associative learning, regarding the presence of adverse events temporally correlated with tinnitus and the treatment outcome. The separate analysis of the 2 subgroups shows a statistically significant difference in the improvement rate between the group with a known triggering factor and the group without a triggering factor, with a preponderance of the former with a 91% improvement rate versus approximately 56% for the latter. In our study, the inability to identify factors triggering bothersome tinnitus negatively affected the treatment outcome in TRT. © 2014 S. Karger AG, Basel.

  2. Random T-DNA mutagenesis identifies a Cu-Zn-superoxide dismutase gene as a virulence factor of Sclerotinia sclerotiorum

    Science.gov (United States)

    Agrobacterium-mediated transformation (AMT) was used to identify potential virulence factors in Sclerotinia sclerotiorum. Screening AMT transformants identified two mutants showing significantly reduced virulence. The mutants showed similar growth rate, colony morphology, and sclerotial and oxalate ...

  3. Identifying and Studying the Factors Effective on Greenhouses Profitability in the Varamin Plain

    Directory of Open Access Journals (Sweden)

    Narges Rajabi Tehrani

    2017-01-01

    Full Text Available The purpose of this research was economic evaluation of green houses and the factors that affect their profitability in the Varamin plain. The type of this research is descriptive-correlation research that was conducted by using a survey method. The statistical population of the research consisted of the beneficiary farmers of established and cultivated green houses in the Varamin plain. The sample size was 108 farmers. The sampling method was simple random sampling method. The main tool of this research study is a questionnaire that whose validity was verified by using a panel of experts and professors in the field of agriculture. The reliability of the questionnaire was assessed through a pre-test for which the Cronbach alpha was between 0.78 and 0.85 which is considered to be acceptable. The results of this research study show that the mean of the profitability index of cost benefit  was 2.286 and thus there is a significant positive correlation between agricultural experience, the level of famer education, agricultural income, the total area of the green house, technical knowledge, using of information resources with the cost benefit  profitability index. The results of regression analysis also indicated that the five variables of agricultural experience, agricultural income, the total area of the green house, technical knowledge, using of information resources well explain for 51.5 % of the changes in the cost benefit profitability index of the green houses located in the Varamin plain. Finally, it is recommended to improve the cost benefit profitability index by actions such as increasing the level of technical knowledge and farmers' access to and use of information resources.

  4. Risk factors for inadequate TB case finding in Rural Western Kenya: a comparison of actively and passively identified TB patients.

    Directory of Open Access Journals (Sweden)

    Anna H Van't Hoog

    Full Text Available The findings of a prevalence survey conducted in western Kenya, in a population with 14.9% HIV prevalence suggested inadequate case finding. We found a high burden of infectious and largely undiagnosed pulmonary tuberculosis (PTB, that a quarter of the prevalent cases had not yet sought care, and a low case detection rate.We aimed to identify factors associated with inadequate case finding among adults with PTB in this population by comparing characteristics of 194 PTB patients diagnosed in a health facility after self-report, i.e., through passive case detection, with 88 patients identified through active case detection during the prevalence survey. We examined associations between method of case detection and patient characteristics, including HIV-status, socio-demographic variables and disease severity in univariable and multivariable logistic regression analyses.HIV-infection was associated with faster passive case detection in univariable analysis (crude OR 3.5, 95% confidence interval (CI 2.0-5.9, but in multivariable logistic regression this was largely explained by the presence of cough, illness and clinically diagnosed smear-negative TB (adjusted OR (aOR HIV 1.8, 95% CI 0.85-3.7. Among the HIV-uninfected passive case detection was less successful in older patients aOR 0.76, 95%CI 0.60-0.97 per 10 years increase, and women (aOR 0.27, 95%CI 0.10-0.73. Reported current or past alcohol use reduced passive case detection in both groups (0.42, 95% CI 0.23-0.79. Among smear-positive patients median durations of cough were 4.0 and 6.9 months in HIV-infected and uninfected patients, respectively.HIV-uninfected patients with infectious TB who were older, female, relatively less ill, or had a cough of a shorter duration were less likely found through passive case detection. In addition to intensified case finding in HIV-infected persons, increasing the suspicion of TB among HIV-uninfected women and the elderly are needed to improve TB case

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

    Directory of Open Access Journals (Sweden)

    Yuanxin Liu

    2018-05-01

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

  6. Spatiotemporal Pattern of PM2.5 Concentrations in Mainland China and Analysis of Its Influencing Factors using Geographically Weighted Regression

    Science.gov (United States)

    Luo, Jieqiong; Du, Peijun; Samat, Alim; Xia, Junshi; Che, Meiqin; Xue, Zhaohui

    2017-01-01

    Based on annual average PM2.5 gridded dataset, this study first analyzed the spatiotemporal pattern of PM2.5 across Mainland China during 1998-2012. Then facilitated with meteorological site data, land cover data, population and Gross Domestic Product (GDP) data, etc., the contributions of latent geographic factors, including socioeconomic factors (e.g., road, agriculture, population, industry) and natural geographical factors (e.g., topography, climate, vegetation) to PM2.5 were explored through Geographically Weighted Regression (GWR) model. The results revealed that PM2.5 concentrations increased while the spatial pattern remained stable, and the proportion of areas with PM2.5 concentrations greater than 35 μg/m3 significantly increased from 23.08% to 29.89%. Moreover, road, agriculture, population and vegetation showed the most significant impacts on PM2.5. Additionally, the Moran’s I for the residuals of GWR was 0.025 (not significant at a 0.01 level), indicating that the GWR model was properly specified. The local coefficient estimates of GDP in some cities were negative, suggesting the existence of the inverted-U shaped Environmental Kuznets Curve (EKC) for PM2.5 in Mainland China. The effects of each latent factor on PM2.5 in various regions were different. Therefore, regional measures and strategies for controlling PM2.5 should be formulated in terms of the local impacts of specific factors.

  7. Identifying the challenging factors in the transition from colleges of engineering to employment

    Science.gov (United States)

    Baytiyeh, Hoda; Naja, Mohamad

    2012-03-01

    The transition from university to a career in engineering is a challenging process. This study examined the perceptions of engineering graduates regarding the difficulties they encountered in their transition from the university to the workplace. Lebanese practising engineers (n=217), living around the world, were surveyed to identify their current employment situations and their attitudes toward their academic preparation. Factor analysis revealed three main challenges facing engineering graduates: communication; responsibility; self-confidence. Seventeen interviews were conducted to gather information on ways to facilitate this transition. Comments reflected the need for better collaboration between engineering schools and engineering firms. The results will provide insight for engineering colleges, faculty members and administrators into the challenges faced by graduates and their aspirations for a smoother transition into employment.

  8. Usability of geographic information -- factors identified from qualitative analysis of task-focused user interviews.

    Science.gov (United States)

    Harding, Jenny

    2013-11-01

    Understanding user needs for geographic information and the factors which influence the usability of such information in diverse user contexts is an essential part of user centred development of information products. There is relatively little existing research focused on the design and usability of information products in general. This paper presents a research approach based on semi structured interviews with people working with geographic information on a day to day basis, to establish a reference base of qualitative data on user needs for geographic information with respect to context of use. From this reference data nine key categories of geographic information usability are identified and discussed in the context of limited existing research concerned with geographic information usability. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  9. Identifying Risk Factors for Elder Falls in Geriatric Rehabilitation in Israel.

    Science.gov (United States)

    Ben Natan, Merav; Heyman, Neomi; Ben Israel, Joshua

    2016-01-01

    To identify risk factors for elder falls in a geriatric rehabilitation center in Israel. Retrospective chart review study. Four hundred and twelve medical records of inpatients in geriatric rehabilitation were retrospectively analyzed to compare between elders who sustained falls and those who did not. Of elders hospitalized during this year, 14% sustained falls. Fallers included a high proportion of males, with little comorbidity, not obese, and cardiovascular patients. Falls occurred frequently during patients' first week at the facility, mostly during the daytime. The falls occurred frequently in patients' rooms, and a common scenario was a fall during transition. The research findings single out patients who are allegedly at a lower risk of falls than more complex patients. Caregivers in geriatric rehabilitation settings should pay attention to patients who are allegedly at a lower risk of falls than more complex patients, and to cardiovascular patients in particular. © 2014 Association of Rehabilitation Nurses.

  10. Allele frequencies of variants in ultra conserved elements identify selective pressure on transcription factor binding.

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    Toomas Silla

    Full Text Available Ultra-conserved genes or elements (UCGs/UCEs in the human genome are extreme examples of conservation. We characterized natural variations in 2884 UCEs and UCGs in two distinct populations; Singaporean Chinese (n = 280 and Italian (n = 501 by using a pooled sample, targeted capture, sequencing approach. We identify, with high confidence, in these regions the abundance of rare SNVs (MAF5% are more often found in relatively less-conserved nucleotides within UCEs, compared to rare variants. Moreover, prevalent variants are less likely to overlap transcription factor binding site. Using SNPfold we found no significant influence of RNA secondary structure on UCE conservation. All together, these results suggest UCEs are not under selective pressure as a stretch of DNA but are under differential evolutionary pressure on the single nucleotide level.

  11. Allele frequencies of variants in ultra conserved elements identify selective pressure on transcription factor binding.

    Science.gov (United States)

    Silla, Toomas; Kepp, Katrin; Tai, E Shyong; Goh, Liang; Davila, Sonia; Catela Ivkovic, Tina; Calin, George A; Voorhoeve, P Mathijs

    2014-01-01

    Ultra-conserved genes or elements (UCGs/UCEs) in the human genome are extreme examples of conservation. We characterized natural variations in 2884 UCEs and UCGs in two distinct populations; Singaporean Chinese (n = 280) and Italian (n = 501) by using a pooled sample, targeted capture, sequencing approach. We identify, with high confidence, in these regions the abundance of rare SNVs (MAFpower for association studies. By combining our data with 1000 Genome Project data, we show in three independent datasets that prevalent UCE variants (MAF>5%) are more often found in relatively less-conserved nucleotides within UCEs, compared to rare variants. Moreover, prevalent variants are less likely to overlap transcription factor binding site. Using SNPfold we found no significant influence of RNA secondary structure on UCE conservation. All together, these results suggest UCEs are not under selective pressure as a stretch of DNA but are under differential evolutionary pressure on the single nucleotide level.

  12. Developing Predictive Models for Algal Bloom Occurrence and Identifying Factors Controlling their Occurrence in the Charlotte County and Surroundings

    Science.gov (United States)

    Karki, S.; Sultan, M.; Elkadiri, R.; Chouinard, K.

    2017-12-01

    Numerous occurrences of harmful algal blooms (Karenia Brevis) were reported from Southwest Florida along the coast of Charlotte County, Florida. We are developing data-driven (remote sensing, field, and meteorological data) models to accomplish the following: (1) identify the factors controlling bloom development, (2) forecast bloom occurrences, and (3) make recommendations for monitoring variables that are found to be most indicative of algal bloom occurrences and for identifying optimum locations for monitoring stations. To accomplish these three tasks we completed/are working on the following steps. Firstly, we developed an automatic system for downloading and processing of ocean color data acquired through MODIS Terra and MODIS Aqua products using SeaDAS ocean color processing software. Examples of extracted variables include: chlorophyll a (OC3M), chlorophyll a Generalized Inherent Optical Property (GIOP), chlorophyll a Garver-Siegel- Maritorena (GSM), sea surface temperature (SST), Secchi disk depth, euphotic depth, turbidity index, wind direction and speed, colored dissolved organic material (CDOM). Secondly we are developing a GIS database and a web-based GIS to host the generated remote sensing-based products in addition to relevant meteorological and field data. Examples of the meteorological and field inputs include: precipitation amount and rates, concentrations of nitrogen, phosphorous, fecal coliform and Dissolved Oxygen (DO). Thirdly, we are constructing and validating a multivariate regression model and an artificial neural network model to simulate past algal bloom occurrences using the compiled archival remote sensing, meteorological, and field data. The validated model will then be used to predict the timing and location of algal bloom occurrences. The developed system, upon completion, could enhance the decision making process, improve the citizen's quality of life, and strengthen the local economy.

  13. Readily Identifiable Risk Factors of Nursing Home Residents' Oral Hygiene: Dementia, Hospice, and Length of Stay.

    Science.gov (United States)

    Zimmerman, Sheryl; Austin, Sophie; Cohen, Lauren; Reed, David; Poole, Patricia; Ward, Kimberly; Sloane, Philip D

    2017-11-01

    The poor oral hygiene of nursing home (NH) residents is a matter of increasing concern, especially because of its relationship with pneumonia and other health events. Because details and related risk factors in this area are scant and providers need to be able to easily identify those residents at most risk, this study comprehensively examined the plaque, gingival, and denture status of NH residents, as well as readily available correlates of those indicators of oral hygiene, including items from the Minimum Data Set (MDS). Oral hygiene assessment and chart abstract conducted on a cross-section of NH residents. NHs in North Carolina (N = 14). NH residents (N = 506). Descriptive data from the MDS and assessments using three standardized measures: the Plaque Index for Long-Term Care (PI-LTC), the Gingival Index for Long-Term Care (GI-LTC), and the Denture Plaque Index (DPI). Oral hygiene scores averaged 1.7 (of 3) for the PI-LTC, 1.5 (of 4) for the GI-LTC, and 2.2 (of 4) for the DPI. Factors most strongly associated with poor oral hygiene scores included having dementia, being on hospice care, and longer stay. MDS ratings of gingivitis differed significantly from oral hygiene assessments. The findings identify resident subgroups at especially high risk of poor oral health who can be targeted in quality improvement efforts related to oral hygiene; they also indicate need to improve the accuracy of how MDS items are completed. © 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.

  14. [Identifying transcription factors involved in Arabidopsis adventious shoot regeneration by RNA-Seq technology].

    Science.gov (United States)

    Wang, Xingchun; Chen, Zhao; Fan, Juan; He, Miaomiao; Han, Yuanhuai; Yang, Zhirong

    2015-04-01

    Transcriptional regulation is one of the major regulations in plant adventious shoot regeneration, but the exact mechanism remains unclear. In our study, the RNA-seq technology based on the IlluminaHiSeq 2000 sequencing platform was used to identify differentially expressed transcription factor (TF) encoding genes during callus formation stage and adventious shoot regeneration stage between wild type and adventious shoot formation defective mutant be1-3 and during the transition from dedifferentiation to redifferentiation stage in wildtype WS. Results show that 155 TFs were differentially expressed between be1-3 mutant and wild type during callus formation, of which 97 genes were up-regulated, and 58 genes were down-regulated; and that 68 genes were differentially expressed during redifferentiation stage, with 40 genes up-regulated and 28 genes down-regulated; whereas at the transition stage from dedifferentiation to redifferention in WS wild type explants, a total of 231 differentially expressed TF genes were identified, including 160 up-regualted genes and 71 down-regulated genes. Among these TF genes, the adventious shoot related transcription factor 1 (ART1) gene encoding a MYB-related (v-myb avian myeloblastosis viral oncogene homolog) TF, was up-regulated 3 217 folds, and was the highest up-regulated gene during be1-3 callus formation. Over expression of the ART1 gene caused defects in callus formation and shoot regeneration and inhibited seedling growth, indicating that the ART1 gene is a negative regulator of callus formation and shoot regeneration. This work not only enriches our knowledge about the transcriptional regulation mechanism of adventious shoot regeneration, but also provides valuable information on candidate TF genes associated with adventious shoot regeneration for future research.

  15. A model for genetic and epigenetic regulatory networks identifies rare pathways for transcription factor induced pluripotency

    Science.gov (United States)

    Artyomov, Maxim; Meissner, Alex; Chakraborty, Arup

    2010-03-01

    Most cells in an organism have the same DNA. Yet, different cell types express different proteins and carry out different functions. This is because of epigenetic differences; i.e., DNA in different cell types is packaged distinctly, making it hard to express certain genes while facilitating the expression of others. During development, upon receipt of appropriate cues, pluripotent embryonic stem cells differentiate into diverse cell types that make up the organism (e.g., a human). There has long been an effort to make this process go backward -- i.e., reprogram a differentiated cell (e.g., a skin cell) to pluripotent status. Recently, this has been achieved by transfecting certain transcription factors into differentiated cells. This method does not use embryonic material and promises the development of patient-specific regenerative medicine, but it is inefficient. The mechanisms that make reprogramming rare, or even possible, are poorly understood. We have developed the first computational model of transcription factor-induced reprogramming. Results obtained from the model are consistent with diverse observations, and identify the rare pathways that allow reprogramming to occur. If validated, our model could be further developed to design optimal strategies for reprogramming and shed light on basic questions in biology.

  16. Proteomic analysis of polyribosomes identifies splicing factors as potential regulators of translation during mitosis.

    Science.gov (United States)

    Aviner, Ranen; Hofmann, Sarah; Elman, Tamar; Shenoy, Anjana; Geiger, Tamar; Elkon, Ran; Ehrlich, Marcelo; Elroy-Stein, Orna

    2017-06-02

    Precise regulation of mRNA translation is critical for proper cell division, but little is known about the factors that mediate it. To identify mRNA-binding proteins that regulate translation during mitosis, we analyzed the composition of polysomes from interphase and mitotic cells using unbiased quantitative mass-spectrometry (LC-MS/MS). We found that mitotic polysomes are enriched with a subset of proteins involved in RNA processing, including alternative splicing and RNA export. To demonstrate that these may indeed be regulators of translation, we focused on heterogeneous nuclear ribonucleoprotein C (hnRNP C) as a test case and confirmed that it is recruited to elongating ribosomes during mitosis. Then, using a combination of pulsed SILAC, metabolic labeling and ribosome profiling, we showed that knockdown of hnRNP C affects both global and transcript-specific translation rates and found that hnRNP C is specifically important for translation of mRNAs that encode ribosomal proteins and translation factors. Taken together, our results demonstrate how proteomic analysis of polysomes can provide insight into translation regulation under various cellular conditions of interest and suggest that hnRNP C facilitates production of translation machinery components during mitosis to provide daughter cells with the ability to efficiently synthesize proteins as they enter G1 phase. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  17. Genome-wide RNAi Screening to Identify Host Factors That Modulate Oncolytic Virus Therapy.

    Science.gov (United States)

    Allan, Kristina J; Mahoney, Douglas J; Baird, Stephen D; Lefebvre, Charles A; Stojdl, David F

    2018-04-03

    High-throughput genome-wide RNAi (RNA interference) screening technology has been widely used for discovering host factors that impact virus replication. Here we present the application of this technology to uncovering host targets that specifically modulate the replication of Maraba virus, an oncolytic rhabdovirus, and vaccinia virus with the goal of enhancing therapy. While the protocol has been tested for use with oncolytic Maraba virus and oncolytic vaccinia virus, this approach is applicable to other oncolytic viruses and can also be utilized for identifying host targets that modulate virus replication in mammalian cells in general. This protocol describes the development and validation of an assay for high-throughput RNAi screening in mammalian cells, the key considerations and preparation steps important for conducting a primary high-throughput RNAi screen, and a step-by-step guide for conducting a primary high-throughput RNAi screen; in addition, it broadly outlines the methods for conducting secondary screen validation and tertiary validation studies. The benefit of high-throughput RNAi screening is that it allows one to catalogue, in an extensive and unbiased fashion, host factors that modulate any aspect of virus replication for which one can develop an in vitro assay such as infectivity, burst size, and cytotoxicity. It has the power to uncover biotherapeutic targets unforeseen based on current knowledge.

  18. Identifying Factors Associated with Risk Assessment Competencies of Public Health Emergency Responders.

    Science.gov (United States)

    Hao, Jiejing; Ren, Jiaojiao; Wu, Qunhong; Hao, Yanhua; Sun, Hong; Ning, Ning; Ding, Ding

    2017-06-04

    This study aimed to better understand the current situation of risk assessment and identify the factors associated with competence of emergency responders in public health risk assessment. The participants were selected by a multi-stage, stratified cluster sampling method in Heilongjiang Centers for Disease Control and Prevention (CDC). The questionnaires that measured their perceptions on risk assessment competences were administered through the face-to-face survey. A final sample of 1889 staff was obtained. Of this sample, 78.6% of respondents rated their own risk assessment competences as "relatively low", contrasting with 21.4% rated as "relatively high". Most of the respondents (62.7%) did not participate in any risk assessment work. Only 13.7% and 42.7% of respondents reported participating in risk assessment training and were familiar with risk assessment tools. There existed statistical significance between risk assessment-related characteristics of respondents and their self-rated competences scores. Financial support from the government and administrative attention were regarded as the important factors contributing to risk assessment competences of CDC responders. Higher attention should be given to risk assessment training and enhancing the availability of surveillance data. Continuous efforts should be made to remove the financial and technical obstacles to improve the competences of risk assessment for public health emergency responders.

  19. In Vivo Functional Selection Identifies Cardiotrophin-1 as a Cardiac Engraftment Factor for Mesenchymal Stromal Cells.

    Science.gov (United States)

    Bortolotti, Francesca; Ruozi, Giulia; Falcione, Antonella; Doimo, Sara; Dal Ferro, Matteo; Lesizza, Pierluigi; Zentilin, Lorena; Banks, Lawrence; Zacchigna, Serena; Giacca, Mauro

    2017-10-17

    Transplantation of cells into the infarcted heart has significant potential to improve myocardial recovery; however, low efficacy of cell engraftment still limits therapeutic benefit. Here, we describe a method for the unbiased, in vivo selection of cytokines that improve mesenchymal stromal cell engraftment into the heart both in normal conditions and after myocardial infarction. An arrayed library of 80 secreted factors, including most of the currently known interleukins and chemokines, were individually cloned into adeno-associated viral vectors. Pools from this library were then used for the batch transduction of bone marrow-derived mesenchymal stromal cells ex vivo, followed by intramyocardial cell administration in normal and infarcted mice. Three weeks after injection, vector genomes were recovered from the few persisting cells and identified by sequencing DNA barcodes uniquely labeling each of the tested cytokines. The most effective molecule identified by this competitive engraftment screening was cardiotrophin-1, a member of the interleukin-6 family. Intracardiac injection of mesenchymal stromal cells transiently preconditioned with cardiotrophin-1 preserved cardiac function and reduced infarct size, parallel to the persistence of the transplanted cells in the healing hearts for at least 2 months after injection. Engraftment of cardiotrophin-1-treated mesenchymal stromal cells was consequent to signal transducer and activator of transcription 3-mediated activation of the focal adhesion kinase and its associated focal adhesion complex and the consequent acquisition of adhesive properties by the cells. These results support the feasibility of selecting molecules in vivo for their functional properties with adeno-associated viral vector libraries and identify cardiotrophin-1 as a powerful cytokine promoting cell engraftment and thus improving cell therapy of the infarcted myocardium. © 2017 American Heart Association, Inc.

  20. The Usage of Association Rule Mining to Identify Influencing Factors on Deafness After Birth.

    Science.gov (United States)

    Shahraki, Azimeh Danesh; Safdari, Reza; Gahfarokhi, Hamid Habibi; Tahmasebian, Shahram

    2015-12-01

    Providing complete and high quality health care services has very important role to enable people to understand the factors related to personal and social health and to make decision regarding choice of suitable healthy behaviors in order to achieve healthy life. For this reason, demographic and clinical data of person are collecting, this huge volume of data can be known as a valuable resource for analyzing, exploring and discovering valuable information and communication. This study using forum rules techniques in the data mining has tried to identify the affecting factors on hearing loss after birth in Iran. The survey is kind of data oriented study. The population of the study is contained questionnaires in several provinces of the country. First, all data of questionnaire was implemented in the form of information table in Software SQL Server and followed by Data Entry using written software of C # .Net, then algorithm Association in SQL Server Data Tools software and Clementine software was implemented to determine the rules and hidden patterns in the gathered data. Two factors of number of deaf brothers and the degree of consanguinity of the parents have a significant impact on severity of deafness of individuals. Also, when the severity of hearing loss is greater than or equal to moderately severe hearing loss, people use hearing aids and Men are also less interested in the use of hearing aids. In fact, it can be said that in families with consanguineous marriage of parents that are from first degree (girl/boy cousins) and 2(nd) degree relatives (girl/boy cousins) and especially from first degree, the number of people with severe hearing loss or deafness are more and in the use of hearing aids, gender of the patient is more important than the severity of the hearing loss.

  1. Case control study to identify risk factors for acute hepatitis C virus infection in Egypt

    Directory of Open Access Journals (Sweden)

    Kandeel Amr M

    2012-11-01

    Full Text Available Abstract Background Identification of risk factors of acute hepatitis C virus (HCV infection in Egypt is crucial to develop appropriate prevention strategies. Methods We conducted a case–control study, June 2007-September 2008, to investigate risk factors for acute HCV infection in Egypt among 86 patients and 287 age and gender matched controls identified in two infectious disease hospitals in Cairo and Alexandria. Case-patients were defined as: any patient with symptoms of acute hepatitis; lab tested positive for HCV antibodies and negative for HBsAg, HBc IgM, HAV IgM; and 7-fold increase in the upper limit of transaminase levels. Controls were selected from patients’ visitors with negative viral hepatitis markers. Subjects were interviewed about previous exposures within six months, including community-acquired and health-care associated practices. Results Case-patients were more likely than controls to have received injection with a reused syringe (OR=23.1, CI 4.7-153, to have been in prison (OR=21.5, CI 2.5-479.6, to have received IV fluids in a hospital (OR=13.8, CI 5.3-37.2, to have been an IV drug user (OR=12.1, CI 4.6-33.1, to have had minimal surgical procedures (OR=9.7, CI 4.2-22.4, to have received IV fluid as an outpatient (OR=8, CI 4–16.2, or to have been admitted to hospital (OR=7.9, CI 4.2-15 within the last 6 months. Multivariate analysis indicated that unsafe health facility practices are the main risk factors associated with transmission of HCV infection in Egypt. Conclusion In Egypt, focusing acute HCV prevention measures on health-care settings would have a beneficial impact.

  2. Hypersensitivity Reactions to Oxaliplatin: Identifying the Risk Factors and Judging the Efficacy of a Desensitization Protocol.

    Science.gov (United States)

    Okayama, Tetsuya; Ishikawa, Takeshi; Sugatani, Kazuko; Yoshida, Naohisa; Kokura, Satoshi; Matsuda, Kiyomi; Tsukamoto, Shigeru; Ihara, Norihiko; Kuriu, Yoshiaki; Nakanishi, Masayoshi; Nakamura, Terukazu; Kamada, Kazuhiro; Katada, Kazuhiro; Uchiyama, Kazuhiko; Takagi, Tomohisa; Handa, Osamu; Konishi, Hideyuki; Yagi, Nobuaki; Naito, Yuji; Otsuji, Eigo; Hosoi, Hajime; Miki, Tsuneharu; Itoh, Yoshito

    2015-06-01

    We examined the clinical data of patients treated with oxaliplatin to determine the risk factors of oxaliplatin-related hypersensitivity reaction (HSR). In addition, we evaluated the efficacy of rechallenging patients with HSRs with oxaliplatin using prophylactic agents or desensitization procedures. This study consisted of 162 patients with colorectal cancer (88 men and 74 women) who were treated consecutively at the outpatient chemotherapy department at University Hospital, Kyoto Prefectural University of Medicine. Patients underwent chemotherapy, including oxaliplatin, between March 2006 and June 2012. We analyzed the patients' clinical backgrounds (eg, age, sex, performance status, disease stage, and allergic history) to uncover any connections to the development of HSR to oxaliplatin. In addition, we rechallenged 10 patients who had oxaliplatin-related HSR using prophylactic agents or desensitization procedures. Of 162 patients, 28 (17.2%) developed oxaliplatin-related HSRs (16, 2, 9 and 1 patient had grade 1, 2, 3, and 4 HSRs, respectively). The total cumulative dose of oxaliplatin at the onset of the HSR was 301 to 1126 mg/m(2) (median, 582 mg/m(2)), and the first reactions developed in these patients after 5 to 17 infusions of oxaliplatin (median, 8 infusions). Logistic regression analysis indicated that sex (male: odds ratio = 3.624; 95% CI, 1.181-11.122; P = 0.024) and eosinophil count in peripheral blood (odds ratio = 35.118; 95% CI, 1.058-1166.007; P = 0.046) were independent variables for oxaliplatin-related HSRs. Rechallenging patients with prophylactic agents was successful in 2 (28.6%) of 7 patients who successfully completed their treatment. On the other hand, all 3 patients rechallenged with oxaliplatin using a desensitization protocol successfully completed their treatment without new HSRs. In this retrospective study, we observed that being male and having higher counts of peripheral eosinophil could be predictors for HSR to oxaliplatin. In

  3. Multicollinearity and Regression Analysis

    Science.gov (United States)

    Daoud, Jamal I.

    2017-12-01

    In regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.

  4. Applying psychological theories to evidence-based clinical practice: identifying factors predictive of placing preventive fissure sealants.

    Science.gov (United States)

    Bonetti, Debbie; Johnston, Marie; Clarkson, Jan E; Grimshaw, Jeremy; Pitts, Nigel B; Eccles, Martin; Steen, Nick; Thomas, Ruth; Maclennan, Graeme; Glidewell, Liz; Walker, Anne

    2010-04-08

    Psychological models are used to understand and predict behaviour in a wide range of settings, but have not been consistently applied to health professional behaviours, and the contribution of differing theories is not clear. This study explored the usefulness of a range of models to predict an evidence-based behaviour -- the placing of fissure sealants. Measures were collected by postal questionnaire from a random sample of general dental practitioners (GDPs) in Scotland. Outcomes were behavioural simulation (scenario decision-making), and behavioural intention. Predictor variables were from the Theory of Planned Behaviour (TPB), Social Cognitive Theory (SCT), Common Sense Self-regulation Model (CS-SRM), Operant Learning Theory (OLT), Implementation Intention (II), Stage Model, and knowledge (a non-theoretical construct). Multiple regression analysis was used to examine the predictive value of each theoretical model individually. Significant constructs from all theories were then entered into a 'cross theory' stepwise regression analysis to investigate their combined predictive value. Behavioural simulation - theory level variance explained was: TPB 31%; SCT 29%; II 7%; OLT 30%. Neither CS-SRM nor stage explained significant variance. In the cross theory analysis, habit (OLT), timeline acute (CS-SRM), and outcome expectancy (SCT) entered the equation, together explaining 38% of the variance. Behavioural intention - theory level variance explained was: TPB 30%; SCT 24%; OLT 58%, CS-SRM 27%. GDPs in the action stage had significantly higher intention to place fissure sealants. In the cross theory analysis, habit (OLT) and attitude (TPB) entered the equation, together explaining 68% of the variance in intention. The study provides evidence that psychological models can be useful in understanding and predicting clinical behaviour. Taking a theory-based approach enables the creation of a replicable methodology for identifying factors that may predict clinical behaviour

  5. Applying psychological theories to evidence-based clinical practice: identifying factors predictive of placing preventive fissure sealants

    Directory of Open Access Journals (Sweden)

    Maclennan Graeme

    2010-04-01

    identifying factors that may predict clinical behaviour and so provide possible targets for knowledge translation interventions. Results suggest that more evidence-based behaviour may be achieved by influencing beliefs about the positive outcomes of placing fissure sealants and building a habit of placing them as part of patient management. However a number of conceptual and methodological challenges remain.

  6. On applying safety archetypes to the Fukushima accident to identify nonlinear influencing factors

    Energy Technology Data Exchange (ETDEWEB)

    Sousa, A.L., E-mail: alsousa@cnen.gov.br [Comissao Nacional de Energia Nuclear (CNEN), Rio de Janeiro, RJ (Brazil); Ribeiro, A.C.O., E-mail: antonio.ribeiro@bayer.com [Bayer Crop Science Brasil S.A., Belford Roxo, RJ (Brazil); Duarte, J.P., E-mail: julianapduarte@poli.ufrj.br [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Escola Politecnica. Departamento de Engenharia Nuclear; Frutuoso e Melo, P.F., E-mail: frutuoso@nuclear.ufrj.br [Coordenacao dos Programas de Pos-Graduacao em Engenharia (COOPE/UFRJ), RJ (Brazil). Programa de Engenharia Nuclear

    2013-07-01

    Nuclear power plants are typically characterized as high reliable organizations. In other words, they are organizations defined as relatively error free over a long period of time. Another relevant characteristic of the nuclear industry is that safety efforts are credited to design. However, major accidents, like the Fukushima accident, have shown that new tools are needed to identify latent deficiencies and help improve their safety level. Safety archetypes proposed elsewhere (e. g., safety issues stalled in the face of technological advances and eroding safety) consonant with International Atomic Energy Agency (IAEA) efforts are used to examine different aspects of accidents in a systemic perspective of the interaction between individuals, technology and organizational factors. Safety archetypes can help consider nonlinear interactions. Effects are rarely proportional to causes and what happens locally in a system (near the current operating point) often does not apply to distant regions (other system states), so that one has to consider the so-called nonlinear interactions. This is the case, for instance, with human probability failure estimates and safety level identification. In this paper, we discuss the Fukushima accident in order to show how archetypes can highlight nonlinear interactions of factors that influenced it and how to maintain safety levels in order to prevent other accidents. The initial evaluation of the set of archetypes suggested in the literature showed that at least four of them are applicable to the Fukushima accident, as is inferred from official reports on the accident. These are: complacency (that is, the effects of complacency on safety), decreased safety awareness, fixing on symptoms and not the real causes and eroding safety. (author)

  7. Identifying factors to improve oral cancer screening uptake: a qualitative study.

    Directory of Open Access Journals (Sweden)

    Fatemeh Vida Zohoori

    Full Text Available To engage with high risk groups to identify knowledge and awareness of oral cancer signs and symptoms and the factors likely to contribute to improved screening uptake.Focus group discussions were undertaken with 18 males; 40+ years of age; smokers and/or drinkers (15+ cigarettes per day and/or 15+ units of alcohol per week, irregular dental attenders living in economically deprived areas of Teesside.There was a striking reported lack of knowledge and awareness of oral cancer and its signs and symptoms among the participants. When oral/mouth cancer leaflets produced by Cancer Research UK were presented to the participants, they claimed that they would seek help on noticing such a condition. There was a preference to seek help from their general practitioner rather than their dentist due to perceptions that a dentist is 'inaccessible' on a physical and psychological level, costly, a 'tooth specialist' not a 'mouth specialist', and also not able to prescribe medication and make referrals to specialists. Interestingly, none of the 18 participants who were offered a free oral cancer examination at a dental practice took up this offer.The uptake of oral cancer screening may be improved by increasing knowledge of the existence and signs and symptoms of oral cancer. Other factors that may increase uptake are increased awareness of the role of dentists in diagnosing oral cancer, promotion of oral cancer screening by health professionals during routine health checks, and the use of a "health" screening setting as opposed to a "dental" setting for such checks.

  8. Using focus groups to identify factors affecting healthy weight maintenance in college men.

    Science.gov (United States)

    Walsh, Jennifer R; White, Adrienne A; Greaney, Mary L

    2009-06-01

    Healthful eating and physical activity are important for healthy weight maintenance. The hypothesis for this study was that college-aged men would perceive factors affecting eating and physical activity as both contributing to and inhibiting healthy weight maintenance. The overall objective was to explore how men view weight maintenance in the context of these aspects. Subjects (n = 47, mean age = 20.3 +/- 1.7 years) completed an online survey, including the 51-item Three-Factor Eating Questionnaire, and participated in 1 of 6 focus groups. Three face-to-face and 3 online synchronous groups were conducted using a 15-question discussion guide to identify weight maintenance issues around eating, physical activity, and body perceptions. Weight satisfaction decreased with increase in both dietary restraint and disinhibition. Number of attempts to lose weight was positively associated with BMI (r [44] = .465, P = .01) and dietary restraint (r [44] = .515, P = .01). Findings from both focus group formats were similar. Motivators (sports performance/fitness, self-esteem, attractiveness, long-term health) were similar for eating healthfully and being physically active; however, more motivators to be physically active than to eat healthfully emerged. Enablers for eating healthfully included liking the taste, availability of healthful foods, using food rules to guide intake, having a habit of healthful eating, and internal drive/will. Barriers to healthful eating included fat in dairy foods, fruit and vegetable taste, and quick spoilage. Barriers to being physically active included lack of time/time management, obligations, being lazy, and girlfriends. Results may be used to inform future obesity prevention interventions.

  9. On applying safety archetypes to the Fukushima accident to identify nonlinear influencing factors

    International Nuclear Information System (INIS)

    Sousa, A.L.; Ribeiro, A.C.O.; Duarte, J.P.; Frutuoso e Melo, P.F.

    2013-01-01

    Nuclear power plants are typically characterized as high reliable organizations. In other words, they are organizations defined as relatively error free over a long period of time. Another relevant characteristic of the nuclear industry is that safety efforts are credited to design. However, major accidents, like the Fukushima accident, have shown that new tools are needed to identify latent deficiencies and help improve their safety level. Safety archetypes proposed elsewhere (e. g., safety issues stalled in the face of technological advances and eroding safety) consonant with International Atomic Energy Agency (IAEA) efforts are used to examine different aspects of accidents in a systemic perspective of the interaction between individuals, technology and organizational factors. Safety archetypes can help consider nonlinear interactions. Effects are rarely proportional to causes and what happens locally in a system (near the current operating point) often does not apply to distant regions (other system states), so that one has to consider the so-called nonlinear interactions. This is the case, for instance, with human probability failure estimates and safety level identification. In this paper, we discuss the Fukushima accident in order to show how archetypes can highlight nonlinear interactions of factors that influenced it and how to maintain safety levels in order to prevent other accidents. The initial evaluation of the set of archetypes suggested in the literature showed that at least four of them are applicable to the Fukushima accident, as is inferred from official reports on the accident. These are: complacency (that is, the effects of complacency on safety), decreased safety awareness, fixing on symptoms and not the real causes and eroding safety. (author)

  10. Selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays and impacts of using incorrect weighting factors on curve stability, data quality, and assay performance.

    Science.gov (United States)

    Gu, Huidong; Liu, Guowen; Wang, Jian; Aubry, Anne-Françoise; Arnold, Mark E

    2014-09-16

    A simple procedure for selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays is reported. The correct weighting factor is determined by the relationship between the standard deviation of instrument responses (σ) and the concentrations (x). The weighting factor of 1, 1/x, or 1/x(2) should be selected if, over the entire concentration range, σ is a constant, σ(2) is proportional to x, or σ is proportional to x, respectively. For the first time, we demonstrated with detailed scientific reasoning, solid historical data, and convincing justification that 1/x(2) should always be used as the weighting factor for all bioanalytical LC-MS/MS assays. The impacts of using incorrect weighting factors on curve stability, data quality, and assay performance were thoroughly investigated. It was found that the most stable curve could be obtained when the correct weighting factor was used, whereas other curves using incorrect weighting factors were unstable. It was also found that there was a very insignificant impact on the concentrations reported with calibration curves using incorrect weighting factors as the concentrations were always reported with the passing curves which actually overlapped with or were very close to the curves using the correct weighting factor. However, the use of incorrect weighting factors did impact the assay performance significantly. Finally, the difference between the weighting factors of 1/x(2) and 1/y(2) was discussed. All of the findings can be generalized and applied into other quantitative analysis techniques using calibration curves with weighted least-squares regression algorithm.

  11. Identifying the Risk Factors for Typhoid Fever among the Residents of Rural Islamabad

    International Nuclear Information System (INIS)

    Javed, N.; Bashir, F.; Abbasi, S.; Tahir, M.

    2017-01-01

    Background: During August 2015, unusually high typhoid fever cases were reported from rural Islamabad at Federal General Hospital (FGH), Islamabad. Objectives: To determine the risk factors for typhoid fever outbreak and recommend preventive measures. Study design, settings and duration: Outbreak investigation study conducted in Union Councils 19 and 22 of rural Islamabad in the catchment area for Federal General Hospital, from 7 th July-30 th August 2015. Subjects and Methods: A questionnaire was used to identify risk factors of typhoid fever. A case was defined as any resident of the rural Islamabad within the mauza Chatta Bakhtawar and Terlai Kalan presenting with high grade fever (>101 F) with one of the following signs/symptoms; headache, abdominal pain and vomiting with positive typhidot test from 7 th July-30 th August 2015. Two age and sex matched controls for each case was selected from the neighborhood. Epi Info 7 was used for analysis. Results: Total of 50 cases and 100 controls were enrolled. Among cases 30 (61 percent) were females and 20 (39 percent) males with M;F ratio of 1:1.5. Mean age was 23.0 years (9.9 +- SD). The most affected age group was 15-25 years (AR 0.19 percent, n=21). Only one case died (CFR 2percent). Use of untreated public water after rains (OR 3.7 CI 1.6-9.7 p< 0.0002), reconstruction areas and bursting/leaking of water pipes (OR 4.017 CI 1.6-9.7 p < 0.001) and presence of confirmed typhoid cases at home/close contacts (OR 5.7 CI 2.019-16.18 p < 0.0003) were the significant risk factors found associated with the disease. Whereas using well/private bore (OR 0.29 CI 0.329-0.653 p < 0.001) and hand washing practices (OR 0.7 CI 0.297-1.9 < 0.5) had a protective effect. Multivariate analysis showed that use of untreated public water (OR: 3.34, CI: 1.52-7.29, p < 0.002), bursting/leaking pipes (OR 2.86, CI 0.96-8.48, p < 0.05) were significantly associated with typhoid disease. Conclusion: Contamination of drinking water with sewage

  12. To identify the factors affecting the risk of recurrent febrile seizures in saudi children

    International Nuclear Information System (INIS)

    Jamal, M.M.; Ahmed, W.

    2015-01-01

    Objective: To identify the risk factors of recurrent febrile seizures (FS) in Saudi children in a Northern Province of Hail in Saudi Arabia. Study Design: Descriptive prospective study. Place and Duration of Study: Pediatric department, King Khalid Hospital Hail, Kingdom of Saudi Arabia from 01 October 2010 to 30 September 2011. Patients and Methods: A total of 132 children (age ranges from 03 months to 60 months) were included in the study, while they were admitted with the diagnosis of FS during the study period, in the Pediatric department of the King Khalid University Hospital, Hail. A predesigned study proforma was utilized for data collection. All the children included in the study were followed for a period of 01 year after discharge from the pediatric ward for any recurrence of FS. Results: During the study period 132 children were admitted for FS, the mean age of children in our sample was 16 months. There was a preponderance of male children. Among the causes of fever, mostly 63(47.73%) had symptoms of viral prodrome. Recurrent febrile seizure was found in 46 (34.85%) children. There was a statistically significant association between low temperature at onset of seizure and recurrent FS in 65.22% cases p-value= 0.001). Similarly, the association of duration of fever (= 6 hour) prior to onset of FS and recurrence was found to be significant in 56.52% (p-value= 0.001). Moreover it was found that lower age <12 months at onset of first FS and complex FS had a statistically significant association with its recurrence in 65.22% and 69.57% cases respectively p-value= 0.01 and 0.001). Non significant factors were sex and family history. Conclusion: FS is a common paediatric problem predominantly seen in males. Almost one third of these children are at risk for recurrence in later dates. The risk factors for these recurrences are modest rise in body temperature at the onset of seizure, younger age at presentation, onset of seizure within 6 hours of fever and

  13. A cross-sectional study of 329 farms in England to identify risk factors for ovine clinical mastitis.

    Science.gov (United States)

    Cooper, S; Huntley, S J; Crump, R; Lovatt, F; Green, L E

    2016-03-01

    The aims of this study were to estimate the incidence rate of clinical mastitis (IRCM) and identify risk factors for clinical mastitis in suckler ewes to generate hypotheses for future study. A postal questionnaire was sent to 999 randomly selected English sheep farmers in 2010 to gather data on farmer reported IRCM and flock management practices for the calendar year 2009, of which 329 provided usable information. The mean IRCM per flock was 1.2/100 ewes/year (CI:1.10:1.35). The IRCM was 2.0, 0.9 and 1.3/100 ewes/year for flocks that lambed indoors, outdoors and a combination of both, respectively. Farmers ran a variety of managements before, during and after lambing that were not comparable within one model, therefore six mixed effects over-dispersed Poisson regression models were developed. Factors significantly associated with increased IRCM were increasing percentage of the flock with poor udder conformation, increasing mean number of lambs reared/ewe and when some or all ewes lambed in barns compared with outdoors (Model 1). For ewes housed in barns before lambing (Model 2), concrete, earth and other materials were associated with an increase in IRCM compared with hardcore floors (an aggregate of broken bricks and stones). For ewes in barns during lambing (Model 3), an increase in IRCM was associated with concrete compared with hardcore flooring and where bedding was stored covered outdoors or in a building compared with bedding stored outdoors uncovered. For ewes in barns after lambing (Model 4), increased IRCM was associated with earth compared with hardcore floors, and when fresh bedding was added once per week compared with at a frequency of ≤2 days or twice/week. The IRCM was lower for flocks where some or all ewes remained in the same fields before, during and after lambing compared with flocks that did not (Model 5). Where ewes and lambs were turned outdoors after lambing (Model 6), the IRCM increased as the age of the oldest lambs at turnout

  14. Factors identified with higher levels of career satisfaction of physicians in Andalusia, Spain

    Directory of Open Access Journals (Sweden)

    Juan Nicolás Peña-Sánchez

    2014-09-01

    Full Text Available The satisfaction of physicians is a world-wide issue linked with the quality of health services; their satisfaction needs to be studied from a multi-dimensional perspective, considering lower- and higher-order needs. The objectives of this study were to: i measure the career satisfaction of physicians; ii identify differences in the dimensions of career satisfaction; and iii test factors that affect higher- and lower-order needs of satisfaction among physicians working in Andalusian hospitals (Spain. Forty-one percent of 299 eligible physicians participated in a study conducted in six selected hospitals. Physicians reported higher professional, inherent, and performance satisfaction than personal satisfaction. Foreign physicians reported higher levels of personal and performance satisfaction than local physicians, and those who received non-monetary incentives had higher professional and performance satisfaction. In conclusion, physicians in the selected Andalusian hospitals reported low levels of personal satisfaction. Non-monetary incentives were more relevant to influence their career satisfaction. Further investigations are recommended to study differences in the career satisfaction between foreign and local physicians.

  15. Conceptual and Operational Considerations in Identifying Socioenvironmental Factors Associated with Disability among Community-Dwelling Adults

    Directory of Open Access Journals (Sweden)

    Mathieu Philibert

    2015-04-01

    Full Text Available Disability is conceived as a person–context interaction. Physical and social environments are identified as intervention targets for improving social participation and independence. In comparison to the body of research on place and health, relatively few reports have been published on residential environments and disability in the health sciences literature. We reviewed studies evaluating the socioenvironmental correlates of disability. Searches were conducted in Medline, Embase and CINAHL databases for peer-reviewed articles published between 1997 and 2014. We found many environmental factors to be associated with disability, particularly area-level socioeconomic status and rurality. However, diversity in conceptual and methodological approaches to such research yields a limited basis for comparing studies. Conceptual inconsistencies in operational measures of disability and conceptual disagreement between studies potentially affect understanding of socioenvironmental influences. Similarly, greater precision in socioenvironmental measures and in study designs are likely to improve inference. Consistent and generalisable support for socioenvironmental influences on disability in the general adult population is scarce.

  16. An All-Recombinant Protein-Based Culture System Specifically Identifies Hematopoietic Stem Cell Maintenance Factors

    Directory of Open Access Journals (Sweden)

    Aki Ieyasu

    2017-03-01

    Full Text Available Hematopoietic stem cells (HSCs are considered one of the most promising therapeutic targets for the treatment of various blood disorders. However, due to difficulties in establishing stable maintenance and expansion of HSCs in vitro, their insufficient supply is a major constraint to transplantation studies. To solve these problems we have developed a fully defined, all-recombinant protein-based culture system. Through this system, we have identified hemopexin (HPX and interleukin-1α as responsible for HSC maintenance in vitro. Subsequent molecular analysis revealed that HPX reduces intracellular reactive oxygen species levels within cultured HSCs. Furthermore, bone marrow immunostaining and 3D immunohistochemistry revealed that HPX is expressed in non-myelinating Schwann cells, known HSC niche constituents. These results highlight the utility of this fully defined all-recombinant protein-based culture system for reproducible in vitro HSC culture and its potential to contribute to the identification of factors responsible for in vitro maintenance, expansion, and differentiation of stem cell populations.

  17. Using sensitivity analysis to identify key factors for the propagation of a plant epidemic.

    Science.gov (United States)

    Rimbaud, Loup; Bruchou, Claude; Dallot, Sylvie; Pleydell, David R J; Jacquot, Emmanuel; Soubeyrand, Samuel; Thébaud, Gaël

    2018-01-01

    Identifying the key factors underlying the spread of a disease is an essential but challenging prerequisite to design management strategies. To tackle this issue, we propose an approach based on sensitivity analyses of a spatiotemporal stochastic model simulating the spread of a plant epidemic. This work is motivated by the spread of sharka, caused by plum pox virus , in a real landscape. We first carried out a broad-range sensitivity analysis, ignoring any prior information on six epidemiological parameters, to assess their intrinsic influence on model behaviour. A second analysis benefited from the available knowledge on sharka epidemiology and was thus restricted to more realistic values. The broad-range analysis revealed that the mean duration of the latent period is the most influential parameter of the model, whereas the sharka-specific analysis uncovered the strong impact of the connectivity of the first infected orchard. In addition to demonstrating the interest of sensitivity analyses for a stochastic model, this study highlights the impact of variation ranges of target parameters on the outcome of a sensitivity analysis. With regard to sharka management, our results suggest that sharka surveillance may benefit from paying closer attention to highly connected patches whose infection could trigger serious epidemics.

  18. Preparedness for physiotherapy in private practice: Novices identify key factors in an interpretive description study.

    Science.gov (United States)

    Atkinson, Robyn; McElroy, Theresa

    2016-04-01

    Physiotherapists in Australia deliver services to a diverse range of clients, across many settings, however little research exists examining graduate preparedness for practice, even in the populous field of private practice. To explore novice physiotherapist perspectives on preparedness for work in private practice. The qualitative approach of interpretive description was used to guide in-depth interviews with 8 novice physiotherapists from 3 universities working in 5 private practices in Melbourne. All interviews were digitally recorded, transcribed verbatim and analyzed thematically. Four main themes influencing graduate preparedness for work in private practice were identified: 1) non-curricular experiences (e.g. sports training) 2) elective curricular: practicum experiences; 3) curricular: attainment of skills specific to private practice; and 4) the private practice setting: supportive colleagues. This combination of non-curricular, curricular, and practice setting factors offered the necessary scaffolding for the graduates to report feeling prepared for work in private practice. Non-curricular activities, radiological instruction, clinical placements, building supportive colleague relations and professional development in private practice are recommended as potential means of building preparedness in novice therapists. Findings have implications for physiotherapy students, educators and private practice clinics looking to recruit new graduates. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Identifying the factors governing attitude towards the e-Agriservice among dairy farmers in Maharashtra, India

    Directory of Open Access Journals (Sweden)

    Sagar Kisan Wadkar

    2016-01-01

    Full Text Available Information and communication technology (ICT projects have a great potential to revolutionise the information delivery system by bridging the gap between farmers and extension personnel. aAQUA (Almost All Questions Answered portal was launched by the Developmental Informatics Laboratory (DIL at Indian Institute of Technology (IIT Mumbai, Maharashtra, India in 2003 as an information providing system to deliver technology options and tailored information for the problems and queries raised by Indian dairy farmers. To measure the effectiveness of this service the attitudinal dimensions of the users of aAQUA e-Agriservice were investigated using a 22 item scale. A simple random sampling technique was used to select 120 dairy farmers from which data were collected and subjected to factor analysis to identify the underlying constructs in this research. From the attitude items, four components were extracted and named as the pessimistic, utility, technical and efficacy perspective, which influenced the development of varied level of attitudinal inclination towards the e-Agriservice. These components explained 64.40 per cent of variation in the attitude of the users towards the aAQUA e-Agriservice. This study provides a framework for technically efficient service provision that might help to reduce the pessimistic attitude of target population to adopt e-Agriservice in their farming system. The results should also be helpful for researchers, academics, ICT based service providers and policy makers to consider these perspectives while planning and implementing ICT projects.

  20. Pharmacy patronage: identifying key factors in the decision making process using the determinant attribute approach.

    Science.gov (United States)

    Franic, Duska M; Haddock, Sarah M; Tucker, Leslie Tootle; Wooten, Nathan

    2008-01-01

    To use the determinant attribute approach, a research method commonly used in marketing to identify the wants of various consumer groups, to evaluate consumer pharmacy choice when having a prescription order filled in different pharmacy settings. Cross sectional. Community independent, grocery store, community chain, and discount store pharmacies in Georgia between April 2005 and April 2006. Convenience sample of adult pharmacy consumers (n = 175). Survey measuring consumer preferences on 26 attributes encompassing general pharmacy site features (16 items), pharmacist characteristics (5 items), and pharmacy staff characteristics (5 items). 26 potential determinant attributes for pharmacy selection. 175 consumers were surveyed at community independent (n = 81), grocery store (n = 44), community chain (n = 27), or discount store (n = 23) pharmacy settings. The attributes of pharmacists and staff at all four pharmacy settings were shown to affect pharmacy patronage motives, although consumers frequenting non-community independent pharmacies were also motivated by secondary convenience factors, e.g., hours of operation, and prescription coverage. Most consumers do not perceive pharmacies as merely prescription-distribution centers that vary only by convenience. Prescriptions are not just another economic good. Pharmacy personnel influence pharmacy selection; therefore, optimal staff selection and training is likely the greatest asset and most important investment for ensuring pharmacy success.

  1. Experimental infections with Mycoplasma agalactiae identify key factors involved in host-colonization.

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    Eric Baranowski

    Full Text Available Mechanisms underlying pathogenic processes in mycoplasma infections are poorly understood, mainly because of limited sequence similarities with classical, bacterial virulence factors. Recently, large-scale transposon mutagenesis in the ruminant pathogen Mycoplasma agalactiae identified the NIF locus, including nifS and nifU, as essential for mycoplasma growth in cell culture, while dispensable in axenic media. To evaluate the importance of this locus in vivo, the infectivity of two knock-out mutants was tested upon experimental infection in the natural host. In this model, the parental PG2 strain was able to establish a systemic infection in lactating ewes, colonizing various body sites such as lymph nodes and the mammary gland, even when inoculated at low doses. In these PG2-infected ewes, we observed over the course of infection (i the development of a specific antibody response and (ii dynamic changes in expression of M. agalactiae surface variable proteins (Vpma, with multiple Vpma profiles co-existing in the same animal. In contrast and despite a sensitive model, none of the knock-out mutants were able to survive and colonize the host. The extreme avirulent phenotype of the two mutants was further supported by the absence of an IgG response in inoculated animals. The exact role of the NIF locus remains to be elucidated but these data demonstrate that it plays a key role in the infectious process of M. agalactiae and most likely of other pathogenic mycoplasma species as many carry closely related homologs.

  2. Identifying Risk Factors of Boot Procurement: A Case Study of Stadium Australia

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    Marcus Jefferies

    2012-11-01

    Full Text Available Private sector input into the procurement of public works and services is continuing to increase. This has partly arisen out of a requirement for infrastructure development to be undertaken at a rate that maintains and allows growth. This has become a major challange for the construction industry that cannot be met by government alone. The emergence of Build-Own-Operate-Transfer (BOOT schemes as a response to this challange provides a means for developing the infrastructure of a country without directly impacting on the governments budgetary constraints. The concepts of BOOT are without doubt extremely complex arrangements, which bring to the construction sector risks not experienced previously. Many of the infrastructure partnerships between public and private sector in the pastare yet to provide evidence of successful completion, since few of the concession periods have expired. This paper provides an identified list of risk factors to a case study of Stadium Australia. The most significant risk associated with Stadium Australia include the bidding process, the high level of public scrutiny, post-Olympic Games facility revenue and the complicated nature of the consortium structure.  

  3. Identifying Risk Factors of Boot Procurement: A Case Study of Stadium Australia

    Directory of Open Access Journals (Sweden)

    Marcus Jefferies

    2012-11-01

    Full Text Available Private sector input into the procurement of public works and services is continuing to increase. This has partly arisen out of a requirement for infrastructure development to be undertaken at a rate that maintains and allows growth. This has become a major challange for the construction industry that cannot be met by government alone. The emergence of Build-Own-Operate-Transfer (BOOT schemes as a response to this challange provides a means for developing the infrastructure of a country without directly impacting on the governments budgetary constraints. The concepts of BOOT are without doubt extremely complex arrangements, which bring to the construction sector risks not experienced previously. Many of the infrastructure partnerships between public and private sector in the pastare yet to provide evidence of successful completion, since few of the concession periods have expired. This paper provides an identified list of risk factors to a case study of Stadium Australia. The most significant risk associated with Stadium Australia include the bidding process, the high level of public scrutiny, post-Olympic Games facility revenue and the complicated nature of the consortium structure.

  4. Modelling categorical data to identify factors influencing concern for the natural environment in Iran.

    Science.gov (United States)

    Parizanganeh, Abdolhossein; Lakhan, V Chris; Yazdani, Mahmoud; Ahmad, Sajid R

    2011-10-01

    Loglinear modelling techniques were used to identify the interactions and interrelationships underlying categorical environmental concern data collected from 9062 respondents in Iran. After fitting various loglinear models to the data, the most parsimonious model highlighted that a combination of interacting factors, namely educational attainment, age, gender, and residential location were responsible for influencing personal concern for the environment. Although high educational attainment had a close correspondence with high concern for the environment the loglinear results, when visualized with a geographical information system, demonstrated wide spatial variations in educational attainment and concern for the environment. Nearly two-thirds of the respondents were not highly educated, and were therefore not highly concerned for the environment. The finding that both rural and urban male and female respondents in the 15-24 years age category, with 10-12 years of education, had the strongest interaction with personal concern for the environment could be beneficial for policy planners to utilize education as the primary instrument to enhance environmental governance and prospects for sustainable development. Copyright © 2011 Elsevier Ltd. All rights reserved.

  5. Identifying factors associated with regular physical activity in leisure time among Canadian adolescents.

    Science.gov (United States)

    Godin, Gaston; Anderson, Donna; Lambert, Léo-Daniel; Desharnais, Raymond

    2005-01-01

    The purpose of this study was to identify the factors explaining regular physical activity among Canadian adolescents. A cohort study conducted over a period of 2 years. A French-language high school located near Québec City. A cohort of 740 students (352 girls; 388 boys) aged 13.3 +/- 1.0 years at baseline. Psychosocial, life context, profile, and sociodemographic variables were assessed at baseline and 1 and 2 years after baseline. Exercising almost every day during leisure time at each measurement time was the dependent variable. The Generalized Estimating Equations (GEE) analysis indicated that exercising almost every day was significantly associated with a high intention to exercise (odds ratio [OR]: 8.33, confidence interval [CI] 95%: 5.26, 13.18), being satisfied with the activity practiced (OR: 2.07, CI 95%: 1.27, 3.38), perceived descriptive norm (OR: 1.82, CI 95%: 1.41, 2.35), being a boy (OR: 1.83, CI 95%: 1.37, 2.46), practicing "competitive" activities (OR: 1.80, CI 95%: 1.37, 2.36), eating a healthy breakfast (OR: 1.68, CI 95%: 1.09, 2.60), and normative beliefs (OR: 1.48, CI 95%: 1.14, 1.90). Specific GEE analysis for gender indicated slight but significant differences. This study provides evidence for the need to design interventions that are gender specific and that focus on increasing intention to exercise regularly.

  6. Epidermal growth factor gene is a newly identified candidate gene for gout

    Science.gov (United States)

    Han, Lin; Cao, Chunwei; Jia, Zhaotong; Liu, Shiguo; Liu, Zhen; Xin, Ruosai; Wang, Can; Li, Xinde; Ren, Wei; Wang, Xuefeng; Li, Changgui

    2016-01-01

    Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 region in 480 male gout patients and 480 controls. The SNP rs12504538, located in the elongation of very-long-chain-fatty-acid-like family member 6 gene (Elovl6), was found to be associated with gout susceptibility (Padjusted = 0.00595). In the second stage of analysis, we performed fine mapping analysis of 93 tag SNPs in Elovl6 and in the epidermal growth factor gene (EGF) and its flanking regions in 1017 male patients gout and 1897 healthy male controls. We observed a significant association between the T allele of EGF rs2298999 and gout (odds ratio = 0.77, 95% confidence interval = 0.67–0.88, Padjusted = 6.42 × 10−3). These results provide the first evidence for an association between the EGF rs2298999 C/T polymorphism and gout. Our findings should be validated in additional populations. PMID:27506295

  7. Epidermal growth factor gene is a newly identified candidate gene for gout.

    Science.gov (United States)

    Han, Lin; Cao, Chunwei; Jia, Zhaotong; Liu, Shiguo; Liu, Zhen; Xin, Ruosai; Wang, Can; Li, Xinde; Ren, Wei; Wang, Xuefeng; Li, Changgui

    2016-08-10

    Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 region in 480 male gout patients and 480 controls. The SNP rs12504538, located in the elongation of very-long-chain-fatty-acid-like family member 6 gene (Elovl6), was found to be associated with gout susceptibility (Padjusted = 0.00595). In the second stage of analysis, we performed fine mapping analysis of 93 tag SNPs in Elovl6 and in the epidermal growth factor gene (EGF) and its flanking regions in 1017 male patients gout and 1897 healthy male controls. We observed a significant association between the T allele of EGF rs2298999 and gout (odds ratio = 0.77, 95% confidence interval = 0.67-0.88, Padjusted = 6.42 × 10(-3)). These results provide the first evidence for an association between the EGF rs2298999 C/T polymorphism and gout. Our findings should be validated in additional populations.

  8. Identifying Associations Between Brain Imaging Phenotypes and Genetic Factors via A Novel Structured SCCA Approach.

    Science.gov (United States)

    Du, Lei; Zhang, Tuo; Liu, Kefei; Yan, Jingwen; Yao, Xiaohui; Risacher, Shannon L; Saykin, Andrew J; Han, Junwei; Guo, Lei; Shen, Li

    2017-06-01

    Brain imaging genetics attracts more and more attention since it can reveal associations between genetic factors and the structures or functions of human brain. Sparse canonical correlation analysis (SCCA) is a powerful bi-multivariate association identification technique in imaging genetics. There have been many SCCA methods which could capture different types of structured imaging genetic relationships. These methods either use the group lasso to recover the group structure, or employ the graph/network guided fused lasso to find out the network structure. However, the group lasso methods have limitation in generalization because of the incomplete or unavailable prior knowledge in real world. The graph/network guided methods are sensitive to the sign of the sample correlation which may be incorrectly estimated. We introduce a new SCCA model using a novel graph guided pairwise group lasso penalty, and propose an efficient optimization algorithm. The proposed method has a strong upper bound for the grouping effect for both positively and negatively correlated variables. We show that our method performs better than or equally to two state-of-the-art SCCA methods on both synthetic and real neuroimaging genetics data. In particular, our method identifies stronger canonical correlations and captures better canonical loading profiles, showing its promise for revealing biologically meaningful imaging genetic associations.

  9. Confirmatory Factor Analysis and Multiple Linear Regression of the Neck Disability Index: Assessment If Subscales Are Equally Relevant in Whiplash and Nonspecific Neck Pain.

    Science.gov (United States)

    Croft, Arthur C; Milam, Bryce; Meylor, Jade; Manning, Richard

    2016-06-01

    Because of previously published recommendations to modify the Neck Disability Index (NDI), we evaluated the responsiveness and dimensionality of the NDI within a population of adult whiplash-injured subjects. The purpose of the present study was to evaluate the responsiveness and dimensionality of the NDI within a population of adult whiplash-injured subjects. Subjects who had sustained whiplash injuries of grade 2 or higher completed an NDI questionnaire. There were 123 subjects (55% female, of which 36% had recovered and 64% had chronic symptoms. NDI subscales were analyzed using confirmatory factor analysis, considering only the subscales and, secondly, using sex as an 11th variable. The subscales were also tested with multiple linear regression modeling using the total score as a target variable. When considering only the 10 NDI subscales, only a single factor emerged, with an eigenvalue of 5.4, explaining 53.7% of the total variance. Strong correlation (> .55) (P factor model of the NDI is not justified based on our results, and in this population of whiplash subjects, the NDI was unidimensional, demonstrating high internal consistency and supporting the original validation study of Vernon and Mior.

  10. Factors influencing superimposition error of 3D cephalometric landmarks by plane orientation method using 4 reference points: 4 point superimposition error regression model.

    Science.gov (United States)

    Hwang, Jae Joon; Kim, Kee-Deog; Park, Hyok; Park, Chang Seo; Jeong, Ho-Gul

    2014-01-01

    Superimposition has been used as a method to evaluate the changes of orthodontic or orthopedic treatment in the dental field. With the introduction of cone beam CT (CBCT), evaluating 3 dimensional changes after treatment became possible by superimposition. 4 point plane orientation is one of the simplest ways to achieve superimposition of 3 dimensional images. To find factors influencing superimposition error of cephalometric landmarks by 4 point plane orientation method and to evaluate the reproducibility of cephalometric landmarks for analyzing superimposition error, 20 patients were analyzed who had normal skeletal and occlusal relationship and took CBCT for diagnosis of temporomandibular disorder. The nasion, sella turcica, basion and midpoint between the left and the right most posterior point of the lesser wing of sphenoidal bone were used to define a three-dimensional (3D) anatomical reference co-ordinate system. Another 15 reference cephalometric points were also determined three times in the same image. Reorientation error of each landmark could be explained substantially (23%) by linear regression model, which consists of 3 factors describing position of each landmark towards reference axes and locating error. 4 point plane orientation system may produce an amount of reorientation error that may vary according to the perpendicular distance between the landmark and the x-axis; the reorientation error also increases as the locating error and shift of reference axes viewed from each landmark increases. Therefore, in order to reduce the reorientation error, accuracy of all landmarks including the reference points is important. Construction of the regression model using reference points of greater precision is required for the clinical application of this model.

  11. The effect of journal impact factor, reporting conflicts, and reporting funding sources, on standardized effect sizes in back pain trials: a systematic review and meta-regression.

    Science.gov (United States)

    Froud, Robert; Bjørkli, Tom; Bright, Philip; Rajendran, Dévan; Buchbinder, Rachelle; Underwood, Martin; Evans, David; Eldridge, Sandra

    2015-11-30

    Low back pain is a common and costly health complaint for which there are several moderately effective treatments. In some fields there is evidence that funder and financial conflicts are associated with trial outcomes. It is not clear whether effect sizes in back pain trials relate to journal impact factor, reporting conflicts of interest, or reporting funding. We performed a systematic review of English-language papers reporting randomised controlled trials of treatments for non-specific low back pain, published between 2006-2012. We modelled the relationship using 5-year journal impact factor, and categories of reported of conflicts of interest, and categories of reported funding (reported none and reported some, compared to not reporting these) using meta-regression, adjusting for sample size, and publication year. We also considered whether impact factor could be predicted by the direction of outcome, or trial sample size. We could abstract data to calculate effect size in 99 of 146 trials that met our inclusion criteria. Effect size is not associated with impact factor, reporting of funding source, or reporting of conflicts of interest. However, explicitly reporting 'no trial funding' is strongly associated with larger absolute values of effect size (adjusted β=1.02 (95 % CI 0.44 to 1.59), P=0.001). Impact factor increases by 0.008 (0.004 to 0.012) per unit increase in trial sample size (Psources of funding, and conflicts of interest reflects positively on research and publisher conduct in the field. Strong evidence of a large association between absolute magnitude of effect size and explicit reporting of 'no funding' suggests authors of unfunded trials are likely to report larger effect sizes, notwithstanding direction. This could relate in part to quality, resources, and/or how pragmatic a trial is.

  12. Regression in autistic spectrum disorders.

    Science.gov (United States)

    Stefanatos, Gerry A

    2008-12-01

    A significant proportion of children diagnosed with Autistic Spectrum Disorder experience a developmental regression characterized by a loss of previously-acquired skills. This may involve a loss of speech or social responsitivity, but often entails both. This paper critically reviews the phenomena of regression in autistic spectrum disorders, highlighting the characteristics of regression, age of onset, temporal course, and long-term outcome. Important considerations for diagnosis are discussed and multiple etiological factors currently hypothesized to underlie the phenomenon are reviewed. It is argued that regressive autistic spectrum disorders can be conceptualized on a spectrum with other regressive disorders that may share common pathophysiological features. The implications of this viewpoint are discussed.

  13. Identifying Metrics before and after Readmission following Head and Neck Surgery and Factors Affecting Readmission Rate.

    Science.gov (United States)

    Puram, Sidharth V; Bhattacharyya, Neil

    2018-05-01

    Objectives Determine nationally representative readmission rates after head and neck cancer (HNCA) surgery and factors associated with readmission. Study Design Cross-sectional analysis of admissions database. Methods The 2013 Nationwide Readmissions Database was analyzed for HNCA surgery admissions and subsequent readmission within 30 days. The readmission rate, length of stay (LOS), disposition, mortality rate, and total charges were determined. Diagnoses and procedures upon readmission were quantified. Factors that were associated with readmission were determined. Results In total, 132,755 HNCA surgery inpatient admissions (mean age, 57.3 years; 52.2% male) were analyzed. Nationally representative metrics for HNCA surgery were mean LOS (4.4 ± 0.1 days), disposition (home without services, 80.5%; home health care, 10.9%; and skilled facility, 6.6%), mortality rate (1.0% ± 0.1%), and total charges ($53,106 ± $1167). The readmission rate was 7.7% ± 0.2% (mean readmission postoperative days, 17.1 ± 0.1), with readmission LOS (5.6 ± 0.1 days), mortality rate (3.7% ± 0.3%), and total charges ($49,425 ± $1548). The most common diagnoses at readmission included surgical complications (15.5%), mental health and substance abuse (13.1%), hypertension (12.8%), septicemia/infection (12.1%), gastrointestinal disease (11.3%), nutritional/metabolic disorders (10.1%), electrolyte abnormalities (8.5%), and esophageal disorders (8.1%). In multivariate analyses, male sex, increasing All Patients Refined Diagnosis Related Group (APR-DRG) severity score, and initial LOS were associated with readmission (odds ratio [95% confidence interval], 1.11 [1.04-1.20], 1.94 [1.77-2.12], and 1.34 [1.22-1.48], respectively), whereas age and discharge location were not ( P = .361 and .482). Conclusion HNCA surgery readmission is associated with significant increases in services/skilled care on discharge, mortality, and additional total health care cost. This national analysis identifies

  14. Sexual Risk Behavior Among Youth With Bipolar Disorder: Identifying Demographic and Clinical Risk Factors.

    Science.gov (United States)

    Krantz, Megan; Goldstein, Tina; Rooks, Brian; Merranko, John; Liao, Fangzi; Gill, Mary Kay; Diler, Rasim; Hafeman, Danella; Ryan, Neal; Goldstein, Benjamin; Yen, Shirley; Hower, Heather; Hunt, Jeffrey; Keller, Martin; Strober, Michael; Axelson, David; Birmaher, Boris

    2018-02-01

    This study aims to document rates of sexual activity among youth with bipolar spectrum disorder (BD) and to examine demographic and clinical factors associated with first sexual activity and sexual risk behavior during follow-up. The sample was drawn from the Course and Outcome of Bipolar Youth (COBY) study of 413 youth 7 to 17 years at baseline who met criteria for bipolar spectrum disorder according to the Schedule for Affective Disorders and Schizophrenia for School-Aged Children. Psychiatric symptoms during follow-up were assessed using the Adolescent Longitudinal Interview Follow-Up Evaluation (ALIFE). Sexual behavior and level of sexual risk (e.g., unprotected sex, multiple partners, and/or partners with known sexually transmitted infections) were assessed by trained evaluators using the ALIFE Psychosocial Functioning Scale. Analyses were conducted in relation to first sexual behavior during follow-up and then to subsequent sexual behaviors (mean 9.7 years, standard deviation 3.2). Sexually active COBY youth (n = 292 of 413; 71%) were more likely females, using substances, and not living with both parents. Consistent with findings among healthy youth, earlier first sexual activity in the sample was significantly associated with low socioeconomic status, female sex, comorbid disruptive behavior disorder, and substance use. As with healthy youth, sexual risk behavior during follow-up was significantly associated with non-Caucasian race, low socioeconomic status, substance use, and history of sexual abuse. Of those COBY youth who were sexually active, 11% reported sexual assault or abuse, 36% reported becoming pregnant (or the significant other becoming pregnant), and 15% reported having at least 1 abortion (or the significant other having an abortion) during follow-up. Hypomanic symptoms during follow-up were temporally associated with the greatest risk for sexual risk behavior. Demographic and clinical factors could help identify youth with bipolar spectrum

  15. Identifying Factors Influencing the Establishment of a Health System Reform Plan in Iran's Public Hospitals

    Directory of Open Access Journals (Sweden)

    Rasul Fani khiavi

    2016-09-01

    Full Text Available In today's world, health views have found a wider perspective in which non-medical expectations are particularly catered to. The health system reform plan seeks to improve society's health, decrease treatment costs, and increase patient satisfaction. This study investigated factors affecting the successful establishment of a health system reform plan. A mixed qualitative – quantitative approach was applied to conduct to explore influential factors associated with the establishment of a health system reform plan in Iran's public hospitals. The health systems and approaches to improving them in other countries have been studied. A Likert-based five-point questionnaire was the measurement instrument, and its content validity based on content validity ratio (CVR was 0.87. The construct validity, calculated using the factorial analysis and Kaiser Mayer Olkin (KMO techniques, was 0.964, which is a high level and suggests a correlation between the scale items. To complete the questionnaire, 185 experts, specialists, and executives of Iran’s health reform plan were selected using the Purposive Stratified Non Random Sampling and snowball methods. The data was then analyzed using exploratory factorial analysis and SPSS and LISREL software applications. The results of this research imply the existence of a pattern with a significant and direct relationship between the identified independent variables and the dependent variable of the establishment of a health system reform plan. The most important indices of establishing a health system reform plan, in the order of priority, were political support; suitable proportion and coverage of services presented in the society; management of resources; existence of necessary infrastructures; commitment of senior managers; constant planning, monitoring, and evaluation; and presentation of feedback to the plan's executives, intrasector/extrasector cooperation, and the plan’s guiding committee. Considering the

  16. Identifying depression severity risk factors in persons with traumatic spinal cord injury.

    Science.gov (United States)

    Williams, Ryan T; Wilson, Catherine S; Heinemann, Allen W; Lazowski, Linda E; Fann, Jesse R; Bombardier, Charles H

    2014-02-01

    Examine the relationship between demographic characteristics, health-, and injury-related characteristics, and substance misuse across multiple levels of depression severity. 204 persons with traumatic spinal cord injury (SCI) volunteered as part of screening efforts for a randomized controlled trial of venlafaxine extended release for major depressive disorder (MDD). Instruments included the Patient Health Questionnaire-9 (PHQ-9) depression scale, the Alcohol Use Disorders Identification Test (AUDIT), and the Substance Abuse in Vocational Rehabilitation-Screener (SAVR-S), which contains 3 subscales: drug misuse, alcohol misuse, and a subtle items scale. Each of the SAVR-S subscales contributes to an overall substance use disorder (SUD) outcome. Three proportional odds models were specified, varying the substance misuse measure included in each model. 44% individuals had no depression symptoms, 31% had mild symptoms, 16% had moderate symptoms, 6% had moderately severe symptoms, and 3% had severe depression symptoms. Alcohol misuse, as indicated by the AUDIT and the SAVR-S drug misuse subscale scores were significant predictors of depression symptom severity. The SAVR-S substance use disorder (SUD) screening outcome was the most predictive variable. Level of education was only significantly predictive of depression severity in the model using the AUDIT alcohol misuse indicator. Likely SUD as measured by the SAVR-S was most predictive of depression symptom severity in this sample of persons with traumatic SCI. Drug and alcohol screening are important for identifying individuals at risk for depression, but screening for both may be optimal. Further research is needed on risk and protective factors for depression, including psychosocial characteristics. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  17. Identifying functional transcription factor binding sites in yeast by considering their positional preference in the promoters.

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    Fu-Jou Lai

    Full Text Available Transcription factor binding site (TFBS identification plays an important role in deciphering gene regulatory codes. With comprehensive knowledge of TFBSs, one can understand molecular mechanisms of gene regulation. In the recent decades, various computational approaches have been proposed to predict TFBSs in the genome. The TFBS dataset of a TF generated by each algorithm is a ranked list of predicted TFBSs of that TF, where top ranked TFBSs are statistically significant ones. However, whether these statistically significant TFBSs are functional (i.e. biologically relevant is still unknown. Here we develop a post-processor, called the functional propensity calculator (FPC, to assign a functional propensity to each TFBS in the existing computationally predicted TFBS datasets. It is known that functional TFBSs reveal strong positional preference towards the transcriptional start site (TSS. This motivates us to take TFBS position relative to the TSS as the key idea in building our FPC. Based on our calculated functional propensities, the TFBSs of a TF in the original TFBS dataset could be reordered, where top ranked TFBSs are now the ones with high functional propensities. To validate the biological significance of our results, we perform three published statistical tests to assess the enrichment of Gene Ontology (GO terms, the enrichment of physical protein-protein interactions, and the tendency of being co-expressed. The top ranked TFBSs in our reordered TFBS dataset outperform the top ranked TFBSs in the original TFBS dataset, justifying the effectiveness of our post-processor in extracting functional TFBSs from the original TFBS dataset. More importantly, assigning functional propensities to putative TFBSs enables biologists to easily identify which TFBSs in the promoter of interest are likely to be biologically relevant and are good candidates to do further detailed experimental investigation. The FPC is implemented as a web tool at http://santiago.ee.ncku.edu.tw/FPC/.

  18. Regression: The Apple Does Not Fall Far From the Tree.

    Science.gov (United States)

    Vetter, Thomas R; Schober, Patrick

    2018-05-15

    Researchers and clinicians are frequently interested in either: (1) assessing whether there is a relationship or association between 2 or more variables and quantifying this association; or (2) determining whether 1 or more variables can predict another variable. The strength of such an association is mainly described by the correlation. However, regression analysis and regression models can be used not only to identify whether there is a significant relationship or association between variables but also to generate estimations of such a predictive relationship between variables. This basic statistical tutorial discusses the fundamental concepts and techniques related to the most common types of regression analysis and modeling, including simple linear regression, multiple regression, logistic regression, ordinal regression, and Poisson regression, as well as the common yet often underrecognized phenomenon of regression toward the mean. The various types of regression analysis are powerful statistical techniques, which when appropriately applied, can allow for the valid interpretation of complex, multifactorial data. Regression analysis and models can assess whether there is a relationship or association between 2 or more observed variables and estimate the strength of this association, as well as determine whether 1 or more variables can predict another variable. Regression is thus being applied more commonly in anesthesia, perioperative, critical care, and pain research. However, it is crucial to note that regression can identify plausible risk factors; it does not prove causation (a definitive cause and effect relationship). The results of a regression analysis instead identify independent (predictor) variable(s) associated with the dependent (outcome) variable. As with other statistical methods, applying regression requires that certain assumptions be met, which can be tested with specific diagnostics.

  19. Genome-wide association analysis of pain severity in dysmenorrhea identifies association at chromosome 1p13.2, near the nerve growth factor locus.

    Science.gov (United States)

    Jones, Amy V; Hockley, James R F; Hyde, Craig; Gorman, Donal; Sredic-Rhodes, Ana; Bilsland, James; McMurray, Gordon; Furlotte, Nicholas A; Hu, Youna; Hinds, David A; Cox, Peter J; Scollen, Serena

    2016-11-01

    Dysmenorrhea is a common chronic pelvic pain syndrome affecting women of childbearing potential. Family studies suggest that genetic background influences the severity of dysmenorrhea, but genetic predisposition and molecular mechanisms underlying dysmenorrhea are not understood. In this study, we conduct the first genome-wide association study to identify genetic factors associated with dysmenorrhea pain severity. A cohort of females of European descent (n = 11,891) aged 18 to 45 years rated their average dysmenorrhea pain severity. We used a linear regression model adjusting for age and body mass index, identifying one genome-wide significant (P dysmenorrhea pain were more likely to report being positive for endometriosis, polycystic ovarian syndrome, depression, and other psychiatric disorders. Our results indicate that dysmenorrhea pain severity is partly genetically determined. NGF already has an established role in chronic pain disorders, and our findings suggest that NGF may be an important mediator for gynaecological/pelvic pain in the viscera.

  20. Association of Stressful Life Events with Psychological Problems: A Large-Scale Community-Based Study Using Grouped Outcomes Latent Factor Regression with Latent Predictors

    Directory of Open Access Journals (Sweden)

    Akbar Hassanzadeh

    2017-01-01

    Full Text Available Objective. The current study is aimed at investigating the association between stressful life events and psychological problems in a large sample of Iranian adults. Method. In a cross-sectional large-scale community-based study, 4763 Iranian adults, living in Isfahan, Iran, were investigated. Grouped outcomes latent factor regression on latent predictors was used for modeling the association of psychological problems (depression, anxiety, and psychological distress, measured by Hospital Anxiety and Depression Scale (HADS and General Health Questionnaire (GHQ-12, as the grouped outcomes, and stressful life events, measured by a self-administered stressful life events (SLEs questionnaire, as the latent predictors. Results. The results showed that the personal stressors domain has significant positive association with psychological distress (β=0.19, anxiety (β=0.25, depression (β=0.15, and their collective profile score (β=0.20, with greater associations in females (β=0.28 than in males (β=0.13 (all P<0.001. In addition, in the adjusted models, the regression coefficients for the association of social stressors domain and psychological problems profile score were 0.37, 0.35, and 0.46 in total sample, males, and females, respectively (P<0.001. Conclusion. Results of our study indicated that different stressors, particularly those socioeconomic related, have an effective impact on psychological problems. It is important to consider the social and cultural background of a population for managing the stressors as an effective approach for preventing and reducing the destructive burden of psychological problems.

  1. HIV-, HCV-, and co-infections and associated risk factors among drug users in southwestern China: a township-level ecological study incorporating spatial regression.

    Directory of Open Access Journals (Sweden)

    Yi-Biao Zhou

    Full Text Available BACKGROUND: The human immunodeficiency virus (HIV and hepatitis C virus (HCV are major public health problems. Many studies have been performed to investigate the association between demographic and behavioral factors and HIV or HCV infection. However, some of the results of these studies have been in conflict. METHODOLOGY/PRINCIPAL FINDINGS: The data of all entrants in the 11 national methadone clinics in the Yi Autonomous Prefecture from March 2004 to December 2012 were collected from the national database. Several spatial regression models were used to analyze specific community characteristics associated with the prevalence of HIV and HCV infection at the township level. The study enrolled 6,417 adult patients. The prevalence of HIV infection, HCV infection and co-infection was 25.4%, 30.9%, and 11.0%, respectively. Prevalence exhibited stark geographical variations in the area studied. The four regression models showed Yi ethnicity to be associated with both the prevalence of HIV and of HIV/HCV co-infection. The male drug users in some northwestern counties had greater odds of being infected with HIV than female drug users, but the opposite was observed in some eastern counties. The 'being in drug rehabilitation variable was found to be positively associated with prevalence of HCV infection in some southern townships, however, it was found to be negatively associated with it in some northern townships. CONCLUSIONS/SIGNIFICANCE: The spatial modeling creates better representations of data such that public health interventions must focus on areas with high frequency of HIV/HCV to prevent further transmission of both HIV and HCV.

  2. Association of Stressful Life Events with Psychological Problems: A Large-Scale Community-Based Study Using Grouped Outcomes Latent Factor Regression with Latent Predictors

    Science.gov (United States)

    Hassanzadeh, Akbar; Heidari, Zahra; Hassanzadeh Keshteli, Ammar; Afshar, Hamid

    2017-01-01

    Objective The current study is aimed at investigating the association between stressful life events and psychological problems in a large sample of Iranian adults. Method In a cross-sectional large-scale community-based study, 4763 Iranian adults, living in Isfahan, Iran, were investigated. Grouped outcomes latent factor regression on latent predictors was used for modeling the association of psychological problems (depression, anxiety, and psychological distress), measured by Hospital Anxiety and Depression Scale (HADS) and General Health Questionnaire (GHQ-12), as the grouped outcomes, and stressful life events, measured by a self-administered stressful life events (SLEs) questionnaire, as the latent predictors. Results The results showed that the personal stressors domain has significant positive association with psychological distress (β = 0.19), anxiety (β = 0.25), depression (β = 0.15), and their collective profile score (β = 0.20), with greater associations in females (β = 0.28) than in males (β = 0.13) (all P < 0.001). In addition, in the adjusted models, the regression coefficients for the association of social stressors domain and psychological problems profile score were 0.37, 0.35, and 0.46 in total sample, males, and females, respectively (P < 0.001). Conclusion Results of our study indicated that different stressors, particularly those socioeconomic related, have an effective impact on psychological problems. It is important to consider the social and cultural background of a population for managing the stressors as an effective approach for preventing and reducing the destructive burden of psychological problems. PMID:29312459

  3. Mechanisms of neuroblastoma regression

    Science.gov (United States)

    Brodeur, Garrett M.; Bagatell, Rochelle

    2014-01-01

    Recent genomic and biological studies of neuroblastoma have shed light on the dramatic heterogeneity in the clinical behaviour of this disease, which spans from spontaneous regression or differentiation in some patients, to relentless disease progression in others, despite intensive multimodality therapy. This evidence also suggests several possible mechanisms to explain the phenomena of spontaneous regression in neuroblastomas, including neurotrophin deprivation, humoral or cellular immunity, loss of telomerase activity and alterations in epigenetic regulation. A better understanding of the mechanisms of spontaneous regression might help to identify optimal therapeutic approaches for patients with these tumours. Currently, the most druggable mechanism is the delayed activation of developmentally programmed cell death regulated by the tropomyosin receptor kinase A pathway. Indeed, targeted therapy aimed at inhibiting neurotrophin receptors might be used in lieu of conventional chemotherapy or radiation in infants with biologically favourable tumours that require treatment. Alternative approaches consist of breaking immune tolerance to tumour antigens or activating neurotrophin receptor pathways to induce neuronal differentiation. These approaches are likely to be most effective against biologically favourable tumours, but they might also provide insights into treatment of biologically unfavourable tumours. We describe the different mechanisms of spontaneous neuroblastoma regression and the consequent therapeutic approaches. PMID:25331179

  4. [Study on sensitivity of climatic factors on influenza A (H1N1) based on classification and regression tree and wavelet analysis].

    Science.gov (United States)

    Xiao, Hong; Lin, Xiao-ling; Dai, Xiang-yu; Gao, Li-dong; Chen, Bi-yun; Zhang, Xi-xing; Zhu, Pei-juan; Tian, Huai-yu

    2012-05-01

    To analyze the periodicity of pandemic influenza A (H1N1) in Changsha in year 2009 and its correlation with sensitive climatic factors. The information of 5439 cases of influenza A (H1N1) and synchronous meteorological data during the period between May 22th and December 31st in year 2009 (223 days in total) in Changsha city were collected. The classification and regression tree (CART) was employed to screen the sensitive climatic factors on influenza A (H1N1); meanwhile, cross wavelet transform and wavelet coherence analysis were applied to assess and compare the periodicity of the pandemic disease and its association with the time-lag phase features of the sensitive climatic factors. The results of CART indicated that the daily minimum temperature and daily absolute humidity were the sensitive climatic factors for the popularity of influenza A (H1N1) in Changsha. The peak of the incidence of influenza A (H1N1) was in the period between October and December (Median (M) = 44.00 cases per day), simultaneously the daily minimum temperature (M = 13°C) and daily absolute humidity (M = 6.69 g/m(3)) were relatively low. The results of wavelet analysis demonstrated that a period of 16 days was found in the epidemic threshold in Changsha, while the daily minimum temperature and daily absolute humidity were the relatively sensitive climatic factors. The number of daily reported patients was statistically relevant to the daily minimum temperature and daily absolute humidity. The frequency domain was mostly in the period of (16 ± 2) days. In the initial stage of the disease (from August 9th and September 8th), a 6-day lag was found between the incidence and the daily minimum temperature. In the peak period of the disease, the daily minimum temperature and daily absolute humidity were negatively relevant to the incidence of the disease. In the pandemic period, the incidence of influenza A (H1N1) showed periodic features; and the sensitive climatic factors did have a "driving

  5. Identifying Critical Factors Influencing the Rents of Public Rental Housing Delivery by PPPs: The Case of Nanjing

    Directory of Open Access Journals (Sweden)

    Jingfeng Yuan

    2017-02-01

    Full Text Available The occupancy rate of Public Rental Housing (PRH in China is relatively low due to the unreasonable rents. At the same time, the development of PRH using Public Private Partnerships (PPPs increases the complexity of the rents. Therefore, the critical factors influencing the rents of PRH delivery by PPPs should be identified. Based on the comprehensive literature, this article identified a conceptual model for the factors influencing the rents of PRH delivery by PPPs in China, composed of 14 factors grouped in three factor packages, and discussed the relationships among three factor packages. A survey based on Nanjing was conducted to assess the relative significance of 14 factors. According to the results, six critical factors were identified: construction costs, household income, floor area and structure, transportation, market rents in the same district and public facilities. In addition, the proposed conceptual model had a good fit. The results also supported two hypothetical relationships among three factor packages: (1 the increase of the affordability of the target tenants had a positive effect on the increase of profits of private sectors; and (2 the increase of the affordability of the target tenants had a positive effect on the increase of level of the characteristics of PRH units. For future research, six critical factors and the relationships among three factor packages can be used to determine the reasonable rents for PRH delivery by PPPs in China.

  6. Identifying the Best-Fitting Factor Structure of the Experience of Close Relations

    DEFF Research Database (Denmark)

    Esbjørn, Barbara Hoff; Breinholst, Sonja; Niclasen, Janni

    2015-01-01

    . The present study used a Danish sample with the purpose of addressing limitations in previous studies, such as the lack of diversity in cultural back- ground, restricted sample characteristics, and poorly fitting structure models. Participants consisted of 253 parents of children between the ages of 7 and 12...... years, 53% being moth- ers. The parents completed the paper version of the questionnaire. Confirmatory Factor Analyses were carried out to determine whether theoretically and empirically established models including one and two factors would also provide adequate fits in a Danish sample. A previous...... study using the original ECR suggested that Scandinavian samples may best be described using a five-factor solution. Our results indicated that the one- and two-factor models of the ECR-R did not fit the data well. Exploratory Factor Analysis revealed a five- factor model. Our study provides evidence...

  7. Regression: A Bibliography.

    Science.gov (United States)

    Pedrini, D. T.; Pedrini, Bonnie C.

    Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…

  8. Identifying and Ranking the Factors Affecting Virtuousness in Yazd University-Affiliated Hospitals

    Directory of Open Access Journals (Sweden)

    H Shekari

    2015-07-01

    Conclusion: The results of ranking the factors of organizational virtuous showed that for moving toward virtuousness, the factors of ethical Culture, vision and Care for Community should be improvedby promoting ethics (Providing ethical standards for employee’s and manager’s behavior, Corporate Philanthropy, considering virtues in mission and vision etc. in mentioned hospitals.

  9. An empirical study on identifying critical success factors on chaos management

    Directory of Open Access Journals (Sweden)

    Naser Azad

    2012-08-01

    Full Text Available Chaos management is one of the most necessary efforts on managing business units. Many organizations fail to cope with undesirable circumstances, which may happen without any prior notice and as a result, they may face with significant financial losses. In this paper, we present an empirical study to determine critical success factors, which could help handle any possible chaos in organizations. The proposed study of this paper is implemented for a set of travel agencies located in Tehran, Iran. Chronbach alpha is calculated as 0.821, which is well above the minimum desirable level. In addition, we have also performed factor analysis, which yields a KMO value of 0.576 with the level of significance of 0.000. The results indicate that there are six important factors including effective management strategy, internal environmental factors, creative and innovative attitudes, external environmental factors and top level management thoughts.

  10. Identifying the most critical project complexity factors using Delphi method: the Iranian construction industry

    Directory of Open Access Journals (Sweden)

    Mohammad Mehdi Mozaffari

    2012-09-01

    Full Text Available Complexity is one of the most important issues influencing success of any construction project and there are literally different studies devoted to detect important factors increasing complexity of projects. During the past few years, there have been growing interests in developing mass construction projects in Iran. The proposed study of this paper uses Delphi technique to find out about important factors as barriers of construction projects in Iran. The results show that among 47 project complexity factors, 19 factors are more important than others are. The study groups different factors into seven categories including environmental, organizational, objectives, tasks, stakeholders, technological, information systems and determines the relative importance of each. In each group, many other sub group activities are determined and they are carefully investigated. The study provides some detailed suggestions on each category to reduce the complexity of construction project.

  11. Item Response Theory Modeling and Categorical Regression Analyses of the Five-Factor Model Rating Form: A Study on Italian Community-Dwelling Adolescent Participants and Adult Participants.

    Science.gov (United States)

    Fossati, Andrea; Widiger, Thomas A; Borroni, Serena; Maffei, Cesare; Somma, Antonella

    2017-06-01

    To extend the evidence on the reliability and construct validity of the Five-Factor Model Rating Form (FFMRF) in its self-report version, two independent samples of Italian participants, which were composed of 510 adolescent high school students and 457 community-dwelling adults, respectively, were administered the FFMRF in its Italian translation. Adolescent participants were also administered the Italian translation of the Borderline Personality Features Scale for Children-11 (BPFSC-11), whereas adult participants were administered the Italian translation of the Triarchic Psychopathy Measure (TriPM). Cronbach α values were consistent with previous findings; in both samples, average interitem r values indicated acceptable internal consistency for all FFMRF scales. A multidimensional graded item response theory model indicated that the majority of FFMRF items had adequate discrimination parameters; information indices supported the reliability of the FFMRF scales. Both categorical (i.e., item-level) and scale-level regression analyses suggested that the FFMRF scores may predict a nonnegligible amount of variance in the BPFSC-11 total score in adolescent participants, and in the TriPM scale scores in adult participants.

  12. Long-Term Military Contingency Operations: Identifying the Factors Affecting Budgeting in Annual or Supplemental Appropriations

    National Research Council Canada - National Science Library

    Evans, Amanda B

    2006-01-01

    .... The results show that planning, timing, accountability, visibility, politics and policy, stakeholder influence, military objectives, and fear of change are the most important factors. These findings can help stakeholders shape funding strategy.

  13. Identifying context factors explaining physician's low performance in communication assessment: an explorative study in general practice.

    NARCIS (Netherlands)

    Essers, G.; Dulmen, S. van; Weel, C. van; Vleuten, C. van der; Kramer, A.

    2011-01-01

    BACKGROUND: Communication is a key competence for health care professionals. Analysis of registrar and GP communication performance in daily practice, however, suggests a suboptimal application of communication skills. The influence of context factors could reveal why communication performance

  14. Identifying context factors explaining physician's low performance in communication assessment: an explorative study in general practice.

    NARCIS (Netherlands)

    Essers, G.T.J.M.; Dulmen, A.M. van; Weel, C. van; Vleuten, C.P.M. van der; Kramer, A.W.

    2011-01-01

    ABSTRACT: BACKGROUND: Communication is a key competence for health care professionals. Analysis of registrar and GP communication performance in daily practice, however, suggests a suboptimal application of communication skills. The influence of context factors could reveal why communication

  15. A literature review to identify factors that determine policies for influenza vaccination.

    NARCIS (Netherlands)

    Silva, M.L.; Perrier, L.; Cohen, J.M.; Paget, W.J.; Mosnier, A.; Späth, H.M.

    2015-01-01

    Objectives: To conduct a literature review of influenza vaccination policy, describing roles and interactions between stakeholders and the factors influencing policy-making. Methods: Major databases were searched using keywords related to influenza vaccination, decision-making and healthpolicy.

  16. Risk factors for atherosclerosis - can they be used to identify the ...

    African Journals Online (AJOL)

    1990-09-01

    Sep 1, 1990 ... fasting serum triglyceride levels (P < 0,04). Grouping these factors together ... brain infarct, coronary artery disease and intermittent claudica- tion. ... subjected to arm ergometer exercise ECG testing on a Wurburg ergometer.

  17. A unique virulence factor for proliferation and dwarfism in plants identified from a phytopathogenic bacterium

    OpenAIRE

    Hoshi, Ayaka; Oshima, Kenro; Kakizawa, Shigeyuki; Ishii, Yoshiko; Ozeki, Johji; Hashimoto, Masayoshi; Komatsu, Ken; Kagiwada, Satoshi; Yamaji, Yasuyuki; Namba, Shigetou

    2009-01-01

    One of the most important themes in agricultural science is the identification of virulence factors involved in plant disease. Here, we show that a single virulence factor, tengu-su inducer (TENGU), induces witches' broom and dwarfism and is a small secreted protein of the plant-pathogenic bacterium, phytoplasma. When tengu was expressed in Nicotiana benthamiana plants, these plants showed symptoms of witches' broom and dwarfism, which are typical of phytoplasma infection. Transgenic Arabidop...

  18. Identifying the Critical Factors Affecting Safety Program Performance for Construction Projects within Pakistan Construction Industry

    Directory of Open Access Journals (Sweden)

    Zubair Ahmed Memon

    2013-04-01

    Full Text Available Many studies have shown that the construction industry one of the most hazardous industries with its high rates of fatalities and injuries and high financial losses incurred through work related accident. To reduce or overcome the safety issues on construction sites, different safety programs are introduced by construction firms. A questionnaire survey study was conducted to highlight the influence of the Construction Safety Factors on safety program implementation. The input from the questionnaire survey was analyzed by using AIM (Average Index Method and rank correlation test was conducted between different groups of respondents to measure the association between different groups of respondent. The finding of this study highlighted that management support is the critical factor for implementing the safety program on projects. From statistical test, it is concluded that all respondent groups were strongly in the favor of management support factor as CSF (Critical Success Factor. The findings of this study were validated on selected case studies. Results of the case studies will help to know the effect of the factors on implementing safety programs during the execution stage.

  19. Identifying and prioritizing industry-level competitiveness factors: evidence from pharmaceutical market.

    Science.gov (United States)

    Shabaninejad, Hosein; Mehralian, Gholamhossein; Rashidian, Arash; Baratimarnani, Ahmad; Rasekh, Hamid Reza

    2014-04-03

    Pharmaceutical industry is knowledge-intensive and highly globalized, in both developed and developing countries. On the other hand, if companies want to survive, they should be able to compete well in both domestic and international markets. The main purpose of this paper is therefore to develop and prioritize key factors affecting companies' competitiveness in pharmaceutical industry. Based on an extensive literature review, a valid and reliable questionnaire was designed, which was later filled up by participants from the industry. To prioritize the key factors, we used the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The results revealed that human capital and macro-level policies were two key factors placed at the highest rank in respect of their effects on the competitiveness considering the industry-level in pharmaceutical area. This study provides fundamental evidence for policymakers and managers in pharma context to enable them formulating better polices to be proactively competitive and responsive to the markets' needs.

  20. Towards more efficient burn care: Identifying factors associated with good quality of life post-burn.

    Science.gov (United States)

    Finlay, V; Phillips, M; Allison, G T; Wood, F M; Ching, D; Wicaksono, D; Plowman, S; Hendrie, D; Edgar, D W

    2015-11-01

    As minor burn patients constitute the vast majority of a developed nation case-mix, streamlining care for this group can promote efficiency from a service-wide perspective. This study tested the hypothesis that a predictive nomogram model that estimates likelihood of good long-term quality of life (QoL) post-burn is a valid way to optimise patient selection and risk management when applying a streamlined model of care. A sample of 224 burn patients managed by the Burn Service of Western Australia who provided both short and long-term outcomes was used to estimate the probability of achieving a good QoL defined as 150 out of a possible 160 points on the Burn Specific Health Scale-Brief (BSHS-B) at least six months from injury. A multivariate logistic regression analysis produced a predictive model provisioned as a nomogram for clinical application. A second, independent cohort of consecutive patients (n=106) was used to validate the predictive merit of the nomogram. Male gender (p=0.02), conservative management (p=0.03), upper limb burn (p=0.04) and high BSHS-B score within one month of burn (pburns were excluded due to loss to follow up. For clinicians managing comparable burn populations, the BSWA burns nomogram is an effective tool to assist the selection of patients to a streamlined care pathway with the aim of improving efficiency of service delivery. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

  1. Identifying the Factors Leading to Success: How an Innovative Science Curriculum Cultivates Student Motivation

    Science.gov (United States)

    Scogin, Stephen C.

    2016-01-01

    "PlantingScience" is an award-winning program recognized for its innovation and use of computer-supported scientist mentoring. Science learners work on inquiry-based experiments in their classrooms and communicate asynchronously with practicing plant scientist-mentors about the projects. The purpose of this study was to identify specific…

  2. Digital Competence at the Beginning of Upper Secondary School: Identifying Factors Explaining Digital Inclusion

    Science.gov (United States)

    Hatlevik, Ove Edvard; Christophersen, Knut-Andreas

    2013-01-01

    During the last decade, information and communication technology has been given an increasingly large importance in our society. There seems to be a consensus regarding the necessity of supporting and developing school-based digital competence. In order to sustain digital inclusion, schools need to identify digital deficiencies and digital…

  3. Identifying the Factors Affecting Science and Mathematics Achievement Using Data Mining Methods

    Science.gov (United States)

    Kiray, S. Ahmet; Gok, Bilge; Bozkir, A. Selman

    2015-01-01

    The purpose of this article is to identify the order of significance of the variables that affect science and mathematics achievement in middle school students. For this aim, the study deals with the relationship between science and math in terms of different angles using the perspectives of multiple causes-single effect and of multiple…

  4. Effects of exposure to factor concentrates containing donations from identified AIDS patients

    International Nuclear Information System (INIS)

    Jason, J.; Holman, R.C.; Dixon, G.; Lawrence, D.N.; Bozeman, L.H.; Chorba, T.L.; Tregillus, L.; Evatt, B.L.

    1986-01-01

    The authors recipients of eight lots of factors VII and IX voluntarily withdrawn from distribution because one donor was known to have subsequently developed the acquired immunodeficiency syndrome with a nonexposed cohort matched by age, sex, and factor use. The factor VIII recipient cohorts did not differ in prevalence of antibody to human immunodeficiency virus (HIV), T-cell subset numbers, T-helper to T-suppressor ratios, or immunogloubulin levels. Exposed individuals had higher levels of immune complexes by C1q binding and staphylococcal binding assays and lower responses to phytohemagglutinin and concanavalin A. However, only the staphylococcal binding assay values were outside the normal range for our laboratory. Factor IX recipient cohorts did not differ in HIV antibody prevalence or any immune tests. Although exposed and nonexposed individuals did not differ from each other in a clinically meaningful fashion at initial testing, both the exposed and nonexposed cohorts had high rats of HIV seroprevalence. Market withdrawals were clearly insufficient means of limiting the spread of HIV in hemophilic patients; however, the currently available methods of donor screening and viral inactivation of blood products will prevent continued exposed within this population

  5. Identifying Factors That Are Most Influential in Veteran Teachers Seriously Considering Leaving the Profession

    Science.gov (United States)

    Culkin, Michaela A.

    2016-01-01

    This study investigated the factors most influential when veteran teachers seriously consider leaving the teaching profession. Teachers in the education profession who are in the later stages of their careers hold the experience that benefits all who teach in schools. There is ample literature discussing why new teachers leave the profession, but…

  6. Testing job typologies and identifying at-risk subpopulations using factor mixture models

    NARCIS (Netherlands)

    Keller, A. C.; Igic, Ivana; Meier, Laurenz L.; Semmer, N. K.; Schaubroeck, J.; Brunner, Beatrice; Elfering, Achim

    2017-01-01

    Research in occupational health psychology has tended to focus on the effects of single job characteristics or various job characteristics combined into 1 factor. However, such a variable-centered approach does not account for the clustering of job attributes among groups of employees. We addressed

  7. Identifying the critical factors of green supply chain management: Environmental benefits in Pakistan.

    Science.gov (United States)

    Mumtaz, Ubaidullah; Ali, Yousaf; Petrillo, Antonella; De Felice, Fabio

    2018-05-30

    Pakistan is a developing country characterized by a growing industrialization, which is the major cause of environmental pollution in the country. To control the significant increase in pollution a green incentive has started, aiming to moderate the adverse effects of environmental pollution. Thus, Green Supply Chain Management (GSCM) plays an important role in influencing the total environment impact of any organizations. This study considers ten Pakistani industries that have implemented GSCM practices. The Decision-Making Trial and Evaluation Laboratory technique (DEMATEL) is used to find influential factors in selecting GSCM criteria. The results show that organizational involvement is the most important dimension useful to implement GSCM practices. In addition, commitment from senior managers, ISO 14000 certification of suppliers and recycle of waste heat are considered significant factors. The paper also signifies the casual relationship among the dimensions and the factors in the form of diagraphs. The main management implication of the paper is to help decision makers to focus on the critical dimensions/factors in order to implement the GSCM practices more effectively in Pakistan. Copyright © 2018 Elsevier B.V. All rights reserved.

  8. The CAREFALL Triage instrument identifying risk factors for recurrent falls in elderly patients

    NARCIS (Netherlands)

    Hensbroek, van P. Boele; Dijk, van N.; Breda, van G.F.; Scheffer, A.C.; Cammen, van der T.J.; Lips, P.T.A.M.; Goslings, J.C.; Rooij, S.E.

    2009-01-01

    OBJECTIVE: To validate the CAREFALL Triage Instrument (CTI), a self-administered questionnaire concerning modifiable risk factors for recurrent falls in elderly patients who experienced fall. METHODS: This study in patients 65 years or older who experienced fall was performed at the accident and

  9. The CAREFALL Triage instrument identifying risk factors for recurrent falls in elderly patients

    NARCIS (Netherlands)

    Boele van Hensbroek, Pieter; van Dijk, Nynke; van Breda, G. Fenna; Scheffer, Alice C.; van der Cammen, Tischa J.; Lips, Paul; Goslings, J. Carel; de Rooij, Sophia E.

    2009-01-01

    Objective: To validate the CAREFALL Triage Instrument (CTI), a self-administered questionnaire concerning modifiable risk factors for recurrent falls in elderly patients who experienced fall. Methods: This study in patients 65 years or older who experienced fall was performed at the accident and

  10. Identifying Academic & Social Risk Factors of Baccalaureate Nursing Students Using the College Persistence Questionnaire

    Science.gov (United States)

    Betts, Kelly J.; Shirley, Janet A.; Kennedy, Robert

    2017-01-01

    Background: Student success in a baccalaureate nursing program is of utmost importance at a southern College of Nursing (CON).CON faculty wanted to understand better what academic/ social risk factors attributed to attrition in the first year of the nursing program. The purpose of this study was to determine academic and social risk factors…

  11. An OMERACT Initiative Toward Consensus to Identify and Characterize Candidate Contextual Factors

    DEFF Research Database (Denmark)

    Finger, Monika E; Boonen, Annelies; Woodworth, Thasia G

    2017-01-01

    OBJECTIVE: The importance of contextual factors (CF) for appropriate patient-specific care is widely acknowledged. However, evidence in clinical trials on how CF influence outcomes remains sparse. The 2014 Outcome Measures in Rheumatology (OMERACT) Handbook introduced the role of CF in outcome as...

  12. Identifying Factors That Affect Higher Educational Achievements of Jamaican Seventh-Day Adventists

    Science.gov (United States)

    Campbell, Samuel P.

    2011-01-01

    This mixed-method explanatory research examined factors that influenced Jamaican Seventh-day Adventist (SDA) members to pursue higher education. It sought to investigate whether the source of the motivation is tied to the Church's general philosophy on education or to its overall programs as experienced by the membership at large. The question of…

  13. Increased sexually transmitted infection incidence in a low risk population: identifying the risk factors.

    LENUS (Irish Health Repository)

    Shiely, Frances

    2010-04-01

    Between 1994 and 2006, the incidence of sexually transmitted infections (STIs) in Ireland has increased by over 300%. Recent literature would suggest that this figure is an underestimation of the true scale of infection. Our objective was to determine the risk factors associated with STI diagnosis in a population with a rapidly increasing STI incidence.

  14. Identifying the factors that affect the job satisfaction of early career Notre Dame graduate physiotherapists.

    Science.gov (United States)

    Bacopanos, Eleni; Edgar, Susan

    2016-11-01

    Objective Previous studies have highlighted the short career intentions and high attrition rates of physiotherapists from the profession. The aim of the present study was to examine the job satisfaction and attrition rates of early career physiotherapists graduating from one Western Australian university. Methods A self-administered online survey was conducted of 157 Notre Dame physiotherapy graduates (2006-2012), incorporating a job satisfaction rating scale. Results Results showed that lowered job satisfaction was related to working in the cardiorespiratory area of physiotherapy and working in multiple jobs since graduation. The majority of graduates did not predict a long-term career in physiotherapy, highlighting a lack of career progression and limited scope of practice as influential factors. Conclusions Job satisfaction in early career physiotherapists varies across different clinical areas of practice related to several factors, including challenge and flexibility. New roles in the profession, including extended scope roles, may impact on the future job satisfaction of physiotherapists. Further studies are needed to explore the effect of these roles on workforce trends, including attrition rates. What is known about the topic? Physiotherapists predict careers of 10 years or less on entry into the profession. No previous studies have explored the individual factors influencing job satisfaction in early career physiotherapists across different clinical settings. What does this paper add? This study highlights specific factors influencing the job satisfaction of early career physiotherapists, including clinical area of practice. Physiotherapists working in the cardiorespiratory area were less satisfied, as were physiotherapists undertaking multiple positions since graduation. What are the implications for practitioners? This study informs employers and workforce planners on the factors affecting job satisfaction in early career physiotherapists. In addition

  15. 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

  16. Identifying and Ranking the Effective Factors on Successful Implementation of Social Commerce in Iran, Using AHP Fuzzy

    Directory of Open Access Journals (Sweden)

    Zahra Rahimi

    2016-07-01

    Full Text Available Social commerce has been introduced as a new approach to increase sales, number of customers and reduce marketing expenditures. This approach is a combination of business, communication between people, as well as communicative and informative technologies based on web 2.0 Its achievement originated from different factors relied on business, individuals, culture, and technology. These factors have been primarily identified on the basis of library researches and classified into six infrastructural groups including:  technical, economical and human resources, cultural, rules governing the countries, style of management, and business. Then, it identified priority of the factors by using the fuzzy analytic hierarchy process (AHP. Innovation of this research was to extract a comprehensive list of factors and to prioritize them based on specific conditions in Iran.

  17. A unique virulence factor for proliferation and dwarfism in plants identified from a phytopathogenic bacterium

    Science.gov (United States)

    Hoshi, Ayaka; Oshima, Kenro; Kakizawa, Shigeyuki; Ishii, Yoshiko; Ozeki, Johji; Hashimoto, Masayoshi; Komatsu, Ken; Kagiwada, Satoshi; Yamaji, Yasuyuki; Namba, Shigetou

    2009-01-01

    One of the most important themes in agricultural science is the identification of virulence factors involved in plant disease. Here, we show that a single virulence factor, tengu-su inducer (TENGU), induces witches' broom and dwarfism and is a small secreted protein of the plant-pathogenic bacterium, phytoplasma. When tengu was expressed in Nicotiana benthamiana plants, these plants showed symptoms of witches' broom and dwarfism, which are typical of phytoplasma infection. Transgenic Arabidopsis thaliana lines expressing tengu exhibited similar symptoms, confirming the effects of tengu expression on plants. Although the localization of phytoplasma was restricted to the phloem, TENGU protein was detected in apical buds by immunohistochemical analysis, suggesting that TENGU was transported from the phloem to other cells. Microarray analyses showed that auxin-responsive genes were significantly down-regulated in the tengu-transgenic plants compared with GUS-transgenic control plants. These results suggest that TENGU inhibits auxin-related pathways, thereby affecting plant development. PMID:19329488

  18. Primary factors identified in sport science students' coaching philosophies : sport education and community involvement

    OpenAIRE

    Liandi van den Berg

    2014-01-01

    Youth sport coaches have a great influence on the experiences and development of children who participate in organized sport. Given this influence of coaches on children and the huge participation numbers of children in sports, coach education programmes received increasing research attention over the past 30 years. Numerous important facets of coach educational programmes have been identified, of which the first key developmental domain as indicated by the President's Council on Fitness, Spo...

  19. IDENTIFYING ELEVEN FACTORS OF SERVICE MARKETING MIX (4PS) EFFECTIVE ON TENDENCY OF PATIENTS TOWARD PRIVATE HOSPITAL

    OpenAIRE

    Hosseini, Seyed Mojtaba; Etesaminia, Samira; Jafari, Mehrnoosh

    2016-01-01

    Introduction: One of the important factors of correct management is to identify the reasons for patient tendency toward private hospitals. This study measures these factors based on service marketing mixes. Patients and methods: This study used a cross sectional descriptive methodology. The study was conducted during 6 months in 2015. The studied population included patients of private hospitals in Tehran. Random sampling was used (n = 200). Data was collected by an author-made questionnaire ...

  20. Calibration of Local Area Weather Radar-Identifying significant factors affecting the calibration

    DEFF Research Database (Denmark)

    Pedersen, Lisbeth; Jensen, Niels Einar; Madsen, Henrik

    2010-01-01

    A Local Area Weather Radar (LAWR) is an X-band weather radar developed to meet the needs of high resolution rainfall data for hydrological applications. The LAWR system and data processing methods are reviewed in the first part of this paper, while the second part of the paper focuses...... cases when the calibration is based on a factorized 3 parameter linear model instead of a single parameter linear model....

  1. Identifying driving factors for the establishment of cooperative GMO-free zones in Germany

    OpenAIRE

    Consmuller, Nicola; Beckmann, Volker; Petrick, Martin

    2012-01-01

    Since the end of the quasi-moratorium on genetically modified organisms (GMO) in the European Union in 2004, the establishment of GMO-free zones has become an EU wide phenomenon. In contrast to other European countries, Germany follows the concept of cooperative GMO-free zones where neighbouring farmers contractually refrain from GMO cultivation. In this article, we address the question which underlying factors could account for the establishment of cooperative GMO-free zones in Germany. Draw...

  2. Job satisfaction of nurses and identifying factors of job satisfaction in Slovenian Hospitals

    OpenAIRE

    Lorber, Mateja; Skela Savič, Brigita

    2012-01-01

    Aim To determine the level of job satisfaction of nursing professionals in Slovenian hospitals and factors influencing job satisfaction in nursing. Methods The study included 4 hospitals selected from the hospital list comprising 26 hospitals in Slovenia. The employees of these hospitals represent 29.8% and 509 employees included in the study represent 6% of all employees in nursing in Slovenian hospitals. One structured survey questionnaire was administered to the lea...

  3. Identifying and Ranking the Factors Affecting Virtuousness in Yazd University-Affiliated Hospitals

    OpenAIRE

    H Shekari; N Jalalian

    2015-01-01

    Abstract Introduction: Recently virtue has become a topic of serious examination among organizational researchers. In other words, organizations are moving toward virtuous organization. The purpose of this paper is determining and prioritizing the principal factors of a virtuous organization in Yazd University-Affiliated Hospitals in order to put virtues into practice. Methods: The procedure we proposed to reach the research aim consists of three steps. In the first Step, we extracted...

  4. Identifying the main Individual Factors Influencing Entrepreneurial Decision making Biases: A Qualitative Content Analysis Approach

    OpenAIRE

    Kambiz Talebi; Pouria Nouri; Abdolah Ahmadi Kafeshani

    2014-01-01

    Entrepreneurial decisions are one of the most important functions of entrepreneurs so as to manage their ventures on a daily basis. These decisions are not fully rational and because of various factors like cognitive and personal characteristics, environmental and firm-related issues, entrepreneurial decisions are prone to biases. Decision making biases has become a favorable research topic among entrepreneurial scholars. Decision making biases are responsible for lots of entrepreneurial succ...

  5. Early-life risk factors identified for owner-reported feline overweight and obesity at around two years of age.

    Science.gov (United States)

    Rowe, E C; Browne, W J; Casey, R A; Gruffydd-Jones, T J; Murray, J K

    2017-08-01

    Obesity is considered the second most common health problem in pet cats in developed countries. This study used prospective data from a longitudinal study of pet cats ('C.L.A.W.S.', www.bristol.ac.uk/vetscience/claws) to identify early-life risk factors for feline overweight/obesity occurring at around two years of age. Data were collected via five owner-completed questionnaires (for cats aged two-six months, six months, 12 months, 18 months and two years respectively) completed between May 2011 and April 2015. Owner-reported body condition scores (BCS) of cats at age two years, assessed using images from the 9-point BCS system (Laflamme, 1997), were categorised into a dichotomous variable: overweight/obese (BCS 6-9) and not overweight (BCS 1-5) and used as the dependent variable. Of the 375 cats with owner-reported BCS, 25.3% were overweight or obese at two years of age. Multivariable logistic regression models were built using stepwise forward-selection. To account for potential hierarchical clustering due to multi-cat households two-level random intercept models were considered but clustering had no impact on the analysis. Models were compared using Wald tests. Six factors were significantly associated with overweight/obesity at two years of age: being overweight or obese at one year of age (OR=10.6, 95%CI 4.4-25.3); owner belief that BCS 7 was the ideal weight (OR=33.2, 95%CI 8.5-129.4), or that BCS represented overweight cats but they would not be concerned if their cat were classified in this category (OR=2.7, 95%CI 1.2-6.2), at questionnaire five completion; vets advising owners that the cat should lose weight, or making no comment on their weight, between one and two years of age (OR=12.1, 95%CI 3.2-44.9 and OR=3.9, 95%CI 1.5-10.3 respectively); owners giving their cat treats when they "felt happy" with them at 18 months of age (OR=2.7, 95%CI 1.0 - 7.3); feeding ≥250g wet food daily between two and six months of age (OR=2.7, 95%CI 1.2-5.9), and feeding

  6. Epidermal growth factor gene is a newly identified candidate gene for gout

    OpenAIRE

    Lin Han; Chunwei Cao; Zhaotong Jia; Shiguo Liu; Zhen Liu; Ruosai Xin; Can Wang; Xinde Li; Wei Ren; Xuefeng Wang; Changgui Li

    2016-01-01

    Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 re...

  7. Identifying Risk Factors for Late-Onset (50+) Alcohol Use Disorder and Heavy Drinking

    DEFF Research Database (Denmark)

    Emiliussen, Jakob; Nielsen, Anette Søgaard; Andersen, Kjeld

    2017-01-01

    databases: MEDLINE, EMBASE, PubMed, and PsychInfo. Nine studies were included in the final review. Results: The search revealed that only very few studies have been conducted. Hence, the evidence is limited but suggests that stress, role/identity loss, and friends’approval of drinking are associated...... base their conclusions on a certain preconception of older adults with alcohol problems, which leads to a rowof circular arguments. The factors that have been measured seem to have changed over time. Conclusion: There has been a lack of focus on the field of late-onset AUD since the 1970s, which...

  8. Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Kleijnen, J.P.C.; Helton, J.C.

    1999-04-01

    The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are considered for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.

  9. A macroepigenetic approach to identify factors responsible for the autism epidemic in the United States

    Directory of Open Access Journals (Sweden)

    Dufault Renee

    2012-04-01

    Full Text Available Abstract The number of children ages 6 to 21 in the United States receiving special education services under the autism disability category increased 91% between 2005 to 2010 while the number of children receiving special education services overall declined by 5%. The demand for special education services continues to rise in disability categories associated with pervasive developmental disorders. Neurodevelopment can be adversely impacted when gene expression is altered by dietary transcription factors, such as zinc insufficiency or deficiency, or by exposure to toxic substances found in our environment, such as mercury or organophosphate pesticides. Gene expression patterns differ geographically between populations and within populations. Gene variants of paraoxonase-1 are associated with autism in North America, but not in Italy, indicating regional specificity in gene-environment interactions. In the current review, we utilize a novel macroepigenetic approach to compare variations in diet and toxic substance exposure between these two geographical populations to determine the likely factors responsible for the autism epidemic in the United States.

  10. IDENTIFYING FACTORS THAT CONTRIBUTE TO THE SATISFACTION OF STUDENTS IN E-LEARNING

    Directory of Open Access Journals (Sweden)

    Levent CALLI,

    2013-01-01

    Full Text Available There has been an increasing interest in the application of e-learning through the enhancement of internet and computer technologies. Satisfaction has appeared as a key factor in order to develop efficient course content in line with students’ demands and expectations. Thus, a lot of research has been conducted on the concept of satisfaction in electronic environments. Satisfaction has been seen to be the most significant variable on loyalty and usage intention in marketing and information science terms, which can also be highly related to academic success. In this regard, this study set out to investigate the effects of several variables on the learning processes of 930 e-learning students in the Sakarya University distance learning program. The findings of the research indicated that factors perceived playfulness, perceived ease of use and multimedia content effectiveness had a significant effect on perceived usefulness. Furthermore, it was concluded that satisfaction was affected by perceived usefulness, perceived playfulness and multimedia content effectivenes

  11. Biomechanical approaches to identify and quantify injury mechanisms and risk factors in women's artistic gymnastics.

    Science.gov (United States)

    Bradshaw, Elizabeth J; Hume, Patria A

    2012-09-01

    Targeted injury prevention strategies, based on biomechanical analyses, have the potential to help reduce the incidence and severity of gymnastics injuries. This review outlines the potential benefits of biomechanics research to contribute to injury prevention strategies for women's artistic gymnastics by identification of mechanisms of injury and quantification of the effects of injury risk factors. One hundred and twenty-three articles were retained for review after searching electronic databases using key words, including 'gymnastic', 'biomech*', and 'inj*', and delimiting by language and relevance to the paper aim. Impact load can be measured biomechanically by the use of instrumented equipment (e.g. beatboard), instrumentation on the gymnast (accelerometers), or by landings on force plates. We need further information on injury mechanisms and risk factors in gymnastics and practical methods of monitoring training loads. We have not yet shown, beyond a theoretical approach, how biomechanical analysis of gymnastics can help reduce injury risk through injury prevention interventions. Given the high magnitude of impact load, both acute and accumulative, coaches should monitor impact loads per training session, taking into consideration training quality and quantity such as the control of rotation and the height from which the landings are executed.

  12. Identifying Critical Success Factors for TQM and Employee Performance in Malaysian Automotive Industry: A Literature Review

    Science.gov (United States)

    Nadia Dedy, Aimie; Zakuan, Norhayati; Zaidi Bahari, Ahamad; Ariff, Mohd Shoki Md; Chin, Thoo Ai; Zameri Mat Saman, Muhamad

    2016-05-01

    TQM is a management philosophy embracing all activities through which the needs and expectations of the customer and the community and the goals of the companies are satisfied in the most efficient and cost effective way by maximizing the potential of all workers in a continuing drive for total quality improvement. TQM is very important to the company especially in automotive industry in order for them to survive in the competitive global market. The main objective of this study is to review a relationship between TQM and employee performance. Authors review updated literature on TQM study with two main targets: (a) evolution of TQM considering as a set of practice, (b) and its impacts to employee performance. Therefore, two research questions are proposed in order to review TQM constructs and employee performance measure: (a) Is the set of critical success factors associated with TQM valid as a whole? (b) What is the critical success factors should be considered to measure employee performance in automotive industry?

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

    Directory of Open Access Journals (Sweden)

    Ahmad Abu Turab Naqvi

    2016-09-01

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

  14. Identifying and Quantifying Cultural Factors That Matter to the IT Workforce: An Approach Based on Automated Content Analysis

    DEFF Research Database (Denmark)

    Schmiedel, Theresa; Müller, Oliver; Debortoli, Stefan

    2016-01-01

    builds on 112,610 online reviews of Fortune 500 IT companies collected from Glassdoor, an online platform on which current and former employees can anonymously review companies and their management. We perform an automated content analysis to identify cultural factors that employees emphasize...

  15. Factor analysis in the Genetics of Asthma International Network family study identifies five major quantitative asthma phenotypes

    NARCIS (Netherlands)

    Pillai, S. G.; Tang, Y.; van den Oord, E.; Klotsman, M.; Barnes, K.; Carlsen, K.; Gerritsen, J.; Lenney, W.; Silverman, M.; Sly, P.; Sundy, J.; Tsanakas, J.; von Berg, A.; Whyte, M.; Ortega, H. G.; Anderson, W. H.; Helms, P. J.

    Background Asthma is a clinically heterogeneous disease caused by a complex interaction between genetic susceptibility and diverse environmental factors. In common with other complex diseases the lack of a standardized scheme to evaluate the phenotypic variability poses challenges in identifying the

  16. Identifying and Prioritizing the Key Factors Influencing Customer Decision Making in Buying Organizational Software (A survey about HAMKARAN Co.

    Directory of Open Access Journals (Sweden)

    shahryar Azizi

    2013-07-01

    Full Text Available Expansion of adopting information systems, specially packed software, facilitate managing the organizational process, hence, identification the factors influence customer buying decision is vital for software providers. This mixed method study tried to identify the factors affecting decision making of buying new organizational software, classify and rank them beside. In-depth interviews with 10 customers of Hamkaran system that had the potential of buying new software have been done and content analysis of these interviews revealed some factors in five categories that became the base of questionnaire design. This study is applied in view of aim, and is descriptive-survey in view of entity. Sample of 177 customers of System Group Co. have been chosen for the study. Kruskal-Wallis test and T test of normality showed all factors to be effective. Then the factors have been prioritized using Frideman test which are as follows: buyer`s internal organizational factors, product feature, factors related to sellers organization, factors related to process and selling promotion, market and environmental factors.

  17. Maternal and anaesthesia-related risk factors and incidence of spinal anaesthesia-induced hypotension in elective caesarean section: A multinomial logistic regression.

    Science.gov (United States)

    Fakherpour, Atousa; Ghaem, Haleh; Fattahi, Zeinabsadat; Zaree, Samaneh

    2018-01-01

    Although spinal anaesthesia (SA) is nowadays the preferred anaesthesia technique for caesarean section (CS), it is associated with considerable haemodynamic effects, such as maternal hypotension. This study aimed to evaluate a wide range of variables (related to parturient and anaesthesia techniques) associated with the incidence of different degrees of SA-induced hypotension during elective CS. This prospective study was conducted on 511 mother-infant pairs, in which the mother underwent elective CS under SA. The data were collected through preset proforma containing three parts related to the parturient, anaesthetic techniques and a table for recording maternal blood pressure. It was hypothesized that some maternal (such as age) and anaesthesia-related risk factors (such as block height) were associated with occurance of SA-induced hypotension during elective CS. The incidence of mild, moderate and severe hypotension was 20%, 35% and 40%, respectively. Eventually, ten risk factors were found to be associated with hypotension, including age >35 years, body mass index ≥25 kg/m 2 , 11-20 kg weight gain, gravidity ≥4, history of hypotension, baseline systolic blood pressure (SBP) 100 beats/min in maternal modelling, fluid preloading ≥1000 ml, adding sufentanil to bupivacaine and sensory block height >T 4 in anaesthesia-related modelling ( P < 0.05). Age, body mass index, weight gain, gravidity, history of hypotension, baseline SBP and heart rate, fluid preloading, adding sufentanil to bupivacaine and sensory block hieght were the main risk factors identified in the study for SA-induced hypotension during CS.

  18. Maternal and anaesthesia-related risk factors and incidence of spinal anaesthesia-induced hypotension in elective caesarean section: A multinomial logistic regression

    Directory of Open Access Journals (Sweden)

    Atousa Fakherpour

    2018-01-01

    Full Text Available Background and Aims: Although spinal anaesthesia (SA is nowadays the preferred anaesthesia technique for caesarean section (CS, it is associated with considerable haemodynamic effects, such as maternal hypotension. This study aimed to evaluate a wide range of variables (related to parturient and anaesthesia techniques associated with the incidence of different degrees of SA-induced hypotension during elective CS. Methods: This prospective study was conducted on 511 mother–infant pairs, in which the mother underwent elective CS under SA. The data were collected through preset proforma containing three parts related to the parturient, anaesthetic techniques and a table for recording maternal blood pressure. It was hypothesized that some maternal (such as age and anaesthesia-related risk factors (such as block height were associated with occurance of SA-induced hypotension during elective CS. Results: The incidence of mild, moderate and severe hypotension was 20%, 35% and 40%, respectively. Eventually, ten risk factors were found to be associated with hypotension, including age >35 years, body mass index ≥25 kg/m2, 11–20 kg weight gain, gravidity ≥4, history of hypotension, baseline systolic blood pressure (SBP 100 beats/min in maternal modelling, fluid preloading ≥1000 ml, adding sufentanil to bupivacaine and sensory block height >T4in anaesthesia-related modelling (P < 0.05. Conclusion: Age, body mass index, weight gain, gravidity, history of hypotension, baseline SBP and heart rate, fluid preloading, adding sufentanil to bupivacaine and sensory block hieght were the main risk factors identified in the study for SA-induced hypotension during CS.

  19. Identifying niche-mediated regulatory factors of stem cell phenotypic state: a systems biology approach.

    Science.gov (United States)

    Ravichandran, Srikanth; Del Sol, Antonio

    2017-02-01

    Understanding how the cellular niche controls the stem cell phenotype is often hampered due to the complexity of variegated niche composition, its dynamics, and nonlinear stem cell-niche interactions. Here, we propose a systems biology view that considers stem cell-niche interactions as a many-body problem amenable to simplification by the concept of mean field approximation. This enables approximation of the niche effect on stem cells as a constant field that induces sustained activation/inhibition of specific stem cell signaling pathways in all stem cells within heterogeneous populations exhibiting the same phenotype (niche determinants). This view offers a new basis for the development of single cell-based computational approaches for identifying niche determinants, which has potential applications in regenerative medicine and tissue engineering. © 2017 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

  20. Staphylococcus aureus virulence factors identified by using a high-throughput Caenorhabditis elegans-killing model.

    Science.gov (United States)

    Begun, Jakob; Sifri, Costi D; Goldman, Samuel; Calderwood, Stephen B; Ausubel, Frederick M

    2005-02-01

    Staphylococcus aureus is an important human pathogen that is also able to kill the model nematode Caenorhabditis elegans. We constructed a 2,950-member Tn917 transposon insertion library in S. aureus strain NCTC 8325. Twenty-one of these insertions exhibited attenuated C. elegans killing, and of these, 12 contained insertions in different genes or chromosomal locations. Ten of these 12 insertions showed attenuated killing phenotypes when transduced into two different S. aureus strains, and 5 of the 10 mutants correspond to genes that have not been previously identified in signature-tagged mutagenesis studies. These latter five mutants were tested in a murine renal abscess model, and one mutant harboring an insertion in nagD exhibited attenuated virulence. Interestingly, Tn917 was shown to have a very strong bias for insertions near the terminus of DNA replication.

  1. Previously identified patellar tendinopathy risk factors differ between elite and sub-elite volleyball players.

    Science.gov (United States)

    Janssen, I; Steele, J R; Munro, B J; Brown, N A T

    2015-06-01

    Patellar tendinopathy is the most common knee injury incurred in volleyball, with its prevalence in elite athletes more than three times that of their sub-elite counterparts. The purpose of this study was to determine whether patellar tendinopathy risk factors differed between elite and sub-elite male volleyball players. Nine elite and nine sub-elite male volleyball players performed a lateral stop-jump block movement. Maximum vertical jump, training history, muscle extensibility and strength, three-dimensional landing kinematics (250 Hz), along with lower limb neuromuscular activation patterns (1500 Hz), and patellar tendon loading were collected during each trial. Multivariate analyses of variance (P volleyball players. Interventions designed to reduce landing frequency and improve quadriceps extensibility are recommended to reduce patellar tendinopathy prevalence in volleyball players. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  2. A Systematic Approach to Identify Candidate Transcription Factors that Control Cell Identity

    Directory of Open Access Journals (Sweden)

    Ana C. D’Alessio

    2015-11-01

    Full Text Available Hundreds of transcription factors (TFs are expressed in each cell type, but cell identity can be induced through the activity of just a small number of core TFs. Systematic identification of these core TFs for a wide variety of cell types is currently lacking and would establish a foundation for understanding the transcriptional control of cell identity in development, disease, and cell-based therapy. Here, we describe a computational approach that generates an atlas of candidate core TFs for a broad spectrum of human cells. The potential impact of the atlas was demonstrated via cellular reprogramming efforts where candidate core TFs proved capable of converting human fibroblasts to retinal pigment epithelial-like cells. These results suggest that candidate core TFs from the atlas will prove a useful starting point for studying transcriptional control of cell identity and reprogramming in many human cell types.

  3. Metabolomics analyses identify platelet activating factors and heme breakdown products as Lassa fever biomarkers.

    Directory of Open Access Journals (Sweden)

    Trevor V Gale

    2017-09-01

    Full Text Available Lassa fever afflicts tens of thousands of people in West Africa annually. The rapid progression of patients from febrile illness to fulminant syndrome and death provides incentive for development of clinical prognostic markers that can guide case management. The small molecule profile of serum from febrile patients triaged to the Viral Hemorrhagic Fever Ward at Kenema Government Hospital in Sierra Leone was assessed using untargeted Ultra High Performance Liquid Chromatography Mass Spectrometry. Physiological dysregulation resulting from Lassa virus (LASV infection occurs at the small molecule level. Effects of LASV infection on pathways mediating blood coagulation, and lipid, amino acid, nucleic acid metabolism are manifest in changes in the levels of numerous metabolites in the circulation. Several compounds, including platelet activating factor (PAF, PAF-like molecules and products of heme breakdown emerged as candidates that may prove useful in diagnostic assays to inform better care of Lassa fever patients.

  4. Identifying risk factors for healthcare-associated infections from electronic medical record home address data

    Directory of Open Access Journals (Sweden)

    Rosenman Marc B

    2010-09-01

    Full Text Available Abstract Background Residential address is a common element in patient electronic medical records. Guidelines from the U.S. Centers for Disease Control and Prevention specify that residence in a nursing home, skilled nursing facility, or hospice within a year prior to a positive culture date is among the criteria for differentiating healthcare-acquired from community-acquired methicillin-resistant Staphylococcus aureus (MRSA infections. Residential addresses may be useful for identifying patients residing in healthcare-associated settings, but methods for categorizing residence type based on electronic medical records have not been widely documented. The aim of this study was to develop a process to assist in differentiating healthcare-associated from community-associated MRSA infections by analyzing patient addresses to determine if residence reported at the time of positive culture was associated with a healthcare facility or other institutional location. Results We identified 1,232 of the patients (8.24% of the sample with positive cultures as probable cases of healthcare-associated MRSA based on residential addresses contained in electronic medical records. Combining manual review with linking to institutional address databases improved geocoding rates from 11,870 records (79.37% to 12,549 records (83.91%. Standardization of patient home address through geocoding increased the number of matches to institutional facilities from 545 (3.64% to 1,379 (9.22%. Conclusions Linking patient home address data from electronic medical records to institutional residential databases provides useful information for epidemiologic researchers, infection control practitioners, and clinicians. This information, coupled with other clinical and laboratory data, can be used to inform differentiation of healthcare-acquired from community-acquired infections. The process presented should be extensible with little or no added data costs.

  5. Imaging-Based Screen Identifies Laminin 411 as a Physiologically Relevant Niche Factor with Importance for i-Hep Applications

    Directory of Open Access Journals (Sweden)

    John Ong

    2018-03-01

    Full Text Available Summary: Use of hepatocytes derived from induced pluripotent stem cells (i-Heps is limited by their functional differences in comparison with primary cells. Extracellular niche factors likely play a critical role in bridging this gap. Using image-based characterization (high content analysis; HCA of freshly isolated hepatocytes from 17 human donors, we devised and validated an algorithm (Hepatocyte Likeness Index; HLI for comparing the hepatic properties of cells against a physiological gold standard. The HLI was then applied in a targeted screen of extracellular niche factors to identify substrates driving i-Heps closer to the standard. Laminin 411, the top hit, was validated in two additional induced pluripotent stem cell (iPSC lines, primary tissue, and an in vitro model of α1-antitrypsin deficiency. Cumulatively, these data provide a reference method to control and screen for i-Hep differentiation, identify Laminin 411 as a key niche protein, and underscore the importance of combining substrates, soluble factors, and HCA when developing iPSC applications. : Rashid and colleagues demonstrate the utility of a high-throughput imaging platform for identification of physiologically relevant extracellular niche factors to advance i-Heps closer to their primary tissue counterparts. The extracellular matrix (ECM protein screen identified Laminin 411 as an important niche factor facilitating i-Hep-based disease modeling in vitro. Keywords: iPS hepatocytes, extracellular niche, image-based screening, disease modeling, laminin

  6. A multi-factor GIS method to identify optimal geographic locations for electric vehicle (EV) charging stations

    Science.gov (United States)

    Zhang, Yongqin; Iman, Kory

    2018-05-01

    Fuel-based transportation is one of the major contributors to poor air quality in the United States. Electric Vehicle (EV) is potentially the cleanest transportation technology to our environment. This research developed a spatial suitability model to identify optimal geographic locations for installing EV charging stations for travelling public. The model takes into account a variety of positive and negative factors to identify prime locations for installing EV charging stations in Wasatch Front, Utah, where automobile emission causes severe air pollution due to atmospheric inversion condition near the valley floor. A walkable factor grid was created to store index scores from input factor layers to determine prime locations. 27 input factors including land use, demographics, employment centers etc. were analyzed. Each factor layer was analyzed to produce a summary statistic table to determine the site suitability. Potential locations that exhibit high EV charging usage were identified and scored. A hot spot map was created to demonstrate high, moderate, and low suitability areas for installing EV charging stations. A spatially well distributed EV charging system was then developed, aiming to reduce "range anxiety" from traveling public. This spatial methodology addresses the complex problem of locating and establishing a robust EV charging station infrastructure for decision makers to build a clean transportation infrastructure, and eventually improve environment pollution.

  7. In vivo transcriptional profiling of Listeria monocytogenes and mutagenesis identify new virulence factors involved in infection.

    Directory of Open Access Journals (Sweden)

    Ana Camejo

    2009-05-01

    Full Text Available Listeria monocytogenes is a human intracellular pathogen able to colonize host tissues after ingestion of contaminated food, causing severe invasive infections. In order to gain a better understanding of the nature of host-pathogen interactions, we studied the L. monocytogenes genome expression during mouse infection. In the spleen of infected mice, approximately 20% of the Listeria genome is differentially expressed, essentially through gene activation, as compared to exponential growth in rich broth medium. Data presented here show that, during infection, Listeria is in an active multiplication phase, as revealed by the high expression of genes involved in replication, cell division and multiplication. In vivo bacterial growth requires increased expression of genes involved in adaptation of the bacterial metabolism and stress responses, in particular to oxidative stress. Listeria interaction with its host induces cell wall metabolism and surface expression of virulence factors. During infection, L. monocytogenes also activates subversion mechanisms of host defenses, including resistance to cationic peptides, peptidoglycan modifications and release of muramyl peptides. We show that the in vivo differential expression of the Listeria genome is coordinated by a complex regulatory network, with a central role for the PrfA-SigB interplay. In particular, L. monocytogenes up regulates in vivo the two major virulence regulators, PrfA and VirR, and their downstream effectors. Mutagenesis of in vivo induced genes allowed the identification of novel L. monocytogenes virulence factors, including an LPXTG surface protein, suggesting a role for S-layer glycoproteins and for cadmium efflux system in Listeria virulence.

  8. Reduced Rank Regression

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

    The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

  9. High-throughput metabolic profiling of diverse green Coffea arabica beans identified tryptophan as a universal discrimination factor for immature beans.

    Science.gov (United States)

    Setoyama, Daiki; Iwasa, Keiko; Seta, Harumichi; Shimizu, Hiroaki; Fujimura, Yoshinori; Miura, Daisuke; Wariishi, Hiroyuki; Nagai, Chifumi; Nakahara, Koichi

    2013-01-01

    The maturity of green coffee beans is the most influential determinant of the quality and flavor of the resultant coffee beverage. However, the chemical compounds that can be used to discriminate the maturity of the beans remain uncharacterized. We herein analyzed four distinct stages of maturity (immature, semi-mature, mature and overripe) of nine different varieties of green Coffea arabica beans hand-harvested from a single experimental field in Hawaii. After developing a high-throughput experimental system for sample preparation and liquid chromatography-mass spectrometry (LC-MS) measurement, we applied metabolic profiling, integrated with chemometric techniques, to explore the relationship between the metabolome and maturity of the sample in a non-biased way. For the multivariate statistical analyses, a partial least square (PLS) regression model was successfully created, which allowed us to accurately predict the maturity of the beans based on the metabolomic information. As a result, tryptophan was identified to be the best contributor to the regression model; the relative MS intensity of tryptophan was higher in immature beans than in those after the semi-mature stages in all arabica varieties investigated, demonstrating a universal discrimination factor for diverse arabica beans. Therefore, typtophan, either alone or together with other metabolites, may be utilized for traders as an assessment standard when purchasing qualified trading green arabica bean products. Furthermore, our results suggest that the tryptophan metabolism may be tightly linked to the development of coffee cherries and/or beans.

  10. Galectin-3 and Beclin1/Atg6 genes in human cancers: using cDNA tissue panel, qRT-PCR, and logistic regression model to identify cancer cell biomarkers.

    Directory of Open Access Journals (Sweden)

    Halliday A Idikio

    Full Text Available Cancer biomarkers are sought to support cancer diagnosis, predict cancer patient response to treatment and survival. Identifying reliable biomarkers for predicting cancer treatment response needs understanding of all aspects of cancer cell death and survival. Galectin-3 and Beclin1 are involved in two coordinated pathways of programmed cell death, apoptosis and autophagy and are linked to necroptosis/necrosis. The aim of the study was to quantify galectin-3 and Beclin1 mRNA in human cancer tissue cDNA panels and determine their utility as biomarkers of cancer cell survival.A panel of 96 cDNAs from eight (8 different normal and cancer tissue types were used for quantitative real-time polymerase chain reaction (qRT-PCR using ABI7900HT. Miner2.0, a web-based 4- and 3-parameter logistic regression software was used to derive individual well polymerase chain reaction efficiencies (E and cycle threshold (Ct values. Miner software derived formula was used to calculate mRNA levels and then fold changes. The ratios of cancer to normal tissue levels of galectin-3 and Beclin1 were calculated (using the mean for each tissue type. Relative mRNA expressions for galectin-3 were higher than for Beclin1 in all tissue (normal and cancer types. In cancer tissues, breast, kidney, thyroid and prostate had the highest galectin-3 mRNA levels compared to normal tissues. High levels of Beclin1 mRNA levels were in liver and prostate cancers when compared to normal tissues. Breast, kidney and thyroid cancers had high galectin-3 levels and low Beclin1 levels.Galectin-3 expression patterns in normal and cancer tissues support its reported roles in human cancer. Beclin1 expression pattern supports its roles in cancer cell survival and in treatment response. qRT-PCR analysis method used may enable high throughput studies to generate molecular biomarker sets for diagnosis and predicting cancer treatment response.

  11. Genome-Wide Analysis to Identify HLA Factors Potentially Associated With Severe Dengue

    Directory of Open Access Journals (Sweden)

    Sudheer Gupta

    2018-04-01

    Full Text Available The pathogenesis of dengue hemorrhagic fever (DHF, following dengue virus (DENV infection, is a complex and poorly understood phenomenon. In view of the clinical need of identifying patients with higher likelihood of developing this severe outcome, we undertook a comparative genome-wide association analysis of epitope variants from sequences available in the ViPR database that have been reported to be differentially related to dengue fever and DHF. Having enumerated the incriminated epitope variants, we determined the corresponding HLA alleles in the context of which DENV infection could potentially precipitate DHF. Our analysis considered the development of DHF in three different perspectives: (a as a consequence of primary DENV infection, (b following secondary DENV infection with a heterologous serotype, (c as a result of DENV infection following infection with related flaviviruses like Zika virus, Japanese Encephalitis virus, West Nile virus, etc. Subject to experimental validation, these viral and host markers would be valuable in triaging DENV-infected patients for closer supervision owing to the relatively higher risk of poor prognostic outcome and also for the judicious allocation of scarce institutional resources during large outbreaks.

  12. Identifying The Effective Factors for Cost Overrun and Time Delay in Water Construction Projects

    Directory of Open Access Journals (Sweden)

    D. Mirzai Matin

    2016-08-01

    Full Text Available Water construction projects in Iran frequently face problems which cause cost overrun and time delay, the two most common issues in construction projects in general. The objective of this survey is to identify and quantify these problems and thus help in avoiding them. This survey represents a collection of the most significant problems found in the literature, classified into 11 groups according to their source. The questionnaire form used contains 84 questions which were answered by random engineers who work in water construction projects. The Relative Importance Weight (RIW method is used to weight the importance of each one of the 84 problems. The focus of this survey is on overall top ten issues which are: bureaucracy in bidding method, inflation, economical condition of the government, not enough information gathered and surveys done before design, monthly payment difficulties, material cost changes, law changes by the government, financial difficulties, mode of financing and payment for completed work and changes made by the owner. A section for each of these issues provides additional information about them. In the full text of this survey the same weighting method is used to classify the main groups, and the results show that issues related to the groups of government, owner and consultant has the most significant impact. The last part of this survey describes the point of view of the engineers who took part in this survey and the recommendations they made.

  13. Tools to identify linear combination of prognostic factors which maximizes area under receiver operator curve.

    Science.gov (United States)

    Todor, Nicolae; Todor, Irina; Săplăcan, Gavril

    2014-01-01

    The linear combination of variables is an attractive method in many medical analyses targeting a score to classify patients. In the case of ROC curves the most popular problem is to identify the linear combination which maximizes area under curve (AUC). This problem is complete closed when normality assumptions are met. With no assumption of normality search algorithm are avoided because it is accepted that we have to evaluate AUC n(d) times where n is the number of distinct observation and d is the number of variables. For d = 2, using particularities of AUC formula, we described an algorithm which lowered the number of evaluations of AUC from n(2) to n(n-1) + 1. For d > 2 our proposed solution is an approximate method by considering equidistant points on the unit sphere in R(d) where we evaluate AUC. The algorithms were applied to data from our lab to predict response of treatment by a set of molecular markers in cervical cancers patients. In order to evaluate the strength of our algorithms a simulation was added. In the case of no normality presented algorithms are feasible. For many variables computation time could be increased but acceptable.

  14. Orthopedic Surgery among Patients with Rheumatoid Arthritis: A Population-based study to Identify Risk factors, Sex differences, and Time trends.

    Science.gov (United States)

    Richter, Michael; Crowson, Cynthia S; Matteson, Eric L; Makol, Ashima

    2017-12-20

    To identify risk factors for large joint (LJS) versus small joint surgery (SJS) in rheumatoid arthritis (RA) and evaluate trends in surgery rates over time. A retrospective medical record review was performed of all orthopedic surgeries following first fulfillment of 1987 ACR criteria for adult-onset RA among residents of Olmsted County, Minnesota, USA in 1980-2013. Risk factors were examined using Cox models adjusted for age, sex and calendar year of RA incidence. Trends in incidence of joint surgeries were examined using Poisson regression models. A total of 1077 patients with RA (mean age 56 years, 69% female, 66% seropositive) were followed for a median of 10.7 years during which 112 (90 women) underwent at least one SJS and 204 (141 women) underwent at least one LJS. Risk factors included advanced age, rheumatoid factor and anti-CCP antibody positivity for both SJS and LJS, and BMI≥30 kg/m 2 for LJS. Risk factors for SJS and LJS at any time during follow-up included the presence of radiographic erosions, large joint swelling, and methotrexate use. SJS rates decreased by calendar year of incidence (hazard ratio 0.53; p=0.001), with significant decline in SJS after 1995. The cumulative incidence of SJS was higher in women than men (p=0.008). In recent years, there has been a significant decline in rates of SJS but not LJS in patients with RA. The incidence of SJS is higher among women. Traditional RA risk factors are strong predictors for SJS and LJS. Increasing age and obesity are predictive of LJS. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  15. A comparative study to identify factors of caregiver burden between baby boomers and post baby boomers: a secondary analysis of a US online caregiver survey.

    Science.gov (United States)

    Kim, Heejung; Lee, Sangeun; Cheon, Jooyoung; Hong, Soyun; Chang, Mido

    2018-05-02

    Baby boomers' position in the caregiving context is shifting from caregiver to care recipient as the population ages. While the unique characteristics of baby boomer caregivers are well established in caregiving literature, there is limited information about the next caregiving group after the baby boomers. In this study, the sociodemographic and caregiving-related characteristics of the two generations are compared and specific factors contributing to caregiver burden between baby boomer and post baby boomer caregivers are identified. This cross-sectional and correlational study used secondary analysis of data from the National Alliance for Caregiving and the American Association of Retired Persons. A structured online survey was conducted in 2014 with randomly selected samples (n = 1069) in the United States focusing on sociodemographics, caregiving-related characteristics, and burden of care. Descriptive statistics, multivariate linear regression analyses, and Steiger's Z-test were used to identify group differences in multivariate factors related to caregiver burden in two generational groups. Baby boomers and post baby boomers experienced caregiver burden to a similar degree. Caregiving-related factors are more likely to increase burden of care than sociodemographics in both groups. Caregiving without choice and spending longer hours on caregiving tasks were common factors that increased the burden in both generational groups (all p values baby boomer caregivers reported additional challenges, such as unemployment during caregiving, the dual responsibility of both adult and child care, and a family relationship with the care recipient. Due to the aging population of baby boomers, post baby boomers encounter different challenges related to caregiving burden, which is often considered an additional workload in their life course. Current policy and program tailored to baby boomers should be re-designed to meet the different needs of emerging caregivers

  16. Gender-differences in risk factors for suicidal behaviour identified by perceived burdensomeness, thwarted belongingness and acquired capability: cross-sectional analysis from a longitudinal cohort study.

    Science.gov (United States)

    Donker, Tara; Batterham, Philip J; Van Orden, Kimberly A; Christensen, Helen

    2014-01-01

    The Interpersonal-Psychological Theory of Suicidal Behavior (IPT) is supported by recent epidemiological data. Unique risk factors for the IPT constructs have been identified in community epidemiological studies. Gender differences in these risk factors may contribute substantially to our understanding of suicidal risk, and require further investigation. The present study explores gender differences in the predictors and correlates of perceived burdensomeness, thwarted belongingness and acquired capability for suicide. Participants (547 males, 739 females) aged 32-38 from the PATH through Life study, an Australian population-based longitudinal cohort study (n=1,177) were assessed on perceived burdensomeness, thwarted belongingness and acquired capability for suicide using the Interpersonal Needs Questionnaire and Acquired Capability for Suicide Survey, and on a range of demographic, social support, psychological, mental health and physical health measures. Gender differences in the predictors of the IPT constructs were assessed using linear regression analyses. Higher perceived burdensomeness increased suicide ideation in both genders, while higher thwarted belongingness increased suicide ideation only in females. In females, thwarted belongingness was uniquely related to perceived burdensomeness, while greater physical health was significantly associated with greater thwarted belongingness in males but not in females. There were trends suggesting greater effects of being single and greater perceived burdensomeness for men, and stronger effects of less positive friendship support for women associated with greater thwarted belongingness. Men and women differ in the pattern of psychological characteristics that predict suicide ideation, and in the factors predicting vulnerability. Suicide prevention strategies need to take account of gender differences.

  17. Genome-wide association study identifies HLA 8.1 ancestral haplotype alleles as major genetic risk factors for myositis phenotypes.

    Science.gov (United States)

    Miller, F W; Chen, W; O'Hanlon, T P; Cooper, R G; Vencovsky, J; Rider, L G; Danko, K; Wedderburn, L R; Lundberg, I E; Pachman, L M; Reed, A M; Ytterberg, S R; Padyukov, L; Selva-O'Callaghan, A; Radstake, T R; Isenberg, D A; Chinoy, H; Ollier, W E R; Scheet, P; Peng, B; Lee, A; Byun, J; Lamb, J A; Gregersen, P K; Amos, C I

    2015-10-01

    Autoimmune muscle diseases (myositis) comprise a group of complex phenotypes influenced by genetic and environmental factors. To identify genetic risk factors in patients of European ancestry, we conducted a genome-wide association study (GWAS) of the major myositis phenotypes in a total of 1710 cases, which included 705 adult dermatomyositis, 473 juvenile dermatomyositis, 532 polymyositis and 202 adult dermatomyositis, juvenile dermatomyositis or polymyositis patients with anti-histidyl-tRNA synthetase (anti-Jo-1) autoantibodies, and compared them with 4724 controls. Single-nucleotide polymorphisms showing strong associations (Pmyositis phenotypes together, as well as for the four clinical and autoantibody phenotypes studied separately. Imputation and regression analyses found that alleles comprising the human leukocyte antigen (HLA) 8.1 ancestral haplotype (AH8.1) defined essentially all the genetic risk in the phenotypes studied. Although the HLA DRB1*03:01 allele showed slightly stronger associations with adult and juvenile dermatomyositis, and HLA B*08:01 with polymyositis and anti-Jo-1 autoantibody-positive myositis, multiple alleles of AH8.1 were required for the full risk effects. Our findings establish that alleles of the AH8.1 comprise the primary genetic risk factors associated with the major myositis phenotypes in geographically diverse Caucasian populations.

  18. Use of physical activity and cardiorespiratory fitness in identifying cardiovascular risk factors in male brazilian adolescents

    Directory of Open Access Journals (Sweden)

    Lilian Messias Sampaio Brito

    2016-02-01

    Full Text Available DOI: http://dx.doi.org/10.5007/1980-0037.2016v18n6p678   The aim of this study was to investigate the impact of physical activity (PA and cardiorespiratory fitness (CRF levels on the prevalence of overweight and high blood pressure levels in adolescents. In this observational, cross-sectional study, 614 boys aged 10-14 years were assessed for height, body mass, body mass index (BMI, waist circumference (WC and blood pressure (BP. CRF was assessed using a run test (Léger Test and subjects were then grouped according to their CRF level. PA level was assessed through a questionnaire (The Three Day Physical Activity Recall and classified into two groups, namely > 300 minutes of PA/week and < 300 minutes of PA/week. Maturational stage was evaluated according to the development of pubic hair (self-assessment as proposed by Tanner. We used statistical descriptive analysis, univariate and multivariate analyses in the total participants and subjects were divided by age. Fifty percent of the sample performed < 300 minutes of PA/week and 67.6% had unsatisfactory CRF levels. There was a higher prevalence of unsatisfactory CRF levels among subjects with altered BMI (overweight, WC (abdominal obesity or BP (high blood pressure for all age groups. PA history, however, did not show any significance. A total of 31% of participants were overweight, 24.8% had abdominal obesity and 15.4% had increased BP. Unsatisfactory CRF levels were found to be a better predictor for the diagnosis of cardiovascular diseases (CV risk factors than PA history, regardless of age group.

  19. Applying psychological theories to evidence-based clinical practice: Identifying factors predictive of managing upper respiratory tract infections without antibiotics

    Directory of Open Access Journals (Sweden)

    Glidewell Elizabeth

    2007-08-01

    try to avoid the use of antibiotics made significantly fewer scenario-based decisions to prescribe. In the cross theory analysis, perceived behavioural control (TPB, evidence of habitual behaviour (OLT, CS-SRM cause (chance/bad luck, and intention entered the equation, together explaining 36% of the variance. When predicting intention, at the theory level, the proportion of variance explained was: TPB, 30%; SCT, 29%; CS-SRM 27%; OLT, 43%. GPs who reported that they had already decided to change their management to try to avoid the use of antibiotics had a significantly higher intention to manage URTIs without prescribing antibiotics. In the cross theory analysis, OLT evidence of habitual behaviour, TPB attitudes, risk perception, CS-SRM control by doctor, TPB perceived behavioural control and CS-SRM control by treatment entered the equation, together explaining 49% of the variance in intention. Conclusion The study provides evidence that psychological models can be useful in understanding and predicting clinical behaviour. Taking a theory-based approach enables the creation of a replicable methodology for identifying factors that predict clinical behaviour. However, a number of conceptual and methodological challenges remain.

  20. IDENTIFYING ELEVEN FACTORS OF SERVICE MARKETING MIX (4PS) EFFECTIVE ON TENDENCY OF PATIENTS TOWARD PRIVATE HOSPITAL.

    Science.gov (United States)

    Hosseini, Seyed Mojtaba; Etesaminia, Samira; Jafari, Mehrnoosh

    2016-10-01

    One of the important factors of correct management is to identify the reasons for patient tendency toward private hospitals. This study measures these factors based on service marketing mixes. This study used a cross sectional descriptive methodology. The study was conducted during 6 months in 2015. The studied population included patients of private hospitals in Tehran. Random sampling was used (n = 200). Data was collected by an author-made questionnaire for service marketing factors. Reliability and validity of the questionnaire were confirmed. Data analysis was done using factor analysis test in SPSS 20. The results showed that constant attendance of physicians and nurses has the highest effect (0.707%) on patient tendency toward private hospitals.

  1. IDENTIFYING ELEVEN FACTORS OF SERVICE MARKETING MIX (4PS) EFFECTIVE ON TENDENCY OF PATIENTS TOWARD PRIVATE HOSPITAL

    Science.gov (United States)

    Hosseini, Seyed Mojtaba; Etesaminia, Samira; Jafari, Mehrnoosh

    2016-01-01

    Introduction: One of the important factors of correct management is to identify the reasons for patient tendency toward private hospitals. This study measures these factors based on service marketing mixes. Patients and methods: This study used a cross sectional descriptive methodology. The study was conducted during 6 months in 2015. The studied population included patients of private hospitals in Tehran. Random sampling was used (n = 200). Data was collected by an author-made questionnaire for service marketing factors. Reliability and validity of the questionnaire were confirmed. Data analysis was done using factor analysis test in SPSS 20. Results: The results showed that constant attendance of physicians and nurses has the highest effect (0.707%) on patient tendency toward private hospitals. PMID:27999486

  2. Identifying the Effective Factors in Making Trust in Online Social Networks on the perspective of Iranian experts Using Fuzzy ELECTRE

    Directory of Open Access Journals (Sweden)

    Elham Haghighi

    2015-12-01

    Full Text Available this paper attempts to rank the effective factors in making trust in social networks to provide the possibility of attracting and increasing users’ trust on these social networks for providers and designers of online social networks. Identifying the effective factors in making trust in social networks is a multi-criteria decision making problem and most of effective factors are ambiguous and uncertain, thereby this article uses Fuzzy ELECTRE to rank them. By implementing Fuzzy ELECTRE on gathered data, respectively «usability factor», «supporting up to date technology factor», «integrity» and «the rate of ethics factor» are on the top of effective factors in making trust in users. In general, «web features» and «technology features» have a higher degree of importance than «security features», «individual-social features» and «cultural features». Ranking of Fuzzy ELECTRE comparison ranking of Fuzzy TOPSIS and Fuzzy ELECTRE method becomes validate because Spearman correlation coefficients is 0/867. Result of sensitivity analysis on changing weight of criteria shows that Fuzzy ELECTRE isn’t affected by ambiguity and uncertainty in inputs.

  3. Identifying the principal driving factors of water ecosystem dependence and the corresponding indicator species in a pilot City, China

    Science.gov (United States)

    Zhao, C. S.; Shao, N. F.; Yang, S. T.; Xiang, H.; Lou, H. Z.; Sun, Y.; Yang, Z. Y.; Zhang, Y.; Yu, X. Y.; Zhang, C. B.; Yu, Q.

    2018-01-01

    The world's aquatic ecosystems yield numerous vital services, which are essential to human existence but have deteriorated seriously in recent years. By studying the mechanisms of interaction between ecosystems and habitat processes, the constraining factors can be identified, and this knowledge can be used to improve the success rate of ecological restoration initiatives. At present, there is insufficient data on the link between hydrological, water quality factors and the changes in the structure of aquatic communities to allow any meaningful study of driving factors of aquatic ecosystems. In this study, the typical monitoring stations were selected by fuzzy clustering analysis based on the spatial and temporal distribution characteristics of water ecology in Jinan City, the first pilot city for the construction of civilized aquatic ecosystems in China. The dominant species identification model was used to identify the dominant species of the aquatic community. The driving effect of hydrological and water quality factors on dominant species was analyzed by Canonical Correspondence Analysis. Then, the principal factors of aquatic ecosystem dependence were selected. The results showed that there were 10 typical monitoring stations out of 59 monitoring sites, which were representative of aquatic ecosystems, 9 dominant fish species, and 20 dominant invertebrate species. The selection of factors for aquatic ecosystem dependence in Jinan were highly influenced by its regional conditions. Chemical environmental parameters influence the temporal and spatial variation of invertebrate much more than that of fish in Jinan City. However, the methodologies coupling typical monitoring stations selection, dominant species determination and driving factors identification were certified to be a cost-effective way, which can provide in-deep theoretical and technical directions for the restoration of aquatic ecosystems elsewhere.

  4. Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance tool.

    Science.gov (United States)

    Auerbach, Raymond K; Chen, Bin; Butte, Atul J

    2013-08-01

    Biological analysis has shifted from identifying genes and transcripts to mapping these genes and transcripts to biological functions. The ENCODE Project has generated hundreds of ChIP-Seq experiments spanning multiple transcription factors and cell lines for public use, but tools for a biomedical scientist to analyze these data are either non-existent or tailored to narrow biological questions. We present the ENCODE ChIP-Seq Significance Tool, a flexible web application leveraging public ENCODE data to identify enriched transcription factors in a gene or transcript list for comparative analyses. The ENCODE ChIP-Seq Significance Tool is written in JavaScript on the client side and has been tested on Google Chrome, Apple Safari and Mozilla Firefox browsers. Server-side scripts are written in PHP and leverage R and a MySQL database. The tool is available at http://encodeqt.stanford.edu. abutte@stanford.edu Supplementary material is available at Bioinformatics online.

  5. Global analysis of WRKY transcription factor superfamily in Setaria identifies potential candidates involved in abiotic stress signaling

    OpenAIRE

    Muthamilarasan, Mehanathan; Bonthala, Venkata S.; Khandelwal, Rohit; Jaishankar, Jananee; Shweta, Shweta; Nawaz, Kashif; Prasad, Manoj

    2015-01-01

    Transcription factors (TFs) are major players in stress signalling and constitute an integral part of signalling networks. Among the major TFs, WRKY proteins play pivotal roles in regulation of transcriptional reprogramming associated with stress responses. In view of this, genome- and transcriptome-wide identification of WRKY TF family was performed in the C4 model plants, Setaria italica (SiWRKY) and S. viridis (SvWRKY), respectively. The study identified 105 SiWRKY and 44 SvWRKY proteins t...

  6. Tumor regression patterns in retinoblastoma

    International Nuclear Information System (INIS)

    Zafar, S.N.; Siddique, S.N.; Zaheer, N.

    2016-01-01

    To observe the types of tumor regression after treatment, and identify the common pattern of regression in our patients. Study Design: Descriptive study. Place and Duration of Study: Department of Pediatric Ophthalmology and Strabismus, Al-Shifa Trust Eye Hospital, Rawalpindi, Pakistan, from October 2011 to October 2014. Methodology: Children with unilateral and bilateral retinoblastoma were included in the study. Patients were referred to Pakistan Institute of Medical Sciences, Islamabad, for chemotherapy. After every cycle of chemotherapy, dilated funds examination under anesthesia was performed to record response of the treatment. Regression patterns were recorded on RetCam II. Results: Seventy-four tumors were included in the study. Out of 74 tumors, 3 were ICRB group A tumors, 43 were ICRB group B tumors, 14 tumors belonged to ICRB group C, and remaining 14 were ICRB group D tumors. Type IV regression was seen in 39.1% (n=29) tumors, type II in 29.7% (n=22), type III in 25.6% (n=19), and type I in 5.4% (n=4). All group A tumors (100%) showed type IV regression. Seventeen (39.5%) group B tumors showed type IV regression. In group C, 5 tumors (35.7%) showed type II regression and 5 tumors (35.7%) showed type IV regression. In group D, 6 tumors (42.9%) regressed to type II non-calcified remnants. Conclusion: The response and success of the focal and systemic treatment, as judged by the appearance of different patterns of tumor regression, varies with the ICRB grouping of the tumor. (author)

  7. Regression analysis by example

    CERN Document Server

    Chatterjee, Samprit

    2012-01-01

    Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded

  8. A Global Interactome Map of the Dengue Virus NS1 Identifies Virus Restriction and Dependency Host Factors

    Directory of Open Access Journals (Sweden)

    Mohamed Lamine Hafirassou

    2017-12-01

    Full Text Available Dengue virus (DENV infections cause the most prevalent mosquito-borne viral disease worldwide, for which no therapies are available. DENV encodes seven non-structural (NS proteins that co-assemble and recruit poorly characterized host factors to form the DENV replication complex essential for viral infection. Here, we provide a global proteomic analysis of the human host factors that interact with the DENV NS1 protein. Combined with a functional RNAi screen, this study reveals a comprehensive network of host cellular processes involved in DENV infection and identifies DENV host restriction and dependency factors. We highlight an important role of RACK1 and the chaperonin TRiC (CCT and oligosaccharyltransferase (OST complexes during DENV replication. We further show that the OST complex mediates NS1 and NS4B glycosylation, and pharmacological inhibition of its N-glycosylation function strongly impairs DENV infection. In conclusion, our study provides a global interactome of the DENV NS1 and identifies host factors targetable for antiviral therapies.

  9. Identifying non-pharmacological risk factors for falling in older adults with type 2 diabetes mellitus: a systematic review.

    Science.gov (United States)

    Gravesande, Janelle; Richardson, Julie

    2017-07-01

    To identify the non-pharmacological risk factors for falling in older adults with type 2 diabetes mellitus (DM2). A systematic review of randomized controlled trials, prospective cohort studies, cross-sectional studies and before/after studies was conducted. Eligible studies identified non-pharmacological risk factors for falling in older adults with DM2. Medline, Embase, Pubmed and CINAHL were searched for relevant studies published through December 2015. Reference lists were also searched for relevant studies. Search terms were DM2, risk factors, falls and falling, older adults, aging, non-insulin dependent diabetes mellitus, accidental falls and trip. Publication language was restricted to English. Thirteen studies met the inclusion criteria: four cross-sectional, six prospective cohorts, two randomized controlled trials and one before/after study. These studies included a total of 13,104 participants, ≥50 years. The most common risk factors for falling were impaired balance, reduced walking velocity, peripheral neuropathy and comorbid conditions. However, lower extremity pain, being overweight and comorbid conditions had the greatest impact on fall risk. Interventions to reduce falling in older adults with type 2 diabetes mellitus should focus on reducing lower extremity pain, reducing body weight and managing comorbid conditions. Implications for Rehabilitation    Diabetes mellitus:   • Older adults with type 2 diabetes mellitus (DM2) have a higher risk for falling than older adults without.   • Older adults with DM2 are more likely to suffer serious injuries when they fall.   • Comprehensive risk factor identification is necessary for rehabilitation professionals to accurately determine whether their clients are at risk for falling.   • Rehabilitation professionals also need to tailor interventions based on the client's risk factors in order to effectively reduce falls and fall-related injuries.

  10. Identifying socio-environmental factors that facilitate resilience among Canadian palliative family caregivers: a qualitative case study.

    Science.gov (United States)

    Giesbrecht, Melissa; Wolse, Faye; Crooks, Valorie A; Stajduhar, Kelli

    2015-06-01

    In Canada, friends and family members are becoming increasingly responsible for providing palliative care in the home. This is resulting in some caregivers experiencing high levels of stress and burden that may ultimately surpass their ability to cope. Recent palliative care research has demonstrated the potential for caregiver resilience within such contexts. This research, however, is primarily focused on exploring individual-level factors that contribute to resilience, minimizing the inherent complexity of this concept, and how it is simultaneously influenced by one's social context. Therefore, our study aims to identify socio-environmental factors that contribute to palliative family caregiver resilience in the Canadian homecare context. Drawing on ethnographic fieldnotes and semistructured interviews with family caregivers, care recipients, and homecare nurses, this secondary analysis employs an intersectionality lens and qualitative case study approach to identify socio-environmental factors that facilitate family caregivers' capacity for resilience. Following a case study methodology, two cases are purposely selected for analysis. Findings demonstrate that family caregiver resilience is influenced not only by individual-level factors but also by the social environment, which sets the lived context from which caregiving roles are experienced. Thematic findings of the two case studies revealed six socio-environmental factors that play a role in shaping resilience: access to social networks, education/knowledge/awareness, employment status, housing status, geographic location, and life-course stage. Findings contribute to existing research on caregiver resilience by empirically demonstrating the role of socio-environmental factors in caregiving experiences. Furthermore, utilizing an intersectional approach, these findings build on existing notions that resilience is a multidimensional and complex process influenced by numerous related variables that intersect

  11. [Milk yield and environmental factors: Multiple regression analysis of the association between milk yield and udder health, fertility data and replacement rate].

    Science.gov (United States)

    Fölsche, C; Staufenbiel, R

    2014-01-01

    The relationship between milk yield and both fertility and general animal health in dairy herds is discussed from opposing viewpoints. The hypothesis (1) that raising the herd milk yield would decrease fertility results, the number of milk cells as an indicator for udder health and the replacement rate as a global indicator for animal health as well as increasing the occurrence of specific diseases as a herd problem was compared to the opposing hypotheses that there is no relationship (2) or that there is a differentiated and changing relationship (3). A total of 743 herd examinations, considered independent, were performed in 489 herds between 1995 and 2010. The milk yield, fertility rate, milk cell count, replacement rate, categorized herd problems and management information were recorded. The relationship between the milk yield and both the fertility data and animal health was evaluated using simple and multiple regression analyses. The period between calving and the first service displayed no significant relationship to the herd milk yield. Simple regression analysis showed that the period between calving and gestation, the calving interval and the insemination number were significantly positively associated with the herd milk yield. This positive correlation was lost in multiple regression analysis. The milk cell count and replacement rate using both the simple and multiple regression analyses displayed a significant negative relationship to the milk yield. The alternative hypothesis (3) was confirmed. A higher milk yield has no negative influence on the milk cell count and the replacement rate in terms of the udder and general health. When parameterizing the fertility, the herd milk yield should be considered. Extending the resting time may increase the milk yield while preventing a decline in the insemination index.

  12. A novel cell growth-promoting factor identified in a B cell leukemia cell line, BALL-1

    International Nuclear Information System (INIS)

    Dao, T.; Holan, V.; Minowada, J.

    1993-01-01

    A novel leukemia cell growth-promoting activity has been identified in the culture supernatant from a human B cell leukemia cell line, BALL-1. The supernatant from unstimulated cultures of the BALL-1 cells significantly promoted the growth of 16 out of 24 leukemia/lymphoma cell lines of different lineages (T, B and non-lymphoid) in a minimal concentration of fetal bovine serum (FBS), and 5 out of 12 cases of fresh leukemia cells in FBS-free medium. The growth-promoting sieve filtration and dialysis. The MW of the factor was less than 10 kDa. The growth-promoting activity was heat and acid stable and resistant to trypsin treatment. The factor isolated from the BALL-1 supernatant was distinct from known polypeptide growth factors with MW below 10 kDa, such as epidermal growth factor, transforming growth factor α, insulin-like growth factor I (IGF-I), IGF-II and insulin, as determine by specific antibodies and by cell-growth-promoting tests. The factor is the BALL-1 supernatant did not promote the proliferation of normal human fresh peripheral blood lymphocytes or mouse fibroblast cell line, BALB/C 3T3. In addition to the BALL-1 supernatant, a similar growth-promoting activity was found in the culture supernatant from 13 of 17 leukemia/lymphoma cell lines tested. The activity in these culture supernatant promoted the growth of leukemia/lymphoma cell lines in autocrine and/or paracrine fashions. These observations suggest that the low MW cell growth-promoting activity found in the BALL-1 culture supernatant is mediated by a novel factor which may be responsible for the clonal expansion of particular leukemic clones. (author)

  13. Human Leptospirosis Infection in Fiji: An Eco-epidemiological Approach to Identifying Risk Factors and Environmental Drivers for Transmission.

    Science.gov (United States)

    Lau, Colleen L; Watson, Conall H; Lowry, John H; David, Michael C; Craig, Scott B; Wynwood, Sarah J; Kama, Mike; Nilles, Eric J

    2016-01-01

    Leptospirosis is an important zoonotic disease in the Pacific Islands. In Fiji, two successive cyclones and severe flooding in 2012 resulted in outbreaks with 576 reported cases and 7% case-fatality. We conducted a cross-sectional seroprevalence study and used an eco-epidemiological approach to characterize risk factors and drivers for human leptospirosis infection in Fiji, and aimed to provide an evidence base for improving the effectiveness of public health mitigation and intervention strategies. Antibodies indicative of previous or recent infection were found in 19.4% of 2152 participants (81 communities on the 3 main islands). Questionnaires and geographic information systems data were used to assess variables related to demographics, individual behaviour, contact with animals, socioeconomics, living conditions, land use, and the natural environment. On multivariable logistic regression analysis, variables associated with the presence of Leptospira antibodies included male gender (OR 1.55), iTaukei ethnicity (OR 3.51), living in villages (OR 1.64), lack of treated water at home (OR 1.52), working outdoors (1.64), living in rural areas (OR 1.43), high poverty rate (OR 1.74), living Fiji are complex and multifactorial, with environmental factors playing crucial roles. With global climate change, severe weather events and flooding are expected to intensify in the South Pacific. Population growth could also lead to more intensive livestock farming; and urbanization in developing countries is often associated with urban and peri-urban slums where diseases of poverty proliferate. Climate change, flooding, population growth, urbanization, poverty and agricultural intensification are important drivers of zoonotic disease transmission; these factors may independently, or potentially synergistically, lead to enhanced leptospirosis transmission in Fiji and other similar settings.

  14. Quantile Regression Methods

    DEFF Research Database (Denmark)

    Fitzenberger, Bernd; Wilke, Ralf Andreas

    2015-01-01

    if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights...... by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even...

  15. A case-control study to identify risk factors for totally implantable central venous port-related bloodstream infection.

    Science.gov (United States)

    Lee, Guk Jin; Hong, Sook Hee; Roh, Sang Young; Park, Sa Rah; Lee, Myung Ah; Chun, Hoo Geun; Hong, Young Seon; Kang, Jin Hyoung; Kim, Sang Il; Kim, Youn Jeong; Chun, Ho Jong; Oh, Jung Suk

    2014-07-01

    To date, the risk factors for central venous port-related bloodstream infection (CVPBSI) in solid cancer patients have not been fully elucidated. We conducted this study in order to determine the risk factors for CVP-BSI in patients with solid cancer. A total of 1,642 patients with solid cancer received an implantable central venous port for delivery of chemotherapy between October 2008 and December 2011 in a single center. CVP-BSI was diagnosed in 66 patients (4%). We selected a control group of 130 patients, who were individually matched with respect to age, sex, and catheter insertion time. CVP-BSI occurred most frequently between September and November (37.9%). The most common pathogen was gram-positive cocci (n=35, 53.0%), followed by fungus (n=14, 21.2%). Multivariate analysis identified monthly catheter-stay as a risk factor for CVP-BSI (p=0.000), however, its risk was lower in primary gastrointestinal cancer than in other cancer (p=0.002). Initial metastatic disease and long catheter-stay were statistically significant factors affecting catheter life span (p=0.005 and p=0.000). Results of multivariate analysis showed that recent transfusion was a risk factor for mortality in patients with CVP-BSI (p=0.047). In analysis of the results with respect to risk factors, prolonged catheter-stay should be avoided as much as possible. It is necessary to be cautious of CVP-BSI in metastatic solid cancer, especially non-gastrointestinal cancer. In addition, avoidance of unnecessary transfusion is essential in order to reduce the mortality of CVP-BSI. Finally, considering the fact that confounding factors may have affected the results, conduct of a well-designed prospective controlled study is warranted.

  16. Advanced statistics: linear regression, part II: multiple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

  17. Designing and determining validity and reliability of a questionnaire to identify factors affecting nutritional behavior among patients with metabolic syndrome

    Directory of Open Access Journals (Sweden)

    Naseh Esmaeili

    2017-06-01

    Full Text Available Background : A number of studies have shown a clear relationship between diet and component of metabolic syndrome. Based on the Theory of Reasoned Action (TRA, attitude and subjective norm are factors affecting behavioral intention and subsequently behavior. The aim of the present study is to design a valid questionnaire identifying factors affecting nutritional behavior among patients with metabolic syndrome. Materials and Methods: Via literature review, six focus group discussion and interview with nutrition specialists were performed to develop an instrument based on the theory of reasoned action. To determine validity of the instrument, content and face validity analyses with 15 expert panels conducted and also to determine reliability, Cronbach’s Alpha coefficient performed. Results: A draft of 100 items questionnaire was developed and after evaluation of validity and reliability, final questionnaire included 46 items: 17 items for attitude, 13 items for subjective norms and 16 items for behavioral intention. For the final questionnaire average of content validity index was 0/92 and Cronbach’s Alpha coefficient was 0/85. Conclusion: Based on the results of the current study the developed questionnaire is a valid and reliable instrument and it can be used to identify factors affecting nutritional behavior among people with metabolic syndrome based on the theory of reasoned action.

  18. Identifying the factors influencing practice variation in thrombosis medicine: A qualitative content analysis of published practice-pattern surveys.

    Science.gov (United States)

    Skeith, Leslie; Gonsalves, Carol

    2017-11-01

    Practice variation, the differences in clinical management between physicians, is one reason why patient outcomes may differ. Identifying factors that contribute to practice variation in areas of clinical uncertainty or equipoise may have implications for understanding and improving patient care. To discern what factors may influence practice variation, we completed a qualitative content analysis of all practice-pattern surveys in thrombosis medicine in the last 10years. Out of 2117 articles screened using a systematic search strategy, 33 practice-pattern surveys met eligibility criteria. Themes were identified using constant comparative analysis of qualitative data. Practice variation was noted in all 33 practice-pattern surveys. Contributing factors to variation included lack of available evidence, lack of clear and specific guideline recommendations, past experience, patient context, institutional culture and the perceived risk and benefit of a particular treatment. Additional themes highlight the value placed on expertise in challenging clinical scenarios, the complexity of practice variation and the value placed on minimizing practice variation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. T cell receptor (TCR-transgenic CD8 lymphocytes rendered insensitive to transforming growth factor beta (TGFβ signaling mediate superior tumor regression in an animal model of adoptive cell therapy

    Directory of Open Access Journals (Sweden)

    Quatromoni Jon G

    2012-06-01

    Full Text Available Abstract Tumor antigen-reactive T cells must enter into an immunosuppressive tumor microenvironment, continue to produce cytokine and deliver apoptotic death signals to affect tumor regression. Many tumors produce transforming growth factor beta (TGFβ, which inhibits T cell activation, proliferation and cytotoxicity. In a murine model of adoptive cell therapy, we demonstrate that transgenic Pmel-1 CD8 T cells, rendered insensitive to TGFβ by transduction with a TGFβ dominant negative receptor II (DN, were more effective in mediating regression of established B16 melanoma. Smaller numbers of DN Pmel-1 T cells effectively mediated tumor regression and retained the ability to produce interferon-γ in the tumor microenvironment. These results support efforts to incorporate this DN receptor in clinical trials of adoptive cell therapy for cancer.

  20. Using the community pharmacy to identify patients at risk of poor asthma control and factors which contribute to this poor control.

    Science.gov (United States)

    Armour, Carol L; Lemay, Kate; Saini, Bandana; Reddel, Helen K; Bosnic-Anticevich, Sinthia Z; Smith, Lorraine D; Burton, Deborah; Song, Yun Ju Christine; Alles, Marie Chehani; Stewart, Kay; Emmerton, Lynne; Krass, Ines

    2011-11-01

    Although asthma can be well controlled by appropriate medication delivered in an appropriate way at an appropriate time, there is evidence that management is often suboptimal. This results in poor asthma control, poor quality of life, and significant morbidity. The objective of this study was to describe a population recruited in community pharmacy identified by trained community pharmacists as being at risk for poor asthma outcomes and to identify factors associated with poor asthma control. It used a cross-sectional design in 96 pharmacies in metropolitan and regional New South Wales, Victoria, Queensland, and Australian Capital Territory in Australia. Community pharmacists with specialized asthma training enrolled 570 patients aged ≥18 years with doctor-diagnosed asthma who were considered at risk of poor asthma outcomes and then conducted a comprehensive asthma assessment. In this assessment, asthma control was classified using a symptom and activity tool based on self-reported frequency of symptoms during the previous month and categorized as poor, fair, or good. Asthma history was discussed, and lung function and inhaler technique were also assessed by the pharmacist. Medication use/adherence was recorded from both pharmacy records and the Brief Medication Questionnaire (BMQ). The symptom and activity tool identified that 437 (77%) recruited patients had poor asthma control. Of the 570 patients, 117 (21%) smoked, 108 (19%) had an action plan, 372 (69%) used combination of inhaled corticosteroid (ICS)/long-acting β(2)-agonist (LABA) medications, and only 17-28% (depending on device) used their inhaler device correctly. In terms of adherence, 90% had their ICS or ICS/LABA dispensed <6 times in the previous 6 months, which is inconsistent with regular use; this low adherence was confirmed from the BMQ scores. A logistic regression model showed that patients who smoked had incorrect inhaler technique or low adherence (assessed by either dispensing history or

  1. Regression Models for Repairable Systems

    Czech Academy of Sciences Publication Activity Database

    Novák, Petr

    2015-01-01

    Roč. 17, č. 4 (2015), s. 963-972 ISSN 1387-5841 Institutional support: RVO:67985556 Keywords : Reliability analysis * Repair models * Regression Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.782, year: 2015 http://library.utia.cas.cz/separaty/2015/SI/novak-0450902.pdf

  2. Identifying critical success factors for designing selection processes into postgraduate specialty training: the case of UK general practice.

    Science.gov (United States)

    Plint, Simon; Patterson, Fiona

    2010-06-01

    The UK national recruitment process into general practice training has been developed over several years, with incremental introduction of stages which have been piloted and validated. Previously independent processes, which encouraged multiple applications and produced inconsistent outcomes, have been replaced by a robust national process which has high reliability and predictive validity, and is perceived to be fair by candidates and allocates applicants equitably across the country. Best selection practice involves a job analysis which identifies required competencies, then designs reliable assessment methods to measure them, and over the long term ensures that the process has predictive validity against future performance. The general practitioner recruitment process introduced machine markable short listing assessments for the first time in the UK postgraduate recruitment context, and also adopted selection centre workplace simulations. The key success factors have been identified as corporate commitment to the goal of a national process, with gradual convergence maintaining locus of control rather than the imposition of change without perceived legitimate authority.

  3. Principal component regression analysis with SPSS.

    Science.gov (United States)

    Liu, R X; Kuang, J; Gong, Q; Hou, X L

    2003-06-01

    The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

  4. Screening for type 2 diabetes in a multiethnic setting using known risk factors to identify those at high risk

    DEFF Research Database (Denmark)

    Gray, Laura J.; Tringham, Jennifer R.; Davies, Melanie J.

    2010-01-01

    population to identify those with abnormal glucose tolerance. ethods: A sample of individuals aged 25-75 years (40-75 white European) with at least one risk factor for T2DM were invited for screening from 17 Leicestershire (UK) general practices or through a health awareness campaign. All participants...... received a 75 g oral glucose tolerance test, cardiovascular risk assessment, detailed medical and family histories and anthropometric measurements. Results: In the 3,225 participants who were screened. 640 (20%) were found to have some form of abnormal glucose tolerance of whom 4% had T2DM, 3% impaired...

  5. Resident and Facility Factors Associated With the Incidence of Urinary Tract Infections Identified in the Nursing Home Minimum Data Set.

    Science.gov (United States)

    Castle, Nicholas; Engberg, John B; Wagner, Laura M; Handler, Steven

    2017-02-01

    This research examined resident and facility-specific factors associated with a diagnosis of a urinary tract infection (UTI) in the nursing home setting. Minimum Data Set and Online Survey, Certification and Reporting system data were used to identify all nursing home residents in the United States on April 1, 2006, who did not have a UTI ( n = 1,138,418). Residents were followed until they contracted a UTI (9.5%), died (8.3%), left the nursing home (33.2%), or the year ended (49.0%). A Cox proportional hazards model was estimated, controlling for resident and facility characteristics and for the state of residence. The presence of an indwelling catheter was the primary predictor of whether a resident contracted a UTI (adjusted incidence ratio = 3.35, p factors such as percentage of Medicaid residents, for-profit, and chain status was less significant. Estimates regarding staffing levels indicate that increased contact hours with more highly educated nursing staff are associated with less catheter use. Several facility-specific risk factors are of significance. Of significance, UTIs may be reduced by modifying factors such as staffing levels.

  6. Identifying cognitive complexity factors affecting the complexity of procedural steps in emergency operating procedures of a nuclear power plant

    International Nuclear Information System (INIS)

    Park, Jinkyun; Jeong, Kwangsup; Jung, Wondea

    2005-01-01

    In complex systems such as a nuclear and chemical plant, it is well known that the provision of understandable procedures that allow operators to clarify what needs to be done and how to do it is one of the requisites to secure their safety. As a previous study in providing understandable procedures, the step complexity (SC) measure that can quantify the complexity of procedural steps in emergency operating procedures (EOPs) of a nuclear power plant (NPP) was suggested. However, the necessity of additional complexity factors that can consider a cognitive aspect in evaluating the complexity of procedural steps is raised. To this end, the comparisons between operators' performance data measured by the form of a step performance time with their behavior in carrying out the prescribed activities of procedural steps are conducted in this study. As a result, two kinds of complexity factors (the abstraction level of knowledge and the level of engineering decision) that could affect an operator's cognitive burden are identified. Although a well-designed experiment is indispensable for confirming the appropriateness of the additional complexity factors, it is strongly believed that the change of operators' performance data can be more authentically explained if the additional complexity factors are taken into consideration

  7. Identifying cognitive complexity factors affecting the complexity of procedural steps in emergency operating procedures of a nuclear power plant

    Energy Technology Data Exchange (ETDEWEB)

    Park, Jinkyun [Integrated Safety Assessment Division, Korea Atomic Energy Research Institute, P.O. Box 105, Duckjin-Dong, Yusong-Ku, Taejon 305-600 (Korea, Republic of)]. E-mail: kshpjk@kaeri.re.kr; Jeong, Kwangsup [Integrated Safety Assessment Division, Korea Atomic Energy Research Institute, P.O. Box 105, Duckjin-Dong, Yusong-Ku, Taejon 305-600 (Korea, Republic of); Jung, Wondea [Integrated Safety Assessment Division, Korea Atomic Energy Research Institute, P.O. Box 105, Duckjin-Dong, Yusong-Ku, Taejon 305-600 (Korea, Republic of)

    2005-08-01

    In complex systems such as a nuclear and chemical plant, it is well known that the provision of understandable procedures that allow operators to clarify what needs to be done and how to do it is one of the requisites to secure their safety. As a previous study in providing understandable procedures, the step complexity (SC) measure that can quantify the complexity of procedural steps in emergency operating procedures (EOPs) of a nuclear power plant (NPP) was suggested. However, the necessity of additional complexity factors that can consider a cognitive aspect in evaluating the complexity of procedural steps is raised. To this end, the comparisons between operators' performance data measured by the form of a step performance time with their behavior in carrying out the prescribed activities of procedural steps are conducted in this study. As a result, two kinds of complexity factors (the abstraction level of knowledge and the level of engineering decision) that could affect an operator's cognitive burden are identified. Although a well-designed experiment is indispensable for confirming the appropriateness of the additional complexity factors, it is strongly believed that the change of operators' performance data can be more authentically explained if the additional complexity factors are taken into consideration.

  8. Identifying cognitive complexity factors affecting the complexity of procedural steps in emergency operating procedures of a nuclear power plant

    Energy Technology Data Exchange (ETDEWEB)

    Jinkyun Park; Kwangsup Jeong; Wondea Jung [Korea Atomic Energy Research Institute, Taejon (Korea). Integrated Safety Assessment Division

    2005-08-15

    In complex systems such as a nuclear and chemical plant, it is well known that the provision of understandable procedures that allow operators to clarify what needs to be done and how to do it is one of the requisites to secure their safety. As a previous study in providing understandable procedures, the step complexity (SC) measure that can quantify the complexity of procedural steps in emergency operating procedures (EOPs) of a nuclear power plant (NPP) was suggested. However, the necessity of additional complexity factors that can consider a cognitive aspect in evaluating the complexity of procedura