WorldWideScience

Sample records for model significant predictors

  1. An adaptive resampling test for detecting the presence of significant predictors

    Science.gov (United States)

    McKeague, Ian W.; Qian, Min

    2015-01-01

    This paper investigates marginal screening for detecting the presence of significant predictors in high-dimensional regression. Screening large numbers of predictors is a challenging problem due to the non-standard limiting behavior of post-model-selected estimators. There is a common misconception that the oracle property for such estimators is a panacea, but the oracle property only holds away from the null hypothesis of interest in marginal screening. To address this difficulty, we propose an adaptive resampling test (ART). Our approach provides an alternative to the popular (yet conservative) Bonferroni method of controlling familywise error rates. ART is adaptive in the sense that thresholding is used to decide whether the centered percentile bootstrap applies, and otherwise adapts to the non-standard asymptotics in the tightest way possible. The performance of the approach is evaluated using a simulation study and applied to gene expression data and HIV drug resistance data. PMID:27073292

  2. Nonparametric Bayes modeling for case control studies with many predictors.

    Science.gov (United States)

    Zhou, Jing; Herring, Amy H; Bhattacharya, Anirban; Olshan, Andrew F; Dunson, David B

    2016-03-01

    It is common in biomedical research to run case-control studies involving high-dimensional predictors, with the main goal being detection of the sparse subset of predictors having a significant association with disease. Usual analyses rely on independent screening, considering each predictor one at a time, or in some cases on logistic regression assuming no interactions. We propose a fundamentally different approach based on a nonparametric Bayesian low rank tensor factorization model for the retrospective likelihood. Our model allows a very flexible structure in characterizing the distribution of multivariate variables as unknown and without any linear assumptions as in logistic regression. Predictors are excluded only if they have no impact on disease risk, either directly or through interactions with other predictors. Hence, we obtain an omnibus approach for screening for important predictors. Computation relies on an efficient Gibbs sampler. The methods are shown to have high power and low false discovery rates in simulation studies, and we consider an application to an epidemiology study of birth defects.

  3. Predictors of Developing Significant Mitral Regurgitation Following Percutaneous Mitral Commissurotomy with Inoue Balloon Technique

    Directory of Open Access Journals (Sweden)

    Abdelfatah A. Elasfar

    2011-01-01

    Full Text Available Background. Despite the high technical expertise in percutaneous mitral commissurotomy (PMC, mitral regurgitation (MR remains a major procedure-related complication. The aim of this work is to find out the most sensitive and applicable predictors of development of significant mitral regurgitation (SMR following percutaneous mitral commissurotomy using Inoue balloon technique. Methods. We studied prospectively the preprocedural (clinical, echocardiography, and hemodynamic and procedural predictors of significant mitral regurgitation (identified as increase of ≥2/4 grades of pre-PMC MR by color Doppler flow mapping following valvuloplasty using Inoue balloon in 108 consecutive patients with severe mitral stenosis. Multiple stepwise logistic regression analysis was performed for variables found positive on univariate analysis to determine the most important predictor(s of developing SMR. Results. The incidence of SMR following PMC using Inoue technique was 18.5% (10 patients. MV scoring systems were the only variables that showed significant differences between both groups (Group A without SMR and Group B with SMR. However, no clinical, other echocardiographic measurements, hemodynamic or procedural variables could predict the development of SMR. Using multiple regression analysis, the best predictive factor for the risk of SMR after Inoue BMV was the total MR-echo score with a cutoff point of 7 and a predictive percentage of 97.7%. Conclusions. The total MR-echo score is the only independent predictor of SMR following PMC using Inoue technique with a cutoff point of 7.

  4. Bayesian modeling of measurement error in predictor variables

    NARCIS (Netherlands)

    Fox, Gerardus J.A.; Glas, Cornelis A.W.

    2003-01-01

    It is shown that measurement error in predictor variables can be modeled using item response theory (IRT). The predictor variables, that may be defined at any level of an hierarchical regression model, are treated as latent variables. The normal ogive model is used to describe the relation between

  5. Inpatient Treatment for Adolescents with Anorexia Nervosa: Clinical Significance and Predictors of Treatment Outcome.

    Science.gov (United States)

    Schlegl, Sandra; Diedrich, Alice; Neumayr, Christina; Fumi, Markus; Naab, Silke; Voderholzer, Ulrich

    2016-05-01

    This study evaluated the clinical significance as well as predictors of outcome for adolescents with severe anorexia nervosa (AN) treated in an inpatient setting. Body mass index (BMI), eating disorder (ED) symptoms [Eating Disorder Inventory-2 (EDI-2)], general psychopathology and depression were assessed in 238 patients at admission and discharge. BMI increased from 14.8 + 1.2 to 17.3 + 1.4 kg/m(2). Almost a fourth (23.6%) of the patients showed reliable changes, and 44.7% showed clinically significant changes (EDI-2). BMI change did not significantly differ between those with reliable or clinically significant change or no reliable change in EDI-2. Length of stay, depression and body dissatisfaction were negative predictors of a clinically significant change. Inpatient treatment is effective in about two thirds of adolescents with AN and should be considered when outpatient treatment fails. About one third of patients showed significant weight gain, but did not improve regarding overall ED symptomatology. Future studies should focus on treatment strategies for non-responders.

  6. Prevalence, predictors and clinical significance of Blastocystis sp. in Sebha, Libya.

    Science.gov (United States)

    Abdulsalam, Awatif M; Ithoi, Init; Al-Mekhlafi, Hesham M; Khan, Abdul Hafeez; Ahmed, Abdulhamid; Surin, Johari; Mak, Joon Wah

    2013-04-08

    Blastocystis sp. has a worldwide distribution and is often the most common human intestinal protozoan reported in children and adults in developing countries. The clinical relevance of Blastocystis sp. remains controversial. This study was undertaken to determine the prevalence of Blastocystis infection and its association with gastrointestinal symptoms among outpatients in Sebha city, Libya. A total of 380 stool samples were collected from outpatients attending the Central Laboratory in Sebha, Libya for routine stool examination. The presence of Blastocystis sp. was screened comparing light microscopy of direct smears against in vitro cultivation. Demographic and socioeconomic information were collected with a standardized questionnaire. The overall prevalence of Blastocystis infection was 22.1%. The prevalence was significantly higher among patients aged ≥18 years compared to those aged Libya. Age and occupational status were the significant predictors of infection. However, more studies from different areas in Libya are needed in order to delineate the epidemiology and clinical significance of this infection.

  7. Prevalence, predictors and clinical significance of Blastocystis sp. in Sebha, Libya

    Science.gov (United States)

    2013-01-01

    Background Blastocystis sp. has a worldwide distribution and is often the most common human intestinal protozoan reported in children and adults in developing countries. The clinical relevance of Blastocystis sp. remains controversial. This study was undertaken to determine the prevalence of Blastocystis infection and its association with gastrointestinal symptoms among outpatients in Sebha city, Libya. Methods A total of 380 stool samples were collected from outpatients attending the Central Laboratory in Sebha, Libya for routine stool examination. The presence of Blastocystis sp. was screened comparing light microscopy of direct smears against in vitro cultivation. Demographic and socioeconomic information were collected with a standardized questionnaire. Results The overall prevalence of Blastocystis infection was 22.1%. The prevalence was significantly higher among patients aged ≥18 years compared to those aged Blastocystis infection and the occupational status (P = 0.017), family size (P = 0.023) and educational level (P = 0.042) of the participants. Multiple logistic regression analysis confirmed that the age of ≥ 18 years (OR = 5.7; 95% CI = 2.21; 9.86) and occupational status (OR = 2.2; 95% CI = 1.02, 4.70) as significant predictors of Blastocystis infection among this population. In those who had only Blastocystis infection but no other gastrointestinal parasitic infections, the prevalence of gastrointestinal symptoms was higher compared to those without Blastocystis infection (35.3% vs 13.2%; x2 = 25.8; P Blastocystis sp. is prevalent and associated with gastrointestinal symptoms among communities in Sebha city, Libya. Age and occupational status were the significant predictors of infection. However, more studies from different areas in Libya are needed in order to delineate the epidemiology and clinical significance of this infection. PMID:23566585

  8. Importance of predictor variables for models of chemical function

    Data.gov (United States)

    U.S. Environmental Protection Agency — Importance of random forest predictors for all classification models of chemical function. This dataset is associated with the following publication: Isaacs , K., M....

  9. Significantly reduced hypoxemic events in morbidly obese patients undergoing gastrointestinal endoscopy: Predictors and practice effect

    Directory of Open Access Journals (Sweden)

    Basavana Gouda Goudra

    2014-01-01

    Full Text Available Background: Providing anesthesia for gastrointestinal (GI endoscopy procedures in morbidly obese patients is a challenge for a variety of reasons. The negative impact of obesity on the respiratory system combined with a need to share the upper airway and necessity to preserve the spontaneous ventilation, together add to difficulties. Materials and Methods: This retrospective cohort study included patients with a body mass index (BMI >40 kg/m 2 that underwent out-patient GI endoscopy between September 2010 and February 2011. Patient data was analyzed for procedure, airway management technique as well as hypoxemic and cardiovascular events. Results: A total of 119 patients met the inclusion criteria. Our innovative airway management technique resulted in a lower rate of intraoperative hypoxemic events compared with any published data available. Frequency of desaturation episodes showed statistically significant relation to previous history of obstructive sleep apnea (OSA. These desaturation episodes were found to be statistically independent of increasing BMI of patients. Conclusion: Pre-operative history of OSA irrespective of associated BMI values can be potentially used as a predictor of intra-procedural desaturation. With suitable modification of anesthesia technique, it is possible to reduce the incidence of adverse respiratory events in morbidly obese patients undergoing GI endoscopy procedures, thereby avoiding the need for endotracheal intubation.

  10. Significantly reduced hypoxemic events in morbidly obese patients undergoing gastrointestinal endoscopy: Predictors and practice effect.

    Science.gov (United States)

    Goudra, Basavana Gouda; Singh, Preet Mohinder; Penugonda, Lakshmi C; Speck, Rebecca M; Sinha, Ashish C

    2014-01-01

    Providing anesthesia for gastrointestinal (GI) endoscopy procedures in morbidly obese patients is a challenge for a variety of reasons. The negative impact of obesity on the respiratory system combined with a need to share the upper airway and necessity to preserve the spontaneous ventilation, together add to difficulties. This retrospective cohort study included patients with a body mass index (BMI) >40 kg/m(2) that underwent out-patient GI endoscopy between September 2010 and February 2011. Patient data was analyzed for procedure, airway management technique as well as hypoxemic and cardiovascular events. A total of 119 patients met the inclusion criteria. Our innovative airway management technique resulted in a lower rate of intraoperative hypoxemic events compared with any published data available. Frequency of desaturation episodes showed statistically significant relation to previous history of obstructive sleep apnea (OSA). These desaturation episodes were found to be statistically independent of increasing BMI of patients. Pre-operative history of OSA irrespective of associated BMI values can be potentially used as a predictor of intra-procedural desaturation. With suitable modification of anesthesia technique, it is possible to reduce the incidence of adverse respiratory events in morbidly obese patients undergoing GI endoscopy procedures, thereby avoiding the need for endotracheal intubation.

  11. Significant Independent Predictors of Vitamin D Deficiency in Inpatients and Outpatients of a Nephrology Unit

    Directory of Open Access Journals (Sweden)

    Recep Bentli

    2013-01-01

    Full Text Available Aims. Kidney disease was found to be a major risk factor for vitamin D deficiency in a population study of patients hospitalized. The aims of the study were to describe the prevalence of vitamin D deficiency inpatients and outpatients in a nephrology department during fall and to evaluate effect of assessing serum 25-hydroxyvitamin D (25(OHD levels and previous supplementation of cholecalciferol on vitamin D status. Methods. We studied 280 subjects in total, between October and January. The subjects were recruited from the following two groups: (a inpatients and (b outpatients in nephrology unit. We examined previous documentary evidence of vitamin D supplementation of the patients. Results. The prevalence of vitamin D deficiency among these 280 patients was 62,1% (174 patients. Fifty-three patients (18.9% had severe vitamin D deficiency, 121 patients (43.2% moderate vitamin D deficiency, and 66 patients (23.6% vitamin D insufficiency. In logistic regression analysis female gender, not having vitamin D supplementation history, low serum albumin, and low blood urea nitrogen levels were significant independent predictors of vitamin D deficiency while no association of vitamin D deficiency with diabetes mellitus, serum creatinine, eGFR, and being hospitalized was found. Conclusion. Vitamin D deficiency, seems to be an important problem in both inpatients and outpatients of nephrology. Monitoring serum 25(OHD concentrations regularly and replacement of vitamin D are important. Women in Turkey are at more risk of deficiency and may therefore need to consume higher doses of vitamin D.

  12. The coronary calcium score is a more accurate predictor of significant coronary stenosis than conventional risk factors in symptomatic patients

    DEFF Research Database (Denmark)

    Nicoll, R; Wiklund, U; Zhao, Y;

    2016-01-01

    risk factor assessment, computed tomographic coronary angiogram (CTCA) or conventional angiography and a CT scan for coronary artery calcium (CAC) scoring. 1539 (27.9%) patients had significant stenosis, 5.5% of whom had zero CAC. In 5074 patients, multiple binary regression showed the most important...... predictor of significant stenosis to be male gender (B=1.07) followed by diabetes mellitus (B=0.70) smoking, hypercholesterolaemia, hypertension, family history of CAD and age but not obesity. When the log transformed CAC score was included, it became the most powerful predictor (B=1.25), followed by male...... gender (B=0.48), diabetes, smoking, family history and age but hypercholesterolaemia and hypertension lost significance. The CAC score is a more accurate predictor of >50% stenosis than risk factors regardless of the means of assessment of stenosis. The sensitivity of risk factors, CAC score...

  13. Predictors and clinical significance of the positive cone margin in cervical intraepithelial neoplasia Ⅲ patients

    Institute of Scientific and Technical Information of China (English)

    SUN Xiao-guang; MA Shui-qing; ZHANG Jin-xia; WU Ming

    2009-01-01

    Background Conization is being widely accepted for diagnosis and treatment of cervical intraepithelial neoplasia (CIN). There is controversy as to which factors are most predictive of a positive cone margin and the clinical significance of it. We conducted this study to identify the predictive factors and to evaluate the clinical significance of a positive cone margin in CIN Ⅲ patients.Methods A retrospective review was conducted of 207 patients who had undergone conization due to CIN Ⅲ from January 2003 to December 2005 at Peking Union Medical College Hospital. Of these, 67 had a subsequent hysterectomy. Univariate and multivariate analysis were utilized to define the predictive factors for a positive cone margin, and to compare the pathologic results of conization with subsequent hysterectomy.Results One hundred and fifty-one (72.9%) were margin free of CIN Ⅰ or worse, 37 (17.9%) had CIN lesions close to the margin and 19 (9.2%) had margin involvement. A total of 56 cases (27.1%) had positive cone margins (defined as the presence of CIN at or close to the edge of a cone specimen). Univariate analysis showed that the parity, cytological grade, multi-quadrants of CIN Ⅲ by punch biopsy, gland involvement, as well as the depth of conization were significant factors correlated with a positive cone margin (P0.05). Multivariate analysis revealed that the cytological grade (OR=1.92), depth of conization (OR=2.03), parity (OR=3.02) and multi-quadrants of CIN Ⅲ (OR=4.60) were significant predictors with increased risk for positive margin. The frequency of residual CIN Ⅰ or worse in hysterectomy specimens was found to be 55.6% (20/36) in patients who were margin free, 71.4% (15/21) in patients with CIN occurring close to margin, and 80.0% (8/10) in patients with margin involvement. The frequency of residual CIN Ⅲ or worse was found to be 13.9% (5/36), 23.8% (5/21) and 50.0% (5/10) respectively in different groups.Conclusions Cytological grade, depth of

  14. A New Perspective for the Calibration of Computational Predictor Models.

    Energy Technology Data Exchange (ETDEWEB)

    Crespo, Luis Guillermo

    2014-11-01

    This paper presents a framework for calibrating computational models using data from sev- eral and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncer- tainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of obser- vations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it is a description of the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain (i.e., roll-up and extrapolation).

  15. Calibration of Predictor Models Using Multiple Validation Experiments

    Science.gov (United States)

    Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

    2015-01-01

    This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

  16. BMI, HOMA-IR, and Fasting Blood Glucose Are Significant Predictors of Peripheral Nerve Dysfunction in Adult Overweight and Obese Nondiabetic Nepalese Individuals: A Study from Central Nepal

    Directory of Open Access Journals (Sweden)

    Lekhjung Thapa

    2016-01-01

    Full Text Available Objective. Nondiabetic obese individuals have subclinical involvement of peripheral nerves. We report the factors predicting peripheral nerve function in overweight and obese nondiabetic Nepalese individuals. Methodology. In this cross-sectional study, we included 50 adult overweight and obese nondiabetic volunteers without features of peripheral neuropathy and 50 healthy volunteers to determine the normative nerve conduction data. In cases of abnormal function, the study population was classified on the basis of the number of nerves involved, namely, “<2” or “≥2.” Multivariable logistic regression analysis was carried out to predict outcomes. Results. Fasting blood glucose (FBG was the significant predictor of motor nerve dysfunction (P=0.039, 95% confidence interval (CI = 1.003–1.127. Homeostatic model assessment of insulin resistance (HOMA-IR was the significant predictor (P=0.019, 96% CI = 1.420–49.322 of sensory nerve dysfunction. Body mass index (BMI was the significant predictor (P=0.034, 95% CI = 1.018–1.577 in case of ≥2 mixed nerves’ involvement. Conclusion. FBG, HOMA-IR, and BMI were significant predictors of peripheral nerve dysfunction in overweight and obese Nepalese individuals.

  17. The relative significance of lexical richness and syntactic complexity as predictors of academic reading performance

    Directory of Open Access Journals (Sweden)

    Mehdi Karami

    2013-11-01

    Full Text Available Reading academic texts that include mainly university textbooks has been a challenge for EAP learners. There are various reasons for text difficulty; however, linguistic elements were investigated in this study. The aim of this study was to determine whether lexical richness of the readers would be a more potent predictor of their academic reading performance or their ability for producing and processing complex syntactic structures. The study involved 50 ELT teacher trainees, 25 juniors and 25 seniors, at Shahid Madani University of Azerbaijan, Iran. In a standard multiple regression design, the participants were given an opinion essay-writing task and an IELTS academic reading test. Their scores on IELTS academic reading test were regressed against LFP (Lexical Frequency Profile and MLTU (Mean Length of T-Unit indexes of their essays. LFP index is a measure of lexical richness adapted to the web for free online access under the name Web-VocabProfile, and MLTU index is a measure of syntactic complexity. Results indicated that the ability in producing and processing complex syntactic structures rather than mere grammatical knowledge can be considered as effective a predictor of academic reading comprehension as lexical richness. Therefore, lexical richness may no longer be supposed as the single most important predictor of academic reading performance.

  18. Multiple Imputation of Predictor Variables Using Generalized Additive Models

    NARCIS (Netherlands)

    de Jong, Roel; van Buuren, Stef; Spiess, Martin

    2016-01-01

    The sensitivity of multiple imputation methods to deviations from their distributional assumptions is investigated using simulations, where the parameters of scientific interest are the coefficients of a linear regression model, and values in predictor variables are missing at random. The performanc

  19. Predictors of Retirement Satisfaction: A Path Model.

    Science.gov (United States)

    Kremer, Yael

    1985-01-01

    Examined adjustment to retirement among 310 former industrial and service workers. Respondents had come to terms with retirement and enjoyed their more relaxed lifestyle. Dominant variables in the path model were retirees' satisfaction with specific aspects of retirement: giving up work, activities with family and friends, rest, and free time. (BH)

  20. A Comparison of Hourly Typhoon Rainfall Forecasting Models Based on Support Vector Machines and Random Forests with Different Predictor Sets

    Science.gov (United States)

    Lin, Kun-Hsiang; Tseng, Hung-Wei; Kuo, Chen-Min; Yang, Tao-Chang; Yu, Pao-Shan

    2016-04-01

    Typhoons with heavy rainfall and strong wind often cause severe floods and losses in Taiwan, which motivates the development of rainfall forecasting models as part of an early warning system. Thus, this study aims to develop rainfall forecasting models based on two machine learning methods, support vector machines (SVMs) and random forests (RFs), and investigate the performances of the models with different predictor sets for searching the optimal predictor set in forecasting. Four predictor sets were used: (1) antecedent rainfalls, (2) antecedent rainfalls and typhoon characteristics, (3) antecedent rainfalls and meteorological factors, and (4) antecedent rainfalls, typhoon characteristics and meteorological factors to construct for 1- to 6-hour ahead rainfall forecasting. An application to three rainfall stations in Yilan River basin, northeastern Taiwan, was conducted. Firstly, the performance of the SVMs-based forecasting model with predictor set #1 was analyzed. The results show that the accuracy of the models for 2- to 6-hour ahead forecasting decrease rapidly as compared to the accuracy of the model for 1-hour ahead forecasting which is acceptable. For improving the model performance, each predictor set was further examined in the SVMs-based forecasting model. The results reveal that the SVMs-based model using predictor set #4 as input variables performs better than the other sets and a significant improvement of model performance is found especially for the long lead time forecasting. Lastly, the performance of the SVMs-based model using predictor set #4 as input variables was compared with the performance of the RFs-based model using predictor set #4 as input variables. It is found that the RFs-based model is superior to the SVMs-based model in hourly typhoon rainfall forecasting. Keywords: hourly typhoon rainfall forecasting, predictor selection, support vector machines, random forests

  1. Neighborhood Predictors of Intimate Partner Violence: A Theory-Informed Analysis Using Hierarchical Linear Modeling.

    Science.gov (United States)

    Voith, Laura A; Brondino, Michael J

    2017-09-01

    Due to high prevalence rates and deleterious effects on individuals, families, and communities, intimate partner violence (IPV) is a significant public health problem. Because IPV occurs in the context of communities and neighborhoods, research must examine the broader environment in addition to individual-level factors to successfully facilitate behavior change. Drawing from the Social Determinants of Health framework and Social Disorganization Theory, neighborhood predictors of IPV were tested using hierarchical linear modeling. Results indicated that concentrated disadvantage and female-to-male partner violence were robust predictors of women's IPV victimization. Implications for theory, practice, and policy, and future research are discussed. © Society for Community Research and Action 2017.

  2. Clinical significance of serum ferritin level as an independent predictor of insulin resistance in Korean men.

    Science.gov (United States)

    Park, Sung Keun; Choi, Won Joon; Oh, Chang-Mo; Kim, Min-Gi; Ham, Woo Taek; Choi, Joong-Myung; Ryoo, Jae-Hong

    2015-01-01

    Elevated serum ferritin level has been reported to be associated with type 2 diabetes mellitus and metabolic syndrome, which have significant relation with insulin resistance (IR). However, clinical association between serum ferritin level and IR remained unclear. Accordingly, this study was designed to evaluate the longitudinal effects of baseline serum ferritin level on the development of IR. An IR-free 22,057 healthy Korean men (HOMA-IRserum ferritin levels. Cox proportional hazards models were used to measure the hazard ratios (HRs) of baseline serum ferritin levels on IR. During 77,471.1 person-years of follow-up, 4494 incident cases of insulin resistance developed between 2006 and 2010 (overall development rate: 20.4%). The development rate of IR increased in proportion to the baseline serum ferritin levels (quartile 1: 16.7%, quartile 2: 18.5%, quartile 3: 19.9%, quartile 4: 25.5%, Pserum ferritin levels with the first quartile, were 1.11 (0.99-1.24), 1.19 (1.07-1.33) and 1.51 (1.35-1.68), respectively (P for trend serum ferritin level was independently associated with the future development of IR in Korean men. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  3. Supervision in Factor Models Using a Large Number of Predictors

    DEFF Research Database (Denmark)

    Boldrini, Lorenzo; Hillebrand, Eric Tobias

    In this paper we investigate the forecasting performance of a particular factor model (FM) in which the factors are extracted from a large number of predictors. We use a semi-parametric state-space representation of the FM in which the forecast objective, as well as the factors, is included.......g. a standard dynamic factor model with separate forecast and state equations....... in the state vector. The factors are informed of the forecast target (supervised) through the state equation dynamics. We propose a way to assess the contribution of the forecast objective on the extracted factors that exploits the Kalman filter recursions. We forecast one target at a time based...

  4. Test of the Fishbein and Ajzen models as predictors of health care workers' glove use.

    Science.gov (United States)

    Levin, P F

    1999-08-01

    The aim of this study was to identify predictors of health care workers' glove use when there is a potential for blood exposure. The study hypothesis was that an extension of the theory of planned behavior would explain more of the variance in glove use behavior than the theory of reasoned action or theory of planned behavior. A random sample of nurses and laboratory workers (N = 527) completed a 26-item questionnaire with acceptable content validity and reliability estimates. Using structural equation modeling techniques, intention, attitude, and perceived risk were significant predictors of behavior. Perceived control and attitude were the significant determinants of intention. The theory of reasoned action was the most parsimonious model, explaining 70% of the variance in glove use behavior. The theory of planned behavior extension was a viable model to study behavior related to glove use and reducing workers' risks to bloodborne diseases.

  5. Crop weather models of corn and soybeans for Agrophysical Units (APU's) in Iowa using monthly meteorological predictors

    Science.gov (United States)

    Leduc, S. (Principal Investigator)

    1982-01-01

    Models based on multiple regression were developed to estimate corn and soybean yield from weather data for agrophysical units (APU) in Iowa. The predictor variables are derived from monthly average temperature and monthly total precipitation data at meteorological stations in the cooperative network. The models are similar in form to the previous models developed for crop reporting districts (CRD). The trends and derived variables were the same and the approach to select the significant predictors was similar to that used in developing the CRD models. The APU's were selected to be more homogeneous with respect crop to production than the CRDs. The APU models are quite similar to the CRD models, similar explained variation and number of predictor variables. The APU models are to be independently evaluated and compared to the previously evaluated CRD models. That comparison should indicate the preferred model area for this application, i.e., APU or CRD.

  6. Women's Endorsement of Models of Sexual Response: Correlates and Predictors.

    Science.gov (United States)

    Nowosielski, Krzysztof; Wróbel, Beata; Kowalczyk, Robert

    2016-02-01

    Few studies have investigated endorsement of female sexual response models, and no single model has been accepted as a normative description of women's sexual response. The aim of the study was to establish how women from a population-based sample endorse current theoretical models of the female sexual response--the linear models and circular model (partial and composite Basson models)--as well as predictors of endorsement. Accordingly, 174 heterosexual women aged 18-55 years were included in a cross-sectional study: 74 women diagnosed with female sexual dysfunction (FSD) based on DSM-5 criteria and 100 non-dysfunctional women. The description of sexual response models was used to divide subjects into four subgroups: linear (Masters-Johnson and Kaplan models), circular (partial Basson model), mixed (linear and circular models in similar proportions, reflective of the composite Basson model), and a different model. Women were asked to choose which of the models best described their pattern of sexual response and how frequently they engaged in each model. Results showed that 28.7% of women endorsed the linear models, 19.5% the partial Basson model, 40.8% the composite Basson model, and 10.9% a different model. Women with FSD endorsed the partial Basson model and a different model more frequently than did non-dysfunctional controls. Individuals who were dissatisfied with a partner as a lover were more likely to endorse a different model. Based on the results, we concluded that the majority of women endorsed a mixed model combining the circular response with the possibility of an innate desire triggering a linear response. Further, relationship difficulties, not FSD, predicted model endorsement.

  7. Introducing nonlinear, multivariate 'Predictor Surfaces' for quantitative modeling of chemical systems with higher-order, coupled predictor variables.

    Science.gov (United States)

    Horton, Rebecca B; McConico, Morgan; Landry, Currie; Tran, Tho; Vogt, Frank

    2012-10-09

    Innovations in chemometrics are required for studies of chemical systems which are governed by nonlinear responses to chemical parameters and/or interdependencies (coupling) among these parameters. Conventional and linear multivariate models have limited use for quantitative and qualitative investigations of such systems because they are based on the assumption that the measured data are simple superpositions of several input parameters. 'Predictor Surfaces' were developed for studies of more chemically complex systems such as biological materials in order to ensure accurate quantitative analyses and proper chemical modeling for in-depth studies of such systems. Predictor Surfaces are based on approximating nonlinear multivariate model functions by multivariate Taylor expansions which inherently introduce the required coupled and higher-order predictor variables. As proof-of-principle for the Predictor Surfaces' capabilities, an application from environmental analytical chemistry was chosen. Microalgae cells are known to sensitively adapt to changes in environmental parameters such as pollution and/or nutrient availability and thus have potential as novel in situ sensors for environmental monitoring. These adaptations of the microalgae cells are reflected in their chemical signatures which were then acquired by means of FT-IR spectroscopy. In this study, the concentrations of three nutrients, namely inorganic carbon and two nitrogen containing ions, were chosen. Biological considerations predict that changes in nutrient availability produce a nonlinear response in the cells' biomass composition; it is also known that microalgae need certain nutrient mixes to thrive. The nonlinear Predictor Surfaces were demonstrated to be more accurate in predicting the values of these nutrients' concentrations than principal component regression. For qualitative chemical studies of biological systems, the Predictor Surfaces themselves are a novel tool as they visualize

  8. Pediatricians' perceptions of vaccine effectiveness and safety are significant predictors of vaccine administration in India.

    Science.gov (United States)

    Gargano, Lisa M; Thacker, Naveen; Choudhury, Panna; Weiss, Paul S; Russ, Rebecca M; Pazol, Karen; Arora, Manisha; Orenstein, Walter A; Omer, Saad B; Hughes, James M

    2013-09-01

    New vaccine introduction is important to decrease morbidity and mortality in India. The goal of this study was to identify perceptions that are associated with administration of four selected vaccines for prevention of Japanese encephalitis (JE), typhoid fever, influenza and human papillomavirus (HPV) infection. A random sample of 785 pediatricians from a national list of Indian Academy of Pediatrics members was selected for a survey to assess perceptions of vaccine effectiveness and safety, and vaccine administration practices. Logistic regression was used to assess factors associated with selective or routine use. Pediatricians reported administering typhoid (91.6%), influenza (60.1%), HPV (46.0%) and JE (41.9%) vaccines selectively or routinely. Pediatricians who perceived the vaccine to be safe were significantly more likely to report administration of JE (OR 2.6, 95% CI 1.3 to 5.3), influenza (OR 4.3, 95% CI 2.0 to 9.6) and HPV vaccine (OR 6.2, 95% CI 3.1 to 12.7). Pediatricians who perceived the vaccine to be effective were significantly more likely to report administration of JE (OR 3.3, 95% CI 1.6 to 6.5), influenza (OR 7.7, 95% CI 2.5 to 23.1) and HPV vaccine (OR 3.2, 95% CI 1.6 to 6.4) CONCLUSION: Understanding the role perceptions play provides an opportunity to design strategies to build support for vaccine use.

  9. Passenger compartment intrusion as a predictor of significant injury for children in motor vehicle crashes.

    Science.gov (United States)

    Evans, Susan L; Nance, Michael L; Arbogast, Kristy B; Elliott, Michael R; Winston, Flaura K

    2009-02-01

    Passenger compartment intrusion, loss of integrity of the vehicle occupant compartment due to a motor vehicle crash, has frequently been used as a triage criterion. Data to support intrusion as a proxy for injury severity in child occupants are lacking. The purpose of this study was to examine the association between intrusion and injury to children in motor vehicle crashes. Crash investigation data were reviewed from the partners for child passenger safety database, a large, child-focused crash surveillance system. Data included: intrusion (centimeters), direction of impact, age of occupant, and Abbreviated Injury Scale (AIS) score. Analyses examined the relationship between the amount of intrusion and the risk of any AIS > or = 2, or > or = 3 injury. Data were available on 880 children, age 0 year to 15 years. AIS > or = 2 and > or = 3 injuries occurred in 40.3% and 12.6% of child occupants, respectively. Intrusion was strongly and positively associated with the odds of both an AIS > or = 2 and > or = 3 injury (p or = 2, or > or = 3 injury increased on average by 2.9% (95% CI = 1.9-3.8%), or 4.0% (95% CI = 2.7-5.2%), respectively, for each additional centimeter of intrusion, adjusting for age, restraint use, seating row, and direction of impact. The association between passenger compartment intrusion and injury in children supports its application in triage, and usefulness in injury predictive models. Future studies should determine methods for providing valid field information on intrusion to the trauma team.

  10. Predictors of social integration for individuals with brain injury: An application of the ICF model.

    Science.gov (United States)

    Ditchman, Nicole; Sheehan, Lindsay; Rafajko, Sean; Haak, Christopher; Kazukauskas, Kelly

    2016-01-01

    People with brain injury often experience significant challenges to social and community engagement following injury. The purpose of this study was to investigate factors impacting social integration for adults with brain injury using the International Classification and Functioning, Disability and Health (ICF) as a conceptual model. Adults with brain injury (n = 103) recruited through two US state brain injury associations participated in a survey study. Hierarchical regression analysis was used to examine the predictive impact of components of the ICF model on social integration outcomes. Specifically, demographic (age, gender, SES), disability (severity of functional limitations), personal (disability acceptance, social self-efficacy) and environmental (neighbourhood climate, stigma, social support network) factors were entered as four conceptual groups of predictors to examine the incremental contribution of the variance in social integration explained by each set. As hypothesized, the inclusion of each block of predictors significantly improved the model. The overall regression model explained 41% of the variance in social integration. Specifically, SES (β = 0.25), severity of functional limitations (β = 0.29) and social support network (β = 0.29) emerged as the strongest independent predictors. Findings from this study highlight the importance of adopting a biopsychosocial approach to understanding social integration for people with brain injury.

  11. Evaluating predictors of dispersion: a comparison of Dominance Analysis and Bayesian Model Averaging.

    Science.gov (United States)

    Shou, Yiyun; Smithson, Michael

    2015-03-01

    Conventional measures of predictor importance in linear models are applicable only when the assumption of homoscedasticity is satisfied. Moreover, they cannot be adapted to evaluating predictor importance in models of heteroscedasticity (i.e., dispersion), an issue that seems not to have been systematically addressed in the literature. We compare two suitable approaches, Dominance Analysis (DA) and Bayesian Model Averaging (BMA), for simultaneously evaluating predictor importance in models of location and dispersion. We apply them to the beta general linear model as a test-case, illustrating this with an example using real data. Simulations using several different model structures, sample sizes, and degrees of multicollinearity suggest that both DA and BMA largely agree on the relative importance of predictors of the mean, but differ when ranking predictors of dispersion. The main implication of these findings for researchers is that the choice between DA and BMA is most important when they wish to evaluate the importance of predictors of dispersion.

  12. Modelling vocal anatomy's significant effect on speech

    NARCIS (Netherlands)

    de Boer, B.

    2010-01-01

    This paper investigates the effect of larynx position on the articulatory abilities of a humanlike vocal tract. Previous work has investigated models that were built to resemble the anatomy of existing species or fossil ancestors. This has led to conflicting conclusions about the relation between

  13. Bayesian modeling of measurement error in predictor variables using item response theory

    NARCIS (Netherlands)

    Fox, Jean-Paul; Glas, Cees A.W.

    2003-01-01

    It is shown that measurement error in predictor variables can be modeled using item response theory (IRT). The predictor variables, that may be defined at any level of an hierarchical regression model, are treated as latent variables. The normal ogive model is used to describe the relation between t

  14. Predictors and Diagnostic Significance of the Adenosine Related Side Effects on Myocardial Perfusion SPECT/CT Imaging

    Directory of Open Access Journals (Sweden)

    Nilüfer Yıldırım Poyraz

    2014-10-01

    Full Text Available Objective: The aim of this study was to investigate the relationship between patient characteristics and adenosine-related side-effects during stress myocard perfusion imaging (MPI. The effect of presence of adenosine-related side-effects on the diagnostic value of MPI with integrated SPECT/CT system for coronary artery disease (CAD, was also assessed in this study. Methods: Total of 281 patients (109 M, 172 F; mean age:62.6±10 who underwent standard adenosine stress protocol for MPI, were included in this study. All symptoms during adenosine infusion were scored according to the severity and duration. For the estimation of diagnostic value of adenosine MPI with integrated SPECT/CT system, coronary angiography (CAG or clinical follow-up were used as gold standard. Results: Total of 173 patients (61.6% experienced adenosine-related side-effects (group 1; flushing, dyspnea, and chest pain were the most common. Other 108 patients completed pharmacologic stress (PS test without any side-effects (group 2. Test tolerability were similar in the patients with cardiovascular or airway disease to others, however dyspnea were observed significantly more common in patients with mild airway disease. Body mass index (BMI ≥30 kg/m2 and age ≤45 years were independent predictors of side-effects. The diagnostic value of MPI was similar in both groups. Sensitivity of adenosine MPI SPECT/CT was calculated to be 86%, specificity was 94% and diagnostic accuracy was 92% for diagnosis of CAD. Conclusion: Adenosine MPI is a feasible and well tolerated method in patients who are not suitable for exercise stress test as well as patients with cardiopulmonary disease. However age ≤45 years and BMI ≥30 kg/m2 are the positive predictors of adenosine-related side-effects, the diagnostic value of adenosine MPI SPECT/CT is not affected by the presence of adenosine related side-effects.

  15. Prevalence and clinical significance of nonorgan specific antibodies in patients with autoimmune thyroiditis as predictor markers for rheumatic diseases

    Science.gov (United States)

    Elnady, Basant M.; Kamal, Naglaa M.; Shaker, Raneyah H.M.; Soliman, Amal F.; Hasan, Waleed A.; Alghamdi, Hamed A.; Algethami, Mohammed M.; Jajah, Mohamed Bilal

    2016-01-01

    Abstract Autoimmune diseases are considered the 3rd leading cause of morbidity and mortality in the industrialized countries. Autoimmune thyroid diseases (ATDs) are associated with high prevalence of nonorgan-specific autoantibodies, such as antinuclear antibodies (ANA), antidouble-stranded deoxyribonucleic acid (anti-dsDNA), antiextractable-nuclear antigens (anti-ENAs), rheumatoid factor (RF), and anticyclic-citrullinated peptides (anti-CCP) whose clinical significance is unknown. We aimed to assess the prevalence of various nonorgan-specific autoantibodies in patients with ATD, and to investigate the possible association between these autoantibodies and occurrence of rheumatic diseases and, if these autoantibodies could be considered as predictor markers for autoimmune rheumatic diseases in the future. This study had 2 phases: phase 1; in which 61 ATD patients free from rheumatic manifestations were assessed for the presence of these nonorgan-specific autoantibodies against healthy 61 control group, followed by 2nd phase longitudinal clinical follow-up in which cases are monitored systematically to establish occurrence and progression of any rheumatic disease in association to these autoantibodies with its influences and prognosis. Regarding ATD patients, ANA, anti-dsDNA, Anti-ENA, and RF were present in a percentage of (50.8%), (18%), (21.3%), and (34.4%), respectively, with statistically significance difference (P < 0.5) rather than controls. Nearly one third of the studied group (32.8%) developed the rheumatic diseases, over 2 years follow-up. It was obvious that those with positive anti-dsDNA had higher risk (2.45 times) to develop rheumatic diseases than those without. There was a statistically significant positive linear relationship between occurrence of disease in months and (age, anti-dsDNA, anti-CCP, RF, and duration of thyroiditis). Anti-dsDNA and RF are the most significant predictors (P < 0.0001). ATD is more associated with rheumatic

  16. Impact of correlation of predictors on discrimination of risk models in development and external populations.

    Science.gov (United States)

    Kundu, Suman; Mazumdar, Madhu; Ferket, Bart

    2017-04-19

    The area under the ROC curve (AUC) of risk models is known to be influenced by differences in case-mix and effect size of predictors. The impact of heterogeneity in correlation among predictors has however been under investigated. We sought to evaluate how correlation among predictors affects the AUC in development and external populations. We simulated hypothetical populations using two different methods based on means, standard deviations, and correlation of two continuous predictors. In the first approach, the distribution and correlation of predictors were assumed for the total population. In the second approach, these parameters were modeled conditional on disease status. In both approaches, multivariable logistic regression models were fitted to predict disease risk in individuals. Each risk model developed in a population was validated in the remaining populations to investigate external validity. For both approaches, we observed that the magnitude of the AUC in the development and external populations depends on the correlation among predictors. Lower AUCs were estimated in scenarios of both strong positive and negative correlation, depending on the direction of predictor effects and the simulation method. However, when adjusted effect sizes of predictors were specified in the opposite directions, increasingly negative correlation consistently improved the AUC. AUCs in external validation populations were higher or lower than in the derivation cohort, even in the presence of similar predictor effects. Discrimination of risk prediction models should be assessed in various external populations with different correlation structures to make better inferences about model generalizability.

  17. Application of Interval Predictor Models to Space Radiation Shielding

    Science.gov (United States)

    Crespo, Luis G.; Kenny, Sean P.; Giesy,Daniel P.; Norman, Ryan B.; Blattnig, Steve R.

    2016-01-01

    This paper develops techniques for predicting the uncertainty range of an output variable given input-output data. These models are called Interval Predictor Models (IPM) because they yield an interval valued function of the input. This paper develops IPMs having a radial basis structure. This structure enables the formal description of (i) the uncertainty in the models parameters, (ii) the predicted output interval, and (iii) the probability that a future observation would fall in such an interval. In contrast to other metamodeling techniques, this probabilistic certi cate of correctness does not require making any assumptions on the structure of the mechanism from which data are drawn. Optimization-based strategies for calculating IPMs having minimal spread while containing all the data are developed. Constraints for bounding the minimum interval spread over the continuum of inputs, regulating the IPMs variation/oscillation, and centering its spread about a target point, are used to prevent data over tting. Furthermore, we develop an approach for using expert opinion during extrapolation. This metamodeling technique is illustrated using a radiation shielding application for space exploration. In this application, we use IPMs to describe the error incurred in predicting the ux of particles resulting from the interaction between a high-energy incident beam and a target.

  18. Genomic predictors for recurrence patterns of hepatocellular carcinoma: model derivation and validation.

    Directory of Open Access Journals (Sweden)

    Ji Hoon Kim

    2014-12-01

    Full Text Available BACKGROUND: Typically observed at 2 y after surgical resection, late recurrence is a major challenge in the management of hepatocellular carcinoma (HCC. We aimed to develop a genomic predictor that can identify patients at high risk for late recurrence and assess its clinical implications. METHODS AND FINDINGS: Systematic analysis of gene expression data from human liver undergoing hepatic injury and regeneration revealed a 233-gene signature that was significantly associated with late recurrence of HCC. Using this signature, we developed a prognostic predictor that can identify patients at high risk of late recurrence, and tested and validated the robustness of the predictor in patients (n = 396 who underwent surgery between 1990 and 2011 at four centers (210 recurrences during a median of 3.7 y of follow-up. In multivariate analysis, this signature was the strongest risk factor for late recurrence (hazard ratio, 2.2; 95% confidence interval, 1.3-3.7; p = 0.002. In contrast, our previously developed tumor-derived 65-gene risk score was significantly associated with early recurrence (p = 0.005 but not with late recurrence (p = 0.7. In multivariate analysis, the 65-gene risk score was the strongest risk factor for very early recurrence (<1 y after surgical resection (hazard ratio, 1.7; 95% confidence interval, 1.1-2.6; p = 0.01. The potential significance of STAT3 activation in late recurrence was predicted by gene network analysis and validated later. We also developed and validated 4- and 20-gene predictors from the full 233-gene predictor. The main limitation of the study is that most of the patients in our study were hepatitis B virus-positive. Further investigations are needed to test our prediction models in patients with different etiologies of HCC, such as hepatitis C virus. CONCLUSIONS: Two independently developed predictors reflected well the differences between early and late recurrence of HCC at the molecular level and provided new

  19. Improving the precision of lake ecosystem metabolism estimates by identifying predictors of model uncertainty

    Science.gov (United States)

    Rose, Kevin C.; Winslow, Luke A.; Read, Jordan S.; Read, Emily K.; Solomon, Christopher T.; Adrian, Rita; Hanson, Paul C.

    2014-01-01

    Diel changes in dissolved oxygen are often used to estimate gross primary production (GPP) and ecosystem respiration (ER) in aquatic ecosystems. Despite the widespread use of this approach to understand ecosystem metabolism, we are only beginning to understand the degree and underlying causes of uncertainty for metabolism model parameter estimates. Here, we present a novel approach to improve the precision and accuracy of ecosystem metabolism estimates by identifying physical metrics that indicate when metabolism estimates are highly uncertain. Using datasets from seventeen instrumented GLEON (Global Lake Ecological Observatory Network) lakes, we discovered that many physical characteristics correlated with uncertainty, including PAR (photosynthetically active radiation, 400-700 nm), daily variance in Schmidt stability, and wind speed. Low PAR was a consistent predictor of high variance in GPP model parameters, but also corresponded with low ER model parameter variance. We identified a threshold (30% of clear sky PAR) below which GPP parameter variance increased rapidly and was significantly greater in nearly all lakes compared with variance on days with PAR levels above this threshold. The relationship between daily variance in Schmidt stability and GPP model parameter variance depended on trophic status, whereas daily variance in Schmidt stability was consistently positively related to ER model parameter variance. Wind speeds in the range of ~0.8-3 m s–1 were consistent predictors of high variance for both GPP and ER model parameters, with greater uncertainty in eutrophic lakes. Our findings can be used to reduce ecosystem metabolism model parameter uncertainty and identify potential sources of that uncertainty.

  20. Joint Bayesian variable and graph selection for regression models with network-structured predictors.

    Science.gov (United States)

    Peterson, Christine B; Stingo, Francesco C; Vannucci, Marina

    2016-03-30

    In this work, we develop a Bayesian approach to perform selection of predictors that are linked within a network. We achieve this by combining a sparse regression model relating the predictors to a response variable with a graphical model describing conditional dependencies among the predictors. The proposed method is well-suited for genomic applications because it allows the identification of pathways of functionally related genes or proteins that impact an outcome of interest. In contrast to previous approaches for network-guided variable selection, we infer the network among predictors using a Gaussian graphical model and do not assume that network information is available a priori. We demonstrate that our method outperforms existing methods in identifying network-structured predictors in simulation settings and illustrate our proposed model with an application to inference of proteins relevant to glioblastoma survival.

  1. Bayesian modeling of measurement error in predictor variables using item response theory

    NARCIS (Netherlands)

    Fox, Gerardus J.A.; Glas, Cornelis A.W.

    2000-01-01

    This paper focuses on handling measurement error in predictor variables using item response theory (IRT). Measurement error is of great important in assessment of theoretical constructs, such as intelligence or the school climate. Measurement error is modeled by treating the predictors as unobserved

  2. Bayesian modeling of measurement error in predictor variables using item response theory

    NARCIS (Netherlands)

    Fox, Jean-Paul; Glas, Cees A.W.

    2000-01-01

    This paper focuses on handling measurement error in predictor variables using item response theory (IRT). Measurement error is of great important in assessment of theoretical constructs, such as intelligence or the school climate. Measurement error is modeled by treating the predictors as unobserved

  3. Predictor characteristics necessary for building a clinically useful risk prediction model: a simulation study

    Directory of Open Access Journals (Sweden)

    Laura Schummers

    2016-09-01

    Full Text Available Abstract Background Compelled by the intuitive appeal of predicting each individual patient’s risk of an outcome, there is a growing interest in risk prediction models. While the statistical methods used to build prediction models are increasingly well understood, the literature offers little insight to researchers seeking to gauge a priori whether a prediction model is likely to perform well for their particular research question. The objective of this study was to inform the development of new risk prediction models by evaluating model performance under a wide range of predictor characteristics. Methods Data from all births to overweight or obese women in British Columbia, Canada from 2004 to 2012 (n = 75,225 were used to build a risk prediction model for preeclampsia. The data were then augmented with simulated predictors of the outcome with pre-set prevalence values and univariable odds ratios. We built 120 risk prediction models that included known demographic and clinical predictors, and one, three, or five of the simulated variables. Finally, we evaluated standard model performance criteria (discrimination, risk stratification capacity, calibration, and Nagelkerke’s r2 for each model. Results Findings from our models built with simulated predictors demonstrated the predictor characteristics required for a risk prediction model to adequately discriminate cases from non-cases and to adequately classify patients into clinically distinct risk groups. Several predictor characteristics can yield well performing risk prediction models; however, these characteristics are not typical of predictor-outcome relationships in many population-based or clinical data sets. Novel predictors must be both strongly associated with the outcome and prevalent in the population to be useful for clinical prediction modeling (e.g., one predictor with prevalence ≥20 % and odds ratio ≥8, or 3 predictors with prevalence ≥10 % and odds ratios ≥4. Area

  4. Exploratory regression analysis: a tool for selecting models and determining predictor importance.

    Science.gov (United States)

    Braun, Michael T; Oswald, Frederick L

    2011-06-01

    Linear regression analysis is one of the most important tools in a researcher's toolbox for creating and testing predictive models. Although linear regression analysis indicates how strongly a set of predictor variables, taken together, will predict a relevant criterion (i.e., the multiple R), the analysis cannot indicate which predictors are the most important. Although there is no definitive or unambiguous method for establishing predictor variable importance, there are several accepted methods. This article reviews those methods for establishing predictor importance and provides a program (in Excel) for implementing them (available for direct download at http://dl.dropbox.com/u/2480715/ERA.xlsm?dl=1) . The program investigates all 2(p) - 1 submodels and produces several indices of predictor importance. This exploratory approach to linear regression, similar to other exploratory data analysis techniques, has the potential to yield both theoretical and practical benefits.

  5. The Optimal Linear Combination of Multiple Predictors Under the Generalized Linear Models.

    Science.gov (United States)

    Jin, Hua; Lu, Ying

    2009-11-15

    Multiple alternative diagnostic tests for one disease are commonly available to clinicians. It's important to use all the good diagnostic predictors simultaneously to establish a new predictor with higher statistical utility. Under the generalized linear model for binary outcomes, the linear combination of multiple predictors in the link function is proved optimal in the sense that the area under the receiver operating characteristic (ROC) curve of this combination is the largest among all possible linear combination. The result was applied to analysis of the data from the Study of Osteoporotic Fractures (SOF) with comparison to Su and Liu's approach.

  6. A comparison of acoustic and observed sediment classifications as predictor variables for modelling biotope distributions in Galway Bay, Ireland

    Science.gov (United States)

    O'Carroll, Jack P. J.; Kennedy, Robert; Ren, Lei; Nash, Stephen; Hartnett, Michael; Brown, Colin

    2017-10-01

    The INFOMAR (Integrated Mapping For the Sustainable Development of Ireland's Marine Resource) initiative has acoustically mapped and classified a significant proportion of Ireland's Exclusive Economic Zone (EEZ), and is likely to be an important tool in Ireland's efforts to meet the criteria of the MSFD. In this study, open source and relic data were used in combination with new grab survey data to model EUNIS level 4 biotope distributions in Galway Bay, Ireland. The correct prediction rates of two artificial neural networks (ANNs) were compared to assess the effectiveness of acoustic sediment classifications versus sediments that were visually classified by an expert in the field as predictor variables. To test for autocorrelation between predictor variables the RELATE routine with Spearman rank correlation method was used. Optimal models were derived by iteratively removing predictor variables and comparing the correct prediction rates of each model. The models with the highest correct prediction rates were chosen as optimal. The optimal models each used a combination of salinity (binary; 0 = polyhaline and 1 = euhaline), proximity to reef (binary; 0 = within 50 m and 1 = outside 50 m), depth (continuous; metres) and a sediment descriptor (acoustic or observed) as predictor variables. As the status of benthic habitats is required to be assessed under the MSFD the Ecological Status (ES) of the subtidal sediments of Galway Bay was also assessed using the Infaunal Quality Index. The ANN that used observed sediment classes as predictor variables could correctly predict the distribution of biotopes 67% of the time, compared to 63% for the ANN using acoustic sediment classes. Acoustic sediment ANN predictions were affected by local sediment heterogeneity, and the lack of a mixed sediment class. The all-round poor performance of ANNs is likely to be a result of the temporally variable and sparsely distributed data within the study area.

  7. An information theoretic approach to select alternate subsets of predictors for data-driven hydrological models

    Science.gov (United States)

    Taormina, R.; Galelli, S.; Karakaya, G.; Ahipasaoglu, S. D.

    2016-11-01

    This work investigates the uncertainty associated to the presence of multiple subsets of predictors yielding data-driven models with the same, or similar, predictive accuracy. To handle this uncertainty effectively, we introduce a novel input variable selection algorithm, called Wrapper for Quasi Equally Informative Subset Selection (W-QEISS), specifically conceived to identify all alternate subsets of predictors in a given dataset. The search process is based on a four-objective optimization problem that minimizes the number of selected predictors, maximizes the predictive accuracy of a data-driven model and optimizes two information theoretic metrics of relevance and redundancy, which guarantee that the selected subsets are highly informative and with little intra-subset similarity. The algorithm is first tested on two synthetic test problems and then demonstrated on a real-world streamflow prediction problem in the Yampa River catchment (US). Results show that complex hydro-meteorological datasets are characterized by a large number of alternate subsets of predictors, which provides useful insights on the underlying physical processes. Furthermore, the presence of multiple subsets of predictors-and associated models-helps find a better trade-off between different measures of predictive accuracy commonly adopted for hydrological modelling problems.

  8. Predictors of Discharge Disposition in Older Adults With Burns: A Study of the Burn Model Systems.

    Science.gov (United States)

    Pham, Tam N; Carrougher, Gretchen J; Martinez, Erin; Lezotte, Dennis; Rietschel, Carly; Holavanahalli, Radha; Kowalske, Karen; Esselman, Peter C

    2015-01-01

    Older patients with burn injury have a greater likelihood for discharge to nursing facilities. Recent research indicates that older patients discharged to nursing facilities are two to three times as likely to die within a 3-year period relative to those discharged to home. In light of these poor long-term outcomes, we conducted this study to identify predictors for discharge to independent vs nonindependent living status in older patients hospitalized for burns. We retrospectively reviewed all older adults (age ≥ 55 years) who were prospectively enrolled in a longitudinal multicenter study of outcomes from 1993 to 2011. Patient, injury, and treatment outcomes data were analyzed. Recognizing that transfer to inpatient rehabilitation may have impacted final hospital discharge disposition: we assessed the likelihood of inpatient rehabilitation stay, based on identified predictors of inpatient rehabilitation. We subsequently performed a logistic regression analysis on the clustered, propensity-matched cohort to assess associations of burn and injury characteristics on the primary outcome of final discharge status. A total of 591 patients aged ≥55 years were treated and discharged alive from three participating U.S. burn centers during the study period. Mean burn size was 14.8% (SD 11.2%) and mean age was 66.7 years (SD 9.3 years). Ninety-three patients had an inpatient rehabilitation stay before discharge (15.7%). Significant factors predictive of inpatient rehabilitation included a burn >20% TBSA, mechanical ventilation, older age, range of motion deficits at acute care discharge, and study site. These factors were included in the propensity model. Four hundred seventy-one patients (80%) were discharged to independent living status. By matched propensity analysis, older age was significantly associated with a higher likelihood of discharge to nonindependent living (P patient factors. Furthermore, clinical practice variations among the three study sites also

  9. Predictors of Academic Performance of University Students: An Application of the Goal Efficacy Model

    Science.gov (United States)

    Klomegah, Roger Yao

    2007-01-01

    This study utilized the goal-efficacy model to examine a) the extent to which index scores of student self-efficacy, self-set goals, assigned goals, and ability (four variables in the model) could predict academic performance of university students; and b) the best predictor of academic performance. The sample comprised 103 undergraduate students…

  10. Predictor Relationships between Values Held by Married Individuals, Resilience and Conflict Resolution Styles: A Model Suggestion

    Science.gov (United States)

    Tosun, Fatma; Dilmac, Bulent

    2015-01-01

    The aim of the present research is to reveal the predictor relationships between the values held by married individuals, resilience and conflict resolution styles. The research adopts a relational screening model that is a sub-type of the general screening model. The sample of the research consists of 375 married individuals, of which 173 are…

  11. The Use of Mixed Models for the Analysis of Mediated Data with Time-Dependent Predictors

    Directory of Open Access Journals (Sweden)

    Emily A. Blood

    2011-01-01

    Full Text Available Linear mixed models (LMMs are frequently used to analyze longitudinal data. Although these models can be used to evaluate mediation, they do not directly model causal pathways. Structural equation models (SEMs are an alternative technique that allows explicit modeling of mediation. The goal of this paper is to evaluate the performance of LMMs relative to SEMs in the analysis of mediated longitudinal data with time-dependent predictors and mediators. We simulated mediated longitudinal data from an SEM and specified delayed effects of the predictor. A variety of model specifications were assessed, and the LMMs and SEMs were evaluated with respect to bias, coverage probability, power, and Type I error. Models evaluated in the simulation were also applied to data from an observational cohort of HIV-infected individuals. We found that when carefully constructed, the LMM adequately models mediated exposure effects that change over time in the presence of mediation, even when the data arise from an SEM.

  12. Reticulocyte production index as a predictor of clinically significant anemia in chronic hepatitis C patients receiving pegylated interferon combination therapy

    Directory of Open Access Journals (Sweden)

    Sheng-Lei Yan

    2016-03-01

    Conclusion: Besides old age and low pretreatment hemoglobin level, our study showed that a reticulocyte production index < 0.9% at Week 4 was a significant factor associated with clinically significant anemia during pegylated interferon combination treatment.

  13. Comparing Bayesian and Maximum Likelihood Predictors in Structural Equation Modeling of Children’s Lifestyle Index

    Directory of Open Access Journals (Sweden)

    Che Wan Jasimah bt Wan Mohamed Radzi

    2016-11-01

    Full Text Available Several factors may influence children’s lifestyle. The main purpose of this study is to introduce a children’s lifestyle index framework and model it based on structural equation modeling (SEM with Maximum likelihood (ML and Bayesian predictors. This framework includes parental socioeconomic status, household food security, parental lifestyle, and children’s lifestyle. The sample for this study involves 452 volunteer Chinese families with children 7–12 years old. The experimental results are compared in terms of root mean square error, coefficient of determination, mean absolute error, and mean absolute percentage error metrics. An analysis of the proposed causal model suggests there are multiple significant interconnections among the variables of interest. According to both Bayesian and ML techniques, the proposed framework illustrates that parental socioeconomic status and parental lifestyle strongly impact children’s lifestyle. The impact of household food security on children’s lifestyle is rejected. However, there is a strong relationship between household food security and both parental socioeconomic status and parental lifestyle. Moreover, the outputs illustrate that the Bayesian prediction model has a good fit with the data, unlike the ML approach. The reasons for this discrepancy between ML and Bayesian prediction are debated and potential advantages and caveats with the application of the Bayesian approach in future studies are discussed.

  14. Committee of machine learning predictors of hydrological models uncertainty

    Science.gov (United States)

    Kayastha, Nagendra; Solomatine, Dimitri

    2014-05-01

    In prediction of uncertainty based on machine learning methods, the results of various sampling schemes namely, Monte Carlo sampling (MCS), generalized likelihood uncertainty estimation (GLUE), Markov chain Monte Carlo (MCMC), shuffled complex evolution metropolis algorithm (SCEMUA), differential evolution adaptive metropolis (DREAM), particle swarm optimization (PSO) and adaptive cluster covering (ACCO)[1] used to build a predictive models. These models predict the uncertainty (quantiles of pdf) of a deterministic output from hydrological model [2]. Inputs to these models are the specially identified representative variables (past events precipitation and flows). The trained machine learning models are then employed to predict the model output uncertainty which is specific for the new input data. For each sampling scheme three machine learning methods namely, artificial neural networks, model tree, locally weighted regression are applied to predict output uncertainties. The problem here is that different sampling algorithms result in different data sets used to train different machine learning models which leads to several models (21 predictive uncertainty models). There is no clear evidence which model is the best since there is no basis for comparison. A solution could be to form a committee of all models and to sue a dynamic averaging scheme to generate the final output [3]. This approach is applied to estimate uncertainty of streamflows simulation from a conceptual hydrological model HBV in the Nzoia catchment in Kenya. [1] N. Kayastha, D. L. Shrestha and D. P. Solomatine. Experiments with several methods of parameter uncertainty estimation in hydrological modeling. Proc. 9th Intern. Conf. on Hydroinformatics, Tianjin, China, September 2010. [2] D. L. Shrestha, N. Kayastha, and D. P. Solomatine, and R. Price. Encapsulation of parameteric uncertainty statistics by various predictive machine learning models: MLUE method, Journal of Hydroinformatic, in press

  15. Stable direction recovery in single-index models with a diverging number of predictors

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Large dimensional predictors are often introduced in regressions to attenuate the possible modeling bias. We consider the stable direction recovery in single-index models in which we solely assume the response Y is independent of the diverging dimensional predictors X when βτ 0 X is given, where β 0 is a p n × 1 vector, and p n →∞ as the sample size n →∞. We first explore sufficient conditions under which the least squares estimation β n0 recovers the direction β 0 consistently even when p n = o(√ n). To enhance the model interpretability by excluding irrelevant predictors in regressions, we suggest an e1-regularization algorithm with a quadratic constraint on magnitude of least squares residuals to search for a sparse estimation of β 0 . Not only can the solution β n of e1-regularization recover β 0 consistently, it also produces sufficiently sparse estimators which enable us to select "important" predictors to facilitate the model interpretation while maintaining the prediction accuracy. Further analysis by simulations and an application to the car price data suggest that our proposed estimation procedures have good finite-sample performance and are computationally efficient.

  16. Taking the Error Term of the Factor Model into Account: The Factor Score Predictor Interval

    Science.gov (United States)

    Beauducel, Andre

    2013-01-01

    The problem of factor score indeterminacy implies that the factor and the error scores cannot be completely disentangled in the factor model. It is therefore proposed to compute Harman's factor score predictor that contains an additive combination of factor and error variance. This additive combination is discussed in the framework of classical…

  17. From Screening to Early Identification and Intervention: Discovering Predictors to Successful Outcomes for Children with Significant Hearing Loss.

    Science.gov (United States)

    Yoshinaga-Itano, Christine

    2003-01-01

    Research findings from a series of longitudinal studies of the language, speech, and social-emotional development of children with hearing impairments and hearing parents found language development is positively and significantly affected by the age of identification of the hearing loss and age of initiation into Colorado early intervention…

  18. Integrating Factor Analysis and a Transgenic Mouse Model to Reveal a Peripheral Blood Predictor of Breast Tumors

    Directory of Open Access Journals (Sweden)

    Nevins Joseph R

    2011-07-01

    Full Text Available Abstract Background Transgenic mouse tumor models have the advantage of facilitating controlled in vivo oncogenic perturbations in a common genetic background. This provides an idealized context for generating transcriptome-based diagnostic models while minimizing the inherent noisiness of high-throughput technologies. However, the question remains whether models developed in such a setting are suitable prototypes for useful human diagnostics. We show that latent factor modeling of the peripheral blood transcriptome in a mouse model of breast cancer provides the basis for using computational methods to link a mouse model to a prototype human diagnostic based on a common underlying biological response to the presence of a tumor. Methods We used gene expression data from mouse peripheral blood cell (PBC samples to identify significantly differentially expressed genes using supervised classification and sparse ANOVA. We employed these transcriptome data as the starting point for developing a breast tumor predictor from human peripheral blood mononuclear cells (PBMCs by using a factor modeling approach. Results The predictor distinguished breast cancer patients from healthy individuals in a cohort of patients independent from that used to build the factors and train the model with 89% sensitivity, 100% specificity and an area under the curve (AUC of 0.97 using Youden's J-statistic to objectively select the model's classification threshold. Both permutation testing of the model and evaluating the model strategy by swapping the training and validation sets highlight its stability. Conclusions We describe a human breast tumor predictor based on the gene expression of mouse PBCs. This strategy overcomes many of the limitations of earlier studies by using the model system to reduce noise and identify transcripts associated with the presence of a breast tumor over other potentially confounding factors. Our results serve as a proof-of-concept for using an

  19. Missing in action: Species competition is a neglected predictor variable in species distribution modelling.

    Science.gov (United States)

    Mpakairi, Kudzai Shaun; Ndaimani, Henry; Tagwireyi, Paradzayi; Gara, Tawanda Winmore; Zvidzai, Mark; Madhlamoto, Daphine

    2017-01-01

    The central role of species competition in shaping community structure in ecosystems is well appreciated amongst ecologists. However species competition is a consistently missing variable in Species Distribution Modelling (SDM). This study presents results of our attempt to incorporate species competition in SDMs. We used a suit of predictor variables including Soil Adjusted Vegetation Index (SAVI), as well as distance from roads, settlements and water, fire frequency and distance from the nearest herbivore sighting (of selected herbivores) to model individual habitat preferences of five grazer species (buffalo, warthog, waterbuck, wildebeest and zebra) with the Ensemble SDM algorithm for Gonarezhou National Park, Zimbabwe. Our results showed that distance from the nearest animal sighting (a proxy for competition among grazers) was the best predictor of the potential distribution of buffalo, wildebeest and zebra but the second best predictor for warthog and waterbuck. Our findings provide evidence to that competition is an important predictor of grazer species' potential distribution. These findings suggest that species distribution modelling that neglects species competition may be inadequate in explaining the potential distribution of species. Therefore our findings encourage the inclusion of competition in SDM as well as potentially igniting discussions that may lead to improving the predictive power of future SDM efforts.

  20. Modeling the predictors of safety behavior in construction workers.

    Science.gov (United States)

    Shin, Dong-Phil; Gwak, Han-Seong; Lee, Dong-Eun

    2015-01-01

    This paper presents a model that quantifies the causal relations among safety variables (latent variables) and workers' safety behavior (indicator) using statistical data and hypotheses obtained from construction workers and existing literatures, respectively. The safety variables that affect workers' safety behaviors are identified from existing studies and operationalized to measure their causal relations with the workers' behaviors. The model identifies the directions and degrees of the effect of every latent variable on the other latent variables and the indicator. Survey questionnaires were administered to construction workers in South Korea. Exploratory and confirmatory factor analyses, Cronbach's α and structural equation modeling were performed to test the causal hypotheses using SPSS 18.0 and AMOS 18.0. This study provides the theoretical model that predicts construction workers' safety behavior on construction sites using path diagram and analysis.

  1. A statistically based seasonal precipitation forecast model with automatic predictor selection and its application to central and south Asia

    Science.gov (United States)

    Gerlitz, Lars; Vorogushyn, Sergiy; Apel, Heiko; Gafurov, Abror; Unger-Shayesteh, Katy; Merz, Bruno

    2016-11-01

    The study presents a statistically based seasonal precipitation forecast model, which automatically identifies suitable predictors from globally gridded sea surface temperature (SST) and climate variables by means of an extensive data-mining procedure and explicitly avoids the utilization of typical large-scale climate indices. This leads to an enhanced flexibility of the model and enables its automatic calibration for any target area without any prior assumption concerning adequate predictor variables. Potential predictor variables are derived by means of a cell-wise correlation analysis of precipitation anomalies with gridded global climate variables under consideration of varying lead times. Significantly correlated grid cells are subsequently aggregated to predictor regions by means of a variability-based cluster analysis. Finally, for every month and lead time, an individual random-forest-based forecast model is constructed, by means of the preliminary generated predictor variables. Monthly predictions are aggregated to running 3-month periods in order to generate a seasonal precipitation forecast. The model is applied and evaluated for selected target regions in central and south Asia. Particularly for winter and spring in westerly-dominated central Asia, correlation coefficients between forecasted and observed precipitation reach values up to 0.48, although the variability of precipitation rates is strongly underestimated. Likewise, for the monsoonal precipitation amounts in the south Asian target area, correlations of up to 0.5 were detected. The skill of the model for the dry winter season over south Asia is found to be low. A sensitivity analysis with well-known climate indices, such as the El Niño- Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO) and the East Atlantic (EA) pattern, reveals the major large-scale controlling mechanisms of the seasonal precipitation climate for each target area. For the central Asian target areas, both

  2. A predictor-corrector algorithm to estimate the fractional flow in oil-water models

    Energy Technology Data Exchange (ETDEWEB)

    Savioli, Gabriela B [Laboratorio de IngenierIa de Reservorios, IGPUBA and Departamento de IngenierIa Quimica, Facultad de IngenierIa, Universidad de Buenos Aires, Av. Las Heras 2214 Piso 3 C1127AAR Buenos Aires (Argentina); Berdaguer, Elena M Fernandez [Instituto de Calculo, Facultad de Ciencias Exactas y Naturales, UBA-CONICET and Departamento de Matematica, Facultad de IngenierIa, Universidad de Buenos Aires, 1428 Buenos Aires (Argentina)], E-mail: gsavioli@di.fcen.uba.ar, E-mail: efernan@ic.fcen.uba.ar

    2008-11-01

    We introduce a predictor-corrector algorithm to estimate parameters in a nonlinear hyperbolic problem. It can be used to estimate the oil-fractional flow function from the Buckley-Leverett equation. The forward model is non-linear: the sought- for parameter is a function of the solution of the equation. Traditionally, the estimation of functions requires the selection of a fitting parametric model. The algorithm that we develop does not require a predetermined parameter model. Therefore, the estimation problem is carried out over a set of parameters which are functions. The algorithm is based on the linearization of the parameter-to-output mapping. This technique is new in the field of nonlinear estimation. It has the advantage of laying aside parametric models. The algorithm is iterative and is of predictor-corrector type. We present theoretical results on the inverse problem. We use synthetic data to test the new algorithm.

  3. Comparing Bayesian and Maximum Likelihood Predictors in Structural Equation Modeling of Children’s Lifestyle Index

    OpenAIRE

    Che Wan Jasimah bt Wan Mohamed Radzi; Huang Hui; Hashem Salarzadeh Jenatabadi

    2016-01-01

    Several factors may influence children’s lifestyle. The main purpose of this study is to introduce a children’s lifestyle index framework and model it based on structural equation modeling (SEM) with Maximum likelihood (ML) and Bayesian predictors. This framework includes parental socioeconomic status, household food security, parental lifestyle, and children’s lifestyle. The sample for this study involves 452 volunteer Chinese families with children 7–12 years old. The experimental results a...

  4. OPLS statistical model versus linear regression to assess sonographic predictors of stroke prognosis.

    Science.gov (United States)

    Vajargah, Kianoush Fathi; Sadeghi-Bazargani, Homayoun; Mehdizadeh-Esfanjani, Robab; Savadi-Oskouei, Daryoush; Farhoudi, Mehdi

    2012-01-01

    The objective of the present study was to assess the comparable applicability of orthogonal projections to latent structures (OPLS) statistical model vs traditional linear regression in order to investigate the role of trans cranial doppler (TCD) sonography in predicting ischemic stroke prognosis. The study was conducted on 116 ischemic stroke patients admitted to a specialty neurology ward. The Unified Neurological Stroke Scale was used once for clinical evaluation on the first week of admission and again six months later. All data was primarily analyzed using simple linear regression and later considered for multivariate analysis using PLS/OPLS models through the SIMCA P+12 statistical software package. The linear regression analysis results used for the identification of TCD predictors of stroke prognosis were confirmed through the OPLS modeling technique. Moreover, in comparison to linear regression, the OPLS model appeared to have higher sensitivity in detecting the predictors of ischemic stroke prognosis and detected several more predictors. Applying the OPLS model made it possible to use both single TCD measures/indicators and arbitrarily dichotomized measures of TCD single vessel involvement as well as the overall TCD result. In conclusion, the authors recommend PLS/OPLS methods as complementary rather than alternative to the available classical regression models such as linear regression.

  5. Parameter and Process Significance in Mechanistic Modeling of Cellulose Hydrolysis

    Science.gov (United States)

    Rotter, B.; Barry, A.; Gerhard, J.; Small, J.; Tahar, B.

    2005-12-01

    The rate of cellulose hydrolysis, and of associated microbial processes, is important in determining the stability of landfills and their potential impact on the environment, as well as associated time scales. To permit further exploration in this field, a process-based model of cellulose hydrolysis was developed. The model, which is relevant to both landfill and anaerobic digesters, includes a novel approach to biomass transfer between a cellulose-bound biofilm and biomass in the surrounding liquid. Model results highlight the significance of the bacterial colonization of cellulose particles by attachment through contact in solution. Simulations revealed that enhanced colonization, and therefore cellulose degradation, was associated with reduced cellulose particle size, higher biomass populations in solution, and increased cellulose-binding ability of the biomass. A sensitivity analysis of the system parameters revealed different sensitivities to model parameters for a typical landfill scenario versus that for an anaerobic digester. The results indicate that relative surface area of cellulose and proximity of hydrolyzing bacteria are key factors determining the cellulose degradation rate.

  6. Modeling zoonotic cutaneous leishmaniasis incidence in central Tunisia from 2009-2015: Forecasting models using climate variables as predictors.

    Science.gov (United States)

    Talmoudi, Khouloud; Bellali, Hedia; Ben-Alaya, Nissaf; Saez, Marc; Malouche, Dhafer; Chahed, Mohamed Kouni

    2017-08-01

    Transmission of zoonotic cutaneous leishmaniasis (ZCL) depends on the presence, density and distribution of Leishmania major rodent reservoir and the development of these rodents is known to have a significant dependence on environmental and climate factors. ZCL in Tunisia is one of the most common forms of leishmaniasis. The aim of this paper was to build a regression model of ZCL cases to identify the relationship between ZCL occurrence and possible risk factors, and to develop a predicting model for ZCL's control and prevention purposes. Monthly reported ZCL cases, environmental and bioclimatic data were collected over 6 years (2009-2015). Three rural areas in the governorate of Sidi Bouzid were selected as the study area. Cross-correlation analysis was used to identify the relevant lagged effects of possible risk factors, associated with ZCL cases. Non-parametric modeling techniques known as generalized additive model (GAM) and generalized additive mixed models (GAMM) were applied in this work. These techniques have the ability to approximate the relationship between the predictors (inputs) and the response variable (output), and express the relationship mathematically. The goodness-of-fit of the constructed model was determined by Generalized cross-validation (GCV) score and residual test. There were a total of 1019 notified ZCL cases from July 2009 to June 2015. The results showed seasonal distribution of reported ZCL cases from August to January. The model highlighted that rodent density, average temperature, cumulative rainfall and average relative humidity, with different time lags, all play role in sustaining and increasing the ZCL incidence. The GAMM model could be applied to predict the occurrence of ZCL in central Tunisia and could help for the establishment of an early warning system to control and prevent ZCL in central Tunisia.

  7. Is flow velocity a significant parameter in flood damage modelling?

    Directory of Open Access Journals (Sweden)

    H. Kreibich

    2009-10-01

    Full Text Available Flow velocity is generally presumed to influence flood damage. However, this influence is hardly quantified and virtually no damage models take it into account. Therefore, the influences of flow velocity, water depth and combinations of these two impact parameters on various types of flood damage were investigated in five communities affected by the Elbe catchment flood in Germany in 2002. 2-D hydraulic models with high to medium spatial resolutions were used to calculate the impact parameters at the sites in which damage occurred. A significant influence of flow velocity on structural damage, particularly on roads, could be shown in contrast to a minor influence on monetary losses and business interruption. Forecasts of structural damage to road infrastructure should be based on flow velocity alone. The energy head is suggested as a suitable flood impact parameter for reliable forecasting of structural damage to residential buildings above a critical impact level of 2 m of energy head or water depth. However, general consideration of flow velocity in flood damage modelling, particularly for estimating monetary loss, cannot be recommended.

  8. Model updating of complex structures using the combination of component mode synthesis and Kriging predictor.

    Science.gov (United States)

    Liu, Yang; Li, Yan; Wang, Dejun; Zhang, Shaoyi

    2014-01-01

    Updating the structural model of complex structures is time-consuming due to the large size of the finite element model (FEM). Using conventional methods for these cases is computationally expensive or even impossible. A two-level method, which combined the Kriging predictor and the component mode synthesis (CMS) technique, was proposed to ensure the successful implementing of FEM updating of large-scale structures. In the first level, the CMS was applied to build a reasonable condensed FEM of complex structures. In the second level, the Kriging predictor that was deemed as a surrogate FEM in structural dynamics was generated based on the condensed FEM. Some key issues of the application of the metamodel (surrogate FEM) to FEM updating were also discussed. Finally, the effectiveness of the proposed method was demonstrated by updating the FEM of a real arch bridge with the measured modal parameters.

  9. Model Updating of Complex Structures Using the Combination of Component Mode Synthesis and Kriging Predictor

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2014-01-01

    Full Text Available Updating the structural model of complex structures is time-consuming due to the large size of the finite element model (FEM. Using conventional methods for these cases is computationally expensive or even impossible. A two-level method, which combined the Kriging predictor and the component mode synthesis (CMS technique, was proposed to ensure the successful implementing of FEM updating of large-scale structures. In the first level, the CMS was applied to build a reasonable condensed FEM of complex structures. In the second level, the Kriging predictor that was deemed as a surrogate FEM in structural dynamics was generated based on the condensed FEM. Some key issues of the application of the metamodel (surrogate FEM to FEM updating were also discussed. Finally, the effectiveness of the proposed method was demonstrated by updating the FEM of a real arch bridge with the measured modal parameters.

  10. Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor Models

    Directory of Open Access Journals (Sweden)

    Jiangyun Li

    2014-01-01

    Full Text Available Automatic rolling process is a high-speed system which always requires high-speed control and communication capabilities. Meanwhile, it is also a typical complex electromechanical system; distributed control has become the mainstream of computer control system for rolling mill. Generally, the control system adopts the 2-level control structure—basic automation (Level 1 and process control (Level 2—to achieve the automatic gauge control. In Level 1, there is always a certain distance between the roll gap of each stand and the thickness testing point, leading to the time delay of gauge control. Smith predictor is a method to cope with time-delay system, but the practical feedback control based on traditional Smith predictor cannot get the ideal control result, because the time delay is hard to be measured precisely and in some situations it may vary in a certain range. In this paper, based on adaptive Smith predictor, we employ multiple models to cover the uncertainties of time delay. The optimal model will be selected by the proposed switch mechanism. Simulations show that the proposed multiple Smith model method exhibits excellent performance in improving the control result even for system with jumping time delay.

  11. Evaluation of Axonal Strain as a Predictor for Mild Traumatic Brain Injuries Using Finite Element Modeling.

    Science.gov (United States)

    Giordano, Chiara; Kleiven, Svein

    2014-11-01

    Finite element (FE) models are often used to study the biomechanical effects of traumatic brain injury (TBI). Measures based on mechanical responses, such as principal strain or invariants of the strain tensor, are used as a metric to predict the risk of injury. However, the reliability of inferences drawn from these models depends on the correspondence between the mechanical measures and injury data, as well as the establishment of accurate thresholds of tissue injury. In the current study, a validated anisotropic FE model of the human head is used to evaluate the hypothesis that strain in the direction of fibers (axonal strain) is a better predictor of TBI than maximum principal strain (MPS), anisotropic equivalent strain (AESM) and cumulative strain damage measure (CSDM). An analysis of head kinematics-based metrics, such as head injury criterion (HIC) and brain injury criterion (BrIC), is also provided. Logistic regression analysis is employed to compare binary injury data (concussion/no concussion) with continuous strain/kinematics data. The threshold corresponding to 50% of injury probability is determined for each parameter. The predictive power (area under the ROC curve, AUC) is calculated from receiver operating characteristic (ROC) curve analysis. The measure with the highest AUC is considered to be the best predictor of mTBI. Logistic regression shows a statistical correlation between all the mechanical predictors and injury data for different regions of the brain. Peaks of axonal strain have the highest AUC and determine a strain threshold of 0.07 for corpus callosum and 0.15 for the brainstem, in agreement with previously experimentally derived injury thresholds for reversible axonal injury. For a data set of mild TBI from the national football league, the strain in the axonal direction is found to be a better injury predictor than MPS, AESM, CSDM, BrIC and HIC.

  12. Salivary protein levels as a predictor of perceived astringency in model systems and solid foods.

    Science.gov (United States)

    Fleming, Erin E; Ziegler, Gregory R; Hayes, John E

    2016-09-01

    Salivary protein difference value (SP D-value) is a quantitative measure of salivary protein replenishment, which reportedly relates to individual differences in perceived astringency. This in vitro measure is calculated as the difference in total salivary protein before (S1) and after (S2) stimulation with tannic acid, with a greater absolute value (S2-S1) indicating less protein replenishment. Others report that this measure predicts perceived astringency and liking of liquid model systems and beverages containing added polyphenols. Whether this relationship generalizes to astringent compounds other than polyphenols, or to solid foods is unknown. Here, the associations between SP D-values and perceived astringency and overall liking/disliking for alum and tannic acid (experiment 1) as well as solid chocolate-flavored compound coating with added tannic acid or grape seed extract (GSE) (experiment 2) were examined. In both experiments, participants (n=84 and 81, respectively) indicated perceived intensity of astringency, bitterness, sweetness, and sourness, and degree of liking of either aqueous solutions, or solid chocolate-flavored compound coating with added astringents. Data were analyzed via linear regression, and as discrete groups for comparison to prior work. Three discrete groups were formed based on first and third quartile splits of the SP D-value distribution: low (LR), medium (MR), and high responding (HR) individuals. In experiment 1, significantly higher mean astringency ratings were observed for the HR as compared to the LR/MR groups for alum and tannic acid, confirming and extending prior work. In experiment 2, significantly higher mean astringency ratings were also observed for HR as compared to LR groups in solid chocolate-flavored compound containing added tannic acid or GSE. Significant differences in liking were found between HR and LR groups for alum and tannic acid in water, but no significant differences in liking were observed for

  13. Using digital elevation models as an environmental predictor for soil clay contents

    DEFF Research Database (Denmark)

    Greve, Mogens Humlekrog; Bou Kheir, Rania; Greve, Mette Balslev

    2012-01-01

    The objective of this study was to evaluate the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) as an environmental predictor for soil clay content (SCC). It was based on the applicability of different DEMs, i.e., SRTM with 90-m resolution and airborne Light Detection...... and Ranging (LIDAR) (in 24- and 90-m resolution), using regression-tree analysis. Ten terrain parameters were generated from these DEMs. These terrain parameters were used along other environmental variables to statistically explain SCC content in Denmark. Results indicated that the SRTM tree model (T1: 90-m...

  14. Minimal percentage of dose received by 90% of the urethra (%UD90 is the most significant predictor of PSA bounce in patients who underwent low-dose-rate brachytherapy (LDR-brachytherapy for prostate cancer

    Directory of Open Access Journals (Sweden)

    Tanaka Nobumichi

    2012-09-01

    Full Text Available Abstract Background To clarify the significant clinicopathological and postdosimetric parameters to predict PSA bounce in patients who underwent low-dose-rate brachytherapy (LDR-brachytherapy for prostate cancer. Methods We studied 200 consecutive patients who received LDR-brachytherapy between July 2004 and November 2008. Of them, 137 patients did not receive neoadjuvant or adjuvant androgen deprivation therapy. One hundred and forty-two patients were treated with LDR-brachytherapy alone, and 58 were treated with LDR-brachytherapy in combination with external beam radiation therapy. The cut-off value of PSA bounce was 0.1 ng/mL. The incidence, time, height, and duration of PSA bounce were investigated. Clinicopathological and postdosimetric parameters were evaluated to elucidate independent factors to predict PSA bounce in hormone-naïve patients who underwent LDR-brachytherapy alone. Results Fifty patients (25% showed PSA bounce and 10 patients (5% showed PSA failure. The median time, height, and duration of PSA bounce were 17 months, 0.29 ng/mL, and 7.0 months, respectively. In 103 hormone-naïve patients treated with LDR-brachytherapy alone, and univariate Cox proportional regression hazard model indicated that age and minimal percentage of the dose received by 30% and 90% of the urethra were independent predictors of PSA bounce. With a multivariate Cox proportional regression hazard model, minimal percentage of the dose received by 90% of the urethra was the most significant parameter of PSA bounce. Conclusions Minimal percentage of the dose received by 90% of the urethra was the most significant predictor of PSA bounce in hormone-naïve patients treated with LDR-brachytherapy alone.

  15. Spatial modelling of marine organisms in Forsmark and Oskarshamn. Including calculation of physical predictor variables

    Energy Technology Data Exchange (ETDEWEB)

    Carlen, Ida; Nikolopoulos, Anna; Isaeus, Martin (AquaBiota Water Research, Stockholm (SE))

    2007-06-15

    GIS grids (maps) of marine parameters were created using point data from previous site investigations in the Forsmark and Oskarshamn areas. The proportion of global radiation reaching the sea bottom in Forsmark and Oskarshamn was calculated in ArcView, using Secchi depth measurements and the digital elevation models for the respective area. The number of days per year when the incoming light exceeds 5 MJ/m2 at the bottom was then calculated using the result of the previous calculations together with measured global radiation. Existing modelled grid-point data on bottom and pelagic temperature for Forsmark were interpolated to create surface covering grids. Bottom and pelagic temperature grids for Oskarshamn were calculated using point measurements to achieve yearly averages for a few points and then using regressions with existing grids to create new maps. Phytoplankton primary production in Forsmark was calculated using point measurements of chlorophyll and irradiance, and a regression with a modelled grid of Secchi depth. Distribution of biomass of macrophyte communities in Forsmark and Oskarshamn was calculated using spatial modelling in GRASP, based on field data from previous surveys. Physical parameters such as those described above were used as predictor variables. Distribution of biomass of different functional groups of fish in Forsmark was calculated using spatial modelling based on previous surveys and with predictor variables such as physical parameters and results from macrophyte modelling. All results are presented as maps in the report. The quality of the modelled predictions varies as a consequence of the quality and amount of the input data, the ecology and knowledge of the predicted phenomena, and by the modelling technique used. A substantial part of the variation is not described by the models, which should be expected for biological modelling. Therefore, the resulting grids should be used with caution and with this uncertainty kept in mind. All

  16. Multiresolution wavelet-ANN model for significant wave height forecasting.

    Digital Repository Service at National Institute of Oceanography (India)

    Deka, P.C.; Mandal, S.; Prahlada, R.

    Hybrid wavelet artificial neural network (WLNN) has been applied in the present study to forecast significant wave heights (Hs). Here Discrete Wavelet Transformation is used to preprocess the time series data (Hs) prior to Artificial Neural Network...

  17. Scalar Dark Matter Models with Significant Internal Bremsstrahlung

    CERN Document Server

    Giacchino, Federica; Tytgat, Michel H G

    2013-01-01

    There has been interest recently on particle physics models that may give rise to sharp gamma ray spectral features from dark matter annihilation. Because dark matter is supposed to be electrically neutral, it is challenging to build weakly interacting massive particle models that may accommodate both a large cross section into gamma rays at, say, the Galactic center, and the right dark matter abundance. In this work, we consider the gamma ray signatures of a class of scalar dark matter models that interact with Standard Model dominantly through heavy vector-like fermions (the vector-like portal). We focus on a real scalar singlet S annihilating into lepton-antilepton pairs. Because this two-body final-state annihilation channel is d-wave suppressed in the chiral limit, we show that virtual internal bremsstrahlung emission of a gamma ray gives a large correction, both today and at the time of freeze-out. For the sake of comparison, we confront this scenario to the familiar case of a Majorana singlet annihilat...

  18. The Causal Meaning of Genomic Predictors and How It Affects Construction and Comparison of Genome-Enabled Selection Models

    Science.gov (United States)

    Valente, Bruno D.; Morota, Gota; Peñagaricano, Francisco; Gianola, Daniel; Weigel, Kent; Rosa, Guilherme J. M.

    2015-01-01

    The term “effect” in additive genetic effect suggests a causal meaning. However, inferences of such quantities for selection purposes are typically viewed and conducted as a prediction task. Predictive ability as tested by cross-validation is currently the most acceptable criterion for comparing models and evaluating new methodologies. Nevertheless, it does not directly indicate if predictors reflect causal effects. Such evaluations would require causal inference methods that are not typical in genomic prediction for selection. This suggests that the usual approach to infer genetic effects contradicts the label of the quantity inferred. Here we investigate if genomic predictors for selection should be treated as standard predictors or if they must reflect a causal effect to be useful, requiring causal inference methods. Conducting the analysis as a prediction or as a causal inference task affects, for example, how covariates of the regression model are chosen, which may heavily affect the magnitude of genomic predictors and therefore selection decisions. We demonstrate that selection requires learning causal genetic effects. However, genomic predictors from some models might capture noncausal signal, providing good predictive ability but poorly representing true genetic effects. Simulated examples are used to show that aiming for predictive ability may lead to poor modeling decisions, while causal inference approaches may guide the construction of regression models that better infer the target genetic effect even when they underperform in cross-validation tests. In conclusion, genomic selection models should be constructed to aim primarily for identifiability of causal genetic effects, not for predictive ability. PMID:25908318

  19. Assessment of Predictor-Corrector strategy for the Burridge-Knopoff model

    CERN Document Server

    Moschetta, Pierfrancesco

    2016-01-01

    A Predictor-Corrector strategy is employed for the numerical simulation of the one-dimensional Burridge-Knopoff model of earthquakes. This approach is totally explicit and allows to reproduce the main features of the model. The results achieved are compared with those of several previous works available in the literature, in order to state the effectiveness of the novel numerical strategy. Simulations are performed starting from the simplest cases and are aimed at studying the qualitative trends of the phenomena under analysis. By increasing the size of the associated differential system, it is possible to examine data on the basis of the Gutenberg-Richter statistical law. Finally, some tests are conducted to investigate the continuum limit of the discrete Burridge-Knopoff model towards a macroscopic dynamics.

  20. Clinical significance of interleukin-1 genotype in smoking patients as a predictor of peri-implantitis: A case-control study.

    Science.gov (United States)

    García-Delaney, Cristina; Sánchez-Garcés, Maria-Ángeles; Figueiredo, Rui; Sánchez-Torres, Alba; Gay-Escoda, Cosme

    2015-11-01

    Interleukin-1 (IL-1) is a proinflammatory cytokine that plays an important role in the pathogenesis of periodontitis, and so it might be useful to detect high-risk cases of peri-implantitis. It has been reported that IL-1 polymorphisms and smoking habit have a synergic effect, increasing the incidence of peri-implantitis. The aim of the present study was to evaluate the relationship between IL-1 gene polymorphisms and peri-implantitis in smoking patients. A case-control study was performed in 27 patients with peri-implantitis and 27 patients with healthy implants. All patients included were smokers. IL-1A-C889T, IL-1B+C3953T and IL-1RN+T2018C were identified by polymerase chain reaction (PCR) amplification in order to establish a relation between these variables and the presence of peri-implantitis. A bivariate analysis was performed and odds-ratio (OR) were calculated. The incidence of peri-implantitis was significantly higher in patients with previous history of periodontitis (p=0.024; OR=10.9). Both groups were similar regarding IL-1A-C889T, IL-1B+C3953T and IL-1RN+T2018C genotypes. No increased risk in heavy smokers with IL-1 polymorphism was found. IL-1 genotypes do not seem to be good predictors of peri-implantitis in the great majority of smoking patients. Furthermore, no synergic effect was found between IL-1 genotypes and heavy smokers. Patients with a previous history of periodontitis were more prone to peri-implantitis.

  1. Clinical significance of interleukin-1 genotype in smoking patients as a predictor of peri-implantitis: A case-control study

    Science.gov (United States)

    García-Delaney, Cristina; Sánchez-Garcés, Maria-Ángeles; Sánchez-Torres, Alba; Gay-Escoda, Cosme

    2015-01-01

    Background Interleukin-1 (IL-1) is a proinflammatory cytokine that plays an important role in the pathogenesis of periodontitis, and so it might be useful to detect high-risk cases of peri-implantitis. It has been reported that IL-1 polymorphisms and smoking habit have a synergic effect, increasing the incidence of peri-implantitis. The aim of the present study was to evaluate the relationship between IL-1 gene polymorphisms and peri-implantitis in smoking patients. Material and Methods A case-control study was performed in 27 patients with peri-implantitis and 27 patients with healthy implants. All patients included were smokers. IL-1A-C889T, IL-1B+C3953T and IL-1RN+T2018C were identified by polymerase chain reaction (PCR) amplification in order to establish a relation between these variables and the presence of peri-implantitis. A bivariate analysis was performed and odds-ratio (OR) were calculated. Results The incidence of peri-implantitis was significantly higher in patients with previous history of periodontitis (p=0.024; OR=10.9). Both groups were similar regarding IL-1A-C889T, IL-1B+C3953T and IL-1RN+T2018C genotypes. No increased risk in heavy smokers with IL-1 polymorphism was found. Conclusions IL-1 genotypes do not seem to be good predictors of peri-implantitis in the great majority of smoking patients. Furthermore, no synergic effect was found between IL-1 genotypes and heavy smokers. Patients with a previous history of periodontitis were more prone to peri-implantitis. Key words:Peri-implantitis, interleukin-1 genotype positive, case-control study, smoking. PMID:26449434

  2. The significance of genetics in pathophysiologic models of premature birth.

    Science.gov (United States)

    Uberos, Jose

    2017-05-31

    Prematurity is a major health problem in all countries, especially in certain ethic groups and increasing recurrence imply the influence of genetic factors. Published genetic polymorphisms are identified in relation to the 4 pathophysiological models of prematurity described: Chorioamniotic-decidual inflammation, premature contraction pathway, decidual haemorrhage and susceptibility to environmental toxins. 240 articles are identified, 52 articles are excluded because they are not original, not written in English or duplicated. From them 125 articles were included in qualitative analysis This review aims to update recent knowledge about genes associated with premature birth.

  3. Oil cracking to gases: Kinetic modeling and geological significance

    Institute of Scientific and Technical Information of China (English)

    TIAN Hui; WANG Zhaoming; XIAO Zhongyao; LI Xianqing; XIAO Xianming

    2006-01-01

    ATriassic oil sample from LN14 of Tarim Basin was pyrolyzed using the sealed gold tubes at 200-620℃ under a constant pressure of 50 MPa.The gaseous and residual soluble hydrocarbons were analyzed. The results show that the cracking of oil to gas can be divided into two distinct stages: the primary generation of total C1-5 gases from liquid oil characterized by the dominance of C2-5 hydrocarbons and the secondary or further cracking of C2-5gases to methane and carbon-rich matters leading to the progressive dryness of gases. Based on the experimental data, the kinetic parameters were determined for the primary generation and secondary cracking of oil cracking gases and extrapolated to geological conditions to predict the thermal stability and cracking extent of crude oil. Finally, an evolution model for the thermal destruction of crude oil was proposed and its implications to the migration and accumulation of oil cracking gases were discussed.

  4. Accuracy of pitch matching significantly improved by live voice model.

    Science.gov (United States)

    Granot, Roni Y; Israel-Kolatt, Rona; Gilboa, Avi; Kolatt, Tsafrir

    2013-05-01

    Singing is, undoubtedly, the most fundamental expression of our musical capacity, yet an estimated 10-15% of Western population sings "out-of-tune (OOT)." Previous research in children and adults suggests, albeit inconsistently, that imitating a human voice can improve pitch matching. In the present study, we focus on the potentially beneficial effects of the human voice and especially the live human voice. Eighteen participants varying in their singing abilities were required to imitate in singing a set of nine ascending and descending intervals presented to them in five different randomized blocked conditions: live piano, recorded piano, live voice using optimal voice production, recorded voice using optimal voice production, and recorded voice using artificial forced voice production. Pitch and interval matching in singing were much more accurate when participants repeated sung intervals as compared with intervals played to them on the piano. The advantage of the vocal over the piano stimuli was robust and emerged clearly regardless of whether piano tones were played live and in full view or were presented via recording. Live vocal stimuli elicited higher accuracy than recorded vocal stimuli, especially when the recorded vocal stimuli were produced in a forced vocal production. Remarkably, even those who would be considered OOT singers on the basis of their performance when repeating piano tones were able to pitch match live vocal sounds, with deviations well within the range of what is considered accurate singing (M=46.0, standard deviation=39.2 cents). In fact, those participants who were most OOT gained the most from the live voice model. Results are discussed in light of the dual auditory-motor encoding of pitch analogous to that found in speech. Copyright © 2013 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

  5. Gender and single nucleotide polymorphisms in MTHFR, BHMT, SPTLC1, CRBP2R, and SCARB1 are significant predictors of plasma homocysteine normalized by RBC folate in healthy adults.

    Science.gov (United States)

    Using linear regression models, we studied the main and two-way interaction effects of the predictor variables gender, age, BMI, and 64 folate/vitamin B-12/homocysteine/lipid/cholesterol-related single nucleotide polymorphisms (SNP) on log-transformed plasma homocysteine normalized by red blood cell...

  6. A stochastic model for optimizing composite predictors based on gene expression profiles.

    Science.gov (United States)

    Ramanathan, Murali

    2003-07-01

    This project was done to develop a mathematical model for optimizing composite predictors based on gene expression profiles from DNA arrays and proteomics. The problem was amenable to a formulation and solution analogous to the portfolio optimization problem in mathematical finance: it requires the optimization of a quadratic function subject to linear constraints. The performance of the approach was compared to that of neighborhood analysis using a data set containing cDNA array-derived gene expression profiles from 14 multiple sclerosis patients receiving intramuscular inteferon-beta1a. The Markowitz portfolio model predicts that the covariance between genes can be exploited to construct an efficient composite. The model predicts that a composite is not needed for maximizing the mean value of a treatment effect: only a single gene is needed, but the usefulness of the effect measure may be compromised by high variability. The model optimized the composite to yield the highest mean for a given level of variability or the least variability for a given mean level. The choices that meet this optimization criteria lie on a curve of composite mean vs. composite variability plot referred to as the "efficient frontier." When a composite is constructed using the model, it outperforms the composite constructed using the neighborhood analysis method. The Markowitz portfolio model may find potential applications in constructing composite biomarkers and in the pharmacogenomic modeling of treatment effects derived from gene expression endpoints.

  7. Structural equation model of intellectual change and continuity and predictors of intelligence in older men.

    Science.gov (United States)

    Gold, D P; Andres, D; Etezadi, J; Arbuckle, T; Schwartzman, A; Chaikelson, J

    1995-06-01

    This study examined the effects of abilities as a young adult, an engaged lifestyle, personality, age, and health on continuity and change in intellectual abilities from early to late adulthood. A battery of measures, including a verbal and nonverbal intelligence test, was given to 326 Canadian army veterans. Archival data provided World War Two enlistment scores on the same intelligence test for this sample: Results indicated relative stability of intellectual scores across 40 years, with increases in vocabulary and decreases in arithmetic, verbal analogies, and nonverbal skills. Young adult intelligence was the most important determinant of older adult performance. Predictors for verbal intelligence were consistent with an engagement model of intellectual maintenance but also indicated the importance of introversion-extraversion and age. Nonverbal intelligence in late life was predicted by young adult nonverbal scores, age, health, and introversion-extraversion.

  8. Predictors of breast self - examination among female teachers in Ethiopia using health belief model.

    Science.gov (United States)

    Birhane, Negussie; Mamo, Abebe; Girma, Eshetu; Asfaw, Shifera

    2015-01-01

    Breast cancer is by far the most frequent cancer of women. It is the second leading cause of death in women worldwide. Approximately one out of eight women develops breast cancer all over the world. Majority of cases of cancer of the breast are detected by women themselves, stressing the importance of breast self-examination. The main objective of this study was to assess predictors of breast self-examination among female teachers in Kafa Zone, South West part of Ethiopia. A cross-sectional study was conducted among randomly selected 315 female teachers. Self administered a structured questionnaire including socio-demographic characteristics, knowledge about breast cancer and perception of teachers on breast self examination using the Champion's revised Health Belief Model sub scales used as data collection instrument. Multivariable logistic regression analyses were used to identify independent predictors of breast self -examination performance. Three hundred and fifteen female teachers were participated in this study. Their mean age was 33 SD [±7] years. Only 52 (16.5 %) participants ever heard about breast self examination and from those who heard about breast self examination 38 (73.07 %) of them ever performed breast self examination. After controlling for possible confounding factors, the result showed that knowledge towards breast self examination, perceived susceptibility, perceived severity and the net perceived benefit were found to be the major predictors of breast self examination. This study revealed that breast self examination performance among female teachers was very low. Therefore, behavior change communication and interventions that emphasize different domains that increase the perceived threat to breast cancer as well as on the benefits of breast self-examination to increase the perception of the teachers in an integrated manner may be the most effective strategies that should be considered by the health offices and educational offices. These

  9. How many predictors in species distribution models at the landscape scale? Land use versus LiDAR-derived canopy height

    NARCIS (Netherlands)

    Ficetola, G.F.; Bonardi, A.; Mücher, C.A.; Gilissen, N.L.M.; Padoa-Schioppa, E.

    2014-01-01

    At the local spatial scale, land-use variables are often employed as predictors for ecological niche models (ENMs). Remote sensing can provide additional synoptic information describing vegetation structure in detail. However, there is limited knowledge on which environmental variables and how many

  10. Spatial autocorrelation in predictors reduces the impact of positional uncertainty in occurrence data on species distribution modelling

    NARCIS (Netherlands)

    Naimi, B.; Skidmore, A.K.; Groen, T.A.; Hamm, N.A.S.

    2011-01-01

    Aim To investigate the impact of positional uncertainty in species occurrences on the predictions of seven commonly used species distribution models (SDMs), and explore its interaction with spatial autocorrelation in predictors. Methods A series of artificial datasets covering 155 scenarios includin

  11. Selection properties of Type II maximum likelihood (empirical bayes) linear models with individual variance components for predictors

    NARCIS (Netherlands)

    Jamil, T.; Braak, ter C.J.F.

    2012-01-01

    Maximum Likelihood (ML) in the linear model overfits when the number of predictors (M) exceeds the number of objects (N). One of the possible solution is the Relevance vector machine (RVM) which is a form of automatic relevance detection and has gained popularity in the pattern recognition machine l

  12. Modeling predictors of risky drug use behavior among male street laborers in urban Vietnam.

    Science.gov (United States)

    Nguyen, Van Huy; Dunne, Michael P; Debattista, Joseph

    2013-05-07

    The application of theoretical frameworks for modeling predictors of drug risk among male street laborers remains limited. The objective of this study was to test a modified version of the IMB (Information-Motivation-Behavioral Skills Model), which includes psychosocial stress, and compare this modified version with the original IMB model in terms of goodness-of-fit to predict risky drug use behavior among this population. In a cross-sectional study, social mapping technique was conducted to recruit 450 male street laborers from 135 street venues across 13 districts of Hanoi city, Vietnam, for face-to-face interviews. Structural equation modeling (SEM) was used to analyze data from interviews. Overall measures of fit via SEM indicated that the original IMB model provided a better fit to the data than the modified version. Although the former model was able to predict a lesser variance than the latter (55% vs. 62%), it was of better fit. The findings suggest that men who are better informed and motivated for HIV prevention are more likely to report higher behavioral skills, which, in turn, are less likely to be engaged in risky drug use behavior. This was the first application of the modified IMB model for drug use in men who were unskilled, unregistered laborers in urban settings. An AIDS prevention program for these men should not only distribute information and enhance motivations for HIV prevention, but consider interventions that could improve self-efficacy for preventing HIV infection. Future public health research and action may also consider broader factors such as structural social capital and social policy to alter the conditions that drive risky drug use among these men.

  13. A method for finding the optimal predictor indices for local wave climate conditions

    Science.gov (United States)

    Camus, Paula; Méndez, Fernando J.; Losada, Inigo J.; Menéndez, Melisa; Espejo, Antonio; Pérez, Jorge; Rueda, Ana; Guanche, Yanira

    2014-07-01

    In this study, a method to obtain local wave predictor indices that take into account the wave generation process is described and applied to several locations. The method is based on a statistical model that relates significant wave height with an atmospheric predictor, defined by sea level pressure fields. The predictor is composed of a local and a regional part, representing the sea and the swell wave components, respectively. The spatial domain of the predictor is determined using the Evaluation of Source and Travel-time of wave Energy reaching a Local Area (ESTELA) method. The regional component of the predictor includes the recent historical atmospheric conditions responsible for the swell wave component at the target point. The regional predictor component has a historical temporal coverage ( n-days) different to the local predictor component (daily coverage). Principal component analysis is applied to the daily predictor in order to detect the dominant variability patterns and their temporal coefficients. Multivariate regression model, fitted at daily scale for different n-days of the regional predictor, determines the optimum historical coverage. The monthly wave predictor indices are selected applying a regression model using the monthly values of the principal components of the daily predictor, with the optimum temporal coverage for the regional predictor. The daily predictor can be used in wave climate projections, while the monthly predictor can help to understand wave climate variability or long-term coastal morphodynamic anomalies.

  14. Predictors of intention to smoke among junior high school students in Shanghai, China: an empirical test of the information-motivation-behavioral skills (IMB model.

    Directory of Open Access Journals (Sweden)

    Chendi Zhu

    Full Text Available BACKGROUND: Adolescent smoking is a worldwide problem that is particularly severe in low- and middle-income countries. Many endogenous and environmental factors affect the intention to smoke, so a comprehensive model is needed to understand the significance and relationship of predictors. The study aimed to test the associations among information-motivation-behavioral skills (IMB model constructs as predictors of intention to smoke in junior high school students in Shanghai, China. METHODS: We conducted a cross-sectional study of 16,500 junior high school students in Shanghai, China. Data on tobacco-related information, motivation, behavioral skills, and behaviors were collected from students. Structural equation model (SEM was used to assess the IMB model. RESULTS: The mean age of participants was 13.8 years old (standard deviation = 1.02; range 11-17. The experimental smoking rate among junior high school students was 6.6% and 8.7% of the participants expected that they would be smokers in 5 years. The IMB model provided acceptable fit to the data (comparative fit index = 0.984, root mean square error of approximation = 0.04. Intention to smoke was predicted by behavioral skills (β = 0.670, P < 0.001 and motivation (β = 0.095, P<0.001 among junior high school students. CONCLUSION: The IMB model provides a good understanding of the predictors of intention to smoke and it suggests future interventions among junior high school students should focus on improving motivation and behavioral skills.

  15. Predictors of intention to smoke among junior high school students in Shanghai, China: an empirical test of the information-motivation-behavioral skills (IMB) model.

    Science.gov (United States)

    Zhu, Chendi; Cai, Yong; Ma, Jin; Li, Na; Zhu, Jingfen; He, Yaping; Redmon, Pamela; Qiao, Yun

    2013-01-01

    Adolescent smoking is a worldwide problem that is particularly severe in low- and middle-income countries. Many endogenous and environmental factors affect the intention to smoke, so a comprehensive model is needed to understand the significance and relationship of predictors. The study aimed to test the associations among information-motivation-behavioral skills (IMB) model constructs as predictors of intention to smoke in junior high school students in Shanghai, China. We conducted a cross-sectional study of 16,500 junior high school students in Shanghai, China. Data on tobacco-related information, motivation, behavioral skills, and behaviors were collected from students. Structural equation model (SEM) was used to assess the IMB model. The mean age of participants was 13.8 years old (standard deviation = 1.02; range 11-17). The experimental smoking rate among junior high school students was 6.6% and 8.7% of the participants expected that they would be smokers in 5 years. The IMB model provided acceptable fit to the data (comparative fit index = 0.984, root mean square error of approximation = 0.04). Intention to smoke was predicted by behavioral skills (β = 0.670, P intention to smoke and it suggests future interventions among junior high school students should focus on improving motivation and behavioral skills.

  16. A simple model for predicting lung cancer occurrence in a lung cancer screening program: The Pittsburgh Predictor.

    Science.gov (United States)

    Wilson, David O; Weissfeld, Joel

    2015-07-01

    A user-friendly method for assessing lung cancer risk may help standardize selection of current and former smokers for screening. We evaluated a simple 4-factor model, the Pittsburgh Predictor, against two well-known, but more complicated models for predicting lung cancer risk. Trained against outcomes observed in the National Lung Screening Trial (NLST), the Pittsburgh Predictor used four risk factors, duration of smoking, smoking status, smoking intensity, and age, to predict 6-year lung cancer incidence. After calibrating the Bach and PLCOM2012 models to outcomes observed in the low-dose computed tomography arm of the NLST, we compared model calibration, discrimination, and clinical usefulness (net benefit) in the NLST and Pittsburgh Lung Screening Study (PLuSS) populations. The Pittsburgh Predictor, Bach, and PLCOM2012 represented risk equally well, except for the tendency of PLCOM2012 to overestimate risk in subjects at highest risk. Relative to the Pittsburgh Predictor, Bach and PLCOM2012 increased the area under the receiver operator characteristic curve by 0.007-0.009 and 0.012-0.021 units, respectively, depending on study population. Across a clinically relevant span of 6-year lung cancer risk thresholds (0.01-0.05), Bach and PLCOM2012 increased net benefit by less than 0.1% in NLST and 0.3% in PLuSS. In exchange for a small reduction in prediction accuracy, a simpler lung cancer risk prediction model may facilitate standardized procedures for advising and selecting patients with respect to lung cancer screening. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  17. Remarriage Beliefs as Predictors of Marital Quality and Positive Interaction in Stepcouples: An Actor-Partner Interdependence Model.

    Science.gov (United States)

    Garneau, Chelsea L; Higginbotham, Brian; Adler-Baeder, Francesca

    2015-12-01

    Using an Actor-Partner Interdependence Model, we examined remarriage beliefs as predictors of marital quality and positive interaction in a sample of 179 stepcouples. Three beliefs were measured using subscales from the Remarriage Belief Inventory (RMBI) including success is slim, children are the priority, and finances should be pooled. Several significant actor and partner effects were found for both wives' and husbands' beliefs. Wives' marital quality was positively associated with their own beliefs that finances should be pooled and negatively associated with their own beliefs that success is slim. Wives' reports of their own and spouses' positive interaction were both positively associated with their beliefs that finances should be pooled. Their reports of spouses' positive interaction were also negatively associated with husbands' beliefs that success is slim. Husbands' marital quality was positively associated with wives' beliefs that children are the priority, positively associated with their own beliefs that finances should be pooled, and negatively with success is slim. Positive interaction for husbands was positively associated with wives' beliefs that finances should be pooled and negatively associated with their own beliefs that success is slim. Finally, husbands' reports of positive interaction for their spouses were positively associated with wives' beliefs that finances should be pooled. Implications for future research utilizing dyadic data analysis with stepcouples are addressed.

  18. Using hierarchical linear modeling to explore predictors of pain after total hip and knee arthroplasty as a consequence of osteoarthritis.

    Science.gov (United States)

    Halket, Ashley; Stratford, Paul W; Kennedy, Deborah M; Woodhouse, Linda J

    2010-02-01

    Hierarchical linear modeling was used to establish differences in, and the average pattern of, recovery of the pain subscale of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and 2 composite performance-specific measures of pain as well as to determine if significant individual variations exist in the growth curves for each measure. Predictors of postoperative pain were also of interest. One hundred forty-seven patients undergoing unilateral primary hip or knee arthroplasty completed 4 performance measures-self-paced 40-m walk, timed up and go, stair test, and 6-minute walk-and the WOMAC prearthroplasty and at multiple points in time between 2 and 27 weeks postarthroplasty. Although patients reported different levels of postoperative pain initially, similar recovery patterns were noted. Predictive variables were found to be site of joint arthroplasty and WOMAC prearthroplasty pain scores for the WOMAC pain subscale, the site of joint arthroplasty and sex for the first composite pain score, and sex for the second composite. 2010 Elsevier Inc. All rights reserved.

  19. Multivariate zero-inflated modeling with latent predictors: Modeling feedback behavior

    NARCIS (Netherlands)

    Fox, Gerardus J.A.

    2013-01-01

    In educational studies, the use of computer-based assessments leads to the collection of multiple outcomes to assess student performance. The student-specific outcomes are correlated and often measured in different scales, such as continuous and count outcomes. A multivariate zero-inflated model

  20. Predictors of Self-Care Behaviors among Diabetic Patients Referred to Yazd Diabetes Research Centre Based on Extended Health Belief Model

    Directory of Open Access Journals (Sweden)

    MH Baghianimoghadam

    2007-12-01

    Full Text Available Introduction: Diabetes is the most common disease related to metabolism disorders with long term complications. It needs lifelong specific self-care, as it causes a promotion in quality of life and decreases disease costs. The Health Belief Model (HBM is a psychological model that attempts to explain and predict health behaviors. This is done by focusing on the attitudes and beliefs of individuals. The model has been used for studying diabetes self care behaviors. The aim of this study was determination of predictors of self-care behaviors among diabetes patients referred to Yazd diabetes research centre based on extended health belief model. Methods: This cross-sectional study carried out on 120 diabetic patients referred to Yazd diabetes research centre who were entered in the study by convenience sampling. A questionnaire was used for data collection with a private interview which included questions regarding extended health belief model constructs including perceived benefits, barriers, severity, sensitivity, threat, self-efficacy, social support, metabolic control and locus of control and some demographic variables. Results: There was a positive significant correlation between model variable of perceived benefits, severity, sensitivity, threat, self-efficacy, social support, metabolic control and internal locus of control with self-care behaviors, and also a negative significant correlation between perceived barriers (P=0.001,chance locus of control (P=0.037 and self-care behaviors. The above variables explained 45.3 % of variance in diabetes self-care behaviors, with self-efficacy as the strongest predictor. Conclusion: The results of this study approved the effectiveness of extended health belief model in predicting self-care behaviors among diabetic patients, which can therefore be used as a framework for designing and implementing educational intervention programs for control of diabetes.

  1. ABSENCE OF SEPTAL Q WAVES: An Important Predictor of Significant Coronary Artery Disease and Mainly Proximal Stenosis of the Left Anterior Descending Artery.

    Science.gov (United States)

    Matta, Anthony; Kallab, Kamal; Kharma, Alexandre

    2016-01-01

    Data concerning the correlation between the absence of septal q waves and significant stenosis of proximal left anterior descending (LAD) artery shows conflicting results. This retrospective study was conducted to show that absence of septal q waves in leads V5-V6 could be of value in predicting significant coronary artery disease (CAD) and mainly significant proximal LAD coronary artery stenosis. Our study included 500 consecutive patients who had coronary angiography, retrospectively chosen, excluding patients with acute coronary syndromes, and patients with abnormal ECGs (abnormal QRS duration, pathological q waves and hemiblocks). ECG and angiography films were reviewed. For the 2x2 tables analysis, a chi-square test was used. Of the 500 patients, 386 had significant CAD defined as 70% luminal stenosis, and 260 had no septal q wave. Of the 386 patients with significant CAD, 233 (60%) did not have septal q waves. Of 260 who did not have septal q wave, 192 (73%) had significant stenosis of proximal LAD. Statistical analysis shows that significant CAD correlates with the absence of septal q waves, with a sensitivity of 60% and a specificity of 76%, and that stenosis of proximal LAD could be predicted by absence of septal q waves in leads V5-V6 with a sensitivity of 83% and a specificity of 74%. The absence of septal q waves in leads V5-V6 on the ECG correlates with the presence of significant CAD and is of highly predictive value in those with significant stenosis of proximal LAD (p < 0.0001).

  2. Predictors of condom use behaviors based on the Health Belief Model (HBM among female sex workers: a cross-sectional study in Hubei Province, China.

    Directory of Open Access Journals (Sweden)

    Jinzhu Zhao

    Full Text Available BACKGROUND: HIV infection related to commercial sexual contact is a serious public health issue in China. The objectives of the present study are to explore the predictors of condom use among female sex workers (FSWs in China and examine the relationship between Health Belief Model (HBM constructs. METHODOLOGY/PRINCIPAL FINDINGS: A cross-sectional study was conducted in two cities (Wuhan and Suizhou in Hubei Province, China, between July 2009 and June 2010. A total of 427 FSWs were recruited through mediators from the 'low-tier' entertainment establishments. Data were obtained by self-administered questionnaires. Structural equation models were constructed to examine the association. We collected 363 valid questionnaires. Within the context of HBM, perceived severity of HIV mediated through perceived benefits of condom use had a weak effect on condom use (r=0.07. Perceived benefits and perceived barriers were proximate determinants of condom use (r=0.23 and r=-0.62, respectively. Self-efficacy had a direct effect on perceived severity, perceived benefits, and perceived barriers, which was indirectly associated with condom use behaviors (r=0.36. CONCLUSIONS/SIGNIFICANCE: The HBM provides a useful framework for investigating predictors of condom use behaviors among FSWs. Future HIV prevention interventions should focus on increasing perceived benefits of condom use, reducing barriers to condoms use, and improving self-efficacy among FSWs.

  3. Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictors.

    Science.gov (United States)

    Heddam, Salim; Kisi, Ozgur

    2017-07-01

    In this paper, several extreme learning machine (ELM) models, including standard extreme learning machine with sigmoid activation function (S-ELM), extreme learning machine with radial basis activation function (R-ELM), online sequential extreme learning machine (OS-ELM), and optimally pruned extreme learning machine (OP-ELM), are newly applied for predicting dissolved oxygen concentration with and without water quality variables as predictors. Firstly, using data from eight United States Geological Survey (USGS) stations located in different rivers basins, USA, the S-ELM, R-ELM, OS-ELM, and OP-ELM were compared against the measured dissolved oxygen (DO) using four water quality variables, water temperature, specific conductance, turbidity, and pH, as predictors. For each station, we used data measured at an hourly time step for a period of 4 years. The dataset was divided into a training set (70%) and a validation set (30%). We selected several combinations of the water quality variables as inputs for each ELM model and six different scenarios were compared. Secondly, an attempt was made to predict DO concentration without water quality variables. To achieve this goal, we used the year numbers, 2008, 2009, etc., month numbers from (1) to (12), day numbers from (1) to (31) and hour numbers from (00:00) to (24:00) as predictors. Thirdly, the best ELM models were trained using validation dataset and tested with the training dataset. The performances of the four ELM models were evaluated using four statistical indices: the coefficient of correlation (R), the Nash-Sutcliffe efficiency (NSE), the root mean squared error (RMSE), and the mean absolute error (MAE). Results obtained from the eight stations indicated that: (i) the best results were obtained by the S-ELM, R-ELM, OS-ELM, and OP-ELM models having four water quality variables as predictors; (ii) out of eight stations, the OP-ELM performed better than the other three ELM models at seven stations while the R

  4. Pretreatment direct bilirubin and total cholesterol are significant predictors of overall survival in advanced non-small-cell lung cancer patients with EGFR mutations.

    Science.gov (United States)

    Zhang, Yanwei; Xu, Jianlin; Lou, Yuqing; Hu, Song; Yu, Keke; Li, Rong; Zhang, Xueyan; Jin, Bo; Han, Baohui

    2017-04-01

    This study was designed to examine the prediction of pretreatment circulating bilirubin and cholesterol for overall survival in 459 advanced non-small-cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutations. Circulating total bilirubin, direct bilirubin (DB), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) levels were measured at baseline. The mean age (standard deviation) of all study patients was 58.7 (10.5) years, and 42.9% of them was males. Ever smokers accounted for 27.0% and lung adenocarcinoma for 90.4%. The median follow-up time and survival time were 29.5 and 34.9 months, respectively. Patients with higher DB had a 1.68-fold increased risk of death compared with patients with lower DB (hazard ratio [HR] = 1.68, 95% confidence interval [CI]: 1.22-2.30, p = 0.001), while patients with higher TC were at a 63% reduced risk of death compared with patients with lower TC (HR = 0.37, 95% CI: 0.20-0.67, p = 0.001). As for HDL-C, patients with higher levels had the risk of death reduced by 46% (HR = 0.54, 95% CI: 0.29-1.00, p = 0.049) compared with patients with lower levels. After the Bonferroni correction, only DB and TC were significantly associated with NSCLC survival. Our findings demonstrate for the first time that pretreatment DB was identified as a significant risk factor, yet TC as a protective factor, for overall survival in NSCLC patients with EGFR mutations. © 2016 UICC.

  5. Significance of radiation models in investigating the flow phenomena around a Jovian entry body

    Science.gov (United States)

    Tiwari, S. N.; Subramanian, S. V.

    1978-01-01

    Formulation is presented to demonstrate the significance of a simplified radiation model in investigating the flow-phenomena in the viscous radiating shock layer of a Jovian entry body. For this, a nongray absorption model for hydrogen-helium gas is developed which consists of 30 steps over the spectral range of 0-20 eV. By employing this model results were obtained for temperature, pressure, density, and radiative flux in the shock layer and along the body surface. These are compared with results of two sophisticated radiative transport models available in the literature. Use of the present radiation model results in significant reduction in computational time. Results of this model are found to be in general agreement with results of other models. It is concluded that use of the present model is justified in investigating the flow phenomena around a Jovian entry body because it is relatively simple, computationally fast, and yields fairly accurate results.

  6. Shallowness of tropical low clouds as a predictor of climate models' response to warming

    Science.gov (United States)

    Brient, Florent; Schneider, Tapio; Tan, Zhihong; Bony, Sandrine; Qu, Xin; Hall, Alex

    2016-07-01

    How tropical low clouds change with climate remains the dominant source of uncertainty in global warming projections. An analysis of an ensemble of CMIP5 climate models reveals that a significant part of the spread in the models' climate sensitivity can be accounted by differences in the climatological shallowness of tropical low clouds in weak-subsidence regimes: models with shallower low clouds in weak-subsidence regimes tend to have a higher climate sensitivity than models with deeper low clouds. The dynamical mechanisms responsible for the model differences are analyzed. Competing effects of parameterized boundary-layer turbulence and shallow convection are found to be essential. Boundary-layer turbulence and shallow convection are typically represented by distinct parameterization schemes in current models—parameterization schemes that often produce opposing effects on low clouds. Convective drying of the boundary layer tends to deepen low clouds and reduce the cloud fraction at the lowest levels; turbulent moistening tends to make low clouds more shallow but affects the low-cloud fraction less. The relative importance different models assign to these opposing mechanisms contributes to the spread of the climatological shallowness of low clouds and thus to the spread of low-cloud changes under global warming.

  7. Predictors of poor outcomes after significant chest trauma in multiply injured patients: a retrospective analysis from the German Trauma Registry (Trauma Register DGU®)

    Science.gov (United States)

    2014-01-01

    Background Blunt thoracic trauma is one of the critical injury mechanisms in multiply injured trauma victims. Although these patients present a plethora of potential structural damages to vital organs, it remains debated which injuries actually influence outcome and thereby should be addressed initially. Hence, the aim of this study was to identify the influence of critical structural damages on mortality. Methods All patients in the database of the TraumaRegister DGU® (TR-DGU) from 2002–2011 with AIS Chest ≥ 2, blunt trauma, age of 16 or older and an ISS ≥ 16 were analyzed. Outcome parameters were in-hospital mortality as well as ventilation time in patients surviving the initial 14 days after trauma. Results 22613 Patients were included (mean ISS 30.5 ± 12.6; 74.7% male; Mean Age 46.1 ± 197 years; mortality 17.5%; mean duration of ventilation 7.3 ± 11.5; mean ICU stay 11.7 ± 14.1 days). Only a limited number of specific injuries had a significant impact on survival. Major thoracic vessel injuries (AIS ≥5), bilateral lung contusion, bilateral flail chest, structural heart injury (AIS ≥3) significantly influence mortality in study patients. Several extrathoracic factors (age, blood transfusion, systolic blood pressure and extrathoracic severe injuries) were also predictive of increased mortality. Most injuries of the thoracic wall had no or only a moderate effect on the duration of ventilation. Injuries to the lung (laceration, contusion or pneumothoraces) had a moderate prolonging effect. Cardiac injuries and severe injuries to the thoracic vessels induced a substantially prolonged ventilation interval. Conclusions We demonstrate quantitatively the influence of specific structural damages of the chest on critical outcome parameters. While most injuries of the chest wall have no or only limited impact in the study collective, injuries to the lung overall show adverse outcome. Injuries to the heart or thoracic vessels have a

  8. Quasi-degenerate Neutrino mass models and their significance: A model independent investigation

    CERN Document Server

    Roy, S

    2016-01-01

    The prediction of possible ordering of neutrino masses relies mostly on the model selected. Alienating the $\\mu-\\tau$ interchange symmetry from discrete flavour symmetry based models, turns the neutrino mass matrix less predictive. But this inspires one to seek the answer from other phenomenological frameworks. We need a proper parametrization of the neutrino mass matrices concerning individual hierarchies. In the present work, we attempt to study the six different cases of Quasi-degenerate (QDN) neutrino models. The related mass matrices, $m_{LL}^{\

  9. Predictors of breast self - examination among female teachers in Ethiopia using health belief model

    OpenAIRE

    Birhane, Negussie; Mamo, Abebe; Girma, Eshetu; Asfaw, Shifera

    2015-01-01

    Background Breast cancer is by far the most frequent cancer of women. It is the second leading cause of death in women worldwide. Approximately one out of eight women develops breast cancer all over the world. Majority of cases of cancer of the breast are detected by women themselves, stressing the importance of breast self-examination. The main objective of this study was to assess predictors of breast self-examination among female teachers in Kafa Zone, South West part of Ethiopia. Methods ...

  10. Diversity As A Predictor Of Leadership Effectiveness

    Directory of Open Access Journals (Sweden)

    Richard Herrera

    2013-05-01

    Full Text Available Drawing upon theexisting literature, this study investigated the significance of Diversity as apredictor of leadership effectiveness, as it relates to the MultidimensionalMeasure of Leader-Member Exchange (LMX-MDM.  A study of 300 working adults found that therewas a significant positive relationship between Diversity and the four LMXdimensions of Contribution, Loyalty, Affect, and Professional Respect.  Collectivism and religious affiliation wereboth strong predictors with regard to Contribution.  With regard to the dimension of Loyalty;collectivism, gender egalitarianism, and age helped to increase ratings of thesupervisor and perceptions of leadership.  Affect only had one significant predictor, collectivism. The LMX dimension of ProfessionalRespect was found to have four significant predictors, including collectivism, religiousaffiliation, age, and years as a manager.  Further regression analysis indicated that theDiversity dimension, Collectivism, was the driving factor of the relationship.  This outcome indicated that Collectivism was astrong predictor of how positively participants rated their attitudes towardtheir immediate supervisor and perceptions of leadership.  The results of this study indicate that diversity,particularly with regard to collectivism, is a positive predictor of leadershipeffectiveness using the LMX model.  Furthermore,it strengthens the argument that organizations must be prepared to re-evaluatetheir policies with regard to diversity in the organization, particularly withrespect to Collectivism.

  11. Significant uncertainty in global scale hydrological modeling from precipitation data errors

    NARCIS (Netherlands)

    Weiland, Frederiek C. Sperna; Vrugt, Jasper A.; van Beek, Rens (L. ) P. H.; Weerts, Albrecht H.; Bierkens, Marc F. P.

    2015-01-01

    In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we

  12. Significant uncertainty in global scale hydrological modeling from precipitation data erros

    NARCIS (Netherlands)

    Sperna Weiland, F.; Vrugt, J.A.; Beek, van P.H.; Weerts, A.H.; Bierkens, M.F.P.

    2015-01-01

    In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we

  13. Predictors of employees’ psychophysical health and sickness absenteeism: Modelling based on REBT framework

    Directory of Open Access Journals (Sweden)

    Popov Boris

    2016-01-01

    Full Text Available The main objective of the study was to examine whether negative experiences at work, irrational beliefs, alone and in interaction, and negative affectivity as a mediator, could predict psychosomatic complaints and frequency of sickness absenteeism. The hypothesized model showed acceptable fit to the data, suggesting that negative affectivity mediates the relationship between negative experiences and irrational beliefs on the one hand, and psychosomatic complaints on the other. The results also revealed no significant effect of interaction between negative experiences and irrational beliefs, while fatigue and physical symptoms have a significant and direct effect on the number of days of absence. It was concluded that the lack of an effect of psychological symptoms on absenteeism may indicate that employees in Serbia do not see them as a sufficient reason for sick leave. The results are discussed within frameworks of Rational-emotive behaviour therapy and strategic stress management approach.

  14. The Significance of the Bystander Effect: Modeling, Experiments, and More Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Brenner, David J.

    2009-07-22

    Non-targeted (bystander) effects of ionizing radiation are caused by intercellular signaling; they include production of DNA damage and alterations in cell fate (i.e. apoptosis, differentiation, senescence or proliferation). Biophysical models capable of quantifying these effects may improve cancer risk estimation at radiation doses below the epidemiological detection threshold. Understanding the spatial patterns of bystander responses is important, because it provides estimates of how many bystander cells are affected per irradiated cell. In a first approach to modeling of bystander spatial effects in a three-dimensional artificial tissue, we assumed the following: (1) The bystander phenomenon results from signaling molecules (S) that rapidly propagate from irradiated cells and decrease in concentration (exponentially in the case of planar symmetry) as distance increases. (2) These signals can convert cells to a long-lived epigenetically activated state, e.g. a state of oxidative stress; cells in this state are more prone to DNA damage and behavior alterations than normal and therefore exhibit an increased response (R) for many end points (e.g. apoptosis, differentiation, micronucleation). These assumptions were implemented by a mathematical formalism and computational algorithms. The model adequately described data on bystander responses in the 3D system using a small number of adjustable parameters. Mathematical models of radiation carcinogenesis are important for understanding mechanisms and for interpreting or extrapolating risk. There are two classes of such models: (1) long-term formalisms that track pre-malignant cell numbers throughout an entire lifetime but treat initial radiation dose-response simplistically and (2) short-term formalisms that provide a detailed initial dose-response even for complicated radiation protocols, but address its modulation during the subsequent cancer latency period only indirectly. We argue that integrating short- and long

  15. Predictors and patterns of problematic Internet game use using a decision tree model.

    Science.gov (United States)

    Rho, Mi Jung; Jeong, Jo-Eun; Chun, Ji-Won; Cho, Hyun; Jung, Dong Jin; Choi, In Young; Kim, Dai-Jin

    2016-09-01

    Background and aims Problematic Internet game use is an important social issue that increases social expenditures for both individuals and nations. This study identified predictors and patterns of problematic Internet game use. Methods Data were collected from online surveys between November 26 and December 26, 2014. We identified 3,881 Internet game users from a total of 5,003 respondents. A total of 511 participants were assigned to the problematic Internet game user group according to the Diagnostic and Statistical Manual of Mental Disorders Internet gaming disorder criteria. From the remaining 3,370 participants, we used propensity score matching to develop a normal comparison group of 511 participants. In all, 1,022 participants were analyzed using the chi-square automatic interaction detector (CHAID) algorithm. Results According to the CHAID algorithm, six important predictors were found: gaming costs (50%), average weekday gaming time (23%), offline Internet gaming community meeting attendance (13%), average weekend and holiday gaming time (7%), marital status (4%), and self-perceptions of addiction to Internet game use (3%). In addition, three patterns out of six classification rules were explored: cost-consuming, socializing, and solitary gamers. Conclusion This study provides direction for future work on the screening of problematic Internet game use in adults.

  16. Talent predictors

    Directory of Open Access Journals (Sweden)

    Raquel Lorenzo

    2007-07-01

    Full Text Available The knowledge of talent predictors is the initial point for building diagnosis and encouragement procedures in this field. The meaning of word predictor is to anticipate the future, to divine. Early prediction of high performance is complex problem no resolute by the science yet. There are many discrepancies about what measure and how to do. The article analyze the art state in this problematic because the excellence is determined by the interaction between internal and environmental factors.

  17. Novel submicronized rebamipide liquid with moderate viscosity: significant effects on oral mucositis in animal models.

    Science.gov (United States)

    Nakashima, Takako; Sako, Nobutomo; Matsuda, Takakuni; Uematsu, Naoya; Sakurai, Kazushi; Ishida, Tatsuhiro

    2014-01-01

    This study aimed at developing a novel rebamipide liquid for an effective treatment of oral mucositis. The healing effects of a variety of liquids comprising submicronized rebamipide crystals were investigated using a rat cauterization-induced oral ulcer model. Whereas 2% rebamipide liquid comprising micro-crystals did not exhibit significant curative effect, 2% rebamipide liquids comprising submicronized crystals with moderate viscosities exhibited healing effects following intra-oral administration. The 2% and 4% optimized rebamipide liquids showed significant healing effects in the rat oral ulcer model (prebamipide liquid significantly reduced the percent area of ulcerated injury (prebamipide liquid with moderate viscosity following intra-oral administration showed better both healing effect in the rat oral ulcer model and preventive effect in the rat irradiation-induced glossitis model.

  18. The quest for significance model of radicalization: implications for the management of terrorist detainees.

    Science.gov (United States)

    Dugas, Michelle; Kruglanski, Arie W

    2014-01-01

    Radicalization and its culmination in terrorism represent a grave threat to the security and stability of the world. A related challenge is effective management of extremists who are detained in prison facilities. The major aim of this article is to review the significance quest model of radicalization and its implications for management of terrorist detainees. First, we review the significance quest model, which elaborates on the roles of motivation, ideology, and social processes in radicalization. Secondly, we explore the implications of the model in relation to the risks of prison radicalization. Finally, we analyze the model's implications for deradicalization strategies and review preliminary evidence for the effectiveness of a rehabilitation program targeting components of the significance quest. Based on this evidence, we argue that the psychology of radicalization provides compelling reason for the inclusion of deradicalization efforts as an essential component of the management of terrorist detainees. Copyright © 2014 John Wiley & Sons, Ltd.

  19. The Job Demands-Resources model as predictor of work identity and work engagement: A comparative analysis

    Directory of Open Access Journals (Sweden)

    Roslyn De Braine

    2011-05-01

    Full Text Available Orientation: Research shows that engaged employees experience high levels of energy and strong identification with their work, hence this study’s focus on work identity and dedication.Research purpose: This study explored possible differences in the Job Demands-Resources model (JD-R as predictor of overall work engagement, dedication only and work-based identity, through comparative predictive analyses.Motivation for the study: This study may shed light on the dedication component of work engagement. Currently no literature indicates that the JD-R model has been used to predict work-based identity.Research design: A census-based survey was conducted amongst a target population of 23134 employees that yielded a sample of 2429 (a response rate of about 10.5%. The Job Demands- Resources scale (JDRS was used to measure job demands and job resources. A work-based identity scale was developed for this study. Work engagement was studied with the Utrecht Work Engagement Scale (UWES. Factor and reliability analyses were conducted on the scales and general multiple regression models were used in the predictive analyses.Main findings: The JD-R model yielded a greater amount of variance in dedication than in work engagement. It, however, yielded the greatest amount of variance in work-based identity, with job resources being its strongest predictor.Practical/managerial implications: Identification and work engagement levels can be improved by managing job resources and demands.Contribution/value-add: This study builds on the literature of the JD-R model by showing that it can be used to predict work-based identity.

  20. Heat waves and climate change: applying the health belief model to identify predictors of risk perception and adaptive behaviours in adelaide, australia.

    Science.gov (United States)

    Akompab, Derick A; Bi, Peng; Williams, Susan; Grant, Janet; Walker, Iain A; Augoustinos, Martha

    2013-05-29

    Heat waves are considered a health risk and they are likely to increase in frequency, intensity and duration as a consequence of climate change. The effects of heat waves on human health could be reduced if individuals recognise the risks and adopt healthy behaviours during a heat wave. The purpose of this study was to determine the predictors of risk perception using a heat wave scenario and identify the constructs of the health belief model that could predict adaptive behaviours during a heat wave. A cross-sectional study was conducted during the summer of 2012 among a sample of persons aged between 30 to 69 years in Adelaide. Participants' perceptions were assessed using the health belief model as a conceptual frame. Their knowledge about heat waves and adaptive behaviours during heat waves was also assessed. Logistic regression analyses were performed to determine the predictors of risk perception to a heat wave scenario and adaptive behaviours during a heat wave. Of the 267 participants, about half (50.9%) had a high risk perception to heat waves while 82.8% had good adaptive behaviours during a heat wave. Multivariate models found that age was a significant predictor of risk perception. In addition, participants who were married (OR = 0.21; 95% CI, 0.07-0.62), who earned a gross annual household income of ≥$60,000 (OR = 0.41; 95% CI, 0.17-0.94) and without a fan (OR = 0.29; 95% CI, 0.11-0.79) were less likely to have a high risk perception to heat waves. Those who were living with others (OR = 2.87; 95% CI, 1.19-6.90) were more likely to have a high risk perception to heat waves. On the other hand, participants with a high perceived benefit (OR = 2.14; 95% CI, 1.00-4.58), a high "cues to action" (OR = 3.71; 95% CI, 1.63-8.43), who had additional training or education after high school (OR = 2.65; 95% CI, 1.25-5.58) and who earned a gross annual household income of ≥$60,000 (OR = 2.66; 95% CI, 1.07-6.56) were more likely to have good adaptive behaviours

  1. Heat Waves and Climate Change: Applying the Health Belief Model to Identify Predictors of Risk Perception and Adaptive Behaviours in Adelaide, Australia

    Directory of Open Access Journals (Sweden)

    Martha Augoustinos

    2013-05-01

    Full Text Available Heat waves are considered a health risk and they are likely to increase in frequency, intensity and duration as a consequence of climate change. The effects of heat waves on human health could be reduced if individuals recognise the risks and adopt healthy behaviours during a heat wave. The purpose of this study was to determine the predictors of risk perception using a heat wave scenario and identify the constructs of the health belief model that could predict adaptive behaviours during a heat wave. A cross-sectional study was conducted during the summer of 2012 among a sample of persons aged between 30 to 69 years in Adelaide. Participants’ perceptions were assessed using the health belief model as a conceptual frame. Their knowledge about heat waves and adaptive behaviours during heat waves was also assessed. Logistic regression analyses were performed to determine the predictors of risk perception to a heat wave scenario and adaptive behaviours during a heat wave. Of the 267 participants, about half (50.9% had a high risk perception to heat waves while 82.8% had good adaptive behaviours during a heat wave. Multivariate models found that age was a significant predictor of risk perception. In addition, participants who were married (OR = 0.21; 95% CI, 0.07–0.62, who earned a gross annual household income of ≥$60,000 (OR = 0.41; 95% CI, 0.17–0.94 and without a fan (OR = 0.29; 95% CI, 0.11–0.79 were less likely to have a high risk perception to heat waves. Those who were living with others (OR = 2.87; 95% CI, 1.19–6.90 were more likely to have a high risk perception to heat waves. On the other hand, participants with a high perceived benefit (OR = 2.14; 95% CI, 1.00–4.58, a high “cues to action” (OR = 3.71; 95% CI, 1.63–8.43, who had additional training or education after high school (OR = 2.65; 95% CI, 1.25–5.58 and who earned a gross annual household income of ≥$60,000 (OR = 2.66; 95% CI, 1.07–6.56 were more likely to

  2. Stable 1-Norm Error Minimization Based Linear Predictors for Speech Modeling

    DEFF Research Database (Denmark)

    Giacobello, Daniele; Christensen, Mads Græsbøll; Jensen, Tobias Lindstrøm;

    2014-01-01

    In linear prediction of speech, the 1-norm error minimization criterion has been shown to provide a valid alternative to the 2-norm minimization criterion. However, unlike 2-norm minimization, 1-norm minimization does not guarantee the stability of the corresponding all-pole filter and can generate...... of the shift operator associated with the particular prediction problem considered. The second method uses the alternative Cauchy bound to impose a convex constraint on the predictor in the 1-norm error minimization. These methods are compared with two existing methods: the Burg method, based on the 1-norm...... minimization of the forward and backward prediction error, and the iteratively reweighted 2-norm minimization known to converge to the 1-norm minimization with an appropriate selection of weights. The evaluation gives proof of the effectiveness of the new methods, performing as well as unconstrained 1-norm...

  3. Non-conventional modeling of extreme significant wave height through random sets

    Institute of Scientific and Technical Information of China (English)

    ZHANG Yi; LAM Jasmine Siu Lee

    2014-01-01

    The analysis and design of offshore structures necessitates the consideration of wave loads. Realistic model-ing of wave loads is particularly important to ensure reliable performance of these structures. Among the available methods for the modeling of the extreme significant wave height on a statistical basis, the peak over threshold method has attracted most attention. This method employs Poisson process to character-ize time-varying properties in the parameters of an extreme value distribution. In this paper, the peak over threshold method is reviewed and extended to account for subjectivity in the modeling. The freedom in selecting the threshold and the time span to separate extremes from the original time series data is incorpo-rated as imprecision in the model. This leads to an extension from random variables to random sets in the probabilistic model for the extreme significant wave height. The extended model is also applied to different periods of the sampled data to evaluate the significance of the climatic conditions on the uncertainties of the parameters.

  4. Prevalence and Predictors of Pre-Diabetes and Diabetes among Adults 18 Years or Older in Florida: A Multinomial Logistic Modeling Approach.

    Directory of Open Access Journals (Sweden)

    Ifechukwude Obiamaka Okwechime

    Full Text Available Individuals with pre-diabetes and diabetes have increased risks of developing macro-vascular complications including heart disease and stroke; which are the leading causes of death globally. The objective of this study was to estimate the prevalence of pre-diabetes and diabetes, and to investigate their predictors among adults ≥18 years in Florida.Data covering the time period January-December 2013, were obtained from Florida's Behavioral Risk Factor Surveillance System (BRFSS. Survey design of the study was declared using SVYSET statement of STATA 13.1. Descriptive analyses were performed to estimate the prevalence of pre-diabetes and diabetes. Predictors of pre-diabetes and diabetes were investigated using multinomial logistic regression model. Model goodness-of-fit was evaluated using both the multinomial goodness-of-fit test proposed by Fagerland, Hosmer, and Bofin, as well as, the Hosmer-Lemeshow's goodness of fit test.There were approximately 2,983 (7.3% and 5,189 (12.1% adults in Florida diagnosed with pre-diabetes and diabetes, respectively. Over half of the study respondents were white, married and over the age of 45 years while 36.4% reported being physically inactive, overweight (36.4% or obese (26.4%, hypertensive (34.6%, hypercholesteremic (40.3%, and 26% were arthritic. Based on the final multivariable multinomial model, only being overweight (Relative Risk Ratio [RRR] = 1.85, 95% Confidence Interval [95% CI] = 1.41, 2.42, obese (RRR = 3.41, 95% CI = 2.61, 4.45, hypertensive (RRR = 1.69, 95% CI = 1.33, 2.15, hypercholesterolemic (RRR = 1.94, 95% CI = 1.55, 2.43, and arthritic (RRR = 1.24, 95% CI = 1.00, 1.55 had significant associations with pre-diabetes. However, more predictors had significant associations with diabetes and the strengths of associations tended to be higher than for the association with pre-diabetes. For instance, the relative risk ratios for the association between diabetes and being overweight (RRR = 2.00, 95

  5. Technology Acceptance Model (TAM As a Predictor Model for Explaining Agricultural Experts Behavior in Acceptance of ICT

    Directory of Open Access Journals (Sweden)

    Amir Alambaigi

    2016-06-01

    Full Text Available This study aimed to develop Technology Acceptance Model (TAM model to explain adoption of information technologies process. a Descriptive – correlation study was conducted and data were collected through a survey. Statistical population was West Azerbaijan Agricultural Extension agents who 120 of them were selected randomly using the Krejcie and Morgan table. A questionnaire was employed to measure the variables in the model. Its validity was confirmed by a panel of experts. The Cronbach's alpha coefficient ranged between from 0.704 to 0.816 show satisfied reliability. For data processing, partial leastsquares (PLS method as a new approach to structural equation modeling was used. The results showed that among three variables for development oftechnology acceptance model including Job relevance, experience and organization willingness to invest, the first and second show significant effects.Thus,Job relevance and experience as an external variable was added to the basic TAM. Other relations between variablesin basic technology acceptance model in current study were also seen significant. Our developed TAM can explain 64% of the actual behavior of employee in information technology utilization. TAM is one of the most influential extensions of Ajzen and Fishbein’s theory of reasoned action (TRA in the literature. The theories behind it assume that when a person forms an intention to act, that s/he will be free to act without limitation. While In the real world there will be many constraints, such as limited freedom to act. For example, people in organized working environments are forced to use most of the relevant applications irrespective of their opinion or attitude. In this research mentioned model was used as a strong model to predict actual use behavior that affected by three variables namely Job relevance, experience and organization willingness to invest.

  6. Teaching physical activities to students with significant disabilities using video modeling.

    Science.gov (United States)

    Cannella-Malone, Helen I; Mizrachi, Sharona V; Sabielny, Linsey M; Jimenez, Eliseo D

    2013-06-01

    The objective of this study was to examine the effectiveness of video modeling on teaching physical activities to three adolescents with significant disabilities. The study implemented a multiple baseline across six physical activities (three per student): jumping rope, scooter board with cones, ladder drill (i.e., feet going in and out), ladder design (i.e., multiple steps), shuttle run, and disc ride. Additional prompt procedures (i.e., verbal, gestural, visual cues, and modeling) were implemented within the study. After the students mastered the physical activities, we tested to see if they would link the skills together (i.e., complete an obstacle course). All three students made progress learning the physical activities, but only one learned them with video modeling alone (i.e., without error correction). Video modeling can be an effective tool for teaching students with significant disabilities various physical activities, though additional prompting procedures may be needed.

  7. A new model to estimate significant wave heights with ERS-1/2 scatterometer data

    Institute of Scientific and Technical Information of China (English)

    GUO Jie; HE Yijun; William Perrie; SHEN Hui; CHU Xiaoqing

    2009-01-01

    A new model is proposed to estimate the significant wave heights with ERS-1/2 scatterometer data. The results show that the relationship between wave parameters and radar backscattering cross section is similar to that between wind and the radar backscattering cross section. Therefore, the relationship between significant wave height and the radar backscattering cross section is established with a neural network algorithm, which is, if the average wave period is ≤7s, the root mean square of significant wave height retrieved from ERS-1/2 data is 0.51 m, or 0.72 m if it is >7s otherwise.

  8. Significance of exchanging SSURGO and STATSGO data when modeling hydrology in diverse physiographic terranes

    Science.gov (United States)

    Williamson, Tanja N.; Taylor, Charles J.; Newson, Jeremy K.

    2013-01-01

    The Water Availability Tool for Environmental Resources (WATER) is a TOPMODEL-based hydrologic model that depends on spatially accurate soils data to function in diverse terranes. In Kentucky, this includes mountainous regions, karstic plateau, and alluvial plains. Soils data are critical because they quantify the space to store water, as well as how water moves through the soil to the stream during storm events. We compared how the model performs using two different sources of soils data--Soil Survey Geographic Database (SSURGO) and State Soil Geographic Database laboratory data (STATSGO)--for 21 basins ranging in size from 17 to 1564 km2. Model results were consistently better when SSURGO data were used, likely due to the higher field capacity, porosity, and available-water holding capacity, which cause the model to store more soil-water in the landscape and improve streamflow estimates for both low- and high-flow conditions. In addition, there were significant differences in the conductivity multiplier and scaling parameter values that describe how water moves vertically and laterally, respectively, as quantified by TOPMODEL. We also evaluated whether partitioning areas that drain to streams via sinkholes in karstic basins as separate hydrologic modeling units (HMUs) improved model performance. There were significant differences between HMUs in properties that control soil-water storage in the model, although the effect of partitioning these HMUs on streamflow simulation was inconclusive.

  9. Determining Predictors of True HIV Status Using an Errors-in-Variables Model with Missing Data

    Science.gov (United States)

    Rindskopf, David; Strauss, Shiela

    2004-01-01

    We demonstrate a model for categorical data that parallels the MIMIC model for continuous data. The model is equivalent to a latent class model with observed covariates; further, it includes simple handling of missing data. The model is used on data from a large-scale study of HIV that had both biological measures of infection and self-report…

  10. Downscaling and projection of precipitation from general circulation model predictors in an equatorial climate region by the automated regression-based statistical method

    Science.gov (United States)

    Amin, Mohd Zaki M.; Islam, Tanvir; Ishak, Asnor M.

    2014-10-01

    The authors have applied an automated regression-based statistical method, namely, the automated statistical downscaling (ASD) model, to downscale and project the precipitation climatology in an equatorial climate region (Peninsular Malaysia). Five precipitation indices are, principally, downscaled and projected: mean monthly values of precipitation (Mean), standard deviation (STD), 90th percentile of rain day amount, percentage of wet days (Wet-day), and maximum number of consecutive dry days (CDD). The predictors, National Centers for Environmental Prediction (NCEP) products, are taken from the daily series reanalysis data, while the global climate model (GCM) outputs are from the Hadley Centre Coupled Model, version 3 (HadCM3) in A2/B2 emission scenarios and Third-Generation Coupled Global Climate Model (CGCM3) in A2 emission scenario. Meanwhile, the predictand data are taken from the arithmetically averaged rain gauge information and used as a baseline data for the evaluation. The results reveal, from the calibration and validation periods spanning a period of 40 years (1961-2000), the ASD model is capable to downscale the precipitation with reasonable accuracy. Overall, during the validation period, the model simulations with the NCEP predictors produce mean monthly precipitation of 6.18-6.20 mm/day (root mean squared error 0.78 and 0.82 mm/day), interpolated, respectively, on HadCM3 and CGCM3 grids, in contrast to 6.00 mm/day as observation. Nevertheless, the model suffers to perform reasonably well at the time of extreme precipitation and summer time, more specifically to generate the CDD and STD indices. The future projections of precipitation (2011-2099) exhibit that there would be an increase in the precipitation amount and frequency in most of the months. Taking the 1961-2000 timeline as the base period, overall, the annual mean precipitation would indicate a surplus projection by nearly 14~18 % under both GCM output cases (HadCM3 A2/B2 scenarios and

  11. Strategies for Testing Statistical and Practical Significance in Detecting DIF with Logistic Regression Models

    Science.gov (United States)

    Fidalgo, Angel M.; Alavi, Seyed Mohammad; Amirian, Seyed Mohammad Reza

    2014-01-01

    This study examines three controversial aspects in differential item functioning (DIF) detection by logistic regression (LR) models: first, the relative effectiveness of different analytical strategies for detecting DIF; second, the suitability of the Wald statistic for determining the statistical significance of the parameters of interest; and…

  12. Neighborhood Crime and Perception of Safety as Predictors of Victimization and Offending Among Youth: A Call for Macro-Level Prevention and Intervention Models.

    Science.gov (United States)

    Hartinger-Saunders, Robin M; Rine, Christine M; Nochajski, Thomas; Wieczorek, William

    2012-09-01

    This paper is one of two in a series that reports detailed findings from a larger study that simultaneously explored individual, family and neighborhood level predictors of victimization and offending among youth. The current analysis aims to identify which neighborhood level factors have better predictive power with regard to type of victimization (direct and vicarious measures) and total offending overtime (Wave 1 and Wave 2). METHODS: Path analysis was conducted using data from a multi-wave, panel study (N=625) of youth ages 16-19 at Wave 1. A best fitting model was determined showing causal pathways from neighborhood level factors including crime and perception of safety, to direct and vicarious victimization through exposure to violence, and subsequent offending. FINDINGS: Neighborhood crime significantly predicted property victimization. Neighborhood crime and perception of safety significantly predicted vicarious victimization by exposure to violence in the neighborhood. Neighborhood crime and perception of safety were significantly associated with Wave 1 offending. Findings highlight the need for professionals who work with youth to be cognizant of how their environments influence their lives. Prevention and intervention models seeking to create sustainable change among youth should consider mezzo and macro level components that build and strengthen neighborhood capacity through community partnerships.

  13. On the significance of the Nash-Sutcliffe efficiency measure for event-based flood models

    Science.gov (United States)

    Moussa, Roger

    2010-05-01

    When modelling flood events, the important challenge that awaits the modeller is first to choose a rainfall-runoff model, then to calibrate a set of parameters that can accurately simulate a number of flood events and related hydrograph shapes, and finally to evaluate the model performance separately on each event using multi-criteria functions. This study analyses the significance of the Nash-Sutcliffe efficiency (NSE) and proposes a new method to assess the performance of flood event models (see Moussa, 2010, "When monstrosity can be beautiful while normality can be ugly : assessing the performance of event-based-flood-models", Hydrological Science Journal, in press). We focus on the specific cases of events difficult to model and characterized by low NSE values, which we call "monsters". The properties of the NSE were analysed as a function of the calculated hydrograph shape and of the benchmark reference model. As application case, a multi-criteria analysis method to assess the model performance on each event is proposed and applied on the Gardon d'Anduze catchment. This paper discusses first the significance of the well-known Nash-Sutcliffe efficiency (NSE) criteria function when calculated separately on flood events. The NSE is a convenient and normalized measure of model performance, but does not provide a reliable basis for comparing the results of different case studies. We show that simulated hydrographs with low or negative values of NSE, called "monsters", can be due solely to a simple lag translation or a homothetic ratio of the observed hydrograph which reproduces the dynamic of the hydrograph, with acceptable errors on other criteria. In the opposite, results show that simulations with a NSE close to 1 can become "monsters" and give very low values (even negative) of the criteria function G, if the average observed discharged used as a benchmark reference model in the NSE is modified. This paper argues that the definition of an appropriate benchmark

  14. RS-predictor

    DEFF Research Database (Denmark)

    Zaretzki, Jed; Bergeron, Charles; Rydberg, Patrik

    2011-01-01

    This article describes RegioSelectivity-Predictor (RS-Predictor), a new in silico method for generating predictive models of P450-mediated metabolism for drug-like compounds. Within this method, potential sites of metabolism (SOMs) are represented as "metabolophores": A concept that describes...... vector that encodes regioselectivity trends across all cases in a training set. The resulting pathway-independent (O-dealkylation vs N-oxidation vs Csp(3) hydroxylation, etc.), isozyme-specific regioselectivity model may be used to predict potential metabolic liabilities. In the present work, cross...

  15. Binary Logistic Regression Modeling of Idle CO Emissions in Order to Estimate Predictors Influences in Old Vehicle Park

    Directory of Open Access Journals (Sweden)

    Branimir Milosavljević

    2015-01-01

    Full Text Available This paper determines, by experiments, the CO emissions at idle running with 1,785 vehicles powered by spark ignition engine, in order to verify the correctness of emissions values with a representative sample of vehicles in Serbia. The permissible emissions limits were considered for three (3 fitted binary logistic regression (BLR models, and the key reason for such analysis is finding the predictors that can have a crucial influence on the accuracy of the estimation whether such vehicles have correct emissions or not. Having summarized the research results, we found out that vehicles produced in Serbia (hereinafter referred to as “domestic vehicles” cause more pollution than imported cars (hereinafter referred to as “foreign vehicles”, although domestic vehicles are of lower average age and mileage. Another trend was observed: low-power vehicles and vehicles produced before 1992 are potentially more serious polluters.

  16. The use of the health belief model to assess predictors of intent to receive the novel (2009 H1N1 influenza vaccine

    Directory of Open Access Journals (Sweden)

    Jean-Venable “Kelly” R.Goode, PharmD, BCPS, FAPhA, FCCP

    2012-01-01

    Full Text Available Objectives: 1 Assess participants’ perceptions of severity, risk, and susceptibility to the novel H1N1 influenza virus and/or vaccine, vaccine benefits and barriers, and cues to action and 2 Identify predictors of participants’ intention to receive the novel H1N1 vaccine.Design: Cross-sectional, descriptive studySetting: Local grocery store chain and university in the central Virginia areaParticipants: Convenience sample of adult college students and grocery store patronsIntervention: Participants filled out an anonymous, self-administered questionnaire based upon the Health Belief Model.Main Outcome Measures: Participants’ predictors of intention to receive the novel H1N1 vaccineResults: A total of 664 participants completed a questionnaire. The majority of participants were aged 25-64 years old (66.9%. The majority were female (69.1%, Caucasian (73.7%, and felt at risk for getting sick from the virus (70.3%. Most disagreed that they would die from the virus (68.0%. Participants received novel H1N1 vaccine recommendations from their physicians (28.2%, pharmacists (20.7%, and nurses (16.1%. The majority intended to receive the H1N1 vaccine (58.1%. Participants were significantly more likely to intend to receive the H1N1 vaccine if they had lower scores on the perceived vaccine barriers domain (OR= 0.57, CI: 0.35-0.93. Physicians’ recommendations (OR=0.26, CI: 0.11-0.62 and 2008 seasonal flu vaccination (OR=0.45, CI: 0.24-0.83 were significant predictors of intention to receive the H1N1 vaccine.Conclusions: Most participants felt at risk for getting the novel H1N1 virus and intended to receive the novel H1N1 vaccine. Educating patients about vaccine benefits and increasing healthcare professionals' vaccine recommendations may increase vaccination rates in future pandemics.

  17. Using animal models to determine the significance of complement activation in Alzheimer's disease

    Directory of Open Access Journals (Sweden)

    Loeffler David A

    2004-10-01

    Full Text Available Abstract Complement inflammation is a major inflammatory mechanism whose function is to promote the removal of microorganisms and the processing of immune complexes. Numerous studies have provided evidence for an increase in this process in areas of pathology in the Alzheimer's disease (AD brain. Because complement activation proteins have been demonstrated in vitro to exert both neuroprotective and neurotoxic effects, the significance of this process in the development and progression of AD is unclear. Studies in animal models of AD, in which brain complement activation can be experimentally altered, should be of value for clarifying this issue. However, surprisingly little is known about complement activation in the transgenic animal models that are popular for studying this disorder. An optimal animal model for studying the significance of complement activation on Alzheimer's – related neuropathology should have complete complement activation associated with senile plaques, neurofibrillary tangles (if present, and dystrophic neurites. Other desirable features include both classical and alternative pathway activation, increased neuronal synthesis of native complement proteins, and evidence for an increase in complement activation prior to the development of extensive pathology. In order to determine the suitability of different animal models for studying the role of complement activation in AD, the extent of complement activation and its association with neuropathology in these models must be understood.

  18. Predictors of work injury in underground mines——an application of a logistic regression model

    Institute of Scientific and Technical Information of China (English)

    E S. Pau

    2009-01-01

    Mine accidents and injuries are complex and generally characterized by several factors starting from personal to technical, and technical to social characteristics. In this study, an attempt has been made to identify the various factors responsible for work related injuries in mines and to estimate the risk of work injury to mine workers. The prediction of work injury in mines was done by a step-by-step multivariate logistic regression modeling with an application to case study mines in India. In total, 18 variables were considered in this study. Most of the variables are not directly quantifiable. Instruments were developed to quantify them through a questionnaire type survey. Underground mine workers were randomly selected for the survey. Responses from 300 participants were used for the analysis. Four variables, age, negative affectivity, job dissatisfaction, and physical hazards, bear significant discriminating power for risk of injury to the workers, comparing between cases and controls in a multivariate situation while controlling all the personal and socio-technical variables. The analysis reveals that negatively affected workers are 2.54 times more prone to injuries than the less negatively affected workers and this factor is a more impOrtant risk factor for the case-study mines. Long term planning through identification of the negative individuals, proper counseling regarding the adverse effects of negative behaviors and special training is urgently required. Care should be taken for the aged and experienced workers in terms of their job responsibility and training requirements. Management should provide a friendly atmosphere during work to increase the confidence of the injury prone miners.

  19. Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

    Science.gov (United States)

    Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

    2017-02-01

    A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is

  20. Rates and predictors of mental stress in Rwanda: investigating the impact of gender, persecution, readiness to reconcile and religiosity via a structural equation model.

    Science.gov (United States)

    Heim, Lale; Schaal, Susanne

    2014-01-01

    As a consequence of the 1994 Rwandan genocide, prevalences of mental disorders are elevated in Rwanda. More knowledge about determinants of mental stress can help to improve mental health services and treatment in the east-central African country. The present study aimed to investigate actual rates of mental stress (posttraumatic stress disorder, syndromal depression and syndromal anxiety) in Rwanda and to examine if gender, persecution during the genocide, readiness to reconcile as well as importance given to religiosity and quality of religiosity are predictors of mental stress. The study comprised a community sample of N = 200 Rwandans from Rwanda's capital Kigali, who experienced the Rwandan genocide. By conducting structured interviews, ten local Master level psychologists examined types of potentially lifetime traumatic events, symptoms of posttraumatic stress disorder (PTSD), depression and anxiety, readiness to reconcile and religiosity. Applying non-recursive structural equation modeling (SEM), the associations between gender, persecution, readiness to reconcile, religiosity and mental stress were investigated. Respondents had experienced an average number of 11.38 types of potentially lifetime traumatic events. Of the total sample, 11% met diagnostic criteria for PTSD, 19% presented with syndromal depression and 23% with syndromal anxiety. Female sex, persecution and readiness to reconcile were significant predictors of mental stress. Twofold association was found between centrality of religion (which captures the importance given to religiosity) and mental stress, showing, that higher mental stress provokes a higher centrality and that higher centrality reduces mental stress. The variables positive and negative religious functioning (which determine the quality of religiosity) respectively had an indirect negative and positive effect on mental stress. Study results provide evidence that rates of mental stress are still elevated in Rwanda and that

  1. Does Statistical Significance Help to Evaluate Predictive Performance of Competing Models?

    Directory of Open Access Journals (Sweden)

    Levent Bulut

    2016-04-01

    Full Text Available In Monte Carlo experiment with simulated data, we show that as a point forecast criterion, the Clark and West's (2006 unconditional test of mean squared prediction errors does not reflect the relative performance of a superior model over a relatively weaker one. The simulation results show that even though the mean squared prediction errors of a constructed superior model is far below a weaker alternative, the Clark- West test does not reflect this in their test statistics. Therefore, studies that use this statistic in testing the predictive accuracy of alternative exchange rate models, stock return predictability, inflation forecasting, and unemployment forecasting should not weight too much on the magnitude of the statistically significant Clark-West tests statistics.

  2. Investigating the Performance of Alternate Regression Weights by Studying All Possible Criteria in Regression Models with a Fixed Set of Predictors

    Science.gov (United States)

    Waller, Niels; Jones, Jeff

    2011-01-01

    We describe methods for assessing all possible criteria (i.e., dependent variables) and subsets of criteria for regression models with a fixed set of predictors, x (where x is an n x 1 vector of independent variables). Our methods build upon the geometry of regression coefficients (hereafter called regression weights) in n-dimensional space. For a…

  3. A background error covariance model of significant wave height employing Monte Carlo simulation

    Institute of Scientific and Technical Information of China (English)

    GUO Yanyou; HOU Yijun; ZHANG Chunmei; YANG Jie

    2012-01-01

    The quality of background error statistics is one of the key components for successful assimilation of observations in a numerical model.The background error covariance(BEC)of ocean waves is generally estimated under an assumption that it is stationary over a period of time and uniform over a domain.However,error statistics are in fact functions of the physical processes governing the meteorological situation and vary with the wave condition.In this paper,we simulated the BEC of the significant wave height(SWH)employing Monte Carlo methods.An interesting result is that the BEC varies consistently with the mean wave direction(MWD).In the model domain,the BEC of the SWH decreases significantly when the MWD changes abruptly.A new BEC model of the SWH based on the correlation between the BEC and MWD was then developed.A case study of regional data assimilation was performed,where the SWH observations of buoy 22001 were used to assess the SWH hindcast.The results show that the new BEC model benefits wave prediction and allows reasonable approximations of anisotropy and inhomogeneous errors.

  4. Predictors of safer sex intentions and protected sex among heterosexual HIV-negative methamphetamine users: an expanded model of the Theory of Planned Behavior.

    Science.gov (United States)

    Mausbach, Brent T; Semple, Shirley J; Strathdee, Steffanie A; Patterson, Thomas L

    2009-01-01

    The purpose of this study was to test a version of the Theory of Planned Behavior (TPB) for predicting safe sex behavior in a sample of 228 HIV-negative heterosexual methamphetamine users. We hypothesized that, in addition to TPB constructs, participants' amount of methamphetamine use and desire to stop unsafe sex behaviors would predict intentions to engage in safer sex behaviors. In turn, we predicted that safer sex intentions would be positively correlated with participants' percentage of protected sex. Hierarchical linear regression indicated that 48% of the total variance in safer sex intentions was predicted by our model, with less negative attitudes toward safer sex, greater normative beliefs, greater control beliefs, less methamphetamine use, less intent to have sex, and greater desire to stop unsafe sex emerging as significant predictors of greater safer sex intentions. Safer sex intentions were positively associated with future percent protected sex (p<0.05). These findings suggest that, among heterosexual methamphetamine users, the TPB is an excellent model for predicting safer sex practices in this population, as are some additional factors (e.g., methamphetamine use). Effective interventions for increasing safer sex practices in methamphetamine user will likely include constructs from this model with augmentations to help reduce methamphetamine use.

  5. Linking Satellite Remote Sensing Based Environmental Predictors to Disease: AN Application to the Spatiotemporal Modelling of Schistosomiasis in Ghana

    Science.gov (United States)

    Wrable, M.; Liss, A.; Kulinkina, A.; Koch, M.; Biritwum, N. K.; Ofosu, A.; Kosinski, K. C.; Gute, D. M.; Naumova, E. N.

    2016-06-01

    90% of the worldwide schistosomiasis burden falls on sub-Saharan Africa. Control efforts are often based on infrequent, small-scale health surveys, which are expensive and logistically difficult to conduct. Use of satellite imagery to predictively model infectious disease transmission has great potential for public health applications. Transmission of schistosomiasis requires specific environmental conditions to sustain freshwater snails, however has unknown seasonality, and is difficult to study due to a long lag between infection and clinical symptoms. To overcome this, we employed a comprehensive 8-year time-series built from remote sensing feeds. The purely environmental predictor variables: accumulated precipitation, land surface temperature, vegetative growth indices, and climate zones created from a novel climate regionalization technique, were regressed against 8 years of national surveillance data in Ghana. All data were aggregated temporally into monthly observations, and spatially at the level of administrative districts. The result of an initial mixed effects model had 41% explained variance overall. Stratification by climate zone brought the R2 as high as 50% for major zones and as high as 59% for minor zones. This can lead to a predictive risk model used to develop a decision support framework to design treatment schemes and direct scarce resources to areas with the highest risk of infection. This framework can be applied to diseases sensitive to climate or to locations where remote sensing would be better suited than health surveys.

  6. LINKING SATELLITE REMOTE SENSING BASED ENVIRONMENTAL PREDICTORS TO DISEASE: AN APPLICATION TO THE SPATIOTEMPORAL MODELLING OF SCHISTOSOMIASIS IN GHANA

    Directory of Open Access Journals (Sweden)

    M. Wrable

    2016-06-01

    Full Text Available 90% of the worldwide schistosomiasis burden falls on sub-Saharan Africa. Control efforts are often based on infrequent, small-scale health surveys, which are expensive and logistically difficult to conduct. Use of satellite imagery to predictively model infectious disease transmission has great potential for public health applications. Transmission of schistosomiasis requires specific environmental conditions to sustain freshwater snails, however has unknown seasonality, and is difficult to study due to a long lag between infection and clinical symptoms. To overcome this, we employed a comprehensive 8-year time-series built from remote sensing feeds. The purely environmental predictor variables: accumulated precipitation, land surface temperature, vegetative growth indices, and climate zones created from a novel climate regionalization technique, were regressed against 8 years of national surveillance data in Ghana. All data were aggregated temporally into monthly observations, and spatially at the level of administrative districts. The result of an initial mixed effects model had 41% explained variance overall. Stratification by climate zone brought the R2 as high as 50% for major zones and as high as 59% for minor zones. This can lead to a predictive risk model used to develop a decision support framework to design treatment schemes and direct scarce resources to areas with the highest risk of infection. This framework can be applied to diseases sensitive to climate or to locations where remote sensing would be better suited than health surveys.

  7. RS-WebPredictor

    DEFF Research Database (Denmark)

    Zaretzki, J.; Bergeron, C.; Huang, T.-W.;

    2013-01-01

    . RS-WebPredictor is the first freely accessible server that predicts the regioselectivity of the last six isozymes. Server execution time is fast, taking on average 2s to encode a submitted molecule and 1s to apply a given model, allowing for high-throughput use in lead optimization projects...

  8. Bulk Insolation Models as Predictors for Locations for High Lunar Hydrogen Concentrations

    Science.gov (United States)

    Mcclanahan, T. P.; Mitrofanov, I.G.; Boynton, W. V.; Chin, G.; Starr, R. D.; Evans, L. G.; Sanin, A.; Livengood, T.; Sagdeev, R.; Milikh, G.

    2013-01-01

    In this study we consider the bulk effects of surface illumination on topography (insolation) and the possible thermodynamic effects on the Moon's hydrogen budget. Insolation is important as one of the dominant loss processes governing distributions of hydrogen volatiles on the Earth, Mars and most recently Mercury. We evaluated three types of high latitude > 65 deg., illumination models that were derived from the Lunar Observing Laser Altimetry (LOLA) digital elevation models (DEM)'s. These models reflect varying accounts of solar flux interactions with the Moon's near-surface. We correlate these models with orbital collimated epithermal neutron measurements made by the Lunar Exploration Neutron Detector (LEND). LEND's measurements derive the Moon's spatial distributions of hydrogen concentration. To perform this analysis we transformed the topographic model into an insolation model described by two variables as each pixels 1) slope and 2) slope angular orientation with respect to the pole. We then decomposed the illumination models and epithermal maps as a function of the insolation model and correlate the datasets.

  9. Predictors and Characteristics of Erikson's Life Cycle Model Among Men: A 32-Year Longitudinal Study

    Science.gov (United States)

    Westermeyer, Jerry F.

    2004-01-01

    To assess Erikson's life cycle model, 86 men, initially selected for health, were prospectively studied at age 21, and reassessed 32 years later at age 53. Using the Vaillant and Milofsky (1980) modification of Erikson's model, 48 men (56%) achieved generativity, an advanced developmental stage, at follow-up. Results generally support Erikson's…

  10. Significance of settling model structures and parameter subsets in modelling WWTPs under wet-weather flow and filamentous bulking conditions.

    Science.gov (United States)

    Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen; Plósz, Benedek Gy

    2014-10-15

    Current research focuses on predicting and mitigating the impacts of high hydraulic loadings on centralized wastewater treatment plants (WWTPs) under wet-weather conditions. The maximum permissible inflow to WWTPs depends not only on the settleability of activated sludge in secondary settling tanks (SSTs) but also on the hydraulic behaviour of SSTs. The present study investigates the impacts of ideal and non-ideal flow (dry and wet weather) and settling (good settling and bulking) boundary conditions on the sensitivity of WWTP model outputs to uncertainties intrinsic to the one-dimensional (1-D) SST model structures and parameters. We identify the critical sources of uncertainty in WWTP models through global sensitivity analysis (GSA) using the Benchmark simulation model No. 1 in combination with first- and second-order 1-D SST models. The results obtained illustrate that the contribution of settling parameters to the total variance of the key WWTP process outputs significantly depends on the influent flow and settling conditions. The magnitude of the impact is found to vary, depending on which type of 1-D SST model is used. Therefore, we identify and recommend potential parameter subsets for WWTP model calibration, and propose optimal choice of 1-D SST models under different flow and settling boundary conditions. Additionally, the hydraulic parameters in the second-order SST model are found significant under dynamic wet-weather flow conditions. These results highlight the importance of developing a more mechanistic based flow-dependent hydraulic sub-model in second-order 1-D SST models in the future.

  11. Spectral Predictors

    Energy Technology Data Exchange (ETDEWEB)

    Ibarria, L; Lindstrom, P; Rossignac, J

    2006-11-17

    Many scientific, imaging, and geospatial applications produce large high-precision scalar fields sampled on a regular grid. Lossless compression of such data is commonly done using predictive coding, in which weighted combinations of previously coded samples known to both encoder and decoder are used to predict subsequent nearby samples. In hierarchical, incremental, or selective transmission, the spatial pattern of the known neighbors is often irregular and varies from one sample to the next, which precludes prediction based on a single stencil and fixed set of weights. To handle such situations and make the best use of available neighboring samples, we propose a local spectral predictor that offers optimal prediction by tailoring the weights to each configuration of known nearby samples. These weights may be precomputed and stored in a small lookup table. We show that predictive coding using our spectral predictor improves compression for various sources of high-precision data.

  12. Dynamical model of series-resonant converter with peak capacitor voltage predictor and switching frequency control

    Science.gov (United States)

    Pietkiewicz, A.; Tollik, D.; Klaassens, J. B.

    1989-08-01

    A simple small-signal low-frequency model of an idealized series resonant converter employing peak capacitor voltage prediction and switching frequency control is proposed. Two different versions of the model describe all possible conversion modes. It is found that step down modes offer better dynamic characteristics over most important network functions than do the step-up modes. The dynamical model of the series resonant converter with peak capacitor voltage prediction and switching frequency programming is much simpler than such popular control stategies as frequency VCO (voltage controlled oscillators) based control, or diode conduction angle control.

  13. Preclinical computational models: predictors of tibial insert damage patterns in total knee arthroplasty: AAOS exhibit selection.

    Science.gov (United States)

    Morra, Edward A; Heim, Christine S; Greenwald, A Seth

    2012-09-19

    Computational models that predict clinical surface damage of the tibial insert during activities of daily living are emerging as powerful tools to assess the safety and efficacy of contemporary total knee arthroplasty designs. These models have the advantage of quickly determining the performance of new designs at low cost, and they allow direct comparison with the performance of classic, clinically successful designs. This study validated finite element and kinematic modeling predictions through comparison with preclinical physical testing results, damage patterns on retrieved tibial inserts, and clinically measured knee motion. There is a mounting body of evidence to support the role of computational modeling as a preclinical tool that enables the optimization of total knee arthroplasty designs and the auditing of component quality control before large-scale manufacturing is undertaken.

  14. Computational models as predictors of HIV treatment outcomes for the Phidisa cohort in South Africa

    Directory of Open Access Journals (Sweden)

    Andrew Revell

    2016-02-01

    Full Text Available Background: Selecting the optimal combination of HIV drugs for an individual in resourcelimited settings is challenging because of the limited availability of drugs and genotyping.Objective: The evaluation as a potential treatment support tool of computational models that predict response to therapy without a genotype, using cases from the Phidisa cohort in South Africa.Methods: Cases from Phidisa of treatment change following failure were identified that had the following data available: baseline CD4 count and viral load, details of failing and previous antiretroviral drugs, drugs in new regimen and time to follow-up. The HIV Resistance Response Database Initiative’s (RDI’s models used these data to predict the probability of a viral load < 50 copies/mL at follow-up. The models were also used to identify effective alternative combinations of three locally available drugs.Results: The models achieved accuracy (area under the receiver–operator characteristic curve of 0.72 when predicting response to therapy, which is less accurate than for an independent global test set (0.80 but at least comparable to that of genotyping with rules-based interpretation. The models were able to identify alternative locally available three-drug regimens that were predicted to be effective in 69% of all cases and 62% of those whose new treatment failed in the clinic.Conclusion: The predictive accuracy of the models for these South African patients together with the results of previous studies suggest that the RDI’s models have the potential to optimise treatment selection and reduce virological failure in different patient populations, without the use of a genotype.Keywords: HIV therapy; mathematical modelling; treatment; genotype

  15. A mediation model linking dispatcher leadership and work ownership with safety climate as predictors of truck driver safety performance.

    Science.gov (United States)

    Zohar, Dov; Huang, Yueng-hsiang; Lee, Jin; Robertson, Michelle

    2014-01-01

    The study was designed to test the effect of safety climate on safety behavior among lone employees whose work environment promotes individual rather than consensual or shared climate perceptions. The paper presents a mediation path model linking psychological (individual-level) safety climate antecedents and consequences as predictors of driving safety of long-haul truck drivers. Climate antecedents included dispatcher (distant) leadership and driver work ownership, two contextual attributes of lone work, whereas its proximal consequence included driving safety. Using a prospective design, safety outcomes, consisting of hard-braking frequency (i.e. traffic near-miss events) were collected six months after survey completion, using GPS-based truck deceleration data. Results supported the hypothesized model, indicating that distant leadership style and work ownership promote psychological safety climate perceptions, with subsequent prediction of hard-braking events mediated by driving safety. Theoretical and practical implications for studying safety climate among lone workers in general and professional drivers in particular are discussed.

  16. Glucose Oxidase Biosensor Modeling and Predictors Optimization by Machine Learning Methods

    Directory of Open Access Journals (Sweden)

    Felix F. Gonzalez-Navarro

    2016-10-01

    Full Text Available Biosensors are small analytical devices incorporating a biological recognition element and a physico-chemical transducer to convert a biological signal into an electrical reading. Nowadays, their technological appeal resides in their fast performance, high sensitivity and continuous measuring capabilities; however, a full understanding is still under research. This paper aims to contribute to this growing field of biotechnology, with a focus on Glucose-Oxidase Biosensor (GOB modeling through statistical learning methods from a regression perspective. We model the amperometric response of a GOB with dependent variables under different conditions, such as temperature, benzoquinone, pH and glucose concentrations, by means of several machine learning algorithms. Since the sensitivity of a GOB response is strongly related to these dependent variables, their interactions should be optimized to maximize the output signal, for which a genetic algorithm and simulated annealing are used. We report a model that shows a good generalization error and is consistent with the optimization.

  17. Glucose Oxidase Biosensor Modeling and Predictors Optimization by Machine Learning Methods †

    Science.gov (United States)

    Gonzalez-Navarro, Felix F.; Stilianova-Stoytcheva, Margarita; Renteria-Gutierrez, Livier; Belanche-Muñoz, Lluís A.; Flores-Rios, Brenda L.; Ibarra-Esquer, Jorge E.

    2016-01-01

    Biosensors are small analytical devices incorporating a biological recognition element and a physico-chemical transducer to convert a biological signal into an electrical reading. Nowadays, their technological appeal resides in their fast performance, high sensitivity and continuous measuring capabilities; however, a full understanding is still under research. This paper aims to contribute to this growing field of biotechnology, with a focus on Glucose-Oxidase Biosensor (GOB) modeling through statistical learning methods from a regression perspective. We model the amperometric response of a GOB with dependent variables under different conditions, such as temperature, benzoquinone, pH and glucose concentrations, by means of several machine learning algorithms. Since the sensitivity of a GOB response is strongly related to these dependent variables, their interactions should be optimized to maximize the output signal, for which a genetic algorithm and simulated annealing are used. We report a model that shows a good generalization error and is consistent with the optimization. PMID:27792165

  18. Using predictors of hormone therapy use to model the healthy user bias: how does healthy user status influence cognitive effects of hormone therapy?

    Science.gov (United States)

    Gleason, Carey E; Dowling, N Maritza; Friedman, Elliot; Wharton, Whitney; Asthana, Sanjay

    2012-05-01

    This study investigated the phenomenon known as the healthy user bias by equating hormone therapy (HT) use (past or current) with healthy user status. Data from the Survey of Midlife in the United States were used to identify the predictors of HT use. The unique Survey of Midlife in the United States data include psychological, demographic, health-related, and behavioral variables as well as history of HT use. Predictors of HT use were combined to derive propensity scores, describing the likelihood that a woman was an HT user, based on her psychological, demographic, physical, and behavioral profile (ie, likelihood of being a healthy user) as opposed to her actual use of HT. Finally, cognitive performance on an executive function test was examined in women stratified by propensity score. Using a multiple logistic regression model, nine variables emerged as predictors of HT use. The nine variables were used to estimate the propensity or conditional probability of using HT for each subject; resultant propensity scores were ranked and divided into tertiles. Women in the highest tertile demonstrated shorter median response latencies on a test of executive function than did women who did not use HT. From an array of psychological, medical, and behavioral variables, nine emerged as predictors of HT use. If validated, these features may serve as a means of estimating the phenomenon known as healthy user bias. Moreover, these data suggest that the degree to which a woman fits a model of a healthy user may influence cognitive response to HT.

  19. Global climate change model natural climate variation: Paleoclimate data base, probabilities and astronomic predictors

    Energy Technology Data Exchange (ETDEWEB)

    Kukla, G.; Gavin, J. [Columbia Univ., Palisades, NY (United States). Lamont-Doherty Geological Observatory

    1994-05-01

    This report was prepared at the Lamont-Doherty Geological Observatory of Columbia University at Palisades, New York, under subcontract to Pacific Northwest Laboratory it is a part of a larger project of global climate studies which supports site characterization work required for the selection of a potential high-level nuclear waste repository and forms part of the Performance Assessment Scientific Support (PASS) Program at PNL. The work under the PASS Program is currently focusing on the proposed site at Yucca Mountain, Nevada, and is under the overall direction of the Yucca Mountain Project Office US Department of Energy, Las Vegas, Nevada. The final results of the PNL project will provide input to global atmospheric models designed to test specific climate scenarios which will be used in the site specific modeling work of others. The primary purpose of the data bases compiled and of the astronomic predictive models is to aid in the estimation of the probabilities of future climate states. The results will be used by two other teams working on the global climate study under contract to PNL. They are located at and the University of Maine in Orono, Maine, and the Applied Research Corporation in College Station, Texas. This report presents the results of the third year`s work on the global climate change models and the data bases describing past climates.

  20. Use of Standard Deviations as Predictors in Models Using Large-Scale International Data Sets

    Science.gov (United States)

    Austin, Bruce; French, Brian; Adesope, Olusola; Gotch, Chad

    2017-01-01

    Measures of variability are successfully used in predictive modeling in research areas outside of education. This study examined how standard deviations can be used to address research questions not easily addressed using traditional measures such as group means based on index variables. Student survey data were obtained from the Organisation for…

  1. A differential-geometric approach to generalized linear models with grouped predictors

    NARCIS (Netherlands)

    Augugliaro, Luigi; Mineo, Angelo M.; Wit, Ernst C.

    2016-01-01

    We propose an extension of the differential-geometric least angle regression method to perform sparse group inference in a generalized linear model. An efficient algorithm is proposed to compute the solution curve. The proposed group differential-geometric least angle regression method has important

  2. Predictors of Coparenting Relationship Quality in African American Single Mother Families: An Ecological Model

    Science.gov (United States)

    Sterrett, Emma; Jones, Deborah J.; Forehand, Rex; Garai, Emily

    2010-01-01

    Nonmarital coparents, or adults who assist mothers with childrearing, play a significant role in the lives of African American single mothers and their children. Yet relatively little research has examined correlates of the quality of the coparenting relationship in these families. Using a broad ecological framework, the current study examined…

  3. Significant glial alterations in response to iron loading in a novel organotypic hippocampal slice culture model

    Science.gov (United States)

    Healy, Sinead; McMahon, Jill; Owens, Peter; FitzGerald, Una

    2016-01-01

    Aberrant iron deposition in the brain is associated with neurodegenerative disorders including Multiple Sclerosis, Alzheimer’s disease and Parkinson’s disease. To study the collective response to iron loading, we have used hippocampal organotypic slices as a platform to develop a novel ex vivo model of iron accumulation. We demonstrated differential uptake and toxicity of iron after 12 h exposure to 10 μM ferrous ammonium sulphate, ferric citrate or ferrocene. Having established the supremacy of ferrocene in this model, the cultures were then loaded with 0.1–100 μM ferrocene for 12 h. One μM ferrocene exposure produced the maximal 1.6-fold increase in iron compared with vehicle. This was accompanied by a 1.4-fold increase in ferritin transcripts and mild toxicity. Using dual-immunohistochemistry, we detected ferritin in oligodendrocytes, microglia, but rarely in astrocytes and never in neurons in iron-loaded slice cultures. Moreover, iron loading led to a 15% loss of olig2-positive cells and a 16% increase in number and greater activation of microglia compared with vehicle. However, there was no appreciable effect of iron loading on astrocytes. In what we believe is a significant advance on traditional mono- or dual-cultures, our novel ex vivo slice-culture model allows characterization of the collective response of brain cells to iron-loading. PMID:27808258

  4. A Parallelized Pumpless Artificial Placenta System Significantly Prolonged Survival Time in a Preterm Lamb Model.

    Science.gov (United States)

    Miura, Yuichiro; Matsuda, Tadashi; Usuda, Haruo; Watanabe, Shimpei; Kitanishi, Ryuta; Saito, Masatoshi; Hanita, Takushi; Kobayashi, Yoshiyasu

    2016-05-01

    An artificial placenta (AP) is an arterio-venous extracorporeal life support system that is connected to the fetal circulation via the umbilical vasculature. Previously, we published an article describing a pumpless AP system with a small priming volume. We subsequently developed a parallelized system, hypothesizing that the reduced circuit resistance conveyed by this modification would enable healthy fetal survival time to be prolonged. We conducted experiments using a premature lamb model to test this hypothesis. As a result, the fetal survival period was significantly prolonged (60.4 ± 3.8 vs. 18.2 ± 3.2 h, P < 0.01), and circuit resistance and minimal blood lactate levels were significantly lower in the parallel circuit group, compared with our previous single circuit group. Fetal physiological parameters remained stable until the conclusion of the experiments. In summary, parallelization of the AP system was associated with reduced circuit resistance and lactate levels and allowed preterm lamb fetuses to survive for a significantly longer period when compared with previous studies.

  5. Competencies from Bartram’s Model as Predictors of Performance in Gambling Sector

    OpenAIRE

    Candel Ruiz, María José; sin filiación; Soler Sánchez, María Isabel; Universidad de Murcia; Meseguer de Pedro, Mariano; Universidad de Murcia

    2013-01-01

    The aim of this study was to analyse whether the Bartram’s model of Greit Competencies could predict the job performance. A sample of 95 workers, 56 men and 39 women, from the casinos sector was used. A member of this gambling company was trained to evaluate workers’ levels of competency. Moreover, a questionnaire was administered to managers and supervisors in order to evaluate the staff performance. After analysing the data using canonical regression, the results showed that the set of Bart...

  6. Outcome prediction after mild and complicated mild traumatic brain injury: external validation of existing models and identification of new predictors using the TRACK-TBI pilot study.

    Science.gov (United States)

    Lingsma, Hester F; Yue, John K; Maas, Andrew I R; Steyerberg, Ewout W; Manley, Geoffrey T

    2015-01-15

    Although the majority of patients with mild traumatic brain injury (mTBI) recover completely, some still suffer from disabling ailments at 3 or 6 months. We validated existing prognostic models for mTBI and explored predictors of poor outcome after mTBI. We selected patients with mTBI from TRACK-TBI Pilot, an unselected observational cohort of TBI patients from three centers in the United States. We validated two prognostic models for the Glasgow Outcome Scale Extended (GOS-E) at 6 months after injury. One model was based on the CRASH study data and another from Nijmegen, The Netherlands. Possible predictors of 3- and 6-month GOS-E were analyzed with univariate and multi-variable proportional odds regression models. Of the 386 of 485 patients included in the study (median age, 44 years; interquartile range, 27-58), 75% (n=290) presented with a Glasgow Coma Score (GCS) of 15. In this mTBI population, both previously developed models had a poor performance (area under the receiver operating characteristic curve, 0.49-0.56). In multivariable analyses, the strongest predictors of lower 3- and 6-month GOS-E were older age, pre-existing psychiatric conditions, and lower education. Injury caused by assault, extracranial injuries, and lower GCS were also predictive of lower GOS-E. Existing models for mTBI performed unsatisfactorily. Our study shows that, for mTBI, different predictors are relevant as for moderate and severe TBI. These include age, pre-existing psychiatric conditions, and lower education. Development of a valid prediction model for mTBI patients requires further research efforts.

  7. Outcome Prediction after Mild and Complicated Mild Traumatic Brain Injury: External Validation of Existing Models and Identification of New Predictors Using the TRACK-TBI Pilot Study

    Science.gov (United States)

    Lingsma, Hester F.; Yue, John K.; Maas, Andrew I.R.; Steyerberg, Ewout W.; Cooper, Shelly R.; Dams-O'Connor, Kristen; Gordon, Wayne A.; Menon, David K.; Mukherjee, Pratik; Okonkwo, David O.; Puccio, Ava M.; Schnyer, David M.; Valadka, Alex B.; Vassar, Mary J.; Yuh, Esther L.

    2015-01-01

    Abstract Although the majority of patients with mild traumatic brain injury (mTBI) recover completely, some still suffer from disabling ailments at 3 or 6 months. We validated existing prognostic models for mTBI and explored predictors of poor outcome after mTBI. We selected patients with mTBI from TRACK-TBI Pilot, an unselected observational cohort of TBI patients from three centers in the United States. We validated two prognostic models for the Glasgow Outcome Scale Extended (GOS-E) at 6 months after injury. One model was based on the CRASH study data and another from Nijmegen, The Netherlands. Possible predictors of 3- and 6-month GOS-E were analyzed with univariate and multi-variable proportional odds regression models. Of the 386 of 485 patients included in the study (median age, 44 years; interquartile range, 27–58), 75% (n=290) presented with a Glasgow Coma Score (GCS) of 15. In this mTBI population, both previously developed models had a poor performance (area under the receiver operating characteristic curve, 0.49–0.56). In multivariable analyses, the strongest predictors of lower 3- and 6-month GOS-E were older age, pre-existing psychiatric conditions, and lower education. Injury caused by assault, extracranial injuries, and lower GCS were also predictive of lower GOS-E. Existing models for mTBI performed unsatisfactorily. Our study shows that, for mTBI, different predictors are relevant as for moderate and severe TBI. These include age, pre-existing psychiatric conditions, and lower education. Development of a valid prediction model for mTBI patients requires further research efforts. PMID:25025611

  8. Phasic firing in vasopressin cells: understanding its functional significance through computational models.

    Directory of Open Access Journals (Sweden)

    Duncan J MacGregor

    Full Text Available Vasopressin neurons, responding to input generated by osmotic pressure, use an intrinsic mechanism to shift from slow irregular firing to a distinct phasic pattern, consisting of long bursts and silences lasting tens of seconds. With increased input, bursts lengthen, eventually shifting to continuous firing. The phasic activity remains asynchronous across the cells and is not reflected in the population output signal. Here we have used a computational vasopressin neuron model to investigate the functional significance of the phasic firing pattern. We generated a concise model of the synaptic input driven spike firing mechanism that gives a close quantitative match to vasopressin neuron spike activity recorded in vivo, tested against endogenous activity and experimental interventions. The integrate-and-fire based model provides a simple physiological explanation of the phasic firing mechanism involving an activity-dependent slow depolarising afterpotential (DAP generated by a calcium-inactivated potassium leak current. This is modulated by the slower, opposing, action of activity-dependent dendritic dynorphin release, which inactivates the DAP, the opposing effects generating successive periods of bursting and silence. Model cells are not spontaneously active, but fire when perturbed by random perturbations mimicking synaptic input. We constructed one population of such phasic neurons, and another population of similar cells but which lacked the ability to fire phasically. We then studied how these two populations differed in the way that they encoded changes in afferent inputs. By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input. Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response

  9. Predictors and mediators of add-on mirtazapine-induced cognitive enhancement in schizophrenia--a path model investigation.

    Science.gov (United States)

    Stenberg, Jan-Henry; Terevnikov, Viacheslav; Joffe, Marina; Tiihonen, Jari; Chukhin, Evgeny; Burkin, Mark; Joffe, Grigori

    2013-01-01

    We aimed to evaluate predictors and mediators of enhancing effect of adjunctive mirtazapine on cognition in schizophrenia. Patients with difficult-to-treat schizophrenia received either mirtazapine (n = 19) or placebo (n = 18) in a double-blind fashion for six weeks. Mirtazapine outperformed placebo on the Block Design and Stroop Dots. In the present subsidiary study, factors underlying this difference were explored with Path Analysis. Add-on mirtazapine had an independent enhancing effect on the Block Design-measured visuo-spatial functioning. Further, this effect was mediated via changes in positive, depressive and parkinsonism symptoms, but not in negative symptoms. This effect was predicted by higher doses of FGAs, longer duration of illness and lower initial Block Design scores. Path Analysis model fit was good. Mirtazapine may have direct and indirect favorable effects on visuo-spatial functioning, but further research is needed. Path analysis may be a feasible statistical method for further research of neurocognition in psychopharmacological interventions in schizophrenia. This article is part of a Special Issue entitled 'Cognitive Enhancers'. Copyright © 2012 Elsevier Ltd. All rights reserved.

  10. Predictors of Quality of Life in Portuguese Obese Patients: A Structural Equation Modeling Application

    Directory of Open Access Journals (Sweden)

    Estela Vilhena

    2014-01-01

    Full Text Available Living with obesity is an experience that may affect multiple aspects of an individual’s life. Obesity is considered a relevant public health problem in modern societies. To determine the comparative efficacy of different treatments and to assess their impact on patients’ everyday life, it is important to identify factors that are relevant to the quality of life of obese patients. The present study aims to evaluate, in Portuguese obese patients, the simultaneous impact of several psychosocial factors on quality of life. This study also explores the mediating role of stigma in the relationship between positive/negative affect and quality of life. A sample of 215 obese patients selected from the main hospitals in Portugal completed self-report questionnaires to assess sociodemographic, clinical, psychosocial, and quality of life variables. Data were analysed using structural equation modeling. The model fitted the data reasonably well, CFI = 0.9, RMSEA = 0.06. More enthusiastic and more active patients had a better quality of life. Those who reflect lower perception of stigma had a better physical and mental health. Partial mediation effects of stigma between positive affect and mental health and between negative affect and physical health were found. The stigma is pervasive and causes consequences for psychological and physical health.

  11. Model Pemesanan Bahan Baku menggunakan Peramalan Time Series dengan CB Predictor

    Directory of Open Access Journals (Sweden)

    Tri Pujadi

    2014-12-01

    Full Text Available A company that manufactures finished goods often faces a shortage of raw materials, due to the determination of the quantity of raw material ordering improper because it is done by intuition and the lack of raw material inventory reserves. This resulted in costs because inefficient production processes are inhibited or had to perform an emergency procurement of raw materials to meet customer orders. The company seeks to use the method in determining the order quantity of raw material, comprising the steps of (1 collecting historical data of raw material use, step (2 forecasting needs raw materials, step (3 calculating the order quantity forecasting based on the data by comparing the deterministic method and probabilistic methods. Calculating safety stock for each raw material is done so as to cope with the situation outside of normal conditions, such a surge in orders. In its design, the system will be developed using the Unified Modeling Language modeling language (UML on the basis of the concept of object-oriented analysis and design (Object Oriented Analysis and Design. With the proposed implementation of the information system, the company can estimate the need for raw materials more quickly and accurately, and can determine the order quantity that is tailored to the needs. So that the costs associated with ordering and storage of raw materials can be minimized.

  12. A systematic experimental investigation of significant parameters affecting model tire hydroplaning

    Science.gov (United States)

    Wray, G. A.; Ehrlich, I. R.

    1973-01-01

    The results of a comprehensive parametric study of model and small pneumatic tires operating on a wet surface are presented. Hydroplaning inception (spin down) and rolling restoration (spin up) are discussed. Conclusions indicate that hydroplaning inception occurs at a speed significantly higher than the rolling restoration speed. Hydroplaning speed increases considerably with tread depth, surface roughness and tire inflation pressure of footprint pressure, and only moderately with increased load. Water film thickness affects spin down speed only slightly. Spin down speed varies inversely as approximately the one-sixth power of film thickness. Empirical equations relating tire inflation pressure, normal load, tire diameter and water film thickness have been generated for various tire tread and surface configurations.

  13. Predictors of relationship power among drug-involved women.

    Science.gov (United States)

    Campbell, Aimee N C; Tross, Susan; Hu, Mei-chen; Pavlicova, Martina; Nunes, Edward V

    2012-08-01

    Gender-based relationship power is frequently linked to women's capacity to reduce sexual risk behaviors. This study offers an exploration of predictors of relationship power, as measured by the multidimensional and theoretically grounded sexual relationship power scale, among women in outpatient substance abuse treatment. Linear models were used to test nine predictors (age, race/ethnicity, education, time in treatment, economic dependence, substance use, sexual concurrency, partner abuse, and sex role orientation) of relationship power among 513 women participating in a multi-site HIV risk reduction intervention study. Significant predictors of relationship control included having a non-abusive male partner, only one male partner, and endorsing traditional masculine (or both masculine and feminine) sex role attributes. Predictors of decision-making dominance were interrelated, with substance use × partner abuse and age × sex role orientation interactions. Results contribute to the understanding of factors which may influence relationship power and to their potential role in HIV sexual risk reduction interventions.

  14. Computer modeling of gastric parietal cell: significance of canalicular space, gland lumen, and variable canalicular [K+].

    Science.gov (United States)

    Crothers, James M; Forte, John G; Machen, Terry E

    2016-05-01

    A computer model, constructed for evaluation of integrated functioning of cellular components involved in acid secretion by the gastric parietal cell, has provided new interpretations of older experimental evidence, showing the functional significance of a canalicular space separated from a mucosal bath by a gland lumen and also shedding light on basolateral Cl(-) transport. The model shows 1) changes in levels of parietal cell secretion (with stimulation or H-K-ATPase inhibitors) result mainly from changes in electrochemical driving forces for apical K(+) and Cl(-) efflux, as canalicular [K(+)] ([K(+)]can) increases or decreases with changes in apical H(+)/K(+) exchange rate; 2) H-K-ATPase inhibition in frog gastric mucosa would increase [K(+)]can similarly with low or high mucosal [K(+)], depolarizing apical membrane voltage similarly, so electrogenic H(+) pumping is not indicated by inhibition causing similar increase in transepithelial potential difference (Vt) with 4 and 80 mM mucosal K(+); 3) decreased H(+) secretion during strongly mucosal-positive voltage clamping is consistent with an electroneutral H-K-ATPase being inhibited by greatly decreased [K(+)]can (Michaelis-Menten mechanism); 4) slow initial change ("long time-constant transient") in current or Vt with clamping of Vt or current involves slow change in [K(+)]can; 5) the Na(+)-K(+)-2Cl(-) symporter (NKCC) is likely to have a significant role in Cl(-) influx, despite evidence that it is not necessary for acid secretion; and 6) relative contributions of Cl(-)/HCO3 (-) exchanger (AE2) and NKCC to Cl(-) influx would differ greatly between resting and stimulated states, possibly explaining reported differences in physiological characteristics of stimulated open-circuit Cl(-) secretion (≈H(+)) and resting short-circuit Cl(-) secretion (>H(+)).

  15. Predictors of Drinking Water Boiling and Bottled Water Consumption in Rural China: A Hierarchical Modeling Approach.

    Science.gov (United States)

    Cohen, Alasdair; Zhang, Qi; Luo, Qing; Tao, Yong; Colford, John M; Ray, Isha

    2017-06-20

    Approximately two billion people drink unsafe water. Boiling is the most commonly used household water treatment (HWT) method globally and in China. HWT can make water safer, but sustained adoption is rare and bottled water consumption is growing. To successfully promote HWT, an understanding of associated socioeconomic factors is critical. We collected survey data and water samples from 450 rural households in Guangxi Province, China. Covariates were grouped into blocks to hierarchically construct modified Poisson models and estimate risk ratios (RR) associated with boiling methods, bottled water, and untreated water. Female-headed households were most likely to boil (RR = 1.36, p boiled. Our findings show that boiling is not an undifferentiated practice, but one with different methods of varying effectiveness, environmental impact, and adoption across socioeconomic strata. Our results can inform programs to promote safer and more efficient boiling using electric kettles, and suggest that if rural China's economy continues to grow then bottled water use will increase.

  16. Significant Features Found in Simulated Tropical Climates Using a Cloud Resolving Model

    Science.gov (United States)

    Shie, C.-L.; Tao, W.-K.; Simpson, J.; Sui, C.-H.

    2000-01-01

    Cloud resolving model (CRM) has widely been used in recent years for simulations involving studies of radiative-convective systems and their role in determining the tropical regional climate. The growing popularity of CRMs usage can be credited for their inclusion of crucial and realistic features such like explicit cloud-scale dynamics, sophisticated microphysical processes, and explicit radiative-convective interaction. For example, by using a two-dimensional cloud model with radiative-convective interaction process, found a QBO-like (quasibiennial oscillation) oscillation of mean zonal wind that affected the convective system. Accordingly, the model-generated rain band corresponding to convective activity propagated in the direction of the low-level zonal mean winds; however, the precipitation became "localized" (limited within a small portion of the domain) as zonal mean winds were removed. Two other CRM simulations by S94 and Grabowski et al. (1996, hereafter G96), respectively that produced distinctive quasi-equilibrium ("climate") states on both tropical water and energy, i.e., a cold/dry state in S94 and a warm/wet state in G96, have later been investigated by T99. They found that the pattern of the imposed large-scale horizontal wind and the magnitude of the imposed surface fluxes were the two crucial mechanisms in determining the tropical climate states. The warm/wet climate was found associated with prescribed strong surface winds, or with maintained strong vertical wind shears that well-organized convective systems prevailed. On the other hand, the cold/dry climate was produced due to imposed weak surface winds and weak wind shears throughout a vertically mixing process by convection. In this study, considered as a sequel of T99, the model simulations to be presented are generally similar to those of T99 (where a detailed model setup can be found), except for a more detailed discussion along with few more simulated experiments. There are twelve major

  17. Crowdsourcing taste research: genetic and phenotypic predictors of bitter taste perception as a model

    Directory of Open Access Journals (Sweden)

    Nicole L. Garneau

    2014-05-01

    Full Text Available Understanding the influence of taste perception on food choice has captured the interest of academics, industry, and the general public. The latter as evidenced by the extent of popular media coverage and use of the term supertaster. Supertasters are highly sensitive to the bitter tastant propylthiouracil (PROP and its chemical relative phenylthiocarbamide. The well-researched differences in taste sensitivity to these bitter chemicals are partially controlled by variation in the TAS2R38 gene; however this variation alone does not explain the supertaster phenomenon. It has been suggested that density of papillae, which house taste buds, may explain supertasting. To address the unresolved role of papillae, we used crowdsourcing in the museum-based Genetics of Taste Lab. This community lab is uniquely situated to attract both a large population of human subjects and host a team of citizen scientists to research population-based questions about human genetics, taste, and health. Using this model, we find that PROP bitterness is not in any way predicted by papillae density. This result holds within the whole sample, when divided into major diplotypes, and when correcting for age, sex, and genotype. Furthermore, it holds when dividing participants into oft-used taster status groups. These data argue against the use of papillae density in predicting taste sensitivity and caution against imprecise use of the term supertaster. Furthermore, it supports a growing volume of evidence that sets the stage for hyperguesia, a reconceptualization of heightened oral sensitivity that is not based solely on PROP or papillae density. Finally, our model demonstrates how community-based research can serve as a unique venue for both study participation and citizen science that makes scientific research accessible and relevant to people’s everyday lives.

  18. Significance tests to determine the direction of effects in linear regression models.

    Science.gov (United States)

    Wiedermann, Wolfgang; Hagmann, Michael; von Eye, Alexander

    2015-02-01

    Previous studies have discussed asymmetric interpretations of the Pearson correlation coefficient and have shown that higher moments can be used to decide on the direction of dependence in the bivariate linear regression setting. The current study extends this approach by illustrating that the third moment of regression residuals may also be used to derive conclusions concerning the direction of effects. Assuming non-normally distributed variables, it is shown that the distribution of residuals of the correctly specified regression model (e.g., Y is regressed on X) is more symmetric than the distribution of residuals of the competing model (i.e., X is regressed on Y). Based on this result, 4 one-sample tests are discussed which can be used to decide which variable is more likely to be the response and which one is more likely to be the explanatory variable. A fifth significance test is proposed based on the differences of skewness estimates, which leads to a more direct test of a hypothesis that is compatible with direction of dependence. A Monte Carlo simulation study was performed to examine the behaviour of the procedures under various degrees of associations, sample sizes, and distributional properties of the underlying population. An empirical example is given which illustrates the application of the tests in practice.

  19. Predictors of diabetes outcomes in Mexico: testing the Hispanic health protection model.

    Science.gov (United States)

    Latham, Christine L; Calvillo, Evelyn

    2013-07-01

    Given the high morbidity and mortality rate of Hispanic immigrants to the United States, a study of the Hispanic Health Protection Model (HHPM) was replicated with 109 residents in Mexico who were newly diagnosed with diabetes. People with diabetes from rural clinics in Tlaxcala underwent a three-phase interview process with laboratory and weight follow-up over 4 to 6 months following a confirmed diagnosis of diabetes. This predictive, correlational study replicated the HHPM and the previous U.S. findings, including relationships between lifestyle profile, health beliefs, professional and social support, self-efficacy, diabetes knowledge, quality of life (self-satisfaction and impact of diabetes), and changes in HbA1c and body mass index. The study found that participants frequently followed good lifestyle practices while continuing to adhere to culturally based treatment and attribution beliefs. There were moderate perceptions of diabetes self-care efficacy, low ratings of support, very poor understanding of diabetes, continued obesity, acceptable quality of life ratings, and near-normal HbA1c levels.

  20. Noncognitive predictors of academic performance. Going beyond the traditional measures.

    Science.gov (United States)

    DeAngelis, Susan

    2003-01-01

    The purpose of this study was to examine comparatively the use of an atypical, noncognitive predictor of academic achievement, the Problem Solving Inventory (PSI), with the traditional cognitive measures of American College Testing (ACT) score and grade point average (CPA). A review of relevant literature on noncognitive variables as predictors of academic success is provided, followed by a general overview of the PSI and pertinent literature. In this study, the PSI was administered to 28 dental hygiene students, and a series of models were tested. The first model examined the relationship between the traditional cognitive predictors of academic success (ACT score and entering GPA) on academic outcomes (National Board Dental Hygiene Examination score and exit CPA). A second model examined the influence of the PSI composite score when added to the cognitive predictors. A third model examined the addition of the three PSI factor scores to the cognitive predictors. The addition of PSI scores in the second and third models increased the predictive capacity of the respective model. Bivariate correlations indicated a significant inverse relationship (p GPA, although its usefulness in augmenting these traditional measures used in the student selection process requires further investigation. The PSI factor score of personal control may provide insight into a student's coping skills, potentially having implications on academic achievement.

  1. Pharmacological kynurenine 3-monooxygenase enzyme inhibition significantly reduces neuropathic pain in a rat model.

    Science.gov (United States)

    Rojewska, Ewelina; Piotrowska, Anna; Makuch, Wioletta; Przewlocka, Barbara; Mika, Joanna

    2016-03-01

    Recent studies have highlighted the involvement of the kynurenine pathway in the pathology of neurodegenerative diseases, but the role of this system in neuropathic pain requires further extensive research. Therefore, the aim of our study was to examine the role of kynurenine 3-monooxygenase (Kmo), an enzyme that is important in this pathway, in a rat model of neuropathy after chronic constriction injury (CCI) to the sciatic nerve. For the first time, we demonstrated that the injury-induced increase in the Kmo mRNA levels in the spinal cord and the dorsal root ganglia (DRG) was reduced by chronic administration of the microglial inhibitor minocycline and that this effect paralleled a decrease in the intensity of neuropathy. Further, minocycline administration alleviated the lipopolysaccharide (LPS)-induced upregulation of Kmo mRNA expression in microglial cell cultures. Moreover, we demonstrated that not only indirect inhibition of Kmo using minocycline but also direct inhibition using Kmo inhibitors (Ro61-6048 and JM6) decreased neuropathic pain intensity on the third and the seventh days after CCI. Chronic Ro61-6048 administration diminished the protein levels of IBA-1, IL-6, IL-1beta and NOS2 in the spinal cord and/or the DRG. Both Kmo inhibitors potentiated the analgesic properties of morphine. In summary, our data suggest that in neuropathic pain model, inhibiting Kmo function significantly reduces pain symptoms and enhances the effectiveness of morphine. The results of our studies show that the kynurenine pathway is an important mediator of neuropathic pain pathology and indicate that Kmo represents a novel pharmacological target for the treatment of neuropathy.

  2. Cyclosporin A significantly improves preeclampsia signs and suppresses inflammation in a rat model.

    Science.gov (United States)

    Hu, Bihui; Yang, Jinying; Huang, Qian; Bao, Junjie; Brennecke, Shaun Patrick; Liu, Huishu

    2016-05-01

    Preeclampsia is associated with an increased inflammatory response. Immune suppression might be an effective treatment. The aim of this study was to examine whether Cyclosporin A (CsA), an immunosuppressant, improves clinical characteristics of preeclampsia and suppresses inflammation in a lipopolysaccharide (LPS) induced preeclampsia rat model. Pregnant rats were randomly divided into 4 groups: group 1 (PE) rats each received LPS via tail vein on gestational day (GD) 14; group 2 (PE+CsA5) rats were pretreated with LPS (1.0 μg/kg) on GD 14 and were then treated with CsA (5mg/kg, ip) on GDs 16, 17 and 18; group 3 (PE+CsA10) rats were pretreated with LPS (1.0 μg/kg) on GD 14 and were then treated with CsA (10mg/kg, ip) on GDs 16, 17 and 18; group 4 (pregnant control, PC) rats were treated with the vehicle (saline) used for groups 1, 2 and 3. Systolic blood pressure, urinary albumin, biometric parameters and the levels of serum cytokines were measured on day 20. CsA treatment significantly reduced LPS-induced systolic blood pressure and the mean 24-h urinary albumin excretion. Pro-inflammatory cytokines IL-6, IL-17, IFN-γ and TNF-α were increased in the LPS treatment group but were reduced in (LPS+CsA) group (PCyclosporine A improved preeclampsia signs and attenuated inflammatory responses in the LPS induced preeclampsia rat model which suggests that immunosuppressant might be an alternative management option for preeclampsia. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Prostate cancer risk and DNA damage: translational significance of selenium supplementation in a canine model.

    Science.gov (United States)

    Waters, David J; Shen, Shuren; Glickman, Lawrence T; Cooley, Dawn M; Bostwick, David G; Qian, Junqi; Combs, Gerald F; Morris, J Steven

    2005-07-01

    Daily supplementation with the essential trace mineral selenium significantly reduced prostate cancer risk in men in the Nutritional Prevention of Cancer Trial. However, the optimal intake of selenium for prostate cancer prevention is unknown. We hypothesized that selenium significantly regulates the extent of genotoxic damage within the aging prostate and that the relationship between dietary selenium intake and DNA damage is non-linear, i.e. more selenium is not necessarily better. To test this hypothesis, we conducted a randomized feeding trial in which 49 elderly beagle dogs (physiologically equivalent to 62-69-year-old men) received nutritionally adequate or supranutritional levels of selenium for 7 months, in order to mimic the range of dietary selenium intake of men in the United States. Our results demonstrate an intriguing U-shaped dose-response relationship between selenium status (toenail selenium concentration) and the extent of DNA damage (alkaline Comet assay) within the prostate. Further, we demonstrate that the concentration of selenium that minimizes DNA damage in the aging dog prostate remarkably parallels the selenium concentration in men that minimizes prostate cancer risk. By studying elderly dogs, the only non-human animal model of spontaneous prostate cancer, we have established a new approach to bridge the gap between laboratory and human studies that can be used to select the appropriate dose of anticancer agents for large-scale human cancer prevention trials. From the U-shaped dose-response, it follows that not all men will necessarily benefit from increasing their selenium intake and that measurement of baseline nutrient status should be required for all individuals in prevention trials to avoid oversupplementation.

  4. Kernel density surface modelling as a means to identify significant concentrations of vulnerable marine ecosystem indicators.

    Directory of Open Access Journals (Sweden)

    Ellen Kenchington

    Full Text Available The United Nations General Assembly Resolution 61/105, concerning sustainable fisheries in the marine ecosystem, calls for the protection of vulnerable marine ecosystems (VME from destructive fishing practices. Subsequently, the Food and Agriculture Organization (FAO produced guidelines for identification of VME indicator species/taxa to assist in the implementation of the resolution, but recommended the development of case-specific operational definitions for their application. We applied kernel density estimation (KDE to research vessel trawl survey data from inside the fishing footprint of the Northwest Atlantic Fisheries Organization (NAFO Regulatory Area in the high seas of the northwest Atlantic to create biomass density surfaces for four VME indicator taxa: large-sized sponges, sea pens, small and large gorgonian corals. These VME indicator taxa were identified previously by NAFO using the fragility, life history characteristics and structural complexity criteria presented by FAO, along with an evaluation of their recovery trajectories. KDE, a non-parametric neighbour-based smoothing function, has been used previously in ecology to identify hotspots, that is, areas of relatively high biomass/abundance. We present a novel approach of examining relative changes in area under polygons created from encircling successive biomass categories on the KDE surface to identify "significant concentrations" of biomass, which we equate to VMEs. This allows identification of the VMEs from the broader distribution of the species in the study area. We provide independent assessments of the VMEs so identified using underwater images, benthic sampling with other gear types (dredges, cores, and/or published species distribution models of probability of occurrence, as available. For each VME indicator taxon we provide a brief review of their ecological function which will be important in future assessments of significant adverse impact on these habitats here

  5. Significance of settling model structures and parameter subsets in modelling WWTPs under wet-weather flow and filamentous bulking conditions

    DEFF Research Database (Denmark)

    Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen;

    2014-01-01

    Current research focuses on predicting and mitigating the impacts of high hydraulic loadings on centralized wastewater treatment plants (WWTPs) under wet-weather conditions. The maximum permissible inflow to WWTPs depends not only on the settleability of activated sludge in secondary settling tanks...... (SSTs) but also on the hydraulic behaviour of SSTs. The present study investigates the impacts of ideal and non-ideal flow (dry and wet weather) and settling (good settling and bulking) boundary conditions on the sensitivity of WWTP model outputs to uncertainties intrinsic to the one-dimensional (1-D...... of settling parameters to the total variance of the key WWTP process outputs significantly depends on the influent flow and settling conditions. The magnitude of the impact is found to vary, depending on which type of 1-D SST model is used. Therefore, we identify and recommend potential parameter subsets...

  6. High-fat diet induces significant metabolic disorders in a mouse model of polycystic ovary syndrome.

    Science.gov (United States)

    Lai, Hao; Jia, Xiao; Yu, Qiuxiao; Zhang, Chenglu; Qiao, Jie; Guan, Youfei; Kang, Jihong

    2014-11-01

    Polycystic ovary syndrome (PCOS) is the most common female endocrinopathy associated with both reproductive and metabolic disorders. Dehydroepiandrosterone (DHEA) is currently used to induce a PCOS mouse model. High-fat diet (HFD) has been shown to cause obesity and infertility in female mice. The possible effect of an HFD on the phenotype of DHEA-induced PCOS mice is unknown. The aim of the present study was to investigate both reproductive and metabolic features of DHEA-induced PCOS mice fed a normal chow or a 60% HFD. Prepubertal C57BL/6 mice (age 25 days) on the normal chow or an HFD were injected (s.c.) daily with the vehicle sesame oil or DHEA for 20 consecutive days. At the end of the experiment, both reproductive and metabolic characteristics were assessed. Our data show that an HFD did not affect the reproductive phenotype of DHEA-treated mice. The treatment of HFD, however, caused significant metabolic alterations in DHEA-treated mice, including obesity, glucose intolerance, dyslipidemia, and pronounced liver steatosis. These findings suggest that HFD induces distinct metabolic features in DHEA-induced PCOS mice. The combined DHEA and HFD treatment may thus serve as a means of studying the mechanisms involved in metabolic derangements of this syndrome, particularly in the high prevalence of hepatic steatosis in women with PCOS.

  7. Comparison of transform coding methods with an optimal predictor for the data compression of digital elevation models

    Science.gov (United States)

    Lewis, Michael

    1994-01-01

    Statistical encoding techniques enable the reduction of the number of bits required to encode a set of symbols, and are derived from their probabilities. Huffman encoding is an example of statistical encoding that has been used for error-free data compression. The degree of compression given by Huffman encoding in this application can be improved by the use of prediction methods. These replace the set of elevations by a set of corrections that have a more advantageous probability distribution. In particular, the method of Lagrange Multipliers for minimization of the mean square error has been applied to local geometrical predictors. Using this technique, an 8-point predictor achieved about a 7 percent improvement over an existing simple triangular predictor.

  8. Use pattern and predictors of use of highly caffeinated energy drinks among South Korean adolescents: a study using the Health Belief Model.

    Science.gov (United States)

    Ha, Dongmun; Song, Inmyung; Jang, Gyeongil; Lee, Eui-Kyung; Shin, Ju-Young

    2017-09-24

    Concerns about the use of highly caffeinated energy drinks among Korean adolescents remains. We compared adolescents' perceptions regarding the use of drinks to their behaviours and factors. A structured questionnaire based on the Health Belief Model was administered to 850 freshmen and sophomores at three high schools in Bucheon, South Korea. Benefits were defined as beneficial effects from the use of highly caffeinated energy drinks (eg, awakening from sleepiness) and harms as adverse effects of the drinks (eg, cardiac palpitation). Likelihood of action represents the likelihood of taking actions that are perceived to be more beneficial after comparison of the benefits and harms of caffeine use. Descriptive analysis was used to quantify the relationship between their beliefs about highly caffeinated energy drinks and their use. We conducted hierarchical logistic regression to compute ORs and 95% CIs for: (1) demographic factors, (2) health threat, (3) likelihood of action and (4) cues to act. Altogether, 833 students responded to the questionnaire (effective response rate=98.0%). About 63.0% reported use of highly caffeinated energy drinks and 35.2% had used them as needed and habitually. The more susceptible the respondents perceived themselves to be to the risk of using these drinks, the less likely they were to use them (OR: 0.73, 95% CI 0.50 to 1.06). The more severe the perception of a health threat, the less that perception was associated with use (OR: 0.44, 95% CI 0.29 to 0.67). Likelihood of action was the strongest predictor of use, explaining 12.5% in use. Benefits and harms (OR: 4.43, 95% CI 2.77 to 7.09; OR: 1.86, 95% CI 1.16 to 2.99) also were significant predictors. Enhancing adolescents' perceptions of benefits and harms regarding using highly caffeinated energy drinks could be an effective way to influence the use of these drinks. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All

  9. Significance of model credibility in estimating climate projection distributions for regional hydroclimatological risk assessments

    Science.gov (United States)

    Brekke, L.D.; Dettinger, M.D.; Maurer, E.P.; Anderson, M.

    2008-01-01

    Ensembles of historical climate simulations and climate projections from the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset were investigated to determine how model credibility affects apparent relative scenario likelihoods in regional risk assessments. Methods were developed and applied in a Northern California case study. An ensemble of 59 twentieth century climate simulations from 17 WCRP CMIP3 models was analyzed to evaluate relative model credibility associated with a 75-member projection ensemble from the same 17 models. Credibility was assessed based on how models realistically reproduced selected statistics of historical climate relevant to California climatology. Metrics of this credibility were used to derive relative model weights leading to weight-threshold culling of models contributing to the projection ensemble. Density functions were then estimated for two projected quantities (temperature and precipitation), with and without considering credibility-based ensemble reductions. An analysis for Northern California showed that, while some models seem more capable at recreating limited aspects twentieth century climate, the overall tendency is for comparable model performance when several credibility measures are combined. Use of these metrics to decide which models to include in density function development led to local adjustments to function shapes, but led to limited affect on breadth and central tendency, which were found to be more influenced by 'completeness' of the original ensemble in terms of models and emissions pathways. ?? 2007 Springer Science+Business Media B.V.

  10. More Use of Peritoneal Dialysis Gives Significant Savings: A Systematic Review and Health Economic Decision Model

    Science.gov (United States)

    Pike, Eva; Hamidi, Vida; Ringerike, Tove; Wisloff, Torbjorn; Klemp, Marianne

    2017-01-01

    Background Patients with end-stage renal disease (ESRD) are in need of renal replacement therapy as dialysis and/or transplantation. The prevalence of ESRD and, thus, the need for dialysis are constantly growing. The dialysis modalities are either peritoneal performed at home or hemodialysis (HD) performed in-center (hospital or satellite) or home. We examined effectiveness and cost-effectiveness of HD performed at different locations (hospital, satellite, and home) and peritoneal dialysis (PD) at home in the Norwegian setting. Methods We conducted a systematic review for patients above 18 years with end-stage renal failure requiring dialysis in several databases and performed several meta-analyses of existing literature. Mortality and major complications that required were our main clinical outcomes. The quality of the evidence for each outcome was evaluated using GRADE. Cost-effectiveness was assessed by developing a probabilistic Markov model. The analysis was carried out from a societal perspective, and effects were expressed in quality-adjusted life-years. Uncertainties in the base-case parameter values were explored with a probabilistic sensitivity analysis. Scenario analyses were conducted by increasing the proportion of patients receiving PD with a corresponding reduction in HD patients in-center both for Norway and Europian Union. We assumed an annual growth rate of 4% in the number of dialysis patients, and a relative distribution between PD and HD in-center of 30% and 70%, respectively. Results From a societal perspective and over a 5-year time horizon, PD was the most cost-effective dialysis alternative. We found no significant difference in mortality between peritoneal and HD modalities. Our scenario analyses showed that a shift toward more patients on PD (as a first choice) with a corresponding reduction in HD in-center gave a saving over a 5-year period of 32 and 10,623 million EURO, respectively, for Norway and the European Union. Conclusions PD was

  11. Significant impacts of irrigation water sources and methods on modeling irrigation effects in the ACME Land Model

    Energy Technology Data Exchange (ETDEWEB)

    Leng, Guoyong; Leung, Lai-Yung; Huang, Maoyi

    2017-07-01

    An irrigation module that considers both irrigation water sources and irrigation methods has been incorporated into the ACME Land Model (ALM). Global numerical experiments were conducted to evaluate the impacts of irrigation water sources and irrigation methods on the simulated irrigation effects. All simulations shared the same irrigation soil moisture target constrained by a global census dataset of irrigation amounts. Irrigation has large impacts on terrestrial water balances especially in regions with extensive irrigation. Such effects depend on the irrigation water sources: surface-water-fed irrigation leads to decreases in runoff and water table depth, while groundwater-fed irrigation increases water table depth, with positive or negative effects on runoff depending on the pumping intensity. Irrigation effects also depend significantly on the irrigation methods. Flood irrigation applies water in large volumes within short durations, resulting in much larger impacts on runoff and water table depth than drip and sprinkler irrigations. Differentiating the irrigation water sources and methods is important not only for representing the distinct pathways of how irrigation influences the terrestrial water balances, but also for estimating irrigation water use efficiency. Specifically, groundwater pumping has lower irrigation water use efficiency due to enhanced recharge rates. Different irrigation methods also affect water use efficiency, with drip irrigation the most efficient followed by sprinkler and flood irrigation. Our results highlight the importance of explicitly accounting for irrigation sources and irrigation methods, which are the least understood and constrained aspects in modeling irrigation water demand, water scarcity and irrigation effects in Earth System Models.

  12. Examining educational attainment, prepregnancy smoking rate, and delay discounting as predictors of spontaneous quitting among pregnant smokers.

    Science.gov (United States)

    White, Thomas J; Redner, Ryan; Skelly, Joan M; Higgins, Stephen T

    2014-10-01

    We investigated three potential predictors (educational attainment, prepregnancy smoking rate, and delay discounting [DD]) of spontaneous quitting among pregnant smokers. These predictors were examined alone and in combination with other potential predictors using study-intake assessments from controlled clinical trials examining the efficacy of financial incentives for smoking cessation and relapse prevention. Data from 349 pregnant women (231 continuing smokers and 118 spontaneous quitters) recruited from the greater Burlington, VT, area contributed to this secondary analysis, including psychiatric/sociodemographic characteristics, smoking characteristics, and performance on a computerized DD task. Educational attainment, smoking rate, and DD values were each significant predictors of spontaneous quitting in univariate analyses. A model examining those three predictors together retained educational attainment as a main effect and revealed a significant interaction of DD and smoking rate (i.e., DD was a significant predictor at lower but not higher smoking rates). A final model considering all potential predictors, included education, the interaction of DD and smoking rate, and five additional predictors (i.e., stress ratings, the belief that smoking during pregnancy will "greatly harm my baby," age of smoking initiation, marital status, and prior quit attempts during pregnancy). The study presented here contributes new knowledge on predictors of spontaneous quitting among pregnant smokers with substantive practical implications for reducing smoking during pregnancy.

  13. Educational Research in Educational Practice: Predictors of Use

    Science.gov (United States)

    Lysenko, Larysa V.; Abrami, Philip C.; Dagenais, Christian; Janosz, Michel

    2014-01-01

    This study investigates the predictors of school practitioners' (N = 2,425) use of educational research. The suggested model explained significantly but modestly the infrequent use of educational research by practitioners. Of the four factors in the study, "opinions about research" had the most explanatory power. The results are…

  14. Electrocardiographic predictors of peripartum cardiomyopathy

    Science.gov (United States)

    Karaye, Kamilu M; Karaye, Kamilu M; Lindmark, Krister; Henein, Michael Y; Lindmark, Krister; Henein, Michael Y

    2016-01-01

    Summary Objective To identify potential electrocardiographic predictors of peripartum cardiomyopathy (PPCM). Methods: This was a case–control study carried out in three hospitals in Kano, Nigeria. Logistic regression models and a risk score were developed to determine electrocardiographic predictors of PPCM. Results: A total of 54 PPCM and 77 controls were consecutively recruited after satisfying the inclusion criteria. After controlling for confounding variables, a rise in heart rate of one beat/minute increased the risk of PPCM by 6.4% (p = 0.001), while the presence of ST–T-wave changes increased the odds of PPCM 12.06-fold (p < 0.001). In the patients, QRS duration modestly correlated (r = 0.4; p < 0.003) with left ventricular dimensions and end-systolic volume index, and was responsible for 19.9% of the variability of the latter (R2 = 0.199; p = 0.003). A risk score of ≥ 2, developed by scoring 1 for each of the three ECG disturbances (tachycardia, ST–T-wave abnormalities and QRS duration), had a sensitivity of 85.2%, specificity of 64.9%, negative predictive value of 86.2% and area under the curve of 83.8% (p < 0.0001) for potentially predicting PPCM. Conclusion In postpartum women, using the risk score could help to streamline the diagnosis of PPCM with significant accuracy, prior to confirmatory investigations PMID:27213852

  15. Predictors of depression in youth with Crohn disease.

    Science.gov (United States)

    Clark, Jeffrey G; Srinath, Arvind I; Youk, Ada O; Kirshner, Margaret A; McCarthy, F Nicole; Keljo, David J; Bousvaros, Athos; DeMaso, David R; Szigethy, Eva M

    2014-05-01

    The aim of the study was to determine whether infliximab use and other potential predictors are associated with decreased prevalence and severity of depression in pediatric patients with Crohn disease (CD). A total of 550 (n = 550) youth ages 9 to 17 years with biopsy-confirmed CD were consecutively recruited as part of a multicenter randomized controlled trial. Out of the 550, 499 patients met study criteria and were included in the analysis. At recruitment, each subject and a parent completed the Children's Depression Inventory (CDI). A child or parent CDI score ≥  12 was used to denote clinically significant depressive symptoms (CSDS). Child and parent CDI scores were summed to form total CDI (CDIT). Infliximab use, demographic information, steroid use, laboratory values, and Pediatric Crohn's Disease Activity Index (PCDAI) were collected as the potential predictors of depression. Univariate regression models were constructed to determine the relations among predictors, CSDS, and CDIT. Stepwise multivariate regression models were constructed to predict the relation between infliximab use and depression while controlling for other predictors of depression. Infliximab use was not associated with a decreased proportion of CSDS and CDIT after adjusting for multiple comparisons. CSDS and CDIT were positively associated with PCDAI, erythrocyte sedimentation rate, and steroid dose (P Disease activity and SES are significant predictors of depression in youth with Crohn disease.

  16. Significance of neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio and prognostic nutrition index as preoperative predictors of early mortality after liver resection for huge (≥10 cm) hepatocellular carcinoma.

    Science.gov (United States)

    Goh, Brian K P; Kam, Juinn Huar; Lee, Ser-Yee; Chan, Chung-Yip; Allen, John C; Jeyaraj, Premaraj; Cheow, Peng-Chung; Chow, Pierce K H; Ooi, London L P J; Chung, Alexander Y F

    2016-05-01

    This study aimed to determine preoperative predictors of early (huge (≥10 cm) HCC, with special emphasis on the importance of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and prognostic nutrition index (PNI). Between 2000 to 2013, 166 patients underwent LR for huge HCC. Optimal cut-offs for alpha fetoprotein (AFP), NLR, PLR, and PNI were determined by plotting the receiver operator curves (ROC) in predicting early mortality and utilizing the Youden index. The 30-day/in-hospital postoperative mortality rate was 4.2%. The 5-year overall survival (OS) and the 5-year recurrence-free survival (RFS) was 43% and 24%, respectively. Early mortality from disease recurrence occurred in 35 of 159 (22%) patients. Multivariate analyses demonstrated that tumor rupture and high AFP (>1,085 ng/ml) were independent preoperative predictors of early mortality after LR for HCC, and both a low PNI (huge HCC. J. Surg. Oncol. 2016;113:621-627. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  17. Paper-based and web-based intervention modeling experiments identified the same predictors of general practitioners' antibiotic-prescribing behavior.

    Science.gov (United States)

    Treweek, Shaun; Bonetti, Debbie; Maclennan, Graeme; Barnett, Karen; Eccles, Martin P; Jones, Claire; Pitts, Nigel B; Ricketts, Ian W; Sullivan, Frank; Weal, Mark; Francis, Jill J

    2014-03-01

    To evaluate the robustness of the intervention modeling experiment (IME) methodology as a way of developing and testing behavioral change interventions before a full-scale trial by replicating an earlier paper-based IME. Web-based questionnaire and clinical scenario study. General practitioners across Scotland were invited to complete the questionnaire and scenarios, which were then used to identify predictors of antibiotic-prescribing behavior. These predictors were compared with the predictors identified in an earlier paper-based IME and used to develop a new intervention. Two hundred seventy general practitioners completed the questionnaires and scenarios. The constructs that predicted simulated behavior and intention were attitude, perceived behavioral control, risk perception/anticipated consequences, and self-efficacy, which match the targets identified in the earlier paper-based IME. The choice of persuasive communication as an intervention in the earlier IME was also confirmed. Additionally, a new intervention, an action plan, was developed. A web-based IME replicated the findings of an earlier paper-based IME, which provides confidence in the IME methodology. The interventions will now be evaluated in the next stage of the IME, a web-based randomized controlled trial. Copyright © 2014 Elsevier Inc. All rights reserved.

  18. Innovations in individual feature history management - The significance of feature-based temporal model

    Science.gov (United States)

    Choi, J.; Seong, J.C.; Kim, B.; Usery, E.L.

    2008-01-01

    A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure. ?? Springer Science+Business Media, LLC 2007.

  19. Is satisfaction a direct predictor of nursing turnover? Modelling the relationship between satisfaction, expressed intention and behaviour in a longitudinal cohort study

    Directory of Open Access Journals (Sweden)

    Griffiths Peter

    2008-10-01

    Full Text Available Abstract Background The theory of planned behaviour states that attitudinal variables (e.g. job satisfaction only have an indirect effect on retention whereas intentions have a direct effect. This study uses secondary data from a longitudinal cohort of newly qualified nurses to test for the direct and indirect effects of job satisfaction (client care, staffing, development, relationships, education, work-life interface, resources, pay and intentions to nurse on working as a nurse during the 3 years after qualification. Methods A national sample (England of newly qualified (1997/98 nurses (n = 3669 were surveyed at 6 months, 18 months and 3 years. ANOVA and MANOVA were used for comparison of mean job satisfaction scores between groups; intentions to nurse (very likely, likely vs. unlikely, very unlikely and unable to say at this stage; working (or not working as a nurse at each time-point. Indirect and direct effects were tested using structural equation and logistic regression models. Results Intentions expressed at 6 months to nurse at 18 months were associated with higher scores on pay and relationships, and intentions at 3 years were associated with higher scores on care, development, relationships, work-life interface, resources, pay respectively. Intentions expressed at 18 months to nurse at 3 years were associated with higher scores on development, relationships, education and work-life interface. Associations with actual nursing were fewer. Those working as a nurse had higher satisfaction scores for development (18 months and relationships (3 years. Regression models found significant associations between the pay and staffing factors and intentions expressed at 6 months to nurse at 18 months, and between pay and intentions to nurse at 3 years. Many of the associations between intentions and working as a nurse were significant. Development was the only job satisfaction factor significantly associated with working as a nurse and just at 18

  20. Significance of hydrological model choice and land use changes when doing climate change impact assessment

    Science.gov (United States)

    Bjørnholt Karlsson, Ida; Obel Sonnenborg, Torben; Refsgaard, Jens Christian; Høgh Jensen, Karsten

    2014-05-01

    Uncertainty in impact studies arises both from Global Climate Models (GCM), emission projections, statistical downscaling, Regional Climate Models (RCM), hydrological models and calibration techniques (Refsgaard et al. 2013). Some of these uncertainties have been evaluated several times in the literature; however few studies have investigated the effect of hydrological model choice on the assessment results (Boorman & Sefton 1997; Jiang et al. 2007; Bastola et al. 2011). These studies have found that model choice results in large differences, up to 70%, in the predicted discharge changes depending on the climate input. The objective of the study is to investigate the impact of climate change on hydrology of the Odense catchment, Denmark both in response to (a) different climate projections (GCM-RCM combinations); (b) different hydrological models and (c) different land use scenarios. This includes: 1. Separation of the climate model signal; the hydrological model signal and the land use signal 2. How do the different hydrological components react under different climate and land use conditions for the different models 3. What land use scenario seems to provide the best adaptation for the challenges of the different future climate change scenarios from a hydrological perspective? Four climate models from the ENSEMBLES project (Hewitt & Griggs 2004): ECHAM5 - HIRHAM5, ECHAM5 - RCA3, ARPEGE - RM5.1 and HadCM3 - HadRM3 are used, assessing the climate change impact in three periods: 1991-2010 (present), 2041-2060 (near future) and 2081-2100 (far future). The four climate models are used in combination with three hydrological models with different conceptual layout: NAM, SWAT and MIKE SHE. Bastola, S., C. Murphy and J. Sweeney (2011). "The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments." Advances in Water Resources 34: 562-576. Boorman, D. B. and C. E. M. Sefton (1997). "Recognising the uncertainty in the

  1. Predictors of wellness and American Indians.

    Science.gov (United States)

    Hodge, Felicia S; Nandy, Karabi

    2011-08-01

    Wellness is an important American Indian (AI) concept, understood as being in balance with one's body, mind, and environment. Wellness predictors are reported in this paper within the context of health. A cross-sectional randomized household survey of 457 AI adults at 13 rural health care sites in California was conducted. Measures included wellness perceptions, barriers, health status/health conditions, spirituality, cultural connectivity, high-risk behaviors and abuse history. Statistical analysis obtained the best predictive model for wellness. Predictors of wellness were general health status perception, participation in AI cultural practices and suicide ideation. Significant differences in wellness status were observed depending on experience of adverse events in childhood and adulthood (neglect, physical abuse, and sexual abuse). Cultural connectivity (speaking tribal language, participating in AI practices, and feeling connected to community) was also associated with perceptions of wellness. Recommendations are for culturally-appropriate education and interventions emphasizing community and cultural connectivity for improving wellness status.

  2. Significance of uncertainties derived from settling tank model structure and parameters on predicting WWTP performance - A global sensitivity analysis study

    DEFF Research Database (Denmark)

    Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen

    2011-01-01

    Uncertainty derived from one of the process models – such as one-dimensional secondary settling tank (SST) models – can impact the output of the other process models, e.g., biokinetic (ASM1), as well as the integrated wastewater treatment plant (WWTP) models. The model structure and parameter...... uncertainty of settler models can therefore propagate, and add to the uncertainties in prediction of any plant performance criteria. Here we present an assessment of the relative significance of secondary settling model performance in WWTP simulations. We perform a global sensitivity analysis (GSA) based....... The outcome of this study contributes to a better understanding of uncertainty in WWTPs, and explicitly demonstrates the significance of secondary settling processes that are crucial elements of model prediction under dry and wet-weather loading conditions....

  3. Significantly improved HIV inhibitor efficacy prediction employing proteochemometric models generated from antivirogram data.

    Directory of Open Access Journals (Sweden)

    Gerard J P van Westen

    Full Text Available Infection with HIV cannot currently be cured; however it can be controlled by combination treatment with multiple anti-retroviral drugs. Given different viral genotypes for virtually each individual patient, the question now arises which drug combination to use to achieve effective treatment. With the availability of viral genotypic data and clinical phenotypic data, it has become possible to create computational models able to predict an optimal treatment regimen for an individual patient. Current models are based only on sequence data derived from viral genotyping; chemical similarity of drugs is not considered. To explore the added value of chemical similarity inclusion we applied proteochemometric models, combining chemical and protein target properties in a single bioactivity model. Our dataset was a large scale clinical database of genotypic and phenotypic information (in total ca. 300,000 drug-mutant bioactivity data points, 4 (NNRTI, 8 (NRTI or 9 (PI drugs, and 10,700 (NNRTI 10,500 (NRTI or 27,000 (PI mutants. Our models achieved a prediction error below 0.5 Log Fold Change. Moreover, when directly compared with previously published sequence data, derived models PCM performed better in resistance classification and prediction of Log Fold Change (0.76 log units versus 0.91. Furthermore, we were able to successfully confirm both known and identify previously unpublished, resistance-conferring mutations of HIV Reverse Transcriptase (e.g. K102Y, T216M and HIV Protease (e.g. Q18N, N88G from our dataset. Finally, we applied our models prospectively to the public HIV resistance database from Stanford University obtaining a correct resistance prediction rate of 84% on the full set (compared to 80% in previous work on a high quality subset. We conclude that proteochemometric models are able to accurately predict the phenotypic resistance based on genotypic data even for novel mutants and mixtures. Furthermore, we add an applicability domain to

  4. 75 FR 29587 - Notice of Availability of Revised Model Proposed No Significant Hazards Consideration...

    Science.gov (United States)

    2010-05-26

    ... of Nuclear Reactor Regulation, U.S. Nuclear Regulatory Commission, Washington, DC, 20555-0001... Processes Branch, Division of Policy and Rulemaking, Office of Nuclear Reactor Regulation. Revised Model... with the confidence in the ability of the fission product barriers (i.e., fuel cladding,...

  5. Significant Term List Based Metadata Conceptual Mining Model for Effective Text Clustering

    Directory of Open Access Journals (Sweden)

    J. Janet

    2012-01-01

    Full Text Available As the engineering world are growing fast, the usage of data for the day to day activity of the engineering industry also growing rapidly. In order to handle and to find the hidden knowledge from huge data storage, data mining is very helpful right now. Text mining, network mining, multimedia mining, trend analysis are few applications of data mining. In text mining, there are variety of methods are proposed by many researchers, even though high precision, better recall are still is a critical issues. In this study, text mining is focused and conceptual mining model is applied for improved clustering in the text mining. The proposed work is termed as Meta data Conceptual Mining Model (MCMM, is validated with few world leading technical digital library data sets such as IEEE, ACM and Scopus. The performance derived as precision, recall are described in terms of Entropy, F-Measure which are calculated and compared with existing term based model and concept based mining model.

  6. Significance of Kinetics for Sorption on Inorganic Colloids: Modeling and Data Interpretation Issues

    Science.gov (United States)

    Painter, S.; Cvetkovic, V.; Pickett, D.; Turner, D.

    2001-12-01

    Irreversible or slowly reversible attachment to inorganic colloids is a process that may enhance radionuclide transport in the environment. An understanding of sorption kinetics is critical in evaluating this process. A two-site kinetic model for sorption on inorganic colloids is developed and used to evaluate laboratory data. This model was developed as an alternative to the equilibrium colloid sorption model employed by the U.S. Department of Energy (DOE) in their performance assessment for the proposed repository for high-level nuclear waste at Yucca Mountain, Nevada. The model quantifies linear first-order sorption on two types of hypothetical sites (fast and slow) characterized by two pairs of rates (forward and reverse). We use the model to explore data requirements for long-term predictive calculations and to evaluate laboratory kinetic sorption data of Lu et al. Five batch sorption data sets are considered with Pu(V) as the tracer and montmorillonite, hematite, silica, and smectite as colloids. Using asymptotic results applicable on the 240 hour time-scale of the experiments, a robust estimation procedure is developed for the fast-site partitioning coefficient and the slow forward rate. The estimated range for the partition coefficient is 1.1-76 L/g; the range for the slow forward rate is 0.0017-0.02 L/h. Comparison of one-site and two-site sorption interpretations reveals the difficulty in discriminating between the two models for montmorillonite and to a lesser extent for hematite. For silica and smectite the two-site model clearly provides a better representation of the data as compared with a single site model. Kinetic data for silica are available for different colloid concentrations (0.2 g/L and 1.0 g/L). For the range of experimental conditions considered, the forward rate appears to be independent of the colloid concentration. The slow reverse rate cannot be estimated on the time scale of the experiments; we estimate the detection limits for the

  7. An Ecological-Transactional Model of Significant Risk Factors for Child Psychopathology in Outer Mongolia

    Science.gov (United States)

    Kohrt, Holbrook E.; Kohrt, Brandon A.; Waldman, Irwin; Saltzman, Kasey; Carrion, Victor G.

    2004-01-01

    The present study examined significant risk factors, including child maltreatment, for child psychopathology in a cross-cultural setting. Ninety-nine Mongolian boys, ages 3-10 years, were assessed. Primary caregivers (PCG) completed structured interviews including the Emory Combined Rating Scale (ECRS) and the Mood and Feelings Questionnaire…

  8. Magnitude, modeling and significance of swelling and shrinkage processes in clay soils.

    NARCIS (Netherlands)

    Bronswijk, J.J.B.

    1991-01-01

    The dynamic process of swelling and shrinkage in clay soils has significant practical consequences, such as the rapid transport of water and solutes via shrinkage cracks to the subsoil, and the destruction of buildings and roads on clay soils. In order to develop measuring methods and computer simul

  9. Significance of different animal species in experimental models for in vivo investigations of hematopoiesis

    Directory of Open Access Journals (Sweden)

    Kovačević-Filipović Milica

    2004-01-01

    Full Text Available Numerous discoveries in medicine are results of experiments on different animal species. The most frequently used animals in hematopoiesis investigations are laboratory mice and rats, but so-called big animals, such as pigs, sheep, cats, dogs, and monkeys, evolution-wise closer to humans have a place in experimental hematology as well. The specific problematics of a certain animal specie can lead to fundamental knowledge on certain aspects of the process of hematopoiesis end the biology of stem cells in hematopoiesis. Furthermore, comparative investigations of certain phenomena in different species help in the recognition of the general rules in the living world. In the area f preclinicalinvesti- gations, animal models are an inevitable step in studies of transplantation biology of stem cells in hematopoiesis, as well as in studies of biologically active molecules which have an effect on the hematopoietic system. Knowledge acquired on animal models is applied in both human and veterinary medicine.

  10. Recent advances in mechanical characterisation of biofilm and their significance for material modelling.

    Science.gov (United States)

    Böl, Markus; Ehret, Alexander E; Bolea Albero, Antonio; Hellriegel, Jan; Krull, Rainer

    2013-06-01

    In recent years, the advances in microbiology show that biofilms are structurally complex, dynamic and adaptable systems including attributes of multicellular organisms and miscellaneous ecosystems. One may distinguish between beneficial and harmful biofilms appearing in daily life as well as various industrial processes. In order to advance the growth of the former or prevent the latter type of biofilm, a detailed understanding of its properties is indispensable. Besides microbiological aspects, this concerns the determination of mechanical characteristics, which provides the basis for material modelling. In the present paper the existing experimental methods that have been proposed since the 1980s are reviewed and critically discussed with respect to their usefulness and applicability to develop numerical modelling approaches.

  11. Development of the PCAD Model to Assess Biological Significance of Acoustic Disturbance

    Science.gov (United States)

    2015-09-30

    mother-calf separation as a function of body mass index ( BMI ) and proportion lipid in blubber. We have also quantified the relationship between those...the approach. This is best accomplished by selecting species that are as similar as possible to target species and are also extremely well-studied...We identified northern elephant seals and Atlantic bottlenose dolphins as the best species to parameterize the PCAD model. These species represent

  12. Significance of genetic information in risk assessment and individual classification using silicosis as a case model

    Energy Technology Data Exchange (ETDEWEB)

    McCanlies, E.; Landsittel, D.P.; Yucesoy, B.; Vallyathan, V.; Luster, M.L.; Sharp, D.S. [NIOSH, Morgantown, WV (United States)

    2002-06-01

    Over the last decade the role of genetic data in epidemiological research has expanded considerably. The authors recently published a case-control study that evaluated the interaction between silica exposure and minor variants in the genes coding for interleukin-1alpha. (IL-1alpha), interleukin-1 receptor antagonist (IL-1RA) and tumor necrosis factor alpha (TNFalpha) as risk factors associated with silicosis, a fibrotic lung disease. In contrast, this report uses data generated from these studies to illustrate the utility of genetic information for the purposes of risk assessment and clinical prediction. Specifically, this study addresses how, given a known exposure, genetic information affects the characterization of risk groups. Relative operating characteristic (ROC) curves were then used to determine the impact of genetic information on individual classification. Logistic regression modeling procedures were used to estimate the predicted probability of developing silicosis. This probability was then used to construct predicted risk deciles, first for a model with occupational exposure only and then for a model containing occupational exposure and genetic main effects and interactions. The results indicate that genetic information plays a valuable role in effectively characterizing risk groups and mechanisms of disease operating in a substantial proportion of the population. However, in the case of fibrotic lung disease caused by silica exposure, information about the presence or absence of the minor variants of IL-1alpha, IL-1RA and TNFalpha is unlikely to be a useful tool for individual classification.

  13. Bayesian Variable Selection with Related Predictors

    CERN Document Server

    Chipman, Hugh

    2008-01-01

    In data sets with many predictors, algorithms for identifying a good subset of predictors are often used. Most such algorithms do not account for any relationships between predictors. For example, stepwise regression might select a model containing an interaction AB but neither main effect A or B. This paper develops mathematical representations of this and other relations between predictors, which may then be incorporated in a model selection procedure. A Bayesian approach that goes beyond the standard independence prior for variable selection is adopted, and preference for certain models is interpreted as prior information. Priors relevant to arbitrary interactions and polynomials, dummy variables for categorical factors, competing predictors, and restrictions on the size of the models are developed. Since the relations developed are for priors, they may be incorporated in any Bayesian variable selection algorithm for any type of linear model. The application of the methods here is illustrated via the Stoch...

  14. Discrete-Time Domain Modelling of Voltage Source Inverters in Standalone Applications: Enhancement of Regulators Performance by Means of Smith Predictor

    DEFF Research Database (Denmark)

    Federico, de Bosio; de Sousa Ribeiro, Luiz Antonio; Freijedo Fernandez, Francisco Daniel

    2017-01-01

    and Smith predictor design, respectively, are obtained. Subsequently, the voltage regulator is also designed for a wide bandwidth, which permits the inclusion of resonant filters for the steady-state mitigation of odd harmonics at nonlinear unbalance load terminals. Discrete-time domain implementation......The decoupling of the capacitor voltage and inductor current has been shown to improve significantly the dynamic performance of voltage source inverters in standalone applications. However, the computation and PWM delays still limit the achievable bandwidth. In this paper a discrete-time domain...

  15. Bayesian inference for generalized linear mixed models with predictors subject to detection limits: an approach that leverages information from auxiliary variables.

    Science.gov (United States)

    Yue, Yu Ryan; Wang, Xiao-Feng

    2016-05-10

    This paper is motivated from a retrospective study of the impact of vitamin D deficiency on the clinical outcomes for critically ill patients in multi-center critical care units. The primary predictors of interest, vitamin D2 and D3 levels, are censored at a known detection limit. Within the context of generalized linear mixed models, we investigate statistical methods to handle multiple censored predictors in the presence of auxiliary variables. A Bayesian joint modeling approach is proposed to fit the complex heterogeneous multi-center data, in which the data information is fully used to estimate parameters of interest. Efficient Monte Carlo Markov chain algorithms are specifically developed depending on the nature of the response. Simulation studies demonstrate the outperformance of the proposed Bayesian approach over other existing methods. An application to the data set from the vitamin D deficiency study is presented. Possible extensions of the method regarding the absence of auxiliary variables, semiparametric models, as well as the type of censoring are also discussed.

  16. Breast cancer-associated metastasis is significantly increased in a model of autoimmune arthritis

    Science.gov (United States)

    Das Roy, Lopamudra; Pathangey, Latha B; Tinder, Teresa L; Schettini, Jorge L; Gruber, Helen E; Mukherjee, Pinku

    2009-01-01

    Introduction Sites of chronic inflammation are often associated with the establishment and growth of various malignancies including breast cancer. A common inflammatory condition in humans is autoimmune arthritis (AA) that causes inflammation and deformity of the joints. Other systemic effects associated with arthritis include increased cellular infiltration and inflammation of the lungs. Several studies have reported statistically significant risk ratios between AA and breast cancer. Despite this knowledge, available for a decade, it has never been questioned if the site of chronic inflammation linked to AA creates a milieu that attracts tumor cells to home and grow in the inflamed bones and lungs which are frequent sites of breast cancer metastasis. Methods To determine if chronic inflammation induced by autoimmune arthritis contributes to increased breast cancer-associated metastasis, we generated mammary gland tumors in SKG mice that were genetically prone to develop AA. Two breast cancer cell lines, one highly metastatic (4T1) and the other non-metastatic (TUBO) were used to generate the tumors in the mammary fat pad. Lung and bone metastasis and the associated inflammatory milieu were evaluated in the arthritic versus the non-arthritic mice. Results We report a three-fold increase in lung metastasis and a significant increase in the incidence of bone metastasis in the pro-arthritic and arthritic mice compared to non-arthritic control mice. We also report that the metastatic breast cancer cells augment the severity of arthritis resulting in a vicious cycle that increases both bone destruction and metastasis. Enhanced neutrophilic and granulocytic infiltration in lungs and bone of the pro-arthritic and arthritic mice and subsequent increase in circulating levels of proinflammatory cytokines, such as macrophage colony stimulating factor (M-CSF), interleukin-17 (IL-17), interleukin-6 (IL-6), vascular endothelial growth factor (VEGF), and tumor necrosis factor

  17. Support for significant evolutions of the user data model in ROOT files

    Energy Technology Data Exchange (ETDEWEB)

    Canal, Ph; Russo, P [Fermilab, Batavia, IL (United States); Brun, R; Janyst, L [CERN, Geneva (Switzerland); Fine, V; Lauret, J, E-mail: pcanal@fnal.go [Brookhaven National Laboratory, Upton, NY (United States)

    2010-04-01

    One of the main strengths of ROOT input and output (I/O) is its inherent support for schema evolution. Two distinct modes are supported, one manual via a hand coded streamer function and one fully automatic via the ROOT StreamerInfo. One draw back of the streamer functions is that they are not usable by TTree objects in split mode. Until now, the user could not customize the automatic schema evolution mechanism and the only mechanism to go beyond the default rules was to revert to using the streamer function. In ROOT 5.22/00, we introduced a new mechanism which allows user provided extensions of the automatic schema evolution that can be used in object-wise, member-wise and split modes. This paper will describe the many possibilities ranging from the simple assignment of transient members to the complex reorganization of the user's object model.

  18. Trait impressions as overgeneralized responses to adaptively significant facial qualities: evidence from connectionist modeling.

    Science.gov (United States)

    Zebrowitz, Leslie A; Fellous, Jean-Marc; Mignault, Alain; Andreoletti, Carrie

    2003-01-01

    Connectionist modeling experiments tested anomalous-face and baby-face overgeneralization hypotheses proposed to explain consensual trait impressions of faces. Activation of a neural network unit trained to respond to anomalous faces predicted impressions of normal adult faces varying in attractiveness as well as several elderly stereotypes. Activation of a neural network unit trained to respond to babies' faces predicted impressions of adults varying in babyfaceness as well as 1 elderly stereotype. Thus, similarities of normal adult faces to anomalous faces or babies' faces contribute to impressions of them quite apart from knowledge of overlapping social stereotypes. The evolutionary importance of appropriate responses to unfit individuals or babies is presumed to produce a strong response preparedness that is overgeneralized to faces resembling the unfit or babies.

  19. Mouse models of lipodystrophy and their significance in understanding fat regulation.

    Science.gov (United States)

    Rochford, Justin J

    2014-01-01

    Adipose tissue plays a critical role in human metabolic health. This is most dramatically illustrated by the severe metabolic disease that occurs in syndromes of lipodystrophy where individuals fail to develop or maintain appropriate adipose tissue mass. The most severe form of this disorder is congenital generalized lipodystrophy (CGL). Individuals with CGL have a striking paucity of adipose tissue and typically display severe metabolic disease with insulin resistance and dyslipidemia. Understanding of the metabolic consequences of lipodystrophies and their underlying molecular mechanisms will provide new information regarding the development and function of human adipose tissue. Mouse models of these conditions offer key resources to investigate this in vivo. Adipocyte dysfunction is believed to underlie the development of metabolic disease in obesity. Hence, understanding how one might beneficially manipulate adipose tissue by studying genes whose disruption causes lipodystrophy is likely to suggest novel means to improve metabolic health in common obesity.

  20. Support for significant evolutions of the user data model in ROOT files

    Energy Technology Data Exchange (ETDEWEB)

    Canal, P.; /Fermilab; Brun, R.; /CERN; Fine, V.; /Brookhaven; Janyst, L.; /CERN; Lauret, J.; /Brookhaven; Russo, P.; /Fermilab

    2010-01-01

    One of the main strengths of ROOT input and output (I/O) is its inherent support for schema evolution. Two distinct modes are supported, one manual via a hand coded streamer function and one fully automatic via the ROOT StreamerInfo. One draw back of the streamer functions is that they are not usable by TTree objects in split mode. Until now, the user could not customize the automatic schema evolution mechanism and the only mechanism to go beyond the default rules was to revert to using the streamer function. In ROOT 5.22/00, we introduced a new mechanism which allows user provided extensions of the automatic schema evolution that can be used in object-wise, member-wise and split modes. This paper will describe the many possibilities ranging from the simple assignment of transient members to the complex reorganization of the user's object model.

  1. Preconditioning Provides Neuroprotection in Models of CNS Disease: Paradigms and Clinical Significance

    Science.gov (United States)

    Stetler, R. Anne; Leak, Rehana K.; Gan, Yu; Li, Peiying; Hu, Xiaoming; Jing, Zheng; Chen, Jun; Zigmond, Michael J.; Gao, Yanqin

    2014-01-01

    Preconditioning is a phenomenon in which brief episodes of a sublethal insult induce robust protection against subsequent lethal injuries. Preconditioning has been observed in multiple organisms and can occur in the brain as well as other tissues. Extensive animal studies suggest that the brain can be preconditioned to resist acute injuries, such as ischemic stroke, neonatal hypoxia/ischemia, trauma, and agents that are used in models of neurodegenerative diseases, such as Parkinson’s disease and Alzheimer’s disease. Effective preconditioning stimuli are numerous and diverse, ranging from transient ischemia, hypoxia, hyperbaric oxygen, hypothermia and hyperthermia, to exposure to neurotoxins and pharmacological agents. The phenomenon of “cross-tolerance,” in which a sublethal stress protects against a different type of injury, suggests that different preconditioning stimuli may confer protection against a wide range of injuries. Research conducted over the past few decades indicates that brain preconditioning is complex, involving multiple effectors such as metabolic inhibition, activation of extra- and intracellular defense mechanisms, a shift in the neuronal excitatory/inhibitory balance, and reduction in inflammatory sequelae. An improved understanding of brain preconditioning should help us identify innovative therapeutic strategies that prevent or at least reduce neuronal damage in susceptible patients. In this review, we focus on the experimental evidence of preconditioning in the brain and systematically survey the models used to develop paradigms for neuroprotection, and then discuss the clinical potential of brain preconditioning. In a subsequent components of this two-part series, we will discuss the cellular and molecular events that are likely to underlie these phenomena. PMID:24389580

  2. Optimal Skin-to-Stone Distance Is a Positive Predictor for Successful Outcomes in Upper Ureter Calculi following Extracorporeal Shock Wave Lithotripsy: A Bayesian Model Averaging Approach.

    Directory of Open Access Journals (Sweden)

    Kang Su Cho

    Full Text Available To investigate whether skin-to-stone distance (SSD, which remains controversial in patients with ureter stones, can be a predicting factor for one session success following extracorporeal shock wave lithotripsy (ESWL in patients with upper ureter stones.We retrospectively reviewed the medical records of 1,519 patients who underwent their first ESWL between January 2005 and December 2013. Among these patients, 492 had upper ureter stones that measured 4-20 mm and were eligible for our analyses. Maximal stone length, mean stone density (HU, and SSD were determined on pretreatment non-contrast computed tomography (NCCT. For subgroup analyses, patients were divided into four groups. Group 1 consisted of patients with SSD<25th percentile, group 2 consisted of patients with SSD in the 25th to 50th percentile, group 3 patients had SSD in the 50th to 75th percentile, and group 4 patients had SSD≥75th percentile.In analyses of group 2 patients versus others, there were no statistical differences in mean age, stone length and density. However, the one session success rate in group 2 was higher than other groups (77.9% vs. 67.0%; P = 0.032. The multivariate logistic regression model revealed that shorter stone length, lower stone density, and the group 2 SSD were positive predictors for successful outcomes in ESWL. Using the Bayesian model-averaging approach, longer stone length, lower stone density, and group 2 SSD can be also positive predictors for successful outcomes following ESWL.Our data indicate that a group 2 SSD of approximately 10 cm is a positive predictor for success following ESWL.

  3. Thermophysical modeling of asteroids from WISE thermal infrared data - Significance of the shape model and the pole orientation uncertainties

    CERN Document Server

    Hanuš, Josef; Ďurech, Josef; Alí-Lagoa, Victor

    2015-01-01

    In the analysis of thermal infrared data of asteroids by means of thermophysical models (TPMs) it is a common practice to neglect the uncertainty of the shape model and the rotational state, which are taken as an input for the model. Here, we present a novel method of investigating the importance of the shape model and the pole orientation uncertainties in the thermophysical modeling - the varied shape TPM (VS-TPM). Our method uses optical photometric data to generate various shape models that map the uncertainty in the shape and the rotational state. The TPM procedure is then run for all these shape models. We apply the implementation of the classical TPM as well as our VS-TPM to the convex shape models of several asteroids together with their thermal infrared data acquired by the NASA's Wide-field Infrared Survey Explorer (WISE) and compare the results. These show that the uncertainties of the shape model and the pole orientation can be very important (e.g., for the determination of the thermal inertia) and...

  4. Towards the Significance of Decision Aid in Building Information Modeling (BIM Software Selection Process

    Directory of Open Access Journals (Sweden)

    Omar Mohd Faizal

    2014-01-01

    Full Text Available Building Information Modeling (BIM has been considered as a solution in construction industry to numerous problems such as delays, increased lead in times and increased costs. This is due to the concept and characteristic of BIM that will reshaped the way construction project teams work together to increase productivity and improve the final project outcomes (cost, time, quality, safety, functionality, maintainability, etc.. As a result, the construction industry has witnesses numerous of BIM software available in market. Each of this software has offers different function, features. Furthermore, the adoption of BIM required high investment on software, hardware and also training expenses. Thus, there is indentified that there is a need of decision aid for appropriated BIM software selection that fulfill the project needs. However, research indicates that there is limited study attempt to guide decision in BIM software selection problem. Thus, this paper highlight the importance of decision making and support for BIM software selection as it is vital to increase productivity, construction project throughout building lifecycle.

  5. Myriocin significantly increases the mortality of a non-mammalian model host during Candida pathogenesis.

    Directory of Open Access Journals (Sweden)

    Nadja Rodrigues de Melo

    Full Text Available Candida albicans is a major human pathogen whose treatment is challenging due to antifungal drug toxicity, drug resistance and paucity of antifungal agents available. Myrocin (MYR inhibits sphingosine synthesis, a precursor of sphingolipids, an important cell membrane and signaling molecule component. MYR also has dual immune suppressive and antifungal properties, potentially modulating mammalian immunity and simultaneously reducing fungal infection risk. Wax moth (Galleria mellonella larvae, alternatives to mice, were used to establish if MYR suppressed insect immunity and increased survival of C. albicans-infected insects. MYR effects were studied in vivo and in vitro, and compared alone and combined with those of approved antifungal drugs, fluconazole (FLC and amphotericin B (AMPH. Insect immune defenses failed to inhibit C. albicans with high mortalities. In insects pretreated with the drug followed by C. albicans inoculation, MYR+C. albicans significantly increased mortality to 93% from 67% with C. albicans alone 48 h post-infection whilst AMPH+C. albicans and FLC+C. albicans only showed 26% and 0% mortalities, respectively. MYR combinations with other antifungal drugs in vivo also enhanced larval mortalities, contrasting the synergistic antifungal effect of the MYR+AMPH combination in vitro. MYR treatment influenced immunity and stress management gene expression during C. albicans pathogenesis, modulating transcripts putatively associated with signal transduction/regulation of cytokines, I-kappaB kinase/NF-kappaB cascade, G-protein coupled receptor and inflammation. In contrast, all stress management gene expression was down-regulated in FLC and AMPH pretreated C. albicans-infected insects. Results are discussed with their implications for clinical use of MYR to treat sphingolipid-associated disorders.

  6. Predictors of attrition among rural breast cancer survivors.

    Science.gov (United States)

    Meneses, Karen; Azuero, Andres; Su, Xiaogang; Benz, Rachel; McNees, Patrick

    2014-02-01

    Attrition can jeopardize both internal and external validity. The goal of this secondary analysis was to examine predictors of attrition using baseline data of 432 participants in the Rural Breast Cancer Survivors study. Attrition predictors were conceptualized based on demographic, social, cancer treatment, physical health, and mental health characteristics. Baseline measures were selected using this conceptualization. Bivariate tests of association, discrete-time Cox regression models and recursive partitioning techniques were used in analysis. Results showed that 100 participants (23%) dropped out by Month 12. Non-linear tree analyses showed that poor mental health and lack of health insurance were significant predictors of attrition. Findings contribute to future research efforts to reduce research attrition among rural underserved populations.

  7. Mental Health Changes and Its Predictors in Adolescents using the Path Analytic Model: A 7-Year Observational Study.

    Directory of Open Access Journals (Sweden)

    Ali Reza Soltanian

    2014-03-01

    Full Text Available This 7-year observational study examines the hours of TV-watching, phone conversation with friends, using the internet, and physical activity as predictors of mental health among adolescents in south of Iran.At the baseline (in 2005, the participants were 2584 high school students in the 9th to 11th grade. At the baseline, 30% of the available participants (n = 775 were selected in the follow-up (2012 using convenience sampling method. This study used the path analysis to examine the predictors of mental health and to obtain direct, indirect and total effects of the independent variables.At the baseline (2005, female gender, internet use, maternal education, physical activity and father's education were associated with mental health (p<0.05. Baseline mental health, internet use and physical activity predicted mental health of the participants in the follow up (p<0.05.The findings of the study revealed that better mental health in later life is associated with better mental health at baseline, male gender, higher physical activity and phone communication with friends, and less use of the internet and TV.

  8. Economic Environment as a Predictor of Effective Sport Marketing in ...

    African Journals Online (AJOL)

    Economic Environment as a Predictor of Effective Sport Marketing in Nigeria. ... Environment as a Predictor of Effective Sport Marketing in Nigeria. E Akarah ... Nigeria economic environment would significantly predict effective sport marketing.

  9. Assessing the effect of quantitative and qualitative predictors on gastric cancer individuals survival using hierarchical artificial neural network models.

    Science.gov (United States)

    Amiri, Zohreh; Mohammad, Kazem; Mahmoudi, Mahmood; Parsaeian, Mahbubeh; Zeraati, Hojjat

    2013-01-01

    There are numerous unanswered questions in the application of artificial neural network models for analysis of survival data. In most studies, independent variables have been studied as qualitative dichotomous variables, and results of using discrete and continuous quantitative, ordinal, or multinomial categorical predictive variables in these models are not well understood in comparison to conventional models. This study was designed and conducted to examine the application of these models in order to determine the survival of gastric cancer patients, in comparison to the Cox proportional hazards model. We studied the postoperative survival of 330 gastric cancer patients who suffered surgery at a surgical unit of the Iran Cancer Institute over a five-year period. Covariates of age, gender, history of substance abuse, cancer site, type of pathology, presence of metastasis, stage, and number of complementary treatments were entered in the models, and survival probabilities were calculated at 6, 12, 18, 24, 36, 48, and 60 months using the Cox proportional hazards and neural network models. We estimated coefficients of the Cox model and the weights in the neural network (with 3, 5, and 7 nodes in the hidden layer) in the training group, and used them to derive predictions in the study group. Predictions with these two methods were compared with those of the Kaplan-Meier product limit estimator as the gold standard. Comparisons were performed with the Friedman and Kruskal-Wallis tests. Survival probabilities at different times were determined using the Cox proportional hazards and a neural network with three nodes in the hidden layer; the ratios of standard errors with these two methods to the Kaplan-Meier method were 1.1593 and 1.0071, respectively, revealed a significant difference between Cox and Kaplan-Meier (P neural network, and the neural network and the standard (Kaplan-Meier), as well as better accuracy for the neural network (with 3 nodes in the hidden layer

  10. Predictors of Sustainability of Social Programs

    Science.gov (United States)

    Savaya, Riki; Spiro, Shimon E.

    2012-01-01

    This article presents the findings of a large scale study that tested a comprehensive model of predictors of three manifestations of sustainability: continuation, institutionalization, and duration. Based on the literature the predictors were arrayed in four groups: variables pertaining to the project, the auspice organization, the community, and…

  11. Material stiffness parameters as potential predictors of presence of left ventricle myocardial infarction: 3D echo-based computational modeling study.

    Science.gov (United States)

    Fan, Longling; Yao, Jing; Yang, Chun; Wu, Zheyang; Xu, Di; Tang, Dalin

    2016-04-05

    Ventricle material properties are difficult to obtain under in vivo conditions and are not readily available in the current literature. It is also desirable to have an initial determination if a patient had an infarction based on echo data before more expensive examinations are recommended. A noninvasive echo-based modeling approach and a predictive method were introduced to determine left ventricle material parameters and differentiate patients with recent myocardial infarction (MI) from those without. Echo data were obtained from 10 patients, 5 with MI (Infarct Group) and 5 without (Non-Infarcted Group). Echo-based patient-specific computational left ventricle (LV) models were constructed to quantify LV material properties. All patients were treated equally in the modeling process without using MI information. Systolic and diastolic material parameter values in the Mooney-Rivlin models were adjusted to match echo volume data. The equivalent Young's modulus (YM) values were obtained for each material stress-strain curve by linear fitting for easy comparison. Predictive logistic regression analysis was used to identify the best parameters for infract prediction. The LV end-systole material stiffness (ES-YMf) was the best single predictor among the 12 individual parameters with an area under the receiver operating characteristic (ROC) curve of 0.9841. LV wall thickness (WT), material stiffness in fiber direction at end-systole (ES-YMf) and material stiffness variation (∆YMf) had positive correlations with LV ejection fraction with correlation coefficients r = 0.8125, 0.9495 and 0.9619, respectively. The best combination of parameters WT + ∆YMf was the best over-all predictor with an area under the ROC curve of 0.9951. Computational modeling and material stiffness parameters may be used as a potential tool to suggest if a patient had infarction based on echo data. Large-scale clinical studies are needed to validate these preliminary findings.

  12. Predictors of Transience among Homeless Emerging Adults

    Science.gov (United States)

    Ferguson, Kristin M.; Bender, Kimberly; Thompson, Sanna J.

    2014-01-01

    This study identified predictors of transience among homeless emerging adults in three cities. A total of 601 homeless emerging adults from Los Angeles, Austin, and Denver were recruited using purposive sampling. Ordinary least squares regression results revealed that significant predictors of greater transience include White ethnicity, high…

  13. Time series analysis of dengue incidence in Guadeloupe, French West Indies: Forecasting models using climate variables as predictors

    Directory of Open Access Journals (Sweden)

    Ruche Guy

    2011-06-01

    Full Text Available Abstract Background During the last decades, dengue viruses have spread throughout the Americas region, with an increase in the number of severe forms of dengue. The surveillance system in Guadeloupe (French West Indies is currently operational for the detection of early outbreaks of dengue. The goal of the study was to improve this surveillance system by assessing a modelling tool to predict the occurrence of dengue epidemics few months ahead and thus to help an efficient dengue control. Methods The Box-Jenkins approach allowed us to fit a Seasonal Autoregressive Integrated Moving Average (SARIMA model of dengue incidence from 2000 to 2006 using clinical suspected cases. Then, this model was used for calculating dengue incidence for the year 2007 compared with observed data, using three different approaches: 1 year-ahead, 3 months-ahead and 1 month-ahead. Finally, we assessed the impact of meteorological variables (rainfall, temperature and relative humidity on the prediction of dengue incidence and outbreaks, incorporating them in the model fitting the best. Results The 3 months-ahead approach was the most appropriate for an effective and operational public health response, and the most accurate (Root Mean Square Error, RMSE = 0.85. Relative humidity at lag-7 weeks, minimum temperature at lag-5 weeks and average temperature at lag-11 weeks were variables the most positively correlated to dengue incidence in Guadeloupe, meanwhile rainfall was not. The predictive power of SARIMA models was enhanced by the inclusion of climatic variables as external regressors to forecast the year 2007. Temperature significantly affected the model for better dengue incidence forecasting (p-value = 0.03 for minimum temperature lag-5, p-value = 0.02 for average temperature lag-11 but not humidity. Minimum temperature at lag-5 weeks was the best climatic variable for predicting dengue outbreaks (RMSE = 0.72. Conclusion Temperature improves dengue outbreaks forecasts

  14. Weighted Feature Significance: A Simple, Interpretable Model of Compound Toxicity Based on the Statistical Enrichment of Structural Features

    OpenAIRE

    Huang, Ruili; Southall, Noel; Xia, Menghang; Cho, Ming-Hsuang; Jadhav, Ajit; Nguyen, Dac-Trung; Inglese, James; Tice, Raymond R.; Austin, Christopher P.

    2009-01-01

    In support of the U.S. Tox21 program, we have developed a simple and chemically intuitive model we call weighted feature significance (WFS) to predict the toxicological activity of compounds, based on the statistical enrichment of structural features in toxic compounds. We trained and tested the model on the following: (1) data from quantitative high–throughput screening cytotoxicity and caspase activation assays conducted at the National Institutes of Health Chemical Genomics Center, (2) dat...

  15. Perceived parental rearing behaviours, responsibility attitudes and life events as predictors of obsessive compulsive symptomatology: test of a cognitive model.

    Science.gov (United States)

    Haciomeroglu, Bikem; Karanci, A Nuray

    2014-11-01

    It is important to investigate the role of cognitive, developmental and environmental factors in the development and maintenance of Obsessive Compulsive Symptomatology (OCS). The main objective of this study was to examine the vulnerability factors of OCS in a non-clinical sample. On the basis of Salkovskis' cognitive model of OCD, the study aimed to investigate the role of perceived parental rearing behaviours, responsibility attitudes, and life events in predicting OCS. Furthermore, the mediator role of responsibility attitudes in the relationship between perceived parental rearing behaviours and OCS was examined. Finally, the specificity of these variables to OCS was evaluated by examining the relationship of the same variables with depression and trait anxiety. A total of 300 university students (M = 19.55±1.79) were administered the Padua Inventory-Washington State University Revision, Responsibility Attitudes Scale, s-EMBU (My memories of upbringing), Life Events Inventory for University Students, Beck Depression Inventory, and State-Trait Anxiety Inventory-Trait Form. Regression analysis revealed that perceived mother overprotection, responsibility attitudes and life events significantly predicted OCS. Furthermore, responsibility attitudes mediated the relationship between perceived mother overprotection and OCS. The predictive role of perceived mother overprotection and the mediator role responsibility attitudes were OCS specific. The findings of the present study supported that perceived mother over-protection as a developmental vulnerability factor significantly contributed to the explanation of a cognitive vulnerability factor (namely responsibility attitudes), and perceived maternal overprotection had its predictive role for OCS through responsibility attitudes.

  16. Low back pain patterns over one year among 842 workers in the DPhacto study and predictors for chronicity based on repetitive measurements

    DEFF Research Database (Denmark)

    Lagersted-Olsen, Julie; Bay, Hans; Jørgensen, Marie Birk

    2016-01-01

    intensity and high variation, (4) high intensity and low variation (defined as chronic LBP). Significant baseline predictors for chronic LBP in the fully adjusted model were high baseline LBP (p blue-collar worker (vs. white-collar worker...

  17. A more robust model of the biodiesel reaction, allowing identification of process conditions for significantly enhanced rate and water tolerance.

    Science.gov (United States)

    Eze, Valentine C; Phan, Anh N; Harvey, Adam P

    2014-03-01

    A more robust kinetic model of base-catalysed transesterification than the conventional reaction scheme has been developed. All the relevant reactions in the base-catalysed transesterification of rapeseed oil (RSO) to fatty acid methyl ester (FAME) were investigated experimentally, and validated numerically in a model implemented using MATLAB. It was found that including the saponification of RSO and FAME side reactions and hydroxide-methoxide equilibrium data explained various effects that are not captured by simpler conventional models. Both the experiment and modelling showed that the "biodiesel reaction" can reach the desired level of conversion (>95%) in less than 2min. Given the right set of conditions, the transesterification can reach over 95% conversion, before the saponification losses become significant. This means that the reaction must be performed in a reactor exhibiting good mixing and good control of residence time, and the reaction mixture must be quenched rapidly as it leaves the reactor.

  18. Behavioral predictors of alcohol drinking in a neurodevelopmental rat model of schizophrenia and co-occurring alcohol use disorder.

    Science.gov (United States)

    Khokhar, Jibran Y; Todd, Travis P

    2017-03-09

    Alcohol use disorder commonly occurs in patients with schizophrenia and contributes greatly to its morbidity. Unfortunately, the neural and behavioral underpinnings of alcohol drinking in these patients are not well understood. In order to begin to understand the cognitive and reward-related changes that may contribute to alcohol drinking, this study was designed to address: 1) latent inhibition; 2) conditioning; and 3) extinction of autoshaping in a neurodevelopmental rat model with relevance to co-occurring schizophrenia and alcohol use disorders, the neonatal ventral hippocampal lesioned (NVHL) rat. NVHL lesions (or sham surgeries) were performed on post-natal day 7 (PND7) and animals were given brief exposure to alcohol during adolescent (PND 28-42). Latent inhibition of autoshaping, conditioning and extinction were assessed between PND 72-90. On PND90 animals were given alcohol again and allowed to establish stable drinking. Latent inhibition of autoshaping was found to be prolonged in the NVHL rats; the NVHL rats pre-exposed to the lever stimulus were slower to acquire autoshaping than sham pre-exposed rats. NVHL rats that were not pre-exposed to the lever stimulus did not differ during conditioning, but were slower to extinguish conditioned responding compared to sham controls. Finally, the NVHL rats from both groups drank significantly more alcohol than sham rats, and the extent of latent inhibition predicted future alcohol intake in the pre-exposed animals. These findings suggest that the latent inhibition of autoshaping procedure can be used to model cognitive- and reward-related dysfunctions in schizophrenia, and these dysfunctions may contribute to the development of co-occurring alcohol use. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Generalized Models: An Application to Identify Environmental Variables That Significantly Affect the Abundance of Three Tree Species

    Directory of Open Access Journals (Sweden)

    Pablo Antúnez

    2017-02-01

    Full Text Available In defining the environmental preferences of plant species, statistical models are part of the essential tools in the field of modern ecology. However, conventional linear models require compliance with some parametric assumptions and if these requirements are not met, imply a serious limitation of the applied model. In this study, the effectiveness of linear and nonlinear generalized models was examined to identify the unitary effect of the principal environmental variables on the abundance of three tree species growing in the natural temperate forests of Oaxaca, Mexico. The covariates that showed a significant effect on the distribution of tree species were the maximum and minimum temperatures and the precipitation during specific periods. Results suggest that the generalized models, particularly smoothed models, were able to detect the increase or decrease of the abundance against changes in an environmental variable; they also revealed the inflection of the regression. In addition, these models allow partial characterization of the realized niche of a given species according to some specific variables, regardless of the type of relationship.

  20. Predictors of reducing sexual and reproductive risk behaviors based on the information-motivation-behavioral skills (IMB model among unmarried rural-to-urban female migrants in Shanghai, China.

    Directory of Open Access Journals (Sweden)

    Yong Cai

    Full Text Available BACKGROUND: Due to the increase of premarital sex and the lack of reproductive health services, unmarried rural-to-urban female migrants experience more risks of sex and reproductive health (SRH. This study was designed to describe SRH related knowledge, attitude and risk behaviors among unmarried rural-to-urban female migrants and examine the predictors of reducing sexual and reproductive risk behaviors based on information-motivation-behavioral skills (IMB model and to describe the relationships between the constructs. METHODS: We conducted a cross-sectional study to assess SRH related information, motivation, behavioral skills and preventive behaviors among unmarried rural-to-urban female migrants in Shanghai, one of the largest importers of migrant laborers in China. Structural equation modeling (SEM was used to assess the IMB model. RESULTS: A total of 944 subjects completed their questionnaires. The mean age was 21.2 years old (SD = 2.3; range 16 to 28. Over one-fourth of participants reported having had premarital sex (N = 261, 27.6% and among whom 15.3% reported having had the experience of unintended pregnancy, 14.6% with the experience of abortion. The final IMB model provided acceptable fit to the data (CFI = 0.99, RMSEA = 0.034. Reducing sexual and reproductive risk behaviors was significantly predicted by SRH related information (β = 0.681, P<0.001 and behavioral skills(β = 0.239, P<0.001. Motivation (β = 0.479, P<0.001 was the significant indirect predictor of reducing sexual and reproductive risk behaviors mediated through behavioral skills. CONCLUSIONS: The results highlight the importance and necessity of conducting reproductive health promotion among unmarried rural-to-urban female migrants in China. The IMB model could be used to predict reducing sexual and reproductive risk behaviors and it suggests future interventions should focus on improving SRH related information and behavioral skills.

  1. Single nucleotide polymorphisms in CETP, SLC46A1, SLC19A1, CD36, BCOM1, APOA5, and ABCA1 are significant predictors of plasma HDL in healthy adults

    Science.gov (United States)

    In a marker-trait association study we estimated the statistical significance of 65 single nucleotide polymorphisms (SNP) in 23 candidate genes on HDL levels of two independent Caucasian populations. Each population consisted of men and women and their HDL levels were adjusted for gender and body we...

  2. The photon dose calculation algorithm used in breast radiotherapy has significant impact on the parameters of radiobiological models.

    Science.gov (United States)

    Petillion, Saskia; Swinnen, Ans; Defraene, Gilles; Verhoeven, Karolien; Weltens, Caroline; Van den Heuvel, Frank

    2014-07-08

    The comparison of the pencil beam dose calculation algorithm with modified Batho heterogeneity correction (PBC-MB) and the analytical anisotropic algorithm (AAA) and the mutual comparison of advanced dose calculation algorithms used in breast radiotherapy have focused on the differences between the physical dose distributions. Studies on the radiobiological impact of the algorithm (both on the tumor control and the moderate breast fibrosis prediction) are lacking. We, therefore, investigated the radiobiological impact of the dose calculation algorithm in whole breast radiotherapy. The clinical dose distributions of 30 breast cancer patients, calculated with PBC-MB, were recalculated with fixed monitor units using more advanced algorithms: AAA and Acuros XB. For the latter, both dose reporting modes were used (i.e., dose-to-medium and dose-to-water). Next, the tumor control probability (TCP) and the normal tissue complication probability (NTCP) of each dose distribution were calculated with the Poisson model and with the relative seriality model, respectively. The endpoint for the NTCP calculation was moderate breast fibrosis five years post treatment. The differences were checked for significance with the paired t-test. The more advanced algorithms predicted a significantly lower TCP and NTCP of moderate breast fibrosis then found during the corresponding clinical follow-up study based on PBC calculations. The differences varied between 1% and 2.1% for the TCP and between 2.9% and 5.5% for the NTCP of moderate breast fibrosis. The significant differences were eliminated by determination of algorithm-specific model parameters using least square fitting. Application of the new parameters on a second group of 30 breast cancer patients proved their appropriateness. In this study, we assessed the impact of the dose calculation algorithms used in whole breast radiotherapy on the parameters of the radiobiological models. The radiobiological impact was eliminated by

  3. Serum NX-DCP as a New Noninvasive Model to Predict Significant Liver Fibrosis in Chronic Hepatitis C.

    Science.gov (United States)

    Saito, Masaya; Yano, Yoshihiko; Hirano, Hirotaka; Momose, Kenji; Yoshida, Masaru; Azuma, Takeshi

    2015-02-01

    Finding a noninvasive method to predict liver fibrosis using inexpensive and easy-to-use markers is important. We aimed to clarify whether NX-des-γ-carboxyprothrombin (NX-DCP) could become a new noninvasive model to predict liver fibrosis in hepatitis C virus (HCV) related liver disease. We performed a prospective cohort study on a consecutive group of 101 patients who underwent liver biopsy for HCV-related liver disease at Kobe University Hospital. Laboratory measurements were performed on the same day as the biopsy. Factors associated with significant fibrosis (F3-4) were assessed by multivariate analyses. A comparison of predictive ability between multivariate factors and abovementioned noninvasive models was also performed. Increase in serum NX-DCP was significantly related to increase in fibrosis stage (P = 0.006). Moreover, NX-DCP was a multivariate factor associated with the presence of significant fibrosis F 3-4 (median 21 of F0-2 group vs. median 22 of F3-4 group with P = 0.002). The AUC of NX-DCP showed no significant differences compared with those of the AST-to-platelet ratio index (APRI), modified-APRI, the Göteborg University Cirrhosis Index (GUCI), the Lok index, the Hui score, cirrhosis discriminating score (CDS) and the Pohl score (P > 0.05). NX-DCP correlated positively with fibrosis stage and could discriminate well between HCV-related patients with or without significant fibrosis. Moreover, NX-DCP had a similar predictive ability to the abovementioned models, and thereby could be a new noninvasive prediction tool for fibrosis.

  4. Motivational factors as predictors of student approach to learning

    DEFF Research Database (Denmark)

    Lassesen, Berit

    for the remaining variables. Results: The results of the multiple linear regression showed that each of the motivational factors of self-efficacy, test-anxiety generally strong independent statistical significant predictors in the expected directions of students approach to learning, both when analyzed separately...... model: R2 = 0.279) and Surface approach (Final model: R2 = 0.214).Conclusion: Although successful learning largely depends on knowledge and skills, factors such as self efficacy and test anxiety play an important role as predictors of students’ learning approaches, and subsequent learning outcomes...... to obtaining them. Besides being a role model by showing enthusiasm for the subject, teachers are important moderators when it comes to building the ability and effort required for deep learning...

  5. A test of the vulnerability model : Temperament and temperament change as predictors of future mental disorders - The TRAILS study

    NARCIS (Netherlands)

    Laceulle, Odilia M.|info:eu-repo/dai/nl/364227885; Ormel, Johan; Vollebergh, Wilma A M|info:eu-repo/dai/nl/090632893; Van Aken, Marcel A G|info:eu-repo/dai/nl/081831218; Nederhof, Esther

    2014-01-01

    Background This study aimed to test the vulnerability model of the relationship between temperament and mental disorders using a large sample of adolescents from the TRacking Adolescents Individual Lives' Survey (TRAILS). The vulnerability model argues that particular temperaments can place

  6. Predictors of Burnout Among Nurses in Taiwan.

    Science.gov (United States)

    Lee, Huan-Fang; Yen, Miaofen; Fetzer, Susan; Chien, Tsair Wei

    2015-08-01

    Nurse burnout is a crucial issue for health care professionals and impacts nurse turnover and nursing shortages. Individual and situational factors are related to nurse burnout with predictors of burnout differing among cultures and health care systems. The predictors of nurse burnout in Asia, particularly Taiwan, are unknown. The purpose of this study was to investigate the predictors of burnout among a national sample of nurses in Taiwan. A secondary data analysis of a nationwide database investigated the predictors of burnout among 1,846 nurses in Taiwan. Hierarchical regression analysis determined the relationship between predictors and burnout. Predictors of Taiwanese nurse burnout were age, physical/psychological symptoms, job satisfaction, work engagement, and work environment. The most significant predictors were physical/psychological symptoms and work engagement. The variables explained 35, 39, and 18 % of the emotional exhaustion, personal accomplishment, and depersonalization variance for 54 % of the total variance of burnout. Individual characteristics and nurse self-awareness, especially work, engagement can impact Taiwanese nurses' burnout. Nurse burnout predictors provide administrators with information to develop strategies including education programs and support services to reduce nurse burnout.

  7. Baseline muscle mass is a poor predictor of functional overload-induced gain in the mouse model

    Directory of Open Access Journals (Sweden)

    Audrius Kilikevicius

    2016-11-01

    Full Text Available Genetic background contributes substantially to individual variability in muscle mass. Muscle hypertrophy in response to resistance training can also vary extensively. However, it is less clear if muscle mass at baseline is predictive of the hypertrophic response.The aim of this study was to examine the effect of genetic background on variability in muscle mass at baseline and in the adaptive response of the mouse fast- and slow-twitch muscles to overload. Males of eight laboratory mouse strains: C57BL/6J (B6, n=17, BALB/cByJ (n=7, DBA/2J (D2, n=12, B6.A-(rs3676616-D10Utsw1/Kjn (B6.A, n=9, C57BL/6J-Chr10A/J/NaJ (B6.A10, n=8, BEH+/+ (n=11, BEH (n=12 and DUHi (n=12, were studied. Compensatory growth of soleus and plantaris muscles was triggered by a 4-week overload induced by synergist unilateral ablation. Muscle weight in the control leg (baseline varied from 5.2±07 mg soleus and 11.4±1.3 mg plantaris in D2 mice to 18.0±1.7 mg soleus in DUHi and 43.7±2.6 mg plantaris in BEH (p<0.001 for both muscles. In addition, soleus in the B6.A10 strain was ~40% larger (p<0.001 compared to the B6. Functional overload increased muscle weight, however, the extent of gain was strain-dependent for both soleus (p<0.01 and plantaris (p<0.02 even after accounting for the baseline differences. For the soleus muscle, the BEH strain emerged as the least responsive, with a 1.3-fold increase, compared to a 1.7-fold gain in the most responsive D2 strain, and there was no difference in the gain between the B6.A10 and B6 strains. The BEH strain appeared the least responsive in the gain of plantaris as well, 1.3-fold, compared to ~1.5-fold gain in the remaining strains. We conclude that variation in muscle mass at baseline is not a reliable predictor of that in the overload-induced gain. This suggests that a different set of genes influence variability in muscle mass acquired in the process of normal development, growth and maintenance, and in the process of adaptive

  8. Predictors of AIDS-preventive behavioral intentions among adult heterosexuals at risk for HIV-infection : Extending current models and measures

    NARCIS (Netherlands)

    Buunk, BP; Bakker, AB; Siero, FW; van den Eijnden, RJJM; Yzer, MC

    This study examined the predictors of the intention to use condoms with new sexual partners. A sample of heterosexual adult females and males (n = 711) was recruited through various channels. A substantial part of the sample had engaged in risky sexual behavior. Predictors were based on various

  9. A model for microbial phosphorus cycling in bioturbated marine sediments: Significance for phosphorus burial in the early Paleozoic

    Science.gov (United States)

    Dale, Andrew W.; Boyle, Richard A.; Lenton, Timothy M.; Ingall, Ellery D.; Wallmann, Klaus

    2016-09-01

    A diagenetic model is used to simulate the diagenesis and burial of particulate organic carbon (Corg) and phosphorus (P) in marine sediments underlying anoxic versus oxic bottom waters. The latter are physically mixed by animals moving through the surface sediment (bioturbation) and ventilated by burrowing, tube-dwelling organisms (bioirrigation). The model is constrained using an empirical database including burial ratios of Corg with respect to organic P (Corg:Porg) and total reactive P (Corg:Preac), burial efficiencies of Corg and Porg, and inorganic carbon-to-phosphorus regeneration ratios. If Porg is preferentially mineralized relative to Corg during aerobic respiration, as many previous studies suggest, then the simulated Porg pool is found to be completely depleted. A modified model that incorporates the redox-dependent microbial synthesis of polyphosphates and Porg (termed the microbial P pump) allows preferential mineralization of the bulk Porg pool relative to Corg during both aerobic and anaerobic respiration and is consistent with the database. Results with this model show that P burial is strongly enhanced in sediments hosting fauna. Animals mix highly labile Porg away from the aerobic sediment layers where mineralization rates are highest, thereby mitigating diffusive PO43- fluxes to the bottom water. They also expand the redox niche where microbial P uptake occurs. The model was applied to a hypothetical shelf setting in the early Paleozoic; a time of the first radiation of benthic fauna. Results show that even shallow bioturbation at that time may have had a significant impact on P burial. Our model provides support for a recent study that proposed that faunal radiation in ocean sediments led to enhanced P burial and, possibly, a stabilization of atmospheric O2 levels. The results also help to explain Corg:Porg ratios in the geological record and the persistence of Porg in ancient marine sediments.

  10. An automated nowcasting model of significant instability events in the flight terminal area of Rio de Janeiro, Brazil

    Science.gov (United States)

    Borges França, Gutemberg; Valdonel de Almeida, Manoel; Rosette, Alessana C.

    2016-05-01

    This paper presents a novel model, based on neural network techniques, to produce short-term and local-specific forecasts of significant instability for flights in the terminal area of Galeão Airport, Rio de Janeiro, Brazil. Twelve years of data were used for neural network training/validation and test. Data are originally from four sources: (1) hourly meteorological observations from surface meteorological stations at five airports distributed around the study area; (2) atmospheric profiles collected twice a day at the meteorological station at Galeão Airport; (3) rain rate data collected from a network of 29 rain gauges in the study area; and (4) lightning data regularly collected by national detection networks. An investigation was undertaken regarding the capability of a neural network to produce early warning signs - or as a nowcasting tool - for significant instability events in the study area. The automated nowcasting model was tested using results from five categorical statistics, indicated in parentheses in forecasts of the first, second, and third hours, respectively, namely proportion correct (0.99, 0.97, and 0.94), BIAS (1.10, 1.42, and 2.31), the probability of detection (0.79, 0.78, and 0.67), false-alarm ratio (0.28, 0.45, and 0.73), and threat score (0.61, 0.47, and 0.25). Possible sources of error related to the test procedure are presented and discussed. The test showed that the proposed model (or neural network) can grab the physical content inside the data set, and its performance is quite encouraging for the first and second hours to nowcast significant instability events in the study area.

  11. Predictors of Clinical Performance

    Science.gov (United States)

    Turner, Edward; And Others

    1974-01-01

    In a search for predictors of clinical competence, 50 third-year medical students studying pediatrics were videotaped during their interview and physical examination of outpatients. Consideration should be given to the possible value of psychological tests as predictors of clinical competence. (Author)

  12. Using ComBase Predictor and Pathogen Modeling Program as support tools in outbreak investigation: an example from Denmark

    DEFF Research Database (Denmark)

    Møller, Cleide; Hansen, Tina Beck; Andersen, Jens Kirk

    of salt to the batter. A deterministic model was constructed in Microsoft Excel using information on the production of the implicated sausage. This model predicted the level of Y. enterocolitica to increase 2.3, 4.2 and 7.8 log-units during fermentation, drying and storage, respectively. At the point...

  13. Using ComBase Predictor and Pathogen Modeling Program as support tools in outbreak investigation: an example from Denmark

    DEFF Research Database (Denmark)

    Møller, Cleide; Hansen, Tina Beck; Andersen, Jens Kirk

    2009-01-01

    of salt to the batter. A deterministic model was constructed in Microsoft Excel using information on the production of the implicated sausage. This model predicted the level of Y. enterocolitica to increase 2.3, 4.2 and 7.8 log-units during fermentation, drying and storage, respectively. At the point...

  14. A Conceptual Model of Cultural Predictors of Anxiety among Japanese American and Part-Japanese American Adolescents.

    Science.gov (United States)

    Williams, John Kino Yamaguchi; Goebert, Deborah; Hishinuma, Earl; Miyamoto, Robin; Anzai, Neal; Izutsu, Satoru; Yanagida, Evelyn; Nishimura, Stephanie; Andrade, Naleen; Baker, F. M.

    2002-01-01

    Develops and assesses a model integrating Japanese ethnicity, cultural identity, and anxiety in Japanese American and part-Japanese American high school seniors. Japanese American adolescents scored higher on the scale and reported fewer anxiety symptoms than part-Japanese American adolescents. The model had a good overall fit, suggesting that…

  15. A test of the vulnerability model : Temperament and temperament change as predictors of future mental disorders - The TRAILS study

    NARCIS (Netherlands)

    Laceulle, Odilia M.; Ormel, Johan; Vollebergh, Wilma A M; Van Aken, Marcel A G; Nederhof, Esther

    2014-01-01

    Background This study aimed to test the vulnerability model of the relationship between temperament and mental disorders using a large sample of adolescents from the TRacking Adolescents Individual Lives' Survey (TRAILS). The vulnerability model argues that particular temperaments can place individu

  16. Pomalidomide shows significant therapeutic activity against CNS lymphoma with a major impact on the tumor microenvironment in murine models.

    Science.gov (United States)

    Li, Zhimin; Qiu, Yushi; Personett, David; Huang, Peng; Edenfield, Brandy; Katz, Jason; Babusis, Darius; Tang, Yang; Shirely, Michael A; Moghaddam, Mehran F; Copland, John A; Tun, Han W

    2013-01-01

    Primary CNS lymphoma carries a poor prognosis. Novel therapeutic agents are urgently needed. Pomalidomide (POM) is a novel immunomodulatory drug with anti-lymphoma activity. CNS pharmacokinetic analysis was performed in rats to assess the CNS penetration of POM. Preclinical evaluation of POM was performed in two murine models to assess its therapeutic activity against CNS lymphoma. The impact of POM on the CNS lymphoma immune microenvironment was evaluated by immunohistochemistry and immunofluorescence. In vitro cell culture experiments were carried out to further investigate the impact of POM on the biology of macrophages. POM crosses the blood brain barrier with CNS penetration of ~ 39%. Preclinical evaluations showed that it had significant therapeutic activity against CNS lymphoma with significant reduction in tumor growth rate and prolongation of survival, that it had a major impact on the tumor microenvironment with an increase in macrophages and natural killer cells, and that it decreased M2-polarized tumor-associated macrophages and increased M1-polarized macrophages when macrophages were evaluated based on polarization status. In vitro studies using various macrophage models showed that POM converted the polarization status of IL4-stimulated macrophages from M2 to M1, that M2 to M1 conversion by POM in the polarization status of lymphoma-associated macrophages is dependent on the presence of NK cells, that POM induced M2 to M1 conversion in the polarization of macrophages by inactivating STAT6 signaling and activating STAT1 signaling, and that POM functionally increased the phagocytic activity of macrophages. Based on our findings, POM is a promising therapeutic agent for CNS lymphoma with excellent CNS penetration, significant preclinical therapeutic activity, and a major impact on the tumor microenvironment. It can induce significant biological changes in tumor-associated macrophages, which likely play a major role in its therapeutic activity against CNS

  17. A conceptual model of individual competency components as one of the predictors of success in mergers and acquisitions

    Directory of Open Access Journals (Sweden)

    Darko Kovač

    2008-12-01

    Full Text Available The increasing challenge of how to balance “soft” human factors with “hard” financial factors in mergers and acquisitions (M&A to be successful is not new. However, the real challenge lies in the question of how, and with which yardstick, to measure and compare the human factor in both the acquiring and the acquired companies in all phases of M&A. In this study, a model for measuring and comparing the human factor with competencies is presented. The model enables the measuring of soft factors with quantitative criteria. A tripartite individual competency components construct is conceived: cognitive, affective and conative, to which the personal value system is added. The model discussed is based on empirical findings and the cases of two companies and literature. The model enables companies to compare differences in competencies and thus to plan activities how to overcome those differences and achieve a higher success rate in M&A.

  18. Academic predictors of success in a nursing program.

    Science.gov (United States)

    Wolkowitz, Amanda A; Kelley, Jeffrey A

    2010-09-01

    The academic content areas that best predict success early in a nursing program affect admission and placement decisions in nursing programs nationwide. The purpose of this research was to apply a multiple regression model to student test scores to determine the relative strength of science, mathematics, reading, and English content areas in predicting early nursing school success. Using a standardized nursing entrance examination, the subtest scores of these four academic areas for 4,105 registered nurse students were used as the predictors in the regression model. Performance on a standardized Fundamentals of Nursing assessment was the criterion variable. Results confirmed those found in the majority of the literature indicating that science is both a statistically significant predictor and the strongest of the four content areas in the prediction of early nursing program success.

  19. Childhood body mass index trajectories: modeling, characterizing, pairwise correlations and socio-demographic predictors of trajectory characteristics

    OpenAIRE

    Wen Xiaozhong; Kleinman Ken; Gillman Matthew W; Rifas-Shiman Sheryl L; Taveras Elsie M

    2012-01-01

    Abstract Background Modeling childhood body mass index (BMI) trajectories, versus estimating change in BMI between specific ages, may improve prediction of later body-size-related outcomes. Prior studies of BMI trajectories are limited by restricted age periods and insufficient use of trajectory information. Methods Among 3,289 children seen at 81,550 pediatric well-child visits from infancy to 18 years between 1980 and 2008, we fit individual BMI trajectories using mixed effect models with f...

  20. Spatio-temporal modeling of particulate air pollution in the conterminous United States using geographic and meteorological predictors

    Science.gov (United States)

    2014-01-01

    Background Exposure to atmospheric particulate matter (PM) remains an important public health concern, although it remains difficult to quantify accurately across large geographic areas with sufficiently high spatial resolution. Recent epidemiologic analyses have demonstrated the importance of spatially- and temporally-resolved exposure estimates, which show larger PM-mediated health effects as compared to nearest monitor or county-specific ambient concentrations. Methods We developed generalized additive mixed models that describe regional and small-scale spatial and temporal gradients (and corresponding uncertainties) in monthly mass concentrations of fine (PM2.5), inhalable (PM10), and coarse mode particle mass (PM2.5–10) for the conterminous United States (U.S.). These models expand our previously developed models for the Northeastern and Midwestern U.S. by virtue of their larger spatial domain, their inclusion of an additional 5 years of PM data to develop predictions through 2007, and their use of refined geographic covariates for population density and point-source PM emissions. Covariate selection and model validation were performed using 10-fold cross-validation (CV). Results The PM2.5 models had high predictive accuracy (CV R2=0.77 for both 1988–1998 and 1999–2007). While model performance remained strong, the predictive ability of models for PM10 (CV R2=0.58 for both 1988–1998 and 1999–2007) and PM2.5–10 (CV R2=0.46 and 0.52 for 1988–1998 and 1999–2007, respectively) was somewhat lower. Regional variation was found in the effects of geographic and meteorological covariates. Models generally performed well in both urban and rural areas and across seasons, though predictive performance varied somewhat by region (CV R2=0.81, 0.81, 0.83, 0.72, 0.69, 0.50, and 0.60 for the Northeast, Midwest, Southeast, Southcentral, Southwest, Northwest, and Central Plains regions, respectively, for PM2.5 from 1999–2007). Conclusions Our models provide

  1. Hydrothermal Fe cycling and deep ocean organic carbon scavenging: Model-based evidence for significant POC supply to seafloor sediments

    Science.gov (United States)

    German, C. R.; Legendre, L. L.; Sander, S. G.; Niquil, N.; Luther, G. W.; Bharati, L.; Han, X.; Le Bris, N.

    2015-06-01

    Submarine hydrothermal venting has recently been identified to have the potential to impact ocean biogeochemistry at the global scale. This is the case because processes active in hydrothermal plumes are so vigorous that the residence time of the ocean, with respect to cycling through hydrothermal plumes, is comparable to that of deep ocean mixing caused by thermohaline circulation. Recently, it has been argued that seafloor venting may provide a significant source of bio-essential Fe to the oceans as the result of a close coupling between Fe and organic carbon in hydrothermal plumes. But a complementary question remains to be addressed: does this same intimate Fe-Corg association in hydrothermal plumes cause any related impact to the global C cycle? To address this, SCOR-InterRidge Working Group 135 developed a modeling approach to synthesize site-specific field data from the East Pacific Rise 9°50‧ N hydrothermal field, where the range of requisite data sets is most complete, and combine those inputs with global estimates for dissolved Fe inputs from venting to the oceans to establish a coherent model with which to investigate hydrothermal Corg cycling. The results place new constraints on submarine Fe vent fluxes worldwide, including an indication that the majority of Fe supplied to hydrothermal plumes should come from entrainment of diffuse flow. While this same entrainment is not predicted to enhance the supply of dissolved organic carbon to hydrothermal plumes by more than ∼10% over background values, what the model does indicate is that scavenging of carbon in association with Fe-rich hydrothermal plume particles should play a significant role in the delivery of particulate organic carbon to deep ocean sediments, worldwide.

  2. Changes of High Mobility Group box 1 in Serum of Pig Acute Hepatic Failure Model and Significance

    Institute of Scientific and Technical Information of China (English)

    Fan ZHANG; Yongwen HE; Zhongping DUAN

    2008-01-01

    The role of the high mobility group box 1 (HMGB-1) in acute hepatic failure and the ef- fect of artificial liver support system treatment on HMGB-1 level were investigated. Pig models of acute hepatic failure were induced by D-galactosamine and randomly divided into two groups with or without artificial liver support system treatment. Tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) levels were detected by the enzyme linked immunosorbent assay (ELISA), the expression of HMGB-1 by Western blot, and serum levels of HMGB-1, liver function and hepatic pathology were observed after artificial liver support system treatment. The levels of TNF-α and IL-1β were increased and reached the peak at 24th h in the acute hepatic failure group, then quickly decreased. The serum level of HMGB-1 was increased at 24th h in the acute hepatic failure group and reached the peak at 48th h, then kept a stable high level. Significant liver injury appeared at 24th h and was continuously getting worse in the pig models of acute hepatic failure. In contrast, the liver injury was significantly alleviated and serum level of HMGB-1 was significantly decreased in the group treated with artificial liver support system (P<0.05). It was suggested that HMGB-1 may participate in the inflammatory response and liver injury in the late stage of the acute liver failure. Artificial liver support system treatment can reduce serum HMGB-1 level and relieve liver pathological damage.

  3. Childhood cardiovascular risk factors, a predictor of late adolescent overweight

    Directory of Open Access Journals (Sweden)

    Saeed Kalantari

    2016-01-01

    Conclusion: Increased CVD risk factors are predictors of future overweight in childhood and adolescent and increased weight is linked significantly with dyslipidemia and hypertension in this age group.

  4. Predictors of Business Return in New Orleans after Hurricane Katrina

    Science.gov (United States)

    Lam, Nina S. N.; Arenas, Helbert; Pace, Kelley; LeSage, James; Campanella, Richard

    2012-01-01

    We analyzed the business reopening process in New Orleans after Hurricane Katrina, which hit the region on August 29, 2005, to better understand what the major predictors were and how their impacts changed through time. A telephone survey of businesses in New Orleans was conducted in October 2007, 26 months after Hurricane Katrina. The data were analyzed using a modified spatial probit regression model to evaluate the importance of each predictor variable through time. The results suggest that the two most important reopening predictors throughout all time periods were the flood depth at the business location and business size as represented by its wages in a logarithmic form. Flood depth was a significant negative predictor and had the largest marginal effects on the reopening probabilities. Smaller businesses had lower reopening probabilities than larger ones. However, the nonlinear response of business size to the reopening probability suggests that recovery aid would be most effective for smaller businesses than for larger ones. The spatial spillovers effect was a significant positive predictor but only for the first nine months. The findings show clearly that flood protection is the overarching issue for New Orleans. A flood protection plan that reduces the vulnerability and length of flooding would be the first and foremost step to mitigate the negative effects from climate-related hazards and enable speedy recovery. The findings cast doubt on the current coastal protection efforts and add to the current debate of whether coastal Louisiana will be sustainable or too costly to protect from further land loss and flooding given the threat of sea-level rise. Finally, a plan to help small businesses to return would also be an effective strategy for recovery, and the temporal window of opportunity that generates the greatest impacts would be the first 6∼9 months after the disaster. PMID:23133530

  5. Predictors of business return in New Orleans after Hurricane Katrina.

    Directory of Open Access Journals (Sweden)

    Nina S N Lam

    Full Text Available We analyzed the business reopening process in New Orleans after Hurricane Katrina, which hit the region on August 29, 2005, to better understand what the major predictors were and how their impacts changed through time. A telephone survey of businesses in New Orleans was conducted in October 2007, 26 months after Hurricane Katrina. The data were analyzed using a modified spatial probit regression model to evaluate the importance of each predictor variable through time. The results suggest that the two most important reopening predictors throughout all time periods were the flood depth at the business location and business size as represented by its wages in a logarithmic form. Flood depth was a significant negative predictor and had the largest marginal effects on the reopening probabilities. Smaller businesses had lower reopening probabilities than larger ones. However, the nonlinear response of business size to the reopening probability suggests that recovery aid would be most effective for smaller businesses than for larger ones. The spatial spillovers effect was a significant positive predictor but only for the first nine months. The findings show clearly that flood protection is the overarching issue for New Orleans. A flood protection plan that reduces the vulnerability and length of flooding would be the first and foremost step to mitigate the negative effects from climate-related hazards and enable speedy recovery. The findings cast doubt on the current coastal protection efforts and add to the current debate of whether coastal Louisiana will be sustainable or too costly to protect from further land loss and flooding given the threat of sea-level rise. Finally, a plan to help small businesses to return would also be an effective strategy for recovery, and the temporal window of opportunity that generates the greatest impacts would be the first 6∼9 months after the disaster.

  6. Predictors of business return in New Orleans after Hurricane Katrina.

    Science.gov (United States)

    Lam, Nina S N; Arenas, Helbert; Pace, Kelley; LeSage, James; Campanella, Richard

    2012-01-01

    We analyzed the business reopening process in New Orleans after Hurricane Katrina, which hit the region on August 29, 2005, to better understand what the major predictors were and how their impacts changed through time. A telephone survey of businesses in New Orleans was conducted in October 2007, 26 months after Hurricane Katrina. The data were analyzed using a modified spatial probit regression model to evaluate the importance of each predictor variable through time. The results suggest that the two most important reopening predictors throughout all time periods were the flood depth at the business location and business size as represented by its wages in a logarithmic form. Flood depth was a significant negative predictor and had the largest marginal effects on the reopening probabilities. Smaller businesses had lower reopening probabilities than larger ones. However, the nonlinear response of business size to the reopening probability suggests that recovery aid would be most effective for smaller businesses than for larger ones. The spatial spillovers effect was a significant positive predictor but only for the first nine months. The findings show clearly that flood protection is the overarching issue for New Orleans. A flood protection plan that reduces the vulnerability and length of flooding would be the first and foremost step to mitigate the negative effects from climate-related hazards and enable speedy recovery. The findings cast doubt on the current coastal protection efforts and add to the current debate of whether coastal Louisiana will be sustainable or too costly to protect from further land loss and flooding given the threat of sea-level rise. Finally, a plan to help small businesses to return would also be an effective strategy for recovery, and the temporal window of opportunity that generates the greatest impacts would be the first 6∼9 months after the disaster.

  7. Modeling plant, microorganisms, and mineral surface competition for soil nitrogen and phosphorus: Competition representations and ecological significance

    Science.gov (United States)

    Zhu, Q.; Riley, W. J.; Chambers, J. Q.; Tang, J.

    2014-12-01

    It is widely accepted that terrestrial ecosystem carbon dynamics are strongly coupled and controlled by soil nutrients status. Nutrient availability serves as an indicator of aboveground carbon productivity and ecosystem stability, especially when soils are infertile. In these conditions, plants have to outcompete microorganism and mineral surfaces to acquire nutrients required for photosynthesis, respiration, seed production, defense, etc. It is usually hypothesized that microbes are short-term winners but long-term losers in nutrient competition. Microbes quickly trap available soil nitrogen and phosphorous, thereby preventing nutrient inaccessibility through hydrological leaching and mineral surface adsorption. Over longer temporal scales, nutrients are released into the soil and become available for plant uptake. Despite its ecological significance, nutrient competition is either absent or over-simplified (e.g., assuming all consumers are equally competitive) in terrestrial biogeochemistry models. Here, we aim to test the representation of different competitive strategies and to investigate their ecological consequences with a newly developed biogeochemical model structure. The new model includes three major soil nutrients (ammonia, nitrate, and phosphate) and multiple consumers (plants, microbes, mineral surfaces, nitrifiers, and denitrifiers). We analyze predicted soil carbon, nitrogen, and phosphorus dynamics with three different competitive strategies: (1) plants compete poorly against microorganisms; (2) all consumers are equally competitive; and (3) an explicit Equilibrium Chemical Approximation (ECA; Tang and Riley (2013)) treatment. We find that very different ecosystem states are predicted when assuming different competitive structures, and that the ECA approach provides the best match with a large suite of observational constraints from tropical experimental and transect studies. We conclude that terrestrial biogeochemical models should represent a

  8. Modeling the significance of including C redistribution when determining changes in net carbon storage along a cultivated toposequence

    Science.gov (United States)

    Chirinda, Ngonidzashe; Olesen, Jørgen E.; Heckrath, Goswin; Paradelo Pérez, Marcos; Taghizadeh-Toosi, Arezoo

    2016-04-01

    Globally, soil carbon (C) reserves are second only to those in the ocean, and accounts for a significant C reservoir. In the case of arable soils, the quantity of stored C is influenced by various factors (e.g. management practices). Currently, the topography related influences on in-field soil C dynamics remain largely unknown. However, topography is known to influence a multiplicity of factors that regulate C input, storage and redistribution. To understand the patterns and untangle the complexity of soil C dynamics in arable landscapes, our study was conducted with soils from shoulderslope and footslope positions on a 7.1 ha winter wheat field in western Denmark. We first collected soil samples from shoulderslope and footslope positions with various depth intervals down to 100 cm and analyzed them for physical and chemical properties including texture and soil organic C contents. In-situ carbon dioxide (CO2) concentrations were measured at different soil profile depths at both positions for a year. Soil moisture content and temperature at 5 and 40 cm depth was measured continuously. Additionally, surface soil CO2 fluxes at shoulderslope and footslope positions were measured. We then used measurement data collected from the two landscape positions to calibrate the one-dimensional mechanistic model SOILCO2 module of the HYDRUS-1D software package and obtained soil CO2 fluxes from soil profile at two landscape positions. Furthermore, we tested whether the inclusion of vertical and lateral soil C movement improved the modeling of C dynamics in cultivated landscapes. For that, soil profile CO2 fluxes were compared with those obtained using a simple process-based soil whole profile C model, C-TOOL, which was modified to include vertical and lateral movement of C on landscape. Our results highlight the need to consider vertical and lateral soil C movement in the modeling of C dynamics in cultivated landscapes, for better qualification of net carbon storage.

  9. Clinical Predictors of Psychopathology

    Directory of Open Access Journals (Sweden)

    Jorge Caraveo Anduaga

    2010-04-01

    Full Text Available Psychiatric disorders affect up to one third of patients with non-psychiatric diseases.1-5 Nevertheless, despite the high prevalence of psychopathology in general medical patients, only between 30-50% of all cases are detected.2,6-8 Some have suggested that the difficulty in the detection and diagnosis of mental disorders among patients who seek medical attention for other reasons, lies in the lack of screening questions that might alert the physician to the possibility of a psychiatric co-morbidity.9 Such questions would identify medical patients at high risk of psychiatric problems. Previous work on clinical predictors of psychopathology have identified the following: specific physical symptoms10-11; patient report of severity of illness11; recent stress12,13; low self-perception of health status13; and age less than 50.14 Two specific studies on the detection of psychopathology in the general medical population are worth highlighting. The first, by Jackson and his research team13 updating a 2001 study evaluating a prediction model with four parameters (recent stress, severity of physical symptoms, five or more specific symptoms, self-assessment of physical condition. They found that those patients who report recent stress, have five or more physical symptoms or a low self-perception of their health state are at a higher risk of having a psychiatric disorder. The second study, by Lowe et al. published in 2003,9 examines a series of factors that could serve as indicators of psychopathology in ambulatory medical (i.e. non-psychiatric patients. After evaluating several different models they found that the combination of four of factors (taken as a group had a high sensitivity (86%, specificity (100%, positive predictive value (100%, and negative predictive value (91%. This suggests that a physician could use the combination of these four indicators to evaluate for the presence of co morbid mental disorders. These factors are: self

  10. Health Promotion Efforts as Predictors of Physical Activity in Schools: An Application of the Diffusion of Innovations Model

    Science.gov (United States)

    Glowacki, Elizabeth M.; Centeio, Erin E.; Van Dongen, Daniel J.; Carson, Russell L.; Castelli, Darla M.

    2016-01-01

    Background: Implementing a comprehensive school physical activity program (CSPAP) effectively addresses public health issues by providing opportunities for physical activity (PA). Grounded in the Diffusion of Innovations model, the purpose of this study was to identify how health promotion efforts facilitate opportunities for PA. Methods: Physical…

  11. Child ADHD Severity and Positive and Negative Parenting as Predictors of Child Social Functioning: Evaluation of Three Theoretical Models

    Science.gov (United States)

    Kaiser, Nina M.; McBurnett, Keith; Pfiffner, Linda J.

    2011-01-01

    Objective: Prior research has established links between child social functioning and both parenting and child ADHD severity; however, research examining the way that these variables work together is lacking. The current article aims to test three possible models (main effects, mediation, and moderation) by which ADHD severity and positive and…

  12. When Two Isn't Better than One: Predictors of Early Sexual Activity in Adolescence Using a Cumulative Risk Model

    Science.gov (United States)

    Price, Myeshia N.; Hyde, Janet Shibley

    2009-01-01

    This study explored factors that may be associated with early initiation of sexual activity among adolescents. Using the cumulative risk model, we hypothesized that as exposure to risk factors increases, so does the likelihood of early sexual debut. A sample of 273 (53% girls, 90% European American) adolescents was followed longitudinally from age…

  13. Optical polarization tractography revealed significant fiber disarray in skeletal muscles of a mouse model for Duchenne muscular dystrophy.

    Science.gov (United States)

    Wang, Y; Zhang, K; Wasala, N B; Duan, D; Yao, G

    2015-02-01

    Optical polarization tractography (OPT) was recently developed to visualize tissue fiber architecture with cellular-level resolution and accuracy. In this study, we explored the feasibility of using OPT to study muscle disease in the mdx4cv mouse model of Duchenne muscular dystrophy. The freshly dissected tibialis anterior muscles of mdx4cv and normal mice were imaged. A "fiber disarray index" (FDI) was developed to quantify the myofiber disorganization. In necrotic muscle regions of the mdx4cv mice, the FDI was significantly elevated and can be used to segment the 3D necrotic regions for assessing the overall muscle damage. These results demonstrated the OPT's capability for imaging microscopic fiber alternations in muscle research.

  14. Exposure to family violence and attachment styles as predictors of dating violence perpetration among men and women: a mediational model.

    Science.gov (United States)

    Lee, Mary; Reese-Weber, Marla; Kahn, Jeffrey H

    2014-01-01

    This study examined a multiple mediator model explaining how sibling perpetration and one's attachment style mediate the relation between parent-to-child victimization and dating violence perpetration. A sample of undergraduate students (n = 392 women, n = 89 men) completed measures of the aforementioned variables on an Internet survey. For men, path analyses found no mediation; parent-to-child victimization had a direct association with dating violence perpetration, no association was found between sibling perpetration and dating violence perpetration, and attachment anxiety, but not attachment avoidance, was positively associated with dating violence perpetration for men. For women, the hypothesized mediation model was supported; parent-to-child victimization had a direct association with dating violence perpetration, and sibling perpetration and attachment anxiety served as mediating variables. Attachment avoidance was not associated with dating violence perpetration for women. Implications for future research and clinical practice are discussed.

  15. Family and Cultural Predictors of Depression among Samoan American Middle and High School Students

    Science.gov (United States)

    Yeh, Christine J.; Borrero, Noah E.; Tito, Patsy

    2013-01-01

    This study investigated family intergenerational conflict and collective self-esteem as predictors of depression in a sample of 128 Samoan middle and high school students. Simultaneous regression analyses revealed that each independent variable significantly contributed to an overall model that accounted for 13% of the variance in depression.…

  16. School Climate as a Predictor of Incivility and Bullying among Public School Employees: A Multilevel Analysis

    Science.gov (United States)

    Powell, Joshua E.; Powell, Anna L.; Petrosko, Joseph M.

    2015-01-01

    We surveyed public school educators on the workplace incivility and workplace bullying they experienced and obtained their ratings of the organizational climate of the school. We used multilevel modeling to determine the effects of individual-level and school-level predictors. Ratings of school climate were significantly related to incivility and…

  17. Predictors of hepatitis B cure using gene therapy to deliver DNA cleavage enzymes: a mathematical modeling approach.

    Directory of Open Access Journals (Sweden)

    Joshua T Schiffer

    Full Text Available Most chronic viral infections are managed with small molecule therapies that inhibit replication but are not curative because non-replicating viral forms can persist despite decades of suppressive treatment. There are therefore numerous strategies in development to eradicate all non-replicating viruses from the body. We are currently engineering DNA cleavage enzymes that specifically target hepatitis B virus covalently closed circular DNA (HBV cccDNA, the episomal form of the virus that persists despite potent antiviral therapies. DNA cleavage enzymes, including homing endonucleases or meganucleases, zinc-finger nucleases (ZFNs, TAL effector nucleases (TALENs, and CRISPR-associated system 9 (Cas9 proteins, can disrupt specific regions of viral DNA. Because DNA repair is error prone, the virus can be neutralized after repeated cleavage events when a target sequence becomes mutated. DNA cleavage enzymes will be delivered as genes within viral vectors that enter hepatocytes. Here we develop mathematical models that describe the delivery and intracellular activity of DNA cleavage enzymes. Model simulations predict that high vector to target cell ratio, limited removal of delivery vectors by humoral immunity, and avid binding between enzyme and its DNA target will promote the highest level of cccDNA disruption. Development of de novo resistance to cleavage enzymes may occur if DNA cleavage and error prone repair does not render the viral episome replication incompetent: our model predicts that concurrent delivery of multiple enzymes which target different vital cccDNA regions, or sequential delivery of different enzymes, are both potentially useful strategies for avoiding multi-enzyme resistance. The underlying dynamics of cccDNA persistence are unlikely to impact the probability of cure provided that antiviral therapy is given concurrently during eradication trials. We conclude by describing experiments that can be used to validate the model, which

  18. Mouse p53-Deficient Cancer Models as Platforms for Obtaining Genomic Predictors of Human Cancer Clinical Outcomes

    Science.gov (United States)

    Dueñas, Marta; Santos, Mirentxu; Aranda, Juan F.; Bielza, Concha; Martínez-Cruz, Ana B.; Lorz, Corina; Taron, Miquel; Ciruelos, Eva M.; Rodríguez-Peralto, José L.; Martín, Miguel; Larrañaga, Pedro; Dahabreh, Jubrail; Stathopoulos, George P.; Rosell, Rafael; Paramio, Jesús M.; García-Escudero, Ramón

    2012-01-01

    Mutations in the TP53 gene are very common in human cancers, and are associated with poor clinical outcome. Transgenic mouse models lacking the Trp53 gene or that express mutant Trp53 transgenes produce tumours with malignant features in many organs. We previously showed the transcriptome of a p53-deficient mouse skin carcinoma model to be similar to those of human cancers with TP53 mutations and associated with poor clinical outcomes. This report shows that much of the 682-gene signature of this murine skin carcinoma transcriptome is also present in breast and lung cancer mouse models in which p53 is inhibited. Further, we report validated gene-expression-based tests for predicting the clinical outcome of human breast and lung adenocarcinoma. It was found that human patients with cancer could be stratified based on the similarity of their transcriptome with the mouse skin carcinoma 682-gene signature. The results also provide new targets for the treatment of p53-defective tumours. PMID:22880004

  19. Significance of stromal-1 and stromal-2 signatures and biologic prognostic model in diffuse large B-cell lymphoma

    Science.gov (United States)

    Abdou, Asmaa Gaber; Asaad, Nancy; Kandil, Mona; Shabaan, Mohammed; Shams, Asmaa

    2017-01-01

    Objective : Diffuse Large B Cell Lymphoma (DLBCL) is a heterogeneous group of tumors with different biological and clinical characteristics that have diverse clinical outcomes and response to therapy. Stromal-1 signature of tumor microenvironment of DLBCL represents extracellular matrix deposition and histiocytic infiltrate, whereas stromal-2 represents angiogenesis that could affect tumor progression. Methods : The aim of the present study is to assess the significance of stromal-1 signature using SPARC-1 and stromal-2 signature using CD31 expression and then finally to construct biologic prognostic model (BPM) in 60 cases of DLBCL via immunohistochemistry. Results : Microvessel density (PBPM showed that 42 cases (70%) were of low biologic score (0–1) and 18 cases (30%) were of high biologic score (2–3). Low BPM cases showed less probability for splenic involvement (P=0.04) and a higher rate of complete response to therapy compared with high score cases (P=0.08). Conclusions : The DLBCL microenvironment could modulate tumor progression behavior since angiogenesis and SPARC positive stromal cells promote dissemination by association with spleen involvement and capsular invasion. Biologic prognostic models, including modified BPM, which considered cell origin of DLBCL and stromal signature pathways, could determine DLBCL progression and response to therapy. PMID:28607806

  20. Attenuation of Rhes activity significantly delays the appearance of behavioral symptoms in a mouse model of Huntington's disease.

    Directory of Open Access Journals (Sweden)

    Brandon A Baiamonte

    Full Text Available Huntington's disease (HD is a neuropsychiatric disorder characterized by choreiform movement of the limbs, cognitive disability, psychosis and dementia. It is invariably associated with an abnormally long CAG expansion within the IT15 gene on human chromosome 4. Although the mutant huntingtin protein is ubiquitously expressed in HD patients, cellular degeneration occurs predominantly in neurons within the corpus striatum and cerebral cortex. The Ras homolog Rhes is expressed very selectively in the precise brain areas affected by HD. Recent in vitro work suggests that Rhes may be a co-factor with mutant huntingtin in cell death. The objective of the present study was to examine whether the inhibition of Rhes would attenuate or delay the symptoms of HD in vivo. We used a transgenic mouse model of HD crossed with Rhes knockout mice to show that the behavioral symptoms of HD are regulated by Rhes. HD(+/Rhes(-/- mice showed significantly delayed expression of HD-like symptoms in this in vivo model. Drugs that block or inhibit the actions of Rhes may be useful as the first treatments for HD.

  1. Predictors of bovine TB risk behaviour amongst meat handlers in Nigeria: a cross-sectional study guided by the health belief model.

    Directory of Open Access Journals (Sweden)

    Dupe Hambolu

    Full Text Available BACKGROUND: Bovine Tuberculosis (bTB is still a serious public health threat in developing countries. The aim of this study is to determine the social and cognitive factors predicting one of the risk behaviours amongst meat handlers in Nigeria, namely, eating Fuku Elegusi. This is the practice of eating the visibly infected parts of the lung in-order to convince customers to buy meat. The study is guided by the health belief model (HBM. METHODS: This is a cross-sectional study of 349 randomly selected meat handlers in Oko-Oba Abattoir, in Lagos State. Descriptive statistics and multiple logistic regression analysis were employed to determine perceptions and prevalence of risk behaviours and to identify predictors of eating Fuku Elegusi. RESULTS: Just over a quarter (28.1% of the study participants knew that eating Fuku Elegusi could be a source of bTB in humans. The prevalence of eating Fuku Elegusi was found to be 22%. Across all knowledge indicators related to bTB, those who don't eat Fuku Elegusi exhibited better knowledge. Strong predictors of eating Fuku Elegusi were: being male (OR: 2.39, 95% CI: 1.10 to 5.19; p = 0.03, not knowing that eating Fuku Elegusi exposes to bTB (OR: 3.72, 95% CI: 1.69 to 8.22; p = 0.001, and the perception that one cannot sell meat without tasting it (perceived barrier (OR: 1.35, 95% CI: 1.13 to 1.60; p = 0.001. Lower risk of eating Fuku Elegusi was predicted by perceived susceptibility to bTB due to another risk behaviour, namely, not washing hands after handling meat (OR: 0.78, 95% CI: 0.64 to 0.96; p-value = 0.021. Television and radio were the most acceptable media for TB prevention messages (78.5% and 75.6% respectively. CONCLUSION: Meat handlers in developing countries bear high risk to bTB owing to prevailing social and cognition determinants. Findings were largely consistent with the propositions of HBM.

  2. [Predictors of Resilience in Adolescents with Leukemia].

    Science.gov (United States)

    Hong, Sung Sil; Park, Ho Ran

    2015-08-01

    The purpose of this study was to identify the factors relating to resilience for adolescents with leukemia and examine the relationship between these factors. From June to September in 2014, 199 adolescents aged 11 to 21 participated in the study as they visited the out-patient clinic at C university hospital for follow-up care. To verify the predictors and the effects of resilience, uncertainty, symptom distress, perceived social support, spiritual perspective, defensive coping, courageous coping, hope, and self-transcendence were measured. Collected data were analyzed using hierarchical regression analysis with the SAS statistics program. The final regression model showed that courageous coping, hope, and self-transcendence were significant predictors related to resilience in adolescents with leukemia and explained for 63% of the variance in resilience. The findings indicate that adolescent-oriented intervention programs enhancing courageous coping, hope, and self-transcendence should be provide for adolescents with leukemia in order to overcome illness-related stress and support physical, psychological and social adjustment.

  3. Longitudinal Predictors of Institutionalization in Old Age.

    Directory of Open Access Journals (Sweden)

    André Hajek

    Full Text Available To investigate time-dependent predictors of institutionalization in old age using a longitudinal approach.In a representative survey of the German general population aged 75 years and older predictors of institutionalization were observed every 1.5 years over six waves. Conditional fixed-effects logistic regressions (with 201 individuals and 960 observations were performed to estimate the effects of marital status, depression, dementia, and physical impairments (mobility, hearing and visual impairments on the risk of admission to old-age home or nursing home. By exploiting the longitudinal data structure using panel econometric models, we were able to control for unobserved heterogeneity such as genetic predisposition and personality traits.The probability of institutionalization increased significantly with occurrence of widowhood, depression, dementia, as well as walking and hearing impairments. In particular, the occurrence of widowhood (OR = 78.3, dementia (OR = 154.1 and substantial mobility impairment (OR = 36.7 were strongly associated with institutionalization.Findings underline the strong influence of loss of spouse as well as dementia on institutionalization. This is relevant as the number of old people (a living alone and (b suffering from dementia is expected to increase rapidly in the next decades. Consequently, it is supposed that the demand for institutionalization among the elderly will increase considerably. Practitioners as well as policy makers should be aware of these upcoming challenges.

  4. Filtrate of Phellinus linteus Broth Culture Reduces Infarct Size Significantly in a Rat Model of Permanent Focal Cerebral Ischemia.

    Science.gov (United States)

    Suzuki, Sakiko; Kawamata, Takakazu; Okada, Yoshikazu; Kobayashi, Tomonori; Nakamura, Tomoyuki; Hori, Tomokatsu

    2011-01-01

    Phellinus linteus, a natural growing mushroom, has been known to exhibit anti-tumor, anti-inflammatory, anti-allergic and anti-oxidant effects. Aiming to exploit the neuroprotective effects of P. linteus, we evaluated its effects on infarct volume reduction in a rat model of focal cerebral ischemia. Male Sprague-Dawley rats were subjected to right middle cerebral artery occlusion. Filtrate of P. linteus broth culture (various doses), fractionated filtrate (based on molecular weight) or control medium was administered intraperitoneally to rats before or after ischemia induction. Rats were killed at 24 h after the stroke surgery. Cortical and caudoputaminal infarct volumes were determined separately using an image analysis program following staining with 2,3,5-triphenyltetrazolium chloride. Significant cortical infarct volume reductions were found in the pre-treatment groups (30 and 60 minutes before onset of cerebral ischemia) compared with the control group, showing dose dependence. Posttreatment (30 minutes after ischemic onset) also significantly reduced cortical infarct volume. Furthermore, the higher molecular weight (≥12 000) fraction of the culture filtrate was more effective compared with the lower molecular weight fraction. The present findings suggest that P. linteus may be a new promising approach for the treatment of focal cerebral ischemia, with the additional benefit of a wide therapeutic time window since significant infarct volume reduction is obtained by administration even after the ischemic event. Our finding that the higher molecular weight fraction of the P. linteus culture filtrate demonstrated more prominent effect may provide a clue to identify the neuroprotective substances and mechanisms.

  5. Filtrate of Phellinus linteus Broth Culture Reduces Infarct Size Significantly in a Rat Model of Permanent Focal Cerebral Ischemia

    Directory of Open Access Journals (Sweden)

    Sakiko Suzuki

    2011-01-01

    Full Text Available Phellinus linteus, a natural growing mushroom, has been known to exhibit anti-tumor, anti-inflammatory, anti-allergic and anti-oxidant effects. Aiming to exploit the neuroprotective effects of P. linteus, we evaluated its effects on infarct volume reduction in a rat model of focal cerebral ischemia. Male Sprague-Dawley rats were subjected to right middle cerebral artery occlusion. Filtrate of P. linteus broth culture (various doses, fractionated filtrate (based on molecular weight or control medium was administered intraperitoneally to rats before or after ischemia induction. Rats were killed at 24 h after the stroke surgery. Cortical and caudoputaminal infarct volumes were determined separately using an image analysis program following staining with 2,3,5-triphenyltetrazolium chloride. Significant cortical infarct volume reductions were found in the pre-treatment groups (30 and 60 minutes before onset of cerebral ischemia compared with the control group, showing dose dependence. Posttreatment (30 minutes after ischemic onset also significantly reduced cortical infarct volume. Furthermore, the higher molecular weight (≥12 000 fraction of the culture filtrate was more effective compared with the lower molecular weight fraction. The present findings suggest that P. linteus may be a new promising approach for the treatment of focal cerebral ischemia, with the additional benefit of a wide therapeutic time window since significant infarct volume reduction is obtained by administration even after the ischemic event. Our finding that the higher molecular weight fraction of the P. linteus culture filtrate demonstrated more prominent effect may provide a clue to identify the neuroprotective substances and mechanisms.

  6. A multi-class predictor based on a probabilistic model: application to gene expression profiling-based diagnosis of thyroid tumors

    Directory of Open Access Journals (Sweden)

    Noguchi Shinzaburo

    2006-07-01

    Full Text Available Abstract Background Although microscopic diagnosis has been playing the decisive role in cancer diagnostics, there have been cases in which it does not satisfy the clinical need. Differential diagnosis of malignant and benign thyroid tissues is one such case, and supplementary diagnosis such as that by gene expression profile is expected. Results With four thyroid tissue types, i.e., papillary carcinoma, follicular carcinoma, follicular adenoma, and normal thyroid, we performed gene expression profiling with adaptor-tagged competitive PCR, a high-throughput RT-PCR technique. For differential diagnosis, we applied a novel multi-class predictor, introducing probabilistic outputs. Multi-class predictors were constructed using various combinations of binary classifiers. The learning set included 119 samples, and the predictors were evaluated by strict leave-one-out cross validation. Trials included classical combinations, i.e., one-to-one, one-to-the-rest, but the predictor using more combination exhibited the better prediction accuracy. This characteristic was consistent with other gene expression data sets. The performance of the selected predictor was then tested with an independent set consisting of 49 samples. The resulting test prediction accuracy was 85.7%. Conclusion Molecular diagnosis of thyroid tissues is feasible by gene expression profiling, and the current level is promising towards the automatic diagnostic tool to complement the present medical procedures. A multi-class predictor with an exhaustive combination of binary classifiers could achieve a higher prediction accuracy than those with classical combinations and other predictors such as multi-class SVM. The probabilistic outputs of the predictor offer more detailed information for each sample, which enables visualization of each sample in low-dimensional classification spaces. These new concepts should help to improve the multi-class classification including that of cancer tissues.

  7. Poverty as a Predictor of 4-Year-Olds’ Executive Function: New Perspectives on Models of Differential Susceptibility

    Science.gov (United States)

    Raver, C. Cybele; Blair, Clancy; Willoughby, Michael

    2017-01-01

    In a predominantly low-income, population-based longitudinal sample of 1,259 children followed from birth, results suggest that chronic exposure to poverty and the strains of financial hardship were each uniquely predictive of young children’s performance on measures of executive functioning. Results suggest that temperament-based vulnerability serves as a statistical moderator of the link between poverty-related risk and children’s executive functioning. Implications for models of ecology and biology in shaping the development of children’s self-regulation are discussed. PMID:22563675

  8. Cytochrome P450 1B1 gene polymorphisms as predictors of anticancer drug activity: studies with in vitro models.

    Science.gov (United States)

    Laroche-Clary, Audrey; Le Morvan, Valérie; Yamori, Takao; Robert, Jacques

    2010-12-01

    Cytochrome P450 1B1 (CYP1B1) is found in tumor tissue and is suspected to play a role in oncogenesis and drug resistance. CYP1B1 gene polymorphisms have been associated with the risk of developing lung and other cancers. They may be associated with tumor response to anticancer drugs. We have determined 4 frequent nonsynonymous gene polymorphisms of CYP1B1 in the human tumor cell lines panels of the National Cancer Institute (NCI) and the Japanese Foundation for Cancer Research (JFCR): rs10012 (R48G), rs1056827 (A119S), rs1056836 (L432V), and rs1800440 (N453S). Numerous anticancer drugs have been tested against these panels that offer the opportunity to detect associations between gene polymorphisms and drug sensitivity. CYP1B1 single nucleotide polymorphisms were in marked linkage disequilibrium. The L432V allelic variants were significantly associated with reduced sensitivity to DNA-interacting anticancer agents, alkylators, camptothecins, topoisomerase II inhibitors, and some antimetabolites. For instance, in the NCI panel, cell lines homozygous for the V432 allele were globally 2-fold resistant to alkylating agents (P = 5 × 10(-10)) and 4.5-fold to camptothecins (P = 6.6 × 10(-9)) than cell lines homozygous for the L432 allele. Similar features were exhibited by the JFCR panel. Cell lines homozygous for the V432 allele were globally less sensitive to DNA-interfering drugs than cell lines having at least 1 common allele. There was no significant association between mRNA expression of CYP1B1 and CYP1B1 genotype, and no significant association between CYP1B1 mRNA expression and drug cytotoxicity. These observations open the way to clinical studies exploring the role of CYP1B1 gene polymorphisms for predicting tumor sensitivity to chemotherapy.

  9. Changes in and predictors of pain characteristics in patients with head and neck cancer undergoing radiotherapy.

    Science.gov (United States)

    Astrup, Guro Lindviksmoen; Rustøen, Tone; Miaskowski, Christine; Paul, Steven M; Bjordal, Kristin

    2015-05-01

    Pain is a common symptom in patients with head and neck cancer (HNC) that is associated with significant decrements in physical and psychological functioning. Only 4 studies have evaluated for changes in and predictors of different pain characteristics in these patients. In this longitudinal study of patients with HNC, changes in pain intensity (i.e., average pain, worst pain), pain interference with function, and pain relief were evaluated from the initiation of radiotherapy and through the following 6 months. Hierarchical linear modeling was used to evaluate for changes over time in these 4 pain characteristics, as well as to identify predictors of interindividual variability in each characteristic. Overall, pain intensity and interference with function scores were in the mild-to-moderate range, while pain relief scores were in the moderate range. The occurrence of pain, as well as scores for each pain characteristic, increased from the initiation to the completion of radiotherapy, followed by a gradual decrease to near pretreatment levels at 6 months. However, interindividual variability existed in patients' ratings of each pain characteristic. Predictors of more severe pain characteristic scores were more comorbidities, worse physical functioning, not having surgery before radiotherapy, difficulty swallowing, mouth sores, sleep disturbance, fatigue, more energy, and less social support. Patients with more depressive symptoms had better pain relief. Although some of the predictors cannot be modified (e.g., rrence of surgery), other predictors (e.g., symptoms) can be treated. Therefore, information about these predictors may result in decreased pain in patients with HNC.

  10. Greater expectations: using hierarchical linear modeling to examine expectancy for treatment outcome as a predictor of treatment response.

    Science.gov (United States)

    Price, Matthew; Anderson, Page; Henrich, Christopher C; Rothbaum, Barbara Olasov

    2008-12-01

    A client's expectation that therapy will be beneficial has long been considered an important factor contributing to therapeutic outcomes, but recent empirical work examining this hypothesis has primarily yielded null findings. The present study examined the contribution of expectancies for treatment outcome to actual treatment outcome from the start of therapy through 12-month follow-up in a clinical sample of individuals (n=72) treated for fear of flying with either in vivo exposure or virtual reality exposure therapy. Using a piecewise hierarchical linear model, outcome expectancy predicted treatment gains made during therapy but not during follow-up. Compared to lower levels, higher expectations for treatment outcome yielded stronger rates of symptom reduction from the beginning to the end of treatment on 2 standardized self-report questionnaires on fear of flying. The analytic approach of the current study is one potential reason that findings contrast with prior literature. The advantages of using hierarchical linear modeling to assess interindividual differences in longitudinal data are discussed.

  11. Childhood body mass index trajectories: modeling, characterizing, pairwise correlations and socio-demographic predictors of trajectory characteristics

    Directory of Open Access Journals (Sweden)

    Wen Xiaozhong

    2012-03-01

    Full Text Available Abstract Background Modeling childhood body mass index (BMI trajectories, versus estimating change in BMI between specific ages, may improve prediction of later body-size-related outcomes. Prior studies of BMI trajectories are limited by restricted age periods and insufficient use of trajectory information. Methods Among 3,289 children seen at 81,550 pediatric well-child visits from infancy to 18 years between 1980 and 2008, we fit individual BMI trajectories using mixed effect models with fractional polynomial functions. From each child's fitted trajectory, we estimated age and BMI at infancy peak and adiposity rebound, and velocity and area under curve between 1 week, infancy peak, adiposity rebound, and 18 years. Results Among boys, mean (SD ages at infancy BMI peak and adiposity rebound were 7.2 (0.9 and 49.2 (11.9 months, respectively. Among girls, mean (SD ages at infancy BMI peak and adiposity rebound were 7.4 (1.1 and 46.8 (11.0 months, respectively. Ages at infancy peak and adiposity rebound were weakly inversely correlated (r = -0.09. BMI at infancy peak and adiposity rebound were positively correlated (r = 0.76. Blacks had earlier adiposity rebound and greater velocity from adiposity rebound to 18 years of age than whites. Higher birth weight z-score predicted earlier adiposity rebound and higher BMI at infancy peak and adiposity rebound. BMI trajectories did not differ by birth year or type of health insurance, after adjusting for other socio-demographics and birth weight z-score. Conclusions Childhood BMI trajectory characteristics are informative in describing childhood body mass changes and can be estimated conveniently. Future research should evaluate associations of these novel BMI trajectory characteristics with adult outcomes.

  12. A Cross-sectional Study Assessing Predictors of Essential Medicines Prescribing Behavior Based on Information-motivation-behavioral Skills Model among County Hospitals in Anhui, China

    Institute of Scientific and Technical Information of China (English)

    Yun-Wu Zhao; Jing-Ya Wu; Heng Wang; Nian-Nian Li; Cheng Bian; Shu-Man Xu; Peng Li

    2015-01-01

    Background:The self-consciousness and practicality of preferentially prescribed essential medicines (EMs) are not high enough in county hospitals.The purposes of this study were to use the information-motivation-behavioral skills (IMB) model to identify the predictors of essential medicines prescribing behavior (EMPB) among doctors and to examine the association between demographic variables,IMB,and EMPB.Methods:A cross-sectional study was carried out to assess predictive relationships among demographic variables and IMB model variables using an anonymous questionnaire administered in nine county hospitals of Anhui province.A structural equation model was constructed for the IMB model to test the instruments using analysis of moment structures 17.0.Results:A total of 732 participants completed the survey.The average age of the participants was 37.7 ± 8.9 years old (range:22-67 years old).The correct rate of information was 90.64%.The average scores of the motivation and behavioral skills were 45.46 ± 7.34 (hundred mark system:75.77) and 19.92 ± 3.44 (hundred mark system:79.68),respectively.Approximately half(50.8%) of respondents reported that the proportion of EM prescription was below 60%.The final revised model indicated a good fit to the data (x2/df=4.146,goodness of fit index =0.948,comparative fit index =0.938,root mean square error of approximation =0.066).More work experience (β =0.153,P < 0.001) and behavioral skills (β =0.449,P < 0.001) predicted more EMPB.Higher income predicted less information (β =-0.197,P < 0.001) and motivation (β =-0.204,P < 0.001).Behavioral skills were positively predicted by information (β =0.135,P < 0.001) and motivation (β =0.742,P < 0.001).Conclusion:The present study predicted some factors of EMPB,and specified the relationships among the model variables.The utilization rate of EM was not high enough.Motivation and behavior skills were crucial factors affecting EMPB.The influence of demographic

  13. Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models.

    Science.gov (United States)

    Kickingereder, Philipp; Burth, Sina; Wick, Antje; Götz, Michael; Eidel, Oliver; Schlemmer, Heinz-Peter; Maier-Hein, Klaus H; Wick, Wolfgang; Bendszus, Martin; Radbruch, Alexander; Bonekamp, David

    2016-09-01

    Purpose To evaluate whether radiomic feature-based magnetic resonance (MR) imaging signatures allow prediction of survival and stratification of patients with newly diagnosed glioblastoma with improved accuracy compared with that of established clinical and radiologic risk models. Materials and Methods Retrospective evaluation of data was approved by the local ethics committee and informed consent was waived. A total of 119 patients (allocated in a 2:1 ratio to a discovery [n = 79] or validation [n = 40] set) with newly diagnosed glioblastoma were subjected to radiomic feature extraction (12 190 features extracted, including first-order, volume, shape, and texture features) from the multiparametric (contrast material-enhanced T1-weighted and fluid-attenuated inversion-recovery imaging sequences) and multiregional (contrast-enhanced and unenhanced) tumor volumes. Radiomic features of patients in the discovery set were subjected to a supervised principal component (SPC) analysis to predict progression-free survival (PFS) and overall survival (OS) and were validated in the validation set. The performance of a Cox proportional hazards model with the SPC analysis predictor was assessed with C index and integrated Brier scores (IBS, lower scores indicating higher accuracy) and compared with Cox models based on clinical (age and Karnofsky performance score) and radiologic (Gaussian normalized relative cerebral blood volume and apparent diffusion coefficient) parameters. Results SPC analysis allowed stratification based on 11 features of patients in the discovery set into a low- or high-risk group for PFS (hazard ratio [HR], 2.43; P = .002) and OS (HR, 4.33; P radiologic (OS: IBS, 0.175; C index, 0.603; PFS: IBS, 0.149; C index, 0.554) and clinical risk models (OS: IBS, 0.161, C index, 0.640; PFS: IBS, 0.139; C index, 0.599). The performance of the SPC analysis model was further improved when combined with clinical data (OS: IBS, 0.142; C index, 0.696; PFS: IBS, 0.132; C

  14. GeoSciML v3.0 - a significant upgrade of the CGI-IUGS geoscience data model

    Science.gov (United States)

    Raymond, O.; Duclaux, G.; Boisvert, E.; Cipolloni, C.; Cox, S.; Laxton, J.; Letourneau, F.; Richard, S.; Ritchie, A.; Sen, M.; Serrano, J.-J.; Simons, B.; Vuollo, J.

    2012-04-01

    GeoSciML version 3.0 (http://www.geosciml.org), released in late 2011, is the latest version of the CGI-IUGS* Interoperability Working Group geoscience data interchange standard. The new version is a significant upgrade and refactoring of GeoSciML v2 which was released in 2008. GeoSciML v3 has already been adopted by several major international interoperability initiatives, including OneGeology, the EU INSPIRE program, and the US Geoscience Information Network, as their standard data exchange format for geoscience data. GeoSciML v3 makes use of recently upgraded versions of several Open Geospatial Consortium (OGC) and ISO data transfer standards, including GML v3.2, SWE Common v2.0, and Observations and Measurements v2 (ISO 19156). The GeoSciML v3 data model has been refactored from a single large application schema with many packages, into a number of smaller, but related, application schema modules with individual namespaces. This refactoring allows the use and future development of modules of GeoSciML (eg; GeologicUnit, GeologicStructure, GeologicAge, Borehole) in smaller, more manageable units. As a result of this refactoring and the integration with new OGC and ISO standards, GeoSciML v3 is not backwardly compatible with previous GeoSciML versions. The scope of GeoSciML has been extended in version 3.0 to include new models for geomorphological data (a Geomorphology application schema), and for geological specimens, geochronological interpretations, and metadata for geochemical and geochronological analyses (a LaboratoryAnalysis-Specimen application schema). In addition, there is better support for borehole data, and the PhysicalProperties model now supports a wider range of petrophysical measurements. The previously used CGI_Value data type has been superseded in favour of externally governed data types provided by OGC's SWE Common v2 and GML v3.2 data standards. The GeoSciML v3 release includes worked examples of best practice in delivering geochemical

  15. Psychosocial Predictors of Compliance with Speed Limits and Alcohol Limits by Spanish Drivers: Modeling Compliance of Traffic Rules

    Directory of Open Access Journals (Sweden)

    Rebeca Bautista

    2015-09-01

    Full Text Available To prevent dangerous driving behaviors, the Spanish government has implemented public policies focused primarily on increasing the harshness of sanctions for violations of traffic laws. However, empirical evidence has demonstrated that other factors, such as social norms and one’s own value system, have an impact on people’s motivation to obey the law. A telephone survey was administered to a random sample of 570 Spanish drivers in order to determine the role played by each of these factors in compliance with two of the most flouted traffic rules. Logistic regression of the data allowed for the construction of models and arrive at the following conclusions: (1 social influence exerted by the reference group is a determining factor in compliance with both traffic laws; (2 legitimacy factors play an important role in complying with alcohol limits; and (3 variables from the deterrence approach only influenced compliance with speed limits, and then only moderately. The results of the present study suggest a need for a review of current public policy approaches for the prevention of dangerous driving behaviors.

  16. A study on the predictors of teenage pregnancy in Japan.

    Science.gov (United States)

    Hayashi, K; Ogino, H; Katabami, J

    1985-01-01

    In this study of teenage birth and abortion in 46 prefectures in Japan, age specific birth rates and percentage of age specific abortion rates constructed specifically for the study constituted the dependent variables. Data from officially published materials in 1970, 1975, and 1980 provided the independent socioeconomic and educational variables for the analysis. The relationship between birth rates or percentage changes of abortion and these independent variables were explored through multivariate regression analysis and path analysis. Demographic and educational variables, particularly the divorce rate, total fertility, percent nuclear family, and the middle level educational attainment in the prefectures, were found to be highly significant predictors of teenage birth and aportion. The study also proposed models to show the relationship among predictors by carrying out the path analysis. The results confirmed that the divorce rate and the middle level educational attainment had the strongest predicting power.

  17. Parenting Style and Behavior as Longitudinal Predictors of Adolescent Alcohol Use.

    Science.gov (United States)

    Minaie, Matin Ghayour; Hui, Ka Kit; Leung, Rachel K; Toumbourou, John W; King, Ross M

    2015-09-01

    Adolescent alcohol use is a serious problem in Australia and other nations. Longitudinal data on family predictors are valuable to guide parental education efforts. The present study tested Baumrind's proposal that parenting styles are direct predictors of adolescent alcohol use. Latent class modeling was used to investigate adolescent perceptions of parenting styles and multivariate regression to examine their predictive effect on the development of adolescent alcohol use. The data set comprised 2,081 secondary school students (55.9% female) from metropolitan Melbourne, Australia, who completed three waves of annual longitudinal data starting in 2004. Baumrind's parenting styles were significant predictors in unadjusted analyses, but these effects were not maintained in multivariate models that also included parenting behavior dimensions. Family influences on the development of adolescent alcohol use appear to operate more directly through specific family management behaviors rather than through more global parenting styles.

  18. Beyond depression: Predictors of self-reported cognitive function in adults living with MS.

    Science.gov (United States)

    Beier, Meghan; Amtmann, Dagmar; Ehde, Dawn M

    2015-08-01

    To investigate the association between self-reported cognition and demographic/psychosocial variables in individuals with a self-reported diagnosis of multiple sclerosis (MS). Secondary longitudinal analysis of mailed self-report surveys over a period of 2 years. Community. 407 community-dwelling individuals from the Pacific Northwest with a self-reported diagnosis of MS. Subjective general cognitive concerns and subjective executive difficulties as measured by the Neuro-QOL Applied Cognition-Executive Function-Short Form (SF) and the Applied Cognition-General Concerns-SF. Univariate and multiple linear regression analyses were used to identify statistically significant longitudinal predictors of perceived cognitive difficulties 2 years later. Fatigue and anxiety were statistically significant predictors of general cognitive concerns. Fatigue and perceived stress were statistically significant predictors of perceived executive difficulties. Fatigue was the strongest predictor in both models. In MS, perceived cognitive impairment is frequently linked to depression without consideration of other possible contributors. This study suggests that in people with MS, fatigue is a stronger predictor of self-reported cognitive function 2 years later than depression. (c) 2015 APA, all rights reserved).

  19. Orthotopic bladder substitution in men revisited: identification of continence predictors.

    Science.gov (United States)

    Koraitim, M M; Atta, M A; Foda, M K

    2006-11-01

    We determined the impact of the functional characteristics of the neobladder and urethral sphincter on continence results, and determined the most significant predictors of continence. A total of 88 male patients 29 to 70 years old underwent orthotopic bladder substitution with tubularized ileocecal segment (40) and detubularized sigmoid (25) or ileum (23). Uroflowmetry, cystometry and urethral pressure profilometry were performed at 13 to 36 months (mean 19) postoperatively. The correlation between urinary continence and 28 urodynamic variables was assessed. Parameters that correlated significantly with continence were entered into a multivariate analysis using a logistic regression model to determine the most significant predictors of continence. Maximum urethral closure pressure was the only parameter that showed a statistically significant correlation with diurnal continence. Nocturnal continence had not only a statistically significant positive correlation with maximum urethral closure pressure, but also statistically significant negative correlations with maximum contraction amplitude, and baseline pressure at mid and maximum capacity. Three of these 4 parameters, including maximum urethral closure pressure, maximum contraction amplitude and baseline pressure at mid capacity, proved to be significant predictors of continence on multivariate analysis. While daytime continence is determined by maximum urethral closure pressure, during the night it is the net result of 2 forces that have about equal influence but in opposite directions, that is maximum urethral closure pressure vs maximum contraction amplitude plus baseline pressure at mid capacity. Two equations were derived from the logistic regression model to predict the probability of continence after orthotopic bladder substitution, including Z1 (diurnal) = 0.605 + 0.0085 maximum urethral closure pressure and Z2 (nocturnal) = 0.841 + 0.01 [maximum urethral closure pressure - (maximum contraction amplitude

  20. Human leukocyte antigen class II transgenic mouse model unmasks the significant extrahepatic pathology in toxic shock syndrome.

    Science.gov (United States)

    Tilahun, Ashenafi Y; Marietta, Eric V; Wu, Tsung-Teh; Patel, Robin; David, Chella S; Rajagopalan, Govindarajan

    2011-06-01

    Among the exotoxins produced by Staphylococcus aureus and Streptococcus pyogenes, the superantigens (SAgs) are the most potent T-cell activators known to date. SAgs are implicated in several serious diseases including toxic shock syndrome (TSS), Kawasaki disease, and sepsis. However, the immunopathogenesis of TSS and other diseases involving SAgs are still not completely understood. The commonly used conventional laboratory mouse strains do not respond robustly to SAgs in vivo. Therefore, they must be artificially rendered susceptible to TSS by using sensitizing agents such as d-galactosamine (d-galN), which skews the disease exclusively to the liver and, hence, is not representative of the disease in humans. SAg-induced TSS was characterized using transgenic mice expressing HLA class II molecules that are extremely susceptible to TSS without d-galN. HLA-DR3 transgenic mice recapitulated TSS in humans with extensive multiple-organ inflammation affecting the lung, liver, kidneys, heart, and small intestines. Heavy infiltration with T lymphocytes (both CD4(+) and CD8+), neutrophils, and macrophages was noted. In particular, the pathologic changes in the small intestines were extensive and accompanied by significantly altered absorptive functions of the enterocytes. In contrast to massive liver failure alone in the d-galN sensitization model of TSS, findings of the present study suggest that gut dysfunction might be a key pathogenic event that leads to high morbidity and mortality in humans with TSS.

  1. Organization as Information Processing Systems. Toward a Model of the Research Factors Associated with Significant Research Outcomes.

    Science.gov (United States)

    1986-04-01

    and %- , during research projects that were related to research outcomes. The Ambidextrous model, which includes both organic and mechanistic research...to make choices with greater li4kelihood for innovative outcomes. p A potential side benefit from better knowledge of the research process * maY...aspect of the research process. The models are referred to respectively as the Davis model, the Antecedents model, and the Ambidextrous model. These

  2. Predictors of reintubation in critically ill patients.

    Science.gov (United States)

    Miu, Timothy; Joffe, Aaron M; Yanez, N David; Khandelwal, Nita; Dagal, Armagan Hc; Deem, Steven; Treggiari, Miriam M

    2014-02-01

    Assessment of a patient's readiness for removal of the endotracheal tube in the ICU is based on respiratory, airway, and neurological measures. However, nearly 20% of patients require reintubation. We created a prediction model for the need for reintubation, which incorporates variables importantly contributing to extubation failure. This was a cohort study of 2,007 endotracheally intubated subjects who required ICU admission at a tertiary care center. Data collection included demographic, hemodynamic, respiratory, and neurological variables preceding extubation. Data were compared between subjects extubated successfully and those who required reintubation, using bivariate logistic regression models, with the binary outcome reintubation and the baseline characteristics as predictors. Multivariable logistic regression analysis with robust variance was used to build the prediction model. Of the 2,007 subjects analyzed, 376 (19%) required reintubation. In the bivariate analysis, admission Simplified Acute Physiology Score II, minute ventilation, breathing frequency, oxygenation, number of prior SBTs, rapid shallow breathing index, airway-secretions suctioning frequency and quantity, heart rate, and diastolic blood pressure differed significantly between the extubation success and failure groups. In the multivariable analysis, higher Simplified Acute Physiology Score II and suctioning frequency were associated with failed extubation. The area under the receiver operating characteristic curve was 0.68 for failure at any time, and 0.71 for failure within 24 hours. However, prior failed SBT, minute ventilation, and diastolic blood pressure were additional independent predictors of failure at any time, whereas oxygenation predicted extubation failure within 24 hours. A small number of independent variables explains a substantial portion of the variability of extubation failure, and can help identify patients at high risk of needing reintubation. These characteristics

  3. Gender-specific predictors of posttraumatic stress disorder in adolescents

    DEFF Research Database (Denmark)

    Donbaek, Dagmar Feddern; Elklit, Ask

    2015-01-01

    that drug abuse and avoidant attachment to best friends were significant predictors of PTSD severity in male adolescents, whereas alcohol abuse and the absence of posttraumatic social support from parents remained significant predictors for female adolescents. The results support the influence of gender......-specific substance abuse patterns and dysfunctional interpersonal relationships on the PTSD severity of traumatized adolescents....

  4. Prediction error variance and expected response to selection, when selection is based on the best predictor - for Gaussian and threshold characters, traits following a Poisson mixed model and survival traits

    DEFF Research Database (Denmark)

    Andersen, Anders Holst; Korsgaard, Inge Riis; Jensen, Just

    2002-01-01

    In this paper, we consider selection based on the best predictor of animal additive genetic values in Gaussian linear mixed models, threshold models, Poisson mixed models, and log normal frailty models for survival data (including models with time-dependent covariates with associated fixed...... or random effects). In the different models, expressions are given (when these can be found - otherwise unbiased estimates are given) for prediction error variance, accuracy of selection and expected response to selection on the additive genetic scale and on the observed scale. The expressions given for non...... Gaussian traits are generalisations of the well-known formulas for Gaussian traits - and reflect, for Poisson mixed models and frailty models for survival data, the hierarchal structure of the models. In general the ratio of the additive genetic variance to the total variance in the Gaussian part...

  5. A non-traditional model of the metabolic syndrome: the adaptive significance of insulin resistance in fasting-adapted seals

    Directory of Open Access Journals (Sweden)

    Dorian S Houser

    2013-11-01

    Full Text Available Insulin resistance in modern society is perceived as a pathological consequence of excess energy consumption and reduced physical activity. Its presence in relation to the development of cardiovascular risk factors has been termed the metabolic syndrome, which produces increased mortality and morbidity and which is rapidly increasing in human populations. Ironically, insulin resistance likely evolved to assist animals during food shortages by increasing the availability of endogenous lipid for catabolism while protecting protein from use in gluconeogenesis and eventual oxidation. Some species that incorporate fasting as a predictable component of their life history demonstrate physiological traits similar to the metabolic syndrome during prolonged fasts. One such species is the northern elephant seal (Mirounga angustirostris, which fasts from food and water for periods of up to three months. During this time, ~90% of the seals metabolic demands are met through fat oxidation and circulating non-esterified fatty acids are high (0.7-3.2 mM. All life history stages of elephant seal studied to date demonstrate insulin resistance and fasting hyperglycemia as well as variations in hormones and adipocytokines that reflect the metabolic syndrome to some degree. Elephant seals demonstrate some intriguing adaptations with the potential for medical advancement; for example, ketosis is negligible despite significant and prolonged fatty acid oxidation and investigation of this feature might provide insight into the treatment of diabetic ketoacidosis. The parallels to the metabolic syndrome are likely reflected to varying degrees in other marine mammals, most of which evolved on diets high in lipid and protein content but essentially devoid of carbohydrate. Utilization of these natural models of insulin resistance may further our understanding of the pathophysiology of the metabolic syndrome in humans and better assist the development of preventative measures

  6. 基于加权损失函数下广义指数预报因子模型的汇率预测%Foreign Exchange Rates Prediction Based on Generalized Exponential Predictor Models with Weighted Loss Function

    Institute of Scientific and Technical Information of China (English)

    尹伟; 严威; 缪柏其

    2012-01-01

    The genenralized exponential predictor models for exchange rate forecasting based on weighted loss function is proposed.This method construct some exponential predictors through different smoothing parameters firstly, and then the weighted loss function based on absolute loss and square loss was proposed to select vaxiable,under which we combine exponential predictors to construct genneralized predictor model.At last compare with some existing methods,the models we proposed improves forecast precision.%本文提出在加权损失函数下构建汇率预测的广义指数预报因子模型。该方法首先选取有限个不同滑动参数构造指数预报因子,同时基于绝对值损失和平方损失的提出加权损失函数作为变量筛选的准则,然后在该准则下将指数预报因子进行线性组合,建立汇率预报的广义指数预报因子模型。本文最后用英镑/美元单周汇率数据与文献中的一些已有方法做比较,实证分析表明本文提出的方法在汇率预测效果上有较大改进。

  7. Predictors of Hospitalization Among Newly Admitted Skilled Nursing Facility Residents: Rethinking the Role of Functional Decline

    Directory of Open Access Journals (Sweden)

    Sun J. Kim

    2014-05-01

    Full Text Available Purpose: Hospital transfer from a skilled nursing facility (SNF is costly, and many are potentially preventable. This study examines: 1 whether functional decline is a predictor of hospital transfer, and 2 the magnitude of relationships between predictors (functional impairment and chronic medical illness and hospital transfer from SNFs. Methods: We used Minimum Data Set (MDS Version 2.0 in the state of Michigan between 2007 and 2009. In total, 196,662 new SNF admissions were observed. Multilevel generalized estimating equations and regression models were performed for each functional and clinical domain while adjusting for demographic variables and change in activities of daily living (ADL. Results: 65% of recently admitted SNF residents experienced functional decline after SNF admission, and 58% were readmitted to a hospital. Residents who needed extensive assistance or were completely dependent in their functional domains had pressure ulcers, deteriorated mood or lower cognitive performance scale scores. These residents experienced higher chances of hospital transfer. However, a deteriorated ADL played a significant role in all multivariate models, indicating that a decline in ADL is a stronger predictor of hospital transfer than other functional or clinical predictors. Conclusion: Although all functional impairments and chronic medical illness can be associated with hospital transfer, functional decline may be the most important predictor of hospital transfer in patients newly admitted to an SNF.

  8. Analysis of the Modified Smith Predictor

    Directory of Open Access Journals (Sweden)

    Jorge A. Herrera-Cuartas

    2013-11-01

    Full Text Available In this paper an analysis about the modified Smith predictor, is presented. The modified Smith predictor is a scheme used to control stable, unstable and integrative systems. The closed loop equation is developed and analyzed. Additionally, various test are made to verify the behavior of the control scheme. Specify, three test are made. First, it is verify the behavior of the scheme to deal with an uncertainty in the delay model. Second, it is verify the behavior in the face of uncertainties in the parameter of the rational model

  9. On the significance of the noise model for the performance of a linear MPC in closed-loop operation

    DEFF Research Database (Denmark)

    Hagdrup, Morten; Boiroux, Dimitri; Mahmoudi, Zeinab

    2016-01-01

    models typically means less parameters to identify. Systematic tuning of such controllers is discussed. Simulation studies are conducted for linear time-invariant systems showing that choosing a noise model of low order is beneficial for closed-loop performance. (C) 2016, IFAC (International Federation...... of Automatic Control) Hosting by Elsevier Ltd. All rights reserved....

  10. Why Do Students Use Mobile Technology for Social Purposes during Class? Modeling Teacher Credibility, Learner Empowerment, and Online Communication Attitude as Predictors

    Science.gov (United States)

    Ledbetter, Andrew M.; Finn, Amber N.

    2016-01-01

    Following research indicating prevalent and deleterious use of social communication technology in college classrooms, this study investigated teacher credibility, learner empowerment, and online communication attitude as predictors of such use. The sample included 379 participants who completed an online survey about a college course. Results…

  11. A Preliminary Study of Perfectionism and Loneliness as Predictors of Depressive and Anxious Symptoms in Latinas: A Top-Down Test of a Model

    Science.gov (United States)

    Chang, Edward C.; Hirsch, Jameson K.; Sanna, Lawrence J.; Jeglic, Elizabeth L.; Fabian, Cathryn G.

    2011-01-01

    In the present study, we used a top-down approach to examine perfectionism and loneliness as additive sociocognitive predictors of depressive and anxious symptoms in a sample of 121 Latina college students. Consistent with expectations, we found perfectionism and loneliness to be associated with both depressive and anxious symptoms. In addition,…

  12. Predictors and outcomes of transfers from peritoneal dialysis to hemodialysis.

    Science.gov (United States)

    Lan, Patrick G; Clayton, Philip A; Saunders, John; Polkinghorne, Kevan R; Snelling, Paul L

    2015-01-01

    Peritoneal dialysis (PD) patients are commonly required to transfer to hemodialysis (HD), however the literature describing the outcomes of such transfers is limited. The aim of our study was to describe the predictors of these transfers and their outcomes according to vascular access at the time of transfer. A retrospective cohort study using registry data of all adult patients commencing PD as their initial renal replacement therapy in Australia or New Zealand between 2004 - 2010 was performed. Follow-up was until 31 December 2010. Logistic regression models were constructed to determine possible predictors of transfer within both 6 and 12 months of PD commencement. Cox analysis and competing risks regression were used to determine the predictors of survival and transplantation post-transfer. The analysis included 4,781 incident PD patients, of whom 1,699 transferred to HD during the study period. Logistic models did not identify any clinically useful predictors of transfer within 6 or 12 months (c-statistics 0.54 and 0.55 respectively). 67% of patients commenced HD with a central venous catheter (CVC). CVC use at transfer was associated with increased mortality (hazard ratio 1.37, 95% confidence interval (CI) 1.11 - 1.68, p = 0.003) and a borderline significant reduction in the incidence of transplantation (subhazard ratio 0.76, 95% CI 0.58 - 1.00, p = 0.05). It is difficult to predict the transfer to HD for incident PD patients. PD patients who commence HD with a CVC have a higher risk of mortality and a lower likelihood of undergoing renal transplantation. Copyright © 2015 International Society for Peritoneal Dialysis.

  13. Sufficient dimension reduction for longitudinally measured predictors.

    Science.gov (United States)

    Pfeiffer, Ruth M; Forzani, Liliana; Bura, Efstathia

    2012-09-28

    We propose a method to combine several predictors (markers) that are measured repeatedly over time into a composite marker score without assuming a model and only requiring a mild condition on the predictor distribution. Assuming that the first and second moments of the predictors can be decomposed into a time and a marker component via a Kronecker product structure that accommodates the longitudinal nature of the predictors, we develop first-moment sufficient dimension reduction techniques to replace the original markers with linear transformations that contain sufficient information for the regression of the predictors on the outcome. These linear combinations can then be combined into a score that has better predictive performance than a score built under a general model that ignores the longitudinal structure of the data. Our methods can be applied to either continuous or categorical outcome measures. In simulations, we focus on binary outcomes and show that our method outperforms existing alternatives by using the AUC, the area under the receiver-operator characteristics (ROC) curve, as a summary measure of the discriminatory ability of a single continuous diagnostic marker for binary disease outcomes.

  14. Patient expectation is the most important predictor of discharge destination after primary total joint arthroplasty.

    Science.gov (United States)

    Halawi, Mohamad J; Vovos, Tyler J; Green, Cindy L; Wellman, Samuel S; Attarian, David E; Bolognesi, Michael P

    2015-04-01

    The purpose of this study was to identify preoperative predictors of discharge destination after total joint arthroplasty. A retrospective study of three hundred and seventy-two consecutive patients who underwent primary total hip and knee arthroplasty was performed. The mean length of stay was 2.9 days and 29.0% of patients were discharged to extended care facilities. Age, caregiver support at home, and patient expectation of discharge destination were the only significant multivariable predictors regardless of the type of surgery (total knee versus total hip arthroplasty). Among those variables, patient expectation was the most important predictor (P < 0.001; OR 169.53). The study was adequately powered to analyze the variables in the multivariable logistic regression model, which had a high concordance index of 0.969.

  15. Individual, team, and coach predictors of players' likelihood to aggress in youth soccer.

    Science.gov (United States)

    Chow, Graig M; Murray, Kristen E; Feltz, Deborah L

    2009-08-01

    The purpose of this study was to examine personal and socioenvironmental factors of players' likelihood to aggress. Participants were youth soccer players (N = 258) and their coaches (N = 23) from high school and club teams. Players completed the Judgments About Moral Behavior in Youth Sports Questionnaire (JAMBYSQ; Stephens, Bredemeier, & Shields, 1997), which assessed athletes' stage of moral development, team norm for aggression, and self-described likelihood to aggress against an opponent. Coaches were administered the Coaching Efficacy Scale (CES; Feltz, Chase, Moritz, & Sullivan, 1999). Using multilevel modeling, results demonstrated that the team norm for aggression at the athlete and team level were significant predictors of athletes' self likelihood to aggress scores. Further, coaches' game strategy efficacy emerged as a positive predictor of their players' self-described likelihood to aggress. The findings contribute to previous research examining the socioenvironmental predictors of athletic aggression in youth sport by demonstrating the importance of coaching efficacy beliefs.

  16. Predictors of human rotation.

    Science.gov (United States)

    Stochl, Jan; Croudace, Tim

    2013-01-01

    Why some humans prefer to rotate clockwise rather than anticlockwise is not well understood. This study aims to identify the predictors of the preferred rotation direction in humans. The variables hypothesised to influence rotation preference include handedness, footedness, sex, brain hemisphere lateralisation, and the Coriolis effect (which results from geospatial location on the Earth). An online questionnaire allowed us to analyse data from 1526 respondents in 97 countries. Factor analysis showed that the direction of rotation should be studied separately for local and global movements. Handedness, footedness, and the item hypothesised to measure brain hemisphere lateralisation are predictors of rotation direction for both global and local movements. Sex is a predictor of the direction of global rotation movements but not local ones, and both sexes tend to rotate clockwise. Geospatial location does not predict the preferred direction of rotation. Our study confirms previous findings concerning the influence of handedness, footedness, and sex on human rotation; our study also provides new insight into the underlying structure of human rotation movements and excludes the Coriolis effect as a predictor of rotation.

  17. Predicting clinically significant changes in motor and functional outcomes after robot-assisted stroke rehabilitation.

    Science.gov (United States)

    Hsieh, Yu-wei; Lin, Keh-chung; Wu, Ching-yi; Lien, Hen-yu; Chen, Jean-lon; Chen, Chih-chi; Chang, Wei-han

    2014-02-01

    To investigate the predictors of minimal clinically important changes on outcome measures after robot-assisted therapy (RT). Observational cohort study. Outpatient rehabilitation clinics. A cohort of outpatients with stroke (N=55). Patients with stroke received RT for 90 to 105min/d, 5d/wk, for 4 weeks. Outcome measures, including the Fugl-Meyer Assessment (FMA) and Motor Activity Log (MAL), were measured before and after the intervention. Potential predictors include age, sex, side of lesion, time since stroke onset, finger extension, Box and Block Test (BBT) score, and FMA distal score. Statistical analysis showed that the BBT score (odds ratio[OR]=1.06; P=.04) was a significant predictor of clinically important changes in the FMA. Being a woman (OR=3.9; P=.05) and BBT score (OR=1.07; P=.02) were the 2 significant predictors of clinically significant changes in the MAL amount of use subscale. The BBT score was the significant predictor of an increased probability of achieving clinically important changes in the MAL quality of movement subscale (OR=1.07; P=.02). The R(2) values for the 3 logistic regression models were low (.114-.272). The results revealed that patients with stroke who had greater manual dexterity measured by the BBT appear to have a higher probability of achieving clinically significant motor and functional outcomes after RT. Further studies are needed to evaluate other potential predictors to improve the models and validate the findings. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  18. Ecological and personal predictors of science achievement in an urban center

    Science.gov (United States)

    Guidubaldi, John Michael

    This study sought to examine selected personal and environmental factors that predict urban students' achievement test scores on the science subject area of the Ohio standardized test. Variables examined were in the general categories of teacher/classroom, student, and parent/home. It assumed that these clusters might add independent variance to a best predictor model, and that discovering relative strength of different predictors might lead to better selection of intervention strategies to improve student performance. This study was conducted in an urban school district and was comprised of teachers and students enrolled in ninth grade science in three of this district's high schools. Consenting teachers (9), students (196), and parents (196) received written surveys with questions designed to examine the predictive power of each variable cluster. Regression analyses were used to determine which factors best correlate with student scores and classroom science grades. Selected factors were then compiled into a best predictive model, predicting success on standardized science tests. Students t tests of gender and racial subgroups confirmed that there were racial differences in OPT scores, and both gender and racial differences in science grades. Additional examinations were therefore conducted for all 12 variables to determine whether gender and race had an impact on the strength of individual variable predictions and on the final best predictor model. Of the 15 original OPT and cluster variable hypotheses, eight showed significant positive relationships that occurred in the expected direction. However, when more broadly based end-of-the-year science class grade was used as a criterion, 13 of the 15 hypotheses showed significant relationships in the expected direction. With both criteria, significant gender and racial differences were observed in the strength of individual predictors and in the composition of best predictor models.

  19. How significant is the slope of the sea-side boundary for modelling seawater intrusion in coastal aquifers?

    Science.gov (United States)

    Walther, Marc; Graf, Thomas; Kolditz, Olaf; Liedl, Rudolf; Post, Vincent

    2017-08-01

    Application of numerical models is a common method to assess groundwater resources. The versatility of these models allows consideration of different levels of complexity, but the accuracy of the outcomes hinges upon a proper description of the system behaviour. In seawater intrusion assessment, the implementation of the sea-side boundary condition is of particular importance. We evaluate the influence of the slope of the sea-side boundary on the simulation results of seawater intrusion in a freshwater aquifer by employing a series of slope variations together with a sensitivity analysis by varying additional sensitive parameters (freshwater inflow and longitudinal and transverse dispersivities). Model results reveal a multi-dimensional dependence of the investigated variables with an increasing relevance of the sea-side boundary slope for seawater intrusion (decrease of up to 32%), submarine groundwater discharge zone (reduction of up to 55%), and turnover times (increase of up to 730%) with increasing freshwater inflow or dispersivity values.

  20. Relations among Socioeconomic Status, Age, and Predictors of Phonological Awareness

    Science.gov (United States)

    McDowell, Kimberly D.; Lonigan, Christopher J.; Goldstein, Howard

    2007-01-01

    Purpose: This study simultaneously examined predictors of phonological awareness within the framework of 2 theories: the phonological distinctness hypothesis and the lexical restructuring model. Additionally, age as a moderator of the relations between predictor variables and phonological awareness was examined. Method: This cross-sectional…

  1. An Effect Size for Regression Predictors in Meta-Analysis

    Science.gov (United States)

    Aloe, Ariel M.; Becker, Betsy Jane

    2012-01-01

    A new effect size representing the predictive power of an independent variable from a multiple regression model is presented. The index, denoted as r[subscript sp], is the semipartial correlation of the predictor with the outcome of interest. This effect size can be computed when multiple predictor variables are included in the regression model…

  2. Investigation of the chromosome regions with significant affinity for the nuclear envelope in fruit fly--a model based approach.

    Directory of Open Access Journals (Sweden)

    Nicholas Allen Kinney

    Full Text Available Three dimensional nuclear architecture is important for genome function, but is still poorly understood. In particular, little is known about the role of the "boundary conditions"--points of attachment between chromosomes and the nuclear envelope. We describe a method for modeling the 3D organization of the interphase nucleus, and its application to analysis of chromosome-nuclear envelope (Chr-NE attachments of polytene (giant chromosomes in Drosophila melanogaster salivary glands. The model represents chromosomes as self-avoiding polymer chains confined within the nucleus; parameters of the model are taken directly from experiment, no fitting parameters are introduced. Methods are developed to objectively quantify chromosome territories and intertwining, which are discussed in the context of corresponding experimental observations. In particular, a mathematically rigorous definition of a territory based on convex hull is proposed. The self-avoiding polymer model is used to re-analyze previous experimental data; the analysis suggests 33 additional Chr-NE attachments in addition to the 15 already explored Chr-NE attachments. Most of these new Chr-NE attachments correspond to intercalary heterochromatin--gene poor, dark staining, late replicating regions of the genome; however, three correspond to euchromatin--gene rich, light staining, early replicating regions of the genome. The analysis also suggests 5 regions of anti-contact, characterized by aversion for the NE, only two of these correspond to euchromatin. This composition of chromatin suggests that heterochromatin may not be necessary or sufficient for the formation of a Chr-NE attachment. To the extent that the proposed model represents reality, the confinement of the polytene chromosomes in a spherical nucleus alone does not favor the positioning of specific chromosome regions at the NE as seen in experiment; consequently, the 15 experimentally known Chr-NE attachment positions do not

  3. Improving winter leaf area index estimation in evergreen coniferous forests and its significance in carbon and water fluxes modeling

    Science.gov (United States)

    Wang, R.; Chen, J. M.; Luo, X.

    2016-12-01

    Modeling of carbon and water fluxes at the continental and global scales requires remotely sensed LAI as inputs. For evergreen coniferous forests (ENF), severely underestimated winter LAI has been one of the issues for mostly available remote sensing products, which could cause negative bias in the modeling of Gross Primary Productivity (GPP) and evapotranspiration (ET). Unlike deciduous trees which shed all the leaves in winter, conifers retains part of their needles and the proportion of the retained needles depends on the needle longevity. In this work, the Boreal Ecosystem Productivity Simulator (BEPS) was used to model GPP and ET at eight FLUXNET Canada ENF sites. Two sets of LAI were used as the model inputs: the 250m 10-day University of Toronto (U of T) LAI product Version 2 and the corrected LAI based on the U of T LAI product and the needle longevity of the corresponding tree species at individual sites. Validating model daily GPP (gC/m2) against site measurements, the mean RMSE over eight sites decreases from 1.85 to 1.15, and the bias changes from -0.99 to -0.19. For daily ET (mm), mean RMSE decreases from 0.63 to 0.33, and the bias changes from -0.31 to -0.16. Most of the improvements occur in the beginning and at the end of the growing season when there is large correction of LAI and meanwhile temperature is still suitable for photosynthesis and transpiration. For the dormant season, the improvement in ET simulation mostly comes from the increased interception of precipitation brought by the elevated LAI during that time. The results indicate that model performance can be improved by the application the corrected LAI. Improving the winter RS LAI can make a large impact on land surface carbon and energy budget.

  4. Segmentation process significantly influences the accuracy of 3D surface models derived from cone beam computed tomography

    NARCIS (Netherlands)

    Fourie, Zacharias; Damstra, Janalt; Schepers, Rutger H; Gerrits, Pieter; Ren, Yijin

    2012-01-01

    AIMS: To assess the accuracy of surface models derived from 3D cone beam computed tomography (CBCT) with two different segmentation protocols. MATERIALS AND METHODS: Seven fresh-frozen cadaver heads were used. There was no conflict of interests in this study. CBCT scans were made of the heads and 3D

  5. Mechanical Predictors of Discomfort during Load Carriage.

    Directory of Open Access Journals (Sweden)

    Patrick D Wettenschwiler

    Full Text Available Discomfort during load carriage is a major issue for activities using backpacks (e.g. infantry maneuvers, children carrying school supplies, or outdoor sports. It is currently unclear which mechanical parameters are responsible for subjectively perceived discomfort. The aim of this study was to identify objectively measured mechanical predictors of discomfort during load carriage. We compared twelve different configurations of a typical load carriage system, a commercially available backpack with a hip belt. The pressure distribution under the hip belt and the shoulder strap, as well as the tensile force in the strap and the relative motion of the backpack were measured. Multiple linear regression analyses were conducted to investigate possible predictors of discomfort. The results demonstrate that static peak pressure, or alternatively, static strap force is a significant (p<0.001 predictor of discomfort during load carriage in the shoulder and hip region, accounting for 85% or more of the variation in discomfort. As an additional finding, we discovered that the regression coefficients of these predictors are significantly smaller for the hip than for the shoulder region. As static peak pressure is measured directly on the body, it is less dependent on the type of load carriage system than static strap force. Therefore, static peak pressure is well suited as a generally applicable, objective mechanical parameter for the optimization of load carriage system design. Alternatively, when limited to load carriage systems of the type backpack with hip belt, static strap force is the most valuable predictor of discomfort. The regionally differing regression coefficients of both predictors imply that the hip region is significantly more tolerant than the shoulder region. In order to minimize discomfort, users should be encouraged to shift load from the shoulders to the hip region wherever possible, at the same time likely decreasing the risk of low

  6. Predictors of Academic Success among College Latinos

    Science.gov (United States)

    Somoza, Yan Manuel, Jr.

    2010-01-01

    Research concerning Latinos and their educational attainment has posited several reasons for Latino underrepresentation and underachievement. This study sought to counter such deficiency models and examine certain predictors of academic success among college Latinos. Specifically, this study predicted a negative correlation between generational…

  7. Attitudes of prejudice as a predictor of cultural competence among baccalaureate nursing students.

    Science.gov (United States)

    Dunagan, Pamela B; Kimble, Laura P; Gunby, Susan Sweat; Andrews, Margaret M

    2014-06-01

    The purpose of this study was to explore the relationship between attitudes of prejudice and cultural competence among nursing students. Using a mixed-methods design, a convenience sample of students (N = 129) currently enrolled in a baccalaureate nursing program was recruited via Web networking. Data regarding attitudes of prejudice, cultural competence, prior cultural experience, and integration of cultural competence were obtained via a Web-based survey. Multiple linear regression was used to predict cultural knowledge, attitudes, and consciousness. Although all three regression models were statistically significant, the significant predictors varied within each model. Greater prejudice was a significant predictor of less culturally competent attitudes toward providing nursing care. Existing prejudice among nursing students needs to be addressed to help promote positive cultural attitudes and, ultimately, cultural competent nursing care.

  8. Evaluation of bedform predictors in tidal environments

    Science.gov (United States)

    Ferret, Y.; Ernstsen, V.; Lefebvre, A.; Winter, C.

    2012-04-01

    The seabed of coastal environments commonly exhibits a large range of complex mobile bedforms due to the interaction between hydrodynamics and sediment transport. Yet, no fundamental law has been identified which describes the initiation and development of these ubiquitous, flow and wave driven features. Thus, the prediction of bedform dimensions and dynamics is carried out using empirical relationships. In this study we evaluate some of these equations, based on a large data set consisting of high resolution multi-beam bathymetry, modelled hydrodynamics and sediment characteristics collected in the Jade Bay, and the Weser and the Elbe estuaries (German Bight, North Sea). More than 2000 individual bedforms were identified; they display a wide range of dimensions with heights ranging from 0.1 to 5 m and wavelengths between 10 and 300 m. They were used to test the classical relationships of Flemming (1988) and Francken et al. (2004) for the interdependency of length and height of individual bedforms. Taking into account all the data resulted in a large scatter, with weak correlations of averaged measured and predicted parameters (bedform height and length). However, applying a generalized extreme value method (which weights the Gaussian distribution of bedform height with the maximum frequency for every measured bedform length) in order to get the maximum density of bedform height, a strong dependency was identified (r2 = 0.76). Furthermore predictor equations that relate equilibrium flow and sediment characteristics to bedform dimensions and hydraulic roughness were tested (e.g. Yalin, 1964; Van Rijn, 1984). Results showed a significant scatter and limited reliability. Statistical analyses were used to accurately quantify the influence of the physical environment (depth, current velocity, grain size) on bedform morphologies in order to enhance the bedform predictors.

  9. Predictors of Homophobia in Female College Students.

    Science.gov (United States)

    Basow, Susan A.; Johnson, Kelly

    2000-01-01

    Investigated how self-esteem, self-discrepancy, and gender-attribute importance related to homophobia in predominantly white college women, noting sex role attitudes, authoritarian attitudes, and extent of contact with homosexuals. The only significant predictor of homophobia was authoritarian attitudes. Other correlations included belief in sex…

  10. Crowdsourcing novel childhood predictors of adult obesity

    NARCIS (Netherlands)

    Bevelander, K.E.; Kaipainen, K.; Swain, R.; Dohle, S.; Bongard, J.C.; Hines, P.D.H.; Wansink, B.

    2014-01-01

    Effective and simple screening tools are needed to detect behaviors that are established early in life and have a significant influence on weight gain later in life. Crowdsourcing could be a novel and potentially useful tool to assess childhood predictors of adult obesity. This exploratory study

  11. Congruence as a Predictor of Occupational Stress.

    Science.gov (United States)

    Sutherland, Lynette F.; And Others

    1995-01-01

    An examination of the relationship among nine measures of Holland's concept of congruence and their relationship to job stress used data from 154 workers. Iachan's M index was the best predictor of stress and strain. The relationship between congruence and stress was significant but dependent on the congruence measure used. (SK)

  12. Predictors of turnover intention in nurse faculty.

    Science.gov (United States)

    Gormley, Denise K; Kennerly, Susan

    2011-04-01

    Turnover of nurse faculty is an increasingly important issue in nursing as the available number of qualified faculty continues to decrease. Understanding the factors that contribute to turnover is important to academic administrators to retain and recruit qualified nursing faculty. The purpose of this study was to examine predictors of turnover intention in nurse faculty working in departments and schools of nursing in Carnegie Doctoral/Research Universities-Extensive, public and private, not-for-profit institutions. The multidimensional model of organizational commitment was used to frame this study. The predictor variables explored were organizational climate, organizational commitment, work role balance, role ambiguity, and role conflict. The work roles examined were research, teaching, and service. Logistical regression was performed to examine the predictors of turnover intention. Organizational climate intimacy and disengagement, affective and continuance organizational commitment, and role ambiguity were shown to predict turnover intention in nurse faculty. Copyright 2011, SLACK Incorporated.

  13. A comparison of model-based imputation methods for handling missing predictor values in a linear regression model: A simulation study

    Science.gov (United States)

    Hasan, Haliza; Ahmad, Sanizah; Osman, Balkish Mohd; Sapri, Shamsiah; Othman, Nadirah

    2017-08-01

    In regression analysis, missing covariate data has been a common problem. Many researchers use ad hoc methods to overcome this problem due to the ease of implementation. However, these methods require assumptions about the data that rarely hold in practice. Model-based methods such as Maximum Likelihood (ML) using the expectation maximization (EM) algorithm and Multiple Imputation (MI) are more promising when dealing with difficulties caused by missing data. Then again, inappropriate methods of missing value imputation can lead to serious bias that severely affects the parameter estimates. The main objective of this study is to provide a better understanding regarding missing data concept that can assist the researcher to select the appropriate missing data imputation methods. A simulation study was performed to assess the effects of different missing data techniques on the performance of a regression model. The covariate data were generated using an underlying multivariate normal distribution and the dependent variable was generated as a combination of explanatory variables. Missing values in covariate were simulated using a mechanism called missing at random (MAR). Four levels of missingness (10%, 20%, 30% and 40%) were imposed. ML and MI techniques available within SAS software were investigated. A linear regression analysis was fitted and the model performance measures; MSE, and R-Squared were obtained. Results of the analysis showed that MI is superior in handling missing data with highest R-Squared and lowest MSE when percent of missingness is less than 30%. Both methods are unable to handle larger than 30% level of missingness.

  14. Predictors of transformational leadership of nurse managers.

    Science.gov (United States)

    Echevarria, Ilia M; Patterson, Barbara J; Krouse, Anne

    2017-04-01

    The aim of this study was to examine the relationships among education, leadership experience, emotional intelligence and transformational leadership of nurse managers. Nursing leadership research provides limited evidence of predictors of transformational leadership style in nurse managers. A predictive correlational design was used with a sample of nurse managers (n = 148) working in varied health care settings. Data were collected using the Genos Emotional Intelligence Inventory, the Multi-factor Leadership Questionnaire and a demographic questionnaire. Simple linear and multiple regression analyses were used to examine relationships. A statistically significant relationship was found between emotional intelligence and transformational leadership (r = 0.59, P transformational leadership. Nurse managers should be well informed of the predictors of transformational leadership in order to pursue continuing education and development opportunities related to those predictors. The results of this study emphasise the need for emotional intelligence continuing education, leadership development and leader assessment programmes. © 2016 John Wiley & Sons Ltd.

  15. Predictors of multiple sexual partners from adolescence through young adulthood.

    Science.gov (United States)

    Vasilenko, Sara A; Lanza, Stephanie T

    2014-10-01

    To examine time-varying associations between predictors of recent multiple sexual partners from middle adolescence through young adulthood. We examined whether the odds of multiple partners in the past year were differentially predicted by substance use and depression over time, using data from a nationally representative longitudinal study (N = 11,963, 52.2% female, 18.3% African-American, 11.9% Hispanic, 3.5% Asian, 2.6% other race, M age at Wave I = 16.1 years, SD = 1.8). Data were analyzed using the time-varying effect model, which estimates associations between predictors and an outcome as a function of near-continuous time. The proportion of participants having multiple partners increased over time, leveling off at around 30% after age 20. Significant positive associations between substance use and multiple partners were strongest early in adolescence and decreased sharply by around age 18. The significant positive association between depression and sexual behavior weakened with age, remaining significant in young adulthood for women but not men. These findings suggest that factors associated with having multiple recent sexual partners change from middle adolescence through young adulthood. The time-varying effect model can be used to identify risk factors that are especially salient at different ages, thus identifying which age periods may hold the greatest promise for intervention. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  16. Predictors of weight maintenance

    NARCIS (Netherlands)

    Pasman, W.J.; Saris, W.H.M.; Westerterp-Plantenga, M.S.

    1999-01-01

    Objective: To obtain predictors of weight maintenance after a weight-loss intervention. Research Methods and Procedures: An overall analysis of data from two-long intervention studies [n = 67 women; age: 37.9±1.0 years; body weight (BW): 87.0±1.2 kg; body mass index: 32.1±0.5 kg·m-2; % body fat: 42.

  17. Predictors of weight maintenance

    NARCIS (Netherlands)

    Pasman, W.J.; Saris, W.H.M.; Westerterp-Plantenga, M.S.

    1999-01-01

    Objective: To obtain predictors of weight maintenance after a weight-loss intervention. Research Methods and Procedures: An overall analysis of data from two-long intervention studies [n = 67 women; age: 37.9±1.0 years; body weight (BW): 87.0±1.2 kg; body mass index: 32.1±0.5 kg·m-2; % body fat: 42.

  18. Predictors of weight maintenance

    NARCIS (Netherlands)

    Pasman, W.J.; Saris, W.H.M.; Westerterp-Plantenga, M.S.

    1999-01-01

    Objective: To obtain predictors of weight maintenance after a weight-loss intervention. Research Methods and Procedures: An overall analysis of data from two-long intervention studies [n = 67 women; age: 37.9±1.0 years; body weight (BW): 87.0±1.2 kg; body mass index: 32.1±0.5 kg·m-2; % body fat:

  19. Significance of the spatial reconstruction based on mathematical modeling in the surgical treatment of giant intracranial aneurysms

    Directory of Open Access Journals (Sweden)

    Nikolić Igor M.

    2006-01-01

    Full Text Available Background. The use of computer models for the 3- dimensional reconstruction could be a reliable method to overcome technical imperfections of diagnostic procedures for the microsurgical operation of giant intracranial aneurysms. Case report. We presented a case of successfully operated 52-year-old woman with giant intracranial aneurysm, in which the computer 3-dimensional reconstruction of blood vessels and the aneurysmal neck had been decisive for making the diagnosis. The model for 3- dimensional reconstruction of blood vessels was based on the two 2-dimensional projections of the conventional angiography. Standard neuroradiologic diagnostic procedures showed a giant aneurysm on the left middle cerebral artery, but the conventional subtraction and CT angiography did not reveal enough information. By the use of a personal computer, we performed a 3-dimensional spatial reconstruction of the left carotid artery to visualize the neck of aneurysm and its supplying blood vessels. Conclusion. The 3-dimensional spatial reconstruction of the cerebral vessels of a giant aneurysm based on the conventional angiography could be useful for planning the surgical procedure.

  20. Autoencoder-based identification of predictors of Indian monsoon

    Science.gov (United States)

    Saha, Moumita; Mitra, Pabitra; Nanjundiah, Ravi S.

    2016-10-01

    Prediction of Indian summer monsoon uses a number of climatic variables that are historically known to provide a high skill. However, relationships between predictors and predictand could be complex and also change with time. The present work attempts to use a machine learning technique to identify new predictors for forecasting the Indian monsoon. A neural network-based non-linear dimensionality reduction technique, namely, the sparse autoencoder is used for this purpose. It extracts a number of new predictors that have prediction skills higher than the existing ones. Two non-linear ensemble prediction models of regression tree and bagged decision tree are designed with identified monsoon predictors and are shown to be superior in terms of prediction accuracy. Proposed model shows mean absolute error of 4.5 % in predicting the Indian summer monsoon rainfall. Lastly, geographical distribution of the new monsoon predictors and their characteristics are discussed.

  1. Acellular bone marrow extracts significantly enhance engraftment levels of human hematopoietic stem cells in mouse xeno-transplantation models.

    Directory of Open Access Journals (Sweden)

    Kazem Zibara

    Full Text Available Hematopoietic stem cells (HSC derived from cord blood (CB, bone marrow (BM, or mobilized peripheral blood (PBSC can differentiate into multiple lineages such as lymphoid, myeloid, erythroid cells and platelets. The local microenvironment is critical to the differentiation of HSCs and to the preservation of their phenotype in vivo. This microenvironment comprises a physical support supplied by the organ matrix as well as tissue specific cytokines, chemokines and growth factors. We investigated the effects of acellular bovine bone marrow extracts (BME on HSC in vitro and in vivo. We observed a significant increase in the number of myeloid and erythroid colonies in CB mononuclear cells (MNC or CB CD34+ cells cultured in methylcellulose media supplemented with BME. Similarly, in xeno-transplantation experiments, pretreatment with BME during ex-vivo culture of HSCs induced a significant increase in HSC engraftment in vivo. Indeed, we observed both an increase in the number of differentiated myeloid, lymphoid and erythroid cells and an acceleration of engraftment. These results were obtained using CB MNCs, BM MNCs or CD34(+ cells, transplanted in immuno-compromised mice (NOD/SCID or NSG. These findings establish the basis for exploring the use of BME in the expansion of CB HSC prior to HSC Transplantation. This study stresses the importance of the mechanical structure and soluble mediators present in the surrounding niche for the proper activity and differentiation of stem cells.

  2. Dual learning processes underlying human decision-making in reversal learning tasks: Functional significance and evidence from the model fit to human behavior

    Directory of Open Access Journals (Sweden)

    Yu eBai

    2014-08-01

    Full Text Available Humans are capable of correcting their actions based on actions performed in the past, and this ability enables them to adapt to a changing environment. The computational field of reinforcement learning (RL has provided a powerful explanation for understanding such processes. Recently, the dual learning system, modeled as a hybrid model that incorporates value update based on reward-prediction error and learning rate modulation based on the surprise signal, has gained attention as a model for explaining various neural signals. However, the functional significance of the hybrid model has not been established. In the present study, we used computer simulation in a reversal learning task to address functional significance. The hybrid model was found to perform better than the standard RL model in a large parameter setting. These results suggest that the hybrid model is more robust against mistuning of parameters compared to the standard RL model when decision makers continue to learn stimulus-reward contingencies, which make an abrupt changes. The parameter fitting results also indicated that the hybrid model fit better than the standard RL model for more than 50% of the participants, which suggests that the hybrid model has more explanatory power for the behavioral data than the standard RL model.

  3. [Different explanatory models for addictive behavior in Turkish and German youths in Germany: significance for prevention and treatment].

    Science.gov (United States)

    Penka, S; Krieg, S; Hunner, Ch; Heinz, A

    2003-07-01

    Due to cultural and social barriers, immigrants seldom frequent centers for information, counseling, and treatment of addictive disorders. We examine cultural differences in the explanatory models of addictive behavior among Turkish and German youths in Germany with statistical devices that map the concepts associated with problems of addiction. Relevant differences were found between the disorder concepts of Turkish and German youth. German but not Turkish youths classified eating disorders among severe addictive disorders and associated them with embarrassment and shame. Concerning substance abuse, German but not Turkish youths clearly differentiated between illegal drug abuse and the abuse of alcohol and nicotine. Nearly half of all Turkish youths rejected central medical concepts such as "physical dependence" or "reduced control of substance intake" as completely inadequate to characterize problems of addictive behavior. Preventive information programs must consider these differences and use concepts that are accepted and clearly associated with addictive behavior by immigrant populations.

  4. Significance of plankton community structure and nutrient availability for the control of dinoflagellate blooms by parasites: a modeling approach.

    Science.gov (United States)

    Alves-de-Souza, Catharina; Pecqueur, David; Le Floc'h, Emilie; Mas, Sébastien; Roques, Cécile; Mostajir, Behzad; Vidussi, Franscesca; Velo-Suárez, Lourdes; Sourisseau, Marc; Fouilland, Eric; Guillou, Laure

    2015-01-01

    Dinoflagellate blooms are frequently observed under temporary eutrophication of coastal waters after heavy rains. Growth of these opportunistic microalgae is believed to be promoted by sudden input of nutrients and the absence or inefficiency of their natural enemies, such as grazers and parasites. Here, numerical simulations indicate that increasing nutrient availability not only promotes the formation of dinoflagellate blooms but can also stimulate their control by protozoan parasites. Moreover, high abundance of phytoplankton other than dinoflagellate hosts might have a significant dilution effect on the control of dinoflagellate blooms by parasites, either by resource competition with dinoflagellates (thus limiting the number of hosts available for infection) or by affecting numerical-functional responses of grazers that consume free-living parasite stages. These outcomes indicate that although both dinoflagellates and their protozoan parasites are directly affected by nutrient availability, the efficacy of the parasitic control of dinoflagellate blooms under temporary eutrophication depends strongly on the structure of the plankton community as a whole.

  5. Improving CCTA-based lesions' hemodynamic significance assessment by accounting for partial volume modeling in automatic coronary lumen segmentation.

    Science.gov (United States)

    Freiman, Moti; Nickisch, Hannes; Prevrhal, Sven; Schmitt, Holger; Vembar, Mani; Maurovich-Horvat, Pál; Donnelly, Patrick; Goshen, Liran

    2017-03-01

    The goal of this study was to assess the potential added benefit of accounting for partial volume effects (PVE) in an automatic coronary lumen segmentation algorithm that is used to determine the hemodynamic significance of a coronary artery stenosis from coronary computed tomography angiography (CCTA). Two sets of data were used in our work: (a) multivendor CCTA datasets of 18 subjects from the MICCAI 2012 challenge with automatically generated centerlines and 3 reference segmentations of 78 coronary segments and (b) additional CCTA datasets of 97 subjects with 132 coronary lesions that had invasive reference standard FFR measurements. We extracted the coronary artery centerlines for the 97 datasets by an automated software program followed by manual correction if required. An automatic machine-learning-based algorithm segmented the coronary tree with and without accounting for the PVE. We obtained CCTA-based FFR measurements using a flow simulation in the coronary trees that were generated by the automatic algorithm with and without accounting for PVE. We assessed the potential added value of PVE integration as a part of the automatic coronary lumen segmentation algorithm by means of segmentation accuracy using the MICCAI 2012 challenge framework and by means of flow simulation overall accuracy, sensitivity, specificity, negative and positive predictive values, and the receiver operated characteristic (ROC) area under the curve. We also evaluated the potential benefit of accounting for PVE in automatic segmentation for flow simulation for lesions that were diagnosed as obstructive based on CCTA which could have indicated a need for an invasive exam and revascularization. Our segmentation algorithm improves the maximal surface distance error by ~39% compared to previously published method on the 18 datasets from the MICCAI 2012 challenge with comparable Dice and mean surface distance. Results with and without accounting for PVE were comparable. In contrast

  6. Exploring Variation and Predictors of Residential Fine Particulate Matter Infiltration

    Directory of Open Access Journals (Sweden)

    Amanda J. Wheeler

    2010-08-01

    Full Text Available Although individuals spend the majority of their time indoors, most epidemiological studies estimate personal air pollution exposures based on outdoor levels. This almost certainly results in exposure misclassification as pollutant infiltration varies between homes. However, it is often not possible to collect detailed measures of infiltration for individual homes in large-scale epidemiological studies and thus there is currently a need to develop models that can be used to predict these values. To address this need, we examined infiltration of fine particulate matter (PM2.5 and identified determinants of infiltration for 46 residential homes in Toronto, Canada. Infiltration was estimated using the indoor/outdoor sulphur ratio and information on hypothesized predictors of infiltration were collected using questionnaires and publicly available databases. Multiple linear regression was used to develop the models. Mean infiltration was 0.52 ± 0.21 with no significant difference across heating and non-heating seasons. Predictors of infiltration were air exchange, presence of central air conditioning, and forced air heating. These variables accounted for 38% of the variability in infiltration. Without air exchange, the model accounted for 26% of the variability. Effective modelling of infiltration in individual homes remains difficult, although key variables such as use of central air conditioning show potential as an easily attainable indicator of infiltration.

  7. Exploring variation and predictors of residential fine particulate matter infiltration.

    Science.gov (United States)

    Clark, Nina A; Allen, Ryan W; Hystad, Perry; Wallace, Lance; Dell, Sharon D; Foty, Richard; Dabek-Zlotorzynska, Ewa; Evans, Greg; Wheeler, Amanda J

    2010-08-01

    Although individuals spend the majority of their time indoors, most epidemiological studies estimate personal air pollution exposures based on outdoor levels. This almost certainly results in exposure misclassification as pollutant infiltration varies between homes. However, it is often not possible to collect detailed measures of infiltration for individual homes in large-scale epidemiological studies and thus there is currently a need to develop models that can be used to predict these values. To address this need, we examined infiltration of fine particulate matter (PM(2.5)) and identified determinants of infiltration for 46 residential homes in Toronto, Canada. Infiltration was estimated using the indoor/outdoor sulphur ratio and information on hypothesized predictors of infiltration were collected using questionnaires and publicly available databases. Multiple linear regression was used to develop the models. Mean infiltration was 0.52 ± 0.21 with no significant difference across heating and non-heating seasons. Predictors of infiltration were air exchange, presence of central air conditioning, and forced air heating. These variables accounted for 38% of the variability in infiltration. Without air exchange, the model accounted for 26% of the variability. Effective modelling of infiltration in individual homes remains difficult, although key variables such as use of central air conditioning show potential as an easily attainable indicator of infiltration.

  8. Surface functionalization of bioactive glasses with natural molecules of biological significance, Part I: Gallic acid as model molecule

    Science.gov (United States)

    Zhang, Xin; Ferraris, Sara; Prenesti, Enrico; Verné, Enrica

    2013-12-01

    Gallic acid (3,4,5-trihydroxybenzoic acid, GA) and its derivatives are a group of biomolecules (polyphenols) obtained from plants. They have effects which are potentially beneficial to heath, for example they are antioxidant, anticarcinogenic and antibacterial, as recently investigated in many fields such as medicine, food and plant sciences. The main drawbacks of these molecules are both low stability and bioavailability. In this research work the opportunity to graft GA to bioactive glasses is investigated, in order to deliver the undamaged biological molecule into the body, using the biomaterial surfaces as a localized carrier. GA was considered for functionalization since it is a good model molecule for polyphenols and presents several interesting biological activities, like antibacterial, antioxidant and anticarcinogenic properties. Two different silica based bioactive glasses (SCNA and CEL2), with different reactivity, were employed as substrates. UV photometry combined with the Folin&Ciocalteu reagent was adopted to test the concentration of GA in uptake solution after functionalization. This test verified how much GA consumption occurred with surface modification and it was also used on solid samples to test the presence of GA on functionalized glasses. XPS and SEM-EDS techniques were employed to characterize the modification of material surface properties and functional group composition before and after functionalization.

  9. Elucidating the significance of spatial memory on movement decisions by African savannah elephants using state-space models.

    Science.gov (United States)

    Polansky, Leo; Kilian, Werner; Wittemyer, George

    2015-04-22

    Spatial memory facilitates resource acquisition where resources are patchy, but how it influences movement behaviour of wide-ranging species remains to be resolved. We examined African elephant spatial memory reflected in movement decisions regarding access to perennial waterholes. State-space models of movement data revealed a rapid, highly directional movement behaviour almost exclusively associated with visiting perennial water. Behavioural change point (BCP) analyses demonstrated that these goal-oriented movements were initiated on average 4.59 km, and up to 49.97 km, from the visited waterhole, with the closest waterhole accessed 90% of the time. Distances of decision points increased when switching to different waterholes, during the dry season, or for female groups relative to males, while selection of the closest waterhole decreased when switching. Overall, our analyses indicated detailed spatial knowledge over large scales, enabling elephants to minimize travel distance through highly directional movement when accessing water. We discuss the likely cognitive and socioecological mechanisms driving these spatially precise movements that are most consistent with our findings. By applying modern analytic techniques to high-resolution movement data, this study illustrates emerging approaches for studying how cognition structures animal movement behaviour in different ecological and social contexts. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  10. Stress field modeling of northwestern South China Sea since 5.3 Ma and its tectonic significance

    Institute of Scientific and Technical Information of China (English)

    YANG Fengli; ZHOU Zuyi; ZHANG Na; LIU Ning; NI Bin

    2013-01-01

    Tectonically, the northwestern South China Sea (SCS) is located at the junction between three micro-plates, i.e., the Indochina, South China and Zhongsha-Xisha micro-plates, and involves three basins, i.e., the Yinggehai Basin, the Qiongdongnan Basin and Xisha Trough in the east, and the Zhongjiannan Basin in the south. Since the Pliocene (5.3 Ma), the Yinggehai Basin has experienced repeated accelerating subsidence, high thermal fluid, and widely developing mud-rich overpressure chambers, abundant mud diapers and crust-mantle mixed CO2. While a large central canyon was developed in the Qiongdongnan Basin, new rift occurred in the Xisha Trough. These characteristics demonstrate a single tectonic unit for the northwestern SCS, for which we have undertaken stress field modeling to understand its plate deformations and sedimen-tary responses. Our results demonstrate that an extension tectonic event occurred after 5.3 Ma in theYingge-hai-Qiongdongnan-Xisha trough area, which is characterized by thinner crust (3500 m). A new rift system subsequently was developed in this area;this event was mainly driven by the combined effects of different movement veloc-ity and direction of the three micro-plates, and the far-field effect of the continental collision between the Indian Plate and the Tibetan Plateau, and subduction of the Pacific Plate underneath the Eurasian Plate.

  11. Predictors for traumatic brain injuries evaluated through accident reconstructions.

    Science.gov (United States)

    Kleiven, Svein

    2007-10-01

    The aim of this study is to evaluate all the 58 available NFL cases and compare various predictors for mild traumatic brain injuries using a detailed and extensively validated finite element model of the human head. Global injury measures such as magnitude in angular and translational acceleration, change in angular velocity, head impact power (HIP) and HIC were also investigated with regard to their ability to predict the intracranial pressure and strains associated with injury. The brain material properties were modeled using a hyperelastic and viscoelastic constitutive law. Also, three different stiffness parameters, encompassing a range of published brain tissue properties, were tested. 8 tissue injury predictors were evaluated for 6 different regions, covering the entire cerebrum, as well as for the whole brain. In addition, 10 head kinematics based predictors were evaluated both for correlation with injury as well as with strain and pressure. When evaluating the results, a statistical correlation between strain, strain rate, product of strain and strain rate, Cumulative Strain Damage Measure (CSDM), strain energy density, maximum pressure, magnitude of minimum pressure, as well as von Mises effective stress, with injury was found when looking into specific regions of the brain. However, the maximal pressure in the gray matter showed a higher correlation with injury than other evaluated measures. On the other hand, it was possible, through the reconstruction of a motocross accident, to re-create the injury pattern in the brain of the injured rider using maximal principal strain. It was also found that a simple linear combination of peak change in rotational velocity and HIC showed a high correlation (R=0.98) with the maximum principal strain in the brain, in addition to being a significant predictor of injury. When applying the rotational and translational kinematics separately for one of the cases, it was found that the translational kinematics contribute

  12. Predictors of distant relapse in patients with FIGO stage IIB-IVA cervical cancer treated with definitive radiotherapy.

    Science.gov (United States)

    Okazawa-Sakai, Mika; Mabuchi, Seiji; Isohashi, Fumiaki; Kawashima, Atsushi; Yokoi, Eriko; Ogawa, Kazuhiko; Kimura, Tadashi

    2017-08-17

    To investigate the predictors of distant relapse in International Federation of Gynecology and Obstetrics (FIGO) stage IIB-IVA cervical cancer patients treated with definitive radiotherapy (RT). The clinical data of 219 patients with FIGO stage IIB-IVA cervical cancer treated with definitive RT between January 1997 and December 2011 were retrospectively reviewed. The cumulative distant relapse, progression-free survival (PFS) and overall survival (OS) rates were calculated using the Kaplan-Meier method and compared using the log-rank test. A Cox proportional hazards regression model was used to investigate the predictors of distant relapse in patients. Following treatment with definitive RT, 61 of the 219 (27.9%) patients developed distant relapse with median PFS and OS rates of 9.9 and 32.8 months, and estimated five-year PFS and OS rates of 4.9% and 21.3%, respectively. Multivariate analysis revealed that pelvic node metastasis, pretreatment leukocytosis and pretreatment neutrophilia were significant predictors of distant relapse. The risk of developing distant relapse was found to be associated with the number of predictors that the patients displayed: the estimated five-year distant relapse rates of the patients with no predictors, one predictor and two predictors were 20.3%, 35.5% and 88.9%, respectively. Roughly 28% of patients with FIGO stage IIB-IVA cervical cancer developed distant relapse after definitive RT. Pelvic lymph node metastasis and pretreatment leukocytosis/neutrophilia are independent predictors of distant relapse. © 2017 Japan Society of Obstetrics and Gynecology.

  13. Inhibition of tumor progression during allergic airway inflammation in a murine model: significant role of TGF-β.

    Science.gov (United States)

    Tirado-Rodriguez, Belen; Baay-Guzman, Guillermina; Hernandez-Pando, Rogelio; Antonio-Andres, Gabriela; Vega, Mario I; Rocha-Zavaleta, Leticia; Bonifaz, Laura C; Huerta-Yepez, Sara

    2015-09-01

    TGF-β is an important mediator of pulmonary allergic inflammation, and it has been recently reported to be a potential inhibitor of lung tumor progression. The correlation between cancer and allergic inflammatory diseases remains controversial. Thus, the aim of the present study was to evaluate the effects of pulmonary allergic inflammation and in particular the role of TGF-β on cancer progression. Cancer cells were implanted in a BALB/c mice model of allergic airway inflammation, and tumor growth was measured. Apoptosis was evaluated by TUNEL assay, and TGF-β was measured by ELISA. Expression of proliferating cell nuclear antigen, TGF-β, TGF-β receptors I and II, phospho-Smad2 and phospho-Smad4 was evaluated by immunohistochemistry and quantified using digital pathology. The effect of a TGF-β activity inhibitor and recombinant TGF-β on tumor growth was analyzed. The effect of exogenous TGF-β on cell proliferation and apoptosis was evaluated in vitro. Mice with allergic airway inflammation exhibited decreased tumor volumes due to cell proliferation inhibition and increased apoptosis. TGF-β was increased in the sera and tumor tissues of allergic mice. TGF-β activity inhibition increased tumor progression in allergic mice by enhancing proliferation and decreasing apoptosis of tumor cells. The administration of TGF-β resulted in reduced tumor growth. This study is the first to establish an inverse relationship between allergic airway inflammation and tumor progression. This effect appears to be mediated by TGF-β, which is overexpressed in tumor cells during pulmonary allergic inflammation. This study indicates that TGF-β is a potential target for antitumor therapy.

  14. The effect of c-fos on acute myocardial infarction and the significance of metoprolol intervention in a rat model.

    Science.gov (United States)

    Zhang, Song; Zhang, Meiqi; Goldstein, Steven; Li, Yigang; Ge, Junbo; He, Ben; Ruiz, George

    2013-03-01

    Over-expression of c-fos may play a role in some diseases. Research pertaining to the expression of c-fos in acute myocardial ınfarction (AMI) is rare, and the detailed role of c-fos in AMI has not been reported. Therefore, the purpose of this project was to elucidate the detailed effect of c-fos on AMI rats and evaluate the effect of a metoprolol intervention. An AMI rat model was established for the purposes of this study. The expression of c-fos in AMI was evaluated via immunohistochemical analysis and in situ hybridization. Simultaneously, we investigated the effect of c-fos on AMI rats via medicinal treatment with c-fos monoclonal antibody, isoproterenol, and metoprolol. Positive c-Fos protein expression and c-fos mRNA expression in cardiomyocytes were increased at 1, 3, 7, and 10 days after ligation in AMI rats compared with a sham-operated group. Peak expression occurred at 3 days after ligation. The weight percentage fraction of infarct size was decreased in rats treated with c-fos monoclonal antibody compared with the control normal saline treatment group. The weight percentage fraction of infarction size was increased after c-fos was increased via the administration of isoproterenol. c-Fos protein expression and the infarct size in rats treated with metoprolol were also decreased compared with the control normal saline treatment group. The results showed that c-fos expression rapidly increased after coronary ligation; c-fos plays an important role in myocardial lesions and is likely to be involved in the pathogenesis of AMI as well. Metoprolol can inhibit the expression of c-fos and has a positive therapeutic effect on rats after AMI; the involvement effect of metoprolol on myocardial infarction might be correlated with its effect on the inhibition of c-fos.

  15. The Significance of Quality Assurance within Model Intercomparison Projects at the World Data Centre for Climate (WDCC)

    Science.gov (United States)

    Toussaint, F.; Hoeck, H.; Stockhause, M.; Lautenschlager, M.

    2014-12-01

    The classical goals of a quality assessment system in the data life cycle are (1) to encourage data creators to improve their quality assessment procedures to reach the next quality level and (2) enable data consumers to decide, whether a dataset has a quality that is sufficient for usage in the target application, i.e. to appraise the data usability for their own purpose.As the data volumes of projects and the interdisciplinarity of data usage grow, the need for homogeneous structure and standardised notation of data and metadata increases. This third aspect is especially valid for the data repositories, as they manage data through machine agents. So checks for homogeneity and consistency in early parts of the workflow become essential to cope with today's data volumes.Selected parts of the workflow in the model intercomparison project CMIP5 and the archival of the data for the interdiscipliary user community of the IPCC-DDC AR5 and the associated quality checks are reviewed. We compare data and metadata checks and relate different types of checks to their positions in the data life cycle.The project's data citation approach is included in the discussion, with focus on temporal aspects of the time necessary to comply with the project's requirements for formal data citations and the demand for the availability of such data citations.In order to make different quality assessments of projects comparable, WDCC developed a generic Quality Assessment System. Based on the self-assessment approach of a maturity matrix, an objective and uniform quality level system for all data at WDCC is derived which consists of five maturity quality levels.

  16. Serum Predictors of Percent Lean Mass in Young Adults.

    Science.gov (United States)

    Lustgarten, Michael S; Price, Lori L; Phillips, Edward M; Kirn, Dylan R; Mills, John; Fielding, Roger A

    2016-08-01

    Lustgarten, MS, Price, LL, Phillips, EM, Kirn, DR, Mills, J, and Fielding, RA. Serum predictors of percent lean mass in young adults. J Strength Cond Res 30(8): 2194-2201, 2016-Elevated lean (skeletal muscle) mass is associated with increased muscle strength and anaerobic exercise performance, whereas low levels of lean mass are associated with insulin resistance and sarcopenia. Therefore, studies aimed at obtaining an improved understanding of mechanisms related to the quantity of lean mass are of interest. Percent lean mass (total lean mass/body weight × 100) in 77 young subjects (18-35 years) was measured with dual-energy x-ray absorptiometry. Twenty analytes and 296 metabolites were evaluated with the use of the standard chemistry screen and mass spectrometry-based metabolomic profiling, respectively. Sex-adjusted multivariable linear regression was used to determine serum analytes and metabolites significantly (p ≤ 0.05 and q ≤ 0.30) associated with the percent lean mass. Two enzymes (alkaline phosphatase and serum glutamate oxaloacetate aminotransferase) and 29 metabolites were found to be significantly associated with the percent lean mass, including metabolites related to microbial metabolism, uremia, inflammation, oxidative stress, branched-chain amino acid metabolism, insulin sensitivity, glycerolipid metabolism, and xenobiotics. Use of sex-adjusted stepwise regression to obtain a final covariate predictor model identified the combination of 5 analytes and metabolites as overall predictors of the percent lean mass (model R = 82.5%). Collectively, these data suggest that a complex interplay of various metabolic processes underlies the maintenance of lean mass in young healthy adults.

  17. Macrophytes may not contribute significantly to removal of nutrients, pharmaceuticals, and antibiotic resistance in model surface constructed wetlands.

    Science.gov (United States)

    Cardinal, Pascal; Anderson, Julie C; Carlson, Jules C; Low, Jennifer E; Challis, Jonathan K; Beattie, Sarah A; Bartel, Caitlin N; Elliott, Ashley D; Montero, Oscar F; Lokesh, Sheetal; Favreau, Alex; Kozlova, Tatiana A; Knapp, Charles W; Hanson, Mark L; Wong, Charles S

    2014-06-01

    Outdoor shallow wetland mesocosms, designed to simulate surface constructed wetlands to improve lagoon wastewater treatment, were used to assess the role of macrophytes in the dissipation of wastewater nutrients, selected pharmaceuticals, and antibiotic resistance genes (ARGs). Specifically, mesocosms were established with or without populations of Typha spp. (cattails), Myriophyllum sibiricum (northern water milfoil), and Utricularia vulgaris (bladderwort). Following macrophyte establishment, mesocosms were seeded with ARG-bearing organisms from a local wastewater lagoon, and treated with a single pulse of artificial municipal wastewater with or without carbamazepine, clofibric acid, fluoxetine, and naproxen (each at 7.6μg/L), as well as sulfamethoxazole and sulfapyridine (each at 150μg/L). Rates of pharmaceutical dissipation over 28d ranged from 0.073 to 3.0d(-1), corresponding to half-lives of 0.23 to 9.4d. Based on calculated rate constants, observed dissipation rates were consistent with photodegradation driving clofibric acid, naproxen, sulfamethoxazole, and sulfapyridine removal, and with sorption also contributing to carbamazepine and fluoxetine loss. Of the seven gene determinants assayed, only two genes for both beta-lactam resistance (blaCTX and blaTEM) and sulfonamide resistance (sulI and sulII) were found in sufficient quantity for monitoring. Genes disappeared relatively rapidly from the water column, with half-lives ranging from 2.1 to 99d. In contrast, detected gene levels did not change in the sediment, with the exception of sulI, which increased after 28d in pharmaceutical-treated systems. These shallow wetland mesocosms were able to dissipate wastewater contaminants rapidly. However, no significant enhancement in removal of nutrients or pharmaceuticals was observed in mesocosms with extensive aquatic plant communities. This was likely due to three factors: first, use of naïve systems with an unchallenged capacity for nutrient assimilation and

  18. Predictors of Poor Pregnancy Outcomes Among Antenatal Care Attendees in Primary Health Care Facilities in Cross River State, Nigeria: A Multilevel Model.

    Science.gov (United States)

    Ameh, Soter; Adeleye, Omokhoa A; Kabiru, Caroline W; Agan, Thomas; Duke, Roseline; Mkpanam, Nkese; Nwoha, Doris

    2016-08-01

    Objectives Pregnancy carries a high risk for millions of women and varies by urban-rural location in Nigeria, a country with the second highest maternal deaths in the world. Addressing multilevel predictors of poor pregnancy outcomes among antenatal care (ANC) attendees in primary health care (PHC) facilities could reduce the high maternal mortality rate in Nigeria. This study utilised the "Risk Approach" strategy to (1) compare the risks of poor pregnancy outcomes among ANC attendees by urban-rural location; and (2) determine predictors of poor pregnancy outcomes among ANC attendees in urban-rural PHC facilities in Cross River State, Nigeria. Methods A cross-sectional survey was conducted in 2011 among 400 ANC attendees aged 15-49 years recruited through multistage sampling. Data on risk factors of poor pregnancy outcomes were collected using interviewer-administered questionnaires and clinic records. Respondents were categorised into low, medium or high risk of poor pregnancy outcomes, based on their overall risk scores. Predictors of poor pregnancy outcomes were determined by multilevel ordinal logistic regression. Results A greater proportion of the women in the rural areas were below the middle socio-economic quintile (75 vs. 4 %, p facilities had a low overall risk of poor pregnancy outcomes than those in the rural facilities (64 vs. 50 %, p = 0.034). Pregnant women in the urban areas had decreased odds of being at high risk of poor pregnancy outcomes versus the combined medium and low risks compared with those in the rural areas (OR 0.55, 95 % CI 0.09-0.65). Conclusions for Practice Pregnant women attending antenatal care in rural PHC facilities are more at risk of poor pregnancy outcomes than those receiving care in the urban facilities. Health programmes that promote safe pregnancy should target pregnant women in rural settings.

  19. Intra-articular (IA) ropivacaine microparticle suspensions reduce pain, inflammation, cytokine, and substance p levels significantly more than oral or IA celecoxib in a rat model of arthritis.

    Science.gov (United States)

    Rabinow, Barrett; Werling, Jane; Bendele, Alison; Gass, Jerome; Bogseth, Roy; Balla, Kelly; Valaitis, Paul; Hutchcraft, Audrey; Graham, Sabine

    2015-02-01

    Current therapeutic treatment options for osteoarthritis entail significant safety concerns. A novel ropivacaine crystalline microsuspension for bolus intra-articular (IA) delivery was thus developed and studied in a peptidoglycan polysaccharide (PGPS)-induced ankle swelling rat model. Compared with celecoxib controls, both oral and IA, ropivacaine IA treatment resulted in a significant reduction of pain upon successive PGPS reactivation, as demonstrated in two different pain models, gait analysis and incapacitance testing. The reduction in pain was attended by a significant reduction in histological inflammation, which in turn was accompanied by significant reductions in the cytokines IL-18 and IL-1β. This may have been due to inhibition of substance P, which was also significantly reduced. Pharmacokinetic analysis indicated that the analgesic effects outlasted measurable ropivacaine levels in either blood or tissue. The results are discussed in the context of pharmacologic mechanisms both of local anesthetics as well as inflammatory arthritis.

  20. Acute hypothalamic suppression significantly affects trabecular bone but not cortical bone following recovery and ovariectomy surgery in a rat model

    Directory of Open Access Journals (Sweden)

    Vanessa R. Yingling

    2016-01-01

    RH-a group compared to C, a similar deficit in BV/TV was also measured following recovery and post-OVX. The trabecular number and thickness were lower in the GnRH-a group compared to control.Conclusion. These data suggest that following a transient delay in pubertal onset, trabecular bone volume was significantly lower and no restoration of bone volume occurred following recovery or post-OVX surgery. However, cortical bone strength was maintained through architectural adaptations in the cortical bone envelope. An increase in the polar moment of inertia offset increased bone resorption. The current data are the first to suppress trabecular bone during growth, and then add an OVX protocol at maturity. Trabecular bone and cortical bone differed in their response to hypothalamic suppression during development; trabecular bone was more sensitive to the negative effects of hypothalamic suppression.

  1. Sense of coherence and hardiness as predictors of the mental health of college students.

    Science.gov (United States)

    Knowlden, Adam P; Sharma, Manoj; Kanekar, Amar; Atri, Ashutosh

    Psychological distress has a deleterious impact on the mental health of college students. The purpose of this study was to specify a theoretical, sense of coherence, and hardiness-based regression model to predict the mental health of college students. The instruments employed to build the model included the Kessler Psychological Distress Scale K-6, the Sense of Coherence-29, and the College Student Hardiness Measure. Data were collected from a sample of college students (n = 220) attending a Midwestern university. Each of the theoretical predictors regressed on mental health was deemed significant. Collectively, the significant predictors produced an R2 adjusted value of 0.434 (p mental health in the sample of participants. Qualitative cut-points were developed for each scale to aid in measurement of health promotion and education interventions designed to improve the mental health of college students.

  2. Prediction error variance and expected response to selection, when selection is based on the best predictor – for Gaussian and threshold characters, traits following a Poisson mixed model and survival traits

    Directory of Open Access Journals (Sweden)

    Jensen Just

    2002-05-01

    Full Text Available Abstract In this paper, we consider selection based on the best predictor of animal additive genetic values in Gaussian linear mixed models, threshold models, Poisson mixed models, and log normal frailty models for survival data (including models with time-dependent covariates with associated fixed or random effects. In the different models, expressions are given (when these can be found – otherwise unbiased estimates are given for prediction error variance, accuracy of selection and expected response to selection on the additive genetic scale and on the observed scale. The expressions given for non Gaussian traits are generalisations of the well-known formulas for Gaussian traits – and reflect, for Poisson mixed models and frailty models for survival data, the hierarchal structure of the models. In general the ratio of the additive genetic variance to the total variance in the Gaussian part of the model (heritability on the normally distributed level of the model or a generalised version of heritability plays a central role in these formulas.

  3. Prediction error variance and expected response to selection, when selection is based on the best predictor – for Gaussian and threshold characters, traits following a Poisson mixed model and survival traits

    Science.gov (United States)

    Korsgaard, Inge Riis; Andersen, Anders Holst; Jensen, Just

    2002-01-01

    In this paper, we consider selection based on the best predictor of animal additive genetic values in Gaussian linear mixed models, threshold models, Poisson mixed models, and log normal frailty models for survival data (including models with time-dependent covariates with associated fixed or random effects). In the different models, expressions are given (when these can be found – otherwise unbiased estimates are given) for prediction error variance, accuracy of selection and expected response to selection on the additive genetic scale and on the observed scale. The expressions given for non Gaussian traits are generalisations of the well-known formulas for Gaussian traits – and reflect, for Poisson mixed models and frailty models for survival data, the hierarchal structure of the models. In general the ratio of the additive genetic variance to the total variance in the Gaussian part of the model (heritability on the normally distributed level of the model) or a generalised version of heritability plays a central role in these formulas. PMID:12081800

  4. Time-dependent predictors in clinical research, performance of a novel method.

    Science.gov (United States)

    van de Bosch, Joan; Atiqi, Roya; Cleophas, Ton J

    2010-01-01

    Individual patients' predictors of survival may change across time, because people may change their lifestyles. Standard statistical methods do not allow adjustments for time-dependent predictors. In the past decade, time-dependent factor analysis has been introduced as a novel approach adequate for the purpose. Using examples from survival studies, we assess the performance of the novel method. SPSS statistical software is used (SPSS Inc., Chicago, IL). Cox regression is a major simplification of real life; it assumes that the ratio of the risks of dying in parallel groups is constant over time. It is, therefore, inadequate to analyze, for example, the effect of elevated low-density lipoprotein cholesterol on survival, because the relative hazard of dying is different in the first, second, and third decades. The time-dependent Cox regression model allowing for nonproportional hazards is applied and provides a better precision than the usual Cox regression (P = 0.117 versus 0.0001). Elevated blood pressure produces the highest risk at the time it is highest. An overall analysis of the effect of blood pressure on survival is not significant, but after adjustment for the periods with highest blood pressures using the segmented time-dependent Cox regression method, blood pressure is a significant predictor of survival (P = 0.04). In a long-term therapeutic study, treatment modality is a significant predictor of survival, but after the inclusion of the time-dependent low-density lipoprotein cholesterol variable, the precision of the estimate improves from a P value of 0.02 to 0.0001. Predictors of survival may change across time, e.g., the effect of smoking, cholesterol, and increased blood pressure in cardiovascular research and patients' frailty in oncology research. Analytical models for survival analysis adjusting such changes are welcome. The time-dependent and segmented time-dependent predictors are adequate for the purpose. The usual multiple Cox regression

  5. Mechanical Predictors of Discomfort during Load Carriage.

    Science.gov (United States)

    Wettenschwiler, Patrick D; Lorenzetti, Silvio; Stämpfli, Rolf; Rossi, René M; Ferguson, Stephen J; Annaheim, Simon

    2015-01-01

    Discomfort during load carriage is a major issue for activities using backpacks (e.g. infantry maneuvers, children carrying school supplies, or outdoor sports). It is currently unclear which mechanical parameters are responsible for subjectively perceived discomfort. The aim of this study was to identify objectively measured mechanical predictors of discomfort during load carriage. We compared twelve different configurations of a typical load carriage system, a commercially available backpack with a hip belt. The pressure distribution under the hip belt and the shoulder strap, as well as the tensile force in the strap and the relative motion of the backpack were measured. Multiple linear regression analyses were conducted to investigate possible predictors of discomfort. The results demonstrate that static peak pressure, or alternatively, static strap force is a significant (pbackpack with hip belt, static strap force is the most valuable predictor of discomfort. The regionally differing regression coefficients of both predictors imply that the hip region is significantly more tolerant than the shoulder region. In order to minimize discomfort, users should be encouraged to shift load from the shoulders to the hip region wherever possible, at the same time likely decreasing the risk of low back pain or injury.

  6. Diversity As A Predictor Of Leadership Effectiveness

    OpenAIRE

    Richard Herrera; Phyllis Duncan; Malcolm Ree; Kevin Williams

    2013-01-01

    Drawing upon theexisting literature, this study investigated the significance of Diversity as apredictor of leadership effectiveness, as it relates to the MultidimensionalMeasure of Leader-Member Exchange (LMX-MDM).  A study of 300 working adults found that therewas a significant positive relationship between Diversity and the four LMXdimensions of Contribution, Loyalty, Affect, and Professional Respect.  Collectivism and religious affiliation wereboth strong predictors with regard to Contrib...

  7. Predictors of cognitive function in candidates for coronary artery bypass graft surgery.

    Science.gov (United States)

    Ernest, Christine S; Elliott, Peter C; Murphy, Barbara M; Le Grande, Michael R; Goble, Alan J; Higgins, Rosemary O; Worcester, Marian U C; Tatoulis, James

    2007-03-01

    Candidates for coronary artery bypass graft surgery have been found to exhibit reduced cognitive function prior to surgery. However, little is known regarding the factors that are associated with pre-bypass cognitive function. A battery of neuropsychological tests was administered to a group of patients listed for bypass surgery (n = 109). Medical, sociodemographic and emotional predictors of cognitive function were investigated using structural equation modeling. Medical factors, namely history of hypertension and low ejection fraction, significantly predicted reduced cognitive function, as did several sociodemographic characteristics, namely older age, less education, non-English speaking background, manual occupation, and male gender. One emotional variable, confusion and bewilderment, was also a significant predictor whereas anxiety and depression were not. When significant predictors from the three sets of variables were included in a combined model, three of the five sociodemographic characteristics, namely age, non-English speaking background and occupation, and the two medical factors remained significant. Apart from sociodemographic characteristics, medical factors such as a history of hypertension and low ejection fraction significantly predicted reduced cognitive function in bypass candidates prior to surgery.

  8. Predictors of Inpatient Utilization among Veterans with Dementia

    Directory of Open Access Journals (Sweden)

    Kyler M. Godwin

    2014-01-01

    Full Text Available Dementia is prevalent and costly, yet the predictors of inpatient hospitalization are not well understood. Logistic and negative binomial regressions were used to identify predictors of inpatient hospital utilization and the frequency of inpatient hospital utilization, respectively, among veterans. Variables significant at the P<0.15 level were subsequently analyzed in a multivariate regression. This study of veterans with a diagnosis of dementia (n=296 and their caregivers found marital status to predict hospitalization in the multivariate logistic model (B=0.493, P=0.029 and personal-care dependency to predict hospitalization and readmission in the multivariate logistic model and the multivariate negative binomial model (B=1.048, P=0.007, B=0.040, and P=0.035, resp.. Persons with dementia with personal-care dependency and spousal caregivers have more inpatient admissions; appropriate care environments should receive special care to reduce hospitalization. This study was part of a larger clinical trial; this trial is registered with ClinicalTrials.gov NCT00291161.

  9. Are competition and extrinsic motivation reliable predictors of academic cheating?

    Directory of Open Access Journals (Sweden)

    Gábor eOrosz

    2013-02-01

    Full Text Available Previous studies suggest that extrinsic motivation and competition are reliable predictors of academic cheating. The aim of the present questionnaire study was to separate the effects of motivation- and competition-related variables on academic cheating by Hungarian high school students (N = 620, M = 264, F = 356. Structural equation modeling showed that intrinsic motivation has a negative effect, and amotivation has a positive indirect effect on self-reported academic cheating. In contrast, extrinsic motivation had no significant effect. Indirect positive influence on cheating, based on some characteristics of hypercompetition, was also found, whereas attitudes towards self-developmental competition had a mediated negative influence. Neither constructive nor destructive competitive classroom climate had a significant impact on academic dishonesty. Acceptance of cheating and guilt has significant and direct effect on self-reported cheating. In comparison with them, the effects of motivational and competition-related variables are relatively small, even negligible. These results suggest that extrinsic motivation and competition are not amongst the most reliable predictors of academic cheating behavior.

  10. Lymphopenia as a predictor of sarcoidosis in patients with uveitis.

    Science.gov (United States)

    Jones, N P; Tsierkezou, L; Patton, N

    2016-10-01

    To investigate the hypothesis that lymphopenia is an independent predictor of sarcoidosis in new patients presenting with uveitis. Retrospective case-control study of 112 patients with sarcoidosis-associated uveitis (SAU) against 398 controls with other forms of uveitis. Of the patients with SAU, 30/112 (26.8%) had significant lymphopenia (uveitis (p≤0.0001, OR 5.7 (95% CI 3.2 to 10.3)). The mean lymphocyte count for patients with SAU was 1.43 vs 2.04 for other uveitis (p≤0.0001). Logistic regression modelling using diagnosis of SAU as the independent variable identified age, ACE levels and lymphocyte count as independent predictors of SAU. A new patient with uveitis with significant lymphopenia has a risk of sarcoidosis (from this parameter alone) of 31.6%. Significant lymphopenia (uveitis. We recommend that diagnostic criteria for SAU should be modified to include this phenomenon. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  11. Are competition and extrinsic motivation reliable predictors of academic cheating?

    Science.gov (United States)

    Orosz, Gábor; Farkas, Dávid; Roland-Lévy, Christine

    2013-01-01

    Previous studies suggest that extrinsic motivation and competition are reliable predictors of academic cheating. The aim of the present questionnaire study was to separate the effects of motivation- and competition-related variables on academic cheating by Hungarian high school students (N = 620, M = 264, F = 356). Structural equation modeling showed that intrinsic motivation has a negative effect, and amotivation has a positive indirect effect on self-reported academic cheating. In contrast, extrinsic motivation had no significant effect. Indirect positive influence on cheating, based on some characteristics of hypercompetition, was also found, whereas attitudes toward self-developmental competition had a mediated negative influence. Neither constructive nor destructive competitive classroom climate had a significant impact on academic dishonesty. Acceptance of cheating and guilt has significant and direct effect on self-reported cheating. In comparison with them, the effects of motivational and competition-related variables are relatively small, even negligible. These results suggest that extrinsic motivation and competition are not amongst the most reliable predictors of academic cheating behavior.

  12. Predictors of Institutionalization of Dementia Patients in Mild and Moderate Stages: A 4-Year Prospective Analysis

    Directory of Open Access Journals (Sweden)

    Kathrin Eska

    2013-11-01

    Full Text Available Background: Institutionalization is the most important milestone in the care of dementia patients. This study was aimed at identifying relevant predictors of institutionalization in a broad empirical context and interpreting them on the basis of the predictor model proposed by Luppa et al. [Dement Geriatr Cogn Disord 2008;26:65-78]. Methods: At the start of this study, 357 patients with mild to moderate dementia were examined by their general practitioners, and a telephone interview was conducted with their caregivers. Four years later, the outcomes ‘institutionalization' and ‘death' were determined from health insurance data. Forty-one variables were examined for their predictive influence by univariate and multivariate Cox regression. Results: The risk of institutionalization increased significantly (p ≤ 0.05 with older ages of patients [hazard ratio (HR = 1.05] and caregivers (HR = 1.03, a higher educational level of the caregiver (HR = 1.83, greater use of community health services (HR = 1.59, greater caregiver burden (HR = 1.02, and when the caregiver and patient lived apart (HR = 1.97. Conclusion: The results show that there is a multifactorial influence on institutionalization of dementia patients by sociodemographic, health-related, and psychological aspects as well as the care situation, thus validating the predictor model by Luppa et al. [Dement Geriatr Cogn Disord 2008;26:65-78]. Caregiver burden was found to be the strongest predictor accessible to interventions.

  13. Predictors of Career Adaptability Skill among Higher Education Students in Nigeria

    Directory of Open Access Journals (Sweden)

    Amos Shaibu Ebenehi

    2016-12-01

    Full Text Available This paper examined predictors of career adaptability skill among higher  education students in Nigeria. A sample of 603 higher education students randomly selected from six colleges of education in Nigeria participated in this study.  A set of self-reported questionnaire was used for data collection, and multiple linear regression analysis was used to analyze the data.  Results indicated that 33.3% of career adaptability skill was explained by the model.  Four out of the five predictor variables significantly predicted career adaptability skill among higher education students in Nigeria.  Among the four predictors, career self-efficacy sources was the most statistically significant predictor of career adaptability skill among higher education students in Nigeria, followed by personal goal orientation, career future concern, and perceived social support respectively.  Vocational identity did not statistically predict career adaptability skill among higher education students in Nigeria.  The study suggested that similar study should be replicated in other parts of the world in view of the importance of career adaptability skill to the smooth transition of graduates from school to the labor market.  The study concluded by requesting stakeholders of higher institutions in Nigeria to provide career exploration database for the students, and encourage career intervention program in order to enhance career adaptability skill among the students.

  14. End-to-end models for marine ecosystems: Are we on the precipice of a significant advance or just putting lipstick on a pig?

    Directory of Open Access Journals (Sweden)

    Kenneth A. Rose

    2012-02-01

    Full Text Available There has been a rapid rise in the development of end-to-end models for marine ecosystems over the past decade. Some reasons for this rise include need for predicting effects of climate change on biota and dissatisfaction with existing models. While the benefits of a well-implemented end-to-end model are straightforward, there are many challenges. In the short term, my view is that the major role of end-to-end models is to push the modelling community forward, and to identify critical data so that these data can be collected now and thus be available for the next generation of end-to-end models. I think we should emulate physicists and build theoretically-oriented models first, and then collect the data. In the long-term, end-to-end models will increase their skill, data collection will catch up, and end-to-end models will move towards site-specific applications with forecasting and management capabilities. One pathway into the future is individual efforts, over-promise, and repackaging of poorly performing component submodels (“lipstick on a pig”. The other pathway is a community-based collaborative effort, with appropriate caution and thoughtfulness, so that the needed improvements are achieved (“significant advance”. The promise of end-to-end modelling is great. We should act now to avoid missing a great opportunity.

  15. Stroke Location Is an Independent Predictor of Cognitive Outcome.

    Science.gov (United States)

    Munsch, Fanny; Sagnier, Sharmila; Asselineau, Julien; Bigourdan, Antoine; Guttmann, Charles R; Debruxelles, Sabrina; Poli, Mathilde; Renou, Pauline; Perez, Paul; Dousset, Vincent; Sibon, Igor; Tourdias, Thomas

    2016-01-01

    On top of functional outcome, accurate prediction of cognitive outcome for stroke patients is an unmet need with major implications for clinical management. We investigated whether stroke location may contribute independent prognostic value to multifactorial predictive models of functional and cognitive outcomes. Four hundred twenty-eight consecutive patients with ischemic stroke were prospectively assessed with magnetic resonance imaging at 24 to 72 hours and at 3 months for functional outcome using the modified Rankin Scale and cognitive outcome using the Montreal Cognitive Assessment (MoCA). Statistical maps of functional and cognitive eloquent regions were derived from the first 215 patients (development sample) using voxel-based lesion-symptom mapping. We used multivariate logistic regression models to study the influence of stroke location (number of eloquent voxels from voxel-based lesion-symptom mapping maps), age, initial National Institutes of Health Stroke Scale and stroke volume on modified Rankin Scale and MoCA. The second part of our cohort was used as an independent replication sample. In univariate analyses, stroke location, age, initial National Institutes of Health Stroke Scale, and stroke volume were all predictive of poor modified Rankin Scale and MoCA. In multivariable analyses, stroke location remained the strongest independent predictor of MoCA and significantly improved the prediction compared with using only age, initial National Institutes of Health Stroke Scale, and stroke volume (area under the curve increased from 0.697-0.771; difference=0.073; 95% confidence interval, 0.008-0.155). In contrast, stroke location did not persist as independent predictor of modified Rankin Scale that was mainly driven by initial National Institutes of Health Stroke Scale (area under the curve going from 0.840 to 0.835). Similar results were obtained in the replication sample. Stroke location is an independent predictor of cognitive outcome (MoCA) at 3

  16. Predictors of serum polychlorinated biphenyl concentrations in Anniston residents

    Science.gov (United States)

    Pavuk, M.; Olson, J.R.; Wattigney, W.A.; Dutton, N.D.; Sjödin, A.; Shelton, C.; Turner, W.E.; Bartell, S.M.; Bartell, S.; Carpenter, D.O.; Cash, J.; Foushee, R.; Percy, A.; Frumkin, H.; Lavender, M.; Moysich, K.; Olson, J.; Pavuk, M.; Rosenbaum, P.; Silverstone, A.; Weinstock, R.; Shelton, C.

    2015-01-01

    The Anniston Community Health Survey was a community-based cross-sectional study of Anniston, Alabama, residents who live in close proximity to a former PCB production facility to identify factors associated with serum PCB levels. The survey comprises 765 Anniston residents who completed a questionnaire interview and provided a blood sample for analysis in 2005–2007. Several reports based on data from the Anniston survey have been previously published, including associations between PCB exposure and diabetes and blood pressure. In this study we examine demographic, behavioral, dietary, and occupational characteristics of Anniston survey participants as predictors of serum PCB concentrations. Of the 765 participants, 54% were White and 45% were African-American; the sample was predominantly female (70%), with a mean age of 55 years. Serum PCB concentrations varied widely between participants (range for sum of 35 PCBs: 0.11–170.4 ng/g wet weight). Linear regression models with stepwise selection were employed to examine factors associated with serum PCBs. Statistically significant positive associations were observed between serum PCB concentrations and age, race, residential variables, current smoking, and local fish consumption, as was a negative association with education level. Age and race were the most influential predictors of serum PCB levels. A small age by sex interaction was noted, indicating that the increase in PCB levels with age was steeper for women than for men. Significant interaction terms indicated that the associations between PCB levels and having ever eaten locally raised livestock and local clay were much stronger among African-Americans than among White participants. In summary, demographic variables and past consumption of locally produced foods were found to be the most important predictors of PCB concentrations in residents living in the vicinity of a former PCB manufacturing facility. PMID:25115605

  17. Predictors of successful transition to registered nurse.

    Science.gov (United States)

    Phillips, Craig; Esterman, Adrian; Smith, Colleen; Kenny, Amanda

    2013-06-01

    To identify predictors of successful transition from undergraduate student to registered nurse and to identify whether any particular pre-registration paid employment choice impacted on transition. Nursing students in Australia and internationally, engage in a variety of paid employment whilst completing their university studies. However, there is little empirical evidence about the different types of employment chosen by students and any relationship to graduate nurse transition. A descriptive questionnaire survey. This cross-sectional study was conducted with newly graduated nurses throughout Australia. The survey data were collected over 4 months in 2011, with 392 registered nurses completing a questionnaire. Respondents were categorized into four groups, according to their chosen work type (hospitality/retail, enrolled nurse, other healthcare worker, and non-worker) and transition scores were identified. Transition scores were significantly higher for undergraduates who were employed compared with non-workers. Postregistration institutional work factors appeared to be stronger predictors of successful transition than pre-registration employment factors. Assistance in dealing with complex patients, orientation to a new environment, and respect from colleagues were the best predictors for successful transition. Engaging in some form of paid employment in the final year of undergraduate university study is beneficial. However, it is not pre-registration employment choice per se that is the best predictor of successful transition, but the influence of work factors which new graduates experience in their first year of practice. © 2012 Blackwell Publishing Ltd.

  18. Calculation of limits for significant unidirectional changes in two or more serial results of a biomarker based on a computer simulation model

    DEFF Research Database (Denmark)

    Lund, Flemming; Petersen, Per Hyltoft; Fraser, Callum G

    2015-01-01

    concept on more than two results will increase the number of false-positive results. Therefore, a simple method is needed to interpret the significance of a difference when all available serial biomarker results are considered. METHODS: A computer simulation model using Excel was developed. Based on 10...

  19. Developmental, Component-Based Model of Reading Fluency: An Investigation of Predictors of Word-Reading Fluency, Text-Reading Fluency, and Reading Comprehension

    Science.gov (United States)

    Kim, Young-Suk Grace

    2015-01-01

    The primary goal was to expand our understanding of text reading fluency (efficiency or automaticity)—how its relation to other constructs (e.g., word reading fluency and reading comprehension) changes over time and how it is different from word reading fluency and reading comprehension. We examined (1) developmentally changing relations among word reading fluency, listening comprehension, text reading fluency, and reading comprehension; (2) the relation of reading comprehension to text reading fluency; (3) unique emergent literacy predictors (i.e., phonological awareness, orthographic awareness, morphological awareness, letter name knowledge, vocabulary) of text reading fluency vs. word reading fluency; and (4) unique language and cognitive predictors (e.g., vocabulary, grammatical knowledge, theory of mind) of text reading fluency vs. reading comprehension. These questions were addressed using longitudinal data (two timepoints; Mean age = 5;24 & 6;08) from Korean-speaking children (N = 143). Results showed that listening comprehension was related to text reading fluency at time 2, but not at time 1. At both times text reading fluency was related to reading comprehension, and reading comprehension was related to text reading fluency over and above word reading fluency and listening comprehension. Orthographic awareness was related to text reading fluency over and above other emergent literacy skills and word reading fluency. Vocabulary and grammatical knowledge were independently related to text reading fluency and reading comprehension whereas theory of mind was related to reading comprehension, but not text reading fluency. These results reveal developmental nature of relations and mechanism of text reading fluency in reading development. PMID:26435550

  20. Developmental, Component-Based Model of Reading Fluency: An Investigation of Predictors of Word-Reading Fluency, Text-Reading Fluency, and Reading Comprehension.

    Science.gov (United States)

    Kim, Young-Suk Grace

    2015-01-01

    The primary goal was to expand our understanding of text reading fluency (efficiency or automaticity)-how its relation to other constructs (e.g., word reading fluency and reading comprehension) changes over time and how it is different from word reading fluency and reading comprehension. We examined (1) developmentally changing relations among word reading fluency, listening comprehension, text reading fluency, and reading comprehension; (2) the relation of reading comprehension to text reading fluency; (3) unique emergent literacy predictors (i.e., phonological awareness, orthographic awareness, morphological awareness, letter name knowledge, vocabulary) of text reading fluency vs. word reading fluency; and (4) unique language and cognitive predictors (e.g., vocabulary, grammatical knowledge, theory of mind) of text reading fluency vs. reading comprehension. These questions were addressed using longitudinal data (two timepoints; Mean age = 5;24 & 6;08) from Korean-speaking children (N = 143). Results showed that listening comprehension was related to text reading fluency at time 2, but not at time 1. At both times text reading fluency was related to reading comprehension, and reading comprehension was related to text reading fluency over and above word reading fluency and listening comprehension. Orthographic awareness was related to text reading fluency over and above other emergent literacy skills and word reading fluency. Vocabulary and grammatical knowledge were independently related to text reading fluency and reading comprehension whereas theory of mind was related to reading comprehension, but not text reading fluency. These results reveal developmental nature of relations and mechanism of text reading fluency in reading development.

  1. Using chi-Squared Automatic Interaction Detection (CHAID) modelling to identify groups of methadone treatment clients experiencing significantly poorer treatment outcomes.

    Science.gov (United States)

    Murphy, Emma L; Comiskey, Catherine M

    2013-10-01

    In times of scarce resources it is important for services to make evidence based decisions when identifying clients with poor outcomes. chi-Squared Automatic Interaction Detection (CHAID) modelling was used to identify characteristics of clients experiencing statistically significant poor outcomes. A national, longitudinal study recruited and interviewed, using the Maudsley Addiction Profile (MAP), 215 clients starting methadone treatment and 78% were interviewed one year later. Four CHAID analyses were conducted to model the interactions between the primary outcome variable, used heroin in the last 90 days prior to one year interview and variables on drug use, treatment history, social functioning and demographics. Results revealed that regardless of these other variables, males over 22 years of age consistently demonstrated significantly poorer outcomes than all other clients. CHAID models can be easily applied by service providers to provide ongoing evidence on clients exhibiting poor outcomes and requiring priority within services.

  2. Predictors of mortality in children with lupus nephritis

    Directory of Open Access Journals (Sweden)

    Lukman Oktadianto

    2014-11-01

    Full Text Available Background Renal involvement during the clinical course of systemic lupus erythematosus (SLE is generally considered to be the most important factor influencing disease prognosis in terms of morbidity and mortality. Various factors have been reported to influence the prognosis of lupus nephritis (LN. Objective To analyze clinical signs and laboratory parameters that might serve as predictors associated with mortality in pediatric LN. Methods Retrospectively, medical records of children with LN at Soetomo Hospital from 1998 to 2011 were studied. Diagnosis of SLE was based on Revised American Rheumatism Association critera, while patients with clinical manifestations of hypertension, abnormal urinalysis, and serum creatinin > 1 mg/dL were considered as lupus nephritis. Cox proportional hazard modeling was used to assess for associations of clinical signs and laboratory parameters with mortality. Kaplan-Meier survival analysis was used to assess the cumulative survival from the time of diagnosis to the outcome. Results There were 57 children with LN of whom 43 (75% were girls. The female-to-male ratio was 3:1. Subjects’ mean age was 10.6 (SD 6.87 years. The mean time of observation was 51 (SD 74.54 months and 23 (40% children died. Age, gender, hypertension, hematuria, proteinuria, and anemia were not significant as predictors for mortality. However, hypertensive crisis (HR=2.79; 95%CI 1.16 to 6.75; P=0.02 and initial glomerular filtration rate (GFR of <75 mL/min/1.73m2 (HR=3.01; 95%CI 1.23 to 7.34; P=0.01 were significant predictors of mortality in children with LN. The mean survival time of LN with hypertensive crisis and initial GFR <75 mL/min/1.73m2 was 36.9 (SD 12.17 months. Conclusion Hypertensive crisis and GFR <75 mL/min/1.73m2 are significant predictors of mortality in children with LN. [Paediatr Indones. 2014;54:338-43.].

  3. Predictor-Year Subspace Clustering Based Ensemble Prediction of Indian Summer Monsoon

    Directory of Open Access Journals (Sweden)

    Moumita Saha

    2016-01-01

    Full Text Available Forecasting the Indian summer monsoon is a challenging task due to its complex and nonlinear behavior. A large number of global climatic variables with varying interaction patterns over years influence monsoon. Various statistical and neural prediction models have been proposed for forecasting monsoon, but many of them fail to capture variability over years. The skill of predictor variables of monsoon also evolves over time. In this article, we propose a joint-clustering of monsoon years and predictors for understanding and predicting the monsoon. This is achieved by subspace clustering algorithm. It groups the years based on prevailing global climatic condition using statistical clustering technique and subsequently for each such group it identifies significant climatic predictor variables which assist in better prediction. Prediction model is designed to frame individual cluster using random forest of regression tree. Prediction of aggregate and regional monsoon is attempted. Mean absolute error of 5.2% is obtained for forecasting aggregate Indian summer monsoon. Errors in predicting the regional monsoons are also comparable in comparison to the high variation of regional precipitation. Proposed joint-clustering based ensemble model is observed to be superior to existing monsoon prediction models and it also surpasses general nonclustering based prediction models.

  4. Comparison of Designated Coefficients and their Predictors in Functional Evaluation of Wheelchair Rugby Athletes

    Directory of Open Access Journals (Sweden)

    Zwierzchowska Anna

    2015-12-01

    Full Text Available The objectives of the present study were twofold: to determine differences between groups by means of chosen coefficients and to create significant predictors using regression models for athletes in wheelchair rugby who had the same spinal cord injury (tetraplegia and were classified as low point and high point players. The study sample consisted of 24 subjects, who had sustained cervical spinal cord injury (CSCI. They were divided into low point (n=15 and high point (n=9 groups according to the IWRF Classification System. A one-way ANOVA revealed statistically significant differences in the following coefficients differentiating the groups: AC (η2=0.778, LC (η2=0.687, IC (η2=0.565, SC (η2=0.580. The Tukey’s HSD post-hoc test indicated statistically significant higher values of coefficients in the HP compared to the LP group: AC=0.958 (p=0.022, LC=0.989 (p=0.031, IC=0.971 (p=0.044, SC=0.938 (p=0.039. In the HP group, the most significant predictor was the sum of visceral and trunk fat which was negatively correlated with the SC (what constituted a positive adaptive change in response to training. With regard to the LP group, body height and circumference of the chest appeared to be most significant predictors and were positively correlated with the SC. In the LP group no predictor with respect to the SC was significantly correlated to sports training. Therefore, the functional classification system confirmed lower status of the LP players. The results of the present study indicate that both metabolic and somatic profiles which highly determine potential of wheelchair rugby athletes are significantly different in LP and HP players, what confirms the reliability of the functional classification system.

  5. Language-minority learners in special education: rates and predictors of identification for services.

    Science.gov (United States)

    Samson, Jennifer F; Lesaux, Nonie K

    2009-01-01

    Using data from the Early Childhood Longitudinal Study-Kindergarten Cohort, this study was designed to investigate proportional representation, identification rates, and predictors of language-minority (LM) learners in special education using a nationally representative sample of kindergarten, first graders, and third graders. The findings indicate that although LM learners were underrepresented in special education in kindergarten and first grade, they were overrepresented in third grade across all disability categories. LM status, teacher ratings of language and literacy skills, and reading proficiency level were significant predictors of placement in special education. Kindergarten teacher ratings of language and literacy skills were highly predictive of subsequent placement in special education. The implications for developing a model of early identification, the response-to-intervention model in particular, for LM learners at risk for academic difficulties are discussed.

  6. Predictors of breast self-examination performance among Jordanian university female students.

    Science.gov (United States)

    Abu Sharour, L; Al-Ghabeesh, S; Suleiman, K; Salameh, A B; Jacoob, S; Al-Kalaldeh, M

    2016-12-27

    Breast cancer is considered one of the main types of cancer among female worldwide and in Jordan also. Early detection of it will improve the prognosis and decrease the mortality rate also. Thus, this study was conducted to assess the predictors of breast self-examination performance among Jordanian university female students. Across-sectional design was utilised in this study. A sample of 100 participants was completed the study survey (The Champion's Health Belief Model Scale). The main results or regression analysis showed that confidence (β = .71, p breast self-examination performance. In summary, other variables of Health belief model were found not be significant indicators of BSE performance in this study. However, the HBM is considered a valid framework to assess the predictors of breast self-examination knowledge, attitude, beliefs and barriers among Jordanian college female students.

  7. Cognitive and affective predictors of smoking after a sentinel health event.

    Science.gov (United States)

    Boudreaux, Edwin D; Abar, Beau; O'Hea, Erin; Sullivan, Ashley F; Cydulka, Rita; Bernstein, Steven L; Camargo, Carlos A

    2014-01-01

    This study examined how smoking-related causal attributions, perceived illness severity, and event-related emotions relate to both intentions to quit and subsequent smoking behavior after an acute medical problem (sentinel event). Three hundred and seventy-five patients were enrolled from 10 emergency departments (EDs) across the USA and followed for six months. Two saturated, manifest structural equation models were performed: one predicting quit attempts and the other predicting seven-day point prevalence abstinence at 14 days, three months, and six months after the index ED visit. Stage of change was regressed onto each of the other predictor variables (causal attribution, perceived illness severity, event-related emotions) and covariates, and tobacco cessation outcomes were regressed on all of the predictor variables and covariates. Non-White race, baseline stage of change, and an interaction between causal attribution and event-related fear were the strongest predictors of quit attempt. In contrast, abstinence at six months was most strongly predicted by baseline stage of change and nicotine dependence. Predictors of smoking behavior after an acute medical illness are complex and dynamic. The relations vary depending on the outcome examined (quit attempts vs. abstinence), differ based on the time that has progressed since the event, and include significant interactions.

  8. Predictors of Traditional and Cyber-Bullying Victimization: A Longitudinal Study of Australian Secondary School Students.

    Science.gov (United States)

    Hemphill, Sheryl A; Tollit, Michelle; Kotevski, Aneta; Heerde, Jessica A

    2015-09-01

    The purpose of the present article is to compare the individual, peer, family, and school risk and protective factors for both traditional and cyber-bullying victimization. This article draws on data from 673 students from Victoria, Australia, to examine Grade 7 (aged 12-13 years) predictors of traditional and cyber-bullying victimization in Grade 9 (aged 14-15 years). Participants completed a modified version of the Communities That Care youth survey. There were few similarities and important differences in the predictors of traditional and cyber-bullying victimization. For Grade 9 cyber-bullying victimization, in the fully adjusted model, having been a victim of traditional bullying in Grade 7 and emotional control in Grade 7 were predictors. For Grade 9 traditional bullying victimization, predictors were Grade 7 traditional bullying victimization, association with antisocial peers, and family conflict, with family attachment and emotional control marginally statistically significant. The use of evidence-based bullying prevention programs is supported to reduce experiences of both traditional and cyber-bullying victimization, as is the implementation of programs to assist students to regulate their emotions effectively. In addition, traditional bullying victimization may be reduced by addressing association with antisocial friends, family conflict, and bonding to families. © The Author(s) 2014.

  9. Have we been ignoring physiological plasticity and genetic variation in stomatal function as a significant source of error in models of water and carbon fluxes?

    Science.gov (United States)

    Wertin, T. M.; Wolz, K.; Richter, K.; Adorbo, M.; Betzelberger, A. M.; Leakey, A.

    2013-12-01

    Accurately predicting plant and ecosystem function across climatic and ecological gradients requires properly parameterized models of both net photosynthetic assimilation of CO2 and stomatal conductance. Photosynthesis models have been parameterized to account for physiological plasticity and genetic variation for decades. However, models describing physiological plasticity or genetic variation in the sensitivity of stomatal conductance to net photosynthetic CO2 assimilation (A), relative humidity (RH), and atmospheric [CO2] have rarely, if ever, been applied. There is no mechanistic basis for the prevailing assumption that models of stomatal conductance can share a universal parameterization for all C3 species. Twelve species of temperate trees were grown in a common garden to test species-specific sensitivity of stomatal conductance to A, RH and [CO2]. Additionally, a Salix and a Populus genotype, grown at three locations throughout the Eastern US in biofuels trails, were measured at three times during the growing season to test for temporal and spatial effects. Soybean was also grown at eight ozone concentrations to test for physiological plasticity in stomatal function. Laboratory-based gas exchange measurements were used to parameterize the widely used Ball et al. (1987) model of stomatal conductance and the Farquhar et al. (1980) model of photosynthesis. These models were coupled to each other and a leaf energy balance model in order to predict in situ leaf CO2 and water fluxes which were compared against field measurements. There was significant physiological plasticity and genetic variation in the sensitivity of stomatal conductance to A, RH and [CO2]. This was reflected in significant variation in parameters of the Ball et al. (1987) model, with the key slope parameter (m) ranging from more than 4-fold. Context-specific parameterization of this widely used stomatal conductance model reduced error in predictions of in situ leaf A and gs by up to 59

  10. Epigenetic predictor of age.

    Directory of Open Access Journals (Sweden)

    Sven Bocklandt

    Full Text Available From the moment of conception, we begin to age. A decay of cellular structures, gene regulation, and DNA sequence ages cells and organisms. DNA methylation patterns change with increasing age and contribute to age related disease. Here we identify 88 sites in or near 80 genes for which the degree of cytosine methylation is significantly correlated with age in saliva of 34 male identical twin pairs between 21 and 55 years of age. Furthermore, we validated sites in the promoters of three genes and replicated our results in a general population sample of 31 males and 29 females between 18 and 70 years of age. The methylation of three sites--in the promoters of the EDARADD, TOM1L1, and NPTX2 genes--is linear with age over a range of five decades. Using just two cytosines from these loci, we built a regression model that explained 73% of the variance in age, and is able to predict the age of an individual with an average accuracy of 5.2 years. In forensic science, such a model could estimate the age of a person, based on a biological sample alone. Furthermore, a measurement of relevant sites in the genome could be a tool in routine medical screening to predict the risk of age-related diseases and to tailor interventions based on the epigenetic bio-age instead of the chronological age.

  11. Parenting style and peer attachment as predictors of emotional instability in children

    National Research Council Canada - National Science Library

    Llorca-Mestre, Anna; Cortes-Tomas, Maria Teresa; Samper-Garcia, Paula; Malonda-Vidal, Elisabet

    2017-01-01

    .... Considering emotional and cognitive variables, the results for our participant group show that parenting styles and peer attachment were equally significant as predictors of emotional instability. Keyword...

  12. Smith Predictor Based Robust Rapid Tracking Controller

    Institute of Scientific and Technical Information of China (English)

    LIU Hongbin; HU Dejin

    2006-01-01

    Precise model is hard to get in real application, a Smith predictor based robust rapid tracking controller for inaccurate model is proposed. Zero phase error feedforward controller which increases system closed-loop dynamics and disturbance observer based Smith feedback control which diminishes model hysteresis and improves stability are integrated. This method is applied in the noncircular machining with piezoelectric ceramic driver. The simulation and experiment show that the performance robustness and stability are well balanced in bandwidth about 200 Hz. The controller can decrease system hysteresis and get good tracking performance for predefined square-wave input signal.

  13. Long-lead probabilistic forecasting of streamflow using ocean-atmospheric and hydrological predictors

    Science.gov (United States)

    Araghinejad, Shahab; Burn, Donald H.; Karamouz, Mohammad

    2006-03-01

    A geostatistically based approach with a local regression method is used to predict the magnitude of seasonal streamflow using ocean-atmospheric signals and the hydrological condition of a basin as predictors. The model characterizes the stochastic behavior of a forecast variable by generating a conditional distribution of the predicted value for different hydroclimatic conditions. The correlation structure between dependent and independent variables is represented by the variography of the predicted values in which the distance variable in the variogram is determined by measuring the distance between the predictors. This variogram in a virtual field constructed from the predictors makes it possible to predict variables as unmeasured points while considering historic information as measurement points of the field. Different types of kriging, as well as a generalized linear model regression, are used to predict data in interpolation and extrapolation modes. The forecast skill is evaluated using a linear error in probability space score for different combinations of predictors and different kriging methods. The method is applied to a case study of the Zayandeh-rud River in Isfahan, Iran. The utility of the method is demonstrated for forecasting autumn-winter and spring streamflow using the Southern Oscillation Index, the North Atlantic Oscillation, serial correlation between seasonal streamflow series, and the snow budget. The study analyzes the application of the proposed method in comparison with a K-nearest neighbor regression method. The results of this study show that the proposed method can significantly improve the long-lead probabilistic forecast skill for a nonlinear relationship between hydroclimatic predictors and streamflow in a region.

  14. Predicting Survival from Telomere Length versus Conventional Predictors: A Multinational Population-Based Cohort Study.

    Science.gov (United States)

    Glei, Dana A; Goldman, Noreen; Risques, Rosa Ana; Rehkopf, David H; Dow, William H; Rosero-Bixby, Luis; Weinstein, Maxine

    2016-01-01

    Telomere length has generated substantial interest as a potential predictor of aging-related diseases and mortality. Some studies have reported significant associations, but few have tested its ability to discriminate between decedents and survivors compared with a broad range of well-established predictors that include both biomarkers and commonly collected self-reported data. Our aim here was to quantify the prognostic value of leukocyte telomere length relative to age, sex, and 19 other variables for predicting five-year mortality among older persons in three countries. We used data from nationally representative surveys in Costa Rica (N = 923, aged 61+), Taiwan (N = 976, aged 54+), and the U.S. (N = 2672, aged 60+). Our study used a prospective cohort design with all-cause mortality during five years post-exam as the outcome. We fit Cox hazards models separately by country, and assessed the discriminatory ability of each predictor. Age was, by far, the single best predictor of all-cause mortality, whereas leukocyte telomere length was only somewhat better than random chance in terms of discriminating between decedents and survivors. After adjustment for age and sex, telomere length ranked between 15th and 17th (out of 20), and its incremental contribution was small; nine self-reported variables (e.g., mobility, global self-assessed health status, limitations with activities of daily living, smoking status), a cognitive assessment, and three biological markers (C-reactive protein, serum creatinine, and glycosylated hemoglobin) were more powerful predictors of mortality in all three countries. Results were similar for cause-specific models (i.e., mortality from cardiovascular disease, cancer, and all other causes combined). Leukocyte telomere length had a statistically discernible, but weak, association with mortality, but it did not predict survival as well as age or many other self-reported variables. Although telomere length may eventually help scientists

  15. Subjective cognitive concerns and neuropsychiatric predictors of progression to the early clinical stages of Alzheimer disease.

    Science.gov (United States)

    Donovan, Nancy J; Amariglio, Rebecca E; Zoller, Amy S; Rudel, Rebecca K; Gomez-Isla, Teresa; Blacker, Deborah; Hyman, Bradley T; Locascio, Joseph J; Johnson, Keith A; Sperling, Reisa A; Marshall, Gad A; Rentz, Dorene M

    2014-12-01

    To examine neuropsychiatric and neuropsychological predictors of progression from normal to early clinical stages of Alzheimer disease (AD). From a total sample of 559 older adults from the Massachusetts Alzheimer's Disease Research Center longitudinal cohort, 454 were included in the primary analysis: 283 with clinically normal cognition (CN), 115 with mild cognitive impairment (MCI), and 56 with subjective cognitive concerns (SCC) but no objective impairment, a proposed transitional group between CN and MCI. Two latent cognitive factors (memory-semantic, attention-executive) and two neuropsychiatric factors (affective, psychotic) were derived from the Alzheimer's Disease Centers' Uniform Data Set neuropsychological battery and Neuropsychiatric Inventory brief questionnaire. Factors were analyzed as predictors of time to progression to a worse diagnosis using a Cox proportional hazards regression model with backward elimination. Covariates included baseline diagnosis, gender, age, education, prior depression, antidepressant medication, symptom duration, and interaction terms. Higher/better memory-semantic factor score predicted lower hazard of progression (hazard ratio [HR] = 0.4 for 1 standard deviation [SD] increase, p <0.0001), and higher/worse affective factor score predicted higher hazard (HR = 1.3 for one SD increase, p = 0.01). No other predictors were significant in adjusted analyses. Using diagnosis as a sole predictor of transition to MCI, the SCC diagnosis carried a fourfold risk of progression compared with CN (HR = 4.1, p <0.0001). These results identify affective and memory-semantic factors as significant predictors of more rapid progression from normal to early stages of cognitive decline and highlight the subgroup of cognitively normal elderly with SCC as those with elevated risk of progression to MCI. Copyright © 2014 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

  16. Predicting significant torso trauma.

    Science.gov (United States)

    Nirula, Ram; Talmor, Daniel; Brasel, Karen

    2005-07-01

    Identification of motor vehicle crash (MVC) characteristics associated with thoracoabdominal injury would advance the development of automatic crash notification systems (ACNS) by improving triage and response times. Our objective was to determine the relationships between MVC characteristics and thoracoabdominal trauma to develop a torso injury probability model. Drivers involved in crashes from 1993 to 2001 within the National Automotive Sampling System were reviewed. Relationships between torso injury and MVC characteristics were assessed using multivariate logistic regression. Receiver operating characteristic curves were used to compare the model to current ACNS models. There were a total of 56,466 drivers. Age, ejection, braking, avoidance, velocity, restraints, passenger-side impact, rollover, and vehicle weight and type were associated with injury (p < 0.05). The area under the receiver operating characteristic curve (83.9) was significantly greater than current ACNS models. We have developed a thoracoabdominal injury probability model that may improve patient triage when used with ACNS.

  17. Psychosocial predictors of treatment outcome for trauma-affected refugees

    Directory of Open Access Journals (Sweden)

    Charlotte Sonne

    2016-05-01

    Full Text Available Background: The effects of treatment in trials with trauma-affected refugees vary considerably not only between studies but also between patients within a single study. However, we know little about why some patients benefit more from treatment, as few studies have analysed predictors of treatment outcome. Objective: The objective of the study was to examine possible psychosocial predictors of treatment outcome for trauma-affected refugees. Method: The participants were 195 adult refugees with posttraumatic stress disorder (PTSD who were enrolled in a 6- to 7-month treatment programme at the Competence Centre for Transcultural Psychiatry (CTP, Denmark. The CTP Predictor Index used in the study included 15 different possible outcome predictors concerning the patients’ past, chronicity of mental health problems, pain, treatment motivation, prerequisites for engaging in psychotherapy, and social situation. The primary outcome measure was PTSD symptoms measured on the Harvard Trauma Questionnaire (HTQ. Other outcome measures included the Hopkins Symptom Check List-25, the WHO-5 Well-being Index, Sheehan Disability Scale, Hamilton Depression and Anxiety Scales, the somatisation scale of the Symptoms Checklist-90, Global Assessment of Functioning scales, and pain rated on visual analogue scales. The relations between treatment outcomes and the total score as well as subscores of the CTP Predictor Index were analysed. Results: Overall, the total score of the CTP Predictor Index was significantly correlated to pre- to post treatment score changes on the majority of the ratings mentioned above. While employment status was the only single item significantly correlated to HTQ-score changes, a number of single items from the CTP Predictor Index correlated significantly with changes in depression and anxiety symptoms, but the size of the correlation coefficients were modest. Conclusions: The total score of the CTP Predictor Index correlated significantly

  18. Modeling, Analysis, and Control of a Hypersonic Vehicle with Significant Aero-Thermo-Elastic-Propulsion Interactions: Elastic, Thermal and Mass Uncertainty

    Science.gov (United States)

    Khatri, Jaidev

    This thesis examines themodeling, analysis, and control system design issues for scramjet powered hypersonic vehicles. A nonlinear three degrees of freedom longitudinal model which includes aero-propulsion-elasticity effects was used for all analyses. This model is based upon classical compressible flow and Euler-Bernouli structural concepts. Higher fidelity computational fluid dynamics and finite element methods are needed for more precise intermediate and final evaluations. The methods presented within this thesis were shown to be useful for guiding initial control relevant design. The model was used to examine the vehicle's static and dynamic characteristics over the vehicle's trimmable region. The vehicle has significant longitudinal coupling between the fuel equivalency ratio (FER) and the flight path angle (FPA). For control system design, a two-input two-output plant (FER - elevator to speed-FPA) with 11 states (including 3 flexible modes) was used. Velocity, FPA, and pitch were assumed to be available for feedback. Aerodynamic heat modeling and design for the assumed TPS was incorporated to original Bolender's model to study the change in static and dynamic properties. De-centralized control stability, feasibility and limitations issues were dealt with the change in TPS elasticity, mass and physical dimension. The impact of elasticity due to TPS mass, TPS physical dimension as well as prolonged heating was also analyzed to understand performance limitations of de-centralized control designed for nominal model.

  19. The significance of the interception in a Thornthwaite-type monthly step water balance model in context of the climate change

    Science.gov (United States)

    Herceg, András; Kalicz, Péter; Kisfaludi, Balázs

    2017-04-01

    The hydrological impacts of the climate change can be dramatic. Our main purpose is the methodical improvement of a previously established Thornthwaite-type monthly step water balance model, which takes the interception item into account, and compare the results of the evapotranspiration and the soil moisture projections for the 21st century of the original and the upgraded models. Both of the models will be calibrated and validated (using remote-sensed actual evapotranspiration data, called CREMAP) and requires only temperature and precipitation time series as inputs. The projections based on 4 bias-corrected regional climate models databases (FORESEE), and the 3 investigation periods are: 2015-2045, 2045-2075, and 2070-2100. The key parameter is the water storage capacity of the soil, which can be also calibrated using the actual evapotranspiration data. The maximal rooting depth is determinable if the physical properties of the soil are available. The interception can be ranges from 5-40% of gross precipitation, which rate are differing in the various plant communities. Generally, the forests canopy intercepts considerable amounts of rainfall and evaporates back into the atmosphere during and after precipitation event. Leaf area index (LAI) is one of the most significant factor, which determine the canopies storage capacity. Here, MODIS sensor based LAI time series are applied to estimate the storage capacity. A forest covered experimental catchment is utilized for testing the models near to Sopron, Hungary. The projections will expected to demonstrate increasing actual evapotranspiration values, but decreasing trends for the 10 percentile minimum soil moisture values at the end of the 21st century in both model runs. The seasonal periodicity of evapotranspiration may demonstrates the maximums in June or July, while in case of the soil moisture it may shows minimum values in autumn. With the comparison of the two model runs, we expect lower soil water storage

  20. Future of Grid-Tied PV Business Models: What Will Happen When PV Penetration on the Distribution Grid is Significant? Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Graham, S.; Katofsky, R.; Frantzis, L.; Sawyer, H.; Margolis, R.

    2008-05-01

    Eventually, distributed PV will become a more significant part of the generation mix. When this happens, it is expected that utilities will have to take on a more active role in the placement, operation and control of these systems. There are operational complexities and concerns of revenue erosion that will drive utilities into greater involvement of distributed PV and will create new business models. This report summarizes work done by Navigant Consulting Inc. for the National Renewable Energy Laboratory as part of the Department of Energy's work on Renewable System Integration. The objective of the work was to better understand the structure of these future business models and the research, development and demonstration (RD&D) required to support their deployment. This report describes potential future PV business models in terms of combinations of utility ownership and control of the PV assets, and the various relationships between end-users and third-party owners.

  1. Incorporating biologic measurements (SF(2), CFE) into a tumor control probability model increases their prognostic significance: a study in cervical carcinoma treated with radiation therapy.

    Science.gov (United States)

    Buffa, F M; Davidson, S E; Hunter, R D; Nahum, A E; West, C M

    2001-08-01

    To assess whether incorporation of measurements of surviving fraction at 2 Gy (SF(2)) and colony-forming efficiency (CFE) into a tumor control probability (tcp) model increases their prognostic significance. Measurements of SF(2) and CFE were available from a study on carcinoma of the cervix treated with radiation alone. These measurements, as well as tumor volume, dose, and treatment time, were incorporated into a Poisson tcp model (tcp(alpha,rho)). Regression analysis was performed to assess the prognostic power of tcp(alpha,rho) vs. the use of either tcp models with biologic parameters fixed to best-fit estimates (but incorporating individual dose, volume, and treatment time) or the use of SF(2) and CFE measurements alone. In a univariate regression analysis of 44 patients, tcp(alpha,rho) was a better prognostic factor for both local control and survival (p CFE alone (p = 0.015 for local control, p = 0.38 for survival). In multivariate analysis, tcp(alpha,rho) emerged as the most important prognostic factor for local control (p CFE was still a significant independent prognostic factor for local control, whereas SF(2) was not. The sensitivities of tcp(alpha,rho) and SF(2) as predictive tests for local control were 87% and 65%, respectively. Specificities were 70% and 77%, respectively. A Poisson tcp model incorporating individual SF(2), CFE, dose, tumor volume, and treatment time was found to be the best independent prognostic factor for local control and survival in cervical carcinoma patients.

  2. Serum and urinary neutrophil gelatinase-associated lipocalin as a predictor of rat kidney histopathology in an early ischemia-reperfusion model

    Directory of Open Access Journals (Sweden)

    Sahala Panggabean

    2012-11-01

    Full Text Available Background: The severity of ischemia-reperfusion (I/R kidney injury is highly correlated with mortality and morbidity rate. Research on human and animal prove that NGAL predicts kidney injury at early phase. The objective of this study is to prove that the increase in serum and urinary NGAL are correlated with kidney tubular epithelial damage, and this increase has occurred in initiation phase, indicated by rat kidney histopathology in an early I/R model.Methods: Twenty eight male Sprague-Dawley rats were divided into 4 groups: 4 hour sham (Sham 4, 8 hour sham (Sham 8, 10 minute ischemia 4 hour reperfusion (I/R 4 and 10 minute ischemia 8 hour reperfusion (I/R 8. Blood, urine and kidney samples were collected. Serum creatinine level was analyzed with Jaffe method, while serum and urinary NGAL level were analyzed with direct sandwich ELISA method. Evaluation of kidney damage were measured semi quantitatively in tissue stained with HE. Further evaluation to confirm cellular changes on kidney was performed by electron microscope and immunohistochemistry.Results: Serum NGAL was found significantly correlated with degree of kidney tissue damage (ρSpearman NGAL serum = 0.701, p < 0.001, also urinary NGAL (ρSpearman = 0.689, p < 0.001. NGAL expression differs significantly between I/R group and sham (t-test, t = -26635.056, p < 0.001, also kidney damage (t-test, t = -5.028, p < 0.001, and serum and urinary NGAL levels (Mann-Whitney, U = 0, p < 0.001. With cutoff points of 136.95 ng/mL and 58.69 ng/mL subsequently for serum and urinary NGAL , it is found that sensitivity = 1, specificity = 1.Conclusion: Elevation of serum and urinary NGAL are significantly correlated with epithelial tubular kidney damage on rat undergoing early ischaemia reperfusion. (Med J Indones. 2012;21:208-13Keywords: Early I/R kidney injury, kidney histopathology, NGAL

  3. Final Report, Distillation Column Flooding Predictor

    Energy Technology Data Exchange (ETDEWEB)

    George E. Dzyacky

    2003-05-31

    The Flooding Predictor is an advanced process control strategy comprising a patented pattern-recognition methodology that identifies pre-flood patterns discovered to precede flooding events in distillation columns. The grantee holds a U.S. patent on the modeling system. The technology was validated at the Separations Research Program, The University of Texas at Austin under a grant from the U. S. Department of Energy, Inventions & Innovation Program. Distillation tower flooding occurs at abnormally high vapor and/or liquid rates. The loss in tray efficiencies is attributed to unusual behavior of liquid inventories inside the column leading to conditions of flooding of the space in between trays with liquid. Depending on the severity of the flood condition, consequences range from off spec products to equipment damage and tower shutdown. This non-intrusive pattern recognition methodology, processes signal data obtained from existing column instrumentation. Once the pattern is identified empirically, it is modeled and coded into the plant's distributed control system. The control system is programmed to briefly "unload" the tower each time the pattern appears. The unloading takes the form of a momentary reduction in column severity, e.g., decrease bottom temperature, reflux or tower throughput. Unloading the tower briefly at the pre-flood state causes long-term column operation to become significantly more stable - allowing an increase in throughput and/or product purity. The technology provides a wide range of value between optimization and flooding. When a distillation column is not running at capacity, it should be run in such a way ("pushed") that optimal product purity is achieved. Additional benefits include low implementation and maintenance costs, and a high level of console operator acceptance. The previous commercial applications experienced 98% uptime over a four-year period. Further, the technology is unique in its ability to distinguish between

  4. Surface tensions of multi-component mixed inorganic/organic aqueous systems of atmospheric significance: measurements, model predictions and importance for cloud activation predictions

    Directory of Open Access Journals (Sweden)

    D. O. Topping

    2006-11-01

    Full Text Available In order to predict the physical properties of aerosol particles, it is necessary to adequately capture the behaviour of the ubiquitous complex organic components. One of the key properties which may affect this behaviour is the contribution of the organic components to the surface tension of aqueous particles in the moist atmosphere. Whilst the qualitative effect of organic compounds on solution surface tensions has been widely reported, our quantitative understanding on mixed organic and mixed inorganic/organic systems is limited.  Furthermore, it is unclear whether models that exist in the literature can reproduce the surface tension variability for binary and higher order multi-component organic and mixed inorganic/organic systems of atmospheric significance. The current study aims to resolve both issues to some extent. Surface tensions of single and multiple solute aqueous solutions were measured and compared with predictions from a number of model treatments. On comparison with binary organic systems, two predictive models found in the literature provided a range of values resulting from sensitivity to calculations of pure component surface tensions.  Results indicate that a fitted model can capture the variability of the measured data very well, producing the lowest average percentage deviation for all compounds studied.  The performance of the other models varies with compound and choice of model parameters. The behaviour of ternary mixed inorganic/organic systems was unreliably captured by using a predictive scheme and this was composition dependent. For more "realistic" higher order systems, entirely predictive schemes performed poorly. It was found that use of the binary data in a relatively simple mixing rule, or modification of an existing thermodynamic model with parameters derived from binary data, was able to accurately capture the surface tension variation with concentration. Thus, it would appear that in order to model

  5. Predictors of hope among women with breast cancer during chemotherapy

    Directory of Open Access Journals (Sweden)

    Alessandra Cristina Sartore Balsanelli

    Full Text Available Abstract OBJECTIVE Identifying the predictors of hope in patients with breast cancer during chemotherapy treatment. METHOD A prospective longitudinal study. The sample was composed of 122 women who responded to the instruments of hope, anxiety and depression, coping, fatigue, religiosity and self-esteem in the first and last cycle of chemotherapy. These variables were used in adjusting the logistic regression model that characterized multivariate statistics, allowing identification of predictor variables. RESULT The increase of hope at the end of chemotherapy treatment was statistically significant (p = 0.012. The delay in undergoing treatment from the onset of breast cancer symptoms, Karnofsky Performance Status, depression, self-esteem and pain were characterized as factors being associated to hope by univariate analysis. Among the variables analyzed, pain was the only predicting factor of hope. CONCLUSION Pain was the predicting factor in this sample. Hope increased during treatment and revealed the following associated factors: Karnofsky Performance Status, delay in starting the treatment, depression, self-esteem and pain. This study brought forth a multidisciplinary contribution, allowing for understanding the factors that can influence hope and presenting support to nursing care. The data evidenced conditions of improvement or worsening of hope, which requires interdisciplinary attention in Oncology.

  6. Predictors of psychological resilience amongst medical students following major earthquakes.

    Science.gov (United States)

    Carter, Frances; Bell, Caroline; Ali, Anthony; McKenzie, Janice; Boden, Joseph M; Wilkinson, Timothy; Bell, Caroline

    2016-05-06

    To identify predictors of self-reported psychological resilience amongst medical students following major earthquakes in Canterbury in 2010 and 2011. Two hundred and fifty-three medical students from the Christchurch campus, University of Otago, were invited to participate in an electronic survey seven months following the most severe earthquake. Students completed the Connor-Davidson Resilience Scale, the Depression, Anxiety and Stress Scale, the Post-traumatic Disorder Checklist, the Work and Adjustment Scale, and the Eysenck Personality Questionnaire. Likert scales and other questions were also used to assess a range of variables including demographic and historical variables (eg, self-rated resilience prior to the earthquakes), plus the impacts of the earthquakes. The response rate was 78%. Univariate analyses identified multiple variables that were significantly associated with higher resilience. Multiple linear regression analyses produced a fitted model that was able to explain 35% of the variance in resilience scores. The best predictors of higher resilience were: retrospectively-rated personality prior to the earthquakes (higher extroversion and lower neuroticism); higher self-rated resilience prior to the earthquakes; not being exposed to the most severe earthquake; and less psychological distress following the earthquakes. Psychological resilience amongst medical students following major earthquakes was able to be predicted to a moderate extent.

  7. Predictors of venous thromboembolism recurrence and bleeding among active cancer patients: a population-based cohort study

    Science.gov (United States)

    Chee, Cheng E.; Ashrani, Aneel A.; Marks, Randolph S.; Petterson, Tanya M.; Bailey, Kent R.; Melton, L. Joseph; Heit, John A.

    2014-01-01

    Active cancer is the major predictor of venous thromboembolism (VTE) recurrence, but further stratification of recurrence risk is uncertain. In a population-based cohort study of all Olmsted County, Minnesota, residents with active cancer-related incident VTE during the 35-year period from 1966 to 2000 who survived 1 day or longer, we estimated VTE recurrence, bleeding on anticoagulant therapy, and survival and tested cancer and noncancer characteristics and secondary prophylaxis as predictors of VTE recurrence and bleeding, using Cox proportional hazards modeling. Of 477 patients, 139 developed recurrent VTE over the course of 1533 person-years of follow-up. The adjusted 10-year cumulative VTE recurrence rate was 28.6%. The adjusted 90-day cumulative incidence of major bleeding on anticoagulation was 1.9%. Survival was significantly worse for patients with cancer who had recurrent VTE (particularly pulmonary embolism) and with bleeding on anticoagulation. In a multivariable model, brain, lung, and ovarian cancer; myeloproliferative or myelodysplastic disorders; stage IV pancreatic cancer; other stage IV cancer; cancer stage progression; and leg paresis were associated with an increased hazard, and warfarin therapy was associated with a reduced hazard, of recurrent VTE. Recurrence rates were significantly higher for cancer patients with 1 or more vs no predictors of recurrence, suggesting these predictors may be useful for stratifying recurrence risk. PMID:24782507

  8. Caregiver-related predictors of thermal burn injuries among Iranian children: A case-control study

    Science.gov (United States)

    Sadeghi-Bazargani, Homayoun; Mohammadi, Reza; Ayubi, Erfan; Almasi-Hashiani, Amir; Pakzad, Reza; Sullman, Mark J. M.; Safiri, Saeid

    2017-01-01

    Purpose Burns are a common and preventable cause of injury in children. The aim of this study was to investigate child and caregiver characteristics which may predict childhood burn injuries among Iranian children and to examine whether confounding exists among these predictors. Methods A hospital based case-control study was conducted using 281 burn victims and 273 hospital-based controls, which were matched by age, gender and place of residence (rural/urban). The characteristics of the children and their caregivers were analyzed using crude and adjusted models to test whether these were predictors of childhood burn injuries. Results The age of the caregiver was significantly lower for burn victims than for the controls (Pcaregiver spent outdoors with the child and their economic status had a significant positive association with the odds of a burn injury (Pcaregivers was independently associated with the child's odds of suffering a burn injury (OR = 1.12, 95% CI: 1.04–1.21). The research also found that children with ADHD (Inattentive subscale: Crude OR = 2.14, 95% CI: 1.16–3.95, Adjusted OR = 5.65, 95% CI: 2.53–12.61; Hyperactive subscale: Crude OR = 1.73, 95% CI: 1.23–2.41, Adjusted OR = 2.53, 95% CI: 1.65–3.87) also had increased odds of suffering a burn injury. However, several variables were identified as possible negative confounder variables, as the associations were stronger in the multivariate model than in the crude models. Conclusion The caregiver's characteristics which were predictors of burn injuries among Iranian children were: being younger, high socio-economic status, Type A behavioural pattern and spending more time outdoors. In addition, the relationship between a child's ADHD scores and the odds of a burn injury may be negatively confounded by the caregivers predictor variables. PMID:28151942

  9. Nonalcoholic fatty liver disease is a novel predictor of cardiovascular disease

    Institute of Scientific and Technical Information of China (English)

    Masahide Hamaguchi; Takahiro Kato; Junichi Okuda; Kazunori Ida; Toshikazu Yoshikawa; Takao Kojima; Noriyuki Takeda; Chisato Nagata; Jun Takeda; Hiroshi Sarui; Yutaka Kawahito; Naohisa Yoshida; Atsushi Suetsugu

    2007-01-01

    AIM: To clarify whether nonalcoholic fatty liver disease (NAFLD) increases the risk of cardiovascular disease.METHODS: We carried out a prospective observational study with a total of 1637 apparently healthy Japanese men and women who were recruited from a health check-up program. NAFLD was diagnosed by abdominal ultrasonography. The metabolic syndrome (MS) was defined according to the modified National Cholesterol Education Program (NCEP) ATP in criteria. Five years after the baseline evaluations, the incidence of cardiovascular disease was assessed by a self-administered questionnaire.RESULTS: Among 1221 participants available for outcome analyses, the incidence of cardiovascular disease was higher in 231 subjects with NAFLD at baseline (5 coronary heart disease, 6 ischemic stroke, and 1 cerebral hemorrhage) than 990 subjects without NAFLD (3 coronary heart disease, 6 ischemic stroke, and 1 cerebral hemorrhage). Multivariate analyses indicated that NAFLD was a predictor of cardiovascular disease independent of conventional risk factors (odds ratio 4.12, 95% CI, 1.58 to 10.75, P = 0.004). MS was alsoindependently associated with cardiovascular events. But simultaneous inclusion of NAFLD and MS in a multivariate model revealed that NAFLD but not MS retained a statistically significant correlation with cardiovascular disease.CONCLUSION: Although both of them were predictors of cardiovascular disease, NAFLD but not MS retained a statistically significant correlation with cardiovascular disease in a multivariate model. NAFLD is a strong predictor of cardiovascular disease and may play a central role in the cardiovascular risk of MS.

  10. Nonalcoholic fatty liver disease is a novel predictor of cardiovascular disease

    Science.gov (United States)

    Hamaguchi, Masahide; Kojima, Takao; Takeda, Noriyuki; Nagata, Chisato; Takeda, Jun; Sarui, Hiroshi; Kawahito, Yutaka; Yoshida, Naohisa; Suetsugu, Atsushi; Kato, Takahiro; Okuda, Junichi; Ida, Kazunori; Yoshikawa, Toshikazu

    2007-01-01

    AIM: To clarify whether nonalcoholic fatty liver disease (NAFLD) increases the risk of cardiovascular disease. METHODS: We carried out a prospective observational study with a total of 1637 apparently healthy Japanese men and women who were recruited from a health check-up program. NAFLD was diagnosed by abdominal ultrasonography. The metabolic syndrome (MS) was defined according to the modified National Cholesterol Education Program (NCEP) ATP III criteria. Five years after the baseline evaluations, the incidence of cardiovascular disease was assessed by a self-administered questionnaire. RESULTS: Among 1221 participants available for outcome analyses, the incidence of cardiovascular disease was higher in 231 subjects with NAFLD at baseline (5 coronary heart disease, 6 ischemic stroke, and 1 cerebral hemorrhage) than 990 subjects without NAFLD (3 coronary heart disease, 6 ischemic stroke, and 1 cerebral hemorrhage). Multivariate analyses indicated that NAFLD was a predictor of cardiovascular disease independent of conventional risk factors (odds ratio 4.12, 95% CI, 1.58 to 10.75, P = 0.004). MS was also independently associated with cardiovascular events. But simultaneous inclusion of NAFLD and MS in a multivariate model revealed that NAFLD but not MS retained a statistically significant correlation with cardiovascular disease. CONCLUSION: Although both of them were predictors of cardiovascular disease, NAFLD but not MS retained a statistically significant correlation with cardiovascular disease in a multivariate model. NAFLD is a strong predictor of cardiovascular disease and may play a central role in the cardiovascular risk of MS. PMID:17461452

  11. Sociodemographic and career history predictors of suicide mortality in the United States Army 2004–2009

    Science.gov (United States)

    Gilman, S. E.; Bromet, E. J.; Cox, K. L.; Colpe, L. J.; Fullerton, C. S.; Gruber, M. J.; Heeringa, S.G.; Lewandowski-Romps, L.; Millikan-Bell, A.M.; Naifeh, J. A.; Nock, M. K.; Petukhova, M. V.; Sampson, N. A.; Schoenbaum, M.; Stein, M. B.; Ursano, R. J.; Wessely, S.; Zaslavsky, A.M.; Kessler, R. C.

    2014-01-01

    Background The US Army suicide rate has increased sharply in recent years. Identifying significant predictors of Army suicides in Army and Department of Defense (DoD) administrative records might help focus prevention efforts and guide intervention content. Previous studies of administrative data, although documenting significant predictors, were based on limited samples and models. A career history perspective is used here to develop more textured models. Method The analysis was carried out as part of the Historical Administrative Data Study (HADS) of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). De-identified data were combined across numerous Army and DoD administrative data systems for all Regular Army soldiers on active duty in 2004–2009. Multivariate associations of sociodemographics and Army career variables with suicide were examined in subgroups defined by time in service, rank and deployment history. Results Several novel results were found that could have intervention implications. The most notable of these were significantly elevated suicide rates (69.6–80.0 suicides per 100000 person-years compared with 18.5 suicides per 100000 person-years in the total Army) among enlisted soldiers deployed either during their first year of service or with less than expected (based on time in service) junior enlisted rank; a substantially greater rise in suicide among women than men during deployment; and a protective effect of marriage against suicide only during deployment. Conclusions A career history approach produces several actionable insights missed in less textured analyses of administrative data predictors. Expansion of analyses to a richer set of predictors might help refine understanding of intervention implications. PMID:25055175

  12. Gender and distance influence performance predictors in young swimmers

    Directory of Open Access Journals (Sweden)

    Paulo Victor Mezzaroba

    2013-12-01

    Full Text Available Predictors of performance in adult swimmers are constantly changing during youth especially because the training routine begins even before puberty in the modality. Therefore this study aimed to determine the group of parameters that best predict short and middle swimming distance performances of young swimmers of both genders. Thirty-three 10-to 16-years-old male and female competitive swimmers participated in the study. Multiple linear regression (MLR was used considering mean speed of maximum 100, 200 and 400 m efforts as dependent variables, and five parameters groups as possible predictors (anthropometry, body composition, physiological and biomechanical parameters, chronological age/pubic hair. The main results revealed explanatory powers of almost 100% for both genders and all performances, but with different predictors entered in MLR models of each parameter group or all variables. Thus, there are considerable differences in short and middle swimming distance, and males and females predictors that should be considered in training programs.

  13. Estimation of torque on mechanical heart valves due to magnetic resonance imaging including an estimation of the significance of the Lenz effect using a computational model

    Energy Technology Data Exchange (ETDEWEB)

    Robertson, Neil M. [44 Ardgowan Street, Greenock PA16 8EL (United Kingdom). E-mail: neil.robertson at physics.org; Diaz-Gomez, Manuel [Plaza Alcalde Horacio Hermoso, 2, 3-A 41013 Seville (Spain). E-mail: manolo-diaz at latinmail.com; Condon, Barrie [Department of Clinical Physics, Institute of Neurological Sciences, Glasgow G51 4TF (United Kingdom). E-mail: barrie.condon at udcf.gla.ac.uk

    2000-12-01

    Mitral and aortic valve replacement is a procedure which is common in cardiac surgery. Some of these replacement valves are mechanical and contain moving metal parts. Should the patient in whom such a valve has been implanted be involved in magnetic resonance imaging, there is a possible dangerous interaction between the moving metal parts and the static magnetic field due to the Lenz effect. Mathematical models of two relatively common forms of single-leaflet valves have been derived and the magnitude of the torque which opposes the motion of the valve leaflet has been calculated for a valve disc of solid metal. In addition, a differential model of a ring-strengthener valve type has been considered to determine the likely significance of the Lenz effect in the context of the human heart. For common magnetic field strengths at present, i.e. 1 to 2 T, the effect is not particularly significant. However, there is a marked increase in back pressure as static magnetic field strength increases. There are concerns that, since field strengths in the range 3 to 4 T are increasingly being used, the Lenz effect could become significant. At 5 to 10 T the malfunction of the mechanical heart valve could cause the heart to behave as though it is diseased. For unhealthy or old patients this could possibly prove fatal. (author)

  14. Predictors of Better Self-Care in Patients with Heart Failure after Six Months of Follow-Up Home Visits

    Science.gov (United States)

    Trojahn, Melina Maria; Ruschel, Karen Brasil; Nogueira de Souza, Emiliane; Mussi, Cláudia Motta; Naomi Hirakata, Vânia; Nogueira Mello Lopes, Alexandra; Rabelo-Silva, Eneida Rejane

    2013-01-01

    This study aimed to examine the predictors of better self-care behavior in patients with heart failure (HF) in a home visiting program. This is a longitudinal study nested in a randomized controlled trial (ISRCTN01213862) in which the home-based educational intervention consisted of a six-month followup that included four home visits by a nurse, interspersed with four telephone calls. The self-care score was measured at baseline and at six months using the Brazilian version of the European Heart Failure Self-Care Behaviour Scale. The associations included eight variables: age, sex, schooling, having received the intervention, social support, income, comorbidities, and symptom severity. A simple linear regression model was developed using significant variables (P ≤ 0.20), followed by a multivariate model to determine the predictors of better self-care. One hundred eighty-eight patients completed the study. A better self-care behavior was associated with patients who received intervention (P < 0.001), had more years of schooling (P = 0.016), and had more comorbidities (P = 0.008). Having received the intervention (P < 0.001) and having a greater number of comorbidities (P = 0.038) were predictors of better self-care. In the multivariate regression model, being in the intervention group and having more comorbidities were a predictor of better self-care. PMID:24083023

  15. Predictor-based error correction method in short-term climate prediction

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    In terms of the basic idea of combining dynamical and statistical methods in short-term climate prediction, a new prediction method of predictor-based error correction (PREC) is put forward in order to effectively use statistical experiences in dynamical prediction. Analyses show that the PREC can reasonably utilize the significant correlations between predictors and model prediction errors and correct prediction errors by establishing statistical prediction model. Besides, the PREC is further applied to the cross-validation experiments of dynamical seasonal prediction on the operational atmosphere-ocean coupled general circulation model of China Meteorological Administration/National Climate Center by selecting the sea surface temperature index in Ni(n)o3 region as the physical predictor that represents the prevailing ENSO-cycle mode of interannual variability in climate system. It is shown from the prediction results of summer mean circulation and total precipitation that the PREC can improve predictive skills to some extent. Thus the PREC provides a new approach for improving short-term climate prediction.

  16. Predictors and outcomes of patient safety culture in hospitals

    Directory of Open Access Journals (Sweden)

    Jaafar Maha

    2011-02-01

    Full Text Available Abstract Background Developing a patient safety culture was one of the recommendations made by the Institute of Medicine to assist hospitals in improving patient safety. In recent years, a multitude of evidence, mostly originating from developed countries, has been published on patient safety culture. One of the first efforts to assess the culture of safety in the Eastern Mediterranean Region was by El-Jardali et al. (2010 in Lebanon. The study entitled "The Current State of Patient Safety Culture: a study at baseline" assessed the culture of safety in Lebanese hospitals. Based on study findings, the objective of this paper is to explore the association between patient safety culture predictors and outcomes, taking into consideration respondent and hospital characteristics. In addition, it will examine the correlation between patient safety culture composites. Methods Sixty-eight hospitals and 6,807 respondents participated in the study. The study which adopted a cross sectional research design utilized an Arabic-translated version of the Hospital Survey on Patient Safety Culture (HSOPSC. The HSOPSC measures 12 patient safety composites. Two of the composites, in addition to a patient safety grade and the number of events reported, represented the four outcome variables. Bivariate and mixed model regression analyses were used to examine the association between the patient safety culture predictors and outcomes. Results Significant correlations were observed among all patient safety culture composites but with differences in the strength of the correlation. Generalized Estimating Equations for the patient safety composite scores and respondent and hospital characteristics against the patient safety grade and the number of events reported revealed significant correlations. Significant correlations were also observed by linear mixed models of the same variables against the frequency of events reported and the overall perception of safety

  17. Interprofessional teamwork skills as predictors of clinical outcomes in a simulated healthcare setting.

    Science.gov (United States)

    Shrader, Sarah; Kern, Donna; Zoller, James; Blue, Amy

    2013-01-01

    Teaching interprofessional (IP) teamwork skills is a goal of interprofessional education. The purpose of this study was to examine the relationship between IP teamwork skills, attitudes and clinical outcomes in a simulated clinical setting. One hundred-twenty health professions students (medicine, pharmacy, physician assistant) worked in interprofessional teams to manage a "patient" in a health care simulation setting. Students completed the Interdisciplinary Education Perception Scale (IEPS) attitudinal survey instrument. Students' responses were averaged by team to create an IEPS attitudes score. Teamwork skills for each team were rated by trained observers using a checklist to calculate a teamwork score (TWS). Clinical outcome scores (COS) were determined by summation of completed clinical tasks performed by the team based on an expert developed checklist. Regression analyses were conducted to determine the relationship of IEPS and TWS with COS. IEPS score was not a significant predictor of COS (p=0.054), but TWS was a significant predictor (p<0.001) of COS. Results suggest that in a simulated clinical setting, students' interprofessional teamwork skills are significant predictors of positive clinical outcomes. Interprofessional curricular models that produce effective teamwork skills can improve student performance in clinical environments and likely improve teamwork practice to positively affect patient care outcomes.

  18. Significance of spatial variability in precipitation for process-oriented modelling: results from two nested catchments using radar and ground station data

    Directory of Open Access Journals (Sweden)

    D. Tetzlaff

    2005-01-01

    Full Text Available The importance of considering the spatial distribution of rainfall for process-oriented hydrological modelling is well-known. However, the application of rainfall radar data to provide such detailed spatial resolution is still under debate. In this study the process-oriented TACD (Tracer Aided Catchment model, Distributed model had been used to investigate the effects of different spatially distributed rainfall input on simulated discharge and runoff components on an event base. TACD is fully distributed (50x50m2 raster cells and was applied on an hourly base. As model input rainfall data from up to 7 ground stations and high resolution rainfall radar data from operational C-band radar were used. For seven rainfall events the discharge simulations were investigated in further detail for the mountainous Brugga catchment (40km2 and the St. Wilhelmer Talbach (15.2km2 sub-basin, which are located in the Southern Black Forest Mountains, south-west Germany. The significance of spatial variable precipitation data was clearly demonstrated. Dependent on event characteristics, localized rain cells were occasionally poorly captured even by a dense ground station network, and this resulted in inadequate model results. For such events, radar data can provide better input data. However, an extensive data adjustment using ground station data is required. For this purpose a method was developed that considers the temporal variability in rainfall intensity in high temporal resolution in combination with the total rainfall amount of both data sets. The use of the distributed catchment model allowed further insights into spatially variable impacts of different rainfall estimates. Impacts for discharge predictions are the largest in areas that are dominated by the production of fast runoff components. The improvements for distributed runoff simulation using high resolution rainfall radar input data are strongly dependent on the investigated scale, the event

  19. Expression and significance of IL-1β and COX-2 in gingiva tissues in rat periodontitis model with different estrogen levels

    Institute of Scientific and Technical Information of China (English)

    Li-Bo Ku; Guo-Quan Xu; Hui Wang; Zhi-Hua Zhao; Shi-Yu Ding; Li Ma

    2017-01-01

    Objective:To explore the expressions of IL-1β and COX-2 in the gingiva tissues in rat periodontitis model with different estrogen levels, and the effect of estrogen level on periodontitis.Methods:A total of 40 female Wistar rats were randomized into 4 groups, i.e. normal control group (n=10), periodontitis group (n=10), castraction periodontitis group (n=10), and estrogen therapy group (n=10). RT-PCR was used to detect the expressions of IL-1β and COX-2 in the gingiva tissues in each group.Results:The expression intensity of IL-1β and COX-2 in the estrogen therapy group was significantly lower than that in the castraction periodontitis group (P<0.05).Conclusions:Estrogen can significantly down regulate the expressions of IL-1β and COX-2 in order to alleviate the symptoms of periodontitis.

  20. Surface tensions of multi-component mixed inorganic/organic aqueous systems of atmospheric significance: measurements, model predictions and importance for cloud activation predictions

    Directory of Open Access Journals (Sweden)

    D. O. Topping

    2007-01-01

    Full Text Available In order to predict the physical properties of aerosol particles, it is necessary to adequately capture the behaviour of the ubiquitous complex organic components. One of the key properties which may affect this behaviour is the contribution of the organic components to the surface tension of aqueous particles in the moist atmosphere. Whilst the qualitative effect of organic compounds on solution surface tensions has been widely reported, our quantitative understanding on mixed organic and mixed inorganic/organic systems is limited. Furthermore, it is unclear whether models that exist in the literature can reproduce the surface tension variability for binary and higher order multi-component organic and mixed inorganic/organic systems of atmospheric significance. The current study aims to resolve both issues to some extent. Surface tensions of single and multiple solute aqueous solutions were measured and compared with predictions from a number of model treatments. On comparison with binary organic systems, two predictive models found in the literature provided a range of values resulting from sensitivity to calculations of pure component surface tensions. Results indicate that a fitted model can capture the variability of the measured data very well, producing the lowest average percentage deviation for all compounds studied. The performance of the other models varies with compound and choice of model parameters. The behaviour of ternary mixed inorganic/organic systems was unreliably captured by using a predictive scheme and this was dependent on the composition of the solutes present. For more atmospherically representative higher order systems, entirely predictive schemes performed poorly. It was found that use of the binary data in a relatively simple mixing rule, or modification of an existing thermodynamic model with parameters derived from binary data, was able to accurately capture the surface tension variation with concentration. Thus

  1. Predictors of employment after liver transplantation.

    Science.gov (United States)

    Sahota, Amandeep; Zaghla, Hassan; Adkins, Rodney; Ramji, Alnoor; Lewis, Susan; Moser, Jennifer; Sher, Linda S; Fong, Tse-Ling

    2006-01-01

    Employment after orthotopic liver transplantation (OLT) indicates recipients' physical/psychosocial adjustment. Our aim was to determine clinical, socioeconomic and health-related quality of life parameters influencing employment after OLT. Questionnaire on demographics, medical conditions, alcohol and drug use before/after OLT, and a validated 12-Item Short Form Health Survey (SF-12) were mailed to 126 adult OLT patients. Stepwise logistic regression was conducted to identify best predictors of post-OLT employment. Among non-retirees, 49% were employed after OLT. The predictors of employment were: employment status, income, disability status before OLT and Model of End Stage Liver Disease score. These variables had prediction rate of 82%. Individuals working during the five yr prior to OLT were likely to return to work (p6 months prior to OLT (p$80 000 before OLT compared with or=6 months prior to OLT, were less likely to work (p=0.0005). Severity/duration of liver dysfunction prior to OLT did not correlate with employment. Sense of physical health was poorer in those employed after OLT than in unemployed (p=0.0003). Socioeconomic factors were the most important predictors of post-OLT employment.

  2. Predictors of intentions to perform six cancer-related behaviours: roles for injunctive and descriptive norms.

    Science.gov (United States)

    Smith-McLallen, Aaron; Fishbein, Martin

    2008-08-01

    This study reports an application of the integrative model to the prediction of intentions to engage in three cancer screening behaviours (mammogram, colonoscopy and PSA test) and three healthy lifestyle behaviours (exercising, eating fruits and vegetables, and controlling ones diet to lose weight). We examined the roles of attitudes, perceived behavioural control, injunctive norms (what important others think one should do), and descriptive norms (perceptions of what others do) as predictors of participant's intentions to engage in each behaviour. Results indicated that injunctive norms were the strongest predictors of prostate and colon cancer screening intentions and contributed significantly to the prediction of intentions to get a mammogram. In contrast, injunctive norms contributed relatively little to the prediction of lifestyle behaviours, but were strongly predictive of intentions to eat fruits and vegetables. Implications for designing behaviour-specific communications and interventions are discussed.

  3. Predictors of growth or attrition of the first language in Latino children with specific language impairment.

    Science.gov (United States)

    Simon-Cereijido, Gabriela; Gutiérrez-Clellen, Vera F; Sweet, Monica

    2013-11-01

    We investigated the factors that may help understand the differential rates of language development in the home language (i.e., Spanish) of Latino preschoolers with specific language impairment (SLI). Children were randomly assigned to either bilingual or English-only small group interventions and followed from preschool to kindergarten. Predictors of Spanish growth included the language of intervention, the child's level of language development or severity, the child's socio-emotional skills, and the child's level of English use. Spanish performance outcomes were assessed over time using a series of longitudinal models with baseline and post-treatment measures nested within child. Children demonstrated growth on Spanish outcomes over time. The language of instruction and the child's level of vocabulary and socio-emotional development at baseline were significant predictors of differences in rates of growth in the home language. Clinicians may need to take into consideration these factors when making clinical recommendations.

  4. Predictors of musculoskeletal discomfort: A cross-cultural comparison between Malaysian and Australian office workers.

    Science.gov (United States)

    Maakip, Ismail; Keegel, Tessa; Oakman, Jodi

    2017-04-01

    Prevalence and predictors associated with musculoskeletal disorders (MSDs) vary considerably between countries. It is plausible that socio-cultural contexts may contribute to these differences. We conducted a cross-sectional survey with 1184 Malaysian and Australian office workers with the aim to examine predictors associated with MSD discomfort. The 6-month period prevalence of self-reported MSD discomfort for Malaysian office workers was 92.8% and 71.2% among Australian workers. In Malaysia, a model regressing level of musculoskeletal discomfort against possible risk factors was significant overall (F [6, 370] = 17.35; p management needs to take into account the work practices and culture of the target population. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

  5. Predictors of extubation failure in myasthenic crisis.

    Science.gov (United States)

    Seneviratne, Janaka; Mandrekar, Jay; Wijdicks, Eelco F M; Rabinstein, Alejandro A

    2008-07-01

    The ideal timing for extubation of patients with myasthenic crisis (MC) and the factors that influence extubation outcome are not well established. To assess the risk of extubation failure in MC and to identify predictors of extubation failure. We reviewed consecutive episodes of MC treated with endotracheal intubation from January 1, 1987, through December 31, 2006. Mayo Clinic. Patients Forty patients with 46 episodes of MC underwent endotracheal intubation and mechanical ventilation. The main outcome measures were extubation failure and reintubation. Extubation failure was defined as reintubation, tracheostomy, or death while intubated. Reintubation was also analyzed as a separate end point. Univariate logistic regression was used to identify predictors of extubation failure and reintubation. Of the 46 episodes of MC, extubation failure occurred in 20 (44%), including 9 of 35 episodes (26%) of reintubation. Male sex, history of previous crisis, atelectasis, and intubation for more than 10 days were associated with extubation failure. Lower pH and lower forced vital capacity on the time of extubation, atelectasis, and bilevel intermittent positive airway pressure use after extubation predicted the need for reintubation. Atelectasis showed the strongest association with both end points. Extubation failure and reintubation were associated with significant prolongation in intensive care unit and hospital length of stay. Extubation failure is relatively common in patients with MC. Atelectasis is the strongest predictor of this complication.

  6. Predictors of Self-Care Behaviors among Diabetic Patients Referred to Yazd Diabetes Research Centre Based on Extended Health Belief Model

    OpenAIRE

    MH Baghianimoghadam; N Rouhani Tonekaboni; MA Morowati -Sharifabad

    2007-01-01

    Introduction: Diabetes is the most common disease related to metabolism disorders with long term complications. It needs lifelong specific self-care, as it causes a promotion in quality of life and decreases disease costs. The Health Belief Model (HBM) is a psychological model that attempts to explain and predict health behaviors. This is done by focusing on the attitudes and beliefs of individuals. The model has been used for studying diabetes self care behaviors. The aim of this study was d...

  7. Prediction of SO{sub 2} pollution incidents near a power station using partially linear models and an historical matrix of predictor-response vectors

    Energy Technology Data Exchange (ETDEWEB)

    Prada-Sanchez, J.M.; Febrero-Bande, M.; Gonzalez-Manteiga, W. [Universidad de Santiago de Compostela, Dept. de Estadistica e Investigacion Operativa, Santiago de Compostela (Spain); Costos-Yanez, T. [Universidad de Vigo, Dept. de Estadistica e Investigacion Operativa, Orense (Spain); Bermudez-Cela, J.L.; Lucas-Dominguez, T. [Laboratorio, Central Termica de As Pontes, La Coruna (Spain)

    2000-07-01

    Atmospheric SO{sub 2} concentrations at sampling stations near the fossil fuel fired power station at As Pontes (La Coruna, Spain) were predicted using a model for the corresponding time series consisting of a self-explicative term and a linear combination of exogenous variables. In a supplementary simulation study, models of this kind behaved better than the corresponding pure self-explicative or pure linear regression models. (Author)

  8. Crowdsourcing novel childhood predictors of adult obesity.

    Directory of Open Access Journals (Sweden)

    Kirsten E Bevelander

    Full Text Available Effective and simple screening tools are needed to detect behaviors that are established early in life and have a significant influence on weight gain later in life. Crowdsourcing could be a novel and potentially useful tool to assess childhood predictors of adult obesity. This exploratory study examined whether crowdsourcing could generate well-documented predictors in obesity research and, moreover, whether new directions for future research could be uncovered. Participants were recruited through social media to a question-generation website, on which they answered questions and were able to pose new questions that they thought could predict obesity. During the two weeks of data collection, 532 participants (62% female; age  =  26.5±6.7; BMI  =  29.0±7.0 registered on the website and suggested a total of 56 unique questions. Nineteen of these questions correlated with body mass index (BMI and covered several themes identified by prior research, such as parenting styles and healthy lifestyle. More importantly, participants were able to identify potential determinants that were related to a lower BMI, but have not been the subject of extensive research, such as parents packing their children's lunch to school or talking to them about nutrition. The findings indicate that crowdsourcing can reproduce already existing hypotheses and also generate ideas that are less well documented. The crowdsourced predictors discovered in this study emphasize the importance of family interventions to fight obesity. The questions generated by participants also suggest new ways to express known predictors.

  9. Crowdsourcing novel childhood predictors of adult obesity.

    Science.gov (United States)

    Bevelander, Kirsten E; Kaipainen, Kirsikka; Swain, Robert; Dohle, Simone; Bongard, Josh C; Hines, Paul D H; Wansink, Brian

    2014-01-01

    Effective and simple screening tools are needed to detect behaviors that are established early in life and have a significant influence on weight gain later in life. Crowdsourcing could be a novel and potentially useful tool to assess childhood predictors of adult obesity. This exploratory study examined whether crowdsourcing could generate well-documented predictors in obesity research and, moreover, whether new directions for future research could be uncovered. Participants were recruited through social media to a question-generation website, on which they answered questions and were able to pose new questions that they thought could predict obesity. During the two weeks of data collection, 532 participants (62% female; age  =  26.5±6.7; BMI  =  29.0±7.0) registered on the website and suggested a total of 56 unique questions. Nineteen of these questions correlated with body mass index (BMI) and covered several themes identified by prior research, such as parenting styles and healthy lifestyle. More importantly, participants were able to identify potential determinants that were related to a lower BMI, but have not been the subject of extensive research, such as parents packing their children's lunch to school or talking to them about nutrition. The findings indicate that crowdsourcing can reproduce already existing hypotheses and also generate ideas that are less well documented. The crowdsourced predictors discovered in this study emphasize the importance of family interventions to fight obesity. The questions generated by participants also suggest new ways to express known predictors.

  10. Predictors for trismus in patients receiving radiotherapy.

    Science.gov (United States)

    van der Geer, S Joyce; Kamstra, Jolanda I; Roodenburg, Jan L N; van Leeuwen, Marianne; Reintsema, Harry; Langendijk, Johannes A; Dijkstra, Pieter U

    2016-11-01

    Trismus, a restricted mouth opening in head and neck cancer patients may be caused by tumor infiltration in masticatory muscles, radiation-induced fibrosis or scarring after surgery. It may impede oral functioning severely. The aims of our study were to determine: (1) the incidence of trismus at various time points; and (2) the patient, tumor, and treatment characteristics that predict the development of trismus after radiotherapy in head and neck cancer patients using a large database (n = 641). Maximal mouth opening was measured prior to and 6, 12, 18, 24, 36, and 48 months after radiotherapy. Patient, tumor, and treatment characteristics were analyzed as potential predictors for trismus using a multivariable logistic regression analysis. At six months after radiotherapy, 28.1% of the patients without trismus prior to radiotherapy developed trismus for the first time. At subsequent time points the incidence declined. Over a total period of 48 months after radiotherapy, the incidence of trismus was 3.6 per 10 person years at risk. Patients who had tumors located in the oral cavity, oropharynx or nasopharynx, and the salivary glands or ear, and who had a longer overall treatment time of radiotherapy, were more likely to develop trismus in the first six months after radiotherapy. Maximal mouth opening was a predictor for developing trismus at all time points. Incidence of trismus is 3.6 per 10 person years at risk. Tumor localization and overall treatment time of radiotherapy are predictors for developing trismus the first six months after radiotherapy. Maximal mouth opening is a significant predictor for developing trismus at all time points. Regular measurements of maximal mouth opening are needed to predict trismus.

  11. Significant blockade of multiple receptor tyrosine kinases by MGCD516 (Sitravatinib), a novel small molecule inhibitor, shows potent anti-tumor activity in preclinical models of sarcoma.

    Science.gov (United States)

    Patwardhan, Parag P; Ivy, Kathryn S; Musi, Elgilda; de Stanchina, Elisa; Schwartz, Gary K

    2016-01-26

    Sarcomas are rare but highly aggressive mesenchymal tumors with a median survival of 10-18 months for metastatic disease. Mutation and/or overexpression of many receptor tyrosine kinases (RTKs) including c-Met, PDGFR, c-Kit and IGF1-R drive defective signaling pathways in sarcomas. MGCD516 (Sitravatinib) is a novel small molecule inhibitor targeting multiple RTKs involved in driving sarcoma cell growth. In the present study, we evaluated the efficacy of MGCD516 both in vitro and in mouse xenograft models in vivo. MGCD516 treatment resulted in significant blockade of phosphorylation of potential driver RTKs and induced potent anti-proliferative effects in vitro. Furthermore, MGCD516 treatment of tumor xenografts in vivo resulted in significant suppression of tumor growth. Efficacy of MGCD516 was superior to imatinib and crizotinib, two other well-studied multi-kinase inhibitors with overlapping target specificities, both in vitro and in vivo. This is the first report describing MGCD516 as a potent multi-kinase inhibitor in different models of sarcoma, superior to imatinib and crizotinib. Results from this study showing blockade of multiple driver signaling pathways provides a rationale for further clinical development of MGCD516 for the treatment of patients with soft-tissue sarcoma.

  12. Predictors of Outcome in Traumatic Brain Injury: New Insight Using Receiver Operating Curve Indices and Bayesian Network Analysis.

    Directory of Open Access Journals (Sweden)

    Zsolt Zador

    Full Text Available Traumatic brain injury remains a global health problem. Understanding the relative importance of outcome predictors helps optimize our treatment strategies by informing assessment protocols, clinical decisions and trial designs. In this study we establish importance ranking for outcome predictors based on receiver operating indices to identify key predictors of outcome and create simple predictive models. We then explore the associations between key outcome predictors using Bayesian networks to gain further insight into predictor importance.We analyzed the corticosteroid randomization after significant head injury (CRASH trial database of 10008 patients and included patients for whom demographics, injury characteristics, computer tomography (CT findings and Glasgow Outcome Scale (GCS were recorded (total of 13 predictors, which would be available to clinicians within a few hours following the injury in 6945 patients. Predictions of clinical outcome (death or severe disability at 6 months were performed using logistic regression models with 5-fold cross validation. Predictive performance was measured using standardized partial area (pAUC under the receiver operating curve (ROC and we used Delong test for comparisons. Variable importance ranking was based on pAUC targeted at specificity (pAUCSP and sensitivity (pAUCSE intervals of 90-100%. Probabilistic associations were depicted using Bayesian networks.Complete AUC analysis showed very good predictive power (AUC = 0.8237, 95% CI: 0.8138-0.8336 for the complete model. Specificity focused importance ranking highlighted age, pupillary, motor responses, obliteration of basal cisterns/3rd ventricle and midline shift. Interestingly when targeting model sensitivity, the highest-ranking variables were age, severe extracranial injury, verbal response, hematoma on CT and motor response. Simplified models, which included only these key predictors, had similar performance (pAUCSP = 0.6523, 95% CI: 0

  13. Predictors of misunderstanding pediatric liquid medication instructions.

    Science.gov (United States)

    Bailey, Stacy Cooper; Pandit, Anjali U; Yin, Shonna; Federman, Alex; Davis, Terry C; Parker, Ruth M; Wolf, Michael S

    2009-01-01

    Our objective was to determine the level of adult understanding of dosage instructions for a liquid medication commonly prescribed for children. Structured interviews were conducted with 373 adults waiting for an appointment at family medicine clinics serving low-income populations in Shreveport, La; Chicago; and Jackson, Mich, from July 2003-August 2004. Subjects were asked to read a prescription label for amoxicillin and explain how they would take the medication. Correct interpretation was determined by a panel of blinded physician reviewers who coded subjects' verbatim responses. Qualitative methods were used to determine the nature of incorrect responses. Twenty-eight percent of subjects misunderstood medication instructions. The prevalence of misinterpreting instructions among subjects with adequate, marginal, and low literacy was 18%, 34%, and 43%, respectively. Common causes for misunderstanding included problems with dosage measurement (28%; ie, tablespoon instead of teaspoon) and frequency of use (33%; ie, every 3 hours instead of every 6-8 hours). In an adjusted analysis that excluded literacy, African Americans were more likely to misunderstand instructions than Caucasians (adjusted odds ratio [AOR] 1.63, 95% confidence interval [CI]=1.02-2.61). When literacy was included in the model, the effect of race on misunderstanding was reduced and nonsignificant. Inadequate and marginal literacy remained independent predictors of misunderstanding (inadequate--AOR 2.90, 95% CI= 1.41-6.00; marginal--AOR 2.20, 95% CI=1.19-3.97). Misinterpretation of pediatric liquid medication instructions is common. Limited literacy is a significant risk factor for misunderstanding and could contribute to racial disparities. Instructions should be written in a concise manner and standardized to ensure comprehension.

  14. Predictors of future falls in Parkinson disease.

    Science.gov (United States)

    Kerr, G K; Worringham, C J; Cole, M H; Lacherez, P F; Wood, J M; Silburn, P A

    2010-07-13

    Falls are a major health and injury problem for people with Parkinson disease (PD). Despite the severe consequences of falls, a major unresolved issue is the identification of factors that predict the risk of falls in individual patients with PD. The primary aim of this study was to prospectively determine an optimal combination of functional and disease-specific tests to predict falls in individuals with PD. A total of 101 people with early-stage PD undertook a battery of neurologic and functional tests in their optimally medicated state. The tests included Tinetti, Berg, Timed Up and Go, Functional Reach, and the Physiological Profile Assessment of Falls Risk; the latter assessment includes physiologic tests of visual function, proprioception, strength, cutaneous sensitivity, reaction time, and postural sway. Falls were recorded prospectively over 6 months. Forty-eight percent of participants reported a fall and 24% more than 1 fall. In the multivariate model, a combination of the Unified Parkinson's Disease Rating Scale (UPDRS) total score, total freezing of gait score, occurrence of symptomatic postural orthostasis, Tinetti total score, and extent of postural sway in the anterior-posterior direction produced the best sensitivity (78%) and specificity (84%) for predicting falls. From the UPDRS items, only the rapid alternating task category was an independent predictor of falls. Reduced peripheral sensation and knee extension strength in fallers contributed to increased postural instability. Falls are a significant problem in optimally medicated early-stage PD. A combination of both disease-specific and balance- and mobility-related measures can accurately predict falls in individuals with PD.

  15. Mortality in Schizophrenia: Clinical and Serological Predictors

    Science.gov (United States)

    Dickerson, Faith; Stallings, Cassie; Origoni, Andrea; Schroeder, Jennifer; Khushalani, Sunil; Yolken, Robert

    2014-01-01

    Persons with schizophrenia have a reduced life expectancy largely due to death from natural causes. Factors that have been previously associated with excess mortality include cigarette smoking and antipsychotic medication. The role of other environmental factors such as exposure to infectious agents has been the subject of only limited investigation. We prospectively assessed a cohort of persons with schizophrenia with a clinical evaluation and a blood sample from which antibodies to human herpes viruses and Toxoplasma gondii were measured. Mortality was determined with data from the National Death Index following a period of up to 11 years. We examined the role of demographic, serological, and clinical factors on mortality. A total of 25 (5%) of 517 persons died of natural causes. The standardized mortality ratio was 2.80 (95% CI 0.89, 6.38). After adjusting for age and gender, mortality from natural causes was predicted in separate models by cigarette smoking (relative risk [RR] = 4.66, P = .0029); lower cognitive score (RR = 0.96, P = .013); level of antibodies to Epstein–Barr virus (RR = 1.22, P = .0041) and to Herpes Simplex virus type 1 (RR = 1.19, P = .030); immunologic disease (RR = 3.14, P = .044); and genitourinary disease (RR = 2.70; P = .035). Because cigarette smoking confers an almost 5-fold risk of mortality, smoking cessation is an urgent priority. Having an elevated level of antibodies to Epstein–Barr virus and to Herpes Simplex virus type 1 are also significant predictors of death from natural causes. PMID:23943410

  16. Nutrition, Balance and Fear of Falling as Predictors of Risk for Falls among Filipino Elderly in Nursing Homes: A Structural Equation Model (SEM)

    Science.gov (United States)

    de Guzman, Allan B.; Ines, Joanna Louise C.; Inofinada, Nina Josefa A.; Ituralde, Nielson Louie J.; Janolo, John Robert E.; Jerezo, Jnyv L.; Jhun, Hyae Suk J.

    2013-01-01

    While a number of empirical studies have been conducted regarding risk for falls among the elderly, there is still a paucity of similar studies in a developing country like the Philippines. This study purports to test through Structural Equation Modeling (SEM) a model that shows the interaction between and among nutrition, balance, fear of…

  17. Nutrition, Balance and Fear of Falling as Predictors of Risk for Falls among Filipino Elderly in Nursing Homes: A Structural Equation Model (SEM)

    Science.gov (United States)

    de Guzman, Allan B.; Ines, Joanna Louise C.; Inofinada, Nina Josefa A.; Ituralde, Nielson Louie J.; Janolo, John Robert E.; Jerezo, Jnyv L.; Jhun, Hyae Suk J.

    2013-01-01

    While a number of empirical studies have been conducted regarding risk for falls among the elderly, there is still a paucity of similar studies in a developing country like the Philippines. This study purports to test through Structural Equation Modeling (SEM) a model that shows the interaction between and among nutrition, balance, fear of…

  18. The acceptance of the K-SADS-PL - potential predictors for the overall satisfaction of parents and interviewers.

    Science.gov (United States)

    Matuschek, Tina; Jaeger, Sonia; Stadelmann, Stephanie; Dölling, Katrin; Weis, Steffi; Von Klitzing, Kai; Grunewald, Madlen; Hiemisch, Andreas; Döhnert, Mirko

    2015-09-01

    The presented study investigated the interviewee (parents) and interviewer acceptance of the semi-structured diagnostic interview Kiddie Schedule for Affective Disorders and Schizophrenia for School Aged Children Present Lifetime version (KSADS-PL; German version). Seventeen certified interviewers conducted 231 interviews (interviewers conducted several interviews; interviewees were only questioned once). Interviewees and interviewers anonymously rated their acceptance right after the interview was finished. The nested data structure was analysed regarding an individual interviewer bias and potential predictors of overall satisfaction. Therefore, factors improvable by interviewer training were included, as well as fixed factors which cannot be improved by professional training. The overall satisfaction was evaluated as highly positive with significant higher interviewee and interviewer ratings in the research as compared to the clinical recruitment setting. An individual bias of the interviewer on his or her own acceptance over time, but not on the evaluation of the corresponding interviewee was found. Neither the professional background nor the gender of the interviewer had a significant contribution in predicting these differences. The interviewer model showed no significant change over time and only the interview duration and the interviewee acceptance were significant predictors for interviewer overall satisfaction. Regarding the interviewee model, just the interviewer acceptance was a significant predictor. Copyright Copyright © 2015 John Wiley & Sons, Ltd.

  19. Quantitative renal perfusion measurements in a rat model of acute kidney injury at 3T: testing inter- and intramethodical significance of ASL and DCE-MRI.

    Directory of Open Access Journals (Sweden)

    Fabian Zimmer

    Full Text Available OBJECTIVES: To establish arterial spin labelling (ASL for quantitative renal perfusion measurements in a rat model at 3 Tesla and to test the diagnostic significance of ASL and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI in a model of acute kidney injury (AKI. MATERIAL AND METHODS: ASL and DCE-MRI were consecutively employed on six Lewis rats, five of which had a unilateral ischaemic AKI. All measurements in this study were performed on a 3 Tesla MR scanner using a FAIR True-FISP approach and a TWIST sequence for ASL and DCE-MRI, respectively. Perfusion maps were calculated for both methods and the cortical perfusion of healthy and diseased kidneys was inter- and intramethodically compared using a region-of-interest based analysis. RESULTS/SIGNIFICANCE: Both methods produce significantly different values for the healthy and the diseased kidneys (P<0.01. The mean difference was 147±47 ml/100 g/min and 141±46 ml/100 g/min for ASL and DCE-MRI, respectively. ASL measurements yielded a mean cortical perfusion of 416±124 ml/100 g/min for the healthy and 316±102 ml/100 g/min for the diseased kidneys. The DCE-MRI values were systematically higher and the mean cortical renal blood flow (RBF was found to be 542±85 ml/100 g/min (healthy and 407±119 ml/100 g/min (AKI. CONCLUSION: Both methods are equally able to detect abnormal perfusion in diseased (AKI kidneys. This shows that ASL is a capable alternative to DCE-MRI regarding the detection of abnormal renal blood flow. Regarding absolute perfusion values, nontrivial differences and variations remain when comparing the two methods.

  20. Internationally educated nurses in Canada: predictors of workforce integration.

    Science.gov (United States)

    Covell, Christine L; Primeau, Marie-Douce; Kilpatrick, Kelley; St-Pierre, Isabelle

    2017-04-04

    Global trends in migration accompanied with recent changes to the immigrant selection process may have influenced the demographic and human capital characteristics of internationally educated nurses (IENs) in Canada and in turn the assistance required to facilitate their workforce integration. This study aimed to describe the demographic and human capital profile of IENs in Canada, to explore recent changes to the profile, and to identify predictors of IENs' workforce integration. A cross-sectional, descriptive, correlational survey design was used. Eligible IENs were immigrants, registered and employed as regulated nurses in Canada. Data were collected in 2014 via online and paper questionnaires. Descriptive statistics were used to examine the data by year of immigration. Logistic regression modeling was employed to identify predictors of IENs' workforce integration measured as passing the licensure exam to acquire professional recertification and securing employment. The sample consisted of 2280 IENs, representative of all Canadian provincial jurisdictions. Since changes to the immigrant selection process in 2002, the IEN population in Canada has become more racially diverse with greater numbers emigrating from developing countries. Recent arrivals (after 2002) had high levels of human capital (knowledge, professional experience, language proficiency). Some, but not all, benefited from the formal and informal assistance available to facilitate their workforce integration. Professional experience and help studying significantly predicted if IENs passed the licensure exam on their first attempt. Bridging program participation and assistance from social networks in Canada were significant predictors if IENs had difficulty securing employment. Nurses will continue to migrate from a wide variety of countries throughout the world that have dissimilar nursing education and health systems. Thus, IENs are not a homogenous group, and a "one size fits all" model may not be

  1. Predictors of condom use behaviour among male street labourers in urban Vietnam using a modified Information-Motivation-Behavioral Skills (IMB) model.

    Science.gov (United States)

    Van Huy, Nguyen; P Dunne, Michael; Debattista, Joseph

    2016-01-01

    HIV risk in vulnerable groups such as itinerant male street labourers is often examined via a focus on individual determinants. This study provides a test of a modified Information-Motivation-Behavioral Skills (IMB) model to predict condom use behaviour among male street workers in urban Vietnam. In a cross-sectional survey using a social mapping technique, 450 male street labourers from 13 districts of Hanoi, Vietnam were recruited and interviewed. Collected data were first examined for completeness; structural equation modelling was then employed to test the model fit. Condoms were used inconsistently by many of these men, and usage varied in relation to a number of factors. A modified IMB model had a better fit than the original IMB model in predicting condom use behaviour. This modified model accounted for 49% of the variance, versus 10% by the original version. In the modified model, the influence of psychosocial factors was moderately high, whilst the influence of HIV prevention information, motivation and perceived behavioural skills was moderately low, explaining in part the limited level of condom use behaviour. This study provides insights into social factors that should be taken into account in public health planning to promote safer sexual behaviour among Asian male street labourers.

  2. Nonlinear Forecasting With Many Predictors Using Kernel Ridge Regression

    DEFF Research Database (Denmark)

    Exterkate, Peter; Groenen, Patrick J.F.; Heij, Christiaan

    This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the predi......This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation...... of the predictive regression model is based on a shrinkage estimator to avoid overfitting. We extend the kernel ridge regression methodology to enable its use for economic time-series forecasting, by including lags of the dependent variable or other individual variables as predictors, as typically desired...... in macroeconomic and financial applications. Monte Carlo simulations as well as an empirical application to various key measures of real economic activity confirm that kernel ridge regression can produce more accurate forecasts than traditional linear and nonlinear methods for dealing with many predictors based...

  3. Changes in Body Composition in Anorexia Nervosa: Predictors of Recovery and Treatment Outcome

    Science.gov (United States)

    Arcelus, Jon; Sánchez, Isabel; Riesco, Nadine; Jiménez-Murcia, Susana; González-Gómez, Jana; Granero, Roser; Custal, Nuria; Montserrat-Gil de Bernabé, Monica; Tárrega, Salomé; Baños, Rosa M.; Botella, Cristina; de la Torre, Rafael; Fernández-García, José C.; Fernández-Real, José M.; Frühbeck, Gema; Gómez-Ambrosi, Javier; Tinahones, Francisco J.; Crujeiras, Ana B.; Casanueva, Felipe F.; Menchón, José M.; Fernández-Aranda, Fernando

    2015-01-01

    The restoration of body composition (BC) parameters is considered to be one of the most important goals in the treatment of patients with anorexia nervosa (AN). However, little is known about differences between AN diagnostic subtypes [restricting (AN-R) and binge/purging (AN-BP)] and weekly changes in BC during refeeding treatment. Therefore, the main objectives of our study were twofold: 1) to assess the changes in BC throughout nutritional treatment in an AN sample and 2) to analyze predictors of BC changes during treatment, as well as predictors of treatment outcome. The whole sample comprised 261 participants [118 adult females with AN (70 AN-R vs. 48 AN-BP), and 143 healthy controls]. BC was measured weekly during 15 weeks of day-hospital treatment using bioelectrical impedance analysis (BIA). Assessment measures also included the Eating Disorders Inventory-2, as well as a number of other clinical indices. Overall, the results showed that AN-R and AN-BP patients statistically differed in all BC measures at admission. However, no significant time×group interaction was found for almost all BC parameters. Significant time×group interactions were only found for basal metabolic rate (p = .041) and body mass index (BMI) (p = .035). Multiple regression models showed that the best predictors of pre-post changes in BC parameters (namely fat-free mass, muscular mass, total body water and BMI) were the baseline values of BC parameters. Stepwise predictive logistic regressions showed that only BMI and age were significantly associated with outcome, but not with the percentage of body fat. In conclusion, these data suggest that although AN patients tended to restore all BC parameters during nutritional treatment, only AN-BP patients obtained the same fat mass values as healthy controls. Put succinctly, the best predictors of changes in BC were baseline BC values, which did not, however, seem to influence treatment outcome. PMID:26600309

  4. Changes in Body Composition in Anorexia Nervosa: Predictors of Recovery and Treatment Outcome.

    Directory of Open Access Journals (Sweden)

    Zaida Agüera

    Full Text Available The restoration of body composition (BC parameters is considered to be one of the most important goals in the treatment of patients with anorexia nervosa (AN. However, little is known about differences between AN diagnostic subtypes [restricting (AN-R and binge/purging (AN-BP] and weekly changes in BC during refeeding treatment. Therefore, the main objectives of our study were twofold: 1 to assess the changes in BC throughout nutritional treatment in an AN sample and 2 to analyze predictors of BC changes during treatment, as well as predictors of treatment outcome. The whole sample comprised 261 participants [118 adult females with AN (70 AN-R vs. 48 AN-BP, and 143 healthy controls]. BC was measured weekly during 15 weeks of day-hospital treatment using bioelectrical impedance analysis (BIA. Assessment measures also included the Eating Disorders Inventory-2, as well as a number of other clinical indices. Overall, the results showed that AN-R and AN-BP patients statistically differed in all BC measures at admission. However, no significant time×group interaction was found for almost all BC parameters. Significant time×group interactions were only found for basal metabolic rate (p = .041 and body mass index (BMI (p = .035. Multiple regression models showed that the best predictors of pre-post changes in BC parameters (namely fat-free mass, muscular mass, total body water and BMI were the baseline values of BC parameters. Stepwise predictive logistic regressions showed that only BMI and age were significantly associated with outcome, but not with the percentage of body fat. In conclusion, these data suggest that although AN patients tended to restore all BC parameters during nutritional treatment, only AN-BP patients obtained the same fat mass values as healthy controls. Put succinctly, the best predictors of changes in BC were baseline BC values, which did not, however, seem to influence treatment outcome.

  5. Changes in Body Composition in Anorexia Nervosa: Predictors of Recovery and Treatment Outcome.

    Science.gov (United States)

    Agüera, Zaida; Romero, Xandra; Arcelus, Jon; Sánchez, Isabel; Riesco, Nadine; Jiménez-Murcia, Susana; González-Gómez, Jana; Granero, Roser; Custal, Nuria; Montserrat-Gil de Bernabé, Monica; Tárrega, Salomé; Baños, Rosa M; Botella, Cristina; de la Torre, Rafael; Fernández-García, José C; Fernández-Real, José M; Frühbeck, Gema; Gómez-Ambrosi, Javier; Tinahones, Francisco J; Crujeiras, Ana B; Casanueva, Felipe F; Menchón, José M; Fernández-Aranda, Fernando

    2015-01-01

    The restoration of body composition (BC) parameters is considered to be one of the most important goals in the treatment of patients with anorexia nervosa (AN). However, little is known about differences between AN diagnostic subtypes [restricting (AN-R) and binge/purging (AN-BP)] and weekly changes in BC during refeeding treatment. Therefore, the main objectives of our study were twofold: 1) to assess the changes in BC throughout nutritional treatment in an AN sample and 2) to analyze predictors of BC changes during treatment, as well as predictors of treatment outcome. The whole sample comprised 261 participants [118 adult females with AN (70 AN-R vs. 48 AN-BP), and 143 healthy controls]. BC was measured weekly during 15 weeks of day-hospital treatment using bioelectrical impedance analysis (BIA). Assessment measures also included the Eating Disorders Inventory-2, as well as a number of other clinical indices. Overall, the results showed that AN-R and AN-BP patients statistically differed in all BC measures at admission. However, no significant time×group interaction was found for almost all BC parameters. Significant time×group interactions were only found for basal metabolic rate (p = .041) and body mass index (BMI) (p = .035). Multiple regression models showed that the best predictors of pre-post changes in BC parameters (namely fat-free mass, muscular mass, total body water and BMI) were the baseline values of BC parameters. Stepwise predictive logistic regressions showed that only BMI and age were significantly associated with outcome, but not with the percentage of body fat. In conclusion, these data suggest that although AN patients tended to restore all BC parameters during nutritional treatment, only AN-BP patients obtained the same fat mass values as healthy controls. Put succinctly, the best predictors of changes in BC were baseline BC values, which did not, however, seem to influence treatment outcome.

  6. Physical assessment as a predictor of mortality in people with Parkinson's disease: a study over 7 years.

    Science.gov (United States)

    Gray, William K; Hildreth, Anthony; Bilclough, Julie A; Wood, Brian H; Baker, Katherine; Walker, Richard W

    2009-10-15

    The primary aim of this study was to ascertain whether a battery of physical function measures in a Parkinson's disease (PD) patient cohort predicted mortality status at 7-year follow-up. Secondary aims were establishing which specific tests were the most useful, and whether PD phenotype was a predictor. A retrospective correlation design was used in this study. A cohort of 109 PD patients underwent baseline physiotherapy assessment of gait, balance, posture, muscle strength, and ability to change postural set. We compared mortality status at 7-year follow-up and baseline physical assessment tests. Tinetti gait and balance scores, UPDRS score, 10-m walk test (time, velocity, and number of strides), posture in standing, lying to sitting, sitting to standing, getting up from floor assessments, and time to ascend and descend four steps were found to be statistically significant physical predictors of mortality at 7-year follow-up. In addition, age, sex, and mini-mental state examination were significant nonphysical predictors of mortality. Using Cox regression, a survival model was constructed with age, sex, and Tinetti gait score as independent predictors of mortality. The results of this study suggest that there is a link between reduced physical function and an increased mortality risk in PD populations.

  7. Paleomagnetic data support Early Permian age for the Abor Volcanics in the lower Siang Valley, NE India: Significance for Gondwana-related break-up models

    Science.gov (United States)

    Ali, Jason R.; Aitchison, Jonathan C.; Chik, Sam Y. S.; Baxter, Alan T.; Bryan, Scott E.

    2012-05-01

    Confusion exists as to the age of the Abor Volcanics of NE India. Some consider the unit to have been emplaced in the Early Permian, others the Early Eocene, a difference of ˜230 million years. The divergence in opinion is significant because fundamentally different models explaining the geotectonic evolution of India depend on the age designation of the unit. Paleomagnetic data reported here from several exposures in the type locality of the formation in the lower Siang Valley indicate that steep dipping primary magnetizations (mean = 72.7 ± 6.2°, equating to a paleo-latitude of 58.1°) are recorded in the formation. These are only consistent with the unit being of Permian age, possibly Artinskian based on a magnetostratigraphic argument. Plate tectonic models for this time consistently show the NE corner of the sub-continent >50°S; in the Early Eocene it was just north of the equator, which would have resulted in the unit recording shallow directions. The mean declination is counter-clockwise rotated by ˜94°, around half of which can be related to the motion of the Indian block; the remainder is likely due local Himalayan-age thrusting in the Eastern Syntaxis. Several workers have correlated the Abor Volcanics with broadly coeval mafic volcanic suites in Oman, NE Pakistan-NW India and southern Tibet-Nepal, which developed in response to the Cimmerian block peeling-off eastern Gondwana in the Early-Middle Permian, but we believe there are problems with this model. Instead, we suggest that the Abor basalts relate to India-Antarctica/India-Australia extension that was happening at about the same time. Such an explanation best accommodates the relevant stratigraphical and structural data (present-day position within the Himalayan thrust stack), as well as the plate tectonic model for Permian eastern Gondwana.

  8. Maternal psychosocial predictors of pediatric health care use: Use of the common sense model of health and illness behaviors to extend beyond the usual suspects.

    Science.gov (United States)

    Moran, Tracy E; O'Hara, Michael W

    2006-01-01

    Determinants of pediatric health care use extend beyond the health status of the child and economic and access considerations. Parental factors, particularly those associated with the mother, are critical. The common sense model of health and illness behaviors, which was developed to account for adult health care use, may constitute a framework to study the role of mothers in determining pediatric health care use. In the common sense model, the person's cognitive representations of and affective reactions to bodily states influence health care decision-making. There is a growing literature that points to the importance of maternal psychopathology (reflecting the affective component of the common sense model) and maternal parenting self-efficacy (reflecting the cognitive component of the model) as important contributors to pediatric health care use. The implications of this conceptualization for future research and clinical practice are discussed.

  9. Severe virus associated community acquired pneumonia: predictors of lethality

    Directory of Open Access Journals (Sweden)

    T. O. Pertseva

    2016-06-01

    Full Text Available Despite the fact that the influenza virus pathogenicity factors have been well studied in vitro, in vivo lack is presented in understanding of the those risk factors, objective and laboratory parameters, which related most of all to the fatal virus-associated community-aquired pneumonia (CAP. That is why the purpose of the study was to study the clinical and laboratory characteristics of patients with severe virus-associated CAP during the 2015–2016 influenza epidemic and their role as predictors of patients’ mortality. To do this, patients with severe virus-associated CAP were examined. They were divided into 2 groups depending on the outcome of treatment: 1st- deaths from the virus-associated severe CAP and 2nd - patients with successful treatment of the severe virus-associated CAP. Special statistical method was used – one-dimensional analysis of variance to compare individual parameters between the two groups of patients (surviving and deceased. Pearson χ2 test (contingency table was used for categorical variables. Factors that were significant predictors of mortality as a result of univariate analysis were tested using multifactorial analysis using logistic regression. In the final model, each parameter must have had a significant impact on mortality. It was found that risk factors for death in patients with severe virus-associated CAP according to univariate analysis were: presence of obesity, disorders of consciousness, BH≥35 min, SaO2<80%, PaO2<50 mm Hg, mmHg PaCO2 ≥50 mmHg during hospitalization. Independent predictors of mortality according to the logistic regression are the presence of obesity, disorders of consciousness, PaO2<50 mm Hg, mmHg PaCO2 ≥50 mmHg. Given that among clinical and laboratory parameters key parameters that significantly influence the outcome, are indicators of the severity of hypoxia and hypoxemia, a major step in determining the severity of the patients with virus-associated severe emergency is

  10. Academic engagement and disengagement as predictors of performance in pathophysiology among nursing students.

    Science.gov (United States)

    Salamonson, Yenna; Andrew, Sharon; Everett, Bronwyn

    2009-01-01

    Connecting students with learning activities to promote academic engagement has been a focus of higher education over the past decade, partly driven by an increasing rate of student participation in part-time employment, and a growing concern about the quality of the student experience. Using a prospective survey design, this study selected three elements of academic engagement (homework completion, lecture attendance, and study hours) and academic disengagement (part-time work), to identify predictors of academic performance in a pathophysiology subject in 126 second year nursing students. Homework completion emerged as the strongest positive predictor of academic performance, followed by lecture attendance; however, time spent studying was not a significant predictor of academic performance. Of concern was the finding that the amount of part-time work had a significant and negative impact on academic performance. Combining all elements of academic engagement and disengagement, and controlling for age and ethnicity, the multiple regression model accounted for 34% of the variance in the academic performance of second year nursing students studying pathophysiology. Results from these findings indicate the importance of active learning engagement in influencing academic success, and provide some direction for nursing academics to design effective learning approaches to promote academic engagement of nursing students.

  11. Predictors of Enrolling in Online Courses: An Exploratory Study of Students in Undergrad Marketing Courses

    Directory of Open Access Journals (Sweden)

    Renée J. Fontenot

    2015-01-01

    Full Text Available An exploratory study of undergraduate students enrolled in marketing courses at a Southeastern regional university was conducted to determine the motivations and characteristics of marketing students who plan to be online learners and examined for differences between those who have taken and those who have not taken online classes. An online survey of Likert scales, open-ended questions and demographic questions was sent via class learning management websites. A total of 165 students of the 438 invited to participate completed the survey. A structural model was developed using SMART-PLS to estimate the relationships of constructs that predict taking online courses. Results of the study showed differences in predictors of those that have taken online courses compared to those who plan on taking online courses. A significant predictor of those planning on taking online courses is quality of learning while a significant predictor of those who have taken online courses is scheduling and timing. The results can be used to examine ways to improve/enhance the student’s educational experience, as well as an institution’s effectiveness in attracting the growing body of online learners.

  12. Predictors of Consent in a Randomized Field Study in Child Welfare.

    Science.gov (United States)

    McDonald, Tom; Bhattarai, Jackie; Akin, Becci

    2017-01-01

    Randomized controlled trials (RCTs) are often viewed as the "gold standard" for proving the efficacy and effectiveness of new interventions. However, some are skeptical of the generalizability of the findings that RCTs produce. The characteristics of those willing to participate in research studies have the potential to affect the generalizability of its findings. This study examined factors that could influence consent among families recruited to participate in a randomized field trial in a real-world child welfare setting. This study tested the Parent Management Training Oregon Model for children in foster care with serious emotional disturbance. It employed a post-randomization consent design, whereby the entire sample of eligible participants, not just those who are willing to consent to randomization, are included in the sample. Initial eligibility assessment data and data from the federally mandated reporting system for public child welfare agencies provided the pool of potential predictors of consent. Bivariate and multivariate analyses were conducted to identify statistically significant predictors of consent. Being a dual reunification family was the most significant factor in predicting consent. Unmarried individuals, younger, female parents, cases where parental incarceration was the reason for removal and cases where the removal reason was not due to their children's behavioral problem(s) were also more likely to participate. As one of the first research studies to examine predictors of consent to a randomized field study in child welfare settings, results presented here can act as a preliminary guide for conducting RCTs in child welfare settings.

  13. Distillation Column Flooding Predictor

    Energy Technology Data Exchange (ETDEWEB)

    George E. Dzyacky

    2010-11-23

    The Flooding Predictor™ is a patented advanced control technology proven in research at the Separations Research Program, University of Texas at Austin, to increase distillation column throughput by over 6%, while also increasing energy efficiency by 10%. The research was conducted under a U. S. Department of Energy Cooperative Agreement awarded to George Dzyacky of 2ndpoint, LLC. The Flooding Predictor™ works by detecting the incipient flood point and controlling the column closer to its actual hydraulic limit than historical practices have allowed. Further, the technology uses existing column instrumentation, meaning no additional refining infrastructure is required. Refiners often push distillation columns to maximize throughput, improve separation, or simply to achieve day-to-day optimization. Attempting to achieve such operating objectives is a tricky undertaking that can result in flooding. Operators and advanced control strategies alike rely on the conventional use of delta-pressure instrumentation to approximate the column’s approach to flood. But column delta-pressure is more an inference of the column’s approach to flood than it is an actual measurement of it. As a consequence, delta pressure limits are established conservatively in order to operate in a regime where the column is never expected to flood. As a result, there is much “left on the table” when operating in such a regime, i.e. the capacity difference between controlling the column to an upper delta-pressure limit and controlling it to the actual hydraulic limit. The Flooding Predictor™, an innovative pattern recognition technology, controls columns at their actual hydraulic limit, which research shows leads to a throughput increase of over 6%. Controlling closer to the hydraulic limit also permits operation in a sweet spot of increased energy-efficiency. In this region of increased column loading, the Flooding Predictor is able to exploit the benefits of higher liquid

  14. Novel Anti-Adhesive CMC-PE Hydrogel Significantly Enhanced Morphological and Physiological Recovery after Surgical Decompression in an Animal Model of Entrapment Neuropathy

    Science.gov (United States)

    Urano, Hideki; Iwatsuki, Katsuyuki; Yamamoto, Michiro; Ohnisi, Tetsuro; Kurimoto, Shigeru; Endo, Nobuyuki; Hirata, Hitoshi

    2016-01-01

    We developed a novel hydrogel derived from sodium carboxymethylcellulose (CMC) in which phosphatidylethanolamine (PE) was introduced into the carboxyl groups of CMC to prevent perineural adhesions. This hydrogel has previously shown excellent anti-adhesive effects even after aggressive internal neurolysis in a rat model. Here, we confirmed the effects of the hydrogel on morphological and physiological recovery after nerve decompression. We prepared a rat model of chronic sciatic nerve compression using silicone tubing. Morphological and physiological recovery was confirmed at one, two, and three months after nerve decompression by assessing motor conduction velocity (MCV), the wet weight of the tibialis anterior muscle and morphometric evaluations of nerves. Electrophysiology showed significantly quicker recovery in the CMC-PE group than in the control group (24.0 ± 3.1 vs. 21.0± 2.1 m/s (p < 0.05) at one months and MCV continued to be significantly faster thereafter. Wet muscle weight at one month significantly differed between the CMC-PE (BW) and control groups (0.148 ± 0.020 vs. 0.108 ± 0.019%BW). The mean wet muscle weight was constantly higher in the CMC-PE group than in the control group throughout the experimental period. The axon area at one month was twice as large in the CMC-PE group compared with the control group (24.1 ± 17.3 vs. 12.3 ± 9 μm2) due to the higher ratio of axons with a larger diameter. Although the trend continued throughout the experimental period, the difference decreased after two months and was not statistically significant at three months. Although anti-adhesives can reduce adhesion after nerve injury, their effects on morphological and physiological recovery after surgical decompression of chronic entrapment neuropathy have not been investigated in detail. The present study showed that the new anti-adhesive CMC-PE gel can accelerate morphological and physiological recovery of nerves after decompression surgery. PMID:27741280

  15. Psychological predictors of sport injuries among junior soccer players.

    Science.gov (United States)

    Johnson, U; Ivarsson, A

    2011-02-01

    Previous researches have established models that specify psychological factors that could predict sport injuries. One example is Williams and Andersen's stress-injury model stressing factors such as anxiety, negative life stress and few coping resources. The purpose of the current study was to find psychological factors that could lead to an increased injury risk among junior soccer players, in addition to construct an empirical model of injury risk factors for soccer players. The participants were 108 male and female soccer players (m=17, 6) studying at soccer high schools in southwest Sweden. Five questionnaires were used, State Trait Anxiety Inventory, Sport Anxiety Scale, Life Events Survey for Collegiate Athletes, Athletic Coping Skills Inventory-28 and Swedish universities Scales of Personality. Injury record was collected by athletic trainers at the schools during a period of 8 months. The result suggested four significant predictors that together could explain 23% of injury occurrence. The main factors are life event stress, somatic trait anxiety, mistrust and ineffective coping. These findings partly support Williams and Andersen's stress-injury model and are organized into an empirical model. Recommendations are given to sport medicine teams and coaches concerning issues in sport injury prevention.

  16. Information graphs for binary predictors.

    Science.gov (United States)

    Hughes, G; McRoberts, N; Burnett, F J

    2015-01-01

    Binary predictors are used in a wide range of crop protection decision-making applications. Such predictors provide a simple analytical apparatus for the formulation of evidence related to risk factors, for use in the process of Bayesian updating of probabilities of crop disease. For diagrammatic interpretation of diagnostic probabilities, the receiver operating characteristic is available. Here, we view binary predictors from the perspective of diagnostic information. After a brief introduction to the basic information theoretic concepts of entropy and expected mutual information, we use an example data set to provide diagrammatic interpretations of expected mutual information, relative entropy, information inaccuracy, information updating, and specific information. Our information graphs also illustrate correspondences between diagnostic information and diagnostic probabilities.

  17. The dimensions and role of commensality: A theoretical model drawn from the significance of communal eating among adults in Santiago, Chile.

    Science.gov (United States)

    Giacoman, Claudia

    2016-12-01

    This article examines the significance of communal eating among adults from Santiago, Chile, by elaborating on a theoretical model for commensality that is based on empirical material. Based on this objective, 24 group interviews were conducted in Santiago with family members, coworkers, and friends who shared meals with one another. The results showed that the practice of commensality strengthens the cohesion among the members of a group, providing an interactive space in which communal belonging is symbolized and shared norms are respected. However, eating together also is assigned an ambiguous value: On the one hand, commensality is viewed as positive in enabling connections with others. On the other hand, participating in commensality can be viewed as negative, causing tensions depending on the characteristics of the commensal group and the context.

  18. Cognitive predictors of articulation in writing.

    Science.gov (United States)

    Wormack, L

    1979-06-01

    Among 106 college students scores on a spontaneous 20-min. essay were regressed on referents of verbal and visual spatial ability. 26% of the variability in writing articulation among males was accounted for by the regression of graded writing scores against logical relations and embedded figures tests. 82% of the variability in writing ability among (females was accounted for by the regression of graded writing scores on visual closure, reading comprehension, spatial visualization, and embedded figures tests. The use of verbal and visual sptial referents as predictors of the degree of articulation in spontaneous writing samples consistent with sex-specific models of.cerebral lateralization was described.

  19. Is parenting style a predictor of suicide attempts in a representative sample of adolescents?

    Science.gov (United States)

    Donath, Carolin; Graessel, Elmar; Baier, Dirk; Bleich, Stefan; Hillemacher, Thomas

    2014-04-26

    Suicidal ideation and suicide attempts are serious but not rare conditions in adolescents. However, there are several research and practical suicide-prevention initiatives that discuss the possibility of preventing serious self-harm. Profound knowledge about risk and protective factors is therefore necessary. The aim of this study is a) to clarify the role of parenting behavior and parenting styles in adolescents' suicide attempts and b) to identify other statistically significant and clinically relevant risk and protective factors for suicide attempts in a representative sample of German adolescents. In the years 2007/2008, a representative written survey of N = 44,610 students in the 9th grade of different school types in Germany was conducted. In this survey, the lifetime prevalence of suicide attempts was investigated as well as potential predictors including parenting behavior. A three-step statistical analysis was carried out: I) As basic model, the association between parenting and suicide attempts was explored via binary logistic regression controlled for age and sex. II) The predictive values of 13 additional potential risk/protective factors were analyzed with single binary logistic regression analyses for each predictor alone. Non-significant predictors were excluded in Step III. III) In a multivariate binary logistic regression analysis, all significant predictor variables from Step II and the parenting styles were included after testing for multicollinearity. Three parental variables showed a relevant association with suicide attempts in adolescents - (all protective): mother's warmth and father's warmth in childhood and mother's control in adolescence (Step I). In the full model (Step III), Authoritative parenting (protective: OR: .79) and Rejecting-Neglecting parenting (risk: OR: 1.63) were identified as significant predictors (p parental separation events. Parenting style does matter. While children of Authoritative parents profit, children of

  20. Is parenting style a predictor of suicide attempts in a representative sample of adolescents?

    Science.gov (United States)

    2014-01-01

    Background Suicidal ideation and suicide attempts are serious but not rare conditions in adolescents. However, there are several research and practical suicide-prevention initiatives that discuss the possibility of preventing serious self-harm. Profound knowledge about risk and protective factors is therefore necessary. The aim of this study is a) to clarify the role of parenting behavior and parenting styles in adolescents’ suicide attempts and b) to identify other statistically significant and clinically relevant risk and protective factors for suicide attempts in a representative sample of German adolescents. Methods In the years 2007/2008, a representative written survey of N = 44,610 students in the 9th grade of different school types in Germany was conducted. In this survey, the lifetime prevalence of suicide attempts was investigated as well as potential predictors including parenting behavior. A three-step statistical analysis was carried out: I) As basic model, the association between parenting and suicide attempts was explored via binary logistic regression controlled for age and sex. II) The predictive values of 13 additional potential risk/protective factors were analyzed with single binary logistic regression analyses for each predictor alone. Non-significant predictors were excluded in Step III. III) In a multivariate binary logistic regression analysis, all significant predictor variables from Step II and the parenting styles were included after testing for multicollinearity. Results Three parental variables showed a relevant association with suicide attempts in adolescents – (all protective): mother’s warmth and father’s warmth in childhood and mother’s control in adolescence (Step I). In the full model (Step III), Authoritative parenting (protective: OR: .79) and Rejecting-Neglecting parenting (risk: OR: 1.63) were identified as significant predictors (p parental separation events. Conclusions Parenting style does matter. While

  1. Utility-based criteria for selecting patients with hepatocellular carcinoma for liver transplantation: A multicenter cohort study using the alpha-fetoprotein model as a survival predictor.

    Science.gov (United States)

    Vitale, Alessandro; Farinati, Fabio; Burra, Patrizia; Trevisani, Franco; Giannini, Edoardo G; Ciccarese, Francesca; Piscaglia, Fabio; Rapaccini, Gian Lodovico; Di Marco, Mariella; Caturelli, Eugenio; Zoli, Marco; Borzio, Franco; Cabibbo, Giuseppe; Felder, Martina; Sacco, Rodolfo; Morisco, Filomena; Missale, Gabriele; Foschi, Francesco Giuseppe; Gasbarrini, Antonio; Svegliati Baroni, Gianluca; Virdone, Roberto; Chiaramonte, Maria; Spolverato, Gaya; Cillo, Umberto

    2015-10-01

    The lifetime utility of liver transplantation (LT) in patients with hepatocellular carcinoma (HCC) is still controversial. The aim of this study was to ascertain when LT is cost-effective for HCC patients, with a view to proposing new transplant selection criteria. The study involved a real cohort of potentially transplantable Italian HCC patients (n = 2419 selected from the Italian Liver Cancer group database) who received nontransplant therapies. A non-LT survival analysis was conducted, the direct costs of therapies were calculated, and a Markov model was used to compute the cost utility of LT over non-LT therapies in Italian and US cost scenarios. Post-LT survival was calculated using the alpha-fetoprotein (AFP) model on the basis of AFP values and radiological size and number of nodules. The primary endpoint was the net health benefit (NHB), defined as LT survival benefit in quality-adjusted life years minus incremental costs (US $)/willingness to pay. The calculated median cost of non-LT therapies per patient was US $53,042 in Italy and US $62,827 in the United States. On Monte Carlo simulation, the NHB of LT was always positive for AFP model values ≤ 3 and always negative for values > 7 in both countries. A multivariate model showed that nontumor variables (patient's age, Child-Turcotte-Pugh [CTP] class, and alternative therapies) had the potential to shift the AFP model threshold of LT cost-ineffectiveness from 3 to 7. LT proved always cost-effective for HCC patients with AFP model values ≤ 3, whereas the cost-ineffectiveness threshold ranged between 3 and 7 using nontumor variables.

  2. Multiple predictor smoothing methods for sensitivity analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Helton, Jon Craig; Storlie, Curtis B.

    2006-08-01

    The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (1) locally weighted regression (LOESS), (2) additive models, (3) projection pursuit regression, and (4) recursive partitioning regression. The indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present.

  3. Predictors of trips to food destinations

    Directory of Open Access Journals (Sweden)

    Kerr Jacqueline

    2012-05-01

    Full Text Available Abstract Background Food environment studies have focused on ethnic and income disparities in food access. Few studies have investigated distance travelled for food and did not aim to inform the geographic scales at which to study the relationship between food environments and obesity. Further, studies have not considered neighborhood design as a predictor of food purchasing behavior. Methods Atlanta residents (N = 4800 who completed a travel diary and reported purchasing or consuming food at one of five food locations were included in the analyses. A total of 11,995 food-related trips were reported. Using mixed modeling to adjust for clustering of trips by participants and households, person-level variables (e.g. demographics, neighborhood-level urban form measures, created in GIS, and trip characteristics (e.g. time of day, origin and destination were investigated as correlates of distance travelled for food and frequency of grocery store and fast food outlet trips. Results Mean travel distance for food ranged from 4.5 miles for coffee shops to 6.3 miles for superstores. Type of store, urban form, type of tour, day of the week and ethnicity were all significantly related to distance travelled for food. Origin and destination environment, type of tour, day of week, age, gender, income, ethnicity, vehicle access and obesity status were all significantly related to visiting a grocery store. Home neighborhood environment, day of week, type of tour, gender, income, education level, age, and obesity status were all significantly related to likelihood of visiting a fastfood outlet. Conclusions The present study demonstrated that people travel sizeable distances for food and this distance is related to urban. Results suggest that researchers need to employ different methods to characterize food environments than have been used to assess urban form in studies of physical activity. Food is most often purchased while traveling from locations other

  4. SIGNIFICANT MOMENTS IN THE HISTORY AND EVOLUTION OF THE TOURISTIC CITY OF CONSTANTA AND ANTICIPATION OF THE NUMBER OF ARRIVED TOURISTS USING THE ARIMA MODELS

    Directory of Open Access Journals (Sweden)

    Mariana C. JUGANARU

    2016-12-01

    Full Text Available For the Romanian economy, Constanța is appreciated mainly because it is the biggest port town in the country, and for many generations it has been the city where they spend many of their summer holidays. But how many of us know that the bathroom resort – Constanța has an officially attested existence of 140 years? In this study, the aim is, on one side, to present the significant moments in the history and evolution of this historic city, in order to bring to the foreground and sustain the position that the city has at the present moment in the system of touristic spots on the Romanian seaside, and on the other side, our concern is to know the future evolution of the touristic activity, to make some previsions using the ARIMA models, for one of the most used indicators in the analysis of touristic circulation, respectively: the number of arrivals of tourists, structurally and totally: Romanian and foreigners. We think that the obtained results, applying these models, may be considered a solid base for different debates regarding the choice of an efficient strategy, that should allow reaching an equilibrium between the effort of attracting a number of tourists as big as possible (Romanian and foreigners, of growing their degree of satisfaction towards the touristic offer and the concern of not generating disruptions in the economic, social and cultural life of the city.

  5. Motavizumab, A Neutralizing Anti-Respiratory Syncytial Virus (Rsv Monoclonal Antibody Significantly Modifies The Local And Systemic Cytokine Responses Induced By Rsv In The Mouse Model

    Directory of Open Access Journals (Sweden)

    Jafri Hasan S

    2007-10-01

    Full Text Available Abstract Motavizumab (MEDI-524 is a monoclonal antibody with enhanced neutralizing activity against RSV. In mice, motavizumab suppressed RSV replication which resulted in significant reduction of clinical parameters of disease severity. We evaluated the effect of motavizumab on the local and systemic immune response induced by RSV in the mouse model. Balb/c mice were intranasally inoculated with 106.5 PFU RSV A2 or medium. Motavizumab was given once intraperitoneally (1.25 mg/mouse as prophylaxis, 24 h before virus inoculation. Bronchoalveolar lavage (BAL and serum samples were obtained at days 1, 5 (acute and 28 (long-term post inoculation and analyzed with a multiplex assay (Beadlyte Upstate, NY for simultaneous quantitation of 18 cytokines: IL-1α, IL-1β, IL-2, IL-3, IL-4, IL-5, IL-6, KC (similar to human IL-8, IL-10, IL-12p40, IL-12p70, IL-13, IL-17, TNF-α, MCP-1, RANTES, IFN-γ and GM-CSF. Overall, cytokine concentrations were lower in serum than in BAL samples. By day 28, only KC was detected in BAL specimens at low concentrations in all groups. Administration of motavizumab significantly reduced (p

  6. Significant RF-EMF and thermal levels observed in a computational model of a person with a tibial plate for grounded 40 MHz exposure.

    Science.gov (United States)

    McIntosh, Robert L; Iskra, Steve; Anderson, Vitas

    2014-05-01

    Using numerical modeling, a worst-case scenario is considered when a person with a metallic implant is exposed to a radiofrequency (RF) electromagnetic field (EMF). An adult male standing on a conductive ground plane was exposed to a 40 MHz vertically polarized plane wave field, close to whole-body resonance where maximal induced current flows are expected in the legs. A metal plate (50-300 mm long) was attached to the tibia in the left leg. The findings from this study re-emphasize the need to ensure compliance with limb current reference levels for exposures near whole-body resonance, and not just rely on compliance with ambient electric (E) and magnetic (H) field reference levels. Moreover, we emphasize this recommendation for someone with a tibial plate, as failure to comply may result in significant tissue damage (increases in the localized temperature of 5-10 °C were suggested by the modeling for an incident E-field of 61.4 V/m root mean square (rms)). It was determined that the occupational reference level for limb current (100 mA rms), as stipulated in the 1998 guidelines of the International Commission on Non-Ionizing Radiation Protection (ICNIRP), is satisfied if the plane wave incident E-field levels are no more than 29.8 V/m rms without an implant and 23.4 V/m rms for the model with a 300 mm implant.

  7. A dual acting compound releasing nitric oxide (NO) and ibuprofen, NCX 320, shows significant therapeutic effects in a mouse model of muscular dystrophy.

    Science.gov (United States)

    Sciorati, Clara; Miglietta, Daniela; Buono, Roberta; Pisa, Viviana; Cattaneo, Dario; Azzoni, Emanuele; Brunelli, Silvia; Clementi, Emilio

    2011-09-01

    A resolutive therapy for muscular dystrophies, a heterogeneous group of genetic diseases leading to muscular degeneration and in the severe forms to death, is still lacking. Since inflammation and defects in nitric oxide generation are recognized key pathogenic events in muscular dystrophy, we have analysed the effects of a derivative of ibuprofen, NCX 320, belonging to the class of cyclooxygenase inhibiting nitric oxide donator (CINOD), in the α-sarcoglycan null mice, a severe mouse model of dystrophy. NCX 320 was administered daily in the diet for 8months starting 1month from weaning. Muscle functional recovery was evaluated by free wheel and treadmill tests at 8months. Serum creatine kinase activity, as well as the number of diaphragm inflammatory infiltrates and necrotic fibres, was measured as indexes of skeletal muscle damage. Muscle regeneration was evaluated in diaphragm and tibialis anterior muscles, measuring the numbers of centronucleated fibres and of myogenic precursor cells. NCX 320 mitigated muscle damage, reducing significantly serum creatine kinase activity, the number of necrotic fibres and inflammatory infiltrates. Moreover, NCX 320 stimulated muscle regeneration increasing significantly the number of myogenic precursor cells and regenerating fibres. All these effects concurred in inducing a significant improvement of muscle function, as assessed by both free wheel and treadmill tests. These results describe the properties of a new compound incorporating nitric oxide donation together with anti-inflammatory properties, showing that it is effective in slowing muscle dystrophy progression long term. Of importance, this new compound deserves specific attention for its potential in the therapy of muscular dystrophy given that ibuprofen is well tolerated in paediatric patients and with a profile of safety that makes it suitable for chronic treatment such as the one required in muscular dystrophies.

  8. Hypoxaemia in Mozambican children <5 years of age admitted to hospital with clinical severe pneumonia: clinical features and performance of predictor models.

    Science.gov (United States)

    Bassat, Quique; Lanaspa, Miguel; Machevo, Sónia; O'Callaghan-Gordo, Cristina; Madrid, Lola; Nhampossa, Tacilta; Acácio, Sozinho; Roca, Anna; Alonso, Pedro L

    2016-09-01

    To determine the prevalence of hypoxaemia among under-five children admitted to hospital with clinical severe pneumonia and to assess the performance to diagnose hypoxaemia of models based on clinical signs. We conducted a hospital-based survey in a district hospital from Southern Mozambique. A total of 825 children were recruited after obtaining an informed consent. The prevalence of hypoxaemia on admission was 27.9%, and 19.8% of these children died (OR compared with non-hypoxaemic children 3.22, 95% CI 1.98-5.21, P < 0.001). The model with larger area under the ROC curve (AUC-ROC) to predict hypoxaemia included cyanosis or thoracoabdominal breathing or respiratory rate ≥70 breaths per minute. None of the models performed well when tested in different case scenarios of oxygen availability through mathematical modelling, with over 50% of hypoxaemic children not receiving oxygen even in favourable case scenarios. Clinical signs alone or in combination are not suitable to diagnose hypoxaemia. The use of pulse oximeters should be strongly encouraged. © 2016 John Wiley & Sons Ltd.

  9. Openness to Experience and Night-Sky Watching Interest as Predictors of Reading for Pleasure: Path Analysis of a Mediation Model

    Science.gov (United States)

    Kelly, William E.

    2010-01-01

    The relation between reading for pleasure, night-sky watching interest, and openness to experience were examined in a sample of 129 college students. Results of a path analysis examining a mediation model indicated that the influence of night-sky interest on reading for pleasure was not mediated by the broad personality domain openness to…

  10. DEVELOPMENT OF A NOVEL RADIATIVELY/CONDUCTIVELY STABILIZED BURNER FOR SIGNIFICANT REDUCTION OF NOx EMISSIONS AND FOR ADVANCING THE MODELING AND UNDERSTANDING OF PULVERIZED COAL COMBUSTION AND EMISSIONS

    Energy Technology Data Exchange (ETDEWEB)

    Noam Lior; Stuart W. Churchill

    2003-10-01

    The primary objective of the proposed study was the study and analysis of, and design recommendations for, a novel radiatively-conductively stabilized combustion (RCSC) process for pulverized coal, which, based on our prior studies with both fluid fuels and pulverized coal, holds a high promise to reduce NO{sub x} production significantly. We have primarily engaged in continuing and improving our process modeling and analysis, obtained a large amount of quantitative information about the effects of the major parameters on NO{sub x} production, conducted an extensive exergy analysis of the process, evaluated the practicalities of employing the Radiatively-Conductively Stabilized Combustor (RCSC) to large power and heat plants, and improved the experimental facility. Prior experimental work has proven the feasibility of the combustor, but slagging during coal combustion was observed and should be dealt with. The primary outcomes and conclusions from the s