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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

An Examination of Master's Student Retention & Completion

ERIC Educational Resources Information Center

Barry, Melissa; Mathies, Charles

2011-01-01

This study was conducted at a research-extensive public university in the southeastern United States. It examined the retention and completion of master's degree students across numerous disciplines. Results were derived from a series of descriptive statistics, T-tests, and a series of binary logistic regression models. The findings from binary…

PARAMETRIC AND NON PARAMETRIC (MARS: MULTIVARIATE ADDITIVE REGRESSION SPLINES) LOGISTIC REGRESSIONS FOR PREDICTION OF A DICHOTOMOUS RESPONSE VARIABLE WITH AN EXAMPLE FOR PRESENCE/ABSENCE OF AMPHIBIANS

EPA Science Inventory

The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response ...

Analyzing Student Learning Outcomes: Usefulness of Logistic and Cox Regression Models. IR Applications, Volume 5

ERIC Educational Resources Information Center

Chen, Chau-Kuang

2005-01-01

Logistic and Cox regression methods are practical tools used to model the relationships between certain student learning outcomes and their relevant explanatory variables. The logistic regression model fits an S-shaped curve into a binary outcome with data points of zero and one. The Cox regression model allows investigators to study the duration…

Risk estimation using probability machines.

PubMed

Dasgupta, Abhijit; Szymczak, Silke; Moore, Jason H; Bailey-Wilson, Joan E; Malley, James D

2014-03-01

Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a "risk machine", will share properties from the statistical machine that it is derived from.

Logistic Map for Cancellable Biometrics

NASA Astrophysics Data System (ADS)

Supriya, V. G., Dr; Manjunatha, Ramachandra, Dr

2017-08-01

This paper presents design and implementation of secured biometric template protection system by transforming the biometric template using binary chaotic signals and 3 different key streams to obtain another form of template and demonstrating its efficiency by the results and investigating on its security through analysis including, key space analysis, information entropy and key sensitivity analysis.

The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models

ERIC Educational Resources Information Center

Schoeneberger, Jason A.

2016-01-01

The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…

Are math readiness and personality predictive of first-year retention in engineering?

PubMed

Moses, Laurie; Hall, Cathy; Wuensch, Karl; De Urquidi, Karen; Kauffmann, Paul; Swart, William; Duncan, Steve; Dixon, Gene

2011-01-01

On the basis of J. G. Borkowski, L. K. Chan, and N. Muthukrishna's model of academic success (2000), the present authors hypothesized that freshman retention in an engineering program would be related to not only basic aptitude but also affective factors. Participants were 129 college freshmen with engineering as their stated major. Aptitude was measured by SAT verbal and math scores, high school grade-point average (GPA), and an assessment of calculus readiness. Affective factors were assessed by the NEO-Five Factor Inventory (FFI; P. I. Costa & R. R. McCrae, 2007), and the Nowicki-Duke Locus of Control (LOC) scale (S. Nowicki & M. Duke, 1974). A binary logistic regression analysis found that calculus readiness and high school GPA were predictive of retention. Scores on the Neuroticism and Openness subscales from the NEO-FFI and LOC were correlated with retention status, but Openness was the only affective factor with a significant unique effect in the binary logistic regression. Results of the study lend modest support to Borkowski's model.

The crux of the method: assumptions in ordinary least squares and logistic regression.

PubMed

Long, Rebecca G

2008-10-01

Logistic regression has increasingly become the tool of choice when analyzing data with a binary dependent variable. While resources relating to the technique are widely available, clear discussions of why logistic regression should be used in place of ordinary least squares regression are difficult to find. The current paper compares and contrasts the assumptions of ordinary least squares with those of logistic regression and explains why logistic regression's looser assumptions make it adept at handling violations of the more important assumptions in ordinary least squares.

Propensity of University Students in the Region of Antofagasta, Chile to Create Enterprise

ERIC Educational Resources Information Center

Romani, Gianni; Didonet, Simone; Contuliano, Sue-Hellen; Portilla, Rodrigo

2013-01-01

The authors aim to discuss the propensity or intention to create enterprise among university students in the region of Antofagasta, Chile, and to analyze the factors that influence the step from desire to intention. 681 students were surveyed. The data were analyzed by binary logistical regression. The results show that curriculum is among the…

An Attempt at Quantifying Factors that Affect Efficiency in the Management of Solid Waste Produced by Commercial Businesses in the City of Tshwane, South Africa

PubMed Central

Worku, Yohannes; Muchie, Mammo

2012-01-01

Objective. The objective was to investigate factors that affect the efficient management of solid waste produced by commercial businesses operating in the city of Pretoria, South Africa. Methods. Data was gathered from 1,034 businesses. Efficiency in solid waste management was assessed by using a structural time-based model designed for evaluating efficiency as a function of the length of time required to manage waste. Data analysis was performed using statistical procedures such as frequency tables, Pearson's chi-square tests of association, and binary logistic regression analysis. Odds ratios estimated from logistic regression analysis were used for identifying key factors that affect efficiency in the proper disposal of waste. Results. The study showed that 857 of the 1,034 businesses selected for the study (83%) were found to be efficient enough with regards to the proper collection and disposal of solid waste. Based on odds ratios estimated from binary logistic regression analysis, efficiency in the proper management of solid waste was significantly influenced by 4 predictor variables. These 4 influential predictor variables are lack of adherence to waste management regulations, wrong perception, failure to provide customers with enough trash cans, and operation of businesses by employed managers, in a decreasing order of importance. PMID:23209483

Unitary Response Regression Models

ERIC Educational Resources Information Center

Lipovetsky, S.

2007-01-01

The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…

Multiple Logistic Regression Analysis of Cigarette Use among High School Students

ERIC Educational Resources Information Center

Adwere-Boamah, Joseph

2011-01-01

A binary logistic regression analysis was performed to predict high school students' cigarette smoking behavior from selected predictors from 2009 CDC Youth Risk Behavior Surveillance Survey. The specific target student behavior of interest was frequent cigarette use. Five predictor variables included in the model were: a) race, b) frequency of…

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

PubMed

Cook, James P; Mahajan, Anubha; Morris, Andrew P

2017-02-01

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

Won't You Be My Neighbor? Using an Ecological Approach to Examine the Impact of Community on Revictimization

ERIC Educational Resources Information Center

Obasaju, Mayowa A.; Palin, Frances L.; Jacobs, Carli; Anderson, Page; Kaslow, Nadine J.

2009-01-01

An ecological model is used to explore the moderating effects of community-level variables on the relation between childhood sexual, physical, and emotional abuse and adult intimate partner violence (IPV) within a sample of 98 African American women from low incomes. Results from hierarchical, binary logistics regressions analyses show that…

The cost of acquiring public hunting access on family forests lands

Treesearch

Michael A. Kilgore; Stephanie A. Snyder; Joesph M. Schertz; Steven J. Taff

2008-01-01

To address the issue of declining access to private forest land in the United States for hunting, over 1,000 Minnesota family forest owners were surveyed to estimate the cost of acquiring non-exclusive public hunting access rights. The results indicate landowner interest in selling access rights is extremely modest. Using binary logistic regression, the mean annual...

Predicting the "graduate on time (GOT)" of PhD students using binary logistics regression model

NASA Astrophysics Data System (ADS)

Shariff, S. Sarifah Radiah; Rodzi, Nur Atiqah Mohd; Rahman, Kahartini Abdul; Zahari, Siti Meriam; Deni, Sayang Mohd

2016-10-01

Malaysian government has recently set a new goal to produce 60,000 Malaysian PhD holders by the year 2023. As a Malaysia's largest institution of higher learning in terms of size and population which offers more than 500 academic programmes in a conducive and vibrant environment, UiTM has taken several initiatives to fill up the gap. Strategies to increase the numbers of graduates with PhD are a process that is challenging. In many occasions, many have already identified that the struggle to get into the target set is even more daunting, and that implementation is far too ideal. This has further being progressing slowly as the attrition rate increases. This study aims to apply the proposed models that incorporates several factors in predicting the number PhD students that will complete their PhD studies on time. Binary Logistic Regression model is proposed and used on the set of data to determine the number. The results show that only 6.8% of the 2014 PhD students are predicted to graduate on time and the results are compared wih the actual number for validation purpose.

Noise exposure-response relationships established from repeated binary observations: Modeling approaches and applications.

PubMed

Schäffer, Beat; Pieren, Reto; Mendolia, Franco; Basner, Mathias; Brink, Mark

2017-05-01

Noise exposure-response relationships are used to estimate the effects of noise on individuals or a population. Such relationships may be derived from independent or repeated binary observations, and modeled by different statistical methods. Depending on the method by which they were established, their application in population risk assessment or estimation of individual responses may yield different results, i.e., predict "weaker" or "stronger" effects. As far as the present body of literature on noise effect studies is concerned, however, the underlying statistical methodology to establish exposure-response relationships has not always been paid sufficient attention. This paper gives an overview on two statistical approaches (subject-specific and population-averaged logistic regression analysis) to establish noise exposure-response relationships from repeated binary observations, and their appropriate applications. The considerations are illustrated with data from three noise effect studies, estimating also the magnitude of differences in results when applying exposure-response relationships derived from the two statistical approaches. Depending on the underlying data set and the probability range of the binary variable it covers, the two approaches yield similar to very different results. The adequate choice of a specific statistical approach and its application in subsequent studies, both depending on the research question, are therefore crucial.

A combination chaotic system and application in color image encryption

NASA Astrophysics Data System (ADS)

Parvaz, R.; Zarebnia, M.

2018-05-01

In this paper, by using Logistic, Sine and Tent systems we define a combination chaotic system. Some properties of the chaotic system are studied by using figures and numerical results. A color image encryption algorithm is introduced based on new chaotic system. Also this encryption algorithm can be used for gray scale or binary images. The experimental results of the encryption algorithm show that the encryption algorithm is secure and practical.

Comparison between students and residents on determinants of willingness to separate waste and waste separation behaviour in Zhengzhou, China.

PubMed

Dai, Xiaoping; Han, Yuping; Zhang, Xiaohong; Hu, Wei; Huang, Liangji; Duan, Wenpei; Li, Siyi; Liu, Xiaolu; Wang, Qian

2017-09-01

A better understanding of willingness to separate waste and waste separation behaviour can aid the design and improvement of waste management policies. Based on the intercept questionnaire survey data of undergraduate students and residents in Zhengzhou City of China, this article compared factors affecting the willingness and behaviour of students and residents to participate in waste separation using two binary logistic regression models. Improvement opportunities for waste separation were also discussed. Binary logistic regression results indicate that knowledge of and attitude to waste separation and acceptance of waste education significantly affect the willingness of undergraduate students to separate waste, and demographic factors, such as gender, age, education level, and income, significantly affect the willingness of residents to do so. Presence of waste-specific bins and attitude to waste separation are drivers of waste separation behaviour for both students and residents. Improved education about waste separation and facilities are effective to stimulate waste separation, and charging on unsorted waste may be an effective way to improve it in Zhengzhou.

Detecting nonsense for Chinese comments based on logistic regression

NASA Astrophysics Data System (ADS)

Zhuolin, Ren; Guang, Chen; Shu, Chen

2016-07-01

To understand cyber citizens' opinion accurately from Chinese news comments, the clear definition on nonsense is present, and a detection model based on logistic regression (LR) is proposed. The detection of nonsense can be treated as a binary-classification problem. Besides of traditional lexical features, we propose three kinds of features in terms of emotion, structure and relevance. By these features, we train an LR model and demonstrate its effect in understanding Chinese news comments. We find that each of proposed features can significantly promote the result. In our experiments, we achieve a prediction accuracy of 84.3% which improves the baseline 77.3% by 7%.

Classifying machinery condition using oil samples and binary logistic regression

NASA Astrophysics Data System (ADS)

Phillips, J.; Cripps, E.; Lau, John W.; Hodkiewicz, M. R.

2015-08-01

The era of big data has resulted in an explosion of condition monitoring information. The result is an increasing motivation to automate the costly and time consuming human elements involved in the classification of machine health. When working with industry it is important to build an understanding and hence some trust in the classification scheme for those who use the analysis to initiate maintenance tasks. Typically "black box" approaches such as artificial neural networks (ANN) and support vector machines (SVM) can be difficult to provide ease of interpretability. In contrast, this paper argues that logistic regression offers easy interpretability to industry experts, providing insight to the drivers of the human classification process and to the ramifications of potential misclassification. Of course, accuracy is of foremost importance in any automated classification scheme, so we also provide a comparative study based on predictive performance of logistic regression, ANN and SVM. A real world oil analysis data set from engines on mining trucks is presented and using cross-validation we demonstrate that logistic regression out-performs the ANN and SVM approaches in terms of prediction for healthy/not healthy engines.

Prevalence and determinants of cardiovascular disease risk factors among the residents of urban community housing projects in Malaysia.

PubMed

Amiri, Mohammadreza; Majid, Hazreen Abdul; Hairi, FarizahMohd; Thangiah, Nithiah; Bulgiba, Awang; Su, Tin Tin

2014-01-01

The objectives are to assess the prevalence and determinants of cardiovascular disease (CVD) risk factors among the residents of Community Housing Projects in metropolitan Kuala Lumpur, Malaysia. By using simple random sampling, we selected and surveyed 833 households which comprised of 3,722 individuals. Out of the 2,360 adults, 50.5% participated in blood sampling and anthropometric measurement sessions. Uni and bivariate data analysis and multivariate binary logistic regression were applied to identify demographic and socioeconomic determinants of the existence of having at least one CVD risk factor. As a Result, while obesity (54.8%), hypercholesterolemia (51.5%), and hypertension (39.3%) were the most common CVD risk factors among the low-income respondents, smoking (16.3%), diabetes mellitus (7.8%) and alcohol consumption (1.4%) were the least prevalent. Finally, the results from the multivariate binary logistic model illustrated that compared to the Malays, the Indians were 41% less likely to have at least one of the CVD risk factors (OR = 0.59; 95% CI: 0.37 - 0.93). In Conclusion, the low-income individuals were at higher risk of developing CVDs. Prospective policies addressing preventive actions and increased awareness focusing on low-income communities are highly recommended and to consider age, gender, ethnic backgrounds, and occupation classes.

Prevalence and determinants of cardiovascular disease risk factors among the residents of urban community housing projects in Malaysia

PubMed Central

2014-01-01

Objectives The objectives are to assess the prevalence and determinants of cardiovascular disease (CVD) risk factors among the residents of Community Housing Projects in metropolitan Kuala Lumpur, Malaysia. Method By using simple random sampling, we selected and surveyed 833 households which comprised of 3,722 individuals. Out of the 2,360 adults, 50.5% participated in blood sampling and anthropometric measurement sessions. Uni and bivariate data analysis and multivariate binary logistic regression were applied to identify demographic and socioeconomic determinants of the existence of having at least one CVD risk factor. Results As a Result, while obesity (54.8%), hypercholesterolemia (51.5%), and hypertension (39.3%) were the most common CVD risk factors among the low-income respondents, smoking (16.3%), diabetes mellitus (7.8%) and alcohol consumption (1.4%) were the least prevalent. Finally, the results from the multivariate binary logistic model illustrated that compared to the Malays, the Indians were 41% less likely to have at least one of the CVD risk factors (OR = 0.59; 95% CI: 0.37 - 0.93). Conclusion In Conclusion, the low-income individuals were at higher risk of developing CVDs. Prospective policies addressing preventive actions and increased awareness focusing on low-income communities are highly recommended and to consider age, gender, ethnic backgrounds, and occupation classes. PMID:25436515

A comparison of multiple imputation methods for incomplete longitudinal binary data.

PubMed

Yamaguchi, Yusuke; Misumi, Toshihiro; Maruo, Kazushi

2018-01-01

Longitudinal binary data are commonly encountered in clinical trials. Multiple imputation is an approach for getting a valid estimation of treatment effects under an assumption of missing at random mechanism. Although there are a variety of multiple imputation methods for the longitudinal binary data, a limited number of researches have reported on relative performances of the methods. Moreover, when focusing on the treatment effect throughout a period that has often been used in clinical evaluations of specific disease areas, no definite investigations comparing the methods have been available. We conducted an extensive simulation study to examine comparative performances of six multiple imputation methods available in the SAS MI procedure for longitudinal binary data, where two endpoints of responder rates at a specified time point and throughout a period were assessed. The simulation study suggested that results from naive approaches of a single imputation with non-responders and a complete case analysis could be very sensitive against missing data. The multiple imputation methods using a monotone method and a full conditional specification with a logistic regression imputation model were recommended for obtaining unbiased and robust estimations of the treatment effect. The methods were illustrated with data from a mental health research.

Predicting the occurrence of wildfires with binary structured additive regression models.

PubMed

Ríos-Pena, Laura; Kneib, Thomas; Cadarso-Suárez, Carmen; Marey-Pérez, Manuel

2017-02-01

Wildfires are one of the main environmental problems facing societies today, and in the case of Galicia (north-west Spain), they are the main cause of forest destruction. This paper used binary structured additive regression (STAR) for modelling the occurrence of wildfires in Galicia. Binary STAR models are a recent contribution to the classical logistic regression and binary generalized additive models. Their main advantage lies in their flexibility for modelling non-linear effects, while simultaneously incorporating spatial and temporal variables directly, thereby making it possible to reveal possible relationships among the variables considered. The results showed that the occurrence of wildfires depends on many covariates which display variable behaviour across space and time, and which largely determine the likelihood of ignition of a fire. The joint possibility of working on spatial scales with a resolution of 1 × 1 km cells and mapping predictions in a colour range makes STAR models a useful tool for plotting and predicting wildfire occurrence. Lastly, it will facilitate the development of fire behaviour models, which can be invaluable when it comes to drawing up fire-prevention and firefighting plans. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

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

2014-12-01

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

Association of Brain-Derived Neurotrophic Factor and Vitamin D with Depression and Obesity: A Population-Based Study.

PubMed

Goltz, Annemarie; Janowitz, Deborah; Hannemann, Anke; Nauck, Matthias; Hoffmann, Johanna; Seyfart, Tom; Völzke, Henry; Terock, Jan; Grabe, Hans Jörgen

2018-06-19

Depression and obesity are widespread and closely linked. Brain-derived neurotrophic factor (BDNF) and vitamin D are both assumed to be associated with depression and obesity. Little is known about the interplay between vitamin D and BDNF. We explored the putative associations and interactions between serum BDNF and vitamin D levels with depressive symptoms and abdominal obesity in a large population-based cohort. Data were obtained from the population-based Study of Health in Pomerania (SHIP)-Trend (n = 3,926). The associations of serum BDNF and vitamin D levels with depressive symptoms (measured using the Patient Health Questionnaire) were assessed with binary and multinomial logistic regression models. The associations of serum BDNF and vitamin D levels with obesity (measured by the waist-to-hip ratio [WHR]) were assessed with binary logistic and linear regression models with restricted cubic splines. Logistic regression models revealed inverse associations of vitamin D with depression (OR = 0.966; 95% CI 0.951-0.981) and obesity (OR = 0.976; 95% CI 0.967-0.985). No linear association of serum BDNF with depression or obesity was found. However, linear regression models revealed a U-shaped association of BDNF with WHR (p < 0.001). Vitamin D was inversely associated with depression and obesity. BDNF was associated with abdominal obesity, but not with depression. At the population level, our results support the relevant roles of vitamin D and BDNF in mental and physical health-related outcomes. © 2018 S. Karger AG, Basel.

Binary Logistic Regression Analysis for Detecting Differential Item Functioning: Effectiveness of R[superscript 2] and Delta Log Odds Ratio Effect Size Measures

ERIC Educational Resources Information Center

Hidalgo, Mª Dolores; Gómez-Benito, Juana; Zumbo, Bruno D.

2014-01-01

The authors analyze the effectiveness of the R[superscript 2] and delta log odds ratio effect size measures when using logistic regression analysis to detect differential item functioning (DIF) in dichotomous items. A simulation study was carried out, and the Type I error rate and power estimates under conditions in which only statistical testing…

Determination of riverbank erosion probability using Locally Weighted Logistic Regression

NASA Astrophysics Data System (ADS)

Ioannidou, Elena; Flori, Aikaterini; Varouchakis, Emmanouil A.; Giannakis, Georgios; Vozinaki, Anthi Eirini K.; Karatzas, George P.; Nikolaidis, Nikolaos

2015-04-01

Riverbank erosion is a natural geomorphologic process that affects the fluvial environment. The most important issue concerning riverbank erosion is the identification of the vulnerable locations. An alternative to the usual hydrodynamic models to predict vulnerable locations is to quantify the probability of erosion occurrence. This can be achieved by identifying the underlying relations between riverbank erosion and the geomorphological or hydrological variables that prevent or stimulate erosion. Thus, riverbank erosion can be determined by a regression model using independent variables that are considered to affect the erosion process. The impact of such variables may vary spatially, therefore, a non-stationary regression model is preferred instead of a stationary equivalent. Locally Weighted Regression (LWR) is proposed as a suitable choice. This method can be extended to predict the binary presence or absence of erosion based on a series of independent local variables by using the logistic regression model. It is referred to as Locally Weighted Logistic Regression (LWLR). Logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable (e.g. binary response) based on one or more predictor variables. The method can be combined with LWR to assign weights to local independent variables of the dependent one. LWR allows model parameters to vary over space in order to reflect spatial heterogeneity. The probabilities of the possible outcomes are modelled as a function of the independent variables using a logistic function. Logistic regression measures the relationship between a categorical dependent variable and, usually, one or several continuous independent variables by converting the dependent variable to probability scores. Then, a logistic regression is formed, which predicts success or failure of a given binary variable (e.g. erosion presence or absence) for any value of the independent variables. The erosion occurrence probability can be calculated in conjunction with the model deviance regarding the independent variables tested. The most straightforward measure for goodness of fit is the G statistic. It is a simple and effective way to study and evaluate the Logistic Regression model efficiency and the reliability of each independent variable. The developed statistical model is applied to the Koiliaris River Basin on the island of Crete, Greece. Two datasets of river bank slope, river cross-section width and indications of erosion were available for the analysis (12 and 8 locations). Two different types of spatial dependence functions, exponential and tricubic, were examined to determine the local spatial dependence of the independent variables at the measurement locations. The results show a significant improvement when the tricubic function is applied as the erosion probability is accurately predicted at all eight validation locations. Results for the model deviance show that cross-section width is more important than bank slope in the estimation of erosion probability along the Koiliaris riverbanks. The proposed statistical model is a useful tool that quantifies the erosion probability along the riverbanks and can be used to assist managing erosion and flooding events. Acknowledgements This work is part of an on-going THALES project (CYBERSENSORS - High Frequency Monitoring System for Integrated Water Resources Management of Rivers). The project has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.

Exploring stop-go decision zones at rural high-speed intersections with flashing green signal and insufficient yellow time in China.

PubMed

Tang, Keshuang; Xu, Yanqing; Wang, Fen; Oguchi, Takashi

2016-10-01

The objective of this study is to empirically analyze and model the stop-go decision behavior of drivers at rural high-speed intersections in China, where a flashing green signal of 3s followed by a yellow signal of 3s is commonly applied to end a green phase. 1, 186 high-resolution vehicle trajectories were collected at four typical high-speed intersection approaches in Shanghai and used for the identification of actual stop-go decision zones and the modeling of stop-go decision behavior. Results indicate that the presence of flashing green significantly changed the theoretical decision zones based on the conventional Dilemma Zone theory. The actual stop-go decision zones at the study intersections were thus formulated and identified based on the empirical data. Binary Logistic model and Fuzzy Logic model were then developed to further explore the impacts of flashing green on the stop-go behavior of drivers. It was found that the Fuzzy Logic model could produce comparably good estimation results as compared to the traditional Binary Logistic models. The findings of this study could contribute the development of effective dilemma zone protection strategies, the improvement of stop-go decision model embedded in the microscopic traffic simulation software and the proper design of signal change and clearance intervals at high-speed intersections in China. Copyright © 2016 Elsevier Ltd. All rights reserved.

Binary logistic regression modelling: Measuring the probability of relapse cases among drug addict

NASA Astrophysics Data System (ADS)

Ismail, Mohd Tahir; Alias, Siti Nor Shadila

2014-07-01

For many years Malaysia faced the drug addiction issues. The most serious case is relapse phenomenon among treated drug addict (drug addict who have under gone the rehabilitation programme at Narcotic Addiction Rehabilitation Centre, PUSPEN). Thus, the main objective of this study is to find the most significant factor that contributes to relapse to happen. The binary logistic regression analysis was employed to model the relationship between independent variables (predictors) and dependent variable. The dependent variable is the status of the drug addict either relapse, (Yes coded as 1) or not, (No coded as 0). Meanwhile the predictors involved are age, age at first taking drug, family history, education level, family crisis, community support and self motivation. The total of the sample is 200 which the data are provided by AADK (National Antidrug Agency). The finding of the study revealed that age and self motivation are statistically significant towards the relapse cases..

Use of antidementia drugs in frontotemporal lobar degeneration.

PubMed

López-Pousa, Secundino; Calvó-Perxas, Laia; Lejarreta, Saioa; Cullell, Marta; Meléndez, Rosa; Hernández, Erélido; Bisbe, Josep; Perkal, Héctor; Manzano, Anna; Roig, Anna Maria; Turró-Garriga, Oriol; Vilalta-Franch, Joan; Garre-Olmo, Josep

2012-06-01

Clinical evidence indicates that acetylcholinesterase inhibitors (AChEIs) are not efficacious to treat frontotemporal lobar degeneration (FTLD). The British Association for Psychopharmacology recommends avoiding the use of AChEI and memantine in patients with FTLD. Cross-sectional design using 1092 cases with Alzheimer's disease (AD) and 64 cases with FTLD registered by the Registry of Dementias of Girona. Bivariate analyses were performed, and binary logistic regressions were used to detect variables associated with antidementia drugs consumption. The AChEIs were consumed by 57.6% and 42.2% of the patients with AD and FTLD, respectively. Memantine was used by 17.2% and 10.9% of patients with AD and FTLD, respectively. Binary logistic regressions yielded no associations with antidementia drugs consumption. There is a discrepancy regarding clinical practice and the recommendations based upon clinical evidence. The increased central nervous system drug use detected in FTLD requires multicentric studies aiming at finding the best means to treat these patients.

Use of generalized ordered logistic regression for the analysis of multidrug resistance data.

PubMed

Agga, Getahun E; Scott, H Morgan

2015-10-01

Statistical analysis of antimicrobial resistance data largely focuses on individual antimicrobial's binary outcome (susceptible or resistant). However, bacteria are becoming increasingly multidrug resistant (MDR). Statistical analysis of MDR data is mostly descriptive often with tabular or graphical presentations. Here we report the applicability of generalized ordinal logistic regression model for the analysis of MDR data. A total of 1,152 Escherichia coli, isolated from the feces of weaned pigs experimentally supplemented with chlortetracycline (CTC) and copper, were tested for susceptibilities against 15 antimicrobials and were binary classified into resistant or susceptible. The 15 antimicrobial agents tested were grouped into eight different antimicrobial classes. We defined MDR as the number of antimicrobial classes to which E. coli isolates were resistant ranging from 0 to 8. Proportionality of the odds assumption of the ordinal logistic regression model was violated only for the effect of treatment period (pre-treatment, during-treatment and post-treatment); but not for the effect of CTC or copper supplementation. Subsequently, a partially constrained generalized ordinal logistic model was built that allows for the effect of treatment period to vary while constraining the effects of treatment (CTC and copper supplementation) to be constant across the levels of MDR classes. Copper (Proportional Odds Ratio [Prop OR]=1.03; 95% CI=0.73-1.47) and CTC (Prop OR=1.1; 95% CI=0.78-1.56) supplementation were not significantly associated with the level of MDR adjusted for the effect of treatment period. MDR generally declined over the trial period. In conclusion, generalized ordered logistic regression can be used for the analysis of ordinal data such as MDR data when the proportionality assumptions for ordered logistic regression are violated. Published by Elsevier B.V.

Logistic regression for circular data

NASA Astrophysics Data System (ADS)

Al-Daffaie, Kadhem; Khan, Shahjahan

2017-05-01

This paper considers the relationship between a binary response and a circular predictor. It develops the logistic regression model by employing the linear-circular regression approach. The maximum likelihood method is used to estimate the parameters. The Newton-Raphson numerical method is used to find the estimated values of the parameters. A data set from weather records of Toowoomba city is analysed by the proposed methods. Moreover, a simulation study is considered. The R software is used for all computations and simulations.

Comparison of support vector machine classification to partial least squares dimension reduction with logistic descrimination of hyperspectral data

NASA Astrophysics Data System (ADS)

Wilson, Machelle; Ustin, Susan L.; Rocke, David

2003-03-01

Remote sensing technologies with high spatial and spectral resolution show a great deal of promise in addressing critical environmental monitoring issues, but the ability to analyze and interpret the data lags behind the technology. Robust analytical methods are required before the wealth of data available through remote sensing can be applied to a wide range of environmental problems for which remote detection is the best method. In this study we compare the classification effectiveness of two relatively new techniques on data consisting of leaf-level reflectance from plants that have been exposed to varying levels of heavy metal toxicity. If these methodologies work well on leaf-level data, then there is some hope that they will also work well on data from airborne and space-borne platforms. The classification methods compared were support vector machine classification of exposed and non-exposed plants based on the reflectance data, and partial east squares compression of the reflectance data followed by classification using logistic discrimination (PLS/LD). PLS/LD was performed in two ways. We used the continuous concentration data as the response during compression, and then used the binary response required during logistic discrimination. We also used a binary response during compression followed by logistic discrimination. The statistics we used to compare the effectiveness of the methodologies was the leave-one-out cross validation estimate of the prediction error.

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes.

PubMed

Li, Baoyue; Lingsma, Hester F; Steyerberg, Ewout W; Lesaffre, Emmanuel

2011-05-23

Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC.Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain.

London Measure of Unplanned Pregnancy: guidance for its use as an outcome measure

PubMed Central

Hall, Jennifer A; Barrett, Geraldine; Copas, Andrew; Stephenson, Judith

2017-01-01

Background The London Measure of Unplanned Pregnancy (LMUP) is a psychometrically validated measure of the degree of intention of a current or recent pregnancy. The LMUP is increasingly being used worldwide, and can be used to evaluate family planning or preconception care programs. However, beyond recommending the use of the full LMUP scale, there is no published guidance on how to use the LMUP as an outcome measure. Ordinal logistic regression has been recommended informally, but studies published to date have all used binary logistic regression and dichotomized the scale at different cut points. There is thus a need for evidence-based guidance to provide a standardized methodology for multivariate analysis and to enable comparison of results. This paper makes recommendations for the regression method for analysis of the LMUP as an outcome measure. Materials and methods Data collected from 4,244 pregnant women in Malawi were used to compare five regression methods: linear, logistic with two cut points, and ordinal logistic with either the full or grouped LMUP score. The recommendations were then tested on the original UK LMUP data. Results There were small but no important differences in the findings across the regression models. Logistic regression resulted in the largest loss of information, and assumptions were violated for the linear and ordinal logistic regression. Consequently, robust standard errors were used for linear regression and a partial proportional odds ordinal logistic regression model attempted. The latter could only be fitted for grouped LMUP score. Conclusion We recommend the linear regression model with robust standard errors to make full use of the LMUP score when analyzed as an outcome measure. Ordinal logistic regression could be considered, but a partial proportional odds model with grouped LMUP score may be required. Logistic regression is the least-favored option, due to the loss of information. For logistic regression, the cut point for un/planned pregnancy should be between nine and ten. These recommendations will standardize the analysis of LMUP data and enhance comparability of results across studies. PMID:28435343

Controlled pattern imputation for sensitivity analysis of longitudinal binary and ordinal outcomes with nonignorable dropout.

PubMed

Tang, Yongqiang

2018-04-30

The controlled imputation method refers to a class of pattern mixture models that have been commonly used as sensitivity analyses of longitudinal clinical trials with nonignorable dropout in recent years. These pattern mixture models assume that participants in the experimental arm after dropout have similar response profiles to the control participants or have worse outcomes than otherwise similar participants who remain on the experimental treatment. In spite of its popularity, the controlled imputation has not been formally developed for longitudinal binary and ordinal outcomes partially due to the lack of a natural multivariate distribution for such endpoints. In this paper, we propose 2 approaches for implementing the controlled imputation for binary and ordinal data based respectively on the sequential logistic regression and the multivariate probit model. Efficient Markov chain Monte Carlo algorithms are developed for missing data imputation by using the monotone data augmentation technique for the sequential logistic regression and a parameter-expanded monotone data augmentation scheme for the multivariate probit model. We assess the performance of the proposed procedures by simulation and the analysis of a schizophrenia clinical trial and compare them with the fully conditional specification, last observation carried forward, and baseline observation carried forward imputation methods. Copyright © 2018 John Wiley & Sons, Ltd.

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes

PubMed Central

2011-01-01

Background Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. Methods We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC. Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. Results The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. Conclusions On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain. PMID:21605357

Investigation on occupant injury severity in rear-end crashes involving trucks as the front vehicle in Beijing area, China.

PubMed

Yuan, Quan; Lu, Meng; Theofilatos, Athanasios; Li, Yi-Bing

2017-02-01

Rear-end crashes attribute to a large portion of total crashes in China, which lead to many casualties and property damage, especially when involving commercial vehicles. This paper aims to investigate the critical factors for occupant injury severity in the specific rear-end crash type involving trucks as the front vehicle (FV). This paper investigated crashes occurred from 2011 to 2013 in Beijing area, China and selected 100 qualified cases i.e., rear-end crashes involving trucks as the FV. The crash data were supplemented with interviews from police officers and vehicle inspection. A binary logistic regression model was used to build the relationship between occupant injury severity and corresponding affecting factors. Moreover, a multinomial logistic model was used to predict the likelihood of fatal or severe injury or no injury in a rear-end crash. The results provided insights on the characteristics of driver, vehicle and environment, and the corresponding influences on the likelihood of a rear-end crash. The binary logistic model showed that drivers' age, weight difference between vehicles, visibility condition and lane number of road significantly increased the likelihood for severe injury of rear-end crash. The multinomial logistic model and the average direct pseudo-elasticity of variables showed that night time, weekdays, drivers from other provinces and passenger vehicles as rear vehicles significantly increased the likelihood of rear drivers being fatal. All the abovementioned significant factors should be improved, such as the conditions of lighting and the layout of lanes on roads. Two of the most common driver factors are drivers' age and drivers' original residence. Young drivers and outsiders have a higher injury severity. Therefore it is imperative to enhance the safety education and management on the young drivers who steer heavy duty truck from other cities to Beijing on weekdays. Copyright © 2016 Daping Hospital and the Research Institute of Surgery of the Third Military Medical University. Production and hosting by Elsevier B.V. All rights reserved.

Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey)

NASA Astrophysics Data System (ADS)

Ozdemir, Adnan

2011-07-01

SummaryThe purpose of this study is to produce a groundwater spring potential map of the Sultan Mountains in central Turkey, based on a logistic regression method within a Geographic Information System (GIS) environment. Using field surveys, the locations of the springs (440 springs) were determined in the study area. In this study, 17 spring-related factors were used in the analysis: geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transport capacity index, distance to drainage, distance to fault, drainage density, and fault density map. The coefficients of the predictor variables were estimated using binary logistic regression analysis and were used to calculate the groundwater spring potential for the entire study area. The accuracy of the final spring potential map was evaluated based on the observed springs. The accuracy of the model was evaluated by calculating the relative operating characteristics. The area value of the relative operating characteristic curve model was found to be 0.82. These results indicate that the model is a good estimator of the spring potential in the study area. The spring potential map shows that the areas of very low, low, moderate and high groundwater spring potential classes are 105.586 km 2 (28.99%), 74.271 km 2 (19.906%), 101.203 km 2 (27.14%), and 90.05 km 2 (24.671%), respectively. The interpretations of the potential map showed that stream power index, relative permeability of lithologies, geology, elevation, aspect, wetness index, plan curvature, and drainage density play major roles in spring occurrence and distribution in the Sultan Mountains. The logistic regression approach has not yet been used to delineate groundwater potential zones. In this study, the logistic regression method was used to locate potential zones for groundwater springs in the Sultan Mountains. The evolved model was found to be in strong agreement with the available groundwater spring test data. Hence, this method can be used routinely in groundwater exploration under favourable conditions.

Do classic blood biomarkers of JSLE identify active lupus nephritis? Evidence from the UK JSLE Cohort Study.

PubMed

Smith, E M D; Jorgensen, A L; Beresford, M W

2017-10-01

Background Lupus nephritis (LN) affects up to 80% of juvenile-onset systemic lupus erythematosus (JSLE) patients. The value of commonly available biomarkers, such as anti-dsDNA antibodies, complement (C3/C4), ESR and full blood count parameters in the identification of active LN remains uncertain. Methods Participants from the UK JSLE Cohort Study, aged <16 years at diagnosis, were categorized as having active or inactive LN according to the renal domain of the British Isles Lupus Assessment Group score. Classic biomarkers: anti-dsDNA, C3, C4, ESR, CRP, haemoglobin, total white cells, neutrophils, lymphocytes, platelets and immunoglobulins were assessed for their ability to identify active LN using binary logistic regression modeling, with stepAIC function applied to select a final model. Receiver-operating curve analysis was used to assess diagnostic accuracy. Results A total of 370 patients were recruited; 191 (52%) had active LN and 179 (48%) had inactive LN. Binary logistic regression modeling demonstrated a combination of ESR, C3, white cell count, neutrophils, lymphocytes and IgG to be best for the identification of active LN (area under the curve 0.724). Conclusions At best, combining common classic blood biomarkers of lupus activity using multivariate analysis provides a 'fair' ability to identify active LN. Urine biomarkers were not included in these analyses. These results add to the concern that classic blood biomarkers are limited in monitoring discrete JSLE manifestations such as LN.

Socioeconomic and Demographic Disparities in Knowledge of Reproductive Healthcare among Female University Students in Bangladesh

PubMed Central

Islam Mondal, Md. Nazrul; Nasir Ullah, Md. Monzur Morshad; Khan, Md. Nuruzzaman; Islam, Mohammad Zamirul; Islam, Md. Nurul; Moni, Sabiha Yasmin; Hoque, Md. Nazrul; Rahman, Md. Mashiur

2015-01-01

Background: Reproductive health (RH) is a critical component of women’s health and overall well-being around the world, especially in developing countries. We examine the factors that determine knowledge of RH care among female university students in Bangladesh. Methods: Data on 300 female students were collected from Rajshahi University, Bangladesh through a structured questionnaire using purposive sampling technique. The data were used for univariate analysis, to carry out the description of the variables; bivariate analysis was used to examine the associations between the variables; and finally, multivariate analysis (binary logistic regression model) was used to examine and fit the model and interpret the parameter estimates, especially in terms of odds ratios. Results: The results revealed that more than one-third (34.3%) respondents do not have sufficient knowledge of RH care. The χ2-test identified the significant (p < 0.05) associations between respondents’ knowledge of RH care with respondents’ age, education, family type, watching television; and knowledge about pregnancy, family planning, and contraceptive use. Finally, the binary logistic regression model identified respondents’ age, education, family type; and knowledge about family planning, and contraceptive use as the significant (p < 0.05) predictors of RH care. Conclusions and Global Health Implications: Knowledge of RH care among female university students was found unsatisfactory. Government and concerned organizations should promote and strengthen various health education programs to focus on RH care especially for the female university students in Bangladesh. PMID:27622005

A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground Test

NASA Technical Reports Server (NTRS)

Messer, Bradley

2007-01-01

Propulsion ground test facilities face the daily challenge of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Over the last decade NASA s propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and exceeded the capabilities of numerous test facility and test article components. A logistic regression mathematical modeling technique has been developed to predict the probability of successfully completing a rocket propulsion test. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),.., X(sub k) to a binary or dichotomous dependent variable Y, where Y can only be one of two possible outcomes, in this case Success or Failure of accomplishing a full duration test. The use of logistic regression modeling is not new; however, modeling propulsion ground test facilities using logistic regression is both a new and unique application of the statistical technique. Results from this type of model provide project managers with insight and confidence into the effectiveness of rocket propulsion ground testing.

Prediction of cold and heat patterns using anthropometric measures based on machine learning.

PubMed

Lee, Bum Ju; Lee, Jae Chul; Nam, Jiho; Kim, Jong Yeol

2018-01-01

To examine the association of body shape with cold and heat patterns, to determine which anthropometric measure is the best indicator for discriminating between the two patterns, and to investigate whether using a combination of measures can improve the predictive power to diagnose these patterns. Based on a total of 4,859 subjects (3,000 women and 1,859 men), statistical analyses using binary logistic regression were performed to assess the significance of the difference and the predictive power of each anthropometric measure, and binary logistic regression and Naive Bayes with the variable selection technique were used to assess the improvement in the predictive power of the patterns using the combined measures. In women, the strongest indicators for determining the cold and heat patterns among anthropometric measures were body mass index (BMI) and rib circumference; in men, the best indicator was BMI. In experiments using a combination of measures, the values of the area under the receiver operating characteristic curve in women were 0.776 by Naive Bayes and 0.772 by logistic regression, and the values in men were 0.788 by Naive Bayes and 0.779 by logistic regression. Individuals with a higher BMI have a tendency toward a heat pattern in both women and men. The use of a combination of anthropometric measures can slightly improve the diagnostic accuracy. Our findings can provide fundamental information for the diagnosis of cold and heat patterns based on body shape for personalized medicine.

[Willingness of Patients with Obesity to Use New Media in Rehabilitation Aftercare].

PubMed

Dorow, M; Löbner, M; Stein, J; Kind, P; Markert, J; Keller, J; Weidauer, E; Riedel-Heller, S G

2017-06-01

Digital media offer new possibilities in rehabilitation aftercare. This study investigates the rehabilitants' willingness to use new media (sms, internet, social networks) in rehabilitation aftercare and factors that are associated with the willingness to use media-based aftercare. 92 rehabilitants (patients with obesity) filled in a questionnaire on the willingness to use new media in rehabilitation aftercare. In order to identify influencing factors, binary logistic regression models were calculated. 3 quarters of the rehabilitants (76.1%) reported that they would be willing to use new media in rehabilitation aftercare. The binary logistic regression model yielded two factors that were associated with the willingness to use media-based aftercare: the possession of a smartphone and the willingness to receive telephone counseling for aftercare. The majority of the rehabilitants was willing to use new media in rehabilitation aftercare. The reasons for refusal of media-based aftercare need to be examined more closely. © Georg Thieme Verlag KG Stuttgart · New York.

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

NASA Astrophysics Data System (ADS)

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

2013-02-01

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

The logistic model for predicting the non-gonoactive Aedes aegypti females.

PubMed

Reyes-Villanueva, Filiberto; Rodríguez-Pérez, Mario A

2004-01-01

To estimate, using logistic regression, the likelihood of occurrence of a non-gonoactive Aedes aegypti female, previously fed human blood, with relation to body size and collection method. This study was conducted in Monterrey, Mexico, between 1994 and 1996. Ten samplings of 60 mosquitoes of Ae. aegypti females were carried out in three dengue endemic areas: six of biting females, two of emerging mosquitoes, and two of indoor resting females. Gravid females, as well as those with blood in the gut were removed. Mosquitoes were taken to the laboratory and engorged on human blood. After 48 hours, ovaries were dissected to register whether they were gonoactive or non-gonoactive. Wing-length in mm was an indicator for body size. The logistic regression model was used to assess the likelihood of non-gonoactivity, as a binary variable, in relation to wing-length and collection method. Of the 600 females, 164 (27%) remained non-gonoactive, with a wing-length range of 1.9-3.2 mm, almost equal to that of all females (1.8-3.3 mm). The logistic regression model showed a significant likelihood of a female remaining non-gonoactive (Y=1). The collection method did not influence the binary response, but there was an inverse relationship between non-gonoactivity and wing-length. Dengue vector populations from Monterrey, Mexico display a wide-range body size. Logistic regression was a useful tool to estimate the likelihood for an engorged female to remain non-gonoactive. The necessity for a second blood meal is present in any female, but small mosquitoes are more likely to bite again within a 2-day interval, in order to attain egg maturation. The English version of this paper is available too at: http://www.insp.mx/salud/index.html.

Missing Data in Alcohol Clinical Trials with Binary Outcomes

PubMed Central

Hallgren, Kevin A.; Witkiewitz, Katie; Kranzler, Henry R.; Falk, Daniel E.; Litten, Raye Z.; O’Malley, Stephanie S.; Anton, Raymond F.

2017-01-01

Background Missing data are common in alcohol clinical trials for both continuous and binary endpoints. Approaches to handle missing data have been explored for continuous outcomes, yet no studies have compared missing data approaches for binary outcomes (e.g., abstinence, no heavy drinking days). The present study compares approaches to modeling binary outcomes with missing data in the COMBINE study. Method We included participants in the COMBINE Study who had complete drinking data during treatment and who were assigned to active medication or placebo conditions (N=1146). Using simulation methods, missing data were introduced under common scenarios with varying sample sizes and amounts of missing data. Logistic regression was used to estimate the effect of naltrexone (vs. placebo) in predicting any drinking and any heavy drinking outcomes at the end of treatment using four analytic approaches: complete case analysis (CCA), last observation carried forward (LOCF), the worst-case scenario of missing equals any drinking or heavy drinking (WCS), and multiple imputation (MI). In separate analyses, these approaches were compared when drinking data were manually deleted for those participants who discontinued treatment but continued to provide drinking data. Results WCS produced the greatest amount of bias in treatment effect estimates. MI usually yielded less biased estimates than WCS and CCA in the simulated data, and performed considerably better than LOCF when estimating treatment effects among individuals who discontinued treatment. Conclusions Missing data can introduce bias in treatment effect estimates in alcohol clinical trials. Researchers should utilize modern missing data methods, including MI, and avoid WCS and CCA when analyzing binary alcohol clinical trial outcomes. PMID:27254113

Locally Weighted Score Estimation for Quantile Classification in Binary Regression Models

PubMed Central

Rice, John D.; Taylor, Jeremy M. G.

2016-01-01

One common use of binary response regression methods is classification based on an arbitrary probability threshold dictated by the particular application. Since this is given to us a priori, it is sensible to incorporate the threshold into our estimation procedure. Specifically, for the linear logistic model, we solve a set of locally weighted score equations, using a kernel-like weight function centered at the threshold. The bandwidth for the weight function is selected by cross validation of a novel hybrid loss function that combines classification error and a continuous measure of divergence between observed and fitted values; other possible cross-validation functions based on more common binary classification metrics are also examined. This work has much in common with robust estimation, but diers from previous approaches in this area in its focus on prediction, specifically classification into high- and low-risk groups. Simulation results are given showing the reduction in error rates that can be obtained with this method when compared with maximum likelihood estimation, especially under certain forms of model misspecification. Analysis of a melanoma data set is presented to illustrate the use of the method in practice. PMID:28018492

The Mantel-Haenszel procedure revisited: models and generalizations.

PubMed

Fidler, Vaclav; Nagelkerke, Nico

2013-01-01

Several statistical methods have been developed for adjusting the Odds Ratio of the relation between two dichotomous variables X and Y for some confounders Z. With the exception of the Mantel-Haenszel method, commonly used methods, notably binary logistic regression, are not symmetrical in X and Y. The classical Mantel-Haenszel method however only works for confounders with a limited number of discrete strata, which limits its utility, and appears to have no basis in statistical models. Here we revisit the Mantel-Haenszel method and propose an extension to continuous and vector valued Z. The idea is to replace the observed cell entries in strata of the Mantel-Haenszel procedure by subject specific classification probabilities for the four possible values of (X,Y) predicted by a suitable statistical model. For situations where X and Y can be treated symmetrically we propose and explore the multinomial logistic model. Under the homogeneity hypothesis, which states that the odds ratio does not depend on Z, the logarithm of the odds ratio estimator can be expressed as a simple linear combination of three parameters of this model. Methods for testing the homogeneity hypothesis are proposed. The relationship between this method and binary logistic regression is explored. A numerical example using survey data is presented.

The Mantel-Haenszel Procedure Revisited: Models and Generalizations

PubMed Central

Fidler, Vaclav; Nagelkerke, Nico

2013-01-01

Several statistical methods have been developed for adjusting the Odds Ratio of the relation between two dichotomous variables X and Y for some confounders Z. With the exception of the Mantel-Haenszel method, commonly used methods, notably binary logistic regression, are not symmetrical in X and Y. The classical Mantel-Haenszel method however only works for confounders with a limited number of discrete strata, which limits its utility, and appears to have no basis in statistical models. Here we revisit the Mantel-Haenszel method and propose an extension to continuous and vector valued Z. The idea is to replace the observed cell entries in strata of the Mantel-Haenszel procedure by subject specific classification probabilities for the four possible values of (X,Y) predicted by a suitable statistical model. For situations where X and Y can be treated symmetrically we propose and explore the multinomial logistic model. Under the homogeneity hypothesis, which states that the odds ratio does not depend on Z, the logarithm of the odds ratio estimator can be expressed as a simple linear combination of three parameters of this model. Methods for testing the homogeneity hypothesis are proposed. The relationship between this method and binary logistic regression is explored. A numerical example using survey data is presented. PMID:23516463

Analysis of factors influencing organic fruit and vegetable purchasing in Istanbul, Turkey.

PubMed

Oraman, Yasemin; Unakitan, Gökhan

2010-01-01

This article examines the influences on the purchasing decisions of fruit and vegetable consumers and presents findings from a survey conducted with 385 respondents living in urban areas in Istanbul, Turkey. It uses a binary logistic model to estimate factor effects in organic fruit and vegetable purchasing in Turkey. The results indicate that concern for human health and safety is a key factor that influences consumer preferences for organic food. Findings will help organic product suppliers understand the key factors influencing consumer purchasing and consumption behaviors.

First trimester vaginal bleeding and adverse pregnancy outcomes among Chinese women: from a large cohort study in China.

PubMed

Sun, Lu; Tao, Fangbiao; Hao, Jiahu; Su, Puyu; Liu, Fang; Xu, Rong

2012-08-01

To examine the effect of first trimester vaginal bleeding on adverse pregnancy outcomes including preterm delivery, low birth weight and small for gestational age. This is a prospective population-based cohort study. A questionnaire survey was conducted on 4342 singleton pregnancies by trained doctors. Binary logistic regression was used to estimate risk ratios (RRs) and 95% confidence intervals (95% CI). Vaginal bleeding occurred among 1050 pregnant women, the incidence of vaginal bleeding was 24.2%, 37.4% of whom didn't see a doctor, 62.6% of whom saw a doctor for vaginal bleeding. Binary logistic regression demonstrated that bleeding with seeing a doctor was significantly associated with preterm birth (RR 1.84, 95% CI 1.25-2.69) and bleeding without seeing a doctor was related to increased of low birth weight (RR 2.52, 95% CI 1.34-4.75) and was 1.97-fold increased of small for gestational age (RR 1.97, 95% CI 1.19-3.25). These results suggest that first trimester vaginal bleeding is an increased risk of low birth weight, preterm delivery and small for gestational age. Find ways to reduce the risk of vaginal bleeding and lower vaginal bleeding rate may be helpful to reduce the incidence of preterm birth, low birth weight and small for gestational age.

National health insurance subscription and maternal healthcare utilisation across mothers' wealth status in Ghana.

PubMed

Ameyaw, Edward Kwabena; Kofinti, Raymond Elikplim; Appiah, Francis

2017-12-01

This study is against the backdrop that despite the forty-nine percent decline in Maternal Mortality Rate in Ghana, the situation still remains high averaging 319 per 100,000 live births between 2011 and 2015. To examine the relationship between National Health Insurance and maternal healthcare utilisation across three main wealth quintiles (Poor, Middle and Rich). The study employed data from the 2014 Ghana Demographic and Health Survey. Both descriptive analysis and binary logistic regression were conducted. Descriptively, rich women had high antenatal attendance and health facility deliveries represented by 96.5% and 95.6% respectively. However, the binary logistic regression results revealed that poor women owning NHIS are 7% (CI = 1.76-2.87) more likely to make at least four antenatal care visits compared to women in the middle wealth quintile (5%, CI = 2.12-4.76) and rich women (2%, CI = 1.14-4.14). Similarly, poor women who owned the NHIS are 14% (CI = 1.42-2.13) likely to deliver in health facility than women in the middle and rich wealth quintile. The study has vindicated the claim that NHIS Scheme is pro-poor in Ghana. The Ministry of Health should target women in the rural area to be enrolled on the NHIS to improve maternal healthcare utilisation since poverty is principally a rural phenomenon in Ghana.

Prevalence and Extrinsic Risk Factors for Dental Erosion in Adolescents.

PubMed

Mafla, Ana C; Cerón-Bastidas, Ximena A; Munoz-Ceballos, Maria E; Vallejo-Bravo, Diana C; Fajardo-Santacruz, Maria C

This manuscript examined the prevalence and extrinsic risk factors for dental erosion (DE) in early and middle adolescents in Pasto, Colombia. Dental erosion was evaluated in a random sample of 384 individuals aged 10-15 years attending three primary and high schools in this cross-sectional study. Clinical dental assessment for DE was done using O'Sullivan index. Data on general sociodemographic variables and extrinsic risks factors were obtained. Descriptive and univariate binary logistic regression analyses were performed. Dental erosion was observed in 57.3% of individuals. The univariate binary logistic regression analysis showed that frequency of drinking natural fruit juices (OR 2.670, 95% CI 1.346 - 5.295, P=0.004) and their pH (OR 2.303, 95% CI 1.292 - 4.107, P=0.004) were more associated with the odd of DE in early adolescence. However, a high SES (OR 10.360, 95% CI 3.700 - 29.010, P<0.001) and frequency of snacks with artificial lemon taste (OR 3.659, 95% CI 1.506 - 8.891, P=0.003) were highly associated with the risk of DE in middle adolescence. The results suggest that DE is a prevalent condition in adolescents living in a city in southern Colombia. The transition from early to middle adolescence implies new bio-psychosocial changes, which increase the risk for DE.

Psychological trauma symptoms and Type 2 diabetes prevalence, glucose control, and treatment modality among American Indians in the Strong Heart Family Study

PubMed Central

Jacob, Michelle M.; Gonzales, Kelly L.; Calhoun, Darren; Beals, Janette; Muller, Clemma Jacobsen; Goldberg, Jack; Nelson, Lonnie; Welty, Thomas K.; Howard, Barbara V.

2013-01-01

Aims The aims of this paper are to examine the relationship between psychological trauma symptoms and Type 2 diabetes prevalence, glucose control, and treatment modality among 3,776 American Indians in Phase V of the Strong Heart Family Study. Methods This cross-sectional analysis measured psychological trauma symptoms using the National Anxiety Disorder Screening Day instrument, diabetes by American Diabetes Association criteria, and treatment modality by four categories: no medication, oral medication only, insulin only, or both oral medication and insulin. We used binary logistic regression to evaluate the association between psychological trauma symptoms and diabetes prevalence. We used ordinary least squares regression to evaluate the association between psychological trauma symptoms and glucose control. We used binary logistic regression to model the association of psychological trauma symptoms with treatment modality. Results Neither diabetes prevalence (22-31%; p = 0.19) nor control (8.0-8.6; p = 0.25) varied significantly by psychological trauma symptoms categories. However, diabetes treatment modality was associated with psychological trauma symptoms categories, as people with greater burden used either no medication, or both oral and insulin medications (odds ratio = 3.1, p < 0.001). Conclusions The positive relationship between treatment modality and psychological trauma symptoms suggests future research investigate patient and provider treatment decision making. PMID:24051029

Predictors of Employment Outcomes for State-Federal Vocational Rehabilitation Consumers with HIV/AIDS

ERIC Educational Resources Information Center

Jung, Youngoh; Schaller, James; Bellini, James

2010-01-01

In this study, the authors investigated the effects of demographic, medical, and vocational rehabilitation service variables on employment outcomes of persons living with HIV/AIDS. Binary logistic regression analyses were conducted to determine predictors of employment outcomes using two groups drawn from Rehabilitation Services Administration…

Who Benefits from Tuition Discounts at Public Universities?

ERIC Educational Resources Information Center

Hillman, Nicholas W.

2010-01-01

This article uses data from the 2004 National Postsecondary Student Aid Study to provide insight about the range of tuition discounting practices at public institutions. Specifically, it examines the characteristics of students who receive tuition discounts from public four-year colleges and universities. A binary logistic regression is applied to…

Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM

ERIC Educational Resources Information Center

Warner, Rebecca M.

2007-01-01

This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…

Graduate Unemployment in South Africa: Social Inequality Reproduced

ERIC Educational Resources Information Center

Baldry, Kim

2016-01-01

In this study, I examine the influence of demographic and educational characteristics of South African graduates on their employment/unemployment status. A sample of 1175 respondents who graduated between 2006 and 2012 completed an online survey. Using binary logistic regression, the strongest determinants of unemployment were the graduates' race,…

Commitment of Licensed Social Workers to Aging Practice

ERIC Educational Resources Information Center

Simons, Kelsey; Bonifas, Robin; Gammonley, Denise

2011-01-01

This study sought to identify client, professional, and employment characteristics that enhance licensed social workers' commitment to aging practice. A series of binary logistic regressions were performed using data from 181 licensed, full-time social workers who reported aging as their primary specialty area as part of the 2004 NASW's national…

Modeling the dynamics of urban growth using multinomial logistic regression: a case study of Jiayu County, Hubei Province, China

NASA Astrophysics Data System (ADS)

Nong, Yu; Du, Qingyun; Wang, Kun; Miao, Lei; Zhang, Weiwei

2008-10-01

Urban growth modeling, one of the most important aspects of land use and land cover change study, has attracted substantial attention because it helps to comprehend the mechanisms of land use change thus helps relevant policies made. This study applied multinomial logistic regression to model urban growth in the Jiayu county of Hubei province, China to discover the relationship between urban growth and the driving forces of which biophysical and social-economic factors are selected as independent variables. This type of regression is similar to binary logistic regression, but it is more general because the dependent variable is not restricted to two categories, as those previous studies did. The multinomial one can simulate the process of multiple land use competition between urban land, bare land, cultivated land and orchard land. Taking the land use type of Urban as reference category, parameters could be estimated with odds ratio. A probability map is generated from the model to predict where urban growth will occur as a result of the computation.

Regression analysis for solving diagnosis problem of children's health

NASA Astrophysics Data System (ADS)

Cherkashina, Yu A.; Gerget, O. M.

2016-04-01

The paper includes results of scientific researches. These researches are devoted to the application of statistical techniques, namely, regression analysis, to assess the health status of children in the neonatal period based on medical data (hemostatic parameters, parameters of blood tests, the gestational age, vascular-endothelial growth factor) measured at 3-5 days of children's life. In this paper a detailed description of the studied medical data is given. A binary logistic regression procedure is discussed in the paper. Basic results of the research are presented. A classification table of predicted values and factual observed values is shown, the overall percentage of correct recognition is determined. Regression equation coefficients are calculated, the general regression equation is written based on them. Based on the results of logistic regression, ROC analysis was performed, sensitivity and specificity of the model are calculated and ROC curves are constructed. These mathematical techniques allow carrying out diagnostics of health of children providing a high quality of recognition. The results make a significant contribution to the development of evidence-based medicine and have a high practical importance in the professional activity of the author.

Serum osteocalcin is significantly related to indices of obesity and lipid profile in Malaysian men.

PubMed

Chin, Kok-Yong; Ima-Nirwana, Soelaiman; Mohamed, Isa Naina; Ahmad, Fairus; Ramli, Elvy Suhana Mohd; Aminuddin, Amilia; Ngah, Wan Zurinah Wan

2014-01-01

Recent studies revealed a possible reciprocal relationship between the skeletal system and obesity and lipid metabolism, mediated by osteocalcin, an osteoblast-specific protein. This study aimed to validate the relationship between serum osteocalcin and indices of obesity and lipid parameters in a group of Malaysian men. A total of 373 men from the Malaysian Aging Male Study were included in the analysis. Data on subjects' demography, body mass index (BMI), body fat (BF) mass, waist circumference (WC), serum osteocalcin and fasting lipid levels were collected. Bioelectrical impendence (BIA) method was used to estimate BF. Multiple linear and binary logistic regression analyses were performed to analyze the association between serum osteocalcin and the aforementioned variables, with adjustment for age, ethnicity and BMI. Multiple regression results indicated that weight, BMI, BF mass, BF %, WC were significantly and negatively associated with serum osteocalcin (p < 0.001). There was a significant positive association between serum osteocalcin and high density lipoprotein (HDL) cholesterol (p = 0.032). Binary logistic results indicated that subjects with low serum osteocalcin level were more likely to be associated with high BMI (obese and overweight), high BF%, high WC and low HDL cholesterol (p < 0.05). Subjects with high osteocalcin level also demonstrated high total cholesterol level (p < 0.05) but this association was probably driven by high HDL level. These variables were not associated with serum C-terminal of telopeptide crosslinks in the subjects (p > 0.05). Serum osteocalcin is associated with indices of obesity and HDL level in men. These relationships should be validated by a longitudinal study, with comprehensive hormone profile testing.

Quality management and job related factors predicting satisfaction of dental clinic staff in Estonia.

PubMed

Merisalu, Eda; Männik, Georg; Põlluste, Kaja

2014-01-01

The aim of the study was to explore the role of managerial style, work environment factors and burnout in determining job satisfaction during the implementation of quality improvement activities in a dental clinic. Quantitative research was carried out using a prestructured anonymous questionnaire to survey 302 respondents in Kaarli Dental Clinic, Estonia. Dental clinic staff assessed job satisfaction, managerial style, work stress and burnout levels through the implementation period of ISO 9000 quality management system in 2003 and annually during 2006-2009. Binary logistic regression was used to explain the impact of satisfaction with management and work organisation, knowledge about managerial activities, work environment and psychosocial stress and burnout on job satisfaction. The response rate limits were between 60% and 89.6%. Job satisfaction increased significantly from 2003 to 2006 and the percentage of very satisfied staff increased from 17 to 38 (p<0.01) over this period. In 2007, the proportion of very satisfied people dropped to 21% before increasing again in 2008-2009 (from 24% to 35%). Binary logistic regression analysis resulted in a model that included five groups of factors: managerial support, information about results achieved and progress to goals, work organisation and working environment, as well as factors related to career, security and planning. The average scores of emotional exhaustion showed significant decrease, correlating negatively with job satisfaction (p<0.05). The implementation of quality improvement activities in the Kaarli Dental Clinic has improved the work environment by decreasing burnout symptoms and increased job satisfaction in staff.

A local equation for differential diagnosis of β-thalassemia trait and iron deficiency anemia by logistic regression analysis in Southeast Iran.

PubMed

Sargolzaie, Narjes; Miri-Moghaddam, Ebrahim

2014-01-01

The most common differential diagnosis of β-thalassemia (β-thal) trait is iron deficiency anemia. Several red blood cell equations were introduced during different studies for differential diagnosis between β-thal trait and iron deficiency anemia. Due to genetic variations in different regions, these equations cannot be useful in all population. The aim of this study was to determine a native equation with high accuracy for differential diagnosis of β-thal trait and iron deficiency anemia for the Sistan and Baluchestan population by logistic regression analysis. We selected 77 iron deficiency anemia and 100 β-thal trait cases. We used binary logistic regression analysis and determined best equations for probability prediction of β-thal trait against iron deficiency anemia in our population. We compared diagnostic values and receiver operative characteristic (ROC) curve related to this equation and another 10 published equations in discriminating β-thal trait and iron deficiency anemia. The binary logistic regression analysis determined the best equation for best probability prediction of β-thal trait against iron deficiency anemia with area under curve (AUC) 0.998. Based on ROC curves and AUC, Green & King, England & Frazer, and then Sirdah indices, respectively, had the most accuracy after our equation. We suggest that to get the best equation and cut-off in each region, one needs to evaluate specific information of each region, specifically in areas where populations are homogeneous, to provide a specific formula for differentiating between β-thal trait and iron deficiency anemia.

Logistic Mixed Models to Investigate Implicit and Explicit Belief Tracking.

PubMed

Lages, Martin; Scheel, Anne

2016-01-01

We investigated the proposition of a two-systems Theory of Mind in adults' belief tracking. A sample of N = 45 participants predicted the choice of one of two opponent players after observing several rounds in an animated card game. Three matches of this card game were played and initial gaze direction on target and subsequent choice predictions were recorded for each belief task and participant. We conducted logistic regressions with mixed effects on the binary data and developed Bayesian logistic mixed models to infer implicit and explicit mentalizing in true belief and false belief tasks. Although logistic regressions with mixed effects predicted the data well a Bayesian logistic mixed model with latent task- and subject-specific parameters gave a better account of the data. As expected explicit choice predictions suggested a clear understanding of true and false beliefs (TB/FB). Surprisingly, however, model parameters for initial gaze direction also indicated belief tracking. We discuss why task-specific parameters for initial gaze directions are different from choice predictions yet reflect second-order perspective taking.

Is parenting style a predictor of suicide attempts in a representative sample of adolescents?

PubMed Central

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 < .001) for suicidal attempts. Seven further variables were interpreted to be statistically significant and clinically relevant: ADHD, female sex, smoking, Binge Drinking, absenteeism/truancy, migration background, and parental separation events. Conclusions Parenting style does matter. While children of Authoritative parents profit, children of Rejecting-Neglecting parents are put at risk – as we were able to show for suicide attempts in adolescence. Some of the identified risk factors contribute new knowledge and potential areas of intervention for special groups such as migrants or children diagnosed with ADHD. PMID:24766881

Bayesian inference for unidirectional misclassification of a binary response trait.

PubMed

Xia, Michelle; Gustafson, Paul

2018-03-15

When assessing association between a binary trait and some covariates, the binary response may be subject to unidirectional misclassification. Unidirectional misclassification can occur when revealing a particular level of the trait is associated with a type of cost, such as a social desirability or financial cost. The feasibility of addressing misclassification is commonly obscured by model identification issues. The current paper attempts to study the efficacy of inference when the binary response variable is subject to unidirectional misclassification. From a theoretical perspective, we demonstrate that the key model parameters possess identifiability, except for the case with a single binary covariate. From a practical standpoint, the logistic model with quantitative covariates can be weakly identified, in the sense that the Fisher information matrix may be near singular. This can make learning some parameters difficult under certain parameter settings, even with quite large samples. In other cases, the stronger identification enables the model to provide more effective adjustment for unidirectional misclassification. An extension to the Poisson approximation of the binomial model reveals the identifiability of the Poisson and zero-inflated Poisson models. For fully identified models, the proposed method adjusts for misclassification based on learning from data. For binary models where there is difficulty in identification, the method is useful for sensitivity analyses on the potential impact from unidirectional misclassification. Copyright © 2017 John Wiley & Sons, Ltd.

America's Democracy Colleges: The Civic Engagement of Community College Students

ERIC Educational Resources Information Center

Angeli Newell, Mallory

2014-01-01

This study explored the civic engagement of current two- and four-year students to explore whether differences exist between the groups and what may explain the differences. Using binary logistic regression and Ordinary Least Squares regression it was found that community-based engagement was lower for two- than four-year students, though…

Attitudes towards Participation in Business Development Programmes: An Ethnic Comparison in Sweden

ERIC Educational Resources Information Center

Abbasian, Saeid; Yazdanfar, Darush

2015-01-01

Purpose: The aim of the study is to investigate whether there are any differences between the attitudes towards participation in development programmes of entrepreneurs who are immigrants and those who are native-born. Design/methodology/approach: Several statistical methods, including a binary logistic regression model, were used to analyse a…

2004 Carolyn Sherif Award Address: Heart Disease and Gender Inequity

ERIC Educational Resources Information Center

Travis, Cheryl Brown

2005-01-01

Individual patient records from the National Hospital Discharge Survey for 1988 and 1998 comprising approximately 10 million cases were the basis for a binary logistic regression model to predict coronary artery bypass graft. Patterns in 1988 and in 1998 indicated a dramatic and pernicious gender discrepancy in medical decisions involving bypass…

Factors Affecting Code Status in a University Hospital Intensive Care Unit

ERIC Educational Resources Information Center

Van Scoy, Lauren Jodi; Sherman, Michael

2013-01-01

The authors collected data on diagnosis, hospital course, and end-of-life preparedness in patients who died in the intensive care unit (ICU) with "full code" status (defined as receiving cardiopulmonary resuscitation), compared with those who didn't. Differences were analyzed using binary and stepwise logistic regression. They found no…

Impact of Perceived Risk and Friend Influence on Alcohol and Marijuana Use among Students

ERIC Educational Resources Information Center

Merianos, Ashley L.; Rosen, Brittany L.; Montgomery, LaTrice; Barry, Adam E.; Smith, Matthew Lee

2017-01-01

We performed a secondary analysis of Adolescent Health Risk Behavior Survey data (N=937), examining associations between lifetime alcohol and marijuana use with intrapersonal (i.e., risk perceptions) and interpersonal (e.g., peer approval and behavior) factors. Multinomial and binary logistic regression analyses contend students reporting lifetime…

Multidimensional Ultrasound Imaging of the Wrist: Changes of Shape and Displacement of the Median Nerve and Tendons in Carpal Tunnel Syndrome

PubMed Central

Filius, Anika; Scheltens, Marjan; Bosch, Hans G.; van Doorn, Pieter A.; Stam, Henk J.; Hovius, Steven E.R.; Amadio, Peter C.; Selles, Ruud W.

2015-01-01

Dynamics of structures within the carpal tunnel may alter in carpal tunnel syndrome (CTS) due to fibrotic changes and increased carpal tunnel pressure. Ultrasound can visualize these potential changes, making ultrasound potentially an accurate diagnostic tool. To study this, we imaged the carpal tunnel of 113 patients and 42 controls. CTS severity was classified according to validated clinical and nerve conduction study (NCS) classifications. Transversal and longitudinal displacement and shape (changes) were calculated for the median nerve, tendons and surrounding tissue. To predict diagnostic value binary logistic regression modeling was applied. Reduced longitudinal nerve displacement (p≤0.019), increased nerve cross-sectional area (p≤0.006) and perimeter (p≤0.007), and a trend of relatively changed tendon displacements were seen in patients. Changes were more convincing when CTS was classified as more severe. Binary logistic modeling to diagnose CTS using ultrasound showed a sensitivity of 70-71% and specificity of 80-84%. In conclusion, CTS patients have altered dynamics of structures within the carpal tunnel. PMID:25865180

Predictors associated with the willingness to take human papilloma virus vaccination.

PubMed

Naing, Cho; Pereira, Joanne; Abe, Tatsuki; Eh Zhen Wei, Daniel; Rahman Bajera, Ibrizah Binti Abdul; Kavinda Perera, Undugodage Heshan

2012-04-01

Human papilloma virus vaccine is considered to be the primary form of cervical cancer prevention. The objectives were (1) to determine knowledge about, and perception of human papilloma virus infection in relation to cervical cancer, (2) to explore the intention of the community to be vaccinated with human papilloma virus vaccine, and (3) to identify variables that could predict the likelihood of uptake of the vaccine. A cross-sectional survey was carried out in a semi-urban Town of Malaysia, using a pre-tested structured questionnaire. Summary statistics, Pearson chi-square test and a binary logistic regression were used for data analysis. A total of 232 respondents were interviewed. Overall, only a few had good knowledge related to human papilloma virus (14%) or vaccination (8%). Many had misconceptions that it could be transmitted through blood transfusion (57%). Sixty percent had intention to take vaccination. In the binary logistic model, willingness to take vaccination was significant with 'trusts that vaccination would be effective for prevention of cervical cancer' (P = 0.001), 'worries for themselves' (P < 0.001) or 'their family members' (P = 0.003) and 'being Indian ethnicity' (P = 0.024). The model could fairly predict the likelihood of uptake of the vaccine (Cox & Snell R(2) = .415; Nagelkerke R(2) = 0.561). Results indicate that intensive health education dispelling misconception and risk perception towards human papilloma virus infection and cervical cancer would be helpful to increase the acceptability of vaccination program.

Self-declared stock ownership and association with positive trial outcome in randomized controlled trials with binary outcomes published in general medical journals: a cross-sectional study.

PubMed

Falk Delgado, Alberto; Falk Delgado, Anna

2017-07-26

Describe the prevalence and types of conflicts of interest (COI) in published randomized controlled trials (RCTs) in general medical journals with a binary primary outcome and assess the association between conflicts of interest and favorable outcome. Parallel-group RCTs with a binary primary outcome published in three general medical journals during 2013-2015 were identified. COI type, funding source, and outcome were extracted. Binomial logistic regression model was performed to assess association between COI and funding source with outcome. A total of 509 consecutive parallel-group RCTs were included in the study. COI was reported in 74% in mixed funded RCTs and in 99% in for-profit funded RCTs. Stock ownership was reported in none of the non-profit RCTs, in 7% of mixed funded RCTs, and in 50% of for-profit funded RCTs. Mixed-funded RCTs had employees from the funding company in 11% and for-profit RCTs in 76%. Multivariable logistic regression revealed that stock ownership in the funding company among any of the authors was associated with a favorable outcome (odds ratio = 3.53; 95% confidence interval = 1.59-7.86; p < 0.01). COI in for-profit funded RCTs is extensive, because the factors related to COI are not fully independent, a multivariable analysis should be cautiously interpreted. However, after multivariable adjustment only stock ownership from the funding company among authors is associated with a favorable outcome.

An empirical comparison of methods for analyzing correlated data from a discrete choice survey to elicit patient preference for colorectal cancer screening

PubMed Central

2012-01-01

Background A discrete choice experiment (DCE) is a preference survey which asks participants to make a choice among product portfolios comparing the key product characteristics by performing several choice tasks. Analyzing DCE data needs to account for within-participant correlation because choices from the same participant are likely to be similar. In this study, we empirically compared some commonly-used statistical methods for analyzing DCE data while accounting for within-participant correlation based on a survey of patient preference for colorectal cancer (CRC) screening tests conducted in Hamilton, Ontario, Canada in 2002. Methods A two-stage DCE design was used to investigate the impact of six attributes on participants' preferences for CRC screening test and willingness to undertake the test. We compared six models for clustered binary outcomes (logistic and probit regressions using cluster-robust standard error (SE), random-effects and generalized estimating equation approaches) and three models for clustered nominal outcomes (multinomial logistic and probit regressions with cluster-robust SE and random-effects multinomial logistic model). We also fitted a bivariate probit model with cluster-robust SE treating the choices from two stages as two correlated binary outcomes. The rank of relative importance between attributes and the estimates of β coefficient within attributes were used to assess the model robustness. Results In total 468 participants with each completing 10 choices were analyzed. Similar results were reported for the rank of relative importance and β coefficients across models for stage-one data on evaluating participants' preferences for the test. The six attributes ranked from high to low as follows: cost, specificity, process, sensitivity, preparation and pain. However, the results differed across models for stage-two data on evaluating participants' willingness to undertake the tests. Little within-patient correlation (ICC ≈ 0) was found in stage-one data, but substantial within-patient correlation existed (ICC = 0.659) in stage-two data. Conclusions When small clustering effect presented in DCE data, results remained robust across statistical models. However, results varied when larger clustering effect presented. Therefore, it is important to assess the robustness of the estimates via sensitivity analysis using different models for analyzing clustered data from DCE studies. PMID:22348526

Summary goodness-of-fit statistics for binary generalized linear models with noncanonical link functions.

PubMed

Canary, Jana D; Blizzard, Leigh; Barry, Ronald P; Hosmer, David W; Quinn, Stephen J

2016-05-01

Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness-of-fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (TG), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J(2) ) statistics can be applied directly. In a simulation study, TG, HL, and J(2) were used to evaluate the fit of probit, log-log, complementary log-log, and log models, all calculated with a common grouping method. The TG statistic consistently maintained Type I error rates, while those of HL and J(2) were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, TG had more power than HL or J(2) . © 2015 John Wiley & Sons Ltd/London School of Economics.

Predictors of Gender Inequalities in the Rank of Full Professor

ERIC Educational Resources Information Center

Heijstra, Thamar; Bjarnason, Thoroddur; Rafnsdóttir, Gudbjörg Linda

2015-01-01

This article examines whether age, work-related, and family-related predictors explain differences in the academic advancement of women and men in Iceland. Survey data were analyzed by binary logistic regression. The findings put that women climb the academic career ladder at a slower pace than men. This finding puts one of the widely known…

South Texas Mexican American Use of Traditional Folk and Mainstream Alternative Therapies

ERIC Educational Resources Information Center

Martinez, Leslie N.

2009-01-01

A telephone survey was conducted with a large sample of Mexican Americans from border (n = 1,001) and nonborder (n = 1,030) regions in Texas. Patterns of traditional folk and mainstream complementary and alternative medicine (CAM) use were analyzed with two binary logistic regressions, using gender, self-rated health, confidence in medical…

Examining the Link Between Public Transit Use and Active Commuting

PubMed Central

Bopp, Melissa; Gayah, Vikash V.; Campbell, Matthew E.

2015-01-01

Background: An established relationship exists between public transportation (PT) use and physical activity. However, there is limited literature that examines the link between PT use and active commuting (AC) behavior. This study examines this link to determine if PT users commute more by active modes. Methods: A volunteer, convenience sample of adults (n = 748) completed an online survey about AC/PT patterns, demographic, psychosocial, community and environmental factors. t-test compared differences between PT riders and non-PT riders. Binary logistic regression analyses examined the effect of multiple factors on AC and a full logistic regression model was conducted to examine AC. Results: Non-PT riders (n = 596) reported less AC than PT riders. There were several significant relationships with AC for demographic, interpersonal, worksite, community and environmental factors when considering PT use. The logistic multivariate analysis for included age, number of children and perceived distance to work as negative predictors and PT use, feelings of bad weather and lack of on-street bike lanes as a barrier to AC, perceived behavioral control and spouse AC were positive predictors. Conclusions: This study revealed the complex relationship between AC and PT use. Further research should investigate how AC and public transit use are related. PMID:25898405

Logistic Mixed Models to Investigate Implicit and Explicit Belief Tracking

PubMed Central

Lages, Martin; Scheel, Anne

2016-01-01

We investigated the proposition of a two-systems Theory of Mind in adults’ belief tracking. A sample of N = 45 participants predicted the choice of one of two opponent players after observing several rounds in an animated card game. Three matches of this card game were played and initial gaze direction on target and subsequent choice predictions were recorded for each belief task and participant. We conducted logistic regressions with mixed effects on the binary data and developed Bayesian logistic mixed models to infer implicit and explicit mentalizing in true belief and false belief tasks. Although logistic regressions with mixed effects predicted the data well a Bayesian logistic mixed model with latent task- and subject-specific parameters gave a better account of the data. As expected explicit choice predictions suggested a clear understanding of true and false beliefs (TB/FB). Surprisingly, however, model parameters for initial gaze direction also indicated belief tracking. We discuss why task-specific parameters for initial gaze directions are different from choice predictions yet reflect second-order perspective taking. PMID:27853440

Predicting High School Students' Interest in Majoring in a STEM Field: Insight into High School Students' Postsecondary Plans

ERIC Educational Resources Information Center

Lichtenberger, Eric; George-Jackson, Casey

2013-01-01

This study examined how various individual, family, and school level contextual factors impact the likelihood of planning to major in one of the science, technology, engineering, or mathematics (STEM) fields for high school students. A binary logistic regression model was developed to determine the extent to which each of the covariates helped to…

Community-Based Juvenile Reentry Services: The Effects of Service Dosage on Juvenile and Adult Recidivism

ERIC Educational Resources Information Center

Abrams, Laura S.; Terry, Diane; Franke, Todd M.

2011-01-01

In this study the authors examined the influence of length of participation in a community-based reentry program on the odds of reconviction in the juvenile and adult criminal justice systems. A structured telephone survey of reentry program alumni was conducted with 75 transition-age (18-25 year-old) young men. Binary logistic regression analysis…

Predicators of Success for Undergraduate Students Reinstated after an Academic Dismissal at a Small Midwest Private University Campus

ERIC Educational Resources Information Center

Meador, Ryan E.

2012-01-01

This study examined students who successfully applied for reinstatement after being academically dismissed for the first time in order to discover indicators of future success. This study examined 666 students' appeals filed at the DeVry University Kansas City campus between 2004 and 2009. Binary logistic regression was used to discover if a…

Experiences That Predict Early Career Teacher Commitment to and Retention in High-Poverty Urban Schools

ERIC Educational Resources Information Center

Whipp, Joan L.; Geronime, Lara

2017-01-01

Correlation analysis was used to analyze what experiences before and during teacher preparation for 72 graduates of an urban teacher education program were associated with urban commitment, first job location, and retention in urban schools for 3 or more years. Binary logistic regression was then used to analyze whether urban K-12 schooling,…

Bayesian Analysis of Item Response Curves. Research Report 84-1. Mathematical Sciences Technical Report No. 132.

ERIC Educational Resources Information Center

Tsutakawa, Robert K.; Lin, Hsin Ying

Item response curves for a set of binary responses are studied from a Bayesian viewpoint of estimating the item parameters. For the two-parameter logistic model with normally distributed ability, restricted bivariate beta priors are used to illustrate the computation of the posterior mode via the EM algorithm. The procedure is illustrated by data…

Understanding the Gap between Cognitive Abilities and Daily Living Skills in Adolescents with Autism Spectrum Disorders with Average Intelligence

ERIC Educational Resources Information Center

Duncan, Amie W.; Bishop, Somer L.

2015-01-01

Daily living skills standard scores on the Vineland Adaptive Behavior Scales-2nd edition were examined in 417 adolescents from the Simons Simplex Collection. All participants had at least average intelligence and a diagnosis of autism spectrum disorder. Descriptive statistics and binary logistic regressions were used to examine the prevalence and…

Sociodemographic Barriers to Early Detection of Autism: Screening and Evaluation Using the M-CHAT, M-CHAT-R, and Follow-Up

ERIC Educational Resources Information Center

Khowaja, Meena K.; Hazzard, Ann P.; Robins, Diana L.

2015-01-01

Parents (n = 11,845) completed the Modified Checklist for Autism in Toddlers (or its latest revision) at pediatric visits. Using sociodemographic predictors of maternal education and race, binary logistic regressions were utilized to examine differences in autism screening, diagnostic evaluation participation rates and outcomes, and reasons for…

The Effect of Participating in Indiana's Twenty-First Century Scholars Program on College Enrollments

ERIC Educational Resources Information Center

Toutkoushian, Robert K.; Hossler, Don; DesJardins, Stephen L.; McCall, Brian; Gonzalez Canche, Manuel S.

2015-01-01

Our study adds to prior work on Indiana's Twenty-first Century Scholars(TFCS) program by focusing on whether participating in--rather than completing--the program affects the likelihood of students going to college and where they initially enrolled. We first employ binary and multinomial logistic regression to obtain estimates of the impact of the…

Sample size adjustments for varying cluster sizes in cluster randomized trials with binary outcomes analyzed with second-order PQL mixed logistic regression.

PubMed

Candel, Math J J M; Van Breukelen, Gerard J P

2010-06-30

Adjustments of sample size formulas are given for varying cluster sizes in cluster randomized trials with a binary outcome when testing the treatment effect with mixed effects logistic regression using second-order penalized quasi-likelihood estimation (PQL). Starting from first-order marginal quasi-likelihood (MQL) estimation of the treatment effect, the asymptotic relative efficiency of unequal versus equal cluster sizes is derived. A Monte Carlo simulation study shows this asymptotic relative efficiency to be rather accurate for realistic sample sizes, when employing second-order PQL. An approximate, simpler formula is presented to estimate the efficiency loss due to varying cluster sizes when planning a trial. In many cases sampling 14 per cent more clusters is sufficient to repair the efficiency loss due to varying cluster sizes. Since current closed-form formulas for sample size calculation are based on first-order MQL, planning a trial also requires a conversion factor to obtain the variance of the second-order PQL estimator. In a second Monte Carlo study, this conversion factor turned out to be 1.25 at most. (c) 2010 John Wiley & Sons, Ltd.

Risk Factors of Subacute Thrombosis After Intracranial Stenting for Symptomatic Intracranial Arterial Stenosis.

PubMed

Sun, Xuan; Tong, Xu; Lo, Wai Ting; Mo, Dapeng; Gao, Feng; Ma, Ning; Wang, Bo; Miao, Zhongrong

2017-03-01

We aimed to explore the risk factors of subacute thrombosis (SAT) after intracranial stenting for patients with symptomatic intracranial arterial stenosis. From January to December 2013, all symptomatic intracranial arterial stenosis patients who underwent intracranial stenting in Beijing Tiantan Hospital were prospectively registered into this study. Baseline clinical features and operative data were compared in patients who developed SAT with those who did not. Binary logistic regression model was used to determine the risk factors associated with SAT. Of the 221 patients enrolled, 9 (4.1%) cases had SAT 2 to 8 days after stenting. Binary logistic analysis showed that SAT was related with tandem stenting (odds ratio [OR], 11.278; 95% confidence interval [CI], 2.422-52.519) and antiplatelet resistance (aspirin resistance: OR, 6.267; 95% CI, 1.574-24.952; clopidogrel resistance: OR, 15.526; 95% CI, 3.105-77.626; aspirin and clopidogrel resistance: OR, 12.246; 95% CI, 2.932-51.147; and aspirin or clopidogrel resistance: OR, 11.340; 95% CI, 2.282-56.344). Tandem stenting and antiplatelet resistance might contribute to the development of SAT after intracranial stenting in patients with symptomatic intracranial arterial stenosis. © 2017 American Heart Association, Inc.

A measurement of disorder in binary sequences

NASA Astrophysics Data System (ADS)

Gong, Longyan; Wang, Haihong; Cheng, Weiwen; Zhao, Shengmei

2015-03-01

We propose a complex quantity, AL, to characterize the degree of disorder of L-length binary symbolic sequences. As examples, we respectively apply it to typical random and deterministic sequences. One kind of random sequences is generated from a periodic binary sequence and the other is generated from the logistic map. The deterministic sequences are the Fibonacci and Thue-Morse sequences. In these analyzed sequences, we find that the modulus of AL, denoted by |AL | , is a (statistically) equivalent quantity to the Boltzmann entropy, the metric entropy, the conditional block entropy and/or other quantities, so it is a useful quantitative measure of disorder. It can be as a fruitful index to discern which sequence is more disordered. Moreover, there is one and only one value of |AL | for the overall disorder characteristics. It needs extremely low computational costs. It can be easily experimentally realized. From all these mentioned, we believe that the proposed measure of disorder is a valuable complement to existing ones in symbolic sequences.

A new method for constructing networks from binary data

NASA Astrophysics Data System (ADS)

van Borkulo, Claudia D.; Borsboom, Denny; Epskamp, Sacha; Blanken, Tessa F.; Boschloo, Lynn; Schoevers, Robert A.; Waldorp, Lourens J.

2014-08-01

Network analysis is entering fields where network structures are unknown, such as psychology and the educational sciences. A crucial step in the application of network models lies in the assessment of network structure. Current methods either have serious drawbacks or are only suitable for Gaussian data. In the present paper, we present a method for assessing network structures from binary data. Although models for binary data are infamous for their computational intractability, we present a computationally efficient model for estimating network structures. The approach, which is based on Ising models as used in physics, combines logistic regression with model selection based on a Goodness-of-Fit measure to identify relevant relationships between variables that define connections in a network. A validation study shows that this method succeeds in revealing the most relevant features of a network for realistic sample sizes. We apply our proposed method to estimate the network of depression and anxiety symptoms from symptom scores of 1108 subjects. Possible extensions of the model are discussed.

Categorical QSAR models for skin sensitization based on local lymph node assay measures and both ground and excited state 4D-fingerprint descriptors

NASA Astrophysics Data System (ADS)

Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Santos-Filho, Osvaldo A.; Esposito, Emilio X.; Hopfinger, Anton J.; Tseng, Yufeng J.

2008-06-01

In previous studies we have developed categorical QSAR models for predicting skin-sensitization potency based on 4D-fingerprint (4D-FP) descriptors and in vivo murine local lymph node assay (LLNA) measures. Only 4D-FP derived from the ground state (GMAX) structures of the molecules were used to build the QSAR models. In this study we have generated 4D-FP descriptors from the first excited state (EMAX) structures of the molecules. The GMAX, EMAX and the combined ground and excited state 4D-FP descriptors (GEMAX) were employed in building categorical QSAR models. Logistic regression (LR) and partial least square coupled logistic regression (PLS-CLR), found to be effective model building for the LLNA skin-sensitization measures in our previous studies, were used again in this study. This also permitted comparison of the prior ground state models to those involving first excited state 4D-FP descriptors. Three types of categorical QSAR models were constructed for each of the GMAX, EMAX and GEMAX datasets: a binary model (2-state), an ordinal model (3-state) and a binary-binary model (two-2-state). No significant differences exist among the LR 2-state model constructed for each of the three datasets. However, the PLS-CLR 3-state and 2-state models based on the EMAX and GEMAX datasets have higher predictivity than those constructed using only the GMAX dataset. These EMAX and GMAX categorical models are also more significant and predictive than corresponding models built in our previous QSAR studies of LLNA skin-sensitization measures.

Nowcasting sunshine number using logistic modeling

NASA Astrophysics Data System (ADS)

Brabec, Marek; Badescu, Viorel; Paulescu, Marius

2013-04-01

In this paper, we present a formalized approach to statistical modeling of the sunshine number, binary indicator of whether the Sun is covered by clouds introduced previously by Badescu (Theor Appl Climatol 72:127-136, 2002). Our statistical approach is based on Markov chain and logistic regression and yields fully specified probability models that are relatively easily identified (and their unknown parameters estimated) from a set of empirical data (observed sunshine number and sunshine stability number series). We discuss general structure of the model and its advantages, demonstrate its performance on real data and compare its results to classical ARIMA approach as to a competitor. Since the model parameters have clear interpretation, we also illustrate how, e.g., their inter-seasonal stability can be tested. We conclude with an outlook to future developments oriented to construction of models allowing for practically desirable smooth transition between data observed with different frequencies and with a short discussion of technical problems that such a goal brings.

Nurses’ knowledge on phlebotomy in tertiary hospitals in China: a cross-sectional multicentric survey

PubMed Central

Cai, Qian; Zhou, Yunxian; Yang, Dangan

2017-01-01

Introduction In China, phlebotomy practice is mostly executed by nurses instead of phlebotomists. Our hypothesis was that these nurses may lack of knowledge on phlebotomy, especially factors influencing quality of blood samples. This study aims to assess the overall nurses’ knowledge on phlebotomy to provide reference for improving blood sampling practice in China. Materials and methods A survey was conducted involving nurses from 4 regions and 13 hospitals in China. A phlebotomy knowledge questionnaire was designed based on the Clinical and Laboratory Standards Institute H3-A6 guidelines, combining with the situations in China. Descriptive analysis and binary logistic regression analysis were used to analyze the knowledge level and its influencing factors. Results A total of 3400 questionnaires were distributed and 3077 valid questionnaires were returned, with an effective return rate of 90.5%. The correct rates of patient identification, hand sanitization, patient assessment, tube mixing time, needle disposing location and tube labelling were greater than 90%. However, the correct rates of order of draw (15.5%), definition of an inversion (22.5%), time to release tourniquet (18.5%) and time to change tube (28.5%) were relatively low. Binary logistic regression analysis showed that the correct rates of the aforementioned four questions were mainly related to the regional distribution of the hospitals (P < 0.001). Conclusions The knowledge level on phlebotomy among Chinese nurses was found unsatisfactory in some areas. An education program on phlebotomy should be developed for Chinese nurses to improve the consistency among different regions and to enhance nurse’s knowledge level on phlebotomy. PMID:29187796

Hopelessness and Suicidal Ideation among Patients with Depression and Neurotic Disorders Attending a Tertiary Care Centre at Eastern Nepal.

PubMed

Pokharel, R; Lama, S; Adhikari, B R

2016-09-01

Hopelessness is thought to result from a negative appraisal system and interacts with, and worsens, appraisals of defeat and trap which in turn interact with suicide schema and lead to suicidal behaviour. This study was intended to assess hopelessness and suicidal ideation among patients with depression and neurotic disorders at tertiary care centre of eastern Nepal. A cross sectional design included 70 respondents by purposive sampling technique. Beck Hopelessness Scale and Scale of Suicidal Ideation were used to measure hopelessness and suicidal ideation, respectively. Data were analyzed using SPSS statistical software. Pearson chi-square, binary logistic regression and Spearmans' rho, test were applied at 95% confidence interval. Mean ± SD age was 32.8 ± 13.5 years. Most (62.8%) of the patients were female and with the diagnosis of depression. Majority (66%) of the patients had hopelessness. There was no significant difference in hopelessness among patients with depression and neurotic disorders. About 17% respondents had suicidal ideation, among them 82.4% were female. There was no significant difference of suicidal ideation among patients with depression and neurotic disorders (p=0.013). Significant positive correlation between hopelessness and suicidal ideation was found (p=0.001). Binary logistic regression revealed hopelessness was independently related to income and family history of mental illness. Similarly, suicidal ideation was independently related to depression and family history of mental illness. Female respondents, people living under poverty and positive family history of mental illness had more hopelessness and suicidal ideation.

Benign-malignant mass classification in mammogram using edge weighted local texture features

NASA Astrophysics Data System (ADS)

Rabidas, Rinku; Midya, Abhishek; Sadhu, Anup; Chakraborty, Jayasree

2016-03-01

This paper introduces novel Discriminative Robust Local Binary Pattern (DRLBP) and Discriminative Robust Local Ternary Pattern (DRLTP) for the classification of mammographic masses as benign or malignant. Mass is one of the common, however, challenging evidence of breast cancer in mammography and diagnosis of masses is a difficult task. Since DRLBP and DRLTP overcome the drawbacks of Local Binary Pattern (LBP) and Local Ternary Pattern (LTP) by discriminating a brighter object against the dark background and vice-versa, in addition to the preservation of the edge information along with the texture information, several edge-preserving texture features are extracted, in this study, from DRLBP and DRLTP. Finally, a Fisher Linear Discriminant Analysis method is incorporated with discriminating features, selected by stepwise logistic regression method, for the classification of benign and malignant masses. The performance characteristics of DRLBP and DRLTP features are evaluated using a ten-fold cross-validation technique with 58 masses from the mini-MIAS database, and the best result is observed with DRLBP having an area under the receiver operating characteristic curve of 0.982.

Estimating the Probability of Rare Events Occurring Using a Local Model Averaging.

PubMed

Chen, Jin-Hua; Chen, Chun-Shu; Huang, Meng-Fan; Lin, Hung-Chih

2016-10-01

In statistical applications, logistic regression is a popular method for analyzing binary data accompanied by explanatory variables. But when one of the two outcomes is rare, the estimation of model parameters has been shown to be severely biased and hence estimating the probability of rare events occurring based on a logistic regression model would be inaccurate. In this article, we focus on estimating the probability of rare events occurring based on logistic regression models. Instead of selecting a best model, we propose a local model averaging procedure based on a data perturbation technique applied to different information criteria to obtain different probability estimates of rare events occurring. Then an approximately unbiased estimator of Kullback-Leibler loss is used to choose the best one among them. We design complete simulations to show the effectiveness of our approach. For illustration, a necrotizing enterocolitis (NEC) data set is analyzed. © 2016 Society for Risk Analysis.

Stochastic model search with binary outcomes for genome-wide association studies

PubMed Central

Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-01-01

Objective The spread of case–control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Materials and methods Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. Results BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. Discussion BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. Conclusion The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model. PMID:22534080

Completing the Remedial Sequence and College-Level Credit-Bearing Math: Comparing Binary, Cumulative, and Continuation Ratio Logistic Regression Models

ERIC Educational Resources Information Center

Davidson, J. Cody

2016-01-01

Mathematics is the most common subject area of remedial need and the majority of remedial math students never pass a college-level credit-bearing math class. The majorities of studies that investigate this phenomenon are conducted at community colleges and use some type of regression model; however, none have used a continuation ratio model. The…

Modeling Student Performance in Mathematics Using Binary Logistic Regression at Selected Secondary Schools a Case Study of Mtwara Municipality and Ilemela District

ERIC Educational Resources Information Center

Mabula, Salyungu

2015-01-01

This study investigated the performance of secondary school students in Mathematics at the Selected Secondary Schools in Mtwara Municipality and Ilemela District by Absenteeism, Conduct, Type of School and Gender as explanatory Factors. The data used in the study was collected from documented records of 250 form three students with 1:1 gender…

User’s Guide to Southeast Asia Combat Data

DTIC Science & Technology

1976-06-01

North latitude Binary coded decimal Bomb damage assessment Battle Damage Assessment and Reporting Team Brigade Basic encyclopedia A University of...and movement routes Bomb wing CALCOMP CANDLESTICK CAP CAP CAS CAS CAVD CBU , CBS California Computer Products, Inc. Call sign...Special Studies Group (a high-level Washington committee) WAC WBLC WIA WOLF WSE3 WWDMS WWMCCS W X World Aeronautical Chart Waterborne logistic

Factors That Contributed to Gifted Students' Success on STEM Pathways: The Role of Race, Personal Interests, and Aspects of High School Experience

ERIC Educational Resources Information Center

Steenbergen-Hu, Saiying; Olszewski-Kubilius, Paula

2017-01-01

In this study, we conducted binary logistic regression on survey data collected from 244 past participants of a Talent Search program who attended regular high schools but supplemented their regular high school education with enriched or accelerated math and science learning activities. The participants completed an online survey 4 to 6 years…

Sample size calculations for case-control studies

Cancer.gov

This R package can be used to calculate the required samples size for unconditional multivariate analyses of unmatched case-control studies. The sample sizes are for a scalar exposure effect, such as binary, ordinal or continuous exposures. The sample sizes can also be computed for scalar interaction effects. The analyses account for the effects of potential confounder variables that are also included in the multivariate logistic model.

Association Between Socio-Demographic Background and Self-Esteem of University Students.

PubMed

Haq, Muhammad Ahsan Ul

2016-12-01

The purpose of this study was to scrutinize self-esteem of university students and explore association of self-esteem with academic achievement, gender and other factors. A sample of 346 students was selected from Punjab University, Lahore Pakistan. Rosenberg self-esteem scale with demographic variables was used for data collection. Besides descriptive statistics, binary logistic regression and t test were used for analysing the data. Significant gender difference was observed, self-esteem was significantly higher in males than females. Logistic regression indicates that age, medium of instruction, family income, student monthly expenditures, GPA and area of residence has direct effect on self-esteem; while number of siblings showed an inverse effect.

glmnetLRC f/k/a lrc package: Logistic Regression Classification

DOE Office of Scientific and Technical Information (OSTI.GOV)

2016-06-09

Methods for fitting and predicting logistic regression classifiers (LRC) with an arbitrary loss function using elastic net or best subsets. This package adds additional model fitting features to the existing glmnet and bestglm R packages. This package was created to perform the analyses described in Amidan BG, Orton DJ, LaMarche BL, et al. 2014. Signatures for Mass Spectrometry Data Quality. Journal of Proteome Research. 13(4), 2215-2222. It makes the model fitting available in the glmnet and bestglm packages more general by identifying optimal model parameters via cross validation with an customizable loss function. It also identifies the optimal threshold formore » binary classification.« less

Is parenting style a predictor of suicide attempts in a representative sample of adolescents?

PubMed

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 < .001) for suicidal attempts. Seven further variables were interpreted to be statistically significant and clinically relevant: ADHD, female sex, smoking, Binge Drinking, absenteeism/truancy, migration background, and parental separation events. Parenting style does matter. While children of Authoritative parents profit, children of Rejecting-Neglecting parents are put at risk - as we were able to show for suicide attempts in adolescence. Some of the identified risk factors contribute new knowledge and potential areas of intervention for special groups such as migrants or children diagnosed with ADHD.

Registered dietitian's personal beliefs and characteristics predict their teaching or intention to teach fresh vegetable food safety.

PubMed

Casagrande, Gina; LeJeune, Jeffery; Belury, Martha A; Medeiros, Lydia C

2011-04-01

The Theory of Planned Behavior was used to determine if dietitians personal characteristics and beliefs about fresh vegetable food safety predict whether they currently teach, intend to teach, or neither currently teach nor intend to teach food safety information to their clients. Dietitians who participated in direct client education responded to this web-based survey (n=327). The survey evaluated three independent belief variables: Subjective Norm, Attitudes, and Perceived Behavioral Control. Spearman rho correlations were completed to determine variables that correlated best with current teaching behavior. Multinomial logistical regression was conducted to determine if the belief variables significantly predicted dietitians teaching behavior. Binary logistic regression was used to determine which independent variable was the better predictor of whether dietitians currently taught. Controlling for age, income, education, and gender, the multinomial logistical regression was significant. Perceived behavioral control was the best predictor of whether a dietitian currently taught fresh vegetable food safety. Factors affecting whether dietitians currently taught were confidence in fresh vegetable food safety knowledge, being socially influenced, and a positive attitude toward the teaching behavior. These results validate the importance of teaching food safety effectively and may be used to create more informed food safety curriculum for dietitians. Copyright © 2011 Elsevier Ltd. All rights reserved.

An appraisal of convergence failures in the application of logistic regression model in published manuscripts.

PubMed

Yusuf, O B; Bamgboye, E A; Afolabi, R F; Shodimu, M A

2014-09-01

Logistic regression model is widely used in health research for description and predictive purposes. Unfortunately, most researchers are sometimes not aware that the underlying principles of the techniques have failed when the algorithm for maximum likelihood does not converge. Young researchers particularly postgraduate students may not know why separation problem whether quasi or complete occurs, how to identify it and how to fix it. This study was designed to critically evaluate convergence issues in articles that employed logistic regression analysis published in an African Journal of Medicine and medical sciences between 2004 and 2013. Problems of quasi or complete separation were described and were illustrated with the National Demographic and Health Survey dataset. A critical evaluation of articles that employed logistic regression was conducted. A total of 581 articles was reviewed, of which 40 (6.9%) used binary logistic regression. Twenty-four (60.0%) stated the use of logistic regression model in the methodology while none of the articles assessed model fit. Only 3 (12.5%) properly described the procedures. Of the 40 that used the logistic regression model, the problem of convergence occurred in 6 (15.0%) of the articles. Logistic regression tends to be poorly reported in studies published between 2004 and 2013. Our findings showed that the procedure may not be well understood by researchers since very few described the process in their reports and may be totally unaware of the problem of convergence or how to deal with it.

Risk of Recurrence in Operated Parasagittal Meningiomas: A Logistic Binary Regression Model.

PubMed

Escribano Mesa, José Alberto; Alonso Morillejo, Enrique; Parrón Carreño, Tesifón; Huete Allut, Antonio; Narro Donate, José María; Méndez Román, Paddy; Contreras Jiménez, Ascensión; Pedrero García, Francisco; Masegosa González, José

2018-02-01

Parasagittal meningiomas arise from the arachnoid cells of the angle formed between the superior sagittal sinus (SSS) and the brain convexity. In this retrospective study, we focused on factors that predict early recurrence and recurrence times. We reviewed 125 patients with parasagittal meningiomas operated from 1985 to 2014. We studied the following variables: age, sex, location, laterality, histology, surgeons, invasion of the SSS, Simpson removal grade, follow-up time, angiography, embolization, radiotherapy, recurrence and recurrence time, reoperation, neurologic deficit, degree of dependency, and patient status at the end of follow-up. Patients ranged in age from 26 to 81 years (mean 57.86 years; median 60 years). There were 44 men (35.2%) and 81 women (64.8%). There were 57 patients with neurologic deficits (45.2%). The most common presenting symptom was motor deficit. World Health Organization grade I tumors were identified in 104 patients (84.6%), and the majority were the meningothelial type. Recurrence was detected in 34 cases. Time of recurrence was 9 to 336 months (mean: 84.4 months; median: 79.5 months). Male sex was identified as an independent risk for recurrence with relative risk 2.7 (95% confidence interval 1.21-6.15), P = 0.014. Kaplan-Meier curves for recurrence had statistically significant differences depending on sex, age, histologic type, and World Health Organization histologic grade. A binary logistic regression was made with the Hosmer-Lemeshow test with P > 0.05; sex, tumor size, and histologic type were used in this model. Male sex is an independent risk factor for recurrence that, associated with other factors such tumor size and histologic type, explains 74.5% of all cases in a binary regression model. Copyright © 2017 Elsevier Inc. All rights reserved.

Diagnostic accuracy of serum antibodies to human papillomavirus type 16 early antigens in the detection of human papillomavirus-related oropharyngeal cancer.

PubMed

Dahlstrom, Kristina R; Anderson, Karen S; Field, Matthew S; Chowell, Diego; Ning, Jing; Li, Nan; Wei, Qingyi; Li, Guojun; Sturgis, Erich M

2017-12-15

Because of the current epidemic of human papillomavirus (HPV)-related oropharyngeal cancer (OPC), a screening strategy is urgently needed. The presence of serum antibodies to HPV-16 early (E) antigens is associated with an increased risk for OPC. The purpose of this study was to evaluate the diagnostic accuracy of antibodies to a panel of HPV-16 E antigens in screening for OPC. This case-control study included 378 patients with OPC, 153 patients with nonoropharyngeal head and neck cancer (non-OPC), and 782 healthy control subjects. The tumor HPV status was determined with p16 immunohistochemistry and HPV in situ hybridization. HPV-16 E antibody levels in serum were identified with an enzyme-linked immunosorbent assay. A trained binary logistic regression model based on the combination of all E antigens was predefined and applied to the data set. The sensitivity and specificity of the assay for distinguishing HPV-related OPC from controls were calculated. Logistic regression analysis was used to calculate odds ratios with 95% confidence intervals for the association of head and neck cancer with the antibody status. Of the 378 patients with OPC, 348 had p16-positive OPC. HPV-16 E antibody levels were significantly higher among patients with p16-positive OPC but not among patients with non-OPC or among controls. Serology showed high sensitivity and specificity for HPV-related OPC (binary classifier: 83% sensitivity and 99% specificity for p16-positive OPC). A trained binary classification algorithm that incorporates information about multiple E antibodies has high sensitivity and specificity and may be advantageous for risk stratification in future screening trials. Cancer 2017;123:4886-94. © 2017 American Cancer Society. © 2017 American Cancer Society.

Team versus individual sport participation as a modifying factor in the development of post-concussion syndrome after first concussion: A pilot study.

PubMed

Jeckell, Aaron S; Brett, Benjamin L; Totten, Douglas J; Solomon, Gary S

2018-01-19

Identification of modifying factors that influence the development of post-concussion syndrome (PCS) following sport-related concussion (SRC) has drawn considerable interest. In this pilot study, we investigate the effect of team vs. individual sport participation on the development of PCS in a sample of 136 high school and college student-athletes. Controlling for several confounding variables, we employed a binary logistic regression and chi-squared test. Results of this pilot study indicate that participation in team versus individual sport is not a significant factor in the development of PCS. The identification of other forms of protective mechanisms is discussed.

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

ERIC Educational Resources Information Center

Zewude, Bereket Tessema; Ashine, Kidus Meskele

2016-01-01

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

The Impact of Additional Weekdays of Active Commuting to School on Children Achieving a Criterion of 300+ Minutes of Moderate-to-Vigorous Physical Activity

ERIC Educational Resources Information Center

Daly-Smith, Andy J. W.; McKenna, Jim; Radley, Duncan; Long, Jonathan

2011-01-01

Objective: To investigate the value of additional days of active commuting for meeting a criterion of 300+ minutes of moderate-to-vigorous physical activity (MVPA; 60+ mins/day x 5) during the school week. Methods: Based on seven-day diaries supported by teachers, binary logistic regression analyses were used to predict achievement of MVPA…

Social Impact of Stigma Regarding Tuberculosis Hindering Adherence to Treatment: A Cross Sectional Study Involving Tuberculosis Patients in Rajshahi City, Bangladesh.

PubMed

Chowdhury, Md Rocky Khan; Rahman, Md Shafiur; Mondal, Md Nazrul Islam; Sayem, Abu; Billah, Baki

2015-01-01

Stigma, considered a social disease, is more apparent in developing societies which are driven by various social affairs, and influences adherence to treatment. The aim of the present study was to examine levels of social stigma related to tuberculosis (TB) in sociodemographic context and identify the effects of sociodemographic factors on stigma. The study sample consisted of 372 TB patients. Data were collected using stratified sampling with simple random sampling techniques. T tests, chi-square tests, and binary logistic regression analysis were performed to examine correlations between stigma and sociodemographic variables. Approximately 85.9% of patients had experienced stigma. The most frequent indicator of the stigma experienced by patients involved problems taking part in social programs (79.5%). Mean levels of stigma were significantly higher in women (55.5%), illiterate individuals (60.8%), and villagers (60.8%) relative to those of other groups. Chi-square tests revealed that education, monthly family income, and type of patient (pulmonary and extrapulmonary) were significantly associated with stigma. Binary logistic regression analysis demonstrated that stigma was influenced by sex, education, and type of patient. Stigma is one of the most important barriers to treatment adherence. Therefore, in interventions that aim to reduce stigma, strong collaboration between various institutions is essential.

Propensity score matching of the gymnastics for diabetes mellitus using logistic regression

NASA Astrophysics Data System (ADS)

Otok, Bambang Widjanarko; Aisyah, Amalia; Purhadi, Andari, Shofi

2017-12-01

Diabetes Mellitus (DM) is a group of metabolic diseases with characteristics shows an abnormal blood glucose level occurring due to pancreatic insulin deficiency, decreased insulin effectiveness or both. The report from the ministry of health shows that DMs prevalence data of East Java province is 2.1%, while the DMs prevalence of Indonesia is only 1,5%. Given the high cases of DM in East Java, it needs the preventive action to control factors causing the complication of DM. This study aims to determine the combination factors causing the complication of DM to reduce the bias by confounding variables using Propensity Score Matching (PSM) with the method of propensity score estimation is binary logistic regression. The data used in this study is the medical record from As-Shafa clinic consisting of 6 covariates and health complication as response variable. The result of PSM analysis showed that there are 22 of 126 DMs patients attending gymnastics paired with patients who didnt attend to diabetes gymnastics. The Average Treatment of Treated (ATT) estimation results showed that the more patients who didnt attend to gymnastics, the more likely the risk for the patients having DMs complications.

Constrained binary classification using ensemble learning: an application to cost-efficient targeted PrEP strategies.

PubMed

Zheng, Wenjing; Balzer, Laura; van der Laan, Mark; Petersen, Maya

2018-01-30

Binary classification problems are ubiquitous in health and social sciences. In many cases, one wishes to balance two competing optimality considerations for a binary classifier. For instance, in resource-limited settings, an human immunodeficiency virus prevention program based on offering pre-exposure prophylaxis (PrEP) to select high-risk individuals must balance the sensitivity of the binary classifier in detecting future seroconverters (and hence offering them PrEP regimens) with the total number of PrEP regimens that is financially and logistically feasible for the program. In this article, we consider a general class of constrained binary classification problems wherein the objective function and the constraint are both monotonic with respect to a threshold. These include the minimization of the rate of positive predictions subject to a minimum sensitivity, the maximization of sensitivity subject to a maximum rate of positive predictions, and the Neyman-Pearson paradigm, which minimizes the type II error subject to an upper bound on the type I error. We propose an ensemble approach to these binary classification problems based on the Super Learner methodology. This approach linearly combines a user-supplied library of scoring algorithms, with combination weights and a discriminating threshold chosen to minimize the constrained optimality criterion. We then illustrate the application of the proposed classifier to develop an individualized PrEP targeting strategy in a resource-limited setting, with the goal of minimizing the number of PrEP offerings while achieving a minimum required sensitivity. This proof of concept data analysis uses baseline data from the ongoing Sustainable East Africa Research in Community Health study. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Stochastic model search with binary outcomes for genome-wide association studies.

PubMed

Russu, Alberto; Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-06-01

The spread of case-control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model.

Affordable Care Act Qualified Health Plan Coverage: Association With Improved HIV Viral Suppression for AIDS Drug Assistance Program Clients in a Medicaid Nonexpansion State

PubMed Central

McManus, Kathleen A.; Rhodes, Anne; Bailey, Steven; Yerkes, Lauren; Engelhard, Carolyn L.; Ingersoll, Karen S.; Stukenborg, George J.; Dillingham, Rebecca

2016-01-01

Background. With the Patient Protection and Affordable Care Act, many state AIDS Drug Assistance Programs (ADAPs) shifted their healthcare delivery model from direct medication provision to purchasing qualified health plans (QHPs). The objective of this study was to characterize the demographic and healthcare delivery factors associated with Virginia ADAP clients' QHP enrollment and to assess the relationship between QHP coverage and human immunodeficiency virus (HIV) viral suppression. Methods. The cohort included persons living with HIV who were enrolled in the Virginia ADAP (n = 3933). Data were collected from 1 January 2013 through 31 December 2014. Multivariable binary logistic regression was conducted to assess for associations with QHP enrollment and between QHP coverage and viral load (VL) suppression. Results. In the cohort, 47.1% enrolled in QHPs, and enrollment varied significantly based on demographic and healthcare delivery factors. In multivariable binary logistic regression, controlling for time, age, sex, race/ethnicity, and region, factors significantly associated with achieving HIV viral suppression included QHP coverage (adjusted odds ratio, 1.346; 95% confidence interval, 1.041–1.740; P = .02), an initially undetectable VL (2.809; 2.174–3.636; P < .001), HIV rather than AIDS disease status (1.377; 1.049–1.808; P = .02), and HIV clinic (P < .001). Conclusions. QHP coverage was associated with viral suppression, an essential outcome for individuals and for public health. Promoting QHP coverage in clinics that provide care to persons living with HIV may offer a new opportunity to increase rates of viral suppression. PMID:27143661

Sleep quality and motor vehicle crashes in adolescents.

PubMed

Pizza, Fabio; Contardi, Sara; Antognini, Alessandro Baldi; Zagoraiou, Maroussa; Borrotti, Matteo; Mostacci, Barbara; Mondini, Susanna; Cirignotta, Fabio

2010-02-15

Sleep-related complaints are common in adolescents, but their impact on the rate of motor vehicle crashes accidents is poorly known. We studied subjective sleep quality, driving habits, and self-reported car crashes in high-school adolescents. Self-administered questionnaires (with items exploring driving habits) were distributed to 339 students who had a driver's license and attended 1 of 7 high schools in Bologna, Italy. Statistical analysis were performed to describe lifestyle habits, sleep quality, sleepiness, and their relationship with the binary dependent variable (presence or absence of car crashes) to identify the factors significantly affecting the probability of car crashes in a multivariate binary logistic regression model. Nineteen percent of the sample reported bad sleep, 64% complained of daytime sleepiness, and 40% reported sleepiness while driving. Eighty students (24%), 76% of which were males, reported that they had already crashed at least once, and 15% considered sleepiness to have been the main cause of their crash. As compared with adolescents who had not had a crash, those who had at least 1 previous crash reported that they more frequently used to drive (79% vs 62%), drove at night (25% vs 9%), drove while sleepy (56% vs 35%), had bad sleep (29% vs 16%), and used stimulants such as caffeinated soft drinks (32% vs 19%), tobacco (54% vs 27%), and drugs (21% vs 7%). The logistic procedure established a significant predictive role of male sex (p < 0.0001; odds ratio = 3.3), tobacco use (p < 0.0001; odds ratio = 3.2), sleepiness while driving (p = 0.010; odds ratio = 2.1), and bad sleep (p = 0.047; odds ratio = 1.9) for the crash risk. Our results confirm the high prevalence of sleep-related complaints among adolescents and highlight their independent role on self-reported crash risk.

Multidetector CT features of pulmonary focal ground-glass opacity: differences between benign and malignant

PubMed Central

Fan, L; Liu, S-Y; Li, Q-C; Yu, H; Xiao, X-S

2012-01-01

Objective To evaluate different features between benign and malignant pulmonary focal ground-glass opacity (fGGO) on multidetector CT (MDCT). Methods 82 pathologically or clinically confirmed fGGOs were retrospectively analysed with regard to demographic data, lesion size and location, attenuation value and MDCT features including shape, margin, interface, internal characteristics and adjacent structure. Differences between benign and malignant fGGOs were analysed using a χ2 test, Fisher's exact test or Mann–Whitney U-test. Morphological characteristics were analysed by binary logistic regression analysis to estimate the likelihood of malignancy. Results There were 21 benign and 61 malignant lesions. No statistical differences were found between benign and malignant fGGOs in terms of demographic data, size, location and attenuation value. The frequency of lobulation (p=0.000), spiculation (p=0.008), spine-like process (p=0.004), well-defined but coarse interface (p=0.000), bronchus cut-off (p=0.003), other air-containing space (p=0.000), pleural indentation (p=0.000) and vascular convergence (p=0.006) was significantly higher in malignant fGGOs than that in benign fGGOs. Binary logistic regression analysis showed that lobulation, interface and pleural indentation were important indicators for malignant diagnosis of fGGO, with the corresponding odds ratios of 8.122, 3.139 and 9.076, respectively. In addition, a well-defined but coarse interface was the most important indicator of malignancy among all interface types. With all three important indicators considered, the diagnostic sensitivity, specificity and accuracy were 93.4%, 66.7% and 86.6%, respectively. Conclusion An fGGO with lobulation, a well-defined but coarse interface and pleural indentation gives a greater than average likelihood of being malignant. PMID:22128130

Assessment of renal function and electrolytes in patients with thyroid dysfunction in Addis Ababa, Ethiopia: a cross sectional study.

PubMed

Abebe, Nardos; Kebede, Tedla; Wolde, Mistire

2016-01-01

Studies demonstrated that abnormal thyroid functions may result in decreased or increased kidney size, kidney weight, and affect renal functions. In this regard, studies on the association of abnormal thyroid functions and renal function tests are scarcely found in Ethiopia. To assess renal function and electrolytes in patients with thyroid dysfunction, in Addis Ababa, Ethiopia. Cross sectional study was conducted from March 21/2015-May 27/2015 at Arsho Advanced Medical Laboratory. During the study period, 71 patients with thyroid dysfunction were eligible, and socio demographic data collected by structured questionnaire. Then blood sample was collected for thyroid function tests, renal function and blood electrolyte analysis. The collected data was analyzed by SPSS version 20. ANOVA and binary logistic regression were employed to evaluate the mean deference and associations of thyroid hormone with renal function and electrolyte balances. Among the renal function tests, serum uric acid, and creatinine mean values were significantly decreased in hyperthyroid patients; whereas, eGFR mean value was significantly increased in hyperthyroid study patients (P<0.05). Meanwhile, from the electrolyte measurements made, only the mean serum sodium value was significantly increased in hyperthyroid study participants. Binary logistic regression analysis on the association of thyroid dysfunction with electrolyte balance and renal function tests indicated that serum sodium, creatinine, eGFR values and hyperthyroidism have a statistical significant association at AOR 95% CI of 0.141(0.033-0.593, P=0.008); 16.236(3.481-75.739, P=0.001), and 13.797(3.261-58.67, P=0.001) respectively. The current study reveals, thyroid abnormalities may lead to renal function alterations and also may disturb electrolyte balance. Knowledge of this significant association has worthwhile value for clinicians, to manage their patients' optimally.

Clinical outcomes and predictors of response to photodynamic therapy in symptomatic circumscribed choroidal hemangioma: A retrospective case series

PubMed Central

Ho, Yeen-Fey; Chao, Anne; Chen, Kuan-Jen; Wang, Nan-Kai; Liu, Laura; Chen, Yen-Po; Hwang, Yih-Shiou; Wu, Wei-Chi; Lai, Chi-Chun; Chen, Tun-Lu

2018-01-01

Background To investigate the treatment outcomes and predictors of response to photodynamic therapy (PDT) in patients with symptomatic circumscribed hemangioma (CCH). Methods This retrospective case series examined 20 patients with symptomatic CCH (10 submacular CCHs and10 juxtapapillary CCHs) who underwent standard PDT (wavelength: 662 nm; light dose: 50J/cm2; exposure time: 83 sec) with verteporfin (6mg/m2), either as monotherapy (n = 9) or in association with other treatments (n = 11), of which 7 received intravitreal injections (IVI) of anti-vascular endothelial growth factor (anti-VEGF). A post-PDT improvement of at least two lines in best-corrected visual acuity (BCVA) was the primary outcome measure. Predictors of response were investigated with binary logistic regression analysis. Results Seventeen (85%) patients received one PDT session, and three patients (15%) underwent PDT at least twice. Ten patients (50%) achieved the primary outcome of a post-PDT BCVA improvement of at least two lines. Macular atrophy and recalcitrant cystoid macular edema in 2 patients. Binary logistic regression analysis revealed that younger age (< 50 years) (P = 0.033), pre-PDT BCVA of ≧20/200 (P = 0.013), exudative retinal detachment resolved within one month after PDT (P = 0.007), and a thinner post-PDT tumor thickness (P = 0.015) were associated with the achievement of a post-PDT BCVA improvement. Additional treatments to PDT including IVI anti-VEGF did not appear to improve visual and anatomical outcomes. Conclusions Symptomatic CCHs respond generally well to PDT. Patients with younger age (< 50 years), pretreatment BCVA≥ 20/200, and thinner foveal edema are most likely to benefit from this approach. PMID:29851977

Exposure to Tobacco Advertising and Promotion among School Children Aged 13-15 in Vietnam - an Overview from GYTS 2014.

PubMed

Long, Tran Khanh; Son, Phung Xuan; Giang, Kim Bao; Hai, Phan Thi; Huyen, Doan Thi Thu; Khue, Luong Ngoc; Nga, Pham Thi Quynh; Lam, Nguyen Tuan; Minh, Hoang Van; Huong, Le Thi Thanh

2016-01-01

Evidence shows that tobacco advertising and promotion activities may increase tobacco consumption and usage, especially in youth. Despite the regulation on prohibiting advertisement of any tobacco product, tobacco advertisement and promotion activities are still common in Vietnam. This article presents current exposure to tobacco advertising and promotion (TAP) among school children aged 13 to 15 years in Vietnam in 2014 and potential influencing factors. Data from the Global Youth Tobacco Survey 2014 in Vietnam covering 3,430 school aged children were used. Both descriptive and analytical statistics were carried out with Stata 13 statistical software. Binary logistic regression was applied to explain the exposure to TAP among youth and examine relationships with individual factors. A significance level of p<0.05 and sampling weights were used in all of the computations. In the past 30 days, 48.6% of the students experienced exposure to at least 1 type of tobacco advertising or promotion. Wearing or otherwise using products related to tobacco was the most exposure TAP type reported by students (22.3%). The internet (22.1), points of sales (19.2) and social events (11.5) were three places that students aged 13-15 frequently were exposed to TAP. Binary logistic results showed that gender (female vs male) (OR = 0.61, 95%CI: 0.52 - 0.71), susceptibility to smoking (OR = 2.12, 95%CI: 1.53 - 2.92), closest friends' smoked (OR = 1.43, 95%CI: 1.2 - 1.7) and parents smoking status (OR = 2.83, 95%CI: 1.6 - 5.01) were significantly associated with TAP exposure among school-aged children. The research findings should contribute to effective implementation of measures for preventing and controlling tobacco use among students aged 13-15 in Viet Nam.

Binary Logistic Regression Versus Boosted Regression Trees in Assessing Landslide Susceptibility for Multiple-Occurring Regional Landslide Events: Application to the 2009 Storm Event in Messina (Sicily, southern Italy).

NASA Astrophysics Data System (ADS)

Lombardo, L.; Cama, M.; Maerker, M.; Parisi, L.; Rotigliano, E.

2014-12-01

This study aims at comparing the performances of Binary Logistic Regression (BLR) and Boosted Regression Trees (BRT) methods in assessing landslide susceptibility for multiple-occurrence regional landslide events within the Mediterranean region. A test area was selected in the north-eastern sector of Sicily (southern Italy), corresponding to the catchments of the Briga and the Giampilieri streams both stretching for few kilometres from the Peloritan ridge (eastern Sicily, Italy) to the Ionian sea. This area was struck on the 1st October 2009 by an extreme climatic event resulting in thousands of rapid shallow landslides, mainly of debris flows and debris avalanches types involving the weathered layer of a low to high grade metamorphic bedrock. Exploiting the same set of predictors and the 2009 landslide archive, BLR- and BRT-based susceptibility models were obtained for the two catchments separately, adopting a random partition (RP) technique for validation; besides, the models trained in one of the two catchments (Briga) were tested in predicting the landslide distribution in the other (Giampilieri), adopting a spatial partition (SP) based validation procedure. All the validation procedures were based on multi-folds tests so to evaluate and compare the reliability of the fitting, the prediction skill, the coherence in the predictor selection and the precision of the susceptibility estimates. All the obtained models for the two methods produced very high predictive performances, with a general congruence between BLR and BRT in the predictor importance. In particular, the research highlighted that BRT-models reached a higher prediction performance with respect to BLR-models, for RP based modelling, whilst for the SP-based models the difference in predictive skills between the two methods dropped drastically, converging to an analogous excellent performance. However, when looking at the precision of the probability estimates, BLR demonstrated to produce more robust models in terms of selected predictors and coefficients, as well as of dispersion of the estimated probabilities around the mean value for each mapped pixel. The difference in the behaviour could be interpreted as the result of overfitting effects, which heavily affect decision tree classification more than logistic regression techniques.

ON MODEL SELECTION STRATEGIES TO IDENTIFY GENES UNDERLYING BINARY TRAITS USING GENOME-WIDE ASSOCIATION DATA.

PubMed

Wu, Zheyang; Zhao, Hongyu

2012-01-01

For more fruitful discoveries of genetic variants associated with diseases in genome-wide association studies, it is important to know whether joint analysis of multiple markers is more powerful than the commonly used single-marker analysis, especially in the presence of gene-gene interactions. This article provides a statistical framework to rigorously address this question through analytical power calculations for common model search strategies to detect binary trait loci: marginal search, exhaustive search, forward search, and two-stage screening search. Our approach incorporates linkage disequilibrium, random genotypes, and correlations among score test statistics of logistic regressions. We derive analytical results under two power definitions: the power of finding all the associated markers and the power of finding at least one associated marker. We also consider two types of error controls: the discovery number control and the Bonferroni type I error rate control. After demonstrating the accuracy of our analytical results by simulations, we apply them to consider a broad genetic model space to investigate the relative performances of different model search strategies. Our analytical study provides rapid computation as well as insights into the statistical mechanism of capturing genetic signals under different genetic models including gene-gene interactions. Even though we focus on genetic association analysis, our results on the power of model selection procedures are clearly very general and applicable to other studies.

ON MODEL SELECTION STRATEGIES TO IDENTIFY GENES UNDERLYING BINARY TRAITS USING GENOME-WIDE ASSOCIATION DATA

PubMed Central

Wu, Zheyang; Zhao, Hongyu

2013-01-01

For more fruitful discoveries of genetic variants associated with diseases in genome-wide association studies, it is important to know whether joint analysis of multiple markers is more powerful than the commonly used single-marker analysis, especially in the presence of gene-gene interactions. This article provides a statistical framework to rigorously address this question through analytical power calculations for common model search strategies to detect binary trait loci: marginal search, exhaustive search, forward search, and two-stage screening search. Our approach incorporates linkage disequilibrium, random genotypes, and correlations among score test statistics of logistic regressions. We derive analytical results under two power definitions: the power of finding all the associated markers and the power of finding at least one associated marker. We also consider two types of error controls: the discovery number control and the Bonferroni type I error rate control. After demonstrating the accuracy of our analytical results by simulations, we apply them to consider a broad genetic model space to investigate the relative performances of different model search strategies. Our analytical study provides rapid computation as well as insights into the statistical mechanism of capturing genetic signals under different genetic models including gene-gene interactions. Even though we focus on genetic association analysis, our results on the power of model selection procedures are clearly very general and applicable to other studies. PMID:23956610

Using Logistic Regression To Predict the Probability of Debris Flows Occurring in Areas Recently Burned By Wildland Fires

USGS Publications Warehouse

Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.

2003-01-01

Logistic regression was used to predict the probability of debris flows occurring in areas recently burned by wildland fires. Multiple logistic regression is conceptually similar to multiple linear regression because statistical relations between one dependent variable and several independent variables are evaluated. In logistic regression, however, the dependent variable is transformed to a binary variable (debris flow did or did not occur), and the actual probability of the debris flow occurring is statistically modeled. Data from 399 basins located within 15 wildland fires that burned during 2000-2002 in Colorado, Idaho, Montana, and New Mexico were evaluated. More than 35 independent variables describing the burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows were delineated from National Elevation Data using a Geographic Information System (GIS). (2) Data describing the burn severity, geology, land surface gradient, rainfall, and soil properties were determined for each basin. These data were then downloaded to a statistics software package for analysis using logistic regression. (3) Relations between the occurrence/non-occurrence of debris flows and burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated and several preliminary multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combination produced the most effective model. The multivariate model that best predicted the occurrence of debris flows was selected. (4) The multivariate logistic regression model was entered into a GIS, and a map showing the probability of debris flows was constructed. The most effective model incorporates the percentage of each basin with slope greater than 30 percent, percentage of land burned at medium and high burn severity in each basin, particle size sorting, average storm intensity (millimeters per hour), soil organic matter content, soil permeability, and soil drainage. The results of this study demonstrate that logistic regression is a valuable tool for predicting the probability of debris flows occurring in recently-burned landscapes.

On Bayesian Rules for Selecting 3PL Binary Items for Criterion-Referenced Interpretations and Creating Booklets for Bookmark Standard Setting.

ERIC Educational Resources Information Center

Huynh, Huynh

By noting that a Rasch or two parameter logistic (2PL) item belongs to the exponential family of random variables and that the probability density function (pdf) of the correct response (X=1) and the incorrect response (X=0) are symmetric with respect to the vertical line at the item location, it is shown that the conjugate prior for ability is…

The cross-validated AUC for MCP-logistic regression with high-dimensional data.

PubMed

Jiang, Dingfeng; Huang, Jian; Zhang, Ying

2013-10-01

We propose a cross-validated area under the receiving operator characteristic (ROC) curve (CV-AUC) criterion for tuning parameter selection for penalized methods in sparse, high-dimensional logistic regression models. We use this criterion in combination with the minimax concave penalty (MCP) method for variable selection. The CV-AUC criterion is specifically designed for optimizing the classification performance for binary outcome data. To implement the proposed approach, we derive an efficient coordinate descent algorithm to compute the MCP-logistic regression solution surface. Simulation studies are conducted to evaluate the finite sample performance of the proposed method and its comparison with the existing methods including the Akaike information criterion (AIC), Bayesian information criterion (BIC) or Extended BIC (EBIC). The model selected based on the CV-AUC criterion tends to have a larger predictive AUC and smaller classification error than those with tuning parameters selected using the AIC, BIC or EBIC. We illustrate the application of the MCP-logistic regression with the CV-AUC criterion on three microarray datasets from the studies that attempt to identify genes related to cancers. Our simulation studies and data examples demonstrate that the CV-AUC is an attractive method for tuning parameter selection for penalized methods in high-dimensional logistic regression models.

Missing Data in Alcohol Clinical Trials with Binary Outcomes.

PubMed

Hallgren, Kevin A; Witkiewitz, Katie; Kranzler, Henry R; Falk, Daniel E; Litten, Raye Z; O'Malley, Stephanie S; Anton, Raymond F

2016-07-01

Missing data are common in alcohol clinical trials for both continuous and binary end points. Approaches to handle missing data have been explored for continuous outcomes, yet no studies have compared missing data approaches for binary outcomes (e.g., abstinence, no heavy drinking days). This study compares approaches to modeling binary outcomes with missing data in the COMBINE study. We included participants in the COMBINE study who had complete drinking data during treatment and who were assigned to active medication or placebo conditions (N = 1,146). Using simulation methods, missing data were introduced under common scenarios with varying sample sizes and amounts of missing data. Logistic regression was used to estimate the effect of naltrexone (vs. placebo) in predicting any drinking and any heavy drinking outcomes at the end of treatment using 4 analytic approaches: complete case analysis (CCA), last observation carried forward (LOCF), the worst case scenario (WCS) of missing equals any drinking or heavy drinking, and multiple imputation (MI). In separate analyses, these approaches were compared when drinking data were manually deleted for those participants who discontinued treatment but continued to provide drinking data. WCS produced the greatest amount of bias in treatment effect estimates. MI usually yielded less biased estimates than WCS and CCA in the simulated data and performed considerably better than LOCF when estimating treatment effects among individuals who discontinued treatment. Missing data can introduce bias in treatment effect estimates in alcohol clinical trials. Researchers should utilize modern missing data methods, including MI, and avoid WCS and CCA when analyzing binary alcohol clinical trial outcomes. Copyright © 2016 by the Research Society on Alcoholism.

Deletion Diagnostics for Alternating Logistic Regressions

PubMed Central

Preisser, John S.; By, Kunthel; Perin, Jamie; Qaqish, Bahjat F.

2013-01-01

Deletion diagnostics are introduced for the regression analysis of clustered binary outcomes estimated with alternating logistic regressions, an implementation of generalized estimating equations (GEE) that estimates regression coefficients in a marginal mean model and in a model for the intracluster association given by the log odds ratio. The diagnostics are developed within an estimating equations framework that recasts the estimating functions for association parameters based upon conditional residuals into equivalent functions based upon marginal residuals. Extensions of earlier work on GEE diagnostics follow directly, including computational formulae for one-step deletion diagnostics that measure the influence of a cluster of observations on the estimated regression parameters and on the overall marginal mean or association model fit. The diagnostic formulae are evaluated with simulations studies and with an application concerning an assessment of factors associated with health maintenance visits in primary care medical practices. The application and the simulations demonstrate that the proposed cluster-deletion diagnostics for alternating logistic regressions are good approximations of their exact fully iterated counterparts. PMID:22777960

An Experimental Realization of a Chaos-Based Secure Communication Using Arduino Microcontrollers.

PubMed

Zapateiro De la Hoz, Mauricio; Acho, Leonardo; Vidal, Yolanda

2015-01-01

Security and secrecy are some of the important concerns in the communications world. In the last years, several encryption techniques have been proposed in order to improve the secrecy of the information transmitted. Chaos-based encryption techniques are being widely studied as part of the problem because of the highly unpredictable and random-look nature of the chaotic signals. In this paper we propose a digital-based communication system that uses the logistic map which is a mathematically simple model that is chaotic under certain conditions. The input message signal is modulated using a simple Delta modulator and encrypted using a logistic map. The key signal is also encrypted using the same logistic map with different initial conditions. In the receiver side, the binary-coded message is decrypted using the encrypted key signal that is sent through one of the communication channels. The proposed scheme is experimentally tested using Arduino shields which are simple yet powerful development kits that allows for the implementation of the communication system for testing purposes.

Impact of low vision on employment.

PubMed

Mojon-Azzi, Stefania M; Sousa-Poza, Alfonso; Mojon, Daniel S

2010-01-01

We investigated the influence of self-reported corrected eyesight on several variables describing the perception by employees and self-employed persons of their employment. Our study was based on data from the Survey of Health, Ageing and Retirement in Europe (SHARE). SHARE is a multidisciplinary, cross-national database of microdata on health, socioeconomic status, social and family networks, collected on 31,115 individuals in 11 European countries and in Israel. With the help of ordered logistic regressions and binary logistic regressions, we analyzed the influence of perceived visual impairment--corrected by 19 covariates capturing socioeconomic and health-related factors--on 10 variables describing the respondents' employment situation. Based on data covering 10,340 working individuals, the results of the logistic and ordered regressions indicate that respondents with lower levels of self-reported general eyesight were significantly less satisfied with their jobs, felt they had less freedom to decide, less opportunity to develop new skills, less support in difficult situations, less recognition for their work, and an inadequate salary. Respondents with a lower eyesight level more frequently reported that they feared their health might limit their ability to work before regular retirement age and more often indicated that they were seeking early retirement. Analysis of this dataset from 12 countries demonstrates the strong impact of self-reported visual impairment on individual employment, and therefore on job satisfaction, productivity, and well-being. Copyright © 2010 S. Karger AG, Basel.

Three quantitative approaches to the diagnosis of abdominal pain in children: practical applications of decision theory.

PubMed

Klein, M D; Rabbani, A B; Rood, K D; Durham, T; Rosenberg, N M; Bahr, M J; Thomas, R L; Langenburg, S E; Kuhns, L R

2001-09-01

The authors compared 3 quantitative methods for assisting clinicians in the differential diagnosis of abdominal pain in children, where the most common important endpoint is whether the patient has appendicitis. Pretest probability in different age and sex groups were determined to perform Bayesian analysis, binary logistic regression was used to determine which variables were statistically significantly likely to contribute to a diagnosis, and recursive partitioning was used to build decision trees with quantitative endpoints. The records of all children (1,208) seen at a large urban emergency department (ED) with a chief complaint of abdominal pain were immediately reviewed retrospectively (24 to 72 hours after the encounter). Attempts were made to contact all the patients' families to determine an accurate final diagnosis. A total of 1,008 (83%) families were contacted. Data were analyzed by calculation of the posttest probability, recursive partitioning, and binary logistic regression. In all groups the most common diagnosis was abdominal pain (ICD-9 Code 789). After this, however, the order of the most common final diagnoses for abdominal pain varied significantly. The entire group had a pretest probability of appendicitis of 0.06. This varied with age and sex from 0.02 in boys 2 to 5 years old to 0.16 in boys older than 12 years. In boys age 5 to 12, recursive partitioning and binary logistic regression agreed on guarding and anorexia as important variables. Guarding and tenderness were important in girls age 5 to 12. In boys age greater than 12, both agreed on guarding and anorexia. Using sensitivities and specificities from the literature, computed tomography improved the posttest probability for the group from.06 to.33; ultrasound improved it from.06 to.48; and barium enema improved it from.06 to.58. Knowing the pretest probabilities in a specific population allows the physician to evaluate the likely diagnoses first. Other quantitative methods can help judge how much importance a certain criterion should have in the decision making and how much a particular test is likely to influence the probability of a correct diagnosis. It now should be possible to make these sophisticated quantitative methods readily available to clinicians via the computer. Copyright 2001 by W.B. Saunders Company.

The role of middle-class status in payday loan borrowing: a multivariate approach.

PubMed

Lim, Younghee; Bickham, Trey; Broussard, Julia; Dinecola, Cassie M; Gregory, Alethia; Weber, Brittany E

2014-10-01

Payday loans refer to small-dollar, high-interest, short-term loans usually extended to lower-income consumers. Despite much research to the contrary, the payday loan industry asserts that it primarily serves middle-class Americans. This article discusses the authors' investigation of the industry's claim, by analyzing data from a U.S. bankruptcy court serving a Southern district. Results of the multivariate binary logistic regression analysis showed that, controlling for various sociodemographic and economic variables, two middle-class indicators--home-ownership and annual income at or greater than the median income--are associated with a decreased likelihood of using payday loans. The article concludes with a discussion of the implications of the results for social work practice and advocacy in regard to financial capability, particularly asset development, income maintenance, and payday loan regulation.

Portugal and Angola: similarities and differences in Toxoplasma gondii seroprevalence and risk factors in pregnant women.

PubMed

Lobo, M L; Patrocinio, G; Sevivas, T; DE Sousa, B; Matos, O

2017-01-01

In this study we determined the presence of IgM/IgG antibodies to Toxoplasma gondii in sera of 155 and 300 pregnant women from Lisbon (Portugal) and Luanda (Angola), respectively, and evaluated the potential risk factors associated with this infection. DNA detection was performed by PCR assays targeting T. gondii regions (RE/B1). Overall, 21·9% (10·9% IgG, 10·9% IgG/IgM) of the Lisbon women and 27·3% (23·7%, IgG, 2% IgM, 1·7% IgG/IgM) of the Luanda women had antibodies to T. gondii. Single variable and binary logistic regression analyses were conducted. Based on the latter, contacts with cats (family/friends), and having more than two births were identified as risk factors for Toxoplasma infection in Lisbon women. In Luanda, the risk factors for T. gondii infection suggested by the single variable analysis (outdoor contact with cats and consumption of pasteurized milk/dairy products) were not confirmed by binary logistic regression. This study shows original data from Angola, and updated data from Portugal in the study of infection by T. gondii in pregnant women, indicating that the prevalence of anti-Toxoplasma antibodies is high enough to alert the government health authorities and implement appropriate measures to control this infection.

Depression and incident dementia. An 8-year population-based prospective study.

PubMed

Luppa, Melanie; Luck, Tobias; Ritschel, Franziska; Angermeyer, Matthias C; Villringer, Arno; Riedel-Heller, Steffi G

2013-01-01

The aim of the study was to investigate the impact of depression (categorical diagnosis; major depression, MD) and depressive symptoms (dimensional diagnosis and symptom patterns) on incident dementia in the German general population. Within the Leipzig Longitudinal Study of the Aged (LEILA 75+), a representative sample of 1,265 individuals aged 75 years and older were interviewed every 1.5 years over 8 years (mean observation time 4.3 years; mean number of visits 4.2). Cox proportional hazards and binary logistic regressions were used to estimate the effect of baseline depression and depressive symptoms on incident dementia. The incidence of dementia was 48 per 1,000 person-years (95% confidence interval (CI) 45-51). Depressive symptoms (Hazard ratio HR 1.03, 95% CI 1.01-1.05), and in particular mood-related symptoms (HR 1.08, 95% CI 1.03-1.14), showed a significant impact on the incidence of dementia only in univariate analysis, but not after adjustment for cognitive and functional impairment. MD showed only a significant impact on incidence of dementia in Cox proportional hazards regression, but not in binary logistic regression models. The present study using different diagnostic measures of depression on future dementia found no clear significant associations of depression and incident dementia. Further in-depth investigation would help to understand the nature of depression in the context of incident dementia.

Cerebrovascular risk factors for patients with cerebral watershed infarction: A case-control study based on computed tomography angiography in a population from Southwest China.

PubMed

Dong, Mei-Xue; Hu, Ling; Huang, Yuan-Jun; Xu, Xiao-Min; Liu, Yang; Wei, You-Dong

2017-07-01

To determine cerebrovascular risk factors for patients with cerebral watershed infarction (CWI) from Southwest China.Patients suffering from acute ischemic stroke were categorized into internal CWI (I-CWI), external CWI (E-CWI), or non-CWI (patients without CWI) groups. Clinical data were collected and degrees of steno-occlusion of all cerebral arteries were scored. Arteries associated with the circle of Willis were also assessed. Data were compared using Pearson chi-squared tests for categorical data and 1-way analysis of variance with Bonferroni post hoc tests for continuous data, as appropriate. Multivariate binary logistic regression analysis was performed to determine independent cerebrovascular risk factors for CWI.Compared with non-CWI, I-CWI had higher degrees of steno-occlusion of the ipsilateral middle cerebral artery, ipsilateral carotid artery, and contralateral middle cerebral artery. E-CWI showed no significant differences. All the 3 arteries were independent cerebrovascular risk factors for I-CWI confirmed by multivariate binary logistic regression analysis. I-CWI had higher degrees of steno-occlusion of the ipsilateral middle cerebral artery compared with E-CWI. No significant differences were found among arteries associated with the circle of Willis.The ipsilateral middle cerebral artery, carotid artery, and contralateral middle cerebral artery were independent cerebrovascular risk factors for I-CWI. No cerebrovascular risk factor was identified for E-CWI.

A binary logistic regression model with complex sampling design of unmet need for family planning among all women aged (15-49) in Ethiopia.

PubMed

Workie, Demeke Lakew; Zike, Dereje Tesfaye; Fenta, Haile Mekonnen; Mekonnen, Mulusew Admasu

2017-09-01

Unintended pregnancy related to unmet need is a worldwide problem that affects societies. The main objective of this study was to identify the prevalence and determinants of unmet need for family planning among women aged (15-49) in Ethiopia. The Performance Monitoring and Accountability2020/Ethiopia was conducted in April 2016 at round-4 from 7494 women with two-stage-stratified sampling. Bi-variable and multi-variable binary logistic regression model with complex sampling design was fitted. The prevalence of unmet-need for family planning was 16.2% in Ethiopia. Women between the age range of 15-24 years were 2.266 times more likely to have unmet need family planning compared to above 35 years. Women who were currently married were about 8 times more likely to have unmet need family planning compared to never married women. Women who had no under-five child were 0.125 times less likely to have unmet need family planning compared to those who had more than two-under-5. The key determinants of unmet need family planning in Ethiopia were residence, age, marital-status, education, household members, birth-events and number of under-5 children. Thus the Government of Ethiopia would take immediate steps to address the causes of high unmet need for family planning among women.

A simple measure of cognitive reserve is relevant for cognitive performance in MS patients.

PubMed

Della Corte, Marida; Santangelo, Gabriella; Bisecco, Alvino; Sacco, Rosaria; Siciliano, Mattia; d'Ambrosio, Alessandro; Docimo, Renato; Cuomo, Teresa; Lavorgna, Luigi; Bonavita, Simona; Tedeschi, Gioacchino; Gallo, Antonio

2018-05-04

Cognitive reserve (CR) contributes to preserve cognition despite brain damage. This theory has been applied to multiple sclerosis (MS) to explain the partial relationship between cognition and MRI markers of brain pathology. Our aim was to determine the relationship between two measures of CR and cognition in MS. One hundred and forty-seven MS patients were enrolled. Cognition was assessed using the Rao's Brief Repeatable Battery and the Stroop Test. CR was measured as the vocabulary subtest of the WAIS-R score (VOC) and the number of years of formal education (EDU). Regression analysis included raw score data on each neuropsychological (NP) test as dependent variables and demographic/clinical parameters, VOC, and EDU as independent predictors. A binary logistic regression analysis including clinical/CR parameters as covariates and absence/presence of cognitive deficits as dependent variables was performed too. VOC, but not EDU, was strongly correlated with performances at all ten NP tests. EDU was correlated with executive performances. The binary logistic regression showed that only the Expanded Disability Status Scale (EDSS) and VOC were independently correlated with the presence/absence of CD. The lower the VOC and/or the higher the EDSS, the higher the frequency of CD. In conclusion, our study supports the relevance of CR in subtending cognitive performances and the presence of CD in MS patients.

Binary Trees and Parallel Scheduling Algorithms.

DTIC Science & Technology

1980-09-01

been pro- cessed for p. time units. If a job does not complete by its due time, it is tardy. In a nonpreemptive schedule, job i is scheduled to process...the preemptive schedule obtained by the algorithm of section 2.1.2 also minimizes 5Ti, this problem is easily solved in parallel. When lci is to e...August 1978, pp. 657-661. 14. Horn, W. A., "Some simple scheduling algorithms," Naval Res. Logist . Qur., Vol. 21, pp. 177-185, 1974. i5. Hforowitz, E

Adolescent sexual victimization: a prospective study on risk factors for first time sexual assault.

PubMed

Bramsen, Rikke Holm; Lasgaard, Mathias; Koss, Mary P; Elklit, Ask; Banner, Jytte

2012-09-01

The present study set out to investigate predictors of first time adolescent peer-on-peer sexual victimization (APSV) among 238 female Grade 9 students from 30 schools in Denmark. A prospective research design was utilized to examine the relationship among five potential predictors as measured at baseline and first time APSV during a 6-month period. Data analysis was a binary logistic regression analysis. Number of sexual partners and displaying sexual risk behaviors significantly predicted subsequent first time peer-on-peer sexual victimization, whereas a history of child sexual abuse, early sexual onset and failing to signal sexual boundaries did not. The present study identifies specific risk factors for first time sexual victimization that are potentially changeable. Thus, the results may inform prevention initiatives targeting initial experiences of APSV.

More caregiving, less working: caregiving roles and gender difference.

PubMed

Lee, Yeonjung; Tang, Fengyan

2015-06-01

This study examined the relationship of caregiving roles to labor force participation using the nationally representative data from the Health and Retirement Study. The sample was composed of men and women aged 50 to 61 years (N = 5,119). Caregiving roles included caregiving for spouse, parents, and grandchildren; a summary of three caregiving roles was used to indicate multiple caregiving roles. Bivariate analysis using chi-square and t tests and binary logistic regression models were applied. Results show that women caregivers for parents and/or grandchildren were less likely to be in the labor force than non-caregivers and that caregiving responsibility was not related to labor force participation for the sample of men. Findings have implication for supporting family caregivers, especially women, to balance work and caregiving commitments. © The Author(s) 2013.

Contributions of sociodemographic factors to criminal behavior

PubMed Central

Mundia, Lawrence; Matzin, Rohani; Mahalle, Salwa; Hamid, Malai Hayati; Osman, Ratna Suriani

2016-01-01

We explored the extent to which prisoner sociodemographic variables (age, education, marital status, employment, and whether their parents were married or not) influenced offending in 64 randomly selected Brunei inmates, comprising both sexes. A quantitative field survey design ideal for the type of participants used in a prison context was employed to investigate the problem. Hierarchical multiple regression analysis with backward elimination identified prisoner marital status and age groups as significantly related to offending. Furthermore, hierarchical multinomial logistic regression analysis with backward elimination indicated that prisoners’ age, primary level education, marital status, employment status, and parental marital status as significantly related to stealing offenses with high odds ratios. All 29 nonrecidivists were false negatives and predicted to reoffend upon release. Similarly, all 33 recidivists were projected to reoffend after release. Hierarchical binary logistic regression analysis revealed age groups (24–29 years and 30–35 years), employed prisoner, and primary level education as variables with high likelihood trends for reoffending. The results suggested that prisoner interventions (educational, counseling, and psychotherapy) in Brunei should treat not only antisocial personality, psychopathy, and mental health problems but also sociodemographic factors. The study generated offending patterns, trends, and norms that may inform subsequent investigations on Brunei prisoners. PMID:27382342

Family violence exposure and associated risk factors for child PTSD in a Mexican sample.

PubMed

Erolin, Kara S; Wieling, Elizabeth; Parra, R Elizabeth Aguilar

2014-06-01

This study was undertaken in an effort to help illuminate the deleterious effects of traumatic stress on children and families in Mexico. Rates of exposure to traumatic events, family and community violence, and posttraumatic stress disorder (PTSD) were investigated in 87 school-age children and their mothers. Binary logistic regression analysis was performed to examine potential family and ecological risk factors for the presence of child PTSD. A total of 51 children (58.6%) reported an event that met the DSM-IV A criteria, and 36 children (41.4%; 20 boys and 16 girls) met criteria for full PTSD. Traumatic exposure in this sample was considerable, particularly intense, and chronic as a result of interpersonal violence in the home and community. Results support the need for preventive systemic interventions targeting the individual level, parent-child dyadic level, and the larger cultural and community context. Published by Elsevier Ltd.

Decoding memory features from hippocampal spiking activities using sparse classification models.

PubMed

Dong Song; Hampson, Robert E; Robinson, Brian S; Marmarelis, Vasilis Z; Deadwyler, Sam A; Berger, Theodore W

2016-08-01

To understand how memory information is encoded in the hippocampus, we build classification models to decode memory features from hippocampal CA3 and CA1 spatio-temporal patterns of spikes recorded from epilepsy patients performing a memory-dependent delayed match-to-sample task. The classification model consists of a set of B-spline basis functions for extracting memory features from the spike patterns, and a sparse logistic regression classifier for generating binary categorical output of memory features. Results show that classification models can extract significant amount of memory information with respects to types of memory tasks and categories of sample images used in the task, despite the high level of variability in prediction accuracy due to the small sample size. These results support the hypothesis that memories are encoded in the hippocampal activities and have important implication to the development of hippocampal memory prostheses.

A general equation to obtain multiple cut-off scores on a test from multinomial logistic regression.

PubMed

Bersabé, Rosa; Rivas, Teresa

2010-05-01

The authors derive a general equation to compute multiple cut-offs on a total test score in order to classify individuals into more than two ordinal categories. The equation is derived from the multinomial logistic regression (MLR) model, which is an extension of the binary logistic regression (BLR) model to accommodate polytomous outcome variables. From this analytical procedure, cut-off scores are established at the test score (the predictor variable) at which an individual is as likely to be in category j as in category j+1 of an ordinal outcome variable. The application of the complete procedure is illustrated by an example with data from an actual study on eating disorders. In this example, two cut-off scores on the Eating Attitudes Test (EAT-26) scores are obtained in order to classify individuals into three ordinal categories: asymptomatic, symptomatic and eating disorder. Diagnoses were made from the responses to a self-report (Q-EDD) that operationalises DSM-IV criteria for eating disorders. Alternatives to the MLR model to set multiple cut-off scores are discussed.

An Experimental Realization of a Chaos-Based Secure Communication Using Arduino Microcontrollers

PubMed Central

Zapateiro De la Hoz, Mauricio; Vidal, Yolanda

2015-01-01

Security and secrecy are some of the important concerns in the communications world. In the last years, several encryption techniques have been proposed in order to improve the secrecy of the information transmitted. Chaos-based encryption techniques are being widely studied as part of the problem because of the highly unpredictable and random-look nature of the chaotic signals. In this paper we propose a digital-based communication system that uses the logistic map which is a mathematically simple model that is chaotic under certain conditions. The input message signal is modulated using a simple Delta modulator and encrypted using a logistic map. The key signal is also encrypted using the same logistic map with different initial conditions. In the receiver side, the binary-coded message is decrypted using the encrypted key signal that is sent through one of the communication channels. The proposed scheme is experimentally tested using Arduino shields which are simple yet powerful development kits that allows for the implementation of the communication system for testing purposes. PMID:26413563

[Logistic regression model of noninvasive prediction for portal hypertensive gastropathy in patients with hepatitis B associated cirrhosis].

PubMed

Wang, Qingliang; Li, Xiaojie; Hu, Kunpeng; Zhao, Kun; Yang, Peisheng; Liu, Bo

2015-05-12

To explore the risk factors of portal hypertensive gastropathy (PHG) in patients with hepatitis B associated cirrhosis and establish a Logistic regression model of noninvasive prediction. The clinical data of 234 hospitalized patients with hepatitis B associated cirrhosis from March 2012 to March 2014 were analyzed retrospectively. The dependent variable was the occurrence of PHG while the independent variables were screened by binary Logistic analysis. Multivariate Logistic regression was used for further analysis of significant noninvasive independent variables. Logistic regression model was established and odds ratio was calculated for each factor. The accuracy, sensitivity and specificity of model were evaluated by the curve of receiver operating characteristic (ROC). According to univariate Logistic regression, the risk factors included hepatic dysfunction, albumin (ALB), bilirubin (TB), prothrombin time (PT), platelet (PLT), white blood cell (WBC), portal vein diameter, spleen index, splenic vein diameter, diameter ratio, PLT to spleen volume ratio, esophageal varices (EV) and gastric varices (GV). Multivariate analysis showed that hepatic dysfunction (X1), TB (X2), PLT (X3) and splenic vein diameter (X4) were the major occurring factors for PHG. The established regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4. The accuracy of model for PHG was 79.1% with a sensitivity of 77.2% and a specificity of 80.8%. Hepatic dysfunction, TB, PLT and splenic vein diameter are risk factors for PHG and the noninvasive predicted Logistic regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4.

New Results on Contact Binary Stars

NASA Astrophysics Data System (ADS)

He, J.; Qian, S.; Zhu, L.; Liu, L.; Liao, W.

2014-08-01

Contact binary star is a kind of close binary with the strongest interaction binary system. Their formations and evolutions are unsolved problems in astrophysics. Since 2000, our groups have observed and studied more than half a hundred of contact binaries. In this report, I will summarize our new results of some contact binary stars (e.g. UZ CMi, GSC 03526-01995, FU Dra, GSC 0763-0572, V524 Mon, MR Com, etc.). They are as follow: (1) We discovered that V524 Mon and MR Com are shallow-contact binaries with their period decreasing; (2) GSC 03526-01995 is middle-contact binary without a period increasing or decreasing continuously; (3) UZ CMi, GSC 0763-0572 and FU Dra are middle-contact binaries with the period increasing continuously; (4) UZ CMi, GSC 03526-01995, FU Dra and V524 Mon show period oscillation which may imply the presence of additional components in these contact binaries.

The rate of adherence to urate-lowering therapy and associated factors in Chinese gout patients: a cross-sectional study.

PubMed

Yin, Rulan; Cao, Haixia; Fu, Ting; Zhang, Qiuxiang; Zhang, Lijuan; Li, Liren; Gu, Zhifeng

2017-07-01

The aim of this study was to assess adherence rate and predictors of non-adherence with urate-lowering therapy (ULT) in Chinese gout patients. A cross-sectional study was administered to 125 gout patients using the Compliance Questionnaire on Rheumatology (CQR) for adherence to ULT. Patients were asked to complete the Treatment Satisfaction Questionnaire for Medication version II, Health Assessment Questionnaire, Confidence in Gout Treatment Questionnaire, Gout Knowledge Questionnaire, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and 36-Item Short Form Health Survey. Data were analyzed by independent sample t test, rank sum test, Chi-square analysis as well as binary stepwise logistic regression modeling. The data showed that the rate of adherence (CQR ≥80%) to ULT was 9.6% in our investigated gout patients. Adherence was associated with functional capacity, gout-related knowledge, satisfaction with medication, confidence in gout treatment and mental components summary. Multivariable analysis of binary stepwise logistic regression identified gout-related knowledge and satisfaction of effectiveness with medication was the independent risk factors of medication non-adherence. Patients unaware of gout-related knowledge, or with low satisfaction of effectiveness with medication, were more likely not to adhere to ULT. Non-adherence to ULT among gout patients is exceedingly common, particularly in patients unaware of gout-related knowledge, or with low satisfaction of effectiveness with medication. These findings could help medical personnel develop useful interventions to improve gout patients' medication adherence.

Financial performance monitoring of the technical efficiency of critical access hospitals: a data envelopment analysis and logistic regression modeling approach.

PubMed

Wilson, Asa B; Kerr, Bernard J; Bastian, Nathaniel D; Fulton, Lawrence V

2012-01-01

From 1980 to 1999, rural designated hospitals closed at a disproportionally high rate. In response to this emergent threat to healthcare access in rural settings, the Balanced Budget Act of 1997 made provisions for the creation of a new rural hospital--the critical access hospital (CAH). The conversion to CAH and the associated cost-based reimbursement scheme significantly slowed the closure rate of rural hospitals. This work investigates which methods can ensure the long-term viability of small hospitals. This article uses a two-step design to focus on a hypothesized relationship between technical efficiency of CAHs and a recently developed set of financial monitors for these entities. The goal is to identify the financial performance measures associated with efficiency. The first step uses data envelopment analysis (DEA) to differentiate efficient from inefficient facilities within a data set of 183 CAHs. Determining DEA efficiency is an a priori categorization of hospitals in the data set as efficient or inefficient. In the second step, DEA efficiency is the categorical dependent variable (efficient = 0, inefficient = 1) in the subsequent binary logistic regression (LR) model. A set of six financial monitors selected from the array of 20 measures were the LR independent variables. We use a binary LR to test the null hypothesis that recently developed CAH financial indicators had no predictive value for categorizing a CAH as efficient or inefficient, (i.e., there is no relationship between DEA efficiency and fiscal performance).

Hierarchical faunal filters: An approach to assessing effects of habitat and nonnative species on native fishes

USGS Publications Warehouse

Quist, M.C.; Rahel, F.J.; Hubert, W.A.

2005-01-01

Understanding factors related to the occurrence of species across multiple spatial and temporal scales is critical to the conservation and management of native fishes, especially for those species at the edge of their natural distribution. We used the concept of hierarchical faunal filters to provide a framework for investigating the influence of habitat characteristics and normative piscivores on the occurrence of 10 native fishes in streams of the North Platte River watershed in Wyoming. Three faunal filters were developed for each species: (i) large-scale biogeographic, (ii) local abiotic, and (iii) biotic. The large-scale biogeographic filter, composed of elevation and stream-size thresholds, was used to determine the boundaries within which each species might be expected to occur. Then, a local abiotic filter (i.e., habitat associations), developed using binary logistic-regression analysis, estimated the probability of occurrence of each species from features such as maximum depth, substrate composition, submergent aquatic vegetation, woody debris, and channel morphology (e.g., amount of pool habitat). Lastly, a biotic faunal filter was developed using binary logistic regression to estimate the probability of occurrence of each species relative to the abundance of nonnative piscivores in a reach. Conceptualising fish assemblages within a framework of hierarchical faunal filters is simple and logical, helps direct conservation and management activities, and provides important information on the ecology of fishes in the western Great Plains of North America. ?? Blackwell Munksgaard, 2004.

Racial residential segregation and preterm birth: built environment as a mediator.

PubMed

Anthopolos, Rebecca; Kaufman, Jay S; Messer, Lynne C; Miranda, Marie Lynn

2014-05-01

Racial residential segregation has been associated with preterm birth. Few studies have examined mediating pathways, in part because, with binary outcomes, indirect effects estimated from multiplicative models generally lack causal interpretation. We develop a method to estimate additive-scale natural direct and indirect effects from logistic regression. We then evaluate whether segregation operates through poor-quality built environment to affect preterm birth. To estimate natural direct and indirect effects, we derive risk differences from logistic regression coefficients. Birth records (2000-2008) for Durham, North Carolina, were linked to neighborhood-level measures of racial isolation and a composite construct of poor-quality built environment. We decomposed the total effect of racial isolation on preterm birth into direct and indirect effects. The adjusted total effect of an interquartile increase in racial isolation on preterm birth was an extra 27 preterm events per 1000 births (risk difference = 0.027 [95% confidence interval = 0.007 to 0.047]). With poor-quality built environment held at the level it would take under isolation at the 25th percentile, the direct effect of an interquartile increase in isolation was 0.022 (-0.001 to 0.042). Poor-quality built environment accounted for 35% (11% to 65%) of the total effect. Our methodology facilitates the estimation of additive-scale natural effects with binary outcomes. In this study, the total effect of racial segregation on preterm birth was partially mediated by poor-quality built environment.

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

PubMed

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

2017-02-01

The risk factors of high trait anger of juvenile offenders were explored through questionnaire study in a youth correctional facility of Hubei province, China. A total of 1090 juvenile offenders in Hubei province were investigated by self-compiled social-demographic questionnaire, Childhood Trauma Questionnaire (CTQ), and State-Trait Anger Expression Inventory-II (STAXI-II). The risk factors were analyzed by chi-square tests, correlation analysis, and binary logistic regression analysis with SPSS 19.0. A total of 1082 copies of valid questionnaires were collected. High trait anger group (n=316) was defined as those who scored in the upper 27th percentile of STAXI-II trait anger scale (TAS), and the rest were defined as low trait anger group (n=766). The risk factors associated with high level of trait anger included: childhood emotional abuse, childhood sexual abuse, step family, frequent drug abuse, and frequent internet using (P<0.05 or P<0.01). Birth sequence, number of sibling, ranking in the family, identity of the main care-taker, the education level of care-taker, educational style of care-taker, family income, relationship between parents, social atmosphere of local area, frequent drinking, and frequent smoking did not predict to high level of trait anger (P>0.05). It was suggested that traumatic experience in childhood and unhealthy life style may significantly increase the level of trait anger in adulthood. The risk factors of high trait anger and their effects should be taken into consideration seriously.

Depression and associated variables in people over 50 years in Spain.

PubMed

Portellano-Ortiz, Cristina; Garre-Olmo, Josep; Calvó-Perxas, Laia; Conde-Sala, Josep Lluís

2016-12-06

Depression is a common and disabling psychiatric disorder in adulthood and is associated with higher mortality and functional disability. To determine the association between clinical and sociodemographic variables with depression in a sample of people over 50 years old living in Spain, and compare the prevalence of depression with the other Survey of Health, Ageing and Retirement (SHARE) countries. There were 5,830 participants in the Spanish sample of the Wave 5, 2013, of SHARE. Tools used: EURO-D (Depression) and CASP-12 (Quality of Life). Bivariate, and binary logistic. The variables associated with depression in the binary logistic regression (EURO-D ≥4) were poor self-perceived physical health (OR=13.34; 95% CI: 9.74-18.27), having more than 2 difficulties in Activities of Daily Living (ADL) (OR=4.46; 95% CI: 3.13-6.34) and female gender (OR=2.16; 95% CI: 1.83-2.56). Depression was more common among participants with Alzheimer (76.4%), emotional disorders (73.9%), Parkinson (57.4%), hip fracture (55.4%), and rheumatism (50.9%). Compared with other European countries, Spain had a percentage of people with depression (29.3%) that was higher than the European average (27.9%). The most important variables associated with depression were poor perceived physical health, presence of difficulties in ADL, and female gender. Copyright © 2016 SEP y SEPB. Publicado por Elsevier España, S.L.U. All rights reserved.

Combined Endoscopic/Sonographic-Based Risk Matrix Model for Predicting One-Year Risk of Surgery: A Prospective Observational Study of a Tertiary Center Severe/Refractory Crohn's Disease Cohort.

PubMed

Rispo, Antonio; Imperatore, Nicola; Testa, Anna; Bucci, Luigi; Luglio, Gaetano; De Palma, Giovanni Domenico; Rea, Matilde; Nardone, Olga Maria; Caporaso, Nicola; Castiglione, Fabiana

2018-03-08

In the management of Crohn's Disease (CD) patients, having a simple score combining clinical, endoscopic and imaging features to predict the risk of surgery could help to tailor treatment more effectively. AIMS: to prospectively evaluate the one-year risk factors for surgery in refractory/severe CD and to generate a risk matrix for predicting the probability of surgery at one year. CD patients needing a disease re-assessment at our tertiary IBD centre underwent clinical, laboratory, endoscopy and bowel sonography (BS) examinations within one week. The optimal cut-off values in predicting surgery were identified using ROC curves for Simple Endoscopic Score for CD (SES-CD), bowel wall thickness (BWT) at BS, and small bowel CD extension at BS. Binary logistic regression and Cox's regression were then carried out. Finally, the probabilities of surgery were calculated for selected baseline levels of covariates and results were arranged in a prediction matrix. Of 100 CD patients, 30 underwent surgery within one year. SES-CD©9 (OR 15.3; p<0.001), BWT©7 mm (OR 15.8; p<0.001), small bowel CD extension at BS©33 cm (OR 8.23; p<0.001) and stricturing/penetrating behavior (OR 4.3; p<0.001) were the only independent factors predictive of surgery at one-year based on binary logistic and Cox's regressions. Our matrix model combined these risk factors and the probability of surgery ranged from 0.48% to 87.5% (sixteen combinations). Our risk matrix combining clinical, endoscopic and ultrasonographic findings can accurately predict the one-year risk of surgery in patients with severe/refractory CD requiring a disease re-evaluation. This tool could be of value in clinical practice, serving as the basis for a tailored management of CD patients.

Association of funding and conclusions in randomized drug trials: a reflection of treatment effect or adverse events?

PubMed

Als-Nielsen, Bodil; Chen, Wendong; Gluud, Christian; Kjaergard, Lise L

2003-08-20

Previous studies indicate that industry-sponsored trials tend to draw proindustry conclusions. To explore whether the association between funding and conclusions in randomized drug trials reflects treatment effects or adverse events. Observational study of 370 randomized drug trials included in meta-analyses from Cochrane reviews selected from the Cochrane Library, May 2001. From a random sample of 167 Cochrane reviews, 25 contained eligible meta-analyses (assessed a binary outcome; pooled at least 5 full-paper trials of which at least 1 reported adequate and 1 reported inadequate allocation concealment). The primary binary outcome from each meta-analysis was considered the primary outcome for all trials included in each meta-analysis. The association between funding and conclusions was analyzed by logistic regression with adjustment for treatment effect, adverse events, and additional confounding factors (methodological quality, control intervention, sample size, publication year, and place of publication). Conclusions in trials, classified into whether the experimental drug was recommended as the treatment of choice or not. The experimental drug was recommended as treatment of choice in 16% of trials funded by nonprofit organizations, 30% of trials not reporting funding, 35% of trials funded by both nonprofit and for-profit organizations, and 51% of trials funded by for-profit organizations (P<.001; chi2 test). Logistic regression analyses indicated that funding, treatment effect, and double blinding were the only significant predictors of conclusions. Adjusted analyses showed that trials funded by for-profit organizations were significantly more likely to recommend the experimental drug as treatment of choice (odds ratio, 5.3; 95% confidence interval, 2.0-14.4) compared with trials funded by nonprofit organizations. This association did not appear to reflect treatment effect or adverse events. Conclusions in trials funded by for-profit organizations may be more positive due to biased interpretation of trial results. Readers should carefully evaluate whether conclusions in randomized trials are supported by data.

Infectious mononucleosis and hepatic function

PubMed Central

Zhang, Li; Zhou, Pingping; Meng, Zhaowei; Pang, Chongjie; Gong, Lu; Zhang, Qing; Jia, Qiyu; Song, Kun

2018-01-01

Abnormal hepatic function is common in infectious mononucleosis (IM). However, it remains unknown why increased transferase levels are more common than bilirubin abnormalities in IM. The current study aimed to investigate these associations in the Chinese population. A total of 95 patients with IM (47 males and 48 females) were enrolled in the current study, as well as 95 healthy controls. Patients were sorted by sex. A receiver operating characteristic (ROC) curve was used to determine cut-off values for IM diagnosis and prediction. Crude and adjusted odds ratios (OR) for IM were analyzed using binary logistic regression. It was determined that alanine aminotransferase (ALT), aspartate aminotransferase (AST) and γ-glutamyl transferase (GGT) levels were significantly higher in patients with IM compared with controls; however, total bilirubin (TB) levels were significantly lower in patients with IM. ROCs demonstrated that, if ALT, AST and GGT concentrations were higher than, or if TB was lower than, cut-off values, they were predictive of IM. Binary logistic regression identified that the risk of IM in patients exhibiting high levels of transferases was significantly increased, particularly in males. Crude ORs in ALT quartile 4 were 21.667 and 10.111 for males and females, respectively and adjusted ORs were 38.054 and 9.882, respectively. A significant IM risk of IM was evident in patients with low bilirubin levels and females appeared to be particularly susceptible. For example, crude ORs in quartile 1 were 8.229 and 8.257 for males and females, respectively and adjusted ORs were 8.883 and 10.048, respectively. Therefore, the current study identified a positive association between transferase levels and IM and a negative association between TB and IM. Therefore, the results of the current study indicate that high transferases are suggestive of IM, particularly in males, whereas low TB is suggestive for IM, particularly in females. PMID:29456696

Neuronal autoantibodies in mesial temporal lobe epilepsy with hippocampal sclerosis.

PubMed

Vanli-Yavuz, Ebru Nur; Erdag, Ece; Tuzun, Erdem; Ekizoglu, Esme; Baysal-Kirac, Leyla; Ulusoy, Canan; Peach, Sian; Gundogdu, Gokcen; Sencer, Serra; Sencer, Altay; Kucukali, Cem Ismail; Bebek, Nerses; Gurses, Candan; Gokyigit, Aysen; Baykan, Betul

2016-07-01

Our aim was to investigate the prevalence of neuronal autoantibodies (NAbs) in a large consecutive series with mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) and to elucidate the clinical and laboratory clues for detection of NAbs in this prototype of frequent, drug-resistant epilepsy syndrome. Consecutive patients diagnosed with MTLE fulfilling the MRI criteria for HS were enrolled. The sera of patients and various control groups (80 subjects) were tested for eight NAbs after ethical approval and signed consents. Brain tissues obtained from surgical specimens were also investigated by immunohistochemical analysis for the presence of inflammatory infiltrates. The features of seropositive versus seronegative groups were compared and binary logistic regression analysis was performed to explore the differentiating variables. We found antibodies against antigens, contactin-associated protein-like 2 in 11 patients, uncharacterised voltage-gated potassium channel (VGKC)-complex antigens in four patients, glycine receptor (GLY-R) in 5 patients, N-methyl-d-aspartate receptor in 4 patients and γ-aminobutyric acid receptor A in 1 patient of 111 patients with MTLE-HS and none of the control subjects. The history of status epilepticus, diagnosis of psychosis and positron emission tomography or single-photon emission CT findings in temporal plus extratemporal regions were found significantly more frequently in the seropositive group. Binary logistic regression analysis disclosed that status epilepticus, psychosis and cognitive dysfunction were statistically significant variables to differentiate between the VGKC-complex subgroup versus seronegative group. This first systematic screening study of various NAbs showed 22.5% seropositivity belonging mostly to VGKC-complex antibodies in a large consecutive series of patients with MTLE-HS. Our results indicated a VGKC-complex autoimmunity-related subgroup in the syndrome of MTLE-HS. 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/

Clinical features and risk factor analysis for lower extremity deep venous thrombosis in Chinese neurosurgical patients

PubMed Central

Guo, Fuyou; Shashikiran, Tagilapalli; Chen, Xi; Yang, Lei; Liu, Xianzhi; Song, Laijun

2015-01-01

Background: Deep venous thrombosis (DVT) contributes significantly to the morbidity and mortality of neurosurgical patients; however, no data regarding lower extremity DVT in postoperative Chinese neurosurgical patients have been reported. Materials and Methods: From January 2012 to December 2013, 196 patients without preoperative DVT who underwent neurosurgical operations were evaluated by color Doppler ultrasonography and D-dimer level measurements on the 3rd, 7th, and 14th days after surgery. Follow-up clinical data were recorded to determine the incidence of lower extremity DVT in postoperative neurosurgical patients and to analyze related clinical features. First, a single factor analysis, Chi-square test, was used to select statistically significant factors. Then, a multivariate analysis, binary logistic regression analysis, was used to determine risk factors for lower extremity DVT in postoperative neurosurgical patients. Results: Lower extremity DVT occurred in 61 patients, and the incidence of DVT was 31.1% in the enrolled Chinese neurosurgical patients. The common symptoms of DVT were limb swelling and lower extremity pain as well as increased soft tissue tension. The common sites of venous involvement were the calf muscle and peroneal and posterior tibial veins. The single factor analysis showed statistically significant differences in DVT risk factors, including age, hypertension, smoking status, operation time, a bedridden or paralyzed state, the presence of a tumor, postoperative dehydration, and glucocorticoid treatment, between the two groups (P < 0.05). The binary logistic regression analysis showed that an age greater than 50 years, hypertension, a bedridden or paralyzed state, the presence of a tumor, and postoperative dehydration were risk factors for lower extremity DVT in postoperative neurosurgical patients. Conclusions: Lower extremity DVT was a common complication following craniotomy in the enrolled Chinese neurosurgical patients. Multiple factors were identified as predictive of DVT in neurosurgical patients, including the presence of a tumor, an age greater than 50 years, hypertension, and immobility. PMID:26752303

Automated particle identification through regression analysis of size, shape and colour

NASA Astrophysics Data System (ADS)

Rodriguez Luna, J. C.; Cooper, J. M.; Neale, S. L.

2016-04-01

Rapid point of care diagnostic tests and tests to provide therapeutic information are now available for a range of specific conditions from the measurement of blood glucose levels for diabetes to card agglutination tests for parasitic infections. Due to a lack of specificity these test are often then backed up by more conventional lab based diagnostic methods for example a card agglutination test may be carried out for a suspected parasitic infection in the field and if positive a blood sample can then be sent to a lab for confirmation. The eventual diagnosis is often achieved by microscopic examination of the sample. In this paper we propose a computerized vision system for aiding in the diagnostic process; this system used a novel particle recognition algorithm to improve specificity and speed during the diagnostic process. We will show the detection and classification of different types of cells in a diluted blood sample using regression analysis of their size, shape and colour. The first step is to define the objects to be tracked by a Gaussian Mixture Model for background subtraction and binary opening and closing for noise suppression. After subtracting the objects of interest from the background the next challenge is to predict if a given object belongs to a certain category or not. This is a classification problem, and the output of the algorithm is a Boolean value (true/false). As such the computer program should be able to "predict" with reasonable level of confidence if a given particle belongs to the kind we are looking for or not. We show the use of a binary logistic regression analysis with three continuous predictors: size, shape and color histogram. The results suggest this variables could be very useful in a logistic regression equation as they proved to have a relatively high predictive value on their own.

Gender differences in depressive symptom profiles and patterns of psychotropic drug usage in Asian patients with depression: Findings from the Research on Asian Psychotropic Prescription Patterns for Antidepressants study.

PubMed

Park, Seon-Cheol; Lee, Min-Soo; Shinfuku, Naotaka; Sartorius, Norman; Park, Yong Chon

2015-09-01

The purpose of this study was to investigate whether there were gender-specific depressive symptom profiles or gender-specific patterns of psychotropic agent usage in Asian patients with depression. Clinical data from the Research on Asian Psychotropic Prescription Patterns for Antidepressant study (1171 depressed patients) were used to determine gender differences by analysis of covariates for continuous variables and by logistic regression analysis for discrete variables. In addition, a binary logistic regression model was fitted to identify independent clinical correlates of the gender-specific pattern on psychotropic drug usage. Men were more likely than women to have loss of interest (adjusted odds ratio = 1.379, p = 0.009), fatigue (adjusted odds ratio = 1.298, p = 0.033) and concurrent substance abuse (adjusted odds ratio = 3.793, p = 0.008), but gender differences in other symptom profiles and clinical features were not significant. Men were also more likely than women to be prescribed adjunctive therapy with a second-generation antipsychotic (adjusted odds ratio = 1.320, p = 0.044). However, men were less likely than women to have suicidal thoughts/acts (adjusted odds ratio = 0.724, p = 0.028). Binary logistic regression models revealed that lower age (odds ratio = 0.986, p = 0.027) and current hospitalization (odds ratio = 3.348, p < 0.0001) were independent clinical correlates of use of second-generation antipsychotics as adjunctive therapy for treating depressed Asian men. Unique gender-specific symptom profiles and gender-specific patterns of psychotropic drug usage can be identified in Asian patients with depression. Hence, ethnic and cultural influences on the gender preponderance of depression should be considered in the clinical psychiatry of Asian patients. © The Royal Australian and New Zealand College of Psychiatrists 2015.

Sleep Quality and Motor Vehicle Crashes in Adolescents

PubMed Central

Pizza, Fabio; Contardi, Sara; Antognini, Alessandro Baldi; Zagoraiou, Maroussa; Borrotti, Matteo; Mostacci, Barbara; Mondini, Susanna; Cirignotta, Fabio

2010-01-01

Study Objectives: Sleep-related complaints are common in adolescents, but their impact on the rate of motor vehicle crashes accidents is poorly known. We studied subjective sleep quality, driving habits, and self-reported car crashes in high-school adolescents. Methods: Self-administered questionnaires (with items exploring driving habits) were distributed to 339 students who had a driver's license and attended 1 of 7 high schools in Bologna, Italy. Statistical analysis were performed to describe lifestyle habits, sleep quality, sleepiness, and their relationship with the binary dependent variable (presence or absence of car crashes) to identify the factors significantly affecting the probability of car crashes in a multivariate binary logistic regression model. Results: Nineteen percent of the sample reported bad sleep, 64% complained of daytime sleepiness, and 40% reported sleepiness while driving. Eighty students (24%), 76% of which were males, reported that they had already crashed at least once, and 15% considered sleepiness to have been the main cause of their crash. As compared with adolescents who had not had a crash, those who had at least 1 previous crash reported that they more frequently used to drive (79% vs 62%), drove at night (25% vs 9%), drove while sleepy (56% vs 35%), had bad sleep (29% vs 16%), and used stimulants such as caffeinated soft drinks (32% vs 19%), tobacco (54% vs 27%), and drugs (21% vs 7%). The logistic procedure established a significant predictive role of male sex (p < 0.0001; odds ratio = 3.3), tobacco use (p < 0.0001; odds ratio = 3.2), sleepiness while driving (p = 0.010; odds ratio = 2.1), and bad sleep (p = 0.047; odds ratio = 1.9) for the crash risk. Conclusions: Our results confirm the high prevalence of sleep-related complaints among adolescents and highlight their independent role on self-reported crash risk. Citation: Pizza F; Contardi S; Baldi Antognini A; Zagoraiou M; Borrotti M; Mostacci B; Mondini S; Cirignotta F. Sleep quality and motor vehicle crashes in adolescents. J Clin Sleep Med 2010;6(1):41-45. PMID:20191936

Classification of Dust Days by Satellite Remotely Sensed Aerosol Products

NASA Technical Reports Server (NTRS)

Sorek-Hammer, M.; Cohen, A.; Levy, Robert C.; Ziv, B.; Broday, D. M.

2013-01-01

Considerable progress in satellite remote sensing (SRS) of dust particles has been seen in the last decade. From an environmental health perspective, such an event detection, after linking it to ground particulate matter (PM) concentrations, can proxy acute exposure to respirable particles of certain properties (i.e. size, composition, and toxicity). Being affected considerably by atmospheric dust, previous studies in the Eastern Mediterranean, and in Israel in particular, have focused on mechanistic and synoptic prediction, classification, and characterization of dust events. In particular, a scheme for identifying dust days (DD) in Israel based on ground PM10 (particulate matter of size smaller than 10 nm) measurements has been suggested, which has been validated by compositional analysis. This scheme requires information regarding ground PM10 levels, which is naturally limited in places with sparse ground-monitoring coverage. In such cases, SRS may be an efficient and cost-effective alternative to ground measurements. This work demonstrates a new model for identifying DD and non-DD (NDD) over Israel based on an integration of aerosol products from different satellite platforms (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)). Analysis of ground-monitoring data from 2007 to 2008 in southern Israel revealed 67 DD, with more than 88 percent occurring during winter and spring. A Classification and Regression Tree (CART) model that was applied to a database containing ground monitoring (the dependent variable) and SRS aerosol product (the independent variables) records revealed an optimal set of binary variables for the identification of DD. These variables are combinations of the following primary variables: the calendar month, ground-level relative humidity (RH), the aerosol optical depth (AOD) from MODIS, and the aerosol absorbing index (AAI) from OMI. A logistic regression that uses these variables, coded as binary variables, demonstrated 93.2 percent correct classifications of DD and NDD. Evaluation of the combined CART-logistic regression scheme in an adjacent geographical region (Gush Dan) demonstrated good results. Using SRS aerosol products for DD and NDD, identification may enable us to distinguish between health, ecological, and environmental effects that result from exposure to these distinct particle populations.

A novel early risk assessment tool for detecting clinical outcomes in patients with heat-related illness (J-ERATO score): Development and validation in independent cohorts in Japan.

PubMed

Hayashida, Kei; Kondo, Yutaka; Hifumi, Toru; Shimazaki, Junya; Oda, Yasutaka; Shiraishi, Shinichiro; Fukuda, Tatsuma; Sasaki, Junichi; Shimizu, Keiki

2018-01-01

We sought to develop a novel risk assessment tool to predict the clinical outcomes after heat-related illness. Prospective, multicenter observational study. Patients who transferred to emergency hospitals in Japan with heat-related illness were registered. The sample was divided into two parts: 60% to construct the score and 40% to validate it. A binary logistic regression model was used to predict hospital admission as a primary outcome. The resulting model was transformed into a scoring system. A total of 3,001 eligible patients were analyzed. There was no difference in variables between development and validation cohorts. Based on the result of a logistic regression model in the development phase (n = 1,805), the J-ERATO score was defined as the sum of the six binary components in the prehospital setting (respiratory rate≥22 /min, Glasgow coma scale<15, systolic blood pressure≤100 mmHg, heart rate≥100 bpm, body temperature≥38°C, and age≥65 y), for a total score ranging from 0 to 6. In the validation phase (n = 1,196), the score had excellent discrimination (C-statistic 0.84; 95% CI 0.79-0.89, p<0.0001) and calibration (P>0.2 by Hosmer-Lemeshow test). The observed proportion of hospital admission increased with increasing J-ERATO score (score = 0, 5.0%; score = 1, 15.0%; score = 2, 24.6%; score = 3, 38.6%; score = 4, 68.0%; score = 5, 85.2%; score = 6, 96.4%). Multivariate analyses showed that the J-ERATO score was an independent positive predictor of hospital admission (adjusted OR, 2.43; 95% CI, 2.06-2.87; P<0.001), intensive care unit (ICU) admission (3.73; 2.95-4.72; P<0.001) and in-hospital mortality (1.65; 1.18-2.32; P = 0.004). The J-ERATO score is simply assessed and can facilitate the identification of patients with higher risk of heat-related hospitalization. This scoring system is also significantly associated with the higher likelihood of ICU admission and in-hospital mortality after heat-related hospitalization.

Polar alignment of a protoplanetary disc around an eccentric binary II: Effect of binary and disc parameters

NASA Astrophysics Data System (ADS)

Martin, Rebecca G.; Lubow, Stephen H.

2018-06-01

In a recent paper Martin & Lubow showed that a circumbinary disc around an eccentric binary can undergo damped nodal oscillations that lead to the polar (perpendicular) alignment of the disc relative to the binary orbit. The disc angular momentum vector aligns to the eccentricity vector of the binary. We explore the robustness of this mechanism for a low mass disc (0.001 of the binary mass) and its dependence on system parameters by means of hydrodynamic disc simulations. We describe how the evolution depends upon the disc viscosity, temperature, size, binary mass ratio, orbital eccentricity and inclination. We compare results with predictions of linear theory. We show that polar alignment of a low mass disc may occur over a wide range of binary-disc parameters. We discuss the application of our results to the formation of planetary systems around eccentric binary stars.

Accounting for informatively missing data in logistic regression by means of reassessment sampling.

PubMed

Lin, Ji; Lyles, Robert H

2015-05-20

We explore the 'reassessment' design in a logistic regression setting, where a second wave of sampling is applied to recover a portion of the missing data on a binary exposure and/or outcome variable. We construct a joint likelihood function based on the original model of interest and a model for the missing data mechanism, with emphasis on non-ignorable missingness. The estimation is carried out by numerical maximization of the joint likelihood function with close approximation of the accompanying Hessian matrix, using sharable programs that take advantage of general optimization routines in standard software. We show how likelihood ratio tests can be used for model selection and how they facilitate direct hypothesis testing for whether missingness is at random. Examples and simulations are presented to demonstrate the performance of the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.

Investigation of shipping accident injury severity and mortality.

PubMed

Weng, Jinxian; Yang, Dong

2015-03-01

Shipping movements are operated in a complex and high-risk environment. Fatal shipping accidents are the nightmares of seafarers. With ten years' worldwide ship accident data, this study develops a binary logistic regression model and a zero-truncated binomial regression model to predict the probability of fatal shipping accidents and corresponding mortalities. The model results show that both the probability of fatal accidents and mortalities are greater for collision, fire/explosion, contact, grounding, sinking accidents occurred in adverse weather conditions and darkness conditions. Sinking has the largest effects on the increment of fatal accident probability and mortalities. The results also show that the bigger number of mortalities is associated with shipping accidents occurred far away from the coastal area/harbor/port. In addition, cruise ships are found to have more mortalities than non-cruise ships. The results of this study are beneficial for policy-makers in proposing efficient strategies to prevent fatal shipping accidents. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of Binary Adherence Data in the Setting of Polypharmacy: A Comparison of Different Approaches

PubMed Central

Esserman, Denise A.; Moore, Charity G.; Roth, Mary T.

2009-01-01

Older community dwelling adults often take multiple medications for numerous chronic diseases. Non-adherence to these medications can have a large public health impact. Therefore, the measurement and modeling of medication adherence in the setting of polypharmacy is an important area of research. We apply a variety of different modeling techniques (standard linear regression; weighted linear regression; adjusted linear regression; naïve logistic regression; beta-binomial (BB) regression; generalized estimating equations (GEE)) to binary medication adherence data from a study in a North Carolina based population of older adults, where each medication an individual was taking was classified as adherent or non-adherent. In addition, through simulation we compare these different methods based on Type I error rates, bias, power, empirical 95% coverage, and goodness of fit. We find that estimation and inference using GEE is robust to a wide variety of scenarios and we recommend using this in the setting of polypharmacy when adherence is dichotomously measured for multiple medications per person. PMID:20414358

Psychosocial Correlates of Frequent Indoor Tanning among Adolescent Boys

PubMed Central

Blashill, Aaron J.

2012-01-01

The aim of the current study was to assess psychosocial correlates (i.e., perceived weight, weight control strategies, substance use, and victimization) of frequent indoor tanning in adolescent boys—a group at high risk for developing skin cancer. Participants (N = 7,907) were drawn from a nationally-representative sample of adolescent boys attending high school in the United States. Binary logistic regression revealed that extreme weight control strategies, particularly steroid use (odds ratio = 3.67) and compensatory vomiting (odds ratio = 2.34), along with substance use and victimization, were significantly related to frequent indoor tanning. These results highlight the role of appearance-changing, and health-risk behaviors in the context of frequent indoor tanning. Skin cancer prevention interventions may benefit from adopting approaches that integrate the treatment of body dissatisfaction and subsequent maladaptive behaviors. PMID:23276832

Psychosocial correlates of frequent indoor tanning among adolescent boys.

PubMed

Blashill, Aaron J

2013-03-01

The aim of the current study was to assess psychosocial correlates (i.e., perceived weight, weight control strategies, substance use, and victimization) of frequent indoor tanning in adolescent boys-a group at high risk for developing skin cancer. Participants (N=7,907) were drawn from a nationally representative sample of adolescent boys attending high school in the United States. Binary logistic regression revealed that extreme weight control strategies, particularly steroid use (odds ratio=3.67) and compensatory vomiting (odds ratio=2.34), along with substance use and victimization, were significantly related to frequent indoor tanning. These results highlight the role of appearance-changing, and health-risk behaviors in the context of frequent indoor tanning. Skin cancer prevention interventions may benefit from adopting approaches that integrate the treatment of body dissatisfaction and subsequent maladaptive behaviors. Copyright © 2012 Elsevier Ltd. All rights reserved.

r-Process Nucleosynthesis in the Early Universe Through Fast Mergers of Compact Binaries in Triple Systems

NASA Astrophysics Data System (ADS)

Bonetti, Matteo; Perego, Albino; Capelo, Pedro R.; Dotti, Massimo; Miller, M. Coleman

2018-05-01

Surface abundance observations of halo stars hint at the occurrence of r-process nucleosynthesis at low metallicity ([Fe/H] < -3), possibly within the first 108 yr after the formation of the first stars. Possible loci of early-Universe r-process nucleosynthesis are the ejecta of either black hole-neutron star or neutron star-neutron star binary mergers. Here, we study the effect of the inclination-eccentricity oscillations raised by a tertiary (e.g. a star) on the coalescence time-scale of the inner compact object binaries. Our results are highly sensitive to the assumed initial distribution of the inner binary semi-major axes. Distributions with mostly wide compact object binaries are most affected by the third object, resulting in a strong increase (by more than a factor of 2) in the fraction of fast coalescences. If instead the distribution preferentially populates very close compact binaries, general relativistic precession prevents the third body from increasing the inner binary eccentricity to very high values. In this last case, the fraction of coalescing binaries is increased much less by tertiaries, but the fraction of binaries that would coalesce within 108 yr even without a third object is already high. Our results provide additional support to the compact-binary merger scenario for r-process nucleosynthesis.

Survival of planets around shrinking stellar binaries

PubMed Central

Muñoz, Diego J.; Lai, Dong

2015-01-01

The discovery of transiting circumbinary planets by the Kepler mission suggests that planets can form efficiently around binary stars. None of the stellar binaries currently known to host planets has a period shorter than 7 d, despite the large number of eclipsing binaries found in the Kepler target list with periods shorter than a few days. These compact binaries are believed to have evolved from wider orbits into their current configurations via the so-called Lidov–Kozai migration mechanism, in which gravitational perturbations from a distant tertiary companion induce large-amplitude eccentricity oscillations in the binary, followed by orbital decay and circularization due to tidal dissipation in the stars. Here we explore the orbital evolution of planets around binaries undergoing orbital decay by this mechanism. We show that planets may survive and become misaligned from their host binary, or may develop erratic behavior in eccentricity, resulting in their consumption by the stars or ejection from the system as the binary decays. Our results suggest that circumbinary planets around compact binaries could still exist, and we offer predictions as to what their orbital configurations should be like. PMID:26159412

Survival of planets around shrinking stellar binaries.

PubMed

Muñoz, Diego J; Lai, Dong

2015-07-28

The discovery of transiting circumbinary planets by the Kepler mission suggests that planets can form efficiently around binary stars. None of the stellar binaries currently known to host planets has a period shorter than 7 d, despite the large number of eclipsing binaries found in the Kepler target list with periods shorter than a few days. These compact binaries are believed to have evolved from wider orbits into their current configurations via the so-called Lidov-Kozai migration mechanism, in which gravitational perturbations from a distant tertiary companion induce large-amplitude eccentricity oscillations in the binary, followed by orbital decay and circularization due to tidal dissipation in the stars. Here we explore the orbital evolution of planets around binaries undergoing orbital decay by this mechanism. We show that planets may survive and become misaligned from their host binary, or may develop erratic behavior in eccentricity, resulting in their consumption by the stars or ejection from the system as the binary decays. Our results suggest that circumbinary planets around compact binaries could still exist, and we offer predictions as to what their orbital configurations should be like.

Search for Gravitational Waves from Low Mass Compact Binary Coalescence in LIGO's Sixth Science Run and Virgo's Science Runs 2 and 3

NASA Technical Reports Server (NTRS)

Abadie, J.; Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M.; Accadia, T.; Acernese, F.; Adams, C.; Adhikari, R.; Affeldt, C.;

Search for gravitational waves from low mass compact binary coalescence in LIGO's sixth science run and Virgo's science runs 2 and 3

NASA Astrophysics Data System (ADS)

Abadie, J.; Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M.; Accadia, T.; Acernese, F.; Adams, C.; Adhikari, R.; Affeldt, C.; Agathos, M.; Ajith, P.; Allen, B.; Allen, G. S.; Amador Ceron, E.; Amariutei, D.; Amin, R. S.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Arain, M. A.; Araya, M. C.; Aston, S. M.; Astone, P.; Atkinson, D.; Aufmuth, P.; Aulbert, C.; Aylott, B. E.; Babak, S.; Baker, P.; Ballardin, G.; Ballmer, S.; Barker, D.; Barone, F.; Barr, B.; Barriga, P.; Barsotti, L.; Barsuglia, M.; Barton, M. A.; Bartos, I.; Bassiri, R.; Bastarrika, M.; Basti, A.; Batch, J.; Bauchrowitz, J.; Bauer, Th. S.; Bebronne, M.; Behnke, B.; Beker, M. G.; Bell, A. S.; Belletoile, A.; Belopolski, I.; Benacquista, M.; Berliner, J. M.; Bertolini, A.; Betzwieser, J.; Beveridge, N.; Beyersdorf, P. T.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Biswas, R.; Bitossi, M.; Bizouard, M. A.; Black, E.; Blackburn, J. K.; Blackburn, L.; Blair, D.; Bland, B.; Blom, M.; Bock, O.; Bodiya, T. P.; Bogan, C.; Bondarescu, R.; Bondu, F.; Bonelli, L.; Bonnand, R.; Bork, R.; Born, M.; Boschi, V.; Bose, S.; Bosi, L.; Bouhou, B.; Braccini, S.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Breyer, J.; Briant, T.; Bridges, D. O.; Brillet, A.; Brinkmann, M.; Brisson, V.; Britzger, M.; Brooks, A. F.; Brown, D. A.; Brummit, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Burguet–Castell, J.; Burmeister, O.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Calloni, E.; Camp, J. B.; Campsie, P.; Cannizzo, J.; Cannon, K.; Canuel, B.; Cao, J.; Capano, C. D.; Carbognani, F.; Caride, S.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C.; Cesarini, E.; Chaibi, O.; Chalermsongsak, T.; Chalkley, E.; Charlton, P.; Chassande-Mottin, E.; Chelkowski, S.; Chen, Y.; Chincarini, A.; Chiummo, A.; Cho, H.; Christensen, N.; Chua, S. S. Y.; Chung, C. T. Y.; Chung, S.; Ciani, G.; Clara, F.; Clark, D. E.; Clark, J.; Clayton, J. H.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colacino, C. N.; Colas, J.; Colla, A.; Colombini, M.; Conte, A.; Conte, R.; Cook, D.; Corbitt, T. R.; Cordier, M.; Cornish, N.; Corsi, A.; Costa, C. A.; Coughlin, M.; Coulon, J.-P.; Couvares, P.; Coward, D. M.; Coyne, D. C.; Creighton, J. D. E.; Creighton, T. D.; Cruise, A. M.; Cumming, A.; Cunningham, L.; Cuoco, E.; Cutler, R. M.; Dahl, K.; Danilishin, S. L.; Dannenberg, R.; D'Antonio, S.; Danzmann, K.; Dattilo, V.; Daudert, B.; Daveloza, H.; Davier, M.; Davies, G.; Daw, E. J.; Day, R.; Dayanga, T.; De Rosa, R.; DeBra, D.; Debreczeni, G.; Degallaix, J.; Del Pozzo, W.; del Prete, M.; Dent, T.; Dergachev, V.; DeRosa, R.; DeSalvo, R.; Dhurandhar, S.; Di Fiore, L.; Di Lieto, A.; Di Palma, I.; Di Paolo Emilio, M.; Di Virgilio, A.; Díaz, M.; Dietz, A.; DiGuglielmo, J.; Donovan, F.; Dooley, K. L.; Dorsher, S.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Dumas, J.-C.; Dwyer, S.; Eberle, T.; Edgar, M.; Edwards, M.; Effler, A.; Ehrens, P.; Endrőczi, G.; Engel, R.; Etzel, T.; Evans, K.; Evans, M.; Evans, T.; Factourovich, M.; Fafone, V.; Fairhurst, S.; Fan, Y.; Farr, B. F.; Farr, W.; Fazi, D.; Fehrmann, H.; Feldbaum, D.; Ferrante, I.; Fidecaro, F.; Finn, L. S.; Fiori, I.; Fisher, R. P.; Flaminio, R.; Flanigan, M.; Foley, S.; Forsi, E.; Forte, L. A.; Fotopoulos, N.; Fournier, J.-D.; Franc, J.; Frasca, S.; Frasconi, F.; Frede, M.; Frei, M.; Frei, Z.; Freise, A.; Frey, R.; Fricke, T. T.; Friedrich, D.; Fritschel, P.; Frolov, V. V.; Fulda, P. J.; Fyffe, M.; Galimberti, M.; Gammaitoni, L.; Ganija, M. R.; Garcia, J.; Garofoli, J. A.; Garufi, F.; Gáspár, M. E.; Gemme, G.; Geng, R.; Genin, E.; Gennai, A.; Gergely, L. Á.; Ghosh, S.; Giaime, J. A.; Giampanis, S.; Giardina, K. D.; Giazotto, A.; Gill, C.; Goetz, E.; Goggin, L. M.; González, G.; Gorodetsky, M. L.; Goßler, S.; Gouaty, R.; Graef, C.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Gray, N.; Greenhalgh, R. J. S.; Gretarsson, A. M.; Greverie, C.; Grosso, R.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guido, C.; Gupta, R.; Gustafson, E. K.; Gustafson, R.; Ha, T.; Hage, B.; Hallam, J. M.; Hammer, D.; Hammond, G.; Hanks, J.; Hanna, C.; Hanson, J.; Hardt, A.; Harms, J.; Harry, G. M.; Harry, I. W.; Harstad, E. D.; Hartman, M. T.; Haughian, K.; Hayama, K.; Hayau, J.-F.; Heefner, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hendry, M. A.; Heng, I. S.; Heptonstall, A. W.; Herrera, V.; Hewitson, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Holt, K.; Hong, T.; Hooper, S.; Hosken, D. J.; Hough, J.; Howell, E. J.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Ingram, D. R.; Inta, R.; Isogai, T.; Ivanov, A.; Izumi, K.; Jacobson, M.; Jang, H.; Jaranowski, P.; Johnson, W. W.; Jones, D. I.; Jones, G.; Jones, R.; Ju, L.; Kalmus, P.; Kalogera, V.; Kamaretsos, I.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Katsavounidis, E.; Katzman, W.; Kaufer, H.; Kawabe, K.; Kawamura, S.; Kawazoe, F.; Kells, W.; Keppel, D. G.; Keresztes, Z.; Khalaidovski, A.; Khalili, F. Y.; Khazanov, E. A.; Kim, B.; Kim, C.; Kim, D.; Kim, H.; Kim, K.; Kim, N.; Kim, Y.-M.; King, P. J.; Kinsey, M.; Kinzel, D. L.; Kissel, J. S.; Klimenko, S.; Kokeyama, K.; Kondrashov, V.; Kopparapu, R.; Koranda, S.; Korth, W. Z.; Kowalska, I.; Kozak, D.; Kringel, V.; Krishnamurthy, S.; Krishnan, B.; Królak, A.; Kuehn, G.; Kumar, R.; Kwee, P.; Lam, P. K.; Landry, M.; Lang, M.; Lantz, B.; Lastzka, N.; Lawrie, C.; Lazzarini, A.; Leaci, P.; Lee, C. H.; Lee, H. M.; Leindecker, N.; Leong, J. R.; Leonor, I.; Leroy, N.; Letendre, N.; Li, J.; Li, T. G. F.; Liguori, N.; Lindquist, P. E.; Lockerbie, N. A.; Lodhia, D.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Luan, J.; Lubinski, M.; Lück, H.; Lundgren, A. P.; Macdonald, E.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Mageswaran, M.; Mailand, K.; Majorana, E.; Maksimovic, I.; Man, N.; Mandel, I.; Mandic, V.; Mantovani, M.; Marandi, A.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A.; Maros, E.; Marque, J.; Martelli, F.; Martin, I. W.; Martin, R. M.; Marx, J. N.; Mason, K.; Masserot, A.; Matichard, F.; Matone, L.; Matzner, R. A.; Mavalvala, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McGuire, S. C.; McIntyre, G.; McIver, J.; McKechan, D. J. A.; Meadors, G. D.; Mehmet, M.; Meier, T.; Melatos, A.; Melissinos, A. C.; Mendell, G.; Menendez, D.; Mercer, R. A.; Meshkov, S.; Messenger, C.; Meyer, M. S.; Miao, H.; Michel, C.; Milano, L.; Miller, J.; Minenkov, Y.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Miyakawa, O.; Moe, B.; Moesta, P.; Mohan, M.; Mohanty, S. D.; Mohapatra, S. R. P.; Moraru, D.; Moreno, G.; Morgado, N.; Morgia, A.; Mori, T.; Mosca, S.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Mukherjee, S.; Mullavey, A.; Müller-Ebhardt, H.; Munch, J.; Murphy, D.; Murray, P. G.; Mytidis, A.; Nash, T.; Naticchioni, L.; Nawrodt, R.; Necula, V.; Nelson, J.; Newton, G.; Nishizawa, A.; Nocera, F.; Nolting, D.; Nuttall, L.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Oldenburg, R. G.; O'Reilly, B.; O'Shaughnessy, R.; Osthelder, C.; Ott, C. D.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Page, A.; Pagliaroli, G.; Palladino, L.; Palomba, C.; Pan, Y.; Pankow, C.; Paoletti, F.; Papa, M. A.; Parisi, M.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patel, P.; Pedraza, M.; Peiris, P.; Pekowsky, L.; Penn, S.; Peralta, C.; Perreca, A.; Persichetti, G.; Phelps, M.; Pickenpack, M.; Piergiovanni, F.; Pietka, M.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Pletsch, H. J.; Plissi, M. V.; Poggiani, R.; Pöld, J.; Postiglione, F.; Prato, M.; Predoi, V.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prix, R.; Prodi, G. A.; Prokhorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Quetschke, V.; Raab, F. J.; Rabeling, D. S.; Rácz, I.; Radkins, H.; Raffai, P.; Rakhmanov, M.; Ramet, C. R.; Rankins, B.; Rapagnani, P.; Raymond, V.; Re, V.; Redwine, K.; Reed, C. M.; Reed, T.; Regimbau, T.; Reid, S.; Reitze, D. H.; Ricci, F.; Riesen, R.; Riles, K.; Robertson, N. A.; Robinet, F.; Robinson, C.; Robinson, E. L.; Rocchi, A.; Roddy, S.; Rodriguez, C.; Rodruck, M.; Rolland, L.; Rollins, J.; Romano, J. D.; Romano, R.; Romie, J. H.; Rosińska, D.; Röver, C.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Ryll, H.; Sainathan, P.; Sakosky, M.; Salemi, F.; Samblowski, A.; Sammut, L.; Sancho de la Jordana, L.; Sandberg, V.; Sankar, S.; Sannibale, V.; Santamaría, L.; Santiago-Prieto, I.; Santostasi, G.; Sassolas, B.; Sathyaprakash, B. S.; Sato, S.; Saulson, P. R.; Savage, R. L.; Schilling, R.; Schlamminger, S.; Schnabel, R.; Schofield, R. M. S.; Schulz, B.; Schutz, B. F.; Schwinberg, P.; Scott, J.; Scott, S. M.; Searle, A. C.; Seifert, F.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sergeev, A.; Shaddock, D. A.; Shaltev, M.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sibley, A.; Siemens, X.; Sigg, D.; Singer, A.; Singer, L.; Sintes, A. M.; Skelton, G.; Slagmolen, B. J. J.; Slutsky, J.; Smith, J. R.; Smith, M. R.; Smith, N. D.; Smith, R. J. E.; Somiya, K.; Sorazu, B.; Soto, J.; Speirits, F. C.; Sperandio, L.; Stefszky, M.; Stein, A. J.; Steinert, E.; Steinlechner, J.; Steinlechner, S.; Steplewski, S.; Stochino, A.; Stone, R.; Strain, K. A.; Strigin, S.; Stroeer, A. S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sung, M.; Susmithan, S.; Sutton, P. J.; Swinkels, B.; Tacca, M.; Taffarello, L.; Talukder, D.; Tanner, D. B.; Tarabrin, S. P.; Taylor, J. R.; Taylor, R.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Thüring, A.; Titsler, C.; Tokmakov, K. V.; Toncelli, A.; Tonelli, M.; Torre, O.; Torres, C.; Torrie, C. I.; Tournefier, E.; Travasso, F.; Traylor, G.; Trias, M.; Tseng, K.; Tucker, E.; Ugolini, D.; Urbanek, K.; Vahlbruch, H.; Vajente, G.; Vallisneri, M.; van den Brand, J. F. J.; Van Den Broeck, C.; van der Putten, S.; van Veggel, A. A.; Vass, S.; Vasuth, M.; Vaulin, R.; Vavoulidis, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Veltkamp, C.; Verkindt, D.; Vetrano, F.; Viceré, A.; Villar, A. E.; Vinet, J.-Y.; Vitale, S.; Vitale, S.; Vocca, H.; Vorvick, C.; Vyatchanin, S. P.; Wade, A.; Waldman, S. J.; Wallace, L.; Wan, Y.; Wang, X.; Wang, Z.; Wanner, A.; Ward, R. L.; Was, M.; Wei, P.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Wen, S.; Wessels, P.; West, M.; Westphal, T.; Wette, K.; Whelan, J. T.; Whitcomb, S. E.; White, D.; Whiting, B. F.; Wilkinson, C.; Willems, P. A.; Williams, H. R.; Williams, L.; Willke, B.; Winkelmann, L.; Winkler, W.; Wipf, C. C.; Wiseman, A. G.; Wittel, H.; Woan, G.; Wooley, R.; Worden, J.; Yablon, J.; Yakushin, I.; Yamamoto, H.; Yamamoto, K.; Yang, H.; Yeaton-Massey, D.; Yoshida, S.; Yu, P.; Yvert, M.; Zadroźny, A.; Zanolin, M.; Zendri, J.-P.; Zhang, F.; Zhang, L.; Zhang, W.; Zhang, Z.; Zhao, C.; Zotov, N.; Zucker, M. E.; Zweizig, J.

2012-04-01

We report on a search for gravitational waves from coalescing compact binaries using LIGO and Virgo observations between July 7, 2009, and October 20, 2010. We searched for signals from binaries with total mass between 2 and 25M⊙; this includes binary neutron stars, binary black holes, and binaries consisting of a black hole and neutron star. The detectors were sensitive to systems up to 40 Mpc distant for binary neutron stars, and further for higher mass systems. No gravitational-wave signals were detected. We report upper limits on the rate of compact binary coalescence as a function of total mass, including the results from previous LIGO and Virgo observations. The cumulative 90% confidence rate upper limits of the binary coalescence of binary neutron star, neutron star-black hole, and binary black hole systems are 1.3×10-4, 3.1×10-5, and 6.4×10-6Mpc-3yr-1, respectively. These upper limits are up to a factor 1.4 lower than previously derived limits. We also report on results from a blind injection challenge.

An approach for combining airborne LiDAR and high-resolution aerial color imagery using Gaussian processes

NASA Astrophysics Data System (ADS)

Liu, Yansong; Monteiro, Sildomar T.; Saber, Eli

2015-10-01

Changes in vegetation cover, building construction, road network and traffic conditions caused by urban expansion affect the human habitat as well as the natural environment in rapidly developing cities. It is crucial to assess these changes and respond accordingly by identifying man-made and natural structures with accurate classification algorithms. With the increase in use of multi-sensor remote sensing systems, researchers are able to obtain a more complete description of the scene of interest. By utilizing multi-sensor data, the accuracy of classification algorithms can be improved. In this paper, we propose a method for combining 3D LiDAR point clouds and high-resolution color images to classify urban areas using Gaussian processes (GP). GP classification is a powerful non-parametric classification method that yields probabilistic classification results. It makes predictions in a way that addresses the uncertainty of real world. In this paper, we attempt to identify man-made and natural objects in urban areas including buildings, roads, trees, grass, water and vehicles. LiDAR features are derived from the 3D point clouds and the spatial and color features are extracted from RGB images. For classification, we use the Laplacian approximation for GP binary classification on the new combined feature space. The multiclass classification has been implemented by using one-vs-all binary classification strategy. The result of applying support vector machines (SVMs) and logistic regression (LR) classifier is also provided for comparison. Our experiments show a clear improvement of classification results by using the two sensors combined instead of each sensor separately. Also we found the advantage of applying GP approach to handle the uncertainty in classification result without compromising accuracy compared to SVM, which is considered as the state-of-the-art classification method.

Examining the link between public transit use and active commuting.

PubMed

Bopp, Melissa; Gayah, Vikash V; Campbell, Matthew E

2015-04-17

An established relationship exists between public transportation (PT) use and physical activity. However, there is limited literature that examines the link between PT use and active commuting (AC) behavior. This study examines this link to determine if PT users commute more by active modes. A volunteer, convenience sample of adults (n = 748) completed an online survey about AC/PT patterns, demographic, psychosocial, community and environmental factors. t-test compared differences between PT riders and non-PT riders. Binary logistic regression analyses examined the effect of multiple factors on AC and a full logistic regression model was conducted to examine AC. Non-PT riders (n = 596) reported less AC than PT riders. There were several significant relationships with AC for demographic, interpersonal, worksite, community and environmental factors when considering PT use. The logistic multivariate analysis for included age, number of children and perceived distance to work as negative predictors and PT use, feelings of bad weather and lack of on-street bike lanes as a barrier to AC, perceived behavioral control and spouse AC were positive predictors. This study revealed the complex relationship between AC and PT use. Further research should investigate how AC and public transit use are related.

Predictors of Smoking among Saudi Dental Students in Jeddah.

PubMed

Mansour, Ameerah Y

2017-05-01

The objective of this study was to assess tobacco use, secondhand smoke exposure, knowledge of health risks, and smoking predictors among dental students attending King Abdulaziz University, Jeddah, Saudi Arabia. A cross-sectional study was conducted and 420 dental students were invited to participate. Binary logistic regression analyses assessed the predictors of smoking. A total of 336 dental students completed the questionnaires with 25% reporting current or previous tobacco use and 96% reporting secondhand smoke exposure. Nearly half of all smokers initiated smoking during the dental program. The logistic regression results revealed that being a male (OR = 7.1, p < .0001; 95%CI = 3.7-13.4) and having a smoker in the family (OR = 2.6, p = .005; 95%CI = 1.3-5.0) increased the likelihood of smoking. In contrast, knowledge of health risks decreased the likelihood of smoking (OR = 0.90, p = .014; 95%CI = 0.82-0.98). Despite possessing knowledge about the health risks of smoking, high numbers of dental students continue to smoke and were exposed to secondhand smoke. Sex and family influence were the main pro-smoking risk factors, whereas increased knowledge of health risks was a protective factor. Tobacco control programs to reduce and/or prevent tobacco use among future dentists are needed.

Age at onset of major depressive disorder in Han Chinese women: Relationship with clinical features and family history☆

PubMed Central

Yang, Fuzhong; Li, Yihan; Xie, Dong; Shao, Chunhong; Ren, Jianer; Wu, Wenyuan; Zhang, Ning; Zhang, Zhen; Zou, Ying; Zhang, Jiulong; Qiao, Dongdong; Gao, Chengge; Li, Youhui; Hu, Jian; Deng, Hong; Wang, Gang; Du, Bo; Wang, Xumei; Liu, Tiebang; Gan, Zhaoyu; Peng, Juyi; Wei, Bo; Pan, Jiyang; Chen, Honghui; Sun, Shufan; Jia, Hong; Liu, Ying; Chen, Qiaoling; Wang, Xueyi; Cao, Juling; Lv, Luxian; Chen, Yunchun; Ha, Baowei; Ning, Yuping; Chen, YiPing; Kendler, Kenneth S.; Flint, Jonathan; Shi, Shenxun

2011-01-01

Background Individuals with early-onset depression may be a clinically distinct group with particular symptom patterns, illness course, comorbidity and family history. This question has not been previously investigated in a Han Chinese population. Methods We examined the clinical features of 1970 Han Chinese women with DSM-IV major depressive disorder (MDD) between 30 and 60 years of age across China. Analysis of linear, logistic and multiple logistic regression models was used to determine the association between age at onset (AAO) with continuous, binary and discrete characteristic clinical features of MDD. Results Earlier AAO was associated with more suicidal ideation and attempts and higher neuroticism, but fewer sleep, appetite and weight changes. Patients with an earlier AAO were more likely to suffer a chronic course (longer illness duration, more MDD episodes and longer index episode), increased rates of MDD in their parents and a lower likelihood of marriage. They tend to have higher comorbidity with anxiety disorders (general anxiety disorder, social phobia and agoraphobia) and dysthymia. Conclusions Early AAO in MDD may be an index of a more severe, highly comorbid and familial disorder. Our findings indicate that the features of MDD in China are similar to those reported elsewhere in the world. PMID:21782247

Beyond the Binary: Differences in Eating Disorder Prevalence by Gender Identity in a Transgender Sample.

PubMed

Diemer, Elizabeth W; White Hughto, Jaclyn M; Gordon, Allegra R; Guss, Carly; Austin, S Bryn; Reisner, Sari L

2018-01-01

Purpose: To investigate whether the prevalence of eating disorders (EDs) differs across diverse gender identity groups in a transgender sample. Methods: Secondary analysis of data from Project VOICE, a cross-sectional study of stress and health among 452 transgender adults (ages 18-75 years) residing in Massachusetts. Age-adjusted logistic regression models were fit to compare the prevalence of self-reported lifetime EDs in female-to-male (FTM), male-to-female (MTF), and gender-nonconforming participants assigned male at birth (MBGNC) to gender-nonconforming participants assigned female at birth (FBGNC; referent). Results: The age-adjusted odds of self-reported ED in MTF participants were 0.14 times the odds of self-reported ED in FBGNC participants ( p =0.022). In FTM participants, the age-adjusted odds of self-reported ED were 0.46 times the odds of self-reported ED in FBGNC participants, a marginally significant finding ( p =0.068). No statistically significant differences in ED prevalence were found for MBGNC individuals. Conclusions: Gender nonconforming individuals assigned a female sex at birth appear to have heightened lifetime risk of EDs relative to MTF participants. Further research into specific biologic and psychosocial ED risk factors and gender-responsive intervention strategies are urgently needed. Training clinical providers and ensuring competency of treatment services beyond the gender binary will be vital to addressing this disparity.

SMARTbot: A Behavioral Analysis Framework Augmented with Machine Learning to Identify Mobile Botnet Applications

PubMed Central

Karim, Ahmad; Salleh, Rosli; Khan, Muhammad Khurram

2016-01-01

Botnet phenomenon in smartphones is evolving with the proliferation in mobile phone technologies after leaving imperative impact on personal computers. It refers to the network of computers, laptops, mobile devices or tablets which is remotely controlled by the cybercriminals to initiate various distributed coordinated attacks including spam emails, ad-click fraud, Bitcoin mining, Distributed Denial of Service (DDoS), disseminating other malwares and much more. Likewise traditional PC based botnet, Mobile botnets have the same operational impact except the target audience is particular to smartphone users. Therefore, it is import to uncover this security issue prior to its widespread adaptation. We propose SMARTbot, a novel dynamic analysis framework augmented with machine learning techniques to automatically detect botnet binaries from malicious corpus. SMARTbot is a component based off-device behavioral analysis framework which can generate mobile botnet learning model by inducing Artificial Neural Networks’ back-propagation method. Moreover, this framework can detect mobile botnet binaries with remarkable accuracy even in case of obfuscated program code. The results conclude that, a classifier model based on simple logistic regression outperform other machine learning classifier for botnet apps’ detection, i.e 99.49% accuracy is achieved. Further, from manual inspection of botnet dataset we have extracted interesting trends in those applications. As an outcome of this research, a mobile botnet dataset is devised which will become the benchmark for future studies. PMID:26978523

Beyond the Binary: Differences in Eating Disorder Prevalence by Gender Identity in a Transgender Sample

PubMed Central

Diemer, Elizabeth W.; White Hughto, Jaclyn M.; Gordon, Allegra R.; Guss, Carly; Austin, S. Bryn; Reisner, Sari L.

2018-01-01

Abstract Purpose: To investigate whether the prevalence of eating disorders (EDs) differs across diverse gender identity groups in a transgender sample. Methods: Secondary analysis of data from Project VOICE, a cross-sectional study of stress and health among 452 transgender adults (ages 18–75 years) residing in Massachusetts. Age-adjusted logistic regression models were fit to compare the prevalence of self-reported lifetime EDs in female-to-male (FTM), male-to-female (MTF), and gender-nonconforming participants assigned male at birth (MBGNC) to gender-nonconforming participants assigned female at birth (FBGNC; referent). Results: The age-adjusted odds of self-reported ED in MTF participants were 0.14 times the odds of self-reported ED in FBGNC participants (p=0.022). In FTM participants, the age-adjusted odds of self-reported ED were 0.46 times the odds of self-reported ED in FBGNC participants, a marginally significant finding (p=0.068). No statistically significant differences in ED prevalence were found for MBGNC individuals. Conclusions: Gender nonconforming individuals assigned a female sex at birth appear to have heightened lifetime risk of EDs relative to MTF participants. Further research into specific biologic and psychosocial ED risk factors and gender-responsive intervention strategies are urgently needed. Training clinical providers and ensuring competency of treatment services beyond the gender binary will be vital to addressing this disparity. PMID:29359198

SMARTbot: A Behavioral Analysis Framework Augmented with Machine Learning to Identify Mobile Botnet Applications.

PubMed

Karim, Ahmad; Salleh, Rosli; Khan, Muhammad Khurram

2016-01-01

Botnet phenomenon in smartphones is evolving with the proliferation in mobile phone technologies after leaving imperative impact on personal computers. It refers to the network of computers, laptops, mobile devices or tablets which is remotely controlled by the cybercriminals to initiate various distributed coordinated attacks including spam emails, ad-click fraud, Bitcoin mining, Distributed Denial of Service (DDoS), disseminating other malwares and much more. Likewise traditional PC based botnet, Mobile botnets have the same operational impact except the target audience is particular to smartphone users. Therefore, it is import to uncover this security issue prior to its widespread adaptation. We propose SMARTbot, a novel dynamic analysis framework augmented with machine learning techniques to automatically detect botnet binaries from malicious corpus. SMARTbot is a component based off-device behavioral analysis framework which can generate mobile botnet learning model by inducing Artificial Neural Networks' back-propagation method. Moreover, this framework can detect mobile botnet binaries with remarkable accuracy even in case of obfuscated program code. The results conclude that, a classifier model based on simple logistic regression outperform other machine learning classifier for botnet apps' detection, i.e 99.49% accuracy is achieved. Further, from manual inspection of botnet dataset we have extracted interesting trends in those applications. As an outcome of this research, a mobile botnet dataset is devised which will become the benchmark for future studies.

The Prevalence of Antenatal Depression and its Related Factors in Chinese Pregnant Women who Present with Obstetrical Complications.

PubMed

Zhao, Ying; Kane, Irene; Mao, Liping; Shi, Shenxun; Wang, Jing; Lin, Qiping; Luo, Jianfeng

2016-06-01

The psychological status of Chinese pregnant women who present with obstetrical complications is concerning to Chinese health professionals. This study aimed to investigate the prevalence of antenatal depression and analyzed related risk factors in a population of high-risk Chinese women. A large sample size, cross-sectional study. A total of 842 pregnant women with complications completed the Chinese version of the Postpartum Depression Screen Scale (PDSS) in this cross-sectional study. t-Test, ANOVA and Binary logistic regression tests were used in data analysis of antenatal depression and risk factors. The prevalence of major or minor depression in high-risk Chinese pregnant women during antenatal period was 8.3% and 28.9%, respectively. Independent-sample t-test and two-way analysis of variance (ANOVA) indicated significant differences in age, education, occupation and the number of complications (P<0.05). Binary logistic regression analysis indicated a significant negative association between depression and education (P<0.01) with lower educational level (OR: 0.590; 95% CI: 0.424-0.820) associated with a higher risk for depression. A significant positive association was observed between depression and age (P<0.05) with higher age (OR: 1.338; 95% CI: 1.008-1.774) correlated with a higher risk for depression. Women who experienced obstetric complications presented with higher PDSS depression scores. Screening for antenatal depression in high-risk pregnant women to promote early detection of depression and reduce health risks for universal health promotion is recommended. Copyright © 2015 Elsevier Inc. All rights reserved.

Electronic health record analysis via deep poisson factor models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

[Developing a predictive model for the caregiver strain index].

PubMed

Álvarez-Tello, Margarita; Casado-Mejía, Rosa; Praena-Fernández, Juan Manuel; Ortega-Calvo, Manuel

Patient homecare with multiple morbidities is an increasingly common occurrence. The caregiver strain index is tool in the form of questionnaire that is designed to measure the perceived burden of those who care for their families. The aim of this study is to construct a diagnostic nomogram of informal caregiver burden using data from a predictive model. The model was drawn up using binary logistic regression and the questionnaire items as dichotomous factors. The dependent variable was the final score obtained with the questionnaire but categorised in accordance with that in the literature. Scores between 0 and 6 were labelled as "no" (no caregiver stress) and at or greater than 7 as "yes". The version 3.1.1R statistical software was used. To construct confidence intervals for the ROC curve 2000 boot strap replicates were used. A sample of 67 caregivers was obtained. A diagnosing nomogram was made up with its calibration graph (Brier scaled = 0.686, Nagelkerke R 2 =0.791), and the corresponding ROC curve (area under the curve=0.962). The predictive model generated using binary logistic regression and the nomogram contain four items (1, 4, 5 and 9) of the questionnaire. R plotting functions allow a very good solution for validating a model like this. The area under the ROC curve (0.96; 95% CI: 0.994-0.941) achieves a high discriminative value. Calibration also shows high goodness of fit values, suggesting that it may be clinically useful in community nursing and geriatric establishments. Copyright © 2015 SEGG. Publicado por Elsevier España, S.L.U. All rights reserved.

Electronic health record analysis via deep poisson factor models

DOE PAGES

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.; ...

2016-01-01

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Injury risk functions for frontal oblique collisions.

PubMed

Andricevic, Nino; Junge, Mirko; Krampe, Jonas

2018-03-09

The objective of this article was the construction of injury risk functions (IRFs) for front row occupants in oblique frontal crashes and a comparison to IRF of nonoblique frontal crashes from the same data set. Crashes of modern vehicles from GIDAS (German In-Depth Accident Study) were used as the basis for the construction of a logistic injury risk model. Static deformation, measured via displaced voxels on the postcrash vehicles, was used to calculate the energy dissipated in the crash. This measure of accident severity was termed objective equivalent speed (oEES) because it does not depend on the accident reconstruction and thus eliminates reconstruction biases like impact direction and vehicle model year. Imputation from property damage cases was used to describe underrepresented low-severity crashes-a known shortcoming of GIDAS. Binary logistic regression was used to relate the stimuli (oEES) to the binary outcome variable (injured or not injured). IRFs for the oblique frontal impact and nonoblique frontal impact were computed for the Maximum Abbreviated Injury Scale (MAIS) 2+ and 3+ levels for adults (18-64 years). For a given stimulus, the probability of injury for a belted driver was higher in oblique crashes than in nonoblique frontal crashes. For the 25% injury risk at MAIS 2+ level, the corresponding stimulus for oblique crashes was 40 km/h but it was 64 km/h for nonoblique frontal crashes. The risk of obtaining MAIS 2+ injuries is significantly higher in oblique crashes than in nonoblique crashes. In the real world, most MAIS 2+ injuries occur in an oEES range from 30 to 60 km/h.

Classification and regression tree analysis vs. multivariable linear and logistic regression methods as statistical tools for studying haemophilia.

PubMed

Henrard, S; Speybroeck, N; Hermans, C

2015-11-01

Haemophilia is a rare genetic haemorrhagic disease characterized by partial or complete deficiency of coagulation factor VIII, for haemophilia A, or IX, for haemophilia B. As in any other medical research domain, the field of haemophilia research is increasingly concerned with finding factors associated with binary or continuous outcomes through multivariable models. Traditional models include multiple logistic regressions, for binary outcomes, and multiple linear regressions for continuous outcomes. Yet these regression models are at times difficult to implement, especially for non-statisticians, and can be difficult to interpret. The present paper sought to didactically explain how, why, and when to use classification and regression tree (CART) analysis for haemophilia research. The CART method is non-parametric and non-linear, based on the repeated partitioning of a sample into subgroups based on a certain criterion. Breiman developed this method in 1984. Classification trees (CTs) are used to analyse categorical outcomes and regression trees (RTs) to analyse continuous ones. The CART methodology has become increasingly popular in the medical field, yet only a few examples of studies using this methodology specifically in haemophilia have to date been published. Two examples using CART analysis and previously published in this field are didactically explained in details. There is increasing interest in using CART analysis in the health domain, primarily due to its ease of implementation, use, and interpretation, thus facilitating medical decision-making. This method should be promoted for analysing continuous or categorical outcomes in haemophilia, when applicable. © 2015 John Wiley & Sons Ltd.

Relationship between postoperative lung atelectasis and position of the endotracheal tube in pediatric living-donor liver transplantation.

PubMed

Lee, H-Y; Lu, C-H; Lu, H-F; Chen, C-L; Wang, C-H; Cheng, K-W; Wu, S-C; Jawan, B; Huang, C-J

2012-05-01

The aims of current study were: 1) to evaluate the incidence of lung atelectasis; and 2) to investigate whether or not the position of the endotracheal (ET) tube is associated with this complication. The medical records and chest roentgenograms of 183 pediatric patients who underwent living-donor liver transplantation were retrospectively reviewed and analyzed. Patients without atelectasis were grouped in group I (GI) and those with atelectasis in group II (GII). The patients' characteristics and ET tube level between groups were compared with unpaired Student's t test. Multiple binary logistic regressions were also performed to identify the important risk factors associated with lung atelectasis. Right upper lung (RUL) atelectsis could be found in ET tube at any level from T1 to T5, with incidence rates of 12.7%, 15.2%, 26.3%, 6.7%, and 100% for T1, T2, T3, T4, and T5, respectively. The incidence of atelectasis is 16.6%, and all of the atelectasis occurred in the RUL. No significant difference between groups was observed in the patients' characteristics, except for the amount of preoperative ascites. The likelihood of this risk factor could not be confirmed by multivariate binary logistic regression analysis. The incidence of lung atelectasis in our study was 16.6%, which all occurred in the RUL. No predictive risk factor from the patients' characteristics could be found, and no correlation between the level of the ET tube and the occurrence of RUL atelectasis could be observed. Copyright © 2012 Elsevier Inc. All rights reserved.

Mental health, employment and gender. Cross-sectional evidence in a sample of refugees from Bosnia-Herzegovina living in two Swedish regions.

PubMed

Blight, Karin Johansson; Ekblad, Solvig; Persson, Jan-Olov; Ekberg, Jan

2006-04-01

Large regional differences regarding access to employment have been observed amongst persons from Bosnia-Herzegovina coming to Sweden in 1993-1994. This has led to questions about the role of mental health. To explore this further, postal survey questionnaires were distributed to a community sample (N = 650) that was stratified and, within strata, randomly selected from a sampling frame of persons coming to Sweden from Bosnia-Herzegovina in 1993-1994. Four hundred and thirteen persons returned the questionnaire providing a response rate of 63.5%. The aim was to increase knowledge about the relationship between mental health and employment in the chosen population. The main mental health outcome measure was the Göteborg Quality of Life instrument from which 360 respondents were grouped according to low or high symptom levels. Data were cross tabulated (chi2-tested) against background variables such as age, gender and occupational status, and then tested using binary logistic regression. Binary logistic regression revealed unemployed men but not women, and women who had been working for longer periods during 1993-1999, to be associated with high levels of symptoms of poor mental health. Women living in the urban region were also overrepresented in the high symptom group. These findings indicate that, job occupancy is important to the health of men in the study. However, for the women, further understanding is needed, as job occupancy at some level as well as living in the urban region appear to be associated with poor mental health.

A predictive model for diagnosing bipolar disorder based on the clinical characteristics of major depressive episodes in Chinese population.

PubMed

Gan, Zhaoyu; Diao, Feici; Wei, Qinling; Wu, Xiaoli; Cheng, Minfeng; Guan, Nianhong; Zhang, Ming; Zhang, Jinbei

2011-11-01

A correct timely diagnosis of bipolar depression remains a big challenge for clinicians. This study aimed to develop a clinical characteristic based model to predict the diagnosis of bipolar disorder among patients with current major depressive episodes. A prospective study was carried out on 344 patients with current major depressive episodes, with 268 completing 1-year follow-up. Data were collected through structured interviews. Univariate binary logistic regression was conducted to select potential predictive variables among 19 initial variables, and then multivariate binary logistic regression was performed to analyze the combination of risk factors and build a predictive model. Receiver operating characteristic (ROC) curve was plotted. Of 19 initial variables, 13 variables were preliminarily selected, and then forward stepwise exercise produced a final model consisting of 6 variables: age at first onset, maximum duration of depressive episodes, somatalgia, hypersomnia, diurnal variation of mood, irritability. The correct prediction rate of this model was 78% (95%CI: 75%-86%) and the area under the ROC curve was 0.85 (95%CI: 0.80-0.90). The cut-off point for age at first onset was 28.5 years old, while the cut-off point for maximum duration of depressive episode was 7.5 months. The limitations of this study include small sample size, relatively short follow-up period and lack of treatment information. Our predictive models based on six clinical characteristics of major depressive episodes prove to be robust and can help differentiate bipolar depression from unipolar depression. Copyright © 2011 Elsevier B.V. All rights reserved.

Analysis of Radiation Effects in Digital Subtraction Angiography of Intracranial Artery Stenosis.

PubMed

Guo, Chaoqun; Shi, Xiaolei; Ding, Xianhui; Zhou, Zhiming

2018-04-21

Intracranial artery stenosis (IAS) is the most common cause for acute cerebral accidents. Digital subtraction angiography (DSA) is the gold standard to detect IAS and usually brings excess radiation exposure to examinees and examiners. The artery pathology might influence the interventional procedure, causing prolonged radiation effects. However, no studies on the association between IAS pathology and operational parameters are available. A retrospective analysis was conducted on 93 patients with first-ever stroke/transient ischemic attack, who received DSA examination within 3 months from onset in this single center. Comparison of baseline characteristics was determined by 2-tailed Student's t-test or the chi-square test between subjects with and without IAS. A binary logistic regression analysis was performed to determine the association between IAS pathology and the items with a P value <0.05 in Student's t-test or chi-square test. There were 93 candidates (42 with IAS and 51 without IAS) in this study. The 2 groups shared no significance of the baseline characteristics (P > 0.05). We found a significantly higher total time, higher kerma area product, greater total dose, and greater DSA dose in the IAS group than in those without IAS (P < 0.05). A binary logistic regression analysis indicated the significant association between total time and IAS pathology (P < 0.05) but no significance in kerma area product, radiation dose, and DSA dose (P > 0.05). IAS pathology would indicate a prolonged total time of DSA procedure in clinical practice. However, the radiation effects would not change with pathologic changes. Copyright © 2018 Elsevier Inc. All rights reserved.

The Impact of Binary Companions on Planetary Systems

NASA Astrophysics Data System (ADS)

Kraus, Adam L.; Ireland, Michael; Dupuy, Trent; Mann, Andrew; Huber, Daniel

2018-01-01

The majority of solar-type stars are found in binary systems, and the dynamical influence of binary companions is expected to profoundly influence planetary systems. However, the difficulty of identifying planets in binary systems has left the magnitude of this effect uncertain; despite numerous theoretical hurdles to their formation and survival, at least some binary systems clearly host planets. We present high-resolution imaging of nearly 500 Kepler Objects of Interest (KOIs) obtained using adaptive-optics imaging and nonredundant aperture-mask interferometry on the Keck II telescope. We super-resolve some binary systems to projected separations of under 5 AU, showing that planets might form in these dynamically active environments. However, the full distribution of projected separations for our planet-host sample more broadly reveals a deep paucity of binary companions at solar-system scales. Our results demonstrate that a fifth of all solar-type stars in the Milky Way are disallowed from hosting planetary systems due to the influence of a binary companion. We now update these results with multi-epoch imaging to reject non-comoving background stars and securely identify even the least massive stellar companions, as well as tracing out the orbital motion of stellar companions. These results are beginning to reveal not just the fraction of binaries that do not host planets, but also potential explanations for planet survival even in some very close, dynamically active binary systems.

WIYN OPEN CLUSTER STUDY. XLVIII. THE HARD-BINARY POPULATION OF NGC 188

DOE Office of Scientific and Technical Information (OSTI.GOV)

Geller, Aaron M.; Mathieu, Robert D., E-mail: a-geller@northwestern.edu, E-mail: mathieu@astro.wisc.edu

2012-08-15

We present an in-depth study of the hard-binary population of the old (7 Gyr) open cluster NGC 188. Utilizing 85 spectroscopic binary orbits out of a complete sample of 129 detected binary members, we study the cluster binary frequency and the distributions of binary orbital elements among the main-sequence (MS), giant, and blue straggler (BS) populations. The results are derived from our ongoing radial velocity survey of the cluster, which spans in magnitude from the brightest stars in the cluster to V = 16.5 (about 1.1-0.9 M{sub Sun} ), and extends to a projected radius of 17 pc ({approx}13 coremore » radii). Our detectable binaries have periods ranging from a few days to of order 10{sup 4} days, and thus are hard binaries that dynamically power the cluster. The MS solar-type hard binaries in NGC 188 are nearly indistinguishable from similar binaries in the Galactic field. We observe a global solar-type MS hard-binary frequency in NGC 188 of 23% {+-} 2%, which when corrected for incompleteness results in a frequency of 29% {+-} 3% for binaries with periods less than 10{sup 4} days. For MS hard binaries in the cluster, we observe a log-period distribution that rises toward our detection limit, a roughly Gaussian eccentricity distribution centered on e = 0.35 (for binaries with periods longer than the circularization period), and a secondary-mass distribution that rises toward lower-mass companions. Importantly, the NGC 188 BS binaries show significantly different characteristics than the solar-type MS binaries in NGC 188. We observe a BS hard-binary frequency of 76% {+-} 19%, three times that of the MS. The excess of this binary frequency over the normal MS binary frequency is valid at the >99% confidence level. Furthermore, the BS binary eccentricity-log-period distribution is distinct from that of the MS at the 99% confidence level, with the majority of the BS binaries having periods of order 1000 days and lower eccentricities. The secondary-mass distribution for these long-period BS binaries is narrow and peaked with a mean value of about 0.5 M{sub Sun }. Predictions for mass-transfer products are most closely consistent with the binary properties of these NGC 188 BSs, which comprise two-thirds of the BS population. Additionally, we compare the NGC 188 binaries to those evolved within the sophisticated Hurley et al. (2005) N-body open cluster simulation. The MS hard-binary population predicted by the simulation is significantly different from the MS hard-binary population observed in NGC 188, in frequency and distributions of period and eccentricity. Many of these differences result from the adopted initial binary population, while others reflect on the physics used in the simulation (e.g., tidal circularization). Additional simulations with initial conditions that are better motivated by observations are necessary to properly investigate the dynamical evolution of a rich binary population in open clusters like NGC 188.« less

The formation of high-mass binary star systems

NASA Astrophysics Data System (ADS)

Lund, Kristin; Bonnell, Ian A.

2018-06-01

We develop a semi-analytic model to investigate how accretion onto wide low-mass binary stars can result in a close high-mass binary system. The key ingredient is to allow mass accretion while limiting the gain in angular momentum. We envision this process as being regulated by an external magnetic field during infall. Molecular clouds are made to collapse spherically with material either accreting onto the stars or settling in a disk. Our aim is to determine what initial conditions are needed for the resulting binary to be both massive and close. Whether material accretes, and what happens to the binary separation as a result, depends on the relative size of its specific angular momentum, compared to the specific angular momentum of the binary. When we add a magnetic field we are introducing a torque to the system which is capable of stripping the molecular cloud of some of its angular momentum, and consequently easing the formation of high-mass binaries. Our results suggest that clouds in excess of 1000 M⊙ and radii of 0.5 pc or larger, can easily form binary systems with masses in excess of 25 M⊙ and separations of order 10 R⊙ with magnetic fields of order 100 μG (mass-to-flux ratios of order 5).

The role of multicollinearity in landslide susceptibility assessment by means of Binary Logistic Regression: comparison between VIF and AIC stepwise selection

NASA Astrophysics Data System (ADS)

Cama, Mariaelena; Cristi Nicu, Ionut; Conoscenti, Christian; Quénéhervé, Geraldine; Maerker, Michael

2016-04-01

Landslide susceptibility can be defined as the likelihood of a landslide occurring in a given area on the basis of local terrain conditions. In the last decades many research focused on its evaluation by means of stochastic approaches under the assumption that 'the past is the key to the future' which means that if a model is able to reproduce a known landslide spatial distribution, it will be able to predict the future locations of new (i.e. unknown) slope failures. Among the various stochastic approaches, Binary Logistic Regression (BLR) is one of the most used because it calculates the susceptibility in probabilistic terms and its results are easily interpretable from a geomorphological point of view. However, very often not much importance is given to multicollinearity assessment whose effect is that the coefficient estimates are unstable, with opposite sign and therefore difficult to interpret. Therefore, it should be evaluated every time in order to make a model whose results are geomorphologically correct. In this study the effects of multicollinearity in the predictive performance and robustness of landslide susceptibility models are analyzed. In particular, the multicollinearity is estimated by means of Variation Inflation Index (VIF) which is also used as selection criterion for the independent variables (VIF Stepwise Selection) and compared to the more commonly used AIC Stepwise Selection. The robustness of the results is evaluated through 100 replicates of the dataset. The study area selected to perform this analysis is the Moldavian Plateau where landslides are among the most frequent geomorphological processes. This area has an increasing trend of urbanization and a very high potential regarding the cultural heritage, being the place of discovery of the largest settlement belonging to the Cucuteni Culture from Eastern Europe (that led to the development of the great complex Cucuteni-Tripyllia). Therefore, identifying the areas susceptible to landslides may lead to a better understanding and mitigation for government, local authorities and stakeholders to plan the economic activities, minimize the damages costs, environmental and cultural heritage protection. The results show that although the VIF Stepwise selection allows a more stable selection of the controlling factors, the AIC Stepwise selection produces better predictive performance. Moreover, when working with replicates the effect of multicollinearity are statistically reduced by the application of the AIC stepwise selection and the results are easily interpretable in geomorphologic terms.

The special case of the 2 × 2 table: asymptotic unconditional McNemar test can be used to estimate sample size even for analysis based on GEE.

PubMed

Borkhoff, Cornelia M; Johnston, Patrick R; Stephens, Derek; Atenafu, Eshetu

2015-07-01

Aligning the method used to estimate sample size with the planned analytic method ensures the sample size needed to achieve the planned power. When using generalized estimating equations (GEE) to analyze a paired binary primary outcome with no covariates, many use an exact McNemar test to calculate sample size. We reviewed the approaches to sample size estimation for paired binary data and compared the sample size estimates on the same numerical examples. We used the hypothesized sample proportions for the 2 × 2 table to calculate the correlation between the marginal proportions to estimate sample size based on GEE. We solved the inside proportions based on the correlation and the marginal proportions to estimate sample size based on exact McNemar, asymptotic unconditional McNemar, and asymptotic conditional McNemar. The asymptotic unconditional McNemar test is a good approximation of GEE method by Pan. The exact McNemar is too conservative and yields unnecessarily large sample size estimates than all other methods. In the special case of a 2 × 2 table, even when a GEE approach to binary logistic regression is the planned analytic method, the asymptotic unconditional McNemar test can be used to estimate sample size. We do not recommend using an exact McNemar test. Copyright © 2015 Elsevier Inc. All rights reserved.

Health Implications of Adults' Eating at and Living near Fast Food or Quick Service Restaurants

PubMed Central

Jiao, J; Moudon, A V; Kim, S Y; Hurvitz, P M; Drewnowski, A

2015-01-01

Background: This paper examined whether the reported health impacts of frequent eating at a fast food or quick service restaurant on health were related to having such a restaurant near home. Methods: Logistic regressions estimated associations between frequent fast food or quick service restaurant use and health status, being overweight or obese, having a cardiovascular disease or diabetes, as binary health outcomes. In all, 2001 participants in the 2008–2009 Seattle Obesity Study survey were included in the analyses. Results: Results showed eating ⩾2 times a week at a fast food or quick service restaurant was associated with perceived poor health status, overweight and obese. However, living close to such restaurants was not related to negative health outcomes. Conclusions: Frequent eating at a fast food or quick service restaurant was associated with perceived poor health status and higher body mass index, but living close to such facilities was not. PMID:26192449

Who are eating and not eating fruits and vegetables in Malaysia?

PubMed

Yen, Steven T; Tan, Andrew K G

2012-12-01

To investigate the roles of sociodemographic factors in fruit and vegetable (FV) consumption in Malaysia. Data are obtained from the Malaysia Non-Communicable Disease Surveillance-1. Logistic regressions are conducted using a multiracial (Malay, Chinese, Indian and other ethnic groups) sample of 2,447 observations to examine the factors affecting individual decisions to consume FV on a daily basis. Based on the binary outcomes of whether individuals consumed FV daily, results indicate that work hours, education, age ethnicity, income, gender, smoking status, and location of residence are significantly correlated with daily fruit consumption. Daily vegetable consumption is significantly correlated with income, gender, health condition, and location of residence. Our results imply the need for programs to educate and motivate consumers to make healthier dietary choices. Interventions to increase FV consumption by changing behaviors should be considered, as should those that increase public awareness of the dietary benefits of FV. These intervention programs should be targeted at and tailored toward individuals who are less educated, younger, less affluent, males, smokers, and metropolitan dwellers.

The impact of HIV antiretroviral treatment perception on risky sexual behaviour in Botswana: a short report.

PubMed

Letamo, Gobopamang; Keetile, Mpho; Navaneetham, Kannan

2017-12-01

The aim of this article is to investigate the impact of ART perception on risky sexual behaviours in Botswana. Using binary logistic regression analysis controlling for individual characteristics, the results tend to support the hypothesis that ART misconceptions do not necessarily increase risky sexual behaviours. In particular, the study findings suggest the belief that ARVs cure HIV and AIDS and that people on ARVs should not always use condoms do not necessarily lead to increased risky sexual behaviours, particularly among women. Gender differentials exist in the perceived sexual risk resulting from the use of ART. Risky sexual behaviours increase for women who, wrongly, believed that ARVs cure HIV and AIDS and people on ARVs should not always use condoms. Although there is evidence to suggest ART perceptions do not necessarily lead to increased risky sexual behaviours, HIV and AIDS prevention programmes are needed to strengthen their information, education and communication intervention component that can address misconceptions about ART treatment and provide correct information that is gender-appropriate.

What we learn from eclipsing binaries in the ultraviolet

NASA Technical Reports Server (NTRS)

Guinan, Edward F.

1990-01-01

Recent results on stars and stellar physics from IUE (International Ultraviolet Explorer) observations of eclipsing binaries are discussed. Several case studies are presented, including V 444 Cyg, Aur stars, V 471 Tau and AR Lac. Topics include stellar winds and mass loss, stellar atmospheres, stellar dynamos, and surface activity. Studies of binary star dynamics and evolution are discussed. The progress made with IUE in understanding the complex dynamical and evolutionary processes taking place in W UMa-type binaries and Algol systems is highlighted. The initial results of intensive studies of the W UMa star VW Cep and three representative Algol-type binaries (in different stages of evolution) focused on gas flows and accretion, are included. The future prospects of eclipsing binary research are explored. Remaining problems are surveyed and the next challenges are presented. The roles that eclipsing binaries could play in studies of stellar evolution, cluster dynamics, galactic structure, mass luminosity relations for extra galactic systems, cosmology, and even possible detection of extra solar system planets using eclipsing binaries are discussed.

FACTORS ASSOCIATED WITH HEALTHCARE UTILIZATION AMONG ARAB IMMIGRANTS AND REFUGEES

PubMed Central

2015-01-01

Background Arab migrants are exposed to pre- and post migration stressors that increase their risk for health problems. However, little is known regarding healthcare utilization rates or factors associated with healthcare utilization among Arab immigrants and refugees. Methods 590 participants were interviewed 1 year post-migration to the United States Factors associated with healthcare utilization including stress coping mechanisms were examined using binary logistic regressions. Results Compared to national healthcare utilization data, immigrants had significantly lower and refugees had significantly higher rates. Being a refugee, married, and having health insurance were significantly associated with medical service utilization. None of the immigrants in this study had utilized psychological services. Among refugees, the use of medications and having strategies for dealing with stress were inversely associated with utilization of psychological services. Discussion (Conclusion) Healthcare utilization was significantly higher among refugees, who also reported a greater need for services than immigrants. PMID:25331684

Certolizumab pegol in a heterogeneous population of patients with moderate-to-severe rheumatoid arthritis

PubMed Central

Soriano, Enrique R; Dellepiane, Analia; Salvatierra, Gabriela; Benítez, Cristian Alejandro; Salinas, Rodrigo Garcia; Baruzzo, Carlos

2018-01-01

Aim: To determine the efficacy and safety of certolizumab pegol for the treatment of rheumatoid arthritis in a real-world setting. Materials & methods: Patients with moderate-to-severe rheumatoid arthritis who initiated therapy with certolizumab were followed for 12 weeks. Response was assessed with Disease Activity Score of 28 joints, European Ligue Against Rheumatism criteria and Simplified Disease Activity Index. Predictors of response were analyzed with binary logistic regression models. Results: Statistically significant decreases in tender and swollen joint counts, laboratory parameters and use of corticosteroids and disease-modifying antirheumatic drugs were found. Disease activity also significantly diminished. Higher Disease Activity Score of 28 joints at baseline was the main predictor of response. No severe adverse events were reported. Conclusion: Certolizumab was effective and well tolerated, particularly in the subpopulation with higher inflammatory burden at baseline. PMID:29682324

Negative Bystander Behavior in Bullying Dynamics: Assessing the Impact of Social Capital Deprivation and Anti-social Capital.

PubMed

Evans, Caroline B R; Smokowski, Paul R

2017-02-01

Bystanders witness bullying, but are not directly involved as a bully or victim; however, they often engage in negative bystander behavior. This study examines how social capital deprivation and anti-social capital are associated with the likelihood of engaging in negative bystander behavior in a sample (N = 5752) of racially/ethnically diverse rural youth. Data were collected using an online, youth self-report; the current study uses cross sectional data. Following multiple imputation, a binary logistic regression with robust standard errors was run. Results partially supported the hypothesis and indicated that social capital deprivation in the form of peer pressure and verbal victimization and anti-social capital in the form of delinquent friends, bullying perpetration, verbal perpetration, and physical perpetration were significantly associated with an increased likelihood of engaging in negative bystander behavior. Findings highlight the importance of establishing sources of positive social support for disenfranchised youth.

The Odds of Success: Predicting Registered Health Information Administrator Exam Success

PubMed Central

Dolezel, Diane; McLeod, Alexander

2017-01-01

The purpose of this study was to craft a predictive model to examine the relationship between grades in specific academic courses, overall grade point average (GPA), on-campus versus online course delivery, and success in passing the Registered Health Information Administrator (RHIA) exam on the first attempt. Because student success in passing the exam on the first attempt is assessed as part of the accreditation process, this study is important to health information management (HIM) programs. Furthermore, passing the exam greatly expands the graduate's job possibilities because the demand for credentialed graduates far exceeds the supply of credentialed graduates. Binary logistic regression was utilized to explore the relationships between the predictor variables and success in passing the RHIA exam on the first attempt. Results indicate that the student's cumulative GPA, specific HIM course grades, and course delivery method were predictive of success. PMID:28566994

Contribution of Psychological, Social, and Mechanical Work Exposures to Low Work Ability

PubMed Central

Knardahl, Stein

2015-01-01

Objective: To determine the contribution of specific psychological, social, and mechanical work exposures to the self-reported low level of work ability. Methods: Employees from 48 organizations were surveyed over a 2-year period (n = 3779). Changes in 16 work exposures and 3 work ability measures—the work ability index score, perceived current, and future work ability—were tested with Spearman rank correlations. Binary logistic regressions were run to determine contribution of work exposures to low work ability. Results: Role conflict, human resource primacy, and positive challenge were the most consistent predictors of low work ability across test designs. Role clarity and fair leadership were less consistent but prominent predictors. Mechanical exposures were not predictive. Conclusions: To protect employee work ability, work place interventions would benefit from focusing on reducing role conflicts and on promoting positive challenges and human resource primacy. PMID:25470453

[Analysis on influential factors of Chinese medicinal herb growers' willingness to use green pesticides: evidence on Panax notoginseng production areas in Wenshan, Yunnan province].

PubMed

Qian, Yun-Xu; Yang, Yue; Zhao, Wei; Cui, Xiu-Ming; Bi, Kai-Shun

2013-10-01

The purpose of the article is to apply a binary logistic model to analyze the major factors, which influence Chinese medicinal herb growers' willingness to use green pesticides by using survey data collected in Wenshan, Yunnan Province. The results indicate that, output per capita, average pesticide cost per mu, cognition of pesticide residues, expectations on Panax notoginseng prices, cognition of pesticides' effect of pests control, cognition of P. notoginseng prices of low pesticide residues have a significant influence on growers' willingness to use green pesticides. According to the analysis above, some proposals for enhancing Chinese medicinal herb growers' willingness to use green pesticides are put forward, such as, moving toward the intensive planting systems, fetching down the pieces of green pesticides, emphasizing and propagating the advantages of green pesticides, keeping the prices of Chinese medicinal herb running at steady rates.

Health Implications of Adults' Eating at and Living near Fast Food or Quick Service Restaurants.

PubMed

Jiao, J; Moudon, A V; Kim, S Y; Hurvitz, P M; Drewnowski, A

2015-07-20

This paper examined whether the reported health impacts of frequent eating at a fast food or quick service restaurant on health were related to having such a restaurant near home. Logistic regressions estimated associations between frequent fast food or quick service restaurant use and health status, being overweight or obese, having a cardiovascular disease or diabetes, as binary health outcomes. In all, 2001 participants in the 2008-2009 Seattle Obesity Study survey were included in the analyses. Results showed eating ⩾2 times a week at a fast food or quick service restaurant was associated with perceived poor health status, overweight and obese. However, living close to such restaurants was not related to negative health outcomes. Frequent eating at a fast food or quick service restaurant was associated with perceived poor health status and higher body mass index, but living close to such facilities was not.

Determinants of unprotected casual heterosexual sex in Ghana.

PubMed

Kumi-Kyereme, Akwasi; Tuoyire, Derek A; Darteh, Eugene K M

2014-05-01

Casual heterosexual sex remains a significant contributor to HIV transmissions in Ghana. The study used data from the 2008 Ghana Demographic and Health Survey (GDHS) to assess the socio-demographic, economic and spatial factors influencing unprotected casual heterosexual sex among men and women. The results of the binary logistic regression models revealed that women aged 35-44 had significantly higher odds of engaging in unprotected casual heterosexual sex than those aged 15-24, unlike the men. There were significantly lower odds of unprotected casual heterosexual sex for women and men with exposure to print media compared with those without exposure. Compared with men residing in the Western Region, unprotected casual heterosexual sex was significantly less likely among those in the Upper East Region. There is the need for behavioural change campaigns in Ghana that take into consideration the multiplicity of factors that determine unprotected casual heterosexual sex.

[Characteristics present in secondary school students who do not smoke and who have no intention to smoke].

PubMed

Lima-Serrano, Marta; Martínez-Montilla, José Manuel; Vargas-Martínez, Ana Magdalena; Zafra-Agea, José Antonio; Lima-Rodríguez, Joaquín Salvador

2018-02-27

To know the variables present in primary and secondary school students who do not smoke or intend to smoke from a positive health model. Cross-sectional study with 482 students from Andalusia and Catalonia using a validated questionnaire (ESFA and PASE project). Binary logistic regression analysis was performed. Those who did not intend to smoke viewed smoking unfavourably and had high self-efficacy (p <0.001). In non-consumers, the most associated variables were attitude, social model (p <0.001), and self-efficacy (p =0.005). The results show motivational factors present in students who do not smoke and do not intend to do so. Attitude and self-efficacy are strongly associated with intention and behaviour. This information might be useful for developing positive health promotion strategies from a salutogenesis approach. Copyright © 2018 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Central nervous system drug consumption depending on the time between symptom onset and the diagnosis of Alzheimer's disease: an analysis by the Registry of Dementias of Girona.

PubMed

Calvó-Perxas, Laia; López-Pousa, Secundino; Vilalta-Franch, Joan; Turró-Garriga, Oriol; Blankenburg, Michael; Febrer, Laia; Flaqué, Margarida; Vallmajó, Natàlia; Aguirregomozcorta, Maria; Genís, David; Casas, Isabel; Perkal, Héctor; Coromina, Joan; Garre-Olmo, Josep

2012-01-01

To describe central nervous system (CNS) drug consumption patterns depending on the time to diagnosis of Alzheimer's disease (AD), and to check whether the cases diagnosed later are associated with greater severity and consuming more CNS drugs. Cross-sectional study using 952 cases of the Registry of Dementias of Girona. A binary logistic regression was used to detect variables associated with the use of CNS drugs depending on the time to diagnosis. CNS drugs were consumed by 95.8% of the AD patients. Only antipsychotics presented a statistically significant increase in the frequency of prescription to patients with longer time elapsed from symptom onset to AD diagnosis. Longer time elapsed from the onset of symptoms to the diagnosis resulted in increased probability of antipsychotic consumption. Copyright © 2012 S. Karger AG, Basel.

The Association of Posttraumatic Stress Disorder with Fast Food and Soda Consumption and Unhealthy Weight Loss Behaviors Among Young Women

PubMed Central

Hirth, Jacqueline M.; Rahman, Mahbubur

2011-01-01

Abstract Objective This study examines the association of posttraumatic stress disorder (PTSD) symptoms with fast food and soda consumption, unhealthy dieting behaviors, and body mass index (BMI) in a group of young women. Methods This study was conducted on cross-sectional data gathered from 3181 females 16–24 years of age attending five publicly funded clinics in Texas. The associations among PTSD, fast food consumption frequency, soda consumption frequency, unhealthy dieting behaviors, and BMI were examined using binary and ordinal logistic regression. Results PTSD symptoms were associated with an increased frequency of consumption of fast food and soda as well as unhealthy dieting behaviors but not with increased body mass index (BMI). Conclusions PTSD symptoms adversely affect both eating and dieting behaviors of young women. These behaviors may have negative long-term consequences for the health of females with PTSD symptoms. PMID:21751875

Working women making it work: intimate partner violence, employment, and workplace support.

PubMed

Swanberg, Jennifer; Macke, Caroline; Logan, T K

2007-03-01

Partner violence may have significant consequences on women's employment, yet limited information is available about how women cope on the job with perpetrators' tactics and the consequences of her coping methods on employment status. This article investigates whether there is an association between workplace disclosure of victimization and current employment status; and whether there is an association between receiving workplace support and current employment status among women who disclosed victimization circumstances to someone at work. Using a sample of partner victimized women who were employed within the past year (N = 485), cross-tabulation and ANOVA procedures were conducted to examine the differences between currently employed and unemployed women. Binary logistic regressions were conducted to examine whether disclosure and receiving workplace support were significantly associated with current employment. Results indicate that disclosure and workplace support are associated with employment. Implications for clinical practice, workplace policies, and future research are discussed.

Catastrophic Health Expenditure Among Colorectal Cancer Patients and Families: A Case of Malaysia.

PubMed

Azzani, Meram; Yahya, Abqariyah; Roslani, April Camilla; Su, Tin Tin

2017-09-01

This study aimed to estimate the cost of colorectal cancer (CRC) management and to explore the prevalence and determinants of catastrophic health expenditure (CHE) among CRC patients and their families arising from the costs of CRC management. Data were collected prospectively from 138 CRC patients. Patients were interviewed by using a structured questionnaire at the time of the diagnosis, then at 6 months and 12 months following diagnosis. Simple descriptive methods and multivariate binary logistic regression were used in the analysis. The mean cost of managing CRC was RM8306.9 (US$2595.9), and 47.8% of patients' families experienced CHE. The main determinants of CHE were the economic status of the family and the likelihood of the patient undergoing surgery. The results of this study strongly suggest that stakeholders and policy makers should provide individuals with financial protection against the consequences of cancer, a costly illness that often requires prolonged treatment.

Risk factors for hookah smoking among arabs and chaldeans.

PubMed

Jamil, Hikmet; Geeso, Sanabil G; Arnetz, Bengt B; Arnetz, Judith E

2014-06-01

Hookah smoking is more prevalent among individuals of Middle Eastern descent. This study examined general and ethnic-specific risk factors for hookah smoking among Arabs and Chaldeans. A self-administered anonymous questionnaire was conducted among 801 adults residing in Southeast Michigan. Binary logistic regression modeling was used to predict risk factors for hookah smoking. Hookah smoking was significantly more prevalent among Arabs (32%) than Chaldeans (26%, p < 0.01) and being Arab was a risk factor for lifetime hookah use. Younger age (<25 years), being male, higher annual income, and having health insurance were significant risk factors for hookah use. Chaldeans believed to a greater extent than Arabs that smoking hookah is less harmful than cigarette smoking (75 vs. 52%, p < 0.001). Hookah smoking is prevalent in both ethnic groups, but significantly higher among Arabs. Results indicate that prevention efforts should target younger males with higher incomes.

Global Patterns in the Implementation of Payments for Environmental Services

PubMed Central

Ezzine-de-Blas, Driss; Wunder, Sven; Ruiz-Pérez, Manuel; Moreno-Sanchez, Rocio del Pilar

2016-01-01

Assessing global tendencies and impacts of conditional payments for environmental services (PES) programs is challenging because of their heterogeneity, and scarcity of comparative studies. This meta-study systematizes 55 PES schemes worldwide in a quantitative database. Using categorical principal component analysis to highlight clustering patterns, we reconfirm frequently hypothesized differences between public and private PES schemes, but also identify diverging patterns between commercial and non-commercial private PES vis-à-vis their service focus, area size, and market orientation. When do these PES schemes likely achieve significant environmental additionality? Using binary logistical regression, we find additionality to be positively influenced by three theoretically recommended PES ‘best design’ features: spatial targeting, payment differentiation, and strong conditionality, alongside some contextual controls (activity paid for and implementation time elapsed). Our results thus stress the preeminence of customized design over operational characteristics when assessing what determines the outcomes of PES implementation. PMID:26938065

Relationships Among Substance Use, Multiple Sexual Partners, and Condomless Sex.

PubMed

Zhao, Yunchuan Lucy; Kim, Heejung; Peltzer, Jill

2017-04-01

Male and female students manifest different behaviors in condomless sex. This cross-sectional, exploratory, correlational study examined the differences in risk factors for condomless sex between male and female high school students, using secondary data from 4,968 sexually active males and females participating in the 2011 National Youth Risk Behavior Survey. Results in descriptive statistics and multivariate binary logistic regressions revealed that condomless sex was reported as 39.70% in general. A greater proportion of females engaged in condomless sex (23.26%) than did males (16.44%). Physical abuse by sex partners was a common reason for failure to use condoms regardless of gender. Lower condom use was found in (1) those experiencing forced sex by a partner in males, (2) female smokers, and (3) female with multiple sex partners. Thus, sexual health education should address the different risk factors and consider gender characteristics to reduce condomless sex.

HEBS and Binary 1-sinc masks simulations, HCIT experiments and results

NASA Technical Reports Server (NTRS)

Balasubramanian, Bala K.; Hoppe, Dan; Wilson, Dan; Echternach, Pierre; Trauger, John; Halverson, Peter; Niessner, Al; Shi, Fang; Lowman, Andrew

2005-01-01

Based on preliminary experiments and results with a binary 1-sinc mask in the HCIT early in August 2004, we planned for a detailed experiment to compare the performance of HEBS and Binary masks under nearly identical conditions in the HCIT. This report details the design and fabrication of the masks, simulated predictions, and experimental results.

A nonparametric multiple imputation approach for missing categorical data.

PubMed

Zhou, Muhan; He, Yulei; Yu, Mandi; Hsu, Chiu-Hsieh

2017-06-06

Incomplete categorical variables with more than two categories are common in public health data. However, most of the existing missing-data methods do not use the information from nonresponse (missingness) probabilities. We propose a nearest-neighbour multiple imputation approach to impute a missing at random categorical outcome and to estimate the proportion of each category. The donor set for imputation is formed by measuring distances between each missing value with other non-missing values. The distance function is calculated based on a predictive score, which is derived from two working models: one fits a multinomial logistic regression for predicting the missing categorical outcome (the outcome model) and the other fits a logistic regression for predicting missingness probabilities (the missingness model). A weighting scheme is used to accommodate contributions from two working models when generating the predictive score. A missing value is imputed by randomly selecting one of the non-missing values with the smallest distances. We conduct a simulation to evaluate the performance of the proposed method and compare it with several alternative methods. A real-data application is also presented. The simulation study suggests that the proposed method performs well when missingness probabilities are not extreme under some misspecifications of the working models. However, the calibration estimator, which is also based on two working models, can be highly unstable when missingness probabilities for some observations are extremely high. In this scenario, the proposed method produces more stable and better estimates. In addition, proper weights need to be chosen to balance the contributions from the two working models and achieve optimal results for the proposed method. We conclude that the proposed multiple imputation method is a reasonable approach to dealing with missing categorical outcome data with more than two levels for assessing the distribution of the outcome. In terms of the choices for the working models, we suggest a multinomial logistic regression for predicting the missing outcome and a binary logistic regression for predicting the missingness probability.

WHITE-LIGHT FLARES ON CLOSE BINARIES OBSERVED WITH KEPLER

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Qing; Xin, Yu; Liu, Ji-Feng

2016-06-01

Based on Kepler data, we present the results of a search for white light flares on 1049 close binaries. We identify 234 flare binaries, of which 6818 flares are detected. We compare the flare-binary fraction in different binary morphologies (“detachedness”). The result shows that the fractions in over-contact and ellipsoidal binaries are approximately 10%–20% lower than those in detached and semi-detached systems. We calculate the binary flare activity level (AL) of all the flare binaries, and discuss its variations along the orbital period ( P {sub orb}) and rotation period ( P {sub rot}, calculated for only detached binaries). Wemore » find that the AL increases with decreasing P {sub orb} or P {sub rot}, up to the critical values at P {sub orb} ∼ 3 days or P {sub rot} ∼ 1.5 days, and thereafter the AL starts decreasing no matter how fast the stars rotate. We examine the flaring rate as a function of orbital phase in two eclipsing binaries on which a large number of flares are detected. It appears that there is no correlation between flaring rate and orbital phase in these two binaries. In contrast, when we examine the function with 203 flares on 20 non-eclipse ellipsoidal binaries, bimodal distribution of amplitude-weighted flare numbers shows up at orbital phases 0.25 and 0.75. Such variation could be larger than what is expected from the cross section modification.« less

Epidemiologic research using probabilistic outcome definitions.

PubMed

Cai, Bing; Hennessy, Sean; Lo Re, Vincent; Small, Dylan S

2015-01-01

Epidemiologic studies using electronic healthcare data often define the presence or absence of binary clinical outcomes by using algorithms with imperfect specificity, sensitivity, and positive predictive value. This results in misclassification and bias in study results. We describe and evaluate a new method called probabilistic outcome definition (POD) that uses logistic regression to estimate the probability of a clinical outcome using multiple potential algorithms and then uses multiple imputation to make valid inferences about the risk ratio or other epidemiologic parameters of interest. We conducted a simulation to evaluate the performance of the POD method with two variables that can predict the true outcome and compared the POD method with the conventional method. The simulation results showed that when the true risk ratio is equal to 1.0 (null), the conventional method based on a binary outcome provides unbiased estimates. However, when the risk ratio is not equal to 1.0, the traditional method, either using one predictive variable or both predictive variables to define the outcome, is biased when the positive predictive value is <100%, and the bias is very severe when the sensitivity or positive predictive value is poor (less than 0.75 in our simulation). In contrast, the POD method provides unbiased estimates of the risk ratio both when this measure of effect is equal to 1.0 and not equal to 1.0. Even when the sensitivity and positive predictive value are low, the POD method continues to provide unbiased estimates of the risk ratio. The POD method provides an improved way to define outcomes in database research. This method has a major advantage over the conventional method in that it provided unbiased estimates of risk ratios and it is easy to use. Copyright © 2014 John Wiley & Sons, Ltd.

Influence of management of variables, sampling zones and land units on LR analysis for landslide spatial prevision

NASA Astrophysics Data System (ADS)

Greco, R.; Sorriso-Valvo, M.

2013-09-01

Several authors, according to different methodological approaches, have employed logistic Regression (LR), a multivariate statistical analysis adopted to assess the spatial probability of landslide, even though its fundamental principles have remained unaltered. This study aims at assessing the influence of some of these methodological approaches on the performance of LR, through a series of sensitivity analyses developed over a test area of about 300 km2 in Calabria (southern Italy). In particular, four types of sampling (1 - the whole study area; 2 - transects running parallel to the general slope direction of the study area with a total surface of about 1/3 of the whole study area; 3 - buffers surrounding the phenomena with a 1/1 ratio between the stable and the unstable area; 4 - buffers surrounding the phenomena with a 1/2 ratio between the stable and the unstable area), two variable coding modes (1 - grouped variables; 2 - binary variables), and two types of elementary land (1 - cells units; 2 - slope units) units have been tested. The obtained results must be considered as statistically relevant in all cases (Aroc values > 70%), thus confirming the soundness of the LR analysis which maintains high predictive capacities notwithstanding the features of input data. As for the area under investigation, the best performing methodological choices are the following: (i) transects produced the best results (0 < P(y) ≤ 93.4%; Aroc = 79.5%); (ii) as for sampling modalities, binary variables (0 < P(y) ≤ 98.3%; Aroc = 80.7%) provide better performance than ordinated variables; (iii) as for the choice of elementary land units, slope units (0 < P(y) ≤ 100%; Aroc = 84.2%) have obtained better results than cells matrix.

Effect of binary fraction on color-magnitude diagram of NGC 1904

NASA Astrophysics Data System (ADS)

Li, Zhongmu; Deng, Yangyang

2018-05-01

The age of a southern globular cluster in Milky Way, NGC 1904, was shown to be larger than the typical age of the universe, around 13.7 Gyr, by some photometric studies which assumed all stars as single stars. Besides the uncertainties in photometry, isochrone and fitting technique, the neglect of binary stars possibly distorted the result. We study the effect of binary fraction on the color-magnitude diagram (CMD) of NGC 1904, via a new tool for CMD studies, Powerful CMD, which can determine binary fraction, age, metallicity, distance modulus, color excess, rotating star fraction and star formation history simultaneously. We finally obtain the youngest age of 14.1±2.1 Gyr with a zero-age binary fraction of 60 percent for cluster NGC 1904. The result is consistent with the age of the universe. Although our result suggests that binary fraction affects the determination of age slightly, it can improve the fitting to observed CMD, in particular blue stragglers. This suggests us to consider the effect of binaries in the studies of star clusters.

Formation and Evolution of X-ray Binaries

NASA Astrophysics Data System (ADS)

Shao, Y.

2017-07-01

X-ray binaries are a class of binary systems, in which the accretor is a compact star (i.e., black hole, neutron star, or white dwarf). They are one of the most important objects in the universe, which can be used to study not only binary evolution but also accretion disks and compact stars. Statistical investigations of these binaries help to understand the formation and evolution of galaxies, and sometimes provide useful constraints on the cosmological models. The goal of this thesis is to investigate the formation and evolution processes of X-ray binaries including Be/X-ray binaries, low-mass X-ray binaries (LMXBs), ultraluminous X-ray sources (ULXs), and cataclysmic variables. In Chapter 1 we give a brief review on the basic knowledge of the binary evolution. In Chapter 2 we discuss the formation of Be stars through binary interaction. In this chapter we investigate the formation of Be stars resulting from mass transfer in binaries in the Galaxy. Using binary evolution and population synthesis calculations, we find that in Be/neutron star binaries the Be stars have a lower limit of mass ˜ 8 M⊙ if they are formed by a stable (i.e., without the occurrence of common envelope evolution) and nonconservative mass transfer. We demonstrate that the isolated Be stars may originate from both mergers of two main-sequence stars and disrupted Be binaries during the supernova explosions of the primary stars, but mergers seem to play a much more important role. Finally the fraction of Be stars produced by binary interactions in all B type stars can be as high as ˜ 13%-30% , implying that most of Be stars may result from binary interaction. In Chapter 3 we show the evolution of intermediate- and low-mass X-ray binaries (I/LMXBs) and the formation of millisecond pulsars. Comparing the calculated results with the observations of binary radio pulsars, we report the following results: (1) The allowed parameter space for forming binary pulsars in the initial orbital period-donor mass plane increases with the increasing neutron star mass. This may help to explain why some millisecond pulsars with orbital periods longer than ˜ 60 d seem to have less massive white dwarfs than expected. Alternatively, some of these wide binary pulsars may be formed through mass transfer driven by planet/brown dwarf-involved common envelope evolution; (2) Some of the pulsars in compact binaries might have evolved from intermediate-mass X-ray binaries with an anomalous magnetic braking; (3) The equilibrium spin periods of neutron stars in low-mass X-ray binaries are in general shorter than the observed spin periods of binary pulsars by more than one order of magnitude, suggesting that either the simple equilibrium spin model does not apply, or there are other mechanisms/processes spinning down the neutron stars. In Chapter 4, angular momentum loss mechanisms in the cataclysmic variables below the period gap are presented. By considering several kinds of consequential angular momentum loss mechanisms, we find that neither isotropic wind from the white dwarf nor outflow from the L1 point can explain the extra angular momentum loss rate, while an ouflow from the L2 point or a circumbinary disk can effectively extract the angular momentum provided that ˜ 15%-45% of the transferred mass is lost from the binary. A more promising mechanism is a circumbinary disk exerting a gravitational torque on the binary. In this case the mass loss fraction can be as low as ≲ 10-3. In Chapter 5 we present a study on the population of ultraluminous X-ray sources with an accreting neutron star. Most ULXs are believed to be X-ray binary systems, but previous observational and theoretical studies tend to prefer a black hole rather than a neutron star accretor. The recent discovery of 1.37 s pulsations from the ULX M82 X-2 has established its nature as a magnetized neutron star. In this chapter we model the formation history of neutron star ULXs in an M82- or Milky Way-like galaxy, by use of both binary population synthesis and detailed binary evolution calculations. We find that the birthrate is around 10-4 yr-1 for the incipient X-ray binaries in both cases. We demonstrate the distribution of the ULX population in the donor mass - orbital period plane. Our results suggest that, compared with black hole X-ray binaries, neutron star X-ray binaries may significantly contribute to the ULX population, and high/intermediate-mass X-ray binaries dominate the neutron star ULX population in M82/Milky Way-like galaxies, respectively. In Chapter 6, the population of intermediate- and low-mass X-ray binaries in the Galaxy is explored. We investigate the formation and evolutionary sequences of Galactic intermediate- and low-mass X-ray binaries by combining binary population synthesis (BPS) and detailed stellar evolutionary calculations. Using an updated BPS code we compute the evolution of massive binaries that leads to the formation of incipient I/LMXBs, and present their distribution in the initial donor mass vs. initial orbital period diagram. We then follow the evolution of I/LMXBs until the formation of binary millisecond pulsars (BMSPs). We show that during the evolution of I/LMXBs they are likely to be observed as relatively compact binaries. The resultant BMSPs have orbital periods ranging from about 1 day to a few hundred days. These features are consistent with observations of LMXBs and BMSPs. We also confirm the discrepancies between theoretical predictions and observations mentioned in the literature, that is, the theoretical average mass transfer rates of LMXBs are considerably lower than observed, and the number of BMSPs with orbital periods ˜ 0.1-1 \\unit{d} is severely underestimated. Both imply that something is missing in the modeling of LMXBs, which is likely to be related to the mechanisms of the orbital angular momentum loss. Finally in Chapter 7 we summarize our results and give the prospects for the future work.

Indicators of suboptimal performance embedded in the Wechsler Memory Scale-Fourth Edition (WMS-IV).

PubMed

Bouman, Zita; Hendriks, Marc P H; Schmand, Ben A; Kessels, Roy P C; Aldenkamp, Albert P

2016-01-01

Recognition and visual working memory tasks from the Wechsler Memory Scale-Fourth Edition (WMS-IV) have previously been documented as useful indicators for suboptimal performance. The present study examined the clinical utility of the Dutch version of the WMS-IV (WMS-IV-NL) for the identification of suboptimal performance using an analogue study design. The patient group consisted of 59 mixed-etiology patients; the experimental malingerers were 50 healthy individuals who were asked to simulate cognitive impairment as a result of a traumatic brain injury; the last group consisted of 50 healthy controls who were instructed to put forth full effort. Experimental malingerers performed significantly lower on all WMS-IV-NL tasks than did the patients and healthy controls. A binary logistic regression analysis was performed on the experimental malingerers and the patients. The first model contained the visual working memory subtests (Spatial Addition and Symbol Span) and the recognition tasks of the following subtests: Logical Memory, Verbal Paired Associates, Designs, Visual Reproduction. The results showed an overall classification rate of 78.4%, and only Spatial Addition explained a significant amount of variation (p < .001). Subsequent logistic regression analysis and receiver operating characteristic (ROC) analysis supported the discriminatory power of the subtest Spatial Addition. A scaled score cutoff of <4 produced 93% specificity and 52% sensitivity for detection of suboptimal performance. The WMS-IV-NL Spatial Addition subtest may provide clinically useful information for the detection of suboptimal performance.

A robust data scaling algorithm to improve classification accuracies in biomedical data.

PubMed

Cao, Xi Hang; Stojkovic, Ivan; Obradovic, Zoran

2016-09-09

Machine learning models have been adapted in biomedical research and practice for knowledge discovery and decision support. While mainstream biomedical informatics research focuses on developing more accurate models, the importance of data preprocessing draws less attention. We propose the Generalized Logistic (GL) algorithm that scales data uniformly to an appropriate interval by learning a generalized logistic function to fit the empirical cumulative distribution function of the data. The GL algorithm is simple yet effective; it is intrinsically robust to outliers, so it is particularly suitable for diagnostic/classification models in clinical/medical applications where the number of samples is usually small; it scales the data in a nonlinear fashion, which leads to potential improvement in accuracy. To evaluate the effectiveness of the proposed algorithm, we conducted experiments on 16 binary classification tasks with different variable types and cover a wide range of applications. The resultant performance in terms of area under the receiver operation characteristic curve (AUROC) and percentage of correct classification showed that models learned using data scaled by the GL algorithm outperform the ones using data scaled by the Min-max and the Z-score algorithm, which are the most commonly used data scaling algorithms. The proposed GL algorithm is simple and effective. It is robust to outliers, so no additional denoising or outlier detection step is needed in data preprocessing. Empirical results also show models learned from data scaled by the GL algorithm have higher accuracy compared to the commonly used data scaling algorithms.

Work related complaints of neck, shoulder and arm among computer office workers: a cross-sectional evaluation of prevalence and risk factors in a developing country.

PubMed

Ranasinghe, Priyanga; Perera, Yashasvi S; Lamabadusuriya, Dilusha A; Kulatunga, Supun; Jayawardana, Naveen; Rajapakse, Senaka; Katulanda, Prasad

2011-08-04

Complaints of arms, neck and shoulders (CANS) is common among computer office workers. We evaluated an aetiological model with physical/psychosocial risk-factors. We invited 2,500 computer office workers for the study. Data on prevalence and risk-factors of CANS were collected by validated Maastricht-Upper-extremity-Questionnaire. Workstations were evaluated by Occupational Safety and Health Administration (OSHA) Visual-Display-Terminal workstation-checklist. Participants' knowledge and awareness was evaluated by a set of expert-validated questions. A binary logistic regression analysis investigated relationships/correlations between risk-factors and symptoms. Sample size was 2,210. Mean age 30.8 ± 8.1 years, 50.8% were males. The 1-year prevalence of CANS was 56.9%, commonest region of complaint was forearm/hand (42.6%), followed by neck (36.7%) and shoulder/arm (32.0%). In those with CANS, 22.7% had taken treatment from a health care professional, only in 1.1% seeking medical advice an occupation-related injury had been suspected/diagnosed. In addition 9.3% reported CANS-related absenteeism from work, while 15.4% reported CANS causing disruption of normal activities. A majority of evaluated workstations in all participants (88.4%,) and in those with CANS (91.9%) had OSHA non-compliant workstations. In the binary logistic regression analyses female gender, daily computer usage, incorrect body posture, bad work-habits, work overload, poor social support and poor ergonomic knowledge were associated with CANS and its' severity In a multiple logistic regression analysis controlling for age, gender and duration of occupation, incorrect body posture, bad work-habits and daily computer usage were significant independent predictors of CANS. The prevalence of work-related CANS among computer office workers in Sri Lanka, a developing, South Asian country is high and comparable to prevalence in developed countries. Work-related physical factors, psychosocial factors and lack of awareness were all important associations of CANS and effective preventive strategies need to address all three areas.

Space logistics simulation: Launch-on-time

NASA Technical Reports Server (NTRS)

Nii, Kendall M.

1990-01-01

During 1989-1990 the Center for Space Construction developed the Launch-On-Time (L-O-T) Model to help asses and improve the likelihood of successfully supporting space construction requiring multi-logistic delivery flights. The model chose a reference by which the L-O-T probability and improvements to L-O-T probability can be judged. The measure of improvement was chosen as the percent reduction in E(S(sub N)), the total expected amount of unscheduled 'hold' time. We have also previously developed an approach to determining the reduction in E(S(sub N)) by reducing some of the causes of unscheduled holds and increasing the speed at which the problems causing the holds may be 'fixed.' We provided a mathematical (binary linear programming) model for measuring the percent reduction in E(S(sub N)) given such improvements. In this presentation we shall exercise the model which was developed and draw some conclusions about the following: methods used, data available and needed, and make suggestions for areas of improvement in 'real world' application of the model.

Approximate Genealogies Under Genetic Hitchhiking

PubMed Central

Pfaffelhuber, P.; Haubold, B.; Wakolbinger, A.

2006-01-01

The rapid fixation of an advantageous allele leads to a reduction in linked neutral variation around the target of selection. The genealogy at a neutral locus in such a selective sweep can be simulated by first generating a random path of the advantageous allele's frequency and then a structured coalescent in this background. Usually the frequency path is approximated by a logistic growth curve. We discuss an alternative method that approximates the genealogy by a random binary splitting tree, a so-called Yule tree that does not require first constructing a frequency path. Compared to the coalescent in a logistic background, this method gives a slightly better approximation for identity by descent during the selective phase and a much better approximation for the number of lineages that stem from the founder of the selective sweep. In applications such as the approximation of the distribution of Tajima's D, the two approximation methods perform equally well. For relevant parameter ranges, the Yule approximation is faster. PMID:17182733

Image encryption with chaotic map and Arnold transform in the gyrator transform domains

NASA Astrophysics Data System (ADS)

Sang, Jun; Luo, Hongling; Zhao, Jun; Alam, Mohammad S.; Cai, Bin

2017-05-01

An image encryption method combing chaotic map and Arnold transform in the gyrator transform domains was proposed. Firstly, the original secret image is XOR-ed with a random binary sequence generated by a logistic map. Then, the gyrator transform is performed. Finally, the amplitude and phase of the gyrator transform are permutated by Arnold transform. The decryption procedure is the inverse operation of encryption. The secret keys used in the proposed method include the control parameter and the initial value of the logistic map, the rotation angle of the gyrator transform, and the transform number of the Arnold transform. Therefore, the key space is large, while the key data volume is small. The numerical simulation was conducted to demonstrate the effectiveness of the proposed method and the security analysis was performed in terms of the histogram of the encrypted image, the sensitiveness to the secret keys, decryption upon ciphertext loss, and resistance to the chosen-plaintext attack.

Efficient logistic regression designs under an imperfect population identifier.

PubMed

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

2014-03-01

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

Ab-initio study of liquid systems: Concentration dependence of electrical resistivity of binary liquid alloy Rb1-xCsx

NASA Astrophysics Data System (ADS)

Thakur, Anil; Sharma, Nalini; Chandel, Surjeet; Ahluwalia, P. K.

2013-02-01

The electrical resistivity (ρL) of Rb1-XCsX binary alloys has been made calculated using Troullier Martins ab-initio pseudopotentials. The present results of the electrical resistivity (ρL) of Rb1-XCsX binary alloys have been found in good agreement with the experimental results. These results suggest that ab-initio approach for calculating electrical resistivity is quite successful in explaining the electronic transport properties of binary Liquid alloys. Hence ab-initio pseudopotentials can be used instead of model pseudopotentials having problem of transferability.

Learning to assign binary weights to binary descriptor

NASA Astrophysics Data System (ADS)

Huang, Zhoudi; Wei, Zhenzhong; Zhang, Guangjun

2016-10-01

Constructing robust binary local feature descriptors are receiving increasing interest due to their binary nature, which can enable fast processing while requiring significantly less memory than their floating-point competitors. To bridge the performance gap between the binary and floating-point descriptors without increasing the computational cost of computing and matching, optimal binary weights are learning to assign to binary descriptor for considering each bit might contribute differently to the distinctiveness and robustness. Technically, a large-scale regularized optimization method is applied to learn float weights for each bit of the binary descriptor. Furthermore, binary approximation for the float weights is performed by utilizing an efficient alternatively greedy strategy, which can significantly improve the discriminative power while preserve fast matching advantage. Extensive experimental results on two challenging datasets (Brown dataset and Oxford dataset) demonstrate the effectiveness and efficiency of the proposed method.

Liquefaction assessment based on combined use of CPT and shear wave velocity measurements

NASA Astrophysics Data System (ADS)

Bán, Zoltán; Mahler, András; Győri, Erzsébet

2017-04-01

Soil liquefaction is one of the most devastating secondary effects of earthquakes and can cause significant damage in built infrastructure. For this reason liquefaction hazard shall be considered in all regions where moderate-to-high seismic activity encounters with saturated, loose, granular soil deposits. Several approaches exist to take into account this hazard, from which the in-situ test based empirical methods are the most commonly used in practice. These methods are generally based on the results of CPT, SPT or shear wave velocity measurements. In more complex or high risk projects CPT and VS measurement are often performed at the same location commonly in the form of seismic CPT. Furthermore, VS profile determined by surface wave methods can also supplement the standard CPT measurement. However, combined use of both in-situ indices in one single empirical method is limited. For this reason, the goal of this research was to develop such an empirical method within the framework of simplified empirical procedures where the results of CPT and VS measurements are used in parallel and can supplement each other. The combination of two in-situ indices, a small strain property measurement with a large strain measurement, can reduce uncertainty of empirical methods. In the first step by careful reviewing of the already existing liquefaction case history databases, sites were selected where the records of both CPT and VS measurement are available. After implementing the necessary corrections on the gathered 98 case histories with respect to fines content, overburden pressure and magnitude, a logistic regression was performed to obtain the probability contours of liquefaction occurrence. Logistic regression is often used to explore the relationship between a binary response and a set of explanatory variables. The occurrence or absence of liquefaction can be considered as binary outcome and the equivalent clean sand value of normalized overburden corrected cone tip resistance (qc1Ncs), the overburden corrected shear wave velocity (V S1), and the magnitude and effective stress corrected cyclic stress ratio (CSRM=7.5,σv'=1atm) were considered as input variables. In this case the graphical representation of the cyclic resistance ratio curve for a given probability has been replaced by a surface that separates the liquefaction and non-liquefaction cases.

Clusters of anthropometric indicators of body fat associated with maximum oxygen uptake in adolescents

PubMed Central

2018-01-01

Introduction The aim of this study was to evaluate different clusters of anthropometric indicators (body mass index | BMI |, waist circumference | WC |, waist-to-height ratio | WHtR |, triceps skinfold |TR SF|, subscapular skinfold |SE SF|, sum of the triceps and subscapular skinfolds | ΣTR + SE |, and sum of the triceps, subscapular and suprailiac folds | ΣTR + SE + SI|) associated with the VO2max levels in adolescents. Methods The study included 1,132 adolescents (aged 14–19 years) enrolled in public schools of São José, Santa Catarina, Brazil, in the 2014 academic year. The dependent variable was the cluster of anthropometric indicators (BMI, WC, WHtR, TR SF, SE SF, SI SF, ΣTR + SE and ΣTR + SE + SI) of excess body fat. The independent variable was maximum oxygen uptake (VO2max), estimated by the modified Canadian aerobic fitness test—mCAFT. Control variables were: age, skin color, economic level, maternal education, physical activity and sexual maturation. Multinomial logistic regression was used for associations between the dependent and independent variables. Binary logistic regression was performed to identify the association between adolescents with all anthropometric indicators in excess and independent variables. Results One in ten adolescents presented all anthropometric indicators of excess body fat. Multinomial regression showed that with each increase of one VO2max unit, the odds of adolescents having three, four, five or more anthropometric indicators of excess body fat decreased by 0.92, 0.85 and 0.73 times, respectively. In the binary regression, this fact was reconfirmed, demonstrating that with each increase of one VO2max unit, the odds of adolescents having simultaneously the eight anthropometric indicators of excess body fat decreased by 0.55. Conclusion It was concluded that with each increase of one VO2max unit, adolescents decreased the odds of simultaneously presenting three or more anthropometric indicators of excess body fat, regardless of biological, economic and lifestyle factors. In addition, the present study identified that one in ten adolescents had all anthropometric indicators of excess body fat. PMID:29534098

Specific technological communication skills and functional health literacy have no influence on self-reported benefits from enrollment in the TeleCare North trial.

PubMed

Lilholt, Pernille Heyckendorff; Hæsum, Lisa Korsbakke Emtekær; Ehlers, Lars Holger; Hejlesen, Ole K

2016-07-01

The Danish TeleCare North trial has developed a telehealth system, Telekit, which is used for self-management by patients diagnosed with chronic obstructive pulmonary disease (COPD). Self-management is the engagement in one's own illness and health by monitoring and managing one's symptoms and signs of illness. The study examines the association between COPD patients' use of Telekit and their functional health literacy and the association between their use of Telekit and their specific technological communication skills. A consecutive sample of participants (n=60) from the TeleCare North trial were recruited. Face-to-face interviews were conducted with each participant to collect demographic data. Functional health literacy was measured with the Danish TOFHLA test. Participants completed a non-standardised questionnaire about their health status, their use of the Telekit system, and their specific technological communication skills. Binary logistic regressions were performed to examine how functional health literacy and specific technological communication skills influenced the use of Telekit by giving users an enhanced sense of freedom, security, control, and a greater awareness of COPD symptoms. Participants (27 women, 33 men) had a mean age of 70 (SD: 8.37) years. Functional health literacy levels were classified as inadequate in 14 (23%) participants, as marginal in 12 (20%), and as adequate in 34 (57%). Participants self-reported a feeling of increased security (72%), greater freedom (27%), more control (62%), and greater awareness of symptoms (50%) when using Telekit. The use of Telekit was not significantly associated with levels of functional health literacy or with the number of specific technological communication skills (p>0.05) based on the binary logistic regressions. The enhanced sense of security, freedom, control, and the greater awareness of COPD symptoms achieved by using Telekit were unassociated both with the patients' score of functional health literacy and with their specific technological communication skills. On the basis of our results it seems that the specific technological communication skills and functional health literacy are not a prerequisite for the use of the Telekit system. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The impact of comorbid post-traumatic stress disorder in patients with major depressive disorder on clinical features, pharmacological treatment strategies, and treatment outcomes - Results from a cross-sectional European multicenter study.

PubMed

Dold, Markus; Bartova, Lucie; Kautzky, Alexander; Souery, Daniel; Mendlewicz, Julien; Serretti, Alessandro; Porcelli, Stefano; Zohar, Joseph; Montgomery, Stuart; Kasper, Siegfried

2017-07-01

This international, multicenter, cross-sectional study comprising 1346 adult in- and outpatients with major depressive disorder (MDD) investigated the association between MDD as primary diagnosis and comorbid post-traumatic stress disorder (PTSD). In a cross-sectional data collection process, the presence of comorbid PTSD was determined by the Mini International Neuropsychiatric Interview (MINI) and the patients' socio-demographic, clinical, psychopharmacological, and response information were obtained. Clinical features between MDD with and without concurrent PTSD were compared using descriptive statistics, analyses of covariance (ANCOVA), and binary logistic regression analyses. 1.49% of the MDD patients suffered from comorbid PTSD. Significantly more MDD + comorbid PTSD patients exhibited atypical features, comorbid anxiety disorders (any comorbid anxiety disorder, panic disorder, agoraphobia, and social phobia), comorbid bulimia nervosa, current suicide risk, and augmentation treatment with low-dose antipsychotic drugs. In the binary logistic regression analyses, the presence of atypical features (odds ratio (OR) = 4.49, 95%CI:1.01-20.12; p≤.05), any comorbid anxiety disorder (OR = 3.89, 95%CI:1.60-9.44; p = .003), comorbid panic disorder (OR = 6.45, 95%CI:2.52-16.51; p = .001), comorbid agoraphobia (OR = 6.51, 95%CI:2.54-16.68; p≤.001), comorbid social phobia (OR = 6.16, 95%CI:1.71-22.17; p≤.001), comorbid bulimia nervosa (OR = 10.39, 95%CI:1.21-88.64; p = .03), current suicide risk (OR = 3.58, 95%CI:1.30-9.91; p = .01), and augmentation with low-potency antipsychotics (OR = 6.66, 95%CI:2.50-17.77; p<.001) were associated with concurrent PTSD in predominant MDD. Major findings of this study were (1.) the much lower prevalence rate of comorbid PTSD in predominant MDD compared to the reverse prevalence rates of concurrent MDD in primary PTSD, (2.) the high association to comorbid anxiety disorders, and (3.) the increased suicide risk due to concurrent PTSD. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

Efficient algorithms for dilated mappings of binary trees

NASA Technical Reports Server (NTRS)

Iqbal, M. Ashraf

1990-01-01

The problem is addressed to find a 1-1 mapping of the vertices of a binary tree onto those of a target binary tree such that the son of a node on the first binary tree is mapped onto a descendent of the image of that node in the second binary tree. There are two natural measures of the cost of this mapping, namely the dilation cost, i.e., the maximum distance in the target binary tree between the images of vertices that are adjacent in the original tree. The other measure, expansion cost, is defined as the number of extra nodes/edges to be added to the target binary tree in order to ensure a 1-1 mapping. An efficient algorithm to find a mapping of one binary tree onto another is described. It is shown that it is possible to minimize one cost of mapping at the expense of the other. This problem arises when designing pipelined arithmetic logic units (ALU) for special purpose computers. The pipeline is composed of ALU chips connected in the form of a binary tree. The operands to the pipeline can be supplied to the leaf nodes of the binary tree which then process and pass the results up to their parents. The final result is available at the root. As each new application may require a distinct nesting of operations, it is useful to be able to find a good mapping of a new binary tree over existing ALU tree. Another problem arises if every distinct required binary tree is known beforehand. Here it is useful to hardwire the pipeline in the form of a minimal supertree that contains all required binary trees.

Do all Planetary Nebulae result from Common Envelopes?

NASA Astrophysics Data System (ADS)

De Marco, O.; Moe, M.; Herwig, F.; Politano, M.

2005-12-01

The common envelope interaction is responsible for evolved close binaries. Some of these binaries reside in the middle of planetary nebulae (PN). Conventional wisdom has it that only about 10% of all PN contain close binary central stars. Recent observational results, however, strongly suggest that most or even all PN are in close binary systems. Interestingly, our population synthesis calculations predict that the number of post-common envelope PN is in agreement with the total number of PN in the Galaxy. On the other hand, if all stars (single and in binaries) with mass between ˜1-8 M⊙ eject a PN, there would be 10-20 times many more PN in the galaxy than observed. This theoretical result is in agreement with the observations in suggesting that binary interactions play a functional rather than marginal role in the creation of PN. FH acknowledges funds from the U.S. Dept. of Energy, under contract W-7405-ENG-36 to Los Alamos National Laboratory. MP gratefully acknowledges NSF grant AST-0328484 to Marquette University.

Waveform model for an eccentric binary black hole based on the effective-one-body-numerical-relativity formalism

NASA Astrophysics Data System (ADS)

Cao, Zhoujian; Han, Wen-Biao

2017-08-01

Binary black hole systems are among the most important sources for gravitational wave detection. They are also good objects for theoretical research for general relativity. A gravitational waveform template is important to data analysis. An effective-one-body-numerical-relativity (EOBNR) model has played an essential role in the LIGO data analysis. For future space-based gravitational wave detection, many binary systems will admit a somewhat orbit eccentricity. At the same time, the eccentric binary is also an interesting topic for theoretical study in general relativity. In this paper, we construct the first eccentric binary waveform model based on an effective-one-body-numerical-relativity framework. Our basic assumption in the model construction is that the involved eccentricity is small. We have compared our eccentric EOBNR model to the circular one used in the LIGO data analysis. We have also tested our eccentric EOBNR model against another recently proposed eccentric binary waveform model; against numerical relativity simulation results; and against perturbation approximation results for extreme mass ratio binary systems. Compared to numerical relativity simulations with an eccentricity as large as about 0.2, the overlap factor for our eccentric EOBNR model is better than 0.98 for all tested cases, including spinless binary and spinning binary, equal mass binary, and unequal mass binary. Hopefully, our eccentric model can be the starting point to develop a faithful template for future space-based gravitational wave detectors.

Assessment and Implication of Prognostic Imbalance in Randomized Controlled Trials with a Binary Outcome – A Simulation Study

PubMed Central

Chu, Rong; Walter, Stephen D.; Guyatt, Gordon; Devereaux, P. J.; Walsh, Michael; Thorlund, Kristian; Thabane, Lehana

2012-01-01

Background Chance imbalance in baseline prognosis of a randomized controlled trial can lead to over or underestimation of treatment effects, particularly in trials with small sample sizes. Our study aimed to (1) evaluate the probability of imbalance in a binary prognostic factor (PF) between two treatment arms, (2) investigate the impact of prognostic imbalance on the estimation of a treatment effect, and (3) examine the effect of sample size (n) in relation to the first two objectives. Methods We simulated data from parallel-group trials evaluating a binary outcome by varying the risk of the outcome, effect of the treatment, power and prevalence of the PF, and n. Logistic regression models with and without adjustment for the PF were compared in terms of bias, standard error, coverage of confidence interval and statistical power. Results For a PF with a prevalence of 0.5, the probability of a difference in the frequency of the PF≥5% reaches 0.42 with 125/arm. Ignoring a strong PF (relative risk = 5) leads to underestimating the strength of a moderate treatment effect, and the underestimate is independent of n when n is >50/arm. Adjusting for such PF increases statistical power. If the PF is weak (RR = 2), adjustment makes little difference in statistical inference. Conditional on a 5% imbalance of a powerful PF, adjustment reduces the likelihood of large bias. If an absolute measure of imbalance ≥5% is deemed important, including 1000 patients/arm provides sufficient protection against such an imbalance. Two thousand patients/arm may provide an adequate control against large random deviations in treatment effect estimation in the presence of a powerful PF. Conclusions The probability of prognostic imbalance in small trials can be substantial. Covariate adjustment improves estimation accuracy and statistical power, and hence should be performed when strong PFs are observed. PMID:22629322

Personality traits and coping styles explain anxiety in lung cancer patients to a greater extent than other factors.

PubMed

Shimizu, Ken; Nakaya, Naoki; Saito-Nakaya, Kumi; Akechi, Tatsuo; Ogawa, Asao; Fujisawa, Daisuke; Sone, Toshimasa; Yoshiuchi, Kazuhiro; Goto, Koichi; Iwasaki, Motoki; Tsugane, Shoichiro; Uchitomi, Yosuke

2015-05-01

Although various factors thought to be correlated with anxiety in cancer patients, relative importance of each factors were unknown. We tested our hypothesis that personality traits and coping styles explain anxiety in lung cancer patients to a greater extent than other factors. A total of 1334 consecutively recruited lung cancer patients were selected, and data on cancer-related variables, demographic characteristics, health behaviors, physical symptoms and psychological factors consisting of personality traits and coping styles were obtained. The participants were divided into groups with or without a significant anxiety using the Hospital Anxiety and Depression Scale-Anxiety, and a binary logistic regression analysis was used to identify factors correlated with significant anxiety using a multivariate model. Among the recruited patients, 440 (33.0%) had significant anxiety. The binary logistic regression analysis revealed a coefficient of determination (overall R(2)) of 39.0%, and the explanation for psychological factors was much higher (30.7%) than those for cancer-related variables (1.1%), demographic characteristics (2.1%), health behaviors (0.8%) and physical symptoms (4.3%). Four specific factors remained significant in a multivariate model. A neurotic personality trait, a coping style of helplessness/hopelessness, and a female sex were positively correlated with significant anxiety, while a coping style of fatalism was negatively correlated. Our hypothesis was supported, and anxiety was strongly linked with personality trait and coping style. As a clinical implication, the use of screening instruments to identify these factors and intervention for psychological crisis may be needed. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The effect of migration on social capital and depression among older adults in China.

PubMed

Li, Qiuju; Zhou, Xudong; Ma, Sha; Jiang, Minmin; Li, Lu

2017-12-01

An estimated 9 million elderly people accompanied their adult children to urban areas in China, raising concerns about their social capital and mental health following re-location. The aim of this study was to examine the effect of migration on social capital and depression among this population. Multistage stratified cluster sampling was applied to recruit the migrant and urban elderly in Hangzhou from May to August, 2013. Data were collected from face-to-face interviews by trained college students using a standardized questionnaire. Social capital measurements included cognitive (generalized trust and reciprocity) and structure (support from individual and social contact) aspects. Depression was measured by Geriatric Depression Scale-30 (GDS-30). Chi-square tests and binary logistic regression models were used for analysis. A total of 1248 migrant elderly and 1322 urban elderly were eligible for analysis. After adjusting for a range of confounder factors, binary logistic regression models revealed that migrant elderly reported significantly lower levels of generalized trust [OR = 1.34, 95% CI (1.10-1.64)], reciprocity [OR = 1.55, 95% CI (1.29-1.87)], support from individual [OR = 1.96, 95% CI (1.61-2.38)] and social contact [OR = 3.27, 95% CI (2.70-3.97)]. In the full adjusted model, migrant elderly were more likely to be mentally unhealthy [OR = 1.85, 95% CI (1.44-2.36)] compared with urban elderly. Migrant elderly suffered from a lower mental health status and social capital than their urban counterparts in the emigrating city. Attention should focus on improving the social capital and mental health of this growing population.

Technical and physical analysis of the 2014 FIFA World Cup Brazil: winners vs. losers.

PubMed

Rumpf, Michael C; Silva, Joao R; Hertzog, Maxime; Farooq, Abdulaziz; Nassis, George

2017-10-01

The purpose of the present study was to investigate the technical and physical performance parameters that distinguish between teams winning and losing matches in the 2014 FIFA World Cup Brazil. Data were derived from the FIFA website and from live-statistics provided during each game of the world cup. Twelve physical (such as total distance covered in meters (TD), TD in distinct locomotor categories: low-intensity running (LIR; <11 km/h), moderate-intensity running (MIR; 11 to 14 km/h) and high-intensity-running (HIR; >14 km/h)) and 21 technical parameters (total passes, short-, medium- and long-distance passes, total pass completion rate, dangerous attacks, attacking attempts, delivery in penalty area, ball possession, goals, goals from set-pieces, goals per shot on goal, defending saves, shots, shots on goal, shot accuracy, set-pieces, crosses, corners, clearances, yellow cards) were analyzed. Forty-two games in which a winner and consequently a loser were presented after 90 minutes of game time were investigated with independent t-tests. A binary-logistic regression was utilized to investigate whether the significant variables predicted success of the winning teams. The winning teams scored significantly (P<0.05) greater amount of goals, goals per set-pieces, goals per shots on goals, shots on goal and shot accuracy and received significantly lower yellow cards. The binary-logistic regression utilized showed that shot accuracy was the best predictor for success. The physical parameters did not differ between teams winning and losing a match. Technical performance related to goal scoring parameters play a decisive role in World Cup games. Furthermore, scoring efficacy from open-play as well as from set-pieces are crucial to win matches in a World Cup tournament. At this level, physical performance was not the factor to discriminate between winners and losers.

Socio-Economic, Demographic and Lifestyle Determinants of Overweight and Obesity among Adults of Northeast India.

PubMed

Rengma, Melody Seb; Sen, Jaydip; Mondal, Nitish

2015-07-01

Overweight and obesity are the accumulation of high body adiposity, which can have detrimental health effects and contribute to the development of numerous preventable non-communicable diseases. This study aims to evaluate the effect of socio-economic, demographic and lifestyle factors on the prevalence of overweight and obesity among adults belonging to the Rengma-Naga population of North-east India. This cross-sectional study was conducted among 826 Rengma-Naga individuals (males: 422; females: 404) aged 20-49 years from the Karbi Anglong District of Assam, using a two-stage stratified random sampling. The socio-economic, demographic and lifestyle variables were recorded using structured schedules. Height and weight were recorded and the Body Mass Index (BMI) was calculated using standard procedures and equation. The WHO (2000) cut-off points were utilized to assess the prevalence of overweight (BMI ≥23.00-24.99 kg/m(2)) and obesity (BMI ≥25.00 kg/m(2)). The data were analysed using ANOVA, chi-square analysis and binary logistic regression analysis using SPSS (version 17.0). The prevalence of overweight and obesity were 32.57% (males: 39.34%; females: 25.50%) and 10.77% (males: 9.95%; females: 11.63%), respectively. The binary logistic regression analysis showed that age groups (e.g., 40-49 years), education (≥9(th) standard), part-time occupation and monthly income (≥Rs.10000) were significantly associated with overweight and obesity (p<0.05). Age, education occupation and income appear to have higher associations with overweight and obesity among adults. Suitable healthcare strategies and intervention programmes are needed for combating such prevalence in population.

Clinical utility of calf front hoof circumference and maternal intrapelvic area in predicting dystocia in 103 late gestation Holstein-Friesian heifers and cows.

PubMed

Hiew, Mark W H; Megahed, Ameer A; Townsend, Jonathan R; Singleton, Wayne L; Constable, Peter D

2016-02-01

The objective of this study was to determine the clinical utility of measuring calf front hoof circumference, maternal intrapelvic area, and selected morphometric values in predicting dystocia in dairy cattle. An observational study using a convenience sample of 103 late-gestation Holstein-Friesian heifers and cows was performed. Intrapelvic height and width of the dam were measured using a pelvimeter, and the intrapelvic area was calculated. Calf front hoof circumference and birth weight were also measured. Data were analyzed using Spearman's correlation coefficient (rs), Mann-Whitney U test, and binary or ordered logistic regression; P < 0.05 was significant. The calving difficulty score (1-5) was greater in heifers (median, 3.0) than in cows (median, 1.0). Median intrapelvic area immediately before parturition was smaller in heifers (268 cm(2)) than in cows (332 cm(2)), whereas front hoof circumference and birth weight of the calf were similar in both groups. The calving difficulty score was positively associated with calf birth weight in heifers (rs = 0.39) and cows (rs = 0.24). Binary logistic regression using both dam and calf data indicated that the ratio of front hoof circumference of the calf to the maternal intrapelvic area provided the best predictor of dystocia (calving difficulty score = 4 or 5), with sensitivity = 0.50 and specificity = 0.93 at the optimal cutpoint for the ratio (>0.068 cm/cm(2)). Determining the ratio of calf front hoof circumference to maternal intrapelvic area has clinical utility in predicting the calving difficulty score in Holstein-Friesian cattle. Copyright © 2016 Elsevier Inc. All rights reserved.

In-hospital mortality after pre-treatment with antiplatelet agents or oral anticoagulants and hematoma evacuation of intracerebral hematomas.

PubMed

Stein, Marco; Misselwitz, Björn; Hamann, Gerhard F; Kolodziej, Malgorzata; Reinges, Marcus H T; Uhl, Eberhard

2016-04-01

Pre-treatment with antiplatelet agents is described to be a risk factor for mortality after spontaneous intracerebral hemorrhage (ICH). However, the impact of antithrombotic agents on mortality in patients who undergo hematoma evacuation compared to conservatively treated patients with ICH remains controversial. This analysis is based on a prospective registry for quality assurance in stroke care in the State of Hesse, Germany. Patients' data were collected between January 2008 and December 2012. Only patients with the diagnosis of spontaneous ICH were included (International Classification of Diseases 10th Revision codes I61.0-I61.9). Predictors of in-hospital mortality were determined by univariate analysis. Predictors with P<0.1 were included in a binary logistic regression model. The binary logistic regression model was adjusted for age, initial Glasgow Coma Score (GCS), the presence of intraventricular hemorrhage (IVH), and pre-ICH disability prior to ictus. In 8,421 patients with spontaneous ICH, pre-treatment with oral anticoagulants or antiplatelet agents was documented in 16.3% and 25.1%, respectively. Overall in-hospital mortality was 23.2%. In-hospital mortality was decreased in operatively treated patients compared to conservatively treated patients (11.6% versus 24.0%; P<0.001). Patients with antiplatelet pre-treatment had a significantly higher risk of death during the hospital stay after hematoma evacuation (odds ratio [OR]: 2.5; 95% confidence interval [CI]: 1.24-4.97; P=0.010) compared to patients without antiplatelet pre-treatment treatment (OR: 0.9; 95% CI: 0.79-1.09; P=0.376). In conclusion a higher rate of in-hospital mortality after pre-treatment with antiplatelet agents in combination with hematoma evacuation after spontaneous ICH was observed in the presented cohort. Copyright © 2015 Elsevier Ltd. All rights reserved.

Using the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) for Predicting Institutionalization of Patients With Dementia in Taiwan

PubMed Central

Huang, Shih-Wei; Chang, Kwang-Hwa; Escorpizo, Reuben; Hu, Chaur-Jong; Chi, Wen-Chou; Yen, Chia-Feng; Liao, Hua-Fang; Chiu, Wen-Ta; Liou, Tsan-Hon

2015-01-01

Abstract World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is an assessment tool and it has been applied for disability status assessment of Taiwanese dementia patients since July 2012. The aim of this study was to investigate the predicting accuracy of WHODAS 2.0 for institutionalization of dementia patients. Of these patients, 13,774 resided in a community and 4406 in a long-term care facility. Demographic data and WHODAS 2.0 standardized scores were analyzed using the Chi-square test and independent t test to compare patients with dementia in an institution with those in a community. The receiver operating characteristic (ROC) curve was applied to investigate accuracy in predicting institutionalization, and the optimal cutoff point was determined using the Youden index. Binary logistic regression was used to analyze variables to determine risk factors for the institutionalization of patients with dementia. WHODAS 2.0 scores in all domains were higher in patients with dementia in a long-term care facility than in those in a community (P < 0.01). The ROC curve showed moderate accuracy for all domains of WHODAS 2.0 (area under curve 0.6∼0.8). Binary logistic regression revealed that the male gender, severity of disease, and standardized WHODAS 2.0 scores surpassing the cutoff values were risk factors for the institutionalization of patients with dementia. Although the accuracy of WHODAS 2.0 in predicting institutionalization is not considerably high for patients with dementia, our study found that the WHODAS 2.0 scores, the male gender, education status, urbanization level, and severity of disease were risk factors for institutionalization in long-term care facilities. PMID:26632747

Expression of p53 Breast Cancer in Kurdish Women in the West of Iran: a Reverse Correlation with Lymph Node Metastasis.

PubMed

Payandeh, Mehrdad; Sadeghi, Masoud; Sadeghi, Edris; Madani, Seyed-Hamid

2016-01-01

In breast cancer (BC), it has been suggested that nuclear overexpression of p53 protein might be an indicator of poor prognosis. The aim of the current study was to evaluate the expression of p53 BC in Kurdish women from the West of Iran and its correlation with other clinicopathology figures. In the present retrospective study, 231 patients were investigated for estrogen receptor (ER) and progesterone receptor (PR) positivity, defined as ≥10% positive tumor cells with nuclear staining. A binary logistic regression model was selected using Akaike Information Criteria (AIC) in stepwise selection for determination of important factors. ER, PR, the human epidermal growth factor receptor 2 (HER2) and p53 were positive in 58.4%, 55.4%, 59.7% and 45% of cases, respectively. Ki67 index was divided into two groups: 54.5% had Ki67<20% and 45.5% had Ki67 ≥20%. Of 214 patients, 137(64%) had lymph node metastasis and of 186 patients, 122(65.6%) had vascular invasion. Binary logistic regression analysis showed that there was inverse significant correlation between lymph node metastasis (P=0.008, OR 0.120 and 95%CI 0.025-0.574), ER status (P=0.006, OR 0.080, 95%CI 0.014-0.477) and a direct correlation between HER2 (P=005, OR 3.047, 95%CI 1.407-6.599) with the expression of p53. As in a number of studies, expression of p53 had a inverse correlation with lymph node metastasis and ER status and also a direct correlation with HER2 status. Also, p53-positivity is more likely in triple negative BC compared to other subtypes.

Prevalence of kidney stones in China: an ultrasonography based cross-sectional study.

PubMed

Zeng, Guohua; Mai, Zanlin; Xia, Shujie; Wang, Zhiping; Zhang, Keqin; Wang, Li; Long, Yongfu; Ma, Jinxiang; Li, Yi; Wan, Show P; Wu, Wenqi; Liu, Yongda; Cui, Zelin; Zhao, Zhijian; Qin, Jing; Zeng, Tao; Liu, Yang; Duan, Xiaolu; Mai, Xin; Yang, Zhou; Kong, Zhenzhen; Zhang, Tao; Cai, Chao; Shao, Yi; Yue, Zhongjin; Li, Shujing; Ding, Jiandong; Tang, Shan; Ye, Zhangqun

2017-07-01

To investigate the prevalence and associated factors of kidney stones among adults in China. A nationwide cross-sectional survey was conducted among individuals aged ≥18 years across China, from May 2013 to July 2014. Participants underwent urinary tract ultrasonographic examinations, completed pre-designed and standardised questionnaires, and provided blood and urine samples for analysis. Kidney stones were defined as particles of ≥4 mm. Prevalence was defined as the proportion of participants with kidney stones and binary logistic regression was used to estimate the associated factors. A total of 12 570 individuals (45.2% men) with a mean (sd, range) age of 48.8 (15.3, 18-96) years were selected and invited to participate in the study. In all, 9310 (40.7% men) participants completed the investigation, with a response rate of 74.1%. The prevalence of kidney stones was 6.4% [95% confidence interval (CI) 5.9, 6.9], and the age- and sex-adjusted prevalence was 5.8% (95% CI 5.3, 6.3; 6.5% in men and 5.1% in women). Binary logistic regression analysis showed that male gender, rural residency, age, family history of urinary stones, concurrent diabetes mellitus and hyperuricaemia, increased consumption of meat, and excessive sweating were all statistically significantly associated with a greater risk of kidney stones. By contrast, consumption of more tea, legumes, and fermented vinegar was statistically significantly associated with a lesser risk of kidney stone formation. Kidney stones are common among Chinese adults, with about one in 17 adults affected currently. Some Chinese dietary habits may lower the risk of kidney stone formation. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Acculturation and healthy lifestyle habits among Hispanics in United States-Mexico border communities.

PubMed

Ghaddar, Suad; Brown, Cynthia J; Pagán, José A; Díaz, Violeta

2010-09-01

To explore the relationship between acculturation and healthy lifestyle habits in the largely Hispanic populations living in underserved communities in the United States of America along the U.S.-Mexico border. A cross-sectional study was conducted from April 2006 to June 2008 using survey data from the Alliance for a Healthy Border, a program designed to reduce health disparities in the U.S.-Mexico border region by funding nutrition and physical activity education programs at 12 federally qualified community health centers in Arizona, California, New Mexico, and Texas. The survey included questions on acculturation, diet, exercise, and demographic factors and was completed by 2,381 Alliance program participants, of whom 95.3% were Hispanic and 45.4% were under the U.S. poverty level for 2007. Chi-square (χ2) and Student's t tests were used for bivariate comparisons between acculturation and dietary and physical activity measures. Linear regression and binary logistic regression were used to control for factors associated with nutrition and exercise. Based on univariate tests and confirmed by regression analysis controlling for sociodemographic and health variables, less acculturated survey respondents reported a significantly higher frequency of fruit and vegetable consumption and healthier dietary habits than those who were more acculturated. Adjusted binary logistic regression confirmed that individuals with low language acculturation were less likely to engage in physical activity than those with moderate to high acculturation (odds ratio 0.75, 95% confidence interval 0.59-0.95). Findings confirmed an association between acculturation and healthy lifestyle habits and supported the hypothesis that acculturation in border community populations tends to decrease the practice of some healthy dietary habits while increasing exposure to and awareness of the importance of other healthy behaviors.

No compelling positive association between ovarian hormones and wearing red clothing when using multinomial analyses.

PubMed

Blake, Khandis R; Dixson, Barnaby J W; O'Dean, Siobhan M; Denson, Thomas F

2017-04-01

Several studies report that wearing red clothing enhances women's attractiveness and signals sexual proceptivity to men. The associated hypothesis that women will choose to wear red clothing when fertility is highest, however, has received mixed support from empirical studies. One possible cause of these mixed findings may be methodological. The current study aimed to replicate recent findings suggesting a positive association between hormonal profiles associated with high fertility (high estradiol to progesterone ratios) and the likelihood of wearing red. We compared the effect of the estradiol to progesterone ratio on the probability of wearing: red versus non-red (binary logistic regression); red versus neutral, black, blue, green, orange, multi-color, and gray (multinomial logistic regression); and each of these same colors in separate binary models (e.g., green versus non-green). Red versus non-red analyses showed a positive trend between a high estradiol to progesterone ratio and wearing red, but the effect only arose for younger women and was not robust across samples. We found no compelling evidence for ovarian hormones increasing the probability of wearing red in the other analyses. However, we did find that the probability of wearing neutral was positively associated with the estradiol to progesterone ratio, though the effect did not reach conventional levels of statistical significance. Findings suggest that although ovarian hormones may affect younger women's preference for red clothing under some conditions, the effect is not robust when differentiating amongst other colors of clothing. In addition, the effect of ovarian hormones on clothing color preference may not be specific to the color red. Copyright © 2017 Elsevier Inc. All rights reserved.

Frontal lobe function and behavioral changes in amyotrophic lateral sclerosis: a study from Southwest China.

PubMed

Wei, QianQian; Chen, XuePing; Zheng, ZhenZhen; Huang, Rui; Guo, XiaoYan; Cao, Bei; Zhao, Bi; Shang, Hui-Fang

2014-12-01

Despite growing interest, the frequency and characteristics of frontal lobe functional and behavioral deficits in Chinese people with amyotrophic lateral sclerosis (ALS), as well as their impact on the survival of ALS patients, remain unknown. The Chinese version of the frontal assessment battery (FAB) and frontal behavioral inventory (FBI) were used to evaluate 126 sporadic ALS patients and 50 healthy controls. The prevalence of frontal lobe dysfunction was 32.5%. The most notable impairment domain of the FAB was lexical fluency (30.7%). The binary logistic regression model revealed that an onset age older than 45 years (OR 5.976, P = 0.002) and a lower educational level (OR 0.858, P = 0.002) were potential determinants of an abnormal FAB. Based on the FBI score, 46.0% of patients showed varied degrees of frontal behavioral changes. The most common impaired neurobehavioral domains were irritability (25.4%), logopenia (20.6%) and apathy (19.0%). The binary logistic regression model revealed that the ALS Functional Rating Scale-Revised scale score (OR 0.127, P = 0.001) was a potential determinant of an abnormal FBI. Frontal functional impairment and the severity of frontal behavioral changes were not associated with the survival status or the progression of ALS by the cox proportional hazard model and multivariate regression analyses, respectively. Frontal lobe dysfunction and frontal behavioral changes are common in Chinese ALS patients. Frontal lobe dysfunction may be related to the onset age and educational level. The severity of frontal behavioral changes may be associated with the ALSFRS-R. However, the frontal functional impairment and the frontal behavioral changes do not worsen the progression or survival of ALS.

Empirical study of seven data mining algorithms on different characteristics of datasets for biomedical classification applications.

PubMed

Zhang, Yiyan; Xin, Yi; Li, Qin; Ma, Jianshe; Li, Shuai; Lv, Xiaodan; Lv, Weiqi

2017-11-02

Various kinds of data mining algorithms are continuously raised with the development of related disciplines. The applicable scopes and their performances of these algorithms are different. Hence, finding a suitable algorithm for a dataset is becoming an important emphasis for biomedical researchers to solve practical problems promptly. In this paper, seven kinds of sophisticated active algorithms, namely, C4.5, support vector machine, AdaBoost, k-nearest neighbor, naïve Bayes, random forest, and logistic regression, were selected as the research objects. The seven algorithms were applied to the 12 top-click UCI public datasets with the task of classification, and their performances were compared through induction and analysis. The sample size, number of attributes, number of missing values, and the sample size of each class, correlation coefficients between variables, class entropy of task variable, and the ratio of the sample size of the largest class to the least class were calculated to character the 12 research datasets. The two ensemble algorithms reach high accuracy of classification on most datasets. Moreover, random forest performs better than AdaBoost on the unbalanced dataset of the multi-class task. Simple algorithms, such as the naïve Bayes and logistic regression model are suitable for a small dataset with high correlation between the task and other non-task attribute variables. K-nearest neighbor and C4.5 decision tree algorithms perform well on binary- and multi-class task datasets. Support vector machine is more adept on the balanced small dataset of the binary-class task. No algorithm can maintain the best performance in all datasets. The applicability of the seven data mining algorithms on the datasets with different characteristics was summarized to provide a reference for biomedical researchers or beginners in different fields.

Correlates of anal sex roles among Malay and Chinese MSM in Kuala Lumpur, Malaysia.

PubMed

Dangerfield, Derek T; Gravitt, Patti; Rompalo, Anne M; Tai, Raymond; Lim, Sin How

2016-03-01

Identifying roles for anal sex is an important issue for populations of MSM. We describe the prevalence of identifying as being 'top', 'bottom', 'versatile', or 'don't know/not applicable' among Malay and Chinese MSM in Kuala Lumpur, Malaysia, and behavioural outcomes according to these labels for sexual role identity. Data analysis was conducted on a survey administered during weekly outreach throughout Kuala Lumpur in 2012. Pearson's Chi square tests were used to compare demographic and behavioural characteristics of MSM who reported roles for anal sex. Binary logistic regression was used to explore the odds of behavioural outcomes among MSM who identified as 'bottom', 'versatile,' and 'don't know' compared to MSM who reported that 'top' was their sexual role. Labels for anal sex roles were significantly associated with condom use for last anal sex. Among MSM who used labels for anal sex roles, MSM who identified as 'bottom' had highest level of not using condoms for last anal sex (24.1%, p = .045). In binary logistic regression model, identifying as 'top' was significantly associated with reporting using a condom during last anal sex and reported consistent condom use for anal sex in the past six months (p = .039 and .017, respectively). With regard to sexual role identity, some MSM may be a part of a special subgroup of at-risk men to be targeted. Future research should evaluate the origins, meanings, and perceptions of these labels, and the developmental process of how these MSM identify with any of these categories. Research should also uncover condom use decision making with regard to these labels for sexual positioning. © The Author(s) 2016.

Disposal of children's stools and its association with childhood diarrhea in India.

PubMed

Bawankule, Rahul; Singh, Abhishek; Kumar, Kaushalendra; Pedgaonkar, Sarang

2017-01-05

Children's stool disposal is often overlooked in sanitation programs of any country. Unsafe disposal of children's stool makes children susceptible to many diseases that transmit through faecal-oral route. Therefore, the study aims to examine the magnitude of unsafe disposal of children's stools in India, the factors associated with it and finally its association with childhood diarrhea. Data from the third round of the National Family Health Survey (NFHS-3) conducted in 2005-06 is used to carry out the analysis. The binary logistic regression model is used to examine the factors associated with unsafe disposal of children's stool. Binary logistic regression is also used to examine the association between unsafe disposal of children's stool and childhood diarrhea. Overall, stools of 79% of children in India were disposed of unsafely. The urban-rural gap in the unsafe disposal of children's stool was wide. Mother's illiteracy and lack of exposure to media, the age of the child, religion and caste/tribe of the household head, wealth index, access to toilet facility and urban-rural residence were statistically associated with unsafe disposal of stool. The odds of diarrhea in children whose stools were disposed of unsafely was estimated to be 11% higher (95% CI: 1.01-1.21) than that of children whose stools were disposed of safely. An increase in the unsafe disposal of children's stool in the community also increased the risk of diarrhea in children. We found significant statistical association between children's stool disposal and diarrhea. Therefore, gains in reduction of childhood diarrhea can be achieved in India through the complete elimination of unsafe disposal of children's stools. The sanitation programmes currently being run in India must also focus on safe disposal of children's stool.

Relationships between stressful life events and impaired fasting glucose among left-behind farmers in rural China.

PubMed

Liang, Han; Cheng, Jing; Shen, Xingrong; Chen, Penglai; Tong, Guixian; Chai, Jing; Li, Kaichun; Xie, Shaoyu; Shi, Yong; Wang, Debin; Sun, Yehuan

2015-02-01

This study aims at examining the effects of stressful life events on risk of impaired fasting glucose among left-behind farmers in rural China. The study collected data about stressful life events, family history of diabetes, lifestyle, demographics and minimum anthropometrics from left-behind famers aged 40-70 years. Calculated life event index was applied to assess the combined effects of stressful life events experienced by the left-behind farmers and its association with impaired fasting glucose was estimated using binary logistic regression models. The prevalence of abnormal fasting glucose was 61.4% by American Diabetes Association (ADA) standard and 32.4% by World Health Organization (WHO) standard. Binary logistic regression analysis revealed a coefficient of 0.033 (P<.001) by ADA standard or 0.028 (P<.001) by WHO standard between impaired fasting glucose and life event index. The overall odds ratios of impaired glucose for the second, third and fourth (highest) versus the first (lowest) quartile of life event index were 1.419 [95% CI=(1.173, 1.717)], 1.711 [95% CI=(1.413, 2.071)] and 1.957 [95% CI=(1.606, 2.385)] respectively by ADA standard. When more and more confounding factors were controlled for, these odds ratios remained statistically significant though decreased to a small extent. The left-behind farmers showed over two-fold prevalence rate of pre-diabetes than that of the nation's average and their risk of impaired fasting glucose was positively associated with stressful life events in a dose-dependent way. Both the population studied and their life events merit special attention. Copyright © 2014 Elsevier Inc. All rights reserved.

Probability estimation with machine learning methods for dichotomous and multicategory outcome: theory.

PubMed

Kruppa, Jochen; Liu, Yufeng; Biau, Gérard; Kohler, Michael; König, Inke R; Malley, James D; Ziegler, Andreas

2014-07-01

Probability estimation for binary and multicategory outcome using logistic and multinomial logistic regression has a long-standing tradition in biostatistics. However, biases may occur if the model is misspecified. In contrast, outcome probabilities for individuals can be estimated consistently with machine learning approaches, including k-nearest neighbors (k-NN), bagged nearest neighbors (b-NN), random forests (RF), and support vector machines (SVM). Because machine learning methods are rarely used by applied biostatisticians, the primary goal of this paper is to explain the concept of probability estimation with these methods and to summarize recent theoretical findings. Probability estimation in k-NN, b-NN, and RF can be embedded into the class of nonparametric regression learning machines; therefore, we start with the construction of nonparametric regression estimates and review results on consistency and rates of convergence. In SVMs, outcome probabilities for individuals are estimated consistently by repeatedly solving classification problems. For SVMs we review classification problem and then dichotomous probability estimation. Next we extend the algorithms for estimating probabilities using k-NN, b-NN, and RF to multicategory outcomes and discuss approaches for the multicategory probability estimation problem using SVM. In simulation studies for dichotomous and multicategory dependent variables we demonstrate the general validity of the machine learning methods and compare it with logistic regression. However, each method fails in at least one simulation scenario. We conclude with a discussion of the failures and give recommendations for selecting and tuning the methods. Applications to real data and example code are provided in a companion article (doi:10.1002/bimj.201300077). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Primordial main equence binary stars in the globular cluster M71

NASA Technical Reports Server (NTRS)

Yan, Lin; Mateo, Mario

1994-01-01

We report the identification of five short-period variables near the center of the metal-rich globular cluster M71. Our observations consist of multiepoch VI charge coupled device (CCD) images centered on the cluster and covering a 6.3 min x 6.3 min field. Four of these variables are contact eclipsing binaries with periods between 0.35 and 0.41 days; one is a detached or semidetached eclipsing binary with a period of 0.56 days. Two of the variables were first identified as possible eclipsing binaries in an earlier survey by Hodder et al. (1992). We have used a variety of arguments to conclude that all five binary stars are probable members of M71, a result that is consistent with the low number (0.15) of short-period field binaries expected along this line of sight. Based on a simple model of how contact binaries evolve from initially detached binaries, we have determined a lower limit of 1.3% on the frequency of primordial binaries in M71 with initial orbital periods in the range 2.5 - 5 days. This implies that the overall primordial binary frequency, f, is 22(sup +26)(sub -12)% assuming df/d log P = const ( the 'flat' distribution), or f = 57(sup +15)(sub -8)% for df/d log P = 0.032 log P + const as observed for G-dwarf binaries in the solar neighborhood (the 'sloped' distribution). Both estimates of f correspond to binaries with initial periods shorter than 800 yr since any longer-period binaries would have been disrupted over the lifetime of the cluster. Our short-period binary frequency is in excellent agreement with the observed frequency of red-giant binaries observed in globulars if we adopt the flat distribution. For the sloped distribution, our results significantly overestimate the number of red-giant binaries. All of the short-period M71 binaries lie within 1 mag of the luminosity of the cluster turnoff in the color-magnitude diagram despite the fact we should have easily detected similar eclipsing binaries 2 - 2.5 mag fainter than this. We discuss the implications of this on our estimates of the binary frequency in M71 and on the formation of blue stragglers.

Intermediate and advanced topics in multilevel logistic regression analysis

PubMed Central

Merlo, Juan

2017-01-01

Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher‐level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within‐cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population‐average effect of covariates measured at the subject and cluster level, in contrast to the within‐cluster or cluster‐specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster‐level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28543517

Intermediate and advanced topics in multilevel logistic regression analysis.

PubMed

Austin, Peter C; Merlo, Juan

2017-09-10

Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Rotation invariant deep binary hashing for fast image retrieval

NASA Astrophysics Data System (ADS)

Dai, Lai; Liu, Jianming; Jiang, Aiwen

2017-07-01

In this paper, we study how to compactly represent image's characteristics for fast image retrieval. We propose supervised rotation invariant compact discriminative binary descriptors through combining convolutional neural network with hashing. In the proposed network, binary codes are learned by employing a hidden layer for representing latent concepts that dominate on class labels. A loss function is proposed to minimize the difference between binary descriptors that describe reference image and the rotated one. Compared with some other supervised methods, the proposed network doesn't have to require pair-wised inputs for binary code learning. Experimental results show that our method is effective and achieves state-of-the-art results on the CIFAR-10 and MNIST datasets.

Binary pulsar evolution: unveiled links and new species

NASA Astrophysics Data System (ADS)

Possenti, Andrea

2013-03-01

In the last years a series of blind and/or targeted pulsar searches led to almost triple the number of known binary pulsars in the galactic field with respect to a decade ago. The focus will be on few outliers, which are emerging from the average properties of the enlarged binary pulsar population. Some of them may represent the long sought missing links between two kinds of neutron star binaries, while others could represent the stereotype of new groups of binaries, resulting from an evolutionary path which is more exotic than those considered until recently. In particular, a new class of binaries, which can be dubbed Ultra Low Mass Binary Pulsars (ULMBPs), is emerging from recent data.

Pulsars in binary systems: probing binary stellar evolution and general relativity.

PubMed

Stairs, Ingrid H

2004-04-23

Radio pulsars in binary orbits often have short millisecond spin periods as a result of mass transfer from their companion stars. They therefore act as very precise, stable, moving clocks that allow us to investigate a large set of otherwise inaccessible astrophysical problems. The orbital parameters derived from high-precision binary pulsar timing provide constraints on binary evolution, characteristics of the binary pulsar population, and the masses of neutron stars with different mass-transfer histories. These binary systems also test gravitational theories, setting strong limits on deviations from general relativity. Surveys for new pulsars yield new binary systems that increase our understanding of all these fields and may open up whole new areas of physics, as most spectacularly evidenced by the recent discovery of an extremely relativistic double-pulsar system.

Ensemble of trees approaches to risk adjustment for evaluating a hospital's performance.

PubMed

Liu, Yang; Traskin, Mikhail; Lorch, Scott A; George, Edward I; Small, Dylan

2015-03-01

A commonly used method for evaluating a hospital's performance on an outcome is to compare the hospital's observed outcome rate to the hospital's expected outcome rate given its patient (case) mix and service. The process of calculating the hospital's expected outcome rate given its patient mix and service is called risk adjustment (Iezzoni 1997). Risk adjustment is critical for accurately evaluating and comparing hospitals' performances since we would not want to unfairly penalize a hospital just because it treats sicker patients. The key to risk adjustment is accurately estimating the probability of an Outcome given patient characteristics. For cases with binary outcomes, the method that is commonly used in risk adjustment is logistic regression. In this paper, we consider ensemble of trees methods as alternatives for risk adjustment, including random forests and Bayesian additive regression trees (BART). Both random forests and BART are modern machine learning methods that have been shown recently to have excellent performance for prediction of outcomes in many settings. We apply these methods to carry out risk adjustment for the performance of neonatal intensive care units (NICU). We show that these ensemble of trees methods outperform logistic regression in predicting mortality among babies treated in NICU, and provide a superior method of risk adjustment compared to logistic regression.

Regression trees for predicting mortality in patients with cardiovascular disease: What improvement is achieved by using ensemble-based methods?

PubMed Central

Austin, Peter C; Lee, Douglas S; Steyerberg, Ewout W; Tu, Jack V

2012-01-01

In biomedical research, the logistic regression model is the most commonly used method for predicting the probability of a binary outcome. While many clinical researchers have expressed an enthusiasm for regression trees, this method may have limited accuracy for predicting health outcomes. We aimed to evaluate the improvement that is achieved by using ensemble-based methods, including bootstrap aggregation (bagging) of regression trees, random forests, and boosted regression trees. We analyzed 30-day mortality in two large cohorts of patients hospitalized with either acute myocardial infarction (N = 16,230) or congestive heart failure (N = 15,848) in two distinct eras (1999–2001 and 2004–2005). We found that both the in-sample and out-of-sample prediction of ensemble methods offered substantial improvement in predicting cardiovascular mortality compared to conventional regression trees. However, conventional logistic regression models that incorporated restricted cubic smoothing splines had even better performance. We conclude that ensemble methods from the data mining and machine learning literature increase the predictive performance of regression trees, but may not lead to clear advantages over conventional logistic regression models for predicting short-term mortality in population-based samples of subjects with cardiovascular disease. PMID:22777999

KEPLER ECLIPSING BINARIES WITH STELLAR COMPANIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gies, D. R.; Matson, R. A.; Guo, Z.

2015-12-15

Many short-period binary stars have distant orbiting companions that have played a role in driving the binary components into close separation. Indirect detection of a tertiary star is possible by measuring apparent changes in eclipse times of eclipsing binaries as the binary orbits the common center of mass. Here we present an analysis of the eclipse timings of 41 eclipsing binaries observed throughout the NASA Kepler mission of long duration and precise photometry. This subset of binaries is characterized by relatively deep and frequent eclipses of both stellar components. We present preliminary orbital elements for seven probable triple stars amongmore » this sample, and we discuss apparent period changes in seven additional eclipsing binaries that may be related to motion about a tertiary in a long period orbit. The results will be used in ongoing investigations of the spectra and light curves of these binaries for further evidence of the presence of third stars.« less

Extrasolar binary planets. I. Formation by tidal capture during planet-planet scattering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ochiai, H.; Nagasawa, M.; Ida, S., E-mail: nagasawa.m.ad@m.titech.ac.jp

2014-08-01

We have investigated (1) the formation of gravitationally bounded pairs of gas-giant planets (which we call 'binary planets') from capturing each other through planet-planet dynamical tide during their close encounters and (2) the subsequent long-term orbital evolution due to planet-planet and planet-star quasi-static tides. For the initial evolution in phase 1, we carried out N-body simulations of the systems consisting of three Jupiter-mass planets taking into account the dynamical tide. The formation rate of the binary planets is as much as 10% of the systems that undergo orbital crossing, and this fraction is almost independent of the initial stellarcentric semimajormore » axes of the planets, while ejection and merging rates sensitively depend on the semimajor axes. As a result of circularization by the planet-planet dynamical tide, typical binary separations are a few times the sum of the physical radii of the planets. After the orbital circularization, the evolution of the binary system is governed by long-term quasi-static tide. We analytically calculated the quasi-static tidal evolution in phase 2. The binary planets first enter the spin-orbit synchronous state by the planet-planet tide. The planet-star tide removes angular momentum of the binary motion, eventually resulting in a collision between the planets. However, we found that the binary planets survive the tidal decay for the main-sequence lifetime of solar-type stars (∼10 Gyr), if the binary planets are beyond ∼0.3 AU from the central stars. These results suggest that the binary planets can be detected by transit observations at ≳ 0.3 AU.« less

Development of a statistical model for the determination of the probability of riverbank erosion in a Meditteranean river basin

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil; Kourgialas, Nektarios; Karatzas, George; Giannakis, Georgios; Lilli, Maria; Nikolaidis, Nikolaos

2014-05-01

Riverbank erosion affects the river morphology and the local habitat and results in riparian land loss, damage to property and infrastructures, ultimately weakening flood defences. An important issue concerning riverbank erosion is the identification of the areas vulnerable to erosion, as it allows for predicting changes and assists with stream management and restoration. One way to predict the vulnerable to erosion areas is to determine the erosion probability by identifying the underlying relations between riverbank erosion and the geomorphological and/or hydrological variables that prevent or stimulate erosion. A statistical model for evaluating the probability of erosion based on a series of independent local variables and by using logistic regression is developed in this work. The main variables affecting erosion are vegetation index (stability), the presence or absence of meanders, bank material (classification), stream power, bank height, river bank slope, riverbed slope, cross section width and water velocities (Luppi et al. 2009). In statistics, logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable, e.g. binary response, based on one or more predictor variables (continuous or categorical). The probabilities of the possible outcomes are modelled as a function of independent variables using a logistic function. Logistic regression measures the relationship between a categorical dependent variable and, usually, one or several continuous independent variables by converting the dependent variable to probability scores. Then, a logistic regression is formed, which predicts success or failure of a given binary variable (e.g. 1 = "presence of erosion" and 0 = "no erosion") for any value of the independent variables. The regression coefficients are estimated by using maximum likelihood estimation. The erosion occurrence probability can be calculated in conjunction with the model deviance regarding the independent variables tested (Atkinson et al. 2003). The developed statistical model is applied to the Koiliaris River Basin in the island of Crete, Greece. The aim is to determine the probability of erosion along the Koiliaris' riverbanks considering a series of independent geomorphological and/or hydrological variables. Data for the river bank slope and for the river cross section width are available at ten locations along the river. The riverbank has indications of erosion at six of the ten locations while four has remained stable. Based on a recent work, measurements for the two independent variables and data regarding bank stability are available at eight different locations along the river. These locations were used as validation points for the proposed statistical model. The results show a very close agreement between the observed erosion indications and the statistical model as the probability of erosion was accurately predicted at seven out of the eight locations. The next step is to apply the model at more locations along the riverbanks. In November 2013, stakes were inserted at selected locations in order to be able to identify the presence or absence of erosion after the winter period. In April 2014 the presence or absence of erosion will be identified and the model results will be compared to the field data. Our intent is to extend the model by increasing the number of independent variables in order to indentify the key factors favouring erosion along the Koiliaris River. We aim at developing an easy to use statistical tool that will provide a quantified measure of the erosion probability along the riverbanks, which could consequently be used to prevent erosion and flooding events. Atkinson, P. M., German, S. E., Sear, D. A. and Clark, M. J. 2003. Exploring the relations between riverbank erosion and geomorphological controls using geographically weighted logistic regression. Geographical Analysis, 35 (1), 58-82. Luppi, L., Rinaldi, M., Teruggi, L. B., Darby, S. E. and Nardi, L. 2009. Monitoring and numerical modelling of riverbank erosion processes: A case study along the Cecina River (central Italy). Earth Surface Processes and Landforms, 34 (4), 530-546. Acknowledgements This work is part of an on-going THALES project (CYBERSENSORS - High Frequency Monitoring System for Integrated Water Resources Management of Rivers). The project has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.

Hydrodynamical processes in coalescing binary stars

NASA Astrophysics Data System (ADS)

Lai, Dong

1994-01-01

Coalescing neutron star binaries are considered to be the most promising sources of gravitational waves that could be detected by the planned laser-interferometer LIGO/VIRGO detectors. Extracting gravity wave signals from noisy data requires accurate theoretical waveforms in the frequency range 10-1000 Hz end detailed understanding of the dynamics of the binary orbits. We investigate the quasi-equilibrium and dynamical tidal interactions in coalescing binary stars, with particular focus on binary neutron stars. We develop a new formalism to study the equilibrium and dynamics of fluid stars in binary systems. The stars are modeled as compressible ellipsoids, and satisfy polytropic equation of state. The hydrodynamic equations are reduced to a set of ordinary differential equations for the evolution of the principal axes and other global quantities. The equilibrium binary structure is determined by a set of algebraic equations. We consider both synchronized and nonsynchronized systems, obtaining the generalizations to compressible fluid of the classical results for the ellipsoidal binary configurations. Our method can be applied to a wide variety of astrophysical binary systems containing neutron stars, white dwarfs, main-sequence stars and planets. We find that both secular and dynamical instabilities can develop in close binaries. The quasi-static (secular) orbital evolution, as well as the dynamical evolution of binaries driven by viscous dissipation and gravitational radiation reaction are studied. The development of the dynamical instability accelerates the binary coalescence at small separation, leading to appreciable radial infall velocity near contact. We also study resonant excitations of g-mode oscillations in coalescing binary neutron stars. A resonance occurs when the frequency of the tidal driving force equals one of the intrinsic g-mode frequencies. Using realistic microscopic nuclear equations of state, we determine the g-modes in a cold neutron atar. Resonant excitations of these g-modes during the last few minutes of the binary coalescence result in energy transfer and angular momentum transfer from the binary orbit to the neutron star. Because of the weak coupling between the g-modes and the tidal potential, the induced orbital phase errors due to resonances are small. However, resonant excitations of the g-modes play an important role in the tidal heating of binary neutron stars.

Air pollution by particulate matter PM10 may trigger multiple sclerosis relapses.

PubMed

Roux, Jonathan; Bard, Denis; Le Pabic, Estelle; Segala, Claire; Reis, Jacques; Ongagna, Jean-Claude; de Sèze, Jérôme; Leray, Emmanuelle

2017-07-01

Seasonal variation of relapses in multiple sclerosis (MS) suggests that season-dependent factors, such as ambient air pollution, may trigger them. However, only few studies have considered possible role of air pollutants as relapse's risk factor. We investigated the effect of particulate matter of aerodynamic diameter smaller than 10µm (PM 10 ) on MS relapses. In total, 536 relapsing MS patients from Strasbourg city (France) were included, accounting for 2052 relapses over 2000-2009 period. A case-crossover design was used with cases defined as the days of relapse and controls being selected in the same patient at plus and minus 35 days. Different lags from 0 to 30 days were considered. Conditional logistic regressions, adjusted on meteorological parameters, school and public holidays, were used and exposure was considered first as a quantitative variable and second, as a binary variable. The natural logarithm of the average PM 10 concentration lagged from 1 to 3 days before relapse onset was significantly associated with relapse risk (OR =1.40 [95% confidence interval 1.08-1.81]) in cold season. Consistent results were observed when considering PM 10 as a binary variable, even if not significant. With an appropriate study design and robust ascertainment of neurological events and exposure, the present study highlights the effect of PM 10 on the risk of relapse in MS patients, probably through oxidative stress mechanisms. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluating uses of data mining techniques in propensity score estimation: a simulation study.

PubMed

Setoguchi, Soko; Schneeweiss, Sebastian; Brookhart, M Alan; Glynn, Robert J; Cook, E Francis

2008-06-01

In propensity score modeling, it is a standard practice to optimize the prediction of exposure status based on the covariate information. In a simulation study, we examined in what situations analyses based on various types of exposure propensity score (EPS) models using data mining techniques such as recursive partitioning (RP) and neural networks (NN) produce unbiased and/or efficient results. We simulated data for a hypothetical cohort study (n = 2000) with a binary exposure/outcome and 10 binary/continuous covariates with seven scenarios differing by non-linear and/or non-additive associations between exposure and covariates. EPS models used logistic regression (LR) (all possible main effects), RP1 (without pruning), RP2 (with pruning), and NN. We calculated c-statistics (C), standard errors (SE), and bias of exposure-effect estimates from outcome models for the PS-matched dataset. Data mining techniques yielded higher C than LR (mean: NN, 0.86; RPI, 0.79; RP2, 0.72; and LR, 0.76). SE tended to be greater in models with higher C. Overall bias was small for each strategy, although NN estimates tended to be the least biased. C was not correlated with the magnitude of bias (correlation coefficient [COR] = -0.3, p = 0.1) but increased SE (COR = 0.7, p < 0.001). Effect estimates from EPS models by simple LR were generally robust. NN models generally provided the least numerically biased estimates. C was not associated with the magnitude of bias but was with the increased SE.

WIYN OPEN CLUSTER STUDY. XXXVI. SPECTROSCOPIC BINARY ORBITS IN NGC 188

DOE Office of Scientific and Technical Information (OSTI.GOV)

Geller, Aaron M.; Mathieu, Robert D.; Harris, Hugh C.

2009-04-15

We present 98 spectroscopic binary orbits resulting from our ongoing radial velocity survey of the old (7 Gyr) open cluster NGC 188. All but 13 are high-probability cluster members based on both radial velocity and proper motion membership analyses. Fifteen of these member binaries are double lined. Our stellar sample spans a magnitude range of 10.8 {<=}V{<=} 16.5 (1.14-0.92 M {sub sun}) and extends spatially to 17 pc ({approx}13 core radii). All of our binary orbits have periods ranging from a few days to on the order of 10{sup 3} days, and thus are hard binaries that dynamically power themore » cluster. For each binary, we present the orbital solutions and place constraints on the component masses. Additionally, we discuss a few binaries of note from our sample, identifying a likely blue straggler-blue straggler binary system (7782), a double-lined binary with a secondary star which is underluminous for its mass (5080), two potential eclipsing binaries (4705 and 5762), and two binaries which are likely members of a quadruple system (5015a and 5015b)« less

Impact of different approaches of primary care mental health on the prevalence of mental disorders.

PubMed

Moscovici, Leonardo; de Azevedo-Marques, Joao Mazzoncini; Bolsoni, Lívia Maria; Rodrigues-Junior, Antonio Luiz; Zuardi, Antonio Waldo

2018-05-01

AimTo compare the impact of three different approaches to primary care mental health on the prevalence of mental disorders. Millions of people suffer from mental disorders. As entry point into the health service, primary healthcare plays an important role in providing mental health prevention and treatment. Random sample of households in three different areas of the city of Ribeirão Preto (state of São Paulo, Brazil) were selected, and 20 trained medical students conducted interviews using a mental health screening instrument, the Mini-Screening of Mental Disorders, and a socio-demographic datasheet. Primary care mental health was provided in each area through a specific approach. The influence of the area of residence and the socio-demographic variables on the prevalence of mental disorder was explored and analyzed by univariate binary logistic regression and then by a multiple logistic regression model.FindingsA total of 1545 subjects were interviewed. Comparison between the three areas showed a significantly higher number of people with mental disorders in the area covered by the primary care team that did not have physicians with specific primary care mental health training, even when this association was adjusted for the influence of age, education, and socio-economic status.Our results suggest that residing in areas with family physicians with mental health training is associated with a lower prevalence of mental disorders.

Association between maternal smoking, gender, and cleft lip and palate.

PubMed

Martelli, Daniella Reis Barbosa; Coletta, Ricardo D; Oliveira, Eduardo A; Swerts, Mário Sérgio Oliveira; Rodrigues, Laíse A Mendes; Oliveira, Maria Christina; Martelli Júnior, Hercílio

2015-01-01

Cleft lip and/or palate (CL/P) represent the most common congenital anomalies of the face. To assess the relationship between maternal smoking, gender and CL/P. This is an epidemiological cross-sectional study. We interviewed 1519 mothers divided into two groups: mothers of children with CL/P (n=843) and mothers of children without CL/P (n=676). All mothers were classified as smoker or non-smoker subjects during the first trimester of pregnancy. To determine an association among maternal smoking, gender, and CL/P, odds ratios were calculated and the adjustment was made by a logistic regression model. An association between maternal smoking and the presence of cleft was observed. There was also a strong association between male gender and the presence of cleft (OR=3.51; 95% CI 2.83-4.37). By binary logistic regression analysis, it was demonstrated that both variables were independently associated with clefts. In a multivariate analysis, male gender and maternal smoking had a 2.5- and a 1.5-time greater chance of having a cleft, respectively. Our findings are consistent with a positive association between maternal smoking during pregnancy and CL/P in male gender. The results support the importance of smoking prevention and introduction of cessation programs among women with childbearing potential. Copyright © 2015 Associação Brasileira de Otorrinolaringologia e Cirurgia Cérvico-Facial. Published by Elsevier Editora Ltda. All rights reserved.

Farmers' Market Manager's Level of Communication and Influence on Electronic Benefits Transfer (EBT) Adoption at Midwest Farmers' Markets.

PubMed

Hasin, Afroza; Smith, Sylvia

2018-01-01

To understand market managers' level of communication and use of technology that might influence decision to adopt Electronic Benefits Transfer (EBT) at farmers' markets. Cross-sectional study using the Theory of Diffusion of Innovation. Electronic survey administered in midwest states of Illinois, Michigan, and Wisconsin. Farmers' market managers in Illinois, Michigan, and Wisconsin. Information on EBT adoption, market managers' communication, and technology use. Binary logistic regression analysis with EBT adoption as the dependent variable and frequency of technology use, partnership with organizations, farmers' market association (FMA) membership, Facebook page and Web site for the market, and primary source of information as independent variables. Chi-square tests and ANOVA were used to compare states and adopter categories. Logistic regression results showed that the odds of adopting EBT was 7.5 times higher for markets that had partnership with other organizations. Compared with non-adopters, a significantly greater number of early adopters had partnership, FMA membership, and a Facebook page and Web site for market, and reported to a board of directors. Markets that had partnership, FMA membership, a Facebook page and Web site, and mandatory reporting to a board of directors were important factors that influenced EBT adoption at midwest farmers' markets. Copyright © 2017 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Statistical Methods for Quality Control of Steel Coils Manufacturing Process using Generalized Linear Models

NASA Astrophysics Data System (ADS)

García-Díaz, J. Carlos

2009-11-01

Fault detection and diagnosis is an important problem in process engineering. Process equipments are subject to malfunctions during operation. Galvanized steel is a value added product, furnishing effective performance by combining the corrosion resistance of zinc with the strength and formability of steel. Fault detection and diagnosis is an important problem in continuous hot dip galvanizing and the increasingly stringent quality requirements in automotive industry has also demanded ongoing efforts in process control to make the process more robust. When faults occur, they change the relationship among these observed variables. This work compares different statistical regression models proposed in the literature for estimating the quality of galvanized steel coils on the basis of short time histories. Data for 26 batches were available. Five variables were selected for monitoring the process: the steel strip velocity, four bath temperatures and bath level. The entire data consisting of 48 galvanized steel coils was divided into sets. The first training data set was 25 conforming coils and the second data set was 23 nonconforming coils. Logistic regression is a modeling tool in which the dependent variable is categorical. In most applications, the dependent variable is binary. The results show that the logistic generalized linear models do provide good estimates of quality coils and can be useful for quality control in manufacturing process.

Dentists' perspectives on caries-related treatment decisions.

PubMed

Gomez, J; Ellwood, R P; Martignon, S; Pretty, I A

2014-06-01

To assess the impact of patient risk status on Colombian dentists' caries related treatment decisions for early to intermediate caries lesions (ICDAS code 2 to 4). A web-based questionnaire assessed dentists' views on the management of early/intermediate lesions. The questionnaire included questions on demographic characteristics, five clinical scenarios with randomised levels of caries risk, and two questions on different clinical and radiographic sets of images with different thresholds of caries. Questionnaires were completed by 439 dentists. For the two scenarios describing occlusal lesions ICDAS code 2, dentists chose to provide a preventive option in 63% and 60% of the cases. For the approximal lesion ICDAS code 2, 81% of the dentists chose to restore. The main findings of the binary logistic regression analysis for the clinical scenarios suggest that for the ICDAS code 2 occlusal lesions, the odds of a high caries risk patient having restorations is higher than for a low caries risk patient. For the questions describing different clinical thresholds of caries, most dentists would restore at ICDAS code 2 (55%) and for the question showing different radiographic thresholds images, 65% of dentists would intervene operatively at the inner half of enamel. No significant differences with respect to risk were found for these questions with the logistic regression. The results of this study indicate that Colombian dentists have not yet fully adopted non-invasive treatment for early caries lesions.

Human papillomavirus vaccination in Auckland: reducing ethnic and socioeconomic inequities.

PubMed

Poole, Tracey; Goodyear-Smith, Felicity; Petousis-Harris, Helen; Desmond, Natalie; Exeter, Daniel; Pointon, Leah; Jayasinha, Ranmalie

2012-12-17

The New Zealand HPV publicly funded immunisation programme commenced in September 2008. Delivery through a school based programme was anticipated to result in higher coverage rates and reduced inequalities compared to vaccination delivered through other settings. The programme provided for on-going vaccination of girls in year 8 with an initial catch-up programme through general practices for young women born after 1 January 1990 until the end of 2010. To assess the uptake of the funded HPV vaccine through school based vaccination programmes in secondary schools and general practices in 2009, and the factors associated with coverage by database matching. Retrospective quantitative analysis of secondary anonymised data School-Based Vaccination Service and National Immunisation Register databases of female students from secondary schools in Auckland District Health Board catchment area. Data included student and school demographic and other variables. Binary logistic regression was used to estimate odds ratios and significance for univariables. Multivariable logistic regression estimated strength of association between individual factors and initiation and completion, adjusted for all other factors. The programme achieved overall coverage of 71.5%, with Pacific girls highest at 88% and Maori at 78%. Girls higher socioeconomic status were more likely be vaccinated in general practice. School-based vaccination service targeted at ethic sub-populations provided equity for the Maori and Pacific student who achieved high levels of vaccination. Copyright © 2012 Elsevier Ltd. All rights reserved.

Diagnostic Algorithm to Reflect Regressive Changes of Human Papilloma Virus in Tissue Biopsies

PubMed Central

Lhee, Min Jin; Cha, Youn Jin; Bae, Jong Man; Kim, Young Tae

2014-01-01

Purpose Landmark indicators have not yet to be developed to detect the regression of cervical intraepithelial neoplasia (CIN). We propose that quantitative viral load and indicative histological criteria can be used to differentiate between atypical squamous cells of undetermined significance (ASCUS) and a CIN of grade 1. Materials and Methods We collected 115 tissue biopsies from women who tested positive for the human papilloma virus (HPV). Nine morphological parameters including nuclear size, perinuclear halo, hyperchromasia, typical koilocyte (TK), abortive koilocyte (AK), bi-/multi-nucleation, keratohyaline granules, inflammation, and dyskeratosis were examined for each case. Correlation analyses, cumulative logistic regression, and binary logistic regression were used to determine optimal cut-off values of HPV copy numbers. The parameters TK, perinuclear halo, multi-nucleation, and nuclear size were significantly correlated quantitatively to HPV copy number. Results An HPV loading number of 58.9 and AK number of 20 were optimal to discriminate between negative and subtle findings in biopsies. An HPV loading number of 271.49 and AK of 20 were optimal for discriminating between equivocal changes and obvious koilocytosis. Conclusion We propose that a squamous epithelial lesion with AK of >20 and quantitative HPV copy number between 58.9-271.49 represents a new spectrum of subtle pathological findings, characterized by AK in ASCUS. This can be described as a distinct entity and called "regressing koilocytosis". PMID:24532500

Association between Serum Cystatin C and Diabetic Foot Ulceration in Patients with Type 2 Diabetes: A Cross-Sectional Study

PubMed Central

Zhao, Jie; Deng, Wuquan; Zhang, Yuping; Zheng, Yanling; Zhou, Lina; Boey, Johnson; Armstrong, David G.; Yang, Gangyi

2016-01-01

Serum cystatin C (CysC) has been identified as a possible potential biomarker in a variety of diabetic complications, including diabetic peripheral neuropathy and peripheral artery disease. We aimed to examine the association between CysC and diabetic foot ulceration (DFU) in patients with type 2 diabetes (T2D). 411 patients with T2D were enrolled in this cross-sectional study at a university hospital. Clinical manifestations and biochemical parameters were compared between DFU group and non-DFU group. The association between serum CysC and DFU was explored by binary logistic regression analysis. The cut point of CysC for DFU was also evaluated by receiver operating characteristic (ROC) curve. The prevalence of coronary artery disease, diabetic nephropathy (DN), and DFU dramatically increased with CysC (P < 0.01) in CysC quartiles. Multivariate logistic regression analysis indicated that the significant risk factors for DFU were serum CysC, coronary artery disease, hypertension, insulin use, the differences between supine and sitting TcPO2, and hypertension. ROC curve analysis revealed that the cut point of CysC for DFU was 0.735 mg/L. Serum CysC levels correlated with DFU and severity of tissue loss. Our study results indicated that serum CysC was associated with a high prevalence of DFU in Chinese T2D subjects. PMID:27668262

Religious variations in perceived infertility and inconsistent contraceptive use among unmarried young adults in the United States.

PubMed

Burdette, Amy M; Haynes, Stacy H; Hill, Terrence D; Bartkowski, John P

2014-06-01

In this paper, we examine associations among personal religiosity, perceived infertility, and inconsistent contraceptive use among unmarried young adults (ages 18-29). The data for this investigation came from the National Survey of Reproductive and Contraceptive Knowledge (n = 1,695). We used multinomial logistic regression to model perceived infertility, adjusted probabilities to model rationales for perceived infertility, and binary logistic regression to model inconsistent contraceptive use. Evangelical Protestants were more likely than non-affiliates to believe that they were infertile. Among the young women who indicated some likelihood of infertility, evangelical Protestants were also more likely than their other Protestant or non-Christian faith counterparts to believe that they were infertile because they had unprotected sex without becoming pregnant. Although evangelical Protestants were more likely to exhibit inconsistent contraception use than non-affiliates, we were unable to attribute any portion of this difference to infertility perceptions. Whereas most studies of religion and health emphasize the salubrious role of personal religiosity, our results suggest that evangelical Protestants may be especially likely to hold misconceptions about their fertility. Because these misconceptions fail to explain higher rates of inconsistent contraception use among evangelical Protestants, additional research is needed to understand the principles and motives of this unique religious community. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Orbital motion in pre-main sequence binaries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schaefer, G. H.; Prato, L.; Simon, M.

2014-06-01

We present results from our ongoing program to map the visual orbits of pre-main sequence (PMS) binaries in the Taurus star forming region using adaptive optics imaging at the Keck Observatory. We combine our results with measurements reported in the literature to analyze the orbital motion for each binary. We present preliminary orbits for DF Tau, T Tau S, ZZ Tau, and the Pleiades binary HBC 351. Seven additional binaries show curvature in their relative motion. Currently, we can place lower limits on the orbital periods for these systems; full solutions will be possible with more orbital coverage. Five othermore » binaries show motion that is indistinguishable from linear motion. We suspect that these systems are bound and might show curvature with additional measurements in the future. The observations reported herein lay critical groundwork toward the goal of measuring precise masses for low-mass PMS stars.« less

Deep Hashing for Scalable Image Search.

PubMed

Lu, Jiwen; Liong, Venice Erin; Zhou, Jie

2017-05-01

In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for scalable image search. Unlike most existing binary codes learning methods, which usually seek a single linear projection to map each sample into a binary feature vector, we develop a deep neural network to seek multiple hierarchical non-linear transformations to learn these binary codes, so that the non-linear relationship of samples can be well exploited. Our model is learned under three constraints at the top layer of the developed deep network: 1) the loss between the compact real-valued code and the learned binary vector is minimized, 2) the binary codes distribute evenly on each bit, and 3) different bits are as independent as possible. To further improve the discriminative power of the learned binary codes, we extend DH into supervised DH (SDH) and multi-label SDH by including a discriminative term into the objective function of DH, which simultaneously maximizes the inter-class variations and minimizes the intra-class variations of the learned binary codes with the single-label and multi-label settings, respectively. Extensive experimental results on eight widely used image search data sets show that our proposed methods achieve very competitive results with the state-of-the-arts.

A deep survey of the X-ray binary populations in the SMC

NASA Astrophysics Data System (ADS)

Zezas, A.; Antoniou, V.

2017-10-01

The Small Magellanic Cloud (SMC) has been the subject of systematic X-ray surveys over the past two decades, which have yielded a rich population of high-mass X-ray binaries consisting predominantly of Be/X-ray binaries. We present results from our deep Chandra survey of the SMC which targeted regions with stellar populations ranging between ˜10-100 Myr. X-ray luminosities down to ˜3×10^{32} erg/s were reached, probing all active accreting binaries and extending well into the regime of quiescent accreting binaries and X-ray emitting normal stars. We measure the dependence of the formation efficiency of X-ray binaries on age. We also detect pulsations from 19 known and one new candidate pulsar. We construct the X-ray luminosity function in different regions of the SMC, which shows clear evidence for the propeller effect the centrifugal inhibition of accretion due to the interaction of the accretion flow with the pulsar's magnetic field. Finally we compare these results with predictions for the formation efficiency of X-ray binaries as a function of age from X-ray binary population synthesis models.

Wind-accelerated orbital evolution in binary systems with giant stars

NASA Astrophysics Data System (ADS)

Chen, Zhuo; Blackman, Eric G.; Nordhaus, Jason; Frank, Adam; Carroll-Nellenback, Jonathan

2018-01-01

Using 3D radiation-hydrodynamic simulations and analytic theory, we study the orbital evolution of asymptotic giant branch (AGB) binary systems for various initial orbital separations and mass ratios, and thus different initial accretion modes. The time evolution of binary separations and orbital periods are calculated directly from the averaged mass-loss rate, accretion rate and angular momentum loss rate. We separately consider spin-orbit synchronized and zero-spin AGB cases. We find that the angular momentum carried away by the mass loss together with the mass transfer can effectively shrink the orbit when accretion occurs via wind-Roche lobe overflow. In contrast, the larger fraction of mass lost in Bondi-Hoyle-Lyttleton accreting systems acts to enlarge the orbit. Synchronized binaries tend to experience stronger orbital period decay in close binaries. We also find that orbital period decay is faster when we account for the non-linear evolution of the accretion mode as the binary starts to tighten. This can increase the fraction of binaries that result in common envelope, luminous red novae, Type Ia supernovae and planetary nebulae with tight central binaries. The results also imply that planets in the habitable zone around white dwarfs are unlikely to be found.

Truncation of the Binary Distribution Function in Globular Cluster Formation

NASA Astrophysics Data System (ADS)

Vesperini, E.; Chernoff, David F.

1996-02-01

We investigate a population of primordial binaries during the initial stage of evolution of a star cluster. For our calculations we assume that equal-mass stars form rapidly in a tidally truncated gas cloud, that ˜10% of the stars are in binaries, and that the resulting star cluster undergoes an epoch of violent relaxation. We study the collisional interaction of the binaries and single stars, in particular, the ionization of the binaries and the energy exchange between binaries and single stars. We find that for large N systems (N > 1000), even the most violent beginning leaves the binary distribution function largely intact. Hence, the binding energy originally tied up in the cloud's protostellar pairs is preserved during the relaxation process, and the binaries are available to interact at later times within the virialized cluster.

The influence of massive black hole binaries on the morphology of merger remnants

NASA Astrophysics Data System (ADS)

Bortolas, E.; Gualandris, A.; Dotti, M.; Read, J. I.

2018-06-01

Massive black hole (MBH) binaries, formed as a result of galaxy mergers, are expected to harden by dynamical friction and three-body stellar scatterings, until emission of gravitational waves (GWs) leads to their final coalescence. According to recent simulations, MBH binaries can efficiently harden via stellar encounters only when the host geometry is triaxial, even if only modestly, as angular momentum diffusion allows an efficient repopulation of the binary loss cone. In this paper, we carry out a suite of N-body simulations of equal-mass galaxy collisions, varying the initial orbits and density profiles for the merging galaxies and running simulations both with and without central MBHs. We find that the presence of an MBH binary in the remnant makes the system nearly oblate, aligned with the galaxy merger plane, within a radius enclosing 100 MBH masses. We never find binary hosts to be prolate on any scale. The decaying MBHs slightly enhance the tangential anisotropy in the centre of the remnant due to angular momentum injection and the slingshot ejection of stars on nearly radial orbits. This latter effect results in about 1 per cent of the remnant stars being expelled from the galactic nucleus. Finally, we do not find any strong connection between the remnant morphology and the binary hardening rate, which depends only on the inner density slope of the remnant galaxy. Our results suggest that MBH binaries are able to coalesce within a few Gyr, even if the binary is found to partially erase the merger-induced triaxiality from the remnant.

The incidence of stellar mergers and mass gainers among massive stars

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Mink, S. E.; Sana, H.; Langer, N.

2014-02-10

Because the majority of massive stars are born as members of close binary systems, populations of massive main-sequence stars contain stellar mergers and products of binary mass transfer. We simulate populations of massive stars accounting for all major binary evolution effects based on the most recent binary parameter statistics and extensively evaluate the effect of model uncertainties. Assuming constant star formation, we find that 8{sub −4}{sup +9}% of a sample of early-type stars are the products of a merger resulting from a close binary system. In total we find that 30{sub −15}{sup +10}% of massive main-sequence stars are the productsmore » of binary interaction. We show that the commonly adopted approach to minimize the effects of binaries on an observed sample by excluding systems detected as binaries through radial velocity campaigns can be counterproductive. Systems with significant radial velocity variations are mostly pre-interaction systems. Excluding them substantially enhances the relative incidence of mergers and binary products in the non-radial velocity variable sample. This poses a challenge for testing single stellar evolutionary models. It also raises the question of whether certain peculiar classes of stars, such as magnetic O stars, are the result of binary interaction and it emphasizes the need to further study the effect of binarity on the diagnostics that are used to derive the fundamental properties (star-formation history, initial mass function, mass-to-light ratio) of stellar populations nearby and at high redshift.« less

Converting optical scanning holograms of real objects to binary Fourier holograms using an iterative direct binary search algorithm.

PubMed

Leportier, Thibault; Park, Min Chul; Kim, You Seok; Kim, Taegeun

2015-02-09

In this paper, we present a three-dimensional holographic imaging system. The proposed approach records a complex hologram of a real object using optical scanning holography, converts the complex form to binary data, and then reconstructs the recorded hologram using a spatial light modulator (SLM). The conversion from the recorded hologram to a binary hologram is achieved using a direct binary search algorithm. We present experimental results that verify the efficacy of our approach. To the best of our knowledge, this is the first time that a hologram of a real object has been reconstructed using a binary SLM.

Cerebrospinal fluid ferritin and albumin index: potential candidates for scoring system to differentiate between bacterial and viral meningitis in children.

PubMed

Jebamalar, Angelin A; Prabhat; Balakrishnapillai, Agiesh K; Parmeswaran, Narayanan; Dhiman, Pooja; Rajendiran, Soundravally

2016-07-01

To evaluate the diagnostic role of cerebrospinal fluid (CSF) ferritin and albumin index (AI = CSF albumin/serum albumin × 1000) in differentiating acute bacterial meningitis (ABM) from acute viral meningitis (AVM) in children. The study included 42 cases each of ABM and AVM in pediatric age group. Receiver operating characteristic (ROC) analysis was carried out for CSF ferritin and AI. Binary logistic regression was also done. CSF ferritin and AI were found significantly higher in ABM compared to AVM. Model obtained using AI and CSF ferritin along with conventional criteria is better than existing models.

Multiwavelength Challenges in the Fermi Era

NASA Technical Reports Server (NTRS)

Thompson, D. J.

2010-01-01

The gamma-ray surveys of the sky by AGILE and the Fermi Gamma-ray Space Telescope offer both opportunities and challenges for multiwavelength and multi-messenger studies. Gamma-ray bursts, pulsars, binary sources, flaring Active Galactic Nuclei, and Galactic transient sources are all phenomena that can best be studied with a wide variety of instruments simultaneously or contemporaneously. From the gamma-ray side, a principal challenge is the latency from the time of an astrophysical event to the recognition of this event in the data. Obtaining quick and complete multiwavelength coverage of gamma-ray sources of interest can be difficult both in terms of logistics and in terms of generating scientific interest.

Lincos: An interplanetary language. [mathematical method for cosmic radio contact with extraterrestrial life

NASA Technical Reports Server (NTRS)

Freudenthal, H.

1974-01-01

A language for cosmic contacts is envisioned that utilizes radio signals of different wavelengths as sounds to form words. These words are in most cases abbreviations of Latin words understood from their English and French cognates. The logistic syntax uses pauses for punctuation in a binary system; pairs of algebraic formulas are transmitted where in a such pair the second element is always derived from the first; between them is transmitted a word that is understood as -follows- by the listener. The concepts of difference in position, of motion, of space, and of mass can be mathematically described by this language.

Spirituality, Religiousness, and Alcoholism Treatment Outcomes: A Comparison between Black and White Participants

PubMed Central

Krentzman, Amy R.; Farkas, Kathleen J.; Townsend, Aloen L.

2012-01-01

This study addresses an unexplained finding in the alcoholism treatment field: despite the health and socioeconomic disparities that exist between blacks and whites at intake, blacks and whites achieve equivalent treatment outcomes. Using Project MATCH data, this study explores religiousness and spirituality as strengths in the African American community that may account in part for equivalent outcomes. Using binary logistic regression, this study found that as purpose in life increased, blacks were more likely to achieve sobriety than whites. This study provides evidence that purpose in life is a cultural strength and an advantage among blacks in achieving sobriety. PMID:22707846

Binary black hole mergers from globular clusters: Masses, merger rates, and the impact of stellar evolution

NASA Astrophysics Data System (ADS)

Rodriguez, Carl L.; Chatterjee, Sourav; Rasio, Frederic A.

2016-04-01

The recent discovery of GW150914, the binary black hole merger detected by Advanced LIGO, has the potential to revolutionize observational astrophysics. But to fully utilize this new window into the Universe, we must compare these new observations to detailed models of binary black hole formation throughout cosmic time. Expanding upon our previous work [C. L. Rodriguez, M. Morscher, B. Pattabiraman, S. Chatterjee, C.-J. Haster, and F. A. Rasio, Phys. Rev. Lett. 115, 051101 (2015).], we study merging binary black holes formed in globular clusters using our Monte Carlo approach to stellar dynamics. We have created a new set of 52 cluster models with different masses, metallicities, and radii to fully characterize the binary black hole merger rate. These models include all the relevant dynamical processes (such as two-body relaxation, strong encounters, and three-body binary formation) and agree well with detailed direct N -body simulations. In addition, we have enhanced our stellar evolution algorithms with updated metallicity-dependent stellar wind and supernova prescriptions, allowing us to compare our results directly to the most recent population synthesis predictions for merger rates from isolated binary evolution. We explore the relationship between a cluster's global properties and the population of binary black holes that it produces. In particular, we derive a numerically calibrated relationship between the merger times of ejected black hole binaries and a cluster's mass and radius. With our improved treatment of stellar evolution, we find that globular clusters can produce a significant population of massive black hole binaries that merge in the local Universe. We explore the masses and mass ratios of these binaries as a function of redshift, and find a merger rate of ˜5 Gpc-3yr-1 in the local Universe, with 80% of sources having total masses from 32 M⊙ to 64 M⊙. Under standard assumptions, approximately one out of every seven binary black hole mergers in the local Universe will have originated in a globular cluster, but we also explore the sensitivity of this result to different assumptions for binary stellar evolution. If black holes were born with significant natal kicks, comparable to those of neutron stars, then the merger rate of binary black holes from globular clusters would be comparable to that from the field, with approximately 1 /2 of mergers originating in clusters. Finally we point out that population synthesis results for the field may also be modified by dynamical interactions of binaries taking place in dense star clusters which, unlike globular clusters, dissolved before the present day.

Mass transfer in white dwarf-neutron star binaries

NASA Astrophysics Data System (ADS)

Bobrick, Alexey; Davies, Melvyn B.; Church, Ross P.

2017-05-01

We perform hydrodynamic simulations of mass transfer in binaries that contain a white dwarf and a neutron star (WD-NS binaries), and measure the specific angular momentum of material lost from the binary in disc winds. By incorporating our results within a long-term evolution model, we measure the long-term stability of mass transfer in these binaries. We find that only binaries containing helium white dwarfs (WDs) with masses less than a critical mass of MWD, crit = 0.2 M⊙ undergo stable mass transfer and evolve into ultracompact X-ray binaries. Systems with higher mass WDs experience unstable mass transfer, which leads to tidal disruption of the WD. Our low critical mass compared to the standard jet-only model of mass-loss arises from the efficient removal of angular momentum in the mechanical disc winds, which develop at highly super-Eddington mass-transfer rates. We find that the eccentricities expected for WD-NS binaries when they come into contact do not affect the loss of angular momentum, and can only affect the long-term evolution if they change on shorter time-scales than the mass-transfer rate. Our results are broadly consistent with the observed numbers of both ultracompact X-ray binaries and radio pulsars with WD companions. The observed calcium-rich gap transients are consistent with the merger rate of unstable systems with higher mass WDs.

Subdwarf B Stars: Tracers Of Binary Evolution

NASA Astrophysics Data System (ADS)

Morales-Rueda, L.; Maxted, P. F. L.; Marsh, T. R.

2007-08-01

Subdwarf B stars are a superb stellar population to study binary evolution. In 2001, Maxted et al. (MNRAS, 326, 1391) found that 21 out of the 36 subdwarf B stars they studied were in short period binaries. These observations inspired new theoretical work that suggests that up to 90 per cent of subdwarf B stars are in binary systems with the remaining apparently single stars being the product of merging pairs. This high binary fraction added to the fact that they are detached binaries that have not changed significantly since they came out of the common envelope, make subdwarf B stars a perfect population to study binary evolution. By comparing the observed orbital period distribution of subdwarf B stars with that obtained from population synthesis calculations we can determine fundamental parameters of binary evolution such as the common envelope ejection efficiency. Here we give an overview of the fraction of short period binaries found from different surveys as well as the most up to date orbital period distribution determined observationally. We also present results from a recent search for subdwarf B stars in long period binaries.

Contact Binaries on Their Way Towards Merging

NASA Astrophysics Data System (ADS)

Gazeas, K.

2015-07-01

Contact binaries are the most frequently observed type of eclipsing star system. They are small, cool, low-mass binaries belonging to a relatively old stellar population. They follow certain empirical relationships that closely connect a number of physical parameters with each other, largely because of constraints coming from the Roche geometry. As a result, contact binaries provide an excellent test of stellar evolution, specifically for stellar merger scenarios. Observing campaigns by many authors have led to the cataloging of thousands of contact binaries and enabled statistical studies of many of their properties. A large number of contact binaries have been found to exhibit extraordinary behavior, requiring follow-up observations to study their peculiarities in detail. For example, a doubly-eclipsing quadruple system consisting of a contact binary and a detached binary is a highly constrained system offering an excellent laboratory to test evolutionary theories for binaries. A new observing project was initiated at the University of Athens in 2012 in order to investigate the possible lower limit for the orbital period of binary systems before coalescence, prior to merging.

Learning Rotation-Invariant Local Binary Descriptor.

PubMed

Duan, Yueqi; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie

2017-08-01

In this paper, we propose a rotation-invariant local binary descriptor (RI-LBD) learning method for visual recognition. Compared with hand-crafted local binary descriptors, such as local binary pattern and its variants, which require strong prior knowledge, local binary feature learning methods are more efficient and data-adaptive. Unlike existing learning-based local binary descriptors, such as compact binary face descriptor and simultaneous local binary feature learning and encoding, which are susceptible to rotations, our RI-LBD first categorizes each local patch into a rotational binary pattern (RBP), and then jointly learns the orientation for each pattern and the projection matrix to obtain RI-LBDs. As all the rotation variants of a patch belong to the same RBP, they are rotated into the same orientation and projected into the same binary descriptor. Then, we construct a codebook by a clustering method on the learned binary codes, and obtain a histogram feature for each image as the final representation. In order to exploit higher order statistical information, we extend our RI-LBD to the triple rotation-invariant co-occurrence local binary descriptor (TRICo-LBD) learning method, which learns a triple co-occurrence binary code for each local patch. Extensive experimental results on four different visual recognition tasks, including image patch matching, texture classification, face recognition, and scene classification, show that our RI-LBD and TRICo-LBD outperform most existing local descriptors.

Seeing Double Old and New: Observations and Lightcurve Analysis at the Palmer Divide Observatory of Six Binary Asteroids

NASA Astrophysics Data System (ADS)

Warner, Brian D.

2013-04-01

Results of the analysis of lightcurves of six binary asteroids obtained at the Palmer Divide Observatory are reported. Of the six, three were previously known to be binary: 9069 Hovland, (26471) 2000 AS152, and 1994 XD. The remaining three are new confirmed or probable binary discoveries made at PDO: 2047 Smetana, (5646) 1990 TR, and (52316) 1992 BD.

Satellite radiance data assimilation for binary tropical cyclone cases over the western North Pacific

NASA Astrophysics Data System (ADS)

Choi, Yonghan; Cha, Dong-Hyun; Lee, Myong-In; Kim, Joowan; Jin, Chun-Sil; Park, Sang-Hun; Joh, Min-Su

2017-06-01

A total of three binary tropical cyclone (TC) cases over the Western North Pacific are selected to investigate the effects of satellite radiance data assimilation on analyses and forecasts of binary TCs. Two parallel cycling experiments with a 6 h interval are performed for each binary TC case, and the difference between the two experiments is whether satellite radiance observations are assimilated. Satellite radiance observations are assimilated using the Weather Research and Forecasting Data Assimilation (WRFDA)'s three-dimensional variational (3D-Var) system, which includes the observation operator, quality control procedures, and bias correction algorithm for radiance observations. On average, radiance assimilation results in slight improvements of environmental fields and track forecasts of binary TC cases, but the detailed effects vary with the case. When there is no direct interaction between binary TCs, radiance assimilation leads to better depictions of environmental fields, and finally it results in improved track forecasts. However, positive effects of radiance assimilation on track forecasts can be reduced when there exists a direct interaction between binary TCs and intensities/structures of binary TCs are not represented well. An initialization method (e.g., dynamic initialization) combined with radiance assimilation and/or more advanced DA techniques (e.g., hybrid method) can be considered to overcome these limitations.

High-mass X-ray binary populations. 1: Galactic modeling

NASA Technical Reports Server (NTRS)

Dalton, William W.; Sarazin, Craig L.

1995-01-01

Modern stellar evolutionary tracks are used to calculate the evolution of a very large number of massive binary star systems (M(sub tot) greater than or = 15 solar mass) which cover a wide range of total masses, mass ratios, and starting separations. Each binary is evolved accounting for mass and angular momentum loss through the supernova of the primary to the X-ray binary phase. Using the observed rate of star formation in our Galaxy and the properties of massive binaries, we calculate the expected high-mass X-ray binary (HMXRB) population in the Galaxy. We test various massive binary evolutionary scenarios by comparing the resulting HMXRB predictions with the X-ray observations. A major goal of this study is the determination of the fraction of matter lost from the system during the Roche lobe overflow phase. Curiously, we find that the total numbers of observable HMXRBs are nearly independent of this assumed mass-loss fraction, with any of the values tested here giving acceptable agreement between predicted and observed numbers. However, comparison of the period distribution of our HMXRB models with the observed period distribution does reveal a distinction among the various models. As a result of this comparison, we conclude that approximately 70% of the overflow matter is lost from a massive binary system during mass transfer in the Roche lobe overflow phase. We compare models constructed assuming that all X-ray emission is due to accretion onto the compact object from the donor star's wind with models that incorporate a simplified disk accretion scheme. By comparing the results of these models with observations, we conclude that the formation of disks in HMXRBs must be relatively common. We also calculate the rate of formation of double degenerate binaries, high velocity detached compact objects, and Thorne-Zytkow objects.

[One-night-stand behavior and associated factors among young men who have sex with men in Wuhan, China].

PubMed

Mao, Y X; Xiao, C C; Wang, T; Li, S Y; Yan, H

2017-06-10

Objective: This present study was to examine the prevalence and determinants of one-night-stand behavior among young men who have sex with men (YMSM). Methods: A total of 403 YMSM aged 16 to 25 were recruited through internet promotion, extending activity and HIV VCT in Wuhan. Data was gathered through anonymous questionnaire. Binary logistic regression was used to examine factors associated with one-night-stand behavior. Results: Of the 398 YMSM, 48.99 % (195/398) reported having had casual sex in the last 6 months. Of the ones having had casual sex, 34.29 % (60/175) and 28.65 % (49/171) reported using condoms consistently during anal or oral sexual contacts, respectively. These figures were lower than those of YMSM not having casual sexual contacts [with anal sex as 49.08 % (80/163) and oral sex as 38.85 % (61/157)]. 76.80 % (149/194) of the YMSM reported having had multiple sexual partners, with the figure higher than those without [33.15 % (60/181)] ( P <0.01). Results from the logistic regression analysis showed that the following factors seemed to be associated with casual sex activities among YMSM, including: often using internet, ( OR =4.89, 95 %CI : 1.90-12.54), taking illegal drugs ( OR =2.72, 95 %CI : 1.60-4.63). Conclusions: YMSM who had engaged in casual sex, practicing unprotected sex or having multiple sexual partners, were recognized as high risk population. Targeted intervention programs are needed to decrease the one-night-stand behavior. Internet intervention strategy seemed an important method to serve the purpose.

Prevalence of and Factors Associated with Negative Microscopic Diagnosis of Cutaneous Leishmaniasis in Rural Peru.

PubMed

Lamm, Ryan; Alves, Clark; Perrotta, Grace; Murphy, Meagan; Messina, Catherine; Sanchez, Juan F; Perez, Erika; Rosales, Luis Angel; Lescano, Andres G; Smith, Edward; Valdivia, Hugo; Fuhrer, Jack; Ballard, Sarah-Blythe

2018-06-04

Cutaneous leishmaniasis is endemic to South America where diagnosis is most commonly conducted via microscopy. Patients with suspected leishmaniasis were referred for enrollment by the Ministry of Health (MoH) in Lima, Iquitos, Puerto Maldonado, and several rural areas of Peru. A 43-question survey requesting age, gender, occupation, characterization of the lesion(s), history of leishmaniasis, and insect-deterrent behaviors was administered. Polymerase chain reaction (PCR) was conducted on lesion materials at the Naval Medical Research Unit No. 6 in Lima, and the results were compared with those obtained by the MoH using microscopy. Factors associated with negative microscopy and positive PCR results were identified using χ 2 test, t -test, and multivariate logistic regression analyses. Negative microscopy with positive PCR occurred in 31% (123/403) of the 403 cases. After adjusting for confounders, binary multivariate logistic regression analyses revealed that negative microscopy with positive PCR was associated with patients who were male (adjusted OR = 1.93 [1.06-3.53], P = 0.032), had previous leishmaniasis (adjusted OR = 2.93 [1.65-5.22], P < 0.0001), had larger lesions (adjusted OR = 1.02 [1.003-1.03], P = 0.016), and/or had a longer duration between lesion appearance and PCR testing (adjusted OR = 1.12 [1.02-1.22], P = 0.017). Future research should focus on further exploration of these underlying variables, discovery of other factors that may be associated with negative microscopy diagnosis, and the development and implementation of improved testing in endemic regions.

Selenium in irrigated agricultural areas of the western United States

USGS Publications Warehouse

Nolan, B.T.; Clark, M.L.

1997-01-01

A logistic regression model was developed to predict the likelihood that Se exceeds the USEPA chronic criterion for aquatic life (5 ??g/L) in irrigated agricultural areas of the western USA. Preliminary analysis of explanatory variables used in the model indicated that surface-water Se concentration increased with increasing dissolved solids (DS) concentration and with the presence of Upper Cretaceous, mainly marine sediment. The presence or absence of Cretaceous sediment was the major variable affecting Se concentration in surface-water samples from the National Irrigation Water Quality Program. Median Se concentration was 14 ??g/L in samples from areas underlain by Cretaceous sediments and < 1 ??g/L in samples from areas underlain by non-Cretaceous sediments. Wilcoxon rank sum tests indicated that elevated Se concentrations in samples from areas with Cretaceous sediments, irrigated areas, and from closed lakes and ponds were statistically significant. Spearman correlations indicated that Se was positively correlated with a binary geology variable (0.64) and DS (0.45). Logistic regression models indicated that the concentration of Se in surface water was almost certain to exceed the Environmental Protection Agency aquatic-life chronic criterion of 5 ??g/L when DS was greater than 3000 mg/L in areas with Cretaceous sediments. The 'best' logistic regression model correctly predicted Se exceedances and nonexceedances 84.4% of the time, and model sensitivity was 80.7%. A regional map of Cretaceous sediment showed the location of potential problem areas. The map and logistic regression model are tools that can be used to determine the potential for Se contamination of irrigated agricultural areas in the western USA.

POPCORN: A comparison of binary population synthesis codes

NASA Astrophysics Data System (ADS)

Claeys, J. S. W.; Toonen, S.; Mennekens, N.

2013-01-01

We compare the results of three binary population synthesis codes to understand the differences in their results. As a first result we find that when equalizing the assumptions the results are similar. The main differences arise from deviating physical input.

A biclustering algorithm for extracting bit-patterns from binary datasets.

PubMed

Rodriguez-Baena, Domingo S; Perez-Pulido, Antonio J; Aguilar-Ruiz, Jesus S

2011-10-01

Binary datasets represent a compact and simple way to store data about the relationships between a group of objects and their possible properties. In the last few years, different biclustering algorithms have been specially developed to be applied to binary datasets. Several approaches based on matrix factorization, suffix trees or divide-and-conquer techniques have been proposed to extract useful biclusters from binary data, and these approaches provide information about the distribution of patterns and intrinsic correlations. A novel approach to extracting biclusters from binary datasets, BiBit, is introduced here. The results obtained from different experiments with synthetic data reveal the excellent performance and the robustness of BiBit to density and size of input data. Also, BiBit is applied to a central nervous system embryonic tumor gene expression dataset to test the quality of the results. A novel gene expression preprocessing methodology, based on expression level layers, and the selective search performed by BiBit, based on a very fast bit-pattern processing technique, provide very satisfactory results in quality and computational cost. The power of biclustering in finding genes involved simultaneously in different cancer processes is also shown. Finally, a comparison with Bimax, one of the most cited binary biclustering algorithms, shows that BiBit is faster while providing essentially the same results. The source and binary codes, the datasets used in the experiments and the results can be found at: http://www.upo.es/eps/bigs/BiBit.html dsrodbae@upo.es Supplementary data are available at Bioinformatics online.

Heterogeneous Suppression of Sequential Effects in Random Sequence Generation, but Not in Operant Learning.

PubMed

Shteingart, Hanan; Loewenstein, Yonatan

2016-01-01

There is a long history of experiments in which participants are instructed to generate a long sequence of binary random numbers. The scope of this line of research has shifted over the years from identifying the basic psychological principles and/or the heuristics that lead to deviations from randomness, to one of predicting future choices. In this paper, we used generalized linear regression and the framework of Reinforcement Learning in order to address both points. In particular, we used logistic regression analysis in order to characterize the temporal sequence of participants' choices. Surprisingly, a population analysis indicated that the contribution of the most recent trial has only a weak effect on behavior, compared to more preceding trials, a result that seems irreconcilable with standard sequential effects that decay monotonously with the delay. However, when considering each participant separately, we found that the magnitudes of the sequential effect are a monotonous decreasing function of the delay, yet these individual sequential effects are largely averaged out in a population analysis because of heterogeneity. The substantial behavioral heterogeneity in this task is further demonstrated quantitatively by considering the predictive power of the model. We show that a heterogeneous model of sequential dependencies captures the structure available in random sequence generation. Finally, we show that the results of the logistic regression analysis can be interpreted in the framework of reinforcement learning, allowing us to compare the sequential effects in the random sequence generation task to those in an operant learning task. We show that in contrast to the random sequence generation task, sequential effects in operant learning are far more homogenous across the population. These results suggest that in the random sequence generation task, different participants adopt different cognitive strategies to suppress sequential dependencies when generating the "random" sequences.

Neurocognitive functioning in children with developmental dyslexia and attention-deficit/hyperactivity disorder: Multiple deficits and diagnostic accuracy.

PubMed

Moura, Octávio; Pereira, Marcelino; Alfaiate, Cláudia; Fernandes, Eva; Fernandes, Boavida; Nogueira, Susana; Moreno, Joana; Simões, Mário R

2017-04-01

This study aimed to investigate the neurocognitive functioning of children with developmental dyslexia (DD) and attention-deficit/hyperactivity disorder (ADHD). Four groups of children between the ages of 8 and 10 years participated in the study: typically developing children (TDC; N = 34), children with DD-only (N = 32), children with ADHD-only (N = 32), and children with DD+ADHD (N = 18). Children with DD and ADHD exhibited significant weaknesses on almost all neurocognitive measures compared with TDC. Large effect sizes were observed for naming speed and phonological awareness. The comorbid group showed deficits consistent with both DD and ADHD without additional impairments. Results from binary logistic regression and receiver-operating characteristic (ROC) curve analyses suggested that some neurocognitive measures revealed an adequate sensitivity for the clinical diagnosis of both neurodevelopmental disorders. Specifically, naming speed and phonological awareness were the strongest predictors to correctly discriminate both disorders. Taken together, the results lend support to the multiple cognitive deficit hypothesis showing a considerable overlap of neurocognitive deficits between both disorders.

Effects of spatial location and household wealth on health insurance subscription among women in Ghana

PubMed Central

2013-01-01

Background This study compares ownership of health insurance among Ghanaian women with respect to wealth status and spatial location. We explore the overarching research question by employing geographic and proxy means targeting through interactive analysis of wealth status and spatial issues. Methods The paper draws on the 2008 Ghana Demographic and Health Survey. Bivariate descriptive analysis coupled with binary logistic regression estimation technique was used to analyse the data. Results By wealth status, the likelihood of purchasing insurance was significantly higher among respondents from the middle, richer and richest households compared to the poorest (reference category) and these differences widened more profoundly in the Northern areas after interacting wealth with zone of residence. Among women at the bottom of household wealth (poorest and poorer), there were no statistically significant differences in insurance subscription in all the areas. Conclusions The results underscore the relevance of geographic and proxy means targeting in identifying populations who may be need of special interventions as part of the efforts to increase enrolment as well as means of social protection against the vulnerable. PMID:23768255

Serial binary interval ratios improve rhythm reproduction.

PubMed

Wu, Xiang; Westanmo, Anders; Zhou, Liang; Pan, Junhao

2013-01-01

Musical rhythm perception is a natural human ability that involves complex cognitive processes. Rhythm refers to the organization of events in time, and musical rhythms have an underlying hierarchical metrical structure. The metrical structure induces the feeling of a beat and the extent to which a rhythm induces the feeling of a beat is referred to as its metrical strength. Binary ratios are the most frequent interval ratio in musical rhythms. Rhythms with hierarchical binary ratios are better discriminated and reproduced than rhythms with hierarchical non-binary ratios. However, it remains unclear whether a superiority of serial binary over non-binary ratios in rhythm perception and reproduction exists. In addition, how different types of serial ratios influence the metrical strength of rhythms remains to be elucidated. The present study investigated serial binary vs. non-binary ratios in a reproduction task. Rhythms formed with exclusively binary (1:2:4:8), non-binary integer (1:3:5:6), and non-integer (1:2.3:5.3:6.4) ratios were examined within a constant meter. The results showed that the 1:2:4:8 rhythm type was more accurately reproduced than the 1:3:5:6 and 1:2.3:5.3:6.4 rhythm types, and the 1:2.3:5.3:6.4 rhythm type was more accurately reproduced than the 1:3:5:6 rhythm type. Further analyses showed that reproduction performance was better predicted by the distribution pattern of event occurrences within an inter-beat interval, than by the coincidence of events with beats, or the magnitude and complexity of interval ratios. Whereas rhythm theories and empirical data emphasize the role of the coincidence of events with beats in determining metrical strength and predicting rhythm performance, the present results suggest that rhythm processing may be better understood when the distribution pattern of event occurrences is taken into account. These results provide new insights into the mechanisms underlining musical rhythm perception.

Serial binary interval ratios improve rhythm reproduction

PubMed Central

Wu, Xiang; Westanmo, Anders; Zhou, Liang; Pan, Junhao

2013-01-01

Musical rhythm perception is a natural human ability that involves complex cognitive processes. Rhythm refers to the organization of events in time, and musical rhythms have an underlying hierarchical metrical structure. The metrical structure induces the feeling of a beat and the extent to which a rhythm induces the feeling of a beat is referred to as its metrical strength. Binary ratios are the most frequent interval ratio in musical rhythms. Rhythms with hierarchical binary ratios are better discriminated and reproduced than rhythms with hierarchical non-binary ratios. However, it remains unclear whether a superiority of serial binary over non-binary ratios in rhythm perception and reproduction exists. In addition, how different types of serial ratios influence the metrical strength of rhythms remains to be elucidated. The present study investigated serial binary vs. non-binary ratios in a reproduction task. Rhythms formed with exclusively binary (1:2:4:8), non-binary integer (1:3:5:6), and non-integer (1:2.3:5.3:6.4) ratios were examined within a constant meter. The results showed that the 1:2:4:8 rhythm type was more accurately reproduced than the 1:3:5:6 and 1:2.3:5.3:6.4 rhythm types, and the 1:2.3:5.3:6.4 rhythm type was more accurately reproduced than the 1:3:5:6 rhythm type. Further analyses showed that reproduction performance was better predicted by the distribution pattern of event occurrences within an inter-beat interval, than by the coincidence of events with beats, or the magnitude and complexity of interval ratios. Whereas rhythm theories and empirical data emphasize the role of the coincidence of events with beats in determining metrical strength and predicting rhythm performance, the present results suggest that rhythm processing may be better understood when the distribution pattern of event occurrences is taken into account. These results provide new insights into the mechanisms underlining musical rhythm perception. PMID:23964258

The True Ultracool Binary Fraction Using Spectral Binaries

NASA Astrophysics Data System (ADS)

Bardalez Gagliuffi, Daniella; Burgasser, Adam J.; Schmidt, Sarah J.; Gagné, Jonathan; Faherty, Jacqueline K.; Cruz, Kelle; Gelino, Chris

2018-01-01

Brown dwarfs bridge the gap between stars and giant planets. While the essential mechanisms governing their formation are not well constrained, binary statistics are a direct outcome of the formation process, and thus provide a means to test formation theories. Observational constraints on the brown dwarf binary fraction place it at 10 ‑ 20%, dominated by imaging studies (85% of systems) with the most common separation at 4 AU. This coincides with the resolution limit of state-of-the-art imaging techniques, suggesting that the binary fraction is underestimated. We have developed a separation-independent method to identify and characterize tightly-separated (< 5 AU) binary systems of brown dwarfs as spectral binaries by identifying traces of methane in the spectra of late-M and early-L dwarfs. Imaging follow-up of 17 spectral binaries yielded 3 (18%) resolved systems, corroborating the observed binary fraction, but 5 (29%) known binaries were missed, reinforcing the hypothesis that the short-separation systems are undercounted. In order to find the true binary fraction of brown dwarfs, we have compiled a volume-limited, spectroscopic sample of M7-L5 dwarfs and searched for T dwarf companions. In the 25 pc volume, 4 candidates were found, three of which are already confirmed, leading to a spectral binary fraction of 0.95 ± 0.50%, albeit for a specific combination of spectral types. To extract the true binary fraction and determine the biases of the spectral binary method, we have produced a binary population simulation based on different assumptions of the mass function, age distribution, evolutionary models and mass ratio distribution. Applying the correction fraction resulting from this method to the observed spectral binary fraction yields a true binary fraction of 27 ± 4%, which is roughly within 1σ of the binary fraction obtained from high resolution imaging studies, radial velocity and astrometric monitoring. This method can be extended to identify giant planet companions to young brown dwarfs.

Inferences about binary stellar populations using gravitational wave observations

NASA Astrophysics Data System (ADS)

Wysocki, Daniel; Gerosa, Davide; O'Shaughnessy, Richard; Belczynski, Krzysztof; Gladysz, Wojciech; Berti, Emanuele; Kesden, Michael; Holz, Daniel

2018-01-01

With the dawn of gravitational wave astronomy, enabled by the LIGO and Virgo interferometers, we now have a new window into the Universe. In the short time these detectors have been in use, multiple confirmed detections of gravitational waves from compact binary coalescences have been made. Stellar binary systems are one of the likely progenitors of the observed compact binary sources. If this is indeed the case, then we can use measured properties of these binary systems to learn about their progenitors. We will discuss the Bayesian framework in which we make these inferences, and results which include mass and spin distributions.

The association between insured male expatriates' knowledge of health insurance benefits and lack of access to health care in Saudi Arabia.

PubMed

Alkhamis, Abdulwahab A

2018-03-15

Insufficient knowledge of health insurance benefits could be associated with lack of access to health care, particularly for minority populations. This study aims to assess the association between expatriates' knowledge of health insurance benefits and lack of access to health care. A cross-sectional study design was conducted from March 2015 to February 2016 among 3398 insured male expatriates in Riyadh, Saudi Arabia. The dependent variable was binary and expresses access or lack of access to health care. Independent variables included perceived and validated knowledge of health insurance benefits and other variables. Data were summarized by computing frequencies and percentage of all quantities of variables. To evaluate variations in knowledge, personal and job characteristics with lack of access to health care, the Chi square test was used. Odds ratio (OR) and 95% confidence interval (CI) were recorded for each independent variable. Multiple logistic regression and stepwise logistic regression were performed and adjusted ORs were extracted. Descriptive analysis showed that 15% of participants lacked access to health care. The majority of these were unskilled laborers, usually with no education (17.5%), who had been working for less than 3 years (28.1%) in Saudi Arabia. A total of 23.3% worked for companies with less than 50 employees and 16.5% earned less than 4500 Saudi Riyals monthly ($1200). Many (20.3%) were young (< 30 years old) or older (17.9% ≥ 56 years old) and had no formal education (24.7%). Nearly half had fair or poor health status (49.5%), were uncomfortable conversing in Arabic (29.7%) or English (16.7%) and lacked previous knowledge of health insurance (18%). For perceived knowledge of health insurance, 55.2% scored 1 or 0 from total of 3. For validated knowledge, 16.9% scored 1 or 0 from total score of 4. Multiple logistic regression analysis showed that only perceived knowledge of health insurance had significant associations with lack of access to health care ((OR) = 0.393, (CI) = 0.335-0.461), but the result was insignificant for validated knowledge. Stepwise logistic regression gave similar findings. Our results confirmed that low perceived knowledge of health insurance in expatriates was associated with less access to health care.

R144: a very massive binary likely ejected from R136 through a binary-binary encounter

NASA Astrophysics Data System (ADS)

Oh, Seungkyung; Kroupa, Pavel; Banerjee, Sambaran

2014-02-01

R144 is a recently confirmed very massive, spectroscopic binary which appears isolated from the core of the massive young star cluster R136. The dynamical ejection hypothesis as an origin for its location is claimed improbable by Sana et al. due to its binary nature and high mass. We demonstrate here by means of direct N-body calculations that a very massive binary system can be readily dynamically ejected from an R136-like cluster, through a close encounter with a very massive system. One out of four N-body cluster models produces a dynamically ejected very massive binary system with a mass comparable to R144. The system has a system mass of ≈355 M⊙ and is located at 36.8 pc from the centre of its parent cluster, moving away from the cluster with a velocity of 57 km s-1 at 2 Myr as a result of a binary-binary interaction. This implies that R144 could have been ejected from R136 through a strong encounter with another massive binary or single star. In addition, we discuss all massive binaries and single stars which are ejected dynamically from their parent cluster in the N-body models.

Evolution of Optical Binary Fraction in Sparse Stellar Systems

NASA Astrophysics Data System (ADS)

Li, Zhongmu; Mao, Caiyan

2018-05-01

This work studies the evolution of the fraction of optical binary stars (OBF; not including components such as neutron stars and black holes), which is caused by stellar evolution, and the contributions of various binaries to OBF via the stellar population synthesis technique. It is shown that OBF decreases from 1 to about 0.81 for stellar populations with the Salpeter initial mass function (IMF), and to about 0.85 for the case of the Kroupa IMF, on a timescale of 15 Gyr. This result depends on metallicity, slightly. The contributions of binaries varying with mass ratio, orbital period, separation, spectral types of primary and secondary, contact degree, and pair type to OBF are calculated for stellar populations with different ages and metallicities. The contribution of different kinds of binaries to OBF depends on age and metallicity. The results can be used for estimating the global OBF of star clusters or galaxies from the fraction of a kind of binary. It is also helpful for estimating the primordial and future binary fractions of sparse stellar systems from the present observations. Our results are suitable for studying field stars, open clusters, and the outer part of globular clusters, because the OBF of such objects is affected by dynamical processes, relatively slightly, but they can also be used for giving some limits for other populations.

The disruption of multiplanet systems through resonance with a binary orbit.

PubMed

Touma, Jihad R; Sridhar, S

2015-08-27

Most exoplanetary systems in binary stars are of S-type, and consist of one or more planets orbiting a primary star with a wide binary stellar companion. Planetary eccentricities and mutual inclinations can be large, perhaps forced gravitationally by the binary companion. Earlier work on single planet systems appealed to the Kozai-Lidov instability wherein a sufficiently inclined binary orbit excites large-amplitude oscillations in the planet's eccentricity and inclination. The instability, however, can be quenched by many agents that induce fast orbital precession, including mutual gravitational forces in a multiplanet system. Here we report that orbital precession, which inhibits Kozai-Lidov cycling in a multiplanet system, can become fast enough to resonate with the orbital motion of a distant binary companion. Resonant binary forcing results in dramatic outcomes ranging from the excitation of large planetary eccentricities and mutual inclinations to total disruption. Processes such as planetary migration can bring an initially non-resonant system into resonance. As it does not require special physical or initial conditions, binary resonant driving is generic and may have altered the architecture of many multiplanet systems. It can also weaken the multiplanet occurrence rate in wide binaries, and affect planet formation in close binaries.

Texture Classification by Texton: Statistical versus Binary

PubMed Central

Guo, Zhenhua; Zhang, Zhongcheng; Li, Xiu; Li, Qin; You, Jane

2014-01-01

Using statistical textons for texture classification has shown great success recently. The maximal response 8 (Statistical_MR8), image patch (Statistical_Joint) and locally invariant fractal (Statistical_Fractal) are typical statistical texton algorithms and state-of-the-art texture classification methods. However, there are two limitations when using these methods. First, it needs a training stage to build a texton library, thus the recognition accuracy will be highly depended on the training samples; second, during feature extraction, local feature is assigned to a texton by searching for the nearest texton in the whole library, which is time consuming when the library size is big and the dimension of feature is high. To address the above two issues, in this paper, three binary texton counterpart methods were proposed, Binary_MR8, Binary_Joint, and Binary_Fractal. These methods do not require any training step but encode local feature into binary representation directly. The experimental results on the CUReT, UIUC and KTH-TIPS databases show that binary texton could get sound results with fast feature extraction, especially when the image size is not big and the quality of image is not poor. PMID:24520346

Using binary statistics in Taurus-Auriga to distinguish between brown dwarf formation processes

NASA Astrophysics Data System (ADS)

Marks, M.; Martín, E. L.; Béjar, V. J. S.; Lodieu, N.; Kroupa, P.; Manjavacas, E.; Thies, I.; Rebolo López, R.; Velasco, S.

2017-08-01

Context. One of the key questions of the star formation problem is whether brown dwarfs (BDs) form in the manner of stars directly from the gravitational collapse of a molecular cloud core (star-like) or whether BDs and some very low-mass stars (VLMSs) constitute a separate population that forms alongside stars comparable to the population of planets, for example through circumstellar disk (peripheral) fragmentation. Aims: For young stars in Taurus-Auriga the binary fraction has been shown to be large with little dependence on primary mass above ≈ 0.2 M⊙, while for BDs the binary fraction is < 10%. Here we investigate a case in which BDs in Taurus formed dominantly, but not exclusively, through peripheral fragmentation, which naturally results in small binary fractions. The decline of the binary frequency in the transition region between star-like formation and peripheral formation is modelled. Methods: We employed a dynamical population synthesis model in which stellar binary formation is universal with a large binary fraction close to unity. Peripheral objects form separately in circumstellar disks with a distinctive initial mass function (IMF), their own orbital parameter distributions for binaries, and small binary fractions, according to observations and expectations from smoothed particle hydrodynamics (SPH) and grid-based computations. A small amount of dynamical processing of the stellar component was accounted for as appropriate for the low-density Taurus-Auriga embedded clusters. Results: The binary fraction declines strongly in the transition region between star-like and peripheral formation, exhibiting characteristic features. The location of these features and the steepness of this trend depend on the mass limits for star-like and peripheral formation. Such a trend might be unique to low density regions, such as Taurus, which host binary populations that are largely unprocessed dynamically in which the binary fraction is large for stars down to M-dwarfs and small for BDs. Conclusions: The existence of a strong decline in the binary fraction - primary mass diagram will become verifiable in future surveys on BD and VLMS binarity in the Taurus-Auriga star-forming region. The binary fraction - primary mass diagram is a diagnostic of the (non-)continuity of star formation along the mass scale, the separateness of the stellar and BD populations, and the dominant formation channel for BDs and BD binaries in regions of low stellar density hosting dynamically unprocessed populations.

Dynamical effects of stellar companions

NASA Astrophysics Data System (ADS)

Naoz, Smadar

2015-08-01

The fraction of stellar binaries in the field is extremely high (about 40% - 70% for > 1 Msun stars), and thus, given this frequency, a large fraction of all exoplanetary systems may reside in binaries. While close-in giant planets tend to be found preferentially in binary stellar systems it seems that the frequency of giant planets in close binaries (<100 AU) is significantly lower than in the overall population. Stellar companions’ gravitational perturbations may significantly alter the planetary orbits around their partner on secular timescales. They can drive planets to large eccentric orbits which can either result in plunging these planets into the star or shrinking their orbits and forming short period planets. I will review the dynamical effects stellar binaries have on a planetary systems. I will also present new results on the influence that stellar evolution has on the dynamical processes in these systems.

Mesoscopic model for binary fluids

NASA Astrophysics Data System (ADS)

Echeverria, C.; Tucci, K.; Alvarez-Llamoza, O.; Orozco-Guillén, E. E.; Morales, M.; Cosenza, M. G.

2017-10-01

We propose a model for studying binary fluids based on the mesoscopic molecular simulation technique known as multiparticle collision, where the space and state variables are continuous, and time is discrete. We include a repulsion rule to simulate segregation processes that does not require calculation of the interaction forces between particles, so binary fluids can be described on a mesoscopic scale. The model is conceptually simple and computationally efficient; it maintains Galilean invariance and conserves the mass and energy in the system at the micro- and macro-scale, whereas momentum is conserved globally. For a wide range of temperatures and densities, the model yields results in good agreement with the known properties of binary fluids, such as the density profile, interface width, phase separation, and phase growth. We also apply the model to the study of binary fluids in crowded environments with consistent results.

Orbital alignment of circumbinary planets that form in misaligned circumbinary discs: the case of Kepler-413b

NASA Astrophysics Data System (ADS)

Pierens, A.; Nelson, R. P.

2018-06-01

Although most of the circumbinary planets detected by the Kepler spacecraft are on orbits that are closely aligned with the binary orbital plane, the systems Kepler-413 and Kepler-453 exhibit small misalignments of ˜2.5°. One possibility is that these planets formed in a circumbinary disc whose midplane was inclined relative to the binary orbital plane. Such a configuration is expected to lead to a warped and twisted disc, and our aim is to examine the inclination evolution of planets embedded in these discs. We employed 3D hydrodynamical simulations that examine the disc response to the presence of a modestly inclined binary with parameters that match the Kepler-413 system, as a function of disc parameters and binary inclinations. The discs all develop slowly varying warps, and generally display very small amounts of twist. Very slow solid body precession occurs because a large outer disc radius is adopted. Simulations of planets embedded in these discs resulted in the planet aligning with the binary orbit plane for disc masses close to the minimum mass solar nebular, such that nodal precession of the planet was controlled by the binary. For higher disc masses, the planet maintains near coplanarity with the local disc midplane. Our results suggest that circumbinary planets born in tilted circumbinary discs should align with the binary orbit plane as the disc ages and loses mass, even if the circumbinary disc remains misaligned from the binary orbit. This result has important implications for understanding the origins of the known circumbinary planets.

COSMIC probes into compact binary formation and evolution

NASA Astrophysics Data System (ADS)

Breivik, Katelyn

2018-01-01

The population of compact binaries in the galaxy represents the final state of all binaries that have lived up to the present epoch. Compact binaries present a unique opportunity to probe binary evolution since many of the interactions binaries experience can be imprinted on the compact binary population. By combining binary evolution simulations with catalogs of observable compact binary systems, we can distill the dominant physical processes that govern binary star evolution, as well as predict the abundance and variety of their end products.The next decades herald a previously unseen opportunity to study compact binaries. Multi-messenger observations from telescopes across all wavelengths and gravitational-wave observatories spanning several decades of frequency will give an unprecedented view into the structure of these systems and the composition of their components. Observations will not always be coincident and in some cases may be separated by several years, providing an avenue for simulations to better constrain binary evolution models in preparation for future observations.I will present the results of three population synthesis studies of compact binary populations carried out with the Compact Object Synthesis and Monte Carlo Investigation Code (COSMIC). I will first show how binary-black-hole formation channels can be understood with LISA observations. I will then show how the population of double white dwarfs observed with LISA and Gaia could provide a detailed view of mass transfer and accretion. Finally, I will show that Gaia could discover thousands black holes in the Milky Way through astrometric observations, yielding view into black-hole astrophysics that is complementary to and independent from both X-ray and gravitational-wave astronomy.

Control of broadband optically generated ultrasound pulses using binary amplitude holograms.

PubMed

Brown, Michael D; Jaros, Jiri; Cox, Ben T; Treeby, Bradley E

2016-04-01

In this work, the use of binary amplitude holography is investigated as a mechanism to focus broadband acoustic pulses generated by high peak-power pulsed lasers. Two algorithms are described for the calculation of the binary holograms; one using ray-tracing, and one using an optimization based on direct binary search. It is shown using numerical simulations that when a binary amplitude hologram is excited by a train of laser pulses at its design frequency, the acoustic field can be focused at a pre-determined distribution of points, including single and multiple focal points, and line and square foci. The numerical results are validated by acoustic field measurements from binary amplitude holograms, excited by a high peak-power laser.

Accretion dynamics in pre-main sequence binaries

NASA Astrophysics Data System (ADS)

Tofflemire, B.; Mathieu, R.; Herczeg, G.; Ardila, D.; Akeson, R.; Ciardi, D.; Johns-Krull, C.

Binary stars are a common outcome of star formation. Orbital resonances, especially in short-period systems, are capable of reshaping the distribution and flows of circumstellar material. Simulations of the binary-disk interaction predict a dynamically cleared gap around the central binary, accompanied by periodic ``pulsed'' accretion events that are driven by orbital motion. To place observational constraints on the binary-disk interaction, we have conducted a long-term monitoring program tracing the time-variable accretion behavior of 9 short-period binaries. In this proceeding we present two results from our campaign: 1) the detection of periodic pulsed accretion events in DQ Tau and TWA 3A, and 2) evidence that the TWA 3A primary is the dominant accretor in the system.

Parent binge eating and depressive symptoms as predictors of attrition in a family-based treatment for pediatric obesity.

PubMed

Braden, Abby L; Madowitz, Jennifer; Matheson, Brittany E; Bergmann, Kristie; Crow, Scott J; Boutelle, Kerri N

2015-04-01

Attrition is a significant problem in family-based treatment (FBT) for childhood obesity. Despite this, very few studies have examined factors associated with attrition. The current study examined parent symptoms of depression and binge eating as predictors of attrition in FBT. Participants included 77 parents of overweight children enrolled in FBT for childhood obesity. Data were collected at baseline and post-treatment. Binary logistic regression was used to assess associations between parent binge eating symptoms, depressive symptoms, and attrition. Results showed that parent binge eating symptoms (p=0.02), but not depressive symptoms (p=0.07), were significantly associated with attrition, after controlling for parent BMI, treatment group assignment, and family income. Higher reported parent binge eating symptoms were significantly related to attrition in FBT. Assessment of parent binge eating may be important in identifying families at risk for dropping out of FBT. Further, FBT may need to be adapted for families with parents who have a high level of psychopathology.

Emotion-related personality traits and peer social standing: unique and interactive effects in cyberbullying behaviors.

PubMed

Ciucci, Enrica; Baroncelli, Andrea

2014-09-01

This study investigated the unique and interactive effects of emotion-related personality traits (i.e., callousness and uncaring traits) and peer social standing (i.e., social preference and perceived popularity) on cyberbullying behaviors in preadolescents. A total of 529 preadolescents (247 boys, 46.69%) were recruited from an Italian middle school (Mage=12 years and 7 months; SD=1 year and 2 months). The participants primarily consisted of Italian children (91.12%). A series of binary logistic regression analyses parted by gender were conducted to examine the main and interactive effects of self-reported emotion-related variables and peer-reported social standing in the prediction of self-reported cyberbullying behaviors, while controlling for cyber victimization and grade effects. In girls, an uncaring disposition was directly associated with cyberbullying behaviors, whereas in boys this association only emerged for those with low perceived popularity. Our results indicated that, in developing anti(cyber)bullying programs, school researchers and practitioners should jointly consider individual and contextual factors.

A Predictive Model of Daily Seismic Activity Induced by Mining, Developed with Data Mining Methods

NASA Astrophysics Data System (ADS)

Jakubowski, Jacek

2014-12-01

The article presents the development and evaluation of a predictive classification model of daily seismic energy emissions induced by longwall mining in sector XVI of the Piast coal mine in Poland. The model uses data on tremor energy, basic characteristics of the longwall face and mined output in this sector over the period from July 1987 to March 2011. The predicted binary variable is the occurrence of a daily sum of tremor seismic energies in a longwall that is greater than or equal to the threshold value of 105 J. Three data mining analytical methods were applied: logistic regression,neural networks, and stochastic gradient boosted trees. The boosted trees model was chosen as the best for the purposes of the prediction. The validation sample results showed its good predictive capability, taking the complex nature of the phenomenon into account. This may indicate the applied model's suitability for a sequential, short-term prediction of mining induced seismic activity.

Association of BPD and IVH with early neutrophil and white counts in VLBW neonates with gestational age <32 weeks

PubMed Central

Palta, Mari; Sadek-Badawi, Mona; Carlton, David P

2008-01-01

Objectives To investigate associations between early low neutrophil count from routine blood samples, white blood count (WBC), pregnancy complications and neonatal outcomes for very low birth weight infants (VLBW ≤1500g) with gestational age <32 weeks. Patients and Methods Information was abstracted on all infants admitted to level III NICUs in Wisconsin 2003-2004. 1002 (78%) had differential and corrected total white counts within 2 ½ hours of birth. Data analyses included frequency tables, binary logistic, ordinal logistc and ordinary regression. Results Low neutrophil count (<1000/μL) was strongly associated with low WBC, pregnancy complications and antenatal steroids. Low neutrophil count predicted bronchopulmonary dysplasia severity level (BPD) (OR: 1.7, 95% CI: 1.1-2.7) and intraventricular hemorrhage (IVH) grade (OR: 2.2, 95% CI: 1.3-3.8). Conclusions Early neutrophil counts may have multiple causes interfering with their routine use as an inflammatory marker. Nonetheless, low neutrophil count has consistent independent associations with outcomes. PMID:18563166

Are Front of Pack Claims Indicators of Nutrition Quality? Evidence from 2 Product Categories.

PubMed

Schaefer, Debra; Hooker, Neal H; Stanton, John L

2016-01-01

American grocery shoppers face an array of front of pack (FOP) nutrition and health claims when making food selections. Such systems have been categorized as summary or nutrient specific. Either type should help consumers make judgments about the nutrition quality of a product. This research tests if the type or quantity of FOP claims are indeed good indicators of objective nutrition quality. Claim and nutrition information from more than 2200 breakfast cereals and prepared meals launched between 2006 and 2010 were analyzed using binary and multinomial logistic regression models. Results suggest that no type or number of front of pack claims could distinguish "healthy" foods. However, some types and frequencies of FOP claims were significant predictors of higher or lower levels of certain key nutrients. Given the complex and crowded label environment in which these FOP claims reside, one may be concerned that such cues are not closely related to objective measures of nutrition quality. © 2015 Institute of Food Technologists®

Unique effects of different components of trait emotional intelligence in traditional bullying and cyberbullying.

PubMed

Baroncelli, Andrea; Ciucci, Enrica

2014-08-01

This study investigated whether different components of trait emotional intelligence (or trait emotional self-efficacy) were uniquely related to traditional bullying and cyberbullying in a sample of 529 preadolescents (mean age of 12 years and 7 months), while controlling for the other forms of bullying/victimization. Binary logistic regressions showed that the dimension of emotional intelligence concerning the regulation and use of emotions was negatively related both to traditional bullying and cyberbullying; however, this association did not emerge when traditional bullying was controlled for cyberbullying, whilst it still emerged when cyberbullying was controlled for traditional bullying and both forms of victimization. Differently, the dimensions concerning appraisal of own and others' emotions were not deficient in children performing bullying and/or cyberbullying behaviors. Despite high co-occurrence between traditional and electronic bullying, our results suggested that these two forms are distinct phenomena, involving different personality traits. Implications for interventions are discussed. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Public university entry in Ghana: Is it equitable?

NASA Astrophysics Data System (ADS)

Yusif, Hadrat; Yussof, Ishak; Osman, Zulkifly

2013-06-01

Public universities in Ghana are highly subsidised by the central government and account for about 80 per cent of university students in the country. Yet issues of fairness in terms of entry into the public university system have so far hardly been addressed. To find out whether participation in public university education is equitable, the authors of this paper carried out a binary logistic regression analysis. Individual data were collected from 1,129 (614 male and 515 female) final year senior high school (SHS) students for the 2009 cohort. The authors measured student, father and mother characteristics likely to influence admission to a public university. The results show that the major predictors of public university entry are students' academic ability, quality of SHS attended and number of siblings. This seems to suggest that there is a significant bias in the selection of students from different socio-economic groups for admission to highly subsidised public universities. The implication is that public financing of university education in Ghana may not be equitable.

Quantitative Analysis of Driving Factors of Grassland Degradation: A Case Study in Xilin River Basin, Inner Mongolia

PubMed Central

Xie, Yichun; Sha, Zongyao

2012-01-01

Current literature suggests that grassland degradation occurs in areas with poor soil conditions or noticeable environmental changes and is often a result of overgrazing or human disturbances. However, these views are questioned in our analyses. Based on the analysis of satellite vegetation maps from 1984, 1998, and 2004 for the Xilin River Basin, Inner Mongolia, China, and binary logistic regression (BLR) analysis, we observe the following: (1) grassland degradation is positively correlated with the growth density of climax communities; (2) our findings do not support a common notion that a decrease of biological productivity is a direct indicator of grassland degradation; (3) a causal relationship between grazing intensity and grassland degradation was not found; (4) degradation severity increased steadily towards roads but showed different trends near human settlements. This study found complex relationships between vegetation degradation and various microhabitat conditions, for example, elevation, slope, aspect, and proximity to water. PMID:22619613

The influence of intrinsic and extrinsic job values on turnover intention among continuing care assistants in Nova Scotia.

PubMed

Dill, Donna M; Keefe, Janice M; McGrath, Daniel S

2012-01-01

This article examines the influence that intrinsic and extrinsic job values have on the turnover intention of continuing care assistants (CCAs) who work either in home care or facility-based care in Nova Scotia (n = 188). Factor analysis of job values identified three latent job values structures: "compensation and commitment," "flexibility and opportunity," and "positive work relationships." Using binary logistic regression, we examined the predictive utility of these factors on two indices of turnover intention. Regression results indicate that, in general, job values constructs did not significantly predict turnover intention when controlling for demographics and job characteristics. However, a trend was found for the "positive work relationships" factor in predicting consideration of changing employers. In addition, CCAs who work in facility-based care were significantly more likely to have considered leaving their current employer. With projected increases in the demand for these workers in both home and continuing care, more attention is needed to identify and address factors to reduce turnover intention.

Gender differences in physical disability among older adults in underprivileged communities in Lebanon.

PubMed

Zeki Al Hazzouri, Adina; Mehio Sibai, Abla; Chaaya, Monique; Mahfoud, Ziyad; Yount, Kathryn M

2011-03-01

To examine the role of health conditions, socioeconomic, and socioenvironmental factors in explaining gender differences in physical disability among older adults. We compared 412 women and 328 men residing in underprivileged communities in Lebanon on their activities of daily living (ADL), instrumental activities of daily living (IADL), and physical tasks (PT). Binary logistic regression analyses adjusting for possible explanatory covariates were conducted sequentially. Women showed higher prevalence rates of ADL, IADL, and PT compared to men. Gender disparities in ADL disability were explained by chronic-disease risk factors and health conditions (OR = 1.46; 95% CI = 0.94-2.25). The odds of disability in IADL and PT remained significantly higher for women compared to men after accounting for all available covariates. These results suggest underlying differences in functional status between women and men, yet, may have been influenced by the sensitivity of the measures to the social context and gendered environment surrounding daily activities.

On the Use of Local Assessments for Monitoring Centrally Reviewed Endpoints with Missing Data in Clinical Trials*

PubMed Central

Brummel, Sean S.; Gillen, Daniel L.

2014-01-01

Due to ethical and logistical concerns it is common for data monitoring committees to periodically monitor accruing clinical trial data to assess the safety, and possibly efficacy, of a new experimental treatment. When formalized, monitoring is typically implemented using group sequential methods. In some cases regulatory agencies have required that primary trial analyses should be based solely on the judgment of an independent review committee (IRC). The IRC assessments can produce difficulties for trial monitoring given the time lag typically associated with receiving assessments from the IRC. This results in a missing data problem wherein a surrogate measure of response may provide useful information for interim decisions and future monitoring strategies. In this paper, we present statistical tools that are helpful for monitoring a group sequential clinical trial with missing IRC data. We illustrate the proposed methodology in the case of binary endpoints under various missingness mechanisms including missing completely at random assessments and when missingness depends on the IRC’s measurement. PMID:25540717

Does Percent Body Fat Predict Outcome in Anorexia Nervosa?

PubMed Central

Mayer, Laurel E.S.; Roberto, Christina A.; Glasofer, Deborah R.; Etu, Sarah Fischer; Gallagher, Dympna; Wang, Jack; Heymsfield, Steven B.; Pierson, Richard N.; Attia, Evelyn; Devlin, Michael J.; Walsh, B. Timothy

2009-01-01

Objective The goal of this study was to investigate the relationship of body composition and neuroendocrine levels with clinical outcome in women with anorexia nervosa in a relapse-prevention trial. Method Body composition and fasting cortisol and leptin levels were assessed before random assignment in 32 weight-recovered subjects with anorexia nervosa from the New York site of the Fluoxetine to Prevent Relapse in Women With Anorexia Nervosa trial. Clinical outcome at the end of study participation was defined using modified Morgan-Russell criteria (full, good, fair, poor), then dichotomized into treatment “success” or “failure.” Results In a binary logistic regression model examining the effect of percent body fat, body mass index, anorexia nervosa subtype, waist-to-hip ratio, and serum cortisol and leptin levels on treatment outcome, only percent body fat was significantly associated with outcome. Conclusions In recently weight-restored women with anorexia nervosa, lower percent body fat was associated with poor long-term outcome. PMID:17541059

Approach and Avoidance Tendencies Toward Picture Stimuli of (Pre-)Pubescent Children and Adults: An Investigation in Pedophilic and Nonpedophilic Samples.

PubMed

Weidacker, K; Kärgel, C; Massau, C; Weiß, S; Kneer, J; Krueger, T H C; Schiffer, B

2017-03-01

The presence of pedophilic sexual interests is considered of high importance for predicting recidivism among individuals who have committed sexual offenses. However, objective and valid assessment methods that are robust against confounding issues such as cognitive capacity and manipulation are sparse. We applied the Approach-Avoidance Task (AAT) for detecting sexual interests in 38 pedophilic men (18 primarily attracted to boys) and 27 male nonpedophilic (11 gay) participants. The AAT relies on automatic approach and avoidance tendencies, independent of cognitive abilities such as memory capacity and intelligence. Approach-avoidance tendencies toward stimuli depicting seminude prepubescent boys and girls as well as men and women are reported. The results were consistent with previous research on the utility of the AAT: Except for pedophiles attracted to girls, the mean AAT scores (approach minus avoidance reaction time for each stimulus category) were positive only for stimuli of the preferred category. A multivariate binary logistic regression approach revealed 80% overall accuracy in differentiating pedophilic from nonpedophilic participants.

The level of consumer information about health insurance in Nanjing, China.

PubMed

Xu, Weiwei; Van de Ven, Wynand P M M

2014-01-01

The Chinese government is considering a (regulated) competitive healthcare system. Sufficient consumer information is a crucial pre-condition to benefit from such a change. We conducted a survey on the level of consumer information regarding health insurance among the insured population in Nanjing, China in 2009. The results from descriptive analysis and binary logistic regression demonstrate that the current level of consumer information about health insurance is low. The level of consumer information is positively correlated with the subscribers' motivation to obtain the information and its availability. The level of searching for health insurance information is also low; moreover, even upon searching, the chance of finding relevant information is less than 25%. We conclude that the level of consumer information is currently insufficient in China. If the Chinese government is determined to adopt market mechanisms in the healthcare sector, it should take the lead in making valid and reliable information publicly available and easily accessible. Copyright © 2012 John Wiley & Sons, Ltd.

The influence of brain abnormalities on psychosocial development, criminal history and paraphilias in sexual murderers.

PubMed

Briken, Peer; Habermann, Niels; Berner, Wolfgang; Hill, Andreas

2005-09-01

The aim of this study was to investigate the number and type of brain abnormalities and their influence on psychosocial development, criminal history and paraphilias in sexual murderers. We analyzed psychiatric court reports of 166 sexual murderers and compared a group with notable signs of brain abnormalities (N = 50) with those without any signs (N = 116). Sexual murderers with brain abnormalities suffered more from early behavior problems. They were less likely to cohabitate with the victim at the time of the homicide and had more victims at the age of six years or younger. Psychiatric diagnoses revealed a higher total number of paraphilias: Transvestic fetishism and paraphilias not otherwise specified were more frequent in offenders with brain abnormalities. A binary logistic regression identified five predictors that accounted for 46.8% of the variance explaining the presence of brain abnormalities. Our results suggest the importance of a comprehensive neurological and psychological examination of this special offender group.

Screening utility of the social anxiety screening scale in Spanish speaking adolescents.

PubMed

Piqueras, José Antonio; Olivares, José; Hidalgo, María Dolores

2012-07-01

The aim of this study was to analyse the screening utility of the Social Anxiety Screening Scale (SASS/EDAS) in a sample of 227 adolescents with social anxiety disorder and 156 Without it (14-17 years). Results showed that the EDAS subscales (Avoidance, Distress and Interference) scores were reliable in terms of internal consistency (alpha > .80). All the subscales discriminated between adolescents with and without the disorder. They also showed a positive and significant correlation with other empirically validated measures of social anxiety. The three subscales indicated relevant sensitivity (69.16-84.14%), specificity (63.46-66.03%) and areas under the curve (.74-.81%). Binary logistic regression analyses indicated the adequate predictive utility of EDAS subscales, with the Distress subscale as the best diagnostic predictor. The data provide empirical evidence of the usefulness of EDAS as a screener for adolescent social anxiety disorder in terms of reliability, convergent and discriminant validity, diagnostic accuracy and clinical usefulness.

An examination of the MASC Social Anxiety Scale in a non-referred sample of adolescents.

PubMed

Anderson, Emily R; Jordan, Judith A; Smith, Ashley J; Inderbitzen-Nolan, Heidi M

2009-12-01

Social phobia is prevalent during adolescence and is associated with negative outcomes. Two self-report instruments are empirically validated to specifically assess social phobia symptomatology in youth: the Social Phobia and Anxiety Inventory for Children and the Social Anxiety Scale for Adolescents. The Multidimensional Anxiety Scale for Children is a broad-band measure of anxiety containing a scale assessing the social phobia construct. The present study investigated the MASC Social Anxiety Scale in relation to other well-established measures of social phobia and depression in a non-referred sample of adolescents. Results support the convergent validity of the MASC Social Anxiety Scale and provide some support for its discriminant validity, suggesting its utility in the initial assessment of social phobia. Receiver Operating Characteristics (ROCs) calculated the sensitivity and specificity of the MASC Social Anxiety Scale. Binary logistic regression analyses determined the predictive utility of the MASC Social Anxiety Scale. Implications for assessment are discussed.

Auditory processing and phonological awareness skills of five-year-old children with and without musical experience.

PubMed

Escalda, Júlia; Lemos, Stela Maris Aguiar; França, Cecília Cavalieri

2011-09-01

To investigate the relations between musical experience, auditory processing and phonological awareness of groups of 5-year-old children with and without musical experience. Participants were 56 5-year-old subjects of both genders, 26 in the Study Group, consisting of children with musical experience, and 30 in the Control Group, consisting of children without musical experience. All participants were assessed with the Simplified Auditory Processing Assessment and Phonological Awareness Test and the data was statistically analyzed. There was a statistically significant difference between the results of the sequential memory test for verbal and non-verbal sounds with four stimuli, phonological awareness tasks of rhyme recognition, phonemic synthesis and phonemic deletion. Analysis of multiple binary logistic regression showed that, with exception of the sequential verbal memory with four syllables, the observed difference in subjects' performance was associated with their musical experience. Musical experience improves auditory and metalinguistic abilities of 5-year-old children.

The association between second-hand smoke exposure and depressive symptoms among pregnant women.

PubMed

Huang, Jingya; Wen, Guoming; Yang, Weikang; Yao, Zhenjiang; Wu, Chuan'an; Ye, Xiaohua

2017-10-01

Tobacco smoking and depression are strongly associated, but the possible association between second-hand smoke (SHS) exposure and depression is unclear. This study aimed to examine the possible relation between SHS exposure and depressive symptoms among pregnant women. A cross-sectional survey was conducted in Shenzhen, China, using a multistage sampling method. The univariable and multivariable logistic regression models were used to explore the associations between SHS exposure and depressive symptoms. Among 2176 pregnant women, 10.5% and 2.0% were classified as having probable and severe depressive symptoms. Both binary and multinomial logistic regression revealed that there were significantly increased risks of severe depressive symptoms corresponding to SHS exposure in homes or regular SHS exposure in workplaces using no exposure as reference. In addition, greater frequency of SHS exposure was significantly associated with the increased risk of severe depressive symptoms. Our findings suggest that SHS exposure is positively associated with depressive symptoms in a dose-response manner among the pregnant women. Copyright © 2017 Elsevier B.V. All rights reserved.

Seroprevalence of human hydatidosis using ELISA method in qom province, central iran.

PubMed

Rakhshanpour, A; Harandi, M Fasihi; Moazezi, Ss; Rahimi, Mt; Mohebali, M; Mowlavi, Ghh; Babaei, Z; Ariaeipour, M; Heidari, Z; Rokni, Mb

2012-01-01

The objective of this study was to determine the prevalence of cystic echinococcosis (CE) in Qom Province, central Iran using ELISA test. Overall, 1564 serum samples (800 males and 764 females) were collected from selected subjects by randomized cluster sampling in 2011-2012. Sera were analyzed by ELISA test using AgB. Before sampling, a questionnaire was filled out for each case. Data were analyzed using Chi-square test and multivariate logistic regression for risk factors analysis. Seropositivity was 1.6% (25 cases). Males (2.2%) showed significantly more positivity than females (0.9%) (P= 0.03). There was no significant association between CE seropositivity and age group, occupation, and region. Age group of 30-60 years encompassed the highest rate of positivity. The seropositivity of CE was 2.1% and 1.2% for urban and rural cases respectively. Binary logistic regression showed that males were 2.5 times at higher risk for infection than females. Although seroprevalence of CE is relatively low in Qom Province, yet due to the importance of the disease, all preventive measures should be taken into consideration.

Performance Comparison of Systemic Inflammatory Response Syndrome with Logistic Regression Models to Predict Sepsis in Neonates

PubMed Central

Thakur, Jyoti; Pahuja, Sharvan Kumar; Pahuja, Roop

2017-01-01

In 2005, an international pediatric sepsis consensus conference defined systemic inflammatory response syndrome (SIRS) for children <18 years of age, but excluded premature infants. In 2012, Hofer et al. investigated the predictive power of SIRS for term neonates. In this paper, we examined the accuracy of SIRS in predicting sepsis in neonates, irrespective of their gestational age (i.e., pre-term, term, and post-term). We also created two prediction models, named Model A and Model B, using binary logistic regression. Both models performed better than SIRS. We also developed an android application so that physicians can easily use Model A and Model B in real-world scenarios. The sensitivity, specificity, positive likelihood ratio (PLR) and negative likelihood ratio (NLR) in cases of SIRS were 16.15%, 95.53%, 3.61, and 0.88, respectively, whereas they were 29.17%, 97.82%, 13.36, and 0.72, respectively, in the case of Model A, and 31.25%, 97.30%, 11.56, and 0.71, respectively, in the case of Model B. All models were significant with p < 0.001. PMID:29257099

A nonlinear isobologram model with Box-Cox transformation to both sides for chemical mixtures.

PubMed

Chen, D G; Pounds, J G

1998-12-01

The linear logistical isobologram is a commonly used and powerful graphical and statistical tool for analyzing the combined effects of simple chemical mixtures. In this paper a nonlinear isobologram model is proposed to analyze the joint action of chemical mixtures for quantitative dose-response relationships. This nonlinear isobologram model incorporates two additional new parameters, Ymin and Ymax, to facilitate analysis of response data that are not constrained between 0 and 1, where parameters Ymin and Ymax represent the minimal and the maximal observed toxic response. This nonlinear isobologram model for binary mixtures can be expressed as [formula: see text] In addition, a Box-Cox transformation to both sides is introduced to improve the goodness of fit and to provide a more robust model for achieving homogeneity and normality of the residuals. Finally, a confidence band is proposed for selected isobols, e.g., the median effective dose, to facilitate graphical and statistical analysis of the isobologram. The versatility of this approach is demonstrated using published data describing the toxicity of the binary mixtures of citrinin and ochratoxin as well as a new experimental data from our laboratory for mixtures of mercury and cadmium.

A nonlinear isobologram model with Box-Cox transformation to both sides for chemical mixtures.

PubMed Central

Chen, D G; Pounds, J G

1998-01-01

The linear logistical isobologram is a commonly used and powerful graphical and statistical tool for analyzing the combined effects of simple chemical mixtures. In this paper a nonlinear isobologram model is proposed to analyze the joint action of chemical mixtures for quantitative dose-response relationships. This nonlinear isobologram model incorporates two additional new parameters, Ymin and Ymax, to facilitate analysis of response data that are not constrained between 0 and 1, where parameters Ymin and Ymax represent the minimal and the maximal observed toxic response. This nonlinear isobologram model for binary mixtures can be expressed as [formula: see text] In addition, a Box-Cox transformation to both sides is introduced to improve the goodness of fit and to provide a more robust model for achieving homogeneity and normality of the residuals. Finally, a confidence band is proposed for selected isobols, e.g., the median effective dose, to facilitate graphical and statistical analysis of the isobologram. The versatility of this approach is demonstrated using published data describing the toxicity of the binary mixtures of citrinin and ochratoxin as well as a new experimental data from our laboratory for mixtures of mercury and cadmium. PMID:9860894

Test equality in binary data for a 4 × 4 crossover trial under a Latin-square design.

PubMed

Lui, Kung-Jong; Chang, Kuang-Chao

2016-10-15

When there are four or more treatments under comparison, the use of a crossover design with a complete set of treatment-receipt sequences in binary data is of limited use because of too many treatment-receipt sequences. Thus, we may consider use of a 4 × 4 Latin square to reduce the number of treatment-receipt sequences when comparing three experimental treatments with a control treatment. Under a distribution-free random effects logistic regression model, we develop simple procedures for testing non-equality between any of the three experimental treatments and the control treatment in a crossover trial with dichotomous responses. We further derive interval estimators in closed forms for the relative effect between treatments. To evaluate the performance of these test procedures and interval estimators, we employ Monte Carlo simulation. We use the data taken from a crossover trial using a 4 × 4 Latin-square design for studying four-treatments to illustrate the use of test procedures and interval estimators developed here. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

The impact of IUE on binary star studies

NASA Technical Reports Server (NTRS)

Plavec, M. J.

1981-01-01

The use of IUE observations in the investigation of binary stars is discussed. The results of data analysis of several classes of binary systems are briefly reviewed including zeta Aurigae and VV Cephei stars, mu Sagittarii, epsilon Aurigae, beta Lyrae and the W Serpentis stars, symbiotic stars, and the Algols.

A Photometric Study of the Eclipsing Binary Star PY Boötis

NASA Astrophysics Data System (ADS)

Michaels, E. J.

2016-12-01

Presented here are the first precision multi-band CCD photometry of the eclipsing binary star PY Boötis. Best-fit stellar models were determined by analyzing the light curves with the Wilson-Devinney program. Asymmetries in the light curves were interpreted as resulting from magnetic activity which required spots to be included in the model. The resulting model is consistent with a W-type contact eclipsing binary having total eclipses.

Finding an appropriate equation to measure similarity between binary vectors: case studies on Indonesian and Japanese herbal medicines.

PubMed

Wijaya, Sony Hartono; Afendi, Farit Mochamad; Batubara, Irmanida; Darusman, Latifah K; Altaf-Ul-Amin, Md; Kanaya, Shigehiko

2016-12-07

The binary similarity and dissimilarity measures have critical roles in the processing of data consisting of binary vectors in various fields including bioinformatics and chemometrics. These metrics express the similarity and dissimilarity values between two binary vectors in terms of the positive matches, absence mismatches or negative matches. To our knowledge, there is no published work presenting a systematic way of finding an appropriate equation to measure binary similarity that performs well for certain data type or application. A proper method to select a suitable binary similarity or dissimilarity measure is needed to obtain better classification results. In this study, we proposed a novel approach to select binary similarity and dissimilarity measures. We collected 79 binary similarity and dissimilarity equations by extensive literature search and implemented those equations as an R package called bmeasures. We applied these metrics to quantify the similarity and dissimilarity between herbal medicine formulas belonging to the Indonesian Jamu and Japanese Kampo separately. We assessed the capability of binary equations to classify herbal medicine pairs into match and mismatch efficacies based on their similarity or dissimilarity coefficients using the Receiver Operating Characteristic (ROC) curve analysis. According to the area under the ROC curve results, we found Indonesian Jamu and Japanese Kampo datasets obtained different ranking of binary similarity and dissimilarity measures. Out of all the equations, the Forbes-2 similarity and the Variant of Correlation similarity measures are recommended for studying the relationship between Jamu formulas and Kampo formulas, respectively. The selection of binary similarity and dissimilarity measures for multivariate analysis is data dependent. The proposed method can be used to find the most suitable binary similarity and dissimilarity equation wisely for a particular data. Our finding suggests that all four types of matching quantities in the Operational Taxonomic Unit (OTU) table are important to calculate the similarity and dissimilarity coefficients between herbal medicine formulas. Also, the binary similarity and dissimilarity measures that include the negative match quantity d achieve better capability to separate herbal medicine pairs compared to equations that exclude d.

Binary Decision Trees for Preoperative Periapical Cyst Screening Using Cone-beam Computed Tomography.

PubMed

Pitcher, Brandon; Alaqla, Ali; Noujeim, Marcel; Wealleans, James A; Kotsakis, Georgios; Chrepa, Vanessa

2017-03-01

Cone-beam computed tomographic (CBCT) analysis allows for 3-dimensional assessment of periradicular lesions and may facilitate preoperative periapical cyst screening. The purpose of this study was to develop and assess the predictive validity of a cyst screening method based on CBCT volumetric analysis alone or combined with designated radiologic criteria. Three independent examiners evaluated 118 presurgical CBCT scans from cases that underwent apicoectomies and had an accompanying gold standard histopathological diagnosis of either a cyst or granuloma. Lesion volume, density, and specific radiologic characteristics were assessed using specialized software. Logistic regression models with histopathological diagnosis as the dependent variable were constructed for cyst prediction, and receiver operating characteristic curves were used to assess the predictive validity of the models. A conditional inference binary decision tree based on a recursive partitioning algorithm was constructed to facilitate preoperative screening. Interobserver agreement was excellent for volume and density, but it varied from poor to good for the radiologic criteria. Volume and root displacement were strong predictors for cyst screening in all analyses. The binary decision tree classifier determined that if the volume of the lesion was >247 mm 3 , there was 80% probability of a cyst. If volume was <247 mm 3 and root displacement was present, cyst probability was 60% (78% accuracy). The good accuracy and high specificity of the decision tree classifier renders it a useful preoperative cyst screening tool that can aid in clinical decision making but not a substitute for definitive histopathological diagnosis after biopsy. Confirmatory studies are required to validate the present findings. Published by Elsevier Inc.

The Eclipsing Binary On-Line Atlas (EBOLA)

NASA Astrophysics Data System (ADS)

Bradstreet, D. H.; Steelman, D. P.; Sanders, S. J.; Hargis, J. R.

2004-05-01

In conjunction with the upcoming release of \\it Binary Maker 3.0, an extensive on-line database of eclipsing binaries is being made available. The purposes of the atlas are: \\begin {enumerate} Allow quick and easy access to information on published eclipsing binaries. Amass a consistent database of light and radial velocity curve solutions to aid in solving new systems. Provide invaluable querying capabilities on all of the parameters of the systems so that informative research can be quickly accomplished on a multitude of published results. Aid observers in establishing new observing programs based upon stars needing new light and/or radial velocity curves. Encourage workers to submit their published results so that others may have easy access to their work. Provide a vast but easily accessible storehouse of information on eclipsing binaries to accelerate the process of understanding analysis techniques and current work in the field. \\end {enumerate} The database will eventually consist of all published eclipsing binaries with light curve solutions. The following information and data will be supplied whenever available for each binary: original light curves in all bandpasses, original radial velocity observations, light curve parameters, RA and Dec, V-magnitudes, spectral types, color indices, periods, binary type, 3D representation of the system near quadrature, plots of the original light curves and synthetic models, plots of the radial velocity observations with theoretical models, and \\it Binary Maker 3.0 data files (parameter, light curve, radial velocity). The pertinent references for each star are also given with hyperlinks directly to the papers via the NASA Abstract website for downloading, if available. In addition the Atlas has extensive searching options so that workers can specifically search for binaries with specific characteristics. The website has more than 150 systems already uploaded. The URL for the site is http://ebola.eastern.edu/.

Exploring students' patterns of reasoning

NASA Astrophysics Data System (ADS)

Matloob Haghanikar, Mojgan

As part of a collaborative study of the science preparation of elementary school teachers, we investigated the quality of students' reasoning and explored the relationship between sophistication of reasoning and the degree to which the courses were considered inquiry oriented. To probe students' reasoning, we developed open-ended written content questions with the distinguishing feature of applying recently learned concepts in a new context. We devised a protocol for developing written content questions that provided a common structure for probing and classifying students' sophistication level of reasoning. In designing our protocol, we considered several distinct criteria, and classified students' responses based on their performance for each criterion. First, we classified concepts into three types: Descriptive, Hypothetical, and Theoretical and categorized the abstraction levels of the responses in terms of the types of concepts and the inter-relationship between the concepts. Second, we devised a rubric based on Bloom's revised taxonomy with seven traits (both knowledge types and cognitive processes) and a defined set of criteria to evaluate each trait. Along with analyzing students' reasoning, we visited universities and observed the courses in which the students were enrolled. We used the Reformed Teaching Observation Protocol (RTOP) to rank the courses with respect to characteristics that are valued for the inquiry courses. We conducted logistic regression for a sample of 18courses with about 900 students and reported the results for performing logistic regression to estimate the relationship between traits of reasoning and RTOP score. In addition, we analyzed conceptual structure of students' responses, based on conceptual classification schemes, and clustered students' responses into six categories. We derived regression model, to estimate the relationship between the sophistication of the categories of conceptual structure and RTOP scores. However, the outcome variable with six categories required a more complicated regression model, known as multinomial logistic regression, generalized from binary logistic regression. With the large amount of collected data, we found that the likelihood of the higher cognitive processes were in favor of classes with higher measures on inquiry. However, the usage of more abstract concepts with higher order conceptual structures was less prevalent in higher RTOP courses.

Be discs in coplanar circular binaries: Phase-locked variations of emission lines

NASA Astrophysics Data System (ADS)

Panoglou, Despina; Faes, Daniel M.; Carciofi, Alex C.; Okazaki, Atsuo T.; Baade, Dietrich; Rivinius, Thomas; Borges Fernandes, Marcelo

2018-01-01

In this paper, we present the first results of radiative transfer calculations on decretion discs of binary Be stars. A smoothed particle hydrodynamics code computes the structure of Be discs in coplanar circular binary systems for a range of orbital and disc parameters. The resulting disc configuration consists of two spiral arms, and this can be given as input into a Monte Carlo code, which calculates the radiative transfer along the line of sight for various observational coordinates. Making use of the property of steady disc structure in coplanar circular binaries, observables are computed as functions of the orbital phase. Some orbital-phase series of line profiles are given for selected parameter sets under various viewing angles, to allow comparison with observations. Flat-topped profiles with and without superimposed multiple structures are reproduced, showing, for example, that triple-peaked profiles do not have to be necessarily associated with warped discs and misaligned binaries. It is demonstrated that binary tidal effects give rise to phase-locked variability of the violet-to-red (V/R) ratio of hydrogen emission lines. The V/R ratio exhibits two maxima per cycle; in certain cases those maxima are equal, leading to a clear new V/R cycle every half orbital period. This study opens a way to identifying binaries and to constraining the parameters of binary systems that exhibit phase-locked variations induced by tidal interaction with a companion star.

Binary optics: Trends and limitations

NASA Technical Reports Server (NTRS)

Farn, Michael W.; Veldkamp, Wilfrid B.

1993-01-01

We describe the current state of binary optics, addressing both the technology and the industry (i.e., marketplace). With respect to the technology, the two dominant aspects are optical design methods and fabrication capabilities, with the optical design problem being limited by human innovation in the search for new applications and the fabrication issue being limited by the availability of resources required to improve fabrication capabilities. With respect to the industry, the current marketplace does not favor binary optics as a separate product line and so we expect that companies whose primary purpose is the production of binary optics will not represent the bulk of binary optics production. Rather, binary optics' more natural role is as an enabling technology - a technology which will directly result in a competitive advantage in a company's other business areas - and so we expect that the majority of binary optics will be produced for internal use.

Peripheral retinal ischaemia, as evaluated by ultra-widefield fluorescein angiography, is associated with diabetic macular oedema

PubMed Central

Wessel, Matthew M; Nair, Nandini; Aaker, Grant D; Ehrlich, Joshua R; D'Amico, Donald J

2012-01-01

Purpose To determine the relationship between retinal ischaemia and the presence of macular oedema (DMO) in patients with diabetic retinopathy (DR) using ultra-widefield fluorescein angiography (UWFA) imaging. Methods A retrospective review of 122 eyes of 70 treatment-naïve diabetic patients who underwent diagnostic UWFA using the Optos 200Tx imaging system. Two independent, masked graders quantified the area of retinal ischaemia. Based on clinical examination and optical coherence tomography (OCT), each patient was given a binary classification as either having DMO or no DMO. McNemar's test (with Yates' correction as indicated) and a two-sample test of proportions were used to determine the relationship between DMO and ischaemia for binary and proportional data, respectively. Linear and logistic models were constructed using generalised estimating equations to test relationships between independent variables, covariates and outcomes while controlling for inter-eye correlation, age, gender, haemoglobin A1c, mean arterial pressure and dependence on insulin. Results Seventy-six eyes (62%) exhibited areas of retinal ischaemia. There was a significant direct correlation between DMO and peripheral retinal ischaemia as seen on UWFA (p<0.001). In addition, patients with retinal ischaemia had 3.75 times increased odds of having DMO compared with those without retinal ischaemia (CI 1.26 to 11.13, p<0.02). Conclusion Retinal ischaemia is significantly correlated with DMO in treatment-naïve patients with DR. UWFA is a useful tool for detecting peripheral retinal ischaemia, which may have direct implications in the diagnosis, follow-up and treatment such as targeted peripheral photocoagulation. PMID:22423055

Ethnicity, education attainment, media exposure, and prenatal care in Vietnam.

PubMed

Trinh, Ha Ngoc; Korinek, Kim

2017-02-01

Prenatal care coverage in Vietnam has been improving, but ethnic minority women still lag behind in receiving adequate level and type of care. This paper examines ethnic disparities in prenatal care utilization by comparing two groups of ethnic minority and majority women. We examine the roots of ethnic disparity in prenatal care utilization, focusing on how education and media exposure change health behaviours and lessen disparities. We rely on the 2002 Vietnam Demographic and Health Survey to draw our sample, predictors and the three dimensions of prenatal care, including timing of onset, frequency of visits, and type of provider. Results from multinomial-, and binary-logistic regression provide evidence that ethnic minority women are less likely to obtain frequent prenatal care and seek care from professional providers than their majority counterparts. However, we find that ethnic minority women are more likely to obtain early care compared to ethnic majority women. Results for predicted probabilities suggest that education and media exposure positively influenced prenatal care behaviours with higher level of education and media exposure associating with accelerated probability of meeting prenatal care requirements. Our results imply the needs for expansion of media access and schools as well as positive health messages being broadcasted in culturally competent ways.

Is black-hole ringdown a memory of its progenitor?

PubMed

Kamaretsos, Ioannis; Hannam, Mark; Sathyaprakash, B S

2012-10-05

We perform an extensive numerical study of coalescing black-hole binaries to understand the gravitational-wave spectrum of quasinormal modes excited in the merged black hole. Remarkably, we find that the masses and spins of the progenitor are clearly encoded in the mode spectrum of the ringdown signal. Some of the mode amplitudes carry the signature of the binary's mass ratio, while others depend critically on the spins. Simulations of precessing binaries suggest that our results carry over to generic systems. Using Bayesian inference, we demonstrate that it is possible to accurately measure the mass ratio and a proper combination of spins even when the binary is itself invisible to a detector. Using a mapping of the binary masses and spins to the final black-hole spin allows us to further extract the spin components of the progenitor. Our results could have tremendous implications for gravitational astronomy by facilitating novel tests of general relativity using merging black holes.

Dielectric properties of grain-grainboundary binary system

NASA Astrophysics Data System (ADS)

Cheng, Peng-Fei; Li, Sheng-Tao; Wang, Hui

2014-09-01

Dielectric properties of grain-grainboundary binary system are analyzed theoretically and compared with unary system and classical Maxwell-Wagner (MW) polarization in binary system. It is found that MW polarization appears at higher frequency compared with intrinsic polarization for grain-grainboundary binary system, which is abnormal compared with classical dielectric theory. This dielectric anomaly is premised on the existence of electronic relaxation at grainboundary. The origin of giant dielectric constant of CaCu3Ti4O12 (CCTO) ceramics is also investigated on the basis of the theoretical results. It is proposed that low frequency relaxation originates from electronic relaxation of oxygen vacancy at depletion layer, while high frequency relaxation comes from MW polarization. The results of this paper offer a quantitative identification of MW polarization from intrinsic polarization at grainboundary and a judgment of the mechanism and location of a certain polarization in grain-grainboundary binary system.

Exploring definitions of financial abuse in elderly Korean immigrants: the contribution of traditional cultural values.

PubMed

Lee, Hee Yun; Lee, Sang E; Eaton, Charissa K

2012-10-01

The purpose of this study is to explore the cultural definitions of financial abuse from the perspective of 124 elderly Korean immigrants and to examine the role of traditional cultural values in their definitions by using a mixed methods approach. The qualitative analysis generated four themes relevant to definition of financial abuse. A binary logistic regression indicated that those with stronger cultural adherence to traditional values had higher odds of providing culture-based definitions of financial abuse. Education is needed for health professionals, social service providers, and adult protective workers to increase their understanding of culture-specific experiences of financial abuse among ethnic minority elders.

From wide to close binaries?

NASA Astrophysics Data System (ADS)

Eggleton, Peter P.

The mechanisms by which the periods of wide binaries (mass 8 solar mass or less and period 10-3000 d) are lengthened or shortened are discussed, synthesizing the results of recent theoretical investigations. A system of nomenclature involving seven evolutionary states, three geometrical states, and 10 types of orbital-period evolution is developed and applied; classifications of 71 binaries are presented in a table along with the basic observational parameters. Evolutionary processes in wide binaries (single-star-type winds, magnetic braking with tidal friction, and companion-reinforced attrition), late case B systems, low-mass X-ray binaries, and triple systems are examined in detail, and possible evolutionary paths are shown in diagrams.

Bayesian performance metrics of binary sensors in homeland security applications

NASA Astrophysics Data System (ADS)

Jannson, Tomasz P.; Forrester, Thomas C.

2008-04-01

Bayesian performance metrics, based on such parameters, as: prior probability, probability of detection (or, accuracy), false alarm rate, and positive predictive value, characterizes the performance of binary sensors; i.e., sensors that have only binary response: true target/false target. Such binary sensors, very common in Homeland Security, produce an alarm that can be true, or false. They include: X-ray airport inspection, IED inspections, product quality control, cancer medical diagnosis, part of ATR, and many others. In this paper, we analyze direct and inverse conditional probabilities in the context of Bayesian inference and binary sensors, using X-ray luggage inspection statistical results as a guideline.

The extraneous eclipses on binary light curves: KIC 5255552, KIC 10091110, and KIC 11495766

NASA Astrophysics Data System (ADS)

Zhang, J.; Qian, S. B.; Wang, S. M.; Sun, L. L.; Wu, Y.; Jiang, L. Q.

2018-03-01

Aims: We aim to find more eclipsing multiple systems and obtain their parameters, thus increasing our understanding of multiple systems. Methods: The extraneous eclipses on the Kepler binary light curves indicating extraneous bodies were searched. The binary light curves were analyzed using the binary model, and the extraneous eclipses were studied on their periodicity and shape changes. Results: Three binaries with extraneous eclipses on the binary light curves were found and studied based on the Kepler observations. The object KIC 5255552 is an eclipsing triple system with a fast changing inner binary and an outer companion uncovered by three groups of extraneous eclipses of 862.1(±0.1) d period. The KIC 10091110 is suggested to be a double eclipsing binary system with several possible extraordinary coincidences: the two binaries share similar extremely small mass ratios (0.060(13) and 0.0564(18)), similar mean primary densities (0.3264(42) ρ⊙ and 0.3019(28) ρ⊙), and, most notably, the ratio of the two binaries' periods is very close to integer 2 (8.5303353/4.2185174 = 2.022). The KIC 11495766 is a probable triple system with a 120.73 d period binary and (at least) one non-eclipse companion. Furthermore, very close to it in the celestial sphere, there is a blended background stellar binary of 8.3404432 d period. A first list of 25 eclipsing multiple candidates is presented, with the hope that it will be beneficial for study of eclipsing multiples.

Choice of optimal working fluid for binary power plants at extremely low temperature brine

NASA Astrophysics Data System (ADS)

Tomarov, G. V.; Shipkov, A. A.; Sorokina, E. V.

2016-12-01

The geothermal energy development problems based on using binary power plants utilizing lowpotential geothermal resources are considered. It is shown that one of the possible ways of increasing the efficiency of heat utilization of geothermal brine in a wide temperature range is the use of multistage power systems with series-connected binary power plants based on incremental primary energy conversion. Some practically significant results of design-analytical investigations of physicochemical properties of various organic substances and their influence on the main parameters of the flowsheet and the technical and operational characteristics of heat-mechanical and heat-exchange equipment for binary power plant operating on extremely-low temperature geothermal brine (70°C) are presented. The calculation results of geothermal brine specific flow rate, capacity (net), and other operation characteristics of binary power plants with the capacity of 2.5 MW at using various organic substances are a practical interest. It is shown that the working fluid selection significantly influences on the parameters of the flowsheet and the operational characteristics of the binary power plant, and the problem of selection of working fluid is in the search for compromise based on the priorities in the field of efficiency, safety, and ecology criteria of a binary power plant. It is proposed in the investigations on the working fluid selection of the binary plant to use the plotting method of multiaxis complex diagrams of relative parameters and characteristic of binary power plants. Some examples of plotting and analyzing these diagrams intended to choose the working fluid provided that the efficiency of geothermal brine is taken as main priority.

Parameter Estimation for Compact Binaries with Ground-Based Gravitational-Wave Observations Using the LALInference

NASA Technical Reports Server (NTRS)

Veitch, J.; Raymond, V.; Farr, B.; Farr, W.; Graff, P.; Vitale, S.; Aylott, B.; Blackburn, K.; Christensen, N.; Coughlin, M.

2015-01-01

The Advanced LIGO and Advanced Virgo gravitational wave (GW) detectors will begin operation in the coming years, with compact binary coalescence events a likely source for the first detections. The gravitational waveforms emitted directly encode information about the sources, including the masses and spins of the compact objects. Recovering the physical parameters of the sources from the GW observations is a key analysis task. This work describes the LALInference software library for Bayesian parameter estimation of compact binary signals, which builds on several previous methods to provide a well-tested toolkit which has already been used for several studies. We show that our implementation is able to correctly recover the parameters of compact binary signals from simulated data from the advanced GW detectors. We demonstrate this with a detailed comparison on three compact binary systems: a binary neutron star (BNS), a neutron star - black hole binary (NSBH) and a binary black hole (BBH), where we show a cross-comparison of results obtained using three independent sampling algorithms. These systems were analysed with non-spinning, aligned spin and generic spin configurations respectively, showing that consistent results can be obtained even with the full 15-dimensional parameter space of the generic spin configurations. We also demonstrate statistically that the Bayesian credible intervals we recover correspond to frequentist confidence intervals under correct prior assumptions by analysing a set of 100 signals drawn from the prior. We discuss the computational cost of these algorithms, and describe the general and problem-specific sampling techniques we have used to improve the efficiency of sampling the compact binary coalescence (CBC) parameter space.

Learning Compact Binary Face Descriptor for Face Recognition.

PubMed

Lu, Jiwen; Liong, Venice Erin; Zhou, Xiuzhuang; Zhou, Jie

2015-10-01

Binary feature descriptors such as local binary patterns (LBP) and its variations have been widely used in many face recognition systems due to their excellent robustness and strong discriminative power. However, most existing binary face descriptors are hand-crafted, which require strong prior knowledge to engineer them by hand. In this paper, we propose a compact binary face descriptor (CBFD) feature learning method for face representation and recognition. Given each face image, we first extract pixel difference vectors (PDVs) in local patches by computing the difference between each pixel and its neighboring pixels. Then, we learn a feature mapping to project these pixel difference vectors into low-dimensional binary vectors in an unsupervised manner, where 1) the variance of all binary codes in the training set is maximized, 2) the loss between the original real-valued codes and the learned binary codes is minimized, and 3) binary codes evenly distribute at each learned bin, so that the redundancy information in PDVs is removed and compact binary codes are obtained. Lastly, we cluster and pool these binary codes into a histogram feature as the final representation for each face image. Moreover, we propose a coupled CBFD (C-CBFD) method by reducing the modality gap of heterogeneous faces at the feature level to make our method applicable to heterogeneous face recognition. Extensive experimental results on five widely used face datasets show that our methods outperform state-of-the-art face descriptors.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sánchez-Salcedo, F. J.; Chametla, Raul O., E-mail: jsanchez@astro.unam.mx

Using time-dependent linear theory, we investigate the morphology of the gravitational wake induced by a binary, whose center of mass moves at velocity V{sub cm} against a uniform background of gas. For simplicity, we assume that the components of the binary are on circular orbits about their common center of mass. The consequences of dynamical friction is twofold. First, gas dynamical friction may drag the center of mass of the binary and cause the binary to migrate. Second, drag forces also induce a braking torque, which causes the orbits of the components of the binary to shrink. We compute themore » drag forces acting on one component of the binary due to the gravitational interaction with its own wake. We show that the dynamical friction force responsible for decelerating the center of mass of the binary is smaller than it is in the point-mass case because of the loss of gravitational focusing. We show that the braking internal torque depends on the Mach numbers of each binary component about their center of mass, and also on the Mach number of the center of mass of the binary. In general, the internal torque decreases with increasing the velocity of the binary relative to the ambient gas cloud. However, this is not always the case. We also mention the relevance of our results to the period distribution of binaries.« less

The Ruinous Influence of Close Binary Companions on Planetary Systems

NASA Astrophysics Data System (ADS)

Kraus, Adam L.; Ireland, Michael; Mann, Andrew; Huber, Daniel; Dupuy, Trent J.

2017-01-01

The majority of solar-type stars are found in binary systems, and the dynamical influence of binary companions is expected to profoundly influence planetary systems. However, the difficulty of identifying planets in binary systems has left the magnitude of this effect uncertain; despite numerous theoretical hurdles to their formation and survival, at least some binary systems clearly host planets. We present high-resolution imaging of nearly 500 Kepler Objects of Interest (KOIs) obtained using adaptive-optics imaging and nonredundant aperture-mask interferometry on the Keck II telescope. We super-resolve some binary systems to projected separations of under 5 AU, showing that planets might form in these dynamically active environments. However, the full distribution of projected separations for our planet-host sample more broadly reveals a deep paucity of binary companions at solar-system scales. When the binary population is parametrized with a semimajor axis cutoff a cut and a suppression factor inside that cutoff S bin, we find with correlated uncertainties that inside acut = 47 +59/-23 AU, the planet occurrence rate in binary systems is only Sbin = 0.34 +0.14/-0.15 times that of wider binaries or single stars. Our results demonstrate that a fifth of all solar-type stars in the Milky Way are disallowed from hosting planetary systems due to the influence of a binary companion.

The Ruinous Influence of Close Binary Companions on Planetary Systems

NASA Astrophysics Data System (ADS)

Kraus, Adam L.; Ireland, Michael; Mann, Andrew; Huber, Daniel; Dupuy, Trent J.

2017-06-01

The majority of solar-type stars are found in binary systems, and the dynamical influence of binary companions is expected to profoundly influence planetary systems. However, the difficulty of identifying planets in binary systems has left the magnitude of this effect uncertain; despite numerous theoretical hurdles to their formation and survival, at least some binary systems clearly host planets. We present high-resolution imaging of nearly 500 Kepler Objects of Interest (KOIs) obtained using adaptive-optics imaging and nonredundant aperture-mask interferometry on the Keck II telescope. We super-resolve some binary systems to projected separations of under 5 AU, showing that planets might form in these dynamically active environments. However, the full distribution of projected separations for our planet-host sample more broadly reveals a deep paucity of binary companions at solar-system scales. When the binary population is parametrized with a semimajor axis cutoff a cut and a suppression factor inside that cutoff S bin, we find with correlated uncertainties that inside acut = 47 +59/-23 AU, the planet occurrence rate in binary systems is only Sbin = 0.34+0.14/-0.15 times that of wider binaries or single stars. Our results demonstrate that a fifth of all solar-type stars in the Milky Way are disallowed from hosting planetary systems due to the influence of a binary companion.

First Higher-Multipole Model of Gravitational Waves from Spinning and Coalescing Black-Hole Binaries

NASA Astrophysics Data System (ADS)

London, Lionel; Khan, Sebastian; Fauchon-Jones, Edward; García, Cecilio; Hannam, Mark; Husa, Sascha; Jiménez-Forteza, Xisco; Kalaghatgi, Chinmay; Ohme, Frank; Pannarale, Francesco

2018-04-01

Gravitational-wave observations of binary black holes currently rely on theoretical models that predict the dominant multipoles (ℓ=2 ,|m |=2 ) of the radiation during inspiral, merger, and ringdown. We introduce a simple method to include the subdominant multipoles to binary black hole gravitational waveforms, given a frequency-domain model for the dominant multipoles. The amplitude and phase of the original model are appropriately stretched and rescaled using post-Newtonian results (for the inspiral), perturbation theory (for the ringdown), and a smooth transition between the two. No additional tuning to numerical-relativity simulations is required. We apply a variant of this method to the nonprecessing PhenomD model. The result, PhenomHM, constitutes the first higher-multipole model of spinning and coalescing black-hole binaries, and currently includes the (ℓ,|m |)=(2 ,2 ),(3 ,3 ),(4 ,4 ),(2 ,1 ),(3 ,2 ),(4 ,3 ) radiative moments. Comparisons with numerical-relativity waveforms demonstrate that PhenomHM is more accurate than dominant-multipole-only models for all binary configurations, and typically improves the measurement of binary properties.

Research on odor interaction between aldehyde compounds via a partial differential equation (PDE) model.

PubMed

Yan, Luchun; Liu, Jiemin; Qu, Chen; Gu, Xingye; Zhao, Xia

2015-01-28

In order to explore the odor interaction of binary odor mixtures, a series of odor intensity evaluation tests were performed using both individual components and binary mixtures of aldehydes. Based on the linear relation between the logarithm of odor activity value and odor intensity of individual substances, the relationship between concentrations of individual constituents and their joint odor intensity was investigated by employing a partial differential equation (PDE) model. The obtained results showed that the binary odor interaction was mainly influenced by the mixing ratio of two constituents, but not the concentration level of an odor sample. Besides, an extended PDE model was also proposed on the basis of the above experiments. Through a series of odor intensity matching tests for several different binary odor mixtures, the extended PDE model was proved effective at odor intensity prediction. Furthermore, odorants of the same chemical group and similar odor type exhibited similar characteristics in the binary odor interaction. The overall results suggested that the PDE model is a more interpretable way of demonstrating the odor interactions of binary odor mixtures.

First Higher-Multipole Model of Gravitational Waves from Spinning and Coalescing Black-Hole Binaries.

PubMed

London, Lionel; Khan, Sebastian; Fauchon-Jones, Edward; García, Cecilio; Hannam, Mark; Husa, Sascha; Jiménez-Forteza, Xisco; Kalaghatgi, Chinmay; Ohme, Frank; Pannarale, Francesco

2018-04-20

Gravitational-wave observations of binary black holes currently rely on theoretical models that predict the dominant multipoles (ℓ=2,|m|=2) of the radiation during inspiral, merger, and ringdown. We introduce a simple method to include the subdominant multipoles to binary black hole gravitational waveforms, given a frequency-domain model for the dominant multipoles. The amplitude and phase of the original model are appropriately stretched and rescaled using post-Newtonian results (for the inspiral), perturbation theory (for the ringdown), and a smooth transition between the two. No additional tuning to numerical-relativity simulations is required. We apply a variant of this method to the nonprecessing PhenomD model. The result, PhenomHM, constitutes the first higher-multipole model of spinning and coalescing black-hole binaries, and currently includes the (ℓ,|m|)=(2,2),(3,3),(4,4),(2,1),(3,2),(4,3) radiative moments. Comparisons with numerical-relativity waveforms demonstrate that PhenomHM is more accurate than dominant-multipole-only models for all binary configurations, and typically improves the measurement of binary properties.

Photometric binary stars in Praesepe and the search for globular cluster binaries

NASA Technical Reports Server (NTRS)

Bolte, Michael

1991-01-01

A radial velocity study of the stars which are located on a second sequence above the single-star zero-age main sequence at a given color in the color-magnitude diagram of the open cluster Praesepe, (NGC 2632) shows that 10, and possibly 11, of 17 are binary systems. Of the binary systems, five have full amplitudes for their velocity variations that are greater than 50 km/s. To the extent that they can be applied to globular clusters, these results suggests that (1) observations of 'second-sequence' stars in globular clusters would be an efficient way of finding main-sequence binary systems in globulars, and (2) current instrumentation on large telescopes is sufficient for establishing unambiguously the existence of main-sequence binary systems in nearby globular clusters.

Dynamic Inertia Weight Binary Bat Algorithm with Neighborhood Search

PubMed Central

2017-01-01

Binary bat algorithm (BBA) is a binary version of the bat algorithm (BA). It has been proven that BBA is competitive compared to other binary heuristic algorithms. Since the update processes of velocity in the algorithm are consistent with BA, in some cases, this algorithm also faces the premature convergence problem. This paper proposes an improved binary bat algorithm (IBBA) to solve this problem. To evaluate the performance of IBBA, standard benchmark functions and zero-one knapsack problems have been employed. The numeric results obtained by benchmark functions experiment prove that the proposed approach greatly outperforms the original BBA and binary particle swarm optimization (BPSO). Compared with several other heuristic algorithms on zero-one knapsack problems, it also verifies that the proposed algorithm is more able to avoid local minima. PMID:28634487

Dynamic Inertia Weight Binary Bat Algorithm with Neighborhood Search.

PubMed

Huang, Xingwang; Zeng, Xuewen; Han, Rui

2017-01-01

Binary bat algorithm (BBA) is a binary version of the bat algorithm (BA). It has been proven that BBA is competitive compared to other binary heuristic algorithms. Since the update processes of velocity in the algorithm are consistent with BA, in some cases, this algorithm also faces the premature convergence problem. This paper proposes an improved binary bat algorithm (IBBA) to solve this problem. To evaluate the performance of IBBA, standard benchmark functions and zero-one knapsack problems have been employed. The numeric results obtained by benchmark functions experiment prove that the proposed approach greatly outperforms the original BBA and binary particle swarm optimization (BPSO). Compared with several other heuristic algorithms on zero-one knapsack problems, it also verifies that the proposed algorithm is more able to avoid local minima.

Formation of a 'planet' by rapid evaporation of a pulsar's companion

NASA Technical Reports Server (NTRS)

Rasio, F. A.; Shapiro, S. L.; Teukolsky, S. A.

1992-01-01

A model based on the binary configuration of the PSR1829-10 pulsar (Bailes et al., 1991) is used to show that the formation of a binary pulsar with a planet-size companion, large original separation, and small eccentricity could result from the rapid evaporation of a much more massive binary companion by the pulsar's radiation. Such an evaporation process is known to be taking place in at least two other binary pulsars: PSR1957 + 20 (Fruchter et al., 1990; Ryba and Taylor, 1991) and PSR1744 - 24A (Lyne et al., 1990). It is shown here that, about one million years ago, the companion mass and binary separation could have been comparable to those currently observed in the eclipsing binary pulsar PSR1957 + 20.

The architecture of the hierarchical triple star KOI 928 from eclipse timing variations seen in Kepler photometry

DOE PAGES

Steffen, J. H.; Quinn, S. N.; Borucki, W. J.; ...

2011-10-01

We present a hierarchical triple star system (KIC 9140402) where a low mass eclipsing binary orbits a more massive third star. The orbital period of the binary (4.98829 Days) is determined by the eclipse times seen in photometry from NASA's Kepler spacecraft. The periodically changing tidal field, due to the eccentric orbit of the binary about the tertiary, causes a change in the orbital period of the binary. The resulting eclipse timing variations provide insight into the dynamics and architecture of this system and allow the inference of the total mass of the binary (0.424±0.017M circle-dot) and the orbital parametersmore » of the binary about the central star.« less

Creation of an anti-imaging system using binary optics.

PubMed

Wang, Haifeng; Lin, Jian; Zhang, Dawei; Wang, Yang; Gu, Min; Urbach, H P; Gan, Fuxi; Zhuang, Songlin

2016-09-13

We present a concealing method in which an anti-point spread function (APSF) is generated using binary optics, which produces a large-scale dark area in the focal region that can hide any object located within it. This result is achieved by generating two identical PSFs of opposite signs, one consisting of positive electromagnetic waves from the zero-phase region of the binary optical element and the other consisting of negative electromagnetic waves from the pi-phase region of the binary optical element.

Creation of an anti-imaging system using binary optics

PubMed Central

Wang, Haifeng; Lin, Jian; Zhang, Dawei; Wang, Yang; Gu, Min; Urbach, H. P.; Gan, Fuxi; Zhuang, Songlin

2016-01-01

We present a concealing method in which an anti-point spread function (APSF) is generated using binary optics, which produces a large-scale dark area in the focal region that can hide any object located within it. This result is achieved by generating two identical PSFs of opposite signs, one consisting of positive electromagnetic waves from the zero-phase region of the binary optical element and the other consisting of negative electromagnetic waves from the pi-phase region of the binary optical element. PMID:27620068

Spectral types of four binaries based on photometric observations

NASA Astrophysics Data System (ADS)

Shimanskii, V. V.; Bikmaev, I. F.; Borisov, N. V.; Vlasyuk, V. V.; Galeev, A. I.; Sakhibullin, N. A.; Spiridonova, O. I.

2008-09-01

We present results of photometric and spectroscopic observations of four close binaries with subdwarf B components: PG 0918+029, PG 1000+408, PG 1116+301, PG 0001+275. We discovered that PG 1000+408 is a close binary, with the most probable orbital period being P orb = 1.041145 day. Based on a comparison of the observed light curves at selected orbital phases and theoretical predictions for their variations, all the systems are classified as doubly degenerate binaries with low-luminosity white-dwarf secondaries.

Radio crickets: chirping jets from black hole binaries entering their gravitational wave inspiral

NASA Astrophysics Data System (ADS)

Kulkarni, Girish; Loeb, Abraham

2016-03-01

We study a novel electromagnetic signature of supermassive black hole (BH) binaries whose inspiral starts being dominated by gravitational wave (GW) emission. Recent simulations suggest that the binary's member BHs can continue to accrete gas from the circumbinary accretion disc in this phase of the binary's evolution, all the way until coalescence. If one of the binary members produces a radio jet as a result of accretion, the jet precesses along a biconical surface due to the binary's orbital motion. When the binary enters the GW phase of its evolution, the opening angle widens, the jet exhibits milliarcsecond-scale wiggles, and the conical surface of jet precession is twisted due to apparent superluminal motion. The rapidly increasing orbital velocity of the binary gives the jet an appearance of a `chirp'. This helical chirping morphology of the jet can be used to infer the binary parameters. For binaries with mass 107-1010 M⊙ at redshifts z < 0.5, monitoring these features in current and archival data will place a lower limit on sources that could be detected by Evolved Laser Interferometer Space Antenna and Pulsar Timing Arrays. In the future, microarcsecond interferometry with the Square Kilometre Array will increase the potential usefulness of this technique.

Mobile phone use during driving: Effects on speed and effectiveness of driver compensatory behaviour.

PubMed

Choudhary, Pushpa; Velaga, Nagendra R

2017-09-01

This study analysed and modelled the effects of conversation and texting (each with two difficulty levels) on driving performance of Indian drivers in terms of their mean speed and accident avoiding abilities; and further explored the relationship between speed reduction strategy of the drivers and their corresponding accident frequency. 100 drivers of three different age groups (young, mid-age and old-age) participated in the simulator study. Two sudden events of Indian context: unexpected crossing of pedestrians and joining of parked vehicles from road side, were simulated for estimating the accident probabilities. Generalized linear mixed models approach was used for developing linear regression models for mean speed and binary logistic regression models for accident probability. The results of the models showed that the drivers significantly compensated the increased workload by reducing their mean speed by 2.62m/s and 5.29m/s in the presence of conversation and texting tasks respectively. The logistic models for accident probabilities showed that the accident probabilities increased by 3 and 4 times respectively when the drivers were conversing or texting on a phone during driving. Further, the relationship between the speed reduction patterns and their corresponding accident frequencies showed that all the drivers compensated differently; but, among all the drivers, only few drivers, who compensated by reducing the speed by 30% or more, were able to fully offset the increased accident risk associated with the phone use. Copyright © 2017 Elsevier Ltd. All rights reserved.

Serological Survey and Associated Risk Factors of Visceral Leish-maniasis in Qom Province, Central Iran

PubMed Central

RAKHSHANPOUR, Arash; MOHEBALI, Mehdi; AKHONDI, Behnaz; RAHIMI, Mohammad Taghi; ROKNI, Mohammad Bagher

2014-01-01

Abstract Background Visceral leishmaniasis (VL) or kala-azar is considered as a parasitic disease caused by the species of Leishmania donovani complex which is intracellular parasites. This systemic disease is endemic in some parts of provinc-es of Iran. The aim of this study was to determine the seroprevalence of VL in Qom Province, central Iran using di-rect agglutination test (DAT). Methods Overall, 1564 serum samples (800 males and 764 females) were collected from selected subjects by random-ized cluster sampling in 2011-2012. Sera were tested and analyzed by DAT. Before sampling; a questionnaire was filled out for each case. Data were analyzed using Chi-square test and multivariate logistic regression for risk factors analysis. Results Of 1564 individuals, 53 cases (3.38%) showed Leishmania specific antibodies as follows: with 1:400 titer 16 cases (1.02%), with 1:800 titer 20 cases (1.27%), with 1:1600 titer 16 cases (1.02%) whereas only one subject (0.06%) showed titers of ≥ 1:3200. There was no significant association between VL seropositivity and gender, age group and occupation. Binary logistic regression showed that rural areas was 0.44 times at higher risk of infection than urban areas (OR= 0.44; %95 CI= 0.25- 0.78). Conclusion Although the seroprevalence of VL is relatively low in Qom Province, yet due to the importance of the disease, the surveillance system should be monitored by health authorities. PMID:26060679

Recognition by Rats of Binary Taste Solutions and Their Components.

PubMed

Katagawa, Yoshihisa; Yasuo, Toshiaki; Suwabe, Takeshi; Yamamura, Tomoki; Gen, Keika; Sako, Noritaka

2016-09-13

This behavioral study investigated how rats conditioned to binary mixtures of preferred and aversive taste stimuli, respectively, responded to the individual components in a conditioned taste aversion (CTA) paradigm. The preference of stimuli was determined based on the initial results of 2 bottle preference test. The preferred stimuli included 5mM sodium saccharin (Sacc), 0.03M NaCl (Na), 0.1M Na, 5mM Sacc + 0.03M Na, and 5mM Sacc + 0.2mM quinine hydrochloride (Q), whereas the aversive stimuli tested were 1.0M Na, 0.2mM Q, 0.3mM Q, 5mM Sacc + 1.0M Na, and 5mM Sacc + 0.3mM Q. In CTA tests where LiCl was the unconditioned stimulus, the number of licks to the preferred binary mixtures and to all tested preferred components were significantly less than in control rats. No significant difference resulted between the number of licks to the aversive binary mixtures or to all tested aversive components. However, when rats pre-exposed to the aversive components contained of the aversive binary mixtures were conditioned to these mixtures, the number of licks to all the tested stimuli was significantly less than in controls. Rats conditioned to components of the aversive binary mixtures generalized to the binary mixtures containing those components. These results suggest that rats recognize and remember preferred and aversive taste mixtures as well as the preferred and aversive components of the binary mixtures, and that pre-exposure before CTA is an available method to study the recognition of aversive taste stimuli. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

On the resonant detonation of sub-Chandrasekhar mass white dwarfs during binary inspiral

NASA Astrophysics Data System (ADS)

McKernan, B.; Ford, K. E. S.

2016-12-01

White dwarfs (WDs) are believed to detonate via explosive Carbon-fusion in a Type Ia supernova (SN) when their temperature and/or density reach the point where Carbon is ignited in a runaway reaction. Observations of the Type Ia SN rate imply that all WD binaries that merge through the emission of gravitational radiation within a Hubble time should result in SNe, regardless of total mass. Here we investigate the conditions under which a single WD in a binary system might extract energy from its orbit, depositing enough energy into a resonant mode such that it detonates before merger. We show that, ignoring non-linear effects in a WD binary in tidal lock at small binary separations, the sustained tidal forcing of a low-order quadrupolar g mode or a harmonic of a low-order quadrupolar p mode could, in principle, drive the average temperature of Carbon nuclei in the mode over the runaway fusion threshold. If growing mode energy is thermalized at a core/atmosphere boundary, rapid Helium burning and inwards-travelling p-waves may result in core detonation. Thermalization at a boundary in the core can also result in detonation. If energy can be efficiently transferred from the orbit to modes as the WD binary passes through resonances, the WD merger time-scale will be shortened by Myr-Gyr compared to expected time-scales from gravitational wave (GW)-emission alone and GW detectors will observe deviations from predicted chirp profiles in resolved WD binaries. Future work in this area should focus on whether tidal locking in WD binaries is naturally driven towards low-order mode frequencies.

Synthetic Survey of the Kepler Field

NASA Astrophysics Data System (ADS)

Wells, Mark; Prša, Andrej

2018-01-01

In the era of large scale surveys, including LSST and Gaia, binary population studies will flourish due to the large influx of data. In addition to probing binary populations as a function of galactic latitude, under-sampled groups such as low mass binaries will be observed at an unprecedented rate. To prepare for these missions, binary population simulations need to be carried out at high fidelity. These simulations will enable the creation of simulated data and, through comparison with real data, will allow the underlying binary parameter distributions to be explored. In order for the simulations to be considered robust, they should reproduce observed distributions accurately. To this end we have developed a simulator which takes input models and creates a synthetic population of eclipsing binaries. Starting from a galactic single star model, implemented using Galaxia, a code by Sharma et al. (2011), and applying observed multiplicity, mass-ratio, period, and eccentricity distributions, as reported by Raghavan et al. (2010), Duchêne & Kraus (2013), and Moe & Di Stefano (2017), we are able to generate synthetic binary surveys that correspond to any survey cadences. In order to calibrate our input models we compare the results of our synthesized eclipsing binary survey to the Kepler Eclipsing Binary catalog.

A New Orbit for the Eclipsing Binary V577 Oph

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jeffery, Elizabeth J.; Barnes, Thomas G. III; Montemayor, Thomas J.

Pulsating stars in eclipsing binary systems are unique objects for providing constraints on stellar models. To fully leverage the information available from the binary system, full orbital radial velocity curves must be obtained. We report 23 radial velocities for components of the eclipsing binary V577 Oph, whose primary star is a δ Sct variable. The velocities cover a nearly complete orbit and a time base of 20 years. We computed orbital elements for the binary and compared them to the ephemeris computed by Creevey et al. The comparison shows marginally different results. In particular, a change in the systemic velocitymore » by −2 km s{sup −1} is suggested by our results. We compare this systemic velocity difference to that expected due to reflex motion of the binary in response to the third body in the system. The systemic velocity difference is consistent with reflex motion, given our mass determination for the eclipsing binary and the orbital parameters determined by Volkov and Volkova for the three-body orbit. We see no evidence for the third body in our spectra, but we do see strong interstellar Na D lines that are consistent in strength with the direction and expected distance of V577 Oph.« less

Constraining Binary Asteroid Mass Distributions Based On Mutual Motion

NASA Astrophysics Data System (ADS)

Davis, Alex B.; Scheeres, Daniel J.

2017-06-01

The mutual gravitational potential and torques of binary asteroid systems results in a complex coupling of attitude and orbital motion based on the mass distribution of each body. For a doubly-synchronous binary system observations of the mutual motion can be leveraged to identify and measure the unique mass distributions of each body. By implementing arbitrary shape and order computation of the full two-body problem (F2BP) equilibria we study the influence of asteroid asymmetries on separation and orientation of a doubly-synchronous system. Additionally, simulations of binary systems perturbed from doubly-synchronous behavior are studied to understand the effects of mass distribution perturbations on precession and nutation rates such that unique behaviors can be isolated and used to measure asteroid mass distributions. We apply our investigation to the Trojan binary asteroid system 617 Patroclus and Menoetius (1906 VY), which will be the final flyby target of the recently announced LUCY Discovery mission in March 2033. This binary asteroid system is of particular interest due to the results of a recent stellar occultation study (DPS 46, id.506.09) that suggests the system to be doubly-synchronous and consisting of two-similarly sized oblate ellipsoids, in addition to suggesting the presence mass asymmetries resulting from an impact crater on the southern limb of Menoetius.

Terrestrial Planet Formation in Binary Star Systems

NASA Technical Reports Server (NTRS)

Lissauer, Jack J.; Quintana, Elisa V.; Chambers, John; Duncan, Martin J.; Adams, Fred

2003-01-01

Most stars reside in multiple star systems; however, virtually all models of planetary growth have assumed an isolated single star. Numerical simulations of the collapse of molecular cloud cores to form binary stars suggest that disks will form within such systems. Observations indirectly suggest disk material around one or both components within young binary star systems. If planets form at the right places within such circumstellar disks, they can remain in stable orbits within the binary star systems for eons. We are simulating the late stages of growth of terrestrial planets within binary star systems, using a new, ultrafast, symplectic integrator that we have developed for this purpose. We show that the late stages of terrestrial planet formation can indeed take place in a wide variety of binary systems and we have begun to delineate the range of parameter space for which this statement is true. Results of our initial simulations of planetary growth around each star in the alpha Centauri system and other 'wide' binary systems, as well as around both stars in very close binary systems, will be presented.

Binary Star Fractions from the LAMOST DR4

NASA Astrophysics Data System (ADS)

Tian, Zhi-Jia; Liu, Xiao-Wei; Yuan, Hai-Bo; Chen, Bing-Qiu; Xiang, Mao-Sheng; Huang, Yang; Wang, Chun; Zhang, Hua-Wei; Guo, Jin-Cheng; Ren, Juan-Juan; Huo, Zhi-Ying; Yang, Yong; Zhang, Meng; Bi, Shao-Lan; Yang, Wu-Ming; Liu, Kang; Zhang, Xian-Fei; Li, Tan-Da; Wu, Ya-Qian; Zhang, Jing-Hua

2018-05-01

Stellar systems composed of single, double, triple or higher-order systems are rightfully regarded as the fundamental building blocks of the Milky Way. Binary stars play an important role in formation and evolution of the Galaxy. Through comparing the radial velocity variations from multi-epoch observations, we analyze the binary fraction of dwarf stars observed with LAMOST. Effects of different model assumptions, such as orbital period distributions on the estimate of binary fractions, are investigated. The results based on log-normal distribution of orbital periods reproduce the previous complete analyses better than the power-law distribution. We find that the binary fraction increases with T eff and decreases with [Fe/H]. We first investigate the relation between α-elements and binary fraction in such a large sample as provided by LAMOST. The old stars with high [α/Fe] dominate with a higher binary fraction than young stars with low [α/Fe]. At the same mass, earlier forming stars possess a higher binary fraction than newly forming ones, which may be related with evolution of the Galaxy.

Embedding intensity image into a binary hologram with strong noise resistant capability

NASA Astrophysics Data System (ADS)

Zhuang, Zhaoyong; Jiao, Shuming; Zou, Wenbin; Li, Xia

2017-11-01

A digital hologram can be employed as a host image for image watermarking applications to protect information security. Past research demonstrates that a gray level intensity image can be embedded into a binary Fresnel hologram by error diffusion method or bit truncation coding method. However, the fidelity of the retrieved watermark image from binary hologram is generally not satisfactory, especially when the binary hologram is contaminated with noise. To address this problem, we propose a JPEG-BCH encoding method in this paper. First, we employ the JPEG standard to compress the intensity image into a binary bit stream. Next, we encode the binary bit stream with BCH code to obtain error correction capability. Finally, the JPEG-BCH code is embedded into the binary hologram. By this way, the intensity image can be retrieved with high fidelity by a BCH-JPEG decoder even if the binary hologram suffers from serious noise contamination. Numerical simulation results show that the image quality of retrieved intensity image with our proposed method is superior to the state-of-the-art work reported.

Computer vision syndrome among computer office workers in a developing country: an evaluation of prevalence and risk factors.

PubMed

Ranasinghe, P; Wathurapatha, W S; Perera, Y S; Lamabadusuriya, D A; Kulatunga, S; Jayawardana, N; Katulanda, P

2016-03-09

Computer vision syndrome (CVS) is a group of visual symptoms experienced in relation to the use of computers. Nearly 60 million people suffer from CVS globally, resulting in reduced productivity at work and reduced quality of life of the computer worker. The present study aims to describe the prevalence of CVS and its associated factors among a nationally-representative sample of Sri Lankan computer workers. Two thousand five hundred computer office workers were invited for the study from all nine provinces of Sri Lanka between May and December 2009. A self-administered questionnaire was used to collect socio-demographic data, symptoms of CVS and its associated factors. A binary logistic regression analysis was performed in all patients with 'presence of CVS' as the dichotomous dependent variable and age, gender, duration of occupation, daily computer usage, pre-existing eye disease, not using a visual display terminal (VDT) filter, adjusting brightness of screen, use of contact lenses, angle of gaze and ergonomic practices knowledge as the continuous/dichotomous independent variables. A similar binary logistic regression analysis was performed in all patients with 'severity of CVS' as the dichotomous dependent variable and other continuous/dichotomous independent variables. Sample size was 2210 (response rate-88.4%). Mean age was 30.8 ± 8.1 years and 50.8% of the sample were males. The 1-year prevalence of CVS in the study population was 67.4%. Female gender (OR: 1.28), duration of occupation (OR: 1.07), daily computer usage (1.10), pre-existing eye disease (OR: 4.49), not using a VDT filter (OR: 1.02), use of contact lenses (OR: 3.21) and ergonomics practices knowledge (OR: 1.24) all were associated with significantly presence of CVS. The duration of occupation (OR: 1.04) and presence of pre-existing eye disease (OR: 1.54) were significantly associated with the presence of 'severe CVS'. Sri Lankan computer workers had a high prevalence of CVS. Female gender, longer duration of occupation, higher daily computer usage, pre-existing eye disease, not using a VDT filter, use of contact lenses and higher ergonomics practices knowledge all were associated with significantly with the presence of CVS. The factors associated with the severity of CVS were the duration of occupation and presence of pre-existing eye disease.

Association of Ghrelin Gene Polymorphisms and Serum Ghrelin Levels with the Risk of Hepatitis B Virus-Related Liver Diseases in a Chinese Population

PubMed Central

Rong, Chengzhi; Qin, Xue; Li, Shan

2015-01-01

Background The functions of ghrelin (GHRL) include anti-inflammatory effects, reduction of the fibrogenic response, protection of liver tissue, and regulation of cell proliferation. Genetic variations in the GHRL gene may play an important role in the development of chronic hepatitis B (CHB), liver cirrhosis (LC) and hepatocellular carcinoma (HCC). Therefore, we investigated whether GHRL gene polymorphisms and its serum levels are associated with hepatitis B virus (HBV)-related diseases risk in a Chinese population. Methods 176 patients with CHB, 106 patients with HBV-related LC, 151 patients with HBV-related HCC, and 167 healthy controls were recruited in the study. Genotyping of GHRL rs26311, rs27647, rs696217, and rs34911341 polymorphisms were determined with the polymerase chain reaction–restriction fragment length polymorphism (PCR–RFLP) and DNA sequencing. The serum GHRL concentrations were determined using enzyme-linked immunosorbent assay (ELISA). Results Binary logistic regression analyses adjusting for gender and age revealed that a significant increased risk of LC was found in the GHRL rs26311 GC genotype and combined GC+CC genotypes when compared with the GG genotype (GC vs. GG: OR = 1.671, 95% CI = 1.013–2.757, P = 0.044; GC+CC vs. GG: OR = 1.674, 95% CI = 1.040–2.696, P = 0.034). In subgroup analysis by gender, binary logistic regression analyses adjusting for age showed that the GHRL rs26311 C allele and combined GC+CC genotypes were associated with a significantly increased risk to LC in males (C vs. G OR = 1.416, 95% CI = 1.017–1.972, P = 0.040; GC+CC vs. GG: OR = 1.729, 95% CI = 1.019–2.933, P = 0.042). In addition, we found significant decreased serum GHRL levels in LC patients compared with the healthy controls. However, there was no significant association of the GHRL rs26311 polymorphism with serum GHRL levels in LC patients. Conclusions These observations suggest that the GHRL rs26311 polymorphism is associated with an increased risk to HBV-related LC, especially in men. We also found an inverse association of serum GHRL levels with LC. PMID:26599409

Low-grade Glioma Surgery in Intraoperative Magnetic Resonance Imaging: Results of a Multicenter Retrospective Assessment of the German Study Group for Intraoperative Magnetic Resonance Imaging.

PubMed

Coburger, Jan; Merkel, Andreas; Scherer, Moritz; Schwartz, Felix; Gessler, Florian; Roder, Constantin; Pala, Andrej; König, Ralph; Bullinger, Lars; Nagel, Gabriele; Jungk, Christine; Bisdas, Sotirios; Nabavi, Arya; Ganslandt, Oliver; Seifert, Volker; Tatagiba, Marcos; Senft, Christian; Mehdorn, Maximilian; Unterberg, Andreas W; Rössler, Karl; Wirtz, Christian Rainer

2016-06-01

The ideal treatment strategy for low-grade gliomas (LGGs) is a controversial topic. Additionally, only smaller single-center series dealing with the concept of intraoperative magnetic resonance imaging (iMRI) have been published. To investigate determinants for patient outcome and progression-free-survival (PFS) after iMRI-guided surgery for LGGs in a multicenter retrospective study initiated by the German Study Group for Intraoperative Magnetic Resonance Imaging. A retrospective consecutive assessment of patients treated for LGGs (World Health Organization grade II) with iMRI-guided resection at 6 neurosurgical centers was performed. Eloquent location, extent of resection, first-line adjuvant treatment, neurophysiological monitoring, awake brain surgery, intraoperative ultrasound, and field-strength of iMRI were analyzed, as well as progression-free survival (PFS), new permanent neurological deficits, and complications. Multivariate binary logistic and Cox regression models were calculated to evaluate determinants of PFS, gross total resection (GTR), and adjuvant treatment. A total of 288 patients met the inclusion criteria. On multivariate analysis, GTR significantly increased PFS (hazard ratio, 0.44; P < .01), whereas "failed" GTR did not differ significantly from intended subtotal-resection. Combined radiochemotherapy as adjuvant therapy was a negative prognostic factor (hazard ratio: 2.84, P < .01). Field strength of iMRI was not associated with PFS. In the binary logistic regression model, use of high-field iMRI (odds ratio: 0.51, P < .01) was positively and eloquent location (odds ratio: 1.99, P < .01) was negatively associated with GTR. GTR was not associated with increased rates of new permanent neurological deficits. GTR was an independent positive prognostic factor for PFS in LGG surgery. Patients with accidentally left tumor remnants showed a similar prognosis compared with patients harboring only partially resectable tumors. Use of high-field iMRI was significantly associated with GTR. However, the field strength of iMRI did not affect PFS. EoR, extent of resectionFLAIR, fluid-attenuated inversion recoveryGTR, gross total resectionIDH1, isocitrate dehydrogenase 1iMRI, intraoperative magnetic resonance imagingLGG, low-grade gliomaMGMT, methylguanine-deoxyribonucleic acid methyltransferasenPND, new permanent neurological deficitOS, overall survivalPFS, progression-free survivalSTR, subtotal resectionWHO, World Health Organization.

Exposure and impact of a mass media campaign targeting sexual health amongst Scottish men who have sex with men: an outcome evaluation

PubMed Central

2013-01-01

Background This paper explores the exposure and impact of a Scottish mass media campaign: Make Your Position Clear. It ran from October 2009 to July 2010, targeted gay men and other men who have sex with men (MSM), and had two key aims: to promote regular sexual health and HIV testing every 6 months, and to promote the use of appropriate condoms and water-based lubricant with each episode of anal intercourse. Methods A cross-sectional survey (anonymous and self-report) was conducted 10 months after the campaign was launched (July 2010). Men were recruited from commercial venues. Outcome measures included use of lubricant, testing for sexually transmitted infections and HIV, and intentions to seek HIV testing within the following six months. Linear-by-linear chi-square analysis and binary logistic regressions were conducted to explore the associations between the outcome measures and campaign exposure. Results The total sample was 822 men (62.6% response rate). Men self-identifying as HIV positive were excluded from the analysis (n = 38). Binary logistic analysis indicated that those with mid or high campaign exposure were more likely to have been tested for HIV in the previous six months when adjusted for age, area of residence and use of the “gay scene” (AOR = 1.96, 95% CI = 1.26 to 3.06, p = .003), but were not more likely to be tested for STIs (AOR = 1.37, 95% CI = 0.88 to 2.16, p = .167). When adjusted for previous HIV testing, those with mid or high campaign exposure were not more likely to indicate intention to be tested for HIV in the following six months (AOR = 1.30, 95% CI = 0.73 to 2.32, p = .367). Those with no campaign exposure were less likely than those with low exposure to have used appropriate lubricant with anal sex partners in the previous year (AOR = 0.42, 95% CI = 0.23 to 0.77, p = .005). Conclusions The campaign had demonstrable reach. The analysis showed partial support for the role of mass media campaigns in improving sexual health outcomes. This suggests that a role for mass media campaigns remains within combination HIV prevention. PMID:23923977

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

PubMed

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

2005-09-01

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

The Großschwabhausen binary survey

NASA Astrophysics Data System (ADS)

Mugrauer, M.; Buder, S.; Reum, F.; Birth, A.

2017-01-01

Background: Since 2009, the Großschwabhausen binary survey is being carried out at the University Observatory Jena. This new imaging survey uses available time slots during photometric monitoring campaigns, caused by nonphotometric weather conditions, which often exhibit good atmospheric seeing. The goal of the project is to obtain current relative astrometric measurements of the binary systems that are listed in the Washington Visual Double Star Catalog. Materials and Methods: For the survey we use the Refraktor-Teleskop-Kamera at the University Observatory Jena to take imaging data of selected visual binary systems. Results: In this paper, we characterize the target sample of the survey, describe the imaging observations and the astrometric measurements including the astrometric calibration, and present the relative astrometric measures of 352 binaries that could be obtained during the course of the Großschwabhausen binary survey, so far.

Probing Intermolecular Interactions in Binary Liquid Mixtures Using Femtosecond Laser-Induced Self-Defocusing.

PubMed

Maurya, Sandeep Kumar; Das, Dhiman; Goswami, Debabrata

2016-06-13

Photo-thermal behavior of binary liquid mixtures has been studied by high repetition rate (HRR) Z-scan technique with femtosecond laser pulses. Changes in the peak-valley difference in transmittance (ΔT P-V ) for closed aperture Z-scan experiments are indicative of thermal effects induced by HRR femtosecond laser pulses. We show such indicative results can have a far-reaching impact on molecular properties and intermolecular interactions in binary liquid mixtures. Spectroscopic parameters derived from this experimental technique show that the combined effect of physical and molecular properties of the constituent binary liquids can be related to the components of the binary liquid. © The Author(s) 2016.

Constraining Accreting Binary Populations in Normal Galaxies

NASA Astrophysics Data System (ADS)

Lehmer, Bret; Hornschemeier, A.; Basu-Zych, A.; Fragos, T.; Jenkins, L.; Kalogera, V.; Ptak, A.; Tzanavaris, P.; Zezas, A.

2011-01-01

X-ray emission from accreting binary systems (X-ray binaries) uniquely probe the binary phase of stellar evolution and the formation of compact objects such as neutron stars and black holes. A detailed understanding of X-ray binary systems is needed to provide physical insight into the formation and evolution of the stars involved, as well as the demographics of interesting binary remnants, such as millisecond pulsars and gravitational wave sources. Our program makes wide use of Chandra observations and complementary multiwavelength data sets (through, e.g., the Spitzer Infrared Nearby Galaxies Survey [SINGS] and the Great Observatories Origins Deep Survey [GOODS]), as well as super-computing facilities, to provide: (1) improved calibrations for correlations between X-ray binary emission and physical properties (e.g., star-formation rate and stellar mass) for galaxies in the local Universe; (2) new physical constraints on accreting binary processes (e.g., common-envelope phase and mass transfer) through the fitting of X-ray binary synthesis models to observed local galaxy X-ray binary luminosity functions; (3) observational and model constraints on the X-ray evolution of normal galaxies over the last 90% of cosmic history (since z 4) from the Chandra Deep Field surveys and accreting binary synthesis models; and (4) predictions for deeper observations from forthcoming generations of X-ray telesopes (e.g., IXO, WFXT, and Gen-X) to provide a science driver for these missions. In this talk, we highlight the details of our program and discuss recent results.

Searching Ultra-compact Pulsar Binaries with Abnormal Timing Behavior

NASA Astrophysics Data System (ADS)

Gong, B. P.; Li, Y. P.; Yuan, J. P.; Tian, J.; Zhang, Y. Y.; Li, D.; Jiang, B.; Li, X. D.; Wang, H. G.; Zou, Y. C.; Shao, L. J.

2018-03-01

Ultra-compact pulsar binaries are both ideal sources of gravitational radiation for gravitational wave detectors and laboratories for fundamental physics. However, the shortest orbital period of all radio pulsar binaries is currently 1.6 hr. The absence of pulsar binaries with a shorter orbital period is most likely due to technique limit. This paper points out that a tidal effect occurring on pulsar binaries with a short orbital period can perturb the orbital elements and result in a significant change in orbital modulation, which dramatically reduces the sensitivity of the acceleration searching that is widely used. Here a new search is proposed. The abnormal timing residual exhibited in a single pulse observation is simulated by a tidal effect occurring on an ultra-compact binary. The reproduction of the main features represented by the sharp peaks displayed in the abnormal timing behavior suggests that pulsars like PSR B0919+06 could be a candidate for an ultra-compact binary of an orbital period of ∼10 minutes and a companion star of a white dwarf star. The binary nature of such a candidate is further tested by (1) comparing the predicted long-term binary effect with decades of timing noise observed and (2) observing the optical counterpart of the expected companion star. Test (1) likely supports our model, while more observations are needed in test (2). Some interesting ultra-compact binaries could be found in the near future by applying such a new approach to other binary candidates.

ILLUMINATING BLACK HOLE BINARY FORMATION CHANNELS WITH SPINS IN ADVANCED LIGO

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodriguez, Carl L.; Zevin, Michael; Pankow, Chris

The recent detections of the binary black hole mergers GW150914 and GW151226 have inaugurated the field of gravitational-wave astronomy. For the two main formation channels that have been proposed for these sources, isolated binary evolution in galactic fields and dynamical formation in dense star clusters, the predicted masses and merger rates overlap significantly, complicating any astrophysical claims that rely on measured masses alone. Here, we examine the distribution of spin–orbit misalignments expected for binaries from the field and from dense star clusters. Under standard assumptions for black hole natal kicks, we find that black hole binaries similar to GW150914 couldmore » be formed with significant spin–orbit misalignment only through dynamical processes. In particular, these heavy-black hole binaries can only form with a significant spin–orbit anti -alignment in the dynamical channel. Our results suggest that future detections of merging black hole binaries with measurable spins will allow us to identify the main formation channel for these systems.« less

Dual-sensitivity profilometry with defocused projection of binary fringes.

PubMed

Garnica, G; Padilla, M; Servin, M

2017-10-01

A dual-sensitivity profilometry technique based on defocused projection of binary fringes is presented. Here, two sets of fringe patterns with a sinusoidal profile are produced by applying the same analog low-pass filter (projector defocusing) to binary fringes with a high- and low-frequency spatial carrier. The high-frequency fringes have a binary square-wave profile, while the low-frequency binary fringes are produced with error-diffusion dithering. The binary nature of the binary fringes removes the need for calibration of the projector's nonlinear gamma. Working with high-frequency carrier fringes, we obtain a high-quality wrapped phase. On the other hand, working with low-frequency carrier fringes we found a lower-quality, nonwrapped phase map. The nonwrapped estimation is used as stepping stone for dual-sensitivity temporal phase unwrapping, extending the applicability of the technique to discontinuous (piecewise continuous) surfaces. We are proposing a single defocusing level for faster high- and low-frequency fringe data acquisition. The proposed technique is validated with experimental results.

Searching for Unresolved Binary Brown Dwarfs

NASA Astrophysics Data System (ADS)

Albretsen, Jacob; Stephens, Denise

2007-10-01

There are currently L and T brown dwarfs (BDs) with errors in their classification of +/- 1 to 2 spectra types. Metallicity and gravitational differences have accounted for some of these discrepancies, and recent studies have shown unresolved binary BDs may offer some explanation as well. However limitations in technology and resources often make it difficult to clearly resolve an object that may be binary in nature. Stephens and Noll (2006) identified statistically strong binary source candidates from Hubble Space Telescope (HST) images of Trans-Neptunian Objects (TNOs) that were apparently unresolved using model point-spread functions for single and binary sources. The HST archive contains numerous observations of BDs using the Near Infrared Camera and Multi-Object Spectrometer (NICMOS) that have never been rigorously analyzed for binary properties. Using methods developed by Stephens and Noll (2006), BD observations from the HST data archive are being analyzed for possible unresolved binaries. Preliminary results will be presented. This technique will identify potential candidates for future observations to determine orbital information.

Home advantage in high-level volleyball varies according to set number.

PubMed

Marcelino, Rui; Mesquita, Isabel; Palao Andrés, José Manuel; Sampaio, Jaime

2009-01-01

The aim of the present study was to identify the probability of winning each Volleyball set according to game location (home, away). Archival data was obtained from 275 sets in the 2005 Men's Senior World League and 65,949 actions were analysed. Set result (win, loss), game location (home, away), set number (first, second, third, fourth and fifth) and performance indicators (serve, reception, set, attack, dig and block) were the variables considered in this study. In a first moment, performance indicators were used in a logistic model of set result, by binary logistic regression analysis. After finding the adjusted logistic model, the log-odds of winning the set were analysed according to game location and set number. The results showed that winning a set is significantly related to performance indicators (Chisquare(18)=660.97, p<0.01). Analyses of log-odds of winning a set demonstrate that home teams always have more probability of winning the game than away teams, regardless of the set number. Home teams have more advantage at the beginning of the game (first set) and in the two last sets of the game (fourth and fifth sets), probably due to facilities familiarity and crowd effects. Different game actions explain these advantages and showed that to win the first set is more important to take risk, through a better performance in the attack and block, and to win the final set is important to manage the risk through a better performance on the reception. These results may suggest intra-game variation in home advantage and can be most useful to better prepare and direct the competition. Key pointsHome teams always have more probability of winning the game than away teams.Home teams have higher performance in reception, set and attack in the total of the sets.The advantage of home teams is more pronounced at the beginning of the game (first set) and in two last sets of the game (fourth and fifth sets) suggesting intra-game variation in home advantage.Analysis by sets showed that home teams have a better performance in the attack and block in the first set and in the reception in the third and fifth sets.

[Overload in the informal caregivers of patients with multiple comorbidities in an urban area].

PubMed

Álvarez-Tello, Margarita; Casado-Mejía, Rosa; Ortega-Calvo, Manuel; Ruiz-Arias, Esperanza

2012-01-01

The aim of the study was, to determine the profile of the family caregiver of patients with multiple pathologies, identify factors associated with overload, and construct predictive models using items from the Caregiver Strain Index (CSI). A cross-sectional study of caregivers of patients with multiple comorbidities who attended an urban health centre. Data were collected from health records and questionnaires (Barthel index, Pfeiffer index, and CSI). Statistical analysis was performed using measures of central tendency and dispersion, and by building multivariate models with binary logistic regression with the CSI items as predictors (program R version 2.14.0). The sample included 67 caregivers, with a mean age of 64.69 years (standard deviation=12.71, median 62 years), of whom 74.6% were women, 35.8% were wives, and 32.8% were daughters. The level of dependence of the patients cared for was total/severe in 77.6%, and moderate in 12% (Barthel), and 47.8% had some level of cognitive impairment (Pfeiffer). A CSI equal or greater than 7 was seen in 47.8% of caregivers, identifying life problems in more than 40% of them such as, restriction of social life, physical exertion, discomfort with change, bad behaviour, personal and family emotional changes, and sleep disturbances. Item 4 of the CSI, analysing the social restriction, was the one that showed a greater significance in the predictive multivariate model. Item 12 (economic burden) was the most significant with age in patients with cognitive impairment. Women tend to take the role of caregiver at an earlier age than men in the urban environment studied, and items from CSI showed that items 4 (social restrictions) and 12 (economic burden) have more significance in the predictive models constructed with Binary Logistic Regression. Copyright © 2012 Elsevier España, S.L. All rights reserved.

Non-specific low back pain: occupational or lifestyle consequences?

PubMed

Stričević, Jadranka; Papež, Breda Jesenšek

2015-12-01

Nursing occupation was identified as a risk occupation for the development of low back pain (LBP). The aim of our study was to find out how much occupational factors influence the development of LBP in hospital nursing personnel. Non-experimental approach with a cross-sectional survey and statistical analysis. Nine hundred questionnaires were distributed among nursing personnel, 663 were returned and 659 (73.2 %) were considered for the analysis. Univariate and multivariate statistics for LBP risk was calculated by the binary logistic regression. The χ(2), influence factor, 95 % confidence interval and P value were calculated. Multivariate binary logistic regression was calculated by the Wald method to omit insignificant variables. Not performing exercises represented the highest risk for the development of LBP (OR 2.8, 95 % CI 1.7-4.4; p < 0.001). The second and third ranked risk factors were frequent manual lifting > 10 kg (OR 2.4, 95 % CI 1.5-3.8; p < 0.001) and duration of employment ≥ 19 years (OR 2.4, 95 % CI 1.6-3.7; p < 0.001). The fourth ranked risk factor was better physical condition by frequent recreation and sports, which reduced the risk for the development of LBP (OR 0.4, 95 % CI 0.3-0.7; p = 0.001). Work with the computer ≥ 2 h per day as last significant risk factor also reduced the risk for the development of LBP (OR 0.6, 95 % CI 0.4-0.1; p = 0.049). Risk factors for LBP established in our study (exercises, duration of employment, frequent manual lifting, recreation and sports and work with the computer) are not specifically linked to the working environment of the nursing personnel. Rather than focusing on mechanical causes and direct workload in the development of non-specific LBP, the complex approach to LBP including genetics, psychosocial environment, lifestyle and quality of life is coming more to the fore.

Knowledge Attıtudes and Behavıors About Organ Donatıon Among Fırst- and Sıxth-class Medıcal Students: A Study From Turkey.

PubMed

Naçar, M; Çetinkaya, F; Baykan, Z; Elmalı, F

2015-01-01

The aim of this study is to determine the knowledge, attitude, and behaviors of Erciyes University School of Medicine students regarding organ donation. This descriptive study was conducted in 2014 on Erciyes University School of Medicine first- and sixth-grade students via questionnaire. It was to be conducted on all 490 students; in total, 464 students were enrolled-304 from first grade and 160 from sixth grade. Data were analyzed using descriptive statistics, χ(2) test, and binary logistic regression analysis. The mean age was 20.9 ± 2.8 years and it was found that 48.9% were male, 65.5% were in first grade; 50.0% of the students who participated in the study were considering donating their organs and this rate is 45.4% in the first grade and 58.8% at sixth grade. Those who donated their organs were 3.4% in the entire group and were 1.6% and 6.9% consequently in first and sixth grades. Those who are; at the sixth grade, female gender, those who feel themselves responsible for the donation of society, who think organ donation is appropriate in terms of religion and conversations within family about organ donations significantly want organ donation more statistically. However, grade and gender had no effect on wishing donating organs according to binary logistic regression analysis. The rate of feeling themselves responsible from the donation in society was 73.9% and finding organ donation appropriate in terms of religion was 75.6% and there wasn't significant difference between first and sixth grades. Although there are increases in many variables about this issue at sixth grade, students are unable to gain sufficient attitude and behavior about organ donation. Training can be planned during medical educations in terms of gaining attitudes and behaviors about the issue. Copyright © 2015 Elsevier Inc. All rights reserved.

Low uric acid level increases the risk of infectious mononucleosis and this effect is more pronounced in women

PubMed Central

Zhang, Li; Zhou, Pingping; Meng, Zhaowei; Gong, Lu; Pang, Chongjie; Li, Xue; Jia, Qiang; Tan, Jian; Liu, Na; Hu, Tianpeng; Zhang, Qing; Jia, Qiyu; Song, Kun

2017-01-01

Infectious mononucleosis (IM) due to Epstein-Barr virus infection is common. Uric acid (UA) is an important endogenous antioxidant. To the best of our knowledge, the association between UA and IM has not been comprehensively investigated to date. The aim of the present study was to investigate this association in Chinese patients. A total of 95 patients (47 men and 48 women) with IM were recruited, along with 95 healthy controls. Clinical data were classified by patient sex. Receiver operating characteristic (ROC) curve analysis was adopted to determine the cut-off values of UA for IM diagnosis and prediction. Crude and adjusted odds ratios (ORs) of UA for IM were analyzed by binary logistic regression. The UA levels were significantly lower in IM patients compared with those in controls. In addition, UA levels in men were significantly higher compared with those in women. The ROC curve demonstrated good diagnostic and predictive values of UA for IM in both sexes. The UA cut-off values were 326.00 and 243.50 µmol/l for diagnosing IM in men and women, respectively, with a diagnostic accuracy of 76.596 and 80.208%, respectively. Binary logistic regression analysis revealed a significant risk of IM in the low UA quartiles in both sexes. Following adjustments, the ORs even increased. Women with low UA levels appeared to be more susceptible to IM. For example, the crude ORs in quartile 1 were 24.000 and 52.500 for men and women, respectively, and the respective adjusted ORs were 31.437 and 301.746 (all P<0.01). To the best of our knowledge, the present study is the first to demonstrate the inverse association between UA and IM, suggesting a progressive decrease of antioxidant reserve in IM. Moreover, low UA was suggestive of IM, particularly in women. PMID:29285370

Knowledge, attitude, and practices related to cervical cancer among adult women: A hospital-based cross-sectional study.

PubMed

Bansal, Agam B; Pakhare, Abhijit P; Kapoor, Neelkamal; Mehrotra, Ragini; Kokane, Arun Mahadeo

2015-01-01

Cervical cancer is the most common cancer among Indian women of reproductive age. Unfortunately, despite the evidence of methods for prevention, most of the women remain unscreened. The reported barriers to screening include unawareness of risk factors, symptoms and prevention; stigma and misconceptions about gynecological diseases and lack of national cervical cancer screening guidelines and policies. This study attempts to assess the knowledge, attitude, and practices related to cervical cancer and its screening among women of reproductive age (15-45 years). A facility-based cross-sectional study was done on 400 females of reproductive age who presented to out-patient-department of All India Institute of Medical Sciences Bhopal. Structured questionnaire consisting 20 knowledge items and 7-items for attitude and history of pap smear for practices were administered by one of the investigators after informed consent. Data were entered and analyzed using Epi-Info version 7. Qualitative variables were summarized as counts and percentages while quantitative variables as mean and standard deviation. Predictors of better knowledge, attitude, and practices were identified by binary logistic regression analysis. A total of 442 women were approached for interview of which 400 responded of which two-third (65.5%) had heard of cervical cancer. At least one symptom and one risk factor were known to 35.25% and 39.75% participants. Only 34.5% participants had heard, and 9.5% actually underwent screening test, however, 76.25% of the participants expressed a favorable attitude for screening. Binary logistic regression analysis revealed that education age and income were independent predictors of better knowledge. Education level influences attitude toward screening and actual practice depends on age, income, and marital status. This study shows that despite the fact that women had suboptimal level of knowledge regarding cervical cancer, their attitude is favorable for screening. However, uptake is low in actual practice. Strategic communication targeting eligible women may increase the uptake of screening.

Postoperative Delirium in Severely Burned Patients Undergoing Early Escharotomy: Incidence, Risk Factors, and Outcomes.

PubMed

Guo, Zhenggang; Liu, Jiabin; Li, Jia; Wang, Xiaoyan; Guo, Hui; Ma, Panpan; Su, Xiaojun; Li, Ping

The aim of this study is to investigate the incidence, related risk factors, and outcomes of postoperative delirium (POD) in severely burned patients undergoing early escharotomy. This study included 385 severely burned patients (injured <1 week; TBSA, 31-50% or 11-20%; American Society of Anesthesiologists physical status, II-IV) aged 18 to 65 years, who underwent early escharotomy between October 2014 and December 2015, and were selected by cluster sampling. The authors excluded patients with preoperative delirium or diagnosed dementia, depression, or cognitive dysfunction. Preoperative, perioperative, intraoperative, and postoperative information, such as demographic characteristics, vital signs, and health history were collected. The Confusion Assessment Method was used once daily for 5 days after surgery to identify POD. Stepwise binary logistic regression analysis was used to identify the risk factors for POD, t-tests, and χ tests were performed to compare the outcomes of patients with and without the condition. Fifty-six (14.55%) of the patients in the sample were diagnosed with POD. Stepwise binary logistic regression showed that the significant risk factors for POD in severely burned patients undergoing early escharotomy were advanced age (>50 years old), a history of alcohol consumption (>3/week), high American Society of Anesthesiologists classification (III or IV), time between injury and surgery (>2 days), number of previous escharotomies (>2), combined intravenous and inhalation anesthesia, no bispectral index applied, long duration surgery (>180 min), and intraoperative hypotension (mean arterial pressure < 55 mm Hg). On the basis of the different odds ratios, the authors established a weighted model. When the score of a patient's weighted odds ratios is more than 6, the incidence of POD increased significantly (P < .05). When the score of a patient's weighted odds ratios is more than 6, the incidence of POD increased significantly (P < .05). Further, POD was associated with more postoperative complications, including hepatic and renal function impairment and hypernatremia, as well as prolonged hospitalization, increased medical costs, and higher mortality.

Progressive Occlusion of Small Saccular Aneurysms Incompletely Occluded After Stent-Assisted Coil Embolization : Analysis of Related Factors and Long-Term Outcomes.

PubMed

Lim, Jeong Wook; Lee, Jeongjun; Cho, Young Dae

2017-08-08

Incompletely occluded aneurysms after coil embolization are subject to recanalization but occasionally progress to a totally occluded state. Deployed stents may actually promote thrombosis of coiled aneurysms. We evaluated outcomes of small aneurysms (<10 mm) wherein saccular filling with contrast medium was evident after stent-assisted coiling, assessing factors implicated in subsequent progressive occlusion. Between September 2012 and June 2016, a total of 463 intracranial aneurysms were treated by stent-assisted coil embolization. Of these, 132 small saccular aneurysms displayed saccular filling with contrast medium in the immediate aftermath of coiling. Progressive thrombosis was defined as complete aneurysmal occlusion at the 6‑month follow-up point. Rates of progressive occlusion and factors predisposing to this were analyzed via binary logistic regression. In 101 (76.5%) of the 132 intracranial aneurysms, complete occlusion was observed in follow-up imaging studies at 6 months. Binary logistic regression analysis indicated that progressive occlusion was linked to smaller neck diameter (odds ratio [OR] = 1.533; p = 0.003), hyperlipidemia (OR = 3.329; p = 0.036) and stent type (p = 0.031). The LVIS stent is especially susceptible to progressive thrombosis, more so than Neuroform (OR = 0.098; p = 0.008) or Enterprise (OR = 0.317; p = 0.098) stents. In 57 instances of progressive thrombosis, followed for ≥12 months (mean 25.0 ± 10.7 months), 56 (98.2%) were stable, with minor recanalization noted once (1.8%) and no major recanalization. Aneurysms associated with smaller diameter necks, hyperlipidemic states and LVIS stent deployment may be inclined to possible thrombosis, if occlusion immediately after stent-assisted coil embolization is incomplete. In such instances, excellent long-term durability is anticipated.

Chronic obstructive pulmonary disease and coronary disease: COPDCoRi, a simple and effective algorithm for predicting the risk of coronary artery disease in COPD patients.

PubMed

Cazzola, Mario; Calzetta, Luigino; Matera, Maria Gabriella; Muscoli, Saverio; Rogliani, Paola; Romeo, Francesco

2015-08-01

Chronic obstructive pulmonary disease (COPD) is often associated with cardiovascular artery disease (CAD), representing a potential and independent risk factor for cardiovascular morbidity. Therefore, the aim of this study was to identify an algorithm for predicting the risk of CAD in COPD patients. We analyzed data of patients afferent to the Cardiology ward and the Respiratory Diseases outpatient clinic of Tor Vergata University (2010-2012, 1596 records). The study population was clustered as training population (COPD patients undergoing coronary arteriography), control population (non-COPD patients undergoing coronary arteriography), test population (COPD patients whose records reported information on the coronary status). The predicting model was built via causal relationship between variables, stepwise binary logistic regression and Hosmer-Lemeshow analysis. The algorithm was validated via split-sample validation method and receiver operating characteristics (ROC) curve analysis. The diagnostic accuracy was assessed. In training population the variables gender (men/women OR: 1.7, 95%CI: 1.237-2.5, P < 0.05), dyslipidemia (OR: 1.8, 95%CI: 1.2-2.5, P < 0.01) and smoking habit (OR: 1.5, 95%CI: 1.2-1.9, P < 0.001) were significantly associated with CAD in COPD patients, whereas in control population also age and diabetes were correlated. The stepwise binary logistic regressions permitted to build a well fitting predictive model for training population but not for control population. The predictive algorithm shown a diagnostic accuracy of 81.5% (95%CI: 77.78-84.71) and an AUC of 0.81 (95%CI: 0.78-0.85) for the validation set. The proposed algorithm is effective for predicting the risk of CAD in COPD patients via a rapid, inexpensive and non-invasive approach. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparison of statistical tests for association between rare variants and binary traits.

PubMed

Bacanu, Silviu-Alin; Nelson, Matthew R; Whittaker, John C

2012-01-01

Genome-wide association studies have found thousands of common genetic variants associated with a wide variety of diseases and other complex traits. However, a large portion of the predicted genetic contribution to many traits remains unknown. One plausible explanation is that some of the missing variation is due to the effects of rare variants. Nonetheless, the statistical analysis of rare variants is challenging. A commonly used method is to contrast, within the same region (gene), the frequency of minor alleles at rare variants between cases and controls. However, this strategy is most useful under the assumption that the tested variants have similar effects. We previously proposed a method that can accommodate heterogeneous effects in the analysis of quantitative traits. Here we extend this method to include binary traits that can accommodate covariates. We use simulations for a variety of causal and covariate impact scenarios to compare the performance of the proposed method to standard logistic regression, C-alpha, SKAT, and EREC. We found that i) logistic regression methods perform well when the heterogeneity of the effects is not extreme and ii) SKAT and EREC have good performance under all tested scenarios but they can be computationally intensive. Consequently, it would be more computationally desirable to use a two-step strategy by (i) selecting promising genes by faster methods and ii) analyzing selected genes using SKAT/EREC. To select promising genes one can use (1) regression methods when effect heterogeneity is assumed to be low and the covariates explain a non-negligible part of trait variability, (2) C-alpha when heterogeneity is assumed to be large and covariates explain a small fraction of trait's variability and (3) the proposed trend and heterogeneity test when the heterogeneity is assumed to be non-trivial and the covariates explain a large fraction of trait variability.

Association of the leptin-to-adiponectin ratio with metabolic syndrome in a sub-Saharan African population.

PubMed

Ayina, Clarisse Noël A; Endomba, Francky Teddy A; Mandengue, Samuel Honoré; Noubiap, Jean Jacques N; Ngoa, Laurent Serge Etoundi; Boudou, Philippe; Gautier, Jean-François; Mbanya, Jean Claude; Sobngwi, Eugene

2017-01-01

Worldwide there is an increased prevalence of metabolic syndrome mainly due to life-style modifications, and Africans are not saved of this situation. Many markers have been studied to predict the risk of this syndrome but the most used are leptin and adiponectin. Data on these metabolic markers are scare in Africa and this study aimed to assess the association between the leptin-to-adiponectin ratio (LAR) with metabolic syndrome in a Cameroonian population. This was a cross-sectional study that included 476 adults among a general population of Cameroon. Data collected concerned the body mass index, waist circumference, systolic blood pressure, diastolic blood pressure, fasting blood glucose, plasma lipids, adiponectin, leptin, insulin and homeostasis model for assessment of insulin resistance (HOMA-IR). To assess correlations we used Spearman's analyses and association of the studied variables with metabolic syndrome were done using binary logistic regression analysis. The leptin to adiponectin ratio was significantly and positively correlated with the body mass index (r = 0.669, p < 0.0001), waist circumference (r = 0.595, p < 0.0001), triglycerides (r = 0.190, p = 0.001), insulin levels (r = 0.333, p < 0.0001) and HOMA-IR (r = 0.306, p < 0.0001). Binary logistic regression analysis revealed that leptin, adiponectin and LAR were significantly associated with metabolic syndrome with respective unadjusted OR of 1.429, 0.468 and 1.502. After adjustment, for age and sex, the associations remained significative; LAR was also found to be significantly associated with metabolic syndrome (OR = 1.573, p value =0.000) as well as lower levels of adiponectin (OR = 0.359, p value =0.000) and higher levels of leptin (OR = 1.469, p value =0.001). This study revealed that LAR is significantly associated with metabolic syndrome in sub-Saharan African population, independently to age and sex.

Factors Associated with HIV Testing Among Participants from Substance Use Disorder Treatment Programs in the US: A Machine Learning Approach.

PubMed

Pan, Yue; Liu, Hongmei; Metsch, Lisa R; Feaster, Daniel J

2017-02-01

HIV testing is the foundation for consolidated HIV treatment and prevention. In this study, we aim to discover the most relevant variables for predicting HIV testing uptake among substance users in substance use disorder treatment programs by applying random forest (RF), a robust multivariate statistical learning method. We also provide a descriptive introduction to this method for those who are unfamiliar with it. We used data from the National Institute on Drug Abuse Clinical Trials Network HIV testing and counseling study (CTN-0032). A total of 1281 HIV-negative or status unknown participants from 12 US community-based substance use disorder treatment programs were included and were randomized into three HIV testing and counseling treatment groups. The a priori primary outcome was self-reported receipt of HIV test results. Classification accuracy of RF was compared to logistic regression, a standard statistical approach for binary outcomes. Variable importance measures for the RF model were used to select the most relevant variables. RF based models produced much higher classification accuracy than those based on logistic regression. Treatment group is the most important predictor among all covariates, with a variable importance index of 12.9%. RF variable importance revealed that several types of condomless sex behaviors, condom use self-efficacy and attitudes towards condom use, and level of depression are the most important predictors of receipt of HIV testing results. There is a non-linear negative relationship between count of condomless sex acts and the receipt of HIV testing. In conclusion, RF seems promising in discovering important factors related to HIV testing uptake among large numbers of predictors and should be encouraged in future HIV prevention and treatment research and intervention program evaluations.

Impact of prior urethral manipulation on outcome of anastomotic urethroplasty for post-traumatic urethral stricture.

PubMed

Singh, Bhupendra P; Andankar, Mukund G; Swain, Sanjaya K; Das, Krishanu; Dassi, Vimal; Kaswan, Harish K; Agrawal, Vipul; Pathak, Hemant R

2010-01-01

To determine the impact of earlier urethral interventions on the outcomes of anastomotic urethroplasty in post-traumatic stricture urethra. From October 1995 to March 2008, a total of 58 patients with post-traumatic posterior urethral stricture underwent anastomotic urethroplasty. Eighteen patients had earlier undergone urethral intervention in the form of urethrotomy (3), endoscopic realignment (7), or open urethroplasty (8). Success was defined as no obstructive urinary symptoms, maximum urine flow rate > or = 15 mL/s, normal urethral imaging and/or urethroscopy, and no need of any intervention in the follow-up period. Patients who met the above objective criteria after needing 1 urethrotomy following urethroplasty were defined to have satisfactory outcome and were included in satisfactory result rate along with patients who had a successful outcome. Results were analyzed using unpaired t test, chi-square test, binary logistic regression, Kaplan-Meier curves, and log rank test. Previous interventions in the form of endoscopic realignment or urethroplasty have significant adverse effect on the success rate of subsequent anastomotic urethroplasty for post-traumatic posterior urethral strictures (P <.05). Previous intervention in the form of visual internal urethrotomies (up to 2 times) did not affect the outcome of subsequent anastomotic urethroplasty. Length of stricture and age of patient did not predict the outcome in traumatic posterior urethral strictures in logistic regression analysis. Previous failed railroading or urethroplasty significantly decrease the success of subsequent anastomotic urethroplasty. Hence, a primary realignment or urethroplasty should be avoided in suboptimal conditions and the cases of post-traumatic urethral stricture should be referred to centers with such expertise. 2010 Elsevier Inc. All rights reserved.

Clinical characteristics and treatment outcomes of patients with major depressive disorder and comorbid anxiety disorders - results from a European multicenter study.

PubMed

Dold, Markus; Bartova, Lucie; Souery, Daniel; Mendlewicz, Julien; Serretti, Alessandro; Porcelli, Stefano; Zohar, Joseph; Montgomery, Stuart; Kasper, Siegfried

2017-08-01

This naturalistic European multicenter study aimed to elucidate the association between major depressive disorder (MDD) and comorbid anxiety disorders. Demographic and clinical information of 1346 MDD patients were compared between those with and without concurrent anxiety disorders. The association between explanatory variables and the presence of comorbid anxiety disorders was examined using binary logistic regression analyses. 286 (21.2%) of the participants exhibited comorbid anxiety disorders, 10.8% generalized anxiety disorder (GAD), 8.3% panic disorder, 8.1% agoraphobia, and 3.3% social phobia. MDD patients with comorbid anxiety disorders were characterized by younger age (social phobia), outpatient status (agoraphobia), suicide risk (any anxiety disorder, panic disorder, agoraphobia, social phobia), higher depressive symptom severity (GAD), polypsychopharmacy (panic disorder, agoraphobia), and a higher proportion receiving augmentation treatment with benzodiazepines (any anxiety disorder, GAD, panic disorder, agoraphobia, social phobia) and pregabalin (any anxiety disorder, GAD, panic disorder). The results in terms of treatment response were conflicting (better response for panic disorder and poorer for GAD). The logistic regression analyses revealed younger age (any anxiety disorder, social phobia), outpatient status (agoraphobia), suicide risk (agoraphobia), severe depressive symptoms (any anxiety disorder, GAD, social phobia), poorer treatment response (GAD), and increased administration of benzodiazepines (any anxiety disorder, agoraphobia, social phobia) and pregabalin (any anxiety disorder, GAD, panic disorder) to be associated with comorbid anxiety disorders. Our findings suggest that the various anxiety disorders subtypes display divergent clinical characteristics and are associated with different variables. Especially comorbid GAD appears to be characterized by high symptom severity and poor treatment response. Copyright © 2017 Elsevier Ltd. All rights reserved.

High statistical heterogeneity is more frequent in meta-analysis of continuous than binary outcomes.

PubMed

Alba, Ana C; Alexander, Paul E; Chang, Joanne; MacIsaac, John; DeFry, Samantha; Guyatt, Gordon H

2016-02-01

We compared the distribution of heterogeneity in meta-analyses of binary and continuous outcomes. We searched citations in MEDLINE and Cochrane databases for meta-analyses of randomized trials published in 2012 that reported a measure of heterogeneity of either binary or continuous outcomes. Two reviewers independently performed eligibility screening and data abstraction. We evaluated the distribution of I(2) in meta-analyses of binary and continuous outcomes and explored hypotheses explaining the difference in distributions. After full-text screening, we selected 671 meta-analyses evaluating 557 binary and 352 continuous outcomes. Heterogeneity as assessed by I(2) proved higher in continuous than in binary outcomes: the proportion of continuous and binary outcomes reporting an I(2) of 0% was 34% vs. 52%, respectively, and reporting an I(2) of 60-100% was 39% vs. 14%. In continuous but not binary outcomes, I(2) increased with larger number of studies included in a meta-analysis. Increased precision and sample size do not explain the larger I(2) found in meta-analyses of continuous outcomes with a larger number of studies. Meta-analyses evaluating continuous outcomes showed substantially higher I(2) than meta-analyses of binary outcomes. Results suggest differing standards for interpreting I(2) in continuous vs. binary outcomes may be appropriate. Copyright © 2016 Elsevier Inc. All rights reserved.

Binary weight distributions of some Reed-Solomon codes

NASA Technical Reports Server (NTRS)

Pollara, F.; Arnold, S.

1992-01-01

The binary weight distributions of the (7,5) and (15,9) Reed-Solomon (RS) codes and their duals are computed using the MacWilliams identities. Several mappings of symbols to bits are considered and those offering the largest binary minimum distance are found. These results are then used to compute bounds on the soft-decoding performance of these codes in the presence of additive Gaussian noise. These bounds are useful for finding large binary block codes with good performance and for verifying the performance obtained by specific soft-coding algorithms presently under development.

The PyCBC search for binary black hole coalescences in Advanced LIGO's first observing run

NASA Astrophysics Data System (ADS)

Willis, Joshua; LIGO Scientific Collaboration

2017-01-01

Advanced LIGO's first observing run saw the first detections of binary black hole coalescences. We describe the PyCBC matched filter analysis, and the results of that search for binary systems with total mass up to 100 solar masses. This is a matched filter search for general-relativistic signals from binary black hole systems. Two signals, GW150914 and GW151226, were identified with very high significance, and a third possible signal, LVT151012, was found, though at much lower significance. Supported by NSF award PHY-1506254.

The Tarantula Massive Binary Monitoring. I. Observational campaign and OB-type spectroscopic binaries

NASA Astrophysics Data System (ADS)

Almeida, L. A.; Sana, H.; Taylor, W.; Barbá, R.; Bonanos, A. Z.; Crowther, P.; Damineli, A.; de Koter, A.; de Mink, S. E.; Evans, C. J.; Gieles, M.; Grin, N. J.; Hénault-Brunet, V.; Langer, N.; Lennon, D.; Lockwood, S.; Maíz Apellániz, J.; Moffat, A. F. J.; Neijssel, C.; Norman, C.; Ramírez-Agudelo, O. H.; Richardson, N. D.; Schootemeijer, A.; Shenar, T.; Soszyński, I.; Tramper, F.; Vink, J. S.

2017-02-01

Context. Massive binaries play a crucial role in the Universe. Knowing the distributions of their orbital parameters is important for a wide range of topics from stellar feedback to binary evolution channels and from the distribution of supernova types to gravitational wave progenitors, yet no direct measurements exist outside the Milky Way. Aims: The Tarantula Massive Binary Monitoring project was designed to help fill this gap by obtaining multi-epoch radial velocity (RV) monitoring of 102 massive binaries in the 30 Doradus region. Methods: In this paper we analyze 32 FLAMES/GIRAFFE observations of 93 O- and 7 B-type binaries. We performed a Fourier analysis and obtained orbital solutions for 82 systems: 51 single-lined (SB1) and 31 double-lined (SB2) spectroscopic binaries. Results: Overall, the binary fraction and orbital properties across the 30 Doradus region are found to be similar to existing Galactic samples. This indicates that within these domains environmental effects are of second order in shaping the properties of massive binary systems. A small difference is found in the distribution of orbital periods, which is slightly flatter (in log space) in 30 Doradus than in the Galaxy, although this may be compatible within error estimates and differences in the fitting methodology. Also, orbital periods in 30 Doradus can be as short as 1.1 d, somewhat shorter than seen in Galactic samples. Equal mass binaries (q> 0.95) in 30 Doradus are all found outside NGC 2070, the central association that surrounds R136a, the very young and massive cluster at 30 Doradus's core. Most of the differences, albeit small, are compatible with expectations from binary evolution. One outstanding exception, however, is the fact that earlier spectral types (O2-O7) tend to have shorter orbital periods than later spectral types (O9.2-O9.7). Conclusions: Our results point to a relative universality of the incidence rate of massive binaries and their orbital properties in the metallicity range from solar (Z⊙) to about half solar. This provides the first direct constraints on massive binary properties in massive star-forming galaxies at the Universe's peak of star formation at redshifts z 1 to 2 which are estimated to have Z 0.5 Z⊙. The log of observations and RV measurements for all targets are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/598/A84

Multiple logistic regression model of signalling practices of drivers on urban highways

NASA Astrophysics Data System (ADS)

Puan, Othman Che; Ibrahim, Muttaka Na'iya; Zakaria, Rozana

2015-05-01

Giving signal is a way of informing other road users, especially to the conflicting drivers, the intention of a driver to change his/her movement course. Other users are exposed to hazard situation and risks of accident if the driver who changes his/her course failed to give signal as required. This paper describes the application of logistic regression model for the analysis of driver's signalling practices on multilane highways based on possible factors affecting driver's decision such as driver's gender, vehicle's type, vehicle's speed and traffic flow intensity. Data pertaining to the analysis of such factors were collected manually. More than 2000 drivers who have performed a lane changing manoeuvre while driving on two sections of multilane highways were observed. Finding from the study shows that relatively a large proportion of drivers failed to give any signals when changing lane. The result of the analysis indicates that although the proportion of the drivers who failed to provide signal prior to lane changing manoeuvre is high, the degree of compliances of the female drivers is better than the male drivers. A binary logistic model was developed to represent the probability of a driver to provide signal indication prior to lane changing manoeuvre. The model indicates that driver's gender, type of vehicle's driven, speed of vehicle and traffic volume influence the driver's decision to provide a signal indication prior to a lane changing manoeuvre on a multilane urban highway. In terms of types of vehicles driven, about 97% of motorcyclists failed to comply with the signal indication requirement. The proportion of non-compliance drivers under stable traffic flow conditions is much higher than when the flow is relatively heavy. This is consistent with the data which indicates a high degree of non-compliances when the average speed of the traffic stream is relatively high.

An axion-like scalar field environment effect on binary black hole merger

NASA Astrophysics Data System (ADS)

Yang, Qing; Ji, Li-Wei; Hu, Bin; Cao, Zhou-Jian; Cai, Rong-Gen

2018-06-01

The environment, such as an accretion disk, could modify the signal of the gravitational wave from astrophysical black hole binaries. In this article, we model the matter field around intermediate-mass binary black holes by means of an axion-like scalar field and investigate their joint evolution. In detail, we consider equal mass binary black holes surrounded by a shell of axion-like scalar field both in spherically symmetric and non-spherically symmetric cases, and with different strengths of the scalar field. Our result shows that the environmental scalar field could essentially modify the dynamics. Firstly, in the spherically symmetric case, with increase of the scalar field strength, the number of circular orbits for the binary black hole is reduced. This means that the scalar field could significantly accelerate the merger process. Secondly, once the scalar field strength exceeds a certain critical value, the scalar field could collapse into a third black hole with its mass being larger than that of the binary. Consequently, the new black hole that collapses from the environmental scalar field could accrete the binary promptly and the binary collides head-on with each other. In this process, there is almost no quadrupole signal produced, and, consequently, the gravitational wave is greatly suppressed. Thirdly, when the scalar field strength is relatively smaller than the critical value, the black hole orbit could develop eccentricity through accretion of the scalar field. Fourthly, during the initial stage of the inspiral, the gravitational attractive force from the axion-like scalar field could induce a sudden turn in the binary orbits, hence resulting in a transient wiggle in the gravitational waveform. Finally, in the non-spherical case, the scalar field could gravitationally attract the binary moving toward the center of mass for the scalar field and slow down the merger process.

Childhood diarrheal morbidity and sanitation predictors in a nomadic community.

PubMed

Bitew, Bikes Destaw; Woldu, Wondwoson; Gizaw, Zemichael

2017-10-06

Diarrhea remains a leading killer of young children on the globe despite the availability of simple and effective solutions to prevent and control it. The disease is more prevalent among under - five children (U5C) in the developing world due to lack of sanitation. A child dies every 15 s from diarrheal disease caused largely by poor sanitation. Nearly 90% of diarrheal disease is attributed to inadequate sanitation. Even though, the health burden of diarrheal disease is widely recognized at global level, its prevalence and sanitation predictors among a nomadic population of Ethiopia are not researched. This study was therefore designed to assess the prevalence of childhood diarrheal disease and sanitation predictors among a nomadic people in Hadaleala district, Afar region, Northeast Ethiopia. A community based cross-sectional study design was carried out to investigate diarrheal disease among U5C. A total of 704 households who had U5C were included in this study and the study subjects were recruited by a multistage cluster sampling technique. Data were collected using a structured questionnaire and an observational checklist. All the mothers of U5C found in the selected clusters were interviewed. Furthermore, the living environment was observed. Univariable binary logistic regression analysis was used to choose variables for the multivariable binary logistic regression analysis on the basis of p- value less than 0.2. Finally, multivariable binary logistic regression analysis was used to identify variables associated with childhood diarrhea disease on the basis of adjusted odds ratio (AOR) with 95% confidence interval (CI) and p < 0.05. The two weeks period prevalence of diarrheal disease among U5C in Hadaleala district was 26.1% (95% CI: 22.9 - 29.3%). Childhood diarrheal disease was statistically associated with unprotected drinking water sources [AOR = 2.449, 95% CI = (1.264, 4.744)], inadequate drinking water service level [AOR = 1.535, 95% CI = (1.004, 2.346)], drinking water sources not protected from animal contact [AOR = 4.403, 95% CI = (2.424, 7.999)], un-availability of any type of latrine [AOR = 2.278, 95% CI = (1.045, 4.965)], presence of human excreta in the compound [AOR = 11.391, 95% CI = (2.100, 61.787)], not washing hand after visiting toilet [AOR = 16.511, 95% CI = (3.304, 82.509)], and live in one living room [AOR = 5.827, 95% CI = (3.208, 10.581)]. Childhood diarrheal disease was the common public health problem in Hadaleala district. Compared with the national and regional prevalence of childhood diarrhea, higher prevalence of diarrhea among U5C was reported. Types of drinking water sources, households whose water sources are shared with livestock, volume of daily water collected, availability of latrine, presence of faeces in the compound, hand washing after visiting the toilet and number of rooms were the sanitation predictors associated with childhood diarrhea. Therefore, enabling the community with safe and continuous supply of water and proper disposal of wastes including excreta is necessary with particular emphasis to the rural nomadic communities.

Dynamic detection-rate-based bit allocation with genuine interval concealment for binary biometric representation.

PubMed

Lim, Meng-Hui; Teoh, Andrew Beng Jin; Toh, Kar-Ann

2013-06-01

Biometric discretization is a key component in biometric cryptographic key generation. It converts an extracted biometric feature vector into a binary string via typical steps such as segmentation of each feature element into a number of labeled intervals, mapping of each interval-captured feature element onto a binary space, and concatenation of the resulted binary output of all feature elements into a binary string. Currently, the detection rate optimized bit allocation (DROBA) scheme is one of the most effective biometric discretization schemes in terms of its capability to assign binary bits dynamically to user-specific features with respect to their discriminability. However, we learn that DROBA suffers from potential discriminative feature misdetection and underdiscretization in its bit allocation process. This paper highlights such drawbacks and improves upon DROBA based on a novel two-stage algorithm: 1) a dynamic search method to efficiently recapture such misdetected features and to optimize the bit allocation of underdiscretized features and 2) a genuine interval concealment technique to alleviate crucial information leakage resulted from the dynamic search. Improvements in classification accuracy on two popular face data sets vindicate the feasibility of our approach compared with DROBA.

Study of polymorphic control in an ethanol-water binary solvent

NASA Astrophysics Data System (ADS)

Kitano, Hiroshi; Tanaka, Takayuki; Hirasawa, Izumi

2017-07-01

Three polymorphs of L-Citrulline crystals, anhydrate (Form α, γ and δ) and pseudo polymorph (dihydrate), were confirmed. In this study, polymorphic control of L-Citrulline was attempted by changing the ethanol concentration in ethanol-water binary solvents. First, each polymorph of L-Citrulline crystals was added to the prepared ethanol-water binary solvents and samples which were obtained chronologically were measured by XRD. Also, the crystal sizes and shapes in transformation were observed by microscope. Then, polymorphs of the crystals after transformation were determined by XRD pattern. As a result, the transformation from dihydrate to anhydrate was observed by adding dihydrate crystals to the ethanol-water binary solvent. Similarly, the transformation from anhydrate to another anhydrate was observed. Especially in the case of adding dihydrate, the existences of all polymorphs were confirmed by adjusting ethanol-water binary solvent. According to the results, it was revealed that polymorphic transformation was affected by the trace amount of water contained in ethanol-water binary solvent. Moreover, transformation from dihydrate to anhydrate was constructed with three phases, dissolution of dihydrate, nucleation and growth of anhydrate. Therefore, the solution-mediated polymorphic transformation was supposed to be a key mechanism for this transformation.

Are the O stars in WR+O binaries exceptionally rapid rotators?

NASA Astrophysics Data System (ADS)

Reeve, Dominic; Howarth, Ian D.

2018-05-01

We examine claims of strong gravity-darkening effects in the O-star components of WR+O binaries. We generate synthetic spectra for a wide range of parameters, and show that the line-width results are consistent with extensive measurements of O stars that are either single or are members of `normal' binaries. By contrast, the WR+O results are at the extremes of, or outside, the distributions of both models and other observations. Remeasurement of the WR+O spectra shows that they can be reconciled with other results by judicious choice of pseudo-continuum normalization. With this interpretation, the supersynchronous rotation previously noted for the O-star components in the WR+O binaries with the longest orbital periods appears to be unexceptional. Our investigation is therefore consistent with the aphorism that if the title of a paper ends with a question mark, the answer is probably `no'.

Iterative quantization: a Procrustean approach to learning binary codes for large-scale image retrieval.

PubMed

Gong, Yunchao; Lazebnik, Svetlana; Gordo, Albert; Perronnin, Florent

2013-12-01

This paper addresses the problem of learning similarity-preserving binary codes for efficient similarity search in large-scale image collections. We formulate this problem in terms of finding a rotation of zero-centered data so as to minimize the quantization error of mapping this data to the vertices of a zero-centered binary hypercube, and propose a simple and efficient alternating minimization algorithm to accomplish this task. This algorithm, dubbed iterative quantization (ITQ), has connections to multiclass spectral clustering and to the orthogonal Procrustes problem, and it can be used both with unsupervised data embeddings such as PCA and supervised embeddings such as canonical correlation analysis (CCA). The resulting binary codes significantly outperform several other state-of-the-art methods. We also show that further performance improvements can result from transforming the data with a nonlinear kernel mapping prior to PCA or CCA. Finally, we demonstrate an application of ITQ to learning binary attributes or "classemes" on the ImageNet data set.

CLOSE BINARIES WITH INFRARED EXCESS: DESTROYERS OF WORLDS?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matranga, M.; Drake, J. J.; Kashyap, V. L.

2010-09-10

We present the results of a Spitzer photometric investigation into the IR excesses of close binary systems. In a sample of 10 objects, excesses in Infrared Array Camera and MIPS24 bands implying the presence of warm dust are found for 3. For two objects, we do not find excesses reported in earlier IRAS studies. We discuss the results in the context of the scenario suggested by Rhee and co-workers, in which warm dust is continuously created by destructive collisions between planetary bodies. A simple numerical model for the steady-state distribution of dust in one IR excess system shows a centralmore » clearing of radius 0.22 AU caused by dynamical perturbations from the binary star. This is consistent with the size of the central clearing derived from the Spitzer spectral energy distribution. We conclude that close binaries could be efficient 'destroyers of worlds' and lead to destabilization of the orbits of their planetary progeny by magnetically driven angular momentum loss and secular shrinkage of the binary separation.« less

The Kozai-Lidov mechanism in hydrodynamical disks. II. Effects of binary and disk parameters

DOE PAGES

Fu, Wen; Lubow, Stephen H.; Martin, Rebecca G.

2015-07-01

Martin et al. (2014b) showed that a substantially misaligned accretion disk around one component of a binary system can undergo global damped Kozai–Lidov (KL) oscillations. During these oscillations, the inclination and eccentricity of the disk are periodically exchanged. However, the robustness of this mechanism and its dependence on the system parameters were unexplored. In this paper, we use three-dimensional hydrodynamical simulations to analyze how various binary and disk parameters affect the KL mechanism in hydrodynamical disks. The simulations include the effect of gas pressure and viscosity, but ignore the effects of disk self-gravity. We describe results for different numerical resolutions,more » binary mass ratios and orbital eccentricities, initial disk sizes, initial disk surface density profiles, disk sound speeds, and disk viscosities. We show that the KL mechanism can operate for a wide range of binary-disk parameters. We discuss the applications of our results to astrophysical disks in various accreting systems.« less

Isobaric vapor-liquid equilibria for binary systems α-phenylethylamine + toluene and α-phenylethylamine + cyclohexane at 100 kPa

NASA Astrophysics Data System (ADS)

Wu, Xiaoru; Gao, Yingyu; Ban, Chunlan; Huang, Qiang

2016-09-01

In this paper the results of the vapor-liquid equilibria study at 100 kPa are presented for two binary systems: α-phenylethylamine(1) + toluene (2) and (α-phenylethylamine(1) + cyclohexane(2)). The binary VLE data of the two systems were correlated by the Wilson, NRTL, and UNIQUAC models. For each binary system the deviations between the results of the correlations and the experimental data have been calculated. For the both binary systems the average relative deviations in temperature for the three models were lower than 0.99%. The average absolute deviations in vapour phase composition (mole fractions) and in temperature T were lower than 0.0271 and 1.93 K, respectively. Thermodynamic consistency has been tested for all vapor-liquid equilibrium data by the Herrington method. The values calculated by Wilson and NRTL equations satisfied the thermodynamics consistency test for the both two systems, while the values calculated by UNIQUAC equation didn't.

Multiclass Reduced-Set Support Vector Machines

NASA Technical Reports Server (NTRS)

Tang, Benyang; Mazzoni, Dominic

2006-01-01

There are well-established methods for reducing the number of support vectors in a trained binary support vector machine, often with minimal impact on accuracy. We show how reduced-set methods can be applied to multiclass SVMs made up of several binary SVMs, with significantly better results than reducing each binary SVM independently. Our approach is based on Burges' approach that constructs each reduced-set vector as the pre-image of a vector in kernel space, but we extend this by recomputing the SVM weights and bias optimally using the original SVM objective function. This leads to greater accuracy for a binary reduced-set SVM, and also allows vectors to be 'shared' between multiple binary SVMs for greater multiclass accuracy with fewer reduced-set vectors. We also propose computing pre-images using differential evolution, which we have found to be more robust than gradient descent alone. We show experimental results on a variety of problems and find that this new approach is consistently better than previous multiclass reduced-set methods, sometimes with a dramatic difference.

Numerical Simulations of Close and Contact Binary Systems Having Bipolytropic Equation of State

NASA Astrophysics Data System (ADS)

Kadam, Kundan; Clayton, Geoffrey C.; Motl, Patrick M.; Marcello, Dominic; Frank, Juhan

2017-01-01

I present the results of the numerical simulations of the mass transfer in close and contact binary systems with both stars having a bipolytropic (composite polytropic) equation of state. The initial binary systems are obtained by a modifying Hachisu’s self-consistent field technique. Both the stars have fully resolved cores with a molecular weight jump at the core-envelope interface. The initial properties of these simulations are chosen such that they satisfy the mass-radius relation, composition and period of a late W-type contact binary system. The simulations are carried out using two different Eulerian hydrocodes, Flow-ER with a fixed cylindrical grid, and Octo-tiger with an AMR capable cartesian grid. The detailed comparison of the simulations suggests an agreement between the results obtained from the two codes at different resolutions. The set of simulations can be treated as a benchmark, enabling us to reliably simulate mass transfer and merger scenarios of binary systems involving bipolytropic components.

Cas A and the Crab were not stellar binaries at death

NASA Astrophysics Data System (ADS)

Kochanek, C. S.

2018-01-01

The majority of massive stars are in binaries, which implies that many core collapse supernovae should be binaries at the time of the explosion. Here we show that the three most recent, local (visual) SNe (the Crab, Cas A and SN 1987A) were not stellar binaries at death, with limits on the initial mass ratios of q = M2/M1 ≲ 0.1. No quantitative limits have previously been set for Cas A and the Crab, while for SN 1987A we merely updated existing limits in view of new estimates of the dust content. The lack of stellar companions to these three ccSNe implies a 90 per cent confidence upper limit on the q ≳ 0.1 binary fraction at death of fb < 44 per cent. In a passively evolving binary model (meaning no binary interactions), with a flat mass ratio distribution and a Salpeter IMF, the resulting 90 per cent confidence upper limit on the initial binary fraction of F < 63 per cent is in tension with observed massive binary statistics. Allowing a significant fraction fM ≃ 25 per cent of stellar binaries to merge reduces the tension, with F < 63({1-f}M)^{-1}{ per cent} ˜eq 81{ per cent}, but allowing for the significant fraction in higher order systems (triples, etc.) reintroduces the tension. That Cas A was not a stellar binary at death also shows that a surviving massive binary companion at the time of the explosion is not necessary for producing a Type IIb SNe. Much larger surveys for binary companions to Galactic SNe will become feasible with the release of the full Gaia proper motion and parallax catalogues providing a powerful probe of the statistics of such binaries and their role in massive star evolution, neutron star velocity distributions and runaway stars.

Flexible link functions in nonparametric binary regression with Gaussian process priors.

PubMed

Li, Dan; Wang, Xia; Lin, Lizhen; Dey, Dipak K

2016-09-01

In many scientific fields, it is a common practice to collect a sequence of 0-1 binary responses from a subject across time, space, or a collection of covariates. Researchers are interested in finding out how the expected binary outcome is related to covariates, and aim at better prediction in the future 0-1 outcomes. Gaussian processes have been widely used to model nonlinear systems; in particular to model the latent structure in a binary regression model allowing nonlinear functional relationship between covariates and the expectation of binary outcomes. A critical issue in modeling binary response data is the appropriate choice of link functions. Commonly adopted link functions such as probit or logit links have fixed skewness and lack the flexibility to allow the data to determine the degree of the skewness. To address this limitation, we propose a flexible binary regression model which combines a generalized extreme value link function with a Gaussian process prior on the latent structure. Bayesian computation is employed in model estimation. Posterior consistency of the resulting posterior distribution is demonstrated. The flexibility and gains of the proposed model are illustrated through detailed simulation studies and two real data examples. Empirical results show that the proposed model outperforms a set of alternative models, which only have either a Gaussian process prior on the latent regression function or a Dirichlet prior on the link function. © 2015, The International Biometric Society.

Flexible Link Functions in Nonparametric Binary Regression with Gaussian Process Priors

PubMed Central

Li, Dan; Lin, Lizhen; Dey, Dipak K.

2015-01-01

Summary In many scientific fields, it is a common practice to collect a sequence of 0-1 binary responses from a subject across time, space, or a collection of covariates. Researchers are interested in finding out how the expected binary outcome is related to covariates, and aim at better prediction in the future 0-1 outcomes. Gaussian processes have been widely used to model nonlinear systems; in particular to model the latent structure in a binary regression model allowing nonlinear functional relationship between covariates and the expectation of binary outcomes. A critical issue in modeling binary response data is the appropriate choice of link functions. Commonly adopted link functions such as probit or logit links have fixed skewness and lack the flexibility to allow the data to determine the degree of the skewness. To address this limitation, we propose a flexible binary regression model which combines a generalized extreme value link function with a Gaussian process prior on the latent structure. Bayesian computation is employed in model estimation. Posterior consistency of the resulting posterior distribution is demonstrated. The flexibility and gains of the proposed model are illustrated through detailed simulation studies and two real data examples. Empirical results show that the proposed model outperforms a set of alternative models, which only have either a Gaussian process prior on the latent regression function or a Dirichlet prior on the link function. PMID:26686333

A possible formation channel for blue hook stars in globular cluster - II. Effects of metallicity, mass ratio, tidal enhancement efficiency and helium abundance

NASA Astrophysics Data System (ADS)

Lei, Zhenxin; Zhao, Gang; Zeng, Aihua; Shen, Lihua; Lan, Zhongjian; Jiang, Dengkai; Han, Zhanwen

2016-12-01

Employing tidally enhanced stellar wind, we studied in binaries the effects of metallicity, mass ratio of primary to secondary, tidal enhancement efficiency and helium abundance on the formation of blue hook (BHk) stars in globular clusters (GCs). A total of 28 sets of binary models combined with different input parameters are studied. For each set of binary model, we presented a range of initial orbital periods that is needed to produce BHk stars in binaries. All the binary models could produce BHk stars within different range of initial orbital periods. We also compared our results with the observation in the Teff-logg diagram of GC NGC 2808 and ω Cen. Most of the BHk stars in these two GCs locate well in the region predicted by our theoretical models, especially when C/N-enhanced model atmospheres are considered. We found that mass ratio of primary to secondary and tidal enhancement efficiency have little effects on the formation of BHk stars in binaries, while metallicity and helium abundance would play important roles, especially for helium abundance. Specifically, with helium abundance increasing in binary models, the space range of initial orbital periods needed to produce BHk stars becomes obviously wider, regardless of other input parameters adopted. Our results were discussed with recent observations and other theoretical models.

An experimental study on the coalescence process of binary droplets in oil under ultrasonic standing waves.

PubMed

Luo, Xiaoming; Cao, Juhang; He, Limin; Wang, Hongping; Yan, Haipeng; Qin, Yahua

2017-01-01

The coalescence process of binary droplets in oil under ultrasonic standing waves was investigated with high-speed photography. Three motion models of binary droplets in coalescence process were illustrated: (1) slight translational oscillation; (2) sinusoidal translational oscillation; (3) migration along with acoustic streaming. To reveal the droplets coalescence mechanisms, the influence of main factors (such as acoustic intensity, droplet size, viscosity and interfacial tension, etc) on the motion and coalescence of binary droplets was studied under ultrasonic standing waves. Results indicate that the shortest coalescence time is achieved when binary droplets show sinusoidal translational oscillation. The corresponding acoustic intensity in this case is the optimum acoustic intensity. Under the optimum acoustic intensity, drop size decrease will bring about coalescence time decrease by enhancing the binary droplets oscillation. Moreover, there is an optimum interfacial tension to achieve the shortest coalescence time. Copyright © 2016 Elsevier B.V. All rights reserved.

Measuring Parameters of Massive Black Hole Binaries with Partially-Aligned Spins

NASA Technical Reports Server (NTRS)

Lang, Ryan N.; Hughes, Scott A.; Cornish, Neil J.

2010-01-01

It is important to understand how well the gravitational-wave observatory LISA can measure parameters of massive black hole binaries. It has been shown that including spin precession in the waveform breaks degeneracies and produces smaller expected parameter errors than a simpler, precession-free analysis. However, recent work has shown that gas in binaries can partially align the spins with the orbital angular momentum, thus reducing the precession effect. We show how this degrades the earlier results, producing more pessimistic errors in gaseous mergers. However, we then add higher harmonics to the signal model; these also break degeneracies, but they are not affected by the presence of gas. The harmonics often restore the errors in partially-aligned binaries to the same as, or better than/ those that are obtained for fully precessing binaries with no harmonics. Finally, we investigate what LISA measurements of spin alignment can tell us about the nature of gas around a binary,

RED GIANTS IN ECLIPSING BINARY AND MULTIPLE-STAR SYSTEMS: MODELING AND ASTEROSEISMIC ANALYSIS OF 70 CANDIDATES FROM KEPLER DATA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaulme, P.; McKeever, J.; Rawls, M. L.

2013-04-10

Red giant stars are proving to be an incredible source of information for testing models of stellar evolution, as asteroseismology has opened up a window into their interiors. Such insights are a direct result of the unprecedented data from space missions CoRoT and Kepler as well as recent theoretical advances. Eclipsing binaries are also fundamental astrophysical objects, and when coupled with asteroseismology, binaries provide two independent methods to obtain masses and radii and exciting opportunities to develop highly constrained stellar models. The possibility of discovering pulsating red giants in eclipsing binary systems is therefore an important goal that could potentiallymore » offer very robust characterization of these systems. Until recently, only one case has been discovered with Kepler. We cross-correlate the detected red giant and eclipsing-binary catalogs from Kepler data to find possible candidate systems. Light-curve modeling and mean properties measured from asteroseismology are combined to yield specific measurements of periods, masses, radii, temperatures, eclipse timing variations, core rotation rates, and red giant evolutionary state. After using three different techniques to eliminate false positives, out of the 70 systems common to the red giant and eclipsing-binary catalogs we find 13 strong candidates (12 previously unknown) to be eclipsing binaries, one to be a non-eclipsing binary with tidally induced oscillations, and 10 more to be hierarchical triple systems, all of which include a pulsating red giant. The systems span a range of orbital eccentricities, periods, and spectral types F, G, K, and M for the companion of the red giant. One case even suggests an eclipsing binary composed of two red giant stars and another of a red giant with a {delta}-Scuti star. The discovery of multiple pulsating red giants in eclipsing binaries provides an exciting test bed for precise astrophysical modeling, and follow-up spectroscopic observations of many of the candidate systems are encouraged. The resulting highly constrained stellar parameters will allow, for example, the exploration of how binary tidal interactions affect pulsations when compared to the single-star case.« less

Formation of Kuiper-belt binaries through multiple chaotic scattering encounters with low-mass intruders

NASA Astrophysics Data System (ADS)

Astakhov, Sergey A.; Lee, Ernestine A.; Farrelly, David

2005-06-01

The discovery that many trans-Neptunian objects exist in pairs, or binaries, is proving invaluable for shedding light on the formation, evolution and structure of the outer Solar system. Based on recent systematic searches it has been estimated that up to 10 per cent of Kuiper-belt objects might be binaries. However, all examples discovered to date are unusual, as compared with near-Earth and main-belt asteroid binaries, for their mass ratios of the order of unity and their large, eccentric orbits. In this article we propose a common dynamical origin for these compositional and orbital properties based on four-body simulations in the Hill approximation. Our calculations suggest that binaries are produced through the following chain of events. Initially, long-lived quasi-bound binaries form by two bodies getting entangled in thin layers of dynamical chaos produced by solar tides within the Hill sphere. Next, energy transfer through gravitational scattering with a low-mass intruder nudges the binary into a nearby non-chaotic, stable zone of phase space. Finally, the binary hardens (loses energy) through a series of relatively gentle gravitational scattering encounters with further intruders. This produces binary orbits that are well fitted by Kepler ellipses. Dynamically, the overall process is strongly favoured if the original quasi-bound binary contains comparable masses. We propose a simplified model of chaotic scattering to explain these results. Our findings suggest that the observed preference for roughly equal-mass ratio binaries is probably a real effect; that is, it is not primarily due to an observational bias for widely separated, comparably bright objects. Nevertheless, we predict that a sizeable population of very unequal-mass Kuiper-belt binaries is probably awaiting discovery.

EXTRASOLAR BINARY PLANETS. II. DETECTABILITY BY TRANSIT OBSERVATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewis, K. M.; Ida, S.; Ochiai, H.

2015-05-20

We discuss the detectability of gravitationally bound pairs of gas-giant planets (which we call “binary planets”) in extrasolar planetary systems that are formed through orbital instability followed by planet–planet dynamical tides during their close encounters, based on the results of N-body simulations by Ochiai et al. (Paper I). Paper I showed that the formation probability of a binary is as much as ∼10% for three giant planet systems that undergo orbital instability, and after post-capture long-term tidal evolution, the typical binary separation is three to five times the sum of the physical radii of the planets. The binary planets aremore » stable during the main-sequence lifetime of solar-type stars, if the stellarcentric semimajor axis of the binary is larger than 0.3 AU. We show that detecting modulations of transit light curves is the most promising observational method to detect binary planets. Since the likely binary separations are comparable to the stellar diameter, the shape of the transit light curve is different from transit to transit, depending on the phase of the binary’s orbit. The transit durations and depth for binary planet transits are generally longer and deeper than those for the single planet case. We point out that binary planets could exist among the known inflated gas-giant planets or objects classified as false positive detections at orbital radii ≳0.3 AU, propose a binary planet explanation for the CoRoT candidate SRc01 E2 1066, and show that binary planets are likely to be present in, and could be detected using, Kepler-quality data.« less

Equilibrium points and associated periodic orbits in the gravity of binary asteroid systems: (66391) 1999 KW4 as an example

NASA Astrophysics Data System (ADS)

Shi, Yu; Wang, Yue; Xu, Shijie

2018-04-01

The motion of a massless particle in the gravity of a binary asteroid system, referred as the restricted full three-body problem (RF3BP), is fundamental, not only for the evolution of the binary system, but also for the design of relevant space missions. In this paper, equilibrium points and associated periodic orbit families in the gravity of a binary system are investigated, with the binary (66391) 1999 KW4 as an example. The polyhedron shape model is used to describe irregular shapes and corresponding gravity fields of the primary and secondary of (66391) 1999 KW4, which is more accurate than the ellipsoid shape model in previous studies and provides a high-fidelity representation of the gravitational environment. Both of the synchronous and non-synchronous states of the binary system are considered. For the synchronous binary system, the equilibrium points and their stability are determined, and periodic orbit families emanating from each equilibrium point are generated by using the shooting (multiple shooting) method and the homotopy method, where the homotopy function connects the circular restricted three-body problem and RF3BP. In the non-synchronous binary system, trajectories of equivalent equilibrium points are calculated, and the associated periodic orbits are obtained by using the homotopy method, where the homotopy function connects the synchronous and non-synchronous systems. Although only the binary (66391) 1999 KW4 is considered, our methods will also be well applicable to other binary systems with polyhedron shape data. Our results on equilibrium points and associated periodic orbits provide general insights into the dynamical environment and orbital behaviors in proximity of small binary asteroids and enable the trajectory design and mission operations in future binary system explorations.

Wide binaries in Tycho-Gaia II: metallicities, abundances and prospects for chemical tagging

NASA Astrophysics Data System (ADS)

Andrews, Jeff J.; Chanamé, Julio; Agüeros, Marcel A.

2018-02-01

From our recent catalogue based on the first Gaia data release (TGAS), we select wide binaries in which both stars have been observed by the Radial Velocity Experiment (RAVE) or the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). Using RAVE and LAMOST metallicities and RAVE Mg, Al, Si, Ti and Fe abundances, we find that the differences in the metallicities and elemental abundances of components of wide binaries are consistent with being due to observational uncertainties, in agreement with previous results for smaller and more restricted samples. The metallicity and elemental abundance consistency between wide binary components presented in this work confirms their common origin and bolsters the status of wide binaries as 'mini-open clusters'. Furthermore, this is evident that wide binaries are effectively co-eval and co-chemical, supporting their use for, e.g. constraining age-activity-rotation relations, the initial-final mass relation for white dwarfs and M-dwarf metallicity indicators. Additionally, we demonstrate that the common proper motion, common parallax pairs in TGAS with the most extreme separations (s ≳ 0.1 pc) typically have inconsistent metallicities, radial velocities or both and are therefore likely to be predominantly comprised of random alignments of unassociated stars with similar astrometry, in agreement with our previous results. Finally, we propose that wide binaries form an ideal data set with which we can test chemical tagging as a method to identify stars of common origin, particularly because the stars in wide binaries span a wide range of metallicities, much wider than that spanned by nearby open clusters.

Separation in 5 Msun Binaries

NASA Astrophysics Data System (ADS)

Evans, Nancy R.; Bond, H. E.; Schaefer, G.; Mason, B. D.; Karovska, M.; Tingle, E.

2013-01-01

Cepheids (5 Msun stars) provide an excellent sample for determining the binary properties of fairly massive stars. International Ultraviolet Explorer (IUE) observations of Cepheids brighter than 8th magnitude resulted in a list of ALL companions more massive than 2.0 Msun uniformly sensitive to all separations. Hubble Space Telescope Wide Field Camera 3 (WFC3) has resolved three of these binaries (Eta Aql, S Nor, and V659 Cen). Combining these separations with orbital data in the literature, we derive an unbiased distribution of binary separations for a sample of 18 Cepheids, and also a distribution of mass ratios. The distribution of orbital periods shows that the 5 Msun binaries prefer shorter periods than 1 Msun stars, reflecting differences in star formation processes.

Binary grafted chitosan film: Synthesis, characterization, antibacterial activity and prospects for food packaging.

PubMed

Kumar, Deepak; Kumar, Pramendra; Pandey, Jyoti

2018-04-17

The antimicrobial binary grafted chitosan film [chit-g-Poly (An-co-Am)] was prepared by grafting of acrylonitrile and acrylamide on to chitosan via microwave initiated graft copolymerization. The grafting of acrylonitrile and acrylamide onto chitosan backbone was confirmed by FTIR, XRD, SEM and TGA/DTA/DTG analytical techniques. The binary grafted chitosan film possessed efficient antimicrobial activity against three tested strains, i.e. Escherichia coli, Staphylococcus aureus and Pseudomonas aeruginosa. The prepared binary grafted chitosan film was tested for packaging apple and guava to prevent microbial infection and extend their shelf life. The biodegradability study of binary grafted chitosan film was also done and all the results were positive. Copyright © 2018. Published by Elsevier B.V.

Investigación observacional sobre el papel de las estrellas binarias en la ecología de cúmulos estelares

NASA Astrophysics Data System (ADS)

González, J. F.; Levato, H.; Grosso, M.

We present preliminary results of a long-term project devoted to the observational study of the binary star population in open clusters and its connection with the dynamical and evolutionary properties of the clusters. We report the discovery of 17 double-lined spectroscopic binaries, 30 radial velocity variables and about 30 suspected variables. In the 17 clusters of our sample the binary frequency ranges between 20 and 40 %, and reaches typically 60 % if all suspected binaries are included. We study the spatial distribution of the binary stars with respect to the cluster center and we discuss the statistical correlation of the mass-ratio distribution with the cluster age.

Eccentric binaries - still interesting targets

NASA Astrophysics Data System (ADS)

Zasche, P.

2018-04-01

Eccentric binaries still provides us with valuable results and new observations of these systems are welcome. Especially these ones never analysed before should be observed for their light curves and minima.

A VLA radio continuum survey of active late-type giants in binary systems - Preliminary results

NASA Technical Reports Server (NTRS)

Drake, S. A.; Simon, T.; Linsky, J. L.

1985-01-01

Preliminary results of a 6 cm continuum survey using the NRAO VLA of binary systems with 10-100 day orbital period containing an 'active' giant component are reported. The results show that strong radio continuum emission at centimeter wavelengths is a common but not universal property of this class of stars. Possible correlations between radio luminosity and other properties, such as X-ray luminosity, rotational period, and type of companion are discussed. Several binary systems which have been detected for the first time as radio sources are reported, and sensitive upper limits are presented for five other systems, including Capella.

Scattering from binary optics

NASA Technical Reports Server (NTRS)

Ricks, Douglas W.

1993-01-01

There are a number of sources of scattering in binary optics: etch depth errors, line edge errors, quantization errors, roughness, and the binary approximation to the ideal surface. These sources of scattering can be systematic (deterministic) or random. In this paper, scattering formulas for both systematic and random errors are derived using Fourier optics. These formulas can be used to explain the results of scattering measurements and computer simulations.

Dynamics of rotationally fissioned asteroids: Source of observed small asteroid systems

NASA Astrophysics Data System (ADS)

Jacobson, Seth A.; Scheeres, Daniel J.

2011-07-01

We present a model of near-Earth asteroid (NEA) rotational fission and ensuing dynamics that describes the creation of synchronous binaries and all other observed NEA systems including: doubly synchronous binaries, high- e binaries, ternary systems, and contact binaries. Our model only presupposes the Yarkovsky-O'Keefe-Radzievskii-Paddack (YORP) effect, "rubble pile" asteroid geophysics, and gravitational interactions. The YORP effect torques a "rubble pile" asteroid until the asteroid reaches its fission spin limit and the components enter orbit about each other (Scheeres, D.J. [2007]. Icarus 189, 370-385). Non-spherical gravitational potentials couple the spin states to the orbit state and chaotically drive the system towards the observed asteroid classes along two evolutionary tracks primarily distinguished by mass ratio. Related to this is a new binary process termed secondary fission - the secondary asteroid of the binary system is rotationally accelerated via gravitational torques until it fissions, thus creating a chaotic ternary system. The initially chaotic binary can be stabilized to create a synchronous binary by components of the fissioned secondary asteroid impacting the primary asteroid, solar gravitational perturbations, and mutual body tides. These results emphasize the importance of the initial component size distribution and configuration within the parent asteroid. NEAs may go through multiple binary cycles and many YORP-induced rotational fissions during their approximately 10 Myr lifetime in the inner Solar System. Rotational fission and the ensuing dynamics are responsible for all NEA systems including the most commonly observed synchronous binaries.

Black hole binaries dynamically formed in globular clusters

NASA Astrophysics Data System (ADS)

Park, Dawoo; Kim, Chunglee; Lee, Hyung Mok; Bae, Yeong-Bok; Belczynski, Krzysztof

2017-08-01

We investigate properties of black hole (BH) binaries formed in globular clusters via dynamical processes, using directN-body simulations. We pay attention to effects of BH mass function on the total mass and mass ratio distributions of BH binaries ejected from clusters. First, we consider BH populations with two different masses in order to learn basic differences from models with single-mass BHs only. Secondly, we consider continuous BH mass functions adapted from recent studies on massive star evolution in a low metallicity environment, where globular clusters are formed. In this work, we consider only binaries that are formed by three-body processes and ignore stellar evolution and primordial binaries for simplicity. Our results imply that most BH binary mergers take place after they get ejected from the cluster. Also, mass ratios of dynamically formed binaries should be close to 1 or likely to be less than 2:1. Since the binary formation efficiency is larger for higher-mass BHs, it is likely that a BH mass function sampled by gravitational-wave observations would be weighed towards higher masses than the mass function of single BHs for a dynamically formed population. Applying conservative assumptions regarding globular cluster populations such as small BH mass fraction and no primordial binaries, the merger rate of BH binaries originated from globular clusters is estimated to be at least 6.5 yr-1 Gpc-3. Actual rate can be up to more than several times of our conservative estimate.

A three-level model for binary time-series data: the effects of air pollution on school absences in the Southern California Children's Health Study.

PubMed

Rondeau, Virginie; Berhane, Kiros; Thomas, Duncan C

2005-04-15

A three-level model is proposed to simultaneously examine the effects of daily exposure to air pollution and individual risk factors on health outcomes without aggregating over subjects or time. We used a logistic transition model with random effects to take into account heterogeneity and overdispersion of the observations. A distributed lag structure for pollution has been included, assuming that the event on day t for a subject depends on the levels of air pollution for several preceding days. We illustrate this proposed model via detailed analysis of the effect of air pollution on school absenteeism based on data from the Southern California Children's Health Study.

Walk Score(TM), Perceived Neighborhood Walkability, and walking in the US.

PubMed

Tuckel, Peter; Milczarski, William

2015-03-01

To investigate both the Walk Score(TM) and a self-reported measure of neighborhood walkability ("Perceived Neighborhood Walkability") as estimators of transport and recreational walking among Americans. The study is based upon a survey of a nationally-representative sample of 1224 American adults. The survey gauged walking for both transport and recreation and included a self-reported measure of neighborhood walkability and each respondent's Walk Score(TM). Binary logistic and linear regression analyses were performed on the data. The Walk Score(TM) is associated with walking for transport, but not recreational walking nor total walking. Perceived Neighborhood Walkability is associated with transport, recreational and total walking. Perceived Neighborhood Walkability captures the experiential nature of walking more than the Walk Score(TM).

The use of auxiliary variables in capture-recapture and removal experiments

USGS Publications Warehouse

Pollock, K.H.; Hines, J.E.; Nichols, J.D.

1984-01-01

The dependence of animal capture probabilities on auxiliary variables is an important practical problem which has not been considered in the development of estimation procedures for capture-recapture and removal experiments. In this paper the linear logistic binary regression model is used to relate the probability of capture to continuous auxiliary variables. The auxiliary variables could be environmental quantities such as air or water temperature, or characteristics of individual animals, such as body length or weight. Maximum likelihood estimators of the population parameters are considered for a variety of models which all assume a closed population. Testing between models is also considered. The models can also be used when one auxiliary variable is a measure of the effort expended in obtaining the sample.

Analytic gravitational waveforms for generic precessing compact binaries

NASA Astrophysics Data System (ADS)

Chatziioannou, Katerina; Klein, Antoine; Cornish, Neil; Yunes, Nicolas

2017-01-01

Gravitational waves from compact binaries are subject to amplitude and phase modulations arising from interactions between the angular momenta of the system. Failure to account for such spin-precession effects in gravitational wave data analysis could hinder detection and completely ruin parameter estimation. In this talk I will describe the construction of closed-form, frequency-domain waveforms for fully-precessing, quasi-circular binary inspirals. The resulting waveforms can model spinning binaries of arbitrary spin magnitudes, spin orientations, and masses during the inspiral phase. I will also describe ongoing efforts to extend these inspiral waveforms to the merger and ringdown phases.

School Collective Efficacy and Bullying Behaviour: A Multilevel Study.

PubMed

Olsson, Gabriella; Låftman, Sara Brolin; Modin, Bitte

2017-12-20

As with other forms of violent behaviour, bullying is the result of multiple influences acting on different societal levels. Yet the majority of studies on bullying focus primarily on the characteristics of individual bullies and bullied. Fewer studies have explored how the characteristics of central contexts in young people's lives are related to bullying behaviour over and above the influence of individual-level characteristics. This study explores how teacher-rated school collective efficacy is related to student-reported bullying behaviour (traditional and cyberbullying victimization and perpetration). A central focus is to explore if school collective efficacy is related similarly to both traditional bullying and cyberbullying. Analyses are based on combined information from two independent data collections conducted in 2016 among 11th grade students ( n = 6067) and teachers ( n = 1251) in 58 upper secondary schools in Stockholm. The statistical method used is multilevel modelling, estimating two-level binary logistic regression models. The results demonstrate statistically significant between-school differences in all outcomes, except traditional bullying perpetration. Strong school collective efficacy is related to less traditional bullying perpetration and less cyberbullying victimization and perpetration, indicating that collective norm regulation and school social cohesion may contribute to reducing the occurrence of bullying.

School Collective Efficacy and Bullying Behaviour: A Multilevel Study

PubMed Central

Olsson, Gabriella; Låftman, Sara Brolin; Modin, Bitte

2017-01-01

As with other forms of violent behaviour, bullying is the result of multiple influences acting on different societal levels. Yet the majority of studies on bullying focus primarily on the characteristics of individual bullies and bullied. Fewer studies have explored how the characteristics of central contexts in young people’s lives are related to bullying behaviour over and above the influence of individual-level characteristics. This study explores how teacher-rated school collective efficacy is related to student-reported bullying behaviour (traditional and cyberbullying victimization and perpetration). A central focus is to explore if school collective efficacy is related similarly to both traditional bullying and cyberbullying. Analyses are based on combined information from two independent data collections conducted in 2016 among 11th grade students (n = 6067) and teachers (n = 1251) in 58 upper secondary schools in Stockholm. The statistical method used is multilevel modelling, estimating two-level binary logistic regression models. The results demonstrate statistically significant between-school differences in all outcomes, except traditional bullying perpetration. Strong school collective efficacy is related to less traditional bullying perpetration and less cyberbullying victimization and perpetration, indicating that collective norm regulation and school social cohesion may contribute to reducing the occurrence of bullying. PMID:29261114

Low cholesterol level as a risk marker of inpatient and post-discharge violence in acute psychiatry - A prospective study with a focus on gender differences.

PubMed

Eriksen, Bjørn Magne S; Bjørkly, Stål; Lockertsen, Øyvind; Færden, Ann; Roaldset, John Olav

2017-09-01

Several studies indicate an association between low levels of serum cholesterol and aggressive behaviour, but prospective studies are scarce. In this naturalistic prospective inpatient and post-discharge study from an acute psychiatric ward, we investigated total cholesterol (TC) and high-density lipoprotein (HDL) as risk markers of violence. From March 21, 2012, to March 20, 2013, 158 men and 204 women were included. TC and HDL were measured at admission. Violence was recorded during hospital stay and for the first 3 months post-discharge. Univariate and multivariate binary logistic regression were used to estimate associations between low TC and low HDL and violence. Results showed that HDL level was significantly inversely associated with violence during hospital stay for all patients. For men, but not for women, HDL level was significantly inversely associated with violence the first 3 months post-discharge. Results indicate that low HDL is a risk marker for inpatient and post-discharge violence in acute psychiatry and also suggest gender differences in HDL as a risk marker for violence. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

The relationship between meeting of recommendations on physical activity for health and perceived work ability among white-collar workers.

PubMed

Nawrocka, Agnieszka; Garbaciak, Wiesław; Cholewa, Jarosław; Mynarski, Władysław

2018-04-01

The aim of this study was to evaluate the association between meeting recommendations on physical activity for health in leisure-time and the ability to work among Polish white-collar workers. The study used a cross-sectional design with a convenience sample of 360 white-collar workers. Participants recorded 7-day physical activity logs, including form, duration and intensity of leisure-time physical activities. The results were compared to health recommendations. A standardized Work Ability Index (WAI) questionnaire was used in assessing the ability to work. Participants who met health recommendations achieved higher scores of the WAI (mean score = 41.93) in comparison to those who were not sufficiently physically active (mean score = 39.35) (p < .001). The results of binary logistic regression show that meeting health-related physical activity recommendations almost double the odds of reaching at least good work ability (OR = 1.94, 95% CI = 1.12-3.36). Meeting leisure-time physical activity recommendations (especially the criterion of vigorous physical activity) is significantly related to higher self-assessed ability to work among white-collar workers.

Maternal dietary diversity and odds of low birth weight: empirical findings from India.

PubMed

Rammohan, Anu; Goli, Srinivas; Singh, Deepti; Ganguly, Dibyasree; Singh, Uma

2018-06-19

India has the highest proportion of low birth weight (LBW) babies born in the developing world. Poor maternal nutrition during pregnancy is associated with adverse infant health outcomes. The main objective of this paper was to assess the socioeconomic factors associated with dietary diversity among pregnant women and to investigate the association between maternal dietary diversity and LBW among their babies. The data for these analyses were derived from a survey conducted in November and December, 2014 among 230 women who had newly delivered in hospitals in Uttar Pradesh, the largest Indian state which has the poorest maternal outcomes in the country. The results from multivariate binary logistic regression model indicated that low maternal education and economic status was significantly associated with poor dietary diversity among participants. Also, women with low maternal dietary diversity had a significantly higher proportion of LBW babies compared to those in the medium to high dietary diversity categories. From a policy perspective, these findings suggest that continuous tracking of pregnant women's nutritional needs through existing monitoring systems, e.g., the Nutrition Resource Platform and Health Management Information System, and necessary interventions through Integrated Child Development Services may yield better results, thereby, addressing maternal under-nutrition and LBW.

Cognitive function and competitive employment in schizophrenia: relative contribution of insight and psychopathology.

PubMed

Giugiario, Michela; Crivelli, Barbara; Mingrone, Cinzia; Montemagni, Cristiana; Scalese, Mara; Sigaudo, Monica; Rocca, Giuseppe; Rocca, Paola

2012-04-01

This study investigated the relationships among insight, psychopathology, cognitive function, and competitive employment in order to determine whether insight and/or psychopathology carried the influence of cognitive function to competitive employment. We recruited 253 outpatients with stable schizophrenia and we further divided our sample into two groups of patients (unemployed and competitive employment subjects). Clinical and neuropsychological assessments were performed. All clinical variables significantly different between the two groups of subjects were subsequently analyzed using a binary logistic regression to assess their independent contribution to competitive employment in the two patients' groups. On the basis of the regression results two mediation analyses were performed. Verbal memory, general psychopathology, and awareness of mental illness were significantly associated with competitive employment in our sample. Both awareness of mental illness and general psychopathology had a role in mediating the verbal memory-competitive employment relationship. Taken together, these findings confirmed the importance of cognitive function in obtaining competitive employment. Our results also highlighted the independent role of general psychopathology and awareness of illness on occupational functioning in schizophrenia. Thus, a greater attention must be given to the systematic investigation of insight and general psychopathology in light of an amelioration of vocational functioning in stable schizophrenia.

Exploring the impact of signal types and adjacent vehicles on drivers' choices after the onset of yellow

NASA Astrophysics Data System (ADS)

Bao, Ji; Chen, Qun; Luo, Dandan; Wu, Yuli; Liang, Zuli

2018-06-01

Drivers' choices at signalized intersections may be made in great uncertainty after the onset of yellow, which creates potential hazards for road safety. These choices are analyzed and modeled based on field observations at three comparable signalized intersections in Changsha, China. The results show that intersections without monitoring devices widen the indecision zone, which can increase the risk of rear-end collisions and the uncertainty of drivers' decision-making. In addition, drivers are more likely to stop during the yellow interval at intersections equipped with a green signal countdown device (GSCD) than at those with a green signal flashing device (GSFD). Subsequently, according to the results of a binary logistic regression model (BLRM), drivers' decision making at the onset of the yellow indication is greatly influenced by the vehicle's spot speed, the distance to the stop line, and signal and monitoring devices. The presence of an adjacent vehicle with a short space headway can particularly motivate the following driver to make a go-decision after the first driver chooses to pass the intersection. However, a stop-decision by a driver in an adjacent lane can also prompt the following driver to stop.

Fast optimization of binary clusters using a novel dynamic lattice searching method.

PubMed

Wu, Xia; Cheng, Wen

2014-09-28

Global optimization of binary clusters has been a difficult task despite of much effort and many efficient methods. Directing toward two types of elements (i.e., homotop problem) in binary clusters, two classes of virtual dynamic lattices are constructed and a modified dynamic lattice searching (DLS) method, i.e., binary DLS (BDLS) method, is developed. However, it was found that the BDLS can only be utilized for the optimization of binary clusters with small sizes because homotop problem is hard to be solved without atomic exchange operation. Therefore, the iterated local search (ILS) method is adopted to solve homotop problem and an efficient method based on the BDLS method and ILS, named as BDLS-ILS, is presented for global optimization of binary clusters. In order to assess the efficiency of the proposed method, binary Lennard-Jones clusters with up to 100 atoms are investigated. Results show that the method is proved to be efficient. Furthermore, the BDLS-ILS method is also adopted to study the geometrical structures of (AuPd)79 clusters with DFT-fit parameters of Gupta potential.

Alternation blindness in the representation of binary sequences.

PubMed

Yu, Ru Qi; Osherson, Daniel; Zhao, Jiaying

2018-03-01

Binary information is prevalent in the environment and contains 2 distinct outcomes. Binary sequences consist of a mixture of alternation and repetition. Understanding how people perceive such sequences would contribute to a general theory of information processing. In this study, we examined how people process alternation and repetition in binary sequences. Across 4 paradigms involving estimation, working memory, change detection, and visual search, we found that the number of alternations is underestimated compared with repetitions (Experiment 1). Moreover, recall for binary sequences deteriorates as the sequence alternates more (Experiment 2). Changes in bits are also harder to detect as the sequence alternates more (Experiment 3). Finally, visual targets superimposed on bits of a binary sequence take longer to process as alternation increases (Experiment 4). Overall, our results indicate that compared with repetition, alternation in a binary sequence is less salient in the sense of requiring more attention for successful encoding. The current study thus reveals the cognitive constraints in the representation of alternation and provides a new explanation for the overalternation bias in randomness perception. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Orbital period changes of OB-type contact binaries and their implications for the triplicity, formation and evolution of this type of binary stars

NASA Astrophysics Data System (ADS)

Qian, S.-B.; Kreiner, J. M.; Liu, L.; He, J.-J.; Zhu, L.-Y.; Yuan, J.-Z.; Dai, Z.-B.

2007-08-01

Orbital period variations of NINE well-observed OB-type contact binary stars, LY Aur, BH Cen, V382 CYg, V729 Cyg, AW Lac, TU Mus, RZ Pyx, V701 Sco and CT Tau, are investigated in detail. Of the nine systems, V701 Sco and CT Tau are two contact binaries containing twin components with a mass ratio of unit, LY Aur and V729 Cyg have the longest period among contact binary stars (P=4.0 and 6.6 days, respectively), and BH Cen and V701 Sco are the members of two extremely young galactic cluster IC 2994 and NGC 6383. It is discovered that, apart from the two systems with twin components (V701 Sco and CT Tau), the orbital periods of the rest SEVEN binary stars show a long-term increase. This is different from the situations of the late-type (W UMa-type) contact binaries where both secular period increase and decrease are usually encountered, indicating that magnetic field may play an important role in causing the long-term period decrease of W UMa-type contact binary stars. The fact that no long-term continuous period variations were found for V701 Sco and CT Tau may suggest that contact binary with twin components can be in an equilibrium. Based on the rates of period changes (dP/dt) of the SEVEN sample binary stars, statistical relations between dP/dt and orbital period (P) and the mean density of the secondary component were found. Our results suggest that the period increases of the short-period systems (P<2 days) may be mainly caused by a mass transfer from the less massive component to the more massive one, while for the long-period ones (P>2 days), LY Aur and V729 Cyg, their period increases may be resulted from a combination of stellar wind and mass transfer from the secondary to the primary. Meanwhile, cyclic period changes are found for all of the nine binary systems. Those periodic variations can be plausibly explained as the results of light-travel time effects suggesting that they are triple systems. The astrophysical parameters of the tertiary components in the nine systems have been determined. The tertiary components in the seven binaries, BH Cen, V382 Cyg, AW Lac, TU Mus, RZ Pyx, V701 Sco and CT Tau, may be invisible, while those in LY Aur and V729 Cyg may be the fainter visual companions in the two systems. It is possible that the tertiary components in those binaries played an important role for the formations and evolutions of the contact configurations by bringing angular momentum out from the central systems. Thus they have initial short period and can evolve into a contact configuration in a short timescale.

Spectroscopy of Hot Horizontal Branch Stars in Globular Clusters

NASA Astrophysics Data System (ADS)

Moni-Bidin, C. M.

2006-06-01

We will present our latest results on spectroscopy of hot horizontal branch stars in globular clusters. This class of stars still presents many puzzling features, and many aspects of their formation and evolution are still unclear. Extreme Horizontal Branch (EHB) stars, also known as Subdwarf B (sdB) stars, are post-He flash stars with a He-burning core and high effective temperature (T_{eff} ≥ 20000 K). They originate from stars of low initial mass that during their evolution have lost great part of their external envelope. Many channel for the formation of these stars have been studied in literature. The scenarios involving dynamical interactions inside close binary systems, deeply investigated by Han et al. (2003, MNRAS, 341, 669), have been recently preferred, since between field sdB stars many close binary systems have been detected. (Morales-Rueda et al. 2003, MNRAS, 338, 752). Maxted et al. (2001, MNRAS, 326, 1391) estimated that 69+/-9% of field sdB stars are close binary systems. Latest results indicates that also this scenario presents some problems (Lisker et al. 2005, A&A, 430, 223), and Napiwotzki et al. (2004) found a lower fraction of binaries among their sample (42%). Moni Bidin et al. (2005, A&A, submitted) recently showed that in globular cluster NGC6752 the binary fraction among EHB stars is sensibly lower than what observed among field sdBs, estimating an upper limit of 20%. This difference between field and cluster sdBs is quite surprising. We are performing further investigation of these stars extending our search for close binary systems to other two clusters with a rich population of EHB stars. This will allow us to tell if the results on NGC6752 indicate a pecular cluster or the lack of binaries is a common trend of EHB stars in globular clusters. Moreover, with a larger sample we will be able to better estimate the binary fraction, or an upper limit for it. With our contribution we are going to show our results on this investigation that at the moment is still a work in progress.

A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground Test

NASA Technical Reports Server (NTRS)

Messer, Bradley P.

2004-01-01

Propulsion ground test facilities face the daily challenges of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Due to budgetary and schedule constraints, NASA and industry customers are pushing to test more components, for less money, in a shorter period of time. As these new rocket engine component test programs are undertaken, the lack of technology maturity in the test articles, combined with pushing the test facilities capabilities to their limits, tends to lead to an increase in facility breakdowns and unsuccessful tests. Over the last five years Stennis Space Center's propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and broken numerous test facility and test article parts. While various initiatives have been implemented to provide better propulsion test techniques and improve the quality, reliability, and maintainability of goods and parts used in the propulsion test facilities, unexpected failures during testing still occur quite regularly due to the harsh environment in which the propulsion test facilities operate. Previous attempts at modeling the lifecycle of a propulsion component test project have met with little success. Each of the attempts suffered form incomplete or inconsistent data on which to base the models. By focusing on the actual test phase of the tests project rather than the formulation, design or construction phases of the test project, the quality and quantity of available data increases dramatically. A logistic regression model has been developed form the data collected over the last five years, allowing the probability of successfully completing a rocket propulsion component test to be calculated. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),..,X(sub k) to a binary or dichotomous dependent variable Y, where Y can only be one of two possible outcomes, in this case Success or Failure. Logistic regression has primarily been used in the fields of epidemiology and biomedical research, but lends itself to many other applications. As indicated the use of logistic regression is not new, however, modeling propulsion ground test facilities using logistic regression is both a new and unique application of the statistical technique. Results from the models provide project managers with insight and confidence into the affectivity of rocket engine component ground test projects. The initial success in modeling rocket propulsion ground test projects clears the way for more complex models to be developed in this area.