Iterative usage of fixed and random effect models for powerful and efficient genome-wide association studies

USDA-ARS?s Scientific Manuscript database

False positives in a Genome-Wide Association Study (GWAS) can be effectively controlled by a fixed effect and random effect Mixed Linear Model (MLM) that incorporates population structure and kinship among individuals to adjust association tests on markers; however, the adjustment also compromises t...

Sensitivity Analysis of Mixed Models for Incomplete Longitudinal Data

ERIC Educational Resources Information Center

Xu, Shu; Blozis, Shelley A.

2011-01-01

Mixed models are used for the analysis of data measured over time to study population-level change and individual differences in change characteristics. Linear and nonlinear functions may be used to describe a longitudinal response, individuals need not be observed at the same time points, and missing data, assumed to be missing at random (MAR),…

Functional mixed effects spectral analysis

PubMed Central

KRAFTY, ROBERT T.; HALL, MARTICA; GUO, WENSHENG

2011-01-01

SUMMARY In many experiments, time series data can be collected from multiple units and multiple time series segments can be collected from the same unit. This article introduces a mixed effects Cramér spectral representation which can be used to model the effects of design covariates on the second-order power spectrum while accounting for potential correlations among the time series segments collected from the same unit. The transfer function is composed of a deterministic component to account for the population-average effects and a random component to account for the unit-specific deviations. The resulting log-spectrum has a functional mixed effects representation where both the fixed effects and random effects are functions in the frequency domain. It is shown that, when the replicate-specific spectra are smooth, the log-periodograms converge to a functional mixed effects model. A data-driven iterative estimation procedure is offered for the periodic smoothing spline estimation of the fixed effects, penalized estimation of the functional covariance of the random effects, and unit-specific random effects prediction via the best linear unbiased predictor. PMID:26855437

Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies

PubMed Central

Liu, Xiaolei; Huang, Meng; Fan, Bin; Buckler, Edward S.; Zhang, Zhiwu

2016-01-01

False positives in a Genome-Wide Association Study (GWAS) can be effectively controlled by a fixed effect and random effect Mixed Linear Model (MLM) that incorporates population structure and kinship among individuals to adjust association tests on markers; however, the adjustment also compromises true positives. The modified MLM method, Multiple Loci Linear Mixed Model (MLMM), incorporates multiple markers simultaneously as covariates in a stepwise MLM to partially remove the confounding between testing markers and kinship. To completely eliminate the confounding, we divided MLMM into two parts: Fixed Effect Model (FEM) and a Random Effect Model (REM) and use them iteratively. FEM contains testing markers, one at a time, and multiple associated markers as covariates to control false positives. To avoid model over-fitting problem in FEM, the associated markers are estimated in REM by using them to define kinship. The P values of testing markers and the associated markers are unified at each iteration. We named the new method as Fixed and random model Circulating Probability Unification (FarmCPU). Both real and simulated data analyses demonstrated that FarmCPU improves statistical power compared to current methods. Additional benefits include an efficient computing time that is linear to both number of individuals and number of markers. Now, a dataset with half million individuals and half million markers can be analyzed within three days. PMID:26828793

Linear Mixed Models: Gum and Beyond

NASA Astrophysics Data System (ADS)

Arendacká, Barbora; Täubner, Angelika; Eichstädt, Sascha; Bruns, Thomas; Elster, Clemens

2014-04-01

In Annex H.5, the Guide to the Evaluation of Uncertainty in Measurement (GUM) [1] recognizes the necessity to analyze certain types of experiments by applying random effects ANOVA models. These belong to the more general family of linear mixed models that we focus on in the current paper. Extending the short introduction provided by the GUM, our aim is to show that the more general, linear mixed models cover a wider range of situations occurring in practice and can be beneficial when employed in data analysis of long-term repeated experiments. Namely, we point out their potential as an aid in establishing an uncertainty budget and as means for gaining more insight into the measurement process. We also comment on computational issues and to make the explanations less abstract, we illustrate all the concepts with the help of a measurement campaign conducted in order to challenge the uncertainty budget in calibration of accelerometers.

Random effects coefficient of determination for mixed and meta-analysis models

PubMed Central

Demidenko, Eugene; Sargent, James; Onega, Tracy

2011-01-01

The key feature of a mixed model is the presence of random effects. We have developed a coefficient, called the random effects coefficient of determination, Rr2, that estimates the proportion of the conditional variance of the dependent variable explained by random effects. This coefficient takes values from 0 to 1 and indicates how strong the random effects are. The difference from the earlier suggested fixed effects coefficient of determination is emphasized. If Rr2 is close to 0, there is weak support for random effects in the model because the reduction of the variance of the dependent variable due to random effects is small; consequently, random effects may be ignored and the model simplifies to standard linear regression. The value of Rr2 apart from 0 indicates the evidence of the variance reduction in support of the mixed model. If random effects coefficient of determination is close to 1 the variance of random effects is very large and random effects turn into free fixed effects—the model can be estimated using the dummy variable approach. We derive explicit formulas for Rr2 in three special cases: the random intercept model, the growth curve model, and meta-analysis model. Theoretical results are illustrated with three mixed model examples: (1) travel time to the nearest cancer center for women with breast cancer in the U.S., (2) cumulative time watching alcohol related scenes in movies among young U.S. teens, as a risk factor for early drinking onset, and (3) the classic example of the meta-analysis model for combination of 13 studies on tuberculosis vaccine. PMID:23750070

Multi-disease analysis of maternal antibody decay using non-linear mixed models accounting for censoring.

PubMed

Goeyvaerts, Nele; Leuridan, Elke; Faes, Christel; Van Damme, Pierre; Hens, Niel

2015-09-10

Biomedical studies often generate repeated measures of multiple outcomes on a set of subjects. It may be of interest to develop a biologically intuitive model for the joint evolution of these outcomes while assessing inter-subject heterogeneity. Even though it is common for biological processes to entail non-linear relationships, examples of multivariate non-linear mixed models (MNMMs) are still fairly rare. We contribute to this area by jointly analyzing the maternal antibody decay for measles, mumps, rubella, and varicella, allowing for a different non-linear decay model for each infectious disease. We present a general modeling framework to analyze multivariate non-linear longitudinal profiles subject to censoring, by combining multivariate random effects, non-linear growth and Tobit regression. We explore the hypothesis of a common infant-specific mechanism underlying maternal immunity using a pairwise correlated random-effects approach and evaluating different correlation matrix structures. The implied marginal correlation between maternal antibody levels is estimated using simulations. The mean duration of passive immunity was less than 4 months for all diseases with substantial heterogeneity between infants. The maternal antibody levels against rubella and varicella were found to be positively correlated, while little to no correlation could be inferred for the other disease pairs. For some pairs, computational issues occurred with increasing correlation matrix complexity, which underlines the importance of further developing estimation methods for MNMMs. Copyright © 2015 John Wiley & Sons, Ltd.

Log-gamma linear-mixed effects models for multiple outcomes with application to a longitudinal glaucoma study

PubMed Central

Zhang, Peng; Luo, Dandan; Li, Pengfei; Sharpsten, Lucie; Medeiros, Felipe A.

2015-01-01

Glaucoma is a progressive disease due to damage in the optic nerve with associated functional losses. Although the relationship between structural and functional progression in glaucoma is well established, there is disagreement on how this association evolves over time. In addressing this issue, we propose a new class of non-Gaussian linear-mixed models to estimate the correlations among subject-specific effects in multivariate longitudinal studies with a skewed distribution of random effects, to be used in a study of glaucoma. This class provides an efficient estimation of subject-specific effects by modeling the skewed random effects through the log-gamma distribution. It also provides more reliable estimates of the correlations between the random effects. To validate the log-gamma assumption against the usual normality assumption of the random effects, we propose a lack-of-fit test using the profile likelihood function of the shape parameter. We apply this method to data from a prospective observation study, the Diagnostic Innovations in Glaucoma Study, to present a statistically significant association between structural and functional change rates that leads to a better understanding of the progression of glaucoma over time. PMID:26075565

Mixed models, linear dependency, and identification in age-period-cohort models.

PubMed

O'Brien, Robert M

2017-07-20

This paper examines the identification problem in age-period-cohort models that use either linear or categorically coded ages, periods, and cohorts or combinations of these parameterizations. These models are not identified using the traditional fixed effect regression model approach because of a linear dependency between the ages, periods, and cohorts. However, these models can be identified if the researcher introduces a single just identifying constraint on the model coefficients. The problem with such constraints is that the results can differ substantially depending on the constraint chosen. Somewhat surprisingly, age-period-cohort models that specify one or more of ages and/or periods and/or cohorts as random effects are identified. This is the case without introducing an additional constraint. I label this identification as statistical model identification and show how statistical model identification comes about in mixed models and why which effects are treated as fixed and which are treated as random can substantially change the estimates of the age, period, and cohort effects. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Linear mixed model for heritability estimation that explicitly addresses environmental variation.

PubMed

Heckerman, David; Gurdasani, Deepti; Kadie, Carl; Pomilla, Cristina; Carstensen, Tommy; Martin, Hilary; Ekoru, Kenneth; Nsubuga, Rebecca N; Ssenyomo, Gerald; Kamali, Anatoli; Kaleebu, Pontiano; Widmer, Christian; Sandhu, Manjinder S

2016-07-05

The linear mixed model (LMM) is now routinely used to estimate heritability. Unfortunately, as we demonstrate, LMM estimates of heritability can be inflated when using a standard model. To help reduce this inflation, we used a more general LMM with two random effects-one based on genomic variants and one based on easily measured spatial location as a proxy for environmental effects. We investigated this approach with simulated data and with data from a Uganda cohort of 4,778 individuals for 34 phenotypes including anthropometric indices, blood factors, glycemic control, blood pressure, lipid tests, and liver function tests. For the genomic random effect, we used identity-by-descent estimates from accurately phased genome-wide data. For the environmental random effect, we constructed a covariance matrix based on a Gaussian radial basis function. Across the simulated and Ugandan data, narrow-sense heritability estimates were lower using the more general model. Thus, our approach addresses, in part, the issue of "missing heritability" in the sense that much of the heritability previously thought to be missing was fictional. Software is available at https://github.com/MicrosoftGenomics/FaST-LMM.

Random effects coefficient of determination for mixed and meta-analysis models.

PubMed

Demidenko, Eugene; Sargent, James; Onega, Tracy

2012-01-01

The key feature of a mixed model is the presence of random effects. We have developed a coefficient, called the random effects coefficient of determination, [Formula: see text], that estimates the proportion of the conditional variance of the dependent variable explained by random effects. This coefficient takes values from 0 to 1 and indicates how strong the random effects are. The difference from the earlier suggested fixed effects coefficient of determination is emphasized. If [Formula: see text] is close to 0, there is weak support for random effects in the model because the reduction of the variance of the dependent variable due to random effects is small; consequently, random effects may be ignored and the model simplifies to standard linear regression. The value of [Formula: see text] apart from 0 indicates the evidence of the variance reduction in support of the mixed model. If random effects coefficient of determination is close to 1 the variance of random effects is very large and random effects turn into free fixed effects-the model can be estimated using the dummy variable approach. We derive explicit formulas for [Formula: see text] in three special cases: the random intercept model, the growth curve model, and meta-analysis model. Theoretical results are illustrated with three mixed model examples: (1) travel time to the nearest cancer center for women with breast cancer in the U.S., (2) cumulative time watching alcohol related scenes in movies among young U.S. teens, as a risk factor for early drinking onset, and (3) the classic example of the meta-analysis model for combination of 13 studies on tuberculosis vaccine.

Linear mixed-effects models to describe individual tree crown width for China-fir in Fujian Province, southeast China.

PubMed

Hao, Xu; Yujun, Sun; Xinjie, Wang; Jin, Wang; Yao, Fu

2015-01-01

A multiple linear model was developed for individual tree crown width of Cunninghamia lanceolata (Lamb.) Hook in Fujian province, southeast China. Data were obtained from 55 sample plots of pure China-fir plantation stands. An Ordinary Linear Least Squares (OLS) regression was used to establish the crown width model. To adjust for correlations between observations from the same sample plots, we developed one level linear mixed-effects (LME) models based on the multiple linear model, which take into account the random effects of plots. The best random effects combinations for the LME models were determined by the Akaike's information criterion, the Bayesian information criterion and the -2logarithm likelihood. Heteroscedasticity was reduced by three residual variance functions: the power function, the exponential function and the constant plus power function. The spatial correlation was modeled by three correlation structures: the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)], and the compound symmetry structure (CS). Then, the LME model was compared to the multiple linear model using the absolute mean residual (AMR), the root mean square error (RMSE), and the adjusted coefficient of determination (adj-R2). For individual tree crown width models, the one level LME model showed the best performance. An independent dataset was used to test the performance of the models and to demonstrate the advantage of calibrating LME models.

Ternary mixed crystal effects on interface optical phonon and electron-phonon coupling in zinc-blende GaN/AlxGa1-xN spherical quantum dots

NASA Astrophysics Data System (ADS)

Huang, Wen Deng; Chen, Guang De; Yuan, Zhao Lin; Yang, Chuang Hua; Ye, Hong Gang; Wu, Ye Long

2016-02-01

The theoretical investigations of the interface optical phonons, electron-phonon couplings and its ternary mixed effects in zinc-blende spherical quantum dots are obtained by using the dielectric continuum model and modified random-element isodisplacement model. The features of dispersion curves, electron-phonon coupling strengths, and its ternary mixed effects for interface optical phonons in a single zinc-blende GaN/AlxGa1-xN spherical quantum dot are calculated and discussed in detail. The numerical results show that there are three branches of interface optical phonons. One branch exists in low frequency region; another two branches exist in high frequency region. The interface optical phonons with small quantum number l have more important contributions to the electron-phonon interactions. It is also found that ternary mixed effects have important influences on the interface optical phonon properties in a single zinc-blende GaN/AlxGa1-xN quantum dot. With the increase of Al component, the interface optical phonon frequencies appear linear changes, and the electron-phonon coupling strengths appear non-linear changes in high frequency region. But in low frequency region, the frequencies appear non-linear changes, and the electron-phonon coupling strengths appear linear changes.

Detecting treatment-subgroup interactions in clustered data with generalized linear mixed-effects model trees.

PubMed

Fokkema, M; Smits, N; Zeileis, A; Hothorn, T; Kelderman, H

2017-10-25

Identification of subgroups of patients for whom treatment A is more effective than treatment B, and vice versa, is of key importance to the development of personalized medicine. Tree-based algorithms are helpful tools for the detection of such interactions, but none of the available algorithms allow for taking into account clustered or nested dataset structures, which are particularly common in psychological research. Therefore, we propose the generalized linear mixed-effects model tree (GLMM tree) algorithm, which allows for the detection of treatment-subgroup interactions, while accounting for the clustered structure of a dataset. The algorithm uses model-based recursive partitioning to detect treatment-subgroup interactions, and a GLMM to estimate the random-effects parameters. In a simulation study, GLMM trees show higher accuracy in recovering treatment-subgroup interactions, higher predictive accuracy, and lower type II error rates than linear-model-based recursive partitioning and mixed-effects regression trees. Also, GLMM trees show somewhat higher predictive accuracy than linear mixed-effects models with pre-specified interaction effects, on average. We illustrate the application of GLMM trees on an individual patient-level data meta-analysis on treatments for depression. We conclude that GLMM trees are a promising exploratory tool for the detection of treatment-subgroup interactions in clustered datasets.

Real longitudinal data analysis for real people: building a good enough mixed model.

PubMed

Cheng, Jing; Edwards, Lloyd J; Maldonado-Molina, Mildred M; Komro, Kelli A; Muller, Keith E

2010-02-20

Mixed effects models have become very popular, especially for the analysis of longitudinal data. One challenge is how to build a good enough mixed effects model. In this paper, we suggest a systematic strategy for addressing this challenge and introduce easily implemented practical advice to build mixed effects models. A general discussion of the scientific strategies motivates the recommended five-step procedure for model fitting. The need to model both the mean structure (the fixed effects) and the covariance structure (the random effects and residual error) creates the fundamental flexibility and complexity. Some very practical recommendations help to conquer the complexity. Centering, scaling, and full-rank coding of all the predictor variables radically improve the chances of convergence, computing speed, and numerical accuracy. Applying computational and assumption diagnostics from univariate linear models to mixed model data greatly helps to detect and solve the related computational problems. Applying computational and assumption diagnostics from the univariate linear models to the mixed model data can radically improve the chances of convergence, computing speed, and numerical accuracy. The approach helps to fit more general covariance models, a crucial step in selecting a credible covariance model needed for defensible inference. A detailed demonstration of the recommended strategy is based on data from a published study of a randomized trial of a multicomponent intervention to prevent young adolescents' alcohol use. The discussion highlights a need for additional covariance and inference tools for mixed models. The discussion also highlights the need for improving how scientists and statisticians teach and review the process of finding a good enough mixed model. (c) 2009 John Wiley & Sons, Ltd.

Conditional Monte Carlo randomization tests for regression models.

PubMed

Parhat, Parwen; Rosenberger, William F; Diao, Guoqing

2014-08-15

We discuss the computation of randomization tests for clinical trials of two treatments when the primary outcome is based on a regression model. We begin by revisiting the seminal paper of Gail, Tan, and Piantadosi (1988), and then describe a method based on Monte Carlo generation of randomization sequences. The tests based on this Monte Carlo procedure are design based, in that they incorporate the particular randomization procedure used. We discuss permuted block designs, complete randomization, and biased coin designs. We also use a new technique by Plamadeala and Rosenberger (2012) for simple computation of conditional randomization tests. Like Gail, Tan, and Piantadosi, we focus on residuals from generalized linear models and martingale residuals from survival models. Such techniques do not apply to longitudinal data analysis, and we introduce a method for computation of randomization tests based on the predicted rate of change from a generalized linear mixed model when outcomes are longitudinal. We show, by simulation, that these randomization tests preserve the size and power well under model misspecification. Copyright © 2014 John Wiley & Sons, Ltd.

Log-normal frailty models fitted as Poisson generalized linear mixed models.

PubMed

Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver

2016-12-01

The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Central Limit Theorem for Exponentially Quasi-local Statistics of Spin Models on Cayley Graphs

NASA Astrophysics Data System (ADS)

Reddy, Tulasi Ram; Vadlamani, Sreekar; Yogeshwaran, D.

2018-04-01

Central limit theorems for linear statistics of lattice random fields (including spin models) are usually proven under suitable mixing conditions or quasi-associativity. Many interesting examples of spin models do not satisfy mixing conditions, and on the other hand, it does not seem easy to show central limit theorem for local statistics via quasi-associativity. In this work, we prove general central limit theorems for local statistics and exponentially quasi-local statistics of spin models on discrete Cayley graphs with polynomial growth. Further, we supplement these results by proving similar central limit theorems for random fields on discrete Cayley graphs taking values in a countable space, but under the stronger assumptions of α -mixing (for local statistics) and exponential α -mixing (for exponentially quasi-local statistics). All our central limit theorems assume a suitable variance lower bound like many others in the literature. We illustrate our general central limit theorem with specific examples of lattice spin models and statistics arising in computational topology, statistical physics and random networks. Examples of clustering spin models include quasi-associated spin models with fast decaying covariances like the off-critical Ising model, level sets of Gaussian random fields with fast decaying covariances like the massive Gaussian free field and determinantal point processes with fast decaying kernels. Examples of local statistics include intrinsic volumes, face counts, component counts of random cubical complexes while exponentially quasi-local statistics include nearest neighbour distances in spin models and Betti numbers of sub-critical random cubical complexes.

The Bayesian group lasso for confounded spatial data

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin E.; Walsh, Daniel P.

2017-01-01

Generalized linear mixed models for spatial processes are widely used in applied statistics. In many applications of the spatial generalized linear mixed model (SGLMM), the goal is to obtain inference about regression coefficients while achieving optimal predictive ability. When implementing the SGLMM, multicollinearity among covariates and the spatial random effects can make computation challenging and influence inference. We present a Bayesian group lasso prior with a single tuning parameter that can be chosen to optimize predictive ability of the SGLMM and jointly regularize the regression coefficients and spatial random effect. We implement the group lasso SGLMM using efficient Markov chain Monte Carlo (MCMC) algorithms and demonstrate how multicollinearity among covariates and the spatial random effect can be monitored as a derived quantity. To test our method, we compared several parameterizations of the SGLMM using simulated data and two examples from plant ecology and disease ecology. In all examples, problematic levels multicollinearity occurred and influenced sampling efficiency and inference. We found that the group lasso prior resulted in roughly twice the effective sample size for MCMC samples of regression coefficients and can have higher and less variable predictive accuracy based on out-of-sample data when compared to the standard SGLMM.

Solving large mixed linear models using preconditioned conjugate gradient iteration.

PubMed

Strandén, I; Lidauer, M

1999-12-01

Continuous evaluation of dairy cattle with a random regression test-day model requires a fast solving method and algorithm. A new computing technique feasible in Jacobi and conjugate gradient based iterative methods using iteration on data is presented. In the new computing technique, the calculations in multiplication of a vector by a matrix were recorded to three steps instead of the commonly used two steps. The three-step method was implemented in a general mixed linear model program that used preconditioned conjugate gradient iteration. Performance of this program in comparison to other general solving programs was assessed via estimation of breeding values using univariate, multivariate, and random regression test-day models. Central processing unit time per iteration with the new three-step technique was, at best, one-third that needed with the old technique. Performance was best with the test-day model, which was the largest and most complex model used. The new program did well in comparison to other general software. Programs keeping the mixed model equations in random access memory required at least 20 and 435% more time to solve the univariate and multivariate animal models, respectively. Computations of the second best iteration on data took approximately three and five times longer for the animal and test-day models, respectively, than did the new program. Good performance was due to fast computing time per iteration and quick convergence to the final solutions. Use of preconditioned conjugate gradient based methods in solving large breeding value problems is supported by our findings.

Genetic mixed linear models for twin survival data.

PubMed

Ha, Il Do; Lee, Youngjo; Pawitan, Yudi

2007-07-01

Twin studies are useful for assessing the relative importance of genetic or heritable component from the environmental component. In this paper we develop a methodology to study the heritability of age-at-onset or lifespan traits, with application to analysis of twin survival data. Due to limited period of observation, the data can be left truncated and right censored (LTRC). Under the LTRC setting we propose a genetic mixed linear model, which allows general fixed predictors and random components to capture genetic and environmental effects. Inferences are based upon the hierarchical-likelihood (h-likelihood), which provides a statistically efficient and unified framework for various mixed-effect models. We also propose a simple and fast computation method for dealing with large data sets. The method is illustrated by the survival data from the Swedish Twin Registry. Finally, a simulation study is carried out to evaluate its performance.

Scaling Laws of Nonlinear Rayleigh-Taylor and Richtmyer-Meshkov Instabilities in Two and Three Dimensions (IFSA 1999)

NASA Astrophysics Data System (ADS)

Shvarts, D.; Oron, D.; Kartoon, D.; Rikanati, A.; Sadot, O.; Srebro, Y.; Yedvab, Y.; Ofer, D.; Levin, A.; Sarid, E.; Ben-Dor, G.; Erez, L.; Erez, G.; Yosef-Hai, A.; Alon, U.; Arazi, L.

2016-10-01

The late-time nonlinear evolution of the Rayleigh-Taylor (RT) and Richtmyer-Meshkov (RM) instabilities for random initial perturbations is investigated using a statistical mechanics model based on single-mode and bubble-competition physics at all Atwood numbers (A) and full numerical simulations in two and three dimensions. It is shown that the RT mixing zone bubble and spike fronts evolve as h ~ α · A · gt2 with different values of a for the bubble and spike fronts. The RM mixing zone fronts evolve as h ~ tθ with different values of θ for bubbles and spikes. Similar analysis yields a linear growth with time of the Kelvin-Helmholtz mixing zone. The dependence of the RT and RM scaling parameters on A and the dimensionality will be discussed. The 3D predictions are found to be in good agreement with recent Linear Electric Motor (LEM) experiments.

Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.

PubMed

Grajeda, Laura M; Ivanescu, Andrada; Saito, Mayuko; Crainiceanu, Ciprian; Jaganath, Devan; Gilman, Robert H; Crabtree, Jean E; Kelleher, Dermott; Cabrera, Lilia; Cama, Vitaliano; Checkley, William

2016-01-01

Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p < 0.001) when using a linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p < 0.001) and slopes (p < 0.001) of the individual growth trajectories. We also identified important serial correlation within the structure of the data (ρ = 0.66; 95 % CI 0.64 to 0.68; p < 0.001), which we modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19,598, respectively). While the regression parameters are more complex to interpret in the former, we argue that inference for any problem depends more on the estimated curve or differences in curves rather than the coefficients. Moreover, use of cubic regression splines provides biological meaningful growth velocity and acceleration curves despite increased complexity in coefficient interpretation. Through this stepwise approach, we provide a set of tools to model longitudinal childhood data for non-statisticians using linear mixed-effect models.

Linear mixed-effects models to describe length-weight relationships for yellow croaker (Larimichthys Polyactis) along the north coast of China.

PubMed

Ma, Qiuyun; Jiao, Yan; Ren, Yiping

2017-01-01

In this study, length-weight relationships and relative condition factors were analyzed for Yellow Croaker (Larimichthys polyactis) along the north coast of China. Data covered six regions from north to south: Yellow River Estuary, Coastal Waters of Northern Shandong, Jiaozhou Bay, Coastal Waters of Qingdao, Haizhou Bay, and South Yellow Sea. In total 3,275 individuals were collected during six years (2008, 2011-2015). One generalized linear model, two simply linear models and nine linear mixed effect models that applied the effects from regions and/or years to coefficient a and/or the exponent b were studied and compared. Among these twelve models, the linear mixed effect model with random effects from both regions and years fit the data best, with lowest Akaike information criterion value and mean absolute error. In this model, the estimated a was 0.0192, with 95% confidence interval 0.0178~0.0308, and the estimated exponent b was 2.917 with 95% confidence interval 2.731~2.945. Estimates for a and b with the random effects in intercept and coefficient from Region and Year, ranged from 0.013 to 0.023 and from 2.835 to 3.017, respectively. Both regions and years had effects on parameters a and b, while the effects from years were shown to be much larger than those from regions. Except for Coastal Waters of Northern Shandong, a decreased from north to south. Condition factors relative to reference years of 1960, 1986, 2005, 2007, 2008~2009 and 2010 revealed that the body shape of Yellow Croaker became thinner in recent years. Furthermore relative condition factors varied among months, years, regions and length. The values of a and relative condition factors decreased, when the environmental pollution became worse, therefore, length-weight relationships could be an indicator for the environment quality. Results from this study provided basic description of current condition of Yellow Croaker along the north coast of China.

Bayesian inference for two-part mixed-effects model using skew distributions, with application to longitudinal semicontinuous alcohol data.

PubMed

Xing, Dongyuan; Huang, Yangxin; Chen, Henian; Zhu, Yiliang; Dagne, Getachew A; Baldwin, Julie

2017-08-01

Semicontinuous data featured with an excessive proportion of zeros and right-skewed continuous positive values arise frequently in practice. One example would be the substance abuse/dependence symptoms data for which a substantial proportion of subjects investigated may report zero. Two-part mixed-effects models have been developed to analyze repeated measures of semicontinuous data from longitudinal studies. In this paper, we propose a flexible two-part mixed-effects model with skew distributions for correlated semicontinuous alcohol data under the framework of a Bayesian approach. The proposed model specification consists of two mixed-effects models linked by the correlated random effects: (i) a model on the occurrence of positive values using a generalized logistic mixed-effects model (Part I); and (ii) a model on the intensity of positive values using a linear mixed-effects model where the model errors follow skew distributions including skew- t and skew-normal distributions (Part II). The proposed method is illustrated with an alcohol abuse/dependence symptoms data from a longitudinal observational study, and the analytic results are reported by comparing potential models under different random-effects structures. Simulation studies are conducted to assess the performance of the proposed models and method.

An Efficient Test for Gene-Environment Interaction in Generalized Linear Mixed Models with Family Data.

PubMed

Mazo Lopera, Mauricio A; Coombes, Brandon J; de Andrade, Mariza

2017-09-27

Gene-environment (GE) interaction has important implications in the etiology of complex diseases that are caused by a combination of genetic factors and environment variables. Several authors have developed GE analysis in the context of independent subjects or longitudinal data using a gene-set. In this paper, we propose to analyze GE interaction for discrete and continuous phenotypes in family studies by incorporating the relatedness among the relatives for each family into a generalized linear mixed model (GLMM) and by using a gene-based variance component test. In addition, we deal with collinearity problems arising from linkage disequilibrium among single nucleotide polymorphisms (SNPs) by considering their coefficients as random effects under the null model estimation. We show that the best linear unbiased predictor (BLUP) of such random effects in the GLMM is equivalent to the ridge regression estimator. This equivalence provides a simple method to estimate the ridge penalty parameter in comparison to other computationally-demanding estimation approaches based on cross-validation schemes. We evaluated the proposed test using simulation studies and applied it to real data from the Baependi Heart Study consisting of 76 families. Using our approach, we identified an interaction between BMI and the Peroxisome Proliferator Activated Receptor Gamma ( PPARG ) gene associated with diabetes.

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.

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications

PubMed Central

Austin, Peter C.

2017-01-01

Summary Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log–log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata). PMID:29307954

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications.

PubMed

Austin, Peter C

2017-08-01

Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log-log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata).

Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach.

PubMed

Chandrasekar, A; Rakkiyappan, R; Cao, Jinde

2015-10-01

This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is governed by Bernoulli random variable. The aim of this paper is to obtain the synchronization criteria, which is suitable for both exactly known and partly unknown transition probabilities such that the coupled neural network is synchronized with mixed time-delay. The considered impulsive effects can be synchronized at partly unknown transition probabilities. Besides, a multiple integral approach is also proposed to strengthen the Markovian jumping randomly coupled neural networks with partly unknown transition probabilities. By making use of Kronecker product and some useful integral inequalities, a novel Lyapunov-Krasovskii functional was designed for handling the coupled neural network with mixed delay and then impulsive synchronization criteria are solvable in a set of linear matrix inequalities. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Correcting for population structure and kinship using the linear mixed model: theory and extensions.

PubMed

Hoffman, Gabriel E

2013-01-01

Population structure and kinship are widespread confounding factors in genome-wide association studies (GWAS). It has been standard practice to include principal components of the genotypes in a regression model in order to account for population structure. More recently, the linear mixed model (LMM) has emerged as a powerful method for simultaneously accounting for population structure and kinship. The statistical theory underlying the differences in empirical performance between modeling principal components as fixed versus random effects has not been thoroughly examined. We undertake an analysis to formalize the relationship between these widely used methods and elucidate the statistical properties of each. Moreover, we introduce a new statistic, effective degrees of freedom, that serves as a metric of model complexity and a novel low rank linear mixed model (LRLMM) to learn the dimensionality of the correction for population structure and kinship, and we assess its performance through simulations. A comparison of the results of LRLMM and a standard LMM analysis applied to GWAS data from the Multi-Ethnic Study of Atherosclerosis (MESA) illustrates how our theoretical results translate into empirical properties of the mixed model. Finally, the analysis demonstrates the ability of the LRLMM to substantially boost the strength of an association for HDL cholesterol in Europeans.

Using a generalized linear mixed model approach to explore the role of age, motor proficiency, and cognitive styles in children's reach estimation accuracy.

PubMed

Caçola, Priscila M; Pant, Mohan D

2014-10-01

The purpose was to use a multi-level statistical technique to analyze how children's age, motor proficiency, and cognitive styles interact to affect accuracy on reach estimation tasks via Motor Imagery and Visual Imagery. Results from the Generalized Linear Mixed Model analysis (GLMM) indicated that only the 7-year-old age group had significant random intercepts for both tasks. Motor proficiency predicted accuracy in reach tasks, and cognitive styles (object scale) predicted accuracy in the motor imagery task. GLMM analysis is suitable to explore age and other parameters of development. In this case, it allowed an assessment of motor proficiency interacting with age to shape how children represent, plan, and act on the environment.

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages.

PubMed

Kim, Yoonsang; Choi, Young-Ku; Emery, Sherry

2013-08-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods' performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages-SAS GLIMMIX Laplace and SuperMix Gaussian quadrature-perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes.

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages

PubMed Central

Kim, Yoonsang; Emery, Sherry

2013-01-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods’ performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages—SAS GLIMMIX Laplace and SuperMix Gaussian quadrature—perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes. PMID:24288415

Small area estimation for semicontinuous data.

PubMed

Chandra, Hukum; Chambers, Ray

2016-03-01

Survey data often contain measurements for variables that are semicontinuous in nature, i.e. they either take a single fixed value (we assume this is zero) or they have a continuous, often skewed, distribution on the positive real line. Standard methods for small area estimation (SAE) based on the use of linear mixed models can be inefficient for such variables. We discuss SAE techniques for semicontinuous variables under a two part random effects model that allows for the presence of excess zeros as well as the skewed nature of the nonzero values of the response variable. In particular, we first model the excess zeros via a generalized linear mixed model fitted to the probability of a nonzero, i.e. strictly positive, value being observed, and then model the response, given that it is strictly positive, using a linear mixed model fitted on the logarithmic scale. Empirical results suggest that the proposed method leads to efficient small area estimates for semicontinuous data of this type. We also propose a parametric bootstrap method to estimate the MSE of the proposed small area estimator. These bootstrap estimates of the MSE are compared to the true MSE in a simulation study. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Isolating the cow-specific part of residual energy intake in lactating dairy cows using random regressions.

PubMed

Fischer, A; Friggens, N C; Berry, D P; Faverdin, P

2018-07-01

The ability to properly assess and accurately phenotype true differences in feed efficiency among dairy cows is key to the development of breeding programs for improving feed efficiency. The variability among individuals in feed efficiency is commonly characterised by the residual intake approach. Residual feed intake is represented by the residuals of a linear regression of intake on the corresponding quantities of the biological functions that consume (or release) energy. However, the residuals include both, model fitting and measurement errors as well as any variability in cow efficiency. The objective of this study was to isolate the individual animal variability in feed efficiency from the residual component. Two separate models were fitted, in one the standard residual energy intake (REI) was calculated as the residual of a multiple linear regression of lactation average net energy intake (NEI) on lactation average milk energy output, average metabolic BW, as well as lactation loss and gain of body condition score. In the other, a linear mixed model was used to simultaneously fit fixed linear regressions and random cow levels on the biological traits and intercept using fortnight repeated measures for the variables. This method split the predicted NEI in two parts: one quantifying the population mean intercept and coefficients, and one quantifying cow-specific deviations in the intercept and coefficients. The cow-specific part of predicted NEI was assumed to isolate true differences in feed efficiency among cows. NEI and associated energy expenditure phenotypes were available for the first 17 fortnights of lactation from 119 Holstein cows; all fed a constant energy-rich diet. Mixed models fitting cow-specific intercept and coefficients to different combinations of the aforementioned energy expenditure traits, calculated on a fortnightly basis, were compared. The variance of REI estimated with the lactation average model represented only 8% of the variance of measured NEI. Among all compared mixed models, the variance of the cow-specific part of predicted NEI represented between 53% and 59% of the variance of REI estimated from the lactation average model or between 4% and 5% of the variance of measured NEI. The remaining 41% to 47% of the variance of REI estimated with the lactation average model may therefore reflect model fitting errors or measurement errors. In conclusion, the use of a mixed model framework with cow-specific random regressions seems to be a promising method to isolate the cow-specific component of REI in dairy cows.

[Primary branch size of Pinus koraiensis plantation: a prediction based on linear mixed effect model].

PubMed

Dong, Ling-Bo; Liu, Zhao-Gang; Li, Feng-Ri; Jiang, Li-Chun

2013-09-01

By using the branch analysis data of 955 standard branches from 60 sampled trees in 12 sampling plots of Pinus koraiensis plantation in Mengjiagang Forest Farm in Heilongjiang Province of Northeast China, and based on the linear mixed-effect model theory and methods, the models for predicting branch variables, including primary branch diameter, length, and angle, were developed. Considering tree effect, the MIXED module of SAS software was used to fit the prediction models. The results indicated that the fitting precision of the models could be improved by choosing appropriate random-effect parameters and variance-covariance structure. Then, the correlation structures including complex symmetry structure (CS), first-order autoregressive structure [AR(1)], and first-order autoregressive and moving average structure [ARMA(1,1)] were added to the optimal branch size mixed-effect model. The AR(1) improved the fitting precision of branch diameter and length mixed-effect model significantly, but all the three structures didn't improve the precision of branch angle mixed-effect model. In order to describe the heteroscedasticity during building mixed-effect model, the CF1 and CF2 functions were added to the branch mixed-effect model. CF1 function improved the fitting effect of branch angle mixed model significantly, whereas CF2 function improved the fitting effect of branch diameter and length mixed model significantly. Model validation confirmed that the mixed-effect model could improve the precision of prediction, as compare to the traditional regression model for the branch size prediction of Pinus koraiensis plantation.

Using empirical Bayes predictors from generalized linear mixed models to test and visualize associations among longitudinal outcomes.

PubMed

Mikulich-Gilbertson, Susan K; Wagner, Brandie D; Grunwald, Gary K; Riggs, Paula D; Zerbe, Gary O

2018-01-01

Medical research is often designed to investigate changes in a collection of response variables that are measured repeatedly on the same subjects. The multivariate generalized linear mixed model (MGLMM) can be used to evaluate random coefficient associations (e.g. simple correlations, partial regression coefficients) among outcomes that may be non-normal and differently distributed by specifying a multivariate normal distribution for their random effects and then evaluating the latent relationship between them. Empirical Bayes predictors are readily available for each subject from any mixed model and are observable and hence, plotable. Here, we evaluate whether second-stage association analyses of empirical Bayes predictors from a MGLMM, provide a good approximation and visual representation of these latent association analyses using medical examples and simulations. Additionally, we compare these results with association analyses of empirical Bayes predictors generated from separate mixed models for each outcome, a procedure that could circumvent computational problems that arise when the dimension of the joint covariance matrix of random effects is large and prohibits estimation of latent associations. As has been shown in other analytic contexts, the p-values for all second-stage coefficients that were determined by naively assuming normality of empirical Bayes predictors provide a good approximation to p-values determined via permutation analysis. Analyzing outcomes that are interrelated with separate models in the first stage and then associating the resulting empirical Bayes predictors in a second stage results in different mean and covariance parameter estimates from the maximum likelihood estimates generated by a MGLMM. The potential for erroneous inference from using results from these separate models increases as the magnitude of the association among the outcomes increases. Thus if computable, scatterplots of the conditionally independent empirical Bayes predictors from a MGLMM are always preferable to scatterplots of empirical Bayes predictors generated by separate models, unless the true association between outcomes is zero.

Phylogenetic mixtures and linear invariants for equal input models.

PubMed

Casanellas, Marta; Steel, Mike

2017-04-01

The reconstruction of phylogenetic trees from molecular sequence data relies on modelling site substitutions by a Markov process, or a mixture of such processes. In general, allowing mixed processes can result in different tree topologies becoming indistinguishable from the data, even for infinitely long sequences. However, when the underlying Markov process supports linear phylogenetic invariants, then provided these are sufficiently informative, the identifiability of the tree topology can be restored. In this paper, we investigate a class of processes that support linear invariants once the stationary distribution is fixed, the 'equal input model'. This model generalizes the 'Felsenstein 1981' model (and thereby the Jukes-Cantor model) from four states to an arbitrary number of states (finite or infinite), and it can also be described by a 'random cluster' process. We describe the structure and dimension of the vector spaces of phylogenetic mixtures and of linear invariants for any fixed phylogenetic tree (and for all trees-the so called 'model invariants'), on any number n of leaves. We also provide a precise description of the space of mixtures and linear invariants for the special case of [Formula: see text] leaves. By combining techniques from discrete random processes and (multi-) linear algebra, our results build on a classic result that was first established by James Lake (Mol Biol Evol 4:167-191, 1987).

Mixed models approaches for joint modeling of different types of responses.

PubMed

Ivanova, Anna; Molenberghs, Geert; Verbeke, Geert

2016-01-01

In many biomedical studies, one jointly collects longitudinal continuous, binary, and survival outcomes, possibly with some observations missing. Random-effects models, sometimes called shared-parameter models or frailty models, received a lot of attention. In such models, the corresponding variance components can be employed to capture the association between the various sequences. In some cases, random effects are considered common to various sequences, perhaps up to a scaling factor; in others, there are different but correlated random effects. Even though a variety of data types has been considered in the literature, less attention has been devoted to ordinal data. For univariate longitudinal or hierarchical data, the proportional odds mixed model (POMM) is an instance of the generalized linear mixed model (GLMM; Breslow and Clayton, 1993). Ordinal data are conveniently replaced by a parsimonious set of dummies, which in the longitudinal setting leads to a repeated set of dummies. When ordinal longitudinal data are part of a joint model, the complexity increases further. This is the setting considered in this paper. We formulate a random-effects based model that, in addition, allows for overdispersion. Using two case studies, it is shown that the combination of random effects to capture association with further correction for overdispersion can improve the model's fit considerably and that the resulting models allow to answer research questions that could not be addressed otherwise. Parameters can be estimated in a fairly straightforward way, using the SAS procedure NLMIXED.

Probe-specific mixed-model approach to detect copy number differences using multiplex ligation-dependent probe amplification (MLPA)

PubMed Central

González, Juan R; Carrasco, Josep L; Armengol, Lluís; Villatoro, Sergi; Jover, Lluís; Yasui, Yutaka; Estivill, Xavier

2008-01-01

Background MLPA method is a potentially useful semi-quantitative method to detect copy number alterations in targeted regions. In this paper, we propose a method for the normalization procedure based on a non-linear mixed-model, as well as a new approach for determining the statistical significance of altered probes based on linear mixed-model. This method establishes a threshold by using different tolerance intervals that accommodates the specific random error variability observed in each test sample. Results Through simulation studies we have shown that our proposed method outperforms two existing methods that are based on simple threshold rules or iterative regression. We have illustrated the method using a controlled MLPA assay in which targeted regions are variable in copy number in individuals suffering from different disorders such as Prader-Willi, DiGeorge or Autism showing the best performace. Conclusion Using the proposed mixed-model, we are able to determine thresholds to decide whether a region is altered. These threholds are specific for each individual, incorporating experimental variability, resulting in improved sensitivity and specificity as the examples with real data have revealed. PMID:18522760

A new compound control method for sine-on-random mixed vibration test

NASA Astrophysics Data System (ADS)

Zhang, Buyun; Wang, Ruochen; Zeng, Falin

2017-09-01

Vibration environmental test (VET) is one of the important and effective methods to provide supports for the strength design, reliability and durability test of mechanical products. A new separation control strategy was proposed to apply in multiple-input multiple-output (MIMO) sine on random (SOR) mixed mode vibration test, which is the advanced and intensive test type of VET. As the key problem of the strategy, correlation integral method was applied to separate the mixed signals which included random and sinusoidal components. The feedback control formula of MIMO linear random vibration system was systematically deduced in frequency domain, and Jacobi control algorithm was proposed in view of the elements, such as self-spectrum, coherence, and phase of power spectral density (PSD) matrix. Based on the excessive correction of excitation in sine vibration test, compression factor was introduced to reduce the excitation correction, avoiding the destruction to vibration table or other devices. The two methods were synthesized to be applied in MIMO SOR vibration test system. In the final, verification test system with the vibration of a cantilever beam as the control object was established to verify the reliability and effectiveness of the methods proposed in the paper. The test results show that the exceeding values can be controlled in the tolerance range of references accurately, and the method can supply theory and application supports for mechanical engineering.

A joint modeling and estimation method for multivariate longitudinal data with mixed types of responses to analyze physical activity data generated by accelerometers.

PubMed

Li, Haocheng; Zhang, Yukun; Carroll, Raymond J; Keadle, Sarah Kozey; Sampson, Joshua N; Matthews, Charles E

2017-11-10

A mixed effect model is proposed to jointly analyze multivariate longitudinal data with continuous, proportion, count, and binary responses. The association of the variables is modeled through the correlation of random effects. We use a quasi-likelihood type approximation for nonlinear variables and transform the proposed model into a multivariate linear mixed model framework for estimation and inference. Via an extension to the EM approach, an efficient algorithm is developed to fit the model. The method is applied to physical activity data, which uses a wearable accelerometer device to measure daily movement and energy expenditure information. Our approach is also evaluated by a simulation study. Copyright © 2017 John Wiley & Sons, Ltd.

Spatial generalised linear mixed models based on distances.

PubMed

Melo, Oscar O; Mateu, Jorge; Melo, Carlos E

2016-10-01

Risk models derived from environmental data have been widely shown to be effective in delineating geographical areas of risk because they are intuitively easy to understand. We present a new method based on distances, which allows the modelling of continuous and non-continuous random variables through distance-based spatial generalised linear mixed models. The parameters are estimated using Markov chain Monte Carlo maximum likelihood, which is a feasible and a useful technique. The proposed method depends on a detrending step built from continuous or categorical explanatory variables, or a mixture among them, by using an appropriate Euclidean distance. The method is illustrated through the analysis of the variation in the prevalence of Loa loa among a sample of village residents in Cameroon, where the explanatory variables included elevation, together with maximum normalised-difference vegetation index and the standard deviation of normalised-difference vegetation index calculated from repeated satellite scans over time. © The Author(s) 2013.

Optimization of the time series NDVI-rainfall relationship using linear mixed-effects modeling for the anti-desertification area in the Beijing and Tianjin sandstorm source region

NASA Astrophysics Data System (ADS)

Wang, Jin; Sun, Tao; Fu, Anmin; Xu, Hao; Wang, Xinjie

2018-05-01

Degradation in drylands is a critically important global issue that threatens ecosystem and environmental in many ways. Researchers have tried to use remote sensing data and meteorological data to perform residual trend analysis and identify human-induced vegetation changes. However, complex interactions between vegetation and climate, soil units and topography have not yet been considered. Data used in the study included annual accumulated Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m normalized difference vegetation index (NDVI) from 2002 to 2013, accumulated rainfall from September to August, digital elevation model (DEM) and soil units. This paper presents linear mixed-effect (LME) modeling methods for the NDVI-rainfall relationship. We developed linear mixed-effects models that considered the random effects of sample points nested in soil units for nested two-level modeling and single-level modeling of soil units and sample points, respectively. Additionally, three functions, including the exponential function (exp), the power function (power), and the constant plus power function (CPP), were tested to remove heterogeneity, and an additional three correlation structures, including the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)] and the compound symmetry structure (CS), were used to address the spatiotemporal correlations. It was concluded that the nested two-level model considering both heteroscedasticity with (CPP) and spatiotemporal correlation with [ARMA(1,1)] showed the best performance (AMR = 0.1881, RMSE = 0.2576, adj- R 2 = 0.9593). Variations between soil units and sample points that may have an effect on the NDVI-rainfall relationship should be included in model structures, and linear mixed-effects modeling achieves this in an effective and accurate way.

A Comparative Study of Randomized Constraint Solvers for Random-Symbolic Testing

NASA Technical Reports Server (NTRS)

Takaki, Mitsuo; Cavalcanti, Diego; Gheyi, Rohit; Iyoda, Juliano; dAmorim, Marcelo; Prudencio, Ricardo

2009-01-01

The complexity of constraints is a major obstacle for constraint-based software verification. Automatic constraint solvers are fundamentally incomplete: input constraints often build on some undecidable theory or some theory the solver does not support. This paper proposes and evaluates several randomized solvers to address this issue. We compare the effectiveness of a symbolic solver (CVC3), a random solver, three hybrid solvers (i.e., mix of random and symbolic), and two heuristic search solvers. We evaluate the solvers on two benchmarks: one consisting of manually generated constraints and another generated with a concolic execution of 8 subjects. In addition to fully decidable constraints, the benchmarks include constraints with non-linear integer arithmetic, integer modulo and division, bitwise arithmetic, and floating-point arithmetic. As expected symbolic solving (in particular, CVC3) subsumes the other solvers for the concolic execution of subjects that only generate decidable constraints. For the remaining subjects the solvers are complementary.

Trending in Probability of Collision Measurements via a Bayesian Zero-Inflated Beta Mixed Model

NASA Technical Reports Server (NTRS)

Vallejo, Jonathon; Hejduk, Matt; Stamey, James

2015-01-01

We investigate the performance of a generalized linear mixed model in predicting the Probabilities of Collision (Pc) for conjunction events. Specifically, we apply this model to the log(sub 10) transformation of these probabilities and argue that this transformation yields values that can be considered bounded in practice. Additionally, this bounded random variable, after scaling, is zero-inflated. Consequently, we model these values using the zero-inflated Beta distribution, and utilize the Bayesian paradigm and the mixed model framework to borrow information from past and current events. This provides a natural way to model the data and provides a basis for answering questions of interest, such as what is the likelihood of observing a probability of collision equal to the effective value of zero on a subsequent observation.

A random distribution reacting mixing layer model

NASA Technical Reports Server (NTRS)

Jones, Richard A.; Marek, C. John; Myrabo, Leik N.; Nagamatsu, Henry T.

1994-01-01

A methodology for simulation of molecular mixing, and the resulting velocity and temperature fields has been developed. The ideas are applied to the flow conditions present in the NASA Lewis Research Center Planar Reacting Shear Layer (PRSL) facility, and results compared to experimental data. A gaussian transverse turbulent velocity distribution is used in conjunction with a linearly increasing time scale to describe the mixing of different regions of the flow. Equilibrium reaction calculations are then performed on the mix to arrive at a new species composition and temperature. Velocities are determined through summation of momentum contributions. The analysis indicates a combustion efficiency of the order of 80 percent for the reacting mixing layer, and a turbulent Schmidt number of 2/3. The success of the model is attributed to the simulation of large-scale transport of fluid. The favorable comparison shows that a relatively quick and simple PC calculation is capable of simulating the basic flow structure in the reacting and nonreacting shear layer present in the facility given basic assumptions about turbulence properties.

Analysis of multivariate longitudinal kidney function outcomes using generalized linear mixed models.

PubMed

Jaffa, Miran A; Gebregziabher, Mulugeta; Jaffa, Ayad A

2015-06-14

Renal transplant patients are mandated to have continuous assessment of their kidney function over time to monitor disease progression determined by changes in blood urea nitrogen (BUN), serum creatinine (Cr), and estimated glomerular filtration rate (eGFR). Multivariate analysis of these outcomes that aims at identifying the differential factors that affect disease progression is of great clinical significance. Thus our study aims at demonstrating the application of different joint modeling approaches with random coefficients on a cohort of renal transplant patients and presenting a comparison of their performance through a pseudo-simulation study. The objective of this comparison is to identify the model with best performance and to determine whether accuracy compensates for complexity in the different multivariate joint models. We propose a novel application of multivariate Generalized Linear Mixed Models (mGLMM) to analyze multiple longitudinal kidney function outcomes collected over 3 years on a cohort of 110 renal transplantation patients. The correlated outcomes BUN, Cr, and eGFR and the effect of various covariates such patient's gender, age and race on these markers was determined holistically using different mGLMMs. The performance of the various mGLMMs that encompass shared random intercept (SHRI), shared random intercept and slope (SHRIS), separate random intercept (SPRI) and separate random intercept and slope (SPRIS) was assessed to identify the one that has the best fit and most accurate estimates. A bootstrap pseudo-simulation study was conducted to gauge the tradeoff between the complexity and accuracy of the models. Accuracy was determined using two measures; the mean of the differences between the estimates of the bootstrapped datasets and the true beta obtained from the application of each model on the renal dataset, and the mean of the square of these differences. The results showed that SPRI provided most accurate estimates and did not exhibit any computational or convergence problem. Higher accuracy was demonstrated when the level of complexity increased from shared random coefficient models to the separate random coefficient alternatives with SPRI showing to have the best fit and most accurate estimates.

Statistical simulation of ensembles of precipitation fields for data assimilation applications

NASA Astrophysics Data System (ADS)

Haese, Barbara; Hörning, Sebastian; Chwala, Christian; Bárdossy, András; Schalge, Bernd; Kunstmann, Harald

2017-04-01

The simulation of the hydrological cycle by models is an indispensable tool for a variety of environmental challenges such as climate prediction, water resources management, or flood forecasting. One of the crucial variables within the hydrological system, and accordingly one of the main drivers for terrestrial hydrological processes, is precipitation. A correct reproduction of the spatio-temporal distribution of precipitation is crucial for the quality and performance of hydrological applications. In our approach we stochastically generate precipitation fields conditioned on various precipitation observations. Rain gauges provide high-quality information for a specific measurement point, but their spatial representativeness is often rare. Microwave links, e. g. from commercial cellular operators, on the other hand can be used to estimate line integrals of near-surface rainfall information. They provide a very dense observational system compared to rain gauges. A further prevalent source of precipitation information are weather radars, which provide rainfall pattern informations. In our approach we derive precipitation fields, which are conditioned on combinations of these different observation types. As method to generate precipitation fields we use the random mixing method. Following this method a precipitation field is received as a linear combination of unconditional spatial random fields, where the spatial dependence structure is described by copulas. The weights of the linear combination are chosen in the way that the observations and the spatial structure of precipitation are reproduced. One main advantage of the random mixing method is the opportunity to consider linear and non-linear constraints. For a demonstration of the method we use virtual observations generated from a virtual reality of the Neckar catchment. These virtual observations mimic advantages and disadvantages of real observations. This virtual data set allows us to evaluate simulated precipitation fields in a very detailed manner as well as to quantify uncertainties which are conveyed by measurement inaccuracies. In a further step we use real observations as a basis for the generation of precipitation fields. The resulting ensembles of precipitation fields are used for example for data assimilation applications or as input data for hydrological models.

A Two-Step Approach for Analysis of Nonignorable Missing Outcomes in Longitudinal Regression: an Application to Upstate KIDS Study.

PubMed

Liu, Danping; Yeung, Edwina H; McLain, Alexander C; Xie, Yunlong; Buck Louis, Germaine M; Sundaram, Rajeshwari

2017-09-01

Imperfect follow-up in longitudinal studies commonly leads to missing outcome data that can potentially bias the inference when the missingness is nonignorable; that is, the propensity of missingness depends on missing values in the data. In the Upstate KIDS Study, we seek to determine if the missingness of child development outcomes is nonignorable, and how a simple model assuming ignorable missingness would compare with more complicated models for a nonignorable mechanism. To correct for nonignorable missingness, the shared random effects model (SREM) jointly models the outcome and the missing mechanism. However, the computational complexity and lack of software packages has limited its practical applications. This paper proposes a novel two-step approach to handle nonignorable missing outcomes in generalized linear mixed models. We first analyse the missing mechanism with a generalized linear mixed model and predict values of the random effects; then, the outcome model is fitted adjusting for the predicted random effects to account for heterogeneity in the missingness propensity. Extensive simulation studies suggest that the proposed method is a reliable approximation to SREM, with a much faster computation. The nonignorability of missing data in the Upstate KIDS Study is estimated to be mild to moderate, and the analyses using the two-step approach or SREM are similar to the model assuming ignorable missingness. The two-step approach is a computationally straightforward method that can be conducted as sensitivity analyses in longitudinal studies to examine violations to the ignorable missingness assumption and the implications relative to health outcomes. © 2017 John Wiley & Sons Ltd.

Spontaneous repulsion in the A +B →0 reaction on coupled networks

NASA Astrophysics Data System (ADS)

Lazaridis, Filippos; Gross, Bnaya; Maragakis, Michael; Argyrakis, Panos; Bonamassa, Ivan; Havlin, Shlomo; Cohen, Reuven

2018-04-01

We study the transient dynamics of an A +B →0 process on a pair of randomly coupled networks, where reactants are initially separated. We find that, for sufficiently small fractions q of cross couplings, the concentration of A (or B ) particles decays linearly in a first stage and crosses over to a second linear decrease at a mixing time tx. By numerical and analytical arguments, we show that for symmetric and homogeneous structures tx∝(/q)log(/q) where is the mean degree of both networks. Being this behavior is in marked contrast with a purely diffusive process, where the mixing time would go simply like /q , we identify the logarithmic slowing down in tx to be the result of a spontaneous mechanism of repulsion between the reactants A and B due to the interactions taking place at the networks' interface. We show numerically how this spontaneous repulsion effect depends on the topology of the underlying networks.

Logit-normal mixed model for Indian monsoon precipitation

NASA Astrophysics Data System (ADS)

Dietz, L. R.; Chatterjee, S.

2014-09-01

Describing the nature and variability of Indian monsoon precipitation is a topic of much debate in the current literature. We suggest the use of a generalized linear mixed model (GLMM), specifically, the logit-normal mixed model, to describe the underlying structure of this complex climatic event. Four GLMM algorithms are described and simulations are performed to vet these algorithms before applying them to the Indian precipitation data. The logit-normal model was applied to light, moderate, and extreme rainfall. Findings indicated that physical constructs were preserved by the models, and random effects were significant in many cases. We also found GLMM estimation methods were sensitive to tuning parameters and assumptions and therefore, recommend use of multiple methods in applications. This work provides a novel use of GLMM and promotes its addition to the gamut of tools for analysis in studying climate phenomena.

Efficacy of a Multi-Component Intervention to Reduce Workplace Sitting Time in Office Workers: A Cluster Randomized Controlled Trial.

PubMed

Maylor, Benjamin D; Edwardson, Charlotte L; Zakrzewski-Fruer, Julia K; Champion, Rachael B; Bailey, Daniel P

2018-05-30

The aim of this study was to investigate the efficacy of a work-based multicomponent intervention to reduce office workers' sitting time. Offices (n = 12; 89 workers) were randomized into an 8-week intervention (n = 48) incorporating organizational, individual, and environmental elements or control arm. Sitting time, physical activity, and cardiometabolic health were measured at baseline and after the intervention. Linear mixed modelling revealed no significant change in workplace sitting time, but changes in workplace prolonged sitting time (-39 min/shift), sit-upright transitions (7.8 per shift), and stepping time (12 min/shift) at follow-up were observed, in favor of the intervention group (P < 0.001). Results for cardiometabolic health markers were mixed. This short multicomponent workplace intervention was successful in reducing prolonged sitting and increasing physical activity in the workplace, although total sitting time was not reduced and the impact on cardiometabolic health was minimal.

Smooth random change point models.

PubMed

van den Hout, Ardo; Muniz-Terrera, Graciela; Matthews, Fiona E

2011-03-15

Change point models are used to describe processes over time that show a change in direction. An example of such a process is cognitive ability, where a decline a few years before death is sometimes observed. A broken-stick model consists of two linear parts and a breakpoint where the two lines intersect. Alternatively, models can be formulated that imply a smooth change between the two linear parts. Change point models can be extended by adding random effects to account for variability between subjects. A new smooth change point model is introduced and examples are presented that show how change point models can be estimated using functions in R for mixed-effects models. The Bayesian inference using WinBUGS is also discussed. The methods are illustrated using data from a population-based longitudinal study of ageing, the Cambridge City over 75 Cohort Study. The aim is to identify how many years before death individuals experience a change in the rate of decline of their cognitive ability. Copyright © 2010 John Wiley & Sons, Ltd.

40 CFR 60.667 - Chemicals affected by subpart NNN.

Code of Federal Regulations, 2010 CFR

2010-07-01

... alcohols, ethoxylated, mixed Linear alcohols, ethoxylated, and sulfated, sodium salt, mixed Linear alcohols, sulfated, sodium salt, mixed Linear alkylbenzene 123-01-3 Magnesium acetate 142-72-3 Maleic anhydride 108...

40 CFR 60.667 - Chemicals affected by subpart NNN.

Code of Federal Regulations, 2011 CFR

2011-07-01

... alcohols, ethoxylated, mixed Linear alcohols, ethoxylated, and sulfated, sodium salt, mixed Linear alcohols, sulfated, sodium salt, mixed Linear alkylbenzene 123-01-3 Magnesium acetate 142-72-3 Maleic anhydride 108...

Comparing performance of standard and iterative linear unmixing methods for hyperspectral signatures

NASA Astrophysics Data System (ADS)

Gault, Travis R.; Jansen, Melissa E.; DeCoster, Mallory E.; Jansing, E. David; Rodriguez, Benjamin M.

2016-05-01

Linear unmixing is a method of decomposing a mixed signature to determine the component materials that are present in sensor's field of view, along with the abundances at which they occur. Linear unmixing assumes that energy from the materials in the field of view is mixed in a linear fashion across the spectrum of interest. Traditional unmixing methods can take advantage of adjacent pixels in the decomposition algorithm, but is not the case for point sensors. This paper explores several iterative and non-iterative methods for linear unmixing, and examines their effectiveness at identifying the individual signatures that make up simulated single pixel mixed signatures, along with their corresponding abundances. The major hurdle addressed in the proposed method is that no neighboring pixel information is available for the spectral signature of interest. Testing is performed using two collections of spectral signatures from the Johns Hopkins University Applied Physics Laboratory's Signatures Database software (SigDB): a hand-selected small dataset of 25 distinct signatures from a larger dataset of approximately 1600 pure visible/near-infrared/short-wave-infrared (VIS/NIR/SWIR) spectra. Simulated spectra are created with three and four material mixtures randomly drawn from a dataset originating from SigDB, where the abundance of one material is swept in 10% increments from 10% to 90%with the abundances of the other materials equally divided amongst the remainder. For the smaller dataset of 25 signatures, all combinations of three or four materials are used to create simulated spectra, from which the accuracy of materials returned, as well as the correctness of the abundances, is compared to the inputs. The experiment is expanded to include the signatures from the larger dataset of almost 1600 signatures evaluated using a Monte Carlo scheme with 5000 draws of three or four materials to create the simulated mixed signatures. The spectral similarity of the inputs to the output component signatures is calculated using the spectral angle mapper. Results show that iterative methods significantly outperform the traditional methods under the given test conditions.

An update on modeling dose-response relationships: Accounting for correlated data structure and heterogeneous error variance in linear and nonlinear mixed models.

PubMed

Gonçalves, M A D; Bello, N M; Dritz, S S; Tokach, M D; DeRouchey, J M; Woodworth, J C; Goodband, R D

2016-05-01

Advanced methods for dose-response assessments are used to estimate the minimum concentrations of a nutrient that maximizes a given outcome of interest, thereby determining nutritional requirements for optimal performance. Contrary to standard modeling assumptions, experimental data often present a design structure that includes correlations between observations (i.e., blocking, nesting, etc.) as well as heterogeneity of error variances; either can mislead inference if disregarded. Our objective is to demonstrate practical implementation of linear and nonlinear mixed models for dose-response relationships accounting for correlated data structure and heterogeneous error variances. To illustrate, we modeled data from a randomized complete block design study to evaluate the standardized ileal digestible (SID) Trp:Lys ratio dose-response on G:F of nursery pigs. A base linear mixed model was fitted to explore the functional form of G:F relative to Trp:Lys ratios and assess model assumptions. Next, we fitted 3 competing dose-response mixed models to G:F, namely a quadratic polynomial (QP) model, a broken-line linear (BLL) ascending model, and a broken-line quadratic (BLQ) ascending model, all of which included heteroskedastic specifications, as dictated by the base model. The GLIMMIX procedure of SAS (version 9.4) was used to fit the base and QP models and the NLMIXED procedure was used to fit the BLL and BLQ models. We further illustrated the use of a grid search of initial parameter values to facilitate convergence and parameter estimation in nonlinear mixed models. Fit between competing dose-response models was compared using a maximum likelihood-based Bayesian information criterion (BIC). The QP, BLL, and BLQ models fitted on G:F of nursery pigs yielded BIC values of 353.7, 343.4, and 345.2, respectively, thus indicating a better fit of the BLL model. The BLL breakpoint estimate of the SID Trp:Lys ratio was 16.5% (95% confidence interval [16.1, 17.0]). Problems with the estimation process rendered results from the BLQ model questionable. Importantly, accounting for heterogeneous variance enhanced inferential precision as the breadth of the confidence interval for the mean breakpoint decreased by approximately 44%. In summary, the article illustrates the use of linear and nonlinear mixed models for dose-response relationships accounting for heterogeneous residual variances, discusses important diagnostics and their implications for inference, and provides practical recommendations for computational troubleshooting.

Logit-normal mixed model for Indian Monsoon rainfall extremes

NASA Astrophysics Data System (ADS)

Dietz, L. R.; Chatterjee, S.

2014-03-01

Describing the nature and variability of Indian monsoon rainfall extremes is a topic of much debate in the current literature. We suggest the use of a generalized linear mixed model (GLMM), specifically, the logit-normal mixed model, to describe the underlying structure of this complex climatic event. Several GLMM algorithms are described and simulations are performed to vet these algorithms before applying them to the Indian precipitation data procured from the National Climatic Data Center. The logit-normal model was applied with fixed covariates of latitude, longitude, elevation, daily minimum and maximum temperatures with a random intercept by weather station. In general, the estimation methods concurred in their suggestion of a relationship between the El Niño Southern Oscillation (ENSO) and extreme rainfall variability estimates. This work provides a valuable starting point for extending GLMM to incorporate the intricate dependencies in extreme climate events.

lme4qtl: linear mixed models with flexible covariance structure for genetic studies of related individuals.

PubMed

Ziyatdinov, Andrey; Vázquez-Santiago, Miquel; Brunel, Helena; Martinez-Perez, Angel; Aschard, Hugues; Soria, Jose Manuel

2018-02-27

Quantitative trait locus (QTL) mapping in genetic data often involves analysis of correlated observations, which need to be accounted for to avoid false association signals. This is commonly performed by modeling such correlations as random effects in linear mixed models (LMMs). The R package lme4 is a well-established tool that implements major LMM features using sparse matrix methods; however, it is not fully adapted for QTL mapping association and linkage studies. In particular, two LMM features are lacking in the base version of lme4: the definition of random effects by custom covariance matrices; and parameter constraints, which are essential in advanced QTL models. Apart from applications in linkage studies of related individuals, such functionalities are of high interest for association studies in situations where multiple covariance matrices need to be modeled, a scenario not covered by many genome-wide association study (GWAS) software. To address the aforementioned limitations, we developed a new R package lme4qtl as an extension of lme4. First, lme4qtl contributes new models for genetic studies within a single tool integrated with lme4 and its companion packages. Second, lme4qtl offers a flexible framework for scenarios with multiple levels of relatedness and becomes efficient when covariance matrices are sparse. We showed the value of our package using real family-based data in the Genetic Analysis of Idiopathic Thrombophilia 2 (GAIT2) project. Our software lme4qtl enables QTL mapping models with a versatile structure of random effects and efficient computation for sparse covariances. lme4qtl is available at https://github.com/variani/lme4qtl .

Nested generalized linear mixed model with ordinal response: Simulation and application on poverty data in Java Island

NASA Astrophysics Data System (ADS)

Widyaningsih, Yekti; Saefuddin, Asep; Notodiputro, Khairil A.; Wigena, Aji H.

2012-05-01

The objective of this research is to build a nested generalized linear mixed model using an ordinal response variable with some covariates. There are three main jobs in this paper, i.e. parameters estimation procedure, simulation, and implementation of the model for the real data. At the part of parameters estimation procedure, concepts of threshold, nested random effect, and computational algorithm are described. The simulations data are built for 3 conditions to know the effect of different parameter values of random effect distributions. The last job is the implementation of the model for the data about poverty in 9 districts of Java Island. The districts are Kuningan, Karawang, and Majalengka chose randomly in West Java; Temanggung, Boyolali, and Cilacap from Central Java; and Blitar, Ngawi, and Jember from East Java. The covariates in this model are province, number of bad nutrition cases, number of farmer families, and number of health personnel. In this modeling, all covariates are grouped as ordinal scale. Unit observation in this research is sub-district (kecamatan) nested in district, and districts (kabupaten) are nested in province. For the result of simulation, ARB (Absolute Relative Bias) and RRMSE (Relative Root of mean square errors) scale is used. They show that prov parameters have the highest bias, but more stable RRMSE in all conditions. The simulation design needs to be improved by adding other condition, such as higher correlation between covariates. Furthermore, as the result of the model implementation for the data, only number of farmer family and number of medical personnel have significant contributions to the level of poverty in Central Java and East Java province, and only district 2 (Karawang) of province 1 (West Java) has different random effect from the others. The source of the data is PODES (Potensi Desa) 2008 from BPS (Badan Pusat Statistik).

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

Zhang, Lin, E-mail: godyalin@163.com; Singh, Uttam, E-mail: uttamsingh@hri.res.in; Pati, Arun K., E-mail: akpati@hri.res.in

Compact expressions for the average subentropy and coherence are obtained for random mixed states that are generated via various probability measures. Surprisingly, our results show that the average subentropy of random mixed states approaches the maximum value of the subentropy which is attained for the maximally mixed state as we increase the dimension. In the special case of the random mixed states sampled from the induced measure via partial tracing of random bipartite pure states, we establish the typicality of the relative entropy of coherence for random mixed states invoking the concentration of measure phenomenon. Our results also indicate thatmore » mixed quantum states are less useful compared to pure quantum states in higher dimension when we extract quantum coherence as a resource. This is because of the fact that average coherence of random mixed states is bounded uniformly, however, the average coherence of random pure states increases with the increasing dimension. As an important application, we establish the typicality of relative entropy of entanglement and distillable entanglement for a specific class of random bipartite mixed states. In particular, most of the random states in this specific class have relative entropy of entanglement and distillable entanglement equal to some fixed number (to within an arbitrary small error), thereby hugely reducing the complexity of computation of these entanglement measures for this specific class of mixed states.« less

Mutation-selection equilibrium in games with mixed strategies.

PubMed

Tarnita, Corina E; Antal, Tibor; Nowak, Martin A

2009-11-07

We develop a new method for studying stochastic evolutionary game dynamics of mixed strategies. We consider the general situation: there are n pure strategies whose interactions are described by an nxn payoff matrix. Players can use mixed strategies, which are given by the vector (p(1),...,p(n)). Each entry specifies the probability to use the corresponding pure strategy. The sum over all entries is one. Therefore, a mixed strategy is a point in the simplex S(n). We study evolutionary dynamics in a well-mixed population of finite size. Individuals reproduce proportional to payoff. We consider the case of weak selection, which means the payoff from the game is only a small contribution to overall fitness. Reproduction can be subject to mutation; a mutant adopts a randomly chosen mixed strategy. We calculate the average abundance of every mixed strategy in the stationary distribution of the mutation-selection process. We find the crucial conditions that specify if a strategy is favored or opposed by selection. One condition holds for low mutation rate, another for high mutation rate. The result for any mutation rate is a linear combination of those two. As a specific example we study the Hawk-Dove game. We prove general statements about the relationship between games with pure and with mixed strategies.

Classification of longitudinal data through a semiparametric mixed-effects model based on lasso-type estimators.

PubMed

Arribas-Gil, Ana; De la Cruz, Rolando; Lebarbier, Emilie; Meza, Cristian

2015-06-01

We propose a classification method for longitudinal data. The Bayes classifier is classically used to determine a classification rule where the underlying density in each class needs to be well modeled and estimated. This work is motivated by a real dataset of hormone levels measured at the early stages of pregnancy that can be used to predict normal versus abnormal pregnancy outcomes. The proposed model, which is a semiparametric linear mixed-effects model (SLMM), is a particular case of the semiparametric nonlinear mixed-effects class of models (SNMM) in which finite dimensional (fixed effects and variance components) and infinite dimensional (an unknown function) parameters have to be estimated. In SNMM's maximum likelihood estimation is performed iteratively alternating parametric and nonparametric procedures. However, if one can make the assumption that the random effects and the unknown function interact in a linear way, more efficient estimation methods can be used. Our contribution is the proposal of a unified estimation procedure based on a penalized EM-type algorithm. The Expectation and Maximization steps are explicit. In this latter step, the unknown function is estimated in a nonparametric fashion using a lasso-type procedure. A simulation study and an application on real data are performed. © 2015, The International Biometric Society.

Influence assessment in censored mixed-effects models using the multivariate Student’s-t distribution

PubMed Central

Matos, Larissa A.; Bandyopadhyay, Dipankar; Castro, Luis M.; Lachos, Victor H.

2015-01-01

In biomedical studies on HIV RNA dynamics, viral loads generate repeated measures that are often subjected to upper and lower detection limits, and hence these responses are either left- or right-censored. Linear and non-linear mixed-effects censored (LMEC/NLMEC) models are routinely used to analyse these longitudinal data, with normality assumptions for the random effects and residual errors. However, the derived inference may not be robust when these underlying normality assumptions are questionable, especially the presence of outliers and thick-tails. Motivated by this, Matos et al. (2013b) recently proposed an exact EM-type algorithm for LMEC/NLMEC models using a multivariate Student’s-t distribution, with closed-form expressions at the E-step. In this paper, we develop influence diagnostics for LMEC/NLMEC models using the multivariate Student’s-t density, based on the conditional expectation of the complete data log-likelihood. This partially eliminates the complexity associated with the approach of Cook (1977, 1986) for censored mixed-effects models. The new methodology is illustrated via an application to a longitudinal HIV dataset. In addition, a simulation study explores the accuracy of the proposed measures in detecting possible influential observations for heavy-tailed censored data under different perturbation and censoring schemes. PMID:26190871

A Lagrangian stochastic model to demonstrate multi-scale interactions between convection and land surface heterogeneity in the atmospheric boundary layer

NASA Astrophysics Data System (ADS)

Parsakhoo, Zahra; Shao, Yaping

2017-04-01

Near-surface turbulent mixing has considerable effect on surface fluxes, cloud formation and convection in the atmospheric boundary layer (ABL). Its quantifications is however a modeling and computational challenge since the small eddies are not fully resolved in Eulerian models directly. We have developed a Lagrangian stochastic model to demonstrate multi-scale interactions between convection and land surface heterogeneity in the atmospheric boundary layer based on the Ito Stochastic Differential Equation (SDE) for air parcels (particles). Due to the complexity of the mixing in the ABL, we find that linear Ito SDE cannot represent convections properly. Three strategies have been tested to solve the problem: 1) to make the deterministic term in the Ito equation non-linear; 2) to change the random term in the Ito equation fractional, and 3) to modify the Ito equation by including Levy flights. We focus on the third strategy and interpret mixing as interaction between at least two stochastic processes with different Lagrangian time scales. The model is in progress to include the collisions among the particles with different characteristic and to apply the 3D model for real cases. One application of the model is emphasized: some land surface patterns are generated and then coupled with the Large Eddy Simulation (LES).

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies.

PubMed

Koerner, Tess K; Zhang, Yang

2017-02-27

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers.

Methodological quality and reporting of generalized linear mixed models in clinical medicine (2000-2012): a systematic review.

PubMed

Casals, Martí; Girabent-Farrés, Montserrat; Carrasco, Josep L

2014-01-01

Modeling count and binary data collected in hierarchical designs have increased the use of Generalized Linear Mixed Models (GLMMs) in medicine. This article presents a systematic review of the application and quality of results and information reported from GLMMs in the field of clinical medicine. A search using the Web of Science database was performed for published original articles in medical journals from 2000 to 2012. The search strategy included the topic "generalized linear mixed models","hierarchical generalized linear models", "multilevel generalized linear model" and as a research domain we refined by science technology. Papers reporting methodological considerations without application, and those that were not involved in clinical medicine or written in English were excluded. A total of 443 articles were detected, with an increase over time in the number of articles. In total, 108 articles fit the inclusion criteria. Of these, 54.6% were declared to be longitudinal studies, whereas 58.3% and 26.9% were defined as repeated measurements and multilevel design, respectively. Twenty-two articles belonged to environmental and occupational public health, 10 articles to clinical neurology, 8 to oncology, and 7 to infectious diseases and pediatrics. The distribution of the response variable was reported in 88% of the articles, predominantly Binomial (n = 64) or Poisson (n = 22). Most of the useful information about GLMMs was not reported in most cases. Variance estimates of random effects were described in only 8 articles (9.2%). The model validation, the method of covariate selection and the method of goodness of fit were only reported in 8.0%, 36.8% and 14.9% of the articles, respectively. During recent years, the use of GLMMs in medical literature has increased to take into account the correlation of data when modeling qualitative data or counts. According to the current recommendations, the quality of reporting has room for improvement regarding the characteristics of the analysis, estimation method, validation, and selection of the model.

The body project 4 all: A pilot randomized controlled trial of a mixed-gender dissonance-based body image program.

PubMed

Kilpela, Lisa Smith; Blomquist, Kerstin; Verzijl, Christina; Wilfred, Salomé; Beyl, Robbie; Becker, Carolyn Black

2016-06-01

The Body Project is a cognitive dissonance-based body image improvement program with ample research support among female samples. More recently, researchers have highlighted the extent of male body dissatisfaction and disordered eating behaviors; however, boys/men have not been included in the majority of body image improvement programs. This study aims to explore the efficacy of a mixed-gender Body Project compared with the historically female-only body image intervention program. Participants included male and female college students (N = 185) across two sites. We randomly assigned women to a mixed-gender modification of the two-session, peer-led Body Project (MG), the two-session, peer-led, female-only (FO) Body Project, or a waitlist control (WL), and men to either MG or WL. Participants completed self-report measures assessing negative affect, appearance-ideal internalization, body satisfaction, and eating disorder pathology at baseline, post-test, and at 2- and 6-month follow-up. Linear mixed effects modeling to estimate the change from baseline over time for each dependent variable across conditions were used. For women, results were mixed regarding post-intervention improvement compared with WL, and were largely non-significant compared with WL at 6-month follow-up. Alternatively, results indicated that men in MG consistently improved compared with WL through 6-month follow-up on all measures except negative affect and appearance-ideal internalization. Results differed markedly between female and male samples, and were more promising for men than for women. Various explanations are provided, and further research is warranted prior to drawing firm conclusions regarding mixed-gender programming of the Body Project. © 2016 Wiley Periodicals, Inc.(Int J Eat Disord 2016; 49:591-602). © 2016 Wiley Periodicals, Inc.

The Body Project 4 All: A pilot randomized controlled trial of a mixed-gender dissonance-based body image program

PubMed Central

Kilpela, Lisa Smith; Blomquist, Kerstin; Verzijl, Christina; Wilfred, Salomé; Beyl, Robbie; Becker, Carolyn Black

2017-01-01

Objective The Body Project is a cognitive dissonance-based body image improvement program with ample research support among female samples. More recently, researchers have highlighted the extent of male body dissatisfaction and disordered eating behaviors; however, boys/men have not been included in the majority of body image improvement programs. This study aims to explore the efficacy of a mixed-gender Body Project compared to the historically female-only body image intervention program. Method Participants included male and female college students (N=185) across two sites. We randomly assigned women to a mixed-gender modification of the two-session, peer-led Body Project (MG), the two-session, peer-led, female-only (FO) Body Project, or a waitlist control (WL), and men to either MG or WL. Participants completed self-report measures assessing negative affect, appearance-ideal internalization, body satisfaction, and eating disorder pathology at baseline, post-test, and at two- and six-month follow-up. Results We used linear mixed effects modeling to estimate the change from baseline over time for each dependent variable across conditions. For women, results were mixed regarding post-intervention improvement compared to WL, and were largely non-significant compared to WL at 6-month follow-up. Alternatively, results indicated that men in MG consistently improved compared to WL through 6-month follow-up on all measures except negative affect and appearance-ideal internalization. Discussion Results differed markedly between female and male samples, and were more promising for men than for women. Various explanations are provided, and further research is warranted prior to drawing firm conclusions regarding mixed-gender programming of the Body Project. PMID:27188688

Mixed H2/H∞ distributed robust model predictive control for polytopic uncertain systems subject to actuator saturation and missing measurements

NASA Astrophysics Data System (ADS)

Song, Yan; Fang, Xiaosheng; Diao, Qingda

2016-03-01

In this paper, we discuss the mixed H2/H∞ distributed robust model predictive control problem for polytopic uncertain systems subject to randomly occurring actuator saturation and packet loss. The global system is decomposed into several subsystems, and all the subsystems are connected by a fixed topology network, which is the definition for the packet loss among the subsystems. To better use the successfully transmitted information via Internet, both the phenomena of actuator saturation and packet loss resulting from the limitation of the communication bandwidth are taken into consideration. A novel distributed controller model is established to account for the actuator saturation and packet loss in a unified representation by using two sets of Bernoulli distributed white sequences with known conditional probabilities. With the nonlinear feedback control law represented by the convex hull of a group of linear feedback laws, the distributed controllers for subsystems are obtained by solving an linear matrix inequality (LMI) optimisation problem. Finally, numerical studies demonstrate the effectiveness of the proposed techniques.

Experimental Effects and Individual Differences in Linear Mixed Models: Estimating the Relationship between Spatial, Object, and Attraction Effects in Visual Attention

PubMed Central

Kliegl, Reinhold; Wei, Ping; Dambacher, Michael; Yan, Ming; Zhou, Xiaolin

2011-01-01

Linear mixed models (LMMs) provide a still underused methodological perspective on combining experimental and individual-differences research. Here we illustrate this approach with two-rectangle cueing in visual attention (Egly et al., 1994). We replicated previous experimental cue-validity effects relating to a spatial shift of attention within an object (spatial effect), to attention switch between objects (object effect), and to the attraction of attention toward the display centroid (attraction effect), also taking into account the design-inherent imbalance of valid and other trials. We simultaneously estimated variance/covariance components of subject-related random effects for these spatial, object, and attraction effects in addition to their mean reaction times (RTs). The spatial effect showed a strong positive correlation with mean RT and a strong negative correlation with the attraction effect. The analysis of individual differences suggests that slow subjects engage attention more strongly at the cued location than fast subjects. We compare this joint LMM analysis of experimental effects and associated subject-related variances and correlations with two frequently used alternative statistical procedures. PMID:21833292

Conditional random slope: A new approach for estimating individual child growth velocity in epidemiological research.

PubMed

Leung, Michael; Bassani, Diego G; Racine-Poon, Amy; Goldenberg, Anna; Ali, Syed Asad; Kang, Gagandeep; Premkumar, Prasanna S; Roth, Daniel E

2017-09-10

Conditioning child growth measures on baseline accounts for regression to the mean (RTM). Here, we present the "conditional random slope" (CRS) model, based on a linear-mixed effects model that incorporates a baseline-time interaction term that can accommodate multiple data points for a child while also directly accounting for RTM. In two birth cohorts, we applied five approaches to estimate child growth velocities from 0 to 12 months to assess the effect of increasing data density (number of measures per child) on the magnitude of RTM of unconditional estimates, and the correlation and concordance between the CRS and four alternative metrics. Further, we demonstrated the differential effect of the choice of velocity metric on the magnitude of the association between infant growth and stunting at 2 years. RTM was minimally attenuated by increasing data density for unconditional growth modeling approaches. CRS and classical conditional models gave nearly identical estimates with two measures per child. Compared to the CRS estimates, unconditional metrics had moderate correlation (r = 0.65-0.91), but poor agreement in the classification of infants with relatively slow growth (kappa = 0.38-0.78). Estimates of the velocity-stunting association were the same for CRS and classical conditional models but differed substantially between conditional versus unconditional metrics. The CRS can leverage the flexibility of linear mixed models while addressing RTM in longitudinal analyses. © 2017 The Authors American Journal of Human Biology Published by Wiley Periodicals, Inc.

A comparison of three random effects approaches to analyze repeated bounded outcome scores with an application in a stroke revalidation study.

PubMed

Molas, Marek; Lesaffre, Emmanuel

2008-12-30

Discrete bounded outcome scores (BOS), i.e. discrete measurements that are restricted on a finite interval, often occur in practice. Examples are compliance measures, quality of life measures, etc. In this paper we examine three related random effects approaches to analyze longitudinal studies with a BOS as response: (1) a linear mixed effects (LM) model applied to a logistic transformed modified BOS; (2) a model assuming that the discrete BOS is a coarsened version of a latent random variable, which after a logistic-normal transformation, satisfies an LM model; and (3) a random effects probit model. We consider also the extension whereby the variability of the BOS is allowed to depend on covariates. The methods are contrasted using a simulation study and on a longitudinal project, which documents stroke rehabilitation in four European countries using measures of motor and functional recovery. Copyright 2008 John Wiley & Sons, Ltd.

Outcomes of a pilot hand hygiene randomized cluster trial to reduce communicable infections among US office-based employees.

PubMed

Stedman-Smith, Maggie; DuBois, Cathy L Z; Grey, Scott F; Kingsbury, Diana M; Shakya, Sunita; Scofield, Jennifer; Slenkovich, Ken

2015-04-01

To determine the effectiveness of an office-based multimodal hand hygiene improvement intervention in reducing self-reported communicable infections and work-related absence. A randomized cluster trial including an electronic training video, hand sanitizer, and educational posters (n = 131, intervention; n = 193, control). Primary outcomes include (1) self-reported acute respiratory infections (ARIs)/influenza-like illness (ILI) and/or gastrointestinal (GI) infections during the prior 30 days; and (2) related lost work days. Incidence rate ratios calculated using generalized linear mixed models with a Poisson distribution, adjusted for confounders and random cluster effects. A 31% relative reduction in self-reported combined ARI-ILI/GI infections (incidence rate ratio: 0.69; 95% confidence interval, 0.49 to 0.98). A 21% nonsignificant relative reduction in lost work days. An office-based multimodal hand hygiene improvement intervention demonstrated a substantive reduction in self-reported combined ARI-ILI/GI infections.

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape

PubMed Central

Coupé, Christophe

2018-01-01

As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for ‘difficult’ variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS, we assess a range of candidate distributions, including the Sichel, Delaporte, Box-Cox Green and Cole, and Box-Cox t distributions. We find that the Box-Cox t distribution, with appropriate modeling of its parameters, best fits the conditional distribution of phonemic inventory size. We finally discuss the specificities of phoneme counts, weak effects, and how GAMLSS should be considered for other linguistic variables. PMID:29713298

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape.

PubMed

Coupé, Christophe

2018-01-01

As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for 'difficult' variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS, we assess a range of candidate distributions, including the Sichel, Delaporte, Box-Cox Green and Cole, and Box-Cox t distributions. We find that the Box-Cox t distribution, with appropriate modeling of its parameters, best fits the conditional distribution of phonemic inventory size. We finally discuss the specificities of phoneme counts, weak effects, and how GAMLSS should be considered for other linguistic variables.

Predictors for Physical Activity in Adolescent Girls Using Statistical Shrinkage Techniques for Hierarchical Longitudinal Mixed Effects Models

PubMed Central

Grant, Edward M.; Young, Deborah Rohm; Wu, Tong Tong

2015-01-01

We examined associations among longitudinal, multilevel variables and girls’ physical activity to determine the important predictors for physical activity change at different adolescent ages. The Trial of Activity for Adolescent Girls 2 study (Maryland) contributed participants from 8th (2009) to 11th grade (2011) (n=561). Questionnaires were used to obtain demographic, and psychosocial information (individual- and social-level variables); height, weight, and triceps skinfold to assess body composition; interviews and surveys for school-level data; and self-report for neighborhood-level variables. Moderate to vigorous physical activity minutes were assessed from accelerometers. A doubly regularized linear mixed effects model was used for the longitudinal multilevel data to identify the most important covariates for physical activity. Three fixed effects at the individual level and one random effect at the school level were chosen from an initial total of 66 variables, consisting of 47 fixed effects and 19 random effects variables, in additional to the time effect. Self-management strategies, perceived barriers, and social support from friends were the three selected fixed effects, and whether intramural or interscholastic programs were offered in middle school was the selected random effect. Psychosocial factors and friend support, plus a school’s physical activity environment, affect adolescent girl’s moderate to vigorous physical activity longitudinally. PMID:25928064

Item Purification in Differential Item Functioning Using Generalized Linear Mixed Models

ERIC Educational Resources Information Center

Liu, Qian

2011-01-01

For this dissertation, four item purification procedures were implemented onto the generalized linear mixed model for differential item functioning (DIF) analysis, and the performance of these item purification procedures was investigated through a series of simulations. Among the four procedures, forward and generalized linear mixed model (GLMM)…

Alkali aluminosilicate melts and glasses: structuring at the middle range order of amorphous matter

NASA Astrophysics Data System (ADS)

Le Losq, C.; neuville, D. R.

2012-12-01

Rheological properties of silicate melts govern both magma ascension from the mantle to the surface of the earth and volcanological eruptions styles and behaviours. It is well known that several parameters impact strongly these properties, such as for instance the temperature, pressure, chemical composition and volatiles concentration, finally influencing eruptive behaviour of volcanoes. In this work, we will focus on the Na2O-K2O-Al2O3-SiO2 system, which is of a prime importance because it deals with a non-negligible part of natural melts, like for instance the Vesuvius (Italy) or Erebus (Antartica) magmas. In an oncoming paper in Chemical Geology (Le Losq and Neuville, 2012), we have communicated results of the study of mixing Na-K in tectosilicate melts containing a high concentration of silica (≥75mol%). In the present communication, we will enlarge this first point of view to tectosilicate melts presenting a lower silica concentration. We will first present our viscosity data, and then the Adam and Gibbs theory that allows theoretically modelling Na-K mixing in aluminosilicate melts by using the so-called "mixed alkali effect". On the basis of the rheological results, the Na-K mixing cannot be explained with the ideal "mixed alkali effect", which involves random exchange of Na-K cationic pairs. To go further and as rheological properties are directly linked with structural properties, we will present our first results obtained by Raman and NMR spectroscopy. These last ones provide important structural pieces of information on the polymerization state of glasses and melts, and also on the environment of tetrahedrally coordinated cations. Rheological and structural results all highlight that Na and K are not randomly distributed in aluminosilicate glasses and melts networks. Na melts present a network with some channels and a non-random distribution of Al and Si. K networks are different. They also present a non-random distribution of Al and Si, but in two sub-networks: one is rich in Si and fully polymerized, the other is richer in Al and K. The size of K+ ions combined to the charge-balancing needs of Al3+ ions determine this structuring of potassium melts. Mixing Na and K melts thus returns to mix two different networks: one composed of Na-Al-Si-O atoms and another of K-Al-Si-O atoms. This impact melts properties, inducing complicated and non-linear effects.

Individualizing drug dosage with longitudinal data.

PubMed

Zhu, Xiaolu; Qu, Annie

2016-10-30

We propose a two-step procedure to personalize drug dosage over time under the framework of a log-linear mixed-effect model. We model patients' heterogeneity using subject-specific random effects, which are treated as the realizations of an unspecified stochastic process. We extend the conditional quadratic inference function to estimate both fixed-effect coefficients and individual random effects on a longitudinal training data sample in the first step and propose an adaptive procedure to estimate new patients' random effects and provide dosage recommendations for new patients in the second step. An advantage of our approach is that we do not impose any distribution assumption on estimating random effects. Moreover, the new approach can accommodate more general time-varying covariates corresponding to random effects. We show in theory and numerical studies that the proposed method is more efficient compared with existing approaches, especially when covariates are time varying. In addition, a real data example of a clozapine study confirms that our two-step procedure leads to more accurate drug dosage recommendations. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Psychosocial education improves low back pain beliefs: results from a cluster randomized clinical trial (NCT00373009) in a primary prevention setting.

PubMed

George, Steven Z; Teyhen, Deydre S; Wu, Samuel S; Wright, Alison C; Dugan, Jessica L; Yang, Guijun; Robinson, Michael E; Childs, John D

2009-07-01

The general population has a pessimistic view of low back pain (LBP), and evidence-based information has been used to positively influence LBP beliefs in previously reported mass media studies. However, there is a lack of randomized trials investigating whether LBP beliefs can be modified in primary prevention settings. This cluster randomized clinical trial investigated the effect of an evidence-based psychosocial educational program (PSEP) on LBP beliefs for soldiers completing military training. A military setting was selected for this clinical trial, because LBP is a common cause of soldier disability. Companies of soldiers (n = 3,792) were recruited, and cluster randomized to receive a PSEP or no education (control group, CG). The PSEP consisted of an interactive seminar, and soldiers were issued the Back Book for reference material. The primary outcome measure was the back beliefs questionnaire (BBQ), which assesses inevitable consequences of and ability to cope with LBP. The BBQ was administered before randomization and 12 weeks later. A linear mixed model was fitted for the BBQ at the 12-week follow-up, and a generalized linear mixed model was fitted for the dichotomous outcomes on BBQ change of greater than two points. Sensitivity analyses were performed to account for drop out. BBQ scores (potential range: 9-45) improved significantly from baseline of 25.6 +/- 5.7 (mean +/- SD) to 26.9 +/- 6.2 for those receiving the PSEP, while there was a significant decline from 26.1 +/- 5.7 to 25.6 +/- 6.0 for those in the CG. The adjusted mean BBQ score at follow-up for those receiving the PSEP was 1.49 points higher than those in the CG (P < 0.0001). The adjusted odds ratio of BBQ improvement of greater than two points for those receiving the PSEP was 1.51 (95% CI = 1.22-1.86) times that of those in the CG. BBQ improvement was also mildly associated with race and college education. Sensitivity analyses suggested minimal influence of drop out. In conclusion, soldiers that received the PSEP had an improvement in their beliefs related to the inevitable consequences of and ability to cope with LBP. This is the first randomized trial to show positive influence on LBP beliefs in a primary prevention setting, and these findings have potentially important public health implications for prevention of LBP.

Influence diagnostics for count data under AB-BA crossover trials.

PubMed

Hao, Chengcheng; von Rosen, Dietrich; von Rosen, Tatjana

2017-12-01

This paper aims to develop diagnostic measures to assess the influence of data perturbations on estimates in AB-BA crossover studies with a Poisson distributed response. Generalised mixed linear models with normally distributed random effects are utilised. We show that in this special case, the model can be decomposed into two independent sub-models which allow to derive closed-form expressions to evaluate the changes in the maximum likelihood estimates under several perturbation schemes. The performance of the new influence measures is illustrated by simulation studies and the analysis of a real dataset.

Genetic parameters and signatures of selection in two divergent laying hen lines selected for feather pecking behaviour.

PubMed

Grams, Vanessa; Wellmann, Robin; Preuß, Siegfried; Grashorn, Michael A; Kjaer, Jörgen B; Bessei, Werner; Bennewitz, Jörn

2015-09-30

Feather pecking (FP) in laying hens is a well-known and multi-factorial behaviour with a genetic background. In a selection experiment, two lines were developed for 11 generations for high (HFP) and low (LFP) feather pecking, respectively. Starting with the second generation of selection, there was a constant difference in mean number of FP bouts between both lines. We used the data from this experiment to perform a quantitative genetic analysis and to map selection signatures. Pedigree and phenotypic data were available for the last six generations of both lines. Univariate quantitative genetic analyses were conducted using mixed linear and generalized mixed linear models assuming a Poisson distribution. Selection signatures were mapped using 33,228 single nucleotide polymorphisms (SNPs) genotyped on 41 HFP and 34 LFP individuals of generation 11. For each SNP, we estimated Wright's fixation index (FST). We tested the null hypothesis that FST is driven purely by genetic drift against the alternative hypothesis that it is driven by genetic drift and selection. The mixed linear model failed to analyze the LFP data because of the large number of 0s in the observation vector. The Poisson model fitted the data well and revealed a small but continuous genetic trend in both lines. Most of the 17 genome-wide significant SNPs were located on chromosomes 3 and 4. Thirteen clusters with at least two significant SNPs within an interval of 3 Mb maximum were identified. Two clusters were mapped on chromosomes 3, 4, 8 and 19. Of the 17 genome-wide significant SNPs, 12 were located within the identified clusters. This indicates a non-random distribution of significant SNPs and points to the presence of selection sweeps. Data on FP should be analysed using generalised linear mixed models assuming a Poisson distribution, especially if the number of FP bouts is small and the distribution is heavily peaked at 0. The FST-based approach was suitable to map selection signatures that need to be confirmed by linkage or association mapping.

Exploring compositional variations on the surface of Mars applying mixing modeling to a telescopic spectral image

NASA Technical Reports Server (NTRS)

Merenyi, E.; Miller, J. S.; Singer, R. B.

1992-01-01

The linear mixing model approach was successfully applied to data sets of various natures. In these sets, the measured radiance could be assumed to be a linear combination of radiance contributions. The present work is an attempt to analyze a spectral image of Mars with linear mixing modeling.

Stochastic Mixing Model with Power Law Decay of Variance

NASA Technical Reports Server (NTRS)

Fedotov, S.; Ihme, M.; Pitsch, H.

2003-01-01

Here we present a simple stochastic mixing model based on the law of large numbers (LLN). The reason why the LLN is involved in our formulation of the mixing problem is that the random conserved scalar c = c(t,x(t)) appears to behave as a sample mean. It converges to the mean value mu, while the variance sigma(sup 2)(sub c) (t) decays approximately as t(exp -1). Since the variance of the scalar decays faster than a sample mean (typically is greater than unity), we will introduce some non-linear modifications into the corresponding pdf-equation. The main idea is to develop a robust model which is independent from restrictive assumptions about the shape of the pdf. The remainder of this paper is organized as follows. In Section 2 we derive the integral equation from a stochastic difference equation describing the evolution of the pdf of a passive scalar in time. The stochastic difference equation introduces an exchange rate gamma(sub n) which we model in a first step as a deterministic function. In a second step, we generalize gamma(sub n) as a stochastic variable taking fluctuations in the inhomogeneous environment into account. In Section 3 we solve the non-linear integral equation numerically and analyze the influence of the different parameters on the decay rate. The paper finishes with a conclusion.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies

PubMed Central

Koerner, Tess K.; Zhang, Yang

2017-01-01

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers. PMID:28264422

GWAS with longitudinal phenotypes: performance of approximate procedures

PubMed Central

Sikorska, Karolina; Montazeri, Nahid Mostafavi; Uitterlinden, André; Rivadeneira, Fernando; Eilers, Paul HC; Lesaffre, Emmanuel

2015-01-01

Analysis of genome-wide association studies with longitudinal data using standard procedures, such as linear mixed model (LMM) fitting, leads to discouragingly long computation times. There is a need to speed up the computations significantly. In our previous work (Sikorska et al: Fast linear mixed model computations for genome-wide association studies with longitudinal data. Stat Med 2012; 32.1: 165–180), we proposed the conditional two-step (CTS) approach as a fast method providing an approximation to the P-value for the longitudinal single-nucleotide polymorphism (SNP) effect. In the first step a reduced conditional LMM is fit, omitting all the SNP terms. In the second step, the estimated random slopes are regressed on SNPs. The CTS has been applied to the bone mineral density data from the Rotterdam Study and proved to work very well even in unbalanced situations. In another article (Sikorska et al: GWAS on your notebook: fast semi-parallel linear and logistic regression for genome-wide association studies. BMC Bioinformatics 2013; 14: 166), we suggested semi-parallel computations, greatly speeding up fitting many linear regressions. Combining CTS with fast linear regression reduces the computation time from several weeks to a few minutes on a single computer. Here, we explore further the properties of the CTS both analytically and by simulations. We investigate the performance of our proposal in comparison with a related but different approach, the two-step procedure. It is analytically shown that for the balanced case, under mild assumptions, the P-value provided by the CTS is the same as from the LMM. For unbalanced data and in realistic situations, simulations show that the CTS method does not inflate the type I error rate and implies only a minimal loss of power. PMID:25712081

An MCMC method for the evaluation of the Fisher information matrix for non-linear mixed effect models.

PubMed

Riviere, Marie-Karelle; Ueckert, Sebastian; Mentré, France

2016-10-01

Non-linear mixed effect models (NLMEMs) are widely used for the analysis of longitudinal data. To design these studies, optimal design based on the expected Fisher information matrix (FIM) can be used instead of performing time-consuming clinical trial simulations. In recent years, estimation algorithms for NLMEMs have transitioned from linearization toward more exact higher-order methods. Optimal design, on the other hand, has mainly relied on first-order (FO) linearization to calculate the FIM. Although efficient in general, FO cannot be applied to complex non-linear models and with difficulty in studies with discrete data. We propose an approach to evaluate the expected FIM in NLMEMs for both discrete and continuous outcomes. We used Markov Chain Monte Carlo (MCMC) to integrate the derivatives of the log-likelihood over the random effects, and Monte Carlo to evaluate its expectation w.r.t. the observations. Our method was implemented in R using Stan, which efficiently draws MCMC samples and calculates partial derivatives of the log-likelihood. Evaluated on several examples, our approach showed good performance with relative standard errors (RSEs) close to those obtained by simulations. We studied the influence of the number of MC and MCMC samples and computed the uncertainty of the FIM evaluation. We also compared our approach to Adaptive Gaussian Quadrature, Laplace approximation, and FO. Our method is available in R-package MIXFIM and can be used to evaluate the FIM, its determinant with confidence intervals (CIs), and RSEs with CIs. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Investigating the linearity assumption between lumber grade mix and yield using design of experiments (DOE)

Treesearch

Xiaoqiu Zuo; Urs Buehlmann; R. Edward Thomas

2004-01-01

Solving the least-cost lumber grade mix problem allows dimension mills to minimize the cost of dimension part production. This problem, due to its economic importance, has attracted much attention from researchers and industry in the past. Most solutions used linear programming models and assumed that a simple linear relationship existed between lumber grade mix and...

Formation of parametric images using mixed-effects models: a feasibility study.

PubMed

Huang, Husan-Ming; Shih, Yi-Yu; Lin, Chieh

2016-03-01

Mixed-effects models have been widely used in the analysis of longitudinal data. By presenting the parameters as a combination of fixed effects and random effects, mixed-effects models incorporating both within- and between-subject variations are capable of improving parameter estimation. In this work, we demonstrate the feasibility of using a non-linear mixed-effects (NLME) approach for generating parametric images from medical imaging data of a single study. By assuming that all voxels in the image are independent, we used simulation and animal data to evaluate whether NLME can improve the voxel-wise parameter estimation. For testing purposes, intravoxel incoherent motion (IVIM) diffusion parameters including perfusion fraction, pseudo-diffusion coefficient and true diffusion coefficient were estimated using diffusion-weighted MR images and NLME through fitting the IVIM model. The conventional method of non-linear least squares (NLLS) was used as the standard approach for comparison of the resulted parametric images. In the simulated data, NLME provides more accurate and precise estimates of diffusion parameters compared with NLLS. Similarly, we found that NLME has the ability to improve the signal-to-noise ratio of parametric images obtained from rat brain data. These data have shown that it is feasible to apply NLME in parametric image generation, and the parametric image quality can be accordingly improved with the use of NLME. With the flexibility to be adapted to other models or modalities, NLME may become a useful tool to improve the parametric image quality in the future. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Promoting ball skills in preschool-age girls.

PubMed

Veldman, Sanne L C; Palmer, Kara K; Okely, Anthony D; Robinson, Leah E

2017-01-01

Evidence supports that girls are less proficient than boys at performing ball skills. This study examined the immediate and long-term effects of a ball skill intervention on preschool-age girls' ball skill performance. Randomized controlled trial. Girls (M age =47.24±7.38 months) were randomly assigned to a high autonomy, mastery-based 9-week motor skill intervention (the Children's Health Activity Motor Program; CHAMP, 540min; n=38) or a control group (free-play; n=16). Ball skill proficiency was assessed at pretest, posttest, and retention test (after 9 weeks) using the object control subscale of the Test of Gross Motor Development - 2nd Edition. Treatment efficacy was examined using linear mixed models. Two models were fit: one for short-term changes (pretest to posttest) and one for long-term changes (pretest to retention). Linear mixed models revealed a significantly time*treatment interaction for both models. Post hoc analysis confirmed that girls in CHAMP experienced significant gains in ball skills from pretest to posttest (p<.001) and pretest to retention (p<.001). Moreover, girls in CHAMP were no different from the control group at pretest (p>.05) but had significantly higher ball skills scores at both posttest (p<.001) and retention (p<.001). This study demonstrates the positive effects of a ball skill intervention (i.e., CHAMP) on improving girls' ball skills both short- and long-term. Findings suggest that early childhood interventions that focus on the development of ball skills in young girls might be an avenue to improve girls' ball skill performance. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

pLARmEB: integration of least angle regression with empirical Bayes for multilocus genome-wide association studies.

PubMed

Zhang, J; Feng, J-Y; Ni, Y-L; Wen, Y-J; Niu, Y; Tamba, C L; Yue, C; Song, Q; Zhang, Y-M

2017-06-01

Multilocus genome-wide association studies (GWAS) have become the state-of-the-art procedure to identify quantitative trait nucleotides (QTNs) associated with complex traits. However, implementation of multilocus model in GWAS is still difficult. In this study, we integrated least angle regression with empirical Bayes to perform multilocus GWAS under polygenic background control. We used an algorithm of model transformation that whitened the covariance matrix of the polygenic matrix K and environmental noise. Markers on one chromosome were included simultaneously in a multilocus model and least angle regression was used to select the most potentially associated single-nucleotide polymorphisms (SNPs), whereas the markers on the other chromosomes were used to calculate kinship matrix as polygenic background control. The selected SNPs in multilocus model were further detected for their association with the trait by empirical Bayes and likelihood ratio test. We herein refer to this method as the pLARmEB (polygenic-background-control-based least angle regression plus empirical Bayes). Results from simulation studies showed that pLARmEB was more powerful in QTN detection and more accurate in QTN effect estimation, had less false positive rate and required less computing time than Bayesian hierarchical generalized linear model, efficient mixed model association (EMMA) and least angle regression plus empirical Bayes. pLARmEB, multilocus random-SNP-effect mixed linear model and fast multilocus random-SNP-effect EMMA methods had almost equal power of QTN detection in simulation experiments. However, only pLARmEB identified 48 previously reported genes for 7 flowering time-related traits in Arabidopsis thaliana.

Predicting Endurance Time in a Repetitive Lift and Carry Task Using Linear Mixed Models

PubMed Central

Ham, Daniel J.; Best, Stuart A.; Carstairs, Greg L.; Savage, Robert J.; Straney, Lahn; Caldwell, Joanne N.

2016-01-01

Objectives Repetitive manual handling tasks account for a substantial portion of work-related injuries. However, few studies report endurance time in repetitive manual handling tasks. Consequently, there is little guidance to inform expected work time for repetitive manual handling tasks. We aimed to investigate endurance time and oxygen consumption of a repetitive lift and carry task using linear mixed models. Methods Fourteen male soldiers (age 22.4 ± 4.5 yrs, height 1.78 ± 0.04 m, body mass 76.3 ± 10.1 kg) conducted four assessment sessions that consisted of one maximal box lifting session and three lift and carry sessions. The relationships between carry mass (range 17.5–37.5 kg) and the duration of carry, and carry mass and oxygen consumption, were assessed using linear mixed models with random effects to account for between-subject variation. Results Results demonstrated that endurance time was inversely associated with carry mass (R2 = 0.24), with significant individual-level variation (R2 = 0.85). Normalising carry mass to performance in a maximal box lifting test improved the prediction of endurance time (R2 = 0.40). Oxygen consumption presented relative to total mass (body mass, external load and carried mass) was not significantly related to lift and carry mass (β1 = 0.16, SE = 0.10, 95%CI: -0.04, 0.36, p = 0.12), indicating that there was no change in oxygen consumption relative to total mass with increasing lift and carry mass. Conclusion Practically, these data can be used to guide work-rest schedules and provide insight into methods assessing the physical capacity of workers conducting repetitive manual handling tasks. PMID:27379902

Density-matrix description of heteronuclear decoupling in A mX n systems

NASA Astrophysics Data System (ADS)

McClung, R. E. D.; John, Boban K.

A detailed investigation of the effects of ordinary noise decoupling and spherical randomization decoupling on the elements of the density matrix for A mX n spin systems is presented. The elements are shown to reach steady-state values in the rotating frame of the decoupled nuclei when the decoupling field is strong and is applied for a sufficient time interval. The steady-state values are found to be linear combinations of the density-matrix elements at the beginning of the decoupling period, and often involve mixing of populations with multiple-quantum coherences, and mixing of the perpendicular components of the magnetization with higher coherences. This description of decoupling is shown to account for the "illusions" of spin decoupling in 2D gated-decoupler 13C J-resolved spectra reported by Levitt et al.

Molecular Interaction Control in Diblock Copolymer Blends and Multiblock Copolymers with Opposite Phase Behaviors

NASA Astrophysics Data System (ADS)

Cho, Junhan

2014-03-01

Here we show how to control molecular interactions via mixing AB and AC diblock copolymers, where one copolymer exhibits upper order-disorder transition and the other does lower disorder-order transition. Linear ABC triblock copolymers possessing both barotropic and baroplastic pairs are also taken into account. A recently developed random-phase approximation (RPA) theory and the self-consistent field theory (SCFT) for general compressible mixtures are used to analyze stability criteria and morphologies for the given systems. It is demonstrated that the copolymer systems can yield a variety of phase behaviors in their temperature and pressure dependence upon proper mixing conditions and compositions, which is caused by the delicate force fields generated in the systems. We acknowledge the financial support from National Research Foundation of Korea and Center for Photofunctional Energy Materials.

Linear mixed-effects modeling approach to FMRI group analysis

PubMed Central

Chen, Gang; Saad, Ziad S.; Britton, Jennifer C.; Pine, Daniel S.; Cox, Robert W.

2013-01-01

Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance–covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance–covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity for activation detection. The importance of hypothesis formulation is also illustrated in the simulations. Comparisons with alternative group analysis approaches and the limitations of LME are discussed in details. PMID:23376789

Linear mixed-effects modeling approach to FMRI group analysis.

PubMed

Chen, Gang; Saad, Ziad S; Britton, Jennifer C; Pine, Daniel S; Cox, Robert W

2013-06-01

Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance-covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance-covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity for activation detection. The importance of hypothesis formulation is also illustrated in the simulations. Comparisons with alternative group analysis approaches and the limitations of LME are discussed in details. Published by Elsevier Inc.

Mixed effect Poisson log-linear models for clinical and epidemiological sleep hypnogram data

PubMed Central

Swihart, Bruce J.; Caffo, Brian S.; Crainiceanu, Ciprian; Punjabi, Naresh M.

2013-01-01

Bayesian Poisson log-linear multilevel models scalable to epidemiological studies are proposed to investigate population variability in sleep state transition rates. Hierarchical random effects are used to account for pairings of subjects and repeated measures within those subjects, as comparing diseased to non-diseased subjects while minimizing bias is of importance. Essentially, non-parametric piecewise constant hazards are estimated and smoothed, allowing for time-varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming exponentially distributed survival times. Such re-derivation allows synthesis of two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed. Supplementary material includes the analyzed data set as well as the code for a reproducible analysis. PMID:22241689

Estimating the variance for heterogeneity in arm-based network meta-analysis.

PubMed

Piepho, Hans-Peter; Madden, Laurence V; Roger, James; Payne, Roger; Williams, Emlyn R

2018-04-19

Network meta-analysis can be implemented by using arm-based or contrast-based models. Here we focus on arm-based models and fit them using generalized linear mixed model procedures. Full maximum likelihood (ML) estimation leads to biased trial-by-treatment interaction variance estimates for heterogeneity. Thus, our objective is to investigate alternative approaches to variance estimation that reduce bias compared with full ML. Specifically, we use penalized quasi-likelihood/pseudo-likelihood and hierarchical (h) likelihood approaches. In addition, we consider a novel model modification that yields estimators akin to the residual maximum likelihood estimator for linear mixed models. The proposed methods are compared by simulation, and 2 real datasets are used for illustration. Simulations show that penalized quasi-likelihood/pseudo-likelihood and h-likelihood reduce bias and yield satisfactory coverage rates. Sum-to-zero restriction and baseline contrasts for random trial-by-treatment interaction effects, as well as a residual ML-like adjustment, also reduce bias compared with an unconstrained model when ML is used, but coverage rates are not quite as good. Penalized quasi-likelihood/pseudo-likelihood and h-likelihood are therefore recommended. Copyright © 2018 John Wiley & Sons, Ltd.

Subpixel Mapping of Hyperspectral Image Based on Linear Subpixel Feature Detection and Object Optimization

NASA Astrophysics Data System (ADS)

Liu, Zhaoxin; Zhao, Liaoying; Li, Xiaorun; Chen, Shuhan

2018-04-01

Owing to the limitation of spatial resolution of the imaging sensor and the variability of ground surfaces, mixed pixels are widesperead in hyperspectral imagery. The traditional subpixel mapping algorithms treat all mixed pixels as boundary-mixed pixels while ignoring the existence of linear subpixels. To solve this question, this paper proposed a new subpixel mapping method based on linear subpixel feature detection and object optimization. Firstly, the fraction value of each class is obtained by spectral unmixing. Secondly, the linear subpixel features are pre-determined based on the hyperspectral characteristics and the linear subpixel feature; the remaining mixed pixels are detected based on maximum linearization index analysis. The classes of linear subpixels are determined by using template matching method. Finally, the whole subpixel mapping results are iteratively optimized by binary particle swarm optimization algorithm. The performance of the proposed subpixel mapping method is evaluated via experiments based on simulated and real hyperspectral data sets. The experimental results demonstrate that the proposed method can improve the accuracy of subpixel mapping.

Application of Hierarchical Linear Models/Linear Mixed-Effects Models in School Effectiveness Research

ERIC Educational Resources Information Center

Ker, H. W.

2014-01-01

Multilevel data are very common in educational research. Hierarchical linear models/linear mixed-effects models (HLMs/LMEs) are often utilized to analyze multilevel data nowadays. This paper discusses the problems of utilizing ordinary regressions for modeling multilevel educational data, compare the data analytic results from three regression…

Box-Cox Mixed Logit Model for Travel Behavior Analysis

NASA Astrophysics Data System (ADS)

Orro, Alfonso; Novales, Margarita; Benitez, Francisco G.

2010-09-01

To represent the behavior of travelers when they are deciding how they are going to get to their destination, discrete choice models, based on the random utility theory, have become one of the most widely used tools. The field in which these models were developed was halfway between econometrics and transport engineering, although the latter now constitutes one of their principal areas of application. In the transport field, they have mainly been applied to mode choice, but also to the selection of destination, route, and other important decisions such as the vehicle ownership. In usual practice, the most frequently employed discrete choice models implement a fixed coefficient utility function that is linear in the parameters. The principal aim of this paper is to present the viability of specifying utility functions with random coefficients that are nonlinear in the parameters, in applications of discrete choice models to transport. Nonlinear specifications in the parameters were present in discrete choice theory at its outset, although they have seldom been used in practice until recently. The specification of random coefficients, however, began with the probit and the hedonic models in the 1970s, and, after a period of apparent little practical interest, has burgeoned into a field of intense activity in recent years with the new generation of mixed logit models. In this communication, we present a Box-Cox mixed logit model, original of the authors. It includes the estimation of the Box-Cox exponents in addition to the parameters of the random coefficients distribution. Probability of choose an alternative is an integral that will be calculated by simulation. The estimation of the model is carried out by maximizing the simulated log-likelihood of a sample of observed individual choices between alternatives. The differences between the predictions yielded by models that are inconsistent with real behavior have been studied with simulation experiments.

Onset of natural convection in a continuously perturbed system

NASA Astrophysics Data System (ADS)

Ghorbani, Zohreh; Riaz, Amir

2017-11-01

The convective mixing triggered by gravitational instability plays an important role in CO2 sequestration in saline aquifers. The linear stability analysis and the numerical simulation concerning convective mixing in porous media requires perturbations of small amplitude to be imposed on the concentration field in the form of an initial shape function. In aquifers, however, the instability is triggered by local porosity and permeability. In this work, we consider a canonical 2D homogeneous system where perturbations arise due to spatial variation of porosity in the system. The advantage of this approach is not only the elimination of the required initial shape function, but it also serves as a more realistic approach. Using a reduced nonlinear method, we first explore the effect of harmonic variations of porosity in the transverse and streamwise direction on the onset time of convection and late time behavior. We then obtain the optimal porosity structure that minimizes the convection onset. We further examine the effect of a random porosity distribution, that is independent of the spatial mode of porosity structure, on the convection onset. Using high-order pseudospectral DNS, we explore how the random distribution differs from the modal approach in predicting the onset time.

Quantum Entanglement in Random Physical States

NASA Astrophysics Data System (ADS)

Hamma, Alioscia; Santra, Siddhartha; Zanardi, Paolo

2012-07-01

Most states in the Hilbert space are maximally entangled. This fact has proven useful to investigate—among other things—the foundations of statistical mechanics. Unfortunately, most states in the Hilbert space of a quantum many-body system are not physically accessible. We define physical ensembles of states acting on random factorized states by a circuit of length k of random and independent unitaries with local support. We study the typicality of entanglement by means of the purity of the reduced state. We find that for a time k=O(1), the typical purity obeys the area law. Thus, the upper bounds for area law are actually saturated, on average, with a variance that goes to zero for large systems. Similarly, we prove that by means of local evolution a subsystem of linear dimensions L is typically entangled with a volume law when the time scales with the size of the subsystem. Moreover, we show that for large values of k the reduced state becomes very close to the completely mixed state.

Outcomes of a Pilot Hand Hygiene Randomized Cluster Trial to Reduce Communicable Infections Among US Office-Based Employees

PubMed Central

DuBois, Cathy L.Z.; Grey, Scott F.; Kingsbury, Diana M.; Shakya, Sunita; Scofield, Jennifer; Slenkovich, Ken

2015-01-01

Objective: To determine the effectiveness of an office-based multimodal hand hygiene improvement intervention in reducing self-reported communicable infections and work-related absence. Methods: A randomized cluster trial including an electronic training video, hand sanitizer, and educational posters (n = 131, intervention; n = 193, control). Primary outcomes include (1) self-reported acute respiratory infections (ARIs)/influenza-like illness (ILI) and/or gastrointestinal (GI) infections during the prior 30 days; and (2) related lost work days. Incidence rate ratios calculated using generalized linear mixed models with a Poisson distribution, adjusted for confounders and random cluster effects. Results: A 31% relative reduction in self-reported combined ARI-ILI/GI infections (incidence rate ratio: 0.69; 95% confidence interval, 0.49 to 0.98). A 21% nonsignificant relative reduction in lost work days. Conclusions: An office-based multimodal hand hygiene improvement intervention demonstrated a substantive reduction in self-reported combined ARI-ILI/GI infections. PMID:25719534

A randomized-control trial for the teachers' diploma programme on psychosocial care, support and protection in Zambian government primary schools.

PubMed

Kaljee, Linda; Zhang, Liying; Langhaug, Lisa; Munjile, Kelvin; Tembo, Stephen; Menon, Anitha; Stanton, Bonita; Li, Xiaoming; Malungo, Jacob

2017-04-01

Orphaned and vulnerable children (OVC) experience poverty, stigma, and abuse resulting in poor physical, emotional, and psychological outcomes. The Teachers' Diploma Programme on Psychosocial Care, Support, and Protection is a child-centered 15-month long-distance learning program focused on providing teachers with the knowledge and skills to enhance their school environments, foster psychosocial support, and facilitate school-community relationships. A randomized controlled trial was implemented in 2013-2014. Both teachers (n=325) and students (n=1378) were assessed at baseline and 15-months post-intervention from randomly assigned primary schools in Lusaka and Eastern Provinces, Zambia. Multilevel linear mixed models (MLM) indicate positive significant changes for intervention teachers on outcomes related to self-care, teaching resources, safety, social support, and gender equity. Positive outcomes for intervention students related to future orientation, respect, support, safety, sexual abuse, and bullying. Outcomes support the hypothesis that teachers and students benefit from a program designed to enhance teachers' psychosocial skills and knowledge.

Effect of spray-dried bovine serum on intake, health, and growth of broilers housed in different environments.

PubMed

Campbell, J M; Quigley, J D; Russell, L E; Kidd, M T

2003-11-01

Three experiments utilizing broilers were conducted in different environments to evaluate the effects of Innavax (INX; spray-dried serum) administered in drinking water on broiler performance. In Exp. 1 (1 to 42 d), 252 Ross x Cobb male broilers were assigned randomly to one of six treatments consisting of tap water mixed with 0, 0.25, 0.50, 0.75, 1.0, or 1.25% (wt/wt) INX. Broilers (six broilers per pen; seven pens per treatment) were housed in Petersime battery cages (raised wire flooring) in temperature-controlled rooms. Average daily gain, and feed and water intake (as-fed) were not affected (P > 0.05) by experimental treatments. Feed efficiency tended to improve linearly (P = 0.076) from d 0 to 7 with increasing levels of INX, but was unaffected (P > 0.05) during the remaining periods. In Exp. 2 and 3, 800 Ross x Ross 308 male broilers (400 broilers in each trial; 10 broilers per pen; 10 pens per treatment) in two 21-d experiments were assigned randomly to one of four treatments consisting of tap water mixed with 0, 0.45, 0.90, or 1.35% (wt/wt) INX. Broilers were housed in floor pens containing clean (Exp. 2) or used (Exp. 3) litter. In Exp. 2, intake, ADG, and feed efficiency were linearly improved (P < 0.05) during the first week with increasing levels of INX. During the second week (d 8 to 14), ADG, water intake, and feed efficiency were linearly improved (P < 0.05) with increasing levels of INX. In the third week (d 15 to 21), ADG and feed and water intake were not affected (P > 0.10) by level of INX. Overall (d 0 to 21), ADG, intake, and feed efficiency were linearly improved (P < 0.05) with INX. In Exp. 3, ADG, water intake, and feed efficiency were linearly improved (P < 0.05) during each period. Feed intake was not affected (P > 0.05) by experimental treatment during d 0 to 7, but was linearly increased (P < 0.05) from d 8 to 14 and 15 to 21. The greatest growth response of broilers to INX was observed when broilers were housed in floor pens with used litter, followed by floor pens with clean litter and battery pens. Further research on the relationship between the response to INX and housing conditions seems warranted.

An R2 statistic for fixed effects in the linear mixed model.

PubMed

Edwards, Lloyd J; Muller, Keith E; Wolfinger, Russell D; Qaqish, Bahjat F; Schabenberger, Oliver

2008-12-20

Statisticians most often use the linear mixed model to analyze Gaussian longitudinal data. The value and familiarity of the R(2) statistic in the linear univariate model naturally creates great interest in extending it to the linear mixed model. We define and describe how to compute a model R(2) statistic for the linear mixed model by using only a single model. The proposed R(2) statistic measures multivariate association between the repeated outcomes and the fixed effects in the linear mixed model. The R(2) statistic arises as a 1-1 function of an appropriate F statistic for testing all fixed effects (except typically the intercept) in a full model. The statistic compares the full model with a null model with all fixed effects deleted (except typically the intercept) while retaining exactly the same covariance structure. Furthermore, the R(2) statistic leads immediately to a natural definition of a partial R(2) statistic. A mixed model in which ethnicity gives a very small p-value as a longitudinal predictor of blood pressure (BP) compellingly illustrates the value of the statistic. In sharp contrast to the extreme p-value, a very small R(2) , a measure of statistical and scientific importance, indicates that ethnicity has an almost negligible association with the repeated BP outcomes for the study.

Convex set and linear mixing model

NASA Technical Reports Server (NTRS)

Xu, P.; Greeley, R.

1993-01-01

A major goal of optical remote sensing is to determine surface compositions of the earth and other planetary objects. For assessment of composition, single pixels in multi-spectral images usually record a mixture of the signals from various materials within the corresponding surface area. In this report, we introduce a closed and bounded convex set as a mathematical model for linear mixing. This model has a clear geometric implication because the closed and bounded convex set is a natural generalization of a triangle in n-space. The endmembers are extreme points of the convex set. Every point in the convex closure of the endmembers is a linear mixture of those endmembers, which is exactly how linear mixing is defined. With this model, some general criteria for selecting endmembers could be described. This model can lead to a better understanding of linear mixing models.

An Efficient Alternative Mixed Randomized Response Procedure

ERIC Educational Resources Information Center

Singh, Housila P.; Tarray, Tanveer A.

2015-01-01

In this article, we have suggested a new modified mixed randomized response (RR) model and studied its properties. It is shown that the proposed mixed RR model is always more efficient than the Kim and Warde's mixed RR model. The proposed mixed RR model has also been extended to stratified sampling. Numerical illustrations and graphical…

An Integrated Method to Analyze Farm Vulnerability to Climatic and Economic Variability According to Farm Configurations and Farmers' Adaptations.

PubMed

Martin, Guillaume; Magne, Marie-Angélina; Cristobal, Magali San

2017-01-01

The need to adapt to decrease farm vulnerability to adverse contextual events has been extensively discussed on a theoretical basis. We developed an integrated and operational method to assess farm vulnerability to multiple and interacting contextual changes and explain how this vulnerability can best be reduced according to farm configurations and farmers' technical adaptations over time. Our method considers farm vulnerability as a function of the raw measurements of vulnerability variables (e.g., economic efficiency of production), the slope of the linear regression of these measurements over time, and the residuals of this linear regression. The last two are extracted from linear mixed models considering a random regression coefficient (an intercept common to all farms), a global trend (a slope common to all farms), a random deviation from the general mean for each farm, and a random deviation from the general trend for each farm. Among all possible combinations, the lowest farm vulnerability is obtained through a combination of high values of measurements, a stable or increasing trend and low variability for all vulnerability variables considered. Our method enables relating the measurements, trends and residuals of vulnerability variables to explanatory variables that illustrate farm exposure to climatic and economic variability, initial farm configurations and farmers' technical adaptations over time. We applied our method to 19 cattle (beef, dairy, and mixed) farms over the period 2008-2013. Selected vulnerability variables, i.e., farm productivity and economic efficiency, varied greatly among cattle farms and across years, with means ranging from 43.0 to 270.0 kg protein/ha and 29.4-66.0% efficiency, respectively. No farm had a high level, stable or increasing trend and low residuals for both farm productivity and economic efficiency of production. Thus, the least vulnerable farms represented a compromise among measurement value, trend, and variability of both performances. No specific combination of farmers' practices emerged for reducing cattle farm vulnerability to climatic and economic variability. In the least vulnerable farms, the practices implemented (stocking rate, input use…) were more consistent with the objective of developing the properties targeted (efficiency, robustness…). Our method can be used to support farmers with sector-specific and local insights about most promising farm adaptations.

An Integrated Method to Analyze Farm Vulnerability to Climatic and Economic Variability According to Farm Configurations and Farmers’ Adaptations

PubMed Central

Martin, Guillaume; Magne, Marie-Angélina; Cristobal, Magali San

2017-01-01

The need to adapt to decrease farm vulnerability to adverse contextual events has been extensively discussed on a theoretical basis. We developed an integrated and operational method to assess farm vulnerability to multiple and interacting contextual changes and explain how this vulnerability can best be reduced according to farm configurations and farmers’ technical adaptations over time. Our method considers farm vulnerability as a function of the raw measurements of vulnerability variables (e.g., economic efficiency of production), the slope of the linear regression of these measurements over time, and the residuals of this linear regression. The last two are extracted from linear mixed models considering a random regression coefficient (an intercept common to all farms), a global trend (a slope common to all farms), a random deviation from the general mean for each farm, and a random deviation from the general trend for each farm. Among all possible combinations, the lowest farm vulnerability is obtained through a combination of high values of measurements, a stable or increasing trend and low variability for all vulnerability variables considered. Our method enables relating the measurements, trends and residuals of vulnerability variables to explanatory variables that illustrate farm exposure to climatic and economic variability, initial farm configurations and farmers’ technical adaptations over time. We applied our method to 19 cattle (beef, dairy, and mixed) farms over the period 2008–2013. Selected vulnerability variables, i.e., farm productivity and economic efficiency, varied greatly among cattle farms and across years, with means ranging from 43.0 to 270.0 kg protein/ha and 29.4–66.0% efficiency, respectively. No farm had a high level, stable or increasing trend and low residuals for both farm productivity and economic efficiency of production. Thus, the least vulnerable farms represented a compromise among measurement value, trend, and variability of both performances. No specific combination of farmers’ practices emerged for reducing cattle farm vulnerability to climatic and economic variability. In the least vulnerable farms, the practices implemented (stocking rate, input use…) were more consistent with the objective of developing the properties targeted (efficiency, robustness…). Our method can be used to support farmers with sector-specific and local insights about most promising farm adaptations. PMID:28900435

Using structural equation modeling for network meta-analysis.

PubMed

Tu, Yu-Kang; Wu, Yun-Chun

2017-07-14

Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison. SEM provides a very flexible framework for univariate and multivariate meta-analysis, and its potential as a powerful tool for advanced meta-analysis is still to be explored.

The Denaturation Transition of DNA in Mixed Solvents

PubMed Central

Hammouda, Boualem; Worcester, David

2006-01-01

The helix-to-coil denaturation transition in DNA has been investigated in mixed solvents at high concentration using ultraviolet light absorption spectroscopy and small-angle neutron scattering. Two solvents have been used: water and ethylene glycol. The “melting” transition temperature was found to be 94°C for 4% mass fraction DNA/d-water and 38°C for 4% mass fraction DNA/d-ethylene glycol. The DNA melting transition temperature was found to vary linearly with the solvent fraction in the mixed solvents case. Deuterated solvents (d-water and d-ethylene glycol) were used to enhance the small-angle neutron scattering signal and 0.1M NaCl (or 0.0058 g/g mass fraction) salt concentration was added to screen charge interactions in all cases. DNA structural information was obtained by small-angle neutron scattering, including a correlation length characteristic of the inter-distance between the hydrogen-containing (desoxyribose sugar-amine base) groups. This correlation length was found to increase from 8.5 to 12.3 Å across the melting transition. Ethylene glycol and water mixed solvents were found to mix randomly in the solvation region in the helix phase, but nonideal solvent mixing was found in the melted coil phase. In the coil phase, solvent mixtures are more effective solvating agents than either of the individual solvents. Once melted, DNA coils behave like swollen water-soluble synthetic polymer chains. PMID:16815902

An adaptive random search for short term generation scheduling with network constraints.

PubMed

Marmolejo, J A; Velasco, Jonás; Selley, Héctor J

2017-01-01

This paper presents an adaptive random search approach to address a short term generation scheduling with network constraints, which determines the startup and shutdown schedules of thermal units over a given planning horizon. In this model, we consider the transmission network through capacity limits and line losses. The mathematical model is stated in the form of a Mixed Integer Non Linear Problem with binary variables. The proposed heuristic is a population-based method that generates a set of new potential solutions via a random search strategy. The random search is based on the Markov Chain Monte Carlo method. The main key of the proposed method is that the noise level of the random search is adaptively controlled in order to exploring and exploiting the entire search space. In order to improve the solutions, we consider coupling a local search into random search process. Several test systems are presented to evaluate the performance of the proposed heuristic. We use a commercial optimizer to compare the quality of the solutions provided by the proposed method. The solution of the proposed algorithm showed a significant reduction in computational effort with respect to the full-scale outer approximation commercial solver. Numerical results show the potential and robustness of our approach.

Marginal and Random Intercepts Models for Longitudinal Binary Data With Examples From Criminology.

PubMed

Long, Jeffrey D; Loeber, Rolf; Farrington, David P

2009-01-01

Two models for the analysis of longitudinal binary data are discussed: the marginal model and the random intercepts model. In contrast to the linear mixed model (LMM), the two models for binary data are not subsumed under a single hierarchical model. The marginal model provides group-level information whereas the random intercepts model provides individual-level information including information about heterogeneity of growth. It is shown how a type of numerical averaging can be used with the random intercepts model to obtain group-level information, thus approximating individual and marginal aspects of the LMM. The types of inferences associated with each model are illustrated with longitudinal criminal offending data based on N = 506 males followed over a 22-year period. Violent offending indexed by official records and self-report were analyzed, with the marginal model estimated using generalized estimating equations and the random intercepts model estimated using maximum likelihood. The results show that the numerical averaging based on the random intercepts can produce prediction curves almost identical to those obtained directly from the marginal model parameter estimates. The results provide a basis for contrasting the models and the estimation procedures and key features are discussed to aid in selecting a method for empirical analysis.

Optimization of light quality from color mixing light-emitting diode systems for general lighting

NASA Astrophysics Data System (ADS)

Thorseth, Anders

2012-03-01

Given the problem of metamerisms inherent in color mixing in light-emitting diode (LED) systems with more than three distinct colors, a method for optimizing the spectral output of multicolor LED system with regards to standardized light quality parameters has been developed. The composite spectral power distribution from the LEDs are simulated using spectral radiometric measurements of single commercially available LEDs for varying input power, to account for the efficiency droop and other non-linear effects in electrical power vs. light output. The method uses electrical input powers as input parameters in a randomized steepest decent optimization. The resulting spectral power distributions are evaluated with regard to the light quality using the standard characteristics: CIE color rendering index, correlated color temperature and chromaticity distance. The results indicate Pareto optimal boundaries for each system, mapping the capabilities of the simulated lighting systems with regard to the light quality characteristics.

Genomic selection for slaughter age in pigs using the Cox frailty model.

PubMed

Santos, V S; Martins Filho, S; Resende, M D V; Azevedo, C F; Lopes, P S; Guimarães, S E F; Glória, L S; Silva, F F

2015-10-19

The aim of this study was to compare genomic selection methodologies using a linear mixed model and the Cox survival model. We used data from an F2 population of pigs, in which the response variable was the time in days from birth to the culling of the animal and the covariates were 238 markers [237 single nucleotide polymorphism (SNP) plus the halothane gene]. The data were corrected for fixed effects, and the accuracy of the method was determined based on the correlation of the ranks of predicted genomic breeding values (GBVs) in both models with the corrected phenotypic values. The analysis was repeated with a subset of SNP markers with largest absolute effects. The results were in agreement with the GBV prediction and the estimation of marker effects for both models for uncensored data and for normality. However, when considering censored data, the Cox model with a normal random effect (S1) was more appropriate. Since there was no agreement between the linear mixed model and the imputed data (L2) for the prediction of genomic values and the estimation of marker effects, the model S1 was considered superior as it took into account the latent variable and the censored data. Marker selection increased correlations between the ranks of predicted GBVs by the linear and Cox frailty models and the corrected phenotypic values, and 120 markers were required to increase the predictive ability for the characteristic analyzed.

A Communication Intervention to Reduce Resistiveness in Dementia Care: A Cluster Randomized Controlled Trial.

PubMed

Williams, Kristine N; Perkhounkova, Yelena; Herman, Ruth; Bossen, Ann

2017-08-01

Nursing home (NH) residents with dementia exhibit challenging behaviors or resistiveness to care (RTC) that increase staff time, stress, and NH costs. RTC is linked to elderspeak communication. Communication training (Changing Talk [CHAT]) was provided to staff to reduce their use of elderspeak. We hypothesized that CHAT would improve staff communication and subsequently reduce RTC. Thirteen NHs were randomized to intervention and control groups. Dyads (n = 42) including 29 staff and 27 persons with dementia were videorecorded during care before and/or after the intervention and at a 3-month follow-up. Videos were behaviorally coded for (a) staff communication (normal, elderspeak, or silence) and (b) resident behaviors (cooperative or RTC). Linear mixed modeling was used to evaluate training effects. On average, elderspeak declined from 34.6% (SD = 18.7) at baseline by 13.6% points (SD = 20.00) post intervention and 12.2% points (SD = 22.0) at 3-month follow-up. RTC declined from 35.7% (SD = 23.2) by 15.3% points (SD = 32.4) post intervention and 13.4% points (SD = 33.7) at 3 months. Linear mixed modeling determined that change in elderspeak was predicted by the intervention (b = -12.20, p = .028) and baseline elderspeak (b = -0.65, p < .001), whereas RTC change was predicted by elderspeak change (b = 0.43, p < .001); baseline RTC (b = -0.58, p < .001); and covariates. A brief intervention can improve communication and reduce RTC, providing an effective nonpharmacological intervention to manage behavior and improve the quality of dementia care. No adverse events occurred. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Contrasting performance of donor-acceptor copolymer pairs in ternary blend solar cells and two-acceptor copolymers in binary blend solar cells.

PubMed

Khlyabich, Petr P; Rudenko, Andrey E; Burkhart, Beate; Thompson, Barry C

2015-02-04

Here two contrasting approaches to polymer-fullerene solar cells are compared. In the first approach, two distinct semi-random donor-acceptor copolymers are blended with phenyl-C61-butyric acid methyl ester (PC61BM) to form ternary blend solar cells. The two poly(3-hexylthiophene)-based polymers contain either the acceptor thienopyrroledione (TPD) or diketopyrrolopyrrole (DPP). In the second approach, semi-random donor-acceptor copolymers containing both TPD and DPP acceptors in the same polymer backbone, termed two-acceptor polymers, are blended with PC61BM to give binary blend solar cells. The two approaches result in bulk heterojunction solar cells that have the same molecular active-layer components but differ in the manner in which these molecular components are mixed, either by physical mixing (ternary blend) or chemical "mixing" in the two-acceptor (binary blend) case. Optical properties and photon-to-electron conversion efficiencies of the binary and ternary blends were found to have similar features and were described as a linear combination of the individual components. At the same time, significant differences were observed in the open-circuit voltage (Voc) behaviors of binary and ternary blend solar cells. While in case of two-acceptor polymers, the Voc was found to be in the range of 0.495-0.552 V, ternary blend solar cells showed behavior inherent to organic alloy formation, displaying an intermediate, composition-dependent and tunable Voc in the range from 0.582 to 0.684 V, significantly exceeding the values achieved in the two-acceptor containing binary blend solar cells. Despite the differences between the physical and chemical mixing approaches, both pathways provided solar cells with similar power conversion efficiencies, highlighting the advantages of both pathways toward highly efficient organic solar cells.

Evolution of the concentration PDF in random environments modeled by global random walk

NASA Astrophysics Data System (ADS)

Suciu, Nicolae; Vamos, Calin; Attinger, Sabine; Knabner, Peter

2013-04-01

The evolution of the probability density function (PDF) of concentrations of chemical species transported in random environments is often modeled by ensembles of notional particles. The particles move in physical space along stochastic-Lagrangian trajectories governed by Ito equations, with drift coefficients given by the local values of the resolved velocity field and diffusion coefficients obtained by stochastic or space-filtering upscaling procedures. A general model for the sub-grid mixing also can be formulated as a system of Ito equations solving for trajectories in the composition space. The PDF is finally estimated by the number of particles in space-concentration control volumes. In spite of their efficiency, Lagrangian approaches suffer from two severe limitations. Since the particle trajectories are constructed sequentially, the demanded computing resources increase linearly with the number of particles. Moreover, the need to gather particles at the center of computational cells to perform the mixing step and to estimate statistical parameters, as well as the interpolation of various terms to particle positions, inevitably produce numerical diffusion in either particle-mesh or grid-free particle methods. To overcome these limitations, we introduce a global random walk method to solve the system of Ito equations in physical and composition spaces, which models the evolution of the random concentration's PDF. The algorithm consists of a superposition on a regular lattice of many weak Euler schemes for the set of Ito equations. Since all particles starting from a site of the space-concentration lattice are spread in a single numerical procedure, one obtains PDF estimates at the lattice sites at computational costs comparable with those for solving the system of Ito equations associated to a single particle. The new method avoids the limitations concerning the number of particles in Lagrangian approaches, completely removes the numerical diffusion, and speeds up the computation by orders of magnitude. The approach is illustrated for the transport of passive scalars in heterogeneous aquifers, with hydraulic conductivity modeled as a random field.

Therapeutic alliance in a randomized clinical trial for bulimia nervosa

PubMed Central

Accurso, Erin C.; Fitzsimmons-Craft, Ellen E.; Ciao, Anna; Cao, Li; Crosby, Ross D.; Smith, Tracey L.; Klein, Marjorie H.; Mitchell, James E.; Crow, Scott J.; Wonderlich, Stephen A.; Peterson, Carol B.

2015-01-01

Objective This study examined the temporal relation between therapeutic alliance and outcome in two treatments for bulimia nervosa (BN). Method Eighty adults with BN symptoms were randomized to 21 sessions of integrative cognitive-affective therapy (ICAT) or enhanced cognitive-behavioral therapy (CBT-E). Bulimic symptoms (i.e., frequency of binge eating and purging) were assessed at each session and post-treatment. Therapeutic alliance (Working Alliance Inventory) was assessed at sessions 2, 8, 14, and post-treatment. Repeated-measures analyses using linear mixed models with random intercepts were conducted to determine differences in alliance growth by treatment and patient characteristics. Mixed-effects models examined the relation between alliance and symptom improvement. Results Overall, patients in both treatments reported strong therapeutic alliances. Regardless of treatment, greater therapeutic alliance between (but not within) subjects predicted greater reductions in bulimic behavior; reductions in bulimic behavior also predicted improved alliance. Patients with higher depression, anxiety, or emotion dysregulation had a stronger therapeutic alliance in CBT-E than ICAT, while those with more intimacy problems had greater improvement in therapeutic alliance in ICAT compared to CBT-E. Conclusions Therapeutic alliance has a unique impact on outcome, independent of the impact of symptom improvement on alliance. Within- and between-subject effects revealed that changes in alliance over time did not predict symptom improvement, but rather that individuals who had a stronger alliance overall had better bulimic symptom outcomes. These findings indicate that therapeutic alliance is an important predictor of outcome in the treatment of BN. PMID:25894667

Therapeutic alliance in a randomized clinical trial for bulimia nervosa.

PubMed

Accurso, Erin C; Fitzsimmons-Craft, Ellen E; Ciao, Anna; Cao, Li; Crosby, Ross D; Smith, Tracey L; Klein, Marjorie H; Mitchell, James E; Crow, Scott J; Wonderlich, Stephen A; Peterson, Carol B

2015-06-01

This study examined the temporal relation between therapeutic alliance and outcome in two treatments for bulimia nervosa (BN). Eighty adults with BN symptoms were randomized to 21 sessions of integrative cognitive-affective therapy (ICAT) or enhanced cognitive-behavioral therapy (CBT-E). Bulimic symptoms (i.e., frequency of binge eating and purging) were assessed at each session and posttreatment. Therapeutic alliance (Working Alliance Inventory) was assessed at Sessions 2, 8, 14, and posttreatment. Repeated-measures analyses using linear mixed models with random intercepts were conducted to determine differences in alliance growth by treatment and patient characteristics. Mixed-effects models examined the relation between alliance and symptom improvement. Overall, patients in both treatments reported strong therapeutic alliances. Regardless of treatment, greater therapeutic alliance between (but not within) subjects predicted greater reductions in bulimic behavior; reductions in bulimic behavior also predicted improved alliance. Patients with higher depression, anxiety, or emotion dysregulation had a stronger therapeutic alliance in CBT-E than ICAT, while those with more intimacy problems had greater improvement in therapeutic alliance in ICAT compared to CBT-E. Therapeutic alliance has a unique impact on outcome, independent of the impact of symptom improvement on alliance. Within- and between-subjects effects revealed that changes in alliance over time did not predict symptom improvement, but rather that individuals who had a stronger alliance overall had better bulimic symptom outcomes. These findings indicate that therapeutic alliance is an important predictor of outcome in the treatment of BN. (c) 2015 APA, all rights reserved).

Communication: Photoionization of degenerate orbitals for randomly oriented molecules: The effect of time-reversal symmetry on recoil-ion momentum angular distributions

NASA Astrophysics Data System (ADS)

Suzuki, Yoshi-Ichi

2018-04-01

The photoelectron asymmetry parameter β, which characterizes the direction of electrons ejected from a randomly oriented molecular ensemble by linearly polarized light, is investigated for degenerate orbitals. We show that β is totally symmetric under the symmetry operation of the point group of a molecule, and it has mixed properties under time reversal. Therefore, all degenerate molecular orbitals, except for the case of degeneracy due to time reversal, have the same β (Wigner-Eckart theorem). The exceptions are e-type complex orbitals of the Cn, Sn, Cnh, T, and Th point groups, and calculations on boric acid (C3h symmetry) are performed as an example. However, including those point groups, all degenerate orbitals have the same β if those orbitals are real. We discuss the implications of this operator formalism for molecular alignment and photoelectron circular dichroism.

The value of comparative research in major day surgery.

PubMed

Llop-Gironés, Alba; Vergara-Duarte, Montse; Sánchez, Josep Anton; Tarafa, Gemma; Benach, Joan

2017-05-19

To measure time trends in major day surgery rates according to hospital ownership and other hospital characteristics among the providers of the public healthcare network of Catalonia, Spain. Data from the Statistics of Health Establishments providing Inpatient Care. A generalized linear mixed model with Gaussian response and random intercept and random slopes. The greatest growth in the rate of major day surgery was observed among private for-profit hospitals: 42.9 (SD: 22.5) in 2009 versus 2.7 (SD: 6.7) in 1996. These hospitals exhibited a significant increase in major day surgery compared to public hospitals (coefficient 2; p-value <0.01) CONCLUSIONS: The comparative evaluation of hospital performance is a decisive tool to ensure that public resources are used as rationally and efficiently as possible. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Statistical Methodology for the Analysis of Repeated Duration Data in Behavioral Studies.

PubMed

Letué, Frédérique; Martinez, Marie-José; Samson, Adeline; Vilain, Anne; Vilain, Coriandre

2018-03-15

Repeated duration data are frequently used in behavioral studies. Classical linear or log-linear mixed models are often inadequate to analyze such data, because they usually consist of nonnegative and skew-distributed variables. Therefore, we recommend use of a statistical methodology specific to duration data. We propose a methodology based on Cox mixed models and written under the R language. This semiparametric model is indeed flexible enough to fit duration data. To compare log-linear and Cox mixed models in terms of goodness-of-fit on real data sets, we also provide a procedure based on simulations and quantile-quantile plots. We present two examples from a data set of speech and gesture interactions, which illustrate the limitations of linear and log-linear mixed models, as compared to Cox models. The linear models are not validated on our data, whereas Cox models are. Moreover, in the second example, the Cox model exhibits a significant effect that the linear model does not. We provide methods to select the best-fitting models for repeated duration data and to compare statistical methodologies. In this study, we show that Cox models are best suited to the analysis of our data set.

Neither fixed nor random: weighted least squares meta-regression.

PubMed

Stanley, T D; Doucouliagos, Hristos

2017-03-01

Our study revisits and challenges two core conventional meta-regression estimators: the prevalent use of 'mixed-effects' or random-effects meta-regression analysis and the correction of standard errors that defines fixed-effects meta-regression analysis (FE-MRA). We show how and explain why an unrestricted weighted least squares MRA (WLS-MRA) estimator is superior to conventional random-effects (or mixed-effects) meta-regression when there is publication (or small-sample) bias that is as good as FE-MRA in all cases and better than fixed effects in most practical applications. Simulations and statistical theory show that WLS-MRA provides satisfactory estimates of meta-regression coefficients that are practically equivalent to mixed effects or random effects when there is no publication bias. When there is publication selection bias, WLS-MRA always has smaller bias than mixed effects or random effects. In practical applications, an unrestricted WLS meta-regression is likely to give practically equivalent or superior estimates to fixed-effects, random-effects, and mixed-effects meta-regression approaches. However, random-effects meta-regression remains viable and perhaps somewhat preferable if selection for statistical significance (publication bias) can be ruled out and when random, additive normal heterogeneity is known to directly affect the 'true' regression coefficient. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

The Quantitative-MFG Test: A Linear Mixed Effect Model to Detect Maternal-Offspring Gene Interactions.

PubMed

Clark, Michelle M; Blangero, John; Dyer, Thomas D; Sobel, Eric M; Sinsheimer, Janet S

2016-01-01

Maternal-offspring gene interactions, aka maternal-fetal genotype (MFG) incompatibilities, are neglected in complex diseases and quantitative trait studies. They are implicated in birth to adult onset diseases but there are limited ways to investigate their influence on quantitative traits. We present the quantitative-MFG (QMFG) test, a linear mixed model where maternal and offspring genotypes are fixed effects and residual correlations between family members are random effects. The QMFG handles families of any size, common or general scenarios of MFG incompatibility, and additional covariates. We develop likelihood ratio tests (LRTs) and rapid score tests and show they provide correct inference. In addition, the LRT's alternative model provides unbiased parameter estimates. We show that testing the association of SNPs by fitting a standard model, which only considers the offspring genotypes, has very low power or can lead to incorrect conclusions. We also show that offspring genetic effects are missed if the MFG modeling assumptions are too restrictive. With genome-wide association study data from the San Antonio Family Heart Study, we demonstrate that the QMFG score test is an effective and rapid screening tool. The QMFG test therefore has important potential to identify pathways of complex diseases for which the genetic etiology remains to be discovered. © 2015 John Wiley & Sons Ltd/University College London.

Epidemiological Survey of Dyslipidemia in Civil Aviators in China from 2006 to 2011

PubMed Central

Zhao, Rongfu; Xiao, Dan; Fan, Xiaoying; Ge, Zesong; Wang, Linsheng; Yan, Tiecheng; Wang, Jianzhi; Wei, Qixin; Zhao, Yan

2014-01-01

Aim. This study aimed to analyze blood lipid levels, temporal trend, and age distribution of dyslipidemia in civil aviators in China. Methods. The 305 Chinese aviators were selected randomly and followed up from 2006 to 2011. Their total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) levels were evaluated annually. Mean values for each parameter by year were compared using a linear mixed-effects model. The temporal trend of borderline high, high, and low status for each index and of overall borderline high, hyperlipidemia, and dyslipidemia by year was tested using a generalized linear mixed model. Results. The aviators' TC (F = 4.33, P < 0.01), HDL-C (F = 23.25, P < 0.01), and LDL-C (F = 6.13, P < 0.01) values differed across years. The prevalence of dyslipidemia (F = 5.53, P < 0.01), borderline high (F = 6.52, P < 0.01), and hyperlipidemia (F = 3.90, P < 0.01) also differed across years. The prevalence rates for hyperlipidemia and dyslipidemia were the highest in the 41–50-year-old and 31–40-year-old groups. Conclusions. Civil aviators in China were in high dyslipidemia and borderline high level and presented with dyslipidemia younger than other Chinese populations. PMID:24693285

Variance approach for multi-objective linear programming with fuzzy random of objective function coefficients

NASA Astrophysics Data System (ADS)

Indarsih, Indrati, Ch. Rini

2016-02-01

In this paper, we define variance of the fuzzy random variables through alpha level. We have a theorem that can be used to know that the variance of fuzzy random variables is a fuzzy number. We have a multi-objective linear programming (MOLP) with fuzzy random of objective function coefficients. We will solve the problem by variance approach. The approach transform the MOLP with fuzzy random of objective function coefficients into MOLP with fuzzy of objective function coefficients. By weighted methods, we have linear programming with fuzzy coefficients and we solve by simplex method for fuzzy linear programming.

A comparison of mixed-integer linear programming models for workforce scheduling with position-dependent processing times

NASA Astrophysics Data System (ADS)

Moreno-Camacho, Carlos A.; Montoya-Torres, Jairo R.; Vélez-Gallego, Mario C.

2018-06-01

Only a few studies in the available scientific literature address the problem of having a group of workers that do not share identical levels of productivity during the planning horizon. This study considers a workforce scheduling problem in which the actual processing time is a function of the scheduling sequence to represent the decline in workers' performance, evaluating two classical performance measures separately: makespan and maximum tardiness. Several mathematical models are compared with each other to highlight the advantages of each approach. The mathematical models are tested with randomly generated instances available from a public e-library.

Valid statistical approaches for analyzing sholl data: Mixed effects versus simple linear models.

PubMed

Wilson, Machelle D; Sethi, Sunjay; Lein, Pamela J; Keil, Kimberly P

2017-03-01

The Sholl technique is widely used to quantify dendritic morphology. Data from such studies, which typically sample multiple neurons per animal, are often analyzed using simple linear models. However, simple linear models fail to account for intra-class correlation that occurs with clustered data, which can lead to faulty inferences. Mixed effects models account for intra-class correlation that occurs with clustered data; thus, these models more accurately estimate the standard deviation of the parameter estimate, which produces more accurate p-values. While mixed models are not new, their use in neuroscience has lagged behind their use in other disciplines. A review of the published literature illustrates common mistakes in analyses of Sholl data. Analysis of Sholl data collected from Golgi-stained pyramidal neurons in the hippocampus of male and female mice using both simple linear and mixed effects models demonstrates that the p-values and standard deviations obtained using the simple linear models are biased downwards and lead to erroneous rejection of the null hypothesis in some analyses. The mixed effects approach more accurately models the true variability in the data set, which leads to correct inference. Mixed effects models avoid faulty inference in Sholl analysis of data sampled from multiple neurons per animal by accounting for intra-class correlation. Given the widespread practice in neuroscience of obtaining multiple measurements per subject, there is a critical need to apply mixed effects models more widely. Copyright © 2017 Elsevier B.V. All rights reserved.

Random discrete linear canonical transform.

PubMed

Wei, Deyun; Wang, Ruikui; Li, Yuan-Min

2016-12-01

Linear canonical transforms (LCTs) are a family of integral transforms with wide applications in optical, acoustical, electromagnetic, and other wave propagation problems. In this paper, we propose the random discrete linear canonical transform (RDLCT) by randomizing the kernel transform matrix of the discrete linear canonical transform (DLCT). The RDLCT inherits excellent mathematical properties from the DLCT along with some fantastic features of its own. It has a greater degree of randomness because of the randomization in terms of both eigenvectors and eigenvalues. Numerical simulations demonstrate that the RDLCT has an important feature that the magnitude and phase of its output are both random. As an important application of the RDLCT, it can be used for image encryption. The simulation results demonstrate that the proposed encryption method is a security-enhanced image encryption scheme.

The RANDOM computer program: A linear congruential random number generator

NASA Technical Reports Server (NTRS)

Miles, R. F., Jr.

1986-01-01

The RANDOM Computer Program is a FORTRAN program for generating random number sequences and testing linear congruential random number generators (LCGs). The linear congruential form of random number generator is discussed, and the selection of parameters of an LCG for a microcomputer described. This document describes the following: (1) The RANDOM Computer Program; (2) RANDOM.MOD, the computer code needed to implement an LCG in a FORTRAN program; and (3) The RANCYCLE and the ARITH Computer Programs that provide computational assistance in the selection of parameters for an LCG. The RANDOM, RANCYCLE, and ARITH Computer Programs are written in Microsoft FORTRAN for the IBM PC microcomputer and its compatibles. With only minor modifications, the RANDOM Computer Program and its LCG can be run on most micromputers or mainframe computers.

Design of a school randomized trial for nudging students towards healthy diet and physical activity to prevent obesity: PAAPAS Nudge study protocol.

PubMed

Cunha, Diana Barbosa; Verly Junior, Eliseu; Paravidino, Vitor Barreto; Araújo, Marina Campos; Mediano, Mauro Felippe Felix; Sgambato, Michele Ribeiro; de Souza, Bárbara da Silva Nalin; Marques, Emanuele Souza; Baltar, Valéria Troncoso; de Oliveira, Alessandra Silva Dias; da Silva, Ana Carolina Feldenheimer; Pérez-Cueto, Federico J; Pereira, Rosangela Alves; Sichieri, Rosely

2017-12-01

To evaluate the effectiveness of nudge activities at school on the students' body mass index (BMI). School-based factorial randomized community trial. Eighteen public schools in the municipality of Duque de Caxias, metropolitan area of Rio de Janeiro, Brazil. The 18 schools will be randomized into 4 group arms: group 1-control (without any activity); group 2-will receive educational activities in the classroom; group 3-will receive changes in the school environment (nudge strategies); group 4-will receive educational activities and changes in the school environment. Activities will occur during the 2018 school-year. The primary (BMI) and secondary (body fat percentage) outcomes will be assessed at baseline and after the study using a portable electronic scale with a segmental body composition monitor. The height will be measured by a portable stadiometer. Statistical analyses for each outcome will be conducted through linear mixed models that took into account the missing data and cluster effect of the schools. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

Inference for binomial probability based on dependent Bernoulli random variables with applications to meta‐analysis and group level studies

PubMed Central

Bakbergenuly, Ilyas; Morgenthaler, Stephan

2016-01-01

We study bias arising as a result of nonlinear transformations of random variables in random or mixed effects models and its effect on inference in group‐level studies or in meta‐analysis. The findings are illustrated on the example of overdispersed binomial distributions, where we demonstrate considerable biases arising from standard log‐odds and arcsine transformations of the estimated probability p^, both for single‐group studies and in combining results from several groups or studies in meta‐analysis. Our simulations confirm that these biases are linear in ρ, for small values of ρ, the intracluster correlation coefficient. These biases do not depend on the sample sizes or the number of studies K in a meta‐analysis and result in abysmal coverage of the combined effect for large K. We also propose bias‐correction for the arcsine transformation. Our simulations demonstrate that this bias‐correction works well for small values of the intraclass correlation. The methods are applied to two examples of meta‐analyses of prevalence. PMID:27192062

Design of a school randomized trial for nudging students towards healthy diet and physical activity to prevent obesity

PubMed Central

Cunha, Diana Barbosa; Verly Junior, Eliseu; Paravidino, Vitor Barreto; Araújo, Marina Campos; Mediano, Mauro Felippe Felix; Sgambato, Michele Ribeiro; de Souza, Bárbara da Silva Nalin; Marques, Emanuele Souza; Baltar, Valéria Troncoso; de Oliveira, Alessandra Silva Dias; da Silva, Ana Carolina Feldenheimer; Pérez-Cueto, Federico J.; Pereira, Rosangela Alves; Sichieri, Rosely

2017-01-01

Abstract Objective: To evaluate the effectiveness of nudge activities at school on the students’ body mass index (BMI). Design: School-based factorial randomized community trial. Setting: Eighteen public schools in the municipality of Duque de Caxias, metropolitan area of Rio de Janeiro, Brazil. Participants and intervention: The 18 schools will be randomized into 4 group arms: group 1—control (without any activity); group 2—will receive educational activities in the classroom; group 3—will receive changes in the school environment (nudge strategies); group 4—will receive educational activities and changes in the school environment. Activities will occur during the 2018 school-year. Main outcome measure(s): The primary (BMI) and secondary (body fat percentage) outcomes will be assessed at baseline and after the study using a portable electronic scale with a segmental body composition monitor. The height will be measured by a portable stadiometer. Analysis: Statistical analyses for each outcome will be conducted through linear mixed models that took into account the missing data and cluster effect of the schools. PMID:29390278

Quantifying the degree of persistence in random amoeboid motion based on the Hurst exponent of fractional Brownian motion.

PubMed

Makarava, Natallia; Menz, Stephan; Theves, Matthias; Huisinga, Wilhelm; Beta, Carsten; Holschneider, Matthias

2014-10-01

Amoebae explore their environment in a random way, unless external cues like, e.g., nutrients, bias their motion. Even in the absence of cues, however, experimental cell tracks show some degree of persistence. In this paper, we analyzed individual cell tracks in the framework of a linear mixed effects model, where each track is modeled by a fractional Brownian motion, i.e., a Gaussian process exhibiting a long-term correlation structure superposed on a linear trend. The degree of persistence was quantified by the Hurst exponent of fractional Brownian motion. Our analysis of experimental cell tracks of the amoeba Dictyostelium discoideum showed a persistent movement for the majority of tracks. Employing a sliding window approach, we estimated the variations of the Hurst exponent over time, which allowed us to identify points in time, where the correlation structure was distorted ("outliers"). Coarse graining of track data via down-sampling allowed us to identify the dependence of persistence on the spatial scale. While one would expect the (mode of the) Hurst exponent to be constant on different temporal scales due to the self-similarity property of fractional Brownian motion, we observed a trend towards stronger persistence for the down-sampled cell tracks indicating stronger persistence on larger time scales.

Evaluating the statistical performance of less applied algorithms in classification of worldview-3 imagery data in an urbanized landscape

NASA Astrophysics Data System (ADS)

Ranaie, Mehrdad; Soffianian, Alireza; Pourmanafi, Saeid; Mirghaffari, Noorollah; Tarkesh, Mostafa

2018-03-01

In recent decade, analyzing the remotely sensed imagery is considered as one of the most common and widely used procedures in the environmental studies. In this case, supervised image classification techniques play a central role. Hence, taking a high resolution Worldview-3 over a mixed urbanized landscape in Iran, three less applied image classification methods including Bagged CART, Stochastic gradient boosting model and Neural network with feature extraction were tested and compared with two prevalent methods: random forest and support vector machine with linear kernel. To do so, each method was run ten time and three validation techniques was used to estimate the accuracy statistics consist of cross validation, independent validation and validation with total of train data. Moreover, using ANOVA and Tukey test, statistical difference significance between the classification methods was significantly surveyed. In general, the results showed that random forest with marginal difference compared to Bagged CART and stochastic gradient boosting model is the best performing method whilst based on independent validation there was no significant difference between the performances of classification methods. It should be finally noted that neural network with feature extraction and linear support vector machine had better processing speed than other.

Local hyperspectral data multisharpening based on linear/linear-quadratic nonnegative matrix factorization by integrating lidar data

NASA Astrophysics Data System (ADS)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2015-10-01

In this paper, a new Spectral-Unmixing-based approach, using Nonnegative Matrix Factorization (NMF), is proposed to locally multi-sharpen hyperspectral data by integrating a Digital Surface Model (DSM) obtained from LIDAR data. In this new approach, the nature of the local mixing model is detected by using the local variance of the object elevations. The hyper/multispectral images are explored using small zones. In each zone, the variance of the object elevations is calculated from the DSM data in this zone. This variance is compared to a threshold value and the adequate linear/linearquadratic spectral unmixing technique is used in the considered zone to independently unmix hyperspectral and multispectral data, using an adequate linear/linear-quadratic NMF-based approach. The obtained spectral and spatial information thus respectively extracted from the hyper/multispectral images are then recombined in the considered zone, according to the selected mixing model. Experiments based on synthetic hyper/multispectral data are carried out to evaluate the performance of the proposed multi-sharpening approach and literature linear/linear-quadratic approaches used on the whole hyper/multispectral data. In these experiments, real DSM data are used to generate synthetic data containing linear and linear-quadratic mixed pixel zones. The DSM data are also used for locally detecting the nature of the mixing model in the proposed approach. Globally, the proposed approach yields good spatial and spectral fidelities for the multi-sharpened data and significantly outperforms the used literature methods.

Emulsion Stability Modulates Gastric Secretion and Its Mixing with Emulsified Fat in Healthy Adults in a Randomized Magnetic Resonance Imaging Study.

PubMed

Liu, Dian; Parker, Helen L; Curcic, Jelena; Kozerke, Sebastian; Steingoetter, Andreas

2016-10-01

Oil-in-water emulsions have recently become of interest to nutritional sciences because of their ability to influence gastrointestinal digestive processes and ultimately benefit human health. MRI offers the potential to noninvasively characterize the interaction between emulsified lipids and gastric secretion within the stomach. We determined noninvasively how emulsion stability modulates volumes of fat and secretion, layering of fat, and the mixing of emulsified fat with secretion within the stomach. This required the development of MRI technology for quantifying fat and secretion concentrations inside the stomach. Twenty-one healthy adults [13 men, mean ± SD age: 22.5 ± 2.5 y, mean ± SD body mass index (in kg/m 2 ): 22.7 ± 1.8] were analyzed in a single-blind, randomized, parallel design. MRI was used to acquire the distributions of fat and secretion in the stomach after ingestion of 2 emulsions: a stable emulsion (E1) or an unstable emulsion (E4) with 20% fat fraction and ∼0.3 mm droplet sizes. Layer, volume, and mixing variables were fitted to the data and compared between the 2 emulsions. The intragastric mixing between fat and secretion was better with the E4 than the E1 [increase in content heterogeneity of 17.1% (95% CI: 12.3%, 21.9%)]. The E4 demonstrated a linear relation [slope 1.57 (95% CI: 0.86, 2.29)] between the degree of layering and mixing. In contrast, no such relation was detected for the E1. Accumulated secretion volume in the stomach was lower with the E4 [decrease in volume variable k s of 2.3 (95% CI: -3.9, -0.7)] and correlated with the degree of layering (r = 0.62, P < 0.001). In healthy adults, intragastric fat layering was influenced mainly by the degree of intragastric mixing, rather than the overall dominance of secretion. The E1 triggered a higher accumulation of gastric secretion, which in turn facilitated homogenization of intragastric content in comparison with its unstable counterpart. This trial was registered at clinicaltrials.gov as NCT02602158. © 2016 American Society for Nutrition.

Model's sparse representation based on reduced mixed GMsFE basis methods

NASA Astrophysics Data System (ADS)

Jiang, Lijian; Li, Qiuqi

2017-06-01

In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a large number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in random porous media is simulated by the proposed sparse representation method.

Model's sparse representation based on reduced mixed GMsFE basis methods

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

Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn; Li, Qiuqi, E-mail: qiuqili@hnu.edu.cn

2017-06-01

In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a largemore » number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in random porous media is simulated by the proposed sparse representation method.« less

Should measures of patient experience in primary care be adjusted for case mix? Evidence from the English General Practice Patient Survey

PubMed Central

Paddison, Charlotte; Elliott, Marc; Parker, Richard; Staetsky, Laura; Lyratzopoulos, Georgios; Campbell, John L

2012-01-01

Objectives Uncertainties exist about when and how best to adjust performance measures for case mix. Our aims are to quantify the impact of case-mix adjustment on practice-level scores in a national survey of patient experience, to identify why and when it may be useful to adjust for case mix, and to discuss unresolved policy issues regarding the use of case-mix adjustment in performance measurement in health care. Design/setting Secondary analysis of the 2009 English General Practice Patient Survey. Responses from 2 163 456 patients registered with 8267 primary care practices. Linear mixed effects models were used with practice included as a random effect and five case-mix variables (gender, age, race/ethnicity, deprivation, and self-reported health) as fixed effects. Main outcome measures Primary outcome was the impact of case-mix adjustment on practice-level means (adjusted minus unadjusted) and changes in practice percentile ranks for questions measuring patient experience in three domains of primary care: access; interpersonal care; anticipatory care planning, and overall satisfaction with primary care services. Results Depending on the survey measure selected, case-mix adjustment changed the rank of between 0.4% and 29.8% of practices by more than 10 percentile points. Adjusting for case-mix resulted in large increases in score for a small number of practices and small decreases in score for a larger number of practices. Practices with younger patients, more ethnic minority patients and patients living in more socio-economically deprived areas were more likely to gain from case-mix adjustment. Age and race/ethnicity were the most influential adjustors. Conclusions While its effect is modest for most practices, case-mix adjustment corrects significant underestimation of scores for a small proportion of practices serving vulnerable patients and may reduce the risk that providers would ‘cream-skim’ by not enrolling patients from vulnerable socio-demographic groups. PMID:22626735

Should measures of patient experience in primary care be adjusted for case mix? Evidence from the English General Practice Patient Survey.

PubMed

Paddison, Charlotte; Elliott, Marc; Parker, Richard; Staetsky, Laura; Lyratzopoulos, Georgios; Campbell, John L; Roland, Martin

2012-08-01

Uncertainties exist about when and how best to adjust performance measures for case mix. Our aims are to quantify the impact of case-mix adjustment on practice-level scores in a national survey of patient experience, to identify why and when it may be useful to adjust for case mix, and to discuss unresolved policy issues regarding the use of case-mix adjustment in performance measurement in health care. Secondary analysis of the 2009 English General Practice Patient Survey. Responses from 2 163 456 patients registered with 8267 primary care practices. Linear mixed effects models were used with practice included as a random effect and five case-mix variables (gender, age, race/ethnicity, deprivation, and self-reported health) as fixed effects. Primary outcome was the impact of case-mix adjustment on practice-level means (adjusted minus unadjusted) and changes in practice percentile ranks for questions measuring patient experience in three domains of primary care: access; interpersonal care; anticipatory care planning, and overall satisfaction with primary care services. Depending on the survey measure selected, case-mix adjustment changed the rank of between 0.4% and 29.8% of practices by more than 10 percentile points. Adjusting for case-mix resulted in large increases in score for a small number of practices and small decreases in score for a larger number of practices. Practices with younger patients, more ethnic minority patients and patients living in more socio-economically deprived areas were more likely to gain from case-mix adjustment. Age and race/ethnicity were the most influential adjustors. While its effect is modest for most practices, case-mix adjustment corrects significant underestimation of scores for a small proportion of practices serving vulnerable patients and may reduce the risk that providers would 'cream-skim' by not enrolling patients from vulnerable socio-demographic groups.

Exploring the efficacy of replacing linear paper-based patient cases in problem-based learning with dynamic Web-based virtual patients: randomized controlled trial.

PubMed

Poulton, Terry; Ellaway, Rachel H; Round, Jonathan; Jivram, Trupti; Kavia, Sheetal; Hilton, Sean

2014-11-05

Problem-based learning (PBL) is well established in medical education and beyond, and continues to be developed and explored. Challenges include how to connect the somewhat abstract nature of classroom-based PBL with clinical practice and how to maintain learner engagement in the process of PBL over time. A study was conducted to investigate the efficacy of decision-PBL (D-PBL), a variant form of PBL that replaces linear PBL cases with virtual patients. These Web-based interactive cases provided learners with a series of patient management pathways. Learners were encouraged to consider and discuss courses of action, take their chosen management pathway, and experience the consequences of their decisions. A Web-based application was essential to allow scenarios to respond dynamically to learners' decisions, to deliver the scenarios to multiple PBL classrooms in the same timeframe, and to record centrally the paths taken by the PBL groups. A randomized controlled trial in crossover design was run involving all learners (N=81) in the second year of the graduate entry stream for the undergraduate medicine program at St George's University of London. Learners were randomized to study groups; half engaged in a D-PBL activity whereas the other half had a traditional linear PBL activity on the same subject material. Groups alternated D-PBL and linear PBL over the semester. The measure was mean cohort performance on specific face-to-face exam questions at the end of the semester. D-PBL groups performed better than linear PBL groups on questions related to D-PBL with the difference being statistically significant for all questions. Differences between the exam performances of the 2 groups were not statistically significant for the questions not related to D-PBL. The effect sizes for D-PBL-related questions were large and positive (>0.6) except for 1 question that showed a medium positive effect size. The effect sizes for questions not related to D-PBL were all small (≤0.3) with a mix of positive and negative values. The efficacy of D-PBL was indicated by improved exam performance for learners who had D-PBL compared to those who had linear PBL. This suggests that the use of D-PBL leads to better midterm learning outcomes than linear PBL, at least for learners with prior experience with linear PBL. On the basis of tutor and student feedback, St George's University of London and the University of Nicosia, Cyprus have replaced paper PBL cases for midstage undergraduate teaching with D-PBL virtual patients, and 6 more institutions in the ePBLnet partnership will be implementing D-PBL in Autumn 2015.

The use of common bean (Phaseolus vulgaris) traditional varieties and their mixtures with commercial varieties to manage bean fly (Ophiomyia spp.) infestations in Uganda.

PubMed

Ssekandi, W; Mulumba, J W; Colangelo, P; Nankya, R; Fadda, C; Karungi, J; Otim, M; De Santis, P; Jarvis, D I

The bean fly ( Ophiomyia spp.) is considered the most economically damaging field insect pest of common beans in Uganda. Despite the use of existing pest management approaches, reported damage has remained high. Forty-eight traditional and improved common bean varieties currently grown in farmers' fields were evaluated for resistance against bean fly. Data on bean fly incidence, severity and root damage from bean stem maggot were collected. Generalized linear mixed model (GLMM) revealed significant resistance to bean fly in the Ugandan traditional varieties. A popular resistant traditional variety and a popular susceptible commercial variety were selected from the 48 varieties and evaluated in pure and mixed stands. The incidence of bean fly infestation on both varieties in mixtures with different arrangements (systematic random versus rows), and different proportions within each of the two arrangements, was measured and analysed using GLMMs. The proportion of resistant varieties in a mixture and the arrangement type significantly decreased bean fly damage compared to pure stands, with the highest decrease in damage registered in the systematic random mixture with at least 50 % of resistant variety. The highest reduction in root damage, obvious 21 days after planting, was found in systematic random mixtures with at least 50 % of the resistant variety. Small holder farmers in East Africa and elsewhere in the world have local preferences for growing bean varieties in genetic mixtures. These mixtures can be enhanced by the use of resistant varieties in the mixtures to reduce bean fly damage on susceptible popular varieties.

Augmented Cognitive Behavioral Therapy for Poststroke Depressive Symptoms: A Randomized Controlled Trial.

PubMed

Kootker, Joyce A; Rasquin, Sascha M C; Lem, Frederik C; van Heugten, Caroline M; Fasotti, Luciano; Geurts, Alexander C H

2017-04-01

To evaluate the effectiveness of individually tailored cognitive behavioral therapy (CBT) for reducing depressive symptoms with or without anxiety poststroke. Multicenter, assessor-blinded, randomized controlled trial. Ambulatory rehabilitation setting. Patients who had a Hospital Anxiety and Depression Scale-depression subscale (HADS-D) score >7 at least 3 months poststroke (N=61). Participants were randomly allocated to either augmented CBT or computerized cognitive training (CCT). The CBT intervention was based on the principles of recognizing, registering, and altering negative thoughts and cognitions. CBT was augmented with goal-directed real-life activity training given by an occupational or movement therapist. HADS-D was the primary outcome, and measures of participation and quality of life were secondary outcomes. Outcome measurements were performed at baseline, immediately posttreatment, and at 4- and 8-month follow-up. Analysis was performed with linear mixed models using group (CBT vs CCT) as the between-subjects factor and time (4 assessments) as the within-subjects factor. Mixed model analyses showed a significant and persistent time effect for HADS-D (mean difference, -4.6; 95% confidence interval, -5.7 to -3.6; P<.001) and for participation and quality of life in both groups. There was no significant group × time effect for any of the outcome measures. Our augmented CBT intervention was not superior to CCT for the treatment of mood disorders after stroke. Future studies should determine whether both interventions are better than natural history. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Multivariate-$t$ nonlinear mixed models with application to censored multi-outcome AIDS studies.

PubMed

Lin, Tsung-I; Wang, Wan-Lun

2017-10-01

In multivariate longitudinal HIV/AIDS studies, multi-outcome repeated measures on each patient over time may contain outliers, and the viral loads are often subject to a upper or lower limit of detection depending on the quantification assays. In this article, we consider an extension of the multivariate nonlinear mixed-effects model by adopting a joint multivariate-$t$ distribution for random effects and within-subject errors and taking the censoring information of multiple responses into account. The proposed model is called the multivariate-$t$ nonlinear mixed-effects model with censored responses (MtNLMMC), allowing for analyzing multi-outcome longitudinal data exhibiting nonlinear growth patterns with censorship and fat-tailed behavior. Utilizing the Taylor-series linearization method, a pseudo-data version of expectation conditional maximization either (ECME) algorithm is developed for iteratively carrying out maximum likelihood estimation. We illustrate our techniques with two data examples from HIV/AIDS studies. Experimental results signify that the MtNLMMC performs favorably compared to its Gaussian analogue and some existing approaches. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Functional Additive Mixed Models

PubMed Central

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2014-01-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach. PMID:26347592

Functional Additive Mixed Models.

PubMed

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2015-04-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach.

Rotational reflectance properties of Arkoma Basin dispersed vitrinite: insights for understanding reflectance populations in high thermal maturity regions

USGS Publications Warehouse

Houseknecht, D.W.; Bensley, D.F.; Hathon, L.A.; Kastens, P.H.

1993-01-01

Analysis and interpretation of dispersed vitrinite reflectance data in regions of high thermal maturity (> 2% vitrinite reflectance) have been equivocal partly because of an increase in width and complexity of reflectance histograms with increasing mean reflectance. Such complexity is illustrated by random reflectance (Rran) data from the Arkoma Basin that display a linear increase in standard deviation of Rran with an increase in mean Rran from 1 to 5%. Evaluating how much of the dispersion in these data is the result of vitrinite anisotropy and how much is the result of mixing of kerogen populations by sedimentary processes and/or sampling procedures has been problematic. Automated collection of reflectance data during polarizer rotation provides preliminary data for solution of this problem. Rotational reflectance data collected from a subset of Arkoma Basin samples reveal positive, linear relationships among maximum (R???max), random (Rran), rotational (Rrot), and minimum (R???min) reflectance, as well as a systematic increase in bireflectance (R???max-R???min) with increasing reflectance. R???max and Rrot display lower standard deviations and narrower, more nearly unimodal histograms than Rran and R???min, suggesting that R???max and Rrot are superior (less ambiguous) indices of thermal maturity. These data patterns are inferred to be mostly an indication of increasing vitrinite anisotropy with increasing thermal maturity, suggesting that the linear covariance observed between mean Rran and standard deviation in dispersed organic data sets from regions of high thermal maturity may be explained mostly as the result of increasing vitrinite anisotropy with increasing thermal maturity. ?? 1993.

Compensatory selection for roads over natural linear features by wolves in northern Ontario: Implications for caribou conservation

PubMed Central

Patterson, Brent R.; Anderson, Morgan L.; Rodgers, Arthur R.; Vander Vennen, Lucas M.; Fryxell, John M.

2017-01-01

Woodland caribou (Rangifer tarandus caribou) in Ontario are a threatened species that have experienced a substantial retraction of their historic range. Part of their decline has been attributed to increasing densities of anthropogenic linear features such as trails, roads, railways, and hydro lines. These features have been shown to increase the search efficiency and kill rate of wolves. However, it is unclear whether selection for anthropogenic linear features is additive or compensatory to selection for natural (water) linear features which may also be used for travel. We studied the selection of water and anthropogenic linear features by 52 resident wolves (Canis lupus x lycaon) over four years across three study areas in northern Ontario that varied in degrees of forestry activity and human disturbance. We used Euclidean distance-based resource selection functions (mixed-effects logistic regression) at the seasonal range scale with random coefficients for distance to water linear features, primary/secondary roads/railways, and hydro lines, and tertiary roads to estimate the strength of selection for each linear feature and for several habitat types, while accounting for availability of each feature. Next, we investigated the trade-off between selection for anthropogenic and water linear features. Wolves selected both anthropogenic and water linear features; selection for anthropogenic features was stronger than for water during the rendezvous season. Selection for anthropogenic linear features increased with increasing density of these features on the landscape, while selection for natural linear features declined, indicating compensatory selection of anthropogenic linear features. These results have implications for woodland caribou conservation. Prey encounter rates between wolves and caribou seem to be strongly influenced by increasing linear feature densities. This behavioral mechanism–a compensatory functional response to anthropogenic linear feature density resulting in decreased use of natural travel corridors–has negative consequences for the viability of woodland caribou. PMID:29117234

Compensatory selection for roads over natural linear features by wolves in northern Ontario: Implications for caribou conservation.

PubMed

Newton, Erica J; Patterson, Brent R; Anderson, Morgan L; Rodgers, Arthur R; Vander Vennen, Lucas M; Fryxell, John M

2017-01-01

Woodland caribou (Rangifer tarandus caribou) in Ontario are a threatened species that have experienced a substantial retraction of their historic range. Part of their decline has been attributed to increasing densities of anthropogenic linear features such as trails, roads, railways, and hydro lines. These features have been shown to increase the search efficiency and kill rate of wolves. However, it is unclear whether selection for anthropogenic linear features is additive or compensatory to selection for natural (water) linear features which may also be used for travel. We studied the selection of water and anthropogenic linear features by 52 resident wolves (Canis lupus x lycaon) over four years across three study areas in northern Ontario that varied in degrees of forestry activity and human disturbance. We used Euclidean distance-based resource selection functions (mixed-effects logistic regression) at the seasonal range scale with random coefficients for distance to water linear features, primary/secondary roads/railways, and hydro lines, and tertiary roads to estimate the strength of selection for each linear feature and for several habitat types, while accounting for availability of each feature. Next, we investigated the trade-off between selection for anthropogenic and water linear features. Wolves selected both anthropogenic and water linear features; selection for anthropogenic features was stronger than for water during the rendezvous season. Selection for anthropogenic linear features increased with increasing density of these features on the landscape, while selection for natural linear features declined, indicating compensatory selection of anthropogenic linear features. These results have implications for woodland caribou conservation. Prey encounter rates between wolves and caribou seem to be strongly influenced by increasing linear feature densities. This behavioral mechanism-a compensatory functional response to anthropogenic linear feature density resulting in decreased use of natural travel corridors-has negative consequences for the viability of woodland caribou.

Robust small area prediction for counts.

PubMed

Tzavidis, Nikos; Ranalli, M Giovanna; Salvati, Nicola; Dreassi, Emanuela; Chambers, Ray

2015-06-01

A new semiparametric approach to model-based small area prediction for counts is proposed and used for estimating the average number of visits to physicians for Health Districts in Central Italy. The proposed small area predictor can be viewed as an outlier robust alternative to the more commonly used empirical plug-in predictor that is based on a Poisson generalized linear mixed model with Gaussian random effects. Results from the real data application and from a simulation experiment confirm that the proposed small area predictor has good robustness properties and in some cases can be more efficient than alternative small area approaches. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Mixed H2/Hinfinity output-feedback control of second-order neutral systems with time-varying state and input delays.

PubMed

Karimi, Hamid Reza; Gao, Huijun

2008-07-01

A mixed H2/Hinfinity output-feedback control design methodology is presented in this paper for second-order neutral linear systems with time-varying state and input delays. Delay-dependent sufficient conditions for the design of a desired control are given in terms of linear matrix inequalities (LMIs). A controller, which guarantees asymptotic stability and a mixed H2/Hinfinity performance for the closed-loop system of the second-order neutral linear system, is then developed directly instead of coupling the model to a first-order neutral system. A Lyapunov-Krasovskii method underlies the LMI-based mixed H2/Hinfinity output-feedback control design using some free weighting matrices. The simulation results illustrate the effectiveness of the proposed methodology.

MULTIVARIATE LINEAR MIXED MODELS FOR MULTIPLE OUTCOMES. (R824757)

EPA Science Inventory

We propose a multivariate linear mixed (MLMM) for the analysis of multiple outcomes, which generalizes the latent variable model of Sammel and Ryan. The proposed model assumes a flexible correlation structure among the multiple outcomes, and allows a global test of the impact of ...

System and method for investigating sub-surface features of a rock formation with acoustic sources generating coded signals

DOEpatents

Vu, Cung Khac; Nihei, Kurt; Johnson, Paul A; Guyer, Robert; Ten Cate, James A; Le Bas, Pierre-Yves; Larmat, Carene S

2014-12-30

A system and a method for investigating rock formations includes generating, by a first acoustic source, a first acoustic signal comprising a first plurality of pulses, each pulse including a first modulated signal at a central frequency; and generating, by a second acoustic source, a second acoustic signal comprising a second plurality of pulses. A receiver arranged within the borehole receives a detected signal including a signal being generated by a non-linear mixing process from the first-and-second acoustic signal in a non-linear mixing zone within the intersection volume. The method also includes-processing the received signal to extract the signal generated by the non-linear mixing process over noise or over signals generated by a linear interaction process, or both.

Deletion Diagnostics for the Generalised Linear Mixed Model with independent random effects

PubMed Central

Ganguli, B.; Roy, S. Sen; Naskar, M.; Malloy, E. J.; Eisen, E. A.

2015-01-01

The Generalised Linear Mixed Model (GLMM) is widely used for modelling environmental data. However, such data are prone to influential observations which can distort the estimated exposure-response curve particularly in regions of high exposure. Deletion diagnostics for iterative estimation schemes commonly derive the deleted estimates based on a single iteration of the full system holding certain pivotal quantities such as the information matrix to be constant. In this paper, we present an approximate formula for the deleted estimates and Cook’s distance for the GLMM which does not assume that the estimates of variance parameters are unaffected by deletion. The procedure allows the user to calculate standardised DFBETAs for mean as well as variance parameters. In certain cases, such as when using the GLMM as a device for smoothing, such residuals for the variance parameters are interesting in their own right. In general, the procedure leads to deleted estimates of mean parameters which are corrected for the effect of deletion on variance components as estimation of the two sets of parameters is interdependent. The probabilistic behaviour of these residuals is investigated and a simulation based procedure suggested for their standardisation. The method is used to identify influential individuals in an occupational cohort exposed to silica. The results show that failure to conduct post model fitting diagnostics for variance components can lead to erroneous conclusions about the fitted curve and unstable confidence intervals. PMID:26626135

Eigenfactor score and alternative bibliometrics surpass the impact factor in a 2-years ahead annual-citation calculation: a linear mixed design model analysis of Radiology, Nuclear Medicine and Medical Imaging journals.

PubMed

Roldan-Valadez, Ernesto; Orbe-Arteaga, Ulises; Rios, Camilo

2018-03-05

Because we believe the journal selection before a manuscript submission deserves further investigation in each medical specialty, we aimed to evaluate the predictive ability of seven bibliometrics in the Radiology, Nuclear Medicine and Medical Imaging category of the Web of Knowledge to calculate total citations over a 7-year period. A linear mixed effects design using random slopes and intercepts were performed on bibliometrics corresponding to 124 journals from 2007 to 2011, with their corresponding citations from 2009 to 2013, which appeared in the Journal Citations Report Science Edition. The Eigenfactor Score, Article Influence Score, Cited Half-life, 5-years impact factor and Number of Articles are significant predictors of 2-year-ahead total citations (p ≤ 0.010 for all variables). The impact factor and Immediacy Index are not significant predictors. There was a significant global effect size (R 2  = 0.934; p < 0.001), which yielded a total variance of 93.4%. Our findings support researchers' decision to stop the misuse of IF alone to evaluate journals. Radiologists and other researchers should review journal's bibliometrics for their decision-making during the manuscript submission phase. A re-ranking of journals using Eigenfactor Score, Article Influence Score, and Cited Half-life provides a better assessment of their significance and importance in particular disciplines.

Multilevel modeling and panel data analysis in educational research (Case study: National examination data senior high school in West Java)

NASA Astrophysics Data System (ADS)

Zulvia, Pepi; Kurnia, Anang; Soleh, Agus M.

2017-03-01

Individual and environment are a hierarchical structure consist of units grouped at different levels. Hierarchical data structures are analyzed based on several levels, with the lowest level nested in the highest level. This modeling is commonly call multilevel modeling. Multilevel modeling is widely used in education research, for example, the average score of National Examination (UN). While in Indonesia UN for high school student is divided into natural science and social science. The purpose of this research is to develop multilevel and panel data modeling using linear mixed model on educational data. The first step is data exploration and identification relationships between independent and dependent variable by checking correlation coefficient and variance inflation factor (VIF). Furthermore, we use a simple model approach with highest level of the hierarchy (level-2) is regency/city while school is the lowest of hierarchy (level-1). The best model was determined by comparing goodness-of-fit and checking assumption from residual plots and predictions for each model. Our finding that for natural science and social science, the regression with random effects of regency/city and fixed effects of the time i.e multilevel model has better performance than the linear mixed model in explaining the variability of the dependent variable, which is the average scores of UN.

Three-dimensional biometric study of palatine rugae in children with a mixed-model analysis: a 9-year longitudinal study.

PubMed

Kim, Hong-Kyun; Moon, Sung-Chul; Lee, Shin-Jae; Park, Young-Seok

2012-05-01

The palatine rugae have been suggested as stable reference points for superimposing 3-dimensional virtual models before and after orthodontic treatment. We investigated 3-dimensional changes in the palatine rugae of children over 9 years. Complete dental stone casts were biennially prepared for 56 subjects (42 girls, 14 boys) aged from 6 to 14 years. Using 3-dimensional laser scanning and reconstruction software, virtual casts were constructed. Medial and lateral points of the first anterior 3 rugae were defined as the 3-dimensional landmarks. The length of each ruga and the distance between the end points of the rugae were measured in virtual 3-dimensional space. The measurement changes over time were analyzed by using the mixed-effect method for longitudinal data. There were slight increases in the linear measurements in the rugae areas: the lengths of the rugae and the distances between them during the observation period. However, the amounts of the increments were relatively small when compared with the initial values and individual random variability. Although age affected the linear dimensions significantly, it was not clinically significant; the rugae were relatively stable. The use of the palatine rugae as reference points for superimposing and evaluating changes during orthodontic treatment was thought to be possible with special cautions. Copyright © 2012 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Commensurate Priors for Incorporating Historical Information in Clinical Trials Using General and Generalized Linear Models

PubMed Central

Hobbs, Brian P.; Sargent, Daniel J.; Carlin, Bradley P.

2014-01-01

Assessing between-study variability in the context of conventional random-effects meta-analysis is notoriously difficult when incorporating data from only a small number of historical studies. In order to borrow strength, historical and current data are often assumed to be fully homogeneous, but this can have drastic consequences for power and Type I error if the historical information is biased. In this paper, we propose empirical and fully Bayesian modifications of the commensurate prior model (Hobbs et al., 2011) extending Pocock (1976), and evaluate their frequentist and Bayesian properties for incorporating patient-level historical data using general and generalized linear mixed regression models. Our proposed commensurate prior models lead to preposterior admissible estimators that facilitate alternative bias-variance trade-offs than those offered by pre-existing methodologies for incorporating historical data from a small number of historical studies. We also provide a sample analysis of a colon cancer trial comparing time-to-disease progression using a Weibull regression model. PMID:24795786

Super non-linear RRAM with ultra-low power for 3D vertical nano-crossbar arrays.

PubMed

Luo, Qing; Xu, Xiaoxin; Liu, Hongtao; Lv, Hangbing; Gong, Tiancheng; Long, Shibing; Liu, Qi; Sun, Haitao; Banerjee, Writam; Li, Ling; Gao, Jianfeng; Lu, Nianduan; Liu, Ming

2016-08-25

Vertical crossbar arrays provide a cost-effective approach for high density three-dimensional (3D) integration of resistive random access memory. However, an individual selector device is not allowed to be integrated with the memory cell separately. The development of V-RRAM has impeded the lack of satisfactory self-selective cells. In this study, we have developed a high performance bilayer self-selective device using HfO2 as the memory switching layer and a mixed ionic and electron conductor as the selective layer. The device exhibits high non-linearity (>10(3)) and ultra-low half-select leakage (<0.1 pA). A four layer vertical crossbar array was successfully demonstrated based on the developed self-selective device. High uniformity, ultra-low leakage, sub-nA operation, self-compliance, and excellent read/write disturbance immunity were achieved. The robust array level performance shows attractive potential for low power and high density 3D data storage applications.

Reversible gelling culture media for in-vitro cell culture in three-dimensional matrices

DOEpatents

An, Yuehuei H.; Mironov, Vladimir A.; Gutowska, Anna

2000-01-01

A gelling cell culture medium useful for forming a three dimensional matrix for cell culture in vitro is prepared by copolymerizing an acrylamide derivative with a hydrophilic comonomer to form a reversible (preferably thermally reversible) gelling linear random copolymer in the form of a plurality of linear chains having a plurality of molecular weights greater than or equal to a minimum gelling molecular weight cutoff, mixing the copolymer with an aqueous solvent to form a reversible gelling solution and adding a cell culture medium to the gelling solution to form the gelling cell culture medium. Cells such as chondrocytes or hepatocytes are added to the culture medium to form a seeded culture medium, and temperature of the medium is raised to gel the seeded culture medium and form a three dimensional matrix containing the cells. After propagating the cells in the matrix, the cells may be recovered by lowering the temperature to dissolve the matrix and centrifuging.

Generalized Multilevel Structural Equation Modeling

ERIC Educational Resources Information Center

Rabe-Hesketh, Sophia; Skrondal, Anders; Pickles, Andrew

2004-01-01

A unifying framework for generalized multilevel structural equation modeling is introduced. The models in the framework, called generalized linear latent and mixed models (GLLAMM), combine features of generalized linear mixed models (GLMM) and structural equation models (SEM) and consist of a response model and a structural model for the latent…

A generalized nonlinear model-based mixed multinomial logit approach for crash data analysis.

PubMed

Zeng, Ziqiang; Zhu, Wenbo; Ke, Ruimin; Ash, John; Wang, Yinhai; Xu, Jiuping; Xu, Xinxin

2017-02-01

The mixed multinomial logit (MNL) approach, which can account for unobserved heterogeneity, is a promising unordered model that has been employed in analyzing the effect of factors contributing to crash severity. However, its basic assumption of using a linear function to explore the relationship between the probability of crash severity and its contributing factors can be violated in reality. This paper develops a generalized nonlinear model-based mixed MNL approach which is capable of capturing non-monotonic relationships by developing nonlinear predictors for the contributing factors in the context of unobserved heterogeneity. The crash data on seven Interstate freeways in Washington between January 2011 and December 2014 are collected to develop the nonlinear predictors in the model. Thirteen contributing factors in terms of traffic characteristics, roadway geometric characteristics, and weather conditions are identified to have significant mixed (fixed or random) effects on the crash density in three crash severity levels: fatal, injury, and property damage only. The proposed model is compared with the standard mixed MNL model. The comparison results suggest a slight superiority of the new approach in terms of model fit measured by the Akaike Information Criterion (12.06 percent decrease) and Bayesian Information Criterion (9.11 percent decrease). The predicted crash densities for all three levels of crash severities of the new approach are also closer (on average) to the observations than the ones predicted by the standard mixed MNL model. Finally, the significance and impacts of the contributing factors are analyzed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Mapping nighttime PM2.5 from VIIRS DNB using a linear mixed-effect model

NASA Astrophysics Data System (ADS)

Fu, D.; Xia, X.; Duan, M.; Zhang, X.; Li, X.; Wang, J.; Liu, J.

2018-04-01

Estimation of particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5) from daytime satellite aerosol products is widely reported in the literature; however, remote sensing of nighttime surface PM2.5 from space is very limited. PM2.5 shows a distinct diurnal cycle and PM2.5 concentration at 1:00 local standard time (LST) has a linear correlation coefficient (R) of 0.80 with daily-mean PM2.5. Therefore, estimation of nighttime PM2.5 is required toward an improved understanding of temporal variation of PM2.5 and its effects on air quality. Using data from the Day/Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) and hourly PM2.5 data at 35 stations in Beijing, a mixed-effect model is developed here to estimate nighttime PM2.5 from nighttime light radiance measurements based on the assumption that the DNB-PM2.5 relationship is constant spatially but varies temporally. Cross-validation showed that the model developed using all stations predict daily PM2.5 with mean determination coefficient (R2) of 0.87 ± 0.12, 0.83 ± 0.10 , 0.87 ± 0.09, 0.83 ± 0.10 in spring, summer, autumn and winter. Further analysis showed that the best model performance was achieved in urban stations with average cross-validation R2 of 0.92. In rural stations, DNB light signal is weak and was likely smeared by lunar illuminance that resulted in relatively poor estimation of PM2.5. The fixed and random parameters of the mixed-effect model in urban stations differed from those in suburban stations, which indicated that the assumption of the mixed-effect model should be carefully evaluated when used at a regional scale.

Mindfulness-Oriented Recovery Enhancement for Internet Gaming Disorder in U.S. Adults: A Stage 1 Randomized Controlled Trial

PubMed Central

Li, Wen; Garland, Eric L.; McGovern, Patricia; O'Brien, Jennifer E.; Tronnier, Christine; Howard, Matthew O.

2017-01-01

Empirical studies have identified increasing rates of Internet Gaming Disorder (IGD) and associated adverse consequences. However, very few evidence-based interventions have been evaluated for IGD or problematic video gaming behaviors. This study evaluated Mindfulness-Oriented Recovery Enhancement (MORE) as a treatment for IGD. Thirty adults (M age = 25.0, SD = 5.4) with IGD or problematic video gaming behaviors were randomized to 8 weeks of group-based MORE or 8 weeks of a support group (SG) control condition. Outcome measures were administered at pre-and posttreatment, and 3-month following treatment completion using self-report instruments. Linear mixed models were used for outcome analyses. MORE participants had significantly greater reductions in the number of DSM-5 IGD criteria they met, craving for video gaming, and maladaptive cognitions associated with gaming than SG participants, and therapeutic benefits were maintained at 3-month follow-up. MORE is a promising treatment approach for IGD. PMID:28437120

Written object naming, spelling to dictation, and immediate copying: Different tasks, different pathways?

PubMed

Bonin, Patrick; Méot, Alain; Lagarrigue, Aurélie; Roux, Sébastien

2015-01-01

We report an investigation of cross-task comparisons of handwritten latencies in written object naming, spelling to dictation, and immediate copying. In three separate sessions, adults had to write down a list of concrete nouns from their corresponding pictures (written naming), from their spoken (spelling to dictation) and from their visual presentation (immediate copying). Linear mixed models without random slopes were performed on the latencies in order to study and compare within-task fixed effects. By-participants random slopes were then included to investigate individual differences within and across tasks. Overall, the findings suggest that written naming, spelling to dictation, and copying all involve a lexical pathway, but that written naming relies on this pathway more than the other two tasks do. Only spelling to dictation strongly involves a nonlexical pathway. Finally, the analyses performed at the level of participants indicate that, depending on the type of task, the slower participants are more or less influenced by certain psycholinguistic variables.

Randomized controlled trial to test the RHANI Wives HIV intervention for women in India at risk for HIV from husbands.

PubMed

Raj, Anita; Saggurti, Niranjan; Battala, Madhusudana; Nair, Saritha; Dasgupta, Anindita; Naik, D D; Abramovitz, Daniela; Silverman, Jay G; Balaiah, Donta

2013-11-01

This study involved evaluation of the short-term impact of the RHANI Wives HIV intervention among wives at risk for HIV from husbands in Mumbai, India. A two-armed cluster RCT was conducted with 220 women surveyed on marital sex at baseline and 4-5 month follow-up. RHANI Wives was a multisession intervention focused on safer sex, marital communication, gender inequities and violence; control participants received basic HIV prevention education. Generalized linear mixed models were conducted to assess program impact, with cluster as a random effect and with time, treatment group, and the time by treatment interaction as fixed effects. A significant time by treatment effect on proportion of unprotected sex with husband (p = 0.01) was observed, and the rate of unprotected sex for intervention participants was lower than that of control participants at follow-up (RR = 0.83, 95 % CI = 0.75, 0.93). RHANI Wives is a promising model for women at risk for HIV from husbands.

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

Restricted spatial regression in practice: Geostatistical models, confounding, and robustness under model misspecification

USGS Publications Warehouse

Hanks, Ephraim M.; Schliep, Erin M.; Hooten, Mevin B.; Hoeting, Jennifer A.

2015-01-01

In spatial generalized linear mixed models (SGLMMs), covariates that are spatially smooth are often collinear with spatially smooth random effects. This phenomenon is known as spatial confounding and has been studied primarily in the case where the spatial support of the process being studied is discrete (e.g., areal spatial data). In this case, the most common approach suggested is restricted spatial regression (RSR) in which the spatial random effects are constrained to be orthogonal to the fixed effects. We consider spatial confounding and RSR in the geostatistical (continuous spatial support) setting. We show that RSR provides computational benefits relative to the confounded SGLMM, but that Bayesian credible intervals under RSR can be inappropriately narrow under model misspecification. We propose a posterior predictive approach to alleviating this potential problem and discuss the appropriateness of RSR in a variety of situations. We illustrate RSR and SGLMM approaches through simulation studies and an analysis of malaria frequencies in The Gambia, Africa.

On the mixing time of geographical threshold graphs

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

Bradonjic, Milan

In this paper, we study the mixing time of random graphs generated by the geographical threshold graph (GTG) model, a generalization of random geometric graphs (RGG). In a GTG, nodes are distributed in a Euclidean space, and edges are assigned according to a threshold function involving the distance between nodes as well as randomly chosen node weights. The motivation for analyzing this model is that many real networks (e.g., wireless networks, the Internet, etc.) need to be studied by using a 'richer' stochastic model (which in this case includes both a distance between nodes and weights on the nodes). Wemore » specifically study the mixing times of random walks on 2-dimensional GTGs near the connectivity threshold. We provide a set of criteria on the distribution of vertex weights that guarantees that the mixing time is {Theta}(n log n).« less

Using generalized additive (mixed) models to analyze single case designs.

PubMed

Shadish, William R; Zuur, Alain F; Sullivan, Kristynn J

2014-04-01

This article shows how to apply generalized additive models and generalized additive mixed models to single-case design data. These models excel at detecting the functional form between two variables (often called trend), that is, whether trend exists, and if it does, what its shape is (e.g., linear and nonlinear). In many respects, however, these models are also an ideal vehicle for analyzing single-case designs because they can consider level, trend, variability, overlap, immediacy of effect, and phase consistency that single-case design researchers examine when interpreting a functional relation. We show how these models can be implemented in a wide variety of ways to test whether treatment is effective, whether cases differ from each other, whether treatment effects vary over cases, and whether trend varies over cases. We illustrate diagnostic statistics and graphs, and we discuss overdispersion of data in detail, with examples of quasibinomial models for overdispersed data, including how to compute dispersion and quasi-AIC fit indices in generalized additive models. We show how generalized additive mixed models can be used to estimate autoregressive models and random effects and discuss the limitations of the mixed models compared to generalized additive models. We provide extensive annotated syntax for doing all these analyses in the free computer program R. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Dose reduction of risperidone and olanzapine can improve cognitive function and negative symptoms in stable schizophrenic patients: A single-blinded, 52-week, randomized controlled study.

PubMed

Zhou, Yanling; Li, Guannan; Li, Dan; Cui, Hongmei; Ning, Yuping

2018-05-01

The long-term effects of dose reduction of atypical antipsychotics on cognitive function and symptomatology in stable patients with schizophrenia remain unclear. We sought to determine the change in cognitive function and symptomatology after reducing risperidone or olanzapine dosage in stable schizophrenic patients. Seventy-five stabilized schizophrenic patients prescribed risperidone (≥4 mg/day) or olanzapine (≥10 mg/day) were randomly divided into a dose-reduction group ( n=37) and a maintenance group ( n=38). For the dose-reduction group, the dose of antipsychotics was reduced by 50%; for the maintenance group, the dose remained unchanged throughout the whole study. The Positive and Negative Syndrome Scale, Negative Symptom Assessment-16, Rating Scale for Extrapyramidal Side Effects, and Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery were measured at baseline, 12, 28, and 52 weeks. Linear mixed models were performed to compare the Positive and Negative Syndrome Scale, Negative Symptom Assessment-16, Rating Scale for Extrapyramidal Side Effects and MATRICS Consensus Cognitive Battery scores between groups. The linear mixed model showed significant time by group interactions on the Positive and Negative Syndrome Scale negative symptoms, Negative Symptom Assessment-16, Rating Scale for Extrapyramidal Side Effects, speed of processing, attention/vigilance, working memory and total score of MATRICS Consensus Cognitive Battery (all p<0.05). Post hoc analyses showed significant improvement in Positive and Negative Syndrome Scale negative subscale, Negative Symptom Assessment-16, Rating Scale for Extrapyramidal Side Effects, speed of processing, working memory and total score of MATRICS Consensus Cognitive Battery for the dose reduction group compared with those for the maintenance group (all p<0.05). This study indicated that a risperidone or olanzapine dose reduction of 50% may not lead to more severe symptomatology but can improve speed of processing, working memory and negative symptoms in patients with stabilized schizophrenia.

Short-Term Effect of Two Semi-Occluded Vocal Tract Training Programs on the Vocal Quality of Future Occupational Voice Users: "Resonant Voice Training Using Nasal Consonants" Versus "Straw Phonation".

PubMed

Meerschman, Iris; Van Lierde, Kristiane; Peeters, Karen; Meersman, Eline; Claeys, Sofie; D'haeseleer, Evelien

2017-09-18

The purpose of this study was to determine the short-term effect of 2 semi-occluded vocal tract training programs, "resonant voice training using nasal consonants" versus "straw phonation," on the vocal quality of vocally healthy future occupational voice users. A multigroup pretest-posttest randomized control group design was used. Thirty healthy speech-language pathology students with a mean age of 19 years (range: 17-22 years) were randomly assigned into a resonant voice training group (practicing resonant exercises across 6 weeks, n = 10), a straw phonation group (practicing straw phonation across 6 weeks, n = 10), or a control group (receiving no voice training, n = 10). A voice assessment protocol consisting of both subjective (questionnaire, participant's self-report, auditory-perceptual evaluation) and objective (maximum performance task, aerodynamic assessment, voice range profile, acoustic analysis, acoustic voice quality index, dysphonia severity index) measurements and determinations was used to evaluate the participants' voice pre- and posttraining. Groups were compared over time using linear mixed models and generalized linear mixed models. Within-group effects of time were determined using post hoc pairwise comparisons. No significant time × group interactions were found for any of the outcome measures, indicating no differences in evolution over time among the 3 groups. Within-group effects of time showed a significant improvement in dysphonia severity index in the resonant voice training group, and a significant improvement in the intensity range in the straw phonation group. Results suggest that the semi-occluded vocal tract training programs using resonant voice training and straw phonation may have a positive impact on the vocal quality and vocal capacities of future occupational voice users. The resonant voice training caused an improved dysphonia severity index, and the straw phonation training caused an expansion of the intensity range in this population.

Time and frequency domain analysis of sampled data controllers via mixed operation equations

NASA Technical Reports Server (NTRS)

Frisch, H. P.

1981-01-01

Specification of the mathematical equations required to define the dynamic response of a linear continuous plant, subject to sampled data control, is complicated by the fact that the digital components of the control system cannot be modeled via linear ordinary differential equations. This complication can be overcome by introducing two new mathematical operations; namely, the operation of zero order hold and digial delay. It is shown that by direct utilization of these operations, a set of linear mixed operation equations can be written and used to define the dynamic response characteristics of the controlled system. It also is shown how these linear mixed operation equations lead, in an automatable manner, directly to a set of finite difference equations which are in a format compatible with follow on time and frequency domain analysis methods.

Final Report---Optimization Under Nonconvexity and Uncertainty: Algorithms and Software

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

Jeff Linderoth

2011-11-06

the goal of this work was to develop new algorithmic techniques for solving large-scale numerical optimization problems, focusing on problems classes that have proven to be among the most challenging for practitioners: those involving uncertainty and those involving nonconvexity. This research advanced the state-of-the-art in solving mixed integer linear programs containing symmetry, mixed integer nonlinear programs, and stochastic optimization problems. The focus of the work done in the continuation was on Mixed Integer Nonlinear Programs (MINLP)s and Mixed Integer Linear Programs (MILP)s, especially those containing a great deal of symmetry.

Waste management with recourse: an inexact dynamic programming model containing fuzzy boundary intervals in objectives and constraints.

PubMed

Tan, Q; Huang, G H; Cai, Y P

2010-09-01

The existing inexact optimization methods based on interval-parameter linear programming can hardly address problems where coefficients in objective functions are subject to dual uncertainties. In this study, a superiority-inferiority-based inexact fuzzy two-stage mixed-integer linear programming (SI-IFTMILP) model was developed for supporting municipal solid waste management under uncertainty. The developed SI-IFTMILP approach is capable of tackling dual uncertainties presented as fuzzy boundary intervals (FuBIs) in not only constraints, but also objective functions. Uncertainties expressed as a combination of intervals and random variables could also be explicitly reflected. An algorithm with high computational efficiency was provided to solve SI-IFTMILP. SI-IFTMILP was then applied to a long-term waste management case to demonstrate its applicability. Useful interval solutions were obtained. SI-IFTMILP could help generate dynamic facility-expansion and waste-allocation plans, as well as provide corrective actions when anticipated waste management plans are violated. It could also greatly reduce system-violation risk and enhance system robustness through examining two sets of penalties resulting from variations in fuzziness and randomness. Moreover, four possible alternative models were formulated to solve the same problem; solutions from them were then compared with those from SI-IFTMILP. The results indicate that SI-IFTMILP could provide more reliable solutions than the alternatives. 2010 Elsevier Ltd. All rights reserved.

Great Taste, Less Waste: A cluster-randomized trial using a communications campaign to improve the quality of foods brought from home to school by elementary school children

PubMed Central

Goldberg, Jeanne P.; Folta, Sara C.; Eliasziw, Misha; Koch-Weser, Susan; Economos, Christina D.; Hubbard, Kristie L.; Peterson, Lindsay A.; Wright, Catherine M.; Must, Aviva

2015-01-01

Objective Great Taste, Less Waste (GTLW), a communications campaign, capitalized on the synergy between healthy eating and eco-friendly behaviors to motivate children to bring more fruits and vegetables and fewer sugar-sweetened beverages (SSBs) to school. Methods A cluster-randomized trial in Eastern Massachusetts elementary schools in 2011–2012 tested the hypothesis that GTLW would improve the quality of foods from home more than a nutrition-only campaign – Foods 2 Choose (F2C) – or control. Lunch and snack items from home were measured at baseline and 7 months later using digital photography. Mixed linear models compared change in mean servings of fruits, vegetables, and SSBs among groups, and change in mean prevalence of packaging type. Change in prevalence of food items of interest was compared among groups using generalized linear models. Results 582 third and fourth graders from 82 classrooms in 12 schools participated. At follow-up, no significant differences were observed between groups in change in mean servings or change in prevalence of items of interest. No packaging differences were observed. Conclusion GTLW was well-received but no significant changes were observed in the quality of food brought to school. Whether classrooms are an effective environment for change remains to be explored. PMID:25735605

Blood pressure and anthropometrics of 4-y-old children born after preimplantation genetic screening: follow-up of a unique, moderately sized, randomized controlled trial.

PubMed

Seggers, Jorien; Haadsma, Maaike L; Bastide-van Gemert, Sacha la; Heineman, Maas Jan; Kok, Joke H; Middelburg, Karin J; Roseboom, Tessa J; Schendelaar, Pamela; Van den Heuvel, Edwin R; Hadders-Algra, Mijna

2013-11-01

Recent studies suggest that in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) are associated with suboptimal cardiometabolic outcome in offspring. It is unknown whether preimplantation genetic screening (PGS), which involves embryo biopsy, affects blood pressure (BP), anthropometrics, and the frequency of received medical care. In this prospective multicenter follow-up study, we assessed BP, anthropometrics, and received medical care of 4-y-old children born to women who were randomly assigned to IVF/ICSI with PGS (n = 49) or without PGS (controls; n = 64). We applied linear and generalized linear mixed-effects models to investigate possible effects of PGS. BP in the PGS and control groups was similar: 102/64 and 100/64 mm Hg, respectively. Main anthropometric outcomes in the PGS vs. control group were: BMI: 16.1 vs. 15.8; triceps skinfold: 108 vs. 98 mm; and subscapular skinfold: 54 vs. 53 mm (all P values > 0.05). More PGS children than controls had received paramedical care (speech, physical, or occupational therapy: 14 (29%) vs. 9 (14%); P = 0.03 in multivariable analysis). The frequency of medicial treatment was comparable. PGS does not seem to affect BP or anthropometrics in 4-y-old children. The higher frequency of received paramedical care after PGS may suggest an effect of PGS on subtle developmental parameters.

Real-time, adaptive machine learning for non-stationary, near chaotic gasoline engine combustion time series.

PubMed

Vaughan, Adam; Bohac, Stanislav V

2015-10-01

Fuel efficient Homogeneous Charge Compression Ignition (HCCI) engine combustion timing predictions must contend with non-linear chemistry, non-linear physics, period doubling bifurcation(s), turbulent mixing, model parameters that can drift day-to-day, and air-fuel mixture state information that cannot typically be resolved on a cycle-to-cycle basis, especially during transients. In previous work, an abstract cycle-to-cycle mapping function coupled with ϵ-Support Vector Regression was shown to predict experimentally observed cycle-to-cycle combustion timing over a wide range of engine conditions, despite some of the aforementioned difficulties. The main limitation of the previous approach was that a partially acasual randomly sampled training dataset was used to train proof of concept offline predictions. The objective of this paper is to address this limitation by proposing a new online adaptive Extreme Learning Machine (ELM) extension named Weighted Ring-ELM. This extension enables fully causal combustion timing predictions at randomly chosen engine set points, and is shown to achieve results that are as good as or better than the previous offline method. The broader objective of this approach is to enable a new class of real-time model predictive control strategies for high variability HCCI and, ultimately, to bring HCCI's low engine-out NOx and reduced CO2 emissions to production engines. Copyright © 2015 Elsevier Ltd. All rights reserved.

Exploring the impact of high intensity interval training on adolescents' objectively measured physical activity: Findings from a randomized controlled trial.

PubMed

Costigan, Sarah A; Ridgers, Nicola D; Eather, Narelle; Plotnikoff, Ronald C; Harris, Nigel; Lubans, David R

2018-05-01

High Intensity Interval Training (HIIT) may be effective for accumulating VPA. However, the contribution of HIIT to overall physical activity is unknown. Our primary aim was to explore the impact of school-based HIIT on physical activity. The secondary aim was to explore within-individual changes in physical activity after participating in HIIT. Participants [n = 65; 15.8(0.6)years] were randomized to a HIIT or control group. Intervention groups participated in three HIIT sessions/week. GENEActiv accelerometers assessed objective physical activity at baseline and week-one, to detect changes in MPA and VPA. Intervention effects were examined using linear mixed models and evidence of a change in physical activity (i.e., compensation) were examined using multilevel linear regression models. The group-by-time interaction effects for MPA and VPA were small and moderate, respectively. Adjusted difference between groups for VPA was 1.70 min/day, 95%CI -1.96 to 5.36; p = 0.354; d = 0.55). Embedding HIIT within the school-day had a moderate effect on VPA compared to controls. Compensation analyses (i.e., individual level) suggested that adolescents were more active on days when they participated in HIIT. Further studies are needed to test the effects of HIIT on adolescents' physical activity over extended time periods.

Conserved linear dynamics of single-molecule Brownian motion.

PubMed

Serag, Maged F; Habuchi, Satoshi

2017-06-06

Macromolecular diffusion in homogeneous fluid at length scales greater than the size of the molecule is regarded as a random process. The mean-squared displacement (MSD) of molecules in this regime increases linearly with time. Here we show that non-random motion of DNA molecules in this regime that is undetectable by the MSD analysis can be quantified by characterizing the molecular motion relative to a latticed frame of reference. Our lattice occupancy analysis reveals unexpected sub-modes of motion of DNA that deviate from expected random motion in the linear, diffusive regime. We demonstrate that a subtle interplay between these sub-modes causes the overall diffusive motion of DNA to appear to conform to the linear regime. Our results show that apparently random motion of macromolecules could be governed by non-random dynamics that are detectable only by their relative motion. Our analytical approach should advance broad understanding of diffusion processes of fundamental relevance.

Conserved linear dynamics of single-molecule Brownian motion

PubMed Central

Serag, Maged F.; Habuchi, Satoshi

2017-01-01

Macromolecular diffusion in homogeneous fluid at length scales greater than the size of the molecule is regarded as a random process. The mean-squared displacement (MSD) of molecules in this regime increases linearly with time. Here we show that non-random motion of DNA molecules in this regime that is undetectable by the MSD analysis can be quantified by characterizing the molecular motion relative to a latticed frame of reference. Our lattice occupancy analysis reveals unexpected sub-modes of motion of DNA that deviate from expected random motion in the linear, diffusive regime. We demonstrate that a subtle interplay between these sub-modes causes the overall diffusive motion of DNA to appear to conform to the linear regime. Our results show that apparently random motion of macromolecules could be governed by non-random dynamics that are detectable only by their relative motion. Our analytical approach should advance broad understanding of diffusion processes of fundamental relevance. PMID:28585925

Conserved linear dynamics of single-molecule Brownian motion

NASA Astrophysics Data System (ADS)

Serag, Maged F.; Habuchi, Satoshi

2017-06-01

Macromolecular diffusion in homogeneous fluid at length scales greater than the size of the molecule is regarded as a random process. The mean-squared displacement (MSD) of molecules in this regime increases linearly with time. Here we show that non-random motion of DNA molecules in this regime that is undetectable by the MSD analysis can be quantified by characterizing the molecular motion relative to a latticed frame of reference. Our lattice occupancy analysis reveals unexpected sub-modes of motion of DNA that deviate from expected random motion in the linear, diffusive regime. We demonstrate that a subtle interplay between these sub-modes causes the overall diffusive motion of DNA to appear to conform to the linear regime. Our results show that apparently random motion of macromolecules could be governed by non-random dynamics that are detectable only by their relative motion. Our analytical approach should advance broad understanding of diffusion processes of fundamental relevance.

Inference for binomial probability based on dependent Bernoulli random variables with applications to meta-analysis and group level studies.

PubMed

Bakbergenuly, Ilyas; Kulinskaya, Elena; Morgenthaler, Stephan

2016-07-01

We study bias arising as a result of nonlinear transformations of random variables in random or mixed effects models and its effect on inference in group-level studies or in meta-analysis. The findings are illustrated on the example of overdispersed binomial distributions, where we demonstrate considerable biases arising from standard log-odds and arcsine transformations of the estimated probability p̂, both for single-group studies and in combining results from several groups or studies in meta-analysis. Our simulations confirm that these biases are linear in ρ, for small values of ρ, the intracluster correlation coefficient. These biases do not depend on the sample sizes or the number of studies K in a meta-analysis and result in abysmal coverage of the combined effect for large K. We also propose bias-correction for the arcsine transformation. Our simulations demonstrate that this bias-correction works well for small values of the intraclass correlation. The methods are applied to two examples of meta-analyses of prevalence. © 2016 The Authors. Biometrical Journal Published by Wiley-VCH Verlag GmbH & Co. KGaA.

A systematic examination of a random sampling strategy for source apportionment calculations.

PubMed

Andersson, August

2011-12-15

Estimating the relative contributions from multiple potential sources of a specific component in a mixed environmental matrix is a general challenge in diverse fields such as atmospheric, environmental and earth sciences. Perhaps the most common strategy for tackling such problems is by setting up a system of linear equations for the fractional influence of different sources. Even though an algebraic solution of this approach is possible for the common situation with N+1 sources and N source markers, such methodology introduces a bias, since it is implicitly assumed that the calculated fractions and the corresponding uncertainties are independent of the variability of the source distributions. Here, a random sampling (RS) strategy for accounting for such statistical bias is examined by investigating rationally designed synthetic data sets. This random sampling methodology is found to be robust and accurate with respect to reproducibility and predictability. This method is also compared to a numerical integration solution for a two-source situation where source variability also is included. A general observation from this examination is that the variability of the source profiles not only affects the calculated precision but also the mean/median source contributions. Copyright © 2011 Elsevier B.V. All rights reserved.

Mediators of Treatment Effects in a Randomized Clinical Trial of Multisystemic Therapy-Health Care in Adolescents With Poorly Controlled Asthma: Disease Knowledge and Device Use Skills.

PubMed

Ellis, Deborah A; King, Pamela; Naar-King, Sylvie

2016-06-01

Determine whether Multisystemic Therapy-Health Care (MST-HC) improved asthma knowledge and controller device use skills among African-American youth with poorly controlled asthma and whether any improvements mediated changes in illness management. A randomized controlled trial was conducted with 170 adolescents with moderate to severe asthma. Families were randomized to MST-HC or attention control. Data were collected at baseline and 6 and 12 months after intervention completion. In linear mixed models, adolescents in the MST-HC group had increases in asthma knowledge; asthma knowledge was unchanged for attention control. Controller device use skills increased for adolescents in the MST-HC group, while skills declined for attention control. Both knowledge and skills mediated the relationship between intervention condition and changes in illness management. Tailored, home-based interventions that include knowledge and skills building components are one means by which illness management in African-American youth with poorly controlled asthma can be improved. © The Author 2015. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A multiphase non-linear mixed effects model: An application to spirometry after lung transplantation.

PubMed

Rajeswaran, Jeevanantham; Blackstone, Eugene H

2017-02-01

In medical sciences, we often encounter longitudinal temporal relationships that are non-linear in nature. The influence of risk factors may also change across longitudinal follow-up. A system of multiphase non-linear mixed effects model is presented to model temporal patterns of longitudinal continuous measurements, with temporal decomposition to identify the phases and risk factors within each phase. Application of this model is illustrated using spirometry data after lung transplantation using readily available statistical software. This application illustrates the usefulness of our flexible model when dealing with complex non-linear patterns and time-varying coefficients.

Confidence Intervals for Assessing Heterogeneity in Generalized Linear Mixed Models

ERIC Educational Resources Information Center

Wagler, Amy E.

2014-01-01

Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for…

Modeling containment of large wildfires using generalized linear mixed-model analysis

Treesearch

Mark Finney; Isaac C. Grenfell; Charles W. McHugh

2009-01-01

Billions of dollars are spent annually in the United States to contain large wildland fires, but the factors contributing to suppression success remain poorly understood. We used a regression model (generalized linear mixed-model) to model containment probability of individual fires, assuming that containment was a repeated-measures problem (fixed effect) and...

Visual, Algebraic and Mixed Strategies in Visually Presented Linear Programming Problems.

ERIC Educational Resources Information Center

Shama, Gilli; Dreyfus, Tommy

1994-01-01

Identified and classified solution strategies of (n=49) 10th-grade students who were presented with linear programming problems in a predominantly visual setting in the form of a computerized game. Visual strategies were developed more frequently than either algebraic or mixed strategies. Appendix includes questionnaires. (Contains 11 references.)…

Mixed H∞ and passive control for linear switched systems via hybrid control approach

NASA Astrophysics Data System (ADS)

Zheng, Qunxian; Ling, Youzhu; Wei, Lisheng; Zhang, Hongbin

2018-03-01

This paper investigates the mixed H∞ and passive control problem for linear switched systems based on a hybrid control strategy. To solve this problem, first, a new performance index is proposed. This performance index can be viewed as the mixed weighted H∞ and passivity performance. Then, the hybrid controllers are used to stabilise the switched systems. The hybrid controllers consist of dynamic output-feedback controllers for every subsystem and state updating controllers at the switching instant. The design of state updating controllers not only depends on the pre-switching subsystem and the post-switching subsystem, but also depends on the measurable output signal. The hybrid controllers proposed in this paper can include some existing ones as special cases. Combine the multiple Lyapunov functions approach with the average dwell time technique, new sufficient conditions are obtained. Under the new conditions, the closed-loop linear switched systems are globally uniformly asymptotically stable with a mixed H∞ and passivity performance index. Moreover, the desired hybrid controllers can be constructed by solving a set of linear matrix inequalities. Finally, a numerical example and a practical example are given.

Elastic properties and optical absorption studies of mixed alkali borogermanate glasses

NASA Astrophysics Data System (ADS)

Taqiullah, S. M.; Ahmmad, Shaik Kareem; Samee, M. A.; Rahman, Syed

2018-05-01

First time the mixed alkali effect (MAE) has been investigated in the glass system xNa2O-(30-x)Li2O-40B2O3- 30GeO2 (0≤x≤30 mol%) through density and optical absorption studies. The present glasses were prepared by melt quench technique. The density of the present glasses varies non-linearly exhibiting mixed alkali effect. Using the density data, the elastic moduli namely Young's modulus, bulk and shear modulus show strong linear dependence as a function of compositional parameter. From the absorption edge studies, the values of optical band gap energies for all transitions have been evaluated. It was established that the type of electronic transition in the present glass system is indirect allowed. The indirect optical band gap exhibit non-linear behavior with compositional parameter showing the mixed alkali effect.

Nevasic audio program for the prevention of chemotherapy induced nausea and vomiting: A feasibility study using a randomized controlled trial design.

PubMed

Moradian, Saeed; Walshe, Catherine; Shahidsales, Soodabeh; Ghavam Nasiri, Mohammad Reza; Pilling, Mark; Molassiotis, Alexander

2015-06-01

Pharmacological therapy is only partially effective in preventing or treating chemotherapy induced nausea and vomiting (CINV). Therefore, exploring the complementary role of non-pharmacological approaches used in addition to pharmacological agents is important. Nevasic uses specially constructed audio signals hypothesized to generate an antiemetic reaction. The aim of this study was to examine the feasibility of conducting a randomized controlled trial (RCT) to evaluate the effectiveness of Nevasic to control CINV. A mixed methods design incorporating an RCT and focus group interviews. For the RCT, female breast cancer patients were randomized to receive either Nevasic plus usual care, music plus usual care, or usual care only. Data were analysed using descriptive statistics and linear mixed-effects models. Five focus group interviews were conducted to obtain participants' views regarding the acceptability of the interventions in the trial. 99 participants were recruited to the RCT and 15 participated in focus group interviews. Recruitment targets were achieved. Issues of Nevasic acceptability were highlighted as weaknesses of the program. This study did not detect any evidence for the effectiveness of Nevasic; however, the results showed statistically significant less use of anti-emetics (p = 0.003) and borderline non-significant improvement in quality of life (p = 0.06). Conducting a non-pharmacological intervention using such an audio program is feasible, although difficulties and limitations exist with its use. Further studies are required to investigate the effectiveness of Nevasic from perspectives such as anti-emetic use, as well as its overall effect on the levels of nausea and vomiting. Copyright © 2014 Elsevier Ltd. All rights reserved.

The velocity of antihypertensive effect of losartan/hydrochlorothiazide and angiotensin II receptor blocker.

PubMed

Metoki, Hirohito; Ohkubo, Takayoshi; Kikuya, Masahiro; Asayama, Kei; Inoue, Ryusuke; Obara, Taku; Hirose, Takuo; Sato, Michihiro; Hashimoto, Takanao; Imai, Yutaka

2012-07-01

The hypotensive effect and the time to attain the maximum antihypertensive effect (stabilization time) of losartan/hydrochlorothiazide (HCTZ) combination therapy and therapy with a maximal dose of angiotensin II receptor blockers (ARBs) in patients who failed to achieve adequate blood pressure (BP) control on a medium-dose of ARBs were compared by analyzing exponential decay functions using daily serial morning home BP measurements. Essential hypertensive patients treated with a medium dose of ARB, in whom a target home SBP (135 mmHg) was not achieved, were randomized into two groups: a combination group (n = 110) and a maximal-dose ARB group (n = 111). The combination therapy provided additional reduction of 5.2 mmHg [95% confidence interval (CI) 1.8 to 8.5 mmHg, P = 0.003] in home SBP over the maximal-dose ARB therapy in 8 weeks after randomization. A greater reduction in the home SBP values was seen in the combination group than in the maximal-dose ARB group from the second day after randomization on the basis of a linear mixed model. The maximum antihypertensive effect and stabilization time for home SBP were 10.9 ± 5.0 mmHg and 7.3 ± 29.7 days, respectively, in the combination group, whereas the corresponding values in the maximal-dose ARB group were 7.9 ± 2.6  mmHg and 122.3 ± 42.7 days, respectively, on the basis of a nonlinear mixed model. Changing from a medium dose of ARB monotherapy to combination therapy was more effective in the reduction of home SBP and achieved goal BP more rapidly than increasing the ARB dose. Home BP measurement is a useful tool for characterizing the antihypertensive effects of drugs.

Daily electronic self-monitoring in bipolar disorder using smartphones - the MONARCA I trial: a randomized, placebo-controlled, single-blind, parallel group trial.

PubMed

Faurholt-Jepsen, M; Frost, M; Ritz, C; Christensen, E M; Jacoby, A S; Mikkelsen, R L; Knorr, U; Bardram, J E; Vinberg, M; Kessing, L V

2015-10-01

The number of studies on electronic self-monitoring in affective disorder and other psychiatric disorders is increasing and indicates high patient acceptance and adherence. Nevertheless, the effect of electronic self-monitoring in patients with bipolar disorder has never been investigated in a randomized controlled trial (RCT). The objective of this trial was to investigate in a RCT whether the use of daily electronic self-monitoring using smartphones reduces depressive and manic symptoms in patients with bipolar disorder. A total of 78 patients with bipolar disorder according to ICD-10 criteria, aged 18-60 years, and with 17-item Hamilton Depression Rating Scale (HAMD-17) and Young Mania Rating Scale (YMRS) scores ≤17 were randomized to the use of a smartphone for daily self-monitoring including a clinical feedback loop (the intervention group) or to the use of a smartphone for normal communicative purposes (the control group) for 6 months. The primary outcomes were differences in depressive and manic symptoms measured using HAMD-17 and YMRS, respectively, between the intervention and control groups. Intention-to-treat analyses using linear mixed models showed no significant effects of daily self-monitoring using smartphones on depressive as well as manic symptoms. There was a tendency towards more sustained depressive symptoms in the intervention group (B = 2.02, 95% confidence interval -0.13 to 4.17, p = 0.066). Sub-group analysis among patients without mixed symptoms and patients with presence of depressive and manic symptoms showed significantly more depressive symptoms and fewer manic symptoms during the trial period in the intervention group. These results highlight that electronic self-monitoring, although intuitive and appealing, needs critical consideration and further clarification before it is implemented as a clinical tool.

Optimal clinical trial design based on a dichotomous Markov-chain mixed-effect sleep model.

PubMed

Steven Ernest, C; Nyberg, Joakim; Karlsson, Mats O; Hooker, Andrew C

2014-12-01

D-optimal designs for discrete-type responses have been derived using generalized linear mixed models, simulation based methods and analytical approximations for computing the fisher information matrix (FIM) of non-linear mixed effect models with homogeneous probabilities over time. In this work, D-optimal designs using an analytical approximation of the FIM for a dichotomous, non-homogeneous, Markov-chain phase advanced sleep non-linear mixed effect model was investigated. The non-linear mixed effect model consisted of transition probabilities of dichotomous sleep data estimated as logistic functions using piecewise linear functions. Theoretical linear and nonlinear dose effects were added to the transition probabilities to modify the probability of being in either sleep stage. D-optimal designs were computed by determining an analytical approximation the FIM for each Markov component (one where the previous state was awake and another where the previous state was asleep). Each Markov component FIM was weighted either equally or by the average probability of response being awake or asleep over the night and summed to derive the total FIM (FIM(total)). The reference designs were placebo, 0.1, 1-, 6-, 10- and 20-mg dosing for a 2- to 6-way crossover study in six dosing groups. Optimized design variables were dose and number of subjects in each dose group. The designs were validated using stochastic simulation/re-estimation (SSE). Contrary to expectations, the predicted parameter uncertainty obtained via FIM(total) was larger than the uncertainty in parameter estimates computed by SSE. Nevertheless, the D-optimal designs decreased the uncertainty of parameter estimates relative to the reference designs. Additionally, the improvement for the D-optimal designs were more pronounced using SSE than predicted via FIM(total). Through the use of an approximate analytic solution and weighting schemes, the FIM(total) for a non-homogeneous, dichotomous Markov-chain phase advanced sleep model was computed and provided more efficient trial designs and increased nonlinear mixed-effects modeling parameter precision.

Effects of isobutyrate supplementation in pre- and post-weaned dairy calves diet on growth performance, rumen development, blood metabolites and hormone secretion.

PubMed

Wang, C; Liu, Q; Zhang, Y L; Pei, C X; Zhang, S L; Guo, G; Huo, W J; Yang, W Z; Wang, H

2017-05-01

Isobutyrate supplements could improve rumen development by increasing ruminal fermentation products, especially butyrate, and then promote the growth performance of calves. The objective of this study was to evaluate the effects of isobutyrate supplementation on growth performance, rumen development, blood metabolites and hormone secretion in pre- and post-weaned dairy calves. In total, 56 Chinese Holstein male calves with 30 days of age and 72.9±1.43 kg of BW, blocked by days of age and BW, were assigned to four groups in a randomized block design. The treatments were as follows: control, low-isobutyrate, moderate-isobutyrate and high-isobutyrate with 0, 0.03, 0.06 and 0.09 g isobutyrate/kg BW per calf per day, respectively. Supplemental isobutyrate was hand-mixed into milk of pre-weaned calves and the concentrate portion of post-weaned calves. The study consisted of 10 days of an adaptation period and a 50-day sampling period. Calves were weaned at 60 days of age. Seven calves were chosen from each treatment at random and slaughtered at 45 and 90 days of age. BW, dry matter (DM) intake and stomach weight were measured, samples of ruminal tissues and blood were determined. For pre- and post-weaned calves, DM intake and average daily gain increased linearly (P<0.05), but feed conversion ratio decreased linearly (P<0.05) with increasing isobutyrate supplementation. Total stomach weight and the ratio of rumen weight to total stomach weight tended to increase (P=0.073) for pre-weaned calves and increased linearly (P=0.021) for post-weaned calves, whereas the ratio of abomasum weight to total stomach weight was not affected for pre-weaned calves and decreased linearly (P<0.05) for post-weaned calves with increasing isobutyrate supplementation. Both length and width of rumen papillae tended to increase linearly for pre-weaned calves, but increased linearly (P<0.05) for post-weaned calves with increasing isobutyrate supplementation. The relative expression of messenger RNA for growth hormone (GH) receptor and 3-hydroxy-3-methylglutaryl-CoA synthase 1 in rumen mucosa increased linearly (P<0.05) for pre- and post-weaned calves with increasing isobutyrate supplementation. Blood concentrations of glucose, acetoacetate, β-hydroxybutyrate, GH and IGF-1 increased linearly (P<0.05) for pre- and post-weaned calves, whereas blood concentration of insulin decreased linearly with increasing isobutyrate supplementation. The present results indicated that isobutyrate promoted growth of calves by improving rumen development and its ketogenesis in a dose-dependent manner.

Linear growth increased in young children in an urban slum of Haiti: a randomized controlled trial of a lipid-based nutrient supplement.

PubMed

Iannotti, Lora L; Dulience, Sherlie Jean Louis; Green, Jamie; Joseph, Saminetha; François, Judith; Anténor, Marie-Lucie; Lesorogol, Carolyn; Mounce, Jacqueline; Nickerson, Nathan M

2014-01-01

Haiti has experienced rapid urbanization that has exacerbated poverty and undernutrition in large slum areas. Stunting affects 1 in 5 young children. We aimed to test the efficacy of a daily lipid-based nutrient supplement (LNS) for increased linear growth in young children. Healthy, singleton infants aged 6-11 mo (n = 589) were recruited from an urban slum of Cap Haitien and randomly assigned to receive: 1) a control; 2) a 3-mo LNS; or 3) a 6-mo LNS. The LNS provided 108 kcal and other nutrients including vitamin A, vitamin B-12, iron, and zinc at ≥80% of the recommended amounts. Infants were followed monthly on growth, morbidity, and developmental outcomes over a 6-mo intervention period and at one additional time point 6 mo postintervention to assess sustained effects. The Bonferroni multiple comparisons test was applied, and generalized least-squares (GLS) regressions with mixed effects was used to examine impacts longitudinally. Baseline characteristics did not differ by trial arm except for a higher mean age in the 6-mo LNS group. GLS modeling showed LNS supplementation for 6 mo significantly increased the length-for-age z score (±SE) by 0.13 ± 0.05 and the weight-for-age z score by 0.12 ± 0.02 compared with in the control group after adjustment for child age (P < 0.001). The effects were sustained 6 mo postintervention. Morbidity and developmental outcomes did not differ by trial arm. A low-energy, fortified product improved the linear growth of young children in this urban setting. The trial was registered at clinicaltrials.gov as NCT01552512.

Non-linear continuous time random walk models★

NASA Astrophysics Data System (ADS)

Stage, Helena; Fedotov, Sergei

2017-11-01

A standard assumption of continuous time random walk (CTRW) processes is that there are no interactions between the random walkers, such that we obtain the celebrated linear fractional equation either for the probability density function of the walker at a certain position and time, or the mean number of walkers. The question arises how one can extend this equation to the non-linear case, where the random walkers interact. The aim of this work is to take into account this interaction under a mean-field approximation where the statistical properties of the random walker depend on the mean number of walkers. The implementation of these non-linear effects within the CTRW integral equations or fractional equations poses difficulties, leading to the alternative methodology we present in this work. We are concerned with non-linear effects which may either inhibit anomalous effects or induce them where they otherwise would not arise. Inhibition of these effects corresponds to a decrease in the waiting times of the random walkers, be this due to overcrowding, competition between walkers or an inherent carrying capacity of the system. Conversely, induced anomalous effects present longer waiting times and are consistent with symbiotic, collaborative or social walkers, or indirect pinpointing of favourable regions by their attractiveness. Contribution to the Topical Issue "Continuous Time Random Walk Still Trendy: Fifty-year History, Current State and Outlook", edited by Ryszard Kutner and Jaume Masoliver.

IMPACT: Investigating the impact of Models of Practice for Allied health Care in subacuTe settings. A protocol for a quasi-experimental mixed methods study of cost effectiveness and outcomes for patients exposed to different models of allied health care.

PubMed

Coker, Freya; Williams, Cylie M; Taylor, Nicholas F; Caspers, Kirsten; McAlinden, Fiona; Wilton, Anita; Shields, Nora; Haines, Terry P

2018-05-10

This protocol considers three allied health staffing models across public health subacute hospitals. This quasi-experimental mixed-methods study, including qualitative process evaluation, aims to evaluate the impact of additional allied health services in subacute care, in rehabilitation and geriatric evaluation management settings, on patient, health service and societal outcomes. This health services research will analyse outcomes of patients exposed to different allied health models of care at three health services. Each health service will have a control ward (routine care) and an intervention ward (additional allied health). This project has two parts. Part 1: a whole of site data extraction for included wards. Outcome measures will include: length of stay, rate of readmissions, discharge destinations, community referrals, patient feedback and staff perspectives. Part 2: Functional Independence Measure scores will be collected every 2-3 days for the duration of 60 patient admissions.Data from part 1 will be analysed by linear regression analysis for continuous outcomes using patient-level data and logistic regression analysis for binary outcomes. Qualitative data will be analysed using a deductive thematic approach. For part 2, a linear mixed model analysis will be conducted using therapy service delivery and days since admission to subacute care as fixed factors in the model and individual participant as a random factor. Graphical analysis will be used to examine the growth curve of the model and transformations. The days since admission factor will be used to examine non-linear growth trajectories to determine if they lead to better model fit. Findings will be disseminated through local reports and to the Department of Health and Human Services Victoria. Results will be presented at conferences and submitted to peer-reviewed journals. The Monash Health Human Research Ethics committee approved this multisite research (HREC/17/MonH/144 and HREC/17/MonH/547). © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Alfvén wave interactions in the solar wind

NASA Astrophysics Data System (ADS)

Webb, G. M.; McKenzie, J. F.; Hu, Q.; le Roux, J. A.; Zank, G. P.

2012-11-01

Alfvén wave mixing (interaction) equations used in locally incompressible turbulence transport equations in the solar wind are analyzed from the perspective of linear wave theory. The connection between the wave mixing equations and non-WKB Alfven wave driven wind theories are delineated. We discuss the physical wave energy equation and the canonical wave energy equation for non-WKB Alfven waves and the WKB limit. Variational principles and conservation laws for the linear wave mixing equations for the Heinemann and Olbert non-WKB wind model are obtained. The connection with wave mixing equations used in locally incompressible turbulence transport in the solar wind are discussed.

Phase mixing versus nonlinear advection in drift-kinetic plasma turbulence

NASA Astrophysics Data System (ADS)

Schekochihin, A. A.; Parker, J. T.; Highcock, E. G.; Dellar, P. J.; Dorland, W.; Hammett, G. W.

2016-04-01

> A scaling theory of long-wavelength electrostatic turbulence in a magnetised, weakly collisional plasma (e.g. drift-wave turbulence driven by ion temperature gradients) is proposed, with account taken both of the nonlinear advection of the perturbed particle distribution by fluctuating flows and of its phase mixing, which is caused by the streaming of the particles along the mean magnetic field and, in a linear problem, would lead to Landau damping. It is found that it is possible to construct a consistent theory in which very little free energy leaks into high velocity moments of the distribution function, rendering the turbulent cascade in the energetically relevant part of the wavenumber space essentially fluid-like. The velocity-space spectra of free energy expressed in terms of Hermite-moment orders are steep power laws and so the free-energy content of the phase space does not diverge at infinitesimal collisionality (while it does for a linear problem); collisional heating due to long-wavelength perturbations vanishes in this limit (also in contrast with the linear problem, in which it occurs at the finite rate equal to the Landau damping rate). The ability of the free energy to stay in the low velocity moments of the distribution function is facilitated by the `anti-phase-mixing' effect, whose presence in the nonlinear system is due to the stochastic version of the plasma echo (the advecting velocity couples the phase-mixing and anti-phase-mixing perturbations). The partitioning of the wavenumber space between the (energetically dominant) region where this is the case and the region where linear phase mixing wins its competition with nonlinear advection is governed by the `critical balance' between linear and nonlinear time scales (which for high Hermite moments splits into two thresholds, one demarcating the wavenumber region where phase mixing predominates, the other where plasma echo does).

A Second-Order Conditionally Linear Mixed Effects Model with Observed and Latent Variable Covariates

ERIC Educational Resources Information Center

Harring, Jeffrey R.; Kohli, Nidhi; Silverman, Rebecca D.; Speece, Deborah L.

2012-01-01

A conditionally linear mixed effects model is an appropriate framework for investigating nonlinear change in a continuous latent variable that is repeatedly measured over time. The efficacy of the model is that it allows parameters that enter the specified nonlinear time-response function to be stochastic, whereas those parameters that enter in a…

Multivariate mixed linear model analysis of longitudinal data: an information-rich statistical technique for analyzing disease resistance data

USDA-ARS?s Scientific Manuscript database

The mixed linear model (MLM) is currently among the most advanced and flexible statistical modeling techniques and its use in tackling problems in plant pathology has begun surfacing in the literature. The longitudinal MLM is a multivariate extension that handles repeatedly measured data, such as r...

Assessing variance components in multilevel linear models using approximate Bayes factors: A case study of ethnic disparities in birthweight

PubMed Central

Saville, Benjamin R.; Herring, Amy H.; Kaufman, Jay S.

2013-01-01

Racial/ethnic disparities in birthweight are a large source of differential morbidity and mortality worldwide and have remained largely unexplained in epidemiologic models. We assess the impact of maternal ancestry and census tract residence on infant birth weights in New York City and the modifying effects of race and nativity by incorporating random effects in a multilevel linear model. Evaluating the significance of these predictors involves the test of whether the variances of the random effects are equal to zero. This is problematic because the null hypothesis lies on the boundary of the parameter space. We generalize an approach for assessing random effects in the two-level linear model to a broader class of multilevel linear models by scaling the random effects to the residual variance and introducing parameters that control the relative contribution of the random effects. After integrating over the random effects and variance components, the resulting integrals needed to calculate the Bayes factor can be efficiently approximated with Laplace’s method. PMID:24082430

surrosurv: An R package for the evaluation of failure time surrogate endpoints in individual patient data meta-analyses of randomized clinical trials.

PubMed

Rotolo, Federico; Paoletti, Xavier; Michiels, Stefan

2018-03-01

Surrogate endpoints are attractive for use in clinical trials instead of well-established endpoints because of practical convenience. To validate a surrogate endpoint, two important measures can be estimated in a meta-analytic context when individual patient data are available: the R indiv 2 or the Kendall's τ at the individual level, and the R trial 2 at the trial level. We aimed at providing an R implementation of classical and well-established as well as more recent statistical methods for surrogacy assessment with failure time endpoints. We also intended incorporating utilities for model checking and visualization and data generating methods described in the literature to date. In the case of failure time endpoints, the classical approach is based on two steps. First, a Kendall's τ is estimated as measure of individual level surrogacy using a copula model. Then, the R trial 2 is computed via a linear regression of the estimated treatment effects; at this second step, the estimation uncertainty can be accounted for via measurement-error model or via weights. In addition to the classical approach, we recently developed an approach based on bivariate auxiliary Poisson models with individual random effects to measure the Kendall's τ and treatment-by-trial interactions to measure the R trial 2 . The most common data simulation models described in the literature are based on: copula models, mixed proportional hazard models, and mixture of half-normal and exponential random variables. The R package surrosurv implements the classical two-step method with Clayton, Plackett, and Hougaard copulas. It also allows to optionally adjusting the second-step linear regression for measurement-error. The mixed Poisson approach is implemented with different reduced models in addition to the full model. We present the package functions for estimating the surrogacy models, for checking their convergence, for performing leave-one-trial-out cross-validation, and for plotting the results. We illustrate their use in practice on individual patient data from a meta-analysis of 4069 patients with advanced gastric cancer from 20 trials of chemotherapy. The surrosurv package provides an R implementation of classical and recent statistical methods for surrogacy assessment of failure time endpoints. Flexible simulation functions are available to generate data according to the methods described in the literature. Copyright © 2017 Elsevier B.V. All rights reserved.

Peer mentor versus teacher delivery of a physical activity program on the effects of BMI and daily activity: protocol of a school-based group randomized controlled trial in Appalachia.

PubMed

Smith, Laureen H; Petosa, Rick L; Shoben, Abigail

2018-05-16

Rural Appalachian populations have poorer health and fewer positive health-related behaviors compared to other United States populations. Appalachians are the most sedentary U.S. population and teens are particularly sedentary. Obesity prevention through improving physical activity is a top priority in Rural Healthy People 2020. Obesity prevalence among Appalachian teens exceeds the national rates of 13.9% and has consistently been greater than 26%. Organized sports has not been effective at improving daily physical activity or health outcomes for Appalachian teens. The purpose of this study is to test the efficacy of a 10-week school-based intervention in promoting self-regulation of physical activity among adolescents not participating in organized sports. By using accelerometers, our study will measure both sedentary time and planned exercise during waking hours. The design for this four-year study is a group-randomized controlled trial (G-RCT). We will recruit high schools in 3 waves, with 4 in Wave 1, 8 in Wave 2, and 8 in Wave 3, for a total of 20 schools. For each wave of schools, we will randomly assign half of the schools to each condition--intervention (peer-to-peer mentoring [MBA]) and comparison (teacher-led [PBA])--for a total of 10 schools in each of the two conditions by study's end. We will collect data at baseline (T 1 ), 3 months post intervention (T 2 ), and 6 months post intervention (T 3 ). Linear Mixed Models (LMMs) and Generalized Linear Mixed Models (GLMMs) will be used to test the main hypotheses. Power for this study was based the primary analysis comparing BMI outcomes at T 2 between the groups, adjusting for baseline BMI values. This study provides age-appropriate lifestyle education and skill building. Peer-to-peer mentoring by local high school students and school-based tailored support strengthens sustainable behavioral change. Focusing on unique healthy-lifestyle challenges prevalent in low-resource areas such as Appalachia such as overcoming environmental, social, and psychological barriers may improve adherence to physical activity. Serving as role models, peer mentors may improve their own lifestyle behaviors, providing a dual intervention. NCT02329262 .

A Multiphase Non-Linear Mixed Effects Model: An Application to Spirometry after Lung Transplantation

PubMed Central

Rajeswaran, Jeevanantham; Blackstone, Eugene H.

2014-01-01

In medical sciences, we often encounter longitudinal temporal relationships that are non-linear in nature. The influence of risk factors may also change across longitudinal follow-up. A system of multiphase non-linear mixed effects model is presented to model temporal patterns of longitudinal continuous measurements, with temporal decomposition to identify the phases and risk factors within each phase. Application of this model is illustrated using spirometry data after lung transplantation using readily available statistical software. This application illustrates the usefulness of our flexible model when dealing with complex non-linear patterns and time varying coefficients. PMID:24919830

Influence of choice on vegetable intake in children: an in-home study.

PubMed

de Wild, Victoire W T; de Graaf, Cees; Boshuizen, Hendriek C; Jager, Gerry

2015-08-01

Children's vegetable consumption is still far below that recommended, and stimulating their intake is a challenge for caregivers. The objective of this study was to investigate whether choice-offering is an effective strategy to increase children's vegetable intake in an in-home situation. Seventy children (mean age 3.7; SD 1) randomly assigned to a choice or a no-choice condition, were exposed 12 times to six familiar target vegetables at home during dinner. In the choice group, two selected vegetables were offered each time, whereas the no-choice group only received one vegetable. Vegetable intake was measured by weighing children's plates before and after dinner. A mixed linear model with age, gender, and baseline vegetable liking as covariates was used to compare intake between the choice and the no-choice group. Mixed linear model analysis yielded estimated means for vegetable intake of 48.5 g +/- 30 in the no-choice group and 57.7 g +/- 31 for the choice group (P = 0.09). In addition, baseline vegetable liking (P <0.001) and age (P = 0.06) predicted vegetable intake to be higher when the child liked vegetables better and with older age. These findings suggest that choice-offering has some, but hardly robust, effect on increasing vegetable intake in children. Other factors such as age and liking of vegetables also mediate the effect of offering a choice. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling and Simulation of Linear and Nonlinear MEMS Scale Electromagnetic Energy Harvesters for Random Vibration Environments

PubMed Central

Sassani, Farrokh

2014-01-01

The simulation results for electromagnetic energy harvesters (EMEHs) under broad band stationary Gaussian random excitations indicate the importance of both a high transformation factor and a high mechanical quality factor to achieve favourable mean power, mean square load voltage, and output spectral density. The optimum load is different for random vibrations and for sinusoidal vibration. Reducing the total damping ratio under band-limited random excitation yields a higher mean square load voltage. Reduced bandwidth resulting from decreased mechanical damping can be compensated by increasing the electrical damping (transformation factor) leading to a higher mean square load voltage and power. Nonlinear EMEHs with a Duffing spring and with linear plus cubic damping are modeled using the method of statistical linearization. These nonlinear EMEHs exhibit approximately linear behaviour under low levels of broadband stationary Gaussian random vibration; however, at higher levels of such excitation the central (resonant) frequency of the spectral density of the output voltage shifts due to the increased nonlinear stiffness and the bandwidth broadens slightly. Nonlinear EMEHs exhibit lower maximum output voltage and central frequency of the spectral density with nonlinear damping compared to linear damping. Stronger nonlinear damping yields broader bandwidths at stable resonant frequency. PMID:24605063

Variability of particle number emissions from diesel and hybrid diesel-electric buses in real driving conditions.

PubMed

Sonntag, Darrell B; Gao, H Oliver; Holmén, Britt A

2008-08-01

A linear mixed model was developed to quantify the variability of particle number emissions from transit buses tested in real-world driving conditions. Two conventional diesel buses and two hybrid diesel-electric buses were tested throughout 2004 under different aftertreatments, fuels, drivers, and bus routes. The mixed model controlled the confounding influence of factors inherent to on-board testing. Statistical tests showed that particle number emissions varied significantly according to the after treatment, bus route, driver, bus type, and daily temperature, with only minor variability attributable to differences between fuel types. The daily setup and operation of the sampling equipment (electrical low pressure impactor) and mini-dilution system contributed to 30-84% of the total random variability of particle measurements among tests with diesel oxidation catalysts. By controlling for the sampling day variability, the model better defined the differences in particle emissions among bus routes. In contrast, the low particle number emissions measured with diesel particle filters (decreased by over 99%) did not vary according to operating conditions or bus type but did vary substantially with ambient temperature.

Design and Analysis of a Neuromemristive Reservoir Computing Architecture for Biosignal Processing

PubMed Central

Kudithipudi, Dhireesha; Saleh, Qutaiba; Merkel, Cory; Thesing, James; Wysocki, Bryant

2016-01-01

Reservoir computing (RC) is gaining traction in several signal processing domains, owing to its non-linear stateful computation, spatiotemporal encoding, and reduced training complexity over recurrent neural networks (RNNs). Previous studies have shown the effectiveness of software-based RCs for a wide spectrum of applications. A parallel body of work indicates that realizing RNN architectures using custom integrated circuits and reconfigurable hardware platforms yields significant improvements in power and latency. In this research, we propose a neuromemristive RC architecture, with doubly twisted toroidal structure, that is validated for biosignal processing applications. We exploit the device mismatch to implement the random weight distributions within the reservoir and propose mixed-signal subthreshold circuits for energy efficiency. A comprehensive analysis is performed to compare the efficiency of the neuromemristive RC architecture in both digital(reconfigurable) and subthreshold mixed-signal realizations. Both Electroencephalogram (EEG) and Electromyogram (EMG) biosignal benchmarks are used for validating the RC designs. The proposed RC architecture demonstrated an accuracy of 90 and 84% for epileptic seizure detection and EMG prosthetic finger control, respectively. PMID:26869876

An Exploratory Study of the Possible Impact of Cerebral Hemisphericity on the Performance of Select Linear, Non-Linear, and Spatial Computer Tasks.

ERIC Educational Resources Information Center

McCluskey, James J.

1997-01-01

A study of 160 undergraduate journalism students trained to design projects (stacks) using HyperCard on Macintosh computers determined that right-brain dominant subjects outperformed left-brain and mixed-brain dominant subjects, whereas left-brain dominant subjects out performed mixed-brain dominant subjects in several areas. Recommends future…

Twice random, once mixed: applying mixed models to simultaneously analyze random effects of language and participants.

PubMed

Janssen, Dirk P

2012-03-01

Psychologists, psycholinguists, and other researchers using language stimuli have been struggling for more than 30 years with the problem of how to analyze experimental data that contain two crossed random effects (items and participants). The classical analysis of variance does not apply; alternatives have been proposed but have failed to catch on, and a statistically unsatisfactory procedure of using two approximations (known as F(1) and F(2)) has become the standard. A simple and elegant solution using mixed model analysis has been available for 15 years, and recent improvements in statistical software have made mixed models analysis widely available. The aim of this article is to increase the use of mixed models by giving a concise practical introduction and by giving clear directions for undertaking the analysis in the most popular statistical packages. The article also introduces the DJMIXED: add-on package for SPSS, which makes entering the models and reporting their results as straightforward as possible.

Detection of Linear Polarization from SNR Cassiopeia A at Low Radio Frequencies

NASA Astrophysics Data System (ADS)

Raja, Wasim; Deshpande, Avinash A.

2015-03-01

We report detection of the weak but significant linear polarization from the Supernova Remnant Cas A at low radio frequencies (327 MHz) using the GMRT. The spectro-polarimetric data (16 MHz bandwidth with 256 spectral channels) was analyzed using the technique of Faraday Tomography. Ascertaining association of this weak polarization to the source is non-trivial in the presence of the remnant instrumental polarization (<1% in our case) - the expected anti-correlation ρlp,x, between the linear polarized intensity and the soft X-ray counts gets masked by the correlation between the Stokes-I dependent instrumental leakage and the X-radiation that is spatially correlated with Stokes-I, if ρ lp,x is computed naively. Hence, we compute ρ lp,x using pixels within ultra narrow bins of Stokes-I within which the instrumental leakage is expected to remain constant, and establish the anti-correlation as well as the correspondence of this correlation with the mean X-ray profile (Figure 1). Given the angular and RM-resolution in our data, the observed depolarization relative to that at higher frequencies, implies that the mixing of thermal and non-thermal plasma within the source might be occurring on spatial scales ~ 1000 AU, assuming random superposition of polarization states.

A modelling approach to assessing the timescale uncertainties in proxy series with chronological errors

NASA Astrophysics Data System (ADS)

Divine, D. V.; Godtliebsen, F.; Rue, H.

2012-01-01

The paper proposes an approach to assessment of timescale errors in proxy-based series with chronological uncertainties. The method relies on approximation of the physical process(es) forming a proxy archive by a random Gamma process. Parameters of the process are partly data-driven and partly determined from prior assumptions. For a particular case of a linear accumulation model and absolutely dated tie points an analytical solution is found suggesting the Beta-distributed probability density on age estimates along the length of a proxy archive. In a general situation of uncertainties in the ages of the tie points the proposed method employs MCMC simulations of age-depth profiles yielding empirical confidence intervals on the constructed piecewise linear best guess timescale. It is suggested that the approach can be further extended to a more general case of a time-varying expected accumulation between the tie points. The approach is illustrated by using two ice and two lake/marine sediment cores representing the typical examples of paleoproxy archives with age models based on tie points of mixed origin.

Light Scattering Study of Mixed Micelles Made from Elastin-Like Polypeptide Linear Chains and Trimers

NASA Astrophysics Data System (ADS)

Terrano, Daniel; Tsuper, Ilona; Maraschky, Adam; Holland, Nolan; Streletzky, Kiril

Temperature sensitive nanoparticles were generated from a construct (H20F) of three chains of elastin-like polypeptides (ELP) linked to a negatively charged foldon domain. This ELP system was mixed at different ratios with linear chains of ELP (H40L) which lacks the foldon domain. The mixed system is soluble at room temperature and at a transition temperature (Tt) will form swollen micelles with the hydrophobic linear chains hidden inside. This system was studied using depolarized dynamic light scattering (DDLS) and static light scattering (SLS) to determine the size, shape, and internal structure of the mixed micelles. The mixed micelle in equal parts of H20F and H40L show a constant apparent hydrodynamic radius of 40-45 nm at the concentration window from 25:25 to 60:60 uM (1:1 ratio). At a fixed 50 uM concentration of the H20F, varying H40L concentration from 5 to 80 uM resulted in a linear growth in the hydrodynamic radius from about 11 to about 62 nm, along with a 1000-fold increase in VH signal. A possible simple model explaining the growth of the swollen micelles is considered. Lastly, the VH signal can indicate elongation in the geometry of the particle or could possibly be a result from anisotropic properties from the core of the micelle. SLS was used to study the molecular weight, and the radius of gyration of the micelle to help identify the structure and morphology of mixed micelles and the tangible cause of the VH signal.

Study on the Spectral Mixing Model for Mineral Pigments Based on Derivative of Ratio Spectroscopy-Take Vermilion and Stone Yellow for Example

NASA Astrophysics Data System (ADS)

Zhao, H.; Hao, Y.; Liu, X.; Hou, M.; Zhao, X.

2018-04-01

Hyperspectral remote sensing is a completely non-invasive technology for measurement of cultural relics, and has been successfully applied in identification and analysis of pigments of Chinese historical paintings. Although the phenomenon of mixing pigments is very usual in Chinese historical paintings, the quantitative analysis of the mixing pigments in the ancient paintings is still unsolved. In this research, we took two typical mineral pigments, vermilion and stone yellow as example, made precisely mixed samples using these two kinds of pigments, and measured their spectra in the laboratory. For the mixing spectra, both fully constrained least square (FCLS) method and derivative of ratio spectroscopy (DRS) were performed. Experimental results showed that the mixing spectra of vermilion and stone yellow had strong nonlinear mixing characteristics, but at some bands linear unmixing could also achieve satisfactory results. DRS using strong linear bands can reach much higher accuracy than that of FCLS using full bands.

Food insecurity and linear growth of adolescents in Jimma Zone, Southwest Ethiopia.

PubMed

Belachew, Tefera; Lindstrom, David; Hadley, Craig; Gebremariam, Abebe; Kasahun, Wondwosen; Kolsteren, Patrick

2013-05-02

Although many studies showed that adolescent food insecurity is a pervasive phenomenon in Southwest Ethiopia, its effect on the linear growth of adolescents has not been documented so far. This study therefore aimed to longitudinally examine the association between food insecurity and linear growth among adolescents. Data for this study were obtained from a longitudinal survey of adolescents conducted in Jimma Zone, which followed an initial sample of 2084 randomly selected adolescents aged 13-17 years. We used linear mixed effects model for 1431 adolescents who were interviewed in three survey rounds one year apart to compare the effect of food insecurity on linear growth of adolescents. Overall, 15.9% of the girls and 12.2% of the boys (P=0.018) were food insecure both at baseline and on the year 1 survey, while 5.5% of the girls and 4.4% of the boys (P=0.331) were food insecure in all the three rounds of the survey. In general, a significantly higher proportion of girls (40%) experienced food insecurity at least in one of the survey rounds compared with boys (36.6%) (P=0.045).The trend of food insecurity showed a very sharp increase over the follow period from the baseline 20.5% to 48.4% on the year 1 survey, which again came down to 27.1% during the year 2 survey.In the linear mixed effects model, after adjusting for other covariates, the mean height of food insecure girls was shorter by 0.87 cm (P<0.001) compared with food secure girls at baseline. However, during the follow up period on average, the heights of food insecure girls increased by 0.38 cm more per year compared with food secure girls (P<0.066). However, the mean height of food insecure boys was not significantly different from food secure boys both at baseline and over the follow up period. Over the follow-up period, adolescents who live in rural and semi-urban areas grew significantly more per year than those who live in the urban areas both for girls (P<0.01) and for boys (P<0.01). Food insecurity is negatively associated with the linear growth of adolescents, especially on girls. High rate of childhood stunting in Ethiopia compounded with lower height of food insecure adolescents compared with their food secure peers calls for the development of direct nutrition interventions targeting adolescents to promote catch-up growth and break the intergenerational cycle of malnutrition.

Psychosocial and Clinical Outcomes of a Cognitive Behavioral Therapy for Asians and Pacific Islanders with Type 2 Diabetes: A Randomized Clinical Trial.

PubMed

Inouye, Jillian; Li, Dongmei; Davis, James; Arakaki, Richard

2015-11-01

Asian Americans and Pacific Islanders are twice as likely to be diagnosed with type 2 diabetes compared to Caucasians. The objective was to determine the effect of cognitive behavioral therapy on quality of life, general health perceptions, depressive symptoms, and glycemia in Asians and Pacific Islanders with type 2 diabetes. The design was a randomized controlled clinical trial comparing cognitive behavioral therapy to diabetes education and support for six weekly sessions. Participants were recruited from two endocrinology practices; 207 were enrolled. The cognitive behavioral therapy group was provided self-management tools which included biofeedback, breathing exercises, and stress relievers, while the diabetes education and support group included diabetes education and group discussions. Assessments of psychosocial and clinical outcomes were obtained before and after sessions and 12 months PostSession. Differences between the two groups were examined using linear mixed-effects models with linear contrasts. The cognitive behavioral therapy group had improved depressive symptom scores from PreSession to EndSession compared to the diabetes education and support group (P < .03), but the improvement did not extend to 12 months PostSession. Similar results were observed with misguided support scores in the Multidimensional Diabetes Questionnaire (P < .03) and susceptibility in health beliefs (P < .01), but no significant differences in HbA1c improvement were found between the two groups. Both interventions improved outcomes from baseline but were not sustained for 1 year.

Radon balneotherapy and physical activity for osteoporosis prevention: a randomized, placebo-controlled intervention study.

PubMed

Winklmayr, Martina; Kluge, Christian; Winklmayr, Wolfgang; Küchenhoff, Helmut; Steiner, Martina; Ritter, Markus; Hartl, Arnulf

2015-03-01

Low-dose radon hyperthermia balneo treatment (LDRnHBT) is applied as a traditional measure in the non-pharmacological treatment of rheumatic diseases in Europe. During the last decades, the main approach of LDRnHBT was focused on the treatment of musculoskeletal disorders, but scientific evidence for the biological background of LDRnHBT is weak. Recently, evidence emerged that LDRnHBT influences bone metabolism. We investigated, whether combined LDRnHBT and exercise treatment has an impact on bone metabolism and quality of life in a study population in an age group at risk for developing osteoporosis. This randomized, double-blind, placebo-controlled trial comprised guided hiking tours and hyperthermia treatment in either radon thermal water (LDRnHBT) or radon-free thermal water (PlaceboHBT). Markers of bone metabolism, quality of life and somatic complaints were evaluated. Statistics was performed by linear regression and a linear mixed model analysis. Significant changes over time were observed for most analytes investigated as well as an improvement in self-assessed health in both groups. No significant impact from the LDRnHBT could be observed. After 6 months, the LDRnHBT group showed a slightly stronger reduction of the osteoclast stimulating protein receptor activator of nuclear kB-ligand compared to the PlaceboHBT group, indicating a possible trend. A combined hyperthermia balneo and exercise treatment has significant immediate and long-term effects on regulators of bone metabolism as well as somatic complaints. LDRnHBT and placeboHBT yielded statistically equal outcomes.

Dynamic models for estimating the effect of HAART on CD4 in observational studies: Application to the Aquitaine Cohort and the Swiss HIV Cohort Study.

PubMed

Prague, Mélanie; Commenges, Daniel; Gran, Jon Michael; Ledergerber, Bruno; Young, Jim; Furrer, Hansjakob; Thiébaut, Rodolphe

2017-03-01

Highly active antiretroviral therapy (HAART) has proved efficient in increasing CD4 counts in many randomized clinical trials. Because randomized trials have some limitations (e.g., short duration, highly selected subjects), it is interesting to assess the effect of treatments using observational studies. This is challenging because treatment is started preferentially in subjects with severe conditions. This general problem had been treated using Marginal Structural Models (MSM) relying on the counterfactual formulation. Another approach to causality is based on dynamical models. We present three discrete-time dynamic models based on linear increments models (LIM): the first one based on one difference equation for CD4 counts, the second with an equilibrium point, and the third based on a system of two difference equations, which allows jointly modeling CD4 counts and viral load. We also consider continuous-time models based on ordinary differential equations with non-linear mixed effects (ODE-NLME). These mechanistic models allow incorporating biological knowledge when available, which leads to increased statistical evidence for detecting treatment effect. Because inference in ODE-NLME is numerically challenging and requires specific methods and softwares, LIM are a valuable intermediary option in terms of consistency, precision, and complexity. We compare the different approaches in simulation and in illustration on the ANRS CO3 Aquitaine Cohort and the Swiss HIV Cohort Study. © 2016, The International Biometric Society.

Anion exchange membranes composed of a poly(2,6-dimethyl-1,4-phenylene oxide) random copolymer functionalized with a bulky phosphonium cation

DOE PAGES

Liu, Ye; Zhang, Bingzi; Kinsinger, Corey L.; ...

2016-01-22

A random copolymer, tris(2,4,6-trimethoxyphenyl) phosphonium functionalized poly(2,6-dimethyl-1,4-phenylene oxide) (PPO-TPQP) was cast from three different solvents: dimethyl sulfoxide (DMSO), ethyl lactate, or a 41:59 vol% mixture of DMSO and ethyl lactate. Solvents were selected via analysis of the Hansen solubility parameters to vary the phase separation of the polymer in the films. An optimized mixture of DMSO and ethyl lactate chosen for film fabrication and this film was contrasted with films cast from the neat constituent solvents. Atomic force microscopy identified domains from nanometer to tens of nanometer sizes, while the light microscopy showed features on the order of micron. SAXSmore » revealed a cation scattering peak with a d-spacing from 7 to 15 Å. Trends in conductivity and water diffusion for the membranes vary depending on the solvent from which they are cast. The mixed solvent cast membrane shows a linear Arrhenius behavior indicating fully dissociated cationic/anionic groups, and has the highest bromide conductivity of 3 mS/cm at 95% RH, 90 °C. The ethyl lactate cast membrane shows a linear Arrhenius relation in conductivity, but a Vogel-Tamman-Fulcher behavior in its water self-diffusion. While water increases bromide dissociation, water and bromide transport in these films seems to be decoupled. Lastly, this is particularly true for the film cast from ethyl lactate.« less

Anion exchange membranes composed of a poly(2,6-dimethyl-1,4-phenylene oxide) random copolymer functionalized with a bulky phosphonium cation

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

Liu, Ye; Zhang, Bingzi; Kinsinger, Corey L.

A random copolymer, tris(2,4,6-trimethoxyphenyl) phosphonium functionalized poly(2,6-dimethyl-1,4-phenylene oxide) (PPO-TPQP) was cast from three different solvents: dimethyl sulfoxide (DMSO), ethyl lactate, or a 41:59 vol% mixture of DMSO and ethyl lactate. Solvents were selected via analysis of the Hansen solubility parameters to vary the phase separation of the polymer in the films. An optimized mixture of DMSO and ethyl lactate chosen for film fabrication and this film was contrasted with films cast from the neat constituent solvents. Atomic force microscopy identified domains from nanometer to tens of nanometer sizes, while the light microscopy showed features on the order of micron. SAXSmore » revealed a cation scattering peak with a d-spacing from 7 to 15 A. Trends in conductivity and water diffusion for the membranes vary depending on the solvent from which they are cast. The mixed solvent cast membrane shows a linear Arrhenius behavior indicating fully dissociated cationic/anionic groups, and has the highest bromide conductivity of 3 mS/cm at 95% RH, 90 degrees C. The ethyl lactate cast membrane shows a linear Arrhenius relation in conductivity, but a Vogel-Tamman-Fulcher behavior in its water self-diffusion. While water increases bromide dissociation, water and bromide transport in these films seems to be decoupled. This is particularly true for the film cast from ethyl lactate.« less

Anion exchange membranes composed of a poly(2,6-dimethyl-1,4-phenylene oxide) random copolymer functionalized with a bulky phosphonium cation

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

Liu, Ye; Zhang, Bingzi; Kinsinger, Corey L.

A random copolymer, tris(2,4,6-trimethoxyphenyl) phosphonium functionalized poly(2,6-dimethyl-1,4-phenylene oxide) (PPO-TPQP) was cast from three different solvents: dimethyl sulfoxide (DMSO), ethyl lactate, or a 41:59 vol% mixture of DMSO and ethyl lactate. Solvents were selected via analysis of the Hansen solubility parameters to vary the phase separation of the polymer in the films. An optimized mixture of DMSO and ethyl lactate chosen for film fabrication and this film was contrasted with films cast from the neat constituent solvents. Atomic force microscopy identified domains from nanometer to tens of nanometer sizes, while the light microscopy showed features on the order of micron. SAXSmore » revealed a cation scattering peak with a d-spacing from 7 to 15 Å. Trends in conductivity and water diffusion for the membranes vary depending on the solvent from which they are cast. The mixed solvent cast membrane shows a linear Arrhenius behavior indicating fully dissociated cationic/anionic groups, and has the highest bromide conductivity of 3 mS/cm at 95% RH, 90 °C. The ethyl lactate cast membrane shows a linear Arrhenius relation in conductivity, but a Vogel-Tamman-Fulcher behavior in its water self-diffusion. While water increases bromide dissociation, water and bromide transport in these films seems to be decoupled. Lastly, this is particularly true for the film cast from ethyl lactate.« less

Key-Generation Algorithms for Linear Piece In Hand Matrix Method

NASA Astrophysics Data System (ADS)

Tadaki, Kohtaro; Tsujii, Shigeo

The linear Piece In Hand (PH, for short) matrix method with random variables was proposed in our former work. It is a general prescription which can be applicable to any type of multivariate public-key cryptosystems for the purpose of enhancing their security. Actually, we showed, in an experimental manner, that the linear PH matrix method with random variables can certainly enhance the security of HFE against the Gröbner basis attack, where HFE is one of the major variants of multivariate public-key cryptosystems. In 1998 Patarin, Goubin, and Courtois introduced the plus method as a general prescription which aims to enhance the security of any given MPKC, just like the linear PH matrix method with random variables. In this paper we prove the equivalence between the plus method and the primitive linear PH matrix method, which is introduced by our previous work to explain the notion of the PH matrix method in general in an illustrative manner and not for a practical use to enhance the security of any given MPKC. Based on this equivalence, we show that the linear PH matrix method with random variables has the substantial advantage over the plus method with respect to the security enhancement. In the linear PH matrix method with random variables, the three matrices, including the PH matrix, play a central role in the secret-key and public-key. In this paper, we clarify how to generate these matrices and thus present two probabilistic polynomial-time algorithms to generate these matrices. In particular, the second one has a concise form, and is obtained as a byproduct of the proof of the equivalence between the plus method and the primitive linear PH matrix method.

Approximating a nonlinear advanced-delayed equation from acoustics

NASA Astrophysics Data System (ADS)

Teodoro, M. Filomena

2016-10-01

We approximate the solution of a particular non-linear mixed type functional differential equation from physiology, the mucosal wave model of the vocal oscillation during phonation. The mathematical equation models a superficial wave propagating through the tissues. The numerical scheme is adapted from the work presented in [1, 2, 3], using homotopy analysis method (HAM) to solve the non linear mixed type equation under study.

Incorporation of diet information derived from Bayesian stable isotope mixing models into mass-balanced marine ecosystem models: A case study from the Marennes-Oleron Estuary, France

EPA Science Inventory

We investigated the use of output from Bayesian stable isotope mixing models as constraints for a linear inverse food web model of a temperate intertidal seagrass system in the Marennes-Oléron Bay, France. Linear inverse modeling (LIM) is a technique that estimates a complete net...

Improving the Power of GWAS and Avoiding Confounding from Population Stratification with PC-Select

PubMed Central

Tucker, George; Price, Alkes L.; Berger, Bonnie

2014-01-01

Using a reduced subset of SNPs in a linear mixed model can improve power for genome-wide association studies, yet this can result in insufficient correction for population stratification. We propose a hybrid approach using principal components that does not inflate statistics in the presence of population stratification and improves power over standard linear mixed models. PMID:24788602

Distinguishability of generic quantum states

NASA Astrophysics Data System (ADS)

Puchała, Zbigniew; Pawela, Łukasz; Życzkowski, Karol

2016-06-01

Properties of random mixed states of dimension N distributed uniformly with respect to the Hilbert-Schmidt measure are investigated. We show that for large N , due to the concentration of measure, the trace distance between two random states tends to a fixed number D ˜=1 /4 +1 /π , which yields the Helstrom bound on their distinguishability. To arrive at this result, we apply free random calculus and derive the symmetrized Marchenko-Pastur distribution, which is shown to describe numerical data for the model of coupled quantum kicked tops. Asymptotic value for the root fidelity between two random states, √{F }=3/4 , can serve as a universal reference value for further theoretical and experimental studies. Analogous results for quantum relative entropy and Chernoff quantity provide other bounds on the distinguishablity of both states in a multiple measurement setup due to the quantum Sanov theorem. We study also mean entropy of coherence of random pure and mixed states and entanglement of a generic mixed state of a bipartite system.

Mixing Methods in Randomized Controlled Trials (RCTs): Validation, Contextualization, Triangulation, and Control

ERIC Educational Resources Information Center

Spillane, James P.; Pareja, Amber Stitziel; Dorner, Lisa; Barnes, Carol; May, Henry; Huff, Jason; Camburn, Eric

2010-01-01

In this paper we described how we mixed research approaches in a Randomized Control Trial (RCT) of a school principal professional development program. Using examples from our study we illustrate how combining qualitative and quantitative data can address some key challenges from validating instruments and measures of mediator variables to…

A unified procedure for meta-analytic evaluation of surrogate end points in randomized clinical trials

PubMed Central

Dai, James Y.; Hughes, James P.

2012-01-01

The meta-analytic approach to evaluating surrogate end points assesses the predictiveness of treatment effect on the surrogate toward treatment effect on the clinical end point based on multiple clinical trials. Definition and estimation of the correlation of treatment effects were developed in linear mixed models and later extended to binary or failure time outcomes on a case-by-case basis. In a general regression setting that covers nonnormal outcomes, we discuss in this paper several metrics that are useful in the meta-analytic evaluation of surrogacy. We propose a unified 3-step procedure to assess these metrics in settings with binary end points, time-to-event outcomes, or repeated measures. First, the joint distribution of estimated treatment effects is ascertained by an estimating equation approach; second, the restricted maximum likelihood method is used to estimate the means and the variance components of the random treatment effects; finally, confidence intervals are constructed by a parametric bootstrap procedure. The proposed method is evaluated by simulations and applications to 2 clinical trials. PMID:22394448

Gene–Environment Correlation: Difficulties and a Natural Experiment–Based Strategy

PubMed Central

Li, Jiang; Liu, Hexuan; Guo, Guang

2013-01-01

Objectives. We explored how gene–environment correlations can result in endogenous models, how natural experiments can protect against this threat, and if unbiased estimates from natural experiments are generalizable to other contexts. Methods. We compared a natural experiment, the College Roommate Study, which measured genes and behaviors of college students and their randomly assigned roommates in a southern public university, with observational data from the National Longitudinal Study of Adolescent Health in 2008. We predicted exposure to exercising peers using genetic markers and estimated environmental effects on alcohol consumption. A mixed-linear model estimated an alcohol consumption variance that was attributable to genetic markers and across peer environments. Results. Peer exercise environment was associated with respondent genotype in observational data, but not in the natural experiment. The effects of peer drinking and presence of a general gene–environment interaction were similar between data sets. Conclusions. Natural experiments, like random roommate assignment, could protect against potential bias introduced by gene–environment correlations. When combined with representative observational data, unbiased and generalizable causal effects could be estimated. PMID:23927502

Mindfulness-oriented recovery enhancement for internet gaming disorder in U.S. adults: A stage I randomized controlled trial.

PubMed

Li, Wen; Garland, Eric L; McGovern, Patricia; O'Brien, Jennifer E; Tronnier, Christine; Howard, Matthew O

2017-06-01

Empirical studies have identified increasing rates of Internet gaming disorder (IGD) and associated adverse consequences. However, very few evidence-based interventions have been evaluated for IGD or problematic video gaming behaviors. This study evaluated Mindfulness-Oriented Recovery Enhancement (MORE) as a treatment for IGD. Thirty adults (Mage = 25.0, SD = 5.4) with IGD or problematic video gaming behaviors were randomized to 8 weeks of group-based MORE or 8 weeks of a support group (SG) control condition. Outcome measures were administered at pre- and posttreatment and 3-months following treatment completion using self-report instruments. Linear mixed models were used for outcome analyses. MORE participants had significantly greater reductions in the number of Diagnostic and Statistical Manual of Mental Disorders-5 IGD criteria they met, craving for video gaming, and maladaptive cognitions associated with gaming than SG participants, and therapeutic benefits were maintained at 3-month follow-up. MORE is a promising treatment approach for IGD. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem

PubMed Central

Molla-Alizadeh-Zavardehi, S.; Tavakkoli-Moghaddam, R.; Lotfi, F. Hosseinzadeh

2014-01-01

This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms. PMID:24883359

A dynamic spatio-temporal model for spatial data

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin; Walsh, Daniel P.

2017-01-01

Analyzing spatial data often requires modeling dependencies created by a dynamic spatio-temporal data generating process. In many applications, a generalized linear mixed model (GLMM) is used with a random effect to account for spatial dependence and to provide optimal spatial predictions. Location-specific covariates are often included as fixed effects in a GLMM and may be collinear with the spatial random effect, which can negatively affect inference. We propose a dynamic approach to account for spatial dependence that incorporates scientific knowledge of the spatio-temporal data generating process. Our approach relies on a dynamic spatio-temporal model that explicitly incorporates location-specific covariates. We illustrate our approach with a spatially varying ecological diffusion model implemented using a computationally efficient homogenization technique. We apply our model to understand individual-level and location-specific risk factors associated with chronic wasting disease in white-tailed deer from Wisconsin, USA and estimate the location the disease was first introduced. We compare our approach to several existing methods that are commonly used in spatial statistics. Our spatio-temporal approach resulted in a higher predictive accuracy when compared to methods based on optimal spatial prediction, obviated confounding among the spatially indexed covariates and the spatial random effect, and provided additional information that will be important for containing disease outbreaks.

Multivariate generalized hidden Markov regression models with random covariates: Physical exercise in an elderly population.

PubMed

Punzo, Antonio; Ingrassia, Salvatore; Maruotti, Antonello

2018-04-22

A time-varying latent variable model is proposed to jointly analyze multivariate mixed-support longitudinal data. The proposal can be viewed as an extension of hidden Markov regression models with fixed covariates (HMRMFCs), which is the state of the art for modelling longitudinal data, with a special focus on the underlying clustering structure. HMRMFCs are inadequate for applications in which a clustering structure can be identified in the distribution of the covariates, as the clustering is independent from the covariates distribution. Here, hidden Markov regression models with random covariates are introduced by explicitly specifying state-specific distributions for the covariates, with the aim of improving the recovering of the clusters in the data with respect to a fixed covariates paradigm. The hidden Markov regression models with random covariates class is defined focusing on the exponential family, in a generalized linear model framework. Model identifiability conditions are sketched, an expectation-maximization algorithm is outlined for parameter estimation, and various implementation and operational issues are discussed. Properties of the estimators of the regression coefficients, as well as of the hidden path parameters, are evaluated through simulation experiments and compared with those of HMRMFCs. The method is applied to physical activity data. Copyright © 2018 John Wiley & Sons, Ltd.

The carry-over effects of school gardens on fruit and vegetable availability at home: A randomized controlled trial with low-income elementary schools.

PubMed

Wells, Nancy M; Meyers, Beth M; Todd, Lauren E; Henderson, Charles R; Barale, Karen; Gaolach, Brad; Ferenz, Gretchen; Aitken, Martha; Tse, Caroline C; Pattison, Karen Ostlie; Hendrix, Laura; Carson, Janet B; Taylor, Cayla; Franz, Nancy K

2018-07-01

This group-randomized controlled trial examines the effects of a school garden intervention on availability of fruits and vegetables (FV) in elementary school children's homes. Within each region, low income U.S. schools in Arkansas, Iowa, New York, and Washington State were randomly assigned to intervention group (n = 24) or waitlist control group (n = 22). Children were in grades 2, 4, and 5 at baseline (n = 2768). The garden intervention consisted of both raised-bed garden kits and a series of grade-appropriate lessons. FV availability at home was measured with a modified version of the GEMS FJV Availability Questionnaire. The instrument was administered at baseline (Fall 2011) and throughout the intervention (Spring 2012, Fall 2012, Spring 2013). Analyses were completed using general linear mixed models. The garden intervention led to an overall increase in availability of low-fat vegetables at home. Among younger children (2nd grade at baseline), the garden intervention led to greater home availability of vegetables, especially, low-fat vegetables. Moreover, for the younger group, garden intervention fidelity (GIF) or robustness predicted home availability of fruit, vegetables, and low-fat vegetables. School gardens have potential to affect FV availability in the home environment. Copyright © 2018 Elsevier Inc. All rights reserved.

The PLUNGE randomized controlled trial: evaluation of a games-based physical activity professional learning program in primary school physical education.

PubMed

Miller, Andrew; Christensen, Erin M; Eather, Narelle; Sproule, John; Annis-Brown, Laura; Lubans, David Revalds

2015-05-01

To evaluate the efficacy of the Professional Learning for Understanding Games Education (PLUNGE) program on fundamental movement skills (FMS), in-class physical activity and perceived sporting competence. A cluster-randomized controlled trial involving one year six class each from seven primary schools (n=168; mean age=11.2 years, SD=1.0) in the Hunter Region, NSW, Australia. In September (2013) participants were randomized by school into the PLUNGE intervention (n=97 students) or the 7-week wait-list control (n=71) condition. PLUNGE involved the use of Game Centered curriculum delivered via an in-class teacher mentoring program. Students were assessed at baseline and 8-week follow-up for three object control FMS (Test of Gross Motor Development 2), in-class physical activity (pedometer steps/min) and perceived sporting competence (Self-perception Profile for Children). Linear mixed models revealed significant group-by-time intervention effects (all p<0.05) for object control competency (effect size: d=0.9), and in-class pedometer steps/min (d=1.0). No significant intervention effects (p>0.05) were observed for perceived sporting competence. The PLUNGE intervention simultaneously improved object control FMS proficiency and in-class PA in stage three students. Copyright © 2015 Elsevier Inc. All rights reserved.

Reversible geling co-polymer and method of making

DOEpatents

Gutowska, Anna

2005-12-27

The present invention is a thereapeutic agent carrier having a thermally reversible gel or geling copolymer that is a linear random copolymer of an [meth-]acrylamide derivative and a hydrophilic comonomer, wherein the linear random copolymer is in the form of a plurality of linear chains having a plurality of molecular weights greater than or equal to a minimum geling molecular weight cutoff and a therapeutic agent.

Application of laser speckle to randomized numerical linear algebra

NASA Astrophysics Data System (ADS)

Valley, George C.; Shaw, Thomas J.; Stapleton, Andrew D.; Scofield, Adam C.; Sefler, George A.; Johannson, Leif

2018-02-01

We propose and simulate integrated optical devices for accelerating numerical linear algebra (NLA) calculations. Data is modulated on chirped optical pulses and these propagate through a multimode waveguide where speckle provides the random projections needed for NLA dimensionality reduction.

Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex.

PubMed

Lindsay, Grace W; Rigotti, Mattia; Warden, Melissa R; Miller, Earl K; Fusi, Stefano

2017-11-08

Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear "mixed" selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli-and in particular, to combinations of stimuli ("mixed selectivity")-is a topic of interest. Even though models with random feedforward connectivity are capable of creating computationally relevant mixed selectivity, such a model does not match the levels of mixed selectivity seen in the data analyzed in this study. Adding simple Hebbian learning to the model increases mixed selectivity to the correct level and makes the model match the data on several other relevant measures. This study thus offers predictions on how mixed selectivity and other properties evolve with training. Copyright © 2017 the authors 0270-6474/17/3711021-16$15.00/0.

High linearity current communicating passive mixer employing a simple resistor bias

NASA Astrophysics Data System (ADS)

Rongjiang, Liu; Guiliang, Guo; Yuepeng, Yan

2013-03-01

A high linearity current communicating passive mixer including the mixing cell and transimpedance amplifier (TIA) is introduced. It employs the resistor in the TIA to reduce the source voltage and the gate voltage of the mixing cell. The optimum linearity and the maximum symmetric switching operation are obtained at the same time. The mixer is implemented in a 0.25 μm CMOS process. The test shows that it achieves an input third-order intercept point of 13.32 dBm, conversion gain of 5.52 dB, and a single sideband noise figure of 20 dB.

Modelling lactation curve for milk fat to protein ratio in Iranian buffaloes (Bubalus bubalis) using non-linear mixed models.

PubMed

Hossein-Zadeh, Navid Ghavi

2016-08-01

The aim of this study was to compare seven non-linear mathematical models (Brody, Wood, Dhanoa, Sikka, Nelder, Rook and Dijkstra) to examine their efficiency in describing the lactation curves for milk fat to protein ratio (FPR) in Iranian buffaloes. Data were 43 818 test-day records for FPR from the first three lactations of Iranian buffaloes which were collected on 523 dairy herds in the period from 1996 to 2012 by the Animal Breeding Center of Iran. Each model was fitted to monthly FPR records of buffaloes using the non-linear mixed model procedure (PROC NLMIXED) in SAS and the parameters were estimated. The models were tested for goodness of fit using Akaike's information criterion (AIC), Bayesian information criterion (BIC) and log maximum likelihood (-2 Log L). The Nelder and Sikka mixed models provided the best fit of lactation curve for FPR in the first and second lactations of Iranian buffaloes, respectively. However, Wood, Dhanoa and Sikka mixed models provided the best fit of lactation curve for FPR in the third parity buffaloes. Evaluation of first, second and third lactation features showed that all models, except for Dijkstra model in the third lactation, under-predicted test time at which daily FPR was minimum. On the other hand, minimum FPR was over-predicted by all equations. Evaluation of the different models used in this study indicated that non-linear mixed models were sufficient for fitting test-day FPR records of Iranian buffaloes.

Enhancing Security of Double Random Phase Encoding Based on Random S-Box

NASA Astrophysics Data System (ADS)

Girija, R.; Singh, Hukum

2018-06-01

In this paper, we propose a novel asymmetric cryptosystem for double random phase encoding (DRPE) using random S-Box. While utilising S-Box separately is not reliable and DRPE does not support non-linearity, so, our system unites the effectiveness of S-Box with an asymmetric system of DRPE (through Fourier transform). The uniqueness of proposed cryptosystem lies on employing high sensitivity dynamic S-Box for our DRPE system. The randomness and scalability achieved due to applied technique is an additional feature of the proposed solution. The firmness of random S-Box is investigated in terms of performance parameters such as non-linearity, strict avalanche criterion, bit independence criterion, linear and differential approximation probabilities etc. S-Boxes convey nonlinearity to cryptosystems which is a significant parameter and very essential for DRPE. The strength of proposed cryptosystem has been analysed using various parameters such as MSE, PSNR, correlation coefficient analysis, noise analysis, SVD analysis, etc. Experimental results are conferred in detail to exhibit proposed cryptosystem is highly secure.

Longitudinal mathematics development of students with learning disabilities and students without disabilities: a comparison of linear, quadratic, and piecewise linear mixed effects models.

PubMed

Kohli, Nidhi; Sullivan, Amanda L; Sadeh, Shanna; Zopluoglu, Cengiz

2015-04-01

Effective instructional planning and intervening rely heavily on accurate understanding of students' growth, but relatively few researchers have examined mathematics achievement trajectories, particularly for students with special needs. We applied linear, quadratic, and piecewise linear mixed-effects models to identify the best-fitting model for mathematics development over elementary and middle school and to ascertain differences in growth trajectories of children with learning disabilities relative to their typically developing peers. The analytic sample of 2150 students was drawn from the Early Childhood Longitudinal Study - Kindergarten Cohort, a nationally representative sample of United States children who entered kindergarten in 1998. We first modeled students' mathematics growth via multiple mixed-effects models to determine the best fitting model of 9-year growth and then compared the trajectories of students with and without learning disabilities. Results indicate that the piecewise linear mixed-effects model captured best the functional form of students' mathematics trajectories. In addition, there were substantial achievement gaps between students with learning disabilities and students with no disabilities, and their trajectories differed such that students without disabilities progressed at a higher rate than their peers who had learning disabilities. The results underscore the need for further research to understand how to appropriately model students' mathematics trajectories and the need for attention to mathematics achievement gaps in policy. Copyright © 2015 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Mixed reality temporal bone surgical dissector: mechanical design.

PubMed

Hochman, Jordan Brent; Sepehri, Nariman; Rampersad, Vivek; Kraut, Jay; Khazraee, Milad; Pisa, Justyn; Unger, Bertram

2014-08-08

The Development of a Novel Mixed Reality (MR) Simulation. An evolving training environment emphasizes the importance of simulation. Current haptic temporal bone simulators have difficulty representing realistic contact forces and while 3D printed models convincingly represent vibrational properties of bone, they cannot reproduce soft tissue. This paper introduces a mixed reality model, where the effective elements of both simulations are combined; haptic rendering of soft tissue directly interacts with a printed bone model. This paper addresses one aspect in a series of challenges, specifically the mechanical merger of a haptic device with an otic drill. This further necessitates gravity cancelation of the work assembly gripper mechanism. In this system, the haptic end-effector is replaced by a high-speed drill and the virtual contact forces need to be repositioned to the drill tip from the mid wand. Previous publications detail generation of both the requisite printed and haptic simulations. Custom software was developed to reposition the haptic interaction point to the drill tip. A custom fitting, to hold the otic drill, was developed and its weight was offset using the haptic device. The robustness of the system to disturbances and its stable performance during drilling were tested. The experiments were performed on a mixed reality model consisting of two drillable rapid-prototyped layers separated by a free-space. Within the free-space, a linear virtual force model is applied to simulate drill contact with soft tissue. Testing illustrated the effectiveness of gravity cancellation. Additionally, the system exhibited excellent performance given random inputs and during the drill's passage between real and virtual components of the model. No issues with registration at model boundaries were encountered. These tests provide a proof of concept for the initial stages in the development of a novel mixed-reality temporal bone simulator.

Extraction of linear features on SAR imagery

NASA Astrophysics Data System (ADS)

Liu, Junyi; Li, Deren; Mei, Xin

2006-10-01

Linear features are usually extracted from SAR imagery by a few edge detectors derived from the contrast ratio edge detector with a constant probability of false alarm. On the other hand, the Hough Transform is an elegant way of extracting global features like curve segments from binary edge images. Randomized Hough Transform can reduce the computation time and memory usage of the HT drastically. While Randomized Hough Transform will bring about a great deal of cells invalid during the randomized sample. In this paper, we propose a new approach to extract linear features on SAR imagery, which is an almost automatic algorithm based on edge detection and Randomized Hough Transform. The presented improved method makes full use of the directional information of each edge candidate points so as to solve invalid cumulate problems. Applied result is in good agreement with the theoretical study, and the main linear features on SAR imagery have been extracted automatically. The method saves storage space and computational time, which shows its effectiveness and applicability.

Predicting the multi-domain progression of Parkinson's disease: a Bayesian multivariate generalized linear mixed-effect model.

PubMed

Wang, Ming; Li, Zheng; Lee, Eun Young; Lewis, Mechelle M; Zhang, Lijun; Sterling, Nicholas W; Wagner, Daymond; Eslinger, Paul; Du, Guangwei; Huang, Xuemei

2017-09-25

It is challenging for current statistical models to predict clinical progression of Parkinson's disease (PD) because of the involvement of multi-domains and longitudinal data. Past univariate longitudinal or multivariate analyses from cross-sectional trials have limited power to predict individual outcomes or a single moment. The multivariate generalized linear mixed-effect model (GLMM) under the Bayesian framework was proposed to study multi-domain longitudinal outcomes obtained at baseline, 18-, and 36-month. The outcomes included motor, non-motor, and postural instability scores from the MDS-UPDRS, and demographic and standardized clinical data were utilized as covariates. The dynamic prediction was performed for both internal and external subjects using the samples from the posterior distributions of the parameter estimates and random effects, and also the predictive accuracy was evaluated based on the root of mean square error (RMSE), absolute bias (AB) and the area under the receiver operating characteristic (ROC) curve. First, our prediction model identified clinical data that were differentially associated with motor, non-motor, and postural stability scores. Second, the predictive accuracy of our model for the training data was assessed, and improved prediction was gained in particularly for non-motor (RMSE and AB: 2.89 and 2.20) compared to univariate analysis (RMSE and AB: 3.04 and 2.35). Third, the individual-level predictions of longitudinal trajectories for the testing data were performed, with ~80% observed values falling within the 95% credible intervals. Multivariate general mixed models hold promise to predict clinical progression of individual outcomes in PD. The data was obtained from Dr. Xuemei Huang's NIH grant R01 NS060722 , part of NINDS PD Biomarker Program (PDBP). All data was entered within 24 h of collection to the Data Management Repository (DMR), which is publically available ( https://pdbp.ninds.nih.gov/data-management ).

Mentalization-based therapy for parents in entrenched conflict: A random allocation feasibility study.

PubMed

Hertzmann, Leezah; Target, Mary; Hewison, David; Casey, Polly; Fearon, Pasco; Lassri, Dana

2016-12-01

To explore the effectiveness of a mentalization-based therapeutic intervention specifically developed for parents in entrenched conflict over their children. To the best of our knowledge, this is the first randomized controlled intervention study in the United Kingdom to work with both parents postseparation, and the first to focus on mentalization in this situation. Using a mixed-methods study design, 30 parents were randomly allocated to either mentalization-based therapy for parental conflict-Parenting Together, or the Parents' Group, a psycho-educational intervention for separated parents based on elements of the Separated Parents Information Program-part of the U.K. Family Justice System and approximating to treatment as usual. Given the challenges of recruiting parents in these difficult circumstances, the sample size was small and permitted only the detection of large differences between conditions. The data, involving repeated measures of related individuals, was explored statistically, using hierarchical linear modeling, and qualitatively. Significant findings were reported on the main predicted outcomes, with clinically important trends on other measures. Qualitative findings further contributed to the understanding of parents' subjective experience, pre- and posttreatment. Findings indicate that a larger scale randomized controlled trial would be worthwhile. These encouraging findings shed light on the dynamics maintaining these high-conflict situations known to be damaging to children. We established that both forms of intervention were acceptable to most parents, and we were able to operate a random allocation design with extensive quantitative and qualitative assessments of the kind that would make a larger-scale trial feasible and productive. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Effectiveness of a virtual intervention for primary healthcare professionals aimed at improving attitudes towards the empowerment of patients with chronic diseases: study protocol for a cluster randomized controlled trial (e-MPODERA project).

PubMed

González-González, Ana Isabel; Orrego, Carola; Perestelo-Perez, Lilisbeth; Bermejo-Caja, Carlos Jesús; Mora, Nuria; Koatz, Débora; Ballester, Marta; Del Pino, Tasmania; Pérez-Ramos, Jeannet; Toledo-Chavarri, Ana; Robles, Noemí; Pérez-Rivas, Francisco Javier; Ramírez-Puerta, Ana Belén; Canellas-Criado, Yolanda; Del Rey-Granado, Yolanda; Muñoz-Balsa, Marcos José; Becerril-Rojas, Beatriz; Rodríguez-Morales, David; Sánchez-Perruca, Luis; Vázquez, José Ramón; Aguirre, Armando

2017-10-30

Communities of practice are based on the idea that learning involves a group of people exchanging experiences and knowledge. The e-MPODERA project aims to assess the effectiveness of a virtual community of practice aimed at improving primary healthcare professional attitudes to the empowerment of patients with chronic diseases. This paper describes the protocol for a cluster randomized controlled trial. We will randomly assign 18 primary-care practices per participating region of Spain (Catalonia, Madrid and Canary Islands) to a virtual community of practice or to usual training. The primary-care practice will be the randomization unit and the primary healthcare professional will be the unit of analysis. We will need a sample of 270 primary healthcare professionals (general practitioners and nurses) and 1382 patients. We will perform randomization after professionals and patients are selected. We will ask the intervention group to participate for 12 months in a virtual community of practice based on a web 2.0 platform. We will measure the primary outcome using the Patient-Provider Orientation Scale questionnaire administered at baseline and after 12 months. Secondary outcomes will be the sociodemographic characteristics of health professionals, sociodemographic and clinical characteristics of patients, the Patient Activation Measure questionnaire for patient activation and outcomes regarding use of the virtual community of practice. We will calculate a linear mixed-effects regression to estimate the effect of participating in the virtual community of practice. This cluster randomized controlled trial will show whether a virtual intervention for primary healthcare professionals improves attitudes to the empowerment of patients with chronic diseases. ClicalTrials.gov, NCT02757781 . Registered on 25 April 2016. Protocol Version. PI15.01 22 January 2016.

A Markov model for blind image separation by a mean-field EM algorithm.

PubMed

Tonazzini, Anna; Bedini, Luigi; Salerno, Emanuele

2006-02-01

This paper deals with blind separation of images from noisy linear mixtures with unknown coefficients, formulated as a Bayesian estimation problem. This is a flexible framework, where any kind of prior knowledge about the source images and the mixing matrix can be accounted for. In particular, we describe local correlation within the individual images through the use of Markov random field (MRF) image models. These are naturally suited to express the joint pdf of the sources in a factorized form, so that the statistical independence requirements of most independent component analysis approaches to blind source separation are retained. Our model also includes edge variables to preserve intensity discontinuities. MRF models have been proved to be very efficient in many visual reconstruction problems, such as blind image restoration, and allow separation and edge detection to be performed simultaneously. We propose an expectation-maximization algorithm with the mean field approximation to derive a procedure for estimating the mixing matrix, the sources, and their edge maps. We tested this procedure on both synthetic and real images, in the fully blind case (i.e., no prior information on mixing is exploited) and found that a source model accounting for local autocorrelation is able to increase robustness against noise, even space variant. Furthermore, when the model closely fits the source characteristics, independence is no longer a strict requirement, and cross-correlated sources can be separated, as well.

Accurate initial conditions in mixed dark matter-baryon simulations

NASA Astrophysics Data System (ADS)

Valkenburg, Wessel; Villaescusa-Navarro, Francisco

2017-06-01

We quantify the error in the results of mixed baryon-dark-matter hydrodynamic simulations, stemming from outdated approximations for the generation of initial conditions. The error at redshift 0 in contemporary large simulations is of the order of few to 10 per cent in the power spectra of baryons and dark matter, and their combined total-matter power spectrum. After describing how to properly assign initial displacements and peculiar velocities to multiple species, we review several approximations: (1) using the total-matter power spectrum to compute displacements and peculiar velocities of both fluids, (2) scaling the linear redshift-zero power spectrum back to the initial power spectrum using the Newtonian growth factor ignoring homogeneous radiation, (3) using a mix of general-relativistic gauges so as to approximate Newtonian gravity, namely longitudinal-gauge velocities with synchronous-gauge densities and (4) ignoring the phase-difference in the Fourier modes for the offset baryon grid, relative to the dark-matter grid. Three of these approximations do not take into account that dark matter and baryons experience a scale-dependent growth after photon decoupling, which results in directions of velocity that are not the same as their direction of displacement. We compare the outcome of hydrodynamic simulations with these four approximations to our reference simulation, all setup with the same random seed and simulated using gadget-III.

An adaptive PID like controller using mix locally recurrent neural network for robotic manipulator with variable payload.

PubMed

Sharma, Richa; Kumar, Vikas; Gaur, Prerna; Mittal, A P

2016-05-01

Being complex, non-linear and coupled system, the robotic manipulator cannot be effectively controlled using classical proportional-integral-derivative (PID) controller. To enhance the effectiveness of the conventional PID controller for the nonlinear and uncertain systems, gains of the PID controller should be conservatively tuned and should adapt to the process parameter variations. In this work, a mix locally recurrent neural network (MLRNN) architecture is investigated to mimic a conventional PID controller which consists of at most three hidden nodes which act as proportional, integral and derivative node. The gains of the mix locally recurrent neural network based PID (MLRNNPID) controller scheme are initialized with a newly developed cuckoo search algorithm (CSA) based optimization method rather than assuming randomly. A sequential learning based least square algorithm is then investigated for the on-line adaptation of the gains of MLRNNPID controller. The performance of the proposed controller scheme is tested against the plant parameters uncertainties and external disturbances for both links of the two link robotic manipulator with variable payload (TL-RMWVP). The stability of the proposed controller is analyzed using Lyapunov stability criteria. A performance comparison is carried out among MLRNNPID controller, CSA optimized NNPID (OPTNNPID) controller and CSA optimized conventional PID (OPTPID) controller in order to establish the effectiveness of the MLRNNPID controller. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A predictive model for early mortality after surgical treatment of heart valve or prosthesis infective endocarditis. The EndoSCORE.

PubMed

Di Mauro, Michele; Dato, Guglielmo Mario Actis; Barili, Fabio; Gelsomino, Sandro; Santè, Pasquale; Corte, Alessandro Della; Carrozza, Antonio; Ratta, Ester Della; Cugola, Diego; Galletti, Lorenzo; Devotini, Roger; Casabona, Riccardo; Santini, Francesco; Salsano, Antonio; Scrofani, Roberto; Antona, Carlo; Botta, Luca; Russo, Claudio; Mancuso, Samuel; Rinaldi, Mauro; De Vincentiis, Carlo; Biondi, Andrea; Beghi, Cesare; Cappabianca, Giangiuseppe; Tarzia, Vincenzo; Gerosa, Gino; De Bonis, Michele; Pozzoli, Alberto; Nicolini, Francesco; Benassi, Filippo; Rosato, Francesco; Grasso, Elena; Livi, Ugolino; Sponga, Sandro; Pacini, Davide; Di Bartolomeo, Roberto; De Martino, Andrea; Bortolotti, Uberto; Onorati, Francesco; Faggian, Giuseppe; Lorusso, Roberto; Vizzardi, Enrico; Di Giammarco, Gabriele; Marinelli, Daniele; Villa, Emmanuel; Troise, Giovanni; Picichè, Marco; Musumeci, Francesco; Paparella, Domenico; Margari, Vito; Tritto, Francesco; Damiani, Girolamo; Scrascia, Giuseppe; Zaccaria, Salvatore; Renzulli, Attilio; Serraino, Giuseppe; Mariscalco, Giovanni; Maselli, Daniele; Foschi, Massimiliano; Parolari, Alessandro; Nappi, Giannantonio

2017-08-15

The aim of this large retrospective study was to provide a logistic risk model along an additive score to predict early mortality after surgical treatment of patients with heart valve or prosthesis infective endocarditis (IE). From 2000 to 2015, 2715 patients with native valve endocarditis (NVE) or prosthesis valve endocarditis (PVE) were operated on in 26 Italian Cardiac Surgery Centers. The relationship between early mortality and covariates was evaluated with logistic mixed effect models. Fixed effects are parameters associated with the entire population or with certain repeatable levels of experimental factors, while random effects are associated with individual experimental units (centers). Early mortality was 11.0% (298/2715); At mixed effect logistic regression the following variables were found associated with early mortality: age class, female gender, LVEF, preoperative shock, COPD, creatinine value above 2mg/dl, presence of abscess, number of treated valve/prosthesis (with respect to one treated valve/prosthesis) and the isolation of Staphylococcus aureus, Fungus spp., Pseudomonas Aeruginosa and other micro-organisms, while Streptococcus spp., Enterococcus spp. and other Staphylococci did not affect early mortality, as well as no micro-organisms isolation. LVEF was found linearly associated with outcomes while non-linear association between mortality and age was tested and the best model was found with a categorization into four classes (AUC=0.851). The following study provides a logistic risk model to predict early mortality in patients with heart valve or prosthesis infective endocarditis undergoing surgical treatment, called "The EndoSCORE". Copyright © 2017. Published by Elsevier B.V.

Group-Level EEG-Processing Pipeline for Flexible Single Trial-Based Analyses Including Linear Mixed Models.

PubMed

Frömer, Romy; Maier, Martin; Abdel Rahman, Rasha

2018-01-01

Here we present an application of an EEG processing pipeline customizing EEGLAB and FieldTrip functions, specifically optimized to flexibly analyze EEG data based on single trial information. The key component of our approach is to create a comprehensive 3-D EEG data structure including all trials and all participants maintaining the original order of recording. This allows straightforward access to subsets of the data based on any information available in a behavioral data structure matched with the EEG data (experimental conditions, but also performance indicators, such accuracy or RTs of single trials). In the present study we exploit this structure to compute linear mixed models (LMMs, using lmer in R) including random intercepts and slopes for items. This information can easily be read out from the matched behavioral data, whereas it might not be accessible in traditional ERP approaches without substantial effort. We further provide easily adaptable scripts for performing cluster-based permutation tests (as implemented in FieldTrip), as a more robust alternative to traditional omnibus ANOVAs. Our approach is particularly advantageous for data with parametric within-subject covariates (e.g., performance) and/or multiple complex stimuli (such as words, faces or objects) that vary in features affecting cognitive processes and ERPs (such as word frequency, salience or familiarity), which are sometimes hard to control experimentally or might themselves constitute variables of interest. The present dataset was recorded from 40 participants who performed a visual search task on previously unfamiliar objects, presented either visually intact or blurred. MATLAB as well as R scripts are provided that can be adapted to different datasets.

Evaluation of goal kicking performance in international rugby union matches.

PubMed

Quarrie, Kenneth L; Hopkins, Will G

2015-03-01

Goal kicking is an important element in rugby but has been the subject of minimal research. To develop and apply a method to describe the on-field pattern of goal-kicking and rank the goal kicking performance of players in international rugby union matches. Longitudinal observational study. A generalized linear mixed model was used to analyze goal-kicking performance in a sample of 582 international rugby matches played from 2002 to 2011. The model adjusted for kick distance, kick angle, a rating of the importance of each kick, and venue-related conditions. Overall, 72% of the 6769 kick attempts were successful. Forty-five percent of points scored during the matches resulted from goal kicks, and in 5.7% of the matches the result of the match hinged on the outcome of a kick attempt. There was an extremely large decrease in success with increasing distance (odds ratio for two SD distance 0.06, 90% confidence interval 0.05-0.07) and a small decrease with increasingly acute angle away from the mid-line of the goal posts (odds ratio for 2 SD angle, 0.44, 0.39-0.49). Differences between players were typically small (odds ratio for 2 between-player SD 0.53, 0.45-0.65). The generalized linear mixed model with its random-effect solutions provides a tool for ranking the performance of goal kickers in rugby. This modelling approach could be applied to other performance indicators in rugby and in other sports in which discrete outcomes are measured repeatedly on players or teams. Copyright © 2015. Published by Elsevier Ltd.

Linear signal noise summer accurately determines and controls S/N ratio

NASA Technical Reports Server (NTRS)

Sundry, J. L.

1966-01-01

Linear signal noise summer precisely controls the relative power levels of signal and noise, and mixes them linearly in accurately known ratios. The S/N ratio accuracy and stability are greatly improved by this technique and are attained simultaneously.

Individual tree diameter increment model for managed even-aged stands of ponderosa pine throughout the western United States using a multilevel linear mixed effects model

Treesearch

Fabian C.C. Uzoh; William W. Oliver

2008-01-01

A diameter increment model is developed and evaluated for individual trees of ponderosa pine throughout the species range in the United States using a multilevel linear mixed model. Stochastic variability is broken down among period, locale, plot, tree and within-tree components. Covariates acting at tree and stand level, as breast height diameter, density, site index...

The effect of dropout on the efficiency of D-optimal designs of linear mixed models.

PubMed

Ortega-Azurduy, S A; Tan, F E S; Berger, M P F

2008-06-30

Dropout is often encountered in longitudinal data. Optimal designs will usually not remain optimal in the presence of dropout. In this paper, we study D-optimal designs for linear mixed models where dropout is encountered. Moreover, we estimate the efficiency loss in cases where a D-optimal design for complete data is chosen instead of that for data with dropout. Two types of monotonically decreasing response probability functions are investigated to describe dropout. Our results show that the location of D-optimal design points for the dropout case will shift with respect to that for the complete and uncorrelated data case. Owing to this shift, the information collected at the D-optimal design points for the complete data case does not correspond to the smallest variance. We show that the size of the displacement of the time points depends on the linear mixed model and that the efficiency loss is moderate.

Theoretical studies of solar oscillations

NASA Technical Reports Server (NTRS)

Goldreich, P.

1980-01-01

Possible sources for the excitation of the solar 5 minute oscillations were investigated and a linear non-adiabatic stability code was applied to a preliminary study of the solar g-modes with periods near 160 minutes. Although no definitive conclusions concerning the excitation of these modes were reached, the excitation of the 5 minute oscillations by turbulent stresses in the convection zone remains a viable possibility. Theoretical calculations do not offer much support for the identification of the 160 minute global solar oscillation (reported by several independent observers) as a solar g-mode. A significant advance was made in attempting to reconcile mixing-length theory with the results of the calculations of linearly unstable normal modes. Calculations show that in a convective envelope prepared according to mixing length theory, the only linearly unstable modes are those which correspond to the turbulent eddies which are the basic element of the heuristic mixing length theory.

A D-vine copula-based model for repeated measurements extending linear mixed models with homogeneous correlation structure.

PubMed

Killiches, Matthias; Czado, Claudia

2018-03-22

We propose a model for unbalanced longitudinal data, where the univariate margins can be selected arbitrarily and the dependence structure is described with the help of a D-vine copula. We show that our approach is an extremely flexible extension of the widely used linear mixed model if the correlation is homogeneous over the considered individuals. As an alternative to joint maximum-likelihood a sequential estimation approach for the D-vine copula is provided and validated in a simulation study. The model can handle missing values without being forced to discard data. Since conditional distributions are known analytically, we easily make predictions for future events. For model selection, we adjust the Bayesian information criterion to our situation. In an application to heart surgery data our model performs clearly better than competing linear mixed models. © 2018, The International Biometric Society.

Extending existing structural identifiability analysis methods to mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2018-01-01

The concept of structural identifiability for state-space models is expanded to cover mixed-effects state-space models. Two methods applicable for the analytical study of the structural identifiability of mixed-effects models are presented. The two methods are based on previously established techniques for non-mixed-effects models; namely the Taylor series expansion and the input-output form approach. By generating an exhaustive summary, and by assuming an infinite number of subjects, functions of random variables can be derived which in turn determine the distribution of the system's observation function(s). By considering the uniqueness of the analytical statistical moments of the derived functions of the random variables, the structural identifiability of the corresponding mixed-effects model can be determined. The two methods are applied to a set of examples of mixed-effects models to illustrate how they work in practice. Copyright © 2017 Elsevier Inc. All rights reserved.

Antibacterial efficacy and effect of Morinda citrifolia L. mixed with irreversible hydrocolloid for dental impressions: A randomized controlled trial.

PubMed

Ahmed, A Shafath; Charles, P David; Cholan, R; Russia, M; Surya, R; Jailance, L

2015-08-01

This study aimed to evaluate whether the extract of Morinda citrifolia L. mixed with irreversible hydrocolloid powder decreases microbial contamination during impression making without affecting the resulting casts. Twenty volunteers were randomly divided into two groups (n = 10). Group A 30 ml extract of M. citrifolia L diluted in 30 ml of water was mixed to make the impression with irreversible hydrocolloid material. Group B 30 ml deionized water was mixed with irreversible hydrocolloid material to make the impressions following which the surface roughness and dimensional stability of casts were evaluated. Extract of M. citrifolia L. mixed with irreversible hydrocolloid decreased the percentage of microorganisms when compared with water (P < 0.001) but did not affect the surface quality or dimensional stability of the casts. Mixing the extract of M. citrifolia L. with irreversible hydrocolloid powder is an alternative method to prevent contamination without sacrificing impression quality.

System and method for generating 3D images of non-linear properties of rock formation using surface seismic or surface to borehole seismic or both

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

Vu, Cung Khac; Nihei, Kurt Toshimi; Johnson, Paul A.

A system and method of characterizing properties of a medium from a non-linear interaction are include generating, by first and second acoustic sources disposed on a surface of the medium on a first line, first and second acoustic waves. The first and second acoustic sources are controllable such that trajectories of the first and second acoustic waves intersect in a mixing zone within the medium. The method further includes receiving, by a receiver positioned in a plane containing the first and second acoustic sources, a third acoustic wave generated by a non-linear mixing process from the first and second acousticmore » waves in the mixing zone; and creating a first two-dimensional image of non-linear properties or a first ratio of compressional velocity and shear velocity, or both, of the medium in a first plane generally perpendicular to the surface and containing the first line, based on the received third acoustic wave.« less

No difference in joint awareness after mobile- and fixed-bearing total knee arthroplasty: 3-year follow-up of a randomized controlled trial.

PubMed

Schotanus, M G M; Pilot, P; Vos, R; Kort, N P

2017-12-01

To compare the patients ability to forget the artificial knee joint in everyday life who were randomized to be operated for mobile- or fixed-bearing total knee arthroplasty (TKA). This single-center randomized controlled trial evaluated the 3-year follow-up of the cemented mobile- and fixed-bearing TKA from the same brand in a series of 41 patients. Clinical examination was during the pre-, 6-week, 6-month, 1-, 2- and 3-year follow-up containing multiple patient-reported outcome measures (PROMs) including the 12-item Forgotten Joint Score (FJS-12) at 3 years. Effect size was calculated for each PROM at 3-year follow-up to quantify the size of the difference between both bearings. At 3-year follow-up, general linear mixed model analysis showed that there were no significant or clinically relevant differences between the two groups for all outcome measures. Calculated effect sizes were small (<0.3) for all the PROMs except for the FJS-12; these were moderate (0.5). The results of this study demonstrate that joint awareness was slightly lower in patients operated with the MB TKA with comparable improved clinical outcome and PROMs at 3-year follow-up. Measuring joint awareness with the FJS-12 is useful and provides more stringent information at 3-year follow-up compared to other PROMs and should be the PROM of choice at each follow-up after TKA. Level I, randomized controlled trial.

Momentary effects of exposure to prosmoking media on college students' future smoking risk.

PubMed

Shadel, William G; Martino, Steven C; Setodji, Claude; Scharf, Deborah

2012-07-01

This study used ecological momentary assessment to examine acute changes in college students' future smoking risk as a function of their exposure to prosmoking media (e.g., smoking in movies, paid advertising, point-of-sale displays). A sample of 135 college students ("ever" and "never" smokers) carried handheld computers for 21 days, recording their exposures to all forms of prosmoking media during the assessment period. They also responded to three investigator-initiated control prompts during each day of the assessment period (i.e., programmed to occur randomly). After each prosmoking media exposure and after each random control prompt they answered questions that measured their risk of future smoking. Responses between prosmoking media encounters were compared (within subjects) to responses made during random control prompts. Compliance with the study protocol was high, with participants responding to over 83% of all random prompts. Participants recorded nearly three encounters with prosmoking media each week. Results of linear mixed modeling indicated that all participants had higher future smoking risk following exposure to prosmoking media compared with control prompts (p < .05); this pattern of response did not differ between ever and never smokers (p = .769). Additional modeling of the variances around participants' risk of future smoking revealed that the response of never smokers to prosmoking media was significantly more variable than the response of ever smokers. Exposure to prosmoking media is associated with acute changes in future smoking risk, and never smokers and ever smokers respond differently to these exposures.

Estimating correlation between multivariate longitudinal data in the presence of heterogeneity.

PubMed

Gao, Feng; Philip Miller, J; Xiong, Chengjie; Luo, Jingqin; Beiser, Julia A; Chen, Ling; Gordon, Mae O

2017-08-17

Estimating correlation coefficients among outcomes is one of the most important analytical tasks in epidemiological and clinical research. Availability of multivariate longitudinal data presents a unique opportunity to assess joint evolution of outcomes over time. Bivariate linear mixed model (BLMM) provides a versatile tool with regard to assessing correlation. However, BLMMs often assume that all individuals are drawn from a single homogenous population where the individual trajectories are distributed smoothly around population average. Using longitudinal mean deviation (MD) and visual acuity (VA) from the Ocular Hypertension Treatment Study (OHTS), we demonstrated strategies to better understand the correlation between multivariate longitudinal data in the presence of potential heterogeneity. Conditional correlation (i.e., marginal correlation given random effects) was calculated to describe how the association between longitudinal outcomes evolved over time within specific subpopulation. The impact of heterogeneity on correlation was also assessed by simulated data. There was a significant positive correlation in both random intercepts (ρ = 0.278, 95% CI: 0.121-0.420) and random slopes (ρ = 0.579, 95% CI: 0.349-0.810) between longitudinal MD and VA, and the strength of correlation constantly increased over time. However, conditional correlation and simulation studies revealed that the correlation was induced primarily by participants with rapid deteriorating MD who only accounted for a small fraction of total samples. Conditional correlation given random effects provides a robust estimate to describe the correlation between multivariate longitudinal data in the presence of unobserved heterogeneity (NCT00000125).

Code Mixing and Modernization across Cultures.

ERIC Educational Resources Information Center

Kamwangamalu, Nkonko M.

A review of recent studies addressed the functional uses of code mixing across cultures. Expressions of code mixing (CM) are not random; in fact, a number of functions of code mixing can easily be delineated, for example, the concept of "modernization.""Modernization" is viewed with respect to how bilingual code mixers perceive…

General practice performance in referral for suspected cancer: influence of number of cases and case-mix on publicly reported data.

PubMed

Murchie, P; Chowdhury, A; Smith, S; Campbell, N C; Lee, A J; Linden, D; Burton, C D

2015-05-26

Publicly available data show variation in GPs' use of urgent suspected cancer (USC) referral pathways. We investigated whether this could be due to small numbers of cancer cases and random case-mix, rather than due to true variation in performance. We analysed individual GP practice USC referral detection rates (proportion of the practice's cancer cases that are detected via USC) and conversion rates (proportion of the practice's USC referrals that prove to be cancer) in routinely collected data from GP practices in all of England (over 4 years) and northeast Scotland (over 7 years). We explored the effect of pooling data. We then modelled the effects of adding random case-mix to practice variation. Correlations between practice detection rate and conversion rate became less positive when data were aggregated over several years. Adding random case-mix to between-practice variation indicated that the median proportion of poorly performing practices correctly identified after 25 cancer cases were examined was 20% (IQR 17 to 24) and after 100 cases was 44% (IQR 40 to 47). Much apparent variation in GPs' use of suspected cancer referral pathways can be attributed to random case-mix. The methods currently used to assess the quality of GP-suspected cancer referral performance, and to compare individual practices, are misleading. These should no longer be used, and more appropriate and robust methods should be developed.

A Mixed Effects Randomized Item Response Model

ERIC Educational Resources Information Center

Fox, J.-P.; Wyrick, Cheryl

2008-01-01

The randomized response technique ensures that individual item responses, denoted as true item responses, are randomized before observing them and so-called randomized item responses are observed. A relationship is specified between randomized item response data and true item response data. True item response data are modeled with a (non)linear…

Information content versus word length in random typing

NASA Astrophysics Data System (ADS)

Ferrer-i-Cancho, Ramon; Moscoso del Prado Martín, Fermín

2011-12-01

Recently, it has been claimed that a linear relationship between a measure of information content and word length is expected from word length optimization and it has been shown that this linearity is supported by a strong correlation between information content and word length in many languages (Piantadosi et al 2011 Proc. Nat. Acad. Sci. 108 3825). Here, we study in detail some connections between this measure and standard information theory. The relationship between the measure and word length is studied for the popular random typing process where a text is constructed by pressing keys at random from a keyboard containing letters and a space behaving as a word delimiter. Although this random process does not optimize word lengths according to information content, it exhibits a linear relationship between information content and word length. The exact slope and intercept are presented for three major variants of the random typing process. A strong correlation between information content and word length can simply arise from the units making a word (e.g., letters) and not necessarily from the interplay between a word and its context as proposed by Piantadosi and co-workers. In itself, the linear relation does not entail the results of any optimization process.

Continuous-variable phase estimation with unitary and random linear disturbance

NASA Astrophysics Data System (ADS)

Delgado de Souza, Douglas; Genoni, Marco G.; Kim, M. S.

2014-10-01

We address the problem of continuous-variable quantum phase estimation in the presence of linear disturbance at the Hamiltonian level by means of Gaussian probe states. In particular we discuss both unitary and random disturbance by considering the parameter which characterizes the unwanted linear term present in the Hamiltonian as fixed (unitary disturbance) or random with a given probability distribution (random disturbance). We derive the optimal input Gaussian states at fixed energy, maximizing the quantum Fisher information over the squeezing angle and the squeezing energy fraction, and we discuss the scaling of the quantum Fisher information in terms of the output number of photons, nout. We observe that, in the case of unitary disturbance, the optimal state is a squeezed vacuum state and the quadratic scaling is conserved. As regards the random disturbance, we observe that the optimal squeezing fraction may not be equal to one and, for any nonzero value of the noise parameter, the quantum Fisher information scales linearly with the average number of photons. Finally, we discuss the performance of homodyne measurement by comparing the achievable precision with the ultimate limit imposed by the quantum Cramér-Rao bound.

Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex

PubMed Central

Lindsay, Grace W.

2017-01-01

Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear “mixed” selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli—and in particular, to combinations of stimuli (“mixed selectivity”)—is a topic of interest. Even though models with random feedforward connectivity are capable of creating computationally relevant mixed selectivity, such a model does not match the levels of mixed selectivity seen in the data analyzed in this study. Adding simple Hebbian learning to the model increases mixed selectivity to the correct level and makes the model match the data on several other relevant measures. This study thus offers predictions on how mixed selectivity and other properties evolve with training. PMID:28986463

On conforming mixed finite element methods for incompressible viscous flow problems

NASA Technical Reports Server (NTRS)

Gunzburger, M. D; Nicolaides, R. A.; Peterson, J. S.

1982-01-01

The application of conforming mixed finite element methods to obtain approximate solutions of linearized Navier-Stokes equations is examined. Attention is given to the convergence rates of various finite element approximations of the pressure and the velocity field. The optimality of the convergence rates are addressed in terms of comparisons of the approximation convergence to a smooth solution in relation to the best approximation available for the finite element space used. Consideration is also devoted to techniques for efficient use of a Gaussian elimination algorithm to obtain a solution to a system of linear algebraic equations derived by finite element discretizations of linear partial differential equations.

A generalized interval fuzzy mixed integer programming model for a multimodal transportation problem under uncertainty

NASA Astrophysics Data System (ADS)

Tian, Wenli; Cao, Chengxuan

2017-03-01

A generalized interval fuzzy mixed integer programming model is proposed for the multimodal freight transportation problem under uncertainty, in which the optimal mode of transport and the optimal amount of each type of freight transported through each path need to be decided. For practical purposes, three mathematical methods, i.e. the interval ranking method, fuzzy linear programming method and linear weighted summation method, are applied to obtain equivalents of constraints and parameters, and then a fuzzy expected value model is presented. A heuristic algorithm based on a greedy criterion and the linear relaxation algorithm are designed to solve the model.

Study protocol: Mobilizing Asian men in Canada to reduce stigma of mental illness.

PubMed

Guruge, Sepali; Fung, Kenneth Po-Lun; Sidani, Souraya; Este, David; Morrow, Marina; McKenzie, Kwame; Wong, Josephine Pui-Hing

2018-06-19

The available evidence on interventions addressing the stigma of mental illness is limited because of small samples, lack of diversity in study samples, and exclusion of people living with mental illness. To date, no published studies have evaluated anti-stigma interventions for Asian men in Canada. Aim This paper describes the protocol of a study to evaluate psychological and collective empowerment interventions (ACT, CEE, and ACT+CEE) in addressing self-stigma and social stigma in Asian communities in three urban settings in Canada: Toronto, Calgary and Vancouver. The study targets Asian men living with or affected by mental illness, and community leaders interested in stigma reduction and advocacy. Guided by a population health promotion framework and an ecological approach to health, the study will use a repeated measure design with mixed methods for data collection. In total, 2160 participants will be enrolled to detect moderate-to-large effect sizes, while accounting for possible attrition. Participants will be randomly assigned to one of three interventions or a control group, using a randomization matrix. Established measures will be used to collect outcome data at pretest, post-test, and 3 and 6 months follow-up, along with focus group discussions and monthly activity logs. Mixed linear models will compare participants' stigma, psychological flexibility, valued life domains, mindfulness, and empowerment readiness within and between groups. The project will generate new knowledge on the applicability and effectiveness of evidence-based psychological and collective empowerment interventions (ACT, CEE, and ACT+CEE) in addressing stigma of mental illness and mobilizing community leadership. Copyright © 2018 Elsevier Inc. All rights reserved.

Enhancing Foster Parent Training with Parent-Child Interaction Therapy: Evidence from a Randomized Field Experiment

PubMed Central

Mersky, Joshua P.; Topitzes, James; Janczewski, Colleen E.; McNeil, Cheryl B.

2015-01-01

Objective Research indicates that foster parents often do not receive sufficient training and support to help them meet the demands of caring for foster children with emotional and behavioral disturbances. Parent-Child Interaction Therapy (PCIT) is a clinically efficacious intervention for child externalizing problems, and it also has been shown to mitigate parenting stress and enhance parenting attitudes and behaviors. However, PCIT is seldom available to foster families, and it rarely has been tested under intervention conditions that are generalizable to community-based child welfare service contexts. To address this gap, PCIT was adapted and implemented in a field experiment using 2 novel approaches—group-based training and telephone consultation—both of which have the potential to be integrated into usual care. Method This study analyzes 129 foster-parent-child dyads who were randomly assigned to 1 of 3 conditions: (a) waitlist control, (b) brief PCIT, and (c) extended PCIT. Self-report and observational data were gathered at multiple time points up to 14 weeks post baseline. Results Findings from mixed-model, repeated measures analyses indicated that the brief and extended PCIT interventions were associated with a significant decrease in self-reported parenting stress. Results from mixed-effects generalized linear models showed that the interventions also led to significant improvements in observed indicators of positive and negative parenting. The brief course of PCIT was as efficacious as the extended PCIT intervention. Conclusions The findings suggest that usual training and support services can be improved upon by introducing foster parents to experiential, interactive PCIT training. PMID:26977251

Aircraft adaptive learning control

NASA Technical Reports Server (NTRS)

Lee, P. S. T.; Vanlandingham, H. F.

1979-01-01

The optimal control theory of stochastic linear systems is discussed in terms of the advantages of distributed-control systems, and the control of randomly-sampled systems. An optimal solution to longitudinal control is derived and applied to the F-8 DFBW aircraft. A randomly-sampled linear process model with additive process and noise is developed.

Nonlinear excitation of the ablative Rayleigh-Taylor instability for all wave numbers

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

Zhang, H.; Betti, R.; Gopalaswamy, V.

Small-scale perturbations in the ablative Rayleigh-Taylor instability (ARTI) are often neglected because they are linearly stable when their wavelength is shorter than a linear cutoff. Using 2D and 3D numerical simulations, it is shown that linearly stable modes of any wavelength can be destabilized. This instability regime requires finite amplitude initial perturbations and linearly stable ARTI modes are more easily destabilized in 3D than in 2D. In conclusion, it is shown that for conditions found in laser fusion targets, short wavelength ARTI modes are more efficient at driving mixing of ablated material throughout the target since the nonlinear bubble densitymore » increases with the wave number and small scale bubbles carry a larger mass flux of mixed material.« less

Nonlinear excitation of the ablative Rayleigh-Taylor instability for all wave numbers

DOE PAGES

Zhang, H.; Betti, R.; Gopalaswamy, V.; ...

2018-01-16

Small-scale perturbations in the ablative Rayleigh-Taylor instability (ARTI) are often neglected because they are linearly stable when their wavelength is shorter than a linear cutoff. Using 2D and 3D numerical simulations, it is shown that linearly stable modes of any wavelength can be destabilized. This instability regime requires finite amplitude initial perturbations and linearly stable ARTI modes are more easily destabilized in 3D than in 2D. In conclusion, it is shown that for conditions found in laser fusion targets, short wavelength ARTI modes are more efficient at driving mixing of ablated material throughout the target since the nonlinear bubble densitymore » increases with the wave number and small scale bubbles carry a larger mass flux of mixed material.« less

The roll-up and merging of coherent structures in shallow mixing layers

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

Lam, M. Y., E-mail: celmy@connect.ust.hk; Ghidaoui, M. S.; Kolyshkin, A. A.

2016-09-15

The current study seeks a fundamental explanation to the development of two-dimensional coherent structures (2DCSs) in shallow mixing layers. A nonlinear numerical model based on the depth-averaged shallow water equations is used to investigate the temporal evolution of shallow mixing layers, where the mapping from temporal to spatial results is made using the velocity at the center of the mixing layers. The flow is periodic in the streamwise direction. Transmissive boundary conditions are used in the cross-stream boundaries to prevent reflections. Numerical results are compared to linear stability analysis, mean-field theory, and secondary stability analysis. Results suggest that the onsetmore » and development of 2DCS in shallow mixing layers are the result of a sequence of instabilities governed by linear theory, mean-field theory, and secondary stability theory. The linear instability of the shearing velocity gradient gives the onset of 2DCS. When the perturbations reach a certain amplitude, the flow field of the perturbations changes from a wavy shape to a vortical (2DCS) structure because of nonlinearity. The development of the vertical 2DCS does not appear to follow weakly nonlinear theory; instead, it follows mean-field theory. After the formation of 2DCS, separate 2DCSs merge to form larger 2DCS. In this way, 2DCSs grow and shallow mixing layers develop and grow in scale. The merging of 2DCS in shallow mixing layers is shown to be caused by the secondary instability of the 2DCS. Eventually 2DCSs are dissipated by bed friction. The sequence of instabilities can cause the upscaling of the turbulent kinetic energy in shallow mixing layers.« less

Comparison of the Predictive Performance and Interpretability of Random Forest and Linear Models on Benchmark Data Sets.

PubMed

Marchese Robinson, Richard L; Palczewska, Anna; Palczewski, Jan; Kidley, Nathan

2017-08-28

The ability to interpret the predictions made by quantitative structure-activity relationships (QSARs) offers a number of advantages. While QSARs built using nonlinear modeling approaches, such as the popular Random Forest algorithm, might sometimes be more predictive than those built using linear modeling approaches, their predictions have been perceived as difficult to interpret. However, a growing number of approaches have been proposed for interpreting nonlinear QSAR models in general and Random Forest in particular. In the current work, we compare the performance of Random Forest to those of two widely used linear modeling approaches: linear Support Vector Machines (SVMs) (or Support Vector Regression (SVR)) and partial least-squares (PLS). We compare their performance in terms of their predictivity as well as the chemical interpretability of the predictions using novel scoring schemes for assessing heat map images of substructural contributions. We critically assess different approaches for interpreting Random Forest models as well as for obtaining predictions from the forest. We assess the models on a large number of widely employed public-domain benchmark data sets corresponding to regression and binary classification problems of relevance to hit identification and toxicology. We conclude that Random Forest typically yields comparable or possibly better predictive performance than the linear modeling approaches and that its predictions may also be interpreted in a chemically and biologically meaningful way. In contrast to earlier work looking at interpretation of nonlinear QSAR models, we directly compare two methodologically distinct approaches for interpreting Random Forest models. The approaches for interpreting Random Forest assessed in our article were implemented using open-source programs that we have made available to the community. These programs are the rfFC package ( https://r-forge.r-project.org/R/?group_id=1725 ) for the R statistical programming language and the Python program HeatMapWrapper [ https://doi.org/10.5281/zenodo.495163 ] for heat map generation.

Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models.

PubMed

Torres, F E; Teodoro, P E; Rodrigues, E V; Santos, A; Corrêa, A M; Ceccon, G

2016-04-29

The aim of this study was to select erect cowpea (Vigna unguiculata L.) genotypes simultaneously for high adaptability, stability, and yield grain in Mato Grosso do Sul, Brazil using mixed models. We conducted six trials of different cowpea genotypes in 2005 and 2006 in Aquidauana, Chapadão do Sul, Dourados, and Primavera do Leste. The experimental design was randomized complete blocks with four replications and 20 genotypes. Genetic parameters were estimated by restricted maximum likelihood/best linear unbiased prediction, and selection was based on the harmonic mean of the relative performance of genetic values method using three strategies: selection based on the predicted breeding value, having considered the performance mean of the genotypes in all environments (no interaction effect); the performance in each environment (with an interaction effect); and the simultaneous selection for grain yield, stability, and adaptability. The MNC99542F-5 and MNC99-537F-4 genotypes could be grown in various environments, as they exhibited high grain yield, adaptability, and stability. The average heritability of the genotypes was moderate to high and the selective accuracy was 82%, indicating an excellent potential for selection.

Broadening of cloud droplet spectra through turbulent entrainment and eddy hopping

NASA Astrophysics Data System (ADS)

Abade, Gustavo; Grabowski, Wojciech; Pawlowska, Hanna

2017-11-01

This work discusses the effect of cloud turbulence and turbulent entrainment on the evolution of the cloud droplet-size spectrum. We simulate an ensemble of idealized turbulent cloud parcels that are subject to entrainment events, modeled as a random Poisson process. Entrainment events, subsequent turbulent mixing inside the parcel, supersaturation fluctuations, and the resulting stochastic droplet growth by condensation are simulated using a Monte Carlo scheme. Quantities characterizing the turbulence intensity, entrainment rate and the mean fraction of environmental air entrained in an event are specified as external parameters. Cloud microphysics is described by applying Lagrangian particles, the so-called superdroplets. They are either unactivated cloud condensation nuclei (CCN) or cloud droplets that form from activated CCN. The model accounts for the transport of environmental CCN into the cloud by the entraining eddies at the cloud edge. Turbulent mixing of the entrained dry air with cloudy air is described using a linear model. We show that turbulence plays an important role in aiding entrained CCN to activate, providing a source of small cloud droplets and thus broadening the droplet size distribution. Further simulation results will be reported at the meeting.

Amesos2 and Belos: Direct and Iterative Solvers for Large Sparse Linear Systems

DOE PAGES

Bavier, Eric; Hoemmen, Mark; Rajamanickam, Sivasankaran; ...

2012-01-01

Solvers for large sparse linear systems come in two categories: direct and iterative. Amesos2, a package in the Trilinos software project, provides direct methods, and Belos, another Trilinos package, provides iterative methods. Amesos2 offers a common interface to many different sparse matrix factorization codes, and can handle any implementation of sparse matrices and vectors, via an easy-to-extend C++ traits interface. It can also factor matrices whose entries have arbitrary “Scalar” type, enabling extended-precision and mixed-precision algorithms. Belos includes many different iterative methods for solving large sparse linear systems and least-squares problems. Unlike competing iterative solver libraries, Belos completely decouples themore » algorithms from the implementations of the underlying linear algebra objects. This lets Belos exploit the latest hardware without changes to the code. Belos favors algorithms that solve higher-level problems, such as multiple simultaneous linear systems and sequences of related linear systems, faster than standard algorithms. The package also supports extended-precision and mixed-precision algorithms. Together, Amesos2 and Belos form a complete suite of sparse linear solvers.« less

An overview of longitudinal data analysis methods for neurological research.

PubMed

Locascio, Joseph J; Atri, Alireza

2011-01-01

The purpose of this article is to provide a concise, broad and readily accessible overview of longitudinal data analysis methods, aimed to be a practical guide for clinical investigators in neurology. In general, we advise that older, traditional methods, including (1) simple regression of the dependent variable on a time measure, (2) analyzing a single summary subject level number that indexes changes for each subject and (3) a general linear model approach with a fixed-subject effect, should be reserved for quick, simple or preliminary analyses. We advocate the general use of mixed-random and fixed-effect regression models for analyses of most longitudinal clinical studies. Under restrictive situations or to provide validation, we recommend: (1) repeated-measure analysis of covariance (ANCOVA), (2) ANCOVA for two time points, (3) generalized estimating equations and (4) latent growth curve/structural equation models.

Hair mercury concentrations and in vitro fertilization (IVF) outcomes among women from a fertility clinic

PubMed Central

Ehrlich, Shelley; Smith, Kristen; Williams, Paige L.; Chavarro, Jorge E.; Batsis, Maria; Toth, Thomas L.; Hauser, Russ

2015-01-01

Total hair mercury (Hg) was measured among 205 women undergoing in vitro fertilization (IVF) treatment and the association with prospectively collected IVF outcomes (229 IVF cycles) was evaluated. Hair Hg levels (median=0.62 ppm, range: 0.03-5.66 ppm) correlated with fish intake (r=0.59), and exceeded the recommended EPA reference of 1ppm in 33% of women. Generalized linear mixed models with random intercepts accounting for within-woman correlations across treatment cycles were used to evaluate the association of hair Hg with IVF outcomes adjusted for age, body mass index, race, smoking status, infertility diagnosis, and protocol type. Hair Hg levels were not related to ovarian stimulation outcomes (peak estradiol levels, total and mature oocyte yields) or to fertilization rate, embryo quality, clinical pregnancy rate or live birth rate. PMID:25601638

Structure de l'univers - quand l'observation guide la théorie... ou pas

NASA Astrophysics Data System (ADS)

Nazé, Yaël

The scientific method is often presented, e.g. to children, as a linear process, starting by a question and ending by the elaboration of a theory, with a few experiments in-between. The reality of the building of science is much more complex, with back-and-forth motions between theories and observations, with some intervention of technology and randomness. This complex process is not always correctly understood and assimilated, even amongst scientists. The hero cult, mixed with some revisionism, still exists despite in-depth historical studies. In this context, it may be useful to comparatively examine the reaction to crucial observations, their interpretation and their impact on the contemporaneous theory development. Four examples are presented here, all linked to the question of the 'construction of the heavens' but at different epochs.

The effects of guided inquiry instruction on student achievement in high school biology

NASA Astrophysics Data System (ADS)

Vass, Laszlo

The purpose of this quantitative, quasi-experimental study was to measure the effect of a student-centered instructional method called guided inquiry on the achievement of students in a unit of study in high school biology. The study used a non-random sample of 109 students, the control group of 55 students enrolled in high school one, received teacher centered instruction while the experimental group of 54 students enrolled at high school two received student-centered, guided inquiry instruction. The pretest-posttest design of the study analyzed scores using an independent t-test, a dependent t-test (p = <.001), an ANCOVA (p = .007), mixed method ANOVA (p = .024) and hierarchical linear regression (p = <.001). The experimental group that received guided inquiry instruction had statistically significantly higher achievement than the control group.

Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

PubMed

Han, Lide; Yang, Jian; Zhu, Jun

2007-06-01

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

Individual Characteristics vs. Experience: An Experimental Study on Cooperation in Prisoner's Dilemma

PubMed Central

Barreda-Tarrazona, Iván; Jaramillo-Gutiérrez, Ainhoa; Pavan, Marina; Sabater-Grande, Gerardo

2017-01-01

Cooperative behavior is often assumed to depend on individuals' characteristics, such as altruism and reasoning ability. Evidence is mixed about what the precise impact of these characteristics is, as the subjects of study are generally randomly paired, generating a heterogeneous mix of the two characteristics. In this study we ex-ante create four different groups of subjects by factoring their higher or lower than the median scores in both altruism and reasoning ability. Then we use these groups in order to analyze the joint effect of the two characteristics on the individual choice of cooperating and on successful paired cooperation. Subjects belonging to each group play first 10 one-shot prisoner's dilemma (PD) games with ten random partners and then three consecutive 10-round repeated PD games with three random partners. In all games, we elicit players' beliefs regarding cooperation using an incentive compatible method. Individuals with high altruism are more optimistic about the cooperative behavior of the other player in the one-shot game. They also show higher individual cooperation and paired cooperation rates in the first repetitions of this game. Contrary to the one-shot PD games where high reasoning ability reduces the probability of playing cooperatively, the sign of the relationship is inverted in the first repeated PD game, showing that high reasoning ability individuals better adjust their behavior to the characteristics of the game they are playing. In this sense, the joint effect of reasoning ability and altruism is not linear, with reasoning ability counteracting the cooperative effect of altruism in the one-shot game and reinforcing it in the first repeated game. However, experience playing the repeated PD games takes over the two individual characteristics in explaining individual and paired cooperation. Thus, in a (PD) setting, altruism and reasoning ability significantly affect behavior in single encounters, while in repeated interactions individual and paired cooperation reach similarly high levels independently of these individual characteristics. PMID:28473787

Nonlinear random response prediction using MSC/NASTRAN

NASA Technical Reports Server (NTRS)

Robinson, J. H.; Chiang, C. K.; Rizzi, S. A.

1993-01-01

An equivalent linearization technique was incorporated into MSC/NASTRAN to predict the nonlinear random response of structures by means of Direct Matrix Abstract Programming (DMAP) modifications and inclusion of the nonlinear differential stiffness module inside the iteration loop. An iterative process was used to determine the rms displacements. Numerical results obtained for validation on simple plates and beams are in good agreement with existing solutions in both the linear and linearized regions. The versatility of the implementation will enable the analyst to determine the nonlinear random responses for complex structures under combined loads. The thermo-acoustic response of a hexagonal thermal protection system panel is used to highlight some of the features of the program.

Use of a Linear Paul Trap to Study Random Noise-Induced Beam Degradation in High-Intensity Accelerators

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

Chung, Moses; Gilson, Erik P.; Davidson, Ronald C.

2009-04-10

A random noise-induced beam degradation that can affect intense beam transport over long propagation distances has been experimentally studied by making use of the transverse beam dynamics equivalence between an alternating-gradient (AG) focusing system and a linear Paul trap system. For the present studies, machine imperfections in the quadrupole focusing lattice are considered, which are emulated by adding small random noise on the voltage waveform of the quadrupole electrodes in the Paul trap. It is observed that externally driven noise continuously produces a nonthermal tail of trapped ions, and increases the transverse emittance almost linearly with the duration of themore » noise.« less

On Fluctuations of Eigenvalues of Random Band Matrices

NASA Astrophysics Data System (ADS)

Shcherbina, M.

2015-10-01

We consider the fluctuations of linear eigenvalue statistics of random band matrices whose entries have the form with i.i.d. possessing the th moment, where the function u has a finite support , so that M has only nonzero diagonals. The parameter b (called the bandwidth) is assumed to grow with n in a way such that . Without any additional assumptions on the growth of b we prove CLT for linear eigenvalue statistics for a rather wide class of test functions. Thus we improve and generalize the results of the previous papers (Jana et al., arXiv:1412.2445; Li et al. Random Matrices 2:04, 2013), where CLT was proven under the assumption . Moreover, we develop a method which allows to prove automatically the CLT for linear eigenvalue statistics of the smooth test functions for almost all classical models of random matrix theory: deformed Wigner and sample covariance matrices, sparse matrices, diluted random matrices, matrices with heavy tales etc.

Recommendations for choosing an analysis method that controls Type I error for unbalanced cluster sample designs with Gaussian outcomes.

PubMed

Johnson, Jacqueline L; Kreidler, Sarah M; Catellier, Diane J; Murray, David M; Muller, Keith E; Glueck, Deborah H

2015-11-30

We used theoretical and simulation-based approaches to study Type I error rates for one-stage and two-stage analytic methods for cluster-randomized designs. The one-stage approach uses the observed data as outcomes and accounts for within-cluster correlation using a general linear mixed model. The two-stage model uses the cluster specific means as the outcomes in a general linear univariate model. We demonstrate analytically that both one-stage and two-stage models achieve exact Type I error rates when cluster sizes are equal. With unbalanced data, an exact size α test does not exist, and Type I error inflation may occur. Via simulation, we compare the Type I error rates for four one-stage and six two-stage hypothesis testing approaches for unbalanced data. With unbalanced data, the two-stage model, weighted by the inverse of the estimated theoretical variance of the cluster means, and with variance constrained to be positive, provided the best Type I error control for studies having at least six clusters per arm. The one-stage model with Kenward-Roger degrees of freedom and unconstrained variance performed well for studies having at least 14 clusters per arm. The popular analytic method of using a one-stage model with denominator degrees of freedom appropriate for balanced data performed poorly for small sample sizes and low intracluster correlation. Because small sample sizes and low intracluster correlation are common features of cluster-randomized trials, the Kenward-Roger method is the preferred one-stage approach. Copyright © 2015 John Wiley & Sons, Ltd.

Dual energy CT: How to best blend both energies in one fused image?

NASA Astrophysics Data System (ADS)

Eusemann, Christian; Holmes, David R., III; Schmidt, Bernhard; Flohr, Thomas G.; Robb, Richard; McCollough, Cynthia; Hough, David M.; Huprich, James E.; Wittmer, Michael; Siddiki, Hasan; Fletcher, Joel G.

2008-03-01

In x-ray based imaging, attenuation depends on the type of tissue scanned and the average energy level of the x-ray beam, which can be adjusted via the x-ray tube potential. Conventional computed tomography (CT) imaging uses a single kV value, usually 120kV. Dual energy CT uses two different tube potentials (e.g. 80kV & 140kV) to obtain two image datasets with different attenuation characteristics. This difference in attenuation levels allows for classification of the composition of the tissues. In addition, the different energies significantly influence the contrast resolution and noise characteristics of the two image datasets. 80kV images provide greater contrast resolution than 140kV, but are limited because of increased noise. While dual-energy CT may provide useful clinical information, the question arises as to how to best realize and visualize this benefit. In conventional single energy CT, patient image data is presented to the physicians using well understood organ specific window and level settings. Instead of viewing two data series (one for each tube potential), the images are most often fused into a single image dataset using a linear mixing of the data with a 70% 140kV and a 30% 80kV mixing ratio, as available on one commercial systems. This ratio provides a reasonable representation of the anatomy/pathology, however due to the linear nature of the blending, the advantages of each dataset (contrast or sharpness) is partially offset by its drawbacks (blurring or noise). This project evaluated a variety of organ specific linear and non-linear mixing algorithms to optimize the blending of the low and high kV information for display in a way that combines the benefits (contrast and sharpness) of both energies in a single image. A blinded review analysis by subspecialty abdominal radiologists found that, unique, tunable, non-linear mixing algorithms that we developed outperformed linear, fixed mixing for a variety of different organs and pathologies of interest.

Comparison of linear and non-linear models for predicting energy expenditure from raw accelerometer data.

PubMed

Montoye, Alexander H K; Begum, Munni; Henning, Zachary; Pfeiffer, Karin A

2017-02-01

This study had three purposes, all related to evaluating energy expenditure (EE) prediction accuracy from body-worn accelerometers: (1) compare linear regression to linear mixed models, (2) compare linear models to artificial neural network models, and (3) compare accuracy of accelerometers placed on the hip, thigh, and wrists. Forty individuals performed 13 activities in a 90 min semi-structured, laboratory-based protocol. Participants wore accelerometers on the right hip, right thigh, and both wrists and a portable metabolic analyzer (EE criterion). Four EE prediction models were developed for each accelerometer: linear regression, linear mixed, and two ANN models. EE prediction accuracy was assessed using correlations, root mean square error (RMSE), and bias and was compared across models and accelerometers using repeated-measures analysis of variance. For all accelerometer placements, there were no significant differences for correlations or RMSE between linear regression and linear mixed models (correlations: r  =  0.71-0.88, RMSE: 1.11-1.61 METs; p  >  0.05). For the thigh-worn accelerometer, there were no differences in correlations or RMSE between linear and ANN models (ANN-correlations: r  =  0.89, RMSE: 1.07-1.08 METs. Linear models-correlations: r  =  0.88, RMSE: 1.10-1.11 METs; p  >  0.05). Conversely, one ANN had higher correlations and lower RMSE than both linear models for the hip (ANN-correlation: r  =  0.88, RMSE: 1.12 METs. Linear models-correlations: r  =  0.86, RMSE: 1.18-1.19 METs; p  <  0.05), and both ANNs had higher correlations and lower RMSE than both linear models for the wrist-worn accelerometers (ANN-correlations: r  =  0.82-0.84, RMSE: 1.26-1.32 METs. Linear models-correlations: r  =  0.71-0.73, RMSE: 1.55-1.61 METs; p  <  0.01). For studies using wrist-worn accelerometers, machine learning models offer a significant improvement in EE prediction accuracy over linear models. Conversely, linear models showed similar EE prediction accuracy to machine learning models for hip- and thigh-worn accelerometers and may be viable alternative modeling techniques for EE prediction for hip- or thigh-worn accelerometers.

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

Kanna, T.; Vijayajayanthi, M.; Lakshmanan, M.

The bright soliton solutions of the mixed coupled nonlinear Schroedinger equations with two components (2-CNLS) with linear self- and cross-coupling terms have been obtained by identifying a transformation that transforms the corresponding equation to the integrable mixed 2-CNLS equations. The study on the collision dynamics of bright solitons shows that there exists periodic energy switching, due to the coupling terms. This periodic energy switching can be controlled by the new type of shape changing collisions of bright solitons arising in a mixed 2-CNLS system, characterized by intensity redistribution, amplitude dependent phase shift, and relative separation distance. We also point outmore » that this system exhibits large periodic intensity switching even with very small linear self-coupling strengths.« less

Characterizing entanglement with global and marginal entropic measures

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

Adesso, Gerardo; Illuminati, Fabrizio; De Siena, Silvio

2003-12-01

We qualify the entanglement of arbitrary mixed states of bipartite quantum systems by comparing global and marginal mixednesses quantified by different entropic measures. For systems of two qubits we discriminate the class of maximally entangled states with fixed marginal mixednesses, and determine an analytical upper bound relating the entanglement of formation to the marginal linear entropies. This result partially generalizes to mixed states the quantification of entanglement with marginal mixednesses holding for pure states. We identify a class of entangled states that, for fixed marginals, are globally more mixed than product states when measured by the linear entropy. Such statesmore » cannot be discriminated by the majorization criterion.« less

Ejecta patterns of Meteor Crater, Arizona derived from the linear un-mixing of TIMS data and laboratory thermal emission spectra

NASA Technical Reports Server (NTRS)

Ramsey, Michael S.; Christensen, Philip R.

1992-01-01

Accurate interpretation of thermal infrared data depends upon the understanding and removal of complicating effects. These effects may include physical mixing of various mineralogies and particle sizes, atmospheric absorption and emission, surficial coatings, geometry effects, and differential surface temperatures. The focus is the examination of the linear spectral mixing of individual mineral or endmember spectra. Linear addition of spectra, for particles larger than the wavelength, allows for a straight-forward method of deconvolving the observed spectra, predicting a volume percent of each endmember. The 'forward analysis' of linear mixing (comparing the spectra of physical mixtures to numerical mixtures) has received much attention. The reverse approach of un-mixing thermal emission spectra was examined with remotely sensed data, but no laboratory verification exists. Understanding of the effects of spectral mixing on high resolution laboratory spectra allows for the extrapolation to lower resolution, and often more complicated, remotely gathered data. Thermal Infrared Multispectral Scanner (TIMS) data for Meteor Crater, Arizona were acquired in Sep. 1987. The spectral un-mixing of these data gives a unique test of the laboratory results. Meteor Crater (1.2 km in diameter and 180 m deep) is located in north-central Arizona, west of Canyon Diablo. The arid environment, paucity of vegetation, and low relief make the region ideal for remote data acquisition. Within the horizontal sedimentary sequence that forms the upper Colorado Plateau, the oldest unit sampled by the impact crater was the Permian Coconino Sandstone. A thin bed of the Toroweap Formation, also of Permian age, conformably overlays the Coconino. Above the Toroweap lies the Permian Kiabab Limestone which, in turn, is covered by a thin veneer of the Moenkopi Formation. The Moenkopi is Triassic in age and has two distinct sub-units in the vicinity of the crater. The lower Wupatki member is a fine-grained sandstone, while the upper Moqui member is a fissile siltstone. Ejecta from these units are preserved as inverted stratigraphy up to 2 crater radii from the rim. The mineralogical contrast between the units, relative lack of post-emplacement erosion and ejecta mixing provide a unique site to apply the un-mixing model. Selection of the aforementioned units as endmembers reveals distinct patterns in the ejecta of the crater.

Modeling Longitudinal Data Containing Non-Normal Within Subject Errors

NASA Technical Reports Server (NTRS)

Feiveson, Alan; Glenn, Nancy L.

2013-01-01

The mission of the National Aeronautics and Space Administration’s (NASA) human research program is to advance safe human spaceflight. This involves conducting experiments, collecting data, and analyzing data. The data are longitudinal and result from a relatively few number of subjects; typically 10 – 20. A longitudinal study refers to an investigation where participant outcomes and possibly treatments are collected at multiple follow-up times. Standard statistical designs such as mean regression with random effects and mixed–effects regression are inadequate for such data because the population is typically not approximately normally distributed. Hence, more advanced data analysis methods are necessary. This research focuses on four such methods for longitudinal data analysis: the recently proposed linear quantile mixed models (lqmm) by Geraci and Bottai (2013), quantile regression, multilevel mixed–effects linear regression, and robust regression. This research also provides computational algorithms for longitudinal data that scientists can directly use for human spaceflight and other longitudinal data applications, then presents statistical evidence that verifies which method is best for specific situations. This advances the study of longitudinal data in a broad range of applications including applications in the sciences, technology, engineering and mathematics fields.

A polymer, random walk model for the size-distribution of large DNA fragments after high linear energy transfer radiation

NASA Technical Reports Server (NTRS)

Ponomarev, A. L.; Brenner, D.; Hlatky, L. R.; Sachs, R. K.

2000-01-01

DNA double-strand breaks (DSBs) produced by densely ionizing radiation are not located randomly in the genome: recent data indicate DSB clustering along chromosomes. Stochastic DSB clustering at large scales, from > 100 Mbp down to < 0.01 Mbp, is modeled using computer simulations and analytic equations. A random-walk, coarse-grained polymer model for chromatin is combined with a simple track structure model in Monte Carlo software called DNAbreak and is applied to data on alpha-particle irradiation of V-79 cells. The chromatin model neglects molecular details but systematically incorporates an increase in average spatial separation between two DNA loci as the number of base-pairs between the loci increases. Fragment-size distributions obtained using DNAbreak match data on large fragments about as well as distributions previously obtained with a less mechanistic approach. Dose-response relations, linear at small doses of high linear energy transfer (LET) radiation, are obtained. They are found to be non-linear when the dose becomes so large that there is a significant probability of overlapping or close juxtaposition, along one chromosome, for different DSB clusters from different tracks. The non-linearity is more evident for large fragments than for small. The DNAbreak results furnish an example of the RLC (randomly located clusters) analytic formalism, which generalizes the broken-stick fragment-size distribution of the random-breakage model that is often applied to low-LET data.

Comparison of Nonlinear Random Response Using Equivalent Linearization and Numerical Simulation

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Muravyov, Alexander A.

2000-01-01

A recently developed finite-element-based equivalent linearization approach for the analysis of random vibrations of geometrically nonlinear multiple degree-of-freedom structures is validated. The validation is based on comparisons with results from a finite element based numerical simulation analysis using a numerical integration technique in physical coordinates. In particular, results for the case of a clamped-clamped beam are considered for an extensive load range to establish the limits of validity of the equivalent linearization approach.

Linearity, Bias, and Precision of Hepatic Proton Density Fat Fraction Measurements by Using MR Imaging: A Meta-Analysis.

PubMed

Yokoo, Takeshi; Serai, Suraj D; Pirasteh, Ali; Bashir, Mustafa R; Hamilton, Gavin; Hernando, Diego; Hu, Houchun H; Hetterich, Holger; Kühn, Jens-Peter; Kukuk, Guido M; Loomba, Rohit; Middleton, Michael S; Obuchowski, Nancy A; Song, Ji Soo; Tang, An; Wu, Xinhuai; Reeder, Scott B; Sirlin, Claude B

2018-02-01

Purpose To determine the linearity, bias, and precision of hepatic proton density fat fraction (PDFF) measurements by using magnetic resonance (MR) imaging across different field strengths, imager manufacturers, and reconstruction methods. Materials and Methods This meta-analysis was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A systematic literature search identified studies that evaluated the linearity and/or bias of hepatic PDFF measurements by using MR imaging (hereafter, MR imaging-PDFF) against PDFF measurements by using colocalized MR spectroscopy (hereafter, MR spectroscopy-PDFF) or the precision of MR imaging-PDFF. The quality of each study was evaluated by using the Quality Assessment of Studies of Diagnostic Accuracy 2 tool. De-identified original data sets from the selected studies were pooled. Linearity was evaluated by using linear regression between MR imaging-PDFF and MR spectroscopy-PDFF measurements. Bias, defined as the mean difference between MR imaging-PDFF and MR spectroscopy-PDFF measurements, was evaluated by using Bland-Altman analysis. Precision, defined as the agreement between repeated MR imaging-PDFF measurements, was evaluated by using a linear mixed-effects model, with field strength, imager manufacturer, reconstruction method, and region of interest as random effects. Results Twenty-three studies (1679 participants) were selected for linearity and bias analyses and 11 studies (425 participants) were selected for precision analyses. MR imaging-PDFF was linear with MR spectroscopy-PDFF (R 2 = 0.96). Regression slope (0.97; P < .001) and mean Bland-Altman bias (-0.13%; 95% limits of agreement: -3.95%, 3.40%) indicated minimal underestimation by using MR imaging-PDFF. MR imaging-PDFF was precise at the region-of-interest level, with repeatability and reproducibility coefficients of 2.99% and 4.12%, respectively. Field strength, imager manufacturer, and reconstruction method each had minimal effects on reproducibility. Conclusion MR imaging-PDFF has excellent linearity, bias, and precision across different field strengths, imager manufacturers, and reconstruction methods. © RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on October 2, 2017.

The Effects of Aroma Foot Massage on Blood Pressure and Anxiety in Japanese Community-Dwelling Men and Women: A Crossover Randomized Controlled Trial

PubMed Central

Tomooka, Kiyohide; Ohira, Tetsuya; Ogino, Keiki; Tanigawa, Takeshi

2016-01-01

Objectives The aim of this study was to investigate the effects of aroma foot massage on blood pressure, anxiety, and health-related quality of life (QOL) in Japanese community-dwelling men and women using a crossover randomized controlled trial. Methods Fifty-seven eligible participants (5 men and 52 women) aged 27 to 72 were randomly divided into 2 intervention groups (group A: n = 29; group B: n = 28) to participate in aroma foot massages 12 times during the 4-week intervention period. Systolic and diastolic blood pressure (SBP and DBP, respectively), heart rate, state anxiety, and health-related QOL were measured at the baseline, 4-week follow-up, and 8-week follow-up. The effects of the aroma foot massage intervention on these factors and the proportion of participants with anxiety were analyzed using a linear mixed-effect model for a crossover design adjusted for participant and period effects. Furthermore, the relationship between the changes in SBP and state anxiety among participants with relieved anxiety was assessed using a linear regression model. Results Aroma foot massage significantly decreased the mean SBP (p = 0.02), DBP (p = 0.006), and state anxiety (p = 0.003) as well as the proportion of participants with anxiety (p = 0.003). Although it was not statistically significant (p = 0.088), aroma foot massage also increased the score of mental health-related QOL. The change in SBP had a significant and positive correlation with the change in state anxiety (p = 0.01) among participants with relieved anxiety. Conclusion The self-administered aroma foot massage intervention significantly decreased the mean SBP and DBP as well as the state anxiety score, and tended to increase the mental health-related QOL scores. The results suggest that aroma foot massage may be an easy and effective way to improve mental health and blood pressure. Trial Registration University Hospital Medical Information Network 000014260 PMID:27010201

The Effects of Aroma Foot Massage on Blood Pressure and Anxiety in Japanese Community-Dwelling Men and Women: A Crossover Randomized Controlled Trial.

PubMed

Eguchi, Eri; Funakubo, Narumi; Tomooka, Kiyohide; Ohira, Tetsuya; Ogino, Keiki; Tanigawa, Takeshi

2016-01-01

The aim of this study was to investigate the effects of aroma foot massage on blood pressure, anxiety, and health-related quality of life (QOL) in Japanese community-dwelling men and women using a crossover randomized controlled trial. Fifty-seven eligible participants (5 men and 52 women) aged 27 to 72 were randomly divided into 2 intervention groups (group A: n = 29; group B: n = 28) to participate in aroma foot massages 12 times during the 4-week intervention period. Systolic and diastolic blood pressure (SBP and DBP, respectively), heart rate, state anxiety, and health-related QOL were measured at the baseline, 4-week follow-up, and 8-week follow-up. The effects of the aroma foot massage intervention on these factors and the proportion of participants with anxiety were analyzed using a linear mixed-effect model for a crossover design adjusted for participant and period effects. Furthermore, the relationship between the changes in SBP and state anxiety among participants with relieved anxiety was assessed using a linear regression model. Aroma foot massage significantly decreased the mean SBP (p = 0.02), DBP (p = 0.006), and state anxiety (p = 0.003) as well as the proportion of participants with anxiety (p = 0.003). Although it was not statistically significant (p = 0.088), aroma foot massage also increased the score of mental health-related QOL. The change in SBP had a significant and positive correlation with the change in state anxiety (p = 0.01) among participants with relieved anxiety. The self-administered aroma foot massage intervention significantly decreased the mean SBP and DBP as well as the state anxiety score, and tended to increase the mental health-related QOL scores. The results suggest that aroma foot massage may be an easy and effective way to improve mental health and blood pressure. University Hospital Medical Information Network 000014260.

Unsupervised Bayesian linear unmixing of gene expression microarrays.

PubMed

Bazot, Cécile; Dobigeon, Nicolas; Tourneret, Jean-Yves; Zaas, Aimee K; Ginsburg, Geoffrey S; Hero, Alfred O

2013-03-19

This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters. Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here. The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores collected during the study. Using a constrained model allows recovery of all the inflammatory genes in a single factor.

Two-Year Trends of Taxane-Induced Neuropathy in Women Enrolled in a Randomized Trial of Acetyl-L-Carnitine (SWOG S0715).

PubMed

Hershman, Dawn L; Unger, Joseph M; Crew, Katherine D; Till, Cathee; Greenlee, Heather; Minasian, Lori M; Moinpour, Carol M; Lew, Danika L; Fehrenbacher, Louis; Wade, James L; Wong, Siu-Fun; Fisch, Michael J; Lynn Henry, N; Albain, Kathy S

2018-06-01

Chemotherapy-induced peripheral neuropathy (CIPN) is a common and disabling side effect of taxanes. Acetyl-L-carnitine (ALC) was unexpectedly found to increase CIPN in a randomized trial. We investigated the long-term patterns of CIPN among patients in this trial. S0715 was a randomized, double-blind, multicenter trial comparing ALC (1000 mg three times a day) with placebo for 24 weeks in women undergoing adjuvant taxane-based chemotherapy for breast cancer. CIPN was measured by the 11-item neurotoxicity (NTX) component of the FACT-Taxane scale at weeks 12, 24, 36, 52, and 104. We examined NTX scores over two years using linear mixed models for longitudinal data. Individual time points were examined using linear regression. Regression analyses included stratification factors and the baseline score as covariates. All statistical tests were two-sided. Four-hundred nine subjects were eligible for evaluation. Patients receiving ALC had a statistically significantly (P = .01) greater reduction in NTX scores (worse CIPN) of -1.39 points (95% confidence interval [CI] = -2.48 to -0.30) than the placebo group. These differences were particularly evident at weeks 24 (-1.68, 95% CI = -3.02 to -0.33), 36 (-1.37, 95% CI = -2.69 to -0.04), and 52 (-1.83, 95% CI = -3.35 to -0.32). At 104 weeks, 39.5% on the ALC arm and 34.4% on the placebo arm reported a five-point (10%) decrease from baseline. For both treatment groups, 104-week NTX scores were statistically significantly different compared with baseline (P < .001). For both groups, NTX scores were reduced from baseline and remained persistently low. Twenty-four weeks of ALC therapy resulted in statistically significantly worse CIPN over two years. Understanding the mechanism of this persistent effect may inform prevention and treatment strategies. Until then, the potential efficacy and harms of commonly used supplements should be rigorously studied.

Random walk, diffusion and mixing in simulations of scalar transport in fluid flows

NASA Astrophysics Data System (ADS)

Klimenko, A. Y.

2008-12-01

Physical similarity and mathematical equivalence of continuous diffusion and particle random walk form one of the cornerstones of modern physics and the theory of stochastic processes. In many applied models used in simulation of turbulent transport and turbulent combustion, mixing between particles is used to reflect the influence of the continuous diffusion terms in the transport equations. We show that the continuous scalar transport and diffusion can be accurately specified by means of mixing between randomly walking Lagrangian particles with scalar properties and assess errors associated with this scheme. This gives an alternative formulation for the stochastic process which is selected to represent the continuous diffusion. This paper focuses on statistical errors and deals with relatively simple cases, where one-particle distributions are sufficient for a complete description of the problem.

Examining the influence of link function misspecification in conventional regression models for developing crash modification factors.

PubMed

Wu, Lingtao; Lord, Dominique

2017-05-01

This study further examined the use of regression models for developing crash modification factors (CMFs), specifically focusing on the misspecification in the link function. The primary objectives were to validate the accuracy of CMFs derived from the commonly used regression models (i.e., generalized linear models or GLMs with additive linear link functions) when some of the variables have nonlinear relationships and quantify the amount of bias as a function of the nonlinearity. Using the concept of artificial realistic data, various linear and nonlinear crash modification functions (CM-Functions) were assumed for three variables. Crash counts were randomly generated based on these CM-Functions. CMFs were then derived from regression models for three different scenarios. The results were compared with the assumed true values. The main findings are summarized as follows: (1) when some variables have nonlinear relationships with crash risk, the CMFs for these variables derived from the commonly used GLMs are all biased, especially around areas away from the baseline conditions (e.g., boundary areas); (2) with the increase in nonlinearity (i.e., nonlinear relationship becomes stronger), the bias becomes more significant; (3) the quality of CMFs for other variables having linear relationships can be influenced when mixed with those having nonlinear relationships, but the accuracy may still be acceptable; and (4) the misuse of the link function for one or more variables can also lead to biased estimates for other parameters. This study raised the importance of the link function when using regression models for developing CMFs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Overshooting thunderstorm cloud top dynamics as approximated by a linear Lagrangian parcel model with analytic exact solutions

NASA Technical Reports Server (NTRS)

Schlesinger, Robert E.

1990-01-01

Results are presented from a linear Lagrangian entraining parcel model of an overshooting thunderstorm cloud top. The model, which is similar to that of Adler and Mack (1986), gives analytic exact solutions for vertical velocity and temperature by representing mixing with Rayleigh damping instead of nonlinearly. Model results are presented for various combinations of stratospheric lapse rate, drag intensity, and mixing strength. The results are compared to those of Adler and Mack.

Linear mixed-effects models for within-participant psychology experiments: an introductory tutorial and free, graphical user interface (LMMgui).

PubMed

Magezi, David A

2015-01-01

Linear mixed-effects models (LMMs) are increasingly being used for data analysis in cognitive neuroscience and experimental psychology, where within-participant designs are common. The current article provides an introductory review of the use of LMMs for within-participant data analysis and describes a free, simple, graphical user interface (LMMgui). LMMgui uses the package lme4 (Bates et al., 2014a,b) in the statistical environment R (R Core Team).

Natural remanent magnetization acquisition in bioturbated sediment: General theory and implications for relative paleointensity reconstructions

NASA Astrophysics Data System (ADS)

Egli, R.; Zhao, X.

2015-04-01

We present a general theory for the acquisition of natural remanent magnetizations (NRM) in sediment under the influence of (a) magnetic torques, (b) randomizing torques, and (c) torques resulting from interaction forces. Dynamic equilibrium between (a) and (b) in the water column and at the sediment-water interface generates a detrital remanent magnetization (DRM), while much stronger randomizing torques may be provided by bioturbation inside the mixed layer. These generate a so-called mixed remanent magnetization (MRM), which is stabilized by mechanical interaction forces. During the time required to cross the surface mixed layer, DRM is lost and MRM is acquired at a rate that depends on bioturbation intensity. Both processes are governed by a MRM lock-in function. The final NRM intensity is controlled mainly by a single parameter γ that is defined as the product of rotational diffusion and mixed-layer thickness, divided by sedimentation rate. This parameter defines three regimes: (1) slow mixing (γ < 0.2) leading to DRM preservation and insignificant MRM acquisition, (2) fast mixing (γ > 10) with MRM acquisition and full DRM randomization, and (3) intermediate mixing. Because the acquisition efficiency of DRM is larger than that of MRM, NRM intensity is particularly sensitive to γ in case of mixed regimes, generating variable NRM acquisition efficiencies. This model explains (1) lock-in delays that can be matched with empirical reconstructions from paleomagnetic records, (2) the existence of small lock-in depths that lead to DRM preservation, (3) specific NRM acquisition efficiencies of magnetofossil-rich sediments, and (4) some relative paleointensity artifacts.

Minimization of required model runs in the Random Mixing approach to inverse groundwater flow and transport modeling

NASA Astrophysics Data System (ADS)

Hoerning, Sebastian; Bardossy, Andras; du Plessis, Jaco

2017-04-01

Most geostatistical inverse groundwater flow and transport modelling approaches utilize a numerical solver to minimize the discrepancy between observed and simulated hydraulic heads and/or hydraulic concentration values. The optimization procedure often requires many model runs, which for complex models lead to long run times. Random Mixing is a promising new geostatistical technique for inverse modelling. The method is an extension of the gradual deformation approach. It works by finding a field which preserves the covariance structure and maintains observed hydraulic conductivities. This field is perturbed by mixing it with new fields that fulfill the homogeneous conditions. This mixing is expressed as an optimization problem which aims to minimize the difference between the observed and simulated hydraulic heads and/or concentration values. To preserve the spatial structure, the mixing weights must lie on the unit hyper-sphere. We present a modification to the Random Mixing algorithm which significantly reduces the number of model runs required. The approach involves taking n equally spaced points on the unit circle as weights for mixing conditional random fields. Each of these mixtures provides a solution to the forward model at the conditioning locations. For each of the locations the solutions are then interpolated around the circle to provide solutions for additional mixing weights at very low computational cost. The interpolated solutions are used to search for a mixture which maximally reduces the objective function. This is in contrast to other approaches which evaluate the objective function for the n mixtures and then interpolate the obtained values. Keeping the mixture on the unit circle makes it easy to generate equidistant sampling points in the space; however, this means that only two fields are mixed at a time. Once the optimal mixture for two fields has been found, they are combined to form the input to the next iteration of the algorithm. This process is repeated until a threshold in the objective function is met or insufficient changes are produced in successive iterations.

Randomized controlled trial on the effects of CCTV training on quality of life, depression, and adaptation to vision loss.

PubMed

Burggraaff, Marloes C; van Nispen, Ruth M A; Knol, Dirk L; Ringens, Peter J; van Rens, Ger H M B

2012-06-14

In addition to performance-based measures, vision-related quality of life (QOL) and other subjective measures of psychosocial functioning are considered important outcomes of training in the visually impaired. In a multicenter, masked, randomized controlled trial, subjective effects of training in the use of closed-circuit televisions (CCTV) were investigated. Patients (n = 122) were randomized either to a treatment group that received usual delivery instructions from the supplier combined with concise outpatient training, or to a control group that received delivery instructions only. Subjective outcomes were the low vision quality-of-life questionnaire (LVQOL), EuroQOL 5 dimensions, adaptation to age-related vision loss (AVL), and the Center of Epidemiologic Studies Depression scales. Linear mixed models were used to investigate treatment effects. Differential effects of patient characteristics were studied by implementing higher order interactions into the models. From baseline to follow-up, all patients perceived significantly less problems on the reading and fine work dimension (-28.8 points; P < 0.001) and the adaptation dimension (-4.67 points; P = 0.04) of the LVQOL. However, no treatment effect was found based on the intention-to-treat analysis. This study demonstrated the effect of receiving and using a CCTV on two vision-related QOL dimensions; however, outpatient training in the use of CCTVs had no additional value. (trialregister.nl number, NTR1031.).

A prospective randomized comparison between pylorus- and subtotal stomach-preserving pancreatoduodenectomy on postoperative delayed gastric emptying occurrence and long-term nutritional status.

PubMed

Matsumoto, Ippei; Shinzeki, Makoto; Asari, Sadaki; Goto, Tadahiro; Shirakawa, Sachiyo; Ajiki, Tetsuo; Fukumoto, Takumi; Suzuki, Yasuyuki; Ku, Yonson

2014-06-01

Pylorus-preserving pancreatoduodenectomy (PPPD) has been associated with a high incidence of delayed gastric emptying (DGE). There are few studies comparing DGE associated with PPPD and subtotal stomach-preserving pancreatoduodenectomy (SSPPD). Moreover, differences between the procedures with respect to long-term results have not been reported. A prospective randomized study was conducted to compare perioperative complications and long-term nutritional status with PPPD and SSPPD. One hundred patients with periampullary lesions were randomized to receive either PPPD (n = 50) or SSPPD (n = 50). All patients were followed up for 3 years after surgery or to the time of recurrence to evaluate nutritional status for the study. The effects of the procedure, age, and malignancy on changes in nutritional indicators were estimated with linear mixed models. This study was registered at UMIN Clinical Trials Registry (UMIN 000012337). The incidence of DGE assessed by the International Study Group of Pancreatic Surgery was 20% with PPPD and 12% with SSPPD (P = 0.414). There were no significant differences between the two procedures on postoperative serum albumin levels, serum total cholesterol levels, and body mass index during the 3-year follow-up period. SSPPD is equally effective in DGE occurrence rate and long-term nutritional status comparing to PPPD. © 2014 Wiley Periodicals, Inc.

Helping Seniors Plan for Posthospital Discharge Needs Before a Hospitalization Occurs: Results from the Randomized Control Trial of PlanYourLifespan.org.

PubMed

Lindquist, Lee A; Ramirez-Zohfeld, Vanessa; Sunkara, Priya D; Forcucci, Chris; Campbell, Dianne S; Mitzen, Phyllis; Ciolino, Jody D; Kricke, Gayle; Seltzer, Anne; Ramirez, Ana V; Cameron, Kenzie A

2017-11-01

Investigate the effect of PlanYourLifespan.org (PYL) on knowledge of posthospital discharge options. Multisite randomized controlled trial. Nonhospitalized adults, aged =65 years, living in urban, suburban, and rural areas of Texas, Illinois, and Indiana. PYL is a national, publicly available tool that provides education on posthospital therapy choices and local home-based resources. Participants completed an in-person baseline survey, followed by exposure to intervention or attention control (AC) websites, then 1-month and 3-month telephone surveys. The primary knowledge outcome was measured with 6 items (possible 0-6 points) pertaining to hospital discharge needs. Among 385 participants randomized, mean age was 71.9 years (standard deviation 5.6) and 79.5% of participants were female. At 1 month, the intervention group had a 0.6 point change (standard deviation = 1.6) versus the AC group who had a -0.1 point change in knowledge score. Linear mixed modeling results suggest sex, health literacy level, level of education, income, and history of high blood pressure/kidney disease were significant predictors of knowledge over time. Controlling for these variables, treatment effect remained significant (P < 0.0001). Seniors who used PYL demonstrated an increased understanding of posthospitalization and home services compared to the control group. © 2017 Society of Hospital Medicine

Comparing Trigger Point Dry Needling and Manual Pressure Technique for the Management of Myofascial Neck/Shoulder Pain: A Randomized Clinical Trial.

PubMed

De Meulemeester, Kayleigh E; Castelein, Birgit; Coppieters, Iris; Barbe, Tom; Cools, Ann; Cagnie, Barbara

2017-01-01

The aim of this study was to investigate short-term and long-term treatment effects of dry needling (DN) and manual pressure (MP) technique with the primary goal of determining if DN has better effects on disability, pain, and muscle characteristics in treating myofascial neck/shoulder pain in women. In this randomized clinical trial, 42 female office workers with myofascial neck/shoulder pain were randomly allocated to either a DN or MP group and received 4 treatments. They were evaluated with the Neck Disability Index, general numeric rating scale, pressure pain threshold, and muscle characteristics before and after treatment. For each outcome parameter, a linear mixed-model analysis was applied to reveal group-by-time interaction effects or main effects for the factor "time." No significant differences were found between DN and MP. In both groups, significant improvement in the Neck Disability Index was observed after 4 treatments and 3 months (P < .001); the general numerical rating scale also significantly decreased after 3 months. After the 4-week treatment program, there was a significant improvement in pain pressure threshold, muscle elasticity, and stiffness. Both treatment techniques lead to short-term and long-term treatment effects. Dry needling was found to be no more effective than MP in the treatment of myofascial neck/shoulder pain. Copyright © 2016. Published by Elsevier Inc.

Natural remananent magnetization acquisition through sediment mixing: theory and implications for relative paleointensity

NASA Astrophysics Data System (ADS)

Egli, Ramon; Zhao, Xiangyu

2015-04-01

We present a general theory on the acquisition of natural remanent magnetizations (NRM) in sediment under the influence of (a) magnetic torques, (b) randomizing torques (e.g. from bioturbation), and (c) torques resulting from interaction forces between remanence carriers and other particles. Dynamic equilibrium between (a) and (b) in the water column and sediment-water interface produce a detrital remanent magnetization (DRM), while much stronger randomizing forces occur in the mixed layer of sediment due to bioturbation forces. These generate a so-called mixing remanent magnetization (MRM), which is stabilized by interaction forces. During the time required to cross the mixed layer, DRM is lost and MRM is acquired at a rate that depends on bioturbation intensity. Both processes are governed by the same MRM lock-in function. The final NRM intensity is controlled mainly by a single parameter defined as the product of rotational diffusion constant and mixed layer thickness, divided by the sedimentation rate. This parameter defines three regimes: (1) slow mixing, leading to DRM preservation and insignificant MRM acquisition, (2) fast mixing with MRM acquisition and full randomization of the original DRM, and (3) intermediate mixing. Because the acquisition efficiency of DRM is expectedly larger than that of a MRM, MRM is particularly sensitive to the mixing rate in case of intermediate regimes, and generates variable NRM acquisition efficiencies. Our model explains (1) lock-in delays that can be matched with empirical reconstructions from paleomagnetic records, (2) the existence of small lock-in depths leading to DRM preservation, (3) NRM acquisition efficiencies of magnetofossil-rich sediments, and (4) relative paleointensity artifacts reported in some recent studies.

Lagrangian particles with mixing. I. Simulating scalar transport

NASA Astrophysics Data System (ADS)

Klimenko, A. Y.

2009-06-01

The physical similarity and mathematical equivalence of continuous diffusion and particle random walk forms one of the cornerstones of modern physics and the theory of stochastic processes. The randomly walking particles do not need to posses any properties other than location in physical space. However, particles used in many models dealing with simulating turbulent transport and turbulent combustion do posses a set of scalar properties and mixing between particle properties is performed to reflect the dissipative nature of the diffusion processes. We show that the continuous scalar transport and diffusion can be accurately specified by means of localized mixing between randomly walking Lagrangian particles with scalar properties and assess errors associated with this scheme. Particles with scalar properties and localized mixing represent an alternative formulation for the process, which is selected to represent the continuous diffusion. Simulating diffusion by Lagrangian particles with mixing involves three main competing requirements: minimizing stochastic uncertainty, minimizing bias introduced by numerical diffusion, and preserving independence of particles. These requirements are analyzed for two limited cases of mixing between two particles and mixing between a large number of particles. The problem of possible dependences between particles is most complicated. This problem is analyzed using a coupled chain of equations that has similarities with Bogolubov-Born-Green-Kirkwood-Yvon chain in statistical physics. Dependences between particles can be significant in close proximity of the particles resulting in a reduced rate of mixing. This work develops further ideas introduced in the previously published letter [Phys. Fluids 19, 031702 (2007)]. Paper I of this work is followed by Paper II [Phys. Fluids 19, 065102 (2009)] where modeling of turbulent reacting flows by Lagrangian particles with localized mixing is specifically considered.

A New Linearized Crank-Nicolson Mixed Element Scheme for the Extended Fisher-Kolmogorov Equation

PubMed Central

Wang, Jinfeng; Li, Hong; He, Siriguleng; Gao, Wei

2013-01-01

We present a new mixed finite element method for solving the extended Fisher-Kolmogorov (EFK) equation. We first decompose the EFK equation as the two second-order equations, then deal with a second-order equation employing finite element method, and handle the other second-order equation using a new mixed finite element method. In the new mixed finite element method, the gradient ∇u belongs to the weaker (L 2(Ω))2 space taking the place of the classical H(div; Ω) space. We prove some a priori bounds for the solution for semidiscrete scheme and derive a fully discrete mixed scheme based on a linearized Crank-Nicolson method. At the same time, we get the optimal a priori error estimates in L 2 and H 1-norm for both the scalar unknown u and the diffusion term w = −Δu and a priori error estimates in (L 2)2-norm for its gradient χ = ∇u for both semi-discrete and fully discrete schemes. PMID:23864831

A new linearized Crank-Nicolson mixed element scheme for the extended Fisher-Kolmogorov equation.

PubMed

Wang, Jinfeng; Li, Hong; He, Siriguleng; Gao, Wei; Liu, Yang

2013-01-01

We present a new mixed finite element method for solving the extended Fisher-Kolmogorov (EFK) equation. We first decompose the EFK equation as the two second-order equations, then deal with a second-order equation employing finite element method, and handle the other second-order equation using a new mixed finite element method. In the new mixed finite element method, the gradient ∇u belongs to the weaker (L²(Ω))² space taking the place of the classical H(div; Ω) space. We prove some a priori bounds for the solution for semidiscrete scheme and derive a fully discrete mixed scheme based on a linearized Crank-Nicolson method. At the same time, we get the optimal a priori error estimates in L² and H¹-norm for both the scalar unknown u and the diffusion term w = -Δu and a priori error estimates in (L²)²-norm for its gradient χ = ∇u for both semi-discrete and fully discrete schemes.

Control for Population Structure and Relatedness for Binary Traits in Genetic Association Studies via Logistic Mixed Models

PubMed Central

Chen, Han; Wang, Chaolong; Conomos, Matthew P.; Stilp, Adrienne M.; Li, Zilin; Sofer, Tamar; Szpiro, Adam A.; Chen, Wei; Brehm, John M.; Celedón, Juan C.; Redline, Susan; Papanicolaou, George J.; Thornton, Timothy A.; Laurie, Cathy C.; Rice, Kenneth; Lin, Xihong

2016-01-01

Linear mixed models (LMMs) are widely used in genome-wide association studies (GWASs) to account for population structure and relatedness, for both continuous and binary traits. Motivated by the failure of LMMs to control type I errors in a GWAS of asthma, a binary trait, we show that LMMs are generally inappropriate for analyzing binary traits when population stratification leads to violation of the LMM’s constant-residual variance assumption. To overcome this problem, we develop a computationally efficient logistic mixed model approach for genome-wide analysis of binary traits, the generalized linear mixed model association test (GMMAT). This approach fits a logistic mixed model once per GWAS and performs score tests under the null hypothesis of no association between a binary trait and individual genetic variants. We show in simulation studies and real data analysis that GMMAT effectively controls for population structure and relatedness when analyzing binary traits in a wide variety of study designs. PMID:27018471

Linear stability analysis of particle-laden hypopycnal plumes

NASA Astrophysics Data System (ADS)

Farenzena, Bruno Avila; Silvestrini, Jorge Hugo

2017-12-01

Gravity-driven riverine outflows are responsible for carrying sediments to the coastal waters. The turbulent mixing in these flows is associated with shear and gravitational instabilities such as Kelvin-Helmholtz, Holmboe, and Rayleigh-Taylor. Results from temporal linear stability analysis of a two-layer stratified flow are presented, investigating the behavior of settling particles and mixing region thickness on the flow stability in the presence of ambient shear. The particles are considered suspended in the transport fluid, and its sedimentation is modeled with a constant valued settling velocity. Three scenarios, regarding the mixing region thickness, were identified: the poorly mixed environment, the strong mixed environment, and intermediate scenario. It was observed that Kelvin-Helmholtz and settling convection modes are the two fastest growing modes depending on the particles settling velocity and the total Richardson number. The second scenario presents a modified Rayleigh-Taylor instability, which is the dominant mode. The third case can have Kelvin-Helmholtz, settling convection, and modified Rayleigh-Taylor modes as the fastest growing mode depending on the combination of parameters.

Longitudinal data analyses using linear mixed models in SPSS: concepts, procedures and illustrations.

PubMed

Shek, Daniel T L; Ma, Cecilia M S

2011-01-05

Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM) are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM) are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models) are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong are presented.

Longitudinal Data Analyses Using Linear Mixed Models in SPSS: Concepts, Procedures and Illustrations

PubMed Central

Shek, Daniel T. L.; Ma, Cecilia M. S.

2011-01-01

Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM) are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM) are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models) are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong are presented. PMID:21218263

A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: I. Robust Linear Optimization and Robust Mixed Integer Linear Optimization

PubMed Central

Li, Zukui; Ding, Ran; Floudas, Christodoulos A.

2011-01-01

Robust counterpart optimization techniques for linear optimization and mixed integer linear optimization problems are studied in this paper. Different uncertainty sets, including those studied in literature (i.e., interval set; combined interval and ellipsoidal set; combined interval and polyhedral set) and new ones (i.e., adjustable box; pure ellipsoidal; pure polyhedral; combined interval, ellipsoidal, and polyhedral set) are studied in this work and their geometric relationship is discussed. For uncertainty in the left hand side, right hand side, and objective function of the optimization problems, robust counterpart optimization formulations induced by those different uncertainty sets are derived. Numerical studies are performed to compare the solutions of the robust counterpart optimization models and applications in refinery production planning and batch process scheduling problem are presented. PMID:21935263

Menu-Driven Solver Of Linear-Programming Problems

NASA Technical Reports Server (NTRS)

Viterna, L. A.; Ferencz, D.

1992-01-01

Program assists inexperienced user in formulating linear-programming problems. A Linear Program Solver (ALPS) computer program is full-featured LP analysis program. Solves plain linear-programming problems as well as more-complicated mixed-integer and pure-integer programs. Also contains efficient technique for solution of purely binary linear-programming problems. Written entirely in IBM's APL2/PC software, Version 1.01. Packed program contains licensed material, property of IBM (copyright 1988, all rights reserved).

Antibacterial efficacy and effect of Morinda citrifolia L. mixed with irreversible hydrocolloid for dental impressions: A randomized controlled trial

PubMed Central

Ahmed, A. Shafath; Charles, P. David; Cholan, R.; Russia, M.; Surya, R.; Jailance, L.

2015-01-01

Aim: This study aimed to evaluate whether the extract of Morinda citrifolia L. mixed with irreversible hydrocolloid powder decreases microbial contamination during impression making without affecting the resulting casts. Materials and Methods: Twenty volunteers were randomly divided into two groups (n = 10). Group A 30 ml extract of M. citrifolia L diluted in 30 ml of water was mixed to make the impression with irreversible hydrocolloid material. Group B 30 ml deionized water was mixed with irreversible hydrocolloid material to make the impressions following which the surface roughness and dimensional stability of casts were evaluated. Results: Extract of M. citrifolia L. mixed with irreversible hydrocolloid decreased the percentage of microorganisms when compared with water (P < 0.001) but did not affect the surface quality or dimensional stability of the casts. Conclusion: Mixing the extract of M. citrifolia L. with irreversible hydrocolloid powder is an alternative method to prevent contamination without sacrificing impression quality. PMID:26538926

The Adolescent Behavioral Activation Program: Adapting Behavioral Activation as a Treatment for Depression in Adolescence.

PubMed

McCauley, Elizabeth; Gudmundsen, Gretchen; Schloredt, Kelly; Martell, Christopher; Rhew, Isaac; Hubley, Samuel; Dimidjian, Sona

2016-01-01

This study aimed to examine implementation feasibility and initial treatment outcomes of a behavioral activation (BA) based treatment for adolescent depression, the Adolescent Behavioral Activation Program (A-BAP). A randomized, controlled trial was conducted with 60 clinically referred adolescents with a depressive disorder who were randomized to receive either 14 sessions of A-BAP or uncontrolled evidenced-based practice for depression. The urban sample was 64% female, predominantly Non-Hispanic White (67%), and had an average age of 14.9 years. Measures of depression, global functioning, activation, and avoidance were obtained through clinical interviews and/or through parent and adolescent self-report at preintervention and end of intervention. Intent-to-treat linear mixed effects modeling and logistic regression analysis revealed that both conditions produced statistically significant improvement from pretreatment to end of treatment in depression, global functioning, and activation and avoidance. There were no significant differences across treatment conditions. These findings provide the first step in establishing the efficacy of BA as a treatment for adolescent depression and support the need for ongoing research on BA as a way to enhance the strategies available for treatment of depression in this population.

Turbulent mixing of a critical fluid: The non-perturbative renormalization

NASA Astrophysics Data System (ADS)

Hnatič, M.; Kalagov, G.; Nalimov, M.

2018-01-01

Non-perturbative Renormalization Group (NPRG) technique is applied to a stochastical model of a non-conserved scalar order parameter near its critical point, subject to turbulent advection. The compressible advecting flow is modeled by a random Gaussian velocity field with zero mean and correlation function 〈υjυi 〉 ∼ (Pji⊥ + αPji∥) /k d + ζ. Depending on the relations between the parameters ζ, α and the space dimensionality d, the model reveals several types of scaling regimes. Some of them are well known (model A of equilibrium critical dynamics and linear passive scalar field advected by a random turbulent flow), but there is a new nonequilibrium regime (universality class) associated with new nontrivial fixed points of the renormalization group equations. We have obtained the phase diagram (d, ζ) of possible scaling regimes in the system. The physical point d = 3, ζ = 4 / 3 corresponding to three-dimensional fully developed Kolmogorov's turbulence, where critical fluctuations are irrelevant, is stable for α ≲ 2.26. Otherwise, in the case of "strong compressibility" α ≳ 2.26, the critical fluctuations of the order parameter become relevant for three-dimensional turbulence. Estimations of critical exponents for each scaling regime are presented.

The effect of random matter density perturbations on the large mixing angle solution to the solar neutrino problem

NASA Astrophysics Data System (ADS)

Guzzo, M. M.; Holanda, P. C.; Reggiani, N.

2003-08-01

The neutrino energy spectrum observed in KamLAND is compatible with the predictions based on the Large Mixing Angle realization of the MSW (Mikheyev-Smirnov-Wolfenstein) mechanism, which provides the best solution to the solar neutrino anomaly. From the agreement between solar neutrino data and KamLAND observations, we can obtain the best fit values of the mixing angle and square difference mass. When doing the fitting of the MSW predictions to the solar neutrino data, it is assumed the solar matter do not have any kind of perturbations, that is, it is assumed the the matter density monothonically decays from the center to the surface of the Sun. There are reasons to believe, nevertheless, that the solar matter density fluctuates around the equilibrium profile. In this work, we analysed the effect on the Large Mixing Angle parameters when the density matter randomically fluctuates around the equilibrium profile, solving the evolution equation in this case. We find that, in the presence of these density perturbations, the best fit values of the mixing angle and the square difference mass assume smaller values, compared with the values obtained for the standard Large Mixing Angle Solution without noise. Considering this effect of the random perturbations, the lowest island of allowed region for KamLAND spectral data in the parameter space must be considered and we call it very-low region.

Turbulence closure for mixing length theories

NASA Astrophysics Data System (ADS)

Jermyn, Adam S.; Lesaffre, Pierre; Tout, Christopher A.; Chitre, Shashikumar M.

2018-05-01

We present an approach to turbulence closure based on mixing length theory with three-dimensional fluctuations against a two-dimensional background. This model is intended to be rapidly computable for implementation in stellar evolution software and to capture a wide range of relevant phenomena with just a single free parameter, namely the mixing length. We incorporate magnetic, rotational, baroclinic, and buoyancy effects exactly within the formalism of linear growth theories with non-linear decay. We treat differential rotation effects perturbatively in the corotating frame using a novel controlled approximation, which matches the time evolution of the reference frame to arbitrary order. We then implement this model in an efficient open source code and discuss the resulting turbulent stresses and transport coefficients. We demonstrate that this model exhibits convective, baroclinic, and shear instabilities as well as the magnetorotational instability. It also exhibits non-linear saturation behaviour, and we use this to extract the asymptotic scaling of various transport coefficients in physically interesting limits.

Separation and reconstruction of high pressure water-jet reflective sound signal based on ICA

NASA Astrophysics Data System (ADS)

Yang, Hongtao; Sun, Yuling; Li, Meng; Zhang, Dongsu; Wu, Tianfeng

2011-12-01

The impact of high pressure water-jet on the different materials target will produce different reflective mixed sound. In order to reconstruct the reflective sound signals distribution on the linear detecting line accurately and to separate the environment noise effectively, the mixed sound signals acquired by linear mike array were processed by ICA. The basic principle of ICA and algorithm of FASTICA were described in detail. The emulation experiment was designed. The environment noise signal was simulated by using band-limited white noise and the reflective sound signal was simulated by using pulse signal. The reflective sound signal attenuation produced by the different distance transmission was simulated by weighting the sound signal with different contingencies. The mixed sound signals acquired by linear mike array were synthesized by using the above simulated signals and were whitened and separated by ICA. The final results verified that the environment noise separation and the reconstruction of the detecting-line sound distribution can be realized effectively.

Partially linear mixed-effects joint models for skewed and missing longitudinal competing risks outcomes.

PubMed

Lu, Tao; Lu, Minggen; Wang, Min; Zhang, Jun; Dong, Guang-Hui; Xu, Yong

2017-12-18

Longitudinal competing risks data frequently arise in clinical studies. Skewness and missingness are commonly observed for these data in practice. However, most joint models do not account for these data features. In this article, we propose partially linear mixed-effects joint models to analyze skew longitudinal competing risks data with missingness. In particular, to account for skewness, we replace the commonly assumed symmetric distributions by asymmetric distribution for model errors. To deal with missingness, we employ an informative missing data model. The joint models that couple the partially linear mixed-effects model for the longitudinal process, the cause-specific proportional hazard model for competing risks process and missing data process are developed. To estimate the parameters in the joint models, we propose a fully Bayesian approach based on the joint likelihood. To illustrate the proposed model and method, we implement them to an AIDS clinical study. Some interesting findings are reported. We also conduct simulation studies to validate the proposed method.

BIODEGRADATION PROBABILITY PROGRAM (BIODEG)

EPA Science Inventory

The Biodegradation Probability Program (BIODEG) calculates the probability that a chemical under aerobic conditions with mixed cultures of microorganisms will biodegrade rapidly or slowly. It uses fragment constants developed using multiple linear and non-linear regressions and d...

Generating synthetic wave climates for coastal modelling: a linear mixed modelling approach

NASA Astrophysics Data System (ADS)

Thomas, C.; Lark, R. M.

2013-12-01

Numerical coastline morphological evolution models require wave climate properties to drive morphological change through time. Wave climate properties (typically wave height, period and direction) may be temporally fixed, culled from real wave buoy data, or allowed to vary in some way defined by a Gaussian or other pdf. However, to examine sensitivity of coastline morphologies to wave climate change, it seems desirable to be able to modify wave climate time series from a current to some new state along a trajectory, but in a way consistent with, or initially conditioned by, the properties of existing data, or to generate fully synthetic data sets with realistic time series properties. For example, mean or significant wave height time series may have underlying periodicities, as revealed in numerous analyses of wave data. Our motivation is to develop a simple methodology to generate synthetic wave climate time series that can change in some stochastic way through time. We wish to use such time series in a coastline evolution model to test sensitivities of coastal landforms to changes in wave climate over decadal and centennial scales. We have worked initially on time series of significant wave height, based on data from a Waverider III buoy located off the coast of Yorkshire, England. The statistical framework for the simulation is the linear mixed model. The target variable, perhaps after transformation (Box-Cox), is modelled as a multivariate Gaussian, the mean modelled as a function of a fixed effect, and two random components, one of which is independently and identically distributed (iid) and the second of which is temporally correlated. The model was fitted to the data by likelihood methods. We considered the option of a periodic mean, the period either fixed (e.g. at 12 months) or estimated from the data. We considered two possible correlation structures for the second random effect. In one the correlation decays exponentially with time. In the second (spherical) model, it cuts off at a temporal range. Having fitted the model, multiple realisations were generated; the random effects were simulated by specifying a covariance matrix for the simulated values, with the estimated parameters. The Cholesky factorisation of the covariance matrix was computed and realizations of the random component of the model generated by pre-multiplying a vector of iid standard Gaussian variables by the lower triangular factor. The resulting random variate was added to the mean value computed from the fixed effects, and the result back-transformed to the original scale of the measurement. Realistic simulations result from approach described above. Background exploratory data analysis was undertaken on 20-day sets of 30-minute buoy data, selected from days 5-24 of months January, April, July, October, 2011, to elucidate daily to weekly variations, and to keep numerical analysis tractable computationally. Work remains to be undertaken to develop suitable models for synthetic directional data. We suggest that the general principles of the method will have applications in other geomorphological modelling endeavours requiring time series of stochastically variable environmental parameters.

CFD simulation of vertical linear motion mixing in anaerobic digester tanks.

PubMed

Meroney, Robert N; Sheker, Robert E

2014-09-01

Computational fluid dynamics (CFD) was used to simulate the mixing characteristics of a small circular anaerobic digester tank (diameter 6 m) equipped sequentially with 13 different plunger type vertical linear motion mixers and two different type internal draft-tube mixers. Rates of mixing of step injection of tracers were calculated from which active volume (AV) and hydraulic retention time (HRT) could be calculated. Washout characteristics were compared to analytic formulae to estimate any presence of partial mixing, dead volume, short-circuiting, or piston flow. Active volumes were also estimated based on tank regions that exceeded minimum velocity criteria. The mixers were ranked based on an ad hoc criteria related to the ratio of AV to unit power (UP) or AV/UP. The best plunger mixers were found to behave about the same as the conventional draft-tube mixers of similar UP.

Adding statistical regularity results in a global slowdown in visual search.

PubMed

Vaskevich, Anna; Luria, Roy

2018-05-01

Current statistical learning theories predict that embedding implicit regularities within a task should further improve online performance, beyond general practice. We challenged this assumption by contrasting performance in a visual search task containing either a consistent-mapping (regularity) condition, a random-mapping condition, or both conditions, mixed. Surprisingly, performance in a random visual search, without any regularity, was better than performance in a mixed design search that contained a beneficial regularity. This result was replicated using different stimuli and different regularities, suggesting that mixing consistent and random conditions leads to an overall slowing down of performance. Relying on the predictive-processing framework, we suggest that this global detrimental effect depends on the validity of the regularity: when its predictive value is low, as it is in the case of a mixed design, reliance on all prior information is reduced, resulting in a general slowdown. Our results suggest that our cognitive system does not maximize speed, but rather continues to gather and implement statistical information at the expense of a possible slowdown in performance. Copyright © 2018 Elsevier B.V. All rights reserved.

Strengthen forensic entomology in court--the need for data exploration and the validation of a generalised additive mixed model.

PubMed

Baqué, Michèle; Amendt, Jens

2013-01-01

Developmental data of juvenile blow flies (Diptera: Calliphoridae) are typically used to calculate the age of immature stages found on or around a corpse and thus to estimate a minimum post-mortem interval (PMI(min)). However, many of those data sets don't take into account that immature blow flies grow in a non-linear fashion. Linear models do not supply a sufficient reliability on age estimates and may even lead to an erroneous determination of the PMI(min). According to the Daubert standard and the need for improvements in forensic science, new statistic tools like smoothing methods and mixed models allow the modelling of non-linear relationships and expand the field of statistical analyses. The present study introduces into the background and application of these statistical techniques by analysing a model which describes the development of the forensically important blow fly Calliphora vicina at different temperatures. The comparison of three statistical methods (linear regression, generalised additive modelling and generalised additive mixed modelling) clearly demonstrates that only the latter provided regression parameters that reflect the data adequately. We focus explicitly on both the exploration of the data--to assure their quality and to show the importance of checking it carefully prior to conducting the statistical tests--and the validation of the resulting models. Hence, we present a common method for evaluating and testing forensic entomological data sets by using for the first time generalised additive mixed models.

The effect of a yoga intervention on alcohol and drug abuse risk in veteran and civilian women with posttraumatic stress disorder.

PubMed

Reddy, Shivani; Dick, Alexandra M; Gerber, Megan R; Mitchell, Karen

2014-10-01

Individuals with posttraumatic stress disorder (PTSD) often exhibit high-risk substance use behaviors. Complementary and alternative therapies are increasingly used for mental health disorders, although evidence is sparse. Investigate the effect of a yoga intervention on alcohol and drug abuse behaviors in women with PTSD. Secondary outcomes include changes in PTSD symptom perception and management and initiation of evidence-based therapies. The current investigation analyzed data from a pilot randomized controlled trial comparing a 12-session yoga intervention with an assessment control for women age 18 to 65 years with PTSD. The Alcohol Use Disorder Identification Test (AUDIT) and Drug Use Disorder Identification Test (DUDIT) were administered at baseline, after the intervention, and a 1-month follow-up. Linear mixed models were used to test the significance of the change in AUDIT and DUDIT scores over time. Treatment-seeking questions were compared by using Fisher exact tests. The mean AUDIT and DUDIT scores decreased in the yoga group; in the control group, mean AUDIT score increased while mean DUDIT score remained stable. In the linear mixed models, the change in AUDIT and DUDIT scores over time did not differ significantly by group. Most yoga group participants reported a reduction in symptoms and improved symptom management. All participants expressed interest in psychotherapy for PTSD, although only two participants, both in the yoga group, initiated therapy. Results from this pilot study suggest that a specialized yoga therapy may play a role in attenuating the symptoms of PTSD, reducing risk of alcohol and drug use, and promoting interest in evidence-based psychotherapy. Further research is needed to confirm and evaluate the strength of these effects.

Measurements of CO2 exchange with an automated chamber system throughout the year: challenges in measuring night-time respiration on porous peat soil

NASA Astrophysics Data System (ADS)

Koskinen, M.; Minkkinen, K.; Ojanen, P.; Kämäräinen, M.; Laurila, T.; Lohila, A.

2014-01-01

We built an automatic chamber system to measure greenhouse gas (GHG) exchange in forested peatland ecosystems. We aimed to build a system robust enough which would work throughout the year and could measure through a changing snowpack in addition to producing annual GHG fluxes by integrating the measurements without the need of using models. The system worked rather well throughout the year, but it was not service free. Gap filling of data was still necessary. We observed problems in carbon dioxide (CO2) respiration flux estimation during calm summer nights, when a CO2 concentration gradient from soil/moss system to atmosphere builds up. Chambers greatly overestimated the night-time respiration. This was due to the disturbance caused by the chamber to the soil-moss CO2 gradient and consequent initial pulse of CO2 to the chamber headspace. We tested different flux calculation and measurement methods to solve this problem. The estimated flux was strongly dependent on (1) the starting point of the fit after closing the chamber, (2) the length of the fit, (3) the type of the fit (linear and polynomial), (4) the speed of the fan mixing the air inside the chamber, and (5) atmospheric turbulence (friction velocity, u*). The best fitting method (the most robust, least random variation) for respiration measurements on our sites was linear fitting with the period of 120-240 s after chamber closure. Furthermore, the fan should be adjusted to spin at minimum speed to avoid the pulse-effect, but it should be kept on to ensure mixing. If night-time problems cannot be solved, emissions can be estimated using daytime data from opaque chambers.

The impact of the National Denture Service on oral health-related quality of life among poor elders.

PubMed

Ha, J E; Heo, Y J; Jin, B H; Paik, D I; Bae, K H

2012-08-01

The objective of this study was to assess the effects of the Korean National Denture Service (NDS) for poor elderly people requiring dentures on oral health-related quality of life (OHRQOL). Data from follow-up studies were collected from 439 subjects at eight public health centres who answered every question of a questionnaire, and the OHRQOL was measured at the baseline and at 3-month follow-up after receiving the NDS according to the type of denture provision. The multivariate linear mixed model with a public health centre as a random effect for the score change of Oral Health Impact Profile (OHIP)-14K was carried out to confirm the factors related to the improvement in OHRQOL. The mean OHIP-14K was 28.60 at the baseline time points, and there was a decrease in the OHIP-14 scores to 21.14 ± 12.52 at the 3-month follow-up of the removable partial denture beneficiaries. The changes in OHIP-14K among complete denture beneficiaries were 21.53 ± 12.01 for previously dentate subjects and 22.54 ± 11.12 for edentate subjects. The multivariate linear mixed model of dentate subjects demonstrated that the improvement in the OHRQOL was associated with the number of remaining teeth, satisfaction with denture and self-reported oral health status after 3 months. In the case of the edentate model, satisfaction with denture was the only factor related to the improvement in OHRQOL. This study revealed considerable improvement in OHRQOL among poor elderly people after NDS. Satisfaction with provision of dentures was associated with improvement in the OHRQOL. © 2012 Blackwell Publishing Ltd.

How Well Can Saliency Models Predict Fixation Selection in Scenes Beyond Central Bias? A New Approach to Model Evaluation Using Generalized Linear Mixed Models.

PubMed

Nuthmann, Antje; Einhäuser, Wolfgang; Schütz, Immo

2017-01-01

Since the turn of the millennium, a large number of computational models of visual salience have been put forward. How best to evaluate a given model's ability to predict where human observers fixate in images of real-world scenes remains an open research question. Assessing the role of spatial biases is a challenging issue; this is particularly true when we consider the tendency for high-salience items to appear in the image center, combined with a tendency to look straight ahead ("central bias"). This problem is further exacerbated in the context of model comparisons, because some-but not all-models implicitly or explicitly incorporate a center preference to improve performance. To address this and other issues, we propose to combine a-priori parcellation of scenes with generalized linear mixed models (GLMM), building upon previous work. With this method, we can explicitly model the central bias of fixation by including a central-bias predictor in the GLMM. A second predictor captures how well the saliency model predicts human fixations, above and beyond the central bias. By-subject and by-item random effects account for individual differences and differences across scene items, respectively. Moreover, we can directly assess whether a given saliency model performs significantly better than others. In this article, we describe the data processing steps required by our analysis approach. In addition, we demonstrate the GLMM analyses by evaluating the performance of different saliency models on a new eye-tracking corpus. To facilitate the application of our method, we make the open-source Python toolbox "GridFix" available.

Feed intake, digestibility and energy partitioning in beef cattle fed diets with cassava pulp instead of rice straw.

PubMed

Kongphitee, Kanokwan; Sommart, Kritapon; Phonbumrung, Thamrongsak; Gunha, Thidarat; Suzuki, Tomoyuki

2018-03-13

This study was conducted to assess the effects of replacing rice straw with different proportions of cassava pulp on growth performance, feed intake, digestibility, rumen microbial population, energy partitioning and efficiency of metabolizable energy utilization in beef cattle. Eighteen yearling Thai native beef cattle (Bos indicus) with an average initial body weight of 98.3 ± 12.8 kg were allocated to one of three dietary treatments and fed ad libitum for 149 days in a randomized complete block design. Three dietary treatments using different proportions of cassava pulp (100, 300 and 500 g/kg dry matter basis) instead of rice straw as a base in a fermented total mixed ration were applied. Animals were placed in a metabolic pen equipped with a ventilated head box respiration system to determine total digestibility and energy balance. The average daily weight gain, digestible intake and apparent digestibility of dry matter, organic matter and non-fiber carbohydrate, total protozoa, energy intake, energy retention and energy efficiency increased linearly (p < 0.05) with an increasing proportion of cassava pulp in the diet, whereas the three main types of fibrolytic bacteria and energy excretion in the urine (p < 0.05) decreased. The metabolizable energy requirement for the maintenance of yearling Thai native cattle, determined by a linear regression analysis, was 399 kJ/kg BW0.75, with an efficiency of metabolizable energy utilization for growth of 0.86. Our results demonstrated that increasing the proportion of cassava pulp up to 500 g/kg of dry matter as a base in a fermented total mixed ration is an effective strategy for improving productivity in zebu cattle.

Group-Level EEG-Processing Pipeline for Flexible Single Trial-Based Analyses Including Linear Mixed Models

PubMed Central

Frömer, Romy; Maier, Martin; Abdel Rahman, Rasha

2018-01-01

Here we present an application of an EEG processing pipeline customizing EEGLAB and FieldTrip functions, specifically optimized to flexibly analyze EEG data based on single trial information. The key component of our approach is to create a comprehensive 3-D EEG data structure including all trials and all participants maintaining the original order of recording. This allows straightforward access to subsets of the data based on any information available in a behavioral data structure matched with the EEG data (experimental conditions, but also performance indicators, such accuracy or RTs of single trials). In the present study we exploit this structure to compute linear mixed models (LMMs, using lmer in R) including random intercepts and slopes for items. This information can easily be read out from the matched behavioral data, whereas it might not be accessible in traditional ERP approaches without substantial effort. We further provide easily adaptable scripts for performing cluster-based permutation tests (as implemented in FieldTrip), as a more robust alternative to traditional omnibus ANOVAs. Our approach is particularly advantageous for data with parametric within-subject covariates (e.g., performance) and/or multiple complex stimuli (such as words, faces or objects) that vary in features affecting cognitive processes and ERPs (such as word frequency, salience or familiarity), which are sometimes hard to control experimentally or might themselves constitute variables of interest. The present dataset was recorded from 40 participants who performed a visual search task on previously unfamiliar objects, presented either visually intact or blurred. MATLAB as well as R scripts are provided that can be adapted to different datasets. PMID:29472836

Community-based comprehensive intervention for people with schizophrenia in Guangzhou, China: Effects on clinical symptoms, social functioning, internalized stigma and discrimination.

PubMed

Li, Jie; Huang, Yuan-Guang; Ran, Mao-Sheng; Fan, Yu; Chen, Wen; Evans-Lacko, Sara; Thornicroft, Graham

2018-04-01

Comprehensive interventions including components of stigma and discrimination reduction in schizophrenia in low- and middle-income countries (LMICs) are lacking. We developed a community-based comprehensive intervention to evaluate its effects on clinical symptoms, social functioning, internalized stigma and discrimination among patients with schizophrenia. A randomized controlled trial including an intervention group (n = 169) and a control group (n = 158) was performed. The intervention group received comprehensive intervention (strategies against stigma and discrimination, psycho-education, social skills training and cognitive behavioral therapy) and the control group received face to face interview. Both lasted for nine months. Participants were measured at baseline, 6 months and 9 months using the Internalized Stigma of Mental Illness scale (ISMI), Discrimination and Stigma Scale (DISC-12), Global Assessment of Functioning (GAF), Schizophrenia Quality of Life Scale (SQLS), Self-Esteem Scale (SES), Brief Psychiatric Rating Scale (BPRS) and PANSS negative scale (PANSS-N). Insight and medication compliance were evaluated by senior psychiatrists. Data were analyzed by descriptive statistics, t-test, chi-square test or Fisher's exact test. Linear Mixed Models were used to show intervention effectiveness on scales. General Linear Mixed Models with multinomial logistic link function were used to assess the effectiveness on medication compliance and insight. We found a significant reduction on anticipated discrimination, BPRS and PANSS-N total scores, and an elevation on overcoming stigma and GAF in the intervention group after 9 months. These suggested the intervention may be effective in reducing anticipated discrimination, increasing skills overcoming stigma as well as improving clinical symptoms and social functioning in Chinese patients with schizophrenia. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Changing perception: facial reanimation surgery improves attractiveness and decreases negative facial perception.

PubMed

Dey, Jacob K; Ishii, Masaru; Boahene, Kofi D O; Byrne, Patrick J; Ishii, Lisa E

2014-01-01

Determine the effect of facial reanimation surgery on observer-graded attractiveness and negative facial perception of patients with facial paralysis. Randomized controlled experiment. Ninety observers viewed images of paralyzed faces, smiling and in repose, before and after reanimation surgery, as well as normal comparison faces. Observers rated the attractiveness of each face and characterized the paralyzed faces by rating severity, disfigured/bothersome, and importance to repair. Iterated factor analysis indicated these highly correlated variables measure a common domain, so they were combined to create the disfigured, important to repair, bothersome, severity (DIBS) factor score. Mixed effects linear regression determined the effect of facial reanimation surgery on attractiveness and DIBS score. Facial paralysis induces an attractiveness penalty of 2.51 on a 10-point scale for faces in repose and 3.38 for smiling faces. Mixed effects linear regression showed that reanimation surgery improved attractiveness for faces both in repose and smiling by 0.84 (95% confidence interval [CI]: 0.67, 1.01) and 1.24 (95% CI: 1.07, 1.42) respectively. Planned hypothesis tests confirmed statistically significant differences in attractiveness ratings between postoperative and normal faces, indicating attractiveness was not completely normalized. Regression analysis also showed that reanimation surgery decreased DIBS by 0.807 (95% CI: 0.704, 0.911) for faces in repose and 0.989 (95% CI: 0.886, 1.093), an entire standard deviation, for smiling faces. Facial reanimation surgery increases attractiveness and decreases negative facial perception of patients with facial paralysis. These data emphasize the need to optimize reanimation surgery to restore not only function, but also symmetry and cosmesis to improve facial perception and patient quality of life. © 2013 The American Laryngological, Rhinological and Otological Society, Inc.

Functional and motor outcome 5 years after stroke is equivalent to outcome at 2 months: follow-up of the collaborative evaluation of rehabilitation in stroke across Europe.

PubMed

Meyer, Sarah; Verheyden, Geert; Brinkmann, Nadine; Dejaeger, Eddy; De Weerdt, Willy; Feys, Hilde; Gantenbein, Andreas R; Jenni, Walter; Laenen, Annouschka; Lincoln, Nadina; Putman, Koen; Schuback, Birgit; Schupp, Wilfried; Thijs, Vincent; De Wit, Liesbet

2015-06-01

Recovery of patients within the first 6 months after stroke is well documented, but there has been little research on long-term recovery. The aim of this study was to analyze functional and motor recovery between admission to rehabilitation centres and 5 years after stroke. This follow-up of the Collaborative Evaluation of Rehabilitation in Stroke Across Europe study, included patients from 4 European rehabilitation centres. Patients were assessed on admission, at 2 and 6 months, and 5 years after stroke, using the Barthel Index, Rivermead Motor Assessment Gross Function, Leg and Trunk function, and Arm function. Linear mixed models were used, corrected for baseline characteristics. To account for the drop-out during follow-up, the analysis is likelihood-based (assumption of missingness at random). A total of 532 patients were included in this study, of which 238 were followed up at 5 years post stroke. Mean age at stroke onset was 69 (±10 SD) years, 53% were men, 84% had ischemic strokes, and 53% had left-sided motor impairment. Linear mixed model analysis revealed a significant deterioration for all 4 outcomes between 6 months and 5 years (P<0.0001). Scores at 2 months were not statistically significant different from scores at 5 years after stroke. Higher age (P<0.0001) and increasing stroke severity on admission (P<0.0001) negatively affected long-term functional and motor recovery. Five-year follow-up revealed deterioration in functional and motor outcome, with a return to the level measured at 2 months. Increasing age and increasing stroke severity negatively affected recovery up to 5 years after stroke. © 2015 American Heart Association, Inc.

Tachydysrhythmia treatment and adverse events in patients with wolff-Parkinson-white syndrome.

PubMed

Siegelman, Jeffrey N; Marill, Keith A; Adler, Jonathan N

2014-09-01

Current guidelines recommend avoiding atrioventricular-nodal blocking agents (AVNB) when treating tachydysrhythmias in Wolff-Parkinson-White syndrome (WPW) patients. We investigated medications selected and resulting outcomes for patients with tachydysrhythmias and WPW. In this single-center retrospective cohort study, we searched a hospital-wide database for the following inclusion criteria: WPW, tachycardia, and intravenous antidysrhythmics. The composite outcome of adverse events was acceleration of tachycardia, new hypotension, new malignant dysrhythmia, and cardioversion. The difference in binomial proportions of patients meeting the composite outcome after AVNB or non-AVNB (NAVNB) treatment was calculated after dividing the groups by QRS duration. A random-effects mixed linear analysis was performed to analyze the vital sign response. The initial database search yielded 1158 patient visits, with 60 meeting inclusion criteria. Patients' median age was 52.5 years; 53% were male, 43% presented in wide complex tachycardia (WCT), with 75% in atrial fibrillation (AF) or flutter. AVNBs were administered in 42 (70%) patient visits. For those patients with WCT in AF, the difference in proportions of patients meeting the composite outcome after AVNBs vs. NAVNBs treatment was an increase of 3% (95% confidence interval [CI] -39%-49%), and for those with narrow complex AF it was a decrease of 13% (95% CI -37%-81%). No instances of malignant dysrhythmia occurred. Mixed linear analysis showed no statistically significant effects on heart rate, though suggested a trend toward increasing heart rate after AVNB in wide complex AF. In this sample of WPW-associated tachydysrhythmia patients, many were treated with AVNBs. The composite outcome was similarly met after use of either AVNB or NAVNB, and no malignant dysrhythmias were observed. Copyright © 2014 Elsevier Inc. All rights reserved.

Mixed linear-non-linear inversion of crustal deformation data: Bayesian inference of model, weighting and regularization parameters

NASA Astrophysics Data System (ADS)

Fukuda, Jun'ichi; Johnson, Kaj M.

2010-06-01

We present a unified theoretical framework and solution method for probabilistic, Bayesian inversions of crustal deformation data. The inversions involve multiple data sets with unknown relative weights, model parameters that are related linearly or non-linearly through theoretic models to observations, prior information on model parameters and regularization priors to stabilize underdetermined problems. To efficiently handle non-linear inversions in which some of the model parameters are linearly related to the observations, this method combines both analytical least-squares solutions and a Monte Carlo sampling technique. In this method, model parameters that are linearly and non-linearly related to observations, relative weights of multiple data sets and relative weights of prior information and regularization priors are determined in a unified Bayesian framework. In this paper, we define the mixed linear-non-linear inverse problem, outline the theoretical basis for the method, provide a step-by-step algorithm for the inversion, validate the inversion method using synthetic data and apply the method to two real data sets. We apply the method to inversions of multiple geodetic data sets with unknown relative data weights for interseismic fault slip and locking depth. We also apply the method to the problem of estimating the spatial distribution of coseismic slip on faults with unknown fault geometry, relative data weights and smoothing regularization weight.

The Effects of Linear and Modified Linear Programed Materials on the Achievement of Slow Learners in Tenth Grade BSCS Special Materials Biology.

ERIC Educational Resources Information Center

Moody, John Charles

Assessed were the effects of linear and modified linear programed materials on the achievement of slow learners in tenth grade Biological Sciences Curriculum Study (BSCS) Special Materials biology. Two hundred and six students were randomly placed into four programed materials formats: linear programed materials, modified linear program with…

Random parameter models for accident prediction on two-lane undivided highways in India.

PubMed

Dinu, R R; Veeraragavan, A

2011-02-01

Generalized linear modeling (GLM), with the assumption of Poisson or negative binomial error structure, has been widely employed in road accident modeling. A number of explanatory variables related to traffic, road geometry, and environment that contribute to accident occurrence have been identified and accident prediction models have been proposed. The accident prediction models reported in literature largely employ the fixed parameter modeling approach, where the magnitude of influence of an explanatory variable is considered to be fixed for any observation in the population. Similar models have been proposed for Indian highways too, which include additional variables representing traffic composition. The mixed traffic on Indian highways comes with a lot of variability within, ranging from difference in vehicle types to variability in driver behavior. This could result in variability in the effect of explanatory variables on accidents across locations. Random parameter models, which can capture some of such variability, are expected to be more appropriate for the Indian situation. The present study is an attempt to employ random parameter modeling for accident prediction on two-lane undivided rural highways in India. Three years of accident history, from nearly 200 km of highway segments, is used to calibrate and validate the models. The results of the analysis suggest that the model coefficients for traffic volume, proportion of cars, motorized two-wheelers and trucks in traffic, and driveway density and horizontal and vertical curvatures are randomly distributed across locations. The paper is concluded with a discussion on modeling results and the limitations of the present study. Copyright © 2010 Elsevier Ltd. All rights reserved.

Momentary Effects of Exposure to Pro-Smoking Media on College Students’ Future Smoking Risk

PubMed Central

Shadel, William G.; Martino, Steven C.; Setodji, Claude; Scharf, Deborah

2012-01-01

Objective This study used ecological momentary assessment to examine acute changes in college students’ future smoking risk as a function of their exposure to pro-smoking media (e.g., smoking in movies, paid advertising, point-of-sale promotions). Methods A sample of 135 college students (ever and never smokers) carried handheld computers for 21 days, recording their exposures to all forms of pro-smoking media during the assessment period. They also responded to three investigator-initiated control prompts during each day of the assessment period (i.e., programmed to occur randomly). After each pro-media smoking exposure and after each random control prompt they answered questions that measured their risk of future smoking. Responses between pro-smoking media encounters were compared to responses made during random control prompts. Results Compliance with the study protocol was high, with participants responding to over 83% of all random prompts. Participants recorded nearly three encounters with pro-smoking media each week. Results of linear mixed modeling indicated that all participants had higher future smoking risk following exposure to pro-smoking media compared with control prompts (p < 0.05); this pattern of response did not differ between ever and never smokers (p = 0.769). Additional modeling of the variances around participants’ risk of future smoking revealed that the response of never smokers to pro-smoking media was significantly more variable than the response of ever smokers. Conclusions Exposure to pro-smoking media is associated with acute changes in future smoking risk, and never smokers and ever smokers respond differently to these exposures. PMID:22353027

Examination of Cognitive Function During Six Months of Calorie Restriction: Results of a Randomized Controlled Trial

PubMed Central

Martin, Corby K.; Anton, Stephen D.; Han, Hongmei; York-Crowe, Emily; Redman, Leanne M.; Ravussin, Eric; Williamson, Donald A.

2009-01-01

Background Calorie restriction increases longevity in many organisms, and calorie restriction or its mimetic might increase longevity in humans. It is unclear if calorie restriction/dieting contributes to cognitive impairment. During this randomized controlled trial, the effect of 6 months of calorie restriction on cognitive functioning was tested. Methods Participants (n = 48) were randomized to one of four groups: (1) control (weight maintenance), (2) calorie restriction (CR; 25% restriction), (3) CR plus structured exercise (CR + EX, 12.5% restriction plus 12.5% increased energy expenditure via exercise), or (4) low-calorie diet (LCD; 890 kcal/d diet until 15% weight loss, followed by weight maintenance). Cognitive tests (verbal memory, visual memory, attention/concentration) were conducted at baseline and months 3 and 6. Mixed linear models tested if cognitive function changed significantly from baseline to months 3 and 6, and if this change differed by group. Correlation analysis was used to determine if average daily energy deficit (quantified from change in body energy stores) was associated with change in cognitive test performance for the three dieting groups combined. Results No consistent pattern of verbal memory, visual retention/memory, or attention/concentration deficits emerged during the trial. Daily energy deficit was not significantly associated with change in cognitive test performance. Conclusions This randomized controlled trial suggests that calorie restriction/dieting was not associated with a consistent pattern of cognitive impairment. These conclusions must be interpreted in the context of study limitations, namely small sample size and limited statistical power. Previous reports of cognitive impairment might reflect sampling biases or information processing biases. PMID:17518698

How preview space/time translates into preview cost/benefit for fixation durations during reading.

PubMed

Kliegl, Reinhold; Hohenstein, Sven; Yan, Ming; McDonald, Scott A

2013-01-01

Eye-movement control during reading depends on foveal and parafoveal information. If the parafoveal preview of the next word is suppressed, reading is less efficient. A linear mixed model (LMM) reanalysis of McDonald (2006) confirmed his observation that preview benefit may be limited to parafoveal words that have been selected as the saccade target. Going beyond the original analyses, in the same LMM, we examined how the preview effect (i.e., the difference in single-fixation duration, SFD, between random-letter and identical preview) depends on the gaze duration on the pretarget word and on the amplitude of the saccade moving the eye onto the target word. There were two key results: (a) The shorter the saccade amplitude (i.e., the larger preview space), the shorter a subsequent SFD with an identical preview; this association was not observed with a random-letter preview. (b) However, the longer the gaze duration on the pretarget word, the longer the subsequent SFD on the target, with the difference between random-letter string and identical previews increasing with preview time. A third pattern-increasing cost of a random-letter string in the parafovea associated with shorter saccade amplitudes-was observed for target gaze durations. Thus, LMMs revealed that preview effects, which are typically summarized under "preview benefit", are a complex mixture of preview cost and preview benefit and vary with preview space and preview time. The consequence for reading is that parafoveal preview may not only facilitate, but also interfere with lexical access.

Transportability of an Evidence-Based Early Childhood Intervention in a Low-Income African Country: Results of a Cluster Randomized Controlled Study.

PubMed

Huang, Keng-Yen; Nakigudde, Janet; Rhule, Dana; Gumikiriza-Onoria, Joy Louise; Abura, Gloria; Kolawole, Bukky; Ndyanabangi, Sheila; Kim, Sharon; Seidman, Edward; Ogedegbe, Gbenga; Brotman, Laurie Miller

2017-11-01

Children in Sub-Saharan Africa (SSA) are burdened by significant unmet mental health needs. Despite the successes of numerous school-based interventions for promoting child mental health, most evidence-based interventions (EBIs) are not available in SSA. This study investigated the implementation quality and effectiveness of one component of an EBI from a developed country (USA) in a SSA country (Uganda). The EBI component, Professional Development, was provided by trained Ugandan mental health professionals to Ugandan primary school teachers. It included large-group experiential training and small-group coaching to introduce and support a range of evidence-based practices (EBPs) to create nurturing and predictable classroom experiences. The study was guided by the Consolidated Framework for Implementation Research, the Teacher Training Implementation Model, and the RE-AIM evaluation framework. Effectiveness outcomes were studied using a cluster randomized design, in which 10 schools were randomized to intervention and wait-list control conditions. A total of 79 early childhood teachers participated. Teacher knowledge and the use of EBPs were assessed at baseline and immediately post-intervention (4-5 months later). A sample of 154 parents was randomly selected to report on child behavior at baseline and post-intervention. Linear mixed effect modeling was applied to examine effectiveness outcomes. Findings support the feasibility of training Ugandan mental health professionals to provide Professional Development for Ugandan teachers. Professional Development was delivered with high levels of fidelity and resulted in improved teacher EBP knowledge and the use of EBPs in the classroom, and child social competence.

Empirical Models for the Shielding and Reflection of Jet Mixing Noise by a Surface

NASA Technical Reports Server (NTRS)

Brown, Cliff

2015-01-01

Empirical models for the shielding and refection of jet mixing noise by a nearby surface are described and the resulting models evaluated. The flow variables are used to non-dimensionalize the surface position variables, reducing the variable space and producing models that are linear function of non-dimensional surface position and logarithmic in Strouhal frequency. A separate set of coefficients are determined at each observer angle in the dataset and linear interpolation is used to for the intermediate observer angles. The shielding and rejection models are then combined with existing empirical models for the jet mixing and jet-surface interaction noise sources to produce predicted spectra for a jet operating near a surface. These predictions are then evaluated against experimental data.

Empirical Models for the Shielding and Reflection of Jet Mixing Noise by a Surface

NASA Technical Reports Server (NTRS)

Brown, Clifford A.

2016-01-01

Empirical models for the shielding and reflection of jet mixing noise by a nearby surface are described and the resulting models evaluated. The flow variables are used to non-dimensionalize the surface position variables, reducing the variable space and producing models that are linear function of non-dimensional surface position and logarithmic in Strouhal frequency. A separate set of coefficients are determined at each observer angle in the dataset and linear interpolation is used to for the intermediate observer angles. The shielding and reflection models are then combined with existing empirical models for the jet mixing and jet-surface interaction noise sources to produce predicted spectra for a jet operating near a surface. These predictions are then evaluated against experimental data.

Size differences in migrant sandpiper flocks: ghosts in ephemeral guilds

USGS Publications Warehouse

Eldridge, J.L.; Johnson, D.H.

1988-01-01

Scolopacid sandpipers were studied from 1980 until 1984 during spring migration in North Dakota. Common species foraging together in mixed-species flocks differed in bill length most often by 20 to 30 percent (ratios from 1.2:1 to 1.3:1). Observed flocks were compared to computer generated flocks drawn from three source pools of Arctic-nesting sandpipers. The source pools included 51 migrant species from a global pool, 33 migrant species from a Western Hemisphere pool, and 13 species that migrated through North Dakota. The observed flocks formed randomly from the available species that used the North Dakota migration corridor but the North Dakota species were not a random selection from the Western Hemisphere and global pools of Arctic-nesting scolopacid sandpipers. In short, the ephemeral, mixed-species foraging flocks that we observed in North Dakota were random mixes from a non-random pool. The size-ratio distributions were consistent with the interpretation that use of this migration corridor by sandpipers has been influenced by some form of size-related selection such as competition.

Practicing Field Hockey Skills Along the Contextual Interference Continuum: A Comparison of Five Practice Schedules

PubMed Central

Cheong, Jadeera Phaik Geok; Lay, Brendan; Grove, J. Robert; Medic, Nikola; Razman, Rizal

2012-01-01

To overcome the weakness of the contextual interference (CI) effect within applied settings, Brady, 2008 recommended that the amount of interference be manipulated. This study investigated the effect of five practice schedules on the learning of three field hockey skills. Fifty-five pre-university students performed a total of 90 trials for each skill under blocked, mixed or random practice orders. Results showed a significant time effect with all five practice conditions leading to improvements in acquisition and learning of the skills. No significant differences were found between the groups. The findings of the present study did not support the CI effect and suggest that either blocked, mixed, or random practice schedules can be used effectively when structuring practice for beginners. Key pointsThe contextual interference effect did not surface when using sport skills.There appears to be no difference between blocked and random practice schedules in the learning of field hockey skills.Low (blocked), moderate (mixed) or high (random) interference practice schedules can be used effectively when conducting a multiple skill practice session for beginners. PMID:24149204

Practicing field hockey skills along the contextual interference continuum: a comparison of five practice schedules.

PubMed

Cheong, Jadeera Phaik Geok; Lay, Brendan; Grove, J Robert; Medic, Nikola; Razman, Rizal

2012-01-01

To overcome the weakness of the contextual interference (CI) effect within applied settings, Brady, 2008 recommended that the amount of interference be manipulated. This study investigated the effect of five practice schedules on the learning of three field hockey skills. Fifty-five pre-university students performed a total of 90 trials for each skill under blocked, mixed or random practice orders. Results showed a significant time effect with all five practice conditions leading to improvements in acquisition and learning of the skills. No significant differences were found between the groups. The findings of the present study did not support the CI effect and suggest that either blocked, mixed, or random practice schedules can be used effectively when structuring practice for beginners. Key pointsThe contextual interference effect did not surface when using sport skills.There appears to be no difference between blocked and random practice schedules in the learning of field hockey skills.Low (blocked), moderate (mixed) or high (random) interference practice schedules can be used effectively when conducting a multiple skill practice session for beginners.

Association between chewing-stimulated salivary flow under the effects of atropine and mixing ability assessed using a color-changeable chewing gum.

PubMed

Kubota, Chieko; Kanazawa, Manabu; Hama, Yohei; Komagamine, Yuriko; Minakuchi, Shunsuke

2017-10-01

To assess the time course of chewing-stimulated salivary flow after oral atropine administration, and determine the association between chewing-stimulated salivary flow and mixing ability using color-changeable chewing gum in dentate adults. Ten healthy dentate adults were administered 1mg oral atropine to induce mouth dryness. The subjects' chewing-stimulated salivary flow was assessed using the Saxon test. They were then asked to rinse their mouth with tap water for 15s, and to chew on color-changeable chewing gum for 60s at a constant rate of 60 cycles per min. This procedure was performed before, and at 10-min intervals for up to 120min after the atropine administration. The experiment was repeated after 1 week. Steel's test was used to compare the chewing-stimulated salivary flow rates at each time point after atropine administration with the baseline value. The effect of the stimulated salivary flow rates on the degree of color change was analyzed using linear mixed effects models, with the stimulated salivary flow rates as fixed factors and subjects as the random factor. Chewing-stimulated salivary flow showed a significant decrease from 50 to 120min after oral atropine administration (P<0.05) and the amount of chewing-stimulated salivary flow had a significant effect on the color change of the color-changeable chewing gum (P<0.001). We observed a decrease in stimulated salivary flow after orally administering 1mg atropine, and a positive association between mixing ability using color-changeable chewing gum and chewing-stimulated salivary flow in dentate subjects. Copyright © 2017 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

System and method for investigating sub-surface features and 3D imaging of non-linear property, compressional velocity VP, shear velocity VS and velocity ratio VP/VS of a rock formation

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

Vu, Cung Khac; Skelt, Christopher; Nihei, Kurt

A system and a method for generating a three-dimensional image of a rock formation, compressional velocity VP, shear velocity VS and velocity ratio VP/VS of a rock formation are provided. A first acoustic signal includes a first plurality of pulses. A second acoustic signal from a second source includes a second plurality of pulses. A detected signal returning to the borehole includes a signal generated by a non-linear mixing process from the first and second acoustic signals in a non-linear mixing zone within an intersection volume. The received signal is processed to extract the signal over noise and/or signals resultingmore » from linear interaction and the three dimensional image of is generated.« less

Pure versus mixed electrosurgical current for endoscopic biliary sphincterotomy: a meta-analysis of adverse outcomes.

PubMed

Verma, Dharmendra; Kapadia, Asha; Adler, Douglas G

2007-08-01

Endoscopic biliary sphincterotomy (ES) can cause bleeding, pancreatitis, and perforation. This has, in part, been attributed to the type of electrosurgical current used for ES. No consensus exists on the optimal type of electrosurgical current for ES to maximize safety. To compare the rates of complications in patients undergoing ES via pure current versus mixed current. A systematic review of published, prospective, randomized trials that compared pure current with mixed current for ES. Patients undergoing ES, with random assignment to either current group. Data were standardized for pancreatitis and postsphincterotomy bleeding. There were insufficient data to analyze perforation risk. A random-effects model was used. Bleeding, pancreatitis, and perforation. A total of 804 patients from 4 trials that compared pure current to mixed current were analyzed. The aggregated rate of pancreatitis was 3.8%, 95% confidence interval (CI) 1.0%-6.6%, for the pure-current group versus 7.9%, 95% CI 3.1%-12.7%, for the mixed-current group; the difference was not statistically significant. The rate of bleeding (all severity groups) for the pure-current group was 37.3% (95% CI 27.3%, 47.3%), which was significantly higher than that of the mixed-current group (12.2% [95% CI 4.1%, 20.3%]). Mild bleeding was significantly more frequent with pure current (28.9% [95% CI 16.3, 41.4]) compared with mixed current (9.4% [95% CI 2.1%, 16.8%]). Variables, including endoscopist skill and cannulation difficulty, were difficult to measure. The rate of pancreatitis in patients who underwent ES when using pure current was not significantly different from those when using mixed current. Pure current was associated with more episodes of bleeding, primarily mild bleeding. Data were insufficient to analyze the perforation risk.

ALPS: A Linear Program Solver

NASA Technical Reports Server (NTRS)

Ferencz, Donald C.; Viterna, Larry A.

1991-01-01

ALPS is a computer program which can be used to solve general linear program (optimization) problems. ALPS was designed for those who have minimal linear programming (LP) knowledge and features a menu-driven scheme to guide the user through the process of creating and solving LP formulations. Once created, the problems can be edited and stored in standard DOS ASCII files to provide portability to various word processors or even other linear programming packages. Unlike many math-oriented LP solvers, ALPS contains an LP parser that reads through the LP formulation and reports several types of errors to the user. ALPS provides a large amount of solution data which is often useful in problem solving. In addition to pure linear programs, ALPS can solve for integer, mixed integer, and binary type problems. Pure linear programs are solved with the revised simplex method. Integer or mixed integer programs are solved initially with the revised simplex, and the completed using the branch-and-bound technique. Binary programs are solved with the method of implicit enumeration. This manual describes how to use ALPS to create, edit, and solve linear programming problems. Instructions for installing ALPS on a PC compatible computer are included in the appendices along with a general introduction to linear programming. A programmers guide is also included for assistance in modifying and maintaining the program.

Theoretical band structure of the superconducting antiperovskite oxide Sr3-xSnO

NASA Astrophysics Data System (ADS)

Ikeda, Atsutoshi; Fukumoto, Toshiyuki; Oudah, Mohamed; Hausmann, Jan Niklas; Yonezawa, Shingo; Kobayashi, Shingo; Sato, Masatoshi; Tassel, Cédric; Takeiri, Fumitaka; Takatsu, Hiroshi; Kageyama, Hiroshi; Maeno, Yoshiteru

2018-05-01

In order to investigate the position of the strontium deficiency in superconductive Sr3-xSnO, we synthesized and measured X-ray-diffraction patterns of Sr3-xSnO (x ∼ 0.5). Because no clear peaks originating from superstructures were observed, strontium deficiency is most likely to be randomly distributed. We also performed first-principles band-structure calculations on Sr3-xSnO (x = 0, 0.5) using two methods: full-potential linearized-augmented plane-wave plus local orbitals method and the Korringa-Kohn-Rostoker Green function method combined with the coherent potential approximation. We revealed that the Fermi energy of Sr3-xSnO in case of x ∼ 0.5 is about 0.8 eV below the original Fermi energy of the stoichiometric Sr3SnO, where the mixing of the valence p and conduction d orbitals are considered to be small.

Hair mercury concentrations and in vitro fertilization (IVF) outcomes among women from a fertility clinic.

PubMed

Wright, Diane L; Afeiche, Myriam C; Ehrlich, Shelley; Smith, Kristen; Williams, Paige L; Chavarro, Jorge E; Batsis, Maria; Toth, Thomas L; Hauser, Russ

2015-01-01

Total hair mercury (Hg) was measured among 205 women undergoing in vitro fertilization (IVF) treatment and the association with prospectively collected IVF outcomes (229 IVF cycles) was evaluated. Hair Hg levels (median=0.62ppm, range: 0.03-5.66ppm) correlated with fish intake (r=0.59), and exceeded the recommended EPA reference of 1ppm in 33% of women. Generalized linear mixed models with random intercepts accounting for within-woman correlations across treatment cycles were used to evaluate the association of hair Hg with IVF outcomes adjusted for age, body mass index, race, smoking status, infertility diagnosis, and protocol type. Hair Hg levels were not related to ovarian stimulation outcomes (peak estradiol levels, total and mature oocyte yields) or to fertilization rate, embryo quality, clinical pregnancy rate or live birth rate. Copyright © 2015 Elsevier Inc. All rights reserved.

Longitudinal changes in bone lead levels: the VA Normative Aging Study.

PubMed

Wilker, Elissa; Korrick, Susan; Nie, Linda H; Sparrow, David; Vokonas, Pantel; Coull, Brent; Wright, Robert O; Schwartz, Joel; Hu, Howard

2011-08-01

Bone lead is a cumulative measure of lead exposure that can also be remobilized. We examined repeated measures of bone lead over 11 years to characterize long-term changes and identify predictors of tibia and patella lead stores in an elderly male population. Lead was measured every 3 to 5 years by k-x-ray fluorescence and mixed-effect models with random effects were used to evaluate change over time. A total of 554 participants provided up to four bone lead measurements. Final models predicted a -1.4% annual decline (95% CI: -2.2 to -0.7) for tibia lead and piecewise linear model for patella with an initial decline of 5.1% per year (95% CI: -6.2 to -3.9) during the first 4.6 years but no significant change thereafter (-0.4% [95% CI: -2.4 to 1.7]). These results suggest that bone lead half-life may be longer than previously reported.

Meta-Analysis of Effect Sizes Reported at Multiple Time Points Using General Linear Mixed Model.

PubMed

Musekiwa, Alfred; Manda, Samuel O M; Mwambi, Henry G; Chen, Ding-Geng

2016-01-01

Meta-analysis of longitudinal studies combines effect sizes measured at pre-determined time points. The most common approach involves performing separate univariate meta-analyses at individual time points. This simplistic approach ignores dependence between longitudinal effect sizes, which might result in less precise parameter estimates. In this paper, we show how to conduct a meta-analysis of longitudinal effect sizes where we contrast different covariance structures for dependence between effect sizes, both within and between studies. We propose new combinations of covariance structures for the dependence between effect size and utilize a practical example involving meta-analysis of 17 trials comparing postoperative treatments for a type of cancer, where survival is measured at 6, 12, 18 and 24 months post randomization. Although the results from this particular data set show the benefit of accounting for within-study serial correlation between effect sizes, simulations are required to confirm these results.

Finite-time synchronization of stochastic coupled neural networks subject to Markovian switching and input saturation.

PubMed

Selvaraj, P; Sakthivel, R; Kwon, O M

2018-06-07

This paper addresses the problem of finite-time synchronization of stochastic coupled neural networks (SCNNs) subject to Markovian switching, mixed time delay, and actuator saturation. In addition, coupling strengths of the SCNNs are characterized by mutually independent random variables. By utilizing a simple linear transformation, the problem of stochastic finite-time synchronization of SCNNs is converted into a mean-square finite-time stabilization problem of an error system. By choosing a suitable mode dependent switched Lyapunov-Krasovskii functional, a new set of sufficient conditions is derived to guarantee the finite-time stability of the error system. Subsequently, with the help of anti-windup control scheme, the actuator saturation risks could be mitigated. Moreover, the derived conditions help to optimize estimation of the domain of attraction by enlarging the contractively invariant set. Furthermore, simulations are conducted to exhibit the efficiency of proposed control scheme. Copyright © 2018 Elsevier Ltd. All rights reserved.

Self-reported mobile phone use and semen parameters among men from a fertility clinic.

PubMed

Lewis, Ryan C; Mínguez-Alarcón, Lidia; Meeker, John D; Williams, Paige L; Mezei, Gabor; Ford, Jennifer B; Hauser, Russ

2017-01-01

There is increasing concern that use of mobile phones, a source of low-level radio-frequency electromagnetic fields, may be associated with poor semen quality, but the epidemiologic evidence is limited and conflicting. The relationship between mobile phone use patterns and markers of semen quality was explored in a longitudinal cohort study of 153 men that attended an academic fertility clinic in Boston, Massachusetts. Information on mobile phone use duration, headset or earpiece use, and the body location in which the mobile phone was carried was ascertained via nurse-administered questionnaire. Semen samples (n=350) were collected and analyzed onsite. To account for multiple semen samples per man, linear mixed models with random intercepts were used to investigate the association between mobile phone use and semen parameters. Overall, there was no evidence for a relationship between mobile phone use and semen quality. Copyright © 2016 Elsevier Inc. All rights reserved.

Self-reported mobile phone use and semen parameters among men from a fertility clinic

PubMed Central

Lewis, Ryan C.; Mínguez-Alarcón, Lidia; Meeker, John D.; Williams, Paige L.; Mezei, Gabor; Ford, Jennifer B.; Hauser, Russ

2017-01-01

There is increasing concern that use of mobile phones, a source of low-level radio-frequency electromagnetic fields, may be associated with poor semen quality, but the epidemiologic evidence is limited and conflicting. The relationship between mobile phone use patterns and markers of semen quality was explored in a longitudinal cohort study of 153 men that attended an academic fertility clinic in Boston, Massachusetts. Information on mobile phone use duration, headset or earpiece use, and the body location in which the mobile phone was carried was ascertained via nurse-administered questionnaire. Semen samples (n=350) were collected and analyzed onsite. To account for multiple semen samples per man, linear mixed models with random intercepts were used to investigate the association between mobile phone use and semen parameters. Overall, there was no evidence for a relationship between mobile phone use and semen quality. PMID:27838386

An Overview of Longitudinal Data Analysis Methods for Neurological Research

PubMed Central

Locascio, Joseph J.; Atri, Alireza

2011-01-01

The purpose of this article is to provide a concise, broad and readily accessible overview of longitudinal data analysis methods, aimed to be a practical guide for clinical investigators in neurology. In general, we advise that older, traditional methods, including (1) simple regression of the dependent variable on a time measure, (2) analyzing a single summary subject level number that indexes changes for each subject and (3) a general linear model approach with a fixed-subject effect, should be reserved for quick, simple or preliminary analyses. We advocate the general use of mixed-random and fixed-effect regression models for analyses of most longitudinal clinical studies. Under restrictive situations or to provide validation, we recommend: (1) repeated-measure analysis of covariance (ANCOVA), (2) ANCOVA for two time points, (3) generalized estimating equations and (4) latent growth curve/structural equation models. PMID:22203825

Impact of 6-month aerobic exercise on Alzheimer's symptoms.

PubMed

Yu, Fang; Thomas, William; Nelson, Nathaniel W; Bronas, Ulf G; Dysken, Maurice; Wyman, Jean F

2015-06-01

Little is known about how aerobic exercise affects Alzheimer's disease (AD). The purpose of this pilot study was to test the impact of 6-month cycling on AD symptoms in community-dwelling older adults with mild-to-moderate AD, using a single-group, repeated-measures design (n = 26). AD symptoms were measured with the AD Assessment Scale-Cognitive (ADAS-Cog), Disability in AD (DAD), and Neuropsychiatric Inventory-Caregiver (NPI-Q) scales at baseline, 3 and 6 months. Data were analyzed using mixed linear models. The ADAS-Cog, DAD, and NPI-Q severity scores remained unchanged over the 6-month period, while caregiver distress decreased 40% (p < .05). We conclude that aerobic exercise may reduce AD symptoms and appears effective in decreasing caregiver distress. Further randomized controlled trials are needed to examine the effects of aerobic exercise in AD. © The Author(s) 2013.

Synthesizing folded band chaos.

PubMed

Corron, Ned J; Hayes, Scott T; Pethel, Shawn D; Blakely, Jonathan N

2007-04-01

A randomly driven linear filter that synthesizes Lorenz-like, reverse-time chaos is shown also to produce Rössler-like folded band wave forms when driven using a different encoding of the random source. The relationship between the topological entropy of the random source, dissipation in the linear filter, and the positive Lyapunov exponent for the reverse-time wave form is exposed. The two drive encodings are viewed as grammar restrictions on a more general encoding that produces a chaotic superset encompassing both the Lorenz butterfly and Rössler folded band paradigms of nonlinear dynamics.

The Use of Mixed Effects Models for Obtaining Low-Cost Ecosystem Carbon Stock Estimates in Mangroves of the Asia-Pacific

NASA Astrophysics Data System (ADS)

Bukoski, J. J.; Broadhead, J. S.; Donato, D.; Murdiyarso, D.; Gregoire, T. G.

2016-12-01

Mangroves provide extensive ecosystem services that support both local livelihoods and international environmental goals, including coastal protection, water filtration, biodiversity conservation and the sequestration of carbon (C). While voluntary C market projects that seek to preserve and enhance forest C stocks offer a potential means of generating finance for mangrove conservation, their implementation faces barriers due to the high costs of quantifying C stocks through measurement, reporting and verification (MRV) activities. To streamline MRV activities in mangrove C forestry projects, we develop predictive models for (i) biomass-based C stocks, and (ii) soil-based C stocks for the mangroves of the Asia-Pacific. We use linear mixed effect models to account for spatial correlation in modeling the expected C as a function of stand attributes. The most parsimonious biomass model predicts total biomass C stocks as a function of both basal area and the interaction between latitude and basal area, whereas the most parsimonious soil C model predicts soil C stocks as a function of the logarithmic transformations of both latitude and basal area. Random effects are specified by site for both models, and are found to explain a substantial proportion of variance within the estimation datasets. The root mean square error (RMSE) of the biomass C model is approximated at 24.6 Mg/ha (18.4% of mean biomass C in the dataset), whereas the RMSE of the soil C model is estimated at 4.9 mg C/cm 3 (14.1% of mean soil C). A substantial proportion of the variation in soil C, however, is explained by the random effects and thus the use of the SOC model may be most valuable for sites in which field measurements of soil C exist.

Effects of a novel sodium channel blocker, GSK2339345, in patients with refractory chronic cough
.

PubMed

Smith, Jaclyn A; McGarvey, Lorcan P A; Badri, Huda; Satia, Imran; Warren, Francis; Siederer, Sarah; Liefaard, Lia; Murdoch, Robert D; Povey, Kathryn; Marks-Konczalik, Joanna

2017-09-01

Voltage-gated sodium channels (VGSC) are important in the initiation and propagation of action potentials in afferent sensory nerve fibers responsible for evoking cough. This study investigated the efficacy of GSK2339345, a VGSC inhibitor, in the treatment of refractory chronic cough (RCC). A three-part randomized, double-blind, placebo-controlled, cross-over study was conducted in the UK. In part A, patients with RCC received two inhaled doses of either GSK2339345 or placebo, 4 hours apart during three study periods. Patients were monitored for cough for 8 hours post-first dose using the VitaloJAK, ambulatory cough monitor. In parts B and C, patients underwent full dose-response cough challenges with capsaicin and citric acid respectively following single doses of randomly assigned GSK2339345 or placebo (4 study days). Part A was analyzed using a mixed effects model and parts B and C using population non-linear mixed effects models. Of 16 enrolled patients, 11 completed the study. 8-hour cough counts increased following GSK2339345 treatment compared with placebo (GSK2339345/placebo ratio of adjusted geometric means: 1.26 (90% credible interval 1.10, 1.44), associated with GSK2339345-evoked coughing, recorded during the 2 minutes post-dose. This was not observed with placebo. The effect of GSK2339345 on cough responses during cough challenges was inconclusive. GSK2339345 was well tolerated. While these data could not determine if GSK2339345 reached the target VGSC, they strongly suggest that GSK2339345 has no anti-tussive effect despite reaching airway sensory nerves as evidenced by the evoked transient cough.
.

Thermal properties of the mixed spin-1 and spin-3/2 Ising ferrimagnetic system with two different random single-ion anisotropies

NASA Astrophysics Data System (ADS)

Pereira, J. R. V.; Tunes, T. M.; de Arruda, A. S.; Godoy, M.

2018-06-01

In this work, we have performed Monte Carlo simulations to study a mixed spin-1 and spin-3/2 Ising ferrimagnetic system on a square lattice with two different random single-ion anisotropies. This lattice is divided in two interpenetrating sublattices with spins SA = 1 in the sublattice A and SB = 3 / 2 in the sublattice B. The exchange interaction between the spins on the sublattices is antiferromagnetic (J < 0). We used two random single-ion anisotropies, DiA and DjB , on the sublattices A and B, respectively. We have determined the phase diagram of the model in the critical temperature Tc versus strength of the random single-ion anisotropy D plane and we shown that it exhibits only second-order phase transition lines. We also shown that this system displays compensation temperatures for some cases of the random single-ion distribution.

VENVAL : a plywood mill cost accounting program

Treesearch

Henry Spelter

1991-01-01

This report documents a package of computer programs called VENVAL. These programs prepare plywood mill data for a linear programming (LP) model that, in turn, calculates the optimum mix of products to make, given a set of technologies and market prices. (The software to solve a linear program is not provided and must be obtained separately.) Linear programming finds...

Autocorrelation peaks in congruential pseudorandom number generators

NASA Technical Reports Server (NTRS)

Neuman, F.; Merrick, R. B.

1976-01-01

The complete correlation structure of several congruential pseudorandom number generators (PRNG) of the same type and small cycle length was studied to deal with the problem of congruential PRNG almost repeating themselves at intervals smaller than their cycle lengths, during simulation of bandpass filtered normal random noise. Maximum period multiplicative and mixed congruential generators were studied, with inferences drawn from examination of several tractable members of a class of random number generators, and moduli from 2 to the 5th power to 2 to the 9th power. High correlation is shown to exist in mixed and multiplicative congruential random number generators and prime moduli Lehmer generators for shifts a fraction of their cycle length. The random noise sequences in question are required when simulating electrical noise, air turbulence, or time variation of wind parameters.

Structural Equation Modeling: A Framework for Ocular and Other Medical Sciences Research

PubMed Central

Christ, Sharon L.; Lee, David J.; Lam, Byron L.; Diane, Zheng D.

2017-01-01

Structural equation modeling (SEM) is a modeling framework that encompasses many types of statistical models and can accommodate a variety of estimation and testing methods. SEM has been used primarily in social sciences but is increasingly used in epidemiology, public health, and the medical sciences. SEM provides many advantages for the analysis of survey and clinical data, including the ability to model latent constructs that may not be directly observable. Another major feature is simultaneous estimation of parameters in systems of equations that may include mediated relationships, correlated dependent variables, and in some instances feedback relationships. SEM allows for the specification of theoretically holistic models because multiple and varied relationships may be estimated together in the same model. SEM has recently expanded by adding generalized linear modeling capabilities that include the simultaneous estimation of parameters of different functional form for outcomes with different distributions in the same model. Therefore, mortality modeling and other relevant health outcomes may be evaluated. Random effects estimation using latent variables has been advanced in the SEM literature and software. In addition, SEM software has increased estimation options. Therefore, modern SEM is quite general and includes model types frequently used by health researchers, including generalized linear modeling, mixed effects linear modeling, and population average modeling. This article does not present any new information. It is meant as an introduction to SEM and its uses in ocular and other health research. PMID:24467557

A non-modal analytical method to predict turbulent properties applied to the Hasegawa-Wakatani model

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

Friedman, B., E-mail: friedman11@llnl.gov; Lawrence Livermore National Laboratory, Livermore, California 94550; Carter, T. A.

2015-01-15

Linear eigenmode analysis often fails to describe turbulence in model systems that have non-normal linear operators and thus nonorthogonal eigenmodes, which can cause fluctuations to transiently grow faster than expected from eigenmode analysis. When combined with energetically conservative nonlinear mode mixing, transient growth can lead to sustained turbulence even in the absence of eigenmode instability. Since linear operators ultimately provide the turbulent fluctuations with energy, it is useful to define a growth rate that takes into account non-modal effects, allowing for prediction of energy injection, transport levels, and possibly even turbulent onset in the subcritical regime. We define such amore » non-modal growth rate using a relatively simple model of the statistical effect that the nonlinearities have on cross-phases and amplitude ratios of the system state variables. In particular, we model the nonlinearities as delta-function-like, periodic forces that randomize the state variables once every eddy turnover time. Furthermore, we estimate the eddy turnover time to be the inverse of the least stable eigenmode frequency or growth rate, which allows for prediction without nonlinear numerical simulation. We test this procedure on the 2D and 3D Hasegawa-Wakatani model [A. Hasegawa and M. Wakatani, Phys. Rev. Lett. 50, 682 (1983)] and find that the non-modal growth rate is a good predictor of energy injection rates, especially in the strongly non-normal, fully developed turbulence regime.« less

A non-modal analytical method to predict turbulent properties applied to the Hasegawa-Wakatani model

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

Friedman, B.; Carter, T. A.

2015-01-15

Linear eigenmode analysis often fails to describe turbulence in model systems that have non-normal linear operators and thus nonorthogonal eigenmodes, which can cause fluctuations to transiently grow faster than expected from eigenmode analysis. When combined with energetically conservative nonlinear mode mixing, transient growth can lead to sustained turbulence even in the absence of eigenmode instability. Since linear operators ultimately provide the turbulent fluctuations with energy, it is useful to define a growth rate that takes into account non-modal effects, allowing for prediction of energy injection, transport levels, and possibly even turbulent onset in the subcritical regime. Here, we define suchmore » a non-modal growth rate using a relatively simple model of the statistical effect that the nonlinearities have on cross-phases and amplitude ratios of the system state variables. In particular, we model the nonlinearities as delta-function-like, periodic forces that randomize the state variables once every eddy turnover time. Furthermore, we estimate the eddy turnover time to be the inverse of the least stable eigenmode frequency or growth rate, which allows for prediction without nonlinear numerical simulation. Also, we test this procedure on the 2D and 3D Hasegawa-Wakatani model [A. Hasegawa and M. Wakatani, Phys. Rev. Lett. 50, 682 (1983)] and find that the non-modal growth rate is a good predictor of energy injection rates, especially in the strongly non-normal, fully developed turbulence regime.« less

Mathematical modeling of the crack growth in linear elastic isotropic materials by conventional fracture mechanics approaches and by molecular dynamics method: crack propagation direction angle under mixed mode loading

NASA Astrophysics Data System (ADS)

Stepanova, Larisa; Bronnikov, Sergej

2018-03-01

The crack growth directional angles in the isotropic linear elastic plane with the central crack under mixed-mode loading conditions for the full range of the mixity parameter are found. Two fracture criteria of traditional linear fracture mechanics (maximum tangential stress and minimum strain energy density criteria) are used. Atomistic simulations of the central crack growth process in an infinite plane medium under mixed-mode loading using Large-scale Molecular Massively Parallel Simulator (LAMMPS), a classical molecular dynamics code, are performed. The inter-atomic potential used in this investigation is Embedded Atom Method (EAM) potential. The plane specimens with initial central crack were subjected to Mixed-Mode loadings. The simulation cell contains 400000 atoms. The crack propagation direction angles under different values of the mixity parameter in a wide range of values from pure tensile loading to pure shear loading in a wide diapason of temperatures (from 0.1 К to 800 К) are obtained and analyzed. It is shown that the crack propagation direction angles obtained by molecular dynamics method coincide with the crack propagation direction angles given by the multi-parameter fracture criteria based on the strain energy density and the multi-parameter description of the crack-tip fields.

SHP465 Mixed Amphetamine Salts in the Treatment of Attention-Deficit/Hyperactivity Disorder in Children and Adolescents: Results of a Randomized, Double-Blind Placebo-Controlled Study

PubMed Central

Childress, Ann C.; Greenbaum, Michael; Yu, Ming; Yan, Brian; Jaffee, Margo; Robertson, Brigitte

2018-01-01

Abstract Objective: The aim of this study was to evaluate the efficacy, safety, and tolerability of SHP465 mixed amphetamine salts (MAS) in children and adolescents with attention-deficit/hyperactivity disorder (ADHD). Methods: This randomized, double-blind dose-optimization study enrolled children and adolescents (6–17 years) meeting Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision ADHD criteria and having baseline ADHD Rating Scale IV (ADHD-RS-IV) total scores ≥28. Participants were randomized 1:1 to placebo or dose-optimized SHP465 MAS (12.5–25 mg) for 4 weeks. Total score change (baseline to week 4) on the ADHD-RS-IV (primary endpoint) and the Clinical Global Impressions-Improvement (CGI-I) scale score at week 4 (key secondary endpoint) were assessed using linear mixed-effects models for repeated measures. Safety and tolerability assessments (secondary endpoints) included treatment-emergent adverse events (TEAEs) and vital sign changes. Results: Of 264 randomized participants (placebo, n = 132; SHP465 MAS, n = 132), 234 (placebo, n = 118; SHP465 MAS, n = 116) completed the study. The least squares mean (95% confidence interval) treatment difference significantly favored SHP465 MAS over placebo for ADHD-RS-IV total score change from baseline to week 4 (−9.9 [−13.0, −6.8]; p < 0.001; effect size = 0.80) and CGI-I score at week 4 (−0.8 [−1.1, −0.5]; p < 0.001; effect size = 0.65). TEAE frequency was 46.6% (61/131) with placebo and 67.4% (89/132) with SHP465 MAS; no serious TEAEs were reported. TEAEs reported at a frequency of ≥5% and ≥2 times the placebo rate were decreased appetite, insomnia, irritability, nausea, and decreased weight. Mean ± standard deviation increases (baseline to final on-treatment assessment) were higher with SHP465 MAS than placebo for pulse (5.7 ± 11.78 vs. 0.7 ± 10.79), systolic blood pressure (3.8 ± 9.15 vs. 2.1 ± 8.72), and diastolic blood pressure (4.0 ± 8.23 vs. 0.5 ± 7.45). Conclusions: SHP465 MAS demonstrated superiority over placebo in improving ADHD symptoms and global functioning in children and adolescents with ADHD. The safety and tolerability profile of SHP465 MAS was consistent with that of SHP465 MAS in adults and other long-acting psychostimulants in children and adolescents. PMID:28816509

Racial/Ethnic Differences in Sexual Network Mixing: A Log-Linear Analysis of HIV Status by Partnership and Sexual Behavior Among Most at-Risk MSM.

PubMed

Fujimoto, Kayo; Williams, Mark L

2015-06-01

Mixing patterns within sexual networks have been shown to have an effect on HIV transmission, both within and across groups. This study examined sexual mixing patterns involving HIV-unknown status and risky sexual behavior conditioned on assortative/dissortative mixing by race/ethnicity. The sample used for this study consisted of drug-using male sex workers and their male sex partners. A log-linear analysis of 257 most at-risk MSM and 3,072 sex partners was conducted. The analysis found two significant patterns. HIV-positive most at-risk Black MSM had a strong tendency to have HIV-unknown Black partners (relative risk, RR = 2.91, p < 0.001) and to engage in risky sexual behavior (RR = 2.22, p < 0.001). White most at-risk MSM with unknown HIV status also had a tendency to engage in risky sexual behavior with Whites (RR = 1.72, p < 0.001). The results suggest that interventions that target the most at-risk MSM and their sex partners should account for specific sexual network mixing patterns by HIV status.

Control for Population Structure and Relatedness for Binary Traits in Genetic Association Studies via Logistic Mixed Models.

PubMed

Chen, Han; Wang, Chaolong; Conomos, Matthew P; Stilp, Adrienne M; Li, Zilin; Sofer, Tamar; Szpiro, Adam A; Chen, Wei; Brehm, John M; Celedón, Juan C; Redline, Susan; Papanicolaou, George J; Thornton, Timothy A; Laurie, Cathy C; Rice, Kenneth; Lin, Xihong

2016-04-07

Linear mixed models (LMMs) are widely used in genome-wide association studies (GWASs) to account for population structure and relatedness, for both continuous and binary traits. Motivated by the failure of LMMs to control type I errors in a GWAS of asthma, a binary trait, we show that LMMs are generally inappropriate for analyzing binary traits when population stratification leads to violation of the LMM's constant-residual variance assumption. To overcome this problem, we develop a computationally efficient logistic mixed model approach for genome-wide analysis of binary traits, the generalized linear mixed model association test (GMMAT). This approach fits a logistic mixed model once per GWAS and performs score tests under the null hypothesis of no association between a binary trait and individual genetic variants. We show in simulation studies and real data analysis that GMMAT effectively controls for population structure and relatedness when analyzing binary traits in a wide variety of study designs. Copyright © 2016 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

The Long-Term Impact of Neurofeedback on Symptom Burden and Interference in Patients With Chronic Chemotherapy-Induced Neuropathy: Analysis of a Randomized Controlled Trial.

PubMed

Prinsloo, Sarah; Novy, Diane; Driver, Larry; Lyle, Randall; Ramondetta, Lois; Eng, Cathy; Lopez, Gabriel; Li, Yisheng; Cohen, Lorenzo

2018-05-01

Chemotherapy-induced peripheral neuropathy (CIPN) is a common side effect of cancer treatment and may adversely affect quality of life (QOL) for years. We explored the long-term effects of electroencephalographic neurofeedback (NFB) as a treatment for CIPN and other aspects of QOL. Seventy-one cancer survivors (mean age 62.5; 87% females) with CIPN were randomized to NFB or to a waitlist control (WLC) group. The NFB group underwent 20 sessions of NFB where rewards were given for voluntary changes in electroencephalography. Measurements of pain, cancer-related symptoms, QOL, sleep, and fatigue were obtained at baseline, end of treatment, and one and four months later. Seventy one participants enrolled in the study. At the end of treatment, 30 in the NFB group and 32 in the WLC group completed assessments; at four months, 23 in the NFB group and 28 in the WLC completed assessments. Linear mixed model analysis revealed significant group × time interaction for pain severity. A general linear model determined that the NFB group had greater improvements in worst pain (primary outcome) and other symptoms such as numbness, cancer-related symptom severity, symptom interference, physical functioning, general health, and fatigue compared with the WLC group at the end of treatment and four months (all P < 0.05). Effect sizes were moderate or large for most measures. NFB appears to result in long-term reduction in multiple CIPN symptoms and improved postchemotherapy QOL and fatigue. Copyright © 2018 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

EVOLUTION OF FAST MAGNETOACOUSTIC PULSES IN RANDOMLY STRUCTURED CORONAL PLASMAS

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

Yuan, D.; Li, B.; Pascoe, D. J.

2015-02-01

We investigate the evolution of fast magnetoacoustic pulses in randomly structured plasmas, in the context of large-scale propagating waves in the solar atmosphere. We perform one-dimensional numerical simulations of fast wave pulses propagating perpendicular to a constant magnetic field in a low-β plasma with a random density profile across the field. Both linear and nonlinear regimes are considered. We study how the evolution of the pulse amplitude and width depends on their initial values and the parameters of the random structuring. Acting as a dispersive medium, a randomly structured plasma causes amplitude attenuation and width broadening of the fast wavemore » pulses. After the passage of the main pulse, secondary propagating and standing fast waves appear. Width evolution of both linear and nonlinear pulses can be well approximated by linear functions; however, narrow pulses may have zero or negative broadening. This arises because narrow pulses are prone to splitting, while broad pulses usually deviate less from their initial Gaussian shape and form ripple structures on top of the main pulse. Linear pulses decay at an almost constant rate, while nonlinear pulses decay exponentially. A pulse interacts most efficiently with a random medium with a correlation length of about half of the initial pulse width. This detailed model of fast wave pulses propagating in highly structured media substantiates the interpretation of EIT waves as fast magnetoacoustic waves. Evolution of a fast pulse provides us with a novel method to diagnose the sub-resolution filamentation of the solar atmosphere.« less

Mixed reality temporal bone surgical dissector: mechanical design

PubMed Central

2014-01-01

Objective The Development of a Novel Mixed Reality (MR) Simulation. An evolving training environment emphasizes the importance of simulation. Current haptic temporal bone simulators have difficulty representing realistic contact forces and while 3D printed models convincingly represent vibrational properties of bone, they cannot reproduce soft tissue. This paper introduces a mixed reality model, where the effective elements of both simulations are combined; haptic rendering of soft tissue directly interacts with a printed bone model. This paper addresses one aspect in a series of challenges, specifically the mechanical merger of a haptic device with an otic drill. This further necessitates gravity cancelation of the work assembly gripper mechanism. In this system, the haptic end-effector is replaced by a high-speed drill and the virtual contact forces need to be repositioned to the drill tip from the mid wand. Previous publications detail generation of both the requisite printed and haptic simulations. Method Custom software was developed to reposition the haptic interaction point to the drill tip. A custom fitting, to hold the otic drill, was developed and its weight was offset using the haptic device. The robustness of the system to disturbances and its stable performance during drilling were tested. The experiments were performed on a mixed reality model consisting of two drillable rapid-prototyped layers separated by a free-space. Within the free-space, a linear virtual force model is applied to simulate drill contact with soft tissue. Results Testing illustrated the effectiveness of gravity cancellation. Additionally, the system exhibited excellent performance given random inputs and during the drill’s passage between real and virtual components of the model. No issues with registration at model boundaries were encountered. Conclusion These tests provide a proof of concept for the initial stages in the development of a novel mixed-reality temporal bone simulator. PMID:25927300

Options for refractive index and viscosity matching to study variable density flows

NASA Astrophysics Data System (ADS)

Clément, Simon A.; Guillemain, Anaïs; McCleney, Amy B.; Bardet, Philippe M.

2018-02-01

Variable density flows are often studied by mixing two miscible aqueous solutions of different densities. To perform optical diagnostics in such environments, the refractive index of the fluids must be matched, which can be achieved by carefully choosing the two solutes and the concentration of the solutions. To separate the effects of buoyancy forces and viscosity variations, it is desirable to match the viscosity of the two solutions in addition to their refractive index. In this manuscript, several pairs of index matched fluids are compared in terms of viscosity matching, monetary cost, and practical use. Two fluid pairs are studied in detail, with two aqueous solutions (binary solutions of water and a salt or alcohol) mixed into a ternary solution. In each case: an aqueous solution of isopropanol mixed with an aqueous solution of sodium chloride (NaCl) and an aqueous solution of glycerol mixed with an aqueous solution of sodium sulfate (Na_2SO_4). The first fluid pair allows reaching high-density differences at low cost, but brings a large difference in dynamic viscosity. The second allows matching dynamic viscosity and refractive index simultaneously, at reasonable cost. For each of these four solutes, the density, kinematic viscosity, and refractive index are measured versus concentration and temperature, as well as wavelength for the refractive index. To investigate non-linear effects when two index-matched, binary solutions are mixed, the ternary solutions formed are also analyzed. Results show that density and refractive index follow a linear variation with concentration. However, the viscosity of the isopropanol and NaCl pair deviates from the linear law and has to be considered. Empirical correlations and their coefficients are given to create index-matched fluids at a chosen temperature and wavelength. Finally, the effectiveness of the refractive index matching is illustrated with particle image velocimetry measurements performed for a buoyant jet in a linearly stratified environment. The creation of the index-matched solutions and linear stratification in a large-scale experimental facility are detailed, as well as the practical challenges to obtain precise refractive index matching.

Nonuniform sampling theorems for random signals in the linear canonical transform domain

NASA Astrophysics Data System (ADS)

Shuiqing, Xu; Congmei, Jiang; Yi, Chai; Youqiang, Hu; Lei, Huang

2018-06-01

Nonuniform sampling can be encountered in various practical processes because of random events or poor timebase. The analysis and applications of the nonuniform sampling for deterministic signals related to the linear canonical transform (LCT) have been well considered and researched, but up to now no papers have been published regarding the various nonuniform sampling theorems for random signals related to the LCT. The aim of this article is to explore the nonuniform sampling and reconstruction of random signals associated with the LCT. First, some special nonuniform sampling models are briefly introduced. Second, based on these models, some reconstruction theorems for random signals from various nonuniform samples associated with the LCT have been derived. Finally, the simulation results are made to prove the accuracy of the sampling theorems. In addition, the latent real practices of the nonuniform sampling for random signals have been also discussed.

Statistical quality assessment criteria for a linear mixing model with elliptical t-distribution errors

NASA Astrophysics Data System (ADS)

Manolakis, Dimitris G.

2004-10-01

The linear mixing model is widely used in hyperspectral imaging applications to model the reflectance spectra of mixed pixels in the SWIR atmospheric window or the radiance spectra of plume gases in the LWIR atmospheric window. In both cases it is important to detect the presence of materials or gases and then estimate their amount, if they are present. The detection and estimation algorithms available for these tasks are related but they are not identical. The objective of this paper is to theoretically investigate how the heavy tails observed in hyperspectral background data affect the quality of abundance estimates and how the F-test, used for endmember selection, is robust to the presence of heavy tails when the model fits the data.

The Linear Mixing Approximation for Planetary Ices

NASA Astrophysics Data System (ADS)

Bethkenhagen, M.; Meyer, E. R.; Hamel, S.; Nettelmann, N.; French, M.; Scheibe, L.; Ticknor, C.; Collins, L. A.; Kress, J. D.; Fortney, J. J.; Redmer, R.

2017-12-01

We investigate the validity of the widely used linear mixing approximation for the equations of state (EOS) of planetary ices, which are thought to dominate the interior of the ice giant planets Uranus and Neptune. For that purpose we perform density functional theory molecular dynamics simulations using the VASP code.[1] In particular, we compute 1:1 binary mixtures of water, ammonia, and methane, as well as their 2:1:4 ternary mixture at pressure-temperature conditions typical for the interior of Uranus and Neptune.[2,3] In addition, a new ab initio EOS for methane is presented. The linear mixing approximation is verified for the conditions present inside Uranus ranging up to 10 Mbar based on the comprehensive EOS data set. We also calculate the diffusion coefficients for the ternary mixture along different Uranus interior profiles and compare them to the values of the pure compounds. We find that deviations of the linear mixing approximation from the real mixture are generally small; for the EOS they fall within about 4% uncertainty while the diffusion coefficients deviate up to 20% . The EOS of planetary ices are applied to adiabatic models of Uranus. It turns out that a deep interior of almost pure ices is consistent with the gravity field data, in which case the planet becomes rather cold (T core ˜ 4000 K). [1] G. Kresse and J. Hafner, Physical Review B 47, 558 (1993). [2] R. Redmer, T.R. Mattsson, N. Nettelmann and M. French, Icarus 211, 798 (2011). [3] N. Nettelmann, K. Wang, J. J. Fortney, S. Hamel, S. Yellamilli, M. Bethkenhagen and R. Redmer, Icarus 275, 107 (2016).

Detecting single-trial EEG evoked potential using a wavelet domain linear mixed model: application to error potentials classification.

PubMed

Spinnato, J; Roubaud, M-C; Burle, B; Torrésani, B

2015-06-01

The main goal of this work is to develop a model for multisensor signals, such as magnetoencephalography or electroencephalography (EEG) signals that account for inter-trial variability, suitable for corresponding binary classification problems. An important constraint is that the model be simple enough to handle small size and unbalanced datasets, as often encountered in BCI-type experiments. The method involves the linear mixed effects statistical model, wavelet transform, and spatial filtering, and aims at the characterization of localized discriminant features in multisensor signals. After discrete wavelet transform and spatial filtering, a projection onto the relevant wavelet and spatial channels subspaces is used for dimension reduction. The projected signals are then decomposed as the sum of a signal of interest (i.e., discriminant) and background noise, using a very simple Gaussian linear mixed model. Thanks to the simplicity of the model, the corresponding parameter estimation problem is simplified. Robust estimates of class-covariance matrices are obtained from small sample sizes and an effective Bayes plug-in classifier is derived. The approach is applied to the detection of error potentials in multichannel EEG data in a very unbalanced situation (detection of rare events). Classification results prove the relevance of the proposed approach in such a context. The combination of the linear mixed model, wavelet transform and spatial filtering for EEG classification is, to the best of our knowledge, an original approach, which is proven to be effective. This paper improves upon earlier results on similar problems, and the three main ingredients all play an important role.

Robust geostatistical analysis of spatial data

NASA Astrophysics Data System (ADS)

Papritz, Andreas; Künsch, Hans Rudolf; Schwierz, Cornelia; Stahel, Werner A.

2013-04-01

Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outliers affect the modelling of the large-scale spatial trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation (Welsh and Richardson, 1997). Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled and non-sampled locations and kriging variances. Apart from presenting our modelling framework, we shall present selected simulation results by which we explored the properties of the new method. This will be complemented by an analysis a data set on heavy metal contamination of the soil in the vicinity of a metal smelter. Marchant, B.P. and Lark, R.M. 2007. Robust estimation of the variogram by residual maximum likelihood. Geoderma 140: 62-72. Richardson, A.M. and Welsh, A.H. 1995. Robust restricted maximum likelihood in mixed linear models. Biometrics 51: 1429-1439. Welsh, A.H. and Richardson, A.M. 1997. Approaches to the robust estimation of mixed models. In: Handbook of Statistics Vol. 15, Elsevier, pp. 343-384.

From diets to foods: using linear programming to formulate a nutritious, minimum-cost porridge mix for children aged 1 to 2 years.

PubMed

De Carvalho, Irene Stuart Torrié; Granfeldt, Yvonne; Dejmek, Petr; Håkansson, Andreas

2015-03-01

Linear programming has been used extensively as a tool for nutritional recommendations. Extending the methodology to food formulation presents new challenges, since not all combinations of nutritious ingredients will produce an acceptable food. Furthermore, it would help in implementation and in ensuring the feasibility of the suggested recommendations. To extend the previously used linear programming methodology from diet optimization to food formulation using consistency constraints. In addition, to exemplify usability using the case of a porridge mix formulation for emergency situations in rural Mozambique. The linear programming method was extended with a consistency constraint based on previously published empirical studies on swelling of starch in soft porridges. The new method was exemplified using the formulation of a nutritious, minimum-cost porridge mix for children aged 1 to 2 years for use as a complete relief food, based primarily on local ingredients, in rural Mozambique. A nutritious porridge fulfilling the consistency constraints was found; however, the minimum cost was unfeasible with local ingredients only. This illustrates the challenges in formulating nutritious yet economically feasible foods from local ingredients. The high cost was caused by the high cost of mineral-rich foods. A nutritious, low-cost porridge that fulfills the consistency constraints was obtained by including supplements of zinc and calcium salts as ingredients. The optimizations were successful in fulfilling all constraints and provided a feasible porridge, showing that the extended constrained linear programming methodology provides a systematic tool for designing nutritious foods.

Random-effects linear modeling and sample size tables for two special crossover designs of average bioequivalence studies: the four-period, two-sequence, two-formulation and six-period, three-sequence, three-formulation designs.

PubMed

Diaz, Francisco J; Berg, Michel J; Krebill, Ron; Welty, Timothy; Gidal, Barry E; Alloway, Rita; Privitera, Michael

2013-12-01

Due to concern and debate in the epilepsy medical community and to the current interest of the US Food and Drug Administration (FDA) in revising approaches to the approval of generic drugs, the FDA is currently supporting ongoing bioequivalence studies of antiepileptic drugs, the EQUIGEN studies. During the design of these crossover studies, the researchers could not find commercial or non-commercial statistical software that quickly allowed computation of sample sizes for their designs, particularly software implementing the FDA requirement of using random-effects linear models for the analyses of bioequivalence studies. This article presents tables for sample-size evaluations of average bioequivalence studies based on the two crossover designs used in the EQUIGEN studies: the four-period, two-sequence, two-formulation design, and the six-period, three-sequence, three-formulation design. Sample-size computations assume that random-effects linear models are used in bioequivalence analyses with crossover designs. Random-effects linear models have been traditionally viewed by many pharmacologists and clinical researchers as just mathematical devices to analyze repeated-measures data. In contrast, a modern view of these models attributes an important mathematical role in theoretical formulations in personalized medicine to them, because these models not only have parameters that represent average patients, but also have parameters that represent individual patients. Moreover, the notation and language of random-effects linear models have evolved over the years. Thus, another goal of this article is to provide a presentation of the statistical modeling of data from bioequivalence studies that highlights the modern view of these models, with special emphasis on power analyses and sample-size computations.

A Crossover Design for Comparative Efficacy: A 36-Week Randomized Trial of Bevacizumab and Ranibizumab for Diabetic Macular Edema.

PubMed

Wiley, Henry E; Thompson, Darby J S; Bailey, Clare; Chew, Emily Y; Cukras, Catherine A; Jaffe, Glenn J; Lee, Richard W J; Loken, Erin K; Meyerle, Catherine B; Wong, Wai; Ferris, Frederick L

2016-04-01

To investigate the comparative efficacy of bevacizumab (Avastin) and ranibizumab (Lucentis; both Genentech, Inc, South San Francisco, CA) for diabetic macular edema (DME) using a crossover study design. Randomized, double-masked, 36-week, 3-period crossover clinical trial. Fifty-six subjects with DME involving the center of the macula in one or both eyes. Monthly intravitreous injections of bevacizumab (1.25 mg) or ranibizumab (0.3 mg). Comparison of mean changes in visual acuity and central retinal thickness, tested using a linear mixed-effects model. Based on the linear mixed-effects model, the 3-month estimated mean improvement in visual acuity was 5.3 letters for bevacizumab and 6.6 letters for ranibizumab (difference, 1.3 letters; P = 0.039). Estimated change in optical coherence tomography (OCT) central subfield mean thickness (CSMT) was -89 μm for bevacizumab and -137 μm for ranibizumab (difference, 48 μm; P < 0.001). Incorporating cumulative treatment benefit, the model yielded a predicted 36-week (9-month) average improvement in visual acuity of 7.1 letters (95% confidence interval [CI], 5.0-9.2) for bevacizumab and 8.4 letters (95% CI, 6.3-10.5) for ranibizumab, and a change in OCT CSMT of -128 μm (95% CI, -155 to -100) for bevacizumab and -176 μm (95% CI, -202 to -149) for ranibizumab. There was no significant treatment-by-period interaction (i.e., treatment difference was constant in all 3 periods), nor was there a significant differential carryover effect from one period to the next. This trial demonstrated a statistically significant but small relative clinical benefit of ranibizumab compared with bevacizumab for treatment of DME, using a markedly reduced sample size relative to a full comparative efficacy study. The effects on visual acuity and central retinal thickness for the 2 drugs are consistent with those reported at 1 year for the concurrent parallel-group trial by the Diabetic Retinopathy Clinical Research Network testing bevacizumab, ranibizumab, and aflibercept for DME. The 3-period crossover design allowed for meaningful and efficient comparison, suggesting that this approach may be useful for future comparative efficacy studies of anti-vascular endothelial growth factor drugs for DME. Published by Elsevier Inc.

The impact of resource quality on the evolution of virulence in spatially heterogeneous environments.

PubMed

Su, Min; Boots, Mike

2017-03-07

Understanding the drivers of parasite evolution and in particular disease virulence remains a major focus of evolutionary theory. Here, we examine the role of resource quality and in particular spatial environmental heterogeneity in the distribution of these resources on the evolution of virulence. There may be direct effects of resources on host susceptibility and pathogenicity alongside effects on reproduction that indirectly impact host-parasite population dynamics. Therefore, we assume that high resource quality may lead to both increased host reproduction and/or increased disease resistance. In completely mixed populations there is no effect of resource quality on the outcome of disease evolution. However, when there are local interactions higher resource quality generally selects for higher virulence/transmission for both linear and saturating transmission-virulence trade-off assumptions. The exception is that in castrators (i.e., infected hosts have no reproduction), higher virulence is selected for both low and high resource qualities at mixed local and global infection. Heterogeneity in the distribution of environment resources only has an effect on the outcome in castrators where random distributions generally select for higher virulence. Overall, our results further underline the importance of considering spatial structure in order to understand evolutionary processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Accelerating Improvement and Narrowing Gaps: Trends in Patients' Experiences with Hospital Care Reflected in HCAHPS Public Reporting.

PubMed

Elliott, Marc N; Cohea, Christopher W; Lehrman, William G; Goldstein, Elizabeth H; Cleary, Paul D; Giordano, Laura A; Beckett, Megan K; Zaslavsky, Alan M

2015-12-01

Measure HCAHPS improvement in hospitals participating in the second and fifth years of HCAHPS public reporting; determine whether change is greater for some hospital types. Surveys from 4,822,960 adult inpatients discharged July 2007-June 2008 or July 2010-June 2011 from 3,541 U.S. hospitals. Linear mixed-effect regression models with fixed effects for time, patient mix, and hospital characteristics (bedsize, ownership, Census division, teaching status, Critical Access status); random effects for hospitals and hospital-time interactions; fixed-effect interactions of hospital characteristics and patient characteristics (gender, health, education) with time predicted HCAHPS measures correcting for regression-to-the-mean biases. National probability sample of adult inpatients in any of four approved survey modes. HCAHPS scores increased by 2.8 percentage points from 2008 to 2011 in the most positive response category. Among the middle 95 percent of hospitals, changes ranged from a 5.1 percent decrease to a 10.2 percent gain overall. The greatest improvement was in for-profit and larger (200 or more beds) hospitals. Five years after HCAHPS public reporting began, meaningful improvement of patients' hospital care experiences continues, especially among initially low-scoring hospitals, reducing some gaps among hospitals. © Health Research and Educational Trust.

A Gaussian Mixture Model Representation of Endmember Variability in Hyperspectral Unmixing

NASA Astrophysics Data System (ADS)

Zhou, Yuan; Rangarajan, Anand; Gader, Paul D.

2018-05-01

Hyperspectral unmixing while considering endmember variability is usually performed by the normal compositional model (NCM), where the endmembers for each pixel are assumed to be sampled from unimodal Gaussian distributions. However, in real applications, the distribution of a material is often not Gaussian. In this paper, we use Gaussian mixture models (GMM) to represent the endmember variability. We show, given the GMM starting premise, that the distribution of the mixed pixel (under the linear mixing model) is also a GMM (and this is shown from two perspectives). The first perspective originates from the random variable transformation and gives a conditional density function of the pixels given the abundances and GMM parameters. With proper smoothness and sparsity prior constraints on the abundances, the conditional density function leads to a standard maximum a posteriori (MAP) problem which can be solved using generalized expectation maximization. The second perspective originates from marginalizing over the endmembers in the GMM, which provides us with a foundation to solve for the endmembers at each pixel. Hence, our model can not only estimate the abundances and distribution parameters, but also the distinct endmember set for each pixel. We tested the proposed GMM on several synthetic and real datasets, and showed its potential by comparing it to current popular methods.

Mixed models for selection of Jatropha progenies with high adaptability and yield stability in Brazilian regions.

PubMed

Teodoro, P E; Bhering, L L; Costa, R D; Rocha, R B; Laviola, B G

2016-08-19

The aim of this study was to estimate genetic parameters via mixed models and simultaneously to select Jatropha progenies grown in three regions of Brazil that meet high adaptability and stability. From a previous phenotypic selection, three progeny tests were installed in 2008 in the municipalities of Planaltina-DF (Midwest), Nova Porteirinha-MG (Southeast), and Pelotas-RS (South). We evaluated 18 families of half-sib in a randomized block design with three replications. Genetic parameters were estimated using restricted maximum likelihood/best linear unbiased prediction. Selection was based on the harmonic mean of the relative performance of genetic values method in three strategies considering: 1) performance in each environment (with interaction effect); 2) performance in each environment (with interaction effect); and 3) simultaneous selection for grain yield, stability and adaptability. Accuracy obtained (91%) reveals excellent experimental quality and consequently safety and credibility in the selection of superior progenies for grain yield. The gain with the selection of the best five progenies was more than 20%, regardless of the selection strategy. Thus, based on the three selection strategies used in this study, the progenies 4, 11, and 3 (selected in all environments and the mean environment and by adaptability and phenotypic stability methods) are the most suitable for growing in the three regions evaluated.

Physician-based activity counseling: intervention effects on mediators of motivational readiness for physical activity.

PubMed

Pinto, B M; Lynn, H; Marcus, B H; DePue, J; Goldstein, M G

2001-01-01

In theory-based interventions for behavior change, there is a need to examine the effects of interventions on the underlying theoretical constructs and the mediating role of such constructs. These two questions are addressed in the Physically Active for Life study, a randomized trial of physician-based exercise counseling for older adults. Three hundred fifty-five patients participated (intervention n = 181, control n = 174; mean age = 65.6 years). The underlying theories used were the Transtheoretical Model, Social Cognitive Theory and the constructs of decisional balance (benefits and barriers), self-efficacy, and behavioral and cognitive processes of change. Motivational readiness for physical activity and related constructs were assessed at baseline, 6 weeks, and 8 months. Linear or logistic mixed effects models were used to examine intervention effects on the constructs, and logistic mixed effects models were used for mediator analyses. At 6 weeks, the intervention had significant effects on decisional balance, self-efficacy, and behavioral processes, but these effects were not maintained at 8 months. At 6 weeks, only decisional balance and behavioral processes were identified as mediators of motivational readiness outcomes. Results suggest that interventions of greater intensity and duration may be needed for sustained changes in mediators and motivational readiness for physical activity among older adults.

Handling Correlations between Covariates and Random Slopes in Multilevel Models

ERIC Educational Resources Information Center

Bates, Michael David; Castellano, Katherine E.; Rabe-Hesketh, Sophia; Skrondal, Anders

2014-01-01

This article discusses estimation of multilevel/hierarchical linear models that include cluster-level random intercepts and random slopes. Viewing the models as structural, the random intercepts and slopes represent the effects of omitted cluster-level covariates that may be correlated with included covariates. The resulting correlations between…

Low-sensitivity, low-bounce, high-linearity current-controlled oscillator suitable for single-supply mixed-mode instrumentation system.

PubMed

Hwang, Yuh-Shyan; Kung, Che-Min; Lin, Ho-Cheng; Chen, Jiann-Jong

2009-02-01

A low-sensitivity, low-bounce, high-linearity current-controlled oscillator (CCO) suitable for a single-supply mixed-mode instrumentation system is designed and proposed in this paper. The designed CCO can be operated at low voltage (2 V). The power bounce and ground bounce generated by this CCO is less than 7 mVpp when the power-line parasitic inductance is increased to 100 nH to demonstrate the effect of power bounce and ground bounce. The power supply noise caused by the proposed CCO is less than 0.35% in reference to the 2 V supply voltage. The average conversion ratio KCCO is equal to 123.5 GHz/A. The linearity of conversion ratio is high and its tolerance is within +/-1.2%. The sensitivity of the proposed CCO is nearly independent of the power supply voltage, which is less than a conventional current-starved oscillator. The performance of the proposed CCO has been compared with the current-starved oscillator. It is shown that the proposed CCO is suitable for single-supply mixed-mode instrumentation systems.

Random crystal field effects on the integer and half-integer mixed-spin system

NASA Astrophysics Data System (ADS)

Yigit, Ali; Albayrak, Erhan

2018-05-01

In this work, we have focused on the random crystal field effects on the phase diagrams of the mixed spin-1 and spin-5/2 Ising system obtained by utilizing the exact recursion relations (ERR) on the Bethe lattice (BL). The distribution function P(Di) = pδ [Di - D(1 + α) ] +(1 - p) δ [Di - D(1 - α) ] is used to randomize the crystal field.The phase diagrams are found to exhibit second- and first-order phase transitions depending on the values of α, D and p. It is also observed that the model displays tricritical point, isolated point, critical end point and three compensation temperatures for suitable values of the system parameters.

Machine-learning-based calving prediction from activity, lying, and ruminating behaviors in dairy cattle.

PubMed

Borchers, M R; Chang, Y M; Proudfoot, K L; Wadsworth, B A; Stone, A E; Bewley, J M

2017-07-01

The objective of this study was to use automated activity, lying, and rumination monitors to characterize prepartum behavior and predict calving in dairy cattle. Data were collected from 20 primiparous and 33 multiparous Holstein dairy cattle from September 2011 to May 2013 at the University of Kentucky Coldstream Dairy. The HR Tag (SCR Engineers Ltd., Netanya, Israel) automatically collected neck activity and rumination data in 2-h increments. The IceQube (IceRobotics Ltd., South Queensferry, United Kingdom) automatically collected number of steps, lying time, standing time, number of transitions from standing to lying (lying bouts), and total motion, summed in 15-min increments. IceQube data were summed in 2-h increments to match HR Tag data. All behavioral data were collected for 14 d before the predicted calving date. Retrospective data analysis was performed using mixed linear models to examine behavioral changes by day in the 14 d before calving. Bihourly behavioral differences from baseline values over the 14 d before calving were also evaluated using mixed linear models. Changes in daily rumination time, total motion, lying time, and lying bouts occurred in the 14 d before calving. In the bihourly analysis, extreme values for all behaviors occurred in the final 24 h, indicating that the monitored behaviors may be useful in calving prediction. To determine whether technologies were useful at predicting calving, random forest, linear discriminant analysis, and neural network machine-learning techniques were constructed and implemented using R version 3.1.0 (R Foundation for Statistical Computing, Vienna, Austria). These methods were used on variables from each technology and all combined variables from both technologies. A neural network analysis that combined variables from both technologies at the daily level yielded 100.0% sensitivity and 86.8% specificity. A neural network analysis that combined variables from both technologies in bihourly increments was used to identify 2-h periods in the 8 h before calving with 82.8% sensitivity and 80.4% specificity. Changes in behavior and machine-learning alerts indicate that commercially marketed behavioral monitors may have calving prediction potential. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Comparative Effectiveness of Two Walking Interventions on Participation, Step Counts, and Health.

PubMed

Smith-McLallen, Aaron; Heller, Debbie; Vernisi, Kristin; Gulick, Diana; Cruz, Samantha; Snyder, Richard L

2017-03-01

To (1) compare the effects of two worksite-based walking interventions on employee participation rates; (2) compare average daily step counts between conditions, and; (3) examine the effects of increases in average daily step counts on biometric and psychologic outcomes. We conducted a cluster-randomized trial in which six employer groups were randomly selected and randomly assigned to condition. Four manufacturing worksites and two office-based worksite served as the setting. A total of 474 employees from six employer groups were included. A standard walking program was compared to an enhanced program that included incentives, feedback, competitive challenges, and monthly wellness workshops. Walking was measured by self-reported daily step counts. Survey measures and biometric screenings were administered at baseline and 3, 6, and 9 months after baseline. Analysis used linear mixed models with repeated measures. During 9 months, participants in the enhanced condition averaged 726 more steps per day compared with those in the standard condition (p < .001). A 1000-step increase in average daily steps was associated with significant weight loss for both men (-3.8 lbs.) and women (-2.1 lbs.), and reductions in body mass index (-0.41 men, -0.31 women). Higher step counts were also associated with improvements in mood, having more energy, and higher ratings of overall health. An enhanced walking program significantly increases participation rates and daily step counts, which were associated with weight loss and reductions in body mass index.

The Effect of Changes in Physical Activity on Sedentary Behavior: Results From a Randomized Lifestyle Intervention Trial.

PubMed

Siddique, Juned; de Chavez, Peter John; Craft, Lynette L; Freedson, Patty; Spring, Bonnie

2017-07-01

To investigate whether changes in physical activity (PA) have an impact on sedentary behavior (SB) during a lifestyle intervention. Study design was a randomized trial. Participants (n = 204) were individuals with low PA and high sedentary leisure screen time from the Chicago area. Participants were randomized to either increase PA (iPA) or decrease sedentary leisure (dSED). The intervention consisted of decision support, coaching, and financial incentives. For iPA participants, the goal was at least 60 min/d of self-reported moderate-tovigorous-intensity PA (MVPA). For dSED participants the goal was less than 90 min/d of sedentary leisure screen time. Daily accelerometer-based measures of SB and bout-corrected MVPA were obtained. Linear mixed-effects models were fit to estimate the effect of the intervention on MVPA and total SB and to estimate the effect of daily changes in MVPA on daily SB. The iPA participants increased their bout-corrected MVPA by 14 min/d (p < .001) and decreased their total SB by 18 min/d (p < .001). The dSED participants did not significantly change their PA or their total SB. On days when participants exercised, each 10-minute bout of MVPA was associated with a 6-minute decrease in SB on the same day (p < .001). In an intervention study designed to increase MVPA, participants who increase their time spent exercising will obtain much of this time by reducing their SB.

Brief report: pulmonary auscultation in the operating room: a prospective randomized blinded trial comparing electronic and conventional stethoscopes.

PubMed

Hoffmann, Clement; Falzone, Elisabeth; Verret, Catherine; Pasquier, Pierre; Leclerc, Thomas; Donat, Nicolas; Jost, Daniel; Mérat, Stephane; Maurice, Guillaume de Saint; Lenoir, Bernard; Auroy, Yves; Tourtier, Jean-Pierre

2013-09-01

We compared the subjective quality of pulmonary auscultation between 2 acoustic stethoscopes (Holtex Ideal® and Littmann Cardiology III®) and an electronic stethoscope (Littmann 3200®) in the operating room. A prospective double-blind randomized study with an evaluation during mechanical ventilation was performed in 100 patients. After each examination, the listeners using a numeric scale (0-10) rated the quality of auscultation. Auscultation quality was compared in patients among stethoscopes with a multilevel mixed-effects linear regression with random intercept (operator effect), adjusted on significant factors in univariate analysis. A significant difference was defined as P < 0.05. One hundred comparative evaluations of pulmonary auscultation were performed. The quality of auscultation was rated 8.2 ± 1.6 for the electronic stethoscope, 7.4 ± 1.8 for the Littmann Cardiology III, and 4.6 ± 1.8 for the Holtex Ideal. Compared with Holtex Ideal, auscultation quality was significantly higher with other stethoscopes (P < 0.0001). Compared with Littmann Cardiology III, auscultation quality was significantly higher with Littmann 3200 electronic stethoscope (β = 0.9 [95% confidence interval, 0.5-1.3]). An electronic stethoscope can provide a better quality of pulmonary auscultation than acoustic stethoscopes in the operating room, yet with a magnitude of improvement marginally higher than that provided with a high performance acoustic stethoscope. Whether this can translate into a clinically relevant benefit requires further studies.

Growth Outcomes of Preterm Infants Exposed to Different Oxygen Saturation Target Ranges from Birth

PubMed Central

Navarrete, Cristina T.; Wrage, Lisa A.; Carlo, Waldemar A.; Walsh, Michele C.; Rich, Wade; Gantz, Marie G.; Das, Abhik; Schibler, Kurt; Newman, Nancy S.; Piazza, Anthony J.; Poindexter, Brenda B.; Shankaran, Seetha; Sánchez, Pablo J.; Morris, Brenda H.; Frantz, Ivan D.; Van Meurs, Krisa P.; Cotten, C. Michael; Ehrenkranz, Richard A.; Bell, Edward F.; Watterberg, Kristi L.; Higgins, Rosemary D.; Duara, Shahnaz

2017-01-01

Objective To test whether infants randomized to a lower oxygen saturation (SpO2) target range while on supplemental oxygen from birth will have better growth velocity from birth to 36 weeks postmenstrual age (PMA), and less growth failure at 36 weeks PMA and 18–22 months corrected age. Study design We evaluated a subgroup of 810 preterm infants from the Surfactant, Positive Pressure, and Oxygenation Randomized Trial, randomized at birth to lower (85–89%, n=402, GA 26 ± 1wk, BW 839 ± 186 g) or higher (91–95%, n=408, GA 26 ± 1wk, BW 840 ± 191 g) SpO2 target ranges. Anthropometric measures were obtained at birth, postnatal days 7, 14, 21, and 28; then at 32 and 36 weeks PMA, and 18–22 months corrected age. Growth velocities were estimated using the exponential method and analyzed using linear mixed models. Poor growth outcome, defined as weight < 10th percentile at 36 weeks PMA and 18–22 months corrected age, was compared across the two treatment groups using robust Poisson regression. Results Growth outcomes including growth at 36 weeks PMA and 18–22 months corrected age, as well as growth velocity were similar in the lower and higher SpO2 target groups. Conclusion Targeting different oxygen saturation ranges between 85% and 95% from birth did not impact growth velocity or reduce growth failure in preterm infants. PMID:27344218

[Work-Related Medical Rehabilitation in Cancer Rehabilitation - Short-Term Results from a Cluster-Randomized Multicenter-Trial].

PubMed

Wienert, Julian; Bethge, Matthias

2018-05-25

Rehabilitation programs that support return to work become increasingly relevant for cancer survivors. In Germany, such programs were established as work-related medical rehabilitation (WMR). The study investigated whether WMR leads to better results compared to medical rehabilitation (MR). We report effects on secondary outcomes when the rehabilitation program was completed. Clusters of participants were randomly assigned to WMR or MR. Patients of working age and an elevated risk of not returning to work were included. The grade of implementation was assessed by dose delivered and dose received. Study outcomes were assessed using scales measuring functioning and symptoms, coping with illness as well as self-reported work ability. Treatment effects were estimated using mixed linear models. From 232 planned randomized intervention groups, 165 (71%) were realized. In total, 476 patients were included. Mean age of participants was 50.7 years (SD=7.3). Most frequent primary diagnoses were malignant neoplasms of the breast. Participants in the WMR program reported significantly better outcomes regarding quality of life (SMD=0.17-0.25), fatigue (SMD=0.18-0.27), coping with illness (SMD=0.17-0.22), and self-reported work-ability (SMD=0.16) compared to participants in MR program (all p<0.05). The results indicate a positive effect in favor of WMR for cancer patients with an elevated risk of not returning to work at the end of their treatment. © Georg Thieme Verlag KG Stuttgart · New York.

Long-lasting effects of a new memory self-efficacy training for stroke patients: a randomized controlled trial.

PubMed

Aben, Laurien; Heijenbrok-Kal, Majanka H; Ponds, Rudolf W H M; Busschbach, Jan J V; Ribbers, Gerard M

2014-01-01

This study aims to determine the long-term effects of a new Memory Self-efficacy (MSE) training program for stroke patients on MSE, depression, and quality of life. In a randomized controlled trial, patients were allocated to a MSE training or a peer support group. Outcome measures were MSE, depression, and quality of life, measured with the Metamemory-In-Adulthood questionnaire, Center for Epidemiological Studies-Depression Scale (CES-D), and the Who-Qol Bref questionnaire, respectively. We used linear mixed models to compare the outcomes of both groups immediately after training, after 6 months, and after 12 months, adjusted for baseline. In total, 153 former inpatients from 2 rehabilitation centers were randomized-77 to the experimental and 76 to the control group. MSE increased significantly more in the experimental group and remained significantly higher than in the control group after 6 and 12 months (B = 0.42; P = .010). Psychological quality of life also increased more in the experimental group but not significantly (B = 0.09; P = .077). However, in the younger subgroup of patients (<65 years old), psychological quality of life significantly improved in the experimental group compared to the control group and remained significantly higher over time (B = 0.14; P = .030). Other outcome measures were not significantly different between both groups. An MSE training program improved MSE and psychological quality of life in stroke patients aged <65 years. These effects persisted during 12 months of follow-up.

NIMROD: a program for inference via a normal approximation of the posterior in models with random effects based on ordinary differential equations.

PubMed

Prague, Mélanie; Commenges, Daniel; Guedj, Jérémie; Drylewicz, Julia; Thiébaut, Rodolphe

2013-08-01

Models based on ordinary differential equations (ODE) are widespread tools for describing dynamical systems. In biomedical sciences, data from each subject can be sparse making difficult to precisely estimate individual parameters by standard non-linear regression but information can often be gained from between-subjects variability. This makes natural the use of mixed-effects models to estimate population parameters. Although the maximum likelihood approach is a valuable option, identifiability issues favour Bayesian approaches which can incorporate prior knowledge in a flexible way. However, the combination of difficulties coming from the ODE system and from the presence of random effects raises a major numerical challenge. Computations can be simplified by making a normal approximation of the posterior to find the maximum of the posterior distribution (MAP). Here we present the NIMROD program (normal approximation inference in models with random effects based on ordinary differential equations) devoted to the MAP estimation in ODE models. We describe the specific implemented features such as convergence criteria and an approximation of the leave-one-out cross-validation to assess the model quality of fit. In pharmacokinetics models, first, we evaluate the properties of this algorithm and compare it with FOCE and MCMC algorithms in simulations. Then, we illustrate NIMROD use on Amprenavir pharmacokinetics data from the PUZZLE clinical trial in HIV infected patients. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Epidermis Microstructure Inspired Graphene Pressure Sensor with Random Distributed Spinosum for High Sensitivity and Large Linearity.

PubMed

Pang, Yu; Zhang, Kunning; Yang, Zhen; Jiang, Song; Ju, Zhenyi; Li, Yuxing; Wang, Xuefeng; Wang, Danyang; Jian, Muqiang; Zhang, Yingying; Liang, Renrong; Tian, He; Yang, Yi; Ren, Tian-Ling

2018-03-27

Recently, wearable pressure sensors have attracted tremendous attention because of their potential applications in monitoring physiological signals for human healthcare. Sensitivity and linearity are the two most essential parameters for pressure sensors. Although various designed micro/nanostructure morphologies have been introduced, the trade-off between sensitivity and linearity has not been well balanced. Human skin, which contains force receptors in a reticular layer, has a high sensitivity even for large external stimuli. Herein, inspired by the skin epidermis with high-performance force sensing, we have proposed a special surface morphology with spinosum microstructure of random distribution via the combination of an abrasive paper template and reduced graphene oxide. The sensitivity of the graphene pressure sensor with random distribution spinosum (RDS) microstructure is as high as 25.1 kPa -1 in a wide linearity range of 0-2.6 kPa. Our pressure sensor exhibits superior comprehensive properties compared with previous surface-modified pressure sensors. According to simulation and mechanism analyses, the spinosum microstructure and random distribution contribute to the high sensitivity and large linearity range, respectively. In addition, the pressure sensor shows promising potential in detecting human physiological signals, such as heartbeat, respiration, phonation, and human motions of a pushup, arm bending, and walking. The wearable pressure sensor array was further used to detect gait states of supination, neutral, and pronation. The RDS microstructure provides an alternative strategy to improve the performance of pressure sensors and extend their potential applications in monitoring human activities.

Decay of random correlation functions for unimodal maps

NASA Astrophysics Data System (ADS)

Baladi, Viviane; Benedicks, Michael; Maume-Deschamps, Véronique

2000-10-01

Since the pioneering results of Jakobson and subsequent work by Benedicks-Carleson and others, it is known that quadratic maps tfa( χ) = a - χ2 admit a unique absolutely continuous invariant measure for a positive measure set of parameters a. For topologically mixing tfa, Young and Keller-Nowicki independently proved exponential decay of correlation functions for this a.c.i.m. and smooth observables. We consider random compositions of small perturbations tf + ωt, with tf = tfa or another unimodal map satisfying certain nonuniform hyperbolicity axioms, and ωt chosen independently and identically in [-ɛ, ɛ]. Baladi-Viana showed exponential mixing of the associated Markov chain, i.e., averaging over all random itineraries. We obtain stretched exponential bounds for the random correlation functions of Lipschitz observables for the sample measure μωof almost every itinerary.

The MHOST finite element program: 3-D inelastic analysis methods for hot section components. Volume 1: Theoretical manual

NASA Technical Reports Server (NTRS)

Nakazawa, Shohei

1991-01-01

Formulations and algorithms implemented in the MHOST finite element program are discussed. The code uses a novel concept of the mixed iterative solution technique for the efficient 3-D computations of turbine engine hot section components. The general framework of variational formulation and solution algorithms are discussed which were derived from the mixed three field Hu-Washizu principle. This formulation enables the use of nodal interpolation for coordinates, displacements, strains, and stresses. Algorithmic description of the mixed iterative method includes variations for the quasi static, transient dynamic and buckling analyses. The global-local analysis procedure referred to as the subelement refinement is developed in the framework of the mixed iterative solution, of which the detail is presented. The numerically integrated isoparametric elements implemented in the framework is discussed. Methods to filter certain parts of strain and project the element discontinuous quantities to the nodes are developed for a family of linear elements. Integration algorithms are described for linear and nonlinear equations included in MHOST program.

Capacity-building and clinical competence in infectious disease in Uganda: a mixed-design study with pre/post and cluster-randomized trial components.

PubMed

Weaver, Marcia R; Crozier, Ian; Eleku, Simon; Makanga, Gyaviira; Mpanga Sebuyira, Lydia; Nyakake, Janepher; Thompson, MaryLou; Willis, Kelly

2012-01-01

Best practices for training mid-level practitioners (MLPs) to improve global health-services are not well-characterized. Two hypotheses were: 1) Integrated Management of Infectious Disease (IMID) training would improve clinical competence as tested with a single arm, pre-post design, and 2) on-site support (OSS) would yield additional improvements as tested with a cluster-randomized trial. Thirty-six Ugandan health facilities (randomized 1∶1 to parallel OSS and control arms) enrolled two MLPs each. All MLPs participated in IMID (3-week core course, two 1-week boost sessions, distance learning). After the 3-week course, OSS-arm trainees participated in monthly OSS. Twelve written case scenarios tested clinical competencies in HIV/AIDS, tuberculosis, malaria, and other infectious diseases. Each participant completed different randomly-assigned blocks of four scenarios before IMID (t0), after 3-week course (t1), and after second boost course (t2, 24 weeks after t1). Scoring guides were harmonized with IMID content and Ugandan national policy. Score analyses used a linear mixed-effects model. The primary outcome measure was longitudinal change in scenario scores. Scores were available for 856 scenarios. Mean correct scores at t0, t1, and t2 were 39.3%, 49.1%, and 49.6%, respectively. Mean score increases (95% CI, p-value) for t0-t1 (pre-post period) and t1-t2 (parallel-arm period) were 12.1 ((9.6, 14.6), p<0.001) and -0.6 ((-3.1, +1.9), p = 0.647) percent for OSS arm and 7.5 ((5.0, 10.0), p<0.001) and 1.6 ((-1.0, +4.1), p = 0.225) for control arm. The estimated mean difference in t1 to t2 score change, comparing arm A (participated in OSS) vs. arm B was -2.2 ((-5.8, +1.4), p = 0.237). From t0-t2, mean scores increased for all 12 scenarios. Clinical competence increased significantly after a 3-week core course; improvement persisted for 24 weeks. No additional impact of OSS was observed. Data on clinical practice, facility-level performance and health outcomes will complete assessment of overall impact of IMID and OSS. ClinicalTrials.gov NCT01190540.

Study Protocol of MINI SALTEN: a technology-based multi-component intervention in the school environment targeting healthy habits of first grade children and their parents.

PubMed

Kovalskys, Irina; Rausch Herscovici, Cecile; Indart Rougier, Paula; De Gregorio, María José; Zonis, Luciana; Orellana, Liliana

2017-05-06

MINI SALTEN is a program developed to increase moderate to vigorous physical activity (PA) and improve eating habits at home and school in first grade children. It aims to assess the effects of a technology family-based and PA school-based intervention. The purpose of this manuscript is to describe the protocol design and the MINISALTEN intervention. This is cluster-randomized controlled trial designed to run from July 2015 to November 2016 in 12 public schools of the city of Buenos Aires, matched for socio-demographic characteristics. The intervention is based on two main components: (a) "active breaks" (AB): implemented during school breaks by a PA instructor; (b) "virtual" (V): web-based contents delivered to the families via a multiplatform application. Using a computer generated random sequence participants are allocated to one of four intervention conditions: (AB), (V), (AB + V), and control (C). Outcomes are measured at baseline and 12 months post intervention, and will include data collected from the child and her/his mother/father or guardian. Primary outcome measures are: PA and sedentary behaviour (measured with accelerometers). Secondary outcome measures related are: percentage of kilocalories (kcal) from added sugars, and from total and saturated fats; grams of fruits and vegetables; and number of snacks and kcal coming from their added sugars and total and saturated fats. Family socio-economic level, home environment, and school environment will also be assessed. Statistical analysis is on an intention-to-treat principle. Baseline characteristics are described using summary measures and mixed models (with school as random effect). The effect of the two interventions will be estimated using a generalized mixed linear model with link and distribution selected according to the type of outcome. Included random effects are: child (or mother/father or guardian) accounting for repeated measures; school accounting for cluster induced by school. The most parsimonious model for each outcome will be reported. The False Discovery Rate criterion will be used to correct for multiple testing in non-planned analyses. It is a pioneer assessment of the impact of a technology-based virtual intervention and a school-based PA program, designed to prevent obesity, and involving the parents at public schools of Buenos Aires. Current Controlled Trials ISRCTN58093412 . Registered March 14th, 2016 (retrospectively registered).

Short term treatment versus long term management of neck and back disability in older adults utilizing spinal manipulative therapy and supervised exercise: a parallel-group randomized clinical trial evaluating relative effectiveness and harms.

PubMed

Vihstadt, Corrie; Maiers, Michele; Westrom, Kristine; Bronfort, Gert; Evans, Roni; Hartvigsen, Jan; Schulz, Craig

2014-01-01

Back and neck disability are frequent in older adults resulting in loss of function and independence. Exercise therapy and manual therapy, like spinal manipulative therapy (SMT), have evidence of short and intermediate term effectiveness for spinal disability in the general population and growing evidence in older adults. For older populations experiencing chronic spinal conditions, long term management may be more appropriate to maintain improvement and minimize the impact of future exacerbations. Research is limited comparing short courses of treatment to long term management of spinal disability. The primary aim is to compare the relative effectiveness of 12 weeks versus 36 weeks of SMT and supervised rehabilitative exercise (SRE) in older adults with back and neck disability. Randomized, mixed-methods, comparative effectiveness trial conducted at a university-affiliated research clinic in the Minneapolis/St. Paul, Minnesota metropolitan area. Independently ambulatory community dwelling adults ≥ 65 years of age with back and neck disability of minimum 12 weeks duration (n = 200). 12 weeks SMT + SRE or 36 weeks SMT + SRE. Blocked 1:1 allocation; computer generated scheme, concealed in sequentially numbered, opaque, sealed envelopes. Functional outcome examiners are blinded to treatment allocation; physical nature of the treatments prevents blinding of participants and providers to treatment assignment. 36 weeks post-randomization. Self-report questionnaires administered at 2 baseline visits and 4, 12, 24, 36, 52, and 78 weeks post-randomization. Primary outcomes include back and neck disability, measured by the Oswestry Disability Index and Neck Disability Index. Secondary outcomes include pain, general health status, improvement, self-efficacy, kinesiophobia, satisfaction, and medication use. Functional outcome assessment occurs at baseline and week 37 for hand grip strength, short physical performance battery, and accelerometry. Individual qualitative interviews are conducted when treatment ends. Data on expectations, falls, side effects, and adverse events are systematically collected. Linear mixed-model method for repeated measures to test for between-group differences with baseline values as covariates. Treatments that address the management of spinal disability in older adults may have far reaching implications for patient outcomes, clinical guidelines, and healthcare policy. www.ClinicalTrials.gov; Identifier: NCT01057706.

Personality disorder moderates outcome in short- and long-term group analytic psychotherapy: A randomized clinical trial.

PubMed

Lorentzen, Steinar; Ruud, Torleif; Fjeldstad, Anette; Høglend, Per A

2015-06-01

In a randomized clinical trial, short- and long-term psychodynamic group psychotherapy (STG and LTG, respectively) schedules were equally effective for the 'typical' patient during a 3-year study period. Although several studies have reported good effects for patients with personality disorders (PD) in diverse forms of psychotherapy, the significance of treatment duration is unclear. Therefore, we tested the hypothesis that PD patients would improve more during and after LTG than STG. A randomized, longitudinal, prospective study contrasting the outcomes during and after short- and long-term dynamic group psychotherapies. One hundred and sixty-seven outpatients with mood disorders, anxiety disorders, or PD were randomized to STG or LTG (respectively, 20 or 80 weekly sessions of 90 min each). Outcome measures are as follows: symptoms (SCL-90-R), interpersonal problems (IIP-C), and psychosocial functioning (GAF split version: GAF-Symptom and GAF-Function). PD pathology (number of PD criteria items) was selected a priori as a putative moderator of treatment effects. Change during the 3-year study period was assessed using linear mixed models. The study was registered at ClinicalTrials.gov as NCT 00021417. Our hypothesis was supported, as patients with PD improved significantly more regarding all outcome variables in LTG than STG. For patients without PD, the rate of change was similar across 3 years; however, the rate of change in symptoms and interpersonal problems was higher in STG during the first 6 months. The effectiveness of LTG is higher for patients with co-morbid PD. Patients without PD do not appear to experience additional gain from LTG. Clinical implications: LTG demonstrates better effectiveness than STG for patients with personality disorder co-morbidity (PD). Patients without PD do not appear to experience additional gain from attending LTG. Correct initial allocation to treatment duration may prevent disruptive breaks in relationships and lead to both human and economic cost savings. Limitations: Trials on mixed diagnostic samples may limit the ability to fully assess change for specific diagnostic groups. Therapists were unable to select patients and compose their own groups. Although this condition might increase the generalizability of the results, it may also have restricted the therapists and the clinical situation inadvertently. © 2014 The British Psychological Society.

Correlation and simple linear regression.

PubMed

Eberly, Lynn E

2007-01-01

This chapter highlights important steps in using correlation and simple linear regression to address scientific questions about the association of two continuous variables with each other. These steps include estimation and inference, assessing model fit, the connection between regression and ANOVA, and study design. Examples in microbiology are used throughout. This chapter provides a framework that is helpful in understanding more complex statistical techniques, such as multiple linear regression, linear mixed effects models, logistic regression, and proportional hazards regression.

Stochastic constructions of flows of rank 1

NASA Astrophysics Data System (ADS)

Prikhod'ko, A. A.

2001-12-01

Automorphisms of rank 1 appeared in the well-known papers of Chacon (1965), who constructed an example of a weakly mixing automorphism not having the strong mixing property, and Ornstein (1970), who proved the existence of mixing automorphisms without a square root. Ornstein's construction is essentially stochastic, since its parameters are chosen in a "sufficiently random manner" according to a certain random law.In the present article it is shown that mixing flows of rank 1 exist. The construction given is also stochastic and is based to a large extent on ideas in Ornstein's paper. At the same time it complements Ornstein's paper and makes it more transparent. The construction can be used also to obtain automorphisms with various approximation and statistical properties. It is established that the new examples of dynamical systems are not isomorphic to Ornstein automorphisms, that is, they are qualitatively new.

Stochastic constructions of flows of rank 1

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

Prikhod'ko, A A

2001-12-31

Automorphisms of rank 1 appeared in the well-known papers of Chacon (1965), who constructed an example of a weakly mixing automorphism not having the strong mixing property, and Ornstein (1970), who proved the existence of mixing automorphisms without a square root. Ornstein's construction is essentially stochastic, since its parameters are chosen in a 'sufficiently random manner' according to a certain random law. In the present article it is shown that mixing flows of rank 1 exist. The construction given is also stochastic and is based to a large extent on ideas in Ornstein's paper. At the same time it complementsmore » Ornstein's paper and makes it more transparent. The construction can be used also to obtain automorphisms with various approximation and statistical properties. It is established that the new examples of dynamical systems are not isomorphic to Ornstein automorphisms, that is, they are qualitatively new.« less

Short term treatment versus long term management of neck and back disability in older adults utilizing spinal manipulative therapy and supervised exercise: a parallel-group randomized clinical trial evaluating relative effectiveness and harms

PubMed Central

2014-01-01

Background Back and neck disability are frequent in older adults resulting in loss of function and independence. Exercise therapy and manual therapy, like spinal manipulative therapy (SMT), have evidence of short and intermediate term effectiveness for spinal disability in the general population and growing evidence in older adults. For older populations experiencing chronic spinal conditions, long term management may be more appropriate to maintain improvement and minimize the impact of future exacerbations. Research is limited comparing short courses of treatment to long term management of spinal disability. The primary aim is to compare the relative effectiveness of 12 weeks versus 36 weeks of SMT and supervised rehabilitative exercise (SRE) in older adults with back and neck disability. Methods/Design Randomized, mixed-methods, comparative effectiveness trial conducted at a university-affiliated research clinic in the Minneapolis/St. Paul, Minnesota metropolitan area. Participants Independently ambulatory community dwelling adults ≥ 65 years of age with back and neck disability of minimum 12 weeks duration (n = 200). Interventions 12 weeks SMT + SRE or 36 weeks SMT + SRE. Randomization Blocked 1:1 allocation; computer generated scheme, concealed in sequentially numbered, opaque, sealed envelopes. Blinding Functional outcome examiners are blinded to treatment allocation; physical nature of the treatments prevents blinding of participants and providers to treatment assignment. Primary endpoint 36 weeks post-randomization. Data collection Self-report questionnaires administered at 2 baseline visits and 4, 12, 24, 36, 52, and 78 weeks post-randomization. Primary outcomes include back and neck disability, measured by the Oswestry Disability Index and Neck Disability Index. Secondary outcomes include pain, general health status, improvement, self-efficacy, kinesiophobia, satisfaction, and medication use. Functional outcome assessment occurs at baseline and week 37 for hand grip strength, short physical performance battery, and accelerometry. Individual qualitative interviews are conducted when treatment ends. Data on expectations, falls, side effects, and adverse events are systematically collected. Primary analysis Linear mixed-model method for repeated measures to test for between-group differences with baseline values as covariates. Discussion Treatments that address the management of spinal disability in older adults may have far reaching implications for patient outcomes, clinical guidelines, and healthcare policy. Trial registry www.ClinicalTrials.gov; Identifier: NCT01057706. PMID:25478141

Comparison of linear, skewed-linear, and proportional hazard models for the analysis of lambing interval in Ripollesa ewes.

PubMed

Casellas, J; Bach, R

2012-06-01

Lambing interval is a relevant reproductive indicator for sheep populations under continuous mating systems, although there is a shortage of selection programs accounting for this trait in the sheep industry. Both the historical assumption of small genetic background and its unorthodox distribution pattern have limited its implementation as a breeding objective. In this manuscript, statistical performances of 3 alternative parametrizations [i.e., symmetric Gaussian mixed linear (GML) model, skew-Gaussian mixed linear (SGML) model, and piecewise Weibull proportional hazard (PWPH) model] have been compared to elucidate the preferred methodology to handle lambing interval data. More specifically, flock-by-flock analyses were performed on 31,986 lambing interval records (257.3 ± 0.2 d) from 6 purebred Ripollesa flocks. Model performances were compared in terms of deviance information criterion (DIC) and Bayes factor (BF). For all flocks, PWPH models were clearly preferred; they generated a reduction of 1,900 or more DIC units and provided BF estimates larger than 100 (i.e., PWPH models against linear models). These differences were reduced when comparing PWPH models with different number of change points for the baseline hazard function. In 4 flocks, only 2 change points were required to minimize the DIC, whereas 4 and 6 change points were needed for the 2 remaining flocks. These differences demonstrated a remarkable degree of heterogeneity across sheep flocks that must be properly accounted for in genetic evaluation models to avoid statistical biases and suboptimal genetic trends. Within this context, all 6 Ripollesa flocks revealed substantial genetic background for lambing interval with heritabilities ranging between 0.13 and 0.19. This study provides the first evidence of the suitability of PWPH models for lambing interval analysis, clearly discarding previous parametrizations focused on mixed linear models.

Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models.

PubMed

Yue, Chen; Chen, Shaojie; Sair, Haris I; Airan, Raag; Caffo, Brian S

2015-09-01

Data reproducibility is a critical issue in all scientific experiments. In this manuscript, the problem of quantifying the reproducibility of graphical measurements is considered. The image intra-class correlation coefficient (I2C2) is generalized and the graphical intra-class correlation coefficient (GICC) is proposed for such purpose. The concept for GICC is based on multivariate probit-linear mixed effect models. A Markov Chain Monte Carlo EM (mcm-cEM) algorithm is used for estimating the GICC. Simulation results with varied settings are demonstrated and our method is applied to the KIRBY21 test-retest dataset.

Skew-t partially linear mixed-effects models for AIDS clinical studies.

PubMed

Lu, Tao

2016-01-01

We propose partially linear mixed-effects models with asymmetry and missingness to investigate the relationship between two biomarkers in clinical studies. The proposed models take into account irregular time effects commonly observed in clinical studies under a semiparametric model framework. In addition, commonly assumed symmetric distributions for model errors are substituted by asymmetric distribution to account for skewness. Further, informative missing data mechanism is accounted for. A Bayesian approach is developed to perform parameter estimation simultaneously. The proposed model and method are applied to an AIDS dataset and comparisons with alternative models are performed.

Predictors of changes in gait performance over four years in persons with late effects of polio.

PubMed

Flansbjer, Ulla-Britt; Lexell, Jan; Brogårdh, Christina

2017-01-01

Reduced gait performance is common in persons with late effects of polio. To identify predictors of change in gait performance over four years in persons with late effects of polio. Gait performance was assessed annually in 51 ambulatory persons (mean age 64 years, SD 6) by the Timed "Up & Go" (TUG), Comfortable and Fast Gait Speed (CGS, FGS), and 6-Minute Walk Test (6MWT). Isokinetic knee extensor and flexor muscle strength was measured with a Biodex dynamometer. Mixed Linear Models were used to analyze changes in gait performance and to identify any predictors of change among the covariates gender, age, body mass index, time with new symptoms, baseline reduction in gait performance and knee muscle strength. There were significant linear effects over time (reduction per year) for three gait performance tests; CGS (0.8%; p < 0.05), FGS (1.7%; p < 0.001), and 6MWT (0.7%; p < 0.05) with significant random effects for all tests. The strongest predictor of a change in gait performance was the individual variations in the knee flexor strength (p < 0.001). The small gradual reduction in gait performance over time in persons with late effects of polio is primarily determined by the individual variations in the knee flexor strength.

Predictive models of poly(ethylene-terephthalate) film degradation under multi-factor accelerated weathering exposures

PubMed Central

Ngendahimana, David K.; Fagerholm, Cara L.; Sun, Jiayang; Bruckman, Laura S.

2017-01-01

Accelerated weathering exposures were performed on poly(ethylene-terephthalate) (PET) films. Longitudinal multi-level predictive models as a function of PET grades and exposure types were developed for the change in yellowness index (YI) and haze (%). Exposures with similar change in YI were modeled using a linear fixed-effects modeling approach. Due to the complex nature of haze formation, measurement uncertainty, and the differences in the samples’ responses, the change in haze (%) depended on individual samples’ responses and a linear mixed-effects modeling approach was used. When compared to fixed-effects models, the addition of random effects in the haze formation models significantly increased the variance explained. For both modeling approaches, diagnostic plots confirmed independence and homogeneity with normally distributed residual errors. Predictive R2 values for true prediction error and predictive power of the models demonstrated that the models were not subject to over-fitting. These models enable prediction under pre-defined exposure conditions for a given exposure time (or photo-dosage in case of UV light exposure). PET degradation under cyclic exposures combining UV light and condensing humidity is caused by photolytic and hydrolytic mechanisms causing yellowing and haze formation. Quantitative knowledge of these degradation pathways enable cross-correlation of these lab-based exposures with real-world conditions for service life prediction. PMID:28498875

SEE induced in SRAM operating in a superconducting electron linear accelerator environment

NASA Astrophysics Data System (ADS)

Makowski, D.; Mukherjee, Bhaskar; Grecki, M.; Simrock, Stefan

2005-02-01

Strong fields of bremsstrahlung photons and photoneutrons are produced during the operation of high-energy electron linacs. Therefore, a mixed gamma and neutron radiation field dominates the accelerators environment. The gamma radiation induced Total Ionizing Dose (TID) effect manifests the long-term deterioration of the electronic devices operating in accelerator environment. On the other hand, the neutron radiation is responsible for Single Event Effects (SEE) and may cause a temporal loss of functionality of electronic systems. This phenomenon is known as Single Event Upset (SEU). The neutron dose (KERMA) was used to scale the neutron induced SEU in the SRAM chips. Hence, in order to estimate the neutron KERMA conversion factor for Silicon (Si), dedicated calibration experiments using an Americium-Beryllium (241Am/Be) neutron standard source was carried out. Single Event Upset (SEU) influences the short-term operation of SRAM compared to the gamma induced TID effect. We are at present investigating the feasibility of an SRAM based real-time beam-loss monitor for high-energy accelerators utilizing the SEU caused by fast neutrons. This paper highlights the effects of gamma and neutron radiations on Static Random Access Memory (SRAM), placed at selected locations near the Superconducting Linear Accelerator driving the Vacuum UV Free Electron Laser (VUVFEL) of DESY.

Olfactory recognition memory is disrupted in young mice with chronic low-level lead exposure

PubMed Central

Flores-Montoya, Mayra Gisel; Alvarez, Juan Manuel; Sobin, Christina

2015-01-01

Chronic developmental lead exposure yielding very low blood lead burden is an unresolved child public health problem. Few studies have attempted to model neurobehavioral changes in young animals following very low level exposure, and studies are needed to identify tests that are sensitive to the neurobehavioral changes that may occur. Mechanisms of action are not yet known however results have suggested that hippocampus/dentate gyrus may be uniquely vulnerable to early chronic low-level lead exposure. This study examined the sensitivity of a novel odor recognition task to differences in pre-adolescent C57BL/6J mice chronically exposed from birth to PND 28, to 0 ppm (control), 30 ppm (low-dose), or 330 ppm (higher-dose) lead acetate (N = 33). Blood lead levels (BLLs) determined by ICP-MS ranged from 0.02 to 20.31 µg/dL. Generalized linear mixed model analyses with litter as a random effect showed a significant interaction of BLL × sex. As BLLs increased olfactory recognition memory decreased in males. Among females, non-linear effects were observed at lower but not higher levels of lead exposure. The novel odor detection task is sensitive to effects associated with early chronic low-level lead exposure in young C57BL/6J mice. PMID:25936521

Antibiotic rotation strategies to reduce antimicrobial resistance in Gram-negative bacteria in European intensive care units: study protocol for a cluster-randomized crossover controlled trial.

PubMed

van Duijn, Pleun J; Bonten, Marc J M

2014-07-10

Intensive care units (ICU) are epicenters for the emergence of antibiotic-resistant Gram-negative bacteria (ARGNB) because of high rates of antibiotic usage, rapid patient turnover, immunological susceptibility of acutely ill patients, and frequent contact between healthcare workers and patients, facilitating cross-transmission.Antibiotic stewardship programs are considered important to reduce antibiotic resistance, but the effectiveness of strategies such as, for instance, antibiotic rotation, have not been determined rigorously. Interpretation of available studies on antibiotic rotation is hampered by heterogeneity in implemented strategies and suboptimal study designs. In this cluster-randomized, crossover trial the effects of two antibiotic rotation strategies, antibiotic mixing and cycling, on the prevalence of ARGNB in ICUs are determined. Antibiotic mixing aims to create maximum antibiotic heterogeneity, and cycling aims to create maximum antibiotic homogeneity during consecutive periods. This is an open cluster-randomized crossover study of mixing and cycling of antibiotics in eight ICUs in five European countries. During cycling (9 months) third- or fourth-generation cephalosporins, piperacillin-tazobactam and carbapenems will be rotated during consecutive 6-week periods as the primary empiric treatment in patients suspected of infection caused by Gram-negative bacteria. During mixing (9 months), the same antibiotics will be rotated for each consecutive antibiotic course. Both intervention periods will be preceded by a baseline period of 4 months. ICUs will be randomized to consecutively implement either the mixing and then cycling strategy, or vice versa. The primary outcome is the ICU prevalence of ARGNB, determined through monthly point-prevalence screening of oropharynx and perineum. Secondary outcomes are rates of acquisition of ARGNB, bacteremia and appropriateness of therapy, length of stay in the ICU and ICU mortality. Results will be adjusted for intracluster correlation, and patient- and ICU-level variables of case-mix and infection-prevention measures using advanced regression modeling. This trial will determine the effects of antibiotic mixing and cycling on the unit-wide prevalence of ARGNB in ICUs. ClinicalTrials.gov NCT01293071 December 2010.

Random numbers from vacuum fluctuations

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

Shi, Yicheng; Kurtsiefer, Christian, E-mail: christian.kurtsiefer@gmail.com; Center for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore 117543

2016-07-25

We implement a quantum random number generator based on a balanced homodyne measurement of vacuum fluctuations of the electromagnetic field. The digitized signal is directly processed with a fast randomness extraction scheme based on a linear feedback shift register. The random bit stream is continuously read in a computer at a rate of about 480 Mbit/s and passes an extended test suite for random numbers.

Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI.

PubMed

Wang, S; Martinez-Lage, M; Sakai, Y; Chawla, S; Kim, S G; Alonso-Basanta, M; Lustig, R A; Brem, S; Mohan, S; Wolf, R L; Desai, A; Poptani, H

2016-01-01

Early assessment of treatment response is critical in patients with glioblastomas. A combination of DTI and DSC perfusion imaging parameters was evaluated to distinguish glioblastomas with true progression from mixed response and pseudoprogression. Forty-one patients with glioblastomas exhibiting enhancing lesions within 6 months after completion of chemoradiation therapy were retrospectively studied. All patients underwent surgery after MR imaging and were histologically classified as having true progression (>75% tumor), mixed response (25%-75% tumor), or pseudoprogression (<25% tumor). Mean diffusivity, fractional anisotropy, linear anisotropy coefficient, planar anisotropy coefficient, spheric anisotropy coefficient, and maximum relative cerebral blood volume values were measured from the enhancing tissue. A multivariate logistic regression analysis was used to determine the best model for classification of true progression from mixed response or pseudoprogression. Significantly elevated maximum relative cerebral blood volume, fractional anisotropy, linear anisotropy coefficient, and planar anisotropy coefficient and decreased spheric anisotropy coefficient were observed in true progression compared with pseudoprogression (P < .05). There were also significant differences in maximum relative cerebral blood volume, fractional anisotropy, planar anisotropy coefficient, and spheric anisotropy coefficient measurements between mixed response and true progression groups. The best model to distinguish true progression from non-true progression (pseudoprogression and mixed) consisted of fractional anisotropy, linear anisotropy coefficient, and maximum relative cerebral blood volume, resulting in an area under the curve of 0.905. This model also differentiated true progression from mixed response with an area under the curve of 0.901. A combination of fractional anisotropy and maximum relative cerebral blood volume differentiated pseudoprogression from nonpseudoprogression (true progression and mixed) with an area under the curve of 0.807. DTI and DSC perfusion imaging can improve accuracy in assessing treatment response and may aid in individualized treatment of patients with glioblastomas. © 2016 by American Journal of Neuroradiology.

Estimation of the Nonlinear Random Coefficient Model when Some Random Effects Are Separable

ERIC Educational Resources Information Center

du Toit, Stephen H. C.; Cudeck, Robert

2009-01-01

A method is presented for marginal maximum likelihood estimation of the nonlinear random coefficient model when the response function has some linear parameters. This is done by writing the marginal distribution of the repeated measures as a conditional distribution of the response given the nonlinear random effects. The resulting distribution…

Asymptotic Linear Spectral Statistics for Spiked Hermitian Random Matrices

NASA Astrophysics Data System (ADS)

Passemier, Damien; McKay, Matthew R.; Chen, Yang

2015-07-01

Using the Coulomb Fluid method, this paper derives central limit theorems (CLTs) for linear spectral statistics of three "spiked" Hermitian random matrix ensembles. These include Johnstone's spiked model (i.e., central Wishart with spiked correlation), non-central Wishart with rank-one non-centrality, and a related class of non-central matrices. For a generic linear statistic, we derive simple and explicit CLT expressions as the matrix dimensions grow large. For all three ensembles under consideration, we find that the primary effect of the spike is to introduce an correction term to the asymptotic mean of the linear spectral statistic, which we characterize with simple formulas. The utility of our proposed framework is demonstrated through application to three different linear statistics problems: the classical likelihood ratio test for a population covariance, the capacity analysis of multi-antenna wireless communication systems with a line-of-sight transmission path, and a classical multiple sample significance testing problem.

Wave kinetics of random fibre lasers

PubMed Central

Churkin, D V.; Kolokolov, I V.; Podivilov, E V.; Vatnik, I D.; Nikulin, M A.; Vergeles, S S.; Terekhov, I S.; Lebedev, V V.; Falkovich, G.; Babin, S A.; Turitsyn, S K.

2015-01-01

Traditional wave kinetics describes the slow evolution of systems with many degrees of freedom to equilibrium via numerous weak non-linear interactions and fails for very important class of dissipative (active) optical systems with cyclic gain and losses, such as lasers with non-linear intracavity dynamics. Here we introduce a conceptually new class of cyclic wave systems, characterized by non-uniform double-scale dynamics with strong periodic changes of the energy spectrum and slow evolution from cycle to cycle to a statistically steady state. Taking a practically important example—random fibre laser—we show that a model describing such a system is close to integrable non-linear Schrödinger equation and needs a new formalism of wave kinetics, developed here. We derive a non-linear kinetic theory of the laser spectrum, generalizing the seminal linear model of Schawlow and Townes. Experimental results agree with our theory. The work has implications for describing kinetics of cyclical systems beyond photonics. PMID:25645177

A green vehicle routing problem with customer satisfaction criteria

NASA Astrophysics Data System (ADS)

Afshar-Bakeshloo, M.; Mehrabi, A.; Safari, H.; Maleki, M.; Jolai, F.

2016-12-01

This paper develops an MILP model, named Satisfactory-Green Vehicle Routing Problem. It consists of routing a heterogeneous fleet of vehicles in order to serve a set of customers within predefined time windows. In this model in addition to the traditional objective of the VRP, both the pollution and customers' satisfaction have been taken into account. Meanwhile, the introduced model prepares an effective dashboard for decision-makers that determines appropriate routes, the best mixed fleet, speed and idle time of vehicles. Additionally, some new factors evaluate the greening of each decision based on three criteria. This model applies piecewise linear functions (PLFs) to linearize a nonlinear fuzzy interval for incorporating customers' satisfaction into other linear objectives. We have presented a mixed integer linear programming formulation for the S-GVRP. This model enriches managerial insights by providing trade-offs between customers' satisfaction, total costs and emission levels. Finally, we have provided a numerical study for showing the applicability of the model.

INCORPORATING CONCENTRATION DEPENDENCE IN STABLE ISOTOPE MIXING MODELS

EPA Science Inventory

Stable isotopes are frequently used to quantify the contributions of multiple sources to a mixture; e.g., C and N isotopic signatures can be used to determine the fraction of three food sources in a consumer's diet. The standard dual isotope, three source linear mixing model ass...

Superradiance Effects in the Linear and Nonlinear Optical Response of Quantum Dot Molecules

NASA Astrophysics Data System (ADS)

Sitek, A.; Machnikowski, P.

2008-11-01

We calculate the linear optical response from a single quantum dot molecule and the nonlinear, four-wave-mixing response from an inhomogeneously broadened ensemble of such molecules. We show that both optical signals are affected by the coupling-dependent superradiance effect and by optical interference between the two polarizations. As a result, the linear and nonlinear responses are not identical.

Decomposition of a Mixed-Valence [2Fe-2S] Cluster to Linear Tetra-Ferric and Ferrous Clusters

PubMed Central

Saouma, Caroline T.; Kaminsky, Werner; Mayer, James M.

2012-01-01

Despite the ease of preparing di-ferric [2Fe-2S] clusters, preparing stable mixed-valence analogues remains a challenge, as these clusters have limited thermal stability. Herein we identify two decomposition products of the mixed-valence thiosalicylate-ligated [2Fe-2S] cluster, [Fe2S2(SArCOO)2]3− ((SArCOO)2− = thiosalicylate). PMID:23976815

Influence of infusion pump operation and flow rate on hemodynamic stability during epinephrine infusion.

PubMed

Klem, S A; Farrington, J M; Leff, R D

1993-08-01

To determine whether variations in the flow rate of epinephrine solutions administered via commonly available infusion pumps lead to significant variations in blood pressure (BP) in vivo. Prospective, randomized, crossover study with factorial design, using infusion pumps with four different operating mechanisms (pulsatile diaphragm, linear piston/syringe, cyclic piston-valve, and linear peristaltic) and three drug delivery rates (1, 5, and 10 mL/hr). Two healthy, mixed-breed dogs (12 to 16 kg). Dogs were made hypotensive with methohexital bolus and continuous infusion. BP was restored to normal with constant-dose epinephrine infusion via two pumps at each rate. Femoral mean arterial pressure (MAP) was recorded every 10 secs. Pump-flow continuity was quantitated in vitro using a digital gravimetric technique. Variations in MAP and flow continuity were expressed by the coefficient of variation; analysis of variance was used for comparisons. The mean coefficients of variations for MAP varied from 3.8 +/- 3.1% (linear piston/syringe) to 6.1 +/- 6.6% (linear peristaltic), and from 3.4 +/- 2.2% (10 mL/hr) to 7.9 +/- 6.6% (1 mL/hr). The coefficients of variation for in vitro flow continuity ranged from 9 +/- 8% (linear piston-syringe) to 250 +/- 162% (pulsatile diaphragm), and from 35 +/- 44% (10 mL/hr) to 138 +/- 196% (1 mL/hr). Both the type of pump and infusion rate significantly (p < .001) influenced variation in drug delivery rate. The 1 mL/hr infusion rate significantly (p < .01) influenced MAP variation. Cyclic fluctuations in MAP of < or = 30 mm Hg were observed using the pulsatile diaphragm pump at 1 mL/hr. Factors inherent in the operating mechanisms of infusion pumps may result in clinically important hemodynamic fluctuations when administering a concentrated short-acting vasoactive medication at slow infusion rates.

Effect of Brief Mindfulness Practice on Self-Reported Affect, Craving, and Smoking: A Pilot Randomized Controlled Trial Using Ecological Momentary Assessment.

PubMed

Ruscio, Aimee C; Muench, Christine; Brede, Emily; Waters, Andrew J

2016-01-01

Despite efficacious pharmacological and behavioral treatments, most smokers attempt to quit without assistance and fail to quit. Mindfulness practice may be useful in smoking cessation. This ecological momentary assessment (EMA) study was a pilot parallel group randomized controlled trial of a brief mindfulness practice (Brief-MP) intervention on self-reported smoking behavior delivered to smokers on a Personal Digital Assistant (PDA) in the field. Adult community smokers (N = 44) were randomly assigned to a Brief-MP (n = 24) or Control (sham meditation; n = 20) group. Participants were instructed to smoke as much or as little as they liked. Participants carried a PDA for 2 weeks and were instructed to initiate 20 minutes of meditation (or control) training on the PDA daily, completing an assessment of cognitive and affective processes immediately afterwards. Additionally, they completed assessments at random times up to four times per day. Primary outcome variables were negative affect, craving, and cigarettes smoked per day, all self-reported. Thirty-seven participants provided EMA data totaling 1874 assessments. Linear Mixed Model analyses on EMA data revealed that Brief-MP (vs. Control) reduced overall negative affect, F(1, 1798) = 13.8, P = .0002; reduced craving immediately post-meditation, (Group × Assessment Type interaction, F(2, 1796) = 12.3, P = .0001); and reduced cigarettes smoked per day over time (Group × Day interaction, F(1, 436) = 5.50, P = .01). Brief-MP administered in the field reduced negative affect, craving, and cigarette use, suggesting it may be a useful treatment. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Effectiveness of an Intervention to Teach Physicians How to Assist Patients to Quit Smoking in Argentina

PubMed Central

Mejia, Raul; Kaplan, Celia P.; Gregorich, Steven E.; Livaudais-Toman, Jennifer; Peña, Lorena; Alderete, Mariela; Schoj, Veronica; Alderete, Ethel

2016-01-01

Abstract Introduction: We evaluated an intervention to teach physicians how to help their smoking patients quit compared to usual care in Argentina. Methods: Physicians were recruited from six clinical systems and randomized to intervention (didactic curriculum in two 3-hour sessions) or usual care. Smoking patients who saw participating physicians within 30 days of the intervention (index clinical visit) were randomly sampled and interviewed by telephone with follow-up surveys at months 6 and 12 after the index clinical visit. Outcomes were tobacco abstinence (main), quit attempt in the past month, use of medications to quit smoking, and cigarettes per day. Repeated measures on the same participants were accommodated via generalized linear mixed models. Results: Two hundred fifty-four physicians were randomized; average age 44.5 years, 53% women and 12% smoked. Of 1378 smoking patients surveyed, 81% were women and 45% had more than 12 years of education. At 1 month, most patients (77%) reported daily smoking, 20% smoked some days and 3% had quit. Mean cigarettes smoked per day was 12.9 ( SD = 8.8) and 49% were ready to quit within the year. Intention-to-treat analyses did not show significant group differences in quit rates at 12 months when assuming outcome response was missing at random (23% vs. 24.1%, P = .435). Using missing=smoking imputation rule, quit rates were not different at 12 months (15.6% vs. 16.4% P = .729). Motivated smokers were more likely to quit at 6 months (17.7% vs. 9.6%, P = .03). Conclusions: Training in tobacco cessation for physicians did not improve abstinence among their unselected smoking patients. PMID:26175459

Reducing Decisional Conflict and Enhancing Satisfaction with Information among Women Considering Breast Reconstruction following Mastectomy: Results from the BRECONDA Randomized Controlled Trial.

PubMed

Sherman, Kerry A; Shaw, Laura-Kate E; Winch, Caleb J; Harcourt, Diana; Boyages, John; Cameron, Linda D; Brown, Paul; Lam, Thomas; Elder, Elisabeth; French, James; Spillane, Andrew

2016-10-01

Deciding whether or not to have breast reconstruction following breast cancer diagnosis is a complex decision process. This randomized controlled trial assessed the impact of an online decision aid [Breast RECONstruction Decision Aid (BRECONDA)] on breast reconstruction decision-making. Women (n = 222) diagnosed with breast cancer or ductal carcinoma in situ, and eligible for reconstruction following mastectomy, completed an online baseline questionnaire. They were then assigned randomly to receive either standard online information about breast reconstruction (control) or standard information plus access to BRECONDA (intervention). Participants then completed questionnaires at 1 and 6 months after randomization. The primary outcome was participants' decisional conflict 1 month after exposure to the intervention. Secondary outcomes included decisional conflict at 6 months, satisfaction with information at 1 and 6 months, and 6-month decisional regret. Linear mixed-model analyses revealed that 1-month decisional conflict was significantly lower in the intervention group (27.18) compared with the control group (35.5). This difference was also sustained at the 6-month follow-up. Intervention participants reported greater satisfaction with information at 1- and 6-month follow-up, and there was a nonsignificant trend for lower decisional regret in the intervention group at 6-month follow-up. Intervention participants' ratings for BRECONDA demonstrated high user acceptability and overall satisfaction. Women who accessed BRECONDA benefited by experiencing significantly less decisional conflict and being more satisfied with information regarding the reconstruction decisional process than women receiving standard care alone. These findings support the efficacy of BRECONDA in helping women to arrive at their breast reconstruction decision.

Efficacy of the Ubiquitous Spaced Retrieval-based Memory Advancement and Rehabilitation Training (USMART) program among patients with mild cognitive impairment: a randomized controlled crossover trial.

PubMed

Han, Ji Won; Son, Kyung Lak; Byun, Hye Jin; Ko, Ji Won; Kim, Kayoung; Hong, Jong Woo; Kim, Tae Hyun; Kim, Ki Woong

2017-06-06

Spaced retrieval training (SRT) is a nonpharmacological intervention for mild cognitive impairment (MCI) and dementia that trains the learning and retention of target information by recalling it over increasingly long intervals. We recently developed the Ubiquitous Spaced Retrieval-based Memory Advancement and Rehabilitation Training (USMART) program as a convenient, self-administered tablet-based SRT program. We also demonstrated the utility of USMART for improving memory in individuals with MCI through an open-label uncontrolled trial. This study had an open-label, single-blind, randomized, controlled, two-period crossover design. Fifty patients with MCI were randomized into USMART-usual care and usual care-USMART treatment sequences. USMART was completed or usual care was provided biweekly over a 4-week treatment period with a 2-week washout period between treatment periods. Primary outcome measures included the Word List Memory Test, Word List Recall Test (WLRT), and Word List Recognition Test. Outcomes were measured at baseline, week 5, and week 11 by raters who were blinded to intervention type. An intention-to-treat analysis and linear mixed modeling were used. Of 50 randomized participants, 41 completed the study (18% dropout rate). The USMART group had larger improvements in WLRT score (effect size = 0.49, p = 0.031) than the usual care group. There were no significant differences in other primary or secondary measures between the USMART and usual care groups. Moreover, no USMART-related adverse events were reported. The 4-week USMART modestly improved information retrieval in older people with MCI, and was well accepted with minimal technical support. ClinicalTrials.gov NCT01688128 . Registered 12 September 2012.

Guided training relative to direct skill training for individuals with cognitive impairments after stroke: a pilot randomized trial

PubMed Central

Skidmore, Elizabeth R.; Butters, Meryl; Whyte, Ellen; Grattan, Emily; Shen, Jennifer; Terhorst, Lauren

2016-01-01

Objective To examine the effects of direct skill training and guided training for promoting independence after stroke. Design Single-blind randomized pilot study. Setting Inpatient rehabilitation facility. Participants Forty-three participants in inpatient rehabilitation with acute stroke and cognitive impairments. Interventions Participants were randomized to receive direct skill training (n=22, 10 sessions as adjunct to usual inpatient rehabilitation) or guided training (n=21, same dose). Main Outcome Measure The Functional Independence Measure assessed independence at baseline, rehabilitation discharge, and months 3, 6, and 12. Results Linear mixed models (random intercept, other effects fixed) revealed a significant intervention by time interaction (F4,150=5.11, p<0.001), a significant main effect of time (F4,150=49.25, p<0.001), and a significant effect of stroke severity (F1,150=34.46, p<.001). There was no main effect of intervention (F1,150=0.07, p=0.79). Change in Functional Independence Measures scores was greater for the DIRECT group at rehabilitation discharge (effect size of between group differences, d=0.28) and greater for the GUIDE group at months 3 (d=0.16), 6 (d=0.39), and 12 (d=0.53). The difference between groups in mean 12 month change scores was 10.57 points. Conclusions Guided training, provided in addition to usual care, offered a small advantage in the recovery of independence, relative to direct skill training. Future studies examining guided training in combination with other potentially potent intervention elements may further advise best practices in rehabilitation for individuals with cognitive impairments after acute stroke. PMID:27794487

A behavioral intervention for war-affected youth in Sierra Leone: a randomized controlled trial.

PubMed

Betancourt, Theresa S; McBain, Ryan; Newnham, Elizabeth A; Akinsulure-Smith, Adeyinka M; Brennan, Robert T; Weisz, John R; Hansen, Nathan B

2014-12-01

Youth in war-affected regions are at risk for poor psychological, social, and educational outcomes. Effective interventions are needed to improve mental health, social behavior, and school functioning. This randomized controlled trial tested the effectiveness of a 10-session cognitive-behavioral therapy (CBT)-based group mental health intervention for multisymptomatic war-affected youth (aged 15-24 years) in Sierra Leone. War-affected youth identified by elevated distress and impairment via community screening were randomized (stratified by sex and age) to the Youth Readiness Intervention (YRI) (n = 222) or to a control condition (n = 214). After treatment, youth were again randomized and offered an education subsidy immediately (n = 220) or waitlisted (n = 216). Emotion regulation, psychological distress, prosocial attitudes/behaviors, social support, functional impairment, and posttraumatic stress disorder (PTSD) symptoms were assessed at pre- and postintervention and at 6-month follow-up. For youth in school, enrollment, attendance, and classroom performance were assessed after 8 months. Linear mixed-effects regressions evaluated outcomes. The YRI showed significant postintervention effects on emotion regulation, prosocial attitudes/behaviors, social support, and reduced functional impairment, and significant follow-up effects on school enrollment, school attendance, and classroom behavior. In contrast, education subsidy was associated with better attendance but had no effect on mental health or functioning, school retention, or classroom behavior. Interactions between education subsidy and YRI were not significant. YRI produced acute improvements in mental health and functioning as well as longer-term effects on school engagement and behavior, suggesting potential to prepare war-affected youth for educational and other opportunities. Clinical trial registration information-Trial of the Youth Readiness Intervention (YRI); http://clinicaltrials.gov; NCT01684488. Copyright © 2014 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Implementation of Treat-to-Target in Rheumatoid Arthritis Through a Learning Collaborative: Results of a Randomized Controlled Trial.

PubMed

Solomon, Daniel H; Losina, Elena; Lu, Bing; Zak, Agnes; Corrigan, Cassandra; Lee, Sara B; Agosti, Jenifer; Bitton, Asaf; Harrold, Leslie R; Pincus, Theodore; Radner, Helga; Yu, Zhi; Smolen, Josef S; Fraenkel, Liana; Katz, Jeffrey N

2017-07-01

Treat-to-target (TTT) is an accepted paradigm for the management of rheumatoid arthritis (RA), but some evidence suggests poor adherence. The purpose of this study was to test the effects of a group-based multisite improvement learning collaborative on adherence to TTT. We conducted a cluster-randomized quality-improvement trial with waitlist control across 11 rheumatology sites in the US. The intervention entailed a 9-month group-based learning collaborative that incorporated rapid-cycle improvement methods. A composite TTT implementation score was calculated as the percentage of 4 required items documented in the visit notes for each patient at 2 time points, as evaluated by trained staff. The mean change in the implementation score for TTT across all patients for the intervention sites was compared with that for the control sites after accounting for intracluster correlation using linear mixed models. Five sites with a total of 23 participating rheumatology providers were randomized to intervention and 6 sites with 23 participating rheumatology providers were randomized to the waitlist control. The intervention included 320 patients, and the control included 321 patients. At baseline, the mean TTT implementation score was 11% in both arms; after the 9-month intervention, the mean TTT implementation score was 57% in the intervention group and 25% in the control group (change in score of 46% for intervention and 14% for control; P = 0.004). We did not observe excessive use of resources or excessive occurrence of adverse events in the intervention arm. A learning collaborative resulted in substantial improvements in adherence to TTT for the management of RA. This study supports the use of an educational collaborative to improve quality. © 2017, American College of Rheumatology.

Therapeutic Exercise Training to Reduce Chronic Headache in Working Women: Design of a Randomized Controlled Trial.

PubMed

Rinne, Marjo; Garam, Sanna; Häkkinen, Arja; Ylinen, Jari; Kukkonen-Harjula, Katriina; Nikander, Riku

2016-05-01

Cervicogenic headache and migraine are common causes of visits to physicians and physical therapists. Few randomized trials utilizing active physical therapy and progressive therapeutic exercise have been previously published. The existing evidence on active treatment methods supports a moderate effect on cervicogenic headache. The aim of this study is to investigate whether a progressive, group-based therapeutic exercise program decreases the intensity and frequency of chronic headache among women compared with a control group receiving a sham dose of transcutaneous electrical nerve stimulation (TENS) and stretching exercises. A randomized controlled trial with 6-month intervention and follow-up was developed. The participants were randomly assigned to either a treatment group or a control group. The study is being conducted at 2 study centers. The participants are women aged 18 to 60 years with chronic cervicogenic headache or migraine. The treatment group's exercise program consisted of 6 progressive therapeutic exercise modules, including proprioceptive low-load progressive craniocervical and cervical exercises and high-load exercises for the neck muscles. The participants in the control group received 6 individually performed sham TENS treatment sessions. The primary outcome is the intensity of headache. The secondary outcomes are changes in frequency and duration of headache, neck muscle strength, neck and shoulder flexibility, impact of headache on daily life, neck disability, fear-avoidance beliefs, work ability, and quality of life. Between-group differences will be analyzed separately at 6, 12, and 24 months with generalized linear mixed models. In the case of count data (eg, frequency of headache), Poisson or negative binomial regression will be used. The therapists are not blinded. The effects of specific therapeutic exercises on frequency, intensity, and duration of chronic headache and migraine will be reported. © 2016 American Physical Therapy Association.

Influence of Gestational Age at Initiation of Antihypertensive Therapy: Secondary Analysis of CHIPS Trial Data (Control of Hypertension in Pregnancy Study).

PubMed

Pels, Anouk; Mol, Ben Willem J; Singer, Joel; Lee, Terry; von Dadelszen, Peter; Ganzevoort, Wessel; Asztalos, Elizabeth; Magee, Laura A

2018-06-01

For hypertensive women in CHIPS (Control of Hypertension in Pregnancy Study), we assessed whether the maternal benefits of tight control could be achieved, while minimizing any potentially negative effect on fetal growth, by delaying initiation of antihypertensive therapy until later in pregnancy. For the 981 women with nonsevere, chronic or gestational hypertension randomized to less-tight (target diastolic blood pressure, 100 mm Hg), or tight (target, 85 mm Hg) control, we used mixed-effects logistic regression to examine whether the effect of less-tight (versus tight) control on major outcomes was dependent on gestational age at randomization, adjusting for baseline factors as in the primary analysis and including an interaction term between gestational age at randomization and treatment allocation. Gestational age was considered categorically (quartiles) and continuously (linear or quadratic form), and the optimal functional form selected to provide the best fit to the data based on the Akaike information criterion. Randomization before (but not after) 24 weeks to less-tight (versus tight) control was associated with fewer babies with birth weight <10th centile ( P interaction =0.005), but more preterm birth ( P interaction =0.043), and no effect on perinatal death or high-level neonatal care >48 hours ( P interaction =0.354). For the mother, less-tight (versus tight) control was associated with more severe hypertension at all gestational ages but particularly so before 28 weeks ( P interaction =0.076). In women with nonsevere, chronic, or gestational hypertension, there seems to be no gestational age at which less-tight (versus tight) control is the preferred management strategy to optimize maternal or perinatal outcomes. URL: https://www.isrctn.com. Unique identifier: ISRCTN71416914. © 2018 The Authors.

Promoting healthful family meals to prevent obesity: HOME Plus, a randomized controlled trial.

PubMed

Fulkerson, Jayne A; Friend, Sarah; Flattum, Colleen; Horning, Melissa; Draxten, Michelle; Neumark-Sztainer, Dianne; Gurvich, Olga; Story, Mary; Garwick, Ann; Kubik, Martha Y

2015-12-15

Family meal frequency has been shown to be strongly associated with better dietary intake; however, associations with weight status have been mixed. Family meals-focused randomized controlled trials with weight outcomes have not been previously conducted. Therefore, this study purpose was to describe weight-related outcomes of the HOME Plus study, the first family meals-focused randomized controlled trial to prevent excess weight gain among youth. Families (n = 160 8-12-year-old children and their parents/guardians) were randomized to intervention (n = 81) or control (n = 79) groups. Data were collected at baseline (2011-2012), post-intervention (12-months post-baseline) and follow-up (21-months post-baseline). The intervention included ten monthly group sessions (nutrition education; hands-on meal and snack planning, preparation, and skill development; screen time reductions) and five motivational, goal-setting phone calls. The main outcome was child body mass index (BMI) z-score. General linear models, adjusted for baseline values and demographics, showed no significant treatment group differences in BMI z-scores at post-intervention or follow-up; however, a promising reduction in excess weight gain was observed. Post-hoc stratification by pubertal onset indicated prepubescent children in the intervention group had significantly lower BMI z-scores than their control group counterparts. The study used a strong theoretical framework, rigorous design, quality measurement and a program with high fidelity to test a family meals-focused obesity prevention intervention. It showed a modest decrease in excess weight gain. The significant intervention effect among prepubescent children suggests the intervention may be more efficacious among relatively young children, although more research with appropriately powered samples are needed to replicate this finding. This study is registered at www.clinicaltrials.gov NCT01538615. Registered 01/17/2012.

Effectiveness of an Energy Management Training Course on Employee Well-Being: A Randomized Controlled Trial.

PubMed

Das, Sai Krupa; Mason, Shawn T; Vail, Taylor A; Rogers, Gail V; Livingston, Kara A; Whelan, Jillian G; Chin, Meghan K; Blanchard, Caroline M; Turgiss, Jennifer L; Roberts, Susan B

2018-01-01

Programs focused on employee well-being have gained momentum in recent years, but few have been rigorously evaluated. This study evaluates the effectiveness of an intervention designed to enhance vitality and purpose in life by assessing changes in employee quality of life (QoL) and health-related behaviors. A worksite-based randomized controlled trial. Twelve eligible worksites (8 randomized to the intervention group [IG] and 4 to the wait-listed control group [CG]). Employees (n = 240) at the randomized worksites. A 2.5-day group-based behavioral intervention. Rand Medical Outcomes Survey (MOS) 36-item Short-Form (SF-36) vitality and QoL measures, Ryff Purpose in Life Scale, Center for Epidemiologic Studies questionnaire for depression, MOS sleep, body weight, physical activity, diet quality, and blood measures for glucose and lipids (which were used to calculate a cardiometabolic risk score) obtained at baseline and 6 months. General linear mixed models were used to compare least squares means or prevalence differences in outcomes between IG and CG participants. As compared to CG, IG had a significantly higher mean 6-month change on the SF-36 vitality scale ( P = .003) and scored in the highest categories for 5 of the remaining 7 SF-36 domains: general health ( P = .014), mental health ( P = .027), absence of role limitations due to physical problems ( P = .026), and social functioning ( P = .007). The IG also had greater improvements in purpose in life ( P < .001) and sleep quality (index I, P = .024; index II, P = .021). No statistically significant changes were observed for weight, diet, physical activity, or cardiometabolic risk factors. An intensive 2.5-day intervention showed improvement in employee QoL and well-being over 6 months.

Sun protection at elementary schools: a cluster randomized trial.

PubMed

Hunter, Seft; Love-Jackson, Kymia; Abdulla, Rania; Zhu, Weiwei; Lee, Ji-Hyun; Wells, Kristen J; Roetzheim, Richard

2010-04-07

Elementary schools represent both a source of childhood sun exposure and a setting for educational interventions. Sun Protection of Florida's Children was a cluster randomized trial promoting hat use at (primary outcome) and outside of schools among fourth-grade students during August 8, 2006, through May 22, 2007. Twenty-two schools were randomly assigned to the intervention (1115 students) or control group (1376 students). Intervention schools received classroom sessions targeting sun protection attitudes and social norms. Each student attending an intervention school received two free wide-brimmed hats. Hat use at school was measured by direct observation and hat use outside of school was measured by self-report. A subgroup of 378 students (178 in the intervention group and 200 in the control group) underwent serial measurements of skin pigmentation to explore potential physiological effects of the intervention. Generalized linear mixed models were used to evaluate the intervention effect by accounting for the cluster randomized trial design. All P values were two-sided and were claimed as statistically significant at a level of .05. The percentage of students observed wearing hats at control schools remained essentially unchanged during the school year (baseline = 2%, fall = 0%, and spring = 1%) but increased statistically significantly at intervention schools (baseline = 2%, fall = 30%, and spring = 41%) (P < .001 for intervention effect comparing the change in rate of hat use over time at intervention vs control schools). Self-reported use of hats outside of school did not change statistically significantly during the study (control: baseline = 14%, fall = 14%, and spring = 11%; intervention: baseline = 24%, fall = 24%, and spring = 23%) nor did measures of skin pigmentation. The intervention increased use of hats among fourth-grade students at school but had no effect on self-reported wide-brimmed hat use outside of school or on measures of skin pigmentation.

Self-help cognitive behavior therapy for working women with problematic hot flushes and night sweats (MENOS@Work): a multicenter randomized controlled trial.

PubMed

Hardy, Claire; Griffiths, Amanda; Norton, Sam; Hunter, Myra S

2018-05-01

The aim of the study was to examine the efficacy of an unguided, self-help cognitive behavior therapy (SH-CBT) booklet on hot flush and night sweat (HFNS) problem rating, delivered in a work setting. Women aged 45 to 60 years, having 10 or more problematic HFNS a week, were recruited to a multicenter randomized controlled trial, via the occupational health/human resources departments of eight organizations. Participants were 1:1 randomized to SH-CBT or no treatment waitlist control (NTWC). The primary outcome was HFNS problem rating; secondary outcomes included HFNS frequency, work and social adjustment, sleep, mood, beliefs and behaviors, and work-related variables (absence, performance, turnover intention, and work impairment due to presenteeism). Intention-to-treat analysis was used, and between-group differences estimated using linear mixed models. A total of 124 women were randomly allocated to SH-CBT (n = 60) and NTWC (n = 64). 104 (84%) were assessed for primary outcome at 6 weeks and 102 (82%) at 20 weeks. SH-CBT significantly reduced HFNS problem rating at 6 weeks (SH-CBT vs NTWC adjusted mean difference, -1.49; 95% CI, -2.11 to -0.86; P < 0.001) and at 20 weeks (-1.09; 95% CI, -1.87 to -0.31; P < 0.01). SH-CBT also significantly reduced HFNS frequency, improved work and social adjustment; sleep, menopause beliefs, HFNS beliefs/behaviors at 6 and 20 weeks; improved wellbeing and somatic symptoms and reduced work impairment due to menopause-related presenteeism at 20 weeks, compared with the NTWC. There was no difference between groups in other work-related outcomes. A brief, unguided SH-CBT booklet is a potentially effective management option for working women experiencing problematic HFNS.

A Behavioral Intervention for War-Affected Youth in Sierra Leone: A Randomized Controlled Trial

PubMed Central

Betancourt, Theresa S.; McBain, Ryan; Newnham, Elizabeth A.; Akinsulure-Smith, Adeyinka M.; Brennan, Robert T.; Weisz, John R.; Hansen, Nathan B.

2016-01-01

Objective Youth in war-affected regions are at risk for poor psychological, social, and educational outcomes. Effective interventions are needed to improve mental health, social behavior, and school functioning. This randomized controlled trial tested the effectiveness of a 10-session cognitive-behavioral therapy (CBT)–based group mental health intervention for multisymptomatic war-affected youth (aged 15–24 years) in Sierra Leone. Method War-affected youth identified by elevated distress and impairment via community screening were randomized (stratified by sex and age) to the Youth Readiness Intervention (YRI) (n = 222) or to a control condition (n = 214). After treatment, youth were again randomized and offered an education subsidy immediately (n = 220) or waitlisted (n = 216). Emotion regulation, psychological distress, prosocial attitudes/behaviors, social support, functional impairment, and posttraumatic stress disorder (PTSD) symptoms were assessed at pre- and postintervention and at 6-month follow-up. For youth in school, enrollment, attendance, and classroom performance were assessed after 8 months. Linear mixed-effects regressions evaluated outcomes. Results The YRI showed significant postintervention effects on emotion regulation, prosocial attitudes/behaviors, social support, and reduced functional impairment, and significant follow-up effects on school enrollment, school attendance, and classroom behavior. In contrast, education subsidy was associated with better attendance but had no effect on mental health or functioning, school retention, or classroom behavior. Interactions between education subsidy and YRI were not significant. Conclusion YRI produced acute improvements in mental health and functioning as well as longer-term effects on school engagement and behavior, suggesting potential to prepare war-affected youth for educational and other opportunities. Clinical trial registration information-Trial of the Youth Readiness Intervention (YRI); http://clinicaltrials.gov; NCT01684488. PMID:25457927

Fluoxetine for Maintenance of Remission and to Improve Quality of Life in Patients with Crohn's Disease: a Pilot Randomized Placebo-Controlled Trial.

PubMed

Mikocka-Walus, Antonina; Hughes, Patrick A; Bampton, Peter; Gordon, Andrea; Campaniello, Melissa A; Mavrangelos, Chris; Stewart, Benjamin J; Esterman, Adrian; Andrews, Jane M

2017-04-01

Previous studies have shown that antidepressants reduce inflammation in animal models of colitis. The present trial aimed to examine whether fluoxetine added to standard therapy for Crohn's disease [CD] maintained remission, improved quality of life [QoL] and/or mental health in people with CD as compared to placebo. A parallel randomized double-blind placebo controlled trial was conducted. Participants with clinically established CD, with quiescent or only mild disease, were randomly assigned to receive either fluoxetine 20 mg daily or placebo, and followed for 12 months. Participants provided blood and stool samples and completed mental health and QoL questionnaires. Immune functions were assessed by stimulated cytokine secretion [CD3/CD28 stimulation] and flow cytometry for cell type. Linear mixed-effects models were used to compare groups. Of the 26 participants, 14 were randomized to receive fluoxetine and 12 to placebo. Overall, 14 [54%] participants were male. The mean age was 37.4 [SD=13.2] years. Fluoxetine had no effect on inflammatory bowel disease activity measured using either the Crohn's Disease Activity Index [F(3, 27.5)=0.064, p=0.978] or faecal calprotectin [F(3, 32.5)=1.08, p=0.371], but did have modest effects on immune function. There was no effect of fluoxetine on physical, psychological, social or environmental QoL, anxiety or depressive symptoms as compared to placebo [all p>0.05]. In this small pilot clinical trial, fluoxetine was not superior to placebo in maintaining remission or improving QoL. [ID: ACTRN12612001067864.]. © European Crohn’s and Colitis Organistion (ECCO) 2016.

Heat kernel for the elliptic system of linear elasticity with boundary conditions

NASA Astrophysics Data System (ADS)

Taylor, Justin; Kim, Seick; Brown, Russell

2014-10-01

We consider the elliptic system of linear elasticity with bounded measurable coefficients in a domain where the second Korn inequality holds. We construct heat kernel of the system subject to Dirichlet, Neumann, or mixed boundary condition under the assumption that weak solutions of the elliptic system are Hölder continuous in the interior. Moreover, we show that if weak solutions of the mixed problem are Hölder continuous up to the boundary, then the corresponding heat kernel has a Gaussian bound. In particular, if the domain is a two dimensional Lipschitz domain satisfying a corkscrew or non-tangential accessibility condition on the set where we specify Dirichlet boundary condition, then we show that the heat kernel has a Gaussian bound. As an application, we construct Green's function for elliptic mixed problem in such a domain.

A spectral analysis of the domain decomposed Monte Carlo method for linear systems

DOE PAGES

Slattery, Stuart R.; Evans, Thomas M.; Wilson, Paul P. H.

2015-09-08

The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear oper- ator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approxi- mation and the mean chord approximation are applied to estimate the leakagemore » frac- tion of random walks from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem in numerical experiments to test the models for symmetric operators with spectral qualities similar to light water reactor problems. We find, in general, the derived approximations show good agreement with random walk lengths and leakage fractions computed by the numerical experiments.« less

General Framework for Effect Sizes in Cluster Randomized Experiments

ERIC Educational Resources Information Center

VanHoudnos, Nathan

2016-01-01

Cluster randomized experiments are ubiquitous in modern education research. Although a variety of modeling approaches are used to analyze these data, perhaps the most common methodology is a normal mixed effects model where some effects, such as the treatment effect, are regarded as fixed, and others, such as the effect of group random assignment…

A Randomized Trial of Telephone Psychotherapy and Pharmacotherapy for Depression: Continuation and Durability of Effects

ERIC Educational Resources Information Center

Ludman, Evette J.; Simon, Gregory E.; Tutty, Steve; Von Korff, Michael

2007-01-01

Randomized trial evidence and expert guidelines are mixed regarding the value of combined pharmacotherapy and psychotherapy as initial treatment for depression. This study describes long-term results of a randomized trial (N = 393) evaluating telephone-based cognitive-behavioral therapy (CBT) plus care management for primary care patients…

After-School Multifamily Groups: A Randomized Controlled Trial Involving Low-Income, Urban, Latino Children

ERIC Educational Resources Information Center

McDonald, Lynn; Moberg, D. Paul; Brown, Roger; Rodriguez-Espiricueta, Ismael; Flores, Nydia I.; Burke, Melissa P.; Coover, Gail

2006-01-01

This randomized controlled trial evaluated a culturally representative parent engagement strategy with Latino parents of elementary school children. Ten urban schools serving low-income children from mixed cultural backgrounds participated in a large study. Classrooms were randomly assigned either either to an after-school, multifamily support…

Effect of rumen-undegradable protein supplementation and fresh forage composition on nitrogen utilization of dairy ewes.

PubMed

Mikolayunas, C; Thomas, D L; Armentano, L E; Berger, Y M

2011-01-01

Previous trials with dairy ewes fed stored feeds indicate a positive effect of rumen-undegradable protein (RUP) supplementation on milk yield. However, dairy sheep production in the United States is primarily based on grazing mixed grass-legume pastures, which contain a high proportion of rumen-degradable protein. Two trials were conducted to evaluate the effects of high-RUP protein supplementation and fresh forage composition on milk yield and N utilization of lactating dairy ewes fed in confinement or on pasture. In a cut-and-carry trial, 16 multiparous dairy ewes in mid-lactation were randomly assigned to 8 pens of 2 ewes each. Pens were randomly assigned 1 of 2 protein supplementation treatments, receiving either 0.0 or 0.3 kg of a high-RUP protein supplement (Soy Pass, LignoTech USA Inc., Rothschild, WI) per day. Within supplementation treatment, pens were randomly assigned to 1 of 4 forage treatments, which were applied in a 4×4 Latin square design for 10-d periods. Forage treatments included the following percentages of orchardgrass:alfalfa dry matter: 25:75, 50:50, 75:25, and 100:0. No interactions were observed between supplement and forage treatments. Supplementation with a high-RUP source tended to increase milk yield by 9%. Milk yield, milk protein yield, milk urea N, and urinary urea N excretion increased linearly with increased percentage of alfalfa. Milk N efficiency was greatest on the 100% orchardgrass diet. In a grazing trial, 12 multiparous dairy ewes in mid lactation were randomly assigned to 3 groups of 4 ewes each. Within group, 2 ewes were randomly assigned to receive either 0.0 or 0.3 kg of a high-RUP protein supplement (SoyPlus, West Central Cooperative, Ralston, IA) per day. Grazing treatments were arranged in a 3×3 Latin square design and applied to groups for 10-d periods. Ewes grazed paddocks that contained the following percentages of surface area of pure stands of orchardgrass:alfalfa: 50:50, 75:25, and 100:0. No interactions were found between supplement and forage treatments. Milk yield, milk protein yield, and milk urea N increased linearly with increased percentage of alfalfa in the paddock. In conclusion, supplementing with high-RUP protein tended to increase milk yield and increasing the proportion of alfalfa in the diet increased dry matter intake, milk yield, and protein yield of lactating dairy ewes fed or grazing fresh forage. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Random regression analyses using B-splines to model growth of Australian Angus cattle

PubMed Central

Meyer, Karin

2005-01-01

Regression on the basis function of B-splines has been advocated as an alternative to orthogonal polynomials in random regression analyses. Basic theory of splines in mixed model analyses is reviewed, and estimates from analyses of weights of Australian Angus cattle from birth to 820 days of age are presented. Data comprised 84 533 records on 20 731 animals in 43 herds, with a high proportion of animals with 4 or more weights recorded. Changes in weights with age were modelled through B-splines of age at recording. A total of thirteen analyses, considering different combinations of linear, quadratic and cubic B-splines and up to six knots, were carried out. Results showed good agreement for all ages with many records, but fluctuated where data were sparse. On the whole, analyses using B-splines appeared more robust against "end-of-range" problems and yielded more consistent and accurate estimates of the first eigenfunctions than previous, polynomial analyses. A model fitting quadratic B-splines, with knots at 0, 200, 400, 600 and 821 days and a total of 91 covariance components, appeared to be a good compromise between detailedness of the model, number of parameters to be estimated, plausibility of results, and fit, measured as residual mean square error. PMID:16093011

Soy Food Intake and Biomarkers of Breast Cancer Risk: Possible Difference in Asian Women?

PubMed Central

Maskarinec, Gertraud; Ju, Dan; Morimoto, Yukiko; Franke, Adrian A.; Stanczyk, Frank Z.

2017-01-01

Soy foods may protect against breast cancer in Asian but not in Western populations. We examined if the levels of various markers of breast cancer risk and inflammation, as well as the effects of soy food consumption on these markers, differ between Asian and non-Asian premenopausal women in two soy intervention trials. One study randomized 220 women to a 2-year intervention and the other one randomized 96 women in a cross-over design to examine the effects of consumption of 2 daily soy servings on nipple aspirate fluid (NAF) volume, estrogens in serum, NAF, and urine, insulin-like growth factor-1 (IGF-1), IGF binding protein 3, and inflammatory markers in serum, and mammographic densities. Mixed linear models were applied to assess ethnic differences in biomarkers and response to the soy diet. Serum C-reactive protein, serum leptin, NAF volume, and NAF estrone-sulfate were lower, while urinary isoflavones were higher in Asian than in non-Asian women. A significant interaction (pinteraction=0.05) between ethnicity and soy diet was observed for IGF-1 but not for other biomarkers. The current findings suggest possible ethnic differences in levels of biomarkers for breast cancer risk but little evidence that Asian women respond differently to soy foods than non-Asian women. PMID:27918846

Cognitive-behavioral therapy for anxiety disordered youth: a randomized clinical trial evaluating child and family modalities.

PubMed

Kendall, Philip C; Hudson, Jennifer L; Gosch, Elizabeth; Flannery-Schroeder, Ellen; Suveg, Cynthia

2008-04-01

This randomized clinical trial compared the relative efficacy of individual (child) cognitive-behavioral therapy (ICBT), family cognitive-behavioral therapy (FCBT), and a family-based education/support/ attention (FESA) active control for treating anxiety disordered youth ages 7-14 years (M = 10.27). Youth (N = 161; 44% female; 85% Caucasian, 9% African American, 3% Hispanic, 3% other/mixed) with a principal diagnosis of separation anxiety disorder, social phobia, or generalized anxiety disorder and their parents participated. Outcome analyses were conducted using hierarchical linear models on the intent-to-treat sample at posttreatment and 1-year follow-up using diagnostic severity, child self-reports, parent reports, and teacher reports. Chi-square analyses were also conducted on diagnostic status at post and 1-year follow-up. Children evidenced treatment gains in all conditions, although FCBT and ICBT were superior to FESA in reducing the presence and principality of the principal anxiety disorder, and ICBT outperformed FCBT and FESA on teacher reports of child anxiety. Treatment gains, when found, were maintained at 1-year follow-up. FCBT outperformed ICBT when both parents had an anxiety disorder. Implications for treatment and suggestions for research are discussed. PsycINFO Database Record (c) 2008 APA, all rights reserved.

Stochastic resonance training reduces musculoskeletal symptoms in metal manufacturing workers: a controlled preventive intervention study.

PubMed

Burger, Christian; Schade, Volker; Lindner, Christina; Radlinger, Lorenz; Elfering, Achim

2012-01-01

This study examined the effects of stochastic resonance whole-body vibration training on work-related musculoskeletal symptoms and accidents. Participants were white and blue-collar employees of a Swiss metal manufacturer (N=38), and participation was voluntary. The study was designed as a switching-replications longitudinal trial with randomized group allocation. The randomized controlled cross-over design consisted of two groups each given four weeks of exercise and no intervention during a second four-week period. Outcome was measured on a daily basis with questionnaires. Three components constituted musculoskeletal symptoms: musculoskeletal pain, related function limitations and musculoskeletal well-being. Accidents were assessed by ratings for balance and daily near-accidents. For statistical analysis, a mixed model was calculated. At the end of the training period musculoskeletal pain and related function limitation were significantly reduced, whereas musculoskeletal well-being had significantly increased. For function limitation and musculoskeletal well-being, change over time was linear. There was no effect on balance or near-accidents. Stochastic resonance whole-body vibration was found to be effective in the prevention of work-related musculoskeletal symptoms. It is well suited for the use in a work environment since it requires very little effort in terms of infrastructure, time and investment from participants.

Sample size determinations for group-based randomized clinical trials with different levels of data hierarchy between experimental and control arms.

PubMed

Heo, Moonseong; Litwin, Alain H; Blackstock, Oni; Kim, Namhee; Arnsten, Julia H

2017-02-01

We derived sample size formulae for detecting main effects in group-based randomized clinical trials with different levels of data hierarchy between experimental and control arms. Such designs are necessary when experimental interventions need to be administered to groups of subjects whereas control conditions need to be administered to individual subjects. This type of trial, often referred to as a partially nested or partially clustered design, has been implemented for management of chronic diseases such as diabetes and is beginning to emerge more commonly in wider clinical settings. Depending on the research setting, the level of hierarchy of data structure for the experimental arm can be three or two, whereas that for the control arm is two or one. Such different levels of data hierarchy assume correlation structures of outcomes that are different between arms, regardless of whether research settings require two or three level data structure for the experimental arm. Therefore, the different correlations should be taken into account for statistical modeling and for sample size determinations. To this end, we considered mixed-effects linear models with different correlation structures between experimental and control arms to theoretically derive and empirically validate the sample size formulae with simulation studies.

Soy Food Intake and Biomarkers of Breast Cancer Risk: Possible Difference in Asian Women?

PubMed

Maskarinec, Gertraud; Ju, Dan; Morimoto, Yukiko; Franke, Adrian A; Stanczyk, Frank Z

2017-01-01

Soy foods may protect against breast cancer in Asian but not in Western populations. We examined if the levels of various markers of breast cancer risk and inflammation, as well as the effects of soy food consumption on these markers, differ between Asian and non-Asian premenopausal women in two soy intervention trials. One study randomized 220 women to a 2-yr intervention and the other one randomized 96 women in a crossover design to examine the effects of consumption of 2 daily soy servings on nipple aspirate fluid (NAF) volume; estrogens in serum, NAF, and urine; insulin-like growth factor-1 (IGF-1), IGF-binding protein 3, and inflammatory markers in serum; and mammographic densities. Mixed linear models were applied to assess ethnic differences in biomarkers and response to the soy diet. Serum C-reactive protein, serum leptin, NAF volume, and NAF estrone sulfate were lower, while urinary isoflavones were higher in Asian than in non-Asian women. A significant interaction (p interaction = 0.05) between ethnicity and soy diet was observed for IGF-1 but not for other biomarkers. The current findings suggest possible ethnic differences in levels of biomarkers for breast cancer risk but little evidence that Asian women respond differently to soy foods than non-Asian women.