[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.

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...

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.

Extended Mixed-Efects Item Response Models with the MH-RM Algorithm

ERIC Educational Resources Information Center

Chalmers, R. Philip

2015-01-01

A mixed-effects item response theory (IRT) model is presented as a logical extension of the generalized linear mixed-effects modeling approach to formulating explanatory IRT models. Fixed and random coefficients in the extended model are estimated using a Metropolis-Hastings Robbins-Monro (MH-RM) stochastic imputation algorithm to accommodate for…

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.

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).

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.

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.

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.

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.

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.

Bayesian quantile regression-based partially linear mixed-effects joint models for longitudinal data with multiple features.

PubMed

Zhang, Hanze; Huang, Yangxin; Wang, Wei; Chen, Henian; Langland-Orban, Barbara

2017-01-01

In longitudinal AIDS studies, it is of interest to investigate the relationship between HIV viral load and CD4 cell counts, as well as the complicated time effect. Most of common models to analyze such complex longitudinal data are based on mean-regression, which fails to provide efficient estimates due to outliers and/or heavy tails. Quantile regression-based partially linear mixed-effects models, a special case of semiparametric models enjoying benefits of both parametric and nonparametric models, have the flexibility to monitor the viral dynamics nonparametrically and detect the varying CD4 effects parametrically at different quantiles of viral load. Meanwhile, it is critical to consider various data features of repeated measurements, including left-censoring due to a limit of detection, covariate measurement error, and asymmetric distribution. In this research, we first establish a Bayesian joint models that accounts for all these data features simultaneously in the framework of quantile regression-based partially linear mixed-effects models. The proposed models are applied to analyze the Multicenter AIDS Cohort Study (MACS) data. Simulation studies are also conducted to assess the performance of the proposed methods under different scenarios.

A Bayesian Semiparametric Latent Variable Model for Mixed Responses

ERIC Educational Resources Information Center

Fahrmeir, Ludwig; Raach, Alexander

2007-01-01

In this paper we introduce a latent variable model (LVM) for mixed ordinal and continuous responses, where covariate effects on the continuous latent variables are modelled through a flexible semiparametric Gaussian regression model. We extend existing LVMs with the usual linear covariate effects by including nonparametric components for nonlinear…

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...

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.

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.

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...

Solving a mixture of many random linear equations by tensor decomposition and alternating minimization.

DOT National Transportation Integrated Search

2016-09-01

We consider the problem of solving mixed random linear equations with k components. This is the noiseless setting of mixed linear regression. The goal is to estimate multiple linear models from mixed samples in the case where the labels (which sample...

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.

A Comparison of Two-Stage Approaches for Fitting Nonlinear Ordinary Differential Equation (ODE) Models with Mixed Effects

PubMed Central

Chow, Sy-Miin; Bendezú, Jason J.; Cole, Pamela M.; Ram, Nilam

2016-01-01

Several approaches currently exist for estimating the derivatives of observed data for model exploration purposes, including functional data analysis (FDA), generalized local linear approximation (GLLA), and generalized orthogonal local derivative approximation (GOLD). These derivative estimation procedures can be used in a two-stage process to fit mixed effects ordinary differential equation (ODE) models. While the performance and utility of these routines for estimating linear ODEs have been established, they have not yet been evaluated in the context of nonlinear ODEs with mixed effects. We compared properties of the GLLA and GOLD to an FDA-based two-stage approach denoted herein as functional ordinary differential equation with mixed effects (FODEmixed) in a Monte Carlo study using a nonlinear coupled oscillators model with mixed effects. Simulation results showed that overall, the FODEmixed outperformed both the GLLA and GOLD across all the embedding dimensions considered, but a novel use of a fourth-order GLLA approach combined with very high embedding dimensions yielded estimation results that almost paralleled those from the FODEmixed. We discuss the strengths and limitations of each approach and demonstrate how output from each stage of FODEmixed may be used to inform empirical modeling of young children’s self-regulation. PMID:27391255

A Comparison of Two-Stage Approaches for Fitting Nonlinear Ordinary Differential Equation Models with Mixed Effects.

PubMed

Chow, Sy-Miin; Bendezú, Jason J; Cole, Pamela M; Ram, Nilam

2016-01-01

Several approaches exist for estimating the derivatives of observed data for model exploration purposes, including functional data analysis (FDA; Ramsay & Silverman, 2005 ), generalized local linear approximation (GLLA; Boker, Deboeck, Edler, & Peel, 2010 ), and generalized orthogonal local derivative approximation (GOLD; Deboeck, 2010 ). These derivative estimation procedures can be used in a two-stage process to fit mixed effects ordinary differential equation (ODE) models. While the performance and utility of these routines for estimating linear ODEs have been established, they have not yet been evaluated in the context of nonlinear ODEs with mixed effects. We compared properties of the GLLA and GOLD to an FDA-based two-stage approach denoted herein as functional ordinary differential equation with mixed effects (FODEmixed) in a Monte Carlo (MC) study using a nonlinear coupled oscillators model with mixed effects. Simulation results showed that overall, the FODEmixed outperformed both the GLLA and GOLD across all the embedding dimensions considered, but a novel use of a fourth-order GLLA approach combined with very high embedding dimensions yielded estimation results that almost paralleled those from the FODEmixed. We discuss the strengths and limitations of each approach and demonstrate how output from each stage of FODEmixed may be used to inform empirical modeling of young children's self-regulation.

Comparative Effects of Methylphenidate and Mixed Salts Amphetamine on Height and Weight in Children with Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Pliszka, Steven R.; Matthews, Thomas L.; Braslow, Kenneth J.; Watson, Melissa A.

2006-01-01

Objective: To determine whether methylphenidate (MPH) and mixed salts amphetamine (MSA) have different effects on growth in children with attention-deficit/hyperactivity disorder. Method: Patients treated for at least 1 year with MPH or MSA were identified. A linear regression was performed to determine the effect of stimulant type, patient…

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.

On testing an unspecified function through a linear mixed effects model with multiple variance components

PubMed Central

Wang, Yuanjia; Chen, Huaihou

2012-01-01

Summary We examine a generalized F-test of a nonparametric function through penalized splines and a linear mixed effects model representation. With a mixed effects model representation of penalized splines, we imbed the test of an unspecified function into a test of some fixed effects and a variance component in a linear mixed effects model with nuisance variance components under the null. The procedure can be used to test a nonparametric function or varying-coefficient with clustered data, compare two spline functions, test the significance of an unspecified function in an additive model with multiple components, and test a row or a column effect in a two-way analysis of variance model. Through a spectral decomposition of the residual sum of squares, we provide a fast algorithm for computing the null distribution of the test, which significantly improves the computational efficiency over bootstrap. The spectral representation reveals a connection between the likelihood ratio test (LRT) in a multiple variance components model and a single component model. We examine our methods through simulations, where we show that the power of the generalized F-test may be higher than the LRT, depending on the hypothesis of interest and the true model under the alternative. We apply these methods to compute the genome-wide critical value and p-value of a genetic association test in a genome-wide association study (GWAS), where the usual bootstrap is computationally intensive (up to 108 simulations) and asymptotic approximation may be unreliable and conservative. PMID:23020801

On testing an unspecified function through a linear mixed effects model with multiple variance components.

PubMed

Wang, Yuanjia; Chen, Huaihou

2012-12-01

We examine a generalized F-test of a nonparametric function through penalized splines and a linear mixed effects model representation. With a mixed effects model representation of penalized splines, we imbed the test of an unspecified function into a test of some fixed effects and a variance component in a linear mixed effects model with nuisance variance components under the null. The procedure can be used to test a nonparametric function or varying-coefficient with clustered data, compare two spline functions, test the significance of an unspecified function in an additive model with multiple components, and test a row or a column effect in a two-way analysis of variance model. Through a spectral decomposition of the residual sum of squares, we provide a fast algorithm for computing the null distribution of the test, which significantly improves the computational efficiency over bootstrap. The spectral representation reveals a connection between the likelihood ratio test (LRT) in a multiple variance components model and a single component model. We examine our methods through simulations, where we show that the power of the generalized F-test may be higher than the LRT, depending on the hypothesis of interest and the true model under the alternative. We apply these methods to compute the genome-wide critical value and p-value of a genetic association test in a genome-wide association study (GWAS), where the usual bootstrap is computationally intensive (up to 10(8) simulations) and asymptotic approximation may be unreliable and conservative. © 2012, The International Biometric Society.

The Box-Cox power transformation on nursing sensitive indicators: Does it matter if structural effects are omitted during the estimation of the transformation parameter?

PubMed Central

2011-01-01

Background Many nursing and health related research studies have continuous outcome measures that are inherently non-normal in distribution. The Box-Cox transformation provides a powerful tool for developing a parsimonious model for data representation and interpretation when the distribution of the dependent variable, or outcome measure, of interest deviates from the normal distribution. The objectives of this study was to contrast the effect of obtaining the Box-Cox power transformation parameter and subsequent analysis of variance with or without a priori knowledge of predictor variables under the classic linear or linear mixed model settings. Methods Simulation data from a 3 × 4 factorial treatments design, along with the Patient Falls and Patient Injury Falls from the National Database of Nursing Quality Indicators (NDNQI®) for the 3rd quarter of 2007 from a convenience sample of over one thousand US hospitals were analyzed. The effect of the nonlinear monotonic transformation was contrasted in two ways: a) estimating the transformation parameter along with factors with potential structural effects, and b) estimating the transformation parameter first and then conducting analysis of variance for the structural effect. Results Linear model ANOVA with Monte Carlo simulation and mixed models with correlated error terms with NDNQI examples showed no substantial differences on statistical tests for structural effects if the factors with structural effects were omitted during the estimation of the transformation parameter. Conclusions The Box-Cox power transformation can still be an effective tool for validating statistical inferences with large observational, cross-sectional, and hierarchical or repeated measure studies under the linear or the mixed model settings without prior knowledge of all the factors with potential structural effects. PMID:21854614

The Box-Cox power transformation on nursing sensitive indicators: does it matter if structural effects are omitted during the estimation of the transformation parameter?

PubMed

Hou, Qingjiang; Mahnken, Jonathan D; Gajewski, Byron J; Dunton, Nancy

2011-08-19

Many nursing and health related research studies have continuous outcome measures that are inherently non-normal in distribution. The Box-Cox transformation provides a powerful tool for developing a parsimonious model for data representation and interpretation when the distribution of the dependent variable, or outcome measure, of interest deviates from the normal distribution. The objectives of this study was to contrast the effect of obtaining the Box-Cox power transformation parameter and subsequent analysis of variance with or without a priori knowledge of predictor variables under the classic linear or linear mixed model settings. Simulation data from a 3 × 4 factorial treatments design, along with the Patient Falls and Patient Injury Falls from the National Database of Nursing Quality Indicators (NDNQI® for the 3rd quarter of 2007 from a convenience sample of over one thousand US hospitals were analyzed. The effect of the nonlinear monotonic transformation was contrasted in two ways: a) estimating the transformation parameter along with factors with potential structural effects, and b) estimating the transformation parameter first and then conducting analysis of variance for the structural effect. Linear model ANOVA with Monte Carlo simulation and mixed models with correlated error terms with NDNQI examples showed no substantial differences on statistical tests for structural effects if the factors with structural effects were omitted during the estimation of the transformation parameter. The Box-Cox power transformation can still be an effective tool for validating statistical inferences with large observational, cross-sectional, and hierarchical or repeated measure studies under the linear or the mixed model settings without prior knowledge of all the factors with potential structural effects.

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.

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.

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.

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.

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.

How large are the consequences of covariate imbalance in cluster randomized trials: a simulation study with a continuous outcome and a binary covariate at the cluster level.

PubMed

Moerbeek, Mirjam; van Schie, Sander

2016-07-11

The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.

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.

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data.

PubMed

Ying, Gui-Shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-04-01

To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field in the elderly. When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI -0.03 to 0.32D, p = 0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, p = 0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller p-values, while analysis of the worse eye provided larger p-values than mixed effects models and marginal models. In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision.

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.

A comparison of methods for estimating the random effects distribution of a linear mixed model.

PubMed

Ghidey, Wendimagegn; Lesaffre, Emmanuel; Verbeke, Geert

2010-12-01

This article reviews various recently suggested approaches to estimate the random effects distribution in a linear mixed model, i.e. (1) the smoothing by roughening approach of Shen and Louis,(1) (2) the semi-non-parametric approach of Zhang and Davidian,(2) (3) the heterogeneity model of Verbeke and Lesaffre( 3) and (4) a flexible approach of Ghidey et al. (4) These four approaches are compared via an extensive simulation study. We conclude that for the considered cases, the approach of Ghidey et al. (4) often shows to have the smallest integrated mean squared error for estimating the random effects distribution. An analysis of a longitudinal dental data set illustrates the performance of the methods in a practical example.

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)…

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).

Application of linear mixed-effects model with LASSO to identify metal components associated with cardiac autonomic responses among welders: a repeated measures study

PubMed Central

Zhang, Jinming; Cavallari, Jennifer M; Fang, Shona C; Weisskopf, Marc G; Lin, Xihong; Mittleman, Murray A; Christiani, David C

2017-01-01

Background Environmental and occupational exposure to metals is ubiquitous worldwide, and understanding the hazardous metal components in this complex mixture is essential for environmental and occupational regulations. Objective To identify hazardous components from metal mixtures that are associated with alterations in cardiac autonomic responses. Methods Urinary concentrations of 16 types of metals were examined and ‘acceleration capacity’ (AC) and ‘deceleration capacity’ (DC), indicators of cardiac autonomic effects, were quantified from ECG recordings among 54 welders. We fitted linear mixed-effects models with least absolute shrinkage and selection operator (LASSO) to identify metal components that are associated with AC and DC. The Bayesian Information Criterion was used as the criterion for model selection procedures. Results Mercury and chromium were selected for DC analysis, whereas mercury, chromium and manganese were selected for AC analysis through the LASSO approach. When we fitted the linear mixed-effects models with ‘selected’ metal components only, the effect of mercury remained significant. Every 1 µg/L increase in urinary mercury was associated with −0.58 ms (−1.03, –0.13) changes in DC and 0.67 ms (0.25, 1.10) changes in AC. Conclusion Our study suggests that exposure to several metals is associated with impaired cardiac autonomic functions. Our findings should be replicated in future studies with larger sample sizes. PMID:28663305

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.

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.

Hierarchical Bayes approach for subgroup analysis.

PubMed

Hsu, Yu-Yi; Zalkikar, Jyoti; Tiwari, Ram C

2017-01-01

In clinical data analysis, both treatment effect estimation and consistency assessment are important for a better understanding of the drug efficacy for the benefit of subjects in individual subgroups. The linear mixed-effects model has been used for subgroup analysis to describe treatment differences among subgroups with great flexibility. The hierarchical Bayes approach has been applied to linear mixed-effects model to derive the posterior distributions of overall and subgroup treatment effects. In this article, we discuss the prior selection for variance components in hierarchical Bayes, estimation and decision making of the overall treatment effect, as well as consistency assessment of the treatment effects across the subgroups based on the posterior predictive p-value. Decision procedures are suggested using either the posterior probability or the Bayes factor. These decision procedures and their properties are illustrated using a simulated example with normally distributed response and repeated measurements.

Determining vehicle operating speed and lateral position along horizontal curves using linear mixed-effects models.

PubMed

Fitzsimmons, Eric J; Kvam, Vanessa; Souleyrette, Reginald R; Nambisan, Shashi S; Bonett, Douglas G

2013-01-01

Despite recent improvements in highway safety in the United States, serious crashes on curves remain a significant problem. To assist in better understanding causal factors leading to this problem, this article presents and demonstrates a methodology for collection and analysis of vehicle trajectory and speed data for rural and urban curves using Z-configured road tubes. For a large number of vehicle observations at 2 horizontal curves located in Dexter and Ames, Iowa, the article develops vehicle speed and lateral position prediction models for multiple points along these curves. Linear mixed-effects models were used to predict vehicle lateral position and speed along the curves as explained by operational, vehicle, and environmental variables. Behavior was visually represented for an identified subset of "risky" drivers. Linear mixed-effect regression models provided the means to predict vehicle speed and lateral position while taking into account repeated observations of the same vehicle along horizontal curves. Speed and lateral position at point of entry were observed to influence trajectory and speed profiles. Rural horizontal curve site models are presented that indicate that the following variables were significant and influenced both vehicle speed and lateral position: time of day, direction of travel (inside or outside lane), and type of vehicle.

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.

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.

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data

PubMed Central

Ying, Gui-shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-01-01

Purpose To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. Methods We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field data in the elderly. Results When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI −0.03 to 0.32D, P=0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, P=0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller P-values, while analysis of the worse eye provided larger P-values than mixed effects models and marginal models. Conclusion In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision. PMID:28102741

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

Effect of correlation on covariate selection in linear and nonlinear mixed effect models.

PubMed

Bonate, Peter L

2017-01-01

The effect of correlation among covariates on covariate selection was examined with linear and nonlinear mixed effect models. Demographic covariates were extracted from the National Health and Nutrition Examination Survey III database. Concentration-time profiles were Monte Carlo simulated where only one covariate affected apparent oral clearance (CL/F). A series of univariate covariate population pharmacokinetic models was fit to the data and compared with the reduced model without covariate. The "best" covariate was identified using either the likelihood ratio test statistic or AIC. Weight and body surface area (calculated using Gehan and George equation, 1970) were highly correlated (r = 0.98). Body surface area was often selected as a better covariate than weight, sometimes as high as 1 in 5 times, when weight was the covariate used in the data generating mechanism. In a second simulation, parent drug concentration and three metabolites were simulated from a thorough QT study and used as covariates in a series of univariate linear mixed effects models of ddQTc interval prolongation. The covariate with the largest significant LRT statistic was deemed the "best" predictor. When the metabolite was formation-rate limited and only parent concentrations affected ddQTc intervals the metabolite was chosen as a better predictor as often as 1 in 5 times depending on the slope of the relationship between parent concentrations and ddQTc intervals. A correlated covariate can be chosen as being a better predictor than another covariate in a linear or nonlinear population analysis by sheer correlation These results explain why for the same drug different covariates may be identified in different analyses. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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.

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.

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...

Nonadiabatic effects in ultracold molecules via anomalous linear and quadratic Zeeman shifts.

PubMed

McGuyer, B H; Osborn, C B; McDonald, M; Reinaudi, G; Skomorowski, W; Moszynski, R; Zelevinsky, T

2013-12-13

Anomalously large linear and quadratic Zeeman shifts are measured for weakly bound ultracold 88Sr2 molecules near the intercombination-line asymptote. Nonadiabatic Coriolis coupling and the nature of long-range molecular potentials explain how this effect arises and scales roughly cubically with the size of the molecule. The linear shifts yield nonadiabatic mixing angles of the molecular states. The quadratic shifts are sensitive to nearby opposite f-parity states and exhibit fourth-order corrections, providing a stringent test of a state-of-the-art ab initio model.

On Fitting Generalized Linear Mixed-effects Models for Binary Responses using Different Statistical Packages

PubMed Central

Zhang, Hui; Lu, Naiji; Feng, Changyong; Thurston, Sally W.; Xia, Yinglin; Tu, Xin M.

2011-01-01

Summary The generalized linear mixed-effects model (GLMM) is a popular paradigm to extend models for cross-sectional data to a longitudinal setting. When applied to modeling binary responses, different software packages and even different procedures within a package may give quite different results. In this report, we describe the statistical approaches that underlie these different procedures and discuss their strengths and weaknesses when applied to fit correlated binary responses. We then illustrate these considerations by applying these procedures implemented in some popular software packages to simulated and real study data. Our simulation results indicate a lack of reliability for most of the procedures considered, which carries significant implications for applying such popular software packages in practice. PMID:21671252

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.

Endotoxin and gender modify lung function recovery after occupational organic dust exposure: a 30-year study.

PubMed

Lai, Peggy S; Hang, Jing-Qing; Valeri, Linda; Zhang, Feng-Ying; Zheng, Bu-Yong; Mehta, Amar J; Shi, Jing; Su, Li; Brown, Dan; Eisen, Ellen A; Christiani, David C

2015-08-01

The purpose of this study is to determine the trajectory of lung function change after exposure cessation to occupational organic dust exposure, and to identify factors that modify improvement. The Shanghai Textile Worker Study is a longitudinal study of 447 cotton workers exposed to endotoxin-containing dust and 472 silk workers exposed to non-endotoxin-containing dust. Spirometry was performed at 5-year intervals. Air sampling was performed to estimate individual cumulative exposures. The effect of work cessation on forced expiratory volume in 1 s (FEV1) was modelled using generalised additive mixed effects models to identify the trajectory of FEV1 recovery. Linear mixed effects models incorporating interaction terms were used to identify modifiers of FEV1 recovery. Loss to follow-up was accounted for with inverse probability of censoring weights. 74.2% of the original cohort still alive participated in 2011. Generalised additive mixed models identified a non-linear improvement in FEV1 for all workers after exposure cessation, with no plateau noted 25 years after retirement. Linear mixed effects models incorporating interaction terms identified prior endotoxin exposure (p=0.01) and male gender (p=0.002) as risk factors for impaired FEV1 improvement after exposure cessation. After adjusting for gender, smoking delayed the onset of FEV1 gain but did not affect the overall magnitude of change. Lung function improvement after cessation of exposure to organic dust is sustained. Endotoxin exposure and male gender are risk factors for less FEV1 improvement. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

On the repeated measures designs and sample sizes for randomized controlled trials.

PubMed

Tango, Toshiro

2016-04-01

For the analysis of longitudinal or repeated measures data, generalized linear mixed-effects models provide a flexible and powerful tool to deal with heterogeneity among subject response profiles. However, the typical statistical design adopted in usual randomized controlled trials is an analysis of covariance type analysis using a pre-defined pair of "pre-post" data, in which pre-(baseline) data are used as a covariate for adjustment together with other covariates. Then, the major design issue is to calculate the sample size or the number of subjects allocated to each treatment group. In this paper, we propose a new repeated measures design and sample size calculations combined with generalized linear mixed-effects models that depend not only on the number of subjects but on the number of repeated measures before and after randomization per subject used for the analysis. The main advantages of the proposed design combined with the generalized linear mixed-effects models are (1) it can easily handle missing data by applying the likelihood-based ignorable analyses under the missing at random assumption and (2) it may lead to a reduction in sample size, compared with the simple pre-post design. The proposed designs and the sample size calculations are illustrated with real data arising from randomized controlled trials. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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.

Linear models for sound from supersonic reacting mixing layers

NASA Astrophysics Data System (ADS)

Chary, P. Shivakanth; Samanta, Arnab

2016-12-01

We perform a linearized reduced-order modeling of the aeroacoustic sound sources in supersonic reacting mixing layers to explore their sensitivities to some of the flow parameters in radiating sound. Specifically, we investigate the role of outer modes as the effective flow compressibility is raised, when some of these are expected to dominate over the traditional Kelvin-Helmholtz (K-H) -type central mode. Although the outer modes are known to be of lesser importance in the near-field mixing, how these radiate to the far-field is uncertain, on which we focus. On keeping the flow compressibility fixed, the outer modes are realized via biasing the respective mean densities of the fast (oxidizer) or slow (fuel) side. Here the mean flows are laminar solutions of two-dimensional compressible boundary layers with an imposed composite (turbulent) spreading rate, which we show to significantly alter the growth of instability waves by saturating them earlier, similar to in nonlinear calculations, achieved here via solving the linear parabolized stability equations. As the flow parameters are varied, instability of the slow modes is shown to be more sensitive to heat release, potentially exceeding equivalent central modes, as these modes yield relatively compact sound sources with lesser spreading of the mixing layer, when compared to the corresponding fast modes. In contrast, the radiated sound seems to be relatively unaffected when the mixture equivalence ratio is varied, except for a lean mixture which is shown to yield a pronounced effect on the slow mode radiation by reducing its modal growth.

On fitting generalized linear mixed-effects models for binary responses using different statistical packages.

PubMed

Zhang, Hui; Lu, Naiji; Feng, Changyong; Thurston, Sally W; Xia, Yinglin; Zhu, Liang; Tu, Xin M

2011-09-10

The generalized linear mixed-effects model (GLMM) is a popular paradigm to extend models for cross-sectional data to a longitudinal setting. When applied to modeling binary responses, different software packages and even different procedures within a package may give quite different results. In this report, we describe the statistical approaches that underlie these different procedures and discuss their strengths and weaknesses when applied to fit correlated binary responses. We then illustrate these considerations by applying these procedures implemented in some popular software packages to simulated and real study data. Our simulation results indicate a lack of reliability for most of the procedures considered, which carries significant implications for applying such popular software packages in practice. Copyright © 2011 John Wiley & Sons, Ltd.

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.

Neutron response of GafChromic® EBT2 film

NASA Astrophysics Data System (ADS)

Hsiao, Ming-Chen; Liu, Yuan-Hao; Chen, Wei-Lin; Jiang, Shiang-Huei

2013-03-01

Neutron and gamma-ray mixed field dosimetry remains one of the most challenging topics in radiation dosimetry studies. However, the requirement for accurate mixed field dosimetry is increasing because of the considerable interest in high-energy radiotherapy machines, medical ion beams and BNCT epithermal neutron beams. Therefore, this study investigated the GafChromic® EBT2 film. The linearity, reproducibility, energy dependence and homogeneity of the film were tested in a 60Co medical beam, 6-MV LINAC and 10-MV LINAC. The linearity and self-developing effect of the film irradiated in an epithermal neutron beam were also examined. These basic detector characteristics showed that EBT2 film can be effectively applied in mixed field dosimetry. A general detector response model was developed to determine the neutron relative effectiveness (RE) values. The RE value of fast neutrons varies with neutron spectra. By contrast, the RE value of thermal neutrons was determined as a constant; it is only 32.5% in relation to gamma rays. No synergy effect was observed in this study. The lithium-6 capture reaction dominates the neutron response in the thermal neutron energy range, and the recoil hydrogen dose becomes the dominant component in the fast neutron energy region. Based on this study, the application of the EBT2 film in the neutron and gamma-ray mixed field is feasible.

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.

Non-linear Growth Models in Mplus and SAS

PubMed Central

Grimm, Kevin J.; Ram, Nilam

2013-01-01

Non-linear growth curves or growth curves that follow a specified non-linear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this paper we describe how a variety of sigmoid curves can be fit using the Mplus structural modeling program and the non-linear mixed-effects modeling procedure NLMIXED in SAS. Using longitudinal achievement data collected as part of a study examining the effects of preschool instruction on academic gain we illustrate the procedures for fitting growth models of logistic, Gompertz, and Richards functions. Brief notes regarding the practical benefits, limitations, and choices faced in the fitting and estimation of such models are included. PMID:23882134

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.

Effects of Saccharomyces cerevisiae fermentation product on in vitro fermentation and microbial communities of low-quality forages and mixed diets.

PubMed

Mao, Hui-ling; Mao, Hua-long; Wang, J K; Liu, J X; Yoon, I

2013-07-01

Two experiments were conducted to investigate the effects of a Saccharomyces cerevisiae fermentation product (XP, Diamond V, Cedar Rapids, IA) on in vitro ruminal fermentation of single forage and mixed diets. In Exp. 1, an in vitro test was used to determine the effects of various concentrations (0, 1, 2, and 3 g/L) of XP on ruminal fermentation of the major forage sources of China (rice straw, RS; corn stover, CS; corn silage without grain, CSNG; and corn silage with grain, CSG). Total VFA reached a peak at 1 g/L XP for RS, CSNG, and CSG and increased linearly (P < 0.01) for CS. The molar proportion of acetate decreased and propionate increased linearly (P < 0.01) with an increasing amount of XP for RS, CS, and CSNG. Microbial protein (MCP) increased linearly (P < 0.01) with an increasing level of XP for RS, and it reached peak values at 1 and 2 g/L XP for CSG and CSNG, respectively. Fungi population was increased (P < 0.05) with 1 g/L XP for all forages except CSNG. The population of Ruminococcus flavefaciens increased (P < 0.05) at 1 or 2 g/L XP for RS, CSNG, and CSG. In Exp. 2, the effects of 3 concentrations of XP (0, 1, and 2 g/L) were tested on in vitro ruminal fermentation of 3 mixed diets with various ingredient combinations: 1) CSC (corn:soybean meal:corn stover = 33:22:45), 2) CSCC (corn:soybean meal:corn stover:corn silage = 33:22:22.5:22.5), and 3) CSCCA (corn:soybean meal:corn stover:corn silage:alfalfa = 33:22:19:21:5). Total VFA concentrations were influenced by diets (P < 0.01) and were enhanced linearly by increasing concentrations of XP (P < 0.01). The molar proportion of acetate was reduced (P < 0.01), but the propionate proportion was enhanced with increasing concentrations of XP (P < 0.01). Ammonia N was decreased and MCP was increased by the addition of XP (linear, P < 0.01; quadratic, P < 0.05). The fungi population was greater with XP addition (quadratic, P < 0.01). The percentage of R. albus was affected by diets (P < 0.01), the level of XP (linear and quadratic, P < 0.01), and their interaction (P < 0.01). From these 2 in vitro studies, it is inferred that the addition of XP could improve the rumen fermentation of forages and mixed diets by stimulating the number of fiber-digesting rumen microbes, especially fungi populations.

Numerical study of steady dissipative mixed convection optically-thick micropolar flow with thermal radiation effects

NASA Astrophysics Data System (ADS)

Gupta, Diksha; Kumar, Lokendra; Bég, O. Anwar; Singh, Bani

2017-10-01

The objective of this paper is to study theoretically and numerically the effect of thermal radiation on mixed convection boundary layer flow of a dissipative micropolar non-Newtonian fluid from a continuously moving vertical porous sheet. The governing partial differential equations are transformed into a set of non-linear differential equations by using similarity transformations. These equations are solved iteratively with the Bellman-Kalaba quasi-linearization algorithm. This method converges quadratically and the solution is valid for a large range of parameters. The effects of transpiration (suction or injection) parameter, buoyancy parameter, radiation parameter and Eckert number on velocity, microrotation and temperature functions have been studied. Under a special case comparison of the present numerical results is made with the results available in the literature and an excellent agreement is found. Additionally skin friction and rate of heat transfer have also been computed. The study has applications in polymer processing.

Numerical simulation of the non-Newtonian mixing layer

NASA Technical Reports Server (NTRS)

Azaiez, Jalel; Homsy, G. M.

1993-01-01

This work is a continuing effort to advance our understanding of the effects of polymer additives on the structures of the mixing layer. In anticipation of full nonlinear simulations of the non-Newtonian mixing layer, we examined in a first stage the linear stability of the non-Newtonian mixing layer. The results of this study show that, for a fluid described by the Oldroyd-B model, viscoelasticity reduces the instability of the inviscid mixing layer in a special limit where the ratio (We/Re) is of order 1 where We is the Weissenberg number, a measure of the elasticity of the flow, and Re is the Reynolds number. In the present study, we pursue this project with numerical simulations of the non-Newtonian mixing layer. Our primary objective is to determine the effects of viscoelasticity on the roll-up structure. We also examine the origin of the numerical instabilities usually encountered in the simulations of non-Newtonian fluids.

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

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.

Effective Teaching Results in Increased Science Achievement for All Students

ERIC Educational Resources Information Center

Johnson, Carla C.; Kahle, Jane Butler; Fargo, Jamison D.

2007-01-01

This study of teacher effectiveness and student achievement in science demonstrated that effective teachers positively impact student learning. A general linear mixed model was used to assess change in student scores on the Discovery Inquiry Test as a function of time, race, teacher effectiveness, gender, and impact of teacher effectiveness in…

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.

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.

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.

Random Effects Structure for Confirmatory Hypothesis Testing: Keep It Maximal

ERIC Educational Resources Information Center

Barr, Dale J.; Levy, Roger; Scheepers, Christoph; Tily, Harry J.

2013-01-01

Linear mixed-effects models (LMEMs) have become increasingly prominent in psycholinguistics and related areas. However, many researchers do not seem to appreciate how random effects structures affect the generalizability of an analysis. Here, we argue that researchers using LMEMs for confirmatory hypothesis testing should minimally adhere to the…

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...

Measuring the individual benefit of a medical or behavioral treatment using generalized linear mixed-effects models.

PubMed

Diaz, Francisco J

2016-10-15

We propose statistical definitions of the individual benefit of a medical or behavioral treatment and of the severity of a chronic illness. These definitions are used to develop a graphical method that can be used by statisticians and clinicians in the data analysis of clinical trials from the perspective of personalized medicine. The method focuses on assessing and comparing individual effects of treatments rather than average effects and can be used with continuous and discrete responses, including dichotomous and count responses. The method is based on new developments in generalized linear mixed-effects models, which are introduced in this article. To illustrate, analyses of data from the Sequenced Treatment Alternatives to Relieve Depression clinical trial of sequences of treatments for depression and data from a clinical trial of respiratory treatments are presented. The estimation of individual benefits is also explained. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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.

A Parameter Subset Selection Algorithm for Mixed-Effects Models

DOE PAGES

Schmidt, Kathleen L.; Smith, Ralph C.

2016-01-01

Mixed-effects models are commonly used to statistically model phenomena that include attributes associated with a population or general underlying mechanism as well as effects specific to individuals or components of the general mechanism. This can include individual effects associated with data from multiple experiments. However, the parameterizations used to incorporate the population and individual effects are often unidentifiable in the sense that parameters are not uniquely specified by the data. As a result, the current literature focuses on model selection, by which insensitive parameters are fixed or removed from the model. Model selection methods that employ information criteria are applicablemore » to both linear and nonlinear mixed-effects models, but such techniques are limited in that they are computationally prohibitive for large problems due to the number of possible models that must be tested. To limit the scope of possible models for model selection via information criteria, we introduce a parameter subset selection (PSS) algorithm for mixed-effects models, which orders the parameters by their significance. In conclusion, we provide examples to verify the effectiveness of the PSS algorithm and to test the performance of mixed-effects model selection that makes use of parameter subset selection.« less

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

Use of non-linear mixed-effects modelling and regression analysis to predict the number of somatic coliphages by plaque enumeration after 3 hours of incubation.

PubMed

Mendez, Javier; Monleon-Getino, Antonio; Jofre, Juan; Lucena, Francisco

2017-10-01

The present study aimed to establish the kinetics of the appearance of coliphage plaques using the double agar layer titration technique to evaluate the feasibility of using traditional coliphage plaque forming unit (PFU) enumeration as a rapid quantification method. Repeated measurements of the appearance of plaques of coliphages titrated according to ISO 10705-2 at different times were analysed using non-linear mixed-effects regression to determine the most suitable model of their appearance kinetics. Although this model is adequate, to simplify its applicability two linear models were developed to predict the numbers of coliphages reliably, using the PFU counts as determined by the ISO after only 3 hours of incubation. One linear model, when the number of plaques detected was between 4 and 26 PFU after 3 hours, had a linear fit of: (1.48 × Counts 3 h + 1.97); and the other, values >26 PFU, had a fit of (1.18 × Counts 3 h + 2.95). If the number of plaques detected was <4 PFU after 3 hours, we recommend incubation for (18 ± 3) hours. The study indicates that the traditional coliphage plating technique has a reasonable potential to provide results in a single working day without the need to invest in additional laboratory equipment.

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

Measurements of Infrared and Acoustic Source Distributions in Jet Plumes

NASA Technical Reports Server (NTRS)

Agboola, Femi A.; Bridges, James; Saiyed, Naseem

2004-01-01

The aim of this investigation was to use the linear phased array (LPA) microphones and infrared (IR) imaging to study the effects of advanced nozzle-mixing techniques on jet noise reduction. Several full-scale engine nozzles were tested at varying power cycles with the linear phased array setup parallel to the jet axis. The array consisted of 16 sparsely distributed microphones. The phased array microphone measurements were taken at a distance of 51.0 ft (15.5 m) from the jet axis, and the results were used to obtain relative overall sound pressure levels from one nozzle design to the other. The IR imaging system was used to acquire real-time dynamic thermal patterns of the exhaust jet from the nozzles tested. The IR camera measured the IR radiation from the nozzle exit to a distance of six fan diameters (X/D(sub FAN) = 6), along the jet plume axis. The images confirmed the expected jet plume mixing intensity, and the phased array results showed the differences in sound pressure level with respect to nozzle configurations. The results show the effects of changes in configurations to the exit nozzles on both the flows mixing patterns and radiant energy dissipation patterns. By comparing the results from these two measurements, a relationship between noise reduction and core/bypass flow mixing is demonstrated.

Modulation of Additive and Interactive Effects in Lexical Decision by Trial History

ERIC Educational Resources Information Center

Masson, Michael E. J.; Kliegl, Reinhold

2013-01-01

Additive and interactive effects of word frequency, stimulus quality, and semantic priming have been used to test theoretical claims about the cognitive architecture of word-reading processes. Additive effects among these factors have been taken as evidence for discrete-stage models of word reading. We present evidence from linear mixed-model…

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

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.

Functional linear models for association analysis of quantitative traits.

PubMed

Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao

2013-11-01

Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY PERIODICALS, INC.

COSOLVENT EFFECTS ON SORPTION ISOTHERM LINEARITY

EPA Science Inventory

Sorption-desorption hysteresis, slow desorption kinetics, and other nonideal phenomena have been attributed to the differing sorptive characteristics of the natural organic polymers associated with soils and sediments. In this study, aqueous and mixed solvent systems were used t...

Modeling Systematicity and Individuality in Nonlinear Second Language Development: The Case of English Grammatical Morphemes

ERIC Educational Resources Information Center

Murakami, Akira

2016-01-01

This article introduces two sophisticated statistical modeling techniques that allow researchers to analyze systematicity, individual variation, and nonlinearity in second language (L2) development. Generalized linear mixed-effects models can be used to quantify individual variation and examine systematic effects simultaneously, and generalized…

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.

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

An analysis of a large dataset on immigrant integration in Spain. The Statistical Mechanics perspective on Social Action

NASA Astrophysics Data System (ADS)

Barra, Adriano; Contucci, Pierluigi; Sandell, Rickard; Vernia, Cecilia

2014-02-01

How does immigrant integration in a country change with immigration density? Guided by a statistical mechanics perspective we propose a novel approach to this problem. The analysis focuses on classical integration quantifiers such as the percentage of jobs (temporary and permanent) given to immigrants, mixed marriages, and newborns with parents of mixed origin. We find that the average values of different quantifiers may exhibit either linear or non-linear growth on immigrant density and we suggest that social action, a concept identified by Max Weber, causes the observed non-linearity. Using the statistical mechanics notion of interaction to quantitatively emulate social action, a unified mathematical model for integration is proposed and it is shown to explain both growth behaviors observed. The linear theory instead, ignoring the possibility of interaction effects would underestimate the quantifiers up to 30% when immigrant densities are low, and overestimate them as much when densities are high. The capacity to quantitatively isolate different types of integration mechanisms makes our framework a suitable tool in the quest for more efficient integration policies.

Ghost interactions in MEG/EEG source space: A note of caution on inter-areal coupling measures.

PubMed

Palva, J Matias; Wang, Sheng H; Palva, Satu; Zhigalov, Alexander; Monto, Simo; Brookes, Matthew J; Schoffelen, Jan-Mathijs; Jerbi, Karim

2018-06-01

When combined with source modeling, magneto- (MEG) and electroencephalography (EEG) can be used to study long-range interactions among cortical processes non-invasively. Estimation of such inter-areal connectivity is nevertheless hindered by instantaneous field spread and volume conduction, which artificially introduce linear correlations and impair source separability in cortical current estimates. To overcome the inflating effects of linear source mixing inherent to standard interaction measures, alternative phase- and amplitude-correlation based connectivity measures, such as imaginary coherence and orthogonalized amplitude correlation have been proposed. Being by definition insensitive to zero-lag correlations, these techniques have become increasingly popular in the identification of correlations that cannot be attributed to field spread or volume conduction. We show here, however, that while these measures are immune to the direct effects of linear mixing, they may still reveal large numbers of spurious false positive connections through field spread in the vicinity of true interactions. This fundamental problem affects both region-of-interest-based analyses and all-to-all connectome mappings. Most importantly, beyond defining and illustrating the problem of spurious, or "ghost" interactions, we provide a rigorous quantification of this effect through extensive simulations. Additionally, we further show that signal mixing also significantly limits the separability of neuronal phase and amplitude correlations. We conclude that spurious correlations must be carefully considered in connectivity analyses in MEG/EEG source space even when using measures that are immune to zero-lag correlations. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Time-dependent analysis of the mixed-field orientation of molecules without rotational symmetry

NASA Astrophysics Data System (ADS)

Thesing, Linda V.; Küpper, Jochen; González-Férez, Rosario

2017-06-01

We present a theoretical study of the mixed-field orientation of molecules without rotational symmetry. The time-dependent one-dimensional and three-dimensional orientation of a thermal ensemble of 6-chloropyridazine-3-carbonitrile molecules in combined linearly or elliptically polarized laser fields and tilted dc electric fields is computed. The results are in good agreement with recent experimental results of one-dimensional orientation for weak dc electric fields [J. L. Hansen, J. Chem. Phys. 139, 234313 (2013)]. Moreover, they predict that using elliptically polarized laser fields or strong dc fields, three-dimensional orientation is obtained. The field-dressed dynamics of excited rotational states is characterized by highly non-adiabatic effects. We analyze the sources of these non-adiabatic effects and investigate their impact on the mixed-field orientation for different field configurations in mixed-field-orientation experiments.

Wavelet-based functional linear mixed models: an application to measurement error-corrected distributed lag models.

PubMed

Malloy, Elizabeth J; Morris, Jeffrey S; Adar, Sara D; Suh, Helen; Gold, Diane R; Coull, Brent A

2010-07-01

Frequently, exposure data are measured over time on a grid of discrete values that collectively define a functional observation. In many applications, researchers are interested in using these measurements as covariates to predict a scalar response in a regression setting, with interest focusing on the most biologically relevant time window of exposure. One example is in panel studies of the health effects of particulate matter (PM), where particle levels are measured over time. In such studies, there are many more values of the functional data than observations in the data set so that regularization of the corresponding functional regression coefficient is necessary for estimation. Additional issues in this setting are the possibility of exposure measurement error and the need to incorporate additional potential confounders, such as meteorological or co-pollutant measures, that themselves may have effects that vary over time. To accommodate all these features, we develop wavelet-based linear mixed distributed lag models that incorporate repeated measures of functional data as covariates into a linear mixed model. A Bayesian approach to model fitting uses wavelet shrinkage to regularize functional coefficients. We show that, as long as the exposure error induces fine-scale variability in the functional exposure profile and the distributed lag function representing the exposure effect varies smoothly in time, the model corrects for the exposure measurement error without further adjustment. Both these conditions are likely to hold in the environmental applications we consider. We examine properties of the method using simulations and apply the method to data from a study examining the association between PM, measured as hourly averages for 1-7 days, and markers of acute systemic inflammation. We use the method to fully control for the effects of confounding by other time-varying predictors, such as temperature and co-pollutants.

Multiple component end-member mixing model of dilution: hydrochemical effects of construction water at Yucca Mountain, Nevada, USA

NASA Astrophysics Data System (ADS)

Lu, Guoping; Sonnenthal, Eric L.; Bodvarsson, Gudmundur S.

2008-12-01

The standard dual-component and two-member linear mixing model is often used to quantify water mixing of different sources. However, it is no longer applicable whenever actual mixture concentrations are not exactly known because of dilution. For example, low-water-content (low-porosity) rock samples are leached for pore-water chemical compositions, which therefore are diluted in the leachates. A multicomponent, two-member mixing model of dilution has been developed to quantify mixing of water sources and multiple chemical components experiencing dilution in leaching. This extended mixing model was used to quantify fracture-matrix interaction in construction-water migration tests along the Exploratory Studies Facility (ESF) tunnel at Yucca Mountain, Nevada, USA. The model effectively recovers the spatial distribution of water and chemical compositions released from the construction water, and provides invaluable data on the matrix fracture interaction. The methodology and formulations described here are applicable to many sorts of mixing-dilution problems, including dilution in petroleum reservoirs, hydrospheres, chemical constituents in rocks and minerals, monitoring of drilling fluids, and leaching, as well as to environmental science studies.

NONLINEAR OPTICAL EFFECTS AND FIBER OPTICS: Theory of four-wave mixing in photorefractive media when the response of a medium is nonlinear in respect of the modulation parameter

NASA Astrophysics Data System (ADS)

Zozulya, A. A.

1988-12-01

A theoretical model is constructed for four-wave mixing in a photorefractive crystal where a transmission grating is formed by the drift-diffusion nonlinearity mechanism in the absence of an external electrostatic field and the response of the medium is nonlinear in respect of the modulation parameter. A comparison is made with a model in which the response of the medium is linear in respect of the modulation parameter. Theoretical models of four-wave and two-wave mixing are also compared with experiments.

Numerical Study of Buoyancy and Different Diffusion Effects on the Structure and Dynamics of Triple Flames

NASA Technical Reports Server (NTRS)

Chen, Jyh-Yuan; Echekki, Tarek

2001-01-01

Numerical simulations of 2-D triple flames under gravity force have been implemented to identify the effects of gravity on triple flame structure and propagation properties and to understand the mechanisms of instabilities resulting from both heat release and buoyancy effects. A wide range of gravity conditions, heat release, and mixing widths for a scalar mixing layer are computed for downward-propagating (in the same direction with the gravity vector) and upward-propagating (in the opposite direction of the gravity vector) triple flames. Results of numerical simulations show that gravity strongly affects the triple flame speed through its contribution to the overall flow field. A simple analytical model for the triple flame speed, which accounts for both buoyancy and heat release, is developed. Comparisons of the proposed model with the numerical results for a wide range of gravity, heat release and mixing width conditions, yield very good agreement. The analysis shows that under neutral diffusion, downward propagation reduces the triple flame speed, while upward propagation enhances it. For the former condition, a critical Froude number may be evaluated, which corresponds to a vanishing triple flame speed. Downward-propagating triple flames at relatively strong gravity effects have exhibited instabilities. These instabilities are generated without any artificial forcing of the flow. Instead disturbances are initiated by minute round-off errors in the numerical simulations, and subsequently amplified by instabilities. A linear stability analysis on mean profiles of stable triple flame configurations have been performed to identify the most amplified frequency in spatially developed flows. The eigenfunction equations obtained from the linearized disturbance equations are solved using the shooting method. The linear stability analysis yields reasonably good agreements with the observed frequencies of the unstable triple flames. The frequencies and amplitudes of disturbances increase with the magnitude of the gravity vector. Moreover, disturbances appear to be most amplified just downstream of the premixed branches. The effects of mixing width and differential diffusion are investigated and their roles on the flame stability are studied.

Investigations of the local distortions and EPR parameters for Cu2+ in xNa2 O-(30-x)K2 O-70B2 O3 (5 ≤ x ≤ 25 mol%) glasses.

PubMed

Zhang, Zhen-Ya; Wu, Shao-Yi; Zhang, Fu; Zhang, Cheng-Xi; Qin, Rui-Jie; Gao, Han

2018-03-01

The local distortions and electron paramagnetic resonance parameters for Cu 2+ in the mixed alkali borate glasses xNa 2 O-(30-x)K 2 O-70B 2 O 3 (5 ≤ x ≤ 25 mol%) are theoretically studied with distinct modifier Na 2 O compositions x. Owing to the Jahn-Teller effect, the octahedral [CuO 6 ] 10- clusters show significant tetragonal elongation ratios p ~19% along the C 4 axis. With the increase of composition x, the cubic field parameter Dq and the orbital reduction factor k exhibit linearly and quasi-linearly decreasing tendencies, respectively, whereas the relative tetragonal elongation ratio p has quasi-linearly increasing rule with some fluctuations, leading to the minima of g factors at x = 10 mol%. The composition dependences of the optical spectra and the electron paramagnetic resonance parameters are suitably reproduced by the linear or quasi-linear relationships of the relevant quantities (i.e., Dq, k, and p) with x. The above composition dependences are analyzed from mixed alkali effect, which brings forward the modifications of the local crystal-fields and the electronic cloud distribution around Cu 2+ with the variation of the composition of Na 2 O. Copyright © 2017 John Wiley & Sons, Ltd.

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.

Ultrafast Single-Shot Optical Oscilloscope based on Time-to-Space Conversion due to Temporal and Spatial Walk-Off Effects in Nonlinear Mixing Crystal

NASA Astrophysics Data System (ADS)

Takagi, Yoshihiro; Yamada, Yoshifumi; Ishikawa, Kiyoshi; Shimizu, Seiji; Sakabe, Shuji

2005-09-01

A simple method for single-shot sub-picosecond optical pulse diagnostics has been demonstrated by imaging the time evolution of the optical mixing onto the beam cross section of the sum-frequency wave when the interrogating pulse passes over the tested pulse in the mixing crystal as a result of the combined effect of group-velocity difference and walk-off beam propagation. A high linearity of the time-to-space projection is deduced from the process solely dependent upon the spatial uniformity of the refractive indices. A snap profile of the accidental coincidence between asynchronous pulses from separate mode-locked lasers has been detected, which demonstrates the single-shot ability.

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

The Effect of Primary School Size on Academic Achievement

ERIC Educational Resources Information Center

Gershenson, Seth; Langbein, Laura

2015-01-01

Evidence on optimal school size is mixed. We estimate the effect of transitory changes in school size on the academic achievement of fourth-and fifth-grade students in North Carolina using student-level longitudinal administrative data. Estimates of value-added models that condition on school-specific linear time trends and a variety of…

Perturbation Effects on a Supercritical C7H16/N2 Mixing Layer

NASA Technical Reports Server (NTRS)

Okongo'o, Nora; Bellan, Josette

2008-01-01

A computational-simulation study has been presented of effects of perturbation wavelengths and initial Reynolds numbers on the transition to turbulence of a heptane/nitrogen mixing layer at supercritical pressure. The governing equations for the simulations were the same as those of related prior studies reported in NASA Tech Briefs. Two-dimensional (2D) simulations were performed with initially im posed span wise perturbations whereas three-dimensional (3D) simulations had both streamwise and spanwise initial perturbations. The 2D simulations were undertaken to ascertain whether perturbations having the shortest unstable wavelength obtained from a linear stability analysis for inviscid flow are unstable in viscous nonlinear flows. The goal of the 3D simulations was to ascertain whether perturbing the mixing layer at different wavelengths affects the transition to turbulence. It was found that transitions to turbulence can be obtained at different perturbation wavelengths, provided that they are longer than the shortest unstable wavelength as determined by 2D linear stability analysis for the inviscid case and that the initial Reynolds number is proportionally increased as the wavelength is decreased. The transitional states thus obtained display different dynamic and mixture characteristics, departing strongly from the behaviors of perfect gases and ideal mixtures.

Factors associated with parasite dominance in fishes from Brazil.

PubMed

Amarante, Cristina Fernandes do; Tassinari, Wagner de Souza; Luque, Jose Luis; Pereira, Maria Julia Salim

2016-06-14

The present study used regression models to evaluate the existence of factors that may influence the numerical parasite dominance with an epidemiological approximation. A database including 3,746 fish specimens and their respective parasites were used to evaluate the relationship between parasite dominance and biotic characteristics inherent to the studied hosts and the parasite taxa. Multivariate, classical, and mixed effects linear regression models were fitted. The calculations were performed using R software (95% CI). In the fitting of the classical multiple linear regression model, freshwater and planktivorous fish species and body length, as well as the species of the taxa Trematoda, Monogenea, and Hirudinea, were associated with parasite dominance. However, the fitting of the mixed effects model showed that the body length of the host and the species of the taxa Nematoda, Trematoda, Monogenea, Hirudinea, and Crustacea were significantly associated with parasite dominance. Studies that consider specific biological aspects of the hosts and parasites should expand the knowledge regarding factors that influence the numerical dominance of fish in Brazil. The use of a mixed model shows, once again, the importance of the appropriate use of a model correlated with the characteristics of the data to obtain consistent results.

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.

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 ...

Eggshell membrane-based biotemplating of mixed hemimicelle/admicelle as a solid-phase extraction adsorbent for carcinogenic polycyclic aromatic hydrocarbons.

PubMed

Wang, Weidong; Chen, Bo; Huang, Yuming

2014-08-13

A new solid-phase extraction (SPE) format was demonstrated, based on eggshell membrane (ESM) templating of the mixed hemimicelle/admicelle of linear alkylbenzenesulfonates (LAS) as an adsorbent for the enrichment of carcinogenic polycyclic aromatic hydrocarbons (PAHs) in environmental aqueous samples. The LAS mixed hemimicelle/admicelle formation and SPE of the target PAHs were conducted simultaneously by adding the organic target and LAS through a column filled with 500 mg of ESM. The effect of various factors, including LAS concentration, solution pH, ionic strength, and humic acid concentration on the recoveries of PAHs were investigated and optimized. The results showed that LAS concentration and solution pH had obvious effect on extraction of PAHs, and the recoveries of PAHs compounds decreased in the presence of salt and humic acid. Under the optimized analytical conditions, the present method could respond down to 0.1-8.6 ng/L PAHs with a linear calibration ranging from 0.02 to 10 μg/L, showing a good PAHs enrichment ability with high sensitivity. The developed method was used satisfactorily for the detection of PAHs in environmental water samples. The mixed hemimicelle/admicelle adsorbent exhibited high extraction efficiency to PAHs and good selectivity with respect to natural organic matter and was advantageous over commercial C₁₈ adsorbent, for example, high extraction yield, high breakthrough volume, and easy regeneration.

An approximate generalized linear model with random effects for informative missing data.

PubMed

Follmann, D; Wu, M

1995-03-01

This paper develops a class of models to deal with missing data from longitudinal studies. We assume that separate models for the primary response and missingness (e.g., number of missed visits) are linked by a common random parameter. Such models have been developed in the econometrics (Heckman, 1979, Econometrica 47, 153-161) and biostatistics (Wu and Carroll, 1988, Biometrics 44, 175-188) literature for a Gaussian primary response. We allow the primary response, conditional on the random parameter, to follow a generalized linear model and approximate the generalized linear model by conditioning on the data that describes missingness. The resultant approximation is a mixed generalized linear model with possibly heterogeneous random effects. An example is given to illustrate the approximate approach, and simulations are performed to critique the adequacy of the approximation for repeated binary data.

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.

Drug awareness in adolescents attending a mental health service: analysis of longitudinal data.

PubMed

Arnau, Jaume; Bono, Roser; Díaz, Rosa; Goti, Javier

2011-11-01

One of the procedures used most recently with longitudinal data is linear mixed models. In the context of health research the increasing number of studies that now use these models bears witness to the growing interest in this type of analysis. This paper describes the application of linear mixed models to a longitudinal study of a sample of Spanish adolescents attending a mental health service, the aim being to investigate their knowledge about the consumption of alcohol and other drugs. More specifically, the main objective was to compare the efficacy of a motivational interviewing programme with a standard approach to drug awareness. The models used to analyse the overall indicator of drug awareness were as follows: (a) unconditional linear growth curve model; (b) growth model with subject-associated variables; and (c) individual curve model with predictive variables. The results showed that awareness increased over time and that the variable 'schooling years' explained part of the between-subjects variation. The effect of motivational interviewing was also significant.

Entropy Analysis in Mixed Convection MHD flow of Nanofluid over a Non-linear Stretching Sheet

NASA Astrophysics Data System (ADS)

Matin, Meisam Habibi; Nobari, Mohammad Reza Heirani; Jahangiri, Pouyan

This article deals with a numerical study of entropy analysis in mixed convection MHD flow of nanofluid over a non-linear stretching sheet taking into account the effects of viscous dissipation and variable magnetic field. The nanofluid is made of such nano particles as SiO2 with pure water as a base fluid. To analyze the problem, at first the boundary layer equations are transformed into non-linear ordinary equations using a similarity transformation. The resultant equations are then solved numerically using the Keller-Box scheme based on the implicit finite-difference method. The effects of different non-dimensional governing parameters such as magnetic parameter, nanoparticles volume fraction, Nusselt, Richardson, Eckert, Hartman, Brinkman, Reynolds and entropy generation numbers are investigated in details. The results indicate that increasing the nano particles to the base fluids causes the reduction in shear forces and a decrease in stretching sheet heat transfer coefficient. Also, decreasing the magnetic parameter and increasing the Eckert number result in improves heat transfer rate. Furthermore, the surface acts as a strong source of irreversibility due to the higher entropy generation number near the surface.

Effect of a grain challenge on ruminal, urine, and fecal pH, apparent total-tract starch digestibility, and milk composition of Holstein and Jersey cows.

PubMed

Luan, S; Cowles, K; Murphy, M R; Cardoso, F C

2016-03-01

The effects of a grain challenge on ruminal, urine, and fecal pH, apparent total-tract starch digestibility, and milk composition were determined. Six Holstein cows, 6 rumen-cannulated Holstein cows, and 6 Jersey cows were used in a replicated 3 × 3 Latin square design balanced to measure carryover effects. Periods (10 d) were divided into 4 stages (S): S1, d 1 to 3, served as baseline with regular total mixed ration ad libitum; S2, d 4, served as restricted feeding, with cows offered 50% of the total mixed ration fed on S1 (dry matter basis); S3, d 5, a grain challenge was performed, in which cows were fed total mixed ration ad libitum and not fed (CON) or fed an addition of 10% (MG) or 20% (HG) pellet wheat-barley (1:1) top-dressed onto the total mixed ration, based on dry matter intake obtained in S1; S4, d 6 to 10, served as recovery stage with regular total mixed ration fed ad libitum. Overall, cows had a quadratic treatment effect for milk yield where CON (22.6 kg/d) and HG (23.5 kg/d) had lower milk yield than cows in MG (23.7 kg/d). Jersey cows had a quadratic treatment effect for dry matter intake where cows in CON (13.2 kg/d) and HG (12.4 kg/d) had lower dry matter intake than cows in MG (14 kg/d). Holstein cows had a linear treatment effect for dry matter intake (17.7, 18.4, and 18.6 kg/d for CON, MG, and HG, respectively). Rumen pH for the rumen-cannulated cows had a linear treatment effect (6.45, 6.35, and 6.24 for CON, MG, and HG, respectively). Cows in HG spent more time with rumen pH below 5.8 (4.33 h) than MG (2 h) or CON (2.17 h) as shown by the quadratic treatment effect. Holstein cows in HG (8.46) had lower urine pH than MG (8.51) or CON (8.54) as showed by the linear treatment effect for urine pH. Apparent total-tract starch digestibility had a tendency for a linear treatment effect on S3 (97.62 ± 1.5, 97.47 ± 1.5, and 91.84 ± 1.6%, for CON, MG, and HG, respectively). Fecal pH was associated with rumen pH depression as early as 15 h after feeding for Holstein cows. In conclusion, a grain challenge reduced urine pH in Holstein cows but not in Jersey cows. Holstein cows' health were not affected when rumen pH was depressed. A potentially useful link between rumen pH and systemic (urine) pH within 2 h after feeding was quantified in Holstein cows. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Multivariate statistical approach to estimate mixing proportions for unknown end members

USGS Publications Warehouse

Valder, Joshua F.; Long, Andrew J.; Davis, Arden D.; Kenner, Scott J.

2012-01-01

A multivariate statistical method is presented, which includes principal components analysis (PCA) and an end-member mixing model to estimate unknown end-member hydrochemical compositions and the relative mixing proportions of those end members in mixed waters. PCA, together with the Hotelling T2 statistic and a conceptual model of groundwater flow and mixing, was used in selecting samples that best approximate end members, which then were used as initial values in optimization of the end-member mixing model. This method was tested on controlled datasets (i.e., true values of estimates were known a priori) and found effective in estimating these end members and mixing proportions. The controlled datasets included synthetically generated hydrochemical data, synthetically generated mixing proportions, and laboratory analyses of sample mixtures, which were used in an evaluation of the effectiveness of this method for potential use in actual hydrological settings. For three different scenarios tested, correlation coefficients (R2) for linear regression between the estimated and known values ranged from 0.968 to 0.993 for mixing proportions and from 0.839 to 0.998 for end-member compositions. The method also was applied to field data from a study of end-member mixing in groundwater as a field example and partial method validation.

Effect of Liquid Surface Turbulent Motion on the Vapor Condensation in a Mixing Tank

NASA Technical Reports Server (NTRS)

Lin, C. S.; Hasan, M. M.

1991-01-01

The effect of liquid surface motion on the vapor condensation in a tank mixed by an axial turbulent jet is numerically investigated. The average value (over the interface area) of the root-mean-squared (rms) turbulent velocity at the interface is shown to be linearly increasing with decreasing liquid height and increasing jet diameter for a given tank size. The average rms turbulent velocity is incorporated in Brown et al. (1990) condensation correlation to predict the condensation of vapor on a liquid surface. The results are in good agreement with available condensation data.

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…

The Effects of Baseline Estimation on the Reliability, Validity, and Precision of CBM-R Growth Estimates

ERIC Educational Resources Information Center

Van Norman, Ethan R.; Christ, Theodore J.; Zopluoglu, Cengiz

2013-01-01

This study examined the effect of baseline estimation on the quality of trend estimates derived from Curriculum Based Measurement of Oral Reading (CBM-R) progress monitoring data. The authors used a linear mixed effects regression (LMER) model to simulate progress monitoring data for schedules ranging from 6-20 weeks for datasets with high and low…

Effect of Commercial Cyanobacteria Products on the Growth and Antagonistic Ability of Some Bioagents under Laboratory Conditions

PubMed Central

El-Mougy, Nehal S.; Abdel-Kader, Mokhtar M.

2013-01-01

Evaluation of the efficacy of blue-green algal compounds against the growth of either pathogenic or antagonistic microorganisms as well as their effect on the antagonistic ability of bioagents was studied under in vitro conditions. The present study was undertaken to explore the inhibitory effect of commercial algal compounds, Weed-Max and Oligo-Mix, against some soil-borne pathogens. In growth medium supplemented with these algal compounds, the linear growth of pathogenic fungi decreased by increasing tested concentrations of the two algal compounds. Complete reduction in pathogenic fungal growth was observed at 2% of both Weed-Max and Oligo-Mix. Gradual significant reduction in the pathogenic fungal growth was caused by the two bioagents and by increasing the concentrations of algal compounds Weed-Max and Oligo-Mix. The present work showed that commercial algal compounds, Weed-Max and Oligo-Mix, have potential for the suppression of soil-borne fungi and enhance the antagonistic ability of fungal, bacterial, and yeast bio-agents. PMID:24307948

Shear-flexible finite-element models of laminated composite plates and shells

NASA Technical Reports Server (NTRS)

Noor, A. K.; Mathers, M. D.

1975-01-01

Several finite-element models are applied to the linear static, stability, and vibration analysis of laminated composite plates and shells. The study is based on linear shallow-shell theory, with the effects of shear deformation, anisotropic material behavior, and bending-extensional coupling included. Both stiffness (displacement) and mixed finite-element models are considered. Discussion is focused on the effects of shear deformation and anisotropic material behavior on the accuracy and convergence of different finite-element models. Numerical studies are presented which show the effects of increasing the order of the approximating polynomials, adding internal degrees of freedom, and using derivatives of generalized displacements as nodal parameters.

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.

Enrichment of statistical power for genome-wide association studies

USDA-ARS?s Scientific Manuscript database

The inheritance of most human diseases and agriculturally important traits is controlled by many genes with small effects. Identifying these genes, while simultaneously controlling false positives, is challenging. Among available statistical methods, the mixed linear model (MLM) has been the most fl...

The Impact of Three Commonly Used Fungicides on Typhlodromus pyri (Acari: Phytoseiidae) in European Vineyards.

PubMed

Kemmitt, G; Valverde-Garcia, P; Hufnagl, A; Bacci, L; Zotz, A

2015-04-01

The impact of the fungicides mancozeb, myclobutanil, and meptyldinocap on populations of Typhlodromus pyri Scheuten was evaluated under field conditions, when applied following the good agricultural practices recommended for their use. Two complementary statistical models were used to analyze the population reduction compared to the control: a linear mixed model to estimate the mean effect of the fungicide, and a generalized linear mixed model (proportional odds mixed model) to estimate the cumulative probability for those effects being equal or less than a specific IOBC class (International Organization for Biological and Integrated Control of Noxious Animal and Plants). Findings from 27 field experiments in a range of different vine-growing regions in Europe indicated that the use of mancozeb, myclobutanil, and meptyldinocap caused minimal impact on naturally occurring populations of T. pyri. Both statistical models confirmed that although adverse effects on T. pyri can occur under certain conditions after several applications of any of the three fungicides studied, the probability of the effects occurring is low and they will not persist. These methods demonstrated how data from a series of trials could be used to evaluate the variability of the effects caused by the chemical rather than relying on the worst-case findings from a single trial. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Spatial Characteristics of Small Green Spaces' Mitigating Effects on Microscopic Urban Heat Islands

NASA Astrophysics Data System (ADS)

Park, J.; Lee, D. K.; Jeong, W.; Kim, J. H.; Huh, K. Y.

2015-12-01

The purpose of the study is to find small greens' disposition, types and sizes to reduce air temperature effectively in urban blocks. The research sites were six high developed blocks in Seoul, Korea. Air temperature was measured with mobile loggers in clear daytime during summer, from August to September, at screen level. Also the measurement repeated over three times a day during three days by walking and circulating around the experimental blocks and the control blocks at the same time. By analyzing spatial characteristics, the averaged air temperatures were classified with three spaces, sunny spaces, building-shaded spaces and small green spaces by using Kruskal-Wallis Test; and small green spaces in 6 blocks were classified into their outward forms, polygonal or linear and single or mixed. The polygonal and mixed types of small green spaces mitigated averaged air temperature of each block which they belonged with a simple linear regression model with adjusted R2 = 0.90**. As the area and volume of these types increased, the effect of air temperature reduction (ΔT; Air temperature difference between sunny space and green space in a block) also increased in a linear relationship. The experimental range of this research is 100m2 ~ 2,000m2 of area, and 1,000m3 ~ 10,000m3 of volume of small green space. As a result, more than 300m2 and 2,300m3 of polygonal green spaces with mixed vegetation is required to lower 1°C; 650m2 and 5,000m3 of them to lower 2°C; about 2,000m2 and about 10,000m3 of them to lower 4°C air temperature reduction in an urban block.

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.

Text-Based Recall and Extra-Textual Generations Resulting from Simplified and Authentic Texts

ERIC Educational Resources Information Center

Crossley, Scott A.; McNamara, Danielle S.

2016-01-01

This study uses a moving windows self-paced reading task to assess text comprehension of beginning and intermediate-level simplified texts and authentic texts by L2 learners engaged in a text-retelling task. Linear mixed effects (LME) models revealed statistically significant main effects for reading proficiency and text level on the number of…

Working Memory Effects in the L2 Processing of Ambiguous Relative Clauses

ERIC Educational Resources Information Center

Hopp, Holger

2014-01-01

This article investigates whether and how L2 sentence processing is affected by memory constraints that force serial parsing. Monitoring eye movements, we test effects of working memory on L2 relative-clause attachment preferences in a sample of 75 late-adult German learners of English and 25 native English controls. Mixed linear regression…

Differences in Osteoarthritis Self-Management Support Intervention Outcomes According to Race and Health Literacy

ERIC Educational Resources Information Center

Sperber, Nina R.; Bosworth, Hayden B.; Coffman, Cynthia J.; Lindquist, Jennifer H.; Oddone, Eugene Z.; Weinberger, Morris; Allen, Kelli D.

2013-01-01

We explored whether the effects of a telephone-based osteoarthritis (OA) self-management support intervention differed by race and health literacy. Participants included 515 veterans with hip and/or knee OA. Linear mixed models assessed differential effects of the intervention compared with health education (HE) and usual care (UC) on pain…

The Effects of Semantic Transparency and Base Frequency on the Recognition of English Complex Words

ERIC Educational Resources Information Center

Xu, Joe; Taft, Marcus

2015-01-01

A visual lexical decision task was used to examine the interaction between base frequency (i.e., the cumulative frequencies of morphologically related forms) and semantic transparency for a list of derived words. Linear mixed effects models revealed that high base frequency facilitates the recognition of the complex word (i.e., a "base…

Neurodevelopment in Early Childhood Affected by Prenatal Lead Exposure and Iron Intake.

PubMed

Shah-Kulkarni, Surabhi; Ha, Mina; Kim, Byung-Mi; Kim, Eunjeong; Hong, Yun-Chul; Park, Hyesook; Kim, Yangho; Kim, Bung-Nyun; Chang, Namsoo; Oh, Se-Young; Kim, Young Ju; Kimʼs, Young Ju; Lee, Boeun; Ha, Eun-Hee

2016-01-01

No safe threshold level of lead exposure in children has been recognized. Also, the information on shielding effect of maternal dietary iron intake during pregnancy on the adverse effects of prenatal lead exposure on children's postnatal neurocognitive development is very limited. We examined the association of prenatal lead exposure and neurodevelopment in children at 6, 12, 24, and 36 months and the protective action of maternal dietary iron intake against the impact of lead exposure. The study participants comprise 965 pregnant women and their subsequent offspring of the total participants enrolled in the Mothers and Children's environmental health study: a prospective birth cohort study. Generalized linear model and linear mixed model analysis were performed to analyze the effect of prenatal lead exposure and mother's dietary iron intake on children's cognitive development at 6, 12, 24, and 36 months. Maternal late pregnancy lead was marginally associated with deficits in mental development index (MDI) of children at 6 months. Mothers having less than 75th percentile of dietary iron intake during pregnancy showed significant increase in the harmful effect of late pregnancy lead exposure on MDI at 6 months. Linear mixed model analyses showed the significant detrimental effect of prenatal lead exposure in late pregnancy on cognitive development up to 36 months in children of mothers having less dietary iron intake during pregnancy. Thus, our findings imply importance to reduce prenatal lead exposure and have adequate iron intake for better neurodevelopment in children.

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.

Neurodevelopment in Early Childhood Affected by Prenatal Lead Exposure and Iron Intake

PubMed Central

Shah-Kulkarni, Surabhi; Ha, Mina; Kim, Byung-Mi; Kim, Eunjeong; Hong, Yun-Chul; Park, Hyesook; Kim, Yangho; Kim, Bung-Nyun; Chang, Namsoo; Oh, Se-Young; Kim, Young Ju; Lee, Boeun; Ha, Eun-Hee

2016-01-01

Abstract No safe threshold level of lead exposure in children has been recognized. Also, the information on shielding effect of maternal dietary iron intake during pregnancy on the adverse effects of prenatal lead exposure on children's postnatal neurocognitive development is very limited. We examined the association of prenatal lead exposure and neurodevelopment in children at 6, 12, 24, and 36 months and the protective action of maternal dietary iron intake against the impact of lead exposure. The study participants comprise 965 pregnant women and their subsequent offspring of the total participants enrolled in the Mothers and Children's environmental health study: a prospective birth cohort study. Generalized linear model and linear mixed model analysis were performed to analyze the effect of prenatal lead exposure and mother's dietary iron intake on children's cognitive development at 6, 12, 24, and 36 months. Maternal late pregnancy lead was marginally associated with deficits in mental development index (MDI) of children at 6 months. Mothers having less than 75th percentile of dietary iron intake during pregnancy showed significant increase in the harmful effect of late pregnancy lead exposure on MDI at 6 months. Linear mixed model analyses showed the significant detrimental effect of prenatal lead exposure in late pregnancy on cognitive development up to 36 months in children of mothers having less dietary iron intake during pregnancy. Thus, our findings imply importance to reduce prenatal lead exposure and have adequate iron intake for better neurodevelopment in children. PMID:26825887

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.

Photon-Z mixing the Weinberg-Salam model: Effective charges and the a = -3 gauge

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

Baulieu, L.; Coquereaux, R.

1982-04-15

We study some properties of the Weinberg-Salam model connected with the photon-Z mixing. We solve the linear Dyson-Schwinger equations between full and 1PI boson propagators. The task is made easier, by the two-point function Ward identities that we derive to all orders and in any gauge. Some aspects of the renormalization of the model are also discussed. We display the exact mass-dependent one-loop two-point functions involving the photon and Z field in any linear xi-gauge. The special gauge a = xi/sup -1/ = -3 is shown to play a peculiar role. In this gauge, the Z field is multiplicatively renormalizablemore » (at the one-loop level), and one can construct both electric and weak effective charges of the theory from the photon and Z propagators, with a very simple expression similar to that of the QED Petermann, Stueckelberg, Gell-Mann and Low charge.« less

Does Marriage Moderate Genetic Effects on Delinquency and Violence?

PubMed Central

Li, Yi; Liu, Hexuan; Guo, Guang

2015-01-01

Using data from the National Longitudinal Study of Adolescent to Adult Health (N = 1,254), the authors investigated whether marriage can foster desistance from delinquency and violence by moderating genetic effects. In contrast to existing gene–environment research that typically focuses on one or a few genetic polymorphisms, they extended a recently developed mixed linear model to consider the collective influence of 580 single nucleotide polymorphisms in 64 genes related to aggression and risky behavior. The mixed linear model estimates the proportion of variance in the phenotype that is explained by the single nucleotide polymorphisms. The authors found that the proportion of variance in delinquency/violence explained was smaller among married individuals than unmarried individuals. Because selection, confounding, and heterogeneity may bias the estimate of the Gene × Marriage interaction, they conducted a series of analyses to address these issues. The findings suggest that the Gene × Marriage interaction results were not seriously affected by these issues. PMID:26549892

Non-linear mixed effects modeling - from methodology and software development to driving implementation in drug development science.

PubMed

Pillai, Goonaseelan Colin; Mentré, France; Steimer, Jean-Louis

2005-04-01

Few scientific contributions have made significant impact unless there was a champion who had the vision to see the potential for its use in seemingly disparate areas-and who then drove active implementation. In this paper, we present a historical summary of the development of non-linear mixed effects (NLME) modeling up to the more recent extensions of this statistical methodology. The paper places strong emphasis on the pivotal role played by Lewis B. Sheiner (1940-2004), who used this statistical methodology to elucidate solutions to real problems identified in clinical practice and in medical research and on how he drove implementation of the proposed solutions. A succinct overview of the evolution of the NLME modeling methodology is presented as well as ideas on how its expansion helped to provide guidance for a more scientific view of (model-based) drug development that reduces empiricism in favor of critical quantitative thinking and decision making.

Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials.

PubMed

Chen, Yong; Luo, Sheng; Chu, Haitao; Wei, Peng

2013-05-01

Multivariate meta-analysis is useful in combining evidence from independent studies which involve several comparisons among groups based on a single outcome. For binary outcomes, the commonly used statistical models for multivariate meta-analysis are multivariate generalized linear mixed effects models which assume risks, after some transformation, follow a multivariate normal distribution with possible correlations. In this article, we consider an alternative model for multivariate meta-analysis where the risks are modeled by the multivariate beta distribution proposed by Sarmanov (1966). This model have several attractive features compared to the conventional multivariate generalized linear mixed effects models, including simplicity of likelihood function, no need to specify a link function, and has a closed-form expression of distribution functions for study-specific risk differences. We investigate the finite sample performance of this model by simulation studies and illustrate its use with an application to multivariate meta-analysis of adverse events of tricyclic antidepressants treatment in clinical trials.

A mixed-effects model approach for the statistical analysis of vocal fold viscoelastic shear properties.

PubMed

Xu, Chet C; Chan, Roger W; Sun, Han; Zhan, Xiaowei

2017-11-01

A mixed-effects model approach was introduced in this study for the statistical analysis of rheological data of vocal fold tissues, in order to account for the data correlation caused by multiple measurements of each tissue sample across the test frequency range. Such data correlation had often been overlooked in previous studies in the past decades. The viscoelastic shear properties of the vocal fold lamina propria of two commonly used laryngeal research animal species (i.e. rabbit, porcine) were measured by a linear, controlled-strain simple-shear rheometer. Along with published canine and human rheological data, the vocal fold viscoelastic shear moduli of these animal species were compared to those of human over a frequency range of 1-250Hz using the mixed-effects models. Our results indicated that tissues of the rabbit, canine and porcine vocal fold lamina propria were significantly stiffer and more viscous than those of human. Mixed-effects models were shown to be able to more accurately analyze rheological data generated from repeated measurements. Copyright © 2017 Elsevier Ltd. All rights reserved.

Polymeric Materials for Electro-Optic Testing.

DTIC Science & Technology

1987-07-01

what Langmuir Blodgett films are, how they are grown and deposited on a material, and the electro - optic effects in Langmuir/Blodgett films. Stephen...Kowel has experimented with several different types of organic dyes mixed in the films to increase the electro - optic effect in the films. The bulk of his...test integrated circuits. Keywords: Langmuir Blodgett films, Electro - optic testing, Integrated circuits, Linear electro - optic effect.

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.)…

Jahn-Teller effect in molecular electronics: quantum cellular automata

NASA Astrophysics Data System (ADS)

Tsukerblat, B.; Palii, A.; Clemente-Juan, J. M.; Coronado, E.

2017-05-01

The article summarizes the main results of application of the theory of the Jahn-Teller (JT) and pseudo JT effects to the description of molecular quantum dot cellular automata (QCA), a new paradigm of quantum computing. The following issues are discussed: 1) QCA as a new paradigm of quantum computing, principles and advantages; 2) molecular implementation of QCA; 3) role of the JT effect in charge trapping, encoding of binary information in the quantum cell and non-linear cell-cell response; 4) spin-switching in molecular QCA based on mixed-valence cell; 5) intervalence optical absorption in tetrameric molecular mixed-valence cell through the symmetry assisted approach to the multimode/multilevel JT and pseudo JT problems.

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.

Robust outer synchronization between two nonlinear complex networks with parametric disturbances and mixed time-varying delays

NASA Astrophysics Data System (ADS)

Zhang, Chuan; Wang, Xingyuan; Luo, Chao; Li, Junqiu; Wang, Chunpeng

2018-03-01

In this paper, we focus on the robust outer synchronization problem between two nonlinear complex networks with parametric disturbances and mixed time-varying delays. Firstly, a general complex network model is proposed. Besides the nonlinear couplings, the network model in this paper can possess parametric disturbances, internal time-varying delay, discrete time-varying delay and distributed time-varying delay. Then, according to the robust control strategy, linear matrix inequality and Lyapunov stability theory, several outer synchronization protocols are strictly derived. Simple linear matrix controllers are designed to driver the response network synchronize to the drive network. Additionally, our results can be applied on the complex networks without parametric disturbances. Finally, by utilizing the delayed Lorenz chaotic system as the dynamics of all nodes, simulation examples are given to demonstrate the effectiveness of our theoretical results.

An adiabatic linearized path integral approach for quantum time-correlation functions II: a cumulant expansion method for improving convergence.

PubMed

Causo, Maria Serena; Ciccotti, Giovanni; Bonella, Sara; Vuilleumier, Rodolphe

2006-08-17

Linearized mixed quantum-classical simulations are a promising approach for calculating time-correlation functions. At the moment, however, they suffer from some numerical problems that may compromise their efficiency and reliability in applications to realistic condensed-phase systems. In this paper, we present a method that improves upon the convergence properties of the standard algorithm for linearized calculations by implementing a cumulant expansion of the relevant averages. The effectiveness of the new approach is tested by applying it to the challenging computation of the diffusion of an excess electron in a metal-molten salt solution.

Composition and structure of Pinus koraiensis mixed forest respond to spatial climatic changes.

PubMed

Zhang, Jingli; Zhou, Yong; Zhou, Guangsheng; Xiao, Chunwang

2014-01-01

Although some studies have indicated that climate changes can affect Pinus koraiensis mixed forest, the responses of composition and structure of Pinus koraiensis mixed forests to climatic changes are unknown and the key climatic factors controlling the composition and structure of Pinus koraiensis mixed forest are uncertain. Field survey was conducted in the natural Pinus koraiensis mixed forests along a latitudinal gradient and an elevational gradient in Northeast China. In order to build the mathematical models for simulating the relationships of compositional and structural attributes of the Pinus koraiensis mixed forest with climatic and non-climatic factors, stepwise linear regression analyses were performed, incorporating 14 dependent variables and the linear and quadratic components of 9 factors. All the selected new models were computed under the +2°C and +10% precipitation and +4°C and +10% precipitation scenarios. The Max Temperature of Warmest Month, Mean Temperature of Warmest Quarter and Precipitation of Wettest Month were observed to be key climatic factors controlling the stand densities and total basal areas of Pinus koraiensis mixed forest. Increased summer temperatures and precipitations strongly enhanced the stand densities and total basal areas of broadleaf trees but had little effect on Pinus koraiensis under the +2°C and +10% precipitation scenario and +4°C and +10% precipitation scenario. These results show that the Max Temperature of Warmest Month, Mean Temperature of Warmest Quarter and Precipitation of Wettest Month are key climatic factors which shape the composition and structure of Pinus koraiensis mixed forest. Although the Pinus koraiensis would persist, the current forests dominated by Pinus koraiensis in the region would all shift and become broadleaf-dominated forests due to the dramatic increase of broadleaf trees under the future global warming and increased precipitation.

Pre-natal exposures to cocaine and alcohol and physical growth patterns to age 8 years

PubMed Central

Lumeng, Julie C.; Cabral, Howard J.; Gannon, Katherine; Heeren, Timothy; Frank, Deborah A.

2007-01-01

Two hundred and two primarily African American/Caribbean children (classified by maternal report and infant meconium as 38 heavier, 74 lighter and 89 not cocaine-exposed) were measured repeatedly from birth to age 8 years to assess whether there is an independent effect of prenatal cocaine exposure on physical growth patterns. Children with fetal alcohol syndrome identifiable at birth were excluded. At birth, cocaine and alcohol exposures were significantly and independently associated with lower weight, length and head circumference in cross-sectional multiple regression analyses. The relationship over time of pre-natal exposures to weight, height, and head circumference was then examined by multiple linear regression using mixed linear models including covariates: child’s gestational age, gender, ethnicity, age at assessment, current caregiver, birth mother’s use of alcohol, marijuana and tobacco during the pregnancy and pre-pregnancy weight (for child’s weight) and height (for child’s height and head circumference). The cocaine effects did not persist beyond infancy in piecewise linear mixed models, but a significant and independent negative effect of pre-natal alcohol exposure persisted for weight, height, and head circumference. Catch-up growth in cocaine-exposed infants occurred primarily by 6 months of age for all growth parameters, with some small fluctuations in growth rates in the preschool age range but no detectable differences between heavier versus unexposed nor lighter versus unexposed thereafter. PMID:17412558

Effect of hypolimnetic oxygenation on oxygen depletion rates in two water-supply reservoirs.

PubMed

Gantzer, Paul A; Bryant, Lee D; Little, John C

2009-04-01

Oxygenation systems, such as bubble-plume diffusers, are used to improve water quality by replenishing dissolved oxygen (DO) in the hypolimnia of water-supply reservoirs. The diffusers induce circulation and mixing, which helps distribute DO throughout the hypolimnion. Mixing, however, has also been observed to increase hypolimnetic oxygen demand (HOD) during system operation, thus accelerating oxygen depletion. Two water-supply reservoirs (Spring Hollow Reservoir (SHR) and Carvins Cove Reservoir (CCR)) that employ linear bubble-plume diffusers were studied to quantify diffuser effects on HOD. A recently validated plume model was used to predict oxygen addition rates. The results were used together with observed oxygen accumulation rates to evaluate HOD over a wide range of applied gas flow rates. Plume-induced mixing correlated well with applied gas flow rate and was observed to increase HOD. Linear relationships between applied gas flow rate and HOD were found for both SHR and CCR. HOD was also observed to be independent of bulk hypolimnion oxygen concentration, indicating that HOD is controlled by induced mixing. Despite transient increases in HOD, oxygenation caused an overall decrease in background HOD, as well as a decrease in induced HOD during diffuser operation, over several years. This suggests that the residual or background oxygen demand decreases from one year to the next. Despite diffuser-induced increases in HOD, hypolimnetic oxygenation remains a viable method for replenishing DO in thermally-stratified water-supply reservoirs such as SHR and CCR.

Non-linear mixing effects on mass-47 CO2 clumped isotope thermometry: Patterns and implications.

PubMed

Defliese, William F; Lohmann, Kyger C

2015-05-15

Mass-47 CO(2) clumped isotope thermometry requires relatively large (~20 mg) samples of carbonate minerals due to detection limits and shot noise in gas source isotope ratio mass spectrometry (IRMS). However, it is unreasonable to assume that natural geologic materials are homogenous on the scale required for sampling. We show that sample heterogeneities can cause offsets from equilibrium Δ(47) values that are controlled solely by end member mixing and are independent of equilibrium temperatures. A numerical model was built to simulate and quantify the effects of end member mixing on Δ(47). The model was run in multiple possible configurations to produce a dataset of mixing effects. We verified that the model accurately simulated real phenomena by comparing two artificial laboratory mixtures measured using IRMS to model output. Mixing effects were found to be dependent on end member isotopic composition in δ(13)C and δ(18)O values, and independent of end member Δ(47) values. Both positive and negative offsets from equilibrium Δ(47) can occur, and the sign is dependent on the interaction between end member isotopic compositions. The overall magnitude of mixing offsets is controlled by the amount of variability within a sample; the larger the disparity between end member compositions, the larger the mixing offset. Samples varying by less than 2 ‰ in both δ(13)C and δ(18)O values have mixing offsets below current IRMS detection limits. We recommend the use of isotopic subsampling for δ(13)C and δ(18)O values to determine sample heterogeneity, and to evaluate any potential mixing effects in samples suspected of being heterogonous. Copyright © 2015 John Wiley & Sons, Ltd.

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.

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.

Mutual Exclusion of Urea and Trimethylamine N-oxide from Amino Acids in Mixed Solvent Environment

NASA Astrophysics Data System (ADS)

Ganguly, Pritam; Hajari, Timir; Shea, Joan-Emma; van der Vegt, Nico F. A.

2015-03-01

We study the solvation thermodynamics of individual amino acids in mixed urea and trimethylamine N-oxide (TMAO) solutions using molecular dynamics simulations and the Kirkwood-Buff theory. Our results on the preferential interactions between the amino acids and the cosolvents (urea and TMAO) show a mutual exclusion of both the cosolvents from the amino acid surface in the mixed cosolvent condition which is followed by an increase in the cosolvent-cosolvent aggregation away from the amino acid surface. The effects of the mixed cosolvents on the association of the amino acids and the preferential solvation of the amino acids by water are found to be highly non-linear in terms of the effects of the individual cosolvents. A similar result has been found for the association of the protein backbone, mimicked by triglycine. Our results have been confirmed by different TMAO force-fields and the mutual exclusions of the cosolvents from the amino acids are found to be independent of the choice of the strength of the TMAO-water interactions. Based on our data, a general mechanism can potentially be proposed for the effects of the mixed cosolvents on the preferential solvations of the solutes including the case of cononsolvency.

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...

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.

Obstetric and Parental Psychiatric Variables as Potential Predictors of Autism Severity

ERIC Educational Resources Information Center

Wallace, Anna E.; Anderson, George M.; Dubrow, Robert

2008-01-01

Associations between obstetric and parental psychiatric variables and subjects' Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule (ADOS) domain scores were examined using linear mixed effects models. Data for the 228 families studied were provided by the Autism Genetic Resource Exchange. Hypertension (P =…

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.

Additive effects of word frequency and stimulus quality: the influence of trial history and data transformations.

PubMed

Balota, David A; Aschenbrenner, Andrew J; Yap, Melvin J

2013-09-01

A counterintuitive and theoretically important pattern of results in the visual word recognition literature is that both word frequency and stimulus quality produce large but additive effects in lexical decision performance. The additive nature of these effects has recently been called into question by Masson and Kliegl (in press), who used linear mixed effects modeling to provide evidence that the additive effects were actually being driven by previous trial history. Because Masson and Kliegl also included semantic priming as a factor in their study and recent evidence has shown that semantic priming can moderate the additivity of word frequency and stimulus quality (Scaltritti, Balota, & Peressotti, 2012), we reanalyzed data from 3 published studies to determine if previous trial history moderated the additive pattern when semantic priming was not also manipulated. The results indicated that previous trial history did not influence the joint influence of word frequency and stimulus quality. More important, and independent of Masson and Kliegl's conclusions, we also show how a common transformation used in linear mixed effects analyses to normalize the residuals can systematically alter the way in which two variables combine to influence performance. Specifically, using transformed, rather than raw reaction times, consistently produces more underadditive patterns. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Rapid-mix and chemical quench studies of ferredoxin-reduced stearoyl-acyl carrier protein desaturase.

PubMed

Lyle, Karen S; Haas, Jeffrey A; Fox, Brian G

2003-05-20

Stearoyl-ACP Delta9 desaturase (Delta9D) catalyzes the NADPH- and O(2)-dependent insertion of a cis double bond between the C9 and C10 positions of stearoyl-ACP (18:0-ACP) to produce oleoyl-ACP (18:1-ACP). This work revealed the ability of reduced [2Fe-2S] ferredoxin (Fd) to act as a catalytically competent electron donor during the rapid conversion of 18:0-ACP into 18:1-ACP. Experiments on the order of addition for substrate and reduced Fd showed high conversion of 18:0-ACP to 18:1-ACP (approximately 95% per Delta9D active site in a single turnover) when 18:0-ACP was added prior to reduced Fd. Reactions of the prereduced enzyme-substrate complex with O(2) and the oxidized enzyme-substrate complex with reduced Fd were studied by rapid-mix and chemical quench methods. For reaction of the prereduced enzyme-substrate complex, an exponential burst phase (k(burst) = 95 s(-1)) of product formation accounted for approximately 90% of the turnover expected for one subunit in the dimeric protein. This rapid phase was followed by a slower phase (k(linear) = 4.0 s(-1)) of product formation corresponding to the turnover expected from the second subunit. For reaction of the oxidized enzyme-substrate complex with excess reduced Fd, a slower, linear rate (k(obsd) = 3.4 s(-1)) of product formation was observed over approximately 1.5 turnovers per Delta9D active site potentially corresponding to a third phase of reaction. An analysis of the deuterium isotope effect on the two rapid-mix reaction sequences revealed only a modest effect on k(burst) ((D)k(burst) approximately 1.5) and k(linear) (D)k(linear) approximately 1.4), indicating C-H bond cleavage does not contribute significantly to the rate-limiting steps of pre-steady-state catalysis. These results were used to assemble and evaluate a minimal kinetic model for Delta9D catalysis.

Asymptotic solution of the turbulent mixing layer for velocity ratio close to unity

NASA Technical Reports Server (NTRS)

Higuera, F. J.; Jimenez, J.; Linan, A.

1996-01-01

The equations describing the first two terms of an asymptotic expansion of the solution of the planar turbulent mixing layer for values of the velocity ratio close to one are obtained. The first term of this expansion is the solution of the well-known time-evolving problem and the second, which includes the effects of the increase of the turbulence scales in the stream-wise direction, obeys a linear system of equations. Numerical solutions of these equations for a two-dimensional reacting mixing layer show that the correction to the time-evolving solution may explain the asymmetry of the entrainment and the differences in product generation observed in flip experiments.

Stability of viscosity stratified flows down an incline: Role of miscibility and wall slip

NASA Astrophysics Data System (ADS)

Ghosh, Sukhendu; Usha, R.

2016-10-01

The effects of wall velocity slip on the linear stability of a gravity-driven miscible two-fluid flow down an incline are examined. The fluids have the matched density but different viscosity. A smooth viscosity stratification is achieved due to the presence of a thin mixed layer between the fluids. The results show that the presence of slip exhibits a promise for stabilizing the miscible flow system by raising the critical Reynolds number at the onset and decreasing the bandwidth of unstable wave numbers beyond the threshold of the dominant instability. This is different from its role in the case of a single fluid down a slippery substrate where slip destabilizes the flow system at the onset. Though the stability properties are analogous to the same flow system down a rigid substrate, slip is shown to delay the surface mode instability for any viscosity contrast. It has a damping/promoting effect on the overlap modes (which exist due to the overlap of critical layer of dominant disturbance with the mixed layer) when the mixed layer is away/close from/to the slippery inclined wall. The trend of slip effect is influenced by the location of the mixed layer, the location of more viscous fluid, and the mass diffusivity of the two fluids. The stabilizing characteristics of slip can be favourably used to suppress the non-linear breakdown which may happen due to the coexistence of the unstable modes in a flow over a substrate with no slip. The results of the present study suggest that it is desirable to design a slippery surface with appropriate slip sensitivity in order to meet a particular need for a specific application.

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…

Non-linear effects of the built environment on automobile-involved pedestrian crash frequency: A machine learning approach.

PubMed

Ding, Chuan; Chen, Peng; Jiao, Junfeng

2018-03-01

Although a growing body of literature focuses on the relationship between the built environment and pedestrian crashes, limited evidence is provided about the relative importance of many built environment attributes by accounting for their mutual interaction effects and their non-linear effects on automobile-involved pedestrian crashes. This study adopts the approach of Multiple Additive Poisson Regression Trees (MAPRT) to fill such gaps using pedestrian collision data collected from Seattle, Washington. Traffic analysis zones are chosen as the analytical unit. The effects of various factors on pedestrian crash frequency investigated include characteristics the of road network, street elements, land use patterns, and traffic demand. Density and the degree of mixed land use have major effects on pedestrian crash frequency, accounting for approximately 66% of the effects in total. More importantly, some factors show clear non-linear relationships with pedestrian crash frequency, challenging the linearity assumption commonly used in existing studies which employ statistical models. With various accurately identified non-linear relationships between the built environment and pedestrian crashes, this study suggests local agencies to adopt geo-spatial differentiated policies to establish a safe walking environment. These findings, especially the effective ranges of the built environment, provide evidence to support for transport and land use planning, policy recommendations, and road safety programs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Efficient non-linear two-photon effects from the Cesium 6D manifold

NASA Astrophysics Data System (ADS)

Haluska, Nathan D.; Perram, Glen P.; Rice, Christopher A.

2018-02-01

We report several non-linear process that occur when two-photon pumping the cesium 6D states. Cesium vapor possess some of the largest two-photon pump cross sections in nature. Pumping these cross sections leads to strong amplified spontaneous emission that we observe on over 17 lasing lines. These new fields are strong enough to couple with the pump to create additional tunable lines. We use a heat pipe with cesium densities of 1014 to 1016 cm-3 and 0 to 5 Torr of helium buffer gas. The cesium 6D States are interrogated by both high energy pulses and low power CW sources. We observe four-wave mixing, six-wave mixing, potential two-photon lasing, other unknown nonlinear processes, and the persistence of some processes at low thresholds. This system is also uniquely qualified to support two-photon lasing under the proper conditions.

Finite-time mixed outer synchronization of complex networks with coupling time-varying delay.

PubMed

He, Ping; Ma, Shu-Hua; Fan, Tao

2012-12-01

This article is concerned with the problem of finite-time mixed outer synchronization (FMOS) of complex networks with coupling time-varying delay. FMOS is a recently developed generalized synchronization concept, i.e., in which different state variables of the corresponding nodes can evolve into finite-time complete synchronization, finite-time anti-synchronization, and even amplitude finite-time death simultaneously for an appropriate choice of the controller gain matrix. Some novel stability criteria for the synchronization between drive and response complex networks with coupling time-varying delay are derived using the Lyapunov stability theory and linear matrix inequalities. And a simple linear state feedback synchronization controller is designed as a result. Numerical simulations for two coupled networks of modified Chua's circuits are then provided to demonstrate the effectiveness and feasibility of the proposed complex networks control and synchronization schemes and then compared with the proposed results and the previous schemes for accuracy.

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.

Intra- and inter-shell Kondo effects in carbon nanotube quantum dots

NASA Astrophysics Data System (ADS)

Krychowski, Damian; Lipiński, Stanisław

2018-01-01

The linear response transport properties of carbon nanotube quantum dot in the strongly correlated regime are discussed. The finite-U mean field slave boson approach is used to study many-body effects. Magnetic field can rebuilt Kondo correlations, which are destroyed by the effect of spin-orbit interaction or valley mixing. Apart from the field induced revivals of SU(2) Kondo effects of different types: spin, valley or spin-valley, also more exotic phenomena appear, such as SU(3) Kondo effect. Threefold degeneracy occurs due to the effective intervalley exchange induced by short-range part of Coulomb interaction or due to the intershell mixing. In narrow gap nanotubes the full spin-orbital degeneracy might be recovered in the absence of magnetic field opening the condition for a formation of SU(4) Kondo resonance.

Neural Population Coding of Multiple Stimuli

PubMed Central

Ma, Wei Ji

2015-01-01

In natural scenes, objects generally appear together with other objects. Yet, theoretical studies of neural population coding typically focus on the encoding of single objects in isolation. Experimental studies suggest that neural responses to multiple objects are well described by linear or nonlinear combinations of the responses to constituent objects, a phenomenon we call stimulus mixing. Here, we present a theoretical analysis of the consequences of common forms of stimulus mixing observed in cortical responses. We show that some of these mixing rules can severely compromise the brain's ability to decode the individual objects. This cost is usually greater than the cost incurred by even large reductions in the gain or large increases in neural variability, explaining why the benefits of attention can be understood primarily in terms of a stimulus selection, or demixing, mechanism rather than purely as a gain increase or noise reduction mechanism. The cost of stimulus mixing becomes even higher when the number of encoded objects increases, suggesting a novel mechanism that might contribute to set size effects observed in myriad psychophysical tasks. We further show that a specific form of neural correlation and heterogeneity in stimulus mixing among the neurons can partially alleviate the harmful effects of stimulus mixing. Finally, we derive simple conditions that must be satisfied for unharmful mixing of stimuli. PMID:25740513

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.

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.

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.

Quantifying residual, eddy, and mean flow effects on mixing in an idealized circumpolar current

DOE PAGES

Wolfram, Phillip J.; Ringler, Todd D.

2017-07-13

Meridional diffusivity is assessed in this paper for a baroclinically unstable jet in a high-latitudeIdealized Circumpolar Current (ICC) using the Model for Prediction Across Scales-Ocean (MPAS-O) and the online Lagrangian In-situ Global High-performance particle Tracking (LIGHT) diagnostic via space-time dispersion of particle clusters over 120 monthly realizations of O(10 6) particles on 11 potential density surfaces. Diffusivity in the jet reaches values of O(6000 m 2 s -1) and is largest near the critical layer supporting mixing suppression and critical layer theory. Values in the vicinity of the shelf break are suppressed to O(100 m 2 s -1) due tomore » the presence of westward slope front currents. Diffusivity attenuates less rapidly with depth in the jet than both eddy velocity and kinetic energy scalings would suggest. Removal of the mean flow via high-pass filtering shifts the nonlinear parameter (ratio of the eddy velocity to eddy phase speed) into the linear wave regime by increasing the eddy phase speed via the depth-mean flow. Low-pass filtering, in contrast, quantifies the effect of mean shear. Diffusivity is decomposed into mean flow shear, linear waves, and the residual nonhomogeneous turbulence components, where turbulence dominates and eddy-produced filamentation strained by background mean shear enhances mixing, accounting for ≥ 80% of the total diffusivity relative to mean shear [O(100 m 2 s -1)], linear waves [O(1000 m 2 s -1)], and undecomposed full diffusivity [O(6000 m 2 s -1)]. Finally, diffusivity parameterizations accounting for both the nonhomogeneous turbulence residual and depth variability are needed.« less

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.

Robust high-precision attitude control for flexible spacecraft with improved mixed H2/H∞ control strategy under poles assignment constraint

NASA Astrophysics Data System (ADS)

Liu, Chuang; Ye, Dong; Shi, Keke; Sun, Zhaowei

2017-07-01

A novel improved mixed H2/H∞ control technique combined with poles assignment theory is presented to achieve attitude stabilization and vibration suppression simultaneously for flexible spacecraft in this paper. The flexible spacecraft dynamics system is described and transformed into corresponding state space form. Based on linear matrix inequalities (LMIs) scheme and poles assignment theory, the improved mixed H2/H∞ controller does not restrict the equivalence of the two Lyapunov variables involved in H2 and H∞ performance, which can reduce conservatives compared with traditional mixed H2/H∞ controller. Moreover, it can eliminate the coupling of Lyapunov matrix variables and system matrices by introducing slack variable that provides additional degree of freedom. Several simulations are performed to demonstrate the effectiveness and feasibility of the proposed method in this paper.

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.

Longitudinal Models of Reading Achievement of Students with Learning Disabilities and without Disabilities

ERIC Educational Resources Information Center

Sullivan, Amanda L.; Kohli, Nidhi; Farnsworth, Elyse M.; Sadeh, Shanna; Jones, Leila

2017-01-01

Objective: Accurate estimation of developmental trajectories can inform instruction and intervention. We compared the fit of linear, quadratic, and piecewise mixed-effects models of reading development among students with learning disabilities relative to their typically developing peers. Method: We drew an analytic sample of 1,990 students from…

Assessing the Impact of Community Marriage Policies on County Divorce Rates

ERIC Educational Resources Information Center

Birch, Paul James; Weed, Stan E.; Olsen, Joseph

2004-01-01

Community marriage initiatives (CMIs) are designed to strengthen marriage and increase marital stability by addressing relevant laws, policies, and cultural factors. We examined a specific CMI designed to lower divorce rates by establishing a shared public commitment among clergy to strengthen marriage. A mixed-effects general linear model was…

Patient turnover and nursing employment in Massachusetts hospitals before and after health insurance reform: implications for the Patient Protection and Affordable Care Act.

PubMed

Shindul-Rothschild, Judith; Gregas, Matt

2013-01-01

The Affordable Care Act is modeled after Massachusetts insurance reforms enacted in 2006. A linear mixed effect model examined trends in patient turnover and nurse employment in Massachusetts, New York, and California nonfederal hospitals from 2000 to 2011. The linear mixed effect analysis found that the rate of increase in hospital admissions was significantly higher in Massachusetts hospitals (p<.001) than that in California and New York (p=.007). The rate of change in registered nurses full-time equivalent hours per patient day was significantly less (p=.02) in Massachusetts than that in California and was not different from zero. The rate of change in admissions to registered nurses full-time equivalent hours per patient day was significantly greater in Massachusetts than California (p=.001) and New York (p<.01). Nurse staffing remained flat in Massachusetts, despite a significant increase in hospital admissions. The implications of the findings for nurse employment and hospital utilization following the implementation of national health insurance reform are discussed.

Effects of hydrokinetic turbine sound on the behavior of four species of fish within an experimental mesocosm

DOE PAGES

Schramm, Michael P.; Bevelhimer, Mark; Scherelis, Constantin

2017-02-04

The development of hydrokinetic energy technologies (e.g., tidal turbines) has raised concern over the potential impacts of underwater sound produced by hydrokinetic turbines on fish species likely to encounter these turbines. To assess the potential for behavioral impacts, we exposed four species of fish to varying intensities of recorded hydrokinetic turbine sound in a semi-natural environment. Although we tested freshwater species (redhorse suckers [Moxostoma spp], freshwater drum [Aplondinotus grunniens], largemouth bass [Micropterus salmoides], and rainbow trout [Oncorhynchus mykiss]), these species are also representative of the hearing physiology and sensitivity of estuarine species that would be affected at tidal energy sites.more » Here, we evaluated changes in fish position relative to different intensities of turbine sound as well as trends in location over time with linear mixed-effects and generalized additive mixed models. We also evaluated changes in the proportion of near-source detections relative to sound intensity and exposure time with generalized linear mixed models and generalized additive models. Models indicated that redhorse suckers may respond to sustained turbine sound by increasing distance from the sound source. Freshwater drum models suggested a mixed response to turbine sound, and largemouth bass and rainbow trout models did not indicate any likely responses to turbine sound. Lastly, findings highlight the importance for future research to utilize accurate localization systems, different species, validated sound transmission distances, and to consider different types of behavioral responses to different turbine designs and to the cumulative sound of arrays of multiple turbines.« less

Effects of hydrokinetic turbine sound on the behavior of four species of fish within an experimental mesocosm

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

Schramm, Michael P.; Bevelhimer, Mark; Scherelis, Constantin

The development of hydrokinetic energy technologies (e.g., tidal turbines) has raised concern over the potential impacts of underwater sound produced by hydrokinetic turbines on fish species likely to encounter these turbines. To assess the potential for behavioral impacts, we exposed four species of fish to varying intensities of recorded hydrokinetic turbine sound in a semi-natural environment. Although we tested freshwater species (redhorse suckers [Moxostoma spp], freshwater drum [Aplondinotus grunniens], largemouth bass [Micropterus salmoides], and rainbow trout [Oncorhynchus mykiss]), these species are also representative of the hearing physiology and sensitivity of estuarine species that would be affected at tidal energy sites.more » Here, we evaluated changes in fish position relative to different intensities of turbine sound as well as trends in location over time with linear mixed-effects and generalized additive mixed models. We also evaluated changes in the proportion of near-source detections relative to sound intensity and exposure time with generalized linear mixed models and generalized additive models. Models indicated that redhorse suckers may respond to sustained turbine sound by increasing distance from the sound source. Freshwater drum models suggested a mixed response to turbine sound, and largemouth bass and rainbow trout models did not indicate any likely responses to turbine sound. Lastly, findings highlight the importance for future research to utilize accurate localization systems, different species, validated sound transmission distances, and to consider different types of behavioral responses to different turbine designs and to the cumulative sound of arrays of multiple turbines.« less

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

The effect of skill mix in non-nursing assistants on work engagements among home visiting nurses in Japan.

PubMed

Naruse, Takashi; Taguchi, Atsuko; Kuwahara, Yuki; Nagata, Satoko; Sakai, Mahiro; Watai, Izumi; Murashima, Sachiyo

2015-05-01

This study evaluated the effect of a skill-mix programme intervention on work engagement in home visiting nurses. A skill-mix programme in which home visiting nurses are assisted by non-nursing workers is assumed to foster home visiting nurses' work engagement. Pre- and post-intervention evaluations of work engagement were conducted using self-administered questionnaires. A skill-mix programme was introduced in the intervention group of home visiting nurses. After 6 months, their pre- and post-intervention work engagement ratings were compared with those of a control group. Baseline questionnaires were returned by 174 home visiting nurses (44 in the intervention group, 130 in the control group). Post-intervention questionnaires were returned by 38 and 97 home visiting nurses from each group. The intervention group's average work engagement scores were 2.2 at baseline and 2.3 at post-intervention; the control group's were 3.3 and 2.6. Generalised linear regression showed significant between-group differences in score changes. The skill-mix programme might foster home visiting nurses' work engagement by improving the quality of care for each client. Future research is needed to explain the exact mechanisms that underlie its effectiveness. In order to improve the efficiency of services provided by home visiting nurses and foster their work engagement, skill-mix programmes might be beneficial. © 2014 John Wiley & Sons Ltd.

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 of linear growth in the first year of life of a prospective cohort of full term children with normal birth weight.

PubMed

Queiroz, Valterlinda A O; Assis, Ana Marlúcia O; Pinheiro, Sandra Maria C; Ribeiro, Hugo C Ribeiro

2012-01-01

To investigate covariates that could affect the variation in mean length/age z scores in the first year of life of children born full term with normal birth weight. This was a prospective study of a cohort of mother-infant pairs recruited at public maternity units in two municipalities in the Brazilian state of Bahia, from March 2005 to October 2006. This paper reports the results for linear growth of 489 children who were followed-up for the first 12 months of their lives. A mixed-effect regression model was used to investigate the influence of covariates of mean length/age z score during the first year of life. The multivariate mixed effect analysis indicated that mothers not cohabiting with a partner (beta = 0.2347; p = 0.004) and increased duration of exclusive breastfeeding (beta = 0.0031; p < 0.001) had a positive impact, whereas mother's height less than 150 cm (beta = -0.4393; p < 0.001), birth weight of 2,500-2,999 g (beta = -0.8084; p < 0.001) and anemia in the child (beta = -0.0875; p < 0.001) all had a negative impact on the variation in estimated length/age z score. Therefore, the results of this study indicate that short maternal stature, birth weight < 3,000 g and anemia in the infant had a negative effect on linear growth during the first year of life, whereas longer duration of exclusive breastfeeding and mothers who did not cohabit with a partner had a positive effect.

Minimum number of clusters and comparison of analysis methods for cross sectional stepped wedge cluster randomised trials with binary outcomes: A simulation study.

PubMed

Barker, Daniel; D'Este, Catherine; Campbell, Michael J; McElduff, Patrick

2017-03-09

Stepped wedge cluster randomised trials frequently involve a relatively small number of clusters. The most common frameworks used to analyse data from these types of trials are generalised estimating equations and generalised linear mixed models. A topic of much research into these methods has been their application to cluster randomised trial data and, in particular, the number of clusters required to make reasonable inferences about the intervention effect. However, for stepped wedge trials, which have been claimed by many researchers to have a statistical power advantage over the parallel cluster randomised trial, the minimum number of clusters required has not been investigated. We conducted a simulation study where we considered the most commonly used methods suggested in the literature to analyse cross-sectional stepped wedge cluster randomised trial data. We compared the per cent bias, the type I error rate and power of these methods in a stepped wedge trial setting with a binary outcome, where there are few clusters available and when the appropriate adjustment for a time trend is made, which by design may be confounding the intervention effect. We found that the generalised linear mixed modelling approach is the most consistent when few clusters are available. We also found that none of the common analysis methods for stepped wedge trials were both unbiased and maintained a 5% type I error rate when there were only three clusters. Of the commonly used analysis approaches, we recommend the generalised linear mixed model for small stepped wedge trials with binary outcomes. We also suggest that in a stepped wedge design with three steps, at least two clusters be randomised at each step, to ensure that the intervention effect estimator maintains the nominal 5% significance level and is also reasonably unbiased.

Another look at zonal flows: Resonance, shearing, and frictionless saturation

NASA Astrophysics Data System (ADS)

Li, J. C.; Diamond, P. H.

2018-04-01

We show that shear is not the exclusive parameter that represents all aspects of flow structure effects on turbulence. Rather, wave-flow resonance enters turbulence regulation, both linearly and nonlinearly. Resonance suppresses the linear instability by wave absorption. Flow shear can weaken the resonance, and thus destabilize drift waves, in contrast to the near-universal conventional shear suppression paradigm. Furthermore, consideration of wave-flow resonance resolves the long-standing problem of how zonal flows (ZFs) saturate in the limit of weak or zero frictional drag, and also determines the ZF scale. We show that resonant vorticity mixing, which conserves potential enstrophy, enables ZF saturation in the absence of drag, and so is effective at regulating the Dimits up-shift regime. Vorticity mixing is incorporated as a nonlinear, self-regulation effect in an extended 0D predator-prey model of drift-ZF turbulence. This analysis determines the saturated ZF shear and shows that the mesoscopic ZF width scales as LZ F˜f3 /16(1-f ) 1 /8ρs5/8l03 /8 in the (relevant) adiabatic limit (i.e., τckk‖2D‖≫1 ). f is the fraction of turbulence energy coupled to ZF and l0 is the base state mixing length, absent ZF shears. We calculate and compare the stationary flow and turbulence level in frictionless, weakly frictional, and strongly frictional regimes. In the frictionless limit, the results differ significantly from conventionally quoted scalings derived for frictional regimes. To leading order, the flow is independent of turbulence intensity. The turbulence level scales as E ˜(γL/εc) 2 , which indicates the extent of the "near-marginal" regime to be γL<εc , for the case of avalanche-induced profile variability. Here, εc is the rate of dissipation of potential enstrophy and γL is the characteristic linear growth rate of fluctuations. The implications for dynamics near marginality of the strong scaling of saturated E with γL are discussed.

Adaptation of non-linear mixed amount with zero amount response surface model for analysis of concentration-dependent synergism and safety with midazolam, alfentanil, and propofol sedation.

PubMed

Liou, J-Y; Ting, C-K; Teng, W-N; Mandell, M S; Tsou, M-Y

2018-06-01

The non-linear mixed amount with zero amounts response surface model can be used to describe drug interactions and predict loss of response to noxious stimuli and respiratory depression. We aimed to determine whether this response surface model could be used to model sedation with the triple drug combination of midazolam, alfentanil and propofol. Sedation was monitored in 56 patients undergoing gastrointestinal endoscopy (modelling group) using modified alertness/sedation scores. A total of 227 combinations of effect-site concentrations were derived from pharmacokinetic models. Accuracy and the area under the receiver operating characteristic curve were calculated. Accuracy was defined as an absolute difference <0.5 between the binary patient responses and the predicted probability of loss of responsiveness. Validation was performed with a separate group (validation group) of 47 patients. Effect-site concentration ranged from 0 to 108 ng ml -1 for midazolam, 0-156 ng ml -1 for alfentanil, and 0-2.6 μg ml -1 for propofol in both groups. Synergy was strongest with midazolam and alfentanil (24.3% decrease in U 50 , concentration for half maximal drug effect). Adding propofol, a third drug, offered little additional synergy (25.8% decrease in U 50 ). Two patients (3%) experienced respiratory depression. Model accuracy was 83% and 76%, area under the curve was 0.87 and 0.80 for the modelling and validation group, respectively. The non-linear mixed amount with zero amounts triple interaction response surface model predicts patient sedation responses during endoscopy with combinations of midazolam, alfentanil, or propofol that fall within clinical use. Our model also suggests a safety margin of alfentanil fraction <0.12 that avoids respiratory depression after loss of responsiveness. Copyright © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.

Numerical solution of a non-linear conservation law applicable to the interior dynamics of partially molten planets

NASA Astrophysics Data System (ADS)

Bower, Dan J.; Sanan, Patrick; Wolf, Aaron S.

2018-01-01

The energy balance of a partially molten rocky planet can be expressed as a non-linear diffusion equation using mixing length theory to quantify heat transport by both convection and mixing of the melt and solid phases. Crucially, in this formulation the effective or eddy diffusivity depends on the entropy gradient, ∂S / ∂r , as well as entropy itself. First we present a simplified model with semi-analytical solutions that highlights the large dynamic range of ∂S / ∂r -around 12 orders of magnitude-for physically-relevant parameters. It also elucidates the thermal structure of a magma ocean during the earliest stage of crystal formation. This motivates the development of a simple yet stable numerical scheme able to capture the large dynamic range of ∂S / ∂r and hence provide a flexible and robust method for time-integrating the energy equation. Using insight gained from the simplified model, we consider a full model, which includes energy fluxes associated with convection, mixing, gravitational separation, and conduction that all depend on the thermophysical properties of the melt and solid phases. This model is discretised and evolved by applying the finite volume method (FVM), allowing for extended precision calculations and using ∂S / ∂r as the solution variable. The FVM is well-suited to this problem since it is naturally energy conserving, flexible, and intuitive to incorporate arbitrary non-linear fluxes that rely on lookup data. Special attention is given to the numerically challenging scenario in which crystals first form in the centre of a magma ocean. The computational framework we devise is immediately applicable to modelling high melt fraction phenomena in Earth and planetary science research. Furthermore, it provides a template for solving similar non-linear diffusion equations that arise in other science and engineering disciplines, particularly for non-linear functional forms of the diffusion coefficient.

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.

Linear score tests for variance components in linear mixed models and applications to genetic association studies.

PubMed

Qu, Long; Guennel, Tobias; Marshall, Scott L

2013-12-01

Following the rapid development of genome-scale genotyping technologies, genetic association mapping has become a popular tool to detect genomic regions responsible for certain (disease) phenotypes, especially in early-phase pharmacogenomic studies with limited sample size. In response to such applications, a good association test needs to be (1) applicable to a wide range of possible genetic models, including, but not limited to, the presence of gene-by-environment or gene-by-gene interactions and non-linearity of a group of marker effects, (2) accurate in small samples, fast to compute on the genomic scale, and amenable to large scale multiple testing corrections, and (3) reasonably powerful to locate causal genomic regions. The kernel machine method represented in linear mixed models provides a viable solution by transforming the problem into testing the nullity of variance components. In this study, we consider score-based tests by choosing a statistic linear in the score function. When the model under the null hypothesis has only one error variance parameter, our test is exact in finite samples. When the null model has more than one variance parameter, we develop a new moment-based approximation that performs well in simulations. Through simulations and analysis of real data, we demonstrate that the new test possesses most of the aforementioned characteristics, especially when compared to existing quadratic score tests or restricted likelihood ratio tests. © 2013, The International Biometric Society.

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).

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.

An extended heterogeneous car-following model accounting for anticipation driving behavior and mixed maximum speeds

NASA Astrophysics Data System (ADS)

Sun, Fengxin; Wang, Jufeng; Cheng, Rongjun; Ge, Hongxia

2018-02-01

The optimal driving speeds of the different vehicles may be different for the same headway. In the optimal velocity function of the optimal velocity (OV) model, the maximum speed vmax is an important parameter determining the optimal driving speed. A vehicle with higher maximum speed is more willing to drive faster than that with lower maximum speed in similar situation. By incorporating the anticipation driving behavior of relative velocity and mixed maximum speeds of different percentages into optimal velocity function, an extended heterogeneous car-following model is presented in this paper. The analytical linear stable condition for this extended heterogeneous traffic model is obtained by using linear stability theory. Numerical simulations are carried out to explore the complex phenomenon resulted from the cooperation between anticipation driving behavior and heterogeneous maximum speeds in the optimal velocity function. The analytical and numerical results all demonstrate that strengthening driver's anticipation effect can improve the stability of heterogeneous traffic flow, and increasing the lowest value in the mixed maximum speeds will result in more instability, but increasing the value or proportion of the part already having higher maximum speed will cause different stabilities at high or low traffic densities.

Effects of Visual Complexity and Sublexical Information in the Occipitotemporal Cortex in the Reading of Chinese Phonograms: A Single-Trial Analysis with MEG

ERIC Educational Resources Information Center

Hsu, Chun-Hsien; Lee, Chia-Ying; Marantz, Alec

2011-01-01

We employ a linear mixed-effects model to estimate the effects of visual form and the linguistic properties of Chinese characters on M100 and M170 MEG responses from single-trial data of Chinese and English speakers in a Chinese lexical decision task. Cortically constrained minimum-norm estimation is used to compute the activation of M100 and M170…

Effects of theory of mind performance training on reducing bullying involvement in children and adolescents with high-functioning autism spectrum disorder.

PubMed

Liu, Meng-Jung; Ma, Le-Yin; Chou, Wen-Jiun; Chen, Yu-Min; Liu, Tai-Ling; Hsiao, Ray C; Hu, Huei-Fan; Yen, Cheng-Fang

2018-01-01

Bullying involvement is prevalent among children and adolescents with autism spectrum disorder (ASD). This study examined the effects of theory of mind performance training (ToMPT) on reducing bullying involvement in children and adolescents with high-functioning ASD. Children and adolescents with high-functioning ASD completed ToMPT (n = 26) and social skills training (SST; n = 23) programs. Participants in both groups and their mothers rated the pretraining and posttraining bullying involvement of participants on the Chinese version of the School Bullying Experience Questionnaire. The paired t test was used to evaluate changes in bullying victimization and perpetration between the pretraining and posttraining assessments. Furthermore, the linear mixed-effect model was used to examine the difference in the training effect between the ToMPT and SST groups. The paired t test indicated that in the ToMPT group, the severities of both self-reported (p = .039) and mother-reported (p = .003) bullying victimization significantly decreased from the pretraining to posttraining assessments, whereas in the SST group, only self-reported bullying victimization significantly decreased (p = .027). The linear mixed-effect model indicated that compared with the SST program, the ToMPT program significantly reduced the severity of mother-reported bullying victimization (p = .041). The present study supports the effects of ToMPT on reducing mother-reported bullying victimization in children and adolescents with high-functioning ASD.

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

Olivares, Stefano; Paris, Matteo G. A.; Andersen, Ulrik L.

We analyze in details a scheme for cloning of Gaussian states based on linear optical components and homodyne detection recently demonstrated by Andersen et al. [Phys. Rev. Lett. 94, 240503 (2005)]. The input-output fidelity is evaluated for a generic (pure or mixed) Gaussian state taking into account the effect of nonunit quantum efficiency and unbalanced mode mixing. In addition, since in most quantum information protocols the covariance matrix of the set of input states is not perfectly known, we evaluate the average cloning fidelity for classes of Gaussian states with the degree of squeezing and the number of thermal photonsmore » being only partially known.« less

High pressure liquid chromatographic gradient mixer

DOEpatents

Daughton, Christian G.; Sakaji, Richard H.

1985-01-01

A gradient mixer which effects the continuous mixing of any two miscible solvents without excessive decay or dispersion of the resultant isocratic effluent or of a linear or exponential gradient. The two solvents are fed under low or high pressure by means of two high performance liquid chromatographic pumps. The mixer comprises a series of ultra-low dead volume stainless steel tubes and low dead volume chambers. The two solvent streams impinge head-on at high fluxes. This initial nonhomogeneous mixture is then passed through a chamber packed with spirally-wound wires which cause turbulent mixing thereby homogenizing the mixture with minimum "band-broadening".

High-pressure liquid chromatographic gradient mixer

DOEpatents

Daughton, C.G.; Sakaji, R.H.

1982-09-08

A gradient mixer effects the continuous mixing of any two miscible solvents without excessive decay or dispersion of the resultant isocratic effluent or of a linear or exponential gradient. The two solvents are fed under low or high pressure by means of two high performance liquid chromatographic pumps. The mixer comprises a series of ultra-low dead volume stainless steel tubes and low dead volume chambers. The two solvent streams impinge head-on at high fluxes. This initial nonhomogeneous mixture is then passed through a chamber packed with spirally-wound wires which cause turbulent mixing thereby homogenizing the mixture with minimum band-broadening.

Terahertz time-domain spectroscopy of chondroitin sulfate

PubMed Central

Shi, Changcheng; Ma, Yuting; Zhang, Jin; Wei, Dongshan; Wang, Huabin; Peng, Xiaoyu; Tang, Mingjie; Yan, Shihan; Zuo, Guokun; Du, Chunlei; Cui, Hongliang

2018-01-01

Chondroitin sulfate (CS), derived from cartilage tissues, is an important type of biomacromolecule. In this paper, the terahertz time-domain spectroscopy (THz-TDS) was investigated as a potential method for content detection of CS. With the increase of the CS content, the THz absorption coefficients of the CS/polyethylene mixed samples linearly increase. The refractive indices of the mixed samples also increase when the CS content increases. The extinction coefficient of CS demonstrates the THz frequency dependence to be approximately the power of 1.4, which can be explained by the effects of CS granular solids on THz scattering. PMID:29541526

Climate change at upper treeline: How do trees on the edge react to increasing temperatures?

NASA Astrophysics Data System (ADS)

Jochner, Matthias; Bugmann, Harald; Nötzli, Magdalena; Bigler, Christof

2017-04-01

Treeline ecotones are thought to be particularly sensitive to climate warming, and an alteration of their growth conditions may have important implications for the ecosystem services they supply in mountain regions. We use a novel approach to quantify effects of a changing climate on tree growth, using case studies in the European Alps. We compiled tree-ring data from almost 600 trees of four species at treeline in three climate regions of Switzerland. Temperature loggers installed along transects provided data for a precise interpolation of temperatures experienced by the sampled trees. To assess the influence of temperature on annual growth, we used linear mixed-effects models, allowing us to quantify effect sizes and to account for between-tree growth variability. After removing biological growth trends, we isolated temporal trends of ring-width indices. Furthermore, we fitted non-linear regression models to radial growth rates of individual years with temperature and tree age as predicting covariates for a fine-scale investigation of the temperature dependency of tree growth. For all species, climate-growth linear mixed-effects models indicated strong positive responses of ring-width indices to temperature in early summer and previous year's autumn, featuring considerable between-tree variability. All species showed positive ring-width index trends at treeline but different interactions with elevation: Larix decidua exhibited a declining ring-width index trend with decreasing elevation, whereas Picea abies, Pinus cembra and Pinus mugo showed increasing and/or stable trends. Not only reflected our findings the effects of ameliorated growth conditions, they might have also revealed suspected negative and positive feedbacks of climate change on growth, and increased the knowledge about the functional form and parameterization of the temperature dependency of tree growth.

Mixed aqueous solutions as dilution media in the determination of residual solvents by static headspace gas chromatography.

PubMed

D'Autry, Ward; Zheng, Chao; Wolfs, Kris; Yarramraju, Sitaramaraju; Hoogmartens, Jos; Van Schepdael, Ann; Adams, Erwin

2011-06-01

Static headspace (HS) sampling has been commonly used to test for volatile organic chemicals, usually referred to as residual solvents (RS) in pharmaceuticals. If the sample is not soluble in water, organic solvents are used. However, these seriously reduce the sensitivity in the determination of some RS. Here, mixed aqueous dilution media (a mixture of water and an organic solvent like dimethyl formamide, dimethyl sulfoxide or dimethyl acetamide) were studied as alternative media for static HS-gas chromatographic analysis. Although it has been known that mixed aqueous dilution media can often improve sensitivity for many RS, this study used a systematic approach to investigate phase volumes and the organic content in the HS sampling media. Reference solutions using 18 different class 1, 2 and 3 RS were evaluated. The effect of salt addition was also studied in this work. A significant increase in the peak area was observed for all RS using mixed aqueous dilution media, when compared with organic solvents alone. Matrix effects related to the mixed aqueous dilution media were also investigated and reported. Repeatability and linearity obtained with mixed aqueous dilution media were found to be similar to those observed with pure organic solvents. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Civic Purpose in Late Adolescence: Factors That Prevent Decline in Civic Engagement after High School

ERIC Educational Resources Information Center

Malin, Heather; Han, Hyemin; Liauw, Indrawati

2017-01-01

This study investigated the effects of internal and demographic variables on civic development in late adolescence using the construct "civic purpose." We conducted surveys on civic engagement with 480 high school seniors, and surveyed them again 2 years later. Using multivariate regression and linear mixed models, we tested the main…

Alternative Models for Small Samples in Psychological Research: Applying Linear Mixed Effects Models and Generalized Estimating Equations to Repeated Measures Data

ERIC Educational Resources Information Center

Muth, Chelsea; Bales, Karen L.; Hinde, Katie; Maninger, Nicole; Mendoza, Sally P.; Ferrer, Emilio

2016-01-01

Unavoidable sample size issues beset psychological research that involves scarce populations or costly laboratory procedures. When incorporating longitudinal designs these samples are further reduced by traditional modeling techniques, which perform listwise deletion for any instance of missing data. Moreover, these techniques are limited in their…

Curriculum-Based Measurement of Oral Reading: Quality of Progress Monitoring Outcomes

ERIC Educational Resources Information Center

Christ, Theodore J.; Zopluoglu, Cengiz; Long, Jeffery D.; Monaghen, Barbara D.

2012-01-01

Curriculum-based measurement of oral reading (CBM-R) is frequently used to set student goals and monitor student progress. This study examined the quality of growth estimates derived from CBM-R progress monitoring data. The authors used a linear mixed effects regression (LMER) model to simulate progress monitoring data for multiple levels of…

The Development of Sensitivity to Grammatical Violations in American Sign Language: Native versus Nonnative Signers

ERIC Educational Resources Information Center

Novogrodsky, Rama; Henner, Jon; Caldwell-Harris, Catherine; Hoffmeister, Robert

2017-01-01

Factors influencing native and nonnative signers' syntactic judgment ability in American Sign Language (ASL) were explored for 421 deaf students aged 7;6-18;5. Predictors for syntactic knowledge were chronological age, age of entering a school for the deaf, gender, and additional learning disabilities. Mixed-effects linear modeling analysis…

Does High School Facility Quality Affect Student Achievement? A Two-Level Hierarchical Linear Model

ERIC Educational Resources Information Center

Bowers, Alex J.; Urick, Angela

2011-01-01

The purpose of this study is to isolate the independent effects of high school facility quality on student achievement using a large, nationally representative U.S. database of student achievement and school facility quality. Prior research on linking school facility quality to student achievement has been mixed. Studies that relate overall…

A Systematic Investigation of Within-Subject and Between-Subject Covariance Structures in Growth Mixture Models

ERIC Educational Resources Information Center

Liu, Junhui

2012-01-01

The current study investigated how between-subject and within-subject variance-covariance structures affected the detection of a finite mixture of unobserved subpopulations and parameter recovery of growth mixture models in the context of linear mixed-effects models. A simulation study was conducted to evaluate the impact of variance-covariance…

Components of a Flipped Classroom Influencing Student Success in an Undergraduate Business Statistics Course

ERIC Educational Resources Information Center

Shinaberger, Lee

2017-01-01

An instructor transformed an undergraduate business statistics course over 10 semesters from a traditional lecture course to a flipped classroom course. The researcher used a linear mixed model to explore the effectiveness of the evolution on student success as measured by exam performance. The results provide guidance to successfully implement a…

Advanced Statistical Analyses to Reduce Inconsistency of Bond Strength Data.

PubMed

Minamino, T; Mine, A; Shintani, A; Higashi, M; Kawaguchi-Uemura, A; Kabetani, T; Hagino, R; Imai, D; Tajiri, Y; Matsumoto, M; Yatani, H

2017-11-01

This study was designed to clarify the interrelationship of factors that affect the value of microtensile bond strength (µTBS), focusing on nondestructive testing by which information of the specimens can be stored and quantified. µTBS test specimens were prepared from 10 noncarious human molars. Six factors of µTBS test specimens were evaluated: presence of voids at the interface, X-ray absorption coefficient of resin, X-ray absorption coefficient of dentin, length of dentin part, size of adhesion area, and individual differences of teeth. All specimens were observed nondestructively by optical coherence tomography and micro-computed tomography before µTBS testing. After µTBS testing, the effect of these factors on µTBS data was analyzed by the general linear model, linear mixed effects regression model, and nonlinear regression model with 95% confidence intervals. By the general linear model, a significant difference in individual differences of teeth was observed ( P < 0.001). A significantly positive correlation was shown between µTBS and length of dentin part ( P < 0.001); however, there was no significant nonlinearity ( P = 0.157). Moreover, a significantly negative correlation was observed between µTBS and size of adhesion area ( P = 0.001), with significant nonlinearity ( P = 0.014). No correlation was observed between µTBS and X-ray absorption coefficient of resin ( P = 0.147), and there was no significant nonlinearity ( P = 0.089). Additionally, a significantly positive correlation was observed between µTBS and X-ray absorption coefficient of dentin ( P = 0.022), with significant nonlinearity ( P = 0.036). A significant difference was also observed between the presence and absence of voids by linear mixed effects regression analysis. Our results showed correlations between various parameters of tooth specimens and µTBS data. To evaluate the performance of the adhesive more precisely, the effect of tooth variability and a method to reduce variation in bond strength values should also be considered.

Entropic effects, shape, and size of mixed micelles formed by copolymers with complex architectures

NASA Astrophysics Data System (ADS)

Kalogirou, Andreas; Gergidis, Leonidas N.; Moultos, Othonas; Vlahos, Costas

2015-11-01

The entropic effects in the comicellization behavior of amphiphilic A B copolymers differing in the chain size of solvophilic A parts were studied by means of molecular dynamics simulations. In particular, mixtures of miktoarm star copolymers differing in the molecular weight of solvophilic arms were investigated. We found that the critical micelle concentration values show a positive deviation from the analytical predictions of the molecular theory of comicellization for chemically identical copolymers. This can be attributed to the effective interactions between copolymers originated from the arm size asymmetry. The effective interactions induce a very small decrease in the aggregation number of preferential micelles triggering the nonrandom mixing between the solvophilic moieties in the corona. Additionally, in order to specify how the chain architecture affects the size distribution and the shape of mixed micelles we studied star-shaped, H-shaped, and homo-linked-rings-linear mixtures. In the first case the individual constituents form micelles with preferential and wide aggregation numbers and in the latter case the individual constituents form wormlike and spherical micelles.

Entropic effects, shape, and size of mixed micelles formed by copolymers with complex architectures.

PubMed

Kalogirou, Andreas; Gergidis, Leonidas N; Moultos, Othonas; Vlahos, Costas

2015-11-01

The entropic effects in the comicellization behavior of amphiphilic AB copolymers differing in the chain size of solvophilic A parts were studied by means of molecular dynamics simulations. In particular, mixtures of miktoarm star copolymers differing in the molecular weight of solvophilic arms were investigated. We found that the critical micelle concentration values show a positive deviation from the analytical predictions of the molecular theory of comicellization for chemically identical copolymers. This can be attributed to the effective interactions between copolymers originated from the arm size asymmetry. The effective interactions induce a very small decrease in the aggregation number of preferential micelles triggering the nonrandom mixing between the solvophilic moieties in the corona. Additionally, in order to specify how the chain architecture affects the size distribution and the shape of mixed micelles we studied star-shaped, H-shaped, and homo-linked-rings-linear mixtures. In the first case the individual constituents form micelles with preferential and wide aggregation numbers and in the latter case the individual constituents form wormlike and spherical micelles.

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.

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.

Influence of Soret-Dufour and thermophoresis on hydromagnetic mixed convection heat and mass transfer over an inclined flat plate with non-uniform heat source/sink and chemical reaction

NASA Astrophysics Data System (ADS)

Pal, Dulal; Mondal, Hiranmoy

2018-03-01

The paper is devoted to the study of thermophoresis and Soret-Dufour effects on magnetohydrodynamic mixed convective heat and mass transfer over an inclined flat plate with non-uniform heat source/sink. Governing non-linear coupled ordinary differential equations are solved numerically using Runge-Kutta Fehlberg technique with shooting scheme. The effects of various physical parameters on the velocity, temperature, and concentration profiles are depicted graphically. The values of skin-friction coefficient, Nusselt number and Sherwood number are presented in a tabular form. It is found that increase in thermophoretic and chemical reaction parameters retard the velocity and concentration distributions in the boundary layer.

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

Organic Light Emitting Devices with Linearly-Graded Mixed Host Architecture

NASA Astrophysics Data System (ADS)

Lee, Sang Min

Organic Light Emitting Devices (OLEDs) with a linearly-graded mixed (LGM) host architecture in the emissive layer (EML) were studied by the application of a newly-developed thermal deposition boat. A new thermal deposition boat, featuring indirect deposition control and fast rate response, was developed in order to make an evaporation coater of high space utilization and to achieve a real time linearly-graded rate control during the device fabrication process. A new design of dual-hole boat, based on the reduced wall resistance of the side hole toward the vapor flow, enabled the indirect deposition rate control with sufficient control accuracy by using the feature of the stable ratio of rates from top and side holes. Minimizing the thermal mass of the body and designing a direct heat transfer with a coil placed inside the boat resulted in the realization of the linearly-graded deposition rate within acceptable deviation range. Thanks to the feature of fast rate response, it was possible to control the linearly-graded rate of each host material during the process and to apply the architecture to some of the fluorescent and phosphorescent OLED devices. The reported efficiency improvement of a fluorescent OLED, based on step-graded junction in the literature, was well reproduced in an OLED with a LGM architecture, demonstrating that charge balance in the emissive layer can be further improved using the LGM architecture. By minimizing the internal energy barrier in the LGM device, a higher EL efficiency was well demonstrated over the uniformly-mixed (UM) host device, where residual internal interfaces were present as additional quenching sites in the EML. Similar effects were observed in blue phosphorescent OLED devices, where the mobility of the hole transport material (HTM) was usually much higher than that of the electron transport material (ETM) such that the recombination zone was more localized at the EML/ETL interface. It was found that the main effect of the LGM host was to shift the recombination zone inside of the EML and away from and ETL interface such that luminance quenching near the interface was much lower compared to the UM host, where the main recombination zone was localized near the interface and so more sensitive to the interface quenching.

Application of the balanced scorecard to an academic medical center in Taiwan: the effect of warning systems on improvement of hospital performance.

PubMed

Chen, Hsueh-Fen; Hou, Ying-Hui; Chang, Ray-E

2012-10-01

The balanced scorecard (BSC) is considered to be a useful tool for management in a variety of business environments. The purpose of this article is to utilize the experimental data produced by the incorporation and implementation of the BSC in hospitals and to investigate the effects of the BSC red light tracking warning system on performance improvement. This research was designed to be a retrospective follow-up study. The linear mixed model was applied for correcting the correlated errors. The data used in this study were secondary data collected by repeated measurements taken between 2004 and 2010 by 67 first-line medical departments of a public academic medical center in Taipei, Taiwan. The linear mixed model of analysis was applied for multilevel analysis. Improvements were observed with various time lags, from the subsequent month to three months after red light warning. During follow-up, the red light warning system more effectively improved controllable costs, infection rates, and the medical records completion rate. This further suggests that follow-up management promotes an enhancing and supportive effect to the red light warning. The red light follow-up management of BSC is an effective and efficient tool where improvement depends on ongoing and consistent attention in a continuing effort to better administer medical care and control costs. Copyright © 2012. Published by Elsevier B.V.

Adjusted adaptive Lasso for covariate model-building in nonlinear mixed-effect pharmacokinetic models.

PubMed

Haem, Elham; Harling, Kajsa; Ayatollahi, Seyyed Mohammad Taghi; Zare, Najaf; Karlsson, Mats O

2017-02-01

One important aim in population pharmacokinetics (PK) and pharmacodynamics is identification and quantification of the relationships between the parameters and covariates. Lasso has been suggested as a technique for simultaneous estimation and covariate selection. In linear regression, it has been shown that Lasso possesses no oracle properties, which means it asymptotically performs as though the true underlying model was given in advance. Adaptive Lasso (ALasso) with appropriate initial weights is claimed to possess oracle properties; however, it can lead to poor predictive performance when there is multicollinearity between covariates. This simulation study implemented a new version of ALasso, called adjusted ALasso (AALasso), to take into account the ratio of the standard error of the maximum likelihood (ML) estimator to the ML coefficient as the initial weight in ALasso to deal with multicollinearity in non-linear mixed-effect models. The performance of AALasso was compared with that of ALasso and Lasso. PK data was simulated in four set-ups from a one-compartment bolus input model. Covariates were created by sampling from a multivariate standard normal distribution with no, low (0.2), moderate (0.5) or high (0.7) correlation. The true covariates influenced only clearance at different magnitudes. AALasso, ALasso and Lasso were compared in terms of mean absolute prediction error and error of the estimated covariate coefficient. The results show that AALasso performed better in small data sets, even in those in which a high correlation existed between covariates. This makes AALasso a promising method for covariate selection in nonlinear mixed-effect models.

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.

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.

Phenomenology of maximal and near-maximal lepton mixing

NASA Astrophysics Data System (ADS)

Gonzalez-Garcia, M. C.; Peña-Garay, Carlos; Nir, Yosef; Smirnov, Alexei Yu.

2001-01-01

The possible existence of maximal or near-maximal lepton mixing constitutes an intriguing challenge for fundamental theories of flavor. We study the phenomenological consequences of maximal and near-maximal mixing of the electron neutrino with other (x=tau and/or muon) neutrinos. We describe the deviations from maximal mixing in terms of a parameter ɛ≡1-2 sin2 θex and quantify the present experimental status for \\|ɛ\\|<0.3. We show that both probabilities and observables depend on ɛ quadratically when effects are due to vacuum oscillations and they depend on ɛ linearly if matter effects dominate. The most important information on νe mixing comes from solar neutrino experiments. We find that the global analysis of solar neutrino data allows maximal mixing with confidence level better than 99% for 10-8 eV2<~Δm2<~2×10-7 eV2. In the mass ranges Δm2>~1.5×10-5 eV2 and 4×10-10 eV2<~Δm2<~2×10-7 eV2 the full interval \\|ɛ\\|<0.3 is allowed within ~4σ (99.995% CL) We suggest ways to measure ɛ in future experiments. The observable that is most sensitive to ɛ is the rate [NC]/[CC] in combination with the day-night asymmetry in the SNO detector. With theoretical and statistical uncertainties, the expected accuracy after 5 years is Δɛ~0.07. We also discuss the effects of maximal and near-maximal νe mixing in atmospheric neutrinos, supernova neutrinos, and neutrinoless double beta decay.

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

A novel formulation for unsteady counterflow flames using a thermal-conductivity-weighted coordinate

NASA Astrophysics Data System (ADS)

Weiss, Adam D.; Vera, Marcos; Liñán, Amable; Sánchez, Antonio L.; Williams, Forman A.

2018-01-01

A general formulation is given for the description of reacting mixing layers in stagnation-type flows subject to both time-varying strain and pressure. The salient feature of the formulation is the introduction of a thermal-conductivity-weighted transverse coordinate that leads to a compact transport operator that facilitates numerical integration and theoretical analysis. For steady counterflow mixing layers, the associated transverse mass flux is shown to be effectively linear in terms of the new coordinate, so that the conservation equations for energy and chemical species uncouple from the mass and momentum conservation equations, thereby greatly simplifying the solution. Comparisons are shown with computations of diffusion flames with infinitely fast reaction using both the classic Howarth-Dorodnitzyn density-weighted coordinate and the new thermal-conductivity-weighted coordinate, illustrating the advantages of the latter. Also, as an illustrative application of the formulation to the computation of unsteady counterflows, the flame response to harmonically varying strain is examined in the linear limit.

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.

The Capability Portfolio Analysis Tool (CPAT): A Mixed Integer Linear Programming Formulation for Fleet Modernization Analysis (Version 2.0.2).

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

Waddell, Lucas; Muldoon, Frank; Henry, Stephen Michael

In order to effectively plan the management and modernization of their large and diverse fleets of vehicles, Program Executive Office Ground Combat Systems (PEO GCS) and Program Executive Office Combat Support and Combat Service Support (PEO CS&CSS) commis- sioned the development of a large-scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This paper contains a thor-more » ough documentation of the terminology, parameters, variables, and constraints that comprise the fleet management mixed integer linear programming (MILP) mathematical formulation. This paper, which is an update to the original CPAT formulation document published in 2015 (SAND2015-3487), covers the formulation of important new CPAT features.« less

Detection of genomic loci associated with environmental variables using generalized linear mixed models.

PubMed

Lobréaux, Stéphane; Melodelima, Christelle

2015-02-01

We tested the use of Generalized Linear Mixed Models to detect associations between genetic loci and environmental variables, taking into account the population structure of sampled individuals. We used a simulation approach to generate datasets under demographically and selectively explicit models. These datasets were used to analyze and optimize GLMM capacity to detect the association between markers and selective coefficients as environmental data in terms of false and true positive rates. Different sampling strategies were tested, maximizing the number of populations sampled, sites sampled per population, or individuals sampled per site, and the effect of different selective intensities on the efficiency of the method was determined. Finally, we apply these models to an Arabidopsis thaliana SNP dataset from different accessions, looking for loci associated with spring minimal temperature. We identified 25 regions that exhibit unusual correlations with the climatic variable and contain genes with functions related to temperature stress. Copyright © 2014 Elsevier Inc. All rights reserved.

Deliberate practice predicts performance over time in adolescent chess players and drop-outs: a linear mixed models analysis.

PubMed

de Bruin, Anique B H; Smits, Niels; Rikers, Remy M J P; Schmidt, Henk G

2008-11-01

In this study, the longitudinal relation between deliberate practice and performance in chess was examined using a linear mixed models analysis. The practice activities and performance ratings of young elite chess players, who were either in, or had dropped out of the Dutch national chess training, were analysed since they had started playing chess seriously. The results revealed that deliberate practice (i.e. serious chess study alone and serious chess play) strongly contributed to chess performance. The influence of deliberate practice was not only observable in current performance, but also over chess players' careers. Moreover, although the drop-outs' chess ratings developed more slowly over time, both the persistent and drop-out chess players benefited to the same extent from investments in deliberate practice. Finally, the effect of gender on chess performance proved to be much smaller than the effect of deliberate practice. This study provides longitudinal support for the monotonic benefits assumption of deliberate practice, by showing that over chess players' careers, deliberate practice has a significant effect on performance, and to the same extent for chess players of different ultimate performance levels. The results of this study are not in line with critique raised against the deliberate practice theory that the factors deliberate practice and talent could be confounded.

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.

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

"Do I Have to Leave?" Beyond Linear Text: Struggling Readers' Motivation with an Innovative Musical Program

ERIC Educational Resources Information Center

Bennett, Susan V.; Calderone, Cynthia; Dedrick, Robert F.; Gunn, AnnMarie Alberton

2015-01-01

In this mixed method research, we examined the effects of reading and singing software program (RSSP) as a reading intervention on struggling readers' reading achievement as measured by the Florida Comprehensive Assessment Test, the high stakes state test administered in the state of Florida, at one elementary school. Our team defined struggling…

Gyrofluid turbulence models with kinetic effects

NASA Astrophysics Data System (ADS)

Dorland, W.; Hammett, G. W.

1993-03-01

Nonlinear gyrofluid equations are derived by taking moments of the nonlinear, electrostatic gyrokinetic equation. The principal model presented includes evolution equations for the guiding center n, u∥, T∥, and T⊥ along with an equation expressing the quasineutrality constraint. Additional evolution equations for higher moments are derived that may be used if greater accuracy is desired. The moment hierarchy is closed with a Landau damping model [G. W. Hammett and F. W. Perkins, Phys. Rev. Lett. 64, 3019 (1990)], which is equivalent to a multipole approximation to the plasma dispersion function, extended to include finite Larmor radius effects (FLR). In particular, new dissipative, nonlinear terms are found that model the perpendicular phase mixing of the distribution function along contours of constant electrostatic potential. These ``FLR phase-mixing'' terms introduce a hyperviscositylike damping ∝k⊥2‖Φkk×k'‖, which should provide a physics-based damping mechanism at high k⊥ρ which is potentially as important as the usual polarization drift nonlinearity. The moments are taken in guiding center space to pick up the correct nonlinear FLR terms and the gyroaveraging of the shear. The equations are solved with a nonlinear, three-dimensional initial value code. Linear results are presented, showing excellent agreement with linear gyrokinetic theory.

Therapy preferences of patients with lung and colon cancer: a discrete choice experiment.

PubMed

Schmidt, Katharina; Damm, Kathrin; Vogel, Arndt; Golpon, Heiko; Manns, Michael P; Welte, Tobias; Graf von der Schulenburg, J-Matthias

2017-01-01

There is increasing interest in studies that examine patient preferences to measure health-related outcomes. Understanding patients' preferences can improve the treatment process and is particularly relevant for oncology. In this study, we aimed to identify the subgroup-specific treatment preferences of German patients with lung cancer (LC) or colorectal cancer (CRC). Six discrete choice experiment (DCE) attributes were established on the basis of a systematic literature review and qualitative interviews. The DCE analyses comprised generalized linear mixed-effects model and latent class mixed logit model. The study cohort comprised 310 patients (194 with LC, 108 with CRC, 8 with both types of cancer) with a median age of 63 (SD =10.66) years. The generalized linear mixed-effects model showed a significant ( P <0.05) degree of association for all of the tested attributes. "Strongly increased life expectancy" was the attribute given the greatest weight by all patient groups. Using latent class mixed logit model analysis, we identified three classes of patients. Patients who were better informed tended to prefer a more balanced relationship between length and health-related quality of life (HRQoL) than those who were less informed. Class 2 (LC patients with low HRQoL who had undergone surgery) gave a very strong weighting to increased length of life. We deduced from Class 3 patients that those with a relatively good life expectancy (CRC compared with LC) gave a greater weight to moderate effects on HRQoL than to a longer life. Overall survival was the most important attribute of therapy for patients with LC or CRC. Differences in treatment preferences between subgroups should be considered in regard to treatment and development of guidelines. Patients' preferences were not affected by sex or age, but were affected by the cancer type, HRQoL, surgery status, and the main source of information on the disease.

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.

Genetic overlap between diagnostic subtypes of ischemic stroke.

PubMed

Holliday, Elizabeth G; Traylor, Matthew; Malik, Rainer; Bevan, Steve; Falcone, Guido; Hopewell, Jemma C; Cheng, Yu-Ching; Cotlarciuc, Ioana; Bis, Joshua C; Boerwinkle, Eric; Boncoraglio, Giorgio B; Clarke, Robert; Cole, John W; Fornage, Myriam; Furie, Karen L; Ikram, M Arfan; Jannes, Jim; Kittner, Steven J; Lincz, Lisa F; Maguire, Jane M; Meschia, James F; Mosley, Thomas H; Nalls, Mike A; Oldmeadow, Christopher; Parati, Eugenio A; Psaty, Bruce M; Rothwell, Peter M; Seshadri, Sudha; Scott, Rodney J; Sharma, Pankaj; Sudlow, Cathie; Wiggins, Kerri L; Worrall, Bradford B; Rosand, Jonathan; Mitchell, Braxton D; Dichgans, Martin; Markus, Hugh S; Levi, Christopher; Attia, John; Wray, Naomi R

2015-03-01

Despite moderate heritability, the phenotypic heterogeneity of ischemic stroke has hampered gene discovery, motivating analyses of diagnostic subtypes with reduced sample sizes. We assessed evidence for a shared genetic basis among the 3 major subtypes: large artery atherosclerosis (LAA), cardioembolism, and small vessel disease (SVD), to inform potential cross-subtype analyses. Analyses used genome-wide summary data for 12 389 ischemic stroke cases (including 2167 LAA, 2405 cardioembolism, and 1854 SVD) and 62 004 controls from the Metastroke consortium. For 4561 cases and 7094 controls, individual-level genotype data were also available. Genetic correlations between subtypes were estimated using linear mixed models and polygenic profile scores. Meta-analysis of a combined LAA-SVD phenotype (4021 cases and 51 976 controls) was performed to identify shared risk alleles. High genetic correlation was identified between LAA and SVD using linear mixed models (rg=0.96, SE=0.47, P=9×10(-4)) and profile scores (rg=0.72; 95% confidence interval, 0.52-0.93). Between LAA and cardioembolism and SVD and cardioembolism, correlation was moderate using linear mixed models but not significantly different from zero for profile scoring. Joint meta-analysis of LAA and SVD identified strong association (P=1×10(-7)) for single nucleotide polymorphisms near the opioid receptor μ1 (OPRM1) gene. Our results suggest that LAA and SVD, which have been hitherto treated as genetically distinct, may share a substantial genetic component. Combined analyses of LAA and SVD may increase power to identify small-effect alleles influencing shared pathophysiological processes. © 2015 American Heart Association, Inc.

Controller Synthesis for Periodically Forced Chaotic Systems

NASA Astrophysics Data System (ADS)

Basso, Michele; Genesio, Roberto; Giovanardi, Lorenzo

Delayed feedback controllers are an appealing tool for stabilization of periodic orbits in chaotic systems. Despite their conceptual simplicity, specific and reliable design procedures are difficult to obtain, partly also because of their inherent infinite-dimensional structure. This chapter considers the use of finite dimensional linear time invariant controllers for stabilization of periodic solutions in a general class of sinusoidally forced nonlinear systems. For such controllers — which can be interpreted as rational approximations of the delayed ones — we provide a computationally attractive synthesis technique based on Linear Matrix Inequalities (LMIs), by mixing results concerning absolute stability of nonlinear systems and robustness of uncertain linear systems. The resulting controllers prove to be effective for chaos suppression in electronic circuits and systems, as shown by two different application examples.

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

Efficient Bayesian mixed model analysis increases association power in large cohorts

PubMed Central

Loh, Po-Ru; Tucker, George; Bulik-Sullivan, Brendan K; Vilhjálmsson, Bjarni J; Finucane, Hilary K; Salem, Rany M; Chasman, Daniel I; Ridker, Paul M; Neale, Benjamin M; Berger, Bonnie; Patterson, Nick; Price, Alkes L

2014-01-01

Linear mixed models are a powerful statistical tool for identifying genetic associations and avoiding confounding. However, existing methods are computationally intractable in large cohorts, and may not optimize power. All existing methods require time cost O(MN2) (where N = #samples and M = #SNPs) and implicitly assume an infinitesimal genetic architecture in which effect sizes are normally distributed, which can limit power. Here, we present a far more efficient mixed model association method, BOLT-LMM, which requires only a small number of O(MN)-time iterations and increases power by modeling more realistic, non-infinitesimal genetic architectures via a Bayesian mixture prior on marker effect sizes. We applied BOLT-LMM to nine quantitative traits in 23,294 samples from the Women’s Genome Health Study (WGHS) and observed significant increases in power, consistent with simulations. Theory and simulations show that the boost in power increases with cohort size, making BOLT-LMM appealing for GWAS in large cohorts. PMID:25642633

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

Effects of theory of mind performance training on reducing bullying involvement in children and adolescents with high-functioning autism spectrum disorder

PubMed Central

Chen, Yu-Min; Liu, Tai-Ling; Hsiao, Ray C.; Hu, Huei-Fan

2018-01-01

Bullying involvement is prevalent among children and adolescents with autism spectrum disorder (ASD). This study examined the effects of theory of mind performance training (ToMPT) on reducing bullying involvement in children and adolescents with high-functioning ASD. Children and adolescents with high-functioning ASD completed ToMPT (n = 26) and social skills training (SST; n = 23) programs. Participants in both groups and their mothers rated the pretraining and posttraining bullying involvement of participants on the Chinese version of the School Bullying Experience Questionnaire. The paired t test was used to evaluate changes in bullying victimization and perpetration between the pretraining and posttraining assessments. Furthermore, the linear mixed-effect model was used to examine the difference in the training effect between the ToMPT and SST groups. The paired t test indicated that in the ToMPT group, the severities of both self-reported (p = .039) and mother-reported (p = .003) bullying victimization significantly decreased from the pretraining to posttraining assessments, whereas in the SST group, only self-reported bullying victimization significantly decreased (p = .027). The linear mixed-effect model indicated that compared with the SST program, the ToMPT program significantly reduced the severity of mother-reported bullying victimization (p = .041). The present study supports the effects of ToMPT on reducing mother-reported bullying victimization in children and adolescents with high-functioning ASD. PMID:29342210

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.

Inference on the Genetic Basis of Eye and Skin Color in an Admixed Population via Bayesian Linear Mixed Models.

PubMed

Lloyd-Jones, Luke R; Robinson, Matthew R; Moser, Gerhard; Zeng, Jian; Beleza, Sandra; Barsh, Gregory S; Tang, Hua; Visscher, Peter M

2017-06-01

Genetic association studies in admixed populations are underrepresented in the genomics literature, with a key concern for researchers being the adequate control of spurious associations due to population structure. Linear mixed models (LMMs) are well suited for genome-wide association studies (GWAS) because they account for both population stratification and cryptic relatedness and achieve increased statistical power by jointly modeling all genotyped markers. Additionally, Bayesian LMMs allow for more flexible assumptions about the underlying distribution of genetic effects, and can concurrently estimate the proportion of phenotypic variance explained by genetic markers. Using three recently published Bayesian LMMs, Bayes R, BSLMM, and BOLT-LMM, we investigate an existing data set on eye ( n = 625) and skin ( n = 684) color from Cape Verde, an island nation off West Africa that is home to individuals with a broad range of phenotypic values for eye and skin color due to the mix of West African and European ancestry. We use simulations to demonstrate the utility of Bayesian LMMs for mapping loci and studying the genetic architecture of quantitative traits in admixed populations. The Bayesian LMMs provide evidence for two new pigmentation loci: one for eye color ( AHRR ) and one for skin color ( DDB1 ). Copyright © 2017 by the Genetics Society of America.

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).

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.

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

A mixed model for the relationship between climate and human cranial form.

PubMed

Katz, David C; Grote, Mark N; Weaver, Timothy D

2016-08-01

We expand upon a multivariate mixed model from quantitative genetics in order to estimate the magnitude of climate effects in a global sample of recent human crania. In humans, genetic distances are correlated with distances based on cranial form, suggesting that population structure influences both genetic and quantitative trait variation. Studies controlling for this structure have demonstrated significant underlying associations of cranial distances with ecological distances derived from climate variables. However, to assess the biological importance of an ecological predictor, estimates of effect size and uncertainty in the original units of measurement are clearly preferable to significance claims based on units of distance. Unfortunately, the magnitudes of ecological effects are difficult to obtain with distance-based methods, while models that produce estimates of effect size generally do not scale to high-dimensional data like cranial shape and form. Using recent innovations that extend quantitative genetics mixed models to highly multivariate observations, we estimate morphological effects associated with a climate predictor for a subset of the Howells craniometric dataset. Several measurements, particularly those associated with cranial vault breadth, show a substantial linear association with climate, and the multivariate model incorporating a climate predictor is preferred in model comparison. Previous studies demonstrated the existence of a relationship between climate and cranial form. The mixed model quantifies this relationship concretely. Evolutionary questions that require population structure and phylogeny to be disentangled from potential drivers of selection may be particularly well addressed by mixed models. Am J Phys Anthropol 160:593-603, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

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).

A mixing-model approach to quantifying sources of organic matter to salt marsh sediments

NASA Astrophysics Data System (ADS)

Bowles, K. M.; Meile, C. D.

2010-12-01

Salt marshes are highly productive ecosystems, where autochthonous production controls an intricate exchange of carbon and energy among organisms. The major sources of organic carbon to these systems include 1) autochthonous production by vascular plant matter, 2) import of allochthonous plant material, and 3) phytoplankton biomass. Quantifying the relative contribution of organic matter sources to a salt marsh is important for understanding the fate and transformation of organic carbon in these systems, which also impacts the timing and magnitude of carbon export to the coastal ocean. A common approach to quantify organic matter source contributions to mixtures is the use of linear mixing models. To estimate the relative contributions of endmember materials to total organic matter in the sediment, the problem is formulated as a constrained linear least-square problem. However, the type of data that is utilized in such mixing models, the uncertainties in endmember compositions and the temporal dynamics of non-conservative entitites can have varying affects on the results. Making use of a comprehensive data set that encompasses several endmember characteristics - including a yearlong degradation experiment - we study the impact of these factors on estimates of the origin of sedimentary organic carbon in a saltmarsh located in the SE United States. We first evaluate the sensitivity of linear mixing models to the type of data employed by analyzing a series of mixing models that utilize various combinations of parameters (i.e. endmember characteristics such as δ13COC, C/N ratios or lignin content). Next, we assess the importance of using more than the minimum number of parameters required to estimate endmember contributions to the total organic matter pool. Then, we quantify the impact of data uncertainty on the outcome of the analysis using Monte Carlo simulations and accounting for the uncertainty in endmember characteristics. Finally, as biogeochemical processes can alter endmember characteristics over time, we investigate the effect of early diagenesis on chosen parameters, an analysis that entails an assessment of the organic matter age distribution. Thus, estimates of the relative contributions of phytoplankton, C3 and C4 plants to bulk sediment organic matter depend not only on environmental characteristics that impact reactivity, but also on sediment mixing processes.

The Development of Web-based Graphical User Interface for Unified Modeling Data with Multi (Correlated) Responses

NASA Astrophysics Data System (ADS)

Made Tirta, I.; Anggraeni, Dian

2018-04-01

Statistical models have been developed rapidly into various directions to accommodate various types of data. Data collected from longitudinal, repeated measured, clustered data (either continuous, binary, count, or ordinal), are more likely to be correlated. Therefore statistical model for independent responses, such as Generalized Linear Model (GLM), Generalized Additive Model (GAM) are not appropriate. There are several models available to apply for correlated responses including GEEs (Generalized Estimating Equations), for marginal model and various mixed effect model such as GLMM (Generalized Linear Mixed Models) and HGLM (Hierarchical Generalized Linear Models) for subject spesific models. These models are available on free open source software R, but they can only be accessed through command line interface (using scrit). On the othe hand, most practical researchers very much rely on menu based or Graphical User Interface (GUI). We develop, using Shiny framework, standard pull down menu Web-GUI that unifies most models for correlated responses. The Web-GUI has accomodated almost all needed features. It enables users to do and compare various modeling for repeated measure data (GEE, GLMM, HGLM, GEE for nominal responses) much more easily trough online menus. This paper discusses the features of the Web-GUI and illustrates the use of them. In General we find that GEE, GLMM, HGLM gave very closed results.

Sulfates as chromophores for multiwavelength photoacoustic imaging phantoms

NASA Astrophysics Data System (ADS)

Fonseca, Martina; An, Lu; Beard, Paul; Cox, Ben

2017-12-01

As multiwavelength photoacoustic imaging becomes increasingly widely used to obtain quantitative estimates, the need for validation studies conducted on well-characterized experimental phantoms becomes ever more pressing. One challenge that such studies face is the design of stable, well-characterized phantoms and absorbers with properties in a physiologically realistic range. This paper performs a full experimental characterization of aqueous solutions of copper and nickel sulfate, whose properties make them close to ideal as chromophores in multiwavelength photoacoustic imaging phantoms. Their absorption varies linearly with concentration, and they mix linearly. The concentrations needed to yield absorption values within the physiological range are below the saturation limit. The shape of their absorption spectra makes them useful analogs for oxy- and deoxyhemoglobin. They display long-term photostability (no indication of bleaching) as well as resistance to transient effects (no saturable absorption phenomena), and are therefore suitable for exposure to typical pulsed photoacoustic light sources, even when exposed to the high number of pulses required in scanning photoacoustic imaging systems. In addition, solutions with tissue-realistic, predictable, and stable scattering can be prepared by mixing sulfates and Intralipid, as long as an appropriate emulsifier is used. Finally, the Grüneisen parameter of the sulfates was found to be larger than that of water and increased linearly with concentration.

Comparing a single case to a control group - Applying linear mixed effects models to repeated measures data.

PubMed

Huber, Stefan; Klein, Elise; Moeller, Korbinian; Willmes, Klaus

2015-10-01

In neuropsychological research, single-cases are often compared with a small control sample. Crawford and colleagues developed inferential methods (i.e., the modified t-test) for such a research design. In the present article, we suggest an extension of the methods of Crawford and colleagues employing linear mixed models (LMM). We first show that a t-test for the significance of a dummy coded predictor variable in a linear regression is equivalent to the modified t-test of Crawford and colleagues. As an extension to this idea, we then generalized the modified t-test to repeated measures data by using LMMs to compare the performance difference in two conditions observed in a single participant to that of a small control group. The performance of LMMs regarding Type I error rates and statistical power were tested based on Monte-Carlo simulations. We found that starting with about 15-20 participants in the control sample Type I error rates were close to the nominal Type I error rate using the Satterthwaite approximation for the degrees of freedom. Moreover, statistical power was acceptable. Therefore, we conclude that LMMs can be applied successfully to statistically evaluate performance differences between a single-case and a control sample. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Effects of Fat Structures and Ice Cream Mix Viscosity on Physical and Sensory Properties of Ice Cream.

PubMed

Amador, Julia; Hartel, Rich; Rankin, Scott

2017-08-01

The purpose of this work was to investigate iciness perception and other sensory textural attributes of ice cream due to ice and fat structures and mix viscosity. Two studies were carried out varying processing conditions and mix formulation. In the 1st study, ice creams were collected at -3, -5, and -7.5 °C draw temperatures. These ice creams contained 0%, 0.1%, or 0.2% emulsifier, an 80:20 blend of mono- and diglycerides: polysorbate 80. In the 2nd study, ice creams were collected at -3 °C draw temperature and contained 0%, 0.2%, or 0.4% stabilizer, a blend of guar gum, locust bean gum, and carrageenan. Multiple linear regressions were used to determine relationships between ice crystal size, destabilized fat, and sensory iciness. In the ice and fat structure study, an inverse correlation was found between fat destabilization and sensory iciness. Ice creams with no difference in ice crystal size were perceived to be less icy with increasing amounts of destabilized fat. Destabilized fat correlated inversely with drip-through rate and sensory greasiness. In the ice cream mix viscosity study, an inverse correlation was found between mix viscosity and sensory iciness. Ice creams with no difference in ice crystal size were perceived to be less icy when formulated with higher mix viscosity. A positive correlation was found between mix viscosity and sensory greasiness. These results indicate that fat structures and mix viscosity have significant effects on ice cream microstructure and sensory texture including the reduction of iciness perception. © 2017 Institute of Food Technologists®.

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.

Robust passivity analysis for discrete-time recurrent neural networks with mixed delays

NASA Astrophysics Data System (ADS)

Huang, Chuan-Kuei; Shu, Yu-Jeng; Chang, Koan-Yuh; Shou, Ho-Nien; Lu, Chien-Yu

2015-02-01

This article considers the robust passivity analysis for a class of discrete-time recurrent neural networks (DRNNs) with mixed time-delays and uncertain parameters. The mixed time-delays that consist of both the discrete time-varying and distributed time-delays in a given range are presented, and the uncertain parameters are norm-bounded. The activation functions are assumed to be globally Lipschitz continuous. Based on new bounding technique and appropriate type of Lyapunov functional, a sufficient condition is investigated to guarantee the existence of the desired robust passivity condition for the DRNNs, which can be derived in terms of a family of linear matrix inequality (LMI). Some free-weighting matrices are introduced to reduce the conservatism of the criterion by using the bounding technique. A numerical example is given to illustrate the effectiveness and applicability.

Stimulus sensitive gel with radioisotope and methods of making

DOEpatents

Weller, Richard E.; Lind, Michael A.; Fisher, Darrell R.; Gutowska, Anna; Campbell, Allison A.

2005-03-22

The present invention is a thermally reversible stimulus-sensitive gel or gelling copolymer radioisotope carrier 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 gelling molecular weight cutoff. Addition of a biodegradable backbone and/or a therapeutic agent imparts further utility. The method of the present invention for making a thermally reversible stimulus-sensitive gelling copolymer radionuclcide carrier has the steps of: (a) mixing a stimulus-sensitive reversible gelling copolymer with an aqueous solvent as a stimulus-sensitive reversible gelling solution; and (b) mixing a radioisotope with said stimulus-sensitive reversible gelling solution as said radioisotope carrier. The gel is enhanced by either combining it with a biodegradable backbone and/or a therapeutic agent in a gelling solution made by mixing the copolymer with an aqueous solvent.

Stimulus sensitive gel with radioisotope and methods of making

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

Weller, Richard E; Lind, Michael A; Fisher, Darrell R

2001-10-02

The present invention is a thermally reversible stimulus-sensitive gel or gelling copolymer radioisotope carrier 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 gelling molecular weight cutoff. Addition of a biodegradable backbone and/or a therapeutic agent imparts further utility. The method of the present invention for making a thermally reversible stimulus-sensitive gelling copolymer radionuclcide carrier has the steps of: (a) mixing a stimulus-sensitive reversible gelling copolymer withmore » an aqueous solvent as a stimulus-sensitive reversible gelling solution; and (b) mixing a radioisotope with said stimulus-sensitive reversible gelling solution as said radioisotope carrier. The gel is enhanced by either combining it with a biodegradable backbone and/or a therapeutic agent in a gelling solution made by mixing the copolymer with an aqueous solvent.« less

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.

Water mass mixing: The dominant control on the zinc distribution in the North Atlantic Ocean

NASA Astrophysics Data System (ADS)

Roshan, Saeed; Wu, Jingfeng

2015-07-01

Dissolved zinc (dZn) concentration was determined in the North Atlantic during the U.S. GEOTRACES 2010 and 2011 cruise (GOETRACES GA03). A relatively poor linear correlation (R2 = 0.756) was observed between dZn and silicic acid (Si), the slope of which was 0.0577 nM/µmol/kg. We attribute the relatively poor dZn-Si correlation to the following processes: (a) differential regeneration of zinc relative to silicic acid, (b) mixing of multiple water masses that have different Zn/Si, and (c) zinc sources such as sedimentary or hydrothermal. To quantitatively distinguish these possibilities, we use the results of Optimum Multi-Parameter Water Mass Analysis by Jenkins et al. (2015) to model the zinc distribution below 500 m. We hypothesized two scenarios: conservative mixing and regenerative mixing. The first scenario (conservative) could be modeled to results in a correlation with observations with a R2 = 0.846. In the second scenario, we took a Si-related regeneration into account, which could model the observations with a R2 = 0.867. Through this regenerative mixing scenario, we estimated a Zn/Si = 0.0548 nM/µmol/kg that may be more realistic than linear regression slope due to accounting for process b. However, this did not improve the model substantially (R2 = 0.867 versus0.846), which may indicate the insignificant effect of remineralization on the zinc distribution in this region. The relative weakness in the model-observation correlation (R2~0.85 for both scenarios) implies that processes (a) and (c) may be plausible. Furthermore, dZn in the upper 500 m exhibited a very poor correlation with apparent oxygen utilization, suggesting a minimal role for the organic matter-associated remineralization process.

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...

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

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.

Children's Compliance with American Academy of Pediatrics' Well-Child Care Visit Guidelines and the Early Detection of Autism

ERIC Educational Resources Information Center

Daniels, Amy M.; Mandell, David S.

2013-01-01

This study estimated compliance with American Academy of Pediatrics (AAP) guidelines for well-child care and the association between compliance and age at diagnosis in a national sample of Medicaid-enrolled children with autism (N = 1,475). Mixed effects linear regression was used to assess the relationship between compliance and age at diagnosis.…

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.

Analysis of longitudinal diffusion-weighted images in healthy and pathological aging: An ADNI study.

PubMed

Kruggel, Frithjof; Masaki, Fumitaro; Solodkin, Ana

2017-02-15

The widely used framework of voxel-based morphometry for analyzing neuroimages is extended here to model longitudinal imaging data by exchanging the linear model with a linear mixed-effects model. The new approach is employed for analyzing a large longitudinal sample of 756 diffusion-weighted images acquired in 177 subjects of the Alzheimer's Disease Neuroimaging initiative (ADNI). While sample- and group-level results from both approaches are equivalent, the mixed-effect model yields information at the single subject level. Interestingly, the neurobiological relevance of the relevant parameter at the individual level describes specific differences associated with aging. In addition, our approach highlights white matter areas that reliably discriminate between patients with Alzheimer's disease and healthy controls with a predictive power of 0.99 and include the hippocampal alveus, the para-hippocampal white matter, the white matter of the posterior cingulate, and optic tracts. In this context, notably the classifier includes a sub-population of patients with minimal cognitive impairment into the pathological domain. Our classifier offers promising features for an accessible biomarker that predicts the risk of conversion to Alzheimer's disease. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how to apply/ADNI Acknowledgement List.pdf. Significance statement This study assesses neuro-degenerative processes in the brain's white matter as revealed by diffusion-weighted imaging, in order to discriminate healthy from pathological aging in a large sample of elderly subjects. The analysis of time-series examinations in a linear mixed effects model allowed the discrimination of population-based aging processes from individual determinants. We demonstrate that a simple classifier based on white matter imaging data is able to predict the conversion to Alzheimer's disease with a high predictive power. Copyright © 2017 Elsevier B.V. All rights reserved.

Joint modelling of repeated measurement and time-to-event data: an introductory tutorial.

PubMed

Asar, Özgür; Ritchie, James; Kalra, Philip A; Diggle, Peter J

2015-02-01

The term 'joint modelling' is used in the statistical literature to refer to methods for simultaneously analysing longitudinal measurement outcomes, also called repeated measurement data, and time-to-event outcomes, also called survival data. A typical example from nephrology is a study in which the data from each participant consist of repeated estimated glomerular filtration rate (eGFR) measurements and time to initiation of renal replacement therapy (RRT). Joint models typically combine linear mixed effects models for repeated measurements and Cox models for censored survival outcomes. Our aim in this paper is to present an introductory tutorial on joint modelling methods, with a case study in nephrology. We describe the development of the joint modelling framework and compare the results with those obtained by the more widely used approaches of conducting separate analyses of the repeated measurements and survival times based on a linear mixed effects model and a Cox model, respectively. Our case study concerns a data set from the Chronic Renal Insufficiency Standards Implementation Study (CRISIS). We also provide details of our open-source software implementation to allow others to replicate and/or modify our analysis. The results for the conventional linear mixed effects model and the longitudinal component of the joint models were found to be similar. However, there were considerable differences between the results for the Cox model with time-varying covariate and the time-to-event component of the joint model. For example, the relationship between kidney function as measured by eGFR and the hazard for initiation of RRT was significantly underestimated by the Cox model that treats eGFR as a time-varying covariate, because the Cox model does not take measurement error in eGFR into account. Joint models should be preferred for simultaneous analyses of repeated measurement and survival data, especially when the former is measured with error and the association between the underlying error-free measurement process and the hazard for survival is of scientific interest. © The Author 2015; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Self-mixing detection of backscattered radiation in a single-mode erbium fibre laser for Doppler spectroscopy and velocity measurements

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

Dmitriev, A K; Konovalov, A N; Ul'yanov, V A

2014-04-28

We report an experimental study of the self-mixing effect in a single-mode multifrequency erbium fibre laser when radiation backscattered from an external moving object arrives at its cavity. To eliminate resulting chaotic pulsations in the laser, we have proposed a technique for suppressing backscattered radiation through the use of multimode fibre for radiation delivery. The multifrequency operation of the laser has been shown to lead to strong fluctuations of the amplitude of the Doppler signal and a nonmonotonic variation of the amplitude with distance to the scattering object. In spite of these features, the self-mixing signal was detected with amore » high signal-to-noise ratio (above 10{sup 2}) when the radiation was scattered by a rotating disc, and the Doppler frequency shift, evaluated as the centroid of its spectrum, had high stability (0.15%) and linearity relative to the rotation rate. We conclude that the self-mixing effect in this type of fibre laser can be used for measuring the velocity of scattering objects and in Doppler spectroscopy for monitoring the laser evaporation of materials and biological tissues. (control of laser radiation parameters)« less

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.

Effects of isobutyrate supplementation on ruminal microflora, rumen enzyme activities and methane emissions in Simmental steers.

PubMed

Wang, C; Liu, Q; Zhang, Y L; Pei, C X; Zhang, S L; Wang, Y X; Yang, W Z; Bai, Y S; Shi, Z G; Liu, X N

2015-02-01

The objective of this study was to evaluate the effects of isobutyrate supplementation on rumen microflora, enzyme activities and methane emissions in Simmental steers consuming a corn stover-based diet. Eight ruminally cannulated Simmental steers were used in a replicated 4 × 4 Latin square experiment. The treatments were control (without isobutyrate), low isobutyrate (LIB), moderate isobutyrate (MIB) and high isobutyrate (HIB) with 8.4, 16.8 and 25.2 g isobutyrate per steer per day respectively. Isobutyrate was hand-mixed into the concentrate portion. Diet consisted of 60% corn stover and 40% concentrate [dry matter (DM) basis]. Dry matter intake (averaged 9 kg/day) was restricted to a maximum of 90% of ad libitum intake. Population of total bacteria, cellulolytic bacteria and anaerobic fungi were linearly increased, whereas that of protozoa and total methanogens was linearly reduced with increasing isobutyrate supplementation. Real-time PCR quantification of population of Ruminococcus albus, Ruminococcus flavefaciens, Butyrivibrio fibrisolvens and Fibrobacter succinogenes was linearly increased with increasing isobutyrate supplementation. Activities of carboxymethyl cellulase, xylanase and β-glucosidase were linearly increased, whereas that of protease was linearly reduced. Methane production was linearly decreased with increasing isobutyrate supplementation. Effective degradabilities of cellulose and hemicellulose of corn stover were linearly increased, whereas that of crude protein in diet was linearly decreased with increasing isobutyrate supplementation. The present results indicate that isobutyrate supplemented improved microflora, rumen enzyme activities and methane emissions in steers. It was suggested that the isobutyrate stimulated the digestive micro-organisms or enzymes in a dose-dependent manner. In the experimental conditions of this trial, the optimum isobutyrate dose was approximately 16.8 g isobutyrate per steer per day. Journal of Animal Physiology and Animal Nutrition © 2014 Blackwell Verlag GmbH.

Gallium Arsenide and Related Compounds, 1986.

DTIC Science & Technology

1986-01-01

AFMRI.1U8 d7 -18 6o 60AM F PERORMING ORGANIZATIN ,1b OFICE SYMBOL. 7a. NAME OF MONITORING ORGANIZATION Of appkiie) Unvriyof Illinois AFOSRINE 6C...effect is shown in the log I vs. V characteristics in figure 5. Both devices exhibit good logarithmic behaviour , but it is clear that the ideality of the...effects at the surface. As also shown in Fig. 5, a 200 nm thick n-doped ion implanted and activated layer shows a "mixed" behaviour , namely a linear

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.

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.

Negligible influence of spatial autocorrelation in the assessment of fire effects in a mixed conifer forest

USGS Publications Warehouse

van Mantgem, P.J.; Schwilk, D.W.

2009-01-01

Fire is an important feature of many forest ecosystems, although the quantification of its effects is compromised by the large scale at which fire occurs and its inherent unpredictability. A recurring problem is the use of subsamples collected within individual burns, potentially resulting in spatially autocorrelated data. Using subsamples from six different fires (and three unburned control areas) we show little evidence for strong spatial autocorrelation either before or after burning for eight measures of forest conditions (both fuels and vegetation). Additionally, including a term for spatially autocorrelated errors provided little improvement for simple linear models contrasting the effects of early versus late season burning. While the effects of spatial autocorrelation should always be examined, it may not always greatly influence assessments of fire effects. If high patch scale variability is common in Sierra Nevada mixed conifer forests, even following more than a century of fire exclusion, treatments designed to encourage further heterogeneity in forest conditions prior to the reintroduction of fire will likely be unnecessary.

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

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.

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

Effects of socioeconomic position and social mobility on linear growth from early childhood until adolescence.

PubMed

Muraro, Ana Paula; Souza, Rita Adriana Gomes de; Rodrigues, Paulo Rogério Melo; Ferreira, Márcia Gonçalves; Sichieri, Rosely

2017-01-01

To assess the effect of socioeconomic position (SEP) in childhood and social mobility on linear growth through adolescence in a population-based cohort. Children born in Cuiabá-MT, central-western Brazil, were evaluated during 1994 - 1999. They were first assessed during 1999 - 2000 (0 - 5 years) and again during 2009 - 2011 (10 - 17 years), and their height-for-age was evaluated during these two periods.Awealth index was used to classify the SEP of each child's family as low, medium, or high. Social mobility was categorized as upward mobility or no upward mobility. Linear mixed models were used. We evaluated 1,716 children (71.4% of baseline) after 10 years, and 60.6% of the families showed upward mobility, with a higher percentage among the lowest economic classes. A higher height-for-age was also observed among those from families with a high SEP both in childhood (low SEP= -0.35 z-score; high SEP= 0.15 z-score, p < 0.01) and adolescence (low SEP= -0.01 z-score; high SEP= 0.45 z-score, p < 0.01), whereas upward mobility did not affect their linear growth. Expressive social mobility was observed, but SEP in childhood and social mobility did not greatly influence linear growth through childhood in this central-western Brazilian cohort.

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.

Mixed emotions across the adult life span in the United States

PubMed Central

Schneider, Stefan; Stone, Arthur A.

2015-01-01

Mixed emotions involve the co-occurrence of positive and negative affect, such that people feel happy and sad at the same time. The purpose of the present study was to investigate age-related differences in the experience of mixed emotions across the adult life span in two nationally representative samples of U.S. residents. Data collected by the Princeton Affect and Time Survey (PATS, n = 3,948) and by the 2010 Wellbeing Module of the American Time Use Survey (ATUS, n = 12,828) were analyzed. In both surveys, respondents (aged 15 years or older) provided a detailed time diary about the preceding day and rated their happiness and sadness for three of the day's episodes. From these reports, three different indices of mixed emotions were derived. Results indicated small, but robust, increases in mixed emotions with age. Linear age increases were consistently evident in both PATS and ATUS, and replicated across the different indices of mixed emotions. There was no significant evidence for curvilinear age trends in either study. Several sociodemographic factors that could plausibly explain age-differences in mixed emotions (e.g., retirement, disability) did not alter the age-effects. The present study adds to the growing literature documenting vital changes in the complexity of emotional experience over the lifespan. PMID:25894487

Kinetic Alfvén Wave Generation by Large-scale Phase Mixing

NASA Astrophysics Data System (ADS)

Vásconez, C. L.; Pucci, F.; Valentini, F.; Servidio, S.; Matthaeus, W. H.; Malara, F.

2015-12-01

One view of the solar wind turbulence is that the observed highly anisotropic fluctuations at spatial scales near the proton inertial length dp may be considered as kinetic Alfvén waves (KAWs). In the present paper, we show how phase mixing of large-scale parallel-propagating Alfvén waves is an efficient mechanism for the production of KAWs at wavelengths close to dp and at a large propagation angle with respect to the magnetic field. Magnetohydrodynamic (MHD), Hall magnetohydrodynamic (HMHD), and hybrid Vlasov–Maxwell (HVM) simulations modeling the propagation of Alfvén waves in inhomogeneous plasmas are performed. In the linear regime, the role of dispersive effects is singled out by comparing MHD and HMHD results. Fluctuations produced by phase mixing are identified as KAWs through a comparison of polarization of magnetic fluctuations and wave-group velocity with analytical linear predictions. In the nonlinear regime, a comparison of HMHD and HVM simulations allows us to point out the role of kinetic effects in shaping the proton-distribution function. We observe the generation of temperature anisotropy with respect to the local magnetic field and the production of field-aligned beams. The regions where the proton-distribution function highly departs from thermal equilibrium are located inside the shear layers, where the KAWs are excited, this suggesting that the distortions of the proton distribution are driven by a resonant interaction of protons with KAW fluctuations. Our results are relevant in configurations where magnetic-field inhomogeneities are present, as, for example, in the solar corona, where the presence of Alfvén waves has been ascertained.

Flipping-shuttle oscillations of bright one- and two-dimensional solitons in spin-orbit-coupled Bose-Einstein condensates with Rabi mixing

NASA Astrophysics Data System (ADS)

Sakaguchi, Hidetsugu; Malomed, Boris A.

2017-10-01

We analyze the possibility of macroscopic quantum effects in the form of coupled structural oscillations and shuttle motion of bright two-component spin-orbit-coupled striped (one-dimensional, 1D) and semivortex (two-dimensional, 2D) matter-wave solitons, under the action of linear mixing (Rabi coupling) between the components. In 1D, the intrinsic oscillations manifest themselves as flippings between spatially even and odd components of striped solitons, while in 2D the system features periodic transitions between zero-vorticity and vortical components of semivortex solitons. The consideration is performed by means of a combination of analytical and numerical methods.

The effect of self-selected complementary therapies on cancer patients' quality of life and symptom distress: A prospective cohort study in an integrative oncology setting.

PubMed

Stomski, N J; Petterson, A; Kristjanson, L; Lobb, E A; Phillips, M; Williams, A; Morrison, P; Joske, D

2018-04-01

To examine the effectiveness of a multifaceted complementary therapies intervention, delivered in a systematic manner within an Australian public hospital setting, on quality of life and symptom distress outcomes for cancer patients. Adults receiving treatment for any form of cancer were eligible to participate in this study. Self-referred participants were offered a course of six complementary therapy sessions. Measures were administered at baseline, and at the third and sixth visit. The primary outcomes were quality of life and symptom distress. Linear mixed models were used to assess change in the primary outcomes. In total, 1376 cancer patients participated in this study. The linear mixed models demonstrated that there were significant improvements in quality of life and significant reductions in symptom distress over six sessions. Body-based therapies demonstrated significantly superior improvement in quality of life over counselling, but no other differences between therapies were identified. Reduced symptom distress was not significantly associated with any particular type of therapy. A self-selected complementary therapies intervention, provided in an Australian public hospital by accredited therapists, for cancer patients significantly mproved quality of life and reduced symptom distress. The effect of this intervention on quality of life has particular salience, since cancer impacts on many areas of people's lives and impairs quality of life. Copyright © 2018 Elsevier Ltd. All rights reserved.

Synergy between air pollution and urban meteorological changes through aerosol-radiation-diffusion feedback―A case study of Beijing in January 2013

NASA Astrophysics Data System (ADS)

Kajino, Mizuo; Ueda, Hiromasa; Han, Zhiwei; Kudo, Rei; Inomata, Yayoi; Kaku, Hidenori

2017-12-01

The interactions of aerosol-radiation-stratification-turbulence-cloud processes during a severe haze event in Beijing in January 2013 were studied using a numerical model. For the clear days, solar radiation flux was reduced by approximately 15% and surface temperature was slightly decreased from 0 to 0.5 K throughout the day and night, except for a 1.4 K decrease around sunrise when fog was presented. The longwave radiation cooling was intensified by the fog or drizzle droplets near the top of the fog layer. Thus, in Beijing, both in the daytime and at night, the surface air temperature was decreased by air pollutants. In the presence of the low-level stratus and light precipitation, the modification of meteorology by aerosols was amplified and changed the wind speed and direction much more significantly compared to clear days. The non-linear effect (or positive feedback) of pollutant emission control on the surface air concentration was newly assessed―severe air pollution leads to the intensification of stable stratification near the surface at night and delays the evolution of the mixing layer, which in turn causes more severe air pollution. The non-linear effect was not significant for the current emission levels in the current case, approximately 10%. In another word, the mixing ratio of aerosols became higher by 10% due to their radiation effects.

Modelling the Progression of Competitive Performance of an Academy's Soccer Teams.

PubMed

Malcata, Rita M; Hopkins, Will G; Richardson, Scott

2012-01-01

Progression of a team's performance is a key issue in competitive sport, but there appears to have been no published research on team progression for periods longer than a season. In this study we report the game-score progression of three teams of a youth talent-development academy over five seasons using a novel analytic approach based on generalised mixed modelling. The teams consisted of players born in 1991, 1992 and 1993; they played totals of 115, 107 and 122 games in Asia and Europe between 2005 and 2010 against teams differing in age by up to 3 years. Game scores predicted by the mixed model were assumed to have an over-dispersed Poisson distribution. The fixed effects in the model estimated an annual linear pro-gression for Aspire and for the other teams (grouped as a single opponent) with adjustment for home-ground advantage and for a linear effect of age difference between competing teams. A random effect allowed for different mean scores for Aspire and opposition teams. All effects were estimated as factors via log-transformation and presented as percent differences in scores. Inferences were based on the span of 90% confidence intervals in relation to thresholds for small factor effects of x/÷1.10 (+10%/-9%). Most effects were clear only when data for the three teams were combined. Older teams showed a small 27% increase in goals scored per year of age difference (90% confidence interval 13 to 42%). Aspire experienced a small home-ground advantage of 16% (-5 to 41%), whereas opposition teams experienced 31% (7 to 60%) on their own ground. After adjustment for these effects, the Aspire teams scored on average 1.5 goals per match, with little change in the five years of their existence, whereas their opponents' scores fell from 1.4 in their first year to 1.0 in their last. The difference in progression was trivial over one year (7%, -4 to 20%), small over two years (15%, -8 to 44%), but unclear over >2 years. In conclusion, the generalized mixed model has marginal utility for estimating progression of soccer scores, owing to the uncertainty arising from low game scores. The estimates are likely to be more precise and useful in sports with higher game scores. Key pointsA generalized linear mixed model is the approach for tracking game scores, key performance indicators or other measures of performance based on counts in sports where changes within and/or between games/seasons have to be considered.Game scores in soccer could be useful to track performance progression of teams, but hundreds of games are needed.Fewer games will be needed for tracking performance represented by counts with high scores, such as game scores in rugby or key performance indicators based on frequent events or player actions in any team sport.

Modelling the Progression of Competitive Performance of an Academy’s Soccer Teams

PubMed Central

Malcata, Rita M.; Hopkins, Will G; Richardson, Scott

2012-01-01

Progression of a team’s performance is a key issue in competitive sport, but there appears to have been no published research on team progression for periods longer than a season. In this study we report the game-score progression of three teams of a youth talent-development academy over five seasons using a novel analytic approach based on generalised mixed modelling. The teams consisted of players born in 1991, 1992 and 1993; they played totals of 115, 107 and 122 games in Asia and Europe between 2005 and 2010 against teams differing in age by up to 3 years. Game scores predicted by the mixed model were assumed to have an over-dispersed Poisson distribution. The fixed effects in the model estimated an annual linear pro-gression for Aspire and for the other teams (grouped as a single opponent) with adjustment for home-ground advantage and for a linear effect of age difference between competing teams. A random effect allowed for different mean scores for Aspire and opposition teams. All effects were estimated as factors via log-transformation and presented as percent differences in scores. Inferences were based on the span of 90% confidence intervals in relation to thresholds for small factor effects of x/÷1.10 (+10%/-9%). Most effects were clear only when data for the three teams were combined. Older teams showed a small 27% increase in goals scored per year of age difference (90% confidence interval 13 to 42%). Aspire experienced a small home-ground advantage of 16% (-5 to 41%), whereas opposition teams experienced 31% (7 to 60%) on their own ground. After adjustment for these effects, the Aspire teams scored on average 1.5 goals per match, with little change in the five years of their existence, whereas their opponents’ scores fell from 1.4 in their first year to 1.0 in their last. The difference in progression was trivial over one year (7%, -4 to 20%), small over two years (15%, -8 to 44%), but unclear over >2 years. In conclusion, the generalized mixed model has marginal utility for estimating progression of soccer scores, owing to the uncertainty arising from low game scores. The estimates are likely to be more precise and useful in sports with higher game scores. Key pointsA generalized linear mixed model is the approach for tracking game scores, key performance indicators or other measures of performance based on counts in sports where changes within and/or between games/seasons have to be considered.Game scores in soccer could be useful to track performance progression of teams, but hundreds of games are needed.Fewer games will be needed for tracking performance represented by counts with high scores, such as game scores in rugby or key performance indicators based on frequent events or player actions in any team sport. PMID:24149364

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...

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

Internal waves and rectification in a linearly stratified fluid

NASA Astrophysics Data System (ADS)

Pérenne, Nicolas; Renouard, Dominique P.

Laboratory experiments were performed in a 13-m diameter rotating tank equipped with a continuous shelf break geometry and a central piston-like plunger. The fluid density was linearly stratified. The amplitude and period of the plunger, the rotation rate of the platform and the stratification are the parameters of the problem. The density fluctuations at six stations above and at mid-depth of the slope, along with dye visualization of the flow, were recorded. A limited set of experiments showed that a barotropic periodical forcing generated a first mode baroclinic wave which initially appears at the slope and propagates offshore. The likely presence of internal energy rays either slightly above, or immediately along the slope, is in agreement with previous analytical, laboratory and selected oceanic observations. In the former case, the stratification was such that the slope flow at mid-depth was supercritical while in the latter case, slope flow at mid-depth was critical. Rotation tended to decrease the amplitude of the generated internal wave. Also, non-linear processes were likely to act upon these waves for their normalized amplitude tended to decrease as the forcing increased (for similar forcing period, rotation rate and stratification). After the internal wave reflected from the plunger reaches the slope, there is a complex non-stationary regime with an occurrence of internal wave breaking in the vicinity of the slope. Thus there was an appearance of localized patches of turbulence and mixing. These events appeared both in dye visualization and in density fluctuations records. The subsequent mixing, or else the combined effect of topographical rectification and mixing, led to the appearance of a distinct Lagrangian transport, localized in the first few centimeters above the slope and oriented so as to leave the shallow waters on the right of its displacement.

Improved estimation of sediment source contributions by concentration-dependent Bayesian isotopic mixing model

NASA Astrophysics Data System (ADS)

Ram Upadhayay, Hari; Bodé, Samuel; Griepentrog, Marco; Bajracharya, Roshan Man; Blake, Will; Cornelis, Wim; Boeckx, Pascal

2017-04-01

The implementation of compound-specific stable isotope (CSSI) analyses of biotracers (e.g. fatty acids, FAs) as constraints on sediment-source contributions has become increasingly relevant to understand the origin of sediments in catchments. The CSSI fingerprinting of sediment utilizes CSSI signature of biotracer as input in an isotopic mixing model (IMM) to apportion source soil contributions. So far source studies relied on the linear mixing assumptions of CSSI signature of sources to the sediment without accounting for potential effects of source biotracer concentration. Here we evaluated the effect of FAs concentration in sources on the accuracy of source contribution estimations in artificial soil mixture of three well-separated land use sources. Soil samples from land use sources were mixed to create three groups of artificial mixture with known source contributions. Sources and artificial mixture were analysed for δ13C of FAs using gas chromatography-combustion-isotope ratio mass spectrometry. The source contributions to the mixture were estimated using with and without concentration-dependent MixSIAR, a Bayesian isotopic mixing model. The concentration-dependent MixSIAR provided the closest estimates to the known artificial mixture source contributions (mean absolute error, MAE = 10.9%, and standard error, SE = 1.4%). In contrast, the concentration-independent MixSIAR with post mixing correction of tracer proportions based on aggregated concentration of FAs of sources biased the source contributions (MAE = 22.0%, SE = 3.4%). This study highlights the importance of accounting the potential effect of a source FA concentration for isotopic mixing in sediments that adds realisms to mixing model and allows more accurate estimates of contributions of sources to the mixture. The potential influence of FA concentration on CSSI signature of sediments is an important underlying factor that determines whether the isotopic signature of a given source is observable even after equilibrium. Therefore inclusion of FA concentrations of the sources in the IMM formulation is standard procedure for accurate estimation of source contributions. The post model correction approach that dominates the CSSI fingerprinting causes bias, especially if the FAs concentration of sources differs substantially.

Review of mixing length estimates and effects of toroidicity in a fluid model for turbulent transport in tokamaks

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

Weiland, J., E-mail: elfjw@chalmers.se

2016-05-15

Basic aspects of turbulent transport in toroidal magnetized plasmas are discussed. In particular the fluid closure has strong effects on zonal flows which are needed to create an absorbing boundary for long wave lengths and also to obtain the Dimits nonlinear upshift. The fluid resonance in the energy equation is found to be instrumental for generating the L–H transition, the spin-up of poloidal rotation in internal transport barriers, as well as the nonlinear Dimits upshift. The difference between the linearly fastest growing mode number and the corresponding longer nonlinear correlation length is also addressed. It is found that the Kadomtsevmore » mixing length result is consistent with the non-Markovian diagonal limit of the transport at the nonlinearly obtained correlation length.« less

Methods and apparatus of entangled photon generation using four-wave mixing

DOEpatents

Camacho, Ryan

2016-02-23

A non-linear optical device is provided. The device comprises an optical disk or ring microresonator fabricated from a material that exhibits an optical nonlinearity able to produce degenerate four-wave mixing (FWM) in response to a pump beam having a pump frequency in a specified effective range. The microresonator is conformed to exhibit an angular group velocity minimum at a pump frequency within the specified effective range such that there is zero angular group velocity dispersion at the pump frequency. We refer to such a pump frequency as the "zero dispersion frequency". In embodiments, excitation of the resonator by a pump beam of sufficient intensity at the zero-dispersion frequency causes the resonator to emit a frequency comb of entangled photon pairs wherein the respective frequencies in each pair are symmetrically placed about the zero-dispersion frequency.

An ab initio study on the effect of iron atom junction on transport characteristics of carbon-silicon mixed chain

NASA Astrophysics Data System (ADS)

Hu, Wei; Zhou, Qinghua; Liu, Wenhua; Liang, Yan; Wang, Tao; Wan, Haiqing

2018-04-01

The effect of iron atom junction on transport characteristics of carbon-silicon mixed chain has been studied from an ab initio study. At zero bias, the Fe(CSi)n system appears to be the decrease of the conductance as the number of the Si-C pairs in the chain increases (n changes). When n > 5, the conductance tends to zero. These changes are independent of the transferring charge of the system, depending on the coupling of the electrodes and the central region. Under bias, the higher the bias voltage, the bigger the transmission coefficient of the system, and the transmission peak moves closer to the Fermi level. The I-V curves of Fe(CSi)2 and Fe (CSi)3 are linear, showing the behavior of metal resistance.

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.

No increase in small-solute transport in peritoneal dialysis patients treated without hypertonic glucose for fifty-four months.

PubMed

Pagniez, Dominique; Duhamel, Alain; Boulanger, Eric; Lessore de Sainte Foy, Celia; Beuscart, Jean-Baptiste

2017-08-31

Glucose is widely used as an osmotic agent in peritoneal dialysis (PD), but exerts untoward effects on the peritoneum. The potential protective effect of a reduced exposure to hypertonic glucose has never been investigated. The cohort of PD patients attending our center which tackled the challenge of a restricted use of hypertonic glucose solutions has been prospectively followed since 1992. Small-solute transport was assessed using an equivalent of the glucose peritoneal equilibration test after 6 months, and then every year. Study was stopped on July 1st, 2008, before use of biocompatible solutions. Repeated measures in patients treated with PD for 54 months were analyzed by using (1) the slopes of the linear regression for D 4 /D 0 ratios over time computed for each individual, and (2) a linear mixed model. In the study period, 44 patients were treated for a total of 2376 months, 2058 without hypertonic glucose. There was one episode of peritoneal infection every 18 patient-months. The mean of slopes of the linear regression for D 4 /D 0 ratios was found to be significantly positive (Student's test, p < .001) and the results of the mixed model reflected a similar significant increase for D 4 /D 0 ratios over time. These results reflected a significant decrease of small-solute transport. In this large series, minimizing the use of hypertonic glucose solutions was associated in patients on long term PD with an overall decrease of small-solute transport within 54 months, despite a high rate of peritoneal infection.

Horses Auto-Recruit Their Lungs by Inspiratory Breath Holding Following Recovery from General Anaesthesia

PubMed Central

Mosing, Martina; Waldmann, Andreas D.; MacFarlane, Paul; Iff, Samuel; Auer, Ulrike; Bohm, Stephan H.; Bettschart-Wolfensberger, Regula; Bardell, David

2016-01-01

This study evaluated the breathing pattern and distribution of ventilation in horses prior to and following recovery from general anaesthesia using electrical impedance tomography (EIT). Six horses were anaesthetised for 6 hours in dorsal recumbency. Arterial blood gas and EIT measurements were performed 24 hours before (baseline) and 1, 2, 3, 4, 5 and 6 hours after horses stood following anaesthesia. At each time point 4 representative spontaneous breaths were analysed. The percentage of the total breath length during which impedance remained greater than 50% of the maximum inspiratory impedance change (breath holding), the fraction of total tidal ventilation within each of four stacked regions of interest (ROI) (distribution of ventilation) and the filling time and inflation period of seven ROI evenly distributed over the dorso-ventral height of the lungs were calculated. Mixed effects multi-linear regression and linear regression were used and significance was set at p<0.05. All horses demonstrated inspiratory breath holding until 5 hours after standing. No change from baseline was seen for the distribution of ventilation during inspiration. Filling time and inflation period were more rapid and shorter in ventral and slower and longer in most dorsal ROI compared to baseline, respectively. In a mixed effects multi-linear regression, breath holding was significantly correlated with PaCO2 in both the univariate and multivariate regression. Following recovery from anaesthesia, horses showed inspiratory breath holding during which gas redistributed from ventral into dorsal regions of the lungs. This suggests auto-recruitment of lung tissue which would have been dependent and likely atelectic during anaesthesia. PMID:27331910

Site-level progression of periodontal disease during a follow-up period

PubMed Central

Morozumi, Toshiya; Nakagawa, Taneaki; Sugaya, Tsutomu; Kawanami, Masamitsu; Suzuki, Fumihiko; Takahashi, Keiso; Abe, Yuzo; Sato, Soh; Makino-Oi, Asako; Saito, Atsushi; Takano, Satomi; Minabe, Masato; Nakayama, Yohei; Ogata, Yorimasa; Kobayashi, Hiroaki; Izumi, Yuichi; Sugano, Naoyuki; Ito, Koichi; Sekino, Satoshi; Numabe, Yukihiro; Fukaya, Chie; Yoshinari, Nobuo; Fukuda, Mitsuo; Noguchi, Toshihide; Kono, Tomoo; Umeda, Makoto; Fujise, Osamu; Nishimura, Fusanori; Yoshimura, Atsutoshi; Hara, Yoshitaka; Nakamura, Toshiaki; Noguchi, Kazuyuki; Kakuta, Erika; Hanada, Nobuhiro; Takashiba, Shogo; Amitani, Yasuharu; Yoshie, Hiromasa

2017-01-01

Periodontal disease is assessed and its progression is determined via observations on a site-by-site basis. Periodontal data are complex and structured in multiple levels; thus, applying a summary statistical approach (i.e., the mean) for site-level evaluations results in loss of information. Previous studies have shown the availability of mixed effects modeling. However, clinically beneficial information on the progression of periodontal disease during the follow-up period is not available. We conducted a multicenter prospective cohort study. Using mixed effects modeling, we analyzed 18,834 sites distributed on 3,139 teeth in 124 patients, and data were collected 5 times over a 24-month follow-up period. The change in the clinical attachment level (CAL) was used as the outcome variable. The CAL at baseline was an important determinant of the CAL changes, which varied widely according to the tooth surface. The salivary levels of periodontal pathogens, such as Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans, were affected by CAL progression. “Linear”- and “burst”-type patterns of CAL progression occurred simultaneously within the same patient. More than half of the teeth that presented burst-type progression sites also presented linear-type progression sites, and most of the progressions were of the linear type. Maxillary premolars and anterior teeth tended to show burst-type progression. The parameters identified in this study may guide practitioners in determining the type and extent of treatment needed at the site and patient levels. In addition, these results show that prior hypotheses concerning "burst" and "linear" theories are not valid. PMID:29206238

Large Eddy Simulations of a Bottom Boundary Layer Under a Shallow Geostrophic Front

NASA Astrophysics Data System (ADS)

Bateman, S. P.; Simeonov, J.; Calantoni, J.

2017-12-01

The unstratified surf zone and the stratified shelf waters are often separated by dynamic fronts that can strongly impact the character of the Ekman bottom boundary layer. Here, we use large eddy simulations to study the turbulent bottom boundary layer associated with a geostrophic current on a stratified shelf of uniform depth. The simulations are initialized with a spatially uniform vertical shear that is in geostrophic balance with a pressure gradient due to a linear horizontal temperature variation. Superposed on the temperature front is a stable vertical temperature gradient. As turbulence develops near the bottom, the turbulence-induced mixing gradually erodes the initial uniform temperature stratification and a well-mixed layer grows in height until the turbulence becomes fully developed. The simulations provide the spatial distribution of the turbulent dissipation and the Reynolds stresses in the fully developed boundary layer. We vary the initial linear stratification and investigate its effect on the height of the bottom boundary layer and the turbulence statistics. The results are compared to previous models and simulations of stratified bottom Ekman layers.

Scaling law on formation and rupture of a dynamical liquid bridge

NASA Astrophysics Data System (ADS)

Zhang, Huang; Zhang, Zehao; Liu, Qianfeng; Li, Shuiqing; Department of Thermal Engineering, Tsinghua University Collaboration; Institute of Nuclear Energy; Technology, Tsinghua University Collaboration

2017-11-01

The formation and breakup of a pendular liquid bridge in dynamic state is investigated experimentally. The experimental setup arises from a system to measure the coefficient of restitution (COR) of a glass sphere impacting and bouncing on a wetted surface. We compare the effect of surface tension and gravity on the liquid bridge rupture by the capillary length κ-1. For water and liquid 1 (50% water mixed with 50% glycerol), the gravity is dominant on the liquid bridge breakup. And we find that the rupture distance is in good linear trend with the non-dimensional number G by the scaling law analysis. Further, for liquid 2 (25% water mixed with 75% glycerol) that is relatively high viscous, the linear changing of the rupture distance with the capillary number Ca is found. The relation of the rupture distance with G and Ca would be helpful in understanding the complex behavior of the dynamical liquid bridge. This work was funded by the Major State Basic Research Development Program of China (Grant No. 2016YFC0203705) and the China Postdoctoral Science Foundation (Grant No. 2016M601024).

Microgrid Optimal Scheduling With Chance-Constrained Islanding Capability

DOE PAGES

Liu, Guodong; Starke, Michael R.; Xiao, B.; ...

2017-01-13

To facilitate the integration of variable renewable generation and improve the resilience of electricity sup-ply in a microgrid, this paper proposes an optimal scheduling strategy for microgrid operation considering constraints of islanding capability. A new concept, probability of successful islanding (PSI), indicating the probability that a microgrid maintains enough spinning reserve (both up and down) to meet local demand and accommodate local renewable generation after instantaneously islanding from the main grid, is developed. The PSI is formulated as mixed-integer linear program using multi-interval approximation taking into account the probability distributions of forecast errors of wind, PV and load. With themore » goal of minimizing the total operating cost while preserving user specified PSI, a chance-constrained optimization problem is formulated for the optimal scheduling of mirogrids and solved by mixed integer linear programming (MILP). Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator and a battery demonstrate the effectiveness of the proposed scheduling strategy. Lastly, we verify the relationship between PSI and various factors.« less

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.

Reliability of environmental sampling culture results using the negative binomial intraclass correlation coefficient.

PubMed

Aly, Sharif S; Zhao, Jianyang; Li, Ben; Jiang, Jiming

2014-01-01

The Intraclass Correlation Coefficient (ICC) is commonly used to estimate the similarity between quantitative measures obtained from different sources. Overdispersed data is traditionally transformed so that linear mixed model (LMM) based ICC can be estimated. A common transformation used is the natural logarithm. The reliability of environmental sampling of fecal slurry on freestall pens has been estimated for Mycobacterium avium subsp. paratuberculosis using the natural logarithm transformed culture results. Recently, the negative binomial ICC was defined based on a generalized linear mixed model for negative binomial distributed data. The current study reports on the negative binomial ICC estimate which includes fixed effects using culture results of environmental samples. Simulations using a wide variety of inputs and negative binomial distribution parameters (r; p) showed better performance of the new negative binomial ICC compared to the ICC based on LMM even when negative binomial data was logarithm, and square root transformed. A second comparison that targeted a wider range of ICC values showed that the mean of estimated ICC closely approximated the true ICC.

Application of Linear Mixed-Effect Models for the Analysis of Exam Scores: Online Video Associated with Higher Scores for Undergraduate Students with Lower Grades

ERIC Educational Resources Information Center

Dupuis, Josee; Coutu, Josee; Laneuville, Odette

2013-01-01

In higher education, many of the new teaching interventions are introduced in the format of audio-visual files distributed through the Internet. A pedagogical tool consisting of questions listed as learning objectives and answers presented using online videos was designed as a supplement for a molecular biology course and made available to a large…

Topics in Statistical Calibration

DTIC Science & Technology

2014-03-27

on a parametric bootstrap where, instead of sampling directly from the residuals , samples are drawn from a normal distribution. This procedure will...addition to centering them (Davison and Hinkley, 1997). When there are outliers in the residuals , the bootstrap distribution of x̂0 can become skewed or...based and inversion methods using the linear mixed-effects model. Then, a simple parametric bootstrap algorithm is proposed that can be used to either

A Preclinical Population Pharmacokinetic Model for Anti-CD20/CD3 T-Cell-Dependent Bispecific Antibodies.

PubMed

Ferl, Gregory Z; Reyes, Arthur; Sun, Liping L; Cheu, Melissa; Oldendorp, Amy; Ramanujan, Saroja; Stefanich, Eric G

2018-05-01

CD20 is a cell-surface receptor expressed by healthy and neoplastic B cells and is a well-established target for biologics used to treat B-cell malignancies. Pharmacokinetic (PK) and pharmacodynamic (PD) data for the anti-CD20/CD3 T-cell-dependent bispecific antibody BTCT4465A were collected in transgenic mouse and nonhuman primate (NHP) studies. Pronounced nonlinearity in drug elimination was observed in the murine studies, and time-varying, nonlinear PK was observed in NHPs, where three empirical drug elimination terms were identified using a mixed-effects modeling approach: i) a constant nonsaturable linear clearance term (7 mL/day/kg); ii) a rapidly decaying time-varying, linear clearance term (t ½  = 1.6 h); and iii) a slowly decaying time-varying, nonlinear clearance term (t ½  = 4.8 days). The two time-varying drug elimination terms approximately track with time scales of B-cell depletion and T-cell migration/expansion within the central blood compartment. The mixed-effects NHP model was scaled to human and prospective clinical simulations were generated. © 2018 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Evaluation of spatial variability of soil arsenic adjacent to a disused cattle-dip site, using model-based geostatistics.

PubMed

Niazi, Nabeel K; Bishop, Thomas F A; Singh, Balwant

2011-12-15

This study investigated the spatial variability of total and phosphate-extractable arsenic (As) concentrations in soil adjacent to a cattle-dip site, employing a linear mixed model-based geostatistical approach. The soil samples in the study area (n = 102 in 8.1 m(2)) were taken at the nodes of a 0.30 × 0.35 m grid. The results showed that total As concentration (0-0.2 m depth) and phosphate-extractable As concentration (at depths of 0-0.2, 0.2-0.4, and 0.4-0.6 m) in soil adjacent to the dip varied greatly. Both total and phosphate-extractable soil As concentrations significantly (p = 0.004-0.048) increased toward the cattle-dip. Using the linear mixed model, we suggest that 5 samples are sufficient to assess a dip site for soil (As) contamination (95% confidence interval of ±475.9 mg kg(-1)), but 15 samples (95% confidence interval of ±212.3 mg kg(-1)) is desirable baseline when the ultimate goal is to evaluate the effects of phytoremediation. Such guidelines on sampling requirements are crucial for the assessment of As contamination levels at other cattle-dip sites, and to determine the effect of phytoremediation on soil As.

Diagnosis of mild Alzheimer disease through the analysis of eye movements during reading.

PubMed

Fernández, Gerardo; Castro, Liliana R; Schumacher, Marcela; Agamennoni, Osvaldo E

2015-03-01

Reading requires the integration of several central cognitive subsystems, ranging from attention and oculomotor control to word identification and language comprehension. Reading saccades and fixations contain information that can be correlated with word properties. When reading a sentence, the brain must decide where to direct the next saccade according to what has been read up to the actual fixation. In this process, the retrieval memory brings information about the current word features and attributes into working memory. According to this information, the prefrontal cortex predicts and triggers the next saccade. The frequency and cloze predictability of the fixated word, the preceding words and the upcoming ones affect when and where the eyes will move next. In this paper we present a diagnostic technique for early stage cognitive impairment detection by analyzing eye movements during reading proverbs. We performed a case-control study involving 20 patients with probable Alzheimer's disease and 40 age-matched, healthy control patients. The measurements were analyzed using linear mixed-effects models, revealing that eye movement behavior while reading can provide valuable information about whether a person is cognitively impaired. To the best of our knowledge, this is the first study using word-based properties, proverbs and linear mixed-effect models for identifying cognitive abnormalities.

Non-linear optical crystal vibration sensing device

DOEpatents

Kalibjian, R.

1994-08-09

A non-linear optical crystal vibration sensing device including a photorefractive crystal and a laser is disclosed. The laser produces a coherent light beam which is split by a beam splitter into a first laser beam and a second laser beam. After passing through the crystal the first laser beam is counter-propagated back upon itself by a retro-mirror, creating a third laser beam. The laser beams are modulated, due to the mixing effect within the crystal by vibration of the crystal. In the third laser beam, modulation is stable and such modulation is converted by a photodetector into a usable electrical output, intensity modulated in accordance with vibration applied to the crystal. 3 figs.

Linear Instability Analysis of non-uniform Bubbly Mixing layer with Two-Fluid model

NASA Astrophysics Data System (ADS)

Sharma, Subash; Chetty, Krishna; Lopez de Bertodano, Martin

We examine the inviscid instability of a non-uniform adiabatic bubbly shear layer with a Two-Fluid model. The Two-Fluid model is made well-posed with the closure relations for interfacial forces. First, a characteristic analysis is carried out to study the well posedness of the model over range of void fraction with interfacial forces for virtual mass, interfacial drag, interfacial pressure. A dispersion analysis then allow us to obtain growth rate and wavelength. Then, the well-posed two-fluid model is solved using CFD to validate the results obtained with the linear stability analysis. The effect of the void fraction and the distribution profile on stability is analyzed.

Unfolded equations for current interactions of 4d massless fields as a free system in mixed dimensions

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

Gelfond, O. A., E-mail: gel@lpi.ru; Vasiliev, M. A., E-mail: vasiliev@lpi.ru

2015-03-15

Interactions of massless fields of all spins in four dimensions with currents of any spin are shown to result from a solution of the linear problem that describes a gluing between a rank-one (massless) system and a rank-two (current) system in the unfolded dynamics approach. Since the rank-two system is dual to a free rank-one higher-dimensional system that effectively describes conformal fields in six space-time dimensions, the constructed system can be interpreted as describing a mixture between linear conformal fields in four and six dimensions. An interpretation of the obtained results in the spirit of the AdS/CFT correspondence is discussed.

An oscillatory kernel function method for lifting surfaces in mixed transonic flow

NASA Technical Reports Server (NTRS)

Cunningham, A. M., Jr.

1974-01-01

A study was conducted on the use of combined subsonic and supersonic linear theory to obtain economical and yet realistic solutions to unsteady transonic flow problems. With some modification, existing linear theory methods were combined into a single computer program. The method was applied to problems for which measured steady Mach number distributions and unsteady pressure distributions were available. By comparing theory and experiment, the transonic method showed a significant improvement over uniform flow methods. The results also indicated that more exact local Mach number effects and normal shock boundary conditions on the perturbation potential were needed. The validity of these improvements was demonstrated by application to steady flow.

Modelling Kepler red giants in eclipsing binaries: calibrating the mixing-length parameter with asteroseismology

NASA Astrophysics Data System (ADS)

Li, Tanda; Bedding, Timothy R.; Huber, Daniel; Ball, Warrick H.; Stello, Dennis; Murphy, Simon J.; Bland-Hawthorn, Joss

2018-03-01

Stellar models rely on a number of free parameters. High-quality observations of eclipsing binary stars observed by Kepler offer a great opportunity to calibrate model parameters for evolved stars. Our study focuses on six Kepler red giants with the goal of calibrating the mixing-length parameter of convection as well as the asteroseismic surface term in models. We introduce a new method to improve the identification of oscillation modes that exploits theoretical frequencies to guide the mode identification (`peak-bagging') stage of the data analysis. Our results indicate that the convective mixing-length parameter (α) is ≈14 per cent larger for red giants than for the Sun, in agreement with recent results from modelling the APOGEE stars. We found that the asteroseismic surface term (i.e. the frequency offset between the observed and predicted modes) correlates with stellar parameters (Teff, log g) and the mixing-length parameter. This frequency offset generally decreases as giants evolve. The two coefficients a-1 and a3 for the inverse and cubic terms that have been used to describe the surface term correction are found to correlate linearly. The effect of the surface term is also seen in the p-g mixed modes; however, established methods for correcting the effect are not able to properly correct the g-dominated modes in late evolved stars.

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).

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.

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.

Boxing and mixed martial arts: preliminary traumatic neuromechanical injury risk analyses from laboratory impact dosage data.

PubMed

Bartsch, Adam J; Benzel, Edward C; Miele, Vincent J; Morr, Douglas R; Prakash, Vikas

2012-05-01

In spite of ample literature pointing to rotational and combined impact dosage being key contributors to head and neck injury, boxing and mixed martial arts (MMA) padding is still designed to primarily reduce cranium linear acceleration. The objects of this study were to quantify preliminary linear and rotational head impact dosage for selected boxing and MMA padding in response to hook punches; compute theoretical skull, brain, and neck injury risk metrics; and statistically compare the protective effect of various glove and head padding conditions. An instrumented Hybrid III 50th percentile anthropomorphic test device (ATD) was struck in 54 pendulum impacts replicating hook punches at low (27-29 J) and high (54-58 J) energy. Five padding combinations were examined: unpadded (control), MMA glove-unpadded head, boxing glove-unpadded head, unpadded pendulum-boxing headgear, and boxing glove-boxing headgear. A total of 17 injury risk parameters were measured or calculated. All padding conditions reduced linear impact dosage. Other parameters significantly decreased, significantly increased, or were unaffected depending on padding condition. Of real-world conditions (MMA glove-bare head, boxing glove-bare head, and boxing glove-headgear), the boxing glove-headgear condition showed the most meaningful reduction in most of the parameters. In equivalent impacts, the MMA glove-bare head condition induced higher rotational dosage than the boxing glove-bare head condition. Finite element analysis indicated a risk of brain strain injury in spite of significant reduction of linear impact dosage. In the replicated hook punch impacts, all padding conditions reduced linear but not rotational impact dosage. Head and neck dosage theoretically accumulates fastest in MMA and boxing bouts without use of protective headgear. The boxing glove-headgear condition provided the best overall reduction in impact dosage. More work is needed to develop improved protective padding to minimize linear and rotational impact dosage and develop next-generation standards for head and neck injury risk.

Effects of photochemical oxidation on the mixing state and light absorption of black carbon in the urban atmosphere of China

NASA Astrophysics Data System (ADS)

Wang, Qiyuan; Huang, Rujin; Zhao, Zhuzi; Cao, Junji; Ni, Haiyan; Tie, Xuexi; Zhu, Chongshu; Shen, Zhenxing; Wang, Meng; Dai, Wenting; Han, Yongming; Zhang, Ningning; Prévôt, André S. H.

2017-04-01

The relationship between the refractory black carbon (rBC) aerosol mixing state and the atmospheric oxidation capacity was investigated to assess the possible influence of oxidants on the particles’ light absorption effects at two large cities in China. The number fraction of thickly-coated rBC particles (F rBC) was positively correlated with a measure of the oxidant concentrations (OX = O3 + NO2), indicating an enhancement of coated rBC particles under more oxidizing conditions. The slope of a linear regression of F rBC versus OX was 0.58% ppb-1 for Beijing and 0.84% ppb-1 for Xi’an, and these relationships provide some insights into the evolution of rBC mixing state in relation to atmospheric oxidation processes. The mass absorption cross-section of rBC (MACrBC) increased with OX during the daytime at Xi’an, at a rate of 0.26 m2 g-1 ppb-1, suggesting that more oxidizing conditions lead to internal mixing that enhances the light-absorbing capacity of rBC particles. Understanding the dependence of the increasing rates of F rBC and MACrBC as a function of OX may lead to improvements of climate models that deal with the warming effects, but more studies in different cities and seasons are needed to gauge the broader implications of these findings.

Elastic properties and short-range structural order in mixed network former glasses.

PubMed

Wang, Weimin; Christensen, Randilynn; Curtis, Brittany; Hynek, David; Keizer, Sydney; Wang, James; Feller, Steve; Martin, Steve W; Kieffer, John

2017-06-21

Elastic properties of alkali containing glasses are of great interest not only because they provide information about overall structural integrity but also they are related to other properties such as thermal conductivity and ion mobility. In this study, we investigate two mixed-network former glass systems, sodium borosilicate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)SiO 2 ] and sodium borogermanate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)GeO 2 ] glasses. By mixing network formers, the network topology can be changed while keeping the network modifier concentration constant, which allows for the effect of network structure on elastic properties to be analyzed over a wide parametric range. In addition to non-linear, non-additive mixed-glass former effects, maxima are observed in longitudinal, shear and Young's moduli with increasing atomic number density. By combining results from NMR spectroscopy and Brillouin light scattering with a newly developed statistical thermodynamic reaction equilibrium model, it is possible to determine the relative proportions of all network structural units. This new analysis reveals that the structural characteristic predominantly responsible for effective mechanical load transmission in these glasses is a high density of network cations coordinated by four or more bridging oxygens, as it provides for establishing a network of covalent bonds among these cations with connectivity in three dimensions.

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.

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.

Effect of solvent hydrogen bonding on the photophysical properties of intramolecular charge transfer probe trans-ethyl p-(dimethylamino) cinamate and its derivative

NASA Astrophysics Data System (ADS)

Singh, T. Sanjoy; Moyon, N. S.; Mitra, Sivaprasad

2009-08-01

Intramolecular charge transfer (ICT) behavior of trans-ethyl p-(dimethylamino) cinamate (EDAC) and 4-(dimethylamino) cinnamic acid (DMACA) were studied by steady state absorption and emission, picosecond time-resolved fluorescence experiments in various pure and mixed solvent systems. The large fluorescence spectral shift in more polar solvents indicates an efficient charge transfer from the donor site to the acceptor moiety in the excited state compared to the ground state. The energy for 0,0 transition ( ν0,0) for EDAC shows very good linear correlation with static solvent dielectric property; however, fluorescence emission maximum, stokes shift and fluorescence quantum yield show significant deviation from linearity in polar protic solvents, indicating a large contribution of solvent hydrogen bonding on the excited state relaxation mechanism. A quantitative estimation of contribution from different solvatochromic parameters was made using linear free energy relationship based on Kamlet-Taft equation.

Device and method for generating a beam of acoustic energy from a borehole, and applications thereof

DOEpatents

Vu, Cung Khac; Sinha, Dipen N; Pantea, Cristian; Nihei, Kurt T; Schmitt, Denis P; Skelt, Christopher

2013-10-01

In some aspects of the invention, a method of generating a beam of acoustic energy in a borehole is disclosed. The method includes generating a first acoustic wave at a first frequency; generating a second acoustic wave at a second frequency different than the first frequency, wherein the first acoustic wave and second acoustic wave are generated by at least one transducer carried by a tool located within the borehole; transmitting the first and the second acoustic waves into an acoustically non-linear medium, wherein the composition of the non-linear medium produces a collimated beam by a non-linear mixing of the first and second acoustic waves, wherein the collimated beam has a frequency based upon a difference between the first frequency and the second frequency; and transmitting the collimated beam through a diverging acoustic lens to compensate for a refractive effect caused by the curvature of the borehole.

Sea surface temperature anomalies, planetary waves, and air-sea feedback in the middle latitudes

NASA Technical Reports Server (NTRS)

Frankignoul, C.

1985-01-01

Current analytical models for large-scale air-sea interactions in the middle latitudes are reviewed in terms of known sea-surface temperature (SST) anomalies. The scales and strength of different atmospheric forcing mechanisms are discussed, along with the damping and feedback processes controlling the evolution of the SST. Difficulties with effective SST modeling are described in terms of the techniques and results of case studies, numerical simulations of mixed-layer variability and statistical modeling. The relationship between SST and diabatic heating anomalies is considered and a linear model is developed for the response of the stationary atmosphere to the air-sea feedback. The results obtained with linear wave models are compared with the linear model results. Finally, sample data are presented from experiments with general circulation models into which specific SST anomaly data for the middle latitudes were introduced.

Dynamic Latent Trait Models with Mixed Hidden Markov Structure for Mixed Longitudinal Outcomes.

PubMed

Zhang, Yue; Berhane, Kiros

2016-01-01

We propose a general Bayesian joint modeling approach to model mixed longitudinal outcomes from the exponential family for taking into account any differential misclassification that may exist among categorical outcomes. Under this framework, outcomes observed without measurement error are related to latent trait variables through generalized linear mixed effect models. The misclassified outcomes are related to the latent class variables, which represent unobserved real states, using mixed hidden Markov models (MHMM). In addition to enabling the estimation of parameters in prevalence, transition and misclassification probabilities, MHMMs capture cluster level heterogeneity. A transition modeling structure allows the latent trait and latent class variables to depend on observed predictors at the same time period and also on latent trait and latent class variables at previous time periods for each individual. Simulation studies are conducted to make comparisons with traditional models in order to illustrate the gains from the proposed approach. The new approach is applied to data from the Southern California Children Health Study (CHS) to jointly model questionnaire based asthma state and multiple lung function measurements in order to gain better insight about the underlying biological mechanism that governs the inter-relationship between asthma state and lung function development.

Assessment of PDF Micromixing Models Using DNS Data for a Two-Step Reaction

NASA Astrophysics Data System (ADS)

Tsai, Kuochen; Chakrabarti, Mitali; Fox, Rodney O.; Hill, James C.

1996-11-01

Although the probability density function (PDF) method is known to treat the chemical reaction terms exactly, its application to turbulent reacting flows have been overshadowed by the ability to model the molecular mixing terms satisfactorily. In this study, two PDF molecular mixing models, the linear-mean-square-estimation (LMSE or IEM) model and the generalized interaction-by-exchange-with-the-mean (GIEM) model, are compared with the DNS data in decaying turbulence with a two-step parallel-consecutive reaction and two segregated initial conditions: ``slabs" and ``blobs". Since the molecular mixing model is expected to have a strong effect on the mean values of chemical species under such initial conditions, the model evaluation is intended to answer the following questions: Can the PDF models predict the mean values of chemical species correctly with completely segregated initial conditions? (2) Is a single molecular mixing timescale sufficient for the PDF models to predict the mean values with different initial conditions? (3) Will the chemical reactions change the molecular mixing timescales of the reacting species enough to affect the accuracy of the model's prediction for the mean values of chemical species?

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.

Automatic analysis with thermometric detection.

PubMed

McLean, W R; Penketh, G E

1968-11-01

The construction of a cell and associated Wheatstone bridge detector circuitry is described for a thermometric detector suitable for attachment to a Technicon Autoanalyzer. The detector produces a d.c. mV signal linearly proportional to the concentration (0.005-0.1M) of the thermally reactive component in the sample stream when it is mixed in the cell with the reagent stream. The influence of various pertinent parameters such as ambient temperature, thermistor voltage, heats of reaction and sensitivity are discussed together with interference effects arising through chemistry, ionic strength effects and heat of dilution.

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

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.

Chemical Reactions in Turbulent Mixing Flows

DTIC Science & Technology

1992-07-01

Chemically-Reacting, Gas-Phase Turbulent Jets (Gilbrech 1991), that explored Reynolds number effects on turbulent flame length and the influence of...and asymptotes to a constant value beyond the flame tip. The main result of the work is that the flame length , as estimated from the temperature...8217. Specifically, the normalized flame length Lf/d* displays a linear dependence on the stoichiometric mixture ratio 0, with a slope that decreases from Re "• 1.0

Prosody-Syntax Integration in a Second Language: Contrasting Event-Related Potentials from German and Chinese Learners of English Using Linear Mixed Effect Models

ERIC Educational Resources Information Center

Nickels, Stefanie; Steinhauer, Karsten

2018-01-01

The role of prosodic information in sentence processing is not usually addressed in second language (L2) instruction, and neurocognitive studies on prosody-syntax interactions are rare. Here we compare event-related potentials (ERP) of Chinese and German learners of English L2 to those of native English speakers and show how first language (L1)…

The mixed alkali effect in ionically conducting glasses revisited: a study by molecular dynamics simulation.

PubMed

Habasaki, Junko; Ngai, Kia L

2007-09-07

When more than two kinds of mobile ions are mixed in ionic conducting glasses and crystals, there is a non-linear decrease of the transport coefficients of either type of ion. This phenomenon is known as the mixed mobile ion effect or Mixed Alkali Effect (MAE), and remains an unsolved problem. We use molecular dynamics simulation to study the complex ion dynamics in ionically conducting glasses including the MAE. In the mixed alkali lithium-potassium silicate glasses and related systems, a distinct part of the van Hove functions reveals that jumps from one kind of site to another are suppressed. Although, consensus for the existence of preferential jump paths for each kind of mobile ions seems to have been reached amongst researchers, the role of network formers and the number of unoccupied ion sites remain controversial in explaining the MAE. In principle, these factors when incorporated into a theory can generate the MAE, but in reality they are not essential for a viable explanation of the ion dynamics and the MAE. Instead, dynamical heterogeneity and "cooperativity blockage" originating from ion-ion interaction and correlation are fundamental for the observed ion dynamics and the MAE. Suppression of long range motion with increased back-correlated motions is shown to be a cause of the large decrease of the diffusivity especially in dilute foreign alkali regions. Support for our conclusion also comes from the fact that these features of ion dynamics are common to other ionic conductors, which have no glassy networks, and yet they all exhibit the MAE.

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...

Modelling non-hydrostatic processes in sill regions

NASA Astrophysics Data System (ADS)

Souza, A.; Xing, J.; Davies, A.; Berntsen, J.

2007-12-01

We use a non-hydrostatic model to compute tidally induced flow and mixing in the region of bottom topography representing the sill at the entrance to Loch Etive (Scotland). This site is chosen since detailed measurements were recently made there. With non-hydrostatic dynamics in the model our results showed that the model could reproduce the observed flow characteristics, e.g., hydraulic transition, flow separation and internal waves. However, when calculations were performed using the model in the hydrostatic form, significant artificial convective mixing occurred. This influenced the computed temperature and flow field. We will discuss in detail the effects of non-hydrostatic dynamics on flow over the sill, especially investigate non-linear and non-hydrostatic contributions to modelled internal waves and internal wave energy fluxes.

A solution to Rayleigh-Taylor instabilities. Bubbles, spikes, and their scalings

DOE PAGES

Mikaelian, Karnig O.

2014-05-12

A fluid that pushes on and accelerates a heavier fluid, small perturbations at their interface grows with time and lead. to turbulent mixing. The same instability, known as the Rayleigh-Taylor instability, operates when a heavy fluid is supported by a lighter fluid in a gravitational field. Moreover, it has a particularly deleterious effect on inertial-confinement-fusion implosions and is known to operate over 18 orders of magnitude in dimension. We propose analytic expressions for the bubble and spike amplitudes and mixing widths in the linear, nonlinear, and turbulent regimes. They cover arbitrary density ratios and accelerations that are constant or changingmore » relatively slowly with time. Here, we discuss their scalings and compare them with simulations and experiments.« less

Characterization of linear viscoelastic anti-vibration rubber mounts

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

Lodhia, B.B.; Esat, I.I.

1996-11-01

The aim of this paper is to identify the dynamic characteristics that are evident in linear viscoelastic rubber mountings. The characteristics under consideration included the static and dynamic stiffnesses with the variation of amplitude and frequency of the sinusoidal excitation. Test samples of various rubber mix were tested and compared to reflect magnitude of dependency on composition. In the light of the results, the validity and effectiveness of a mathematical model was investigated and a suitable technique based on the Tschoegl and Emri Algorithm, was utilized to fit the model to the experimental data. The model which was chosen, wasmore » an extension of the basic Maxwell model, which is based on linear spring and dashpot elements in series and parallel called the Wiechert model. It was found that the extent to which the filler and vulcanisate was present in the rubber sample, did have a great effect on the static stiffness characteristics, and the storage and loss moduli. The Tschoegl and Emri Algorithm was successfully utilized in modelling the frequency response of the samples.« less

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

NUMERICAL SIMULATIONS OF THERMOHALINE CONVECTION: IMPLICATIONS FOR EXTRA-MIXING IN LOW-MASS RGB STARS

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

Denissenkov, Pavel A., E-mail: pavel.denisenkov@gmail.co

2010-11-01

Low-mass stars are known to experience extra-mixing in their radiative zones on the red giant branch (RGB) above the bump luminosity. To determine if the salt-fingering transport of chemical composition driven by {sup 3}He burning is efficient enough to produce RGB extra-mixing, two-dimensional numerical simulations of thermohaline convection for physical conditions corresponding to the RGB case have been carried out. We have found that the effective ratio of a salt finger's length to its diameter a{sub eff} {approx}< 0.5 is more than 10 times smaller than the value needed to reproduce observations (a{sub obs} {approx}> 7). On the other hand,more » using the thermohaline diffusion coefficient from linear stability analysis together with a = a{sub obs} is able to describe the RGB extra-mixing at all metallicities so well that it is tempting to believe that it may represent the true mechanism. In view of these results, follow-up three-dimensional numerical simulations of thermohaline convection for the RGB case are clearly needed.« less

Mixed H ∞ and Passive Projective Synchronization for Fractional Order Memristor-Based Neural Networks with Time-Delay and Parameter Uncertainty

NASA Astrophysics Data System (ADS)

Song, Xiao-Na; Song, Shuai; Tejado Balsera, Inés; Liu, Lei-Po

2017-10-01

This paper investigates the mixed H ∞ and passive projective synchronization problem for fractional-order (FO) memristor-based neural networks. Our aim is to design a controller such that, though the unavoidable phenomena of time-delay and parameter uncertainty are fully considered, the resulting closed-loop system is asymptotically stable with a mixed H ∞ and passive performance level. By combining active and adaptive control methods, a novel hybrid control strategy is designed, which can guarantee the robust stability of the closed-loop system and also ensure a mixed H ∞ and passive performance level. Via the application of FO Lyapunov stability theory, the projective synchronization conditions are addressed in terms of linear matrix inequality techniques. Finally, two simulation examples are given to illustrate the effectiveness of the proposed method. Supported by National Natural Science Foundation of China under Grant Nos. U1604146, U1404610, 61473115, 61203047, Science and Technology Research Project in Henan Province under Grant Nos. 152102210273, 162102410024, and Foundation for the University Technological Innovative Talents of Henan Province under Grant No. 18HASTIT019

Unveiling the Dependence of Glass Transitions on Mixing Thermodynamics in Miscible Systems

NASA Astrophysics Data System (ADS)

Tu, Wenkang; Wang, Yunxi; Li, Xin; Zhang, Peng; Tian, Yongjun; Jin, Shaohua; Wang, Li-Min

2015-02-01

The dependence of the glass transition in mixtures on mixing thermodynamics is examined by focusing on enthalpy of mixing, ΔHmix with the change in sign (positive vs. negative) and magnitude (small vs. large). The effects of positive and negative ΔHmix are demonstrated based on two isomeric systems of o- vs. m- methoxymethylbenzene (MMB) and o- vs. m- dibromobenzene (DBB) with comparably small absolute ΔHmix. Two opposite composition dependences of the glass transition temperature, Tg, are observed with the MMB mixtures showing a distinct negative deviation from the ideal mixing rule and the DBB mixtures having a marginally positive deviation. The system of 1, 2- propanediamine (12PDA) vs. propylene glycol (PG) with large and negative ΔHmix is compared with the systems of small ΔHmix, and a considerably positive Tg shift is seen. Models involving the properties of pure components such as Tg, glass transition heat capacity increment, ΔCp, and density, ρ, do not interpret the observed Tg shifts in the systems. In contrast, a linear correlation is revealed between ΔHmix and maximum Tg shifts.

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.

KINETIC ALFVÉN WAVE GENERATION BY LARGE-SCALE PHASE MIXING

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

Vásconez, C. L.; Pucci, F.; Valentini, F.

One view of the solar wind turbulence is that the observed highly anisotropic fluctuations at spatial scales near the proton inertial length d{sub p} may be considered as kinetic Alfvén waves (KAWs). In the present paper, we show how phase mixing of large-scale parallel-propagating Alfvén waves is an efficient mechanism for the production of KAWs at wavelengths close to d{sub p} and at a large propagation angle with respect to the magnetic field. Magnetohydrodynamic (MHD), Hall magnetohydrodynamic (HMHD), and hybrid Vlasov–Maxwell (HVM) simulations modeling the propagation of Alfvén waves in inhomogeneous plasmas are performed. In the linear regime, the rolemore » of dispersive effects is singled out by comparing MHD and HMHD results. Fluctuations produced by phase mixing are identified as KAWs through a comparison of polarization of magnetic fluctuations and wave-group velocity with analytical linear predictions. In the nonlinear regime, a comparison of HMHD and HVM simulations allows us to point out the role of kinetic effects in shaping the proton-distribution function. We observe the generation of temperature anisotropy with respect to the local magnetic field and the production of field-aligned beams. The regions where the proton-distribution function highly departs from thermal equilibrium are located inside the shear layers, where the KAWs are excited, this suggesting that the distortions of the proton distribution are driven by a resonant interaction of protons with KAW fluctuations. Our results are relevant in configurations where magnetic-field inhomogeneities are present, as, for example, in the solar corona, where the presence of Alfvén waves has been ascertained.« less

A big data approach to the development of mixed-effects models for seizure count data.

PubMed

Tharayil, Joseph J; Chiang, Sharon; Moss, Robert; Stern, John M; Theodore, William H; Goldenholz, Daniel M

2017-05-01

Our objective was to develop a generalized linear mixed model for predicting seizure count that is useful in the design and analysis of clinical trials. This model also may benefit the design and interpretation of seizure-recording paradigms. Most existing seizure count models do not include children, and there is currently no consensus regarding the most suitable model that can be applied to children and adults. Therefore, an additional objective was to develop a model that accounts for both adult and pediatric epilepsy. Using data from SeizureTracker.com, a patient-reported seizure diary tool with >1.2 million recorded seizures across 8 years, we evaluated the appropriateness of Poisson, negative binomial, zero-inflated negative binomial, and modified negative binomial models for seizure count data based on minimization of the Bayesian information criterion. Generalized linear mixed-effects models were used to account for demographic and etiologic covariates and for autocorrelation structure. Holdout cross-validation was used to evaluate predictive accuracy in simulating seizure frequencies. For both adults and children, we found that a negative binomial model with autocorrelation over 1 day was optimal. Using holdout cross-validation, the proposed model was found to provide accurate simulation of seizure counts for patients with up to four seizures per day. The optimal model can be used to generate more realistic simulated patient data with very few input parameters. The availability of a parsimonious, realistic virtual patient model can be of great utility in simulations of phase II/III clinical trials, epilepsy monitoring units, outpatient biosensors, and mobile Health (mHealth) applications. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

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.

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.

Elimination of trait blocks from multiple trait mixed model equations with singular (Co)variance parameter matrices

USDA-ARS?s Scientific Manuscript database

Transformations to multiple trait mixed model equations (MME) which are intended to improve computational efficiency in best linear unbiased prediction (BLUP) and restricted maximum likelihood (REML) are described. It is shown that traits that are expected or estimated to have zero residual variance...

D.b.h./crown diameter relationships in mixed Appalachian hardwood stands

Treesearch

Neil I. Lamson; Neil I. Lamson

1987-01-01

Linear regression formulae for predicting crown diameter as a function of stem diameter are presented for nine species found in 50- to 80-year-old mixed hardwood stands in north-central West Virginia. Generally, crown diameter was closely related to tolerance; more tolerant species had larger crowns.

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.

Rayleigh-enhanced attosecond sum-frequency polarization beats via twin color-locking noisy lights

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

Zhang Yanpeng; Li Long; Ma Ruiqiong

2005-07-15

Based on color-locking noisy field correlation, a time-delayed method is proposed to suppress the thermal effect, and the ultrafast longitudinal relaxation time can be measured even in an absorbing medium. One interesting feature in field-correlation effects is that Rayleigh-enhanced four-wave mixing (RFWM) with color-locking noisy light exhibits spectral symmetry and temporal asymmetry with no coherence spike at {tau}=0. Due to the interference between the Rayleigh-resonant signal and the nonresonant background, RFWM exhibits hybrid radiation-matter detuning with terahertz damping oscillations. The subtle Markovian high-order correlation effects have been investigated in the homodyne- or heterodyne-detected Rayleigh-enhanced attosecond sum-frequency polarization beats (RASPBs). Analyticmore » closed forms of fourth-order Markovian stochastic correlations are characterized for homodyne (quadratic) and heterodyne (linear) detection, respectively. Based on the polarization interference between two four-wave mixing processes, the phase-sensitive detection of RASPBs has also been used to obtain the real and imaginary parts of the Rayleigh resonance.« less

Knowledge and Behavioral Effects in Cardiovascular Health: Community Health Worker Health Disparities Initiative, 2007–2010

PubMed Central

Hurtado, Margarita; Yang, Manshu; Evensen, Christian; Windham, Amy; Ortiz, Gloria; Tracy, Rachel; Ivy, Edward Donnell

2014-01-01

Introduction Cardiovascular disease is the leading cause of death in the United States, and disparities in cardiovascular health exist among African Americans, American Indians, Hispanics, and Filipinos. The Community Health Worker Health Disparities Initiative of the National Heart, Lung, and Blood Institute (NHLBI) includes culturally tailored curricula taught by community health workers (CHWs) to improve knowledge and heart-healthy behaviors in these racial/ethnic groups. Methods We used data from 1,004 community participants in a 10-session curriculum taught by CHWs at 15 sites to evaluate the NHLBI’s health disparities initiative by using a 1-group pretest–posttest design. The curriculum addressed identification and management of cardiovascular disease risk factors. We used linear mixed effects and generalized linear mixed effects models to examine results. Results Average participant age was 48; 75% were female, 50% were Hispanic, 35% were African American, 8% were Filipino, and 7% were American Indian. Twenty-three percent reported a history of diabetes, and 37% reported a family history of heart disease. Correct pretest to posttest knowledge scores increased from 48% to 74% for heart healthy knowledge. The percentage of participants at the action or maintenance stage of behavior change increased from 41% to 85%. Conclusion Using the CHW model to implement community education with culturally tailored curricula may improve heart health knowledge and behaviors among minorities. Further studies should examine the influence of such programs on clinical risk factors for cardiovascular disease. PMID:24524426

Word skipping: effects of word length, predictability, spelling and reading skill.

PubMed

Slattery, Timothy J; Yates, Mark

2017-08-31

Readers eyes often skip over words as they read. Skipping rates are largely determined by word length; short words are skipped more than long words. However, the predictability of a word in context also impacts skipping rates. Rayner, Slattery, Drieghe and Liversedge (2011) reported an effect of predictability on word skipping for even long words (10-13 characters) that extend beyond the word identification span. Recent research suggests that better readers and spellers have an enhanced perceptual span (Veldre & Andrews, 2014). We explored whether reading and spelling skill interact with word length and predictability to impact word skipping rates in a large sample (N=92) of average and poor adult readers. Participants read the items from Rayner et al. (2011) while their eye movements were recorded. Spelling skill (zSpell) was assessed using the dictation and recognition tasks developed by Sally Andrews and colleagues. Reading skill (zRead) was assessed from reading speed (words per minute) and accuracy of three 120 word passages each with 10 comprehension questions. We fit linear mixed models to the target gaze duration data and generalized linear mixed models to the target word skipping data. Target word gaze durations were significantly predicted by zRead while, the skipping likelihoods were significantly predicted by zSpell. Additionally, for gaze durations, zRead significantly interacted with word predictability as better readers relied less on context to support word processing. These effects are discussed in relation to the lexical quality hypothesis and eye movement models of reading.

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.

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.

Dynamics of Transformation from Segregation to Mixed Wealth Cities

PubMed Central

Sahasranaman, Anand; Jensen, Henrik Jeldtoft

2016-01-01

We model the dynamics of a variation of the Schelling model for agents described simply by a continuously distributed variable—wealth. Agent movement is not dictated by agent choice as in the classic Schelling model, but by their wealth status. Agents move to neighborhoods where their wealth is not lesser than that of some proportion of their neighbors, the threshold level. As in the case of the classic Schelling model, we find here that wealth-based segregation occurs and persists. However, introducing uncertainty into the decision to move—that is, with some probability, if agents are allowed to move even though the threshold condition is contravened—we find that even for small proportions of such disallowed moves, the dynamics no longer yield segregation but instead sharply transition into a persistent mixed wealth distribution, consistent with empirical findings of Benenson, Hatna, and Or. We investigate the nature of this sharp transformation, and find that it is because of a non-linear relationship between allowed moves (moves where threshold condition is satisfied) and disallowed moves (moves where it is not). For small increases in disallowed moves, there is a rapid corresponding increase in allowed moves (before the rate of increase tapers off and tends to zero), and it is the effect of this non-linearity on the dynamics of the system that causes the rapid transition from a segregated to a mixed wealth state. The contravention of the tolerance condition, sanctioning disallowed moves, could be interpreted as public policy interventions to drive de-segregation. Our finding therefore suggests that it might require limited, but continually implemented, public intervention—just sufficient to enable a small, persistently sustained fraction of disallowed moves so as to trigger the dynamics that drive the transformation from a segregated to mixed equilibrium. PMID:27861578

Blood biomarkers in male and female participants after an Ironman-distance triathlon.

PubMed

Danielsson, Tom; Carlsson, Jörg; Schreyer, Hendrik; Ahnesjö, Jonas; Ten Siethoff, Lasse; Ragnarsson, Thony; Tugetam, Åsa; Bergman, Patrick

2017-01-01

While overall physical activity is clearly associated with a better short-term and long-term health, prolonged strenuous physical activity may result in a rise in acute levels of blood-biomarkers used in clinical practice for diagnosis of various conditions or diseases. In this study, we explored the acute effects of a full Ironman-distance triathlon on biomarkers related to heart-, liver-, kidney- and skeletal muscle damage immediately post-race and after one week's rest. We also examined if sex, age, finishing time and body composition influenced the post-race values of the biomarkers. A sample of 30 subjects was recruited (50% women) to the study. The subjects were evaluated for body composition and blood samples were taken at three occasions, before the race (T1), immediately after (T2) and one week after the race (T3). Linear regression models were fitted to analyse the independent contribution of sex and finishing time controlled for weight, body fat percentage and age, on the biomarkers at the termination of the race (T2). Linear mixed models were fitted to examine if the biomarkers differed between the sexes over time (T1-T3). Being male was a significant predictor of higher post-race (T2) levels of myoglobin, CK, and creatinine levels and body weight was negatively associated with myoglobin. In general, the models were unable to explain the variation of the dependent variables. In the linear mixed models, an interaction between time (T1-T3) and sex was seen for myoglobin and creatinine, in which women had a less pronounced response to the race. Overall women appear to tolerate the effects of prolonged strenuous physical activity better than men as illustrated by their lower values of the biomarkers both post-race as well as during recovery.

Improving the Accuracy of Mapping Urban Vegetation Carbon Density by Combining Shadow Remove, Spectral Unmixing Analysis and Spatial Modeling

NASA Astrophysics Data System (ADS)

Qie, G.; Wang, G.; Wang, M.

2016-12-01

Mixed pixels and shadows due to buildings in urban areas impede accurate estimation and mapping of city vegetation carbon density. In most of previous studies, these factors are often ignored, which thus result in underestimation of city vegetation carbon density. In this study we presented an integrated methodology to improve the accuracy of mapping city vegetation carbon density. Firstly, we applied a linear shadow remove analysis (LSRA) on remotely sensed Landsat 8 images to reduce the shadow effects on carbon estimation. Secondly, we integrated a linear spectral unmixing analysis (LSUA) with a linear stepwise regression (LSR), a logistic model-based stepwise regression (LMSR) and k-Nearest Neighbors (kNN), and utilized and compared the integrated models on shadow-removed images to map vegetation carbon density. This methodology was examined in Shenzhen City of Southeast China. A data set from a total of 175 sample plots measured in 2013 and 2014 was used to train the models. The independent variables statistically significantly contributing to improving the fit of the models to the data and reducing the sum of squared errors were selected from a total of 608 variables derived from different image band combinations and transformations. The vegetation fraction from LSUA was then added into the models as an important independent variable. The estimates obtained were evaluated using a cross-validation method. Our results showed that higher accuracies were obtained from the integrated models compared with the ones using traditional methods which ignore the effects of mixed pixels and shadows. This study indicates that the integrated method has great potential on improving the accuracy of urban vegetation carbon density estimation. Key words: Urban vegetation carbon, shadow, spectral unmixing, spatial modeling, Landsat 8 images

A linear shock cell model for non-circular jets using conformal mapping with a pseudo-spectral hybrid scheme

NASA Technical Reports Server (NTRS)

Bhat, Thonse R. S.; Baty, Roy S.; Morris, Philip J.

1990-01-01

The shock structure in non-circular supersonic jets is predicted using a linear model. This model includes the effects of the finite thickness of the mixing layer and the turbulence in the jet shear layer. A numerical solution is obtained using a conformal mapping grid generation scheme with a hybrid pseudo-spectral discretization method. The uniform pressure perturbation at the jet exit is approximated by a Fourier-Mathieu series. The pressure at downstream locations is obtained from an eigenfunction expansion that is matched to the pressure perturbation at the jet exit. Results are presented for a circular jet and for an elliptic jet of aspect ratio 2.0. Comparisons are made with experimental data.

Simulating quantum spin Hall effect in the topological Lieb lattice of a linear circuit network

NASA Astrophysics Data System (ADS)

Zhu, Weiwei; Hou, Shanshan; Long, Yang; Chen, Hong; Ren, Jie

2018-02-01

Inspired by the topological insulator circuit experimentally proposed by Jia Ningyuan et al. [Phys. Rev. X 5, 021031 (2015), 10.1103/PhysRevX.5.021031], we theoretically realize the topological Lieb lattice, a line-centered square lattice with rich topological properties, in a radio-frequency circuit. We design a specific capacitor-inductor connection to resemble the intrinsic spin-orbit coupling and construct the analog spin by mixing degrees of freedom of voltages. As such, we are able to simulate the quantum spin Hall effect in the topological Lieb lattice of linear circuits. We then investigate the spin-resolved topological edge mode and the topological phase transition of the band structure varied with capacitances. Finally, we discuss the extension of the π /2 phase change of hopping between sites to arbitrary phase values. Our results may find implications in engineering microwave topological metamaterials for signal transmission and energy harvesting.

The morphology of blends of linear and branched polyethylenes in solid state by SANS

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

Wignall, G.D.; Londono, J.D.; Alamo, R.G.

1994-12-31

In a previous paper the authors have shown how small-angle neutron and X-ray scattering (SANS, SAXS) can be used to determine the melt compatibility of different polyolefins, including high-density (HD), low-density (LD), and linear low density (LLD) polyethylene. Such blends have attained widespread commercial applications, though the understanding of the mechanical and melt-flow properties of such blends has hitherto been handicapped by the absence of a consensus concerning the degree of mixing of the components, both in the melt and solid states. Recent SANS data indicate that for HDPE/LDPE blends, the melt is homogeneous for all compositions after proper accountingmore » for H/D isotope effects. In this publication the authors use complementary SANS, DSC, and SAXS to examine the types of morphologies and the different degrees of phase separation which may arise via crystallization effects on cooling from a homogeneous melt.« less

The morphology of blends of linear and branched polyethylenes in solid state by SANS

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

Wignall, G.D.; Londono, J.D.; Alamo, R.G.

1995-03-01

In a previous paper, the authors have shown how small-angle neutron and X-ray scattering (SANS, SAXS) can be used to determine the melt compatibility of different polyolefins, including high-density (HD), low-density (LD), and linear low density (LLD) polyethylene. Such blends have attained widespread commercial applications, though the understanding of the mechanical and melt-flow properties of such blends has hitherto been handicapped by the absence of a consensus concerning the degree of mixing of the components, both in the melt and solid states. Recent SANS data indicate that for HDPE/LDPE blends, the melt is homogeneous for all compositions after proper accountingmore » for H/D isotope effects. In this publication the authors use complementary SANS, DSC, and SAXS to examine the types of morphologies and the different degrees of phase separation which may arise via crystallization effects on cooling from a homogeneous melt.« less

Analyses of a heterogeneous lattice hydrodynamic model with low and high-sensitivity vehicles

NASA Astrophysics Data System (ADS)

Kaur, Ramanpreet; Sharma, Sapna

2018-06-01

Basic lattice model is extended to study the heterogeneous traffic by considering the optimal current difference effect on a unidirectional single lane highway. Heterogeneous traffic consisting of low- and high-sensitivity vehicles is modeled and their impact on stability of mixed traffic flow has been examined through linear stability analysis. The stability of flow is investigated in five distinct regions of the neutral stability diagram corresponding to the amount of higher sensitivity vehicles present on road. In order to investigate the propagating behavior of density waves non linear analysis is performed and near the critical point, the kink antikink soliton is obtained by driving mKdV equation. The effect of fraction parameter corresponding to high sensitivity vehicles is investigated and the results indicates that the stability rise up due to the fraction parameter. The theoretical findings are verified via direct numerical simulation.

Analysis of Modeling Assumptions used in Production Cost Models for Renewable Integration Studies

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

Stoll, Brady; Brinkman, Gregory; Townsend, Aaron

2016-01-01

Renewable energy integration studies have been published for many different regions exploring the question of how higher penetration of renewable energy will impact the electric grid. These studies each make assumptions about the systems they are analyzing; however the effect of many of these assumptions has not been yet been examined and published. In this paper we analyze the impact of modeling assumptions in renewable integration studies, including the optimization method used (linear or mixed-integer programming) and the temporal resolution of the dispatch stage (hourly or sub-hourly). We analyze each of these assumptions on a large and a small systemmore » and determine the impact of each assumption on key metrics including the total production cost, curtailment of renewables, CO2 emissions, and generator starts and ramps. Additionally, we identified the impact on these metrics if a four-hour ahead commitment step is included before the dispatch step and the impact of retiring generators to reduce the degree to which the system is overbuilt. We find that the largest effect of these assumptions is at the unit level on starts and ramps, particularly for the temporal resolution, and saw a smaller impact at the aggregate level on system costs and emissions. For each fossil fuel generator type we measured the average capacity started, average run-time per start, and average number of ramps. Linear programming results saw up to a 20% difference in number of starts and average run time of traditional generators, and up to a 4% difference in the number of ramps, when compared to mixed-integer programming. Utilizing hourly dispatch instead of sub-hourly dispatch saw no difference in coal or gas CC units for either start metric, while gas CT units had a 5% increase in the number of starts and 2% increase in the average on-time per start. The number of ramps decreased up to 44%. The smallest effect seen was on the CO2 emissions and total production cost, with a 0.8% and 0.9% reduction respectively when using linear programming compared to mixed-integer programming and 0.07% and 0.6% reduction, respectively, in the hourly dispatch compared to sub-hourly dispatch.« less

Mixing of ultrasonic Lamb waves in thin plates with quadratic nonlinearity.

PubMed

Li, Feilong; Zhao, Youxuan; Cao, Peng; Hu, Ning

2018-07-01

This paper investigates the propagation of Lamb waves in thin plates with quadratic nonlinearity by one-way mixing method using numerical simulations. It is shown that an A 0 -mode wave can be generated by a pair of S 0 and A 0 mode waves only when mixing condition is satisfied, and mixing wave signals are capable of locating the damage zone. Additionally, it is manifested that the acoustic nonlinear parameter increases linearly with quadratic nonlinearity but monotonously with the size of mixing zone. Furthermore, because of frequency deviation, the waveform of the mixing wave changes significantly from a regular diamond shape to toneburst trains. Copyright © 2018 Elsevier B.V. All rights reserved.

Multiple injected and natural conservative tracers quantify mixing in a stream confluence affected by acid mine drainage near Silverton, Colorado

NASA Astrophysics Data System (ADS)

Schemel, Laurence E.; Cox, Marisa H.; Runkel, Robert L.; Kimball, Briant A.

2006-08-01

The acidic discharge from Cement Creek, containing elevated concentrations of dissolved metals and sulphate, mixed with the circumneutral-pH Animas River over a several hundred metre reach (mixing zone) near Silverton, CO, during this study. Differences in concentrations of Ca, Mg, Si, Sr, and SO42- between the creek and the river were sufficiently large for these analytes to be used as natural tracers in the mixing zone. In addition, a sodium chloride (NaCl) tracer was injected into Cement Creek, which provided a Cl- reference tracer in the mixing zone. Conservative transport of the dissolved metals and sulphate through the mixing zone was verified by mass balances and by linear mixing plots relative to the injected reference tracer. At each of seven sites in the mixing zone, five samples were collected at evenly spaced increments of the observed across-channel gradients, as determined by specific conductance. This created sets of samples that adequately covered the ranges of mixtures (mixing ratios, in terms of the fraction of Animas River water, %AR). Concentratis measured in each mixing zone sample and in the upstream Animas River and Cement Creek were used to compute %AR for the reference and natural tracers. Values of %AR from natural tracers generally showed good agreement with values from the reference tracer, but variability in discharge and end-member concentrations and analytical errors contributed to unexpected outlier values for both injected and natural tracers. The median value (MV) %AR (calculated from all of the tracers) reduced scatter in the mixing plots for the dissolved metals, indicating that the MV estimate reduced the effects of various potential errors that could affect any tracer.

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.

Experimental study of linear and nonlinear regimes of density-driven instabilities induced by CO{sub 2} dissolution in water

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

Outeda, R.; D'Onofrio, A.; El Hasi, C.

Density driven instabilities produced by CO{sub 2} (gas) dissolution in water containing a color indicator were studied in a Hele Shaw cell. The images were analyzed and instability patterns were characterized by mixing zone temporal evolution, dispersion curves, and the growth rate for different CO{sub 2} pressures and different color indicator concentrations. The results obtained from an exhaustive analysis of experimental data show that this system has a different behaviour in the linear regime of the instabilities (when the growth rate has a linear dependence with time), from the nonlinear regime at longer times. At short times using a colormore » indicator to see the evolution of the pattern, the images show that the effects of both the color indicator and CO{sub 2} pressure are of the same order of magnitude: The growth rates are similar and the wave numbers are in the same range (0–30 cm{sup −1}) when the system is unstable. Although in the linear regime the dynamics is affected similarly by the presence of the indicator and CO{sub 2} pressure, in the nonlinear regime, the influence of the latter is clearly more pronounced than the effects of the color indicator.« less

Radio Propagation Prediction Software for Complex Mixed Path Physical Channels

DTIC Science & Technology

2006-08-14

63 4.4.6. Applied Linear Regression Analysis in the Frequency Range 1-50 MHz 69 4.4.7. Projected Scaling to...4.4.6. Applied Linear Regression Analysis in the Frequency Range 1-50 MHz In order to construct a comprehensive numerical algorithm capable of

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

Treesearch

Fabian Uzoh; William W. Oliver

2006-01-01

A height increment model is developed and evaluated for individual trees of ponderosa pine throughout the species range in western United States. The data set used in this study came from long-term permanent research plots in even-aged, pure stands both planted and of natural origin. The data base consists of six levels-of-growing stock studies supplemented by initial...

Spider diversity in coffee agroecosystems: the influence of agricultural intensification and aggressive ants.

PubMed

Marín, Linda; Perfecto, Ivette

2013-04-01

Spiders are a very diverse group of invertebrate predators found in agroecosystems and natural systems. However, spider distribution, abundance, and eventually their ecological function in ecosystems can be influenced by abiotic and biotic factors such as agricultural intensification and dominant ants. Here we explore the influence of both agricultural intensification and the dominant arboreal ant Azteca instabilis on the spider community in coffee agroecosystems in southern Mexico. To measure the influence of the arboreal ant Azteca instabilis (F. Smith) on the spider community inhabiting the coffee layer of coffee agroecosystems, spiders were collected from coffee plants that were and were not patrolled by the ant in sites differing in agricultural intensification. For 2008, generalized linear mixed models showed that spider diversity was affected positively by agricultural intensification but not by the ant. However, results suggested that some spider species were associated with A. instabilis. Therefore, in 2009 we concentrated our research on the effect of A. instabilis on spider diversity and composition. For 2009, generalized linear mixed models show that spider richness and abundance per plant were significantly higher in the presence of A. instabilis. In addition, analyses of visual counts of insects and sticky traps data show that more resources were present in plants patrolled by the ant. The positive effect of A. instabilis on spiders seems to be caused by at least two mechanisms: high abundance of insects and protection against predators.

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.

Mixed Linear/Square-Root Encoded Single Slope Ramp Provides a Fast, Low Noise Analog to Digital Converter with Very High Linearity for Focal Plane Arrays

NASA Technical Reports Server (NTRS)

Wrigley, Christopher James (Inventor); Hancock, Bruce R. (Inventor); Cunningham, Thomas J. (Inventor); Newton, Kenneth W. (Inventor)

2014-01-01

An analog-to-digital converter (ADC) converts pixel voltages from a CMOS image into a digital output. A voltage ramp generator generates a voltage ramp that has a linear first portion and a non-linear second portion. A digital output generator generates a digital output based on the voltage ramp, the pixel voltages, and comparator output from an array of comparators that compare the voltage ramp to the pixel voltages. A return lookup table linearizes the digital output values.

Iterative methods for mixed finite element equations

NASA Technical Reports Server (NTRS)

Nakazawa, S.; Nagtegaal, J. C.; Zienkiewicz, O. C.

1985-01-01

Iterative strategies for the solution of indefinite system of equations arising from the mixed finite element method are investigated in this paper with application to linear and nonlinear problems in solid and structural mechanics. The augmented Hu-Washizu form is derived, which is then utilized to construct a family of iterative algorithms using the displacement method as the preconditioner. Two types of iterative algorithms are implemented. Those are: constant metric iterations which does not involve the update of preconditioner; variable metric iterations, in which the inverse of the preconditioning matrix is updated. A series of numerical experiments is conducted to evaluate the numerical performance with application to linear and nonlinear model problems.

Modeling Learning in Doubly Multilevel Binary Longitudinal Data Using Generalized Linear Mixed Models: An Application to Measuring and Explaining Word Learning.

PubMed

Cho, Sun-Joo; Goodwin, Amanda P

2016-04-01

When word learning is supported by instruction in experimental studies for adolescents, word knowledge outcomes tend to be collected from complex data structure, such as multiple aspects of word knowledge, multilevel reader data, multilevel item data, longitudinal design, and multiple groups. This study illustrates how generalized linear mixed models can be used to measure and explain word learning for data having such complexity. Results from this application provide deeper understanding of word knowledge than could be attained from simpler models and show that word knowledge is multidimensional and depends on word characteristics and instructional contexts.

Heavy neutrino mixing and single production at linear collider

NASA Astrophysics Data System (ADS)

Gluza, J.; Maalampi, J.; Raidal, M.; Zrałek, M.

1997-02-01

We study the single production of heavy neutrinos via the processes e- e+ -> νN and e- γ -> W- N at future linear colliders. As a base of our considerations we take a wide class of models, both with vanishing and non-vanishing left-handed Majorana neutrino mass matrix mL. We perform a model independent analyses of the existing experimental data and find connections between the characteristic of heavy neutrinos (masses, mixings, CP eigenvalues) and the mL parameters. We show that with the present experimental constraints heavy neutrino masses almost up to the collision energy can be tested in the future experiments.

Highly non-linear solid core photonic crystal fiber with one nano hole

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

Gangwar, Rahul Kumar, E-mail: rahul0889@gmail.com; Bhardwaj, Vanita, E-mail: bhardwajphy12@gmail.com; Singh, Vinod Kumar, E-mail: singh.vk.ap@ismdhanbad.co.in

2015-08-28

The numerical study of newly designed solid core photonic crystal fiber (SCPCF) having three hexagonal air hole rings in cladding region and one small nano hole at the center are presented. By using full vectorial finite element method (FV-FEM), we analyses the optical properties like effective area, nonlinearity and confinement loss of the proposed PCF. Results show that the change in core diameter controls the effective area, nonlinearity and confinement loss. A low effective area (3.34 µm{sup 2}), high nonlinearity (36.34 W{sup −1}km{sup −1}) and low confinement loss (0.00106 dB/km) are achieved at the communication wavelength 1.55 µm for themore » SCPCF having core air hole diameter 0.10 µm, cladding air holes diameter 1.00 µm and pitch 2.50 µm. This type of PCF is very useful in non-linear applications such as supercontinuum generation, four wave mixing, second harmonic generation etc.« less

Identifying pleiotropic genes in genome-wide association studies from related subjects using the linear mixed model and Fisher combination function.

PubMed

Yang, James J; Williams, L Keoki; Buu, Anne

2017-08-24

A multivariate genome-wide association test is proposed for analyzing data on multivariate quantitative phenotypes collected from related subjects. The proposed method is a two-step approach. The first step models the association between the genotype and marginal phenotype using a linear mixed model. The second step uses the correlation between residuals of the linear mixed model to estimate the null distribution of the Fisher combination test statistic. The simulation results show that the proposed method controls the type I error rate and is more powerful than the marginal tests across different population structures (admixed or non-admixed) and relatedness (related or independent). The statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that applying the multivariate association test may facilitate identification of the pleiotropic genes contributing to the risk for alcohol dependence commonly expressed by four correlated phenotypes. This study proposes a multivariate method for identifying pleiotropic genes while adjusting for cryptic relatedness and population structure between subjects. The two-step approach is not only powerful but also computationally efficient even when the number of subjects and the number of phenotypes are both very large.

Interpreting spectral unmixing coefficients: From spectral weights to mass fractions

NASA Astrophysics Data System (ADS)

Grumpe, Arne; Mengewein, Natascha; Rommel, Daniela; Mall, Urs; Wöhler, Christian

2018-01-01

It is well known that many common planetary minerals exhibit prominent absorption features. Consequently, the analysis of spectral reflectance measurements has become a major tool of remote sensing. Quantifying the mineral abundances, however, is not a trivial task. The interaction between the incident light rays and particulate surfaces, e.g., the lunar regolith, leads to a non-linear relationship between the reflectance spectra of the pure minerals, the so-called ;endmembers;, and the surface's reflectance spectrum. It is, however, possible to transform the non-linear reflectance mixture into a linear mixture of single-scattering albedos of the Hapke model. The abundances obtained by inverting the linear single-scattering albedo mixture may be interpreted as volume fractions which are weighted by the endmember's extinction coefficient. Commonly, identical extinction coefficients are assumed throughout all endmembers and the obtained volume fractions are converted to mass fractions using either measured or assumed densities. In theory, the proposed method may cover different grain sizes if each grain size range of a mineral is treated as a distinct endmember. Here, we present a method to transform the mixing coefficients to mass fractions for arbitrary combinations of extinction coefficients and densities. The required parameters are computed from reflectance measurements of well defined endmember mixtures. Consequently, additional measurements, e.g., the endmember density, are no longer required. We evaluate the method based on laboratory measurements and various results presented in the literature, respectively. It is shown that the procedure transforms the mixing coefficients to mass fractions yielding an accuracy comparable to carefully calibrated laboratory measurements without additional knowledge. For our laboratory measurements, the square root of the mean squared error is less than 4.82 wt%. In addition, the method corrects for systematic effects originating from mixtures of endmembers showing a highly varying albedo, e.g., plagioclase and pyroxene.

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 ).

Global determinants of mortality in under 5s: 10 year worldwide longitudinal study.

PubMed

Hanf, Matthieu; Nacher, Mathieu; Guihenneuc, Chantal; Tubert-Bitter, Pascale; Chavance, Michel

2013-11-08

To assess at country level the association of mortality in under 5s with a large set of determinants. Longitudinal study. 193 United Nations member countries, 2000-09. Yearly data between 2000 and 2009 based on 12 world development indicators were used in a multivariable general additive mixed model allowing for non-linear relations and lag effects. National rate of deaths in under 5s per 1000 live births The model retained the variables: gross domestic product per capita; percentage of the population having access to improved water sources, having access to improved sanitation facilities, and living in urban areas; adolescent fertility rate; public health expenditure per capita; prevalence of HIV; perceived level of corruption and of violence; and mean number of years in school for women of reproductive age. Most of these variables exhibited non-linear behaviours and lag effects. By providing a unified framework for mortality in under 5s, encompassing both high and low income countries this study showed non-linear behaviours and lag effects of known or suspected determinants of mortality in this age group. Although some of the determinants presented a linear action on log mortality indicating that whatever the context, acting on them would be a pertinent strategy to effectively reduce mortality, others had a threshold based relation potentially mediated by lag effects. These findings could help designing efficient strategies to achieve maximum progress towards millennium development goal 4, which aims to reduce mortality in under 5s by two thirds between 1990 and 2015.

Inexact fuzzy-stochastic mixed-integer programming approach for long-term planning of waste management--Part A: methodology.

PubMed

Guo, P; Huang, G H

2009-01-01

In this study, an inexact fuzzy chance-constrained two-stage mixed-integer linear programming (IFCTIP) approach is proposed for supporting long-term planning of waste-management systems under multiple uncertainties in the City of Regina, Canada. The method improves upon the existing inexact two-stage programming and mixed-integer linear programming techniques by incorporating uncertainties expressed as multiple uncertainties of intervals and dual probability distributions within a general optimization framework. The developed method can provide an effective linkage between the predefined environmental policies and the associated economic implications. Four special characteristics of the proposed method make it unique compared with other optimization techniques that deal with uncertainties. Firstly, it provides a linkage to predefined policies that have to be respected when a modeling effort is undertaken; secondly, it is useful for tackling uncertainties presented as intervals, probabilities, fuzzy sets and their incorporation; thirdly, it facilitates dynamic analysis for decisions of facility-expansion planning and waste-flow allocation within a multi-facility, multi-period, multi-level, and multi-option context; fourthly, the penalties are exercised with recourse against any infeasibility, which permits in-depth analyses of various policy scenarios that are associated with different levels of economic consequences when the promised solid waste-generation rates are violated. In a companion paper, the developed method is applied to a real case for the long-term planning of waste management in the City of Regina, Canada.

On relation between scalar interfaces and vorticity in inviscid flows

NASA Astrophysics Data System (ADS)

Ramesh, O. N.; Patwardhan, Saurabh

2013-11-01

A great variety of applications like pollutant mixing in the atmosphere, mixing of reactants in combustion highlight the importance of passive scalar dynamics in fluid flows. The other dynamically important variable in the study of fluid flow is the vorticity. Vorticity though, unlike a passive scalar, does affect the fluid motion. The dynamics of scalar (linear) and vorticity (non-linear) are governed by the equations which inherently have different characteristics. This paper addresses the question of the faithfulness of representation of vorticity by scalar marker and the motivation for this comes from the experiment of Head and Bandyopadhyay (1981) which showed the existence of coherent vortices by using smoke flow visualization in a turbulent boundary layer. We will show analytically in regions where the molecular diffusion effects are negligible, the vorticity and scalar gradients are orthogonal to each other. The iso- surface of scalar follows the vorticity in an inviscid situation. Also, we will demonstrate that in the case of unsteady burgers vortex and vortex shedding behind a finite circular cylinder, the scalar gradient is orthogonal to vorticity and inner product of vorticity and scalar gradients is zero in regions away from the wall.

Spatial Holmboe instability

NASA Astrophysics Data System (ADS)

Ortiz, Sabine; Chomaz, Jean-Marc; Loiseleux, Thomas

2002-08-01

In mixing-layers between two parallel streams of different densities, shear and gravity effects interplay; buoyancy acts as a restoring force and the Kelvin-Helmholtz mode is known to be stabilized by the stratification. If the density interface is sharp enough, two new instability modes, known as Holmboe modes, appear, propagating in opposite directions. This mechanism has been studied in the temporal instability framework. The present paper analyzes the associated spatial instability problem. It considers, in the Boussinesq approximation, two immiscible inviscid fluids with a piecewise linear broken-line velocity profile. We show how the classical scenario for transition between absolute and convective instability should be modified due to the presence of propagating waves. In the convective region, the spatial theory is relevant and the slowest propagating wave is shown to be the most spatially amplified, as suggested by intuition. Predictions of spatial linear theory are compared with mixing-layer [C. G. Koop and F. K. Browand, J. Fluid Mech. 93, 135 (1979)] and exchange flow [G. Pawlak and L. Armi, J. Fluid Mech. 376, 1 (1999)] experiments. The physical mechanism for Holmboe mode destabilization is analyzed via an asymptotic expansion that predicts the absolute instability domain at large Richardson number.

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.

Coordinated Control Method of Voltage and Reactive Power for Active Distribution Networks Based on Soft Open Point

DOE PAGES

Li, Peng; Ji, Haoran; Wang, Chengshan; ...

2017-03-22

The increasing penetration of distributed generators (DGs) exacerbates the risk of voltage violations in active distribution networks (ADNs). The conventional voltage regulation devices limited by the physical constraints are difficult to meet the requirement of real-time voltage and VAR control (VVC) with high precision when DGs fluctuate frequently. But, soft open point (SOP), a flexible power electronic device, can be used as the continuous reactive power source to realize the fast voltage regulation. Considering the cooperation of SOP and multiple regulation devices, this paper proposes a coordinated VVC method based on SOP for ADNs. Firstly, a time-series model of coordi-natedmore » VVC is developed to minimize operation costs and eliminate voltage violations of ADNs. Then, by applying the linearization and conic relaxation, the original nonconvex mixed-integer non-linear optimization model is converted into a mixed-integer second-order cone programming (MISOCP) model which can be efficiently solved to meet the requirement of voltage regulation rapidity. Here, we carried out some case studies on the IEEE 33-node system and IEEE 123-node system to illustrate the effectiveness of the proposed method.« less

Coordinated Control Method of Voltage and Reactive Power for Active Distribution Networks Based on Soft Open Point

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

Li, Peng; Ji, Haoran; Wang, Chengshan

The increasing penetration of distributed generators (DGs) exacerbates the risk of voltage violations in active distribution networks (ADNs). The conventional voltage regulation devices limited by the physical constraints are difficult to meet the requirement of real-time voltage and VAR control (VVC) with high precision when DGs fluctuate frequently. But, soft open point (SOP), a flexible power electronic device, can be used as the continuous reactive power source to realize the fast voltage regulation. Considering the cooperation of SOP and multiple regulation devices, this paper proposes a coordinated VVC method based on SOP for ADNs. Firstly, a time-series model of coordi-natedmore » VVC is developed to minimize operation costs and eliminate voltage violations of ADNs. Then, by applying the linearization and conic relaxation, the original nonconvex mixed-integer non-linear optimization model is converted into a mixed-integer second-order cone programming (MISOCP) model which can be efficiently solved to meet the requirement of voltage regulation rapidity. Here, we carried out some case studies on the IEEE 33-node system and IEEE 123-node system to illustrate the effectiveness of the proposed method.« less

Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast.

PubMed

Poos, Alexandra M; Maicher, André; Dieckmann, Anna K; Oswald, Marcus; Eils, Roland; Kupiec, Martin; Luke, Brian; König, Rainer

2016-06-02

Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Resolving Mixed Algal Species in Hyperspectral Images

PubMed Central

Mehrubeoglu, Mehrube; Teng, Ming Y.; Zimba, Paul V.

2014-01-01

We investigated a lab-based hyperspectral imaging system's response from pure (single) and mixed (two) algal cultures containing known algae types and volumetric combinations to characterize the system's performance. The spectral response to volumetric changes in single and combinations of algal mixtures with known ratios were tested. Constrained linear spectral unmixing was applied to extract the algal content of the mixtures based on abundances that produced the lowest root mean square error. Percent prediction error was computed as the difference between actual percent volumetric content and abundances at minimum RMS error. Best prediction errors were computed as 0.4%, 0.4% and 6.3% for the mixed spectra from three independent experiments. The worst prediction errors were found as 5.6%, 5.4% and 13.4% for the same order of experiments. Additionally, Beer-Lambert's law was utilized to relate transmittance to different volumes of pure algal suspensions demonstrating linear logarithmic trends for optical property measurements. PMID:24451451

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.

Linear mixing model applied to AVHRR LAC data

NASA Technical Reports Server (NTRS)

Holben, Brent N.; Shimabukuro, Yosio E.

1993-01-01

A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55 - 3.93 microns channel was extracted and used with the two reflective channels 0.58 - 0.68 microns and 0.725 - 1.1 microns to run a Constraine Least Squares model to generate vegetation, soil, and shade fraction images for an area in the Western region of Brazil. The Landsat Thematic Mapper data covering the Emas National park region was used for estimating the spectral response of the mixture components and for evaluating the mixing model results. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse resolution data for global studies.

Separate-channel analysis of two-channel microarrays: recovering inter-spot information.

PubMed

Smyth, Gordon K; Altman, Naomi S

2013-05-26

Two-channel (or two-color) microarrays are cost-effective platforms for comparative analysis of gene expression. They are traditionally analysed in terms of the log-ratios (M-values) of the two channel intensities at each spot, but this analysis does not use all the information available in the separate channel observations. Mixed models have been proposed to analyse intensities from the two channels as separate observations, but such models can be complex to use and the gain in efficiency over the log-ratio analysis is difficult to quantify. Mixed models yield test statistics for the null distributions can be specified only approximately, and some approaches do not borrow strength between genes. This article reformulates the mixed model to clarify the relationship with the traditional log-ratio analysis, to facilitate information borrowing between genes, and to obtain an exact distributional theory for the resulting test statistics. The mixed model is transformed to operate on the M-values and A-values (average log-expression for each spot) instead of on the log-expression values. The log-ratio analysis is shown to ignore information contained in the A-values. The relative efficiency of the log-ratio analysis is shown to depend on the size of the intraspot correlation. A new separate channel analysis method is proposed that assumes a constant intra-spot correlation coefficient across all genes. This approach permits the mixed model to be transformed into an ordinary linear model, allowing the data analysis to use a well-understood empirical Bayes analysis pipeline for linear modeling of microarray data. This yields statistically powerful test statistics that have an exact distributional theory. The log-ratio, mixed model and common correlation methods are compared using three case studies. The results show that separate channel analyses that borrow strength between genes are more powerful than log-ratio analyses. The common correlation analysis is the most powerful of all. The common correlation method proposed in this article for separate-channel analysis of two-channel microarray data is no more difficult to apply in practice than the traditional log-ratio analysis. It provides an intuitive and powerful means to conduct analyses and make comparisons that might otherwise not be possible.

An optimal proportion of mixing broad-leaved forest for enhancing the effective productivity of moso bamboo.

PubMed

Cheng, Xiao-Fei; Shi, Pei-Jian; Hui, Cang; Wang, Fu-Sheng; Liu, Guo-Hua; Li, Bai-Lian

2015-04-01

Moso bamboos (Phyllostachys edulis) are important forestry plants in southern China, with substantial roles to play in regional economic and ecological systems. Mixing broad-leaved forests and moso bamboos is a common management practice in China, and it is fundamental to elucidate the interactions between broad-leaved trees and moso bamboos for ensuring the sustainable provision of ecosystem services. We examine how the proportion of broad-leaved forest in a mixed managed zone, topology, and soil profile affects the effective productivity of moso bamboos (i.e., those with significant economic value), using linear regression and generalized additive models. Bamboo's diameter at breast height follows a Weibull distribution. The importance of these variables to bamboo productivity is, respectively, slope (25.9%), the proportion of broad-leaved forest (24.8%), elevation (23.3%), gravel content by volume (16.6%), slope location (8.3%), and soil layer thickness (1.2%). Highest productivity is found on the 25° slope, with a 600-m elevation, and 30% broad-leaved forest. As such, broad-leaved forest in the upper slope can have a strong influence on the effective productivity of moso bamboo, ranking only after slope and before elevation. These factors can be considered in future management practice.

Nonlinear Wave Mixing Technique for Nondestructive Assessment of Infrastructure Materials

NASA Astrophysics Data System (ADS)

Ju, Taeho

To operate safely, structures and components need to be inspected or monitored either periodically or in real time for potential failure. For this purpose, ultrasonic nondestructive evaluation (NDE) techniques have been used extensively. Most of these ultrasonic NDE techniques utilize only the linear behavior of the ultrasound. These linear techniques are effective in detecting discontinuities in materials such as cracks, voids, interfaces, inclusions, etc. However, in many engineering materials, it is the accumulation of microdamage that leads to degradation and eventual failure of a component. Unfortunately, it is difficult for linear ultrasonic NDE techniques to characterize or quantify such damage. On the other hand, the acoustic nonlinearity parameter (ANLP) of a material is often positively correlated with such damage in a material. Thus, nonlinear ultrasonic NDE methods have been used in recently years to characterize cumulative damage such as fatigue in metallic materials, aging in polymeric materials, and degradation of cement-based materials due to chemical reactions. In this thesis, we focus on developing a suit of novel nonlinear ultrasonic NDE techniques based on the interactions of nonlinear ultrasonic waves, namely wave mixing. First, a noncollinear wave mixing technique is developed to detect localized damage in a homogeneous material by using a pair of noncollinear a longitudinal wave (L-wave) and a shear wave (S-wave). This pair of incident waves make it possible to conduct NDE from a single side of the component, a condition that is often encountered in practical applications. The proposed noncollinear wave mixing technique is verified experimentally by carrying out measurements on aluminum alloy (AA 6061) samples. Numerical simulations using the Finite Element Method (FEM) are also conducted to further demonstrate the potential of the proposed technique to detect localized damage in structural components. Second, the aforementioned nonlinear mixing technique is adapted to develop an NDE technique for characterizing thermal aging of adhesive joints. To this end, a nonlinear spring model is used to simulate the effect of the adhesive layer. Based on this nonlinear spring model, analytical expressions of the resonant wave generated by the adhesive layers is obtained through an asymptotic analysis when the adhesive layer thickness is much smaller than the pertinent wavelength. The solutions are expressed in terms of the properties of the adhesive layer. The nonlinear spring model shows a good agreement with the finite layer model solutions in the limit of a small thickness to wavelength ratio. Third, to demonstrate the effectiveness of this newly developed technique, measurements are conducted on adhesive joint samples made of two aluminum adherends bonded together by a polymer adhesive tape. The samples are aged in a thermal chamber to induce thermal ageing degradation in the adhesive layer. Using the developed wave-mixing technique in conjunction with the nonlinear spring model, we show that the thermal aging damage of the adhesive layer can be quantified from only one side of the sample. Finally, by mixing two L-waves, we develop a mixing technique to nondestructively evaluate the damage induced by alkali-silica reaction (ASR) in concrete. Experimental measurements are conducted on concrete prism samples that contain reactive aggregates and have been subjected to different ASR conditioning. This new technique takes into consideration of the significant attenuation caused by ASR-induced microcracks and scattering by the aggregates. The measurement results show that the ANLP has a much greater sensitivity to ASR damage than other parameters such as attenuation and wave speed. More remarkably, it is also found that the measured acoustic nonlinearity parameter is well-correlated with the reduction of the compressive strength induced by ASR damage. Thus, ANLP can be used to nondestructively track ASR damage in concrete.

Robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming.

PubMed

Baran, Richard; Northen, Trent R

2013-10-15

Untargeted metabolite profiling using liquid chromatography and mass spectrometry coupled via electrospray ionization is a powerful tool for the discovery of novel natural products, metabolic capabilities, and biomarkers. However, the elucidation of the identities of uncharacterized metabolites from spectral features remains challenging. A critical step in the metabolite identification workflow is the assignment of redundant spectral features (adducts, fragments, multimers) and calculation of the underlying chemical formula. Inspection of the data by experts using computational tools solving partial problems (e.g., chemical formula calculation for individual ions) can be performed to disambiguate alternative solutions and provide reliable results. However, manual curation is tedious and not readily scalable or standardized. Here we describe an automated procedure for the robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming optimization (RAMSI). Chemical rules among related ions are expressed as linear constraints and both the spectra interpretation and chemical formula calculation are performed in a single optimization step. This approach is unbiased in that it does not require predefined sets of neutral losses and positive and negative polarity spectra can be combined in a single optimization. The procedure was evaluated with 30 experimental mass spectra and was found to effectively identify the protonated or deprotonated molecule ([M + H](+) or [M - H](-)) while being robust to the presence of background ions. RAMSI provides a much-needed standardized tool for interpreting ions for subsequent identification in untargeted metabolomics workflows.

Analyzing longitudinal data with the linear mixed models procedure in SPSS.

PubMed

West, Brady T

2009-09-01

Many applied researchers analyzing longitudinal data share a common misconception: that specialized statistical software is necessary to fit hierarchical linear models (also known as linear mixed models [LMMs], or multilevel models) to longitudinal data sets. Although several specialized statistical software programs of high quality are available that allow researchers to fit these models to longitudinal data sets (e.g., HLM), rapid advances in general purpose statistical software packages have recently enabled analysts to fit these same models when using preferred packages that also enable other more common analyses. One of these general purpose statistical packages is SPSS, which includes a very flexible and powerful procedure for fitting LMMs to longitudinal data sets with continuous outcomes. This article aims to present readers with a practical discussion of how to analyze longitudinal data using the LMMs procedure in the SPSS statistical software package.

Linear aerospike engine study. [for reusable launch vehicles

NASA Technical Reports Server (NTRS)

Diem, H. G.; Kirby, F. M.

1977-01-01

Parametric data on split-combustor linear engine propulsion systems are presented for use in mixed-mode single-stage-to-orbit (SSTO) vehicle studies. Preliminary design data for two selected engine systems are included. The split combustor was investigated for mixed-mode operations with oxygen/hydrogen propellants used in the inner combustor in Mode 2, and in conjunction with either oxygen/RP-1, oxygen/RJ-5, O2/CH4, or O2/H2 propellants in the outer combustor for Mode 1. Both gas generator and staged combustion power cycles were analyzed for providing power to the turbopumps of the inner and outer combustors. Numerous cooling circuits and cooling fluids (propellants) were analyzed and hydrogen was selected as the preferred coolant for both combustors and the linear aerospike nozzle. The maximum operating chamber pressure was determined to be limited by the availability of hydrogen coolant pressure drop in the coolant circuit.

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.

Emergent odd-parity multipoles and magnetoelectric effects on a diamond structure: Implication for the 5 d transition metal oxides A OsO4 (A =K ,Rb, and Cs)

NASA Astrophysics Data System (ADS)

Hayami, Satoru; Kusunose, Hiroaki; Motome, Yukitoshi

2018-01-01

We report our theoretical predictions on the linear magnetoelectric (ME) effects originating from odd-parity multipoles associated with spontaneous spin and orbital ordering on a diamond structure. We derive a two-orbital model for d electrons in eg orbitals by including the effective spin-orbit coupling which arises from the mixing between eg and t2 g orbitals. We show that the model acquires a net antisymmetric spin-orbit coupling once staggered spin and orbital orders occur spontaneously. The staggered orders are accompanied by odd-parity multipoles: magnetic monopole, quadrupoles, and toroidal dipoles. We classify the types of the odd-parity multipoles according to the symmetry of the spin and orbital orders. Furthermore, by computing the ME tensor using the linear response theory, we show that the staggered orders induce a variety of the linear ME responses. We elaborate all possible ME responses for each staggered order, which are useful to identify the order parameter and to detect the odd-parity multipoles by measuring the ME effects. We also elucidate the effect of lowering symmetry by a tetragonal distortion, which leads to richer ME responses. The implications of our results are discussed for the 5 d transition metal oxides, A OsO4 (A =K,Rb, and Cs) , in which the order parameters are not fully identified.

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

Effects of dietary addition of capsicum extract on intake, water consumption, and rumen fermentation of fattening heifers fed a high-concentrate diet.

PubMed

Rodríguez-Prado, M; Ferret, A; Zwieten, J; Gonzalez, L; Bravo, D; Calsamiglia, S

2012-06-01

Four beef Holstein heifers (BW = 438 ± 71 kg) fitted with a 1-cm i.d. plastic ruminal trocars were used in a 4 × 4 Latin square design to evaluate the effect of 3 doses of capsicum extract (CAP) on intake, water consumption, and ruminal fermentation in heifers fed a high-concentrate diet. Animals were fed (DM basis) 10% barley straw and 90% concentrate (32.2% barley grain, 27.9% ground corn, 7.5% wheat bran, 10.7% soybean meal, 10.7% soybean hulls, 7.2% corn gluten feed, 3.1% mineral-vitamin mix; 16.6% CP, 18.3% NDF). Treatments were no additive (CTR), 125 (CAP125), 250 (CAP250), and 500 (CAP500) mg/d of capsicum oleoresin standardized with 6% of capsaicin and dihydrocapsaicin (XTract 6933, Pancosma, Geneva, Switzerland). Each experimental period consisted of 25 d (15 d for adaptation, 5 d of continuous measurement of DMI, and 3 d for rumen sample collection). Animals had ad libitum access to water and feed offered once daily at 0800 h. Data were analyzed by the MIXED procedure of SAS. The model included the fixed effects of period and treatment, the random effect of heifer, and the residual error. The effects were tested for linear and quadratic effects. A linear response was observed (CTR, CAP125, CAP250, and CAP500, respectively) for DMI (8.56, 9.84, 8.68, and 9.40 kg/d; P < 0.04), ruminal pH (6.03, 5.84, 5.96, and 5.86; P < 0.08) and total VFA (134.3, 144.8, 140.1, and 142.8 mM; P < 0.08). There was a strong correlation between water consumption and DMI (R(2) = 0.98). Dry matter intake in the first 2 h after feeding was reduced (P < 0.05) in all CAP treatments compared with control. The molar proportion of acetate tended to decrease linearly (from 59.6 to 55.5 mol/100 mol; P < 0.06), and ammonia N concentration tended to increase linearly (from 14.4 to 16.0 mg N/dL; P < 0.08). In contrast, the molar proportion of propionate (23.8 mol/100 mol), butyrate (14.2 mol/100 mol), and lactate (0.28 mol/100 mol) were not affected by treatments. Results indicate that capsicum extract stimulated DMI and modified the pattern of DMI in beef cattle fed high concentrate diets.

Investigation of micromixing by acoustically oscillated sharp-edges

PubMed Central

Nama, Nitesh; Huang, Po-Hsun; Huang, Tony Jun; Costanzo, Francesco

2016-01-01

Recently, acoustically oscillated sharp-edges have been utilized to achieve rapid and homogeneous mixing in microchannels. Here, we present a numerical model to investigate acoustic mixing inside a sharp-edge-based micromixer in the presence of a background flow. We extend our previously reported numerical model to include the mixing phenomena by using perturbation analysis and the Generalized Lagrangian Mean (GLM) theory in conjunction with the convection-diffusion equation. We divide the flow variables into zeroth-order, first-order, and second-order variables. This results in three sets of equations representing the background flow, acoustic response, and the time-averaged streaming flow, respectively. These equations are then solved successively to obtain the mean Lagrangian velocity which is combined with the convection-diffusion equation to predict the concentration profile. We validate our numerical model via a comparison of the numerical results with the experimentally obtained values of the mixing index for different flow rates. Further, we employ our model to study the effect of the applied input power and the background flow on the mixing performance of the sharp-edge-based micromixer. We also suggest potential design changes to the previously reported sharp-edge-based micromixer to improve its performance. Finally, we investigate the generation of a tunable concentration gradient by a linear arrangement of the sharp-edge structures inside the microchannel. PMID:27158292

Investigation of micromixing by acoustically oscillated sharp-edges.

PubMed

Nama, Nitesh; Huang, Po-Hsun; Huang, Tony Jun; Costanzo, Francesco

2016-03-01

Recently, acoustically oscillated sharp-edges have been utilized to achieve rapid and homogeneous mixing in microchannels. Here, we present a numerical model to investigate acoustic mixing inside a sharp-edge-based micromixer in the presence of a background flow. We extend our previously reported numerical model to include the mixing phenomena by using perturbation analysis and the Generalized Lagrangian Mean (GLM) theory in conjunction with the convection-diffusion equation. We divide the flow variables into zeroth-order, first-order, and second-order variables. This results in three sets of equations representing the background flow, acoustic response, and the time-averaged streaming flow, respectively. These equations are then solved successively to obtain the mean Lagrangian velocity which is combined with the convection-diffusion equation to predict the concentration profile. We validate our numerical model via a comparison of the numerical results with the experimentally obtained values of the mixing index for different flow rates. Further, we employ our model to study the effect of the applied input power and the background flow on the mixing performance of the sharp-edge-based micromixer. We also suggest potential design changes to the previously reported sharp-edge-based micromixer to improve its performance. Finally, we investigate the generation of a tunable concentration gradient by a linear arrangement of the sharp-edge structures inside the microchannel.

The effects of couplings to symmetric and antisymmetric modes and minor asymmetry on the spectral properties of mixed-valence and related charge-transfer systems

NASA Astrophysics Data System (ADS)

Reimers, J. R.; Hush, N. S.

1996-08-01

The most common methods used to describe the energy levels of charge-transfer systems (including mixed-valence systems) are the linear response approach of Rice and co-workers and the essentially equivalent PKS model described initially by Piepho, Krausz, and Schatz. While these methods were quite successful, in their original form they omitted the effects of overall symmetric vibrations. As a consequence, in particular they were not capable of adequately describing the electronic band width in the strong-coupling limit: Hush and later Ondrechen et al. demonstrated that symmetric modes are essential in this case, and modern versions of these models now include them. Here, we explore the relationship between symmetric and antisymmetric modes, concentrating on how this is modified by the presence of weak (e.g., environmentally or substitutionally induced) asymmetry. For the symmetric case, we show that when the electronic Hamiltonian operators are transformed from their usual localized diabatic representation into a delocalized diabatic representation, the effects of the symmetric and antisymmetric modes are interchanged. The primary effect of weak asymmetry is to mix the properties of the various modes, and possible consequences of this for the spectroscopy of bacterial photosynthetic reaction centre and substituted Creutz—Taube cations are discussed. We also consider the problem from an adiabatic Bom—Oppenheimer perspective and examine the regions in which this approach is appropriate.

Effects of patient safety auditing in hospital care: results of a mixed-method evaluation (part 1).

PubMed

Hanskamp-Sebregts, Mirelle; Zegers, Marieke; Westert, Gert P; Boeijen, Wilma; Teerenstra, Steven; van Gurp, Petra J; Wollersheim, Hub

2018-06-15

To evaluate the effectiveness of internal auditing in hospital care focussed on improving patient safety. A before-and-after mixed-method evaluation study was carried out in eight departments of a university medical center in the Netherlands. Internal auditing and feedback focussed on improving patient safety. The effect of internal auditing was assessed 15 months after the audit, using linear mixed models, on the patient, professional, team and departmental levels. The measurement methods were patient record review on adverse events (AEs), surveys regarding patient experiences, safety culture and team climate, analysis of administrative hospital data (standardized mortality rate, SMR) and safety walk rounds (SWRs) to observe frontline care processes on safety. The AE rate decreased from 36.1% to 31.3% and the preventable AE rate from 5.5% to 3.6%; however, the differences before and after auditing were not statistically significant. The patient-reported experience measures regarding patient safety improved slightly over time (P < 0.001). The SMR, patient safety culture and team climate remained unchanged after the internal audit. The SWRs showed that medication safety and information security were improved (P < 0.05). Internal auditing was associated with improved patient experiences and observed safety on wards. No effects were found on adverse outcomes, safety culture and team climate 15 months after the internal audit.

Performance comparison of two efficient genomic selection methods (gsbay & MixP) applied in aquacultural organisms

NASA Astrophysics Data System (ADS)

Su, Hailin; Li, Hengde; Wang, Shi; Wang, Yangfan; Bao, Zhenmin

2017-02-01

Genomic selection is more and more popular in animal and plant breeding industries all around the world, as it can be applied early in life without impacting selection candidates. The objective of this study was to bring the advantages of genomic selection to scallop breeding. Two different genomic selection tools MixP and gsbay were applied on genomic evaluation of simulated data and Zhikong scallop ( Chlamys farreri) field data. The data were compared with genomic best linear unbiased prediction (GBLUP) method which has been applied widely. Our results showed that both MixP and gsbay could accurately estimate single-nucleotide polymorphism (SNP) marker effects, and thereby could be applied for the analysis of genomic estimated breeding values (GEBV). In simulated data from different scenarios, the accuracy of GEBV acquired was ranged from 0.20 to 0.78 by MixP; it was ranged from 0.21 to 0.67 by gsbay; and it was ranged from 0.21 to 0.61 by GBLUP. Estimations made by MixP and gsbay were expected to be more reliable than those estimated by GBLUP. Predictions made by gsbay were more robust, while with MixP the computation is much faster, especially in dealing with large-scale data. These results suggested that both algorithms implemented by MixP and gsbay are feasible to carry out genomic selection in scallop breeding, and more genotype data will be necessary to produce genomic estimated breeding values with a higher accuracy for the industry.

Optimal Facility Location Tool for Logistics Battle Command (LBC)

DTIC Science & Technology

2015-08-01

64 Appendix B. VBA Code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 Appendix C. Story...should city planners have located emergency service facilities so that all households (the demand) had equal access to coverage?” The critical...programming language called Visual Basic for Applications ( VBA ). CPLEX is a commercial solver for linear, integer, and mixed integer linear programming problems

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

ERIC Educational Resources Information Center

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

2018-01-01

Purpose: 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. Method: We propose a…

An Aptitude-Strategy Interaction in Linear Syllogistic Reading. Technical Report No. 15.

ERIC Educational Resources Information Center

Sternberg, Robert J.; Weil, Evelyn M.

An aptitude-strategy interaction in linear syllogistic reasoning was tested on 144 undergraduate and graduate students of both sexes. It was hypothesized that the efficiency of each of four alternative strategies--control, visual, algorithmic, and mixed--would depend upon the subjects' pattern of verbal and spatial abilities. Two tests of verbal…

[Analysis on the trend of long-term change of blood pressure in hypertensive patients treated with benazepril].

PubMed

Lu, Jun; Li, Li-Ming; He, Ping-Ping; Cao, Wei-Hua; Zhan, Si-Yan; Hu, Yong-Hua

2004-06-01

To introduce the application of mixed linear model in the analysis of secular trend of blood pressure under antihypertensive treatment. A community-based postmarketing surveillance of benazepril was conducted in 1831 essential hypertensive patients (age range from 35 to 88 years) in Shanghai. Data of blood pressure was analyzed every 3 months with mixed linear model to describe the secular trend of blood pressure and changes of age-specific and gender-specific. The changing trends of systolic blood pressure (SBP) and diastolic blood pressure (DBP) were found to fit the curvilinear models. A piecewise model was fit for pulse pressure (PP), i.e., curvilinear model in the first 9 months and linear model after 9 months of taking medication. Both blood pressure and its velocity gradually slowed down. There were significant variation for the curve parameters of intercept, slope, and acceleration. Blood pressure in patients with higher initial levels was persistently declining in the 3-year-treatment. However blood pressures of patients with relatively low initial levels remained low when dropped down to some degree. Elderly patients showed high SBP but low DBP, so as with higher PP. The velocity and sizes of blood pressure reductions increased with the initial level of blood pressure. Mixed linear model is flexible and robust when applied to the analysis of longitudinal data but with missing values and can also make the maximum use of available information.

Assessment of combined antiandrogenic effects of binary parabens mixtures in a yeast-based reporter assay.

PubMed

Ma, Dehua; Chen, Lujun; Zhu, Xiaobiao; Li, Feifei; Liu, Cong; Liu, Rui

2014-05-01

To date, toxicological studies of endocrine disrupting chemicals (EDCs) have typically focused on single chemical exposures and associated effects. However, exposure to EDCs mixtures in the environment is common. Antiandrogens represent a group of EDCs, which draw increasing attention due to their resultant demasculinization and sexual disruption of aquatic organisms. Although there are a number of in vivo and in vitro studies investigating the combined effects of antiandrogen mixtures, these studies are mainly on selected model compounds such as flutamide, procymidone, and vinclozolin. The aim of the present study is to investigate the combined antiandrogenic effects of parabens, which are widely used antiandrogens in industrial and domestic commodities. A yeast-based human androgen receptor (hAR) assay (YAS) was applied to assess the antiandrogenic activities of n-propylparaben (nPrP), iso-propylparaben (iPrP), methylparaben (MeP), and 4-n-pentylphenol (PeP), as well as the binary mixtures of nPrP with each of the other three antiandrogens. All of the four compounds could exhibit antiandrogenic activity via the hAR. A linear interaction model was applied to quantitatively analyze the interaction between nPrP and each of the other three antiandrogens. The isoboles method was modified to show the variation of combined effects as the concentrations of mixed antiandrogens were changed. Graphs were constructed to show isoeffective curves of three binary mixtures based on the fitted linear interaction model and to evaluate the interaction of the mixed antiandrogens (synergism or antagonism). The combined effect of equimolar combinations of the three mixtures was also considered with the nonlinear isoboles method. The main effect parameters and interaction effect parameters in the linear interaction models of the three mixtures were different from zero. The results showed that any two antiandrogens in their binary mixtures tended to exert equal antiandrogenic activity in the linear concentration ranges. The antiandrogenicity of the binary mixture and the concentration of nPrP were fitted to a sigmoidal model if the concentrations of the other antiandrogens (iPrP, MeP, and PeP) in the mixture were lower than the AR saturation concentrations. Some concave isoboles above the additivity line appeared in all the three mixtures. There were some synergistic effects of the binary mixture of nPrP and MeP at low concentrations in the linear concentration ranges. Interesting, when the antiandrogens concentrations approached the saturation, the interaction between chemicals were antagonistic for all the three mixtures tested. When the toxicity of the three mixtures was assessed using nonlinear isoboles, only antagonism was observed for equimolar combinations of nPrP and iPrP as the concentrations were increased from the no-observed-effect-concentration (NOEC) to effective concentration of 80%. In addition, the interactions were changed from synergistic to antagonistic as effective concentrations were increased in the equimolar combinations of nPrP and MeP, as well as nPrP and PeP. The combined effects of three binary antiandrogens mixtures in the linear ranges were successfully evaluated by curve fitting and isoboles. The combined effects of specific binary mixtures varied depending on the concentrations of the chemicals in the mixtures. At low concentrations in the linear concentration ranges, there was synergistic interaction existing in the binary mixture of nPrP and MeP. The interaction tended to be antagonistic as the antiandrogens approached saturation concentrations in mixtures of nPrP with each of the other three antiandrogens. The synergistic interaction was also found in the equimolar combinations of nPrP and MeP, as well as nPrP and PeP, at low concentrations with another method of nonlinear isoboles. The mixture activities of binary antiandrogens had a tendency towards antagonism at high concentrations and synergism at low concentrations.

Stabilization of the Rayleigh-Taylor instability in quantum magnetized plasmas

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

Wang, L. F.; Ye, W. H.; He, X. T.

2012-07-15

In this research, stabilization of the Rayleigh-Taylor instability (RTI) due to density gradients, magnetic fields, and quantum effects, in an ideal incompressible plasma, is studied analytically and numerically. A second-order ordinary differential equation (ODE) for the RTI including quantum corrections, with a continuous density profile, in a uniform external magnetic field, is obtained. Analytic expressions of the linear growth rate of the RTI, considering modifications of density gradients, magnetic fields, and quantum effects, are presented. Numerical approaches are performed to solve the second-order ODE. The analytical model proposed here agrees with the numerical calculation. It is found that the densitymore » gradients, the magnetic fields, and the quantum effects, respectively, have a stabilizing effect on the RTI (reduce the linear growth of the RTI). The RTI can be completely quenched by the magnetic field stabilization and/or the quantum effect stabilization in proper circumstances leading to a cutoff wavelength. The quantum effect stabilization plays a central role in systems with large Atwood number and small normalized density gradient scale length. The presence of external transverse magnetic fields beside the quantum effects will bring about more stability on the RTI. The stabilization of the linear growth of the RTI, for parameters closely related to inertial confinement fusion and white dwarfs, is discussed. Results could potentially be valuable for the RTI treatment to analyze the mixing in supernovas and other RTI-driven objects.« less

Analysis of lithology: Vegetation mixes in multispectral images

NASA Technical Reports Server (NTRS)

Adams, J. B.; Smith, M.; Adams, J. D.

1982-01-01

Discrimination and identification of lithologies from multispectral images is discussed. Rock/soil identification can be facilitated by removing the component of the signal in the images that is contributed by the vegetation. Mixing models were developed to predict the spectra of combinations of pure end members, and those models were refined using laboratory measurements of real mixtures. Models in use include a simple linear (checkerboard) mix, granular mixing, semi-transparent coatings, and combinations of the above. The use of interactive computer techniques that allow quick comparison of the spectrum of a pixel stack (in a multiband set) with laboratory spectra is discussed.

Mixing and Formation of Layers by Internal Wave Forcing

NASA Astrophysics Data System (ADS)

Dossmann, Yvan; Pollet, Florence; Odier, Philippe; Dauxois, Thierry

2017-12-01

The energy pathways from propagating internal waves to the scales of irreversible mixing in the ocean are not fully described. In the ocean interior, the triadic resonant instability is an intrinsic destabilization process that may enhance the energy cascade away from topographies. The present study focuses on the integrated impact of mixing processes induced by a propagative normal mode-1 over long-term experiments in an idealized setup. The internal wave dynamics and the evolution of the density profile are followed using the light attenuation technique. Diagnostics of the turbulent diffusivity KT and background potential energy BPE are provided. Mixing effects result in a partially mixed layer colocated with the region of maximum shear induced by the forcing normal mode. The maximum measured turbulent diffusivity is 250 times larger than the molecular value, showing that diapycnal mixing is largely enhanced by small-scale turbulent processes. Intermittency and reversible energy transfers are discussed to bridge the gap between the present diagnostic and the larger values measured in Dossmann et al. (). The mixing efficiency η is assessed by relating the BPE growth to the linearized KE input. One finds a value of Γ=12-19%, larger than the mixing efficiency in the case of breaking interfacial wave. After several hours of forcing, the development of staircases in the density profile is observed. This mechanism has been previously observed in experiments with weak homogeneous turbulence and explained by Phillips (1972) argument. The present experiments suggest that internal wave forcing could also induce the formation of density interfaces in the ocean.

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.

Design optimization of single mixed refrigerant LNG process using a hybrid modified coordinate descent algorithm

NASA Astrophysics Data System (ADS)

Qyyum, Muhammad Abdul; Long, Nguyen Van Duc; Minh, Le Quang; Lee, Moonyong

2018-01-01

Design optimization of the single mixed refrigerant (SMR) natural gas liquefaction (LNG) process involves highly non-linear interactions between decision variables, constraints, and the objective function. These non-linear interactions lead to an irreversibility, which deteriorates the energy efficiency of the LNG process. In this study, a simple and highly efficient hybrid modified coordinate descent (HMCD) algorithm was proposed to cope with the optimization of the natural gas liquefaction process. The single mixed refrigerant process was modeled in Aspen Hysys® and then connected to a Microsoft Visual Studio environment. The proposed optimization algorithm provided an improved result compared to the other existing methodologies to find the optimal condition of the complex mixed refrigerant natural gas liquefaction process. By applying the proposed optimization algorithm, the SMR process can be designed with the 0.2555 kW specific compression power which is equivalent to 44.3% energy saving as compared to the base case. Furthermore, in terms of coefficient of performance (COP), it can be enhanced up to 34.7% as compared to the base case. The proposed optimization algorithm provides a deep understanding of the optimization of the liquefaction process in both technical and numerical perspectives. In addition, the HMCD algorithm can be employed to any mixed refrigerant based liquefaction process in the natural gas industry.

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

Zhang, Fu-Lin, E-mail: flzhang@tju.edu.cn; Chen, Jing-Ling, E-mail: chenjl@nankai.edu.cn; Centre for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore 117543

Recent experimental progress in prolonging the coherence time of a quantum system prompts us to explore the behavior of quantum entanglement at the beginning of the decoherence process. The response of the entanglement under an infinitesimal noise can serve as a signature of the robustness of entangled states. A crucial problem of this topic in multipartite systems is to compute the degree of entanglement in a mixed state. We find a family of global noise in three-qubit systems, which is composed of four W states. Under its influence, the linear response of the tripartite entanglement of a symmetrical three-qubit puremore » state is studied. A lower bound of the linear response is found to depend completely on the initial tripartite and bipartite entanglement. This result shows that the decay of tripartite entanglement is hastened by the bipartite one. - Highlights: • We study a set of W-type noise and its linear effect on symmetric pure states. • Its effect on two-qubit entanglement depends only on the initial concurrence. • A lower bound of the effect on 3-tangle is found in terms of initial entanglements. • We obtain the time of three-tangle sudden death for two families of typical states. • These reveal that the bipartite entanglement speeds up the decay of the tripartite one.« less

Three-dimensional Navier-Stokes analysis of turbine passage heat transfer

NASA Technical Reports Server (NTRS)

Ameri, Ali A.; Arnone, Andrea

1991-01-01

The three-dimensional Reynolds-averaged Navier-Stokes equations are numerically solved to obtain the pressure distribution and heat transfer rates on the endwalls and the blades of two linear turbine cascades. The TRAF3D code which has recently been developed in a joint project between researchers from the University of Florence and NASA Lewis Research Center is used. The effect of turbulence is taken into account by using the eddy viscosity hypothesis and the two-layer mixing length model of Baldwin and Lomax. Predictions of surface heat transfer are made for Langston's cascade and compared with the data obtained for that cascade by Graziani. The comparison was found to be favorable. The code is also applied to a linear transonic rotor cascade to predict the pressure distributions and heat transfer rates.

Non-linear optical crystal vibration sensing device

DOEpatents

Kalibjian, Ralph

1994-01-11

A non-linear optical crystal vibration sensing device (10) including a photorefractive crystal (26) and a laser (12). The laser (12 ) produces a coherent light beam (14) which is split by a beam splitter (18) into a first laser beam (20) and a second laser beam (22). After passing through the crystal (26) the first laser beam (20) is counter-propagated back upon itself by a retro-mirror (32), creating a third laser beam (30). The laser beams (20, 22, 30) are modulated, due to the mixing effect within the crystal (26) by vibration of the crystal (30). In the third laser beam (30), modulation is stable and such modulation is converted by a photodetector (34) into a usable electrical output, intensity modulated in accordance with vibration applied to the crystal (26).

Tangent linear super-parameterization: attributable, decomposable moist processes for tropical variability studies

NASA Astrophysics Data System (ADS)

Mapes, B. E.; Kelly, P.; Song, S.; Hu, I. K.; Kuang, Z.

2015-12-01

An economical 10-layer global primitive equation solver is driven by time-independent forcing terms, derived from a training process, to produce a realisting eddying basic state with a tracer q trained to act like water vapor mixing ratio. Within this basic state, linearized anomaly moist physics in the column are applied in the form of a 20x20 matrix. The control matrix was derived from the results of Kuang (2010, 2012) who fitted a linear response function from a cloud resolving model in a state of deep convecting equilibrium. By editing this matrix in physical space and eigenspace, scaling and clipping its action, and optionally adding terms for processes that do not conserve moist statice energy (radiation, surface fluxes), we can decompose and explain the model's diverse moist process coupled variability. Recitified effects of this variability on the general circulation and climate, even in strictly zero-mean centered anomaly physic cases, also are sometimes surprising.

Robust Nonlinear Feedback Control of Aircraft Propulsion Systems

NASA Technical Reports Server (NTRS)

Garrard, William L.; Balas, Gary J.; Litt, Jonathan (Technical Monitor)

2001-01-01

This is the final report on the research performed under NASA Glen grant NASA/NAG-3-1975 concerning feedback control of the Pratt & Whitney (PW) STF 952, a twin spool, mixed flow, after burning turbofan engine. The research focussed on the design of linear and gain-scheduled, multivariable inner-loop controllers for the PW turbofan engine using H-infinity and linear, parameter-varying (LPV) control techniques. The nonlinear turbofan engine simulation was provided by PW within the NASA Rocket Engine Transient Simulator (ROCETS) simulation software environment. ROCETS was used to generate linearized models of the turbofan engine for control design and analysis as well as the simulation environment to evaluate the performance and robustness of the controllers. Comparison between the H-infinity, and LPV controllers are made with the baseline multivariable controller and developed by Pratt & Whitney engineers included in the ROCETS simulation. Simulation results indicate that H-infinity and LPV techniques effectively achieve desired response characteristics with minimal cross coupling between commanded values and are very robust to unmodeled dynamics and sensor noise.

A comparison of the experimental subsonic pressure distributions about several bodies of revolution with pressure distributions computed by means of the linearized theory

NASA Technical Reports Server (NTRS)

Matthews, Clarence W

1953-01-01

An analysis is made of the effects of compressibility on the pressure coefficients about several bodies of revolution by comparing experimentally determined pressure coefficients with corresponding pressure coefficients calculated by the use of the linearized equations of compressible flow. The results show that the theoretical methods predict the subsonic pressure-coefficient changes over the central part of the body but do not predict the pressure-coefficient changes near the nose. Extrapolation of the linearized subsonic theory into the mixed subsonic-supersonic flow region fails to predict a rearward movement of the negative pressure-coefficient peak which occurs after the critical stream Mach number has been attained. Two equations developed from a consideration of the subsonic compressible flow about a prolate spheroid are shown to predict, approximately, the change with Mach number of the subsonic pressure coefficients for regular bodies of revolution of fineness ratio 6 or greater.

Within crown variation in the relationship between foliage biomass and sapwood area in jack pine.

PubMed

Schneider, Robert; Berninger, Frank; Ung, Chhun-Huor; Mäkelä, Annikki; Swift, D Edwin; Zhang, S Y

2011-01-01

The relationship between sapwood area and foliage biomass is the basis for a lot of research on eco-phyisology. In this paper, foliage biomass change between two consecutive whorls is studied, using different variations in the pipe model theory. Linear and non-linear mixed-effect models relating foliage differences to sapwood area increments were tested to take into account whorl location, with the best fit statistics supporting the non-linear formulation. The estimated value of the exponent is 0.5130, which is significantly different from 1, the expected value given by the pipe model theory. When applied to crown stem sapwood taper, the model indicates that foliage biomass distribution influences the foliage biomass to sapwood area at crown base ratio. This result is interpreted as being the consequence of differences in the turnover rates of sapwood and foliage. More importantly, the model explains previously reported trends in jack pine sapwood area at crown base to tree foliage biomass ratio.

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),…

Generalized Path Analysis and Generalized Simultaneous Equations Model for Recursive Systems with Responses of Mixed Types

ERIC Educational Resources Information Center

Tsai, Tien-Lung; Shau, Wen-Yi; Hu, Fu-Chang

2006-01-01

This article generalizes linear path analysis (PA) and simultaneous equations models (SiEM) to deal with mixed responses of different types in a recursive or triangular system. An efficient instrumental variable (IV) method for estimating the structural coefficients of a 2-equation partially recursive generalized path analysis (GPA) model and…

Mixed Integer Linear Programming model for Crude Palm Oil Supply Chain Planning

NASA Astrophysics Data System (ADS)

Sembiring, Pasukat; Mawengkang, Herman; Sadyadharma, Hendaru; Bu'ulolo, F.; Fajriana

2018-01-01

The production process of crude palm oil (CPO) can be defined as the milling process of raw materials, called fresh fruit bunch (FFB) into end products palm oil. The process usually through a series of steps producing and consuming intermediate products. The CPO milling industry considered in this paper does not have oil palm plantation, therefore the FFB are supplied by several public oil palm plantations. Due to the limited availability of FFB, then it is necessary to choose from which plantations would be appropriate. This paper proposes a mixed integer linear programming model the supply chain integrated problem, which include waste processing. The mathematical programming model is solved using neighborhood search approach.

Alternative mathematical programming formulations for FSS synthesis

NASA Technical Reports Server (NTRS)

Reilly, C. H.; Mount-Campbell, C. A.; Gonsalvez, D. J. A.; Levis, C. A.

1986-01-01

A variety of mathematical programming models and two solution strategies are suggested for the problem of allocating orbital positions to (synthesizing) satellites in the Fixed Satellite Service. Mixed integer programming and almost linear programming formulations are presented in detail for each of two objectives: (1) positioning satellites as closely as possible to specified desired locations, and (2) minimizing the total length of the geostationary arc allocated to the satellites whose positions are to be determined. Computational results for mixed integer and almost linear programming models, with the objective of positioning satellites as closely as possible to their desired locations, are reported for three six-administration test problems and a thirteen-administration test problem.

A Mixed Integer Linear Programming Approach to Electrical Stimulation Optimization Problems.

PubMed

Abouelseoud, Gehan; Abouelseoud, Yasmine; Shoukry, Amin; Ismail, Nour; Mekky, Jaidaa

2018-02-01

Electrical stimulation optimization is a challenging problem. Even when a single region is targeted for excitation, the problem remains a constrained multi-objective optimization problem. The constrained nature of the problem results from safety concerns while its multi-objectives originate from the requirement that non-targeted regions should remain unaffected. In this paper, we propose a mixed integer linear programming formulation that can successfully address the challenges facing this problem. Moreover, the proposed framework can conclusively check the feasibility of the stimulation goals. This helps researchers to avoid wasting time trying to achieve goals that are impossible under a chosen stimulation setup. The superiority of the proposed framework over alternative methods is demonstrated through simulation examples.

Alternating direction implicit methods for parabolic equations with a mixed derivative

NASA Technical Reports Server (NTRS)

Beam, R. M.; Warming, R. F.

1980-01-01

Alternating direction implicit (ADI) schemes for two-dimensional parabolic equations with a mixed derivative are constructed by using the class of all A(0)-stable linear two-step methods in conjunction with the method of approximate factorization. The mixed derivative is treated with an explicit two-step method which is compatible with an implicit A(0)-stable method. The parameter space for which the resulting ADI schemes are second-order accurate and unconditionally stable is determined. Some numerical examples are given.

Alternating direction implicit methods for parabolic equations with a mixed derivative

NASA Technical Reports Server (NTRS)

Beam, R. M.; Warming, R. F.

1979-01-01

Alternating direction implicit (ADI) schemes for two-dimensional parabolic equations with a mixed derivative are constructed by using the class of all A sub 0-stable linear two-step methods in conjunction with the method of approximation factorization. The mixed derivative is treated with an explicit two-step method which is compatible with an implicit A sub 0-stable method. The parameter space for which the resulting ADI schemes are second order accurate and unconditionally stable is determined. Some numerical examples are given.

G-Jitter Induced Magnetohydrodynamics Flow of Nanofluid with Constant Convective Thermal and Solutal Boundary Conditions

PubMed Central

Uddin, Mohammed J.; Khan, Waqar A.; Ismail, Ahmad Izani Md.

2015-01-01

Taking into account the effect of constant convective thermal and mass boundary conditions, we present numerical solution of the 2-D laminar g-jitter mixed convective boundary layer flow of water-based nanofluids. The governing transport equations are converted into non-similar equations using suitable transformations, before being solved numerically by an implicit finite difference method with quasi-linearization technique. The skin friction decreases with time, buoyancy ratio, and thermophoresis parameters while it increases with frequency, mixed convection and Brownian motion parameters. Heat transfer rate decreases with time, Brownian motion, thermophoresis and diffusion-convection parameters while it increases with the Reynolds number, frequency, mixed convection, buoyancy ratio and conduction-convection parameters. Mass transfer rate decreases with time, frequency, thermophoresis, conduction-convection parameters while it increases with mixed convection, buoyancy ratio, diffusion-convection and Brownian motion parameters. To the best of our knowledge, this is the first paper on this topic and hence the results are new. We believe that the results will be useful in designing and operating thermal fluids systems for space materials processing. Special cases of the results have been compared with published results and an excellent agreement is found. PMID:25933066

Efficiency of circulant diallels via mixed models in the selection of papaya genotypes resistant to foliar fungal diseases.

PubMed

Vivas, M; Silveira, S F; Viana, A P; Amaral, A T; Cardoso, D L; Pereira, M G

2014-07-02

Diallel crossing methods provide information regarding the performance of genitors between themselves and their hybrid combinations. However, with a large number of parents, the number of hybrid combinations that can be obtained and evaluated become limited. One option regarding the number of parents involved is the adoption of circulant diallels. However, information is lacking regarding diallel analysis using mixed models. This study aimed to evaluate the efficacy of the method of linear mixed models to estimate, for variable resistance to foliar fungal diseases, components of general and specific combining ability in a circulant table with different s values. Subsequently, 50 diallels were simulated for each s value, and the correlations and estimates of the combining abilities of the different diallel combinations were analyzed. The circulant diallel method using mixed modeling was effective in the classification of genitors regarding their combining abilities relative to the complete diallels. The numbers of crosses in which each genitor(s) will compose the circulant diallel and the estimated heritability affect the combining ability estimates. With three crosses per parent, it is possible to obtain good concordance (correlation above 0.8) between the combining ability estimates.

A multifaceted workplace intervention for low back pain in nurses' aides: a pragmatic stepped wedge cluster randomised controlled trial

PubMed Central

Rasmussen, Charlotte Diana Nørregaard; Holtermann, Andreas; Bay, Hans; Søgaard, Karen; Birk Jørgensen, Marie

2015-01-01

Abstract This study established the effectiveness of a workplace multifaceted intervention consisting of participatory ergonomics, physical training, and cognitive–behavioural training (CBT) for low back pain (LBP). Between November 2012 and May 2014, we conducted a pragmatic stepped wedge cluster randomised controlled trial with 594 workers from eldercare workplaces (nursing homes and home care) randomised to 4 successive time periods, 3 months apart. The intervention lasted 12 weeks and consisted of 19 sessions in total (physical training [12 sessions], CBT [2 sessions], and participatory ergonomics [5 sessions]). Low back pain was the outcome and was measured as days, intensity (worst pain on a 0-10 numeric rank scale), and bothersomeness (days) by monthly text messages. Linear mixed models were used to estimate the intervention effect. Analyses were performed according to intention to treat, including all eligible randomised participants, and were adjusted for baseline values of the outcome. The linear mixed models yielded significant effects on LBP days of −0.8 (95% confidence interval [CI], −1.19 to −0.38), LBP intensity of −0.4 (95% CI, −0.60 to −0.26), and bothersomeness days of −0.5 (95% CI, −0.85 to −0.13) after the intervention compared with the control group. This study shows that a multifaceted intervention consisting of participatory ergonomics, physical training, and CBT can reduce LBP among workers in eldercare. Thus, multifaceted interventions may be relevant for improving LBP in a working population. PMID:25993549

Perturbation theory for cosmologies with nonlinear structure

NASA Astrophysics Data System (ADS)

Goldberg, Sophia R.; Gallagher, Christopher S.; Clifton, Timothy

2017-11-01

The next generation of cosmological surveys will operate over unprecedented scales, and will therefore provide exciting new opportunities for testing general relativity. The standard method for modelling the structures that these surveys will observe is to use cosmological perturbation theory for linear structures on horizon-sized scales, and Newtonian gravity for nonlinear structures on much smaller scales. We propose a two-parameter formalism that generalizes this approach, thereby allowing interactions between large and small scales to be studied in a self-consistent and well-defined way. This uses both post-Newtonian gravity and cosmological perturbation theory, and can be used to model realistic cosmological scenarios including matter, radiation and a cosmological constant. We find that the resulting field equations can be written as a hierarchical set of perturbation equations. At leading-order, these equations allow us to recover a standard set of Friedmann equations, as well as a Newton-Poisson equation for the inhomogeneous part of the Newtonian energy density in an expanding background. For the perturbations in the large-scale cosmology, however, we find that the field equations are sourced by both nonlinear and mode-mixing terms, due to the existence of small-scale structures. These extra terms should be expected to give rise to new gravitational effects, through the mixing of gravitational modes on small and large scales—effects that are beyond the scope of standard linear cosmological perturbation theory. We expect our formalism to be useful for accurately modeling gravitational physics in universes that contain nonlinear structures, and for investigating the effects of nonlinear gravity in the era of ultra-large-scale surveys.

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.

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.

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.

Effect of Consuming Oat Bran Mixed in Water before a Meal on Glycemic Responses in Healthy Humans-A Pilot Study.

PubMed

Steinert, Robert E; Raederstorff, Daniel; Wolever, Thomas M S

2016-08-26

Viscous dietary fibers including oat β-glucan are one of the most effective classes of functional food ingredients for reducing postprandial blood glucose. The mechanism of action is thought to be via an increase in viscosity of the stomach contents that delays gastric emptying and reduces mixing of food with digestive enzymes, which, in turn, retards glucose absorption. Previous studies suggest that taking viscous fibers separate from a meal may not be effective in reducing postprandial glycemia. We aimed to re-assess the effect of consuming a preload of a commercially available oat-bran (4.5, 13.6 or 27.3 g) containing 22% of high molecular weight oat β-glucan (O22 (OatWell(®)22)) mixed in water before a test-meal of white bread on glycemic responses in 10 healthy humans. We found a significant effect of dose on blood glucose area under the curve (AUC) (p = 0.006) with AUC after 27.3 g of O22 being significantly lower than white bread only. Linear regression analysis showed that each gram of oat β-glucan reduced glucose AUC by 4.35% ± 1.20% (r = 0.507, p = 0.0008, n = 40) and peak rise by 6.57% ± 1.49% (r = 0.582, p < 0.0001). These data suggest the use of oat bran as nutritional preload strategy in the management of postprandial glycemia.

Pharmaceutical grade phyllosilicate dispersions: the influence of shear history on floc structure.

PubMed

Viseras, C; Meeten, G H; Lopez-Galindo, A

1999-05-10

The effect of mixing conditions on the flow curves of some clay-water dispersions was studied. Two Spanish fibrous phyllosilicates (sepiolite from Vicálvaro and palygorskite from Turón) and a commercial bentonite (Bentopharm Copyright, UK) were selected as model clays. The disperse systems were made up using a rotor-stator mixer working at two different mixing rates (1000 and 8000 rpm), for periods of 1 and 10 min. Rheological measurements were taken and the corresponding flow curves obtained immediately after interposition and then after a period of 24 h under low shear caused by a roller apparatus. Aqueous sepiolite dispersions showed the highest viscosity and were easily interposed, whereas palygorskite dispersions were more difficult to obtain, resulting in low to medium viscosity gels. Bentonite dispersions provided medium viscosity systems, which greatly increased their viscosity after the low shear treatment (as a result of swelling), whereas the viscosity of the fibrous clays stayed at approximately the same values or even decreased. A linear relation was found between mixing energy and apparent viscosity in the bentonite systems, while apparent viscosity in the sepiolite samples was related to mixing power, with minor influence of mixing times. All the systems studied had thixotropic behaviour, changing from clearly positive to even negative thixotropy in some palygorskite systems. Finally, we studied the effect of drastic pH changes on the system structure. Results showed that rheological properties were highly sensitive to pH in the fibrous dispersions, but less sensitive behaviour was found in the laminar clay systems. Copyright.

The effect of work shift configurations on emergency medical dispatch center response.

PubMed

Montassier, Emmanuel; Labady, Julien; Andre, Antoine; Potel, Gilles; Berthier, Frederic; Jenvrin, Joel; Penverne, Yann

2015-01-01

It has been proved that emergency medical dispatch centers (EMDC) save lives by promoting an appropriate allocation of emergency medical service resources. Indeed, optimal dispatcher call duration is pivotal to reduce the time gap between the time a call is placed and the delivery of medical care. However, little is known about the impact of work shift configurations (i.e., work shift duration and work shift rotation throughout the day) and dispatcher call duration. Thus, the objective of our study was to assess the effect of work shift configurations on dispatcher call duration. During a 1-year study period, we analyzed the dispatcher call durations for medical and trauma calls during the 4 different work shift rotations (day, morning, evening, and night) and during the 10-hour work shift of each dispatcher in the EMDC of Nantes. We extracted dispatcher call durations from our advanced telephone system, configured with CC Pulse + (Genesys, Alcatel Lucent), and collected them in a custom designed database (Excel, Microsoft). Afterward, we analyzed these data using linear mixed effects models. During the study period, our EMDC received 408,077 calls. Globally, the mean dispatcher call duration was 107 ± 45 seconds. Based on multivariate linear mixed effects models, the dispatcher call duration was affected by night work shift and work shift duration greater than 8 hours, increasing it by about 10 ± 1 seconds and 4 ± 1 seconds, respectively (both p < 0.001). Our study showed that there was a statistically significant difference in dispatcher call duration over work shift rotation and duration, with longer durations seen over night shifts and shifts over 8 hours. While these differences are small and may not have clinical significance, they may have implications for EMDC efficiency.

Potential Factors Affecting Survival Differ by Run-Timing and Location: Linear Mixed-Effects Models of Pacific Salmonids (Oncorhynchus spp.) in the Klamath River, California

PubMed Central

Quiñones, Rebecca M.; Holyoak, Marcel; Johnson, Michael L.; Moyle, Peter B.

2014-01-01

Understanding factors influencing survival of Pacific salmonids (Oncorhynchus spp.) is essential to species conservation, because drivers of mortality can vary over multiple spatial and temporal scales. Although recent studies have evaluated the effects of climate, habitat quality, or resource management (e.g., hatchery operations) on salmonid recruitment and survival, a failure to look at multiple factors simultaneously leaves open questions about the relative importance of different factors. We analyzed the relationship between ten factors and survival (1980–2007) of four populations of salmonids with distinct life histories from two adjacent watersheds (Salmon and Scott rivers) in the Klamath River basin, California. The factors were ocean abundance, ocean harvest, hatchery releases, hatchery returns, Pacific Decadal Oscillation, North Pacific Gyre Oscillation, El Niño Southern Oscillation, snow depth, flow, and watershed disturbance. Permutation tests and linear mixed-effects models tested effects of factors on survival of each taxon. Potential factors affecting survival differed among taxa and between locations. Fall Chinook salmon O. tshawytscha survival trends appeared to be driven partially or entirely by hatchery practices. Trends in three taxa (Salmon River spring Chinook salmon, Scott River fall Chinook salmon; Salmon River summer steelhead trout O. mykiss) were also likely driven by factors subject to climatic forcing (ocean abundance, summer flow). Our findings underscore the importance of multiple factors in simultaneously driving population trends in widespread species such as anadromous salmonids. They also show that the suite of factors may differ among different taxa in the same location as well as among populations of the same taxa in different watersheds. In the Klamath basin, hatchery practices need to be reevaluated to protect wild salmonids. PMID:24866173

Generalized functional linear models for gene-based case-control association studies.

PubMed

Fan, Ruzong; Wang, Yifan; Mills, James L; Carter, Tonia C; Lobach, Iryna; Wilson, Alexander F; Bailey-Wilson, Joan E; Weeks, Daniel E; Xiong, Momiao

2014-11-01

By using functional data analysis techniques, we developed generalized functional linear models for testing association between a dichotomous trait and multiple genetic variants in a genetic region while adjusting for covariates. Both fixed and mixed effect models are developed and compared. Extensive simulations show that Rao's efficient score tests of the fixed effect models are very conservative since they generate lower type I errors than nominal levels, and global tests of the mixed effect models generate accurate type I errors. Furthermore, we found that the Rao's efficient score test statistics of the fixed effect models have higher power than the sequence kernel association test (SKAT) and its optimal unified version (SKAT-O) in most cases when the causal variants are both rare and common. When the causal variants are all rare (i.e., minor allele frequencies less than 0.03), the Rao's efficient score test statistics and the global tests have similar or slightly lower power than SKAT and SKAT-O. In practice, it is not known whether rare variants or common variants in a gene region are disease related. All we can assume is that a combination of rare and common variants influences disease susceptibility. Thus, the improved performance of our models when the causal variants are both rare and common shows that the proposed models can be very useful in dissecting complex traits. We compare the performance of our methods with SKAT and SKAT-O on real neural tube defects and Hirschsprung's disease datasets. The Rao's efficient score test statistics and the global tests are more sensitive than SKAT and SKAT-O in the real data analysis. Our methods can be used in either gene-disease genome-wide/exome-wide association studies or candidate gene analyses. © 2014 WILEY PERIODICALS, INC.

Generalized Functional Linear Models for Gene-based Case-Control Association Studies

PubMed Central

Mills, James L.; Carter, Tonia C.; Lobach, Iryna; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Weeks, Daniel E.; Xiong, Momiao

2014-01-01

By using functional data analysis techniques, we developed generalized functional linear models for testing association between a dichotomous trait and multiple genetic variants in a genetic region while adjusting for covariates. Both fixed and mixed effect models are developed and compared. Extensive simulations show that Rao's efficient score tests of the fixed effect models are very conservative since they generate lower type I errors than nominal levels, and global tests of the mixed effect models generate accurate type I errors. Furthermore, we found that the Rao's efficient score test statistics of the fixed effect models have higher power than the sequence kernel association test (SKAT) and its optimal unified version (SKAT-O) in most cases when the causal variants are both rare and common. When the causal variants are all rare (i.e., minor allele frequencies less than 0.03), the Rao's efficient score test statistics and the global tests have similar or slightly lower power than SKAT and SKAT-O. In practice, it is not known whether rare variants or common variants in a gene are disease-related. All we can assume is that a combination of rare and common variants influences disease susceptibility. Thus, the improved performance of our models when the causal variants are both rare and common shows that the proposed models can be very useful in dissecting complex traits. We compare the performance of our methods with SKAT and SKAT-O on real neural tube defects and Hirschsprung's disease data sets. The Rao's efficient score test statistics and the global tests are more sensitive than SKAT and SKAT-O in the real data analysis. Our methods can be used in either gene-disease genome-wide/exome-wide association studies or candidate gene analyses. PMID:25203683

Genetics-Based Population Pharmacokinetics and Pharmacodynamics of Risperidone in a Psychiatric Cohort.

PubMed

Vandenberghe, Frederik; Guidi, Monia; Choong, Eva; von Gunten, Armin; Conus, Philippe; Csajka, Chantal; Eap, Chin B

2015-12-01

High interindividual variability in plasma concentrations of risperidone and its active metabolite, 9-hydroxyrisperidone, may lead to suboptimal drug concentration. Using a population pharmacokinetic approach, we aimed to characterize the genetic and non-genetic sources of variability affecting risperidone and 9-hydroxyrisperidone pharmacokinetics, and relate them to common side effects. Overall, 150 psychiatric patients (178 observations) treated with risperidone were genotyped for common polymorphisms in NR1/2, POR, PPARα, ABCB1, CYP2D6 and CYP3A genes. Plasma risperidone and 9-hydroxyrisperidone were measured, and clinical data and common clinical chemistry parameters were collected. Drug and metabolite concentrations were analyzed using non-linear mixed effect modeling (NONMEM(®)). Correlations between trough concentrations of the active moiety (risperidone plus 9-hydroxyrisperidone) and common side effects were assessed using logistic regression and linear mixed modeling. The cytochrome P450 (CYP) 2D6 phenotype explained 52% of interindividual variability in risperidone pharmacokinetics. The area under the concentration-time curve (AUC) of the active moiety was found to be 28% higher in CYP2D6 poor metabolizers compared with intermediate, extensive and ultrarapid metabolizers. No other genetic markers were found to significantly affect risperidone concentrations. 9-hydroxyrisperidone elimination was decreased by 26% with doubling of age. A correlation between trough predicted concentration of the active moiety and neurologic symptoms was found (p = 0.03), suggesting that a concentration >40 ng/mL should be targeted only in cases of insufficient, or absence of, response. Genetic polymorphisms of CYP2D6 play an important role in risperidone, 9-hydroxyrisperidone and active moiety plasma concentration variability, which were associated with common side effects. These results highlight the importance of a personalized dosage adjustment during risperidone treatment.

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.

Transformation of Summary Statistics from Linear Mixed Model Association on All-or-None Traits to Odds Ratio.

PubMed

Lloyd-Jones, Luke R; Robinson, Matthew R; Yang, Jian; Visscher, Peter M

2018-04-01

Genome-wide association studies (GWAS) have identified thousands of loci that are robustly associated with complex diseases. The use of linear mixed model (LMM) methodology for GWAS is becoming more prevalent due to its ability to control for population structure and cryptic relatedness and to increase power. The odds ratio (OR) is a common measure of the association of a disease with an exposure ( e.g. , a genetic variant) and is readably available from logistic regression. However, when the LMM is applied to all-or-none traits it provides estimates of genetic effects on the observed 0-1 scale, a different scale to that in logistic regression. This limits the comparability of results across studies, for example in a meta-analysis, and makes the interpretation of the magnitude of an effect from an LMM GWAS difficult. In this study, we derived transformations from the genetic effects estimated under the LMM to the OR that only rely on summary statistics. To test the proposed transformations, we used real genotypes from two large, publicly available data sets to simulate all-or-none phenotypes for a set of scenarios that differ in underlying model, disease prevalence, and heritability. Furthermore, we applied these transformations to GWAS summary statistics for type 2 diabetes generated from 108,042 individuals in the UK Biobank. In both simulation and real-data application, we observed very high concordance between the transformed OR from the LMM and either the simulated truth or estimates from logistic regression. The transformations derived and validated in this study improve the comparability of results from prospective and already performed LMM GWAS on complex diseases by providing a reliable transformation to a common comparative scale for the genetic effects. Copyright © 2018 by the Genetics Society of America.

The role of zonal flows in the saturation of multi-scale gyrokinetic turbulence

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

Staebler, G. M.; Candy, J.; Howard, N. T.

2016-06-15

The 2D spectrum of the saturated electric potential from gyrokinetic turbulence simulations that include both ion and electron scales (multi-scale) in axisymmetric tokamak geometry is analyzed. The paradigm that the turbulence is saturated when the zonal (axisymmetic) ExB flow shearing rate competes with linear growth is shown to not apply to the electron scale turbulence. Instead, it is the mixing rate by the zonal ExB velocity spectrum with the turbulent distribution function that competes with linear growth. A model of this mechanism is shown to be able to capture the suppression of electron-scale turbulence by ion-scale turbulence and the thresholdmore » for the increase in electron scale turbulence when the ion-scale turbulence is reduced. The model computes the strength of the zonal flow velocity and the saturated potential spectrum from the linear growth rate spectrum. The model for the saturated electric potential spectrum is applied to a quasilinear transport model and shown to accurately reproduce the electron and ion energy fluxes of the non-linear gyrokinetic multi-scale simulations. The zonal flow mixing saturation model is also shown to reproduce the non-linear upshift in the critical temperature gradient caused by zonal flows in ion-scale gyrokinetic simulations.« less

Quadratic constrained mixed discrete optimization with an adiabatic quantum optimizer

NASA Astrophysics Data System (ADS)

Chandra, Rishabh; Jacobson, N. Tobias; Moussa, Jonathan E.; Frankel, Steven H.; Kais, Sabre

2014-07-01

We extend the family of problems that may be implemented on an adiabatic quantum optimizer (AQO). When a quadratic optimization problem has at least one set of discrete controls and the constraints are linear, we call this a quadratic constrained mixed discrete optimization (QCMDO) problem. QCMDO problems are NP-hard, and no efficient classical algorithm for their solution is known. Included in the class of QCMDO problems are combinatorial optimization problems constrained by a linear partial differential equation (PDE) or system of linear PDEs. An essential complication commonly encountered in solving this type of problem is that the linear constraint may introduce many intermediate continuous variables into the optimization while the computational cost grows exponentially with problem size. We resolve this difficulty by developing a constructive mapping from QCMDO to quadratic unconstrained binary optimization (QUBO) such that the size of the QUBO problem depends only on the number of discrete control variables. With a suitable embedding, taking into account the physical constraints of the realizable coupling graph, the resulting QUBO problem can be implemented on an existing AQO. The mapping itself is efficient, scaling cubically with the number of continuous variables in the general case and linearly in the PDE case if an efficient preconditioner is available.

The role of zonal flows in the saturation of multi-scale gyrokinetic turbulence

DOE PAGES

Staebler, Gary M.; Candy, John; Howard, Nathan T.; ...

2016-06-29

The 2D spectrum of the saturated electric potential from gyrokinetic turbulence simulations that include both ion and electron scales (multi-scale) in axisymmetric tokamak geometry is analyzed. The paradigm that the turbulence is saturated when the zonal (axisymmetic) ExB flow shearing rate competes with linear growth is shown to not apply to the electron scale turbulence. Instead, it is the mixing rate by the zonal ExB velocity spectrum with the turbulent distribution function that competes with linear growth. A model of this mechanism is shown to be able to capture the suppression of electron-scale turbulence by ion-scale turbulence and the thresholdmore » for the increase in electron scale turbulence when the ion-scale turbulence is reduced. The model computes the strength of the zonal flow velocity and the saturated potential spectrum from the linear growth rate spectrum. The model for the saturated electric potential spectrum is applied to a quasilinear transport model and shown to accurately reproduce the electron and ion energy fluxes of the non-linear gyrokinetic multi-scale simulations. Finally, the zonal flow mixing saturation model is also shown to reproduce the non-linear upshift in the critical temperature gradient caused by zonal flows in ionscale gyrokinetic simulations.« less

Hg-Xe exciplex formation in mixed Xe/Ar matrices: molecular dynamics and luminescence study.

PubMed

Lozada-García, Rolando; Rojas-Lorenzo, Germán; Crépin, Claudine; Ryan, Maryanne; McCaffrey, John G

2015-03-19

Luminescence of Hg((3)P1) atoms trapped in mixed Ar/Xe matrices containing a small amount of Xe is reported. Broad emission bands, strongly red-shifted from absorption are recorded which are assigned to strong complexes formed between the excited mercury Hg* and xenon atoms. Molecular dynamics calculations are performed on simulated Xe/Ar samples doped with Hg to follow the behavior of Hg* in the mixed rare gas matrices leading to exciplex formation. The role of Xe atoms in the first solvation shell (SS1) around Hg was investigated in detail, revealing the formation of two kinds of triatomic exciplexes; namely, Xe-Hg*-Xe and Ar-Hg*-Xe. The first species exists only when two xenon atoms are present in SS1 with specific geometries allowing the formation of a linear or quasi-linear exciplex. In the other geometries, or in the presence of only one Xe in SS1, a linear Ar-Hg*-Xe exciplex is formed. The two kinds of exciplexes have different emission bands, the most red-shifted being that involving two Xe atoms, whose emission is very close to that observed in pure Xe matrices. Simulations give a direct access to the analysis of the experimental absorption, emission, and excitation spectra, together with the dynamics of exciplexes formation.

The Non-Linear Nature of Information and its Implications for Advanced Technology Forces

DTIC Science & Technology

1998-05-18

anticipated tremendous benefits from the growth of information based technology. It is now axiomatic that the ability to achieve information dominance against...the commercial world are mix. To achieve the information dominance anticipated through advances in technology, military decision makers must understand and accommodate the non-linear nature of the information systems they employ.

Radar Resource Management in a Dense Target Environment

DTIC Science & Technology

2014-03-01

problem faced by networked MFRs . While relaxing our assumptions concerning information gain presents numerous challenges worth exploring, future research...linear programming MFR multifunction phased array radar MILP mixed integer linear programming NATO North Atlantic Treaty Organization PDF probability...1: INTRODUCTION Multifunction phased array radars ( MFRs ) are capable of performing various tasks in rapid succession. The performance of target search

Pattern or process? Evaluating the peninsula effect as a determinant of species richness in coastal dune forests

PubMed Central

Olivier, Pieter I.; van Aarde, Rudi J.

2017-01-01

The peninsula effect predicts that the number of species should decline from the base of a peninsula to the tip. However, evidence for the peninsula effect is ambiguous, as different analytical methods, study taxa, and variations in local habitat or regional climatic conditions influence conclusions on its presence. We address this uncertainty by using two analytical methods to investigate the peninsula effect in three taxa that occupy different trophic levels: trees, millipedes, and birds. We surveyed 81 tree quadrants, 102 millipede transects, and 152 bird points within 150 km of coastal dune forest that resemble a habitat peninsula along the northeast coast of South Africa. We then used spatial (trend surface analyses) and non-spatial regressions (generalized linear mixed models) to test for the presence of the peninsula effect in each of the three taxa. We also used linear mixed models to test if climate (temperature and precipitation) and/or local habitat conditions (water availability associated with topography and landscape structural variables) could explain gradients in species richness. Non-spatial models suggest that the peninsula effect was present in all three taxa. However, spatial models indicated that only bird species richness declined from the peninsula base to the peninsula tip. Millipede species richness increased near the centre of the peninsula, while tree species richness increased near the tip. Local habitat conditions explained species richness patterns of birds and trees, but not of millipedes, regardless of model type. Our study highlights the idiosyncrasies associated with the peninsula effect—conclusions on the presence of the peninsula effect depend on the analytical methods used and the taxon studied. The peninsula effect might therefore be better suited to describe a species richness pattern where the number of species decline from a broader habitat base to a narrow tip, rather than a process that drives species richness. PMID:28376096

Effects of alfalfa flavonoids extract on the microbial flora of dairy cow rumen.

PubMed

Zhan, Jinshun; Liu, Mingmei; Wu, Caixia; Su, Xiaoshuang; Zhan, Kang; Zhao, Guo Qi

2017-09-01

The effect of flavonoids from alfalfa on the microbial flora was determined using molecular techniques of 16S ribosome deoxyribonucleic acid (rDNA) analysis. Four primiparous Holstein heifers fitted with ruminal cannulas were used in a 4×4 Latin square design and fed a total mixed ration to which alfalfa flavonoids extract (AFE) was added at the rates of 0 (A, control), 20 (B), 60 (C), or 100 (D) mg per kg of heifer BW. The number of operational taxonomic units in heifers given higher levels of flavonoid extract (C and D) was higher than for the two other treatments. The Shannon, Ace, and Chao indices for treatment C were significantly higher than for the other treatments (p<0.05). The number of phyla and genera increased linearly with increasing dietary supplementation of AFE (p<0.05). The principal co-ordinates analysis plot showed substantial differences in the microbial flora for the four treatments. The microbial flora in treatment A was similar to that in B, C, and D were similar by the weighted analysis. The richness of Tenericutes at the phylum level tended to increase with increasing AFE (p = 0.10). The proportion of Euryarchaeota at the phylum level increased linearly, whereas the proportion of Fusobacteria decreased linearly with increasing AFE supplementation (p = 0.04). The percentage of Mogibacterium , Pyramidobacter , and Asteroleplasma at the genus level decreased linearly with increasing AFE (p<0.05). The abundance of Spirochaeta , Succinivibrio , and Suttonella at the genus level tended to decrease linearly with increasing AFE (0.05

Nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates of typical desert vegetation in western China.

PubMed

Ji, Cuicui; Jia, Yonghong; Gao, Zhihai; Wei, Huaidong; Li, Xiaosong

2017-01-01

Desert vegetation plays significant roles in securing the ecological integrity of oasis ecosystems in western China. Timely monitoring of photosynthetic/non-photosynthetic desert vegetation cover is necessary to guide management practices on land desertification and research into the mechanisms driving vegetation recession. In this study, nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates are investigated through comparing the performance of linear and nonlinear spectral mixture models with different endmembers applied to field spectral measurements of two types of typical desert vegetation, namely, Nitraria shrubs and Haloxylon. The main results were as follows. (1) The correct selection of endmembers is important for improving the accuracy of vegetation cover estimates, and in particular, shadow endmembers cannot be neglected. (2) For both the Nitraria shrubs and Haloxylon, the Kernel-based Nonlinear Spectral Mixture Model (KNSMM) with nonlinear parameters was the best unmixing model. In consideration of the computational complexity and accuracy requirements, the Linear Spectral Mixture Model (LSMM) could be adopted for Nitraria shrubs plots, but this will result in significant errors for the Haloxylon plots since the nonlinear spectral mixture effects were more obvious for this vegetation type. (3) The vegetation canopy structure (planophile or erectophile) determines the strength of the nonlinear spectral mixture effects. Therefore, no matter for Nitraria shrubs or Haloxylon, the non-linear spectral mixing effects between the photosynthetic / non-photosynthetic vegetation and the bare soil do exist, and its strength is dependent on the three-dimensional structure of the vegetation canopy. The choice of linear or nonlinear spectral mixture models is up to the consideration of computational complexity and the accuracy requirement.

Nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates of typical desert vegetation in western China

PubMed Central

Jia, Yonghong; Gao, Zhihai; Wei, Huaidong

2017-01-01

Desert vegetation plays significant roles in securing the ecological integrity of oasis ecosystems in western China. Timely monitoring of photosynthetic/non-photosynthetic desert vegetation cover is necessary to guide management practices on land desertification and research into the mechanisms driving vegetation recession. In this study, nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates are investigated through comparing the performance of linear and nonlinear spectral mixture models with different endmembers applied to field spectral measurements of two types of typical desert vegetation, namely, Nitraria shrubs and Haloxylon. The main results were as follows. (1) The correct selection of endmembers is important for improving the accuracy of vegetation cover estimates, and in particular, shadow endmembers cannot be neglected. (2) For both the Nitraria shrubs and Haloxylon, the Kernel-based Nonlinear Spectral Mixture Model (KNSMM) with nonlinear parameters was the best unmixing model. In consideration of the computational complexity and accuracy requirements, the Linear Spectral Mixture Model (LSMM) could be adopted for Nitraria shrubs plots, but this will result in significant errors for the Haloxylon plots since the nonlinear spectral mixture effects were more obvious for this vegetation type. (3) The vegetation canopy structure (planophile or erectophile) determines the strength of the nonlinear spectral mixture effects. Therefore, no matter for Nitraria shrubs or Haloxylon, the non-linear spectral mixing effects between the photosynthetic / non-photosynthetic vegetation and the bare soil do exist, and its strength is dependent on the three-dimensional structure of the vegetation canopy. The choice of linear or nonlinear spectral mixture models is up to the consideration of computational complexity and the accuracy requirement. PMID:29240777

The role of multi-target policy instruments in agri-environmental policy mixes.

PubMed

Schader, Christian; Lampkin, Nicholas; Muller, Adrian; Stolze, Matthias

2014-12-01

The Tinbergen Rule has been used to criticise multi-target policy instruments for being inefficient. The aim of this paper is to clarify the role of multi-target policy instruments using the case of agri-environmental policy. Employing an analytical linear optimisation model, this paper demonstrates that there is no general contradiction between multi-target policy instruments and the Tinbergen Rule, if multi-target policy instruments are embedded in a policy-mix with a sufficient number of targeted instruments. We show that the relation between cost-effectiveness of the instruments, related to all policy targets, is the key determinant for an economically sound choice of policy instruments. If economies of scope with respect to achieving policy targets are realised, a higher cost-effectiveness of multi-target policy instruments can be achieved. Using the example of organic farming support policy, we discuss several reasons why economies of scope could be realised by multi-target agri-environmental policy instruments. Copyright © 2014 Elsevier Ltd. All rights reserved.

Longitudinal models of reading achievement of students with learning disabilities and without disabilities.

PubMed

Sullivan, Amanda L; Kohli, Nidhi; Farnsworth, Elyse M; Sadeh, Shanna; Jones, Leila

2017-09-01

Accurate estimation of developmental trajectories can inform instruction and intervention. We compared the fit of linear, quadratic, and piecewise mixed-effects models of reading development among students with learning disabilities relative to their typically developing peers. We drew an analytic sample of 1,990 students from the nationally representative Early Childhood Longitudinal Study-Kindergarten Cohort of 1998, using reading achievement scores from kindergarten through eighth grade to estimate three models of students' reading growth. The piecewise mixed-effects models provided the best functional form of the students' reading trajectories as indicated by model fit indices. Results showed slightly different trajectories between students with learning disabilities and without disabilities, with varying but divergent rates of growth throughout elementary grades, as well as an increasing gap over time. These results highlight the need for additional research on appropriate methods for modeling reading trajectories and the implications for students' response to instruction. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Hybrid Model Predictive Control for Sequential Decision Policies in Adaptive Behavioral Interventions.

PubMed

Dong, Yuwen; Deshpande, Sunil; Rivera, Daniel E; Downs, Danielle S; Savage, Jennifer S

2014-06-01

Control engineering offers a systematic and efficient method to optimize the effectiveness of individually tailored treatment and prevention policies known as adaptive or "just-in-time" behavioral interventions. The nature of these interventions requires assigning dosages at categorical levels, which has been addressed in prior work using Mixed Logical Dynamical (MLD)-based hybrid model predictive control (HMPC) schemes. However, certain requirements of adaptive behavioral interventions that involve sequential decision making have not been comprehensively explored in the literature. This paper presents an extension of the traditional MLD framework for HMPC by representing the requirements of sequential decision policies as mixed-integer linear constraints. This is accomplished with user-specified dosage sequence tables, manipulation of one input at a time, and a switching time strategy for assigning dosages at time intervals less frequent than the measurement sampling interval. A model developed for a gestational weight gain (GWG) intervention is used to illustrate the generation of these sequential decision policies and their effectiveness for implementing adaptive behavioral interventions involving multiple components.

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

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.