Interpretable inference on the mixed effect model with the Box-Cox transformation.

Science.gov (United States)

Maruo, K; Yamaguchi, Y; Noma, H; Gosho, M

2017-07-10

We derived results for inference on parameters of the marginal model of the mixed effect model with the Box-Cox transformation based on the asymptotic theory approach. We also provided a robust variance estimator of the maximum likelihood estimator of the parameters of this model in consideration of the model misspecifications. Using these results, we developed an inference procedure for the difference of the model median between treatment groups at the specified occasion in the context of mixed effects models for repeated measures analysis for randomized clinical trials, which provided interpretable estimates of the treatment effect. From simulation studies, it was shown that our proposed method controlled type I error of the statistical test for the model median difference in almost all the situations and had moderate or high performance for power compared with the existing methods. We illustrated our method with cluster of differentiation 4 (CD4) data in an AIDS clinical trial, where the interpretability of the analysis results based on our proposed method is demonstrated. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Stochastic Mixed-Effects Parameters Bertalanffy Process, with Applications to Tree Crown Width Modeling

Directory of Open Access Journals (Sweden)

Petras Rupšys

2015-01-01

Full Text Available A stochastic modeling approach based on the Bertalanffy law gained interest due to its ability to produce more accurate results than the deterministic approaches. We examine tree crown width dynamic with the Bertalanffy type stochastic differential equation (SDE and mixed-effects parameters. In this study, we demonstrate how this simple model can be used to calculate predictions of crown width. We propose a parameter estimation method and computational guidelines. The primary goal of the study was to estimate the parameters by considering discrete sampling of the diameter at breast height and crown width and by using maximum likelihood procedure. Performance statistics for the crown width equation include statistical indexes and analysis of residuals. We use data provided by the Lithuanian National Forest Inventory from Scots pine trees to illustrate issues of our modeling technique. Comparison of the predicted crown width values of mixed-effects parameters model with those obtained using fixed-effects parameters model demonstrates the predictive power of the stochastic differential equations model with mixed-effects parameters. All results were implemented in a symbolic algebra system MAPLE.

A Linear Mixed-Effects Model of Wireless Spectrum Occupancy

Directory of Open Access Journals (Sweden)

Pagadarai Srikanth

2010-01-01

Full Text Available We provide regression analysis-based statistical models to explain the usage of wireless spectrum across four mid-size US cities in four frequency bands. Specifically, the variations in spectrum occupancy across space, time, and frequency are investigated and compared between different sites within the city as well as with other cities. By applying the mixed-effects models, several conclusions are drawn that give the occupancy percentage and the ON time duration of the licensed signal transmission as a function of several predictor variables.

Analysis and modeling of subgrid scalar mixing using numerical data

Science.gov (United States)

Girimaji, Sharath S.; Zhou, YE

1995-01-01

Direct numerical simulations (DNS) of passive scalar mixing in isotropic turbulence is used to study, analyze and, subsequently, model the role of small (subgrid) scales in the mixing process. In particular, we attempt to model the dissipation of the large scale (supergrid) scalar fluctuations caused by the subgrid scales by decomposing it into two parts: (1) the effect due to the interaction among the subgrid scales; and (2) the effect due to interaction between the supergrid and the subgrid scales. Model comparisons with DNS data show good agreement. This model is expected to be useful in the large eddy simulations of scalar mixing and reaction.

Linear and Generalized Linear Mixed Models and Their Applications

CERN Document Server

Jiang, Jiming

2007-01-01

This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it has included recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the context of mixed models. The book is aimed at students, researchers and other practitioners who are interested

Extending the linear model with R generalized linear, mixed effects and nonparametric regression models

CERN Document Server

Faraway, Julian J

2005-01-01

Linear models are central to the practice of statistics and form the foundation of a vast range of statistical methodologies. Julian J. Faraway''s critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods available, and showed in which situations each one applies. Following in those footsteps, Extending the Linear Model with R surveys the techniques that grow from the regression model, presenting three extensions to that framework: generalized linear models (GLMs), mixed effect models, and nonparametric regression models. The author''s treatment is thoroughly modern and covers topics that include GLM diagnostics, generalized linear mixed models, trees, and even the use of neural networks in statistics. To demonstrate the interplay of theory and practice, throughout the book the author weaves the use of the R software environment to analyze the data of real examples, providing all of the R commands necessary to reproduce the analyses. All of the ...

Analysis of oligonucleotide array experiments with repeated measures using mixed models

Directory of Open Access Journals (Sweden)

Getchell Thomas V

2004-12-01

Full Text Available Abstract Background Two or more factor mixed factorial experiments are becoming increasingly common in microarray data analysis. In this case study, the two factors are presence (Patients with Alzheimer's disease or absence (Control of the disease, and brain regions including olfactory bulb (OB or cerebellum (CER. In the design considered in this manuscript, OB and CER are repeated measurements from the same subject and, hence, are correlated. It is critical to identify sources of variability in the analysis of oligonucleotide array experiments with repeated measures and correlations among data points have to be considered. In addition, multiple testing problems are more complicated in experiments with multi-level treatments or treatment combinations. Results In this study we adopted a linear mixed model to analyze oligonucleotide array experiments with repeated measures. We first construct a generalized F test to select differentially expressed genes. The Benjamini and Hochberg (BH procedure of controlling false discovery rate (FDR at 5% was applied to the P values of the generalized F test. For those genes with significant generalized F test, we then categorize them based on whether the interaction terms were significant or not at the α-level (αnew = 0.0033 determined by the FDR procedure. Since simple effects may be examined for the genes with significant interaction effect, we adopt the protected Fisher's least significant difference test (LSD procedure at the level of αnew to control the family-wise error rate (FWER for each gene examined. Conclusions A linear mixed model is appropriate for analysis of oligonucleotide array experiments with repeated measures. We constructed a generalized F test to select differentially expressed genes, and then applied a specific sequence of tests to identify factorial effects. This sequence of tests applied was designed to control for gene based FWER.

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

Science.gov (United States)

Ker, H. W.

2014-01-01

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

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

Science.gov (United States)

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...

Modeling Dynamic Effects of the Marketing Mix on Market Shares

NARCIS (Netherlands)

D. Fok (Dennis); R. Paap (Richard); Ph.H.B.F. Franses (Philip Hans)

2003-01-01

textabstractTo comprehend the competitive structure of a market, it is important to understand the short-run and long-run effects of the marketing mix on market shares. A useful model to link market shares with marketing-mix variables, like price and promotion, is the market share attraction model.

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

Science.gov (United States)

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

2017-10-25

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

Estimation and Inference for Very Large Linear Mixed Effects Models

OpenAIRE

Gao, K.; Owen, A. B.

2016-01-01

Linear mixed models with large imbalanced crossed random effects structures pose severe computational problems for maximum likelihood estimation and for Bayesian analysis. The costs can grow as fast as $N^{3/2}$ when there are N observations. Such problems arise in any setting where the underlying factors satisfy a many to many relationship (instead of a nested one) and in electronic commerce applications, the N can be quite large. Methods that do not account for the correlation structure can...

The salinity effect in a mixed layer ocean model

Science.gov (United States)

Miller, J. R.

1976-01-01

A model of the thermally mixed layer in the upper ocean as developed by Kraus and Turner and extended by Denman is further extended to investigate the effects of salinity. In the tropical and subtropical Atlantic Ocean rapid increases in salinity occur at the bottom of a uniformly mixed surface layer. The most significant effects produced by the inclusion of salinity are the reduction of the deepening rate and the corresponding change in the heating characteristics of the mixed layer. If the net surface heating is positive, but small, salinity effects must be included to determine whether the mixed layer temperature will increase or decrease. Precipitation over tropical oceans leads to the development of a shallow stable layer accompanied by a decrease in the temperature and salinity at the sea surface.

Mixing Modeling Analysis For SRS Salt Waste Disposition

International Nuclear Information System (INIS)

Lee, S.

2011-01-01

Nuclear waste at Savannah River Site (SRS) waste tanks consists of three different types of waste forms. They are the lighter salt solutions referred to as supernate, the precipitated salts as salt cake, and heavier fine solids as sludge. The sludge is settled on the tank floor. About half of the residual waste radioactivity is contained in the sludge, which is only about 8 percentage of the total waste volume. Mixing study to be evaluated here for the Salt Disposition Integration (SDI) project focuses on supernate preparations in waste tanks prior to transfer to the Salt Waste Processing Facility (SWPF) feed tank. The methods to mix and blend the contents of the SRS blend tanks were evalutaed to ensure that the contents are properly blended before they are transferred from the blend tank such as Tank 50H to the SWPF feed tank. The work consists of two principal objectives to investigate two different pumps. One objective is to identify a suitable pumping arrangement that will adequately blend/mix two miscible liquids to obtain a uniform composition in the tank with a minimum level of sludge solid particulate in suspension. The other is to estimate the elevation in the tank at which the transfer pump inlet should be located where the solid concentration of the entrained fluid remains below the acceptance criterion (0.09 wt% or 1200 mg/liter) during transfer operation to the SWPF. Tank 50H is a Waste Tank that will be used to prepare batches of salt feed for SWPF. The salt feed must be a homogeneous solution satisfying the acceptance criterion of the solids entrainment during transfer operation. The work described here consists of two modeling areas. They are the mixing modeling analysis during miscible liquid blending operation, and the flow pattern analysis during transfer operation of the blended liquid. The modeling results will provide quantitative design and operation information during the mixing/blending process and the transfer operation of the blended

Performance of nonlinear mixed effects models in the presence of informative dropout.

Science.gov (United States)

Björnsson, Marcus A; Friberg, Lena E; Simonsson, Ulrika S H

2015-01-01

Informative dropout can lead to bias in statistical analyses if not handled appropriately. The objective of this simulation study was to investigate the performance of nonlinear mixed effects models with regard to bias and precision, with and without handling informative dropout. An efficacy variable and dropout depending on that efficacy variable were simulated and model parameters were reestimated, with or without including a dropout model. The Laplace and FOCE-I estimation methods in NONMEM 7, and the stochastic simulations and estimations (SSE) functionality in PsN, were used in the analysis. For the base scenario, bias was low, less than 5% for all fixed effects parameters, when a dropout model was used in the estimations. When a dropout model was not included, bias increased up to 8% for the Laplace method and up to 21% if the FOCE-I estimation method was applied. The bias increased with decreasing number of observations per subject, increasing placebo effect and increasing dropout rate, but was relatively unaffected by the number of subjects in the study. This study illustrates that ignoring informative dropout can lead to biased parameters in nonlinear mixed effects modeling, but even in cases with few observations or high dropout rate, the bias is relatively low and only translates into small effects on predictions of the underlying effect variable. A dropout model is, however, crucial in the presence of informative dropout in order to make realistic simulations of trial outcomes.

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

Science.gov (United States)

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

2008-12-20

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

Evaluating significance in linear mixed-effects models in R.

Science.gov (United States)

Luke, Steven G

2017-08-01

Mixed-effects models are being used ever more frequently in the analysis of experimental data. However, in the lme4 package in R the standards for evaluating significance of fixed effects in these models (i.e., obtaining p-values) are somewhat vague. There are good reasons for this, but as researchers who are using these models are required in many cases to report p-values, some method for evaluating the significance of the model output is needed. This paper reports the results of simulations showing that the two most common methods for evaluating significance, using likelihood ratio tests and applying the z distribution to the Wald t values from the model output (t-as-z), are somewhat anti-conservative, especially for smaller sample sizes. Other methods for evaluating significance, including parametric bootstrapping and the Kenward-Roger and Satterthwaite approximations for degrees of freedom, were also evaluated. The results of these simulations suggest that Type 1 error rates are closest to .05 when models are fitted using REML and p-values are derived using the Kenward-Roger or Satterthwaite approximations, as these approximations both produced acceptable Type 1 error rates even for smaller samples.

Development of two mix model postprocessors for the investigation of shell mix in indirect drive implosion cores

International Nuclear Information System (INIS)

Welser-Sherrill, L.; Mancini, R. C.; Haynes, D. A.; Haan, S. W.; Koch, J. A.; Izumi, N.; Tommasini, R.; Golovkin, I. E.; MacFarlane, J. J.; Radha, P. B.; Delettrez, J. A.; Regan, S. P.; Smalyuk, V. A.

2007-01-01

The presence of shell mix in inertial confinement fusion implosion cores is an important characteristic. Mixing in this experimental regime is primarily due to hydrodynamic instabilities, such as Rayleigh-Taylor and Richtmyer-Meshkov, which can affect implosion dynamics. Two independent theoretical mix models, Youngs' model and the Haan saturation model, were used to estimate the level of Rayleigh-Taylor mixing in a series of indirect drive experiments. The models were used to predict the radial width of the region containing mixed fuel and shell materials. The results for Rayleigh-Taylor mixing provided by Youngs' model are considered to be a lower bound for the mix width, while those generated by Haan's model incorporate more experimental characteristics and consequently have larger mix widths. These results are compared with an independent experimental analysis, which infers a larger mix width based on all instabilities and effects captured in the experimental data

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

Science.gov (United States)

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.

Sensitivity Analysis of Mixed Models for Incomplete Longitudinal Data

Science.gov (United States)

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, Linear, and Mixed Models

CERN Document Server

McCulloch, Charles E; Neuhaus, John M

2011-01-01

An accessible and self-contained introduction to statistical models-now in a modernized new editionGeneralized, Linear, and Mixed Models, Second Edition provides an up-to-date treatment of the essential techniques for developing and applying a wide variety of statistical models. The book presents thorough and unified coverage of the theory behind generalized, linear, and mixed models and highlights their similarities and differences in various construction, application, and computational aspects.A clear introduction to the basic ideas of fixed effects models, random effects models, and mixed m

A brief introduction to regression designs and mixed-effects modelling by a recent convert

DEFF Research Database (Denmark)

Balling, Laura Winther

2008-01-01

This article discusses the advantages of multiple regression designs over the factorial designs traditionally used in many psycholinguistic experiments. It is shown that regression designs are typically more informative, statistically more powerful and better suited to the analysis of naturalistic...... tasks. The advantages of including both fixed and random effects are demonstrated with reference to linear mixed-effects models, and problems of collinearity, variable distribution and variable selection are discussed. The advantages of these techniques are exemplified in an analysis of a word...

Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

DEFF Research Database (Denmark)

Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

2014-01-01

A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...

Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

DEFF Research Database (Denmark)

Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

2013-01-01

A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...

Longitudinal mixed-effects models for latent cognitive function

NARCIS (Netherlands)

van den Hout, Ardo; Fox, Gerardus J.A.; Muniz-Terrera, Graciela

2015-01-01

A mixed-effects regression model with a bent-cable change-point predictor is formulated to describe potential decline of cognitive function over time in the older population. For the individual trajectories, cognitive function is considered to be a latent variable measured through an item response

Development of two phase turbulent mixing model for subchannel analysis relevant to BWR

International Nuclear Information System (INIS)

Sharma, M.P.; Nayak, A.K.; Kannan, Umasankari

2014-01-01

A two phase flow model is presented, which predicts both liquid and gas phase turbulent mixing rate between adjacent subchannels of reactor rod bundles. The model presented here is for slug churn flow regime, which is dominant as compared to the other regimes like bubbly flow and annular flow regimes, since turbulent mixing rate is the highest in slug churn flow regime. In this paper, we have defined new dimensionless parameters i.e. liquid mixing number and gas mixing number for two phase turbulent mixing. The liquid mixing number is a function of mixture Reynolds number whereas the gas phase mixing number is a function of both mixture Reynolds number and volumetric fraction of gas. The effect of pressure, geometrical influence of subchannel is also included in this model. The present model has been tested against low pressure and temperature air-water and high pressure and temperature steam-water experimental data found that it shows good agreement with available experimental data. (author)

Mixed Models and Reduction Techniques for Large-Rotation, Nonlinear Analysis of Shells of Revolution with Application to Tires

Science.gov (United States)

Noor, A. K.; Andersen, C. M.; Tanner, J. A.

1984-01-01

An effective computational strategy is presented for the large-rotation, nonlinear axisymmetric analysis of shells of revolution. The three key elements of the computational strategy are: (1) use of mixed finite-element models with discontinuous stress resultants at the element interfaces; (2) substantial reduction in the total number of degrees of freedom through the use of a multiple-parameter reduction technique; and (3) reduction in the size of the analysis model through the decomposition of asymmetric loads into symmetric and antisymmetric components coupled with the use of the multiple-parameter reduction technique. The potential of the proposed computational strategy is discussed. Numerical results are presented to demonstrate the high accuracy of the mixed models developed and to show the potential of using the proposed computational strategy for the analysis of tires.

Linear mixed models for longitudinal data

CERN Document Server

Molenberghs, Geert

2000-01-01

This paperback edition is a reprint of the 2000 edition. This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Several variations to the conventional linear mixed model are discussed (a heterogeity model, conditional linear mixed models). This book will be of interest to applied statisticians and biomedical researchers in industry, public health organizations, contract research organizations, and academia. The book is explanatory rather than mathematically rigorous. Most analyses were done with the MIXED procedure of the SAS software package, and many of its features are clearly elucidated. However, some other commerc...

Effects of the ρ - ω mixing interaction in relativistic models

International Nuclear Information System (INIS)

Menezes, D.P.; Providencia, C.

2003-01-01

The effects of the ρ-ω mixing term in infinite nuclear matter and in finite nuclei are investigated with the non-linear Walecka model in a Thomas-Fermi approximation. For infinite nuclear matter the influence of the mixing term in the binding energy calculated with the NL3 and TM1 parametrizations can be neglected. Its influence on the symmetry energy is only felt for the TM1 with a unrealistically large value for the mixing term strength. For finite nuclei the contribution of the isospin mixing term is very large as compared with the expected value to solve the Nolen-Schiffer anomaly

A brief introduction to regression designs and mixed-effects modelling by a recent convert

OpenAIRE

Balling, Laura Winther

2008-01-01

This article discusses the advantages of multiple regression designs over the factorial designs traditionally used in many psycholinguistic experiments. It is shown that regression designs are typically more informative, statistically more powerful and better suited to the analysis of naturalistic tasks. The advantages of including both fixed and random effects are demonstrated with reference to linear mixed-effects models, and problems of collinearity, variable distribution and variable sele...

AUTOMATED ANALYSIS OF QUANTITATIVE IMAGE DATA USING ISOMORPHIC FUNCTIONAL MIXED MODELS, WITH APPLICATION TO PROTEOMICS DATA.

Science.gov (United States)

Morris, Jeffrey S; Baladandayuthapani, Veerabhadran; Herrick, Richard C; Sanna, Pietro; Gutstein, Howard

2011-01-01

Image data are increasingly encountered and are of growing importance in many areas of science. Much of these data are quantitative image data, which are characterized by intensities that represent some measurement of interest in the scanned images. The data typically consist of multiple images on the same domain and the goal of the research is to combine the quantitative information across images to make inference about populations or interventions. In this paper, we present a unified analysis framework for the analysis of quantitative image data using a Bayesian functional mixed model approach. This framework is flexible enough to handle complex, irregular images with many local features, and can model the simultaneous effects of multiple factors on the image intensities and account for the correlation between images induced by the design. We introduce a general isomorphic modeling approach to fitting the functional mixed model, of which the wavelet-based functional mixed model is one special case. With suitable modeling choices, this approach leads to efficient calculations and can result in flexible modeling and adaptive smoothing of the salient features in the data. The proposed method has the following advantages: it can be run automatically, it produces inferential plots indicating which regions of the image are associated with each factor, it simultaneously considers the practical and statistical significance of findings, and it controls the false discovery rate. Although the method we present is general and can be applied to quantitative image data from any application, in this paper we focus on image-based proteomic data. We apply our method to an animal study investigating the effects of opiate addiction on the brain proteome. Our image-based functional mixed model approach finds results that are missed with conventional spot-based analysis approaches. In particular, we find that the significant regions of the image identified by the proposed method

Dialectical behavior therapy for borderline personality disorder: a meta-analysis using mixed-effects modeling.

Science.gov (United States)

Kliem, Sören; Kröger, Christoph; Kosfelder, Joachim

2010-12-01

At present, the most frequently investigated psychosocial intervention for borderline personality disorder (BPD) is dialectical behavior therapy (DBT). We conducted a meta-analysis to examine the efficacy and long-term effectiveness of DBT. Systematic bibliographic research was undertaken to find relevant literature from online databases (PubMed, PsycINFO, PsychSpider, Medline). We excluded studies in which patients with diagnoses other than BPD were treated, the treatment did not comprise all components specified in the DBT manual or in the suggestions for inpatient DBT programs, patients failed to be diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, and the intervention group comprised fewer than 10 patients. Using a mixed-effect hierarchical modeling approach, we calculated global effect sizes and effect sizes for suicidal and self-injurious behaviors. Calculations of postintervention global effect sizes were based on 16 studies. Of these, 8 were randomized controlled trials (RCTs), and 8 were neither randomized nor controlled (nRCT). The dropout rate was 27.3% pre- to posttreatment. A moderate global effect and a moderate effect size for suicidal and self-injurious behaviors were found, when including a moderator for RCTs with borderline-specific treatments. There was no evidence for the influence of other moderators (e.g., quality of studies, setting, duration of intervention). A small impairment was shown from posttreatment to follow-up, including 5 RCTs only. Future research should compare DBT with other active borderline-specific treatments that have also demonstrated their efficacy using several long-term follow-up assessment points. (c) 2010 APA, all rights reserved.

Decision-case mix model for analyzing variation in cesarean rates.

Science.gov (United States)

Eldenburg, L; Waller, W S

2001-01-01

This article contributes a decision-case mix model for analyzing variation in c-section rates. Like recent contributions to the literature, the model systematically takes into account the effect of case mix. Going beyond past research, the model highlights differences in physician decision making in response to obstetric factors. Distinguishing the effects of physician decision making and case mix is important in understanding why c-section rates vary and in developing programs to effect change in physician behavior. The model was applied to a sample of deliveries at a hospital where physicians exhibited considerable variation in their c-section rates. Comparing groups with a low versus high rate, the authors' general conclusion is that the difference in physician decision tendencies (to perform a c-section), in response to specific obstetric factors, is at least as important as case mix in explaining variation in c-section rates. The exact effects of decision making versus case mix depend on how the model application defines the obstetric condition of interest and on the weighting of deliveries by their estimated "risk of Cesarean." The general conclusion is supported by an additional analysis that uses the model's elements to predict individual physicians' annual c-section rates.

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

Science.gov (United States)

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.

CFD analysis on mixing effects of spacer grids with different dimples and sizes for advanced fuel assemblies

Energy Technology Data Exchange (ETDEWEB)

Yang, B.W.; Zhang, H.; Han, B.; Zha, Y.D.; Shan, J.Q. [Xi' an Jiaotong Univ. (China). School of Nuclear Science and Technology

2016-07-15

The thermal hydraulic characteristics of a mixing vane grid are largely dependent on the structure of key components, such as strip, spring, dimple, weld nugget, as well as the mixing vane configuration. In this paper, several types of spacer grids with different dimple shapes are modeled under subcooled boiling conditions. Prior to the application of CFD on the dimple shape analysis, the mixing effects of spacer grids were studied. After the dimple shape analysis, the side channel effect is discussed by comparing the simulation results of a 3 x 3 and a 5 x 5 spacer grid. The two phase flow CFD models in this study are validated through simple geometry showing that the calculated void fraction is in good agreement with the experimental data. The dimple comparison result shows that varying dimple structures can result in different temperatures, lateral velocities and void fraction distributions downstream of the spacer grids. Comparison of two sizes of spacer grids demonstrate that the side channel generates different flow distribution pattern in the center channel.

Differential expression analysis for RNAseq using Poisson mixed models.

Science.gov (United States)

Sun, Shiquan; Hood, Michelle; Scott, Laura; Peng, Qinke; Mukherjee, Sayan; Tung, Jenny; Zhou, Xiang

2017-06-20

Identifying differentially expressed (DE) genes from RNA sequencing (RNAseq) studies is among the most common analyses in genomics. However, RNAseq DE analysis presents several statistical and computational challenges, including over-dispersed read counts and, in some settings, sample non-independence. Previous count-based methods rely on simple hierarchical Poisson models (e.g. negative binomial) to model independent over-dispersion, but do not account for sample non-independence due to relatedness, population structure and/or hidden confounders. Here, we present a Poisson mixed model with two random effects terms that account for both independent over-dispersion and sample non-independence. We also develop a scalable sampling-based inference algorithm using a latent variable representation of the Poisson distribution. With simulations, we show that our method properly controls for type I error and is generally more powerful than other widely used approaches, except in small samples (n <15) with other unfavorable properties (e.g. small effect sizes). We also apply our method to three real datasets that contain related individuals, population stratification or hidden confounders. Our results show that our method increases power in all three data compared to other approaches, though the power gain is smallest in the smallest sample (n = 6). Our method is implemented in MACAU, freely available at www.xzlab.org/software.html. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Examples of mixed-effects modeling with crossed random effects and with binomial data

NARCIS (Netherlands)

Quené, H.; van den Bergh, H.

2008-01-01

Psycholinguistic data are often analyzed with repeated-measures analyses of variance (ANOVA), but this paper argues that mixed-effects (multilevel) models provide a better alternative method. First, models are discussed in which the two random factors of participants and items are crossed, and not

[Application of Mixed-effect Model in PMI Estimation by Vitreous Humor].

Science.gov (United States)

Yang, M Z; Li, H J; Zhang, T Y; Ding, Z J; Wu, S F; Qiu, X G; Liu, Q

2018-02-01

To test the changes of the potassium （K⁺） and magnesium （Mg²⁺） concentrations in vitreous humor of rabbits along with postmortem interval （PMI） under different temperatures, and explore the feasibility of PMI estimation using mixed-effect model. After sacrifice, rabbit carcasses were preserved at 5 ℃, 15 ℃, 25 ℃ and 35 ℃, and 80-100 μL of vitreous humor was collected by the double-eye alternating micro-sampling method at every 12 h. The concentrations of K⁺ and Mg²⁺ in vitreous humor were measured by a biochemical-immune analyser. The mixed-effect model was used to perform analysis and fitting, and established the equations for PMI estimation. The data detected from the samples that were stoned at 10 ℃, 20 ℃ and 30 ℃ with 20, 40 and 65 h were used to validate the equations of PMI estimation. The concentrations of K⁺ and Mg²⁺ [f（ x , y ）] in vitreous humor of rabbits under different temperature increased along with PMI （ x ）. The relative equations of K⁺ and Mg²⁺ concentration with PMI and temperature under 5 ℃~35 ℃ were f K⁺ （ x , y ）=3.413 0+0.309 2 x +0.337 6 y +0.010 83 xy -0.002 47 x ² （ P PMI estimation by K⁺ and Mg²⁺ was in 10 h when PMI was between 0 to 40 h, and the time of deviation was in 21 h when PMI was between 40 to 65 h. the ambient temperature range of 5 ℃-35 ℃, the mixed-effect model based on temperature and vitreous humor substance concentrations can provide a new method for the practical application of vitreous humor chemicals for PMI estimation. Copyright© by the Editorial Department of Journal of Forensic Medicine.

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

Science.gov (United States)

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 linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p 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

The transition model test for serial dependence in mixed-effects models for binary data

DEFF Research Database (Denmark)

Breinegaard, Nina; Rabe-Hesketh, Sophia; Skrondal, Anders

2017-01-01

Generalized linear mixed models for longitudinal data assume that responses at different occasions are conditionally independent, given the random effects and covariates. Although this assumption is pivotal for consistent estimation, violation due to serial dependence is hard to assess by model...

A brief introduction to mixed effects modelling and multi-model inference in ecology.

Science.gov (United States)

Harrison, Xavier A; Donaldson, Lynda; Correa-Cano, Maria Eugenia; Evans, Julian; Fisher, David N; Goodwin, Cecily E D; Robinson, Beth S; Hodgson, David J; Inger, Richard

2018-01-01

The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological data. Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models is not always straightforward. The ability to achieve robust biological inference requires that practitioners know how and when to apply these tools. Here, we provide a general overview of current methods for the application of LMMs to biological data, and highlight the typical pitfalls that can be encountered in the statistical modelling process. We tackle several issues regarding methods of model selection, with particular reference to the use of information theory and multi-model inference in ecology. We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding. This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions.

Comparison of Repeated Measurement Design and Mixed Models in Evaluation of the Entonox Effect on Labor Pain

Directory of Open Access Journals (Sweden)

Nasim Karimi

2017-01-01

Full Text Available Background & objectives: In many medical studies, the response variable is measured repeatedly over time to evaluate the treatment effect that is known as longitudinal study. The analysis method for this type of data is repeated measures ANOVA that uses only one correlation structure and the results are not valid with inappropriate correlation structure. To avoid this problem, a convenient alternative is mixed models. So, the aim of this study was to compare of mixed and repeated measurement models for examination of the Entonox effect on the labor pain. Methods: This experimental study was designed to compare the effect of Entonox and oxygen inhalation on pain relief between two groups. Data were analyzed using repeated measurement and mixed models with different correlation structures. Selection and comparison of proper correlation structures performed using Akaike information criterion, Bayesian information criterion and restricted log-likelihood. Data were analyzed using SPSS-22. Results: Results of our study showed that all variables containing analgesia methods, labor duration of the first and second stages, and time were significant in these tests. In mixed model, heterogeneous first-order autoregressive, first-order autoregressive, heterogeneous Toeplitz and unstructured correlation structures were recognized as the best structures. Also, all variables were significant in these structures. Unstructured variance covariance matrix was recognized as the worst structure and labor duration of the first and second stages was not significant in this structure. Conclusions: This study showed that the Entonox inhalation has a significant effect on pain relief in primiparous and it is confirmed by all of the models.

Modelling ventricular fibrillation coarseness during cardiopulmonary resuscitation by mixed effects stochastic differential equations.

Science.gov (United States)

Gundersen, Kenneth; Kvaløy, Jan Terje; Eftestøl, Trygve; Kramer-Johansen, Jo

2015-10-15

For patients undergoing cardiopulmonary resuscitation (CPR) and being in a shockable rhythm, the coarseness of the electrocardiogram (ECG) signal is an indicator of the state of the patient. In the current work, we show how mixed effects stochastic differential equations (SDE) models, commonly used in pharmacokinetic and pharmacodynamic modelling, can be used to model the relationship between CPR quality measurements and ECG coarseness. This is a novel application of mixed effects SDE models to a setting quite different from previous applications of such models and where using such models nicely solves many of the challenges involved in analysing the available data. Copyright © 2015 John Wiley & Sons, Ltd.

Estimating the numerical diapycnal mixing in an eddy-permitting ocean model

Science.gov (United States)

Megann, Alex

2018-01-01

Constant-depth (or "z-coordinate") ocean models such as MOM4 and NEMO have become the de facto workhorse in climate applications, having attained a mature stage in their development and are well understood. A generic shortcoming of this model type, however, is a tendency for the advection scheme to produce unphysical numerical diapycnal mixing, which in some cases may exceed the explicitly parameterised mixing based on observed physical processes, and this is likely to have effects on the long-timescale evolution of the simulated climate system. Despite this, few quantitative estimates have been made of the typical magnitude of the effective diapycnal diffusivity due to numerical mixing in these models. GO5.0 is a recent ocean model configuration developed jointly by the UK Met Office and the National Oceanography Centre. It forms the ocean component of the GC2 climate model, and is closely related to the ocean component of the UKESM1 Earth System Model, the UK's contribution to the CMIP6 model intercomparison. GO5.0 uses version 3.4 of the NEMO model, on the ORCA025 global tripolar grid. An approach to quantifying the numerical diapycnal mixing in this model, based on the isopycnal watermass analysis of Lee et al. (2002), is described, and the estimates thereby obtained of the effective diapycnal diffusivity in GO5.0 are compared with the values of the explicit diffusivity used by the model. It is shown that the effective mixing in this model configuration is up to an order of magnitude higher than the explicit mixing in much of the ocean interior, implying that mixing in the model below the mixed layer is largely dominated by numerical mixing. This is likely to have adverse consequences for the representation of heat uptake in climate models intended for decadal climate projections, and in particular is highly relevant to the interpretation of the CMIP6 class of climate models, many of which use constant-depth ocean models at ¼° resolution

Some consequences of assuming simple patterns for the treatment effect over time in a linear mixed model.

Science.gov (United States)

Bamia, Christina; White, Ian R; Kenward, Michael G

2013-07-10

Linear mixed models are often used for the analysis of data from clinical trials with repeated quantitative outcomes. This paper considers linear mixed models where a particular form is assumed for the treatment effect, in particular constant over time or proportional to time. For simplicity, we assume no baseline covariates and complete post-baseline measures, and we model arbitrary mean responses for the control group at each time. For the variance-covariance matrix, we consider an unstructured model, a random intercepts model and a random intercepts and slopes model. We show that the treatment effect estimator can be expressed as a weighted average of the observed time-specific treatment effects, with weights depending on the covariance structure and the magnitude of the estimated variance components. For an assumed constant treatment effect, under the random intercepts model, all weights are equal, but in the random intercepts and slopes and the unstructured models, we show that some weights can be negative: thus, the estimated treatment effect can be negative, even if all time-specific treatment effects are positive. Our results suggest that particular models for the treatment effect combined with particular covariance structures may result in estimated treatment effects of unexpected magnitude and/or direction. Methods are illustrated using a Parkinson's disease trial. Copyright © 2012 John Wiley & Sons, Ltd.

An overview of modeling methods for thermal mixing and stratification in large enclosures for reactor safety analysis

Energy Technology Data Exchange (ETDEWEB)

Haihua Zhao; Per F. Peterson

2010-10-01

Thermal mixing and stratification phenomena play major roles in the safety of reactor systems with large enclosures, such as containment safety in current fleet of LWRs, long-term passive containment cooling in Gen III+ plants including AP-1000 and ESBWR, the cold and hot pool mixing in pool type sodium cooled fast reactor systems (SFR), and reactor cavity cooling system behavior in high temperature gas cooled reactors (HTGR), etc. Depending on the fidelity requirement and computational resources, 0-D steady state models (heat transfer correlations), 0-D lumped parameter based transient models, 1-D physical-based coarse grain models, and 3-D CFD models are available. Current major system analysis codes either have no models or only 0-D models for thermal stratification and mixing, which can only give highly approximate results for simple cases. While 3-D CFD methods can be used to analyze simple configurations, these methods require very fine grid resolution to resolve thin substructures such as jets and wall boundaries. Due to prohibitive computational expenses for long transients in very large volumes, 3-D CFD simulations remain impractical for system analyses. For mixing in stably stratified large enclosures, UC Berkeley developed 1-D models basing on Zuber’s hierarchical two-tiered scaling analysis (HTTSA) method where the ambient fluid volume is represented by 1-D transient partial differential equations and substructures such as free or wall jets are modeled with 1-D integral models. This allows very large reductions in computational effort compared to 3-D CFD modeling. This paper will present an overview on important thermal mixing and stratification phenomena in large enclosures for different reactors, major modeling methods and their advantages and limits, potential paths to improve simulation capability and reduce analysis uncertainty in this area for advanced reactor system analysis tools.

Mixed-effects height–diameter models for ten conifers in the inland ...

African Journals Online (AJOL)

To demonstrate the utility of mixed-effects height–diameter models when conducting forest inventories, mixedeffects height–diameter models are presented for several commercially and ecologically important conifers in the inland Northwest of the USA. After obtaining height–diameter measurements from a plot/stand of ...

Estimating the Numerical Diapycnal Mixing in the GO5.0 Ocean Model

Science.gov (United States)

Megann, A.; Nurser, G.

2014-12-01

Constant-depth (or "z-coordinate") ocean models such as MOM4 and NEMO have become the de facto workhorse in climate applications, and have attained a mature stage in their development and are well understood. A generic shortcoming of this model type, however, is a tendency for the advection scheme to produce unphysical numerical diapycnal mixing, which in some cases may exceed the explicitly parameterised mixing based on observed physical processes, and this is likely to have effects on the long-timescale evolution of the simulated climate system. Despite this, few quantitative estimations have been made of the magnitude of the effective diapycnal diffusivity due to numerical mixing in these models. GO5.0 is the latest ocean model configuration developed jointly by the UK Met Office and the National Oceanography Centre (Megann et al, 2014), and forms part of the GC1 and GC2 climate models. It uses version 3.4 of the NEMO model, on the ORCA025 ¼° global tripolar grid. We describe various approaches to quantifying the numerical diapycnal mixing in this model, and present results from analysis of the GO5.0 model based on the isopycnal watermass analysis of Lee et al (2002) that indicate that numerical mixing does indeed form a significant component of the watermass transformation in the ocean interior.

Mixed models theory and applications with R

CERN Document Server

Demidenko, Eugene

2013-01-01

Mixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book provides in-depth mathematical coverage of mixed models' statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image. The new edition includes significant updating, over 300 exercises, stimulating chapter projects and model simulations, inclusion of R subroutines, and a revised text format. The target audience continues to be g

Reliability analysis and prediction of mixed mode load using Markov Chain Model

International Nuclear Information System (INIS)

Nikabdullah, N.; Singh, S. S. K.; Alebrahim, R.; Azizi, M. A.; K, Elwaleed A.; Noorani, M. S. M.

2014-01-01

The aim of this paper is to present the reliability analysis and prediction of mixed mode loading by using a simple two state Markov Chain Model for an automotive crankshaft. The reliability analysis and prediction for any automotive component or structure is important for analyzing and measuring the failure to increase the design life, eliminate or reduce the likelihood of failures and safety risk. The mechanical failures of the crankshaft are due of high bending and torsion stress concentration from high cycle and low rotating bending and torsional stress. The Markov Chain was used to model the two states based on the probability of failure due to bending and torsion stress. In most investigations it revealed that bending stress is much serve than torsional stress, therefore the probability criteria for the bending state would be higher compared to the torsion state. A statistical comparison between the developed Markov Chain Model and field data was done to observe the percentage of error. The reliability analysis and prediction was derived and illustrated from the Markov Chain Model were shown in the Weibull probability and cumulative distribution function, hazard rate and reliability curve and the bathtub curve. It can be concluded that Markov Chain Model has the ability to generate near similar data with minimal percentage of error and for a practical application; the proposed model provides a good accuracy in determining the reliability for the crankshaft under mixed mode loading

Skew-t partially linear mixed-effects models for AIDS clinical studies.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Study on effects of mixing vane grids on coolant temperature distribution by subchannel analysis

Energy Technology Data Exchange (ETDEWEB)

Mao, H.; Yang, B.W.; Han, B. [Xi' an Jiaotong Univ., Shaanxi (China). Science and Technology Center for Advanced Nuclear Fuel Research

2016-07-15

Mixing vane grids (MVG) have great influence on coolant temperature field in the rod bundle. The MVG could enhance convective heat transfer between the fuel rod wall and the coolant, and promote inter-subchannel mixing at the same time. For the influence of the MVG on convective heat transfer enhancement, many experiments have been done and several correlations have been developed based on the experimental data. However, inter-subchannel mixing promotion caused by the MVG is not well estimated in subchannel analysis because the information of mixing vanes is totally missing in most subchannel codes. This paper analyzes the influence of mixing vanes on coolant temperature distribution using the improved MVG model in subchannel analysis. The coolant temperature distributions with the MVG are analyzed, and the results show that mixing vanes lead to a more uniform temperature distribution. The performances of split vane grids under different power conditions are evaluated. The results are compared with those of spacer grids without mixing vanes and some conclusions are obtained.

Study on effects of mixing vane grids on coolant temperature distribution by subchannel analysis

International Nuclear Information System (INIS)

Mao, H.; Yang, B.W.; Han, B.

2016-01-01

Mixing vane grids (MVG) have great influence on coolant temperature field in the rod bundle. The MVG could enhance convective heat transfer between the fuel rod wall and the coolant, and promote inter-subchannel mixing at the same time. For the influence of the MVG on convective heat transfer enhancement, many experiments have been done and several correlations have been developed based on the experimental data. However, inter-subchannel mixing promotion caused by the MVG is not well estimated in subchannel analysis because the information of mixing vanes is totally missing in most subchannel codes. This paper analyzes the influence of mixing vanes on coolant temperature distribution using the improved MVG model in subchannel analysis. The coolant temperature distributions with the MVG are analyzed, and the results show that mixing vanes lead to a more uniform temperature distribution. The performances of split vane grids under different power conditions are evaluated. The results are compared with those of spacer grids without mixing vanes and some conclusions are obtained.

CFD analysis for spacer grid mixing vane design

International Nuclear Information System (INIS)

Park, Sung-Kew; Kim, Kang-Hoon; Park, Eung-Jun; Jung, Yil-Sup; Suh, Jung-Min; Jeong, Ji-Hun

2008-01-01

A computational fluid dynamics (CFD) analysis for a rod bundle with the larger scale model (6x6 array model) has been performed to develop the base shape of mixing vane in accordance with the hydraulic and thermal performance. Explanatory parameters are span pressure drop and span average heat transfer coefficient. The concern related to hot spot is also considered as a subsidiary criterion. Of the several candidates, the final candidate was determined by using the CFD analysis code, STAR-CD. And then, the optimization for it was performed using the response surface method (RSM) that the proper tolerance was considered under the two acceptance criteria such as lower span pressure drop while maintaining the span average heat transfer coefficient with respect to the current shape. The optimized mixing vane shape was verified by the CFD analysis including the effects of allowable tolerance. (author)

Statistical Tests for Mixed Linear Models

CERN Document Server

Khuri, André I; Sinha, Bimal K

2011-01-01

An advanced discussion of linear models with mixed or random effects. In recent years a breakthrough has occurred in our ability to draw inferences from exact and optimum tests of variance component models, generating much research activity that relies on linear models with mixed and random effects. This volume covers the most important research of the past decade as well as the latest developments in hypothesis testing. It compiles all currently available results in the area of exact and optimum tests for variance component models and offers the only comprehensive treatment for these models a

Statistical models of global Langmuir mixing

Science.gov (United States)

Li, Qing; Fox-Kemper, Baylor; Breivik, Øyvind; Webb, Adrean

2017-05-01

The effects of Langmuir mixing on the surface ocean mixing may be parameterized by applying an enhancement factor which depends on wave, wind, and ocean state to the turbulent velocity scale in the K-Profile Parameterization. Diagnosing the appropriate enhancement factor online in global climate simulations is readily achieved by coupling with a prognostic wave model, but with significant computational and code development expenses. In this paper, two alternatives that do not require a prognostic wave model, (i) a monthly mean enhancement factor climatology, and (ii) an approximation to the enhancement factor based on the empirical wave spectra, are explored and tested in a global climate model. Both appear to reproduce the Langmuir mixing effects as estimated using a prognostic wave model, with nearly identical and substantial improvements in the simulated mixed layer depth and intermediate water ventilation over control simulations, but significantly less computational cost. Simpler approaches, such as ignoring Langmuir mixing altogether or setting a globally constant Langmuir number, are found to be deficient. Thus, the consequences of Stokes depth and misaligned wind and waves are important.

A multilevel nonlinear mixed-effects approach to model growth in pigs

DEFF Research Database (Denmark)

Strathe, Anders Bjerring; Danfær, Allan Christian; Sørensen, H.

2010-01-01

Growth functions have been used to predict market weight of pigs and maximize return over feed costs. This study was undertaken to compare 4 growth functions and methods of analyzing data, particularly one that considers nonlinear repeated measures. Data were collected from an experiment with 40...... pigs maintained from birth to maturity and their BW measured weekly or every 2 wk up to 1,007 d. Gompertz, logistic, Bridges, and Lopez functions were fitted to the data and compared using information criteria. For each function, a multilevel nonlinear mixed effects model was employed because....... Furthermore, studies should consider adding continuous autoregressive process when analyzing nonlinear mixed models with repeated measures....

A method for fitting regression splines with varying polynomial order in the linear mixed model.

Science.gov (United States)

Edwards, Lloyd J; Stewart, Paul W; MacDougall, James E; Helms, Ronald W

2006-02-15

The linear mixed model has become a widely used tool for longitudinal analysis of continuous variables. The use of regression splines in these models offers the analyst additional flexibility in the formulation of descriptive analyses, exploratory analyses and hypothesis-driven confirmatory analyses. We propose a method for fitting piecewise polynomial regression splines with varying polynomial order in the fixed effects and/or random effects of the linear mixed model. The polynomial segments are explicitly constrained by side conditions for continuity and some smoothness at the points where they join. By using a reparameterization of this explicitly constrained linear mixed model, an implicitly constrained linear mixed model is constructed that simplifies implementation of fixed-knot regression splines. The proposed approach is relatively simple, handles splines in one variable or multiple variables, and can be easily programmed using existing commercial software such as SAS or S-plus. The method is illustrated using two examples: an analysis of longitudinal viral load data from a study of subjects with acute HIV-1 infection and an analysis of 24-hour ambulatory blood pressure profiles.

Quantifying the effect of mixing on the mean age of air in CCMVal-2 and CCMI-1 models

Science.gov (United States)

Dietmüller, Simone; Eichinger, Roland; Garny, Hella; Birner, Thomas; Boenisch, Harald; Pitari, Giovanni; Mancini, Eva; Visioni, Daniele; Stenke, Andrea; Revell, Laura; Rozanov, Eugene; Plummer, David A.; Scinocca, John; Jöckel, Patrick; Oman, Luke; Deushi, Makoto; Kiyotaka, Shibata; Kinnison, Douglas E.; Garcia, Rolando; Morgenstern, Olaf; Zeng, Guang; Stone, Kane Adam; Schofield, Robyn

2018-05-01

The stratospheric age of air (AoA) is a useful measure of the overall capabilities of a general circulation model (GCM) to simulate stratospheric transport. Previous studies have reported a large spread in the simulation of AoA by GCMs and coupled chemistry-climate models (CCMs). Compared to observational estimates, simulated AoA is mostly too low. Here we attempt to untangle the processes that lead to the AoA differences between the models and between models and observations. AoA is influenced by both mean transport by the residual circulation and two-way mixing; we quantify the effects of these processes using data from the CCM inter-comparison projects CCMVal-2 (Chemistry-Climate Model Validation Activity 2) and CCMI-1 (Chemistry-Climate Model Initiative, phase 1). Transport along the residual circulation is measured by the residual circulation transit time (RCTT). We interpret the difference between AoA and RCTT as additional aging by mixing. Aging by mixing thus includes mixing on both the resolved and subgrid scale. We find that the spread in AoA between the models is primarily caused by differences in the effects of mixing and only to some extent by differences in residual circulation strength. These effects are quantified by the mixing efficiency, a measure of the relative increase in AoA by mixing. The mixing efficiency varies strongly between the models from 0.24 to 1.02. We show that the mixing efficiency is not only controlled by horizontal mixing, but by vertical mixing and vertical diffusion as well. Possible causes for the differences in the models' mixing efficiencies are discussed. Differences in subgrid-scale mixing (including differences in advection schemes and model resolutions) likely contribute to the differences in mixing efficiency. However, differences in the relative contribution of resolved versus parameterized wave forcing do not appear to be related to differences in mixing efficiency or AoA.

Practical likelihood analysis for spatial generalized linear mixed models

DEFF Research Database (Denmark)

Bonat, W. H.; Ribeiro, Paulo Justiniano

2016-01-01

We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are......, respectively, examples of binomial and count datasets modeled by spatial generalized linear mixed models. Our results show that the Laplace approximation provides similar estimates to Markov Chain Monte Carlo likelihood, Monte Carlo expectation maximization, and modified Laplace approximation. Some advantages...... of Laplace approximation include the computation of the maximized log-likelihood value, which can be used for model selection and tests, and the possibility to obtain realistic confidence intervals for model parameters based on profile likelihoods. The Laplace approximation also avoids the tuning...

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

Science.gov (United States)

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).

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

Science.gov (United States)

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…

A Nonlinear Mixed Effects Model for the Prediction of Natural Gas Consumption by Individual Customers

Czech Academy of Sciences Publication Activity Database

Brabec, Marek; Konár, Ondřej; Pelikán, Emil; Malý, Marek

2008-01-01

Roč. 24, č. 4 (2008), s. 659-678 ISSN 0169-2070 R&D Projects: GA AV ČR 1ET400300513 Institutional research plan: CEZ:AV0Z10300504 Keywords : individual gas consumption * nonlinear mixed effects model * ARIMAX * ARX * generalized linear mixed model * conditional modeling Subject RIV: JE - Non-nuclear Energetics, Energy Consumption ; Use Impact factor: 1.685, year: 2008

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

Science.gov (United States)

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.

Reliability assessment of competing risks with generalized mixed shock models

International Nuclear Information System (INIS)

Rafiee, Koosha; Feng, Qianmei; Coit, David W.

2017-01-01

This paper investigates reliability modeling for systems subject to dependent competing risks considering the impact from a new generalized mixed shock model. Two dependent competing risks are soft failure due to a degradation process, and hard failure due to random shocks. The shock process contains fatal shocks that can cause hard failure instantaneously, and nonfatal shocks that impact the system in three different ways: 1) damaging the unit by immediately increasing the degradation level, 2) speeding up the deterioration by accelerating the degradation rate, and 3) weakening the unit strength by reducing the hard failure threshold. While the first impact from nonfatal shocks comes from each individual shock, the other two impacts are realized when the condition for a new generalized mixed shock model is satisfied. Unlike most existing mixed shock models that consider a combination of two shock patterns, our new generalized mixed shock model includes three classic shock patterns. According to the proposed generalized mixed shock model, the degradation rate and the hard failure threshold can simultaneously shift multiple times, whenever the condition for one of these three shock patterns is satisfied. An example using micro-electro-mechanical systems devices illustrates the effectiveness of the proposed approach with sensitivity analysis. - Highlights: • A rich reliability model for systems subject to dependent failures is proposed. • The degradation rate and the hard failure threshold can shift simultaneously. • The shift is triggered by a new generalized mixed shock model. • The shift can occur multiple times under the generalized mixed shock model.

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

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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.

Species Distribution Modeling: Comparison of Fixed and Mixed Effects Models Using INLA

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Lara Dutra Silva

2017-12-01

Full Text Available Invasive alien species are among the most important, least controlled, and least reversible of human impacts on the world’s ecosystems, with negative consequences affecting biodiversity and socioeconomic systems. Species distribution models have become a fundamental tool in assessing the potential spread of invasive species in face of their native counterparts. In this study we compared two different modeling techniques: (i fixed effects models accounting for the effect of ecogeographical variables (EGVs; and (ii mixed effects models including also a Gaussian random field (GRF to model spatial correlation (Matérn covariance function. To estimate the potential distribution of Pittosporum undulatum and Morella faya (respectively, invasive and native trees, we used geo-referenced data of their distribution in Pico and São Miguel islands (Azores and topographic, climatic and land use EGVs. Fixed effects models run with maximum likelihood or the INLA (Integrated Nested Laplace Approximation approach provided very similar results, even when reducing the size of the presences data set. The addition of the GRF increased model adjustment (lower Deviance Information Criterion, particularly for the less abundant tree, M. faya. However, the random field parameters were clearly affected by sample size and species distribution pattern. A high degree of spatial autocorrelation was found and should be taken into account when modeling species distribution.

Multi-objective Analysis for a Sequencing Planning of Mixed-model Assembly Line

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Shimizu, Yoshiaki; Waki, Toshiya; Yoo, Jae Kyu

Diversified customer demands are raising importance of just-in-time and agile manufacturing much more than before. Accordingly, introduction of mixed-model assembly lines becomes popular to realize the small-lot-multi-kinds production. Since it produces various kinds on the same assembly line, a rational management is of special importance. With this point of view, this study focuses on a sequencing problem of mixed-model assembly line including a paint line as its preceding process. By taking into account the paint line together, reducing work-in-process (WIP) inventory between these heterogeneous lines becomes a major concern of the sequencing problem besides improving production efficiency. Finally, we have formulated the sequencing problem as a bi-objective optimization problem to prevent various line stoppages, and to reduce the volume of WIP inventory simultaneously. Then we have proposed a practical method for the multi-objective analysis. For this purpose, we applied the weighting method to derive the Pareto front. Actually, the resulting problem is solved by a meta-heuristic method like SA (Simulated Annealing). Through numerical experiments, we verified the validity of the proposed approach, and discussed the significance of trade-off analysis between the conflicting objectives.

Unified Analysis of Multi-Chamber Contact Tanks and Mixing Efficiency Evaluation Based on Vorticity Field. Part II: Transport Analysis

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Ender Demirel

2016-11-01

Full Text Available Mixing characteristics of multi-chambered contact tank are analyzed employing the validated three-dimensional numerical model developed in the companion paper. Based on the flow characterization, novel volumetric mixing efficiency definitions are proposed for the assessment of the hydrodynamic and chemical transport properties of the contact tank and its chambers. Residence time distribution functions are analyzed not only at the outlet of each chamber but also inside the chambers using the efficiency definitions for both Reynolds averaged Navier–Stokes (RANS and large eddy simulation (LES results. A novel tracer mixing index is defined to characterize short circuiting and mixing effects of the contact system. Comparisons of the results of these indexes for RANS and LES solutions indicate that mixing characteristics are stronger in LES due to the unsteady turbulent eddy mixing even though short circuiting effects are also more prominent in LES results. This result indicates that the mixing analysis based on the LES results simulates the mixing characteristics instantaneously, which is more realistic than that in RANS. Since LES analysis can capture turbulent eddy mixing better than RANS analysis, the interaction of recirculation and jet zones are captured more effectively in LES, which tends to predict higher turbulent mixing in the contact system. The analysis also shows that the mixing efficiency of each chamber of the contact tank is different, thus it is necessary to consider distinct chemical release and volumetric designs for each chamber in order to maximize the mixing efficiency of the overall process in a contact tank system.

Translational mixed-effects PKPD modelling of recombinant human growth hormone - from hypophysectomized rat to patients

DEFF Research Database (Denmark)

Thorsted, A; Thygesen, P; Agersø, H

2016-01-01

BACKGROUND AND PURPOSE: We aimed to develop a mechanistic mixed-effects pharmacokinetic (PK)-pharmacodynamic (PD) (PKPD) model for recombinant human growth hormone (rhGH) in hypophysectomized rats and to predict the human PKPD relationship. EXPERIMENTAL APPROACH: A non-linear mixed-effects model...... was developed from experimental PKPD studies of rhGH and effects of long-term treatment as measured by insulin-like growth factor 1 (IGF-1) and bodyweight gain in rats. Modelled parameter values were scaled to human values using the allometric approach with fixed exponents for PKs and unscaled for PDs...... s.c. administration was over predicted. After correction of the human s.c. absorption model, the induction model for IGF-1 well described the human PKPD data. CONCLUSIONS: A translational mechanistic PKPD model for rhGH was successfully developed from experimental rat data. The model links...

BWR MARK I pressure suppression pool mixing and stratification analysis using GOTHIC lumped parameter modeling methodology

International Nuclear Information System (INIS)

Ozdemir, Ozkan Emre; George, Thomas L.

2015-01-01

As a part of the GOTHIC (GOTHIC incorporates technology developed for the electric power industry under the sponsorship of EPRI.) Fukushima Technical Evaluation project (EPRI, 2014a, b, 2015), GOTHIC (EPRI, 2014c) has been benchmarked against test data for pool stratification (EPRI, 2014a, b, Ozdemir and George, 2013). These tests confirmed GOTHIC’s ability to simulate pool mixing and stratification under a variety of anticipated suppression pool operating conditions. The multidimensional modeling requires long simulation times for events that may occur over a period of hours or days. For these scenarios a lumped model of the pressure suppression chamber is desirable to maintain reasonable simulation times. However, a lumped model for the pool is not able to predict the effects of pool stratification that can influence the overall containment response. The main objective of this work is on the development of a correlation that can be used to estimate pool mixing and stratification effects in a lumped modeling approach. A simplified lumped GOTHIC model that includes a two zone model for the suppression pool with controlled circulation between the upper and lower zones was constructed. A pump and associated flow connections are included to provide mixing between the upper and lower pool volumes. Using numerically generated data from a multidimensional GOTHIC model for the suppression pool, a correlation was developed for the mixing rate between the upper and lower pool volumes in a two-zone, lumped model. The mixing rate depends on the pool subcooling, the steam injection rate and the injection depth

The use of copulas to practical estimation of multivariate stochastic differential equation mixed effects models

International Nuclear Information System (INIS)

Rupšys, P.

2015-01-01

A system of stochastic differential equations (SDE) with mixed-effects parameters and multivariate normal copula density function were used to develop tree height model for Scots pine trees in Lithuania. A two-step maximum likelihood parameter estimation method is used and computational guidelines are given. After fitting the conditional probability density functions to outside bark diameter at breast height, and total tree height, a bivariate normal copula distribution model was constructed. Predictions from the mixed-effects parameters SDE tree height model calculated during this research were compared to the regression tree height equations. The results are implemented in the symbolic computational language MAPLE

The use of copulas to practical estimation of multivariate stochastic differential equation mixed effects models

Energy Technology Data Exchange (ETDEWEB)

Rupšys, P. [Aleksandras Stulginskis University, Studenų g. 11, Akademija, Kaunas district, LT – 53361 Lithuania (Lithuania)

2015-10-28

A system of stochastic differential equations (SDE) with mixed-effects parameters and multivariate normal copula density function were used to develop tree height model for Scots pine trees in Lithuania. A two-step maximum likelihood parameter estimation method is used and computational guidelines are given. After fitting the conditional probability density functions to outside bark diameter at breast height, and total tree height, a bivariate normal copula distribution model was constructed. Predictions from the mixed-effects parameters SDE tree height model calculated during this research were compared to the regression tree height equations. The results are implemented in the symbolic computational language MAPLE.

Partially linear mixed-effects joint models for skewed and missing longitudinal competing risks outcomes.

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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.

Compressibility effects on turbulent mixing

Science.gov (United States)

Panickacheril John, John; Donzis, Diego

2016-11-01

We investigate the effect of compressibility on passive scalar mixing in isotropic turbulence with a focus on the fundamental mechanisms that are responsible for such effects using a large Direct Numerical Simulation (DNS) database. The database includes simulations with Taylor Reynolds number (Rλ) up to 100, turbulent Mach number (Mt) between 0.1 and 0.6 and Schmidt number (Sc) from 0.5 to 1.0. We present several measures of mixing efficiency on different canonical flows to robustly identify compressibility effects. We found that, like shear layers, mixing is reduced as Mach number increases. However, data also reveal a non-monotonic trend with Mt. To assess directly the effect of dilatational motions we also present results with both dilatational and soleniodal forcing. Analysis suggests that a small fraction of dilatational forcing decreases mixing time at higher Mt. Scalar spectra collapse when normalized by Batchelor variables which suggests that a compressive mechanism similar to Batchelor mixing in incompressible flows might be responsible for better mixing at high Mt and with dilatational forcing compared to pure solenoidal mixing. We also present results on scalar budgets, in particular on production and dissipation. Support from NSF is gratefully acknowledged.

Probability of atrial fibrillation after ablation: Using a parametric nonlinear temporal decomposition mixed effects model.

Science.gov (United States)

Rajeswaran, Jeevanantham; Blackstone, Eugene H; Ehrlinger, John; Li, Liang; Ishwaran, Hemant; Parides, Michael K

2018-01-01

Atrial fibrillation is an arrhythmic disorder where the electrical signals of the heart become irregular. The probability of atrial fibrillation (binary response) is often time varying in a structured fashion, as is the influence of associated risk factors. A generalized nonlinear mixed effects model is presented to estimate the time-related probability of atrial fibrillation using a temporal decomposition approach to reveal the pattern of the probability of atrial fibrillation and their determinants. This methodology generalizes to patient-specific analysis of longitudinal binary data with possibly time-varying effects of covariates and with different patient-specific random effects influencing different temporal phases. The motivation and application of this model is illustrated using longitudinally measured atrial fibrillation data obtained through weekly trans-telephonic monitoring from an NIH sponsored clinical trial being conducted by the Cardiothoracic Surgery Clinical Trials Network.

Comparison between the SIMPLE and ENERGY mixing models

International Nuclear Information System (INIS)

Burns, K.J.; Todreas, N.E.

1980-07-01

The SIMPLE and ENERGY mixing models were compared in order to investigate the limitations of SIMPLE's analytically formulated mixing parameter, relative to the experimentally calibrated ENERGY mixing parameters. For interior subchannels, it was shown that when the SIMPLE and ENERGY parameters are reduced to a common form, there is good agreement between the two models for a typical fuel geometry. However, large discrepancies exist for typical blanket (lower P/D) geometries. Furthermore, the discrepancies between the mixing parameters result in significant differences in terms of the temperature profiles generated by the ENERGY code utilizing these mixing parameters as input. For edge subchannels, the assumptions made in the development of the SIMPLE model were extended to the rectangular edge subchannel geometry used in ENERGY. The resulting effective eddy diffusivities (used by the ENERGY code) associated with the SIMPLE model are again closest to those of the ENERGY model for the fuel assembly geometry. Finally, the SIMPLE model's neglect of a net swirl effect in the edge region is most limiting for assemblies exhibiting relatively large radial power skews

ADVANCED MIXING MODELS

International Nuclear Information System (INIS)

Lee, S; Richard Dimenna, R; David Tamburello, D

2008-01-01

,000 to 300,000) with a relative standard deviation of ± 11.83%. An improved correlation including the effect of circulation time was proposed by Grenville and Tilton [11] via a better fit of mixing time data for turbulent jet mixing under a wider range of jet Reynolds numbers (50,000 to 300,000). The circulation time was defined as the liquid volume divided by the entrained flow rate. They assumed that the mixing rate at the end of the jet length controls the mixing time for the entire tank by estimating the kinetic energy dissipation rate as discussed earlier. They predicted that for a given volume, an optimum geometry exists for a mixing vessel, allowing a desired mixing time to be achieved for a minimum power input. The current work will compare their correlation of the jet mixing time with CFD modeling results for their experimental tanks in an attempt to achieve a fundamental understanding of the turbulent jet mixing and to establish mixing indicators

ADVANCED MIXING MODELS

Energy Technology Data Exchange (ETDEWEB)

Lee, S; Richard Dimenna, R; David Tamburello, D

2008-11-13

(50,000 to 300,000) with a relative standard deviation of {+-} 11.83%. An improved correlation including the effect of circulation time was proposed by Grenville and Tilton [11] via a better fit of mixing time data for turbulent jet mixing under a wider range of jet Reynolds numbers (50,000 to 300,000). The circulation time was defined as the liquid volume divided by the entrained flow rate. They assumed that the mixing rate at the end of the jet length controls the mixing time for the entire tank by estimating the kinetic energy dissipation rate as discussed earlier. They predicted that for a given volume, an optimum geometry exists for a mixing vessel, allowing a desired mixing time to be achieved for a minimum power input. The current work will compare their correlation of the jet mixing time with CFD modeling results for their experimental tanks in an attempt to achieve a fundamental understanding of the turbulent jet mixing and to establish mixing indicators.

Multilevel nonlinear mixed-effects models for the modeling of earlywood and latewood microfibril angle

Science.gov (United States)

Lewis Jordon; Richard F. Daniels; Alexander Clark; Rechun He

2005-01-01

Earlywood and latewood microfibril angle (MFA) was determined at I-millimeter intervals from disks at 1.4 meters, then at 3-meter intervals to a height of 13.7 meters, from 18 loblolly pine (Pinus taeda L.) trees grown in southeastern Texas. A modified three-parameter logistic function with mixed effects is used for modeling earlywood and latewood...

Regression analysis of mixed recurrent-event and panel-count data with additive rate models.

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Zhu, Liang; Zhao, Hui; Sun, Jianguo; Leisenring, Wendy; Robison, Leslie L

2015-03-01

Event-history studies of recurrent events are often conducted in fields such as demography, epidemiology, medicine, and social sciences (Cook and Lawless, 2007, The Statistical Analysis of Recurrent Events. New York: Springer-Verlag; Zhao et al., 2011, Test 20, 1-42). For such analysis, two types of data have been extensively investigated: recurrent-event data and panel-count data. However, in practice, one may face a third type of data, mixed recurrent-event and panel-count data or mixed event-history data. Such data occur if some study subjects are monitored or observed continuously and thus provide recurrent-event data, while the others are observed only at discrete times and hence give only panel-count data. A more general situation is that each subject is observed continuously over certain time periods but only at discrete times over other time periods. There exists little literature on the analysis of such mixed data except that published by Zhu et al. (2013, Statistics in Medicine 32, 1954-1963). In this article, we consider the regression analysis of mixed data using the additive rate model and develop some estimating equation-based approaches to estimate the regression parameters of interest. Both finite sample and asymptotic properties of the resulting estimators are established, and the numerical studies suggest that the proposed methodology works well for practical situations. The approach is applied to a Childhood Cancer Survivor Study that motivated this study. © 2014, The International Biometric Society.

Model Selection with the Linear Mixed Model for Longitudinal Data

Science.gov (United States)

Ryoo, Ji Hoon

2011-01-01

Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…

Item Response Theory Models for Wording Effects in Mixed-Format Scales

Science.gov (United States)

Wang, Wen-Chung; Chen, Hui-Fang; Jin, Kuan-Yu

2015-01-01

Many scales contain both positively and negatively worded items. Reverse recoding of negatively worded items might not be enough for them to function as positively worded items do. In this study, we commented on the drawbacks of existing approaches to wording effect in mixed-format scales and used bi-factor item response theory (IRT) models to…

Multivariate generalized linear mixed models using R

CERN Document Server

Berridge, Damon Mark

2011-01-01

Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data from panel and related studies via the Sabre software package in R. A Unified Framework for a Broad Class of Models The authors first discuss members of the family of generalized linear models, gradually adding complexity to the modeling framework by incorporating random effects. After reviewing the generalized linear model notation, they illustrate a range of random effects models, including three-level, multivariate, endpoint, event history, and state dependence models. They estimate the multivariate generalized linear mixed models (MGLMMs) using either standard or adaptive Gaussian quadrature. The authors also compare two-level fixed and random effects linear models. The appendices contain additional information on quadrature, model...

Flapping model of scalar mixing in turbulence

International Nuclear Information System (INIS)

Kerstein, A.R.

1991-01-01

Motivated by the fluctuating plume model of turbulent mixing downstream of a point source, a flapping model is formulated for application to other configurations. For the scalar mixing layer, simple expressions for single-point scalar fluctuation statistics are obtained that agree with measurements. For a spatially homogeneous scalar mixing field, the family of probability density functions previously derived using mapping closure is reproduced. It is inferred that single-point scalar statistics may depend primarily on large-scale flapping motions in many cases of interest, and thus that multipoint statistics may be the principal indicators of finer-scale mixing effects

Effectiveness and cost effectiveness of expanding harm reduction and antiretroviral therapy in a mixed HIV epidemic: a modeling analysis for Ukraine.

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Sabina S Alistar

2011-03-01

Full Text Available Injection drug use (IDU and heterosexual virus transmission both contribute to the growing mixed HIV epidemics in Eastern Europe and Central Asia. In Ukraine-chosen in this study as a representative country-IDU-related risk behaviors cause half of new infections, but few injection drug users (IDUs receive methadone substitution therapy. Only 10% of eligible individuals receive antiretroviral therapy (ART. The appropriate resource allocation between these programs has not been studied. We estimated the effectiveness and cost-effectiveness of strategies for expanding methadone substitution therapy programs and ART in mixed HIV epidemics, using Ukraine as a case study.We developed a dynamic compartmental model of the HIV epidemic in a population of non-IDUs, IDUs using opiates, and IDUs on methadone substitution therapy, stratified by HIV status, and populated it with data from the Ukraine. We considered interventions expanding methadone substitution therapy, increasing access to ART, or both. We measured health care costs, quality-adjusted life years (QALYs, HIV prevalence, infections averted, and incremental cost-effectiveness. Without incremental interventions, HIV prevalence reached 67.2% (IDUs and 0.88% (non-IDUs after 20 years. Offering methadone substitution therapy to 25% of IDUs reduced prevalence most effectively (to 53.1% IDUs, 0.80% non-IDUs, and was most cost-effective, averting 4,700 infections and adding 76,000 QALYs compared with no intervention at US$530/QALY gained. Expanding both ART (80% coverage of those eligible for ART according to WHO criteria and methadone substitution therapy (25% coverage was the next most cost-effective strategy, adding 105,000 QALYs at US$1,120/QALY gained versus the methadone substitution therapy-only strategy and averting 8,300 infections versus no intervention. Expanding only ART (80% coverage added 38,000 QALYs at US$2,240/QALY gained versus the methadone substitution therapy-only strategy, and

Modelling the multilevel structure and mixed effects of the factors influencing the energy consumption of electric vehicles

International Nuclear Information System (INIS)

Liu, Kai; Wang, Jiangbo; Yamamoto, Toshiyuki; Morikawa, Takayuki

2016-01-01

Highlights: • The impacts of driving heterogeneity on EVs’ energy efficiency are examined. • Several multilevel mixed-effects regression models are proposed and compared. • The most reasonable nested structure is extracted from the long term GPS data. • Proposed model improves the energy estimation accuracy by 7.5%. - Abstract: To improve the accuracy of estimation of the energy consumption of electric vehicles (EVs) and to enable the alleviation of range anxiety through the introduction of EV charging stations at suitable locations for the near future, multilevel mixed-effects linear regression models were used in this study to estimate the actual energy efficiency of EVs. The impacts of the heterogeneity in driving behaviour among various road environments and traffic conditions on EV energy efficiency were extracted from long-term daily trip-based energy consumption data, which were collected over 12 months from 68 in-use EVs in Aichi Prefecture in Japan. Considering the variations in energy efficiency associated with different types of EV ownership, different external environments, and different driving habits, a two-level random intercept model, three two-level mixed-effects models, and two three-level mixed-effects models were developed and compared. The most reasonable nesting structure was determined by comparing the models, which were designed with different nesting structures and different random variance component specifications, thereby revealing the potential correlations and non-constant variability of the energy consumption per kilometre (ECPK) and improving the estimation accuracy by 7.5%.

Node-Splitting Generalized Linear Mixed Models for Evaluation of Inconsistency in Network Meta-Analysis.

Science.gov (United States)

Yu-Kang, Tu

2016-12-01

Network meta-analysis for multiple treatment comparisons has been a major development in evidence synthesis methodology. The validity of a network meta-analysis, however, can be threatened by inconsistency in evidence within the network. One particular issue of inconsistency is how to directly evaluate the inconsistency between direct and indirect evidence with regard to the effects difference between two treatments. A Bayesian node-splitting model was first proposed and a similar frequentist side-splitting model has been put forward recently. Yet, assigning the inconsistency parameter to one or the other of the two treatments or splitting the parameter symmetrically between the two treatments can yield different results when multi-arm trials are involved in the evaluation. We aimed to show that a side-splitting model can be viewed as a special case of design-by-treatment interaction model, and different parameterizations correspond to different design-by-treatment interactions. We demonstrated how to evaluate the side-splitting model using the arm-based generalized linear mixed model, and an example data set was used to compare results from the arm-based models with those from the contrast-based models. The three parameterizations of side-splitting make slightly different assumptions: the symmetrical method assumes that both treatments in a treatment contrast contribute to inconsistency between direct and indirect evidence, whereas the other two parameterizations assume that only one of the two treatments contributes to this inconsistency. With this understanding in mind, meta-analysts can then make a choice about how to implement the side-splitting method for their analysis. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Assessing robustness of designs for random effects parameters for nonlinear mixed-effects models.

Science.gov (United States)

Duffull, Stephen B; Hooker, Andrew C

2017-12-01

Optimal designs for nonlinear models are dependent on the choice of parameter values. Various methods have been proposed to provide designs that are robust to uncertainty in the prior choice of parameter values. These methods are generally based on estimating the expectation of the determinant (or a transformation of the determinant) of the information matrix over the prior distribution of the parameter values. For high dimensional models this can be computationally challenging. For nonlinear mixed-effects models the question arises as to the importance of accounting for uncertainty in the prior value of the variances of the random effects parameters. In this work we explore the influence of the variance of the random effects parameters on the optimal design. We find that the method for approximating the expectation and variance of the likelihood is of potential importance for considering the influence of random effects. The most common approximation to the likelihood, based on a first-order Taylor series approximation, yields designs that are relatively insensitive to the prior value of the variance of the random effects parameters and under these conditions it appears to be sufficient to consider uncertainty on the fixed-effects parameters only.

Linear mixed models a practical guide using statistical software

CERN Document Server

West, Brady T; Galecki, Andrzej T

2014-01-01

Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues to lead readers step by step through the process of fitting LMMs. This second edition covers additional topics on the application of LMMs that are valuable for data analysts in all fields. It also updates the case studies using the latest versions of the software procedures and provides up-to-date information on the options and features of the software procedures available for fitting LMMs in SAS, SPSS, Stata, R/S-plus, and HLM.New to the Second Edition A new chapter on models with crossed random effects that uses a case study to illustrate software procedures capable of fitting these models Power analysis methods for longitudinal and clustered study designs, including software options for power analyses and suggest...

Sensitivity of fluvial sediment source apportionment to mixing model assumptions: A Bayesian model comparison.

Science.gov (United States)

Cooper, Richard J; Krueger, Tobias; Hiscock, Kevin M; Rawlins, Barry G

2014-11-01

Mixing models have become increasingly common tools for apportioning fluvial sediment load to various sediment sources across catchments using a wide variety of Bayesian and frequentist modeling approaches. In this study, we demonstrate how different model setups can impact upon resulting source apportionment estimates in a Bayesian framework via a one-factor-at-a-time (OFAT) sensitivity analysis. We formulate 13 versions of a mixing model, each with different error assumptions and model structural choices, and apply them to sediment geochemistry data from the River Blackwater, Norfolk, UK, to apportion suspended particulate matter (SPM) contributions from three sources (arable topsoils, road verges, and subsurface material) under base flow conditions between August 2012 and August 2013. Whilst all 13 models estimate subsurface sources to be the largest contributor of SPM (median ∼76%), comparison of apportionment estimates reveal varying degrees of sensitivity to changing priors, inclusion of covariance terms, incorporation of time-variant distributions, and methods of proportion characterization. We also demonstrate differences in apportionment results between a full and an empirical Bayesian setup, and between a Bayesian and a frequentist optimization approach. This OFAT sensitivity analysis reveals that mixing model structural choices and error assumptions can significantly impact upon sediment source apportionment results, with estimated median contributions in this study varying by up to 21% between model versions. Users of mixing models are therefore strongly advised to carefully consider and justify their choice of model structure prior to conducting sediment source apportionment investigations. An OFAT sensitivity analysis of sediment fingerprinting mixing models is conductedBayesian models display high sensitivity to error assumptions and structural choicesSource apportionment results differ between Bayesian and frequentist approaches.

Mixed models in cerebral ischemia study

Directory of Open Access Journals (Sweden)

Matheus Henrique Dal Molin Ribeiro

2016-06-01

Full Text Available The data modeling from longitudinal studies stands out in the current scientific scenario, especially in the areas of health and biological sciences, which induces a correlation between measurements for the same observed unit. Thus, the modeling of the intra-individual dependency is required through the choice of a covariance structure that is able to receive and accommodate the sample variability. However, the lack of methodology for correlated data analysis may result in an increased occurrence of type I or type II errors and underestimate/overestimate the standard errors of the model estimates. In the present study, a Gaussian mixed model was adopted for the variable response latency of an experiment investigating the memory deficits in animals subjected to cerebral ischemia when treated with fish oil (FO. The model parameters estimation was based on maximum likelihood methods. Based on the restricted likelihood ratio test and information criteria, the autoregressive covariance matrix was adopted for errors. The diagnostic analyses for the model were satisfactory, since basic assumptions and results obtained corroborate with biological evidence; that is, the effectiveness of the FO treatment to alleviate the cognitive effects caused by cerebral ischemia was found.

Mixed Effects Modeling Using Stochastic Differential Equations: Illustrated by Pharmacokinetic Data of Nicotinic Acid in Obese Zucker Rats.

Science.gov (United States)

Leander, Jacob; Almquist, Joachim; Ahlström, Christine; Gabrielsson, Johan; Jirstrand, Mats

2015-05-01

Inclusion of stochastic differential equations in mixed effects models provides means to quantify and distinguish three sources of variability in data. In addition to the two commonly encountered sources, measurement error and interindividual variability, we also consider uncertainty in the dynamical model itself. To this end, we extend the ordinary differential equation setting used in nonlinear mixed effects models to include stochastic differential equations. The approximate population likelihood is derived using the first-order conditional estimation with interaction method and extended Kalman filtering. To illustrate the application of the stochastic differential mixed effects model, two pharmacokinetic models are considered. First, we use a stochastic one-compartmental model with first-order input and nonlinear elimination to generate synthetic data in a simulated study. We show that by using the proposed method, the three sources of variability can be successfully separated. If the stochastic part is neglected, the parameter estimates become biased, and the measurement error variance is significantly overestimated. Second, we consider an extension to a stochastic pharmacokinetic model in a preclinical study of nicotinic acid kinetics in obese Zucker rats. The parameter estimates are compared between a deterministic and a stochastic NiAc disposition model, respectively. Discrepancies between model predictions and observations, previously described as measurement noise only, are now separated into a comparatively lower level of measurement noise and a significant uncertainty in model dynamics. These examples demonstrate that stochastic differential mixed effects models are useful tools for identifying incomplete or inaccurate model dynamics and for reducing potential bias in parameter estimates due to such model deficiencies.

Process simulation and uncertainty analysis of plasma arc mixed waste treatment

International Nuclear Information System (INIS)

Ferrada, J.J.; Welch, T.D.

1994-01-01

Innovative mixed waste treatment subsystems have been analyzed for performance, risk, and life-cycle cost as part of the U.S. Department of Energy's (DOE)'s Mixed Waste Integrated Program (MWIP) treatment alternatives development and evaluation process. This paper concerns the analysis of mixed waste treatment system performance. Performance systems analysis includes approximate material and energy balances and assessments of operability, effectiveness, and reliability. Preliminary material and energy balances of innovative processes have been analyzed using FLOW, an object-oriented, process simulator for waste management systems under development at Oak Ridge National Laboratory. The preliminary models developed for FLOW provide rough order-of-magnitude calculations useful for sensitivity analysis. The insight gained from early modeling of these technologies approximately will ease the transition to more sophisticated simulators as adequate performance and property data become available. Such models are being developed in ASPEN by DOE's Mixed Waste Treatment Project (MWTP) for baseline and alternative flow sheets based on commercial technologies. One alternative to the baseline developed by the MWIP support groups in plasma arc treatment. This process offers a noticeable reduction in the number of process operations as compared to the baseline process because a plasma arc melter is capable of accepting a wide variety of waste streams as direct inputs (without sorting or preprocessing). This innovative process for treating mixed waste replaces several units from the baseline process and, thus, promises an economic advantage. The performance in the plasma arc furnace will directly affect the quality of the waste form and the requirements of the off-gas treatment units. The ultimate objective of MWIP is to reduce the amount of final waste produced, the cost, and the environmental impact

Computational model for turbulent flow around a grid spacer with mixing vane

International Nuclear Information System (INIS)

Tsutomu Ikeno; Takeo Kajishima

2005-01-01

Turbulent mixing coefficient and pressure drop are important factors in subchannel analysis to predict onset of DNB. However, universal correlations are difficult since these factors are significantly affected by the geometry of subchannel and a grid spacer with mixing vane. Therefore, we propose a computational model to estimate these factors. Computational model: To represent the effect of geometry of grid spacer in computational model, we applied a large eddy simulation (LES) technique in couple with an improved immersed-boundary method. In our previous work (Ikeno, et al., NURETH-10), detailed properties of turbulence in subchannel were successfully investigated by developing the immersed boundary method in LES. In this study, additional improvements are given: new one-equation dynamic sub-grid scale (SGS) model is introduced to account for the complex geometry without any artificial modification; the higher order accuracy is maintained by consistent treatment for boundary conditions for velocity and pressure. NUMERICAL TEST AND DISCUSSION: Turbulent mixing coefficient and pressure drop are affected strongly by the arrangement and inclination of mixing vane. Therefore, computations are carried out for each of convolute and periodic arrangements, and for each of 30 degree and 20 degree inclinations. The difference in turbulent mixing coefficient due to these factors is reasonably predicted by our method. (An example of this numerical test is shown in Fig. 1.) Turbulent flow of the problem includes unsteady separation behind the mixing vane and vortex shedding in downstream. Anisotropic distribution of turbulent stress is also appeared in rod gap. Therefore, our computational model has advantage for assessing the influence of arrangement and inclination of mixing vane. By coarser computational mesh, one can screen several candidates for spacer design. Then, by finer mesh, more quantitative analysis is possible. By such a scheme, we believe this method is useful

Development and validation of effective models for simulation of stratification and mixing phenomena in a pool of water

Energy Technology Data Exchange (ETDEWEB)

Li, H.; Kudinov, P.; Villanueva, W. (Royal Institute of Technology (KTH). Div. of Nuclear Power Safety (Sweden))

2011-06-15

This work pertains to the research program on Containment Thermal-Hydraulics at KTH. The objective is to evaluate and improve performance of methods, which are used to analyze thermal-hydraulics of steam suppression pools in a BWR plant under different abnormal transient and accident conditions. The pressure suppression pool was designed to have the capability as a heat sink to cool and condense steam released from the core vessel and/or main steam line during loss of coolant accident (LOCA) or opening of safety relief valve in normal operation of BWRs. For the case of small flow rates of steam influx, thermal stratification could develop on the part above the blowdown pipe exit and significantly impede the pool's pressure suppression capacity. Once steam flow rate increases significantly, momentum introduced by the steam injection and/or periodic expansion and collapse of large steam bubbles due to direct contact condensation can destroy stratified layers and lead to mixing of the pool water. We use CFD-like model of the general purpose thermal-hydraulic code GOTHIC for addressing the issues of stratification and mixing in the pool. In the previous works we have demonstrated that accurate and computationally efficient prediction of the pool thermal-hydraulics in the scenarios with transition between thermal stratification and mixing, presents a computational challenge. The reason is that direct contact condensation phenomena, which drive oscillatory motion of the water in the blowdown pipes, are difficult to simulate with original GOTHIC models because of appearance of artificial oscillations due to numerical disturbances. To resolve this problem we propose to model the effect of steam injection on the mixing and stratification with the Effective Heat Source (EHS) model and the Effective Momentum Source (EMS) model. We use POOLEX/PPOOLEX experiment (Lappeenranta University of Technology in Finland), in order to (a) quantify errors due to GOTHIC

Development and validation of effective models for simulation of stratification and mixing phenomena in a pool of water

International Nuclear Information System (INIS)

Li, H.; Kudinov, P.; Villanueva, W.

2011-06-01

This work pertains to the research program on Containment Thermal-Hydraulics at KTH. The objective is to evaluate and improve performance of methods, which are used to analyze thermal-hydraulics of steam suppression pools in a BWR plant under different abnormal transient and accident conditions. The pressure suppression pool was designed to have the capability as a heat sink to cool and condense steam released from the core vessel and/or main steam line during loss of coolant accident (LOCA) or opening of safety relief valve in normal operation of BWRs. For the case of small flow rates of steam influx, thermal stratification could develop on the part above the blowdown pipe exit and significantly impede the pool's pressure suppression capacity. Once steam flow rate increases significantly, momentum introduced by the steam injection and/or periodic expansion and collapse of large steam bubbles due to direct contact condensation can destroy stratified layers and lead to mixing of the pool water. We use CFD-like model of the general purpose thermal-hydraulic code GOTHIC for addressing the issues of stratification and mixing in the pool. In the previous works we have demonstrated that accurate and computationally efficient prediction of the pool thermal-hydraulics in the scenarios with transition between thermal stratification and mixing, presents a computational challenge. The reason is that direct contact condensation phenomena, which drive oscillatory motion of the water in the blowdown pipes, are difficult to simulate with original GOTHIC models because of appearance of artificial oscillations due to numerical disturbances. To resolve this problem we propose to model the effect of steam injection on the mixing and stratification with the Effective Heat Source (EHS) model and the Effective Momentum Source (EMS) model. We use POOLEX/PPOOLEX experiment (Lappeenranta University of Technology in Finland), in order to (a) quantify errors due to GOTHIC's physical models

Model for transversal turbulent mixing in axial flow in rod bundles

International Nuclear Information System (INIS)

Carajilescov, P.

1990-01-01

The present work consists in the development of a model for the transversal eddy diffusivity to account for the effect of turbulent thermal mixing in axial flows in rod bundles. The results were compared to existing correlations that are currently being used in reactor thermalhydraulic analysis and considered satisfactory. (author)

Mixed-mode modelling mixing methodologies for organisational intervention

CERN Document Server

Clarke, Steve; Lehaney, Brian

2001-01-01

The 1980s and 1990s have seen a growing interest in research and practice in the use of methodologies within problem contexts characterised by a primary focus on technology, human issues, or power. During the last five to ten years, this has given rise to challenges regarding the ability of a single methodology to address all such contexts, and the consequent development of approaches which aim to mix methodologies within a single problem situation. This has been particularly so where the situation has called for a mix of technological (the so-called 'hard') and human­ centred (so-called 'soft') methods. The approach developed has been termed mixed-mode modelling. The area of mixed-mode modelling is relatively new, with the phrase being coined approximately four years ago by Brian Lehaney in a keynote paper published at the 1996 Annual Conference of the UK Operational Research Society. Mixed-mode modelling, as suggested above, is a new way of considering problem situations faced by organisations. Traditional...

Band mixing effects in mean field theories

International Nuclear Information System (INIS)

Kuyucak, S.; Morrison, I.

1989-01-01

The 1/N expansion method, which is an angular momentum projected mean field theory, is used to investigate the nature of electromagnetic transitions in the interacting boson model (IBM). Conversely, comparison with the exact IBM results sheds light on the range of validity of the mean field theory. It is shown that the projected mean field results for the E2 transitions among the ground, β and γ bands are incomplete for the spin dependent terms and it is essential to include band mixing effect for a correct (Mikhailov) analysis of E2 data. The algebraic expressions derived are general and will be useful in the analysis of experimental data in terms of both the sd and sdg boson models. 17 refs., 7 figs., 8 tabs

Modeling tides and vertical tidal mixing: A reality check

International Nuclear Information System (INIS)

Robertson, Robin

2010-01-01

Recently, there has been a great interest in the tidal contribution to vertical mixing in the ocean. In models, vertical mixing is estimated using parameterization of the sub-grid scale processes. Estimates of the vertical mixing varied widely depending on which vertical mixing parameterization was used. This study investigated the performance of ten different vertical mixing parameterizations in a terrain-following ocean model when simulating internal tides. The vertical mixing parameterization was found to have minor effects on the velocity fields at the tidal frequencies, but large effects on the estimates of vertical diffusivity of temperature. Although there was no definitive best performer for the vertical mixing parameterization, several parameterizations were eliminated based on comparison of the vertical diffusivity estimates with observations. The best performers were the new generic coefficients for the generic length scale schemes and Mellor-Yamada's 2.5 level closure scheme.

Nonlinear mixed effects dose response modeling in high throughput drug screens: application to melanoma cell line analysis.

Science.gov (United States)

Ding, Kuan-Fu; Petricoin, Emanuel F; Finlay, Darren; Yin, Hongwei; Hendricks, William P D; Sereduk, Chris; Kiefer, Jeffrey; Sekulic, Aleksandar; LoRusso, Patricia M; Vuori, Kristiina; Trent, Jeffrey M; Schork, Nicholas J

2018-01-12

Cancer cell lines are often used in high throughput drug screens (HTS) to explore the relationship between cell line characteristics and responsiveness to different therapies. Many current analysis methods infer relationships by focusing on one aspect of cell line drug-specific dose-response curves (DRCs), the concentration causing 50% inhibition of a phenotypic endpoint (IC 50 ). Such methods may overlook DRC features and do not simultaneously leverage information about drug response patterns across cell lines, potentially increasing false positive and negative rates in drug response associations. We consider the application of two methods, each rooted in nonlinear mixed effects (NLME) models, that test the relationship relationships between estimated cell line DRCs and factors that might mitigate response. Both methods leverage estimation and testing techniques that consider the simultaneous analysis of different cell lines to draw inferences about any one cell line. One of the methods is designed to provide an omnibus test of the differences between cell line DRCs that is not focused on any one aspect of the DRC (such as the IC 50 value). We simulated different settings and compared the different methods on the simulated data. We also compared the proposed methods against traditional IC 50 -based methods using 40 melanoma cell lines whose transcriptomes, proteomes, and, importantly, BRAF and related mutation profiles were available. Ultimately, we find that the NLME-based methods are more robust, powerful and, for the omnibus test, more flexible, than traditional methods. Their application to the melanoma cell lines reveals insights into factors that may be clinically useful.

Effect of Water-Air Clearing on Thermal Mixing in IRWST Using Three-Dimensional CFD Analysis

International Nuclear Information System (INIS)

Ha, Jeong Hee; Lee, Doo Yong; Hong, Soon Joon; Jeong, Jae Sik; Park, Man Heung; Moon, Young Tae

2013-01-01

In this paper, the water-air clearing effects on thermal mixing in the IRWST were investigated with the CFD simulation. The boundary conditions for each discharge phase were obtained from the RELAP5 simulation. The flow distribution in the IRWST for the water clearing phase was reflected as the initial condition for the air clearing simulation. The flow distribution for the air clearing phase was applied as the initial condition for the steam condensation phase. The result of the steam condensation phase with the SCRM showed that the thermal mixing in the IRWST might be enhanced by the mixing effects of the water-air clearing before the steam discharge. IRWST (in-containment refueling water storage tank) is one of the advanced design features of APR1400 (Advanced Power Reactor . 1400). Connected to the Safety Depressurization and Vent System (SDVS), IRWST is designed to absorb the high energy flow from Pilot Operated Safety and Relief Valves (POSRVs) to protect the over-pressurization of the Reactor Coolant System. Due to thermal hydraulic loads induced by discharged fluids, it is crucial to understand the phenomena occur in the IRWST and thermal mixing is one of them. It has been known that the unstable steam condensation which results in oscillations and acts as the loads on the IRWST wall and structures can occur if there is a large local temperature difference. Thus, there is a regulation related to IRWST temperature distribution (difference) to be satisfied. To understand the phenomena and design the IRWST with sufficient safety margin, many experimental and numerical researches have been performed. The results of these researches showed that the CFD analysis predicts well the temperature distribution in the pool globally and can be a proper evaluation methodology to analyze the complex thermal mixing phenomena in the IRWST with a sufficiently fine mesh distribution and proper numerical models. But the previous studies have tended to focus the phenomenological

lmerTest Package: Tests in Linear Mixed Effects Models

DEFF Research Database (Denmark)

Kuznetsova, Alexandra; Brockhoff, Per B.; Christensen, Rune Haubo Bojesen

2017-01-01

One of the frequent questions by users of the mixed model function lmer of the lme4 package has been: How can I get p values for the F and t tests for objects returned by lmer? The lmerTest package extends the 'lmerMod' class of the lme4 package, by overloading the anova and summary functions...... by providing p values for tests for fixed effects. We have implemented the Satterthwaite's method for approximating degrees of freedom for the t and F tests. We have also implemented the construction of Type I - III ANOVA tables. Furthermore, one may also obtain the summary as well as the anova table using...

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

Science.gov (United States)

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

2012-01-01

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

Reduced Rank Mixed Effects Models for Spatially Correlated Hierarchical Functional Data

KAUST Repository

Zhou, Lan

2010-03-01

Hierarchical functional data are widely seen in complex studies where sub-units are nested within units, which in turn are nested within treatment groups. We propose a general framework of functional mixed effects model for such data: within unit and within sub-unit variations are modeled through two separate sets of principal components; the sub-unit level functions are allowed to be correlated. Penalized splines are used to model both the mean functions and the principal components functions, where roughness penalties are used to regularize the spline fit. An EM algorithm is developed to fit the model, while the specific covariance structure of the model is utilized for computational efficiency to avoid storage and inversion of large matrices. Our dimension reduction with principal components provides an effective solution to the difficult tasks of modeling the covariance kernel of a random function and modeling the correlation between functions. The proposed methodology is illustrated using simulations and an empirical data set from a colon carcinogenesis study. Supplemental materials are available online.

Configuration mixing in the sdg interacting boson model

International Nuclear Information System (INIS)

Bouldjedri, A; Van Isacker, P; Zerguine, S

2005-01-01

A wavefunction analysis of the strong-coupling limits of the sdg interacting boson model is presented. The analysis is carried out for two-boson states and allows us to characterize the boson configuration mixing in the different limits. Based on these results and those of a shell-model analysis of the sdg IBM, qualitative conclusions are drawn about the range of applicability of each limit

Configuration mixing in the sdg interacting boson model

Energy Technology Data Exchange (ETDEWEB)

Bouldjedri, A [Department of Physics, Faculty of Science, University of Batna, Avenue Boukhelouf M El Hadi, 05000 Batna (Algeria); Van Isacker, P [GANIL, BP 55027, F-14076 Caen cedex 5 (France); Zerguine, S [Department of Physics, Faculty of Science, University of Batna, Avenue Boukhelouf M El Hadi, 05000 Batna (Algeria)

2005-11-01

A wavefunction analysis of the strong-coupling limits of the sdg interacting boson model is presented. The analysis is carried out for two-boson states and allows us to characterize the boson configuration mixing in the different limits. Based on these results and those of a shell-model analysis of the sdg IBM, qualitative conclusions are drawn about the range of applicability of each limit.

Validation of effective momentum and heat flux models for stratification and mixing in a water pool

Energy Technology Data Exchange (ETDEWEB)

Hua Li; Villanueva, W.; Kudinov, P. [Royal Institute of Technology (KTH), Div. of Nuclear Power Safety, Stockholm (Sweden)

2013-06-15

The pressure suppression pool is the most important feature of the pressure suppression system in a Boiling Water Reactor (BWR) that acts primarily as a passive heat sink during a loss of coolant accident (LOCA) or when the reactor is isolated from the main heat sink. The steam injection into the pool through the blowdown pipes can lead to short term dynamic phenomena and long term thermal transient in the pool. The development of thermal stratification or mixing in the pool is a transient phenomenon that can influence the pool's pressure suppression capacity. Different condensation regimes depending on the pool's bulk temperature and steam flow rates determine the onset of thermal stratification or erosion of stratified layers. Previously, we have proposed to model the effect of steam injection on the mixing and stratification with the Effective Heat Source (EHS) and the Effective Momentum Source (EMS) models. The EHS model is used to provide thermal effect of steam injection on the pool, preserving heat and mass balance. The EMS model is used to simulate momentum induced by steam injection in different flow regimes. The EMS model is based on the combination of (i) synthetic jet theory, which predicts effective momentum if amplitude and frequency of flow oscillations in the pipe are given, and (ii) model proposed by Aya and Nariai for prediction of the amplitude and frequency of oscillations at a given pool temperature and steam mass flux. The complete EHS/EMS models only require the steam mass flux, initial pool bulk temperature, and design-specific parameters, to predict thermal stratification and mixing in a pressure suppression pool. In this work we use EHS/EMS models implemented in containment thermal hydraulic code GOTHIC. The PPOOLEX experiments (Lappeenranta University of Technology, Finland) are utilized to (a) quantify errors due to GOTHIC's physical models and numerical schemes, (b) propose necessary improvements in GOTHIC sub-grid scale

A simulation-based goodness-of-fit test for random effects in generalized linear mixed models

DEFF Research Database (Denmark)

Waagepetersen, Rasmus

2006-01-01

The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal...... distribution of the simulated random effects coincides with the assumed random effects distribution. In practice, the specified model depends on some unknown parameter which is replaced by an estimate. We obtain a correction for this by deriving the asymptotic distribution of the empirical distribution...

A simulation-based goodness-of-fit test for random effects in generalized linear mixed models

DEFF Research Database (Denmark)

Waagepetersen, Rasmus Plenge

The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal...... distribution of the simulated random effects coincides with the assumed random effects distribution. In practice the specified model depends on some unknown parameter which is replaced by an estimate. We obtain a correction for this by deriving the asymptotic distribution of the empirical distribution function...

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

Science.gov (United States)

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…

Negative binomial mixed models for analyzing microbiome count data.

Science.gov (United States)

Zhang, Xinyan; Mallick, Himel; Tang, Zaixiang; Zhang, Lei; Cui, Xiangqin; Benson, Andrew K; Yi, Nengjun

2017-01-03

Recent advances in next-generation sequencing (NGS) technology enable researchers to collect a large volume of metagenomic sequencing data. These data provide valuable resources for investigating interactions between the microbiome and host environmental/clinical factors. In addition to the well-known properties of microbiome count measurements, for example, varied total sequence reads across samples, over-dispersion and zero-inflation, microbiome studies usually collect samples with hierarchical structures, which introduce correlation among the samples and thus further complicate the analysis and interpretation of microbiome count data. In this article, we propose negative binomial mixed models (NBMMs) for detecting the association between the microbiome and host environmental/clinical factors for correlated microbiome count data. Although having not dealt with zero-inflation, the proposed mixed-effects models account for correlation among the samples by incorporating random effects into the commonly used fixed-effects negative binomial model, and can efficiently handle over-dispersion and varying total reads. We have developed a flexible and efficient IWLS (Iterative Weighted Least Squares) algorithm to fit the proposed NBMMs by taking advantage of the standard procedure for fitting the linear mixed models. We evaluate and demonstrate the proposed method via extensive simulation studies and the application to mouse gut microbiome data. The results show that the proposed method has desirable properties and outperform the previously used methods in terms of both empirical power and Type I error. The method has been incorporated into the freely available R package BhGLM ( http://www.ssg.uab.edu/bhglm/ and http://github.com/abbyyan3/BhGLM ), providing a useful tool for analyzing microbiome data.

Survival analysis of clinical mastitis data using a nested frailty Cox model fit as a mixed-effects Poisson model.

Science.gov (United States)

Elghafghuf, Adel; Dufour, Simon; Reyher, Kristen; Dohoo, Ian; Stryhn, Henrik

2014-12-01

Mastitis is a complex disease affecting dairy cows and is considered to be the most costly disease of dairy herds. The hazard of mastitis is a function of many factors, both managerial and environmental, making its control a difficult issue to milk producers. Observational studies of clinical mastitis (CM) often generate datasets with a number of characteristics which influence the analysis of those data: the outcome of interest may be the time to occurrence of a case of mastitis, predictors may change over time (time-dependent predictors), the effects of factors may change over time (time-dependent effects), there are usually multiple hierarchical levels, and datasets may be very large. Analysis of such data often requires expansion of the data into the counting-process format - leading to larger datasets - thus complicating the analysis and requiring excessive computing time. In this study, a nested frailty Cox model with time-dependent predictors and effects was applied to Canadian Bovine Mastitis Research Network data in which 10,831 lactations of 8035 cows from 69 herds were followed through lactation until the first occurrence of CM. The model was fit to the data as a Poisson model with nested normally distributed random effects at the cow and herd levels. Risk factors associated with the hazard of CM during the lactation were identified, such as parity, calving season, herd somatic cell score, pasture access, fore-stripping, and proportion of treated cases of CM in a herd. The analysis showed that most of the predictors had a strong effect early in lactation and also demonstrated substantial variation in the baseline hazard among cows and between herds. A small simulation study for a setting similar to the real data was conducted to evaluate the Poisson maximum likelihood estimation approach with both Gaussian quadrature method and Laplace approximation. Further, the performance of the two methods was compared with the performance of a widely used estimation

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

Effects of Precipitation on Ocean Mixed-Layer Temperature and Salinity as Simulated in a 2-D Coupled Ocean-Cloud Resolving Atmosphere Model

Science.gov (United States)

Li, Xiaofan; Sui, C.-H.; Lau, K-M.; Adamec, D.

1999-01-01

A two-dimensional coupled ocean-cloud resolving atmosphere model is used to investigate possible roles of convective scale ocean disturbances induced by atmospheric precipitation on ocean mixed-layer heat and salt budgets. The model couples a cloud resolving model with an embedded mixed layer-ocean circulation model. Five experiment are performed under imposed large-scale atmospheric forcing in terms of vertical velocity derived from the TOGA COARE observations during a selected seven-day period. The dominant variability of mixed-layer temperature and salinity are simulated by the coupled model with imposed large-scale forcing. The mixed-layer temperatures in the coupled experiments with 1-D and 2-D ocean models show similar variations when salinity effects are not included. When salinity effects are included, however, differences in the domain-mean mixed-layer salinity and temperature between coupled experiments with 1-D and 2-D ocean models could be as large as 0.3 PSU and 0.4 C respectively. Without fresh water effects, the nocturnal heat loss over ocean surface causes deep mixed layers and weak cooling rates so that the nocturnal mixed-layer temperatures tend to be horizontally-uniform. The fresh water flux, however, causes shallow mixed layers over convective areas while the nocturnal heat loss causes deep mixed layer over convection-free areas so that the mixed-layer temperatures have large horizontal fluctuations. Furthermore, fresh water flux exhibits larger spatial fluctuations than surface heat flux because heavy rainfall occurs over convective areas embedded in broad non-convective or clear areas, whereas diurnal signals over whole model areas yield high spatial correlation of surface heat flux. As a result, mixed-layer salinities contribute more to the density differences than do mixed-layer temperatures.

A marketing mix model for a complex and turbulent environment

Directory of Open Access Journals (Sweden)

R. B. Mason

2007-12-01

Full Text Available Purpose: This paper is based on the proposition that the choice of marketing tactics is determined, or at least significantly influenced, by the nature of the company’s external environment. It aims to illustrate the type of marketing mix tactics that are suggested for a complex and turbulent environment when marketing and the environment are viewed through a chaos and complexity theory lens. Design/Methodology/Approach: Since chaos and complexity theories are proposed as a good means of understanding the dynamics of complex and turbulent markets, a comprehensive review and analysis of literature on the marketing mix and marketing tactics from a chaos and complexity viewpoint was conducted. From this literature review, a marketing mix model was conceptualised. Findings: A marketing mix model considered appropriate for success in complex and turbulent environments was developed. In such environments, the literature suggests destabilising marketing activities are more effective, whereas stabilising type activities are more effective in simple, stable environments. Therefore the model proposes predominantly destabilising type tactics as appropriate for a complex and turbulent environment such as is currently being experienced in South Africa. Implications: This paper is of benefit to marketers by emphasising a new way to consider the future marketing activities of their companies. How this model can assist marketers and suggestions for research to develop and apply this model are provided. It is hoped that the model suggested will form the basis of empirical research to test its applicability in the turbulent South African environment. Originality/Value: Since businesses and markets are complex adaptive systems, using complexity theory to understand how to cope in complex, turbulent environments is necessary, but has not been widely researched. In fact, most chaos and complexity theory work in marketing has concentrated on marketing strategy, with

Improving Mixed-phase Cloud Parameterization in Climate Model with the ACRF Measurements

Energy Technology Data Exchange (ETDEWEB)

Wang, Zhien [Univ. of Wyoming, Laramie, WY (United States)

2016-12-13

Mixed-phase cloud microphysical and dynamical processes are still poorly understood, and their representation in GCMs is a major source of uncertainties in overall cloud feedback in GCMs. Thus improving mixed-phase cloud parameterizations in climate models is critical to reducing the climate forecast uncertainties. This study aims at providing improved knowledge of mixed-phase cloud properties from the long-term ACRF observations and improving mixed-phase clouds simulations in the NCAR Community Atmosphere Model version 5 (CAM5). The key accomplishments are: 1) An improved retrieval algorithm was developed to provide liquid droplet concentration for drizzling or mixed-phase stratiform clouds. 2) A new ice concentration retrieval algorithm for stratiform mixed-phase clouds was developed. 3) A strong seasonal aerosol impact on ice generation in Arctic mixed-phase clouds was identified, which is mainly attributed to the high dust occurrence during the spring season. 4) A suite of multi-senor algorithms was applied to long-term ARM observations at the Barrow site to provide a complete dataset (LWC and effective radius profile for liquid phase, and IWC, Dge profiles and ice concentration for ice phase) to characterize Arctic stratiform mixed-phase clouds. This multi-year stratiform mixed-phase cloud dataset provides necessary information to study related processes, evaluate model stratiform mixed-phase cloud simulations, and improve model stratiform mixed-phase cloud parameterization. 5). A new in situ data analysis method was developed to quantify liquid mass partition in convective mixed-phase clouds. For the first time, we reliably compared liquid mass partitions in stratiform and convective mixed-phase clouds. Due to the different dynamics in stratiform and convective mixed-phase clouds, the temperature dependencies of liquid mass partitions are significantly different due to much higher ice concentrations in convective mixed phase clouds. 6) Systematic evaluations

Mixing-model Sensitivity to Initial Conditions in Hydrodynamic Predictions

Science.gov (United States)

Bigelow, Josiah; Silva, Humberto; Truman, C. Randall; Vorobieff, Peter

2017-11-01

Amagat and Dalton mixing-models were studied to compare their thermodynamic prediction of shock states. Numerical simulations with the Sandia National Laboratories shock hydrodynamic code CTH modeled University of New Mexico (UNM) shock tube laboratory experiments shocking a 1:1 molar mixture of helium (He) and sulfur hexafluoride (SF6) . Five input parameters were varied for sensitivity analysis: driver section pressure, driver section density, test section pressure, test section density, and mixture ratio (mole fraction). We show via incremental Latin hypercube sampling (LHS) analysis that significant differences exist between Amagat and Dalton mixing-model predictions. The differences observed in predicted shock speeds, temperatures, and pressures grow more pronounced with higher shock speeds. Supported by NNSA Grant DE-0002913.

Effective Momentum and heat flux models for simulation of stratification and mixing in a large pool of water

Energy Technology Data Exchange (ETDEWEB)

Hua Li; Villanueva, W.; Kudinov, P. [Royal Institute of Technology (KTH). Div. of Nuclear Power Safety, Stockholm (Sweden)

2012-06-15

Performance of a boiling water reactor (BWR) containment is mostly determined by reliable operation of pressure suppression pool which serves as a heat sink to cool and condense steam released from the core vessel. Thermal stratification in the pool can significantly impede the pool's pressure suppression capacity. A source of momentum is required in order to break stratification and mix the pool. It is important to have reliable prediction of transient development of stratification and mixing in the pool in different regimes of steam injection. Previously, we have proposed to model the effect of steam injection on the mixing and stratification with the Effective Heat Source (EHS) and the Effective Momentum Source (EMS) models. The EHS model is used to provide thermal effect of steam injection on the pool, preserving heat and mass balance. The EMS model is used to simulate momentum induced by steam injection in different flow regimes. The EMS model is based on the combination of (1) synthetic jet theory, which predicts effective momentum if amplitude and frequency of flow oscillations in the pipe are given, and (2) model proposed by Aya and Nariai for prediction of the amplitude and frequency of oscillations at a given pool temperature and steam mass flux. The complete EHS/EMS models only require the steam mass flux, initial pool bulk temperature, and design-specific parameters, to predict thermal stratification and mixing in a pressure suppression pool. In this work we use EHS/EMS models implemented in containment thermal hydraulic code GOTHIC. The POOLEX/PPOOLEX experiments (Lappeenranta University of Technology, Finland) are utilized, to (a) quantify errors due to GOTHIC's physical models and numerical schemes, (b) propose necessary improvements in GOTHIC sub-grid scale modeling, and (c) validate our proposed models. Specifically the data from POOLEX STB-21 and PPOOLEX STR-03 and STR-04 tests are used for validation of the EHS and EMS models in this

Effective Momentum and heat flux models for simulation of stratification and mixing in a large pool of water

International Nuclear Information System (INIS)

Hua Li; Villanueva, W.; Kudinov, P.

2012-06-01

Performance of a boiling water reactor (BWR) containment is mostly determined by reliable operation of pressure suppression pool which serves as a heat sink to cool and condense steam released from the core vessel. Thermal stratification in the pool can significantly impede the pool's pressure suppression capacity. A source of momentum is required in order to break stratification and mix the pool. It is important to have reliable prediction of transient development of stratification and mixing in the pool in different regimes of steam injection. Previously, we have proposed to model the effect of steam injection on the mixing and stratification with the Effective Heat Source (EHS) and the Effective Momentum Source (EMS) models. The EHS model is used to provide thermal effect of steam injection on the pool, preserving heat and mass balance. The EMS model is used to simulate momentum induced by steam injection in different flow regimes. The EMS model is based on the combination of (1) synthetic jet theory, which predicts effective momentum if amplitude and frequency of flow oscillations in the pipe are given, and (2) model proposed by Aya and Nariai for prediction of the amplitude and frequency of oscillations at a given pool temperature and steam mass flux. The complete EHS/EMS models only require the steam mass flux, initial pool bulk temperature, and design-specific parameters, to predict thermal stratification and mixing in a pressure suppression pool. In this work we use EHS/EMS models implemented in containment thermal hydraulic code GOTHIC. The POOLEX/PPOOLEX experiments (Lappeenranta University of Technology, Finland) are utilized, to (a) quantify errors due to GOTHIC's physical models and numerical schemes, (b) propose necessary improvements in GOTHIC sub-grid scale modeling, and (c) validate our proposed models. Specifically the data from POOLEX STB-21 and PPOOLEX STR-03 and STR-04 tests are used for validation of the EHS and EMS models in this work. We

Goodness-of-fit tests in mixed models

KAUST Repository

Claeskens, Gerda; Hart, Jeffrey D.

2009-01-01

Mixed models, with both random and fixed effects, are most often estimated on the assumption that the random effects are normally distributed. In this paper we propose several formal tests of the hypothesis that the random effects and/or errors

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

Science.gov (United States)

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

Subchannel analysis with turbulent mixing rate of supercritical pressure fluid

International Nuclear Information System (INIS)

Wu, Jianhui; Oka, Yoshiaki

2015-01-01

Highlights: • Subchannel analysis with turbulent mixing rate law of supercritical pressure fluid (SPF) is carried out. • Turbulent mixing rate is enhanced, compared with that calculated by the law of pressurized water reactor (PWR). • Increase in maximum cladding surface temperature (MCST) is smaller comparing with PWR model. • The sensitivities of MCST on non-uniformity of subchannel area and power peaking are reduced by using SPF model. - Abstract: The subchannel analysis with turbulent mixing rate law of supercritical pressure fluid (SPF) is carried out for supercritical-pressurized light water cooled and moderated reactor (Super LWR). It is different from the turbulent mixing rate law of pressurized water reactor (PWR), which is widely adopted in Super LWR subchannel analysis study, the density difference between adjacent subchannels is taken into account for turbulent mixing rate law of SPF. MCSTs are evaluated on three kinds of fuel assemblies with different pin power distribution patterns, gap spacings and mass flow rates. Compared with that calculated by employing turbulent mixing rate law of PWR, the increase in MCST is smaller even when peaking factor is large and gap spacing is uneven. The sensitivities of MCST on non-uniformity of the subchannel area and power peaking are reduced

Impact of Grain Shape and Multiple Black Carbon Internal Mixing on Snow Albedo: Parameterization and Radiative Effect Analysis

Science.gov (United States)

He, Cenlin; Liou, Kuo-Nan; Takano, Yoshi; Yang, Ping; Qi, Ling; Chen, Fei

2018-01-01

We quantify the effects of grain shape and multiple black carbon (BC)-snow internal mixing on snow albedo by explicitly resolving shape and mixing structures. Nonspherical snow grains tend to have higher albedos than spheres with the same effective sizes, while the albedo difference due to shape effects increases with grain size, with up to 0.013 and 0.055 for effective radii of 1,000 μm at visible and near-infrared bands, respectively. BC-snow internal mixing reduces snow albedo at wavelengths external mixing, internal mixing enhances snow albedo reduction by a factor of 1.2-2.0 at visible wavelengths depending on BC concentration and snow shape. The opposite effects on albedo reductions due to snow grain nonsphericity and BC-snow internal mixing point toward a careful investigation of these two factors simultaneously in climate modeling. We further develop parameterizations for snow albedo and its reduction by accounting for grain shape and BC-snow internal/external mixing. Combining the parameterizations with BC-in-snow measurements in China, North America, and the Arctic, we estimate that nonspherical snow grains reduce BC-induced albedo radiative effects by up to 50% compared with spherical grains. Moreover, BC-snow internal mixing enhances the albedo effects by up to 30% (130%) for spherical (nonspherical) grains relative to external mixing. The overall uncertainty induced by snow shape and BC-snow mixing state is about 21-32%.

Multivariate longitudinal data analysis with mixed effects hidden Markov models.

Science.gov (United States)

Raffa, Jesse D; Dubin, Joel A

2015-09-01

Multiple longitudinal responses are often collected as a means to capture relevant features of the true outcome of interest, which is often hidden and not directly measurable. We outline an approach which models these multivariate longitudinal responses as generated from a hidden disease process. We propose a class of models which uses a hidden Markov model with separate but correlated random effects between multiple longitudinal responses. This approach was motivated by a smoking cessation clinical trial, where a bivariate longitudinal response involving both a continuous and a binomial response was collected for each participant to monitor smoking behavior. A Bayesian method using Markov chain Monte Carlo is used. Comparison of separate univariate response models to the bivariate response models was undertaken. Our methods are demonstrated on the smoking cessation clinical trial dataset, and properties of our approach are examined through extensive simulation studies. © 2015, The International Biometric Society.

Mixed-culture transcriptome analysis reveals the molecular basis of mixed-culture growth in Streptococcus thermophilus and Lactobacillus bulgaricus.

Science.gov (United States)

Sieuwerts, Sander; Molenaar, Douwe; van Hijum, Sacha A F T; Beerthuyzen, Marke; Stevens, Marc J A; Janssen, Patrick W M; Ingham, Colin J; de Bok, Frank A M; de Vos, Willem M; van Hylckama Vlieg, Johan E T

2010-12-01

Many food fermentations are performed using mixed cultures of lactic acid bacteria. Interactions between strains are of key importance for the performance of these fermentations. Yogurt fermentation by Streptococcus thermophilus and Lactobacillus bulgaricus (basonym, Lactobacillus delbrueckii subsp. bulgaricus) is one of the best-described mixed-culture fermentations. These species are believed to stimulate each other's growth by the exchange of metabolites such as folic acid and carbon dioxide. Recently, postgenomic studies revealed that an upregulation of biosynthesis pathways for nucleotides and sulfur-containing amino acids is part of the global physiological response to mixed-culture growth in S. thermophilus, but an in-depth molecular analysis of mixed-culture growth of both strains remains to be established. We report here the application of mixed-culture transcriptome profiling and a systematic analysis of the effect of interaction-related compounds on growth, which allowed us to unravel the molecular responses associated with batch mixed-culture growth in milk of S. thermophilus CNRZ1066 and L. bulgaricus ATCC BAA-365. The results indicate that interactions between these bacteria are primarily related to purine, amino acid, and long-chain fatty acid metabolism. The results support a model in which formic acid, folic acid, and fatty acids are provided by S. thermophilus. Proteolysis by L. bulgaricus supplies both strains with amino acids but is insufficient to meet the biosynthetic demands for sulfur and branched-chain amino acids, as becomes clear from the upregulation of genes associated with these amino acids in mixed culture. Moreover, genes involved in iron uptake in S. thermophilus are affected by mixed-culture growth, and genes coding for exopolysaccharide production were upregulated in both organisms in mixed culture compared to monocultures. The confirmation of previously identified responses in S. thermophilus using a different strain combination

ADVANCED MIXING MODELS

Energy Technology Data Exchange (ETDEWEB)

Lee, S; Dimenna, R; Tamburello, D

2011-02-14

The process of recovering and processing High Level Waste (HLW) the waste in storage tanks at the Savannah River Site (SRS) typically requires mixing the contents of the tank with one to four mixers (pumps) located within the tank. The typical criteria to establish a mixed condition in a tank are based on the number of pumps in operation and the time duration of operation. To ensure that a mixed condition is achieved, operating times are typically set conservatively long. This approach results in high operational costs because of the long mixing times and high maintenance and repair costs for the same reason. A significant reduction in both of these costs might be realized by reducing the required mixing time based on calculating a reliable indicator of mixing with a suitably validated computer code. The focus of the present work is to establish mixing criteria applicable to miscible fluids, with an ultimate goal of addressing waste processing in HLW tanks at SRS and quantifying the mixing time required to suspend sludge particles with the submersible jet pump. A single-phase computational fluid dynamics (CFD) approach was taken for the analysis of jet flow patterns with an emphasis on the velocity decay and the turbulent flow evolution for the farfield region from the pump. Literature results for a turbulent jet flow are reviewed, since the decay of the axial jet velocity and the evolution of the jet flow patterns are important phenomena affecting sludge suspension and mixing operations. The work described in this report suggests a basis for further development of the theory leading to the identified mixing indicators, with benchmark analyses demonstrating their consistency with widely accepted correlations. Although the indicators are somewhat generic in nature, they are applied to Savannah River Site (SRS) waste tanks to provide a better, physically based estimate of the required mixing time. Waste storage tanks at SRS contain settled sludge which varies in

Modeling and analysis of ORNL horizontal storage tank mobilization and mixing

International Nuclear Information System (INIS)

Mahoney, L.A.; Terrones, G.; Eyler, L.L.

1994-06-01

The retrieval and treatment of radioactive sludges that are stored in tanks constitute a prevalent problem at several US Department of Energy sites. The tanks typically contain a settled sludge layer with non-Newtonian rheological characteristics covered by a layer of supernatant. The first step in retrieval is the mobilization and mixing of the supernatant and sludge in the storage tanks. Submerged jets have been proposed to achieve sludge mobilization in tanks, including the 189 m 3 (50,000 gallon) Melton Valley Storage tanks (MVST) at Oak Ridge National Laboratory (ORNL) and the planned 378 m 3 (100,000 gallon) tanks being designed as part of the MVST Capacity Increase Project (MVST-CIP). This report focuses on the modeling of mixing and mobilization in horizontal cylindrical tanks like those of the MVST design using submerged, recirculating liquid jets. The computer modeling of the mobilization and mixing processes uses the TEMPEST computational fluid dynamics program (Trend and Eyler 1992). The goals of the simulations are to determine under what conditions sludge mobilization using submerged liquid jets is feasible in tanks of this configuration, and to estimate mixing times required to approach homogeneity of the contents

Modeling of particle mixing in the atmosphere

International Nuclear Information System (INIS)

Zhu, Shupeng

2015-01-01

This thesis presents a newly developed size-composition resolved aerosol model (SCRAM), which is able to simulate the dynamics of externally-mixed particles in the atmosphere, and evaluates its performance in three-dimensional air-quality simulations. The main work is split into four parts. First, the research context of external mixing and aerosol modelling is introduced. Secondly, the development of the SCRAM box model is presented along with validation tests. Each particle composition is defined by the combination of mass-fraction sections of its chemical components or aggregates of components. The three main processes involved in aerosol dynamic (nucleation, coagulation, condensation/ evaporation) are included in SCRAM. The model is first validated by comparisons with published reference solutions for coagulation and condensation/evaporation of internally-mixed particles. The particle mixing state is investigated in a 0-D simulation using data representative of air pollution at a traffic site in Paris. The relative influence on the mixing state of the different aerosol processes and of the algorithm used to model condensation/evaporation (dynamic evolution or bulk equilibrium between particles and gas) is studied. Then, SCRAM is integrated into the Polyphemus air quality platform and used to conduct simulations over Greater Paris during the summer period of 2009. This evaluation showed that SCRAM gives satisfactory results for both PM2.5/PM10 concentrations and aerosol optical depths, as assessed from comparisons to observations. Besides, the model allows us to analyze the particle mixing state, as well as the impact of the mixing state assumption made in the modelling on particle formation, aerosols optical properties, and cloud condensation nuclei activation. Finally, two simulations are conducted during the winter campaign of MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric Pollution and climate effects, and Integrated tools for

Additive action model for mixed irradiation

International Nuclear Information System (INIS)

Lam, G.K.Y.

1984-01-01

Recent experimental results indicate that a mixture of high and low LET radiation may have some beneficial features (such as lower OER but with skin sparing) for clinical use, and interest has been renewed in the study of mixtures of high and low LET radiation. Several standard radiation inactivation models can readily accommodate interaction between two mixed radiations, however, this is usually handled by postulating extra free parameters, which can only be determined by fitting to experimental data. A model without any free parameter is proposed to explain the biological effect of mixed radiations, based on the following two assumptions: (a) The combined biological action due to two radiations is additive, assuming no repair has taken place during the interval between the two irradiations; and (b) The initial physical damage induced by radiation develops into final biological effect (e.g. cell killing) over a relatively long period (hours) after irradiation. This model has been shown to provide satisfactory fit to the experiment results of previous studies

Mixed models for predictive modeling in actuarial science

NARCIS (Netherlands)

Antonio, K.; Zhang, Y.

2012-01-01

We start with a general discussion of mixed (also called multilevel) models and continue with illustrating specific (actuarial) applications of this type of models. Technical details on (linear, generalized, non-linear) mixed models follow: model assumptions, specifications, estimation techniques

Nonlinear mixed effects modelling for the analysis of longitudinal body core temperature data in healthy volunteers.

Science.gov (United States)

Seng, Kok-Yong; Chen, Ying; Wang, Ting; Ming Chai, Adam Kian; Yuen Fun, David Chiok; Teo, Ya Shi; Sze Tan, Pearl Min; Ang, Wee Hon; Wei Lee, Jason Kai

2016-04-01

Many longitudinal studies have collected serial body core temperature (T c) data to understand thermal work strain of workers under various environmental and operational heat stress environments. This provides the opportunity for the development of mathematical models to analyse and forecast temporal T c changes across populations of subjects. Such models can reduce the need for invasive methods that continuously measure T c. This current work sought to develop a nonlinear mixed effects modelling framework to delineate the dynamic changes of T c and its association with a set of covariates of interest (e.g. heart rate, chest skin temperature), and the structure of the variability of T c in various longitudinal studies. Data to train and evaluate the model were derived from two laboratory investigations involving male soldiers who participated in either a 12 (N  =  18) or 15 km (N  =  16) foot march with varied clothing, load and heat acclimatisation status. Model qualification was conducted using nonparametric bootstrap and cross validation procedures. For cross validation, the trajectory of a new subject's T c was simulated via Bayesian maximum a posteriori estimation when using only the baseline T c or using the baseline T c as well as measured T c at the end of every work (march) phase. The final model described T c versus time profiles using a parametric function with its main parameters modelled as a sigmoid hyperbolic function of the load and/or chest skin temperature. Overall, T c predictions corresponded well with the measured data (root mean square deviation: 0.16 °C), and compared favourably with those provided by two recently published Kalman filter models.

Validation of Effective Models for Simulation of Thermal Stratification and Mixing Induced by Steam Injection into a Large Pool of Water

Directory of Open Access Journals (Sweden)

Hua Li

2014-01-01

Full Text Available The Effective Heat Source (EHS and Effective Momentum Source (EMS models have been proposed to predict the development of thermal stratification and mixing during a steam injection into a large pool of water. These effective models are implemented in GOTHIC software and validated against the POOLEX STB-20 and STB-21 tests and the PPOOLEX MIX-01 test. First, the EHS model is validated against STB-20 test which shows the development of thermal stratification. Different numerical schemes and grid resolutions have been tested. A 48×114 grid with second order scheme is sufficient to capture the vertical temperature distribution in the pool. Next, the EHS and EMS models are validated against STB-21 test. Effective momentum is estimated based on the water level oscillations in the blowdown pipe. An effective momentum selected within the experimental measurement uncertainty can reproduce the mixing details. Finally, the EHS-EMS models are validated against MIX-01 test which has improved space and time resolution of temperature measurements inside the blowdown pipe. Excellent agreement in averaged pool temperature and water level in the pool between the experiment and simulation has been achieved. The development of thermal stratification in the pool is also well captured in the simulation as well as the thermal behavior of the pool during the mixing phase.

Markov and semi-Markov switching linear mixed models used to identify forest tree growth components.

Science.gov (United States)

Chaubert-Pereira, Florence; Guédon, Yann; Lavergne, Christian; Trottier, Catherine

2010-09-01

Tree growth is assumed to be mainly the result of three components: (i) an endogenous component assumed to be structured as a succession of roughly stationary phases separated by marked change points that are asynchronous among individuals, (ii) a time-varying environmental component assumed to take the form of synchronous fluctuations among individuals, and (iii) an individual component corresponding mainly to the local environment of each tree. To identify and characterize these three components, we propose to use semi-Markov switching linear mixed models, i.e., models that combine linear mixed models in a semi-Markovian manner. The underlying semi-Markov chain represents the succession of growth phases and their lengths (endogenous component) whereas the linear mixed models attached to each state of the underlying semi-Markov chain represent-in the corresponding growth phase-both the influence of time-varying climatic covariates (environmental component) as fixed effects, and interindividual heterogeneity (individual component) as random effects. In this article, we address the estimation of Markov and semi-Markov switching linear mixed models in a general framework. We propose a Monte Carlo expectation-maximization like algorithm whose iterations decompose into three steps: (i) sampling of state sequences given random effects, (ii) prediction of random effects given state sequences, and (iii) maximization. The proposed statistical modeling approach is illustrated by the analysis of successive annual shoots along Corsican pine trunks influenced by climatic covariates. © 2009, The International Biometric Society.

Data on copula modeling of mixed discrete and continuous neural time series.

Science.gov (United States)

Hu, Meng; Li, Mingyao; Li, Wu; Liang, Hualou

2016-06-01

Copula is an important tool for modeling neural dependence. Recent work on copula has been expanded to jointly model mixed time series in neuroscience ("Hu et al., 2016, Joint Analysis of Spikes and Local Field Potentials using Copula" [1]). Here we present further data for joint analysis of spike and local field potential (LFP) with copula modeling. In particular, the details of different model orders and the influence of possible spike contamination in LFP data from the same and different electrode recordings are presented. To further facilitate the use of our copula model for the analysis of mixed data, we provide the Matlab codes, together with example data.

A Lagrangian mixing frequency model for transported PDF modeling

Science.gov (United States)

Turkeri, Hasret; Zhao, Xinyu

2017-11-01

In this study, a Lagrangian mixing frequency model is proposed for molecular mixing models within the framework of transported probability density function (PDF) methods. The model is based on the dissipations of mixture fraction and progress variables obtained from Lagrangian particles in PDF methods. The new model is proposed as a remedy to the difficulty in choosing the optimal model constant parameters when using conventional mixing frequency models. The model is implemented in combination with the Interaction by exchange with the mean (IEM) mixing model. The performance of the new model is examined by performing simulations of Sandia Flame D and the turbulent premixed flame from the Cambridge stratified flame series. The simulations are performed using the pdfFOAM solver which is a LES/PDF solver developed entirely in OpenFOAM. A 16-species reduced mechanism is used to represent methane/air combustion, and in situ adaptive tabulation is employed to accelerate the finite-rate chemistry calculations. The results are compared with experimental measurements as well as with the results obtained using conventional mixing frequency models. Dynamic mixing frequencies are predicted using the new model without solving additional transport equations, and good agreement with experimental data is observed.

Sediment fingerprinting experiments to test the sensitivity of multivariate mixing models

Science.gov (United States)

Gaspar, Leticia; Blake, Will; Smith, Hugh; Navas, Ana

2014-05-01

Sediment fingerprinting techniques provide insight into the dynamics of sediment transfer processes and support for catchment management decisions. As questions being asked of fingerprinting datasets become increasingly complex, validation of model output and sensitivity tests are increasingly important. This study adopts an experimental approach to explore the validity and sensitivity of mixing model outputs for materials with contrasting geochemical and particle size composition. The experiments reported here focused on (i) the sensitivity of model output to different fingerprint selection procedures and (ii) the influence of source material particle size distributions on model output. Five soils with significantly different geochemistry, soil organic matter and particle size distributions were selected as experimental source materials. A total of twelve sediment mixtures were prepared in the laboratory by combining different quantified proportions of the Kruskal-Wallis test, Discriminant Function Analysis (DFA), Principal Component Analysis (PCA), or correlation matrix). Summary results for the use of the mixing model with the different sets of fingerprint properties for the twelve mixed soils were reasonably consistent with the initial mixing percentages initially known. Given the experimental nature of the work and dry mixing of materials, geochemical conservative behavior was assumed for all elements, even for those that might be disregarded in aquatic systems (e.g. P). In general, the best fits between actual and modeled proportions were found using a set of nine tracer properties (Sr, Rb, Fe, Ti, Ca, Al, P, Si, K, Si) that were derived using DFA coupled with a multivariate stepwise algorithm, with errors between real and estimated value that did not exceed 6.7 % and values of GOF above 94.5 %. The second set of experiments aimed to explore the sensitivity of model output to variability in the particle size of source materials assuming that a degree of

Mixed-effects models for estimating stand volume by means of small footprint airborne laser scanner data.

Science.gov (United States)

J. Breidenbach; E. Kublin; R. McGaughey; H.-E. Andersen; S. Reutebuch

2008-01-01

For this study, hierarchical data sets--in that several sample plots are located within a stand--were analyzed for study sites in the USA and Germany. The German data had an additional hierarchy as the stands are located within four distinct public forests. Fixed-effects models and mixed-effects models with a random intercept on the stand level were fit to each data...

RO1 Funding for Mixed Methods Research: Lessons learned from the Mixed-Method Analysis of Japanese Depression Project

OpenAIRE

Arnault, Denise Saint; Fetters, Michael D.

2011-01-01

Mixed methods research has made significant in-roads in the effort to examine complex health related phenomenon. However, little has been published on the funding of mixed methods research projects. This paper addresses that gap by presenting an example of an NIMH funded project using a mixed methods QUAL-QUAN triangulation design entitled “The Mixed-Method Analysis of Japanese Depression.” We present the Cultural Determinants of Health Seeking model that framed the study, the specific aims, ...

From linear to generalized linear mixed models: A case study in repeated measures

Science.gov (United States)

Compared to traditional linear mixed models, generalized linear mixed models (GLMMs) can offer better correspondence between response variables and explanatory models, yielding more efficient estimates and tests in the analysis of data from designed experiments. Using proportion data from a designed...

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

Science.gov (United States)

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 ).

Deliberate practice predicts performance throughout time in adolescent chess players and dropouts: A linear mixed models analysis.

NARCIS (Netherlands)

de Bruin, A.B.H.; Smits, N.; Rikers, R.M.J.P.; Schmidt, H.G.

2008-01-01

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,

Bayes factor between Student t and Gaussian mixed models within an animal breeding context

Directory of Open Access Journals (Sweden)

García-Cortés Luis

2008-07-01

Full Text Available Abstract The implementation of Student t mixed models in animal breeding has been suggested as a useful statistical tool to effectively mute the impact of preferential treatment or other sources of outliers in field data. Nevertheless, these additional sources of variation are undeclared and we do not know whether a Student t mixed model is required or if a standard, and less parameterized, Gaussian mixed model would be sufficient to serve the intended purpose. Within this context, our aim was to develop the Bayes factor between two nested models that only differed in a bounded variable in order to easily compare a Student t and a Gaussian mixed model. It is important to highlight that the Student t density converges to a Gaussian process when degrees of freedom tend to infinity. The twomodels can then be viewed as nested models that differ in terms of degrees of freedom. The Bayes factor can be easily calculated from the output of a Markov chain Monte Carlo sampling of the complex model (Student t mixed model. The performance of this Bayes factor was tested under simulation and on a real dataset, using the deviation information criterion (DIC as the standard reference criterion. The two statistical tools showed similar trends along the parameter space, although the Bayes factor appeared to be the more conservative. There was considerable evidence favoring the Student t mixed model for data sets simulated under Student t processes with limited degrees of freedom, and moderate advantages associated with using the Gaussian mixed model when working with datasets simulated with 50 or more degrees of freedom. For the analysis of real data (weight of Pietrain pigs at six months, both the Bayes factor and DIC slightly favored the Student t mixed model, with there being a reduced incidence of outlier individuals in this population.

The Effects of Living in Segregated vs. Mixed Areas in Northern Ireland: A Simultaneous Analysis of Contact and Threat Effects in the Context of Micro-Level Neighbourhoods

Directory of Open Access Journals (Sweden)

Joanne Hughes

2008-06-01

Full Text Available This study examines the consequences of living in segregated and mixed neighbourhoods on ingroup bias and offensive action tendencies, taking into consideration the role of intergroup experiences and perceived threat. Using adult data from a cross-sectional survey in Belfast, Northern Ireland, we tested a model that examined the relationship between living in segregated (N = 396 and mixed (N = 562 neighbourhoods and positive contact, exposure to violence, perceived threat and outgroup orientations. Our results show that living in mixed neighbourhoods was associated with lower ingroup bias and reduced offensive action tendencies. These effects were partially mediated by positive contact. However, our analysis also shows that respondents living in mixed neighbourhoods report higher exposure to political violence and higher perceived threat to physical safety. These findings demonstrate the importance of examining both social experience and threat perceptions when testing the relationship between social environment and prejudice.

An investment plan for preventing child injuries using risk priority number of failure mode and effects analysis methodology and a multi-objective, multi-dimensional mixed 0-1 knapsack model

International Nuclear Information System (INIS)

Bas, Esra

2011-01-01

In this paper, a general framework for child injury prevention and a multi-objective, multi-dimensional mixed 0-1 knapsack model were developed to determine the optimal time to introduce preventive measures against child injuries. Furthermore, the model maximises the prevention of injuries with the highest risks for each age period by combining preventive measures and supervision as well as satisfying budget limits and supervision time constraints. The risk factors for each injury, variable, and time period were based on risk priority numbers (RPNs) obtained from failure mode and effects analysis (FMEA) methodology, and these risk factors were incorporated into the model as objective function parameters. A numerical experiment based on several different situations was conducted, revealing that the model provided optimal timing of preventive measures for child injuries based on variables considered.

Application of zero-inflated poisson mixed models in prognostic factors of hepatitis C.

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Akbarzadeh Baghban, Alireza; Pourhoseingholi, Asma; Zayeri, Farid; Jafari, Ali Akbar; Alavian, Seyed Moayed

2013-01-01

In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C. The data was collected from a longitudinal study during 2005-2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the proposed mixed model, standard errors of estimators were compared. The results obtained from mixed PR showed that genotype 3 and treatment protocol were statistically significant. Results of zero-inflated Poisson mixed model showed that age, sex, genotypes 2 and 3, the treatment protocol, and having risk factors had significant effects on viral load of HCV patients. Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors. The results showed that a mixed zero-inflated Poisson model was the almost best fit. The proposed model can capture serial dependence, additional overdispersion, and excess zeros in the longitudinal count data.

Population stochastic modelling (PSM)--an R package for mixed-effects models based on stochastic differential equations.

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Klim, Søren; Mortensen, Stig Bousgaard; Kristensen, Niels Rode; Overgaard, Rune Viig; Madsen, Henrik

2009-06-01

The extension from ordinary to stochastic differential equations (SDEs) in pharmacokinetic and pharmacodynamic (PK/PD) modelling is an emerging field and has been motivated in a number of articles [N.R. Kristensen, H. Madsen, S.H. Ingwersen, Using stochastic differential equations for PK/PD model development, J. Pharmacokinet. Pharmacodyn. 32 (February(1)) (2005) 109-141; C.W. Tornøe, R.V. Overgaard, H. Agersø, H.A. Nielsen, H. Madsen, E.N. Jonsson, Stochastic differential equations in NONMEM: implementation, application, and comparison with ordinary differential equations, Pharm. Res. 22 (August(8)) (2005) 1247-1258; R.V. Overgaard, N. Jonsson, C.W. Tornøe, H. Madsen, Non-linear mixed-effects models with stochastic differential equations: implementation of an estimation algorithm, J. Pharmacokinet. Pharmacodyn. 32 (February(1)) (2005) 85-107; U. Picchini, S. Ditlevsen, A. De Gaetano, Maximum likelihood estimation of a time-inhomogeneous stochastic differential model of glucose dynamics, Math. Med. Biol. 25 (June(2)) (2008) 141-155]. PK/PD models are traditionally based ordinary differential equations (ODEs) with an observation link that incorporates noise. This state-space formulation only allows for observation noise and not for system noise. Extending to SDEs allows for a Wiener noise component in the system equations. This additional noise component enables handling of autocorrelated residuals originating from natural variation or systematic model error. Autocorrelated residuals are often partly ignored in PK/PD modelling although violating the hypothesis for many standard statistical tests. This article presents a package for the statistical program R that is able to handle SDEs in a mixed-effects setting. The estimation method implemented is the FOCE(1) approximation to the population likelihood which is generated from the individual likelihoods that are approximated using the Extended Kalman Filter's one-step predictions.

Are mixed explicit/implicit solvation models reliable for studying phosphate hydrolysis? A comparative study of continuum, explicit and mixed solvation models.

Energy Technology Data Exchange (ETDEWEB)

Kamerlin, Shina C. L.; Haranczyk, Maciej; Warshel, Arieh

2009-05-01

Phosphate hydrolysis is ubiquitous in biology. However, despite intensive research on this class of reactions, the precise nature of the reaction mechanism remains controversial. In this work, we have examined the hydrolysis of three homologous phosphate diesters. The solvation free energy was simulated by means of either an implicit solvation model (COSMO), hybrid quantum mechanical / molecular mechanical free energy perturbation (QM/MM-FEP) or a mixed solvation model in which N water molecules were explicitly included in the ab initio description of the reacting system (where N=1-3), with the remainder of the solvent being implicitly modelled as a continuum. Here, both COSMO and QM/MM-FEP reproduce Delta Gobs within an error of about 2kcal/mol. However, we demonstrate that in order to obtain any form of reliable results from a mixed model, it is essential to carefully select the explicit water molecules from short QM/MM runs that act as a model for the true infinite system. Additionally, the mixed models tend to be increasingly inaccurate the more explicit water molecules are placed into the system. Thus, our analysis indicates that this approach provides an unreliable way for modelling phosphate hydrolysis in solution.

Using multilevel modeling to assess case-mix adjusters in consumer experience surveys in health care.

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Damman, Olga C; Stubbe, Janine H; Hendriks, Michelle; Arah, Onyebuchi A; Spreeuwenberg, Peter; Delnoij, Diana M J; Groenewegen, Peter P

2009-04-01

Ratings on the quality of healthcare from the consumer's perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for analyzing healthcare performance data, it has rarely been used to assess case-mix adjustment of such data. The purpose of this article is to investigate whether multilevel regression analysis is a useful tool to detect case-mix adjusters in consumer assessment of healthcare. We used data on 11,539 consumers from 27 Dutch health plans, which were collected using the Dutch Consumer Quality Index health plan instrument. We conducted multilevel regression analyses of consumers' responses nested within health plans to assess the effects of consumer characteristics on consumer experience. We compared our findings to the results of another methodology: the impact factor approach, which combines the predictive effect of each case-mix variable with its heterogeneity across health plans. Both multilevel regression and impact factor analyses showed that age and education were the most important case-mix adjusters for consumer experience and ratings of health plans. With the exception of age, case-mix adjustment had little impact on the ranking of health plans. On both theoretical and practical grounds, multilevel modeling is useful for adequate case-mix adjustment and analysis of performance ratings.

Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening

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Wang, Ke-Sheng; Liu, Xuefeng; Ategbole, Muyiwa; Xie, Xin; Liu, Ying; Xu, Chun; Xie, Changchun; Sha, Zhanxin

2017-09-27

Objective: Screening for colorectal cancer (CRC) can reduce disease incidence, morbidity, and mortality. However, few studies have investigated the urban-rural differences in social and behavioral factors influencing CRC screening. The objective of the study was to investigate the potential factors across urban-rural groups on the usage of CRC screening. Methods: A total of 38,505 adults (aged ≥40 years) were selected from the 2009 California Health Interview Survey (CHIS) data - the latest CHIS data on CRC screening. The weighted generalized linear mixed-model (WGLIMM) was used to deal with this hierarchical structure data. Weighted simple and multiple mixed logistic regression analyses in SAS ver. 9.4 were used to obtain the odds ratios (ORs) and their 95% confidence intervals (CIs). Results: The overall prevalence of CRC screening was 48.1% while the prevalence in four residence groups - urban, second city, suburban, and town/rural, were 45.8%, 46.9%, 53.7% and 50.1%, respectively. The results of WGLIMM analysis showed that there was residence effect (pregression analysis revealed that age, race, marital status, education level, employment stats, binge drinking, and smoking status were associated with CRC screening (p<0.05). Stratified by residence regions, age and poverty level showed associations with CRC screening in all four residence groups. Education level was positively associated with CRC screening in second city and suburban. Infrequent binge drinking was associated with CRC screening in urban and suburban; while current smoking was a protective factor in urban and town/rural groups. Conclusions: Mixed models are useful to deal with the clustered survey data. Social factors and behavioral factors (binge drinking and smoking) were associated with CRC screening and the associations were affected by living areas such as urban and rural regions. Creative Commons Attribution License

The effect of turbulent mixing models on the predictions of subchannel codes

International Nuclear Information System (INIS)

Tapucu, A.; Teyssedou, A.; Tye, P.; Troche, N.

1994-01-01

In this paper, the predictions of the COBRA-IV and ASSERT-4 subchannel codes have been compared with experimental data on void fraction, mass flow rate, and pressure drop obtained for two interconnected subchannels. COBRA-IV is based on a one-dimensional separated flow model with the turbulent intersubchannel mixing formulated as an extension of the single-phase mixing model, i.e. fluctuating equal mass exchange. ASSERT-4 is based on a drift flux model with the turbulent mixing modelled by assuming an exchange of equal volumes with different densities thus allowing a net fluctuating transverse mass flux from one subchannel to the other. This feature is implemented in the constitutive relationship for the relative velocity required by the conservation equations. It is observed that the predictions of ASSERT-4 follow the experimental trends better than COBRA-IV; therefore the approach of equal volume exchange constitutes an improvement over that of the equal mass exchange. ((orig.))

Reliability Estimation of Aero-engine Based on Mixed Weibull Distribution Model

Science.gov (United States)

Yuan, Zhongda; Deng, Junxiang; Wang, Dawei

2018-02-01

Aero-engine is a complex mechanical electronic system, based on analysis of reliability of mechanical electronic system, Weibull distribution model has an irreplaceable role. Till now, only two-parameter Weibull distribution model and three-parameter Weibull distribution are widely used. Due to diversity of engine failure modes, there is a big error with single Weibull distribution model. By contrast, a variety of engine failure modes can be taken into account with mixed Weibull distribution model, so it is a good statistical analysis model. Except the concept of dynamic weight coefficient, in order to make reliability estimation result more accurately, three-parameter correlation coefficient optimization method is applied to enhance Weibull distribution model, thus precision of mixed distribution reliability model is improved greatly. All of these are advantageous to popularize Weibull distribution model in engineering applications.

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

Science.gov (United States)

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.

Using Poisson mixed-effects model to quantify transcript-level gene expression in RNA-Seq.

Science.gov (United States)

Hu, Ming; Zhu, Yu; Taylor, Jeremy M G; Liu, Jun S; Qin, Zhaohui S

2012-01-01

RNA sequencing (RNA-Seq) is a powerful new technology for mapping and quantifying transcriptomes using ultra high-throughput next-generation sequencing technologies. Using deep sequencing, gene expression levels of all transcripts including novel ones can be quantified digitally. Although extremely promising, the massive amounts of data generated by RNA-Seq, substantial biases and uncertainty in short read alignment pose challenges for data analysis. In particular, large base-specific variation and between-base dependence make simple approaches, such as those that use averaging to normalize RNA-Seq data and quantify gene expressions, ineffective. In this study, we propose a Poisson mixed-effects (POME) model to characterize base-level read coverage within each transcript. The underlying expression level is included as a key parameter in this model. Since the proposed model is capable of incorporating base-specific variation as well as between-base dependence that affect read coverage profile throughout the transcript, it can lead to improved quantification of the true underlying expression level. POME can be freely downloaded at http://www.stat.purdue.edu/~yuzhu/pome.html. yuzhu@purdue.edu; zhaohui.qin@emory.edu Supplementary data are available at Bioinformatics online.

An isoeffect approach to the study of combined effects of mixed radiations--the nonparametric analysis of in vivo data

International Nuclear Information System (INIS)

Lam, G.K.

1989-01-01

The combined effects of mixed radiations can be examined using a system of simple isoeffect relations which are derived from a recent analysis of in vitro results obtained for a variety of radiation mixtures. Similar isoeffect analysis methods have been used for over two decades in studies of the combined action of toxic agents such as drugs and antibiotics. Because of the isoeffect approach, the method is particularly useful for the analysis of ordinal data for which conventional models that are based on parametric dose-effect relations may not be suitable. This is illustrated by applying the method to the analysis of a set of recently published in vivo data using the mouse foot skin reaction system for mixtures of neutrons and X rays. The good agreement between this method and the ordinal data also helps to provide further experimental support for the existence of a class of radiobiological data for which the simple isoeffect relations are valid

TRANSP modeling of minority ion sawtooth mixing in ICRF + NBI heated discharges in TFTR

International Nuclear Information System (INIS)

Goldfinger, R.C.; Batchelor, D.B.; Murakami, M.; Phillips, C.K.; Budny, R.; Hammett, G.W.; McCune, D.M.; Wilson, J.R.; Zarnstorff, M.C.

1995-01-01

Time independent code analysis indicates that the sawtooth relaxation phenomenon affects RF power deposition profiles through the mixing of fast ions. Predicted central electron heating rates are substantially above experimental values unless sawtooth relaxation is included. The PPPL time dependent transport analysis code, TRANSP, currently has a model to redistribute thermal electron and ion species, energy densities, plasma current density, and fast ions from neutral beam injection at each sawtooth event using the Kadomtsev (3) prescription. Results are presented here in which the set of models is extended to include sawtooth mixing effects on the hot ion population generated from ICRF heating. The ICRF generated hot ion distribution function, line-integral(ν parallel , ν perpendicular ), which is strongly peaked at the center before each sawtooth, is replaced throughout the sawtooth mixing volume by its volume averaged value at each sawtooth. The modified line-integral(ν parallel ,ν perpendicular ) is then used to recalculate the collisional transfer of power from the minority species to the background species. Results demonstrate that neglect of sawtooth mixing of ICRF-induced fast ions leads to prediction of faster central electron reheat rates than are measured experimentally

Estimate the time varying brain receptor occupancy in PET imaging experiments using non-linear fixed and mixed effect modeling approach

International Nuclear Information System (INIS)

Zamuner, Stefano; Gomeni, Roberto; Bye, Alan

2002-01-01

Positron-Emission Tomography (PET) is an imaging technology currently used in drug development as a non-invasive measure of drug distribution and interaction with biochemical target system. The level of receptor occupancy achieved by a compound can be estimated by comparing time-activity measurements in an experiment done using tracer alone with the activity measured when the tracer is given following administration of unlabelled compound. The effective use of this surrogate marker as an enabling tool for drug development requires the definition of a model linking the brain receptor occupancy with the fluctuation of plasma concentrations. However, the predictive performance of such a model is strongly related to the precision on the estimate of receptor occupancy evaluated in PET scans collected at different times following drug treatment. Several methods have been proposed for the analysis and the quantification of the ligand-receptor interactions investigated from PET data. The aim of the present study is to evaluate alternative parameter estimation strategies based on the use of non-linear mixed effect models allowing to account for intra and inter-subject variability on the time-activity and for covariates potentially explaining this variability. A comparison of the different modeling approaches is presented using real data. The results of this comparison indicates that the mixed effect approach with a primary model partitioning the variance in term of Inter-Individual Variability (IIV) and Inter-Occasion Variability (IOV) and a second stage model relating the changes on binding potential to the dose of unlabelled drug is definitely the preferred approach

Axial displacement of external and internal implant-abutment connection evaluated by linear mixed model analysis.

Science.gov (United States)

Seol, Hyon-Woo; Heo, Seong-Joo; Koak, Jai-Young; Kim, Seong-Kyun; Kim, Shin-Koo

2015-01-01

To analyze the axial displacement of external and internal implant-abutment connection after cyclic loading. Three groups of external abutments (Ext group), an internal tapered one-piece-type abutment (Int-1 group), and an internal tapered two-piece-type abutment (Int-2 group) were prepared. Cyclic loading was applied to implant-abutment assemblies at 150 N with a frequency of 3 Hz. The amount of axial displacement, the Periotest values (PTVs), and the removal torque values(RTVs) were measured. Both a repeated measures analysis of variance and pattern analysis based on the linear mixed model were used for statistical analysis. Scanning electron microscopy (SEM) was used to evaluate the surface of the implant-abutment connection. The mean axial displacements after 1,000,000 cycles were 0.6 μm in the Ext group, 3.7 μm in the Int-1 group, and 9.0 μm in the Int-2 group. Pattern analysis revealed a breakpoint at 171 cycles. The Ext group showed no declining pattern, and the Int-1 group showed no declining pattern after the breakpoint (171 cycles). However, the Int-2 group experienced continuous axial displacement. After cyclic loading, the PTV decreased in the Int-2 group, and the RTV decreased in all groups. SEM imaging revealed surface wear in all groups. Axial displacement and surface wear occurred in all groups. The PTVs remained stable, but the RTVs decreased after cyclic loading. Based on linear mixed model analysis, the Ext and Int-1 groups' axial displacements plateaued after little cyclic loading. The Int-2 group's rate of axial displacement slowed after 100,000 cycles.

Analysis of a PDF model in a mixing layer case

International Nuclear Information System (INIS)

Minier, J.P.; Pozorski, J.

1996-04-01

A recent turbulence model put forward by Pope (1991) in the context of PDF modeling has been applied to a mixing layer case. This model solves the one-point joint velocity-dissipation pdf equation by simulating the instantaneous behaviour of a large number of Lagrangian fluid particles. Closure of the evolution equations of these Lagrangian particles is based on diffusion stochastic processes. The paper reports numerical results and tries to analyse the physical meaning of some variables, in particular the dissipation-weighted kinetic energy and its relation with external intermittency. (authors). 14 refs., 7 figs

Linear mixed-effects models for central statistical monitoring of multicenter clinical trials

OpenAIRE

Desmet, L.; Venet, D.; Doffagne, E.; Timmermans, C.; BURZYKOWSKI, Tomasz; LEGRAND, Catherine; BUYSE, Marc

2014-01-01

Multicenter studies are widely used to meet accrual targets in clinical trials. Clinical data monitoring is required to ensure the quality and validity of the data gathered across centers. One approach to this end is central statistical monitoring, which aims at detecting atypical patterns in the data by means of statistical methods. In this context, we consider the simple case of a continuous variable, and we propose a detection procedure based on a linear mixed-effects model to detect locat...

Perturbative estimates of lepton mixing angles in unified models

International Nuclear Information System (INIS)

Antusch, Stefan; King, Stephen F.; Malinsky, Michal

2009-01-01

Many unified models predict two large neutrino mixing angles, with the charged lepton mixing angles being small and quark-like, and the neutrino masses being hierarchical. Assuming this, we present simple approximate analytic formulae giving the lepton mixing angles in terms of the underlying high energy neutrino mixing angles together with small perturbations due to both charged lepton corrections and renormalisation group (RG) effects, including also the effects of third family canonical normalization (CN). We apply the perturbative formulae to the ubiquitous case of tri-bimaximal neutrino mixing at the unification scale, in order to predict the theoretical corrections to mixing angle predictions and sum rule relations, and give a general discussion of all limiting cases. We also discuss the implications for the sum rule relations of the measurement of a non-zero reactor angle, as hinted at by recent experimental measurements.

Spatial variability in floodplain sedimentation: the use of generalized linear mixed-effects models

Directory of Open Access Journals (Sweden)

A. Cabezas

2010-08-01

Full Text Available Sediment, Total Organic Carbon (TOC and total nitrogen (TN accumulation during one overbank flood (1.15 y return interval were examined at one reach of the Middle Ebro River (NE Spain for elucidating spatial patterns. To achieve this goal, four areas with different geomorphological features and located within the study reach were examined by using artificial grass mats. Within each area, 1 m² study plots consisting of three pseudo-replicates were placed in a semi-regular grid oriented perpendicular to the main channel. TOC, TN and Particle-Size composition of deposited sediments were examined and accumulation rates estimated. Generalized linear mixed-effects models were used to analyze sedimentation patterns in order to handle clustered sampling units, specific-site effects and spatial self-correlation between observations. Our results confirm the importance of channel-floodplain morphology and site micro-topography in explaining sediment, TOC and TN deposition patterns, although the importance of other factors as vegetation pattern should be included in further studies to explain small-scale variability. Generalized linear mixed-effect models provide a good framework to deal with the high spatial heterogeneity of this phenomenon at different spatial scales, and should be further investigated in order to explore its validity when examining the importance of factors such as flood magnitude or suspended sediment concentration.

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

Science.gov (United States)

Rajeswaran, Jeevanantham; Blackstone, Eugene H.

2014-01-01

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

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

Science.gov (United States)

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.

Local Genealogies in a Linear Mixed Model for Genome-wide Association Mapping in Complex Pedigreed Populations

DEFF Research Database (Denmark)

Sahana, Goutam; Mailund, Thomas; Lund, Mogens Sandø

2011-01-01

be extended to incorporate other effects in a straightforward and rigorous fashion. Here, we present a complementary approach, called ‘GENMIX (genealogy based mixed model)’ which combines advantages from two powerful GWAS methods: genealogy-based haplotype grouping and MMA. Subjects and Methods: We validated......Introduction: The state-of-the-art for dealing with multiple levels of relationship among the samples in genome-wide association studies (GWAS) is unified mixed model analysis (MMA). This approach is very flexible, can be applied to both family-based and population-based samples, and can...

Cell size spatial convergence analysis on GOTHIC distributed parameter models for studying hydrogen mixing behaviour in CANDU containments

International Nuclear Information System (INIS)

Yim, K.; Wong, R.C.

1995-01-01

Gas mixing phenomena can be modelled using distributed parameter codes such as GOTHIC, but the selection of the optimum cell size is an important user input. The tradeoff between accuracy and practical computation times affect the choice of cell sizes, where small cells provide better accuracy at the expense of longer computing time. A study on cell size effect on hydrogen distribution is presented for the problem of hydrogen mixing behaviour in a typical CANDU reactor containment following a severe reactor accident. Optimal cell sizes were found for different room volumes, hydrogen release profiles and elevations using spatial convergence criteria. The findings of this study provide the technical basis for the cell size selection in the GOTHIC distributed parameter models used for analysing hydrogen mixing behaviour. (author). 1 ref., 1 tab., 13 figs

A mixed model framework for teratology studies.

Science.gov (United States)

Braeken, Johan; Tuerlinckx, Francis

2009-10-01

A mixed model framework is presented to model the characteristic multivariate binary anomaly data as provided in some teratology studies. The key features of the model are the incorporation of covariate effects, a flexible random effects distribution by means of a finite mixture, and the application of copula functions to better account for the relation structure of the anomalies. The framework is motivated by data of the Boston Anticonvulsant Teratogenesis study and offers an integrated approach to investigate substantive questions, concerning general and anomaly-specific exposure effects of covariates, interrelations between anomalies, and objective diagnostic measurement.

Ill-posedness in modeling mixed sediment river morphodynamics

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Chavarrías, Víctor; Stecca, Guglielmo; Blom, Astrid

2018-04-01

In this paper we analyze the Hirano active layer model used in mixed sediment river morphodynamics concerning its ill-posedness. Ill-posedness causes the solution to be unstable to short-wave perturbations. This implies that the solution presents spurious oscillations, the amplitude of which depends on the domain discretization. Ill-posedness not only produces physically unrealistic results but may also cause failure of numerical simulations. By considering a two-fraction sediment mixture we obtain analytical expressions for the mathematical characterization of the model. Using these we show that the ill-posed domain is larger than what was found in previous analyses, not only comprising cases of bed degradation into a substrate finer than the active layer but also in aggradational cases. Furthermore, by analyzing a three-fraction model we observe ill-posedness under conditions of bed degradation into a coarse substrate. We observe that oscillations in the numerical solution of ill-posed simulations grow until the model becomes well-posed, as the spurious mixing of the active layer sediment and substrate sediment acts as a regularization mechanism. Finally we conduct an eigenstructure analysis of a simplified vertically continuous model for mixed sediment for which we show that ill-posedness occurs in a wider range of conditions than the active layer model.

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

Science.gov (United States)

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.

Study on mixed analysis method for fatigue analysis of oblique safety injection nozzle on main piping

International Nuclear Information System (INIS)

Lu Xifeng; Zhang Yixiong; Ai Honglei; Wang Xinjun; He Feng

2014-01-01

The simplified analysis method and the detailed analysis method were used for the fatigue analysis of the nozzle on the main piping. Because the structure of the oblique safety injection nozzle is complex and some more severe transients are subjected. The results obtained are more penalized and cannot be validate when the simplified analysis method used for the fatigue analysis. It will be little conservative when the detailed analysis method used, but it is more complex and time-consuming and boring labor. To reduce the conservatism and save time, the mixed analysis method which combining the simplified analysis method with the detailed analysis method is used for the fatigue analysis. The heat transfer parameters between the fluid and the structure which used for analysis were obtained by heat transfer property experiment. The results show that the mixed analysis which heat transfer property is considered can reduce the conservatism effectively, and the mixed analysis method is a more effective and practical method used for the fatigue analysis of the oblique safety injection nozzle. (authors)

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

Science.gov (United States)

Han, Lide; Yang, Jian; Zhu, Jun

2007-06-01

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

Analysis of the type II robotic mixed-model assembly line balancing problem

Science.gov (United States)

Çil, Zeynel Abidin; Mete, Süleyman; Ağpak, Kürşad

2017-06-01

In recent years, there has been an increasing trend towards using robots in production systems. Robots are used in different areas such as packaging, transportation, loading/unloading and especially assembly lines. One important step in taking advantage of robots on the assembly line is considering them while balancing the line. On the other hand, market conditions have increased the importance of mixed-model assembly lines. Therefore, in this article, the robotic mixed-model assembly line balancing problem is studied. The aim of this study is to develop a new efficient heuristic algorithm based on beam search in order to minimize the sum of cycle times over all models. In addition, mathematical models of the problem are presented for comparison. The proposed heuristic is tested on benchmark problems and compared with the optimal solutions. The results show that the algorithm is very competitive and is a promising tool for further research.

Energy mix and employment effects

International Nuclear Information System (INIS)

Wodopia, F.J.

2005-01-01

''Energy Mix and Employment Effects'' is a subject not to be reduced to the so-called ''job argument''. It also involves the question whether it will be possible to achieve consensus again about the composition of a balanced sustainable energy mix. This term must not be interpreted in a static sense; after all, the framework conditions of energy policy are changing. However, this must not render energy policy unsteady. This requirement should be imposed on economic policy in general, i.e. political interventions, it they are really unavoidable, must be predictable on a long term. This contribution also examines the meaning of the term ''energy mix.'' Aspects of the debate about the climate, especially potential factors influencing the climate, are discussed against the backdrop of scientific validity. Other key points covered are the description and analysis of the energy policy framework. One major aspect under study are all kinds of ''subsidies'' of energy resources and the consequences to the whole economy arising from these financial support mechanisms. The findings are projected onto the employment effects. Finally, the question is raised how to design an energy mix sustainable for the future, and how to achieve it politically and in society. (orig.)

Associating Crash Avoidance Maneuvers with Driver Attributes and Accident Characteristics: A Mixed Logit Model Approach

DEFF Research Database (Denmark)

Kaplan, Sigal; Prato, Carlo Giacomo

2012-01-01

as from the key role of the ability of drivers to perform effective corrective maneuvers for the success of automated in-vehicle warning and driver assistance systems. The analysis is conducted by means of a mixed logit model that accommodates correlations across alternatives and heteroscedasticity. Data...

Dispersion analysis of the Pn -Pn-1DG mixed finite element pair for atmospheric modelling

Science.gov (United States)

Melvin, Thomas

2018-02-01

Mixed finite element methods provide a generalisation of staggered grid finite difference methods with a framework to extend the method to high orders. The ability to generate a high order method is appealing for applications on the kind of quasi-uniform grids that are popular for atmospheric modelling, so that the method retains an acceptable level of accuracy even around special points in the grid. The dispersion properties of such schemes are important to study as they provide insight into the numerical adjustment to imbalance that is an important component in atmospheric modelling. This paper extends the recent analysis of the P2 - P1DG pair, that is a quadratic continuous and linear discontinuous finite element pair, to higher polynomial orders and also spectral element type pairs. In common with the previously studied element pair, and also with other schemes such as the spectral element and discontinuous Galerkin methods, increasing the polynomial order is found to provide a more accurate dispersion relation for the well resolved part of the spectrum but at the cost of a number of unphysical spectral gaps. The effects of these spectral gaps are investigated and shown to have a varying impact depending upon the width of the gap. Finally, the tensor product nature of the finite element spaces is exploited to extend the dispersion analysis into two-dimensions.

Analysis of 24-Hour Ambulatory Blood Pressure Monitoring Data using Orthonormal Polynomials in the Linear Mixed Model

OpenAIRE

Edwards, Lloyd J.; Simpson, Sean L.

2010-01-01

The use of 24-hour ambulatory blood pressure monitoring (ABPM) in clinical practice and observational epidemiological studies has grown considerably in the past 25 years. ABPM is a very effective technique for assessing biological, environmental, and drug effects on blood pressure. In order to enhance the effectiveness of ABPM for clinical and observational research studies via analytical and graphical results, developing alternative data analysis approaches are important. The linear mixed mo...

Fitting and Calibrating a Multilevel Mixed-Effects Stem Taper Model for Maritime Pine in NW Spain

Science.gov (United States)

Arias-Rodil, Manuel; Castedo-Dorado, Fernando; Cámara-Obregón, Asunción; Diéguez-Aranda, Ulises

2015-01-01

Stem taper data are usually hierarchical (several measurements per tree, and several trees per plot), making application of a multilevel mixed-effects modelling approach essential. However, correlation between trees in the same plot/stand has often been ignored in previous studies. Fitting and calibration of a variable-exponent stem taper function were conducted using data from 420 trees felled in even-aged maritime pine (Pinus pinaster Ait.) stands in NW Spain. In the fitting step, the tree level explained much more variability than the plot level, and therefore calibration at plot level was omitted. Several stem heights were evaluated for measurement of the additional diameter needed for calibration at tree level. Calibration with an additional diameter measured at between 40 and 60% of total tree height showed the greatest improvement in volume and diameter predictions. If additional diameter measurement is not available, the fixed-effects model fitted by the ordinary least squares technique should be used. Finally, we also evaluated how the expansion of parameters with random effects affects the stem taper prediction, as we consider this a key question when applying the mixed-effects modelling approach to taper equations. The results showed that correlation between random effects should be taken into account when assessing the influence of random effects in stem taper prediction. PMID:26630156

Mixing with applications to inertial-confinement-fusion implosions

Science.gov (United States)

Rana, V.; Lim, H.; Melvin, J.; Glimm, J.; Cheng, B.; Sharp, D. H.

2017-01-01

Approximate one-dimensional (1D) as well as 2D and 3D simulations are playing an important supporting role in the design and analysis of future experiments at National Ignition Facility. This paper is mainly concerned with 1D simulations, used extensively in design and optimization. We couple a 1D buoyancy-drag mix model for the mixing zone edges with a 1D inertial confinement fusion simulation code. This analysis predicts that National Ignition Campaign (NIC) designs are located close to a performance cliff, so modeling errors, design features (fill tube and tent) and additional, unmodeled instabilities could lead to significant levels of mix. The performance cliff we identify is associated with multimode plastic ablator (CH) mix into the hot-spot deuterium and tritium (DT). The buoyancy-drag mix model is mode number independent and selects implicitly a range of maximum growth modes. Our main conclusion is that single effect instabilities are predicted not to lead to hot-spot mix, while combined mode mixing effects are predicted to affect hot-spot thermodynamics and possibly hot-spot mix. Combined with the stagnation Rayleigh-Taylor instability, we find the potential for mix effects in combination with the ice-to-gas DT boundary, numerical effects of Eulerian species CH concentration diffusion, and ablation-driven instabilities. With the help of a convenient package of plasma transport parameters developed here, we give an approximate determination of these quantities in the regime relevant to the NIC experiments, while ruling out a variety of mix possibilities. Plasma transport parameters affect the 1D buoyancy-drag mix model primarily through its phenomenological drag coefficient as well as the 1D hydro model to which the buoyancy-drag equation is coupled.

Inference of ICF Implosion Core Mix using Experimental Data and Theoretical Mix Modeling

International Nuclear Information System (INIS)

Welser-Sherrill, L.; Haynes, D.A.; Mancini, R.C.; Cooley, J.H.; Tommasini, R.; Golovkin, I.E.; Sherrill, M.E.; Haan, S.W.

2009-01-01

The mixing between fuel and shell materials in Inertial Confinement Fusion (ICF) implosion cores is a current topic of interest. The goal of this work was to design direct-drive ICF experiments which have varying levels of mix, and subsequently to extract information on mixing directly from the experimental data using spectroscopic techniques. The experimental design was accomplished using hydrodynamic simulations in conjunction with Haan's saturation model, which was used to predict the mix levels of candidate experimental configurations. These theoretical predictions were then compared to the mixing information which was extracted from the experimental data, and it was found that Haan's mix model performed well in predicting trends in the width of the mix layer. With these results, we have contributed to an assessment of the range of validity and predictive capability of the Haan saturation model, as well as increased our confidence in the methods used to extract mixing information from experimental data.

Theoretical Models of Neutrino Mixing Recent Developments

CERN Document Server

Altarelli, Guido

2009-01-01

The data on neutrino mixing are at present compatible with Tri-Bimaximal (TB) mixing. If one takes this indication seriously then the models that lead to TB mixing in first approximation are particularly interesting and A4 models are prominent in this list. However, the agreement of TB mixing with the data could still be an accident. We discuss a recent model based on S4 where Bimaximal mixing is instead valid at leading order and the large corrections needed to reproduce the data arise from the diagonalization of charged leptons. The value of $\\theta_{13}$ could distinguish between the two alternatives.

CFD simulation for thermal mixing of a SMART flow mixing header assembly

International Nuclear Information System (INIS)

Kim, Young In; Bae, Youngmin; Chung, Young Jong; Kim, Keung Koo

2015-01-01

Highlights: • Thermal mixing performance of a FMHA installed in SMART is investigated numerically. • Effects of operating condition and discharge hole configuration are examined. • FMHA performance satisfies the design requirements under various abnormal conditions. - Abstract: A flow mixing header assembly (FMHA) is installed in a system-integrated modular advanced reactor (SMART) to enhance the thermal mixing capability and create a uniform core flow distribution under both normal operation and accident conditions. In this study, the thermal mixing characteristics of the FMHA are investigated for various steam generator conditions using a commercial CFD code. Simulations include investigations for the effects of FMHA discharge flow rate differences, turbulence models, and steam generator conditions. The results of the analysis show that the FMHA works effectively for thermal mixing in various conditions and makes the temperature difference at the core inlet decrease noticeably. We verified that the mixing capability of the FMHA is excellent and satisfies the design requirement in all simulation cases tested here

Inflow, Outflow, Yields, and Stellar Population Mixing in Chemical Evolution Models

Energy Technology Data Exchange (ETDEWEB)

Andrews, Brett H. [PITT PACC, Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15260 (United States); Weinberg, David H.; Schönrich, Ralph; Johnson, Jennifer A., E-mail: andrewsb@pitt.edu [Department of Astronomy, The Ohio State University, 140 West 18th Avenue, Columbus, OH 43210 (United States)

2017-02-01

Chemical evolution models are powerful tools for interpreting stellar abundance surveys and understanding galaxy evolution. However, their predictions depend heavily on the treatment of inflow, outflow, star formation efficiency (SFE), the stellar initial mass function, the SN Ia delay time distribution, stellar yields, and stellar population mixing. Using flexCE, a flexible one-zone chemical evolution code, we investigate the effects of and trade-offs between parameters. Two critical parameters are SFE and the outflow mass-loading parameter, which shift the knee in [O/Fe]–[Fe/H] and the equilibrium abundances that the simulations asymptotically approach, respectively. One-zone models with simple star formation histories follow narrow tracks in [O/Fe]–[Fe/H] unlike the observed bimodality (separate high- α and low- α sequences) in this plane. A mix of one-zone models with inflow timescale and outflow mass-loading parameter variations, motivated by the inside-out galaxy formation scenario with radial mixing, reproduces the two sequences better than a one-zone model with two infall epochs. We present [X/Fe]–[Fe/H] tracks for 20 elements assuming three different supernova yield models and find some significant discrepancies with solar neighborhood observations, especially for elements with strongly metallicity-dependent yields. We apply principal component abundance analysis to the simulations and existing data to reveal the main correlations among abundances and quantify their contributions to variation in abundance space. For the stellar population mixing scenario, the abundances of α -elements and elements with metallicity-dependent yields dominate the first and second principal components, respectively, and collectively explain 99% of the variance in the model. flexCE is a python package available at https://github.com/bretthandrews/flexCE.

Inflow, Outflow, Yields, and Stellar Population Mixing in Chemical Evolution Models

International Nuclear Information System (INIS)

Andrews, Brett H.; Weinberg, David H.; Schönrich, Ralph; Johnson, Jennifer A.

2017-01-01

Chemical evolution models are powerful tools for interpreting stellar abundance surveys and understanding galaxy evolution. However, their predictions depend heavily on the treatment of inflow, outflow, star formation efficiency (SFE), the stellar initial mass function, the SN Ia delay time distribution, stellar yields, and stellar population mixing. Using flexCE, a flexible one-zone chemical evolution code, we investigate the effects of and trade-offs between parameters. Two critical parameters are SFE and the outflow mass-loading parameter, which shift the knee in [O/Fe]–[Fe/H] and the equilibrium abundances that the simulations asymptotically approach, respectively. One-zone models with simple star formation histories follow narrow tracks in [O/Fe]–[Fe/H] unlike the observed bimodality (separate high- α and low- α sequences) in this plane. A mix of one-zone models with inflow timescale and outflow mass-loading parameter variations, motivated by the inside-out galaxy formation scenario with radial mixing, reproduces the two sequences better than a one-zone model with two infall epochs. We present [X/Fe]–[Fe/H] tracks for 20 elements assuming three different supernova yield models and find some significant discrepancies with solar neighborhood observations, especially for elements with strongly metallicity-dependent yields. We apply principal component abundance analysis to the simulations and existing data to reveal the main correlations among abundances and quantify their contributions to variation in abundance space. For the stellar population mixing scenario, the abundances of α -elements and elements with metallicity-dependent yields dominate the first and second principal components, respectively, and collectively explain 99% of the variance in the model. flexCE is a python package available at https://github.com/bretthandrews/flexCE.

Mixed models for data from thorough QT studies: part 2. One-step assessment of conditional QT prolongation.

Science.gov (United States)

Schall, Robert

2011-01-01

We investigate mixed analysis of covariance models for the 'one-step' assessment of conditional QT prolongation. Initially, we consider three different covariance structures for the data, where between-treatment covariance of repeated measures is modelled respectively through random effects, random coefficients, and through a combination of random effects and random coefficients. In all three of those models, an unstructured covariance pattern is used to model within-treatment covariance. In a fourth model, proposed earlier in the literature, between-treatment covariance is modelled through random coefficients but the residuals are assumed to be independent identically distributed (i.i.d.). Finally, we consider a mixed model with saturated covariance structure. We investigate the precision and robustness of those models by fitting them to a large group of real data sets from thorough QT studies. Our findings suggest: (i) Point estimates of treatment contrasts from all five models are similar. (ii) The random coefficients model with i.i.d. residuals is not robust; the model potentially leads to both under- and overestimation of standard errors of treatment contrasts and therefore cannot be recommended for the analysis of conditional QT prolongation. (iii) The combined random effects/random coefficients model does not always converge; in the cases where it converges, its precision is generally inferior to the other models considered. (iv) Both the random effects and the random coefficients model are robust. (v) The random effects, the random coefficients, and the saturated model have similar precision and all three models are suitable for the one-step assessment of conditional QT prolongation. Copyright © 2010 John Wiley & Sons, Ltd.

CFD Analysis of a Slug Mixing Experiment Conducted on a VVER-1000 Model

Directory of Open Access Journals (Sweden)

F. Moretti

2009-01-01

Full Text Available A commercial CFD code was applied, for validation purposes, to the simulation of a slug mixing experiment carried out at OKB “Gidropress” scaled facility in the framework of EC TACIS project R2.02/02: “Development of safety analysis capabilities for VVER-1000 transients involving spatial variations of coolant properties (temperature or boron concentration at core inlet.” Such experimental model reproduces a VVER-1000 nuclear reactor and is aimed at investigating the in-vessel mixing phenomena. The addressed experiment involves the start-up of one of the four reactor coolant pumps (the other three remaining idle, and the presence of a tracer slug on the starting loop, which is thus transported to the reactor pressure vessel where it mixes with the clear water. Such conditions may occur in a boron dilution scenario, hence the relevance of the addressed phenomena for nuclear reactor safety. Both a pretest and a posttest CFD simulations of the mentioned experiment were performed, which differ in the definition of the boundary conditions (based either on nominal quantities or on measured quantities, resp.. The numerical results are qualitatively and quantitatively analyzed and compared against the measured data in terms of space and time tracer distribution at the core inlet. The improvement of the results due to the optimization of the boundary conditions is evidenced, and a quantification of the simulation accuracy is proposed.

Mixed-Effects Modeling of Neurofeedback Self-Regulation Performance: Moderators for Learning in Children with ADHD.

Science.gov (United States)

Zuberer, Agnieszka; Minder, Franziska; Brandeis, Daniel; Drechsler, Renate

2018-01-01

Neurofeedback (NF) has gained increasing popularity as a training method for children and adults with attention deficit hyperactivity disorder (ADHD). However, it is unclear to what extent children learn to regulate their brain activity and in what way NF learning may be affected by subject- and treatment-related factors. In total, 48 subjects with ADHD (age 8.5-16.5 years; 16 subjects on methylphenidate (MPH)) underwent 15 double training sessions of NF in either a clinical or a school setting. Four mixed-effects models were employed to analyze learning: training within-sessions, across-sessions, with continuous feedback, and with transfer in which performance feedback is delayed. Age and MPH affected the NF performance in all models. Cross-session learning in the feedback condition was mainly moderated by age and MPH, whereas NF learning in the transfer condition was mainly boosted by MPH. Apart from IQ and task types, other subject-related or treatment-related effects were unrelated to NF learning. This first study analyzing moderators of NF learning in ADHD with a mixed-effects modeling approach shows that NF performance is moderated differentially by effects of age and MPH depending on the training task and time window. Future studies may benefit from using this approach to analyze NF learning and NF specificity. The trial name Neurofeedback and Computerized Cognitive Training in Different Settings for Children and Adolescents With ADHD is registered with NCT02358941.

Latent Fundamentals Arbitrage with a Mixed Effects Factor Model

Directory of Open Access Journals (Sweden)

Andrei Salem Gonçalves

2012-09-01

Full Text Available We propose a single-factor mixed effects panel data model to create an arbitrage portfolio that identifies differences in firm-level latent fundamentals. Furthermore, we show that even though the characteristics that affect returns are unknown variables, it is possible to identify the strength of the combination of these latent fundamentals for each stock by following a simple approach using historical data. As a result, a trading strategy that bought the stocks with the best fundamentals (strong fundamentals portfolio and sold the stocks with the worst ones (weak fundamentals portfolio realized significant risk-adjusted returns in the U.S. market for the period between July 1986 and June 2008. To ensure robustness, we performed sub period and seasonal analyses and adjusted for trading costs and we found further empirical evidence that using a simple investment rule, that identified these latent fundamentals from the structure of past returns, can lead to profit.

Handbook of mixed membership models and their applications

CERN Document Server

Airoldi, Edoardo M; Erosheva, Elena A; Fienberg, Stephen E

2014-01-01

In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology.Through examples using real data sets, yo

MARKETING MIX ANALYSIS OF NATURAL TOURISM AREA 'KAWAH PUTIH’ AND ITS EFFECT ON VISITORS’ DECISION

Directory of Open Access Journals (Sweden)

Isyana Rahayu

2015-05-01

Full Text Available Kawah Putih is one of the leading tourist places in Bandung which has significantly contributed to the revenue of travel business division in the Forestry Housing as the manager. The revenue obtained depends on the marketing mix strategy conducted by the management because the marketing mix is the elements which become a consideration basis when making marketing communication strategy services in order to understand the demands of tourists. Therefore, the objectives of this study were to obtain and understand information and analyze the visitors’ responses on the natural tourism area related to the marketing mix that has been implemented by the management. The dependent variables included the elements of marketing mix, that involves 7P – product, price, place, promotion, people, procees and physical evidence, while the independent variable included the visitors’ decision. From the validity and tests, it is revealed that the overall regression model bring effects or at least there is one variable of the marketing mix factors that influences the decision of the visitors. From the data analysis, it is found that the process variables and physical appearance do not significantly affect the decision of the visitors. The other variables. that involve variables of product, price, place, promotion, and human have significantly influence the visitors’ decision.Keywords: Marketing mix, Kawah Putih, decision of visitors, touristsABSTRAKKawah Putih merupakan salah satu wisata unggulan Kota Bandung dan telah berkontribusi cukup signifikan untuk pendapatan divisi bisnis wisata Perum Perhutani. Pendapatan yang diperoleh tergantung dari strategi bauran pemasaran yang dilakukan oleh pengelola karena pada bauran pemasaran terdapat unsur atau elemen yang menjadi dasar pertimbangan pembuatan strategi komunikasi pemasaran jasa dalam rangka untuk memahami tuntutan dari wisatawan. Tujuan penelitian ini adalah memperoleh informasi, memahami dan menganalisis

Modelling mixed forest growth : a review of models for forest management

NARCIS (Netherlands)

Porte, A.; Bartelink, H.H.

2002-01-01

Most forests today are multi-specific and heterogeneous forests (`mixed forests'). However, forest modelling has been focusing on mono-specific stands for a long time, only recently have models been developed for mixed forests. Previous reviews of mixed forest modelling were restricted to certain

Bs0–B-bars0 mixing within minimal flavor-violating two-Higgs-doublet models

International Nuclear Information System (INIS)

Chang, Qin; Li, Pei-Fu; Li, Xin-Qiang

2015-01-01

In the “Higgs basis” for a generic 2HDM, only one scalar doublet gets a nonzero vacuum expectation value and, under the criterion of minimal flavor violation, the other one is fixed to be either color-singlet or color-octet, which are named as the type-III and type-C models, respectively. In this paper, the charged-Higgs effects of these two models on B s 0 –B -bar s 0 mixing are studied. First of all, we perform a complete one-loop computation of the electro-weak corrections to the amplitudes of B s 0 –B -bar s 0 mixing. Together with the up-to-date experimental measurements, a detailed phenomenological analysis is then performed in the cases of both real and complex Yukawa couplings of charged scalars to quarks. The spaces of model parameters allowed by the current experimental data on B s 0 –B -bar s 0 mixing are obtained and the differences between type-III and type-C models are investigated, which is helpful to distinguish between these two models

Modelling rainfall amounts using mixed-gamma model for Kuantan district

Science.gov (United States)

Zakaria, Roslinazairimah; Moslim, Nor Hafizah

2017-05-01

An efficient design of flood mitigation and construction of crop growth models depend upon good understanding of the rainfall process and characteristics. Gamma distribution is usually used to model nonzero rainfall amounts. In this study, the mixed-gamma model is applied to accommodate both zero and nonzero rainfall amounts. The mixed-gamma model presented is for the independent case. The formulae of mean and variance are derived for the sum of two and three independent mixed-gamma variables, respectively. Firstly, the gamma distribution is used to model the nonzero rainfall amounts and the parameters of the distribution (shape and scale) are estimated using the maximum likelihood estimation method. Then, the mixed-gamma model is defined for both zero and nonzero rainfall amounts simultaneously. The formulae of mean and variance for the sum of two and three independent mixed-gamma variables derived are tested using the monthly rainfall amounts from rainfall stations within Kuantan district in Pahang Malaysia. Based on the Kolmogorov-Smirnov goodness of fit test, the results demonstrate that the descriptive statistics of the observed sum of rainfall amounts is not significantly different at 5% significance level from the generated sum of independent mixed-gamma variables. The methodology and formulae demonstrated can be applied to find the sum of more than three independent mixed-gamma variables.

Spatial generalised linear mixed models based on distances.

Science.gov (United States)

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.

Mixed Hitting-Time Models

NARCIS (Netherlands)

Abbring, J.H.

2009-01-01

We study mixed hitting-time models, which specify durations as the first time a Levy process (a continuous-time process with stationary and independent increments) crosses a heterogeneous threshold. Such models of substantial interest because they can be reduced from optimal-stopping models with

Mixed Finite Element Simulation with Stability Analysis for Gas Transport in Low-Permeability Reservoirs

Directory of Open Access Journals (Sweden)

Mohamed F. El-Amin

2018-01-01

Full Text Available Natural gas exists in considerable quantities in tight reservoirs. Tight formations are rocks with very tiny or poorly connected pors that make flow through them very difficult, i.e., the permeability is very low. The mixed finite element method (MFEM, which is locally conservative, is suitable to simulate the flow in porous media. This paper is devoted to developing a mixed finite element (MFE technique to simulate the gas transport in low permeability reservoirs. The mathematical model, which describes gas transport in low permeability formations, contains slippage effect, as well as adsorption and diffusion mechanisms. The apparent permeability is employed to represent the slippage effect in low-permeability formations. The gas adsorption on the pore surface has been described by Langmuir isotherm model, while the Peng-Robinson equation of state is used in the thermodynamic calculations. Important compatibility conditions must hold to guarantee the stability of the mixed method by adding additional constraints to the numerical discretization. The stability conditions of the MFE scheme has been provided. A theorem and three lemmas on the stability analysis of the mixed finite element method (MFEM have been established and proven. A semi-implicit scheme is developed to solve the governing equations. Numerical experiments are carried out under various values of the physical parameters.

Generalized linear longitudinal mixed models with linear covariance structure and multiplicative random effects

DEFF Research Database (Denmark)

Holst, René; Jørgensen, Bent

2015-01-01

The paper proposes a versatile class of multiplicative generalized linear longitudinal mixed models (GLLMM) with additive dispersion components, based on explicit modelling of the covariance structure. The class incorporates a longitudinal structure into the random effects models and retains...... a marginal as well as a conditional interpretation. The estimation procedure is based on a computationally efficient quasi-score method for the regression parameters combined with a REML-like bias-corrected Pearson estimating function for the dispersion and correlation parameters. This avoids...... the multidimensional integral of the conventional GLMM likelihood and allows an extension of the robust empirical sandwich estimator for use with both association and regression parameters. The method is applied to a set of otholit data, used for age determination of fish....

Visualizing the flow of evidence in network meta-analysis and characterizing mixed treatment comparisons.

Science.gov (United States)

König, Jochem; Krahn, Ulrike; Binder, Harald

2013-12-30

Network meta-analysis techniques allow for pooling evidence from different studies with only partially overlapping designs for getting a broader basis for decision support. The results are network-based effect estimates that take indirect evidence into account for all pairs of treatments. The results critically depend on homogeneity and consistency assumptions, which are sometimes difficult to investigate. To support such evaluation, we propose a display of the flow of evidence and introduce new measures that characterize the structure of a mixed treatment comparison. Specifically, a linear fixed effects model for network meta-analysis is considered, where the network estimates for two treatments are linear combinations of direct effect estimates comparing these or other treatments. The linear coefficients can be seen as the generalization of weights known from classical meta-analysis. We summarize properties of these coefficients and display them as a weighted directed acyclic graph, representing the flow of evidence. Furthermore, measures are introduced that quantify the direct evidence proportion, the mean path length, and the minimal parallelism of mixed treatment comparisons. The graphical display and the measures are illustrated for two published network meta-analyses. In these applications, the proposed methods are seen to render transparent the process of data pooling in mixed treatment comparisons. They can be expected to be more generally useful for guiding and facilitating the validity assessment in network meta-analysis. Copyright © 2013 John Wiley & Sons, Ltd.

Analytical model for transient fluid mixing in upper outlet plenum of an LMFBR

International Nuclear Information System (INIS)

Yang, J.W.; Agrawal, A.K.

1976-01-01

A two-zone mixing model based on the lumped-parameter approach was developed for the analysis of transient thermal response in the outlet plenum of an LMFBR. The maximum penetration of core flow is used as the criterion for dividing the sodium region into two mixing zones. The model considers the transient sodium temperature affected by the thermal expansion of sodium, heat transfer with cover gas, heat capacity of different sections of metal and the addition of by-pass flow into the plenum. The results of numerical calculations indicate that effects of flow stratification, chimney height, metal heat capacity and by-pass flow are important for transient sodium temperature calculation. Thermal expansion of sodium and heat transfer with the cover gas do not play any significant role on sodium temperature

Groundwater Mixing Process Identification in Deep Mines Based on Hydrogeochemical Property Analysis

Directory of Open Access Journals (Sweden)

Bo Liu

2016-12-01

Full Text Available Karst collapse columns, as a potential water passageway for mine water inrush, are always considered a critical problem for the development of deep mining techniques. This study aims to identify the mixing process of groundwater deriving two different limestone karst-fissure aquifer systems. Based on analysis of mining groundwater hydrogeochemical properties, hydraulic connection between the karst-fissure objective aquifer systems was revealed. In this paper, piper diagram was used to calculate the mixing ratios at different sampling points in the aquifer systems, and PHREEQC Interactive model (Version 2.5, USGS, Reston, VA, USA, 2001 was applied to modify the mixing ratios and model the water–rock interactions during the mixing processes. The analysis results show that the highest mixing ratio is 0.905 in the C12 borehole that is located nearest to the #2 karst collapse column, and the mixing ratio decreases with the increase of the distance from the #2 karst collapse column. It demonstrated that groundwater of the two aquifers mixed through the passage of #2 karst collapse column. As a result, the proposed Piper-PHREEQC based method can provide accurate identification of karst collapse columns’ water conductivity, and can be applied to practical applications.

Modeling Individual Differences in Within-Person Variation of Negative and Positive Affect in a Mixed Effects Location Scale Model Using BUGS/JAGS

Science.gov (United States)

Rast, Philippe; Hofer, Scott M.; Sparks, Catharine

2012-01-01

A mixed effects location scale model was used to model and explain individual differences in within-person variability of negative and positive affect across 7 days (N=178) within a measurement burst design. The data come from undergraduate university students and are pooled from a study that was repeated at two consecutive years. Individual…

Software engineering the mixed model for genome-wide association studies on large samples.

Science.gov (United States)

Zhang, Zhiwu; Buckler, Edward S; Casstevens, Terry M; Bradbury, Peter J

2009-11-01

Mixed models improve the ability to detect phenotype-genotype associations in the presence of population stratification and multiple levels of relatedness in genome-wide association studies (GWAS), but for large data sets the resource consumption becomes impractical. At the same time, the sample size and number of markers used for GWAS is increasing dramatically, resulting in greater statistical power to detect those associations. The use of mixed models with increasingly large data sets depends on the availability of software for analyzing those models. While multiple software packages implement the mixed model method, no single package provides the best combination of fast computation, ability to handle large samples, flexible modeling and ease of use. Key elements of association analysis with mixed models are reviewed, including modeling phenotype-genotype associations using mixed models, population stratification, kinship and its estimation, variance component estimation, use of best linear unbiased predictors or residuals in place of raw phenotype, improving efficiency and software-user interaction. The available software packages are evaluated, and suggestions made for future software development.

COMBINING SOURCES IN STABLE ISOTOPE MIXING MODELS: ALTERNATIVE METHODS

Science.gov (United States)

Stable isotope mixing models are often used to quantify source contributions to a mixture. Examples include pollution source identification; trophic web studies; analysis of water sources for soils, plants, or water bodies; and many others. A common problem is having too many s...

Population stochastic modelling (PSM)-An R package for mixed-effects models based on stochastic differential equations

DEFF Research Database (Denmark)

Klim, Søren; Mortensen, Stig Bousgaard; Kristensen, Niels Rode

2009-01-01

are often partly ignored in PK/PD modelling although violating the hypothesis for many standard statistical tests. This article presents a package for the statistical program R that is able to handle SDEs in a mixed-effects setting. The estimation method implemented is the FOCE1 approximation......The extension from ordinary to stochastic differential equations (SDEs) in pharmacokinetic and pharmacodynamic (PK/PD) modelling is an emerging field and has been motivated in a number of articles [N.R. Kristensen, H. Madsen, S.H. Ingwersen, Using stochastic differential equations for PK/PD model...... development, J. Pharmacokinet. Pharmacodyn. 32 (February(l)) (2005) 109-141; C.W. Tornoe, R.V Overgaard, H. Agerso, H.A. Nielsen, H. Madsen, E.N. Jonsson, Stochastic differential equations in NONMEM: implementation, application, and comparison with ordinary differential equations, Pharm. Res. 22 (August(8...

Analysis of correlated count data using generalised linear mixed models exemplified by field data on aggressive behaviour of boars

Directory of Open Access Journals (Sweden)

N. Mielenz

2015-01-01

Full Text Available Population-averaged and subject-specific models are available to evaluate count data when repeated observations per subject are present. The latter are also known in the literature as generalised linear mixed models (GLMM. In GLMM repeated measures are taken into account explicitly through random animal effects in the linear predictor. In this paper the relevant GLMMs are presented based on conditional Poisson or negative binomial distribution of the response variable for given random animal effects. Equations for the repeatability of count data are derived assuming normal distribution and logarithmic gamma distribution for the random animal effects. Using count data on aggressive behaviour events of pigs (barrows, sows and boars in mixed-sex housing, we demonstrate the use of the Poisson »log-gamma intercept«, the Poisson »normal intercept« and the »normal intercept« model with negative binomial distribution. Since not all count data can definitely be seen as Poisson or negative-binomially distributed, questions of model selection and model checking are examined. Emanating from the example, we also interpret the least squares means, estimated on the link as well as the response scale. Options provided by the SAS procedure NLMIXED for estimating model parameters and for estimating marginal expected values are presented.

Passive Mixing inside Microdroplets

Directory of Open Access Journals (Sweden)

Chengmin Chen

2018-04-01

Full Text Available Droplet-based micromixers are essential units in many microfluidic devices for widespread applications, such as diagnostics and synthesis. The mixers can be either passive or active. When compared to active methods, the passive mixer is widely used because it does not require extra energy input apart from the pump drive. In recent years, several passive droplet-based mixers were developed, where mixing was characterized by both experiments and simulation. A unified physical understanding of both experimental processes and simulation models is beneficial for effectively developing new and efficient mixing techniques. This review covers the state-of-the-art passive droplet-based micromixers in microfluidics, which mainly focuses on three aspects: (1 Mixing parameters and analysis method; (2 Typical mixing element designs and the mixing characters in experiments; and, (3 Comprehensive introduction of numerical models used in microfluidic flow and diffusion.

Advantage of make-to-stock strategy based on linear mixed-effect model: a comparison with regression, autoregressive, times series, and exponential smoothing models

Directory of Open Access Journals (Sweden)

Yu-Pin Liao

2017-11-01

Full Text Available In the past few decades, demand forecasting has become relatively difficult due to rapid changes in the global environment. This research illustrates the use of the make-to-stock (MTS production strategy in order to explain how forecasting plays an essential role in business management. The linear mixed-effect (LME model has been extensively developed and is widely applied in various fields. However, no study has used the LME model for business forecasting. We suggest that the LME model be used as a tool for prediction and to overcome environment complexity. The data analysis is based on real data in an international display company, where the company needs accurate demand forecasting before adopting a MTS strategy. The forecasting result from the LME model is compared to the commonly used approaches, including the regression model, autoregressive model, times series model, and exponential smoothing model, with the results revealing that prediction performance provided by the LME model is more stable than using the other methods. Furthermore, product types in the data are regarded as a random effect in the LME model, hence demands of all types can be predicted simultaneously using a single LME model. However, some approaches require splitting the data into different type categories, and then predicting the type demand by establishing a model for each type. This feature also demonstrates the practicability of the LME model in real business operations.

A general method to determine sampling windows for nonlinear mixed effects models with an application to population pharmacokinetic studies.

Science.gov (United States)

Foo, Lee Kien; McGree, James; Duffull, Stephen

2012-01-01

Optimal design methods have been proposed to determine the best sampling times when sparse blood sampling is required in clinical pharmacokinetic studies. However, the optimal blood sampling time points may not be feasible in clinical practice. Sampling windows, a time interval for blood sample collection, have been proposed to provide flexibility in blood sampling times while preserving efficient parameter estimation. Because of the complexity of the population pharmacokinetic models, which are generally nonlinear mixed effects models, there is no analytical solution available to determine sampling windows. We propose a method for determination of sampling windows based on MCMC sampling techniques. The proposed method attains a stationary distribution rapidly and provides time-sensitive windows around the optimal design points. The proposed method is applicable to determine sampling windows for any nonlinear mixed effects model although our work focuses on an application to population pharmacokinetic models. Copyright © 2012 John Wiley & Sons, Ltd.

Corrective Measures Study Modeling Results for the Southwest Plume - Burial Ground Complex/Mixed Waste Management Facility

International Nuclear Information System (INIS)

Harris, M.K.

1999-01-01

Groundwater modeling scenarios were performed to support the Corrective Measures Study and Interim Action Plan for the southwest plume of the Burial Ground Complex/Mixed Waste Management Facility. The modeling scenarios were designed to provide data for an economic analysis of alternatives, and subsequently evaluate the effectiveness of the selected remedial technologies for tritium reduction to Fourmile Branch. Modeling scenarios assessed include no action, vertical barriers, pump, treat, and reinject; and vertical recirculation wells

Nonlinear mixed effects modelling approach in investigating phenobarbital pharmacokinetic interactions in epileptic patients.

Science.gov (United States)

Vučićević, Katarina; Jovanović, Marija; Golubović, Bojana; Kovačević, Sandra Vezmar; Miljković, Branislava; Martinović, Žarko; Prostran, Milica

2015-02-01

The present study aimed to establish population pharmacokinetic model for phenobarbital (PB), examining and quantifying the magnitude of PB interactions with other antiepileptic drugs concomitantly used and to demonstrate its use for individualization of PB dosing regimen in adult epileptic patients. In total 205 PB concentrations were obtained during routine clinical monitoring of 136 adult epilepsy patients. PB steady state concentrations were measured by homogeneous enzyme immunoassay. Nonlinear mixed effects modelling (NONMEM) was applied for data analyses and evaluation of the final model. According to the final population model, significant determinant of apparent PB clearance (CL/F) was daily dose of concomitantly given valproic acid (VPA). Typical value of PB CL/F for final model was estimated at 0.314 l/h. Based on the final model, co-therapy with usual VPA dose of 1000 mg/day, resulted in PB CL/F average decrease of about 25 %, while 2000 mg/day leads to an average 50 % decrease in PB CL/F. Developed population PB model may be used in estimating individual CL/F for adult epileptic patients and could be applied for individualizing dosing regimen taking into account dose-dependent effect of concomitantly given VPA.

System equivalent model mixing

Science.gov (United States)

Klaassen, Steven W. B.; van der Seijs, Maarten V.; de Klerk, Dennis

2018-05-01

This paper introduces SEMM: a method based on Frequency Based Substructuring (FBS) techniques that enables the construction of hybrid dynamic models. With System Equivalent Model Mixing (SEMM) frequency based models, either of numerical or experimental nature, can be mixed to form a hybrid model. This model follows the dynamic behaviour of a predefined weighted master model. A large variety of applications can be thought of, such as the DoF-space expansion of relatively small experimental models using numerical models, or the blending of different models in the frequency spectrum. SEMM is outlined, both mathematically and conceptually, based on a notation commonly used in FBS. A critical physical interpretation of the theory is provided next, along with a comparison to similar techniques; namely DoF expansion techniques. SEMM's concept is further illustrated by means of a numerical example. It will become apparent that the basic method of SEMM has some shortcomings which warrant a few extensions to the method. One of the main applications is tested in a practical case, performed on a validated benchmark structure; it will emphasize the practicality of the method.

Anlaysis of the Effects of the ρ-ω Mixing in ρ and ω Mesons

International Nuclear Information System (INIS)

Kuecuekarslan, A.

2004-01-01

We review the radiative ω→π 0 π 0 γ, ρ→π 0 π 0 γ, ω →π 0 ηγ, ρ→π 0 ηγ, ω→π + π - γ and ρ→π + π - γ, decays in a phenomenological framework in which the contributions of vector meson dominance model, chiral loop, bremsstrahlung, σ-meson and a 0 -meson intermediate state amplitude and the effects of ω-ρ mixing are considered. We conclude that ρ-ω mixing contribution is dominant for ω→ππγ, decays, but for other decays it is relevant in the rest of the decays. Therefore, this mixing should be included in the analysis of the vector meson

Surface wind mixing in the Regional Ocean Modeling System (ROMS)

Science.gov (United States)

Robertson, Robin; Hartlipp, Paul

2017-12-01

Mixing at the ocean surface is key for atmosphere-ocean interactions and the distribution of heat, energy, and gases in the upper ocean. Winds are the primary force for surface mixing. To properly simulate upper ocean dynamics and the flux of these quantities within the upper ocean, models must reproduce mixing in the upper ocean. To evaluate the performance of the Regional Ocean Modeling System (ROMS) in replicating the surface mixing, the results of four different vertical mixing parameterizations were compared against observations, using the surface mixed layer depth, the temperature fields, and observed diffusivities for comparisons. The vertical mixing parameterizations investigated were Mellor- Yamada 2.5 level turbulent closure (MY), Large- McWilliams- Doney Kpp (LMD), Nakanishi- Niino (NN), and the generic length scale (GLS) schemes. This was done for one temperate site in deep water in the Eastern Pacific and three shallow water sites in the Baltic Sea. The model reproduced the surface mixed layer depth reasonably well for all sites; however, the temperature fields were reproduced well for the deep site, but not for the shallow Baltic Sea sites. In the Baltic Sea, the models overmixed the water column after a few days. Vertical temperature diffusivities were higher than those observed and did not show the temporal fluctuations present in the observations. The best performance was by NN and MY; however, MY became unstable in two of the shallow simulations with high winds. The performance of GLS nearly as good as NN and MY. LMD had the poorest performance as it generated temperature diffusivities that were too high and induced too much mixing. Further observational comparisons are needed to evaluate the effects of different stratification and wind conditions and the limitations on the vertical mixing parameterizations.

A model for quasi parity-doublet spectra with strong coriolis mixing

International Nuclear Information System (INIS)

Minkov, N.; Drenska, S.; Strecker, M.

2013-01-01

The model of coherent quadrupole and octupole motion (CQOM) is combined with the reflection-asymmetric deformed shell model (DSM) in a way allowing fully microscopic description of the Coriolis decoupling and K-mixing effects in the quasi parity-doublet spectra of odd-mass nuclei. In this approach the even-even core is considered within the CQOM model, while the odd nucleon is described within DSM with pairing interaction. The Coriolis decoupling/mixing factors are calculated through a parity-projection of the single-particle wave function. Expressions for the Coriolis mixed quasi parity-doublet levels are obtained in the second order of perturbation theory, while the K-mixed core plus particle wave function is obtained in the first order. Expressions for the B(E1), B(E2) and B(E3) reduced probabilities for transitions within and between different quasi-doublets are obtained by using the total K-mixed wave function. The model scheme is elaborated in a form capable of describing the yrast and non-yrast quasi parity-doublet spectra in odd-mass nuclei. (author)

Mixed Platoon Flow Dispersion Model Based on Speed-Truncated Gaussian Mixture Distribution

Directory of Open Access Journals (Sweden)

Weitiao Wu

2013-01-01

Full Text Available A mixed traffic flow feature is presented on urban arterials in China due to a large amount of buses. Based on field data, a macroscopic mixed platoon flow dispersion model (MPFDM was proposed to simulate the platoon dispersion process along the road section between two adjacent intersections from the flow view. More close to field observation, truncated Gaussian mixture distribution was adopted as the speed density distribution for mixed platoon. Expectation maximum (EM algorithm was used for parameters estimation. The relationship between the arriving flow distribution at downstream intersection and the departing flow distribution at upstream intersection was investigated using the proposed model. Comparison analysis using virtual flow data was performed between the Robertson model and the MPFDM. The results confirmed the validity of the proposed model.

Modeling of Mixing Behavior in a Combined Blowing Steelmaking Converter with a Filter-Based Euler-Lagrange Model

Science.gov (United States)

Li, Mingming; Li, Lin; Li, Qiang; Zou, Zongshu

2018-05-01

A filter-based Euler-Lagrange multiphase flow model is used to study the mixing behavior in a combined blowing steelmaking converter. The Euler-based volume of fluid approach is employed to simulate the top blowing, while the Lagrange-based discrete phase model that embeds the local volume change of rising bubbles for the bottom blowing. A filter-based turbulence method based on the local meshing resolution is proposed aiming to improve the modeling of turbulent eddy viscosities. The model validity is verified through comparison with physical experiments in terms of mixing curves and mixing times. The effects of the bottom gas flow rate on bath flow and mixing behavior are investigated and the inherent reasons for the mixing result are clarified in terms of the characteristics of bottom-blowing plumes, the interaction between plumes and top-blowing jets, and the change of bath flow structure.

Cluster Correlation in Mixed Models

Science.gov (United States)

Gardini, A.; Bonometto, S. A.; Murante, G.; Yepes, G.

2000-10-01

We evaluate the dependence of the cluster correlation length, rc, on the mean intercluster separation, Dc, for three models with critical matter density, vanishing vacuum energy (Λ=0), and COBE normalization: a tilted cold dark matter (tCDM) model (n=0.8) and two blue mixed models with two light massive neutrinos, yielding Ωh=0.26 and 0.14 (MDM1 and MDM2, respectively). All models approach the observational value of σ8 (and hence the observed cluster abundance) and are consistent with the observed abundance of damped Lyα systems. Mixed models have a motivation in recent results of neutrino physics; they also agree with the observed value of the ratio σ8/σ25, yielding the spectral slope parameter Γ, and nicely fit Las Campanas Redshift Survey (LCRS) reconstructed spectra. We use parallel AP3M simulations, performed in a wide box (of side 360 h-1 Mpc) and with high mass and distance resolution, enabling us to build artificial samples of clusters, whose total number and mass range allow us to cover the same Dc interval inspected through Automatic Plate Measuring Facility (APM) and Abell cluster clustering data. We find that the tCDM model performs substantially better than n=1 critical density CDM models. Our main finding, however, is that mixed models provide a surprisingly good fit to cluster clustering data.

Hierarchical linear modeling of longitudinal pedigree data for genetic association analysis

DEFF Research Database (Denmark)

Tan, Qihua; B Hjelmborg, Jacob V; Thomassen, Mads

2014-01-01

-effect models to explicitly model the genetic relationship. These have proved to be an efficient way of dealing with sample clustering in pedigree data. Although current algorithms implemented in popular statistical packages are useful for adjusting relatedness in the mixed modeling of genetic effects...... associated with blood pressure with estimated inflation factors of 0.99, suggesting that our modeling of random effects efficiently handles the genetic relatedness in pedigrees. Application to simulated data captures important variants specified in the simulation. Our results show that the method is useful......Genetic association analysis on complex phenotypes under a longitudinal design involving pedigrees encounters the problem of correlation within pedigrees, which could affect statistical assessment of the genetic effects. Approaches have been proposed to integrate kinship correlation into the mixed...

QCD mixing effects in a gauge invariant quark model for photo- and electroproduction of baryon resonances

International Nuclear Information System (INIS)

Zhenping Li; Close, F.E.

1990-03-01

The photo and electroproduction of baryon resonances has been calculated using the Constituent Quark Model with chromodynamics consistent with O(υ 2 /c 2 ) for the quarks. We find that the successes of the nonrelativistic quark model are preserved, some problems are removed and that QCD mixing effects may become important with increasing q 2 in electroproduction. For the first time both spectroscopy and transitions receive a unified treatment with a single set of parameters. (author)

Application of the Fokker-Planck molecular mixing model to turbulent scalar mixing using moment methods

Science.gov (United States)

Madadi-Kandjani, E.; Fox, R. O.; Passalacqua, A.

2017-06-01

An extended quadrature method of moments using the β kernel density function (β -EQMOM) is used to approximate solutions to the evolution equation for univariate and bivariate composition probability distribution functions (PDFs) of a passive scalar for binary and ternary mixing. The key element of interest is the molecular mixing term, which is described using the Fokker-Planck (FP) molecular mixing model. The direct numerical simulations (DNSs) of Eswaran and Pope ["Direct numerical simulations of the turbulent mixing of a passive scalar," Phys. Fluids 31, 506 (1988)] and the amplitude mapping closure (AMC) of Pope ["Mapping closures for turbulent mixing and reaction," Theor. Comput. Fluid Dyn. 2, 255 (1991)] are taken as reference solutions to establish the accuracy of the FP model in the case of binary mixing. The DNSs of Juneja and Pope ["A DNS study of turbulent mixing of two passive scalars," Phys. Fluids 8, 2161 (1996)] are used to validate the results obtained for ternary mixing. Simulations are performed with both the conditional scalar dissipation rate (CSDR) proposed by Fox [Computational Methods for Turbulent Reacting Flows (Cambridge University Press, 2003)] and the CSDR from AMC, with the scalar dissipation rate provided as input and obtained from the DNS. Using scalar moments up to fourth order, the ability of the FP model to capture the evolution of the shape of the PDF, important in turbulent mixing problems, is demonstrated. Compared to the widely used assumed β -PDF model [S. S. Girimaji, "Assumed β-pdf model for turbulent mixing: Validation and extension to multiple scalar mixing," Combust. Sci. Technol. 78, 177 (1991)], the β -EQMOM solution to the FP model more accurately describes the initial mixing process with a relatively small increase in computational cost.

Mixed kernel function support vector regression for global sensitivity analysis

Science.gov (United States)

Cheng, Kai; Lu, Zhenzhou; Wei, Yuhao; Shi, Yan; Zhou, Yicheng

2017-11-01

Global sensitivity analysis (GSA) plays an important role in exploring the respective effects of input variables on an assigned output response. Amongst the wide sensitivity analyses in literature, the Sobol indices have attracted much attention since they can provide accurate information for most models. In this paper, a mixed kernel function (MKF) based support vector regression (SVR) model is employed to evaluate the Sobol indices at low computational cost. By the proposed derivation, the estimation of the Sobol indices can be obtained by post-processing the coefficients of the SVR meta-model. The MKF is constituted by the orthogonal polynomials kernel function and Gaussian radial basis kernel function, thus the MKF possesses both the global characteristic advantage of the polynomials kernel function and the local characteristic advantage of the Gaussian radial basis kernel function. The proposed approach is suitable for high-dimensional and non-linear problems. Performance of the proposed approach is validated by various analytical functions and compared with the popular polynomial chaos expansion (PCE). Results demonstrate that the proposed approach is an efficient method for global sensitivity analysis.

A general mixed boundary model reduction method for component mode synthesis

International Nuclear Information System (INIS)

Voormeeren, S N; Van der Valk, P L C; Rixen, D J

2010-01-01

A classic issue in component mode synthesis (CMS) methods is the choice for fixed or free boundary conditions at the interface degrees of freedom (DoF) and the associated vibration modes in the components reduction base. In this paper, a novel mixed boundary CMS method called the 'Mixed Craig-Bampton' method is proposed. The method is derived by dividing the substructure DoF into a set of internal DoF, free interface DoF and fixed interface DoF. To this end a simple but effective scheme is introduced that, for every pair of interface DoF, selects a free or fixed boundary condition for each DoF individually. Based on this selection a reduction basis is computed consisting of vibration modes, static constraint modes and static residual flexibility modes. In order to assemble the reduced substructures a novel mixed assembly procedure is developed. It is shown that this approach leads to relatively sparse reduced matrices, whereas other mixed boundary methods often lead to full matrices. As such, the Mixed Craig-Bampton method forms a natural generalization of the classic Craig-Bampton and more recent Dual Craig-Bampton methods. Finally, the method is applied to a finite element test model. Analysis reveals that the proposed method has comparable or better accuracy and superior versatility with respect to the existing methods.

Lagrangian mixed layer modeling of the western equatorial Pacific

Science.gov (United States)

Shinoda, Toshiaki; Lukas, Roger

1995-01-01

Processes that control the upper ocean thermohaline structure in the western equatorial Pacific are examined using a Lagrangian mixed layer model. The one-dimensional bulk mixed layer model of Garwood (1977) is integrated along the trajectories derived from a nonlinear 1 1/2 layer reduced gravity model forced with actual wind fields. The Global Precipitation Climatology Project (GPCP) data are used to estimate surface freshwater fluxes for the mixed layer model. The wind stress data which forced the 1 1/2 layer model are used for the mixed layer model. The model was run for the period 1987-1988. This simple model is able to simulate the isothermal layer below the mixed layer in the western Pacific warm pool and its variation. The subduction mechanism hypothesized by Lukas and Lindstrom (1991) is evident in the model results. During periods of strong South Equatorial Current, the warm and salty mixed layer waters in the central Pacific are subducted below the fresh shallow mixed layer in the western Pacific. However, this subduction mechanism is not evident when upwelling Rossby waves reach the western equatorial Pacific or when a prominent deepening of the mixed layer occurs in the western equatorial Pacific or when a prominent deepening of the mixed layer occurs in the western equatorial Pacific due to episodes of strong wind and light precipitation associated with the El Nino-Southern Oscillation. Comparison of the results between the Lagrangian mixed layer model and a locally forced Eulerian mixed layer model indicated that horizontal advection of salty waters from the central Pacific strongly affects the upper ocean salinity variation in the western Pacific, and that this advection is necessary to maintain the upper ocean thermohaline structure in this region.

Relating masses and mixing angles. A model-independent model

Energy Technology Data Exchange (ETDEWEB)

Hollik, Wolfgang Gregor [DESY, Hamburg (Germany); Saldana-Salazar, Ulises Jesus [CINVESTAV (Mexico)

2016-07-01

In general, mixing angles and fermion masses are seen to be independent parameters of the Standard Model. However, exploiting the observed hierarchy in the masses, it is viable to construct the mixing matrices for both quarks and leptons in terms of the corresponding mass ratios only. A closer view on the symmetry properties leads to potential realizations of that approach in extensions of the Standard Model. We discuss the application in the context of flavored multi-Higgs models.

Analysis of the mixing processes in the subtropical Advancetown Lake, Australia

Science.gov (United States)

Bertone, Edoardo; Stewart, Rodney A.; Zhang, Hong; O'Halloran, Kelvin

2015-03-01

This paper presents an extensive investigation of the mixing processes occurring in the subtropical monomictic Advancetown Lake, which is the main water body supplying the Gold Coast City in Australia. Meteorological, chemical and physical data were collected from weather stations, laboratory analysis of grab samples and an in-situ Vertical Profiling System (VPS), for the period 2008-2012. This comprehensive, high frequency dataset was utilised to develop a one-dimensional model of the vertical transport and mixing processes occurring along the water column. Multivariate analysis revealed that air temperature and rain forecasts enabled a reliable prediction of the strength of the lake stratification. Vertical diffusion is the main process driving vertical mixing, particularly during winter circulation. However, a high reservoir volume and warm winters can limit the degree of winter mixing, causing only partial circulation to occur, as was the case in 2013. This research study provides a comprehensive approach for understanding and predicting mixing processes for similar lakes, whenever high-frequency data are available from VPS or other autonomous water monitoring systems.

Characterisation and modelling of mixing processes in groundwaters of a potential geological repository for nuclear wastes in crystalline rocks of Sweden

Energy Technology Data Exchange (ETDEWEB)

Gómez, Javier B., E-mail: jgomez@unizar.es; Gimeno, María J., E-mail: mjgimeno@unizar.es; Auqué, Luis F., E-mail: lauque@unizar.es; Acero, Patricia, E-mail: patriace@unizar.es

2014-01-01

This paper presents the mixing modelling results for the hydrogeochemical characterisation of groundwaters in the Laxemar area (Sweden). This area is one of the two sites that have been investigated, under the financial patronage of the Swedish Nuclear Waste and Management Co. (SKB), as possible candidates for hosting the proposed repository for the long-term storage of spent nuclear fuel. The classical geochemical modelling, interpreted in the light of the palaeohydrogeological history of the system, has shown that the driving process in the geochemical evolution of this groundwater system is the mixing between four end-member waters: a deep and old saline water, a glacial meltwater, an old marine water, and a meteoric water. In this paper we put the focus on mixing and its effects on the final chemical composition of the groundwaters using a comprehensive methodology that combines principal component analysis with mass balance calculations. This methodology allows us to test several combinations of end member waters and several combinations of compositional variables in order to find optimal solutions in terms of mixing proportions. We have applied this methodology to a dataset of 287 groundwater samples from the Laxemar area collected and analysed by SKB. The best model found uses four conservative elements (Cl, Br, oxygen-18 and deuterium), and computes mixing proportions with respect to three end member waters (saline, glacial and meteoric). Once the first order effect of mixing has been taken into account, water–rock interaction can be used to explain the remaining variability. In this way, the chemistry of each water sample can be obtained by using the mixing proportions for the conservative elements, only affected by mixing, or combining the mixing proportions and the chemical reactions for the non-conservative elements in the system, establishing the basis for predictive calculations. - Highlights: • Laxemar (Sweden) groundwater is the combined result

Characterisation and modelling of mixing processes in groundwaters of a potential geological repository for nuclear wastes in crystalline rocks of Sweden

International Nuclear Information System (INIS)

Gómez, Javier B.; Gimeno, María J.; Auqué, Luis F.; Acero, Patricia

2014-01-01

This paper presents the mixing modelling results for the hydrogeochemical characterisation of groundwaters in the Laxemar area (Sweden). This area is one of the two sites that have been investigated, under the financial patronage of the Swedish Nuclear Waste and Management Co. (SKB), as possible candidates for hosting the proposed repository for the long-term storage of spent nuclear fuel. The classical geochemical modelling, interpreted in the light of the palaeohydrogeological history of the system, has shown that the driving process in the geochemical evolution of this groundwater system is the mixing between four end-member waters: a deep and old saline water, a glacial meltwater, an old marine water, and a meteoric water. In this paper we put the focus on mixing and its effects on the final chemical composition of the groundwaters using a comprehensive methodology that combines principal component analysis with mass balance calculations. This methodology allows us to test several combinations of end member waters and several combinations of compositional variables in order to find optimal solutions in terms of mixing proportions. We have applied this methodology to a dataset of 287 groundwater samples from the Laxemar area collected and analysed by SKB. The best model found uses four conservative elements (Cl, Br, oxygen-18 and deuterium), and computes mixing proportions with respect to three end member waters (saline, glacial and meteoric). Once the first order effect of mixing has been taken into account, water–rock interaction can be used to explain the remaining variability. In this way, the chemistry of each water sample can be obtained by using the mixing proportions for the conservative elements, only affected by mixing, or combining the mixing proportions and the chemical reactions for the non-conservative elements in the system, establishing the basis for predictive calculations. - Highlights: • Laxemar (Sweden) groundwater is the combined result

Scotogenic model for co-bimaximal mixing

Energy Technology Data Exchange (ETDEWEB)

Ferreira, P.M. [Instituto Superior de Engenharia de Lisboa - ISEL,1959-007 Lisboa (Portugal); Centro de Física Teórica e Computacional - FCUL, Universidade de Lisboa,R. Ernesto de Vasconcelos, 1749-016 Lisboa (Portugal); Grimus, W. [Faculty of Physics, University of Vienna,Boltzmanngasse 5, A-1090 Wien (Austria); Jurčiukonis, D. [Institute of Theoretical Physics and Astronomy, Vilnius University,Saul?etekio ave. 3, LT-10222 Vilnius (Lithuania); Lavoura, L. [CFTP, Instituto Superior Técnico, Universidade de Lisboa,1049-001 Lisboa (Portugal)

2016-07-04

We present a scotogenic model, i.e. a one-loop neutrino mass model with dark right-handed neutrino gauge singlets and one inert dark scalar gauge doublet η, which has symmetries that lead to co-bimaximal mixing, i.e. to an atmospheric mixing angle θ{sub 23}=45{sup ∘} and to a CP-violating phase δ=±π/2, while the mixing angle θ{sub 13} remains arbitrary. The symmetries consist of softly broken lepton numbers L{sub α} (α=e,μ,τ), a non-standard CP symmetry, and three ℤ{sub 2} symmetries. We indicate two possibilities for extending the model to the quark sector. Since the model has, besides η, three scalar gauge doublets, we perform a thorough discussion of its scalar sector. We demonstrate that it can accommodate a Standard Model-like scalar with mass 125 GeV, with all the other charged and neutral scalars having much higher masses.

Isotropic damage model and serial/parallel mix theory applied to nonlinear analysis of ferrocement thin walls. Experimental and numerical analysis

Directory of Open Access Journals (Sweden)

Jairo A. Paredes

2016-01-01

Full Text Available Ferrocement thin walls are the structural elements that comprise the earthquake resistant system of dwellings built with this material. This article presents the results drawn from an experimental campaign carried out over full-scale precast ferrocement thin walls that were assessed under lateral static loading conditions. The tests allowed the identification of structural parameters and the evaluation of the performance of the walls under static loading conditions. Additionally, an isotropic damage model for modelling the mortar was applied, as well as the classic elasto-plastic theory for modelling the meshes and reinforcing bars. The ferrocement is considered as a composite material, thus the serial/parallel mix theory is used for modelling its mechanical behavior. In this work a methodology for the numerical analysis that allows modeling the nonlinear behavior exhibited by ferrocement walls under static loading conditions, as well as their potential use in earthquake resistant design, is proposed.

Models of neutrino mass and mixing

International Nuclear Information System (INIS)

Ma, Ernest

2000-01-01

There are two basic theoretical approaches to obtaining neutrino mass and mixing. In the minimalist approach, one adds just enough new stuff to the Minimal Standard Model to get m ν ≠0 and U αi ≠1. In the holistic approach, one uses a general framework or principle to enlarge the Minimal Standard Model such that, among other things, m ν ≠0 and U αi ≠1. In both cases, there are important side effects besides neutrino oscillations. I discuss a number of examples, including the possibility of leptogenesis from R parity nonconservation in supersymmetry

Dynamic Stability Analysis of Autonomous Medium-Voltage Mixed-Source Microgrid

DEFF Research Database (Denmark)

Zhao, Zhuoli; Yang, Ping; Guerrero, Josep M.

2015-01-01

-space model of the autonomous MV mixed-source microgrid containing diesel generator set (DGS), grid-supporting battery energy storage system (BESS), squirrel cage induction generator (SCIG) wind turbine and network is developed. Sensitivity analysis is carried out to reveal the dynamic stability margin...

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

Science.gov (United States)

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.

Personalized prediction of chronic wound healing: an exponential mixed effects model using stereophotogrammetric measurement.

Science.gov (United States)

Xu, Yifan; Sun, Jiayang; Carter, Rebecca R; Bogie, Kath M

2014-05-01

Stereophotogrammetric digital imaging enables rapid and accurate detailed 3D wound monitoring. This rich data source was used to develop a statistically validated model to provide personalized predictive healing information for chronic wounds. 147 valid wound images were obtained from a sample of 13 category III/IV pressure ulcers from 10 individuals with spinal cord injury. Statistical comparison of several models indicated the best fit for the clinical data was a personalized mixed-effects exponential model (pMEE), with initial wound size and time as predictors and observed wound size as the response variable. Random effects capture personalized differences. Other models are only valid when wound size constantly decreases. This is often not achieved for clinical wounds. Our model accommodates this reality. Two criteria to determine effective healing time outcomes are proposed: r-fold wound size reduction time, t(r-fold), is defined as the time when wound size reduces to 1/r of initial size. t(δ) is defined as the time when the rate of the wound healing/size change reduces to a predetermined threshold δ current model improves with each additional evaluation. Routine assessment of wounds using detailed stereophotogrammetric imaging can provide personalized predictions of wound healing time. Application of a valid model will help the clinical team to determine wound management care pathways. Published by Elsevier Ltd.

Fuzzy interval Finite Element/Statistical Energy Analysis for mid-frequency analysis of built-up systems with mixed fuzzy and interval parameters

Science.gov (United States)

Yin, Hui; Yu, Dejie; Yin, Shengwen; Xia, Baizhan

2016-10-01

This paper introduces mixed fuzzy and interval parametric uncertainties into the FE components of the hybrid Finite Element/Statistical Energy Analysis (FE/SEA) model for mid-frequency analysis of built-up systems, thus an uncertain ensemble combining non-parametric with mixed fuzzy and interval parametric uncertainties comes into being. A fuzzy interval Finite Element/Statistical Energy Analysis (FIFE/SEA) framework is proposed to obtain the uncertain responses of built-up systems, which are described as intervals with fuzzy bounds, termed as fuzzy-bounded intervals (FBIs) in this paper. Based on the level-cut technique, a first-order fuzzy interval perturbation FE/SEA (FFIPFE/SEA) and a second-order fuzzy interval perturbation FE/SEA method (SFIPFE/SEA) are developed to handle the mixed parametric uncertainties efficiently. FFIPFE/SEA approximates the response functions by the first-order Taylor series, while SFIPFE/SEA improves the accuracy by considering the second-order items of Taylor series, in which all the mixed second-order items are neglected. To further improve the accuracy, a Chebyshev fuzzy interval method (CFIM) is proposed, in which the Chebyshev polynomials is used to approximate the response functions. The FBIs are eventually reconstructed by assembling the extrema solutions at all cut levels. Numerical results on two built-up systems verify the effectiveness of the proposed methods.

Analysis of mixed data methods & applications

CERN Document Server

de Leon, Alexander R

2013-01-01

A comprehensive source on mixed data analysis, Analysis of Mixed Data: Methods & Applications summarizes the fundamental developments in the field. Case studies are used extensively throughout the book to illustrate interesting applications from economics, medicine and health, marketing, and genetics. Carefully edited for smooth readability and seamless transitions between chaptersAll chapters follow a common structure, with an introduction and a concluding summary, and include illustrative examples from real-life case studies in developmental toxicolog

[Spatial heterogeneity in body condition of small yellow croaker in Yellow Sea and East China Sea based on mixed-effects model and quantile regression analysis].

Science.gov (United States)

Liu, Zun-Lei; Yuan, Xing-Wei; Yan, Li-Ping; Yang, Lin-Lin; Cheng, Jia-Hua

2013-09-01

By using the 2008-2010 investigation data about the body condition of small yellow croaker in the offshore waters of southern Yellow Sea (SYS), open waters of northern East China Sea (NECS), and offshore waters of middle East China Sea (MECS), this paper analyzed the spatial heterogeneity of body length-body mass of juvenile and adult small yellow croakers by the statistical approaches of mean regression model and quantile regression model. The results showed that the residual standard errors from the analysis of covariance (ANCOVA) and the linear mixed-effects model were similar, and those from the simple linear regression were the highest. For the juvenile small yellow croakers, their mean body mass in SYS and NECS estimated by the mixed-effects mean regression model was higher than the overall average mass across the three regions, while the mean body mass in MECS was below the overall average. For the adult small yellow croakers, their mean body mass in NECS was higher than the overall average, while the mean body mass in SYS and MECS was below the overall average. The results from quantile regression indicated the substantial differences in the allometric relationships of juvenile small yellow croakers between SYS, NECS, and MECS, with the estimated mean exponent of the allometric relationship in SYS being 2.85, and the interquartile range being from 2.63 to 2.96, which indicated the heterogeneity of body form. The results from ANCOVA showed that the allometric body length-body mass relationships were significantly different between the 25th and 75th percentile exponent values (F=6.38, df=1737, P<0.01) and the 25th percentile and median exponent values (F=2.35, df=1737, P=0.039). The relationship was marginally different between the median and 75th percentile exponent values (F=2.21, df=1737, P=0.051). The estimated body length-body mass exponent of adult small yellow croakers in SYS was 3.01 (10th and 95th percentiles = 2.77 and 3.1, respectively). The

Fluctuations in a mixed IS-LM business cycle model

Directory of Open Access Journals (Sweden)

Hamad Talibi Alaoui

2008-09-01

Full Text Available In the present paper, we extend a delayed IS-LM business cycle model by introducing an additional advance (anticipated capital stock in the investment function. The resulting model is represented in terms of mixed differential equations. For the deviating argument $au$ (advance and delay being a bifurcation parameter we investigate the local stability and the local Hopf bifurcation. Also some numerical simulations are given to support the theoretical analysis.

MetabR: an R script for linear model analysis of quantitative metabolomic data

Directory of Open Access Journals (Sweden)

Ernest Ben

2012-10-01

Full Text Available Abstract Background Metabolomics is an emerging high-throughput approach to systems biology, but data analysis tools are lacking compared to other systems level disciplines such as transcriptomics and proteomics. Metabolomic data analysis requires a normalization step to remove systematic effects of confounding variables on metabolite measurements. Current tools may not correctly normalize every metabolite when the relationships between each metabolite quantity and fixed-effect confounding variables are different, or for the effects of random-effect confounding variables. Linear mixed models, an established methodology in the microarray literature, offer a standardized and flexible approach for removing the effects of fixed- and random-effect confounding variables from metabolomic data. Findings Here we present a simple menu-driven program, “MetabR”, designed to aid researchers with no programming background in statistical analysis of metabolomic data. Written in the open-source statistical programming language R, MetabR implements linear mixed models to normalize metabolomic data and analysis of variance (ANOVA to test treatment differences. MetabR exports normalized data, checks statistical model assumptions, identifies differentially abundant metabolites, and produces output files to help with data interpretation. Example data are provided to illustrate normalization for common confounding variables and to demonstrate the utility of the MetabR program. Conclusions We developed MetabR as a simple and user-friendly tool for implementing linear mixed model-based normalization and statistical analysis of targeted metabolomic data, which helps to fill a lack of available data analysis tools in this field. The program, user guide, example data, and any future news or updates related to the program may be found at http://metabr.r-forge.r-project.org/.

Canards and mixed-mode oscillations in a forest pest model

DEFF Research Database (Denmark)

Brøns, Morten; Kaasen, Rune

2010-01-01

of high pest concentration. For small values of the timescale of the young trees, the model can be reduced to a two-dimensional model. By a geometrical analysis we identify a canard explosion in the reduced model, that is, a change over a narrow parameter interval from outbreak dynamics to small...... oscillations around an endemic state. For larger values of the timescale of the young trees the two-dimensional approximation breaks down, and a broader parameter interval with mixed-mode oscillations appear, replacing the simple canard explosion. The analysis only relies on simple and generic properties...

A detailed aerosol mixing state model for investigating interactions between mixing state, semivolatile partitioning, and coagulation

Directory of Open Access Journals (Sweden)

J. Lu

2010-04-01

Full Text Available A new method for describing externally mixed particles, the Detailed Aerosol Mixing State (DAMS representation, is presented in this study. This novel method classifies aerosols by both composition and size, using a user-specified mixing criterion to define boundaries between compositional populations. Interactions between aerosol mixing state, semivolatile partitioning, and coagulation are investigated with a Lagrangian box model that incorporates the DAMS approach. Model results predict that mixing state affects the amount and types of semivolatile organics that partition to available aerosol phases, causing external mixtures to produce a more size-varying composition than internal mixtures. Both coagulation and condensation contribute to the mixing of emitted particles, producing a collection of multiple compositionally distinct aerosol populations that exists somewhere between the extremes of a strictly external or internal mixture. The selection of mixing criteria has a significant impact on the size and type of individual populations that compose the modeled aerosol mixture. Computational demands for external mixture modeling are significant and can be controlled by limiting the number of aerosol populations used in the model.

A mathematical model for turbulent incompressible flows through mixing grids

International Nuclear Information System (INIS)

Allaire, G.

1989-01-01

A mathematical model is proposed for the computation of turbulent incompressible flows through mixing grids. This model is obtained as follows: in a three-dimentional-domain we represent a mixing grid by small identical wings of size ε 2 periodically distributed at the nodes of a plane regular mesh of size ε, and we consider incompressible Navier-Stokes equations with a no-slip condition on the wings. Using an appropriate homogenization process we pass to the limit when ε tends to zero and we obtain a Brinkman equation, i.e. a Navier-Stokes equation plus a zero-order term for the velocity, in a homogeneous domain without anymore wings. The interest of this model is that the spatial discretization is simpler in a homogeneous domain, and, moreover, the new term, which expresses the grid's mixing effect, can be evaluated with a local computation around a single wing

Goodness-of-fit tests in mixed models

KAUST Repository

Claeskens, Gerda

2009-05-12

Mixed models, with both random and fixed effects, are most often estimated on the assumption that the random effects are normally distributed. In this paper we propose several formal tests of the hypothesis that the random effects and/or errors are normally distributed. Most of the proposed methods can be extended to generalized linear models where tests for non-normal distributions are of interest. Our tests are nonparametric in the sense that they are designed to detect virtually any alternative to normality. In case of rejection of the null hypothesis, the nonparametric estimation method that is used to construct a test provides an estimator of the alternative distribution. © 2009 Sociedad de Estadística e Investigación Operativa.

The Analysis for the Effect of Mixing Vane Shape on TDC

International Nuclear Information System (INIS)

Moon, Kang Hoon; Park, Ho Young; Kim, Kang Hoon; Park, Eung Jun; Suh, Jung Min

2011-01-01

The Thermal Diffusion Coefficient (TDC) is an input parameter to subchannel code, and it is required to predict local flow conditions in a PWR fuel bundle. TDC influences on the prediction of thermal interchange or mixing of thermal energy between the hot subchannel and interconnected adjacent subchannels. The thermal mixing term in the energy equation is generally represented in terms of a non-dimensional inverse Peclet number or TDC. The parameters associated with thermal mixing can be defined as Eq.(1): TDC =Pe x De/a (1) where: Pe : Inverse Peclet Number (dimensionless) = ε/ Va De : Equivalent hydraulic diameter, in. a : Lateral flow area between channels per unit length, in 2 /in ε : Mixing coefficient, in 2 /sec V : Velocity, in/sec TDC is an important factor to evaluate thermal performance. So, flow temperature maps were obtained from the 5x5 rod bundle test section to assess the thermal performance of corresponding fuels. The flow temperatures were measured by thermocouple at the end of heated length and the centroid of subchannel. There are two typical methods to arrange the hot and cold fuel rods as shown in Fig. 1. Configuration Fig. 1(b) is adopted in this work. This paper presents how to determine the TDC and verifies whether all TDC with the effect of mixing vane shape is valid with respect to current design value

Sensitivity studies of different aerosol indirect effects in mixed-phase clouds

Science.gov (United States)

Lohmann, U.; Hoose, C.

2009-11-01

Aerosols affect the climate system by changing cloud characteristics. Using the global climate model ECHAM5-HAM, we investigate different aerosol effects on mixed-phase clouds: The glaciation effect, which refers to a more frequent glaciation due to anthropogenic aerosols, versus the de-activation effect, which suggests that ice nuclei become less effective because of an anthropogenic sulfate coating. The glaciation effect can partly offset the indirect aerosol effect on warm clouds and thus causes the total anthropogenic aerosol effect to be smaller. It is investigated by varying the parameterization for the Bergeron-Findeisen process and the threshold coating thickness of sulfate (SO4-crit), which is required to convert an externally mixed aerosol particle into an internally mixed particle. Differences in the net radiation at the top-of-the-atmosphere due to anthropogenic aerosols between the different sensitivity studies amount up to 0.5 W m-2. This suggests that the investigated mixed-phase processes have a major effect on the total anthropogenic aerosol effect.

Effect of mix parameters on longevity of bituminous mixtures

Science.gov (United States)

Reichle, Clayton Matthew

This study was performed to evaluate the effects of varying aggregate sources, aggregate gradations on the stripping and rutting potential of bituminous based plant mixes specified by the Missouri Department of Transportation. The different aggregate combinations included two different aggregate sources (Potosi Dolomite and Jefferson City Dolomite) including two variations for the Jefferson City Dolomite mix to simulate a marginally in-specification mix and an out-of-specification but in-field tolerance mix. The "field" mix simulated the marginal mix where field tolerance of high dust and low binder content were maximized. All three mixes were evaluated for stripping susceptibility using the Tensile Strength Ratio (TSR) test and the Hamburg Wheel Tracking Device (HWTD). The mix characteristics (unit weight, effective binder content, and air voids) were used for a Level 3 analysis in the Mechanistic-Empirical Pavement Design Guide (MEPDG) to determine long term pavement distress conditions such as fatigue cracking, rutting, and IRI (smoothness). The Potosi mix exhibited the best resistance to rutting and stripping during both the TSR testing as well as the Hamburg testing. The Jefferson City In-Spec and Out-of-Spec mixes showed less resistance to rutting and stripping in order, respectively. This was expected for the Jefferson City mixes where the aggregate was of lower quality (higher Los Angeles Abrasion, Micro Deval loss, absorption, and deleterious materials). Also, in the case of the Jefferson City Out-of-Spec mix, the binder content was lower. Upon evaluating the mixes using the MEPDG software, it was shown that mix characteristics such as air voids, VMA, and VFA influenced the fatigue cracking, rutting, and IRI predictions to a minor degree.

Fixed versus mixed RSA: Explaining visual representations by fixed and mixed feature sets from shallow and deep computational models.

Science.gov (United States)

Khaligh-Razavi, Seyed-Mahdi; Henriksson, Linda; Kay, Kendrick; Kriegeskorte, Nikolaus

2017-02-01

Studies of the primate visual system have begun to test a wide range of complex computational object-vision models. Realistic models have many parameters, which in practice cannot be fitted using the limited amounts of brain-activity data typically available. Task performance optimization (e.g. using backpropagation to train neural networks) provides major constraints for fitting parameters and discovering nonlinear representational features appropriate for the task (e.g. object classification). Model representations can be compared to brain representations in terms of the representational dissimilarities they predict for an image set. This method, called representational similarity analysis (RSA), enables us to test the representational feature space as is (fixed RSA) or to fit a linear transformation that mixes the nonlinear model features so as to best explain a cortical area's representational space (mixed RSA). Like voxel/population-receptive-field modelling, mixed RSA uses a training set (different stimuli) to fit one weight per model feature and response channel (voxels here), so as to best predict the response profile across images for each response channel. We analysed response patterns elicited by natural images, which were measured with functional magnetic resonance imaging (fMRI). We found that early visual areas were best accounted for by shallow models, such as a Gabor wavelet pyramid (GWP). The GWP model performed similarly with and without mixing, suggesting that the original features already approximated the representational space, obviating the need for mixing. However, a higher ventral-stream visual representation (lateral occipital region) was best explained by the higher layers of a deep convolutional network and mixing of its feature set was essential for this model to explain the representation. We suspect that mixing was essential because the convolutional network had been trained to discriminate a set of 1000 categories, whose frequencies

National socioeconomic indicators are associated with outcomes after aneurysmal subarachnoid hemorrhage: a hierarchical mixed-effects analysis.

Science.gov (United States)

Guha, Daipayan; Ibrahim, George M; Kertzer, Joshua D; Macdonald, R Loch

2014-11-01

Although heterogeneity exists in patient outcomes following subarachnoid hemorrhage (SAH) across different centers and countries, it is unclear which factors contribute to such disparities. In this study, the authors performed a post hoc analysis of a large international database to evaluate the association between a country's socioeconomic indicators and patient outcome following aneurysmal SAH. An analysis was performed on a database of 3552 patients enrolled in studies of tirilazad mesylate for aneurysmal SAH from 1991 to 1997, which included 162 neurosurgical centers in North and Central America, Australia, Europe, and Africa. Two primary outcomes were assessed at 3 months after SAH: mortality and Glasgow Outcome Scale (GOS) score. The association between these outcomes, nation-level socioeconomic indicators (percapita gross domestic product [GDP], population-to-neurosurgeon ratio, and health care funding model), and patientlevel covariates were assessed using a hierarchical mixed-effects logistic regression analysis. Multiple previously identified patient-level covariates were significantly associated with increased mortality and worse neurological outcome, including age, intraventricular hemorrhage, and initial neurological grade. Among national-level covariates, higher per-capita GDP (p funding model was not a significant predictor of either primary outcome. Higher per-capita gross GDP and population-to-neurosurgeon ratio were associated with improved outcome after aneurysmal SAH. The former result may speak to the availability of resources, while the latter may be a reflection of better outcomes with centralized care. Although patient clinical and radiographic phenotypes remain the primary predictors of outcome, this study shows that national socioeconomic disparities also explain heterogeneity in outcomes following SAH.

MARKETING MIX: AN ATTEMPT AT CRITICAL ANALYSIS

OpenAIRE

Kotliarov I.D.

2012-01-01

The present paper contains an analysis of main directions of evolution of marketing mix concept. Typical problems of each approach are demonstrated. Classical form of marketing mix (4Ps) is recommended as the basic form of marketing mix, which, however, may be adapted to specific characteristics of the firm and its industry

Effect of Mixing Process on Polypropylene Modified Bituminous Concrete Mix Properties

OpenAIRE

Noor Zainab Habib; Ibrahim Kamaruddin; Madzalan Napiah; Isa Mohd Tan

2011-01-01

This paper presents a research conducted to investigate the effect of mixing process on polypropylene (PP) modified bitumen mixed with well graded aggregate to form modified bituminous concrete mix. Two mode of mixing, namely dry and wet with different concentration of polymer polypropylene was used with 80/100 pen bitumen, to evaluate the bituminous concrete mix properties. Three percentages of polymer varying from 1-3% by the weight of bitumen was used in this study. Three mixes namely cont...

Analysis of litter size and average litter weight in pigs using a recursive model

DEFF Research Database (Denmark)

Varona, Luis; Sorensen, Daniel; Thompson, Robin

2007-01-01

An analysis of litter size and average piglet weight at birth in Landrace and Yorkshire using a standard two-trait mixed model (SMM) and a recursive mixed model (RMM) is presented. The RMM establishes a one-way link from litter size to average piglet weight. It is shown that there is a one......-to-one correspondence between the parameters of SMM and RMM and that they generate equivalent likelihoods. As parameterized in this work, the RMM tests for the presence of a recursive relationship between additive genetic values, permanent environmental effects, and specific environmental effects of litter size......, on average piglet weight. The equivalent standard mixed model tests whether or not the covariance matrices of the random effects have a diagonal structure. In Landrace, posterior predictive model checking supports a model without any form of recursion or, alternatively, a SMM with diagonal covariance...

A turbulent mixing Reynolds stress model fitted to match linear interaction analysis predictions

International Nuclear Information System (INIS)

Griffond, J; Soulard, O; Souffland, D

2010-01-01

To predict the evolution of turbulent mixing zones developing in shock tube experiments with different gases, a turbulence model must be able to reliably evaluate the production due to the shock-turbulence interaction. In the limit of homogeneous weak turbulence, 'linear interaction analysis' (LIA) can be applied. This theory relies on Kovasznay's decomposition and allows the computation of waves transmitted or produced at the shock front. With assumptions about the composition of the upstream turbulent mixture, one can connect the second-order moments downstream from the shock front to those upstream through a transfer matrix, depending on shock strength. The purpose of this work is to provide a turbulence model that matches LIA results for the shock-turbulent mixture interaction. Reynolds stress models (RSMs) with additional equations for the density-velocity correlation and the density variance are considered here. The turbulent states upstream and downstream from the shock front calculated with these models can also be related through a transfer matrix, provided that the numerical implementation is based on a pseudo-pressure formulation. Then, the RSM should be modified in such a way that its transfer matrix matches the LIA one. Using the pseudo-pressure to introduce ad hoc production terms, we are able to obtain a close agreement between LIA and RSM matrices for any shock strength and thus improve the capabilities of the RSM.

Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model

Energy Technology Data Exchange (ETDEWEB)

Rossi, R; Gallagher, B; Neville, J; Henderson, K

2011-11-11

Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied our model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.

Effects of marine microbial biofilms on the biocide release rate from antifouling paints – A model-based analysis

DEFF Research Database (Denmark)

Yebra, Diego Meseguer; Kiil, Søren; Erik Weinell, Claus

2006-01-01

The antifouling (AF) paint model of Kiil et al. [S. Kiil, C.E. Weinell, M.S. Pedersen, K. Dam-Johansen, Analysis of self-polishing antifouling paints using rotary experiments and mathematical modelling, Ind. Eng. Chem. Res. 40 (2001) 3906-3920] and the simplified biofilm. growth model of Gujer...... and Warmer [W. Gujer, O. Warmer, Modeling mixed population biofilms, in: W.G. Characklis, K.C. Marshall (Eds.), Biofilms, Wiley-Interscience, New York, 1990] are used to provide a reaction engineering-based insight to the effects of marine microbial slimes on biocide leaching and, to a minor extent...

Job-mix modeling and system analysis of an aerospace multiprocessor.

Science.gov (United States)

Mallach, E. G.

1972-01-01

An aerospace guidance computer organization, consisting of multiple processors and memory units attached to a central time-multiplexed data bus, is described. A job mix for this type of computer is obtained by analysis of Apollo mission programs. Multiprocessor performance is then analyzed using: 1) queuing theory, under certain 'limiting case' assumptions; 2) Markov process methods; and 3) system simulation. Results of the analyses indicate: 1) Markov process analysis is a useful and efficient predictor of simulation results; 2) efficient job execution is not seriously impaired even when the system is so overloaded that new jobs are inordinately delayed in starting; 3) job scheduling is significant in determining system performance; and 4) a system having many slow processors may or may not perform better than a system of equal power having few fast processors, but will not perform significantly worse.

Modeling molecular mixing in a spatially inhomogeneous turbulent flow

Science.gov (United States)

Meyer, Daniel W.; Deb, Rajdeep

2012-02-01

Simulations of spatially inhomogeneous turbulent mixing in decaying grid turbulence with a joint velocity-concentration probability density function (PDF) method were conducted. The inert mixing scenario involves three streams with different compositions. The mixing model of Meyer ["A new particle interaction mixing model for turbulent dispersion and turbulent reactive flows," Phys. Fluids 22(3), 035103 (2010)], the interaction by exchange with the mean (IEM) model and its velocity-conditional variant, i.e., the IECM model, were applied. For reference, the direct numerical simulation data provided by Sawford and de Bruyn Kops ["Direct numerical simulation and lagrangian modeling of joint scalar statistics in ternary mixing," Phys. Fluids 20(9), 095106 (2008)] was used. It was found that velocity conditioning is essential to obtain accurate concentration PDF predictions. Moreover, the model of Meyer provides significantly better results compared to the IECM model at comparable computational expense.

Meta-Analysis of Effect Sizes Reported at Multiple Time Points Using General Linear Mixed Model

Science.gov (United States)

Musekiwa, Alfred; Manda, Samuel O. M.; Mwambi, Henry G.; Chen, Ding-Geng

2016-01-01

Meta-analysis of longitudinal studies combines effect sizes measured at pre-determined time points. The most common approach involves performing separate univariate meta-analyses at individual time points. This simplistic approach ignores dependence between longitudinal effect sizes, which might result in less precise parameter estimates. In this paper, we show how to conduct a meta-analysis of longitudinal effect sizes where we contrast different covariance structures for dependence between effect sizes, both within and between studies. We propose new combinations of covariance structures for the dependence between effect size and utilize a practical example involving meta-analysis of 17 trials comparing postoperative treatments for a type of cancer, where survival is measured at 6, 12, 18 and 24 months post randomization. Although the results from this particular data set show the benefit of accounting for within-study serial correlation between effect sizes, simulations are required to confirm these results. PMID:27798661

Simultaneous injection effective mixing flow analysis of urinary albumin using dye-binding reaction.

Science.gov (United States)

Ratanawimarnwong, Nuanlaor; Ponhong, Kraingkrai; Teshima, Norio; Nacapricha, Duangjai; Grudpan, Kate; Sakai, Tadao; Motomizu, Shoji

2012-07-15

A new four-channel simultaneous injection effective mixing flow analysis (SIEMA) system has been assembled for the determination of urinary albumin. The SIEMA system consisted of a syringe pump, two 5-way cross connectors, four holding coils, five 3-way solenoid valves, a 50-cm long mixing coil and a spectrophotometer. Tetrabromophenol blue anion (TBPB) in Triton X-100 micelle reacted with albumin at pH 3.2 to form a blue ion complex with a λ(max) 625nm. TBPB, Triton X-100, acetate buffer and albumin standard solutions were aspirated into four individual holding coils by a syringe pump and then the aspirated zones were simultaneously pushed in the reverse direction to the detector flow cell. Baseline drift, due to adsorption of TBPB-albumin complex on the wall of the hydrophobic PTFE tubing, was minimized by aspiration of Triton X-100 and acetate buffer solutions between samples. The calibration graph was linear in the range of 10-50μg/mL and the detection limit for albumin (3σ) was 0.53μg/mL. The RSD (n=11) at 30μg/mL was 1.35%. The sample throughput was 37/h. With a 10-fold dilution, interference from urine matrix was removed. The proposed method has advantages in terms of simple automation operation and short analysis time. Copyright © 2012 Elsevier B.V. All rights reserved.

Design and Analysis of Fused Deposition Modeling 3D Printer Nozzle for Color Mixing

Directory of Open Access Journals (Sweden)

Shanling Han

2017-01-01

Full Text Available Fused deposition modeling (FDM has been one of the most widely used rapid prototyping (RP technologies leading to the increase in market attention. Obviously it is desirable to print 3D objects; however, existing FDM printers are restricted to printing only monochrome objects because of the entry-level nozzle structure, and literature on the topic is also sparse. In this paper, the CAD model of the nozzle is established first by UG (Unigraphics NX software to show the structure of fused deposition modeling 3D printer nozzle for color mixing. Second, the flow channel model of the nozzle is extracted and simplified. Then, the CAD and finite element model are established by UG and ICEM CFD software, respectively, to prepare for the simulation. The flow field is simulated by Fluent software. The nozzle’s suitable temperature at different extrusion speeds is obtained, and the reason for the blockage at the intersection of the heating block is revealed. Finally, test verification of the nozzle is performed, which can produce mixed-color artifacts stably.

A detailed aerosol mixing state model for investigating interactions between mixing state, semivolatile partitioning, and coagulation

OpenAIRE

J. Lu; F. M. Bowman

2010-01-01

A new method for describing externally mixed particles, the Detailed Aerosol Mixing State (DAMS) representation, is presented in this study. This novel method classifies aerosols by both composition and size, using a user-specified mixing criterion to define boundaries between compositional populations. Interactions between aerosol mixing state, semivolatile partitioning, and coagulation are investigated with a Lagrangian box model that incorporates the DAMS approach. Model results predict th...

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

Science.gov (United States)

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

2015-04-01

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

EXPERIMENTAL DESIGN AND RESPONSE SURFACE MODELING OF PI/PES-ZEOLITE 4A MIXED MATRIX MEMBRANE FOR CO2 SEPARATION

Directory of Open Access Journals (Sweden)

T. D. KUSWORO

2015-09-01

Full Text Available This paper investigates the effect of preparation of polyimide/polyethersulfone (PI/PES blending-zeolite mixed matrix membrane through the manipulation of membrane production variables such as polymer concentration, blending composition and zeolite loading. Combination of central composite design and response surface methodology were applied to determine the main effect and interaction effects of these variables on membrane separation performance. The quadratic models between each response and the independent parameters were developed and the response surface models were tested with analysis of variance (ANOVA. In this study, PI/ (PES–zeolite 4A mixed matrix membranes were casted using dry/wet phase inversion technique. The separation performance of mixed matrix membrane had been tested using pure gases such as CO2 and CH4. The results showed that zeolite loading was the most significant variable that influenced the CO2/CH4 selectivity among three variables and the experimental results were in good agreement with those predicted by the proposed regression models. The gas separation performance of the membrane was relatively higher as compare to polymeric membrane. Therefore, combination of central composite design and response surface methodology can be used to prepare optimal condition for mixed matrix membrane fabrication. The incorporation of 20 wt% zeolite 4A into 25 wt% of PI/PES matrix had resulted in a high separation performance of membrane material.

A Mixed Land Cover Spatio-temporal Data Model Based on Object-oriented and Snapshot

Directory of Open Access Journals (Sweden)

LI Yinchao

2016-07-01

Full Text Available Spatio-temporal data model (STDM is one of the hot topics in the domains of spatio-temporal database and data analysis. There is a common view that a universal STDM is always of high complexity due to the various situation of spatio-temporal data. In this article, a mixed STDM is proposed based on object-oriented and snapshot models for modelling and analyzing landcover change (LCC. This model uses the object-oriented STDM to describe the spatio-temporal processes of land cover patches and organize their spatial and attributive properties. In the meantime, it uses the snapshot STDM to present the spatio-temporal distribution of LCC on the whole via snapshot images. The two types of models are spatially and temporally combined into a mixed version. In addition to presenting the spatio-temporal events themselves, this model could express the transformation events between different classes of spatio-temporal objects. It can be used to create database for historical data of LCC, do spatio-temporal statistics, simulation and data mining with the data. In this article, the LCC data in Heilongjiang province is used for case study to validate spatio-temporal data management and analysis abilities of mixed STDM, including creating database, spatio-temporal query, global evolution analysis and patches spatio-temporal process expression.

Modeling of Cd(II) sorption on mixed oxide

International Nuclear Information System (INIS)

Waseem, M.; Mustafa, S.; Naeem, A.; Shah, K.H.; Hussain, S.Y.; Safdar, M.

2011-01-01

Mixed oxide of iron and silicon (0.75 M Fe(OH)3:0.25 M SiO/sub 2/) was synthesized and characterized by various techniques like surface area analysis, point of zero charge (PZC), energy dispersive X-rays (EDX) spectroscopy, Thermogravimetric and differential thermal analysis (TG-DTA), Fourier transform infrared spectroscopy (FTIR) and X-rays diffraction (XRD) analysis. The uptake of Cd/sup 2+/ ions on mixed oxide increased with pH, temperature and metal ion concentration. Sorption data have been interpreted in terms of both Langmuir and Freundlich models. The Xm values at pH 7 are found to be almost twice as compared to pH 5. The values of both DH and DS were found to be positive indicating that the sorption process was endothermic and accompanied by the dehydration of Cd/sup 2+/. Further, the negative value of DG confirms the spontaneity of the reaction. The ion exchange mechanism was suggested to take place for each Cd/sup 2+/ ions at pH 5, whereas ion exchange was found coupled with non specific adsorption of metal cations at pH 7. (author)

The Relaxation Matrix for Symmetric Tops with Inversion Symmetry. II; Line Mixing Effects in the V1 Band of NH3

Science.gov (United States)

Boulet, C.; Ma, Q.

2016-01-01

Line mixing effects have been calculated in the ?1 parallel band of self-broadened NH3. The theoretical approach is an extension of a semi-classical model to symmetric-top molecules with inversion symmetry developed in the companion paper [Q. Ma and C. Boulet, J. Chem. Phys. 144, 224303 (2016)]. This model takes into account line coupling effects and hence enables the calculation of the entire relaxation matrix. A detailed analysis of the various coupling mechanisms is carried out for Q and R inversion doublets. The model has been applied to the calculation of the shape of the Q branch and of some R manifolds for which an obvious signature of line mixing effects has been experimentally demonstrated. Comparisons with measurements show that the present formalism leads to an accurate prediction of the available experimental line shapes. Discrepancies between the experimental and theoretical sets of first order mixing parameters are discussed as well as some extensions of both theory and experiment.

Mixing characterisation of full-scale membrane bioreactors: CFD modelling with experimental validation.

Science.gov (United States)

Brannock, M; Wang, Y; Leslie, G

2010-05-01

Membrane Bioreactors (MBRs) have been successfully used in aerobic biological wastewater treatment to solve the perennial problem of effective solids-liquid separation. The optimisation of MBRs requires knowledge of the membrane fouling, biokinetics and mixing. However, research has mainly concentrated on the fouling and biokinetics (Ng and Kim, 2007). Current methods of design for a desired flow regime within MBRs are largely based on assumptions (e.g. complete mixing of tanks) and empirical techniques (e.g. specific mixing energy). However, it is difficult to predict how sludge rheology and vessel design in full-scale installations affects hydrodynamics, hence overall performance. Computational Fluid Dynamics (CFD) provides a method for prediction of how vessel features and mixing energy usage affect the hydrodynamics. In this study, a CFD model was developed which accounts for aeration, sludge rheology and geometry (i.e. bioreactor and membrane module). This MBR CFD model was then applied to two full-scale MBRs and was successfully validated against experimental results. The effect of sludge settling and rheology was found to have a minimal impact on the bulk mixing (i.e. the residence time distribution).

Sensitivity studies of different aerosol indirect effects in mixed-phase clouds

Directory of Open Access Journals (Sweden)

C. Hoose

2009-11-01

Full Text Available Aerosols affect the climate system by changing cloud characteristics. Using the global climate model ECHAM5-HAM, we investigate different aerosol effects on mixed-phase clouds: The glaciation effect, which refers to a more frequent glaciation due to anthropogenic aerosols, versus the de-activation effect, which suggests that ice nuclei become less effective because of an anthropogenic sulfate coating. The glaciation effect can partly offset the indirect aerosol effect on warm clouds and thus causes the total anthropogenic aerosol effect to be smaller. It is investigated by varying the parameterization for the Bergeron-Findeisen process and the threshold coating thickness of sulfate (SO₄-crit, which is required to convert an externally mixed aerosol particle into an internally mixed particle. Differences in the net radiation at the top-of-the-atmosphere due to anthropogenic aerosols between the different sensitivity studies amount up to 0.5 W m⁻². This suggests that the investigated mixed-phase processes have a major effect on the total anthropogenic aerosol effect.

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

Science.gov (United States)

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

Mixed-effects and fMRI studies

DEFF Research Database (Denmark)

Friston, K.J; Stephan, K.E; Ellegaard Lund, Torben

2005-01-01

This note concerns mixed-effect (MFX) analyses in multisession functional magnetic resonance imaging (fMRI) studies. It clarifies the relationship between mixed-effect analyses and the two-stage 'summary statistics' procedure (Holmes, A.P., Friston, K.J., 1998. Generalisability, random effects...

Performance Degradation Analysis of Aviation Hydraulic Piston Pump Based on Mixed Wear Theory

Directory of Open Access Journals (Sweden)

C. Zhang

2017-06-01

Full Text Available This paper focuses on the mathematical modeling of axial piston pump through dividing the failure development of friction pair into lubrication, mixed lubrication and abrasion. Directing to the wedge-shaped oil film between cylinder block and valve plate, the support force distribution under the temperature variance was obtained. Considering the rough peak of valve plate, the contact load model is built under plastic deformation and elastic deformation and the corresponding wear volume is calculated. Computing the wear and tear along the counter-clockwise, the total amount of friction and wear can be calculated. Simulation and preliminary wear particle monitoring test indicates that proposed modeling and analysis can effectively reflect the real abrasion process of hydraulic piston pump.

Monte Carlo simulation of OLS and linear mixed model inference of phenotypic effects on gene expression.

Science.gov (United States)

Walker, Jeffrey A

2016-01-01

Self-contained tests estimate and test the association between a phenotype and mean expression level in a gene set defined a priori . Many self-contained gene set analysis methods have been developed but the performance of these methods for phenotypes that are continuous rather than discrete and with multiple nuisance covariates has not been well studied. Here, I use Monte Carlo simulation to evaluate the performance of both novel and previously published (and readily available via R) methods for inferring effects of a continuous predictor on mean expression in the presence of nuisance covariates. The motivating data are a high-profile dataset which was used to show opposing effects of hedonic and eudaimonic well-being (or happiness) on the mean expression level of a set of genes that has been correlated with social adversity (the CTRA gene set). The original analysis of these data used a linear model (GLS) of fixed effects with correlated error to infer effects of Hedonia and Eudaimonia on mean CTRA expression. The standardized effects of Hedonia and Eudaimonia on CTRA gene set expression estimated by GLS were compared to estimates using multivariate (OLS) linear models and generalized estimating equation (GEE) models. The OLS estimates were tested using O'Brien's OLS test, Anderson's permutation [Formula: see text]-test, two permutation F -tests (including GlobalAncova), and a rotation z -test (Roast). The GEE estimates were tested using a Wald test with robust standard errors. The performance (Type I, II, S, and M errors) of all tests was investigated using a Monte Carlo simulation of data explicitly modeled on the re-analyzed dataset. GLS estimates are inconsistent between data sets, and, in each dataset, at least one coefficient is large and highly statistically significant. By contrast, effects estimated by OLS or GEE are very small, especially relative to the standard errors. Bootstrap and permutation GLS distributions suggest that the GLS results in

Monte Carlo simulation of OLS and linear mixed model inference of phenotypic effects on gene expression

Directory of Open Access Journals (Sweden)

Jeffrey A. Walker

2016-10-01

Full Text Available Background Self-contained tests estimate and test the association between a phenotype and mean expression level in a gene set defined a priori. Many self-contained gene set analysis methods have been developed but the performance of these methods for phenotypes that are continuous rather than discrete and with multiple nuisance covariates has not been well studied. Here, I use Monte Carlo simulation to evaluate the performance of both novel and previously published (and readily available via R methods for inferring effects of a continuous predictor on mean expression in the presence of nuisance covariates. The motivating data are a high-profile dataset which was used to show opposing effects of hedonic and eudaimonic well-being (or happiness on the mean expression level of a set of genes that has been correlated with social adversity (the CTRA gene set. The original analysis of these data used a linear model (GLS of fixed effects with correlated error to infer effects of Hedonia and Eudaimonia on mean CTRA expression. Methods The standardized effects of Hedonia and Eudaimonia on CTRA gene set expression estimated by GLS were compared to estimates using multivariate (OLS linear models and generalized estimating equation (GEE models. The OLS estimates were tested using O’Brien’s OLS test, Anderson’s permutation ${r}_{F}^{2}$ r F 2 -test, two permutation F-tests (including GlobalAncova, and a rotation z-test (Roast. The GEE estimates were tested using a Wald test with robust standard errors. The performance (Type I, II, S, and M errors of all tests was investigated using a Monte Carlo simulation of data explicitly modeled on the re-analyzed dataset. Results GLS estimates are inconsistent between data sets, and, in each dataset, at least one coefficient is large and highly statistically significant. By contrast, effects estimated by OLS or GEE are very small, especially relative to the standard errors. Bootstrap and permutation GLS

Moyer's method of mixed dentition analysis: a meta-analysis ...

African Journals Online (AJOL)

The applicability of tables derived from the data Moyer used to other ethnic groups has ... This implies that Moyer's method of prediction may have population variations. ... Key Words: meta-analysis, mixed dentition analysis, Moyer's method

Analyzing the Mixing Dynamics of an Industrial Batch Bin Blender via Discrete Element Modeling Method

Directory of Open Access Journals (Sweden)

Maitraye Sen

2017-04-01

Full Text Available A discrete element model (DEM has been developed for an industrial batch bin blender in which three different types of materials are mixed. The mixing dynamics have been evaluated from a model-based study with respect to the blend critical quality attributes (CQAs which are relative standard deviation (RSD and segregation intensity. In the actual industrial setup, a sensor mounted on the blender lid is used to determine the blend composition in this region. A model-based analysis has been used to understand the mixing efficiency in the other zones inside the blender and to determine if the data obtained near the blender-lid region are able to provide a good representation of the overall blend quality. Sub-optimal mixing zones have been identified and other potential sampling locations have been investigated in order to obtain a good approximation of the blend variability. The model has been used to study how the mixing efficiency can be improved by varying the key processing parameters, i.e., blender RPM/speed, fill level/volume and loading order. Both segregation intensity and RSD reduce at a lower fill level and higher blender RPM and are a function of the mixing time. This work demonstrates the use of a model-based approach to improve process knowledge regarding a pharmaceutical mixing process. The model can be used to acquire qualitative information about the influence of different critical process parameters and equipment geometry on the mixing dynamics.

Multivariate genetic divergence among sugarcane clones by multivariate analysis associated with mixed models

Directory of Open Access Journals (Sweden)

Valéria Rosa Lopes

2014-02-01

Full Text Available This work had the aim to evaluate the genetic divergence in sugarcane clones using the methodology of graphic dispersion by principal components analysis associated to linear mixed models, indentifying the more divergent and productive genotypes with more precision, for a subsequent combination. 138 sugarcane clones of the RB97 series of the Sugarcane Breeding Program of the Universidade Federal do Parana, more two standard cultivars were evaluated in three environments, with two replications. The two first components explained 96% of the total variation, sufficiently for explaining the divergence found. The variable that contributed the most to de divergence was kilogram of brix per plot (BKP followed by brix, mass of 10 stalks and number of stalks per plot. The more divergent sugarcane clones were RB975008, RB975112, RB975019, RB975153 and RB975067 and the more productive clones were RB975269, RB977533, RB975102, RB975317 and RB975038.

Modeling the oxygen uptake kinetics during exercise testing of patients with chronic obstructive pulmonary diseases using nonlinear mixed models

DEFF Research Database (Denmark)

Baty, Florent; Ritz, Christian; van Gestel, Arnoldus

2016-01-01

describe functionality of the R package medrc that extends the framework of the commonly used packages drc and nlme and allows fitting nonlinear mixed effects models for automated nonlinear regression modeling. The methodology was applied to a data set including 6MWT [Formula: see text]O2 kinetics from 61...... patients with chronic obstructive pulmonary disease (disease severity stage II to IV). The mixed effects approach was compared to a traditional curve-by-curve approach. RESULTS: A six-parameter nonlinear regression model was jointly fitted to the set of [Formula: see text]O2 kinetics. Significant...

Prediction of stock markets by the evolutionary mix-game model

Science.gov (United States)

Chen, Fang; Gou, Chengling; Guo, Xiaoqian; Gao, Jieping

2008-06-01

This paper presents the efforts of using the evolutionary mix-game model, which is a modified form of the agent-based mix-game model, to predict financial time series. Here, we have carried out three methods to improve the original mix-game model by adding the abilities of strategy evolution to agents, and then applying the new model referred to as the evolutionary mix-game model to forecast the Shanghai Stock Exchange Composite Index. The results show that these modifications can improve the accuracy of prediction greatly when proper parameters are chosen.

Mathematical model and metaheuristics for simultaneous balancing and sequencing of a robotic mixed-model assembly line

Science.gov (United States)

Li, Zixiang; Janardhanan, Mukund Nilakantan; Tang, Qiuhua; Nielsen, Peter

2018-05-01

This article presents the first method to simultaneously balance and sequence robotic mixed-model assembly lines (RMALB/S), which involves three sub-problems: task assignment, model sequencing and robot allocation. A new mixed-integer programming model is developed to minimize makespan and, using CPLEX solver, small-size problems are solved for optimality. Two metaheuristics, the restarted simulated annealing algorithm and co-evolutionary algorithm, are developed and improved to address this NP-hard problem. The restarted simulated annealing method replaces the current temperature with a new temperature to restart the search process. The co-evolutionary method uses a restart mechanism to generate a new population by modifying several vectors simultaneously. The proposed algorithms are tested on a set of benchmark problems and compared with five other high-performing metaheuristics. The proposed algorithms outperform their original editions and the benchmarked methods. The proposed algorithms are able to solve the balancing and sequencing problem of a robotic mixed-model assembly line effectively and efficiently.

Development of a transverse mixing model for large scale impulsion phenomenon in tight lattice

International Nuclear Information System (INIS)

Liu, Xiaojing; Ren, Shuo; Cheng, Xu

2017-01-01

Highlights: • Experiment data of Krauss is used to validate the feasibility of CFD simulation method. • CFD simulation is performed to simulate the large scale impulsion phenomenon for tight-lattice bundle. • A mixing model to simulate the large scale impulsion phenomenon is proposed based on CFD result fitting. • The new developed mixing model has been added in the subchannel code. - Abstract: Tight-lattice is widely adopted in the innovative reactor fuel bundles design since it can increase the conversion ratio and improve the heat transfer between fuel bundles and coolant. It has been noticed that a large scale impulsion of cross-velocity exists in the gap region, which plays an important role on the transverse mixing flow and heat transfer. Although many experiments and numerical simulation have been carried out to study the impulsion of velocity, a model to describe the wave length, amplitude and frequency of mixing coefficient is still missing. This research work takes advantage of the CFD method to simulate the experiment of Krauss and to compare experiment data and simulation result in order to demonstrate the feasibility of simulation method and turbulence model. Then, based on this verified method and model, several simulations are performed with different Reynolds number and different Pitch-to-Diameter ratio. By fitting the CFD results achieved, a mixing model to simulate the large scale impulsion phenomenon is proposed and adopted in the current subchannel code. The new mixing model is applied to some fuel assembly analysis by subchannel calculation, it can be noticed that the new developed mixing model can reduce the hot channel factor and contribute to a uniform distribution of outlet temperature.

Effects of two-phase mixing and void drift models on subchannel void fraction predictions in vertical bundles

Energy Technology Data Exchange (ETDEWEB)

Leung, K.H. [McMaster Univ., Hamilton, Ontario (Canada)], E-mail: leungk4@mcmaster.ca

2009-07-01

The evaluation of the subchannel code ASSERT against the OECD/NEA BFBT benchmark data demonstrated that at low pressures, the void fraction in the corner and side subchannels of a vertical bundle was over-predicted. Preliminary results suggest that this was due to the use of Carlucci's empirical correlation for void drift beyond its applicable range of pressure. Further examination indicates that the choice of the mixing and void drift models has a negligible effect on the error of the subchannel void fraction predictions. A single, isolated subchannel was simulated and results suggest that the root cause behind the over-prediction is inadequate mixing at the sides and corners of the bundle. Increasing the magnitude of the void drift coefficients in Carlucci's model at low pressure was found to improve the overall accuracy of the predictions. A simple correlation relating {omega} to the outlet pressure was found to increase the number of points falling within experimental error by 1.0%. (author)

Effects of two-phase mixing and void drift models on subchannel void fraction predictions in vertical bundles

International Nuclear Information System (INIS)

Leung, K.H.

2009-01-01

The evaluation of the subchannel code ASSERT against the OECD/NEA BFBT benchmark data demonstrated that at low pressures, the void fraction in the corner and side subchannels of a vertical bundle was over-predicted. Preliminary results suggest that this was due to the use of Carlucci's empirical correlation for void drift beyond its applicable range of pressure. Further examination indicates that the choice of the mixing and void drift models has a negligible effect on the error of the subchannel void fraction predictions. A single, isolated subchannel was simulated and results suggest that the root cause behind the over-prediction is inadequate mixing at the sides and corners of the bundle. Increasing the magnitude of the void drift coefficients in Carlucci's model at low pressure was found to improve the overall accuracy of the predictions. A simple correlation relating Ω to the outlet pressure was found to increase the number of points falling within experimental error by 1.0%. (author)

Analysis of stratified flow mixing

International Nuclear Information System (INIS)

Soo, S.L.; Lyczkowski, R.W.

1985-01-01

The Creare 1/5-scale Phase II experiments which model fluid and thermal mixing of relatively cold high pressure injection (HPI) water into a cold leg of a full-scale pressurized water reactor (PWR) having loop flow are analyzed and found that they cannot achieve complete similarity with respect to characteristic Reynolds and Froude numbers and developing hydrodynamic entry length. Several analyses show that these experiments fall into two distinct regimes of mixing: momentum controlled and gravity controlled (stratification). 18 refs., 9 figs

Progress Report on SAM Reduced-Order Model Development for Thermal Stratification and Mixing during Reactor Transients

Energy Technology Data Exchange (ETDEWEB)

Hu, R. [Argonne National Lab. (ANL), Argonne, IL (United States)

2017-09-01

This report documents the initial progress on the reduced-order flow model developments in SAM for thermal stratification and mixing modeling. Two different modeling approaches are pursued. The first one is based on one-dimensional fluid equations with additional terms accounting for the thermal mixing from both flow circulations and turbulent mixing. The second approach is based on three-dimensional coarse-grid CFD approach, in which the full three-dimensional fluid conservation equations are modeled with closure models to account for the effects of turbulence.

Modeling vehicle operating speed on urban roads in Montreal: a panel mixed ordered probit fractional split model.

Science.gov (United States)

Eluru, Naveen; Chakour, Vincent; Chamberlain, Morgan; Miranda-Moreno, Luis F

2013-10-01

Vehicle operating speed measured on roadways is a critical component for a host of analysis in the transportation field including transportation safety, traffic flow modeling, roadway geometric design, vehicle emissions modeling, and road user route decisions. The current research effort contributes to the literature on examining vehicle speed on urban roads methodologically and substantively. In terms of methodology, we formulate a new econometric model framework for examining speed profiles. The proposed model is an ordered response formulation of a fractional split model. The ordered nature of the speed variable allows us to propose an ordered variant of the fractional split model in the literature. The proposed formulation allows us to model the proportion of vehicles traveling in each speed interval for the entire segment of roadway. We extend the model to allow the influence of exogenous variables to vary across the population. Further, we develop a panel mixed version of the fractional split model to account for the influence of site-specific unobserved effects. The paper contributes substantively by estimating the proposed model using a unique dataset from Montreal consisting of weekly speed data (collected in hourly intervals) for about 50 local roads and 70 arterial roads. We estimate separate models for local roads and arterial roads. The model estimation exercise considers a whole host of variables including geometric design attributes, roadway attributes, traffic characteristics and environmental factors. The model results highlight the role of various street characteristics including number of lanes, presence of parking, presence of sidewalks, vertical grade, and bicycle route on vehicle speed proportions. The results also highlight the presence of site-specific unobserved effects influencing the speed distribution. The parameters from the modeling exercise are validated using a hold-out sample not considered for model estimation. The results indicate

Black carbon mixing state impacts on cloud microphysical properties: effects of aerosol plume and environmental conditions

Energy Technology Data Exchange (ETDEWEB)

Ching, Ping Pui; Riemer, Nicole; West, Matthew

2016-05-27

Black carbon (BC) is usually mixed with other aerosol species within individual aerosol particles. This mixture, along with the particles' size and morphology, determines the particles' optical and cloud condensation nuclei properties, and hence black carbon's climate impacts. In this study the particle-resolved aerosol model PartMC-MOSAIC was used to quantify the importance of black carbon mixing state for predicting cloud microphysical quantities. Based on a set of about 100 cloud parcel simulations a process level analysis framework was developed to attribute the response in cloud microphysical properties to changes in the underlying aerosol population ("plume effect") and the cloud parcel cooling rate ("parcel effect"). It shows that the response of cloud droplet number concentration to changes in BC emissions depends on the BC mixing state. When the aerosol population contains mainly aged BC particles an increase in BC emission results in increasing cloud droplet number concentrations ("additive effect"). In contrast, when the aerosol population contains mainly fresh BC particles they act as sinks for condensable gaseous species, resulting in a decrease in cloud droplet number concentration as BC emissions are increased ("competition effect"). Additionally, we quantified the error in cloud microphysical quantities when neglecting the information on BC mixing state, which is often done in aerosol models. The errors ranged from -12% to +45% for the cloud droplet number fraction, from 0% to +1022% for the nucleation-scavenged black carbon (BC) mass fraction, from -12% to +4% for the effective radius, and from -30% to +60% for the relative dispersion.

Visualizing multifactorial and multi-attribute effect sizes in linear mixed models with a view towards sensometrics

DEFF Research Database (Denmark)

and straightforward idea is to interpret effects relative to the residual error and to choose the proper effect size measure. For multi-attribute bar plots of F-statistics this amounts, in balanced settings, to a simple transformation of the bar heights to get them transformed into depicting what can be seen...... on a multifactorial sensory profile data set and compared to actual d-prime calculations based on ordinal regression modelling through the ordinal package. A generic ``plug-in'' implementation of the method is given in the SensMixed package, which again depends on the lmerTest package. We discuss and clarify the bias...

Detailed analysis of coolant mixing in WWER-440 fuel assembly heads

International Nuclear Information System (INIS)

Toth, S.; Aszodi, A.

2008-01-01

Based on experiences of former validation and sensitivity studies, a CFD model for head part of real working fuel assemblies with pitch of 12.3 mm has been developed with the code ANSYS CFX. Calculations were performed for typical fuel assemblies used in the Paks NPP. Differences between the outlet average temperatures and thermocouple signals were determined. Effect of the mixing grid position on thermocouple signal was investigated also. Mixing was analyzed in details with using so-called mixing scalars and weight factors of the central tube and rod bundle regions for in-core thermocouple signal were determined. Sensitivity of the weight factors for pin power distribution and mixing grid position were investigated. (Authors)

Mathematical study of mixing models

International Nuclear Information System (INIS)

Lagoutiere, F.; Despres, B.

1999-01-01

This report presents the construction and the study of a class of models that describe the behavior of compressible and non-reactive Eulerian fluid mixtures. Mixture models can have two different applications. Either they are used to describe physical mixtures, in the case of a true zone of extensive mixing (but then this modelization is incomplete and must be considered only as a point of departure for the elaboration of models of mixtures actually relevant). Either they are used to solve the problem of the numerical mixture. This problem appears during the discretization of an interface which separates fluids having laws of different state: the zone of numerical mixing is the set of meshes which cover the interface. The attention is focused on numerical mixtures, for which the hypothesis of non-miscibility (physics) will bring two equations (the sixth and the eighth of the system). It is important to emphasize that even in the case of the only numerical mixture, the presence in one and same place (same mesh) of several fluids have to be taken into account. This will be formalized by the possibility for mass fractions to take all values between 0 and 1. This is not at odds with the equations that derive from the hypothesis of non-miscibility. One way of looking at things is to consider that there are two scales of observation: the physical scale at which one observes the separation of fluids, and the numerical scale, given by the fineness of the mesh, to which a mixture appears. In this work, mixtures are considered from the mathematical angle (both in the elaboration phase and during their study). In particular, Chapter 5 shows a result of model degeneration for a non-extended mixing zone (case of an interface): this justifies the use of models in the case of numerical mixing. All these models are based on the classical model of non-viscous compressible fluids recalled in Chapter 2. In Chapter 3, the central point of the elaboration of the class of models is

Warped linear mixed models for the genetic analysis of transformed phenotypes.

Science.gov (United States)

Fusi, Nicolo; Lippert, Christoph; Lawrence, Neil D; Stegle, Oliver

2014-09-19

Linear mixed models (LMMs) are a powerful and established tool for studying genotype-phenotype relationships. A limitation of the LMM is that the model assumes Gaussian distributed residuals, a requirement that rarely holds in practice. Violations of this assumption can lead to false conclusions and loss in power. To mitigate this problem, it is common practice to pre-process the phenotypic values to make them as Gaussian as possible, for instance by applying logarithmic or other nonlinear transformations. Unfortunately, different phenotypes require different transformations, and choosing an appropriate transformation is challenging and subjective. Here we present an extension of the LMM that estimates an optimal transformation from the observed data. In simulations and applications to real data from human, mouse and yeast, we show that using transformations inferred by our model increases power in genome-wide association studies and increases the accuracy of heritability estimation and phenotype prediction.

A model of radiative neutrino masses. Mixing and a possible fourth generation

International Nuclear Information System (INIS)

Babu, K.S.; Ma, E.; Pantaleone, J.

1989-01-01

We consider the phenomenological consequences of a recently proposed model with four lepton generations such that the three known neutrinos have radiatively induced Majorana masses. Mixing among generations in the presence of a heavy fourth neutrino necessitates a reevaluation of the usual experimental tests of the standard model. One interesting possibility is to have a τ lifetime longer than predicted by the standard three-generation model. Another is to have neutrino masses and mixing angles in the range needed for a natural explanation of the solar-neutrino puzzle in terms of the Mikheyev-Smirnov-Wolfenstein effect. (orig.)

Effective delayed neutron fraction and prompt neutron lifetime of Tehran research reactor mixed-core

International Nuclear Information System (INIS)

Lashkari, A.; Khalafi, H.; Kazeminejad, H.

2013-01-01

Highlights: ► Kinetic parameters of Tehran research reactor mixed-core have been calculated. ► Burn-up effect on TRR kinetics parameters has been studied. ► Replacement of LEU-CFE with HEU-CFE in the TRR core has been investigated. ► Results of each mixed core were compared to the reference core. ► Calculation of kinetic parameters are necessary for reactivity and power excursion transient analysis. - Abstract: In this work, kinetic parameters of Tehran research reactor (TRR) mixed cores have been calculated. The mixed core configurations are made by replacement of the low enriched uranium control fuel elements with highly enriched uranium control fuel elements in the reference core. The MTR P C package, a nuclear reactor analysis tool, is used to perform the analysis. Simulations were carried out to compute effective delayed neutron fraction and prompt neutron lifetime. Calculation of kinetic parameters is necessary for reactivity and power excursion transient analysis. The results of this research show that effective delayed neutron fraction decreases and prompt neutron lifetime increases with the fuels burn-up. Also, by increasing the number of highly enriched uranium control fuel elements in the reference core, the prompt neutron lifetime increases, but effective delayed neutron fraction does not show any considerable change

Continuous synthesis of drug-loaded nanoparticles using microchannel emulsification and numerical modeling: effect of passive mixing

Directory of Open Access Journals (Sweden)

Ortiz de Solorzano I

2016-07-01

Full Text Available Isabel Ortiz de Solorzano,1,2,* Laura Uson,1,2,* Ane Larrea,1,2,* Mario Miana,3 Victor Sebastian,1,2 Manuel Arruebo1,2 1Department of Chemical Engineering and Environmental Technologies, Institute of Nanoscience of Aragon (INA, University of Zaragoza, 2CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN, Centro de Investigación Biomédica en Red, Madrid, 3ITAINNOVA, Instituto Tecnológico de Aragón, Materials & Components, Zaragoza, Spain *These authors contributed equally to this work Abstract: By using interdigital microfluidic reactors, monodisperse poly(d,l lactic-co-glycolic acid nanoparticles (NPs can be produced in a continuous manner and at a large scale (~10 g/h. An optimized synthesis protocol was obtained by selecting the appropriated passive mixer and fluid flow conditions to produce monodisperse NPs. A reduced NP polydispersity was obtained when using the microfluidic platform compared with the one obtained with NPs produced in a conventional discontinuous batch reactor. Cyclosporin, an immunosuppressant drug, was used as a model to validate the efficiency of the microfluidic platform to produce drug-loaded monodisperse poly(d,l lactic-co-glycolic acid NPs. The influence of the mixer geometries and temperatures were analyzed, and the experimental results were corroborated by using computational fluid dynamic three-dimensional simulations. Flow patterns, mixing times, and mixing efficiencies were calculated, and the model supported with experimental results. The progress of mixing in the interdigital mixer was quantified by using the volume fractions of the organic and aqueous phases used during the emulsification–evaporation process. The developed model and methods were applied to determine the required time for achieving a complete mixing in each microreactor at different fluid flow conditions, temperatures, and mixing rates. Keywords: microchannel emulsification, high-throughput synthesis, drug-loaded polymer

Research on ration selection of mixed absorbent solution for membrane air-conditioning system

International Nuclear Information System (INIS)

Li, Xiu-Wei; Zhang, Xiao-Song; Wang, Fang; Zhao, Xiao; Zhang, Zhuo

2015-01-01

Highlights: • We derive models of the membrane air-conditioning system with mixed absorbents. • We make analysis on system COP, cost-effectiveness and economy. • The paper provides a new method for ideal absorbent selection. • The solutes concentration of 50% achieves the best cost-effectiveness and the economy. - Abstract: Absorption air-conditioning system is a good alternative to vapor compression system for developing low carbon society. To improve the performance of the traditional absorption system, the membrane air-conditioning system is configured and its COP can reach as high as 6. Mixed absorbents are potential for cost reduction of the membrane system while maintaining a high COP. On the purpose of finding ideal mixed absorbent groups, this paper makes analysis on COP, cost-effectiveness and economy of the membrane system with mixed LiBr–CaCl 2 absorbent solution. The models of the system have been developed for the analysis. The results show the COP is higher for the absorbent groups with lower concentration of the total solute and higher concentration ratio of LiBr. It also reveals when the total solutes concentration is about 50%, it achieves the best cost-effectiveness and the economy. The process of the analysis provides a useful method for mixed absorbents selection

Laminar/transition sweeping flow-mixing model for wire-wrapped LMFBR assemblies

International Nuclear Information System (INIS)

Burns, K.F.; Rohsenow, W.M.; Todreas, N.E.

1980-07-01

Recent interest in analyzing the thermal hydraulic characteristics of LMFBR assemblies operating in the mixed convection regime motivates the extension of the aforementioned turbulent sweeping flow model to low Reynolds number flows. The accuracy to which knowledge of the mixing parameters is required has not been well determined, due to the increased influence of conduction and buoyancy effects with respect to energy transport at low Reynolds numbers. This study represents a best estimate attempt to correlate the existing low Reynolds number sweeping flow data. The laminar/transition model which is presented is expected to be useful in anayzing mixed convection conditions. However, the justification for making additional improvemements is contingent upon two factors. First, the ability of the proposed laminar/transition model to predict additional low Reynolds number sweeping flow data for other geometries needs to be investigated. Secondly, the sensitivity of temperature predictions to uncertainties in the values of the sweeping flow parameters should be quantified

Advanced exergoeconomic analysis of the multistage mixed refrigerant systems

International Nuclear Information System (INIS)

Mehrpooya, Mehdi; Ansarinasab, Hojat

2015-01-01

Highlights: • Advanced exergoeconomic analysis is performed for mixed refrigerant systems. • Cost of investment is divided into avoidable/unavoidable and endogenous/exogenous. • Results show that interactions between the components is not considerable. - Abstract: Advanced exergoeconomic analysis is applied on three multi stage mixed refrigerant liquefaction processes. They are propane precooled mixed refrigerant, dual mixed refrigerant and mixed fluid cascade. Cost of investment and exergy destruction for the components with high inefficiencies are divided into avoidable/unavoidable and endogenous/exogenous parts. According to the avoidable exergy destruction cost in propane precooled mixed refrigerant process, C-2 compressor with 455.5 ($/h), in dual mixed refrigerant process, C-1 compressor with 510.8 ($/h) and in mixed fluid cascade process, C-2/1 compressor with 338.8 ($/h) should be considered first. A comparison between the conventional and advanced exergoeconomic analysis is done by three important parameters: Exergy efficiency, exergoeconomic factor and total costs. Results show that interactions between the process components are not considerable because cost of investment and exergy destruction in most of them are endogenous. Exergy destruction cost of the compressors is avoidable while heat exchangers and air coolers destruction cost are unavoidable. Investment cost of heat exchangers and air coolers are avoidable while compressor’s are unavoidable

A Bayesian Approach to Functional Mixed Effect Modeling for Longitudinal Data with Binomial Outcomes

Science.gov (United States)

Kliethermes, Stephanie; Oleson, Jacob

2014-01-01

Longitudinal growth patterns are routinely seen in medical studies where individual and population growth is followed over a period of time. Many current methods for modeling growth presuppose a parametric relationship between the outcome and time (e.g., linear, quadratic); however, these relationships may not accurately capture growth over time. Functional mixed effects (FME) models provide flexibility in handling longitudinal data with nonparametric temporal trends. Although FME methods are well-developed for continuous, normally distributed outcome measures, nonparametric methods for handling categorical outcomes are limited. We consider the situation with binomially distributed longitudinal outcomes. Although percent correct data can be modeled assuming normality, estimates outside the parameter space are possible and thus estimated curves can be unrealistic. We propose a binomial FME model using Bayesian methodology to account for growth curves with binomial (percentage) outcomes. The usefulness of our methods is demonstrated using a longitudinal study of speech perception outcomes from cochlear implant users where we successfully model both the population and individual growth trajectories. Simulation studies also advocate the usefulness of the binomial model particularly when outcomes occur near the boundary of the probability parameter space and in situations with a small number of trials. PMID:24723495

The mixing effects for real gases and their mixtures

Science.gov (United States)

Gong, M. Q.; Luo, E. C.; Wu, J. F.

2004-10-01

The definitions of the adiabatic and isothermal mixing effects in the mixing processes of real gases were presented in this paper. Eight substances with boiling-point temperatures from cryogenic temperature to the ambient temperature were selected from the interest of low temperature refrigeration to study their binary and multicomponent mixing effects. Detailed analyses were made on the parameters of the mixing process to know their influences on mixing effects. Those parameters include the temperatures, pressures, and mole fraction ratios of pure substances before mixing. The results show that the maximum temperature variation occurs at the saturation state of each component in the mixing process. Those components with higher boiling-point temperatures have higher isothermal mixing effects. The maximum temperature variation which is defined as the adiabatic mixing effect can even reach up to 50 K, and the isothermal mixing effect can reach about 20 kJ/mol. The possible applications of the mixing cooling effect in both open cycle and closed cycle refrigeration systems were also discussed.

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

Science.gov (United States)

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.

Computer modeling of jet mixing in INEL waste tanks

International Nuclear Information System (INIS)

Meyer, P.A.

1994-01-01

The objective of this study is to examine the feasibility of using submerged jet mixing pumps to mobilize and suspend settled sludge materials in INEL High Level Radioactive Waste Tanks. Scenarios include removing the heel (a shallow liquid and sludge layer remaining after tank emptying processes) and mobilizing and suspending solids in full or partially full tanks. The approach used was to (1) briefly review jet mixing theory, (2) review erosion literature in order to identify and estimate important sludge characterization parameters (3) perform computer modeling of submerged liquid mixing jets in INEL tank geometries, (4) develop analytical models from which pump operating conditions and mixing times can be estimated, and (5) analyze model results to determine overall feasibility of using jet mixing pumps and make design recommendations

Modelling ice microphysics of mixed-phase clouds

Science.gov (United States)

Ahola, J.; Raatikainen, T.; Tonttila, J.; Romakkaniemi, S.; Kokkola, H.; Korhonen, H.

2017-12-01

The low-level Arctic mixed-phase clouds have a significant role for the Arctic climate due to their ability to absorb and reflect radiation. Since the climate change is amplified in polar areas, it is vital to apprehend the mixed-phase cloud processes. From a modelling point of view, this requires a high spatiotemporal resolution to capture turbulence and the relevant microphysical processes, which has shown to be difficult.In order to solve this problem about modelling mixed-phase clouds, a new ice microphysics description has been developed. The recently published large-eddy simulation cloud model UCLALES-SALSA offers a good base for a feasible solution (Tonttila et al., Geosci. Mod. Dev., 10:169-188, 2017). The model includes aerosol-cloud interactions described with a sectional SALSA module (Kokkola et al., Atmos. Chem. Phys., 8, 2469-2483, 2008), which represents a good compromise between detail and computational expense.Newly, the SALSA module has been upgraded to include also ice microphysics. The dynamical part of the model is based on well-known UCLA-LES model (Stevens et al., J. Atmos. Sci., 56, 3963-3984, 1999) which can be used to study cloud dynamics on a fine grid.The microphysical description of ice is sectional and the included processes consist of formation, growth and removal of ice and snow particles. Ice cloud particles are formed by parameterized homo- or heterogeneous nucleation. The growth mechanisms of ice particles and snow include coagulation and condensation of water vapor. Autoconversion from cloud ice particles to snow is parameterized. The removal of ice particles and snow happens by sedimentation and melting.The implementation of ice microphysics is tested by initializing the cloud simulation with atmospheric observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC). The results are compared to the model results shown in the paper of Ovchinnikov et al. (J. Adv. Model. Earth Syst., 6, 223-248, 2014) and they show a good

Effects of partitioned enthalpy of mixing on glass-forming ability

Energy Technology Data Exchange (ETDEWEB)

Song, Wen-Xiong; Zhao, Shi-Jin, E-mail: shijin.zhao@shu.edu.cn [Institute of Materials Science, Shanghai University, Shanghai 200072 (China)

2015-04-14

We explore the inherent reason at atomic level for the glass-forming ability of alloys by molecular simulation, in which the effect of partitioned enthalpy of mixing is studied. Based on Morse potential, we divide the enthalpy of mixing into three parts: the chemical part (Δ E{sub nn}), strain part (Δ E{sub strain}), and non-bond part (Δ E{sub nnn}). We find that a large negative Δ E{sub nn} value represents strong AB chemical bonding in AB alloy and is the driving force to form a local ordered structure, meanwhile the transformed local ordered structure needs to satisfy the condition (Δ E{sub nn}/2 + Δ E{sub strain}) < 0 to be stabilized. Understanding the chemical and strain parts of enthalpy of mixing is helpful to design a new metallic glass with a good glass forming ability. Moreover, two types of metallic glasses (i.e., “strain dominant” and “chemical dominant”) are classified according to the relative importance between chemical effect and strain effect, which enriches our knowledge of the forming mechanism of metallic glass. Finally, a soft sphere model is established, different from the common hard sphere model.

Prevention of chronic PTSD with early cognitive behavioral therapy. A meta-analysis using mixed-effects modeling.

Science.gov (United States)

Kliem, Sören; Kröger, Christoph

2013-11-01

Post-traumatic stress disorder (PTSD) is of great interest to public health, due to the high burden it places on both the individual and society. We meta-analyzed randomized-controlled trials to examine the effectiveness of early trauma-focused cognitive-behavioral treatment (TFCBT) for preventing chronic PTSD. Systematic bibliographic research was undertaken to find relevant literature from on-line databases (Pubmed, PsycINFO, Psyndex, Medline). Using a mixed-effect approach, we calculated effect sizes (ES) for the PTSD diagnoses (main outcome) as well as PTSD and depressive symptoms (secondary outcomes), respectively. Calculations of ES from pre-intervention to first follow-up assessment were based on 10 studies. A moderate effect (ES = 0.54) was found for the main outcome, whereas ES for secondary outcomes were predominantly small (ES = 0.27-0.45). The ES for the main outcome decreased to small (ES = 0.34) from first follow-up to long-term follow-up assessment. The mean dropout rate was 16.7% pre- to post-treatment. There was evidence for the impact of moderators on different outcomes (e.g., the number of sessions on PTSD symptoms). Future studies should include survivors of other trauma types (e.g., burn injuries) rather than predominantly survivors of accidents and physical assault, and should compare early TFCBT with other interventions that previously demonstrated effectiveness. Copyright © 2013 Elsevier Ltd. All rights reserved.

Modeling policy mix to improve the competitiveness of Indonesian palm oil industry

Energy Technology Data Exchange (ETDEWEB)

Silitonga, R. Y.H.; Siswanto, J.; Simatupang, T.; Bahagia, S.N.

2016-07-01

The purpose of this research is to develop a model that will explain the impact of government policies to the competitiveness of palm oil industry. The model involves two commodities in this industry, namely crude palm oil (CPO) and refined palm oil (RPO), each has different added value. The model built will define the behavior of government in controlling palm oil industry, and their interactions with macro-environment, in order to improve the competitiveness of the industry. Therefore the first step was to map the main activities in this industry using value chain analysis. After that a conceptual model was built, where the output of the model is competitiveness of the industry based on market share. The third step was model formulation. The model is then utilized to simulate the policy mix given by government in improving the competitiveness of Palm Oil Industry. The model was developed using only some policies which give direct impact to the competitiveness of the industry. For macro environment input, only price is considered in this model. The model can simulate the output of the industry for various government policies mix given to the industry. This research develops a model that can represent the structure and relationship between industry, government and macro environment, using value chain analysis and hierarchical multilevel system approach. (Author)

Modeling policy mix to improve the competitiveness of Indonesian palm oil industry

Directory of Open Access Journals (Sweden)

Roland Y H Silitonga

2016-04-01

Full Text Available Purpose: The purpose of this research is to develop a model that will explain the impact of government policies to the competitiveness of palm oil industry. The model involves two commodities in this industry, namely crude palm oil (CPO and refined palm oil (RPO, each has different added value. Design/methodology/approach: The model built will define the behavior of government in controlling palm oil industry, and their interactions with macro-environment, in order to improve the competitiveness of the industry. Therefore the first step was to map the main activities in this industry using value chain analysis. After that a conceptual model was built, where the output of the model is competitiveness of the industry based on market share. The third step was model formulation. The model is then utilized to simulate the policy mix given by government in improving the competitiveness of Palm Oil Industry. Research limitations/implications: The model was developed using only some policies which give direct impact to the competitiveness of the industry. For macro environment input, only price is considered in this model. Practical implications: The model can simulate the output of the industry for various government policies mix given to the industry. Originality/value: This research develops a model that can represent the structure and relationship between industry, government and macro environment, using value chain analysis and hierarchical multilevel system approach.

Evaluation of vertical coordinate and vertical mixing algorithms in the HYbrid-Coordinate Ocean Model (HYCOM)

Science.gov (United States)

Halliwell, George R.

Vertical coordinate and vertical mixing algorithms included in the HYbrid Coordinate Ocean Model (HYCOM) are evaluated in low-resolution climatological simulations of the Atlantic Ocean. The hybrid vertical coordinates are isopycnic in the deep ocean interior, but smoothly transition to level (pressure) coordinates near the ocean surface, to sigma coordinates in shallow water regions, and back again to level coordinates in very shallow water. By comparing simulations to climatology, the best model performance is realized using hybrid coordinates in conjunction with one of the three available differential vertical mixing models: the nonlocal K-Profile Parameterization, the NASA GISS level 2 turbulence closure, and the Mellor-Yamada level 2.5 turbulence closure. Good performance is also achieved using the quasi-slab Price-Weller-Pinkel dynamical instability model. Differences among these simulations are too small relative to other errors and biases to identify the "best" vertical mixing model for low-resolution climate simulations. Model performance deteriorates slightly when the Kraus-Turner slab mixed layer model is used with hybrid coordinates. This deterioration is smallest when solar radiation penetrates beneath the mixed layer and when shear instability mixing is included. A simulation performed using isopycnic coordinates to emulate the Miami Isopycnic Coordinate Ocean Model (MICOM), which uses Kraus-Turner mixing without penetrating shortwave radiation and shear instability mixing, demonstrates that the advantages of switching from isopycnic to hybrid coordinates and including more sophisticated turbulence closures outweigh the negative numerical effects of maintaining hybrid vertical coordinates.

Heats of Mixing Using an Isothermal Titration Calorimeter: Associated Thermal Effects

Directory of Open Access Journals (Sweden)

Fabiola Socorro

2009-06-01

Full Text Available The correct determination of the energy generated or absorbed in the sample cell of an Isothermal Titration Calorimeter (ITC requires a thorough analysis of the calorimetric signal. This means the identification and quantification of any thermal effect inherent to the working method. In this work, it is carried out a review on several thermal effects, studied by us in previous work, and which appear when an ITC is used for measuring the heats of mixing of liquids in a continuous mode. These effects are due to: (i the difference between the temperature of the injected liquid and the temperature of the mixture during the mixing process, (ii the increase of the liquid volume located in the mixing cell and (iii the stirring velocity. Besides, methods for the identification and quantification of the mentioned effects are suggested.

The Effects of Marketing Mix Elements on Brand Equity

OpenAIRE

Rajh, Edo

2006-01-01

The structural model of the effects of marketing mix elements on brand equity is defined in line with the existing theoretical findings. Research hypotheses are defined according to the identified structural model. In order to test the defined structural model and research hypotheses empirical research was conducted on the sample of undergraduate students of the Faculty of Economics and Business in Zagreb. Research results indicate that the structural model has an acceptable level of fit to t...

Effects of mixing on resolved and unresolved scales on stratospheric age of air

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S. Dietmüller

2017-06-01

Full Text Available Mean age of air (AoA is a widely used metric to describe the transport along the Brewer–Dobson circulation. We seek to untangle the effects of different processes on the simulation of AoA, using the chemistry–climate model EMAC (ECHAM/MESSy Atmospheric Chemistry and the Chemical Lagrangian Model of the Stratosphere (CLaMS. Here, the effects of residual transport and two-way mixing on AoA are calculated. To do so, we calculate the residual circulation transit time (RCTT. The difference of AoA and RCTT is defined as aging by mixing. However, as diffusion is also included in this difference, we further use a method to directly calculate aging by mixing on resolved scales. Comparing these two methods of calculating aging by mixing allows for separating the effect of unresolved aging by mixing (which we term aging by diffusion in the following in EMAC and CLaMS. We find that diffusion impacts AoA by making air older, but its contribution plays a minor role (order of 10 % in all simulations. However, due to the different advection schemes of the two models, aging by diffusion has a larger effect on AoA and mixing efficiency in EMAC, compared to CLaMS. Regarding the trends in AoA, in CLaMS the AoA trend is negative throughout the stratosphere except in the Northern Hemisphere middle stratosphere, consistent with observations. This slight positive trend is neither reproduced in a free-running nor in a nudged simulation with EMAC – in both simulations the AoA trend is negative throughout the stratosphere. Trends in AoA are mainly driven by the contributions of RCTT and aging by mixing, whereas the contribution of aging by diffusion plays a minor role.

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

Science.gov (United States)

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.

Efficient and robust estimation for longitudinal mixed models for binary data

DEFF Research Database (Denmark)

Holst, René

2009-01-01

This paper proposes a longitudinal mixed model for binary data. The model extends the classical Poisson trick, in which a binomial regression is fitted by switching to a Poisson framework. A recent estimating equations method for generalized linear longitudinal mixed models, called GEEP, is used...... as a vehicle for fitting the conditional Poisson regressions, given a latent process of serial correlated Tweedie variables. The regression parameters are estimated using a quasi-score method, whereas the dispersion and correlation parameters are estimated by use of bias-corrected Pearson-type estimating...... equations, using second moments only. Random effects are predicted by BLUPs. The method provides a computationally efficient and robust approach to the estimation of longitudinal clustered binary data and accommodates linear and non-linear models. A simulation study is used for validation and finally...

Numerical analysis of coolant mixing in the pressure vessel of WWER-440 type nuclear reactors

International Nuclear Information System (INIS)

Boros, I.; Aszodi, A.

2003-01-01

The precise description of the coolant mixing processes taking place in the reactor pressure vessel (RPV) of pressurized water nuclear reactors has an essential importance during power operation, as well as in case of incidental or accidental conditions. In this paper the detailed CFD model of the pressure vessel of a WWER-440 type reactor and calculations performed with this RPV model are presented. The CFD model of the pressure vessel contains all the important internal structural elements of the RPV. Sensitivity study on the effect of these elements was also carried out. Both steady-state and transient calculation were performed using the CFD code CFX-5.5.1. The results of the steady-state calculations give the so called mixing factors, i.e. the effect of each single primary loop at the core inlet. The mixing factors can be given for nominal circumstances (i.e. all main coolant pumps are working) or in case of less than six working MCPs. In order to validate the model the calculated mixing factors are compared with the values measured in the Paks NPP (Authors)

Using Swiss Webster mice to model Fetal Alcohol Spectrum Disorders (FASD): An analysis of multilevel time-to-event data through mixed-effects Cox proportional hazards models.

Science.gov (United States)

Chi, Peter; Aras, Radha; Martin, Katie; Favero, Carlita

2016-05-15

Fetal Alcohol Spectrum Disorders (FASD) collectively describes the constellation of effects resulting from human alcohol consumption during pregnancy. Even with public awareness, the incidence of FASD is estimated to be upwards of 5% in the general population and is becoming a global health problem. The physical, cognitive, and behavioral impairments of FASD are recapitulated in animal models. Recently rodent models utilizing voluntary drinking paradigms have been developed that accurately reflect moderate consumption, which makes up the majority of FASD cases. The range in severity of FASD characteristics reflects the frequency, dose, developmental timing, and individual susceptibility to alcohol exposure. As most rodent models of FASD use C57BL/6 mice, there is a need to expand the stocks of mice studied in order to more fully understand the complex neurobiology of this disorder. To that end, we allowed pregnant Swiss Webster mice to voluntarily drink ethanol via the drinking in the dark (DID) paradigm throughout their gestation period. Ethanol exposure did not alter gestational outcomes as determined by no significant differences in maternal weight gain, maternal liquid consumption, litter size, or pup weight at birth or weaning. Despite seemingly normal gestation, ethanol-exposed offspring exhibit significantly altered timing to achieve developmental milestones (surface righting, cliff aversion, and open field traversal), as analyzed through mixed-effects Cox proportional hazards models. These results confirm Swiss Webster mice as a viable option to study the incidence and causes of ethanol-induced neurobehavioral alterations during development. Future studies in our laboratory will investigate the brain regions and molecules responsible for these behavioral changes. Copyright © 2016. Published by Elsevier B.V.

Development of a Reduced-Order Three-Dimensional Flow Model for Thermal Mixing and Stratification Simulation during Reactor Transients

Energy Technology Data Exchange (ETDEWEB)

Hu, Rui

2017-09-03

Mixing, thermal-stratification, and mass transport phenomena in large pools or enclosures play major roles for the safety of reactor systems. Depending on the fidelity requirement and computational resources, various modeling methods, from the 0-D perfect mixing model to 3-D Computational Fluid Dynamics (CFD) models, are available. Each is associated with its own advantages and shortcomings. It is very desirable to develop an advanced and efficient thermal mixing and stratification modeling capability embedded in a modern system analysis code to improve the accuracy of reactor safety analyses and to reduce modeling uncertainties. An advanced system analysis tool, SAM, is being developed at Argonne National Laboratory for advanced non-LWR reactor safety analysis. While SAM is being developed as a system-level modeling and simulation tool, a reduced-order three-dimensional module is under development to model the multi-dimensional flow and thermal mixing and stratification in large enclosures of reactor systems. This paper provides an overview of the three-dimensional finite element flow model in SAM, including the governing equations, stabilization scheme, and solution methods. Additionally, several verification and validation tests are presented, including lid-driven cavity flow, natural convection inside a cavity, laminar flow in a channel of parallel plates. Based on the comparisons with the analytical solutions and experimental results, it is demonstrated that the developed 3-D fluid model can perform very well for a wide range of flow problems.

Mixed Beam Murine Harderian Gland Tumorigenesis: Predicted Dose-Effect Relationships if neither Synergism nor Antagonism Occurs

Energy Technology Data Exchange (ETDEWEB)

Siranart, Nopphon; Blakely, Eleanor A.; Cheng, Alden; Handa, Naval; Sachs, Rainer K.

2016-12-01

Complex mixed radiation fields exist in interplanetary space, and not much is known about their latent effects on space travelers. In silico synergy analysis default predictions are useful when planning relevant mixed-ion-beam experiments and interpreting their results. These predictions are based on individual dose-effect relationships (IDER) for each component of the mixed-ion beam, assuming no synergy or antagonism. For example, a default hypothesis of simple effect additivity has often been used throughout the study of biology. However, for more than a century pharmacologists interested in mixtures of therapeutic drugs have analyzed conceptual, mathematical and practical questions similar to those that arise when analyzing mixed radiation fields, and have shown that simple effect additivity often gives unreasonable predictions when the IDER are curvilinear. Various alternatives to simple effect additivity proposed in radiobiology, pharmacometrics, toxicology and other fields are also known to have important limitations. In this work, we analyze upcoming murine Harderian gland (HG) tumor prevalence mixed-beam experiments, using customized open-source software and published IDER from past single-ion experiments. The upcoming experiments will use acute irradiation and the mixed beam will include components of high atomic number and energy (HZE). We introduce a new alternative to simple effect additivity, "incremental effect additivity", which is more suitable for the HG analysis and perhaps for other end points. We use incremental effect additivity to calculate default predictions for mixture dose-effect relationships, including 95% confidence intervals. We have drawn three main conclusions from this work. 1. It is important to supplement mixed-beam experiments with single-ion experiments, with matching end point(s), shielding and dose timing. 2. For HG tumorigenesis due to a mixed beam, simple effect additivity and incremental effect additivity sometimes give

A Note on the Identifiability of Generalized Linear Mixed Models

DEFF Research Database (Denmark)

Labouriau, Rodrigo

2014-01-01

I present here a simple proof that, under general regularity conditions, the standard parametrization of generalized linear mixed model is identifiable. The proof is based on the assumptions of generalized linear mixed models on the first and second order moments and some general mild regularity...... conditions, and, therefore, is extensible to quasi-likelihood based generalized linear models. In particular, binomial and Poisson mixed models with dispersion parameter are identifiable when equipped with the standard parametrization...

Primary Student-Teachers' Conceptual Understanding of the Greenhouse Effect: A mixed method study

Science.gov (United States)

Ratinen, Ilkka Johannes

2013-04-01

The greenhouse effect is a reasonably complex scientific phenomenon which can be used as a model to examine students' conceptual understanding in science. Primary student-teachers' understanding of global environmental problems, such as climate change and ozone depletion, indicates that they have many misconceptions. The present mixed method study examines Finnish primary student-teachers' understanding of the greenhouse effect based on the results obtained via open-ended and closed-form questionnaires. The open-ended questionnaire considers primary student-teachers' spontaneous ideas about the greenhouse effect depicted by concept maps. The present study also uses statistical analysis to reveal respondents' conceptualization of the greenhouse effect. The concept maps and statistical analysis reveal that the primary student-teachers' factual knowledge and their conceptual understanding of the greenhouse effect are incomplete and even misleading. In the light of the results of the present study, proposals for modifying the instruction of climate change in science, especially in geography, are presented.

Functional linear models for association analysis of quantitative traits.

Science.gov (United States)

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

Mixed-waste pyrolysis of biomass and plastics waste – A modelling approach to reduce energy usage

International Nuclear Information System (INIS)

Oyedun, Adetoyese Olajire; Gebreegziabher, Tesfaldet; Ng, Denny K.S.; Hui, Chi Wai

2014-01-01