Model Selection with the Linear Mixed Model for Longitudinal Data

ERIC Educational Resources Information Center

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…

Application of mixing-controlled combustion models to gas turbine combustors

NASA Technical Reports Server (NTRS)

Nguyen, Hung Lee

1990-01-01

Gas emissions were studied from a staged Rich Burn/Quick-Quench Mix/Lean Burn combustor were studied under test conditions encountered in High Speed Research engines. The combustor was modeled at conditions corresponding to different engine power settings, and the effect of primary dilution airflow split on emissions, flow field, flame size and shape, and combustion intensity, as well as mixing, was investigated. A mathematical model was developed from a two-equation model of turbulence, a quasi-global kinetics mechanism for the oxidation of propane, and the Zeldovich mechanism for nitric oxide formation. A mixing-controlled combustion model was used to account for turbulent mixing effects on the chemical reaction rate. This model assumes that the chemical reaction rate is much faster than the turbulent mixing rate.

MIXOR: a computer program for mixed-effects ordinal regression analysis.

PubMed

Hedeker, D; Gibbons, R D

1996-03-01

MIXOR provides maximum marginal likelihood estimates for mixed-effects ordinal probit, logistic, and complementary log-log regression models. These models can be used for analysis of dichotomous and ordinal outcomes from either a clustered or longitudinal design. For clustered data, the mixed-effects model assumes that data within clusters are dependent. The degree of dependency is jointly estimated with the usual model parameters, thus adjusting for dependence resulting from clustering of the data. Similarly, for longitudinal data, the mixed-effects approach can allow for individual-varying intercepts and slopes across time, and can estimate the degree to which these time-related effects vary in the population of individuals. MIXOR uses marginal maximum likelihood estimation, utilizing a Fisher-scoring solution. For the scoring solution, the Cholesky factor of the random-effects variance-covariance matrix is estimated, along with the effects of model covariates. Examples illustrating usage and features of MIXOR are provided.

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

PubMed

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.

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

ERIC Educational Resources Information Center

Ker, H. W.

2014-01-01

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

Functional Mixed Effects Model for Small Area Estimation.

PubMed

Maiti, Tapabrata; Sinha, Samiran; Zhong, Ping-Shou

2016-09-01

Functional data analysis has become an important area of research due to its ability of handling high dimensional and complex data structures. However, the development is limited in the context of linear mixed effect models, and in particular, for small area estimation. The linear mixed effect models are the backbone of small area estimation. In this article, we consider area level data, and fit a varying coefficient linear mixed effect model where the varying coefficients are semi-parametrically modeled via B-splines. We propose a method of estimating the fixed effect parameters and consider prediction of random effects that can be implemented using a standard software. For measuring prediction uncertainties, we derive an analytical expression for the mean squared errors, and propose a method of estimating the mean squared errors. The procedure is illustrated via a real data example, and operating characteristics of the method are judged using finite sample simulation studies.

Mixed models and reduced/selective integration displacement models for nonlinear analysis of curved beams

NASA Technical Reports Server (NTRS)

Noor, A. K.; Peters, J. M.

1981-01-01

Simple mixed models are developed for use in the geometrically nonlinear analysis of deep arches. A total Lagrangian description of the arch deformation is used, the analytical formulation being based on a form of the nonlinear deep arch theory with the effects of transverse shear deformation included. The fundamental unknowns comprise the six internal forces and generalized displacements of the arch, and the element characteristic arrays are obtained by using Hellinger-Reissner mixed variational principle. The polynomial interpolation functions employed in approximating the forces are one degree lower than those used in approximating the displacements, and the forces are discontinuous at the interelement boundaries. Attention is given to the equivalence between the mixed models developed herein and displacement models based on reduced integration of both the transverse shear and extensional energy terms. The advantages of mixed models over equivalent displacement models are summarized. Numerical results are presented to demonstrate the high accuracy and effectiveness of the mixed models developed and to permit a comparison of their performance with that of other mixed models reported in the literature.

Eliciting mixed emotions: a meta-analysis comparing models, types, and measures.

PubMed

Berrios, Raul; Totterdell, Peter; Kellett, Stephen

2015-01-01

The idea that people can experience two oppositely valenced emotions has been controversial ever since early attempts to investigate the construct of mixed emotions. This meta-analysis examined the robustness with which mixed emotions have been elicited experimentally. A systematic literature search identified 63 experimental studies that instigated the experience of mixed emotions. Studies were distinguished according to the structure of the underlying affect model-dimensional or discrete-as well as according to the type of mixed emotions studied (e.g., happy-sad, fearful-happy, positive-negative). The meta-analysis using a random-effects model revealed a moderate to high effect size for the elicitation of mixed emotions (d IG+ = 0.77), which remained consistent regardless of the structure of the affect model, and across different types of mixed emotions. Several methodological and design moderators were tested. Studies using the minimum index (i.e., the minimum value between a pair of opposite valenced affects) resulted in smaller effect sizes, whereas subjective measures of mixed emotions increased the effect sizes. The presence of more women in the samples was also associated with larger effect sizes. The current study indicates that mixed emotions are a robust, measurable and non-artifactual experience. The results are discussed in terms of the implications for an affect system that has greater versatility and flexibility than previously thought.

Effect of electrode positions on the mixing characteristics of an electroosmotic micromixer.

PubMed

Seo, H S; Kim, Y J

2014-08-01

In this study, an electrokinetic microchannel with a ring-type mixing chamber is introduced for fast mixing. The modeled micromixer that is used for the study of the electroosmotic effect takes two fluids from different inlets and combines them in a ring-type mixing chamber and, then, they are mixed by the electric fields at the electrodes. In order to compare the mixing performance in the modeled micromixer, we numerically investigated the flow characteristics with different positions of the electrodes in the mixing chamber using the commercial code, COMSOL. In addition, we discussed the concentration distributions of the dissolved substances in the flow fields and compared the mixing efficiency in the modeled micromixer with different electrode positions and operating conditions, such as the frequencies and electric potentials at the electrodes.

One-dimensional modelling of upper ocean mixing by turbulence due to wave orbital motion

NASA Astrophysics Data System (ADS)

Ghantous, M.; Babanin, A. V.

2014-02-01

Mixing of the upper ocean affects the sea surface temperature by bringing deeper, colder water to the surface. Because even small changes in the surface temperature can have a large impact on weather and climate, accurately determining the rate of mixing is of central importance for forecasting. Although there are several mixing mechanisms, one that has until recently been overlooked is the effect of turbulence generated by non-breaking, wind-generated surface waves. Lately there has been a lot of interest in introducing this mechanism into ocean mixing models, and real gains have been made in terms of increased fidelity to observational data. However, our knowledge of the mechanism is still incomplete. We indicate areas where we believe the existing parameterisations need refinement and propose an alternative one. We use two of the parameterisations to demonstrate the effect on the mixed layer of wave-induced turbulence by applying them to a one-dimensional mixing model and a stable temperature profile. Our modelling experiment suggests a strong effect on sea surface temperature due to non-breaking wave-induced turbulent mixing.

Analysis of baseline, average, and longitudinally measured blood pressure data using linear mixed models.

PubMed

Hossain, Ahmed; Beyene, Joseph

2014-01-01

This article compares baseline, average, and longitudinal data analysis methods for identifying genetic variants in genome-wide association study using the Genetic Analysis Workshop 18 data. We apply methods that include (a) linear mixed models with baseline measures, (b) random intercept linear mixed models with mean measures outcome, and (c) random intercept linear mixed models with longitudinal measurements. In the linear mixed models, covariates are included as fixed effects, whereas relatedness among individuals is incorporated as the variance-covariance structure of the random effect for the individuals. The overall strategy of applying linear mixed models decorrelate the data is based on Aulchenko et al.'s GRAMMAR. By analyzing systolic and diastolic blood pressure, which are used separately as outcomes, we compare the 3 methods in identifying a known genetic variant that is associated with blood pressure from chromosome 3 and simulated phenotype data. We also analyze the real phenotype data to illustrate the methods. We conclude that the linear mixed model with longitudinal measurements of diastolic blood pressure is the most accurate at identifying the known single-nucleotide polymorphism among the methods, but linear mixed models with baseline measures perform best with systolic blood pressure as the outcome.

Mixing with applications to inertial-confinement-fusion implosions

NASA Astrophysics Data System (ADS)

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.

Mixing with applications to inertial-confinement-fusion implosions.

PubMed

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.

Model free simulations of a high speed reacting mixing layer

NASA Technical Reports Server (NTRS)

Steinberger, Craig J.

1992-01-01

The effects of compressibility, chemical reaction exothermicity and non-equilibrium chemical modeling in a combusting plane mixing layer were investigated by means of two-dimensional model free numerical simulations. It was shown that increased compressibility generally had a stabilizing effect, resulting in reduced mixing and chemical reaction conversion rate. The appearance of 'eddy shocklets' in the flow was observed at high convective Mach numbers. Reaction exothermicity was found to enhance mixing at the initial stages of the layer's growth, but had a stabilizing effect at later times. Calculations were performed for a constant rate chemical rate kinetics model and an Arrhenius type kinetics prototype. The Arrhenius model was found to cause a greater temperature increase due to reaction than the constant kinetics model. This had the same stabilizing effect as increasing the exothermicity of the reaction. Localized flame quenching was also observed when the Zeldovich number was relatively large.

Analysis and modeling of subgrid scalar mixing using numerical data

NASA Technical Reports Server (NTRS)

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.

A vine copula mixed effect model for trivariate meta-analysis of diagnostic test accuracy studies accounting for disease prevalence.

PubMed

Nikoloulopoulos, Aristidis K

2017-10-01

A bivariate copula mixed model has been recently proposed to synthesize diagnostic test accuracy studies and it has been shown that it is superior to the standard generalized linear mixed model in this context. Here, we call trivariate vine copulas to extend the bivariate meta-analysis of diagnostic test accuracy studies by accounting for disease prevalence. Our vine copula mixed model includes the trivariate generalized linear mixed model as a special case and can also operate on the original scale of sensitivity, specificity, and disease prevalence. Our general methodology is illustrated by re-analyzing the data of two published meta-analyses. Our study suggests that there can be an improvement on trivariate generalized linear mixed model in fit to data and makes the argument for moving to vine copula random effects models especially because of their richness, including reflection asymmetric tail dependence, and computational feasibility despite their three dimensionality.

On the validity of effective formulations for transport through heterogeneous porous media

NASA Astrophysics Data System (ADS)

de Dreuzy, Jean-Raynald; Carrera, Jesus

2016-04-01

Geological heterogeneity enhances spreading of solutes and causes transport to be anomalous (i.e., non-Fickian), with much less mixing than suggested by dispersion. This implies that modeling transport requires adopting either stochastic approaches that model heterogeneity explicitly or effective transport formulations that acknowledge the effects of heterogeneity. A number of such formulations have been developed and tested as upscaled representations of enhanced spreading. However, their ability to represent mixing has not been formally tested, which is required for proper reproduction of chemical reactions and which motivates our work. We propose that, for an effective transport formulation to be considered a valid representation of transport through heterogeneous porous media (HPM), it should honor mean advection, mixing and spreading. It should also be flexible enough to be applicable to real problems. We test the capacity of the multi-rate mass transfer (MRMT) model to reproduce mixing observed in HPM, as represented by the classical multi-Gaussian log-permeability field with a Gaussian correlation pattern. Non-dispersive mixing comes from heterogeneity structures in the concentration fields that are not captured by macrodispersion. These fine structures limit mixing initially, but eventually enhance it. Numerical results show that, relative to HPM, MRMT models display a much stronger memory of initial conditions on mixing than on dispersion because of the sensitivity of the mixing state to the actual values of concentration. Because MRMT does not restitute the local concentration structures, it induces smaller non-dispersive mixing than HPM. However long-lived trapping in the immobile zones may sustain the deviation from dispersive mixing over much longer times. While spreading can be well captured by MRMT models, in general non-dispersive mixing cannot.

Mixed Single/Double Precision in OpenIFS: A Detailed Study of Energy Savings, Scaling Effects, Architectural Effects, and Compilation Effects

NASA Astrophysics Data System (ADS)

Fagan, Mike; Dueben, Peter; Palem, Krishna; Carver, Glenn; Chantry, Matthew; Palmer, Tim; Schlacter, Jeremy

2017-04-01

It has been shown that a mixed precision approach that judiciously replaces double precision with single precision calculations can speed-up global simulations. In particular, a mixed precision variation of the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) showed virtually the same quality model results as the standard double precision version (Vana et al., Single precision in weather forecasting models: An evaluation with the IFS, Monthly Weather Review, in print). In this study, we perform detailed measurements of savings in computing time and energy using a mixed precision variation of the -OpenIFS- model. The mixed precision variation of OpenIFS is analogous to the IFS variation used in Vana et al. We (1) present results for energy measurements for simulations in single and double precision using Intel's RAPL technology, (2) conduct a -scaling- study to quantify the effects that increasing model resolution has on both energy dissipation and computing cycles, (3) analyze the differences between single core and multicore processing, and (4) compare the effects of different compiler technologies on the mixed precision OpenIFS code. In particular, we compare intel icc/ifort with gnu gcc/gfortran.

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

PubMed

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.

A Bayesian Semiparametric Latent Variable Model for Mixed Responses

ERIC Educational Resources Information Center

Fahrmeir, Ludwig; Raach, Alexander

2007-01-01

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

Effective Stochastic Model for Reactive Transport

NASA Astrophysics Data System (ADS)

Tartakovsky, A. M.; Zheng, B.; Barajas-Solano, D. A.

2017-12-01

We propose an effective stochastic advection-diffusion-reaction (SADR) model. Unlike traditional advection-dispersion-reaction models, the SADR model describes mechanical and diffusive mixing as two separate processes. In the SADR model, the mechanical mixing is driven by random advective velocity with the variance given by the coefficient of mechanical dispersion. The diffusive mixing is modeled as a fickian diffusion with the effective diffusion coefficient. Both coefficients are given in terms of Peclet number (Pe) and the coefficient of molecular diffusion. We use the experimental results of to demonstrate that for transport and bimolecular reactions in porous media the SADR model is significantly more accurate than the traditional dispersion model, which overestimates the mass of the reaction product by as much as 25%.

Eliciting mixed emotions: a meta-analysis comparing models, types, and measures

PubMed Central

Berrios, Raul; Totterdell, Peter; Kellett, Stephen

2015-01-01

The idea that people can experience two oppositely valenced emotions has been controversial ever since early attempts to investigate the construct of mixed emotions. This meta-analysis examined the robustness with which mixed emotions have been elicited experimentally. A systematic literature search identified 63 experimental studies that instigated the experience of mixed emotions. Studies were distinguished according to the structure of the underlying affect model—dimensional or discrete—as well as according to the type of mixed emotions studied (e.g., happy-sad, fearful-happy, positive-negative). The meta-analysis using a random-effects model revealed a moderate to high effect size for the elicitation of mixed emotions (dIG+ = 0.77), which remained consistent regardless of the structure of the affect model, and across different types of mixed emotions. Several methodological and design moderators were tested. Studies using the minimum index (i.e., the minimum value between a pair of opposite valenced affects) resulted in smaller effect sizes, whereas subjective measures of mixed emotions increased the effect sizes. The presence of more women in the samples was also associated with larger effect sizes. The current study indicates that mixed emotions are a robust, measurable and non-artifactual experience. The results are discussed in terms of the implications for an affect system that has greater versatility and flexibility than previously thought. PMID:25926805

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

PubMed

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.

Semiparametric mixed-effects analysis of PK/PD models using differential equations.

PubMed

Wang, Yi; Eskridge, Kent M; Zhang, Shunpu

2008-08-01

Motivated by the use of semiparametric nonlinear mixed-effects modeling on longitudinal data, we develop a new semiparametric modeling approach to address potential structural model misspecification for population pharmacokinetic/pharmacodynamic (PK/PD) analysis. Specifically, we use a set of ordinary differential equations (ODEs) with form dx/dt = A(t)x + B(t) where B(t) is a nonparametric function that is estimated using penalized splines. The inclusion of a nonparametric function in the ODEs makes identification of structural model misspecification feasible by quantifying the model uncertainty and provides flexibility for accommodating possible structural model deficiencies. The resulting model will be implemented in a nonlinear mixed-effects modeling setup for population analysis. We illustrate the method with an application to cefamandole data and evaluate its performance through simulations.

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

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

Mixing and non-equilibrium chemical reaction in a compressible mixing layer. M.S. Thesis Final Report

NASA Technical Reports Server (NTRS)

Steinberger, Craig J.

1991-01-01

The effects of compressibility, chemical reaction exothermicity, and non-equilibrium chemical modeling in a reacting plane mixing layer were investigated by means of two dimensional direct numerical simulations. The chemical reaction was irreversible and second order of the type A + B yields Products + Heat. The general governing fluid equations of a compressible reacting flow field were solved by means of high order finite difference methods. Physical effects were then determined by examining the response of the mixing layer to variation of the relevant non-dimensionalized parameters. The simulations show that increased compressibility generally results in a suppressed mixing, and consequently a reduced chemical reaction conversion rate. Reaction heat release was found to enhance mixing at the initial stages of the layer growth, but had a stabilizing effect at later times. The increased stability manifested itself in the suppression or delay of the formation of large coherent structures within the flow. Calculations were performed for a constant rate chemical kinetics model and an Arrhenius type kinetic prototype. The choice of the model was shown to have an effect on the development of the flow. The Arrhenius model caused a greater temperature increase due to reaction than the constant kinetic model. This had the same effect as increasing the exothermicity of the reaction. Localized flame quenching was also observed when the Zeldovich number was relatively large.

Effect of Blockage and Location on Mixing of Swirling Coaxial Jets in a Non-expanding Circular Confinement

NASA Astrophysics Data System (ADS)

Patel, V. K.; Singh, S. N.; Seshadri, V.

2013-06-01

A study is conducted to evolve an effective design concept to improve mixing in a combustor chamber to reduce the amount of intake air. The geometry used is that of a gas turbine combustor model. For simplicity, both the jets have been considered as air jets and effect of heat release and chemical reaction has not been modeled. Various contraction shapes and blockage have been investigated by placing them downstream at different locations with respect to inlet to obtain better mixing. A commercial CFD code `Fluent 6.3' which is based on finite volume method has been used to solve the flow in the combustor model. Validation is done with the experimental data available in literature using standard k-ω turbulence model. The study has shown that contraction and blockage at optimum location enhances the mixing process. Further, the effect of swirl in the jets has also investigated.

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

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

Hu, R.

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.

On the validity of effective formulations for transport through heterogeneous porous media

NASA Astrophysics Data System (ADS)

de Dreuzy, J.-R.; Carrera, J.

2015-11-01

Geological heterogeneity enhances spreading of solutes, and causes transport to be anomalous (i.e., non-Fickian), with much less mixing than suggested by dispersion. This implies that modeling transport requires adopting either stochastic approaches that model heterogeneity explicitly or effective transport formulations that acknowledge the effects of heterogeneity. A number of such formulations have been developed and tested as upscaled representations of enhanced spreading. However, their ability to represent mixing has not been formally tested, which is required for proper reproduction of chemical reactions and which motivates our work. We propose that, for an effective transport formulation to be considered a valid representation of transport through Heterogeneous Porous Media (HPM), it should honor mean advection, mixing and spreading. It should also be flexible enough to be applicable to real problems. We test the capacity of the Multi-Rate Mass Transfer (MRMT) to reproduce mixing observed in HPM, as represented by the classical multi-Gaussian log-permeability field with a Gaussian correlation pattern. Non-dispersive mixing comes from heterogeneity structures in the concentration fields that are not captured by macrodispersion. These fine structures limit mixing initially, but eventually enhance it. Numerical results show that, relative to HPM, MRMT models display a much stronger memory of initial conditions on mixing than on dispersion because of the sensitivity of the mixing state to the actual values of concentration. Because MRMT does not restitute the local concentration structures, it induces smaller non-dispersive mixing than HPM. However long-lived trapping in the immobile zones may sustain the deviation from dispersive mixing over much longer times. While spreading can be well captured by MRMT models, non-dispersive mixing cannot.

Prediction of hemoglobin in blood donors using a latent class mixed-effects transition model.

PubMed

Nasserinejad, Kazem; van Rosmalen, Joost; de Kort, Wim; Rizopoulos, Dimitris; Lesaffre, Emmanuel

2016-02-20

Blood donors experience a temporary reduction in their hemoglobin (Hb) value after donation. At each visit, the Hb value is measured, and a too low Hb value leads to a deferral for donation. Because of the recovery process after each donation as well as state dependence and unobserved heterogeneity, longitudinal data of Hb values of blood donors provide unique statistical challenges. To estimate the shape and duration of the recovery process and to predict future Hb values, we employed three models for the Hb value: (i) a mixed-effects models; (ii) a latent-class mixed-effects model; and (iii) a latent-class mixed-effects transition model. In each model, a flexible function was used to model the recovery process after donation. The latent classes identify groups of donors with fast or slow recovery times and donors whose recovery time increases with the number of donations. The transition effect accounts for possible state dependence in the observed data. All models were estimated in a Bayesian way, using data of new entrant donors from the Donor InSight study. Informative priors were used for parameters of the recovery process that were not identified using the observed data, based on results from the clinical literature. The results show that the latent-class mixed-effects transition model fits the data best, which illustrates the importance of modeling state dependence, unobserved heterogeneity, and the recovery process after donation. The estimated recovery time is much longer than the current minimum interval between donations, suggesting that an increase of this interval may be warranted. Copyright © 2015 John Wiley & Sons, Ltd.

Modeling of molecular diffusion and thermal conduction with multi-particle interaction in compressible turbulence

NASA Astrophysics Data System (ADS)

Tai, Y.; Watanabe, T.; Nagata, K.

2018-03-01

A mixing volume model (MVM) originally proposed for molecular diffusion in incompressible flows is extended as a model for molecular diffusion and thermal conduction in compressible turbulence. The model, established for implementation in Lagrangian simulations, is based on the interactions among spatially distributed notional particles within a finite volume. The MVM is tested with the direct numerical simulation of compressible planar jets with the jet Mach number ranging from 0.6 to 2.6. The MVM well predicts molecular diffusion and thermal conduction for a wide range of the size of mixing volume and the number of mixing particles. In the transitional region of the jet, where the scalar field exhibits a sharp jump at the edge of the shear layer, a smaller mixing volume is required for an accurate prediction of mean effects of molecular diffusion. The mixing time scale in the model is defined as the time scale of diffusive effects at a length scale of the mixing volume. The mixing time scale is well correlated for passive scalar and temperature. Probability density functions of the mixing time scale are similar for molecular diffusion and thermal conduction when the mixing volume is larger than a dissipative scale because the mixing time scale at small scales is easily affected by different distributions of intermittent small-scale structures between passive scalar and temperature. The MVM with an assumption of equal mixing time scales for molecular diffusion and thermal conduction is useful in the modeling of the thermal conduction when the modeling of the dissipation rate of temperature fluctuations is difficult.

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

PubMed Central

Demidenko, Eugene; Sargent, James; Onega, Tracy

2011-01-01

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

The Mixed Effects Trend Vector Model

ERIC Educational Resources Information Center

de Rooij, Mark; Schouteden, Martijn

2012-01-01

Maximum likelihood estimation of mixed effect baseline category logit models for multinomial longitudinal data can be prohibitive due to the integral dimension of the random effects distribution. We propose to use multidimensional unfolding methodology to reduce the dimensionality of the problem. As a by-product, readily interpretable graphical…

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

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

Rupšys, P.

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.

Effects of mixing states on the multiple-scattering properties of soot aerosols.

PubMed

Cheng, Tianhai; Wu, Yu; Gu, Xingfa; Chen, Hao

2015-04-20

The radiative properties of soot aerosols are highly sensitive to the mixing states of black carbon particles and other aerosol components. Light absorption properties are enhanced by the mixing state of soot aerosols. Quantification of the effects of mixing states on the scattering properties of soot aerosol are still not completely resolved, especially for multiple-scattering properties. This study focuses on the effects of the mixing state on the multiple scattering of soot aerosols using the vector radiative transfer model. Two types of soot aerosols with different mixing states such as external mixture soot aerosols and internal mixture soot aerosols are studied. Upward radiance/polarization and hemispheric flux are studied with variable soot aerosol loadings for clear and haze scenarios. Our study showed dramatic changes in upward radiance/polarization due to the effects of the mixing state on the multiple scattering of soot aerosols. The relative difference in upward radiance due to the different mixing states can reach 16%, whereas the relative difference of upward polarization can reach 200%. The effects of the mixing state on the multiple-scattering properties of soot aerosols increase with increasing soot aerosol loading. The effects of the soot aerosol mixing state on upwelling hemispheric flux are much smaller than in upward radiance/polarization, which increase with increasing solar zenith angle. The relative difference in upwelling hemispheric flux due to the different soot aerosol mixing states can reach 18% when the solar zenith angle is 75°. The findings should improve our understanding of the effects of mixing states on the optical properties of soot aerosols and their effects on climate. The mixing mechanism of soot aerosols is of critical importance in evaluating the climate effects of soot aerosols, which should be explicitly included in radiative forcing models and aerosol remote sensing.

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

PubMed

Defliese, William F; Lohmann, Kyger C

2015-05-15

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

The salinity effect in a mixed layer ocean model

NASA Technical Reports Server (NTRS)

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.

APPLICATION OF STABLE ISOTOPE TECHNIQUES TO AIR POLLUTION RESEARCH

EPA Science Inventory

Stable isotope techniques provide a robust, yet under-utilized tool for examining pollutant effects on plant growth and ecosystem function. Here, we survey a range of mixing model, physiological and system level applications for documenting pollutant effects. Mixing model examp...

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Transient modeling/analysis of hyperbolic heat conduction problems employing mixed implicit-explicit alpha method

NASA Technical Reports Server (NTRS)

Tamma, Kumar K.; D'Costa, Joseph F.

1991-01-01

This paper describes the evaluation of mixed implicit-explicit finite element formulations for hyperbolic heat conduction problems involving non-Fourier effects. In particular, mixed implicit-explicit formulations employing the alpha method proposed by Hughes et al. (1987, 1990) are described for the numerical simulation of hyperbolic heat conduction models, which involves time-dependent relaxation effects. Existing analytical approaches for modeling/analysis of such models involve complex mathematical formulations for obtaining closed-form solutions, while in certain numerical formulations the difficulties include severe oscillatory solution behavior (which often disguises the true response) in the vicinity of the thermal disturbances, which propagate with finite velocities. In view of these factors, the alpha method is evaluated to assess the control of the amount of numerical dissipation for predicting the transient propagating thermal disturbances. Numerical test models are presented, and pertinent conclusions are drawn for the mixed-time integration simulation of hyperbolic heat conduction models involving non-Fourier effects.

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

PubMed

Demidenko, Eugene; Sargent, James; Onega, Tracy

2012-01-01

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

Effective temperatures of red giants in the APOKASC catalogue and the mixing length calibration in stellar models

NASA Astrophysics Data System (ADS)

Salaris, M.; Cassisi, S.; Schiavon, R. P.; Pietrinferni, A.

2018-04-01

Red giants in the updated APOGEE-Kepler catalogue, with estimates of mass, chemical composition, surface gravity and effective temperature, have recently challenged stellar models computed under the standard assumption of solar calibrated mixing length. In this work, we critically reanalyse this sample of red giants, adopting our own stellar model calculations. Contrary to previous results, we find that the disagreement between the Teff scale of red giants and models with solar calibrated mixing length disappears when considering our models and the APOGEE-Kepler stars with scaled solar metal distribution. However, a discrepancy shows up when α-enhanced stars are included in the sample. We have found that assuming mass, chemical composition and effective temperature scale of the APOGEE-Kepler catalogue, stellar models generally underpredict the change of temperature of red giants caused by α-element enhancements at fixed [Fe/H]. A second important conclusion is that the choice of the outer boundary conditions employed in model calculations is critical. Effective temperature differences (metallicity dependent) between models with solar calibrated mixing length and observations appear for some choices of the boundary conditions, but this is not a general result.

Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms

NASA Astrophysics Data System (ADS)

Sednev, I.; Menon, S.; McFarquhar, G.

2008-06-01

The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM) scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE) campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP) on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during 9th-10th October, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-h simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors' concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity) against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process of ice phase initiation due to freezing of supercooled water in both saturated and undersaturated (w.r.t. water) environments is as important as primary ice crystal origination from water vapor. We also find that the BFP is a process mainly responsible for the rates of glaciation of simulated clouds. These glaciation rates cannot be adequately represented by a water-ice saturation adjustment scheme that only depends on temperature and liquid and solid hydrometeors' contents as is widely used in bulk microphysics schemes and are better represented by processes that also account for supersaturation changes as the hydrometeors grow.

Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms

NASA Astrophysics Data System (ADS)

Sednev, I.; Menon, S.; McFarquhar, G.

2009-07-01

The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM) scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE) campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP) on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during 9-10 October, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-h simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors' concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity) against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process of ice phase initiation due to freezing of supercooled water in both saturated and subsaturated (w.r.t. water) environments is as important as primary ice crystal origination from water vapor. We also find that the BFP is a process mainly responsible for the rates of glaciation of simulated clouds. These glaciation rates cannot be adequately represented by a water-ice saturation adjustment scheme that only depends on temperature and liquid and solid hydrometeors' contents as is widely used in bulk microphysics schemes and are better represented by processes that also account for supersaturation changes as the hydrometeors grow.

Influence of non-homogeneous mixing on final epidemic size in a meta-population model.

PubMed

Cui, Jingan; Zhang, Yanan; Feng, Zhilan

2018-06-18

In meta-population models for infectious diseases, the basic reproduction number [Formula: see text] can be as much as 70% larger in the case of preferential mixing than that in homogeneous mixing [J.W. Glasser, Z. Feng, S.B. Omer, P.J. Smith, and L.E. Rodewald, The effect of heterogeneity in uptake of the measles, mumps, and rubella vaccine on the potential for outbreaks of measles: A modelling study, Lancet ID 16 (2016), pp. 599-605. doi: 10.1016/S1473-3099(16)00004-9 ]. This suggests that realistic mixing can be an important factor to consider in order for the models to provide a reliable assessment of intervention strategies. The influence of mixing is more significant when the population is highly heterogeneous. In this paper, another quantity, the final epidemic size ([Formula: see text]) of an outbreak, is considered to examine the influence of mixing and population heterogeneity. Final size relation is derived for a meta-population model accounting for a general mixing. The results show that [Formula: see text] can be influenced by the pattern of mixing in a significant way. Another interesting finding is that, heterogeneity in various sub-population characteristics may have the opposite effect on [Formula: see text] and [Formula: see text].

Statistical models of global Langmuir mixing

NASA Astrophysics Data System (ADS)

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.

Modeling of the Wegener Bergeron Findeisen process—implications for aerosol indirect effects

NASA Astrophysics Data System (ADS)

Storelvmo, T.; Kristjánsson, J. E.; Lohmann, U.; Iversen, T.; Kirkevåg, A.; Seland, Ø.

2008-10-01

A new parameterization of the Wegener-Bergeron-Findeisen (WBF) process has been developed, and implemented in the general circulation model CAM-Oslo. The new parameterization scheme has important implications for the process of phase transition in mixed-phase clouds. The new treatment of the WBF process replaces a previous formulation, in which the onset of the WBF effect depended on a threshold value of the mixing ratio of cloud ice. As no observational guidance for such a threshold value exists, the previous treatment added uncertainty to estimates of aerosol effects on mixed-phase clouds. The new scheme takes subgrid variability into account when simulating the WBF process, allowing for smoother phase transitions in mixed-phase clouds compared to the previous approach. The new parameterization yields a model state which gives reasonable agreement with observed quantities, allowing for calculations of aerosol effects on mixed-phase clouds involving a reduced number of tunable parameters. Furthermore, we find a significant sensitivity to perturbations in ice nuclei concentrations with the new parameterization, which leads to a reversal of the traditional cloud lifetime effect.

Stellar evolution with turbulent diffusion. I. A new formalism of mixing.

NASA Astrophysics Data System (ADS)

Deng, L.; Bressan, A.; Chiosi, C.

1996-09-01

In this paper we present a new formulation of diffusive mixing in stellar interiors aimed at casting light on the kind of mixing that should take place in the so-called overshoot regions surrounding fully convective zones. Key points of the analysis are the inclusion the concept of scale length most effective for mixing, by means of which the diffusion coefficient is formulated, and the inclusion of intermittence and stirring, two properties of turbulence known from laboratory fluid dynamics. The formalism is applied to follow the evolution of a 20Msun_ star with composition Z=0.008 and Y=0.25. Depending on the value of the diffusion coefficient holding in the overshoot region, the evolutionary behaviour of the test stars goes from the case of virtually no mixing (semiconvective like structures) to that of full mixing over there (standard overshoot models). Indeed, the efficiency of mixing in this region drives the extension of the intermediate fully convective shell developing at the onset of the the shell H-burning, and in turn the path in the HR Diagram (HRD). Models with low efficiency of mixing burn helium in the core at high effective temperatures, models with intermediate efficiency perform extended loops in the HRD, finally models with high efficiency spend the whole core He-burning phase at low effective temperatures. In order to cast light on this important point of stellar structure, we test whether or not in the regions of the H-burning shell a convective layer can develop. More precisely, we examine whether the Schwarzschild or the Ledoux criterion ought to be adopted in this region. Furthermore, we test the response of stellar models to the kind of mixing supposed to occur in the H-burning shell regions. Finally, comparing the time scale of thermal dissipation to the evolutionary time scale, we get the conclusion that no mixing in this region should occur. The models with intermediate efficiency of mixing and no mixing at all in the shell H-burning regions are of particular interest as they possess at the same time evolutionary characteristics that are separately typical of models calculated with different schemes of mixing. In other words, the new models share the same properties of models with standard overshoot, namely a wider main sequence band, higher luminosity, and longer lifetimes than classical models, but they also possess extended loops that are the main signature of the classical (semiconvective) description of convection at the border of the core.

The use of mixed effects ANCOVA to characterize vehicle emission profiles

DOT National Transportation Integrated Search

2000-09-01

A mixed effects analysis of covariance model to characterize mileage dependent emissions profiles for any given group of vehicles having a common model design is used in this paper. These types of evaluations are used by the U.S. Environmental Protec...

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

ERIC Educational Resources Information Center

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

2012-01-01

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

An improved NSGA - II algorithm for mixed model assembly line balancing

NASA Astrophysics Data System (ADS)

Wu, Yongming; Xu, Yanxia; Luo, Lifei; Zhang, Han; Zhao, Xudong

2018-05-01

Aiming at the problems of assembly line balancing and path optimization for material vehicles in mixed model manufacturing system, a multi-objective mixed model assembly line (MMAL), which is based on optimization objectives, influencing factors and constraints, is established. According to the specific situation, an improved NSGA-II algorithm based on ecological evolution strategy is designed. An environment self-detecting operator, which is used to detect whether the environment changes, is adopted in the algorithm. Finally, the effectiveness of proposed model and algorithm is verified by examples in a concrete mixing system.

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

PubMed

Janssen, Dirk P

2012-03-01

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

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

Treesearch

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...

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

PubMed

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

2016-08-01

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

Coding response to a case-mix measurement system based on multiple diagnoses.

PubMed

Preyra, Colin

2004-08-01

To examine the hospital coding response to a payment model using a case-mix measurement system based on multiple diagnoses and the resulting impact on a hospital cost model. Financial, clinical, and supplementary data for all Ontario short stay hospitals from years 1997 to 2002. Disaggregated trends in hospital case-mix growth are examined for five years following the adoption of an inpatient classification system making extensive use of combinations of secondary diagnoses. Hospital case mix is decomposed into base and complexity components. The longitudinal effects of coding variation on a standard hospital payment model are examined in terms of payment accuracy and impact on adjustment factors. Introduction of the refined case-mix system provided incentives for hospitals to increase reporting of secondary diagnoses and resulted in growth in highest complexity cases that were not matched by increased resource use over time. Despite a pronounced coding response on the part of hospitals, the increase in measured complexity and case mix did not reduce the unexplained variation in hospital unit cost nor did it reduce the reliance on the teaching adjustment factor, a potential proxy for case mix. The main implication was changes in the size and distribution of predicted hospital operating costs. Jurisdictions introducing extensive refinements to standard diagnostic related group (DRG)-type payment systems should consider the effects of induced changes to hospital coding practices. Assessing model performance should include analysis of the robustness of classification systems to hospital-level variation in coding practices. Unanticipated coding effects imply that case-mix models hypothesized to perform well ex ante may not meet expectations ex post.

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

PubMed

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

2014-04-01

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

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

PubMed

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

2017-10-25

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

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

NASA Astrophysics Data System (ADS)

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.

Coastal Ocean Variability Off the Coast of Taiwan in Response toTyphoon Morakot: River Forcing, Atmospheric Forcing, and Cold Dome Dynamics

DTIC Science & Technology

2014-09-01

very short time period and in this research, we model and study the effects of this rainfall on Taiwan?s coastal oceans as a result of river discharge...model and study the effects of this rainfall on Taiwan’s coastal oceans as a result of river discharge. We do this through the use of a river discharge... Effects of Footprint Shape on the Bulk Mixing Model . . . . . . . . . 57 4.2 Effects of the Horizontal Extent of the Bulk Mixing Model . . . . . . 59

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

PubMed

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.

Using Mixed-Effects Structural Equation Models to Study Student Academic Development.

ERIC Educational Resources Information Center

Pike, Gary R.

1992-01-01

A study at the University of Tennessee Knoxville used mixed-effect structural equation models incorporating latent variables as an alternative to conventional methods of analyzing college students' (n=722) first-year-to-senior academic gains. Results indicate, contrary to previous analysis, that coursework and student characteristics interact to…

Budget model can aid group practice planning.

PubMed

Bender, A D

1991-12-01

A medical practice can enhance its planning by developing a budgetary model to test effects of planning assumptions on its profitability and cash requirements. A model focusing on patient visits, payment mix, patient mix, and fee and payment schedules can help assess effects of proposed decisions. A planning model is not a substitute for planning but should complement a plan that includes mission, goals, values, strategic issues, and different outcomes.

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

ERIC Educational Resources Information Center

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…

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

Lu, Tao

2016-01-01

We propose partially linear mixed-effects models with asymmetry and missingness to investigate the relationship between two biomarkers in clinical studies. The proposed models take into account irregular time effects commonly observed in clinical studies under a semiparametric model framework. In addition, commonly assumed symmetric distributions for model errors are substituted by asymmetric distribution to account for skewness. Further, informative missing data mechanism is accounted for. A Bayesian approach is developed to perform parameter estimation simultaneously. The proposed model and method are applied to an AIDS dataset and comparisons with alternative models are performed.

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

PubMed

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

2014-12-01

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

Comparing colon cancer outcomes: The impact of low hospital case volume and case-mix adjustment.

PubMed

Fischer, C; Lingsma, H F; van Leersum, N; Tollenaar, R A E M; Wouters, M W; Steyerberg, E W

2015-08-01

When comparing performance across hospitals it is essential to consider the noise caused by low hospital case volume and to perform adequate case-mix adjustment. We aimed to quantify the role of noise and case-mix adjustment on standardized postoperative mortality and anastomotic leakage (AL) rates. We studied 13,120 patients who underwent colon cancer resection in 85 Dutch hospitals. We addressed differences between hospitals in postoperative mortality and AL, using fixed (ignoring noise) and random effects (incorporating noise) logistic regression models with general and additional, disease specific, case-mix adjustment. Adding disease specific variables improved the performance of the case-mix adjustment models for postoperative mortality (c-statistic increased from 0.77 to 0.81). The overall variation in standardized mortality ratios was similar, but some individual hospitals changed considerably. For the standardized AL rates the performance of the adjustment models was poor (c-statistic 0.59 and 0.60) and overall variation was small. Most of the observed variation between hospitals was actually noise. Noise had a larger effect on hospital performance than extended case-mix adjustment, although some individual hospital outcome rates were affected by more detailed case-mix adjustment. To compare outcomes between hospitals it is crucial to consider noise due to low hospital case volume with a random effects model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effects of imperfect mixing on low-density polyethylene reactor dynamics

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

Villa, C.M.; Dihora, J.O.; Ray, W.H.

1998-07-01

Earlier work considered the effect of feed conditions and controller configuration on the runaway behavior of LDPE autoclave reactors assuming a perfectly mixed reactor. This study provides additional insight on the dynamics of such reactors by using an imperfectly mixed reactor model and bifurcation analysis to show the changes in the stability region when there is imperfect macroscale mixing. The presence of imperfect mixing substantially increases the range of stable operation of the reactor and makes the process much easier to control than for a perfectly mixed reactor. The results of model analysis and simulations are used to identify somemore » of the conditions that lead to unstable reactor behavior and to suggest ways to avoid reactor runaway or reactor extinction during grade transitions and other process operation disturbances.« less

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

PubMed

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.

Estimation of the linear mixed integrated Ornstein–Uhlenbeck model

PubMed Central

Hughes, Rachael A.; Kenward, Michael G.; Sterne, Jonathan A. C.; Tilling, Kate

2017-01-01

ABSTRACT The linear mixed model with an added integrated Ornstein–Uhlenbeck (IOU) process (linear mixed IOU model) allows for serial correlation and estimation of the degree of derivative tracking. It is rarely used, partly due to the lack of available software. We implemented the linear mixed IOU model in Stata and using simulations we assessed the feasibility of fitting the model by restricted maximum likelihood when applied to balanced and unbalanced data. We compared different (1) optimization algorithms, (2) parameterizations of the IOU process, (3) data structures and (4) random-effects structures. Fitting the model was practical and feasible when applied to large and moderately sized balanced datasets (20,000 and 500 observations), and large unbalanced datasets with (non-informative) dropout and intermittent missingness. Analysis of a real dataset showed that the linear mixed IOU model was a better fit to the data than the standard linear mixed model (i.e. independent within-subject errors with constant variance). PMID:28515536

Effect of shroud geometry on the effectiveness of a short mixing stack gas eductor model

NASA Astrophysics Data System (ADS)

Kavalis, A. E.

1983-06-01

An existing apparatus for testing models of gas eductor systems using high temperature primary flow was modified to provide improved control and performance over a wide range of gas temperature and flow rates. Secondary flow pumping, temperature and pressure data were recorded for two gas eductor system models. The first, previously tested under hot flow conditions, consists of a primary plate with four tilted-angled nozzles and a slotted, shrouded mixing stack with two diffuser rings (overall L/D = 1.5). A portable pyrometer with a surface probe was used for the second model in order to identify any hot spots at the external surface of the mixing stack, shroud and diffuser rings. The second model is shown to have almost the same mixing and pumping performance with the first one but to exhibit much lower shroud and diffuser surface temperatures.

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

PubMed

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

2017-11-10

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

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

PubMed

Lu, Tao; Lu, Minggen; Wang, Min; Zhang, Jun; Dong, Guang-Hui; Xu, Yong

2017-12-18

Longitudinal competing risks data frequently arise in clinical studies. Skewness and missingness are commonly observed for these data in practice. However, most joint models do not account for these data features. In this article, we propose partially linear mixed-effects joint models to analyze skew longitudinal competing risks data with missingness. In particular, to account for skewness, we replace the commonly assumed symmetric distributions by asymmetric distribution for model errors. To deal with missingness, we employ an informative missing data model. The joint models that couple the partially linear mixed-effects model for the longitudinal process, the cause-specific proportional hazard model for competing risks process and missing data process are developed. To estimate the parameters in the joint models, we propose a fully Bayesian approach based on the joint likelihood. To illustrate the proposed model and method, we implement them to an AIDS clinical study. Some interesting findings are reported. We also conduct simulation studies to validate the proposed method.

Impact of Antarctic mixed-phase clouds on climate.

PubMed

Lawson, R Paul; Gettelman, Andrew

2014-12-23

Precious little is known about the composition of low-level clouds over the Antarctic Plateau and their effect on climate. In situ measurements at the South Pole using a unique tethered balloon system and ground-based lidar reveal a much higher than anticipated incidence of low-level, mixed-phase clouds (i.e., consisting of supercooled liquid water drops and ice crystals). The high incidence of mixed-phase clouds is currently poorly represented in global climate models (GCMs). As a result, the effects that mixed-phase clouds have on climate predictions are highly uncertain. We modify the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM) GCM to align with the new observations and evaluate the radiative effects on a continental scale. The net cloud radiative effects (CREs) over Antarctica are increased by +7.4 Wm(-2), and although this is a significant change, a much larger effect occurs when the modified model physics are extended beyond the Antarctic continent. The simulations show significant net CRE over the Southern Ocean storm tracks, where recent measurements also indicate substantial regions of supercooled liquid. These sensitivity tests confirm that Southern Ocean CREs are strongly sensitive to mixed-phase clouds colder than -20 °C.

Impact of Antarctic mixed-phase clouds on climate

PubMed Central

Lawson, R. Paul; Gettelman, Andrew

2014-01-01

Precious little is known about the composition of low-level clouds over the Antarctic Plateau and their effect on climate. In situ measurements at the South Pole using a unique tethered balloon system and ground-based lidar reveal a much higher than anticipated incidence of low-level, mixed-phase clouds (i.e., consisting of supercooled liquid water drops and ice crystals). The high incidence of mixed-phase clouds is currently poorly represented in global climate models (GCMs). As a result, the effects that mixed-phase clouds have on climate predictions are highly uncertain. We modify the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM) GCM to align with the new observations and evaluate the radiative effects on a continental scale. The net cloud radiative effects (CREs) over Antarctica are increased by +7.4 Wm−2, and although this is a significant change, a much larger effect occurs when the modified model physics are extended beyond the Antarctic continent. The simulations show significant net CRE over the Southern Ocean storm tracks, where recent measurements also indicate substantial regions of supercooled liquid. These sensitivity tests confirm that Southern Ocean CREs are strongly sensitive to mixed-phase clouds colder than −20 °C. PMID:25489069

Multivariate statistical approach to estimate mixing proportions for unknown end members

USGS Publications Warehouse

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

2012-01-01

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

Relationship between attributional style, perceived control, self-esteem, and depressive mood in a nonclinical sample: a structural equation-modelling approach.

PubMed

Ledrich, Julie; Gana, Kamel

2013-12-01

The aim of this study was to examine the intricate relationship between some personality traits (i.e., attributional style, perceived control over consequences, self-esteem), and depressive mood in a nonclinical sample (N= 334). Method. Structural equation modelling was used to estimate five competing models: two vulnerability models describing the effects of personality traits on depressive mood, one scar model describing the effects of depression on personality traits, a mixed model describing the effects of attributional style and perceived control over consequences on depressive mood, which in turn affects self-esteem, and a reciprocal model which is a non-recursive version of the mixed model that specifies bidirectional effects between depressive mood and self-esteem. The best-fitting model was the mixed model. Moreover, we observed a significant negative effect of depression on self-esteem, but no effect in the opposite direction. These findings provide supporting arguments against the continuum model of the relationship between self-esteem and depression, and lend substantial support to the scar model, which claims that depressive mood damages and erodes self-esteem. In addition, the 'depressogenic' nature of the pessimistic attributional style, and the 'antidepressant' nature of perceived control over consequences plead in favour of the vulnerability model. © 2012 The British Psychological Society.

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

Treesearch

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

2009-01-01

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

Modeling Intrajunction Dispersion at a Well-Mixed Tidal River Junction

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

Wolfram, Phillip J.; Fringer, Oliver B.; Monsen, Nancy E.

In this paper, the relative importance of small-scale, intrajunction flow features such as shear layers, separation zones, and secondary flows on dispersion in a well-mixed tidal river junction is explored. A fully nonlinear, nonhydrostatic, and unstructured three-dimensional (3D) model is used to resolve supertidal dispersion via scalar transport at a well-mixed tidal river junction. Mass transport simulated in the junction is compared against predictions using a simple node-channel model to quantify the effects of small-scale, 3D intrajunction flow features on mixing and dispersion. The effects of three-dimensionality are demonstrated by quantifying the difference between two-dimensional (2D) and 3D model results.more » An intermediate 3D model that does not resolve the secondary circulation or the recirculating flow at the junction is also compared to the 3D model to quantify the relative sensitivity of mixing on intrajunction flow features. Resolution of complex flow features simulated by the full 3D model is not always necessary because mixing is primarily governed by bulk flow splitting due to the confluence–diffluence cycle. Finally, results in 3D are comparable to the 2D case for many flow pathways simulated, suggesting that 2D modeling may be reasonable for nonstratified and predominantly hydrostatic flows through relatively straight junctions, but not necessarily for the full junction network.« less

Modeling Intrajunction Dispersion at a Well-Mixed Tidal River Junction

DOE PAGES

Wolfram, Phillip J.; Fringer, Oliver B.; Monsen, Nancy E.; ...

2016-08-01

In this paper, the relative importance of small-scale, intrajunction flow features such as shear layers, separation zones, and secondary flows on dispersion in a well-mixed tidal river junction is explored. A fully nonlinear, nonhydrostatic, and unstructured three-dimensional (3D) model is used to resolve supertidal dispersion via scalar transport at a well-mixed tidal river junction. Mass transport simulated in the junction is compared against predictions using a simple node-channel model to quantify the effects of small-scale, 3D intrajunction flow features on mixing and dispersion. The effects of three-dimensionality are demonstrated by quantifying the difference between two-dimensional (2D) and 3D model results.more » An intermediate 3D model that does not resolve the secondary circulation or the recirculating flow at the junction is also compared to the 3D model to quantify the relative sensitivity of mixing on intrajunction flow features. Resolution of complex flow features simulated by the full 3D model is not always necessary because mixing is primarily governed by bulk flow splitting due to the confluence–diffluence cycle. Finally, results in 3D are comparable to the 2D case for many flow pathways simulated, suggesting that 2D modeling may be reasonable for nonstratified and predominantly hydrostatic flows through relatively straight junctions, but not necessarily for the full junction network.« less

Logistic Mixed Models to Investigate Implicit and Explicit Belief Tracking.

PubMed

Lages, Martin; Scheel, Anne

2016-01-01

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

Experimental and mathematical model of the interactions in the mixed culture of links in the "producer-consumer" cycle

NASA Astrophysics Data System (ADS)

Pisman, T. I.; Galayda, Ya. V.

The paper presents experimental and mathematical model of interactions between invertebrates the ciliates Paramecium caudatum and the rotifers Brachionus plicatilis and algae Chlorella vulgaris and Scenedesmus quadricauda in the producer -- consumer aquatic biotic cycle with spatially separated components The model describes the dynamics of the mixed culture of ciliates and rotifers in the consumer component feeding on the mixed algal culture of the producer component It has been found that metabolites of the algae Scenedesmus produce an adverse effect on the reproduction of the ciliates P caudatum Taking into account this effect the results of investigation of the mathematical model were in qualitative agreement with the experimental results In the producer -- consumer biotic cycle it was shown that coexistence is impossible in the mixed algal culture of the producer component and in the mixed culture of invertebrates of the consumer component The ciliates P caudatum are driven out by the rotifers Brachionus plicatilis

Modelling individual tree height to crown base of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.)

PubMed Central

Jansa, Václav

2017-01-01

Height to crown base (HCB) of a tree is an important variable often included as a predictor in various forest models that serve as the fundamental tools for decision-making in forestry. We developed spatially explicit and spatially inexplicit mixed-effects HCB models using measurements from a total 19,404 trees of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.) on the permanent sample plots that are located across the Czech Republic. Variables describing site quality, stand density or competition, and species mixing effects were included into the HCB model with use of dominant height (HDOM), basal area of trees larger in diameters than a subject tree (BAL- spatially inexplicit measure) or Hegyi’s competition index (HCI—spatially explicit measure), and basal area proportion of a species of interest (BAPOR), respectively. The parameters describing sample plot-level random effects were included into the HCB model by applying the mixed-effects modelling approach. Among several functional forms evaluated, the logistic function was found most suited to our data. The HCB model for Norway spruce was tested against the data originated from different inventory designs, but model for European beech was tested using partitioned dataset (a part of the main dataset). The variance heteroscedasticity in the residuals was substantially reduced through inclusion of a power variance function into the HCB model. The results showed that spatially explicit model described significantly a larger part of the HCB variations [R2adj = 0.86 (spruce), 0.85 (beech)] than its spatially inexplicit counterpart [R2adj = 0.84 (spruce), 0.83 (beech)]. The HCB increased with increasing competitive interactions described by tree-centered competition measure: BAL or HCI, and species mixing effects described by BAPOR. A test of the mixed-effects HCB model with the random effects estimated using at least four trees per sample plot in the validation data confirmed that the model was precise enough for the prediction of HCB for a range of site quality, tree size, stand density, and stand structure. We therefore recommend measuring of HCB on four randomly selected trees of a species of interest on each sample plot for localizing the mixed-effects model and predicting HCB of the remaining trees on the plot. Growth simulations can be made from the data that lack the values for either crown ratio or HCB using the HCB models. PMID:29049391

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

Treesearch

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...

Spurious Latent Class Problem in the Mixed Rasch Model: A Comparison of Three Maximum Likelihood Estimation Methods under Different Ability Distributions

ERIC Educational Resources Information Center

Sen, Sedat

2018-01-01

Recent research has shown that over-extraction of latent classes can be observed in the Bayesian estimation of the mixed Rasch model when the distribution of ability is non-normal. This study examined the effect of non-normal ability distributions on the number of latent classes in the mixed Rasch model when estimated with maximum likelihood…

A mixed-effects height-diameter model for cottonwood in the Mississippi Delta

Treesearch

Curtis L. VanderSchaaf; H. Christoph Stuhlinger

2012-01-01

Eastern cottonwood (Populus deltoides Bartr. ex Marsh.) has been artificially regenerated throughout the Mississippi Delta region because of its fast growth and is being considered for biofuel production.This paper presents a mixed-effects height-diameter model for cottonwood in the Mississippi Delta region. After obtaining height-diameter...

Estimation of Complex Generalized Linear Mixed Models for Measurement and Growth

ERIC Educational Resources Information Center

Jeon, Minjeong

2012-01-01

Maximum likelihood (ML) estimation of generalized linear mixed models (GLMMs) is technically challenging because of the intractable likelihoods that involve high dimensional integrations over random effects. The problem is magnified when the random effects have a crossed design and thus the data cannot be reduced to small independent clusters. A…

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

PubMed

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

2017-11-01

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

Coding Response to a Case-Mix Measurement System Based on Multiple Diagnoses

PubMed Central

Preyra, Colin

2004-01-01

Objective To examine the hospital coding response to a payment model using a case-mix measurement system based on multiple diagnoses and the resulting impact on a hospital cost model. Data Sources Financial, clinical, and supplementary data for all Ontario short stay hospitals from years 1997 to 2002. Study Design Disaggregated trends in hospital case-mix growth are examined for five years following the adoption of an inpatient classification system making extensive use of combinations of secondary diagnoses. Hospital case mix is decomposed into base and complexity components. The longitudinal effects of coding variation on a standard hospital payment model are examined in terms of payment accuracy and impact on adjustment factors. Principal Findings Introduction of the refined case-mix system provided incentives for hospitals to increase reporting of secondary diagnoses and resulted in growth in highest complexity cases that were not matched by increased resource use over time. Despite a pronounced coding response on the part of hospitals, the increase in measured complexity and case mix did not reduce the unexplained variation in hospital unit cost nor did it reduce the reliance on the teaching adjustment factor, a potential proxy for case mix. The main implication was changes in the size and distribution of predicted hospital operating costs. Conclusions Jurisdictions introducing extensive refinements to standard diagnostic related group (DRG)-type payment systems should consider the effects of induced changes to hospital coding practices. Assessing model performance should include analysis of the robustness of classification systems to hospital-level variation in coding practices. Unanticipated coding effects imply that case-mix models hypothesized to perform well ex ante may not meet expectations ex post. PMID:15230940

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

NASA Technical Reports Server (NTRS)

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.

A mixed model framework for teratology studies.

PubMed

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.

Multilevel mixed effects parametric survival models using adaptive Gauss-Hermite quadrature with application to recurrent events and individual participant data meta-analysis.

PubMed

Crowther, Michael J; Look, Maxime P; Riley, Richard D

2014-09-28

Multilevel mixed effects survival models are used in the analysis of clustered survival data, such as repeated events, multicenter clinical trials, and individual participant data (IPD) meta-analyses, to investigate heterogeneity in baseline risk and covariate effects. In this paper, we extend parametric frailty models including the exponential, Weibull and Gompertz proportional hazards (PH) models and the log logistic, log normal, and generalized gamma accelerated failure time models to allow any number of normally distributed random effects. Furthermore, we extend the flexible parametric survival model of Royston and Parmar, modeled on the log-cumulative hazard scale using restricted cubic splines, to include random effects while also allowing for non-PH (time-dependent effects). Maximum likelihood is used to estimate the models utilizing adaptive or nonadaptive Gauss-Hermite quadrature. The methods are evaluated through simulation studies representing clinically plausible scenarios of a multicenter trial and IPD meta-analysis, showing good performance of the estimation method. The flexible parametric mixed effects model is illustrated using a dataset of patients with kidney disease and repeated times to infection and an IPD meta-analysis of prognostic factor studies in patients with breast cancer. User-friendly Stata software is provided to implement the methods. Copyright © 2014 John Wiley & Sons, Ltd.

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

PubMed Central

Wang, Yuanjia; Chen, Huaihou

2012-01-01

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

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

PubMed

Wang, Yuanjia; Chen, Huaihou

2012-12-01

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

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

PubMed

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.

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

PubMed

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

2015-04-01

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

Experimental and mathematical model of the interactions in the mixed culture of links in the “producer-consumer” cycle

NASA Astrophysics Data System (ADS)

Pisman, T. I.

2009-07-01

The paper presents a experimental and mathematical model of interactions between invertebrates (the ciliates Paramecium caudatum and the rotifers Brachionus plicatilis) in the "producer-consumer" aquatic biotic cycle with spatially separated components. The model describes the dynamics of the mixed culture of ciliates and rotifers in the "consumer" component, feeding on the mixed algal culture of the "producer" component. It has been found that metabolites of the algae Scenedesmus produce an adverse effect on the reproduction of the ciliates P. caudatum. Taking into account this effect, the results of investigation of the mathematical model were in qualitative agreement with the experimental results. In the "producer-consumer" biotic cycle it was shown that coexistence is impossible in the mixed culture of invertebrates of the "consumer" component. The ciliates P. caudatum are driven out by the rotifers B. plicatilis.

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

NASA Astrophysics Data System (ADS)

Dietmüller, Simone; Garny, Hella; Plöger, Felix; Jöckel, Patrick; Cai, Duy

2017-06-01

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.

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

ERIC Educational Resources Information Center

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…

Physical Modelling of the Effect of Slag and Top-Blowing on Mixing in the AOD Process

NASA Astrophysics Data System (ADS)

Haas, Tim; Visuri, Ville-Valtteri; Kärnä, Aki; Isohookana, Erik; Sulasalmi, Petri; Eriç, Rauf Hürman; Pfeifer, Herbert; Fabritius, Timo

The argon-oxygen decarburization (AOD) process is the most common process for refining stainless steel. High blowing rates and the resulting efficient mixing of the steel bath are characteristic of the AOD process. In this work, a 1:9-scale physical model was used to study mixing in a 150 t AOD vessel. Water, air and rapeseed oil were used to represent steel, argon and slag, respectively, while the dynamic similarity with the actual converter was maintained using the modified Froude number and the momentum number. Employing sulfuric acid as a tracer, the mixing times were determined on the basis of pH measurements according to the 97.5% criterion. The gas blowing rate and slag-steel volume ratio were varied in order to study their effect on the mixing time. The effect of top-blowing was also investigated. The results suggest that mixing time decreases as the modified Froude number of the tuyères increases and that the presence of a slag layer increases the mixing time. Furthermore, top-blowing was found to increase the mixing time both with and without the slag layer.

Mixing states of aerosols over four environmentally distinct atmospheric regimes in Asia: coastal, urban, and industrial locations influenced by dust.

PubMed

Ramachandran, S; Srivastava, Rohit

2016-06-01

Mixing can influence the optical, physical, and chemical characteristics of aerosols, which in turn can modify their life cycle and radiative effects. Assumptions on the mixing state can lead to uncertain estimates of aerosol radiative effects. To examine the effect of mixing on the aerosol characteristics, and their influence on radiative effects, aerosol mixing states are determined over four environmentally distinct locations (Karachi, Gwangju, Osaka, and Singapore) in Asia, an aerosol hot spot region, using measured spectral aerosol optical properties and optical properties model. Aerosol optical depth (AOD), single scattering albedo (SSA), and asymmetry parameter (g) exhibit spectral, spatial, and temporal variations. Aerosol mixing states exhibit large spatial and temporal variations consistent with aerosol characteristics and aerosol type over each location. External mixing of aerosol species is unable to reproduce measured SSA over Asia, thus providing a strong evidence that aerosols exist in mixed state. Mineral dust (MD) (core)-Black carbon (BC) (shell) is one of the most preferred aerosol mixing states. Over locations influenced by biomass burning aerosols, BC (core)-water soluble (WS, shell) is a preferred mixing state, while dust gets coated by anthropogenic aerosols (BC, WS) over urban regions influenced by dust. MD (core)-sea salt (shell) mixing is found over Gwangju corroborating the observations. Aerosol radiative forcing exhibits large seasonal and spatial variations consistent with features seen in aerosol optical properties and mixing states. TOA forcing is less negative/positive for external mixing scenario because of lower SSA. Aerosol radiative forcing in Karachi is a factor of 2 higher when compared to Gwangju, Osaka, and Singapore. The influence of g on aerosol radiative forcing is insignificant. Results emphasize that rather than prescribing one single aerosol mixing state in global climate models regionally and temporally varying aerosol mixing states should be included for more accurate assessment of aerosol radiative effects.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

PubMed

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

2017-01-01

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

Mixed-effects Gaussian process functional regression models with application to dose-response curve prediction.

PubMed

Shi, J Q; Wang, B; Will, E J; West, R M

2012-11-20

We propose a new semiparametric model for functional regression analysis, combining a parametric mixed-effects model with a nonparametric Gaussian process regression model, namely a mixed-effects Gaussian process functional regression model. The parametric component can provide explanatory information between the response and the covariates, whereas the nonparametric component can add nonlinearity. We can model the mean and covariance structures simultaneously, combining the information borrowed from other subjects with the information collected from each individual subject. We apply the model to dose-response curves that describe changes in the responses of subjects for differing levels of the dose of a drug or agent and have a wide application in many areas. We illustrate the method for the management of renal anaemia. An individual dose-response curve is improved when more information is included by this mechanism from the subject/patient over time, enabling a patient-specific treatment regime. Copyright © 2012 John Wiley & Sons, Ltd.

Impact of Antarctic mixed-phase clouds on climate

DOE PAGES

Lawson, R. Paul; Gettelman, Andrew

2014-12-08

Precious little is known about the composition of low-level clouds over the Antarctic Plateau and their effect on climate. In situ measurements at the South Pole using a unique tethered balloon system and ground-based lidar reveal a much higher than anticipated incidence of low-level, mixed-phase clouds (i.e., consisting of supercooled liquid water drops and ice crystals). The high incidence of mixed-phase clouds is currently poorly represented in global climate models (GCMs). As a result, the effects that mixed-phase clouds have on climate predictions are highly uncertain. In this paper, we modify the National Center for Atmospheric Research (NCAR) Community Earthmore » System Model (CESM) GCM to align with the new observations and evaluate the radiative effects on a continental scale. The net cloud radiative effects (CREs) over Antarctica are increased by +7.4 Wm –2, and although this is a significant change, a much larger effect occurs when the modified model physics are extended beyond the Antarctic continent. The simulations show significant net CRE over the Southern Ocean storm tracks, where recent measurements also indicate substantial regions of supercooled liquid. Finally, these sensitivity tests confirm that Southern Ocean CREs are strongly sensitive to mixed-phase clouds colder than –20 °C.« less

Transition mixing study empirical model report

NASA Technical Reports Server (NTRS)

Srinivasan, R.; White, C.

1988-01-01

The empirical model developed in the NASA Dilution Jet Mixing Program has been extended to include the curvature effects of transition liners. This extension is based on the results of a 3-D numerical model generated under this contract. The empirical model results agree well with the numerical model results for all tests cases evaluated. The empirical model shows faster mixing rates compared to the numerical model. Both models show drift of jets toward the inner wall of a turning duct. The structure of the jets from the inner wall does not exhibit the familiar kidney-shaped structures observed for the outer wall jets or for jets injected in rectangular ducts.

A new unsteady mixing model to predict NO(x) production during rapid mixing in a dual-stage combustor

NASA Technical Reports Server (NTRS)

Menon, Suresh

1992-01-01

An advanced gas turbine engine to power supersonic transport aircraft is currently under study. In addition to high combustion efficiency requirements, environmental concerns have placed stringent restrictions on the pollutant emissions from these engines. A combustor design with the potential for minimizing pollutants such as NO(x) emissions is undergoing experimental evaluation. A major technical issue in the design of this combustor is how to rapidly mix the hot, fuel-rich primary zone product with the secondary diluent air to obtain a fuel-lean mixture for combustion in the second stage. Numerical predictions using steady-state methods cannot account for the unsteady phenomena in the mixing region. Therefore, to evaluate the effect of unsteady mixing and combustion processes, a novel unsteady mixing model is demonstrated here. This model has been used to study multispecies mixing as well as propane-air and hydrogen-air jet nonpremixed flames, and has been used to predict NO(x) production in the mixing region. Comparison with available experimental data show good agreement, thereby providing validation of the mixing model. With this demonstration, this mixing model is ready to be implemented in conjunction with steady-state prediction methods and provide an improved engineering design analysis tool.

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

NASA Astrophysics Data System (ADS)

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.

A systematic comparison of two-equation Reynolds-averaged Navier-Stokes turbulence models applied to shock-cloud interactions

NASA Astrophysics Data System (ADS)

Goodson, Matthew D.; Heitsch, Fabian; Eklund, Karl; Williams, Virginia A.

2017-07-01

Turbulence models attempt to account for unresolved dynamics and diffusion in hydrodynamical simulations. We develop a common framework for two-equation Reynolds-averaged Navier-Stokes turbulence models, and we implement six models in the athena code. We verify each implementation with the standard subsonic mixing layer, although the level of agreement depends on the definition of the mixing layer width. We then test the validity of each model into the supersonic regime, showing that compressibility corrections can improve agreement with experiment. For models with buoyancy effects, we also verify our implementation via the growth of the Rayleigh-Taylor instability in a stratified medium. The models are then applied to the ubiquitous astrophysical shock-cloud interaction in three dimensions. We focus on the mixing of shock and cloud material, comparing results from turbulence models to high-resolution simulations (up to 200 cells per cloud radius) and ensemble-averaged simulations. We find that the turbulence models lead to increased spreading and mixing of the cloud, although no two models predict the same result. Increased mixing is also observed in inviscid simulations at resolutions greater than 100 cells per radius, which suggests that the turbulent mixing begins to be resolved.

Functional mixed effects spectral analysis

PubMed Central

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

2011-01-01

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

The prediction of sea-surface temperature variations by means of an advective mixed-layer ocean model

NASA Technical Reports Server (NTRS)

Atlas, R. M.

1976-01-01

An advective mixed layer ocean model was developed by eliminating the assumption of horizontal homogeneity in an already existing mixed layer model, and then superimposing a mean and anomalous wind driven current field. This model is based on the principle of conservation of heat and mechanical energy and utilizes a box grid for the advective part of the calculation. Three phases of experiments were conducted: evaluation of the model's ability to account for climatological sea surface temperature (SST) variations in the cooling and heating seasons, sensitivity tests in which the effect of hypothetical anomalous winds was evaluated, and a thirty-day synoptic calculation using the model. For the case studied, the accuracy of the predictions was improved by the inclusion of advection, although nonadvective effects appear to have dominated.

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

PubMed

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).

Logistic Mixed Models to Investigate Implicit and Explicit Belief Tracking

PubMed Central

Lages, Martin; Scheel, Anne

2016-01-01

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

Numerical Study of Mixing Thermal Conductivity Models for Nanofluid Heat Transfer Enhancement

NASA Astrophysics Data System (ADS)

Pramuanjaroenkij, A.; Tongkratoke, A.; Kakaç, S.

2018-01-01

Researchers have paid attention to nanofluid applications, since nanofluids have revealed their potentials as working fluids in many thermal systems. Numerical studies of convective heat transfer in nanofluids can be based on considering them as single- and two-phase fluids. This work is focused on improving the single-phase nanofluid model performance, since the employment of this model requires less calculation time and it is less complicated due to utilizing the mixing thermal conductivity model, which combines static and dynamic parts used in the simulation domain alternately. The in-house numerical program has been developed to analyze the effects of the grid nodes, effective viscosity model, boundary-layer thickness, and of the mixing thermal conductivity model on the nanofluid heat transfer enhancement. CuO-water, Al2O3-water, and Cu-water nanofluids are chosen, and their laminar fully developed flows through a rectangular channel are considered. The influence of the effective viscosity model on the nanofluid heat transfer enhancement is estimated through the average differences between the numerical and experimental results for the nanofluids mentioned. The nanofluid heat transfer enhancement results show that the mixing thermal conductivity model consisting of the Maxwell model as the static part and the Yu and Choi model as the dynamic part, being applied to all three nanofluids, brings the numerical results closer to the experimental ones. The average differences between those results for CuO-water, Al2O3-water, and CuO-water nanofluid flows are 3.25, 2.74, and 3.02%, respectively. The mixing thermal conductivity model has been proved to increase the accuracy of the single-phase nanofluid simulation and to reveal its potentials in the single-phase nanofluid numerical studies.

Equatorial waves in the NCAR stratospheric general circulation model

NASA Technical Reports Server (NTRS)

Boville, B. A.

1985-01-01

Equatorially trapped wave modes are very important in the tropical stratospheric momentum balance. Kelvin waves and mixed Rossby-gravity waves are believed to be responsible for the quasi-biennial oscillation of the zonal winds in the equatorial lower stratosphere. Both Kelvin and mixed Rossby-gravity waves have been identified in observations and in numerical models. Kelvin and mixed Rossby-gravity waves are identified in a general circulation model extending from the surface into the mesosphere and looks at the effect on the waves of lowering the top of the model.

MIXREG: a computer program for mixed-effects regression analysis with autocorrelated errors.

PubMed

Hedeker, D; Gibbons, R D

1996-05-01

MIXREG is a program that provides estimates for a mixed-effects regression model (MRM) for normally-distributed response data including autocorrelated errors. This model can be used for analysis of unbalanced longitudinal data, where individuals may be measured at a different number of timepoints, or even at different timepoints. Autocorrelated errors of a general form or following an AR(1), MA(1), or ARMA(1,1) form are allowable. This model can also be used for analysis of clustered data, where the mixed-effects model assumes data within clusters are dependent. The degree of dependency is estimated jointly with estimates of the usual model parameters, thus adjusting for clustering. MIXREG uses maximum marginal likelihood estimation, utilizing both the EM algorithm and a Fisher-scoring solution. For the scoring solution, the covariance matrix of the random effects is expressed in its Gaussian decomposition, and the diagonal matrix reparameterized using the exponential transformation. Estimation of the individual random effects is accomplished using an empirical Bayes approach. Examples illustrating usage and features of MIXREG are provided.

Generalized linear mixed models with varying coefficients for longitudinal data.

PubMed

Zhang, Daowen

2004-03-01

The routinely assumed parametric functional form in the linear predictor of a generalized linear mixed model for longitudinal data may be too restrictive to represent true underlying covariate effects. We relax this assumption by representing these covariate effects by smooth but otherwise arbitrary functions of time, with random effects used to model the correlation induced by among-subject and within-subject variation. Due to the usually intractable integration involved in evaluating the quasi-likelihood function, the double penalized quasi-likelihood (DPQL) approach of Lin and Zhang (1999, Journal of the Royal Statistical Society, Series B61, 381-400) is used to estimate the varying coefficients and the variance components simultaneously by representing a nonparametric function by a linear combination of fixed effects and random effects. A scaled chi-squared test based on the mixed model representation of the proposed model is developed to test whether an underlying varying coefficient is a polynomial of certain degree. We evaluate the performance of the procedures through simulation studies and illustrate their application with Indonesian children infectious disease data.

Bias and inference from misspecified mixed-effect models in stepped wedge trial analysis.

PubMed

Thompson, Jennifer A; Fielding, Katherine L; Davey, Calum; Aiken, Alexander M; Hargreaves, James R; Hayes, Richard J

2017-10-15

Many stepped wedge trials (SWTs) are analysed by using a mixed-effect model with a random intercept and fixed effects for the intervention and time periods (referred to here as the standard model). However, it is not known whether this model is robust to misspecification. We simulated SWTs with three groups of clusters and two time periods; one group received the intervention during the first period and two groups in the second period. We simulated period and intervention effects that were either common-to-all or varied-between clusters. Data were analysed with the standard model or with additional random effects for period effect or intervention effect. In a second simulation study, we explored the weight given to within-cluster comparisons by simulating a larger intervention effect in the group of the trial that experienced both the control and intervention conditions and applying the three analysis models described previously. Across 500 simulations, we computed bias and confidence interval coverage of the estimated intervention effect. We found up to 50% bias in intervention effect estimates when period or intervention effects varied between clusters and were treated as fixed effects in the analysis. All misspecified models showed undercoverage of 95% confidence intervals, particularly the standard model. A large weight was given to within-cluster comparisons in the standard model. In the SWTs simulated here, mixed-effect models were highly sensitive to departures from the model assumptions, which can be explained by the high dependence on within-cluster comparisons. Trialists should consider including a random effect for time period in their SWT analysis model. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Modeling condensation with a noncondensable gas for mixed convection flow

NASA Astrophysics Data System (ADS)

Liao, Yehong

2007-05-01

This research theoretically developed a novel mixed convection model for condensation with a noncondensable gas. The model developed herein is comprised of three components: a convection regime map; a mixed convection correlation; and a generalized diffusion layer model. These components were developed in a way to be consistent with the three-level methodology in MELCOR. The overall mixed convection model was implemented into MELCOR and satisfactorily validated with data covering a wide variety of test conditions. In the development of the convection regime map, two analyses with approximations of the local similarity method were performed to solve the multi-component two-phase boundary layer equations. The first analysis studied effects of the bulk velocity on a basic natural convection condensation process and setup conditions to distinguish natural convection from mixed convection. It was found that the superimposed velocity increases condensation heat transfer by sweeping away the noncondensable gas accumulated at the condensation boundary. The second analysis studied effects of the buoyancy force on a basic forced convection condensation process and setup conditions to distinguish forced convection from mixed convection. It was found that the superimposed buoyancy force increases condensation heat transfer by thinning the liquid film thickness and creating a steeper noncondensable gas concentration profile near the condensation interface. In the development of the mixed convection correlation accounting for suction effects, numerical data were obtained from boundary layer analysis for the three convection regimes and used to fit a curve for the Nusselt number of the mixed convection regime as a function of the Nusselt numbers of the natural and forced convection regimes. In the development of the generalized diffusion layer model, the driving potential for mass transfer was expressed as the temperature difference between the bulk and the liquid-gas interface using the Clausius-Clapeyron equation. The model was developed on a mass basis instead of a molar basis to be consistent with general conservation equations. It was found that vapor diffusion is not only driven by a gradient of the molar fraction but also a gradient of the mixture molecular weight at the diffusion layer.

Estimating the numerical diapycnal mixing in the GO5.0 ocean model

NASA Astrophysics Data System (ADS)

Megann, Alex; Nurser, George

2014-05-01

Constant-depth (or "z-coordinate") ocean models such as MOM 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 (e.g. Hofmann and Maqueda, 2006), 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 typical 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, 2013). It uses version 3.4 of the NEMO model, on the ORCA025 global tripolar grid. Two approaches to quantifying the numerical diapycnal mixing in this model are described: the first is based on the isopycnal watermass analysis of Lee et al (2002), while the second uses a passive tracer to diagnose mixing across density surfaces. Results from these two methods will be compared and contrasted. Hofmann, M. and Maqueda, M. A. M., 2006. Performance of a second-order moments advection scheme in an ocean general circulation model. JGR-Oceans, 111(C5). Lee, M.-M., Coward, A.C., Nurser, A.G., 2002. Spurious diapycnal mixing of deep waters in an eddy-permitting global ocean model. JPO 32, 1522-1535 Megann, A., Storkey, D., Aksenov, Y., Alderson, S., Calvert, D., Graham, T., Hyder, P., Siddorn, J., and Sinha, B., 2013: GO5.0: The joint NERC-Met Office NEMO global ocean model for use in coupled and forced applications, Geosci. Model Dev. Discuss., 6, 5747-5799,.

Attribution of horizontal and vertical contributions to spurious mixing in an Arbitrary Lagrangian-Eulerian ocean model

NASA Astrophysics Data System (ADS)

Gibson, Angus H.; Hogg, Andrew McC.; Kiss, Andrew E.; Shakespeare, Callum J.; Adcroft, Alistair

2017-11-01

We examine the separate contributions to spurious mixing from horizontal and vertical processes in an ALE ocean model, MOM6, using reference potential energy (RPE). The RPE is a global diagnostic which changes only due to mixing between density classes. We extend this diagnostic to a sub-timestep timescale in order to individually separate contributions to spurious mixing through horizontal (tracer advection) and vertical (regridding/remapping) processes within the model. We both evaluate the overall spurious mixing in MOM6 against previously published output from other models (MOM5, MITGCM and MPAS-O), and investigate impacts on the components of spurious mixing in MOM6 across a suite of test cases: a lock exchange, internal wave propagation, and a baroclinically-unstable eddying channel. The split RPE diagnostic demonstrates that the spurious mixing in a lock exchange test case is dominated by horizontal tracer advection, due to the spatial variability in the velocity field. In contrast, the vertical component of spurious mixing dominates in an internal waves test case. MOM6 performs well in this test case owing to its quasi-Lagrangian implementation of ALE. Finally, the effects of model resolution are examined in a baroclinic eddies test case. In particular, the vertical component of spurious mixing dominates as horizontal resolution increases, an important consideration as global models evolve towards higher horizontal resolutions.

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

PubMed

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

2017-02-01

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

Investigating the effect of cardiac oscillations and deadspace gas mixing during apnea using computer simulation.

PubMed

Laviola, Marianna; Das, Anup; Chikhani, Marc; Bates, Declan G; Hardman, Jonathan G

2017-07-01

Gaseous mixing in the anatomical deadspace with stimulation of respiratory ventilation through cardiogenic oscillations is an important physiological mechanism at the onset of apnea, which has been credited with various beneficial effects, e.g. reduction of hypercapnia during the use of low flow ventilation techniques. In this paper, a novel method is proposed to investigate the effect of these mechanisms in silico. An existing computational model of cardio-pulmonary physiology is extended to include the apneic state, gas mixing within the anatomical deadspace, insufflation into the trachea and cardiogenic oscillations. The new model is validated against data published in an experimental animal (dog) study that reported an increase in arterial partial pressure of carbon dioxide (PaCO 2 ) during apnea. Computational simulations confirm that the model outputs accurately reproduce the available experimental data. This new model can be used to investigate the physiological mechanisms underlying clearance of carbon dioxide during apnea, and hence to develop more effective ventilation strategies for apneic patients.

The Effect of a Dissipative Ladle Shroud on Mixing in Tundish: Mathematical and Experimental Modelling

NASA Astrophysics Data System (ADS)

Zhang, Jiangshan; Yang, Shufeng; Li, Jingshe; Tang, Haiyan; Jiang, Zhengyi

2018-01-01

The effect of a dissipative ladle shroud (DLS) on mixing in tundish was investigated, compared with that of a conventional ladle shroud (CLS) using mathematical and physical modelling. The tracer profiles of mathematical results, achieved using large eddy simulation, were validated by physical observations employing high-speed cinephotography. The design of a DLS dramatically changed the flow patterns and contributed the intermixing of fluid elements inside the ladle shroud. The vortex flow encouraged the turbulent mixing and was verified by tracking of physical tracer dispersion inside the DLS. Residence Time Distribution (RTD) curves were obtained in two different sized tundishes to examine the mixing behaviours. The findings indicated that the DLS benefited the tundish mixing in terms of increasing active volume. The effect seemed to be more remarkable in the smaller tundish. The DLS gave rise to a more plug-like flow pattern inside the tundish, showing potential to shorten the transition length during grade change.

Drizzle formation in stratocumulus clouds: Effects of turbulent mixing

DOE PAGES

Magaritz-Ronen, L.; Pinsky, M.; Khain, A.

2016-02-17

The mechanism of drizzle formation in shallow stratocumulus clouds and the effect of turbulent mixing on this process are investigated. A Lagrangian–Eularian model of the cloud-topped boundary layer is used to simulate the cloud measured during flight RF07 of the DYCOMS-II field experiment. The model contains ~ 2000 air parcels that are advected in a turbulence-like velocity field. In the model all microphysical processes are described for each Lagrangian air volume, and turbulent mixing between the parcels is also taken into account. It was found that the first large drops form in air volumes that are closest to adiabatic andmore » characterized by high humidity, extended residence near cloud top, and maximum values of liquid water content, allowing the formation of drops as a result of efficient collisions. The first large drops form near cloud top and initiate drizzle formation in the cloud. Drizzle is developed only when turbulent mixing of parcels is included in the model. Without mixing, the cloud structure is extremely inhomogeneous and the few large drops that do form in the cloud evaporate during their sedimentation. Lastly, it was found that turbulent mixing can delay the process of drizzle initiation but is essential for the further development of drizzle in the cloud.« less

Drizzle formation in stratocumulus clouds: Effects of turbulent mixing

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

Magaritz-Ronen, L.; Pinsky, M.; Khain, A.

The mechanism of drizzle formation in shallow stratocumulus clouds and the effect of turbulent mixing on this process are investigated. A Lagrangian–Eularian model of the cloud-topped boundary layer is used to simulate the cloud measured during flight RF07 of the DYCOMS-II field experiment. The model contains ~ 2000 air parcels that are advected in a turbulence-like velocity field. In the model all microphysical processes are described for each Lagrangian air volume, and turbulent mixing between the parcels is also taken into account. It was found that the first large drops form in air volumes that are closest to adiabatic andmore » characterized by high humidity, extended residence near cloud top, and maximum values of liquid water content, allowing the formation of drops as a result of efficient collisions. The first large drops form near cloud top and initiate drizzle formation in the cloud. Drizzle is developed only when turbulent mixing of parcels is included in the model. Without mixing, the cloud structure is extremely inhomogeneous and the few large drops that do form in the cloud evaporate during their sedimentation. Lastly, it was found that turbulent mixing can delay the process of drizzle initiation but is essential for the further development of drizzle in the cloud.« less

Investigation of Compressibility Effect for Aeropropulsive Shear Flows

NASA Technical Reports Server (NTRS)

Balasubramanyam, M. S.; Chen, C. P.

2005-01-01

Rocket Based Combined Cycle (RBCC) engines operate within a wide range of Mach numbers and altitudes. Fundamental fluid dynamic mechanisms involve complex choking, mass entrainment, stream mixing and wall interactions. The Propulsion Research Center at the University of Alabama in Huntsville is involved in an on- going experimental and numerical modeling study of non-axisymmetric ejector-based combined cycle propulsion systems. This paper attempts to address the modeling issues related to mixing, shear layer/wall interaction in a supersonic Strutjet/ejector flow field. Reynolds Averaged Navier-Stokes (RANS) solutions incorporating turbulence models are sought and compared to experimental measurements to characterize detailed flow dynamics. The effect of compressibility on fluids mixing and wall interactions were investigated using an existing CFD methodology. The compressibility correction to conventional incompressible two- equation models is found to be necessary for the supersonic mixing aspect of the ejector flows based on 2-D simulation results. 3-D strut-base flows involving flow separations were also investigated.

A Methodology for Identifying Cost Effective Strategic Force Mixes.

DTIC Science & Technology

1984-12-01

is not to say that the model could not be used to examine force increases. Given that the strategic force is already a mix of weapons, what is the...rules allow for the determination of what weapon mix to buy based on only the relative prices of the weapons and the parameters of the CES production...AD-A 151 773 AFIT/GOR/OS/84j /r A METHODOLOGY FOR IDENTIFYING COST EFFECTIVE STRATEGIC FORCE MIXES THESIS D I Thomas W. Manacapilli

Making a mixed-model line more efficient and flexible by introducing a bypass line

NASA Astrophysics Data System (ADS)

Matsuura, Sho; Matsuura, Haruki; Asada, Akiko

2017-04-01

This paper provides a design procedure for the bypass subline in a mixed-model assembly line. The bypass subline is installed to reduce the effect of the large difference in operation times among products assembled together in a mixed-model line. The importance of the bypass subline has been increasing in association with the rising necessity for efficiency and flexibility in modern manufacturing. The main topics of this paper are as follows: 1) the conditions in which the bypass subline effectively functions, and 2) how the load should be distributed between the main line and the bypass subline, depending on production conditions such as degree of difference in operation times among products and the mixing ratio of products. To address these issues, we analyzed the lower and the upper bounds of the line length. Based on the results, a design procedure and a numerical example are demonstrated.

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

PubMed

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.

Analytical solution for reactive solute transport considering incomplete mixing within a reference elementary volume

NASA Astrophysics Data System (ADS)

Chiogna, Gabriele; Bellin, Alberto

2013-05-01

The laboratory experiments of Gramling et al. (2002) showed that incomplete mixing at the pore scale exerts a significant impact on transport of reactive solutes and that assuming complete mixing leads to overestimation of product concentration in bimolecular reactions. Successively, several attempts have been made to model this experiment, either considering spatial segregation of the reactants, non-Fickian transport applying a Continuous Time Random Walk (CTRW) or an effective upscaled time-dependent kinetic reaction term. Previous analyses of these experimental results showed that, at the Darcy scale, conservative solute transport is well described by a standard advection dispersion equation, which assumes complete mixing at the pore scale. However, reactive transport is significantly affected by incomplete mixing at smaller scales, i.e., within a reference elementary volume (REV). We consider here the family of equilibrium reactions for which the concentration of the reactants and the product can be expressed as a function of the mixing ratio, the concentration of a fictitious non reactive solute. For this type of reactions we propose, in agreement with previous studies, to model the effect of incomplete mixing at scales smaller than the Darcy scale assuming that the mixing ratio is distributed within an REV according to a Beta distribution. We compute the parameters of the Beta model by imposing that the mean concentration is equal to the value that the concentration assumes at the continuum Darcy scale, while the variance decays with time as a power law. We show that our model reproduces the concentration profiles of the reaction product measured in the Gramling et al. (2002) experiments using the transport parameters obtained from conservative experiments and an instantaneous reaction kinetic. The results are obtained applying analytical solutions both for conservative and for reactive solute transport, thereby providing a method to handle the effect of incomplete mixing on multispecies reactive solute transport, which is simpler than other previously developed methods.

Finite element modeling and analysis of tires

NASA Technical Reports Server (NTRS)

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

1983-01-01

Predicting the response of tires under various loading conditions using finite element technology is addressed. Some of the recent advances in finite element technology which have high potential for application to tire modeling problems are reviewed. The analysis and modeling needs for tires are identified. Reduction methods for large-scale nonlinear analysis, with particular emphasis on treatment of combined loads, displacement-dependent and nonconservative loadings; development of simple and efficient mixed finite element models for shell analysis, identification of equivalent mixed and purely displacement models, and determination of the advantages of using mixed models; and effective computational models for large-rotation nonlinear problems, based on a total Lagrangian description of the deformation are included.

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

PubMed

Rajeswaran, Jeevanantham; Blackstone, Eugene H

2017-02-01

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

The Evaluation of Bivariate Mixed Models in Meta-analyses of Diagnostic Accuracy Studies with SAS, Stata and R.

PubMed

Vogelgesang, Felicitas; Schlattmann, Peter; Dewey, Marc

2018-05-01

Meta-analyses require a thoroughly planned procedure to obtain unbiased overall estimates. From a statistical point of view not only model selection but also model implementation in the software affects the results. The present simulation study investigates the accuracy of different implementations of general and generalized bivariate mixed models in SAS (using proc mixed, proc glimmix and proc nlmixed), Stata (using gllamm, xtmelogit and midas) and R (using reitsma from package mada and glmer from package lme4). Both models incorporate the relationship between sensitivity and specificity - the two outcomes of interest in meta-analyses of diagnostic accuracy studies - utilizing random effects. Model performance is compared in nine meta-analytic scenarios reflecting the combination of three sizes for meta-analyses (89, 30 and 10 studies) with three pairs of sensitivity/specificity values (97%/87%; 85%/75%; 90%/93%). The evaluation of accuracy in terms of bias, standard error and mean squared error reveals that all implementations of the generalized bivariate model calculate sensitivity and specificity estimates with deviations less than two percentage points. proc mixed which together with reitsma implements the general bivariate mixed model proposed by Reitsma rather shows convergence problems. The random effect parameters are in general underestimated. This study shows that flexibility and simplicity of model specification together with convergence robustness should influence implementation recommendations, as the accuracy in terms of bias was acceptable in all implementations using the generalized approach. Schattauer GmbH.

Modeling of mixing in 96-well microplates observed with fluorescence indicators.

PubMed

Weiss, Svenja; John, Gernot T; Klimant, Ingo; Heinzle, Elmar

2002-01-01

Mixing in 96-well microplates was studied using soluble pH indicators and a fluorescence pH sensor. Small amounts of alkali were added with the aid of a multichannel pipet, a piston pump, and a piezoelectric actuator. Mixing patterns were observed visually using a video camera. Addition of drops each of about 1 nL with the piezoelectric actuator resulted in umbrella and double-disklike shapes. Convective mixing was mainly observed in the upper part of the well, whereas the lower part was only mixed quickly when using the multichannel pipet and the piston pump with an addition volume of 5 microL or larger. Estimated mixing times were between a few seconds and several minutes. Mixing by liquid dispensing was much more effective than by shaking. A mixing model consisting of 21 elements could describe mixing dynamics observed by the dissolved fluorescence dye and by the optical immobilized pH sensor. This model can be applied for designing pH control in microplates or for design of kinetic experiments with liquid addition.

Parametric Study of a Mixer/Ejector Nozzle with Mixing Enhancement Devices

NASA Technical Reports Server (NTRS)

DalBello, T.; Steffen, C. J., Jr.

2001-01-01

A numerical study employing a simplified model of the High Speed Civil Transport mixer/ejector nozzle has been conducted to investigate the effect of tabs (vortex generators) on the mixing process. More complete mixing of the primary and secondary flows within the confined ejector lowers peak exit velocity resulting in reduced jet noise. Tabs were modeled as vortex pairs and inserted into the computational model. The location, size, and number of tabs were varied and its effect on the mixing process is presented here both quantitatively and qualitatively. A baseline case (no tabs) along with six other cases involving two different vortex strengths at three different orientations have been computed and analyzed. The case with the highest vorticity (six vortices representing large tabs) gives the best mixing. It is shown that the influence of the vorticity acts primarily in the forward or middle portions of the duct, significantly alters the flow structure, and promotes some mixing in the lateral direction. Unmixed pockets were found at the top and bottom of the lobe, and more clever placement of tabs improved mixing in the vertical direction. The technique of replacing tabs with vortices shows promise as an efficient tool for quickly optimizing tab placement in lobed mixers.

Singlet model interference effects with high scale UV physics

DOE PAGES

Dawson, S.; Lewis, I. M.

2017-01-06

One of the simplest extensions of the Standard Model (SM) is the addition of a scalar gauge singlet, S . If S is not forbidden by a symmetry from mixing with the Standard Model Higgs boson, the mixing will generate non-SM rates for Higgs production and decays. Generally, there could also be unknown high energy physics that generates additional effective low energy interactions. We show that interference effects between the scalar resonance of the singlet model and the effective field theory (EFT) operators can have significant effects in the Higgs sector. Here, we examine a non- Z 2 symmetricmore » scalar singlet model and demonstrate that a fit to the 125 GeV Higgs boson couplings and to limits on high mass resonances, S , exhibit an interesting structure and possible large cancellations of effects between the resonance contribution and the new EFT interactions, that invalidate conclusions based on the renormalizable singlet model alone.« less

Analysis and Modeling of a Two-Phase Jet Pump of a Thermal Management System for Aerospace Applications

NASA Technical Reports Server (NTRS)

Sherif, S.A.; Hunt, P. L.; Holladay, J. B.; Lear, W. E.; Steadham, J. M.

1998-01-01

Jet pumps are devices capable of pumping fluids to a higher pressure by inducing the motion of a secondary fluid employing a high speed primary fluid. The main components of a jet pump are a primary nozzle, secondary fluid injectors, a mixing chamber, a throat, and a diffuser. The work described in this paper models the flow of a two-phase primary fluid inducing a secondary liquid (saturated or subcooled) injected into the jet pump mixing chamber. The model is capable of accounting for phase transformations due to compression, expansion, and mixing. The model is also capable of incorporating the effects of the temperature and pressure dependency in the analysis. The approach adopted utilizes an isentropic constant pressure mixing in the mixing chamber and at times employs iterative techniques to determine the flow conditions in the different parts of the jet pump.

Modelling, fabrication and characterization of a polymeric micromixer based on sequential segmentation.

PubMed

Nguyen, Nam-Trung; Huang, Xiaoyang

2006-06-01

Effective and fast mixing is important for many microfluidic applications. In many cases, mixing is limited by molecular diffusion due to constrains of the laminar flow in the microscale regime. According to scaling law, decreasing the mixing path can shorten the mixing time and enhance mixing quality. One of the techniques for reducing mixing path is sequential segmentation. This technique divides solvent and solute into segments in axial direction. The so-called Taylor-Aris dispersion can improve axial transport by three orders of magnitudes. The mixing path can be controlled by the switching frequency and the mean velocity of the flow. Mixing ratio can be controlled by pulse width modulation of the switching signal. This paper first presents a simple time-dependent one-dimensional analytical model for sequential segmentation. The model considers an arbitrary mixing ratio between solute and solvent as well as the axial Taylor-Aris dispersion. Next, a micromixer was designed and fabricated based on polymeric micromachining. The micromixer was formed by laminating four polymer layers. The layers are micro machined by a CO(2) laser. Switching of the fluid flows was realized by two piezoelectric valves. Mixing experiments were evaluated optically. The concentration profile along the mixing channel agrees qualitatively well with the analytical model. Furthermore, mixing results at different switching frequencies were investigated. Due to the dynamic behavior of the valves and the fluidic system, mixing quality decreases with increasing switching frequency.

A corrected formulation for marginal inference derived from two-part mixed models for longitudinal semi-continuous data

PubMed Central

Su, Li; Farewell, Vernon T

2013-01-01

For semi-continuous data which are a mixture of true zeros and continuously distributed positive values, the use of two-part mixed models provides a convenient modelling framework. However, deriving population-averaged (marginal) effects from such models is not always straightforward. Su et al. presented a model that provided convenient estimation of marginal effects for the logistic component of the two-part model but the specification of marginal effects for the continuous part of the model presented in that paper was based on an incorrect formulation. We present a corrected formulation and additionally explore the use of the two-part model for inferences on the overall marginal mean, which may be of more practical relevance in our application and more generally. PMID:24201470

Characteristics of the mixing volume model with the interactions among spatially distributed particles for Lagrangian simulations of turbulent mixing

NASA Astrophysics Data System (ADS)

Watanabe, Tomoaki; Nagata, Koji

2016-11-01

The mixing volume model (MVM), which is a mixing model for molecular diffusion in Lagrangian simulations of turbulent mixing problems, is proposed based on the interactions among spatially distributed particles in a finite volume. The mixing timescale in the MVM is derived by comparison between the model and the subgrid scale scalar variance equation. A-priori test of the MVM is conducted based on the direct numerical simulations of planar jets. The MVM is shown to predict well the mean effects of the molecular diffusion under various conditions. However, a predicted value of the molecular diffusion term is positively correlated to the exact value in the DNS only when the number of the mixing particles is larger than two. Furthermore, the MVM is tested in the hybrid implicit large-eddy-simulation/Lagrangian-particle-simulation (ILES/LPS). The ILES/LPS with the present mixing model predicts well the decay of the scalar variance in planar jets. This work was supported by JSPS KAKENHI Nos. 25289030 and 16K18013. The numerical simulations presented in this manuscript were carried out on the high performance computing system (NEC SX-ACE) in the Japan Agency for Marine-Earth Science and Technology.

Flavor effects at the MeV and TeV scales

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

Machado, P. A. N., E-mail: pedro.machado@uam.es

2016-06-21

We provide a renormalizable model which encompasses a light Z′, at the O(100 MeV) scale with non trivial flavor structure. The Z′ can mix both with the photon by kinetic mixing and with the Z by mass mixing, exhibiting a rich low energy phenomenology. We emphasize the importance of considering the complete model, contemplating the scalar sector as well as the gauge sector. The model can satisfy all flavor constraints from quark and charged lepton flavor and still lead to observable non standard neutrino oscillation results.

Modeling the diurnal cycle of carbon monoxide: Sensitivity to physics, chemistry, biology, and optics

NASA Astrophysics Data System (ADS)

Gnanadesikan, Anand

1996-05-01

As carbon monoxide within the oceanic surface layer is produced by solar radiation, diluted by mixing, consumed by biota, and outgassed to the atmosphere, it exhibits a diurnal cycle. The effect of dilution and mixing on this cycle is examined using a simple model for production and consumption, coupled to three different mixed layer models. The magnitude and timing of the peak concentration, the magnitude of the average concentration, and the air-sea flux are considered. The models are run through a range of heating and wind stress and compared to experimental data reported by Kettle [1994]. The key to the dynamics is the relative size of four length scales; Dmix, the depth to which mixing occurs over the consumption time; L, the length scale over which production occurs; Lout, the depth to which the mixed layer is ventilated over the consumption time; and Lcomp, the depth to which the diurnal production can maintain a concentration in equilibrium with the atmosphere. If Dmix ≫ L, the actual model parameterization can be important. If the mixed layer is maintained by turbulent diffusion, Dmix can be substantially less than the mixed layer depth. If the mixed layer is parameterized as a homogeneous slab, Dmix is equivalent to the mixed layer depth. If Dmix > Lout, production is balanced by consumption rather than outgassing. The ratio between Dmix and Lcomp determines whether the ocean is a source or a sink for CO. The main thermocline depth H sets an upper limit for Dmix and hence Dmix/L, Dmix/Lout, and Dmix/Lcomp. The models are run to simulate a single day of observations. The mixing parameterization is shown to be very important, with a model which mixes using small-scale diffusion, producing markedly larger surface concentrations than models which homogenize the mixed layer completely and instantaneously.

Mixed quantum-classical simulation of the hydride transfer reaction catalyzed by dihydrofolate reductase based on a mapped system-harmonic bath model

NASA Astrophysics Data System (ADS)

Xu, Yang; Song, Kai; Shi, Qiang

2018-03-01

The hydride transfer reaction catalyzed by dihydrofolate reductase is studied using a recently developed mixed quantum-classical method to investigate the nuclear quantum effects on the reaction. Molecular dynamics simulation is first performed based on a two-state empirical valence bond potential to map the atomistic model to an effective double-well potential coupled to a harmonic bath. In the mixed quantum-classical simulation, the hydride degree of freedom is quantized, and the effective harmonic oscillator modes are treated classically. It is shown that the hydride transfer reaction rate using the mapped effective double-well/harmonic-bath model is dominated by the contribution from the ground vibrational state. Further comparison with the adiabatic reaction rate constant based on the Kramers theory confirms that the reaction is primarily vibrationally adiabatic, which agrees well with the high transmission coefficients found in previous theoretical studies. The calculated kinetic isotope effect is also consistent with the experimental and recent theoretical results.

Resolving Size Distribution of Black Carbon Internally Mixed With Snow: Impact on Snow Optical Properties and Albedo

NASA Astrophysics Data System (ADS)

He, Cenlin; Liou, Kuo-Nan; Takano, Yoshi

2018-03-01

We develop a stochastic aerosol-snow albedo model that explicitly resolves size distribution of aerosols internally mixed with various snow grains. We use the model to quantify black carbon (BC) size effects on snow albedo and optical properties for BC-snow internal mixing. Results show that BC-induced snow single-scattering coalbedo enhancement and albedo reduction decrease by a factor of 2-3 with increasing BC effective radii from 0.05 to 0.25 μm, while polydisperse BC results in up to 40% smaller visible single-scattering coalbedo enhancement and albedo reduction compared to monodisperse BC with equivalent effective radii. We further develop parameterizations for BC size effects for application to climate models. Compared with a realistic polydisperse assumption and observed shifts to larger BC sizes in snow, respectively, assuming monodisperse BC and typical atmospheric BC effective radii could lead to overestimates of 24% and 40% in BC-snow albedo forcing averaged over different BC and snow conditions.

A Mixed Learning Approach in Mechatronics Education

ERIC Educational Resources Information Center

Yilmaz, O.; Tuncalp, K.

2011-01-01

This study aims to investigate the effect of a Web-based mixed learning approach model on mechatronics education. The model combines different perception methods such as reading, listening, and speaking and practice methods developed in accordance with the vocational background of students enrolled in the course Electromechanical Systems in…

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

NASA Astrophysics Data System (ADS)

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

1996-11-01

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

Numerical Investigations of Wave-Induced Mixing in Upper Ocean Layer

NASA Astrophysics Data System (ADS)

Guan, Changlong

2017-04-01

The upper ocean layer is playing an important role in ocean-atmosphere interaction. The typical characteristics depicting the upper ocean layer are the sea surface temperature (SST) and the mixed layer depth (MLD). So far, the existing ocean models tend to over-estimate SST and to under-estimate MLD, due to the inadequate mixing in the mixing layer, which is owing to that several processes related mixing in physics are ignored in these ocean models. The mixing induced by surface gravity wave is expected to be able to enhance the mixing in the upper ocean layer, and therefore the over-estimation of SST and the under-estimate of MLD could be improved by including wave-induced mixing. The wave-induced mixing could be accomplished by the physical mechanisms, such as wave breaking (WB), wave-induced Reynolds stress (WR), and wave-turbulence interaction (WT). The General Ocean Turbulence Model (GOTM) is employed to investigate the effects of the three mechanisms concerning wave-induced mixing. The numerical investigation is carried out for three turbulence closure schemes, say, k-epsilon, k-omega and Mellor-Yamada (1982), with the observational data from OSC Papa station and wave data from ECMWF. The mixing enhancement by various waved-induced mixing mechanisms is investigated and verified.

Uncertainties in global aerosols and climate effects due to biofuel emissions

NASA Astrophysics Data System (ADS)

Kodros, J. K.; Scott, C. E.; Farina, S. C.; Lee, Y. H.; L'Orange, C.; Volckens, J.; Pierce, J. R.

2015-04-01

Aerosol emissions from biofuel combustion impact both health and climate; however, while reducing emissions through improvements to combustion technologies will improve health, the net effect on climate is largely unconstrained. In this study, we examine sensitivities in global aerosol concentration, direct radiative climate effect, and cloud-albedo aerosol indirect climate effect to uncertainties in biofuel emission factors, optical mixing-state, and model nucleation and background SOA. We use the Goddard Earth Observing System global chemical-transport model (GEOS-Chem) with TwO Moment Aerosol Sectional (TOMAS) microphysics. The emission factors include: amount, composition, size and hygroscopicity, as well as optical mixing-state properties. We also evaluate emissions from domestic coal use, which is not biofuel but is also frequently emitted from homes. We estimate the direct radiative effect assuming different mixing states (internal, core-shell, and external) with and without absorptive organic aerosol (brown carbon). We find the global-mean direct radiative effect of biofuel emissions ranges from -0.02 to +0.06 W m-2 across all simulation/mixing state combinations with regional effects in source regions ranging from -0.2 to +1.2 W m-2. The global-mean cloud-albedo aerosol indirect effect ranges from +0.01 to -0.02 W m-2 with regional effects in source regions ranging from -1.0 to -0.05 W m-2. The direct radiative effect is strongly dependent on uncertainties in emissions mass, composition, emissions aerosol size distributions and assumed optical mixing state, while the indirect effect is dependent on the emissions mass, emissions aerosol size distribution and the choice of model nucleation and secondary organic aerosol schemes. The sign and magnitude of these effects have a strong regional dependence. We conclude that the climate effects of biofuel aerosols are largely unconstrained, and the overall sign of the aerosol effects is unclear due to uncertainties in model inputs. This uncertainty limits our ability to introduce mitigation strategies aimed at reducing biofuel black carbon emissions in order to counter warming effects from greenhouse-gases. To better understand the climate impact of particle emissions from biofuel combustion, we recommend field/laboratory measurements to narrow constraints on: (1) emissions mass, (2) emission size distribution, (3) mixing state, and (4) ratio of black carbon to organic aerosol.

Uncertainties in global aerosols and climate effects due to biofuel emissions

NASA Astrophysics Data System (ADS)

Kodros, J. K.; Scott, C. E.; Farina, S. C.; Lee, Y. H.; L'Orange, C.; Volckens, J.; Pierce, J. R.

2015-08-01

Aerosol emissions from biofuel combustion impact both health and climate; however, while reducing emissions through improvements to combustion technologies will improve health, the net effect on climate is largely unconstrained. In this study, we examine sensitivities in global aerosol concentration, direct radiative climate effect, and cloud-albedo aerosol indirect climate effect to uncertainties in biofuel emission factors, optical mixing state, and model nucleation and background secondary organic aerosol (SOA). We use the Goddard Earth Observing System global chemical-transport model (GEOS-Chem) with TwO Moment Aerosol Sectional (TOMAS) microphysics. The emission factors include amount, composition, size, and hygroscopicity, as well as optical mixing-state properties. We also evaluate emissions from domestic coal use, which is not biofuel but is also frequently emitted from homes. We estimate the direct radiative effect assuming different mixing states (homogeneous, core-shell, and external) with and without absorptive organic aerosol (brown carbon). We find the global-mean direct radiative effect of biofuel emissions ranges from -0.02 to +0.06 W m-2 across all simulation/mixing-state combinations with regional effects in source regions ranging from -0.2 to +0.8 W m-2. The global-mean cloud-albedo aerosol indirect effect (AIE) ranges from +0.01 to -0.02 W m-2 with regional effects in source regions ranging from -1.0 to -0.05 W m-2. The direct radiative effect is strongly dependent on uncertainties in emissions mass, composition, emissions aerosol size distributions, and assumed optical mixing state, while the indirect effect is dependent on the emissions mass, emissions aerosol size distribution, and the choice of model nucleation and secondary organic aerosol schemes. The sign and magnitude of these effects have a strong regional dependence. We conclude that the climate effects of biofuel aerosols are largely unconstrained, and the overall sign of the aerosol effects is unclear due to uncertainties in model inputs. This uncertainty limits our ability to introduce mitigation strategies aimed at reducing biofuel black carbon emissions in order to counter warming effects from greenhouse gases. To better understand the climate impact of particle emissions from biofuel combustion, we recommend field/laboratory measurements to narrow constraints on (1) emissions mass, (2) emission size distribution, (3) mixing state, and (4) ratio of black carbon to organic aerosol.

Mixing Regimes in a Spatially Confined, Two-Dimensional, Supersonic Shear Layer

DTIC Science & Technology

1992-07-31

MODEL ................................... 3 THE MODEL PROBLEMS .............................................. 6 THE ONE-DIMENSIONAL PROBLEM...the effects of the numerical diffusion on the spectrum. Guirguis et al.ś and Farouk et al."’ have studied spatially evolving mixing layers for equal...approximations. Physical and Numerical Model General Formulation We solve the time-dependent, two-dimensional, compressible, Navier-Stokes equations for a

Learning Environment Associated with Use of Mixed Mode Delivery Model among Secondary Business Studies Students in Singapore

ERIC Educational Resources Information Center

Koh, Noi Keng; Fraser, Barry J.

2014-01-01

At many teacher education institutes around the world, preservice teachers are empowered to use pedagogical tools and strategies that engage their students. We used a modified version of the Constructivist Learning Environment Survey (CLES) to evaluate the effectiveness of a pedagogical model known as the Mixed Mode Delivery (MMD) model in terms…

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

PubMed

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

2017-04-01

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

Control for Population Structure and Relatedness for Binary Traits in Genetic Association Studies via Logistic Mixed Models

PubMed Central

Chen, Han; Wang, Chaolong; Conomos, Matthew P.; Stilp, Adrienne M.; Li, Zilin; Sofer, Tamar; Szpiro, Adam A.; Chen, Wei; Brehm, John M.; Celedón, Juan C.; Redline, Susan; Papanicolaou, George J.; Thornton, Timothy A.; Laurie, Cathy C.; Rice, Kenneth; Lin, Xihong

2016-01-01

Linear mixed models (LMMs) are widely used in genome-wide association studies (GWASs) to account for population structure and relatedness, for both continuous and binary traits. Motivated by the failure of LMMs to control type I errors in a GWAS of asthma, a binary trait, we show that LMMs are generally inappropriate for analyzing binary traits when population stratification leads to violation of the LMM’s constant-residual variance assumption. To overcome this problem, we develop a computationally efficient logistic mixed model approach for genome-wide analysis of binary traits, the generalized linear mixed model association test (GMMAT). This approach fits a logistic mixed model once per GWAS and performs score tests under the null hypothesis of no association between a binary trait and individual genetic variants. We show in simulation studies and real data analysis that GMMAT effectively controls for population structure and relatedness when analyzing binary traits in a wide variety of study designs. PMID:27018471

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

PubMed

Ivanova, Anna; Molenberghs, Geert; Verbeke, Geert

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

Lohmann, U.; Hoose, C.

2009-07-01

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.

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

PubMed

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.

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

PubMed

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

2016-03-01

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

The estimation of branching curves in the presence of subject-specific random effects.

PubMed

Elmi, Angelo; Ratcliffe, Sarah J; Guo, Wensheng

2014-12-20

Branching curves are a technique for modeling curves that change trajectory at a change (branching) point. Currently, the estimation framework is limited to independent data, and smoothing splines are used for estimation. This article aims to extend the branching curve framework to the longitudinal data setting where the branching point varies by subject. If the branching point is modeled as a random effect, then the longitudinal branching curve framework is a semiparametric nonlinear mixed effects model. Given existing issues with using random effects within a smoothing spline, we express the model as a B-spline based semiparametric nonlinear mixed effects model. Simple, clever smoothness constraints are enforced on the B-splines at the change point. The method is applied to Women's Health data where we model the shape of the labor curve (cervical dilation measured longitudinally) before and after treatment with oxytocin (a labor stimulant). Copyright © 2014 John Wiley & Sons, Ltd.

Performance of an Automated-Mixed-Traffic-Vehicle /AMTV/ System. [urban people mover

NASA Technical Reports Server (NTRS)

Peng, T. K. C.; Chon, K.

1978-01-01

This study analyzes the operation and evaluates the expected performance of a proposed automatic guideway transit system which uses low-speed Automated Mixed Traffic Vehicles (AMTV's). Vehicle scheduling and headway control policies are evaluated with a transit system simulation model. The effect of mixed-traffic interference on the average vehicle speed is examined with a vehicle-pedestrian interface model. Control parameters regulating vehicle speed are evaluated for safe stopping and passenger comfort.

Eulerian and Lagrangian Parameterization of the Oceanic Mixed Layer using Large Eddy Simulation and MPAS-Ocean

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

Van Roekel, Luke

We have conducted a suite of Large Eddy Simulation (LES) to form the basis of a multi-model comparison (left). The results have led to proposed model improvements. We have verified that Eulerian-Lagrangian effective diffusivity estimates of mesoscale mixing are consistent with traditional particle statistics metrics (right). LES and Lagrangian particles will be utilized to better represent the movement of water into and out of the mixed layer.

Experimental testing and modeling analysis of solute mixing at water distribution pipe junctions.

PubMed

Shao, Yu; Jeffrey Yang, Y; Jiang, Lijie; Yu, Tingchao; Shen, Cheng

2014-06-01

Flow dynamics at a pipe junction controls particle trajectories, solute mixing and concentrations in downstream pipes. The effect can lead to different outcomes of water quality modeling and, hence, drinking water management in a distribution network. Here we have investigated solute mixing behavior in pipe junctions of five hydraulic types, for which flow distribution factors and analytical equations for network modeling are proposed. First, based on experiments, the degree of mixing at a cross is found to be a function of flow momentum ratio that defines a junction flow distribution pattern and the degree of departure from complete mixing. Corresponding analytical solutions are also validated using computational-fluid-dynamics (CFD) simulations. Second, the analytical mixing model is further extended to double-Tee junctions. Correspondingly the flow distribution factor is modified to account for hydraulic departure from a cross configuration. For a double-Tee(A) junction, CFD simulations show that the solute mixing depends on flow momentum ratio and connection pipe length, whereas the mixing at double-Tee(B) is well represented by two independent single-Tee junctions with a potential water stagnation zone in between. Notably, double-Tee junctions differ significantly from a cross in solute mixing and transport. However, it is noted that these pipe connections are widely, but incorrectly, simplified as cross junctions of assumed complete solute mixing in network skeletonization and water quality modeling. For the studied pipe junction types, analytical solutions are proposed to characterize the incomplete mixing and hence may allow better water quality simulation in a distribution network. Published by Elsevier Ltd.

Surface wave effects in the NEMO ocean model: Forced and coupled experiments

NASA Astrophysics Data System (ADS)

Breivik, Øyvind; Mogensen, Kristian; Bidlot, Jean-Raymond; Balmaseda, Magdalena Alonso; Janssen, Peter A. E. M.

2015-04-01

The NEMO general circulation ocean model is extended to incorporate three physical processes related to ocean surface waves, namely the surface stress (modified by growth and dissipation of the oceanic wavefield), the turbulent kinetic energy flux from breaking waves, and the Stokes-Coriolis force. Experiments are done with NEMO in ocean-only (forced) mode and coupled to the ECMWF atmospheric and wave models. Ocean-only integrations are forced with fields from the ERA-Interim reanalysis. All three effects are noticeable in the extratropics, but the sea-state-dependent turbulent kinetic energy flux yields by far the largest difference. This is partly because the control run has too vigorous deep mixing due to an empirical mixing term in NEMO. We investigate the relation between this ad hoc mixing and Langmuir turbulence and find that it is much more effective than the Langmuir parameterization used in NEMO. The biases in sea surface temperature as well as subsurface temperature are reduced, and the total ocean heat content exhibits a trend closer to that observed in a recent ocean reanalysis (ORAS4) when wave effects are included. Seasonal integrations of the coupled atmosphere-wave-ocean model consisting of NEMO, the wave model ECWAM, and the atmospheric model of ECMWF similarly show that the sea surface temperature biases are greatly reduced when the mixing is controlled by the sea state and properly weighted by the thickness of the uppermost level of the ocean model. These wave-related physical processes were recently implemented in the operational coupled ensemble forecast system of ECMWF.

Interannual control of plankton communities by deep winter mixing and prey/predator interactions in the NW Mediterranean: Results from a 30-year 3D modeling study

NASA Astrophysics Data System (ADS)

Auger, P. A.; Ulses, C.; Estournel, C.; Stemmann, L.; Somot, S.; Diaz, F.

2014-05-01

A realistic modeling approach is designed to address the role of winter mixing on the interannual variability of plankton dynamics in the north-western (NW) Mediterranean basin. For the first time, a high-resolution coupled hydrodynamic-biogeochemical model (Eco3m-S) covering a 30-year period (1976-2005) is validated on available in situ and satellite data for the NW Mediterranean. In this region, cold, dry winds in winter often lead to deep convection and strong upwelling of nutrients into the euphotic layer. High nutrient contents at the end of winter then support the development of a strong spring bloom of phytoplankton. Model results indicate that annual primary production is not affected by winter mixing due to seasonal balance (minimum in winter and maximum in spring). However, the total annual water column-integrated phytoplankton biomass appears to be favored by winter mixing because zooplankton grazing activity is low in winter and early spring. This reduced grazing is explained here by the rarefaction of prey due to both light limitation and the effect of mixing-induced dilution on prey/predator interactions. A negative impact of winter mixing on winter zooplankton biomass is generally simulated except for mesozooplankton. This difference is assumed to stem from the lower parameterized mortality, top trophic position and detritivorous diet of mesozooplankton in the model. Moreover, model suggests that the variability of annual mesozooplankton biomass is principally modulated by the effects of winter mixing on winter biomass. Thus, interannual variability of winter nutrient contents in the euphotic layer, resulting from winter mixing, would control spring primary production and thus annual mesozooplankton biomass. Our results show a bottom-up control of mesozooplankton communities, as observed at a coastal location of the Ligurian Sea.

A Robust Wireless Sensor Network Localization Algorithm in Mixed LOS/NLOS Scenario.

PubMed

Li, Bing; Cui, Wei; Wang, Bin

2015-09-16

Localization algorithms based on received signal strength indication (RSSI) are widely used in the field of target localization due to its advantages of convenient application and independent from hardware devices. Unfortunately, the RSSI values are susceptible to fluctuate under the influence of non-line-of-sight (NLOS) in indoor space. Existing algorithms often produce unreliable estimated distances, leading to low accuracy and low effectiveness in indoor target localization. Moreover, these approaches require extra prior knowledge about the propagation model. As such, we focus on the problem of localization in mixed LOS/NLOS scenario and propose a novel localization algorithm: Gaussian mixed model based non-metric Multidimensional (GMDS). In GMDS, the RSSI is estimated using a Gaussian mixed model (GMM). The dissimilarity matrix is built to generate relative coordinates of nodes by a multi-dimensional scaling (MDS) approach. Finally, based on the anchor nodes' actual coordinates and target's relative coordinates, the target's actual coordinates can be computed via coordinate transformation. Our algorithm could perform localization estimation well without being provided with prior knowledge. The experimental verification shows that GMDS effectively reduces NLOS error and is of higher accuracy in indoor mixed LOS/NLOS localization and still remains effective when we extend single NLOS to multiple NLOS.

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

PubMed Central

Rajeswaran, Jeevanantham; Blackstone, Eugene H.

2014-01-01

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

Effects of Transition-Metal Mixing on Na Ordering and Kinetics in Layered P 2 Oxides

NASA Astrophysics Data System (ADS)

Zheng, Chen; Radhakrishnan, Balachandran; Chu, Iek-Heng; Wang, Zhenbin; Ong, Shyue Ping

2017-06-01

Layered P 2 oxides are promising cathode materials for rechargeable sodium-ion batteries. In this work, we systematically investigate the effects of transition-metal (TM) mixing on Na ordering and kinetics in the NaxCo1 -yMnyO2 model system using density-functional-theory (DFT) calculations. The DFT-predicted 0-K stability diagrams indicate that Co-Mn mixing reduces the energetic differences between Na orderings, which may account for the reduction of the number of phase transformations observed during the cycling of mixed-TM P 2 layered oxides compared to a single TM. Using ab initio molecular-dynamics simulations and nudged elastic-band calculations, we show that the TM composition at the Na(1) (face-sharing) site has a strong influence on the Na site energies, which in turn impacts the kinetics of Na diffusion towards the end of the charge. By employing a site-percolation model, we establish theoretical upper and lower bounds for TM concentrations based on their effect on Na(1) site energies, providing a framework to rationally tune mixed-TM compositions for optimal Na diffusion.

A corrected formulation for marginal inference derived from two-part mixed models for longitudinal semi-continuous data.

PubMed

Tom, Brian Dm; Su, Li; Farewell, Vernon T

2016-10-01

For semi-continuous data which are a mixture of true zeros and continuously distributed positive values, the use of two-part mixed models provides a convenient modelling framework. However, deriving population-averaged (marginal) effects from such models is not always straightforward. Su et al. presented a model that provided convenient estimation of marginal effects for the logistic component of the two-part model but the specification of marginal effects for the continuous part of the model presented in that paper was based on an incorrect formulation. We present a corrected formulation and additionally explore the use of the two-part model for inferences on the overall marginal mean, which may be of more practical relevance in our application and more generally. © The Author(s) 2013.

Confidence Intervals for Assessing Heterogeneity in Generalized Linear Mixed Models

ERIC Educational Resources Information Center

Wagler, Amy E.

2014-01-01

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

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

PubMed

Hoffman, Gabriel E

2013-01-01

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

Rayleigh-Taylor and Richtmyer-Meshkov instability induced flow, turbulence, and mixing. II

NASA Astrophysics Data System (ADS)

Zhou, Ye

2017-12-01

Rayleigh-Taylor (RT) and Richtmyer-Meshkov(RM) instabilities are well-known pathways towards turbulent mixing layers, in many cases characterized by significant mass and species exchange across the mixing layers (Zhou, 2017. Physics Reports, 720-722, 1-136). Mathematically, the pathway to turbulent mixing requires that the initial interface be multimodal, to permit cross-mode coupling leading to turbulence. Practically speaking, it is difficult to experimentally produce a non-multi-mode initial interface. Numerous methods and approaches have been developed to describe the late, multimodal, turbulent stages of RT and RM mixing layers. This paper first presents the initial condition dependence of RT mixing layers, and introduces parameters that are used to evaluate the level of "mixedness" and "mixed mass" within the layers, as well as the dependence on density differences, as well as the characteristic anisotropy of this acceleration-driven flow, emphasizing some of the key differences between the two-dimensional and three-dimensional RT mixing layers. Next, the RM mixing layers are discussed, and differences with the RT mixing layer are elucidated, including the RM mixing layers dependence on the Mach number of the initiating shock. Another key feature of the RM induced flows is its response to a reshock event, as frequently seen in shock-tube experiments as well as inertial confinement events. A number of approaches to modeling the evolution of these mixing layers are then described, in order of increasing complexity. These include simple buoyancy-drag models, Reynolds-averaged Navier-Stokes models of increased complexity, including K- ε, K-L, and K- L- a models, up to full Reynolds-stress models with more than one length-scale. Multifield models and multiphase models have also been implemented. Additional complexities to these flows are examined as well as modifications to the models to understand the effects of these complexities. These complexities include the presence of magnetic fields, compressibility, rotation, stratification and additional instabilities. The complications induced by the presence of converging geometries are also considered. Finally, the unique problems of astrophysical and high-energy-density applications, and efforts to model these are discussed.

Gravity Wave Mixing and Effective Diffusivity for Minor Chemical Constituents in the Mesosphere/Lower Thermosphere

NASA Astrophysics Data System (ADS)

Grygalashvyly, M.; Becker, E.; Sonnemann, G. R.

2012-06-01

The influence of gravity waves (GWs) on the distributions of minor chemical constituents in the mesosphere-lower thermosphere (MLT) is studied on the basis of the effective diffusivity concept. The mixing ratios of chemical species used for calculations of the effective diffusivity are obtained from numerical experiments with an off-line coupled model of the dynamics and chemistry abbreviated as KMCM-MECTM (Kuehlungsborn Mechanistic general Circulation Model—MEsospheric Chemistry-Transport Model). In our control simulation the MECTM is driven with the full dynamical fields from an annual cycle simulation with the KMCM, where mid-frequency GWs down to horizontal wavelengths of 350 km are resolved and their wave-mean flow interaction is self-consistently induced by an advanced turbulence model. A perturbation simulation with the MECTM is defined by eliminating all meso-scale variations with horizontal wavelengths shorter than 1000 km from the dynamical fields by means of spectral filtering before running the MECTM. The response of the MECTM to GWs perturbations reveals strong effects on the minor chemical constituents. We show by theoretical arguments and numerical diagnostics that GWs have direct, down-gradient mixing effects on all long-lived minor chemical species that possess a mean vertical gradient in the MLT. Introducing the term wave diffusion (WD) and showing that wave mixing yields approximately the same WD coefficient for different chemical constituents, we argue that it is a useful tool for diagnostic irreversible transport processes. We also present a detailed discussion of the gravity-wave mixing effects on the photochemistry and highlight the consequences for the general circulation of the MLT.

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

PubMed

Zhang, Yue; Berhane, Kiros

2016-01-01

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

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

Treesearch

Fabian C.C. Uzoh; William W. Oliver

2008-01-01

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

Langmuir cells and mixing in the upper ocean

NASA Astrophysics Data System (ADS)

Carniel, S.; Sclavo, M.; Kantha, L. H.; Clayson, C. A.

2005-01-01

The presence of surface gravity waves at the ocean surface has two important effects on turbulence in the oceanic mixed layer (ML): the wave breaking and the Langmuir cells (LC). Both these effects act as additional sources of turbulent kinetic energy (TKE) in the oceanic ML, and hence are important to mixing in the upper ocean. The breaking of high wave-number components of the wind wave spectrum provides an intense but sporadic source of turbulence in the upper surface; turbulence thus injected diffuses downward, while decaying rapidly, modifying oceanic near-surface properties which in turn could affect the air-sea transfer of heat and dissolved gases. LC provide another source of additional turbulence in the water column; they are counter-rotating cells inside the ML, with their axes roughly aligned in the direction of the wind (Langmuir I., Science871938119). These structures are usually made evident by the presence of debris and foam in the convergence area of the cells, and are generated by the interaction of the wave-field-induced Stokes drift with the wind-induced shear stress. LC have long been thought to have a substantial influence on mixing in the upper ocean, but the difficulty in their parameterization have made ML modelers consistently ignore them in the past. However, recent Large Eddy Simulations (LES) studies suggest that it is possible to include their effect on mixing by simply adding additional production terms in the turbulence equations, thus enabling even 1D models to incorporate LC-driven turbulence. Since LC also modify the Coriolis terms in the mean momentum equations by the addition of a term involving the Stokes drift, their effect on the velocity structure in the ML is also quite significant and could have a major impact on the drift of objects and spilled oil in the upper ocean. In this paper we examine the effect of surface gravity waves on mixing in the upper ocean, focusing on Langmuir circulations, which is by far the dominant part of the surface wave contribution to mixing. Oceanic ML models incorporating these effects are applied to an observation station in the Northern Adriatic Sea to see what the extent of these effects might be. It is shown that the surface wave effects can indeed be significant; in particular, the modification of the velocity profile due to LC-generated turbulence can be large under certain conditions. However, the surface wave effects on the bulk properties of the ML, such as the associated temperature, while significant, are generally speaking well within the errors introduced by uncertainties in the external forcing of the models. This seems to be the reason why ML models, though pretty much ignoring surface wave effects until recently, have been reasonably successful in depicting the evolution of the mixed layer temperature (MLT) at various timescales.

Unveiling the thermal entanglement in a mixed-spin XXZ model with Dzyaloshinskii-Moriya interaction under a homogeneous magnetic field

NASA Astrophysics Data System (ADS)

Liu, Cheng-Cheng; Xu, Shuai; He, Juan; Ye, Liu

2015-10-01

We analytically investigate the thermal entanglement of three-mixed-spin (1/2, 1, 1/2) XXZ model with the DM interaction under an external magnetic field B. Two different cases are considered: one subsystem (1/2, 1/2) consists of two spin-1/2 fermions and the other subsystem (1/2, 1) contains a spin-1/2 fermion and a spin-1 boson. It is shown that the DM interaction parameter D, the external magnetic field strength B and coupling constant J have different effects on Fermi and mixed Fermi-Bose systems. All of the factors mentioned above can be utilized to control entanglement switch of any two particles in mixed spins model.

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

NASA Astrophysics Data System (ADS)

Zozulya, A. A.

1988-12-01

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

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

PubMed

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

2013-08-01

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

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

PubMed Central

Kim, Yoonsang; Emery, Sherry

2013-01-01

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

Three-dimensional turbulent-mixing-length modeling for discrete-hole coolant injection into a crossflow

NASA Technical Reports Server (NTRS)

Wang, C. R.; Papell, S. S.

1983-01-01

Three dimensional mixing length models of a flow field immediately downstream of coolant injection through a discrete circular hole at a 30 deg angle into a crossflow were derived from the measurements of turbulence intensity. To verify their effectiveness, the models were used to estimate the anisotropic turbulent effects in a simplified theoretical and numerical analysis to compute the velocity and temperature fields. With small coolant injection mass flow rate and constant surface temperature, numerical results of the local crossflow streamwise velocity component and surface heat transfer rate are consistent with the velocity measurement and the surface film cooling effectiveness distributions reported in previous studies.

Three-dimensional turbulent-mixing-length modeling for discrete-hole coolant injection into a crossflow

NASA Astrophysics Data System (ADS)

Wang, C. R.; Papell, S. S.

1983-09-01

Three dimensional mixing length models of a flow field immediately downstream of coolant injection through a discrete circular hole at a 30 deg angle into a crossflow were derived from the measurements of turbulence intensity. To verify their effectiveness, the models were used to estimate the anisotropic turbulent effects in a simplified theoretical and numerical analysis to compute the velocity and temperature fields. With small coolant injection mass flow rate and constant surface temperature, numerical results of the local crossflow streamwise velocity component and surface heat transfer rate are consistent with the velocity measurement and the surface film cooling effectiveness distributions reported in previous studies.

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

PubMed

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

2014-01-15

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. © 2013 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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 < 1.5 μm, with negligible effects at longer wavelengths. Nonspherical snow grains show less BC-induced albedo reductions than spheres with the same effective sizes by up to 0.06 at ultraviolet and visible bands. Compared with 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%.

Single- and mixture toxicity of three organic UV-filters, ethylhexyl methoxycinnamate, octocrylene, and avobenzone on Daphnia magna.

PubMed

Park, Chang-Beom; Jang, Jiyi; Kim, Sanghun; Kim, Young Jun

2017-03-01

In freshwater environments, aquatic organisms are generally exposed to mixtures of various chemical substances. In this study, we tested the toxicity of three organic UV-filters (ethylhexyl methoxycinnamate, octocrylene, and avobenzone) to Daphnia magna in order to evaluate the combined toxicity of these substances when in they occur in a mixture. The values of effective concentrations (ECx) for each UV-filter were calculated by concentration-response curves; concentration-combinations of three different UV-filters in a mixture were determined by the fraction of components based on EC 25 values predicted by concentration addition (CA) model. The interaction between the UV-filters were also assessed by model deviation ratio (MDR) using observed and predicted toxicity values obtained from mixture-exposure tests and CA model. The results from this study indicated that observed ECx mix (e.g., EC 10mix , EC 25mix , or EC 50mix ) values obtained from mixture-exposure tests were higher than predicted ECx mix (e.g., EC 10mix , EC 25mix , or EC 50mix ) values calculated by CA model. MDR values were also less than a factor of 1.0 in a mixtures of three different UV-filters. Based on these results, we suggest for the first time a reduction of toxic effects in the mixtures of three UV-filters, caused by antagonistic action of the components. Our findings from this study will provide important information for hazard or risk assessment of organic UV-filters, when they existed together in the aquatic environment. To better understand the mixture toxicity and the interaction of components in a mixture, further studies for various combinations of mixture components are also required. Copyright © 2016 Elsevier Inc. All rights reserved.

Modeling the interplay between sea ice formation and the oceanic mixed layer: Limitations of simple brine rejection parameterizations

NASA Astrophysics Data System (ADS)

Barthélemy, Antoine; Fichefet, Thierry; Goosse, Hugues; Madec, Gurvan

2015-02-01

The subtle interplay between sea ice formation and ocean vertical mixing is hardly represented in current large-scale models designed for climate studies. Convective mixing caused by the brine release when ice forms is likely to prevail in leads and thin ice areas, while it occurs in models at the much larger horizontal grid cell scale. Subgrid-scale parameterizations have hence been developed to mimic the effects of small-scale convection using a vertical distribution of the salt rejected by sea ice within the mixed layer, instead of releasing it in the top ocean layer. Such a brine rejection parameterization is included in the global ocean-sea ice model NEMO-LIM3. Impacts on the simulated mixed layers and ocean temperature and salinity profiles, along with feedbacks on the sea ice cover, are then investigated in both hemispheres. The changes are overall relatively weak, except for mixed layer depths, which are in general excessively reduced compared to observation-based estimates. While potential model biases prevent a definitive attribution of this vertical mixing underestimation to the brine rejection parameterization, it is unlikely that the latter can be applied in all conditions. In that case, salt rejections do not play any role in mixed layer deepening, which is unrealistic. Applying the parameterization only for low ice-ocean relative velocities improves model results, but introduces additional parameters that are not well constrained by observations.

Modelling the interplay between sea ice formation and the oceanic mixed layer: limitations of simple brine rejection parameterizations

NASA Astrophysics Data System (ADS)

Barthélemy, Antoine; Fichefet, Thierry; Goosse, Hugues; Madec, Gurvan

2015-04-01

The subtle interplay between sea ice formation and ocean vertical mixing is hardly represented in current large-scale models designed for climate studies. Convective mixing caused by the brine release when ice forms is likely to prevail in leads and thin ice areas, while it occurs in models at the much larger horizontal grid cell scale. Subgrid-scale parameterizations have hence been developed to mimic the effects of small-scale convection using a vertical distribution of the salt rejected by sea ice within the mixed layer, instead of releasing it in the top ocean layer. Such a brine rejection parameterization is included in the global ocean--sea ice model NEMO-LIM3. Impacts on the simulated mixed layers and ocean temperature and salinity profiles, along with feedbacks on the sea ice cover, are then investigated in both hemispheres. The changes are overall relatively weak, except for mixed layer depths, which are in general excessively reduced compared to observation-based estimates. While potential model biases prevent a definitive attribution of this vertical mixing underestimation to the brine rejection parameterization, it is unlikely that the latter can be applied in all conditions. In that case, salt rejections do not play any role in mixed layer deepening, which is unrealistic. Applying the parameterization only for low ice--ocean relative velocities improves model results, but introduces additional parameters that are not well constrained by observations.

Fermion masses and mixing in general warped extra dimensional models

NASA Astrophysics Data System (ADS)

Frank, Mariana; Hamzaoui, Cherif; Pourtolami, Nima; Toharia, Manuel

2015-06-01

We analyze fermion masses and mixing in a general warped extra dimensional model, where all the Standard Model (SM) fields, including the Higgs, are allowed to propagate in the bulk. In this context, a slightly broken flavor symmetry imposed universally on all fermion fields, without distinction, can generate the full flavor structure of the SM, including quarks, charged leptons and neutrinos. For quarks and charged leptons, the exponential sensitivity of their wave functions to small flavor breaking effects yield hierarchical masses and mixing as it is usual in warped models with fermions in the bulk. In the neutrino sector, the exponential wave-function factors can be flavor blind and thus insensitive to the small flavor symmetry breaking effects, directly linking their masses and mixing angles to the flavor symmetric structure of the five-dimensional neutrino Yukawa couplings. The Higgs must be localized in the bulk and the model is more successful in generalized warped scenarios where the metric background solution is different than five-dimensional anti-de Sitter (AdS5 ). We study these features in two simple frameworks, flavor complimentarity and flavor democracy, which provide specific predictions and correlations between quarks and leptons, testable as more precise data in the neutrino sector becomes available.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Studies of the effects of curvature on dilution jet mixing

NASA Technical Reports Server (NTRS)

Holdeman, James D.; Srinivasan, Ram; Reynolds, Robert S.; White, Craig D.

1992-01-01

An analytical program was conducted using both three-dimensional numerical and empirical models to investigate the effects of transition liner curvature on the mixing of jets injected into a confined crossflow. The numerical code is of the TEACH type with hybrid numerics; it uses the power-law and SIMPLER algorithms, an orthogonal curvilinear coordinate system, and an algebraic Reynolds stress turbulence model. From the results of the numerical calculations, an existing empirical model for the temperature field downstream of single and multiple rows of jets injected into a straight rectangular duct was extended to model the effects of curvature. Temperature distributions, calculated with both the numerical and empirical models, are presented to show the effects of radius of curvature and inner and outer wall injection for single and opposed rows of cool dilution jets injected into a hot mainstream flow.

Likelihood-Based Random-Effect Meta-Analysis of Binary Events.

PubMed

Amatya, Anup; Bhaumik, Dulal K; Normand, Sharon-Lise; Greenhouse, Joel; Kaizar, Eloise; Neelon, Brian; Gibbons, Robert D

2015-01-01

Meta-analysis has been used extensively for evaluation of efficacy and safety of medical interventions. Its advantages and utilities are well known. However, recent studies have raised questions about the accuracy of the commonly used moment-based meta-analytic methods in general and for rare binary outcomes in particular. The issue is further complicated for studies with heterogeneous effect sizes. Likelihood-based mixed-effects modeling provides an alternative to moment-based methods such as inverse-variance weighted fixed- and random-effects estimators. In this article, we compare and contrast different mixed-effect modeling strategies in the context of meta-analysis. Their performance in estimation and testing of overall effect and heterogeneity are evaluated when combining results from studies with a binary outcome. Models that allow heterogeneity in both baseline rate and treatment effect across studies have low type I and type II error rates, and their estimates are the least biased among the models considered.

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

Dawson, S.; Lewis, I. M.

One of the simplest extensions of the Standard Model (SM) is the addition of a scalar gauge singlet, S . If S is not forbidden by a symmetry from mixing with the Standard Model Higgs boson, the mixing will generate non-SM rates for Higgs production and decays. Generally, there could also be unknown high energy physics that generates additional effective low energy interactions. We show that interference effects between the scalar resonance of the singlet model and the effective field theory (EFT) operators can have significant effects in the Higgs sector. Here, we examine a non- Z 2 symmetricmore » scalar singlet model and demonstrate that a fit to the 125 GeV Higgs boson couplings and to limits on high mass resonances, S , exhibit an interesting structure and possible large cancellations of effects between the resonance contribution and the new EFT interactions, that invalidate conclusions based on the renormalizable singlet model alone.« less

The effect of different methods to compute N on estimates of mixing in stratified flows

NASA Astrophysics Data System (ADS)

Fringer, Oliver; Arthur, Robert; Venayagamoorthy, Subhas; Koseff, Jeffrey

2017-11-01

The background stratification is typically well defined in idealized numerical models of stratified flows, although it is more difficult to define in observations. This may have important ramifications for estimates of mixing which rely on knowledge of the background stratification against which turbulence must work to mix the density field. Using direct numerical simulation data of breaking internal waves on slopes, we demonstrate a discrepancy in ocean mixing estimates depending on the method in which the background stratification is computed. Two common methods are employed to calculate the buoyancy frequency N, namely a three-dimensionally resorted density field (often used in numerical models) and a locally-resorted vertical density profile (often used in the field). We show that how N is calculated has a significant effect on the flux Richardson number Rf, which is often used to parameterize turbulent mixing, and the turbulence activity number Gi, which leads to errors when estimating the mixing efficiency using Gi-based parameterizations. Supported by ONR Grant N00014-08-1-0904 and LLNL Contract DE-AC52-07NA27344.

Synergistic effects of oleaginous yeast Rhodotorula glutinis and microalga Chlorella vulgaris for enhancement of biomass and lipid yields.

PubMed

Zhang, Zhiping; Ji, Hairui; Gong, Guiping; Zhang, Xu; Tan, Tianwei

2014-07-01

The optimal mixed culture model of oleaginous yeast Rhodotorula glutinis and microalga Chlorella vulgaris was confirmed to enhance lipid production. A double system bubble column photo-bioreactor was designed and used for demonstrating the relationship of yeast and alga in mixed culture. The results showed that using the log-phase cultures of yeast and alga as seeds for mixed culture, the improvements of biomass and lipid yields reached 17.3% and 70.9%, respectively, compared with those of monocultures. Growth curves of two species were confirmed in the double system bubble column photo-bioreactor, and the second growth of yeast was observed during 36-48 h of mixed culture. Synergistic effects of two species for cell growth and lipid accumulation were demonstrated on O2/CO2 balance, substance exchange, dissolved oxygen and pH adjustment in mixed culture. This study provided a theoretical basis and culture model for producing lipids by mixed culture in place of monoculture. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analytical Solution for Reactive Solute Transport Considering Incomplete Mixing

NASA Astrophysics Data System (ADS)

Bellin, A.; Chiogna, G.

2013-12-01

The laboratory experiments of Gramling et al. (2002) showed that incomplete mixing at the pore scale exerts a significant impact on transport of reactive solutes and that assuming complete mixing leads to overestimation of product concentration in bimolecular reactions. We consider here the family of equilibrium reactions for which the concentration of the reactants and the product can be expressed as a function of the mixing ratio, the concentration of a fictitious non reactive solute. For this type of reactions we propose, in agreement with previous studies, to model the effect of incomplete mixing at scales smaller than the Darcy scale assuming that the mixing ratio is distributed within an REV according to a Beta distribution. We compute the parameters of the Beta model by imposing that the mean concentration is equal to the value that the concentration assumes at the continuum Darcy scale, while the variance decays with time as a power law. We show that our model reproduces the concentration profiles of the reaction product measured in the Gramling et al. (2002) experiments using the transport parameters obtained from conservative experiments and an instantaneous reaction kinetic. The results are obtained applying analytical solutions both for conservative and for reactive solute transport, thereby providing a method to handle the effect of incomplete mixing on multispecies reactive solute transport, which is simpler than other previously developed methods. Gramling, C. M., C. F. Harvey, and L. C. Meigs (2002), Reactive transport in porous media: A comparison of model prediction with laboratory visualization, Environ. Sci. Technol., 36(11), 2508-2514.

Effect of the 6PBT stirrer eccentricity and off-bottom clearance on mixing of pseudoplastic fluid in a stirred tank

NASA Astrophysics Data System (ADS)

Luan, Deyu; Zhang, Shengfeng; Wei, Xing; Duan, Zhenya

The aim of this work is to investigate the effect of the shaft eccentricity on the flow field and mixing characteristics in a stirred tank with the novel stirrer composed of perturbed six-bent-bladed turbine (6PBT). The difference between coaxial and eccentric agitations is studied using computational fluid dynamics (CFD) simulations combined with standard k-ε turbulent equations, that offer a complete image of the three-dimensional flow field. In order to determine the capability of CFD to forecast the mixing process, particle image velocimetry (PIV), which provide an accurate representation of the time-averaged velocity, was used to measure fluid velocity. The test liquid used was 1.25% (wt) xanthan gum solution, a pseudoplastic fluid with a yield stress. The comparison of the experimental and simulated mean flow fields has demonstrated that calculations based on Reynolds-averaged Navier-Stokes equations are suitable for obtaining accurate results. The effects of the shaft eccentricity and the stirrer off-bottom distance on the flow model, mixing time and mixing efficiency were extensively analyzed. It is observed that the microstructure of the flow field has a significant effect on the tracer mixing process. The eccentric agitation can lead to the flow model change and the non-symmetric flow structure, which would possess an obvious superiority of mixing behavior. Moreover, the mixing rate and mixing efficiency are dependent on the shaft eccentricity and the stirrer off-bottom distance, showing the corresponding increase of the eccentricity with the off-bottom distance. The efficient mixing process of pseudoplastic fluid stirred by 6PBT impeller is obtained with the considerably low mixing energy per unit volume when the stirrer off-bottom distance, C, is T/3 and the eccentricity, e, is 0.2. The research results provide valuable references for the improvement of pseudoplastic fluid agitation technology.

A mixed-effects regression model for longitudinal multivariate ordinal data.

PubMed

Liu, Li C; Hedeker, Donald

2006-03-01

A mixed-effects item response theory model that allows for three-level multivariate ordinal outcomes and accommodates multiple random subject effects is proposed for analysis of multivariate ordinal outcomes in longitudinal studies. This model allows for the estimation of different item factor loadings (item discrimination parameters) for the multiple outcomes. The covariates in the model do not have to follow the proportional odds assumption and can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is proposed utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher scoring solution, which provides standard errors for all model parameters, is used. An analysis of a longitudinal substance use data set, where four items of substance use behavior (cigarette use, alcohol use, marijuana use, and getting drunk or high) are repeatedly measured over time, is used to illustrate application of the proposed model.

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

PubMed Central

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

2017-01-01

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

SPH investigation of the thermal effects on the fluid mixing in a microchannel with rotating stirrers

NASA Astrophysics Data System (ADS)

Shamsoddini, Rahim

2018-04-01

An incompressible smoothed particle hydrodynamics algorithm is proposed to model and investigate the thermal effect on the mixing rate of an active micromixer in which the rotating stirrers enhance the mixing rate. In liquids, mass diffusion increases with increasing temperature, while viscosity decreases; so, the local Schmidt number decreases considerably with increasing temperature. The present study investigates the effect of wall temperature on mixing rate with an improved SPH method. The robust SPH method used in the present work is equipped with a shifting algorithm and renormalization tensors. By introducing this new algorithm, the several mass, momentum, energy, and concentration equations are solved. The results, discussed for different temperature ratios, show that mixing rate increases significantly with increased temperature ratio.

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

PubMed

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

2015-06-01

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

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

PubMed

Koerner, Tess K; Zhang, Yang

2017-02-27

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

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

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

Wang, Zhien

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 concentrationmore » 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 of mixed-phase cloud simulations by CAM5 were performed. Measurement results indicate that ice concentrations control stratiform mixed-phase cloud properties. The improvement of ice concentration parameterization in the CAM5 was done in close collaboration with Dr. Xiaohong Liu, PNNL (now at University of Wyoming).« less

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

NASA Astrophysics Data System (ADS)

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.

Experiments in dilution jet mixing effects of multiple rows and non-circular orifices

NASA Technical Reports Server (NTRS)

Holdeman, J. D.; Srinivasan, R.; Coleman, E. B.; Meyers, G. D.; White, C. D.

1985-01-01

Experimental and empirical model results are presented that extend previous studies of the mixing of single-sided and opposed rows of jets in a confined duct flow to include effects of non-circular orifices and double rows of jets. Analysis of the mean temperature data obtained in this investigation showed that the effects of orifice shape and double rows are significant only in the region close to the injection plane, provided that the orifices are symmetric with respect to the main flow direction. The penetration and mixing of jets from 45-degree slanted slots is slightly less than that from equivalent-area symmetric orifices. The penetration from 2-dimensional slots is similar to that from equivalent-area closely-spaced rows of holes, but the mixing is slower for the 2-D slots. Calculated mean temperature profiles downstream of jets from non-circular and double rows of orifices, made using an extension developed for a previous empirical model, are shown to be in good agreement with the measured distributions.

Experiments in dilution jet mixing - Effects of multiple rows and non-circular orifices

NASA Technical Reports Server (NTRS)

Holdeman, J. D.; Srinivasan, R.; Coleman, E. B.; Meyers, G. D.; White, C. D.

1985-01-01

Experimental and empirical model results are presented that extend previous studies of the mixing of single-sided and opposed rows of jets in a confined duct flow to include effects of non-circular orifices and double rows of jets. Analysis of the mean temperature data obtained in this investigation showed that the effects of orifice shape and double rows are significant only in the region close to the injection plane, provided that the orifices are symmetric with respect to the main flow direction. The penetration and mixing of jets from 45-degree slanted slots is slightly less than that from equivalent-area symmetric orifices. The penetration from two-dimensional slots is similar to that from equivalent-area closely-spaced rows of holes, but the mixing is slower for the 2-D slots. Calculated mean temperature profiles downstream of jets from non-circular and double rows of orifices, made using an extension developed for a previous empirical model, are shown to be in good agreement with the measured distributions.

Effects of mixing in threshold models of social behavior

NASA Astrophysics Data System (ADS)

Akhmetzhanov, Andrei R.; Worden, Lee; Dushoff, Jonathan

2013-07-01

We consider the dynamics of an extension of the influential Granovetter model of social behavior, where individuals are affected by their personal preferences and observation of the neighbors’ behavior. Individuals are arranged in a network (usually the square lattice), and each has a state and a fixed threshold for behavior changes. We simulate the system asynchronously by picking a random individual and we either update its state or exchange it with another randomly chosen individual (mixing). We describe the dynamics analytically in the fast-mixing limit by using the mean-field approximation and investigate it mainly numerically in the case of finite mixing. We show that the dynamics converge to a manifold in state space, which determines the possible equilibria, and show how to estimate the projection of this manifold by using simulated trajectories, emitted from different initial points. We show that the effects of considering the network can be decomposed into finite-neighborhood effects, and finite-mixing-rate effects, which have qualitatively similar effects. Both of these effects increase the tendency of the system to move from a less-desired equilibrium to the “ground state.” Our findings can be used to probe shifts in behavioral norms and have implications for the role of information flow in determining when social norms that have become unpopular in particular communities (such as foot binding or female genital cutting) persist or vanish.

Pressure ratio effects on self-similar scalar mixing of high-pressure turbulent jets in a pressurized volume

NASA Astrophysics Data System (ADS)

Ruggles, Adam; Pickett, Lyle; Frank, Jonathan

2014-11-01

Many real world combustion devices model fuel scalar mixing by assuming the self-similar argument established in atmospheric free jets. This allows simple prediction of the mean and rms fuel scalar fields to describe the mixing. This approach has been adopted in super critical liquid injections found in diesel engines where the liquid behaves as a dense fluid. The effect of pressure ratio (injection to ambient) when the ambient is greater than atmospheric pressure, upon the self-similar collapse has not been well characterized, particularly the effect upon mixing constants, jet spreading rates, and virtual origins. Changes in these self-similar parameters control the reproduction of the scalar mixing statistics. This experiment investigates the steady state mixing of high pressure ethylene jets in a pressurized pure nitrogen environment for various pressure ratios and jet orifice diameters. Quantitative laser Rayleigh scattering imaging was performed utilizing a calibration procedure to account for the pressure effects upon scattering interference within the high-pressure vessel.

Control for Population Structure and Relatedness for Binary Traits in Genetic Association Studies via Logistic Mixed Models.

PubMed

Chen, Han; Wang, Chaolong; Conomos, Matthew P; Stilp, Adrienne M; Li, Zilin; Sofer, Tamar; Szpiro, Adam A; Chen, Wei; Brehm, John M; Celedón, Juan C; Redline, Susan; Papanicolaou, George J; Thornton, Timothy A; Laurie, Cathy C; Rice, Kenneth; Lin, Xihong

2016-04-07

Linear mixed models (LMMs) are widely used in genome-wide association studies (GWASs) to account for population structure and relatedness, for both continuous and binary traits. Motivated by the failure of LMMs to control type I errors in a GWAS of asthma, a binary trait, we show that LMMs are generally inappropriate for analyzing binary traits when population stratification leads to violation of the LMM's constant-residual variance assumption. To overcome this problem, we develop a computationally efficient logistic mixed model approach for genome-wide analysis of binary traits, the generalized linear mixed model association test (GMMAT). This approach fits a logistic mixed model once per GWAS and performs score tests under the null hypothesis of no association between a binary trait and individual genetic variants. We show in simulation studies and real data analysis that GMMAT effectively controls for population structure and relatedness when analyzing binary traits in a wide variety of study designs. Copyright © 2016 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

MANOVA vs nonlinear mixed effects modeling: The comparison of growth patterns of female and male quail

NASA Astrophysics Data System (ADS)

Gürcan, Eser Kemal

2017-04-01

The most commonly used methods for analyzing time-dependent data are multivariate analysis of variance (MANOVA) and nonlinear regression models. The aim of this study was to compare some MANOVA techniques and nonlinear mixed modeling approach for investigation of growth differentiation in female and male Japanese quail. Weekly individual body weight data of 352 male and 335 female quail from hatch to 8 weeks of age were used to perform analyses. It is possible to say that when all the analyses are evaluated, the nonlinear mixed modeling is superior to the other techniques because it also reveals the individual variation. In addition, the profile analysis also provides important information.

A Turbulence model taking into account the longitudinal flow inhomogeneity in mixing layers and jets

NASA Astrophysics Data System (ADS)

Troshin, A. I.

2017-06-01

The problem of potential core length overestimation of subsonic free jets by Reynolds-averaged Navier-Stokes (RANS) based turbulence models is addressed. It is shown that the issue is due to the incorrect velocity profile modeling of the jet mixing layers. An additional source term in ω equation is proposed which takes into account the effect of longitudinal flow inhomogeneity on turbulence in mixing layers. Computations confirm that the modified Speziale-Sarkar-Gatski/Launder- Reece-Rodi-omega (SSG/LRR-ω) turbulence model correctly predicts the mean velocity profiles in both initial and far-field regions of subsonic free plane jet as well as the centerline velocity decay rate.

Estimating Stage Specific Vital Rate Responses to Stress Within Mixed Age Populations of the Opossum Shrimp Americamysis bahia Using Digital Imaging

EPA Science Inventory

Most observations of stressor effects on marine crustaceans are made on individuals or even-aged cohorts. Results of these studies are difficult to translate into ecological predictions, either because life cycle models are incomplete, or because stressor effects on mixed age po...

Environmental Effects on Constitutive and Inducible Resin Defences of Pinus taeda

Treesearch

Maria L. Lombardero; Matthew P. Ayres; Peter L. Lorio; Jonathan J. Ruel

2000-01-01

The ecological literature abounds with studies of environmental effects on plant antiherbivore defences. While various models have been proposed (e.g. plant stress, optimal allocation, growth-differentiation balance), each has met with mixed support. One possible explanation for the mixed results is that constitutive and induced defences are differentialiy affected by...

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

NASA Astrophysics Data System (ADS)

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.

Physiological effects of diet mixing on consumer fitness: a meta-analysis.

PubMed

Lefcheck, Jonathan S; Whalen, Matthew A; Davenport, Theresa M; Stone, Joshua P; Duffy, J Emmett

2013-03-01

The degree of dietary generalism among consumers has important consequences for population, community, and ecosystem processes, yet the effects on consumer fitness of mixing food types have not been examined comprehensively. We conducted a meta-analysis of 161 peer-reviewed studies reporting 493 experimental manipulations of prey diversity to test whether diet mixing enhances consumer fitness based on the intrinsic nutritional quality of foods and consumer physiology. Averaged across studies, mixed diets conferred significantly higher fitness than the average of single-species diets, but not the best single prey species. More than half of individual experiments, however, showed maximal growth and reproduction on mixed diets, consistent with the predicted benefits of a balanced diet. Mixed diets including chemically defended prey were no better than the average prey type, opposing the prediction that a diverse diet dilutes toxins. Finally, mixed-model analysis showed that the effect of diet mixing was stronger for herbivores than for higher trophic levels. The generally weak evidence for the nutritional benefits of diet mixing in these primarily laboratory experiments suggests that diet generalism is not strongly favored by the inherent physiological benefits of mixing food types, but is more likely driven by ecological and environmental influences on consumer foraging.

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

NASA Technical Reports Server (NTRS)

Vallejo, Jonathon; Hejduk, Matt; Stamey, James

2015-01-01

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

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

PubMed

Magezi, David A

2015-01-01

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

Weak Interaction Models with New Quarks and Right-handed Currents

DOE R&D Accomplishments Database

Wilczek, F. A.; Zee, A.; Kingsley, R. L.; Treiman, S. B.

1975-06-01

We discuss various weak interaction issues for a general class of models within the SU(2) x U(1) gauge theory framework, with special emphasis on the effects of right-handed, charged currents and of quarks bearing new quantum numbers. In particular we consider the restrictions on model building which are imposed by the small KL - KS mass difference and by the .I = = rule; and we classify various possibilities for neutral current interactions and, in the case of heavy mesons with new quantum numbers, various possibilities for mixing effects analogous to KL - KS mixing.

Freshwater-Brine Mixing Zone Hydrodynamics in Salt Flats (Salar de Atacama)

NASA Astrophysics Data System (ADS)

Marazuela, M. A.; Vázquez-Suñé, E.; Custodio, E.; Palma, T.; García-Gil, A.

2017-12-01

The increase in the demand of strategic minerals for the development of medicines and batteries require detailed knowledge of the salt flats freshwater-brine interface to make its exploitation efficient. The interface zone is the result of a physical balance between the recharged and evaporated water. The sharp interface approach assumes the immiscibility of the fluids and thus neglects the mixing between them. As a consequence, for miscible fluids it is more accurate and often needed to use the mixing zone concept, which results from the dynamic equilibrium of flowing freshwater and brine. In this study, we consider two and three-dimensional scale approaches for the management of the mixing zone. The two-dimensional approach is used to understand the dynamics and the characteristics of the salt flat mixing zone, especially in the Salar de Atacama (Atacama salt flat) case. By making use of this model we analyze and quantify the effects of the aquitards on the mixing zone geometry. However, the understanding of the complex physical processes occurring in the salt flats and the management of these environments requires the adoption of three-dimensional regional scale numerical models. The models that take into account the effects of variable density represent the best management tool, but they require large computational resources, especially in the three-dimensional case. In order to avoid these computational limitations in the modeling of salt flats and their valuable ecosystems, we propose a three-step methodology, consisting of: (1) collection, validation and interpretation of the hydrogeochemical data, (2) identification and three-dimensional mapping of the mixing zone on the land surface and in depth, and (3) application of a water head correction to the freshwater and mixed water heads in order to compensate the density variations and to transform them to brine water heads. Finally, an evaluation of the sensibility of the mixing zone to anthropogenic and climate changes is included.

Perspectives on dilution jet mixing

NASA Technical Reports Server (NTRS)

Holdeman, J. D.

1986-01-01

A microcomputer code which displays 3-D oblique and 2-D plots of the temperature distribution downstream of jets mixing with a confined crossflow has been used to investigate the effects of varying the several independent flow and geometric parameters on the mixing. Temperature profiles calculated with this empirical model are presented to show the effects of orifice size and spacing, momentum flux ratio, density ratio, variable temperature mainstream, flow area convergence, orifice aspect ratio, and opposed and axially staged rows of jets.

Spatial Heterogeneity and Imperfect Mixing in Chemical Reactions: Visualization of Density-Driven Pattern Formation

DOE PAGES

Sobel, Sabrina G.; Hastings, Harold M.; Testa, Matthew

2009-01-01

Imore » mperfect mixing is a concern in industrial processes, everyday processes (mixing paint, bread machines), and in understanding salt water-fresh water mixing in ecosystems. The effects of imperfect mixing become evident in the unstirred ferroin-catalyzed Belousov-Zhabotinsky reaction, the prototype for chemical pattern formation. Over time, waves of oxidation (high ferriin concentration, blue) propagate into a background of low ferriin concentration (red); their structure reflects in part the history of mixing in the reaction vessel. However, it may be difficult to separate mixing effects from reaction effects. We describe a simpler model system for visualizing density-driven pattern formation in an essentially unmixed chemical system: the reaction of pale yellow Fe 3 + with colorless SCN − to form the blood-red Fe ( SCN ) 2 + complex ion in aqueous solution. Careful addition of one drop of Fe ( NO 3 ) 3 to KSCN yields striped patterns after several minutes. The patterns appear reminiscent of Rayleigh-Taylor instabilities and convection rolls, arguing that pattern formation is caused by density-driven mixing.« less

Spatial Heterogeneity and Imperfect Mixing in Chemical Reactions: Visualization of Density-Driven Pattern Formation

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

Sobel, Sabrina G.; Hastings, Harold M.; Testa, Matthew

Imore » mperfect mixing is a concern in industrial processes, everyday processes (mixing paint, bread machines), and in understanding salt water-fresh water mixing in ecosystems. The effects of imperfect mixing become evident in the unstirred ferroin-catalyzed Belousov-Zhabotinsky reaction, the prototype for chemical pattern formation. Over time, waves of oxidation (high ferriin concentration, blue) propagate into a background of low ferriin concentration (red); their structure reflects in part the history of mixing in the reaction vessel. However, it may be difficult to separate mixing effects from reaction effects. We describe a simpler model system for visualizing density-driven pattern formation in an essentially unmixed chemical system: the reaction of pale yellow Fe 3 + with colorless SCN − to form the blood-red Fe ( SCN ) 2 + complex ion in aqueous solution. Careful addition of one drop of Fe ( NO 3 ) 3 to KSCN yields striped patterns after several minutes. The patterns appear reminiscent of Rayleigh-Taylor instabilities and convection rolls, arguing that pattern formation is caused by density-driven mixing.« less

Model for compressible turbulence in hypersonic wall boundary and high-speed mixing layers

NASA Astrophysics Data System (ADS)

Bowersox, Rodney D. W.; Schetz, Joseph A.

1994-07-01

The most common approach to Navier-Stokes predictions of turbulent flows is based on either the classical Reynolds-or Favre-averaged Navier-Stokes equations or some combination. The main goal of the current work was to numerically assess the effects of the compressible turbulence terms that were experimentaly found to be important. The compressible apparent mass mixing length extension (CAMMLE) model, which was based on measured experimental data, was found to produce accurate predictions of the measured compressible turbulence data for both the wall bounded and free mixing layer. Hence, that model was incorporated into a finite volume Navier-Stokes code.

Mathematical Modelling and Analysis of the Tumor Treatment Regimens with Pulsed Immunotherapy and Chemotherapy

PubMed Central

Pang, Liuyong; Shen, Lin; Zhao, Zhong

2016-01-01

To begin with, in this paper, single immunotherapy, single chemotherapy, and mixed treatment are discussed, and sufficient conditions under which tumor cells will be eliminated ultimately are obtained. We analyze the impacts of the least effective concentration and the half-life of the drug on therapeutic results and then find that increasing the least effective concentration or extending the half-life of the drug can achieve better therapeutic effects. In addition, since most types of tumors are resistant to common chemotherapy drugs, we consider the impact of drug resistance on therapeutic results and propose a new mathematical model to explain the cause of the chemotherapeutic failure using single drug. Based on this, in the end, we explore the therapeutic effects of two-drug combination chemotherapy, as well as mixed immunotherapy with combination chemotherapy. Numerical simulations indicate that combination chemotherapy is very effective in controlling tumor growth. In comparison, mixed immunotherapy with combination chemotherapy can achieve a better treatment effect. PMID:26997972

Mathematical Modelling and Analysis of the Tumor Treatment Regimens with Pulsed Immunotherapy and Chemotherapy.

PubMed

Pang, Liuyong; Shen, Lin; Zhao, Zhong

2016-01-01

To begin with, in this paper, single immunotherapy, single chemotherapy, and mixed treatment are discussed, and sufficient conditions under which tumor cells will be eliminated ultimately are obtained. We analyze the impacts of the least effective concentration and the half-life of the drug on therapeutic results and then find that increasing the least effective concentration or extending the half-life of the drug can achieve better therapeutic effects. In addition, since most types of tumors are resistant to common chemotherapy drugs, we consider the impact of drug resistance on therapeutic results and propose a new mathematical model to explain the cause of the chemotherapeutic failure using single drug. Based on this, in the end, we explore the therapeutic effects of two-drug combination chemotherapy, as well as mixed immunotherapy with combination chemotherapy. Numerical simulations indicate that combination chemotherapy is very effective in controlling tumor growth. In comparison, mixed immunotherapy with combination chemotherapy can achieve a better treatment effect.

Detecting single-trial EEG evoked potential using a wavelet domain linear mixed model: application to error potentials classification.

PubMed

Spinnato, J; Roubaud, M-C; Burle, B; Torrésani, B

2015-06-01

The main goal of this work is to develop a model for multisensor signals, such as magnetoencephalography or electroencephalography (EEG) signals that account for inter-trial variability, suitable for corresponding binary classification problems. An important constraint is that the model be simple enough to handle small size and unbalanced datasets, as often encountered in BCI-type experiments. The method involves the linear mixed effects statistical model, wavelet transform, and spatial filtering, and aims at the characterization of localized discriminant features in multisensor signals. After discrete wavelet transform and spatial filtering, a projection onto the relevant wavelet and spatial channels subspaces is used for dimension reduction. The projected signals are then decomposed as the sum of a signal of interest (i.e., discriminant) and background noise, using a very simple Gaussian linear mixed model. Thanks to the simplicity of the model, the corresponding parameter estimation problem is simplified. Robust estimates of class-covariance matrices are obtained from small sample sizes and an effective Bayes plug-in classifier is derived. The approach is applied to the detection of error potentials in multichannel EEG data in a very unbalanced situation (detection of rare events). Classification results prove the relevance of the proposed approach in such a context. The combination of the linear mixed model, wavelet transform and spatial filtering for EEG classification is, to the best of our knowledge, an original approach, which is proven to be effective. This paper improves upon earlier results on similar problems, and the three main ingredients all play an important role.

Radiative corrections to the solar lepton mixing sum rule

NASA Astrophysics Data System (ADS)

Zhang, Jue; Zhou, Shun

2016-08-01

The simple correlation among three lepton flavor mixing angles ( θ 12, θ 13, θ 23) and the leptonic Dirac CP-violating phase δ is conventionally called a sum rule of lepton flavor mixing, which may be derived from a class of neutrino mass models with flavor symmetries. In this paper, we consider the solar lepton mixing sum rule θ 12 ≈ θ 12 ν + θ 13 cos δ, where θ 12 ν stems from a constant mixing pattern in the neutrino sector and takes the value of θ 12 ν = 45 ° for the bi-maximal mixing (BM), {θ}_{12}^{ν } = { tan}^{-1}(1/√{2}) ≈ 35.3° for the tri-bimaximal mixing (TBM) or {θ}_{12}^{ν } = { tan}^{-1}(1/√{5+1}) ≈ 31.7° for the golden-ratio mixing (GR), and investigate the renormalization-group (RG) running effects on lepton flavor mixing parameters when this sum rule is assumed at a superhigh-energy scale. For illustration, we work within the framework of the minimal supersymmetric standard model (MSSM), and implement the Bayesian approach to explore the posterior distribution of δ at the low-energy scale, which becomes quite broad when the RG running effects are significant. Moreover, we also discuss the compatibility of the above three mixing scenarios with current neutrino oscillation data, and observe that radiative corrections can increase such a compatibility for the BM scenario, resulting in a weaker preference for the TBM and GR ones.

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

PubMed

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

2018-03-15

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

Influence of mixed electrolytes and pH on adsorption of bovine serum albumin in hydrophobic interaction chromatography.

PubMed

Hackemann, Eva; Hasse, Hans

2017-10-27

Using salt mixtures instead of single salts can be beneficial for hydrophobic interaction chromatography (HIC). The effect of electrolytes on the adsorption of proteins, however, depends on the pH. Little is known on that dependence for mixed electrolytes. Therefore, the effect of the pH on protein adsorption from aqueous solutions containing mixed salts is systematically studied in the present work for a model system: the adsorption of bovine serum albumin (BSA) on the mildly hydrophobic resin Toyopearl PPG-600M. The pH is adjusted to 4.0, 4.7 or 7.0 using 25mM sodium phosphate or sodium citrate buffer. Binary and ternary salt mixtures of sodium chloride, ammonium chloride, sodium sulfate and ammonium sulfate as well as the pure salts are used at overall ionic strengths between 1500 and 4200mM. The temperature is always 25°C. The influence of the mixed electrolytes on the adsorption behavior of BSA changes completely with varying pH. Positive as well as negative cooperative effects of the mixed electrolytes are observed. The results are analyzed using a mathematical model which was recently introduced by our group. In that model the influence of the electrolytes is described by a Taylor series expansion in the individual ion molarities. After suitable parametrization using a subset of the data determined in the present work, the model successfully predicts the influence of mixed electrolytes on the protein adsorption. Furthermore, results for BSA from the present study are compared to literature data for lysozyme, which are available for the same adsorbent, temperature and salts. By calculating the ratio of the loading of the adsorbent for both proteins particularly favorable separation conditions can be selected. Hence, a model-based optimization of solvents for protein separation is possible. Copyright © 2017 Elsevier B.V. All rights reserved.

On the Effect of an Anisotropy-Resolving Subgrid-Scale Model on Turbulent Vortex Motions

DTIC Science & Technology

2014-09-19

sense, the model by Abe (2013) can be named the ”stabilized mixed model” ( SMM , hereafter). Furthermore, considering the basic concept of the mixed model...with SMM . Further investigations of this ex- tended anisotropic SGS model will be necessary in fu- ture studies. 3 Computational Conditions Although the...basic capability of the SMM was val- idated by application to some test cases (Abe, 2013; Abe 2014), there still remain several points to be fur

Incomplete Mixing and Reactions - A Lagrangian Approach in a Pure Shear Flow

NASA Astrophysics Data System (ADS)

Paster, A.; Aquino, T.; Bolster, D.

2014-12-01

Incomplete mixing of reactive solutes is well known to slow down reaction rates relative to what would be expected from assuming perfect mixing. As reactions progress in a system and deplete reactant concentrations, initial fluctuations in the concentrations of reactions can be amplified relative to mean background concentrations and lead to spatial segregation of reactants. As the system evolves, in the absence of sufficient mixing, this segregation will increase, leading to a persistence of incomplete mixing that fundamentally changes the effective rate at which overall reactions will progress. On the other hand, non-uniform fluid flows are known to affect mixing between interacting solutes. Thus a natural question arises: Can non-uniform flows sufficiently enhance mixing to suppress incomplete mixing effects, and if so, under what conditions? In this work we address this question by considering one of the simplest possible flows, a laminar pure shear flow, which is known to significantly enhance mixing relative to diffusion alone. To study this system we adapt a novel Lagrangian particle-based random walk method, originally designed to simulate reactions in purely diffusive systems, to the case of advection and diffusion in a shear flow. To interpret the results we develop a semi-analytical solution, by proposing a closure approximation that aims to capture the effect of incomplete mixing. The results obtained via the Lagrangian model and the semi-analytical solutions consistently highlight that if shear effects in the system are not sufficiently strong, incomplete mixing effects initially similar to purely diffusive systems will occur, slowing down the overall reaction rate. Then, at some later time, dependent on the strength of the shear, the system will return to behaving as if it were well-mixed, but represented by a reduced effective reaction rate. If shear effects are sufficiently strong, the incomplete mixing regime never emerges and the system can behave as well-mixed at all times.

Incomplete Mixing and Reactions - A Lagrangian Approach in a Pure Shear Flow

NASA Astrophysics Data System (ADS)

Paster, Amir; Bolster, Diogo; Aquino, Tomas

2015-04-01

Incomplete mixing of reactive solutes is well known to slow down reaction rates relative to what would be expected from assuming perfect mixing. As reactions progress in a system and deplete reactant concentrations, initial fluctuations in the concentrations of reactions can be amplified relative to mean background concentrations and lead to spatial segregation of reactants. As the system evolves, in the absence of sufficient mixing, this segregation will increase, leading to a persistence of incomplete mixing that fundamentally changes the effective rate at which overall reactions will progress. On the other hand, nonuniform fluid flows are known to affect mixing between interacting solutes. Thus a natural question arises: Can non-uniform flows sufficiently enhance mixing to suppress incomplete mixing effects, and if so, under what conditions? In this work we address this question by considering one of the simplest possible flows, a laminar pure shear flow, which is known to significantly enhance mixing relative to diffusion alone. To study this system we adapt a novel Lagrangian particle-based random walk method, originally designed to simulate reactions in purely diffusive systems, to the case of advection and diffusion in a shear flow. To interpret the results we develop a semi-analytical solution, by proposing a closure approximation that aims to capture the effect of incomplete mixing. The results obtained via the Lagrangian model and the semi-analytical solutions consistently highlight that if shear effects in the system are not sufficiently strong, incomplete mixing effects initially similar to purely diffusive systems will occur, slowing down the overall reaction rate. Then, at some later time, dependent on the strength of the shear, the system will return to behaving as if it were well-mixed, but represented by a reduced effective reaction rate. If shear effects are sufficiently strong, the incomplete mixing regime never emerges and the system can behave as well-mixed at all times.

Nursing home case mix in Wisconsin. Findings and policy implications.

PubMed

Arling, G; Zimmerman, D; Updike, L

1989-02-01

Along with many other states, Wisconsin is considering a case mix approach to Medicaid nursing home reimbursement. To support this effort, a nursing home case mix model was developed from a representative sample of 410 Medicaid nursing home residents from 56 facilities in Wisconsin. The model classified residents into mutually exclusive groups that were homogeneous in their use of direct care resources, i.e., minutes of direct care time (weighted for nurse skill level) over a 7-day period. Groups were defined initially by intense, Special, or Routine nursing requirements. Within these nursing requirement categories, subgroups were formed by the presence/absence of behavioral problems and dependency in activities of daily living (ADL). Wisconsin's current Skilled/Intermediate Care (SNF/ICF) classification system was analyzed in light of the case mix model and found to be less effective in distinguishing residents by resource use. The case mix model accounted for 48% of the variance in resource use, whereas the SNF/ICF classification system explained 22%. Comparisons were drawn with nursing home case mix models in New York State (RUG-II) and Minnesota. Despite progress in the study of nursing home case mix and its application to reimbursement reform, methodologic and policy issues remain. These include the differing operational definitions for nursing requirements and ADL dependency, the inconsistency in findings concerning psychobehavioral problems, and the problem of promoting positive health and functional outcomes based on models that may be insensitive to change in resident conditions over time.

A Mixed-Effects Heterogeneous Negative Binomial Model for Postfire Conifer Regeneration in Northeastern California, USA

Treesearch

Justin S. Crotteau; Martin W. Ritchie; J. Morgan Varner

2014-01-01

Many western USA fire regimes are typified by mixed-severity fire, which compounds the variability inherent to natural regeneration densities in associated forests. Tree regeneration data are often discrete and nonnegative; accordingly, we fit a series of Poisson and negative binomial variation models to conifer seedling counts across four distinct burn severities and...

Marginal revenue and length of stay in inpatient psychiatry.

PubMed

Pletscher, Mark

2016-09-01

This study examines the changes in marginal revenue during psychiatric inpatient stays in a large Swiss psychiatric hospital after the introduction of a mixed reimbursement system with tariff rates that vary over length of stay. A discrete time duration model with a difference-in-difference specification and time-varying coefficients is estimated to assess variations in policy effects over length of stay. Among patients whose costs are fully reimbursed by the mixed scheme, the model demonstrates a significant effect of marginal revenue on length of stay. No significant policy effects are found among patients for whom only health insurance rates are delivered as mixed tariffs and government contributions are made retrospectively. The results indicate that marginal revenue can affect length of stay in inpatient psychiatry facilities, but that the reduction in marginal revenue must be sufficiently large.

Mixing in the shear superposition micromixer: three-dimensional analysis.

PubMed

Bottausci, Frederic; Mezić, Igor; Meinhart, Carl D; Cardonne, Caroline

2004-05-15

In this paper, we analyse mixing in an active chaotic advection micromixer. The micromixer consists of a main rectangular channel and three cross-stream secondary channels that provide ability for time-dependent actuation of the flow stream in the direction orthogonal to the main stream. Three-dimensional motion in the mixer is studied. Numerical simulations and modelling of the flow are pursued in order to understand the experiments. It is shown that for some values of parameters a simple model can be derived that clearly represents the flow nature. Particle image velocimetry measurements of the flow are compared with numerical simulations and the analytical model. A measure for mixing, the mixing variance coefficient (MVC), is analysed. It is shown that mixing is substantially improved with multiple side channels with oscillatory flows, whose frequencies are increasing downstream. The optimization of MVC results for single side-channel mixing is presented. It is shown that dependence of MVC on frequency is not monotone, and a local minimum is found. Residence time distributions derived from the analytical model are analysed. It is shown that, while the average Lagrangian velocity profile is flattened over the steady flow, Taylor-dispersion effects are still present for the current micromixer configuration.

Assessing variation in life-history tactics within a population using mixture regression models: a practical guide for evolutionary ecologists.

PubMed

Hamel, Sandra; Yoccoz, Nigel G; Gaillard, Jean-Michel

2017-05-01

Mixed models are now well-established methods in ecology and evolution because they allow accounting for and quantifying within- and between-individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi-modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life-history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life-history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long-term studies of large mammals to illustrate the potential of using mixture models for assessing within-population variation in life-history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often violated in life-history data. Mixed models were quite robust to this violation in the sense that fixed effects were unbiased at the population level. However, fixed effects at the cluster level and random effects were better estimated using mixture models. Our empirical analyses demonstrated that using mixture models facilitates the identification of the diversity of growth and reproductive tactics occurring within a population. Therefore, using this modelling framework allows testing for the presence of clusters and, when clusters occur, provides reliable estimates of fixed and random effects for each cluster of the population. In the presence or expectation of clusters, using mixture models offers a suitable extension of mixed models, particularly when evolutionary ecologists aim at identifying how ecological and evolutionary processes change within a population. Mixture regression models therefore provide a valuable addition to the statistical toolbox of evolutionary ecologists. As these models are complex and have their own limitations, we provide recommendations to guide future users. © 2016 Cambridge Philosophical Society.

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

PubMed Central

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

2015-01-01

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

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

PubMed

O'Brien, Robert M

2017-07-20

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

Carbonate dissolution in mixed waters due to ocean acidification

NASA Astrophysics Data System (ADS)

Koski, K.; Wilson, J. L.

2009-12-01

Much of the anthropogenically released carbon dioxide has been stored as a dissolved gas in the ocean, causing a 0.1 decrease in ocean surface pH, with models predicting that by 2100 the surface ocean pH will be 0.5 below pre-industrial levels. In mixed ocean water - fresh water environments (e.g. estuaries, coastal aquifers, and edges of ice sheets), the decreased ocean pH couples with the mixed water geochemistry to make water more undersaturated with respect to calcium carbonate than ocean acidification alone. Mixed-water calcite dissolution may be one of the first directly observable effects of ocean acidification, as the ocean water and the fresh water can both be saturated with respect to calcium carbonate while their mixture will be undersaturated. We present a basic quantitative model describing mixed water dissolution in coastal or island freshwater aquifers, using temporally changing ocean pH, sea level, precipitation, and groundwater pumping. The model describes the potential for an increased rate of speleogenesis and porosity/permeability development along the lower edge of a fresh water lens aquifer. The model accounts the indirect effects of rising sea level and a growing coastal population on these processes. Applications are to freshwater carbonate aquifers on islands (e.g. the Bahamas) and in coastal areas (e.g. the unconfined Floridan aquifer of the United States, the Yucatan Peninsula of Mexico).

Combined Effect of Contraction Ratio and Chamber Pressure on the Performance of a Gaseous Hydrogen-Liquid-Oxygen Combustor for a Given Propellant Weight Flow and Oxidant-Fuel Ratio

NASA Technical Reports Server (NTRS)

Hersch, Martin

1961-01-01

The effect of contraction ratio and chamber pressure on the combustion performance of a gaseous-hydrogen-liquid-oxygen combustor was investigated analytically and experimentally. The experiment was conducted with a "two-dimensional" gaseous-hydrogen-liquid-oxygen engine of about 150-pound thrust. The contraction ratio was varied from 1.5 to 6 by changing the nozzle throat area. This variation resulted in a chamber pressure variation of about 25 to 120 pounds per square inch. The experimental results were corrected for heat transfer to the engine walls and momentum pressure losses. The experimental performance, as evaluated in terms of characteristic exhaust velocity, was 98 percent of theoretical at contraction ratios greater than 3 but decreased very rapidly at smaller contraction ratios. The heat-transfer rate increased with increasing contraction ratio and chamber pressure; it was about 1 Btu per square inch per second at a contraction ratio of 1.5 and increased to about 3 at a contraction ratio of 6. The combined effects of contraction-ratio and chamber-pressure changes on performance were investigated analytically with a mixing model and a vaporization model. The mixing model predicted very poor mixing at contraction ratios below 3 and almost perfect mixing at higher contraction ratios. The performance predicted by the vaporization model was very close to 100 percent for all contraction ratios. From these results, it was concluded that the performance was limited by poor mixing at low contraction ratios and chamber pressures.

Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer.

PubMed

Covarrubias-Pazaran, Giovanny

2016-01-01

Most traits of agronomic importance are quantitative in nature, and genetic markers have been used for decades to dissect such traits. Recently, genomic selection has earned attention as next generation sequencing technologies became feasible for major and minor crops. Mixed models have become a key tool for fitting genomic selection models, but most current genomic selection software can only include a single variance component other than the error, making hybrid prediction using additive, dominance and epistatic effects unfeasible for species displaying heterotic effects. Moreover, Likelihood-based software for fitting mixed models with multiple random effects that allows the user to specify the variance-covariance structure of random effects has not been fully exploited. A new open-source R package called sommer is presented to facilitate the use of mixed models for genomic selection and hybrid prediction purposes using more than one variance component and allowing specification of covariance structures. The use of sommer for genomic prediction is demonstrated through several examples using maize and wheat genotypic and phenotypic data. At its core, the program contains three algorithms for estimating variance components: Average information (AI), Expectation-Maximization (EM) and Efficient Mixed Model Association (EMMA). Kernels for calculating the additive, dominance and epistatic relationship matrices are included, along with other useful functions for genomic analysis. Results from sommer were comparable to other software, but the analysis was faster than Bayesian counterparts in the magnitude of hours to days. In addition, ability to deal with missing data, combined with greater flexibility and speed than other REML-based software was achieved by putting together some of the most efficient algorithms to fit models in a gentle environment such as R.

Estimating Stage-Specific Vital Rate Responses to Stress within Mixed Age Populations of the Opossum Shrimp Americamysis Bahia Using Digital Imaging (NAC SETAC 2011)

EPA Science Inventory

Most observations of stressor effects on marine crustaceans are made on individuals or even-aged cohorts. Results of these studies are difficult to translate into ecological predictions, either because life cycle models are incomplete, or because stressor effects on mixed age po...

The Pediatric Home Care/Expenditure Classification Model (P/ECM): A Home Care Case-Mix Model for Children Facing Special Health Care Challenges.

PubMed

Phillips, Charles D

2015-01-01

Case-mix classification and payment systems help assure that persons with similar needs receive similar amounts of care resources, which is a major equity concern for consumers, providers, and programs. Although health service programs for adults regularly use case-mix payment systems, programs providing health services to children and youth rarely use such models. This research utilized Medicaid home care expenditures and assessment data on 2,578 children receiving home care in one large state in the USA. Using classification and regression tree analyses, a case-mix model for long-term pediatric home care was developed. The Pediatric Home Care/Expenditure Classification Model (P/ECM) grouped children and youth in the study sample into 24 groups, explaining 41% of the variance in annual home care expenditures. The P/ECM creates the possibility of a more equitable, and potentially more effective, allocation of home care resources among children and youth facing serious health care challenges.

The Pediatric Home Care/Expenditure Classification Model (P/ECM): A Home Care Case-Mix Model for Children Facing Special Health Care Challenges

PubMed Central

Phillips, Charles D.

2015-01-01

Case-mix classification and payment systems help assure that persons with similar needs receive similar amounts of care resources, which is a major equity concern for consumers, providers, and programs. Although health service programs for adults regularly use case-mix payment systems, programs providing health services to children and youth rarely use such models. This research utilized Medicaid home care expenditures and assessment data on 2,578 children receiving home care in one large state in the USA. Using classification and regression tree analyses, a case-mix model for long-term pediatric home care was developed. The Pediatric Home Care/Expenditure Classification Model (P/ECM) grouped children and youth in the study sample into 24 groups, explaining 41% of the variance in annual home care expenditures. The P/ECM creates the possibility of a more equitable, and potentially more effective, allocation of home care resources among children and youth facing serious health care challenges. PMID:26740744

Numerical Investigation of a Cavitating Mixing Layer of Liquefied Natural Gas (LNG) Behind a Flat Plate Splitter

NASA Astrophysics Data System (ADS)

Rahbarimanesh, Saeed; Brinkerhoff, Joshua

2017-11-01

The mutual interaction of shear layer instabilities and phase change in a two-dimensional cryogenic cavitating mixing layer is investigated using a numerical model. The developed model employs the homogeneous equilibrium mixture (HEM) approach in a density-based framework to compute the temperature-dependent cavitation field for liquefied natural gas (LNG). Thermal and baroclinic effects are captured via iterative coupled solution of the governing equations with dynamic thermophysical models that accurately capture the properties of LNG. The mixing layer is simulated for vorticity-thickness Reynolds numbers of 44 to 215 and cavitation numbers of 0.1 to 1.1. Attached cavity structures develop on the splitter plate followed by roll-up of the separated shear layer via the well-known Kelvin-Helmholtz mode, leading to streamwise accumulation of vorticity and eventual shedding of discrete vortices. Cavitation occurs as vapor cavities nucleate and grow from the low-pressure cores in the rolled-up vortices. Thermal effects and baroclinic vorticity production are found to have significant impacts on the mixing layer instability and cavitation processes.

Modeling reactive transport with particle tracking and kernel estimators

NASA Astrophysics Data System (ADS)

Rahbaralam, Maryam; Fernandez-Garcia, Daniel; Sanchez-Vila, Xavier

2015-04-01

Groundwater reactive transport models are useful to assess and quantify the fate and transport of contaminants in subsurface media and are an essential tool for the analysis of coupled physical, chemical, and biological processes in Earth Systems. Particle Tracking Method (PTM) provides a computationally efficient and adaptable approach to solve the solute transport partial differential equation. On a molecular level, chemical reactions are the result of collisions, combinations, and/or decay of different species. For a well-mixed system, the chem- ical reactions are controlled by the classical thermodynamic rate coefficient. Each of these actions occurs with some probability that is a function of solute concentrations. PTM is based on considering that each particle actually represents a group of molecules. To properly simulate this system, an infinite number of particles is required, which is computationally unfeasible. On the other hand, a finite number of particles lead to a poor-mixed system which is limited by diffusion. Recent works have used this effect to actually model incomplete mix- ing in naturally occurring porous media. In this work, we demonstrate that this effect in most cases should be attributed to a defficient estimation of the concentrations and not to the occurrence of true incomplete mixing processes in porous media. To illustrate this, we show that a Kernel Density Estimation (KDE) of the concentrations can approach the well-mixed solution with a limited number of particles. KDEs provide weighting functions of each particle mass that expands its region of influence, hence providing a wider region for chemical reactions with time. Simulation results show that KDEs are powerful tools to improve state-of-the-art simulations of chemical reactions and indicates that incomplete mixing in diluted systems should be modeled based on alternative conceptual models and not on a limited number of particles.

Additive mixed effect model for recurrent gap time data.

PubMed

Ding, Jieli; Sun, Liuquan

2017-04-01

Gap times between recurrent events are often of primary interest in medical and observational studies. The additive hazards model, focusing on risk differences rather than risk ratios, has been widely used in practice. However, the marginal additive hazards model does not take the dependence among gap times into account. In this paper, we propose an additive mixed effect model to analyze gap time data, and the proposed model includes a subject-specific random effect to account for the dependence among the gap times. Estimating equation approaches are developed for parameter estimation, and the asymptotic properties of the resulting estimators are established. In addition, some graphical and numerical procedures are presented for model checking. The finite sample behavior of the proposed methods is evaluated through simulation studies, and an application to a data set from a clinic study on chronic granulomatous disease is provided.

Agents of Change: Mixed-Race Households and the Dynamics of Neighborhood Segregation in the United States

PubMed Central

Ellis, Mark; Holloway, Steven R.; Wright, Richard; Fowler, Christopher S.

2014-01-01

This article explores the effects of mixed-race household formation on trends in neighborhood-scale racial segregation. Census data show that these effects are nontrivial in relation to the magnitude of decadal changes in residential segregation. An agent-based model illustrates the potential long-run impacts of rising numbers of mixed-race households on measures of neighborhood-scale segregation. It reveals that high rates of mixed-race household formation will reduce residential segregation considerably. This occurs even when preferences for own-group neighbors are high enough to maintain racial separation in residential space in a Schelling-type model. We uncover a disturbing trend, however; levels of neighborhood-scale segregation of single-race households can remain persistently high even while a growing number of mixed-race households drives down the overall rate of residential segregation. Thus, the article’s main conclusion is that parsing neighborhood segregation levels by household type—single versus mixed race—is essential to interpret correctly trends in the spatial separation of racial groups, especially when the fraction of households that are mixed race is dynamic. More broadly, the article illustrates the importance of household-scale processes for urban outcomes and joins debates in geography about interscalar relationships. PMID:25082984

Flow and active mixing have a strong impact on bacterial growth dynamics in the proximal large intestine

NASA Astrophysics Data System (ADS)

Cremer, Jonas; Segota, Igor; Yang, Chih-Yu; Arnoldini, Markus; Groisman, Alex; Hwa, Terence

2016-11-01

More than half of fecal dry weight is bacterial mass with bacterial densities reaching up to 1012 cells per gram. Mostly, these bacteria grow in the proximal large intestine where lateral flow along the intestine is strong: flow can in principal lead to a washout of bacteria from the proximal large intestine. Active mixing by contractions of the intestinal wall together with bacterial growth might counteract such a washout and allow high bacterial densities to occur. As a step towards understanding bacterial growth in the presence of mixing and flow, we constructed an in-vitro setup where controlled wall-deformations of a channel emulate contractions. We investigate growth along the channel under a steady nutrient inflow. Depending on mixing and flow, we observe varying spatial gradients in bacterial density along the channel. Active mixing by deformations of the channel wall is shown to be crucial in maintaining a steady-state bacterial population in the presence of flow. The growth-dynamics is quantitatively captured by a simple mathematical model, with the effect of mixing described by an effective diffusion term. Based on this model, we discuss bacterial growth dynamics in the human large intestine using flow- and mixing-behavior having been observed for humans.

Variation in fistula use across dialysis facilities: is it explained by case-mix?

PubMed

Tangri, Navdeep; Moorthi, Ranjani; Tighiouhart, Hocine; Meyer, Klemens B; Miskulin, Dana C

2010-02-01

Arteriovenous fistulas (AVFs) remain the preferred vascular access for hemodialysis patients. Dialysis facilities that fail to meet Centers for Medicare & Medicaid Services goals cite patient case-mix as a reason for low AVF prevalence. This study aimed to determine the magnitude of the variability in AVF usage across dialysis facilities and the extent to which patient case-mix explains it. The vascular access used in 10,112 patients dialyzed at 173 Dialysis Clinic Inc. facilities from October 1 to December 31, 2004, was evaluated. The access in use was considered to be an AVF if it was used for >70% of hemodialysis treatments. Mixed-effects models with a random intercept for dialysis facilities evaluated the effect of facilities on AVF usage. Sequentially adjusted multivariate models measured the extent to which patient factors (case-mix) explain variation across facilities in AVF rates. 3787 patients (38%) were dialyzed using AVFs. There was a significant facility effect: 7.6% of variation in AVF use was attributable to facility. This was reduced to 7.1% after case-mix adjustment. There were no identified specific facility-level factors that explained the interfacility variation. AVF usage varies across dialysis facilities, and patient case-mix did not reduce this variation. In this study, 92% of the total variation in AVF usage was due to patient factors, but most were not measurable. A combination of patient factors and process indicators should be considered in adjudicating facility performance for this quality indicator.

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

PubMed Central

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

Line mixing calculation in the ν 6Q-branches of N 2-broadened CH 3Br at low temperatures

NASA Astrophysics Data System (ADS)

Gomez, L.; Tran, H.; Jacquemart, D.

2009-07-01

In an early study [H. Tran, D. Jacquemart, J.Y. Mandin, N. Lacome, JQSRT 109 (2008) 119-131], line mixing effects of the ν 6 band of methyl bromide were observed and modeled at room temperature. In the present work, line mixing effects have been considered at low temperatures using state-to-state collisional rates which were modeled by a fitting law based on the energy gap and a few fitting parameters. To validate the model, several spectra of methyl bromide perturbed by nitrogen have been recorded at various temperatures (205-299 K) and pressures (230-825 hPa). Comparisons between measured spectra and calculations using both direct calculation from relaxation operator and Rosenkranz profile have been performed showing improvement compared to the usual Lorentz profile. Note that the temperature dependence of the spectroscopic parameters has been taken into account using results of previous studies.

Genetic mixed linear models for twin survival data.

PubMed

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

2007-07-01

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

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

PubMed Central

Koerner, Tess K.; Zhang, Yang

2017-01-01

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

Efficient Bayesian mixed model analysis increases association power in large cohorts

PubMed Central

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

2014-01-01

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

Evaluation of a hybrid kinetics/mixing-controlled combustion model for turbulent premixed and diffusion combustion using KIVA-II

NASA Technical Reports Server (NTRS)

Nguyen, H. Lee; Wey, Ming-Jyh

1990-01-01

Two-dimensional calculations were made of spark ignited premixed-charge combustion and direct injection stratified-charge combustion in gasoline fueled piston engines. Results are obtained using kinetic-controlled combustion submodel governed by a four-step global chemical reaction or a hybrid laminar kinetics/mixing-controlled combustion submodel that accounts for laminar kinetics and turbulent mixing effects. The numerical solutions are obtained by using KIVA-2 computer code which uses a kinetic-controlled combustion submodel governed by a four-step global chemical reaction (i.e., it assumes that the mixing time is smaller than the chemistry). A hybrid laminar/mixing-controlled combustion submodel was implemented into KIVA-2. In this model, chemical species approach their thermodynamics equilibrium with a rate that is a combination of the turbulent-mixing time and the chemical-kinetics time. The combination is formed in such a way that the longer of the two times has more influence on the conversion rate and the energy release. An additional element of the model is that the laminar-flame kinetics strongly influence the early flame development following ignition.

Evaluation of a hybrid kinetics/mixing-controlled combustion model for turbulent premixed and diffusion combustion using KIVA-2

NASA Technical Reports Server (NTRS)

Nguyen, H. Lee; Wey, Ming-Jyh

1990-01-01

Two dimensional calculations were made of spark ignited premixed-charge combustion and direct injection stratified-charge combustion in gasoline fueled piston engines. Results are obtained using kinetic-controlled combustion submodel governed by a four-step global chemical reaction or a hybrid laminar kinetics/mixing-controlled combustion submodel that accounts for laminar kinetics and turbulent mixing effects. The numerical solutions are obtained by using KIVA-2 computer code which uses a kinetic-controlled combustion submodel governed by a four-step global chemical reaction (i.e., it assumes that the mixing time is smaller than the chemistry). A hybrid laminar/mixing-controlled combustion submodel was implemented into KIVA-2. In this model, chemical species approach their thermodynamics equilibrium with a rate that is a combination of the turbulent-mixing time and the chemical-kinetics time. The combination is formed in such a way that the longer of the two times has more influence on the conversion rate and the energy release. An additional element of the model is that the laminar-flame kinetics strongly influence the early flame development following ignition.

Inter-provider comparison of patient-reported outcomes: developing an adjustment to account for differences in patient case mix.

PubMed

Nuttall, David; Parkin, David; Devlin, Nancy

2015-01-01

This paper describes the development of a methodology for the case-mix adjustment of patient-reported outcome measures (PROMs) data permitting the comparison of outcomes between providers on a like-for-like basis. Statistical models that take account of provider-specific effects form the basis of the proposed case-mix adjustment methodology. Indirect standardisation provides a transparent means of case mix adjusting the PROMs data, which are updated on a monthly basis. Recently published PROMs data for patients undergoing unilateral knee replacement are used to estimate empirical models and to demonstrate the application of the proposed case-mix adjustment methodology in practice. The results are illustrative and are used to highlight a number of theoretical and empirical issues that warrant further exploration. For example, because of differences between PROMs instruments, case-mix adjustment methodologies may require instrument-specific approaches. A number of key assumptions are made in estimating the empirical models, which could be open to challenge. The covariates of post-operative health status could be expanded, and alternative econometric methods could be employed. © 2013 Crown copyright.

Mix Model Comparison of Low Feed-Through Implosions

NASA Astrophysics Data System (ADS)

Pino, Jesse; MacLaren, S.; Greenough, J.; Casey, D.; Dewald, E.; Dittrich, T.; Khan, S.; Ma, T.; Sacks, R.; Salmonson, J.; Smalyuk, V.; Tipton, R.; Kyrala, G.

2016-10-01

The CD Mix campaign previously demonstrated the use of nuclear diagnostics to study the mix of separated reactants in plastic capsule implosions at the NIF. Recently, the separated reactants technique has been applied to the Two Shock (TS) implosion platform, which is designed to minimize this feed-through and isolate local mix at the gas-ablator interface and produce core yields in good agreement with 1D clean simulations. The effects of both inner surface roughness and convergence ratio have been probed. The TT, DT, and DD neutron signals respectively give information about core gas performance, gas-shell atomic mix, and heating of the shell. In this talk, we describe efforts to model these implosions using high-resolution 2D ARES simulations. Various methods of interfacial mix will be considered, including the Reynolds-Averaged Navier Stokes (RANS) KL method as well as and a multicomponent enhanced diffusivity model with species, thermal, and pressure gradient terms. We also give predictions of a upcoming campaign to investigate Mid-Z mixing by adding a Ge dopant to the CD layer. LLNL-ABS-697251 This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

A numerical study of automotive turbocharger mixed flow turbine inlet geometry for off design performance

NASA Astrophysics Data System (ADS)

Leonard, T.; Spence, S.; Early, J.; Filsinger, D.

2013-12-01

Mixed flow turbines represent a potential solution to the increasing requirement for high pressure, low velocity ratio operation in turbocharger applications. While literature exists for the use of these turbines at such operating conditions, there is a lack of detailed design guidance for defining the basic geometry of the turbine, in particular, the cone angle - the angle at which the inlet of the mixed flow turbine is inclined to the axis. This investigates the effect and interaction of such mixed flow turbine design parameters. Computational Fluids Dynamics was initially used to investigate the performance of a modern radial turbine to create a baseline for subsequent mixed flow designs. Existing experimental data was used to validate this model. Using the CFD model, a number of mixed flow turbine designs were investigated. These included studies varying the cone angle and the associated inlet blade angle. The results of this analysis provide insight into the performance of a mixed flow turbine with respect to cone and inlet blade angle.

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

PubMed

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

2016-01-01

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

A mathematical model for soil solute transfer into surface runoff as influenced by rainfall detachment.

PubMed

Yang, Ting; Wang, Quanjiu; Wu, Laosheng; Zhao, Guangxu; Liu, Yanli; Zhang, Pengyu

2016-07-01

Nutrients transport is a main source of water pollution. Several models describing transport of soil nutrients such as potassium, phosphate and nitrate in runoff water have been developed. The objectives of this research were to describe the nutrients transport processes by considering the effect of rainfall detachment, and to evaluate the factors that have greatest influence on nutrients transport into runoff. In this study, an existing mass-conservation equation and rainfall detachment process were combined and augmented to predict runoff of nutrients in surface water in a Loess Plateau soil in Northwestern Yangling, China. The mixing depth is a function of time as a result of rainfall impact, not a constant as described in previous models. The new model was tested using two different sub-models of complete-mixing and incomplete-mixing. The complete-mixing model is more popular to use for its simplicity. It captured the runoff trends of those high adsorption nutrients, and of nutrients transport along steep slopes. While the incomplete-mixing model predicted well for the highest observed concentrations of the test nutrients. Parameters inversely estimated by the models were applied to simulate nutrients transport, results suggested that both models can be adopted to describe nutrients transport in runoff under the impact of rainfall. Copyright © 2016 Elsevier B.V. All rights reserved.

Mixed reality temporal bone surgical dissector: mechanical design.

PubMed

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

2014-08-08

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

Free energy of mixing of acetone and methanol: a computer simulation investigation.

PubMed

Idrissi, Abdenacer; Polok, Kamil; Barj, Mohammed; Marekha, Bogdan; Kiselev, Mikhail; Jedlovszky, Pál

2013-12-19

The change of the Helmholtz free energy, internal energy, and entropy accompanying the mixing of acetone and methanol is calculated in the entire composition range by the method of thermodynamic integration using three different potential model combinations of the two compounds. In the first system, both molecules are described by the OPLS, and in the second system, both molecules are described by the original TraPPE force field, whereas in the third system a modified version of the TraPPE potential is used for acetone in combination with the original TraPPE model of methanol. The results reveal that, in contrast with the acetone-water system, all of these three model combinations are able to reproduce the full miscibility of acetone and methanol, although the thermodynamic driving force of this mixing is very small. It is also seen, in accordance with the finding of former structural analyses, that the mixing of the two components is driven by the entropy term corresponding to the ideal mixing, which is large enough to overcompensate the effect of the energy increase and entropy loss due to the interaction of the unlike components in the mixtures. Among the three model combinations, the use of the original TraPPE model of methanol and modified TraPPE model of acetone turns out to be clearly the best in this respect, as it is able to reproduce the experimental free energy, internal energy, and entropy of mixing values within 0.15 kJ/mol, 0.2 kJ/mol, and 1 J/(mol K), respectively, in the entire composition range. The success of this model combination originates from the fact that the use of the modified TraPPE model of acetone instead of the original one in these mixtures improves the reproduction of the entropy of mixing, while it retains the ability of the original model of excellently reproducing the internal energy of mixing.

Development and Experimental Verification of Surface Effects in a Fluidic Model

DTIC Science & Technology

2006-01-01

FROM A HE PLASMA INSIDE A POLYSTYRENE MICROCHANNEL. 43 FIGURE 30: THE EMISSION SPECTRA FROM A MIXED HEXAFLUOROETHYLENE/HE PLASMA INSIDE THE...MICROCHANNEL 47 FIGURE 35: THE ADSORPTION OF GLUCOSE OXIDASE TO DIFFERENT POLYMER SURFACES WAS SHOWN TO HAVE A SIGNIFICANT EFFECT ON ELECTROOSMOTIC FLOW...approach involves neglecting non-ideal (convective-diffusive) effects 5 by assuming well- mixed protein in contact with an idealized surface. Coupled

Combined Recirculatory-compartmental Population Pharmacokinetic Modeling of Arterial and Venous Plasma S(+) and R(-) Ketamine Concentrations.

PubMed

Henthorn, Thomas K; Avram, Michael J; Dahan, Albert; Gustafsson, Lars L; Persson, Jan; Krejcie, Tom C; Olofsen, Erik

2018-05-16

The pharmacokinetics of infused drugs have been modeled without regard for recirculatory or mixing kinetics. We used a unique ketamine dataset with simultaneous arterial and venous blood sampling, during and after separate S(+) and R(-) ketamine infusions, to develop a simplified recirculatory model of arterial and venous plasma drug concentrations. S(+) or R(-) ketamine was infused over 30 min on two occasions to 10 healthy male volunteers. Frequent, simultaneous arterial and forearm venous blood samples were obtained for up to 11 h. A multicompartmental pharmacokinetic model with front-end arterial mixing and venous blood components was developed using nonlinear mixed effects analyses. A three-compartment base pharmacokinetic model with additional arterial mixing and arm venous compartments and with shared S(+)/R(-) distribution kinetics proved superior to standard compartmental modeling approaches. Total pharmacokinetic flow was estimated to be 7.59 ± 0.36 l/min (mean ± standard error of the estimate), and S(+) and R(-) elimination clearances were 1.23 ± 0.04 and 1.06 ± 0.03 l/min, respectively. The arm-tissue link rate constant was 0.18 ± 0.01 min and the fraction of arm blood flow estimated to exchange with arm tissue was 0.04 ± 0.01. Arterial drug concentrations measured during drug infusion have two kinetically distinct components: partially or lung-mixed drug and fully mixed-recirculated drug. Front-end kinetics suggest the partially mixed concentration is proportional to the ratio of infusion rate and total pharmacokinetic flow. This simplified modeling approach could lead to more generalizable models for target-controlled infusions and improved methods for analyzing pharmacokinetic-pharmacodynamic data.

Effects of polymer additives on Rayleigh-Taylor turbulence.

PubMed

Boffetta, G; Mazzino, A; Musacchio, S

2011-05-01

The role of polymer additives on the turbulent convective flow of a Rayleigh-Taylor system is investigated by means of direct numerical simulations of Oldroyd-B viscoelastic model. The dynamics of polymer elongations follows adiabatically the self-similar evolution of the turbulent mixing layer and shows the appearance of a strong feedback on the flow which originates a cutoff for polymer elongations. The viscoelastic effects on the mixing properties of the flow are twofold. Mixing is appreciably enhanced at large scales (the mixing layer growth rate is larger than that of the purely Newtonian case) and depleted at small scales (thermal plumes are more coherent with respect to the Newtonian case). The observed speed up of the thermal plumes, together with an increase of the correlations between temperature field and vertical velocity, contributes to a significant enhancement of heat transport. Our findings are consistent with a scenario of drag reduction induced by polymers. A weakly nonlinear model proposed by Fermi for the growth of the mixing layer is reported in the Appendix. © 2011 American Physical Society

Modeling climate and fuel reduction impacts on mixed-conifer forest carbon stocks in the Sierra Nevada, California

Treesearch

Matthew D. Hurteau; Timothy A. Robards; Donald Stevens; David Saah; Malcolm North; George W. Koch

2014-01-01

Quantifying the impacts of changing climatic conditions on forest growth is integral to estimating future forest carbon balance. We used a growth-and-yield model, modified for climate sensitivity, to quantify the effects of altered climate on mixed-conifer forest growth in the Lake Tahoe Basin, California. Estimates of forest growth and live tree carbon stocks were...

Ascorbyl palmitate/d-α-tocopheryl polyethylene glycol 1000 succinate monoester mixed micelles for prolonged circulation and targeted delivery of compound K for antilung cancer therapy in vitro and in vivo

PubMed Central

Zhang, Youwen; Tong, Deyin; Che, Daobiao; Pei, Bing; Xia, Xiaodong; Yuan, Gaofeng; Jin, Xin

2017-01-01

The roles of ginsenoside compound K (CK) in inhibiting tumor have been widely recognized in recent years. However, low water solubility and significant P-gp efflux have restricted its application. In this study, CK ascorbyl palmitate (AP)/d-α-tocopheryl polyethylene glycol 1000 succinate monoester (TPGS) mixed micelles were prepared as a delivery system to increase the absorption and targeted antitumor effect of CK. Consequently, the solubility of CK increased from 35.2±4.3 to 1,463.2±153.3 μg/mL. Furthermore, in an in vitro A549 cell model, CK AP/TPGS mixed micelles significantly inhibited cell growth, induced G0/G1 phase cell cycle arrest, induced cell apoptosis, and inhibited cell migration compared to free CK, all indicating that the developed micellar delivery system could increase the antitumor effect of CK in vitro. Both in vitro cellular fluorescence uptake and in vivo near-infrared imaging studies indicated that AP/TPGS mixed micelles can promote cellular uptake and enhance tumor targeting. Moreover, studies in the A549 lung cancer xenograft mouse model showed that CK AP/TPGS mixed micelles are an efficient tumor-targeted drug delivery system with an effective antitumor effect. Western blot analysis further confirmed that the marked antitumor effect in vivo could likely be due to apoptosis promotion and P-gp efflux inhibition. Therefore, these findings suggest that the AP/TPGS mixed micellar delivery system could be an efficient delivery strategy for enhanced tumor targeting and antitumor effects. PMID:28144142

Magnetic anisotropy in binuclear complexes in the weak-exchange limit: From the multispin to the giant-spin Hamiltonian

NASA Astrophysics Data System (ADS)

Maurice, Rémi; de Graaf, Coen; Guihéry, Nathalie

2010-06-01

This paper studies the physical basis of the giant-spin Hamiltonian, which is usually used to describe the anisotropy of single-molecule magnets. A rigorous extraction of the model has been performed in the weak-exchange limit of a binuclear centrosymmetric Ni(II) complex, using correlated ab initio calculations and effective Hamiltonian theory. It is shown that the giant-spin Hamiltonian is not appropriate to describe polynuclear complexes as soon as spin mixing becomes non-negligible. A relevant model is proposed involving fourth-order operators, different from the traditionally used Stevens operators. The new giant-spin Hamiltonian correctly reproduces the effects of the spin mixing in the weak-exchange limit. A procedure to switch on and off the spin mixing in the extraction has been implemented in order to separate this effect from other anisotropic effects and to numerically evaluate both contributions to the tunnel splitting. Furthermore, the new giant-spin Hamiltonian has been derived analytically from the multispin Hamiltonian at the second order of perturbation and the theoretical link between the two models is studied to gain understanding concerning the microscopic origin of the fourth-order interaction in terms of axial, rhombic, or mixed (axial-rhombic) character. Finally, an adequate method is proposed to extract the proper magnetic axes frame for polynuclear anisotropic systems.

Stochastic parameterization for light absorption by internally mixed BC/dust in snow grains for application to climate models

NASA Astrophysics Data System (ADS)

Liou, K. N.; Takano, Y.; He, C.; Yang, P.; Leung, L. R.; Gu, Y.; Lee, W. L.

2014-06-01

A stochastic approach has been developed to model the positions of BC (black carbon)/dust internally mixed with two snow grain types: hexagonal plate/column (convex) and Koch snowflake (concave). Subsequently, light absorption and scattering analysis can be followed by means of an improved geometric-optics approach coupled with Monte Carlo photon tracing to determine BC/dust single-scattering properties. For a given shape (plate, Koch snowflake, spheroid, or sphere), the action of internal mixing absorbs substantially more light than external mixing. The snow grain shape effect on absorption is relatively small, but its effect on asymmetry factor is substantial. Due to a greater probability of intercepting photons, multiple inclusions of BC/dust exhibit a larger absorption than an equal-volume single inclusion. The spectral absorption (0.2-5 µm) for snow grains internally mixed with BC/dust is confined to wavelengths shorter than about 1.4 µm, beyond which ice absorption predominates. Based on the single-scattering properties determined from stochastic and light absorption parameterizations and using the adding/doubling method for spectral radiative transfer, we find that internal mixing reduces snow albedo substantially more than external mixing and that the snow grain shape plays a critical role in snow albedo calculations through its forward scattering strength. Also, multiple inclusion of BC/dust significantly reduces snow albedo as compared to an equal-volume single sphere. For application to land/snow models, we propose a two-layer spectral snow parameterization involving contaminated fresh snow on top of old snow for investigating and understanding the climatic impact of multiple BC/dust internal mixing associated with snow grain metamorphism, particularly over mountain/snow topography.

Stochastic Parameterization for Light Absorption by Internally Mixed BC/dust in Snow Grains for Application to Climate Models

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

Liou, K. N.; Takano, Y.; He, Cenlin

2014-06-27

A stochastic approach to model the positions of BC/dust internally mixed with two snow-grain types has been developed, including hexagonal plate/column (convex) and Koch snowflake (concave). Subsequently, light absorption and scattering analysis can be followed by means of an improved geometric-optics approach coupled with Monte Carlo photon tracing to determine their single-scattering properties. For a given shape (plate, Koch snowflake, spheroid, or sphere), internal mixing absorbs more light than external mixing. The snow-grain shape effect on absorption is relatively small, but its effect on the asymmetry factor is substantial. Due to a greater probability of intercepting photons, multiple inclusions ofmore » BC/dust exhibit a larger absorption than an equal-volume single inclusion. The spectral absorption (0.2 – 5 um) for snow grains internally mixed with BC/dust is confined to wavelengths shorter than about 1.4 um, beyond which ice absorption predominates. Based on the single-scattering properties determined from stochastic and light absorption parameterizations and using the adding/doubling method for spectral radiative transfer, we find that internal mixing reduces snow albedo more than external mixing and that the snow-grain shape plays a critical role in snow albedo calculations through the asymmetry factor. Also, snow albedo reduces more in the case of multiple inclusion of BC/dust compared to that of an equal-volume single sphere. For application to land/snow models, we propose a two-layer spectral snow parameterization containing contaminated fresh snow on top of old snow for investigating and understanding the climatic impact of multiple BC/dust internal mixing associated with snow grain metamorphism, particularly over mountains/snow topography.« less

Coupling between lower-tropospheric convective mixing and low-level clouds: Physical mechanisms and dependence on convection scheme.

PubMed

Vial, Jessica; Bony, Sandrine; Dufresne, Jean-Louis; Roehrig, Romain

2016-12-01

Several studies have pointed out the dependence of low-cloud feedbacks on the strength of the lower-tropospheric convective mixing. By analyzing a series of single-column model experiments run by a climate model using two different convective parametrizations, this study elucidates the physical mechanisms through which marine boundary-layer clouds depend on this mixing in the present-day climate and under surface warming. An increased lower-tropospheric convective mixing leads to a reduction of low-cloud fraction. However, the rate of decrease strongly depends on how the surface latent heat flux couples to the convective mixing and to boundary-layer cloud radiative effects: (i) on the one hand, the latent heat flux is enhanced by the lower-tropospheric drying induced by the convective mixing, which damps the reduction of the low-cloud fraction, (ii) on the other hand, the latent heat flux is reduced as the lower troposphere stabilizes under the effect of reduced low-cloud radiative cooling, which enhances the reduction of the low-cloud fraction. The relative importance of these two different processes depends on the closure of the convective parameterization. The convective scheme that favors the coupling between latent heat flux and low-cloud radiative cooling exhibits a stronger sensitivity of low-clouds to convective mixing in the present-day climate, and a stronger low-cloud feedback in response to surface warming. In this model, the low-cloud feedback is stronger when the present-day convective mixing is weaker and when present-day clouds are shallower and more radiatively active. The implications of these insights for constraining the strength of low-cloud feedbacks observationally is discussed.

Coupling between lower‐tropospheric convective mixing and low‐level clouds: Physical mechanisms and dependence on convection scheme

PubMed Central

Bony, Sandrine; Dufresne, Jean‐Louis; Roehrig, Romain

2016-01-01

Abstract Several studies have pointed out the dependence of low‐cloud feedbacks on the strength of the lower‐tropospheric convective mixing. By analyzing a series of single‐column model experiments run by a climate model using two different convective parametrizations, this study elucidates the physical mechanisms through which marine boundary‐layer clouds depend on this mixing in the present‐day climate and under surface warming. An increased lower‐tropospheric convective mixing leads to a reduction of low‐cloud fraction. However, the rate of decrease strongly depends on how the surface latent heat flux couples to the convective mixing and to boundary‐layer cloud radiative effects: (i) on the one hand, the latent heat flux is enhanced by the lower‐tropospheric drying induced by the convective mixing, which damps the reduction of the low‐cloud fraction, (ii) on the other hand, the latent heat flux is reduced as the lower troposphere stabilizes under the effect of reduced low‐cloud radiative cooling, which enhances the reduction of the low‐cloud fraction. The relative importance of these two different processes depends on the closure of the convective parameterization. The convective scheme that favors the coupling between latent heat flux and low‐cloud radiative cooling exhibits a stronger sensitivity of low‐clouds to convective mixing in the present‐day climate, and a stronger low‐cloud feedback in response to surface warming. In this model, the low‐cloud feedback is stronger when the present‐day convective mixing is weaker and when present‐day clouds are shallower and more radiatively active. The implications of these insights for constraining the strength of low‐cloud feedbacks observationally is discussed. PMID:28239438

Impact of Lateral Mixing in the Ocean on El Nino in Fully Coupled Climate Models

NASA Astrophysics Data System (ADS)

Gnanadesikan, A.; Russell, A.; Pradal, M. A. S.; Abernathey, R. P.

2016-02-01

Given the large number of processes that can affect El Nino, it is difficult to understand why different climate models simulate El Nino differently. This paper focusses on the role of lateral mixing by mesoscale eddies. There is significant disagreement about the value of the mixing coefficient ARedi which parameterizes the lateral mixing of tracers. Coupled climate models usually prescribe small values of this coefficient, ranging between a few hundred and a few thousand m2/s. Observations, however, suggest values that are much larger. We present a sensitivity study with a suite of Earth System Models that examines the impact of varying ARedi on the amplitude of El Nino. We examine the effect of varying a spatially constant ARedi over a range of values similar to that seen in the IPCC AR5 models, as well as looking at two spatially varying distributions based on altimetric velocity estimates. While the expectation that higher values of ARedi should damp anomalies is borne out in the model, it is more than compensated by a weaker damping due to vertical mixing and a stronger response of atmospheric winds to SST anomalies. Under higher mixing, a weaker zonal SST gradient causes the center of convection over the Warm pool to shift eastward and to become more sensitive to changes in cold tongue SSTs . Changes in the SST gradient also explain interdecadal ENSO variability within individual model runs.

The roles of vertical mixing, solar radiation, and wind stress in a model simulation of the sea surface temperature seasonal cycle in the tropical Pacfic Ocean

NASA Technical Reports Server (NTRS)

Chen, Dake; Busalacchi, Antonio J.; Rothstein, Lewis M.

1994-01-01

The climatological seasonal cycle of sea surface temperature (SST) in the tropical Pacific is simulated using a newly developed upper ocean model. The roles of vertical mixing, solar radiation, and wind stress are investigated in a hierarchy of numerical experiments with various combinations of vertical mixing algorithms and surface-forcing products. It is found that the large SST annual cycle in the eastern equatorial Pacific is, to a large extent, controlled by the annually varying mixed layer depth which, in turn, is mainly determined by the competing effects of solar radiation and wind forcing. With the application of our hybrid vertical mixing scheme the model-simulated SST annual cycle is much improved in both amplitude and phase as compared to the case of a constant mixed layer depth. Beside the strong effects on vertical mixing, solar radiation is the primary heating term in the surface layer heat budget, and wind forcing influences SST by driving oceanic advective processes that redistribute heat in the upper ocean. For example, the SST seasonal cycle in the western Pacific basically follows the semiannual variation of solar heating, and the cycle in the central equatorial region is significantly affected by the zonal advective heat flux associated with the seasonally reversing South Equatorial Current. It has been shown in our experiments that the amount of heat flux modification needed to eliminate the annual mean SST errors in the model is, on average, no larger than the annual mean uncertainties among the various surface flux products used in this study. Whereas a bias correction is needed to account for remaining uncertainties in the annual mean heat flux, this study demonstrates that with proper treatment of mixed layer physics and realistic forcing functions the seasonal variability of SST is capable of being simulated successfully in response to external forcing without relying on a relaxation or damping formulation for the dominant surface heat flux contributions.

Impact of freeze-drying, mixing and horizontal transport on water vapor in the upper troposphere and lower stratosphere (UTLS)

NASA Astrophysics Data System (ADS)

Poshyvailo, Liubov; Ploeger, Felix; Müller, Rolf; Tao, Mengchu; Konopka, Paul; Abdoulaye Diallo, Mohamadou; Grooß, Jens-Uwe; Günther, Gebhard; Riese, Martin

2017-04-01

Water vapor in the upper troposphere and lower stratosphere (UTLS) is a key player in the global radiation budget. Therefore, a realistic representation of the water vapor distribution in this region and the involved control processes is critical for climate models, but largely uncertain hitherto. It is known that the extremely low temperatures around the tropical tropopause cause the dominant factor controlling water vapor in the lower stratosphere. Here, we focus on additional processes, such as horizontal transport between tropics and extratropics, small-scale mixing, and freeze-drying. We assess the sensitivities of simulated water vapor in the UTLS from simulations with the Chemical Lagrangian Model of the Stratosphere (CLaMS). CLaMS is a Lagrangian transport model, with a parameterization of small-scale mixing (model diffusion) which is coupled to deformations in the large-scale flow. First, to assess the robustness of water vapor with respect to the meteorological datasets we examine CLaMS driven by ECMWF ERA-Interim and the Japanese 55-year reanalysis. Second, to investigate the effects of small-scale mixing we vary the parameterized mixing strength in the CLaMS model between the reference case with the mixing strength optimized to reproduce atmospheric trace gas observations and a purely advective simulation with parameterized mixing turned off. Also calculation of Lagrangian cold points gives further insight of the processes involved. Third, to assess the effects of horizontal transport between the tropics and extratropics we carry out sensitivity simulations with horizontal transport barriers along latitude circles at the equator, 15°N/S and 35°N/S. Finally, the impact of Antarctic dehydration is estimated from additional sensitivity simulations with switched off freeze-drying in the model at high latitudes of 50°N/S. Our results show that the uncertainty in the tropical tropopause temperatures between current reanalysis datasets causes significant differences in simulated water vapor in the lower stratosphere of about 0.5 ppmv. We further find that small-scale mixing increases troposphere-stratosphere exchange causing moistening of the tropopause region and the tropical stratosphere. Besides, there is an enhancement of water vapor along the subtropical jets, particularly in the Southern hemisphere, and in the Asian monsoon in the UTLS. In the Northern extratropics above about 430K potential temperature, small-scale mixing causes drying by increasing horizontal transport between tropics and extratropics. The negligible effect of a transport barrier along the equator shows that the impact of intrahemispheric exchange on water vapor in the UTLS is very weak. Comparison to simulations with transport barriers in the subtropics, on the other hand, shows the effect of the Asian monsoon in moistening middle and high latitudes and the impact of transported dry air from the tropics towards high latitudes.

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

PubMed

Ghidey, Wendimagegn; Lesaffre, Emmanuel; Verbeke, Geert

2010-12-01

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

Synergism and effect of high initial volatile fatty acid concentrations during food waste and pig manure anaerobic co-digestion.

PubMed

Dennehy, Conor; Lawlor, Peadar G; Croize, Thomas; Jiang, Yan; Morrison, Liam; Gardiner, Gillian E; Zhan, Xinmin

2016-10-01

Anaerobic co-digestion of food waste (FW) and pig manure (PM) was undertaken in batch mode at 37°C in order to identify and quantify the synergistic effects of co-digestion on the specific methane yield (SMY) and reaction kinetics. The effects of the high initial volatile fatty acid (VFA) concentrations in PM on synergy observed during co-digestion, and on kinetic modelling were investigated. PM to FW mixing ratios of 1/0, 4/1, 3/2, 2/3, 1/4 and 0/1 (VS basis) were examined. No VFA or ammonia inhibition was observed. The highest SMY of 521±29ml CH4/gVS was achieved at a PM/FW mixing ratio of 1/4. Synergy in terms of both reaction kinetics and SMY occurred at PM/FW mixing ratios of 3/2, 2/3 and 1/4. Initial VFA concentrations did not explain the synergy observed. Throughout the study the conversion of butyric acid was inhibited. Due to the high initial VFA content of PM, conventional first order and Gompertz models were inappropriate for determining reaction kinetics. A dual pooled first order model was found to provide the best fit for the data generated in this study. The optimal mixing ratio in terms of both reaction kinetics and SMY was found at a PM/FW mixing ratio of 1/4. Copyright © 2016 Elsevier Ltd. All rights reserved.

Role of crystal field in mixed alkali metal effect: electron paramagnetic resonance study of mixed alkali metal oxyfluoro vanadate glasses.

PubMed

Honnavar, Gajanan V; Ramesh, K P; Bhat, S V

2014-01-23

The mixed alkali metal effect is a long-standing problem in glasses. Electron paramagnetic resonance (EPR) is used by several researchers to study the mixed alkali metal effect, but a detailed analysis of the nearest neighbor environment of the glass former using spin-Hamiltonian parameters was elusive. In this study we have prepared a series of vanadate glasses having general formula (mol %) 40 V2O5-30BaF2-(30 - x)LiF-xRbF with x = 5, 10, 15, 20, 25, and 30. Spin-Hamiltonian parameters of V(4+) ions were extracted by simulating and fitting to the experimental spectra using EasySpin. From the analysis of these parameters it is observed that the replacement of lithium ions by rubidium ions follows a "preferential substitution model". Using this proposed model, we were able to account for the observed variation in the ratio of the g parameter, which goes through a maximum. This reflects an asymmetric to symmetric changeover of the alkali metal ion environment around the vanadium site. Further, this model also accounts for the variation in oxidation state of vanadium ion, which was confirmed from the variation in signal intensity of EPR spectra.

Effects of partitioned enthalpy of mixing on glass-forming ability

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

Song, Wen-Xiong; Zhao, Shi-Jin, E-mail: shijin.zhao@shu.edu.cn

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{submore » 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.« less

Perspectives on dilution jet mixing. [in creating temperature patterns at combustor exits in gas turbine engines

NASA Technical Reports Server (NTRS)

Holdeman, J. D.; Srinivasan, R.

1986-01-01

A microcomputer code which displays 3-D oblique and 2-D plots of the temperature distribution downstream of jets mixing with a confined crossflow has been used to investigate the effects of varying the several independent flow and geometric parameters on the mixing. Temperature profiles calculated with this empirical model are presented to show the effects of orifice size and spacing, momentum flux ratio, density ratio, variable temperature mainstream, flow area convergence, orifice aspect ratio, and opposed and axially staged rows of jets.

Fuel treatments alter the effects of wildfire in a mixed-evergreen forest, Oregon, USA.

Treesearch

Crystal L. Raymond; David L. Peterson

2005-01-01

We had the rare opportunity to quantify the relationship between fuels and fire severity using prefire surface and canopy fuel data and fire severity data after a wildfire. The study area is a mixed-evergreen forest of southwestern Oregon with a mixed-severity fire regime. Modeled fire behavior showed that thinning reduced canopy fuels, thereby decreasing the potential...

Automated mixed traffic vehicle control and scheduling study

NASA Technical Reports Server (NTRS)

Peng, T. K. C.; Chon, K.

1976-01-01

The operation and the expected performance of a proposed automatic guideway transit system which uses low speed automated mixed traffic vehicles (AMTVs) were analyzed. Vehicle scheduling and headway control policies were evaluated with a transit system simulation model. The effect of mixed traffic interference on the average vehicle speed was examined with a vehicle pedestrian interface model. Control parameters regulating vehicle speed were evaluated for safe stopping and passenger comfort. Some preliminary data on the cost and operation of an experimental AMTV system are included. These data were the result of a separate task conducted at JPL, and were included as background information.

Scale model performance test investigation of exhaust system mixers for an Energy Efficient Engine /E3/ propulsion system

NASA Technical Reports Server (NTRS)

Kuchar, A. P.; Chamberlin, R.

1980-01-01

A scale model performance test was conducted as part of the NASA Energy Efficient Engine (E3) Program, to investigate the geometric variables that influence the aerodynamic design of exhaust system mixers for high-bypass, mixed-flow engines. Mixer configuration variables included lobe number, penetration and perimeter, as well as several cutback mixer geometries. Mixing effectiveness and mixer pressure loss were determined using measured thrust and nozzle exit total pressure and temperature surveys. Results provide a data base to aid the analysis and design development of the E3 mixed-flow exhaust system.

Logit-normal mixed model for Indian monsoon precipitation

NASA Astrophysics Data System (ADS)

Dietz, L. R.; Chatterjee, S.

2014-09-01

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

General Framework for Effect Sizes in Cluster Randomized Experiments

ERIC Educational Resources Information Center

VanHoudnos, Nathan

2016-01-01

Cluster randomized experiments are ubiquitous in modern education research. Although a variety of modeling approaches are used to analyze these data, perhaps the most common methodology is a normal mixed effects model where some effects, such as the treatment effect, are regarded as fixed, and others, such as the effect of group random assignment…

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

PubMed

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

2015-08-01

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

Assessing and Upgrading Ocean Mixing for the Study of Climate Change

NASA Astrophysics Data System (ADS)

Howard, A. M.; Fells, J.; Lindo, F.; Tulsee, V.; Canuto, V.; Cheng, Y.; Dubovikov, M. S.; Leboissetier, A.

2016-12-01

Climate is critical. Climate variability affects us all; Climate Change is a burning issue. Droughts, floods, other extreme events, and Global Warming's effects on these and problems such as sea-level rise and ecosystem disruption threaten lives. Citizens must be informed to make decisions concerning climate such as "business as usual" vs. mitigating emissions to keep warming within bounds. Medgar Evers undergraduates aid NASA research while learning climate science and developing computer&math skills. To make useful predictions we must realistically model each component of the climate system, including the ocean, whose critical role includes transporting&storing heat and dissolved CO2. We need physically based parameterizations of key ocean processes that can't be put explicitly in a global climate model, e.g. vertical&lateral mixing. The NASA-GISS turbulence group uses theory to model mixing including: 1) a comprehensive scheme for small scale vertical mixing, including convection&shear, internal waves & double-diffusion, and bottom tides 2) a new parameterization for the lateral&vertical mixing by mesoscale eddies. For better understanding we write our own programs. To assess the modelling MATLAB programs visualize and calculate statistics, including means, standard deviations and correlations, on NASA-GISS OGCM output with different mixing schemes and help us study drift from observations. We also try to upgrade the schemes, e.g. the bottom tidal mixing parameterizations' roughness, calculated from high resolution topographic data using Gaussian weighting functions with cut-offs. We study the effects of their parameters to improve them. A FORTRAN program extracts topography data subsets of manageable size for a MATLAB program, tested on idealized cases, to visualize&calculate roughness on. Students are introduced to modeling a complex system, gain a deeper appreciation of climate science, programming skills and familiarity with MATLAB, while furthering climate science by improving our mixing schemes. We are incorporating climate research into our college curriculum. The PI is both a member of the turbulence group at NASA-GISS and an associate professor at Medgar Evers College of CUNY, an urban minority serving institution in central Brooklyn. Supported by NSF Award AGS-1359293.

Dynamic Infinite Mixed-Membership Stochastic Blockmodel.

PubMed

Fan, Xuhui; Cao, Longbing; Xu, Richard Yi Da

2015-09-01

Directional and pairwise measurements are often used to model interactions in a social network setting. The mixed-membership stochastic blockmodel (MMSB) was a seminal work in this area, and its ability has been extended. However, models such as MMSB face particular challenges in modeling dynamic networks, for example, with the unknown number of communities. Accordingly, this paper proposes a dynamic infinite mixed-membership stochastic blockmodel, a generalized framework that extends the existing work to potentially infinite communities inside a network in dynamic settings (i.e., networks are observed over time). Additional model parameters are introduced to reflect the degree of persistence among one's memberships at consecutive time stamps. Under this framework, two specific models, namely mixture time variant and mixture time invariant models, are proposed to depict two different time correlation structures. Two effective posterior sampling strategies and their results are presented, respectively, using synthetic and real-world data.

Design of a rapid magnetic microfluidic mixer

NASA Astrophysics Data System (ADS)

Ballard, Matthew; Owen, Drew; Mills, Zachary Grant; Hanasoge, Srinivas; Hesketh, Peter; Alexeev, Alexander

2015-11-01

Using three-dimensional simulations and experiments, we demonstrate rapid mixing of fluid streams in a microchannel using orbiting magnetic microbeads. We use a lattice Boltzmann model coupled to a Brownian dynamics model to perform numerical simulations that study in depth the effect of system parameters such as channel configuration and fluid and bead velocities. We use our findings to aid the design of an experimental micromixer. Using this experimental device, we demonstrate rapid microfluidic mixing over a compact channel length, and validate our numerical simulation results. Finally, we use numerical simulations to study the physical mechanisms leading to microfluidic mixing in our system. Our findings demonstrate a promising method of rapid microfluidic mixing over a short distance, with applications in lab-on-a-chip sample testing.

Internal friction and vulnerability of mixed alkali glasses.

PubMed

Peibst, Robby; Schott, Stephan; Maass, Philipp

2005-09-09

Based on a hopping model we show how the mixed alkali effect in glasses can be understood if only a small fraction c(V) of the available sites for the mobile ions is vacant. In particular, we reproduce the peculiar behavior of the internal friction and the steep fall ("vulnerability") of the mobility of the majority ion upon small replacements by the minority ion. The single and mixed alkali internal friction peaks are caused by ion-vacancy and ion-ion exchange processes. If c(V) is small, they can become comparable in height even at small mixing ratios. The large vulnerability is explained by a trapping of vacancies induced by the minority ions. Reasonable choices of model parameters yield typical behaviors found in experiments.

Effects of preheat and mix on the fuel adiabat of an imploding capsule

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

Cheng, B.; Kwan, T. J. T.; Wang, Y. M.

We demonstrate the effect of preheat, hydrodynamic mix and vorticity on the adiabat of the deuterium-tritium (DT) fuel in fusion capsule experiments. We show that the adiabat of the DT fuel increases resulting from hydrodynamic mixing due to the phenomenon of entropy of mixture. An upper limit of mix, M clean=M DT ≥ 0:98 is found necessary to keep the DT fuel on a low adiabat. We demonstrate in this study that the use of a high adiabat for the DT fuel in theoretical analysis and with the aid of 1D code simulations could explain some aspects of 3D effectsmore » and mix in capsule implosion. Furthermore, we can infer from our physics model and the observed neutron images the adiabat of the DT fuel in the capsule and the amount of mix produced on the hot spot.« less

Numerical simulation of the non-Newtonian mixing layer

NASA Technical Reports Server (NTRS)

Azaiez, Jalel; Homsy, G. M.

1993-01-01

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

Effects of preheat and mix on the fuel adiabat of an imploding capsule

DOE PAGES

Cheng, B.; Kwan, T. J. T.; Wang, Y. M.; ...

2016-12-01

We demonstrate the effect of preheat, hydrodynamic mix and vorticity on the adiabat of the deuterium-tritium (DT) fuel in fusion capsule experiments. We show that the adiabat of the DT fuel increases resulting from hydrodynamic mixing due to the phenomenon of entropy of mixture. An upper limit of mix, M clean=M DT ≥ 0:98 is found necessary to keep the DT fuel on a low adiabat. We demonstrate in this study that the use of a high adiabat for the DT fuel in theoretical analysis and with the aid of 1D code simulations could explain some aspects of 3D effectsmore » and mix in capsule implosion. Furthermore, we can infer from our physics model and the observed neutron images the adiabat of the DT fuel in the capsule and the amount of mix produced on the hot spot.« less

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

PubMed

Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver

2016-12-01

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

Modeling and Qualification of a Modified Emission Unit for Radioactive Air Emissions Stack Sampling Compliance.

PubMed

Barnett, J Matthew; Yu, Xiao-Ying; Recknagle, Kurtis P; Glissmeyer, John A

2016-11-01

A planned laboratory space and exhaust system modification to the Pacific Northwest National Laboratory Material Science and Technology Building indicated that a new evaluation of the mixing at the air sampling system location would be required for compliance to ANSI/HPS N13.1-2011. The modified exhaust system would add a third fan, thereby increasing the overall exhaust rate out the stack, thus voiding the previous mixing study. Prior to modifying the radioactive air emissions exhaust system, a three-dimensional computational fluid dynamics computer model was used to evaluate the mixing at the sampling system location. Modeling of the original three-fan system indicated that not all mixing criteria could be met. A second modeling effort was conducted with the addition of an air blender downstream of the confluence of the three fans, which then showed satisfactory mixing results. The final installation included an air blender, and the exhaust system underwent full-scale tests to verify velocity, cyclonic flow, gas, and particulate uniformity. The modeling results and those of the full-scale tests show agreement between each of the evaluated criteria. The use of a computational fluid dynamics code was an effective aid in the design process and allowed the sampling system to remain in its original location while still meeting the requirements for sampling at a well mixed location.

Assessing Discriminative Performance at External Validation of Clinical Prediction Models

PubMed Central

Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W.

2016-01-01

Introduction External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. Methods We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. Results The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. Conclusion The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients. PMID:26881753

Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

PubMed

Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W

2016-01-01

External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.

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

PubMed Central

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

2011-01-01

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

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

PubMed

Lin, Tsung-I; Wang, Wan-Lun

2017-10-01

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

A kinematic eddy viscosity model including the influence of density variations and preturbulence

NASA Technical Reports Server (NTRS)

Cohen, L. S.

1973-01-01

A model for the kinematic eddy viscosity was developed which accounts for the turbulence produced as a result of jet interactions between adjacent streams as well as the turbulence initially present in the streams. In order to describe the turbulence contribution from jet interaction, the eddy viscosity suggested by Prandtl was adopted, and a modification was introduced to account for the effect of density variation through the mixing layer. The form of the modification was ascertained from a study of the compressible turbulent boundary layer on a flat plate. A kinematic eddy viscosity relation which corresponds to the initial turbulence contribution was derived by employing arguments used by Prandtl in his mixing length hypothesis. The resulting expression for self-preserving flow is similar to that which describes the mixing of a submerged jet. Application of the model has led to analytical predictions which are in good agreement with available turbulent mixing experimental data.

Unification of gauge, family, and flavor symmetries illustrated in gauged SU(12) models

DOE PAGES

Albright, Carl H.; Feger, Robert P.; Kephart, Thomas W.

2016-04-25

In this study, to explain quark and lepton masses and mixing angles, one has to extend the standard model, and the usual practice is to put the quarks and leptons into irreducible representations of discrete groups. We argue that discrete flavor symmetries (and their concomitant problems) can be avoided if we extend the gauge group. In the framework of SU(12) we give explicit examples of models having varying degrees of predictability obtained by scanning over groups and representations and identifying cases with operators contributing to mass and mixing matrices that need little fine- tuning of prefactors. Fitting with quark andmore » lepton masses run to the GUT scale and known mixing angles allows us to make predictions for the neutrino masses and hierarchy, the octant of the atmospheric mixing angle, leptonic CP violation, Majorana phases, and the effective mass observed in neutrinoless double beta decay.« less

Adaptive mixed finite element methods for Darcy flow in fractured porous media

NASA Astrophysics Data System (ADS)

Chen, Huangxin; Salama, Amgad; Sun, Shuyu

2016-10-01

In this paper, we propose adaptive mixed finite element methods for simulating the single-phase Darcy flow in two-dimensional fractured porous media. The reduced model that we use for the simulation is a discrete fracture model coupling Darcy flows in the matrix and the fractures, and the fractures are modeled by one-dimensional entities. The Raviart-Thomas mixed finite element methods are utilized for the solution of the coupled Darcy flows in the matrix and the fractures. In order to improve the efficiency of the simulation, we use adaptive mixed finite element methods based on novel residual-based a posteriori error estimators. In addition, we develop an efficient upscaling algorithm to compute the effective permeability of the fractured porous media. Several interesting examples of Darcy flow in the fractured porous media are presented to demonstrate the robustness of the algorithm.

Wave–turbulence interaction-induced vertical mixing and its effects in ocean and climate models

PubMed Central

Qiao, Fangli; Yuan, Yeli; Deng, Jia; Dai, Dejun; Song, Zhenya

2016-01-01

Heated from above, the oceans are stably stratified. Therefore, the performance of general ocean circulation models and climate studies through coupled atmosphere–ocean models depends critically on vertical mixing of energy and momentum in the water column. Many of the traditional general circulation models are based on total kinetic energy (TKE), in which the roles of waves are averaged out. Although theoretical calculations suggest that waves could greatly enhance coexisting turbulence, no field measurements on turbulence have ever validated this mechanism directly. To address this problem, a specially designed field experiment has been conducted. The experimental results indicate that the wave–turbulence interaction-induced enhancement of the background turbulence is indeed the predominant mechanism for turbulence generation and enhancement. Based on this understanding, we propose a new parametrization for vertical mixing as an additive part to the traditional TKE approach. This new result reconfirmed the past theoretical model that had been tested and validated in numerical model experiments and field observations. It firmly establishes the critical role of wave–turbulence interaction effects in both general ocean circulation models and atmosphere–ocean coupled models, which could greatly improve the understanding of the sea surface temperature and water column properties distributions, and hence model-based climate forecasting capability. PMID:26953182

Magnetic properties of magnetic bilayer Kekulene structure: A Monte Carlo study

NASA Astrophysics Data System (ADS)

Jabar, A.; Masrour, R.

2018-06-01

In the present work, we have studied the magnetic properties of magnetic bilayer Kekulene structure with mixed spin-5/2 and spin-2 Ising model using Monte Carlo study. The magnetic phase diagrams of mixed spins Ising model have been given. The thermal total, partial magnetization and magnetic susceptibilities of the mixed spin-5/2 and spin-2 Ising model on a magnetic bilayer Kekulene structure are obtained. The transition temperature has been deduced. The effect of crystal field and exchange interactions on the this bilayers has been studied. The partial and total magnetic hysteresis cycles of the mixed spin-5/2 and spin-2 Ising model on a magnetic bilayer Kekulene structure have been given. The superparamagnetism behavior is observed in magnetic bilayer Kekulene structure. The magnetic coercive field decreases with increasing the exchange interactions between σ-σ and temperatures values and increases with increasing the absolute value of exchange interactions between σ-S. The multiple hysteresis behavior appears.

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

PubMed Central

Ortiz de Solorzano, Isabel; Uson, Laura; Larrea, Ane; Miana, Mario; Sebastian, Victor; Arruebo, Manuel

2016-01-01

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. PMID:27524896

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

PubMed

Ortiz de Solorzano, Isabel; Uson, Laura; Larrea, Ane; Miana, Mario; Sebastian, Victor; Arruebo, Manuel

2016-01-01

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.

Intercomparison of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds

NASA Astrophysics Data System (ADS)

Muhlbauer, A.; Hashino, T.; Xue, L.; Teller, A.; Lohmann, U.; Rasmussen, R. M.; Geresdi, I.; Pan, Z.

2010-09-01

Anthropogenic aerosols serve as a source of both cloud condensation nuclei (CCN) and ice nuclei (IN) and affect microphysical properties of clouds. Increasing aerosol number concentrations is hypothesized to retard the cloud droplet coalescence and the riming in mixed-phase clouds, thereby decreasing orographic precipitation. This study presents results from a model intercomparison of 2-D simulations of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds. The sensitivity of orographic precipitation to changes in the aerosol number concentrations is analysed and compared for various dynamical and thermodynamical situations. Furthermore, the sensitivities of microphysical processes such as coalescence, aggregation, riming and diffusional growth to changes in the aerosol number concentrations are evaluated and compared. The participating numerical models are the model from the Consortium for Small-Scale Modeling (COSMO) with bulk microphysics, the Weather Research and Forecasting (WRF) model with bin microphysics and the University of Wisconsin modeling system (UWNMS) with a spectral ice habit prediction microphysics scheme. All models are operated on a cloud-resolving scale with 2 km horizontal grid spacing. The results of the model intercomparison suggest that the sensitivity of orographic precipitation to aerosol modifications varies greatly from case to case and from model to model. Neither a precipitation decrease nor a precipitation increase is found robustly in all simulations. Qualitative robust results can only be found for a subset of the simulations but even then quantitative agreement is scarce. Estimates of the aerosol effect on orographic precipitation are found to range from -19% to 0% depending on the simulated case and the model. Similarly, riming is shown to decrease in some cases and models whereas it increases in others, which implies that a decrease in riming with increasing aerosol load is not a robust result. Furthermore, it is found that neither a decrease in cloud droplet coalescence nor a decrease in riming necessarily implies a decrease in precipitation due to compensation effects by other microphysical pathways. The simulations suggest that mixed-phase conditions play an important role in buffering the effect of aerosol perturbations on cloud microphysics and reducing the overall susceptibility of clouds and precipitation to changes in the aerosol number concentrations. As a consequence the aerosol effect on precipitation is suggested to be less pronounced or even inverted in regions with high terrain (e.g., the Alps or Rocky Mountains) or in regions where mixed-phase microphysics is important for the climatology of orographic precipitation.

Impact of Langmuir Turbulence on Upper Ocean Response to Hurricane Edouard: Model and Observations

NASA Astrophysics Data System (ADS)

Blair, A.; Ginis, I.; Hara, T.; Ulhorn, E.

2017-12-01

Tropical cyclone intensity is strongly affected by the air-sea heat flux beneath the storm. When strong storm winds enhance upper ocean turbulent mixing and entrainment of colder water from below the thermocline, the resulting sea surface temperature cooling may reduce the heat flux to the storm and weaken the storm. Recent studies suggest that this upper ocean turbulence is strongly affected by different sea states (Langmuir turbulence), which are highly complex and variable in tropical cyclone conditions. In this study, the upper ocean response under Hurricane Edouard (2014) is investigated using a coupled ocean-wave model with and without an explicit sea state dependent Langmuir turbulence parameterization. The results are compared with in situ observations of sea surface temperature and mixed layer depth from AXBTs, as well as satellite sea surface temperature observations. Overall, the model results of mixed layer deepening and sea surface temperature cooling under and behind the storm are consistent with observations. The model results show that the effects of sea state dependent Langmuir turbulence can be significant, particularly on the mixed layer depth evolution. Although available observations are not sufficient to confirm such effects, some observed trends suggest that the sea state dependent parameterization might be more accurate than the traditional (sea state independent) parameterization.

Synergistic effect of mixed neutron and gamma irradiation in bipolar operational amplifier OP07

NASA Astrophysics Data System (ADS)

Yan, Liu; Wei, Chen; Shanchao, Yang; Xiaoming, Jin; Chaohui, He

2016-09-01

This paper presents the synergistic effects in bipolar operational amplifier OP07. The radiation effects are studied by neutron beam, gamma ray, and mixed neutron/gamma ray environments. The characterateristics of the synergistic effects are studied through comparison of different experiment results. The results show that the bipolar operational amplifier OP07 exhibited significant synergistic effects in the mixed neutron and gamma irradiation. The bipolar transistor is identified as the most radiation sensitive unit of the operational amplifier. In this paper, a series of simulations are performed on bipolar transistors in different radiation environments. In the theoretical simulation, the geometric model and calculations based on the Medici toolkit are built to study the radiation effects in bipolar components. The effect of mixed neutron and gamma irradiation is simulated based on the understanding of the underlying mechanisms of radiation effects in bipolar transistors. The simulated results agree well with the experimental data. The results of the experiments and simulation indicate that the radiation effects in the bipolar devices subjected to mixed neutron and gamma environments is not a simple combination of total ionizing dose (TID) effects and displacement damage. The data suggests that the TID effect could enhance the displacement damage. The synergistic effect should not be neglected in complex radiation environments.

Mixed-effects location and scale Tobit joint models for heterogeneous longitudinal data with skewness, detection limits, and measurement errors.

PubMed

Lu, Tao

2017-01-01

The joint modeling of mean and variance for longitudinal data is an active research area. This type of model has the advantage of accounting for heteroscedasticity commonly observed in between and within subject variations. Most of researches focus on improving the estimating efficiency but ignore many data features frequently encountered in practice. In this article, we develop a mixed-effects location scale joint model that concurrently accounts for longitudinal data with multiple features. Specifically, our joint model handles heterogeneity, skewness, limit of detection, measurement errors in covariates which are typically observed in the collection of longitudinal data from many studies. We employ a Bayesian approach for making inference on the joint model. The proposed model and method are applied to an AIDS study. Simulation studies are performed to assess the performance of the proposed method. Alternative models under different conditions are compared.

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

ERIC Educational Resources Information Center

Murakami, Akira

2016-01-01

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

Using a tracer technique to identify the extent of non-ideal flows in the continuous mixing of non-Newtonian fluids

NASA Astrophysics Data System (ADS)

Patel, D.; Ein-Mozaffari, F.; Mehrvar, M.

2013-05-01

The identification of non-ideal flows in a continuous-flow mixing of non-Newtonian fluids is a challenging task for various chemical industries: plastic manufacturing, water and wastewater treatment, and pulp and paper manufacturing. Non-ideal flows such as channelling, recirculation, and dead zones significantly affect the performance of continuous-flow mixing systems. Therefore, the main objective of this paper was to develop an identification protocol to measure non-ideal flows in the continuous-flow mixing system. The extent of non-ideal flows was quantified using a dynamic model that incorporated channelling, recirculation, and dead volume in the mixing vessel. To estimate the dynamic model parameters, the system was excited using a frequency-modulated random binary input by injecting the saline solution (as a tracer) into the fresh feed stream prior to being pumped into the mixing vessel. The injection of the tracer was controlled by a computer-controlled on-off solenoid valve. Using the trace technique, the extent of channelling and the effective mixed volume were successfully determined and used as mixing quality criteria. Such identification procedures can be applied at various areas of chemical engineering in order to improve the mixing quality.

Intercomparison of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds

NASA Astrophysics Data System (ADS)

Muhlbauer, A.; Hashino, T.; Xue, L.; Teller, A.; Lohmann, U.; Rasmussen, R. M.; Geresdi, I.; Pan, Z.

2010-04-01

Anthropogenic aerosols serve as a source of both cloud condensation nuclei (CCN) and ice nuclei (IN) and affect microphysical properties of clouds. Increasing aerosol number concentrations is hypothesized to retard the cloud droplet collision/coalescence and the riming in mixed-phase clouds, thereby decreasing orographic precipitation. This study presents results from a model intercomparison of 2-D simulations of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds. The sensitivity of orographic precipitation to changes in the aerosol number concentrations is analyzed and compared for various dynamical and thermodynamical situations. Furthermore, the sensitivities of microphysical processes such as collision/coalescence, aggregation and riming to changes in the aerosol number concentrations are evaluated and compared. The participating models are the Consortium for Small-Scale Modeling's (COSMO) model with bulk-microphysics, the Weather Research and Forecasting (WRF) model with bin-microphysics and the University of Wisconsin modeling system (UWNMS) with a spectral ice-habit prediction microphysics scheme. All models are operated on a cloud-resolving scale with 2 km horizontal grid spacing. The results of the model intercomparison suggest that the sensitivity of orographic precipitation to aerosol modifications varies greatly from case to case and from model to model. Neither a precipitation decrease nor a precipitation increase is found robustly in all simulations. Qualitative robust results can only be found for a subset of the simulations but even then quantitative agreement is scarce. Estimates of the second indirect aerosol effect on orographic precipitation are found to range from -19% to 0% depending on the simulated case and the model. Similarly, riming is shown to decrease in some cases and models whereas it increases in others which implies that a decrease in riming with increasing aerosol load is not a robust result. Furthermore, it is found that neither a decrease in cloud droplet coalescence nor a decrease in riming necessarily implies a decrease in precipitation due to compensation effects by other microphysical pathways. The simulations suggest that mixed-phase conditions play an important role in reducing the overall susceptibility of clouds and precipitation with respect to changes in the aerosols number concentrations. As a consequence the indirect aerosol effect on precipitation is suggested to be less pronounced or even inverted in regions with high terrain (e.g., the Alps or Rocky Mountains) or in regions where mixed-phase microphysics climatologically plays an important role for orographic precipitation.

A mixing timescale model for TPDF simulations of turbulent premixed flames

DOE PAGES

Kuron, Michael; Ren, Zhuyin; Hawkes, Evatt R.; ...

2017-02-06

Transported probability density function (TPDF) methods are an attractive modeling approach for turbulent flames as chemical reactions appear in closed form. However, molecular micro-mixing needs to be modeled and this modeling is considered a primary challenge for TPDF methods. In the present study, a new algebraic mixing rate model for TPDF simulations of turbulent premixed flames is proposed, which is a key ingredient in commonly used molecular mixing models. The new model aims to properly account for the transition in reactive scalar mixing rate behavior from the limit of turbulence-dominated mixing to molecular mixing behavior in flamelets. An a priorimore » assessment of the new model is performed using direct numerical simulation (DNS) data of a lean premixed hydrogen–air jet flame. The new model accurately captures the mixing timescale behavior in the DNS and is found to be a significant improvement over the commonly used constant mechanical-to-scalar mixing timescale ratio model. An a posteriori TPDF study is then performed using the same DNS data as a numerical test bed. The DNS provides the initial conditions and time-varying input quantities, including the mean velocity, turbulent diffusion coefficient, and modeled scalar mixing rate for the TPDF simulations, thus allowing an exclusive focus on the mixing model. Here, the new mixing timescale model is compared with the constant mechanical-to-scalar mixing timescale ratio coupled with the Euclidean Minimum Spanning Tree (EMST) mixing model, as well as a laminar flamelet closure. It is found that the laminar flamelet closure is unable to properly capture the mixing behavior in the thin reaction zones regime while the constant mechanical-to-scalar mixing timescale model under-predicts the flame speed. Furthermore, the EMST model coupled with the new mixing timescale model provides the best prediction of the flame structure and flame propagation among the models tested, as the dynamics of reactive scalar mixing across different flame regimes are appropriately accounted for.« less

A mixing timescale model for TPDF simulations of turbulent premixed flames

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

Kuron, Michael; Ren, Zhuyin; Hawkes, Evatt R.

Transported probability density function (TPDF) methods are an attractive modeling approach for turbulent flames as chemical reactions appear in closed form. However, molecular micro-mixing needs to be modeled and this modeling is considered a primary challenge for TPDF methods. In the present study, a new algebraic mixing rate model for TPDF simulations of turbulent premixed flames is proposed, which is a key ingredient in commonly used molecular mixing models. The new model aims to properly account for the transition in reactive scalar mixing rate behavior from the limit of turbulence-dominated mixing to molecular mixing behavior in flamelets. An a priorimore » assessment of the new model is performed using direct numerical simulation (DNS) data of a lean premixed hydrogen–air jet flame. The new model accurately captures the mixing timescale behavior in the DNS and is found to be a significant improvement over the commonly used constant mechanical-to-scalar mixing timescale ratio model. An a posteriori TPDF study is then performed using the same DNS data as a numerical test bed. The DNS provides the initial conditions and time-varying input quantities, including the mean velocity, turbulent diffusion coefficient, and modeled scalar mixing rate for the TPDF simulations, thus allowing an exclusive focus on the mixing model. Here, the new mixing timescale model is compared with the constant mechanical-to-scalar mixing timescale ratio coupled with the Euclidean Minimum Spanning Tree (EMST) mixing model, as well as a laminar flamelet closure. It is found that the laminar flamelet closure is unable to properly capture the mixing behavior in the thin reaction zones regime while the constant mechanical-to-scalar mixing timescale model under-predicts the flame speed. Furthermore, the EMST model coupled with the new mixing timescale model provides the best prediction of the flame structure and flame propagation among the models tested, as the dynamics of reactive scalar mixing across different flame regimes are appropriately accounted for.« less

Scaling laws and reduced-order models for mixing and reactive-transport in heterogeneous anisotropic porous media

NASA Astrophysics Data System (ADS)

Mudunuru, M. K.; Karra, S.; Nakshatrala, K. B.

2016-12-01

Fundamental to enhancement and control of the macroscopic spreading, mixing, and dilution of solute plumes in porous media structures is the topology of flow field and underlying heterogeneity and anisotropy contrast of porous media. Traditionally, in literature, the main focus was limited to the shearing effects of flow field (i.e., flow has zero helical density, meaning that flow is always perpendicular to vorticity vector) on scalar mixing [2]. However, the combined effect of anisotropy of the porous media and the helical structure (or chaotic nature) of the flow field on the species reactive-transport and mixing has been rarely studied. Recently, it has been experimentally shown that there is an irrefutable evidence that chaotic advection and helical flows are inherent in porous media flows [1,2]. In this poster presentation, we present a non-intrusive physics-based model-order reduction framework to quantify the effects of species mixing in-terms of reduced-order models (ROMs) and scaling laws. The ROM framework is constructed based on the recent advancements in non-negative formulations for reactive-transport in heterogeneous anisotropic porous media [3] and non-intrusive ROM methods [4]. The objective is to generate computationally efficient and accurate ROMs for species mixing for different values of input data and reactive-transport model parameters. This is achieved by using multiple ROMs, which is a way to determine the robustness of the proposed framework. Sensitivity analysis is performed to identify the important parameters. Representative numerical examples from reactive-transport are presented to illustrate the importance of the proposed ROMs to accurately describe mixing process in porous media. [1] Lester, Metcalfe, and Trefry, "Is chaotic advection inherent to porous media flow?," PRL, 2013. [2] Ye, Chiogna, Cirpka, Grathwohl, and Rolle, "Experimental evidence of helical flow in porous media," PRL, 2015. [3] Mudunuru, and Nakshatrala, "On enforcing maximum principles and achieving element-wise species balance for advection-diffusion-reaction equations under the finite element method," JCP, 2016. [4] Quarteroni, Manzoni, and Negri. "Reduced Basis Methods for Partial Differential Equations: An Introduction," Springer, 2016.

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

PubMed

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.

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

PubMed

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

2013-01-01

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

Quantification and Statistical Modeling—Part I: Breathing-Zone Concentrations of Monomeric and Polymeric 1,6-Hexamethylene Diisocyanate

PubMed Central

Fent, Kenneth W.; Gaines, Linda G. Trelles; Thomasen, Jennifer M.; Flack, Sheila L.; Ding, Kai; Herring, Amy H.; Whittaker, Stephen G.; Nylander-French, Leena A.

2009-01-01

We conducted a repeated exposure-assessment survey for task-based breathing-zone concentrations (BZCs) of monomeric and polymeric 1,6-hexamethylene diisocyanate (HDI) during spray painting on 47 automotive spray painters from North Carolina and Washington State. We report here the use of linear mixed modeling to identify the primary determinants of the measured BZCs. Both one-stage (N = 98 paint tasks) and two-stage (N = 198 paint tasks) filter sampling was used to measure concentrations of HDI, uretidone, biuret, and isocyanurate. The geometric mean (GM) level of isocyanurate (1410 μg m−3) was higher than all other analytes (i.e. GM < 7.85 μg m−3). The mixed models were unique to each analyte and included factors such as analyte-specific paint concentration, airflow in the paint booth, and sampler type. The effect of sampler type was corroborated by side-by-side one- and two-stage personal air sampling (N = 16 paint tasks). According to paired t-tests, significantly higher concentrations of HDI (P = 0.0363) and isocyanurate (P = 0.0035) were measured using one-stage samplers. Marginal R2 statistics were calculated for each model; significant fixed effects were able to describe 25, 52, 54, and 20% of the variability in BZCs of HDI, uretidone, biuret, and isocyanurate, respectively. Mixed models developed in this study characterize the processes governing individual polyisocyanate BZCs. In addition, the mixed models identify ways to reduce polyisocyanate BZCs and, hence, protect painters from potential adverse health effects. PMID:19622637

Factors associated with parasite dominance in fishes from Brazil.

PubMed

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

2016-06-14

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

Mixing state of regionally transported soot particles and the coating effect on their size and shape at a mountain site in Japan

NASA Astrophysics Data System (ADS)

Adachi, Kouji; Zaizen, Yuji; Kajino, Mizuo; Igarashi, Yasuhito

2014-05-01

Soot particles influence the global climate through interactions with sunlight. A coating on soot particles increases their light absorption by increasing their absorption cross section and cloud condensation nuclei activity when mixed with other hygroscopic aerosol components. Therefore, it is important to understand how soot internally mixes with other materials to accurately simulate its effects in climate models. In this study, we used a transmission electron microscope (TEM) with an auto particle analysis system, which enables more particles to be analyzed than a conventional TEM. Using the TEM, soot particle size and shape (shape factor) were determined with and without coating from samples collected at a remote mountain site in Japan. The results indicate that ~10% of aerosol particles between 60 and 350 nm in aerodynamic diameters contain or consist of soot particles and ~75% of soot particles were internally mixed with nonvolatile ammonium sulfate or other materials. In contrast to an assumption that coatings change soot shape, both internally and externally mixed soot particles had similar shape and size distributions. Larger aerosol particles had higher soot mixing ratios, i.e., more than 40% of aerosol particles with diameters >1 µm had soot inclusions, whereas <20% of aerosol particles with diameters <1 µm included soot. Our results suggest that climate models may use the same size distributions and shapes for both internally and externally mixed soot; however, changing the soot mixing ratios in the different aerosol size bins is necessary.

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

PubMed

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

2017-11-08

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

PDF turbulence modeling and DNS

NASA Technical Reports Server (NTRS)

Hsu, A. T.

1992-01-01

The problem of time discontinuity (or jump condition) in the coalescence/dispersion (C/D) mixing model is addressed in probability density function (pdf). A C/D mixing model continuous in time is introduced. With the continuous mixing model, the process of chemical reaction can be fully coupled with mixing. In the case of homogeneous turbulence decay, the new model predicts a pdf very close to a Gaussian distribution, with finite higher moments also close to that of a Gaussian distribution. Results from the continuous mixing model are compared with both experimental data and numerical results from conventional C/D models. The effect of Coriolis forces on compressible homogeneous turbulence is studied using direct numerical simulation (DNS). The numerical method used in this study is an eight order compact difference scheme. Contrary to the conclusions reached by previous DNS studies on incompressible isotropic turbulence, the present results show that the Coriolis force increases the dissipation rate of turbulent kinetic energy, and that anisotropy develops as the Coriolis force increases. The Taylor-Proudman theory does apply since the derivatives in the direction of the rotation axis vanishes rapidly. A closer analysis reveals that the dissipation rate of the incompressible component of the turbulent kinetic energy indeed decreases with a higher rotation rate, consistent with incompressible flow simulations (Bardina), while the dissipation rate of the compressible part increases; the net gain is positive. Inertial waves are observed in the simulation results.

External Validation of a Case-Mix Adjustment Model for the Standardized Reporting of 30-Day Stroke Mortality Rates in China.

PubMed

Yu, Ping; Pan, Yuesong; Wang, Yongjun; Wang, Xianwei; Liu, Liping; Ji, Ruijun; Meng, Xia; Jing, Jing; Tong, Xu; Guo, Li; Wang, Yilong

2016-01-01

A case-mix adjustment model has been developed and externally validated, demonstrating promise. However, the model has not been thoroughly tested among populations in China. In our study, we evaluated the performance of the model in Chinese patients with acute stroke. The case-mix adjustment model A includes items on age, presence of atrial fibrillation on admission, National Institutes of Health Stroke Severity Scale (NIHSS) score on admission, and stroke type. Model B is similar to Model A but includes only the consciousness component of the NIHSS score. Both model A and B were evaluated to predict 30-day mortality rates in 13,948 patients with acute stroke from the China National Stroke Registry. The discrimination of the models was quantified by c-statistic. Calibration was assessed using Pearson's correlation coefficient. The c-statistic of model A in our external validation cohort was 0.80 (95% confidence interval, 0.79-0.82), and the c-statistic of model B was 0.82 (95% confidence interval, 0.81-0.84). Excellent calibration was reported in the two models with Pearson's correlation coefficient (0.892 for model A, p<0.001; 0.927 for model B, p = 0.008). The case-mix adjustment model could be used to effectively predict 30-day mortality rates in Chinese patients with acute stroke.

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

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

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 parcelmore » 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.« less

Phototherapy with blue and green mixed-light is as effective against unconjugated jaundice as blue light and reduces oxidative stress in the Gunn rat model.

PubMed

Uchida, Yumiko; Morimoto, Yukihiro; Uchiike, Takao; Kamamoto, Tomoyuki; Hayashi, Tamaki; Arai, Ikuyo; Nishikubo, Toshiya; Takahashi, Yukihiro

2015-07-01

Phototherapy using blue light-emitting diodes (LED) is effective against neonatal jaundice. However, green light phototherapy also reduces unconjugated jaundice. We aimed to determine whether mixed blue and green light can relieve jaundice with minimal oxidative stress as effectively as either blue or green light alone in a rat model. Gunn rats were exposed to phototherapy with blue (420-520 nm), filtered blue (FB; 440-520 nm without<440-nm wavelengths, FB50 (half the irradiance of filtered blue), mixed (filtered 50% blue and 50% green), and green (490-590 nm) LED irradiation for 24h. The effects of phototherapy are expressed as ratios of serum total (TB) and unbound (UB) bilirubin before and after exposure to each LED. Urinary 8-hydroxy-2'-deoxyguanosine (8-OHdG) was measured by HPLC before and after exposure to each LED to determine photo-oxidative stress. Values < 1.00 indicate effective phototherapy. The ratios of TB and UB were decreased to 0.85, 0.89, 1.07, 0.90, and 1.04, and 0.85, 0.94, 0.93, 0.89, and 1.09 after exposure to blue, filtered blue, FB50, and filtered blue mixed with green LED, respectively. In contrast, urinary 8-OHdG increased to 2.03, 1.25, 0.96, 1.36, 1.31, and 1.23 after exposure to blue, filtered blue, FB50, mixed, green LED, and control, indicating side-effects (> 1.00), respectively. Blue plus green phototherapy is as effective as blue phototherapy and it attenuates irradiation-induced oxidative stress. Combined blue and green spectra might be effective against neonatal hyperbilirubinemia. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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

2015-04-01

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

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

PubMed Central

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

2017-01-01

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

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

USDA-ARS?s Scientific Manuscript database

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

Modeling Cloud Phase Fraction Based on In-situ Observations in Stratiform Clouds

NASA Astrophysics Data System (ADS)

Boudala, F. S.; Isaac, G. A.

2005-12-01

Mixed-phase clouds influence weather and climate in several ways. Due to the fact that they exhibit very different optical properties as compared to ice or liquid only clouds, they play an important role in the earth's radiation balance by modifying the optical properties of clouds. Precipitation development in clouds is also enhanced under mixed-phase conditions and these clouds may contain large supercooled drops that freeze quickly in contact with aircraft surfaces that may be a hazard to aviation. The existence of ice and liquid phase clouds together in the same environment is thermodynamically unstable, and thus they are expected to disappear quickly. However, several observations show that mixed-phase clouds are relatively stable in the natural environment and last for several hours. Although there have been some efforts being made in the past to study the microphysical properties of mixed-phase clouds, there are still a number of uncertainties in modeling these clouds particularly in large scale numerical models. In most models, very simple temperature dependent parameterizations of cloud phase fraction are being used to estimate the fraction of ice or liquid phase in a given mixed-phase cloud. In this talk, two different parameterizations of ice fraction using in-situ aircraft measurements of cloud microphysical properties collected in extratropical stratiform clouds during several field programs will be presented. One of the parameterizations has been tested using a single prognostic equation developed by Tremblay et al. (1996) for application in the Canadian regional weather prediction model. The addition of small ice particles significantly increased the vapor deposition rate when the natural atmosphere is assumed to be water saturated, and thus this enhanced the glaciation of simulated mixed-phase cloud via the Bergeron-Findeisen process without significantly affecting the other cloud microphysical processes such as riming and particle sedimentation rates. After the water vapor pressure in mixed-phase cloud was modified based on the Lord et al. (1984) scheme by weighting the saturation water vapor pressure with ice fraction, it was possible to simulate more stable mixed-phase cloud. It was also noted that the ice particle concentration (L>100 μm) in mixed-phase cloud is lower on average by a factor 3 and as a result the parameterization should be corrected for this effect. After accounting for this effect, the parameterized ice fraction agreed well with observed mean ice fraction.

Experimental and Modeling Investigation of the Effect of Air Preheat on the Formation of NOx in an RQL Combustor

NASA Technical Reports Server (NTRS)

Samuelsen, G. S.; Brouwer, J.; Vardakas, M. A.; Holderman, J. D.

2012-01-01

The Rich-burn/Quick-mix/Lean-burn (RQL) combustor concept has been proposed to minimize the formation of oxides of nitrogen (NOx) in gas turbine systems. The success of this low-NOx combustor strategy is dependent upon the links between the formation of NOx, inlet air preheat temperature, and the mixing of the jet air and fuel-rich streams. Chemical equilibrium and kinetics modeling calculations and experiments were performed to further understand NOx emissions in an RQL combustor. The results indicate that as the temperature at the inlet to the mixing zone increases (due to preheating and/or operating conditions) the fuel-rich zone equivalence ratio must be increased to achieve minimum NOx formation in the primary zone of the combustor. The chemical kinetics model illustrates that there is sufficient residence time to produce NOx at concentrations that agree well with the NOx measurements. Air preheat was found to have very little effect on mixing, but preheating the air did increase NOx emissions significantly. By understanding the mechanisms governing NOx formation and the temperature dependence of key reactions in the RQL combustor, a strategy can be devised to further reduce NOx emissions using the RQL concept.

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

PubMed Central

2011-01-01

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

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

PubMed

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

2011-08-19

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

An adjoint-based framework for maximizing mixing in binary fluids

NASA Astrophysics Data System (ADS)

Eggl, Maximilian; Schmid, Peter

2017-11-01

Mixing in the inertial, but laminar parameter regime is a common application in a wide range of industries. Enhancing the efficiency of mixing processes thus has a fundamental effect on product quality, material homogeneity and, last but not least, production costs. In this project, we address mixing efficiency in the above mentioned regime (Reynolds number Re = 1000 , Peclet number Pe = 1000) by developing and demonstrating an algorithm based on nonlinear adjoint looping that minimizes the variance of a passive scalar field which models our binary Newtonian fluids. The numerical method is based on the FLUSI code (Engels et al. 2016), a Fourier pseudo-spectral code, which we modified and augmented by scalar transport and adjoint equations. Mixing is accomplished by moving stirrers which are numerically modeled using a penalization approach. In our two-dimensional simulations we consider rotating circular and elliptic stirrers and extract optimal mixing strategies from the iterative scheme. The case of optimizing shape and rotational speed of the stirrers will be demonstrated.

Soil mixing of stratified contaminated sands.

PubMed

Al-Tabba, A; Ayotamuno, M J; Martin, R J

2000-02-01

Validation of soil mixing for the treatment of contaminated ground is needed in a wide range of site conditions to widen the application of the technology and to understand the mechanisms involved. Since very limited work has been carried out in heterogeneous ground conditions, this paper investigates the effectiveness of soil mixing in stratified sands using laboratory-scale augers. This enabled a low cost investigation of factors such as grout type and form, auger design, installation procedure, mixing mode, curing period, thickness of soil layers and natural moisture content on the unconfined compressive strength, leachability and leachate pH of the soil-grout mixes. The results showed that the auger design plays a very important part in the mixing process in heterogeneous sands. The variability of the properties measured in the stratified soils and the measurable variations caused by the various factors considered, highlighted the importance of duplicating appropriate in situ conditions, the usefulness of laboratory-scale modelling of in situ conditions and the importance of modelling soil and contaminant heterogeneities at the treatability study stage.

Effect of exercise on patient specific abdominal aortic aneurysm flow topology and mixing

PubMed Central

Arzani, Amirhossein; Les, Andrea S.; Dalman, Ronald L.; Shadden, Shawn C.

2014-01-01

SUMMARY Computational fluid dynamics modeling was used to investigate changes in blood transport topology between rest and exercise conditions in five patient-specific abdominal aortic aneurysm models. Magnetic resonance imaging was used to provide the vascular anatomy and necessary boundary conditions for simulating blood velocity and pressure fields inside each model. Finite-time Lyapunov exponent fields, and associated Lagrangian coherent structures, were computed from blood velocity data, and used to compare features of the transport topology between rest and exercise both mechanistically and qualitatively. A mix-norm and mix-variance measure based on fresh blood distribution throughout the aneurysm over time were implemented to quantitatively compare mixing between rest and exercise. Exercise conditions resulted in higher and more uniform mixing, and reduced the overall residence time in all aneurysms. Separated regions of recirculating flow were commonly observed in rest, and these regions were either reduced or removed by attached and unidirectional flow during exercise, or replaced with regional chaotic and transiently turbulent mixing, or persisted and even extended during exercise. The main factor that dictated the change in flow topology from rest to exercise was the behavior of the jet of blood penetrating into the aneurysm during systole. PMID:24493404

Application of monotone integrated large eddy simulation to Rayleigh-Taylor mixing.

PubMed

Youngs, David L

2009-07-28

Rayleigh-Taylor (RT) instability occurs when a dense fluid rests on top of a light fluid in a gravitational field. It also occurs in an equivalent situation (in the absence of gravity) when an interface between fluids of different density is accelerated by a pressure gradient, e.g. in inertial confinement fusion implosions. Engineering models (Reynolds-averaged Navier-Stokes models) are needed to represent the effect of mixing in complex applications. However, large eddy simulation (LES) currently makes an essential contribution to understanding the mixing process and calibration or validation of the engineering models. In this paper, three cases are used to illustrate the current role of LES: (i) mixing at a plane boundary, (ii) break-up of a layer of dense fluid due to RT instability, and (iii) mixing in a simple spherical implosion. A monotone integrated LES approach is preferred because of the need to treat discontinuities in the flow, i.e. the initial density discontinuities or shock waves. Of particular interest is the influence of initial conditions and how this needs to be allowed for in engineering modelling. It is argued that loss of memory of the initial conditions is unlikely to occur in practical applications.

Analysis of air quality with numerical simulation (CMAQ), and observations of trace gases

NASA Astrophysics Data System (ADS)

Castellanos, Patricia

Ozone, a secondary pollutant, is a strong oxidant that can pose a risk to human health. It is formed from a complex set of photochemical reactions involving nitrogen oxides (NOx) and volatile organic compounds (VOCs). Ambient measurements and air quality modeling of ozone and its precursors are important tools for support of regulatory decisions, and analyzing atmospheric chemical and physical processes. I worked on three methods to improve our understanding of photochemical ozone production in the Eastern U.S.: a new detector for NO2, a numerical experiment to test the sensitivity to the timing to emissions, and comparison of modeled and observed vertical profiles of CO and ozone. A small, commercially available cavity ring-down spectroscopy (CRDS) NO2 detector suitable for surface and aircraft monitoring was modified and characterized. The CRDS detector was run in parallel to an ozone chemiluminescence device with photolytic conversion of NO2 to NO. The two instruments measured ambient air in suburban Maryland. A linear least-squares fit to a direct comparison of the data resulted in a slope of 0.960+/-0.002 and R of 0.995, showing agreement between two measurement techniques within experimental uncertainty. The sensitivity of the Community Multiscale Air Quality (CMAQ) model to the temporal variation of four emissions sectors was investigated to understand the effect of emissions' daily variability on modeled ozone. Decreasing the variability of mobile source emissions changed the 8-hour maximum ozone concentration by +/-7 parts per billion by volume (ppbv). Increasing the variability of point source emissions affected ozone concentrations by +/-6 ppbv, but only in areas close to the source. CO is an ideal tracer for analyzing pollutant transport in AQMs because the atmospheric lifetime is longer than the timescale of boundary layer mixing. CO can be used as a tracer if model performance of CO is well understood. An evaluation of CO model performance in CMAQ was carried out using aircraft observations taken for the Regional Atmospheric Measurement, Modeling and Prediction Program (RAMMPP) in the summer of 2002. Comparison of modeled and observed CO total columns were generally in agreement within 5-10%. There is little evidence that the CO emissions inventory is grossly overestimated. CMAQ predicts the same vertical profile shape for all of the observations, i.e. CO is well mixed throughout the boundary layer. However, the majority of observations have poorly mixed air below 500 m, and well mixed air above. CMAQ appears to be transporting CO away from the surface more quickly than what is observed. Turbulent mixing in the model is represented with K-theory. A minimum Kz that scales with fractional urban land use is imposed in order to account for subgrid scale obstacles in urban areas and the urban heat island effect. Micrometeorological observations suggest that the minimum Kz is somewhat high. A sensitivity case where the minimum K z was reduced from 0.5 m2/s to 0.1 m2/s was carried out. Model performance of surface ozone observations at night increased significantly. The model better captures the observed ozone minimum with slower mixing, and increases ozone concentrations in the residual layer. Model performance of CO and ozone morning vertical profiles improves, but the effect is not large enough to bring the model and measurements into agreement. Comparison of modeled CO and O3 vertical profiles shows that turbulent mixing (as represented by eddy diffusivity) appears to be too fast, while convective mixing may be too slow.

Applications of MIDAS regression in analysing trends in water quality

NASA Astrophysics Data System (ADS)

Penev, Spiridon; Leonte, Daniela; Lazarov, Zdravetz; Mann, Rob A.

2014-04-01

We discuss novel statistical methods in analysing trends in water quality. Such analysis uses complex data sets of different classes of variables, including water quality, hydrological and meteorological. We analyse the effect of rainfall and flow on trends in water quality utilising a flexible model called Mixed Data Sampling (MIDAS). This model arises because of the mixed frequency in the data collection. Typically, water quality variables are sampled fortnightly, whereas the rain data is sampled daily. The advantage of using MIDAS regression is in the flexible and parsimonious modelling of the influence of the rain and flow on trends in water quality variables. We discuss the model and its implementation on a data set from the Shoalhaven Supply System and Catchments in the state of New South Wales, Australia. Information criteria indicate that MIDAS modelling improves upon simplistic approaches that do not utilise the mixed data sampling nature of the data.

Computational fluid dynamics investigation of turbulence models for non-newtonian fluid flow in anaerobic digesters.

PubMed

Wu, Binxin

2010-12-01

In this paper, 12 turbulence models for single-phase non-newtonian fluid flow in a pipe are evaluated by comparing the frictional pressure drops obtained from computational fluid dynamics (CFD) with those from three friction factor correlations. The turbulence models studied are (1) three high-Reynolds-number k-ε models, (2) six low-Reynolds-number k-ε models, (3) two k-ω models, and (4) the Reynolds stress model. The simulation results indicate that the Chang-Hsieh-Chen version of the low-Reynolds-number k-ε model performs better than the other models in predicting the frictional pressure drops while the standard k-ω model has an acceptable accuracy and a low computing cost. In the model applications, CFD simulation of mixing in a full-scale anaerobic digester with pumped circulation is performed to propose an improvement in the effective mixing standards recommended by the U.S. EPA based on the effect of rheology on the flow fields. Characterization of the velocity gradient is conducted to quantify the growth or breakage of an assumed floc size. Placement of two discharge nozzles in the digester is analyzed to show that spacing two nozzles 180° apart with each one discharging at an angle of 45° off the wall is the most efficient. Moreover, the similarity rules of geometry and mixing energy are checked for scaling up the digester.

Physical Interpretation of Mixing Diagrams

NASA Astrophysics Data System (ADS)

Khain, Alexander; Pinsky, Mark; Magaritz-Ronen, L.

2018-01-01

Type of mixing at cloud edges is often determined by means of mixing diagrams showing the dependence of normalized cube of the mean volume radius on the dilution level. The mixing diagrams correspond to the final equilibrium state of mixing between two air volumes. While interpreting in situ measurements, scattering diagrams are plotted in which normalized droplet concentration is used instead of dilution level. Utilization of such scattering diagrams for interpretation of in situ observations faces significant difficulties and often leads to misinterpretation of the mixing process and to uncertain conclusions concerning the mixing type. In this study we analyze the scattering diagrams obtained by means of a Lagrangian-Eulerian model of a stratocumulus cloud. The model consists of 2,000 interacting Largangian parcels which mix with their neighbors during their motion in the atmospheric boundary layer. In the diagram, each parcel is denoted by a point. Changes of microphysical parameters of the parcel are represented by movements of the point in the scattering diagram. The method of plotting the scattering diagrams using the model is in many aspects similar to that used in in situ measurements. It is shown that a scattering diagram shows snapshots of a transient mixing process. The location of points in the scattering diagrams reflects largely the history and the origin of air parcels. Location of points on scattering diagram characterizes intensity of entrainment, and different parameters of droplet size distributions (DSDs) like concentration, mean volume (or effective) radius, and DSD width.

Comparison of mixed effects models of antimicrobial resistance metrics of livestock and poultry Salmonella isolates from a national monitoring system.

PubMed

Bjork, K E; Kopral, C A; Wagner, B A; Dargatz, D A

2015-12-01

Antimicrobial use in agriculture is considered a pathway for the selection and dissemination of resistance determinants among animal and human populations. From 1997 through 2003 the U.S. National Antimicrobial Resistance Monitoring System (NARMS) tested clinical Salmonella isolates from multiple animal and environmental sources throughout the United States for resistance to panels of 16-19 antimicrobials. In this study we applied two mixed effects models, the generalized linear mixed model (GLMM) and accelerated failure time frailty (AFT-frailty) model, to susceptible/resistant and interval-censored minimum inhibitory concentration (MIC) metrics, respectively, from Salmonella enterica subspecies enterica serovar Typhimurium isolates from livestock and poultry. Objectives were to compare characteristics of the two models and to examine the effects of time, species, and multidrug resistance (MDR) on the resistance of isolates to individual antimicrobials, as revealed by the models. Fixed effects were year of sample collection, isolate source species and MDR indicators; laboratory study site was included as a random effect. MDR indicators were significant for every antimicrobial and were dominant effects in multivariable models. Temporal trends and source species influences varied by antimicrobial. In GLMMs, the intra-class correlation coefficient ranged up to 0.8, indicating that the proportion of variance accounted for by laboratory study site could be high. AFT models tended to be more sensitive, detecting more curvilinear temporal trends and species differences; however, high levels of left- or right-censoring made some models unstable and results uninterpretable. Results from GLMMs may be biased by cutoff criteria used to collapse MIC data into binary categories, and may miss signaling important trends or shifts if the series of antibiotic dilutions tested does not span a resistance threshold. Our findings demonstrate the challenges of measuring the AMR ecosystem and the complexity of interacting factors, and have implications for future monitoring. We include suggestions for future data collection and analyses, including alternative modeling approaches. Published by Elsevier B.V.

The Managed Readiness Simulator: A Force Readiness Model

DTIC Science & Technology

2011-12-01

specific mili- tary occupations. Tyche Fleet Mix Model (Eisler, Bourque, and Reive 2009) provides the most effective mix of maritime fleet assets to...through the GUI input screens or imported from an external source such as a corporate database or spreadsheet. As the Simulation Manager, the GUI...Memorandum DRDC CORA TM 2011-xx. (in press) Skraba, A., M. Kljajic, A. Knaflic, D. Kofjac, and I. Podbregar. 2007. “Development of a Human Re

Effect of magnetic exchange, double exchange, vibronic coupling, and asymmetry on magnetic properties in d2-d3 mixed-valence dimers

NASA Astrophysics Data System (ADS)

Yang, Xiaohua; Hu, Haiquan; Chen, Zhida

The effect of magnetic exchange, double exchange, vibronic coupling, and asymmetry on magnetic properties of d2-d3 systems is discussed. The temperature-dependent magnetic moment was calculated with the semiclassical adiabatic approach. The results show that the vibronic coupling from the out-of-phase breathing vibration on the metal sites (Piepho, Krausz, and Schatz [PKS] model) and the vibronic coupling from the stretching vibration between the metal sites (P model) favor the localization and delocalization of the "extra" electron in mixed-valence dimers, respectively. The magnetic properties are determined by the interplay among magnetic exchange, double exchange, and vibronic coupling. The results obtained by analyzing d2-d3 systems can be generalized to other full delocalized dinuclear mixed valence systems with a unique transferable electron.

Acoustic and Aerothermal Performance Test of the Axisymmetric Coannular Ejector Nozzle. Volume 2; Acoustic Performance

NASA Technical Reports Server (NTRS)

Herkes, William

2000-01-01

Acoustic and propulsion performance testing of a model-scale Axisymmetric Coannular Ejector nozzle was conducted in the Boeing Low-speed Aeroacoustic Facility. This nozzle is a plug nozzle with an ejector design to provide aspiration of about 20% of the engine flow. A variety of mixing enhancers were designed to promote mixing of the engine and the aspirated flows. These included delta tabs, tone-injection rods, and wheeler ramps. This report addresses the acoustic aspects of the testing. The spectral characteristics of the various configurations of the nozzle are examined on a model-scale basis. This includes indentifying particular noise sources contributing to the spectra and the data are projected to full-scale flyover conditions to evaluate the effectiveness of the nozzle, and of the various mixing enhancers, on reducing the Effective Perceived Noise Levels.

A bayesian hierarchical model for classification with selection of functional predictors.

PubMed

Zhu, Hongxiao; Vannucci, Marina; Cox, Dennis D

2010-06-01

In functional data classification, functional observations are often contaminated by various systematic effects, such as random batch effects caused by device artifacts, or fixed effects caused by sample-related factors. These effects may lead to classification bias and thus should not be neglected. Another issue of concern is the selection of functions when predictors consist of multiple functions, some of which may be redundant. The above issues arise in a real data application where we use fluorescence spectroscopy to detect cervical precancer. In this article, we propose a Bayesian hierarchical model that takes into account random batch effects and selects effective functions among multiple functional predictors. Fixed effects or predictors in nonfunctional form are also included in the model. The dimension of the functional data is reduced through orthonormal basis expansion or functional principal components. For posterior sampling, we use a hybrid Metropolis-Hastings/Gibbs sampler, which suffers slow mixing. An evolutionary Monte Carlo algorithm is applied to improve the mixing. Simulation and real data application show that the proposed model provides accurate selection of functional predictors as well as good classification.

Turbulence closure for mixing length theories

NASA Astrophysics Data System (ADS)

Jermyn, Adam S.; Lesaffre, Pierre; Tout, Christopher A.; Chitre, Shashikumar M.

2018-05-01

We present an approach to turbulence closure based on mixing length theory with three-dimensional fluctuations against a two-dimensional background. This model is intended to be rapidly computable for implementation in stellar evolution software and to capture a wide range of relevant phenomena with just a single free parameter, namely the mixing length. We incorporate magnetic, rotational, baroclinic, and buoyancy effects exactly within the formalism of linear growth theories with non-linear decay. We treat differential rotation effects perturbatively in the corotating frame using a novel controlled approximation, which matches the time evolution of the reference frame to arbitrary order. We then implement this model in an efficient open source code and discuss the resulting turbulent stresses and transport coefficients. We demonstrate that this model exhibits convective, baroclinic, and shear instabilities as well as the magnetorotational instability. It also exhibits non-linear saturation behaviour, and we use this to extract the asymptotic scaling of various transport coefficients in physically interesting limits.

3D Visualization of Global Ocean Circulation

NASA Astrophysics Data System (ADS)

Nelson, V. G.; Sharma, R.; Zhang, E.; Schmittner, A.; Jenny, B.

2015-12-01

Advanced 3D visualization techniques are seldom used to explore the dynamic behavior of ocean circulation. Streamlines are an effective method for visualization of flow, and they can be designed to clearly show the dynamic behavior of a fluidic system. We employ vector field editing and extraction software to examine the topology of velocity vector fields generated by a 3D global circulation model coupled to a one-layer atmosphere model simulating preindustrial and last glacial maximum (LGM) conditions. This results in a streamline-based visualization along multiple density isosurfaces on which we visualize points of vertical exchange and the distribution of properties such as temperature and biogeochemical tracers. Previous work involving this model examined the change in the energetics driving overturning circulation and mixing between simulations of LGM and preindustrial conditions. This visualization elucidates the relationship between locations of vertical exchange and mixing, as well as demonstrates the effects of circulation and mixing on the distribution of tracers such as carbon isotopes.

Upscaling of dilution and mixing using a trajectory based Spatial Markov random walk model in a periodic flow domain

NASA Astrophysics Data System (ADS)

Sund, Nicole L.; Porta, Giovanni M.; Bolster, Diogo

2017-05-01

The Spatial Markov Model (SMM) is an upscaled model that has been used successfully to predict effective mean transport across a broad range of hydrologic settings. Here we propose a novel variant of the SMM, applicable to spatially periodic systems. This SMM is built using particle trajectories, rather than travel times. By applying the proposed SMM to a simple benchmark problem we demonstrate that it can predict mean effective transport, when compared to data from fully resolved direct numerical simulations. Next we propose a methodology for using this SMM framework to predict measures of mixing and dilution, that do not just depend on mean concentrations, but are strongly impacted by pore-scale concentration fluctuations. We use information from trajectories of particles to downscale and reconstruct pore-scale approximate concentration fields from which mixing and dilution measures are then calculated. The comparison between measurements from fully resolved simulations and predictions with the SMM agree very favorably.

Effect of driver's age and side of impact on crash severity along urban freeways: a mixed logit approach.

PubMed

Haleem, Kirolos; Gan, Albert

2013-09-01

This study identifies geometric, traffic, environmental, vehicle-related, and driver-related predictors of crash injury severity on urban freeways. The study takes advantage of the mixed logit model's ability to account for unobserved effects that are difficult to quantify and may affect the model estimation, such as the driver's reaction at the time of crash. Crashes of 5 years occurring on 89 urban freeway segments throughout the state of Florida in the United States were used. Examples of severity predictors explored include traffic volume, distance of the crash to the nearest ramp, and detailed driver's age, vehicle types, and sides of impact. To show how the parameter estimates could vary, a binary logit model was compared with the mixed logit model. It was found that the at-fault driver's age, traffic volume, distance of the crash to the nearest ramp, vehicle type, side of impact, and percentage of trucks significantly influence severity on urban freeways. Additionally, young at-fault drivers were associated with a significant severity risk increase relative to other age groups. It was also observed that some variables in the binary logit model yielded illogic estimates due to ignoring the random variation of the estimation. Since the at-fault driver's age and side of impact were significant random parameters in the mixed logit model, an in-depth investigation was performed. It was noticed that back, left, and right impacts had the highest risk among middle-aged drivers, followed by young drivers, very young drivers, and finally, old and very old drivers. To reduce side impacts due to lane changing, two primary strategies can be recommended. The first strategy is to conduct campaigns to convey the hazardous effect of changing lanes at higher speeds. The second is to devise in-vehicle side crash avoidance systems to alert drivers of a potential crash risk. The study provided a promising approach to screening the predictors before fitting the mixed logit model using the random forest technique. Furthermore, potential countermeasures were proposed to reduce the severity of impacts. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

Computer modeling movement of biomass in the bioreactors with bubbling mixing

NASA Astrophysics Data System (ADS)

Kuschev, L. A.; Suslov, D. Yu; Alifanova, A. I.

2017-01-01

Recently in the Russian Federation there is an observation of the development of biogas technologies which are used in organic waste conversion of agricultural enterprises, consequently improving the ecological environment. To intensify the process and effective outstanding performance of the acquisition of biogas the application of systems of mixing of bubbling is used. In the case of bubbling mixing of biomass in the bioreactor two-phase portions consisting of biomass and bubbles of gas are formed. The bioreactor computer model with bubble pipeline has been made in a vertical spiral form forming a cone type turned upside down. With the help of computing program of OpenFVM-Flow, an evaluation experiment was conducted to determine the key technological parameters of process of bubbling mixing and to get a visual picture of biomass flows distribution in the bioreactor. For the experimental bioreactor the following equation of V=190 l, speed level, the biomass circulation, and the time of a single cycle of uax =0,029 m/s; QC =0,00087 m3/s, Δtbm .=159 s. In future, we plan to conduct a series of theoretical and experimental researches into the mixing frequency influence on the biogas acquisition process effectiveness.

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

NASA Technical Reports Server (NTRS)

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.

Rating the raters in a mixed model: An approach to deciphering the rater reliability

NASA Astrophysics Data System (ADS)

Shang, Junfeng; Wang, Yougui

2013-05-01

Rating the raters has attracted extensive attention in recent years. Ratings are quite complex in that the subjective assessment and a number of criteria are involved in a rating system. Whenever the human judgment is a part of ratings, the inconsistency of ratings is the source of variance in scores, and it is therefore quite natural for people to verify the trustworthiness of ratings. Accordingly, estimation of the rater reliability will be of great interest and an appealing issue. To facilitate the evaluation of the rater reliability in a rating system, we propose a mixed model where the scores of the ratees offered by a rater are described with the fixed effects determined by the ability of the ratees and the random effects produced by the disagreement of the raters. In such a mixed model, for the rater random effects, we derive its posterior distribution for the prediction of random effects. To quantitatively make a decision in revealing the unreliable raters, the predictive influence function (PIF) serves as a criterion which compares the posterior distributions of random effects between the full data and rater-deleted data sets. The benchmark for this criterion is also discussed. This proposed methodology of deciphering the rater reliability is investigated in the multiple simulated and two real data sets.

An assumed pdf approach for the calculation of supersonic mixing layers

NASA Technical Reports Server (NTRS)

Baurle, R. A.; Drummond, J. P.; Hassan, H. A.

1992-01-01

In an effort to predict the effect that turbulent mixing has on the extent of combustion, a one-equation turbulence model is added to an existing Navier-Stokes solver with finite-rate chemistry. To average the chemical-source terms appearing in the species-continuity equations, an assumed pdf approach is also used. This code was used to analyze the mixing and combustion caused by the mixing layer formed by supersonic coaxial H2-air streams. The chemistry model employed allows for the formation of H2O2 and HO2. Comparisons are made with recent measurements using laser Raman diagnostics. Comparisons include temperature and its rms, and concentrations of H2, O2, N2, H2O, and OH. In general, good agreement with experiment was noted.

How we compute N matters to estimates of mixing in stratified flows

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

Arthur, Robert S.; Venayagamoorthy, Subhas K.; Koseff, Jeffrey R.

We know that most commonly used models for turbulent mixing in the ocean rely on a background stratification against which turbulence must work to stir the fluid. While this background stratification is typically well defined in idealized numerical models, it is more difficult to capture in observations. Here, a potential discrepancy in ocean mixing estimates due to the chosen calculation of the background stratification is explored using direct numerical simulation data of breaking internal waves on slopes. There are two different methods for computing the buoyancy frequencymore » $N$$, one based on a three-dimensionally sorted density field (often used in numerical models) and the other based on locally sorted vertical density profiles (often used in the field), are used to quantify the effect of$$N$$on turbulence quantities. It is shown that how$$N$$is calculated changes not only the flux Richardson number$$R_{f}$$, which is often used to parameterize turbulent mixing, but also the turbulence activity number or the Gibson number$$Gi$$, leading to potential errors in estimates of the mixing efficiency using$$Gi$-based parameterizations.« less

How we compute N matters to estimates of mixing in stratified flows

DOE PAGES

Arthur, Robert S.; Venayagamoorthy, Subhas K.; Koseff, Jeffrey R.; ...

2017-10-13

We know that most commonly used models for turbulent mixing in the ocean rely on a background stratification against which turbulence must work to stir the fluid. While this background stratification is typically well defined in idealized numerical models, it is more difficult to capture in observations. Here, a potential discrepancy in ocean mixing estimates due to the chosen calculation of the background stratification is explored using direct numerical simulation data of breaking internal waves on slopes. There are two different methods for computing the buoyancy frequencymore » $N$$, one based on a three-dimensionally sorted density field (often used in numerical models) and the other based on locally sorted vertical density profiles (often used in the field), are used to quantify the effect of$$N$$on turbulence quantities. It is shown that how$$N$$is calculated changes not only the flux Richardson number$$R_{f}$$, which is often used to parameterize turbulent mixing, but also the turbulence activity number or the Gibson number$$Gi$$, leading to potential errors in estimates of the mixing efficiency using$$Gi$-based parameterizations.« less

Variability in Proactive and Reactive Cognitive Control Processes Across the Adult Lifespan

PubMed Central

Karayanidis, Frini; Whitson, Lisa Rebecca; Heathcote, Andrew; Michie, Patricia T.

2011-01-01

Task-switching paradigms produce a highly consistent age-related increase in mixing cost [longer response time (RT) on repeat trials in mixed-task than single-task blocks] but a less consistent age effect on switch cost (longer RT on switch than repeat trials in mixed-task blocks). We use two approaches to examine the adult lifespan trajectory of control processes contributing to mixing cost and switch cost: latent variables derived from an evidence accumulation model of choice, and event-related potentials (ERP) that temporally differentiate proactive (cue-driven) and reactive (target-driven) control processes. Under highly practiced and prepared task conditions, aging was associated with increasing RT mixing cost but reducing RT switch cost. Both effects were largely due to the same cause: an age effect for mixed-repeat trials. In terms of latent variables, increasing age was associated with slower non-decision processes, slower rate of evidence accumulation about the target, and higher response criterion. Age effects on mixing costs were evident only on response criterion, the amount of evidence required to trigger a decision, whereas age effects on switch cost were present for all three latent variables. ERPs showed age-related increases in preparation for mixed-repeat trials, anticipatory attention, and post-target interference. Cue-locked ERPs that are linked to proactive control were associated with early emergence of age differences in response criterion. These results are consistent with age effects on strategic processes controlling decision caution. Consistent with an age-related decline in cognitive flexibility, younger adults flexibly adjusted response criterion from trial-to-trial on mixed-task blocks, whereas older adults maintained a high criterion for all trials. PMID:22073037

A Joint Modeling Approach for Reaction Time and Accuracy in Psycholinguistic Experiments

ERIC Educational Resources Information Center

Loeys, T.; Rosseel, Y.; Baten, K.

2011-01-01

In the psycholinguistic literature, reaction times and accuracy can be analyzed separately using mixed (logistic) effects models with crossed random effects for item and subject. Given the potential correlation between these two outcomes, a joint model for the reaction time and accuracy may provide further insight. In this paper, a Bayesian…

Simultaneous diagnosis of radial profiles and mix in NIF ignition-scale implosions via X-ray spectroscopy

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

Ciricosta, O.; Scott, H.; Durey, P.

In a National Ignition Facility implosion, hydrodynamic instabilities may cause the cold material from the imploding shell to be injected into the hot-spot (hot-spot mix), enhancing the radiative and conductive losses, which in turn may lead to a quenching of the ignition process. The bound-bound features of the spectrum emitted by high-Z ablator dopants that get mixed into the hot-spot have been previously used to infer the total amount of mixed mass; however, the typical errorbars are larger than the maximum tolerable mix. We present in this paper an improved 2D model for mix spectroscopy which can be used tomore » retrieve information on both the amount of mixed mass and the full imploded plasma profile. By performing radiation transfer and simultaneously fitting all of the features exhibited by the spectra, we are able to constrain self-consistently the effect of the opacity of the external layers of the target on the emission, thus improving the accuracy of the inferred mixed mass. The model's predictive capabilities are first validated by fitting simulated spectra arising from fully characterized hydrodynamic simulations, and then, the model is applied to previously published experimental results, providing values of mix mass in agreement with previous estimates. Finally, we show that the new self consistent procedure leads to better constrained estimates of mix and also provides insight into the sensitivity of the hot-spot spectroscopy to the spatial properties of the imploded capsule, such as the in-flight aspect ratio of the cold fuel surrounding the hotspot.« less

Simultaneous diagnosis of radial profiles and mix in NIF ignition-scale implosions via X-ray spectroscopy

DOE PAGES

Ciricosta, O.; Scott, H.; Durey, P.; ...

2017-11-06

In a National Ignition Facility implosion, hydrodynamic instabilities may cause the cold material from the imploding shell to be injected into the hot-spot (hot-spot mix), enhancing the radiative and conductive losses, which in turn may lead to a quenching of the ignition process. The bound-bound features of the spectrum emitted by high-Z ablator dopants that get mixed into the hot-spot have been previously used to infer the total amount of mixed mass; however, the typical errorbars are larger than the maximum tolerable mix. We present in this paper an improved 2D model for mix spectroscopy which can be used tomore » retrieve information on both the amount of mixed mass and the full imploded plasma profile. By performing radiation transfer and simultaneously fitting all of the features exhibited by the spectra, we are able to constrain self-consistently the effect of the opacity of the external layers of the target on the emission, thus improving the accuracy of the inferred mixed mass. The model's predictive capabilities are first validated by fitting simulated spectra arising from fully characterized hydrodynamic simulations, and then, the model is applied to previously published experimental results, providing values of mix mass in agreement with previous estimates. Finally, we show that the new self consistent procedure leads to better constrained estimates of mix and also provides insight into the sensitivity of the hot-spot spectroscopy to the spatial properties of the imploded capsule, such as the in-flight aspect ratio of the cold fuel surrounding the hotspot.« less

Simultaneous diagnosis of radial profiles and mix in NIF ignition-scale implosions via X-ray spectroscopy

NASA Astrophysics Data System (ADS)

Ciricosta, O.; Scott, H.; Durey, P.; Hammel, B. A.; Epstein, R.; Preston, T. R.; Regan, S. P.; Vinko, S. M.; Woolsey, N. C.; Wark, J. S.

2017-11-01

In a National Ignition Facility implosion, hydrodynamic instabilities may cause the cold material from the imploding shell to be injected into the hot-spot (hot-spot mix), enhancing the radiative and conductive losses, which in turn may lead to a quenching of the ignition process. The bound-bound features of the spectrum emitted by high-Z ablator dopants that get mixed into the hot-spot have been previously used to infer the total amount of mixed mass; however, the typical errorbars are larger than the maximum tolerable mix. We present here an improved 2D model for mix spectroscopy which can be used to retrieve information on both the amount of mixed mass and the full imploded plasma profile. By performing radiation transfer and simultaneously fitting all of the features exhibited by the spectra, we are able to constrain self-consistently the effect of the opacity of the external layers of the target on the emission, thus improving the accuracy of the inferred mixed mass. The model's predictive capabilities are first validated by fitting simulated spectra arising from fully characterized hydrodynamic simulations, and then, the model is applied to previously published experimental results, providing values of mix mass in agreement with previous estimates. We show that the new self consistent procedure leads to better constrained estimates of mix and also provides insight into the sensitivity of the hot-spot spectroscopy to the spatial properties of the imploded capsule, such as the in-flight aspect ratio of the cold fuel surrounding the hotspot.

Southern Ocean vertical iron fluxes; the ocean model effect

NASA Astrophysics Data System (ADS)

Schourup-Kristensen, V.; Haucke, J.; Losch, M. J.; Wolf-Gladrow, D.; Voelker, C. D.

2016-02-01

The Southern Ocean plays a key role in the climate system, but commonly used large-scale ocean general circulation biogeochemical models give different estimates of current and future Southern Ocean net primary and export production. The representation of the Southern Ocean iron sources plays an important role for the modeled biogeochemistry. Studies of the iron supply to the surface mixed layer have traditionally focused on the aeolian and sediment contributions, but recent work has highlighted the importance of the vertical supply from below. We have performed a model study in which the biogeochemical model REcoM2 was coupled to two different ocean models, the Finite Element Sea-ice Ocean Model (FESOM) and the MIT general circulation model (MITgcm) and analyzed the magnitude of the iron sources to the surface mixed layer from below in the two models. Our results revealed a remarkable difference in terms of mechanism and magnitude of transport. The mean iron supply from below in the Southern Ocean was on average four times higher in MITgcm than in FESOM and the dominant pathway was entrainment in MITgcm, whereas diffusion dominated in FESOM. Differences in the depth and seasonal amplitude of the mixed layer between the models affect on the vertical iron profile, the relative position of the base of the mixed layer and ferricline and thereby also on the iron fluxes. These differences contribute to differences in the phytoplankton composition in the two models, as well as in the timing of the onset of the spring bloom. The study shows that the choice of ocean model has a significant impact on the iron supply to the Southern Ocean mixed layer and thus on the modeled carbon cycle, with possible implications for model runs predicting the future carbon uptake in the region.

AC electrothermal mixing for high conductive biofluids by arc-electrodes

NASA Astrophysics Data System (ADS)

Meng, Jiyu; Li, Shanshan; Li, Junwei; Yu, Chengzhuang; Wei, Chunyang; Dai, Shijie

2018-06-01

As a platform to mix the bioagents (i.e. serum, urine), we take advantage of the alternating current electrothermal (ACET) effect which is quite suitable for rapid pumping/mixing of high conductive biomicrofluids. Here we demonstrate the concept of a high-efficient mixing microfluidic chip as a basic unit to provide rapid mixing for lab-on-a-chip applications. As an active mixer, two streams are introduced into a ring-shape microchamber by a passive flow rate regulator, and then the microfluids in the chamber are actuated by a nonuniform electric field with a phase shift of 180°. It shows perfect mixing performance by arranging four arc-electrodes around the ring-shape microchamber subsequently. Taking the Joule heating and conductivity/permittivity changes into consideration, a temperature dependent fully coupled numerical model is presented. Then, the effects of applied voltages on mixing performance and temperature rise are provided to get an optimized design for ACET mixer. Moreover, the arrangement of the electrode array is analyzed to show the effects of electrode patterns on the swirls and mixing efficiencies. Since all the electrodes here are located along a ring-shape central microchamber, the ring-shape micromixer is quite suitable to function as a compact element modular for integrated microfluidic chips.

The economic implications of case-mix Medicaid reimbursement for nursing home care.

PubMed

Grabowski, David C

2002-01-01

In recent years, there has been large growth in the nursing home industry in the use of case-mix adjusted Medicaid payment systems that employ resident characteristics to predict the relative use of resources in setting payment levels. Little attention has been paid to the access and quality incentives that these systems provide in the presence of excess demand conditions due to certificate-of-need (CON) and construction moratoria. Using 1991 to 1998 panel data for all certified U.S. nursing homes, a fixed-effects model indicates that adoption of a case-mix payment system led to increased access for more dependent residents, but the effect was modified in excess demand markets. Quality remained relatively stable with the introduction of case-mix reimbursement, regardless of the presence of excess demand conditions. These results suggest that CON and construction moratoria are still important barriers within the nursing home market, and recent quality assurance activities related to the introduction of case-mix payment systems may have been effective.

Modeling indoor particulate exposures in inner city school classrooms

PubMed Central

Gaffin, Jonathan M.; Petty, Carter R.; Hauptman, Marissa; Kang, Choong-Min; Wolfson, Jack M.; Awad, Yara Abu; Di, Qian; Lai, Peggy S.; Sheehan, William J.; Baxi, Sachin; Coull, Brent A.; Schwartz, Joel D.; Gold, Diane R.; Koutrakis, Petros; Phipatanakul, Wanda

2016-01-01

Outdoor air pollution penetrates buildings and contributes to total indoor exposures. We investigated the relationship of indoor to outdoor particulate matter in inner-city school classrooms. The School Inner City Asthma Study investigates the effect of classroom-based environmental exposures on students with asthma in the northeast United States. Mixed-effects linear models were used to determine the relationships between indoor PM2.5 and BC and their corresponding outdoor concentrations, and to develop a model for predicting exposures to these pollutants. The indoor-outdoor sulfur ratio was used as an infiltration factor of outdoor fine particles. Weeklong concentrations of PM2.5 and BC in 199 samples from 136 classrooms (30 school buildings) were compared to those measured at a central monitoring site averaged over the same timeframe. Mixed effects regression models found significant random intercept and slope effects, which indicate that: 1) there are important PM2.5 sources in classrooms; 2) the penetration of outdoor PM2.5 particles varies by school, and 3) the site-specific outside PM2.5 levels (inferred by the models) differ from those observed at the central monitor site. Similar results were found for BC except for lack of indoor sources. The fitted predictions from the sulfur-adjusted models were moderately predictive of observed indoor pollutant levels (Out of sample correlations: PM2.5: r2 = 0.68, BC; r2 = 0.61). Our results suggest that PM2.5 has important classroom sources, which vary by school. Furthermore, using these mixed effects models, classroom exposures can be accurately predicted for dates when central site measures are available but indoor measures are not available. PMID:27599884

Did Irving Langmuir Observe Langmuir Circulations?

NASA Astrophysics Data System (ADS)

D'Asaro, E. A.; Harcourt, R. R.; Shcherbina, A.; Thomson, J. M.; Fox-Kemper, B.

2012-12-01

Although surface waves are known to play an important role in mixing the upper ocean, the current generation of upper ocean boundary layer parameterizations does not include the explicit effects of surface waves. Detailed simulations using LES models which include the Craik-Leibovich wave-current interactions, now provide quantitative predictions of the enhancement of boundary layer mixing by waves. Here, using parallel experiments in Lake Washington and at Ocean Station Papa, we show a clear enhancement of vertical kinetic energy across the entire upper ocean boundary layer which can be attributed to surface wave effects. The magnitude of this effect is close to that predicted by LES models, but is not large, less than a factor of 2 on average, and increased by large Stokes drift and shallow mixed layers. Global estimates show the largest wave enhancements occur on the equatorial side of the westerlies in late Spring, due to the combination of large waves, shallow mixed layers and weak winds. In Lakes, however, the waves and the Craik-Leibovich interactions are weak, making it likely that the counter-rotating vortices famously observed by Irving Langmuir in Lake George were not driven by wave-current interactions.

The modelling of dispersion in 2-D tidal flow over an uneven bed

NASA Astrophysics Data System (ADS)

Kalkwijk, Jan P. Th.

This paper deals with the effective mixing by topographic induced velocity variations in 2-D tidal flow. This type of mixing is characterized by tidally-averaged dispersion coefficients, which depend on the magnitude of the depth variations with respect to a mean depth, the velocity variations and the basic dispersion coefficients. The analysis is principally based on a Taylor type approximation (large clouds, small concentration variations) of the 2-D advection diffusion equation and a 2-D velocity field that behaves harmonically both in time and in space. Neglecting transient phenomena and applying time and space averaging the effective dispersion coefficients can be derived. Under certain circumstances it is possible to relate the velocity variations to the depth variations, so that finally effective dispersion coefficients can be determined using the power spectrum of the depth variations. In a special paragraph attention is paid to the modelling of sub-grid mixing in case of numerical integration of the advection-diffusion equation. It appears that the dispersion coefficients taking account of the sub-grid mixing are not only determined by the velocity variations within a certain grid cell, but also by the velocity variations at a larger scale.

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

Further improvements of a new model for turbulent convection in stars

NASA Technical Reports Server (NTRS)

Canuto, V. M.; Mazzitelli, I.

1992-01-01

The effects of including a variable molecular weight and of using the newest opacities of Rogers and Iglesias (1991) as inputs to a recent model by Canuto and Mazzitelli (1991) for stellar turbulent convection are studied. Solar evolutionary tracks are used to conclude that the the original model for turbulence with mixing length Lambda = z, Giuli's variable Q unequal to 1 and the new opacities yields a fit to solar T(eff) within 0.5 percent. A formulation of Lambda is proposed that extends the purely nonlocal Lambda = z expression to include local effects. A new expression for Lambda is obtained which generalizes both the mixing length theory (MLT) phenomenological expression for Lambda as well as the model Lambda = z. It is argued that the MLT should now be abandoned.

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

PubMed

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

2011-09-10

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

Mixing {Xi}--{Xi}' Effects and Static Properties of Heavy {Xi}'s

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

Aliev, T. M.; Ozpineci, A.; Zamiralov, V. S.

It is shown the importance of mixing of heavy baryons {Xi}--{Xi}' with the new quantum numbers for analysis of its characteristics. The quark model of Ono is used as an example. Masses of new baryons as well as mixing angles of the states {Xi}--{Xi}' are obtained. The same reasoning is shown to be valid for the interpolating currents of these baryons in the framework of the QCD sum rules.

The application of mixed recommendation algorithm with user clustering in the microblog advertisements promotion

NASA Astrophysics Data System (ADS)

Gong, Lina; Xu, Tao; Zhang, Wei; Li, Xuhong; Wang, Xia; Pan, Wenwen

2017-03-01

The traditional microblog recommendation algorithm has the problems of low efficiency and modest effect in the era of big data. In the aim of solving these issues, this paper proposed a mixed recommendation algorithm with user clustering. This paper first introduced the situation of microblog marketing industry. Then, this paper elaborates the user interest modeling process and detailed advertisement recommendation methods. Finally, this paper compared the mixed recommendation algorithm with the traditional classification algorithm and mixed recommendation algorithm without user clustering. The results show that the mixed recommendation algorithm with user clustering has good accuracy and recall rate in the microblog advertisements promotion.

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

PubMed

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.

Modeling of surface temperature effects on mixed material migration in NSTX-U

NASA Astrophysics Data System (ADS)

Nichols, J. H.; Jaworski, M. A.; Schmid, K.

2016-10-01

NSTX-U will initially operate with graphite walls, periodically coated with thin lithium films to improve plasma performance. However, the spatial and temporal evolution of these films during and after plasma exposure is poorly understood. The WallDYN global mixed-material surface evolution model has recently been applied to the NSTX-U geometry to simulate the evolution of poloidally inhomogenous mixed C/Li/O plasma-facing surfaces. The WallDYN model couples local erosion and deposition processes with plasma impurity transport in a non-iterative, self-consistent manner that maintains overall material balance. Temperature-dependent sputtering of lithium has been added to WallDYN, utilizing an adatom sputtering model developed from test stand experimental data. Additionally, a simplified temperature-dependent diffusion model has been added to WallDYN so as to capture the intercalation of lithium into a graphite bulk matrix. The sensitivity of global lithium migration patterns to changes in surface temperature magnitude and distribution will be examined. The effect of intra-discharge increases in surface temperature due to plasma heating, such as those observed during NSTX Liquid Lithium Divertor experiments, will also be examined. Work supported by US DOE contract DE-AC02-09CH11466.

Preliminary Empirical Model of Crucial Determinants of Best Practice for Peer Tutoring on Academic Achievement

ERIC Educational Resources Information Center

Leung, Kim Chau

2015-01-01

Previous meta-analyses of the effects of peer tutoring on academic achievement have been plagued with theoretical and methodological flaws. Specifically, these studies have not adopted both fixed and mixed effects models for analyzing the effect size; they have not evaluated the moderating effect of some commonly used parameters, such as comparing…

Impact of wave mixing on the sea ice cover

NASA Astrophysics Data System (ADS)

Rynders, Stefanie; Aksenov, Yevgeny; Madec, Gurvan; Nurser, George; Feltham, Daniel

2017-04-01

As information on surface waves in ice-covered regions becomes available in ice-ocean models, there is an opportunity to model wave-related processes more accurate. Breaking waves cause mixing of the upper water column and present mixing schemes in ocean models take this into account through surface roughness. A commonly used approach is to calculate surface roughness from significant wave height, parameterised from wind speed. We present results from simulations using modelled significant wave height instead, which accounts for the presence of sea ice and the effect of swell. The simulations use the NEMO ocean model coupled to the CICE sea ice model, with wave information from the ECWAM model of the European Centre for Medium-Range Weather Forecasts (ECMWF). The new waves-in-ice module allows waves to propagate in sea ice and attenuates waves according to multiple scattering and non-elastic losses. It is found that in the simulations with wave mixing the mixed layer depth (MLD) under ice cover is reduced, since the parameterisation from wind speed overestimates wave height in the ice-covered regions. The MLD change, in turn, affects sea ice concentration and ice thickness. In the Arctic, reduced MLD in winter translates into increased ice thicknesses overall, with higher increases in the Western Arctic and decreases along the Siberian coast. In summer, shallowing of the mixed layer results in more heat accumulating in the surface ocean, increasing ice melting. In the Southern Ocean the meridional gradient in ice thickness and concentration is increased. We argue that coupling waves with sea ice - ocean models can reduce negative biases in sea ice cover, affecting the distribution of nutrients and, thus, biological productivity and ecosystems. This coupling will become more important in the future, when wave heights in a large part of the Arctic are expected to increase due to sea ice retreat and a larger wave fetch. Therefore, wave mixing constitutes a possible positive feedback mechanism.

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

PubMed

Ma, Qiuyun; Jiao, Yan; Ren, Yiping

2017-01-01

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

Rain Impact Model Assessment of Near-Surface Salinity Stratification Following Rainfall

NASA Astrophysics Data System (ADS)

Drushka, K.; Jones, L.; Jacob, M. M.; Asher, W.; Santos-Garcia, A.

2016-12-01

Rainfall over oceans produces a layer of fresher surface water, which can have a significant effect on the exchanges between the surface and the bulk mixed layer and also on satellite/in-situ comparisons. For satellite sea surface salinity (SSS) measurements, the standard is the Hybrid Coordinate Ocean Model (HYCOM), but there is a significant difference between the remote sensing sampling depth of 0.01 m and the typical range of 5-10 m of in-situ instruments. Under normal conditions the upper layer of the ocean is well mixed and there is uniform salinity; however, under rainy conditions, there is a dilution of the near-surface salinity that mixes downward by diffusion and by mechanical mixing (gravity waves/wind speed). This significantly modifies the salinity gradient in the upper 1-2 m of the ocean, but these transient salinity stratifications dissipate in a few hours, and the upper layer becomes well mixed at a slightly fresher salinity. Based upon research conducted within the NASA/CONAE Aquarius/SAC-D mission, a rain impact model (RIM) was developed to estimate the change in SSS due to rainfall near the time of the satellite observation, with the objective to identify the probability of salinity stratification. RIM uses HYCOM (which does not include the short-term rain effects) and a NOAA global rainfall product CMORPH to model changes in the near-surface salinity profile in 0.5 h increments. Based upon SPURS-2 experimental near-surface salinity measurements with rain, this paper introduces a term in the RIM model that accounts for the effect of wind speed in the mechanical mixing, which translates into a dynamic vertical diffusivity; whereby a Generalized Ocean Turbulence Model (GOTM) is used to investigate the response to rain events of the upper few meters of the ocean. The objective is to determine how rain and wind forcing control the thickness, stratification strength, and lifetime of fresh lenses and to quantify the impacts of rain-formed fresh lenses on the fresh bias in satellite retrievals of salinity. Results will be presented of comparisons of RIM measurements at depth of a few meters with measurements from in-situ salinity instruments. Also, analytical results will be shown, which assess the accuracy of RIM salinity profiles under a variety of rain rate, wind/wave conditions.

Growth rate characteristics of acidophilic heterotrophic organisms from mine waste rock piles

NASA Astrophysics Data System (ADS)

Yacob, T. W.; Silverstein, J.; Jenkins, J.; Andre, B. J.; Rajaram, H.

2010-12-01

Autotrophic iron oxidizing bacteria play a key role in pyrite oxidation and generation of acid mine drainage AMD. Scarcity of organic substrates in many disturbed sites insures that IOB have sufficient oxygen and other nutrients for growth. It is proposed that addition of organic carbon substrate to waste rock piles will result in enrichment of heterotrophic microorganisms limiting the role of IOB in AMD generation. Previous researchers have used the acidophilic heterotroph Acidiphilium cryptum as a model to study the effects of organic substrate addition on the pyrite oxidation/AMD cycle. In order to develop a quantitative model of effects such as competition for oxygen, it is necessary to use growth and substrate consumption rate expressions, and one approach is to choose a model strain such as A. cryptum for kinetic studies. However we have found that the growth rate characteristics of A. cryptum may not provide an accurate model of the remediation effects of organic addition to subsurface mined sites. Fluorescent in-situ hybridization (FISH) assays of extracts of mine waste rock enriched with glucose and yeast extract did not produce countable numbers of cells in the Acidiphilium genus, with a detection limit of3 x 104 cells/gram rock, despite evidence of the presence of well established heterotrophic organisms. However, an MPN enrichment produced heterotrophic population estimates of 1x107 and 1x109 cells/gram rock. Growth rate studies of A. cryptum showed that cultures took 120 hours to degrade 50% of an initial glucose concentration of 2,000 mg/L. However a mixed culture enriched from mine waste rock consumed 100% of the same amount of glucose in 24 hours. Substrate consumption data for the mixed culture were fit to a Monod growth model: {dS}/{dt} = μ_{max}S {( {X_0}/{Y} + S_0 -S )}/{(K_s +S)} Kinetic parameters were estimated utilizing a non linear regression method coupled with an ODE solver. The maximum specific growth rate of the mixed population with μ max was calculated to be 0.13 hr-1 and a yield of 0.52 g cells/g glucose and Ks of 0.2 g/L glucose. The effect of pH on growth was compared for A. cryptum and the mixed population. It was found that the mixed culture had a higher tolerance for extremely low pH conditions, with no growth at pH = 1; whereas no growth of A cryptum was observed at pH = 1.5. Both A. cryptum and the mixed cultures grew within a pH range of 2.5 - 6. A phospholipid fatty acid analysis (PLFA) of the mixed culture indicated that both eukaryotic and prokaryotic organisms are present at a ratio of approximately 1:1, indicating that organisms such as fungi may be important in carbon cycling in these acidic subsurface formations. The results from this research show that utilization of mixed wild cultures for environmental modeling may yield better results than selection of a single strain to represent populations in a quantitative model.

Experimental study of stratified jet by simultaneous measurements of velocity and density fields

NASA Astrophysics Data System (ADS)

Xu, Duo; Chen, Jun

2012-07-01

Stratified flows with small density difference commonly exist in geophysical and engineering applications, which often involve interaction of turbulence and buoyancy effect. A combined particle image velocimetry (PIV) and planar laser-induced fluorescence (PLIF) system is developed to measure the velocity and density fields in a dense jet discharged horizontally into a tank filled with light fluid. The illumination of PIV particles and excitation of PLIF dye are achieved by a dual-head pulsed Nd:YAG laser and two CCD cameras with a set of optical filters. The procedure for matching refractive indexes of two fluids and calibration of the combined system are presented, as well as a quantitative analysis of the measurement uncertainties. The flow structures and mixing dynamics within the central vertical plane are studied by examining the averaged parameters, turbulent kinetic energy budget, and modeling of momentum flux and buoyancy flux. At downstream, profiles of velocity and density display strong asymmetry with respect to its center. This is attributed to the fact that stable stratification reduces mixing and unstable stratification enhances mixing. In stable stratification region, most of turbulence production is consumed by mean-flow convection, whereas in unstable stratification region, turbulence production is nearly balanced by viscous dissipation. Experimental data also indicate that at downstream locations, mixing length model performs better in mixing zone of stable stratification regions, whereas in other regions, eddy viscosity/diffusivity models with static model coefficients represent effectively momentum and buoyancy flux terms. The measured turbulent Prandtl number displays strong spatial variation in the stratified jet.

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

PubMed Central

Lindsay, Grace W.

2017-01-01

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

A Multilevel Bifactor Approach to Construct Validation of Mixed-Format Scales

ERIC Educational Resources Information Center

Wang, Yan; Kim, Eun Sook; Dedrick, Robert F.; Ferron, John M.; Tan, Tony

2018-01-01

Wording effects associated with positively and negatively worded items have been found in many scales. Such effects may threaten construct validity and introduce systematic bias in the interpretation of results. A variety of models have been applied to address wording effects, such as the correlated uniqueness model and the correlated traits and…

Modeling forest fire occurrences using count-data mixed models in Qiannan autonomous prefecture of Guizhou province in China.

PubMed

Xiao, Yundan; Zhang, Xiongqing; Ji, Ping

2015-01-01

Forest fires can cause catastrophic damage on natural resources. In the meantime, it can also bring serious economic and social impacts. Meteorological factors play a critical role in establishing conditions favorable for a forest fire. Effective prediction of forest fire occurrences could prevent or minimize losses. This paper uses count data models to analyze fire occurrence data which is likely to be dispersed and frequently contain an excess of zero counts (no fire occurrence). Such data have commonly been analyzed using count data models such as a Poisson model, negative binomial model (NB), zero-inflated models, and hurdle models. Data we used in this paper is collected from Qiannan autonomous prefecture of Guizhou province in China. Using the fire occurrence data from January to April (spring fire season) for the years 1996 through 2007, we introduced random effects to the count data models. In this study, the results indicated that the prediction achieved through NB model provided a more compelling and credible inferential basis for fitting actual forest fire occurrence, and mixed-effects model performed better than corresponding fixed-effects model in forest fire forecasting. Besides, among all meteorological factors, we found that relative humidity and wind speed is highly correlated with fire occurrence.

Modeling Forest Fire Occurrences Using Count-Data Mixed Models in Qiannan Autonomous Prefecture of Guizhou Province in China

PubMed Central

Ji, Ping

2015-01-01

Forest fires can cause catastrophic damage on natural resources. In the meantime, it can also bring serious economic and social impacts. Meteorological factors play a critical role in establishing conditions favorable for a forest fire. Effective prediction of forest fire occurrences could prevent or minimize losses. This paper uses count data models to analyze fire occurrence data which is likely to be dispersed and frequently contain an excess of zero counts (no fire occurrence). Such data have commonly been analyzed using count data models such as a Poisson model, negative binomial model (NB), zero-inflated models, and hurdle models. Data we used in this paper is collected from Qiannan autonomous prefecture of Guizhou province in China. Using the fire occurrence data from January to April (spring fire season) for the years 1996 through 2007, we introduced random effects to the count data models. In this study, the results indicated that the prediction achieved through NB model provided a more compelling and credible inferential basis for fitting actual forest fire occurrence, and mixed-effects model performed better than corresponding fixed-effects model in forest fire forecasting. Besides, among all meteorological factors, we found that relative humidity and wind speed is highly correlated with fire occurrence. PMID:25790309

Trial type mixing substantially reduces the response set effect in the Stroop task.

PubMed

Hasshim, Nabil; Parris, Benjamin A

2017-03-20

The response set effect refers to the finding that an irrelevant incongruent colour-word produces greater interference when it is one of the response options (referred to as a response set trial), compared to when it is not (a non-response set trial). Despite being a key effect for models of selective attention, the magnitude of the effect varies considerably across studies. We report two within-subjects experiments that tested the hypothesis that presentation format modulates the magnitude of the response set effect. Trial types (e.g. response set, non-response set, neutral) were either presented in separate blocks (pure) or in blocks containing trials from all conditions presented randomly (mixed). In the first experiment we show that the response set effect is substantially reduced in the mixed block context as a result of a decrease in RTs to response set trials. By demonstrating the modulation of the response set effect under conditions of trial type mixing we present evidence that is difficult for models of the effect based on strategic, top-down biasing of attention to explain. In a second experiment we tested a stimulus-driven account of the response set effect by manipulating the number of colour-words that make up the non-response set of distractors. The results show that the greater the number of non-response set colour concepts, the smaller the response set effect. Alternative accounts of the data and its implications for research debating the automaticity of reading are discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Mixed reality temporal bone surgical dissector: mechanical design

PubMed Central

2014-01-01

Objective The Development of a Novel Mixed Reality (MR) Simulation. An evolving training environment emphasizes the importance of simulation. Current haptic temporal bone simulators have difficulty representing realistic contact forces and while 3D printed models convincingly represent vibrational properties of bone, they cannot reproduce soft tissue. This paper introduces a mixed reality model, where the effective elements of both simulations are combined; haptic rendering of soft tissue directly interacts with a printed bone model. This paper addresses one aspect in a series of challenges, specifically the mechanical merger of a haptic device with an otic drill. This further necessitates gravity cancelation of the work assembly gripper mechanism. In this system, the haptic end-effector is replaced by a high-speed drill and the virtual contact forces need to be repositioned to the drill tip from the mid wand. Previous publications detail generation of both the requisite printed and haptic simulations. Method Custom software was developed to reposition the haptic interaction point to the drill tip. A custom fitting, to hold the otic drill, was developed and its weight was offset using the haptic device. The robustness of the system to disturbances and its stable performance during drilling were tested. The experiments were performed on a mixed reality model consisting of two drillable rapid-prototyped layers separated by a free-space. Within the free-space, a linear virtual force model is applied to simulate drill contact with soft tissue. Results Testing illustrated the effectiveness of gravity cancellation. Additionally, the system exhibited excellent performance given random inputs and during the drill’s passage between real and virtual components of the model. No issues with registration at model boundaries were encountered. Conclusion These tests provide a proof of concept for the initial stages in the development of a novel mixed-reality temporal bone simulator. PMID:25927300

An efficient use of mixing model for computing the effective dielectric and thermal properties of the human head.

PubMed

Mishra, Varsha; Puthucheri, Smitha; Singh, Dharmendra

2018-05-07

As a preventive measure against the electromagnetic (EM) wave exposure to human body, EM radiation regulatory authorities such as ICNIRP and FCC defined the value of specific absorption rate (SAR) for the human head during EM wave exposure from mobile phone. SAR quantifies the absorption of EM waves in the human body and it mainly depends on the dielectric properties (ε', σ) of the corresponding tissues. The head part of the human body is more susceptible to EM wave exposure due to the usage of mobile phones. The human head is a complex structure made up of multiple tissues with intermixing of many layers; thus, the accurate measurement of permittivity (ε') and conductivity (σ) of the tissues of the human head is still a challenge. For computing the SAR, researchers are using multilayer model, which has some challenges for defining the boundary for layers. Therefore, in this paper, an attempt has been made to propose a method to compute effective complex permittivity of the human head in the range of 0.3 to 3.0 GHz by applying De-Loor mixing model. Similarly, for defining the thermal effect in the tissue, thermal properties of the human head have also been computed using the De-Loor mixing method. The effective dielectric and thermal properties of equivalent human head model are compared with the IEEE Std. 1528. Graphical abstract ᅟ.

External Validation of a Case-Mix Adjustment Model for the Standardized Reporting of 30-Day Stroke Mortality Rates in China

PubMed Central

Yu, Ping; Pan, Yuesong; Wang, Yongjun; Wang, Xianwei; Liu, Liping; Ji, Ruijun; Meng, Xia; Jing, Jing; Tong, Xu; Guo, Li; Wang, Yilong

2016-01-01

Background and Purpose A case-mix adjustment model has been developed and externally validated, demonstrating promise. However, the model has not been thoroughly tested among populations in China. In our study, we evaluated the performance of the model in Chinese patients with acute stroke. Methods The case-mix adjustment model A includes items on age, presence of atrial fibrillation on admission, National Institutes of Health Stroke Severity Scale (NIHSS) score on admission, and stroke type. Model B is similar to Model A but includes only the consciousness component of the NIHSS score. Both model A and B were evaluated to predict 30-day mortality rates in 13,948 patients with acute stroke from the China National Stroke Registry. The discrimination of the models was quantified by c-statistic. Calibration was assessed using Pearson’s correlation coefficient. Results The c-statistic of model A in our external validation cohort was 0.80 (95% confidence interval, 0.79–0.82), and the c-statistic of model B was 0.82 (95% confidence interval, 0.81–0.84). Excellent calibration was reported in the two models with Pearson’s correlation coefficient (0.892 for model A, p<0.001; 0.927 for model B, p = 0.008). Conclusions The case-mix adjustment model could be used to effectively predict 30-day mortality rates in Chinese patients with acute stroke. PMID:27846282

Cloud-Resolving Model Simulations of Aerosol-Cloud Interactions Triggered by Strong Aerosol Emissions in the Arctic

NASA Astrophysics Data System (ADS)

Wang, H.; Kravitz, B.; Rasch, P. J.; Morrison, H.; Solomon, A.

2014-12-01

Previous process-oriented modeling studies have highlighted the dependence of effectiveness of cloud brightening by aerosols on cloud regimes in warm marine boundary layer. Cloud microphysical processes in clouds that contain ice, and hence the mechanisms that drive aerosol-cloud interactions, are more complicated than in warm clouds. Interactions between ice particles and liquid drops add additional levels of complexity to aerosol effects. A cloud-resolving model is used to study aerosol-cloud interactions in the Arctic triggered by strong aerosol emissions, through either geoengineering injection or concentrated sources such as shipping and fires. An updated cloud microphysical scheme with prognostic aerosol and cloud particle numbers is employed. Model simulations are performed in pure super-cooled liquid and mixed-phase clouds, separately, with or without an injection of aerosols into either a clean or a more polluted Arctic boundary layer. Vertical mixing and cloud scavenging of particles injected from the surface is still quite efficient in the less turbulent cold environment. Overall, the injection of aerosols into the Arctic boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. The pure liquid clouds are more susceptible to the increase in aerosol number concentration than the mixed-phase clouds. Rain production processes are more effectively suppressed by aerosol injection, whereas ice precipitation (snow) is affected less; thus the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. Aerosol injection into a clean boundary layer results in a greater cloud albedo increase than injection into a polluted one, consistent with current knowledge about aerosol-cloud interactions. Unlike previous studies investigating warm clouds, the impact of dynamical feedback due to precipitation changes is small. According to these results, which are dependent upon the representation of ice nucleation processes in the employed microphysical scheme, Arctic geoengineering/shipping could have substantial local radiative effects, but is unlikely to be effective as the sole means of counterbalancing warming due to climate change.

Qualitative and numerical analyses of the effects of river inflow variations on mixing diagrams in estuaries

USGS Publications Warehouse

Cifuentes, L.A.; Schemel, L.E.; Sharp, J.H.

1990-01-01

The effects of river inflow variations on alkalinity/salinity distributions in San Francisco Bay and nitrate/salinity distributions in Delaware Bay are described. One-dimensional, advective-dispersion equations for salinity and the dissolved constituents are solved numerically and are used to simulate mixing in the estuaries. These simulations account for time-varying river inflow, variations in estuarine cross-sectional area, and longitudinally varying dispersion coefficients. The model simulates field observations better than models that use constant hydrodynamic coefficients and uniform estuarine geometry. Furthermore, field observations and model simulations are consistent with theoretical 'predictions' that the curvature of propery-salinity distributions depends on the relation between the estuarine residence time and the period of river concentration variation. ?? 1990.

Effect of initial conditions on constant pressure mixing between two turbulent streams

NASA Astrophysics Data System (ADS)

Kangovi, S.

1983-02-01

It is pointed out that a study of the process of mixing between two dissimilar streams has varied applications in different fields. The applications include the design of an after burner in a high by-pass ratio aircraft engine and the disposal of effluents in a stream. The mixing process determines important quantities related to the energy transfer from main stream to the secondary stream, the temperature and velocity profiles, and the local kinematic and dissipative structure within the mixing region, and the growth of the mixing layer. Hill and Page (1968) have proposed the employment of an 'assumed epsilon' method in which the eddy viscosity model of Goertler (1942) is modified to account for the initial boundary layer. The present investigation is concerned with the application of the assumed epsilon technique to the study of the effect of initial conditions on the development of the turbulent mixing layer between two compressible, nonisoenergetic streams at constant pressure.

Sizable NSI from the SU(2) L scalar doublet-singlet mixing and the implications in DUNE

DOE PAGES

Forero, David V.; Huang, Wei -Chih

2017-03-03

Here, we propose a novel and simple mechanism where sizable effects of non-standard interactions (NSI) in neutrino propagation are induced from the mixing between an electrophilic second Higgs doublet and a charged singlet. The mixing arises from a dimensionful coupling of the scalar doublet and singlet to the standard model Higgs boson. In light of the small mass, the light mass eigenstate from the doublet-singlet mixing can generate much larger NSI than those induced by the heavy eigenstate. We show that a sizable NSI ε eτ (~0.3) can be attained without being excluded by a variety of experimental constraints. Furthermore,more » we demonstrate that NSI can mimic effects of the Dirac CP phase in the neutrino mixing matrix but they can potentially be disentangled by future long-baseline neutrino experiments, such as the Deep Underground Neutrino Experiment (DUNE).« less

Sizable NSI from the SU(2) L scalar doublet-singlet mixing and the implications in DUNE

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

Forero, David V.; Huang, Wei -Chih

Here, we propose a novel and simple mechanism where sizable effects of non-standard interactions (NSI) in neutrino propagation are induced from the mixing between an electrophilic second Higgs doublet and a charged singlet. The mixing arises from a dimensionful coupling of the scalar doublet and singlet to the standard model Higgs boson. In light of the small mass, the light mass eigenstate from the doublet-singlet mixing can generate much larger NSI than those induced by the heavy eigenstate. We show that a sizable NSI ε eτ (~0.3) can be attained without being excluded by a variety of experimental constraints. Furthermore,more » we demonstrate that NSI can mimic effects of the Dirac CP phase in the neutrino mixing matrix but they can potentially be disentangled by future long-baseline neutrino experiments, such as the Deep Underground Neutrino Experiment (DUNE).« less

MixSIAR: advanced stable isotope mixing models in R

EPA Science Inventory

Background/Question/Methods The development of stable isotope mixing models has coincided with modeling products (e.g. IsoSource, MixSIR, SIAR), where methodological advances are published in parity with software packages. However, while mixing model theory has recently been ex...

Determining the impact of cell mixing on signaling during development.

PubMed

Uriu, Koichiro; Morelli, Luis G

2017-06-01

Cell movement and intercellular signaling occur simultaneously to organize morphogenesis during embryonic development. Cell movement can cause relative positional changes between neighboring cells. When intercellular signals are local such cell mixing may affect signaling, changing the flow of information in developing tissues. Little is known about the effect of cell mixing on intercellular signaling in collective cellular behaviors and methods to quantify its impact are lacking. Here we discuss how to determine the impact of cell mixing on cell signaling drawing an example from vertebrate embryogenesis: the segmentation clock, a collective rhythm of interacting genetic oscillators. We argue that comparing cell mixing and signaling timescales is key to determining the influence of mixing. A signaling timescale can be estimated by combining theoretical models with cell signaling perturbation experiments. A mixing timescale can be obtained by analysis of cell trajectories from live imaging. After comparing cell movement analyses in different experimental settings, we highlight challenges in quantifying cell mixing from embryonic timelapse experiments, especially a reference frame problem due to embryonic motions and shape changes. We propose statistical observables characterizing cell mixing that do not depend on the choice of reference frames. Finally, we consider situations in which both cell mixing and signaling involve multiple timescales, precluding a direct comparison between single characteristic timescales. In such situations, physical models based on observables of cell mixing and signaling can simulate the flow of information in tissues and reveal the impact of observed cell mixing on signaling. © 2017 Japanese Society of Developmental Biologists.

Conditions for super-adiabatic droplet growth after entrainment mixing

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

Yang, Fan; Shaw, Raymond; Xue, Huiwen

Cloud droplet response to entrainment and mixing between a cloud and its environment is considered, accounting for subsequent droplet growth during adiabatic ascent following a mixing event. The vertical profile for liquid water mixing ratio after a mixing event is derived analytically, allowing the reduction to be predicted from the mixing fraction and from the temperature and humidity for both the cloud and environment. It is derived for the limit of homogeneous mixing. The expression leads to a critical height above the mixing level: at the critical height the cloud droplet radius is the same for both mixed and unmixedmore » parcels, and the critical height is independent of the updraft velocity and mixing fraction. Cloud droplets in a mixed parcel are larger than in an unmixed parcel above the critical height, which we refer to as the “super-adiabatic” growth region. Analytical results are confirmed with a bin microphysics cloud model. Using the model, we explore the effects of updraft velocity, aerosol source in the environmental air, and polydisperse cloud droplets. Results show that the mixed parcel is more likely to reach the super-adiabatic growth region when the environmental air is humid and clean. It is also confirmed that the analytical predictions are matched by the volume-mean cloud droplet radius for polydisperse size distributions. Lastly, these findings have implications for the origin of large cloud droplets that may contribute to onset of collision–coalescence in warm clouds.« less

Conditions for super-adiabatic droplet growth after entrainment mixing

DOE PAGES

Yang, Fan; Shaw, Raymond; Xue, Huiwen

2016-07-29

Cloud droplet response to entrainment and mixing between a cloud and its environment is considered, accounting for subsequent droplet growth during adiabatic ascent following a mixing event. The vertical profile for liquid water mixing ratio after a mixing event is derived analytically, allowing the reduction to be predicted from the mixing fraction and from the temperature and humidity for both the cloud and environment. It is derived for the limit of homogeneous mixing. The expression leads to a critical height above the mixing level: at the critical height the cloud droplet radius is the same for both mixed and unmixedmore » parcels, and the critical height is independent of the updraft velocity and mixing fraction. Cloud droplets in a mixed parcel are larger than in an unmixed parcel above the critical height, which we refer to as the “super-adiabatic” growth region. Analytical results are confirmed with a bin microphysics cloud model. Using the model, we explore the effects of updraft velocity, aerosol source in the environmental air, and polydisperse cloud droplets. Results show that the mixed parcel is more likely to reach the super-adiabatic growth region when the environmental air is humid and clean. It is also confirmed that the analytical predictions are matched by the volume-mean cloud droplet radius for polydisperse size distributions. Lastly, these findings have implications for the origin of large cloud droplets that may contribute to onset of collision–coalescence in warm clouds.« less

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

PubMed

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.

Stochastic models to study the impact of mixing on a fed-batch culture of Saccharomyces cerevisiae.

PubMed

Delvigne, F; Lejeune, A; Destain, J; Thonart, P

2006-01-01

The mechanisms of interaction between microorganisms and their environment in a stirred bioreactor can be modeled by a stochastic approach. The procedure comprises two submodels: a classical stochastic model for the microbial cell circulation and a Markov chain model for the concentration gradient calculus. The advantage lies in the fact that the core of each submodel, i.e., the transition matrix (which contains the probabilities to shift from a perfectly mixed compartment to another in the bioreactor representation), is identical for the two cases. That means that both the particle circulation and fluid mixing process can be analyzed by use of the same modeling basis. This assumption has been validated by performing inert tracer (NaCl) and stained yeast cells dispersion experiments that have shown good agreement with simulation results. The stochastic model has been used to define a characteristic concentration profile experienced by the microorganisms during a fermentation test performed in a scale-down reactor. The concentration profiles obtained in this way can explain the scale-down effect in the case of a Saccharomyces cerevisiae fed-batch process. The simulation results are analyzed in order to give some explanations about the effect of the substrate fluctuation dynamics on S. cerevisiae.

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

DOE PAGES

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

2017-02-04

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

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

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

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

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

Testing Extensions of Our Quantitative Daily of San Joaquin Wintertime Aerosols Using MAIAC and Meteorology Without Transport/Transformation Assumptions

NASA Technical Reports Server (NTRS)

Chatfield, Robert B.; Sorek Hamer, Meytar; Esswein, Robert F.

2017-01-01

The Western US and many regions globally present daunting difficulties in understanding and mapping PM2.5 episodes. We evaluate extensions of a method independent of source-description and transport/transformation. These regions suffer frequent few-day episodes due to shallow mixing; low satellite AOT and bright surfaces complicate the description. Nevertheless, we expect residual errors in our maps of less than 8 ug/m^3 in episodes reaching 60-100 ug/m^3; maps which detail pollution from Interstate 5. Our current success is due to use of physically meaningful functions of MODIS-MAIAC-derived AOD, afternoon mixed-layer height, and relative humidity for a basin in which the latter are correlated. A mixed-effects model then describes a daily AOT-to-PM2.5 relationship. (Note: in other published mixed-effects models, AOT contributes minimally. We seek to extend on these to develop useful estimation methods for similar situations. We evaluate existing but more spotty information on size distribution (AERONET, MISR, MAIA, CALIPSO, other remote sensing). We also describe the usefulness of an equivalent mixing depth for water vapor vs meteorological boundary layer height. Each has virtues and limitations. Finally, we begin to evaluate methods for removing the complications due to detached but polluted layers (which don't mix to the surface) using geographical, meteorological, and remotely sensed data.

Linear Mixed Models: Gum and Beyond

NASA Astrophysics Data System (ADS)

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

2014-04-01

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

Effect of gravity waves on the North Atlantic circulation

NASA Astrophysics Data System (ADS)

Eden, Carsten

2017-04-01

The recently proposed IDEMIX (Internal wave Dissipation, Energy and MIXing) parameterisation for the effect of gravity waves offers the possibility to construct consistent ocean models with a closed energy cycle. This means that the energy available for interior mixing in the ocean is only controlled by external energy input from the atmosphere and the tidal system and by internal exchanges. A central difficulty is the unknown fate of meso-scale eddy energy. In different scenarios for that eddy dissipation, the parameterized internal wave field provides between 2 and 3 TW for interior mixing from the total external energy input of about 4 TW, such that a transfer between 0.3 and 0.4 TW into mean potential energy contributes to drive the large-scale circulation in the model. The impact of the different mixing on the meridional overturning in the North Atlantic is discussed and compared to hydrographic observations. Furthermore, the direct energy exchange of the wave field with the geostrophic flow is parameterized in extended IDEMIX versions and the sensitivity of the North Atlantic circulation by this gravity wave drag is discussed.

A mixed methods approach to assess animal vaccination programmes: The case of rabies control in Bamako, Mali.

PubMed

Mosimann, Laura; Traoré, Abdallah; Mauti, Stephanie; Léchenne, Monique; Obrist, Brigit; Véron, René; Hattendorf, Jan; Zinsstag, Jakob

2017-01-01

In the framework of the research network on integrated control of zoonoses in Africa (ICONZ) a dog rabies mass vaccination campaign was carried out in two communes of Bamako (Mali) in September 2014. A mixed method approach, combining quantitative and qualitative tools, was developed to evaluate the effectiveness of the intervention towards optimization for future scale-up. Actions to control rabies occur on one level in households when individuals take the decision to vaccinate their dogs. However, control also depends on provision of vaccination services and community participation at the intermediate level of social resilience. Mixed methods seem necessary as the problem-driven transdisciplinary project includes epidemiological components in addition to social dynamics and cultural, political and institutional issues. Adapting earlier effectiveness models for health intervention to rabies control, we propose a mixed method assessment of individual effectiveness parameters like availability, affordability, accessibility, adequacy or acceptability. Triangulation of quantitative methods (household survey, empirical coverage estimation and spatial analysis) with qualitative findings (participant observation, focus group discussions) facilitate a better understanding of the weight of each effectiveness determinant, and the underlying reasons embedded in the local understandings, cultural practices, and social and political realities of the setting. Using this method, a final effectiveness of 33% for commune Five and 28% for commune Six was estimated, with vaccination coverage of 27% and 20%, respectively. Availability was identified as the most sensitive effectiveness parameter, attributed to lack of information about the campaign. We propose a mixed methods approach to optimize intervention design, using an "intervention effectiveness optimization cycle" with the aim of maximizing effectiveness. Empirical vaccination coverage estimation is compared to the effectiveness model with its determinants. In addition, qualitative data provide an explanatory framework for deeper insight, validation and interpretation of results which should improve the intervention design while involving all stakeholders and increasing community participation. This work contributes vital information for the optimization and scale-up of future vaccination campaigns in Bamako, Mali. The proposed mixed method, although incompletely applied in this case study, should be applicable to similar rabies interventions targeting elimination in other settings. Copyright © 2016 Elsevier B.V. All rights reserved.

The Parallel Episodic Processing (PEP) model 2.0: A single computational model of stimulus-response binding, contingency learning, power curves, and mixing costs.

PubMed

Schmidt, James R; De Houwer, Jan; Rothermund, Klaus

2016-12-01

The current paper presents an extension of the Parallel Episodic Processing model. The model is developed for simulating behaviour in performance (i.e., speeded response time) tasks and learns to anticipate both how and when to respond based on retrieval of memories of previous trials. With one fixed parameter set, the model is shown to successfully simulate a wide range of different findings. These include: practice curves in the Stroop paradigm, contingency learning effects, learning acquisition curves, stimulus-response binding effects, mixing costs, and various findings from the attentional control domain. The results demonstrate several important points. First, the same retrieval mechanism parsimoniously explains stimulus-response binding, contingency learning, and practice effects. Second, as performance improves with practice, any effects will shrink with it. Third, a model of simple learning processes is sufficient to explain phenomena that are typically (but perhaps incorrectly) interpreted in terms of higher-order control processes. More generally, we argue that computational models with a fixed parameter set and wider breadth should be preferred over those that are restricted to a narrow set of phenomena. Copyright © 2016 Elsevier Inc. All rights reserved.

Extension of the Haseman-Elston regression model to longitudinal data.

PubMed

Won, Sungho; Elston, Robert C; Park, Taesung

2006-01-01

We propose an extension to longitudinal data of the Haseman and Elston regression method for linkage analysis. The proposed model is a mixed model having several random effects. As response variable, we investigate the sibship sample mean corrected cross-product (smHE) and the BLUP-mean corrected cross product (pmHE), comparing them with the original squared difference (oHE), the overall mean corrected cross-product (rHE), and the weighted average of the squared difference and the squared mean-corrected sum (wHE). The proposed model allows for the correlation structure of longitudinal data. Also, the model can test for gene x time interaction to discover genetic variation over time. The model was applied in an analysis of the Genetic Analysis Workshop 13 (GAW13) simulated dataset for a quantitative trait simulating systolic blood pressure. Independence models did not preserve the test sizes, while the mixed models with both family and sibpair random effects tended to preserve size well. Copyright 2006 S. Karger AG, Basel.

Effect of exercise on patient specific abdominal aortic aneurysm flow topology and mixing.

PubMed

Arzani, Amirhossein; Les, Andrea S; Dalman, Ronald L; Shadden, Shawn C

2014-02-01

Computational fluid dynamics modeling was used to investigate changes in blood transport topology between rest and exercise conditions in five patient-specific abdominal aortic aneurysm models. MRI was used to provide the vascular anatomy and necessary boundary conditions for simulating blood velocity and pressure fields inside each model. Finite-time Lyapunov exponent fields and associated Lagrangian coherent structures were computed from blood velocity data and were used to compare features of the transport topology between rest and exercise both mechanistically and qualitatively. A mix-norm and mix-variance measure based on fresh blood distribution throughout the aneurysm over time were implemented to quantitatively compare mixing between rest and exercise. Exercise conditions resulted in higher and more uniform mixing and reduced the overall residence time in all aneurysms. Separated regions of recirculating flow were commonly observed in rest, and these regions were either reduced or removed by attached and unidirectional flow during exercise, or replaced with regional chaotic and transiently turbulent mixing, or persisted and even extended during exercise. The main factor that dictated the change in flow topology from rest to exercise was the behavior of the jet of blood penetrating into the aneurysm during systole. Copyright © 2013 John Wiley & Sons, Ltd.

Three-Dimensional Effects of Artificial Mixing in a Shallow Drinking-Water Reservoir

NASA Astrophysics Data System (ADS)

Chen, Shengyang; Little, John C.; Carey, Cayelan C.; McClure, Ryan P.; Lofton, Mary E.; Lei, Chengwang

2018-01-01

Studies that examine the effects of artificial mixing for water-quality mitigation in lakes and reservoirs often view a water column with a one-dimensional (1-D) perspective (e.g., homogenized epilimnetic and hypolimnetic layers). Artificial mixing in natural water bodies, however, is inherently three dimensional (3-D). Using a 3-D approach experimentally and numerically, the present study visualizes thermal structure and analyzes constituent transport under the influence of artificial mixing in a shallow drinking-water reservoir. The purpose is to improve the understanding of artificial mixing, which may help to better design and operate mixing systems. In this reservoir, a side-stream supersaturation (SSS) hypolimnetic oxygenation system and an epilimnetic bubble-plume mixing (EM) system were concurrently deployed in the deep region. The present study found that, while the mixing induced by the SSS system does not have a distinct 3-D effect on the thermal structure, epilimnetic mixing by the EM system causes 3-D heterogeneity. In the experiments, epilimnetic mixing deepened the lower metalimnetic boundary near the diffuser by about 1 m, with 55% reduction of the deepening rate at 120 m upstream of the diffuser. In a tracer study using a 3-D hydrodynamic model, the operational flow rate of the EM system is found to be an important short-term driver of constituent transport in the reservoir, whereas the duration of the EM system operation is the dominant long-term driver. The results suggest that artificial mixing substantially alters both 3-D thermal structure and constituent transport, and thus needs to be taken into account for reservoir management.

Dark gauge bosons: LHC signatures of non-abelian kinetic mixing

DOE PAGES

Argüelles, Carlos A.; He, Xiao-Gang; Ovanesyan, Grigory; ...

2017-04-20

We consider non-abelian kinetic mixing between the Standard Model and a dark sector gauge group associated with the presence of a scalar triplet. The magnitude of the resulting dark photon coupling ϵ is determined by the ratio of the triplet vacuum expectation value, constrained to by by electroweak precision tests, to the scale Λ of the effective theory. The corresponding effective operator Wilson coefficient can be while accommodating null results for dark photon searches, allowing for a distinctive LHC dark photon phenomenology. After outlining the possible LHC signatures, we illustrate by recasting current ATLAS dark photon results into the non-abelianmore » mixing context.« less

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

PubMed Central

Austin, Peter C.

2017-01-01

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

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

PubMed

Austin, Peter C

2017-08-01

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

Investigation of micromixing by acoustically oscillated sharp-edges

PubMed Central

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

2016-01-01

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

Investigation of micromixing by acoustically oscillated sharp-edges.

PubMed

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

2016-03-01

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

Rapid and efficient mixing in a slip-driven three-dimensional flow in a rectangular channel

NASA Astrophysics Data System (ADS)

Pacheco, J. Rafael; Ping Chen, Kang; Hayes, Mark A.

2006-08-01

A method for generating mixing in an electroosmotic flow of an electrolytic solution in a three-dimensional channel is proposed. When the width-to-height aspect ratio of the channel cross-section is large, mixing of a blob of a solute in a slip-driven three-dimensional flow in a rectangular channel can be used to model and assess the effectiveness of this method. It is demonstrated through numerical simulations that under certain operating conditions, rapid and efficient mixing can be achieved. Future investigation will include the solution of the exact equations and experimentation.

Using Atmosphere-Forest Measurements To Examine The Potential For Reduced Downwind Dose

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

Viner, B.

2015-10-13

A 2-D dispersion model was developed to address how airborne plumes interact with the forest at Savannah River Site. Parameters describing turbulence and mixing of the atmosphere within and just above the forest were estimated using measurements of water vapor or carbon dioxide concentration made at the Aiken AmeriFlux tower for a range of stability and seasonal conditions. Stability periods when the greatest amount of mixing of an airborne plume into the forest were found for 1) very unstable environments, when atmospheric turbulence is usually at a maximum, and 2) very stable environments, when the plume concentration at the forestmore » top is at a maximum and small amounts of turbulent mixing can move a substantial portion of the plume into the forest. Plume interactions with the forest during stable periods are of particular importance because these conditions are usually considered the worst-case scenario for downwind effects from a plume. The pattern of plume mixing into the forest was similar during the year except during summer when the amount of plume mixed into the forest was nearly negligible for all but stable periods. If the model results indicating increased deposition into the forest during stable conditions can be confirmed, it would allow for a reduction in the limitations that restrict facility operations while maintaining conservative estimates for downwind effects. Continuing work is planned to confirm these results as well as estimate specific deposition velocity values for use in toolbox models used in regulatory roles.« less

Effects of incomplete mixing on reactive transport in flows through heterogeneous porous media

NASA Astrophysics Data System (ADS)

Wright, Elise E.; Richter, David H.; Bolster, Diogo

2017-11-01

The phenomenon of incomplete mixing reduces bulk effective reaction rates in reactive transport. Many existing models do not account for these effects, resulting in the overestimation of reaction rates in laboratory and field settings. To date, most studies on incomplete mixing have focused on diffusive systems; here, we extend these to explore the role that flow heterogeneity has on incomplete mixing. To do this, we examine reactive transport using a Lagrangian reactive particle tracking algorithm in two-dimensional idealized heterogeneous porous media. Contingent on the nondimensional Peclet and Damköhler numbers in the system, it was found that near well-mixed behavior could be observed at late times in the heterogeneous flow field simulations. We look at three common flow deformation metrics that describe the enhancement of mixing in the flow due to velocity gradients: the Okubo-Weiss parameter (θ ), the largest eigenvalue of the Cauchy-Green strain tensor (λC), and the finite-time Lyapunov exponent (Λ ). Strong mixing regions in the heterogeneous flow field identified by these metrics were found to correspond to regions with higher numbers of reactions, but the infrequency of these regions compared to the large numbers of reactions occurring elsewhere in the domain imply that these strong mixing regions are insufficient in explaining the observed near well-mixed behavior. Since it was found that reactive transport in these heterogeneous flows could overcome the effects of incomplete mixing, we also search for a closure for the mean concentration. The conservative quantity u2¯, where u =CA-CB , was found to predict the late time scaling of the mean concentration, i.e., Ci¯˜u2¯ .

Regulation mechanisms in mixed and pure culture microbial fermentation.

PubMed

Hoelzle, Robert D; Virdis, Bernardino; Batstone, Damien J

2014-11-01

Mixed-culture fermentation is a key central process to enable next generation biofuels and biocommodity production due to economic and process advantages over application of pure cultures. However, a key limitation to the application of mixed-culture fermentation is predicting culture product response, related to metabolic regulation mechanisms. This is also a limitation in pure culture bacterial fermentation. This review evaluates recent literature in both pure and mixed culture studies with a focus on understanding how regulation and signaling mechanisms interact with metabolic routes and activity. In particular, we focus on how microorganisms balance electron sinking while maximizing catabolic energy generation. Analysis of these mechanisms and their effect on metabolism dynamics is absent in current models of mixed-culture fermentation. This limits process prediction and control, which in turn limits industrial application of mixed-culture fermentation. A key mechanism appears to be the role of internal electron mediating cofactors, and related regulatory signaling. This may determine direction of electrons towards either hydrogen or reduced organics as end-products and may form the basis for future mechanistic models. © 2014 Wiley Periodicals, Inc.

Effect of flow and active mixing on bacterial growth in a colon-like geometry

NASA Astrophysics Data System (ADS)

Cremer, Jonas; Segota, Igor; Arnoldini, Markus; Groisman, Alex; Hwa, Terence

The large intestine harbors bacteria from hundreds of species, with bacterial densities reaching up to 1012 cells per gram. Many different factors influence bacterial growth dynamics and thus bacterial density and microbiota composition. One dominant force is flow which can in principle lead to a washout of bacteria from the proximal colon. Active mixing by Contractions of the colonic wall together with bacterial growth might counteract such flow-forces and allow high bacterial densities to occur. As a step towards understanding bacterial growth in the presence of mixing and flow, we constructed an in-vitro setup where controlled wall-deformations of a channel emulate Contractions. We investigate growth along the channel under a steady nutrient inflow. In the limits of no or very frequent Contractions, the device behaves like a plug-flow reactor and a chemostat respectively. Depending on mixing and flow, we observe varying spatial gradients in bacterial density along the channel. Active mixing by deformations of the channel wall is shown to be crucial in maintaining a steady-state bacterial population in the presence of flow. The growth-dynamics is quantitatively captured by a simple mathematical model, with the effect of mixing described by an effective diffusion term.

Complex networks generated by the Penna bit-string model: Emergence of small-world and assortative mixing

NASA Astrophysics Data System (ADS)

Li, Chunguang; Maini, Philip K.

2005-10-01

The Penna bit-string model successfully encompasses many phenomena of population evolution, including inheritance, mutation, evolution, and aging. If we consider social interactions among individuals in the Penna model, the population will form a complex network. In this paper, we first modify the Verhulst factor to control only the birth rate, and introduce activity-based preferential reproduction of offspring in the Penna model. The social interactions among individuals are generated by both inheritance and activity-based preferential increase. Then we study the properties of the complex network generated by the modified Penna model. We find that the resulting complex network has a small-world effect and the assortative mixing property.

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

PubMed

Moerbeek, Mirjam; van Schie, Sander

2016-07-11

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

Model for toroidal velocity in H-mode plasmas in the presence of internal transport barriers

NASA Astrophysics Data System (ADS)

Chatthong, B.; Onjun, T.; Singhsomroje, W.

2010-06-01

A model for predicting toroidal velocity in H-mode plasmas in the presence of internal transport barriers (ITBs) is developed using an empirical approach. In this model, it is assumed that the toroidal velocity is directly proportional to the local ion temperature. This model is implemented in the BALDUR integrated predictive modelling code so that simulations of ITB plasmas can be carried out self-consistently. In these simulations, a combination of a semi-empirical mixed Bohm/gyro-Bohm (mixed B/gB) core transport model that includes ITB effects and NCLASS neoclassical transport is used to compute a core transport. The boundary is taken to be at the top of the pedestal, where the pedestal values are described using a theory-based pedestal model based on a combination of magnetic and flow shear stabilization pedestal width scaling and an infinite-n ballooning pressure gradient model. The combination of the mixed B/gB core transport model with ITB effects, together with the pedestal and the toroidal velocity models, is used to simulate the time evolution of plasma current, temperature and density profiles of 10 JET optimized shear discharges. It is found that the simulations can reproduce an ITB formation in these discharges. Statistical analyses including root mean square error (RMSE) and offset are used to quantify the agreement. It is found that the averaged RMSE and offset among these discharges are about 24.59% and -0.14%, respectively.

Mixing Phenomena in a Bottom Blown Copper Smelter: A Water Model Study

NASA Astrophysics Data System (ADS)

Shui, Lang; Cui, Zhixiang; Ma, Xiaodong; Akbar Rhamdhani, M.; Nguyen, Anh; Zhao, Baojun

2015-03-01

The first commercial bottom blown oxygen copper smelting furnace has been installed and operated at Dongying Fangyuan Nonferrous Metals since 2008. Significant advantages have been demonstrated in this technology mainly due to its bottom blown oxygen-enriched gas. In this study, a scaled-down 1:12 model was set up to simulate the flow behavior for understanding the mixing phenomena in the furnace. A single lance was used in the present study for gas blowing to establish a reliable research technique and quantitative characterisation of the mixing behavior. Operating parameters such as horizontal distance from the blowing lance, detector depth, bath height, and gas flow rate were adjusted to investigate the mixing time under different conditions. It was found that when the horizontal distance between the lance and detector is within an effective stirring range, the mixing time decreases slightly with increasing the horizontal distance. Outside this range, the mixing time was found to increase with increasing the horizontal distance and it is more significant on the surface. The mixing time always decreases with increasing gas flow rate and bath height. An empirical relationship of mixing time as functions of gas flow rate and bath height has been established first time for the horizontal bottom blowing furnace.

Technical note: Examining ozone deposition over seawater

NASA Astrophysics Data System (ADS)

Sarwar, Golam; Kang, Daiwen; Foley, Kristen; Schwede, Donna; Gantt, Brett; Mathur, Rohit

2016-09-01

Surface layer resistance plays an important role in determining ozone deposition velocity over sea-water and can be influenced by chemical interactions at the air-water interface. Here, we examine the effect of chemical interactions of iodide, dimethylsulfide, dissolved organic carbon, and bromide in seawater on ozone deposition. We perform a series of simulations using the hemispheric Community Multiscale Air Quality model for summer months in the Northern Hemisphere. Our results suggest that each chemical interaction enhances the ozone deposition velocity and decreases the atmospheric ozone mixing ratio over seawater. Iodide enhances the median deposition velocity over seawater by 0.023 cm s-1, dissolved organic carbon by 0.021 cm s-1, dimethylsulfide by 0.002 cm s-1, and bromide by ∼0.0006 cm s-1. Consequently, iodide decreases the median atmospheric ozone mixing ratio over seawater by 0.7 ppb, dissolved organic carbon by 0.8 ppb, dimethylsulfide by 0.1 ppb, and bromide by 0.02 ppb. In a separate model simulation, we account for the effect of dissolved salts in seawater on the Henry's law constant for ozone and find that it reduces the median deposition velocity by 0.007 cm s-1 and increases surface ozone mixing ratio by 0.2 ppb. The combined effect of these processes increases the median ozone deposition velocity over seawater by 0.040 cm s-1, lowers the atmospheric ozone mixing ratio by 5%, and slightly improves model performance relative to observations.

Microstructural modeling of thermal conductivity of high burn-up mixed oxide fuel

NASA Astrophysics Data System (ADS)

Teague, Melissa; Tonks, Michael; Novascone, Stephen; Hayes, Steven

2014-01-01

Predicting the thermal conductivity of oxide fuels as a function of burn-up and temperature is fundamental to the efficient and safe operation of nuclear reactors. However, modeling the thermal conductivity of fuel is greatly complicated by the radially inhomogeneous nature of irradiated fuel in both composition and microstructure. In this work, radially and temperature-dependent models for effective thermal conductivity were developed utilizing optical micrographs of high burn-up mixed oxide fuel. The micrographs were employed to create finite element meshes with the OOF2 software. The meshes were then used to calculate the effective thermal conductivity of the microstructures using the BISON [1] fuel performance code. The new thermal conductivity models were used to calculate thermal profiles at end of life for the fuel pellets. These results were compared to thermal conductivity models from the literature, and comparison between the new finite element-based thermal conductivity model and the Duriez-Lucuta model was favorable.

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

PubMed

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

2013-05-01

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

Microstructural Modeling of Thermal Conductivity of High Burn-up Mixed Oxide Fuel

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

Melissa Teague; Michael Tonks; Stephen Novascone

2014-01-01

Predicting the thermal conductivity of oxide fuels as a function of burn-up and temperature is fundamental to the efficient and safe operation of nuclear reactors. However, modeling the thermal conductivity of fuel is greatly complicated by the radially inhomogeneous nature of irradiated fuel in both composition and microstructure. In this work, radially and temperature-dependent models for effective thermal conductivity were developed utilizing optical micrographs of high burn-up mixed oxide fuel. The micrographs were employed to create finite element meshes with the OOF2 software. The meshes were then used to calculate the effective thermal conductivity of the microstructures using the BISONmore » fuel performance code. The new thermal conductivity models were used to calculate thermal profiles at end of life for the fuel pellets. These results were compared to thermal conductivity models from the literature, and comparison between the new finite element-based thermal conductivity model and the Duriez–Lucuta model was favorable.« less

Characterization of superconducting radiofrequency breakdown by two-mode excitation

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

Eremeev, Grigory V.; Palczewski, Ari D.

2014-01-14

We show that thermal and magnetic contributions to the breakdown of superconductivity in radiofrequency (RF) fields can be separated by applying two RF modes simultaneously to a superconducting surface. We develop a simple model that illustrates how mode-mixing RF data can be related to properties of the superconductor. Within our model the data can be described by a single parameter, which can be derived either from RF or thermometry data. Our RF and thermometry data are in good agreement with the model. We propose to use mode-mixing technique to decouple thermal and magnetic effects on RF breakdown of superconductors.

Hierarchical Bayes approach for subgroup analysis.

PubMed

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

2017-01-01

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

Development and Validation of a 3-Dimensional CFB Furnace Model

NASA Astrophysics Data System (ADS)

Vepsäläinen, Arl; Myöhänen, Karl; Hyppäneni, Timo; Leino, Timo; Tourunen, Antti

At Foster Wheeler, a three-dimensional CFB furnace model is essential part of knowledge development of CFB furnace process regarding solid mixing, combustion, emission formation and heat transfer. Results of laboratory and pilot scale phenomenon research are utilized in development of sub-models. Analyses of field-test results in industrial-scale CFB boilers including furnace profile measurements are simultaneously carried out with development of 3-dimensional process modeling, which provides a chain of knowledge that is utilized as feedback for phenomenon research. Knowledge gathered by model validation studies and up-to-date parameter databases are utilized in performance prediction and design development of CFB boiler furnaces. This paper reports recent development steps related to modeling of combustion and formation of char and volatiles of various fuel types in CFB conditions. Also a new model for predicting the formation of nitrogen oxides is presented. Validation of mixing and combustion parameters for solids and gases are based on test balances at several large-scale CFB boilers combusting coal, peat and bio-fuels. Field-tests including lateral and vertical furnace profile measurements and characterization of solid materials provides a window for characterization of fuel specific mixing and combustion behavior in CFB furnace at different loads and operation conditions. Measured horizontal gas profiles are projection of balance between fuel mixing and reactions at lower part of furnace and are used together with both lateral temperature profiles at bed and upper parts of furnace for determination of solid mixing and combustion model parameters. Modeling of char and volatile based formation of NO profiles is followed by analysis of oxidizing and reducing regions formed due lower furnace design and mixing characteristics of fuel and combustion airs effecting to formation ofNO furnace profile by reduction and volatile-nitrogen reactions. This paper presents CFB process analysis focused on combustion and NO profiles in pilot and industrial scale bituminous coal combustion.

An Efficient Alternative Mixed Randomized Response Procedure

ERIC Educational Resources Information Center

Singh, Housila P.; Tarray, Tanveer A.

2015-01-01

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

The effect of state medicaid case-mix payment on nursing home resident acuity.

PubMed

Feng, Zhanlian; Grabowski, David C; Intrator, Orna; Mor, Vincent

2006-08-01

To examine the relationship between Medicaid case-mix payment and nursing home resident acuity. Longitudinal Minimum Data Set (MDS) resident assessments from 1999 to 2002 and Online Survey Certification and Reporting (OSCAR) data from 1996 to 2002, for all freestanding nursing homes in the 48 contiguous U.S. states. We used a facility fixed-effects model to examine the effect of introducing state case-mix payment on changes in nursing home case-mix acuity. Facility acuity was measured by aggregating the nursing case-mix index (NCMI) from the MDS using the Resource Utilization Group (Version III) resident classification system, separately for new admits and long-stay residents, and by an OSCAR-derived index combining a range of activity of daily living dependencies and special treatment measures. We followed facilities over the study period to create a longitudinal data file based on the MDS and OSCAR, respectively, and linked facilities with longitudinal data on state case-mix payment policies for the same period. Across three acuity measures and two data sources, we found that states shifting to case-mix payment increased nursing home acuity levels over the study period. Specifically, we observed a 2.5 percent increase in the average acuity of new admits and a 1.3 to 1.4 percent increase in the acuity of long-stay residents, following the introduction of case-mix payment. The adoption of case-mix payment increased access to care for higher acuity Medicaid residents.

Mixed valent metals

NASA Astrophysics Data System (ADS)

Riseborough, P. S.; Lawrence, J. M.

2016-08-01

We review the theory of mixed-valent metals and make comparison with experiments. A single-impurity description of the mixed-valent state is discussed alongside the description of the nearly-integer valent or Kondo limit. The degeneracy N of the f-shell plays an important role in the description of the low-temperature Fermi-liquid state. In particular, for large N, there is a rapid cross-over between the mixed-valent and the Kondo limit when the number of f electrons is changed. We discuss the limitations on the application of the single-impurity description to concentrated compounds such as those caused by the saturation of the Kondo effect and those due to the presence of magnetic interactions between the impurities. This discussion is followed by a description of a periodic lattice of mixed-valent ions, including the role of the degeneracy N. The article concludes with a comparison of theory and experiment. Topics covered include the single-impurity Anderson model, Luttinger’s theorem, the Friedel sum rule, the Schrieffer-Wolff transformation, the single-impurity Kondo model, Kondo screening, the Wilson ratio, local Fermi-liquids, Fermi-liquid sum rules, the Noziéres exhaustion principle, Doniach’s diagram, the Anderson lattice model, the Slave-Boson method, etc.

The impact of payer-specific hospital case mix on hospital costs and revenues for third-party patients.

PubMed

Lee, Keon-Hyung; Roh, M P H Chul-Young

2007-02-01

Competition among hospitals and managed care have forced hospital industry to be more efficient. With higher degrees of hospital competition and managed care penetration, hospitals have argued that the rate of increase in hospital cost is greater than the rate of increase in hospital revenue. By developing a payer-specific case mix index (CMI) for third-party patients, this paper examined the effect of hospital case mix on hospital cost and revenue for third-party patients in California using the hospital financial and utilization data covering 1986-1998. This study found that the coefficients for CMIs in the third-party hospital revenue model were greater than those in the hospital cost model until 1995. Since 1995, however, the coefficients for CMIs in the third-party hospital revenue model have been less than those in hospital cost models. Over time, the differences in coefficients for CMIs in hospital revenue and cost models for third-party patients have become smaller and smaller although those differences are statistically insignificant.

Panel Stiffener Debonding Analysis using a Shell/3D Modeling Technique

NASA Technical Reports Server (NTRS)

Krueger, Ronald; Ratcliffe, James G.; Minguet, Pierre J.

2008-01-01

A shear loaded, stringer reinforced composite panel is analyzed to evaluate the fidelity of computational fracture mechanics analyses of complex structures. Shear loading causes the panel to buckle. The resulting out -of-plane deformations initiate skin/stringer separation at the location of an embedded defect. The panel and surrounding load fixture were modeled with shell elements. A small section of the stringer foot, web and noodle as well as the panel skin near the delamination front were modeled with a local 3D solid model. Across the width of the stringer fo to, the mixed-mode strain energy release rates were calculated using the virtual crack closure technique. A failure index was calculated by correlating the results with a mixed-mode failure criterion of the graphite/epoxy material. The objective was to study the effect of the fidelity of the local 3D finite element model on the computed mixed-mode strain energy release rates and the failure index.

Panel-Stiffener Debonding and Analysis Using a Shell/3D Modeling Technique

NASA Technical Reports Server (NTRS)

Krueger, Ronald; Ratcliffe, James G.; Minguet, Pierre J.

2007-01-01

A shear loaded, stringer reinforced composite panel is analyzed to evaluate the fidelity of computational fracture mechanics analyses of complex structures. Shear loading causes the panel to buckle. The resulting out-of-plane deformations initiate skin/stringer separation at the location of an embedded defect. The panel and surrounding load fixture were modeled with shell elements. A small section of the stringer foot, web and noodle as well as the panel skin near the delamination front were modeled with a local 3D solid model. Across the width of the stringer foot, the mixed-mode strain energy release rates were calculated using the virtual crack closure technique. A failure index was calculated by correlating the results with a mixed-mode failure criterion of the graphite/epoxy material. The objective was to study the effect of the fidelity of the local 3D finite element model on the computed mixed-mode strain energy release rates and the failure index.

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2012-08-01

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

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

PubMed

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

2017-02-01

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

3D mapping, hydrodynamics and modelling of the freshwater-brine mixing zone in salt flats similar to the Salar de Atacama (Chile)

NASA Astrophysics Data System (ADS)

Marazuela, M. A.; Vázquez-Suñé, E.; Custodio, E.; Palma, T.; García-Gil, A.; Ayora, C.

2018-06-01

Salt flat brines are a major source of minerals and especially lithium. Moreover, valuable wetlands with delicate ecologies are also commonly present at the margins of salt flats. Therefore, the efficient and sustainable exploitation of the brines they contain requires detailed knowledge about the hydrogeology of the system. A critical issue is the freshwater-brine mixing zone, which develops as a result of the mass balance between the recharged freshwater and the evaporating brine. The complex processes occurring in salt flats require a three-dimensional (3D) approach to assess the mixing zone geometry. In this study, a 3D map of the mixing zone in a salt flat is presented, using the Salar de Atacama as an example. This mapping procedure is proposed as the basis of computationally efficient three-dimensional numerical models, provided that the hydraulic heads of freshwater and mixed waters are corrected based on their density variations to convert them into brine heads. After this correction, the locations of lagoons and wetlands that are characteristic of the marginal zones of the salt flats coincide with the regional minimum water (brine) heads. The different morphologies of the mixing zone resulting from this 3D mapping have been interpreted using a two-dimensional (2D) flow and transport numerical model of an idealized cross-section of the mixing zone. The result of the model shows a slope of the mixing zone that is similar to that obtained by 3D mapping and lower than in previous models. To explain this geometry, the 2D model was used to evaluate the effects of heterogeneity in the mixing zone geometry. The higher the permeability of the upper aquifer is, the lower the slope and the shallower the mixing zone become. This occurs because most of the freshwater lateral recharge flows through the upper aquifer due to its much higher transmissivity, thus reducing the freshwater head. The presence of a few meters of highly permeable materials in the upper part of these hydrogeological systems, such as alluvial fans or karstified evaporites that are frequently associated with the salt flats, is enough to greatly modify the geometry of the saline interface.

Analyzing Association Mapping in Pedigree-Based GWAS Using a Penalized Multitrait Mixed Model

PubMed Central

Liu, Jin; Yang, Can; Shi, Xingjie; Li, Cong; Huang, Jian; Zhao, Hongyu; Ma, Shuangge

2017-01-01

Genome-wide association studies (GWAS) have led to the identification of many genetic variants associated with complex diseases in the past 10 years. Penalization methods, with significant numerical and statistical advantages, have been extensively adopted in analyzing GWAS. This study has been partly motivated by the analysis of Genetic Analysis Workshop (GAW) 18 data, which have two notable characteristics. First, the subjects are from a small number of pedigrees and hence related. Second, for each subject, multiple correlated traits have been measured. Most of the existing penalization methods assume independence between subjects and traits and can be suboptimal. There are a few methods in the literature based on mixed modeling that can accommodate correlations. However, they cannot fully accommodate the two types of correlations while conducting effective marker selection. In this study, we develop a penalized multitrait mixed modeling approach. It accommodates the two different types of correlations and includes several existing methods as special cases. Effective penalization is adopted for marker selection. Simulation demonstrates its satisfactory performance. The GAW 18 data are analyzed using the proposed method. PMID:27247027

A Perceptual Pathway to Bias: Interracial Exposure Reduces Abrupt Shifts in Real-Time Race Perception That Predict Mixed-Race Bias.

PubMed

Freeman, Jonathan B; Pauker, Kristin; Sanchez, Diana T

2016-04-01

In two national samples, we examined the influence of interracial exposure in one's local environment on the dynamic process underlying race perception and its evaluative consequences. Using a mouse-tracking paradigm, we found in Study 1 that White individuals with low interracial exposure exhibited a unique effect of abrupt, unstable White-Black category shifting during real-time perception of mixed-race faces, consistent with predictions from a neural-dynamic model of social categorization and computational simulations. In Study 2, this shifting effect was replicated and shown to predict a trust bias against mixed-race individuals and to mediate the effect of low interracial exposure on that trust bias. Taken together, the findings demonstrate that interracial exposure shapes the dynamics through which racial categories activate and resolve during real-time perceptions, and these initial perceptual dynamics, in turn, may help drive evaluative biases against mixed-race individuals. Thus, lower-level perceptual aspects of encounters with racial ambiguity may serve as a foundation for mixed-race prejudice. © The Author(s) 2016.

Modelling non-hydrostatic processes in sill regions

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

Experimental and numerical study on particle distribution in a two-zone chamber

NASA Astrophysics Data System (ADS)

Lai, Alvin C. K.; Wang, K.; Chen, F. Z.

Better understanding of aerosol dynamics is an important step for improving personal exposure assessments in indoor environments. Although the limitation of the assumptions in a well-mixed model is well known, there has been very little research reported in the published literature on the discrepancy of exposure assessments between numerical models which take account of gravitational effects and the well-mixed model. A new Eulerian-type drift-flux model has been developed to simulate particle dispersion and personal exposure in a two-zone geometry, which accounts for the drift velocity resulting from gravitational settling and diffusion. To validate the numerical model, a small-scale chamber was fabricated. The airflow characteristics and particle concentrations were measured by a phase Doppler Anemometer. Both simulated airflow and concentration profiles agree well with the experimental results. A strong inhomogeneous concentration was observed experimentally for 10 μm aerosols. The computational model was further applied to study a simple hypothetical, yet more realistic scenario. The aim was to explore different levels of exposure predicted by the new model and the well-mixed model. Aerosols are initially uniformly distributed in one zone and subsequently transported and dispersed to an adjacent zone through an opening. Owing to the significant difference in the rates of transport and dispersion between aerosols and gases, inferred from the results, the well-mixed model tends to overpredict the concentration in the source zone, and under-predict the concentration in the exposed zone. The results are very useful to illustrate that the well-mixed assumption must be applied cautiously for exposure assessments as such an ideal condition may not be applied for coarse particles.

Short-chain fatty acids administration is protective in colitis-associated colorectal cancer development.

PubMed

Tian, Yun; Xu, Qing; Sun, Liqun; Ye, Ying; Ji, Guozhong

2018-03-17

Reduced short-chain fatty acids (SCFAs) have been reported in patients with ulcerative colitis, and increased intake of dietary fiber has shown to be clinically beneficial for colitis. Whether SCFAs suppress tumorigenesis in colitis-associated colorectal cancer remains unknown. The chemopreventive effect of SCFAs in colitis-associated colorectal cancer was evaluated in this study. Model of colitis-associated colorectal cancer in male BALB/c mice was induced by azoxymethane (AOM) and dextran sodium sulfate (DSS). SCFAs mix (67.5 mM acetate, 40 mM butyrate, 25.9 mM propionate) was administered in drink water during the study period. Macroscopic and histological studies were performed to examine the colorectal inflammation and tumorigenesis in AOM/DSS-induced mice treated with or without SCFA mix. The effects of SCFAs mix on colonic epithelial cellular proliferation were also assessed using Ki67 immunohistochemistry and TUNEL staining. The administration of SCFAs mix significantly reduced the tumor incidence and size in mice with AOM/DSS-induced colitis associated colorectal cancer. SCFAs mix protected from AOM/DSS-induced colorectal cancer by improving colon inflammation and disease activity index score as well as suppressing the expression of proinflammatory cytokines including IL-6, TNF-α and IL-17. A decrease in cell proliferation markers and an increase in TUNEL-positive tumor epithelial cells were also demonstrated in AOM/DSS mice treated with SCFAs mix. SCFAs mix administration prevented development of tumor and attenuated the colonic inflammation in a mouse model of colitis-associated colorectal cancer. SCFAs mix may be a potential agent in the prevention and treatment of colitis-associated colorectal cancer. Copyright © 2018 Elsevier Inc. All rights reserved.

Functional Additive Mixed Models

PubMed Central

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

2014-01-01

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

Functional Additive Mixed Models.

PubMed

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

2015-04-01

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

Next-to-minimal two Higgs Doublet Model

DOE PAGES

Chen, Chien -Yi; Freid, Michael; Sher, Marc

2014-04-07

The simplest extension of the Two Higgs Doublet Model is the addition of a real scalar singlet, S. The effects of mixing between the singlet and the doublets can be manifested in two ways. It can modify the couplings of the 126 GeV Higgs boson, h, and it can lead to direct detection of the heavy Higgs at the LHC. In this paper, we show that in the type-I Model, for heavy Higgs masses in the 200-600 GeV range, the latter effect will be detected earlier than the former for most of parameter space. Should no such Higgs be discoveredmore » in this mass range, then the upper limit on the mixing will be sufficiently strong such that there will be no significant effects on the couplings of the h for most of parameter space. Thus, the reverse is true in the type-II model, the limits from measurements of the couplings of the h will dominate over the limits from non-observation of the heavy Higgs.« less

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

PubMed

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.

Forecasting carbon dioxide emissions based on a hybrid of mixed data sampling regression model and back propagation neural network in the USA.

PubMed

Zhao, Xin; Han, Meng; Ding, Lili; Calin, Adrian Cantemir

2018-01-01

The accurate forecast of carbon dioxide emissions is critical for policy makers to take proper measures to establish a low carbon society. This paper discusses a hybrid of the mixed data sampling (MIDAS) regression model and BP (back propagation) neural network (MIDAS-BP model) to forecast carbon dioxide emissions. Such analysis uses mixed frequency data to study the effects of quarterly economic growth on annual carbon dioxide emissions. The forecasting ability of MIDAS-BP is remarkably better than MIDAS, ordinary least square (OLS), polynomial distributed lags (PDL), autoregressive distributed lags (ADL), and auto-regressive moving average (ARMA) models. The MIDAS-BP model is suitable for forecasting carbon dioxide emissions for both the short and longer term. This research is expected to influence the methodology for forecasting carbon dioxide emissions by improving the forecast accuracy. Empirical results show that economic growth has both negative and positive effects on carbon dioxide emissions that last 15 quarters. Carbon dioxide emissions are also affected by their own change within 3 years. Therefore, there is a need for policy makers to explore an alternative way to develop the economy, especially applying new energy policies to establish a low carbon society.

Effect of Micro-Teaching Practices with Concrete Models on Pre-Service Mathematics Teachers' Self-Efficacy Beliefs about Using Concrete Models

ERIC Educational Resources Information Center

Ünlü, Melihan

2018-01-01

The purpose of the current study was to investigate the effect of micro-teaching practices with concrete models on the pre-service teachers' self-efficacy beliefs about using concrete models and to determine the opinions of the pre-service teachers about this issue. In the current study, one of the mixed methods, the convergent design (embedded)…

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

PubMed

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.

THE ROLE OF THE MAGNETOROTATIONAL INSTABILITY IN MASSIVE STARS

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

Wheeler, J. Craig; Kagan, Daniel; Chatzopoulos, Emmanouil, E-mail: wheel@astro.as.utexas.edu

2015-01-20

The magnetorotational instability (MRI) is key to physics in accretion disks and is widely considered to play some role in massive star core collapse. Models of rotating massive stars naturally develop very strong shear at composition boundaries, a necessary condition for MRI instability, and the MRI is subject to triply diffusive destabilizing effects in radiative regions. We have used the MESA stellar evolution code to compute magnetic effects due to the Spruit-Tayler (ST) mechanism and the MRI, separately and together, in a sample of massive star models. We find that the MRI can be active in the later stages ofmore » massive star evolution, leading to mixing effects that are not captured in models that neglect the MRI. The MRI and related magnetorotational effects can move models of given zero-age main sequence mass across ''boundaries'' from degenerate CO cores to degenerate O/Ne/Mg cores and from degenerate O/Ne/Mg cores to iron cores, thus affecting the final evolution and the physics of core collapse. The MRI acting alone can slow the rotation of the inner core in general agreement with the observed ''initial'' rotation rates of pulsars. The MRI analysis suggests that localized fields ∼10{sup 12} G may exist at the boundary of the iron core. With both the ST and MRI mechanisms active in the 20 M {sub ☉} model, we find that the helium shell mixes entirely out into the envelope. Enhanced mixing could yield a population of yellow or even blue supergiant supernova progenitors that would not be standard SN IIP.« less

Scheduling Real-Time Mixed-Criticality Jobs

NASA Astrophysics Data System (ADS)

Baruah, Sanjoy K.; Bonifaci, Vincenzo; D'Angelo, Gianlorenzo; Li, Haohan; Marchetti-Spaccamela, Alberto; Megow, Nicole; Stougie, Leen

Many safety-critical embedded systems are subject to certification requirements; some systems may be required to meet multiple sets of certification requirements, from different certification authorities. Certification requirements in such "mixed-criticality" systems give rise to interesting scheduling problems, that cannot be satisfactorily addressed using techniques from conventional scheduling theory. In this paper, we study a formal model for representing such mixed-criticality workloads. We demonstrate first the intractability of determining whether a system specified in this model can be scheduled to meet all its certification requirements, even for systems subject to two sets of certification requirements. Then we quantify, via the metric of processor speedup factor, the effectiveness of two techniques, reservation-based scheduling and priority-based scheduling, that are widely used in scheduling such mixed-criticality systems, showing that the latter of the two is superior to the former. We also show that the speedup factors are tight for these two techniques.

Simulation analysis of rectifying microfluidic mixing with field-effect-tunable electrothermal induced flow.

PubMed

Liu, Weiyu; Ren, Yukun; Tao, Ye; Yao, Bobin; Li, You

2018-03-01

We report herein field-effect control on in-phase electrothermal streaming from a theoretical point of view, a phenomenon termed "alternating-current electrothermal-flow field effect transistor" (ACET-FFET), in the context of a new technology for handing analytes in microfluidics. Field-effect control through a gate terminal endows ACET-FFET the ability to generate arbitrary symmetry breaking in the transverse vortex flow pattern, which makes it attractive for mixing microfluidic samples. A computational model is developed to study the feasibility of this new microfluidic device design for micromixing. The influence of various parameters on developing an efficient mixer is investigated, and an integrated layout of discrete electrode array is suggested for achieving high-throughput mixing. Our physical demonstration with field-effect electrothermal flow control using a simple electrode structure proves invaluable for designing active micromixers for modern micro total analytical system. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A continuous mixing model for pdf simulations and its applications to combusting shear flows

NASA Technical Reports Server (NTRS)

Hsu, A. T.; Chen, J.-Y.

1991-01-01

The problem of time discontinuity (or jump condition) in the coalescence/dispersion (C/D) mixing model is addressed in this work. A C/D mixing model continuous in time is introduced. With the continuous mixing model, the process of chemical reaction can be fully coupled with mixing. In the case of homogeneous turbulence decay, the new model predicts a pdf very close to a Gaussian distribution, with finite higher moments also close to that of a Gaussian distribution. Results from the continuous mixing model are compared with both experimental data and numerical results from conventional C/D models.

Models to understand the population-level impact of mixed strain M. tuberculosis infections.

PubMed

Sergeev, Rinat; Colijn, Caroline; Cohen, Ted

2011-07-07

Over the past decade, numerous studies have identified tuberculosis patients in whom more than one distinct strain of Mycobacterium tuberculosis is present. While it has been shown that these mixed strain infections can reduce the probability of treatment success for individuals simultaneously harboring both drug-sensitive and drug-resistant strains, it is not yet known if and how this phenomenon impacts the long-term dynamics for tuberculosis within communities. Strain-specific differences in immunogenicity and associations with drug resistance suggest that a better understanding of how strains compete within hosts will be necessary to project the effects of mixed strain infections on the future burden of drug-sensitive and drug-resistant tuberculosis. In this paper, we develop a modeling framework that allows us to investigate mechanisms of strain competition within hosts and to assess the long-term effects of such competition on the ecology of strains in a population. These models permit us to systematically evaluate the importance of unknown parameters and to suggest priority areas for future experimental research. Despite the current scarcity of data to inform the values of several model parameters, we are able to draw important qualitative conclusions from this work. We find that mixed strain infections may promote the coexistence of drug-sensitive and drug-resistant strains in two ways. First, mixed strain infections allow a strain with a lower basic reproductive number to persist in a population where it would otherwise be outcompeted if has competitive advantages within a co-infected host. Second, some individuals progressing to phenotypically drug-sensitive tuberculosis from a state of mixed drug-sensitive and drug-resistant infection may retain small subpopulations of drug-resistant bacteria that can flourish once the host is treated with antibiotics. We propose that these types of mixed infections, by increasing the ability of low fitness drug-resistant strains to persist, may provide opportunities for compensatory mutations to accumulate and for relatively fit, highly drug-resistant strains of M. tuberculosis to emerge. Published by Elsevier Ltd.

Evidence of a major gene from Bayesian segregation analyses of liability to osteochondral diseases in pigs.

PubMed

Kadarmideen, Haja N; Janss, Luc L G

2005-11-01

Bayesian segregation analyses were used to investigate the mode of inheritance of osteochondral lesions (osteochondrosis, OC) in pigs. Data consisted of 1163 animals with OC and their pedigrees included 2891 animals. Mixed-inheritance threshold models (MITM) and several variants of MITM, in conjunction with Markov chain Monte Carlo methods, were developed for the analysis of these (categorical) data. Results showed major genes with significant and substantially higher variances (range 1.384-37.81), compared to the polygenic variance (sigmau2). Consequently, heritabilities for a mixed inheritance (range 0.65-0.90) were much higher than the heritabilities from the polygenes. Disease allele frequencies range was 0.38-0.88. Additional analyses estimating the transmission probabilities of the major gene showed clear evidence for Mendelian segregation of a major gene affecting osteochondrosis. The variants, MITM with informative prior on sigmau2, showed significant improvement in marginal distributions and accuracy of parameters. MITM with a "reduced polygenic model" for parameterization of polygenic effects avoided convergence problems and poor mixing encountered in an "individual polygenic model." In all cases, "shrinkage estimators" for fixed effects avoided unidentifiability for these parameters. The mixed-inheritance linear model (MILM) was also applied to all OC lesions and compared with the MITM. This is the first study to report evidence of major genes for osteochondral lesions in pigs; these results may also form a basis for underpinning the genetic inheritance of this disease in other animals as well as in humans.

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

PubMed

Bonate, Peter L

2017-01-01

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

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

PubMed Central

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

2016-01-01

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

The effect of under-ice melt ponds on their surroundings in the Arctic

NASA Astrophysics Data System (ADS)

Feltham, D. L.; Smith, N.; Flocco, D.

2016-12-01

In the summer months, melt water from the surface of the Arctic sea ice can percolate down through the ice and flow out of its base. This water is relatively warm and fresh compared to the ocean water beneath it, and so it floats between the ice and the oceanic mixed layer, forming pools of melt water called under-ice melt ponds. Sheets of ice, known as false bottoms, can subsequently form via double diffusion processes at the under-ice melt pond interface with the ocean, trapping the pond against the ice and completely isolating it from the ocean below. This has an insulating effect on the parent sea ice above the trapped pond, altering its rate of basal ablation. A one-dimensional, thermodynamic model of Arctic sea ice has been adapted to study the evolution of under-ice melt ponds and false bottoms over time. Comparing simulations of sea ice evolution with and without an under-ice melt pond provides a measure of how an under-ice melt pond affects the mass balance of the sea ice above it. Sensitivity studies testing the response of the model to a range of uncertain parameters have been performed, revealing some interesting implications of under-ice ponds during their life cycle. By changing the rate of basal ablation of the parent sea ice, and so the flux of fresh water and salt into the ocean, under-ice melt ponds affect the properties of the mixed layer beneath the sea ice. Our model of under-ice melt pond refreezing has been coupled to a simple oceanic mixed layer model to determine the effect on mixed layer depth, salinity and temperature.

Modeling complex chemical effects in turbulent nonpremixed combustion

NASA Technical Reports Server (NTRS)

Smith, Nigel S. A.

1995-01-01

Virtually all of the energy derived from the consumption of combustibles occurs in systems which utilize turbulent fluid motion. Since combustion is largely related to the mixing of fluids and mixing processes are orders of magnitude more rapid when enhanced by turbulent motion, efficiency criteria dictate that chemically powered devices necessarily involve fluid turbulence. Where combustion occurs concurrently with mixing at an interface between two reactive fluid bodies, this mode of combustion is called nonpremixed combustion. This is distinct from premixed combustion where flame-fronts propagate into a homogeneous mixture of reactants. These two modes are limiting cases in the range of temporal lag between mixing of reactants and the onset of reaction. Nonpremixed combustion occurs where this lag tends to zero, while premixed combustion occurs where this lag tends to infinity. Many combustion processes are hybrids of these two extremes with finite non-zero lag times. Turbulent nonpremixed combustion is important from a practical standpoint because it occurs in gas fired boilers, furnaces, waste incinerators, diesel engines, gas turbine combustors, and afterburners etc. To a large extent, past development of these practical systems involved an empirical methodology. Presently, efficiency standards and emission regulations are being further tightened (Correa 1993), and empiricism has had to give way to more fundamental research in order to understand and effectively model practical combustion processes (Pope 1991). A key element in effective modeling of turbulent combustion is making use of a sufficiently detailed chemical kinetic mechanism. The prediction of pollutant emission such as oxides of nitrogen (NO(x)) and sulphur (SO(x)) unburned hydrocarbons, and particulates demands the use of detailed chemical mechanisms. It is essential that practical models for turbulent nonpremixed combustion are capable of handling large numbers of 'stiff' chemical species equations.

Effects of wildland fire smoke on a tree-roosting bat: integrating a plume model, field measurements, and mammalian dose-response relationships

Treesearch

M.B. Dickinson; J.C. Norris; A.S. Bova; R.L. Kremens; V. Young; M.J. Lacki

2010-01-01

Faunal injury and mortality in wildland fires is a concern for wildlife and fire management although little work has been done on the mechanisms by which exposures cause their effects. In this paper, we use an integral plume model, field measurements, and models of carbon monoxide and heat effects to explore risk to tree-roosting bats during prescribed fires in mixed-...

Mathematical modelling of particle mixing effect on the combustion of municipal solid wastes in a packed-bed furnace.

PubMed

Yang, Yao Bin; Swithenbank, Jim

2008-01-01

Packed bed combustion is still the most common way to burn municipal solid wastes. In this paper, a dispersion model for particle mixing, mainly caused by the movement of the grate in a moving-burning bed, has been proposed and transport equations for the continuity, momentum, species, and energy conservation are described. Particle-mixing coefficients obtained from model tests range from 2.0x10(-6) to 3.0x10(-5)m2/s. A numerical solution is sought to simulate the combustion behaviour of a full-scale 12-tonne-per-h waste incineration furnace at different levels of bed mixing. It is found that an increase in mixing causes a slight delay in the bed ignition but greatly enhances the combustion processes during the main combustion period in the bed. A medium-level mixing produces a combustion profile that is positioned more at the central part of the combustion chamber, and any leftover combustible gases (mainly CO) enter directly into the most intensive turbulence area created by the opposing secondary-air jets and thus are consumed quickly. Generally, the specific arrangement of the impinging secondary-air jets dumps most of the non-uniformity in temperature and CO into the gas flow coming from the bed-top, while medium-level mixing results in the lowest CO emission at the furnace exit and the highest combustion efficiency in the bed.

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

PubMed

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

2017-09-01

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

An attempt to estimate isotropic and anisotropic lateral structure of the Earth by spectral inversion incorporating mixed coupling

NASA Astrophysics Data System (ADS)

Oda, Hitoshi

2005-02-01

We present a way to calculate free oscillation spectra for an aspherical earth model, which is constructed by adding isotropic and anisotropic velocity perturbations to the seismic velocity parameters of a reference earth model, and examine the effect of the velocity perturbations on the free oscillation spectrum. Lateral variations of the velocity perturbations are parametrized as an expansion in generalized spherical harmonics. We assume weak hexagonal anisotropy for the seismic wave anisotropy in the upper mantle, where the hexagonal symmetry axes are horizontally distributed. The synthetic spectra show that the velocity perturbations cause not only strong self-coupling among singlets of a multiplet but also mixed coupling between toroidal and spheroidal multiplets. Both the couplings give rise to an amplitude anomaly on the vertical component spectrum. In this study, we identify the amplitude anomaly resulting from the mixed coupling as quasi-toroidal mode. Excitation of the quasi-toroidal mode by a vertical strike-slip fault is largest on nodal lines of the Rayleigh wave, decreases with increasing azimuth angle and becomes smallest on loop lines. This azimuthal dependence of the spectral amplitude is quite similar to the Love wave radiation pattern. In addition, the amplitude spectrum of the quasi-toroidal mode is more sensitive to the anisotropic velocity perturbation than to the isotropic velocity perturbation. This means that the mode spectrum allowing for the mixed-coupling effect may provide constraints on the anisotropic lateral structure as well as the isotropic lateral structure. An inversion method, called mixed-coupling spectral inversion, is devised to retrieve the isotropic and anisotropic velocity perturbations from the free oscillation spectra incorporating the quasi-toroidal mode. We confirm that the spectral inversion method correctly recovers the isotropic and anisotropic lateral structure. Moreover introducing the mixed-coupling effect in the spectral inversion makes it possible to estimate the odd-order lateral structure, which cannot be determined by the conventional spectral inversion, which takes no account of the mixed coupling. Higher order structure is biased by the mixed coupling when the conventional spectral inversion is applied to the amplitude spectra incorporating the mixed coupling.

The Development and Evaluation of Speaking Learning Model by Cooperative Approach

ERIC Educational Resources Information Center

Darmuki, Agus; Andayani; Nurkamto, Joko; Saddhono, Kundharu

2018-01-01

A cooperative approach-based Speaking Learning Model (SLM) has been developed to improve speaking skill of Higher Education students. This research aimed at evaluating the effectiveness of cooperative-based SLM viewed from the development of student's speaking ability and its effectiveness on speaking activity. This mixed method study combined…

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

PubMed

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

2010-07-01

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

Predicting daily PM2.5 concentrations in Texas using high-resolution satellite aerosol optical depth.

PubMed

Zhang, Xueying; Chu, Yiyi; Wang, Yuxuan; Zhang, Kai

2018-08-01

The regulatory monitoring data of particulate matter with an aerodynamic diameter <2.5μm (PM 2.5 ) in Texas have limited spatial and temporal coverage. The purpose of this study is to estimate the ground-level PM 2.5 concentrations on a daily basis using satellite-retrieved Aerosol Optical Depth (AOD) in the state of Texas. We obtained the AOD values at 1-km resolution generated through the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm based on the images retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellites. We then developed mixed-effects models based on AODs, land use features, geographic characteristics, and weather conditions, and the day-specific as well as site-specific random effects to estimate the PM 2.5 concentrations (μg/m 3 ) in the state of Texas during the period 2008-2013. The mixed-effects models' performance was evaluated using the coefficient of determination (R 2 ) and square root of the mean squared prediction error (RMSPE) from ten-fold cross-validation, which randomly selected 90% of the observations for training purpose and 10% of the observations for assessing the models' true prediction ability. Mixed-effects regression models showed good prediction performance (R 2 values from 10-fold cross validation: 0.63-0.69). The model performance varied by regions and study years, and the East region of Texas, and year of 2009 presented relatively higher prediction precision (R 2 : 0.62 for the East region; R 2 : 0.69 for the year of 2009). The PM 2.5 concentrations generated through our developed models at 1-km grid cells in the state of Texas showed a decreasing trend from 2008 to 2013 and a higher reduction of predicted PM 2.5 in more polluted areas. Our findings suggest that mixed-effects regression models developed based on MAIAC AOD are a feasible approach to predict ground-level PM 2.5 in Texas. Predicted PM 2.5 concentrations at the 1-km resolution on a daily basis can be used for epidemiological studies to investigate short- and long-term health impact of PM 2.5 in Texas. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

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

2016-07-05

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

Four-component numerical simulation model of radiative convective interactions in large-scale oxygen-hydrogen turbulent fire balls

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

Surzhikov, S.T.

1996-12-31

Two-dimensional radiative gas dynamics model for numerical simulation of oxygen-hydrogen fire ball which may be generated by an explosion of a launch vehicle with cryogenic (LO{sub 2}-LH{sub 2}) fuel components is presented. The following physical-chemical processes are taken into account in the numerical model: and effective chemical reaction between the gaseous components (O{sub 2}-H{sub 2}) of the propellant, turbulent mixing and diffusion of the components, and radiative heat transfer. The results of numerical investigations of the following problems are presented: The influence of radiative heat transfer on fire ball gas dynamics during the first 13 sec after explosion, the effectmore » of the fuel gaseous components afterburning on fire ball gas dynamics, and the effect of turbulence on fire ball gas dynamics (in a framework of algebraic model of turbulent mixing).« less

Statistical power calculations for mixed pharmacokinetic study designs using a population approach.

PubMed

Kloprogge, Frank; Simpson, Julie A; Day, Nicholas P J; White, Nicholas J; Tarning, Joel

2014-09-01

Simultaneous modelling of dense and sparse pharmacokinetic data is possible with a population approach. To determine the number of individuals required to detect the effect of a covariate, simulation-based power calculation methodologies can be employed. The Monte Carlo Mapped Power method (a simulation-based power calculation methodology using the likelihood ratio test) was extended in the current study to perform sample size calculations for mixed pharmacokinetic studies (i.e. both sparse and dense data collection). A workflow guiding an easy and straightforward pharmacokinetic study design, considering also the cost-effectiveness of alternative study designs, was used in this analysis. Initially, data were simulated for a hypothetical drug and then for the anti-malarial drug, dihydroartemisinin. Two datasets (sampling design A: dense; sampling design B: sparse) were simulated using a pharmacokinetic model that included a binary covariate effect and subsequently re-estimated using (1) the same model and (2) a model not including the covariate effect in NONMEM 7.2. Power calculations were performed for varying numbers of patients with sampling designs A and B. Study designs with statistical power >80% were selected and further evaluated for cost-effectiveness. The simulation studies of the hypothetical drug and the anti-malarial drug dihydroartemisinin demonstrated that the simulation-based power calculation methodology, based on the Monte Carlo Mapped Power method, can be utilised to evaluate and determine the sample size of mixed (part sparsely and part densely sampled) study designs. The developed method can contribute to the design of robust and efficient pharmacokinetic studies.

A time dependent mixing model to close PDF equations for transport in heterogeneous aquifers

NASA Astrophysics Data System (ADS)

Schüler, L.; Suciu, N.; Knabner, P.; Attinger, S.

2016-10-01

Probability density function (PDF) methods are a promising alternative to predicting the transport of solutes in groundwater under uncertainty. They make it possible to derive the evolution equations of the mean concentration and the concentration variance, used in moment methods. The mixing model, describing the transport of the PDF in concentration space, is essential for both methods. Finding a satisfactory mixing model is still an open question and due to the rather elaborate PDF methods, a difficult undertaking. Both the PDF equation and the concentration variance equation depend on the same mixing model. This connection is used to find and test an improved mixing model for the much easier to handle concentration variance. Subsequently, this mixing model is transferred to the PDF equation and tested. The newly proposed mixing model yields significantly improved results for both variance modelling and PDF modelling.

Medicaid payment rates, case-mix reimbursement, and nursing home staffing--1996-2004.

PubMed

Feng, Zhanlian; Grabowski, David C; Intrator, Orna; Zinn, Jacqueline; Mor, Vincent

2008-01-01

We examined the impact of state Medicaid payment rates and case-mix reimbursement on direct care staffing levels in US nursing homes. We used a recent time series of national nursing home data from the Online Survey Certification and Reporting system for 1996-2004, merged with annual state Medicaid payment rates and case-mix reimbursement information. A 5-category response measure of total staffing levels was defined according to expert recommended thresholds, and examined in a multinomial logistic regression model. Facility fixed-effects models were estimated separately for Registered Nurse (RN), Licensed Practical Nurse (LPN), and Certified Nurse Aide (CNA) staffing levels measured as average hours per resident day. Higher Medicaid payment rates were associated with increases in total staffing levels to meet a higher recommended threshold. However, these gains in overall staffing were accompanied by a reduction of RN staffing and an increase in both LPN and CNA staffing levels. Under case-mix reimbursement, the likelihood of nursing homes achieving higher recommended staffing thresholds decreased, as did levels of professional staffing. Independent of the effects of state, market, and facility characteristics, there was a significant downward trend in RN staffing and an upward trend in both LPN and CNA staffing. Although overall staffing may increase in response to more generous Medicaid reimbursement, it may not translate into improvements in the skill mix of staff. Adjusting for reimbursement levels and resident acuity, total staffing has not increased after the implementation of case-mix reimbursement.

Structure Elucidation of Mixed-Linker Zeolitic Imidazolate Frameworks by Solid-State (1)H CRAMPS NMR Spectroscopy and Computational Modeling.

PubMed

Jayachandrababu, Krishna C; Verploegh, Ross J; Leisen, Johannes; Nieuwendaal, Ryan C; Sholl, David S; Nair, Sankar

2016-06-15

Mixed-linker zeolitic imidazolate frameworks (ZIFs) are nanoporous materials that exhibit continuous and controllable tunability of properties like effective pore size, hydrophobicity, and organophilicity. The structure of mixed-linker ZIFs has been studied on macroscopic scales using gravimetric and spectroscopic techniques. However, it has so far not been possible to obtain information on unit-cell-level linker distribution, an understanding of which is key to predicting and controlling their adsorption and diffusion properties. We demonstrate the use of (1)H combined rotation and multiple pulse spectroscopy (CRAMPS) NMR spin exchange measurements in combination with computational modeling to elucidate potential structures of mixed-linker ZIFs, particularly the ZIF 8-90 series. All of the compositions studied have structures that have linkers mixed at a unit-cell-level as opposed to separated or highly clustered phases within the same crystal. Direct experimental observations of linker mixing were accomplished by measuring the proton spin exchange behavior between functional groups on the linkers. The data were then fitted to a kinetic spin exchange model using proton positions from candidate mixed-linker ZIF structures that were generated computationally using the short-range order (SRO) parameter as a measure of the ordering, clustering, or randomization of the linkers. The present method offers the advantages of sensitivity without requiring isotope enrichment, a straightforward NMR pulse sequence, and an analysis framework that allows one to relate spin diffusion behavior to proposed atomic positions. We find that structures close to equimolar composition of the two linkers show a greater tendency for linker clustering than what would be predicted based on random models. Using computational modeling we have also shown how the window-type distribution in experimentally synthesized mixed-linker ZIF-8-90 materials varies as a function of their composition. The structural information thus obtained can be further used for predicting, screening, or understanding the tunable adsorption and diffusion behavior of mixed-linker ZIFs, for which the knowledge of linker distributions in the framework is expected to be important.