Formulating Mixed Models for Experiments, Including Longitudinal Experiments

Mixed models have become important in analyzing the results of experiments, particularly those that require more complicated models (e.g., those that involve longitudinal data). This article describes a method for deriving the terms in a mixed model. Our approach extends an earlier method by Brien and Bailey to explicitly identify terms for which autocorrelation and smooth trend arising from longitudinal observations need to be incorporated in the model. At the same time we retain the principle that the model used should include, at least, all the terms that are justified by the randomization. This is done by dividing the factors into sets, called tiers, based on the randomization and determining the crossing and nesting relationships between factors. The method is applied to formulate mixed models for a wide range of examples. We also describe the mixed model analysis of data from a three-phase experiment to investigate the effect of time of refinement on Eucalyptus pulp from four different sources. Cubic smoothing splines are used to describe differences in the trend over time and unstructured covariance matrices between times are found to be necessary.

On the use of correlated beta random variables with animal population modelling

We give reasons why demographic parameters such as survival and reproduction rates are often modelled well in stochastic population simulation using beta distributions. In practice, it is frequently expected that these parameters will be correlated, for example with survival rates for all age classes tending to be high or low in the same year. We therefore discuss a method for producing correlated beta random variables by transforming correlated normal random variables, and show how it can be applied in practice by means of a simple example. We also note how the same approach can be used to produce correlated uniform triangular, and exponential random variables. (C) 2008 Elsevier B.V. All rights reserved.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved

A Log-Linear Regression Model for the Beta-Weibull Distribution

We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

Development and In Vitro Evaluation of Propranolol Hydrochloride Controlled Release Tablets Using HPMC as Matrix Former

The purpose of this paper was to produce controlled-release matrices with 120 mg of propranolol hydrochloride (PHCl) employing hydroxypropyl methylcellulose (HPMC, Methocel (R) K100) as the gel forming barrier. Although this class of polymers has been commonly used for direct compression, with the intent of use reduced polymer concentrations to achieve controlled drug release, in this study tablets were produced by the wet granulation process. HPMC percentages ranged from 15-34 % and both soluble and non soluble diluents were tested in the 10 proposed tablet compositions. Dissolution testing of matrices was performed over a 12 h period in 1.2 pH medium (the first 2 h) and in pH 6.8 (10 h). Dissolution kinetic analysis was performed by applying Zero-order, First-order and Higuchi models with the aim of elucidating the drug release mechanism. All physical-chemical characteristics such as average weight, friability, hardness, diameter, height, and drug content were in accordance to the pharmacopeial specifications. Taking into account that PHCl is a very soluble drug, low concentrations (15 %) of HPMC were sufficient to reduce the drug release and to promote controlled release of PHCl, presenting good dissolution efficiencies, between 50 % and 63 %. The Higuchi model has presented the best fit to the 15 % HPMC formulations, indicating that the main release mechanism was diffusion. It could be concluded that the application of the wet granulation method reduced matrices erosion and promoted controlled release of the drug at low HPMC percentages.

Probing the electronic delocalization in a cyclic pyrazine ruthenium cluster hexamer

[Ru(3)O(CH(3)COO)(6)(pz)(CO)](6) is a cyclic hexamer species encompassing six triangular ruthenium cluster centers bridged by pyrazine ligands. The electronic communication among the cluster units strongly depends on their oxidation states, and has been successfully probed by means of cyclic voltammetry and UV-vis spectroelectrochemistry. (C) 2010 Elsevier B.V. All rights reserved.

Enantioselective Analysis of Fluoxetine and Norfluoxetine by LC in Culture Medium for Application in Biotransformation Studies Employing Fungi

A liquid chromatography method is described for the analysis of fluoxetine and norfluoxetine enantiomers in fungi cultures. The analytes were separated simultaneously by LC employing a serial system. The resolution was performed using a mobile phase of ethanol: 15 mM ammonium acetate buffer solution, pH 5.9: acetonitrile (77.5:17.5:5, v/v/v). UV detection was at 227 nm. Hexane: isoamyl alcohol (98:2, v/v) was used as extractor solvent. The calibration curves were linear over the concentration range of 12.5-3,750 ng mL(-1) (r a parts per thousand yen 0.996). The values for intra- and inter-day precision and accuracy were a parts per thousand currency sign10% for all analytes. The validated method was used to evaluate fluoxetine biotransformation to its mammalian metabolite, norfluoxetine, by selected endophytic fungi. Although the desired biotransformation was not observed in the conditions used here, the method could be used to evaluate the biotransformation of fluoxetine by other fungi or to be extended to other matrices with adequate procedures for sample preparation.

Interior under construction, Carpenter Hall house, Wilston, Brisbane

Triangular window openings to upper section of house.

One size doesn't fit all: Research methodologies in a language variation study of Sudanese teens

The research reported here draws on a study of five teenagers from a Dinka-speaking community of Sudanese settling in Australia. A range of factors including language proficiency, social network structure and language attitudes are examined as possible causes for the variability of language use. The results and discussion illustrate how the use of a triangular research approach captured the complexity of the participants' language situation and was critical to developing a full understanding of the interplay of factors influencing the teens' language maintenance and shift in a way that no single method could. Further, it shows that employment of different methodologies allowed for flexibility in data collection to ensure the fullest response from participants. Overall, this research suggests that for studies of non-standard communities, variability in research methods may prove more of a strength that the use of standardised instruments and approaches.

Half-Filled Layered Organic Superconductors and the Resonating-Valence-Bond Theory of the Hubbard-Heisenberg Model

We present a resonating-valence-bond theory of superconductivity for the Hubbard-Heisenberg model on an anisotropic triangular lattice. Our calculations are consistent with the observed phase diagram of the half-filled layered organic superconductors, such as the beta, beta('), kappa, and lambda phases of (BEDT-TTF)(2)X [bis(ethylenedithio)tetrathiafulvalene] and (BETS)(2)X [bis(ethylenedithio)tetraselenafulvalene]. We find a first order transition from a Mott insulator to a d(x)(2)-y(2) superconductor with a small superfluid stiffness and a pseudogap with d(x)(2)-y(2) symmetry.

Exact solution of the A(n-1)((1)) trigonometric vertex model with non-diagonal open boundaries

The A(n-1)((1)) trigonometric vertex model with generic non-diagonal boundaries is studied. The double-row transfer matrix of the model is diagonalized by algebraic Bethe ansatz method in terms of the intertwiner and the corresponding face-vertex relation. The eigenvalues and the corresponding Bethe ansatz equations are obtained.

Comparison of BR and QR Eigenvalue Algorithms for Power System Small Signal Stability Analysis

The BR algorithm is a novel and efficient method to find all eigenvalues of upper Hessenberg matrices and has never been applied to eigenanalysis for power system small signal stability. This paper analyzes differences between the BR and the QR algorithms with performance comparison in terms of CPU time based on stopping criteria and storage requirement. The BR algorithm utilizes accelerating strategies to improve its performance when computing eigenvalues of narrowly banded, nearly tridiagonal upper Hessenberg matrices. These strategies significantly reduce the computation time at a reasonable level of precision. Compared with the QR algorithm, the BR algorithm requires fewer iteration steps and less storage space without depriving of appropriate precision in solving eigenvalue problems of large-scale power systems. Numerical examples demonstrate the efficiency of the BR algorithm in pursuing eigenanalysis tasks of 39-, 68-, 115-, 300-, and 600-bus systems. Experiment results suggest that the BR algorithm is a more efficient algorithm for large-scale power system small signal stability eigenanalysis.

Matrix elements of U(2n) generators in a multishell spin-orbit basis. II. The two-shell nonzero shift ACCs and U(2n) generator MEs

This is the second in a series of articles whose ultimate goal is the evaluation of the matrix elements (MEs) of the U(2n) generators in a multishell spin-orbit basis. This extends the existing unitary group approach to spin-dependent configuration interaction (CI) and many-body perturbation theory calculations on molecules to systems where there is a natural partitioning of the electronic orbital space. As a necessary preliminary to obtaining the U(2n) generator MEs in a multishell spin-orbit basis, we must obtain a complete set of adjoint coupling coefficients for the two-shell composite Gelfand-Paldus basis. The zero-shift coefficients were obtained in the first article of the series. in this article, we evaluate the nonzero shift adjoint coupling coefficients for the two-shell composite Gelfand-Paldus basis. We then demonstrate that the one-shell versions of these coefficients may be obtained by taking the Gelfand-Tsetlin limit of the two-shell formulas. These coefficients,together with the zero-shift types, then enable us to write down formulas for the U(2n) generator matrix elements in a two-shell spin-orbit basis. Ultimately, the results of the series may be used to determine the many-electron density matrices for a partitioned system. (C) 1998 John Wiley & Sons, Inc.

Integrable multiparametric quantum spin chains

Using Reshetikhin's construction for multiparametric quantum algebras we obtain the associated multiparametric quantum spin chains. We show that under certain restrictions these models can be mapped to quantum spin chains with twisted boundary conditions, We illustrate how this general formalism applier; to construct multiparametric versions of the supersymmetric t-J and Li models.