Use of a predictive model for food insecurity estimates in Brazil

In 2004 the National Household Survey (Pesquisa Nacional par Amostras de Domicilios - PNAD) estimated the prevalence of food and nutrition insecurity in Brazil. However, PNAD data cannot be disaggregated at the municipal level. The objective of this study was to build a statistical model to predict severe food insecurity for Brazilian municipalities based on the PNAD dataset. Exclusion criteria were: incomplete food security data (19.30%); informants younger than 18 years old (0.07%); collective households (0.05%); households headed by indigenous persons (0.19%). The modeling was carried out in three stages, beginning with the selection of variables related to food insecurity using univariate logistic regression. The variables chosen to construct the municipal estimates were selected from those included in PNAD as well as the 2000 Census. Multivariate logistic regression was then initiated, removing the non-significant variables with odds ratios adjusted by multiple logistic regression. The Wald Test was applied to check the significance of the coefficients in the logistic equation. The final model included the variables: per capita income; years of schooling; race and gender of the household head; urban or rural residence; access to public water supply; presence of children; total number of household inhabitants and state of residence. The adequacy of the model was tested using the Hosmer-Lemeshow test (p=0.561) and ROC curve (area=0.823). Tests indicated that the model has strong predictive power and can be used to determine household food insecurity in Brazilian municipalities, suggesting that similar predictive models may be useful tools in other Latin American countries.

Mixture of changing uniaxial micellar forms in lyotropic biaxial nematics

Lyotropic nematics consisting of surfactant-cosurfactant water solutions may present a biaxial phase or direct U(+) <-> U(-) transitions, in different regions of the temperature-relative concentration phase diagram, for different systems and compositions. We propose that these may be related to changes of uniaxial micellar form, which may occur either smoothly or abruptly. Smooth change of cylinder-like into disc-like shapes requires a distribution of Maier-Saupe interaction constants and we consider two limiting cases for the distribution of forms: a single Gaussian and a double Gaussian. Alternatively, an abrupt change of form is described by a discontinuous distribution of interaction constants. Our results show that the dispersive distributions yield a biaxial phase, while an abrupt change of shape leads to coexistence of uniaxial phases. Fitting the theory to the experiment for the ternary system KL/decanol/D2O leads to transition lines in very good agreement with experimental results. In order to rationalise the results of the comparison, we analyse temperature and concentration form dependence, which connects micellar and experimental macroscopic parameters. Physically consistent variations of micellar asymmetry, amphiphile partitioning and volume are obtained. To the best of the authors` knowledge, this is the first truly statistical microscopic approach that is able to model experimentally observed lyotropic biaxial nematic phases.

Lipid bilayer pre-transition as the beginning of the melting process

We investigate the bilayer pre-transition exhibited by some lipids at temperatures below their main phase transition, and which is generally associated to the formation of periodic ripples in the membrane. Experimentally we focus on the anionic lipid dipalmytoylphosphatidylglycerol (DPPG) at different ionic strengths, and on the neutral lipid dipalmytoylphosphatidylcholine (DPPC). From the analysis of differential scanning calorimetry traces of the two lipids we find that both pre- and main transitions are part of the same melting process. Electron spin resonance of spin labels and excitation generalized polarization of Laurdan reveal the coexistence of gel and fluid domains at temperatures between the pre- and main transitions of both lipids, reinforcing the first finding. Also, the melting process of DPPG at low ionic strength is found to be less cooperative than that of DPPC. From the theoretical side, we introduce a statistical model in which a next-nearest-neighbor competing interaction is added to the usual two-state model. For the first time, modulated phases (ordered and disordered lipids periodically aligned) emerge between the gel and fluid phases as a natural consequence of the competition between lipid-lipid interactions. (C) 2009 Elsevier B.V. All rights reserved.

Reaction mechanisms in the (6)Li+(59)Co system

The reactions induced by the weakly bound (6)Li projectile interacting with the intermediate mass target (59)Co were investigated. Light charged particles singles and alpha-d coincidence measurements were performed at the near barrier energies E(lab) = 17.4, 21.5, 25.5 and 29.6 MeV. The main contributions of the different competing mechanisms are discussed. A statistical model analysis. Continuum-Discretized Coupled-Channels (CDCC) calculations and two-body kinematics were used as tools to provide information to disentangle the main components of these mechanisms. A significant contribution of the direct breakup was observed through the difference between the experimental sequential breakup cross section and the CDCC prediction for the non-capture breakup cross section. (C) 2009 Elsevier B.V. All rights reserved.

Local influence in estimating equations

Local influence diagnostics based on estimating equations as the role of a gradient vector derived from any fit function are developed for repeated measures regression analysis. Our proposal generalizes tools used in other studies (Cook, 1986: Cadigan and Farrell, 2002), considering herein local influence diagnostics for a statistical model where estimation involves an estimating equation in which all observations are not necessarily independent of each other. Moreover, the measures of local influence are illustrated with some simulated data sets to assess influential observations. Applications using real data are presented. (C) 2010 Elsevier B.V. All rights reserved.

Optimization of the ultrasound-assisted synthesis of allyl 1-naphthyl ether using response surface methodology

Allyl 1-naphthyl ethers are useful compounds for different purposes, but reported methods to synthesize them require long reaction times. In this work, we have obtained allyl 1-naphthyl ether in good yield using ultrasonic-assisted methodology in a 1-h reaction. A central composite design was used to obtain a statistical model and a response surface (p < 0.05; R(2) = 0.970; R(adj)(2) = 0.949; R(pred)(2) = 0.818) that can predict the optimal conditions to maximize the yield, validated experimentally. (C) 2010 Elsevier B.V. All rights reserved.

Signed likelihood ratio tests in the Birnbaum-Saunders regression model

The Birnbaum-Saunders regression model is becoming increasingly popular in lifetime analyses and reliability studies. In this model, the signed likelihood ratio statistic provides the basis for testing inference and construction of confidence limits for a single parameter of interest. We focus on the small sample case, where the standard normal distribution gives a poor approximation to the true distribution of the statistic. We derive three adjusted signed likelihood ratio statistics that lead to very accurate inference even for very small samples. Two empirical applications are presented. (C) 2010 Elsevier B.V. All rights reserved.

An information-theoretic approach to statistical dependence: Copula information

We discuss the connection between information and copula theories by showing that a copula can be employed to decompose the information content of a multivariate distribution into marginal and dependence components, with the latter quantified by the mutual information. We define the information excess as a measure of deviation from a maximum-entropy distribution. The idea of marginal invariant dependence measures is also discussed and used to show that empirical linear correlation underestimates the amplitude of the actual correlation in the case of non-Gaussian marginals. The mutual information is shown to provide an upper bound for the asymptotic empirical log-likelihood of a copula. An analytical expression for the information excess of T-copulas is provided, allowing for simple model identification within this family. We illustrate the framework in a financial data set. Copyright (C) EPLA, 2009