Exact Search Directions for Optimization of Linear and Nonlinear Models Based on Generalized Orthonormal Functions

A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.

Numerical prediction of three-dimensional time-dependent viscoelastic extrudate swell using differential and algebraic models

This study investigates the numerical simulation of three-dimensional time-dependent viscoelastic free surface flows using the Upper-Convected Maxwell (UCM) constitutive equation and an algebraic explicit model. This investigation was carried out to develop a simplified approach that can be applied to the extrudate swell problem. The relevant physics of this flow phenomenon is discussed in the paper and an algebraic model to predict the extrudate swell problem is presented. It is based on an explicit algebraic representation of the non-Newtonian extra-stress through a kinematic tensor formed with the scaled dyadic product of the velocity field. The elasticity of the fluid is governed by a single transport equation for a scalar quantity which has dimension of strain rate. Mass and momentum conservations, and the constitutive equation (UCM and algebraic model) were solved by a three-dimensional time-dependent finite difference method. The free surface of the fluid was modeled using a marker-and-cell approach. The algebraic model was validated by comparing the numerical predictions with analytic solutions for pipe flow. In comparison with the classical UCM model, one advantage of this approach is that computational workload is substantially reduced: the UCM model employs six differential equations while the algebraic model uses only one. The results showed stable flows with very large extrudate growths beyond those usually obtained with standard differential viscoelastic models. (C) 2010 Elsevier Ltd. All rights reserved.

Sampling, WLS, and Mixed Models

Mixed models may be defined with or without reference to sampling, and can be used to predict realized random effects, as when estimating the latent values of study subjects measured with response error. When the model is specified without reference to sampling, a simple mixed model includes two random variables, one stemming from an exchangeable distribution of latent values of study subjects and the other, from the study subjects` response error distributions. Positive probabilities are assigned to both potentially realizable responses and artificial responses that are not potentially realizable, resulting in artificial latent values. In contrast, finite population mixed models represent the two-stage process of sampling subjects and measuring their responses, where positive probabilities are only assigned to potentially realizable responses. A comparison of the estimators over the same potentially realizable responses indicates that the optimal linear mixed model estimator (the usual best linear unbiased predictor, BLUP) is often (but not always) more accurate than the comparable finite population mixed model estimator (the FPMM BLUP). We examine a simple example and provide the basis for a broader discussion of the role of conditioning, sampling, and model assumptions in developing inference.

Peritrophic membrane role in enhancing digestive efficiency Theoretical and experimental models

The pentrophic membrane (PM) is an anatomical structure surrounding the food bolus in most insects. Rejecting the idea that PM has evolved from coating mucus to play the same protective role as it, novel functions were proposed and experimentally tested. The theoretical principles underlying the digestive enzyme recycling mechanism were described and used to develop an algorithm to calculate enzyme distributions along the midgut and to infer secretory and absorptive sites. The activity of a Spodoptera frugiperda microvillar aminopeptidase decreases by 50% if placed in the presence of midgut contents. S. frugiperda trypsin preparations placed into dialysis bags in stirred and unstirred media have activities of 210 and 160%, respectively, over the activities of samples in a test tube. The ectoperitrophic fluid (EF) present in the midgut caeca of Rhynchosciara americana may be collected. If the enzymes restricted to this fluid are assayed in the presence of PM contents (PMC) their activities decrease by at least 58%. The lack of PM caused by calcofluor feeding impairs growth due to an increase in the metabolic cost associated with the conversion of food into body mass. This probably results from an increase in digestive enzyme excretion and useless homeostatic attempt to reestablish destroyed midgut gradients. The experimental models support the view that PM enhances digestive efficiency by: (a) prevention of non-specific binding of undigested material onto cell Surface; (b) prevention of excretion by allowing enzyme recycling powered by an ectoperitrophic counterflux of fluid; (c) removal from inside PM of the oligomeric molecules that may inhibit the enzymes involved in initial digestion; (d) restriction of oligomer hydrolases to ectoperitrophic space (ECS) to avoid probable partial inhibition by non-dispersed undigested food. Finally,PM functions are discussed regarding insects feeding on any diet. (C) 2008 Elsevier Ltd. All rights reserved.

EXACT AND QUASI-EXACT MODELS OF STRANGE STARS

We construct and compare in this work a variety of simple models for strange stars, namely, hypothetical self-bound objects made of a cold stable version of the quark-gluon plasma. Exact, quasi-exact and numerical models are examined to find the most economical description for these objects. A simple and successful parametrization of them is given in terms of the central density, and the differences among the models are explicitly shown and discussed. In particular, we present a model starting with a Gaussian ansatz for the density profile that provides a very accurate and almost complete analytical integration of the problem, modulo a small difference for one of the metric potentials.

Bayesian analysis and constraints on kinematic models from union SNIa

The kinematic expansion history of the universe is investigated by using the 307 supernovae type Ia from the Union Compilation set. Three simple model parameterizations for the deceleration parameter ( constant, linear and abrupt transition) and two different models that are explicitly parametrized by the cosmic jerk parameter ( constant and variable) are considered. Likelihood and Bayesian analyses are employed to find best fit parameters and compare models among themselves and with the flat Lambda CDM model. Analytical expressions and estimates for the deceleration and cosmic jerk parameters today (q(0) and j(0)) and for the transition redshift (z(t)) between a past phase of cosmic deceleration to a current phase of acceleration are given. All models characterize an accelerated expansion for the universe today and largely indicate that it was decelerating in the past, having a transition redshift around 0.5. The cosmic jerk is not strongly constrained by the present supernovae data. For the most realistic kinematic models the 1 sigma confidence limits imply the following ranges of values: q(0) is an element of [-0.96, -0.46], j(0) is an element of [-3.2,-0.3] and z(t) is an element of [0.36, 0.84], which are compatible with the Lambda CDM predictions, q(0) = -0.57 +/- 0.04, j(0) = -1 and z(t) = 0.71 +/- 0.08. We find that even very simple kinematic models are equally good to describe the data compared to the concordance Lambda CDM model, and that the current observations are not powerful enough to discriminate among all of them.

Continuum, Discrete, and Explicit Solvation Models for Describing the Low-Lying Absorption Spectrum of the Pterin Acid in Aqueous Environment

The absorption spectrum of the acid form of pterin in water was investigated theoretically. Different procedures using continuum, discrete, and explicit models were used to include the solvation effect on the absorption spectrum, characterized by two bands. The discrete and explicit models used Monte Carlo simulation to generate the liquid structure and time-dependent density functional theory (B3LYP/6-31G+(d)) to obtain the excitation energies. The discrete model failed to give the correct qualitative effect on the second absorption band. The continuum model, in turn, has given a correct qualitative picture and a semiquantitative description. The explicit use of 29 solvent molecules, forming a hydration shell of 6 angstrom, embedded in the electrostatic field of the remaining solvent molecules, gives absorption transitions at 3.67 and 4.59 eV in excellent agreement with the S(0)-S(1) and S(0)-S(2) absorption bands at of 3.66 and 4.59 eV, respectively, that characterize the experimental spectrum of pterin in water environment. (C) 2010 Wiley Periodicals, Inc. Int J Quantum Chem 110: 2371-2377, 2010

Extraction of free fatty acids from peanut oil and avocado seed oil: Liquid-liquid equilibrium data at 298.2 K

The present paper reports phase equilibrium experimental data for two systems composed by peanut oil or avocado seed oil + commercial oleic acid + ethanol + water at 298.2 K and different water contents in the solvent. The addition of water to the solvent reduces the loss of neutral oil in the alcoholic phase and improves the solvent selectivity. The experimental data were correlated by the NRTL and UNIQUAC models. The global deviations between calculated and experimental values were 0.63 % and 1.08 %, respectively, for the systems containing avocado seed oil. In the case of systems containing peanut oil those deviations were 0.65 % and 0.98 %, respectively. Such results indicate that both models were able to reproduce correctly the experimental data, although the NRTL model presented a better performance.

Effect of chemical treatment on the mechanical properties, water vapour permeability and sorption isotherms of gelatin-based films

Proteins contain hydrophilic groups, which can bind to water molecules through hydrogen bridges, resulting in water vapour adsorption. An increase in the degree of cross-linking can be a method to improve the cohesiveness force and functional properties of protein-based films. Thus, the objective of this work was to evaluate the effect of chemical treatment of gelatin with formaldehyde and glyoxal on the mechanical properties, water vapour permeability (WVP) and water vapour sorption characteristics of gelatin-based films. Films were produced using gelatin, with and without chemical treatment. The formaldehyde treatments caused a significant increase in the tensile strength and a reduction in the WVP of films. The Guggenheim-Anderson-De Boer and Halsey models could be used to model the sorption isotherms of films. It was observed that an increase in temperature produced a decrease in water sorption, and the chemical modifications did not affect the monolayer moisture content. Copyright (c) 2007 John Wiley & Sons, Ltd.

DENSITY PROFILE, VELOCITY ANISOTROPY, AND LINE-OF-SIGHT EXTERNAL CONVERGENCE OF SLACS GRAVITATIONAL LENSES

Data from 58 strong-lensing events surveyed by the Sloan Lens ACS Survey are used to estimate the projected galaxy mass inside their Einstein radii by two independent methods: stellar dynamics and strong gravitational lensing. We perform a joint analysis of these two estimates inside models with up to three degrees of freedom with respect to the lens density profile, stellar velocity anisotropy, and line-of-sight (LOS) external convergence, which incorporates the effect of the large-scale structure on strong lensing. A Bayesian analysis is employed to estimate the model parameters, evaluate their significance, and compare models. We find that the data favor Jaffe`s light profile over Hernquist`s, but that any particular choice between these two does not change the qualitative conclusions with respect to the features of the system that we investigate. The density profile is compatible with an isothermal, being sightly steeper and having an uncertainty in the logarithmic slope of the order of 5% in models that take into account a prior ignorance on anisotropy and external convergence. We identify a considerable degeneracy between the density profile slope and the anisotropy parameter, which largely increases the uncertainties in the estimates of these parameters, but we encounter no evidence in favor of an anisotropic velocity distribution on average for the whole sample. An LOS external convergence following a prior probability distribution given by cosmology has a small effect on the estimation of the lens density profile, but can increase the dispersion of its value by nearly 40%.

Palaeomagnetism, rock magnetism and AMS of the Cabo Magmatic Province, NE Brazil, and the opening of South Atlantic

P>Reconstruction of the South Atlantic opening has long been a matter of debate and several models have been proposed. One problem in tracing properly the Atlantic history arises from the existence of a long interval without geomagnetic reversals, the Cretaceous Normal Superchron, for which ages are difficult to assign. Palaeomagnetism may help in addressing this issue if high-quality palaeomagnetic poles are available for the two drifting continental blocks, and if precise absolute ages are available. In this work we have investigated the Cabo Magmatic Province, northeastern Brazil, recently dated at 102 +/- 1 Ma (zircon fission tracks, Ar39/Ar40). All volcanic and plutonic rocks showed stable thermal and AF demagnetization patterns, and exhibit primary magnetic signatures. AMS data also support a primary origin for the magnetic fabric and is interpreted to be contemporaneous of the rock formation. The obtained pole is located at 335.9 degrees E/87.9 degrees S (N = 24; A(95) = 2.5; K = 138) and satisfies modern quality criteria, resulting in a reference pole for South America at similar to 100 Ma. This new pole also gives an insight to test and discuss the kinematic models currently proposed for the South Atlantic opening during mid-Cretaceous.

Major gene and multifactorial inheritance of mandibular prognathism

Mandibular prognathism typically shows familial aggregation. Various genetic models have been described and it is assumed to be a multifactorial and polygenic trait, with a threshold for expression. Our goal was to examine specific genetic models of the familial transmission of this trait. The study sample comprised of 2,562 individuals from 55 families. Complete family histories for each proband were ascertained and the affection status of relatives were confirmed by lateral cephalograms, photographs, and dental models. Pedigrees were drawn using PELICAN and complex segregation analysis was performed using POINTER. Parts of some pedigrees were excluded to create one founder pedigrees, so the total N was 2,050. Analysis showed more affected females than males (P = 0.030). The majority of the pedigrees suggest autosomal dominant inheritance. Incomplete penetrance was demonstrated by the ratio of affected/unaffected parents and siblings. The heritability of mandibular prognathism was estimated to be 0.316. We conclude that there is a major gene that influences the expression of mandibular prognathism with clear signs of Mendelian inheritance and a multifactorial component. (C) 2007 Wiley-Liss, Inc.

A vaccine against S. pyogenes: Design and experimental immune response

Streptococcus pyogenes causes severe invasive infections: the post-streptococcal sequelae of acute rheumatic fever (RF) and rheumatic heart disease (RHD), acute glomerulonephritis, and uncomplicated pharyngitis and pyoderma. Efforts to produce a vaccine against S. pyogenes began several decades ago, and different models have been proposed. Here, we describe the methodology used in the development of a new vaccine model, consisting of both T and B protective epitopes constructed as synthetic peptides and recombinant proteins. Two adjuvants were tested in an experimental inbred mouse model: a classical Freund`s adjuvant and a new adjuvant (AFCo1) that induces mucosal immune responses and is obtained by calcium precipitation of a proteoliposome derived from the outer membrane of Neisseria meningitides B. The StreptInCor vaccine epitope co-administrated with AFCo1 adjuvant induced mucosal (IgA) and systemic (IgG) antibodies as preferential Th1-mediated immune responses. No autoimmune reactions were observed, suggesting that the vaccine epitope is safe. (c) 2009 Elsevier Inc. All rights reserved.

Transformed generalized linear models

The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the rth moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin er al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214-223]. The usefulness of these models is illustrated in a Simulation study and in applications to three real data sets. (C) 2009 Elsevier B.V. All rights reserved.

Transformed symmetric models

For the first time, we introduce a class of transformed symmetric models to extend the Box and Cox models to more general symmetric models. The new class of models includes all symmetric continuous distributions with a possible non-linear structure for the mean and enables the fitting of a wide range of models to several data types. The proposed methods offer more flexible alternatives to Box-Cox or other existing procedures. We derive a very simple iterative process for fitting these models by maximum likelihood, whereas a direct unconditional maximization would be more difficult. We give simple formulae to estimate the parameter that indexes the transformation of the response variable and the moments of the original dependent variable which generalize previous published results. We discuss inference on the model parameters. The usefulness of the new class of models is illustrated in one application to a real dataset.