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.

Dermaseptin 01 as antimicrobial peptide with rich biotechnological potential: study of peptide interaction with membranes containing Leishmania amazonensis lipid-rich extract and membrane models

This article addresses the interactions of the synthetic antimicrobial peptide dermaseptin 01 (GLWSTIKQKGKEAAIAAA-KAAGQAALGAL-NH(2), DS 01) with phospholipid (PL) monolayers comprising (i) a lipid-rich extract of Leishmania amazonensis (LRE-La), (ii) zwitterionic PL (dipalmitoylphosphatidylcholine, DPPC), and (iii) negatively charged PL (dipalmitoylphosphatidylglycerol, DPPG). The degree of interaction of DS 01 with the different biomembrane models was quantified from equilibrium and dynamic liquid-air interface parameters. At low peptide concentrations, interactions between DS 01 and zwitterionic PL, as well as with the LRE-La monolayers were very weak, whereas with negatively charged PLs the interactions were stronger. For peptide concentrations above 1 mu g/ml, a considerable expansion of negatively charged monolayers occurred. In the case of DPPC, it was possible to return to the original lipid area in the condensed phase, suggesting that the peptide was expelled from the monolayer. However, in the case of DPPG, the average area per lipid molecule in the presence of DS 01 was higher than pure PLs even at high surface pressures, suggesting that at least part of DS 01 remained incorporated in the monolayer. For the LRE-La monolayers, DS 01 also remained in the monolayer. This is the first report on the antiparasitic activity of AMPs using Langmuir monolayers of a natural lipid extract from L. amazonensis. Copyright (C) 2011 European Peptide Society and John Wiley & Sons, Ltd.

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.

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.

Data collapse, scaling functions, and analytical solutions of generalized growth models

We consider a nontrivial one-species population dynamics model with finite and infinite carrying capacities. Time-dependent intrinsic and extrinsic growth rates are considered in these models. Through the model per capita growth rate we obtain a heuristic general procedure to generate scaling functions to collapse data into a simple linear behavior even if an extrinsic growth rate is included. With this data collapse, all the models studied become independent from the parameters and initial condition. Analytical solutions are found when time-dependent coefficients are considered. These solutions allow us to perceive nontrivial transitions between species extinction and survival and to calculate the transition's critical exponents. Considering an extrinsic growth rate as a cancer treatment, we show that the relevant quantity depends not only on the intensity of the treatment, but also on when the cancerous cell growth is maximum.

Evaluation of Antiproliferative, Anti-Type 2 Diabetes, and Antihypertension Potentials of Ellagitannins from Strawberries (Fragaria x ananassa Duch.) Using In Vitro Models

Strawberries represent the main source of ellagic acid derivatives in the Brazilian diet, corresponding to more than 50% of all phenolic compounds found in the fruit. There is a particular interest in the determination of the ellagic acid content in fruits because of possible chemopreventive benefits. In the present study, the potential health benefits of purified ellagitannins from strawberries were evaluated in relation to the antiproliferative activity and in vitro inhibition of alpha-amylase, alpha-glucosidase, and angiotensin I-converting enzyme (ACE) relevant for potential management of hyperglycemia and hypertension. Therefore, a comparison among ellagic acid, purified ellagitannins, and a strawberry extract was done to evaluate the possible synergistic effects of phenolics. In relation to the antiproliferative activity, it was observed that ellagic acid had the highest percentage inhibition of cell proliferation. The strawberry extract had lower efficacy in inhibiting the cell proliferation, indicating that in the case of this fruit there is no synergism. Purified ellagitannins had high alpha-amylase and ACE inhibitory activities. However, these compounds had low alpha-glucosidase inhibitory activity. These results suggested that the ellagitannins and ellagic acid have good potential for the management of hyperglycemia and hypertension linked to type 2 diabetes. However, further studies with animal and human models are needed to advance the in vitro assay-based biochemical rationale from this study.

Effect of spatial inhomogeneity on the mapping between strongly interacting fermions and weakly interacting spins

A combined analytical and numerical study is performed of the mapping between strongly interacting fermions and weakly interacting spins, in the framework of the Hubbard, t-J, and Heisenberg models. While for spatially homogeneous models in the thermodynamic limit the mapping is thoroughly understood, we here focus on aspects that become relevant in spatially inhomogeneous situations, such as the effect of boundaries, impurities, superlattices, and interfaces. We consider parameter regimes that are relevant for traditional applications of these models, such as electrons in cuprates and manganites, and for more recent applications to atoms in optical lattices. The rate of the mapping as a function of the interaction strength is determined from the Bethe-Ansatz for infinite systems and from numerical diagonalization for finite systems. We show analytically that if translational symmetry is broken through the presence of impurities, the mapping persists and is, in a certain sense, as local as possible, provided the spin-spin interaction between two sites of the Heisenberg model is calculated from the harmonic mean of the onsite Coulomb interaction on adjacent sites of the Hubbard model. Numerical calculations corroborate these findings also in interfaces and superlattices, where analytical calculations are more complicated.

Failure analysis of low velocity impact on thin composite laminates: Experimental and numerical approaches

The dynamic behavior of composite laminates is very complex because there are many concurrent phenomena during composite laminate failure under impact load. Fiber breakage, delaminations, matrix cracking, plastic deformations due to contact and large displacements are some effects which should be considered when a structure made from composite material is impacted by a foreign object. Thus, an investigation of the low velocity impact on laminated composite thin disks of epoxy resin reinforced by carbon fiber is presented. The influence of stacking sequence and energy impact was investigated using load-time histories, displacement-time histories and energy-time histories as well as images from NDE. Indentation tests results were compared to dynamic results, verifying the inertia effects when thin composite laminate was impacted by foreign object with low velocity. Finite element analysis (FEA) was developed, using Hill`s model and material models implemented by UMAT (User Material Subroutine) into software ABAQUS (TM), in order to simulate the failure mechanisms under indentation tests. (C) 2007 Elsevier Ltd. All rights reserved.

Modeling and Analysis of Piezoelectric Energy Harvesting From Aeroelastic Vibrations Using the Doublet-Lattice Method

Multifunctional structures are pointed out as an important technology for the design of aircraft with volume, mass, and energy source limitations such as unmanned air vehicles (UAVs) and micro air vehicles (MAVs). In addition to its primary function of bearing aerodynamic loads, the wing/spar structure of an UAV or a MAV with embedded piezoceramics can provide an extra electrical energy source based on the concept of vibration energy harvesting to power small and wireless electronic components. Aeroelastic vibrations of a lifting surface can be converted into electricity using piezoelectric transduction. In this paper, frequency-domain piezoaeroelastic modeling and analysis of a canti-levered platelike wing with embedded piezoceramics is presented for energy harvesting. The electromechanical finite-element plate model is based on the thin-plate (Kirchhoff) assumptions while the unsteady aerodynamic model uses the doublet-lattice method. The electromechanical and aerodynamic models are combined to obtain the piezoaeroelastic equations, which are solved using a p-k scheme that accounts for the electromechanical coupling. The evolution of the aerodynamic damping and the frequency of each mode are obtained with changing airflow speed for a given electrical circuit. Expressions for piezoaeroelastically coupled frequency response functions (voltage, current, and electrical power as well the vibratory motion) are also defined by combining flow excitation with harmonic base excitation. Hence, piezoaeroelastic evolution can be investigated in frequency domain for different airflow speeds and electrical boundary conditions. [DOI:10.1115/1.4002785]

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

Renormalization of the S parameter in holographic models of electroweak symmetry breaking

We show that the S parameter is not finite in theories of electroweak symmetry breaking in a slice of anti-de Sitter five-dimensional space, with the light fermions localized in the ultraviolet. We compute the one-loop contributions to S from the Higgs sector and show that they are logarithmically dependent on the cutoff of the theory. We discuss the renormalization of S, as well as the implications for bounds from electroweak precision measurements on these models. We argue that, although in principle the choice of renormalization condition could eliminate the S parameter constraint, a more consistent condition would still result in a large and positive S. On the other hand, we show that the dependence on the Higgs mass in S can be entirely eliminated by the renormalization procedure, making it impossible in these theories to extract a Higgs mass bound from electroweak precision constraints.

Predicting random effects with an expanded finite population mixed model

Prediction of random effects is an important problem with expanding applications. In the simplest context, the problem corresponds to prediction of the latent value (the mean) of a realized cluster selected via two-stage sampling. Recently, Stanek and Singer [Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 119-130] developed best linear unbiased predictors (BLUP) under a finite population mixed model that outperform BLUPs from mixed models and superpopulation models. Their setup, however, does not allow for unequally sized clusters. To overcome this drawback, we consider an expanded finite population mixed model based on a larger set of random variables that span a higher dimensional space than those typically applied to such problems. We show that BLUPs for linear combinations of the realized cluster means derived under such a model have considerably smaller mean squared error (MSE) than those obtained from mixed models, superpopulation models, and finite population mixed models. We motivate our general approach by an example developed for two-stage cluster sampling and show that it faithfully captures the stochastic aspects of sampling in the problem. We also consider simulation studies to illustrate the increased accuracy of the BLUP obtained under the expanded finite population mixed model. (C) 2007 Elsevier B.V. All rights reserved.