Equilibrium and dynamic swelling of polyacrylates

Polyacrylates were prepared by solution polymerization of partially neutralized acrylic acid at 37°C. The swelling behavior of the polyacrylates was examined using equilibrium and dynamic swelling studies. Equilibrium swelling studies in deionized water were used to determine the molecular weight between crosslinks using the Flory-Rehner theory. The amount of crosslinking agent incorporated into the network was a function of the nominal crosslinking ratio. Dynamic swelling studies in saline solutions were used to investigate the initial swelling rate for the polyacrylates. Swelling studies of the polyacrylates in saline solutions under load were used to elucidate the degree of swelling under load, the compliance, and sample elasticity.     

Stability of emulsions formulated with high concentrations of sodium caseinate and trehalose

Stability of emulsions formulated with 10 wt.% oil (concentrated fish oil, CFO, sunflower oil, SFO, or olive oil, OO), sodium caseinate concentrations varying from 0.5 to 5 wt.%, giving oil-to-protein ratios of 20–2, and 0, 20, 30 or 40 wt.% aqueous trehalose solution was studied by Turbiscan. Particle size distribution, microstructure, and small angle X-ray scattering (SAXS) patterns were also obtained. The main mechanism of destabilization in a given formulation strongly depended on oil-to-protein ratio. As evidenced by the BS-profile changes with time, emulsions formulated with 0.5 and 1 wt.% NaCas destabilized mainly by creaming while for the 2 wt.% NaCas concentration, both creaming and flocculation mechanisms, were involved. The main destabilization mechanism for the 3, 4 or 5 wt.% NaCas emulsions was flocculation. Stability of emulsions was also affected by the content of trehalose in the aqueous phase. Trehalose diminished the volume-weighted mean diameter (D_4,3) and greatly improved stability.     

Global stability of adaptive pole placement algorithms

This paper presents direct and indirect adaptive control schemes for assigning the closed-loop poles of a single-input, single-output system in both the continuous- and discrete-time cases. The resulting closed-loop system is shown to be globally stable when driven by an external reference signal consisting of a sum of sinusoids. In particular, persistent excitation of the potentially unbounded closed-loop input-output data, and hence convergence of a sequential least-squares identification algorithm is proved. The results are applicable to standard sequential least squares, and least squares with covariance reset.     

Effect of Aqueous Phase Composition on Stability of Sodium Caseinate/Sunflower oil Emulsions

The aim of the present work was to investigate the effect of aqueous phase composition on the stability of emulsions formulated with 10 wt% sunflower oil as fat phase. Aqueous phase was formulated with 0.5, 2, or 5 wt% sodium caseinate, or sodium caseinate with the addition of two different hydrocolloids, xanthan gum or locust bean gum, both at 0.3 or 0.5 wt% level or sodium caseinate or with addition of 20 wt% sucrose. Emulsions were processed by Ultra-Turrax and then further homogenized by ultrasound. Creaming and flocculation kinetics were quantified by analyzing the samples with a Turbiscan MA 2000. Emulsions were also analyzed for particle size distribution, microstructure, viscosity, and dynamic surface properties. The most stable systems of all selected in the present work were the 0.3 or 0.5 wt% XG or 0.5 wt% LBG/0.5 wt% NaCas coarse emulsion and the 20 wt% sucrose/5 wt% NaCas fine emulsion. Surprisingly, coarse emulsions with the lower concentration of NaCas, which had greater D _4,3, were more stable than fine emulsions when the aqueous phase contained XG or LBG. In these conditions, the overall effect was less negative bulk interactions between hydrocolloids and sodium caseinate, which led to stability. Sugar interacted in a positive way, both in bulk and at the interface sites, producing more stable systems for small-droplet high-protein-concentration emulsions. This study shows the relevance of components interactions in microstructure and stability of caseinate emulsions.     

Controllability of the Impulsive Semilinear Heat Equation with Memory and Delay

For many control systems in real life, impulses and delays are intrinsic properties that do not modify their controllability. So we conjecture that under certain conditions the abrupt changes and delays as perturbations of a system do not modify certain properties such as controllability. In other words, the controllability is robust by looking the impulses and delays as perturbations. In this regard, in this paper, we prove the interior approximate controllability of the Impulsive Semilinear Heat Equation with Memory and Delay. This is done by employing A.E. Bashirov and at. technique which avoids fixed point theorems. In this case, the delay helps us to prove the approximate controllability by pulling back the control solution to a fixed curve in a short time interval.     

Examining relationships between anxiety and dangerous driving

Driving anxiety that has developed following crashes has been studied relatively frequently, but anxiety per se and its effects on driving has not as yet garnered much attention in the literature. The current study included 1121 participants and found higher levels of general anxiety were related to a wide variety of dangerous driving behaviors. While there were clear and expected sex differences on many dangerous driving variables, there were still more such differences with regard to anxiety levels and independent of sex, higher levels of anxiety were associated with greater levels of dangerous driving. Of particular import, it was found that the high anxiety group had caused significantly more crashes and engaged in more DUI episodes than the low and/or medium anxiety groups. Taken as a whole, the results suggest there is a tremendous need for more research in the area of anxiety and dangerous driving and that interventions for highly anxious drivers may well be warranted.     

Effects of Medial Septal Lesions on Action-Outcome Associations in Rats Under Conditions of Delayed Reinforcement.

In operant tasks, control rats maintain high response rates under positive contingencies, when the probability of reinforcement is greater following a response (contingent reinforcement) than during the absence of that response. However, as contingencies approach zero, response rates decrease. In this experiment, under immediate contingent reinforcement, rats with medial septal lesions reduced their response rates, just like controls, when contingencies were shifted from positive toward zero. However, the septal rats were less sensitive to this contingency shift, compared with controls, when there was a 5-s delay between lever presses and contingent reinforcements. This lesion effect appeared to be due to a failure of voluntary response memory, which impaired sensitivity to operant contingencies when there was a delay between action and outcome. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Bayes smoothing algorithms for segmentation of binary images modeled by markov random fields

A new image segmentation algorithm is presented, based on recursive Bayes smoothing of images modeled by Markov random fields and corrupted by independent additive noise. The Bayes smoothing algorithm yields the a posteriori distribution of the scene value at each pixel, given the total noisy image, in a recursive way. The a posteriori distribution together with a criterion of optimality then determine a Bayes estimate of the scene. The algorithm presented is an extension of a 1-D Bayes smoothing algorithm to 2-D and it gives the optimum Bayes estimate for the scene value at each pixel. Computational concerns in 2-D, however, necessitate certain simplifying assumptions on the model and approximations on the implementation of the algorithm. In particular, the scene (noiseless image) is modeled as a Markov mesh random field, a special class of Markov random fields, and the Bayes smoothing algorithm is applied on overlapping strips (horizontal/vertical) of the image consisting of several rows (columns). It is assumed that the signal (scene values) vector sequence along the strip is a vector Markov chain. Since signal correlation in one of the dimensions is not fully used along the edges of the strip, estimates are generated only along the middle sections of the strips. The overlapping strips are chosen such that the union of the middle sections of the strips gives the whole image. The Bayes smoothing algorithm presented here is valid for scene random fields consisting of multilevel (discrete) or continuous random variables.