Enhancing the oxidative stability of rice crackers by addition of the ethanolic extract of phytochemicals from Cratoxylum formosum Dyer

Craloxylum formosum Dyer is consumed throughout the year as food and medicine in Thailand. It contains large amounts of chlorogenic acid and quinic acid derivatives. The antioxidative activity of the extract was studied in refined soybean oil coating on rice crackers without any seasoning. They were stored in accelerated oxidation conditions at 40 degrees C, 80% relative humidity (RH) in the dark for 18 days. The oxidative state of each sample was monitored by analyzing of the peroxide value (PV) and thiobarbituric acid reactive substances (TBARS) as well as by odor analysis by quantitative descriptive analysis (QDA). The C formosum extract was more effective than alpha-tocopherol due to metal ions present in the crackers, which resulted in alpha-tocopherol being less effective as an antioxidant. Sensory odor attributes of rice crackers were related more closely to TBARS than to PV values by linear regression analysis. The present study indicated that C. formosum extract was a promising source of a natural food antioxidant and was effective in inhibiting lipid oxidation in rice crackers.

The effect of free Ca2+ on the heat stability and other characteristics of low-heat skim milk powder

Low-heat skim milk powder (SMP), reconstituted to 25% total solids, was found to have poor heat stability. This could be improved by reducing the free Ca2+ concentration to 1.14 mm, or lower, by the addition of either Amberlite IR-120 ion-exchange resin in its sodium form or tri-sodium citrate in skim milk prior to evaporation and spray drying. Reduction in Ca2+ concentration was accompanied by increases in pH, particle size, and kinematic viscosity, and by a reduction in zeta-potential and changes in colour. In-container sterilisation of the reconstituted powder increased particle size, zeta-potential, kinematic viscosity and a* and b* values. However. Ca2+ concentration, pH and whiteness decreased. This study elucidated the importance of Ca2+ concentration and pH on heat stability of low-heat SMP, suggesting that Ca2+ concentration and pH in bulk milk are useful indicators for ensuring that spray dried milk powder has good heat stability. (C) 2009 Elsevier Ltd. All rights reserved.

Extensional rheology and stability of gas cell walls in bread doughs at elevated temperatures in relation to breadmaking performance

The rheological properties of gas cell walls in bread doughs are considered to be important in relation to their stability and gas retention during proof and baking. Large deformation rheological properties of gas cell walls were measured using biaxial extension for a number of doughs of varying breadmaking quality at constant strain rate and elevated temperatures of 25-60degreesC. Strain hardening and failure strain of cell walls both decreased with temperature, with cell walls in good breadmaking doughs remaining stable and retaining their strain hardening properties at higher temperatures (60degreesC), while the cell walls of poor breadmaking doughs became unstable at lower temperatures (45-50degreesC) and had lower strain hardening. Strain hardening measured at 50degreesC gave good correlations with baking volume, with the best correlations achieved between rheological measurements and baking tests that used similar mixing conditions. As predicted by the considered failure criterion, a strain hardening value of I defines a region below which gas cell walls become unstable, and discriminates well between the baking quality of a range of commercial flour blends of varying quality. This indicates that the stability of gas cell walls during baking is strongly related to strain hardening properties, and that extensional rheological measurements can be used as indicators of baking quality.

Effect of pH on the antimicrobial activity and oxidative stability of oil-in-water emulsions containing caffeic acid

Antioxidant properties in food are dependent on various parameters. These include the pH value and interactions with food components, including proteins or metal ions. food components affect antioxidant stability and also influence the properties of microorganisms and their viability. This paper describes an investigation of the effect of pH on the antioxidant and antibacterial properties of caffeic acid in different media. The pH values studied, using an oil-in-water emulsion as model system, were 3, 5 (with and without phosphate buffer), and 9. Effects of mixtures of caffeic acid, bovine serum albumin (BSA), and Fe (III) on oxidative deterioration in the emulsion samples were studied. The results show that the antioxidant activity of caffeic acid was increased by the presence of BSA. This effect was pH dependent and was affected by the presence of iron Ions. Antibacterial properties were also pH dependent. The minimum concentration of caffeic acid required to inhibit some microorganisms in the pH range of 5 to 7 was determined. A concentration of 0.41% (w/w) caffeic acid was enough to inhibit the growth of some of the studied microorganisms in the pH range of 5 to 7. However, near-neutral pH concentrations higher than 0.4% were needed to inhibit some microorganisms, including Listeria monocytogenes, E. coli, and Staphylococcus aureus, in the medium.

Systematic distortions of perceptual stability investigated using immersive virtual reality

Using an immersive virtual reality system, we measured the ability of observers to detect the rotation of an object when its movement was yoked to the observer's own translation. Most subjects had a large bias such that a static object appeared to rotate away from them as they moved. Thresholds for detecting target rotation were similar to those for an equivalent speed discrimination task carried out by static observers, suggesting that visual discrimination is the predominant limiting factor in detecting target rotation. Adding a stable visual reference frame almost eliminated the bias. Varying the viewing distance of the target had little effect, consistent with observers underestimating distance walked. However, accuracy of walking to a briefly presented visual target was high and not consistent with an underestimation of distance walked. We discuss implications for theories of a task-independent representation of visual space. © 2005 Elsevier Ltd. All rights reserved.

Stability criteria for the contextual emergence of macrostates in neural networks

More than thirty years ago, Amari and colleagues proposed a statistical framework for identifying structurally stable macrostates of neural networks from observations of their microstates. We compare their stochastic stability criterion with a deterministic stability criterion based on the ergodic theory of dynamical systems, recently proposed for the scheme of contextual emergence and applied to particular inter-level relations in neuroscience. Stochastic and deterministic stability criteria for macrostates rely on macro-level contexts, which make them sensitive to differences between different macro-levels.

Robust identification for linear-in-the-parameters models

In this paper new robust nonlinear model construction algorithms for a large class of linear-in-the-parameters models are introduced to enhance model robustness, including three algorithms using combined A- or D-optimality or PRESS statistic (Predicted REsidual Sum of Squares) with regularised orthogonal least squares algorithm respectively. A common characteristic of these algorithms is that the inherent computation efficiency associated with the orthogonalisation scheme in orthogonal least squares or regularised orthogonal least squares has been extended such that the new algorithms are computationally efficient. A numerical example is included to demonstrate effectiveness of the algorithms. Copyright (C) 2003 IFAC.

Robust classification of SAR imagery

In this work the G(A)(0) distribution is assumed as the universal model for amplitude Synthetic Aperture (SAR) imagery data under the Multiplicative Model. The observed data, therefore, is assumed to obey a G(A)(0) (alpha; gamma, n) law, where the parameter n is related to the speckle noise, and (alpha, gamma) are related to the ground truth, giving information about the background. Therefore, maps generated by the estimation of (alpha, gamma) in each coordinate can be used as the input for classification methods. Maximum likelihood estimators are derived and used to form estimated parameter maps. This estimation can be hampered by the presence of corner reflectors, man-made objects used to calibrate SAR images that produce large return values. In order to alleviate this contamination, robust (M) estimators are also derived for the universal model. Gaussian Maximum Likelihood classification is used to obtain maps using hard-to-deal-with simulated data, and the superiority of robust estimation is quantitatively assessed.

Robust background model for pixel based people counting using a single uncalibrated camera

Several pixel-based people counting methods have been developed over the years. Among these the product of scale-weighted pixel sums and a linear correlation coefficient is a popular people counting approach. However most approaches have paid little attention to resolving the true background and instead take all foreground pixels into account. With large crowds moving at varying speeds and with the presence of other moving objects such as vehicles this approach is prone to problems. In this paper we present a method which concentrates on determining the true-foreground, i.e. human-image pixels only. To do this we have proposed, implemented and comparatively evaluated a human detection layer to make people counting more robust in the presence of noise and lack of empty background sequences. We show the effect of combining human detection with a pixel-map based algorithm to i) count only human-classified pixels and ii) prevent foreground pixels belonging to humans from being absorbed into the background model. We evaluate the performance of this approach on the PETS 2009 dataset using various configurations of the proposed methods. Our evaluation demonstrates that the basic benchmark method we implemented can achieve an accuracy of up to 87% on sequence ¿S1.L1 13-57 View 001¿ and our proposed approach can achieve up to 82% on sequence ¿S1.L3 14-33 View 001¿ where the crowd stops and the benchmark accuracy falls to 64%.