Lycopene from two food sources does not affect antioxidant or cholesterol status of middle-aged adults

Background

Epidemiological studies have reported associations between reduced cardiovascular disease and diets rich in tomato and/or lycopene. Intervention studies have shown that lycopene-containing foods may reduce cholesterol levels and lipid peroxidation, factors implicated in the initiation of cardiovascular disease. The objective of this study was to determine whether consumption of lycopene rich foods conferred cardiovascular protection to middle-aged adults as indicated by plasma lipid concentrations and measures of ex vivo antioxidants.

Methods

Ten healthy men and women consumed a low lycopene diet with no added lycopene (control treatment) or supplemented with watermelon or tomato juice each containing 20 mg lycopene. Subjects consumed each treatment for three weeks in a crossover design. Plasma, collected weekly was analyzed for total cholesterol, high density lipoprotein cholesterol (HDL-C) and triglyceride concentrations and for the antioxidant biomarkers of malondialdehyde formation products (MDA), plasma glutathione peroxidase (GPX) and ferric reducing ability of plasma (FRAP). Data were analyzed using Proc Mixed Procedure and associations between antioxidant and lipid measures were identified by Pearson's product moment correlation analysis.

Results

Compared to the control diet, the lycopene-containing foods did not affect plasma lipid concentrations or antioxidant biomarkers. Women had higher total cholesterol, HDL-C and triglyceride concentrations than did the men. Total cholesterol was positively correlated to MDA and FRAP while HDL-C was positively correlated to MDA and GPX. GPX was negatively correlated to triglyceride concentration.

Conclusions

The inclusion of watermelon or tomato juice containing 20 mg lycopene did not affect plasma lipid concentrations or antioxidant status of healthy subjects. However, plasma cholesterol levels impacted the results of MDA and FRAP antioxidant tests.     

Crystal plasticity investigation of friction effect on texture evolution of Al single crystal during ECAP

A crystal plasticity finite element model has been developed to study the effect of friction between the die wall and the billet on texture evolution during equal channel angular pressing of an aluminum single crystal. Four cases with different coefficients of friction μ = 0, 0.05, 0.1, and 0.15 have been simulated. It has been found that the friction of μ = 0.05 and 0.1 can capture the major texture features shown in the experimental results, and μ = 0.05 predicts a slightly better texture than μ = 0.1. The frictional condition significantly affects texture evolution in the region between 1/2 and 3/4 of the billet thickness from the top surface. It can be attributed to the effect of friction on the corner gap and the distribution of stresses in the die corner.     

Intelligent wavelet fuzzy brain emotional controller using dual function-link network for uncertain nonlinear control systems

This study aims to propose a more efficient hybrid algorithm to achieve favorable control performance for uncertain nonlinear systems. The proposed algorithm comprises a dual function-link network-based multilayer wavelet fuzzy brain emotional controller and a sign(.) functional compensator. The proposed algorithm estimates the judgment and emotion of a brain that includes two fuzzy inference systems for the amygdala network and the prefrontal cortex network via using a dual-function-link network and three sub-structures. Three sub-structures are a dual-function-link network, an amygdala network, and a prefrontal cortex network. Particularly, the dual-function-link network is used to adjust the amygdala and orbitofrontal weights separately so that the proposed algorithm can efficiently reduce the tracking error, follow the reference signal well, and achieve good performance. A Lyapunov stability function is used to determine the adaptive laws, which are used to efficiently tune the system parameters online. Simulation and experimental studies for an antilock braking system and a magnetic levitation system are presented to verify the effectiveness and advantage of the proposed algorithm.

     

Wavelet CMAC for MIMO uncertain nonlinear systems using a modified social ski-driver algorithm

This study uses a Mexican hat wavelet membership function for a cerebellar model articulation controller (CMAC) to develop a more efficient adaptive controller for multiple input multiple output (MIMO) uncertain nonlinear systems. The main controller is called the adaptive Mexican hat wavelet CMAC (MWCMAC), and an auxiliary controller is used to remove the residual error. For the MWCMAC, the online learning laws are derived from the gradient descent method. In addition, the learning rate values are very important and have a great impact on the performance of the control system; however, they are difficult to choose accurately. Therefore, a modified social ski driver (SSD) algorithm is proposed to find optimal learning rates for the control parameters. Finally, a magnetic ball levitation system and a nine-link biped robot are used to illustrate the effectiveness of the proposed SSD-based MWCMAC control system. The comparisons with other existing control algorithms have shown the superiority of the proposed control system.     

Hierarchical ATPG for analog circuits and systems

Automatic test-pattern generation (ATPG) algorithms for analog circuits have been under intense investigation for the last several years. As system design aggressively moves to system-on-a-chip (SoC) and core-based integration, hierarchical analog ATPG emerges as an even more difficult challenge. Attempts to develop an effective algorithm have had varying degrees of success. This article reviews some fundamental issues and recent work in hierarchical analog ATPG and presents an algorithm based on controllability and observability computation. This algorithm has been implemented in a prototype tool, and results based on several case studies show the application of the technique     

Practical issues on the projection of polyhedral sets

Projection of polyhedral sets is a fundamental operation in both geometry and symbolic computation. In most cases, however, it is not practically feasible to generate projections as the size of the output can be exponential in the size of the input. Even when the size of the output is manageable, we still face two serious problems: overwhelming redundancy and degeneracy. Here, we address these problems from a practical point of view. We discuss three algorithms based on algebraic and geometric techniques and we compare their performance in order to assess the feasibility of these approaches.     

On Deciding Readiness and Failure Equivalences for Processes

In this paper, we study the complexity of deciding readiness and failure equivalences for finite state processes and recursively defined processes specified by normed context-free grammars (CFGs) in Greibach normal form (GNF). The results are as follows: (1) Readiness and failure equivalences for processes specified by normed GNF CFGs are both undecidable. For this class of processes, the regularity problem with respect to failure or readiness equivalence is also undecidable. Moreover, all these undecidability results hold even for locally unary processes. In the unary case, these problems become decidable. In fact, they are Π^p₂-complete, We also show that with respect to bisimulation equivalence, the regularity for processes specified by normed GNF CFGs is NL-complete. (2) Readiness and failure equivalences for finite state processes are PSPACE-complete. This holds even for locally unary finite state processes. These two equivalences are co-NP-complete for unary finite state processes. Further, for acyclic finite state processes, readiness and failure equivalences are co-NP-complete and they are NL-complete in the unary case. (3) For finite tree processes, we show that finite trace, readiness, and failure equivalences are all L-complete. Further, the results remain true for the unary case. Our results provide a complete characterization of the computational complexity of deciding readiness and failure equivalences for several important classes of processes.     

A Two-Step Certified Reduced Basis Method

In this paper we introduce a two-step Certified Reduced Basis (RB) method. In the first step we construct from an expensive finite element “truth” discretization of dimension N{mathcal{N}} an intermediate RB model of dimension N << NNll {mathcal{N}}. In the second step we construct from this intermediate RB model a derived RB (DRB) model of dimension M≤N. The construction of the DRB model is effected at cost O(N){mathcal{O}}(N) and in particular at cost independent of N{mathcal{N}}; subsequent evaluation of the DRB model may then be effected at cost O(M){mathcal{O}}(M). The DRB model comprises both the DRB output and a rigorous a posteriori error bound for the error in the DRB output with respect to the truth discretization.