Self-organized criticality in MHD driven plasma edge turbulence

We analyze long-range time correlations and self-similar characteristics of the electrostatic turbulence at the plasma edge and scrape-off layer in the Tokamak Chauffage Alfven Bresillien (TCABR), with low and high Magnetohydrodynamics (MHD) activity. We find evidence of self-organized criticality (SOC), mainly in the region near the tokamak limiter. Comparative analyses of data before and during the MHD activity reveals that during the high mHD activity the Hurst parameter decreases. Finally, we present a cellular automaton whose parameters are adjusted to simulate the analyzed turbulence SOC change with the MHD activity variation. (C) 2011 Published by Elsevier B.V.

HEALTH EDUCATION IN THE CARE TO CLIENTS OF THE BLOOD GLUCOSE SELF-MONITORING PROGRAM

This article reports, in a systemized and analytical way, the experience of an Outreach Program in the period between 2010 and 2011. The study focused on health education interventions as strategies to improve the adherence of individuals with insulin- dependent diabetes mellitus (IDDM), clients of a blood glucose self-Monitoring program. In addition, we intended to contribute to the reorganization of the program's working processes in the unit. Health education strategies were used in both educational groups and home visits, thus permitting the provision of care that was more individualized. Data regarding the clients were organized on a spreadsheet and in files for the Family Health teams, which made it easier to identify the patients, including those who were absent, helping to decentralize the care. By using health education strategies, we intended to contribute to a more comprehensive and emancipatory care of the clients, aimed at a continuous reflection of the workers regarding their practices.

Self-similarities of periodic structures for a discrete model of a two-gene system

We report self-similar properties of periodic structures remarkably organized in the two-parameter space for a two-gene system, described by two-dimensional symmetric map. The map consists of difference equations derived from the chemical reactions for gene expression and regulation. We characterize the system by using Lyapunov exponents and isoperiodic diagrams identifying periodic windows, denominated Arnold tongues and shrimp-shaped structures. Period-adding sequences are observed for both periodic windows. We also identify Fibonacci-type series and Golden ratio for Arnold tongues, and period multiple-of-three windows for shrimps. (C) 2012 Elsevier B.V. All rights reserved.

Self-assembled films from chitosan and poly(vinyl sulfonic acid) on Nafion® for direct methanol fuel cell

Chitosan/poly(vinyl sulfonic acid) (PVS) films have been prepared on Nafion® membranes by the layer-by-layer (LbL) method for use in direct methanol fuel cell (DMFC). Computational methods and Fourier transform infrared (FTIR) spectra suggest that an ionic pair is formed between the sulfonic group of PVS and the protonated amine group of chitosan, thereby promoting the growth of LbL films on the Nafion® membrane as well as partial blocking of methanol. Chronopotentiometry and potential linear scanning experiments have been carried out for investigation of methanol crossover through the Nafion® and chitosan/PVS/Nafion® membranes in a diaphragm diffusion cell. On the basis of electrical impedance measurements, the values of proton resistance of the Nafion® and chitosan/PVS/Nafion® membranes are close due to the small thickness of the LbL film. Thus, it is expected an improved DMFC performance once the additional resistance of the self-assembled film is negligible compared to the result associated with the decrease in the crossover effect.

Dynamic texture segmentation based on deterministic partially self-avoiding walks

Recently there has been a considerable interest in dynamic textures due to the explosive growth of multimedia databases. In addition, dynamic texture appears in a wide range of videos, which makes it very important in applications concerning to model physical phenomena. Thus, dynamic textures have emerged as a new field of investigation that extends the static or spatial textures to the spatio-temporal domain. In this paper, we propose a novel approach for dynamic texture segmentation based on automata theory and k-means algorithm. In this approach, a feature vector is extracted for each pixel by applying deterministic partially self-avoiding walks on three orthogonal planes of the video. Then, these feature vectors are clustered by the well-known k-means algorithm. Although the k-means algorithm has shown interesting results, it only ensures its convergence to a local minimum, which affects the final result of segmentation. In order to overcome this drawback, we compare six methods of initialization of the k-means. The experimental results have demonstrated the effectiveness of our proposed approach compared to the state-of-the-art segmentation methods.