Intervention Based Exclusively on Stage- Matched Printed EducationalMaterials Regarding Healthy Eating Does Not Result in Changes to Adolescents' Dietary Behavior

Purpose. To assess the impact of a six-month stage-based intervention on fruit and vegetable intake, regarding perceived benefits and barriers, and self-efficacy among adolescents. Design. Randomized treatment-control, pre-post design. Subjects/ Setting. Schools were randomized between control and experimental groups. 860 adolescents from ten public schools in Bras ' ilia, Federal District, Brazil were evaluated at baseline; 771 (81%) completed the study. Intervention. Experimental group received monthly magazines and newsletters aimed at promotion of healthy eating. Measures. Self-reported fruit and vegetable intake, stages of change, self-efficacy and decisional balance scores were evaluated at baseline and post-intervention in both groups. Analysis. The effectiveness of the intervention was evaluated using the analysis of covariance model (ANCOVA) and repeated measurement analysis by means of weighted least squares. Comparison between the proportions of adolescents who advanced through the stages during the intervention was performed using the Mantel-Haenszel chi-square test. Results. After adjusting for sex and age, study variables showed no modifications through the proposed intervention. There was no statistical difference in participant mobility in the intervention and control groups between the stages of change, throughout the study. Conclusion. A nutritional intervention based exclusively on distribution of stage-matched printed educational materials was insufficient to change adolescents' dietary behavior.

Analog circuit synthesis performing fast Pareto frontier exploration and analysis through 3D graphs

This paper presents a technique for performing analog design synthesis at circuit level providing feedback to the designer through the exploration of the Pareto frontier. A modified simulated annealing which is able to perform crossover with past anchor points when a local minimum is found which is used as the optimization algorithm on the initial synthesis procedure. After all specifications are met, the algorithm searches for the extreme points of the Pareto frontier in order to obtain a non-exhaustive exploration of the Pareto front. Finally, multi-objective particle swarm optimization is used to spread the results and to find a more accurate frontier. Piecewise linear functions are used as single-objective cost functions to produce a smooth and equal convergence of all measurements to the desired specifications during the composition of the aggregate objective function. To verify the presented technique two circuits were designed, which are: a Miller amplifier with 96 dB Voltage gain, 15.48 MHz unity gain frequency, slew rate of 19.2 V/mu s with a current supply of 385.15 mu A, and a complementary folded cascode with 104.25 dB Voltage gain, 18.15 MHz of unity gain frequency and a slew rate of 13.370 MV/mu s. These circuits were synthesized using a 0.35 mu m technology. The results show that the method provides a fast approach for good solutions using the modified SA and further good Pareto front exploration through its connection to the particle swarm optimization algorithm.

Design methodology of piezoelectric energy-harvesting skin using topology optimization

Abstract This paper describes a design methodology for piezoelectric energy harvester s that thinly encapsulate the mechanical devices and expl oit resonances from higher- order vibrational modes. The direction of polarization determines the sign of the pi ezoelectric tensor to avoid cancellations of electric fields from opposite polarizations in the same circuit. The resultant modified equations of state are solved by finite element method (FEM). Com- bining this method with the solid isotropic material with penalization (SIMP) method for piezoelectric material, we have developed an optimization methodology that optimizes the piezoelectric material layout and polarization direc- tion. Updating the density function of the SIMP method is performed based on sensitivity analysis, the sequen- tial linear programming on the early stage of the opti- mization, and the phase field method on the latter stage