Efeitos da terapia laser de baixa intensidade associada ao exercício aeróbio no reparo de tenotomia do tendão de aquiles de ratos diabéticos

Diabetes Mellitus (DM ) is a complex disease that requires continuous medical care for the reduction of risk factors in addition to glycemic control. The typical hyperglycemia of this disease produces glycosylation of proteins and so the consequence is the accumulation of glycosylation final products in various human tissues, among them, the tendon. The aerobic exercise (AE) and the low level laser therapy (LLLT) have been used to treat tendinopathies in individuals with or without DM. Objective: The aim of this study was to watch the effect of the LLLT and the AE, in association, in partial tenotomy of the tissue repair of the Achilles tendon (AT) of diabetic rats. Methods: 91 animals were utilized and divided in to the following groups: control group (GC), injured control group (GCL), diabetic group (GD), diabetic group LLLT (GD – TLBI), diabetic group trained (GD - EX) and diabetic group trained laser (GD-EX+TLBI). The animals were submitted to intervention with AE, using a protocol with a progressive increase of time (12 to 60 min) and speed of (4 to 9 m/min), and the LLLT (660 nm laser, 10mW, 4 J/cm², single point for 16 seconds, three times for week). It was analyzed morphological, biomechanical and molecular characteristics. For data showing normal distribution was used one-way ANOVA test and post hoc Tukey and data without normal distribution was used Mann Whitney test and post hoc Dunn's. It was accepted p <0.05 for statistical significance Results: The biomechanical tests indicated major improvement in the GC and GD-EX+TLBI groups when compared with the diabetic groups in the following variables: maximum load, strain, absorbed energy, stress, cross section area, elastic modulus and energy density (p<0.05). The analysis through molecular biology indicated that the association of aerobic exercise and LLLT generated an increase of the collagen I gene expression and modulated the expression of the MMP2 and MMP9 (p<0.05). No observed any major improvement in the morphological variable studied. Conclusion: the LLLT associated with aerobic exercise promotes and increase of the mechanical properties, in the control of collagen I gene expression and of the MMP2 and MMP9 of the diabetic rats.

Análise de métodos de predição de conforto térmico de habitação em clima quente-úmido com condicionamento passivo

The assessment of building thermal performance is often carried out using HVAC energy consumption data, when available, or thermal comfort variables measurements, for free-running buildings. Both types of data can be determined by monitoring or computer simulation. The assessment based on thermal comfort variables is the most complex because it depends on the determination of the thermal comfort zone. For these reasons, this master thesis explores methods of building thermal performance assessment using variables of thermal comfort simulated by DesignBuilder software. The main objective is to contribute to the development of methods to support architectural decisions during the design process, and energy and sustainable rating systems. The research method consists on selecting thermal comfort methods, modeling them in electronic sheets with output charts developed to optimize the analyses, which are used to assess the simulation results of low cost house configurations. The house models consist in a base case, which are already built, and changes in thermal transmittance, absorptance, and shading. The simulation results are assessed using each thermal comfort method, to identify the sensitivity of them. The final results show the limitations of the methods, the importance of a method that considers thermal radiance and wind speed, and the contribution of the chart proposed

Mapeamento acústico como ferramenta para predição de ruído urbano na área de influência do estádio Arena das Dunas, Natal/ RN

The Noise Pollution causes degradation in the quality of the environment and presents itself as one of the most common environmental problems in the big cities. An Urban environment present scenario and their complex acoustic study need to consider the contribution of various noise sources. Accordingly to computational models through mapping and prediction of acoustic scene become important, because they enable the realization of calculations, analyzes and reports, allowing the interpretation of satisfactory results. The study neighborhood is the neighborhood of Lagoa Nova, a central area of the city of Natal, which will undergo major changes in urban space due to urban mobility projects planned for the area around the stadium and the consequent changes of urban form and traffic. Thus, this study aims to evaluate the noise impact caused by road and morphological changes around the stadium Arena das Dunas in the neighborhood of Lagoa Nova, through on-site measurements and mapping using the computational model SoundPLAN year 2012 and the scenario evolution acoustic for the year 2017. For this analysis was the construction of the first acoustic mapping based on current diagnostic acoustic neighborhood, physical mapping, classified vehicle count and measurement of sound pressure level, and to build the prediction of noise were observed for the area study the modifications provided for traffic, urban form and mobility work. In this study, it is concluded that the sound pressure levels of the year in 2012 and 2017 extrapolate current legislation. For the prediction of noise were numerous changes in the acoustic scene, in which the works of urban mobility provided will improve traffic flow, thus reduce the sound pressure level where interventions are expected

Predição não-linear de curvas de produção de petróleo via redes neurais recursivas

One of the main activities in the petroleum engineering is to estimate the oil production in the existing oil reserves. The calculation of these reserves is crucial to determine the economical feasibility of your explotation. Currently, the petroleum industry is facing problems to analyze production due to the exponentially increasing amount of data provided by the production facilities. Conventional reservoir modeling techniques like numerical reservoir simulation and visualization were well developed and are available. This work proposes intelligent methods, like artificial neural networks, to predict the oil production and compare the results with the ones obtained by the numerical simulation, method quite a lot used in the practice to realization of the oil production prediction behavior. The artificial neural networks will be used due your learning, adaptation and interpolation capabilities