685 research outputs found
Clustering of risk factors for chronic diseases among adolescents from Southern Brazil
AbstractObjectiveTo investigate the clustering of risk behaviors for chronic non-communicable diseases and their associated factors among adolescents from Southern Brazil.MethodsIn 2008, a survey was conducted with 3990 adolescents aged 14–15years (mean: 14.3; SD: 0.6) from the 1993 Pelotas Birth Cohort Study. Clustering was determined by comparing observed (O) and expected (E) prevalence of all possible combinations of the four risk factors investigated (smoking, alcohol intake, low fruit intake, and physical inactivity). We carried out Poisson regression to evaluate the effect of individual characteristics on the presence of at least three risk behaviors.ResultsAll risk factors tended to cluster together (O/E prevalence=3.0), especially smoking and alcohol intake (odds ratio to present on behavior in the presence of other >5.0). Approximately 15% of adolescents displayed three or more risk behaviors. Females (adjusted OR=1.55), people 15years and older (OR=1.47), with black skin color (OR=1.23), and of low socioeconomic level (OR=1.29) were more likely to display three or more risk factors.ConclusionThese findings suggest that lifestyle-related risk factors tend to cluster among adolescents. Identifying subgroups at greater risk of simultaneously engaging in multiple risk behaviors may aid in the planning of preventive strategies
ESBMC-Jimple: Verifying Kotlin Programs via Jimple Intermediate Representation
In this work, we describe and evaluate the first model checker for verifying
Kotlin programs through the Jimple intermediate representation. The verifier,
named ESBMC-Jimple, is built on top of the Efficient SMT-based Context-Bounded
Model Checker (ESBMC). It uses the Soot framework to obtain the Jimple IR,
representing a simplified version of the Kotlin source code, containing a
maximum of three operands per instruction. ESBMC-Jimple processes Kotlin source
code together with a model of the standard Kotlin libraries and checks a set of
safety properties. Experimental results show that ESBMC-Jimple can correctly
verify a set of Kotlin benchmarks from the literature and that it is
competitive with state-of-the-art Java bytecode verifiers. A demonstration is
available at https://youtu.be/J6WhNfXvJNc.Comment: ACM SIGSOFT International Symposium on Software Testing and Analysis
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Chemerin receptor blockade improves vascular function in diabetic obese mice via redox-sensitive- and Akt-dependent pathways
Chemerin and its G protein-coupled receptor [chemerin receptor 23 (ChemR23)] have been associated with endothelial dysfunction, inflammation, and insulin resistance. However, the role of chemerin on insulin signaling in the vasculature is still unknown. We aimed to determine whether chemerin reduces vascular insulin signaling and whether there is interplay between chemerin/ChemR23, insulin resistance, and vascular complications associated with type 2 diabetes (T2D). Molecular and vascular mechanisms were probed in mesenteric arteries and cultured vascular smooth muscle cells (VSMCs) from C57BL/6J, nondiabetic lean db/m, and diabetic obese db/db mice as well as in human microvascular endothelial cells (HMECs). Chemerin decreased insulin-induced vasodilatation in C57BL/6J mice, an effect prevented by CCX832 (ChemR23 antagonist) treatment. In VSMCs, chemerin, via oxidative stress- and ChemR23-dependent mechanisms, decreased insulin-induced Akt phosphorylation, glucose transporter 4 translocation to the membrane, and glucose uptake. In HMECs, chemerin decreased insulin-activated nitric oxide signaling. AMP-activated protein kinase phosphorylation was reduced by chemerin in both HMECs and VSMCs. CCX832 treatment of db/db mice decreased body weight, insulin, and glucose levels as well as vascular oxidative stress. CCX832 also partially restored vascular insulin responses in db/db and high-fat diet-fed mice. Our novel in vivo findings highlight chemerin/ChemR23 as a promising therapeutic target to limit insulin resistance and vascular complications associated with obesity-related diabetes
KINEMATIC ANALYSIS OF VOLLEYBALL SPIKE
Volleyball nowadays is, after soccer, the most practiced sport in Brazil (Bojikian, 2004). However, studies related to the patterns used by the athletes during training are not in common use, especially those aiming to help the coach detect failures. Our goal was to compare the kinematic pattern of the volleyball spike performed by three female athletes of the Sport Club Pinheiros who played as outside hitters. The analysed variables were: ankle, knee and elbow angles during the last step and jump, and the maximum height attained during the jump
INFLUENCE OF THE TYPE OF OXIDANT IN THE COMBUSTION OF NATURAL GAS INSIDE AN ALUMINUM MELTING FURNACE
ABSTRACT The fuel used as energy source for aluminum melting is of extreme importance for a better performance of the process. However, the type of oxidant can also lead to better performance, leading to a greater preservation of the equipments. Air is more abundant and cheaper, however due to the presence of nitrogen, there is undesirable NOx formation. An alternative is to employ pure oxygen. Although it is more expensive, it can lead to a cleaner and much more efficient combustion process, by significantly altering the combustion aspects inside the furnace, such as the shape of the flame and the distribution of temperature and heat flux. In the present work, numerical simulations were carried out using the commercial package FLUENT, analyzing different cases with pure oxygen and air as the oxidant for the combustion of natural gas. The results showed the possible damages caused by the process if long or too intense and concentrated flames are present. Copyright © 2006 by ASME 2 INTRODUCTION There are several industrial combustion applications which may benefit from the use of oxygen-enriched air or pure oxygen as the oxidizer during the combustion process. The resulting effects are many. Oxygen enrichment increases the flame temperature, promotes oxidation, and can lead to smaller pollutant (NOx) emissions compared with hydrocarbon-air systems, due to the absence of nitrogen. The formation of nitrogen oxides (NOx) in air-feed combustion systems represents a significant source for this pollutant within the industrial sector. With the increase in the world-wide utilization of fossil fuels, the control of NOx emissions has become an issue of global concern. Additionally, with increasing oil prices, the use of lower quality fuels will worsen the problem. Advances in computational modeling tools and the increased performance of computers have made comprehensive modeling of NOx formation and destruction a valuable tool to provide insights and understanding of the NOx reaction processes in combustion systems. This technology has the potential to enhance the application of various combustion techniques used to reduce NOx emissions from practical combustion systems Numerical modeling has became an important tool in the design and optimization of industrial equipments and also in the prediction of the emission of pollutants such as CO (carbon monoxide), SOx (sulfur oxides), and NOx. Recently, several numerical studies In the work by Frassoldati et al. [2], the attention was focused on a new procedure, based on CFD, for the determination of NOx emissions from combustion processes, which allowed the use of very detailed reaction schemes. The predictions of NOx were obtained by post-processing the flow and temperature fields, as predicted by the CFD model, and lumping together computational cells similar in terms of NOx formation. The resulting macro-cells were assumed to be a network of ideal reactors, which were simulated adopting detailed kinetic mechanisms. Nieckele et al. [3] described a numerical simulation of the 100% oxy-firing combustion process inside an industrial aluminum re-melting reverb furnace. Three different configurations were analyzed including the comparison between the staged versus non-staged combustion processes. The numerical procedure was based on the finite volume formulation and the κ−ε model of turbulence. The combustion was modeled based on the finite rate models of Arrhenius and Magnussen, and the Discrete Transfer Radiation model was employed for predicting the radiation heat transfer. The numerical predictions allowed for the determination of the flame patterns, species concentration distribution, temperature and velocity fields
Upregulation of Nrf2 and decreased redox signaling contribute to renoprotective effects of chemerin receptor blockade in diabetic mice
Chemerin, acting through its receptor ChemR23, is an adipokine associated with inflammatory response, glucose and lipid metabolism and vascular function. Although this adipokine has been associated with the development and progression of kidney disease, it is not clear whether the chemerin/ChemR23 system plays a role in renal function in the context of diabetes. Therefore, we sought to determine whether ChemR23 receptor blockade prevents the development and/or progression of diabetic nephropathy and questioned the role of oxidative stress and Nrf2 in this process. Renal redox state and function were assessed in non-diabetic lean db/m and diabetic obese db/db mice treated with vehicle or CCX832 (ChemR23 antagonist). Renal reactive oxygen species (ROS) production, which was increased in diabetic mice, was attenuated by CCX832. This was associated with an increase in Nox 4 expression. Augmented protein oxidation in db/db mice was not observed when mice were treated with CCX832. CCX832 also abrogated impaired Nrf2 nuclear activity and associated downregulation in antioxidants expression in kidneys from db/db mice. Our in vivo findings highlight the role of the redox signaling and Nrf2 system as renoprotective players during chemerin receptor blockade in diabetic mice. The chemerin/ChemR23 system may be an important target to limit renal dysfunction associated with obesity-related diabetes
COVERED DISTANCES OF HANDBALL PLAYERS OBTAINED BY AN AUTOMATIC TRACKING METHOD
The aim of this work is to obtain the distances covered by handball players and their velocities during a match using a new approach based on automatic tracking method described in Figueroa et. al. (2006a, 2006b) and the Adaboost detector (Okuma, 2004). A whole game of a Brazilian regional handball championship for players under age of 21 was recorded. Applying the mentioned automatic tracking, the accumulated covered distances and the velocities were calculated for all the players. The results of average covered distances (±SD) in the 1st and 2 nd halves were 2199(±230) and 2453(±214). The results of covered distances and the velocities allow individual and collective analyses of the players by the team staff. The proposed method revealed to be a powerful tool to improve physical analysis of the handball players
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