The renin-angiotensin system is modulated by swimming training depending on the age of spontaneously hypertensive rats

Aim: To investigate the effects of swimming training on the renin-angiotensin system (RAS) during the development of hypertensive disease. Main methods: Male spontaneously hypertensive rats (SHR) were randomized into: sedentary young (SY), trained young (TV), sedentary adult (SA), and trained adult (TA) groups. Swimming was performed 5 times/wk/8wks. Key findings: Trained young and adult rats showed both decreased systolic and mean blood pressure, and bradycardia after the training protocol. The left ventricular hypertrophy (LVH) was observed only in the TA group (12.7%), but there was no increase on the collagen volume fraction. Regarding the components of the RAS, TV showed lower activity and gene expression of angiotensinogen (AGT) compared to SY. The TA group showed lower activity of circulatory RAS components, such as decreased serum ACE activity and plasma renin activity compared to SA. However, depending on the age, although there were marked differences in the modulation of the RAS by training, both trained groups showed a reduction in circulating angiotensin II levels which may explain the lower blood pressure in both groups after swimming training. Significance: Swimming training regulates the RAS differently in adult and young SHR rats. Decreased local cardiac RAS may have prevented the LVH exercise-induced in the TV group. Both groups decreased serum angiotensin II content, which may, at least in part, contribute to the lowering blood pressure effect of exercise training. (C) 2011 Elsevier Inc. All rights reserved.

Relation of genetic phylogeny and geographical distance of tick-borne encephalitis virus in central Europe

Tick-borne encephalitis virus (TBEV) is the most important arboviral agent causing disease of the central nervous system in central Europe. In this study, 61 TBEV E gene sequences derived from 48 isolates from the Czech Republic, and four isolates and nine TBEV strains detected in ticks from Germany, covering more than half a century from 1954 to 2009, were sequenced and subjected to phylogenetic and Bayesian phylodynamic analysis to determine the phylogeography of TBEV in central Europe. The general Eurasian continental east-to-west pattern of the spread of TBEV was confirmed at the regional level but is interlaced with spreading that arises because of local geography and anthropogenic influence. This spread is reflected by the disease pattern in the Czech Republic that has been observed since 1991. The overall evolutionary rate was estimated to be approximately 8x10(-4) substitutions per nucleotide per year. The analysis of the TBEV E genes of 11 strains isolated at one natural focus in Zd`ar Kaplice proved for the first time that TBEV is indeed subject to local evolution.

Genetic Algorithm for the Determination of Linear Viscoelastic Relaxation Spectrum from Experimental Data

Conventional procedures employed in the modeling of viscoelastic properties of polymer rely on the determination of the polymer`s discrete relaxation spectrum from experimentally obtained data. In the past decades, several analytical regression techniques have been proposed to determine an explicit equation which describes the measured spectra. With a diverse approach, the procedure herein introduced constitutes a simulation-based computational optimization technique based on non-deterministic search method arisen from the field of evolutionary computation. Instead of comparing numerical results, this purpose of this paper is to highlight some Subtle differences between both strategies and focus on what properties of the exploited technique emerge as new possibilities for the field, In oder to illustrate this, essayed cases show how the employed technique can outperform conventional approaches in terms of fitting quality. Moreover, in some instances, it produces equivalent results With much fewer fitting parameters, which is convenient for computational simulation applications. I-lie problem formulation and the rationale of the highlighted method are herein discussed and constitute the main intended contribution. (C) 2009 Wiley Periodicals, Inc. J Appl Polym Sci 113: 122-135, 2009

Grid job scheduling using Route with Genetic Algorithm support

In 2006 the Route load balancing algorithm was proposed and compared to other techniques aiming at optimizing the process allocation in grid environments. This algorithm schedules tasks of parallel applications considering computer neighborhoods (where the distance is defined by the network latency). Route presents good results for large environments, although there are cases where neighbors do not have an enough computational capacity nor communication system capable of serving the application. In those situations the Route migrates tasks until they stabilize in a grid area with enough resources. This migration may take long time what reduces the overall performance. In order to improve such stabilization time, this paper proposes RouteGA (Route with Genetic Algorithm support) which considers historical information on parallel application behavior and also the computer capacities and load to optimize the scheduling. This information is extracted by using monitors and summarized in a knowledge base used to quantify the occupation of tasks. Afterwards, such information is used to parameterize a genetic algorithm responsible for optimizing the task allocation. Results confirm that RouteGA outperforms the load balancing carried out by the original Route, which had previously outperformed others scheduling algorithms from literature.

A Genetic Algorithm for Solar Boat

Genetic algorithm has been widely used in different areas of optimization problems. Ithas been combined with renewable energy domain, photovoltaic system, in this thesis.To participate and win the solar boat race, a control program is needed and C++ hasbeen chosen for programming. To implement the program, the mathematic model hasbeen built. Besides, the approaches to calculate the boundaries related to conditionhave been explained. Afterward, the processing of the prediction and real time controlfunction are offered. The program has been simulated and the results proved thatgenetic algorithm is helpful to get the good results but it does not improve the resultstoo much since the particularity of the solar driven boat project such as the limitationof energy production

University Scheduling using Genetic Algorithm

The automated timetabling and scheduling is one of the hardest problem areas. This isbecause of constraints and satisfying those constraints to get the feasible and optimizedschedule, and it is already proved as an NP Complete (1) [1]. The basic idea behind this studyis to investigate the performance of Genetic Algorithm on general scheduling problem underpredefined constraints and check the validity of results, and then having comparative analysiswith other available approaches like Tabu search, simulated annealing, direct and indirectheuristics [2] and expert system. It is observed that Genetic Algorithm is good solutiontechnique for solving such problems and later analysis will prove this argument. The programis written in C++ and analysis is done by using variation in various parameters.

The Pollination Biology and Mating System of a Peripheral Population of Witheringia solanacea (Solanaceae)

Pollinator visitation rates over the life of a flower are determined by pollinator abundance and floral longevity. If flowers are not visited frequently enough, pollen limitation may occur, favoring the evolution of self-compatibility (SC). In plant species with varying SC levels, central populations often are self-incompatible (SI) and peripheral populations are SC. Witheringia solanacea (Solanaceae) is a species that follows this trend with the exception of one population in the Monteverde Cloud Forest Reserve, which is peripheral yet SI. I investigated this population using multiple techniques including floral bagging, pollinator observations, microsatellite analysis, and floral longevity manipulations. My results confirmed the self-incompatibility of the Monteverde population and indicated low but perhaps adequate rates of pollinator visitation per flower per hour. I found reduced genetic diversity at Monteverde and gene flow occurring unidirectionally from San Luis (a central population) to Monteverde. In the greenhouse, there was more of an effect of male than female function on floral longevity, but the largest differences were environmental. Flowers stayed open substantially longer when cool, cloudy weather was simulated and shorter when conditions were hot and sunny. The results indicate that the Monteverde population of W. solanacea is SI because 1) it is unable to maximize its fitness due to gene flow from San Luis and its relatively recent colonization of the area and 2) pollen limitation may not be severe because of supplemental pollinator availability from other Witheringia species in the area and increased floral longevities due to cool and cloudy conditions.

Multi-Objective Pipe Smoothing Genetic Algorithm For Water Distribution Network Design

This paper describes the formulation of a Multi-objective Pipe Smoothing Genetic Algorithm (MOPSGA) and its application to the least cost water distribution network design problem. Evolutionary Algorithms have been widely utilised for the optimisation of both theoretical and real-world non-linear optimisation problems, including water system design and maintenance problems. In this work we present a pipe smoothing based approach to the creation and mutation of chromosomes which utilises engineering expertise with the view to increasing the performance of the algorithm whilst promoting engineering feasibility within the population of solutions. MOPSGA is based upon the standard Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and incorporates a modified population initialiser and mutation operator which directly targets elements of a network with the aim to increase network smoothness (in terms of progression from one diameter to the next) using network element awareness and an elementary heuristic. The pipe smoothing heuristic used in this algorithm is based upon a fundamental principle employed by water system engineers when designing water distribution pipe networks where the diameter of any pipe is never greater than the sum of the diameters of the pipes directly upstream resulting in the transition from large to small diameters from source to the extremities of the network. MOPSGA is assessed on a number of water distribution network benchmarks from the literature including some real-world based, large scale systems. The performance of MOPSGA is directly compared to that of NSGA-II with regard to solution quality, engineering feasibility (network smoothness) and computational efficiency. MOPSGA is shown to promote both engineering and hydraulic feasibility whilst attaining good infrastructure costs compared to NSGA-II.

Genetic associations between age at first calving and heifer body weight and scrotal circumference in Nelore cattle

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Mating system of a population of Myracrodruon urundeuva F.F. & M.F. Allemão using the fAFLP molecular marker

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Selection strategies for dairy buffaloes: economic and genetic consequences

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bayesian inference in genetic parameter estimation of visual scores in Nellore beef-cattle

The aim of this study was to estimate the components of variance and genetic parameters for the visual scores which constitute the Morphological Evaluation System (MES), such as body structure (S), precocity (P) and musculature (M) in Nellore beef-cattle at the weaning and yearling stages, by using threshold Bayesian models. The information used for this was gleaned from visual scores of 5,407 animals evaluated at the weaning and 2,649 at the yearling stages. The genetic parameters for visual score traits were estimated through two-trait analysis, using the threshold animal model, with Bayesian statistics methodology and MTGSAM (Multiple Trait Gibbs Sampler for Animal Models) threshold software. Heritability estimates for S, P and M were 0.68, 0.65 and 0.62 (at weaning) and 0.44, 0.38 and 0.32 (at the yearling stage), respectively. Heritability estimates for S, P and M were found to be high, and so it is expected that these traits should respond favorably to direct selection. The visual scores evaluated at the weaning and yearling stages might be used in the composition of new selection indexes, as they presented sufficient genetic variability to promote genetic progress in such morphological traits.

Genetic diversity and population structure of pumas (Puma concolor) in southeastern Brazil: implications for conservation in a human-dominated landscape

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genetic parameters and relationships between growth traits and scrotal circumference measured at different ages in Nellore cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A fuzzy logic system applied in lightning models

This paper describes a novel approach for mapping lightning processes using fuzzy logic. The estimation process is carried out using a fuzzy system based on Sugeno's architecture. Simulation results confirm that proposed approach can be efficiently used in these types of problem.