Genetic data of 15 autosomal STR loci: an analysis of the Araraquara population colonization (São Paulo, Brazil)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Isolation and characterization of Wharton's jelly-derived multipotent mesenchymal stromal cells obtained from bovine umbilical cord and maintained in a defined serum-free three-dimensional system

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

Selection of alfalfa cultivars adapted for tropical environments with repeated measures using PROC MIXED of SAS (R) System

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

Epidemiology and genetics of endemic goiter. II. Genetic aspects

Complex genetic models and segregation analysis were applied to family data obtained in a hyperendemic goiter area in Brazil. The single locus and Falconer's models did not fit the data. Edward's model showed convergency, but statistical concordance has not been obtained. Although the genetic load model explains statistically the family data, it would be hard to imagine that endemic goiter could be explained by a model where synergism among genetic and environmental factors is not assumed.

Combining genetic algorithm and simulated annealing: A molecular geometry optimization study

We introduce a new hybrid approach to determine the ground state geometry of molecular systems. Firstly, we compared the ability of genetic algorithm (GA) and simulated annealing (SA) to find the lowest energy geometry of silicon clusters with six and 10 atoms. This comparison showed that GA exhibits fast initial convergence, but its performance deteriorates as it approaches the desired global extreme. Interestingly, SA showed a complementary convergence pattern, in addition to high accuracy. Our new procedure combines selected features from GA and SA to achieve weak dependence on initial parameters, parallel search strategy, fast convergence and high accuracy. This hybrid algorithm outperforms GA and SA by one order of magnitude for small silicon clusters (Si6 and Si10). Next, we applied the hybrid method to study the geometry of a 20-atom silicon cluster. It was able to find an original geometry, apparently lower in energy than those previously described in literature. In principle, our procedure can be applied successfully to any molecular system. © 1998 Elsevier Science B.V.

VAr planning using genetic algorithm and linear programming

A combined methodology consisting of successive linear programming (SLP) and a simple genetic algorithm (SGA) solves the reactive planning problem. The problem is divided into operating and planning subproblems; the operating subproblem, which is a nonlinear, ill-conditioned and nonconvex problem, consists of determining the voltage control and the adjustment of reactive sources. The planning subproblem consists of obtaining the optimal reactive source expansion considering operational, economical and physical characteristics of the system. SLP solves the optimal reactive dispatch problem related to real variables, while SGA is used to determine the necessary adjustments of both the binary and discrete variables existing in the modelling problem. Once the set of candidate busbars has been defined, the program implemented gives the location and size of the reactive sources needed, if any, to maintain the operating and security constraints.

Defects location in power systems components through a dedicated genetic algorithm

In this work the problem of defects location in power systems is formulated through a binary linear programming (BLP) model based on alarms historical database of control and protection devices from the system control center, sets theory of minimal coverage (AI) and protection philosophy adopted by the electric utility. In this model, circuit breaker operations are compared to their expected states in a strictly mathematical manner. For solving this BLP problem, which presents a great number of decision variables, a dedicated Genetic Algorithm (GA), is proposed. Control parameters of the GA, such as crossing over and mutation rates, population size, iterations number and population diversification, are calibrated in order to obtain efficiency and robustness. Results for a test system found in literature, are presented and discussed. © 2004 IEEE.

Interactive system for placement and coordination of overcurrent protective devices

In this paper, an expert and interactive system for developing protection system for overhead and radial distribution feeders is proposed. In this system the protective devices can be allocated through heuristic and an optimized way. In the latter one, the placement problem is modeled as a mixed integer non-linear programming, which is solved by genetic algorithm (GA). Using information stored in a database as well as a knowledge base, the computational system is able to obtain excellent conditions of selectivity and coordination for improving the feeder reliability indices. Tests for assessment of the algorithm efficiency were carried out using a real-life 660-nodes feeder. © 2006 IEEE.

Identification of structural damage in flexible structures using system norm and neural networks

Nowadays there is great interest in damage identification using non destructive tests. Predictive maintenance is one of the most important techniques that are based on analysis of vibrations and it consists basically of monitoring the condition of structures or machines. A complete procedure should be able to detect the damage, to foresee the probable time of occurrence and to diagnosis the type of fault in order to plan the maintenance operation in a convenient form and occasion. In practical problems, it is frequent the necessity of getting the solution of non linear equations. These processes have been studied for a long time due to its great utility. Among the methods, there are different approaches, as for instance numerical methods (classic), intelligent methods (artificial neural networks), evolutions methods (genetic algorithms), and others. The characterization of damages, for better agreement, can be classified by levels. A new one uses seven levels of classification: detect the existence of the damage; detect and locate the damage; detect, locate and quantify the damages; predict the equipment's working life; auto-diagnoses; control for auto structural repair; and system of simultaneous control and monitoring. The neural networks are computational models or systems for information processing that, in a general way, can be thought as a device black box that accepts an input and produces an output. Artificial neural nets (ANN) are based on the biological neural nets and possess habilities for identification of functions and classification of standards. In this paper a methodology for structural damages location is presented. This procedure can be divided on two phases. The first one uses norms of systems to localize the damage positions. The second one uses ANN to quantify the severity of the damage. The paper concludes with a numerical application in a beam like structure with five cases of structural damages with different levels of severities. The results show the applicability of the presented methodology. A great advantage is the possibility of to apply this approach for identification of simultaneous damages.

Experimental damage detection using system norms

Nowadays there is great interest in structural damage detection in systems using nondestructive tests. Once the failure is detected, as for instance a crack, it is possible to take providences. There are several different approaches that can be used to obtain information about the existence, location and extension of the fault in the system by non-destructive tests. Among these methodologies, one can mention different optimization techniques, as for instance classical methods, genetic algorithms, neural networks, etc. Most of these techniques, which are based on element-byelement adjustments of a finite element (FE) model, take advantage of the dynamic behavior of the model. However, in practical situations, usually, is almost impossible to obtain an accuracy model. In this paper, it is proposed an experimental technique for damage location. This technique is based on H: norm to obtain the damage location. The dynamic properties of the structure were identified using experimental data by eigensystem realization algorithm (ERA). The experimental test was carried out in a beam structure through varying the mass of an element. For the output signal was used a piezoelectric sensor. The signal of input of sine form was generated through SignalCalc® software.

Genetic vaccine for tuberculosis (pVAXhsp65) primes neonate mice for a strong immune response at the adult stage

Background: Vaccination of neonates is generally difficult due to the immaturity of the immune system and consequent higher susceptibility to tolerance induction. Genetic immunization has been described as an alternative to trigger a stronger immune response in neonates, including significant Th1 polarization. In this investigation we analysed the potential use of a genetic vaccine containing the heat shock protein (hsp65) from Mycobacterium leprae (pVAXhsp65) against tuberculosis (TB) in neonate mice. Aspects as antigen production, genomic integration and immunogenicity were evaluated. Methods: Hsp65 message and genomic integration were evaluated by RT-PCR and Southern blot, respectively. Immunogenicity of pVAXhsp65 alone or combined with BCG was analysed by specific induction of antibodies and cytokines, both quantified by ELISA. Results: This DNA vaccine was transcribed by muscular cells of neonate mice without integration into the cellular genome. Even though this vaccine was not strongly immunogenic when entirely administered (three doses) during early animal's life, it was not tolerogenic. In addition, pVAXhsp65 and BCG were equally able to prime newborn mice for a strong and mixed immune response (Th1 + Th2) to pVAXhsp65 boosters administered later, at the adult life. Conclusion: These results suggest that pVAXhsp65 can be safely used as a priming stimulus in neonate animals in prime-boost similar strategies to control TB. However, priming with BCG or pVAXhsp65, directed the ensuing immune response triggered by an heterologous or homologous booster, to a mixed Th1/Th2 pattern of response. Measures as introduction of IL-12 or GM-CSF genes in the vaccine construct or even IL-4 neutralization, are probably required to increase the priming towards Th1 polarization to ensure control of tuberculosis infection. © 2007 Pelizon et al; licensee BioMed Central Ltd.

A genetic neuro-model reference adaptive controller for petroleum wells drilling operations

Motivated by rising drilling operation costs, the oil industry has shown a trend towards real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated to parameters modeling. One of the drill-bit performance evaluators, the Rate of Penetration (ROP), has been used in the literature as a drilling control parameter. However, the relationships between the operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on the Auto-Regressive with Extra Input Signals model, or ARX model, to accomplish the system identification and on a Genetic Algorithm (GA) to provide a robust control for the ROP. Results of simulations run over a real offshore oil field data, consisted of seven wells drilled with equal diameter bits, are provided. © 2006 IEEE.

Induction of chromosome aberrations in the Allium cepa test system caused by the exposure of seeds to industrial effluents contaminated with azo dyes

Numerous potentially mutagenic chemicals have been studied mainly because they can cause damaging and inheritable changes in the genetic material. Several tests are commonly used for biomonitoring pollution levels and to evaluate the effects of toxic and mutagenic agents present in the natural environment. This study aimed at assessing the potential of a textile effluent contaminated with azo dyes to induce chromosomal and nuclear aberrations in Allium cepa test systems. A continuous exposure of seeds in samples of the textile effluent in different concentrations was carried out (0.3%, 3%, 10%, and 100%). Cells in interphase and undergoing division were examined to assess the presence of chromosome aberrations, nuclear changes, and micronuclei. Our results revealed a mutagenic effect of the effluent at concentrations of 10% and 100%. At lower concentrations, the effluent (3% and 0.3%) did not induce mutagenic alterations in the test organism A. cepa. These findings are of concern, since cell damage may be transmitted to subsequent generations, possibly affecting the organism as a whole, as well as the local biota exposed to the effluent discharge. If the damage results in cell death, the development of the organism may be affected, which could also lead to its death. © 2008 Elsevier Ltd. All rights reserved.

Population genetic data of five X-chromosomal loci in Bauru (São Paulo, Brazil)

Genetic population data for five X-STR (DXS6854, DXS7424, DXS101, DXS6808 and DXS7132) were obtained from Bauru population (São Paulo, Brazil). No deviations from the Hardy-Weinberg equilibrium were observed, with the exception of DXS101. The combined powers of discrimination in males and females were 0.99897253 and 0.99999120, respectively. These high values show the potential of this system in human identification and paternity testing. © 2008 Elsevier B.V. All rights reserved.

A clinical decision support system for cancer diseases

The second main cause of death in Brazil is cancer, and according to statistics disclosed by National Cancer Institute from Brazil (INCA) 466,730 new cases of cancer are forecast for 2008. The analysis of tumour tissues of various types and patients' clinical data, genetic profiles, characteristics of diseases and epidemiological data may lead to more precise diagnoses, providing more effective treatments. In this work we present a clinical decision support system for cancer diseases, which manages a relational database containing information relating to the tumour tissue and their location in freezers, patients and medical forms. Furthermore, it is also discussed some problems encountered, as database integration and the adoption of a standard to describe topography and morphology. It is also discussed the dynamic report generation functionality, that shows data in table and graph format, according to the user's configuration. © ACM 2008.