864 resultados para Genetic Algorithms and Simulated Annealing
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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.
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Until mid 2006, SCIAMACHY data processors for the operational retrieval of nitrogen dioxide (NO2) column data were based on the historical version 2 of the GOME Data Processor (GDP). On top of known problems inherent to GDP 2, ground-based validations of SCIAMACHY NO2 data revealed issues specific to SCIAMACHY, like a large cloud-dependent offset occurring at Northern latitudes. In 2006, the GDOAS prototype algorithm of the improved GDP version 4 was transferred to the off-line SCIAMACHY Ground Processor (SGP) version 3.0. In parallel, the calibration of SCIAMACHY radiometric data was upgraded. Before operational switch-on of SGP 3.0 and public release of upgraded SCIAMACHY NO2 data, we have investigated the accuracy of the algorithm transfer: (a) by checking the consistency of SGP 3.0 with prototype algorithms; and (b) by comparing SGP 3.0 NO2 data with ground-based observations reported by the WMO/GAW NDACC network of UV-visible DOAS/SAOZ spectrometers. This delta-validation study concludes that SGP 3.0 is a significant improvement with respect to the previous processor IPF 5.04. For three particular SCIAMACHY states, the study reveals unexplained features in the slant columns and air mass factors, although the quantitative impact on SGP 3.0 vertical columns is not significant.
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Background: New challenges are rising in the animal protein market, and one of the main world challenges is to produce more in shorter time, with better quality and in a sustainable way. Brazil is the largest beef exporter in volume hence the factors affecting the beef meat chain are of major concern in countrýs economy. An emerging class of biotechnological approaches, the molecular markers, is bringing new perspectives to face these challenges, particularly after the publication of the first complete livestock genome (bovine), which has triggered a massive initiative to put in practice the benefits of the so called the Post-Genomic Era. Review: This article aimed at showing the directions and insights in the application of molecular markers on livestock genetic improvement and reproduction as well at organizing the progress so far, pointing some perspectives of these emerging technologies in Brazilian ruminant production context. An overview on the nature of the main molecular markers explored in ruminant production is provided, which describes the molecular bases and detection approaches available for microsatellites (STR) and single nucleotide polymorphisms (SNP). A topic is dedicated to review the history of association studies between markers and important trait variation in livestock, showing the timeline starting on quantitative trait loci (QTL) identification using STR markers and ending in high resolution SNP panels to proceed whole genome scans for phenotype/genotype association. Also the article organizes this information to reveal how QTL prospection using STR could open ground to the feasibility of marker-assisted selection and why this approach is quickly being replaced by studies involving the application of genome-wide association using SNP research in a new concept called genomic selection. Conclusion: The world's scientific community is dedicating effort and resources to apply SNP information in livestock selection through the development of high density panels for genomic association studies, connecting molecular genetic data with phenotypes of economic interest. Once generated, this information can be used to take decisions in genetic improvement programs by selecting animals with the assistance of molecular markers.
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The purpose of this study it was to evaluate the frequency of Multiple Endocrine Neoplasia type 1 (MEN1) in patients with pituitary adenoma and to perform genetic analysis and familial screening of those individuals afflicted with MEN1. 144 patients with pituitary adenoma at Botucatu Medical School, UNESP-Univ Estadual Paulista, were assessed retrospectively for MEN1 during the years of 2005-2011. The patients were evaluated for the presence of primary hyperparathyroidism (PHP) and enteropancreatic tumors. Genetic analysis was performed for the individuals with clinically diagnosed MEN1. Thirteen patients met the diagnostic criteria for MEN1, but three individuals belong to the same family and they were considered as a single MEN1 event, revealing 7.7 % frequency of MEN1 in this patient group. Genetic analysis showed MEN1 mutations in four index cases: IVS4+1 G>A, IVS3-6 C>T, c.1547insC and a new D180A mutation. One patient did not agree to participate in the genetic study and another one was referred for follow up in other hospital. Only polymorphisms were found in the other individuals, one of which was novel. We identified a high frequency of MEN1 in pituitary adenoma patients. Since PHP is one of the most common MEN1 tumor and patients are mostly asymptomatic, we suggest that all pituitary adenoma patients have their calcium profile analyzed. © 2013 Springer Science+Business Media New York.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The objectives of the present study were to estimate genetic parameters of monthly test-day milk yield (TDMY) of the first lactation of Brazilian Holstein cows using random regression (RR), and to compare the genetic gains for milk production and persistency, derived from RR models, using eigenvector indices and selection indices that did not consider eigenvectors. The data set contained monthly TDMY of 3,543 first lactations of Brazilian Holstein cows calving between 1994 and 2011. The RR model included the fixed effect of the contemporary group (herd-month-year of test days), the covariate calving age (linear and quadratic effects), and a fourth-order regression on Legendre orthogonal polynomials of days in milk (DIM) to model the population-based mean curve. Additive genetic and nongenetic animal effects were fit as RR with 4 classes of residual variance random effect. Eigenvector indices based on the additive genetic RR covariance matrix were used to evaluate the genetic gains of milk yield and persistency compared with the traditional selection index (selection index based on breeding values of milk yield until 305 DIM). The heritability estimates for monthly TDMY ranged from 0.12 ± 0.04 to 0.31 ± 0.04. The estimates of additive genetic and nongenetic animal effects correlation were close to 1 at adjacent monthly TDMY, with a tendency to diminish as the time between DIM classes increased. The first eigenvector was related to the increase of the genetic response of the milk yield and the second eigenvector was related to the increase of the genetic gains of the persistency but it contributed to decrease the genetic gains for total milk yield. Therefore, using this eigenvector to improve persistency will not contribute to change the shape of genetic curve pattern. If the breeding goal is to improve milk production and persistency, complete sequential eigenvector indices (selection indices composite with all eigenvectors) could be used with higher economic values for persistency. However, if the breeding goal is to improve only milk yield, the traditional selection index is indicated. © 2013 American Dairy Science Association.
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Bacterial fruit blotch of cucurbits (BFB), caused by the seed borne Gramnegative bacterium Acidovorax citrulli is a serious threat to cucurbit industry worldwide. Since late 1980`s after devastating outbreaks in watermelon fields in southern United States, BFB has spread worldwide and has been reported in other cucurbit crops such as melon, pumpkin, cucumber and squash. To date, there is evidence for the existence of at least two genetically and pathogenically distinct populations of A. citrulli. In Brazil, the first report of BFB was in 1991, in a watermelon field in São Paulo. Although widespread in the country, BFB has been a major problem to melon production. More precisely, BFB has caused significant yield losses to melon production in northeastern Brazil, which concentrates > 90% of the country`s melon production. Despite the management efforts and the recent advances in A. citrulli research, BFB is still a continuous threat to the cucurbit industry, including seed producers, growers and transplant nurseries. To better understand the population structure of A. citrulli strains in Brazil, and to provide a basis for the integrated management of BFB, we used pulsed-field gel electrophoresis (PFGE), multilocus sequence analysis (MLSA) of housekeeping and virulence-associated genes and pathogenicity tests on different cucurbit seedlings to characterize a Brazilian population of A. citrulli strains from different hosts and regions. Additionally, we conducted for the first time a comparative analysis of the A. citrulli group I and II population at genomic level and showed that these two groups differ on their genome sizes due to the presence of eight DNA segments, which are present in group II and absent in group I genomes. We also provide the first evidence to suggest that temperature might be a driver in the ecological adaptation of A. citrulli populations under nutrient-rich or -depleted conditions. Finally, in order to improve the routine detection of A. citrulli on melon seedlots, we designed a new primer set that is able to detect the different Brazilian haplotypes, thus minimizing the risk of false-negatives on PCR-based seed health testing.
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In this study, 15 microsatellite DNA loci used in comparative tests by the International Society for Animal Genetics were applied to the evaluation of genetic diversity and management, and the efficiency of paternity testing in Marajoara horses and Puruca ponies from the Marajó Archipelago. Based on the genotyping of 93 animals, mean allelic diversity was estimated as 9.14 and 7.00 for the Marajoara and Puruca breeds, respectively. While these values are similar to those recorded in most European breeds, mean levels of heterozygosity were much lower (Marajoara 49%, Puruca 40%), probably as a result of high levels of inbreeding in the Marajó populations. The mean informative polymorphic content of this 15-marker system was over 50% in both breeds, and was slightly higher in the Marajoara horses. The discriminative power and exclusion probabilities derived from this system were over 99% for both populations, emphasizing the efficacy of these markers for paternity testing and genetic management in the two breeds.
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Para estudar o relacionamento genético entre as raças suínas Landrace, Large White e Duroc foram utilizados os dados sobre três polimorfismos protéicos, investigados em três amostras brasileiras e em 13 populações de outros países, incluindo uma população de Landrace Belga. O dendrograma, construído a partir da matriz dos coeficientes de distância genética, mostrou três grandes grupos reunidos por raça. Os agrupamentos de Landrace e os de Large White mostraram em média maior semelhança entre si (D = 0,203) do que entre eles e os de Duroc (D = 0,241). Nas três raças, as menores distâncias genéticas foram verificadas entre as populações brasileiras e as cubanas (Landrace: D = 0,060; Large White: D = 0,052; Duroc: D = 0,065), apesar de não haver relatos de trocas de animais entre estes dois países.
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O objetivo deste trabalho foi estimar parâmetros genéticos e avaliar a seleção simultânea quanto à produtividade de raízes e à adaptabilidade e estabilidade de genótipos de mandioca. Os efeitos dos genótipos foram considerados como fixos e aleatórios, e a metodologia de modelos mistos (REML/Blup) foi utilizada para estimar os parâmetros genéticos e a média harmônica do desempenho relativo dos valores genotípicos (MHPRVG), para seleção simultânea. Dez genótipos foram avaliados em delineamento de blocos ao acaso, com quatro repetições. O experimento foi realizado nos municípios de Altamira, Santarém e Santa Luzia do Pará, PA, nos anos agrícolas de 2009/2010, 2010/2011 e 2011/2012. As raízes foram colhidas 12 meses após o plantio, em todos os locais testados. A produtividade de raízes apresentou baixo coeficiente de variação genotípica (4,25%) e herdabilidade de parcelas individuais no sentido amplo (0,0424), o que resultou em baixo ganho genético. Em razão da baixa correlação genotípica (0,15), a classificação dos genótipos quanto à produtividade de raízes variou de acordo com o ambiente. Os genótipos CPATU 060, CPATU 229 e CPATU 404 destacaram-se quanto à produtividade, adaptabilidade e estabilidade.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)