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In recent years, the use of smart numerical search techniques in active control of structure has been considered by researchers. Genetic algorithm is one of these methods that is based on natural evolution patterns. Here, the genetic algorithm is used to minimize the constrained objective function of the structure and determine the appropriate control forces. By connecting the sensor to the degrees of freedom of the structure, nodal displacement is monitored at each time step and genetic algorithm determines the proper control forces by using constrained objective function and solving dynamic equation of the structure. Choosing appropriate constrained objective function according to the structure conditions has a great impact on the efficiency of the proposed method. This function is obtained by combining the structural constraints and the assumed weighting factors for each constraint. Then, the weighting factors are calculated from the optimization methods. Such a process, leads to achieve a new active control method based on using genetic algorithm. The efficiency and accuracy of the proposed algorithm are investigate by controlling the oscillations of several structures. The results show that the proposed method is able to reduce structural oscillations effectively. The results of the linear modeling show that the use of the proposed active control method is able to reduce the displacements of the structure against the earthquake properly. By using this method, the displacement reduction is about 79% compared to the uncontrolled mode and 36% in the linear mode compared to the genetic algorithm method with constant weighting factors. In addition, the results in nonlinear modeling of the structure show an average improvement of 45%. [ABSTRACT FROM AUTHOR]

The analysis of the post-buckling behavior of elastic structures still needs the resolution of a body of non-linear differential equations according to equilibrium equations. Also, the yielding and buckling factors are important in the procedure of designing members under forces such as axial or conjoint axial force and bending moment. In such a way that if the length of the member is too long or the member is thin, before the yielding, buckling will occur in the member, and it is necessary to check and control the member for possible buckling. The present work deals with the stability analysis of elastic columns with variable cross-sections under concentrated end load and proposes a simplified approach to the evaluation of the critical buckling force of columns according to the assumptions of the Elastica theory. In this paper, the power series are used to simplify the equations. The numerical issues of the critical buckling force are presented for prismatic and non-prismatic columns subjected to end force, and the effectiveness of this approach is verified for buckling analysis of tapered columns, and the rate of accuracy is assessed. The elastic buckling force of elastic structures shows that the introduced model is computationally extremely efficient with the details presented in general. This paper should be a basic reference to compare the results with other research. [ABSTRACT FROM AUTHOR]

Problem statement: A wide range of studies for the assessment of genetic diversity in livestock breed were conducted using genetic distance. For high-accuracy and unbiased estimation sampling methods, criteria of choosing type of DNA markers, distance measurement strategies, cluster analysis will be important for any genetic diversity projects. Approach: Main objective of this short review is focusing on application statistical procedures and methods in analysis of genetic diversity data in animals. Results: There is no simple strategy to address for best and effectively genetic diversity results by the way regarding to some important factors can make reliable results for next analysis. Conclusion: There is still a distinct need for developing comprehensive and user-friendly statistical packages that facilitate an integrated analysis of different data sets for generating reliable information about genetic relationships, genome diversity, and favorable allele variation. Equally important and perhaps more challenging, is the concerted and planned utilization of genome information in animal breeding programs on the basis of knowledge accrued from studies on genetic diversity. Key words: Genetic diversity, statistical procedure, distance method, clustering methods, INTRODUCTION Genetic diversity: Livestock breeding is important strategy for supporting our future requirement for best response against different environments [12]. Genetic conservation also is significant powerful tools for keep long [...]

Salmonella infection is an important risk to public health, as newly hatched chicks are very sensitive to Salmonella and the infection transfers to humans through contaminated meat and eggs. Vaccination and antibiotic treatment are common strategies to control salmonellosis. However, it is doubtful whether these strategies succeed, because immune functions depend on the activity of several genes. Genetic improvement of the immune system is an effective method to control salmonellosis. There is genetic variation among breeds and individuals inside breeds in terms of resistance to infection. Genes responsible for resistance to disease can be identified through quantitative trait loci and gene expression analysis. High-throughput technologies assist us to detect single nucleotide polymorphisms (SNPs) and to analyse the regulation of several genes simultaneously. By now, several SNPs have been detected in the chicken genome that influence the function of immune genes. Additionally, the expression level of genes varies during infection depending on the breed and age of chicken and environmental conditions. This review summarizes the results of previous studies on the identification of genes and gene regulation during Salmonella infection in chickens. [ABSTRACT FROM AUTHOR]

Salmonella Enteritidis is a major cause of food poisoning worldwide, and poultry products are the main source of S. Enteritidis contamination for humans. Among the numerous strategies for disease control, improving genetic resistance to S. Enteritidis has been the most effective approach. We investigated the association between S. Enteritidis burden in the caecum, spleen, and liver of young indigenous chickens and seven candidate genes, selected on the basis of their critical roles in immunological functions. The genes included those encoding interleukin 2 (IL-2), interferon-γ (IFN-γ), transforming growth factor β2 (TGF-β2), immunoglobulin light chain (IgL), toll-like receptor 4 (TLR-4), myeloid differentiation protein 2 (MD-2), and inducible nitric oxide synthase (iNOS). Two Malaysian indigenous chicken breeds were used as sustainable genetic sources of alleles that are resistant to salmonellosis. The polymerase chain reaction restriction fragment-length polymorphism technique was used to genotype the candidate genes. Three different genotypes were observed in all of the candidate genes, except for MD-2. All of the candidate genes showed the Hardy–Weinberg equilibrium for the two populations. The IL-2-MnlI polymorphism was associated with S. Enteritidis burden in the caecum and spleen. The TGF-β2-RsaI, TLR-4-Sau 96I, and iNOS-AluI polymorphisms were associated with the caecum S. Enteritidis load. The other candidate genes were not associated with S. Enteritidis load in any organ. The results indicate that the IL-2, TGF-β2, TLR-4, and iNOS genes are potential candidates for use in selection programmes for increasing genetic resistance against S. Enteritidis in Malaysian indigenous chickens. [ABSTRACT FROM AUTHOR]