Introduction: Phaseolous vulgaris is highly important among bean species. China, Iran and Japan are the most important countries producing bean in Asia. According to reported information, cultivated area of bean was 94000 ha in Iran which 17841 ha located in Lorestan province. Improvement of new cultivar with high genetic potential for grain yield is the final goal in many breeding programs. To achieve this goal, many characteristics should be considered. Positive and negative significant correlation has been reported between traits in common bean. Various, traits had different direct and indirect effects on grain yield which should be considered. In addition to path analysis, evaluation and relationship of traits by other multivariate statistical methods such as cluster and factor analysis have been studied for better understanding of these relationships. This study aimed to investigate superior lines, study the relationship between important traits with seed yield by some univariate and multivariate statistical methods, and provide functional recommendation to breeding programs. Materials & Methods Elite lines obtained from red common bean (Phaseolus vulgaris L. ) local populations of Lorestan province and suburbs, Iran, including 14 lines belonged to Azna (2 lines), Aligudarz (4 lines), Aleshtar (1 line), Borujerd (1 lines), Durood (2 lines), Shazand (2 line) and Nourabad (2 lines), with two control cultivars Goli and Sayyad were evaluated in randomized complete block design (RCBD) with 4 replications in Borujerd station, Lorestan, Iran, in 2011. Plant height, node number, stem number, pod length, pod number per plant, seed number per plant, 100 seed weight and seed yield characteristics were measured. Data were normalized by Kolmogorov-Smirnov test at 0. 01 probability level. Error, genetic and phenotypic variances, and broad sense heritability pertreatment mean were estimated. Pearson correlation coefficient was used to determine the relationship between traits. Cluster analysis based on UPGMA was performed and Wilks' lambda statistic was used for cutting dendrogram. Then, a code was allocated to each group and these groups were compared. However, in order to fix type I error, Hotelling’ s T2 test was used at 0. 05 probability level. Before that, the assumption of homogeneous variance-covariance matrix was tested by BOX test at 0. 01 probability level. Then, traits were compared. Seed yield was considered as dependent variable (y) and regression analysis was performed by stepwise method. Traits, that had significant standardized coefficient, were used in path analysis. For statistical analysis, Excel, SPSS and MSTAT-C software were used. Results & Discussion The results of ANOVA showed that the lines had significant difference for all studied traits. Mean comparison by Duncan test showed the highest and lowest seed yield belonged to Aligodarz-3 line (6058 Kg ha-1) and Goli cultivar (3175 Kg ha-1), respectively. All of the genotypes that were located in high seed yield group by cluster analysis belonged to elite lines that indicated the local red common bean populations, as a heterozygote germplasm source that been mixed of homozygous genotypes, had high potential to selection of superior lines in the breeding program. Comparison between groups by Hotelling-T2 statistics indicated seed number per plant and had significant difference at 0. 01 probability level. The highest and lowest significant correlation coefficient was observed for seed number per plant with seed yield (0. 91**) and node number with stem number (0. 27*), respectively. The results of multiple regression for seed yield as dependent variable showed that seed number per plant and 100 seed weight had significant standardized regression coefficient. While, 100 seed weight had no significant correlation coefficient with seed yield that breeders should be considered different aspect of trait relationships. Path analysis results showed seed number per plant with direct effect 1. 03 had more effect on seed yield than 100 seed weight with direct effect 0. 43. While, both seed number per plant and 100 seed weight had negative indirect effect on seed yield by each other. The results of factor analysis showed four factors explained 93% of total variation. The first and second factor were called yield and yield component, and phenological type explained 60% of total variation. The lines that located in high yield group had the highest value for yield and yield components factor. While, the lowest score for mentioned factor belonged to Goli cultivar that showed factor analysis can be used both to summarize many dependent variables (traits) into little independent variables (factors) and to selective genotypes based on factor value. According to reports, the genetic base of bean cultivars has been limited. One of the useful results of multivariate analysis is the investigation of genotypes that locate at the end of distribution for several traits and these genotypes can be used as parents for better utilizing of probably heterosis. Heterosis and crossing one of the sustainable agricultural goals would improve germplasm, increase human food, promotion of farmer’ s livelihoods and provide food. Conclusion Local populations of red common bean should be considered by breeders to select superior lines because of its potential and adaptation. Some studied traits had high diversity that could be exploited in breeding programs. While, other traits need to increase diversity by breeding strategies. Considering that each of studied analysis showed the different aspects of traits relationships and genotypes potential. So, the results should be considered simultaneously by breeders to better interpretation. Among the studied traits seed number per plant, according to high heritability, the identification of groups with different grain yield, high correlation and positive direct effect on grain yield was appropriate to increase seed yield. Multivariate analysis can be used to evaluate desirable genotypes and accumulate favorable alleles in breeding programs. The results of this study can be useful for breeders to investigate and utilize both traits and genotypes in breeding programs.

The central issue of the present paper is the study of the causes of the mother tongue decline in the Sahne city in Kermanshah province. The issue of language is beyond the dialect of people and is refer to the form of life and the matter of macroeconomic and political relations. From this perspective, the form of life and the language associated with it explain the praxis of the members of the society. The appropriate method of examining the problem should be able to analyze the justification of agents to their situation, that is why Grounded Theory is chosen as the method of this research and data analysis is taken from abduction reasoning. The results of the analysis introduced the categories of globalizing, modernizing, de-use of language, economic necessity and the government as the most important factors of local language fading. In this essay the meaning of globalization is the globalizing of special type of economic relation that explain other categories role in the process of fading of languages.

Identifying the constraining factors of production and yield gap is very important. Therefore; this research was performed to identify the production constraining factors of local rice cultivars. All management practices from nursery preparation to harvesting stages for 100 paddy fields of local rice cultivars were recorded through field studies, in Sari, from 2015-2016. In the CPA, the actual and calculated potential yield were 4495 and 5703 kg/ha, respectively and the gap was 1221 kg/ha. The yield gap caused by number of top-dressing variables was 324 kg/ha, equal to 27% of the total yield gap. The yield gap related to previous year of legumes cultivation was 218 kg ha-1, equal to 18% of the total yield variation. Among the 10 variables entered in the CPA model, the effects of top-dress fertilizer application and its application frequency and foliar application were remarkable, which could compensate a significant part of the yield gap (444 kg/ha, 37% of total) in the farmers’ fields by managing these variables. According to boundary line analysis (BLA) finding, actual yield mean on the basis of optimal limit related to 12 variables under study was 5369 kg/ha, with 881 kg/ha yield gap . Mean relative yield and relative yield gap for 12 variables (transplanting date, seedling age, number of seedlings per hill, planting density, nitrogen and phosphorous per hectare, nitrogen before transplanting, harvesting date, lodging problem, pest problem, diseases problem and weeds problem) were 83.64 and 16.35 kg/ha, respectively. Based on the finding, it can be stated that the model precision is appropriate and can be applied for both estimation of the quantity of yield gap and determining the portion of each restricting yield variables.

The aim of present study was to compare somepsychological skills of elite and noelite volleyball players. The relevant skills were motivation, concentration, selfconfidence, level psych control, imagery and goal setting. 50 subjects from the member of the junior national team and super league ( elite) and 50 subjects from the interschool teams from Khorasan state (non-elite) sampled for this study and SASI used to gather data. The findings revealed that there are significant differences (P<0.05) for all psychological skills. These results discuss about the role of psychological preparation in elite and non-elite athletes to approach in their peak readiness.

Background: Previous studies have shown detrimental effects of muscle fatigue on balance. Also they have reported the effects of kinesio taping (KT) on postural control, joint support, and muscle function. However, no studies have been conducted so far to assess the immediate effects of KT after local muscle fatigue on balance. Therefore, the aim of this study was to determine whether KT improves the Y-balance test scores after quadriceps fatigue.Methods: Fifty healthy male athletes (18-35 years old) participated in this quasiexperimental study and were randomly allocated to one of the two groups. The control group received only a fatigue protocol and the KT group received both quadriceps KT and the fatigue protocol. The balance of the subjects was assessed by a Y-balance test before and after the interventions.Results: The results revealed a significant decrease in Y-balance test scores after interventions in both groups. The KT group showed better scores in Y-balance test in all directions compared to the control.Conclusion: The study confirmed the positive effect of KT on balance after a fatigue protocol in athletes. We conclude that the application of KT can be an effective intervention for improving balance after induced fatigue in athletes.

Multi-label classification aims at assigning more than one label to each instance. Many real-world multi-label classification tasks are high dimensional, leading to reduced performance of traditional classifiers. Feature selection is a common approach to tackle this issue by choosing prominent features. Multi-label feature selection is an NP-hard approach, and so far, some swarm intelligence-based strategies and have been proposed to find a near optimal solution within a reasonable time. In this paper, a hybrid intelligence algorithm based on the binary algorithm of particle swarm optimization and a novel local search strategy has been proposed to select a set of prominent features. To this aim, features are divided into two categories based on the extension rate and the relationship between the output and the local search strategy to increase the convergence speed. The first group features have more similarity to class and less similarity to other features, and the second is redundant and less relevant features. Accordingly, a local operator is added to the particle swarm optimization algorithm to reduce redundant features and keep relevant ones among each solution. The aim of this operator leads to enhance the convergence speed of the proposed algorithm compared to other algorithms presented in this field. Evaluation of the proposed solution and the proposed statistical test shows that the proposed approach improves different classification criteria of multi-label classification and outperforms other methods in most cases. Also in cases where achieving higher accuracy is more important than time, it is more appropriate to use this method.