فهرست مطالب مرتضی شکرزاده

Pronation of foot is one of the most common abnormalities of the lower limb; so the purpose of this study was to compare the immediate and long-term effects of arch support on the electrical activity of muscles during landing in the three-step shot technique in handball players with pronation foot.

The present study was semi-experimental with a pre-test and post-test design with a control group. The statistical population of this research was male handball players with pronated foot. Sampling was done using convenient sampling method, and 10 people with pronated foot along with 10 healthy people were selected. The sole of the shoe used in this study had a protrusion on the inner edge of the foot (Arch support). To measure the electrical activity of the muscles of the lower limbs, it was recorded by an electromyography device and analyzed by the biometric datalite program. ANOVA test with repeated measurements was used to analyze the data, and the independent t-test was used to check the sameness of the initial conditions.

The results showed that there were significant increases in gastrocnemius muscles (P=0.04), vastus medialis (p=0.001), and biceps femoris muscles (p=0.089) in the pronation foot group after 4 weeks of using arch support insoles compared to the pre-test stage. Also, there was a significant increase in the vastus medialis muscle (p=0.06) in the pronation group in the immediate stage compared to the pre-test stage. In addition, the semitendinosus muscle in the pronation group had a significant increase after 4 weeks compared to the immediate phase (p=0.035).

It seems that in addition to improving the electrical activity of the lower limb muscles during jumping and landing, the immediate and long-term use of Arch Support insoles can lead to improved balance, absorption of landing shocks, and stability of the ankle joint in handball players with pronation foot.

To analyze the data of this research descriptive statistics and inferential statistics were used and experts selection software, MATLAB SPSS and PLS software were employed.Using theoretical foundations and libraries, six effective factors and variables predicting the success or failure of Investment projects in the free and special economic zones of the country were identified. After describing the variables and testing the normality,using the PLS software, a confirmatory factor analysis of the variables was carried out, in which all of the factors had a good confirmatory factor analysis and all the questions were approvedThen, using linear regression and ANOVA, the effect of each of the factors on the success or failure of investment projects was investigated, and the results of this test showed confirmation of the impact of each of the factors, and then the results of the hierarchical analysis indicated this was the first rank of product and service, followed by the second-rank ,that is geographical considerations, and the characteristics of the investor's psychology, the third rank, the product market characteristics, the fourth rank, the investor's ability to rank fifth, and financial considerations ,also, earned the last rank. Considering this prioritization, the neural network used in this research contained data from 6 variables as an input variable, with two intermediate layers with 30 nodes in the first layer, and three nodes in the second layer,which had one outlet. The results indicated that the neural network model had the power to predict the success of the investment projects to1.2%of the error

To analyze the data of this research, descriptive statistics and inferential statistics were used and experts selection software, MATLAB, SPSS and PLS software were employed Using theoretical foundations and libraries, six effective factors and variables predicting the success or failure of Investment projects in the free and special economic zones of the country were identified.After describing the variables and testing the normality,using the PLS software, a confirmatory factor analysis of the variables was carried out, in which all of the factors had a good confirmatory factor analysis and all the questions were approved Then, using linear regression and ANOVA, the effect of each of the factors on the success or failure of investment projects was investigated, and the results of this test showed confirmation of the impact of each of the factors, and then the results of the hierarchical analysis indicated this was the first rank of product and service, followed by the second-rank ,that is geographical considerations, and the characteristics of the investor's psychology, the third rank, the product market characteristics, the fourth rank, the investor's ability to rank fifth, and financial considerations ,also, earned the last rank.Considering this prioritization, the neural network used in this research contained data from 6variables as an input variable, with two intermediate layers with 30 nodes in the first layer, and three nodes in the second layer, which had one outlet.The results indicated that the neural network model had the power to predict the success of the investment projects.

Preliminary researche on job path and job progress has been typically in relation with examining demographic and individual factors and job achievement. For example, demographic factors like age and marital status, and individual factors like education and experience were recognized as strong job achievement determinants. Recent experimental evidence also supports that social-demographic features (age, gender) are the basic or strong predictors of job achievement.In this respect, the issue of emotional intelligence has also been recognized as another factor in this field. For this purpose, a questionnaire was used, whose validity and reliability were confirmed. A sample of 100 people from the. Staff of Islamic Azad University of Tabriz was selected, whose objective and subjective job achievements were examined. The results of these examinations were as follows: 1) There is no significant and direct correlation between emotional intelligence and subjective job achievement, 2)There is a significant and direct correlation between emotional intelligence and objective job achievement, 3)There is no significant correlation between age and objective job achievements, 4) There is no significant correlation between age and subjective job achievements, 5)Score difference of objective job achievement based on gender is significant, and 6) Score difference of subjective job achievement based on gender is insignificant.