فهرست مطالب saba moradi

In today's world, sports diplomacy is considered as one of the most important factors for producing soft power for the countries. The purpose of this research is to compare the sports diplomacy of Iran and one of the countries of the Persian Gulf region, Qatar, which has made significant achievements in this field. The main question of this research is, what are the similarities and differences between the sports diplomacy of the Islamic Republic of Iran and Qatar? This research was done by using a comparative method, and the method of collecting information is the library. The theoretical foundations of this research are based on Joseph Nye's soft power, as the use of sports diplomacy is one of the tools of soft power. The Findings of this research show that in the field of investment in sports, the country of Qatar has made huge expenses to promote sports diplomacy. While the state of investment and sports facilities and infrastructure in Iran is experiencing disorder. In terms of power and influence in international sports forums and in terms of obtaining the privileges of hosting world-class and prestigious competitions Qatar has more ideal conditions than Iran; But in winning international sports honors, Iran has performed better due to its large population compared to Qatar. In the field of sports development, Qatar has more significant progress and development than Iran, and finally, Qatar benefits from a better media power than Iran to promote sports diplomacy and gain soft power.

Credit risk assessment has always been one of the most important concerns of banks. Widely used models such as financial models have been used to assess credit risk so far. But increasing non-performing loans indicates that today these models cannot assess the credit risk of customers. Inconstant and uncertain environmental, social and political factors affect customer behavior and change customer behavior over time so that low risk customers become high risk customer. Hence a dynamic model had better to design for customers’ credit risk evaluation. Recognizing patterns of changes of customer behavior is a key factor in the bank's success in assessing and managing customer credit risk. Previous research has used conventional models such as financial and empirical data models. In this study, considering the dynamics of customers over time in different segments of low risk, medium risk and high risk and using big data analysis methods, dynamic customer behavior patterns have been extracted. In this study, the loans information of individual customers of three banks in a sample of 284,000 customers between 1389 and 1396 were examined and 30 variables were used to assess credit risk. The results showed that the model with a sensitivity of 92.1% and a detection of 89.1% has a high efficiency and performs better and has a higher efficiency compared to the probit, logit and neural network models. The result of this research is the recognition of dynamic patterns of customers' credit risk and using it. The bank has a more accurate assessment of customers' credit risk. Also in this method there is no need to retrain the data and run the algorithms again, therefore, this method saves time and money. Most importantly, the results of this study are significantly different from the results of the current bank model (static method).

Climate change along with human interventions has changed natural hydrological cycle and consequently the need for more water resources, timely supply of water needs has faced serious challenges. Estimation of basal flow index has been one of the important issues in hydrology. In order to analyze the minimum flows in this study, 12 hydrometric stations with a statistical period of 30 years in northwestern Iran were selected due to the presence of Lake Urmia and then the annual minimum flow series were calculated with continuities of 3, 5, 7, 15 and 30 days. Based on the goodness-of-fit test of Kolmogorov-Smirnov, among the various distributions of the Wakeby distribution and based on Mann-Kendall test 66.67 Percent have a decreasing trend of minimum flow, based on Pettit 75 Percent of the studied stations have an increasing trend of minimum flow and according to Phenomenon test, 41.67 Percent of the stations have a minimum increasing trend of 95 Percent with different continuities. The results can be useful for having an accurate plan for the amount of water consumed and sustainable management of water resources in arid and semi-arid regions.

Agriculture is a risky activity and a wide range of risks are affecting the income earned from agricultural products. Market risk is the main source of revenue fluctuations in agriculture in all over the world. One of the subsectors of agricultural sector is animal farming industry that its changes during recent years have greatly influenced the revenue of investors in this industry. Considering the importance of livestock subsector in the agriculture sector, identifying and estimating the risk of livestock units are important.

The first step in activity risk management is to choose a model to identify and measure the risk of that activity. Risk assessment models are selected based on different factors such as the type of projects and their risks. In this regard, a concept discussed in the field of risk assessment in agricultural units is the value at risk (VaR) criteria. Value at risk is a statistical analysis that is mainly used in determining the quantitative risk of market and measures the most expected losses under normal conditions of the market and also during a certain period of time at a specific level of confidence (Radpour & Abeduh Tabrizi, 2009). This criterion summarizes the risk of portfolio in just one number under the value at risk measure. In the present study, the profit of each calf was calculated and the risk of weekly profit of a head of calf was determined by the value at risk method using Monte Carlo simulation for two time periods of 2004 to 2018 and 2013 to 2018 by @Risk add-in. Also, a multivariate regression was estimated by @Risk to analyze the sensitivity of the expected profit for each variable in the model. Parameters that have the most impact on the profit of each head of calf are identified as the most sensitive and important inputs related to the profit variable. Finally, the value at risk of the last cattle feeding period in the confidence level of 95% using weekly VaR at a level of 95% is predicted.

In this study, after calculating the profit of each Holstein calf, a linear regression was estimated to evaluate the standard deviation of the calculated profit on the time trend. This regression coefficients indicate that the standard deviation of the profit is increasing at the rate of 1622.9 Rials/week during the studied period. In other words, the risk of fattening activity has increased over time. To assess the risk of cattle fattening industry profits, price and performance variables were considered as expected variables in calculating the risk of profit. As the concept of value at risk is tied to the probability distribution of inputs and outputs, and its calculation process is equivalent to the probability distribution estimation process in the future period and also, considering that the Monte Carlo simulation is done on the repeated unstable and random inputs prices based on their probability distribution, finding the best distribution of inputs to produce random numbers is very important. Therefore, at first, the most important inputs in calculating profit were determined and then, their probability distributions were obtained according to the defined range of distribution using @Risk add-in. Because of the continuous nature of data, the Anderson-Darling test was used for verification of the obtained distributions. After Monte Carlo simulation and production of semi-random numbers for the desired inputs, 100000 simulated profits were obtained which the corresponding percentile of 90, 95, and 99% confidence intervals of the profit distribution were extracted as a weekly value at risk of per head Holstein calf. The results of estimating profit risk by VaR criteria showed that the weekly profit value at risk during 2004 to 2018 was 302108 Rials/week which is not a small figure for each calf profit during a week and presents the high profit risk of this industry. Also, the value at risk at the last 6 years of studied period was 600000 Rials. In conclusion, the results showed that weekly profit VaR increases 65292.07 Rials in each period. According to the predictions, the VaR of next period with a confidence coefficient of 95% will be 7197729 Rials. Also, the results of sensitivity analysis revealed that the most effective inputs on weekly profits were the prices changes of the calf, maize, and alfalfa inputs. Therefore, these inputs changes can also affect the risk of profit in cattle feeding units. In conclusion, controlling the living calf market as the most important input and veal market as the product of the fattening industry and corn, alfalfa, and soy markets has the most impact on the stability of the producers' profitability and ensures the profit of each head of livestock.

In this study, VaR criterion was used to assess the profit risk of cattle feeding units in Iran. According to the results, it is suggested to introduce the VaR criterion as an applied criterion in determining the risk to producers and investors of the agricultural sector. Therefore, it is necessary to provide continuous report of the value at risk amount of the industry by relevant organizations to help the investors and producers to clarify the status of the cattle feeding industry. Also, considering the changes in market conditions during different periods, finding the most important effective inputs on profit and controlling these inputs markets in order to control the producer’s profit fluctuations should be taken into account.

Multinodular goiter (MNG) is regarded as one of the most common causes of hyperthyroidism, particularly in areas of mild-to-moderate iodine deficiency. The present study aims to explore the effects of the radioactive iodine (RAI) therapy on benign non-toxic MNG and evaluate its side effects. Patients with benign non-toxic MNG entered the study. Ultrasonography was applied to calculate the percentage of the decrease in the size of the thyroid before and six months minimum after the treatment. Chi-square, Mann-Whiteny-U and T-test were done using SPSS v.18.0 (p<0.05). The volumes of the thyroid lobes and nodules decreased significantly due to RAI therapy (p<0.001). The total volume of the thyroid, volume of the right nodule, and volume of the left nodule decreased by 77.8%, 40.7%, and 34.6% respectively. According to the results of the current study, RAI therapy is an effective treatment method although it has short-term side effects. This treatment option is recommended for patients with benign non-toxic MNG, notably those who cannot be a candidate for surgery. This treatment affects the size of the thyroid and its nodules significantly and decreases almost all of the complications.