hamid jamshidi

Universal Design (UD) means designing the products and environments everyone can use as far as possible without requiring specialized compatibility or design. The present study aimed to design and develop a comprehensive and valid checklist to evaluate the design of banks based on UD principles and implement it in Iranian banks.

Based on the seven UD principles and using a mixed methods sequential exploratory design, an initial checklist with 61 items was developed. Then, its psychometric properties were evaluated based on face and content validity and inter-rater agreement. The final checklist was prepared based on the results of this stage and used in the next stage to evaluate the design of 17 banks.

The final checklist consisted of 10 areas (as per the seven UD principles). The Content Validity Ratio (CVR) and Content Validity Index (CVI) were calculated as 0.91 and 0.93, respectively. Based on areas of the checklist, all the evaluated banks showed many problems, the most significant of which were related to the areas of equal use by different groups, flexibility in use, and the size and space of access and use.

The present study’s findings led to the design of a comprehensive and standard checklist to evaluate the design of banks in terms of UD principles. The results indicated that the UD principles were not observed in most studied banks, and they need to implement targeted design interventions.

The present study investigates the effect of oil resource rent on financial development through the stock market. In this case, the analysis process has been accomplished in two different states: considering and ignoring the institutional quality index in oil resource rent at the values above and below the financial development threshold. The threshold structural vector autoregression (TSVAR) model has been employed to analyze the stock markets in Norway and Brazil from 1984 to 2019. In Brazil, by ignoring the institutional quality index, the resource curse hypothesis is confirmed at the values below the financial development threshold. If the institutional quality index increases, the positive oil rent shock leads to the increment of financial development through the stock market. Therefore, the hypothesis of the resource curse is rejected in this country. In Norway, by ignoring the institutional quality, the resource curse hypothesis is confirmed at the values above the financial development threshold. If the institutional quality is considered in oil rent, a positive shock to oil rent reduces the financial development through the stock market in a short-term period. This situation increases the financial development through the stock market in a long-term period. As a result, an increase in institutional quality contradicts the resource curse hypothesis at the values above the threshold level. In Norway, if the institutional quality in oil rent is considered, a positive shock to oil rent enhances financial development through the stock market at values below the threshold.

Organizational development is highly dependent on human resources. It can even be said that human resources are the most important resources of any organization; Therefore, it needs a new approach in the planning and decision-making system called strategic foresight. Because traditional approaches to strategic planning in the face of environmental turbulence and uncertainty are not flexible and do not have the appropriate response. The present research is applied-developmental in terms of purpose and descriptive-analytical in nature. In order to conduct the research, the method mixed with the successive exploration strategy has been used. In this regard, the present study tries to identify and analyze the key drivers first by using two methods of foresight, namely cross-impact analysis and scenario planning, and then draws scenarios for human resources in Qazvin Municipality. As a result of identifying the two key uncertainties "Database and computer software for human resource information modeling" and "Management and staff commitment" right, the scenarios of digital municipality, snow municipality and silent municipality are formed from the interaction of these two factors. Drawing scenarios shows us which scenario we are moving towards (digital municipality) and if we want to move towards the desired scenario, ie digital municipality scenario, what drivers should be considered.

The Black-Scholes model assumes that the price of the underlying asset follows a geometric Brownian motion. This assumption has two implications: first, log-returns over any horizon are normally distributed with constant volatility σ and the second, stock price evolution is continuous, therefore, there is no market gaps. These conditions are commonly violated in practice: empirical returns typically exhibit fatter tails than a normal distribution, volatility is not constant over time, and markets do sometimes gap. The existence of volatility skew will misprice options price. Derived from these flaws, a number of models have proposed. In this paper we will analyze, simulate and compare two most important models which have widespread using: jump diffusion model and stochastic volatility model. Each of the aforementioned models have programmed in MATLAB and Python, then their results have been compared together in order to provide a robust understanding of each of them. Our results show that in comparison to Black-Scholes model these two models yield better performance.

Valproic acid is a broad-spectrum anticonvulsant drug that is also useful for other diseases such as bipolar disorder and migraine. The most important side effect of this drug is hepatotoxicity. Oxidative stress and mitochondrial dysfunction play a role in the pathogenesis of liver toxicity of valproic acid. Mito-TEMPO is an antioxidant-based compound, which is selectively accumulated in mitochondria. The effects of its mitochondrial protection against oxidative damage in various pathologies, such as liver damage, have been observed. The aim of this study was to evaluate the protective effect of mito-TEMPO on liver toxicity induced by sodium valproate in mice.

Animals were divided into five groups and treated intraperitonealy over a 4-week period. Group 1 received normal saline, served as vehicle control, group 2 treated with 12.5 mg/kg of sodium valproate, group 3 was treated with 1 mg/kg of Mito-TEMPO, group 4 received both sodium valproate (12.5 mg/kg) and Mito-TEMPO (1mg/kg), and group 5 received sodium valproate (12.5 mg/kg) and vitamin E (5mg/kg) served as positive control. At the end of the experiment, blood samples collected by cardiac puncture and all the animals were killed under ether anesthesia. Biochemical parameters including AST, ALT, ALP and GGT in serum samples and glutathione (GSH) and malondialdehyde (MDA) contents in liver homogenates were determined.

Findings of this study showed that activity of AST and ALT were significantly lower in the sodium valproate + mito-TEMPO treated animals as compared to sodium valproate group (group 2). Furthermore, mito-TEMPO was able to recover glutathione content (GSH) of liver tissue. Effect of mito-TEMPO on the activity of ALP and GGT and serum level of MDA was not significant.

Taken collectively, mito-TEMPO has a protective role in sodium valproate hepatotoxicity. Considering the present results, further studies, in view of the potential therapeutic properties of mito-TEMPO in improving liver damage caused by the use of valproic acid, may lead to the clinical applications of mito-TEMPO in the treatment of liver disease.

Block trade is a significant part of stock exchange transactions. They involve trading a large volume of stocks at agreed prices that usually differ from the volatile and spot market prices. The large volume of block Trade has pushed academics to conduct a wide range of researches in this area. The main goal of this paper is to study the information content of block Trade.

For the above purpose, gathered data from 208 block trades in the Tehran Stock Exchange during the years of 2008-2016 were analyzed by the event study method. The results indicate that those block Trades are influential indicators for investors engaged in the stock exchange.

Evidence shows that after premium and controlled block trades, there exist significant cumulative abnormal returns. Overall, such cumulative abnormal returns imply the abnormal shareholder response to the block Trades. The results also demonstrate there are significant reductions in idiosyncratic volatility following block Trades.

Hyperglycemia may associate with improper use of glucocorticoids, impaired insulin function, or both, and is associated with many complications such as hyperlipidemia and Hyperglycemia. Researches suggests that proper use of glucocorticoids, can delay the onset and progression of complications of hyperglycemia and hyperlipidemia. In the present study we compare two of these compounds on glucose and lipid profile level.

we use 40 male Wistar rats from Yazd Animal infertility center. Initially, the rats were randomly divided into 2 groups and then each group was divided into 4 groups. Subsequently, fludrocortisone doses of 12, 24 and 36 mg / kg were administered to rats, and dosages of 6, 12 and 18 mg / kg for betamethasone administered to rats on a daily basis at 1 o'clock for 21 days by intraperitoneally injection.

Betamethasone and Fludrocortisone increased blood glucose and AST, ALT, TG, LDL, VLDL, and decreased HDL, causing red pigmentation in the skin, and obesity and puffiness of the rats. In all of the measured factors, fludrocortisone changes were more than betamethasone. Fludrocortisone and betamethasone also had significant effects on weight, which was more pronounced with fludrocortisone.

As the dose increased, the levels of AST, ALT, and cholesterol, TG, VLDL and LDL in the blood increased significantly and HDL levels decreased more in the blood, but fludrocortisone showed a stronger effect than betamethasone. Therefore, it can be expected that the use of Betamethasone would be logical due to fewer side effects than fludrocortisone.

Stock price prediction is one of the crucial concepts in finance area. Machine learning can provide the opportunity for traders and investors to predict stock prices more accurately. In this paper, Closing Price is dependent variable and First Price, Last Price, Opening Price, Today’s High, Today’s Low, Volume, Total Index of Tehran Stock Exchange, Brent Index, WTI Index and Exchange Rate are independent variables. Seven different machine learning algorithms are implemented to predict stock prices. Those include Bayesian Linear, Boosted Tree, Decision Forest, Neural Network, Support Vector, and Ensemble Regression. The sample of the study is fifteen oil and gas companies active in the Tehran Stock Exchange. For each stock the data from the September 23, 2017 to September 23, 2019 gathered. Each algorithm provided two metrics for performance: Root Mean Square Error and Mean Absolute Error. By comparing the aforementioned metrics, the Bayesian Linear Regression had the best performance to predict stock price in the oil and gas industry in the Tehran Stock Exchange.

The logistic regression technique was used to propose a model for predicting stock targeting through block trades. Those characteristics related to the likelihood of companies turning into a target for block trades were investigated. For this purpose gathered data on 117 Tehran Stock Exchange members, whose target of block trades with a trades volume of over 5% and 117 companies that did not target trading, was selected during the period of 2009-2017, using Logit method And probit were studied. The results showed that financial leverage and the change in assets negatively influenced the (block trades) commercialization frequency of the studied companies. It was also found that companies having a greater free cash flow, a higher market share, and a more distributed ownership, as well as companies with state organizations as principal shareholders, were more likely to be turned into commercial blocks. In addition, a comparison was made between the proposed logistic regression model and other well-known prediction models, namely, the artificial neural network and the fuzzy neural network models. The obtained results showed that the fuzzy neural network approach provided a more accurate prediction in terms of stock targeting than other techniques.

The logistic regression technique was used to propose a model for predicting stock targeting through block trades. Those characteristics related to the likelihood of companies turning into a target for block trades were investigated. For this purpose gathered data on 117 Tehran Stock Exchange members, whose target of block trades with a trades volume of over 5% and 117 companies that did not target trading, was selected during the period of 2009-2017, using Logit method And probit were studied. The results showed that financial leverage and the change in assets negatively influenced the (block trades) commercialization frequency of the studied companies. It was also found that companies having a greater free cash flow, a higher market share, and a more distributed ownership, as well as companies with state organizations as principal shareholders, were more likely to be turned into commercial blocks. In addition, a comparison was made between the proposed logistic regression model and other well-known prediction models, namely, the artificial neural network and the fuzzy neural network models. The obtained results showed that the fuzzy neural network approach provided a more accurate prediction in terms of stock targeting than other techniques.

Importance as a major source of state income tax, known to everybody, accordingly tax audits, and to consider the effectiveness, efficiency and economy of tax audit process and the role and adequacy of internal controls in this regard, due to the complex business environment over it is important to use the audit risk model as a solution to a tax audit is taken into consideration. This research is on adaptability of the risk-based audit model aims to address the risks identified in the census sample handling and how to calculate the relationship between the identified risks and determine the actual tax rate. Results of the sampling theory are also indicated to reduce the risk, the adequacy of the audit model variables and only on the assumption that the effectiveness of the model resultsTest the adequacy and comprehensiveness of the model in order to coverall topics addressed in the balance sheet and profit and loss statement shows.

Working capital management is one of the most important areas in financial management and management of organizations to be considered, because it directly affects the liquidity and profitability of companies. The aim of this study was to investigate the importance of working capital management and its components in the profitability of small and medium enterprises are non-exchange firms. In this study territory was five-year period between 1388 to 1392, and 50 companies were selected after performing the sampling process. As well as for analysis and regression analysis was used to test research hypotheses. The results show the index constituents on working capital management and profitability of small and medium non-exchange firms and there was a significant inverse relationship. Firms can have the optimal level of capital that maximizes the value they provide. Being abundant and generous credit policy can lead to increased sales and reduced inventory shortages Available high risk and trade credit because the evaluation of product quality to provide payment to customers can lead to increased sales.

In the present era، Internet as an accepted and useful tool for commerce، buying and selling has become and Fundamental changes in the structure of industry and commerce has brought; in this among the preservation and strengthening customer loyalty for companies that are operating in Electronics space as a strategic challenge Is discussed In the field of maintain and develop a competitive position in the virtual space. This study sought to evaluate the impact of system quality، information quality and interface design quality on customer loyalty websites through role of the customers’ satisfaction and trust. The Population Statistical of this study is “Center market” website customers that among them 320 samples were selected randomly. Data analysis by using SPSS and AMOS statistical software was done and the statistical methods used in this study، structural equation modeling. The results show that the system quality and interface design quality significantly influences on the satisfaction and trust of web site customers; But does not influence the quality of information on these variables. The study also found that customer trust causing is His satisfaction and both variables the trust and satisfaction are influence on the customer loyalty.

Friction stir welding is a solid state welding processes due to the low temperature in the welding zone, prevent formation of defect that can occur during fusion welding. In this paper, the effects of three important parameters of rotational speed, welding speed and tool tilt angle on mechanical properties lap joint of aluminum alloy to austenitic stainless steel have been studied. The results showed that higher increasing the rotational speed or decreasing the welding speed can be cause the creation of defects such as created flash around the weld zone, cavity and sheet thinning defect which will strongly affect on the mechanical properties of the joint, So that maximum fracture load was obtained 7750N in the rotational and welding speed,1000rpm and 80mm/min, respectively which the rotational speed to 2000rpm led to reduce the fracture load of joint to 3350N. It also became clear that strength of the joint increases and then decreases with increasing tool tilt angle. Therefore, that with increases tool tilt angle from 1.5 to 2.5 degree, fracture strength reduce from 7750N to 4180N. Which due to increase of the heat input, create flash around the weld zone reducing the volume of material under the tool shoulder, and finally the formation of defects in the joint.

Optimal portfolio selection and how to invest in، is one of the key issues which is considered in the capital market and should be paid attention by investors. In this regard، investors studies in selecting optimal portfolio accords to risk and return level. What has been done in the field of financial calculations and portfolio selection should prioritize existing investments in terms of risk and return respectively، until investors be able to constitute their optimal portfolio according to the finance and their level of risk-taking. Hence، measuring risk is considered as a major issue in the investment of portfolio. So in this research which was done in a capital market of Iran، it is presented a multi objective single - period mathematical model for measuring the risk of portfolio which integrates measure of return and two measures of risk (semivariance، Cvar). This model enables investors to measure the risk of portfolio carefully under transactions cost constrains and invest in a portfolio with maximum rate of return and minimum rate of risk Results show that using integraed risk measure can increase the carefulness of investors in capital market for optimal portfolio selection.