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An efficient banking system with the right monetary policy by controlling liquidity and inflation and directing resources to productive economic activities plays an essential role in economic development. However, banks' performance is influenced by various political, economic, managerial, and social factors, and the study of these factors has been considered the topic of interest to researchers. This paper uses the structural equation modeling method to investigate the effect of ownership structure and corporate governance on listed banks' performance in the Tehran Stock Exchange from 2011 to 2017. Based on the results, ownership structure dimensions have a relatively insignificant impact on corporate governance. However, the financial performance dimension has a statistically significant negative effect. The results also indicate that corporate governance is significantly associated with a positive effect on financial performance. Consequently, the results indicate that corporate governance may mitigate the negative impact that ownership structure dimensions may have on bank financial performance. [ABSTRACT FROM AUTHOR]

The functional classification system (FCS) of roads means categorizing roads based on their service characteristics. The two primary considerations in classifying highway and street networks are accessibility and mobility, where by increasing the role of one, the other's role is reduced. In this paper, besides the conventional variables such as geometric design characteristics, parking lots, land use features, and accessibility; the Sydney Coordinated Adaptive Traffic System (SCATS) data following the real-time traffic flow and average speed of vehicles collected by Location-Based Services (LBS) are considered as new variables for estimating the FCS. Linear regression is used to model the importance of the variables. The chi-square test compared the observational and predicted speeds in the five categories of roads in Tehran, the capital of Iran. Results show that on-street parking has the highest impact and the land use variable has the lowest impact on speed that changes the FCS. Moreover, the presented classification was one to two categories compared with the conventional FCS presented in manuals in the case of Tehran's transportation network as a developing city. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to investigate the effects of COVID-19 regarding the efficiency of industries based on data in the Tehran stock market. A hybrid model of Data Envelopment Analysis (DEA) and data mining techniques is used to analyze the investment behavior in Tehran stock market. Particularly during the COVID-19 pandemic, many companies face financial crises. That is why companies with inferior performance must be benchmarked with efficient companies. First, the financial data of investments on selective companies are analyzed using data mining approaches to recognize the behavioral patterns of investors and securities. Second, customers are clustered into 3 selling and 4 buying groups using data mining techniques. Then, the efficiency of active companies in stock exchange is evaluated using input-oriented DEA. The results indicate that, among 23 industries listed on the stock market in Iran, solely nine were efficient in 2019. Moreover, in 2020, the number of efficient industries further decreased to six industries. Comparing the obtained results with those of another study which was conducted in 2018 by other researchers revealed that COVID-19 strongly affects the performance of an industry and some industries which were efficient in the past such as the bank industry became inefficient in the following year. [ABSTRACT FROM AUTHOR]

The present study was done to evaluate the prevalence of intestinal parasitic infections (IPIs) in patients with COVID-19 in health care centers (Imam Reza and Golestan hospitals), Tehran, capital of Iran. By designing a matched case-control study, 200 fecal samples were collected for each of the COVID-19 patients and healthy individuals. Nasopharyngeal/oropharyngeal swab samples were collected from all participants for the diagnosis of COVID-19. RNA extraction was performed, and then real time reverse-transcription polymerase chain reaction (rRT-PCR) assay was applied to detect viral RNA. Considering the lung complications, 25%> lung complications was detected in 49 patients, 25–49% in 42 patients, and 50%≤ in 109 patients. Fecal samples were examined using different parasitological techniques. After nested-PCR, sequencing was applied to identify Cryptosporidium spp. and microsporidia spp. A relatively lower prevalence of IPIs was detected among control group (7.5%), than in COVID-19 patients (13%), though not significant P = 0.13 . The most prevalent parasite among patients was Blastocystis sp. (6%). Also, 13.76% of IPIs were detected in inpatients with more than 50% lung complication. As well, a remarkably significant difference in IPIs was observed among diarrheic COVID-19 patients, in comparison with nondiarrheic patients P < 0.00001 . Moreover, the isolated sequences in the present study belonged to C. parvum subtype IIa and Enterocytozoon bieneusi genotypes D and Peru 8. In conclusion, more epidemiological and clinical research studies are needed to better understand the status and interaction of IPI in COVID-19 in Iran and other countries. [ABSTRACT FROM AUTHOR]

Increasing construction and demolition (C&D) waste generation has faced serious challenges in the metropolitan areas of Iran. The objective of this research is to present a system dynamics model for C&D waste management of Tehran. In particular, variables such as energy consumption and carbon dioxide (CO2) emissions for the city of Tehran to the horizon of 2041 are studied and predicted. Increasing the rate of construction of housing and urban infrastructure will increase C&D waste and, on the other hand, increase the demand for raw materials, which is contrary to the principles of sustainable development. The increase in quarries exploitation and the increase in C&D waste generation can reduce the buildable area of the city. The impacts of such factors are in a cyclic and systemic approach that either reinforces a destructive factor or balances the existing solution. In general, the assessment of the implementation or nonimplementation of C&D waste recycling in each city requires a system insight that examines the aspects of the subject with a systemic perspective over time. To this end, the system dynamic approach, along with the environmental and economic approach of the life cycle, can clarify the hidden dimensions of the problem. One of the important limitations of the research is the large number of variables in the model and finding reliable historical information for these variables. [ABSTRACT FROM AUTHOR]

The essential principles in sustainable development are information and communication technology and their influence on the country's economic progress. In essence, in culture, politics, economics, and society, information and communication technology are the driving force behind globalization. This has a significant impact on the emergence of the network society and cross-national awareness, and it is the primary driver behind global markets. A descriptive-analytical method is used in a scrolling manner, and a scientific approach is taken from the methodology's standpoint. ICT companies in a selected region of Iran were surveyed in a questionnaire survey. "Success" in ICT standard setting is discussed in this study. A fuzzy analytical hierarchy process (FAHP) and VIKOR methods were used to analyze data and prioritize the beneficial factors that contribute to the success of ICT companies. Twenty five ICT companies were evaluated using these methods. Utilizing the expert's opinion and previous research, 21 criteria into five categories were elicited and estimated near Tehran (Qom), Iran's capital. In this research, native influential factors are compared with other countries' general vital factors, which are distinct from previous studies. Based on the results, in-company management factors, technological and marketing factors, financial costs, government policies, and native features were the most important critical factors. As significant factors that influence the success of ICT companies, employee involvement, teamwork, customer focus, the state of the economy, and conflict of interest between governmental and private sectors were selected. [ABSTRACT FROM AUTHOR]

In the modern era, intellectual capital encompasses all resources within an organization that enhance the value and competence of the organization. Consequently, this indicates that managing intellectual capital effectively will enhance the value and performance of an organization. This study aims to investigate the effects of intellectual capital on business performance through the use of customer knowledge management in the Bank Mellat branches of Iran. In this study, all managers and employees working for Bank Mellat in Tehran are included. Based on Morgan's table, the sample size was 220 people. Sampling was done by the simple random method. We used a descriptive correlation method to conduct this study and a questionnaire was used to collect data. The questionnaires were scored using a Likert scale. It was confirmed by a consensus of experts that the research instrument was valid, and the reliability of the research was 0.894%. Structural equation modeling was used to analyze the data. According to the results, the dimensions of intellectual capital (human, structural, and relational) have a significant impact on business performance. However, relational capital has been more influential on business performance than other factors. [ABSTRACT FROM AUTHOR]

The aim of the current research was to develop models to predict the severity of accidents on rural roads in Tehran province, Iran. In this regard, using accident data from 2017 to 2020, the machine learning algorithms, including multiple logistic regression, multilayer perceptron neural network (MLPNN), and radial basis function neural network (RBFNN) models, as well as statistical methods, including Kolmogorov–Smirnov test, Friedman test, and factor analysis, were implemented to determine the contributory factors in the severity of accidents. Thus, nine variables affecting the severity of accidents were considered in modeling, and then the effect of each variable was calculated. By comparing the results of artificial neural network (ANN) models and the Friedman test, it was indicated that the human factor had a remarkable effect on accident severity. In addition, both machine learning and statistical methods can be served as guidance for safety authorities to provide safety solutions, thereby leading to reducing accidents. Finally, the performances of ANN models were analyzed by other mathematical models built by MATLAB programming. [ABSTRACT FROM AUTHOR]

Traffic accidents occur due to a combination of factors that lead to casualties and injuries. By identifying the most effective factors, it is possible for safety authorities to provide appropriate solutions for decreasing the accident severity and implementing preventive measures. The aim of this research was to present models to predict the accident severity on two-lane two-way (TLTW) rural highways in Iran over a one-year period from 2019 to 2020. Therefore, the occurrence probability of any type of accident was determined by artificial neural network (ANN)-based prediction models using nine independent variables affecting the accident severity. This study developed numerous ANN structures using back-propagation to model the potential nonlinear relationship between the accident severity and accident-related factors. Results indicated that among the models, the multilayer perceptron neural network (MLPNN) model with 6-2-2 partition had the best performance and prediction power. This model was developed using the standardized rescaling method for covariates and batch for training. Also, 9, 5, and 2 units were considered automatically for the input, hidden, and output layers, respectively, and the hyperbolic tangent and softmax were used as an activation function in the hidden and output layers, respectively. This model had the lowest cross-entropy error of 39.6 and the highest correct percentage of 82.5%, and the area under the receiver operating characteristic (ROC) curve was 0.852. Moreover, among all the effective variables, pavement condition index, roadside hazard, shoulder width, and passing zone ratio had the greatest impact on the accident severity. Finally, safety strategies were proposed to increase safety and reduce accidents along these roads. [ABSTRACT FROM AUTHOR]

Azithromycin (AZT) has widely been used for the treatment of shigellosis in children. Recent studies showed a high rate of decreased susceptibility to azithromycin due to different mechanisms of resistance in Shigella isolates. Accordingly, the purpose of this study was to investigate the role of azithromycin resistance mechanisms of Shigella isolates in Iran during a two-year period. In this study, we investigated the mechanisms of resistance among Shigella spp. that were isolated from children with shigellosis. The minimum inhibitory concentration (MIC) of Shigella isolates to azithromycin was determined by the agar dilution method in the presence and absence of Phe-Arg-β-naphthylamide inhibitor. The presence of 12 macrolide resistance genes was investigated for all isolates by PCR for the first time in Tehran province in Iran. Among the 120 Shigella spp., only the mph(A) gene (49.2%) was detected and other macrolide resistance genes were absent. The phenotypic activity of efflux pump was observed in 1.9% of isolates which were associated with over expression of both omp(A) and omp(W) genes. The high prevalence of the mph(A) gene among DSA isolates may indicate that azithromycin resistance has evolved as a result of antimicrobial selection pressures and inappropriate use of azithromycin. [ABSTRACT FROM AUTHOR]