مجتبی صالحی

In general, inventory optimization is one of the most important techniques in the production system, because the high cost of an empty warehouse and the cost of losing customers can cause serious damage to a system. The basic idea for inventory is to provide flexibility for a system and protect the system against events such as stock out. Inventory capacity for each product or part is defined by demand, delivery time and part price. By balancing the supply and demand rates, the optimal inventory capacity can be achieved. It is necessary to use practical and effective techniques and solutions to reduce breakdowns to optimally use existing equipment and resources and reduce large costs in terms of energy wastage and repairs and repurchase of equipment. In this context, spare parts are one of the most important links in performing optimal maintenance and repairs and quickly returning equipment to the production line. In good management of spare parts, the inventory system of the warehouse will lead to the reduction of maintenance and repair costs, manpower and the duration of equipment failure and will ultimately help to increase productivity. This study aims to optimize the inventory level of spare parts for military vehicles using a mixed probability distribution.                                                           

Design/methodology/approach: 

First, based on the literature review and selected basic articles, the research gaps have been identified, and accordingly, a mathematical model has been developed and solved to optimize the spare parts of military vehicles. Then, a meta-inventive method has been used to solve the problem. This is because the use of meta-heuristic methods to check and analyze the sensitivity of inventory optimization models can lead to better and more accurate results, and also the use of these methods is relatively new and helps in solving optimization problems. Also, the problem studied in this research is a non-linear integer programming model, which has been used for the problems of medium and large dimensions due to the complexity of the problem. The meta-heuristic method based on the genetic algorithm has been applied to save the total costs. Finally, to prove the effectiveness of the model, the proposed model has been implemented in a case study on the parts of military vehicles in the 177th Brigade of Torbet Heydarieh.

Findings indicated that the optimal system cost value and the economic order value were obtained during specific iterations of the model, i.e., the first, fourth, and tenth iterations. These points implied the effectiveness of integrating Poisson and Exponential distributions in the model and optimizing the system performance in different scenarios. Such results emphasize the consistency and robustness of the proposed inventory management strategy, especially when demand fluctuates and supply challenges. As the model is subjected to more iterations, differences in results are observed, indicating the potential for variability with increasing iterations. For example, if the model considers 100 different problems or scenarios, different results may appear, although a general consistency in system behaviour is noted. This indicates flexibility in the modelling approach, where even significant changes in parameters such as inventory costs or lead times are unlikely to drastically change the economic value or efficiency of the system.

Research limitations: 

This research was conducted on a case-by-case basis on the parts of military vehicles of the 177th brigade of Torbat Heydarieh city, so it should be possible to generalize it to other organizations, and because it was typically a cross-sectional study, conclusions about on the causality might seem difficult.

Practical implications: 

The main challenge in the supply chain is to control inventory levels by determining the size of orders for each department during each period to optimize the objective function, which has been investigated in various studies because inventory optimization is one of the important and practical techniques for optimizing the economic value of the order and realizing a stable situation in a production system. This is particularly important since the high cost of an empty warehouse and the cost of losing customers can cause serious damage to a system

Social implications:

 Due to the specific conditions of embargo and restrictions on access to international markets, accurate inventory management can serve as a key tool to maintain efficiency and sustainability in military operations. This research recommends that relevant organizations continuously analyze and optimize their inventory levels using mathematical models and optimization algorithms such as genetic algorithms to avoid additional costs and at the same time, to ensure the supply of parts in times of need.

Originality/value: 

Predicting exactly what and how many spare parts are needed for the necessary equipment in a business and when they are needed to be available in its warehouse is an important issue to consider. These parts are identified and managed to support the functions of critical equipment, and the lack of critical spare parts during planned or unplanned repairs will significantly influence the overall effectiveness of the equipment.

The purpose of this study is to investigate the service brand verdict model as one of the most widely used service brand models in the Karafarin Bank as one one the privates banks of Islamic Republic of Irand and its development. Therefore, in the first phase of this research, after collecting literature related to service brand models and studying the background of service brand verdict model, the researcher reached his proposed model in this research. This model suggests that bank customers form a mindset of brand quality in their minds before verdict a brand. The next point is that the research literature led the researcher to the conclusion that the service brand model does not end with the customers verdict the brand; Therefore, it is assumed that after judging the brand, the intention to buy again and then loyalty to the brand occurs.

The research method used in this article is a mixed method. In the qualitative section, the proposed research model which is extracted from the study of literature and research background by the researcher, with Fuzzy Delphi Technique has been evaluated by a panel of experts including five banking specialists and five university marketing professors. After that, the extracted model was presented to the panel of experts in the first phase and their opinions were collected in the next stage, and according to the extent of their disagreement in the two stages, it was decided which variables remain in the model. Then, according to the final model which accepted by the panel of experts, the questionnaire was prepared as a measurement tool in the quantitative section and after confirming its reliability and validity, the questionnaire was distributed and collected among a sample of 384 customers of Karafarin Bank in Tehran (capital of Iran) by cluster random sampling. In this research the data analysis was performed by Structural Equation Modeling using Smart PLS software.

The research findings confirmed the relationships between the hypotheses and showed that the effect of brand hearsay on brand evidence. In this research the effect of brand hearsay which consist of controlled variables (advertisments and promotions) and uncontorolled variables (publicity and word of mouth) on customer satisfaction has been proven. The brand evidence which is consist of brand name, brand value or price, core service, physical environment, service provider employee, feelings and self-image congruity also affects on customer satisfaction.Based on the findings of the research the effect of brand evidence and brand hearsay on brand attitude has been confirmed by the customers of Karafarin Bank. Customer satisfaction affects the attitude towards the brand. Brand attitude affects the  perceived quality. Also it is proven that the perceived quality affects the brand verdict. According to the findings of this research the brand verdict affects the repurchase intention of the customer. It has been proven that at the end of this path and as an conclusion of the model customer loyalty will appear.

Brand loyalty is strongly influenced by both types of service cues, namely brand hearsay and brand evidence. Both the tangible dimensions of the service and its intangible dimensions, along with advertisements and promotion programs, strongly affect the consumer's behavior at every stage of his brand experience consist of his satisfaction, attitude, perception of quality, vedict toward the brand, intention to repurchase and finally becoming a loyal customer. Therefore, the results of this research suggeste that bank's programs must be planed based on strategies that use brand dimensions to lead customers to loyalty to their services. This model gives bank managers and decision makers a written program of the effective aspects of banking services on customer satisfaction and their attitude towards the bank brand, which ultimately leads to having loyal customers.This study, like other studies, has limited generalizability and its results cannot be used in all service sections. Although the researcher has tried to increase the validity of the results by selecting a large number of respondents, but due to the self-expression of the participants and also the large number of questions in the questionnaire, the ambiguity may arise that the questions were not answered with great accuracy and patience. Future researchers can study and evaluate this model in the wider statistical community or study it in other service sections in addition to the banking system to increase the generalizability of this model.It is also possible to examine the model of this research in the cultural contexts of other cities in the country and study the effects of cultural diffrences on the variables of the model and the relationships between them.

The compatibility of any innovation and integration with environmental considerations is significant. Hence, the concept of green innovation through the promotion of environmental efficiency gives the organization a competitive advantage in the domestic and global markets. Therefore, in this research, the effect of green customer integration on green innovation performance considering the moderating role of company size and internal integration as a mediating variable of environmental awareness of the senior managers is investigated in the Bahman Company as a case study.

Design/methodology/approach: 

This is typically an applied study in terms of the purpose of the research and is a descriptive survey in terms of the method of data collection and analysis. The statistical population included 425 personnel of the Bahman manufacturing company. Sampling has been done based on a simple random sampling method; and according to Cochran's formula, the sample size has been determined 200. The data and information needed to conduct the research have been collected through library studies and field methods. The data collection tool included a questionnaire containing 14 questions. To determine the validity of the present research questionnaire, the opinions of experts have been examined using the convergent and divergent validity indices. Also, the reliability of the questionnaire has been confirmed by computing the Cronbach's alpha coefficient. In this research, modelling and data analysis have been performed using Structural Equation Modelling (SEM) and the Amos software.

The findings indicated that the integration of green customers has a significant positive effect on the performance of green innovation and the environmental awareness of senior managers. The environmental awareness of senior managers had a significant positive effect on the performance of green innovation. The mediating role of senior managers' environmental awareness and the moderating role of company size and internal integration were confirmed. The environmental awareness of senior managers had a significant positive effect on the performance of green innovation.

Originality/value:

 The literature review indicated that in none of the previous studies, the parameters of environmental awareness of senior management, internal integrity, company size, green innovation performance, and green customer integrity have not been investigated simultaneously. The simultaneous use of such parameters gives a broader view. This is a significant feature that distinguishes the current study from previous studies.

Determination or state estimation is one of the pillars of the Attitude Control System. Sensors are the main instrument for determining the attitude of the system, but due to the presence of various noises and disturbances affecting the attitude sensors, appropriate filtering methods should be used. Cost and weight reduction in flight systems has been very important, so the use of microelectromechanical sensors, due to energy consumption, weight and low price, has received much attention. But noise is one of the drawbacks of microelectromechanical sensors that by combining data from different sensors using fusion algorithms, the data can be improved. In this research, the Gain scheduled complementary filter algorithm on a low-cost sensor and in laboratory conditions, based on a test platform with high dynamics and noise is implemented and compared with Kalman filter data and fixed reference. Finally, laboratory tests that the proposed algorithm works more accurately than the Kalman filter by applying noises in a static state as well as considering the oscillatory motion.

Defense industries are considered as one of the most important pillars of a nation's national power and one of the most strategic and important sectors due to their role in creating a deterrent capability against foreign threats, and therefore they are effective in creating and promoting national security from which the whole society benefits. On the other hand, the performance of the defense sector is tied to the supply chain performance and project risk management to a large extent. Defense industries as set of project-based organization with a high-tech, always need to use new tools and methods in these projects and projects success in this sector and maintain the continuity of network operations, is highly dependent on having strong and stable supply chains and the ability to project risk management. Therefore, identifying and evaluating risks and hazards can provide better and more accurate decision-making conditions for project management and achieve the goals and success of defense projects. So, research about it is one of the important and basic issues in this field. In this study, in order to evaluate the improvement of project management based on risk management and green supply chain in products related to defense industries, data on project risk management variables, green supply chain management, project management performance and project success were collected using a questionnaire. Based on the results, according to the model hypotheses and modeling of structural equations, the partial least squares method was implemented in SmartPLS software. The analysis of the results indicates a suitable model and good effect of variables. According to the results obtained in the model fit, all variables in all domains gained a good amount of validity and reliability in the model. Also, in the overall effects of the model, it was shown that all the relationships and effects of the variables of project risk management and green supply chain management on project management performance and project success are significant. Therefore, it can be concluded that project risk management and green supply chain management are two important and fundamental factors in project management performance and project success in our country's defense industry.

In a flying system, attitude control is one of the essential subsystems. In this subsystem, estimating the current state is very important to control the state, which is achieved by considering the attitude sensors. Comprehensive research is being done today to reduce the cost of Attitude sensors in applications such as drones, satellite simulation platforms, etc. For this purpose, sensors based on Micro-electromechanical Systems have received much attention due to their small size and low energy consumption. This model of sensors, despite its many advantages, has various noises and disturbances that require the application of fusion and estimation algorithms to obtain an acceptable output. In this research, to determine the attitude of the test platform, data fusion algorithms including complementary filter, Kalman filter, and Extended Kalman filter are implemented on a low-cost sensor. The mentioned estimation methods were implemented on the test platform and by determining the effective parameters in the estimation algorithms, the desired accuracy was obtained. The module obtained in these experiments is comparable to more expensive sensors.

Time and cost are significant factors in every project. By reducing the resources allocated to the project, project costs are reduced, while the reduction of available resources means the inability to simultaneously implement activities or activities in the shortest possible time, which in turn increases the duration of the project. This is although, in all projects, the completion of the projects in the earliest time is considered one of the important parameters of the project. Considering the highly practical application of the examined problem, project scheduling by investing multi-skill resources with the possibility of changing the skill level in fuzzy conditions can be considered a positive step towards creating project scheduling problems.                         
Design/methodology/approach: In this paper, the proposed mathematical model of meta-heuristic genetic algorithms to solve the proposed model is discussed and explained in detail. Several skills are needed to perform each activity. The goal is to optimally determine resource availability and find the best schedule by minimizing investment in resources.              
Considering the activities' need for different skills as well as the expertise of the project members in different skills, it seems obvious that each activity can be done with several different situations in terms of human resources allocation, which might be only for one activity, reaching more than 10 modes. As a result, compared to MRCPSP, this issue has a much higher complexity. The Resource Investment Problem (RIP) is a variant of RCPSP where renewable resource constraints are considered decision variables. In many projects, managers, in addition to making decisions about the time of implementation of activities, should determine the number of resources allocated to activities in each period of the implementation of activities according to the status of the project, which means ignoring the constant pattern of resource consumption for activities during their implementation.                          
Practical implications: By comparing the algorithms with the indicators of maximum extension, distance from the ideal solution, distance, and several Pareto solutions, it was found that the multi-objective genetic algorithm performs far better than the multi-objective Cuckoo algorithm regarding the criteria, distance from the ideal solution, and the largest expansion. However, in terms of the number of Pareto solutions, the algorithm is not superior to the other algorithms. Therefore, it can be concluded that the multi-objective genetic algorithm has relatively a better performance than the multi-objective Cuckoo algorithm.           
Social implications: In this research, each activity can be performed with several different situations in terms of human resource allocation, which may reach more than 10 situations just for one activity. As a result, compared to MRCPSP, this issue has a higher level of complexity. Literature review indicates that being multi-skilled increases the productivity, quality, and consistency of work and gives managers more flexibility in work allocation.              
Originality/value: One of the most important branches of project scheduling knowledge is the problem of project scheduling with limited resources. This new concept has led to the development of one of the most general modes of scheduling problems under the title of multi-mode project scheduling with limited resources, which solves many real problems and can be modeled for application.

Today, the efficiency of the supply chain is a prerequisite for the success of many economic enterprises. Performance evaluation is also an important issue in the supply chain management. The purpose of the current research is to evaluate the performance of the service supply chain using the supply chain operational reference (SCOR) model and the fuzzy prioritization technique. In this research, samples are obtained through the purposeful and non-probability snowball sampling methods and the opinions of 15 Atka Company experts. The process of conducting this research includes three stages. The first stage is identifying the effective factors in performance evaluation of the service supply chain based on the SCOR approach. The second and third stages are screening the identified factors using the fuzzy Delphi technique and prioritizing the factors using the fuzzy approach. In the prioritization of the measurement scales the non-linear optimization model is used. The results show that in this performance evaluation, the criteria of reliability, property, agility, flexibility, cost and responsiveness achieve the highest priorities in descending order.

Science production through the publication of articles in indexed journals is one of the most important outputs of higher education centers. Today, quantitative and qualitative evaluation of scientific articles is one of the usual methods of evaluating the research activities of universities. The managers of Ferdowsi University of Mashhad have always been concerned about the level of scientific production of their faculty members in order to maintain and improve the scientific status of the university. The publication of academic faculty members' articles in different years can be affected by various factors which identifying them can help the university managers in planning and policy-making in order to achieve the goal of increasing the growth of science production.

There are studies conducted about the influence of effective factors on the production of science, but most are qualitative and limited to the identification of the factors and have not focused on measuring the factors qualitatively.This research is based on a mixed-exploratory approach that seeks to discover the influencing factors in the number of publications of international scientific articles and the effective scenarios for its growth. This research has been done in two qualitative and quantitative phases. In the qualitative phase, using the Delphi method, which identified the key factors influencing the increase in the number of articles published, and in the quantitative phase, using the system dynamics method, which evaluated the impact of each factor and finally determined the best scenarios.

In the first phase of this research, some influential factors in the publication of articles by the faculty members of Ferdowsi University of Mashhad were identified by reviewing the sources and using the content analysis method. Then, using the Delphi method, the identified factors were available to experts, which included 20 faculty members in the five fields of pure sciences, engineering, agriculture and biological sciences, behavioral sciences, and humanities with the highest number of published articles. In the second phase conducted using the system dynamics method, the data related to the factors identified between 2005 and 2019 were collected, and after determining their logical relationships and drawing a causal-circular diagram, their dynamic diagram was used to examine the extent of their influence on each other was drawn.The results obtained from the review of sources and experts' opinions led to the identification of five key factors and variables, which are: increase in the recruitment of doctoral students, increase in the recruitment of master's students, increase in research projects, increase in sabbatical leaves and increase in a grant.In the second phase, after obtaining the dynamic diagram and data analysis in the simulation model, the initial results showed that the average article of each faculty member in the target year (2030) with the increase of the doctoral student variable is 35.36, the master student variable is 31.88, the grant variable is 31.51, The research project variable will be 31.47 and the sabbatical leave variable will be 31.2.But by calculating the cost-effectiveness of each of the variables in order to have a better strategic plan by increasing the budget of each variable by an equal amount, the average articles of each faculty member in the target year was: Ph.D. student 36.62, sabbatical leave 31.77, research project 31.37, master's student 31.19 and grant 31.16

According to the obtained results, three scenarios were suggested as the best scenarios to increase the number of articles by academic staff members at Ferdowsi University of Mashhad. Increasing the number of doctoral students, both with limited financial resources and with regard to a limited budget, is considered the best scenario for increasing the number of articles.Assuming that the university does not have a policy to increase the ratio of doctoral students to faculty members for any reason, the best scenario after that is to invest in the sabbatical leave variable.Currency restrictions and the absence of faculty members in the university may make the sabbatical leave not among the priorities of the university. Therefore, in this case, the third proposal scenario-based to increase the faculty members’ articles on this research is to increase the number of research projects.

The relief logistics and humanitarian supply chain in academic literature refer to the process of planning‎, ‎execution‎, ‎and effective controlling of the flow of costs and information and storage of necessary goods and materials from the point of origin to consumption with the primary purpose of reducing and relieving the affected people suffer. This paper discusses a multi-objective model for multi-period location-distribution-routing problems considering the evacuation of casualties and homeless people and fuzzy paths in relief logistics‎. ‎Firstly‎, ‎an uncertain multi-objective model of the problem was developed based on uncertain parameters of demand‎, ‎time‎, ‎and transport capacity‎, ‎and then‎, ‎using the fuzzy programming method‎, ‎uncertain parameters of the problem were controlled‎. ‎As the problem is NP-hard and GAMS software has not able to solve the model in larger sizes‎, meta-heuristic algorithms of NSGA-II and MOPSO were used to solve the problem.

Nowadays algae, which are Phototroph  diatom, are capable of converting nonorganic photos into organic matter, have found many applications in the food, pharmaceutical and sanitary industries. In this study, the effect of adding different levels of Dunaliella salina microalgae biomass on the physicochemical and sensory properties of yogurt during a 21-day storage period was investigated. Dunaliella salina mass powder was added to milk at 4 levels (0, 0.5, 1 and 2% by weight) in the pre-pasteurization stage. Tests including pH measurement, water holding capacity, tissue measurement and colorimetry of samples performed on the first, seventh, fourteenth and twenty-first days after production and evaluation of viscosity and sensory characteristics on the first day after production on the produced yogurt. The results showed that the addition of Dunaliella salina biomass at different levels caused a significant decrease in pH. The water holding capacity of the samples decreased with increasing algal level and storage time (P <0.05). The amount of stiffness, viscosity and color parameters of the yogurt samples showed a significant decrease with increasing algal surface (P <0.05). Sensory evaluations showed that with increasing biomass levels, sensory scores and overall acceptance from consumers decreased. Due to the unique nutritional properties of Dunaliella salina powder, the use of bioactive compounds of this microalgae can also be one of the proposed approaches for use in various food products, including yogurt.

In recent years, the use and implementation of the closed loop supply chain has been important because of the improvement in corporate profitability, environmental issues and sustainable development. This has led to a wider range of research and articles in this area. Therefore, studying the effective factors and their impact level is a better understanding of the design of a closed loop supply chain. The main focuses of this paper is on the planning of production capacity, taking into account customer behavior and service on the level of returns in the supply chain. The purpose of this paper is to clarify the effective variables and how they approach each other in order to achieve the goals of the chain. So, first, there is an overview of the subject literature and the key variables of some of the papers have been identified. In the next step, by drawing the causal and nonlinear diagrams, the relationships of the variables were examined together and then determined by the flow diagram, state variables, and accumulation locations in the chain. Finally, the model has been validated and validated using dynamic modeling tests such as sensitivity analysis, boundary condition testing, etc.

Public transport plays an essential role in the social and economic development of any country by facilitating relocation and increasing access to services. Therefore, identifying the economic, social and cultural factors influencing the demand for public transportation will greatly help planners and policymakers in this area. In this study, using public transportation data and the opinion of experts, the causal diagram of public transportation in Mashhad was designed and simulated using Vansim software. Finally, with the opinion of experts, 4 scenarios were presented, the results of each of which were examined based on the demand of the public transportation system in Mashhad. The results of the scenarios show that with the doubling of the budget by 70% and the tripling of the budget by 91%, the demand for public transport will increase. Reducing the price of the bus to 50 percent (50 percent discount) will add 10 percent to the number of passengers using the bus, while a further reduction of up to 70 percent will not lead to a further increase. Initially, by increasing fuel prices threefold in the current situation, it will increase demand by 20% in public transport, which will decrease over time to about 7%. By doubling the rate of cultural activity, the percentage increase in public transport use is about 17 percent.

vStock market has been one of the most influential economic phenomena in the world for many years. The main players in the stock market are investors that are always looking to make the most profit. Since prices of stock market transactions is Impressionable from political, economic, social problems and the high volatility of prices, the prediction of stock market is very difficult.  The main solution for more profits in the market is making the right decisions about buying and selling appropriate stocks in appropriate time. Therefore, prediction is the most important requirements for traders. I this research, a new hybrid algorithm is proposed that uses imperialist competitive algorithm as a feature selection method and fuzzy adaptive neural inference system as a prediction function. This approach uses 63 features that affect the stock market, including economic features, Iran and other countries stock market indexes, technical analysis indexes and Japanese Candlestick on a daily basis in the period from 2010-2016. The Exchange Stock Index for the next day is considered as the target variable. The results show that the hybrid model includes Adaptive Neural Fuzzy Inference System (ANFIS) and Imperialist Competitive Algorithm, is much appropriate. This model is compared with a single ANFIS model has better approximation speed and the ability to predict the sto

Urbanization, growing population, and economic development cause a growing trend in waste generation of the world including our country. On the other hand, other concerns like landll limitation and pollutions of waste disposal, bring this matter to fore. In this paper, we are trying to represent a dierent approach in terms of systematic and managerial aspects of Solid Waste Management (SWM) using dynamic modeling for Household Waste Management (HWM), which contains an important part of current waste generation in Tehran. In terms of management, our new approach is concerned with addressing the issue of HWM in particular, such that the use of social and qualitative variables (such as culture,education,familysize,andimpactofadvertising budget and source waste separation on recycling level) and also economic variables such as in ation, per capita income, buying power and per capita consumption, increase our innovation in terms of systematic approach. Casual loop and ow diagram were drawn by Vensim software. In the last sections, we performed the model validationandvericationusingtheestablishmentofextreme conditions, reality check, logical boundaries for variables and matching with historical data. Considering socio-economic factors, simulation time period, and current delays dealing with our issue, we are trying to analyze the best policies for HWM in Tehran in order to achieve the best possible results in recycling cost, recycling ratio, and disposal ratio regarding budget limitation. One of the main problems in (WHM) is the pollution caused by the landll and the shortage of land for burial. Two solutions are proposed to deal with this problem: therstisincreasingofbudgettomakeculture and also advertising and planning to promote the consumption culture; the second is focusing on the planning and implementation of source waste separation. The model indicates the second solution is better than the rst.

Interleukin 18 is a member of the cytokines that play an important role in the Th1-mediated immune response by inducing interferon-gamma activity in collaboration with Interleukin-12 (IL-18). Interleukin 12 and Interleukin 18 can play an important role in purifying viruses. Considering the importance of IL-18, this study was conducted to investigate the relationship between Interleukin-18 Gene polymorphism (-607 C/A: rs1946518) and the susceptibility to chronic hepatitis B infection.
In this case-control study, the genomic DNA of 115 patients with chronic hepatitis B (with positive results of HBsAg and Anti-HBcAb serology testing) and 115 non-HBV-infected controls (negative results of HBsAg and Anti-HbcAb serology testing and no history of liver disease) was extracted by salting-out method and the genotype of single-nucleotide polymorphism (-607 C / A: rs1946518) was sequenced using PCR-RFLP method.
FINDING: The genotype frequency of TT, GT, and GG in patients was 40%, 49.6%, and 10.4% in patients, and 41.7%, 42.6%, and 15.7% in the control group, respectively. No significant difference was found between the patients group and the control group.
Based on the results of this study, there was no clear relationship between IL-18 polymorphism and the potential for chronic hepatitis B infection. Therefore, this polymorphism cannot be a potential factor for chronic hepatitis B.

This paper presents a dynamic model to determine the effective factors which are responsible for making changes to the number of insured persons in health insurance companies and to study different policies for improving the system behavior toward its desired goals. For this purpose, all components of an insurance company including investment units, payment of medical expenses units, units which are related to the advertisement policies of the company and all other components that together will result in a complete collection of the company have been studied. According to the feedback relationships between these variables and the complexity of the issues, we use system dynamics approach for modeling and analyzing the effect of different policies. Given the goal of achieving the detailed results, Iranian Social Security Insurance is used as a case study. By taking into consideration this organization data from 2001 to 2011 in the proposed model, the results show that some parameters such as changes in investment policies and advertisement are effective factors, as far as the attraction of insurance company for people is concerned.

Credit risk interprets as the probability of obligations non-repayment by customer in due date is considered as one of causes financial institutions bankruptcy. For this purpose, data mining techniques such as neural networks, Decision Tree, Bayesian networks, Support Vector Machine is used for customer segmentation to high-risk and low-risk groups. In this paper, we present the hybrid Imperialist Competitive optimization algorithm and neural network for increasing classification accuracy in evaluation and measurement credit risk of bank customers. The proposed method identifies the optimistic features and eliminates unnecessary features decreases problem dimension and increases classification accuracy. To validate this method, it implements on UCI dataset and also on a reality dataset of a private Iranian bank. The experimental results show this method is more satisfactory than other data mining techniques. The neural network error for the test set decreases with selection of effective features and elimination of low-impact features by the Binary Imperialist Competitive Optimization Algorithm.
In addition test data error rate remains at acceptable level for other used classification methods. This article is the first use of algorithms Imperialist Competitive for credit risk assessment of bank customers.

This study designed to evaluate the effectiveness of non-verbal motor imitation on Length of Utterance of 8-12 years-old children afflicted with Autism Spectrum Disorders. The population included all children with autism spectrum disorder aged 16-8 years in Miandoab city in 1395. They were 30 children which recruited through available sampling and randomly assigned to two control and experimental groups. Research design was pretest- post-test design with control group and follow-up. Childhood Autism Rating Scale (CARS), non-verbal motor imitation package and package Action Pictures were employed. The repeated measures were used for the purpose of data analysis.The results showed that the non-verbal motor imitation is effective significantly in increasing the speech of children with autism spectrum disorder. According to benefits of non-verbal motor imitation in treatment for children with autism, it is recommended that this therapy method in conjunction with conventional methods is offered to parents and teacher of children with autism.

The Purpose of this study was to analyze the challenges of micro-credit fund of rural women. Statistical population of this research consisted the rural women of micro credit fund members in Lorestan province (N= 772) that 160 of them determined as a statistical sample by using Cochran’s formula. Samples were selected based on multi stage cluster sampling method and data were collected by questionnaire of them. Questionnaire's reliability and validity were confirmed respectively through computing Cronbach's alpha coefficient (0.96) and content validity. Data analyzed by SPSS and LISREL software. According to results of the exploratory factor analysis challenges of micro-credit fund in the empowering of rural women in Lorestan province categorized in seven factors that in order of importance are: Managerial – Administrative, Legal - Political, Production – Marketing, Members Character, Educational, Financial - Credit and Monitoring- Planning challenges. These challenges explained 74.5 percent of the total variance. Results of the confirmed factor analysis indicated the significance of these factors as challenges of micro-credit fund in the empowering of rural women in Lorestan province.

Dark triad of personality (narcissism, Machiavellianism and psychopathy) is one of the annoying and unhealthy personalities in psychology field. The purpose of the current study is first to introduce dark triad of personality tos scientific community of psychology and then investigate and compare these traits in convicts and non-convicts individuals.

This was a causal-comparative research. Statistical sample included 85 male prisoners of Urmia prison and 85 non-convicts. Participants were matched demographically. Research tools included Research-made Questionnaire for demographic information, Narcissism Personality Inventory (NPI), Machiavellianism Scale and Self-Report Psychopathy Scale (3rd edition). Data were analyzed by Multivariate Regression Analysis.

Data analysis showed that the differences between two groups were significant for narcissism and psychopathy at the level of p<0.01 and for Machiavellianism at the level of p<0.05. The most important difference was related to narcissism (p<0.001).

Results showed that there’s a significant difference between two groups regarding dark triad of personality. Thus, it can be concluded that the level of social aversive traits (dark triad) is higher in convicts. Because of the limitation of the participants in the research, it is suggested that future researches consider large groups, women, and different contexts and separated crime.

Public-private partnership means providing financial resources by the private sector to assist the government in carrying out large-scale infrastructure projects. Usually participatory projects of urban management that need high investment and have a great complexity in terms of technology and design are considered as participatory macro projects. So the performance evaluation of this kind of projects according to their regional influence is necessary. This study identifies and ranks the performance evaluation criteria of participatory urban management projects to use these criteria for creating a comprehensive approach for performance evaluation. The performance evaluation criteria are obtained for two major projects of Tehran urban management namely neighborhood house and cultural-sport complex by questionnaire with Cronbach’s Alpha = 0.97% coefficient. Then, these critera are grouped based on the aspects of the Balanced Scorecard including financial, clients, internal processes and learning and growth. Then, using the fuzzy analysis network process, the network structure was designed to display and measure weight of relationships between criteria and sub-criteria. Finally two projects are evaluated and ranked by TOPSIS and VIKOR and SAW methods. In the financial, clients, internal processes aspects, neighborhood house project showed a better performance than cultural-sport complex, but in the growth and learning aspect the result for two projects was almost identical.

Hepatitis B virus (HBV) infection is a major health problem worldwide and may lead to serious clinical complications, including chronic hepatitis, liver cirrhosis, and hepatocellular carcinoma. The host’s genetic background in immune system genes is a crucial etiologic factor in progression of HBV infection to chronic disease or clearance of the virus from the body. Interleukin 12 and its receptor (IL12 Receptor) play an important role in the clearance of viral infections, especially HBV. The aim of this study is to investigate the association between interleukin 12 receptor B1 gene single nucleotide polymorphism (rs401502 C/G) and chronic HBV infection.
In this case control study, genomic DNA of 105 chronically HBV infected patients and 105 healthy controls was extracted. Genotype of (rs401502 C/G) single nucleotide polymorphism was determined using polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) method.
The frequency of (rs401502 C/G) SNP for GG, GC, CC genotypes and G, C alleles was %53.3, %41, %5.7 and %73.3, %26.7 in the chronic patients and %51.4, %41, %7.6 %71.9 , and %28.1 in the control group, respectively. Statistical analysis of the results showed that there was not any significant difference between the case and control groups (p=0.851).
In this study, no association was found between (rs401502 C/G) single nucleotide polymorphism within IL12RB1 gene and chronic hepatitis B virus infection. It seems that this SNP does not play a crucial role in susceptibility to HBV chronic infection

Projects are planned based on estimated amounts that are the result of having little information about the future plans. According to the uncertainty of planning, time delays and costs of uncertainty are inevitable. The main objective of this study is to present a new approach based on failure mode and effects analysis and fuzzy logic to identify the affecting risks on duration of projects and ranking them using Kepland technique. In addition, in this research Shannon entropy is used for calculation of the weights of indexes. So after the study of related researches as well as through interviews and Delphi technique, some risks were identified. Then, based on three indicators of risk in the FMEA (severity, probability of occurrence, probability of detection), three questionnaire was prepared and their validity was confirmed by experts and reliability was calculated by Cronbach coefficient using SPSS software. The population of the study is 22 managers and experts that work on Debal Khazaei Company. Using triangular fuzzy numbers, the verbal variables of questionnaires became fuzzy numbers. Shannon entropy is used for calculation of weight of each index. Then, using decision making methods, ELECTRE TAXONOMY, TOPSIS and SAW, the risks are ranked. Finally, because of the relative difference of ranking in different techniques, Kapland technique is used to combine the results. TO help for developing the strategies of responding to the risks, some suggestions are presented. The contribution of this research is the simultaneous use of FMEA and Shannon's entropy to analisys the importance of risks and the ranking of them using Kepland technique.