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The purpose of this research is to compile a model of digital marketing strategies in successful Iranian startups. According to its purpose, the research method is practical, and in terms of its implementation, it is mixed (qualitative-quantitative). The statistical population of the research in the qualitative part includes 13 academic and executive experts in the field of startups in the country, who were selected using the purposeful judgment method and the snowball method, and the statistical population in the quantitative part includes the marketing unit of active successful startups. There are 250 people in the country (5 companies) and marketing professors of 5 top universities in Tehran, and the statistical sample was 148 people, 180 distributed and 163 analytical questionnaires were selected using Morgan's table. A semi-structured interview and a researcher-made questionnaire taken from the qualitative section were used to collect information. In the qualitative part, the data theory method of the foundation was used, and the data obtained from the interviews were coded and analyzed in the three main stages of open coding, central coding, and selective coding, and in the quantitative part, the factor analysis of the indicators was done. The results of the qualitative part indicated that 241 primary codes, 46 central codes and 14 selective codes were identified and extracted. The results of the research showed that the causal conditions with 4 variables of network capability, use of artificial intelligence, marketing capability and customer knowledge have an effect on digital marketing strategies, and the results of confirmatory factor analysis showed that the fit indices of the model were confirmed. Extended Abstract Introduction With the growth of ECT technologies including artificial intelligence, GPS, Bluetooth, QR code and other mobile and Internet connected technologies, marketers can offer micro-experiences/activities/services at an ultra-local level and adjust their messaging to effectively target small consumer segments locally (Singh & Keating, 2018). In this regard, digital marketing activities including mobile marketing, search engine based marketing, institutional marketing, email marketing, social network based marketing, etc. have been proposed. (Dwivedi et al, 2020). On the other hand, social networks have also created new challenges and advantages. It is important for companies to act in the field of specialized social networks so that digital marketing is not used by inexperienced experts and companies are safe from adverse effects by paying special attention to aligning their organizational goals with digital marketing solutions (Aswani et al., 2019). Internet technology and the increase in the number of Internet startups have fundamentally affected the world economy. The Internet provides companies with the opportunity to offer their products and services internationally 24 hours a day (Kohler, 2016). Experience shows that in the future, all organizations must operate online in order to remain competitive. The cost of advertising and marketing products and services on the Internet is very low compared to advertising and distribution costs related to traditional methods. Small and medium businesses are an important part of the economy in all countries, but they are heavily influenced by rapid changes in the external environment, especially demographic and economic. These rapid changes affect the marketing department of these businesses to meet the needs and expectations of customers in order to maintain a competitive position in the market (Sedaghati & Seiedin, 2023). Based on this, the current research is looking for an answer to this question: How is the formulation of digital marketing strategies model in successful Iranian startups? Theoretical Framework Digital marketing The term digital marketing has been referred to as a subset of marketing management and advertising management since two decades ago (Kannan, 2017). Digital marketing includes the set of all tools and activities that are used to market products and services on a digital platform (web, mobile internet or other (digital) tools) (Vaziri Gohar & Abdolhosani, 2020).Digital marketing strategiesIn this changing world, there is an urgent need for a strategic vision and a clear strategy map to sustain business growth. As a result, organizations cannot implement digital marketing without a clear definition of the strategy.Create a good quality customer experience.In defining the digital marketing strategy, management should determine the transition plan to identify the ability of human resources to cope with the change. The company must help, accompany its employees during this transformation, and invest in their retention and competitive advantage (Erdmann & Ponzoa, 2021). Javid et al, (2023) investigated the quality of customer relationship management for the development of digital marketing strategies in Bank-e Shahr. The results of the research showed that the variables of infrastructure, organizational environment, customer orientation, human resources, communication management, service quality, management and planning, strategic management, marketing and performance are in a favorable condition in Bank-e Shahr. The use of up-to-date technologies and the implementation of a suitable organizational structure for managing relationships with customers were identified as reasons for this favorability. Hamdi et al, (2023) investigated the identification of dimensions and components of acceptance of customer relationship management social systems by professional users using Web 2.0 technology. The identified factors were extracted in the form of 40 indicators, 8 components and 3 dimensions. Components and indicators of dimensions and components of acceptance of customer relationship management social systems, including three dimensions; organizational, customer, and technological; which organizational dimension has three components (manpower, organizational culture, organizational structure), customer dimension includes three components (value creation, performance expectation, customer satisfaction), and technological has been identified as having two components (social networks, content production). Research methodology According to its purpose, the research method is applicable, and in terms of its implementation, it is mixed (qualitative-quantitative). The statistical population of the research in the qualitative part includes 13 academic and executive experts in the field of startups in the country, who were selected using the purposeful judgment method and the snowball method; and the statistical population in the quantitative part includes the marketing unit of active successful startups in the country (5 companies) and marketing professors of 5 top universities in Tehran; as many as 250 people, and the statistical sample was 148 people, 180 analytical questionnaires distributed and 163 were selected using Morgan's table. A semi-structured interview and a researcher-made questionnaire taken from the qualitative section were used to collect information. Research findings In the qualitative part, the data-based theory method was used, and the data obtained from the interviews were coded and analyzed in the three main stages of open coding, central coding, and selective coding; and in the quantitative part, factor analysis of the indicators was done. The results of the qualitative part indicated that 241 primary codes, 46 central codes and 14 selective codes were identified and extracted. The results of the research showed that causal conditions with 4 variables of network capability, use of artificial intelligence, marketing capability and customer knowledge have an effect on digital marketing strategies; and the results of confirmatory factor analysis showed that the fit indices of the model were confirmed. Conclusion The current research has been conducted with the aim of developing a model of digital marketing strategies in successful Iranian startups. The results of the present study are in agreement with the results of Javid et al, (2023), Saeidi & Hoseinzadeh Naer (2022), Gholipur (2022), Boban et al, (2020), Bozkut & Gligor (2021), Musavirad & Ahmadi (2022), Dehghan (2018). Malek Akhlagh et al, (2021) showed that electronic customer relationship management means the development of traditional customer relationship management with the help of Internet technologies and an attempt to improve and fill the communication gap in which companies' marketing performance helps through examining the created development. Digitalization blurs the boundaries between technology and management and facilitates new business models based on the concepts, methods and tools of the digital environment. According to the results obtained from the research, it is suggested: Strengthening business practices with the aim of increasing competitiveness based on artificial intelligence should be considered, which leads to a major transformation in business. By using artificial intelligence, startups are able to identify, consider and understand their target buyers, and understand which type of product may be most needed at a specific time. With the evolution of big data and technologies, startups will be able to estimate buyer activity and monitor data-driven companies in any catastrophic situation and will obtain significant results that will improve their marketing decisions. Based on marketing capabilities, startups can meet the needs of current and new customers both through the development of new products and through the development of features and applications of existing products in order to ensure stability and survival, and to avoid shocks caused by new waves of competition based on new technologies.

The purpose of this research is to investigate the effective factors in predicting the academic performance of undergraduate students in the classification of four classes. To achieve this goal, the study follows the CRISP data mining method. The data set was extracted from the NAD educational system for the bachelor's degree in Shahed University for the entry of the years 2011 to 2021. 1468 records were used in data mining. First, the effective features on students' academic performance were extracted. Modeling was done using Rapidminer9.9 tool. To improve classification performance and satisfactory prediction accuracy, we use a combination of principal component analysis combined with machine learning algorithms and feature selection techniques and optimization algorithms. The performance of the prediction models is verified using 10-fold cross-validation. The results showed that the decision tree algorithm is the best algorithm in predicting students' performance with an accuracy of 84.71%. This algorithm correctly predicted the graduation of 77.88% of excellent students, 85.26% of good students, 84.69% of medium students, and 85.96% of weak students based on the final GPA.

IntroductionWheat (Triticum aestivum L.) is one of the most important grains used in the world and its production is reduced in different regions due to drought stress. the plant antioxidant system can scavenge the reactive oxygen species (ROS) produced under drought. Induction of mutation using gamma ray is one of the common methods for genetic modification and identification of tolerant and resistant mutants. Mutant T65-58-8 is one of these drought tolerant genotypes that has been obtained by irradiation to Tabasi wheat genotype. The wheat plant needs irrigation during the flowering stage and drought stress is very important in this stage. In this study, in the flowering stage, the enzymes superoxide dismutase (SOD), catalase (CAT), glutathione reductase (GR) and glutathione peroxidase (GPX) involved in the mechanisms of tolerance to oxidative damage of ROS in the flag leaf were studied and the expression of the genes related to these enzymes was investigated using RNAseq. method.Materials and methodsDrought stress was applied based on field capacity (FC). The experiment was performed as a factorial experiment in a completely randomized design with three replications. Factors studied in this experiment include genotype at two levels (Tabasi parent and Mutant T65-58-8) and drought stress at 5 levels (100% FC or control, 75%, 22%, re-sampling from control pots at 18% FC and sampling after re-irrigation to the pot when had 90% FC). Wheat growth stages can be studied by Zadoks index. SOD activity was measured by Minami and Yoshikawa method, CAT activity by Aebi method, GR activity by Foyer and Halliwell method and GPX activity by Hopkins and Tudhope method. RNA sequencing was performed using Illumina NovaSeq 6000. Gene expression was obtained based on sequencing data by Bowtie2, Tophat2, HTseq-count and Featurecount softwares. After normalization by generating FPKM, Log2FC gene expression was calculated.Results and discussionExamination of superoxide dismutase (SOD), catalase (CAT), glutathione reductase (GR) and glutathione peroxidase (GPX) indices showed a significant difference (p

Background: Air pollution is one of the most important problems facing people all over the world today, especially in big cities. The ever-increasing population growth, as well as the increase in vehicles and the number of industrial factories in the city of Isfahan, have led to this city being considered one of the largest industrial cities in Iran. Therefore, this city is considered the second most polluted city in Iran after Tehran. The city of Isfahan faces the crisis of air pollution on many days of the year, which directly and indirectly affects all aspects of people's lives in this city. Among these impacts is the quality of rainwater in the area, which joins the surface and groundwater in the region and affects its quality. This cycle will continue and air pollution will affect the quality of drinking water, agriculture, respiratory diseases and, in a word, the health of the people in this region.Materials and methods: In this study, the effects of air pollution in Isfahan on the quality of rainwater in the 10th district of Isfahan city were investigated. The quality of rainwater was studied based on the World Health Organization standard for drinking water, APHA standard for running water, Chinese standard for agricultural use, and Iranian standard for drinking water and agricultural use. To evaluate the air quality of the region, the statistics of the Isfahan Meteorological Organization station were used and the meteorological parameters were analyzed based on the American Environmental Protection Agency standards. Results: The results showed that the EC value of rainwater is more sensitive than pH to determine the suitability of rainwater quality for drinking uses, so when considering pH, many samples have favorable quality, but when considering EC value of the same sample, the quality of rainwater is unfavorable. The results of air quality monitoring based on the amount of PM2.5 on rainy days showed that 5 days were clean, 13 days were acceptable, and 6 days were unsanitary for sensitive groups. Conclusion: Isfahan urban runoff needs to be treated for drinking but it is suitable for agriculture. The results showed that the EC of rainwater is more dependent than pH to the rainfall depth. The results show that rainfall with a relatively small depth caused a significant increase in EC of stormwater. This decrease in the amount of precipitation has led to an increase in the amount of CO and PM2.5 in the atmosphere. The amount of rainfall did not affect the pH of rainwater, while with the increase of rainfall depth, the EC of rainwater has decreased significantly. In general, rainfall depth has a significant effect on EC concentration of rainwater. The results showed that in all the rainy days, the amount of CO, SO2 and O3 pollutants are in a clean state.

Introduction: One of the main challenges of the health system is improving the quality of healthcare services by adjusting the costs. The right choice of tools will bring economic savings besides excellent service quality. Since medical supplies are among the fundamental and costly elements in providing services, the expertise of purchasing has become an important and complex issue. This study aimed to prioritize criteria for purchasing medical supplies. Method: This research is an applied study conducted with a descriptive survey method. In this study, the criteria collected from related studies and completed with the opinion of experts were prioritized and weighted for four categories of medical supplies by the linear best-worst multi-criteria decision-making method using Lingo and Excel software. Results: By weighting sixteen sub-criteria of purchasing medical supplies in the form of five categories, the importance of each criterion was determined. According to the results, the two sub-criteria of "quality" and "price" were recognized as the most important and "seller's record" as the least important indicator in the purchase of medical supplies. Conclusion: Using the linear best-worst multi-criteria decision-making method with definite consistency of results and high reliability led to the prioritization and accurate weighting of criteria for purchasing supplies. Paying attention to the indicators in the purchase of medical supplies, in addition to guaranteeing the quality and continuity of services, will lead to a significant reduction in supply costs.

Nowdays, supply chain specialists are looking for the integrated development of the supply chain model in order to increase the competitiveness, effectiveness and reduce the problems in the supply chain. They always seek to identify and develop this process so that they can cover more aspects of the chain. Adding effectiveness indicators along with LARG indicators and using the basics of the dynamic system to improve the efficiency of the supply chain is one of the innovations of this study. At first, by using research literature and studies, 12 headings of indicators were selected as LARG-E indicators. Then, with the Fuzzy Delphi method, the relationships and importance of each of these components were determined, and more important variables were modeled for further investigation. With using the concepts of dynamic systems, causal loops were drawn. Then, to check the function of the model, dynamic hypotheses were developed with the opinion of experts. In the next step, the flow diagram of the model and also the validation tests of the proposed model were done. Finally, by examining the outputs obtained from the proposed scenarios, it was found that most of variables have better behavior in LARG-E approach.IntroductionIn recent years, with the addition of various competitions in the world markets, many researches have been conducted to use new technologies and researches in order to improve the production process and increase the effectiveness of these competitions as much as possible (Mohghar et al., 2017). All the goals that work in this field increase the competitiveness of the organization. This competition is by reducing costs, being present in the market and satisfying the customer. To increase profits, protect the environment, keep the markets stable and meet the expectations of customers, organizations should be provided using the existing environments in a set of customers (Pisha et al., 2016). Use chain management requires the use of new facilities and improvements to previous findings such as lean, agile, resilience and green to increase speed and competitiveness, selection and decision-making to achieve the organization and maximum effectiveness.Today, supply chain specialists are looking for the integrated development of the supply chain model to increase the effectiveness and efficiency of the supply chain in order to increase competitiveness and reduce supply chain problems. In this case, there is a consensus among experts that there is no comprehensive model. All the mentioned cases make it inevitable to design a comprehensive and effective model for the supply chain. The verifiable issue is the conflicts and the non-alignment of all the indicators of the paradigms with each other. LARG paradigms, without considering the spirit of effectiveness in each supply chain, cannot fully protect it against continuous changes in the competitive market arena. A comprehensive model that pays particular attention to effectiveness while implementing LARG paradigms has not been examined in the literature review and the consensus of experts. Therefore, in this research, we are looking to design a comprehensive model in a LARG-effective manner so that the effect of various LARG-effective indicators on the performance of the supply chain can be investigated. The integration of LARG paradigms has been studied a lot so far, but its development is based on the concepts of innovation effectiveness of this research, and in this way, the dynamic system approach was used.Materials and MethodsTo formulate a LARG supply chain, first the framework, indicators and variables of each LARG paradigm were extracted from the research literature, then in order to develop them with effective concepts, the effective supply chain was studied. In order to implement the fuzzy Delphi approach, based on the effectiveness indicators extracted from the subject literature and LARG supply chain approaches, operational indicators were provided to the experts participating in the research in the form of a questionnaire via email and after initial coordination. After collecting the completed questionnaires, fuzzification operations, fuzzy averaging and then de-fuzzification were performed. The results were brought to the attention of the participants and they were asked to apply their desired changes according to the obtained results. This approach reached the saturation stage in the third round and there was no change in the opinions of the participants and the consensus of the panel experts was the final and trusted output of the Delphi method. Finally, according to these weights, 9 quantitative variables had the highest importance and were used for dynamic modeling. The simulation stage is done with the help of software and Nasim. According to the features of modeling based on system dynamics, this approach was chosen as the main research tool in this study because there are linear relationships between the variables and there are nested feedbacks between the variables of the subsystems, the importance of simultaneously improving the performance in different layers of the producer, supplier and distributor. Which is one of the goals of this research, with this approach, it can be a very suitable tool for decision-making by the senior managers of the organization.Discussion and ResultsOrganizations are trying to improve their competitiveness by adopting Lean, Resilient, Green and Agile strategies; But as it was said, the implementation of these paradigms, which sometimes have conflicting results, requires a new integration and index to align the goals. So far, many researches have been done by merging two or more paradigms, the combination of all 4 paradigms called LARG has greatly helped to improve the performance of supply chains, but in this research, in order to improve the conflicts between paradigms, a new concept of spiritual effectiveness was given to the supply chain. Understanding the dynamics of applying the above four strategies and their effectiveness was done using the dynamic systems approach. In this research, the indicators of the LARG supply chain were defined based on theoretical foundations and interviews with experts; then the effectiveness indicators were placed next to them. These indicators were implemented in the printing and ink industry. In this way, an effective LARG integrated system was defined; then, using a dynamic model, dynamic hypotheses were first defined and state and flow diagrams were drawn. After correctness of the model and validation of the model, two scenarios were examined for 8 important variables. After applying the scenarios, the performance of LARG and effective LARG was compared. By applying each scenario in the designed model, it was possible to check the effect of new indicators on the variables and their behavior.ConclusionsAs a result, if the components of the effective supply chain are properly integrated with the LARG concepts, they integrate the conflict that may exist between the LARG paradigms and play the role of synchronization and improvement as a ruler and standard. The effective management of the LARG supply chain may not be defined as an independent variable, but it is a result of variables and indicators that improved performance in most cases.

Artificial Intelligence is an emerging technology that simulate human intelligence in machines and systems for their application business. Development of artificial intelligence requires extensive R&D activities. Management of R&D in field of AI needs to deploy novel knowledge to formulate and implementation of strategy, assign resources, organize and use of special tools. This paper aims, to identify and prioritize the components of data driven management of R&D in artificial intelligence technology. A hybrid technique was employed to perform the research. In Qualitative part, the literature of topic is reviewed, and 12 experts are interreviewed. Their opinions are analyzed based on grounded theory and 8 axial components were identified. In Quantitative part, by a questionnaire, the opinions of 85 experts of R&D and artificial intelligence were gathered through a questionaire and analyized based on structural equations model. The relvance and validity of the components were confirmed. The found components were weighted and proiritized through SWARA method as: systematic management, resources supplying, capability of big data analytics, supportive policies, infrastructures, data science development, organizational factors and business advantages.

AbstractMedical or therapeutic biology is dedicated to the development of research tools, diagnosis, development and delivery of drugs and vaccines through the use of cellular systems or processes and biological molecules. A very important strategic choice of companies in the biological drug industry is technology trading strategy. Independent commercialization strategy is recognized as one of the trade drugs in the world. The purpose of the present study is to identify predictions for the performance of independent commercialization strategy in Iran's biological industry using a comprehensive method. In this method, after the filtering of the articles, finally 42 studies that directly addressed the performance of independent commercialization in biological drugs entered the analysis phase of the Maxicioda software. After the combination of 68 distinct passwords, and at higher abstraction levels of the passwords in the form of 9 themes (strategic orientation, technology commercialization intelligence, R&D capability, product development knowledge integration, commercialization (production and marketing), The state -supporting mechanism of government and ownership regimes, formal integration and environmental dynamics were set. In order to construct the conceptual model of the research, they were extracted based on the component output, predictive structures of independent trading strategy, how the structures communication, and their measurement indicators were extracted. The validity of the proposed model based on the country's biotechnology experts with the Lavos content validity method and the minimum square minimum technique is: Independent commercial strategy performance predictions with a 91% determination coefficient include: Official integrity and integrity. Innovation, strategic orientation, technology commercialization, R&D capability, production capability and marketing.IntroductionBiotechnology is an important part of the society and economy of Iran. In the world, 140 drugs are produced from biotechnology, of which 16 are the most commonly used drugs. Nowadays 9 biotechnology and vaccine drugs such as hepatitis B drugs and various types of interferons (alpha, gamma and beta) are produced inside the country, producing 250 billion tomans worth of currency savings for the country. About $ 8 billion worth of biotechnology imports into the country are expected to cost $ 150 billion annually, which is expected to increase by about 900-800 billion USD annually. Biotechnology drugs are expensive drugs and if we can plan to produce these drugs in the next five years, we have to pay a thousand billion dollars for the import of such drugs, which will disrupt the health and medicine system of the country. This implicitly implies the necessity of commercialization, the formulation of commercialization strategies, and the successful performance of commercialization strategies in the field of biotechnology (Kebriaeezadeh et al., 2010). The question that is posed is that the predictors (determinants) of the operation of the independent commercialization strategy in Iran's bio-environmental industry?Case StudyIn the present research, the industry of biological drugs in Iran has been studied.Materials and MethodThe present study is based on the results of development; on the basis of purpose, explanatory-descriptive and based on the type of data is quantitative and the research quality is a hypothesis test. The design of the research has been done according to the five-step approach presented by McKinsey et al. (1999). Accordingly, the research stages are as follows: the design of the research includes the explanation of the problem and the review of the theoretical background; the formulation of a conceptual framework and the determination of the components and relevant indicators; validation of the research including general validation, validation of the research tool and data collection; analysis and Data analysis; Reporting the results of the research including summarizing the findings of research and writing the analyzes of the researchers.Results and DiscussionConsidering the content validity ratios calculated, in the conceptual model, the predictors of the performance of the independent commercialization strategy, the factors; the strategic orientation, the formal and informal integration of research units with the units of production and marketing, the ability to R & D, commercialization and intelligence of technology commercialization are the determinants of the operation of an independent commercialization strategy in the country's biotechnology industry.According to the model of performance prediction of independent commercialization strategy in the country's biotechnology industry, the following hypotheses have been developed.Hypothesis 1. There is a significant relationship between BI-technology intelligence and the performance of the development of a new biological medicine.Hypothesis 2. There is a significant relationship between the integrity (formal and informal) and the performance of the development of the new biological drug.Hypothesis 3. There is a significant relationship between firm strategic orientation and technology commercialization intelligence.Hypothesis 4. There is a significant relationship between the R & D capability and the performance of the new biological drug development.Hypothesis 5. There is a significant relationship between the commercialization (production and marketing) of the firm and the performance of the development of the new biological drug.Hypothesis 6. There is a significant relationship between R & D capability and commercialization (production and marketing) capabilities of the firm.ConclusionConsidering the significant relationships between the structure of the company's research and development capability, the structure of the enterprise's commercialization (production and marketing), the strategic directional structure of the firm, the formal and informal integration structure, the technology intelligence technology intelligence structure with the performance of the new product development, It can be said that in the case of: the existence of a suitable R & D workforce, proportional investment in R & D, and ..., we can expect a successful performance (the realization of new product objectives; new product life cycle management; the success of engaging in business activities; Making technology in comparison with direct rivals of the company; a significant increase in corporate revenues versus commercialization revenues Direct use; the company's more successful use of technology commercialization for strategic purposes in comparison with its competitors; providing unique features to customers; increasing the number of patents obtained from the new product development program; receiving good returns to costs; The program used for the new product development program and the competitiveness of the new product in the market) had an independent commercialization strategy.

Evaporation losses from free surface water in reservoir dams are one of the important processes in meteorology and hydrology. Each experimental methods estimates the evaporation based on the climatic conditions of each region. For this reason, calibration of the relationship between evaporation estimates in different regions are required (Vanzyl et al., 1989). experimental methods are common in engineering sciences. Most scholars, by modifying experimental methods and discovering new relationships, try to find a simple and high-level relationship to replace with the field methods. More than 50 experimental relationships have been proposed for estimating evapotranspiration by various researchers (Naorem and Devi, 2014). Despite the importance of evaporation in hydrology, less attention has been paid to it. However, with the correct estimation, it can be applied in water resource planning with fewer errors (Saadatkhah et al., 2002).In this research, the experimental methods of Mayer, Marciano, Shahthin, Henfer, Ivanov and USBR have been used to study the evaporation from the free surface of the Choghakhor lake, located in Chaharmahal and Bakhtiari province of Iran. The results have been compared with actual evaporation values from the free surface.

Changing the business environment and increasing the complexity of organizational decisions are important issues that organizations can use e-commerce to deal with. The successful deployment of e-commerce depends on the existence of specific strategies without which all the efforts of the organization may fail. Therefore, the success of establishing and implementing e-commerce lies in the application of appropriate strategic management. In line with this issue, the present study was an attempt to develop an effective e-business strategy development model or combined BS and BI approach to improve productivity. In this applied study, expert systems were used. Finally, based on the results and considering two components of business continuity management and business intelligence, some strategies have been proposed to draw attention to strategic planning in e-business.

Objectives: The development of information technology and its use in the health system have undertaken numerous measures for the protection and promotion of human health. However, long-term threats and the recurrence of infectious diseases are still the challenges in the world. Management of infectious diseases is of paramount importance in the global health system and is very complicated. Therefore, the aim of this research is designing a model to predict the covid-19 using artificial intelligence, which will ultimately be useful for rapid detection and control of Covid-19.Methods: To design a proposed model to analyze the spread of infectious diseases, an intelligent system is presented by combining mathematical dimensions, machine learning, and epidemiology. In this research, the target disease is COVID-19 due to its importance and epidemic. Despite extensive research on this disease, each study focused on a specific area due to its extensive dimension, and no detailed study is available on the main aspects of the disease. The research method is interpretive and exploratory in terms of paradigm and strategy, respectively, and is classified as descriptive-prescriptive in terms of implementation. The research was carried out in a seven-step process.Results: The results of the systematic review showed the rapid growth of documents since 2015, which can indicate the application of various fields of information technology such as the Internet of Things and machine learning in the field of public health and prevention of infectious diseases.In the algorithm, K values from 1 to 20 neighborhoods were calculated and the best accuracy was obtained at K equal to 2. Therefore, the accuracy of the algorithm is higher than 98% to predict the disease of Covid-19. After calculating the accuracy, the analysis of the confusion matrix showed that in K equal to 2, the sensitivity is 99% and the specificity is 92%.Conclusions: A comparison of algorithm results shows that in addition to accuracy, sensitivity and specificity obtained for algorithm are higher than traditional methods of diagnosing infectious diseases. Also, due to not having unnecessary complex features that only increase the model implementation time, the algorithm runs in a few minutes, and therefore the detection speed is completely acceptable. High sensitivity (99%) was obtained in the DT algorithm, which is very important for the diagnosis of COVID-19 and indicates the minimum number of false negatives in the test results. Therefore, the proposed algorithm is practical for the purpose of identifying the maximum number of people infected with Covid-19.

Technological innovation in the financial industry created the financial technology ecosystem. With the advent of artificial intelligence, the technology and financial worlds are intertwined to allow smarter financial processes to enable managers to make smarter decisions. It is not a fixed method of using the machine and accurate prediction of the test results using the machine algorithms is challenging. Much research has been done on the specific management of the customer experience, but research on financial technology in the artificial intelligence and machine industry in the sense of constructing a theory that can create a customer experience is a subject that pays less attention to. . This article, by reviewing 75 articles and summarizing it in 41 research articles, has examined the subject of the present study. In order to predict the presentation of theory, research method is a fundamental theory. The purpose of this article is to cover the gap of studies through which a research path is studied and the field of financial technology and artificial intelligence is examined. Findings show that what is done in extraordinary networks can be divided into five main parts of innovation. The findings provide a good way to address some of the issues in financial and artificial technology research for knowledge management experience through the possibility of providing a customer performance model.

Purpose – Organization managers tend to use an optimal and precise method to evaluate the performance of their organization by understanding the organization dynamics. The immediate research goal was to propose a dynamic model for the performance evaluation of a LARG supply chain with the balanced scorecard (BSC) approach. Design/methodology/approach – In this study, dynamic simulations are carried out for the performance evaluation of a supply chain. At first, a strategy map was designed, and measures are identified for each strategic objective considering the LARG supply chain measures. Afterward, a quantitative dynamic model was designed to identify the mathematical relationships among them. Findings – The proposed model is implemented in a company operating in the automotive industry. Based on the company’s strategic objectives, scenarios were designed and analyzed to evaluate the performance of the LARG supply chain with the balanced scorecard approach. Research limitations/implications – The BSC- based LARG supply chain evaluation has been studied for the auto part manufacturer sector. The different industry may lead to different results as the model designed important in each sector may differ as well as how each model is designed.Originality/value – The dynamic model enables managers to identify the determinants of the supply chain performance and set the scene for the necessary decisions by analyzing the possible scenarios in advance.

The purpose of this research is to evaluate the level to which a company’s activities in a supply chain are LARG. In this study, an integrated method is used to evaluate the LARG supply chain performance of a company resulting from the integration of LARG concepts and Balanced Scorecard approach. The BSC measures are selected based on the LARG concepts, and then the indicators entered into the dynamic model. Variables are changed in different scenarios to analyze changes in the company’s performance. Scenarios are designed to evaluate the supply chain performance using the strategic objectives. The results show that simultaneous implementation of LARG elements is not possible due to the trade off relationship. By analyzing the scenarios, it was found that by changing each parameter in the dynamic model, some LARG elements increase and at the same time, some other elements decrease. For example, by increasing the productivity of education, the level of leanness and resilience increases, but it has no effect on the environment. Using the designed dynamic model, the effect of each managerial action and decision on LARG can be determined and the extent to which strategic goals can be achieved.

Background and Aim: Children with Attention Deficit Hyperactivity Disorder are a good target group for cognitive rehabilitation Because their behavioral problems, including inattention, impulsivity, and hyperactivity, have a specific cognitive and cerebral origin. This adaptation of behavior to cognitive function provides an opportunity to repair behavior by strengthening cognitive function. This study aimed to compare the effectiveness of cognitive rehabilitation based on virtual reality technology as a new method and classical cognitive rehabilitation in improving the executive functions of children with attention deficit hyperactivity disorder. Methods & Materials: This research was a quasi-experimental study using a pre-test-post-test design with a control group. The statistical population included all children aged 7-12 years with Attention Deficit Hyperactivity Disorder in Tehran in 1398 who were selected by convenience sampling method and randomly divided into 3 groups of 12 people. In the pre-test stage, participants were assessed with the Attention Deficit Hyperactivity Disorder Rating Scale and the Computer Integrated Visual and Auditory Test (IVA-2). The first group received a virtual reality-based cognitive rehabilitation package and the second group received a Captain Log computer cognitive rehabilitation package, 12 sessions twice a week. No intervention was performed in the control group during this period. Post-tests were taken from all 3 groups after the intervention. Univariate analysis of covariance (ANCOVA) was used to analyze the data using SPSS software v. 26. Ethical Considerations: This study was approved by the Research Ethics Committee of the Islamic Azad University, Central Tehran Branch (Code: IR.IAU.CTB.REC.1400.001). Results: The results showed that both methods of cognitive rehabilitation intervention had a significant effect on cognitive functions (selective attention, sustained attention) of Attention deficit hyperactivity disorder (ADHD) children (P0.05). Conclusion: Virtual reality-based cognitive rehabilitation is as effective as classical cognitive rehabilitation on selective attention and sustained attention in children with ADHD. Virtual reality-based cognitive rehabilitation can be used as a new approach to rehabilitating this disorder.

The present study was conducted to evaluate the effects of nanosilver coating on the reduction of fouling fish cages of rainbow trout in the Ayush dam of Khorramabad from winter 2016 to autumn 2016. The nets were applied for antibacterial properties according to the exhaustion method The samples were collected from net panels (0.0625 m2) that were attached to the PVC frame, located at a depth of one meter from the side of the fish culture cages, and wet weight was measured, then it was identified with valid authentication keys. In this study, three genera of green algae and diatom were identified. The analyses showed that Do, temperature, and pH were positively and significantly correlated with Tetrasporaceae, wet weight and algae cover percentage. The Seasonal nanosilver panels treatment was free of fouling. Nanosilver coating can provide at least three months of effective protection against biofouling conditions. Nanosilver occupies the interstices of the polyamide polymer chain and interacts strongly with single pair electrons of nitrogen hence a coordinated complex is formed.

The increasing growth of space achievements, which is the result of the NPD and the increase in the level of exploitation of its findings, has made the space sector an effective role in economic development and increasing GDP and the space industry is also subject to this category. Structural actions in space have created problems in the field of rockets and satellites as a concern in space over the past decade. A review of the research background reveals the impact of three levels of industry, firm and process on NPD. In this research, the problematic situation in the space industry was identified, through interviews and documentation, and the results were validated by creating a focus group. 34 factors related to NPD at this level were identified by reviewing the research background. The extent of their impact on achieving the country's space goals was assessed by the SAW method of MADM and five factors affecting NPD were selected. Then, the interaction of factors was evaluated with Micmac software. Relationships between factors were prioritized by structural analysis of factors. It was found that the factor of structure and organizational relationships at the level of the space industry has a direct impact on the time of new product entry into the market. Therefore, the rulers of the space sector should pay special attention to them. Finally, priorities and suggestions for improving decisions for NPD were presented.

Background: Numerous studies have examined the effectiveness of behavioral therapy based on the acceptance and assessment of anxiety in patients with cardiovascular disease. However, research that has examined the effectiveness of acceptance-based behavior therapy on hidden anxiety, overt anxiety, and hypertension in cardiovascular patients has been neglected. Aims: To investigate the effectiveness of acceptance therapy based on acceptance of hidden anxiety, overt anxiety and hypertension in cardiovascular patients. Method: The present study was a randomized controlled clinical trial with a pretest-posttest design with a control group with baseline measurement after 3 months of intervention and follow-up. The statistical population included all cardiovascular patients referred to Baqiyatallah Hospital in Tehran from June to September 2017. Twenty-four patients were selected as target samples based on sampling and randomly assigned to two experimental and control groups (12 people). The instruments of this study were researcher-made demographic questionnaire (2019), open and hidden anxiety questionnaire of Spielberger (Gerash and Lashn, 1970) and acceptance and commitment-based behavioral therapy protocol (Finance, Ghaderi, Dahl, Niger and Inibrink, 2019). Data analysis was performed using repeated size analysis of variance. Results: Acceptance-based behavioral therapy had a significant effect on reducing hidden anxiety, overt anxiety, and blood pressure (p< 0/001). the results obtained in the follow-up phase were constant. Conclusions: Patients who attended admission-based behavioral therapy sessions had reduced levels of hidden anxiety, overt anxiety, and high blood pressure.

Background: Developmental delay in preterm infants was estimated to be more common than term infants. Identifying the factors predisposing to developmental delay can help experts and health professionals in this field to prevent developmental delay of the infants, and leads to better management of the condition of them. This study aimed to evaluate and investigate the predisposing factors of developmental delay in preterm infants in the first year of their lives. Methods: In this analytical cross-sectional study, 87 preterm infants were enrolled in the study by convenience sampling during the period of April 2016 to the end of March 2017 from two educational hospitals of Shahid Beheshti University of Medical Sciences (Imam Hussein hospital and Mahdiyeh hospital). Demographic and other initial data such as age, sex, gestational age, and the data about clinical problems observed at birth were collected through infantschr('39') medical records and were recorded in a special form for each infant. Also, the ASQ test was used to assess infantschr('39') developmental status at one year of age. Results: Based on the findings, 23 infants (26.4%) had the abnormal developmental condition at the end of one year. There was a significant relationship between infantschr('39') developmental status and their age, birth height, one-year-old weight, one-year-old height, duration of ventilator use, Apgar scores at first and twentieth minutes, seizures, reflex reduction, pneumonia, breastfeeding status in the first year of life, Retinopathy of prematurity (ROP), receiving occupational therapy services, and electrocardiogram (ECG) findings at one year of age. Among these variables, only breastfeeding status in the first year of life was able to predict infantschr('39') developmental status at the end of one year (OR=0.18). Conclusion: This study showed that the risk of developmental delay in preterm infants who are breastfed in the first year of life or fed the combination of breast milk and supplemental feeding is one-fifth lower than other preterm infants who were not breastfed.

Networking is performed by physically aligning its members and, in a real network, the correct placement of network components and the interaction between them are based on the network perspective and complementary capabilities for achieving continuous growth and set goals. Therefore, it is necessary to assign a role to network orchestration in the network formation and configuration, the network collaborative management, and ultimately network success. Despite a notable volume of research done in this regard, the problem of managing collaborative networks, different types of such networks, and differences between them require further study. This study aims to compare the types of orchestration structures of formal collaborative networks in Iran. To this end, based on judicial sampling, 5 selected collaborative networks were compared with by content analysis method and modeling of a valid orchestration model. The research results showed that collaborative networks in Iran followed three types of Shared orchestration structure, Lead Organization (orchestration networks), and each of these structures has different performance according to the type of collaborative networks in different areas. Therefore, when forming a network, it is necessary to select an orchestration structure that fits the characteristics of the network. Accordingly, in the end, a number of suggestions were made for each of the structures.

The purpose of this study is to identify the mental patterns of tourism industry co-creation. The present study is a mixed-exploratory study conducted using the Q-methodology. This research was conducted with the participation of ten professors familiar with the subject of the research as well as tourism experts. The discourse space of the present study was collected from a variety of sources and after evaluating and summarizing the discourse space, 39 terms were selected for the sample. Then, after collecting data from Q sorting, this information was analyzed using Q factor analysis. Distribution analysis showed that three distinct mental patterns can be identified among the research participants about mental patterns of tourism industry co-creation that explained about 76.903% of the total variance. These three mental models were named service development, customer value and organization,

Research Article Hamed Heidari* Morteza Mousakhani** Abstract: Providing financial services on Blockchain-based platforms as a new approach to financial markets has a lot of room for growth. This demonstrates the need to study and identify the drivers of users' attitudes towards using Blockchain-based financial services. For this purpose, technology adoption models have been used. Using a combination of several technology adoption models, this research aims to study the factors affecting customers' intention to use financial services in Blockchain-based platforms to determine what factors drive users to use them. For this purpose, first, the literature was studied and a conceptual framework was extracted, and in accordance with the model, a structural equation model has been developed. The results have shown that the individual tendency to trust and also structural guarantees, directly affect initial trust and in the following users’ initial trust influences users' behavioral intentions. In addition, technological features and task characteristics, directly influence technology-task fit and technology-task fit affects users' behavioral intention. Furthermore, expecting performance directly affects the behavioral intention of users. This study has concluded that the propensity to use financial services in Blockchain-based platforms is under the influence of social needs and even Blockchain constraints cannot reduce the desire to use financial services based on this technology. * Ph.D. Student, Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran. ** Faculty Member, Department of Management, Science and Research Branch, Islamic Azad University, Tehran (Corresponding Author: pres@qiau.ac.ir) , Iran. *** Faculty Member, Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran. **** Faculty Member, Department of Management Faculty of Management, University of Tehran, Tehran, Iran. ****** Faculty Member, Department of Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran. Received: July 16, 2019 Accepted: January 20, 2020 Research Article Drivers affecting the users' attitudes towards using financial Services in Blockchain-Based Platforms Hamed Heidari* Morteza Mousakhani** Mahmood Alborzi*** Ali Divandari **** Reza Radfar****** Abstract: Providing financial services on Blockchain-based platforms as a new approach to financial markets has a lot of room for growth. This demonstrates the need to study and identify the drivers of users' attitudes towards using Blockchain-based financial services. For this purpose, technology adoption models have been used. Using a combination of several technology adoption models, this research aims to study the factors affecting customers' intention to use financial services in Blockchain-based platforms to determine what factors drive users to use them. For this purpose, first, the literature was studied and a conceptual framework was extracted, and in accordance with the model, a structural equation model has been developed. The results have shown that the individual tendency to trust and also structural guarantees, directly affect initial trust and in the following users’ initial trust influences users' behavioral intentions. In addition, technological features and task characteristics, directly influence technology-task fit and technology-task fit affects users' behavioral intention. Furthermore, expecting performance directly affects the behavioral intention of users. This study has concluded that the propensity to use financial services in Blockchain-based platforms is under the influence of social needs and even Blockchain constraints cannot reduce the desire to use financial services based on this technology. * Ph.D. Student, Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran. ** Faculty Member, Department of Management, Science and Research Branch, Islamic Azad University, Tehran (Corresponding Author: pres@qiau.ac.ir) , Iran. *** Faculty Member, Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran. **** Faculty Member, Department of Management Faculty of Management, University of Tehran, Tehran, Iran. ****** Faculty Member, Department of Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran. Received: July 16, 2019 Accepted: January 20, 2020

Reviewing the recently published and authentic texts in the field of Library & Information Science’s education indicates some fundamental problems in this pedagogic process. According to different factors dealing with the process such as professors, learners, educational department and learning resources, confronting the challenges is considered as complex issues. Therefore, in this research Soft Systems Methodolgy (SSM) was chosen to propose a comprehensive model to solve the mentioned problems. Soft Systems Methodolgy (SSM) is one of the Action Research’s methods. In view of research approach, SSM’s considered qualitative. Based on the Checkland seven proposed stages, problem situation was identified, and then it was expressed in the form of rich picture. Driving root definitions and CATWOE model were cleared to accomplish the conceptual model. Comparison of the conceptual model to real world, also proposing feasible and desired changes are the fifth and sixth stages of the reserach. Finally, taking action to improve the current situation in the field of Library & Information Science’s education finished the procedure. Utilizing the seven steps of SSM, this resrarch draws the rich picture illustrating the process of Library & Information Science’s education and its issues dealing with the related ecosystem. Accordingly, the final model consisting of three ontologies (learners, professors, and educational content) was attained. To validate the semantic model, Cohen’s kappa coefficient was calculated. Pertaining to the high level of agreement coefficient, 9203/., the achieved conceptual model was approved. To utilize the comprehensive model, it was implemented by Protégé4.3 software and OWL2 language. The obtained model, approved by high level of expert agreement, not only can be an appropriate solution for the problems involved in Library & Information Science’s education in Iran, but also can be considered as a pattern for future researches in designation and implementation of semantic model of education in the other disciplines. The findings indicate that the semantic model is a complex concept including different aspects and indices which can be easily implemented and noticed by policy-makers, designers and other players in designation and assessment of teaching-learning environments.

Background and Aim: Given the increasing variety of biological drugs in the world and the significant role of these drugs in patientschr('39') quality of life, as well as the high risk of drug productions, biopharmaceutical companies need to revise their business model. The purpose of this study is to review the dimensions and components of biopharmaceutical companies. Materials and Methods: This is a comprehensive review and is based on the existing studies by searching valid databases such as PubMed, Science Direct, SID, Iran doc and Google Scholar from 2000 to 2019. All the searches were performed based on keywords such as “Components of Business Model”, and “Business Model of Biopharmaceutical Companies”. The initial search yielded 820 articles. After screening, 23 articles were selected for final study. Results: The overall dimensions of business model in biopharmaceutical companies are identical to other companies, but the components of the business model of these kinds of companies are various based on their performance, and the most important components include the value proposition, key resources, success factors, revenue stream and cost structure. Conclusion: Introducing the components of business model in this study can be adjusted based on the dimensions of business model and the characteristics of each biopharmaceutical company.

Owing to sanctions imposed on our country, it has become increasingly difficult but not impossible to improve organizational productivity. Achieving productivity entails flexible and accountable strategy adoption in the form of a comprehensive plan. The comprehensive industrial program underscores the importance of developing resource-based industries to gain competitive advantages and such a comprehensive plan is outlined based on getting a wider view and putting all relevant influential factors in perspective. The purpose of this qualitative study was to identify the factors influencing the perspectives on productivity improvement in Saipa Automotive Group. Six factors influencing organizational perspectives (political, economic, legal, social, environmental and technological) were detected while investigating Asian countries of Vietnam, Thailand, Indonesia, China and India. The research population comprised ten managers of Saipan Research and Innovation Department who completed an open-ended questionnaire. The research data were analyzed using supersession software, Delphi and paired comparisons.Then, Super Dissociation software was employed to prioritize the effective factors which were found to be: political (0.35), economic (0.27), social (0.14), legal (0.13), environmental (0.05), and technological (0.03).

This study investigates the factors affecting users' understanding of digital libraries with emphasis on Allameh Tabataba'i University Digital Library.The method of this study is descriptive-analytical and it is a purposeful one. All students of Allameh Tabatabai University were the statistical population of this study(18000 students) out of which 378 students were selected using simple random sampling method. Due to the lack of a standard questionnaire, a researcher-made questionnaire was used. The questionnaire used for data collection consisted of three demographic questions (gender, digital library experience and educational level) and eight components with 25 closed questions including system quality, information quality, service quality, usefulness, ease of use, digital library Affinity, user satisfaction and user loyalty. Data were analyzed using t-test, independent t-test and ANOVA, at significance level α = 0.05.: The findings showed that considering the calculated significance level, all factors affected students' perception of digital library of Allameh Tabatabai University including system quality (-39.88), information quality (-57.425), service quality (571.721) -), usefulness (-66.320), ease of use (-49.558), digital library Affinity (-60.944), user satisfaction (-61.497), and user loyalty (-60.488). Also, there was no significant difference between students' perception of digital library of Allameh Tabatabai University in terms of gender (0.554) and educational level (0.064). But there was a significant difference between students' perception of digital library of Allameh Tabatabai University and digital library experience (0.000) according to the level of significance calculated.The results of the study show the overall effect of the students' perceptions of the digital library of Allameh Tabataba'i University, and each of these components of understanding can be defined according to different models in different environments.

Groundwater is the main source of potable water for more than 1.5 billion people throughout the world, including arid and semi-arid regions like Iran. Literature review showed that there is no use of the dimensional similitude and physical modelling for estimating seepage from channels and its effect on the groundwater, yet. Thus, in order to better understand this phenomenon, the current study aimed at investigating the effects of infiltration and seepage on the groundwater recharge at different water level depths. Numerous studies have been conducted to assess the groundwater recharge, such as Yin et al. (2011) that utilized some methods such as the water table fluctuation method and the Darcian flux and water balance method in China. Similarly, using data from some irrigation projects and piezometric level data, Ochoa et al. (2013) evaluated the effects of seepage on the groundwater recharge in New Mexico. Moreover, Demlie (2015) compared the water balance method and the chloride mass balance method to quantify and investigate the groundwater recharge in Ethiopia. In the current research, the earth channel of Boldaji with loamy soil, located in Borujen city, Chaharmahal and Bakhtiari province, was chosen as the prototype. The dimensions of such a channel were transmitted to laboratory models at soil mechanics lab at Shahrekord University. Using dimensional similitude equations, 9 discharges (40-161 l/s) and 4 water-table depths (0.75, 0.8, 0.85 and 0.9 m from soil surface) were converted to the applicable discharges of the model. The results of the laboratory physical model showed that the infiltrated water raised the groundwater 3.5-11 cm. The values of recharged groundwater were, in turn, calculated by means of water balance method and the results showed no suitable estimates of such a method for the trapezoid and triangle cross-sections.

Integrating decisions in the supply chain is a challenge for producers who intend to optimize their supply chain costs. Vendor managed inventory (VMI) is one of the popular strategies for integrated supply chain management. In this strategy, customers provide their information to the vendor, and the vendor uses this information to manage their inventory and decide on the order quantity and delivery schedules. In this study, a three-tier green supply chain consisting of multi-retailers, multi-vendors with backorders is considered. The total cost of green supply chain is minimized and system reliability for manufactured goods is maximized by considering the constraints. The meta-heuristic methods of GA, SA and a combination of SA-GA are used to solve the model. Taguchi method was used to increase the efficiency of the algorithms. After performing the algorithms for problems of different sizes, the results were compared with respect to the efficiency of the algorithms. The obtained results suggest that the efficiency of the SA-GA is better than other algorithms. Finally, since the model is multi-objective, Pareto optimal solutions are analyzed.

Nowadays the growth in the use of social networks among different classes of world community is increasingly undeniable. Social networks database include Rich and valuable resources whose release and analysis with the purpose of marketing, publicity, National Security, Health and etc. can benefit researchers of public and private institutions. But respect the privacy of the entities whose information is available to data miner analysis is essential as a legal protocol. In this Paper, through qualitative methodology Meta synthesis, all related dimensions, indicators and codes were identified and then the importance and priority of each of the factors was determined. Subsequently, the improved model of anonymity was presented by an optimizing firefly algorithm and fuzzy clustering. The result of simulation and assessment of the proposed model on the data of four social networks such as Facebook, YouTube, Twitter and Google+ depicts that privacy preserving of data with the lowest distortion ratio and the more usefulness of data.

1. Introduction Farsi speakers have not paid much attention to Persian grammar publishing for the last few centuries, particularly in the case of prepositions and their equivalent meaning in Jar letters. Researchers have encountered many difficulties, due to the significant role which these prepositions play in conveying meanings, especially in the translated texts of ancient Persian literature. Considering that Arabic is the language of the Qur'an and the religious language of Muslim Iranians, Many valuable books such as those pertaining to the literature and history are written in Arabic, so Persian speakers must be familiar with this language and its rules for translating literary and religious texts into Persian. One of these critical literary books is the Tarikh-i Bel'ami, translated from Arabic into Persian. An important feature of the book is its style of writing, which is very close to the Arabic prose, and too many Arabic vocabulary has been used throughout it. Notwithstanding the translator has tried to translate Arabic into Persian, following the Persian style, he was not successful on that. Because due to numbers of reasons, he created some meanings, which had never been applied in the second (destination) language before. Those reasons are introduced as follows. The role of the grammatical topic, the similarity of the meanings of the Persian prepositions with the Jar letters in Arabic, the influence of the book’s original language (Arabic) on the translated text, and considering the fact that the meanings of each language can affect on the second language through translation. In this book, many Persian prepositions are adapted from Arabic or vice versa. In this paper, the meanings of the Persian prepositions "BE" compared with the Jar letter "BĀ" in the Arabic, as well as comparing their similarities and differences. By doing this research, the equivalence of the "BE" and "BĀ" becomes more accurate through the translation of the bilingual texts, and the substitution of the words associated with those is going to accomplish more accurately. Eventually the possible translation errors are going to be reduced, and the exact meaning of each word extracted from source texts are going to transfer to the destination texts correctly. 2. Methodology This research is fundamental and is done based on the criticism and analysis of data and documentation. The method of data collection is library-based and then analyzed by the comparative method. For this purpose, firstly, the Persian and Arabic grammatical books about the prepositions "BE" and the Jar letter "BĀ" were studied. Then, the meanings of these two words were extracted using authentic books and references. It is important to note that in the course of this study, the book of Tarikh-i Bel'ami was thoroughly examined. The statistical population is the preposition, "BE," in the Tarikh-i Bel'ami and the Jar letter, "BĀ." The analysis of the data in this study is based on a comparison of written evidence and documents, and any specific tools for this research have not been used. 3. Discussion The Jar letters are BA, TA, CAF, LAM, WAV, MONZO, MOZ, kHALA, ROBBA, HASHA, MEN, ADA, FI, AN, ALA, HATA, ELA. (Ibn Malik, 1996: 34) These letters are one of the most essential categories of the Arabic language that link the meaning of the verb to the noun. Some have stated that since the ability of some verbs to reach out the object is too low, these letters help the verb to reach out the object. (Ibn Aqil, 2011:3/8) The primary meaning of the letter "BĀ" in Arabic is "Elsagh." This letter is one of the seventeen letters of Jar that comes up before the noun and makes it "Majror," and has all the properties of the Jar letters as well. (Ibn Hisham, 1999: 2/11) The common meanings of the letter "BĀ" in the Arabic language with the preposition "BE" in the Tarikh-i Bel'ami book include: "Elsagh", "Sababiat or Talil", "Mosabehat", "Ghasam", "Zarfiat-e Makani," Zarfiat-e Zamani, " Mojavezat (An / Az) "," ["BĀ" synonymous with "Men" and "BE" synonymous with "Az"], "Estela", "Esteanat", "Entaha-e ghaiat", "Avaz va Badal", "Movafeghat va Motabeghat". Uncommon meanings of the preposition "BE" with the letter "BĀ" in the Arabic language in the the Tarikh-i Bel'ami include: "Tozih", "Seirourat", "Esteghragh-e Jens va Bayan-e Vahdat", "Tavali va Ta’aghob", "Moshabehat", "Ra-e Mafouli", "Taghsim", "Haal", "Souy va Janeb", "synonym of Dar-bareye", "Ekhtesas", "Mozadat", "Moghayese va Nesbat", synonyms "Kasre-e Ezafe"," "synonym of Be-Rasme, Be-Onvane, and Be-Masabe", "synonym of Bar-Ohde-e, Bar-Zemme-e", "Meghdar va Andaze". The non-common meanings of the letter of "BĀ" in Arabic with the preposition, "BE," include: "Moghabeleh," "Tadieh", "Tafdieh," "Tabeiz", "Ba-e Takid". 4- Conclusion There are many different meanings for the Arabic Jar letter, "BĀ", and the Persian preposition, "BĀ". The total number of the meanings of "BE" and "BĀ" is thirty-five, which thirty of them goes to "BE, and the rest eighteen goes to the "BĀ". These two letters share thirteen meanings; the preposition "BE" alone has seventeen meanings, while the letter of Jar "BĀ" has five of these meanings (Table 1). Therefore, in addition to considering the many commonalities in this field, we can say that the meaning of "BE" is more extensive than "BĀ," and the application of the most meanings of "BE" in the Tarikh-i Bel'ami is enormous (Fig. 1). We also state that the Persian language, especially the language of ancient texts, is highly influenced by Arabic rules and has plenty of grammatical commonalities, including; the common meanings in the Jar letter and preposition. In order to obtain these meanings, mastery of the Arabic language and the rules of that are necessary. Table 1: Number of Differences, common, and Total meaning of the preposition "BE" with Arabic Jar letter "BĀ"

Abstract Nowadays, the commercialization of technological products is considered as one of the most important requirements in Iran to improve the economic cycle. Using indigenous technology seems to be a rational approach due to the sanctions; therefore, identification of important factors in the commercialization context considering market downturn conditions can play an important role in the optimal performance of companies in the markets on technological product supply. This study aimed to develop and provide a model for commercialization of technological products in market downturn conditions. This research is purposefully a practical study and an exploratory mixed research in nature. The statistical population of this study consisted of marketing and commercialization experts in qualitative stage. These experts were identified using purposive sampling along with the snowball method, among which 20 experts were finally interviewed regarding data adequacy. As well as, 123 active companies in technology-based businesses were also used to test the model. Grounded theory and structural equation approach are the methods of analysis. The data were collected through in-depth interviews with the distribution of the 47-item questionnaire. The results confirm that "intra-organizational potential" is proposed in the case of causal conditions. "Localization of modern technology" was the main phenomenon identified in the study and "institutions involved in the commercialization process" was the intervening factors identified in the model. The context of this research is also "intra-organizational commitment" and "intra-enterprise economic conditions". The main strategies included "market orientation" and "financial resources" and ultimately the main consequence of these strategies was "improve sales performance". The results of the structural equation approach confirm the relationships designed in the grounded theory model. Introduction In fact, technology commercialization is the creation of a new product, service or process based on satisfying new demand, and therefore providing it requires continuous efforts to transform the results of new products and services and their successful marketing. Accordingly, it can be stated that in addition to facilitating the process of converting ideas into product and services, market and marketing conditions are also among the issues involved in technology commercialization. The country should be able to benefit from the ability of companies operating in the field of commercialization to achieve a resilient economy and reduce dependence on developed countries' technologies. This issue is very important given the current sanctions, and failure in this area is recognized as a major challenge. Therefore, designing a model for the commercialization of technological products in technology-driven companies can have great advantages for Iran. The main question of this research is as follows: What is the pattern of technology commercialization in technology-based companies in market downturn conditions? Case study The statistical population of this study consists of two parts: (i) The first part of statistical population was related to individuals who were selected for the interview included experts in the field of commercialization of technological products and active academic elites according to the subject area. They were selected by purposeful sampling through criteria such as expertise in commercialization issues, practical experience in delivering technological products to the market, and so forth. Eight experts were identified; then the number of respondents increased by continuing the interviews using the snowball sampling method. Usually this sampling was continued until the researcher obtained the sufficient data. Thus, 20 in-depth interviews were conducted in this field, in which information were repetitive from the 15th interview onwards, and the researchers reached theoretical saturation, but interviews were continued with 20 individuals for sure. (ii) The second part of the statistical population consisted of active companies in the field of technological products. The number of these companies was 180. Using Cochran's formula, the sample size was 123 companies. The researcher has attempted to use a simple random sampling method. It was attempted to provide each senior executive of the companies with a questionnaire. SmartPLS software was used for data analysis in this study. Materials and Methods In the first part of this study, the grounded theory approach was used to identify the pattern of commercialization of technological products under recession, and the partial least squares approach was used to test the model. The interviewing tool was used in the first step and the questionnaire in the second step in order to collect data. Interview sessions began with questions about causal factors affecting the pattern of technological product commercialization in a recession (open interview) and questions continued based on the participants' response. In the questionnaire section, a 47-item questionnaire was designed based on the final model. Discussion and Results Six specific aspects of systematic pattern design were examined in this study: intra-organizational potentials were identified in the case of causal conditions; considering the technical characteristics of the organization and the intangible assets of the organization was the major component regarding the intra-organizational potential; on the other hand, the important issue of infrastructure and its enhancement is to improve performance; localization of novel technologies has been identified as a major phenomenon in the process of commercialization of technological products. The context of the phenomenon of commercialization can be described in two areas: (a) intra-organizational commitment, and (b) economic conditions prevailing in society. Commercialization can progress properly if corporate management within the organization has sufficient commitment to research and development (R&D). On the other hand, it is budget, financial resources, and targeted allocation in this area that can increase the activity in these projects. The presence of constant financial resources in companies, preventing downturns, and marketing platforms are other critical issues that can be very effective in commercialization. Marketing measures can well draw market demands in the field of technological products, and this undoubtedly provides the required background for enhancing and improving technological products tailored to market demands. Conclusion In the model of this research, the corporate strategy in the field of commercialization of products is discussed which can play an important role. On the one hand, financing is an issue that should be considered. Inexpensive financial resources as well as financial allies are a topic of great interest in the field of financing. Working in the commercialization of technological products requires extensive investment. Another strategy in this area is to focus on market orientation, activities that make commercialization successful in domestic and international markets. Undoubtedly, working properly in commercialization will have no consequence except improving sales performance and welcoming market performance. Sales performance and its improvement can transfer higher revenue to technology organizations.

Innovation ecosystems have two leading options in the last phase of their life cycle, usually associated with massive socioeconomic changes or emerging ecosystems: Either adapted to new conditions and continue to innovate, or fail to renew and eventually die. In the latter case, reviving of an obsolete innovation ecosystem can be important for policymakers and managers. The city of Laljin is the most important pottery and ceramic manufacturing center in Iran, where pottery industry has a history of at least 200 years. Despite the historical record of innovative activity in the form of an ecosystem structure, this industry now lacks the features of a dynamic and active innovation ecosystem. In this research, in-depth interviews were conducted with 50 people representing actors involved in this ecosystem as well as informed people of historical events. At first, the historical trend of the Laljin innovation ecosystem was studied from before 1936 until present, and then the status quo was described. In this research, the method of qualitative content analysis has been used to extract and categorize concepts from interviews and identify the main issues. Finally, the stimuli and barriers to innovation were identified and the ways to revive this ecosystem were presented. These approaches are summarized in a four-step pattern along with the role of each actor in this ecosystem

The ever-increasing global competition leads companies and industries to find new solutions for survival and market preservation. To this end, companies are trying to invest in innovative activities such as R&D projects and streamline their business and competition. Regarding the characteristics of future R&D projects, it is important to have access to methods that provide the success of these projects. R&D projects have been considered very little in terms of project management in technology-oriented companies. In order to implement the results of new research and to help resolve the problems in this field, it is necessary to identify and prioritize the factors affecting future R&D projects. The purpose of this research is applied and is a descriptive-survey method. Factors influencing future R&D projects in advanced technology industries have been extracted from the review of the literature and opinion of the aerospace industry experts and the approved questionnaires have been distributed in the expert community and the results have been verified using confirmatory factor analysis and structural equations with Smart-PLS software. In this study, eight main dimensions influencing future R&D projects in the aerospace advanced technology industry with 56 factors were identified and confirmed, which are important for all of them. All identified key factors have a significant impact on future R&D projects management capability in advanced aerospace industries.

Organizations should consider process improvement for promoting their performance. The main problem is the high volume of process dataset along with the wide variety of their features that leads to increase the complexity in process improvement methods. Previous methods cannot improve processes in a high volume of process dataset. Data mining approach can support improvement methods by identifying valuable hidden patterns in high volume of process dataset. In this paper a framework of using data mining techniques for extracting valuable hidden patterns in high volume of process dataset is developed for presenting the improvement suggestions. In order to evaluate the proposed framework, a real set of processes along with their features were gathered. After that, using classification, clustering, and features selection algorithms, valuable patterns in high volume of process dataset were identified. After evaluating these patterns, improvement suggestions were recommended by the identified patterns. The results showed that identified patterns can support processes improvement activities with recommending the improvement suggestions. Introduction: Processes are one of the most important resources in organizations. Improving processes can lead to enhance the organizational performance. Several methodologies are presented for process improvement. However, they did not consider the problem of high volume of process dataset along with their features in organizations. There are many processes in organizations that lead to increase the complex interactions between processes and high dimensionality problem (Jeong et al., 2008). In addition, there is a single view to processes in the improvement actions (Houy et al., 2011). Huang et al. (2012) stated that there is a low attention to the internal aspects of the processes. In this situation, data mining techniques can identify and discover valuable patterns hidden in the large number of processes in the organizations. These patterns can be utilized for recommending the improvement suggestion for enhancing the performance of the processes. Recently, there is a link between data mining and process improvement. A few studies considered the interaction between data mining and process improvement. However, these studies did not consider a real large number of processes in their computations. In addition, they did not have a comprehensive and practical view to the application of data mining for process improvement. This paper presents a framework for using data mining techniques for identifying and extracting valuable and suitable patterns hidden in the large number of processes. These patterns can be employed for recommending the process improvement suggestions. Materials and Methods: This paper employs three data mining techniques including clustering, classification, and feature selection techniques for extracting valuable patterns hidden in the large number of processes. CRISP-DM (cross industry standard process for data mining) standard is used to implement data mining activities. In the classification technique, C5 decision tree algorithm is employed to classify processes. In clustering, K-means algorithm is applied to segment processes in several clusters. In feature selection technique, the most important process features are selected for process improvement. In the proposed framework, at first, all processes are gathered from a variety of the resources in the organization. After that, process features are identified from the literature and they are defined based on an interaction between data miner and process improvement expert. In the following, a process dataset is provided for using data mining techniques. For this dataset, a variety of data preparation and preprocessing methods are employed for achieving better results of implementing data mining techniques. After that, three classification, clustering, and feature selection data mining techniques are applied for extracting valuable patterns hidden in the large number of processes. In the classification techniques, C5 decision tree algorithm employs a target features for classifying processes. Cross validation method is applied to train and test the constructed decision tree. The output is several if-then rules for classifying processes based on the target feature. In clustering, K-means algorithm segments processes in several clusters. Processes in a cluster have a similar behavior and they are dissimilar to the processes in the other clusters. Euclidean distance function is used for calculating the distance between processes. The output is the cluster profiling to describe the behavior of processes in each cluster. In the feature selection, the most important features are selected based on a target process feature. These features are more correlated to the target process feature. In addition, they are more important to consider for process improvement purposes. The output is a variety of more important process features so that they can be considered for recommending the process improvement suggestions. After extracting valuable patterns hidden in the large number of processes, the accuracy and quality and these patterns are evaluated by an interaction between data miner, process owner, and process improvement expert. Evaluated patterns are considered for recommending the improvement suggestions. These suggestions must be aligned with the process improvement concepts in the organization. Processes are improved based on these suggestions. In last, the performance of the improved processes is evaluated. The proposed framework is based on an iterative and continuous method for using data mining in process improvement. Results and Discussion: The proposed framework was evaluated based on a real process dataset including 1318 processes and 80 process features. Several preprocessing methods were employed to prepare dataset. Three classification, clustering, and feature selection techniques were applied to extract valuable patterns hidden in the large number of processes. Using C5 classification algorithm, processes were classified by the if-then rules based on a target process feature. In the proposed model, as an example, key processes were classified using C5 decision tree. The classification accuracy in the test dataset was set to 92.31%. The output was several if-then rules to classify key processes. These rules can identify key processes. In addition, processes features applied to construct the if-then rules can be employed for recommending the improvement suggestions for key processes. In clustering, using K-means algorithm, processes were segmented into 10 clusters. Some features were considered to cluster processes. The output was cluster profiling to describe the behavior of processes based on the selected features. In this paper, for example, the behaviors of processes in cluster 1 were described through the selected features. Several suggestions were recommended by the selected features for improving processes in this cluster. In the feature selection technique, for example, “cost of process” was considered as the target process feature. The output was the selection of 10 more important process features that they were more related to the target process features. These features can describe the cost of processes better than the other features. The improvement suggestions for reducing cost of processes were recommended based on these selected features. Conclusion: This paper presented a framework of using data mining techniques for identifying valuable patterns hidden in the large number of processes for the process improvement purposes. A real process dataset was employed to evaluate the applicability and effectiveness of the proposed framework. In the proposed framework, classification, clustering, and feature selection data mining techniques were applied to extract valuable patterns hidden in high volume of process dataset. Process improvement methodologies cannot recommend the improvement suggestions in a rapid and accurate method, when there are many processes along with a variety of the process features. These methodologies are restricted to recommend a limited number of the process improvement suggestions. In the other direction, there are few studies on the application of data mining for the process improvement that they include some weaknesses. The proposed framework employed a lot of real processes in the data mining techniques to discover valuable patterns for process improvement. In addition, a variety of the process features were extracted from the literature to describe the behavior of the processes. In last, a wide variety of the several suggestions were recommended for process improvement based on the extracted patterns hidden in the large number of processes. The organizations can utilize the proposed framework for improving their processes. In addition, this framework can help organizations with the large number of processes for employing the process improvement methodologies in a productive manner. Future studies can apply the other data mining techniques for the proposed framework. In addition, the proposed framework can be developed for knowledge-intensive processes. The proposed framework can be integrated with the knowledge management methodologies for improving knowledge-based processes. In last, the proposed framework can be enhanced as a decision support system for the process improvement. References Houy, C., Fettke, P., Loos, P., van der Aalst, W.M.P., Krogstie, J. (2011). Business Process Management in the Large. Business and Information Systems Engineering, 3, 385–388. Huang, Z., Lu, X., Duan, H. (2012). Resource behavior measure and application in business process management. Expert Systems with Applications, 39 (7), 6458–6468. Jeong, H., Song, S., Shin, S., Rae Cho, B. (2008). Integrating data mining to a process design using the robust bayesian approach. International Journal of Reliability, Quality and Safety Engineering, 15 (05), 441–464.

Background: Bullous pemphigoid is one of the most common autoimmune blistering diseases. Incidence of bullous pemphigoid has been estimated 4 new cases per 100000, but new studies show that the incidence rate is increasing. The disease typically happens in the elderly people usually after 70 years. Annual mortality rate for bullous pemphigoid is reported up to 40%. The aim of this study was to evaluate epidemiological features of bullous pemphigoid in center of Iran. Methods: This was a cross-sectional study conducted in Alzahra hospital in Isfahan City. 69 patients with bullous pemphigoid hospitalized during the years 2008-2016 were studied. Findings: 59.45% of the patients were women. The mean and standard deviation of age was 68 ± 13 and 72 ± 14 years in woman and men, respectively (P = 0.01). Mucosal involvement was seen in 55.4%., and the most common underlying disease was hypertension (23.6%). 15.4% of women and 3.7% of men used furosemide, and the most commonly prescribed drugs were antihistamine (98%), antibiotics (97%), and topical (91%) and systemic (88.4%) corticosteroids, respectively. The mean and standard deviation of the dose of prednisolone was 54 ± 12 mg per day. Rise in serum blood sugar was reported in 30% of patients, and 3.6% of men and 15% of women needed intensive care unit (ICU) admission. 42.9% of men and 44.4% of women had relapse after discharge, and 38.64% of patients died during one-year follow-up. Conclusion: It seems that patients with bullous pemphigoid need careful follow up, especially during treatment, and at least for one year, because of their age (> 60), underlying diseases, type of treatment (corticosteroid use), and high mortality and relapsing rates in the first year after diagnosis.

Background and Objective: The phenomenon of aging is one of the evolutionary stages of life and it is an inevitable part of human society that can lead to poor balance and consequent harm, loss of independence and early death. This study was done to determine the effect of Pilates exercise on functional balance of elderly men. Methods: This quasi-experimental study was done on 28 elderly men with an average age of above 60 years. Subjects were non-randomly divided into intervention and control groups. Eldely men in intervention group were received Pilates training for 6 weeks, 3 sessions per week. To measure the functional balance was used of the timed up and go test. Pre-test and post-test of was done for functional balance in intervention and control groups. Results: The functional balance significantly reduced in intervention group (10.11±0.53 sec) in compared to controls (12.61±1.14 sec) (p

Introduction: Professional socialization is an essential process of learning skills, attitudes and behaviors necessary to fulfill professional roles. The consequences of professional socialization are widely varied and influenced by personal, situational and organizational factors. The aim of this study was to review the role of educational activities on professional socialization of nursing students. Methods: This narrative review study was carried out by searching library resources and the databases of CINAHL, Science Direct, Scopus, Google Scholar, Elsevier, SID, and Magiran for articles published during 2002-17. The keywords used for the search included socialization, professional, educational activity, and nursing students. Preliminary results yielded 106 articles of which 10 articles were selected for the review. Results: Contemporary studies show that professional socialization of nursing students is influenced by different factors among which the role of mentors, peers and effective role models is of great importance. Personal experiences and the role of clinical trainers are also important in facilitating students’ learning development and socialization. Conclusion: Improvement and organization of the educational system and focus on selection of effective and interested clinical trainers, as well as utilization of mentors, peers and effective role models are the proposed solutions to facilitate and promote the professional socialization of nursing students.

Many of manufacturing organizations have known the benefits of implementing enterprise resource planning system. Yet, they have doubt about adopting the system due to its high cost, uncertainty, and risk. This study identifies the key factors for successful implementation ofenterprise resource planning system in manufacturing industries and provides a model based on structural equation modeling after the obtaining the effective factors from the literature. The results of the study indicated that the effect of performance on perceived usefulness of enterprise resource planning system. The obtained results were analyzed through the least partial equations and some of the hypotheses have been confirmed. This research based on analysis offers recommendations for successful implementation of enterprise resource planning system. The success factors help the senior managers in manufacturing organization to make better decisions and improve their business value through effective enterprise resource planning system.

Introduction: Hearing loss in children is a main cause of malfunction in them. On the other hand, adaptive Behavior includes the age-appropriate behaviors necessary for people to live normally and in daily life. The objective of this study was to compare the adaptive behaviors of 12-36 months deaf and normal children. Methods: In this case- control study, we compared adaptive behaviors score of 40 deaf children with 40 normal children. Adaptive behaviors were measured using Vineland scale. Results: In 12 to 24 month children, there was a significant difference between two groups (P=0.007). However, in 24 to 36 month children there was no significant difference between the two groups (P > 0.05). Conclusion: It seems that parental acceptance of children;#39s hearing losses can lead to an improvement in adaptive behaviors of their children.

The continuity of every business depends on rational economic profit, and the amount of economic profit is directly related to efficiency. For management and comparison of similar decision making units (DMUS), relative efficiency is usually used. Tow methods are generally used for efficiency measurement, ratio Analysis and Efficiency Bound Analysis. In the Efficiency Bound Analysis method, at first a boundary is made via the information from the best producers or service providers, so that any activity above this boundary is considered the best performance, and any activity below it is viewed as inefficiency. One of the methods of estimating Efficiency Bound and measuring Relative Efficiency is Linear Programming, which is also called Data Envelopment Analysis (DEA). In this research at first by obtaining the views of the extperts and using pairwise comparisons, the researchers determined the indexes effective on the relative efficiency of toll switched exchanges (Sc/Pcs). Next, the relative efficiency of 39 Sclpc was measured in the constant and variable Return to Scale (CRS, VRS) conditions. Also, additional measurements of DEA and Anderson Piterson (AP), Multi Criteria Decision Making (MCDM) and fuzzy MCDM (FMCDM) were used for ranking Sc/Pcs. The results indicate that in CRS conditions, the average of relative efficiency is 80.23 percent, and that 11 sc/pcs out of 39 Sc/Pcs have 100 percent efficiency. Likewise, in VRS conditions, the average of relative efficiency is 97.77 percent, and 25 Sc/Pcs out of 39 Sc/Pcs have 100% efficiency. An other results of this research indicates that, the moment coefficients of Manpower, Quality of Services and Maintenace have been calculated. The amounts of them are ranked with 0.424, 0.334 and 0.242.

Background: Toxoplasma gondii, is a mandatory intracellular protozoa, that many people worldwide are infected with. In children, the infection enters central nervous system and leads to inflammation of the gray matter. Autism, is a complex develop-mental disorder, altering social communication, with unknown origin. Neuropathologi-cal changes in autism are the same as those occurred in brain toxoplasmosis. The objective of this survey was to evaluate positive serology of toxoplasma gondii, in autistic children. Methods: This case-control study was done on 3-12 years old children, referring to the neurology and psychiatry sub-special clinics of Baqiyatallah hospital and also autistic children of Omid-e Asr and Navid-e Asr general rehabilitation centers in Tehran, Iran. The study performed at 2012-2013. Forty autistic children were placed in the case group and 40 children, suffering from no neuropsychiatric disease or other ones, were placed in the control group. A folder, containing demographic data, type of the disor-der, onset of diagnosis and child characteristics at birth, such as time of birth (preterm/ term) fulfilled for each child. Sampling was done with 5 ml blood, for determining IgM and IgG antibody levels against toxoplasma gondii, using ELISA method. Data ana-lyzed by the software SPSS ver. 17 and descriptive and analytic analysis were done, us-ing central and dispersion indexes and also chi-Square test. Results: The autistic group contained 34 boys and 6 girls (85 and 15 percent respectively), with the average age of 6 (±2.71) years old [minimum of 2.33 and maximum of 12]. The average age at the time of diagnosis was 4.01 (±1.87) years old. 87. The non-autistic group contained 17 boys and 23 girls (42.5 and 57.5 percent respectively), with the average age of 5.67 (±3.09) years old [minimum of two and maximum of 12]. IgM and IgG serology of all autistic children were negative, while in non-autistic group, 2.5 percent (1 child) were positive and 97.5 percent (39 ones) were negative. There were no statistically significant difference among these two groups according to the serology results. (P=0.31). Conclusion: There was no statistically significant difference in comparing positive se-rology of toxoplasmosis, between the two groups. However, to obtain a perfect result, a larger sample size are required.

Classifying customers using data mining algorithms, enables banks to keep old customers loyality while attracting new ones. Using decision tree as a data mining technique, we can optimize customer classification provided that the appropriate decision tree is selected. In this article we have presented an appropriate model to classify customers who use internet banking service. The model is developed based on CRISP-DM standard and we have used real data of Sina bank’s Internet bank. In compare to other decision trees, ours is based on both optimization and accuracy factors that recognizes new potential internet banking customers using a three level classification, which is low/medium and high. This is a practical, documentary-based research. Mining customer rules enables managers to make policies based on found out patterns in order to have a better perception of what customers really desire.

In recent decade, with increasing competition, attracting and retaining customers are known as the most valuable competitive tool for many organizations. Customers have a key role in success of businesses, so the managing of customers' relationship is one of organization priorities. Although some organizations have customer relationship management, they are not able to absorb customer satisfaction. With formation of private banks in Iran, state banks were exposed with many problems in marketing. This article has attempted to present a model of improving customer relationship management with knowledge management by managing efficiency and priority knowledge of the organization. Therefore knowledge management factors including customer knowledge, staff knowledge, knowledge of the market that are called independent variables and customer relationship management variables (management services, complaints, suggestions) were identified as dependent variables, were selected. Bank Sepah was chosen as the sample. For data analysis, structure equation model and lisrel software are used.

Objective: Depression is the most common mood disorder. Today, family has main responsibility in caring of psychiatric patients. For ensuring best care for depressed patients, families require social and health systems supports. The aim of this study was to explain the experiences of the families about function of these supportive sources. Materials & Methods: This is a qualitative research carried out using conventional content analysis method. Twenty-four family members of the patients suffering from depression and referred to Razi psychiatric clinic in Tehran were selected using purposeful sampling. Unstructured and in-depth interviews were applied to collect data. The interviews were transcribed and constant comparison analysis was applied. MaxQDA 2007 software was used to manage the data. Results: According to the family experiences, social and health support resources are not comprehensive and efficient. The performances of the supporting sources have been extracted in four themes. These themes include: “incorrect viewpoints of the society”, “inadequate support”, "ineffective health system”, “economic–cognitive deficiency of the families” that they were the main themes. Conclusion: During the process of depressed patient care, families find themselves alone. They need to access to have easy comprehensive support systems. In addition, health team must implement the follow up programs regularly and dynamically.

Knowledge Management (KM) is one of the growing apprehension in existing business in the new age of the complex and quickly changing business environment, and it has been realized that knowledge is the organization's critical asset and latent strategic resource that gives a basis for competitive advantage. At this situation, banks require to use knowledge and it prone to implementation related applications of knowledge management. One of the most important issues to implementation of knowledge management is how to select appropriate KM strategy. It is a kind of multiple attributedecision-making (MADM) problem required to consider a large number of complex factors. To determine the knowledge management strategy, there are many influencing factors. The purpose of this paper is to ranking the appropriate KM strategy with TOPSIS and VIKOR, and prioritization the effective important factors for evaluating KM strategies for reducing the cost and time. Additionally, an empirical study is presented to illustrate the application of the proposed method.

Background: Cognitive problems in patients with post-traumatic stress disorder (PTSD) include poor concentration and impaired memory. Prevalence of PTSD in all aspects of life is 8% in USA. Regarding the importance of memory in functional levels, this study was performed to review memory status in these patients. Methods: Fifty male war veterans with PTSD and major depression and 50 male non-veterans with depression participated in this study performed at psychiatric outpatient ward in Baqiyatallah hospital during 2008-2009. The patients met the DSM-IV diagnostic criteria. Depression severity, sex, age, educational level, and marital status were matched in both groups. A psychologist completed demographic and Mississippi questionnaires, PTSD checklist (PCL), beck depression Inventory and wechsler memory scale. The collected data were analyzed using SPSS software (version 11.0). A P-value smaller than 0.05 was considered significant. Results: The mean age of the veterans and non-veterans was 43.9±4.7 and 42±9.4 years, respectively. Memory status did not differ between the two groups (P>0.05). There was no statistically significant correlation between duration and severity of PTSD with memory impairment (P>0.05). A negative correlation was found between personal and general information with re-experiencing in the veterans (P

"nBackground: Efforts have been made worldwide to identify and to study parasites of laboratory animals, aiming at the achievement of proper procedures for eradication of parasitic infestations, considering the important role of these animals in scientific research. There is no sufficient data about parasitic infestations of Laboratory animals which are kept in conventional systems in Iran. In this scope, peresent study was designed to investigate the presence of ectoparasites and endoparasites in conventionally maintained laboratory rats (Rattus norvegicus) and in mices (Mus musculus). "n "n Methods: A descriptive cross-sectional study was performed on 240 randomly selected rats and mice from two different animal houses in Kerman city, Iran. Skin scraping; blood samples and alimentary tract contents of all animals were fully examined for the presence of parasitic infections. "n "n Results: In the first animal house, Nosopsylla fasciatus (flea), Hymenolepis dimminuta, Entamoeba muris and Cryptosporidium spp. infestation were diagnosed respectively in 35.41%, 36.1%, 3.57%, and 1.25% of rat colonies but only Entamoeba muris infestation was detected in 4.58% of mice colonies. In the second animal house, 2.5% and 2% of rat and mice colonies were infected by Entamoeba muris. "n "n Conclusion: Based to presence of asymptomatic parasitic infection in conventionally maintained laboratory animals, regular periodical samplings, precise sanitary monitoring of barrier maintained system, environment and food seem necessary in animal houses. Eradication of parasites could eliminate the confounding effects of these infections on researches and additionally decrease the risk of zoonotic disease transmission to investigators and animal house personnel's.

Background and aims The fluoride of water can increase the resistance of enamel of teeth against dental caries. In places with low fluoride level in potable water, dental caries is very high before puberty. The aim of this study was to determine the fluoride level of potable water of Ilam- Iran and it's relation to DMF criteria in workers of industrial city of Ilam. Methods This study was done in fall of 1999 on the 320 workers which their age was between 20-34 (x ± SD:28.1 ± 1) years old by descriptive analytical method. The factories were selected by cluster sampling and workers were selected by random sampling from different socio-economic status. Results The mean concentration of fluoride in potable water was 0.28 mg/l which is lower the standard limit. The average value for DMF Index was 4.3 in workers. There was a significant negative correlation between fluoride control of potable water and number of DMF teeth (r=0.1 , p= 0.01 ). The lowest value of DMF index was in range of 20-23 years old. When the fluoride content of water was higher, the dental caries was lower. Conclusion The addition of fluoride to potable water to about 1mg/l, health educational programs and fortification of foods in Industrial regions and factories is recommended.

Background and Objective: There are 3 sensitive cells with a few basal cells in the rat tongue (Dark cell I, light cells II and III). The aim of this study was to determine the effect of different concentrations of phosphate on the rate of Acid Phosphatase in taste bud cells in papilla of rat tongue. Methods: To determine the influence of Phosphorous on Acid Phosphatase in taste buds, the dose of 0.5, 1.5, 3 and 6% and control group of NaH2PO4, 2H2O in the drinking water were used for 30 days then all rats were killed, and their tongues were isolated for histological examination. Black granules in the papillary cells (Cytoplasm) of rat taste buds due to plumbsulfhydril from the Phosphorous and Acid Phosphatase with staining region were counted. Gomori’s staining method and counting black granules were statistically analyzed with non-parametrical of Kruskal-Wallis and ANOVA. Findings: Based on salts were used in the water There was a linear relationship between the concentration of salt and the rate of Acid Phosphatase. It was seen a significant difference in mean of black granules in taste bud cells in 5 different groups of food Phosphorous (P