Some subjects such as economic growth, optimum distribution of national income and also economic justice have been considered by the economics and economic policies in Iran. In this regard, there are a variety of ideas about the interaction effects of distribution of incomes and eeconomic growth. According of the foundations of theoretical, there is a U reverse relation between distribution of national income and economic growth. This curve in known as Simon Kuznets hypothesis in economic literature of growth. Some different result have been obtained about the relation between economic growth and income inequality based on several studies in Iran and out of Iran. According to doing the law enforcement targeted subsidies in Iran during recent years, one of the most important goal of this plan was to improve distribution of national income among the poor layers of social. In this regard, this study aims to evaluate the relationship between economic growth and income distribution during 1350-1389 in Iran. For this purpose, Gini index for income distribution measurement and autoregressive logistical approach or methodology smooth transition logistic smooth transition auto regression (LSTAR) is used as the econometric approach. In this method, the relation between variables is changed nonlinearly. So, first the problem is modeled nonlinear. According to the number of observations that are less than 100 observations, Schwarz- Bayesian criterion is used to in order to finding the optimum amount of lag. Based on this criterion, the optimum amount for both dependent and independent variable is 1. Based on result about estimation the model and rejection two hypothesizes and and, the model of LSTAR1 is selected. Next results show that gross domestic product (GDP) growth has a negative and significant effect on Gini index as a criterion for measurement income distribution both in linear and nonlinear cases in the period under review. Non-linear relationship between these two variables shows that the optimal level of the Economic Growth involves maximizing Gini coefficient in Iran. On the other hand, more increasing in Gini index means shows more unequally in income distribution. Therefore adoption and deploying polities for increasing growth economic will cause decreasing Gini index and more equally income distribution in Irani economic. This result also show that, the hypothesis of Kuznets about existing a nonlinear relation between economic growth and income distribution cannot be rejected. In order to evaluate the nonlinear estimated model some tests were used such as ARCH- LM test, lack of autocorrelation, and stability of parameters. This evaluation was done by using the JMULTI software. The results of evaluation confirm that there is no error relevant to existing autocorrelation in none of lags. This result show that there is no autocorrelation in variable lag of the gross domestic product (GDP) growth in Iran economic. Additional analysis show that there is no other nonlinear variable in the estimated model and so, the null hypothesis about suitable specification of the model cannot be rejected. Also in order to evaluate the dissimilarity of variance between disturbances of the estimated phrases, the Auto Regressive Conditional Heteroskedasticity Lagrange Multiplier (ARCH-LM) test was done. The result of analysis in this section presents that the hypothesis of absence of dissimilarity of variance between disturbances of the estimated phrases, cannot be rejected. Additional analysis confirm that equality of the coefficient in linear and nonlinear model is rejected. Finally the Jarque-Bera test confirm that the disturbance phrases have a normal distribution. The basic results of this study have a good compatibility with foundations of theoretical and also the result of studies of Uge Panizza (1999), Rafael Gomez & David K. Foot (2003). Angles – castro, Gerardo (2006), and Ben – David Nissim (2007).

This study aimed to explain the effect of currency shock and the monetary policy of the central bank on the production gap during business cycles. A model with a threshold approach (LSTAR) was used based on the seasonal data of the Iranian economy from April 2001 to July 2019. According to the statistical tests related to the correct specification of the model, the currency shock rate is a threshold variable for changing the coefficients as its function. The results showed that the central bank intervention and the oil shock had more effects on the production gap. The nature of production in Iran's economy is oil, and its booms and busts are synchronized with the booms and busts of oil income. The injection of high oil revenues and the experience of high economic growth increase the GDP growth and reduce the production gap due to the low currency shock rate. The continuation of economic growth in the upper stages increases investment in production, decreasing the production cost and gap. In addition, the effect of currency shock increases with the foreign exchange interventions of the central bank and crossing the threshold and entering the non-linear sector. In other words, policymakers have tried to control the growth of currency shock by more reaction to the growth of the exchange rate. However, the reaction to exchange rate deviations decreases after crossing the threshold. Therefore, controlling the exchange rate becomes more robust with the increase of its growth rate in foreign exchange interventions.

This paper investigates non linear effects of income on health expenditure (as out of pocket payment). The explanatory variables in health expenditure equation include urbanization, age, insurance, employment of household's head, the number of people employed, earned income and the number of persons aged fewer than 12 and over 60 years in the household. Database used was chosen from the household income & expenditure surveys in 1386. Database contains 31277 rural and urban households. Linear and non-linear econometric models based on logistic smooth transition regression (STR) are estimated. One of the most important findings is that health spending shows asymmetric behavior relative to household income or total expenditure (as a transition variable) so that the impact of explanatory variables on health expenditure in the high and low income regime is different. Also the results show that health expenditure is a necessary good for households, because the coefficient of the logarithm of income in the demand function is positive and much smaller than unity. In addition, out of pocket payments for health care services in high income groups are more than low income ones. Based on the results, with increased urbanization and for high aged people (beyond sixty years of old), health expenditure increase but if family members are covered by insurance, out of pocket payment for health expenses will reduce. So, it is important to develop the social security system and increase its efficiency to cover more health expenditure, especially for poorer households which lead to justice in health areas and increase in welfare of society.

The main objective of this paper is to investigate the effect of research and development expenditures on the Iranian industry market Share over the period of 1995:1-2007:4.For this purpose, we convert the annual time series data to the seasonal time series data by using of JMALTI econometric software.The main model of this paper has been estimated by nonlinear LSTAR approach. The result of this study reveals that there is nonlinear positive and significant relationship between research and development expenditures and market share of Iranian industry sector.

Economic and finance time series are typically asymmetric and are expected to be modeled using asymmetric nonlinear time series models. The logistic smooth transition autoregressive, LSTAR, model which is an asymmetric type of the smooth transition autoregressive, is becoming popular in modeling economic and financial time series. In this paper, we have considered the logistic smooth transition autoregressive model and have estimated unknown parameters based on the method of moment and modified maximum likelihood method. The performance of the proposed estimation methods are studied by simulation and are compared with the performance of maximum likelihood estimators. It shown that for large sample sizes, the modified maximum likelihood estimators usually have the lowest mean square error and bias. We proposed a LSTAR model to finance rate on consumer installment loans at commercial banks and conclude that the estimated LSTAR model based on the modified maximum likelihood method has the lowest value of MSE. ‎

Plant development can be defined as a programmed qualitative change in plant form, which leads plant to maturity, and researchers call it as phasic development or phenology. Recognizing the timing of occurring each development stage is necessary for managing system in order to yield increment. The timing of occurring development stages depend on climate, genotype specifications and sowing date then determination of these times in different regions is difficult and it is only possible through the using of crop simulation models which can predict the timing of occurrence each development stage by integrating effective factors. The model was constructed based on linear equation of plant temperature response. In order to model evaluation two experiments were carried out in agricultural and natural resources research center of Khuzistan in 2003-2004 and 2004-2005 cropping years. Wheat development stages were determined based on Kirby and Appleyard’s scale by stereoscopic microscope and required GDD for each development stage as well. The constructed model was calibrated and run for simulation. Comparison of simulated and observed data showed that the model can strongly predict wheat development stages.

Today, one of the most widely used natural language representation methods is meaning representation for text processing in different systems. Meaning representation methods have had many applications in the field of natural language processing in recent years, including automatic text summarization systems and question and answer systems, etc. Many text expressions may be different in terms of grammatical structure, but they are the same in terms of meaning, so how to apply a single and uniform meaning to them is one of the challenges of text processing. The main goal of this paper is to design an Integrated Semantic Representation (ISR) model for natural language. The proposed model, while maintaining its simplicity in annotation and understanding, does not depend on specific natural language features or on syntactic and lexical structure. In this regard, several examples in both English and Persian language, which have different in terms of written and grammatical structure, are presented in this paper. Moreover, by using the proposed model, the same representation is provided for texts with the same meaning and different grammatical structure. The proposed model is designed in graph and list format is recommended to annotate its corpuses. One of the main features of this model is that it can represent semantic relations at both sentence-level and document-level and is able to represent complex and important linguistic phenomena such as aspect, tense, and quantification. The simplicity of the proposed model helps to avoid making language processing slow or complicated in various applications, and the preparation of structures based on this model for different natural languages will not be too complicated, so that it can be used both for natural languages with low resources and for those with various resources. Further, features of the proposed model are compared with one of the most important related works.

Purpose: Resilience in start-ups is a challenging issue that has caught the attention of policymakers and business owners. The present study is an attempt to provide a model for designing the resilience model of start-up businesses as a path to the future of start-up businesses. Method: This research is practical in terms of purpose and from the perspective of data collection is a qualitative research that has been done by content analysis method. The data collection method is semi-structured interview. Interviews with participants continued until they reached the theoretical saturation point, which was achieved by conducting 15 interviews. Participants were selected by snowball and purposeful method and data analysis was done through three coding steps (open, axial, selective) with MAXQDA2020 software. Findings: Based on the research results, the components of "cognitive resilience, financial resilience, adaptive resilience" as well as the effective organizational factors of "precedent, drivers and boys and resilience consequences" were identified. In this research, foresight and futures studies were identified as the drivers of resilience of start-up businesses. Conclusion: Resilience enables businesses to respond effectively to the dynamic conditions of their environment and maximize their competencies through strategic foresight and as a result gain more value than their competitors in the field of business. In this regard, the integration of foresight in the process of business resilience can be suggested as a facilitator of drivers.