Environment and its conservation is one of the present issues in risky modern life. Although, the present world has been improving during last years, it hasn’t been able to solve environmental problems and it has caused its deterioration. Littering in jungle, seashore, public places and passages is one of the significant environmental issues in society of Iran. The Purpose of the present study is investigation of the reasons of littering formation by the approach of Causal Layered Analyses (CLA) and planning scenario. The present study analyzed the layers forming the present social issue and searched the origin of it. In order to accomplish this study, 15 experts in environment and society were interviewed by Qualitative and exploring method and applying deep interview technique. Then, after exploiting the contents and content analysis of interviews, their opinions presented in 4 forms as litany, systematic, discourse analysis and metaphor. By applying the present discourses, the gap between state-people and people-people were recognized as important variables and were applied in presenting scenario. Finally 4 scenarios presented in a diagram which can help strategists and officials of the society.

ABSTRACT Despite a wide range of components and criteria affecting travel Behavior presented through empirical research, the results of these studies are inconclusive, which could be due to the difference between these components and criteria in the study areas. Therefore, this research presented a method to determine which factors in different physical developments affect travel Behavior due to the differences in various physical developments. The required information was collected through 271 questionnaires at the level of three neighborhoods of Monirieh, Koye Bimeh, and Koye Golestan in Tehran, Iran, as the old, conventional, and new neighborhoods, respectively. ANOVA test was exerted to analyze the significant difference between different development patterns in three neighborhoods. Dunnett's T3 was applied to determine which neighborhood caused the difference between groups. Also, the factors affecting travel Behavior were obtained based on exploratory factor analysis indicators. Finally, by comparing the results of the ANOVA test and regression analysis, it was discovered that factors such as car ownership, dependence and pro-liking for private cars, density and access to educational centers and parks, access to medical and service centers, and variety and density of retail stores had been introduced as the factors affecting travel Behavior due to the differences in development patterns. However, proximity to the public transportation station, accessibility preferences in choosing a residence, dependence, and pro-liking for other than a private car, having a license, number of children under five years old, and age have influenced travel Behavior regardless of the variation between neighborhoods. Extended Abstract Introduction Finding factors affecting travel Behavior has been one of the main concerns of transportation planners. However, in the last two decades, the importance of the influence of the features of the built environment, including land use, along with demographic-economic characteristics, travel Behavior, and attitudes of people, has been raised by urban planners. Studies seek to find factors affecting travel Behavior, especially land use characteristics. Despite presenting a wide range of components and criteria affecting travel Behavior, the results of the studies are inconclusive, which could be due to the difference between these components and criteria in the study areas. Therefore, this research presented a method to determine which factors in different physical developments affect travel Behavior due to the differences in various physical developments. In order to do this, it must first be determined whether the study areas/different development patterns have a significant difference in terms of travel Behavior or not. In case of a positive answer to the previous question, the following question is which study areas caused this difference. The next question arises: -Which physical and non-physical characteristics affect travel Behavior due to distinctions between different development patterns?   Methodology The present research method is analytical and experimental based on quantitative methods. This research chose the frequency of travel by private car, public transportation, and walking as the travel Behavior. According to the research's purpose, indicators and criteria affecting travel Behavior were extracted after reviewing the theoretical and experimental literature. Then, the required information was collected through 271 questionnaires at the level of three neighborhoods of Monirieh, Koye Bimeh, and Koye Golestan as the old, conventional, and new neighborhoods, respectively. The questionnaire was compiled as a Likert scale in five parts of travel information, demographic-economic characteristics, perceptual characteristics of land use, travel habits, and access preferences of people in choosing their residence. ANOVA test was used to analyze the significant difference between different groups of a characteristic (here, different development patterns or the three case studies). Dunnett T3 was exerted to determine which neighborhood caused the difference between groups. Also, the factors affecting travel Behavior were obtained based on exploratory factor analysis indicators. Finally, by comparing the results of the ANOVA test and regression analysis, it was discovered which factors affecting travel Behavior were due to the differences in study areas and which factors affect travel Behavior regardless of development patterns.   Results and discussion This research aims to identify the factors affecting travel Behavior due to the differences in development patterns. In this regard, the findings in line with the first research question show that the frequency of three modes of travel, by private car, transportation, and pedestrian, differ significantly in the three neighborhoods. Furthermore, ANOVA test results depict that there is a significant difference between these three neighborhoods in terms of factors affecting travel Behavior, such as perceptually environmental characteristics of the neighborhood, dependence and pro-liking for personal cars, variety and density of retail stores, density and access to educational units and parks, access to medical and service centers, and car ownership. Finally, by comparing the results of the ANOVA test with the regression analysis assessing the relationship between physical and non-physical factors (the same indicators in the same study areas) with travel Behavior, the factors affecting travel Behavior owing to different development patterns were identified. Factors such as car ownership, dependence and pro-liking for private cars, density and access to educational units and parks, access to medical and service centers, and variety and density of retail stores have been introduced as the factors affecting travel Behavior due to the differences in development patterns. However, proximity to the public transportation station, accessibility preferences in choosing a place of residence, dependence, and pro-liking for other than a private car, having a certificate, number of children under five years old, and age have influenced on travel Behavior regardless of the variation between neighborhoods (different physical development patterns).   Conclusion In In order to discover the factors affecting travel Behavior due to the differences in patterns of physical development, this research has provided a more detailed analysis of the factors affecting travel Behavior. It has achieved more accurate components than previous studies in this regard. Detailed analysis of studies related to travel Behavior and finding the main components affecting it, considering the extent of variables and data, can pave the way for professionals in transportation planning and urban planning, in addition to providing detailed methods and criteria in the related literature.   Funding There is no funding support.   Authors’ Contribution Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.   Conflict of Interest Authors declared no conflict of interest.   Acknowledgments  We are grateful to all the scientific consultants of this paper.

Gender socialization, as one of the most basic types of socialization, affects a person's individual and social life, including the stability of his or her marital life. The aim of this study was to explain the relationship between gender socialization and divorce between 178 divorced women and 222 women with emotional divorce, which was conducted by survey method in Bandar Abbas. This study used biological and social theories to explain gender socialization and theories of structural functionalism and the love triangle to explain divorce. In the present study, simple and stratified random sampling proportional to volume was used for women with emotional divorce and chain sampling was used for divorced women. Questionnaire data were collected through interviews and face validity was confirmed through literature review and expert judgment, structural validity was confirmed by factor analysis and its reliability was confirmed by Cronbach's alpha. The results showed that gender socialization of 29.4% of divorced women and 70.6% of women with emotional divorce is traditional, and on the other hand 60.2% of divorced women and 39.8% of women with emotional divorce, Had a modern gender socialization. According to the results of Chi-square test, there is a significant relationship between the type of gender socialization of women, gender values, gender inequality and power relations with the type of divorce. Accordingly, women with emotional divorce have a more traditional outlook than divorced women.

A common method for controlling a group of parallel converters in decentralized control strategy structure in an island microgrid, the use is the droop-down characteristics of frequency ω-P and voltage E-Q. However, the problem with using this method is that the reactive power is not properly distributed (in proportion to the capacity of the micronutrients) between the micronutrients, which may lead to overload in the converters. Microgrids may also suffer from dynamic stability problems such as power fluctuations, which can be increased by switching between active and reactive power control. To avoid this problem, the X / R ratio of transmission lines is an important parameter that should be carefully considered in the design of micronutrient controllers. By linearizing and simplifying conditions, the control system conversion function model becomes a single input-single output system, which is efficient enough to show the relationship between control parameters such as slope of droop characteristics and derivative sentences, virtual impedance, and voltage controllers. Using this model, stability conditions for different parameters are analyzed. Also, to improve power distribution stability, common droop strategies are modified by adjusting the slope as well as adding nonlinear sentence sections. This approach reduces the coupling between active and reactive power control and reduces the dependence of power distribution on grid parameters such as the X / R ratio. To evaluate the reliability of the proposed model, the simulation results in a sample island microgrid in MATLAB software are presented.