Abstract: This study sought to answer the question of what are the causes of marital infidelity in the Iranian family. To Answer the Research Question, Qualitative Meta-Synthesis (QMS) Method Were Used. Then, 78 Scientific Papers Which Were Considered Marital Infidelity in Iran were identified and were Analyzed. The results showed that the FACTORS of infidelity in Iran can be classified into 9 main categories, including: 1. Social FACTORS, 2. Psychological FACTORS, 3. Cultural FACTORS, 4. Family FACTORS, 5. Personal FACTORS, 6. Relational FACTORS, 7. Economic FACTORS, 8. Media FACTORS, 9. Contextual FACTORS. Each of the main Categories is divided into Different Subcategories. The Social FACTORS of infidelity were including “Infidelity Opportunities”, “Friend groups” and “Environmental Conditions”. Psychological FACTORS of Infidelity Were Including “Personality Type”, “Attachment Styles”, and their “Love Schema”. Cultural FACTORS have Pointed to “Change in Beliefs and values” and “the level of Religious Education” of people. The Family FACTORS were including “Inappropriate Marriage”, “Family Conflict” and “the Kind of Family Background of people”. The Personal FACTORS are “Sexual Dissatisfaction”, “Emotional Dissatisfaction”, “the Feeling of Loneliness”, “the Spouse Unavailability”, “Weakness in Controlling Spouse”, “Domestic Violence”, “Revenge of the Spouse” and “the Role of the Third Person in the Relationship”. The Economic FACTORS are including “the Economic Status of the person”, “the Role of Economic Problems”, “the motivation of entering into infidelity under the Pretext of Job promotion”. The media FACTORS Were Emphasized on “weakening Iranian Values through Social Media Networks and Foreign Satellite Channels” and “Producing of New Needs by Media”. Finally, the Contextual FACTORS were including the Role of “Age” and “Gender” in the Infidelity. Findings showed that Infidelity Occurred in the group of men and youth in Iran, more than other Social Groups.

The purpose of this research is to investigate the FACTORS affecting the formation of leading schools, so that it can be used in Iran's education. For this purpose, first, according to the research background and theoretical foundations, a conceptual framework was presented in the field of the components of an efficient and progressive school. Due to the nature of the subject, this research is an applied and developmental research and its method is of a mixed type, and includes quantitative and qualitative methods. According to the obtained information, the statistical population is about 3000 people. The sample size is estimated to be 344 people using Morgan's table. Stratified sampling method was used for sampling in this research, and 84 managers and 260 teachers participated in this study. The tool of this research is a researcher-made questionnaire. To analyze the data and answer the research questions, the correlation coefficient test and factor analysis were used. The results of the research showed that the components of management and leadership, research FACTORS, educational FACTORS, human resources, budget and infrastructure, technology and equipment are the main components of the formation of leading schools, and the component of educational FACTORS has the largest contribution.

Identifying the constraining FACTORS of production and yield gap is very important. Therefore; this research was performed to identify the production constraining FACTORS of local rice cultivars. All management practices from nursery preparation to harvesting stages for 100 paddy fields of local rice cultivars were recorded through field studies, in Sari, from 2015-2016. In the CPA, the actual and calculated potential yield were 4495 and 5703 kg/ha, respectively and the gap was 1221 kg/ha. The yield gap caused by number of top-dressing variables was 324 kg/ha, equal to 27% of the total yield gap. The yield gap related to previous year of legumes cultivation was 218 kg ha-1, equal to 18% of the total yield variation. Among the 10 variables entered in the CPA model, the effects of top-dress fertilizer application and its application frequency and foliar application were remarkable, which could compensate a significant part of the yield gap (444 kg/ha, 37% of total) in the farmers’ fields by managing these variables. According to boundary line analysis (BLA) finding, actual yield mean on the basis of optimal limit related to 12 variables under study was 5369 kg/ha, with 881 kg/ha yield gap . Mean relative yield and relative yield gap for 12 variables (transplanting date, seedling age, number of seedlings per hill, planting density, nitrogen and phosphorous per hectare, nitrogen before transplanting, harvesting date, lodging problem, pest problem, diseases problem and weeds problem) were 83.64 and 16.35 kg/ha, respectively. Based on the finding, it can be stated that the model precision is appropriate and can be applied for both estimation of the quantity of yield gap and determining the portion of each restricting yield variables.

A new GEOMETRICAL hydrogen bond parameter, defined as delta(+) which takes the position of hydrogen into account, has been introduced. It is shown that there exists a strong correlation between delta(+) and other GEOMETRICAL parameters and proton anisotropic chemical shift. It has been suggested that this correlation could be used for estimating the position of hydrogen bond from proton anisotropic chemical shift measurements and X-ray diffraction data.

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.

Good estimation of fragmentation potential is very important topic before selection of caving extraction methods. In-situ fragmentation is result of discontinuities with zero tension strength but primary and secondary fragmentations happen in rock blocks that seem intact and without any discontinuity. In reality in these blocks when induced stresses (due to under cutting) or shock and stress (due to transition of rock mass) affect the blocks, weak surfaces such as rock bridges, veinlet and schistose surfaces (surfaces with tension strength) are first candidates for breakage and slice. Thus it is necessary to quantify these discontinuities in a rock mass. The purpose is to construct a way for prediction of potential discontinuities. In the next step based on necessary energy for breakage, potential discontinuities are classified. We try to design and construct a new method for quantifying and classifying discontinuities in rock mass.  This method helps us to have an initial estimate of fragmentation when induced stress and large scale displacement affect rock blocks. Rock bridges, veinlet and weak surfaces in rock like as schistose surfaces (surfaces with tension strength) are potential discontinuity. Those joints that have potential of being counted as discontinuities but are not considered discontinuity in in-situ form are put in class No, 2 versus in situ fractures (surfaces without tension strength) are classified No, 1. fractures which are created after large scale displacements are known class No, 3.

Among the theories related to geometry education‎, ‎the theory of figural apprehension has attracted the attention of researchers because it has a special focus on GEOMETRICAL figures‎. ‎This theory was presented by a theorist named Raymond Duval‎. ‎The purpose of this article is to give a brief description of this theory and to reveal its importance in the process of teaching and learning geometry‎. ‎In this theory‎, ‎the use of GEOMETRICAL figures is related to four apprehensions named perceptual‎, ‎sequential‎, ‎discursive and operative‎, ‎each of which has special characteristics and it is necessary to focus on all of them‎. ‎However‎, ‎researchers put special importance on operative apprehension‎. ‎Because with the help of this apprehension‎, ‎you can get an insight to solve a problem or to provide a proof‎. ‎Also‎, ‎mastering these four apprehensions is a prerequisite for solving GEOMETRICAL problems with multiple solutions and is also effective in promoting creativity‎. ‎Although this theory has met with good luck in new global research studies‎, ‎internal research sources have rarely dealt with it and most of them have dealt with Van Hielie’s theory‎. ‎Therefore‎, ‎the discussing such theories can be useful in reviewing the process of teaching geometry and planning for in-service courses for mathematics teachers‎.

Despite the many studies conducted in the field of mathematics education and especially geometry, we see that the process of teaching and learning geometry has many challenges. Students' challenges in geometry usually appear when solving problems. Two of the approaches that describe the process of solving geometric problems are called GEOMETRICAL paradigms and working spaces. The purpose of this article, which is a review article, is to briefly describe these two approaches based on related studies and then show their importance in the process of teaching and learning geometry. In general, GEOMETRICAL working space refers to the interaction between the three components of visualization, construction and proof. The working space in which a person is reasoning depends on the GEOMETRICAL paradigm. In Geometry I, the reasoning is based on intuition and experiment, and in Geometry II, the reasoning is made by axioms, but the connection with the physical world is still maintained. Finally, in Geometry III, there’s no connection with the physical world and the reasoning is completely logical and abstract. Identifying students' GEOMETRICAL paradigms and studying the working space in which they solve problems allows teachers to design their teaching according to students' understanding and also in case of difficulties in the process of teaching and learning, they can use a useful approach.1. IntroductionLearning geometry causes many challenges for students. Many of these difficulties appear when facing geometric problems and choosing the right strategies for solving or proving them. In general, the way students deal with geometric problems and the strategies they use to solve or prove them, reveals important information about their attitude toward geometry. The GEOMETRICAL paradigms and working spaces describe the students’ way of looking at problems and also the strategies they use in solving them [3, 4].2. Main ResultsParadigm means all the beliefs held by the members of a community. Learners and teachers with similar paradigms can easily communicate with each other, and when they have different paradigms, many difficulties and misconceptions occur \cite{5}. For example, in the process of proving a claim, it is sometimes allowed to use drawing, but sometimes it is not acceptable and providing more detailed reasonings is needed. Therefore, in different situations and problems, learners use different paradigms and we can't say one paradigm is more accurate than the others. In general, three different GEOMETRICAL paradigms are introduced by Houdement and Kuzniak [3]. In Geometry I, learners use perception, experiment and connection with the physical world to solve a geometric problem. It is related to reality. So the backward and forward movement between the model and reality is allowed to prove the geometric assertions. In Geometry II, the objects are not material. Definitions and axioms are necessary to define and create the objects, but in this paradigm, they are close to intuition. At last, in Geometry III, the system of axioms has no relation with reality. It is independent of any application of the objects of the real world. This paradigm is mainly used in university courses and it doesn’t exist in school geometry. A common educational misconception happens when students and teachers are not in the same paradigm. The passage from one type of Geometry to another is a complex phenomenon. Because it’s a change of theory and can be considered an educational evolution. At least, two transitions happen that are not the same. The first transition (from Geometry I to Geometry II) deals with the nature of the objects and the space. The second one (from Geometry II to Geometry III) concerns the system of axioms and it leads to a more complex process. During elementary school, the first transition must happen and teachers can think about how to prepare students for Geometry II [2,3,5,6]. In order to identify the students' GEOMETRICAL paradigm, it is necessary to examine the strategies they use in problem solving. In fact, the GEOMETRICAL working space in which they solve problems should be identified. If we consider mathematics as an activity that is done by the human brain, we can find out how learners have a GEOMETRICAL paradigm. When experts solve geometric problems, they go back and forth between paradigms. A GEOMETRICAL working space is a place that is organized to explain the process of solving geometric problems. It illustrates the structure of the complex situation in which the problem solver acts. It involves two planes which are called the epistemological and the cognitive planes. In the epistemological plane, there are three elements. In fact, learners use three components which are the theoretical system of references, the real space, and artifacts to solve a geometric problem. These components are not sufficient to define the meaning of the GEOMETRICAL working space clearly. Because it strongly depends on its users too. So the cognitive plane was introduced to describe the cognitive activity of each user which consists of visualization, construction and proof. The process of linking the epistemological plane and the cognitive plane is part of GEOMETRICAL work. In fact, problem solvers use more than one component to reach the correct response to a problem and a set of these actions represents their GEOMETRICAL working space [4,5,6,9]. The variety of GEOMETRICAL working spaces depends on the way users synthesize the cognitive and epistemological planes to solve geometric problems. It also depends on the cognitive abilities of each user too. In fact, being an expert or a beginner in solving problems affects the structure of GEOMETRICAL working space [4].3. Summary of Proofs/ConclusionMany of the difficulties in the process of teaching and learning geometry are due to the difference in the paradigms and working spaces of students and teachers. Several FACTORS influence the students' GEOMETRICAL paradigm and the working space in which they solve problems, among which the role of the teachers and the textbooks are the most prominent. In fact, the educational system of each country can determine the type of preferred paradigm for each educational level according to the goals of the curriculum. So teachers should be familiar with these approaches and in addition to being aware of them, they can guide the students toward a suitable working space [4,6].

Stepped spillways are consisting of some steps, which started from top crest of weirs to the down stream of spillways. These structures are used now because of their efficiency in dissipating energy of flow, and their benefits in economical aspects. This kind of spillways is also used in agriculture because of air entrance along them and natural purification of water. This study was carried out to find a mathematical model for estimating the relative dissipation of energy by making 10 physical models of stepped spillways in a laboratory flume. The models were built up to 31 steps, and data was collected by passing many different discharges through them. Effective parameters such as: a, N, Hdam, Yc, and (h, l) were obtained by data analysis and then some important and effective dimensionless parameters for geometric optimization of the stepped spillways were found using a dimensionless technique and analyzing the results. There was a relation between the relative dissipating energy and some dimensionless parameters like yc/h, Hdam/yc. Results showed that the best physical model for dissipating the energy was 15 step spillways. Finally, the geometric optimized formula were proposed for mentioned spillway by analyzing the obtained parameters.

This article aims at studying the GEOMETRICAL proportions of five types of most outstanding designs of Safavid carpets as one of the most important styles in carpet art of Iran. This research has been conducted using geometric methods of translation of measures and finding the basic module for identifying the proportions in carpets for to determination and comparison of modules with each other. Then the findings of the research have been compared with reference GEOMETRICAL proportions of the Iranian geometry. Ultimately, the findings of this paper have been compared with special proportions present in decorative arts of the Timurids, Ilkhanid, and Seljuk periods, which possess special and specific proportions according to researchers, in order for determining the origin of this system of proportions. The results indicate that the carpets have general GEOMETRICAL proportions. Such proportions include certain proportions between the pattern and dimensions of carpets.