Introduction: Academic faculty members need to emphasize ethical principles in order to improve higher education, with the understanding of this importance, the current research was conducted with the aim of designing the ethical model of academic faculty members in Iran's higher education. Material & Methods: This research is a type of qualitative study that uses foundational data theory. The participants, including experts and faculty members of the country's public universities, who were responsible for the promotion of academic members, were selected as key informants through a targeted sampling method of 45 people. Data were collected through semi-structured interviews. The reliability and validity of the data were obtained from the two methods of reviewing the participants and recoding by experts. Data were analyzed by open, central and selective coding. Results: The results showed that the moral model of faculty members in Iran's higher education is explained in 10 main categories and 27 subcategories. Major and core categories in the form of 6 dimensions of causal conditions including (individual factors, organizational factors), core (cultural-educational, educational ethics, research ethics, scientific-executive), background conditions (higher education policies, moral activism), intervening conditions (environmental factors), strategies (micro level-university, macro level-higher education) and consequences (individual and organizational) were elevated to a higher abstract level and finally the research paradigm model was presented. Conclusion: The regulations for the promotion of academic staff members in Iran require a detailed revision of the content with an ethical and qualitative approach in order to make the indicators of the promotion regulations efficient and effective.

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.

Background: The expansion of the use of audio and video media technology has faced society with many medical, cultural and economic challenges. In the meantime, excessive use of mobile phones can cause many problems. Objective: The aim of this study was to construct and validate a questionnaire on physical and psychological injuries of mobile phones. Method: The method of the present study was descriptive-correlational and confirmatory factor analysis. The statistical population of the study consisted of all citizens of Khorramabad with a diploma or higher in 1399, which was selected as a statistical sample by available sampling method of 200 people online and virtual. Results: The results showed that the factorized physical and psychological harm questionnaire of cell phone with 42 questions and 10 components (fear of loss, vibration syndrome, duck syndrome, nomophobia, insomnia, hearing problem, eye syndrome, tunnel and neck syndrome SMS) and has good reliability, validity and flexibility in terms of psychometrics. Discussion and Conclusion: The questionnaire of factor analysis of physical and psychological injuries of mobile phones can be used to identify and study the physical and psychological injuries of mobile phones.

The recognition of physical-spatial development patterns of cities is necessary for achieving to urban sustainability. Because, many of sc, ientists believed that a meaningful relation between urban form and urban sustainability exist. With attention to this issue, the purpose of this research is evaluating of Sabzevar physical-spatial development pattern with using quantities models such as size-rank rule, Gini coefficient, relative entropy, geary coefficient, and density gradient and correlation analysis. Methodology of research is combination of inductive and apriority methods. The results of this research indicated that during 1993-2006 years, gross population density of Sabzevar very reduced and from 128 per/h received to 76 per/h. this reduction says that in these periods Sabzevar have had s sprawl. Investigation of size-rank rule represented that during 1921-2006 rate of physical development growth is much more than rate of population growth. Density gradient in sabzevar in 2006 is reducing with distance from city center. It means that in Sabzevar city outskirts is developing. Investigation of Equal distribution grade of population with using Gini and relative entropy coefficient indicated that population distribution in Sabzevar in 2006 rather than 1993 has been equaled. Surveys of agglomeration grade of population with use of geary coefficient shows that distribution of population in Sabzevar city in 1993 has been random agglomeration while in 2006 became sprawl. The use of Holdern model indicates that significant part of sprawl in Sabzevar city has been occurred during 2003-2006 years. In these years, 30 percent of urban physical growth derives population growth and 70 percent of this growth derives sprawl and horizontal expansion and finally, Correlation analysis indicates that between gross population density and variables such as statistic district area, literacy, family dimension and family in residential unit had existed significant relations. Pay attention to this issue that during 1993-2006 years, sprawl has been one of the important features of physical development Sabzevar, it is necessary to urban Manager's restrict factors that create sprawl and horizontal expansion in Sabzevar city.

Introduction Having knowledge about spatial form of city is one of the important factors affecting the success rate of urban planners and practitioners, and it helps improving urban environment. In the present research, we are trying to evaluate spatial – physical growth pattern of Tabriz metropolis using quantitative methods. Methodology The current research is descriptive – analytical and practical approach in terms of nature and method, so that, using survey, documentary and library studies, data were firstly gathered and studied, and then physical – spatial form of Tabriz city growth was calculated using quantitative methods (metropolis size, density, aggregation degree and balanced distribution). Results and Discussion The results of the research show that Tabriz metropolis is facing an imbalanced growth pattern. Conclusion lack of balance was created between the increase of city area and population growth which caused the city to be formed greater than what it is determined to be.

The purpose of the present study was to investigate the effect of generative learning teaching based to pattern cognitive Load on the memorization math of 7th grade students of in the academic year of 2021- 2022. The research method is quasi-experimental with pre-test and post-test with four groups: two control group and two experimental groups. The statistical population of the study consisted of all 7th grade male and female students of District 2 of Mashhad city that 112 person sample was selected by single stage cluster sampling method. The subjects in the experimental group involved in generative learning based to cognitive Load in 16 sessions and the control group did not receive any interventions. The research instrument consisted of a 20-questions researcher-made test. To analyze the obtained data, Multivariate analysis of covariance and SPSS version 24 software were used. The results showed that generative learning teaching based to approach cognitive Load have a positive and significant effect on 7th grade students' memorization math. Based on the findings, it can be concluded that one of the effective training on math memorization students is the use of generative learning on the based load cognitive pattern.

Background and Objectives: One of the quantum computing models without a direct classical counterpart is one-way quantum computing (1WQC). The computations are represented by measurement patterns in this model. One of the main downsides of the 1WQC model is the much larger number of qubits in a measurement pattern, compared to its equivalent in the circuit model. Therefore, proposing a method for optimally using the physical qubits to implement a measurement pattern is of interest,Methods: In a measurement pattern, despite a large number of qubits, the measured qubit is not needed after each measurement and can be used as another logical qubit. In this study, by using this feature and presenting an integer linear programming (ILP) model to change the ordering of a standard measurement pattern actions, the number of physical qubits required to implement that measurement pattern is minimized. Results: In the proposed method, compared to the scheduling based on the standard pattern, the number of required physical qubits on benchmark circuits is reduced by 56.7% on average. Although the proposed method produces the optimal solution, one of the most important limitations of that and ILP-based methods, in general, is their high execution time and memory requirements, which grow exponentially with the increase of the problem size. Conclusions: In this study, an ILP model is proposed to minimize the number of physical qubits used to realize a measurement pattern by efficiently scheduling the operations and reusing the physical qubits. Due to its exponential complexity, the proposed method cannot be used for large measurement patterns whose solution can be conspired as future works.

The rapid expansion of cities, make most of the world faced with many problems. Although population growth is the primary cause of the rapid expansion of cities, however, its unreasonable sprawl will have adverse effects on the natural environment and cultural communities. Many attempts have been made to alleviate the negative effects of cities sprawl that most notably is "smart growth" strategy as one way of opposition to urban development " sprawl ", in fact, smart growth is alternative to sprawl. In this research, research methodology is descriptive-analytic method. The data has been achieved from Statistical Center of Iran 's statistical block 1390. For this study, data extraction and classification software (SPSS) and (GIS) is used. The Moora method is used to rank neighborhoods. The results show most central neighborhoods have more favorable conditions terms of smart urban growth indicators than urban surrounding neighborhoods. Whereas urban central neighborhoods have more appropriate level than other neighborhoods in term of the main indicators of smart growth such as mixed use, connections, open spaces, infrastructure and car ownership. multi objective optimization ratio analysis(MOORA) ranking test results showed that three neighborhoods 7, 2 and 6, respectively, have the best ranking among the city's 25 neighborhoods and in against urban surrounding neighborhoods 14, 13 and 4 have the worst condition and ranking among the city’ s neighborhoods. Due to the single-core structure, high levels of car ownership (47 percent) and Amol business-services dominant function, aspect of smart growth strategy can be implement in this city management through make policy in increased mixed uses, make attractive the pedestrian-oriented path and public transport development.