The phenomenon of poverty is a social, economic, cultural, and political reality that has long been one of the greatest human problems. The purpose of this study was to identify the factors affecting poverty and examine the internal relations and its leveling with an interpretive structural approach in the Imam Khomeini Relief Committee of Tabriz. In this regard, based on the factors extracted from literature, a questionnaire has been developed. In this phase, 41 indicators have been selected as the most important indicators affecting poverty at Imam Khomeini Relief Committee of Tabriz city. After obtaining appropriate validity and reliability for the questionnaire, it has been distributed among the statistical sample. After distributing the questionnaire, factor analysis was used to analyze the information and reduce the variables to dimensions. The results of factor analysis showed that about 68.3% of the total variance of variables was explained by 14 factors and about 31.7% of the variance was explained by other variables that were not measured. As a result, 14 factors have been identified as the most important factors affecting poverty. These 14 factors are important in order of importance: 1- Economic; 2- Social; 3- Individual; 4- Legal; 5- Family; 6; Environment; 7; Political; 8; Management; 9; Cultural; 10- Overseas; 11. Security; 12. Scientific; 13. Organizational; 14. Geographical. Finally, the interrelationships between factors and the leveling of poverty-related factors have been examined by presenting an extended structural-comparative model (ISM).

In fact, the growth of urban consciousness is a wise strategy to drive urban development and control dispersion and drive urban growth toward sustainability. The purpose of this study was to evaluate the rate of Bushehr city area in terms of growth indices. In this regard, this research is a goal-oriented, applied-developmental one, and a combination of documentary, analytical, causal and survey methods. Reliability of the research instrument based on Cronbach's alpha coefficient of the research was 0.749 which is higher than 0.7 and is appropriate. The statistical population of the study is Bushehr inhabitants which according to Cochran formula is estimated 384 samples. According to the statistical population, the questionnaire was distributed randomly among the citizens. In order to compare between two regions, T-test with two independent samples was used for evaluation of urban smart growth in District 1 and 2 of Bushehr. In this test, the first option to be considered is the significance level while the significance level or sig between the two regions is less than 0.05 indicates a significant difference between the two regions and vice versa. Significance level analysis (0.000) shows that there is a significant difference between the two regions in terms of urban smart growth. Meanwhile, the mean of Region 1 with 3.21 was higher than that of Region 2 with 2.86. Although there is a significant difference in Bushehr region in terms of smart growth indices, this difference is not significant and in general Bushehr regions are not in a good position in terms of smart growth indices.

Extreme precipitation events pose a significant and growing threat to society, often leading to floods, landslides, and widespread socio-economic damage. Daily precipitation data collected from 9 rain gauges during 1/1/1991 to 31/12/2023. To identify days associated with heavy precipitation, the 95th-percentile threshold was employed. Days on which the recorded precipitation exceeded the long-term mean of the 95th percentile at more than half stations were classified as heavy-precipitation days for Kurdistan Province. Based on this threshold and criterion, 210 days were selected. Two data arrays with an S-mode structure were constructed for sea-level pressure and 500-hPa geopotential height. Using Principle Component Analysis (PCA) analysis, components explaining more than one percent of the variance were retained as significant modes. For sea-level pressure, nine components were identified, and for the 500-hPa geopotential height, eight components were extracted. Together, these components explained over 92% of the variance in sea-level pressure and more than 95% of the variance in the 500-hPa geopotential height over the study domain. Cluster analysis (CA) performed on the score matrix of the 17 components was then used to identify the prevailing circulation patterns.
 

 Extra-regional threats refer to a set of military, security, political, and economic measures or pressures exerted by countries or coalitions from outside a specific geographical region against the interests and security of a country. These threats typically exploit geographical distance, modern warfare tools, comprehensive sanctions, and the establishment of influence in neighboring countries to undermine stability and limit the regional power of the target. This research has been conducted with the aim of identifying and analyzing the key drivers affecting trans-regional threats to Iran using a future studies approach, in order to analyze the systemic structure of these threats and outline the most probable scenario ahead. The method of this research is mixed (quantitative-qualitative). For this purpose, initial indicators were extracted through multi-stage interviews with a panel of 15 experts and then screened using the Delphi method. In the next stage, a cross-impact analysis questionnaire was administered to 15 specialists and experts, and the data were structurally analyzed using MICMAC software. The distribution of variables on the influence-dependence map indicates the instability of Iran's trans-regional threats system. Among the 49 variables examined across five dimensions—political, economic, socio-cultural, defense-security, and natural-environmental—three variables were identified as the most key drivers and as dual-risk/target variables: new regional coalitions in Iran's periphery involving global powers (P3), pressure on countries party to agreements with Iran to terminate cooperation (P7), and new trans-regional political coalitions against Iran's political positions (P1). Furthermore, the variable "keeping the minds of the country's decision-makers occupied with domestic issues" (P8) ranked first in terms of direct influence. The results of the research indicate that the future of trans-regional threats to Iran can be depicted in the form of the "Intelligent Siege" scenario. In this scenario, trans-regional powers, through regional and trans-regional coalition-building and severing Iran's contractual ties with the world, drive the country toward strategic passivity and reduced room for maneuver without a full-scale military war. The paradigm shift of threats from a purely military nature to political, cognitive, and intelligent threats is the most important characteristic of the future of these threats.

Characterizing the scaling structure of topography is essential for linking observable land-surface morphology to the processes governing landscape evolution. Conventional geomorphometric approaches often describe terrain using self-affine models parameterized by a single roughness exponent, implicitly assuming statistical homogeneity across scales. Such formulations, however, may not adequately capture landscapes shaped by the coupled action of tectonic deformation, climatic forcing, and nonlinear erosional dynamics. In this study, we evaluate the scale dependence of surface roughness using high-resolution digital elevation data from the Iranian Plateau, a morphotectonically diverse region representative of actively evolving continental domains in West Asia. Fractal analysis based on box-counting yields a dimension of Df≈2.20, while spectral analysis of elevation fields provides a Hurst-type roughness exponent of α≈0.48. The lack of agreement with the canonical self-affine relation Df=3−α indicates that the terrain cannot be characterized by a single scaling descriptor. To investigate this departure, we compute higher-order statistical measures of elevation variability, including generalized structure functions, multiscale height–height correlations, and scale-dependent curvature metrics. These analyses reveal that the scaling exponents vary systematically with statistical moment, demonstrating clear multiscaling and supporting a multifractal description of the surface. The results suggest that topographic organization in tectonically active settings reflects heterogeneous process interactions operating over a hierarchy of spatial scales, rather than uniform rough-surface behavior. This work underscores the limitations of single-exponent geomorphic parameterizations and highlights the value of multifractal diagnostics for quantitative terrain analysis, comparative morphotectonic studies, and improved representation of landscape complexity in Earth-surface models.

When empires and great nations decline, there are many interrelated reasons involved in. Empires are considered to be powerful entities in the world, and via historical surveys, one can identify several important empires that have existed in different eras. Geopolitical knowledge and its constituent concepts (power, politics, and space) are closely associated with empires and can be explored from this perspective. The aim of this research is to conduct a geopolitical investigation of the collapse of empires. The research deal with the geopolitical factors contributing to the collapse of empires such as Persia, Rome, Byzantium, Ottoman, Britain, Russia, Spain, and Arab countries, using a descriptive-analytical method and field research. The statistical population consists of 50 specialists and experts in the field of geopolitical studies. The Dimtel method has been utilized to test the conceptual model of the research. The findings demonstrate that variables such as the incompetence and capriciousness of rulers, the collapse of the domestic economy, the extravagance and corruption of the governing class, oppression and slavery, and internal rebellions have a high level of interaction and a strong systemic connection with other variables. In other words, when a country faces these challenges in terms of its leadership and governance, it becomes unable to effectively address other problems caused by these factors, leading to a crisis and the eventual collapse of the empire.

The current research is based on the process of algorithmic design and simulation of village boundaries using the Grasshopper plugin in the Rhino software. The proposed algorithm utilizes the image simulator component and its importer in the Grasshopper plugin to input two-dimensional images taken from samples into this plugin. Before entering the data, the input images are converted to black and white to allow the system to distinguish between the background texture and the subject of analysis. Additionally, the proposed algorithm identifies the village boundary by comparing the subject and the text in the pixels of the two-dimensional image. By calculating the internal area of the identified boundary, the algorithm estimates the proportion of textures relative to the background. The main objective of this research is to examine the impact of green and dry textures as natural factors on the density of residential texture in terraced villages in Iran, across various climates. In addition to identifying the density of village textures, emphasizing the comparison of parameters will provide new insights into the texture of terraced villages. The simulation analysis tool, known as the density measurement algorithm, is developed based on aerial maps created by the researchers for this study. By using inverted aerial maps, this algorithm can determine the density of natural texture in the formation of villages and residential texture. This capability reduces the need for physical presence and enhances the accuracy of outputs in analyzing village texture. Furthermore, the identification of parameters will provide the next generation of rural housing with the density pattern of previous generations.

Idealism for urban living necessitates the establishment of infrastructure and a platform that considers all stakeholders, including managers, planners, and citizens, regardless of their social and economic backgrounds, social class, gender, etc. This concept is encapsulated in the notion of the right to the city. However, implementing this concept can pose challenges in smaller cities with more unfavorable conditions. Hence, this research aims to introduce a model for actualizing the right to the city based on the Analytical Network Process (ANP) in the rural cities of western Mazandaran. The current study is categorized as applied research. The statistical population for this study comprised urban experts (chosen through the Delphi technique with a sample size of 25). Alongside on-site observations, information was gathered utilizing the fundamental maps of the country's mapping organization and studies focusing on the three cities of Baldeh, Kejur, and Pol (Kham-shahrs in the western part of Mazandaran province). The Analytical Network Process (ANP) method was employed to process and analyze the data, leading to the extraction of a balanced supermatrix using the Super Decision software. Following various steps, the final priorities of indicators and options for realizing the right to the city were determined. The results of the network analysis (ANP) of the dimensions of realizing the right to the city in the western cities of Mazandaran province indicate that the physical-biological dimension holds the highest weight and importance (0.1970). It is trailed by the economic dimension (0.1725) and the social and cultural dimensions (with a final weight of 0.0847). Among the criteria for realizing the right to the city in the western cities of Mazandaran province, the right to self-determination carries the most significance with a weight of 0.1461, followed by environmental rights (0.0943) and the right to a sustainable city economy (0.0840).

As cities develop and expand, their encounters with various topographic and geomorphological units and related issues increase. Geomorphological units are always related to the dynamics and dynamism of the natural environment, and any action taken in the direction of the development and construction of cities in some way intersects with the aforementioned dynamics and dynamism and, as a result, with morphological phenomena. In this encounter, if some essential principles and points are not observed, the morphodynamic balance of the environment will be disrupted and major risks will threaten the majority of urban equipment and facilities. The purpose of the present study is to investigate the role of unevenness in coastal city planning by comparing the two analytical hierarchy process methods, AHP and AHP FUZZY, in the city of Noor. The research method is descriptive, analytical and field-based in terms of applied and developmental purpose and in terms of data collection, in which the researcher-made questionnaire was used as a tool. The result of the sensitivity analysis showed that AHP is sensitive to uncertainty in the decision model; However, the comparative analysis shows that the differences between the criteria rankings in the two models do not necessarily result in the selection of different options (as focal points), but rather differences in the spatial extent of the selected options are more important. The findings provide a new direction for the selection of MCDM methods for urban planning. If the planning objective is to identify priority areas for development as focal points, then simpler MCDM methods such as AHP should suffice; but in more detailed planning where the identification of spatial boundaries is required (such as determining the master plan), a multiple approach using two or more MCDM techniques would be ideal.

The application of structural analysis to development drivers facilitates a more nuanced understanding of the developmental landscape of provinces and enhances regional equilibrium in decision-making processes. This study examines the ten cities within Ilam province through a comprehensive assessment of 44 combined development indicators. Methodologically, this research is classified as applied in nature and employs a descriptive-analytical approach, utilizing contemporary futurology techniques. Theoretical data were gathered through documentary methods, while empirical data were collected via surveys. Development drivers were identified through documentary analysis and environmental scanning, complemented by empirical data obtained through the Delphi method. Data processing employed the structural interaction analysis method using MIC MAC software. Findings from the interaction analysis reveal a dispersion of propulsive forces within a complex and intermediate context of impact and effectiveness; the clustering of drivers illustrates the concentration of both effective and regulatory forces. Among the 44 identified development drivers, the borders of Ilam province and managerial decision-making processes emerged as significant effective drivers. The results indicate that development in Ilam province is characterized by pronounced imbalances, with a trend towards increasing inequality. It is suggested that only through improved and more comprehensive planning can these disparities be partially mitigated.
 

 

for the spatial analysis of precipitation in the Middle East, have been used gridded precipitation data from the World Precipitation Climatology Center (GPCC) with a monthly temporal resolution and a spatial resolution of 0.5×0.5 arc degrees. Therefore, a matrix of 80 x 160 dimensions was obtained for the Middle East region (160 longitudinal cells and 80 transverse cells). The reason for choosing network data is their proper spatial and temporal separation and their up-to-date compared to station data. The period under investigation is from 1970 to 2020 AD. Finally, the long-term maps of the Middle East precipitation were drawn on an annual and monthly basis. The results indicate that precipitation in the Middle East tends to concentrate and cluster in the spatial and temporal dimension. In other words, due to the special geographical location of the Middle East region, such as uneven topography, distance and proximity to moisture-feeding sources (Caspian Sea, Black Sea, Mediterranean Sea, Atlantic Ocean, and Indian Ocean) and the direction of unevenness, Precipitation in high altitude areas, It is concentrated in the neighborhood of seas and oceans and also in the windy slopes of the mountain range of the region. The uneven distribution of geographical conditions has caused uneven distribution of Precipitation in the Middle East. So that; The center and gravity of the Middle Eastern Precipitation is concentrated in the eastern end of the Black Sea, southern Turkey in the neighborhood of Syria and Iraq, the Ararat-Zagors belt in the west of Iran, the southern shore of the Caspian Sea, the Pamir highlands and the Bay of Bengal in India, and the Hindu Kush highlands in Pakistan. Is. However, the many parts of the Middle East, due to their proximity to large deserts (African Sahara, Lut Desert, Dasht-Kavir, Arabia's Rab-al-Khali and Afghan deserts), have less than 100 mm of Precipitation. The results showed that the maximum Precipitation of this region has been transferred to the winter season, and the summer season is still the driest period in the Middle East, and only the coasts of the Indian Ocean and the Bay of Bengal have monsoon rains

Resiliency is one of the approaches to reducing the vulnerability of communities and strengthening peoplechr('39')s ability to deal with the dangers of natural disasters, especially earthquakes, and has economic, social, institutional, physical, and environmental dimensions. This research is applied in terms of purpose and descriptive-analytical in terms of nature and research method. The researcher-made questionnaire with 102 items was a tool for collecting research data. The sample size was 386 simple based on Cochranchr('39')s formulas and the sampling method was random. Exploratory factor analysis and path analysis were used in the SPSS25 software platform for data analysis and factor modeling. The results indicate that Parsabad city has the lowest scores in terms of social and physical resilience and is in a moderate to good condition; environmental resilience is in a moderate condition, institutional and economic resilience are in a bad situation. Also question factorization, 13 factors for social dimensions, (behavior during the crisis, crisis awareness, crisis preparedness, knowledge, cooperation, trust, assistance, reliance, interaction, accuracy, attitude, first aid, and necessary measures); 3 factors (Damages, Compensation and ability to return) for economic dimensions; 5 factors (performance of public institutions, the performance of semi-public institutions, institutional communication, institutional measures, and institutional context) for institutional resilience; 4 factors (open space, building resistance, public access and Relief access) for physical resilience and 3 factors (environmental, nutritional and soil factors) for environmental resilience. Finally, the modeling of resilience indicators for Parsabad city was presented.

Tehran’s District 12, as one of the capital’s cultural and tourism hubs, hosts a collection of prominent cultural institutions and museums that serve as major attractions for domestic and international visitors. However, the absence of systematic planning for routing between these centers leads to wasted time and energy for tourists and diminishes the quality of their visitation experience. This study aims to optimize museum visitation routes in Tehran’s District 12, focusing on minimizing travel time and distance, by selecting 22 active and significant museums in the area as case studies. To achieve this, the mathematical model of the Open Traveling Salesman Problem (Open TSP) was applied within the framework of network analysis in a Geographic Information System (GIS) environment. Precise spatial data—including the geographic locations of museums and the local street network—were imported into ArcGIS software and processed using the Network Analyst tool. Travel cost matrices (based on time and distance) between all museum pairs were calculated, and optimal visitation routes were extracted and ranked using heuristic Open TSP algorithms according to the criteria of minimum time and shortest distance. Findings indicate that applying the Open TSP model within network analysis leads to the identification of significantly more efficient routes compared to conventional patterns or unplanned visits. Quantitative results show that, under normal (non-optimized) conditions, visiting all 22 museums covers a distance of 25.91 km with a travel time of 310 minutes, whereas the optimized proposed route requires only 9.896 km and 118 minutes of travel time. This improvement represents a 62% reduction in both distance and travel time. The study demonstrates the high efficiency of integrating combinatorial optimization models with GIS spatial analysis capabilities for urban tourism planning and can serve as a model for intelligent management of tourist visitation routes in other urban areas. The results enable informed decision-making and optimal planning for both group and individual visits, significantly enhancing the tourism experience by reducing time and physical costs.