رضا دهقانی

Despite the growing body of literature on the advancement of authoritarian tactics and tools in competitive authoritarian regimes, we still lack sufficient knowledge about the discourses and strategies that the opposition creates and uses against populist-authoritarian governments. With the case study of Turkey, this article introduces "transnationalization" as one of the innovative discourses and strategies based on which the opposition bloc succeeds in exploiting its tactics and tools in order to maintain its political position in the political arena. And it has become an identity. Introducing the governance methods and techniques of authoritarian regimes is one of the other goals.

Method and theoretical framework:

The method of this research is based on qualitative research with the approach of "process tracing" technique. The content of this research is based on documentary-library sources and analysis of Twitter accounts and is presented in the form of the theoretical framework of "transnationalization".

Transnationalization is defined as a discourse and strategy through which local leaders under the leadership of the opposition change local and global boundaries by creating a conscious link with the liberal-democratic world to expand their space for maneuver. Based on this, the question that is raised is that the opposition bloc of Turkey, focusing on the performance of the mayor of Istanbul, uses which methods and mechanisms to operationalize the discourse and strategy of transnationalization? The answer to this question, which was mostly obtained by analyzing the content of the international Twitter accounts of the mayor of Istanbul, seems that the municipality of Istanbul, in order to maintain its position and credit the political nature of the opposition bloc and to deal with the political threats of the ruling structure, uses material and symbolic tools. And this political strategy and rational and normative motivations have been exploited to the maximum and successfully.

Based on the study of the situation in Turkey, which is considered an example of competitive authoritarian regimes, transnationalization as a discourse and strategy of opposition struggle has been implemented by the municipal institution under the leadership of the opposition bloc (independent variable). Is. So that the mayor of Istanbul belonging to the opposition bloc became a transnational identity materially, symbolically and politically through establishing international relations, showing commitment to global and liberal norms and increasing his agency over foreign policy programs. (The dependent variable) Also, this research highlights the role of international and global forces in supporting democracy and how they can provide effective assistance to democratic agents in authoritarian regimes. As conventional efforts to promote democracy have generated backlash and strong anti-Western sentiments in many countries, international democratic forces no longer have the power or desire to engage in democracy promotion, competing authoritarian leaders like Erdogan in Turkey, a long-standing tradition. They inflame nationalist sentiments by accusing the opposition forces of being in alliance with international "enemies". Nevertheless, this article showed that in Turkey, local leaders under the leadership of the opposition struggled to establish a link with the West as a result of their rational and normative motivations and were in dire need of support from international institutions. Through the symbolic, material, and political means of transnationalization, the mayor of Istanbul aimed to build international credibility and enhance his ability to govern, which is especially important when opposition-controlled municipalities are subject to central government discrimination.

Groundwater sources are essential for drinking water, agriculture, and industrial use. Assessing the quality of these sources, including water hardness, is a crucial aspect of hydrogeological studies. This research aims to estimate and model the level of groundwater hardness in the coastal areas of the Caspian Sea, which is vital for effective management planning and land preparation. We employed a hybrid support vector regression model enhanced by firefly and chicken swarm algorithms. For this purpose, we selected various quality parameters from Babolsar piezometer wells located in Mazandaran Province, which include bicarbonate, chloride, sulfate, magnesium, and calcium, as input parameters, with water hardness as the output parameter, analyzed on a monthly basis over a statistical period from 2012 to 2022. The performance of the models was evaluated and compared using the correlation coefficient, root mean square error (RMSE), and Nash-Sutcliffe efficiency coefficient. The results demonstrated that the hybrid support vector regression model combined with the firefly algorithm achieved the highest correlation coefficient of 0.980, the lowest RMSE of 0.115 ppm, an average absolute error of 0.087 ppm, and a Nash-Sutcliffe value of 0.950. Overall, our findings indicate that artificial intelligence hybrid models perform effectively in estimating groundwater quality parameters.

Predicting Total Dissolved Solids (TDS) in water bodies such as rivers and lakes is challenging but essential for effective water resource management in agriculture, industry, and drinking water sectors. This study develops a hybrid intelligent model based on the Support Vector Regression (SVR) approach to predict the TDS levels in river water. Three optimization algorithms—Wavelet, Firefly, and Grey Wolf—were employed to model the TDS in river water. The study utilized hydrometric station data from the Kashkan River in Lorestan Province as a case study, using eight scenarios combining input parameters from 2003 to 2023. Model performance was evaluated using correlation coefficient, root mean square error (RMSE), mean absolute error (MAE), and Nash-Sutcliffe efficiency coefficient. Time series plots, box plots, and Taylor diagrams were used to analyze the model results. The findings indicated that the combined scenarios improved model performance. The evaluation criteria showed that the Wavelet-SVR model achieved a correlation coefficient of 0.980, RMSE of 0.881 mg/l, MAE of 0.473 mg/l, and a Nash-Sutcliffe efficiency of 0.990 during the validation phase. Overall, the results suggest that intelligent models based on the SVR approach can be an effective strategy for maintaining river quality for aquatic health.

In this study, a hybrid Support Vector Regression (SVR) model, combined with optimization algorithms including Wavelet, Firefly, and Grey Wolf, was employed to estimate groundwater hardness at the Naservand well in the Khorramabad Plain of Lorestan Province. For modeling, monthly quality data of the well during the water year (1382-1402) were used. This included parameters such as bicarbonate (HCO3), chloride (Cl), sulfate (SO4), magnesium (Mg), calcium (Ca), and total hardness (TH), all measured in ppm, which were used as inputs. Groundwater hardness was selected as the model output. To evaluate the performance of the models, assessment metrics such as the correlation coefficient, root mean square error (RMSE), mean absolute error (MAE), and Nash-Sutcliffe efficiency coefficient (NSE) were used. Time series, box plots, and Taylor diagrams were also used for analyzing the model results. The results indicated that hybrid scenarios in the studied models improve the model’s performance. Comparing results showed that the Support Vector Regression-Wavelet model performed better than the Support Vector Regression-Grey Wolf model, with the Support Vector Regression-Wavelet model achieving a correlation coefficient of 0.917, the lowest RMSE of 0.190 ppm, the lowest MAE of 0.115 ppm, and the highest NSE of 0.920 in the validation stage. Overall, the results indicate that using intelligent models based on the Support Vector Regression approach can be an effective approach for managing groundwater quality.

The survey of the fish assemblage in the planned place to establish artificial reefs in the western and eastern bays of Jask was carried out in the winter and spring of 2024. Sampling was done by Gillnet and Trap methods in 4 stations located in the western bay and eastern bay of Jask at a depth of 10 to 30 meters. 68 aquatic species (60 fishes, 5 crabs, 2 oysters, and 1 shrimp) were sampled and recorded. Of these, Nemipterus japonicus (32.6 %) was the most abundant, Saurida tumbil (12.6 %), Anodontostoma chacunda (12.5 %), Ilisha megaloptera (9.8 %), Scomberoides tol (6.4 %), Sphyraena putnamae (4.1 %), Lactarius lactarius (2.6 %), Muraenesox bagio (2 %), Pomadasys kaakan (1.9 %), Otolithes ruber (1.6 %) located in the next rank. The average catch per unit of effort of gillnet was 45±10.2 kg/piece×hour and for Trap 7.3±4.2 kg/trap×day. In this research, it was found that the population of species related to artificial reefs, such as Epinephelus coioides , Lutjanus johnii , and Lethrinus nebulosus were relatively low, and mainly below the maturity size, it seems that the stocks of this group of fish need to be enhanced. Therefore, it is recommended to consider the target species in the design of the structure and arrangement of the artificial reefs, on the other hand, the shelter and protective aspects of the artificial reefs for the reef-dependent juvenile also be considered.

Prediction of average daily evaporation is valuable in various fields such as water resource management, agri-culture, etc. Evaporation is also one of the input components for evaluation models, ecological and hydrological models. On the other hand, many scientific centers try to investigate atmospheric problems, because weather has a major impact on the social and individual life of humans. Weather forecasting is about how the weather changes from day to day. Temperature, evaporation and precipitation are the most important climatic elements that play a major role in determining the role and distribution of other climatic elements. Since temperature plays an essential role in climate classification, its fluctuations and changes are important. It is well known that temperature affects evapotranspiration, surface water, disease, forest fires, and drought. Daily evaporation is the most important climate parameter that is calculated by accurate and approximate methods in weather stations. Studies have shown that this method has low accuracy and usually the difference is 3 degrees Celsius. Today, intelligent methods are used to predict nonlinear phenomena, of which Wavelet Neural Network (WNN) and Artificial Neural Network (ANN) methods are two examples of them.

Dehno weather station (Kakareza) is one of the most important synoptic stations in the north of Lorestan prov-ince, and this area is the main agricultural center dependent on evaporation and temperature. Therefore, accurate modeling of daily evaporation at this station is necessary to increase the efficiency of agricultural practices and water management. The present study aims to estimate daily evaporation using wavelet neural network and artificial neural network. The wavelet neural network is able to divide the signal into high and low frequencies, and the low-pass and high-pass signals decomposed from the wavelet have suitable sinusoidal equations, so that the accuracy increases with the increase in resolution. Low-pass frequencies are more noisy, but the signal becomes smoother as the level of decomposition increases.Artificial neural network is widely used in hydrology studies and water resources management. The structure of neural network consists of input layer, hidden layer and output layer. The input layer is a tool for data prepara-tion. The output layer contains the values predicted by the network and the hidden layer or middle layer consists of processing nodes for data processing. The first application of artificial neural network was implemented using multilayer perceptron. Learning algorithms, back-propagation (BP) and feed-forward neural network with three-layer architecture are mostly used to solve complex engineering problems and predict hydrological time series. The criteria of coefficient of determination, root mean square error and Nash Sutcliffe coefficient were used to evaluate the accuracy and compare the performance of the models.

In order to estimate the rate of evaporation of Kakarza station, wavelet neural network model with different number of neurons was used. In the wavelet neural model, the appropriate wavelet (simlet) was first selected. Then by applying the transformation on the data, the approximation coefficients and their details were extracted and the data are transformed by the Mexican hat wavelet function as the activation function which is the second derivative of the Gaussian function. To train the network, the gradient descent algorithm was used, which is used in learning neural networks and minimizing the amount of error and adjusting the network parameter.Also, artificial neural network model of multi-layer perceptron network with hidden layers with different num-ber of neurons has been used. Hyperbolic tangent function is the most common form of stimulus function, which was used in this research toconstruct the output layer of artificial neural networks. Training of multi-layer perceptron networks using back propagation training algorithm called Lunberg-Marquardt algorithm was used due to faster convergence in network training.The results showed that both models can simulate the daily evaporation rate for the studied area, so that both models perform well according to the observed values. Also, the results showed that both models perform better in the combined structure consisting of all input data. Overall, the results showed that the wavelet neural net-work model showed high accuracy and less error in estimating the daily evaporation rate.

In this research, it was tried to evaluate the effectiveness of artificial neural network and wavelet neural network models to simulate the daily evaporation rate of Kakarza synoptic station located in the north of Lorestan province using daily data during the years 2013 to 2023. The results showed that the increase of the parameter It causes better efficiency in estimating daily evaporation rate. It was observed that the wavelet neural network model provided better results through signal decomposition and discontinuous performance compared to the artificial neural network. As a result, the wavelet neural network model well estimated the air temperature during 10 statistical years in this study and its results can help to improve water resources and agriculture.

The Zangezur Corridor, connecting the self-governing Republic of Nakhchivan to the mainland of the Republic of Azerbaijan, aims to disrupt the geopolitical balance in the Caucasus region in favor of Azerbaijan and Turkey, while placing Armenia and Iran under geopolitical pressure and threats. Various speculations exist regarding the construction methods, transit points, and the location of this corridor, leading to interventions by Russia, France, and at times, the United States. The potential exploitation of this corridor is expected to bring about significant transformations in both regional and transregional relations, possibly leading to the emergence of new crises and shifts in alignment among regional countries, ultimately reshaping the entire face of the region. This paper explores the factors influencing the involvement of different actors in this project, the interests they seek to gain from their interventions, and the impact the Zangezur Corridor has on the geopolitical dynamics of the region and the relationships between regional countries.The research method employed in this article is the Causal research method. Findings indicate that the strategic position of the Caucasus, its proximity to Russia, and the normative ties of regional countries with Azerbaijan and Armenia have prompted both regional and transregional actors to engage in this issue to pursue their respective interests and leverage their capabilities.

River flow prediction is one of the key issues in the management and planning of water resources, in particular the adoption of proper decisions in the event of floods and droughts. To predict the flow rate of rivers, various approaches have been introduced in hydrology, the most important of which are the intelligent models. In this study, a hybrid, model Firefly Algorithm- support vector machine, was applied to estimate the discharge of Dez river basin based on the daily discharge statistics provided by the hydrometric stations located at the upstream of the dam during the statistical period (2002-2022) and its performance was compared with the support vector machine model. The correlation coefficients, root mean square error, and mean absolute error was used for evaluation and a comparison of the performance of models. The results showed that the hybrid structures presented acceptable outcomes in the modeling of river discharge. A comparison of models also showed that the hybrid model of Firefly Algorithm-support vector machine has a better performance in forecasting the flow. In conclusion, the use of the FA-SVM model could be effective in estimating flood peak discharge.

The industrialization of societies has led to a rise in the emission of greenhouse gases in recent years. Such a rise causes global warming and, in turn, affects other components of the climate system, leading to certain climatic events that are fundamentally different from the natural course of climatic events, called climate change . According to the IPCC in 2007, the process of climate change and global warming have a significant impact on various systems such as water resources, agriculture, drinking, and industry such that the continuous increase in greenhouse gas emissions will intensify these effects, causing a warmer climate. Climate change represents the changes in precipitation pattern, snowmelt, and access to drinking water and agriculture . Groundwater resources are susceptible to both climate changes through (A) direct interaction with surface water sources such as rivers and lakes and (B) indirect interaction via the feeding process . Climate change indirectly affects the discharge and storage of groundwater by changing the nutritional conditions induced by rainfall and runoff; therefore, identifying and analyzing effective parameters such as climatic parameters can greatly help predict serious hazards threatening groundwater resources such as subsidence and drought. Moreover, considering that the relationship between climatic parameters and groundwater resources is complex and non-linear, the application of artificial intelligence models including modern hybrid models is a good solution to solving these problems. Therefore, the objective of this study is to analyze and predict climatic parameters using general atmospheric circulation models in coming years and groundwater level forecasting in Khorramabad plain using integrated vector regression model with the help of Wavelet Transform (WT) and modern optimization algorithms such as creative rifle and grey wolf optimizer. The basis of climatic parameters is the groundwater level and abstraction from the aquifer.

it is necessary to provide a solution and make proper forecasting of groundwater resources in order to prevent subsidence and drought phenomena around the world and in Iran. Therefore, in Iran, Khorramabad plain located in Lorestan province, which is very important in terms of drinking and agriculture whose products in this plain feed on groundwater for growth and development, has been subjected to illegal harvesting and digging of illegal wells. The level of groundwater resources has declined sharply in recent years. Therefore, groundwater level changes are more than necessary for forecasting and management measures to improve it.In this study, in order to simulate and predict the groundwater level of Khorramabad plain, the climatic parameters affecting the groundwater level were studied first according to the general circulation models of the atmosphere. In addition, the support vector regression model approach was used to predict the surface water level, assuming that the amount of groundwater abstraction from the Khorramabad plain was consistent with that in the previous statistical period. Since the SVR model is subject to errors according to recent findings, the strategy of optimizing the adjustment parameters using meta-heuristic algorithms was adopted to reduce the model error. To facilitate the groundwater level simulation, new meta-heuristic algorithms with WSVR support vector wave regression model, having acceptable performance according to several studies, were used. This approach can ensure taking an effective step in simulating and predicting groundwater levels.Based on the structure of the SVR, the most basic step is to determine the tuning parameters. The coefficients of these parameters are usually determined through trial and error in SVR. Many factors affect the viability of trial and error and the accuracy ofmodel prediction. Given the nature of trial and error, the predictive power may be generally reduced. Numerous solutions have been proposed by various researchers to address this fundamental weakness. One of these solutions adopted by researchers is to calculate the coefficients of parameter adjustment and optimize these coefficients by using meta-heuristic algorithms. A meta-initiative is the general framework of an algorithm that can provide solutions to the same problem with minor variations of various problems. There are many meta-heuristic algorithms such as Genetic Algorithm, Forbidden Search Simulation, Ant Society, Particle Swarm, Differential Evolution, Harmony Search, Artificial Bee Society, Firefly, Cuckoo or Coco, Frog Leap, Invasive Weed, and Competition, in addition to spirals, pollen, gray wolves, social spiders, ant lions, whales, locusts, and so on. Therefore, to optimize the adjustment coefficients in SVR, this study has employed new optimization algorithms including creative rifle and black widow spider, presented in 2021, for the first time in hydrology and water issues.

In this study, upon using climate change modeling, meteorological parameters (temperature and precipitation) for the years 2021-2040 were predicted and, then, by using ultra-exploratory hybrid models such as WSVR, AIG-SVR, and BWO-SVR, the groundwater level decline in Khorramabad plain located in Iran was predicted with the help of rainfall, temperature and harvest parameters associated with the four piezometric aquifers (Sarab Pardeh, Sali, Pol baba, and Naservand). Evaluation of LARS-WG model using baseline data (1990-2014) demonstrated that this model had a good performance in predicting meteorological parameters. The simulated temperature in all of the climatic models (EC-EARTH, GFDL-CM3, HADGEM2, MIROC4, and MPI-ESM) under the RCP85 emission scenario in the future time period (2021-2040) experienced an increase, compared to the base period in all months, while the average rainfall did not follow a definite trend. According to the statistical time periods of 2000-2020, WSVR, AIG-SVR, and BWO-SVR hybrid models in the combined structure including all input parameters had better performance due to higher memory, and WSVR model was more accurate with less error due to

Therefore, due to the decline in groundwater levels over the next 20 years, it is recommended that smart meters be installed on all agricultural and industrial wells and the drilling of illegal wells be prevented. In addition, the owners of agricultural wells need to be informed and notified of the dangers associated with the cultivation of hydrophilic crops. This strategy is useful and facilitates the development and implementation of groundwater management strategies and it is a step forward towards management decisions to improve the quantity of groundwater resources.

The anti Zandiqeh movement has been a prevalent issue in Iran's political culture throughout history due to the intertwining of religion and politics. However, their applications have varied in each period. During the Qajar era, their applications underwent a transformation due to the clash between tradition and modernity. The question is how did the circumstances of the new era, particularly the influence of European modernity on religious and political reformists, affected the transformation of Zandiqeh? The hypothesis is that in religious-dominated societies like Iran, the applications of Zandiqeh undergo changes in accordance with the requirements of each era. This article seeks to analyze the actions of certain fanatic traditionalists and extremist reformists who, by polarizing society, contributed to the spread of Zandiqeh. Data collection for this article is based on library research and analytical methods. According to the findings, the transformation of Zandiqeh during the Qajar era was influenced not only by religious concerns but also by the cultural and religious conditions of society and personal motives.

Coastal areas represent the most vulnerable regions of the ocean. Thus, the identification and estimation of sedimentation rates in the sensitive coastal habitats of Qeshm and Lark islands were conducted during 2022-2023. The diving team identified three habitats consisting of natural structures in the north of Larak Island, characterized by the predominance of Acropora sp., and one habitat featuring flora and fauna originating from human-made structures (Doha Qeshm Jetty). These habitats, resembling those on Larak Island but on a smaller scale, were mapped using ArcGIS software 10.1. Three sediment traps were placed at 500-meter intervals in each station to cover each habitat comprehensively. The minimum and maximum sedimentation rates were measured at Larak Islands (St3) with 28 and Doha Qeshm Jetty with 196 (g/m2/day), respectively. Additionally, the minimum and maximum concentrations of suspended substances in the water column, ranging from 9.44 to 21.31 (mg/lit), were observed at these two stations during autumn. The freshness of Acropora sp. served as an indicator in all four habitats, potentially reflecting either the negligible impact of sedimentation rates on communities or the resilience of these communities to sedimentation during the study period

Due to their descent from Prophet Muhammad, Sayyids have been highly respected by the public since the advent of Islam and have enjoyed a special status. The fall of the Abbasid Caliphate and the Mongol rule created an atmosphere of religious free thinking across the Islamic world, allowing sects, Sufi orders and intellectual currents to freely propagate their ideas. Sayyids also benefited from this freedom, and some prominent families got the chance to enter politics and establish small, local governments like Mar'ashis. Apart from the states founded by Sayyids, Timur and his successors had great respect for Sayyids, appointing them to high positions in the administrative structure of the Timurid state. Owing to their social status and noble lineage, Sayyids played a mediatory role between the ruling elite as superordinates and the masses as subordinates. This mediatory function and their mutual respect by superordinates and subordinates allowed them to be socially and politically active, and serve as the sole refuge of the public in times of crisis like wars. Therefore, this study aims to investigate the role of Sayyids in the Timurid era as an intermediary group between the ruling and ruled classes. The research question is how Sayyids functioned as mediators between the ruling class and commoners under Timurid rule,

The present study was conducted in order to obtain the necessary information on the diversity, abundance and distribution of macroinvertebrates, as well as to investigate the grazing status of batoid fishes (stingrays) from benthic macroinvertebrtes in coastal waters of Hormozgan province. For this purpose, sampling was done in the years 2017 and 2018 and once every year in the autumn season. At the end of the identification process, a number of 125 genus and 104 species belonging to 85 families, 31 classes, 9 orders, and 7 phyla were successfully identified. Results revealed that Malacostraca was the frequent order in the studied area. In order to investigate the possible relationship between composition and abundance of benthic macroinvertebrte and stingrays, CCA analysis was employed. Results of stomach content of stingrays revealed that in the diet of M. randall, crustacean (93.25 %IRI) has the highest amount. This pattern was the same for M. gerrardi and H. walga. However, in M. gerrardi, bivalvia were in the first place of importance (31.33 %IRI). Also, trophic level analysis was done for three species which shows all species are Mesopredators that place in the same level of food web. According to the mentioned cases, some benthic macroinvertebrates identified in this research have a significant  relationship with the benthic fishes, which requires more studies to investigate their relationship.

Akbar Shah as the greatest Mughal king of India, in order to complete his policy of free thinking and religious tolerance in the multi-religious and multi-ethnic society of India, he ordered prominent works of Hindu, Christian, Buddhist and other religions in the fields of religious, historical and literary to be translated into Persian language. In this way, during his period, a translation movement was launched in which Iranians living in India played a prominent role, so that Iranian elites, translators and poets can be considered the main pioneers of this translation movement.The purpose of this article is to study the role of Iranian elites in the scientific-literary movement of Akbar Shah's era, and accordingly, the main question of the research is, in which fields and disciplines did Iranian elites play a role in the scientific-literary movement of Akbar Shah's era?The findings of the research show that the Iranians living in India were not only the promoters of science and literature in the period of Akbar and the subsequent Mughal rulers, but also greatly helped the growth, expansion and deepening of the Persian language in India. The research method in this article is the descriptive-analytical method and the method of collecting information is the library method.

 The issue of Turkish-Israel relations is a significant topic in regional studies. Since the establishment of diplomatic relations in 1949, bilateral relations between Turkey and Israel have witnessed substantial growth and development in various fields. As two powerful players in the Middle East and the Mediterranean, the developments in the Mediterranean region have a crucial impact on their future relations. This research aims to investigate how the developments in the Mediterranean Sea will affect the future of Turkish-Israeli relations. The research hypothesis suggests that although Ankara and Tel Aviv share common interests and threats in the Mediterranean, these factors may limit their cooperation in the future. To evaluate the impact of Mediterranean developments on their relationship, the study employs the explanatory capacities of regional security theory, which identifies the influencing components as the main factors of a security complex. Additionally, this research uses future studies to examine the connection between Turkish-Israeli relations and the developments in the Mediterranean Sea. The results indicate that based on their shared interests and threats, Turkey and Israel seek to establish cooperative relations.

Standing biomass of coral fish was estimated by the Underwater Visual Census method(UVCm) and belt transect in five stations (St.) (dead corals, continuous and developed reefs, discrete and undeveloped reefs, Acropora spp. in small amounts and rocky reefs), in Larak Island from Sep.2020 to Apr.2021seasonally.The maximum and minimum of standing biomass was estimated  908.79 (Kg/Km2) and 235.85 (Kg/Km2) in the Abbas St. and Arabha St. respectively, also the maximum of coral fish standing biomass belonged to Scarus ghobban with 703.99 (Kg/Km2). The maximum of average (standard deviation) was estimated for the Jetty St.(Kg/Km2)16.36(± 4.3) (Feb.2021), and the lowest value at Ghail St. 1.4 (± 1.96) (Kg/Km2)(Sep.2020), also confidence interval of these estimations from bootstrapping simulations (n=2000) was calculated(95%). The results of one-way analysis of variance, Tukey's test, comparing the standing biomass of coral-fish (temporal and spatial analyses), was concluded differences in the most of seasons and stations (P<0.05), and the highest of standing biomass belongs to cold seasons of the year(Oct.2020, Feb.2021) and the lowest of them in the warm seasons(Sep.2020, Apr.2021) is estimated. The study of coral fishes showed although the bleaching event in the Persian Gulf has destroyed the habitat of coral fishes, but the dead corals are covered with microalgae, rocks, developed reefs and a few colonies of living corals (Acropora spp.) at depths above 10 meters have been able to play the role of their habitat. Furthermore, the type of substrate cover, the integrity of evolution reefs, being sheltered from waves and winds, and being away from sources of stress have influenced more than the size of the habitat on the coral-fish stocks of the Hengam Island.

In this research, the frequency of coral fishes from Hengam Island were studied seasonally from summer of 2020 to the spring of 2021 by Underwater Visual Census (UVCm) and belt transect method. A total of 38 species were identified in five selected stations, of which 31 species were herbivorous fishes,  Pomacentridae and Labridae families had the highest frequency with 7 and 4 species. The abundance of herbivorous fish Thalassoma lunare was estimated at 80(±71) number per square kilometer in station two. In addition, two species of parrotfish (Scarus persicus and Scarus ghobban) were the most frequent in all stations. The highest seasonal frequency of herbivorous fishes was recorded at station 2 in winter 58(±12) numbers per square kilometer and the lowest at station 3 in summer 5(±21) numbers per square kilometer. The seasonal abundance of herbivorous fishes were significantly differ between stations, except in summer (p<0.05). The temporal and spatial changes in the abundance of herbivorous fish in the stations indicate the importance of selective performance of fishes for ecological niche. In this regard, the role of functional redundancy is more effective than the role of functional complement among these fishes in the biological future of the coral communities of Hengam Island. Therefore, it is recommended to protect the coral fish stock of the island.

Estimation of coral fishes biomass is needed as a basic benchmark for assessing the ecological status and fishing potential of coral reefs. Different methods are used to sampling the biomass of these communities, that direct observation is one of the preferred methods with respect to the non-destructive advantage. The purpose of investigation was to estimation standing biomass of coral fishes by Underwater Visual Census method (UVCm) in Abu-Musa Island seasonally from October 2019 to September 2020. also confidence interval was calculated of these estimations from the bootstrapping test (95%). Standing biomass of Coral fish and their confidence interval (95%) by bootstrapping simulation (n=479) were determinated 2923.6 kg., 4576.2 kg, and 1645.4 kg for the stations one, two and three respectively. The difference in the biomass standing of coral fish in three station could be related to the lack of differences in the amount of developed reefs, coral communities and significant differences in habitat availability.  Also, the standing biomass of coral fishes in the Abu-Musa Island are limited, that can be attributed to their low habitat, shortage of carrying capacity and the short life of the Persian Gulf basin, and stress that occurs in the ecosystem, especially bleaching events, that need more study in the future.

To eliminate the defects of merely systematic materialistic attitudes, one can refer to the divine systematic thinking and benefit from the transcendental teachings of Islam. Non-linear thinking and dynamic view of phenomena and consequences is the neglected point of managers' decisions in businesses and commercial and non-commercial organizations. The employees of the organization always seek to know the results of their performance and are interested in monitoring their performance changes. In all the organizations of the world, managers and organizational leaders seek to improve and improve the performance of their organizations. Organizational performance is an indicator that measures how an organization or institution achieves its goals. With the aim of investigating and evaluating organizational performance through systemic thinking, this article reviews the viewpoints of managerial and organizational performance evaluation criteria, indicators and types of performance evaluation models. The results showed that the design and selection of performance evaluation indicators is one of the basic phases in the design of the organizational performance management system. In the performance evaluation process, the organization excellence model (EFQM) is a self-evaluation process and a comprehensive systematic method to identify the organization's strengths and improvement points. As a result, the organization compares itself with the best in the world or national class.

In this paper, dynamic modeling of a soft micro robot equipped with shape memory alloy (SMA) actuator is presented. Due to the structure of the soft micro robots, these robots have various applications. Since the shape memory alloys have features such that biocompatibility, high power, small dimensions and working silently, they are suitable for the micro robots. Because there is not a dynamic model for the soft robots equipped with shape memory alloy, here a dynamic model of a micro robot equipped with SMA is introduced. To this end, the motion equations of the robot and actuator’s structural equations are extracted. In dynamic modeling of the soft robot, Cosserat theory is used and Liang and Roger’s model is used for the SMA modeling. Also, modeling of free and forced convection heat transfer in the heating and cooling processes has been done. Then, the dynamic behavior of the micro robot is simulated and its electrical current effect and fluid velocity on the robot's dynamic behavior have been investigated. The simulation results show that the proposed model simulates correctly the behavior of the micro robot.

The phenomenon of the exploitation of groundwater recently has caused a sharp decline in groundwater levels, resulting in both subsidence and desertification caused by the groundwater withdrawal. Thus, reliable prediction of groundwater level has been an important component in sustainable water resources management. In this study, a data-driven prediction wavelet neural network model (WNN) was proposed for groundwater level in Azna-Aligodarz, Dourod-Brojerd, Delfan, Selseleh plain forecasting, and the results were compared with the artificial neural network. Parameters including precipitation, temperature, flow rate and water level balance during the period of the previous month were used as input of the model and level of the water table in each period as the output of the model through monthly scale (2002-2019) were selected. The criterion of the correlation coefficient, Root-Mean-Square-Error and average absolute error and coefficient of Nash Sutcliff for evaluating and the comparison of performance models were used.  The results of the hydrograph analysis indicated that the increase of rainfall has an effect on groundwater resources, and also the findings evaluation of criteria showed that WNN has better performance and less error than the artificial neural network.

Although the Safavids took over the administrative structure of the previous governments, due to the small and big changes that took place, they also made changes in this structure. Among these changes was the creation of a new position in the military affairs of Khorasan province and the surrounding lands called the post of Khorasan commander. This position was added to other military positions during the Shah Safi period, and by the end of the Safavid rule, a large part of the large-scale military affairs were organized through it. This geography included different areas of Khorasan (Herat, Merv and Mashhad) as well as more or less the surrounding lands such as Astarabad, Kandahar and Sistan. In the present article, the author has tried to answer the question: what were the backgrounds of the establishment of the post of Khorasan commander, as well as its performance, changes and developments? This research was done using a descriptive-analytical method. The data was collected examining the available historical sources. The findings indicate that the Khorasan commander is the result of a sense of the need to show a unified and coordinated response initially to the invasions and attacks of the Uzbeks and then other ethnic groups such as the Gurkhanids, Baluchis and Afghans. It has also been in line with the policy of increasing central government influence in the state affairs. This was done by appointing one of the elders, who was generally affiliated with the court, to head the army and send him to Khorasan, depending on factors such as the power and authority of the kings and his concern for the affairs of Khorasan. In periods such as Shah Suleiman and a part of the reign of Shah Sultan Hussein, this position has been severely weakened. Also, it has undergone changes in its history, including the combination between the commander and the state, and has continued until the last years of the Safavid rule (the fall of Isfahan) and even after that.

Flood is one of the natural phenomena that causes a lot of human and financial losses in the world every year and creates many problems for the economic and social development of countries. Therefore, in order to reduce the damage, control and guidance of this phenomenon, estimating flood discharge and identifying the factors affecting it is very important. In this study, in order to estimate the flood discharge of Kashkan catchment located in Lorestan province, new hybrid artificial intelligence models including artificial neural network - innovative gunner, artificial neural network - black widow spider and artificial neural network - chicken crowding during the period 1300-1400 were used. To evaluate the simulation performance, statistical indices of determination coefficient (R2), absolute mean error (MAE), Nash-Sutcliffe productivity coefficient (NSE), bias percentage (PBIAS) were used. The results showed that hybrid artificial intelligence models improve the performance of the single model. The results showed that the artificial neural network- innovative gunner model has more accuracy and less error than other models. Overall, the results showed that the use of hybrid artificial intelligence models is effective in estimating flood discharge and can be considered as a suitable and rapid solution in water resources management.