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During the last two decades, some international treaties have played a decisive role in facilitating scientific collaboration between member countries. For this reason, this study aims to predict the effect of Iran’s membership in these treaties on three things: first, the amount of scientific collaboration between Iran and the members of each treaty; second, the total amount of Iran’s international scientific collaboration; third, the extent of Iran’s dependence on scientific collaboration with the USA as the most key actor in the international scientific collaboration network. According to the background, the treaties that have a significant impact on international scientific collaboration are G7, G20, EU, OECD, OPEC, APEC, and BRICS. This study is based on the simulation method (with an agent-based modeling approach). This method was used to simulate the network of scientific collaboration between independent countries with more than one million people in the period of 2023-2042. The secondary data required for the simulation were collected from the Web of Science database and the United Nations database. Hypotheses related to possible scenarios were tested based on difference-in-difference statistical model. All calculations, including network simulation and hypothesis testing, were performed in the R software environment. The findings showed that Iran’s joining G20, OECD, and APEC will significantly increase Iran’s scientific collaboration with the members of each treaty. However, Iran’s membership in the BRICS will not have a significant effect on its collaboration with the BRICS members. Also, Iran’s joining each of these four treaties will significantly increase the total amount of Iran’s international scientific collaboration. However, the increase in the G20 scenario is higher, and in the BRICS scenario is lower than other treaties. At the same time, Iran’s membership in G20 and BRICS will lead to a significant increase in Iran’s dependence on collaboration with the USA. In return, Iran’s membership in OECD and APEC will play a significant role in reducing Iran’s dependence on collaboration with the USA. Another advantage of Iran’s membership in the OECD is strengthening its collaboration with two of the key players in Europe (France and Italy). One of the side benefits of Iran’s joining APEC is the significant increase in its collaboration with the key player in East Asia (China). The results indicated that Iran’s joining OECD and APEC will help to increase Iran’s visibility in the international scientific collaboration network and reduce Iran’s dependence on collaboration with the USA. [ABSTRACT FROM AUTHOR]

In this study, the accuracy of the Adaptive Network-Based Fuzzy Inference System (ANFIS) in integrating with the Gray Wolf Algorithm (ANFIS-GWO) in predicting groundwater level was evaluated for the first time using unpublished observational data from 1998 to 2018 in the Zarandieh aquifer, central Iran. Three observational wells were randomly selected for analysis. Assessment of evaluation criteria demonstrated that among the proposed scenarios using the hybrid model, the D scenario was selected as the optimal scenario with input data including the previous month's groundwater level, precipitation, temperature, and groundwater extraction. In the D scenario, parameters including MAPE, RMSE, and NASH were 0.29 m, 0.47 m, and 0.99, respectively for the first observational well. Also, C scenario with input data including the previous month's groundwater level, precipitation, and groundwater extraction for the second observational well, for the same parameters mentioned above equal to 0.20 m, 0.26 m, and 0.99. As well for the third observational well, the A scenario with input data including the previous month's groundwater level for the same parameters equal to 0.29 m, 0.41 m, and 0.99 as the optimal scenarios were selected using the ANFIS-GWO model. Based on the results, the Gray wolf algorithm in training the ANFIS model was able to reduce the average forecast error by equal to 0.03 (RMSE) and 0.02 (MAPE) meter and increased the average NASH value equal to 0.01 and increased the accuracy of predictions. [ABSTRACT FROM AUTHOR]

The aim of the study was to determine the most important environmental factors (topography, climate, and soil) affecting changes in production and canopy cover of plant variations and to prepare prediction maps, based on the most important factor, in semi-steppe rangelands of Hir-Baghrou, Ardabil province, Iran. First, by detecting the vegetation types and different classes of environmental factors, the production and canopy cover were estimated in 1-m2 plots at full flower stage of dominant species. Then, to determine the most important environmental factors, affecting the production and canopy cover changes, the principal component analysis (PCA) was used. For modeling, first, the correlation between the most effective environmental factors was obtained from the PCA. Then, the highly correlated factors were eliminated and the quadratic polynomial models were obtained. Finally, the obtained models were simulated in GIS. The results of the PCA showed that the first six components with 71.65% had the greatest effect on the production and canopy cover changes. Based on the root mean squared error (RMSE), simulating maps of production (RMSE=0.76) and canopy cover (RMSE=0.48) by effective factor (annual precipitation) showed the highest accuracy. The results of this study can be used to manage the rangelands of Ardabil province to create a balance between supply and demand of production and also to balance carbon. [ABSTRACT FROM AUTHOR]

Cooling and heating energy accounts for a significant portion of the total energy consumption in residential sector. Building envelope is exposed to sunlight and outside air and therefore have a significant role in determining the thermal loads of buildings. Meanwhile, roofs which are exposed to sunlight all the day long are important envelope components and have a significant share of buildings energy consumption. Therefore, applying appropriate roof solutions can significantly reduce building energy consumption for air-conditioning and improve indoor comfort conditions. This paper aims to investigate the effect of different roofing techniques on thermal performance of a single-storey residential building with two types of uninsulated and insulated configurations under different climatic conditions of Iran. For this purpose, different cool roof albedos 0.5, 0.7, and 0.9 and two types of green roofs, GR with actual local rainfall and wet GR, are considered. The thermal loads of the buildings are calculated using the DesignBuilder software and compared with a conventional cast concrete roof. The results show that by choosing an appropriate type of roof technique, the total air-conditioning energy requirement of the building can be reduced between 7-31%, depending on the building configuration and climatic condition. [ABSTRACT FROM AUTHOR]

Purpose: The problem of wheat production sustainability is an important issue that quarantines the availability of people's food at present as well as the nutrition of the next generations. Food is the essential human's need and has been used from human beings' creation until the end of its life. The existence of systems satisfying such requirements and the sustainability of them is always essential for the survival of the human race. Therefore, this study aims to investigate the sustainability of the wheat production system in Iran. Design/methodology/approach: In this research, using the system dynamics approach, the sustainability of Iran's wheat production has been studied. The literature review section of this paper concentrates on several research papers in this context, considering the systems dynamics approach. In this study, an introduction has been expressed to the human's need for food and the position of wheat as the primary source of food in meeting this need in Iran. System dynamics is one of the most commonly used approaches for modeling and simulating environmental and socio-economic phenomena. The wheat production system covering environmental, economic, and social subsystems has been taken into consideration as a case to model the problem. Key factors affecting wheat production have been collected based on a literature review. 50 years historical data for essential factors such as rain, wheat harvesting area, agricultural technology, fertilizers, population, wheat imports, and exports have been used in modeling and hence in the mathematical formulation of the problem. Based on the history of these factors and related research, the dynamic hypothesis of the problem has been defined, and the causal diagrams of the relationships between critical factors and the wheat production have been developed. After modeling and formulation, the problem has been simulated and validated. Then, various scenarios have been proposed and simulated for the sustainability of the wheat production system, and the results have been addressed. The scenarios for changing the machinery level, reducing chemical fertilizer's use, increasing organic fertilizer use, and rainfall fluctuations have been simulated one by one, and their combinations have been simulated, respectively. Findings: The simulation results indicated that the production of wheat is highly sensitive to precipitation and technology levels in the field. Therefore, it is better to focus more on such two factors and to have more concentration on them. Since water is the most crucial resource in wheat production, it would be better to concentrate the research and development efforts on water management technologies in the field. Due to the high sensitivity of wheat production to precipitation fluctuations and technology levels, more investment and better plans should be provided for the better and more efficient use of the two sources. Research limitations/implications: While numerous factors such as pesticides, seeds, planting and harvesting, irrigation methods, management, human resources, and related requirements affect wheat production, due to the large scale of this research, only the most critical factors were selected for the study. Examining the behavior of each of the above-mentioned factors will result in a better awareness of the existing reality and better planning for wheat production. Practical implications: The wheat production system includes environmental, economic, and social subsystems as well as numerous and complex relationships between the human and the environment. The systemic nature of such interdependencies and interactions needs systematic approaches and integrated assessment tools. Identifying and modeling correctly the intrinsic characteristics of the wheat production system assure preserves or increases its essential results over the time and help governmental organizations and institutes to move towards sustainable development and to set policies that encourage positive changes. Social implications: Since the proposed model is expected to help the government and agricultural institutions in planning wheat production efficiently, it will make the country move towards selfsufficiency in wheat production, which in turn results in psychological and social security in terms of food and increases social sustainability. Originality/value: To the best knowledge of the authors, there is no comprehensive investigation on the sustainability of wheat production in Iran. The literature review indicates that the agricultural context is almost limited to a particular zone and this problem has not been addressed on the national scale. Thus, this is the first research that examines such a problem. [ABSTRACT FROM AUTHOR]

Strategies to enhance local adaptation capacity are needed to mitigate climate change impacts and to maintain regional stability of food production. The objectives of this study were to simulate the climate change effects on phenology stages, potato production in the future and to explore the possibilities of employing planting dates and various varieties (Agria, Arinda and Santeh) as mitigating options to decrease the climate change impacts on potato production in Feridonshahr, Isfahan province, Central Iran. For this purpose, we employed two types of General Circulation Models ((United Kingdom Met. Office Hadley Center: HadCM3) and (Institute Pierre Simon Laplace: IPCM4)) and three scenarios (A1B, A2 and B1) for three time periods of 2030, 2060 and 2090. LARS-WG was used to produce daily climatic parameters as one stochastic growing season for each projection period and SUBSTOR-Potato model was used to simulate potato growth. Time period from cultivation until flowering and tuber yield were reduced in a majority of the climate change scenarios. Simulation results indicated that delayed planting (5 June) alleviated the harmful effects of climate change by improving tuber yield, while early planting (5 May) in both GCMs and under all scenarios reduced tuber yield compared with the conventional planting date. Arinda (early maturing), Sante and Agria (conventional maturing) varieties had higher tuber yield in all scenarios. Selecting 5 June and Arinda as the planting date and variety of choice will alleviate negative effects of climate change and seem to be the most appropriate approach of cultural management in the studied region. [ABSTRACT FROM AUTHOR]

The history of Iran's economy after the revolution has been in recession for some years and, with the 70s, this trend has deepened, and with the 1990s it seems that the real GDP trend is making serious changes. In this paper, the markov chain monte carlo and byesian approach are used to simulate the effects of factors affecting the economic recession in iran during the years 1979-1357. The results show that the Bayesian approach confirm the results of the model estimation using the Monte Carlo Markov chain approach, and at a reliable level, 97.5% of the coefficients of the variables are statistically significant and reliable. so, the most influential variables were estimated on the economic recession in Iran, exchange rate changes, crude oil prices, and real GDP. The results also show that the matrix of bayes factors for all pairings of models is reliable. The later probabilities of regimes and the likelihood ratio indicate that the change points in the sixth model are different with the rest of the models, so the regime change is happening in the sixth model. [ABSTRACT FROM AUTHOR]

Introduction: Simulation is a version of some real tools or work situations that tries to exhibit some behavioral features of an abstract or physical system through behavior of another system. The main purpose of application of simulation in health care is preparing students to confront with clinical situations which can increase patients' safety, decrease errors and refine nurses' clinical judgments. This approach decreases so much complications of learning which exist in real world. By this method, students gain the opportunity of learning skills which in real world there is little possibility to gain them. Simulators are planned in a way that can show reaction against wrong actions of students and assist in correcting actions with proper feedback. Conclusion: Simulation leads to change in learner's view, preparedness of learner to learn new roles and will also help learners towards understanding professional roles, exhibiting effective roles, and will increase learners' interest and motivation and create critical thinking processes in learners. [ABSTRACT FROM AUTHOR]