Search

Introduction Drying is one of the oldest methods of food preservation. To increase the efficiency of heat and mass transfer while maintaining product quality, the study of the drying process is crucial scientifically and meticulously. It is possible to conduct experimental tests, trial and error, in the drying process. However, this approach consumes time and cost, with a significant amount of energy resources. By harnessing available software and leveraging technological advancement to develop a general model for drying food under varying initial conditions, the drying process can be significantly optimized. Materials and Methods This study was conducted with the aim of simulating heat and mass transfer during Refractance window drying for aloe vera gel. Comsol Multiphysics version 5.6 is a three-dimensional model used to solve heat and mass transfer equations. For this purpose, the differential equations of heat and mass transfer were solved simultaneously and interdependently. The above model considered various initial conditions: water temperature of 60, 70, 80, and 90°C, and aloe vera gel thickness of 5 and 10 mm. The initial humidity and temperature of the aloe vera is uniform. The initial temperature is 4° and the initial humidity of the fresh aloe vera sample is 110 gwater/gdry matter. Heat is supplied only by hot water from the bottom surface of the product. Results and Discussion The drying time was needed to reduce the moisture content of aloe vera gel from 110 to 0.1 gwater/gdry matter during Refractance window drying. Aloe vera gel with a thickness of 5 mm dried in 120, 100, 70, and 50 minutes at water temperatures of 60, 70, 80, and 90°, respectively. For a 10 mm thick layer of aloe vera gel, the drying time was 240, 190, 150, and 120 minutes, for water temperatures of 60 to 90°, respectively. These results demonstrate the importance of both the water temperature and thickness on the drying time. Furthermore, the drying rate of aloe vera gel increased as the water temperature increased from 60 to 90°, the drying rates were 0.915, 1.099, 1.57, and 2.198 gwater/min for 5 mm thickness and 0.457, 0.578, 0.732, and 0.915 gwater/min for 10 mm thick layer of aloe vera gel, respectively. Conclusion Based on the simulation results, the optimal model is with a water temperature of 90° and an aloe vera gel thickness of 5 mm. Overall, the modeling results are consistent with the results of experimental data. [ABSTRACT FROM AUTHOR]

Background and Aim: Operating room students have experienced anxiety for various reasons that affect their educational process such as stitching. Due to the effective role of simulation in improving the education of students, this study was conducted with the aim of the effect of animal skin suturing simulation on the skill level and anxiety level of operating room students. Materials and Methods: In this study, 30 people (75%) of the samples were aged 18-25 and 10 people (25%) of them were 26-35. 10 people (25%) were men and 30 people (75%) were women. Also, in terms of marriage, 7 people (17.5%) were married and 33 people (82.5%) were single. The present quasi-experimental study was performed with a two-group plan before and after with 40 operating room students of Shahrekord University of Medical Sciences (Shahrekord, Broujen) in 2020. The samples were randomly assigned to two test and control groups using the method based on the purpose of selection. Data were collected before and after the intervention by Spielberger Anxiety Tool and Suturing Skills Questionnaire and analyzed by SPSS software and descriptive and analytical statistical tests (Chi-square test, t-test, paired t-test). Results: The t-test test showed that the mean of obvious anxiety in the intervention group (36.35±10.22) and the control group (41.15±7.92) after the intervention was not significant (P=0.346). Also, the mean hidden anxiety in the intervention group (36.65±10.47) and the control group (38.65±6.13) had no significant difference (P=0.089). The t-test test showed that there was a significant difference in sewing skills after the intervention in the two intervention groups (28.2±58.22) and the control group (23.42±3.12) (P=0.04). Conclusion: The texture of suture mannequins is very different from human skin in terms of consistency, and it does not convey the same feeling of sutures on natural skin to students. On the other hand, it is easier to enter and exit and move the needle and thread in the sheepskin, and this provides the students with the possibility of stitching more easily. Therefore, it is suggested to buy and prepare sheep skin for training students and teach them stitches on it. [ABSTRACT FROM AUTHOR]

Background and Objectives: Agriculture is one of the most important economic activities highly dependent on climatic conditions more than any other factors. Climate change significantly affects crop production. Due to the limitation in production factors, inputs, climatic and geographic properties of different provinces, identification of the comparative advantage of crops is essential. Lack of knowledge about comparative advantage would lead to improper and non-optimal use of resources. Therefore, knowledge about comparative advantage in different regions is useful to plan and exploit the resources. The present study was conducted to identify the comparative advantage of some important rainfed winter crops. Materials and Methods: In the agronomic section of this study, the yield of rainfed crops including wheat, barley, chickpea and lentil in Ardabil, Fars and Khorasan Razavi provinces were simulated using the SSM-iCrop2 model. Long-term meteorological data were used to decrease climatic fluctuations and more precise estimation. Economic evaluations were performed using policy analysis matrix (PAM), domestic resource cost (DRC) and social cost-benefit index (SCB) methods. Also, nominal protection coefficient (NPC), effective protection of crops (EPC) and nominal protection input (NPI) were measured. In the agronomic section of this study, the yield of each region was simulated according to the climatic conditions and using the SSM-iCrop2 model (to determine the production potential of each region). For this purpose, long-term weather data were used and simulation was done for a 30-year period from 1986 to 2015. Under the moderate production conditions (moderate agronomic management or unsuitable climatic conditions), 50 percent of the yield potential, and under the optimum production conditions (optimum agronomic management or good climatic conditions), 70 percent of the potential yield is attainable. Therefore, 50 and 70 percent of yield potential were simulated using the SSM-iCrop2 model and their effect on comparative advantage and social profit were investigated. Results: The results indicate that according to the DRC index, Ardabil in wheat, chickpea and lentil production, Khorasan Razavi in chickpea and lentil and Fars in chickpea production have a comparative advantage. Based on the SCB index, the production of wheat in Ardabil, chickpea in all three provinces and lentil in Ardabil and Khorasan Razavi provinces have social profit. According to the results, increase yield leads to improved comparative advantage and social profit so that all three provinces will have social profit in crop production (rainfed, wheat, barley, chickpea and lentil) provided that the farmers attain at least 50 percent of the yield potential (exploitable yield). According to the results of the simulation, Fars and Ardabil had the highest exploitable yield in wheat production, and regarding barley, chickpea and lentil, the highest exploitable yield was related to Ardabil province. Based on the actual yields, only Ardabil province had high yields and was superior to other provinces in terms of the economic indices. Conclusion: Wheat, barley, chickpea and lentil crops had higher yield in Ardabil province due to the suitable climatic conditions of this region. One of the reasons for the advantage of crop production in Ardabil is its higher yield which has increased the income of growers compared with the other two provinces, and production of rainfed crops in this province has led to benefits. [ABSTRACT FROM AUTHOR]

Introduction As a result of droughts and human interventions, the Urmia Lake basin has faced increasing unallowable withdrawal of water resources and environmental requirements share. Over the past two decades, a series of natural and human factors have gradually changed the water balance of Lake Urmia. In addition, decreases in precipitation have been the main reason for the gap between water resources and increasing water consumption in the basin, especially in the agricultural sector. In order to deal with the Urmia Lake catastrophe, a working group was formed for the Urmia Lake restoration. The working group planned and proposed solutions to reach the ecological level of the lake in three stages within 10 years through in-basin water supply and inter-basin water transfer programs. The present research, while investigating the solutions for providing the environmental water requirement of Lake Urmia using the Analytic Hierarchy Process (AHP) method, changes in the water volume of Lake Urmia in the scenarios of water transfer from the surface flow of each entering river in the lake in the years of high intensity severe to mild drought, the implementation of the approvals of the national working group to restore Urmia Lake, including a 40% reduction in agricultural consumption from the sources of dams and other rivers without dams, releasing water from dams in non-agricultural seasons, transferring water from urban wastewater and finally transferring water between the Zab basin has quantitatively been evaluated using the MODSIM simulation model. This research will help to predict the amount of transferable water in drought, normal, and drought conditions and to plan the water accounting of the Urmia catchment. Materials and Methods The watershed of Lake Urmia, located in the northwest of Iran, with an area of 51,876 square kilometers, is one of the six main watersheds of the country, which is located between the provinces of West Azerbaijan, East Azerbaijan, and Kurdistan. In terms of its territorial location, the catchment area of the Zab Kochak river is in the western part of the international border with Iraq and in the catchment area of the Western Border River basin. A significant part of the Zab watershed (source of water transfer) is located outside the country and in Iraq. The route of water transfer between the basins of the Zab basin is from the place of two dams, Silweh and Kaniseeb, which after entering the Godarchai river will eventually enter the Urmia lake water body. The different solutions from the working group’s approval have been selected for developing six scenarios. Then, the Scenarios have been evaluated by the MODSIM model and AHP analysis method. The scenarios are including reducing agricultural expenses from dams in operation, saving by reducing agricultural expenses from other rivers, transferring water between basins, transferring effluent to Lake Urmia, releasing water from dams in operation to Lake Urmia. A hierarchical structure was developed with the aim of evaluating solutions to save Lake Urmia through internal sources and transfer water sources. In this structure, there are four criteria of climate, consumption, economic-social, and environmental status. Sub-criteria of drought, surface water extraction from rivers, extraction from dam sources, extraction from groundwater resources, development of agricultural lands, and ensuring the sustainability of river flow. and providing solutions for inter-basin water transfer, a 40% reduction of agricultural water consumption from surface water sources of rivers and dams, wastewater transfer, and a 40% reduction of agricultural water consumption from underground water sources in Expert Choice software, were analyzed. Results and Discussion In order to evaluate the effectiveness of the defined scenarios, the simulation model was implemented for future conditions during the next 10 or 15 water years for different scenarios. The results show that the implementation of scenarios 4 and 6, will bring the largest increase in the volume of lake water, of course, with the occurrence of precipitation and proper input. Regarding the results of scenario 1 and the sameness of its results in two periods of 10 and 15 years, it can be stated because in the definition of the scenario, it is a dry year and the amount of evaporation of the lake water is more than the amount of input into the lake. There has been no increase in the lake's water volume for several consecutive years. Also, the results show that in wet and dry years, if the maximum transfer flow scenario is implemented, we will not have a flow from the Zab river to the downstream side, and it will not be accepted from the hydrodiplomacy point of view for the neighboring country in terms of influencing the use of the Dukan dam. Therefore, water diplomacy solutions are needed to reduce environmental threats. Therefore, the issue of transferring water from the Zab basin to Lake Urmia cannot be considered guaranteed in the long term due to the impossibility of reducing the outflow of water from the country to zero. Conclusion In conclusion, in order to evaluate all scenarios to satisfy the environmental needs of Lake Urmia shows that the protection of the lake requires correcting the mistakes of the path traveled in the current and past years, and preferably with a 40% reduction in agricultural consumption from dams and other rivers, groundwater in the basin is the main supplier of Urmia Lake. Inter-basin water transfer is the next priority because the source catchment is able to transfer water in the face of droughts due to the reduction of runoff and related challenges as well as its negative economic and social effects. It will not be as much as predicted and included in the program (600 million cubic meters per year). In addition to that, water diplomacy is necessary in terms of impacting downstream transboundary uses and reducing environmental threats. The results of this research and the high costs of water supply requirements, in parallel with the investigation of controversial options and costs of interbasin water transfer projects, macro-management of water resources towards demand and consumption management and water saving programs and the modification of water consumption patterns and the legality of the behavior of water users from within the catchment area of Lake Urmia should be low-cost, sustainable and reliable solutions. [ABSTRACT FROM AUTHOR]

Background and objectives: A new dimension in agricultural science has been opened up by the rapid development of computer-based information systems. Physiological processes of plant growth and development can be represented mathematically with a plant simulation model. Many studies have used simulation models to quantitatively analyze the effects of different environmental and management factors on the processes of agricultural plants due to the capability to simulate different processes. Since there is limited data on the ability of CERES-Maize to simulate maize under different nitrogen management treatments in Mazandaran, On the basis of graphical representations and statistical analyses of CERES-Maize performance and physiological traits, the model was recalibrated in Qaemshahr. Material and methods: In order to simulate the physiological traits of maize using CERES-Maize model in different nitrogen treatments, an experiment was carried out in Qarakhil, a research farm in Mazandaran Agricultural Research Center, during 2017 and 2018 as randomized completely block design in four replications. The 10 treatments used in this research included: N1: not use of nitrogen (control), N2: use of 60 kg n ha-1 before planting, N3: use of 120 kg n ha-1 before planting, N4: use of 180 kg n ha-1 before planting, N5: Use of 60 kg n ha-1 in two stages (50% before planting + 50% in stage R1), N6: Use of 120 kg n ha-1 in two stages (50% before planting + 50% in R1), N7: use 180 kg n ha-1 in two stages (50% before planting + 50% in R1), N8: 60 kg n ha-1 in 3 stages (one third before planting + one third in stage R1 + one third in stage R3), N9: 120 kg n ha-1 in 3 stages (one third before planting + one third in stage R1 + one third in stage R3), N10: 180 kg n ha-1 in 3 stages ( One third was before planting + one third at R1 stage + one third at R3 stage). Results: It was shown that the model had an acceptable accuracy in simulating the yield, biomass and nitrogen level of a shoot at harvest time. It has also been shown that the trait model does not accurately simulate the leaf area index as well as other traits. According to linear regression analysis, R2 coefficients for the calibration and validation data of the model were 0.69 and 0.57, respectively,. Model validation showed a coefficient of explanation of 0.81, while calibration showed a coefficient of explanation of 0.79. Based on the two-year data, the simulated nitrogen value does not differ significantly from the measured value at 0.95 probability level. The model provided a 0.87 explanation coefficient for the difference between simulated and measured shoot nitrogen, thus indicating its accuracy in simulating total shoot nitrogen over the two-year period. Conclusion: As a result of this research, the highest yield was achieved in the years 2017 and 2018 with 120 kg n ha-1 applied to the soil as 50% of the base + 50% in R1 stage. In view of the obtained results, the CERES-Maize model can be used as a suitable simulation model to find the optimal nitrogen fertilizer management strategy for maize. For generalizable results, this model can also be applied to interpreting climate data in the northern region of the country in terms of potential production, limitations, and reduction of long-term field experiments. [ABSTRACT FROM AUTHOR]

Awareness of water resources status is essential for the proper management of resources and planning for the future due to the occurrence of climate change in most parts of the world and its impact on different parts of the water cycle. Hence, many studies have been carried out in different regions to analyze the effects of climate change on the hydrological process in the coming periods. The present study examined the effects of climate change on surface runoff using the Atmosphere-Ocean General Circulation Model (AOGCM) in Khomeini Shahr City. The maximum and minimum temperatures and precipitation of the upcoming period (2020-2049) were simulated using a weighted average of three models for each of the minimum and maximum temperatures and precipitation parameters based on the scenario A2 and B1 (pessimistic and optimistic states, respectively) of the AOGCM-AR4 models. The LARS-WG model was also used to measure the downscaling. The HEC-HMS was used to predict runoff. The effects of climate change in the coming period (2020-2049) compared with the observation period (1971-2000), in the A2 scenario, the minimum and maximum temperatures would increase by 1.1 and 1.6 Degrees Celsius, respectively, and the precipitation would decrease 17.8 percent. In the B1 scenario, the minimum and maximum temperatures would increase by 1.1 and 1.4 degrees Celsius, respectively, and the precipitation would decrease by 13 percent. The results of runoff were different in the six scenarios in the way the most runoff reduction is related to the scenario of fixed land use and scenario A2 (22.2% reduction), and the most increase is related to the scenario of 45% urban growth and scenario B1 (5.8% increase). So, according to increase urban texture in the future and consequently enhance the volume of runoff, this volume of runoff can be used to feed groundwater, irrigate gardens, and green space in the city. [ABSTRACT FROM AUTHOR]

Background and Objectives: In order to identify the possibility of supplying food to the world's population, given the need for continued production in sustainable agriculture, it is necessary to correctly predict the yield of crops. For this purpose, modeling of growth stages and yield of rice based on meteorological statistics of Iran, was studied in Gorgan University of Agricultural Sciences and Natural Resources. The purpose of this study was to use the simple model SSM-iCrop2 to simulate rice growth and yield to investigate the effects of climatic factors, soil, agronomic management and to determine the genetic coefficients of rice in Iran. Due to the appropriate ability of the model in rice simulation, it can be used as a suitable tool for better planning and management of rice fields in the country. Materials and Methods: In this study, the SSM-iCrop2 model was used to simulate the potential yield. In this model, the amount of potential yield is calculated based on meteorological data, soil conditions, management and plant parameters. The model needs a series of inputs to run, which is made to perform the simulation of the collected model. The most important processes to be simulated in the model are plant phenology, leaf area changes, dry matter production and distribution, and soil water balance. For parameterization and evaluation of the model, the values of performance and day to maturity of the simulated were compared with those observed. According to the statistics of the Ministry of Agriculture, 2001-2016, the main areas of rice cultivation and production in Iran were identified. In this study, to compare the deviation of the simulated values from the observed squared error mean (RMSE), coefficient of variation (CV), correlation coefficient (r) and the deviation of the simulated results from line 1:1 with a range of 20% difference. Between the simulated and observed values was used to test the model results. Results: In parameterization of SSM-iCrop2 model for rice, the comparison of observed and simulated days to maturity with RMSE, CV and r values of respectively 12 days, 11 percent and 0.61, respectively, and for grain yield of 56 g m-2, 21 percent and 0.80 indicated the accuracy of the used parameters. Furthermore, in evaluation the model, RMSE, CV and r values for days to maturity were 9 days, 10 percent and 0.95 and for grain yield were 43 g m-2, 14 percent and 0.77 and in simulation evapotranspiration were 44 mm, 9 percent and 0.79 respectively, which confirms the precision of the model simulation. Application of SSM-iCrop2 model is simple and acceptably precise simulation is possible with minimal parameters and inputs. Conclusion: The results of parameterization and evaluation of SSM-iCrop2 model, which was (RMSE), (r) and (CV), showed that this model includes phenological stages and grain yield in the history of different plantings in the climatic conditions of Iran simulates with great accuracy, which indicates the appropriate structure of the model in the simulation. Therefore, considering the appropriate accuracy of SSM-iCrop2 model in simulating rice phenology and yield, it can be used as a suitable tool to study cropping systems and interpret the results in different environmental and management conditions to plan and improve the management of rice fields in the country. [ABSTRACT FROM AUTHOR]

Background and objectives: Among the types of heat exchangers, shell and tube heat exchangers are the most common heat exchange equipment. The energy efficiency of a heat exchanger can be increased by improving the heat transfer properties. Nanofluids are a Colloidal suspension of nanoparticles are in a base fluid.The nanoparticles used in nanofluids are usually made of metals, oxides, carbides, or carbon nanotubes. The heat transfer rate is affected by the thermophysical properties of the nanofluid, which increases with the increasing volume of nanoparticles in the base fluid. Nanofluid properties are affected by nanoparticle concentration, purity level, and variable structure. The main purpose of this paper is to provide an overview of the use of nanofluids in shell and tube heat exchangers to increase heat transfer coefficients and simulate the parameters affecting the flow and heat transfer to predict temperature distribution, velocity, and pressure drop in different parts of the heat exchanger. Material and methods: In this study, Camsol multiphysicas simulation software version 6 was used to build a computational model of shell and tube heat exchanger to simulate temperature, velocity, and pressure drop changes in the heat exchanger. Hot nanofluid (353.15 ° K) enters the tube and water (298.15 ° K) enters the shell. The role of geometry parameters used on heat transfer rate has been investigated and presented. The temperature and total heat transfer characteristics of the pipe wall are calculated and designed for theoretical, experimental, and numerical methods using the K- ɛ heat transfer model. Results: By performing a computational fluid dynamics study, and calculating the desired values of each of the studied parameters, a good agreement was obtained between the computational fluid dynamics study and experimental results. The results of temperature, velocity, and pressure drop counters show that the addition of nanoparticles to the fluid can effectively increase the thermal conductivity of the fluid the temperature of the added nanoparticles are directly related to the thermal conductivity ratio. The velocity changes in the shell are very small and in most areas of the shell, the speed according to numerical calculations and according to the colored guide bar is about 0.05 meters per second, but at the points of collision of the current with the baffles and inlet and outlet values are different and between 0.15 to 0.2 meters. Is seconds. From the numerical results, it can be seen that the velocity values in the vicinity of the walls are very low, which is due to the strong friction gradient. Examining the temperature-related contours, it can be seen that the heat transfer is not uniform throughout the length of the exchanger and the decrease in temperature in the direction of flow is visible. Conclusion: The use of alumina nanoparticles in the base fluid by 4% increased the average output temperature by 0.9 degrees in a passing cycle of the system, which increases more and more with the repetition of this cycle. According to the pressure drop contour, the pressure drop of nanofluids is much higher than the base fluid and the pressure drop increases with increasing the concentration of nanofluid. [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 current research was performed to present a quick and proper method for basin irrigation infiltration equation estimation by optimization of the Manning roughness coefficient. A two-level optimization of the Manning roughness coefficient method was presented by developing a zimod simulation model and initial intake families method, USDA-NRCS, (infiltration equation based on soil characteristics), and modified intake families (infiltration equation based on soil characteristics and inflow discharge). The investigation of the results of the model based on observed advance, recession, and surface storage showed the relative error of surface storage volume estimation was decreased by 38 to 50 % by adjusting the initial intake families method. The normalized root mean square error (NRMSE) of the advance estimation was between 0.22 to 0.85 for initial intake families and this parameter was between 0.09 to 0.5 for modified intake families. NRMSE of the recession estimation was between 0.13 to 0.75 for initial intake families and this parameter was between 0.09 to 0.19 for modified intake families. The presented method based on modified intake families increases the accuracy of infiltration estimation as compared to the initial intake families method and can evaluate basin irrigation acceptably. In addition, this method needs less time for basin irrigation evaluation as compared to the complete methods of optimization of infiltration parameters and roughness coefficient. [ABSTRACT FROM AUTHOR]

Introduction: Nurses' sensitivity to ethical issues and their way of reasoning at the bedside is one of the professional principles in nursing that needs special attention. Therefore, the current research was conducted with the aim of determining the effect of the narrative method on the reasoning and moral sensitivity of nursing students through simulation. Materials and Methods: The present research is a clinical trial on 60 undergraduate students in the field of nursing who were divided into 2 intervention and control groups by throwing dice. Demographic questionnaires, Kohlberg's moral reasoning and Latzen's moral sensitivity were completed for data collection in 3 times before and after the intervention and one month later. The intervention was conducted during 4 sessions of 3 hours based on 10 narrated scenarios, with the theme of ethical challenges in nursing and 2 sessions in the form of expressing students' experiences, in the clinical environment. The data were analyzed by SPSS version 16 software and using chi-square, Fisher's exact and ANOVA statistical tests. Results: The results of the study showed that the group had no significant difference before the intervention and were harmonious in terms of demographic variables, the level of reasoning and moral sensitivity. After the intervention, the moral reasoning of the control group was 39.23±6.88 and the intervention was 49.03±7.55, which showed a significant difference between the two groups at P<0.001, which indicated that there is a significant difference in the follow-up. Moral sensitivity after the intervention was 32.56±24.03 in the control group and 84.36±14.14 in the intervention group, with P<0.001, a significant difference was observed between the two groups. Conclusion: Storytelling through simulation can be an effective method to increase the sensitivity and moral reasoning of nursing students. Therefore, the results showed that the evolution in ethics education methods will increase the moral capabilities of nursing students. [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]

The relationship between man and nature and its importance in the urban environment is one of the issues considered by theorists and planners in the field of urban space for a long time. However, human beings as the basis for this relationship have jeopardizing this vital interaction by making changes in cities for some time now. One of the significanr in human communication and the redidence in cities is his satisfaction by climate conditions. The outdoor thermal comfort is affected by the built environment, land cover, plant evapotranspiration, and other factors present at the site. In this study, among the ways of promoting thermal comfort in urban space, the use of plants is focused on. In this article, the effects of plants on temperature and relative humidity were firstly analyzed in a case study. Then, using Envi-met software, an existing urban block was simulated by placing hypothetical trees and another hypothetical block was simulated as well. According to the results, the air temperature in the places, which were very close to the nearly 50-cm plants, was obtained to be almost 0.5◦C lower than other places. In addition, the relative humidity within the studied limits was higher. Therefore, the effects of these two factors on improving the thermal comfort of urban microclimates, especially in hot seasons, could be well evidenced. The assessment of different types of plants also showed that the temperature adjustment could be achieved regardless of plant type. [ABSTRACT FROM AUTHOR]

Introduction: Educating students in a safe environment such as simulated centers can be effective in providing educational services and preparation for clinical work. Accordingly, the present study was conducted with the aim of designing, implementing and evaluating clinical pharmacology simulation training method for nursing students. Methods: This study was performed in 2019-2021 in three main phases of design, implementation and evaluation of Pharmaceutical Skills Center in Clinical Skills Center of Tehran School of Nursing and Midwifery. First, the design phase was accomplished by preparing the space and the desired drugs. Due to the prevalence of Covid-19 disease, part of the implementation and evaluation phase was carried out in the virtual context. Before and after the internship, students' knowledge, skills, satisfaction and clinical reasoning were measured using relevant questionnaires and analyzed using descriptive and analytical statistics. Result: The mean scores of the three variables in terms of pharmacology knowledge, drug calculation skills and clinical reasoning of pharmacology of nursing students before and after the internship were examined. The results demonstrated that all three means were significantly improved compared to that of before the intervention (P <0.001 and P = 0.001). The mean of total students' satisfaction with pharmacology internship course turned out to be 30.57 (3.2), which indicated the relative satisfaction with the training course. Conclusion: In general, the results of the study indicated an improvement at the level of pharmacological knowledge, clinical reasoning of pharmacology and a significant improvement in pharmacological skills. Despite the limitations of Covid 19, this training method seems to augment the performance of nursing students in pharmacology. [ABSTRACT FROM AUTHOR]

At present, the occurrence of dust storms is one of the most important environmental problems in Khuzestan Province, and the south and southeast regions of Ahwaz have been recognized as one of the interior dust sources and are the priority of corrective operations. Given that land use change is one of the desertification factors in the mentioned region, therefore, modeling its changes is necessary and provides useful information for planners to control and revive the degraded lands. The objective of this study was to evaluate the efficiency of the CA-Markov model in predicting land use changes in the dust source of south and southeast of Ahwaz based on two long-term and short-term approaches. In the long-term approach, land use maps of 1986 and 2002 years and in the short-term approach, land use maps of 2002 and 2007 years have been used to predict land use for the year 2016 and then the simulation results were validated. The results showed that the values of allocation error, quantity error, and kappa coefficient for the long-term approach were 42.55%, 13.95%, and 0.08 respectively, and for the short-term approach were 12.56%, 10.42%, and 0.22 respectively, which indicates the weak ability of the CA-Markov model to evaluate the desertification trend in the dust Source of south and southeast Ahwaz. Use of uniform transition rule throughout the simulation period without considering the factors and processes affecting land use change, the non-same trend of land use change during study periods, changes due to human activities, drought, and long forecast period can be the reasons for the poor performance of the CA-Markov model to predict the desertification trend the dust Source of south and southeast Ahwaz. [ABSTRACT FROM AUTHOR]

Thunderstorms often appear with a strong, energetic and short-term air flow. These types of storm are caused by the ascent of hot and humid air in an unstable atmosphere and can lead to heavy rainfall if there is sufficient moisture, and otherwise they will lead to a dust storm. The purpose of this study was to investigate the storms in Khuzestan province, which usually experiences gusty winds, and convective storm events during spring and early summer. With regard to the frequent occurrence of dust storms in Khuzestan in recent years, it has become ever more important to study the convective storms. In order to identify the storm events in Khuzestan, Ahvaz station was selected due to much longer record of data and more accurate information than other stations in the province. A statistical analysis has been carried out on the long-term data of Ahvaz synoptic station between 1981 and 2016. After a thorough analysis of the long-term data, five cases of severe convective storms were selected. The cases include the 16th of October 1981 (case 1), the 27th of August 1985 (case 2), the 18th of December 1985 (case 3), the 24th of April 1992 (case 4) and the 8th of May 2000 (case 5). Finally, the characteristics of the cases were determined by numerical simulations using the Weather Research and Forecasting (WRF) model. The simulations were performed using four nested domains D1 to D4 with horizontal resolutions of 81, 27, 9 and 3km, respectively. The NCEP/NCAR reanalysis data were used for the boundary and initial conditions. Statistical analysis shows a decrease in the intensity and frequency of occurrences of the convective storms with maximum wind speed of greater than 12m/s during the 36-year period. Monthly analysis reveals that the most (least) frequent severe convective storms occur in April (October). Another important finding is that the severe convective storms occur mainly in spring and in the interval between 12UTC and 15UTC. From the early hours of the day until 13:00 UTC, the percentage of events increases, and then until the end hours of the day, the percentage of events decreases as the surface heating is maximized in the afternoon. The low frequency of occurrence in autumn and winter is due to reduced surface heating as a result of reduced solar energy received from the sun. The results of numerical simulations demonstrate that the position of the maximum wind speed is different in the considered cases. The comparison of the results of simulation of the selected cases with observational data shows that the model of simulated storm has a time delay of about 1 to 3 hours with respect to the actual storm occurred in the area. Tracking the storms from 30 min before to 30 min after the occurrence of the maximum wind speed along the path in the fourth domain of the model points out that the cases 1 to 3 evolve in the northeast and the cases 4 and 5 evolve in the northwest of Ahvaz station. [ABSTRACT FROM AUTHOR]

In the present study, a convective heat transfer coefficient (h) changes during deep fat frying was investigated. So, by keeping the oil temperature constant as a heat transfer medium, temperature changes in a potato strip (cube-shaped), in the center and left-right sides of the strip during frying by a three-channel thermocouple was measured. Processing temperature of oil was 150, 160 and 170°C. The strip temperature was recorded by a data logger at ten-second intervals. Due to no significant changes in the temperature of different selected locations in potato strip, the center temperature was selected and recorded as an effective temperature. Also, heat transfer parameter included convective coefficient (h) was calculated in the range of 128_515 W/m².K .Result showed that (h) is high in high levels temperature because of increasing rate of moisture exiting and turbulence in the oil. Also, with increasing oil temperature, decreasing of oil content and decreasing in moisture content of slices were observed. The mass transfer parameters including the effective moisture diffusivity (Deff) and the oil diffusivity (Doil) were calculated in the range of 9.12×10-9 _1.31×10-8 m²/s and 1.26×10-5_1.52×10-5 m² /s, respectively. By using the calculated coefficients, heat and mass transfer modeling, was done by mathematical equations and the relevant equations were solved by the method of separation variables. Simulation was also done with COMSOL Multiphysics version 5.3a and the resulted profiles were also presented. [ABSTRACT FROM AUTHOR]

Due to drought and climate change, estimation and prediction of rainfall is quite important in various areas all over the world. In this study, a novel artificial intelligence (AI) technique (WGEP) was developed to model long-term rainfall (67 years period) in Anzali city for the first time. This model was combined using Wavelet Transform (WT) and Gene Expression Programming (GEP) model. Firstly, the most optimized member of wavelet families was chosen. Then, by analyzing the numerical models, the most accurate linking function and fitness function were selected for the GEP model. Next, using the autocorrelation function (ACF), the partial autocorrelation function (PACF) and different lags, 15 WGEP models were introduced. The GEP models were trained, tested and validated in 37, 20- and 10-years periods, respectively. Also, using sensitivity analysis, the superior model and the most effective lags for estimating long-term rainfall were identified. The superior model estimated the target function with high accuracy. For instance, correlation coefficient and scatter index for this model were 0.946 and 0.310, respectively. Additionally, lags 1, 2, 4 and 12 were proposed as the most effective lags for simulating rainfall using hybrid model. Furthermore, results of the superior hybrid model were compared with GEP model that the hybrid model had more accuracy. [ABSTRACT FROM AUTHOR]

Transplanting or pot culture has been mentioned as a promising approach to increase crop yield and decrease irrigation water use in recent years. Using simulation models to assess pot culture is a valuable way in investigating the effect on yield, water consumption and other properties of crops such as soybean. For this purpose, several pot culture levels (seedling sizes) plus direct sowing were evaluated in soybean using SSM-iCrop2 for four different sowing dates in Gorgan, Iran. Seedling sizes were 13, 18, 24 and 29 cm² per plant leaf area and at 200, 250, 300 and 350°C cumulative temperature, respectively. Sowing dates were June 10 (early), June 25 (usual), July 14 (late) and July 27 (very late). The results of simulation showed that direct seed planting method at late sowing date (14 July) and all treatments at very late sowing date (27 July) are not feasible and cannot be recommended due to disturbance that cause in sowing of next crop in double cropping system of the region. Transplanting method at early (10 June), usual (25 June) and late planting dates resulted in earlier maturity. There was no significant difference between two methods regarding seed yield at early and usual planting dates, but at late planting date transplanting method resulted in higher yield compared to direct seed planting method. Seedling size had no significant effect on yield. In addition, there was no significant difference among sowing methods in all planting dates in terms of net irrigation requirement of soybean. It was concluded that transplanting is only preferred at late sowing date for its higher yield, but considering the higher production costs of this method compared to direct sowing, it is necessary to find some cost-effective measures before pot culture could be adopted by farmers. [ABSTRACT FROM AUTHOR]

The construction of irrigation network and the water transfer from Karkheh Dam to Dashte-Abbas, due to neglecting the groundwater resources has increased groundwater level and waterlogging of the agricultural land in the recent years. The aim of this study was, therefore, to optimize the conjunctive use of surface and groundwater resources in DashteAbbas to minimize waterlogging problems and achieve the maximum net income. For this purpose, the behavior of groundwater was simulated using the system dynamics (SD) approach. The conjunctive use of surface and groundwater resources was then optimized using the Vensim multi-criteria optimization method with the objective function of maximizing the net income of the plain. The SD model calibration was done using climatic, hydrological, agricultural, and environmental data from the 2001-2009 time period; then it was validated based on the information from the 2009- 2016 period. Evaluation of the developed SD model showed that the model had high accuracy in simulating key variables such as groundwater levels (ME=60cm, R² =97%, RMSE=47cm) and groundwater salinity (RMSE=100μS/cm, R² =74%, and ME=123μS/cm). Furthermore, the results of the optimization model showed that the optimum use of surface and groundwater resources for the agricultural demand was 65% and 35%, respectively. To sum up, it could be concluded that with the optimization of the conjunctive use of surface and groundwater resource, s about 10 MCM of water consumption could be annually saved to irrigate almost 800 ha of the new lands. [ABSTRACT FROM AUTHOR]

Rainfall may be considered as the most important source of drinking water and watering land in different areas all over the world. Therefore, simulation and estimation of the hydrological phenomenon is of paramount importance. In this study, for the first time, the long-term rainfall in Rasht city was simulated using an optimum hybrid artificial intelligence (AI) model over a 62 year period from 1956 to 2017. The gene expression programming (GEP) and wavelet transform (WT) were combined to develop the hybrid AI model (WGEP). Firstly, the most effective lags of time series data were identified by means of the autocorrelation function (ACF); then eight various GEP and WGEP models were defined. Next, the GEP models were analyzed and the superior GEP model as well as the most influenced lags was detected. For instance, the variance accounting for (VAF), correlation coefficient (R) and scatter index (SI) for the superior GEP model was calculated to be 0.765, 0.508 and 0.709, respectively. Additionally, lags (t-1), (t-2), (t-3) and (t-12) were the most influenced. Then, the different mother wavelets were examined, indicating that the demy mother wavelet was the most optimal one. Moreover, analyzing the numerical simulations showed that the mother wavelet enhanced the performance of the GEP model significantly. For example, the VAF index for the superior WGEP model was increased almost three times after using the mother wavelet. Furthermore, the R and MARE statistical indices for the WGEP model were computed to be 0.935 and 0.862, respectively. [ABSTRACT FROM AUTHOR]

Purpose: One of the salient features of today's competitive world is the widespread use of Information Technology. E-business, which has grown significantly in recent years, has many benefits for organizations, customers and the community. The purpose of this study is to find the best policies to improve the demand response rate in online sales in e-business. In this study, the main variables of the study is identified, using system dynamics and the demand response rate is forecasted and described as the core variable. By creating a simulation model, different policies implemented, and the results and consequences of each are studied. Out of them, only those policies that guarantee the growth and success of the business, in reality, are selected. Design/methodology/approach: Using System Dynamics, the main variables of an online home food distribution system has been identified and their interrelationships created in the form of cause and effect loops and state-flow model. The data needed to simulate the system, obtained from interviews with business executives as well as internet search, and the model simulated using the Vensim software for 72 months. After validating the model using appropriate tests, to validate the model, the proposed policies implemented, and their results compared with the current performance of the system. For this purpose, SPSS software and paired comparison test used to analyze the data obtained from the simulation and to find the policy that made a significant difference at the 5% error level under conditions of the current system. Findings: The simulation results of the proposed policies indicated that it is possible to improve the demand response rate by holding training courses, increasing production to the extent of capacity, as well as combining these two policies. Findings also indicated that increasing the food prices and implementing advertising programs did not affect improving demand response rates. The statistical analysis resulted in an insignificant difference for the second policy at 95% confidence level. The third policy emphasized increasing the number of food produced to the production capacity. The results of this policy indicated a significant difference between this policy and the current system at the 5% error level. The fourth policy suggested an increase in the final price of food. There was a significant difference at the 5% error level. However, due to the value close to the significance level of 0.05, it was not suggested to implement the policy. The last policy implemented in the system was a combination of the first and third policies. At the 95% confidence level, the fifth policy was significantly different from the current state of the system. Research limitations/implications: Due to the large size of the model, variables such as revenue and profit entered into the system. The variables of food quality, customer's expected quality and customer's complaints removed from the model because they did not directly affect the behaviour of the main variables. Moreover, the variables of raw material prices and final food prices considered as average since it was not possible to enter different daily prices for more than 80 types of food. Practical implications: The proposed model helps managers to evaluate the results of their suggested policies efficiently before their implementation and to make effective policy. Making the first policy, i.e. holding a training course, has affected all of the three variables of demand response rate, production capacity and profitability, significantly; hence managers are advised to put significant emphasis on such policy. Also, increasing the production to the maximum capacity was associated with a slight increase in the studied variables; hence, making this policy was not recommended. Furthermore, the simultaneous implementation of the training course and equalization of the number of food produced with the production capacity, each of which alone significantly changes the behaviour of the main variables, and can significantly increase the demand response rate, production capacity and profitability. Therefore, it is a suitable choice for managers and decision-makers to combine and implement these two effective policies simultaneously. Originality/value: By the use of System Dynamics approach, the causal relationships between different variables of the internet business system transformed into a dynamic model and the interactions of variables over time simulated. In similar studies on simulated e-business by a system dynamics approach, the simultaneous impacts of the production, demand, sales, and investment subsystems have not investigated. [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]

Background and Aim Sicne in many dosimetry calculations, the water and soft tissue phantoms are used, this study aimed to investigate the difference of these two phantoms with a phantom consisted of realistic liver materials in proton therapy for liver cancer. Methods & Materials Three phantoms with different materials of water, soft tissue and realistic liver materials were used for the study. A spherical tumor with 2 cm radius was considered in the liver. The Spreadout Bragg Peaks (SOBPs) were measured to cover the complete tumor for the three phantoms. Dose distribution and deposited dose ratio in tumor and surrounding organs were calculated using Monte Carlo N-Particle Extended (MCNPX) code. Ethical Considerations The best proton energy interval to complete the coverage of tumor in the liver for phantoms with realistic and soft tissue materials was 90-120 MeV and for water phantom, it was 88-116 MeV. The shift of the Bragg peaks depth per energy in the water phantom mm relative to two other phantoms was about 4.5. The dose parameters were evaluated according to the International Commission on Radiation Units and Measurements (ICRU), and the results showed no any significant difference between them. The dose distribution in the tumor and surrounding organs showed that for all three phantoms, the dose distribution around the tumor was negligible. Results The use of soft tissue phantom has more acceptable results than water phantom in simulating treatment and can be replaced with realistic liver tissue. More realistic phantoms should be used in treatment plan. Conclusion The use of soft tissue phantom has more acceptable results than water phantom in simulating treatment and can be replaced with realistic liver tissue. More realistic phantoms should be used in treatment plan. [ABSTRACT FROM AUTHOR]

Forecasting maximum discharge of the basin requires accurate information on the amount, severity and distribution of precipitation. For prediction of maximum runoff of a basin using relationship of Q = 0.278 CiA, the rainfall intensity in the whole basin is considered constant. The amount of precipitation in different parts of a basin is obtained through interpolation methods. This method is known as duration-area. Because rainfall is a very variable parameter, probability of an unpredictable estimate of precipitation is high. In this study, using the radar data, the amount and severity of rainfall over the basin were obtained. (intensity-duration-area method). Basin concentration time lines were prepared in G.I.S. Software. Coordinates of environment and area of the curves were defined for radar and its implementation program was written in radar software. Then amount and severity of precipitation were estimated by the radar. Because volume was directly used, the relationship changed. The maximum runoff was simulated and compared with observation runoff. Maximum runoff was high in severe rainfall. If soils of basin were already wet, maximum runoff was high. Conditions were different in low rainfall. If the severity of the rainfall was low and then increased, the amount of runoff was more than expected. If the intensity was high and then decreased, the amount of runoff was lower. This was the result of the spatial and temporal dispersion of precipitation in maximum runoff. Time delay between maximum runoff and simulation in severe rainfall was short. And time lag in ordinary and low rainfall was long. Using a constant runoff coefficient does not estimate maximum runoff value accurately. Due to the characteristics of rainfall (intensity, amount, duration, spatial and temporal distribution) and soil moisture characteristics of the soil, various coefficients should be used. [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]

Lack of the proper conjunctive use of surface and groundwater resources causes large water stresses in one of these resources. Conjunctive use of surface and groundwater, especially in arid and semi-arid regions, is a scientific and practical solution for sustainable water resources management. The aim of this research was to prepare some mathematical modeling to apply the conjunctive use of surface and groundwater in the Dehloran plain aquifer. In this study, the mathematical model of the Dehloran plain aquifer was developed using GMS 9.1 and the river data were entered. For the steady state condition, the time series data in the average year 2010-2011 were utilized. In the next step, the time series data from October, 2010, to September, 2011, were used for the unsteady state analysis. In the unsteady state, four stress periods were taken; then the model calibration was carried out in three steps for each stress period; after the optimization of the hydrogeological parameters of the model, its verification was done for the period of 2011- 2012 period. After the calibration of the model in the unsteady state, the values of the mean error (ME), the mean absolute error (MAE) and the root mean squared (RMS) errors measured in piezometers were obtained to be -0.24, 0.46 and 0.65, respectively. The results of verification confirmed the ability of the model in simulating the natural conditions of the aquifer. Finally, applying different scenarios to the model showed that the proper conjunctive use of surface and groundwater could increase the volume of water at a rate of 2.23 million cubic meters per year. [ABSTRACT FROM AUTHOR]

Simulation of water and salt transfer in soil is very effective in managing optimal water and fertilizer use in the field. In this study, the HYDRUS-1D model was used to simulate the transfer of water and bromide in a laboratory column of soil with clay loam texture. Soil hydraulic parameters (including air entry point) α, (saturated hydraulic conductivity) ks, (residual moisture content) θr (saturation moisture content) θs, (pore and particle joint parameter) l (parameter of moisture curve shape) n through measurement and using Retc software was obtained Solubility transfer parameters including difiusion coefficient and actual velocity were estimated using soil hydraulic parameters and bromide concentration data by reverse modeling method. According to the target coefficients, the sensitivity analysis of the physical model was performed .The results showed that the correlation coefficient of observation and simulation bromide concentration in optimal mode was 0.84%. accordingly, the diffusion coefficient was estimated to be 4.9 cm. based on the results of the sensitivity analysis, the saturation hydraulic conductivity had the greatest effect on the variation of this parameter, so that the amount sensitivity coefficient of this parameter was 2.64 The RMSE coefficient with a value of 0.04 was the lowest and ME coefficient with the value of -0.0001 had the most parameter variations. [ABSTRACT FROM AUTHOR]

In the vast majority parts of the Earth, a prospect now visible is the mostly synthetic thinking and fabrication by the human hand. Collision and impact of humans on the natural environment in the short and long-term courses for obvious geographical features have changed a variety of spaces. One of the consequences of human impact on the natural environment during the current period is the phenomenon of climate change. One of the climatic parameters that plays an important role in agriculture, energy, urban, tourism and road transport is the minimum temperature. In this study, an attempt was made using the minimum temperature data from 5 meteorological stations in the West Mazandaran province, as well as HADCM3 model data, to show how to change this parameter in the future periods based on simulation by the SDSM model. Accordingly, after selection of the suitable climate variables and model calibration, the accuracy of the created model in the base period was evaluated; after ensuring the sufficient accuracy of the model according to A2 and B2 scenario, data minimum temperature in 2100 was simulated. Based on the simulation results showed that the values of minimum temperature in the region over the coming years would increase. This parameter was such that the average seasonal periods 2016 to 2039, 2040 to 2069 and 2070 to 2099, as compared to the baseline period would increase, on average, by 1.8, 3.5 and 6 percent. The largest increases in the minimum temperature in the western and southern parts of the region could occur. It was also found that unlike other months of the year, the minimum temperature in January would be a decreasing trend. [ABSTRACT FROM AUTHOR]

The use of knowledge integration framework will result in relating different individual ideas of learners and will lead to a collective idea about concept of a phenomena among learners. Using dynamic visualizations, learners will be able to view and test phenomena in the non-visible levels. So, this study was conducted with the aim of examining the effect of using dynamic visualizations and knowledge integration framework on chemistry learning of tenth grade high school female students. In this research, the pretest-posttest, quasi-experimental method with control group was used. Statistical Population consisted of all tenth grade high school female students in Tehran, using convenience sampling method, 34 students were selected as the sample and were randomly assigned into two experimental and control groups. Measuring the instrument was a researcher-made tool for measuring academic achievement in chemistry lesson consisted of 13 items designed to test the relationship between learners' ideas towards a concept and different levels of chemistry. Before starting the course, a pre-test was performed in both groups, dynamic visualizations and knowledge integration framework strategy was used in experimental group in six 60-minutes sessions while the control group were taught using traditional teaching method in five 60-minutes sessions. Post-test was conducted in both groups. Results of covariance analysis confirmed the effect of using knowledge integration framework and dynamic visualizations in comparison with the traditional teaching method and the difference between the experimental and control group in terms of chemistry performance after the posttest (F=41. 462, p<0.0001). Findings showed that the group which has been taught using the dynamic visualizations and knowledge integration framework, established a better relationship between different levels of chemical reactions. In addition, the use of knowledge integration framework helped students to have a common understanding toward concepts of phenomena and systematically understand the connections between different ideas in a phenomenon. [ABSTRACT FROM AUTHOR]

Climate modeling is one of the fundamental methods of simplifying the complexity of the climate that can increase our understanding of the system’s behavior. Climate simulating through using the outputs of general circulation models in order to be aware of the characteristics of the climate, will be required in the coming years. The achievements of general circulation models cannot be used directly in regional and smaller-scale climate simulations. A common way to solve this problem is by statistically downscaling the output of general circulation models. SDSM is one of the most practical models in the mentioned fields. In this study, attempts are made to assess the ability of the SDSM in downscaling and simulating the temperature data of Urmia since the beginning of 1961 until the end of 2010 using National Emergency Communications Plan’s re-analyzed data and the outputs of HadCM3 under A2 and B2 scenarios. To assess the adequacy of the models obtained and the SDSM’s ability to simulate, some statistical tests such as the Chow test, the standard error, Wilmot index compatibility and also monthly and annual diagrammed data have been used. The results of this study show that the greater the time period is, the more preferable and closer to reality the simulated mean temperature will be. However the SDSM model’s function is inadequate in simulating the maximums and minimums. Therefore the achievements of this model are suitable only to obtain a general understanding of the characteristics of future climate and they cannot be used in precise projects. [ABSTRACT FROM AUTHOR]

One of the factors leading to the contamination of water resources is human activity, producing waste materials. In this paper, the effects of contamination on the water quality of Taleghan River, was simulated using of Qual2k model and the seasonal changes were evaluated. The qualified data collected during two months, August (as the dry season) and February (as the wet season), were used in the modelling. The results showed that the dissolved oxygen change was in the range of 4.5-6.52 mg/L in August. However, it changed between 4.8-5.3 mg/l in February and this reduction in the wet season was due to the run off deposition and the seepages of farmland near the river. Furthermore, BOD in the wet season and the dry season changed by 6-31 and 10-26 mg/l, respectively. These changes were due to the sewage dilution in flow during the wet season. Evaluation of the pH values in wet and dry seasons also showed that water of the river was more alkaline in the wet season, which is due to the effect of non-point resources or the fertilizer entrance after farm land bleaching by rain. Evaluation of Taleghan river EC variation also showed these changes were not significant during the wet and dry seasons. Water temperature was altered by 3-10°C and 19-25°C, respectively, in February and August. [ABSTRACT FROM AUTHOR]

Rivers has long been regarded as one of the most basic human water supplies. If the topography, a morphology, water requirements conditions, etc. allow water to be transferred to gravity, the use of the dike can have a significant impact on the flow rate and the sediment input to Intake. Dike design needs to consider several parameters such as position, length, type, etc. Using a good design can increase the input flow rate and reduce the sediment entering it. In this study, to evaluate the dike impact on flow hydraulic conditions in the Intake with different situations, 30, 45, 60 and 90 degrees two simple L-shaped dikes in the upstream and downstream Intake and for five inlet flows (0.7, 1.12, 2.84, 5.04 and 6.23 Lit/s) were considered in the laboratory flume made by the author as a physical model to simulate the flow of the basin; then different effects of the dike on the hydraulic flow were studied. The results of the tests showed that the L-shaped dike in the upstream and downstream Intake in the internal arc flume increased the inflow flow rate into the Intake. Also, the best angle of deviation for the maximum flow entered the Intake angle of 60 degrees. [ABSTRACT FROM AUTHOR]

The simulation and prediction of pollutants dispersion entering into the atmosphere (such as material releases from the chimneys of industries and power plants) are important in different views, long-term environmental monitoring and dose calculations as well as issuing an appropriate warning in the event of an accident. To this end, a system of coupled meteorology-dispersion model can be used. In fact, a numerical weather prediction model is coupled to a dispersion model. In the present work, the weather research and forecasting (WRF) model is used to provide the meteorological data for the HYSPLIT (HYbrid Single Particle Lagrangian Integrated Trajectory) dispersion model. Sensitivity and validation of the WRF model are conducted by utilizing different combinations of physical parameterization schemes (microphysics, longwave radiation, shortwave radiation, surface layer, land surface, boundary layer and cumulus convection) for the prediction of meteorological parameters in an area containing the Bushehr power plant. For this purpose, eight different configurations are used. Then, for several dates, sensitivity, and validation of the model results is carried out to find the proper configuration of the model. Assessment of the predictions of the WRF model is carried out by computing the statistical parameters including correlation coefficient (CC), root mean square error (RMSE), and comparing with the collected observational data (on-site the meteorological tower and Sodar system in Bushehr power plant and synoptic meteorological stations nearby). After determining the proper configuration of the WRF model, dispersion simulations and annual effective dose for the adult age group are carried out by WRF-HYSPLIT coupled model under normal conditions for Bushehr power plant. The predicted annual effective dose for the adult age group by the coupled model for the years 2014, 2015 and 2016, provided 5.8×10-8 (Sv), 6.7×10-8 (Sv) and 1.1×10-7 (Sv) respectively, in return value 7.7×10-8 (Sv) for Bushehr power plant final safety analysis report (FSAR report). Comparing these results show that the simulation and prediction of dose by the coupled WRF-HYSPLIT model are in good agreement with observations and indicates the validity of the simulations. The ratio of predicted annual effective dose to dose limit for normal operation is obtained less than 0.2 percent (<0.2%), which shows that public annual exposure dose for normal operation of Bushehr power plant is negligible compared to the legal limit. The results of the present work showed that the coupled WRF-HYSPLIT model can be used as a promising tool for the prediction of dispersion and dose calculations for Bushehr power plant under normal operation. In addition, the results of this coupled model can provide the required information for emergency management to forecast the movement and direction of radioactive plume and exposure dose calculations. [ABSTRACT FROM AUTHOR]

Precipitation is one of the most important components of water balance in any region and the development of efficient models for estimating its spatiotemporal distribution is of considerable importance. The goal of the present research was to investigate the efficiency of the first order multiple-site auto regressive model in the estimation of spatiotemporal precipitation in Kurdistan, Iran. For this purpose, synoptic stations which had long time data were selected. To determine the model parameters, data covering 21 years r (1992-2012) were employed. These parameters were obtained by computing the lag zero and lag one correlation between the annual precipitation time series of stations. In this method, the region precipitation in a year (t) was estimated based on its precipitation in the previous year (t-1). To evaluate the model, annual precipitation in the studied area was estimated using the developed model for the years 2013 and 2014; then, the obtained data were compared with the observed data. The results showed that the used model had a suitable accuracy in estimating the annual precipitation in the studied area. The percentages of the model in estimating the region's annual precipitation for the years 2013 and 2014 was obtained to be 7.9% and 17.3%, respectively. Also, the correlation coefficient between the estimated and observed data was significant at the significance level of one percent (R=0.978). Furthermore, the model performance was suitable in terms of data generation; so the statistical properties of the generated and historical data were similar and their difference was not significant. Therefore, due to the suitable efficiency of the model in estimating and generating the annual precipitation, its application could be recommended to help the better management of water resources in the studied region. [ABSTRACT FROM AUTHOR]

The withdrawal Kanban system, by capability of data transferring in supply chain reduces different types of the waists such as inventories level and unnecessary movements. To achieve the aims of lean production, the parameters of the Kanban system such as the number of Kanban should be determined properly. The number of Kanban problem is a multi-objective problem which should met the aims of producers and suppliers simultaneously. In this paper, the objectives and constraints of withdrawal Kanban problem has been determined based on a case study in automobile supply chain. A mathematical integer multi-objective model with non-linear objects has been developed. Two sets of solutions are generated by the optimization model. A simulation model is developed to check the possibility and validity of solutions. The simulation studies show that one of the solutions can reduce up to 46 percent the inventory costs while increase 11 percent transportation costs compared to the current state. [ABSTRACT FROM AUTHOR]

In the single-mode resource-constrained project scheduling problem, it is assumed that each activity has a specified known execution time and resource consumption can be done only in one way. In practice, there are many cases in which the make span can be reduced by providing additional resources activities. In this case, each activity can be done in one of the procedures, which is called the multi-mode resource-constrained project scheduling. In this paper, the problem includes determination of the basic schedule for the project activities which may be done in several models and the precedence relations are met, While the project make-span, cost and resource fluctuations are minimal. In this research project scheduling problem network will model using ED simulation software and the results of the simulation and a meta-heuristic algorithm has been compared. Finally, management strategies to optimize the scheduling, i.e such minimize total time, cost and resource leveling, will be offered. [ABSTRACT FROM AUTHOR]

Computational intelligence techniques have a great potential to solve different computational problems in engineering sciences. In this paper, modeling and simulation of down hole drilling motor using the computational intelligence methods such as artificial neural network (ANN), radial basis function (RBF) and adaptive neuro-fuzzy inference system (ANFIS) is presented. Experimental data are used to train and test the proposed models. The results of the proposed models are compared with the experimental data. The predicated values are found to be in a good agreement with the experimental values. Also, they are very faster than the experimental measurement method. These compact models can reduce the computational time while keeping the accuracy of physics-based model and allow the fast and accurate system level simulation and modeling of industrial packages. Finally, using the proposed ANN model, which is the best proposed model, an equation to describe the nonlinear behavior of down hole drilling motor is introduced. [ABSTRACT FROM AUTHOR]

Increasing urban growth, increasing population growth and increasing urban migration have doubled the need for informed guidance and spatial organization. On the other hand, urban development prediction is essential for planning and providing the necessary facilities for the future growth of the city. The present study aims at evaluating the changes in the land of Chabahar during the years 1991 to 2014, then, predicting these changes until 2041. Research method is descriptive-analytic. Landsat satellite images for the years 1991, 2001, and 2015 have been analyzed. For data analysis, ARC & GIS, ENVI and IDRISI software were used. And the prediction of user variations until 2041, has been shown using CA and Markov chain models. Results of the prediction show that body expansion of the leads to the compression. From 1991 to 2001, an average of 43.5 hectares per year; and from 2001 to 2014 (during 13 years) 59.5 hectares of expansion are showed. And on the horizon of 2041 it will reach about 28.7 hectares per year. [ABSTRACT FROM AUTHOR]

Background and Aim: Modeling of organizational knowledge creation process is one of the key areas of research in knowledge management. The aim of this paper was to determine solutions for developing and improving evolutionary knowledge creation model based on the model validation results in real world. Materials and Methods: This study was an analytical and empirical research that was done by multi case study and simulation strategy. The committee was formed to collect information from various source of data including organizational documents and interview with senior managers about knowledge creation history for 5 years in Development and Planning Management department of Tehran University of Medical Sciences. Data analysis was done using descriptive statistics and qualitative analysis. Also, the mathematical formulation was analyzed using simulation in Excel. Results: In most of analyzed knowledge creation cases, knowledge absorption from external source through changing managers or employing consultant following integration with exist knowledge was occurred. Also, simulation results show that, mathematical relations were not well defined and changing them makes results more acceptable. Conclusion: Knowledge grow in organization has occurred through three ways including planned knowledge creation based on managerial decisions, planned knowledge absorption based on managerial decisions, and random knowledge creation mechanism, and all of them have impact on essential knowledge contents. [ABSTRACT FROM AUTHOR]

Land is the place of interactions, transactions and the node of conflicts between various social groups. It is through the land, the way of using it, and realization of forces that encounter on it (constructing the artificial environment), which the spatial organization shapes. There are lots of factors influence the land-use change, but it is human activities that generally form these changes, and subsequently changing the spatial configurations of region. The concrete crystallization of these uncontrolled activities is unequal accumulation of capital in the metropolitan region, and increasing the regional imbalances more and more. Thus it is essential that through studying the driving forces of changes in land-use, and related spatial factors, one think about the possible future processes. Then, the objective of this study is forecasting land-use changes in Mashhad metropolitan region, using Cellular Automata (ca) and Artificial Neural Network algorithm. The research method was quantitative, and using land maps in the years 1993 and 2011, land-use changes for the years of 2030, 2048, 2066 and 2084 will be simulated in Q Gis2.4 environment. The conclusions show that first, future land-use changes will lead to consuming more and more agricultural lands and grasslands, so that, deteriorating rural settlements. Secondly, the continuing of present development of urban settlements and land-use changes, may cause environmental disasters and consequently leaving irreparable socio-economic damages in the region. According to the results, it is necessary for the planning and management system of the region, to adopt a comprehensive approach in order to prevent the future environmental problems, also to control horizontal expansion of settlements. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to study climate changes and fluctuations in the four synoptic stations in Sistan and Baluchistan province in the past few years and to analyze statistically and simulates and forecast for the next years (2040-2009). This study used data from the outputs of general circulation climate model ECHO-G with A1 scenario that are now used at the University of Hamburg, Germany, and the Korea Research Center for Downscaling on selected stations and the results were analyzed. Model of the stations studied, indicated that the model parameters at the stations could simulate the minimum temperature, maximum temperature and the radiation well, but simulation of rainfall had an error especially in Zabol station. Analyzing the data generated in the course of future climate and its comparison with the previous period indicated an increase in precipitation stations and the heavy precipitation in the range of the station. In the course of the future, climatic factors increased in minimum temperature more than the maximum temperature that lead to a decrease in the range of temperature and reduced thermal comfort in the coming years for the province. An increase in the number of hot days and decrease in the number of frost days (especially in Zabol and Zahedan station) in the course of future climatic are other results of the data. Radiating element in Zahedan station in all months, and at other stations in most months increases compared to the previous period. [ABSTRACT FROM AUTHOR]

Background and purpose: Postpartum haemorrhage (PPH) is the most important cause of maternal death. Improving clinical competence could increase the quality of midwives' works and decrease maternal death. This study was done to compare the effect of traditional, web based and simulation training on clinical competencies of midwifery students in PPH management. Materials and methods: This semi-experimental study was performed in 91 midwifery students in Mashhad School of Nursing and Midwifery, 2013. The samples were randomly divided into three groups of web-based, simulation and traditional training using table of random numbers. The web-based group was trained on-line for one week, through educational web site. The students in simulation-based group were trained in Clinical Skills Centre for four hours and the traditional group was trained for 4 hours by lecture and PowerPoint presentation. Students' clinical competencies were measured before and one week after the intervention by a questionnaire and objective structured clinical exam. Data was analyzed by descriptive statistical test, paired t-test, and ANOVA. Results: No significant difference was found between the three groups in clinical competence to manage PPH before the intervention (P>0.326). One week after training, the mean score for students' clinical competence showed significant increase in all groups (P<0.001). The intergroup comparison indicated no significant difference between the groups in clinical competence one week after the intervention (P=0.128). Conclusion: All three methods were found to be similarly effective in improving clinical competence to manage PPH. [ABSTRACT FROM AUTHOR]

Introduction: Triage is the basis for incident management and triage training to medical emergency faculty in planning Disasters is a very important issue. This study has been done with the aim of evaluating the effects of simulated workshop triage on their learning level and determining their satisfaction with the operational workshop. Materials and Methods: This quasi-experimental study was carried out on 15 senior students of medical emergency in the first semester of 2014-2015 in Jahrom University of Medical Sciences. Teaching fundamental modified triage was done in a two-hour meeting. After a week, workshop triage training was carried out in a simulated environment for 4 hours. Before and after workshop training, the students were tested in a simulated environment with Models and pseudo-injured patients. To assess the impact of workshop on student learning, pre-test and post-test scores were compared. Students' satisfaction with operating workshop was evaluated by a reliable and valid questionnaire (a = 0.8). Results: A significant difference was seen in students' pre-test and post-test scores (p<0.001, df = 14, t=-6.41) and post-test scores increased compared to the pre-test scores. All students (100%) fully agreed with issues such as that the operational workshops has caused deep learning and that it creates the necessary readiness for students to work in a real environment. Conclusion: It is recommended that emphasis be put on effective and operational training in practical skills training, especially in theoretical-practical courses so as to facilitate more the student learning to achieve skills. [ABSTRACT FROM AUTHOR]

One of the most important problem and issues in metropolises is natural hazards and the earthquake is the most important of them in developing countries. According to this theme, comprehensive disaster management especially earthquake is an important factor to safe people life and evaluate risks by complete and update information bank, exact and modern hardware and GIS and Karmania Hazard software. This paper discusses with regard to the earthquake damage of Kerman and active faults evaluate vulnerability of the 13 operational area. In this method (survey), by the Karmania Hazard software and GIS, land use damage and the number of casualties are calculated; and then the efficiency rate of all kinds of emergency centers will be evaluated. 13th area is the old region of Kerman city that is included of different kinds of emergency center, one fire station, 14 health center and 10 police centers. By evaluating reports and vulnerabilities map results of simulation an earthquake with 6.3 (Ms) of magnitude caused by Koohbanan fault in Karmania Hazard software, except 7 hospitals the other emergency centers will be unusable; And because the population is more than 28000, there will be no enough area and open spaces for emergency and temporary housing and no enough space to set up search and rescue centers. The main problem here is old houses and mazing and narrow paths that hinders and rescue procedure and increases the dead people's numbers. [ABSTRACT FROM AUTHOR]

Background and Aim: Liposuction is one of the most popular procedures for removing unwanted body fat deposits now. The conventional methods for liposuction however have many drawbacks; among them is long recovery time, scars, bruising, skin flaccidity and excessive blood loss. Considering the increasing demand for body sculpting, the need to improve these techniques is of vital importance. One of these newly proposed techniques is laser assisted lipolysis. Laser lipolysis is now widely used for body contouring and sculpting. Less trauma, bleeding and pain is among the main advantages of this method. Methods: Photons propagation and scattering within the biological tissues can effectively investigated by using numerical methods. In this study we used the Monte Carlo simulation method to simulate photons directions, absorption and scattering inside the tissue. This method uses a random number generator for photons creation, moving inside the tissue and termination. In this simulation we considered both the wavelength and fluence variations effects on the photon absorption rate and penetration depth inside the fat tissue. Results: Our study showed the increasing of penetration depth with decreasing of absorption coefficient. We observed that deepest penetration depth for 920 nm wavelength as it has lowest absorption coefficient. We also concluded that increasing the laser power (increase in fluence of laser) resulted in increasing the penetration depth of laser radiation. Increasing the radius of laser beam (decreasing the fluence) on the other hand resulted in reduction in penetration depth. Conclusion: Monte Carlo simulation of radiation propagation within the biological tissue has proved to be an efficient method. This method effectively simulates the physical components of laser radiation. Our findings indicate that to have laser lipolysis more efficient and safe, it is essential to choose suitable wavelength. [ABSTRACT FROM AUTHOR]