This study examines the theoretical and empirical aspects of the effect of capital inflow on exchange rate in 14 developing countries for the period 1980-2009. We developed an empirical model to investigate the effects of term of trade, real per capita output and trade openness on real exchange rate using dynamic and heterogeneous panel and Pool Mean Group (PMG) methods. Estimation results show that various capital inflow channels have different effect on real exchange rate. For non-oil countries, only foreign aid inflow causes exchange rate appreciation in long-run and short-run and creates Dutch disease. In oil exporting countries, oil revenues and foreign direct investment cause exchange rate appreciation and create Dutch disease problems in the long-run. However, an increase in oil revenues in oil exporting countries causes more exchange rate appreciation than an increase in foreign direct investment.

Surge flow irrigation is a new concept in surface irrigation methods that improves preformance efficiency and uniformity in furrow irrigation. Surge flow irrigation is only effective in the first two irrigations. Its effectiveness will be the same as continuous irrigation on the rest. In surge flow irrigation, inflow rate is kept constant. Stepwise inflow rate increment promotes wetted perimeter over which infiltration occurs. The effect of this concept is not yet known on application efficiency and irrigation uniformity. In order to compare advance phase water saving and moisture uniformity, three treatments such as continuous flow, surge flow with constant inflow rate, surge flow with stepwise flow rate were selected. Field experiments for this research were carried out in Agricultural Research Station at University of Tehran located in Karaj. Soil texture in study area is sandy clay loam. Tests were conducted two times for the first irrigation in 150 and 200 m furrows.Results indicated on the first two irrigations, the volume of water required to complete advance phase in surge flow irrigation with stepwise inflow increase, was 10 and 12 percent less, respectively, in compare to surge flow irrigation with constant inflow rate. In the meantime, soil moisture distribution also was more uniform than the surge flow irrigation with constant inflow rate.

In water resources management, there is a critical need to the prediction of the amount of inflow into the water supply system in order to be aware of future conditions and planning for optimal allocation of water resources to different sectors such as drinking, agriculture and. The aim of this study is to forecasting the monthly inflow to the Gorgan dam for future. To this aim, the data of the Qazaghli station with a 47-years history period and three Time series, neural network and Support vector machine models used for prediction. According to the obtained results, the ARIMA (1, 0, 0) (1, 0, 1) was found to be the premier parsimonious time series model based on the Akaike and Schwarz criteria. Moreover, The ANN model with 2 input and 10 neurons tuning and the SVM model with one input were the best performing models. Finally, according to the obtained results and evaluation criteria, the SVM model has the best efficacy in comparison with two other methods. The RMSE and AARE was 5. 31 and 1. 07 for SVM model, respectively; 9. 88 and 2. 78 for neural network, respectively and 8. 84 and 1. 07 has been obtained for Time Series model, respectively. Based on the results of this research, the best model to predict the monthly discharge input to the Gorgan dam was SVM.

In this paper, a finite element model is developed for the fully hydro-mechanical analysis of hydraulic fracturing in saturated porous media. The model is derived within the framework of generalized Biot theory. The fracture propagation is governed by a cohesive fracture model. The flow within the fracture zone is modeled considering the lubrication equation. In order to describe the fracture in the saturated porous media, momentum equation and mass balance equation with Darcy law are employed. The standard Galerkin method and Newmark scheme are used for discretization in space and time, respectively. Finally, the effects of permeability and rate of injection on the hydraulic fracture propagation are studied. It is observed that an increase in permeability leads to slower crack propagation. In addition, increasing flow rate leads to a faster crack propagation. When permeability increases by 3.3 times, CMOD and crack length decreases by 43.8% and 20%, respectively after 1 second and decreases by 29.4% and 15.9%, respectively after 6 seconds. In addition, when flow rate increases by 2, 3, and 4 times, the crack length increases by 30.5%, 55.9%, and 76.3% after one second.

Background and Objectives: Surface irrigation is the most common method of irrigation. over 80% of agricultural lands in Iran are irrigated by this method. Generally, this technique has lower investment and energy requirements than pressurized irrigation methods. Many efforts are applied to improve the economic output of water use and to preserve the environment in Iran. Modifying the design and management parameters at the farm level can improve the performance of irrigation systems. The main objective of this study is to optimize surface irrigation efficiency, with low-cost tools, using a simulation model. Materials and Methods: The study areas were selected fields of the Molla-Sani region in Khuzestan province, located southwest of Iran. Field experiments were carried out in two fields, irrigated using a surface irrigation system. Three irrigation events and three plots (as repeats) were applied per field. Experiments were conducted on the three borders of 150 m in length, 7 m in width, and 0. 125 % slope, in Field 1, and on three borders of 200 m in length, 7 m in width, and 0. 1 % slope, in Field 2. The inflow rates of 25 and 35 L/s were applied in fields 1 and 2. The inflow rate was checked using a W. S. C flume. The borders were divided into parts of 10 m distances to measure the advance and recession times. The best combination of parameters was determined with the simulation model. The objective function (OF) including the application efficiency and the distribution uniformity was applied to optimize the irrigation performance. Results: This study showed that, based on the simulation model, changing the inflow rate, does not affect the best value of an objective function. The optimal inflow rate and cut-off time are recommended as 35 L/s and 30 min in a border with a length of 50 m, in Field 1, and, the best performance in Field 2, is obtained from the inflow rate of 20 L/s and the cut-off time of 48 min and length of 50 m. Field experiments showed that the difference in infiltration rates, was not significant, during this study. Based on the data obtained from three events, in both fields, and analyzed via the simulation model, the average NRMSE (Normalized Root Mean Square Error) index values for the evaluation of the advance curves were 12. 7, 12. 5, and 11. 6%, while the recession curves were 6. 9, 6. 8, and 6. 6%. Conclusion: Pressurized irrigation has the high investment and energy requirements than surface irrigation. Furthermore, the evaporation rate is much, in the research region. Because the inflow rate and cutoff time are the most effective parameters in improving irrigation, thus, in this region, prediction and selection of the optimum combination of cut-off time and inflow rate are the low-cost tools to improve the surface irrigation performance compared to modifying length and slope in border irrigation or transform of surface to the pressurized system, in the farm level.

Background: The current study is to evaluate cardiovascular effects of anesthetic medications and volatile anesthetics on cardiac stress using cardiac stress index (CSI) and rate pressure product (RPP) and to determine which of them in useful in evaluating cardiac stress after comparing results obtained from each method.Materials and methods: 40 patients, 60-80 years old, who were all performed trans abdominal prostatectomy were studied. Patients were divided into two groups, half of patients were placed in group A and the other half in group B. The study was carried out as a blinded study. CSI was measured and evaluated in group A and RPP changes were studied in group B.Results: The mean CSI were 60.25±5.57, 63.05±5.54, 55.75±4.78 and 67.65±4.88 before anesthesia induction, after induction, before surgical incision and in recovery respectively. There was no meaningful difference.RPP mean in four above mentioned stages was 10.15±0.44, 9.9±0.69, 6.8±0.36 and 9.2±0.61 respectively. There was a meaningful difference between RPP in stages before anesthesia induction and before surgical incision (P<0.0001).Conclusion: Considering the obtained results from this study, it can be seen that even in noncardiac surgery, the stress level is high in patients in the stage before surgery. This figure was not clear in RPP index case and was not in accordance with CSI, which means CSI has been able to illustrate existing stress level better and efficiently.

Evaluating the cutting rate (CR) of stones is important in the cost estimation and the planning of the stone processing plants. This research used regression models to estimate the stones’ CR based on their physico-mechanical characteristics. Stone processing factories in Mahallat City (Markazi province, Iran) were visited, and the CR of diamond circular saws was recorded on six different travertine stones. Next, the stone block samples were collected from the quarries for laboratory tests. Stones’ porosity (n), uniaxial compressive strength (UCS), and Schmidt hammer hardness (SH) were determined in the laboratory as their physico-mechanical characteristics. Correlation relationships of CR with physico-mechanical characteristics were evaluated using simple and multiple regression analyses, and estimator models were developed. Results showed that multiple regression models are more reliable than simple regression for estimating the stones’ CR. The validity of the developed multiple regression models was verified with the published data of one researcher. The findings indicated that these models are accurate enough for estimating the CR of stones. Consequently, the multiple regression models provide practical advantages for estimating the CR and save time and cost during the planning and design of the stone processing factories.

Furrow irrigation is the most common type of surface irrigation. Determine the advance and recession time in the field is required the accurate measurement and this can be costly and time consuming. WinSRFR model is used for simulation furrow irrigation by zero inertia and kinematic wave engines. Using this model, advance time, reaction time, infiltration depth, runoff depth and application efficiency are calculated and compared with field data. Also, different inflow hydrograph shapes such as steady, incremental, cut back and hydrograph has been investigated in the research field in Shahid Bahonar University of Kerman. Based on the results, the kinematic wave model, Because of assuming the uniform flow through the furrow's length, has lower precision than zero inertia engine. The results showed that when an inflow hydrograph shape has smooth changes, the precision is increased. The model has the highest accuracy in calculation of advance time (1.2%) in steady inflow hydrograph and lowest accuracy in calculation of advance time (11.2%) in incremental inflow hydrograph. The highest application efficiency and the lowest runoff are accrued in cutback inflow hydrograph with 72 and 28%, respectively.

Urmia Lake, located in north-west of Iran, has been exposed to various threats such as drought, construction of dams, land use changes and increased global temperature. Due to the importance of Urmia Lake, it is feasible to conduct different kinds of studies to identify the problems of its watershed. The main objective of this study was to evaluate SWAT program’s ability to simulate runoff in Urmia Lake watershed with an area of 52000 km2. The model was run for the 1980-1997 period. Calibration and validation periods were from 1980 to 1991 and from 1992 to 1997, respectively. The results of calibration for 10% and 85% of hydrometric stations were very good and suitable, respectively. Also, validation results for 25% and 45% of hydrometric stations were very good and suitable, respectively. These results show the high ability of SWAT model to simulate discharges in Urmia Lake watershed. Moreover, some factors influencing inflow to the lake in recent years were evaluated. The outcomes revealed that recent changes (dam cconstructions, climate change and land use change) in the watershed have caused inflow volume to the lake to decrease by 80%. So, if natural management conditions had prevailed in the watershed, the Lake’s conditions would have been much better.