The radars that use medium PRF, have either range ambiguity or Doppler ambiguity, but these ambiguities can be resolved with selecting a PRF set. Avoiding ghost targets detection and minimizing blind zones are two important points that should be considered in targets detection. Then, using this set, coincident algorithm and clustering the closely detected points, we resolve ambiguity and detect the targets. After that, to decrease ghost target detection, deghosting algorithm is used. In this paper, a new definition of uniqueness condition is presented to be robust against errors when clustering is employed. Also, it is shown that the medium PRF range depends on the maximum range and Doppler as well as range bin and Doppler bin.

Introduction Crop models can integrate the complex interactions of soil properties, climatic conditions, crop management practices, and crop genetic characteristics. One of the main aspects of crop simulation models is the possibility to use them across various environmental and management conditions, provided that they have been evaluated under a wide range of growing conditions. The Decision Support System for Agrotechnology Transfer (DSSAT) modeling platform is leading crop modeling system that is widely applied in various environments. Testing crop models under various temperature environments are essential to apply models to climate impact studies. The objective of this study was the testing and evaluation of DSSAT-Nwheat model across a wide range of climate conditions in Iran. Materials and Methods Nwheat model, which recently integrated into DSSAT, was evaluated for four wheat cultivars using observations from field experiments included a wide range of climate and management. Cultivars were Shahriyar, Pishtaz, Tajan, and Chamran cultivated in cold, temperate, humid and tropical regions in Iran, respectively. The locations represent four different wheat mega-environments, a concept used by wheat breeders for testing cultivars. The management information used at each site was obtained from the Seed and Plant Improvement Institute. Daily weather data, management events, and soil characteristics imported to DSSAT. The performance of the DSSAT-Nwheat during the calibration and evaluation was assessed using different statistics, Root Mean Square Error (RMSE), Normalized Root Mean Square Error (nRMSE), Willmott’ s index (d), and coefficient of determination (R2) of a 1: 1 regression line. A sensitivity analysis was conducted using 30 years of observed weather data from Tabriz, Mashhad, Gorgan, and Ahwaz. For the sensitivity analysis scenarios, the temperaturewas increased by 3, 6, and 9° C, and atmospheric CO2 concentration levels were set at 360, 540, and 720 ppm. Results and Discussion Evaluation results showed that DSSAT-Nwheat model simulated planting to anthesis and planting to maturity accurately with RMSE values less than four days, nRMSE less than 3%, and d index close to one. Also, evaluation of grain yield showed that RMSE varied from 568 kg ha-1 for Tajan cultivar up to 933 kg ha-1 for Chamran cultivar. In general, nRMSE and d index for grain yield were less than 20% and higher than 0. 8, respectively, which showed good calibration accuracy. In DSSAT-Nwheat model, the specific heat stress function explains heat stress effects during grain filling on grain yield in cultivars. Chamran cultivar is somewhat resistant to end season heat stress, so the DSSAT-Nwheat model underestimated in the warm regions. Because the cultivars differ regarding resistance to the end season heat stress, crop models need to consider cultivar-specific tolerance to heat stress to better simulate temperature effects on wheat cropping systems. The response of the model to the increase in temperature was different in regions and levels of CO2 concentrations. Elevated atmospheric CO2 concentrations lessened some of the adverse effects of high temperature. Therefore, the sensitivity analysis of DSSAT-Nwheat model to temperature variations and elevated atmospheric CO2 concentrations showed that the model could be used in studies of climate change impacts on wheat production. This model can be employed to explore the integrated effects of temperature, atmospheric CO2concentrations, water, nutrients, and agronomic management practices in a range of wheat growing environments. Conclusion The results of this study showed that the DSSAT-Nwheat model had reliably good performance under a wide range of management and environmental conditions. This calibrated model can now be used for assessing impacts of various agronomic management strategies and decisions in wheat cropping systems under current and anticipated climate change. But more importantly is the calibration method and using a large number of climatological data to calibrate.

The present research studied the (causal, contextual, and intervening) conditions, strategies, and consequences of violence in the lives of child wives in Chabahar city, conducted with a qualitative methodology based on grounded theory. For this purpose, in-depth semi-structured interviews were conducted with 28 child-married girls in Chabahar city who were selected through theoretical sampling and snowball method. The analysis of the data in the framework of the three-level open, axial and selective coding system showed that gendered inequality and discrimination, women's inferiority, men's value, the culture of silence and the culture of violence play a role in the experience of child-wives in terms of violence (causal conditions), which leads to a type of increased, double violence for them (core category); violence that operates within the framework of the family institution, the main mechanism of which are previous traditions and rules, and the perpetrators of which are men and women who were themselves the victims of the same traditions and rules that they have, now, internalized and used again against their daughters. This increased violence happens in a context where patriarchy is widespread (contextual conditions) and due to the generalized self-deprecation among child wives (intervening conditions), they may attempt to escape, get separated, threaten, and commit suicide (strategies), and these actions have consequences such as symbolic, physical, and sexual violence and even social isolation (consequences).

This study was aimed to determine the variation of species diversity, richness and evenness of plant species under various managements (different range conditions) in five vegetation types. After determining vegetation types, range condition was measured applying the method of society for range management (SRM). In order to assess species diversity, richness and evenness, canopy cover percentage and species density were determined along transects within plots. Species diversity was determined using Simpson index, Shannon-wiener function and Hill index (N1 and N2) and species richness was determined by Margalef, Minhinnick, Bootstrap and Jack-Knife methods and species evenness was measured using Simpson, Camargo, Smith-Wilson and Nay revised index. Mean comparison test (non-paired t-student test) was used to determine the relationship between species diversity, richness and species evenness under different conditions. The results showed that in various managements with changes in range condition, a trend of regular changes could be observed between vegetation cover and range condition. In other words, the value of estimated indices of species diversity and evenness was higher in good range condition as compared to the fair and poor range condition; however, the maximum value of species richness was related to good, fair, and poor conditions, respectively. Results of mean comparisons showed a significant difference between good and poor condition for most of the indices used in species diversity, richness and evenness, while there was no significant difference between good and moderate condition.

The range conditions explain its health as a management tool. Obviously, the implementation of this important assessment requires the most appropriate study method for each region. In order to select the most appropriate methods of range conditions in Kabirkooh grasslands of Zagros in Iran, five estimation methods (i.e. six-factor, fourfactor, vegetation and soil combination, value of pasture and climax) were studied in three key and critical areas. In each area, five stations were selected using the randomizedsystematic method. The differences between methods were analyzed using the factorial experiment by the help of the randomized complete blocks design with five replications.The results showed that there were significant differences (p<0.01) between both range conditions’ determination methods and different areas. Regarding Kabirkooh rangelands in current circumstances, four-factor method for semi-arid region is more applicable for the range condition determination. Biomass production and range conditions had a close relationship using Pearson correlation test (p<0.01, r=0.86).

The effects of climatic factors on four dominant range land species of Markazi province, Iran, were studied. Species were Artemisia sieberi, Salsola rigida, Noaea mucronata, Stipa barbata and were monitored from 1998 to 2005. Site is located in steppe lands and called Nemati range, Akhtarabad of Saveh. Climatic factors were annual rainfall, rainfall of grazing season plus rainfall of previous year, temperature, solar radiation and wind velocity. Among the main indicators, as results shows, growing season plus previous rainfalls is the most effective indicator on forage production with high and significant correlation. Total yield have positive and significant correlation with growing season rainfall and previous rainfall as well as production of Artemisia sieberi, Salsola rigida. Soil and water regime in dry and semi-dry areas, in growing season, is in a way that plants are dependent on stored moisture. Shrubs, with their deep roots, are more capable of using this moisture. Therefore stored moisture could be known as an indicator of rain quantity. Result of this research showed that rainfall indicator in growing season and previous season is a variable that plays fundamental rule in production, showing a linear relationship. Negative correlation was shown between number of sunny days, total yield and yield of two species, Salsola rigida and Artemisia sieberi.