The most current way for measuring the SOIL FRAGMENTATION is determination of mean weight diameter (MWD). In this study, the adaptive neuro-fuzzy inference system (ANFIS) was used to predict of range SOIL FRAGMENTATION affected by different grazing intensities, distance from village and sampling depth. Present study conducted at 2015 in 3 adjacent rural areas (Alvars, Aldashin and Asbe marz) in Darvishchai watershed in Ardabil County. The studied parameters on the SOIL FRAGMENTATION including different grazing intensities in 3 levels (low, medium and high intensity), distance from village in 3 levels (200, 400 and 600 meters) and the SOIL sampling depths in 2 levels (0-15cm and 15-30cm). Obtained data were transferred to MATLAB software for the development of ANFIS models. For evaluating the models operation, mean squares error (MSE) and correlation (R2) were used. The result of best ANFIS model in prediction of SOIL FRAGMENTATION was compared with results of regression model. The results show that different grazing intensities, distance from village, sampling depth and their combinations had significant effect on the SOIL FRAGMENTATION. Increase of grazing intensity resulted in increment of SOIL FRAGMENTATION. With increment the distance from village from 200 to 400 meters, SOIL FRAGMENTATION decreased but with increment of distance, increased. SOIL FRAGMENTATION in all conditions was higher at depth of 0-15 cm than depth of 15-30 cm. ANFIS model had more precision in prediction of SOIL FRAGMENTATION (R2=0. 96) relative to regression model (R2=0. 76).

Suitable SOIL structure is important for crop growth. One of the main characteristics of SOIL structure is the size of SOIL aggregates. There are several ways of showing the stability of SOIL aggregates, among which the determination of the median weight diameter of SOIL aggregates is the most common method. In this paper, a method based on adaptive neuro fuzzy inference system (ANFIS) was used to describe the SOIL FRAGMENTATION for seedbed preparation with combination of primary and secondary tillage implements including subSOILer, moldboard plow and disk harrow. Adaptive neuro fuzzy inference system (ANFIS) is a suitable approach to solving non-linear problems. ANFIS is a combination of fuzzy inference system (FIS) and an artificial neural network (ANN) method and it uses the ability of both models. In this study, the model inputs included “SOIL moisture content”, “tractor forward speed” and “working depth”. The performance of the model was evaluated using the statistical parameters of root mean square error (RMSE), percentage of relative error (e), mean absolute error (MAE) and the coefficient of determination (R2). These parameters were determined as 0.135, 3.6%, 0.122 and 0.981, respectively. For the evaluation of the ANFIS model, the predicted data using this model were compared to the data of artificial neural network model. The simulation results by ANFIS model showed to be closer to the actual data compared with those made by the artificial neural network model.

Background and Objective: Biological SOIL crusts are a collection of lichens, mosses, fungi, cyanobacteria, etc. that are part of the SOIL ecosystem. Estimation of density and distribution of biological SOIL crusts in arid and semi-arid regions of Iran, which is the subject of SOIL erosion and wastage is very important. Methods based on remote sensing techniques are important in terms of cost and time less efficient methods to achieve this goal. Segzi plain is one of the critical points of wind erosion in Iran and identifying and determining the distribution of biological SOIL crusts as a SOIL modifier is an effective step in reducing wind erosion in the region. In this research, BSCI (Biological SOIL Crust) index has been used to prepare the distribution map of lichen-dominated biological SOIL crusts. Materials and Methods: The study area is part of the Sajzi Desert (Central Deserts of Iran) which is located in Isfahan province of Iran. The study area with an area of 199. 5 hectares is spread between the eastern lengths of 51o52'32" to 52o27'41" and the northern widths of 32o33'31" to 32o55'01". The average slope of Segzi plain is 1. 08 percent and its average height is 1680 meters. According to the statistics of East Isfahan Meteorological Station (Shahid Beheshti Station), the average annual rainfall in the region is 106 mm. According to the Dumarten climatic classification, the climate of the region is dry and according to the Amberge classification it is cold. The BSCI index is a combination of the relationships used to estimate vegetation and bare SOIL surface, and its mathematical relationship is the slope of the SOIL line. To calculate the SOIL line in an area, one must first separate the pixels that have bare SOIL and no vegetation. In order to calculate the SOIL line equation, in four seasons of a year, images of Landsat OLI 8 satellite related to 2018 were downloaded from the site of the US Geological Survey and 20 to 30 pixels of pure bare SOIL were extracted by drawing the reflection values of these pixels in the red and infrared band. Red near SOIL line coefficients were calculated for each season in the Segzi Plain. Based on BSCI index, lichen-dominated biological SOIL crust are identified using at least VIS-NIR spectral reflection and the slope between the red and green bands compared to bare SOIL and dry vegetation. Using ENVI software, the distribution shells of biological shells with lichen dominance were prepared in four seasons since 2018 in Segzi plain. Then, the prepared maps were validated based on land points and the total accuracy and kappa index were calculated in all four seasons. The collected lichen samples were identified based on their morphological characteristics and using a stereomicroscope, conventional microscope and common color reagents such as potassium hydroxide (KOH). After applying the BSCI index on the Landsat OLI 8 satellite image, using ENVI software, spectral profiles related to 4 points of Segzi plain in four seasons of the year were prepared and the spectral reflection in four seasons of the year in different points were examined. Results and Discussion: The slope of the SOIL line is lower in the rainy season, which coincides with the growth of herbaceous and annual plants, compared to the summer season, which has the least amount of rainfall, and the annual plants have dried up and become extinct. In May, the slope of the SOIL line was minimal (0. 39) and in late summer it has its maximum value (0. 78). In fact, the slope of the SOIL line has decreased from mid-August to May, and then has increased with the loss of annual vegetation and the increase of bare SOIL surface. The distribution maps of bio-shells in all four seasons of the year were validated during field visits and the year it was found that the highest accuracy of the map related to the map produced from Landsat 8 image is related to summer with 94% total accuracy and Kappa index equal to 0. 7412. Interpretation of the spectral profiles of the BSCI index shows that the reflections of the spectra related to the zephyr and strain prepared on the lichen dispersion points are very close to each other and also the spectral profiles of the mid-autumn and early spring are quite consistent. Whereas in the faults, which did not cover the biological crust, the amount of reflection was higher and there was a slight difference between the reflection diagrams of autumn and spring. Although the reflectance values of a range of agricultural lands and the distribution points of biological crusts are very close to each other, the spectral diagrams of all four seasons are very different from each other. But in all seasons of the year and in all places, the least reflection has occurred in the beginning of winter and the most reflection has occurred in summer. The climate of Segzi plain is Mediterranean and precipitation occurs in the cold season of the year. Simultaneously with the increase of precipitation from the middle of autumn, annual plants and mosses at the base of shrubs begin to grow and reach their peak in early winter and again at the beginning of spring. Decreases in rainfall have reduced their density. If the winter spectrum has the least reflection in all places. While in late summer, when the annuals and mosses have dried up, it has had the greatest spectral reflection. In Fasaran, which is a barren area and a landfill, it has shown its maximum reflection. Therefore, the BSCI index relative to the percentage of organic matter has a significant error in the detection of biological SOIL crust and where the organic matter is high may not provide accurate diagnosis of SOIL bioshells. Of course, since the BSCI index is defined for the detection of throat compounds in lichen tissues. The error rate for organic matter is reduced to a minimum. As it has been observed in the final map, there is no cover of biological SOIL crusts in Fasaran and only SOIL biological crusts are observed in the areas around Fasaran in the agricultural areas. In agricultural areas, due to human intervention and cultivation, the amount of annual plants is different from the field of natural resources in different seasons of a year have become. Conclusion: Spectral similarity of the most important SOIL surface, including vegetation, the involvement of human factors in increasing or decreasing SOIL organic matter, bare SOIL, etc. limits the efficiency of the BSCI index and therefore in the time period of satellite images and regional conditions have a great impact on It has the accuracy of BSCI index.

The diagnosis of male fertility is based on microscopic assessment and analysis of sperm concentration, motility and morphology as routine indicators of human semen quality. Successful pregnancy requires a sperm with genetic integrity. Several studies have shown that male fertility is affected by sperm DNA damage. Subsequently, the assessment of DNA integrity in sperm and the study of its consequences have received considerable attention. Several clinical studies have examined the relationships between sperm DNA damage and reproductive outcomes in the context of natural and ART pregnancies. For IVF and ICSI, the true utility of sperm DNA damage assays remains to be firmly established, since the available studies are generally small, heterogeneous, with conflicting results. Current data suggest that impaired sperm DNA integrity may have the greatest effect on IUI pregnancy rates, further prospective studies are needed before testing becomes a routine part of patient management.

Large Hadron Collider (LHC) at CERN will provide excellent opportunity to study the production and decay of heavy mesons and baryons with high statistics. We aim at the heavy mesons in this work and calculate their FRAGMENTATION functions consistent with this machine and present their total FRAGMENTATION probabilities and average FRAGMENTATION parameters.

There has been increasing concern in the international law profession about the FRAGMENTATION of international law. Although the international legal system has always developed in a fragmented way, the expansion of international law in new areas has created problems of coherence between its different branches, institutions and norm-systems. Normative conflicts and tensions between specialized regimes have emerged between general international law and its specialized branches (trade law, criminal law, human rights law, environmental law etc.). In this article we will analysis the FRAGMENTATION of international judicial system and the ways of resolving the possible contradictions. To do so, we will first consider the possibility of a uniform international judicial system and then a fragmented (pluralistic) judicial system.

Facilities built in areas affected by earthquake activity, such as tunnels, which have always been an integral part of human life, must withstand both dynamic and static loading. It has led to the need for practical studies on the effects of earthquakes on underground structures and the factors affecting their destruction. For this purpose, in this research, at first different patterns of tunnel’s excavation were investigated and by using Plaxis 2D software and based on Tabas earthquake in Iran, sensitivity analysis on geotechnical parameters of the SOIL surrounding tunnel such as cohesion, friction angle, unit weight and modulus of elasticity was carried out, and the parameters whose changes have the greatest and least effects on the bending moment changes on the tunnel lining are introduced. The results show that tunnel excavation patterns significantly affect the bending moment, axial forces, displacements, and surface settlement of the tunnel. Often, by dividing tunnel excavation area to small parts, the values of bending moment, axial forces, displacements, and surface settlement of the tunnel decreases in static analysis. Also, outputs of sensitivity analysis on geotechnical parameters of the SOIL surrounding tunnel showed that modulus of elasticity of the SOIL surrounding tunnel has the most effect and cohesion changes have the least effect on bending moment induced on tunnel lining..