In order to predict the behavior of Soil-related phenomena, it is necessary to have knowledge about unsaturated flow and using models that provide optimal estimates of the retention curve and hydraulic conductivity of Soils. Despite the widespread use of the classic van Genuchten-Mualem model (VGM), this model usually performs poorly in predicting hydraulic conductivity and modification of some of its parameters seems necessary. In this research, 283 Soils from different textures of the UNSODA bank were selected and divided into two sections of calibration and validation and their Soil parameters were exported and categorized. Then, by defining the modified unsaturated hydraulic conductivity (Ksc) instead of the saturated hydraulic conductivity (Ks) and determining the limits for l and n parameters, the hydraulic conductivity-moisture function of VGM were solved using 24600 pairs of points li and nj for each Soil of the three main Soil texture classes. In the following, the optimal l value (l̂) of each texture class was selected based on the minimum value of the hydraulic conductivity estimation error using the root mean square error (RMSE) index and the n values that had created the minimum errors, were selected as the optimal pore size distribution coefficients of the hydraulic conductivity-moisture function (n̂opt). In order to create pedotransfer functions for estimating n̂opt, we ran stepwise regression in MATLAB software considering the condition of statistical significance (P-value=0.05) for independent variables and functions for each Soil texture class. After creating pedotransfer functions, the results of the proposed method of this research (MVGM) were compared with the VGM results using RMSE and Nash-Sutcliffe (NSE) indices. The results showed that in both sections of creation and validation functions, the MVGM performed better in estimating hydraulic conductivity and had a higher efficiency index in all textural classes of Soil.

Soil moisture characteristic curve (SMC) is an important hydraulic characteristics of Soil in design of irrigation and drainage systems, determination of hydraulic conductivity, and contaminants transport study in porous media. Direct method in the derivation of SMC is often costly and time consuming. Hence, physical and empirical models are widely used to simulate SMC. The main objectives of the present study were to compare the actual SMC with those predicted from Arya and Paris (1981), Arya et. a1. (1999), and Tyler and Wheatcraft (1989) models and to modify the simulated results with scaling parameter (a) applicable for different types of Soils. The input data for these models ara particle-size distribution and α parameter. In this study, nine different Soil series from Urumie and Salmas regions representing wide range of Soil texture class from loamy sand to clay were examined. Results indicated that the simulated SMC without modifying α parameter for particle size distribution are significantly different from the measured SMC, and the deviation in α for each type of Soils is the major factor in the discrepancies. Hence, the scaling parameter α plays a major role in the simulation process. The parameter a is generally evaluated by a relationship in the form of αi = (a+blog (Wi/Ri3»/logni. In the present study, empirical coefficients a and b were determined for nine Soil texture classes. Results indicated that with a= log (3/4 Лps» and b= 1.0156 e-0953, a could be calculated regardless of Soil texture, thereby, the simulation of SMC could be accurately possible. Simulated SMC were in good agreements with the experimental ones, and the relative error was in the order of 0.79% indicating a great accuracy in SMC prediction.

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.

Introduction and Objective: Collembola are most abundant decomposer Soil living arthropoda in forest ecosystems. They are among the best indicators within the Soil mesofauna to determine the health and sustainability of forest ecosystems. The Hyrcanian forests, most of which are located in Iran, are among the most valuable forests on Earth, which, despite their climatic diversity, unique plant and animal species, are inscribed on the UNESCO World Heritage List. Despite the very important role of Collembola in ecological processes of forests, including the decomposition of organic matter and nutrient cycles but the role of these small arthropods in the Iranian Hyrcanian forests has not been much studied. The study was conducted to investigate and identify the fauna of Collembola in the forest Soils to introduce their importance for forest ecologists in Iran. Materials and Methods: The research was carried out at a station in the Samsakandeh mixed forest of Sari as part of the temperate deciduous forests of the Hyrcanian region. For studying collembolan fauna in Soil and leaf litter of the forest, in 2016-2017, Soil and leaf litter samples were collected from different locations by Soil core (depth 10 cm) and pitfall traps. The springtails were extracted by Berlese funnel and were identified after preparing microscopic slides with available keys. Results: In sum, 25 species belonging to 21 genera from 9 families were collected and identified as species level. The specimens of Lepidocyrtus, Sminthurinus, Neanura, Sphyrotheca and Dicyrtoma identified as genus level. Conclusion: Six species including Entomobrya obscurella (Brown, 1926), Heteromurus gigans (Mari Mutt & Stomp, 1980), Heteromurus variabilis (Martynova, 1974), Orchesella spectabilis (Stach, 1960), Pseudachorutes corticicolus (Schaffer, 1897) and Protaphorura ombrophila (Stach, 1960) were reported for the first time for Iran fauna. Two species, Neelus murinus (Folsom, 1986) and Pseudachorutes subcrassus Tullberg, 1871, are re-reported to the Samsakandeh mixed forest, 38 years after the first Cox report (1982).

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..

Introduction: The Malocclusion or misalignment of teeth affects not only oral function but also facial esthetics and the psychological well-being of patients. In addition, obsessivecompulsive disorder is a psychological disorder associated with anxiety involving 22. 5% of the population during their life. This study aimed to assess the severity of obsessive-compulsive disorder in patients having class I malocclusion with crowding. Materials & Methods: In this case-control trial, Using the Yale-Brown questionnaire, female patients with 18-22 years old of ages having class I crowding malocclusion and referring to orthodontic department of Azad Dental school enrolled in the trial as the case group (n = 60). The participants with similar malocclusion without reference for orthodontic treatments followed up as the control group (n = 60). The obtained data by Yale-Brown questionnaire classified the obsessive-compulsive disorder in the participants into four groups of mild, fairly mild, moderate and severe levels. The results of the two groups were analyzed using the Chi-square test (p value < 0. 05). Results: In malocclusion patients referring for orthodontic treatments, 19 (31. 7%) had mild OCD; 7 (11. 7%) had fairly mild OCD; 23 (38. 3%) had moderate OCD and 11 (18. 3%) showed severe OCD. These values were 28 (46. 7%); 12 (20. 0%); 15 (25. 0%) and 5 (8. 3%) for malocclusion patients not referring for orthodontic patients respectively. No significant differences were found among 2 groups regarding severity of OCD (p value = 0. 07). Conclusion: In terms of the severity of OCD, there were no significant variations between malocclusion patients with and without referring for orthodontic treatments.

Aggregate stability as a basis of sustainable Soil management is greatly influenced by the interaction of various organic materials and microorganisms. The aim of this research was to investigate the effect of simultaneous application of organic residues and its decomposing microorganisms on the stability of Soil aggregates in two Soils with different textures. An experiment was conducted using a factorial arrangement in a completely randomized design with 18 treatments and 3 replications (54 pots). Factors included Soil texture: sandy loam (SL) and clay loam (CL), organic residues: no application (control), cow manure 2% (w/w), wheat straw 2% (w/w), and inoculation with microorganisms: no inoculation (control), inoculation of Trichoderma sp., and Bacillus sp. After applying the treatments, the pots were placed in the incubation conditions (laboratory temperature and 50 to 75% of the field capacity) for 6 months. Measurements were taken for mean weight diameter, geometric mean diameter (GMD), and tensile strength of Soil aggregates, fractal dimension, water stable Soil aggregates, organic carbon (OC) content, pH, Soil electrical conductivity and microbial basal respiration (MBR). Mean comparisons for the effect of Soil texture × organic residues × microorganisms on OC and GMD showed that the highest values (6.32% and 1.95 mm, respectively) was obtained in clay loam Soil treated with cow manure inoculated with Bacillus sp. Comparing Soil textures separately, the highest amount MBR values (0.44 and 0.26 µgC-CO2 g-1 day-1 for CL and SL Soils, respectively) were obtained in the Bacillus inoculated-cow manure treatment. Overall, cow manure had a greater effect on improving Soil properties compared to wheat straw, and Bacillus bacterium had a greater effect compared to Trichoderma fungus inoculation, particularly in improving Soil structure stability. This effect was most noticeable in sandy Soil.