محمدرضا آزاد

Actual evapotranspiration (ET) is one of the most important and complex components of the water balance. In recent years, various remote sensing techniques and algorithms have been developed which provide a cost‐effective and reliable estimate of actual ET. In this research, the spatial distribution of actual ET at the basin scale was estimated based on SEBS algorithm and world-known information data sources which are rarely used in Iran. The estimated actual ET values were compared to the results of well-known SEBAL algorithm and the SWAT hydrological model. The study shows that the SEBS algorithm has overestimated actual ET in comparison with SEBAL algorithm. The primary cause of differences between two models is in their algorithms for calculating sensible heat. Moreover, SEBS algorithm is highly sensitive to the air temperature. SEBAL is a more complex and reliable method, but it needs reliable ground-based weather data. On the other hand, SEBS does not depend on ground-based data and its results could be acceptable under limited data condition.

Wind erosion is a phenomenon that causes severe environmental changes in arid and semi-arid climates. As surface soil texture is very effective in soil erodibility, identifying soil erodibility index is important and efficient. Mismanagement greatly contributes to the development of wind erosion. The velocity that makes the first particles of soil move from the surface is called the erosion threshold speed. Measuring the factors involved in wind erosion has always been difficult and costly. Therefore, using wind tunnels is suggested as an alternative method. This study investigated the physical and chemical properties of soil and their effects on wind erosion.

The Meybod wind canal is located at 32° 07ʹ 00"- 32° 11ʹ 00" and 35° 56ʹ 00"-54° 06ʹ 00". Using satellite images derived from Google Earth and the GIS software and the data gathered via field visits, a study border was designated for the region. Based on the area’s characteristics and the existing facies, a forty-points sampling network was randomly applied to the study area. As for the threshold speed test, first the wind erosion measuring device was placed on the desired point, and the wind speed was increased slowly to reach the erosion threshold speed; then the intended samples were collected from the surface soil (0-5 cm of soil surface). The soil’s physical and chemical properties including sodium, calcium, magnesium, organic carbon, organic matter, salinity, sodium absorption ratio, sand, clay and silt, gravel percentage, as well as soil moisture and texture were measured in the laboratory. In the next step, the Weka 3.8 software was used to determine the role of each physical and chemical parameter on the erosion threshold speed.

 Land use Using the decision tree algorithm, the relationship between land use characteristics of all points with threshold speed was investigated and the results were extracted. The effect of each parameter on the velocity of the erosion threshold was also obtained. Data mining results showed a high correlation between land use parameters and the erosion threshold speed. It was also found that the land use characteristics had a greater impact on the secondary threshold speed.  Physical parameters The results of data mining indicated a significant correlation between physical parameters and the threshold speed. According to the obtained statistical results, it was found that physical properties had the greatest effect on the secondary threshold speed. Therefore, the secondary threshold velocity had been used to examine the correlation and trend.  Chemical properties: The results of data mining suggested a high correlation between chemical parameters and the threshold speed. According to the obtained statistical results, it could be found that chemical properties had a greater effect on the secondary threshold speed; Therefore, to investigate the correlation and the effect of each parameter on the threshold speed, the secondary threshold speed was used. Based on the significant correlation between threshold velocity and erodibility index, it was found that the erodibility index had an effect on the erosion threshold speed. It was also found that the threshold speed decreased with an increase in erodibility index.

This study investigated the effect of physical and chemical properties, and land use on erosion threshold speed using data mining with decision tree algorithm. Moreover, the SPSS software was used for discovering the correlation between those factors and erosion threshold. The results of land use data mining showed that land use characteristics, including surface pavement, cultivation status, and canopy status affected the threshold speed. The results of physical properties’ data mining indicated that soil saturation percentage, Special Weight and sand and silt percentage, soil texture, surface gravel percentage, and moisture were respectively effective up to 40%, 20%, 90%, 30%, and 100% on the threshold speed. On the other hand, the results of chemical properties’ data mining suggested that the sodium adsorption ratio could be effective up to 90% on the threshold speed. It was also found that organic carbon and organic matter were 100% effective on the erosion threshold rate. However, calcium and magnesium were found to affect the erosion threshold only by 10%. This study’s findings are consistent with those found by Lee (2007), Lee et al. (2008), Mahmoudabadi and Rajabpour (2017), Azimzadeh et al. (2002) and Nourozzadeh Haddad and Bahrami (2015). Physical parameters’ statistical results showed that parameters such as the percentage of gravel, silt, and sand had the greatest effect on the velocity threshold, and that the special weight and clay percentage were least effective in this regard. These findings are consistent with those found by Zare Arnani (2014), Azimzadeh et al. (2004). Furthermore, the statistical results of soil’s chemical parameters suggested that sodium and magnesium had the least effect on wind erosion threshold speed, while the highest impact belonged to the percentage of organic carbon and organic matter, which could be attributed to the high adhesion of soil particles in the presence of organic matter and organic carbon. These findings are consistent with those found by Ekhtesasiet al. (2003), Azimzadeh et al. (2004) and Zahrabi et al. (2019).

In this paper we are used as two different approaches; wavelet transformation and adaptive bandwidth in kernel method in upscaling process of geomechanical parameters of the reservoir. Geomechanics in oil field have been investigated compressive strength parameters, Young's Moduli, Bulk Moduli and shear Moduli to determine the quality of reservoir and rock as well as the effect of rock resistance and stress on the behavior of formations as a result of oil activities. The geomechanical parameters of the reservoir rock are calculated using petrophysical logs such as acoustic and porosity log. Identifying uniform zones and classifying rock quality requires looking at geomechanical parameters along a well. Upscaling can be used to ease the use of this classifier. In the wavelet theory, after the analyze or the desired signal to the desired level, the upscaled signal will be obtained from the composition of the approximation section of the same level and the remaining samples of the coefficient of detail. This is the same as multiresolution upscaling. In upscaling using the bandwidth of the kernel function, the threshold or bandwidth is defined which is in fact a function of the geomechanical parameter variability. Adaptive bandwidth method can provide a good model upscaling of cells. In areas of high variability, by choosing optimal bandwidth, the cells remain fine, and vice versa, in areas with smooth changes, the number of cells will be merged more together. Comparison of the results of the two methods is observed. Under identical conditions, the upscaling error of the upscaled-optimized model with the kernel bandwidth method is about 1.4 wavelet transforms, and it is also possible that according to the probable error rate, depending on the threshold and appropriate bandwidth can be used to determine the number of upscaled block of the simulated model according to the computational time.

Lizards have significant roles in life cycle and are related to humans either directly or indirectly. Identifying of the fauna of a region is the most necessary and the most significant biological and fundamental research in it. Mazandaran Province has diverse biological conditions because of its geographical location and special ecological conditions, the proximity of the sea to the mountains and diverse vegetation. Samples were collected in Mazandaran and bio-systematic study of Cyrtopodionscabrum was manipulated there as well from March, 2012 to June, 2013. The samples were collected by hands or sticks and after being photographed, they were fixed in formalin 4% and ethyl alcohol 75% and were identified using valid sources. Seven samples belonging toCyrtopodionscabrum, including 2 female and 5 male samples, were collected in the current study. Then, morphologic, morphometric and meristic characteristics of the samples were studied. Cyrtopodion scabrum has been collected and reported for the first time in Mazandaran Province in this study.

According to this reality that iron bulks because of having ferromagnetic minerals، they have high magnetic intensity، in mining explorations most usual geophysical method suggested to explore these resources is magnetic method. Basically in order to process and interpretation of magnetic anomaly maps several methods be used of which most of these methods are based on try and error. One of usual geophysical data refining or filtration methods is upward continuation which will be applied in this study. Upward continuation can be used to separate a regional and local magnetic anomaly from the observed magnetic. One of problems that we encounter it through this filtration is determining optimum height of upward continuation. We use a practical method to derive an optimum height for upward continuation. In this study magnetic data of northern anomaly of Mansoorabad region of Yazd was investigated. According to past studies in order to handle geophysical investigations for carry out magnetic investigation a region of 450x700 square meters were adapted. Data acquisitions of magnetic data in exploration grid were done via 10 meter distance for both profiles and measuring stations. Outcrops of iron in the form of hematite in Ooliti''c''s limestone rocks are evident. In order to separation of regional anomaly the usual upward continuation were used firstly. Using this method a map of 35 meter height were detected as regional anomaly. In the following in order to more accurate interpertation and process and also determination of height of upward continuation filter، one of practical methods of which is based on cross correlation of two successive heights were used. With the aid of this method without any comparison of several maps related to various heights and without any interference of a body one can obtain suitable upward continuation filter to determine regional magnetic anomaly and consequently by subtracting this magnitudes from observed overall anomaly one can estimate map of remained anomaly that could be a better evident of local anomaly in that region. Cross correlation for upward continuation of heights from 30 meters to 40 meters by the distance of 2 meters were calculated in which the height of 39 meters were selected as optimum height of investigated data. The map of upward continuation which was calculated by this height for magnetic data of Mansoorabad region showed the best fitting with regional anomaly of data based on used method. Also the map of remained data will be obtained according to this height. In terms of geology mineralization of iron that was formed in this region is sedimentary iron type of Oolitic which were created in the time limit of Paleozoic age. Considering location of determined anomaly and geology map of region، observed that this kind of mineralization of iron in limestones by the pattern of Oolitic were created. After investigation and coincidence of magnetic anomaly in studying area، it is determined that the iron bulks were the reason of anomaly. Depth continuations of this kind of anomalies are different and are continued to the depth of 80 meters.

Considering this fact that chromite masses possess high density, the gravity method is the most common geophysical method suggested for prospecting of chromite deposits. Usually, the result of superposition of several factors is observed in the acquired datum, which includes different spatial scales. The observed potential field could be assumed as the sum of the regional field, the residual field, and noise. Despite filtering out several factors to obtain a bouguer anomaly map from gravity survey data, the obtained values are still the result of superposition of several components; these components are different from the view points of scale and importance. Definition and recognition of these components are essential in interpretation of geophysical surveys. There are various methods for processing and interpretation of bouguer gravity anomaly maps. These methods, e.g. potential field filters, are mostly based on mathematical analyses using trial and error technique. There are many different methods concerned with separation of the regional and residual components from the gravity map. Upward continuation technique is frequently used to identify regional anomalies and gravity variations of deeper recourses. The upward continuation is a general filter in processing geophysical data that can remove or considerably lessen the contribution of high-frequency, near-surface, shallow causative bodies from the gravity field, resulting in a smooth field reflecting the deeper causative bodies and/or density structures. This method is applied to separate a regional anomaly from the observed gravity. This filter is a low pass filter since the residual component, which is concerned with local anomalies, can be assumed as high frequency part of the signal. The main weakness of usual potential field filters comes from the fact that they cannot take into account spatial structure of components while filtering them. Spatial structure of a variable is an indicator of the amount of data correlation with respect to the distances between the data. Factorial Kriging analysis (FKA) is principally a geostatistical filtering method that includes classic factorial analysis and geostatistics. The FKA method consists of three basic steps: variogram, factorial analysis and Kriging/co-Kriging. This method computes of the experimental variograms to choose the number of spatial scales to be considered and fit by theoretical models, (generally linear model of regionalization/coregionalization), applies the decomposition method on variance-covariance/variogram matrix of spatial components (generally principle component analysis/spectral decomposition), estimats the regionalized factors in order to determine the relative contribution of each factor for the estimation of a particular location and mapping. Factorial Kriging decomposes the raw variable into as many components as the identified structures in the variogram. The basic step in FKA is experimental variogram calculation and fitting a valid model to this variogram. If the variogram is nested, it can be represented as a combination of several individual components variograms. The FKA method includes two types of univariate and multivariate. In the case of a geophysical variable, the univariate type is applied. Therefore, the variogram in this case can be written as a linear combination of its components. In this research, the gravity data, acquired from Faryab chromite mine area, are processed and interpreted using the FKA method. Based on this study, three components, which may represent regional, local, and noise components are defined and filtered based on spatial structure study. Moreover, two locations are proposed for further detailed exploration considering the extracted local component map. Also, the gravity data are processed using potential field filters. In this regard, different heights are considered in the upward continuation filter method applying on the gravity data, and then, the results are shown in the relevant maps. Low value gravity anomalies can be interpreted as the geological structures having low density or special geometric shapes such as a geo-anticline. High value gravity anomalies can be considered as densie masses like chromite lenses. Finally, in this research work, the obtained results from applying the FKA method on the gravity data are compared with the potential field filtering results using the upward continuation filter method. The basic difference between the upward continuation and the FKA methods is that the latter method takes into account the spatial structure of the data while the former does not. This study clearly indicates the capability of the FKA method in filtering gravity data.

Statement of Problem: One of the greatest problems in metal –ceramic restorations is debonding of porcelain from dental alloys. Production of dental alloys by Iranian companies necessitates the evaluation of physical and handling properties of these products. In this study the bond strength between porcelain and two types of base metal alloys, Supercast (with beryllium) and Minalux (without beryllium) was investigated. In this experimental study 10 cylindric bars from each base metal alloy were prepared. The bars were degassed and porcelain was applied around them in a disc form (8 mm diameter and 2 mm thickness). The bond strength of porcelain to metal bars was tested with the shear strength test by Instron. Data were analyzed with student t-test and P<0.05 was considered as the limit of significance. The mean failure load was 71.58±6.4 KgF for Supercast and 67.34±5.48 for Minalux alloy. The bond strength of Supercast and Minalux were 55.85±4.99 MPa and 52.54±4.27 MPa respectively. The difference was statistically significant (P0.001). This study showed that nickel-chromium-beryllium alloy (Supercast) produced significantly better ceramometal bonding than nickel chromium alloy without beryllium (Minalux).