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Geological mapping of exposed geologic units of Earth surface is a common and important activity for geologists. This process is the first step of geological prospecting. Remote sensing can provide useful driven data for further studies and also it reduces the time and cost of this process. Sometimes it is possible that some lithologies have similar spectral responses while they have different surficial texture properties. Geological units of the Earth surface are more separable by including their textural properties along with their spectral behaviour in remote sensing so authors used spectral-Radar data integration with novel idea which is named Radar data resultant vector in this study. In this paper, two different neural network methods (Neural Pattern Recognition and Neural Net Fitting) were implemented in Matlab environment for lithological classification using two different input datasets, namely (1) only multispectral data and (2) integrated Radarmultispectral data. The reason was to evaluate the performance of Spectral-Radar fused data in lithological classification in comparison with the spectral data alone. The results show that integrated Radar-multispectral data results in better classification of lithological units due to the integration of surficial textural parameters and spectral responses of such surficial features. The results also showed that the Neural Pattern Recognition method (NPRTool) performed better than Neural Net Fitting (NFTool) method. The results further show that, among the three different algorithms of the Neural Net Fitting method (i.e., Levenberg-Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient), the Levenberg-Marquardt performed best. [ABSTRACT FROM AUTHOR]

Heavy metals Zn, Cu, Pb, Cd concentration in. sediments of the Iranian waters of the Caspian Sea was measured in fall 2001.Samples were collected from transects along the Iranian coastline in five stations lying between Astara (48o52', 38o26') up to Kiyashahr (49o 53', 37o27'). Metals were extracted from sediments by digesting with hydrofluoric and hydrochloric acid. Metals concentrations were measured using the Atomic Absorption Spectrophotometer. Reliability of results was tested using Soil-7, a certificated reference material (CRM). Sediment samples were-:also collected from each station to determine grain Size. The results showed that except for Cd concentration which was measured at 4.5mg g-1 dry weight, other values were lower than the Effects Range Low (ERL) (1.2mg g-1 dry weight) based on the Sediment Quality Guidelines from NOAA, USA for Cd. Also, the highest concentration determined for Cu (19.55mg g-1 dry weight) in this study was lower than the ERL (34mg g g-1 dry weight) value determined by NOAA for Cu. The highest concentrations for Pb and Zn in the present study were 25.7mg g-1 dry weight and 54.5mg g-1 dry weight, respectively that were lower than the ERL values (pb=47mg g-1 dry weight and Zn=124mg g1 dry weight) declared by NOAA for these metals. It is evident from the present study that heavy metals concentrations in sediments in the study area were lower than Effects Range Low values for these metals. We conclude that the studied metals are not threatening to the environment at the present time.

Microgrids (MGs) are designed to serve their hosting critical load in an island mode in case of major events. However, in normal conditions when MGs are in a grid-connected mode, they may face an opportunity to achieve financial profits through optimization of the operation of energy resources and proper participation in wholesale markets. This paper proposes a model to optimize the participation of MGs in the markets and operation of energy resources. Since MGs usually host renewable energy resources, making decisions without considering uncertainties may put MGs at risk. Therefore, the model considers uncertainties associated with the generation of renewable Distributed Generation (DGs), demand, and market prices via robust optimization technique. The model is formulated as a bi-level max-min optimization problem. The problem is solved in two iterative steps. In the first step, a Genetic Algorithm (GA) finds the worst situation of uncertain parameters such that MG profit is minimized. Then, a mixed-integer linear problem is solved to maximize the profit over MG decision variables considering the values determined in the first step. The steps are iterated to reach convergence to the best solution. To confirm the performance of the approach, it is applied to a typical MG and the results are reported. [ABSTRACT FROM AUTHOR]

In this paper, we present a split-step Rosenbrock type method for stiff stochastic differential systems. The method is proved to be mean-square (MS) convergent with strong order 1 2 . For one- and two-dimensional Itô test equations with multiplicative noise, we analysis asymptotically MS stability and plot asymptotic MS stability regions. Numerical examples and simulations are given to illustrate the effectiveness of theoretical results. [ABSTRACT FROM AUTHOR]

Degradation and disintegration of concrete depend on the formation of cracks and micro cracks intensively. With increase loading, micro cracks are linked together and form cracks. To solve the problem and to provide the homogenous condition, a series of thin fibers having been spread through the volume of concrete are used in the several last decades and they are called as fibers. In the study, the steel fibers integrated in the different percentages of weight have been investigated. The performance of fibers has been studied how to increase compressive strength, tensile strength, and bending strength. To survey compressive strength, tensile strength, and bending strength in the produced concrete, three plans of mixtures including the different percentages of the steel fibers have been examined. The results show that compressive strength in the concrete reinforced with steel fibers relies mainly on the quality of mortar. The added steel fibers cause the inconsiderable changes in the compressive strength of concrete. The results demonstrate that the concrete reinforced with steel fibers increase tensile strength considerably. The more the volume of steel fibers is, the more tensile strength is. Pozzolanic materials used in the specimens reinforced in steel fibers improve tensile strength. To investigate bending strength of the specimens reinforced with steel fibers, the study has used 4-point loading system. Generally, steel fibers used in the concrete increase bending strength of the concrete. The results indicate the increased steel fibers enhance bending strength in three plans of mixtures. Among the specimen reinforced with steel fibres, the most mechanical properties are related to the plans including 1, 1.5, and 2 percentages of dramix hooked steel fibers in the study. To examine crack pattern of the matrix tensile specimen reinforced with the different percentages of fibers, parameters such as the number of cracks, width of cracks, and distance between them are investigated.

The study area is located in the Kerman magmatic arc in southern Iran, which is known for its world-class porphyry-type deposits. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Advanced Land Imager (ALI) visible–near-infrared to shortwave-infrared bands were used to investigate the spectral discrimination of hydrothermally altered rocks based on their mineral assemblages. Band ratioing, directed principal component analysis (DPCA), and the Spectral Angle Mapper (SAM) were applied on ASTER and ALI data for separating ferric iron-poor from ferric iron-rich phyllic alteration zones. The individual principal component images through DPCA could detect specific alteration zones dominated by minerals such as iron oxides, sericite, kaolinite, chlorite, and epidote. The phyllic zone associated with copper mineralization is generally rich in iron oxide minerals at the surface, which can be especially detected by ALI. The altered areas were sampled and studied using X-ray diffraction analysis, spectral measurements, chemical analysis, and thin-section studies. The results of this analysis have shown that more than 90% of the known copper mineralization falls within the ASTER/ALI-mapped alteration areas. These data can be useful for mapping alteration minerals related to porphyry deposits in other regions with similar geological settings. [ABSTRACT FROM PUBLISHER]

Background and Objectives Establishing an intravenous line, which is one of the most common invasive procedures in children, is a source of physical and mental stress. Since one of the responsibilities of medical staff is to take care of children pain and anxiety, attention to this matter is necessary. The aim of this study was to evaluate the correlation between pain and anxiety in children with thalassemia caused by intravenous catheters. Materials and Methods In a descriptive study, one hundred and twenty 6-12 year old children with thalassemia in Kerman attended Thalassemia Center through 2009-2010. Demographic characteristics and numerical rating scale were used for measurement of pain and anxiety. Data were analyzed by using descriptive and analytical testing and Spearman rank correlation coefficient. Results The results showed that children experienced severe to moderate pain and anxiety during injection and also reports showed a significant positive association between anxiety before the injection and pain after the injection. Conclusions Since nurses play an important role in controlling pain and anxiety especially in case of children, it would be a better and more effective strategy if they are offered necessary training in this regard. [ABSTRACT FROM AUTHOR]