Least-squares modification of extended Stokes’ formula and its second-order radial derivative for validation of satellite gravity gradiometry data

The gravity anomalies at sea level can be used to validate the satellite gravity gradiometry data. Validation of such a data is important prior to downward continuation because of amplification of the data errors through this process. In this paper the second-order radial derivative of the extended Stokes’ formula is employed and the emphasis is on least-squares modification of this formula to generate the second-order radial gradient at satellite level. Two methods in this respect are proposed: (a) modifying the second-order radial derivative of extended Stokes’ formula directly, and (b) modifying extended Stokes’ formula prior to taking the second-order radial derivative. Numerical studies show that the former method works well but the latter is very sensitive to the proper choice of the cap size of integration and degree of modification.     

Time effects on dynamic soil properties under random excitation conditions

Two types of clayey soils, a kaolinite and a bentonite, were tested using a resonant column apparatus under random excitation conditions. The concept of root mean square (rms) strain was utilized for the purpose of strain calculations during random loading. The conventional estimator of the transfer function was used for random vibration analysis. The effect of confinement duration (at a constant pressure) on dynamic soil properties, namely damping and shear modulus, was evaluated. The results indicate that for both cohesive soils, the effect of time was less pronounced during random vibration than sinusoidal loading at the same rms strain. This effect is however more pronounced when the peak shearing strain of sinusoidal loading is considered. Furthermore, time effects were more pronounced at low strain levels than at high strain levels.     

Estimation from incomplete data files based on magnitude-frequency relation for earthquakes

The problem of incorporating the available seismological information provided by the major events of the historical catalog with those for the short period of instrumental data is investigated. Assuming that the frequency-magnitude law of Gutenberg and Richter is valid for both periods, an estimation procedure for the main parameter of this law and the rate of earthquake occurrence for historical period is presented. Application of the proposed method is demonstrated, using both real and simulated data. An extension to allow for variable quality of complete data with different magnitude values is also included.     

Assessment of copper,cobalt and zinc contaminations in soils and plants of industrial area in Esfahan city (in Iran)

This paper discusses the artificial groundwater recharge effect of high-infiltration basins. For this purpose, the hydrogeological parameters of the study area are collected to construct a conceptualized physical model. The TOUGH2 numerical simulation software is then used to simulate the infiltration behavior of an artificial recharge into an underground aquifer. Four wells (MW-1, MW-2, MW-3, and MW-4) are observed at the field site, after which the groundwater levels are compared with the simulation results. It is found that good agreement exists between the observed and numerical data for MW-1 and MW-2. However, the observed groundwater level in MW-3 is higher than the simulated level. We also find that MW-3 is at the edge of the artificial recharge lake, and that the high groundwater level may well be the result of a portion of the infiltration load following the well border into the well screen. Conversely, the groundwater level in MW-4 is found to be lower than in the simulated well due to local permeability in the well location. Finally, the numerical results predict that the groundwater level will attain a steady state at approximately 47 h after the onset of infiltration.     

Chemical identification,antioxidant, cholinesterase inhibitory,and cytotoxic properties of fucoidan extracted from Persian Gulf Sargassum angustifolium

Marine macroalgal sulfated fucose-containing polysaccharides, like fucoidan, have drawn significant attention due to their biotechnological potentials, such as anti-cancer, antioxidant, and anti-cholinesterase activities. The fucoidan derived from brown macroalgae Sargassum angustifolium species (FSA) was investigated for its cytotoxic effects and alterations in cell proliferation, and cell cycle-related gene expression in the present study occurred on NB4 cell line. The results showed that FSA would induce p53, p21, pro-apoptotic genes and increase expression of the p15 gene as a cell arrest marker. Also, FSA inhibited the anti-apoptotic effect of the Bcl-2 gene and decreased dnmt-1 gene expression. FSA significantly exhibited potent 2, 2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity (p<0.05) with an IC₅₀ value of 0.157 mg/mL and showed moderate anti-acetylcholinesterase activity with an IC₅₀ value of 1.20 μg/mL. These results indicated the potential of FSA for the development of therapeutic or preventive agents of cancer and Alzheimer’s disease mainly through cytotoxic effect and AChE (acetylcholinesterase) inhibition as well as additional antioxidant capacities.     

Selection of Less Biased Threshold Angles for SAM Classification Using the Real Value–Area Fractal Technique

The accuracy of classification of the Spectral Angle Mapping (SAM) is warranted by choosing the appropriate threshold angles, which are normally defined by the user. Trial‐and‐error and statistical methods are commonly applied to determine threshold angles. In this paper, we discuss a real value–area (RV–A) technique based on the established concentration–area (C–A) fractal model to determine less biased threshold angles for SAM classification of multispectral images. Short wave infrared (SWIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images were used over and around the Sar Cheshmeh porphyry Cu deposit and Seridune porphyry Cu prospect. Reference spectra from the known hydrothermal alteration zones in each study area were chosen for producing respective rule images. Segmentation of each rule image resulted in a RV–A curve. Hydrothermal alteration mapping based on threshold values of each RV–A curve showed that the first break in each curve is practical for selection of optimum threshold angles. The hydrothermal alteration maps of the study areas were evaluated by field and laboratory studies including X–ray diffraction analysis, spectral analysis, and thin section study of rock samples. The accuracy of the SAM classification was evaluated by using an error matrix. Overall accuracies of 80.62% and 75.45% were acquired in the Sar Cheshmeh and Seridune areas, respectively. We also used different threshold angles obtained by some statistical techniques to evaluate the efficiency of the proposed RV–A technique. Threshold angles provided by statistical techniques could not enhance the hydrothermal alteration zones around the known deposits, as good as threshold angles obtained by the RV–A technique. Since no arbitrary parameter is defined by the user in the application of the RV‐A technique, its application prevents introduction of human bias to the selection of optimum threshold angle for SAM classification.     

Monitoring above-zone temperature variations associated with CO2 and brine leakage from a storage aquifer

CO₂ injection in saline aquifers induces temperature changes owing to processes such as Joule–Thomson cooling, endothermic water vaporization, exothermic CO₂ dissolution besides the temperature discrepancy between injected and native fluids. CO₂ leaking from the injection zone, in addition to initial temperature contrast due to the geothermal gradient, undergoes similar processes, causing temperature changes in the above zone. Numerical simulation tools were used to evaluate temperature changes associated with CO₂ leakage from the storage aquifer to an above-zone monitoring interval and to assess the monitorability of CO₂ leakage on the basis of temperature data. The impact of both CO₂ and brine leakage on temperature response is considered for three cases (1) a leaky well co-located with the injection well, (2) a leaky well distant from the injector, and (3) a leaky fault. A sensitivity analysis was performed to determine key operational and reservoir parameters that control the temperature signal in the above zone. Throughout the analysis injection-zone parameters remain unchanged. Significant pressure drop upon leakage causes expansion of CO₂ associated with Joule–Thomson cooling. However, brine may begin leaking before CO₂ breakthrough at the leakage pathway, causing heating in the above zone. Thus, unlike the pressure which increases in response to both CO₂ and brine leakage, the temperature signal may differentiate between the leaking fluids. In addition, the strength of the temperature signal correlates with leakage velocity unlike pressure signal whose strength depends on leakage rate. Increasing leakage conduit cross-sectional area increases leakage rate and thus increases pressure change in the above zone. However, it decreases leakage velocity, and therefore, reduces temperature cooling and signal. It is also shown that the leakage-induced temperature change covers a small area around the leakage pathway. Thus, temperature data will be most useful if collected along potential leaky wells and/or wells intersecting potential leaky faults.     

Application of artificial intelligence techniques for predicting the flyrock distance caused by blasting operation

Flyrock arising from blasting operations is one of the crucial and complex problems in mining industry and its prediction plays an important role in the minimization of related hazards. In past years, various empirical methods were developed for the prediction of flyrock distance using statistical analysis techniques, which have very low predictive capacity. Artificial intelligence (AI) techniques are now being used as alternate statistical techniques. In this paper, two predictive models were developed by using AI techniques to predict flyrock distance in Sungun copper mine of Iran. One of the models employed artificial neural network (ANN), and another, fuzzy logic. The results showed that both models were useful and efficient whereas the fuzzy model exhibited high performance than ANN model for predicting flyrock distance. The performance of the models showed that the AI is a good tool for minimizing the uncertainties in the blasting operations.     

Estimation and validation of atmospheric water vapor content using a MODIS NIR band ratio technique based on AIRS water vapor products

Atmospheric water vapor validation needs simultaneous, well-defined, and independent information which are not easily available causing limitations in the development of remote sensing water vapor retrieval algorithms. This study is concerned with the retrieval of total atmospheric water vapor content and its validation. A band ratio method has been used to estimate the water vapor content based on Moderate Resolution Imaging Spectroradiometer (MODIS) Near InfraRed (NIR) data. The method uses MODIS bands 17, 18, and 19 as NIR bands and band 2 to remove the land cover reflectance. Furthermore, the Atmospheric Infrared Sounder (AIRS) has been used for both algorithm development and analysis of the results. The method has been modified to take into account the dry condition of the central parts of Iran. Using some various datasets, the method is implemented and evaluated quantitatively. The validation of the water vapor estimates has been undertaken by an analysis of AIRS data. The validation results shows error as low as 9 % for the estimated water vapor using the MODIS NIR band ratio method.