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The aim of this paper deals with the study of the Horn matrix function of two complex variables. The convergent properties, an integral representation of H2(A,A′,B,B′;C;z,w) is obtained and recurrence matrix relations are given. Some result when operating on Horn matrix function with the differential operator D and a solution of certain partial differential equations are established. The Hadamard product of two Horn’s matrix functions is studied, certain results as, the domain of regularity, contiguous functional relations and operating with the differential operator D and D2 are established.

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DFT with B3LYP/6-311++G(d,p) level were used for all calculations in this work. In biological system, 5-FU- 3H2O has the highest stabilization energy compared to 5-FU- 3NH3, 5-FU dimer, and 5-FU monomer. The chemical interactions of 2′-deoxyribose radical with uracil and 5-FU radicals to form 2′-deoxyuridine and 2′-deoxy-5-fluorouridine show that the difference in stabilization energies, ΔE, for their formation are quite low which facilitates the exchange reactions in DNA structure. Size, shape density distributions, and chemical reactivity sites of 5-FU were obtained by mapping electron density isosurface with electronic surface. Additionally, the intermolecular hydrogen bonding in 5-FU (sugarphosphate) backbone system was simulated by NBO analysis to describe the role of intermolecular hydrogen bonding on the structure and chemical reactivity of 5-FU in biological systems. Molecular docking study of the interaction between 5- FU and human serum albumin (HSA) indicated that 5-FU binds to HSAwith low affinity and low specificity compared to other anticancer drugs.

Text detection from scene images is a challenging topics because of low resolution, complex background and font/font size variations. In this paper, we design a method to detect text based on Naïve Bayes classifier and connected component analysis. We used Naïve Bayes classifier to convert original gray level image into binary image, then connected component analysis is used to identify candidate text regions. In the last step we use empirical rules to determine threshold which used to discard non-text regions and keep the text regions. The proposed method compares between three classifiers outcome; the first is based on Otsu method, the second classifier outcome is derived using Naïve Bayes classifier based on mean feature and standard deviation feature, we named this method Bayes_Two_Features or shortly Bayes2. The last classifier outcome is derived using Naïve Bayes classifier based on just the mean feature, we named this method Bayes_Single_Feature or shortly Bayes1. Otsu’s method is used to convert grayscale image to binary image by assuming that image contains two classes; foreground and background. Experimental results show that Bayes2 classifier outperforms the other two methods, in the case of big letters especially when these letters are in non-horizontal and skewed form.

Text detection from scene images is a challenging topics because of low resolution, complex background and font/font size variations. In this paper, we design a method to detect text based on Naïve Bayes classifier and connected component analysis. We used Naïve Bayes classifier to convert original gray level image into binary image, then connected component analysis is used to identify candidate text regions. In the last step we use empirical rules to determine threshold which used to discard non-text regions and keep the text regions. The proposed method compares between three classifiers outcome; the first is based on Otsu method, the second classifier outcome is derived using Naïve Bayes classifier based on mean feature and standard deviation feature, we named this method Bayes_Two_Features or shortly Bayes2. The last classifier outcome is derived using Naïve Bayes classifier based on just the mean feature, we named this method Bayes_Single_Feature or shortly Bayes1. Otsu’s method is used to convert grayscale image to binary image by assuming that image contains two classes; foreground and background. Experimental results show that Bayes2 classifier outperforms the other two methods, in the case of big letters especially when these letters are in non-horizontal and skewed form.

Text extraction from scene images is a defy subject in light of low resolution, complex background and textual style/text size varieties. In this paper, we design a scheme to detect text based on shape features like Euler Number, a number of pixels for each region which candidate to be a character and vertical distances as a geometric feature between these regions. We divide these features into base features to collect the text regions, and the other features as a filter to discard the non-text regions. We use some threshold with the features either those to extract text regions or to discard non-text regions. The proposed method outperforms some existed method through the basis metric.

The distribution of the natural radioisotopes 238U, 226Ra, 232Th, and 40K in addition to their radiological parameters in granitic rock samples from five different localities (Gebel El-Missikat, Gebel El-Gidamy, Gebel Ria El-Garra, Gebel El-Aradiya, and Gebel Kab Amira) in the central area of the Eastern Desert, Egypt, was measured using high purity germanium (HPGe) detector-based γ-spectrometry. The average activity concentrations of 238U, 226Ra, 232Th, and 40K in all five studied areas are higher than the corresponding global average values. The highest average activity concentrations of 238U and 226Ra were observed in Gebel El-Missikat, whereas the highest average value of 232Th activity concentration was found at Gebel El-Gidamy, and the highest concentration of 40K was obtained at Gebel El-Aradiya. The radiological hazard parameters radium equivalent (Raeq), external hazard index (Hex), internal hazard index (Hin), absorbed dose rate (ADR), annual effective dose rate (AEDR) outdoors, annual gonadal dose equivalent (AGDE), and excess lifetime cancer risks (ELCR) were calculated to assess the radiation hazards associated with the rock samples. The average values of these parameters are higher than the recommended reference levels. The obtained data provide a valuable future database for estimating the impact of radioactive contamination in the studied area and in the places where the rocks are used.