The paper probes into minute identification of the data of the methods followed in the electronic newspapers that aim to promote terrorist organizations like Al Qaeda and ISIS to draw emotional empathy and sympathy with them.
The paper aims at identifying:
How emotional empathy was utilized by terrorists in E-newspapers.
How useful utilizing emotional empathy was in attracting supporters. The sample that is used in the paper is based on the opening articles of E-newspapers that propagate Al Qaeda and ISIS, e.g. (Sawtu el jihad) “The Sound of Fighting in the Name of God”, (Mua’skar el Battar wal Shamikha wal Khansaa) “Camps of Al Battar, Shamika, and Khansaa”, “Inspire” and (Thurwatu el Sanam, Dabiq, and Rumiyah)

Chemical analysis for evaluation of Nigella sativa L. (black cumin) seeds showed a composition of Fat 39% ; Protein 28% ; Carbohydrate 21% ; Moisture 6% and Ash 4.5% . It was found that the black seed contains the following mineral element : Magnesium 0.26 gm /100gm seed ; Calcium 0.25 gm /100gm seed and Iron 25 ?g / gm /100gm seed ; zinc 4.51?g /gm /100gm seed and Copper 3.60 ?g /gm /100gm seed. The analysis also showed that mineral element I. e. ; lead ; Cobalt ; Nickel ; Chrom ; Cadmium and Aresenic are not present . It was found that the fat of the black seed contains the following fatty acids : Myristic 2.8%; Palmtic 16.6%; Stearic 0.8 % ; Oleic 13.79% ; Linoleic 64.2% and Arachidic 1.9% .

The researchers wanted to make a new azo imidazole as a follow-up to their previous work. The ligand 4-[(2-Amino-4-phenylazo)-methyl]-cyclohexane carboxylic acid as a derivative of trans-4-(aminomethyl) cyclohexane carboxylic acid diazonium salt, and synthesis a series of its chelate complexes with metalions, characterized these compounds using a variety technique, including elemental analysis, FTIR, LC-Mass, ¹H-NMRand UV-Vis spectral process as well TGA, conductivity and magnetic quantifications. Analytical data showed that the Co (II) complex out to 1:1 metal-ligand ratio with square planner and tetrahedral geometry, respectively while 1:2 metal-ligand ratio in the Cu(II), Cr(III), Mn(II), Zn(II), Ru(III)and Rh(III)complexes

We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St