The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

The preparation and characterization of the Cu (II), Co(II), Ni(II), Zn(II), Cd(II), and Hg(II) metal complexes of heterocyclic azo ligand 2-[(4`-sulphamide phenyl) azo] -4,5-diphenyl imidazole (4-SuBAI) have been studied by elemental analysis, FT-IR and UV-Vis Spectroscopic, magnetic moment and molar conductance methods. The analytical data showed that all chelate complexes were prepared with (metal-ligand) ratio of (1:2). The general formula of these complexes was [ML2X2]. nH2O [were L=2-[(4`-sulphamide phenyl) azo]-4,5-diphenyl imidazole and X=Cl, and the octahedral geometry were suggested for these complexes .

2-(2-amino-5-nitro-phenylazo),-phenol was ready by grouping the diazonium salt of 2-aminophenol with 4-nitroaniline.Thegeometry of azo ligand(HL)was resolved on the origin of (C.H.N) analysis,1H and 13CNMR spectra, infrared spectra and UV–vis electronic absorption spectra. Dealing with the azo ligand produced with Rh+3 and La+3ataqueous ethanol for a 1:3 metal: ligand rate, and in perfect ph. The formation for compounds have been described by utilizing flame atomic, absorption,(C.H.N),Analyses, conductivity, infrared spectra and UV–vis spectral procedures. Nature in the produced compounds, have been studied, obey the ratio of mole and continuous, variance, manners, Beer's law, yielded up a concentration, rate (1×10-4- 3×10-4M),. High

Aspartate aminotransferase was purified from urine and serum of patients with type 2 diabetes in a 2 steps procedure involving dialysis bag and sephadex G-25 gel filtration (column chromatography). The enzyme was purified 346.23 fold with 1467% yield and 3.46 fold with 142.85% yield in urine and serum of patients with type 2 diabetes respectively. The purified enzyme showed single peak. The results of this study revealed that AST activity of type 2 diabetes urine and serum increased significantly (p<0.001) compared with control group.