The complexes Shiff base  and  mixed ligands complexes of bipyridyl and Schiff base 1,5-dimethyl-4-(5-oxohexan-2-ylideneamino)-2-phenyl-1H-pyrazol-3(2H)-one (L) with Cr(III), Mn(II), Fe(II) and Co(II) were prepared. The compounds have been characterized by FT-IR, UV-Vis, mass and ¹H and ¹³C-NMR spectra, magnetic moment, elemental microanalyses (C.H.N.), chloride containing, atomic absorption and molar conductance. The studies made are indicating towards octahedral geometry for these complexes. Hyper Chem-8 program has been used to prediction structural geometries of compounds in gas state, the heat of formation, binding energy, total energy and electronic energy and dipole moment at 298^oK. The c

Mixed ligand complexes of bivalent metal ions, viz; Co(II), Ni(II), Cu(II) and Zn(II) of the composition [M(A)2((PBu3)2]in(1:2:2)(M:A:(PBu3). molar ratio, (where A- Anthranilate ion ,(PBu3)= tributylphosphine. M= Co(II),Ni(II),Cu(II) and Zn(II). The prepared complexes were characterized using flame atomic absorption, by FT-IR, UV/visible spectra methods as well as magnetic susceptibility and conductivity measurements. The metal complexes were tested in vitro against three types of pathogenic bacteria microorganisms: (Staphylococcus, Klebsiella SPP .and Bacillas)to assess their antimicrobial properties. Results. The study shows that all complexes have octahedral geometry; in addition, it has high activity against tested bacteria. Based on th

Mass transfer has been studied at rotating cylinder electrodes fabricated with spiral-wound woven-wire meshes using reduction of copper as a test reaction. The experimental data were correlated by an empirical expression between the Sherwood number and the Reynolds number, both regarding the hydraulic diameter as a characteristic length. It was found that the Sherwood number was dependent upon the Reynolds number to the power of 0.521. An enhancement factor was adopted to compare the efficiency of the new rotating cylinder electrode with previous three-dimensional rotating cylinder electrodes. The results showed that the new type has a mass-transfer enhancement factor 2.3 times higher than those obtained with smooth rotating cylinder electr

Co+2, Ni+2, Cu+2 as well Zn+2 compounds mixed ligand from 8-hydroxyquinoline(8-HQ) also tributylphosphine (PBu3) have been attended at aquatic ethyl alcohol for (1:2:2) (M:8-HQ:PBu3). Produced complexes have been identified by utilizing atomic absorption flame, FT-IR as well UV-Vis spectrum manners also magnetic susceptibility as well as conductivity methods. At addendum antibacterial efficiency from the ligands as well complexes oboist three species about bacteria have been as well examined. Ligands and their complexes show good bacterial efficiencies. Of the gained datum the octahedral geometry was proposed into whole prepared complexes

Water is the basis of the existence of all kinds of life, so obtaining it with good quality represents a challenge to human existence and development especially in the desert and remote cities because these areas contain small populations and water purification requires great materials and huge amounts of fossil fuels resulting pollution of the environment. Cheap and environmentally friendly desalination methods have been done by using solar distillations. Passive solar stills have low yields, so in this research, the problem is overcome by connecting four heat pipes which are installed on the parabolic concentrator reflector with passive solar still to increase the temperature of hot water to more than 90°C, as a resul

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