The biological activities of some ternary nickel complexes with a Schiff base obtained from 4-dimethylaminobenzaldehyde and 2-aminophenol have been reported. The Schiff base ( HL1) acts as a primary ligand whereas, anthranilic acid ( HL2), 2-nitroaniline ( HL3), alanine ( HL4) and histidine ( HL5) act as secondary ligand or co-ligand. The anticancer activity of these compounds was studied against human colon carcinoma (HCT-116), human hepatocellular liver carcinoma (HEPG-2) and human breast carcinoma (MCF-7) cell lines. As per the results, the compounds were active against the cell lines. The antioxidant activity of the same compounds was evaluated using DPPH (1,1-diphenyl-2-picryl-hydrazyl) radical scavenging and compared with ascorbic aci

The research addressed an analytical field investigation of the locality of meander, the factors responsible of the locality of the meander at certain points of the stream other than others, and the role sequence of these factors in the formation process.
The research revealed that the location of forming the meander was associated closely with the scale structural composition of the bank materials from which the first stage of forming the curved stream, for the inhomogeneous or non-identical opposite banks in their scale structural composition saw an activity of differential corrosion, while the homogeneous and identical opposite banks in their scale structural composition saw an identical corrosion activity in its intensity at both

Everybody is connected with social media like (Facebook, Twitter, LinkedIn, Instagram…etc.) that generate a large quantity of data and which traditional applications are inadequate to process. Social media are regarded as an important platform for sharing information, opinion, and knowledge of many subscribers. These basic media attribute Big data also to many issues, such as data collection, storage, moving, updating, reviewing, posting, scanning, visualization, Data protection, etc. To deal with all these problems, this is a need for an adequate system that not just prepares the details, but also provides meaningful analysis to take advantage of the difficult situations, relevant to business, proper decision, Health, social media, sc

New types of hydrodesulfurization (HDS) catalyst Re-Ni-Mo/ γ-Al₂O₃ was prepared and tested separately with two prepared conventional HDS catalysts (Ni-Mo/ γ-Al₂O₃ and Co-Mo//γ-Al₂O₃) by using a pilot plant hydrotreatment unit. Activities of three prepared hydrodesulfurization catalysts were examined in hydrodesulfurization (HDS) of atmospheric gas oil at different temperatures 275 to 350 °C and LHSV 1 to 4 h^-1, the reactions conducted under constant pressure 40 bar and H₂/HC ratio 500 ml/ml .Moreover, the hydrogenation of aromatic (HAD) in gas oil has been studied. HDS was much improved by adding promoter Re to the Ni-Mo/Al₂O₃

New types of hydrodesulfurization (HDS) catalyst Re-Ni-Mo/ γ-Al2O3 was prepared and tested separately with two prepared conventional HDS catalysts (Ni-Mo/ γ-Al2O3 and Co-Mo//γ-Al2O3) by using a pilot plant hydrotreatment unit. Activities of three prepared hydrodesulfurization catalysts were examined in hydrodesulfurization (HDS) of atmospheric gas oil at different temperatures 275 to 350 °C and LHSV 1 to 4 h-1, the reactions conducted under constant pressure 40 bar and H2/HC ratio 500 ml/ml .Moreover, the hydrogenation of aromatic (HAD) in gas oil has been studied. HDS was much improved by adding promoter Re to the Ni-Mo/Al2O3 catalyst. The results showed that Re-Ni-Mo/ γ-Al2O3 have more activity in desulfurization than Ni-Mo//γ-Al2O3

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number