This work is based on the synthesis of Cobalt(II) and Cadmium(II) mixed-ligands compounds obtained from the reaction of N'-(4-methylsulfanyl-benzoyl)-hydrazine carbodithioic acid methyl ester as a ligand and using ethylendiamine (en), 2,2'-bipyridine (bipy) or 1,10-phenanthroline (phen) as a co-ligand. The synthesis of ligand (HL) was based on multi-steps synthetic procedure. The reaction of 4-methylsulfanyl-benzoyl chloride with hydrazine gave 4-methylsulfanyl-benzoic acid hydrazide. This compound was reacted with carbon disulfide and potassium hydroxide in methanol to yield N'-(4-methylsulfanylbenzoyl)-hydrazine potassium thiocarbamate, which upon reaction with methyl iodide resulted in the formation of the ligand. A range of physico-chemical techniques was used to characterise the new ligand and its mixed-ligand metal complexes. These include; IR, UVVis, 1H, 13C NMR, elemental micro analyses, magnetic susceptibility, atomic absorption, chloride content, and melting point. The physico-chemical analyses indicated the formation of complexes of the general formula [M(L)2X], (X = ethylene diamine (en), 2,2` bipyridine`(bipy) and 1,10 phenanthroline` (phen)), in which the coordination sphere about metal centre is octahedral.
Transactions on Engineering and Sciences
Background: The gene responsible for encoding the protein of cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) has been found to be associated with rheumatoid arthritis (RA) in different ethnic populations. But the association of +49A/G CTLA-4 polymorphism with susceptibility of RA among Iraqi Arab populations has not yet been determined. Methods: One hundred and seventy-eight patients were examined, 67 of them were males (mean age 54.71 ± 10.4 years), while 167 were examined for the control group, of whom 64 were males and the rest were females. CTLA-4 DNA genotyping was carried on to determine the +49 A/G (rs231775) polymorphism using a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Enzyme-linked immuno
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In this study, titanium dioxide (TiO2) nanoparticles incorporated with cement were synthesis by a simple casting method as a function concentration of TiO2 (0.2, 0.4, 0.8, 1, and 2 wt%). The prepared samples were characterized using the technique of Field Emission Scanning Electron Microscope (FESEM) and UV-Visible spectrophotometer, which was used to measure the adsorption spectra. The observed photocatalytic efficiency of TiO2 nanoparticles (NP) incorporated with cement was investigated by decomposing the dye methyl blue (MB) solution under sunlight irradiation. According to the slope, the value of the k constant at the best sample is 0.8wt%, k=0.8265 min-1. FESEM image of the TiO2
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The present research included synthesis of silver nanoparticle from(1*10-3,1*10-4 and1*10-5) M aqueous AgNO3 solution through the extract of M.parviflora reducing agent. In the process of synthesizing silver nanoparticles we detected a rapid reduction of silver ions leading to the formation of stable crystalline silver nanoparticles in the solution.
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A simple indirect spectrophotometric method for determination of mebendazol in pure and pharmaceutical formulation was presented in this study. UV-Visible spectrophotometry using the optimal conditions was developed for determination of mebendazole in pure drug and different preparation samples. The method is based on the oxidation of drug by nbromosuccinimide with hydrochloric acid and the left amount of oxidizing agent was determined by the reaction with tartarazine and the absorbance was measured at 428 nm. Calibration curves were linear in the range of 5 to 30 µg.mL-1 with molar absorptivity 8437.2 L.mol-1 .cm-1 . The limits of detection and quantification were determined and found to be 0.7770 µg.mL-1 and 2.3400 µg.mL-1 respec
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Manufacturing industry is constantly looking for ways to improve the efficiency of production processes so as to lower production costs, maintain product quality, and improve production planning. This study aims to provide an integrated optimization and forecasting framework that combines Cutting Optimization Pro5, linear programming, and an Enhanced N-BEATS deep learning model to minimize material waste and manufacturing cost and to predict the number of production items with a price-reduction strategy. The real industrial case study is based on production and pricing data from the Akad factory of the General Company for Electrical and Electronic Products in Iraq for the period from 2014 to 2025, concerning the manufacture of 80 L
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