Four Co(II), (C1); Ni(II), (C2); Cu(II), (C3) and Zn(II), (C4) chelates have been synthesized with 1-(4-((2-amino- 5‑methoxy)diazenyl)phenyl)ethanone ligand (L). The produced compounds have been identified by using spectral studies, elemental analysis (C.H.N.O), conductivity and magnetic properties. The produced metal chelates were studied using molar ratio as well as sequences contrast types. Rate of concentration (1 ×10 4 - 3 ×10 4 Mol/L) sequence Beer’s law. Compound solutions have been noticed height molar absorptivity. The free of ligand and metal chelates had been applied as disperse dyes on cotton fabrics. Furthermore, the antibacterial activity of the produced compounds against various bacteria had been investigated. For the gained datum, a tetrahedral geometrical structure has been suggested for each primed complex. Molecular docking investigation was carried out to ascertain the inhibitory action of the studied compounds against 1HNJ protein, the target enzyme for the antimicrobial agents. The findings showed that, when compared to other compounds, (C1) has the highest binding affinity. Therefore, these molecules might make good candidates for antimicrobials. The quantum chemical parameters are calculated, and the molecular structure complexes were theoretically optimized.
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Zinc oxide nanoparticles sample is prepared by the precipitation method. This method involves using zinc nitrate and urea in aqueous solution, then (AgNO3) Solution with different concentrations is added. The obtained precipitated compound is structurally characterized by X-ray diffraction (XRD), Scanning electron microscopy (SEM), Atomic force microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR). The average particle size of nanoparticles is around 28nm in pure, the average particle size reaches 26nm with adding AgNO3 (0.05g in100ml =0.002 M) (0.1g in100ml=0.0058M), AgNO3 (0.2g in 100ml=0.01M) was 25nm. The FTIR result shows the existence of -CO, -CO2, -OH, and -NO2- groups in sample and oxides (ZnO, Ag2O).and used an
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The integer simulation and development finite impulse response (FIR) filters taking into account the possibilities of their realization on digital integer platforms are considered. The problem statement and solution of multifunctional synthesis of digital FIR filters such a problem on the basis of the numerical methods of integer nonlinear mathematical programming are given. As an several examples, the problem solution of synthesis FIR-filters with short coefficient word length has been given. The analysis of their characteristics is resulted. The paper discusses issues of modeling and synthesis of digital FIR filters with provision for the possibilities of their implementation on digital platforms with integer computation arithme
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Volumetric chemical adsorption was done in a volumetric apparatus using hydrogen gas at room temperature on eleven platinum catalyst, commercial catalysts (RG-412,RG-402 ,RG-432, RG-451, RG-482, and PS-10) and prepared platinum catalysts with 0.1, 0.2 , 0.45 , and 0.55% by weight of Pt supported with Y-alumina. The results show that the metal crystallite area increases with increasing platinum content. The dispersion and particle size of metal crystallite located between 48.2-96.1% and 3.85-12.72 nm, respectively. For bimetallic catalysts, the hydrogen intake decrease in the following order : Re < Sn < Ir.
Carbazone Derivatives (CD) (semicarbazone, semithiocarbasone) are produced by the condensation reaction between a aldehyde (or ketone) with a carbazide derivatives (semicarbazide, semithiocarbazide). CD and their metal complexes existent a wide range of implementation that stretch from their ply in the medicinal and pharmaceutical area because of their major significant pharmacological characteristic such as anti-fungal,anti-bacterial, anti-cancer, anti-human immunodeficiency virus, anti-inflammation, anti-neoplastic,inhibition corrosion, antioxidation, antiradical. This paper reviews the definition, importance and various applications of carbazone derivatives with transitional meta
Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt
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Background: low back pain is one of the most common public health problems and of the most common musculoskeletal complaint. Many risk factors have been considered for developing low back pain include smoking, obesity and sedentary lifestyle.
Aim of study: To evaluate smoking, obesity, and sedentary lifestyle associations with low back pain in young adults aged (18 – 39 years).
Methods: a comparative cross sectional study for young adults aged 18 – 39 years, participants with low back pain as a symptom constitutes the first group, others free of this symptom considered as the control group. Age and gender matched in both groups. Smoking, obesity and sedentary life sty
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