KE Sharquie, AA Noaimi, RA Flayih, Am J Clin Res Rev, 2020 - Cited by 4

This research focuses on improving the photoelectrochemical performance of binary heterostructure Ag2S/ZnO NRs/ITO by manipulating synthesis conditions, particularly the concentrations of sliver nitrate AgNO3 and thiourea CS(NH2)2. The photoelectrochemical performance of Ag2S/ZnO nanorods on indium tin oxide (ITO) nanocomposite was compared to pristine ZnO NRs/ITO photoanode. The hydrothermal technique, an eco-friendly, low-cost method, was used to successfully produce Ag2S/ZnO NRs at different concentrations of AgNO3 and CS(NH2)2. The obtained thin films were characterized using field emission scanning electron microscopy (FESEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), ultraviolet-visible spectroscopy

Newly 4-amino-1,2,4-triazole-3-thione ring 2 was formed at position six of 2-methylphenol from the reaction of 6-(5-thio1,3,4-oxadiazol-2-yl)-2-methylphenol 1 with hydrazine hydrochloride in the presence of anhydrase sodium acetate. Seven newly fused heterocyclic compounds were synthesized from compound 2. First fused heterocyclic was 6-(6-(3,5-di-tertbutyl-4-hydroxyphenyl)-[1,2,4]triazolo[3,4-b][1,3,4]thiadiazol-3-yl)-2-methylphenol 3 synthesized from reaction compound 2 with 3,5-di-tert-butyl-4-hydroxybenzoic acid in POCl3. Reaction compound 2 with bromophencylbromide afford 6-(6-(4-bromophenyl)-5H-[1,2,4]triazolo[3,4-b][1,3,4]-thiadiazin-3-yl)-2-methylphenol 4. 6-(6-thio-1,7a-dihydro-[1,2,4] triazolo[3,4-b][1,3,4]-thiadiazol-3-yl)-2

Molar conductivity of different concentrations of thymine and adenosine in water , sodium acetate and ammonium chloride solution at different temperatures , 283. 15-323.15 K has been determined from direct conductivity measurements , examination of aqueous mixture of thymine and adenosine with Onsager equation reveal deviation from linearity at high concentration .This deviation was explained in term of molecular interaction . Ostwald dilution law also examined with the above mixtures lead to calculation of limiting molar conductivities and dissociation constants of both nucleic acid in water , sodium acetate and ammonium chloride. The agreement between the values obtained for Onsager equa

Project deal with the study of the suitability of the planning standards of the select sites for sports facilities for the holy city of Karbala and the extent of convergence and divergence between these standards and points of strength and weakness in each of these standards.

It was found that there was a lack of the   role given to the sports as a kind of luxury does not deserve to spend money and efforts, and was then incorporated with a lot of entertainment services by planners.

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Background Direct-acting antivirals (DAAs) combination therapies from various mechanisms of action and families have been revolutionized the management landscape of chronic hepatitis C virus (HCV). Ombitasvir, paritaprevir with ritonavir (OBV/PTV/r) ± ribavirin (RBV) is approved to treat HCV genotype 4 (GT4) infection. Here, our objective was to delineate the efficacy and safety of OBV/PTV/r plus RBV in treating of Egyptian naïve patients infected with HCV GT4.

Methods a cohort of 100 Egyptian patients infected with HCV GT4 was allocated and administered orally OBV/PTV/r with RBV. The primary endpoint of our study was a sustained virological response (HCV RNA < 12 IU/mL) 12 weeks after the c

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

KE Sharquie, AA Noaimi, HA Al-Mudaris, Journal of Drugs in Dermatology: JDD, 2013 - Cited by 22