The present research was conducted to reduce the sulfur content of Iraqi heavy naphtha by adsorption using different metals oxides over Y-Zeolite. The Y-Zeolite was synthesized by a sol-gel technique. The average size of zeolite was 92.39 nm, surface area 558 m2/g, and pore volume 0.231 cm3/g. The metals of nickel, zinc, and copper were dispersed by an impregnation method to prepare Ni/HY, Zn/HY, Cu/HY, and Ni + Zn /HY catalysts for desulfurization. The adsorptive desulfurization was carried out in a batch mode at different operating conditions such as mixing time (10,15,30,60, and 600 min) and catalyst dosage (0.2,0.4,0.6,0.8,1, and 1.2 g). The most of the sulfur compounds were removed at 10 min for all catalyst types. The maximum

Background Green synthesis of silver nanoparticles (AgNPs) using plant extracts has gained increasing attention as an environmentally friendly alternative to conventional chemical methods. Salix alba L contains bioactive phytochemicals that can act as reducing and stabilizing agents during nanoparticle synthesis. This study aimed to synthesize AgNPs using an aqueous bark extract of S. alba and to evaluate their antimicrobial and cytogenetic effects. Methods Silver nanoparticles were synthesized by mixing S. alba aqueous e

A Schiff base ligand (L) was used as primary ligand and potassium anthranilate (Anth) was used as the secondary ligand in the molar ratio M: L:2Anth to synthesize a new platinum(IV) mixed-ligand complex [Pt(L)(Anth)₂]Cl₂. The Schiff base ligand was synthesized by the condensation of 4-Aminoantipyrine with 4-Hydroxybenzaldehyde and was verified as a bidentate ligand. The UV-visible, FT-IR, 1 H NMR, 13 C NMR, CHN elemental analysis, molar conductance, chloride ion determination and melting point measurements were used to characterize the ligand and the complex. The results of the molar conductance showed that the electrolytic behavior was 1:2, where the two chloride ions were present outside the coordination sphere, while the spectroscopi

Among the many modern skill-enhancing work practices, machine learning is among the mostskill-enhancing practices in the workplace, as it helps students remember more of what they havelearned, hone the technical talents and skills of football players, and make better use of theirmotor skills. The use of machine learning and its practical applications in football could havesignificant benefits by improving talent development and making better use of scientifictechniques. The primary objective of this study was to determine the effectiveness of machinelearning in improving soccer dribbling and passing accuracy in children aged 10-12 years. Thestudy authors hypothesized that soccer players in the Al-Zohour Neighborhood Youth Forumwould greatly