The mixed ligand complexes of Schiff base ligand (Z)-2-(((4-bromo-2-methylphenyl) imino) methyl)-4-methylphenol (L) with some metals ion (II); Mn(1), Co(2), Ni(3), Cu(4), Zn(5) Cd(6) and Hg(7) and 1,10-Phenanthroline (phen) were Synthesis and characterized by the mass and 1HNMR spectrometry (ligand Schiff base), the FTIR, UV-visible and the flame atomic absorption (A.A) spectrum, the C.H.N analysis and the chlorine content, in addition to measuring the magnetic sensitivity of the complexes. All the complexes had octahedral geometry. The bioactivity activity for compounds against; Rhizopodium, Staphylococcus aureus and Escherichia coli, the compounds showed different efficacy towards these microorganisms

The Schiff base (E)-2-(((2-(1H-benzo[d]imidazol-2-yl) phenyl) imino) methyl)-4-methylphenol (Lb) ligand with some metals(II) ion such as; Co, Cu, Cd, and Hg, were synthesis and characterized by the mass and 1 HNMR spectrometry for ligand Schiff base, the fourier-transform infrared spectroscop (FTIR), UV- visible and the flame atomic absorption (AA) spectrum, the CHN analysis, and the chlorine content, in addition to measuring the magnetic sensitivity of the complexes. All the complexes had octahedral geometry. The bioactivity activity for compounds against; Rhizopodium, Staphylococcus aureus, and Escherichia coli showed different efficacy towards these microorganisms

New metal ion complexes were synthesized with the general formula; K[PtLCl4], [ReLCl4] and K[ML(Cl)2] where M = Pd(II), Cd(II), Zn(II) and Hg(II), from the Azo ligand (HL) [2-Hydroxy-3-((5-mercapto-1,3,4-thiadiazol-2-yl)diazenyl)-1-naphth aldehyde] (HL) the ligand was synthesized from (2-hydroxy-1-naphthaldehyde) and (5-amino-1,3,4-thiadiazole-2-thiol). The ligand and its metal complexes are characterized by phisco- chemical spectroscopic techniques (FT.IR, UV-Vis and Mass spectra, elemental analysis, molar conductivity, Atomic Absorption, Chloride contain and magnetic susceptibility). The spectral data suggest that the (HL) behaves as a bidentate ligand in all complexes. These studies revealed tetrahedral geometries for all metal complexes

A simple ,accurate and sensitive spectrophotometric method has been developed the determination of Cobalt(II) and Cupper (II) .The method is based on the chelation of Co(II) and Cu(II) ions with 4-(4´-pyrazolon azo) -2-Naphthol(APAN) in aqueous medium . The complexes have a maximum absorption at (513) and (506) nm and ? max 0.531×10 4 and 0.12×10 5 L.mol -1.cm -1 for Co(II) and Cu(II) respectively .The reagent and two complexes have been prepared in ethanolic solution.The stoichiometry of both complexes were found to be 1:2 (metal :legend) .The effects of various cations and anions on Co(II) and Cu(II) determination have been investigated .The stability constants and standard deviations for Co(II) and Cu(II) 0.291 x107 ,0.909X108 L.mol

Ni and Cd complexes of new Schiff base derived from 5-Amino-2-phenyl-2,4-dihydro-pyrazol-3-one with 4-chlorobenzalaldehyde (A) , 2-Hydroxy-benzalaldehyde (B) and 4-Hydroxy-benzaldehyde (C) have been prepared and characterized by elemental analysis , molar conductivity measurements , FTIR , UV- vis , 1HNMR, mass spectrometer and magnetic susceptibility. Analytical data revealed that six complexes were a distorted tetrahedral geometry and exhibited (1:1) metal :ligand ratio. The biological activity for the three ligands and its complexes were studied

The pandemic SARS-CoV-2 is highly transmittable with its proliferation among nations. This study aims to design and exploring the efficacy of novel nirmatrelvir derivatives as SARS entry inhibitors by adapting a molecular modeling approach combined with theoretical design. The study focuses on the preparation of these derivatives and understanding their effectiveness, with a special focus on their binding affinity to the S protein, which is pivotal for the virus’s access to the host cell. Considering molecular docking aspects in the scope of a study on nirmatrelvir derivatives and S protein, dynamics simulations with 25 nanoseconds of their binding are explored. The study shows that these derivatives might work as effective antivi

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial