In the present work, the phthalic acid (phthH2) and 1.10 phenonthroline (phen), and their complexes were synthesized and isolated as [M(phth)(phen)2], Mn(II), Fe(II), Co(II), Ni(II) Cu(II), Zn(II), and Cd(II) ions. These complexes were characterized by elemental analysis, melting point, conductivity, percentage metal, UV–Vis, FT-IR, and magnetic moment measurements. The molar conductance indicates that all the metal complexes in DMSO are nonelectrolytic. phthalic acid (phtha), and 1,10-Phenanthroline (phen), behaved as bidentate, coordinating to the metal ion through their two oxygen and two pyridinyl nitrogen atoms respectively, as corroborated by. Electronic spectra, FTIR, spectroscopy amusement indicated that all the metal complexes ad

Some transition metal ions (Cr +3, Co+2 , Ni+2,Cu+2, Zn+2,Ag + ,Cd+2 ) complexes of [(N, N- - Bis(2- hydroxy ethyl) Glycine] (Bicine) have been synthesized and characterized by FTIR ,UV-Visble spectroscopy, atomic absorption, magnetic susceptibility, conductivity measurements and study of the nature of the complexes formed in ethanolic solution following the moleratio method. From the results obtained the following general formola have been given for the prepared complexes [M m+ (Bicine)n]. XH2O

Coupling reaction of 4-amino antipyrene with 4-amino benzoic acid gave bidentate azo ligand. The prepared ligand was identified by Microelemental Analysis, 1HNMR, FT-IR and UV-Vis spectroscopic techniques. Treatment of the prepared ligand with the following metal ions (CoII, NiII, CuII and ZnII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2]Cl2 . The prepared complexes were characterized using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. Chloride ion content was also evaluated by (Mohr method). The nature of the complexes formed were studied following the mol

Some of metal compounds have been synthesized of record ligand from aldehid interaction of a substance which is salicyladehyde with another material which is urea. During the analysis of the metal component, The prepared complexes were characterized by elemental analysis, IR ,UV-visible , conductivity and magnetic susceptibility measurements. this confirms the ratio[1:1] between the metal and ligand. It is found that theortical values agree with practical values All the studied complexes are suggested as an octahedral stereochemistry.

In this study, a new Azo ligand 5-((2-(1H-indol-2-yl)ethyl)diazinyl)-2-aminophenol is synthesized from a reaction of Tryptamine with 2-aminophenol. The ligand and their metal ion complexes Ni(II), Pd(II) , Pt(IV) and Au(III) have been synthesized and characterized by various analytical techniques, including elemental microanalysis, metal content, chloride-containing, measurement of electrical conductivity, magnetic susceptibility, ¹H and ¹³C-NMR, FT-IR, UV-Vis, mass spectra (MS), and thermal analysis (TGA and DSC) curves. The DCS curve was used to calculate the thermodynamic parameters ΔH, ΔS, and ΔG. The characterization results promote the metal complexes of azo ligand structures. The results indicate that the

In this research, the preparation of bidentate Schiff base was carried out via the condensation reaction of both the salicylaldehyde with 1-phenyl-2,3-dimethyl-4-amino-5-oxo-pyrazole to form the ligand (L). The mentioned ligand was used to prepare complexes with transition metal ions Mn(II), Co(II), Ni(II), Cu(II) and Zn(II). The resulting complexes were separated and characterized by FTIR and UV-Vis spectroscopic technique. Elemental analysis for Carbon, Hydrogen and Nitrogen elements, electronic spectra of the ligand and complexes were obtained, and the magnetic susceptibility tests were also achieved to measure the dipole moments. The molar conductivities were also measured and determination of chlorine content in the complexes and

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea