The study involved the synthesis of new complexes with tetradentate ligand (LH). The general formula of complexes was [M(LH)(H2O)2] with M of Ni2+, Co2+, Cu2+, and Zn+. The ligand was synthesized by treating the 2-hydroxybenzohydrazide with salicylaldehyde. The structural characteristics of ligands and complexes were analyzed using various techniques, including elemental analyses, magnetic susceptibility, molar conductivity, infrared, ultraviolet absorption, mass, and NMR spectroscopy studies. The physical measurements indicated that the prepared complexes are non-electrolyte and showed that the ligand is tetradentate when coordinated with metal ions through the nitrogen of azomethine (–C=N–), two oxygen atoms of O–H phenolic,

In this study, the new azo dye,5,5-[1,2-phenylenebis(2,1-biazenediyl)] bis[8-quinolino], was used to synthesize complexes with Co2+, Ni2+, Cu2+, Zn2+, and Cd2+ ions. The compounds were characterized using 1H and 13C nuclear magnetic resonance (NMR) spectroscopy, Fourier transform infrared (FT-IR) spectroscopy, ultraviolet-visible (UV-Vis) spectroscopy, mass spectrometry, thermo gravimetric analysis (TGA), diffevential scanning calovimltry (DSC), CHN analysis. Further, conductivity, magnetic susceptibility, and metal and chlorine content analysis using FT-IR spectroscopy revealed that the ligand chelates as a bidentate (OH) phenol group and a bidentate (C=N) ring group. The ligand exhibited tetradentate behavior, forming tetrahedral complexe

Abstract

A series of new 4(3H)-quinazolinone derivatives (S1-S4) were synthesized and characterized   by FTIR,¹HNMR and ¹³CNMR .Their cytotoxic activity against a set of human cancer cell lines MCF-7 (breast) and A549 (lung) was evaluated using MTT assay. To detect their selectivity toward cancer cells, the compounds were also tested against epithelial cells derived from normal human fibroblast (NHF). Methotrexate (MTX) was used as a reference for comparison . All the tested compounds exhibited toxicity against the normal cells lower than cancer cells. All the tested compounds displayed higher cytotoxicity against lung cancer cell line (A549) than MTX with the most

Synthesis of a new class of Schiff-base ligand with a tetrazole moiety to form polymeric metal complexes with Co^II, Ni^II, Zn^II, and Cd^II ions has been demonstrated. The ligand was synthesised by a multi-steps by treating 5-amino-2-chlorobenzonitrile and cyclohexane -1,3-dione, the 5,5'-(((1E,3E)-cyclohexane-1,3-diylidene)bis(azanylylidene))bis(2-chlorobenzonitrile) was obtained. The precursor (M) was prepared  from the reaction 5,5'-(((1E,3E)-cyclohexane-1,3-diylidene)bis(azanylylidene))bis(2-chlorobenzonitrile) with NaN₃ to obtained (1E,3E)-N¹,N³-bis(4-chloro-3-(1H-tetrazol-5-yl)phenyl)cyclohexane-1,3-diimine (N). By reacting the precursor (M) with CS₂

<span lang="EN-US">The fundamental of a downlink massive multiple-input multiple-output (MIMO) energy- issue efficiency strategy is known as minimum mean squared error (MMSE) implementation degrades the performance of a downlink massive MIMO energy-efficiency scheme, so some improvements are adding for this precoding scheme to improve its workthat is called our proposal solution as a proposed improved MMSE precoder (PIMP). The energy efficiency (EE) study has also taken into mind drastically lowering radiated power while maintaining high throughput and minimizing interference issues. We further find the tradeoff between spectral efficiency (SE) and EE although they coincide at the beginning but later their interests become con

      The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin