Azo-ligand-(HL) ([4- ((2-hydroxyquinolin-3-yl) diazenyl) -N- (5-methylisoxazol-3yl) benzenesulfonamide]), (2- hydroxy quinolin derivative),reacts with the next metal ions (Cr (III), Fe (III),Co (II) and Cu(II)) forming stable complexes with unique geometries such as(tetrahedral for bothCo (II) and Cu (II), octahedral for both Cr (III) and Fe (III)). The creation of such complexes was detected by employing spectroscopic means involving ultraviolet-visible which proved the obtained geometries, Fourier transfer proved the involvement of coordinated water molecule in all complexes besides the pyrolysis (TGA & DSC) studies proved the coordination of water residues with metal ions inside the coordination sphere as well as chlorine atoms. Moreover

     Atenolol was used with ammonium molybdate to prove the efficiency, reliability and repeatability of the long distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis. The method is based on reaction between atenolol and ammonium molybdate in an aqueous medium to obtain a dark brown precipitate. Optimum parameters was studied to increase the sensitivity for developed method. A linear range for calibration graph was 0.1-3.5 mmol/L for cell A and 0.3-3.5 mmol/L for cell B, and LOD 133.1680 ng/100 µL and 532.6720 ng/100 µL for cell A and cell B respectively with correlation coefficient (r) 0.9910 for cell A and 0.9901 for cell B, RSD% was lower than 1%, (n=8) for the determination of ate

  The formation of  Co(II), Ni(II), Cu(II), Zn(II), and Cd(II)-complexes (C1-C5) respectively was studied with new Schiff base ligand [benzyl(2-hydroxy-1-naphthalidene) hydrazine carbodithioate  derived from reaction of  2-hydroxy-1-naphthaldehyde and benzyl hydrazine carbodithioate. The suggested structures of the ligand and its complexes have been determined   by using C.H.N.S analyzer, thermal analysis, FT-IR, U.V-Visible, 1HNMR, 13CNMR , conductivity measurement , magnetic susceptibility and atomic absorption. According to these studies,  the ligand coordinates as  a tridentate with metal ions through nitrogen atom of azomethane , oxygen atom of  hydroxyl, and  sulfur atom of thione  

  Numerous integral and local electron density’s topological parameters of significant metal-metal and metal-ligand bonding interactions in a trinuclear tetrahydrido cluster [(Cp* Ir) (Cp Ru)₂ (μ₃-H) (μ-H)₃]1 (Cp = η⁵ -C₅Me₅), (Cp* = η⁵ -C₅Me₄Et) were calculated and interpreted by using the quantum theory of atoms in molecules (QTAIM). The properties of bond critical points such as the delocalization indices δ (A, B), the electron density ρ(r), the local kinetic energy density G(r), the Laplacian of the electron density ∇²ρ(r), the local energy density

The adsorption ability of Iraqi initiated calcined granulated montmorillonite to adsorb Symmetrical Schiff Base Ligand 4,4’-[hydrazine-1, 2-diylidenebis (methan-1-yl-1-ylidene)) bis (2-methoxyphenol)] derived from condensation reaction of hydrazine hydrate and 4-hydroxy-3-methoxybenzaldehyde, from aqueous solutions has been investigated through columnar method.The ligand (H2L) adsorption found to be dependent on adsorbent dosage, initial concentration and contact time.All columnar experiments were carried out at three different pH values (5.5, 7and 8) using buffer solutions at flow rate of (3 drops/ min.),at room temperature (25±2)°C. The experimental isotherm data were analyzed using Langmuir, Freundlich and Temkin equations. The monol

In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

Background: The prevalence of obesity is continuously rising world-wide. Obesity is an important risk factor of cardiovascular disease (CVD), metabolic syndrome (MS), and type 2 diabetes (T2D).
Objective: To estimate the frequency of MS in obese versus non-obese subjects in Basrah, Iraq .
Methods: This is a prospective clinical study performed in Al-Sadr Teaching Hospital, Basrah, and included 86 obese subjects (with a BMI ≥ 30), 39 males and 47 females, and 132 non-obese subjects ( with a BMI < 30 ), 60 males and 73 females as a control group. Measurement of height, weight, waist circumference (WC), blood pressure ( BP ), fasting blood glucose ( FBG ), total cholesterol (TC), triglycerides (TG ) and high density lipoprotein-