A series of new compounds including p-bromo methyl pheno acetate [2]. N-( aminocarbonyl)–p-bromo pheno acetamide [3] , N-( aminothioyl) -p-bromo phenoacetyl amide [4], N-[4-(p-di phenyl)-1,3-oxazol-2-yl]-p-bromopheno acetamide [5],N-[4-p-di phenyl]-1,3-thiazol-2-yl-p-bromo phenoacet amide [6], p-bromopheno acetic acid hydrazide [7] , 1-N-(p-bromo pheno acetyl)-1,2-dihydro-pyridazin-3,6- dione [8], 1-N-(p-bromo pheno acetyl)-1,2-dihydro-phthalazin-3,8- dione[ 9], 1-(p-bromo pheno acetyl)-3-methylpyrazol-5-one [10] and 1-(p-bromo phenol acetyl)- 3,5-dimethyl pyrazole [11] have been synthesized. The prepared compounds were characterized by m.p.,FT-IR and 1H-NMR spectroscopy. Also ,the biological activity was evaluated .

Mixing aluminum nitrate nonahydrate with urea produced room temperatures clear colorless ionic liquid with lowest freezing temperature at (1: 1.2) mole ratio respectively. Freezing point phase diagram was determined and density, viscosity and conductivity were measured at room temperature. It showed physical properties similar to other ionic liquids. FT-IR,UV-Vis, 1H NMR and 13C NMR were used to study the interaction between its species where - CO ??? Al- bond was suggested and basic ion [Al(NO3)4]? and acidic ions [Al(NO3)2. xU]+ were proposed. Water molecule believed to interact with both ions. Redox potential was determined to be about 2 Volt from – 0.6 to + 1.4 Volt with thermal stability up to 326 ?.

Abstract:

Background: Retinol binding protein 4 (RBP4), an adipokine that participate in a lipid metabolism or insulin resistance through a complex regulatory network. Recently, RBP4 was reported to be associated with many cardiovascular diseases (CVDs) risk factors in patients of type 2 diabetes mellitus (T2DM). This study aims to study the correlation of  serum RBP4 with some markers of glycemic control, dyslipidemia, hypertension and obesity in T2DM Iraqi patients.

Subjects and Methods: one hundred fifty participants were enrolled in this coss-sectional study, 120 of participants were T2DM patients and 30 were apparently healthy individuals to serve as control gro

This search includes the preparation of Schiff base ligand (SB) from condensation primary amine with vanillin. The new ligand was diagnosed by spectroscopic methods as Mass, NMR, CHN and FTIR. Ligand complexes were mixed from new (SB) and Anthranillic acid (A) with five metal (II) chlorides. The preparation and diagnosis were conducted by FTIR, CHN, UV-visible, molar conductivity, atomic absorption and magnetic moment. The octahedral geometrical shape of the complexes was proposed. The ligands and their new complexes were screened with two different types of bacteria.

I've been in this work to prepare some complexes containing mixed Kandat with some transitional elements which new complexes according to the best of our knowledge and to refer to the information from the Internet until I have been studying this diagnosis Aalmakdat

A novel Schiff base ligand [N1-benzylidenebenezene-1,2-diamine(L) = C20H16N2] was prepared through intensification of benzaldehyde (C6H5CHO) and O- amino aniline O-C6H4(NH2)2 in ethanol with 8-Hydroxyquinoline (8HQ) . Formed compounds were acquired of 1:1:2 molar proportion reactions for metal ions and ligands (L) and 2(8HQ) during reaction for MCl2 .nH2O salt products complexes conformable into the forms [M(L)(8HQ)2] ,where M = Mn(II),Co(II) and Ni(II). Whole the compounds were identified during the basis of their; FT-IR and U.V spectrum, melting point, molar conduct, identify of the percentage from the metal at the complexes via flame (AAS), C, H and N content of the Schiff base (L) and metal complexes were analysis and magnetic susceptib

Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff