The [2-hydroxy -1,2-diphynel-ethanone oxime] was reacted with 1,2- dichloroethan to give the new ligand [H2L].this ligand was reacted with some metal ions (Co(II),Ni(II),Cu(II),Zn(II) and Cd(II) in methanol as a solvent to give a series of new (1:1)complexes of the general formula [ M(HL)]Cl ,( where : M= Co(II),Ni(II),Cu(II),Zn(II) and Cd(II)) are isolated All compounds have been characterized by spectroscopic methods [ I.R , U.V -Vis ] atomic absorption . Chloride content along with conductivity measurements. From the above data the proposed molecular structure for (Co, Cu, Ni, Zn and Cd) complexes adopting a tetrahedral structure.
A New ligand, N-(2-oxo-1,2- Dihydropyrimidin-4- ylcarbamothioyl) Acetamide (DPA) was prepared by reaction of iso thiosyanate derivative with Cytosine. The ligand has been characterized through elemental analysis, H1 NMR, C13NMR, FT-IR, and UV Visible spectra, such ligand’s transition metal complexes have been characterized through conductivity measurement, FT-IR, UV Visible spectra and magnetic susceptibility, all the complexes of this ligand are solid crystal and molar ratio (2:1) (ligand: metal). The form of molecular for these complexes octa hedral. The general formula [M(DPA)2Cl2], where M+2 = (Mn, Co, Ni, Cu, Zn, Cd, Hg).
The current study focuses on utilizing artificial intelligence (AI) techniques to identify the optimal locations of production wells and types for achieving the production company’s primary objective, which is to increase oil production from the Sa’di carbonate reservoir of the Halfaya oil field in southeast Iraq, with the determination of the optimal scenario of various designs for production wells, which include vertical, horizontal, multi-horizontal, and fishbone lateral wells, for all reservoir production layers. Artificial neural network tool was used to identify the optimal locations for obtaining the highest production from the reservoir layers and the optimal well type. Fo
The present study was conducted to investigate effect of prey type on the relationship between age of females of Macrocyclops albidus and reproductive performance, which included each of mean number of nauplii, age at first brood, and age at first clutch. Results revealed that the correlation coefficient between the age at first brood and clutch and age of females fed on Artemia was significant P <0.05, being 0.65 and 0.81 respectively, while the correlations were not significant P>0.05 in females fed on mosquito larvae (Culex quinquefasciatus) and Paramecium nauplii. It was also found that the correlation coefficients between mean number of the nauplii and longevity in M. albidus were significant P<0.05 whereas, the correlations were not s
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The present study envisaged utilizing 4-aminoantipyrine as key intermediate for the synthesis of some new derivatives bearing anti-bacterial and anti-cancer activities moieties viz., antipyrine diazenyl benzaldehydes 2(ad) which were obtained by coupling of diazotized 4-aminoantipyrine (1) with substituted benzaldehydes at 0◦C (iced) temperature. The other antipyrine derivatives where containing bis heterocycles like bis thiazolidinone-antipyrine (4), bis imidazolidinone -antipyrine (5) and bis azetidinone -antipyrine (6).These compounds were prepared through the reaction between 4- aminoantipyrine and terephthaldicarboxaldehyde to get (3) which were reacted with mercaptoacetic acid , glycine or chloroacetyl chloride separately to get com
... Show MoreThis paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number
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