Complexes of Co(II),Ni(II),Cu(II)and Zn(II) with mixed ligand of 4 tributylphosphine (PBu3) were prepared in aqueous ethanol with (1:2:2) (M:L:PBu3)The prepared

A new Macrocyclic Schiff base ligand Bis[4-hydroxy(1,2-ethylene-dioxidebenzylidene) pheylenediamine] [H2L] and its complexes with (Co(II) , Ni(II) , Cu(II) , Zn(II) and Cd(II)) are reported . The ligand was prepared in two steps,in the first step a solution of (o-phenylene diamine) in methanol react under reflux with (2,4-dihydroxybenzylaldeyed) to give an (intermediatecompound) [Bis-1,2 (2,4-dihydroxybenzylediene)pheylinediamine] which react in the second step with (1,2- dichloro ethane) giving the mentioned ligand.Then the complexes were synthesis of adding of corresponding metal salts to the solution of the ligand in methanol under reflux with 1:1 metal to ligand ratio. On the basis of, molar conductance, I.R., UV-Vis, chloride content a

four coordinated complexes for divalent metal ions : Mn, Fe, Co, Ni, Cu and Cd have been synthesized using bidentate Schiff base ligand type (NN)formed by the condensation of o-phenylenediamine , p- methylbenzadehyde and furfural in methanol. The ligand was reacted with divalent metal chloride forming complexes of the types :[M(L)Cl2] where : MII=Mn, Fe, Ni, Cu, and Cd . These new compounds were characterized by elemental analysis, spectroscopic methods (FT-IR, U.V-Vis, 1HNMR (for ligand only and atomic absorption) , magnetic susceptibility, chloride content along with conductivity measurement. These studies revealed that the geometry for all complexes about central metal ion is tetrahedral.

في هذا البحث تم تحضير المركبات المعدنية النانوية الجديدة لأيونات البلاتين 4+و الذهب 3+ مع ليكاند قاعدة مانخ جديد مشتق من السيبروفلوكساسين بطريقة الموجات فوق الصوتية. تم تشخيص المعقدات النانوية والليكاند الجديد بأستخدام  تقنيات فيزيائية و كيميائية مختلفة مثل أطياف الاشعة تحت الحمراء، حيود الاشعة السينية ، المجهر الالكتروني الماسح ، المجهر الالكتروني النافذ و مجهر القوة الذرية.  تم تحديد نشاط مضادات الأك

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

   A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro