Coupling reaction of 2-amino benzoic acid with 8-hydroxy quinoline gave bidentate azo ligand. The prepared ligand has been identified by Microelemental Analysis,1HNMR,FT-IR and UV-Vis spectroscopic techniques. Treatment of the prepared ligand with the following metal ions (ZnII,CdII and HgII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2]. The prepared complexes have been characterized by using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectroscopic methods as well as conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration range

The current study  was carried out at the Fields belongs of Horticulture  Department, Collage of Agricultural Engineering Science, University of  Baghdad, Al-Jadiriyah for the spring season 2016 -2017 to study the effect for  inoculation mycorrhizae and  folair application  with bio stimulators and their interaction in the growth characters of  (local okra  ptera). A factorial experiment  (2  in randomized complete block design (RCBD), the experiment included (12) treatment  Distributed  in three  replicates. The three factors used in this experiment included . The inoculation with control (C) Mycorrhizae  ( M ) , Biozyme  (B ) ( B1 2cm3.L-1), ( B2 4cm1-.L-1) , Phosphalas (P) (P 2cm3.L-1),  ( M + B1), ( M + B2), (P +

The current study used extracts from the aloe vera (AV) plant and the hibiscus sabdariffa flower to make Ag-ZnO nanoparticles (NPs) and Ag-ZnO nanocomposites (NCs). Ag/ZnO NCs were compared to Ag NPs and ZnO NPs. They exhibited unique properties against bacteria and fungi that aren't present in either of the individual parts. The Ag-ZnO NCs from AV showed the best performance against E. coli, with an inhibition zone of up to 27 mm, compared to the other samples. The maximum absorbance peaks were observed at 431 nm and 410 nm for Ag NPs, at 374 nm and 377 nm for ZnO NPs and at 384 nm and 391 nm for Ag-ZnO NCs using AV leaf extract and hibiscus sabdariffa flower extract, respectively. Using field emission-scanning electron microscopes (FE-

The Significance of this research comes as a result of the development occurring in various life fields including the field of technical and technological development in the domain of industrial products which are in direct touch with the receiver, and because the study of deletion and addition mechanism didn't Find the Scientific space through researches and Studies. On this basis , the aim of this study is defining the forms of deletion and addition mechanism in designing the industrial product in a way that fits the functional presser . As to the limitations of this study, they involve examples of readymade Turkish House furniture, which is available in Iraqi local markets in Baghdad city 2013. The study included four chapters. The fi

To evaluate the shear bond strength and interfacial morphology of sound and caries-affected dentin (CAD) bonded to two resin-modified glass ionomer cements (RMGICs) after 24 hours and two months of storage in simulated body fluid at 37°C.

Objective This study aims to investigate the impact of integrated training on kinematics variables and defensive accuracy in volleyball, focusing on enhancing balance and muscle tension control through proprioceptive neuromuscular facilitation (PNF) exercises. Methods The sample consisted of 14 male volleyball athletes from the first volleyball league of Al-Jaish Sports Club were divided into experimental (n=7) and control group (n=7). In the pre- and post-intervention periods, dynamic balance, muscle tension control and kinematic variables (during a lateral reaching task) as well as defensive performance accuracy upon fatigue onset of recoil laser strikes were assessed. Exposure the intervention program was carried out for six weeks, and t

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

Preparation of Carboxy Methylated mPEG-Block-(4-Dodecyl Anilide) Copolymers and Their Visco Metric and Surface Tension Properties in THF