Azo derivative ligand[H3L] have been synthesized by the reaction of diazonium salt of p-amino benzoic acid with orcinol in(1:1)mole ratio. The bidente ligand was reacted with the metal ions MnII,FeIIandCrIIIin(2:1)mole ratio via reflux in ethanol using Et3N as a base to give complexes of the general formula: [ M(H2L)2(H2O)x]Cly The synthesized compounds were characterized by spectroscopic methods[ I.R , UV-Vis, A.A and H1 NMR]along with melting point, chloride content and conductivity measurements. The complexes were screend for their in vitro antibacterial activity against one strain of staphylococcus as Gram(+) positive and one strain of pseudomonas as Gram(-) Negative, using the agar diffusion technique.

     In this research, new Schiff base is derived from chitosan O-nitrobenzyldehyde and its complexes were synthesized. All compounds were characterized by FT-IR, UV-Visible, TGA, DTA, TG and molar conductivity with melting point. The results showed that Schiff base was coordinated via  nitrogen atom azomethine with the center metal ions Co+2,Ni+2 and Cu+2 behaving monodentate ligand and forming complexes with molecular formula [M(L)Cl2H2O] The tetrahedral geometrical was suggested for all prepared complexes based on the characterization data for all techniques.   +2,Cu+2, Ni+2M = Co   

         Cardiovascular disorders  are  refer to the class of diseases that involve the heart or blood vessels (arteries and veins). While the term technically refers to any disease that affects the cardiovascular system. Cholesterol is classified as a sterol (a contraction of steroid and

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

    The depth conversion process is a significant task in seismic interpretation to establish the link between the seismic data in the time domain and the drilled wells in the depth domain. To promote the exploration and development of the Subba oilfield, more accurate depth conversion is required. In this paper, three approaches of depth conversions: Models 1, 2, and 3 are applied from the simplest to the most complex on Nahr Umr Reservoir in Suba oilfield. This is to obtain the best approach, giving less mistakes with the actual depth at well locations and good inter/extrapolation between or away from well controls. The results of these approaches, together with the uncertainty analysis provide a reliable velocity model

I have studied the relationship between blood groups in humans and disease Cutaneous injury for the first time in Iraq study showed the presence of a significant statistical relationship between them leather Bmsoy in hospitals in Baghdad and its suburbs