Mixed ligands of 2-benzoyl Thiobenzimiazole (L1) with 1,10-phenanthroline (L2) complexes of Cr(III) , Ni(II) and Cu(II) ions were prepared. The ligand and the complexes were isolated and characterized in solid state by using FT-IR, UV-Vis spectroscopy, 1H, 13C-NMR, flame atomic absorption, elemental micro analysis C.H.N.S, magnetic susceptibility , melting points and conductivity measurements. 2-Benzoyl thiobenzimiazole behaves as bidenetate through oxygen atom of carbonyl group and nitrogen atom of imine group. From the analyses Octahedral geometry was suggested for all prepared complexes. A theoretical treatment of ligands and their metal complexes in gas phase were studied using HyperChem-8 program, moreover, ligands in gas phase

M(II) Ions using amino acid L- proline as a primary ligand and either Nicotinamide or 8- hydroxyqinoline as secondary ligand, respectively: a. The mixed ligand complexes of composition,[M(pro)2(na)2]. b. The mixed ligand complexes of composition , Na[M(pro)2(Q)]. Where proline (C5H9NO2) symbolized as pro H , Nicotinamide (C6H6N2O) symbolized as (NA) , 8- hydroxyqinoline, (C9H7NO2) symbolized as (8-HQ). The ligands and the metal chlorides were brought into reaction at room temperature (37ºc) in ethanol as solvent .The reaction required the following molar ratios [(1:2:2) metal:2NA:2pro-] and [(1:1:2) metal:Q:2pro-] with M+2 ions, where M = [Mn (II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and pd(II)]. Products were found to be solid crystall

The new Schiff base, namely (2-Amino-phenylimino)-acetic acid (L) was prepared
from condensation of glyoxylic acid with o-phenylene diamine. The structure (L) was
characterized by, IR,
1
H,
13
C-NMR and CHN analysis. Metal complexes of the ligand (L)
were synthesized and their structures were characterized by Atomic absorption, IR and UV-Visible spectra, molar conductivity, magnetic moment and molar ratio determination (Co
+2
,
Cd
+2
) complexes. All complexes showed octahedral geometries.

The research aims to identify the effect of applying administrative decentralization to an educational performance by assessing educational performance before and after the process of transferring powers from the federal government (the Iraqi Ministry of Education) to local governments (governorates) as well as identifying the appropriate central or decentralized administrative system to advance the educational reality and performance. To achieve the goal of the research, educational data was collected and analyzed, as well as the measurement of educational performance indicators and analysis during two phases, the first represents the stage of applying the central system and spanned between the academic year (2011-2012) and the

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

Docetaxel is an effective treatment approved for many types of cancers, but its effectiveness in clinical practice can be compromised by significant occurrence of adverse drug reactions. The aim of the current study was to measure the distribution of adverse drug reactions of docetaxel reported in Iraq and to assess the causality, severity, seriousness, preventability, expectedness and outcome of these adverse reactions. A retrospective study conducted on individual case safety reports from the Iraqi Pharmacovigilance Center / Ministry of Health. The study included 118 individual case safety report containing 236 adverse drug reactions.
Most of the adverse drug reactions were related to skin and subcutaneous tissue disorders(26.7%), f

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 internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat