Tetradentate complexes type [M (HL) 2] were prepared from the reaction of 2-hydroxy -1, 2-diphynel-ethanone oxime [H2L] and KOH with ( Mn II, Fe II, Co II, Ni II , Cu II and Hg II ), in methanol with (2:1) metal: ligand ratio. The general formula for Cu II and Mn II complexes are [M (HL) 2 Cl.H2O] K, for Co II [Co (HL) 2. H2O] and [M (HL) 2] for the rest of complexes. All compounds were characterised by spectroscopic methods, I.R, U.V-Vis, H.P.L.C, atomic absorption and conductivity measurements chloride content. From the data of these measurements, the proposed molecular structures for Fe II and Hg II complexes are tetrahedrals, while Mn II and Cu II complexes are octahedrals, Ni II complex adopting square planar structure and the complex

In the resent years, there is a robust scientific interest in discovery of new anti-septic and anti-oxidant naturally products with no/or limited side effects. The current study aimed to investigate the protective role of the quercetin on inflammations induced by lipopolysaccharide (LPS) in male mice A number of criteria included i.e. liver and spleen index and IL-6 and IL1-β cytokines level in spleen homogenate were considered. Sixty male mice (8-9 week age) was divided into six groups and treated for 5 days as the following: the first group represented control, the second and third group were injected with 5, 10 mg/kg b.w doses of quercetin respectively. While the fourth and fifth groups were co-treatment with (5, 10 mg/kg b.w.) intraper

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

The Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.