The Coronavirus Disease (COVID-19) has recently emerged as a human pathogen caused by SARS-CoV-2 virus was first reported from Wuhan, China, on 31 December 2019. Upon study, it has been used molecular docking to binding affinity between COVID-19 protease enzyme and flavonoids with evaluations based on docking scores calculated by AutoDock Vina. Results showed that naringin suppressed COVID-19 protease, as it has the highest binding value than other flavonoids including quercetin, hesperetin, garcina and naringenin. An important finding in this study is that naringin with neighboring poly hydroxyl groups can serve as inhibitors of COVID-19 protease bind to the S pocket of protein, it is shown that residues His163, Glu166, Asn142, His41and PHe181 participate in the hydrogen bonding and pi-pi interactions, the same as happened with decahydroisoquinolin as a novel scaffold for SARS 3CL protease inhibitors.In other hand, some of the known protease inhibitors and anti-influenza drugs docked with COVID-19 protease, it has low binding value than naringin
The current study has sought to identify the levels of the compound thinking among secondary school students basing and relying on the opinions of Lipman who sees that the compound thinking consists of creative thinking and critical thinking, In accordance with this point of view, researchers have resorted to build scale of the critical thinking in its final form of (28) item additionally to the adoption of Torrance for the creative thinking which was translated by sayed. Khairallah in 1981 after confirming psychometric Properties Of both scales and then collect scores of both scales and be the final score represented the level of the compound thinking that has been shown by the results of secondary school students they have no skill of
... Show MoreOrtho amino hydrazobenzene (L) has been prepared from the reaction of ortho amino phenyl thiol with phenyl hyrazan in mole ratio(1:1). It has been characterized by elemental analysis (C, H, N), IR, UV–Vis. The complexes of the bivalent ions (Co, Ni, Cu, Zn, Pd, Cd, Hg and Pb) and the trivalent (Cr) have been prepared and characterized too. The structural have been established by elemental analysis(C,H,N), IR , UV – Vis spectra , conductivity measurements , atomic absorption and magnetic susceptibility . The complexes showed characteristic behaviour of octahedral geometry around the metal ion and the( N,N) ligand coordinated in bidentate modeexcept with pd showed square planer. ? ,kf , ?max for the complexes were estimated too . ? for Co
... Show Morene,؛Stability constants were determined for complexes of amino acids : L-leuc tryptophane and Aspartic acid with thorium (IV ) and uranyle ( U02++) ions at ؛ serine
The permeable reactive barrier (PRB) is one of the promising innovative in situ groundwater remediation technologies, in removing of copper from a contaminated shallow aquifer. The 1:1- mixture of waste foundry sand (WFS) and Kerbala’s sand (KS) was used for PRB. The WFS was represented the reactivity material while KS used to increase the permeability of PRB only. However, Fourier-transform infrared (FTIR) analysis proved that the carboxylic and alkyl halides groups are responsible for the sorption of copper onto WFS. Batch tests have been performed to characterize the equilibrium sorption properties of the (WFS+KS) mix in copper- containing aqueous
solutions. The sorption data for Cu+2 ions, obtained by batch experiments, have be
HBV and HCV are the major causes of chronic liver diseases throughout the world, and constitute a major global health risk. There is accumulated evidence that the imbalance of proinflammatory and anti-inflammatory cytokine production may play an important role in the pathogenesis of viral hepatic infections and may influence the clinical outcome and disease progression. This study was undertaken to analyze the circulating levels of Tumor Necrotic Factor (TNF-α) and Th2 cytokine IL-10 in patients infected with Hepatitis B and C virus. The study population consisted of 30 patients with chronic HBV, in addition to other 30 patients with chronic HCV infection were recruited on their first examination at the Al-Kindy General Hospital in Baghdad
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreIn the leaves of Olea europaea L. Olive trees an endophytic fungus was discovered. Cladosporium sp. was identified to be the fungus based on its morphological characteristics and nuclear ribosomal DNA ITS sequence analysis and was registered in NCBI as the Cladosporium genus has been registered under the number (0P939922.1) The species was not specified, and it was considered of unknown species after comparing it to global isolates. In comparison to olive leaf extract, Cladosporium sp. including total flavonoid, total phenolic, total terpenoid, and total saponins, Which were 121.9%, 198.1%, 89.13%, and 29.87 % respectively compared to its content in olive leaf extract, which was 61.54 %, 67.88 % , 17.1
... Show MoreKE Sharquie, R Hayani, J Al-Rawi, A Noaimi, SH Radhy, CLINICAL AND EXPERIMENTAL RHEUMATOLOGY, 2010
The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
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