The corona virus epidemic outbreak has urged an extreme worldwide effort for re‐purposing obtainable approved medications for its treatment. In this review, we're focusing on the chemicals properties andpharmacologicaleffectiveness of medicationsofsmallmolecule that are presently being evaluated in clinical trials for the management of corona virus (COVID‐19). The current review sheds light on a number of drugs that have been diagnosed to treat COVID‐19 and their biological effects.

In this study , Iraqi Bentonite clay was used as a filler for polyvinyl chloride polymer. Bentonite clay was prepared as a powder for some certain particle size ,followed by calcinations process at (300,700,900) OC ,then milled and sieved. The selected sizes were D ~75 µm and D ~150. After that polyvinyl Al-Cohool solution prepared and used as a coated layer covered the Bentonite powder before applied as a filler ,followed by drying , milling and sieving for limited recommend sizes. polyvinyl chloride solutions were prepared and adding of modified Bentonite power at certain quantities were followed .Sheet of these variables on the mechanical and thermal properties of the prepared reinforced particular polyvinyl chloride composite

: Cervical malignancy positioned as the fourth most prevalent disease among women around the world. HPVs especially HPV16 are the causative agent of cervical cancer, responsible of about 5% of all human cancers worldwide. Some researchers found that the fibronectin is repressed by the papillomavirus (HPV) type 16 E7 oncoprotein in both HPV-positive nontumorigenic and tumorigenic cell lines, while others found that the HPV oncoprotein increase the levels of fibronectin. The aim is to study the effect of HPV infection on Fibronectin expression and their correlation onthe development of Cervicalcancinoma. The current retrospective study enrolled paraffinized blocks of two groups. The research included 30 cervical carcinomatous tissues as well

Ab – initio density function theory (DFT) calculations coupled with Large Unit Cell (LUC) method were carried out to evaluate the electronic structure properties of III-V zinc blend (GaAs). The nano – scale that have dimension (1.56-2.04)nm. The Gaussian 03 computational packages has been employed through out this study to compute the electronic properties include lattice constant, energy gap, valence and conduction band width, total energy, cohesive energy and density of state etc. Results show that the total energy and energy gap are decreasing with increase the size of nano crystal . Results revealed that electronic properties converge to some limit as the size of LUC increase .

Optimum perforation location selection is an important study to improve well production and hence in the reservoir development process, especially for unconventional high-pressure formations such as the formations under study. Reservoir geomechanics is one of the key factors to find optimal perforation location. This study aims to detect optimum perforation location by investigating the changes in geomechanical properties and wellbore stress for high-pressure formations and studying the difference in different stress type behaviors between normal and abnormal formations. The calculations are achieved by building one-dimensional mechanical earth model using the data of four deep abnormal wells located in Southern Iraqi oil fields. The magni

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par