The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a pandemic of coronavirus disease 2019 (COVID-19) which represents a global public health crisis. Based on recent published studies, this review discusses current evidence related to the transmission, clinical characteristics, diagnosis, management and prevention of COVID-19. It is hoped that this review article will provide a benefit for the public to well understand and deal with this new virus, and give a reference for future researches.

In this work, we synthesized thirteen compounds of 1-(2-furoyl)thiourea derivatives 1-13 by conversion of 2-furoyl chloride to 2-furoyl isothiocyanate by reacting it with potassium thiocyanate in dry acetone in a quite short reflux time then, in the same pot, different of (primary and secondary amines) were added individually to achieve thiourea derivatives. The products were characterized spectroscopically using (FT-IR, 1H NMR and 13C NMR) techniques. Some of them were evaluated as antioxidant agents using DPPH radical scavenging method, and all were examined theoretically as enzyme inhibitors against Bacillus pasteurii urease (pdb id: 4ubp) and  by studying  molecular docking using Autodock (4.2.6) software.

This study was aimed to isolate and identify Saccharomyces boulardii from Mangosteen fruits (Garcinia mangostana L.) by traditional and molecular identification methods To get safe and healthy foods probiotics for use, The isolates and two commercial strains were subjected to cultural, morphological and biochemical tests, The colonies of the isolates were spherical, smooth, mucoidal, dull and white to cream colour on SD agar media .The shape of cells was globose to ovoid and sometimes with budding, in a single form or clustered like a beehive. The isolates and two commercial strains were unable to metabolized galactose and lactose , Results shows that all isolates were unable to utilize potassium nitrate and not grow in the presence of (

structural and electrical of CuIn (Sex Te1-x)2

Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of

Corona virus sickness has become a big public health issue in 2019. Because of its contact-transparent characteristics, it is rapidly spreading. The use of a face mask is among the most efficient methods for preventing the transmission of the Covid-19 virus. Wearing the face mask alone can cut the chance of catching the virus by over 70\%. Consequently, World Health Organization (WHO) advised wearing masks in crowded places as precautionary measures. Because of the incorrect use of facial masks, illnesses have spread rapidly in some locations. To solve this challenge, we needed a reliable mask monitoring system. Numerous government entities are attempting to make wearing a face mask mandatory; this process can be facilitated by using face m

Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

Background: Coronary artery disease remains the main cause of death despite several preventive programs. Epicardial adipose tissue is a visceral fat depot of the heart located along the large coronary arteries and on the surface of ventricles and apex. Intima media thickness is commonly recognized as the initial stage in the development of atherosclerosis. The development of ultrasound machines, advances in echocardiographic devices and high resolution transducers facilitate comprehensive analysis of epicardial fat thickness (EFT) and carotid –intima media thickness (C-IMT).
Aim: To investigate the relationship of echocardiographic epicardial fat thickness (EFT) and carotid –intima media thickness (C-IMT) with the severity of coro

    The main goal of this research is to determine the impact of some variables that we believe that they are important to cause renal failuredisease by using logistic regression approach.The study includes eight explanatory variables and the response variable represented by (Infected,uninfected).The statistical program SPSS is used to proform the required calculations