SMNs like Facebook, YouTube, Twitter, WhatsApp,..etc. are among the most popular sites on the Internet. These sites can provide a powerful means of sharing, organizing, finding information and knowledge. The popularity of these sites provides an opportunity to measure the use them in knowledge sharing, which needs a special scale, but unfortunately, there is no special scale for that. Thus, this study supposes to use SCT as a scale to measure the use of SMNs in electronic knowledge sharing due to it has been used to measure knowledge sharing with its traditional form. This study can help the decision-makers to use these SMNs to share the academics’ knowledge in educational institutes to the communi

Three-dimensional cavity was investigated numerical in the current study filled with porous medium from a saturated fluid. The problem configuration consists of two insulated bottom and right wall and left vertical wall maintained at constant temperatures at variable locations, using two discretized heaters. The porous cavity fluid motion was represented by the momentum equation generalized model. The present investigation thermophysical parameters included the local thermal equilibrium condition. The isotherms and streamlines was used to examine energy transport and momentum. The meaning of changing parameters on the established average Nusselt number, temperature and velocity distribution are highlighted and discussed.

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

Background: The ultimate purpose of this prospective study is to estimate and measure swelling associated with surgical extrac¬tion of impacted mandibular third molars in different four post-operative times and to identify the risk factors associated with determination of their risk degree. Material and Methods: In this prospective cohort study 159 consecutive cases in which removal of impacted lower third molars in 107outpatients were evaluated. Five groups of variables have been studied which are regarded as a potential factor for swelling after mandibular third removal which will enable the surgeon to predict and counsel high risk patients in order to offer a preventive strategy. Results: Facial measurements were carried out on 1st, 2

In order to reduce the environmental pollution associated with the conventional energy sources and to achieve the increased global energy demand, alterative and renewable sustainable energy sources need to be developed. Microbial fuel cells (MFCs) represent a bio-electrochemical innovative technology for pollution control and a simultaneous sustainable energy production from biodegradable, reduced compounds. This study mainly considers the performance of continuous up flow dual-chambers MFC
fueled with actual domestic wastewater and bio-catalyzed with anaerobic aged sludge obtained from an aged septic tank. The performance of MFCs was mainly evaluated in terms of COD reductions and electrical power output. Results revealed that the C