This study aimed at examining the role played by the media outlets during the coverage
of the presidential election campaigns 2020 of the United States of America.
The analytical study used through a partial inventory of the research community
for almost three months from the announcement of the candidates’ names by
the major parties on August 13 to November 6، which is the official election day in
the U.S. National Public Radio Station (NPR) to achieve the objectives of the study.
The study reached a number of conclusions related to the contents، methods and
sources of media coverage of the election campaigns of the 2020 U.S. at the mentioned
station، where the researcher proposed a number of recommendations

Background: One of the most common problem associated with the used of soft denture lining material is microorganisms and fungal growth especially Candida albicans, which can result in chronic mucosal inflammation. The aim of this study was to evaluate the influence of chlorhexidine diacetate (CDA) salt Incorporation into soft denture lining material on antifungal activity; against Candida albicans, and the amount of chlorhexidine di-acetate salt leached out of soft liner/CDA composite. Furthermore, evaluate shear bond strength and hardness after CDA addition to soft liner Materials and methods: chlorhexidine diacetate salt was added to soft denture lining material at four different concentrations (0.05%, 0.1% and 0.2% by weight). Four hund

Pushover analysis is an efficient method for the seismic evaluation of buildings under severe earthquakes. This paper aims to develop and verify the pushover analysis methodology for reinforced concrete frames. This technique depends on a nonlinear representation of the structure by using SAP2000 software. The properties of plastic hinges will be defined by generating the moment-curvature analysis for all the frame sections (beams and columns). The verification of the technique above was compared with the previous study for two-dimensional frames (4-and 7-story frames). The former study leaned on automatic identification of positive and negative moments, where the concrete sections and steel reinforcement quantities the

In this paper , concrete micro-piles were used to improve the bearing capacity of the soil which is supporting the shallow foundation by using groups of (4; 6 and 9)bored short micro-piles which have, (D=0.125m and D=0.1m), and length to diameter ratio (L/D) equal to (6; 10 and 12) respectively. To calculate the bearing capacity of the micro-piles,(Tomlinson) and (Lamda) methods were used; also the soil properties were taken from Al-Muthana airport,(Al-Qyssi,2001) [1]. The results show that; increasing the number of piles and/ or the diameters and lengths; and the interaction between the bearing capacity of the shallow foundation with the bearing capacity of the pile group which leads to increasing the strength against the external loads

Industrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m³ (B-400) to 300 kg/m³ (B-300) then to 200 kg/m³ (B-200). While (B-380) was produced using 380 kg/m³ cement and 20 kg/m³ nano-sil

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne