In this paper, a novel coronavirus (COVID-19) model is proposed and investigated. In fact, the pandemic spread through a close contact between infected people and other people but sometimes the infected people could show two cases; the first is symptomatic and the other is asymptomatic (carrier) as the source of the risk. The outbreak of Covid-19 virus is described by a mathematical model dividing the population into four classes. The first class represents the susceptible people who are unaware of the disease. The second class refers to the susceptible people who are aware of the epidemic by media coverage. The third class is the carrier individuals (asymptomatic) and the fourth class represents the infected ind

Objective: To assess role of obesity in Covid-19 patients on antibodies production, diabetes development, and treatment of this disease. Methodology: This observational study included 200 Covid-19 patients in privet centers from January 1, 2021 to January 1, 2022. All patients had fasting blood sugars and anti-Covid-19 antibodies. Anthropometric parameters were measured in all participants. Results: The patients were divided into two groups according to body weight; normal body weight (50) and excess body weight (150). There was a significant difference between them regarding age. Diabetes mellitus developed in 20% of normal weight patients while 80% of excess weight patients had diabetes (p=0.0001). Antibodies production (IgM and

Abstract

The aim of the research is to identify the level of awareness and emotional experience among university students and to identify the effect of the educational program based on (Guttmann) model for developing awareness and emotional experience among university students by verifying the validity of the following zero hypotheses: 1) There are no statistically significant differences in the development of awareness and emotional experience among university students at the level of (0.05) between the mean scores of the experimental group in the pre and post-tests. 2) There are no statistically significant differences in the development of awareness and emotional experience among university students at the lev

Incremental forming is a flexible sheet metal forming process which is performed by utilizing simple tools to locally deform a sheet of metal along a predefined tool path without using of dies. This work presents the single point incremental forming process for producing pyramid geometry and studies the effect of tool geometry, tool diameter, and spindle speed on the residual stresses. The residual stresses were measured by ORIONRKS 6000 test measuring instrument. This instrument was used with four angles of (0º,15º,30º, and 45º) and the average value of residual stresses was determined, the value of the residual stress in the original blanks was (10.626 MPa). The X-ray diffraction technology was used to measure the residual stresses

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

Background: Asthma is one of the most common chronic respiratory diseases in the world, standing for the most frequent cause for hospitalization and emergency cases. Respiratory viruses are the most triggering cause. Aim: To assess the role of viral infections, especially COVID-19, in the pathogenesis of asthma initiation and exacerbations. Method: Electronic search was done for the manuscripts focusing on asthma as a risk factor for complications after COVID-19 infection. The outcomes were titles, materials, methods and classified studies related or not related to the review study. Three hundred publications were identified and only ten studies were selected for analysis. Seven studies were review, one retrospective, one longitudin

          The study of services in villages is one of the imperative matters that must   be focused on, because it leads to increased attention, which reduces the differences between the countryside and the urban. The extent of its.

  It is well known that community services need to be reached by a person, unlike the anchor services that reach people, here the population distribution plays an important and prominent role in signing these services, so the dispersed distribution pattern and the gathering pattern appeared in the distribution, thus an effect on the time and distance that the person walked to obtain The services are community-based. Therefore

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