The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

Background: Molars and premolars are considered as the most vulnerable teeth of caries attack, which is related to the morphology of their occlusal surfaces along with the difficulty of plaque removal. different methods were used for early caries detection that provide sensitive, accurate preoperative diagnosis of caries depths to establish adequate preventive measures and avoid premature tooth treatment by restoration. The aim of the present study was to evaluate the clinical sensitivity and specificity rates of DIAGNOdent and visual inspection as opposed to the ICDAS for the detection of initial occlusal caries in noncavitated first permanent molars. Materials and Methods: This study examined 139 occlusal surface of the first permanent

Reading Trend in the Recent school book

“Child of today is a man of the future" this slogan is one of the most popular logos of international organizations and institutions that dealing with human beings needs in general and children needs in particular, whether these needs are educational, health, social, or economic. Children require special care and extra legal protection, since the child-raising is not the Child’s own issue, but it's the issue of the society in which he/she would integrate.

As the education and language skillsacquisition primarily associated with hearing, because human being receives most of the skills and knowledge through the hearing; that imitate sounds and learn how to speak isacquired only by hearing, so therefore the hearing - impairedchi

Fencing sport coaches seek fencers who have high velocity and work hard to develop it through training. The research problem lies on when measuring movement abilities through some tests. Manual measurement does not give reasonable impartiality of timing because there is a time-frame between the movement of the fencer and the speed of the movement of the human time setter. Therefore, the authors sought to design an electronic vest to evaluate movement abilities in foil fencers. The study design was experimental, with 12 Iranian foil fencers of the national team, who were divided into two equal groups of 6 fencers. Moreover, there were 12 students from Physical Education and Sport Sciences that worked on the scientific f

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

The research deals with analyzing the influencing role of trade policies in the growth and development of productive economic sectors and their contribution to GDP and its reflection on workforce employment. Studies have proven the success of the Malaysian experience in stimulating the productive economic sectors to grow and their contribution to the gross domestic product with an increase in the growth of local markets and access to international markets for national products. The research also deals with the ineffectiveness of Iraqi trade policies after 2003 in stimulating the productive economic sectors (agricultural and industrial) on economic growth, as most of the increase in Iraqi GDP growth throughout the study period was