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 molecule. A sequence DL model based on a bidirectional gated recurrent unit (GRU) is implemented. The model is applied to the Stanford COVID-19 mRNA vaccine dataset to predict the mRNA sequences deterioration by predicting five reactivity values for every base in the sequence, namely reactivity values, deterioration rates at high pH, at high temperature, at high pH with Magnesium, and at high temperature with Magnesium. The Stanford COVID-19 mRNA vaccine dataset is split into the training set, validation set, and test set. The bidirectional GRU model minimizes the mean column wise root mean squared error (MCRMSE) of deterioration rates at each base of the mRNA sequence molecule with a value of 0.32086 for the test set which outperformed the winning models with a margin of (0.02112). This study would help other researchers better understand how to forecast mRNA sequence molecule properties to develop a stable COVID-19 vaccine.
Since the beginning of 21st century, the prices of Agricultural crops have increased. This Increases is accompanied with that increases of crude oil prices and fluctuation of a dollar exchange rate as a dominant currency used in the global trade. The paper aimed to analysis the short run and long run cointegration relationships between prices of some of Agricultural crops imported by Iraq such as wheat and rice crops and both the crude oil prices and the Iraq dinar exchange rate a gained America dollar using ARDL model. The results show the long run equilibrium between they three variable throng the error correction mechanizem. The results also show the significant and economically sound effects of cru
... Show MoreVariable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage
... Show MoreThe post-Corona Covid-19 world is not the world before it, the problem of perception of personality traits with two axes: the characteristics of psychological and social compatibility, and the second aspect the mental disorder during the pandemic, and the accompanying precautions and prohibitions during the academic year 2020 AD. The aim of the research is to reveal the perception of the personal characteristics of Bisha University employees (students and faculty) during the Corona Covid-19 pandemic, and to reveal statistically significant differences in the perception of the personality traits of Bisha’s members during the Covid 19 according to the scientific qualification variables (female students -faculty members), marital st
... Show MoreBACKGROUND: SARS-CoV-2 (COVID-19) is considered a highly infectious and life threatening disease. OBJECTIVE: The present paper aims to evaluate various aspects of preventive measures and clinical management of the scheduled visits for orthodontic patients to the dental clinics during the outbreak of COVID-19, and to assess how orthodontists dealt with this challenge. METHODS: Orthodontists in private and public clinics were invited to fill a questionnaire that addressed infection control protocols and concerns about clinical management of patients in the clinics during the pandemic. Frequncies and percentages of the responses were obtained and compared using Chi-square tests. RESULTS: About 77% of those working in private clinics, a
... Show MoreThe world is currently challenging the serious effects of the pandemic of the Coronavirus disease (COVID-19) caused by severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2). Data on pediatric COVID are rare and scattered in the literature. In this article, we presented the updated knowledge on the pediatric COVID-19 from different aspects. We hope it will increase the awareness of the pediatricians and health care professionals on this pandemic.
Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq
... Show MoreImage compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
... Show MoreSome new norms need to be adapted due to COVID-19 pandemic period where people need to wear masks, wash their hands frequently, maintain social distancing, and avoid going out unless necessary. Therefore, educational institutions were closed to minimize the spread of COVID-19. As a result of this, online education was adapted to substitute face-to-face learning. Therefore, this study aimed to assess the Malaysian university students’ adaptation to the new norms, knowledge and practices toward COVID-19, besides, their attitudes toward online learning. A convenient sampling technique was used to recruit 500 Malaysian university students from January to February 2021 through social media. For data collection, all students
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