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.
The first chapter the importance of research and need for education scientists see that the roots of the use of a specimen Wheatley in learning and teaching back to Grayson Wheatley, one of the largest supporters of a modern construction, which lay the groundwork for the specimen stage and the form in which it is. That was attributed to him, often called his name called while some educators based learning strategy on the issue. He sees the learner in this model make him a meaningful understanding of problems during his progress, thereby acting with his colleagues to find solutions to them in small groups. He
Borders Search: Search by students is determined by th
... Show MoreWellbore instability is a significant problem faced during drilling operations and causes loss of circulation, caving, stuck pipe, and well kick or blowout. These problems take extra time to treat and increase the Nonproductive Time (NPT). This paper aims to review the factors that influence the stability of wellbores and know the methods that have been reached to reduce them. Based on a current survey, the factors that affect the stability of the wellbore are far-field stress, rock mechanical properties, natural fractures, pore pressure, wellbore trajectory, drilling fluid chemicals, mobile formations, naturally over-pressured shale collapse, mud weight, temperature, and time. Also, the most suitable ways to reduce well
... Show MoreA Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreAsthma is a condition characterized by bronchial spasms, inflammation, and mucous hypersecretion which leads to difficulties in respiration. Asthmatic patients are usually presented with recurrent attacks of coughing, wheezing, and shortness of breath which could be life-threatening. More than three million cases of asthma in the United States are diagnosed annually. Resveratrol, a polyphenolic stilbene, is known to be useful in controlling asthmatic attacks via different molecular mechanisms within the lung epithelium and infiltrating immune cells. However, few studies mentioned the effect of resveratrol on the microbiome in ovalbumin-induced asthma mouse model. In this study, we ind
This paper shews how to estimate the parameter of generalized exponential Rayleigh (GER) distribution by three estimation methods. The first one is maximum likelihood estimator method the second one is moment employing estimation method (MEM), the third one is rank set sampling estimator method (RSSEM)The simulation technique is used for all these estimation methods to find the parameters for generalized exponential Rayleigh distribution. Finally using the mean squares error criterion to compare between these estimation methods to find which of these methods are best to the others
Abstract Planetary nebulae (PN) represents the short phase in the life of stars with masses (0.89-7) M☉. Several physical processes taking place during the red giant phase of low and intermediates-mass stars. These processes include :1) The regular (early ) wind and the envelope ejection, 2) The thermal pulses during Asymptotic Giant Branch (AGB ) phase. In this paper it is briefly discussed how such processes affect the mass range of Planetary Nebulae(PN) nuclei(core) and their evolution, and the PN life time, and fading time for the masses which adopted. The Synthetic model is adopted. The envelope mass of star (MeN ) and transition time (ttr) calculated respectively for the parameter (MeR =1.5,2, 3×10-3 M☉). Another time scale is o
... Show MoreBackground and purpose: Animal model helps researchers to evaluate new treatment plan for human and understand pathological mechanism involved in a development of disease. The use of rats as an animal model for Alzheimer's research has become a favorite among researchers. Rats are capable in mimicking Alzheimer disease due to their intelligence and quick adaptation to nature. At present there are several methods that can be used to induce Alzheimer's animals, but each method has advantages and disadvantages. We need to learn other methods that can provide many advantages and few disadvantages. The Amyloid-beta 42 (Aβ-42) and Reactive Oxygen Species (ROS) are thought to play an important role in the pathology of Alzheimer’s disease. Th
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