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Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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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.

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Publication Date
Sun Mar 01 2020
Journal Name
Agricultural Engineering
Analysis of the Vacuum-Steam Defrosting Process of Plums Pre-Treated with Dehydrofreezing
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Abstract<p>The research material was prune plums (<italic>Prunus domestica</italic> L.), subjected to osmotic pre-treatment, with variable process time parameters and osmotic solution concentration. Plums thus fixed were frozen and stored for 6 months. At even (monthly) intervals, the product was defrosted by the vacuum-steam method, using the s-p-p chamber, until the thermocouple indicated a temperature of 4ºC in the sample’s thermal center. In order to study the kinetics of phenomena occurring during the defrosting process, the chamber was equipped with a measuring system to enable measurement and recording of temperature changes in time in the geometric center of the sample, as w</p> ... Show More
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Publication Date
Sun Jun 20 2021
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
MULTIVARIATE ANALYSIS OF THE STEM ANATOMICAL CHARACTERS OF TERMINALIA L. (COMBRETACEAE) IN EGYPT
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A comparative investigation of the anatomical characters through a microscopical examination of the prepared transverse sections of the stem was carried out. Six plates with 32 photomicrographs were provided to convincingly show the considerable variations of anatomical characters within the nine examined species. The matrix of 18 anatomical characters which included nine quantitative and nine qualitative was applied for the clustering analysis (CA) followed by the principal component analysis (PCA) using the Multivariate Analysis of Ecological Data, PC-ORD.
The results exhibited significant variations among the species resulting in the construction of an artificial key; this key accurately represents a sufficient tool to display the

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Publication Date
Tue Nov 15 2022
Journal Name
Nasaq Journal
Componential Analysis of Hatred Synonymy in the Lexicons of English and Standard Arabic
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ABSTRACT This paper has a three-pronged objective: offering a unitary set of semantic distinctive features to the analysis of nominal “hatred synonyms” in the lexicon of both English and Standard Arabic (SA), applying it procedurally to test its scope of functionality crosslinguistically, and singling out the closest noun synonymous equivalents among the membership of the two sets in this particular lexical semantic field in both languages. The componential analysis and the matching procedures carried have been functional in identifying ten totally matching equivalents (i.e. at 55.6%), and eight partially matching ones (i.e. at %44.4%). This result shows that while total matching equivalences do exist in the translation of certain Eng

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Publication Date
Thu Oct 08 2026
Journal Name
Journal Of Physical Education
The impact of proposed approach for flexibility and agility in learning some basic skills on the table land movements in the artistic gymnastics
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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Synthesis, characterization, molecular docking, ADMET prediction, and anti-inflammatory activity of some Schiff bases derived from salicylaldehyde as a potential cyclooxygenase inhibitor
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A series of Schiff base-bearing salicylaldehyde moiety compounds (1-4) had been designed, synthesized, subjected to insilico ADMET prediction, molecular docking, characterization by FT-IR, and CHNS analysis techniques, and finally to their Anti-inflammatory profile using cyclooxygenase fluorescence inhibitor screening assay methods along with standard drugs, celecoxib, and diclofenac. The ADMET studies were used to predict which compounds would be suitable for oral administration, as well as absorption sites, bioavailability, TPSA, and drug likeness. According to the results of ADME data, all of the produced chemicals can be absorbed through the GIT and have passed Lipinski’s rule of five. Through molecular docking with PyRx 0.8, these

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Publication Date
Tue Mar 01 2016
Journal Name
International Journal Of Engineering Research And Advanced Technology (ijerat)
Speeding Up Back-Propagation Learning (SUBPL) Algorithm: A New Modified Back_Propagation Algorithm
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The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.

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Publication Date
Fri May 16 2025
Journal Name
Asean Journal Of Science And Engineering
Enhancing Predictive Maintenance in Energy Systems Using a Hybrid Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) Framework for Rotating Machinery
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This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K

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Publication Date
Sun Apr 03 2016
Journal Name
Journal Of Educational And Psychological Researches
The impact of the model and follows on the collection and Retention of fifth grade students (oiterary) in history
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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

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Publication Date
Tue May 06 2025
Journal Name
Aip Conference Proceedings
Enhance the performance of the wind turbine blade based on the blade element momentum theory
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In order to improve the effectiveness, increase the life cycle, and avoid the blade structural failure of wind turbines, the blades need to be perfectly designed. Knowing the flow angle and the geometric characteristics of the blade is necessary to calculate the values of the induction factors (axial and tangential), which are the basis of the Blade Element Momentum theory (BEM). The aforementioned equations form an implicit and nonlinear system. Consequently, a straightforward iterative solution process can be used to solve this problem. A theoretical study of the aerodynamic performance of a horizontal-axis wind turbine blade was introduced using the BEM. The main objective of the current work is to examine the wind turbine blade’s perf

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Publication Date
Sat Jul 22 2023
Journal Name
Journal Of Engineering
Fatigue Analysis of Hip Prosthesis
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The present work covers the analytical design process of three dimensional (3-D) hip joint prosthesis with numerical fatigue stress analysis. The analytical generation equations describing the different stem constructive parts (ball, neck, tour, cone, lower ball) have been presented to reform the stem model in a mathematical feature. The generated surface has been introduced to FE solver (Ansys version 11) in order to simulate the induced dynamic stresses and investigate the effect of every design parameter (ball radius, angle of neck, radius of neck, neck ratio, main tour radius, and outer tour radius) on the max. equivalent stresses for hip prosthesis made from titanium alloy. The dynamic loading case has been studied to a stumbling ca

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