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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
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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Publication Date
Tue Jun 08 2021
Journal Name
مجلة العلوم و التكنولوجية للنشاطات البدنية و الرياضية
The effectiveness of using (7E’s) learning cycle in learning a movement chain on the uneven bars in the artistic gymnastics for women
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Abstract The Object of the study aims to identify the effectiveness of using the 7E’s learning cycle to learn movement chains on uneven bars, for this purpose, we used the method SPSS. On a sample composed (20) students on collage of physical education at the university of Baghdad Chosen as two groups experimental and control group (10) student for each group, and for data collection, we used SPSS After collecting the results and having treated them statistically, we conclude the use 7E’s learning cycle has achieved remarkable positive progress, but it has diverged between to methods, On this basis, the study recommended the necessity of applying 7E’s learning cycle strategy in learning the movement chain on uneven bar

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Iraqi stock market structure analysis based on minimum spanning tree
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tock markets changed up and down during time. Some companies’ affect others due to dependency on each other . In this work, the network model of the stock market is discribed as a complete weighted graph. This paper aims to investigate the Iraqi stock markets using graph theory tools. The vertices of this graph correspond to the Iraqi markets companies, and the weights of the edges are set ulrametric distance of minimum spanning tree.

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Publication Date
Sun Nov 04 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
MEASURING OBESITYLEVEL BY BIO-ELECTRICAL IMPEDANCE ANALYSIS TECHNIQUE AND COMPARED TO TRADITIONAL METHODS: MEASURING OBESITYLEVEL BY BIO-ELECTRICAL IMPEDANCE ANALYSIS TECHNIQUE AND COMPARED TO TRADITIONAL METHODS
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This study aimed to determine obesity level of some population in Baghdad by using Bio-electrical impedance analysis (BIA) and compared with anthropometric measurements such as body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR). Statistical analysis results of linear correlation coefficients for obesity indicators showed that BIA correlation 0.92 was most significant and reliable for obesity measurement.

Results of BIA method for age group 20-29 years showed that 44.4% of females were healthy body while 37.8% of males suffer from increased body fat. Results of age group 30-39 year showed that 32.6 of females were in healthy body and 42% of males were obese. In case age group 40-4

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Publication Date
Fri Oct 31 2025
Journal Name
Mathematical Modelling Of Engineering Problems
Heterogeneous Traffic Management in SDN-Enabled Data Center Network Using Machine Learning-SPIKE Model
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Software-Defined Networking (SDN) has evolved network management by detaching the control plane from the data forwarding plane, resulting in unparalleled flexibility and efficiency in network administration. However, the heterogeneity of traffic in SDN presents issues in achieving Quality of Service (QoS) demands and efficiently managing network resources. SDN traffic flows are often divided into elephant flows (EFs) and mice flows (MFs). EFs, which are distinguished by their huge packet sizes and long durations, account for a small amount of total traffic but require disproportionate network resources, thus causing congestion and delays for smaller MFs. MFs, on the other hand, have a short lifetime and are latency-sensitive, but they accou

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Convergence Analysis for the Homotopy Perturbation Method for a Linear System of Mixed Volterra-Fredholm Integral Equations
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           In this paper, the homotopy perturbation method (HPM) is presented for treating a linear system of second-kind mixed Volterra-Fredholm integral equations. The method is based on constructing the series whose summation is the solution of the considered system. Convergence of constructed series is discussed and its proof is given; also, the error estimation is obtained. Algorithm is suggested and applied on several examples and the results are computed by using MATLAB (R2015a). To show the accuracy of the results and the effectiveness of the method, the approximate solutions of some examples are compared with the exact solution by computing the absolute errors.

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Predictive Significance of Interleukins 17A and 33 in Risk of Relapsing–Remitting Multiple Sclerosis
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Cytokines are signaling molecules between inflammatory cells that play a significant role in the pathogenesis of a disease. Among these cytokines are interleukins (ILs) 17A and 33, and accordingly, the current case-control study sought to investigate the role of each of the two cytokines in the risk of developing multiple sclerosis (MS). Sixty-eight relapsing-remitting MS (RRMS) Iraqi patients and twenty healthy individuals (control group) were enrolled. Enzyme linked immunosorbent assay (ELISA) kits were used to determine serum levels of IL-17A and IL-33. Results revealed that IL-17A and IL-33 levels were significantly higher in MS patients than in controls (14.1 ± 4.5 vs. 7.5 ± 3.8 pg/mL; p < 0.001 and 65.3 ± 16

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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of The College Of Languages (jcl)
Analisis de la metáfora en la poema " Noche oscura del alma" de San Juan de la Cruz Analysis metaphor in the poem "Dark Night of the Soul" John of the Cross
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RESUMEN

 Una joven cuenta cómo, en plena noche, aprovechando la tranquilidad de esa hora, sale a escondidas de su casa y va a reunirse con su enamorado. Envuelta en la oscuridad, se deja dirigir por la luz de su propio amor hasta el lugar de la cita, donde la pasión de los amantes culmina. A continuación, relajados por la brisa nocturna, los amantes se adormecen, primero, el amado velado por la amada, por último, ella misma.

Amor entre dos enamorados. Unión mística de alma y Dios , aunque , de hecho , podría servirnos de clara exposición temática el subtitulo con que el poema suele publicarse en la tradición , tanto manuscrita como impresa : Canciones del alma que se goza d

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Publication Date
Mon Sep 20 2021
Journal Name
College Of Islamic Sciences
Positive images in the Holy Quran The story of Solomon - peace be upon him - in Surat An-Naml is a model An objective study
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God Almighty put in his great book secrets that do not end, and wonders that do not expire, for he is the one from which the scholars are not satisfied, and he does not create due to the multitude of response, and it is the comprehensive and inhibitory book that God conceals to the worlds, and he challenged the two heavyweights to come up with something like it.

At all times, issues arise in the Noble Qur’an that fit the needs of the people of that time and their culture, for it is an eternal book, characterized by the ability to give, extend and respond to addressing the problems of the age and its variables, when the Arabs had little luck at the time of the message’s descent from the scientific culture, and their proficienc

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Publication Date
Thu Dec 31 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Application of data content analysis (DEA) technology to evaluate performance efficiency: applied research in the General Tax Authority
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The aim of the research is to use the data content analysis technique (DEA) in evaluating the efficiency of the performance of the eight branches of the General Tax Authority, located in Baghdad, represented by Karrada, Karkh parties, Karkh Center, Dora, Bayaa, Kadhimiya, New Baghdad, Rusafa according to the determination of the inputs represented by the number of non-accountable taxpayers and according to the categories professions and commercial business, deduction, transfer of property ownership, real estate and tenders, In addition to determining the outputs according to the checklist that contains nine dimensions to assess the efficiency of the performance of the investigated branches by investing their available resources T

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