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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 Jan 04 2024
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Analysis of the performance of the stock market in light of inflation : empirical research in the Iraqi Stock Exchange
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Abstract:

                The aim of this research to try to determine the type of expected relationship between inflation as the explanatory variable and market performance as a dependent variable, for that used data issued and published by the Central Bank of Iraq and the Iraqi Stock Exchange for a sample consisting of (159) observations using the intentional or intentional sampling method for the period extending between the months (January 2010 to March 2023), in the light of each of the Consumer Price Index (CPI), the Iraqi Stock Exchange Index, the number of traded shares and the number of market capital shares to ex

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Publication Date
Mon Jan 01 2024
Journal Name
Russian Electronic Journal Of Radiology
COHORT COMPARATIVE STUDY OF COVID-19 VACCINATED AND NON-VACCINATED PATIENTS DEPENDING ON CT CHEST FINDINGS BETWEEN IRAQI AND JORDANIAN POPULATION
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Publication Date
Fri Jan 20 2023
Journal Name
Bionatura
Impact of inflammatory markers, dread diseases and cycle threshold (Ct) Values in COVID-19 progression. Revis Bionatura 2023; 8 (1) 33
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Publication Date
Sat Jan 31 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
Low-complexity Deep Learning for Joint Channel-type Identification and SNR Estimation in MIMO-OFDM Using CNN–BRNN with LUT Labels
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Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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Publication Date
Mon Jul 17 2023
Journal Name
Journal Of The Iraqi University
Analysis of the Content of the Physics Textbook of the 3rd Intermediate Grade According to the Criteria for Designing and Producing in Fographics
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In this study, the researcher aims to analyze the content of the physics textbook for the 3rd intermediate grade according to the criteria for designing and producing infographics, and the research community consists of the content of the physics textbook for the 3rd intermediate grade intermediate grade for the academic year 2021-2022. The researcher adopted the analysis instruments with a number of the criteria for designing and producing infographics. The results revealed randomness in the percentage of the criteria included in the content of the physics textbook for the 3rd intermediate grade, and they are not compatible with the proposed criteria by the experts also.

Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The impact of governmental consumer spending on the development of the current account balance in Iraq for the period (1990-2014) using ARDL model
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To avoid the negative effects due to inflexibility of the domestic production inresponse to the increase in government consumption expenditure leads to more  imports to meet the increase in domestic demand resulting from the increase in government consumption expenditure. Since the Iraqi economy economy yield unilateral depends on oil revenues to finance spending, and the fact government consumer spending is a progressive high flexibility the increase in overall revenues, while being a regressive flexibility is very low in the event of reduced public revenues, and therefore lead to a deficit in the current account position. And that caused the deficit for imbalance are the disruption of the

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of The College Of Languages (jcl)
A Discoursal Analysis of Gender Differences in Selected English TV Interviews
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     This study aims at discussing how gender differences might affect communication among people. For this purpose, several TV interviews are selected and examined on the discourse level. Developing a model of analysis ,is found that certain linguistics have been used by male speakers ,whereas  different aspects have been utilized my female speakers like deictic expressions and lexical items of emotion and delicacy .

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Publication Date
Mon Sep 01 2014
Journal Name
Journal Of The College Of Education For Women
A Stylistic Analysis of Two Selected Poems: تحليل اسلوبي لقصيدتين مختارتين
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This paper presents a stylistic analysis of two poems of well-known poets of the English literature, namely; E.E. Cummings and the Irish noble laureate Seamus Heaney.  The researcher's attempt here is to approach Cummings’s poem “maggie and milly and molly and may” and Heaney’s “A Kite for Aibhín from the stylistics’ point of view.  The paper also analyzes the poems using the tools of linguistics with a view to make their meaning explicit.

          It is worth noting that stylistics as a scientific discipline is really beneficial to those who are teaching and studyi

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Publication Date
Fri Jun 30 2023
Journal Name
Journal Of The College Of Education For Women
The Construction of the Iraqi Child in the UNICEF Reports during Covid19 Pandemic: A Critical Discourse Analysis
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The present paper aims at investigating the linguistic image portrayed by UNICEF reports on the Iraqi child from a critical discourse analysis perspective during Covid19 pandemic (2020). The paper attempts to fill a gap in research literature concerning the linguistic construction of the Iraqi child by the UNICEF reports during the critical health crisis of Covid19. Van  Leeuwen’s (2008) approach of social actor representation has been adopted for this purpose. From Van  Leeuwen’s approach, the category of determination (single determination and overdetermination) has been selected to be the main analytical tool for its high compatibility with the set of objectives put forward to figure out how such a globally effective and

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