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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
Fri Jun 18 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Quadtree partitioning scheme of color image based
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Publication Date
Sat Jan 01 2022
Journal Name
Proceeding Of The 1st International Conference On Advanced Research In Pure And Applied Science (icarpas2021): Third Annual Conference Of Al-muthanna University/college Of Science
Dimensional analysis of predicting the removal of chemical oxygen demand from domestic wastewater using moving bed biofilm reactor
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Municipal wastewater sources are becoming increasingly important for reuse, for irrigation purposes, so they must be treated to meet environmentally friendly local or global standards. The aim of this study is to establish, calibrate, and validate a model for predicting chemical oxygen demand for the pilot plant of mobile biofilm reactors operating from municipal wastewater in Maaymyrh located in Hilla city Using the approach of dimensional analysis. The approach of Buckingham's theorem was used to derive a model of dimensional analysis design for the forecast of (COD) in the pilot plant. The effluent concentration (COD) It has been derived as a result of the influential concentration of (COD), dissolved oxygen (DO), volume of pilot plant

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Publication Date
Mon Jan 01 2024
Journal Name
مجلة الدراسات المستدامة
The Quality of University Environment According to the Viewpoint of Female Students: The College of Sciences for Woman an Example
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This research aims at identifying the level of quality of University environment according to the viewpoint of female students taking the College of Sciences for Woman an example, as represented in the college units as registration unit and the unit of students' affairs, the curricula, instructors, study halls, the college library, scientific labs, computer access, stationary and photocopying services, health care center, the unit of artistic, cultural and sportive activity, the canteen, the college gardens, college buildings and equipment and bathrooms. To achieve the objectives of the research, the researcher prepared a questionnaire to identify the viewpoints of female students concerning the extent of the availability of the standards o

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Publication Date
Thu Dec 28 2023
Journal Name
Al–bahith Al–a'alami
Contents of the photo coverage of the Gulf Cup Championship on the pages of photojournalists on Instagram: An analytical study
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This study intends to examine the content of photo coverage related to the Gulf Cup (Gulf 25) as presented by Iraqi photojournalists on Instagram between 02/01/2023 and 27/01/2023. Utilizing content analysis, the two researchers employed the survey method to evaluate 674 digital photos posted by seven photojournalists specializing in this sporting event, which concluded with the Iraqi team's victory in the city of Basra.
Key findings from the study include:
1. The Category "Photos from the Gulf Cup matches" predominated, accounting for 291 instances or 42.794% of the total.
2. Photojournalists exhibited a keen interest in capturing images of attending fans and documenting celebrations surrounding th

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Water Resource And Hydraulic Engineering (jwrhe)
Large Scale Field Physical Model Simulation of Roseires Dam-Break, Sudan
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Physically based modeling approach has been widely developed in recent years for the simulation of dam failure process due to the lack of field data. This paper provides and describes a physically-based model depending on dimensional analysis and hydraulic simulation methods for estimating the maximum water level and the wave propagation time from breaching of field test dams. The field physical model has been constructed in Dabbah city to represent the collapse of the Roseires dam in Sudan. Five cases of a dam failure were studied to simulate water flood conditions by changing initial water height in the reservoir (0.8, 1.0, 1.2, 1.4 and 1.5 m respectively).The physical model working under five cases, case 5 had the greatest influence of t

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Publication Date
Mon Apr 04 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of Electronic System Based on Cloud Computing to Develop Electronic Tasks for Students of the University of Mosul
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The present research aims to design an electronic system based on cloud computing to develop electronic tasks for students of the University of Mosul. Achieving this goal required designing an electronic system that includes all theoretical information, applied procedures, instructions, orders for computer programs, and identifying its effectiveness in developing Electronic tasks for students of the University of Mosul. Accordingly, the researchers formulated three hypotheses related to the cognitive and performance aspects of the electronic tasks. To verify the research hypotheses, a sample of (91) students is intentionally chosen from the research community, represented by the students of the college of education for humanities and col

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Publication Date
Sat Feb 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Performance of piled raft foundations under the effect of dewatering nearby an open pit
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Abstract<p>The dewatering arrangement is required in execution works and it needs more attention due to the additional vertical settlement produced on the adjacent pile foundations. Raft foundations are being increasingly utilized for construction in cases of subsoil conditions with a high water table. Also, soil displacements in adjacent un-braced deep open pit may be a reason for high damages to the close buildings and foundations systems. The aim of this study is to examine the behaviour of piled raft foundations considering different pile locations under the effect of line drain and stage drilling of nearby open foundation pit. The line drain was used as dewatering process through the soil i</p> ... Show More
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Publication Date
Sun Jul 26 2026
Journal Name
Journal Of Baghdad College Of Dentistry
An evaluation of an Iraqi phosphate-bonded investment and a commercial type on the marginal fit of ceramometalcopings using three different investing and burnout techniques
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Background: The accuracy of fitness of any dental casting is imperative for the success of any prosthodontic treatment. From the time that dental casting was first introduced, efforts have been made to produce more accurate and better fitted castings with minimal marginal discrepancy. The aim of this in vitro study was to evaluate the effects of three different investing and burnout techniques on the vertical marginal discrepancies ofceramometalcopings invested with two types of phosphate- bonded investments. Materials and methods: Sixty wax patterns were fabricated on a standardized prepared brass die representing an upper central incisor by the aid of a custom-made split mold. Three different investing and burnout techniques were applied

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Publication Date
Tue Jan 11 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Effect of Anabasis articulata Stems Extract on Lowering Intraocular Pressure in the Glaucoma Rat Model(Conference Paper )#
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High intraocular pressure (IOP) is a recognized risk factor for glaucoma and optic nerve injury, and it is one of the primary causes of vision loss globally. Anabasis articulata (AA) is a desert plant found in Iraq. The extract of AA is used to cure diabetes, fever, eczema, and kidney infections. The aim of the study is to evaluate the antioxidant effect of methanol extract of AA on intraocular pressure in the glaucoma rat model. Forty-two rats were allocated into seven groups, each with six animals:: group 1 (normal), group 2 (control), in which animals were induced to have elevated IOP by betamethasone suspension injection, groups 3,4 and 5 for evaluating the effect of 50,100 and 150 mg/kg/day of the tested extract, respective

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Publication Date
Mon Jun 01 2026
Journal Name
Iraqi Journal For Computers And Informatics
Explainable Federated Learning for Brain Tumor Classification Using Multi-Source MRI Data
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Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings

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