Preferred Language
Articles
/
bsj-8504
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
...Show More Authors

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.

Scopus Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of the relationship of public budget deficit on external debt in lraq with in the framework of joint integration of the period (1990 – 2016 )
...Show More Authors

 

Abstract

The term public budget defects became nowadays a chronic, economical phenomenon, almost all the countries weather advanced or development country suffered from it, despite the different visions to economic schools of a thought to accept or reject the deficit in public budget but the prevailed opinion that is needed to rule the role of the state by reducing the public spending which led to continuous deficits in public budget and the consequent upon increase in government borrowing, increase taxes on income and wealth, thus weakening the in contrive for private investment which contributed to the increase of in flationary stagnation, it became a duty to state covered by the lack of financial sources

... Show More
View Publication Preview PDF
Crossref
Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Determining the Mobility of some Essential Elements in Saffron (Crocus sativus L.) by the Neutron Activation Analysis
...Show More Authors

The main purpose of this investigation is to evaluate the concentrations of six essential metals (Na+, Mg2+, K+, Ca2+, Fe2+ and Zn2+) in saffron and a farm soil using the neutron activation analysis (NAA) as a nuclear spectrometry method. The stratified random sampling method was used here. The NAA results showed the well uptake of Mg2+, K+, Ca2+, Fe2+, and Zn2+ in saffron, which is lower than the toxicity range. Based on the contamination factor and geoaccumulation index, soil contamination levels were determined uncontaminated by Zn, moderately contaminated by Na+ and Fe2+, and strongly contamin

... Show More
View Publication Preview PDF
Scopus (6)
Crossref (5)
Scopus Clarivate Crossref
Publication Date
Thu Jun 29 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications (ijnaa)
Applying a suitable approximate-simulation technique of an epidemic model with random parameters
...Show More Authors

Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat

... Show More
Publication Date
Tue Dec 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of relations and forces of production in extraction And pearl industry in the Arabian Gulf 1900-1950 *
...Show More Authors

بسبب محدودية الموارد الطبيعية، فأن سكان الخليج ومنذ القدم وجهوا جلّ نشاطاتهم توجهاً بحرياً: صيد الاسماك وصناعة اللؤلؤ العنصر الرئيس في حجم التشغيل، وتكوين الفائض الاقتصادي في المنطقة آنذاك.

لقد تزايدت أهمية هذا النشاط بخاصة بعد النصف الثاني من القرن التاسع عشر، لرواج تجارة اللؤلؤ عالمياً، وأنفتاح الخليج على الدول الاوروبية التي شهدت نهضة صناعية متسارعة، وحيث وصلت الخليج العديد من بضائع

... Show More
View Publication Preview PDF
Crossref
Publication Date
Tue Aug 01 2017
Journal Name
Journal Of Engineering
Rigid trunk sewer deterioration prediction models using multiple discriminant and neural network models in Baghdad city, Iraq
...Show More Authors

The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the

... Show More
Publication Date
Mon Jul 31 2017
Journal Name
Journal Of Engineering
Rigid Trunk Sewer Deterioration Prediction Models using Multiple Discriminant and Neural Network Models in Baghdad City, Iraq
...Show More Authors

View Publication Preview PDF
Publication Date
Sun Dec 31 2023
Journal Name
College Of Islamic Sciences
The relationship between the rule of mental improvement and ugliness and the objectives of Sharia And its impact on rulings
...Show More Authors

The research addresses a fundamental Islamic jurisprudential Purposeful issue, which is (Sharia), and to indicate the impact of this on Islamic jurisprudence, deriving rulings and extracting purposes, and to repel the illusion that this issue is only doctrinal, and clarifying the aspects of similarities and links between them by explaining the origin of deriving the purposes of Islamic Law (Sharia) through the meanings and wisdom learned from the texts and the explanation of the rulings. The rulings of Islamic Law (Sharia) have urged bringing benefits and repelling harms, and that the path to do so is reason and its production. I began the research by defining the purposes of Islamic Law (Sharia), then defining the rule of rational right

... Show More
View Publication Preview PDF
Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Robust Two-Step Estimation and Approximation Local Polynomial Kernel For Time-Varying Coefficient Model With Balance Longitudinal Data
...Show More Authors

      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
The effect of Analysis of internal environment in the quality of health care service survey study at AL_Elwiya Maternity Teaching Hospital
...Show More Authors

he current research aims at showing the correlation and effect of the internal environment analysis in the quality of health service in AL_Elwiya Maternity Teaching Hospital, researcher depended on the integral method in the "analytical descriptive method" for the study of the relation between the main variables and the sub-variables throughout data collection required by the theme of this study, a case study" in tackling the data and information related to the financial aspects of the internal environment.

The problem of the study was manifested in the essential question, that is (is there internal struc

... Show More
View Publication Preview PDF
Crossref
Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
...Show More Authors

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

... Show More
View Publication Preview PDF
Scopus (11)
Crossref (5)
Scopus Crossref