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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
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Processing of missing values in survey data using Principal Component Analysis and probabilistic Principal Component Analysis methods
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The idea of ​​carrying out research on incomplete data came from the circumstances of our dear country and the horrors of war, which resulted in the missing of many important data and in all aspects of economic, natural, health, scientific life, etc.,. The reasons for the missing are different, including what is outside the will of the concerned or be the will of the concerned, which is planned for that because of the cost or risk or because of the lack of possibilities for inspection. The missing data in this study were processed using Principal Component  Analysis and self-organizing map methods using simulation. The variables of child health and variables affecting children's health were taken into account: breastfeed

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Publication Date
Sun May 01 2016
Journal Name
International Journal Of Computer Applications
Lossless Image Compression using Adaptive Predictive Coding of Selected Seed Values
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Publication Date
Tue Jan 30 2024
Journal Name
International Journal Of Engineering Pedagogy (ijep)
The Impact of Two Proposed Strategies Based on Active Learning on Students' Achievement at the Computer and Their Social Intelligence
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Active learning is a teaching method that involves students actively participating in activities, exercises, and projects within a rich and diverse educational environment. The teacher plays a role in encouraging students to take responsibility for their own education under their scientific and pedagogical supervision and motivates them to achieve ambitious educational goals that focus on developing an integrated personality for today’s students and tomorrow’s leaders. It is important to understand the impact of two proposed strategies based on active learning on the academic performance of first-class intermediate students in computer subjects and their social intelligence. The research sample was intentionally selected, consis

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Proposed method to estimate missing values in Non - Parametric multiple regression model
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In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.

 

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Forecasting the financial failure of Islamic banks using the Altman model, ---- springate model and ---- Sherrod model / an analytical study in Islamic banks listed on the Iraq Stock Exchange
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Profit is a goal sought by all banks because it brings them income and guarantees them survival and continuity, and on the other hand, facing commitments without financial crisis. Hence the idea of research in his quest to build scientific tools and means that can help bank management in particular, investors, lenders and others to predict financial failure and to detect early financial failures. The research has produced a number of conclusions, the most important of which is that all Islamic banks sample a safe case of financial failure under the Altman model, while according to the Springate model all Islamic banks sample a search for a financial failure except the Islamic Bank of Noor Iraq for Investment and Finance )BINI(. A

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Publication Date
Sat Mar 26 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Role of Big Data applications in forecasting corporate bankruptcy: Field analysis in the Saudi Business Environment
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This study aimed to investigate the role of Big Data in forecasting corporate bankruptcy and that is through a field analysis in the Saudi business environment, to test that relationship. The study found: that Big Data is a recently used variable in the business context and has multiple accounting effects and benefits. Among the benefits is forecasting and disclosing corporate financial failures and bankruptcies, which is based on three main elements for reporting and disclosing that, these elements are the firms’ internal control system, the external auditing, and financial analysts' forecasts. The study recommends: Since the greatest risk of Big Data is the slow adaptation of accountants and auditors to these technologies, wh

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Publication Date
Wed Oct 07 2020
Journal Name
Journal Of Interdisciplinary Mathematics
Discrete an SIS model with immigrants and treatment
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In this paper, a discrete SIS epidemic model with immigrant and treatment effects is proposed. Stability analysis of the endemic equilibria and disease-free is presented. Numerical simulations are conformed the theoretical results, and it is illustrated how the immigrants, as well as treatment effects, change current model behavior

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Publication Date
Sun Jul 02 2017
Journal Name
Journal Of Educational And Psychological Researches
Analysis of third intermediate chemistry book following sustainable development standards
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The current research seeks to Analyze third intermediate chemistry book following sustainable development standards for academic year (2016-2017). To do this, a list of sustainable development standards that should be included in chemistry book was designed based on the previous studies. The first version of the list consisted of (50) sub-case divided into three standards (social, economic, and environmental) which was exposed to group of experts in teaching chemistry and teaching methods. The list has modified to (43) sub-case. The researcher followed the implicit and explicit meaning in his analysis: one for recording and repetition and the other for frequency. The result showed that third intermediate chemistry book has achieved (20)

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Analysis the Causal Relationship between Oil Exports and Economic Growth in Iraq
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The oil exports play a vital role in supporting economic development and raise the economic growth. The oil exports can increase the economic growth via three main channels which are supporting the productive, distributive and service sectors; increasing the investment and capital formation; and increasing the employment rate.

However, the oil exports did not have an important role in increasing the economic growth in Iraq. Therefore, it also did not provide the required support to other economic sectors, neither participated in increase the employees’ skills nor increase the investment rate. It may slightly contribute in enhancement the infrastructure that can attract the public and private investments

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Publication Date
Fri Nov 01 2019
Journal Name
Journal Of Physics: Conference Series
The Bifurcation analysis of Prey-Predator Model in The Presence of Stage Structured with Harvesting and Toxicity
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Abstract<p>For a mathematical model the local bifurcation like pitchfork, transcritical and saddle node occurrence condition is defined in this paper. With the existing of toxicity and harvesting in predator and prey it consist of stage-structured. Near the positive equilibrium point of mathematical model on the Hopf bifurcation with particular emphasis it established. Near the equilibrium point E<sub>0</sub> the transcritical bifurcation occurs it is described with analysis. And it shown that at equilibrium points E<sub>1</sub> and E<sub>2</sub> happened the occurrence of saddle-node bifurcation. At each point the pitch fork bifurcation occurrence is not happened. </p> ... Show More
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