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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
Mon May 23 2022
Journal Name
The International Journal Of Artificial Organs
Quantitative analysis and control of the torque profile of the upper limb using a kinetic model and motion measurements
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This paper investigates a new approach to the rapid control of an upper limb exoskeleton actuator. We used a mathematical model and motion measurements of a human arm to estimate joint torque as a means to control the exoskeleton’s actuator. The proposed arm model is based on a two-pendulum configuration and is used to obtain instantaneous joint torques which are then passed into control law to regulate the actuator torque. Nine subjects volunteered to take part in the experimental protocol, in which inertial measurement units (IMUs) and a digital goniometer were used to measure and estimate the torque profiles. To validate the control law, a Simscape model was developed to simulate the arm model and control law in which measurem

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Publication Date
Sat Jun 01 2024
Journal Name
Results In Engineering
Stability analysis for the phytoplankton-zooplankton model with depletion of dissolved oxygen and strong Allee effects
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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Analysis of actuarial experience and acceptance of individual life insurance: A case study in the Iraqi General Insurance Company
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This research seeks through the adoption of two basic variables, where he considered the actuarial experience as an independent variable, while the process of accepting the risk and dimensions related to it is a dependent variable, the research was adopted to present the data achieved by the company during the life insurance business during the adoption of actuarial experience at the beginning of its work where Adoption of the historical method in the analysis of those data to prove the researcher's opinion, through the analysis of data (5 years) for the first period, which extends between (1975-1979), the period during which the company adopted the actuarial experience at the time, also taken data for the same dimensions related to the

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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Measuring and analyzing the demand function for agricultural imports in Iraq for the period (1980-2012) in Autoregressive Distributed Lag Model(ARDL)
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Abstract:

The issues related to foreign trade is a broad field for discussions and captures the interest of economists for their contribution to the process of economic development in the economies of the countries, especially developing ones. The imports of goods and services in foreign trade constitute an important part of the local by which the economy gets goods and services that the economy cannot produce because of the incompetent base of production. Further, the demand function of imports occupied a good deal of the attention of researchers in the field of international economics for which agricultural imports constitute an important part. The reason for the interest in the subject is due to its im

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Examining the Asymmetric Impacts of Interest and Exchange Rate on Investment in Egypt for the Period 1976-2020: Applying NARDL Model
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Most of the studies conducted in the past decades focused on the effect of interest rates and exchange rates on domestic investment under the assumption that the independent variables have the same effect on the dependent variable, but there were limited studies that investigated the unequal effects of changes in interest rates and exchange rates, both positive and negative, on domestic investment.  This study used a nonlinear autoregressive distributed lag (NARDL) model to assess the unequal effects of the real interest rate and real exchange rate variables on domestic investment in Egypt for the period 1976 - 2020.  The results revealed that positive and negative shocks for both exchange rates have unequal effects on

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
1-DOF Model for Fluid-Structure-Interaction Vibration Analysis
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In this paper an attempt to provide a single degree of freedom lumped model for fluid structure interaction (FSI) dynamical analysis will be presented. The model can be used to clarify some important concept in the FSI dynamics such as the added mass, added stiffness, added damping, wave coupling ,influence mass coefficient and critical fluid depth . The numerical results of the model show that the natural frequency decrease with the increasing of many parameters related to the structure and the fluid .It is found that the interaction phenomena can become weak or strong depending on the depth of the containing fluid .The damped and un damped free response are plotted in time domain and phase plane for different model parameters It is fou

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Publication Date
Sun Sep 30 2018
Journal Name
الجامعة المستنصرية كلية الإدارة و الاقتصاد
The possibility of adoption of hybrid cloud computing in Iraqi universities : an analytical study using technology acceptance model
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الناصر، عامر عبد الرزاق عبد المحسن والكبيسي، صلاح الدين عواد كريم. 2018. إمكانية تبني الحوسبة السحابية الهجينة في الجامعات العراقية : دراسة تحليلية باستخدام أنموذج القبول التكنولوجي. مجلة الإدا

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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
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
Mon Apr 01 2013
Journal Name
Al–bahith Al–a'alami
WHAT IS DEMOCRACY? A MEDIA CONCEPT: (Socio-Cultural Linguistic Analysis)
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It is easy to talk about democracy, but it is difficult to practice. We talk about postmodernism, but difficult to be embodied in the ground. Yet, the age of democracy and modernity at the same time prompted the researcher to try to find a media concept for it. It does not mean that this concept has not yet formed. But the rooting of democracy and the approaching of states and groups towards it, made it necessary to by studied again.

The relationship between democracy and the media has made them look like one concept. The existence of one is linked to the existence of the other. The reality is only a linguistic formulation, but the social and cultural aspect is related to democracy origin

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