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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 Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Analysing errors in learning the preasent continuous tense:Associating interference with strategy of instruction
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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
A modified Mobilenetv2 architecture for fire detection systems in open areas by deep learning
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Wed Sep 15 2021
Journal Name
Journal Of Baghdad College Of Dentistry
Prevalence of viral co-infection among COVID-19 cases in association disease severity and oral hygiene
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Background: In December 2019, an episode of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARSCoV2) was reported in Wuhan, China and has spread around the world, increasing the number of contagions. Cytomegalovirus (CMV) and Epstein-Barr virus (EBV) are common herpesviruses that can cause persistent latent infections and affect the developing immune system.The study was conducted to explore the prevalence and reactivation of CMV and EBV antibodies in COVID-19 patients group in comparison to healthy group and to investigate the association between the presence of these viruses with each of severity of disease and oral hygiene. Materials and Methods: Eighty Five subjects were participated in this case control study (5

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Publication Date
Sun Jun 27 2021
Journal Name
Iraqi National Journal Of Nursing Specialties
Detection of Depression among Nurses Providing Care for Patients with COVID-19 at Baqubah Teaching Hospital
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Objectives: The present study aims at detecting the depression among nurses who provide care for infected patients with corona virus phenomenon and to find out relationships between the depression and their demographic characteristics of age, gender, marital status, type of family, education, and years of experience of nurses in heath institutions, infection by corona virus, and their participation in training courses.
Methodology: A descriptive study is established for a period from October 10th, 2020 to April 15th, 2021. The study is conducted on a purposive (non-probability) sample of (100) nurse who are providing care for patients with COVID-19 and they are selected from the isolation wards. The instrument of the study is develope

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Publication Date
Sat Jan 01 2022
Journal Name
Annals Of Parasitology
Serum levels of C-reactive protein and ferritin in COVID-19 patients infected with Toxoplasma gondii
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During infection, T. gondii disseminates by the circulatory system and establishes chronic infection in several organs. Almost third of humans, immunosuppressed individuals such as HIV/AIDS patients, cancer patients, and organ transplant recipients are exposed to toxoplasmosis. Therefore, the study aimed to investigate the possibility that Toxoplasma infection could be a risk factor for COVID-19 patients and its possible correlation with C-reactive protein and ferritin. Overall 220 patients referred to the Al Furat General Hospital, Baghdad, Iraq were enrolled from 2020–2021. All serum samples were tested for T. gondii immunoglobulins (IgG and IgM) antibodies, C-reactive protein and ferritin levels. In patients with COVID-19, the results

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Robotics And Control (jrc)
Artificial Intelligence Based Deep Bayesian Neural Network (DBNN) Toward Personalized Treatment of Leukemia with Stem Cells
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The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

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Publication Date
Fri Dec 03 2021
Journal Name
Baghdad Journal Of Biochemistry And Applied Biological Sciences
A clinical-statistical study on COVID-19 infection and death status at the Alshifaa Healthcare Center/ Baghdad
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Background: COVID-19 is an ongoing disease that caused, and still causes, many challenges for humanity. In fact, COVID-19 death cases reached more than 4.5 million by the end of August 2021, although an improvement in the medical treatments and pharmaceutical protocols was obtained, and many vaccines were released. Objective: To, statistically, analyze the data of COVID-19 patients at Alshifaa Healthcare Center (Baghdad, Iraq). Methods: In this work, a statistical analysis was conducted on data included the total number, positive cases, and negative cases of people tested for COVID-19 at the Alshifaa Healthcare Center/Baghdad for the period 1 September – 31 December 2020. The number of people who got the test was 1080, where 424 w

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Publication Date
Sat Dec 24 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Highlighting the Treatment Regimens used in COVID-19 epidemic in Iraq with Special Regards to Vitamin D
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Coronavirus disease 2019 (COVID-19) is a flu-like infection caused by a novel virus known as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). After the widespread around the world, it was announced by the World Health Organization (WHO) as a global pandemic. The symptoms of COVID-19 may arise within 2 weeks and the severity ranged from mild with signs of respiratory infection to severe cases of organ failure and even death. Management of COVID-19 patients includes supportive treatment and pharmacological medications expected to be effective with no definitive cure of the disease. The aims of this study are highlighting the management protocol and supportive therapy especially vitamin D and manifesting the clinical symptoms b

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Technical analysis of the salary scale for public sector employees
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            The research discusses the mechanism for analyzing the salary scale in the public sector through an analysis of grades, their stages, occupants and their financial entitlements, and the extent to which the information obtained for their investment in strategic planning, conducting correction and treatment can be used. The salaries of the employees in them, whose number is (1117) employees, to be a field of research, as the salary structure in it for the year 2019 was analyzed by relying on a number of statistical tools in the analysis process, including the arithmetic circles, upper limits, minimum limits and percentage, and with

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