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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 Jan 01 2019
Journal Name
Inorganica Chimica Acta
Synthesis, characterisation and electrochemistry of eight Fe coordination compounds containing substituted 2-(1-(4-R-phenyl-1H-1,2,3-triazol-4-yl)pyridine ligands, R = CH3, OCH3, COOH, F, Cl, CN, H and CF3.
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Eight different Dichloro(bis{2-[1-(4-R-phenyl)-1H-1,2,3-triazol-4-yl-κN3]pyridine-κN})iron(II) compounds, 2–9, have been synthesised and characterised, where group R=CH3 (L2), OCH3 (L3), COOH (L4), F (L5), Cl (L6), CN (L7), H (L8) and CF3 (L9). The single crystal X-ray structure was determined for the L3 which was complemented with Density Functional Theory calculations for all complexes. The structure exhibits a distorted octahedral geometry, with the two triazole ligands coordinated to the iron centre positioned in the equatorial plane and the two chloro atoms in the axial positions. The values of the FeII/III redox couple, observed at ca. −0.3 V versus Fc/ Fc+ for complexes 2–9, varied over a very small potential range of 0.05 V.

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Publication Date
Wed Jan 13 2021
Journal Name
Iraqi Journal Of Science
MRI Probabilistic Neural Network Screening System: a benign and malignant recognition case study
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This work is aimed to design a system which is able to diagnose two types of tumors in a human brain (benign and malignant), using curvelet transform and probabilistic neural network. Our proposed method follows an approach in which the stages are preprocessing using Gaussian filter, segmentation using fuzzy c-means and feature extraction using curvelet transform. These features are trained and tested the probabilistic neural network. Curvelet transform is to extract the feature of MRI images. The proposed screening technique has successfully detected the brain cancer from MRI images of an almost 100% recognition rate accuracy.

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Using Backpropagation to Predict Drought Factor in Keetch-Byram Drought Index
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Forest fires continue to rise during the dry season and they are difficult to stop. In this case, high temperatures in the dry season can cause an increase in drought index that could potentially burn the forest every time. Thus, the government should conduct surveillance throughout the dry season. Continuous surveillance without the focus on a particular time becomes ineffective and inefficient because of preventive measures carried out without the knowledge of potential fire risk. Based on the Keetch-Byram Drought Index (KBDI), formulation of Drought Factor is used just for calculating the drought today based on current weather conditions, and yesterday's drought index. However, to find out the factors of drought a day after, the data

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Automatic voice activity detection using fuzzy-neuro classifier
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Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

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Publication Date
Sun Dec 19 2021
Journal Name
Iraqi Journal Of Science
Geological Modeling for Yamama Formation in Abu Amood Oil Field
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3D geological model of a simple petroleum reservoir for Yamama Formation has
been built in Abu Amood Oil Field using Petrel software, which is a product of
Schlumberger. This model contains the structure, stratigraphy and reservoir
properties (porosity and water saturation) in three directions(X, Y and Z).Geologic
modeling is an applied science of creating computerized representations of portions
of the earth's crust, especially oil and gas fields.
Yamama Formation in Abu Amood Oil Field is divided into thirteen zones by
using well logs and their petrophysical properties, six of which are reservoir zones.
From the top of the formation these six zones are: (YB-1, YB-2, YB-3, YC-1, YC-2
and YC-3). These reservoir

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Publication Date
Sat Dec 26 2020
Journal Name
International Journal Of Pharmaceutical Research
Complexes of Co(II), Cu(II), Ni(II), Pt(II) And Pd(II) with N 3 O-Chelating Ligand Incorporating Azo and Schiff Base Moieties: Synthesis, Spectroscopic, Thermal Decomposition, Theoretical Studies, and thermodynamic parameters
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Publication Date
Sat Sep 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Synthesis and Charact'erizatio.n of new Schiff base ligand [(2-{1-[(2 hydraxy­ benzylidene)-hydrazono]-ethyl} benzene-I, 3, 5--triol.] and it's CQmp.lexes. with Co en\ Ni . (U),, c·u(U)' and · zn(II).
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The eaction  of 2 4 .6-trihydroxyactophenonemonohydra1e  with

l hydr.azine monohydrate was realized ti·nder reflu.(( in methanol and i:l.

Jew drops of glacial acetic acid we.re added to give lhe'(int rmediate)

2-(1hydr pno-ctbyt)-benzcne-·1.3.5-r:Qql,       which      reacted     wittl

saEcy.laldehyde. jn methm)ql to gjy;e 'a new :tyRe CNzOi) Ligand  (H:flL]

f(2-{1-[(2-=bydroxy-bertzylide·ne)-bydrazqoo,J-e·thy.1}bcnze·neJ ;3·,5

of

 

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Publication Date
Thu Mar 25 2021
Journal Name
International Journal Of Drug Delivery Technology
Synthesis, Structural Study, and Biological Activity Evaluation of VO(II), Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II), and Hg(II) Complexes with New Schiff Base Ligand Derived from Pyrazine
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New Schiff base [3-(3-acetylthioureido)pyrazine-2-carboxylic acid][L] has been prepared through 2 stages, the chloro acetyl chloride has been reacting with the ammonium thiocyanate in the initial phase for producing precursor [A], after that [A] has been reacting with the 3-amino pyrazine-2-carboxilic acid to provide a novel bidentate ligand [L], such ligand [L] has been reacting with certain metal ions in the Mn(II), VO(II), Ni(II), Co(II), Zn(II), Cu(II), Hg(II), and Cd(II) for providing series of new metal complexes regarding general molecular formula [M(L)2XY], in which; VO(II); X=SO4,Y=0, Co(II), Mn(II), Cu(II), Ni(II), Cd(II), Zn(II), and Hg(II); Y=Cl, X=Cl. Also, all the compounds were characterized through spectroscopic techniques [

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Physics
Detection of Physical and Chemical Parameters Using Water Indices (NDWI, MNDWI, NDMI, WRI, and AWEI) for Al-Abbasia River in Al-Najaf Al-Ashraf Governorate Using Remote Sensing and Geographic Information System (GIS) Techniques
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The purpose of this study was to find out the connection between the water parameters that were examined in the laboratory and the water index acquired from the examination of the satellite image of the study area. This was accomplished by analysing the Landsat-8 satellite picture results as well as the geographic information system (GIS). The primary goal of this study is to develop a model for the chemical and physical characteristics of the Al-Abbasia River in Al-Najaf Al-Ashraf Governorate. The water parameters employed in this investigation are as follows: (PH, EC, TDS, TSS, Na, Mg, K, SO4, Cl, and NO3). To collect the samples, ten sampling locations were identified, and the satellite image was obtained on the

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Publication Date
Wed Apr 25 2018
Journal Name
Oriental Journal Of Chemistry
Diagnosis, Structure, and In vitro Antimicrobial and Antifungal Evaluation of some Amino benzoic acids, derived Ligand Schiff base and their Mixed Complexes with Cu(II), Hg(II), Mn(II), Ni(II) and Co(II)
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