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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 Nov 01 2022
Journal Name
Environmental Technology & Innovation
Photo-Fenton-like degradation of direct blue 15 using fixed bed reactor containing bimetallic nanoparticles: Effects and Box–Behnken optimization
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This study involved the treatment of textile wastewater contaminated with direct blue 15 dye (DB15) using a heterogeneous photo-Fenton-like process. Bimetallic iron/copper nanoparticles loaded on bentonite clay were used as heterogeneous catalysts and prepared via liquid-phase reduction method using eucalyptus leaves extract (E-Fe/Cu@BNPs). Characterization methods were applied to resultant particles (NPs), including SEM, BET, and FTIR techniques. The prepared NPs were found with porous and spherical shapes with a specific surface area of particles was 28.589 m2/g. The effect of main parameters on the photo-Fenton-like degradation of DB15 was investigated through batch and continuous fixed-bed systems. In batch mode, pH, H2O2 dosage, DB15 c

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Publication Date
Thu Aug 18 2016
Journal Name
Artificial Cells, Nanomedicine, And Biotechnology
Biosynthesis of silver nanoparticles from <i>Catharanthus roseus</i> leaf extract and assessing their antioxidant, antimicrobial, and wound-healing activities
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Publication Date
Wed Sep 22 2021
Journal Name
International Journal Of Corrosion And Scale Inhibition
Synthesis of a CoO–ZnO nanocomposite and its study as a corrosion protection coating for stainless steel in saline solution
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Reaxys Chemistry database information SciVal Topics Metrics Abstract A novel CoO–ZnO nanocomposite was synthesized by the photo irradiation method using a solution of cobalt and zinc complexes and used as a coating applied by electrophoretic deposition (EPD) for corrosion protection of stainless steel (SS) in saline solution. The samples were characterized using powder XRD, scanning electron microscopy (SEM) and electrochemical polarization. It was also found that the coating was still stable after conducting the corrosion test: it contained no cracks and CoO–ZnO nanocomposites clearly appeared on the surface. SEM showed that the significant surface cracking disappeared. XRD confirmed that CoO–ZnO nanocomposites comprised CoO and Zn

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Publication Date
Mon Jan 18 2016
Journal Name
Open Journal Of Biophysics
Structural and Characteristics of Manganese Doped Zinc Sulfide Nanoparticles and Its Antibacterial Effect against Gram-Positive and Gram-Negative Bacteria
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The Manganese doped zinc sulfide nanoparticles of the cubic zinc blende structure with the average crystallite size of about 3.56 nm were synthesized using a coprecipitation method using Thioglycolic Acid as an external capping agent for surface modification. The ZnS:Mn2+ nanoparticles of diameter 3.56 nm were manufactured through using inexpensive precursors in an efficient and eco-friendly way. X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM) and Fourier Transform Infrared (FTIR) spectroscopy are used to examine the structure, morphology and chemical composition of the nanoparticles. The antimicrobial activity of (ZnS:Mn2+) nanocrystals was investigated by measuring the diameter of inhibition zone using well diffusion mechanism

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Publication Date
Sun Mar 06 2022
Journal Name
Nature Environment And Pollution Technology
Green Synthesis Of Bimetallic Iron/Copper Nanoparticles Using Ficus Leaves Extract For Removing Orange G(OG) Dye From Aqueous Medium
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This study shows that it is possible to fabricate and characterize green bimetallic nanoparticles using eco-friendly reduction and a capping agent, which is then used for removing the orange G dye (OG) from an aqueous solution. Characterization techniques such as scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDAX), X-Ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) were applied on the resultant bimetallic nanoparticles to ensure the size, and surface area of particles nanoparticles. The results found that the removal efficiency of OG depends on the G‑Fe/Cu‑NPs concentration (0.5-2.0 g.L-1), initial pH (2‑9), OG concentration (10-50 mg.L-1), and temperature (30-50 °C). The batch experiments showed

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Publication Date
Tue Mar 15 2022
Journal Name
Journal Of Baghdad College Of Dentistry
Natural preparation of rice husk-derived silica and eggshell-derived calcium carbonate composite as a coating material for dental implant
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Background: The world is in front of two emerging problems being scarceness of virgin re-sources for bioactive materials and the gathering of waste production. Employment of the surplus waste in the mainstream production can resolve these problems. The current study aimed to prepare and characterize a natural composite CaO-SiO2 based bioactive material derived from naturally sustained raw materials. Then deposit this innovative novel bioactive coating composite materials overlying Yttria-stabilized tetragonal zirconia substrate. Mate-rials and method; Hen eggshell-derived calcium carbonate and rice husk-derived silica were extracted from natural resources to prepare the composite coating material. The manufac-tured powder was characterized

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Publication Date
Mon Dec 15 2025
Journal Name
Bionatura Journal: Ibero-american Journal Of Biotechnology And Life Sciences
Fourteen Years of Organic Amendments Enhance Soil Organic Carbon in Semiarid Iraqi Soils: FTIR Spectroscopy, PLS Modelling and RothC Simulations
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Long-term organic amendments are a key strategy to build soil organic carbon (SOC) stocks in semiarid agroecosystems, where low biomass inputs and calcareous parent material constrain carbon accumulation. This 14-year field experiment in central Iraq (2000–2014) evaluated how a gradient of organic matter (OM) additions (0, 1, 2.5, 5, 10, and 20%) affects SOC dynamics, nutrient availability, and soil organic matter composition in clay-dominated, semiarid soils. Surface and subsurface samples (0–30, 30–60, and 60–90 cm) were analysed for SOC, nutrients, and mid-infrared Fourier transform infrared (FTIR) spectra, which were then integrated with Partial Least Squares (PLS) regression and RothC simulations. Moderate OM inputs (5

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Convolutional Multi-Spike Neural Network as Intelligent System Prediction for Control Systems
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The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

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Publication Date
Mon Jul 01 2024
Journal Name
Imam Ja'afar Al-sadiq University Journal Of Legal Studies
Criminal responsibilities arising from artificial intelligence crimes المسؤولية الجزائية عن جرائم الذكاء الاصطناعي
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لقد كان للثورة الرقمية التي ظهرت في القرن العشرين أثر في إحداث تأثيرات جذرية تضمنت نواحي الحياة المختلفة، خصوصًا في المجال الإقتصادي، والتي تمثلت بثلاث صور ( الذكاء الإصطناعيArtificial Intelligence( AI) وإنترنت الأشياء Internet of Things والبيانات الضخمة Big Data ، وفيما يتعلق بالذكاء الإصطناعي، فقد تم إكتشافهُ في منتصف خمسينات القرن الماضي الذي تعد الولادة الحقيقية لهُ في المؤتمر الذي نُظم في الولايات المتحدة الأمريكية على يد

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Publication Date
Wed Jun 16 2021
Journal Name
Biochemical And Cellular Archives
Synthesis, characterization and pharmaceutical studies of schiff base from 2-pyrrolidinone derivative and imidazole-2-carboxaldehyde and corresponding complexes with Metal (||)
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Synthesis, characterization and pharmaceutical studies of schiff base from 2-pyrrolidinone derivative and imidazole-2-carboxaldehyde and corresponding complexes with Metal (||)