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Effect of reduced graphene oxide hybridization on ZnO nanoparticles sensitivity to NO2 gas: A DFT study
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In the present work, a density functional theory (DFT) calculation to simulate reduced graphene oxide (rGO) hybrid with zinc oxide (ZnO) nanoparticle's sensitivity to NO2 gas is performed. In comparison with the experiment, DFT calculations give acceptable results to available bond lengths, lattice parameters, X-ray photoelectron spectroscopy (XPS), energy gaps, Gibbs free energy, enthalpy, entropy, etc. to ZnO, rGO, and ZnO/rGO hybrid. ZnO and rGO show n-type and p-type semiconductor behavior, respectively. The formed p-n heterojunction between rGO and ZnO is of the staggering gap type. Results show that rGO increases the sensitivity of ZnO to NO2 gas as they form a hybrid. ZnO/rGO hybrid has a higher number of vacancies that can be used to attract oxygen atoms from NO2 and change the resistivity of the hybrid. The combined reduction of oxygen from NO2 and NO can give a very high value of the Gibbs free energy of reaction that explains the ppb level sensitivity of the ZnO/rGO hybrid. The dissociation of NO2 in the air reduces the sensitivity of the ZnO/rGO hybrid at temperatures higher than 300 ̊C.

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Publication Date
Wed Mar 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
The use of ARIMA, ANN and SVR models in time series hybridization with practical application
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Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
The use of ARIMA, LSTM and GRU models in time series hybridization with practical application
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The importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h

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Publication Date
Thu Oct 20 2022
Journal Name
Nano Biomedicine And Engineering
DFT-Quantum Chemical and Experimental Studies of a New 2-(Substituted Thio) Furan as a Corrosion Inhibitor in Acidic Media
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The corrosion inhibiting properties of the new furan derivative 5-(furan-2-ylmethylsulfonyl-4-phenyl-2,4- dihydro [1,2,4] triazole-3-thione in acidic solution (1.0 M HCl) were explored utilizing electrochemical, surface morphology (AFM), and quantum chemical calculations approaches. The novel furan derivative 5-(furan-2-ylmethylsulfonyl-4-phenyl-2,4- dihydro [1,2,4] triazole-3-thione shows with an inhibitory efficiency value of 99.4 percent at 150 ppm, carbon steel corrosion in acidic medium is effectively inhibited, according to the results. The influence of temperature on corrosion prevention was studied using adsorption parameters and activation thermodynamics. The novel furan derivative creates a protective layer over the metallic surfa

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Publication Date
Fri Oct 02 2026
Journal Name
Advances In Environmental Biology
A study effect of thyme on biochemical and histological changes in liver of male rats
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Publication Date
Sat Apr 01 2023
Journal Name
Egyptian Journal Of Veterinary Sciences
Effect of Crocin on the Spermatogenesis Indices of Mice Testis: A Histopathological and Histomorphological Study
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Publication Date
Mon Mar 13 2023
Journal Name
Diagnostics
The Effect of a Bioactive Oral System and CO2 Laser on Enamel Susceptibility to Acid Challenge
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This study evaluated the structural changes of enamel treated by the Regenerate system and carbon dioxide (CO2) laser against acid challenge. Thirty human enamel slabs were prepared and assigned into three groups: Group I: untreated (control); Group II: treated with the Regenerate system; and Group III exposed to CO2 laser. All specimens were subjected to an acid challenge (pH 4.5–7.0) for 14 days. Specimens were evaluated and compared at 120 points using five Raman microspectroscopic peaks; the phosphate vibrations ν1, ν2, ν3, and ν4 at 960, 433, 1029, and 579 cm−1, respectively, and the carbonate at 1070 cm−1, followed by Vickers microhardness test. The ratio of carbonate to phosphate was correlated to the equivalent mic

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Publication Date
Sun Mar 04 2018
Journal Name
Baghdad Science Journal
Using Texture Analysis Image Processing Technique to Study the Effect of Microwave Plasma on the Living Tissue
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The present study is a hybrid method of studying the effect of plasma on the living tissue by using the image processing technique. This research explains the effect of microwave plasma on the DNA cell using the comet score application, texture analysis image processing and the effect of microwave plasma on the liver using texture analysis image processing. The study was applied on the mice cells. The exposure to the plasma is done by dividing the mice for four groups, each group includes four mice (control group, 20, 50, 90 second exposure to microwave plasma). The exposure to microwave plasma was done with voltage 175v and gas flow on 2 with room temperature; the statistical features are obtained from the comet score images and the textur

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Publication Date
Thu Dec 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
FLUID CATALYTIC CRACKING OF PETROLEUM FRACTION (VACUUM GAS OIL) TO PRODUCE GASOLINE
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In this work, fluid catalytic cracking of vacuum gas oil to produce gasoline over prepared faujasite type Y zeolite was investigated using experimental laboratory plant scale of fluidized bed reactor.
The catalytic activity of prepared faujasite type NaY, NaNH4Y and NaHY zeolites was investigated. The cracking process was carried out in the temperature range 440 to 500 oC, weight hourly space velocity (WHSV) range 10 to 25 h-1 ,and atmospheric pressure . The catalytic activities of the prepared faujasite type NaY , NaNH4Y and NaHY zeolites were determined in terms of vacuum gas oil (VGO) conversion, and gasoline yield . The conversion at 500oC and WHSV10 hr-1 by using faujasite type NaY, NaNH4Y and NaHY zeolite were 50.2%, 64.1% and 6

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Engineering
Microbicidal Effect of Fe2O3 Nanoparticles in Antimicrobial Agent System
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Microbial antibiotics resistance is considered a serious health issue in the Middle East and developing countries. In this study, the Fe2O3 nanoparticles was prepared chemically, and the particles size and shape were analyzed by using Scan electron microscope (SEM) and X-Ray diffraction (XRD). Different concentration of Fe2O3 nanoparticles were used and examined on E.coli and S. aureus. Using liquid dilution and in vitro cytotoxicity assay by microplate toxicity test (MTT). The microbial cell metabolic activity was measured on gram-negative, gram-positive bacteria and fungi after treating with different concentrations of Fe2O3 nanoparticl

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Publication Date
Wed May 22 2024
Journal Name
Scientific Reports
The use of image analysis to study the effect of moisture content on the physical properties of grains
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Abstract<p>Designing machines and equipment for post-harvest operations of agricultural products requires information about their physical properties. The aim of the work was to evaluate the possibility of introducing a new approach to predict the moisture content in bean and corn seeds based on measuring their dimensions using image analysis using artificial neural networks (ANN). Experimental tests were carried out at three levels of wet basis moisture content of seeds: 9, 13 and 17%. The analysis of the results showed a direct relationship between the wet basis moisture content and the main dimensions of the seeds. Based on the statistical analysis of the seed material, it was shown that the characteristics </p> ... Show More
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