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Deep Oxidative Desulfurization of Model fuels by Prepared Nano TiO2 with Phosphotungstic acid
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In this study, nano TiO2 was prepared with titanium isopropoxide (TTIP) as a resource to titanium oxide. The catalyst was synthesized using phosphotungstic acid (PTA) and, stearyl trimethyl ammonium bromide (STAB) was used as the structure-directing material. Characterization of the product was done by the X-ray diffraction (XRD), X-ray fluorescent spectroscopy (XRF), nitrogen adsorption/desorption measurements, Atomic Force Microscope (AFM) and Fourier transform infrared (FTIR) spectra, were used to characterize the calcined TiO2 nanoparticles by STAB and PWA. The TiO2 nanomaterials were prepared in three crystalline forms (amorphous, anatase, anatase-rutile). The results showed that the nanoparticles of anatase TiO2 have good catalytic oxidative activity. This is because of the conversions of 100% within 90 sec from 300 ppm of dibenzothiophene. This is compared to conversion rates for anatase–rutile nanoparticles and amorphous nanoparticles which reached 52% and 31 %, respectively. The influence of the temperature of reaction, catalyst amount, H2O2 concentration, and initial DBT concentration on the oxidation of DBT was investigated.

 

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
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    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

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Publication Date
Tue Apr 30 2024
Journal Name
International Journal On Technical And Physical Problems Of Engineering
Deep Learning Techniques For Skull Stripping of Brain MR Images
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Deep Learning Techniques For Skull Stripping of Brain MR Images

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Publication Date
Mon Nov 03 2025
Journal Name
Frontiers In Dental Medicine
Effects of cavity depth (moderate vs. deep with pulp exposure) on the release of prostaglandin E2 and nitric oxide in rat mandibular incisors
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Background/objectives: Inflammatory mediators such as prostaglandin E2 (PGE2) and nitric oxide (NO) are key indicators of pulp response to mechanical trauma. However, the influence of cavity depth on their release dynamics remains unclear. This study aimed to evaluate the effects of different cavity depths—moderate (without pulp exposure) and deep (with pulp exposure)—on the release of PGE2 and NO in the pulp tissue of rat mandibular incisors at two time intervals (3 and 9 h).Methods: In total, 40 male Wistar rats were divided into two main groups (n = 20) based on cavity depth. A split-mouth design was used, with cavities of different depths prepared on the left mandibular incisors, leaving the right incisors without cavities as

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Publication Date
Sat Mar 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Study on Kinetic and Optimization of Continuous Advanced Oxidative Decolorization of Brilliant Reactive Red Dye
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The azo dye brilliant reactive red K-2BP (λmax = 534 nm) is widely used for coloring textiles because of its low-cost and tolerance fastness properties. Wastewaters treatment that contains the dye by conventional ways is usually inadequate due to its resistance to biological and chemical degradation. During this study, the continuous reactor of an advanced oxidation method supported the use of H2O2/sunlight, H2O2/UV, H2O2/TiO2/sunlight, and H2O2/TiO2/UV for decolorization of brilliant reactive red dye from the effluent. The existence of an optimum pH, H2O2 concentration, TiO2 concentration, and d

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Publication Date
Sat Oct 14 2017
Journal Name
European Chemical Bulletin
SYNTHESIS, SPECTROSCOPIC AND ANTIBACTERIAL STUDY OF ZINC, COPPER AND NICKEL COMPLEXES WITH NEW DERIVATIVE OF L-ASCORBIC ACID
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Publication Date
Mon Jul 29 2013
Journal Name
Al- Mustansiriyah J. Sci.
Synthesis and Characterization of Some Mixed Ligand Complexes of Quinaldic Acid and α-Picoline with Some Metal Salts
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Some metal ions (Mn+2, Co+2, Ni+2, Cu+2, Zn+2, Cd+2 and Hg+2) complexes of quinaldic acid (QuinH) and α-picoline (α-Pic) have been synthesized and characterized on the basis of their , FTIR, (U.V-Vis) spectroscopy, conductivity measurements, magnetic susceptibility and atomic absorption. From the results obtained the following general formula has suggested for the prepared complexes [M(Quin)2( α-Pic)2].XH2O where M+2 = (Mn, Co, Ni, Cu, Zn, Cd and Hg), X = 2, X = zero for (Co+2 and Hg+2) complexes, (Quin-) = quinaldate ion, (α-Pic) = α-picoline. The results showed that the deprotonated ligand (QuinH) by using (KOH) coordinated to metal ions as bidentate ligand through the oxygen atom of the carboxylate group (-COO-) and the nitrogen ato

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Publication Date
Wed Jun 26 2019
Journal Name
Research Journal Of Pharmaceutical, Biological And Chemical Sciences
Synthesis, Characterization Antimicrobial Activities Studies Of Mixed-Ligand Complexes Of Curcumin And Anthranilic Acid With Bivalent Metals Chlorides
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Publication Date
Tue Jan 01 2013
Journal Name
Al- Mustansiriyah J. Sci.
Synthesis and Characterization of Some Mixed Ligand Complexes of Quinaldic Acid and α-Picoline with Some Metal Salts
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Some metal ions (Mn+2, Co+2, Ni+2, Cu+2, Zn+2, Cd+2 and Hg+2) complexes of quinaldic acid (QuinH) and α-picoline (α-Pic) have been synthesized and characterized on the basis of their , FTIR, (U.V-Vis) spectroscopy, conductivity measurements, magnetic susceptibility and atomic absorption. From the results obtained the following general formula has suggested for the prepared complexes [M(Quin)2( α-Pic)2].XH2O where M+2 = (Mn, Co, Ni, Cu, Zn, Cd and Hg), X = 2, X = zero for (Co+2 and Hg+2) complexes, (Quin-) = quinaldate ion, (α-Pic) = α-picoline. The results showed that the deprotonated ligand (QuinH) by using (KOH) coordinated to metal ions as bidentate ligand through the oxygen atom of the carboxylate group (-COO-) and the nitrogen ato

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Publication Date
Sun Sep 01 2013
Journal Name
Baghdad Science Journal
Synthesis and characterization of novel metal complexes of (pentulose-?-lactone-2,3-enedibenzoate barbituric acid) with some metal ions
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New (pentulose-?-lactone-2,3-enedibenzoate barbituric acid) (L) have been synthesized by reaction of (5-C-dimethyl malonyl-pentulose-?-lactone-2,3-enedibenzoate) with urea in alkaline media (sodium methoxide). (Ca+2, Co+2, Ni+2, Cu+2, Zn+2, Cd+2 and Hg+2) complexes of (pentulose-?-lactone-2,3-enedibenzoate barbituric acid) (L) have been prepared and characterized by (1H and 13CNMR), FTIR, (U.V-Vis) spectroscopy, Atomic absorption spectrophotometer (A.A.S), Molar conductivity measurements and Magnetic moment measurements, and the following general formula has been given for the prepared complexes [MLCl2(H2O)].XH2O, where M = (Ca+2, Co+2, Ni+2, Cu+2, Zn+2, Cd+2, Hg+2), X = five molecules with (Cd+2) complex, L = (pentulose-?-lactone-2,3

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