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bsj-6046
Synthesis and Characterization of New nano catalyst Mo-Ni /TiO2- γAl2O3 for Hydrodesulphurization of Iraqi Gas Oil
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   A new nano-sized NiMo/TiO2-γ-Al2O3 was prepared as a Hydrodesulphurization catalyst for Iraqi gas oil with sulfur content of 8980 ppm, supplied from Al-Dura Refinery. Sol-gel method was used to prepare TiO2- γ-Al2O3 nano catalyst support with 64% TiO2, 32% Al2O3, Ni-Mo/TiO-γ-Al2O3 catalyst was prepared under vacuum impregnation conditions to loading metals with percentage 3.8 wt.% and 14 wt.% for nickel and molybdenum respectively while the percentage for alumina, and titanium became 21.7, and 58.61 respectively. The synthesized TiO2- γ-Al2O3 nanocomposites and Ni-Mo /TiO2- γ-Al2O3 Nano catalyst were then characterized by XRD, AFM, and BET surface area, SEM, XRF, and FTIR. The performance of the synthesized catalyst for removing sulfur compounds was conducted through the pilot HDS laboratory unit, various temperatures range 275oC to 375°C, LHSV 1 h-1 were studied; moreover, the effect of LHSV 1 to 4 h-1 on the percentage of sulfur removal was also studied at the temperature of the best removal with constant pressure 35 bar and H2/HC ratio 200cm3/200cm3. The sulfur content results generally revealed that there was a substantial decrease at all operating conditions used, while the maximum sulfur removal was 87.75% in gas oil on Ni-Mo/TiO2-γ-Al2O3 catalyst at temperature 375˚C and LHSV 1h-1.

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Publication Date
Wed Mar 10 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A hybrid Grey Wolf optimizer with multi-population differential evolution for global optimization problems
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Publication Date
Wed Jan 01 2014
Journal Name
International Journal Of Computer Applications
Enhancing the Delta Training Rule for a Single Layer Feedforward Heteroassociative Memory Neural Network
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In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Radon concentrations assessment in tap water for different areas in Baghdad city using Rad7
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Publication Date
Thu Sep 26 2024
Journal Name
Journal Of Optics
Cysteine-cupped CdSe/CdS quantum dots as an opticalbiosensor for early skin cancer detection
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This study represents an optical biosensor for early skin cancer detection using cysteine-cupped CdSe/CdS Quantum Dots (QDs). The study optimizes QD synthesis, surface, optical functionalization, and bioconjugation to enhance specificity and sensitivity for early skin cancer cell detection. The research provides insights into QD interactions with skin cancer biomarkers, demonstrating high-contrast, precise cellular imaging. Cysteine-capped CdSe/CdS absorption spectra reveal characteristic peaks for undamaged DNA, while spectral shifts indicate structural changes in skin-cancer-damaged DNA. Additionally, fluorescence spectra show sharp peaks for undamaged DNA and notable shifts and intensity variations when interacting with skin cancer. This

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Publication Date
Sun Dec 30 2012
Journal Name
Journal Of Kufa For Mathematics And Computer
On Jeffery Prior Distribution in Modified Double Stage Shrinkage-Bayesian Estimator for Exponential Mean
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Publication Date
Mon Oct 04 2021
Journal Name
Journal Of Petroleum Exploration And Production Technology
Perforation location optimization through 1-D mechanical earth model for high-pressure deep formations
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Optimum perforation location selection is an important study to improve well production and hence in the reservoir development process, especially for unconventional high-pressure formations such as the formations under study. Reservoir geomechanics is one of the key factors to find optimal perforation location. This study aims to detect optimum perforation location by investigating the changes in geomechanical properties and wellbore stress for high-pressure formations and studying the difference in different stress type behaviors between normal and abnormal formations. The calculations are achieved by building one-dimensional mechanical earth model using the data of four deep abnormal wells located in Southern Iraqi oil fields. The magni

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
An Approximate solution for two points oundary value problem corresponding to some optimal control
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this paper presents a novel method for solving nonlinear optimal conrol problems of regular type via its equivalent two points boundary value problems using the non-classical

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
Generalized tupled common fixed point theorems for weakly compatible mappings in fuzzy metric space
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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Physics: Conference Series
Gamma Irradiation Effects on Energy Transfer Parameters for Acrvlaven – Rhodamine19 Binary Laser Dye Mixtures
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Publication Date
Fri Sep 01 2023
Journal Name
Al-khwarizmi Engineering Journal
High Transaction Rates Performance Evaluation for Secure E-government Based on Private Blockchain Scheme
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The implementation of technology in the provision of public services and communication to citizens, which is commonly referred to as e-government, has brought multitude of benefits, including enhanced efficiency, accessibility, and transparency. Nevertheless, this approach also presents particular security concerns, such as cyber threats, data breaches, and access control. One technology that can aid in mitigating the effects of security vulnerabilities within e-government is permissioned blockchain. This work examines the performance of the hyperledger fabric private blockchain under high transaction loads by analyzing two scenarios that involve six organizations as case studies. Several parameters, such as transaction send ra

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