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Study of Catalysts Deactivation in Isomerization Process to Produce High Octane Gasoline
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In this study  the isomerization of desulfuerized light Iraqi petroleum naphtha (Al-Dura Refinery) with boiling point range of 37 to 124 °C , 80.5 API specific gravity and 68.2 octane number has been investigated. Two types of catalysts were prepared (Pt/HX and Pt/SrX) by impregnation of 0.8 wt% Pt on l 3X-zeolite. The catalyst activity and selectivity toward isomerization, and catalyst deactivation were investigated.

The isomerization unit consisted of a vertical tubular stainless steel reactor of 2 cm internal diameter, 3 cm external diameter and 68 cm height. The operating pressure was atmospheric for all experimental runs.  The liquid flow of light­naphtha was 0.4 Uh, and the catalyst weight was 50 gm, H/ H.C ratio used was 4 for all experimental runs. The isomerization process was studied at different temperatures of 250, 270, 275, 300, 325, and 350 °C . It was found that, the optimum isomerization temperature is 270 °C.

The isomerization activities and selectivities as a function of time showed high activity at the beginning of the reaction and were deactivated rapidly. This indicates that the deactivation of Pt/HX and Pt/SrX results from the blocking of pore mouth by the deposited carbon. The following deactivation decreasing order, Pt/HX > Pt/SrX was found. On the other hand, Pt/HX catalyst shows higher activity and selectivity than that of Pt/SrX

It was concluded that, only an average o/ 90 wt% of the carbon atoms feed  into the reactor (light naphtha) is detected " the product stream due to formation of coke deposits which leads to catalyst deactivation. The results clearly showed 1at hydrogen is necessary for the hydrogenation of olefins in order to prevent oligomerization reaction that leads to coke formation and catalyst deactivation.

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Publication Date
Sun Nov 01 2020
Journal Name
Iscience
Identification and Characterization of Highly Fluorescent Pigment Cells in Embryos of the Arabian Killifish (Aphanius Dispar)
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Publication Date
Sat Dec 02 2023
Journal Name
Journal Of Engineering
Numerical Simulation of Pile Group Response in Slope Layered Soil under the Effect of Seismic Loading
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This work investigates the effect of earthquakes on the stability of a collective pile subjected to seismic loads in the soil layer. Plaxis 3D 2020 finite element software modeled pile behavior in dry soils with sloping layers. The results showed a remarkable fluctuation between the earthquakes, where the three earthquakes (Halabja, El Centro, and Kobe) and the acceleration peak in the Kobe earthquake had a time of about 11 seconds. Different settlement results were shown, as different values were recorded for the three types of earthquakes. Settlement ratios were increased by increasing the seismic intensity; hence the maximum settlement was observed with the model under the effect of the Kobe earthquake (0.58 g), where

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Engineering
Assessment of the Cost and Time Impact of Variation Orders on Construction Projects in Sulaimani Governorate
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Variation orders are an on-going phenomenon in construction and industry projects worldwide, particularly in the province of Sulaimani, where the project's damage from cost and schedule overrun because of variation orders. However, the effect on project costs and time overrun of variation order has yet to be identified. This study evaluates the impact of variation orders on the cost and time off in the Sulaimani governorate. Two hundred twenty-eight projects from various construction sectors built between 2007-2012 were adopted to calculate the contract cost and schedule overruns due to variation orders. Data analysis was applied in the study were descriptive statistics. One-way ANOVA was also applied to determine w

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Publication Date
Sun Feb 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
The role of the integration of the knowledge economy and international accounting in achieving sustainable development
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     The current environment is witnessing several developments as a result of the changes  taking place in all areas of economic, social , political and legal that led to the transformation of the industrial economy , which depends based on quantitative production to a knowledge economy which relies based on information and knowledge , as the central pillar of this economy during the trading  of  these information and knowledge between all individuals in general and decision makers , in particular, through information and communication technology of computers and the Internet to achieve sustainable human development in the social dimension.         &

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Publication Date
Mon Dec 23 2019
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Inhibition of NF-kB Pathway by Gggulsterone in the Protective Effects of Cyclophosphamide-Induced Renal Toxicity
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Cyclophosphamide which acts as cytotoxic alkylating agent can induce a renal damage through the toxic metabolites which result from metabolic activation of Cyclophosphamide by cytochrome P-450 inside hepatocyte and develop renal toxicity by direct binding with cellular organelles in the urinary tract cells. Guggulsterone is a sterol derived from plant has ability to bind to farsenoid X receptor, mineral corticosteroid receptor, androgen receptor, glucocorticoid receptor and estrogen receptor.

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Publication Date
Fri Jul 19 2024
Journal Name
Baghdad Science Journal
An Analytical Comparison of the Behavior of Machine Learning and Deep Learning in Stock Market Prediction
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Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec

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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
The Effect of Spatial Organization on the Sustainability of the Neighborhood Unit in the Residential Environment
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Contemporary residential neighborhoods suffer from weak sustainability of urban residential environments as a result of the adoption of inefficient spatial organization at the neighborhood unit level. This resulted negative characteristics which affected the achievement of sustainable development plans for the residential environment that constitute the majority of the urban fabric of cities.

The physical affordances ,within the vocabulary of recent times,overcame the spiritual ones and affected the residential environment. Accordingly,the concept of space changed in contemporary residential areas through the dominance of the physical aspect (mass) on the symbolic aspect (space).The modern technology occupied an important level b

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Publication Date
Wed Feb 20 2019
Journal Name
Political Sciences Journal
A political perusal of Initiations in Declaring Middle East a District vacant of mass Destruction weapons
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A political perusal of Initiations in Declaring Middle East a District vacant of mass Destruction weapons

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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of Artificial Intelligence Models for Estimating Rate of Penetration in East Baghdad Field, Middle Iraq
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It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i

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Publication Date
Mon Jan 01 2024
Journal Name
Rsc Advances
Rapid colorimetric sensing of chlorpromazine HCl antipsychotic through <i>in situ</i> growth of gold nanoparticles
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This assay rapidly detects chlorpromazine hydrochloride using its ability to reduce gold ions to form nanoparticles. Its low cost, resilience to interferences and short analysis time could facilitate environmental monitoring and biomedical analysis.

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