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Coupled Eulerian–Lagrangian prediction of thermal and residual stress environments in dissimilar friction stir welding of aluminum alloys
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The evaluation of residual stresses (RS) induced by the friction stir welding (FSW) process is crucial in anticipating the performance of the welded structure. The existence of such residual stresses within a friction stir welded structure may lead to excessive distortion and weakness to afford the applied external loads. To assess quantitatively the effect of these residual stresses generated by FSW process, the current paper implements a Coupled Eulerian–Lagrangian (CEL) finite element simulation to analyze both thermal and subsequent resulted remaining stress environments in dissimilar friction stir welding of AA6061-T6 and AA2024-T3 alloys. The thermal analysis step was conducted first and followed by a mechanical analysis step in which the residual stresses distribution throughout the whole dissimilar FSWed alloys were captured. To validate the simulation results, K-type thermocouples, in addition to A-type rosette strain gauges, were planted to measure both temperature history and residual stress field generated as a consequence of the thermal environment. The effect of changing FSW working variables like rotation and traverse speeds on both the thermal and residual stress environments was investigated. The obtained results demonstrated that the temperature, as well as the residual stress, was higher in the sample retreating side rather than the proposed advancing side, and a fair correlation between the experimental and simulation results was attained. Quantitatively, the longitudinal residual stress was higher in contrast to the transverse value, and it varied from being tensile in the zone beneath the tool shoulder to compressive away from the welding tool. Furthermore, the plastic strain produced owing to the surface contact between the welding tool and the dissimilar aluminum sample was higher on the retreating side.

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Synthesis of Coumarin Derivatives Coupled to Amino Acid Esters and Studying their Biological Activity as Antimicrobial Agents
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A series of coumarin derivatives linked to amino acid ester side chains were synthesized and evaluated of their antibacterial and antifungal activity. The coumarin derivatives was alkylated by the ethyl bromoacetate and then using potassium carbonate to get alkylated hymecromone. Conventional solution method for amide bond formation was used as a coupling method between the carboxy-protected amino acids with acetic acid side chain of coumarin derivatives. The DCC/ HOBt coupling reagents were used for peptide bond formation. The proposed analogues were successfully synthesized and their structural formulas were consistent with the proposed struct

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Publication Date
Tue Nov 11 2014
Journal Name
Pakistan Journal Of Biological Sciences
Effects of Local Curcumin on Oxidative Stress and Total Antioxidant Capacity in vivo Study
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Publication Date
Thu Jan 01 2015
Journal Name
Iosr Journal Of Applied Chemistry
Purification of G-Protein Coupled Receptor from Membrane Cell of Local Strain of Saccharomyces cerevisiae
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Publication Date
Sun Nov 01 2015
Journal Name
Journal Of Natural Science Research
Purification of G-Protein Coupled Receptor from Whole Cell of Local Strain of Saccharomyces cerevisiae
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The aim of study To purify GPCR from a local strain of S. cerevisiae using Ion exchange and gel filtration chromatography techniques , by packing materials for columns which will be chosen of low cost comparing to the already used in published researches, which depend on the costly affinity chromatography and other expensive methods of purification. Local strain of S. cerevisiae chosen for extraction and purification of G-protein coupled receptor (GPCR) .The strains were obtained from biology department in Al- Mosul University, Iraq. The isolated colony was activated on Yeast Extract Pepton Dextrose Broth (YEPDB) and incubated at 30 C˚ for 24 h .Loop fully of the yeast culture was transferred to (10ml) of yeast extract peptone glucose

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Publication Date
Sat Mar 19 2022
Journal Name
Al-khwarizmi Engineering Journal
Effect of MIG Welding Parameters on the Mechanical Properties of AISI 304 Austenitic Stainless Steels
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The present research  investigates joints welding of 304L austenitic stainless steel using metal inert gas (MIG) welding method. The research explores the effect of process parameters (arc voltage, wire feed rate, and electrode wire diameter) on the mechanical properties of stainless steel.  The above variables are varied  respectively with 18.5, 19, 19.5 V, 116, 127, 137 mm/s, and 0.8, 1, 1.2 mm, with E308L as a filler electrode. The design matrix of the experiments was determined using the design of experiment (DOE) program Minitab 17 based on the levels of input elements used. The Taguchi orthogonal matrix methodology (Taguchi) technique was used to develop some empirical analysis for the maximum tensile strength and proper surface

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Publication Date
Tue Sep 28 2021
Journal Name
Journal Of The College Of Education For Women
Social Safety Nets and Sustainable Development in Fragile Environments: A Field Social Study of Slums in the City of Baghdad/Al-Karkh: هبة صالح مهدي, عدنان ياسين مصطفى
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Almost human societies are not void of poverty, as the latter accompanied the emergence of humanity, and it, thus, represents an eternal problem. To advance an individual's reality and raise the level of the poor social classes, social security networks have been established. Such networks operate in society following social systems and laws to provide food, and material support. Besides, such networks help to rehabilitate the individual academically and vocationally. They empower vulnerable groups through the establishment of courses and workshop, provide (conditional) subsidies related to the health and educational aspects in order to achieve the sustainable development goals of (2030), and apply developmental roles of social safety ne

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Effect of Al2O3 Particles and Precipitation Hardening on the Properties of Cast 332 Aluminum Alloy
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In this work, 332 Al alloy was prepared and reinforced with (0.5% and 1%) nano-Al2O3 particles. The prepared unreinforced and reinforced 332 Al alloy with nano-Al2O3 were solution heat treated (T6) at 510 ̊C and aged at 225 ̊C with different times (1, 3, and 5 h). Hardness test was performed on all the prepared alloys. All prepared alloys were dry slided under different applied loads (5, 10, 15, and 20 N) against steel counterface surface using pin on disk apparatus. The results showed that refinement effect was observed after addition of nano-Al2O3 particles and a change in silicon morphology after performing the solution heat treatment. The results also showed that har

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Enhance the Properties of Lignosulfonate Mud by Adding Nanoparticles of Aluminum Oxide and Iron Oxide
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Oil well drilling fluid rheology, lubricity, swelling, and fluid loss control are all critical factors to take into account before beginning the hole's construction. Drilling fluids can be made smoother, more cost-effective, and more efficient by investigating and evaluating the effects of various nanoparticles including aluminum oxide (Al2O3) and iron oxide (Fe2O3) on their performance. A drilling fluid's performance can be assessed by comparing its baseline characteristics to those of nanoparticle (NPs) enhanced fluids. It was found that the drilling mud contained NPs in concentrations of 0,0.25, 0. 5, 0.75 and 1 g. According to the results, when drilling fluid was used without NPs, the coeff

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Publication Date
Sun Jun 08 2025
Journal Name
J Nat Sc Biol Med
The Value of White Blood Cells and Platelets Indices in Prediction of Tubal Ectopic Pregnancy Rupture
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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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