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Fatigue Characterization for Composite Materials used in Artificial Socket Prostheses with the Adding of Nanoparticles
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Abstract<p>The prostheses sockets use normally composite materials which means that their applications may be related with the human body. Therefore, it was very necessary to improve the mechanical properties of these materials. The prosthetic sockets are subjected to varying stresses in gait cycle scenario which may cause a fatigue damage. Therefore, it is necessary or this work to modify the fatigue behavior of the materials used for manufacturing the prostheses sockets. In this work, different Nano particle materials are used to modify the mechanical properties of the composite materials, and increase the fatigue strength. By using an experimental technique, the effect of using different volume fractions for various types for Nano particle materials on the fatigue behavior for composite materials, and preparing the fatigue samples and tested using the fatigue apparatus. The Nano particles used were (Nano SiO<sub>2</sub> and Nano Al<sub>2</sub>O<sub>3</sub>) materials with volume fraction as (0% to 2%), for each type of Nano material used. The artificial neural network technique was adopted to have a verification for the experimental results and calculating the fatigue life and strength for composite materials, with the addition of nanoparticles and then, a comparison of the results was achieved. The comparison of the results indicate a maximum error between results calculated by two technique did not exceeded about (1%). Then, the results calculated showed that the mechanical properties and fatigue life and strength increase with reinforcement with Nano particle. Also, the results showed that the modified for fatigue limits with materials by (Nano SiO<sub>2</sub>) Nano particle was more than the modified for fatigue limits for materials reinforcement with other materials. Finally, it can be concluded that the modified for fatigue strength, by reinforcement with (Nano SiO<sub>2</sub>), leads to 60% more than fatigue limit without Nano additive.</p>
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Publication Date
Mon Jan 17 2011
Journal Name
مجلة كلية التربية
Synthesis and Characterization of Complexes of [(N,N- -Bis(2- Hydroxy Ethyl) Glycine] with Some Metal Salts
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Some transition metal ions (Cr +3, Co+2 , Ni+2,Cu+2, Zn+2,Ag + ,Cd+2 ) complexes of [(N, N- - Bis(2- hydroxy ethyl) Glycine] (Bicine) have been synthesized and characterized by FTIR ,UV-Visble spectroscopy, atomic absorption, magnetic susceptibility, conductivity measurements and study of the nature of the complexes formed in ethanolic solution following the moleratio method. From the results obtained the following general formola have been given for the prepared complexes [M m+ (Bicine)n]. XH2O

Publication Date
Thu Apr 29 2010
Journal Name
Journal Of The First Specialized National Conference In Chemistry 29-30 April 2010 University Of Thi-qar College Of Science
Preparation and Characterization of Mixed ligand complexes of Lanthanum (III) with 8- hydroxyqinoline and some amino acids
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Publication Date
Thu Jan 22 2015
Journal Name
مجلة التربية الاساسية
Synthesis and Characterization of Some New Heterocyclic Compounds Via Unsaturated Ketone with Evaluating of Their biological Activity
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Publication Date
Tue Feb 01 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

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Publication Date
Wed Mar 23 2022
Journal Name
Modern Sport
Using Artificial intelligence to evaluate skill performance of some karate skills
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Human beings are starting to benefit from the technology revolution that witness in our time. Where most researchers are trying to apply modern sciences in different areas of life to catch up on the benefits of these technologies. The field of artificial intelligence is one of the sciences that simulate the human mind, and its applications have invaded human life. The sports field is one of the areas that artificial intelligence has been introduced. In this paper, artificial intelligence technology Fast-DTW (Fast-Dynamic Time Warping) algorithm was used to assess the skill performance of some karate skills. The results were shown that the percentage of improvement in the skill performance of Mai Geri is 100%.

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Publication Date
Sat Jan 01 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

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Publication Date
Tue Sep 06 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

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Publication Date
Mon Dec 02 2024
Journal Name
Engineering, Technology &amp; Applied Science Research
An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

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Publication Date
Sun Aug 01 2021
Journal Name
Nano Biomedicine And Engineering
In-vivo and In-vitro Anti-Acinetobacter Baumannii Activity of Citrate-Capped Silver Nanoparticles
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Silver nanoparticles (AgNPs) are of potential interest because of their effective antibacterial and antiviral activities. Capping agents are used for exhibiting a better antibacterial activity than uncapped Ag NPs. There are very few reports that have shown the usage of AgNPs for in-vivo antibacterial therapy. Citrate-capped silver nanoparticles were synthesized chemically by citrate reduction method; the size of Cit-AgNPs was determined by an atomic force microscope (AFM) and was between 15-90 nm. Acinetobacter baumannii (A. baumannii) isolates were the only sensitive species to Cit-AgNPs. MICs and MBC of Cit-AgNPs were determined by using A. baumannii. The results showed an additive effect of Cit-AgNPs. Four mice groups were infected with

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Publication Date
Tue Dec 31 2024
Journal Name
Iraqi Geological Journal
Petrophysical Characterization and Lithology of the Mishrif Formation in Ratawi Oil Field, Southern Iraq
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The Ratawi Oil Field (ROF) is one of Iraq's most important oil fields because of its significant economic oil reserves. The major oil reserves of ROF are in the Mishrif Formation. The main objective of this paper is to assess the petrophysical properties, lithology identification, and hydrocarbon potential of the Mishrif Formation using interpreting data from five open-hole logs of wells RT-2, RT-4, RT-5, RT-6, and RT-42. Understanding reservoir properties allows for a more accurate assessment of recoverable oil reserves. The rock type (limestone) and permeability variations help tailor oil extraction methods, extraction methods and improving recovery techniques. The petrophysical properties were calculated using Interactive Petroph

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