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 SiO2 and Nano Al2O3) 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 SiO2) 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 SiO2), leads to 60% more than fatigue limit without Nano additive.
Construction of artificial higher order protein complexes allows sampling of structural architectures and functional features not accessible by classical monomeric proteins. Here, we combine in silico modelling with expanded genetic code facilitated strain promoted azide-alkyne cycloaddition to construct artificial complexes that are structurally integrated protein dimers and demonstrate functional synergy. Using fluorescent proteins sfGFP and Venus as models, homodimers and heterodimers are constructed that switched ON once assembled and display enhanced spectral properties. Symmetrical crosslinks are found to be important for functional enhancement. The determined molecular structure of one artific
ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel
... Show MorePatch in transdermal drug delivery(TDDS) used to overcome the hypodermic drawback, but these patch also have absorption limitation for hydrophilic and macromolecule like peptide and DNA. So that micronized projection have the ability for skin penetration developed named as microneedle. Microneedle drug delivery system is a novel drug delivery to overcome the limitation of TDDS like skin barrier restriction for large molecule. Microneedle patch can penetrate through skin subcutaneous into epidermis, avoiding nerve fiber and blood vessel contact. There are many type of microneedle patch like solid, polymer, hallow, hydrogel forming microneedle and dissolving microneedle with different method of microfabrication
Cubosomes are nanosized structures self-assembled nanostructured materials used for controlling the release of the entrapped drug molecule. Lornoxicam (LXM) is a potent analgesic nonsteroidal anti-inflammatory (NSAID) drug with a short half-life (3-4) hours. The present study aims to prepare LXM-loaded cubosomes with well-defined morphology, particle size, PDI, high entrapment efficiency, sustained drug release, and high zeta potential value, as a transdermal drug delivery system.
Twelve formulas of LXM-loaded cubosomal dispersions were prepared by a solvent dilution method using Glyceryl monooleate ( GMO) as polar lipid with different stabilizers as Pluronic® F127 or tween 80 and different types o
... Show MoreThe purpose of this study is to determine the useful of Schiff bases derivatives containing (oxazepine, tetrazole) rings with biological activity which can be used as drug and antimicrobial, the present work is started from [Binary (2,5(4,'4-diaminophenyl) – 1,3,4 – oxadiazole]. A variety of Schiff bases and heterocyclic (oxazepine, tetrazole) have been synthesis, and confirm that structures by physical properties , FTIR , 1H-NMR, 13C-NMR, elemental analysis, [Microbial study against three type of bacteria (staphylococcus aurea and klebsiella pneumonia) and (Canadida albncans) fungi].All analyzation performed in center of consulatation University of Jordan.
This research aims to demonstrate the impact of the going concern assumption in different accounting applications to provide a realistic look and more accurate result of activity and financial situation, as well as determining the responsibility of the Company's administration in compliance with the going concern assumption during the preparation for their financial statements, and to clarify the concept of integration between internal audit and external audit about going concern assumption, besides its importance and usefulness on the work of both of the internal auditor and the external auditor, as well as on the company under auditing process.This research purports preparing an internal audit program, including a set of auditing actio
... Show MoreThe aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.
A geographic information system (GIS) is a very effective management and analysis tool. Geographic locations rely on data. The use of artificial neural networks (ANNs) for the interpretation of natural resource data has been shown to be beneficial. Back-propagation neural networks are one of the most widespread and prevalent designs. The combination of geographic information systems with artificial neural networks provides a method for decreasing the cost of landscape change studies by shortening the time required to evaluate data. Numerous designs and kinds of ANNs have been created; the majority of them are PC-based service domains. Using the ArcGIS Network Analyst add-on, you can locate service regions around any network
... Show MoreWeibull distribution is considered as one of the most widely distribution applied in real life, Its similar to normal distribution in the way of applications, it's also considered as one of the distributions that can applied in many fields such as industrial engineering to represent replaced and manufacturing time ,weather forecasting, and other scientific uses in reliability studies and survival function in medical and communication engineering fields.
In this paper, The scale parameter has been estimated for weibull distribution using Bayesian method based on Jeffery prior information as a first method , then enhanced by improving Jeffery prior information and then used as a se
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