Iron oxide(Fe3O4) nanoparticles of different sizes and shapes were synthesized by solve-hydrothermal reaction assisted by microwave irradiation using ferrous ammonium sulfate as a metal precursor, oleic acid as dispersing agent, ethanol as reducing agent and NaOH as precipitating agent at pH=12. The synthesized Fe3O4 nano particles were characterized by X-ray diffraction (XRD), FTIR and thermal analysis TG-DTG. Sizes and shapes of Fe3O4 nanoparticles were characterized by Scanning Electron Microscopy (SEM), and atomic force microscopy (AFM).

Background: This study was conducted to evaluate the hard palate bone density and thickness during 3rd and 4th decades and their relationships with body mass index (BMI) and compositions, to allow more accurate mini-implant placement. Materials and method: Computed tomographic (CT) images were obtained for 60 patients (30 males and 30 females) with age range 20-39 years. The hard palate bone density and thickness were measured at 20 sites at the intersection of five anterioposterior and four mediolateral reference lines with 6 and 3 mm intervals from incisive foramen and mid-palatal suture respectively. Diagnostic scale operates according to the bioelectric impedance analysis principle was used to measure body weight; percentages of body fa

In this paper, construction microwaves induced plasma jet(MIPJ) system. This system was used to produce a non-thermal plasma jet at atmospheric pressure, at standard frequency of 2.45 GHz and microwave power of 800 W. The working gas Argon (Ar) was supplied to flow through the torch with adjustable flow rate by using flow meter, to diagnose microwave plasma optical emission spectroscopy(OES) was used to measure the important plasma parameters such as electron temperature (Te), residence time (Rt), plasma frequency (?pe), collisional skin depth (?), plasma conductivity (?dc), Debye length(?D). Also, the density of the plasma electron is calculated with the use of Stark broadened profiles

Carbon-fiber-reinforced polymer (CFRP) is widely acknowledged as a leading advanced material structure, offering superior properties compared to traditional materials, and has found diverse applications in several industrial sectors, such as that of automobiles, aircrafts, and power plants. However, the production of CFRP composites is prone to fabrication problems, leading to structural defects arising from cycling and aging processes. Identifying these defects at an early stage is crucial to prevent service issues that could result in catastrophic failures. Hence, routine inspection and maintenance are crucial to prevent system collapse. To achieve this objective, conventional nondestructive testing (NDT) methods are utilized to i

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

‎ Sixteen new complexes with the general formula [M(L)2(H2O)2] were ‎prepared resulting from the reaction of the two new Schiff base ligands, which ‎are‏: -‏ L1= (E)-5-((2-hydroxybenzylidene)amino)-2-phenyl-2,4-dihydro-3H-pyrazol-3-one)‎ L2 = (E)-5-((2-hydroxy-3-methoxybenzylidene)amino)-2-phenylpyrazolidin-3-one) ‎ ‎ With divalent metal ions (manganese, cobalt, nickel, copper, zinc, cadmium, ‎mercury) and (tetravalent platinum).‎‏ ‏ ‎ Ligands was derived from the reaction of the amine (5-amino-2-phenyl-2,4-‎dihydro-3H-pyrazol-3-one) with Salicylaldehyde and ortho-vanillin, which is ‎linked to the metal ions via the nitrogen atoms are the isomethene group and ‎the oxygen is the hydroxide group of t

In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes