Pure grade II titanium disks were coated with a thin coating of polyetherketoneketone (PEKK) polymer by RF magnetron sputtering using either nitrogen or argon gas. Sputtering technique was employed at 50 W for one hour at 60°C with continuous flow of nitrogen or argon gas. Field-emission scanning electron microscopy (FE-SEM) showed a continuous, homogeneous, rough PEKK surface coating without cracks. In addition, cross-sectional FE-SEM revealed an average coat thickness of 1.86 μm with argon gas and 1.96 μm with nitrogen gas. There was homogenous adhesion between the coating layer and substrate. The elemental analysis of titanium substrate revealed the presence of carbon, titanium, and oxygen. The RF magnetron sputtering with argon or nitrogen gas coated the titanium substrate with PEKK to provide a uniform coating thickness with increased roughness and wettability resulting in a more advantageous surface for implant osteointegration.
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In this paper, the construction of Hermite wavelets functions and their operational matrix of integration is presented. The Hermite wavelets method is applied to solve nth order Volterra integro diferential equations (VIDE) by expanding the unknown functions, as series in terms of Hermite wavelets with unknown coefficients. Finally, two examples are given
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Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.
In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.
The longitudinal balanced data profile was compiled into subgroup
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In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .
Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage
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The research aimed to study the decision-making of the administrative bodies of sports clubs participating in the Iraqi Football Premier League for the 2022-2023 season. The researchers used the descriptive approach (survey study) to suit the nature of the research. The research community is represented by members of the administrative bodies of the sports clubs participating in the Iraqi Premier Football League for the 2022-2023 season, who number (177) members of the administrative body. The researchers used the questionnaire to collect the necessary data to achieve the goal of researching The method of applying a questionnaire aimed to identify the decision-making of the administrative bodies of sports clubs. The most important r
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