Abstract Background: The daily usage of maxillofacial prostheses causes them to mechanically deteriorate with time. This study was aimed to evaluate the reinforcement of VST50F maxillofacial silicone by using yttrium oxide (Y2O3) nanoparticles (NPs) to resist aging and mechanical deterioration. Materials and Method: Y2O3 NPs (30–45nm) were loaded into VST50F maxillofacial silicone in two weight percentages (1 and 1.5 wt%), which were predetermined in a pilot study as the best rates for improving tear strength with minimum increase in hardness values. A total of 120 specimens were prepared and divided into the control and experimental groups (with 1 and 1.5 wt% Y2O3 addition). Each group included 40 specimens, 10 specimens for each parameter tested (i.e., tear strength, surface roughness, hardness, tensile strength and elongation percentage). Specimens were artificially aged in a weathering chamber for 150 h and then tested. Data were analyzed by ANOVA and Tukey’s honestly significant difference (HSD). Statistical significance was set to P ≤ 0.05. Scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy were also conducted. Results and Discussion: SEM results showed that Y2O3 NPs were distributed well within the silicon matrix. FTIR results indicated that the NPs were physically dispersed within VST50F silicone without chemical interaction. After 150 h of accelerated artificial aging, adding Y2O3 NPs significantly increased the tear strength, hardness, surface roughness, and elongation percentage. Tensile strength increased non significantly. Conclusion: Adding Y2O3 NPs as fillers improved the mechanical properties of artificially aged maxillofacial silicone elastomer. Keywords: maxillofacial silicone, Y2O3, nanoparticles, fillers, artificial aging.
The aim of the research is to measure the length between the variable the efficiency of the tax examiner with its dimensions represented by (scientific questions, practical process (experience), training and development, impartiality and independence, ethics of the profession) and the approved variable discovering the artificial adaptation of profits, and the degree of arrangement of those dimensions its importance and priority, and the research problem has been identified In a main question that is there any effect of copying the images of the image examiner in discovering the adaptation, the financial statements and reports of the companies (X, Y) and the banks (A, B) were relied on in the interpretation of the results, t
... Show MoreIn this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe
... Show MoreMacrocheles glaber (Müller) is one of several mites that feeds on eggs, newly hatched &
small larvae of house fly Musca domestica L. This mite was reared in the laboratory on house
fly frozen eggs at constant conditions of 28°C±1 and 90% relative humidity using sterilized
horse dung substrate. The predation rate of adult female and male on frozen eggs was (18, 3)
eggs/mite/day respectively, the number of frozen eggs destroyed by adult female through its
life was 185.6 eggs.
The mean duration of adult female from egg to adult stage was 2.67 days, the longevity of
female was 27.8 days, the mean daily egg production was 2.7 egg with total egg productivity
of 72.1 egg.
Background: The roles of AI in the academic community continue to grow, especially in the enhancement of learning outcomes and the improvement of writing quality and efficiency. Objectives: To explore in depth the experience of senior pharmacy students in using artificial intelligence for academic purposes. Methods: This qualitative study included face-to-face individual interviews with senior pharmacy students from March to May 2023 using a pre-planned interview guide of open-ended questions. All interviews were audio-recorded. Thematic analysis was used to analyze the data. Results: The results were obtained from 15 in-depth face-to-face interviews with senior pharmacy students (5th and 4th years). Eight participants were male, and seven
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