Background: Colonization of soft denture liners by Candida albicans and other microorganisms continued to be a serious problem. The aim of this study was to evaluate the effect of incorporating silver nanoparticles into heat cured acrylic-based soft denture liner on the antifungal activity, and on water sorption, solubility, shear bond strength and color change of the soft lining material. Furthermore, evaluating the amount of silver released. Materials and methods: Silver nanoparticles were incorporated into soft denture liner in different percentages (0.05%, 0.1% and 0.2% by weight). Four hundred and twenty specimens were prepared and divided into five groups according to the test to be performed. The antifungal activity of the soft liner/AgNPs composite was evaluated in three different periods by using (viable count of C. albicans and disk-diffusion test). The amount of silver released in artificial saliva was measured by atomic absorption spectroscopy. The water sorptions, solubility, shear bond strength and color change was measured and the results were statistically analyzed. Results:All experimental groups showed a highly significant decrease in colony forming units of C. albicans in comparison to control group. There was no inhibition zone around any test specimen of any test group. There was no silver detected to be released. The addition of AgNPs resulted in a highly significant decrease in water sorption, while only 0.2% group showed highly significant decrease in solubility. Non significant differences in shear bond strength were found. A highly significant increase in light absorption percentage was observed in all experimental groups. Conclusion: The addition of AgNPs helps to produce soft denture liner with antifungal properties. Silver was not detected to be released. This addition resulted in decrease in water sorption, and did not affect the shear bond strength and it increased the opacity of the material.
Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
... Show MoreThe specifications of lubricating oil are fundamentally the final product of materials that have been added for producing the desired properties. In this research, spherical nanoparticles copper oxide (CuO) and titanium oxides (TiO2) are added to SAE 15W40 engine oil to study the thermal conductivity, stability, viscosity of nano-lubricants, which are prepared at different concentrations of 0.1%, 0.2%, 0.5%, and 1% by weight, and also their pour point, and flash point as five quality parameters. The obtained results show that CuO nanoparticles in all cases, give the best functionality and effect on engine oil with respect to TiO2. With 0.1 wt. % concentration, the thermal conductivity of CuO/oil and TiO2/
... Show MoreThe antimicrobial potency of the crude ethanolic extracts from different Iraqi plants were evaluated . Further more, total sesquiterpene lactones and phenolic compounds were isolated and their antimicrobial activity attempted. The results indicated that crude extracts have no activity except that of Callistemon lanceolatus. Also, the sesquiterpene lactones and phenolic compounds isolated from Callistemon lanceolatus were the most significant antimicrobial active constituents of the studied plants.
Five derivatives of thiadiazole were prepared with aldehydes and alkyl halides, compoundA: 2-amino-5-thiol-1,3,4- thiadiazole, compound B :2-(o-hydroxybenzylidine)amino-5-thiol-1,3,4-thiadiazole, compoundC: 2(2-butan-lidine)amino-5-thiol-1,3,4-thiadiazole, compound E: 2- amino-5-(2-Propanylthio)-1,3,4-thiadiazol) and compound F:2(o-chlorobenzylamino)-5-(2-propanyl thio)-1,3,4 thiadiazol. All prepared compounds were diagnosed by (IR) and (UV) Spectroscopy. All of those compounds were screened for their anti-microbial activity in vitro. The results show that most of the compounds A, B, C exhibited moderate to good activity against Gram-positive bacteria and the same compound exhibit low to moderate activity on most gram-negative bacte
... Show MoreIn this work, a series of new Nucleoside analogues (D-galactopyranose linked to oxepanebenzimidazole moiety) was synthesized via multisteps synthesis. The first step involved preparation of two benzimidazoles 2-styrylbenzimidazole and 2-(phenyl ethynyl) benzimidazole via reaction of phenylenediamine with cinnamic acid or ?-phenyl propiolic acid. Electrophilic addition of the prepared benzimidazoles by three anhydrides in the second step afforded (4-6) and (14-16) which in turn were treated with 1,2,3,4-di-O-isopropylidene galactopyranose in the third step to afford a series of the desirable protected nucleoside analogues (7-9) ,(17-19)which after hydrolysis in methanolic sodium methoxidein the fourth step afforded the free nucleoside analog
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