Background: One of the most important complications of fixed orthodontic treatment is formation of white spots, which are initial carious lesions. Addition of antimicrobial agents into orthodontic adhesive material might be wise solution for prevention of white spots formation. The aim of this study was to evaluate the antibacterial properties of orthodontic adhesive primer against S. Mutans after adding the three different types of nanoparticles (Ag, ZnO, or TiO2). Materials and methods: Discs were prepared using empty insulin syringe approximately 2 mm×2 mm rounded in shape specimens (40 discs) were divided into four groups (ten discs for each group): The first group was the control (made from primer only), the second group (10 discs made from primer and incorporation of Ag NPs), the third group (10 discs made from primer and incorporation of ZnO NPs), and the fourth group (10 discs made from primer and incorporation of TiO2 NPs). The antibacterial properties of orthodontic bonding agent after incorporation of (Ag, ZnO, or TiO2) nanoparticles were evaluated by disc diffusion test and viable count of mutans streptococci. Results: The results of this study showed that there were high significant differences between the all groups using ANOVA F-test, and the colony forming unit were 99×10³, 39.6×10³, 19.4×10³, 6.6×10³ CFU/mL respectively. Conclusion: The incorporation of these nanoparticles (Ag, ZnO, or TiO2) into Transbond ™ XT adhesive primer helps to enhance the antibacterial properties of primer against the S. mutans.
The insulation system of a machine coil includes several layers made of materials with different characteristics. The effective insulation design of machine coils, especially in the machine end winding, depends upon an accurate model of the stress grading system. This paper proposes a modeling approach to predict the transient overvoltage, electric field, and heat generation in machine coils with a stress grading system, considering the variation of physical properties in the insulation layers. A non-uniform line model is used to divide the coil in different segments based on material properties and lengths: overhang, stress grading and slot. The cascaded connection of chain matrices is used to connect segments for the representation of the
... Show MoreAn experimental study was carried out to improve the surface roughness quality of the stainless steel 420 using magnetic abrasive finishing method (MAF). Four independent operation parameters were studied (working gap, coil current, feed rate, and table stroke), and their effects on the MAF process were introduced. A rotating coil electromagnet was designed and implemented to use with plane surfaces. The magnetic abrasive powder used was formed from 33%Fe and 67% Quartz of (250µm mesh size). The lubricant type SAE 20W was used as a binder for the powder contents. Taguchi method was used for designing the experiments and the optimal values of the selected parameters were found. An empirical equation representing the r
... Show MoreOne of the most important problems that would continuously face the Higher education organizations is how to improve the service level presented by them, and how this can lead to increase demand for services of this organizations.As this issue has exhausted many organizations pushed some of them to withdraw from the market Because of weaknesses in their services. Here lies the importance of this matter to be given more attention in order to maintain the organization competitive position. According to that, The selection of the research title (The Impact of Quality on the Level of the University Service Request) which seeks to measure the impact of service quality on the level of demand, At a time when world&
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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