Background: Dental erosion is a common oral condition which results due to consumption of high caloric and low pH acidic food such as carbonated drinks and fruit juices. It is expected that these food types can cause irreversible damage to dental hard tissues and early deterioration of the dental restorations. So, this study aimed to evaluate and compare the erosive potential effects of orange fruit juice and Miranda orange drink on the microhardness of an orthodontic composite material. Materials and methods: Thirty discs with a thickness of 2 mm and a diameter of 10 mm were prepared from orthodontic bonding composite. The prepared discs were equally divided into three groups (n=10). Microhardness analysis was carried out both prior to and subsequent to immersion cycles. The microhardness of the specimens underwent evaluation subsequent to immersion in the beverages for durations of 6 hours (equivalent to one day) and 42 hours (equivalent to seven days). Microhardness measurements at baseline, one day, and one week were performed utilizing the Vickers microhardness testing. Statistical analyses were carried out using repeated measure one way ANOVA test and Bonferroni post-hoc test with a level of significant p< 0.05. Results: The micro hardness of composite exposed to the selected soft drinks was significantly decreased (p< 0.05). Conclusions: Natural, industrial orange juices and Miranda can affect the micro hardness of composite. The beverage effect on the orthodontic composite based on the type of juice and the exposure time to these beverages.
The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of
... Show MoreIn current article an easy and selective method is proposed for spectrophotometric estimation of metoclopramide (MCP) in pharmaceutical preparations using cloud point extraction (CPE) procedure. The method involved reaction between MCP with 1-Naphthol in alkali conditions using Triton X-114 to form a stable dark purple dye. The Beer’s law limit in the range 0.34-9 μg mL-1 of MCP with r =0.9959 (n=3) after optimization. The relative standard deviation (RSD) and percentage recoveries were 0.89 %, and (96.99–104.11%) respectively. As well, using surfactant cloud point extraction as a method to extract MCP was reinforced the extinction coefficient(ε) to 1.7333×105L/mol.cm in surfactant-rich phase. The small volume of organi
... Show MoreABSTRACT:
Microencapsulation is used to modify and retard drug release as well as to overcome the unpleasant effect
(gastrointestinal disturbances) which are associated with repeated and overdose of ibuprofen per day.
So that, a newly developed method of microencapsulation was utilized (a modified organic method) through a
modification of aqueous colloidal polymer dispersion method using ethylcellulose and sodium alginate coating materials to
prepare a sustained release ibuprofen microcapsules.
The effect of core : wall ratio on the percent yield and encapsulation efficiency of prepared microcapsules was low, whereas
, the release of drug from prepared microcapsules was affected by core: wall ratio ,proportion of coa
The temperature control process of electric heating furnace (EHF) systems is a quite difficult and changeable task owing to non-linearity, time delay, time-varying parameters, and the harsh environment of the furnace. In this paper, a robust temperature control scheme for an EHF system is developed using an adaptive active disturbance rejection control (AADRC) technique with a continuous sliding-mode based component. First, a comprehensive dynamic model is established by using convection laws, in which the EHF systems can be characterized as an uncertain second order system. Second, an adaptive extended state observer (AESO) is utilized to estimate the states of the EHF system and total disturbances, in which the observer gains are updated
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