Objective: Evaluate the effects of different storage periods on flexural strength (FS) and degree of conversion (DC) of Bis-Acryl composite and Urethane dimethacrylate provisional restorative materials. Material and Methods: A total of 60 specimens were prepared from four temporary crown materials commercially available and assigned to four tested groups (n = 15 for each group): Prevision Temp, B&E CROWN, Primma Art, and Charm Temp groups. The specimens were stored in artificial saliva, and the FS was tested after 24 h, 7 d, and 14 d. A standard three-point bending test was conducted using a universal testing machine. Additionally, the DC was determined using a Fourier transform infrared spectroscopy (FTIR) device. The data were analyzed statistically using two- way ANOVA, Tukey`s HSD post-hoc test, and the Bonferroni test, all at a 5% significance level. For each group, a paired samples test was applied to compare the DC of the immediate and 24 h samples. Results: The highest FS value was found for the Prevision Temp material, while the Charm Temp material showed the lowest FS, with no statistically significant difference between the mean values of the groups at 24 h; while there were significant differences at 7d and 14 d of storage. However, within each group, the aging had no significant impact on the FS, except for an increase in the FS of the B&E CROWN group after 14 d. Prevision Temp also had the highest mean DC value. At each time interval, significant differences were recorded. Moreover, within each group of material, aging significantly increased the DC, except for the Primma Art. Conclusion: Bis-acryl composite resin materials exhibited higher flexural strength compared to traditional methyl methacrylate resin during the 14 d investigation period. Aging in artificial saliva did not significantly affect the mechanical performance of the tested materials. Materials with higher DC values showed greater flexural strength; where the Prevision Temp showed higher FS and DC values than the other tested materials.
NA Nasir, SHM Ali, HQMA AL-Ess, WA Hussein, MKW Al-Janabi, KIA Mohammed, JM Mosa, Euromediterranean Biomedical Journal, 2020
Introduction: Cerebral hydatid disease (CHD) is rare and the multiple-cystic variety is even rarer. In this paper, we report a case of multiple CHD and explore a possible link with a preceding spontaneous intracerebral haemorrhage (ICH). Case presentation: A 27-year old gentleman with a history of surgically-evacuated, spontaneous ICH presented with severe headache, left-sided weakness - Medical Research Council (MRC) grade II - and recurrent tonic-clonic seizures, while on a full dose of anti-epileptic medication. Brain magnetic resonance imaging (MRI) scans showed multiple intra-axial cystic lesions in the right hemisphere. The cysts were removed intact using Dowling’s technique through a large temporoparietal crani
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... Show MoreThe current research is concerned with studying the variables in the promotion process which influence the advertisement design structure, as the accomplished design and construction process is subject to many variables, whether they were intellectual or technological, internal or external variables. These variables may overlap in order to get a comprehensive system for the artistic configuration, that any design in its content reaches the highest levels of perfection is connected to the extent of its compliance with and approximation to these variables, that is why we find their reflections deeply rooted in the individual's mind, especially the designer artist who is influenced by everything surrounding him forming knowledge systems res
... Show MoreWireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s
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