Background: The high reactivity of hydrogen peroxide used in bleaching agents have raised important questions on their potential adverse effects on physical properties of restorative materials. The purpose of this in vitro study was to evaluate the effect of in-office bleaching agents on the microhardness of a new Silorane-based restorative material in comparison to methacrylate-based restorative material. Materials and method: Forty specimens of Filtek™ P90 (3M ESPE,USA) and Filtek™ Supreme XT (3M ESPE, USA) of (8mm diameter and 3m height) were prepared. All specimens were polished with Sof-Lex disks (3M ESPE, USA). All samples were rinsed and stored in incubator 37˚C for 24 hours in DDW. Ten sample of each material were subjected to 37.5% hydrogen peroxide gel (Pola office +, SDI)for 8 minutes while exposed to light curing device, this step was repeated three times for 3 weeks. While the other ten samples for each material was served as control. All specimens were subjected to microhardness test using digital microhardness tester to determine the VHN (Vickers Hardness Number) Results : The Filtek™ P90 exhibited higher microhardness value than Filtek™ Supreme XT. After hydrogen peroxide treatment, both types of composites exhibited low microhardness values but still Filtek™ P90 is harder than Filtek™ Supreme XT. Conclusion : In-office hydrogen peroxide bleaching agent resulted in reduction in microhardness values for both composite materials. Silorane- based composite is more affected by the bleaching agent than methacrylate-based composite.
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The present study dealt with the removal of methylene blue from wastewater by using peanut hulls (PNH) as adsorbent. Two modes of operation were used in the present work, batch mode and inverse fluidized bed mode. In batch experiment, the effect of peanut hulls doses 2, 4, 8, 12 and 16 g, with constant initial pH =5.6, concentration 20 mg/L and particle size 2-3.35 mm were studied. The results showed that the percent removal of methylene blue increased with the increase of peanut hulls dose. Batch kinetics experiments showed that equilibrium time was about 3 hours, isotherm models (Langmuir and Freundlich) were used to correlate these results. The results showed that the (Freundlich) model gave the best fitting for adsorption capacity. D
... Show MoreFirst: People’s need for advocacy:
Calling for a legal necessity for all people, regardless of their races, colours, tongues, and culture, to explain the truth, spread fear, bring benefits, ward off evil, regulate a person’s relationship with his Lord, and his relationship with creatures, so that he knows his money and what he owes.
All of creation is in dire need of the call to God’s religion with insight due to their inability to reach out to goodness, righteousness, guidance, and success on their own. Man is limited in thinking in this universe, limited in his resolve, unable to know what will improve his affairs in the two worlds. His need for religion is one of the necessities of his life, and one of the comple
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In the present work effect of recycled heating and cooling on the values of concrete compressive strength due to high temperature of 4000C was studied.
The tests show that the percent of reduction in compressive strength of the samples which exposed to a temperature of 4000C for one cycle was 32.5%, while the reduction was 52.7% for the samples which were exposed to recycled heating and cooling of ten times .
Moreover a study of the effect of specimen sizes on the percentages of compressive strength reduction due to high temperature
... Show MoreThis study aims to conduct an exhaustive comparison between the performance of human translators and artificial intelligence-powered machine translation systems, specifically examining the top three systems: Spider-AI, Metacate, and DeepL. A variety of texts from distinct categories were evaluated to gain a profound understanding of the qualitative differences, as well as the strengths and weaknesses, between human and machine translations. The results demonstrated that human translation significantly outperforms machine translation, with larger gaps in literary texts and texts characterized by high linguistic complexity. However, the performance of machine translation systems, particularly DeepL, has improved and in some contexts
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme
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