Background: In capturing a negative image, the digital impression secures a digital record for the purposeof designing and creating restorations. The introduction of scanning system presents a paradigm shift in the way of the dental impression procedure and encourages the accuracy of obtained restoration especially in the marginal area as a result of producing accurate final impression The digital system offers many advantages over the Conventional method.. The objective of this present in vitro study was to evaluate the marginal fitness of all ceramic crowns fabricated by direct digital scanning of the prepared tooth using two types of intra-oral cameras (Bluecam camera with strip light projection technique and Omnicam camera with video sampling technique). Materials and Methods: Sixteen sound upper first premolar teeth of comparable size were collected. Standardized preparation of all teeth samples were carried out to receive all ceramic crown restoration with deep chamfer finishing line (1mm), axial length (4mm) and convergence angle (6â—¦). The specimens divided in to two groups according to the type of digital impression technique: Group A, eight prepared teeth scanned directly by Bluecam camera; Group B, eight prepared teeth scanned directly by Omnicam camera. Then CAD/CAM all ceramic crowns constructed for each tooth sample. Marginal discrepancy was measured at Sixteen points per tooth using digital microscope at (120X) magnification. Results: Independent sample t-test was used to identify and localize the source of difference among the groups. It was found that there is statistically non- significant difference in the marginal gap mean values between (group A and group B). Conclusions: From the above result we can conclude that the two types of direct digitization techniques have the same accuracy.
thin films of se:2.5% as were deposited on a glass substates by thermal coevaporation techniqi=ue under high vacuum at different thikness
A theoretical analysis studied was performed to study the opacity broadening of spectral lines emitted from aluminum plasma produced by Nd-YLF laser. The plasma density was in the range 1028-1026 )) m-3 with length of plasma about ?300) m) , the opacity was studied as function of plasma density & principle quantum number. The results show that the opacity broadening increases as plasma density increases & decreases with the spacing between energy levels of emission spectral line.
The study included adding antimony oxide to mixtures of coating metal surfaces (Enameling), after it was selected ceramic materials used in the coating metal pieces of the type of steel and cast iron in two layers. The first is called a ground coat and the second is a cover coat.
Ceramic materials layer for ground coat have been melted down in
platinum crucible at a temperature of 1200oC to prepare the glass
mixture (Frit). It was coated on metals at a temperature of 780oC for
two minutes, while the second layer was prepared glass mixture
(Frit) at a temperature of 1200oC, but was coated at a temperature of
760oC for two minutes.
Underwent tests crystalline state of powders (Frits) and enameled samples using X-ray di
Experimental work has been performed on three capillary tubes of different lengths and diameters using R-12 and R-134a. The test also studies the effect of discharge and speed of evaporator fan. The results clearly showed that refrigerant type and discharge significantly influence the temperature drop across the capillary tube. While the speed of evaporator fan has small effect. Experimental results showed that the temperature gradient for the two refrigerants are the same, but after approximatly one meter the temperature gradient of R-134a is steeper than R-12.
Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
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1 – The discloser of the level of moral values in the children of kindergarten.
2 - Building an educational program designed to develop moral values on the children of kindergarten.
3 - Knowing the impact of the program in the development of moral values in children
Purposive sample was selected consisted of 40 children and a child aged 5-6 years and to achieve objectives of the research promising measure of the moral values kindergarten has been applied to the children of the two groups was based on pre and post test
Background: Dolutegravir sodium (DTG), used to treat HIV, faces challenges in delivering effective therapeutic concentrations to the brain due to the blood-brain barrier (BBB). Nanostructured lipid carriers (NLCs) combined with in situ gels present a promising strategy for enhancing brain drug delivery via the intranasal route. Objective: To compare brain pharmacokinetics of DTGs delivered via NLC-loaded in situ gel intranasal administration with the conventional intravenous (IV) drug solution. Methods: 80 Wistar rats, which were divided into three groups: two groups consisting of 39 animals each and a control group with 2 animals. Rats were administered with a dose of 1.0 mg/kg of DTGs IV, and DTGs NLC-loaded in situ gel were admin
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