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Objective: To evaluate the microleakage at the junction between amalgam-composite resin restorations using different bonding systems. Material and Methods: In this in-vitro study, standard class II cavities were prepared on 40 human maxillary premolars. The axial and gingival floor depths of the cavities were 2 mm and 1 mm below (cementoenamel junction), respectively. The samples were divided into 4 groups (n = 10). In all groups, a layer of 1-mm thick amalgam was used as a coating for the initial part of the gingival floor. In group 1, no bonding system was used for amalgam restoration. In group 2, G-Premio Bond was applied. G-Premio bond + alloy primer and single bond + alloy primer were used in group 3 and group 4, respectively. The rest of the cavities in all groups were then repaired using FiltekZ250 composite. The samples were thermocycled at 500 rpm and immersed in 1% methylene blue solution for 24 hours to allow dye penetration. Once cut, the samples were placed under a stereomicroscope (40X) to determine the microleakage rate. Data analysis was carried out using post-hoc and Chi-square tests (p<0.05). Results: The highest and lowest microleakage rate was related to groups 1 and 3, respectively. There was a significant difference between groups (1,2) and (1,3), and (1,4), and groups (2,3) (p<0.05). Conclusion: The use of alloy primer and bonding could reduce the microleakage between the two restorations.

Construction progress monitoring ensures the construction project is consistent with the schedule and enables the detection of any deviations in the geometry and/or any variation in the schedule. The traditional progress monitoring requires specialized personnel to walk around on the construction site to manually collect data and verify the progress of activities, which is time consuming, costly and/or error prone. Image-based technology is effective for recording on-site data geospatially and chronologically. It has gained increasing attention in the construction field for progress monitoring, work space analysis and quality assurance. However, a notable downside of image processing is the light condition, particularly for noisy environments such as construction sites. Poor or undesirable ambient light conditions produce low quality images that significantly affect the accuracy of data extracted from related images and lead to a high level of errors. This paper presents an innovative approach based on thermal image analysis to overcome problems related to the image quality. Thirty preliminary tests and three case studies have been implemented to show the feasibility of the method. A range of improvement between 8 to 48% has been attained that confirms the great potential of thermal images to overcome the limitation of image-based approaches.