The aim of this study was to evaluate the use of fluorescence inducing light to aid the clean-up of tooth surfaces after bracket removal when using buccal or lingual orthodontic appliances. Two full sets of dental arches using extracted human teeth were assembled, with 14 teeth per arch. All teeth were bonded on their buccal and lingual surfaces. After debonding, a single blinded operator performed the tooth surface clean-up, as commonly performed in clinical practice; without the use of fluorescent light (non-FIT) and with two methods using fluorescent light to identify composite remnants on the tooth surfaces (FIT; OPAL and BRACE). Tooth surfaces were scanned before bonding and after clean-up, and the two scans were superimposed using the best-fit method. The results showed that the debonding method, type of tooth and type of tooth surface had a significant effect on the presence of composite remnants, enamel defects, and on debonding time. Contrary to the non-FIT method, there were no composite remnants after clean-up with the use of fluorescence inducing light. Clean-up time was significantly reduced on the buccal surfaces when using the FIT methods. On the lingual surfaces, the FIT methods resulted in larger enamel defects.
In StopLoc we consider the location of new stops along the edges of an existing public transportation network. Examples of StopLoc include the location of bus stops along some given bus routes or of railway stations along the tracks in a railway system. In order to measure the "convenience" of the location decision for potential customers in given demand facilities, two objectives are proposed. In the first one, we give an upper bound on reaching a closest station from any of the demand facilities and minimize the number of stations. In the second objective, we fix the number of new stations and minimize the sum of the distances between demand facilities and stations. The resulting two problems CovStopLoc and AccessStopLoc are solved by a reduction to a classical set covering and a restricted location problem, respectively. We implement the general ideas in two different environments -the plane, where demand facilities are represented by coordinates and in networks, where they are nodes of a graph.
Facial expressions play a leading role in human interactions because they provide signaling information of emotion and create social perceptions of an individuals’ physical and personality traits. Smiling increases socially perceived attractiveness and is considered a signal of trustworthiness and intelligence. Despite the ample information regarding the social importance of an attractive smile, little is known about the association between smile characteristics and self-assessed smile attractiveness. Here we investigate the effect of smile dimensions on ratings of self-perceived smile attractiveness, in a group of 613 young adults using 3D facial imaging. We show a significant effect of proportional smile width (ratio of smile width to facial width) on self-perceived smile attractiveness. In fact, for every 10% increase in proportional smile width, self-perceived attractiveness ratings increased by 10.26%. In the present sample, this association was primarily evident in females. Our results indicate that objective characteristics of the smile influence self-perception of smile attractiveness. The increased strength of the effect in females provides support to the notion that females are overall more aware of their smile and the impact it has on their public image.
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