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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http://dx.doi.org/10.1038/s41598-021-82478-9 | DOI Listing |
Cureus
January 2025
Department of Orthodontics, School of Dental Sciences, University Sains Malaysia, Kota Bharu, MYS.
Background: Soft tissue specifications and facial values vary depending on the underlying skeletal structures. To achieve the ideal treatment result and patient satisfaction, one must know the attractive soft tissue specifications compatible with each type of malocclusion. This study aims to analyze the facial measurements that contribute to perceived facial attractiveness in patients with vertical growth patterns and skeletal class I malocclusion, focusing on gender-specific differences.
View Article and Find Full Text PDFJ Esthet Restor Dent
December 2024
Head Prosthodontics, Akademie für Orale Implantologie (Academy for Oral Implantology), Vienna, Austria.
Statement Of Problem: Esthetic dental features, especially the maxillary anterior teeth, significantly influence perceived attractiveness. Gingival recessions can negatively affect smile esthetics, particularly when asymmetrical.
Purpose: This study aimed to investigate the perception of dentists and non-professionals regarding subtle variations in the apically displaced soft tissue surrounding a lateral or central incisor.
Emotion
December 2024
Department of Psychology, Ben Gurion University of the Negev.
Dyadic affective processes are key determinants of romantic relationship quality. One such process termed emotional synchrony (i.e.
View Article and Find Full Text PDFJ R Soc N Z
February 2024
Discipline of Orthodontics, Faculty of Dentistry, University of Otago, Dunedin, New Zealand.
The desire for an attractive smile is a major reason people seek orthodontic and other forms of cosmetic dental treatment. An understanding of the features of a smile is important for dental diagnosis and treatment planning. The common methods of smile analysis rely on the visual analysis of smile aesthetics using posed photographs, and videos and gathering information about smiles through patient questionnaires and diaries.
View Article and Find Full Text PDFHeliyon
October 2024
Chungbuk National University, Department of Computer Engineering, Cheongju, 28644, South Korea.
Pre-trained chemical language models (CLMs) have attracted increasing attention within the domains of cheminformatics and bioinformatics, inspired by their remarkable success in the natural language processing (NLP) domain such as speech recognition, text analysis, translation, and other objectives associated with language. Furthermore, the vast amount of unlabeled data associated with chemical compounds or molecules has emerged as a crucial research focus, prompting the need for CLMs with reasoning capabilities over such data. Molecular graphs and molecular descriptors are the predominant approaches to representing molecules for property prediction in machine learning (ML).
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