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Objectives: Translucent skin is an attribute widely appreciated by people in East Asian countries. There have been studies in the literature to describe the phenomenon by means of clinical grading, instrumental measurement and image analysis. However, due to its subjective and complex nature, skin translucency has not been comprehensively and rigorously characterized and modelled, particularly in the Chinese population. This study is to develop a mathematical model that quantitatively describes skin translucency from visual cues objectively measured from the skin., Materials and Methods: The study was designed to characterize and model skin translucency by incorporating expert evaluation, panel perception and image analysis of multiple skin visual attributes in one analysis. Faces of 36 Chinese females aged 18-65 years old were evaluated by a dermatologist to obtain clinical translucency scores. Subject pairs were formed with a relatively high and low translucency score in each pair. Their faces were judged in person by 9 panellists in paired-comparison (2-AFC) fashion to pick a 'more translucent skin' from each subject pair. Front-view facial images of the subjects were taken, and multiple colour and other visually perceivable skin attributes were measured using image analysis. Bradley-Terry analysis and multiple regressions were performed to correlate the panel choices of 'more translucent skin' with the objectively measured skin parameters., Results: Multiple skin colour properties affected the panel choices towards translucent skin. Among them skin tone lightness and skin glossiness had positive effects on skin translucency while the hue, colour unevenness, severity of red and dark spots affected it negatively. Subsurface light reflection and skin visual smoothness had some effect but were not statistically significant. A mathematical model was constructed to predict a person's skin translucency from objectively measured skin attributes., Conclusion: The subjective property of skin translucency can be characterized and quantified via a comprehensive modelling process involving clinical grading, panel evaluation, image-based measurement of skin attributes and statistical analysis. A novel skin parameter, Skin Translucency Index (STI) was established, which provides a way to measure skin translucency, making it possible to assess treatment efficacy before and after product application., (© 2022 Society of Cosmetic Scientists and Societe Francaise de Cosmetologie.)

Demographics and psychographics are used to study the influence of different consumers on product effects in food development and testing. Demographics have a longer history and are routinely used in most research; psychographics are more recent, raising the question of whether they add to research on food products. The research presented here represents extensive exploratory data that demonstrate that both demographic measures and psychographic measures add to our understanding of consumer's liking ratings for nutrient supplements. The results are discussed in the context of broader research on a range of food products. In addition, the research reported here was conducted in four different countries, demonstrating many country effects. Finally, tests were conducted with users of the products, lapsed users of the product, and users of other nutrient supplements (non-users), and this led to many differences in product testing. These results further suggest that age and gender are not the only demographic variables to be studied, along with psychographic variables. The psychographic variables should be selected for a particular product category under investigation, as effects of specific psychographic measures vary for product categories. Specific variables do not fit all products for both demographics and psychographics.

We propose objective, image-based techniques for quantitative evaluation of facial skin gloss that is consistent with human judgments. We use polarization photography to obtain separate images of surface and subsurface reflections, and rely on psychophysical studies to uncover and separate the influence of the two components on skin gloss perception. We capture images of facial skin at two levels, macro-scale (whole face) and meso-scale (skin patch), before and after cleansing. To generate a broad range of skin appearances for each subject, we apply photometric image transformations to the surface and subsurface reflection images. We then use linear regression to link statistics of the surface and subsurface reflections to the perceived gloss obtained in our empirical studies. The focus of this paper is on within-subject gloss perception, that is, on visual differences among images of the same subject. Our analysis shows that the contrast of the surface reflection has a strong positive influence on skin gloss perception, while the darkness of the subsurface reflection (skin tone) has a weaker positive effect on perceived gloss. We show that a regression model based on the concatenation of statistics from the two reflection images can successfully predict relative gloss differences.

Conventional drivers of liking analysis was extended with a time dimension into temporal drivers of liking (TDOL) based on functional data analysis methodology and non-additive models for multiple-attribute time-intensity (MATI) data. The non-additive models, which consider both direct effects and interaction effects of attributes to consumer overall liking, include Choquet integral and fuzzy measure in the multi-criteria decision-making, and linear regression based on variance decomposition. Dynamics of TDOL, i.e., the derivatives of the relative importance functional curves were also explored. Well-established R packages 'fda', 'kappalab' and 'relaimpo' were used in the paper for developing TDOL. Applied use of these methods shows that the relative importance of MATI curves offers insights for understanding the temporal aspects of consumer liking for fruit chews., Competing Interests: The authors declare no conflict of interest.