The Impact of Nutrition and Health Claims on Consumer Perceptions and Portion Size Selection: Results from a Nationally Representative Survey

Nutrition and health claims on foods can help consumers make healthier food choices. However, claims may have a ‘halo’ effect, influencing consumer perceptions of foods and increasing consumption. Evidence for these effects are typically demonstrated in experiments with small samples, limiting generalisability. The current study aimed to overcome this limitation through the use of a nationally representative survey. In a cross-sectional survey of 1039 adults across the island of Ireland, respondents were presented with three different claims (nutrition claim = “Low in fat”; health claim = “With plant sterols. Proven to lower cholesterol”; satiety claim = “Fuller for longer”) on four different foods (cereal, soup, lasagne, and yoghurt). Participants answered questions on perceived healthiness, tastiness, and fillingness of the products with different claims and also selected a portion size they would consume. Claims influenced fillingness perceptions of some of the foods. However, there was little influence of claims on tastiness or healthiness perceptions or the portion size selected. Psychological factors such as consumers’ familiarity with foods carrying claims and belief in the claims were the most consistent predictors of perceptions and portion size selection. Future research should identify additional consumer factors that may moderate the relationships between claims, perceptions, and consumption

EVORA: Deep Evidential Traversability Learning for Risk-Aware Off-Road Autonomy

Traversing terrain with good traction is crucial for achieving fast off-road navigation. Instead of manually designing costs based on terrain features, existing methods learn terrain properties directly from data via self-supervision, but challenges remain to properly quantify and mitigate risks due to uncertainties in learned models. This work efficiently quantifies both aleatoric and epistemic uncertainties by learning discrete traction distributions and probability densities of the traction predictor's latent features. Leveraging evidential deep learning, we parameterize Dirichlet distributions with the network outputs and propose a novel uncertainty-aware squared Earth Mover's distance loss with a closed-form expression that improves learning accuracy and navigation performance. The proposed risk-aware planner simulates state trajectories with the worst-case expected traction to handle aleatoric uncertainty, and penalizes trajectories moving through terrain with high epistemic uncertainty. Our approach is extensively validated in simulation and on wheeled and quadruped robots, showing improved navigation performance compared to methods that assume no slip, assume the expected traction, or optimize for the worst-case expected cost.Comment: Under review. Journal extension for arXiv:2210.00153. Project website: https://xiaoyi-cai.github.io/evora

M. Singer, Man's Glassy Essence. Explorations in Semiotic Anthropology

Bucher Bernadette. M. Singer, Man's Glassy Essence. Explorations in Semiotic Anthropology. In: L'Homme, 1987, tome 27 n°103. pp. 133-134

7. Métamorphoses de la chasse à courre

Plus qu’aucune tradition, la chasse à courre peut apparaître comme une survivance, voire un anachronisme au milieu des mutations technologiques, économiques et sociales qu’a connues la région depuis trente ans. Avec son cérémonial et ses règles élaborées sous des formes multiples (houraillement*, petite et grande vénerie) de l’époque gallo-romaine jusqu’aux Valois, codifiée sous sa forme plus restreinte et raffinée en de savants traités du xive au xviiie siècle, la chasse à courre évoque les ..

D. Schneider, Schneider on Schneider. The Conversion of the Jews and other Anthro­pological Stories as told to Richard Handler

Bucher Bernadette. D. Schneider, Schneider on Schneider. The Conversion of the Jews and other Anthro­pological Stories as told to Richard Handler. In: L'Homme, 1997, tome 37 n°144. pp. 158-160