Modeling obesity in complex food systems: Systematic review.

Obesity-related data derived from multiple complex systems spanning media, social, economic, food activity, health records, and infrastructure (sensors, smartphones, etc.) can assist us in understanding the relationship between obesity drivers for more efficient prevention and treatment. Reviewed literature shows a growing adaptation of the machine-learning model in recent years dealing with mechanisms and interventions in social influence, nutritional diet, eating behavior, physical activity, built environment, obesity prevalence prediction, distribution, and healthcare cost-related outcomes of obesity.

Could positive affect help engineer robot control systems?

Emotions have long been seen as counteracting rational thought, but over the last decades, they have been viewed as adaptive processes to optimize human (but also animal) behaviour. In particular, positive affect appears to be a functional aspect of emotions closely related to that. We argue that positive affect as understood in Kuhl's PSI model of the human cognitive architecture appears to have an interpretation in state-of-the-art hybrid robot control architectures, which might help tackle some open questions in the field.