Logical modeling of emotions for Ambient Intelligence

International audienceAmbient Intelligence (AmI) is the art of designing intelligent and user-focused environments. It is thus of great importance to take human factors into account. In this chapter we especially focus on emotions, that have been proved to be essential in human reasoning and interaction. To this end, we assume that we can take advantage of the results obtained in Artificial Intelligence about the formal modeling of emotions. This chapter specifically aims at showing the interest of logic as a tool to design agents endowed with emotional abilities useful for Ambient Intelligence applications. In particular, we show that modal logics allow the representation of the mental attitudes involved in emotions such as beliefs, goals or ideals. Moreover, we illustrate how modal logics can be used to represent complex emotions (also called self-conscious emotions) involving elaborated forms of reasoning, such as self-attribution of responsibility and counterfactual reasoning. Examples of complex emotions are regret and guilt. We illustrate our logical approach by formalizing some case studies concerning an intelligent house taking care of its inhabitants

The effect of type 1 diabetes mellitus on the gender difference in coronary artery calcification

AbstractOBJECTIVESTo examine whether the gender difference in coronary artery calcification, a measure of atherosclerotic plaque burden, is lost in type 1 diabetic patients, and whether abnormalities in established coronary heart disease risk factors explain this.BACKGROUNDType 1 diabetes abolishes the gender difference in coronary heart disease mortality because it is associated with a greater elevation of coronary disease risk in women than men. The pathophysiological basis of this is not understood.METHODSCoronary artery calcification and coronary risk factors were compared in 199 type 1 diabetic patients and 201 nondiabetic participants of similar age (30 to 55 years) and gender (50% female) distribution. Only one subject had a history of coronary disease. Calcification was measured with electron beam computed tomography.RESULTSIn nondiabetic participants there was a large gender difference in calcification prevalence (men 54%, women 21%, odds ratio 4.5, p < 0.001), half of which was explained by established risk factors (odds ratio after adjustment = 2.2). Diabetes was associated with a greatly increased prevalence of calcification in women (47%), but not men (52%), so that the gender difference in calcification was lost (p = 0.002 for the greater effect of diabetes on calcification in women than men). On adjustment for risk factors, diabetes remained associated with a threefold higher odds ratio of calcification in women than men (p = 0.02).CONCLUSIONSIn type 1 diabetes coronary artery calcification is greatly increased in women and the gender difference in calcification is lost. Little of this is explained by known coronary risk factors