An Actor-Critic based controller for glucose regulation in type 1 diabetes

A novel adaptive approach for glucose control in individuals with type 1 diabetes under sensor-augmented pump therapy is proposed. The controller, is based on Actor-Critic (AC) learning and is inspired by the principles of reinforcement learning and optimal control theory. The main characteristics of the proposed controller are (i) simultaneous adjustment of both the insulin basal rate and the bolus dose, (ii) initialization based on clinical procedures, and (iii) real-time personalization. The effectiveness of the proposed algorithm in terms of glycemic control has been investigated in silico in adults, adolescents and children under open-loop and closed-loop approaches, using announced meals with uncertainties in the order of ±25% in the estimation of carbohydrates. The results show that glucose regulation is efficient in all three groups of patients, even with uncertainties in the level of carbohydrates in the meal. The percentages in the A+B zones of the Control Variability Grid Analysis (CVGA) were 100% for adults, and 93% for both adolescents and children. The AC based controller seems to be a promising approach for the automatic adjustment of insulin infusion in order to improve glycemic control. After optimization of the algorithm, the controller will be tested in a clinical trial.

Actor and partner effects of self-esteem on relationship satisfaction and the mediating role of secure attachment between the partners

We examined actor and partner effects of self-esteem on relationship satisfaction, using the actor-partner interdependence model and data from five independent samples of couples. The results indicated that self-esteem predicted the individual’s own relationship satisfaction (i.e., an actor effect) and the relationship satisfaction of his or her partner (i.e., a partner effect), controlling for the effect of the partner’s selfesteem. Gender, age, and length of relationship did not moderate the effect sizes. Moreover, using one of the samples, we tested whether secure attachment to the current partner (assessed as low attachment-related anxiety and avoidance) mediated the effects. The results showed that attachment-related anxiety and avoidance independently mediated both the actor and the partner effect of self-esteem on relationship satisfaction.

How large are actor and partner effects of personality on relationship satisfaction? The importance of controlling for shared method variance

Previous research suggests that the personality of a relationship partner predicts not only the individual’s own satisfaction with the relationship but also the partner’s satisfaction. Based on the actor–partner interdependence model, the present research tested whether actor and partner effects of personality are biased when the same method (e.g., self-report) is used for the assessment of personality and relationship satisfaction and, consequently, shared method variance is not controlled for. Data came from 186 couples, of whom both partners provided self- and partner reports on the Big Five personality traits. Depending on the research design, actor effects were larger than partner effects (when using only self-reports), smaller than partner effects (when using only partner reports), or of about the same size as partner effects (when using self- and partner reports). The findings attest to the importance of controlling for shared method variance in dyadic data analysis.

How involved are they really? A comparative network analysis of the institutional drivers of local actor inclusion

Different socio-economic and environmental drivers lead local communities in mountain regions to adapt land use practices and engage in protection policies. The political system also has to develop new approaches to adapt to those drivers. Local actors are the target group of those policy approaches, and the question arises of if and how much those actors are consulted or even integrated into the design of local land use and protection policies. This article addresses this question by comparing seven different case studies in Swiss mountain regions. Through a formal social network analysis, the inclusion of local actors in collaborative policy networks is investigated and compared to the involvement of other stakeholders representing the next higher sub-national or national decisional levels. Results show that there is a significant difference (1) in how local actors are embedded compared to other stakeholders; and (2) between top-down versus bottom-up designed policy processes.