The changing politics of preference formation in international trade negotiations: the European Union in the Doha Round

This research seeks to provide an explanation for variations of “politics” of preference formation in international trade negotiations. Building on the ‘policy determines politics’ argument, I hypothesize the existence of a causal relationship between issue-characteristics and their variations with politics dynamics and their variations. More specifically, this study seeks to integrate into a single analytical framework two dimensions along which variations in the “politics of preference formation” can be organized: configurations of power relationships among the relevant actors in the structures within which they interact as well as the logic and the motivations of the actors involved in the policy making process. To do so, I first construct a four-cell typology of ‘politics of preference formation’ and, then, I proceed by specifying that the type of state-society configurations as well as the type of actors’ motivations in the “politics of preference formation” depend, respectively, on the degree to which a policy issue is perceived as politically salient and on the extent to which the distributional implications of such an issue can be calculated by the relevant stakeholders in the policy making process. The empirical yardstick against which the validity of the theoretical argument proposed is tested is drawn from evidence concerning the European Union’s negotiating strategy in four negotiating areas in the context of the so-called WTO’s Doha Development Round of multilateral trade negotiations: agriculture, competition, environment and technical assistance and capacity building.

From fall-risk assessment to fall detection: inertial sensors in the clinical routine and daily life

Falls are caused by complex interaction between multiple risk factors which may be modified by age, disease and environment. A variety of methods and tools for fall risk assessment have been proposed, but none of which is universally accepted. Existing tools are generally not capable of providing a quantitative predictive assessment of fall risk. The need for objective, cost-effective and clinically applicable methods would enable quantitative assessment of fall risk on a subject-specific basis. Tracking objectively falls risk could provide timely feedback about the effectiveness of administered interventions enabling intervention strategies to be modified or changed if found to be ineffective. Moreover, some of the fundamental factors leading to falls and what actually happens during a fall remain unclear. Objectively documented and measured falls are needed to improve knowledge of fall in order to develop more effective prevention strategies and prolong independent living. In the last decade, several research groups have developed sensor-based automatic or semi-automatic fall risk assessment tools using wearable inertial sensors. This approach may also serve to detect falls. At the moment, i) several fall-risk assessment studies based on inertial sensors, even if promising, lack of a biomechanical model-based approach which could provide accurate and more detailed measurements of interests (e.g., joint moments, forces) and ii) the number of published real-world fall data of older people in a real-world environment is minimal since most authors have used simulations with healthy volunteers as a surrogate for real-world falls. With these limitations in mind, this thesis aims i) to suggest a novel method for the kinematics and dynamics evaluation of functional motor tasks, often used in clinics for the fall-risk evaluation, through a body sensor network and a biomechanical approach and ii) to define the guidelines for a fall detection algorithm based on a real-world fall database availability.