IVIE working-papers offer in advance the results of economic research under way in order to encourage a discussion process before sending them to scientific journals for their final publication. ___________________ • The authors wish to thank David B. Humphrey for his comments and suggestions, and Juan Fernández de Guevara for his help in preparing information. The paper is part of project SEC98-0895 of the CICYT.

SUMMARYOften inspection and maintenance work involve a large number of highly dangerous manual operations, especially within industrial fields such as shipbuilding and construction. This paper deals with the autonomous climbing robot which uses the "caterpillar" concept to climb in complex 3D metallic-based structures. During its motion the robot generates in real-time the path and grasp planning in order to ensure stable self-support to avoid the environment obstacles, and to optimise the robot consumption during the inspection. The control and monitoring of the robot is achieved through an advanced Graphical User Interface to allow an effective and user friendly operation of the robot. The experiments confirm its advantages in executing the inspection operations.

This paper introduces an architecture as a proof-of-concept for emotion detection and regulation in smart health environments. The aim of the proposal is to detect the patient's emotional state by analysing his/her physiological signals, facial expression and behaviour. Then, the system provides the best-tailored actions in the environment to regulate these emotions towards a positive mood when possible. The current state-of-the-art in emotion regulation through music and colour/light is implemented with the final goal of enhancing the quality of life and care of the subject. The paper describes the three main parts of the architecture, namely "Emotion Detection", "Emotion Regulation" and "Emotion Feedback Control". "Emotion Detection" works with the data captured from the patient, whereas "Emotion Regulation" offers him/her different musical pieces and colour/light settings. "Emotion Feedback Control" performs as a feedback control loop to assess the effect of emotion regulation over emotion detection. We are currently testing the overall architecture and the intervention in real environments to achieve our final goal.

Increased competition and the attempts of European banks to increase their presence in other markets may have affected the efficiency and credit risk in the banking system. The first aspect is the incentive in reducing costs in order to gain in competitiveness. The second is associated with their lack of knowledge of such markets and/ or acceptance of a higher risk in order to increase their market share. Despite the importance of these aspects, banking literature has usually analysed the effects of competition on the efficiency of banking systems without considering these aspects. The few studies that attempt to obtain risk adjusted efficiency measures do not consider that part of the risk is due to exogeneous circumstances. This article proposes a new three-stage sequential technique, based on the DEA model and on the decomposition of risk into its internal and external components, for obtaining efficiency measures adjusted for risk and environment. It is seen that the technique allows the use of any existing technique of incorporation of environmental variables in DEA analysis.

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This article introduces a new and unobtrusive wearable monitoring device based on electrodermal activity (EDA) to be used in health-related computing systems. This paper introduces the description of the wearable device capable of acquiring the EDA of a subject in order to detect his/her calm/distress condition from the acquired physiological signals. The lightweight wearable device is placed in the wrist of the subject to allow continuous physiological measurements. With the aim of validating the correct operation of the wearable EDA device, pictures from the International Affective Picture System are used in a control experiment involving fifty participants. The collected signals are processed, features are extracted and a statistical analysis is performed on the calm/distress condition classification. The results show that the wearable device solely based on EDA signal processing reports around 89% accuracy when distinguishing calm condition from distress condition.

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PCT has a high negative predictive value (94%) and lower PCT levels seems to be a good tool for excluding coinfection, particularly for patients without shock.