In mobile and ambient environments, devices need to become autonomous, managing and resolving problems without interference from a user. The database of a (mobile) device can be seen as its knowledge about objects in the 'real world'. Data exchange between small and/or large computing devices can be used to supplement and update this knowledge whenever a connection gets established. In many situations, however, data from different data sources referring to the same real world objects, may conflict. It is the task of the data management system of the device to resolve such conflicts without interference from a user. In this paper, we take a first step in the development of a probabilistic XML DBMS. The main idea is to drop the assumption that data in the database should be certain: subtrees in XML documents may denote possible views on the real world. We formally define the notion of probabilistic XML tree and several operations thereon. We also present an approach for determining a logical semantics for queries on probabilistic XML data. Finally, we introduce an approach for XML data integration where conflicts are resolved by the introduction of possibilities in the database.

PPV, SPV, and SVV are the only reliable predictors of fluid responsiveness under strict conditions. In routine clinical practice, factors including low TV, cardiac arrhythmias, and the calculation method can substantially reduce their predictive value.

In patients receiving controlled mechanical ventilation after CABG, PPV and SPV can be measured reliably non-invasively using the inflatable finger cuff of the Nexfin™ monitor.

In data integration efforts, portal development in particular, much development time is devoted to entity resolution. Often advanced similarity measurement techniques are used to remove semantic duplicates or solve other semantic conflicts. It proves impossible, however, to automatically get rid of all semantic problems. An often-used rule of thumb states that about 90% of the development effort is devoted to semi-automatically resolving the remaining 10% hard cases. In an attempt to significantly decrease human effort at data integration time, we have proposed an approach that strives for a 'good enough' initial integration which stores any remaining semantic uncertainty and conflicts in a probabilistic database. The remaining cases are to be resolved with user feedback during query time. The main contribution of this paper is an experimental investigation of the effects and sensitivity of rule definition, threshold tuning, and user feedback on the integration quality. We claim that our approach indeed reduces development effort -and not merely shifts the effort -by showing that setting rough safe thresholds and defining only a few rules suffices to produce a 'good enough' initial integration that can be meaningfully used, and that user feedback is effective in gradually improving the integration quality. IntroductionData integration is a challenging problem in many application areas as it usually requires manual resolution of seman-

Feedback plays a central role in learning. Crucial to this is the nature and timing of the feedback. A number of studies have advocated for immediate feedback having the greater potential to influence learning outcomes. However, alternative studies have challenged this and highlighted that delayed feedback is perhaps preferable, especially when calling for more in-depth cognitive processing. This experimental study explores these two types within a Virtual Reality (VR) environment designed to facilitate the development of pre-university students' presentation skills.Participants were divided across two feedback conditions: immediate and delayed. Results showed that students in both groups made significant development in all presentation criteria across the two-week programme. Further, students perceived the environment to be an effective and motivating platform in which to practise their presentation skills. These findings are crucial as educators seek viable alternatives to provide for and enhance learning beyond the traditional confines of the classroom.