Bose-Einstein correlations in WW events at LEP

The current status of the LEP results on Bose-Einstein correlations is discussed. Emphasis is given to the measurement of Bose-Einstein correlations between decay products from different W's, in an energy range between 172 and 209 GeV, dependent on the experiment. For the first time all four LEP experiments conclude that no evidence for correlations between pions from different W's is seen at the current level of precision.Comment: 6 pages, 4 figures, Talk given at XXXVI Rencontres de Moriond, Les Arcs, France, March 17-24 200

The emerging practice of food forest - a promise for a sustainable urban food system?

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Lecture notes on ridge regression

The linear regression model cannot be fitted to high-dimensional data, as the high-dimensionality brings about empirical non-identifiability. Penalized regression overcomes this non-identifiability by augmentation of the loss function by a penalty (i.e. a function of regression coefficients). The ridge penalty is the sum of squared regression coefficients, giving rise to ridge regression. Here many aspect of ridge regression are reviewed e.g. moments, mean squared error, its equivalence to constrained estimation, and its relation to Bayesian regression. Finally, its behaviour and use are illustrated in simulation and on omics data. Subsequently, ridge regression is generalized to allow for a more general penalty. The ridge penalization framework is then translated to logistic regression and its properties are shown to carry over. To contrast ridge penalized estimation, the final chapter introduces its lasso counterpart

Data degradation to enhance privacy for the Ambient Intelligence

Increasing research in ubiquitous computing techniques towards the development of an Ambient Intelligence raises issues regarding privacy. To gain the required data needed to enable application in this Ambient Intelligence to offer smart services to users, sensors will monitor users' behavior to fill personal context histories. Those context histories will be stored on database/information systems which we consider as honest: they can be trusted now, but might be subject to attacks in the future. Making this assumption implies that protecting context histories by means of access control might be not enough. To reduce the impact of possible attacks, we propose to use limited retention techniques. In our approach, we present applications a degraded set of data with a retention delay attached to it which matches both application requirements and users privacy wishes. Data degradation can be twofold: the accuracy of context data can be lowered such that the less privacy sensitive parts are retained, and context data can be transformed such that only particular abilities for application remain available. Retention periods can be specified to trigger irreversible removal of the context data from the system

Theoretical understanding of the nuclear incompressibility: where do we stand ?

The status of the theoretical research on the compressional modes of finite nuclei and the incompressibility $K_\infty$ of nuclear matter, is reviewed. It is argued that the recent experimental data on the Isoscalar Giant Monopole Resonance (ISGMR) allow extracting the value of $K_\infty$ with an uncertainity of about $\pm$ 12 MeV. Non-relativistic (Skyrme, Gogny) and relativistic mean field models predict for $K_\infty$ values which are significantly different from one another, namely $\approx$ 220-235 and $\approx$ 250-270 MeV respectively. It is shown that the solution of this puzzle requires a better determination of the symmetry energy at, and around, saturation. The role played by the experimental data of the Isoscalar Giant Dipole Resonance (ISGDR) is also discussed.Comment: To appear in the proceedings of the COMEX1 conference (special issue of Nucl. Phys. A). Few changes and corrections compared to the previous version. General conclusion unchange

Non-parametric indices of dependence between components for inhomogeneous multivariate random measures and marked sets

We propose new summary statistics to quantify the association between the components in coverage-reweighted moment stationary multivariate random sets and measures. They are defined in terms of the coverage-reweighted cumulant densities and extend classic functional statistics for stationary random closed sets. We study the relations between these statistics and evaluate them explicitly for a range of models. Unbiased estimators are given for all statistics and applied to simulated examples.Comment: Added examples in version

A damage-based temperature-dependent model for ductile fracture with finite strains and configurational forces

A temperature dependent model for ductile fractur

Support of the collaborative inquiry learning process: influence of support on task and team regulation

Regulation of the learning process is an important condition for efficient and effective learning. In collaborative learning, students have to regulate their collaborative activities (team regulation) next to the regulation of their own learning process focused on the task at hand (task regulation). In this study, we investigate how support of collaborative inquiry learning can influence the use of regulative activities of students. Furthermore, we explore the possible relations between task regulation, team regulation and learning results. This study involves tenth-grade students who worked in pairs in a collaborative inquiry learning environment that was based on a computer simulation, Collisions, developed in the program SimQuest. Students of the same team worked on two different computers and communicated through chat. Chat logs of students from three different conditions are compared. Students in the first condition did not receive any support at all (Control condition). In the second condition, students received an instruction in effective communication, the RIDE rules (RIDE condition). In the third condition, students were, in addition to receiving the RIDE rules instruction, supported by the Collaborative Hypothesis Tool (CHT), which helped the students with formulating hypotheses together (CHT condition). The results show that students overall used more team regulation than task regulation. In the RIDE condition and the CHT condition, students regulated their team activities most often. Moreover, in the CHT condition the regulation of team activities was positively related to the learning results. We can conclude that different measures of support can enhance the use of team regulative activities, which in turn can lead to better learning results

A spectral mean for point sampled closed curves

We propose a spectral mean for closed curves described by sample points on its boundary subject to mis-alignment and noise. First, we ignore mis-alignment and derive maximum likelihood estimators of the model and noise parameters in the Fourier domain. We estimate the unknown curve by back-transformation and derive the distribution of the integrated squared error. Then, we model mis-alignment by means of a shifted parametric diffeomorphism and minimise a suitable objective function simultaneously over the unknown curve and the mis-alignment parameters. Finally, the method is illustrated on simulated data as well as on photographs of Lake Tana taken by astronauts during a Shuttle mission