Fast detection of nonlinearity and nonstationarity in short and noisy time series

We introduce a statistical method to detect nonlinearity and nonstationarity in time series, that works even for short sequences and in presence of noise. The method has a discrimination power similar to that of the most advanced estimators on the market, yet it depends only on one parameter, is easier to implement and faster. Applications to real data sets reject the null hypothesis of an underlying stationary linear stochastic process with a higher confidence interval than the best known nonlinear discriminators up to date.Comment: 5 pages, 6 figure

A quartet in E : investigating collaborative learning and tutoring as knowledge creation processes

This paper is a short report of a continuing international study that is investigating networked collaborative learning among an advanced community of learners engaged in a master’s programme in e-learning. The study is undertaking empirical work using content analysis (CA), critical event recall (CER) and social network analysis (SNA). The first two methods are employed in the work reported in this paper. We are particularly interested in knowledge creation among the participants as they engage in action research for their master’s work. At the same time, another underlying aim of the main study is to develop methodology, enrich theory and explore the ways in which praxis (theory informed tutoring and learning on the programme) and theory interact as we try to understand the complex processes of tutoring and learning. The paper reports some of the current findings of this work and discusses future prospects

Lie groupoids and algebroids applied to the study of uniformity and homogeneity of material bodies

A Lie groupoid, called \textit{material Lie groupoid}, is associated in a natural way to any elastic material. The corresponding Lie algebroid, called \textit{material algebroid}, is used to characterize the uniformity and the homogeneity properties of the material. The relation to previous results in terms of $G-$structures is discussed in detail. An illustrative example is presented as an application of the theory

On the propagation of semiclassical Wigner functions

We establish the difference between the propagation of semiclassical Wigner functions and classical Liouville propagation. First we re-discuss the semiclassical limit for the propagator of Wigner functions, which on its own leads to their classical propagation. Then, via stationary phase evaluation of the full integral evolution equation, using the semiclassical expressions of Wigner functions, we provide the correct geometrical prescription for their semiclassical propagation. This is determined by the classical trajectories of the tips of the chords defined by the initial semiclassical Wigner function and centered on their arguments, in contrast to the Liouville propagation which is determined by the classical trajectories of the arguments themselves.Comment: 9 pages, 1 figure. To appear in J. Phys. A. This version matches the one set to print and differs from the previous one (07 Nov 2001) by the addition of two references, a few extra words of explanation and an augmented figure captio