Disentangling different types of El Ni\~no episodes by evolving climate network analysis

Complex network theory provides a powerful toolbox for studying the structure of statistical interrelationships between multiple time series in various scientific disciplines. In this work, we apply the recently proposed climate network approach for characterizing the evolving correlation structure of the Earth's climate system based on reanalysis data of surface air temperatures. We provide a detailed study on the temporal variability of several global climate network characteristics. Based on a simple conceptual view on red climate networks (i.e., networks with a comparably low number of edges), we give a thorough interpretation of our evolving climate network characteristics, which allows a functional discrimination between recently recognized different types of El Ni\~no episodes. Our analysis provides deep insights into the Earth's climate system, particularly its global response to strong volcanic eruptions and large-scale impacts of different phases of the El Ni\~no Southern Oscillation (ENSO).Comment: 20 pages, 12 figure

A time series feature of variability to detect two types of boredom from motion capture of the head and shoulders

Boredom and disengagement metrics are crucial to the correctly timed implementation of adaptive interventions in interactive systems. psychological research suggests that boredom (which other HCI teams have been able to partially quantify with pressure-sensing chair mats) is actually a composite: lethargy and restlessness. Here we present an innovative approach to the measurement and recognition of these two kinds of boredom, based on motion capture and video analysis of changes in head and shoulder positions. Discrete, three-minute, computer-presented stimuli (games, quizzes, films and music) covering a spectrum from engaging to boring/disengaging were used to elicit changes in cognitive/emotional states in seated, healthy volunteers. Interaction with the stimuli occurred with a handheld trackball instead of a mouse, so movements were assumed to be non-instrumental. Our results include a feature (standard deviation of windowed ranges) that may be more specific to boredom than mean speed of head movement, and that could be implemented in computer vision algorithms for disengagement detection

Thermonuclear burst oscillations

Burst oscillations, a phenomenon observed in a significant fraction of Type I (thermonuclear) X-ray bursts, involve the development of highly asymmetric brightness patches in the burning surface layers of accreting neutron stars. Intrinsically interesting as nuclear phenomena, they are also important as probes of dense matter physics and the strong gravity, high magnetic field environment of the neutron star surface. Burst oscillation frequency is also used to measure stellar spin, and doubles the sample of rapidly rotating (above 10 Hz) accreting neutron stars with known spins. Although the mechanism remains mysterious, burst oscillation models must take into account thermonuclear flame spread, nuclear processes, rapid rotation, and the dynamical role of the magnetic field. This review provides a comprehensive summary of the observational properties of burst oscillations, an assessment of the status of the theoretical models that are being developed to explain them, and an overview of how they can be used to constrain neutron star properties such as spin, mass and radius.Comment: Preprint of article submitted to Annual Reviews of Astronomy and Astrophysics (2012). 35 page