1,212 research outputs found
On the nature of the fast moving star S2 in the Galactic Center
We analyze the properties of the star S2 orbiting the supermassive black hole
at the center of the Galaxy. A high quality SINFONI H and K band spectrum
obtained from coadding 23.5 hours of observation between 2004 and 2007 reveals
that S2 is an early B dwarf (B0-2.5V). Using model atmospheres, we constrain
its stellar and wind properties. We show that S2 is a genuine massive star, and
not the core of a stripped giant star as sometimes speculated to resolve the
problem of star formation so close to the supermassive black hole. We give an
upper limit on its mass loss rate, and show that it is He enriched, possibly
because of the presence of a magnetic field.Comment: 4 pages, 5 figures, ApJ letters accepte
Spectroscopy of mechanical dissipation in micro-mechanical membranes
We measure the frequency dependence of the mechanical quality factor (Q) of
SiN membrane oscillators and observe a resonant variation of Q by more than two
orders of magnitude. The frequency of the fundamental mechanical mode is tuned
reversibly by up to 40% through local heating with a laser. Several distinct
resonances in Q are observed that can be explained by coupling to membrane
frame modes. Away from the resonances, the background Q is independent of
frequency and temperature in the measured range.Comment: 4 pages, 5 figure
Seizure characterisation using frequency-dependent multivariate dynamics
The characterisation of epileptic seizures assists in the design of targeted pharmaceutical seizure prevention techniques
and pre-surgical evaluations. In this paper, we expand on recent use of multivariate techniques to study the crosscorrelation
dynamics between electroencephalographic (EEG) channels. The Maximum Overlap Discrete Wavelet
Transform (MODWT) is applied in order to separate the EEG channels into their underlying frequencies. The
dynamics of the cross-correlation matrix between channels, at each frequency, are then analysed in terms of the
eigenspectrum. By examination of the eigenspectrum, we show that it is possible to identify frequency dependent
changes in the correlation structure between channels which may be indicative of seizure activity.
The technique is applied to EEG epileptiform data and the results indicate that the correlation dynamics vary over
time and frequency, with larger correlations between channels at high frequencies. Additionally, a redistribution of wavelet energy is found, with increased fractional energy demonstrating the relative importance of high frequencies
during seizures. Dynamical changes also occur in both correlation and energy at lower frequencies during seizures,
suggesting that monitoring frequency dependent correlation structure can characterise changes in EEG signals during
these. Future work will involve the study of other large eigenvalues and inter-frequency correlations to determine
additional seizure characteristics
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