Spectropolarimetric investigation of the propagation of magnetoacoustic waves and shock formation in sunspot atmospheres

Velocity oscillations in sunspot umbrae have been measured simultaneously in two spectral lines: the photospheric Silicon I 10827 A line and the chromospheric Helium I 10830 A multiplet. From the full Stokes inversion of temporal series of spectropolarimetric observations we retrieved, among other parameters, the line of sight velocity temporal variations at photospheric and chromospheric heights. Chromospheric velocity oscillations show a three minute period with a clear sawtooth shape typical of propagating shock wave fronts. Photospheric velocity oscillations have basically a five minute period, although the power spectrum also shows a secondary peak in the three minute band which has proven to be predecessor for its chromospheric counterpart. The derived phase spectra yield a value of the atmospheric cut-off frequency around 4 mHz and give evidence for the upward propagation of higher frequency oscillation modes. The phase spectrum has been reproduced with a simple model of linear vertical propagation of slow magneto-acoustic waves in a stratified magnetized atmosphere that accounts for radiative losses through Newton's cooling law. The model explains the main features in the phase spectrum, and allows us to compute the theoretical time delay between the photospheric and chromospheric signals, which happens to have a strong dependence on frequency. We find a very good agreement between this and the time delay obtained directly from the cross-correlation of photospheric and chromospheric velocity maps filtered around the 6 mHz band. This allows us to infer that the 3-minute power observed at chromospheric heights comes directly from the photosphere by means of linear wave propagation, rather than from non-linear interaction of 5-minute (and/or higher frequency) modes.Comment: aastex preprint, 32 pages, 12 figure

A New Framework for Understanding Memories and Preference for Music

What can musical memories tell us about preference, and what can musical preferences tell us about memory? In this article we contrast the two perspectives using a dialogic conversation, drawing on insights brought into relief at the recent Music and Lifetime Memories conference. We use dialogue to present two different bodies of relevant background literature and theory and consider their overlaps, interactions, and contradictions in depth. We then compare our two different approaches to the same dataset – the Desert Island Discs archive – which provide complementary perspectives and insights. We interpret each other’s analyses from our own perspectives, and finally conclude with reflections on future directions for the field

Can high resolution 3D topographic surveys provide reliable grain size estimates in gravel bed rivers?

High resolution topographic surveys such as those provided by Structure-from-Motion (SfM) contain a wealth of information that is not always exploited in the generation of Digital Elevation Models (DEMs). In particular, several authors have related sub-metre scale topographic variability (or ‘surface roughness’) to sediment grain size by deriving empirical relationships between the two. In fluvial applications, such relationships permit rapid analysis of the spatial distribution of grain size over entire river reaches, providing improved data to drive three-dimensional hydraulic models, allowing rapid geomorphic monitoring of sub-reach river restoration projects, and enabling more robust characterisation of riverbed habitats. However, comparison of previously published roughness-grain-size relationships shows substantial variability between field sites. Using a combination of over 300 laboratory and field-based SfM surveys, we demonstrate the influence of inherent survey error, irregularity of natural gravels, particle shape, grain packing structure, sorting, and form roughness on roughness-grain-size relationships. Roughness analysis from SfM datasets can accurately predict the diameter of smooth hemispheres, though natural, irregular gravels result in a higher roughness value for a given diameter and different grain shapes yield different relationships. A suite of empirical relationships is presented as a decision tree which improves predictions of grain size. By accounting for differences in patch facies, large improvements in D50 prediction are possible. SfM is capable of providing accurate grain size estimates, although further refinement is needed for poorly sorted gravel patches, for which c-axis percentiles are better predicted than b-axis percentiles

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in Bone-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2) = 0.18, P value = 0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data