Solar Atmospheric Oscillations and the Chromospheric Magnetic Topology

We investigate the oscillatory properties of the quiet solar chromosphere in relation to the underlying photosphere, with particular regard to the effects of the magnetic topology. We perform a Fourier analysis on a sequence of line-of-sight velocities measured simultaneously in a photospheric (Fe I 709.0 nm) and a chromospheric line (Ca II 854.2 nm). The velocities were obtained from full spectroscopic data acquired at high spatial resolution with the Interferometric BIdimensional Spectrometer (IBIS). The field of view encompasses a full supergranular cell, allowing us to discriminate between areas with different magnetic characteristics. We show that waves with frequencies above the acoustic cut-off propagate from the photosphere to upper layers only in restricted areas of the quiet Sun. A large fraction of the quiet chromosphere is in fact occupied by ``magnetic shadows'', surrounding network regions, that we identify as originating from fibril-like structures observed in the core intensity of the Ca II line. We show that a large fraction of the chromospheric acoustic power at frequencies below the acoustic cut-off, residing in the proximity of the magnetic network elements, directly propagates from the underlying photosphere. This supports recent results arguing that network magnetic elements can channel low-frequency photospheric oscillations into the chromosphere, thus providing a way to input mechanical energy in the upper layers.Comment: 4 pages, 3 figure, A&A Letters in pres

Explanatory debugging: Supporting end-user debugging of machine-learned programs

Many machine-learning algorithms learn rules of behavior from individual end users, such as task-oriented desktop organizers and handwriting recognizers. These rules form a “program” that tells the computer what to do when future inputs arrive. Little research has explored how an end user can debug these programs when they make mistakes. We present our progress toward enabling end users to debug these learned programs via a Natural Programming methodology. We began with a formative study exploring how users reason about and correct a text-classification program. From the results, we derived and prototyped a concept based on “explanatory debugging”, then empirically evaluated it. Our results contribute methods for exposing a learned program's logic to end users and for eliciting user corrections to improve the program's predictions

Neural mechanisms of resistance to peer influence in early adolescence

During the shift from a parent-dependent child to a fully autonomous adult, peers take on a significant role in shaping the adolescent’s behaviour. Peer-derived influences are not always positive, however. Here we explore neural correlates of inter-individual differences in the probability of resisting peer influence in early adolescence. Using functional magnetic-resonance imaging (fMRI), we found striking differences between 10-year old children with high and low resistance to peer influence in their brain activity during observation of angry hand-movements and angry facial expressions: compared with subjects with low resistance to peer influence, individuals with high resistance showed a highly coordinated brain activity in neural systems underlying perception of action and decision making. These findings suggest that the probability of resisting peer influence depends on neural interactions during observation of emotion-laden actions

Critiquing Variational Theories of the Anderson-Hubbard Model: Real-Space Self-Consistent Hartree-Fock Solutions

A simple and commonly employed approximate technique with which one can examine spatially disordered systems when strong electronic correlations are present is based on the use of real-space unrestricted self-consistent Hartree-Fock wave functions. In such an approach the disorder is treated exactly while the correlations are treated approximately. In this report we critique the success of this approximation by making comparisons between such solutions and the exact wave functions for the Anderson-Hubbard model. Due to the sizes of the complete Hilbert spaces for these problems, the comparisons are restricted to small one-dimensional chains, up to ten sites, and a 4x4 two-dimensional cluster, and at 1/2 filling these Hilbert spaces contain about 63,500 and 166 million states, respectively. We have completed these calculations both at and away from 1/2 filling. This approximation is based on a variational approach which minimizes the Hartree-Fock energy, and we have completed comparisons of the exact and Hartree-Fock energies. However, in order to assess the success of this approximation in reproducing ground-state correlations we have completed comparisons of the local charge and spin correlations, including the calculation of the overlap of the Hartree-Fock wave functions with those of the exact solutions. We find that this approximation reproduces the local charge densities to quite a high accuracy, but that the local spin correlations, as represented by , are not as well represented. In addition to these comparisons, we discuss the properties of the spin degrees of freedom in the HF approximation, and where in the disorder-interaction phase diagram such physics may be important

End-user feature labeling: a locally-weighted regression approach

When intelligent interfaces, such as intelligent desktop assistants, email classifiers, and recommender systems, customize themselves to a particular end user, such customizations can decrease productivity and increase frustration due to inaccurate predictions - especially in early stages, when training data is limited. The end user can improve the learning algorithm by tediously labeling a substantial amount of additional training data, but this takes time and is too ad hoc to target a particular area of inaccuracy. To solve this problem, we propose a new learning algorithm based on locally weighted regression for feature labeling by end users, enabling them to point out which features are important for a class, rather than provide new training instances. In our user study, the first allowing ordinary end users to freely choose features to label directly from text documents, our algorithm was both more effective than others at leveraging end users' feature labels to improve the learning algorithm, and more robust to real users' noisy feature labels. These results strongly suggest that allowing users to freely choose features to label is a promising method for allowing end users to improve learning algorithms effectively

End-User Feature Labeling via Locally Weighted Logistic Regression

Applications that adapt to a particular end user often make inaccurate predictions during the early stages when training data is limited. Although an end user can improve the learning algorithm by labeling more training data, this process is time consuming and too ad hoc to target a particular area of inaccuracy. To solve this problem, we propose a new learning algorithm based on Locally Weighted Logistic Regression for feature labeling by end users, enabling them to point out which features are important for a class, rather than provide new training instances. In our user study, the first allowing ordinary end users to freely choose features to label directly from text documents, our algorithm was more effective than others at leveraging end users’ feature labels to improve the learning algorithm. Our results strongly suggest that allowing users to freely choose features to label is a promising method for allowing end users to improve learning algorithms effectively

Three-dimensional organization of basal bodies from wild-type and δ-tubulin deletion strains of Chlamydomonas reinhardtii

Improved methods of specimen preparation and dual-axis electron tomography have been used to study the structure and organization of basal bodies in the unicellular alga Chlamydomonas reinhardtii. Novel structures have been found in both wild type and strains with mutations that affect specific tubulin isoforms. Previous studies have shown that strains lacking δ-tubulin fail to assemble the C-tubule of the basal body. Tomographic reconstructions of basal bodies from the δ-tubulin deletion mutant uni3-1 have confirmed that basal bodies contain mostly doublet microtubules. Our methods now show that the stellate fibers, which are present only in the transition zone of wild-type cells, repeat within the core of uni3-1 basal bodies. The distal striated fiber is incomplete in this mutant, rootlet microtubules can be misplaced, and multiflagellate cells have been observed. A suppressor of uni3-1, designated tua2-6, contains a mutation in α-tubulin. tua2-6; uni3-1 cells build both flagella, yet they retain defects in basal body structure and in rootlet microtubule positioning. These data suggest that the presence of specific tubulin isoforms in Chlamydomonas directly affects the assembly and function of both basal bodies and basal body-associated structures

Azoniaspiro salts: towards bridging the gap between room-temperature ionic liquids and molten salts.

In a continued effort to improve the suitability of ionic liquids in applications operating at raised temperatures, novel spirocyclic 'azoniaspiro' salts (with cations derived from five-, six-, seven-and eight-membered rings) are prepared and characterised. The structural and thermal properties of these salts are compared against those of established analogues. The stable geometries and ion pairing behaviour of these species are investigated via a combined experimental/computational approach, employing X-ray crystallography and Density Functional Theory (DFT) methods. Subsequently, the thermal stabilities of these organic salts are characterised and compared using a broad range of techniques. Hyphenated Thermogravimetry-Mass Spectrometry investigations enable complex mechanisms underlying thermal decomposition to be elucidated. Lastly, transition state structures are optimised, corresponding to plausible decomposition mechanisms of the azoniaspiro salt, 6-azoniaspiro[6.5]dodecanium chloride, and one prototypical monocyclic species 1-butyl-1-methylpiperidinium chloride, using DFT. The observed improved thermal stabilities of the azoniaspiro salts, and their potential higher-temperature stable-liquid ranges, render them promising candidates for future ionic liquid applications

A Tale Of Two Spicules: The Impact of Spicules on the Magnetic Chromosphere

We use high-resolution observations of the Sun in Ca II H 3968 A from the Solar Optical Telescope on Hinode to show that there are at least two types of spicules that dominate the structure of the magnetic solar chromosphere. Both types are tied to the relentless magnetoconvective driving in the photosphere, but have very different dynamic properties. ``Type-I'' spicules are driven by shock waves that form when global oscillations and convective flows leak into the upper atmosphere along magnetic field lines on 3-7 minute timescales. ``Type-II'' spicules are much more dynamic: they form rapidly (in ~10s), are very thin (<200km wide), have lifetimes of 10-150s (at any one height) and seem to be rapidly heated to (at least) transition region temperatures, sending material through the chromosphere at speeds of order 50-150 km/s. The properties of Type II spicules suggest a formation process that is a consequence of magnetic reconnection, typically in the vicinity of magnetic flux concentrations in plage and network. Both types of spicules are observed to carry Alfven waves with significant amplitudes of order 20 km/s.Comment: 8 pages, 5 figures, accepted for Hinode special issue of PAS