Resolved Imaging of the HD191089 Debris Disc

Two thirds of the F star members of the 12 Myr old Beta Pictoris Moving Group (BPMG) show significant excess emission in the mid-infrared, several million years after the expected dispersal of the protoplanetary disc. Theoretical models of planet formation suggest that this peak in the mid-infrared emission could be due to the formation of Pluto-sized bodies in the disc, which ignite the collisional cascade and enhance the production of small dust. Here we present resolved mid-infrared imaging of the disc of HD191089 (F5V in the BPMG) and consider its implications for the state of planet formation in this system. HD191089 was observed at 18.3 microns using T-ReCS on Gemini South and the images were compared to models of the disc to constrain the radial distribution of the dust. The emission observed at 18.3 microns is shown to be significantly extended beyond the PSF at a position angle of 80 degrees. This is the first time dust emission has been resolved around HD191089. Modelling indicates that the emission arises from a dust belt from 28-90 AU, inclined at 35 degrees from edge on with very little emission from the inner 28AU of the disc, indicating the presence of an inner cavity. The steep slope of the inner edge is more consistent with truncation by a planet than with ongoing stirring. A tentative brightness asymmetry F(W)/F(E)=0.80+/-0.12 (1.8 sigma) between the two sides of the disc could be evidence for perturbations from a massive body on an eccentric orbit in the system.Comment: 11 Pages Accepted to MNRA

Authorship Attribution Using a Neural Network Language Model

In practice, training language models for individual authors is often expensive because of limited data resources. In such cases, Neural Network Language Models (NNLMs), generally outperform the traditional non-parametric N-gram models. Here we investigate the performance of a feed-forward NNLM on an authorship attribution problem, with moderate author set size and relatively limited data. We also consider how the text topics impact performance. Compared with a well-constructed N-gram baseline method with Kneser-Ney smoothing, the proposed method achieves nearly 2:5% reduction in perplexity and increases author classification accuracy by 3:43% on average, given as few as 5 test sentences. The performance is very competitive with the state of the art in terms of accuracy and demand on test data. The source code, preprocessed datasets, a detailed description of the methodology and results are available at https://github.com/zge/authorship-attribution.Comment: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16

Job quality in Europe

Promoting job quality and gender equality are objectives of the European Employment Strategy (EES) in spite of a downgrading of the attention given to both in the revised employment guidelines and the re-launch of the Lisbon Process. However, advances on both of these objectives may be important complements to the employment rate targets of the EES, as access to good quality jobs for both sexes is likely to help sustain higher employment rates. While the European Commission has a broad view of the concept of job quality in practice, it relies on a selection of labour market type indicators that say little about the quality of the actual jobs people do. Using data from the 2005 European Working Conditions survey, we analyse job quality along three dimensions: job content, autonomy and working conditions. We conclude that gender and occupational status, along with other job characteristics such as working time and sector, have more influence on an individual’s job quality than the country or ‘national model’ they are situated in. Our results also demonstrate the value of developing indicators of job quality that are both gender sensitive and derived at the level of the job rather than the labour market in order to advance EU policy and academic debate on this topic

Effect of plyometric training on swimming block start performance in adolescents

This study aimed to identify the effect of plyometric training (PT), when added to habitual training (HT) regimes, on swim start performance. After the completion of a baseline competitive swim start, 22 adolescent swimmers were randomly assigned to either a PT (n = 11, age: 13.1 ± 1.4 yr, mass: 50.6 ± 12.3 kg, stature: 162.9 ± 11.9 cm) or an HT group (n = 11, age: 12.6 ± 1.9 yr, mass: 43.3 ± 11.6 kg, stature: 157.6 ± 11.9 cm). Over an 8-week preseason period, the HT group continued with their normal training program, whereas the PT group added 2 additional 1-hour plyometric-specific sessions, incorporating prescribed exercises relating to the swimming block start (SBS). After completion of the training intervention, post-training swim start performance was reassessed. For both baseline and post-trials, swim performance was recorded using videography (50Hz Canon MVX460) in the sagital plane of motion. Through the use of Silicon Coach Pro analysis package, data revealed significantly greater change between baseline and post-trials for PT when compared with the HT group for swim performance time to 5.5 m (−0.59 s vs. −0.21 s; p < 0.01) and velocity of take-off to contact (0.19 ms−1 vs. −0.07 ms−1; p < 0.01). Considering the practical importance of a successful swim start to overall performance outcome, the current study has found that inclusion of suitable and safely implemented PT to adolescent performers, in addition to HT routines, can have a positive impact on swim start performance

Breast cancer detection using microwave holography

Breast cancer is one of the most common forms of cancer in women. X-ray mammography is the most widely used technique for early detection but has limitations. In this paper, an alternative approach for breast cancer detection using microwave imaging is presented. This is based upon microwave indirect holographic approach, central to which is the use of a synthetic reference beam. This approach has benefits in terms of simplicity and expense. Experimental results using a simple breast phantom are included to demonstrate the potential of this approach

Using molecular mechanics to predict bulk material properties of fibronectin fibers

The structural proteins of the extracellular matrix (ECM) form fibers with finely tuned mechanical properties matched to the time scales of cell traction forces. Several proteins such as fibronectin (Fn) and fibrin undergo molecular conformational changes that extend the proteins and are believed to be a major contributor to the extensibility of bulk fibers. The dynamics of these conformational changes have been thoroughly explored since the advent of single molecule force spectroscopy and molecular dynamics simulations but remarkably, these data have not been rigorously applied to the understanding of the time dependent mechanics of bulk ECM fibers. Using measurements of protein density within fibers, we have examined the influence of dynamic molecular conformational changes and the intermolecular arrangement of Fn within fibers on the bulk mechanical properties of Fn fibers. Fibers were simulated as molecular strands with architectures that promote either equal or disparate molecular loading under conditions of constant extension rate. Measurements of protein concentration within micron scale fibers using deep ultraviolet transmission microscopy allowed the simulations to be scaled appropriately for comparison to in vitro measurements of fiber mechanics as well as providing estimates of fiber porosity and water content, suggesting Fn fibers are approximately 75% solute. Comparing the properties predicted by single molecule measurements to in vitro measurements of Fn fibers showed that domain unfolding is sufficient to predict the high extensibility and nonlinear stiffness of Fn fibers with surprising accuracy, with disparately loaded fibers providing the best fit to experiment. This work shows the promise of this microstructural modeling approach for understanding Fn fiber properties, which is generally applicable to other ECM fibers, and could be further expanded to tissue scale by incorporating these simulated fibers into three dimensional network models