Progress at JET in integrating ITER-relevant core and edge plasmas within the constraints of an ITER-like wall

This paper reports the progress made at JET-ILW on integrating the requirements of the reference ITER baseline scenario with normalized confinement factor of 1, at a normalized pressure of 1.8 together with partially detached divertor whilst maintaining these conditions over many energy confinement times. The 2.5 MA high triangularity ELMy H-modes are studied with two different divertor configurations with D-gas injection and nitrogen seeding. The power load reduction with N seeding is reported. The relationship between an increase in energy confinement and pedestal pressure with triangularity is investigated. The operational space of both plasma configurations is studied together with the ELM energy losses and stability of the pedestal of unseeded and seeded plasmas. The achievement of stationary plasma conditions over many energy confinement times is also reported.

The Shakespearean Auteur and the Televisual Medium

In the wake offundamental shifts in television, programming and production have seen television creations which rival—even go beyond—standard cinema in scope, length and character development. This essay takes the distinctive approach of applying auteur theory to the small screen, exploring what understandings of the auteur might mean for a new era of television Shakespeare, and, as its case-study, considers the BBC’s Hollow Crown series. Characterized by a feature-film appearance, a multimillion pound budget, and an all-star cast, the series is exemplary of how television is now made; hence, the essay argues, the series needs to be investigated in relation to the most recent understandings of the medium. Central to this investigation is the way in which producer Sam Mendes’s vision imprintsitself upon each of the series’s four episodes, and the first part of the essay is accordingly concerned with his recognizable style and credentials as the series “showrunner.” However, Mendes’s is not the only auteurial stamp on the series, and the essay is equally concerned with how each of Mendes’s three co-directors places his or her auteurial signature on the Shakespearean source material in such a way as to lend each production a unique character. These individualized creative visions, the essay argues, unfold in concert with Mendes’s conceptualization of the series in its entirety. Ultimately, televisual auteurism is understood as a complex phenomenon that allows for more than one creative approach to be entertained.

Machine learning for transient discovery in Pan-STARRS1 difference imaging

Efficient identification and follow-up of astronomical transients is hindered by the need for humans to manually select promising candidates from data streams that contain many false positives. These artefacts arise in the difference images that are produced by most major ground-based time-domain surveys with large format CCD cameras. This dependence on humans to reject bogus detections is unsustainable for next generation all-sky surveys and significant effort is now being invested to solve the problem computationally. In this paper, we explore a simple machine learning approach to real-bogus classification by constructing a training set from the image data of similar to 32 000 real astrophysical transients and bogus detections from the Pan-STARRS1 Medium Deep Survey. We derive our feature representation from the pixel intensity values of a 20 x 20 pixel stamp around the centre of the candidates. This differs from previous work in that it works directly on the pixels rather than catalogued domain knowledge for feature design or selection. Three machine learning algorithms are trained (artificial neural networks, support vector machines and random forests) and their performances are tested on a held-out subset of 25 per cent of the training data. We find the best results from the random forest classifier and demonstrate that by accepting a false positive rate of 1 per cent, the classifier initially suggests a missed detection rate of around 10 per cent. However, we also find that a combination of bright star variability, nuclear transients and uncertainty in human labelling means that our best estimate of the missed detection rate is approximately 6 per cent.