The Edges

My personal introduction to Debbie was through learning about writing: twenty years ago she stood in front of a diverse group of postgrads and read from work in progress. She lyrically described driving across the Alligator River Flood Plain in Kakadu National Park in the late afternoon with an Aboriginal man, who says a version of ‘Hey Debbie, if you look out the window to the east you’ll see a cool thing’. She looks out the window of the Toyota, and the dark edge of Burrungkuy – the Nourlangie Rock escarpment – is lit up with tiny glittering sparkles of light. The man laughingly explains that it is tourists’ camera flashes, as they photograph the sunset from one of the most famous Indigenous rock art galleries in the world

Extremely Low-light Image Enhancement with Scene Text Restoration

Deep learning-based methods have made impressive progress in enhancing extremely low-light images - the image quality of the reconstructed images has generally improved. However, we found out that most of these methods could not sufficiently recover the image details, for instance, the texts in the scene. In this paper, a novel image enhancement framework is proposed to precisely restore the scene texts, as well as the overall quality of the image simultaneously under extremely low-light images conditions. Mainly, we employed a self-regularised attention map, an edge map, and a novel text detection loss. In addition, leveraging synthetic low-light images is beneficial for image enhancement on the genuine ones in terms of text detection. The quantitative and qualitative experimental results have shown that the proposed model outperforms state-of-the-art methods in image restoration, text detection, and text spotting on See In the Dark and ICDAR15 datasets

Generalization of form in visual pattern classification.

Human observers were trained to criterion in classifying compound Gabor signals with sym- metry relationships, and were then tested with each of 18 blob-only versions of the learning set. General- ization to dark-only and light-only blob versions of the learning signals, as well as to dark-and-light blob versions was found to be excellent, thus implying virtually perfect generalization of the ability to classify mirror-image signals. The hypothesis that the learning signals are internally represented in terms of a 'blob code' with explicit labelling of contrast polarities was tested by predicting observed generalization behaviour in terms of various types of signal representations (pixelwise, Laplacian pyramid, curvature pyramid, ON/OFF, local maxima of Laplacian and curvature operators) and a minimum-distance rule. Most representations could explain generalization for dark-only and light-only blob patterns but not for the high-thresholded versions thereof. This led to the proposal of a structure-oriented blob-code. Whether such a code could be used in conjunction with simple classifiers or should be transformed into a propo- sitional scheme of representation operated upon by a rule-based classification process remains an open question

Null test for interactions in the dark sector

Since there is no known symmetry in Nature that prevents a non-minimal coupling between the dark energy (DE) and cold dark matter (CDM) components, such a possibility constitutes an alternative to standard cosmology, with its theoretical and observational consequences being of great interest. In this paper we propose a new null test on the standard evolution of the dark sector based on the time dependence of the ratio between the CDM and DE energy densities which, in the standard $\Lambda$CDM scenario, scales necessarily as $a^{-3}$. We use the latest measurements of type Ia supernovae, cosmic chronometers and angular baryonic acoustic oscillations to reconstruct the expansion history using model-independent Machine Learning techniques, namely, the Linear Model formalism and Gaussian Processes. We find that while the standard evolution is consistent with the data at $3\sigma$ level, some deviations from the $\Lambda$CDM model are found at low redshifts, which may be associated with the current tension between local and global determinations of $H_0$.Comment: 15 pages, 12 figure

Battle of the Blockbusters: Joss Whedon as Public Pedagogue

This article discusses the concept of public pedagogy and the reasons for considering it relevant to the work of the writer/ director/ producer Joss Whedon, creator of numberous TV programmes, such as Buffy the Vampire Slayer, Angel and Firefly, and Films Serenity, Marvel's The Avengers and The Age of Ultron. It analyzes Marvel’s The Avengers (Whedon, 2012) and Christopher Nolan’s (2012b) The Dark Knight Rises as competing public pedagogies.It suggests that popular films can be seen as important educational projects; filmmakers have tremendous resources at their disposal and their creations have a global reach that cannot be matched by individual teachers or national education systems. Whedon can be seen as a radical educator; he enables his audiences to experience ways of looking at the world that challenge aspects of neo-liberal hegemony, and also encourages them to become critical thinkers who have to reflect on their own feelings and perspectives and resist simplistic perspectives on morality and the difficult political choices facing global society

Identifying WIMP dark matter from particle and astroparticle data

One of the most promising strategies to identify the nature of dark matter consists in the search for new particles at accelerators and with so-called direct detection experiments. Working within the framework of simplified models, and making use of machine learning tools to speed up statistical inference, we address the question of what we can learn about dark matter from a detection at the LHC and a forthcoming direct detection experiment. We show that with a combination of accelerator and direct detection data, it is possible to identify newly discovered particles as dark matter, by reconstructing their relic density assuming they are weakly interacting massive particles (WIMPs) thermally produced in the early Universe, and demonstrating that it is consistent with the measured dark matter abundance. An inconsistency between these two quantities would instead point either towards additional physics in the dark sector, or towards a non-standard cosmology, with a thermal history substantially different from that of the standard cosmological model.Comment: 24 pages (+21 pages of appendices and references) and 14 figures. v2: Updated to match JCAP version; includes minor clarifications in text and updated reference

Beneficial effects of dark chocolate for episodic memory in healthy young adults: a parallel-groups acute intervention with a white chocolate control

There is good evidence that cocoa flavonoids can acutely improve cognitive function in humans, possibly via mechanisms such as increased cerebral blood flow. To date, much of the evidence is based on measures of executive function with extracts and cocoa-based interventions with a high flavonoid content. The aim of the present study was to explore whether benefits to episodic verbal memory and mood are observed two hours post consumption of a commercially available dark chocolate (DC) bar relative to a 35 g white chocolate bar (WC). Ninety-eight healthy young adults (n = 57 females) aged 18−24 years consumed either a 35 g DC bar or a calorie-matched low flavonoid WC bar. Verbal episodic memory and mood were assessed pre consumption and 2 h post consumption. An ANOVA analysis showed that the DC was associated with better verbal memory performance for several outcome measures of the Rey Auditory Verbal Learning Test relative to the WC, however, there were no effects on mood. These findings lend support to the notion that everyday available portions of dark chocolate can confer benefits to the brain in healthy consumers