The Maximum Flux of Star-Forming Galaxies

The importance of radiation pressure feedback in galaxy formation has been extensively debated over the last decade. The regime of greatest uncertainty is in the most actively star-forming galaxies, where large dust columns can potentially produce a dust-reprocessed infrared radiation field with enough pressure to drive turbulence or eject material. Here we derive the conditions under which a self-gravitating, mixed gas-star disc can remain hydrostatic despite trapped radiation pressure. Consistently taking into account the self-gravity of the medium, the star- and dust-to-gas ratios, and the effects of turbulent motions not driven by radiation, we show that galaxies can achieve a maximum Eddington-limited star formation rate per unit area $\dot{\Sigma}_{\rm *,crit} \sim 10^3 M_{\odot}$ pc$^{-2}$ Myr$^{-1}$, corresponding to a critical flux of $F_{\rm *,crit} \sim 10^{13} L_{\odot}$ kpc$^{-2}$ similar to previous estimates; higher fluxes eject mass in bulk, halting further star formation. Conversely, we show that in galaxies below this limit, our one-dimensional models imply simple vertical hydrostatic equilibrium and that radiation pressure is ineffective at driving turbulence or ejecting matter. Because the vast majority of star-forming galaxies lie below the maximum limit for typical dust-to-gas ratios, we conclude that infrared radiation pressure is likely unimportant for all but the most extreme systems on galaxy-wide scales. Thus, while radiation pressure does not explain the Kennicutt-Schmidt relation, it does impose an upper truncation on it. Our predicted truncation is in good agreement with the highest observed gas and star formation rate surface densities found both locally and at high redshift.Comment: Version accepted for publication in MNRAS. 12 pages, 8 figures. New appendix on photon tirin

POCUS: mining genomic sequence annotation to predict disease genes

Here we present POCUS (prioritization of candidate genes using statistics), a novel computational approach to prioritize candidate disease genes that is based on over-representation of functional annotation between loci for the same disease. We show that POCUS can provide high (up to 81-fold) enrichment of real disease genes in the candidate-gene shortlists it produces compared with the original large sets of positional candidates. In contrast to existing methods, POCUS can also suggest counterintuitive candidates

Eyes on the bog. Long-term monitoring network for UK peatlands

Eyes on the Bog provides a scientifically robust, repeatable, low tech, long-term monitoring initiative. The standardised methodology enables individual peatland sites to be consistently monitored across the UK, creating a network of comparable sites. The initiative employs cheap, simple techniques and modern technology to enable useful monitoring information to be collected by peatland community employees or volunteers on: Peat subsidence and carbon loss Carbon capture Water table behaviour Peat soil condition Vegetation status, structure and composition Historical context of change and current trajectorie

Evidence for view-invariant Face Recognition Units in unfamiliar face learning

Many models of face recognition incorporate the idea of a face recognition unit (FRU). This is an abstracted representation formed from each experience of a face. Longmore et al. (2008) devised a face learning experiment to investigate such a construct (i.e., view-invariance) but failed to find evidence of its existence. Three experiments developed Longmore et al.’s study further by using a different learning task, by employing more stimuli. One or two views of previously unfamiliar faces were shown to participants in a serial matching task (learning). Later, participants attempted to recognise both seen and novel views of the learned faces. Experiment one tested participants’ recognition of a novel view, a day after learning. Experiment two was identical, but tested participants on the same day as learning. And experiment three repeated experiment one, but tested participants on a novel view that was outside the rotation of those views learned. Results revealed a significant advantage for recognising a novel view when two views had been learned, rather than a single learned view – for all experiments. The effect of view-invariance found when both views were learned is discussed

Raising the Standard of AI Products

We propose a mechanism for the promotion of high-standards in commercial Artificial Intelligence products, namely an association of companies which would regulate their own membership using a code of practice and the precedents set by previous cases. Membership would provide some assurance of quality. We argue the benefits of such a mechanism, and discuss some of the details including the proposal of a code of practice. This paper is intended as a vehicle for discussion rather than as the presentation of a definitive solution