Young people with diabetes and their peers

Type 1 Diabetes (T1D) is amongst the most common form of chronic illness affecting young people in the UK. Self- management is crucial, but managing their T1D is often difficult for young people

The KX method for producing K-band flux-limited samples of quasars

The longstanding question of the extent to which the quasar population is affected by dust extinction, within host galaxies or galaxies along the line of sight, remains open. More generally, the spectral energy distributions of quasars vary significantly and flux-limited samples defined at different wavelengths include different quasars. Surveys employing flux measurements at widely separated wavelengths are necessary to characterise fully the spectral properties of the quasar population. The availability of panoramic near-infrared detectors on large telescopes provides the opportunity to undertake surveys capable of establishing the importance of extinction by dust on the observed population of quasars. We introduce an efficient method for selecting K-band, flux-limited samples of quasars, termed ``KX'' by analogy with the UVX method. This method exploits the difference between the power-law nature of quasar spectra and the convex spectra of stars: quasars are relatively brighter than stars at both short wavelengths (the UVX method) and long wavelengths (the KX method). We consider the feasibility of undertaking a large-area KX survey for damped Ly-alpha galaxies and gravitational lenses using the planned UKIRT wide-field near-infrared camera.Comment: 6 pages, 3 figures, to appear in MNRA

A small area faint KX redshift survey for QSOs in the ESO Imaging Survey Chandra Deep Field South

In this paper we present preliminary spectroscopic results from a small area faint K-excess (KX) survey, and compare KX selection against UVX selection. The aim of the KX method is to produce complete samples of QSOs flux-limited in the K band, in order to minimize any selection bias in samples of QSOs from the effects of reddening and extinction. Using the photometric catalogue of the ESO Imaging Survey Chandra Deep Field South (48 arcmin^2) we have identified compact objects with J-K colours redder than the stellar sequence, that are brighter than K=19.5. We have obtained spectra of 33 candidates, using the LDSS++ spectrograph on the AAT. Amongst the 11 bluer candidates, with V-J<3, three are confirmed as QSOs. Identification of the 22 redder candidates with V-J>3 is substantially incomplete, but so far no reddened QSOs have been found. Near-infrared spectroscopy will be more effective in identifying some of these targets. Only two UVX (U-B<-0.2) sources brighter than K=19.5 are found which are not also KX selected. These are both identified as galactic stars. Thus KX selection appears to select all UVX QSOs. The surface density of QSOs in the blue subsample (V-J<3) at K<19.5 is 325^+316_-177 deg^-2. Because identification of the red subsample (V-J>3) is substantially incomplete, the 2sigma upper limit on the density of reddened QSO is large, <1150 deg^-2. As anticipated, at these faint magnitudes the KX sample includes several compact galaxies. Of the 14 with measured redshifts, there are roughly equal numbers of early and late type objects. Nearly all the early type galaxies are found in a single structure at z=0.66.Comment: 9 pages, 8 figures. Accepted for publication in MNRA

An Evaluation of the Excitation Class Parameter for the Central Stars of Planetary Nebulae

The three main methods currently in use for estimating the excitation class of planetary nebulae (PNe) central stars are compared and evaluated using 586 newly discovered and previously known PNe in the Large Magellanic Cloud (LMC). In order to achieve this we ran a series of evaluation tests using line ratios derived from de-reddened, flux calibrated spectra. Pronounced differences between the methods are exposed. Diagrams were created by comparing excitation classes with H-beta line fluxes. The best methods are then compared to published temperatures using the Zanstra method and assessed for their ability to reflect central star effective temperatures and evolution. As a result we call for a clarification of the term `excitation class' according to the different input parameters used. The first method, which we refer to as Exneb relies purely on the ratios of certain key emission lines. The second method, which we refer to as Ex* includes modeling to create a continuous variable and, for optically thick PNe in the Magellanic Clouds, is designed to relate more closely to intrinsic stellar parameters. The third method, we refer to as Ex [OIII]/H-beta since the [OIII]/H-beta ratio is used in isolation to other temperature diagnostics. Each of these methods is shown to have serious drawbacks when used as an indicator for central star temperature. Finally, we suggest a new method (Exrho) for estimating excitation class incorporating both the [OIII]/H-beta and the HeII4686 /H-beta ratios. Although any attempt to provide accurate central star temperatures using the excitation class derived from nebula lines will always be limited, we show that this new method provides a substantial improvement over previous methods with better agreement to temperatures derived through the Zanstra method.Comment: 14 pages, 18 figure. This peer reviewed paper has been accepted for publication in PAS

Learning and climate change

Learning – i.e. the acquisition of new information that leads to changes in our assessment of uncertainty – plays a prominent role in the international climate policy debate. For example, the view that we should postpone actions until we know more continues to be influential. The latest work on learning and climate change includes new theoretical models, better informed simulations of how learning affects the optimal timing of emissions reductions, analyses of how new information could affect the prospects for reaching and maintaining political agreements and for adapting to climate change, and explorations of how learning could lead us astray rather than closer to the truth. Despite the diversity of this new work, a clear consensus on a central point is that the prospect of learning does not support the postponement of emissions reductions today.Learning; Uncertainty; Climate change; Decision analysis