Screening strategies in surveillance and control of methicillin-resistant Staphylococcus aureus (MRSA)

With reports of hospital-acquired methicillin-resistant Staphylococcus aureus (MRSA) continuing to increase and therapeutic options decrease, infection control methods are of increasing importance. Here we investigate the relationship between surveillance and infection control. Surveillance plays two roles with respect to control: it allows detection of infected/colonized individuals necessary for their removal from the general population, and it allows quantification of control success. We develop a stochastic model of MRSA transmission dynamics exploring the effects of two screening strategies in an epidemic setting: random and on admission. We consider both hospital and community populations and include control and surveillance in a single framework. Random screening was more efficient at hospital surveillance and allowed nosocomial control, which also prevented epidemic behaviour in the community. Therefore, random screening was the more effective control strategy for both the hospital and community populations in this setting. Surveillance strategies have significant impact on both ascertainment of infection prevalence and its control

Measuring the growth rate of structure with Type IA Supernovae from LSST

We investigate measuring the peculiar motions of galaxies up to $z=0.5$ using Type Ia supernovae (SNe Ia) from LSST, and predict the subsequent constraints on the growth rate of structure. We consider two cases. Our first is based on measurements of the volumetric SNe Ia rate and assumes we can obtain spectroscopic redshifts and light curves for varying fractions of objects that are detected pre-peak luminosity by LSST (some of which may be obtained by LSST itself and others which would require additional follow-up). We find that these measurements could produce growth rate constraints at $z<0.5$ that significantly outperform those using Redshift Space Distortions (RSD) with DESI or 4MOST, even though there are $\sim4\times$ fewer objects. For our second case, we use semi-analytic simulations and a prescription for the SNe Ia rate as a function of stellar mass and star formation rate to predict the number of LSST SNe IA whose host redshifts may already have been obtained with the Taipan+WALLABY surveys, or with a future multi-object spectroscopic survey. We find $\sim 18,000$ and $\sim 160,000$ SN Ia with host redshifts for these cases respectively. Whilst this is only a fraction of the total LSST-detected SNe Ia, they could be used to significantly augment and improve the growth rate constraints compared to only RSD. Ultimately, we find that combining LSST SNe Ia with large numbers of galaxy redshifts will provide the most powerful probe of large scale gravity in the $z<0.5$ regime over the coming decades.Comment: 12 pages, 1 table, 5 figures. Accepted for publication in ApJ. The Fisher matrix forecast code used in this paper can be found at: https://github.com/CullanHowlett/PV_fisher. Updated to fix error in Eq. 1 (thanks to Eric Linder for pointing this out

ProFit : Bayesian profile fitting of galaxy images

We present ProFit, a new code for Bayesian two-dimensional photometric galaxy profile modelling. ProFit consists of a low-level c++ library (libprofit), accessible via a command-line interface and documented API, along with high-level R (ProFit) and Python (PyProFit) interfaces (available at github.com/ICRAR/libprofit, github.com/ICRAR/ProFit, and github.com/ICRAR/pyprofit, respectively). R ProFit is also available pre-built from cran; however, this version will be slightly behind the latest GitHub version. libprofit offers fast and accurate two-dimensional integration for a useful number of profiles, including Sérsic, Core-Sérsic, broken-exponential, Ferrer, Moffat, empirical King, point-source, and sky, with a simple mechanism for adding new profiles. We show detailed comparisons between libprofit and galfit. libprofit is both faster and more accurate than galfit at integrating the ubiquitous Sérsic profile for the most common values of the Sérsic index n (0.5 < n < 8). The high-level fitting code ProFit is tested on a sample of galaxies with both SDSS and deeper KiDS imaging. We find good agreement in the fit parameters, with larger scatter in best-fitting parameters from fitting images from different sources (SDSS versus KiDS) than from using different codes (ProFit versus galfit). A large suite of Monte Carlo-simulated images are used to assess prospects for automated bulge-disc decomposition with ProFit on SDSS, KiDS, and future LSST imaging. We find that the biggest increases in fit quality come from moving from SDSS- to KiDS-quality data, with less significant gains moving from KiDS to LSST.Publisher PDFPeer reviewe

ProFound : source extraction and application to modern survey data

Parts of this research were conducted by the Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO), through project number CE110001020.We introduce ProFound, a source finding and image analysis package. ProFound provides methods to detect sources in noisy images, generate segmentation maps identifying the pixels belonging to each source, and measure statistics like flux, size and ellipticity. These inputs are key requirements of ProFit, our recently released galaxy profiling package, where the design aim is that these two software packages will be used in unison to semi-automatically profile large samples of galaxies. The key novel feature introduced in ProFound is that all photometry is executed on dilated segmentation maps that fully contain the identifiable flux, rather than using more traditional circular or ellipse based photometry. Also, to be less sensitive to pathological segmentation issues, the de-blending is made across saddle points in flux. We apply ProFound in a number of simulated and real world cases, and demonstrate that it behaves reasonably given its stated design goals. In particular, it offers good initial parameter estimation for ProFit, and also segmentation maps that follow the sometimes complex geometry of resolved sources, whilst capturing nearly all of the flux. A number of bulge-disc decomposition projects are already making use of the ProFound and ProFit pipeline, and adoption is being encouraged by publicly releasing the software for the open source R data analysis platform under an LGPL-3 license on GitHub (github.com/asgr/ProFound).PostprintPeer reviewe

Peer mentorship and positive effects on student mentor and mentee retention and academic success

This study examined how the introduction of peer mentorship in an undergraduate health and social welfare programme at a large northern university affected student learning. Using an ethnographic case study approach, the study draws upon data collected from a small group of mentors and their mentees over a period of one academic year using interviews, reflective journals, assessment and course evaluation data. Analysis of the data collected identified a number of key findings: peer mentorship improves assessment performance for both mentee and mentor; reduces stress and anxiety, enhances participation and engagement in the academic community, and adds value to student outcomes

Galaxy And Mass Assembly (GAMA): trends in galaxy colours, morphology, and stellar populations with large-scale structure, group, and pair environments

We explore trends in galaxy properties with Mpc-scale structures using catalogues of environment and large scale structure from the Galaxy And Mass Assembly (GAMA) survey. Existing GAMA catalogues of large scale structure, group and pair membership allow us to construct galaxy stellar mass functions for different environmental types. To avoid simply extracting the known underlying correlations between galaxy properties and stellar mass, we create a mass matched sample of galaxies with stellar masses between 9.5≤logM∗/h−2M⊙≤11 for each environmental population. Using these samples, we show that mass normalised galaxies in different large scale environments have similar energy outputs, u−r colours, luminosities, and morphologies. Extending our analysis to group and pair environments, we show galaxies that are not in groups or pairs exhibit similar characteristics to each other regardless of broader environment. For our mass controlled sample, we fail to see a strong dependence of S\'{e}rsic index or galaxy luminosity on halo mass, but do find that it correlates very strongly with colour. Repeating our analysis for galaxies that have not been mass controlled introduces and amplifies trends in the properties of galaxies in pairs, groups, and large scale structure, indicating that stellar mass is the most important predictor of the galaxy properties we examine, as opposed to environmental classifications

Galaxy And Mass Assembly (GAMA): a deeper view of the mass, metallicity and SFR relationships

A full appreciation of the role played by gas metallicity (Z), star formation rate (SFR) and stellar mass (M*) is fundamental to understanding how galaxies form and evolve. The connections between these three parameters at different redshifts significantly affect galaxy evolution, and thus provide important constraints for galaxy evolution models. Using data from the Sloan Digital Sky Survey–Data Release 7 (SDSS–DR7) and the Galaxy and Mass Assembly (GAMA) surveys, we study the relationships and dependences between SFR, Z and M*, as well as the Fundamental Plane for star-forming galaxies. We combine both surveys using volume-limited samples up to a redshift of z ≈ 0.36. The GAMA and SDSS surveys complement each other when analysing the relationships between SFR, M* and Z. We present evidence for SFR and metallicity evolution to z ∼ 0.2. We study the dependences between SFR, M*, Z and specific SFR (SSFR) on the M*–Z, M*–SFR, M*–SSFR, Z–SFR and Z–SSFR relations, finding strong correlations between all. Based on those dependences, we propose a simple model that allows us to explain the different behaviour observed between low- and high-mass galaxies. Finally, our analysis allows us to confirm the existence of a Fundamental Plane, for which M* = f(Z, SFR) in star-forming galaxies

Galaxy And Mass Assembly (GAMA) blended spectra catalogue: strong galaxy-galaxy lens and occulting galaxy pair candidates

We present the catalogue of blended galaxy spectra from the Galaxy And Mass Assembly (GAMA) survey. These are cases where light from two galaxies are significantly detected in a single GAMA fibre. Galaxy pairs identified from their blended spectrum fall into two principal classes: they are either strong lenses, a passive galaxy lensing an emission-line galaxy; or occulting galaxies, serendipitous overlaps of two galaxies, of any type. Blended spectra can thus be used to reliably identify strong lenses for follow-up observations (high-resolution imaging) and occulting pairs, especially those that are a late-type partly obscuring an early-type galaxy which are of interest for the study of dust content of spiral and irregular galaxies. The GAMA survey setup and its AUTOZ automated redshift determination were used to identify candidate blended galaxy spectra from the cross-correlation peaks. We identify 280 blended spectra with a minimum velocity separation of 600 km s−1, of which 104 are lens pair candidates, 71 emission-line-passive pairs, 78 are pairs of emission-line galaxies and 27 are pairs of galaxies with passive spectra. We have visually inspected the candidates in the Sloan Digital Sky Survey (SDSS) and Kilo Degree Survey (KiDS) images. Many blended objects are ellipticals with blue fuzz (Ef in our classification). These latter ‘Ef’ classifications are candidates for possible strong lenses, massive ellipticals with an emission-line galaxy in one or more lensed images. The GAMA lens and occulting galaxy candidate samples are similar in size to those identified in the entire SDSS. This blended spectrum sample stands as a testament of the power of this highly complete, second-largest spectroscopic survey in existence and offers the possibility to expand e.g. strong gravitational lens surveys

Discipline-Specific Compared to Generic Training of Teachers in Higher Education

A recurrent theme arising in the higher education sector is the suitability and effectiveness of generic versus discipline-specific training of university teachers, who are often recruited based on their disciplinary specialties to become teachers in higher education. We compared two groups of participants who had undergone training using a generic post-graduate certificate in higher education (PGCertGeneric) versus a discipline-specific course in veterinary education (PGCertVetEd). The study was conducted using a survey that allowed comparison of participants who completed PGCertGeneric (n=21) with PGCertVetEd (n=22). Results indicated that participants from both PGCertGeneric and PGCertVetEd considered teaching to be satisfying and important to their careers, valued the teaching observation component of the course, and identified similar training needs. However, the participants of the PGCertVetEd felt that the course made them better teachers, valued the relevance of the components taught, understood course design better, were encouraged to do further courses/reading in teaching and learning, changed their teaching as a result of the course, and were less stressed about teaching as compared to the PGCertGeneric participants (p<.05). It is likely that the PGCertVetEd, which was designed and developed by veterinarians with a wider understanding of the veterinary sector, helped the participants perceive the training course as suited to their needs