15 research outputs found

    The Galaxy Content of SDSS Clusters and Groups

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    Imaging data from the Sloan Digital Sky Survey are used to characterize the population of galaxies in groups and clusters detected with the MaxBCG algorithm. We investigate the dependence of Brightest Cluster Galaxy (BCG) luminosity, and the distributions of satellite galaxy luminosity and satellite color, on cluster properties over the redshift range 0.1 < z < 0.3. The size of the dataset allows us to make measurements in many bins of cluster richness, radius and redshift. We find that, within r_200 of clusters with mass above 3e13 h-1 M_sun, the luminosity function of both red and blue satellites is only weakly dependent on richness. We further find that the shape of the satellite luminosity function does not depend on cluster-centric distance for magnitudes brighter than ^{0.25}M_i - 5log(h) < -19. However, the mix of faint red and blue galaxies changes dramatically. The satellite red fraction is dependent on cluster-centric distance, galaxy luminosity and cluster mass, and also increases by ~5% between redshifts 0.28 and 0.2, independent of richness. We find that BCG luminosity is tightly correlated with cluster richness, scaling as L_{BCG} ~ M_{200}^{0.3}, and has a Gaussian distribution at fixed richness, with sigma_{log L} ~ 0.17 for massive clusters. The ratios of BCG luminosity to total cluster luminosity and characteristic satellite luminosity scale strongly with cluster richness: in richer systems, BCGs contribute a smaller fraction of the total light, but are brighter compared to typical satellites. This study demonstrates the power of cross-correlation techniques for measuring galaxy populations in purely photometric data.Comment: 22 pages, 14 figures, submitted to Ap

    Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

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    Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries
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