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The WARPS (Wide Angle ROSAT Pointed Survey) team reviews the properties and history of discovery of ClJ0152.7-1357, an X-ray luminous, rich cluster of galaxies at a redshift of z = 0.833. At L X = 8 × 10 44 h −2 50 erg s −1 (0.5 − 2.0 keV) ClJ0152.7-1357 is the most X-ray luminous cluster known at redshifts z > 0.55. The high X-ray luminosity of the system suggests that massive clusters may begin to form at redshifts considerably greater than unity. This scenario is supported by the high degree of optical and X-ray substructure in ClJ0152.7-1357, which is similarly complex as that of other X-ray selected clusters at comparable redshift and consistent with the hypothesized picture of cluster formation by mass infall along large-scale filaments.X-ray emission from ClJ0152.7-1357 was detected already in 1980 with the EINSTEIN IPC. However, because the complex morphology of the emission caused its significance to be underestimated, the corresponding source was not included in the cluster sample of the EINSTEIN Extended Medium Sensitivity Survey (EMSS) and hence not previously identified. Simulations of the EMSS source detection and selection procedure performed by us suggest a general, mild bias of the EMSS cluster sample against X-ray luminous clusters with pronounced substructure.If highly unrelaxed, merging clusters are common at intermediate to high redshift (as is suggested by the current data) they could create a bias in some samples as the morphological complexity of mergers may cause them to fall below the flux limit of surveys that make the implicit or explicit assumption of a unimodal spatial source geometry. Conversely, the enhanced X-ray luminosity of mergers might cause them to, temporarily, rise above the flux limit. Either effect could lead to erroneous conclusions about the evolution of the comoving cluster space density. A high fraction of morphologically complex clusters at high redshift would also call into question the validity of evolutionary studies (and, specifically, cosmological conclusions) which implicitly or explicitly assume that the systems under investigation are virialized.

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We present initial results from a wide‐field, multicolour imaging project, designed to study galaxy evolution in X‐ray‐selected clusters at intermediate (z∼0.25) and high redshifts (z∼0.5). We give blue galaxy fractions from eight X‐ray‐selected clusters, drawn from a combined sample of three X‐ray surveys. We find that all the clusters exhibit excess blue galaxy populations over the numbers observed in local systems, although a large scatter is present in the results. We find no significant correlation of blue fraction with redshift at z>0.2, although the large scatter could mask a positive trend. We also find no systematic trend of blue fraction with X‐ray luminosity. We show that the blue fraction is a function of (a) radius within a cluster, (b) absolute magnitude and (c) the passbands used to measure the colour. We find that our blue fractions (fb) from galaxy colours close to rest frame (U−B)0, fb∼0.4, are systematically higher than those from rest frame (B−V)0 colours, fb∼0.2. We conclude this effect is real, may offer a partial explanation of the widely differing levels of blue fraction found in previous studies, and may have implications for biases in optical samples selected in different bands. While the increasing blue fraction with radius can be interpreted as evidence of cluster infall of field galaxies, the exact physical processes which these galaxies undergo is unclear. We estimate that, in the cores of the more massive clusters, galaxies should be experiencing ram‐pressure stripping of galactic gas by the intracluster medium. The fact that our low X‐ray luminosity systems show a similar blue fraction as the high‐luminosity systems, as well as a significant blue fraction gradient with radius, implies other physical effects are also important.

Background Internet-based physical activity (PA) and weight management programs have the potential to improve employees’ health in large occupational health settings. To be successful, the program must engage a wide range of employees, especially those at risk of weight gain or ill health.Objective The aim of the study was to assess the use and nonuse (user attrition) of a Web-based and monitoring device–based PA and weight management program in a range of employees and to determine if engagement with the program was related to the employees’ baseline characteristics or measured outcomes.MethodsLongitudinal observational study of a cohort of employees having access to the MiLife Web-based automated behavior change system. Employees were recruited from manufacturing and office sites in the North West and the South of England. Baseline health data were collected, and participants were given devices to monitor their weight and PA via data upload to the website. Website use, PA, and weight data were collected throughout the 12-week program.Results Overall, 12% of employees at the four sites (265/2302) agreed to participate in the program, with 130 men (49%) and 135 women (51%), and of these, 233 went on to start the program. During the program, the dropout rate was 5% (11/233). Of the remaining 222 Web program users, 173 (78%) were using the program at the end of the 12 weeks, with 69% (153/222) continuing after this period. Engagement with the program varied by site but was not significantly different between the office and factory sites. During the first 2 weeks, participants used the website, on average, 6 times per week, suggesting an initial learning period after which the frequency of website log-in was typically 2 visits per week and 7 minutes per visit. Employees who uploaded weight data had a significant reduction in weight (−2.6 kg, SD 3.2, P< .001). The reduction in weight was largest for employees using the program’s weight loss mode (−3.4 kg, SD 3.5). Mean PA level recorded throughout the program was 173 minutes (SE 12.8) of moderate/high intensity PA per week. Website interaction time was higher and attrition rates were lower (OR 1.38, P= .03) in those individuals with the greatest weight loss.Conclusions This Web-based PA and weight management program showed high levels of engagement across a wide range of employees, including overweight or obese workers, shift workers, and those who do not work with computers. Weight loss was observed at both office and manufacturing sites. The use of monitoring devices to capture and send data to the automated Web-based coaching program may have influenced the high levels of engagement observed in this study. When combined with objective monitoring devices for PA and weight, both use of the website and outcomes can be tracked, allowing the online coaching program to become more personalized to the individual.