The WARPS survey: III. The discovery of an X-ray luminous galaxy cluster at z=0.833 and the impact of X-ray substructure on cluster abundance measurements

The WARPS team reviews the properties and history of discovery of ClJ0152.7-1357, an X-ray luminous, rich cluster of galaxies at z=0.833. At L_X = 8 x 10^44 h^(-2) erg/s (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 distant clusters and consistent with the 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 EMSS cluster sample and hence not previously identified. Simulations of the EMSS source detection and selection procedure suggest a general bias of the EMSS against X-ray luminous clusters with pronounced substructure. If highly unrelaxed, merging clusters are common at high redshift, 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 assume 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 cosmological studies that assume that the systems under investigation are virialized.Comment: 17 pages, 7 figures; revised to focus on possible detection biases caused by substructure in clusters; accepted for publication in ApJ; uses emulateapj.sty; eps files of figures 1 and 2 can be obtained from ftp://hubble.ifa.hawaii.edu/pub/ebeling/warp

A global synthesis reveals biodiversity-mediated benefits for crop production

Human land use threatens global biodiversity and compromises multiple ecosystem functions critical to food production. Whether crop yield-related ecosystem services can be maintained by a few dominant species or rely on high richness remains unclear. Using a global database from 89 studies (with 1475 locations), we partition the relative importance of species richness, abundance, and dominance for pollination; biological pest control; and final yields in the context of ongoing land-use change. Pollinator and enemy richness directly supported ecosystem services in addition to and independent of abundance and dominance. Up to 50% of the negative effects of landscape simplification on ecosystem services was due to richness losses of service-providing organisms, with negative consequences for crop yields. Maintaining the biodiversity of ecosystem service providers is therefore vital to sustain the flow of key agroecosystem benefits to society. [Abstract copyright: Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

Core components for effective infection prevention and control programmes: new WHO evidence-based recommendations

Abstract Health care-associated infections (HAI) are a major public health problem with a significant impact on morbidity, mortality and quality of life. They represent also an important economic burden to health systems worldwide. However, a large proportion of HAI are preventable through effective infection prevention and control (IPC) measures. Improvements in IPC at the national and facility level are critical for the successful containment of antimicrobial resistance and the prevention of HAI, including outbreaks of highly transmissible diseases through high quality care within the context of universal health coverage. Given the limited availability of IPC evidence-based guidance and standards, the World Health Organization (WHO) decided to prioritize the development of global recommendations on the core components of effective IPC programmes both at the national and acute health care facility level, based on systematic literature reviews and expert consensus. The aim of the guideline development process was to identify the evidence and evaluate its quality, consider patient values and preferences, resource implications, and the feasibility and acceptability of the recommendations. As a result, 11 recommendations and three good practice statements are presented here, including a summary of the supporting evidence, and form the substance of a new WHO IPC guideline

Comparison of Bayesian and frequentist approaches in modelling risk of preterm birth near the Sydney Tar Ponds, Nova Scotia, Canada

<p>Abstract</p> <p>Background</p> <p>This study compares the Bayesian and frequentist (non-Bayesian) approaches in the modelling of the association between the risk of preterm birth and maternal proximity to hazardous waste and pollution from the Sydney Tar Pond site in Nova Scotia, Canada.</p> <p>Methods</p> <p>The data includes 1604 observed cases of preterm birth out of a total population of 17559 at risk of preterm birth from 144 enumeration districts in the Cape Breton Regional Municipality. Other covariates include the distance from the Tar Pond; the rate of unemployment to population; the proportion of persons who are separated, divorced or widowed; the proportion of persons who have no high school diploma; the proportion of persons living alone; the proportion of single parent families and average income. Bayesian hierarchical Poisson regression, quasi-likelihood Poisson regression and weighted linear regression models were fitted to the data.</p> <p>Results</p> <p>The results of the analyses were compared together with their limitations.</p> <p>Conclusion</p> <p>The results of the weighted linear regression and the quasi-likelihood Poisson regression agrees with the result from the Bayesian hierarchical modelling which incorporates the spatial effects.</p

A review of the distribution of particulate trace elements in urban terrestrial environments and its application to considerations of risk

We review the evolution, state of the art and future lines of research on the sources, transport pathways, and sinks of particulate trace elements in urban terrestrial environments to include the atmosphere, soils, and street and indoor dusts. Such studies reveal reductions in the emissions of some elements of historical concern such as Pb, with interest consequently focusing on other toxic trace elements such as As, Cd, Hg, Zn, and Cu. While establishment of levels of these elements is important in assessing the potential impacts of human society on the urban environment, it is also necessary to apply this knowledge in conjunction with information on the toxicity of those trace elements and the degree of exposure of human receptors to an assessment of whether such contamination represents a real risk to the city’s inhabitants and therefore how this risk can be addressed

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed