Is there evidence of shifting baseline syndrome in environmental managers? An assessment using perceptions of bird population targets in UK nature reserves

Shifting baseline syndrome (SBS) describes changing perceptions of biological conditions due to a loss of historical knowledge. Perceptions of ‘normal’ environmental conditions are continually updated, leading to underestimation of the true magnitude of long-term ecological change and potential setting of unambitious management targets. There has been speculation as to the presence and impacts of SBS within conservation management since Daniel Pauly's seminal paper in 1995, which outlined the potential effects of SBS on target-setting in fisheries management. Previous case studies have suggested that SBS may not occur in management, despite empirical evidence of SBS in other systems. In this study, 44 professionals and volunteers involved in bird species management, monitoring and target-setting across England were interviewed. Interviews asked for personal perceptions of current, maximum and target abundance, long-term trends, and perceived conservation priority for six bird species. Using paired tests, this study found no significant effect of experience on perceptions of current, maximum or target abundance of all species, despite differences in national abundance and trends, and differences in participant experience. Further power analysis indicated that even if SBS was statistically detectible with a larger sample, the practical implications of the syndrome would be minimal due to small effect sizes. Finally, the effect of experience on individual perceptions of species conservation priority varied between species, with generational amnesia in the form of ‘lifting baselines’ suggested for only one of the six species. This study suggests that shifting baseline syndrome may not be as significant a threat in conservation management as first thought

Effects of layer shift and yarn path variability on mechanical properties of a twill weave composite

Experimental and numerical analysis of a woven composite were performed in order to assess the effect of yarn path and layer shift variability on properties of the composite. Analysis of the geometry of a 12K carbon fibre 2×2 twill weave at the meso- and macro-scales showed the prevalence of the yarn path variations at the macro-scale over the meso-scale variations. Numerical analysis of yarn path variability showed that it is responsible for a Young’s modulus reduction of 0.5% and CoV of 1% which makes this type of variability in the selected reinforcement almost insignificant for an elastic analysis. Finite element analysis of damage propagation in laminates with layer shift showed good agreement with the experiments. Both numerical analysis and experiments showed that layer shift has a strong effect on the shape of the stress-strain curve. In particular, laminates with no layer shift tend to exhibit a kink in the stress-strain curve which was attributed solely to the layer configuration

Simulating Reionization: Character and Observability

In recent years there has been considerable progress in our understanding of the nature and properties of the reionization process. In particular, the numerical simulations of this epoch have made a qualitative leap forward, reaching sufficiently large scales to derive the characteristic scales of the reionization process and thus allowing for realistic observational predictions. Our group has recently performed the first such large-scale radiative transfer simulations of reionization, run on top of state-of-the-art simulations of early structure formation. This allowed us to make the first realistic observational predictions about the Epoch of Reionization based on detailed radiative transfer and structure formation simulations. We discuss the basic features of reionization derived from our simulations and some recent results on the observational implications for the high-redshift Ly-alpha sources.Comment: 3 pages, to appear in the Proceedings of First Stars III, Santa Fe, July 2007, AIP Conference Serie

Glucocorticoid treatment in patients with newly diagnosed immune thrombocytopenia switches CD14(++)CD16(+) intermediate monocytes from a pro-inflammatory to an anti-inflammatory phenotype

Immune thrombocytopenia (ITP) is thought to result from an aberrant adaptive autoimmune response, involving autoantibodies, B and T lymphocytes, directed at platelets and megakaryocytes. Previous reports have demonstrated skewed CD4+ T-helper subset distribution and enhanced production of pro-inflammatory cytokines such as interleukin 17A and interferon gamma. The role of monocytes (MCs) in ITP is less widely described, but innate immune cells have a role in shaping CD4+ T-cell phenotypes. Glucocorticoids (GCs) are commonly used for first-line ITP treatment and modulate a broad range of immune cells including T cells and MCs. Using multiparameter flow cytometry analysis, we demonstrate the expansion of intermediate MCs (CD14++CD16+ ) in untreated patients with newly diagnosed ITP, with these cells displaying a pro-inflammatory phenotype, characterised by enhanced expression of CD64 and CD80. After 2 weeks of prednisolone treatment (1 mg/kg daily), the proportion of intermediate MCs reduced, with enhanced expression of the anti-inflammatory markers CD206 and CD163. Healthy control MCs were distinctly different than MCs from patients with ITP before and after GC treatment. Furthermore, the GC-induced phenotype was not observed in patients with chronic ITP receiving thrombopoietin receptor agonists. These data suggest a role of MCs in ITP pathogenesis and clinical response to GC therapy

The first maps of κd - the dust mass absorption coefficient - in nearby galaxies, with DustPedia

The dust mass absorption coefficient, κd is the conversion function used to infer physical dust masses from observations of dust emission. However, it is notoriously poorly constrained, and it is highly uncertain how it varies, either between or within galaxies. Here we present the results of a proof-of-concept study, using the DustPedia data for two nearby face-on spiral galaxies M 74 (NGC 628) and M 83 (NGC 5236), to create the first ever maps of κd in galaxies. We determine κd using an empirical method that exploits the fact that the dust-to-metals ratio of the interstellar medium is constrained by direct measurements of the depletion of gas-phase metals. We apply this method pixel-by-pixel within M 74 and M 83, to create maps of κd. We also demonstrate a novel method of producing metallicity maps for galaxies with irregularly sampled measurements, using the machine learning technique of Gaussian process regression. We find strong evidence for significant variation in κd. We find values of κd at 500 μm spanning the range 0.11-0.25 m^{2 kg^{-1}} in M 74, and 0.15-0.80 m^{2 kg^{-1}} in M 83. Surprisingly, we find that κd shows a distinct inverse correlation with the local density of the interstellar medium. This inverse correlation is the opposite of what is predicted by standard dust models. However, we find this relationship to be robust against a large range of changes to our method - only the adoption of unphysical or highly unusual assumptions would be able to suppress it

Bayesian optimization for materials design

We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets. Bayesian optimization guides the choice of experiments during materials design and discovery to find good material designs in as few experiments as possible. We focus on the case when materials designs are parameterized by a low-dimensional vector. Bayesian optimization is built on a statistical technique called Gaussian process regression, which allows predicting the performance of a new design based on previously tested designs. After providing a detailed introduction to Gaussian process regression, we introduce two Bayesian optimization methods: expected improvement, for design problems with noise-free evaluations; and the knowledge-gradient method, which generalizes expected improvement and may be used in design problems with noisy evaluations. Both methods are derived using a value-of-information analysis, and enjoy one-step Bayes-optimality

Research protocol: investigating the feasibility of a group self-management intervention for stroke (the GUSTO study)

Background: Life after stroke can be an ongoing struggle with over half of all survivors reporting unmet emotional and social needs. In the United Kingdom's (UK) national clinical guidelines for stroke, self-management is suggested as one approach which can support long-term needs. In the UK NHS, self-management interventions are delivered in various ways. Regardless of the delivery mechanism, a tailored approach and ways to integrate peer support are advocated. Group delivery offers a platform for peer support and has the potential to remain individualised. However, before the efficacy of a group self-management intervention can be tested, the feasibility must be explored. This research investigates the feasibility of a GroUp Self-management intervention for sTrOke (GUSTO). Methods: A randomised waitlist control design will be used to investigate the feasibility of a group self-management intervention adapted from an existing one-to-one intervention called Bridges. A mixed methods approach will be used. Qualitative work will capture participant experience, while quantitative work will allow preliminary comparison between the intervention and waitlist groups (between subjects) and pre-post intervention measures (within subjects). Interviews will be conducted with stroke survivors and focus groups with family and friends to assess acceptability of the intervention. Discussion: There is a growing interest in group-based self-management interventions for stroke as a method of supporting stroke survivors' ongoing unmet needs. This is an area with limited research to date. This study will inform design of a fully powered trial which would assess the efficacy of a group self-management intervention following stroke. Trial registration: ISRCTN19867168

The Imprint of Galaxy Formation on X-ray Clusters

It is widely believed that structure in the Universe evolves hierarchically, as primordial density fluctuations, amplified by gravity, collapse and merge to form progressively larger systems. The structure and evolution of X-ray clusters, however, seems at odds with this hierarchical scenario for structure formation. Poor clusters and groups, as well as most distant clusters detected to date, are substantially fainter than expected from the tight relations between luminosity, temperature and redshift predicted by these models. Here we show that these discrepancies arise because, near the centre, the entropy of the hot, diffuse intracluster medium (ICM) is higher tha$achievable through gravitational collapse, indicating substantial non-gravitational heating of the ICM. We estimate this excess entropy for the first time, and argue that it represents a relic of the energetic winds through which forming galaxies polluted the ICM with metals. Energetically, this is onl$ possible if the ICM is heated at modest redshift (z \ltsim 2) but prior to cluster collapse, indicating that the formation of galaxies precedes that of clusters and that most clusters have been assembled very recently.Comment: 5 pages, plus 2 postscript figures (one in colour), accepted for publication in Natur

Four patients with a history of acute exacerbations of COPD: implementing the CHEST/Canadian Thoracic Society guidelines for preventing exacerbations

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