TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Cluster Lenses

Clusters of galaxies are the most recently assembled, massive, bound structures in the Universe. As predicted by General Relativity, given their masses, clusters strongly deform space-time in their vicinity. Clusters act as some of the most powerful gravitational lenses in the Universe. Light rays traversing through clusters from distant sources are hence deflected, and the resulting images of these distant objects therefore appear distorted and magnified. Lensing by clusters occurs in two regimes, each with unique observational signatures. The strong lensing regime is characterized by effects readily seen by eye, namely, the production of giant arcs, multiple-images, and arclets. The weak lensing regime is characterized by small deformations in the shapes of background galaxies only detectable statistically. Cluster lenses have been exploited successfully to address several important current questions in cosmology: (i) the study of the lens(es) - understanding cluster mass distributions and issues pertaining to cluster formation and evolution, as well as constraining the nature of dark matter; (ii) the study of the lensed objects - probing the properties of the background lensed galaxy population - which is statistically at higher redshifts and of lower intrinsic luminosity thus enabling the probing of galaxy formation at the earliest times right up to the Dark Ages; and (iii) the study of the geometry of the Universe - as the strength of lensing depends on the ratios of angular diameter distances between the lens, source and observer, lens deflections are sensitive to the value of cosmological parameters and offer a powerful geometric tool to probe Dark Energy. In this review, we present the basics of cluster lensing and provide a current status report of the field.Comment: About 120 pages - Published in Open Access at: http://www.springerlink.com/content/j183018170485723/ . arXiv admin note: text overlap with arXiv:astro-ph/0504478 and arXiv:1003.3674 by other author

X-Ray Spectroscopy of Stars

(abridged) Non-degenerate stars of essentially all spectral classes are soft X-ray sources. Low-mass stars on the cooler part of the main sequence and their pre-main sequence predecessors define the dominant stellar population in the galaxy by number. Their X-ray spectra are reminiscent, in the broadest sense, of X-ray spectra from the solar corona. X-ray emission from cool stars is indeed ascribed to magnetically trapped hot gas analogous to the solar coronal plasma. Coronal structure, its thermal stratification and geometric extent can be interpreted based on various spectral diagnostics. New features have been identified in pre-main sequence stars; some of these may be related to accretion shocks on the stellar surface, fluorescence on circumstellar disks due to X-ray irradiation, or shock heating in stellar outflows. Massive, hot stars clearly dominate the interaction with the galactic interstellar medium: they are the main sources of ionizing radiation, mechanical energy and chemical enrichment in galaxies. High-energy emission permits to probe some of the most important processes at work in these stars, and put constraints on their most peculiar feature: the stellar wind. Here, we review recent advances in our understanding of cool and hot stars through the study of X-ray spectra, in particular high-resolution spectra now available from XMM-Newton and Chandra. We address issues related to coronal structure, flares, the composition of coronal plasma, X-ray production in accretion streams and outflows, X-rays from single OB-type stars, massive binaries, magnetic hot objects and evolved WR stars.Comment: accepted for Astron. Astrophys. Rev., 98 journal pages, 30 figures (partly multiple); some corrections made after proof stag

Effect of genotypic, meteorological and agronomic factors on the gluten index of winter durum wheat

The determination of the gluten index is a widely used method for analysing the gluten strength of bread wheat and spring durum wheat genotypes. The present work was carried out to study the effect of the genotype, meteorological factors (temperature, precipitation and number of days with Tmax ≥ 30 °C) and agronomic treatments (N fertilisation and plant protection) on the gluten index of winter durum wheat varieties and breeding lines. The results indicated that the gluten index had little dependence on the environment, being determined to the greatest extent by the genotype. Compared with varieties having weak gluten, those with a strong gluten matrix responded less sensitively to changes in environmental conditions. Among the meteorological factors, high temperature at the end of the grain-filling period caused the greatest reduction in the mean gluten index of three varieties (R 2 = 0.462), while the fertiliser was found to be a significant factor affecting the gluten strength of winter durum wheat varieties. Using selection based on the gluten index, the gluten strength of winter durum wheat lines can be improved sufficiently to make them competitive with high quality spring varieties

Integration of a nationally procured electronic health record system into user work practices

BACKGROUND: Evidence suggests that many small- and medium-scale Electronic Health Record (EHR) implementations encounter problems, these often stemming from users' difficulties in accommodating the new technology into their work practices. There is the possibility that these challenges may be exacerbated in the context of the larger-scale, more standardised, implementation strategies now being pursued as part of major national modernisation initiatives. We sought to understand how England's centrally procured and delivered EHR software was integrated within the work practices of users in selected secondary and specialist care settings. METHODS: We conducted a qualitative longitudinal case study-based investigation drawing on sociotechnical theory in three purposefully selected sites implementing early functionality of a nationally procured EHR system. The complete dataset comprised semi-structured interview data from a total of 66 different participants, 38.5 hours of non-participant observation of use of the software in context, accompanying researcher field notes, and hospital documents (including project initiation and lessons learnt reports). Transcribed data were analysed thematically using a combination of deductive and inductive approaches, and drawing on NVivo8 software to facilitate coding. RESULTS: The nationally led "top-down" implementation and the associated focus on interoperability limited the opportunity to customise software to local needs. Lack of system usability led users to employ a range of workarounds unanticipated by management to compensate for the perceived shortcomings of the system. These had a number of knock-on effects relating to the nature of collaborative work, patterns of communication, the timeliness and availability of records (including paper) and the ability for hospital management to monitor organisational performance. CONCLUSIONS: This work has highlighted the importance of addressing potentially adverse unintended consequences of workarounds associated with the introduction of EHRs. This can be achieved with customisation, which is inevitably somewhat restricted in the context of attempts to implement national solutions. The tensions and potential trade-offs between achieving large-scale interoperability and local requirements is likely to be the subject of continuous debate in England and beyond with no easy answers in sight

Conceptual Frameworks and Methods for Advancing Invasion Ecology

Invasion ecology has much advanced since its early beginnings. Nevertheless, explanation, prediction, and management of biological invasions remain difficult. We argue that progress in invasion research can be accelerated by, first, pointing out difficulties this field is currently facing and, second, looking for measures to overcome them. We see basic and applied research in invasion ecology confronted with difficulties arising from (A) societal issues, e.g., disparate perceptions of invasive species; (B) the peculiarity of the invasion process, e.g., its complexity and context dependency; and (C) the scientific methodology, e.g., imprecise hypotheses. To overcome these difficulties, we propose three key measures: (1) a checklist for definitions to encourage explicit definitions; (2) implementation of a hierarchy of hypotheses (HoH), where general hypotheses branch into specific and precisely testable hypotheses; and (3) platforms for improved communication. These measures may significantly increase conceptual clarity and enhance communication, thus advancing invasion ecology

Human immunoglobulin G levels of viruses and associated glioma risk

Few consistent etiological factors have been identified for primary brain tumors. Inverse associations to asthma and low levels of varicella-zoster virus, immunoglobulin (Ig) levels in prevalent cases have indicted a role for the immune system in the development of glioma. Because samples from prevalent cases of glioma could be influenced by treatments such as steroids and chemotherapy, we investigated pre-diagnostic samples from three large Scandinavian cohorts. To test the hypothesis that immune response levels to these viruses are associated etiologically with glioma risk, we investigated pre-diagnostic immunoglobulin levels for cytomegalovirus (CMV), varicella-zoster virus (VZV), adenovirus (Ad), and Epstein-Barr virus (EBV) including the nuclear antigen (EBNA1) using plasma samples from 197 cases of adult glioma and 394 controls collected from population-based cohorts in Sweden and Denmark. Low VZV IgG levels were marginally significantly more common in glioma cases than the controls (odds ratio (OR) = 0.68, 95% CI 0.41–1.13) for the fourth compared with the first quartile (p = 0.06 for trend). These results were more prominent when analyzing cases with blood sampling at least 2 years before diagnosis (OR = 0.63, 95% CI 0.37–1.08) (p = 0.03). No association with glioma risk was observed for CMV, EBV, and adenovirus

Impact of periodic health examination on surgical treatment for uterine fibroids in Beijing: a case-control study

<p>Abstract</p> <p>Background</p> <p>During the past 2 decades, there has been a rapid proliferation of "health examination center (HEC)" across China. The effects of their services on public's health have not been systemically investigated. This study aimed to assess the impact of periodic health examination (PHE) at HEC on surgical treatment for uterine fibroids in Beijing residents.</p> <p>Methods</p> <p>We identified 224 patients with a primary diagnosis of uterine fibroids who had surgical treatment at four Level-1 general hospitals in Beijing, from June 1, 2009 to October 20, 2009. Controls were women who did not have surgery for uterine fibroids, matched (1:1 ratio) for age (within 2 years). A standard questionnaire was used to inquire about whether participants had PHE at HEC during the previous 2 years.</p> <p>Results</p> <p>PHE at HEC within 2 years were associated with surgical treatment for uterine fibroids. Odds ratios was 4.05 (95% CI, 2.61-6.29 P < 0.001), after adjustment for marital status, whether have children, annual family income, health insurance, education level and self-rated uterine fibroids-related symptom severity.</p> <p>Conclusions</p> <p>Our study showed PHE currently provided at HEC in China were associated with significantly increased use of surgical treatment for uterine fibroids in women. Further studies are needed to assess the effects of PHE on clinical as well as on broad societal outcomes in Chinese in contemporary medical settings.</p

Role and task allocation framework for Multi-Robot Collaboration with latent knowledge estimation

In this work a novel framework for modeling role and task allocation in Cooperative Heterogeneous Multi‐Robot Systems (CHMRSs) is presented. This framework encodes a CHMRS as a set of multidimensional relational structures (MDRSs). This set of structure defines collaborative tasks through both temporal and spatial relations between processes of heterogeneous robots. These relations are enriched with tensors which allow for geometrical reasoning about collaborative tasks. A learning schema is also proposed in order to derive the components of each MDRS. According to this schema, the components are learnt from data reporting the situated history of the processes executed by the team of robots. Data are organized as a multirobot collaboration treebank (MRCT) in order to support learning. Moreover, a generative approach, based on a probabilistic model, is combined together with nonnegative tensor decomposition (NTD) for both building the tensors and estimating latent knowledge. Preliminary evaluation of the performance of this framework is performed in simulation with three heterogeneous robots, namely, two Unmanned Ground Vehicles (UGVs) and one Unmanned Aerial Vehicle (UAV)