3,110 research outputs found

    Gathering evidence of benefits: a structured approach from the JISC Managing Research Data Programme

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    The work of the Jisc Managing Research Data programme is – along with the rest of the UK higher education sector – taking place in an environment of increasing pressure on research funding. In order to justify the investment made by Jisc in this activity – and to help make the case more widely for the value of investing time and money in research data management – projects and the programme as a whole must be able to clearly express the resultant benefits to the host institutions and to the broader sector. This paper describes a structured approach to the measurement and description of benefits provided by the work of these projects for the benefit of funders, institutions and researchers. We outline the context of the programme and its work; discuss the drivers and challenges of gathering evidence of benefits; specify benefits as distinct from aims and outputs; present emerging findings and the types of metrics and other evidence which projects have provided; explain the value of gathering evidence in a structured way to demonstrate benefits generated by work in this field; and share lessons learned from progress to date

    Techniques for the Microanalysis of Higher Plants with Particular Reference to Silicon in Cryofixed Wheat Tissues

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    The applications of x-ray microanalysis in research into silicon in higher plants are reviewed, recent developments are assessed, and new data are presented. Conventionally prepared material [air or freeze drying for scanning electron microscopy (SEM), and glutaraldehyde/osmium tetroxide fixation for transmission electron microscopy (TEM)) has been studied using both wavelength and energy dispersive microanalysis. These techniques are reliable provided that the deposited form of silica is the major focus of investigation. Recently, studies concerning the soluble, mobile forms of silica, and the ionic environment at deposition sites have been initiated. In these investigations x -ray microanalysis has been carried out on the cold stage of an SEM, or after freeze substitution on sections in TEM. Two other developments which are considered are the use of proton induced x-ray emission, and electron energy loss spectroscopy. To illustrate the most recent developments in this field we present new observations on mineral distribution in the culm and awn of wheat using microanalysis of frozen hydrated material in SEM, and in the wheat leaf using freeze substitution and TE M and scanning transmission electron microscopy

    Managing urban socio-technical change? Comparing energy technology controversies in three European contexts

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    A {\em local graph partitioning algorithm} finds a set of vertices with small conductance (i.e. a sparse cut) by adaptively exploring part of a large graph GG, starting from a specified vertex. For the algorithm to be local, its complexity must be bounded in terms of the size of the set that it outputs, with at most a weak dependence on the number nn of vertices in GG. Previous local partitioning algorithms find sparse cuts using random walks and personalized PageRank. In this paper, we introduce a randomized local partitioning algorithm that finds a sparse cut by simulating the {\em volume-biased evolving set process}, which is a Markov chain on sets of vertices. We prove that for any set of vertices AA that has conductance at most ϕ\phi, for at least half of the starting vertices in AA our algorithm will output (with probability at least half), a set of conductance O(ϕ1/2log1/2n)O(\phi^{1/2} \log^{1/2} n). We prove that for a given run of the algorithm, the expected ratio between its computational complexity and the volume of the set that it outputs is O(ϕ1/2polylog(n))O(\phi^{-1/2} polylog(n)). In comparison, the best previous local partitioning algorithm, due to Andersen, Chung, and Lang, has the same approximation guarantee, but a larger ratio of O(ϕ1polylog(n))O(\phi^{-1} polylog(n)) between the complexity and output volume. Using our local partitioning algorithm as a subroutine, we construct a fast algorithm for finding balanced cuts. Given a fixed value of ϕ\phi, the resulting algorithm has complexity O((m+nϕ1/2)polylog(n))O((m+n\phi^{-1/2}) polylog(n)) and returns a cut with conductance O(ϕ1/2log1/2n)O(\phi^{1/2} \log^{1/2} n) and volume at least vϕ/2v_{\phi}/2, where vϕv_{\phi} is the largest volume of any set with conductance at most ϕ\phi.Comment: 20 pages, no figure

    Dark ice dynamics of the south-west Greenland Ice Sheet

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    Runoff from the Greenland Ice Sheet (GrIS) has increased in recent years due largely to changes in atmospheric circulation and atmospheric warming. Albedo reductions resulting from these changes have amplified surface melting. Some of the largest declines in GrIS albedo have occurred in the ablation zone of the south-west sector and are associated with the development of "dark" ice surfaces. Field observations at local scales reveal that a variety of light-absorbing impurities (LAIs) can be present on the surface, ranging from inorganic particulates to cryoconite materials and ice algae. Meanwhile, satellite observations show that the areal extent of dark ice has varied significantly between recent successive melt seasons. However, the processes that drive such large interannual variability in dark ice extent remain essentially unconstrained. At present we are therefore unable to project how the albedo of bare ice sectors of the GrIS will evolve in the future, causing uncertainty in the projected sea level contribution from the GrIS over the coming decades. Here we use MODIS satellite imagery to examine dark ice dynamics on the south-west GrIS each year from 2000 to 2016. We quantify dark ice in terms of its annual extent, duration, intensity and timing of first appearance. Not only does dark ice extent vary significantly between years but so too does its duration (from 0 to > 80 % of June-July-August, JJA), intensity and the timing of its first appearance. Comparison of dark ice dynamics with potential meteorological drivers from the regional climate model MAR reveals that the JJA sensible heat flux, the number of positive minimum-air-temperature days and the timing of bare ice appearance are significant interannual synoptic controls. We use these findings to identify the surface processes which are most likely to explain recent dark ice dynamics. We suggest that whilst the spatial distribution of dark ice is best explained by outcropping of particulates from ablating ice, these particulates alone do not drive dark ice dynamics. Instead, they may enable the growth of pigmented ice algal assemblages which cause visible surface darkening, but only when the climatological prerequisites of liquid meltwater presence and sufficient photosynthetically active radiation fluxes are met. Further field studies are required to fully constrain the processes by which ice algae growth proceeds and the apparent dependency of algae growth on melt-out particulates

    Quantifying bioalbedo:a new physically based model and discussions of empirical methods for characterising biological influence on ice and snow albedo

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    The darkening effects of biological impurities on ice and snow have been recognised as a control on the surface energy balance of terrestrial snow, sea ice, glaciers and ice sheets. With a heightened interest in understanding the impacts of a changing climate on snow and ice processes, quantifying the impact of biological impurities on ice and snow albedo (bioalbedo) and its evolution through time is a rapidly growing field of research. However, rigorous quantification of bioalbedo has remained elusive because of difficulties in isolating the biological contribution to ice albedo from that of inorganic impurities and the variable optical properties of the ice itself. For this reason, isolation of the biological signature in reflectance data obtained from aerial/orbital platforms has not been achieved, even when ground-based biological measurements have been available. This paper provides the cell-specific optical properties that are required to model the spectral signatures and broadband darkening of ice. Applying radiative transfer theory, these properties provide the physical basis needed to link biological and glaciological ground measurements with remotely sensed reflectance data. Using these new capabilities we confirm that biological impurities can influence ice albedo, then we identify 10 challenges to the measurement of bioalbedo in the field with the aim of improving future experimental designs to better quantify bioalbedo feedbacks. These challenges are (1) ambiguity in terminology, (2) characterising snow or ice optical properties, (3) characterising solar irradiance, (4) determining optical properties of cells, (5) measuring biomass, (6) characterising vertical distribution of cells, (7) characterising abiotic impurities, (8) surface anisotropy, (9) measuring indirect albedo feedbacks, and (10) measurement and instrument configurations. This paper aims to provide a broad audience of glaciologists and biologists with an overview of radiative transfer and albedo that could support future experimental design

    The person-based nature of prejudice: Individual difference predictors of intergroup negativity

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    Person-based factors influence a range of meaningful life outcomes, including intergroup processes, and have long been implicated in explaining prejudice. In addition to demonstrating significant heritability, person-based factors are evident in expressions of generalised prejudice, a robust finding that some people (relative to others) consistently score higher in prejudice towards multiple outgroups. Our contemporary review includes personality factors, ideological orientations (e.g., authoritarianism), religiosity, anxiety, threat, disgust sensitivity, and cognitive abilities and styles. Meta-analytic syntheses demonstrate that such constructs consistently predict prejudice, often at the upper bounds of effect sizes observed in psychological research. We conclude that prejudice theories need to better integrate person- and situation-based factors, including their interaction, to capture the complexity of prejudice and inform intervention development
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