847 research outputs found

    The mycorrhizal relations of Larch III. mycorrhiza-formation in nature

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    The thesis consists of four papers of which the first two have already been published. Paper I entitled "A study of Boletus elegans Schum. in pure culture", deals with the morphological characters and the physiological behaviour of this fungus in pure culture. Paper II entitled "The role of the Larch root in the nutrition Boletus elegans Schum.", is concerned with the results of adding excised roots to fungal cultures; these indicate that a water-soluble substance capable of stimulating the growth of the fungus is present in the roots of European and Japanese Larch, but not in those of Scots Pine. Paper III entitled "Mycorrhiza--formation in nature," contains an account of the isolation of three endophytes, detailed descriptions of the structure of seven types of infection and a general survey of mycorrhiza-formation in mature Larch trees. Paper IV entitled "Mycorrhiza-formation in experimental culture", is concerned with four sets of experimental cultures with Larch seedlings in which various methods of inoculation were tested.<p

    On the Estimation of Bivariate Return Curves for Extreme Values

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    In the multivariate setting, defining extremal risk measures is important in many contexts, such as finance, environmental planning and structural engineering. In this paper, we review the literature on extremal bivariate return curves, a risk measure that is the natural bivariate extension to a return level, and propose new estimation methods based on multivariate extreme value models that can account for both asymptotic dependence and asymptotic independence. We identify gaps in the existing literature and propose novel tools for testing and validating return curves and comparing estimates from a range of multivariate models. These tools are then used to compare a selection of models through simulation and case studies. We conclude with a discussion and list some of the challenges.Comment: 41 pages (without supplementary), 11 figures, 2 table

    Improving estimation for asymptotically independent bivariate extremes via global estimators for the angular dependence function

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    Modelling the extremal dependence of bivariate variables is important in a wide variety of practical applications, including environmental planning, catastrophe modelling and hydrology. The majority of these approaches are based on the framework of bivariate regular variation, and a wide range of literature is available for estimating the dependence structure in this setting. However, this framework is only applicable to variables exhibiting asymptotic dependence, even though asymptotic independence is often observed in practice. In this paper, we consider the so-called `angular dependence function'; this quantity summarises the extremal dependence structure for asymptotically independent variables. Until recently, only pointwise estimators of the angular dependence function have been available. We introduce a range of global estimators and compare them to another recently introduced technique for global estimation through a systematic simulation study, and a case study on river flow data from the north of England, UK

    Magnetic surfactants

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    Electrolyte-induced Instability of Colloidal Dispersions in Nonpolar Solvents

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    Dispersions of poly(methyl methacrylate) (PMMA) latexes were prepared in a low dielectric, nonpolar solvent (dodecane) both with and without the oil-soluble electrolyte, tetradodecylammonium-tetrakis(3,5-bis(trifluoromethyl)phenyl)borate. For dispersions with a high concentration of background electrolyte, the latexes become colloidally unstable and sediment in a short period of time (<1 h). This is completely reversible upon dilution. Instability of the dispersions is due to an apparent attraction between the colloids, directly observed using optical tweezers by bringing optically trapped particles into close proximity. Simple explanations generally used by colloid scientists to explain loss of stability (charge screening or stabilizer collapse) are insufficient to explain this observation. This unexpected interaction seems, therefore, to be a consequence of the materials that can be dispersed in low dielectric media and is expected to have ramifications for studying colloids in such solvents

    Low-surface energy surfactants with branched hydrocarbon architectures

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    International audienceSurface tensiometry and small-angle neutron scattering have been used to characterize a new class of low-surface energy surfactants (LSESs), "hedgehog" surfactants. These surfactants are based on highly branched hydrocarbon (HC) chains as replacements for environmentally hazardous fluorocarbon surfactants and polymers. Tensiometric analyses indicate that a subtle structural modification in the tails and headgroup results in significant effects on limiting surface tensions γcmc at the critical micelle concentration: a higher level of branching and an increased counterion size promote an effective reduction of surface tension to low values for HC surfactants (γcmc 24 mN m-1). These LSESs present a new class of potentially very important materials, which form lamellar aggregates in aqueous solutions independent of dilution

    A machine learning approach to downscale EMEP4UK: analysis of UK ozone variability and trends

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    High-resolution modelling of surface ozone is an essential step in the quantification of the impacts on health and ecosystems from historic and future concentrations. It also provides a principled way in which to extend analysis beyond measurement locations. Often, such modelling uses relatively coarse-resolution chemistry transport models (CTMs), which exhibit biases when compared to measurements. EMEP4UK is a CTM that is used extensively to inform UK air quality policy, including the effects on ozone from mitigation of its precursors. Our evaluation of EMEP4UK for the years 2001–2018 finds a high bias in reproducing daily maximum 8 h average ozone (MDA8), due in part to the coarse spatial resolution. We present a machine learning downscaling methodology to downscale EMEP4UK ozone output from a 5×5 km to 1×1 km resolution using a gradient-boosted tree. By addressing the high bias present in EMEP4UK, the downscaled surface better represents the measured data, with a 128 % improvement in R2 and 37 % reduction in RMSE. Our analysis of the downscaled surface shows a decreasing trend in annual and March–August mean MDA8 ozone for all regions of the UK between 2001–2018, differing from increasing measurement trends in some regions. We find the proportion of the UK which fails the government objective to have at most 10 exceedances of 100 µg m−3 per annum is 27 % (2014–2018 average), compared to 99 % from the unadjusted EMEP4UK model. A statistically significant trend in this proportion of −2.19 % yr−1 is found from the downscaled surface only, highlighting the importance of bias correction in the assessment of policy metrics. Finally, we use the downscaling approach to examine the sensitivity of UK surface ozone to reductions in UK terrestrial NOx (i.e. NO + NO2) emissions on a 1×1 km surface. Moderate NOx emission reductions with respect to present day (20 % or 40 %) increase both average and high-level ozone concentrations in large portions of the UK, whereas larger NOx reductions (80 %) cause a similarly widespread decrease in high-level ozone. In all three scenarios, very urban areas (i.e. major cities) are the most affected by increasing concentrations of ozone, emphasizing the broader air quality challenges of NOx control
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