944 resultados para Real Root Isolation Methods
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Requirements for research, practices and policies affecting soil management in relation to global food security are reviewed. Managing soil organic carbon (C) is central because soil organic matter influences numerous soil properties relevant to ecosystem functioning and crop growth. Even small changes in total C content can have disproportionately large impacts on key soil physical properties. Practices to encourage maintenance of soil C are important for ensuring sustainability of all soil functions. Soil is a major store of C within the biosphere – increases or decreases in this large stock can either mitigate or worsen climate change. Deforestation, conversion of grasslands to arable cropping and drainage of wetlands all cause emission of C; policies and international action to minimise these changes are urgently required. Sequestration of C in soil can contribute to climate change mitigation but the real impact of different options is often misunderstood. Some changes in management that are beneficial for soil C, increase emissions of nitrous oxide (a powerful greenhouse gas) thus cancelling the benefit. Research on soil physical processes and their interactions with roots can lead to improved and novel practices to improve crop access to water and nutrients. Increased understanding of root function has implications for selection and breeding of crops to maximise capture of water and nutrients. Roots are also a means of delivering natural plant-produced chemicals into soil with potentially beneficial impacts. These include biocontrol of soil-borne pests and diseases and inhibition of the nitrification process in soil (conversion of ammonium to nitrate) with possible benefits for improved nitrogen use efficiency and decreased nitrous oxide emission. The application of molecular methods to studies of soil organisms, and their interactions with roots, is providing new understanding of soil ecology and the basis for novel practical applications. Policy makers and those concerned with development of management approaches need to keep a watching brief on emerging possibilities from this fast-moving area of science. Nutrient management is a key challenge for global food production: there is an urgent need to increase nutrient availability to crops grown by smallholder farmers in developing countries. Many changes in practices including inter-cropping, inclusion of nitrogen-fixing crops, agroforestry and improved recycling have been clearly demonstrated to be beneficial: facilitating policies and practical strategies are needed to make these widely available, taking account of local economic and social conditions. In the longer term fertilizers will be essential for food security: policies and actions are needed to make these available and affordable to small farmers. In developed regions, and those developing rapidly such as China, strategies and policies to manage more precisely the necessarily large flows of nutrients in ways that minimise environmental damage are essential. A specific issue is to minimise emissions of nitrous oxide whilst ensuring sufficient nitrogen is available for adequate food production. Application of known strategies (through either regulation or education), technological developments, and continued research to improve understanding of basic processes will all play a part. Decreasing soil erosion is essential, both to maintain the soil resource and to minimise downstream damage such as sedimentation of rivers with adverse impacts on fisheries. Practical strategies are well known but often have financial implications for farmers. Examples of systems for paying one group of land users for ecosystem services affecting others exist in several parts of the world and serve as a model.
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The objective of this book is to present the quantitative techniques that are commonly employed in empirical finance research together with real world, state of the art research examples. Each chapter is written by international experts in their fields. The unique approach is to describe a question or issue in finance and then to demonstrate the methodologies that may be used to solve it. All of the techniques described are used to address real problems rather than being presented for their own sake and the areas of application have been carefully selected so that a broad range of methodological approaches can be covered. This book is aimed primarily at doctoral researchers and academics who are engaged in conducting original empirical research in finance. In addition, the book will be useful to researchers in the financial markets and also advanced Masters-level students who are writing dissertations.
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Objective: To describe the training undertaken by pharmacists employed in a pharmacist-led information technology-based intervention study to reduce medication errors in primary care (PINCER Trial), evaluate pharmacists’ assessment of the training, and the time implications of undertaking the training. Methods: Six pharmacists received training, which included training on root cause analysis and educational outreach, to enable them to deliver the PINCER Trial intervention. This was evaluated using self-report questionnaires at the end of each training session. The time taken to complete each session was recorded. Data from the evaluation forms were entered onto a Microsoft Excel spreadsheet, independently checked and the summary of results further verified. Frequencies were calculated for responses to the three-point Likert scale questions. Free-text comments from the evaluation forms and pharmacists’ diaries were analysed thematically. Key findings: All six pharmacists received 22 hours of training over five sessions. In four out of the five sessions, the pharmacists who completed an evaluation form (27 out of 30 were completed) stated they were satisfied or very satisfied with the various elements of the training package. Analysis of free-text comments and the pharmacists’ diaries showed that the principles of root cause analysis and educational outreach were viewed as useful tools to help pharmacists conduct pharmaceutical interventions in both the study and other pharmacy roles that they undertook. The opportunity to undertake role play was a valuable part of the training received. Conclusions: Findings presented in this paper suggest that providing the PINCER pharmacists with training in root cause analysis and educational outreach contributed to the successful delivery of PINCER interventions and could potentially be utilised by other pharmacists based in general practice to deliver pharmaceutical interventions to improve patient safety.
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We propose a Nystr¨om/product integration method for a class of second kind integral equations on the real line which arise in problems of two-dimensional scalar and elastic wave scattering by unbounded surfaces. Stability and convergence of the method is established with convergence rates dependent on the smoothness of components of the kernel. The method is applied to the problem of acoustic scattering by a sound soft one-dimensional surface which is the graph of a function f, and superalgebraic convergence is established in the case when f is infinitely smooth. Numerical results are presented illustrating this behavior for the case when f is periodic (the diffraction grating case). The Nystr¨om method for this problem is stable and convergent uniformly with respect to the period of the grating, in contrast to standard integral equation methods for diffraction gratings which fail at a countable set of grating periods.
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Background and Aims: Phosphate (Pi) deficiency in soils is a major limiting factor for crop growth worldwide. Plant growth under low Pi conditions correlates with root architectural traits and it may therefore be possible to select these traits for crop improvement. The aim of this study was to characterize root architectural traits, and to test quantitative trait loci (QTL) associated with these traits, under low Pi (LP) and high Pi (HP) availability in Brassica napus. Methods: Root architectural traits were characterized in seedlings of a double haploid (DH) mapping population (n = 190) of B. napus 'Tapidor' x 'Ningyou 7' (TNDH) using high-throughput phenotyping methods. Primary root length (PRL), lateral root length (LRL), lateral root number (LRN), lateral root density (LRD) and biomass traits were measured 12 d post-germination in agar at LP and HP. Key Results: In general, root and biomass traits were highly correlated under LP and HP conditions. 'Ningyou 7' had greater LRL, LRN and LRD than 'Tapidor', at both LP and HP availability, but smaller PRL. A cluster of highly significant QTL for LRN, LRD and biomass traits at LP availability were identified on chromosome A03; QTL for PRL were identified on chromosomes A07 and C06. Conclusions: High-throughput phenotyping of Brassica can be used to identify root architectural traits which correlate with shoot biomass. It is feasible that these traits could be used in crop improvement strategies. The identification of QTL linked to root traits under LP and HP conditions provides further insights on the genetic basis of plant tolerance to P deficiency, and these QTL warrant further dissection.
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We examine how the accuracy of real-time forecasts from models that include autoregressive terms can be improved by estimating the models on ‘lightly revised’ data instead of using data from the latest-available vintage. The benefits of estimating autoregressive models on lightly revised data are related to the nature of the data revision process and the underlying process for the true values. Empirically, we find improvements in root mean square forecasting error of 2–4% when forecasting output growth and inflation with univariate models, and of 8% with multivariate models. We show that multiple-vintage models, which explicitly model data revisions, require large estimation samples to deliver competitive forecasts. Copyright © 2012 John Wiley & Sons, Ltd.
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With a wide range of applications benefiting from dense network air temperature observations but with limitations of costs, existing siting guidelines and risk of damage to sensors, new methods are required to gain a high resolution understanding of the spatio-temporal patterns of urban meteorological phenomena such as the urban heat island or precision farming needs. With the launch of a new generation of low cost sensors it is possible to deploy a network to monitor air temperature at finer spatial resolutions. Here we investigate the Aginova Sentinel Micro (ASM) sensor with a bespoke radiation shield (together < US$150) which can provide secure near-real-time air temperature data to a server utilising existing (or user deployed) Wireless Fidelity (Wi-Fi) networks. This makes it ideally suited for deployment where wireless communications readily exist, notably urban areas. Assessment of the performance of the ASM relative to traceable standards in a water bath and atmospheric chamber show it to have good measurement accuracy with mean errors < ± 0.22 °C between -25 and 30 °C, with a time constant in ambient air of 110 ± 15 s. Subsequent field tests of it within the bespoke shield also had excellent performance (root-mean-square error = 0.13 °C) over a range of meteorological conditions relative to a traceable operational UK Met Office platinum resistance thermometer. These results indicate that the ASM and bespoke shield are more than fit-for-purpose for dense network deployment in urban areas at relatively low cost compared to existing observation techniques.
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Adult human neural crest-derived stem cells (NCSCs) are of extraordinary high plasticity and promising candidates for the use in regenerative medicine. Here we describe for the first time a novel neural crest-derived stem cell population within the respiratory epithelium of human adult inferior turbinate. In contrast to superior and middle turbinates, high amounts of source material could be isolated from human inferior turbinates. Using minimally-invasive surgery methods isolation is efficient even in older patients. Within their endogenous niche, inferior turbinate stem cells (ITSCs) expressed high levels of nestin, p75(NTR), and S100. Immunoelectron microscopy using anti-p75 antibodies displayed that ITSCs are of glial origin and closely related to nonmyelinating Schwann cells. Cultivated ITSCs were positive for nestin and S100 and the neural crest markers Slug and SOX10. Whole genome microarray analysis showed pronounced differences to human ES cells in respect to pluripotency markers OCT4, SOX2, LIN28, and NANOG, whereas expression of WDR5, KLF4, and c-MYC was nearly similar. ITSCs were able to differentiate into cells with neuro-ectodermal and mesodermal phenotype. Additionally ITSCs are able to survive and perform neural crest typical chain migration in vivo when transplanted into chicken embryos. However ITSCs do not form teratomas in severe combined immunodeficient mice. Finally, we developed a separation strategy based on magnetic cell sorting of p75(NTR) positive ITSCs that formed larger neurospheres and proliferated faster than p75(NTR) negative ITSCs. Taken together our study describes a novel, readily accessible source of multipotent human NCSCs for potential cell-replacement therapy.
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We systematically compare the performance of ETKF-4DVAR, 4DVAR-BEN and 4DENVAR with respect to two traditional methods (4DVAR and ETKF) and an ensemble transform Kalman smoother (ETKS) on the Lorenz 1963 model. We specifically investigated this performance with increasing nonlinearity and using a quasi-static variational assimilation algorithm as a comparison. Using the analysis root mean square error (RMSE) as a metric, these methods have been compared considering (1) assimilation window length and observation interval size and (2) ensemble size to investigate the influence of hybrid background error covariance matrices and nonlinearity on the performance of the methods. For short assimilation windows with close to linear dynamics, it has been shown that all hybrid methods show an improvement in RMSE compared to the traditional methods. For long assimilation window lengths in which nonlinear dynamics are substantial, the variational framework can have diffculties fnding the global minimum of the cost function, so we explore a quasi-static variational assimilation (QSVA) framework. Of the hybrid methods, it is seen that under certain parameters, hybrid methods which do not use a climatological background error covariance do not need QSVA to perform accurately. Generally, results show that the ETKS and hybrid methods that do not use a climatological background error covariance matrix with QSVA outperform all other methods due to the full flow dependency of the background error covariance matrix which also allows for the most nonlinearity.
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Aims: To understand effects of tissue type, growth stage and soil fertilisers on bacterial endophyte communities of winter wheat (Triticum aestivum cv. Hereward). Methods: Endophytes were isolated from wheat grown under six fertiliser conditions in the long term Broadbalk Experiment at Rothamsted Research, UK. Samples were taken in May and July from root and leaf tissues. Results: Root and leaf communities differed in abundance and composition of endophytes. Endophytes were most abundant in roots and the Proteobacteria were most prevalent. In contrast, Firmicutes and Actinobacteria, the Gram positive phyla, were most prevalent in the leaves. Both fertiliser treatment and sample time influenced abundance and relative proportions of each phylum and genus in the endosphere. A higher density of endophytes was found in the Nil input treatment plants. Conclusions: Robust isolation techniques and stringent controls are critical for accurate recovery of endophytes. The plant tissue type, plant growth stage, and soil fertiliser treatment all contribute to the composition of the endophytic bacterial community in wheat. These results should help facilitate targeted development of endophytes for beneficial applications in agriculture.
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Aims Potatoes are a globally important source of food whose production requires large inputs of fertiliser and water. Recent research has highlighted the importance of the root system in acquiring resources. Here measurements, previously generated by field phenotyping, tested the effect of root size on maintenance of yield under drought (drought tolerance). Methods Twelve potato genotypes, including genotypes with extremes of root size, were grown to maturity in the field under a rain shelter and either irrigated or subjected to drought. Soil moisture, canopy growth, carbon isotope discrimination and final yields were measured. Destructively harvested field phenotype data were used as explanatory variables in a general linear model (GLM) to investigate yield under conditions of drought or irrigation. Results Drought severely affected the small rooted genotype Pentland Dell but not the large rooted genotype Cara. More plantlets, longer and more numerous stolons and stolon roots were associated with drought tolerance. Previously measured carbon isotope discrimination did not correlate with the effect of drought. Conclusions These data suggest that in-field phenotyping can be used to identify useful characteristics when known genotypes are subjected to an environmental stress. Stolon root traits were associated with drought tolerance in potato and could be used to select genotypes with resilience to drought.
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Aim Most vascular plants on Earth form mycorrhizae, a symbiotic relationship between plants and fungi. Despite the broad recognition of the importance of mycorrhizae for global carbon and nutrient cycling, we do not know how soil and climate variables relate to the intensity of colonization of plant roots by mycorrhizal fungi. Here we quantify the global patterns of these relationships. Location Global. Methods Data on plant root colonization intensities by the two dominant types of mycorrhizal fungi world-wide, arbuscular (4887 plant species in 233 sites) and ectomycorrhizal fungi (125 plant species in 92 sites), were compiled from published studies. Data for climatic and soil factors were extracted from global datasets. For a given mycorrhizal type, we calculated at each site the mean root colonization intensity by mycorrhizal fungi across all potentially mycorrhizal plant species found at the site, and subjected these data to generalized additive model regression analysis with environmental factors as predictor variables. Results We show for the first time that at the global scale the intensity of plant root colonization by arbuscular mycorrhizal fungi strongly relates to warm-season temperature, frost periods and soil carbon-to-nitrogen ratio, and is highest at sites featuring continental climates with mild summers and a high availability of soil nitrogen. In contrast, the intensity of ectomycorrhizal infection in plant roots is related to soil acidity, soil carbon-to-nitrogen ratio and seasonality of precipitation, and is highest at sites with acidic soils and relatively constant precipitation levels. Main conclusions We provide the first quantitative global maps of intensity of mycorrhizal colonization based on environmental drivers, and suggest that environmental changes will affect distinct types of mycorrhizae differently. Future analyses of the potential effects of environmental change on global carbon and nutrient cycling via mycorrhizal pathways will need to take into account the relationships discovered in this study.
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The weak-constraint inverse for nonlinear dynamical models is discussed and derived in terms of a probabilistic formulation. The well-known result that for Gaussian error statistics the minimum of the weak-constraint inverse is equal to the maximum-likelihood estimate is rederived. Then several methods based on ensemble statistics that can be used to find the smoother (as opposed to the filter) solution are introduced and compared to traditional methods. A strong point of the new methods is that they avoid the integration of adjoint equations, which is a complex task for real oceanographic or atmospheric applications. they also avoid iterative searches in a Hilbert space, and error estimates can be obtained without much additional computational effort. the feasibility of the new methods is illustrated in a two-layer quasigeostrophic model.
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The real-time quality control (RTQC) methods applied to Argo profiling float data by the United Kingdom (UK) Met Office, the United States (US) Fleet Numerical Meteorology and Oceanography Centre, the Australian Bureau of Meteorology and the Coriolis Centre are compared and contrasted. Data are taken from the period 2007 to 2011 inclusive and RTQC performance is assessed with respect to Argo delayed-mode quality control (DMQC). An intercomparison of RTQC techniques is performed using a common data set of profiles from 2010 and 2011. The RTQC systems are found to have similar power in identifying faulty Argo profiles but to vary widely in the number of good profiles incorrectly rejected. The efficacy of individual QC tests are inferred from the results of the intercomparison. Techniques to increase QC performance are discussed.