966 resultados para quantifying heteroskedasticity


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Suprathermal electrons (>70 eV) form a small fraction of the total solar wind electron density but serve as valuable tracers of heliospheric magnetic field topology. Their usefulness as tracers of magnetic loops with both feet rooted on the Sun, however, most likely fades as the loops expand beyond some distance owing to scattering. As a first step toward quantifying that distance, we construct an observationally constrained model for the evolution of the suprathermal electron pitch-angle distributions on open field lines. We begin with a near-Sun isotropic distribution moving antisunward along a Parker spiral magnetic field while conserving magnetic moment, resulting in a field-aligned strahl within a few solar radii. Past this point, the distribution undergoes little evolution with heliocentric distance. We then add constant (with heliocentric distance, energy, and pitch angle) ad-hoc pitch-angle scattering. Close to the Sun, pitch-angle focusing still dominates, again resulting in a narrow strahl. Farther from the Sun, however, pitch-angle scattering dominates because focusing is effectively weakened by the increasing angle between the magnetic field direction and intensity gradient, a result of the spiral field. We determine the amount of scattering required to match Ulysses observations of strahl width in the fast solar wind, providing an important tool for inferring the large-scale properties and topologies of field lines in the interplanetary medium. Although the pitch-angle scattering term is independent of energy, time-of-flight effects in the spiral geometry result in an energy dependence of the strahl width that is in the observed sense although weaker in magnitude.

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One of the largest uncertainties in quantifying the impact of aviation on climate concerns the formation and spreading of persistent contrails. The inclusion of a cloud scheme that allows for ice supersaturation into the integrated forecast system (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) can be a useful tool to help reduce these uncertainties. This study evaluates the quality of the ECMWF forecasts with respect to ice super saturation in the upper troposphere by comparing them to visual observations of persistent contrails and radiosonde measurements of ice supersaturation over England. The performance of 1- to 3-day forecasts is compared including also the vertical accuracy of the supersaturation forecasts. It is found that the operational forecasts from the ECMWF are able to predict cold ice supersaturated regions very well. For the best cases Peirce skill scores of 0.7 are obtained, with hit rates at times exceeding 80% and false-alarm rates below 20%. Results are very similar for comparisons with visual observations and radiosonde measurements, the latter providing the better statistical significance.

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The measurement of the impact of technical change has received significant attention within the economics literature. One popular method of quantifying the impact of technical change is the use of growth accounting index numbers. However, in a recent article Nelson and Pack (1999) criticise the use of such index numbers in situations where technical change is likely to be biased in favour of one or other inputs. In particular they criticise the common approach of applying observed cost shares, as proxies for partial output elasticities, to weight the change in quantities which they claim is only valid under Hicks neutrality. Recent advances in the measurement of product and factor biases of technical change developed by Balcombe et al (2000) provide a relatively straight-forward means of correcting product and factor shares in the face of biased technical progress. This paper demonstrates the correction of both revenue and cost shares used in the construction of a TFP index for UK agriculture over the period 1953 to 2000 using both revenue and cost function share equations appended with stochastic latent variables to capture the bias effect. Technical progress is shown to be biased between both individual input and output groups. Output and input quantity aggregates are then constructed using both observed and corrected share weights and the resulting TFPs are compared. There does appear to be some significant bias in TFP if the effect of biased technical progress is not taken into account when constructing the weights

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Communities of nectar-producing plants show high spatio-temporal variation in the patterns of volume and concentration presentation. We illustrate a novel approach for quantifying nectar reward structures in complex communities, demonstrating that nectar resource diversity (defined as the variety of nectar volume-concentration combinations available) may be a fundamental factor organising nectarivore communities. In a series of diverse bee and entomophilous flower communities in Israel, our measure of nectar resource diversity alone explains the majority of variation in bee species richness, while other nectar variables (volume, concentration, energy value, and water content) have little predictive value per se. The new measure of nectar resource diversity is highly correlated with floral species richness and particularly with the species richness of annuals, yet it is additive in its effect on bee diversity. We conclude that relying solely upon measurements of mean nectar volume and mean nectar concentration overlooks a key characteristic of community-level reward structure, nectar resource diversity, so that previous studies may have failed to identify an important determinant of flower-visitor community structure.

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Pollination by bees and other animals increases the size, quality, or stability of harvests for 70% of leading global crops. Because native species pollinate many of these crops effectively, conserving habitats for wild pollinators within agricultural landscapes can help maintain pollination services. Using hierarchical Bayesian techniques, we synthesize the results of 23 studies - representing 16 crops on five continents - to estimate the general relationship between pollination services and distance from natural or semi-natural habitats. We find strong exponential declines in both pollinator richness and native visitation rate. Visitation rate declines more steeply, dropping to half of its maximum at 0.6 km from natural habitat, compared to 1.5 km for richness. Evidence of general decline in fruit and seed set - variables that directly affect yields - is less clear. Visitation rate drops more steeply in tropical compared with temperate regions, and slightly more steeply for social compared with solitary bees. Tropical crops pollinated primarily by social bees may therefore be most susceptible to pollination failure from habitat loss. Quantifying these general relationships can help predict consequences of land use change on pollinator communities and crop productivity, and can inform landscape conservation efforts that balance the needs of native species and people.

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The effectiveness of development assistance has come under renewed scrutiny in recent years. In an era of growing economic liberalisation, research organisations are increasingly being asked to account for the use of public funds by demonstrating achievements. However, in the natural resources (NR) research field, conventional economic assessment techniques have focused on quantifying the impact achieved rather understanding the process that delivered it. As a result, they provide limited guidance for planners and researchers charged with selecting and implementing future research. In response, “pathways” or logic models have attracted increased interest in recent years as a remedy to this shortcoming. However, as commonly applied these suffer from two key limitations in their ability to incorporate risk and assess variance from plan. The paper reports the results of a case study that used a Bayesian belief network approach to address these limitations and outlines its potential value as a tool to assist the planning, monitoring and evaluation of development-orientated research.

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Inferring population admixture from genetic data and quantifying it is a difficult but crucial task in evolutionary and conservation biology. Unfortunately state-of-the-art probabilistic approaches are computationally demanding. Effectively exploiting the computational power of modern multiprocessor systems can thus have a positive impact to Monte Carlo-based simulation of admixture modeling. A novel parallel approach is briefly described and promising results on its message passing interface (MPI)-based C implementation are reported.

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This paper presents a reappraisal of the blood clotting response (BCR) tests for anticoagulant rodenticides, and proposes a standardised methodology for identifying and quantifying physiological resistance in populations of rodent species. The standardisation is based on the International Normalised Ratio, which is standardised against a WHO international reference preparation of thromboplastin, and allows comparison of data obtained using different thromboplastin reagents. ne methodology is statistically sound, being based on the 50% response, and has been validated against the Norway rat (Rattus norvegicus) and the house mouse (Mus domesticus). Susceptibility baseline data are presented for warfarin, diphacinone, chlorophacinone and coumatetralyl against the Norway rat, and for bromadiolone, difenacoum, difethialone, flocoumafen and brodifacoum against the Norway rat and the house mouse. A 'test dose' of twice the ED50 can be used for initial identification of resistance, and will provide a similar level of information to previously published methods. Higher multiples of the ED50 can be used to assess the resistance factor, and to predict the likely impact on field control.

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BACKGROUND: Chronic fatigue syndrome (CFS) is an increasing medical phenomenon of unknown aetiology leading to high levels of chronic morbidity. Of the many hypotheses that purport to explain this disease, immune system activation, as a central feature, has remained prominent but unsubstantiated. Supporting this, a number of important cytokines have previously been shown to be over-expressed in disease subjects. The diagnosis of CFS is highly problematic since no biological markers specific to this disease have been identified. The discovery of genes relating to this condition is an important goal in seeking to correctly categorize and understand this complex syndrome. OBJECTIVE: The aim of this study was to screen for changes in gene expression in the lymphocytes of CFS patients. METHODS: 'Differential Display' is a method for comparing mRNA populations for the induction or suppression of genes. In this technique, mRNA populations from control and test subjects can be 'displayed' by gel electrophoresis and screened for differing banding patterns. These differences are indicative of altered gene expression between samples, and the genes that correspond to these bands can be cloned and identified. Differential display has been used to compare expression levels between four control subjects and seven CFS patients. RESULTS: Twelve short expressed sequence tags have been identified that were over-expressed in lymphocytes from CFS patients. Two of these correspond to cathepsin C and MAIL1 - genes known to be upregulated in activated lymphocytes. The expression level of seven of the differentially displayed sequences have been verified by quantifying relative level of these transcripts using TAQman quantitative PCR. CONCLUSION: Taken as a whole, the identification of novel gene tags up-regulated in CFS patients adds weight to the idea that CFS is a disease characterized by subtle changes in the immune system.

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Purpose – The purpose of this paper is to focus on the Fédération Internationale des Ingénieurs-Conseils (FIDIC) White Book standard form of building contract. It tracks the changes to this contract over its four editions, and seeks to identify their underlying causes. Design/methodology/approach – The changes made to the White Book are quantified using a specific type of quantitative content analysis. The amended clauses are then examined to understand the nature of the changes made. Findings – The length of the contract increased by 34 per cent between 1990 and 2006. A large proportion of the overall increase can be attributed to the clauses dealing with “conflict of interest/corruption” and “dispute resolution”. In both instances, the FIDIC drafting committees have responded to international developments to discourage corruption, and to encourage the use of alternative dispute resolution. Between 1998 and 2006, the average length of the sentences increased slightly, raising the question of whether long sentences are easily understood by users of contracts. Research limitations/implications – Quantification of text appears to be particularly useful for the analysis of documents which are regularly updated because changes can be clearly identified and the length of sentences can be determined, leading to conclusions about the readability of the text. However, caution is needed because changes of great relevance can be made to contract clauses without actually affecting their length. Practical implications – The paper will be instructive for contract drafters and informative for users of FIDIC's White Book. Originality/value – Quantifying text has been rarely used regarding standard-form contracts in the field of construction.

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Aims: To develop a quantitative equation [prebiotic index ( PI)] to aid the analysis of prebiotic fermentation of commercially available and novel prebiotic carbohydrates in vitro, using previously published fermentation data. Methods: The PI equation is based on the changes in key bacterial groups during fermentation. The bacterial groups incorporated into this PI equation were bifidobacteria, lactobacilli, clostridia and bacteroides. The changes in these bacterial groups from previous studies were entered into the PI equation in order to determine a quantitative PI score. PI scores were than compared with the qualitative conclusions made in these publications. In general the PI scores agreed with the qualitative conclusions drawn and provided a quantitative measure. Conclusions: The PI allows the magnitude of prebiotic effects to be quantified rather than evaluations being solely qualitative. Significance and Impact of the Study: The PI equation may be of great use in quantifying prebiotic effects in vitro. It is expected that this will facilitate more rational food product development and the development of more potent prebiotics with activity at lower doses.

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Quantitative analysis by mass spectrometry (MS) is a major challenge in proteomics as the correlation between analyte concentration and signal intensity is often poor due to varying ionisation efficiencies in the presence of molecular competitors. However, relative quantitation methods that utilise differential stable isotope labelling and mass spectrometric detection are available. Many drawbacks inherent to chemical labelling methods (ICAT, iTRAQ) can be overcome by metabolic labelling with amino acids containing stable isotopes (e.g. 13C and/or 15N) in methods such as Stable Isotope Labelling with Amino acids in Cell culture (SILAC). SILAC has also been used for labelling of proteins in plant cell cultures (1) but is not suitable for whole plant labelling. Plants are usually autotrophic (fixing carbon from atmospheric CO2) and, thus, labelling with carbon isotopes becomes impractical. In addition, SILAC is expensive. Recently, Arabidopsis cell cultures were labelled with 15N in a medium containing nitrate as sole nitrogen source. This was shown to be suitable for quantifying proteins and nitrogen-containing metabolites from this cell culture (2,3). Labelling whole plants, however, offers the advantage of studying quantitatively the response to stimulation or disease of a whole multicellular organism or multi-organism systems at the molecular level. Furthermore, plant metabolism enables the use of inexpensive labelling media without introducing additional stress to the organism. And finally, hydroponics is ideal to undertake metabolic labelling under extremely well-controlled conditions. We demonstrate the suitability of metabolic 15N hydroponic isotope labelling of entire plants (HILEP) for relative quantitative proteomic analysis by mass spectrometry. To evaluate this methodology, Arabidopsis plants were grown hydroponically in 14N and 15N media and subjected to oxidative stress.

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A theoretical framework is developed for the evolution of baroclinic waves with latent heat release parameterized in terms of vertical velocity. Both wave–conditional instability of the second kind (CISK) and large-scale rain approaches are included. The new quasigeostrophic framework covers evolution from general initial conditions on zonal flows with vertical shear, planetary vorticity gradient, a lower boundary, and a tropopause. The formulation is given completely in terms of potential vorticity, enabling the partition of perturbations into Rossby wave components, just as for the dry problem. Both modal and nonmodal development can be understood to a good approximation in terms of propagation and interaction between these components alone. The key change with moisture is that growing normal modes are described in terms of four counterpropagating Rossby wave (CRW) components rather than two. Moist CRWs exist above and below the maximum in latent heating, in addition to the upper- and lower-level CRWs of dry theory. Four classifications of baroclinic development are defined by quantifying the strength of interaction between the four components and identifying the dominant pairs, which range from essentially dry instability to instability in the limit of strong heating far from boundaries, with type-C cyclogenesis and diabatic Rossby waves being intermediate types. General initial conditions must also include passively advected residual PV, as in the dry problem.

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The urban heat island (UHI) is a well-known effect of urbanisation and is particularly important in world megacities. Overheating in such cities is expected to be exacerbated in the future as a result of further urban growth and climate change. Demonstrating and quantifying the impact of individual design interventions on the UHI is currently difficult using available software tools. The tools developed in the LUCID (‘The Development of a Local Urban Climate Model and its Application to the Intelligent Design of Cities’) research project will enable the related impacts to be better understood, quantified and addressed. This article summarises the relevant literature and reports on the ongoing work of the project.

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A significant challenge in the prediction of climate change impacts on ecosystems and biodiversity is quantifying the sources of uncertainty that emerge within and between different models. Statistical species niche models have grown in popularity, yet no single best technique has been identified reflecting differing performance in different situations. Our aim was to quantify uncertainties associated with the application of 2 complimentary modelling techniques. Generalised linear mixed models (GLMM) and generalised additive mixed models (GAMM) were used to model the realised niche of ombrotrophic Sphagnum species in British peatlands. These models were then used to predict changes in Sphagnum cover between 2020 and 2050 based on projections of climate change and atmospheric deposition of nitrogen and sulphur. Over 90% of the variation in the GLMM predictions was due to niche model parameter uncertainty, dropping to 14% for the GAMM. After having covaried out other factors, average variation in predicted values of Sphagnum cover across UK peatlands was the next largest source of variation (8% for the GLMM and 86% for the GAMM). The better performance of the GAMM needs to be weighed against its tendency to overfit the training data. While our niche models are only a first approximation, we used them to undertake a preliminary evaluation of the relative importance of climate change and nitrogen and sulphur deposition and the geographic locations of the largest expected changes in Sphagnum cover. Predicted changes in cover were all small (generally <1% in an average 4 m2 unit area) but also highly uncertain. Peatlands expected to be most affected by climate change in combination with atmospheric pollution were Dartmoor, Brecon Beacons and the western Lake District.