1000 resultados para Effective emittances


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This paper proposes a method for describing the distribution of observed temperatures on any day of the year such that the distribution and summary statistics of interest derived from the distribution vary smoothly through the year. The method removes the noise inherent in calculating summary statistics directly from the data thus easing comparisons of distributions and summary statistics between different periods. The method is demonstrated using daily effective temperatures (DET) derived from observations of temperature and wind speed at De Bilt, Holland. Distributions and summary statistics are obtained from 1985 to 2009 and compared to the period 1904–1984. A two-stage process first obtains parameters of a theoretical probability distribution, in this case the generalized extreme value (GEV) distribution, which describes the distribution of DET on any day of the year. Second, linear models describe seasonal variation in the parameters. Model predictions provide parameters of the GEV distribution, and therefore summary statistics, that vary smoothly through the year. There is evidence of an increasing mean temperature, a decrease in the variability in temperatures mainly in the winter and more positive skew, more warm days, in the summer. In the winter, the 2% point, the value below which 2% of observations are expected to fall, has risen by 1.2 °C, in the summer the 98% point has risen by 0.8 °C. Medians have risen by 1.1 and 0.9 °C in winter and summer, respectively. The method can be used to describe distributions of future climate projections and other climate variables. Further extensions to the methodology are suggested.

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Airborne lidar provides accurate height information of objects on the earth and has been recognized as a reliable and accurate surveying tool in many applications. In particular, lidar data offer vital and significant features for urban land-cover classification, which is an important task in urban land-use studies. In this article, we present an effective approach in which lidar data fused with its co-registered images (i.e. aerial colour images containing red, green and blue (RGB) bands and near-infrared (NIR) images) and other derived features are used effectively for accurate urban land-cover classification. The proposed approach begins with an initial classification performed by the Dempster–Shafer theory of evidence with a specifically designed basic probability assignment function. It outputs two results, i.e. the initial classification and pseudo-training samples, which are selected automatically according to the combined probability masses. Second, a support vector machine (SVM)-based probability estimator is adopted to compute the class conditional probability (CCP) for each pixel from the pseudo-training samples. Finally, a Markov random field (MRF) model is established to combine spatial contextual information into the classification. In this stage, the initial classification result and the CCP are exploited. An efficient belief propagation (EBP) algorithm is developed to search for the global minimum-energy solution for the maximum a posteriori (MAP)-MRF framework in which three techniques are developed to speed up the standard belief propagation (BP) algorithm. Lidar and its co-registered data acquired by Toposys Falcon II are used in performance tests. The experimental results prove that fusing the height data and optical images is particularly suited for urban land-cover classification. There is no training sample needed in the proposed approach, and the computational cost is relatively low. An average classification accuracy of 93.63% is achieved.

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This letter presents an effective approach for selection of appropriate terrain modeling methods in forming a digital elevation model (DEM). This approach achieves a balance between modeling accuracy and modeling speed. A terrain complexity index is defined to represent a terrain's complexity. A support vector machine (SVM) classifies terrain surfaces into either complex or moderate based on this index associated with the terrain elevation range. The classification result recommends a terrain modeling method for a given data set in accordance with its required modeling accuracy. Sample terrain data from the lunar surface are used in constructing an experimental data set. The results have shown that the terrain complexity index properly reflects the terrain complexity, and the SVM classifier derived from both the terrain complexity index and the terrain elevation range is more effective and generic than that designed from either the terrain complexity index or the terrain elevation range only. The statistical results have shown that the average classification accuracy of SVMs is about 84.3% ± 0.9% for terrain types (complex or moderate). For various ratios of complex and moderate terrain types in a selected data set, the DEM modeling speed increases up to 19.5% with given DEM accuracy.

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This study examines the relationship between community based organisations and marine and coastal resource management in the Western Indian Ocean Region.

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Soluble reactive phosphorus (SRP) plays a key role in eutrophication, a global problem decreasing habitat quality and in-stream biodiversity. Mitigation strategies are required to prevent SRP fluxes from exceeding critical levels, and must be robust in the face of potential changes in climate, land use and a myriad of other influences. To establish the longevity of these strategies it is therefore crucial to consider the sensitivity of catchments to multiple future stressors. This study evaluates how the water quality and hydrology of a major river system in the UK (the River Thames) respond to alterations in climate, land use and water resource allocations, and investigates how these changes impact the relative performance of management strategies over an 80-year period. In the River Thames, the relative contributions of SRP from diffuse and point sources vary seasonally. Diffuse sources of SRP from agriculture dominate during periods of high runoff, and point sources during low flow periods. SRP concentrations rose under any future scenario which either increased a) surface runoff or b) the area of cultivated land. Under these conditions, SRP was sourced from agriculture, and the most effective single mitigation measures were those which addressed diffuse SRP sources. Conversely, where future scenarios reduced flow e.g. during winters of reservoir construction, the significance of point source inputs increased, and mitigation measures addressing these issues became more effective. In catchments with multiple point and diffuse sources of SRP, an all-encompassing effective mitigation approach is difficult to achieve with a single strategy. In order to attain maximum efficiency, multiple strategies might therefore be employed at different times and locations, to target the variable nature of dominant SRP sources and pathways.

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The Richards equation has been widely used for simulating soil water movement. However, the take-up of agro-hydrological models using the basic theory of soil water flow for optimizing irrigation, fertilizer and pesticide practices is still low. This is partly due to the difficulties in obtaining accurate values for soil hydraulic properties at a field scale. Here, we use an inverse technique to deduce the effective soil hydraulic properties, based on measuring the changes in the distribution of soil water with depth in a fallow field over a long period, subject to natural rainfall and evaporation using a robust micro Genetic Algorithm. A new optimized function was constructed from the soil water contents at different depths, and the soil water at field capacity. The deduced soil water retention curve was approximately parallel but higher than that derived from published pedo-tranfer functions for a given soil pressure head. The water contents calculated from the deduced soil hydraulic properties were in good agreement with the measured values. The reliability of the deduced soil hydraulic properties was tested in reproducing data measured from an independent experiment on the same soil cropped with leek. The calculation of root water uptake took account for both soil water potential and root density distribution. Results show that the predictions of soil water contents at various depths agree fairly well with the measurements, indicating that the inverse analysis is an effective and reliable approach to estimate soil hydraulic properties, and thus permits the simulation of soil water dynamics in both cropped and fallow soils in the field accurately. (C) 2009 Elsevier B.V. All rights reserved.

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BACKGROUND: Reduction of vegetation height is recommended as a management strategy for controlling rodent pests of rice in South-east Asia, but there are limited field data to assess its effectiveness. The breeding biology of the main pest species of rodent in the Philippines, Rattus tanezumi, suggests that habitat manipulation in irrigated rice–coconut cropping systems may be an effective strategy to limit the quality and availability of their nesting habitat. The authors imposed a replicated manipulation of vegetation cover in adjacent coconut groves during a single rice-cropping season, and added artificial nest sites to facilitate capture and culling of young. RESULTS: Three trapping sessions in four rice fields (two treatments, two controls) adjacent to coconut groves led to the capture of 176 R. tanezumi, 12Rattus exulans and seven Chrotomysmindorensis individuals. There was no significant difference in overall abundance between crop stages or between treatments, and there was no treatment effect on damage to tillers or rice yield. Only two R. tanezumi were caught at the artificial nest sites. CONCLUSION: Habitat manipulation to reduce the quality of R. tanezumi nesting habitat adjacent to rice fields is not effective as a lone rodent management tool in rice–coconut cropping systems.

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Weak institutional development and information flows have constrained the extent to which the small-holder farming sector in developing countries can significantly drive growth and poverty reduction. Thisis despite widely implemented economic liberalisation policies focussing on market efficiency. Farmerorganisations are viewed as a potential means of addressing public and private institutional failure but thishas frequently been limited by inequalities in access to power and information. This article investigatestwo issues that have received little research attention to date: what role downward accountability plays inenabling farmer organisations to improve services and markets, and what influences the extent to whichdownward accountability is achieved. Kenya Tea Development Agency (KTDA), one of the largest farmerorganisations in the world (>400,000 farmers) is examined alongside wider literature. Mixed methodswere used including key informant interviews, and eight months of participant observation followedby a questionnaire survey. The article concludes that without effective downward accountability farmerorganisations can become characterised by institutions and mechanisms that favour elites, restrictedweak coordination and regulation, and manipulated information flows. This in turn reduces individuals’incentives to invest. If farmer organisations are to realise their potential as a means of enabling the small-holder sector to significantly contribute to economic growth and poverty reduction, policy and researchneeds to address key factors which influence accountability including: how to ensure initial processes information of farmer organisations establish appropriate structures and rules; strong state regulation toenhance corporate accountability; transparent information provision regarding actions of farmer organi-sation leaders; and the role independent non-government organisations can play. Consequently attentionneeds to focus on developing means of legitimising rights, building poor people’s capacity to challengeexclusion, and moving from rights to obligations regarding information provision.

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This letter has tested the canopy height profile (CHP) methodology as a way of effective leaf area index (LAIe) and vertical vegetation profile retrieval at a single-tree level. Waveform and discrete airborne LiDAR data from six swaths, as well as from the combined data of six swaths, were used to extract the LAIe of a single live Callitris glaucophylla tree. LAIe was extracted from raw waveform as an intermediate step in the CHP methodology, with two different vegetation-ground reflectance ratios. Discrete point LAIe estimates were derived from the gap probability using the following: 1) single ground returns and 2) all ground returns. LiDAR LAIe retrievals were subsequently compared to hemispherical photography estimates, yielding mean values within ±7% of the latter, depending on the method used. The CHP of a single dead Callitris glaucophylla tree, representing the distribution of vegetation material, was verified with a field profile manually reconstructed from convergent photographs taken with a fixed-focal-length camera. A binwise comparison of the two profiles showed very high correlation between the data reaching R2 of 0.86 for the CHP from combined swaths. Using a study-area-adjusted reflectance ratio improved the correlation between the profiles, but only marginally in comparison to using an arbitrary ratio of 0.5 for the laser wavelength of 1550 nm.

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25 years ago when the Durham conferences were in full swing, I presented results of investigations on language and behaviour in autism. I tentatively proposed that early language in autism might tell us about the cognitive skills of people with ASD and the behaviour might lead to greater understanding of which brain systems might be affected. In this presentation, I will update these topics and present a summary of other work I have been involved with in attempting to improve the lives of people with autism and their families. Data on three people with autism at the early stages of speech development showed an unusual pattern of learning colour and number names early. One possibility was that this skill represented a sign of weak central coherence – they only attended to one dimension. Colleagues of mine were equally puzzled so we tried to find out if my results could be replicated – they were not (see Schafer, Williams & Smith, 2014). Instead we found this pattern was also seen in Down Syndrome, but that early vocabulary in autism was associated with low Colorado Meaningfulness at least in comprehension. The Colorado Meaningfulness of a word is a measure of how many words can be associated with it and often involve extensive use of context. Our data suggest that the number of contexts in which a particular word can appear has a role in determining vocabulary in ASD which is consistent with the weak central coherence theory of autism. In the course of this work I also came across a group of young people with autism who appeared to have a written vocabulary but not a spoken one. It seems possible that print might be a medium of communication when speech is not. Repetitive behaviour in autism remains a mystery. We can use functional analysis to determine why the behaviour occurs, but a worryingly large percentage of behaviours are described as being internally driven or sensory reinforced. What does that mean in terms of brain activity – could it be system analogous to epilepsy, where brain activity becomes inappropriately synchronised? At the moment I cannot claim to have solved this problem, but if sensation is a driver then sensory interventions should make a difference. Data from a recent study will be presented to suggest that for some individuals this is the case. Social behaviour remains the key however, and it remains to be seen whether it is possible for social behaviour to be aided. One route that has potential is direct teaching of skills through drama and working with others who do not have social difficulties of the same type. The picture is complicated by changes in social skills with age and experience, but the failure of people with ASD to interact when in settings of social contact is little researched.

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It has been shown that CyMe4-BTPhen-functionalized silica-coated maghemite (c-Fe2O3) magnetic nanoparticles (MNPs) are capable of quantitative separation of Am(III) from Eu(III) from HNO3 solutions. These MNPs also show a small but significant selectivity for Am(III) over Cm(III) with a separation factor of around 2 in 4 M HNO3. The water molecule in the cavity of the BTPhen may also play an important part in the selectivity.

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A series of hydro- and organo-supergelators have been synthesised via coupling of simple bis aromaticureas via alkyl amide linkages. These bis amide-aromatic-ureas exhibited reduced critical gelator concentrations, improved gelator stability, mechanical and dye removal properties for potential use in water purification, in comparison to related bis aromatic-ureas. Systematic structure studies via variation of the bis amide-aromatic-urea linker length as well as functionalization of the terminal aromatic moieties have enabled control over the gel properties.