994 resultados para Distance sampling


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1  A set of 316 modern surface pollen samples, sampling all the alpine vegetation types that occur on the Tibetan Plateau, has been compiled and analysed. Between 82 and 92% of the pollen present in these samples is derived from only 28 major taxa. These 28 taxa include examples of both tree (AP) and herb (NAP) pollen types. 2  Most of the modern surface pollen samples accurately reflect the composition of the modern vegetation in the sampling region. However, airborne dust-trap pollen samples do not provide a reliable assessment of the modern vegetation. Dust-trap samples contain much higher percentages of tree pollen than non-dust-trap samples, and many of the taxa present are exotic. In the extremely windy environments of the Tibetan Plateau, contamination of dust-trap samples by long-distance transport of exotic pollen is a serious problem. 3  The most characteristic vegetation types present on the Tibetan Plateau are alpine meadows, steppe and desert. Non-arboreal pollen (NAP) therefore dominates the pollen samples in most regions. Percentages of arboreal pollen (AP) are high in samples from the southern and eastern Tibetan Plateau, where alpine forests are an important component of the vegetation. The relative importance of forest and non-forest vegetation across the Plateau clearly follows climatic gradients: forests occur on the southern and eastern margins of the Plateau, supported by the penetration of moisture-bearing airmasses associated with the Indian and Pacific summer monsoons; open, treeless vegetation is dominant in the interior and northern margins of the Plateau, far from these moisture sources. 4  The different types of non-forest vegetation are characterized by different modern pollen assemblages. Thus, alpine deserts are characterized by high percentages of Chenopodiaceae and Artemisia, with Ephedra and Nitraria. Alpine meadows are characterized by high percentages of Cyperaceae and Artemisia, with Ranunculaceae and Polygonaceae. Alpine steppe is characterized by high abundances of Artemisia, with Compositae, Cruciferae and Chenopodiaceae. Although Artemisia is a common component of all non-forest vegetation types on the Tibetan Plateau, the presence of other taxa makes it possible to discriminate between the different vegetation types. 5  The good agreement between modern vegetation and modern surface pollen samples across the Tibetan Plateau provides a measure of the reliability of using pollen data to reconstruct past vegetation patterns in non-forested areas.

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This contribution proposes a novel probability density function (PDF) estimation based over-sampling (PDFOS) approach for two-class imbalanced classification problems. The classical Parzen-window kernel function is adopted to estimate the PDF of the positive class. Then according to the estimated PDF, synthetic instances are generated as the additional training data. The essential concept is to re-balance the class distribution of the original imbalanced data set under the principle that synthetic data sample follows the same statistical properties. Based on the over-sampled training data, the radial basis function (RBF) classifier is constructed by applying the orthogonal forward selection procedure, in which the classifier’s structure and the parameters of RBF kernels are determined using a particle swarm optimisation algorithm based on the criterion of minimising the leave-one-out misclassification rate. The effectiveness of the proposed PDFOS approach is demonstrated by the empirical study on several imbalanced data sets.

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The purpose of this paper is to explore the implementation of online learning in distance educational delivery at Yellow Fields University (pseudonymous) in Sri Lanka. The implementation of online distance education at the University included the use of blended learning. The policy initiative to introduce online for distance education in Sri Lanka was guided by the expectation of cost reduction and the implementation was financed under the Distance Education Modernization Project. The paper presents one case study of a larger multiple case study research that employed an ethnographic research approach in investigating the impact of ICT on distance education in Sri Lanka. Documents, questionnaires and qualitative interviews were used for data collection. There was a significant positive relationship between ownership of computers and students’ ability to use computer for word processing, emailing and Web searching. The lack of access to computers and the Internet, the lack of infrastructure, low levels of computer literacy, the lack of local language content, and the lack of formal student support services at the University were found to be major barriers to implementing compulsory online activities at the University

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Monthly zonal mean climatologies of atmospheric measurements from satellite instruments can have biases due to the nonuniform sampling of the atmosphere by the instruments. We characterize potential sampling biases in stratospheric trace gas climatologies of the Stratospheric Processes and Their Role in Climate (SPARC) Data Initiative using chemical fields from a chemistry climate model simulation and sampling patterns from 16 satellite-borne instruments. The exercise is performed for the long-lived stratospheric trace gases O3 and H2O. Monthly sampling biases for O3 exceed 10% for many instruments in the high-latitude stratosphere and in the upper troposphere/lower stratosphere, while annual mean sampling biases reach values of up to 20% in the same regions for some instruments. Sampling biases for H2O are generally smaller than for O3, although still notable in the upper troposphere/lower stratosphere and Southern Hemisphere high latitudes. The most important mechanism leading to monthly sampling bias is nonuniform temporal sampling, i.e., the fact that for many instruments, monthly means are produced from measurements which span less than the full month in question. Similarly, annual mean sampling biases are well explained by nonuniformity in the month-to-month sampling by different instruments. Nonuniform sampling in latitude and longitude are shown to also lead to nonnegligible sampling biases, which are most relevant for climatologies which are otherwise free of biases due to nonuniform temporal sampling.

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Wild pollinators have been shown to enhance the pollination of Brassica napus(oilseed rape) and thus increase its market value. Several studies have previously shown that pollination services are greater in crops adjoining forest patches or other seminatural habitats than in crops completely surrounded by other crops. In this study, we investigated the specific importance of forest edges in providing potential pollinators in B. napus fields in two areas in France. Bees were caught with yellow pan traps at increasing distances from both warm and cold forest edges into B. napus fields during the blooming period. A total of 4594 individual bees, representing six families and 83 taxa, were collected. We found that both bee abundance and taxa richness were negatively affected by the distance from forest edge. However, responses varied between bee groups and edge orientations. The ITD (Inter-Tegular distance) of the species, a good proxy for bee foraging range, seems to limit how far the bees can travel from the forest edge. We found a greater abundance of cuckoo bees (Nomada spp.) of Andrena spp. and Andrena spp. males at forest edges, which we assume indicate suitable nesting sites, or at least mating sites, for some abundant Andrena species and their parasites (Fig. 1). Synthesis and Applications. This study provides one of the first examples in temperate ecosystems of how forest edges may actually act as a reservoir of potential pollinators and directly benefit agricultural crops by providing nesting or mating sites for important early spring pollinators. Policymakers and land managers should take forest edges into account and encourage their protection in the agricultural matrix to promote wild bees and their pollination services.

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Education, especially higher education, is considered vital for maintaining national and individual competitiveness in the global knowledge economy. Following the introduction of its “Free Education Policy” as early as 1947, Sri Lanka is now the best performer in basic education in the South Asian region, with a remarkable record in terms of high literacy rates and the achievement of universal primary education. However, access to tertiary education is a bottleneck, due to an acute shortage of university places. In an attempt to address this problem, the government of Sri Lanka has invested heavily in information and communications technologies (ICTs) for distance education. Although this has resulted in some improvement, the authors of this article identify several barriers which are still impeding successful participation for the majority of Sri Lankans wanting to study at tertiary level. These impediments include the lack of infrastructure/resources, low English language proficiency, weak digital literacy, poor quality of materials and insufficient provision of student support. In the hope that future implementations of ICT-enabled education programmes can avoid repeating the mistakes identified by their research in this Sri Lankan case, the authors conclude their paper with a list of suggested policy options.

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A pass of the AMPTE-UKS satellite through the low-latitude boundary layer (LLBL) at 8:30 MLT is studied in detail. The magnetosheath field is predominantly northward. It is shown that multiple transitions through part or all of the layer of antisunward flow lead to overestimation of both the voltage across this layer and its width. The voltage is estimated to be only about 3 kV and this implies that the full LLBL is about 1200 km thick, consistent with previous studies.

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A new class of parameter estimation algorithms is introduced for Gaussian process regression (GPR) models. It is shown that the integration of the GPR model with probability distance measures of (i) the integrated square error and (ii) Kullback–Leibler (K–L) divergence are analytically tractable. An efficient coordinate descent algorithm is proposed to iteratively estimate the kernel width using golden section search which includes a fast gradient descent algorithm as an inner loop to estimate the noise variance. Numerical examples are included to demonstrate the effectiveness of the new identification approaches.

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The high computational cost of calculating the radiative heating rates in numerical weather prediction (NWP) and climate models requires that calculations are made infrequently, leading to poor sampling of the fast-changing cloud field and a poor representation of the feedback that would occur. This paper presents two related schemes for improving the temporal sampling of the cloud field. Firstly, the ‘split time-stepping’ scheme takes advantage of the independent nature of the monochromatic calculations of the ‘correlated-k’ method to split the calculation into gaseous absorption terms that are highly dependent on changes in cloud (the optically thin terms) and those that are not (optically thick). The small number of optically thin terms can then be calculated more often to capture changes in the grey absorption and scattering associated with cloud droplets and ice crystals. Secondly, the ‘incremental time-stepping’ scheme uses a simple radiative transfer calculation using only one or two monochromatic calculations representing the optically thin part of the atmospheric spectrum. These are found to be sufficient to represent the heating rate increments caused by changes in the cloud field, which can then be added to the last full calculation of the radiation code. We test these schemes in an operational forecast model configuration and find a significant improvement is achieved, for a small computational cost, over the current scheme employed at the Met Office. The ‘incremental time-stepping’ scheme is recommended for operational use, along with a new scheme to correct the surface fluxes for the change in solar zenith angle between radiation calculations.

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Purpose – This paper aims to investigate the scale and drivers of cross-border real estate development in Western Europe and Central and Eastern Europe. Design/methodology/approach – Placing cross-border real estate development within the framework of foreign direct investment (FDI), conceptual complexities in characterizing the notional real estate developer are emphasized. Drawing upon a transaction database, this paper proxies cross-border real estate development flows with asset sales by developers. Findings – Much higher levels of market penetration by international real estate developers are found in the less mature markets of Central and Eastern Europe. Analysis suggests a complex range of determinants with physical distance remaining a consistent barrier to cross-border development flows. Originality/value – This analysis adds significant value in terms of understanding cross-border real estate development flows. In this study, a detailed examination of the issues based on a rigorous empirical analysis through gravity modelling is offered. The gravity framework is one of the most confirmed empirical regularities in international economics and commonly applied to trade, FDI, migration, foreign portfolio investment inter alia. This paper assesses the extent to which it provides useful insights into the pattern of cross-border real estate development flows.

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The EU Water Framework Directive (WFD) requires that the ecological and chemical status of water bodies in Europe should be assessed, and action taken where possible to ensure that at least "good" quality is attained in each case by 2015. This paper is concerned with the accuracy and precision with which chemical status in rivers can be measured given certain sampling strategies, and how this can be improved. High-frequency (hourly) chemical data from four rivers in southern England were subsampled to simulate different sampling strategies for four parameters used for WFD classification: dissolved phosphorus, dissolved oxygen, pH and water temperature. These data sub-sets were then used to calculate the WFD classification for each site. Monthly sampling was less precise than weekly sampling, but the effect on WFD classification depended on the closeness of the range of concentrations to the class boundaries. In some cases, monthly sampling for a year could result in the same water body being assigned to three or four of the WFD classes with 95% confidence, due to random sampling effects, whereas with weekly sampling this was one or two classes for the same cases. In the most extreme case, the same water body could have been assigned to any of the five WFD quality classes. Weekly sampling considerably reduces the uncertainties compared to monthly sampling. The width of the weekly sampled confidence intervals was about 33% that of the monthly for P species and pH, about 50% for dissolved oxygen, and about 67% for water temperature. For water temperature, which is assessed as the 98th percentile in the UK, monthly sampling biases the mean downwards by about 1 °C compared to the true value, due to problems of assessing high percentiles with limited data. Low-frequency measurements will generally be unsuitable for assessing standards expressed as high percentiles. Confining sampling to the working week compared to all 7 days made little difference, but a modest improvement in precision could be obtained by sampling at the same time of day within a 3 h time window, and this is recommended. For parameters with a strong diel variation, such as dissolved oxygen, the value obtained, and thus possibly the WFD classification, can depend markedly on when in the cycle the sample was taken. Specifying this in the sampling regime would be a straightforward way to improve precision, but there needs to be agreement about how best to characterise risk in different types of river. These results suggest that in some cases it will be difficult to assign accurate WFD chemical classes or to detect likely trends using current sampling regimes, even for these largely groundwater-fed rivers. A more critical approach to sampling is needed to ensure that management actions are appropriate and supported by data.

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We investigated the time course of anaphor resolution in children and whether this is modulated by individual differences in working memory and reading skill. The eye movements of 30 children (10-11 years) were monitored as they read short paragraphs in which (i) the semantic typicality of an antecedent and (ii) its distance in relation to an anaphor, were orthogonally manipulated. Children showed effects of distance and typicality on the anaphor itself, and also on the word to the right of the anaphor, suggesting that anaphoric processing begins immediately but continues after the eyes have left the anaphor. Furthermore, children showed no evidence of resolving anaphors in the most difficult condition (distant atypical antecedent), suggesting that anaphoric processing that is demanding may not occur online in children of this age. Finally, working memory capacity and reading comprehension skill affect the magnitude and time course of typicality and distance effects during anaphoric processing.

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This paper shows that value creation by multinational enterprises (MNEs) is the result of activities where geographic distance effects can be overcome. We submit that geographic distance has a relatively low impact on international research and development (R&D) investments, owing to the spiky nature of innovation, and to the unique ability of MNEs to absorb and transfer knowledge on a global scale. On the one hand, MNEs need to set up their labs as close as possible to specialized technology clusters where valuable knowledge is concentrated, largely regardless of distance from their home base. On the other, MNEs have historically developed technical and organizational competencies that enable them to transfer knowledge within their internal networks and across technology clusters at relatively low cost. Using data on R&D and manufacturing investments of 6320 firms in 59 countries, we find that geographic distance has a lower negative impact on the probability of setting up R&D than manufacturing plants. Furthermore, once measures of institutional proximity are accounted for, MNEs are equally likely to set up R&D labs in nearby or in more remote locations. This result is driven by MNEs based in Triad countries, whereas for non-Triad MNEs the effect of geographic distance on cross-border R&D is negative and significant.