45 resultados para 434
Resumo:
This paper introduces a method for simulating multivariate samples that have exact means, covariances, skewness and kurtosis. We introduce a new class of rectangular orthogonal matrix which is fundamental to the methodology and we call these matrices L matrices. They may be deterministic, parametric or data specific in nature. The target moments determine the L matrix then infinitely many random samples with the same exact moments may be generated by multiplying the L matrix by arbitrary random orthogonal matrices. This methodology is thus termed “ROM simulation”. Considering certain elementary types of random orthogonal matrices we demonstrate that they generate samples with different characteristics. ROM simulation has applications to many problems that are resolved using standard Monte Carlo methods. But no parametric assumptions are required (unless parametric L matrices are used) so there is no sampling error caused by the discrete approximation of a continuous distribution, which is a major source of error in standard Monte Carlo simulations. For illustration, we apply ROM simulation to determine the value-at-risk of a stock portfolio.
Resumo:
1. Wild bees are one of the most important groups of pollinators in the temperate zone. Therefore, population declines have potentially negative impacts for both crop and wildflower pollination. Although heavy metal pollution is recognized to be a problem affecting large parts of the European Union, we currently lack insights into the effects of heavy metals on wild bees. 2. We investigated whether heavy metal pollution is a potential threat to wild bee communities by comparing (i) species number, (ii) diversity and (iii) abundance as well as (iv) natural mortality of emerging bees along two independent gradients of heavy metal pollution, one at Olkusz (OLK), Poland and the other at Avonmouth (AVO), UK. We used standardized nesting traps to measure species richness and abundance of wild bees, and we recorded the heavy metal concentration in pollen collected by the red mason bee Osmia rufa as a measure of pollution. 3. The concentration of cadmium, lead and zinc in pollen collected by bees ranged from a background level in unpolluted sites [OLK: 1·3, 43·4, 99·8 (mg kg−1); AVO: 0·8, 42·0, 56·0 (mg kg−1), respectively] to a high level on sites in the vicinity of the OLK and AVO smelters [OLK: 6·7, 277·0, 440·1 (mg kg−1); AVO: 9·3, 356·2, 592·4 (mg kg−1), respectively]. 4. We found that with increasing heavy metal concentration, there was a steady decrease in the number, diversity and abundance of solitary, wild bees. In the most polluted sites, traps were empty or contained single occupants, whereas in unpolluted sites, the nesting traps collected from 4 to 5 species represented by up to ten individuals. Moreover, the proportion of dead individuals of the solitary bee Megachile ligniseca increased along the heavy metal pollution gradient at OLK from 0·2 in uncontaminated sites to 0·5 in sites with a high concentration of pollution. 5. Synthesis and applications. Our findings highlight the negative relationship between heavy metal pollution and populations of wild bees and suggest that increasing wild bee richness in highly contaminated areas will require special conservation strategies. These may include creating suitable nesting sites and sowing a mixture of flowering plants as well as installing artificial nests with wild bee cocoons in polluted areas. Applying protection plans to wild pollinating bee communities in heavy metal-contaminated areas will contribute to integrated land rehabilitation to minimize the impact of pollution on the environment.
Resumo:
This paper examines two hydrochemical time-series derived from stream samples taken in the Upper Hafren catchment, Plynlimon, Wales. One time-series comprises data collected at 7-hour intervals over 22 months (Neal et al., submitted, this issue), while the other is based on weekly sampling over 20 years. A subset of determinands: aluminium, calcium, chloride, conductivity, dissolved organic carbon, iron, nitrate, pH, silicon and sulphate are examined within a framework of non-stationary time-series analysis to identify determinand trends, seasonality and short-term dynamics. The results demonstrate that both long-term and high-frequency monitoring provide valuable and unique insights into the hydrochemistry of a catchment. The long-term data allowed analysis of long-termtrends, demonstrating continued increases in DOC concentrations accompanied by declining SO4 concentrations within the stream, and provided new insights into the changing amplitude and phase of the seasonality of the determinands such as DOC and Al. Additionally, these data proved invaluable for placing the short-term variability demonstrated within the high-frequency data within context. The 7-hour data highlighted complex diurnal cycles for NO3, Ca and Fe with cycles displaying changes in phase and amplitude on a seasonal basis. The high-frequency data also demonstrated the need to consider the impact that the time of sample collection can have on the summary statistics of the data and also that sampling during the hours of darkness provides additional hydrochemical information for determinands which exhibit pronounced diurnal variability. Moving forward, this research demonstrates the need for both long-term and high-frequency monitoring to facilitate a full and accurate understanding of catchment hydrochemical dynamics.
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A new drug delivery method for infants is presented which incorporates an active pharmaceutical ingredient (API)-loaded insert into a nipple shield delivery system (NSDS). The API is released directly into milk during breastfeeding. This study investigates the feasibility of using the NSDS to deliver the microbicide sodium dodecyl sulfate (SDS), with the goal of preventing mother-to-child transmission (MTCT) of HIV during breastfeeding in low-resource settings, when there is no safer alternative for the infant but to breastfeed. SDS has been previously shown to effectively inactivate HIV in human milk. An apparatus was developed to simulate milk flow through and drug release from a NSDS. Using this apparatus milk was pulsed through a prototype device containing a non-woven fiber insert impregnated with SDS and the microbicide was rapidly released. The total SDS release from inserts ranged from 70 to 100% of the average 0.07 g load within 50 ml (the volume of a typical breastfeed). Human milk spiked with H9/HIVIIIB cells was also passed through the same set-up. Greater than 99% reduction of cell-associated HIV infectivity was achieved in the first 10 ml of milk. This proof of concept study demonstrates efficient drug delivery to breastfeeding infants is achievable using the NSDS.
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This study compares two sets of measurements of the composition of bulk precipitation and throughfall at a site in southern England with a 20-year gap between them. During this time, SO2 emissions from the UK fell by 82%, NOx emissions by 35% and NH3 emissions by 7%. These reductions were partly reflected in bulk precipitation, with deposition reductions of 56% in SO4,38% in NO3, 32% in NH4, and 73% in H+. In throughfall under Scots pine, the effects were more dramatic, with an 89% reduction in SO4 deposition and a 98% reduction in H+ deposition. The mean pH under these trees increased from 2.85 to 4.30. Nitrate and ammonium deposition in throughfall increased slightly, however. In the earlier period, the Scots pines were unable to neutralise the high flux of acidity associated with sulphur deposition, even though this was not a highly polluted part of the UK, and deciduous trees (oak and birch) were only able to neutralise it in summer when the leaves were present. In the later period, the sulphur flux had reduced to the point where the acidity could be neutralised by all species — the neutralisation mechanism is thus likely to be largely leaching of base cations and buffering substances from the foliage. The high fluxes are partly due to the fact that these are 60–80 year old trees growing in an open forest structure. The increase in NO3 and NH4 in throughfall in spite of decreased deposition seems likely due to a decrease in foliar uptake, perhaps due to the increasing nitrogen saturation of the catchment soils. These changes may increase the rate of soil microbial activity as nitrogen increases and acidity declines, with consequent effects on water quality of the catchment drainage stream.
Resumo:
A two-phase system composed by a leach bed and a methanogenic reactor was modified for the first time to improve volumetric substrate degradation and methane yields from a complex substrate (maize; Zea mays). The system, which was operated for consecutive feed cycles of different durations for 120 days, was highly flexible and its performance improved by altering operational conditions. Daily substrate degradation was higher the shorter the feed cycle, reaching 8.5 g TSdestroyed d�1 (7-day feed cycle) but the overall substrate degradation was higher by up to 55% when longer feed cycles (14 and 28 days) were applied. The same occurred with volumetric methane yields, reaching 0.839 m3 (m3)�1 d�1. The system performed better than others on specific methane yields, reaching 0.434 m3 kg�1 TSadded, in the 14-day and 28-day systems. The UASB and AF designs performed similarly as second stage reactors on methane yields, SCOD and VFA removal efficiencies.
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This paper provides an introduction to the Special Issue on “Climate Change and Coupling of Macronutrient Cycles along the Atmospheric, Terrestrial, Freshwater and Estuarine Continuum”, dedicated to Colin Neal on his retirement. It is not intended to be a review of this vast subject, but an attempt to synthesize some of the major findings from the 22 contributions to the Special Issue in the context of what is already known. The major research challenges involved in understanding coupled macronutrient cycles in these environmental media are highlighted, and the difficulties of making credible predictions of the effects of climate change are discussed. Of particular concern is the possibility of interactions which will enhance greenhouse gas concentrations and provide positive feedback to global warming.
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When performing data fusion, one often measures where targets were and then wishes to deduce where targets currently are. There has been recent research on the processing of such out-of-sequence data. This research has culminated in the development of a number of algorithms for solving the associated tracking problem. This paper reviews these different approaches in a common Bayesian framework and proposes an architecture that orthogonalises the data association and out-of-sequence problems such that any combination of solutions to these two problems can be used together. The emphasis is not on advocating one approach over another on the basis of computational expense, but rather on understanding the relationships among the algorithms so that any approximations made are explicit. Results for a multi-sensor scenario involving out-of-sequence data association are used to illustrate the utility of this approach in a specific context.