133 resultados para Anaconda Reduction Works


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Despite a number of papers that discuss the advantages of increased size on risk levels in real estate portfolios there is remarkably little empirical evidence based on actual portfolios. The objective of this paper is to remedy this deficiency by examining the portfolio risk of a large sample of actual property data over the period 1981 to 1996. The results show that all that can be said is that portfolios of properties of a large size, on the average, tend to have lower risks than small sized portfolios. More importantly portfolios of a few properties can have very high or very low risk.

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This paper introduces new insights into the hydrochemical functioning of lowland river systems using field-based spectrophotometric and electrode technologies. The streamwater concentrations of nitrogen species and phosphorus fractions were measured at hourly intervals on a continuous basis at two contrasting sites on tributaries of the River Thames – one draining a rural catchment, the River Enborne, and one draining a more urban system, The Cut. The measurements complement those from an existing network of multi-parameter water quality sondes maintained across the Thames catchment and weekly monitoring based on grab samples. The results of the sub-daily monitoring show that streamwater phosphorus concentrations display highly complex dynamics under storm conditions dependent on the antecedent catchment wetness, and that diurnal phosphorus and nitrogen cycles occur under low flow conditions. The diurnal patterns highlight the dominance of sewage inputs in controlling the streamwater phosphorus and nitrogen concentrations at low flows, even at a distance of 7 km from the nearest sewage treatment works in the rural River Enborne. The time of sample collection is important when judging water quality against ecological thresholds or standards. An exhaustion of the supply of phosphorus from diffuse and multiple septic tank sources during storm events was evident and load estimation was not improved by sub-daily monitoring beyond that achieved by daily sampling because of the eventual reduction in the phosphorus mass entering the stream during events. The results highlight the utility of sub-daily water quality measurements and the discussion considers the practicalities and challenges of in situ, sub-daily monitoring.

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This paper presents the development of an export coefficient model to characterise the rates and sources of P export from land to water in four reservoir systems located in a semi-arid rural region in southern of Portugal. The model was developed to enable effective management of these important water resource systems under the EU Water Framework Directive. This is the first time such an approach has been fully adapted for the semi-arid systems typical of Mediterranean Europe. The sources of P loading delivered to each reservoir from its catchment were determined and scenario analysis was undertaken to predict the likely impact of catchment management strategies on the scale of rate of P loading delivered to each water body from its catchment. The results indicate the importance of farming and sewage treatment works/collective septic tanks discharges as the main contributors to the total diffuse and point source P loading delivered to the reservoirs, respectively. A reduction in the total P loading for all study areas would require control of farming practices and more efficient removal of P from human wastes prior to discharge to surface waters. The scenario analysis indicates a strategy based solely on reducing the agricultural P surplus may result in only a slow improvement in water quality, which would be unlikely to support the generation of good ecological status in reservoirs. The model application indicates that a reduction of P-inputs to the reservoirs should first focus on reducing P loading from sewage effluent discharges through the introduction of tertiary treatment (P-stripping) in all major residential areas. The fully calibrated export coefficient modelling approach transferred well to semi-arid regions, with the only significant limitation being the availability of suitable input data to drive the model. Further studies using this approach in semi-arid catchments are now needed to increase the knowledge of nutrient export behaviours in semi-arid regions.

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The feasibility of halving greenhousegasemissions from hotels by 2030 has been studied as part of the Carbon Vision Buildings Programme. The aim of that programme was to study ways of reducing emissions from the existing stock because it will be responsible for the majority of building emissions over the next few decades. The work was carried out using detailed computer simulation using the ESP-r tool. Two hotels were studied, one older and converted and the other newer and purpose-built, with the aim of representing the most common UKhotel types. The effects were studied of interventions expected to be available in 2030 including fabric improvements, HVAC changes, lighting and appliance improvements and renewable energy generation. The main finding was that it is technically feasible to reduce emissions by 50% without compromising guest comfort. Ranking of the interventions was problematical for several reasons including interdependence and the impacts on boiler sizing of large reductions in the heating load

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The issue of diversification in direct real estate investment portfolios has been widely studied in academic and practitioner literature. Most work, however, has been done using either partially aggregated data or data for small samples of individual properties. This paper reports results from tests of both risk reduction and diversification that use the records of 10,000+ UK properties tracked by Investment Property Databank. It provides, for the first time, robust estimates of the diversification gains attainable given the returns, risks and cross‐correlations across the individual properties available to fund managers. The results quantify the number of assets and amount of money needed to construct both ‘balanced’ and ‘specialist’ property portfolios by direct investment. Target numbers will vary according to the objectives of investors and the degree to which tracking error is tolerated. The top‐level results are consistent with previous work, showing that a large measure of risk reduction can be achieved with portfolios of 30–50 properties, but full diversification of specific risk can only be achieved in very large portfolios. However, the paper extends previous work by demonstrating on a single, large dataset the implications of different methods of calculating risk reduction, and also by showing more disaggregated results relevant to the construction of specialist, sector‐focussed funds.

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Olive oil, an important component of the Mediterranean diet, is rich in polyphenols and is known to possess positive health effects relative to other dietary fats. In addition, the leaves of the olive plant (Olea europaea) contain similar phenolics (oleuropein, luteolin-7-glucoside, apigenin-7-glucoside, verbascoside and hydroxytyrosol) to those of olives and olive oil, although at higher concentrations. For example, the most abundant is the secoiridoid, oleuropein, representing 1–14% of olive leaf weight vs. 0.005–0.12% in olive oil. Although currently considered a waste product of the olive oil industry, recent research has suggested beneficial effects of phenolic-rich olive leaf extracts (OLE) in modifying cardiovascular risk biomarkers such as blood pressure, hyperglycaemia, oxidative stress and inflammation, as well as improving vascular function and lipid profiles. Despite this, data regarding the biological actions of OLE has mostly derived from animal, in vitro and ex vivo studies, with limited evidence deriving from human trials. Although the absorption and metabolism of olive oil phenolics has been investigated, less is known about the bioavailability of phenolics from OLE, limiting the interpretation of existing in vitro and ex vivo data. The current review will begin by describing the phenolic composition of olive leaves in comparison with that of the better studied olive oil. It will then review the effects of OLE on cardiovascular risk factors, covering both animal and human studies and will end by considering potential mechanisms of action

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With the advent of mass digitization projects, such as the Google Book Search, a peculiar shift has occurred in the way that copyright works are dealt with. Contrary to what has so far been the case, works are turned into machine-readable data to be automatically processed for various purposes without the expression of works being displayed to the public. In the Google Book Settlement Agreement, this new kind of usage is referred to as ‘non-display uses’ of digital works. The legitimacy of these uses has not yet been tested by Courts and does not comfortably fit in the current copyright doctrine, plainly because the works are not used as works but as something else, namely as data. Since non-display uses may prove to be a very lucrative market in the near future, with the potential to affect the way people use copyright works, we examine non-display uses under the prism of copyright principles to determine the boundaries of their legitimacy. Through this examination, we provide a categorization of the activities carried out under the heading of ‘non-display uses’, we examine their lawfulness under the current copyright doctrine and approach the phenomenon from the spectrum of data protection law that could apply, by analogy, to the use of copyright works as processable data.

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This article explores the contribution that artisanal and small-scale mining (ASM) makes to poverty reduction in Tanzania, based on data on gold and diamond mining in Mwanza Region. The evidence suggests that people working in mining or related services are less likely to be in poverty than those with other occupations. However, the picture is complex; while mining income can help reduce poverty and provide a buffer from livelihood shocks, peoples inability to obtain a formal mineral claim, or to effectively exploit their claims, contributes to insecurity. This is reinforced by a context in which ASM is peripheral to large-scale mining interests, is only gradually being addressed within national poverty reduction policies, and is segregated from district-level planning.

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In Sub-Saharan Africa (SSA) the technological advances of the Green Revolution (GR) have not been very successful. However, the efforts being made to re-introduce the revolution call for more socio-economic research into the adoption and the effects of the new technologies. The paper discusses an investigation on the effects of GR technology adoption on poverty among households in Ghana. Maximum likelihood estimation of a poverty model within the framework of Heckman's two stage method of correcting for sample selection was employed. Technology adoption was found to have positive effects in reducing poverty. Other factors that reduce poverty include education, credit, durable assets, living in the forest belt and in the south of the country. Technology adoption itself was also facilitated by education, credit, non-farm income and household labour supply as well as living in urban centres. Inarguably, technology adoption can be taken seriously by increasing the levels of complementary inputs such as credit, extension services and infrastructure. Above all, the fundamental problems of illiteracy, inequality and lack of effective markets must be addressed through increasing the levels of formal and non-formal education, equitable distribution of the 'national cake' and a more pragmatic management of the ongoing Structural Adjustment Programme.

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It is known that the empirical orthogonal function method is unable to detect possible nonlinear structure in climate data. Here, isometric feature mapping (Isomap), as a tool for nonlinear dimensionality reduction, is applied to 1958–2001 ERA-40 sea-level pressure anomalies to study nonlinearity of the Asian summer monsoon intraseasonal variability. Using the leading two Isomap time series, the probability density function is shown to be bimodal. A two-dimensional bivariate Gaussian mixture model is then applied to identify the monsoon phases, the obtained regimes representing enhanced and suppressed phases, respectively. The relationship with the large-scale seasonal mean monsoon indicates that the frequency of monsoon regime occurrence is significantly perturbed in agreement with conceptual ideas, with preference for enhanced convection on intraseasonal time scales during large-scale strong monsoons. Trend analysis suggests a shift in concentration of monsoon convection, with less emphasis on South Asia and more on the East China Sea.

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Delayed ettringite formation (DEF) is a chemical reaction with proven damaging effects on hydrated concrete. Ettringite crystals can cause cracks and their widening due to pressure on cracked walls caused by the positive volume difference in the reaction. Concrete may show improvements in strength at early ages but further growth of cracks causes widening and spreading through the concrete structure. In this study, finely dispersed crystallization nuclei achieved by adding air-entraining agent (AEA) and short vibration of specimens is presented as the main prerequisite for reducing DEF-induced deterioration of hydrated concrete. The study presents the method and mechanism for obtaining the required nucleation. Controlling long-term DEF by providing AEA-induced crystallisation nuclei, prevented excessive and rapid initial strength improvements, and resulted in a slight increase of compressive strength of fine grained concrete with only marginally lower density.

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Approximate Bayesian computation (ABC) methods make use of comparisons between simulated and observed summary statistics to overcome the problem of computationally intractable likelihood functions. As the practical implementation of ABC requires computations based on vectors of summary statistics, rather than full data sets, a central question is how to derive low-dimensional summary statistics from the observed data with minimal loss of information. In this article we provide a comprehensive review and comparison of the performance of the principal methods of dimension reduction proposed in the ABC literature. The methods are split into three nonmutually exclusive classes consisting of best subset selection methods, projection techniques and regularization. In addition, we introduce two new methods of dimension reduction. The first is a best subset selection method based on Akaike and Bayesian information criteria, and the second uses ridge regression as a regularization procedure. We illustrate the performance of these dimension reduction techniques through the analysis of three challenging models and data sets.