790 resultados para Futures Price


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Uplands around the world are facing significant social, economic and environmental changes, and decision-makers need to better understand what the future may hold if they are to adapt and maintain upland goods and services. This paper draws together all major research comprising eight studies that have used scenarios to describe possible futures for UK uplands. The paper evaluates which scenarios are perceived by stakeholders to be most likely and desirable, and assesses the benefits and drawbacks of the scenario methods used in UK uplands to date. Stakeholders agreed that the most desirable and likely scenario would be a continuation of hill farming (albeit at reduced levels) based on cross-compliance with environmental measures. The least desirable scenario is a withdrawal of government financial support for hill farming. Although this was deemed by stakeholders to be the least likely scenario, the loss of government support warrants close attention due to its potential implications for the local economy. Stakeholders noted that the environmental implications of this scenario are much less clear-cut. As such, there is an urgent need to understand the full implications of this scenario, so that upland stakeholders can adequately prepare, and policy-makers can better evaluate the likely implications of different policy options. The paper concludes that in future, upland scenario research needs to: (1) better integrate in-depth and representative participation from stakeholders during both scenario development and evaluation; and (2) make more effective use of visualisation techniques and simulation models. (C) 2009 Elsevier Ltd. All rights reserved.

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The mechanism of action and properties of a solid-phase ligand library made of hexapeptides (combinatorial peptide ligand libraries or CPLL, for capturing the "hidden proteome", i.e. the low- and very low-abundance proteins Constituting the vast majority of species in any proteome. as applied to plant tissues, are reviewed here. Plant tissues are notoriously recalcitrant to protein extraction and to proteome analysis, Firstly, rigid plant cell walls need to be mechanically disrupted to release the cell content and, in addition to their poor protein yield, plant tissues are rich in proteases and oxidative enzymes, contain phenolic Compounds, starches, oils, pigments and secondary metabolites that massively contaminate protein extracts. In addition, complex matrices of polysaccharides, including large amount of anionic pectins, are present. All these species compete with the binding of proteins to the CPLL beads, impeding proper capture and identification I detection of low-abundance species. When properly pre-treated, plant tissue extracts are amenable to capture by the CPLL beads revealing thus many new species among them low-abundance proteins. Examples are given on the treatment of leaf proteins, of corn seed extracts and of exudate proteins (latex from Hevea brasiliensis). In all cases, the detection of unique gene products via CPLL Capture is at least twice that of control, untreated sample. (c) 2008 Elsevier B.V. All rights reserved.

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Formal and analytical models that contractors can use to assess and price project risk at the tender stage have proliferated in recent years. However, they are rarely used in practice. Introducing more models would, therefore, not necessarily help. A better understanding is needed of how contractors arrive at a bid price in practice, and how, and in what circumstances, risk apportionment actually influences pricing levels. More than 60 proposed risk models for contractors that are published in journals were examined and classified. Then exploratory interviews with five UK contractors and documentary analyses on how contractors price work generally and risk specifically were carried out to help in comparing the propositions from the literature to what contractors actually do. No comprehensive literature on the real bidding processes used in practice was found, and there is no evidence that pricing is systematic. Hence, systematic risk and pricing models for contractors may have no justifiable basis. Contractors process their bids through certain tendering gateways. They acknowledge the risk that they should price. However, the final settlement depends on a set of complex, micro-economic factors. Hence, risk accountability may be smaller than its true cost to the contractor. Risk apportionment occurs at three stages of the whole bid-pricing process. However, analytical approaches tend not to incorporate this, although they could.

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Previous studies of ignorance-driven decision-making have either analyzed when ignorance should prove advantageous on theoretical grounds, or else they have examined whether human behavior is consistent with an ignorance driven inference strategy (e.g., the recognition heuristic). The current study merges these research goals by examining whether – under conditions where ignorance driven inference might be expected – the type of advantages theoretical analyses predict are evident in human performance data. A single experiment shows that, when asked to make relative wealth judgments, participants reliably use recognition as a basis for their judgments. Their wealth judgments under these conditions are reliably more accurate when some of the target names are unknown than when participants recognize all the names (the “less-is-more effect”). these data are robust against a number of variations on the size of the pool from which participants have to choose and the nature of the wealth judgment.

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Little attention has been focussed on a precise definition and evaluation mechanism for project management risk specifically related to contractors. When bidding, contractors traditionally price risks using unsystematic approaches. The high business failure rate our industry records may indicate that the current unsystematic mechanisms contractors use for building up contingencies may be inadequate. The reluctance of some contractors to include a price for risk in their tenders when bidding for work competitively may also not be a useful approach. Here, instead, we first define the meaning of contractor contingency, and then we develop a facile quantitative technique that contractors can use to estimate a price for project risk. This model will help contractors analyse their exposure to project risks; and help them express the risk in monetary terms for management action. When bidding for work, they can decide how to allocate contingencies strategically in a way that balances risk and reward.