33 resultados para 356

em CentAUR: Central Archive University of Reading - UK


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Many modelling studies examine the impacts of climate change on crop yield, but few explore either the underlying bio-physical processes, or the uncertainty inherent in the parameterisation of crop growth and development. We used a perturbed-parameter crop modelling method together with a regional climate model (PRECIS) driven by the 2071-2100 SRES A2 emissions scenario in order to examine processes and uncertainties in yield simulation. Crop simulations used the groundnut (i.e. peanut; Arachis hypogaea L.) version of the General Large-Area Model for annual crops (GLAM). Two sets of GLAM simulations were carried out: control simulations and fixed-duration simulations, where the impact of mean temperature on crop development rate was removed. Model results were compared to sensitivity tests using two other crop models of differing levels of complexity: CROPGRO, and the groundnut model of Hammer et al. [Hammer, G.L., Sinclair, T.R., Boote, K.J., Wright, G.C., Meinke, H., and Bell, M.J., 1995, A peanut simulation model: I. Model development and testing. Agron. J. 87, 1085-1093]. GLAM simulations were particularly sensitive to two processes. First, elevated vapour pressure deficit (VPD) consistently reduced yield. The same result was seen in some simulations using both other crop models. Second, GLAM crop duration was longer, and yield greater, when the optimal temperature for the rate of development was exceeded. Yield increases were also seen in one other crop model. Overall, the models differed in their response to super-optimal temperatures, and that difference increased with mean temperature; percentage changes in yield between current and future climates were as diverse as -50% and over +30% for the same input data. The first process has been observed in many crop experiments, whilst the second has not. Thus, we conclude that there is a need for: (i) more process-based modelling studies of the impact of VPD on assimilation, and (ii) more experimental studies at super-optimal temperatures. Using the GLAM results, central values and uncertainty ranges were projected for mean 2071-2100 crop yields in India. In the fixed-duration simulations, ensemble mean yields mostly rose by 10-30%. The full ensemble range was greater than this mean change (20-60% over most of India). In the control simulations, yield stimulation by elevated CO2 was more than offset by other processes-principally accelerated crop development rates at elevated, but sub-optimal, mean temperatures. Hence, the quantification of uncertainty can facilitate relatively robust indications of the likely sign of crop yield changes in future climates. (C) 2007 Elsevier B.V. All rights reserved.

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The simulated annealing approach to structure solution from powder diffraction data, as implemented in the DASH program, is easily amenable to parallelization at the individual run level. Very large scale increases in speed of execution can therefore be achieved by distributing individual DASH runs over a network of computers. The GDASH program achieves this by packaging DASH in a form that enables it to run under the Univa UD Grid MP system, which harnesses networks of existing computing resources to perform calculations.

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With 25% of the UK population predicted to be obese by 2010, the costs to individuals and society are set to rise. Due to the extra economic and social pressures obesity causes, there is an increasing need to understand what motivates and prevents consumers from eating a healthy diet so as to be able to tailor policy interventions to specific groups in society. In so doing, it is important to explore potential variations in attitudes, motivation and behaviour as a function of age and gender. Both demographic factors are easily distinguished within society and a future intervention study which targets either, or both, of these would likely be both feasible and cost-effective for policy makers. As part of a preliminary study, six focus groups (total n = 43) were conducted at the University of Reading in November 2006, with groups segmented on the basis of age and gender. In order to gather more sensitive information, participants were also asked to fill out a short anonymous questionnaire before each focus group began, relating to healthy eating, alcohol consumption and body dissatisfaction. Making use of thematic content analysis, results suggested that most participants were aware of the type of foods that contribute to a healthy diet and the importance of achieving a healthy balance within a diet. However, they believed that healthy eating messages were often conflicting, and were uncertain about where to find information on the topic. Participants believed that the family has an important role in educating children about eating habits. Despite these similarities, there were a number of key differences among the groups in terms of their reasons for making food choices. Older participants (60+ years old) were more likely to make food choices based on health considerations. Participants between the ages of 18–30 were less concerned with this link, and instead focused on issues of food preparation and knowledge, prices and time. Younger female participants said they had more energy when they ate healthier diets; however, very often their food choices related to concern with their appearance. Older female participants also expressed this concern within the questionnaire, rather than in the group discussions. Overall, these results suggest that consumer motivations for healthy eating are diverse and that this must be considered by government, retailers and food producers.

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Statistical approaches have been applied to examine amino acid pairing preferences within parallel beta-sheets. The main chain hydrogen bonding pattern in parallel beta-sheets means that, for each residue pair, only one of the residues is involved in main chain hydrogen bonding with the strand containing the partner residue. We call this the hydrogen bonded (HB) residue and the partner residue the non-hydrogen bonded (nHB) residue, and differentiate between the favorability of a pair and that of its reverse pair, e.g. Asn(HB)-Thr(nHB)versus Thr(HB)-Asn(nHB). Significantly (p < or = 0.000001) favoured pairings were rationalised using stereochemical arguments. For instance, Asn(HB)-Thr(nHB) and Arg(HB)-Thr(nHB) were favoured pairs, where the residues adopted favoured chi1 rotamer positions that allowed side-chain interactions to occur. In contrast, Thr(HB)-Asn(nHB) and Thr(HB)-Arg(nHB) were not significantly favoured, and could only form side-chain interactions if the residues involved adopted less favourable chi1 conformations. The favourability of hydrophobic pairs e.g. Ile(HB)-Ile(nHB), Val(HB)-Val(nHB) and Leu(HB)-Ile(nHB) was explained by the residues adopting their most preferred chi1 and chi2 conformations, which enabled them to form nested arrangements. Cysteine-cysteine pairs are significantly favoured, although these do not form intrasheet disulphide bridges. Interactions between positively and negatively charged residues were asymmetrically preferred: those with the negatively charged residue at the HB position were more favoured. This trend was accounted for by the presence of general electrostatic interactions, which, based on analysis of distances between charged atoms, were likely to be stronger when the negatively charged residue is the HB partner. The Arg(HB)-Asp(nHB) interaction was an exception to this trend and its favorability was rationalised by the formation of specific side-chain interactions. This research provides rules that could be applied to protein structure prediction, comparative modelling and protein engineering and design. The methods used to analyse the pairing preferences are automated and detailed results are available (http://www.rubic.rdg.ac.uk/betapairprefsparallel/).

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Statistical approaches have been applied to examine amino acid pairing preferences within parallel beta-sheets. The main chain hydrogen bonding pattern in parallel beta-sheets means that, for each residue pair, only one of the residues is involved in main chain hydrogen bonding with the strand containing the partner residue. We call this the hydrogen bonded (HB) residue and the partner residue the non-hydrogen bonded (nHB) residue, and differentiate between the favourability of a pair and that of its reverse pair, e.g. Asn(HB)-Thr(nHB) versus Thr(HB)-Asn(nHB). Significantly (p <= 0.000001) favoured pairings were rationalised using stereochemical arguments. For instance, Asn(HB)-Thr(nHB) and Arg(HB)-Thr(nHB) were favoured pairs, where the residues adopted favoured chi(1) rotamer positions that allowed side-chain interactions to occur. In contrast, Thr(HB)-Asn(nHB) and Thr(HB)-Arg(nHB) were not significantly favoured, and could only form side-chain interactions if the residues involved adopted less favourable chi(1) conformations. The favourability of hydrophobic pairs e.g. Ile(HB)-Ile(nHB), Val(HB)-Val(nHB) and Leu(HB)-Ile(nHB) was explained by the residues adopting their most preferred chi(1) and chi(2) conformations, which enabled them to form nested arrangements. Cysteine-cysteine pairs are significantly favoured, although these do not form intrasheet disulphide bridges. Interactions between positively and negatively charged residues were asymmetrically preferred: those with the negatively charged residue at the HB position were more favoured. This trend was accounted for by the presence of general electrostatic interactions, which, based on analysis of distances between charged atoms, were likely to be stronger when the negatively charged residue is the HB partner. The Arg(HB)-Asp(nHB) interaction was an exception to this trend and its favourability was rationalised by the formation of specific side-chain interactions. This research provides rules that could be applied to protein structure prediction, comparative modelling and protein engineering and design. The methods used to analyse the pairing preferences are automated and detailed results are available (http:// www.rubic.rdg.ac.uk/betapairprefsparallel/). (c) 2005 Elsevier Ltd. All rights reserved.

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The knowledge economy offers opportunity to a broad and diverse community of information systems users to efficiently gain information and know-how for improving qualifications and enhancing productivity in the work place. Such demand will continue and users will frequently require optimised and personalised information content. The advancement of information technology and the wide dissemination of information endorse individual users when constructing new knowledge from their experience in the real-world context. However, a design of personalised information provision is challenging because users’ requirements and information provision specifications are complex in their representation. The existing methods are not able to effectively support this analysis process. This paper presents a mechanism which can holistically facilitate customisation of information provision based on individual users’ goals, level of knowledge and cognitive styles preferences. An ontology model with embedded norms represents the domain knowledge of information provision in a specific context where users’ needs can be articulated and represented in a user profile. These formal requirements can then be transformed onto information provision specifications which are used to discover suitable information content from repositories and pedagogically organise the selected content to meet the users’ needs. The method is provided with adaptability which enables an appropriate response to changes in users’ requirements during the process of acquiring knowledge and skills.

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Evidence is presented of widespread changes in structure and species composition between the 1980s and 2003–2004 from surveys of 249 British broadleaved woodlands. Structural components examined include canopy cover, vertical vegetation profiles, field-layer cover and deadwood abundance. Woods were located in 13 geographical localities and the patterns of change were examined for each locality as well as across all woods. Changes were not uniform throughout the localities; overall, there were significant decreases in canopy cover and increases in sub-canopy (2–10 m) cover. Changes in 0.5–2 m vegetation cover showed strong geographic patterns, increasing in western localities, but declining or showing no change in eastern localities. There were significant increases in canopy ash Fraxinus excelsior and decreases in oak Quercus robur/petraea. Shrub layer ash and honeysuckle Lonicera periclymenum increased while birch Betula spp. hawthorn Crataegus monogyna and hazel Corylus avellana declined. Within the field layer, both bracken Pteridium aquilinum and herbs increased. Overall, deadwood generally increased. Changes were consistent with reductions in active woodland management and changes in grazing and browsing pressure. These findings have important implications for sustainable active management of British broadleaved woodlands to meet silvicultural and biodiversity objectives.

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The kinetics of the reactions of the atoms O(P-3), S(P-3), Se(P-3), and Te((3)p) with a series of alkenes are examined for correlations relating the logarithms of the rate coefficients to the energies of the highest occupied molecular orbitals (HOMOs) of the alkenes. These correlations may be employed to predict rate coefficients from the calculated HOMO energy of any other alkene of interest. The rate coefficients obtained from the correlations were used to formulate structure-activity relations (SARs) for reactions of O((3)p), S(P-3), Se (P-3), and Te((3)p) with alkenes. A comparison of the values predicted by both the correlations and the SARs with experimental data where they exist allowed us to assess the reliability of our method. We demonstrate the applicability of perturbation frontier molecular orbital theory to gas-phase reactions of these atoms with alkenes. The correlations are apparently not applicable to reactions of C(P-3), Si(P-3), N(S-4), and Al(P-2) atoms with alkenes, a conclusion that could be explained in terms of a different mechanism for reaction of these atoms.

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It is generally assumed that the variability of neuronal morphology has an important effect on both the connectivity and the activity of the nervous system, but this effect has not been thoroughly investigated. Neuroanatomical archives represent a crucial tool to explore structure–function relationships in the brain. We are developing computational tools to describe, generate, store and render large sets of three–dimensional neuronal structures in a format that is compact, quantitative, accurate and readily accessible to the neuroscientist. Single–cell neuroanatomy can be characterized quantitatively at several levels. In computer–aided neuronal tracing files, a dendritic tree is described as a series of cylinders, each represented by diameter, spatial coordinates and the connectivity to other cylinders in the tree. This ‘Cartesian’ description constitutes a completely accurate mapping of dendritic morphology but it bears little intuitive information for the neuroscientist. In contrast, a classical neuroanatomical analysis characterizes neuronal dendrites on the basis of the statistical distributions of morphological parameters, e.g. maximum branching order or bifurcation asymmetry. This description is intuitively more accessible, but it only yields information on the collective anatomy of a group of dendrites, i.e. it is not complete enough to provide a precise ‘blueprint’ of the original data. We are adopting a third, intermediate level of description, which consists of the algorithmic generation of neuronal structures within a certain morphological class based on a set of ‘fundamental’, measured parameters. This description is as intuitive as a classical neuroanatomical analysis (parameters have an intuitive interpretation), and as complete as a Cartesian file (the algorithms generate and display complete neurons). The advantages of the algorithmic description of neuronal structure are immense. If an algorithm can measure the values of a handful of parameters from an experimental database and generate virtual neurons whose anatomy is statistically indistinguishable from that of their real counterparts, a great deal of data compression and amplification can be achieved. Data compression results from the quantitative and complete description of thousands of neurons with a handful of statistical distributions of parameters. Data amplification is possible because, from a set of experimental neurons, many more virtual analogues can be generated. This approach could allow one, in principle, to create and store a neuroanatomical database containing data for an entire human brain in a personal computer. We are using two programs, L–NEURON and ARBORVITAE, to investigate systematically the potential of several different algorithms for the generation of virtual neurons. Using these programs, we have generated anatomically plausible virtual neurons for several morphological classes, including guinea pig cerebellar Purkinje cells and cat spinal cord motor neurons. These virtual neurons are stored in an online electronic archive of dendritic morphology. This process highlights the potential and the limitations of the ‘computational neuroanatomy’ strategy for neuroscience databases.

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This paper presents a study that identifies a stakeholder-defined concept of Corporate Responsibility (CR) in the context of a UK financial service organisation in the immediate pre-credit crunch era. From qualitative analysis of interviews and focus groups with employees and customers, we identify, in a wide-ranging stakeholder-defined concept of CR, six themes that together imply two necessary conditions for a firm to be regarded as responsible— both corporate actions and character must be consonant with CR. This provides both empirical support for a notable, recent theoretical contribution by Godfrey (in Acad Manag Rev 30:777–798, 2005) and novel lessons for reputation management practice.