11 resultados para 937

em CentAUR: Central Archive University of Reading - UK


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Decadal prediction uses climate models forced by changing greenhouse gases, as in the International Panel for Climate Change, but unlike longer range predictions they also require initialization with observations of the current climate. In particular, the upper-ocean heat content and circulation have a critical influence. Decadal prediction is still in its infancy and there is an urgent need to understand the important processes that determine predictability on these timescales. We have taken the first Hadley Centre Decadal Prediction System (DePreSys) and implemented it on several NERC institute compute clusters in order to study a wider range of initial condition impacts on decadal forecasting, eventually including the state of the land and cryosphere. The eScience methods are used to manage submission and output from the many ensemble model runs required to assess predictive skill. Early results suggest initial condition skill may extend for several years, even over land areas, but this depends sensitively on the definition used to measure skill, and alternatives are presented. The Grid for Coupled Ensemble Prediction (GCEP) system will allow the UK academic community to contribute to international experiments being planned to explore decadal climate predictability.

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Edition and commentary of the Latin verse inscription thought to be written in the so-called Saturnian verse

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We use geomagnetic activity data to study the rise and fall over the past century of the solar wind flow speed VSW, the interplanetary magnetic field strength B, and the open solar flux FS. Our estimates include allowance for the kinematic effect of longitudinal structure in the solar wind flow speed. As well as solar cycle variations, all three parameters show a long-term rise during the first half of the 20th century followed by peaks around 1955 and 1986 and then a recent decline. Cosmogenic isotope data reveal that this constitutes a grand maximum of solar activity which began in 1920, using the definition that such grand maxima are when 25-year averages of the heliospheric modulation potential exceeds 600 MV. Extrapolating the linear declines seen in all three parameters since 1985, yields predictions that the grand maximum will end in the years 2013, 2014, or 2027 using VSW, FS, or B, respectively. These estimates are consistent with predictions based on the probability distribution of the durations of past grand solar maxima seen in cosmogenic isotope data. The data contradict any suggestions of a floor to the open solar flux: we show that the solar minimum open solar flux, kinematically corrected to allow for the excess flux effect, has halved over the past two solar cycles.

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Abnormal vascular smooth muscle cell (VSMC) proliferation is known to play an important role in the pathogenesis of atherosclerosis, restenosis and instent stenosis. Recent studies suggest that salicylates, in addition to inhibiting cyclooxygenase activity, exert an antiproliferative effect on VSMC growth both in vitro and in vivo. However, whether all non-steroidal anti-inflammatory drugs (NSAID) exert similar antiproliferative effects on VSMCs, and do so via a common mechanism of action, remains unknown. In the present study, we demonstrated that the NSAIDs, aspirin, ibuprofen and sulindac induced a dose-dependent inhibition of proliferation in rat A10 VSMCs (IC50 = 1666 mumol/L, 937 mumol/L and 520 mumol/L, respectively). These drugs did not show significant cytotoxic effects as determined by LDH release assay, even at the highest concentrations tested (aspirin, 5000 mumol/L; ibuprofen, 2500 mumol/L; and sulindac, 1000 mumol/L). Flow cytometric analyses showed that a 48 h exposure of A10 VSMCs to ibuprofen (1000 mumol/L) and sulindac (750 mumol/L) led to a significant G1 arrest (from 68.7 +/- 2.0% of cells in G1 to 76.6 +/- 2.2% and 75.8 +/- 2.2%, respectively, p < 0.05). In contrast, aspirin (2500 mumol/L) failed to induce a significant G1 arrest (68.1 +/- 5.2%). Clearer evidence of a G1 block was obtained by treatment of cells with the mitotic inhibitor, nocodazole (40 ng/ml), for the final 24 h of the experiment. Under these conditions, aspirin still failed to induce a G1 arrest (from 25.9 +/- 10.9% of cells in G1 to 19.6 +/- 2.3%) whereas ibuprofen and sulindac led to a significant accumulation of cells in G1(51.8% +/- 17.2% and 54.1% +/- 10.6%, respectively, p < 0.05). These results indicate that ibuprofen and sulindac inhibit VSMC proliferation by arresting the cell cycle in the G1 phase whereas the effect of aspirin appears to be independent of any special phase of the cell cycle. Irrespective of mechanism, our results suggest that NSAIDs might be of benefit to the treatment of vascular proliferative disorders.

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For both MoO42− and WO42− the maximum rate of uptake by the small intestine of the rat (studied in vitro using the everted sac technique) occurs in the lower ileum. Kinetic constants, derived by a least squares procedure, are compared with those previously obtained for SO42− transport. For both and , , with only small differences between sacs IV and V. Mutual inhibition of MoO42− and WO42− transport and inhibition of both by SO42− are competitive processes. This is shown by the generally good agreement between values and derived values and by V values in the presence and absence of the inhibiting species. The three ions SO42−, MoO42− and WO42− are probably transferred across the intestine by a common carrier system. Implications for the sulphate-molybdenum interaction in molybdosis are discussed.

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Thin section petrographical analysis of chalk tesserae at Brading Roman Villa, Isle of Wight, England, identifies a range of planktonic foraminifera and the calcareous algal cyst Pithonella that identify the Late Cenomanian Rotalipora cushmani Biozone (BGS Foraminiferal Biozones 4iii to 7). The local chalk crop to the north of the villa includes rocks of R. cushmani Biozone age, and indicates a likely local, rather than long distance, source for the tesserae. Microfossils provide a powerful tool for identifying the provenance of artefacts in Roman Britain.

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Business and IT alignment has continued as a top concern for business and IT executives for almost three decades. Many researchers have conducted empirical studies on the relationship between business-IT alignment and performance. Yet, these approaches, lacking a social perspective, have had little impact on sustaining performance and competitive advantage. In addition to the limited alignment literature that explores organisational learning that is represented in shared understanding, communication, cognitive maps and experiences. Hence, this paper proposes an integrated process that enables social and intellectual dimensions through the concept of organisational learning. In particular, the feedback and feed- forward process which provide a value creation across dynamic multilevel of learning. This mechanism enables on-going effectiveness through development of individuals, groups and organisations, which improves the quality of business and IT strategies and drives to performance.

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Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperatures are modelled empirically, accounting for a nonlinear technology trend and interactions between temperature and precipitation, and applied specifically for a case study of maize in France. The relative importance of precipitation variability for maize yields in France has decreased significantly since the 1960s, likely due to increased irrigation. In addition, heat stress is found to be as important for yield as precipitation since around 2000. A significant reduction in maize yield is found for each day with a maximum temperature above 32 °C, in broad agreement with previous estimates. The recent increase in such hot days has likely contributed to the observed yield stagnation. Furthermore, a general method for producing near-term crop yield projections, based on climate model simulations, is developed and utilized. We use projections of future daily maximum temperatures to assess the likely change in yields due to variations in climate. Importantly, we calibrate the climate model projections using observed data to ensure both reliable temperature mean and daily variability characteristics, and demonstrate that these methods work using retrospective predictions. We conclude that, to offset the projected increased daily maximum temperatures over France, improved technology will need to increase base level yields by 12% to be confident about maintaining current levels of yield for the period 2016–2035; the current rate of yield technology increase is not sufficient to meet this target.