54 resultados para David, Gérard, approximately 1460-1523.
em CentAUR: Central Archive University of Reading - UK
Resumo:
The objective of the study was to determine if there were adverse effects on animal health and performance when a range of ruminant animals species were fed at least 10 times the maximum permitted European Union (EU) selenium (Se) dietary inclusion rate (0.568 mg Se/kg DM) in the form of selenium enriched yeast (SY) derived from a specific strain of Saccharomyces cerevisiae CNCM I-3060. In a series of studies, dairy cows, beef cattle, calves and lambs were offered either a control diet which contained no Se supplement or a treatment diet which contained the same basal feed ingredients plus a SY supplement which increased total dietary Se from 0.15 to 6.25, 0.20 to 6.74, 0.15 to 5.86 and 0.14 to 6.63 mg Se/kg DM, respectively. The inclusion of the SY supplement (P < 0.001) increased whole blood Se concentrations, reaching maximum mean values of 716, 1,505, 1,377, and 724 ng Se/mL for dairy cattle, beef cattle, calves and lambs, respectively. Selenomethionine accounted for 10% of total whole blood Se in control animals whereas the proportion in SY animals ranged between 40 and 75%. Glutathione peroxidase (EC 1.11.1.9) activity was higher (P < 0.05) in SY animals when compared with controls. A range of other biochemical and hematological parameters were assessed, but few differences of biological significance were established between treatments groups. There were no differences between treatment groups within each species with regard to animal physical performance or overall animal health. It was concluded that there were no adverse effects on animal health, performance and voluntary feed intake to the administration of at least ten times the EU maximum, or approximately twenty times the US FDA permitted concentration of dietary Se in the form of SY derived from a specific strain of Saccharomyces cerevisiae CNCM I-3060.
Resumo:
QUAGMIRE is a quasi-geostrophic numerical model for performing fast, high-resolution simulations of multi-layer rotating annulus laboratory experiments on a desktop personal computer. The model uses a hybrid finite-difference/spectral approach to numerically integrate the coupled nonlinear partial differential equations of motion in cylindrical geometry in each layer. Version 1.3 implements the special case of two fluid layers of equal resting depths. The flow is forced either by a differentially rotating lid, or by relaxation to specified streamfunction or potential vorticity fields, or both. Dissipation is achieved through Ekman layer pumping and suction at the horizontal boundaries, including the internal interface. The effects of weak interfacial tension are included, as well as the linear topographic beta-effect and the quadratic centripetal beta-effect. Stochastic forcing may optionally be activated, to represent approximately the effects of random unresolved features. A leapfrog time stepping scheme is used, with a Robert filter. Flows simulated by the model agree well with those observed in the corresponding laboratory experiments.
Resumo:
Understanding and predicting changes in storm tracks over longer time scales is a challenging problem, particularly in the North Atlantic. This is due in part to the complex range of forcings (land–sea contrast, orography, sea surface temperatures, etc.) that combine to produce the structure of the storm track. The impact of land–sea contrast and midlatitude orography on the North Atlantic storm track is investigated through a hierarchy of GCM simulations using idealized and “semirealistic” boundary conditions in a high-resolution version of the Hadley Centre atmosphere model (HadAM3). This framework captures the large-scale essence of features such as the North and South American continents, Eurasia, and the Rocky Mountains, enabling the results to be applied more directly to realistic modeling situations than was possible with previous idealized studies. The physical processes by which the forcing mechanisms impact the large-scale flow and the midlatitude storm tracks are discussed. The characteristics of the North American continent are found to be very important in generating the structure of the North Atlantic storm track. In particular, the southwest–northeast tilt in the upper tropospheric jet produced by southward deflection of the westerly flow incident on the Rocky Mountains leads to enhanced storm development along an axis close to that of the continent’s eastern coastline. The approximately triangular shape of North America also enables a cold pool of air to develop in the northeast, intensifying the surface temperature contrast across the eastern coastline, consistent with further enhancements of baroclinicity and storm growth along the same axis.
Resumo:
Improvements in the resolution of satellite imagery have enabled extraction of water surface elevations at the margins of the flood. Comparison between modelled and observed water surface elevations provides a new means for calibrating and validating flood inundation models, however the uncertainty in this observed data has yet to be addressed. Here a flood inundation model is calibrated using a probabilistic treatment of the observed data. A LiDAR guided snake algorithm is used to determine an outline of a flood event in 2006 on the River Dee, North Wales, UK, using a 12.5m ERS-1 image. Points at approximately 100m intervals along this outline are selected, and the water surface elevation recorded as the LiDAR DEM elevation at each point. With a planar water surface from the gauged upstream to downstream water elevations as an approximation, the water surface elevations at points along this flooded extent are compared to their ‘expected’ value. The pattern of errors between the two show a roughly normal distribution, however when plotted against coordinates there is obvious spatial autocorrelation. The source of this spatial dependency is investigated by comparing errors to the slope gradient and aspect of the LiDAR DEM. A LISFLOOD-FP model of the flood event is set-up to investigate the effect of observed data uncertainty on the calibration of flood inundation models. Multiple simulations are run using different combinations of friction parameters, from which the optimum parameter set will be selected. For each simulation a T-test is used to quantify the fit between modelled and observed water surface elevations. The points chosen for use in this T-test are selected based on their error. The criteria for selection enables evaluation of the sensitivity of the choice of optimum parameter set to uncertainty in the observed data. This work explores the observed data in detail and highlights possible causes of error. The identification of significant error (RMSE = 0.8m) between approximate expected and actual observed elevations from the remotely sensed data emphasises the limitations of using this data in a deterministic manner within the calibration process. These limitations are addressed by developing a new probabilistic approach to using the observed data.
Resumo:
Satellite observed data for flood events have been used to calibrate and validate flood inundation models, providing valuable information on the spatial extent of the flood. Improvements in the resolution of this satellite imagery have enabled indirect remote sensing of water levels by using an underlying LiDAR DEM to extract the water surface elevation at the flood margin. Further to comparison of the spatial extent, this now allows for direct comparison between modelled and observed water surface elevations. Using a 12.5m ERS-1 image of a flood event in 2006 on the River Dee, North Wales, UK, both of these data types are extracted and each assessed for their value in the calibration of flood inundation models. A LiDAR guided snake algorithm is used to extract an outline of the flood from the satellite image. From the extracted outline a binary grid of wet / dry cells is created at the same resolution as the model, using this the spatial extent of the modelled and observed flood can be compared using a measure of fit between the two binary patterns of flooding. Water heights are extracted using points at intervals of approximately 100m along the extracted outline, and the students T-test is used to compare modelled and observed water surface elevations. A LISFLOOD-FP model of the catchment is set up using LiDAR topographic data resampled to the 12.5m resolution of the satellite image, and calibration of the friction parameter in the model is undertaken using each of the two approaches. Comparison between the two approaches highlights the sensitivity of the spatial measure of fit to uncertainty in the observed data and the potential drawbacks of using the spatial extent when parts of the flood are contained by the topography.
Resumo:
Locomoting through the environment typically involves anticipating impending changes in heading trajectory in addition to maintaining the current direction of travel. We explored the neural systems involved in the “far road” and “near road” mechanisms proposed by Land and Horwood (1995) using simulated forward or backward travel where participants were required to gauge their current direction of travel (rather than directly control it). During forward egomotion, the distant road edges provided future path information, which participants used to improve their heading judgments. During backward egomotion, the road edges did not enhance performance because they no longer provided prospective information. This behavioral dissociation was reflected at the neural level, where only simulated forward travel increased activation in a region of the superior parietal lobe and the medial intraparietal sulcus. Providing only near road information during a forward heading judgment task resulted in activation in the motion complex. We propose a complementary role for the posterior parietal cortex and motion complex in detecting future path information and maintaining current lane positioning, respectively. (PsycINFO Database Record (c) 2010 APA, all rights reserved)