883 resultados para Local Field Potentials
Resumo:
Agriculture's contribution to radiative forcing is principally through its historical release of carbon in soil and vegetation to the atmosphere and through its contemporary release of nitrous oxide (N2O) and methane (CHM4). The sequestration of soil carbon in soils now depleted in soil organic matter is a well-known strategy for mitigating the buildup of CO2 in the atmosphere. Less well-recognized are other mitigation potentials. A full-cost accounting of the effects of agriculture on greenhouse gas emissions is necessary to quantify the relative importance of all mitigation options. Such an analysis shows nitrogen fertilizer, agricultural liming, fuel use, N2O emissions, and CH4 fluxes to have additional significant potential for mitigation. By evaluating all sources in terms of their global warming potential it becomes possible to directly evaluate greenhouse policy options for agriculture. A comparison of temperate and tropical systems illustrates some of these options.
Resumo:
This work is focussed on developing a commissioning procedure so that a Monte Carlo model, which uses BEAMnrc’s standard VARMLC component module, can be adapted to match a specific BrainLAB m3 micro-multileaf collimator (μMLC). A set of measurements are recommended, for use as a reference against which the model can be tested and optimised. These include radiochromic film measurements of dose from small and offset fields, as well as measurements of μMLC transmission and interleaf leakage. Simulations and measurements to obtain μMLC scatter factors are shown to be insensitive to relevant model parameters and are therefore not recommended, unless the output of the linear accelerator model is in doubt. Ultimately, this note provides detailed instructions for those intending to optimise a VARMLC model to match the dose delivered by their local BrainLAB m3 μMLC device.
Resumo:
Key resource areas (KRAs), defined as dry season foraging zones for herbivores, were studied relative to the more extensive outlying rangeland areas (non-KRAs) in Kenya. Field surveys with pastoralists, ranchers, scientists and government officials delineated KRAs on the ground. Identified KRAs were mapped based on global positioning and local experts' information on KRAs accessibility and ecological attributes. Using the map of known KRAs and non-KRAs, we examined characteristics of soils, climate, topography, land use/cover attributes at KRAs relative to non-KRAs. How and why do some areas (KRAs) support herbivores during droughts when forage is scarce in other areas of the landscape? We hypothesized that KRAs have fundamental ecological and socially determined attributes that enable them to provide forage during critical times and we sought to characterize some of those attributes in this study. At the landscape level, KRAs took different forms based on forage availability during the dry season but generally occurred in locations of the landscape with aseasonal water availability and/or difficult to access areas during wet season forage abundance. Greenness trends for KRAs versus non-KRAs were evaluated with a 22-year dataset of Normalized Difference Vegetation Index (NDVI). Field surveys of KRAs provided qualitative information on KRAs as dry season foraging zones. At the scale of the study, soil attributes did not significantly differ for KRAs compared to non-KRAs. Slopes of KRA were generally steeper compared to non-KRAs and elevation was higher at KRAs. Field survey respondents indicated that animals and humans generally avoid difficult to access hilly areas using them only when all other easily accessible rangeland is depleted of forage during droughts. Understanding the nature of KRAs will support identification, protection and restoration of critical forage hotspots for herbivores by strengthening rangeland inventory, monitoring, policy formulation, and conservation efforts to improve habitats and human welfare. (c) 2007 Elsevier Ltd. All rights reserved.
Resumo:
The iPlan treatment planning sys-tem uses a pencil beam algorithm, with density cor-rections, to predict the doses delivered by very small (stereotactic) radiotherapy fields. This study tests the accuracy of dose predictions made by iPlan, for small-field treatments delivered to a planar solid wa-ter phantom and to heterogeneous human tissue using the BrainLAB m3 micro-multileaf collimator.
Resumo:
Knowledge of the accuracy of dose calculations in intensity-modulated radiotherapy of the head and neck is essential for clinical confidence in these highly conformal treatments. High dose gradients are frequently placed very close to critical structures, such as the spinal cord, and good coverage of complex shaped nodal target volumes is important for long term-local control. A phantom study is presented comparing the performance of standard clinical pencil-beam and collapsed-cone dose algorithms to Monte Carlo calculation and three-dimensional gel dosimetry measurement. All calculations and measurements are normalized to the median dose in the primary planning target volume, making this a purely relative study. The phantom simulates tissue, air and bone for a typical neck section and is treated using an inverse-planned 5-field IMRT treatment, similar in character to clinically used class solutions. Results indicate that the pencil-beam algorithm fails to correctly model the relative dose distribution surrounding the air cavity, leading to an overestimate of the target coverage. The collapsed-cone and Monte Carlo results are very similar, indicating that the clinical collapsed-cone algorithm is perfectly sufficient for routine clinical use. The gel measurement shows generally good agreement with the collapsed-cone and Monte Carlo calculated dose, particularly in the spinal cord dose and nodal target coverage, thus giving greater confidence in the use of this class solution.