3 resultados para Kathmandu Valley
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Resumo:
Here we present the results of magneto resistance measurements in tilted magnetic field and compare them with calculations. The comparison between calculated and measured spectra for the case of perpendicular fields enable us to estimate the dependence of the valley splitting as a function of the magnetic field and the total Lande g-factor (which is assumed to be independent of the magnetic field). Since both the exchange contribution to the Zeeman splitting as well as the valley splitting are properties associated with the 2D quantum confinement, they depend only on the perpendicular component of the magnetic field, while the bare Zeeman splitting depends on the total magnetic field. This information aided by the comparison between experimental and calculated gray scale maps permits to obtain separately the values of the exchange and the bare contribution to the g-factor.
Resumo:
The age of some ancient pottery from the Valley of Vitor in the region of Arequipa, Peru, is determined by the thermoluminescence (TL) method. For dating, a 325 degrees C TL peak was used and irradiation with -dose from 5 to 50Gy was carried out for the additive method, and from 0.4 to 5Gy for the regeneration method. For these dose values, the TL intensity is observed to grow linearly, obtaining an accumulated dose of 1.62 +/- 0.09Gy and 1.36 +/- 0.03Gy for the additive and regeneration methods, respectively. The age (A) of the sample was calculated by the two methods, being A=867 +/- 195 years after Christ (AC) for the additive method and A=1050 +/- 157 years AC for the regeneration method. Both results are within 800-1200 years AC, which is the period of the Wari culture.
Resumo:
Surface roughness is an important geomorphological variable which has been used in the Earth and planetary sciences to infer material properties, current/past processes, and the time elapsed since formation. No single definition exists; however, within the context of geomorphometry, we use surface roughness as an expression of the variability of a topographic surface at a given scale, where the scale of analysis is determined by the size of the landforms or geomorphic features of interest. Six techniques for the calculation of surface roughness were selected for an assessment of the parameter`s behavior at different spatial scales and data-set resolutions. Area ratio operated independently of scale, providing consistent results across spatial resolutions. Vector dispersion produced results with increasing roughness and homogenization of terrain at coarser resolutions and larger window sizes. Standard deviation of residual topography highlighted local features and did not detect regional relief. Standard deviation of elevation correctly identified breaks of slope and was good at detecting regional relief. Standard deviation of slope (SD(slope)) also correctly identified smooth sloping areas and breaks of slope, providing the best results for geomorphological analysis. Standard deviation of profile curvature identified the breaks of slope, although not as strongly as SD(slope), and it is sensitive to noise and spurious data. In general, SD(slope) offered good performance at a variety of scales, while the simplicity of calculation is perhaps its single greatest benefit.