The role of the harmonic vector average in motion integration

The local speeds of object contours vary systematically with the cosine of the angle between the normal component of the local velocity and the global object motion direction. An array of Gabor elements whose speed changes with local spatial orientation in accordance with this pattern can appear to move as a single surface. The apparent direction of motion of plaids and Gabor arrays has variously been proposed to result from feature tracking, vector addition and vector averaging in addition to the geometrically correct global velocity as indicated by the intersection of constraints (IOC) solution. Here a new combination rule, the harmonic vector average (HVA), is introduced, as well as a new algorithm for computing the IOC solution. The vector sum can be discounted as an integration strategy as it increases with the number of elements. The vector average over local vectors that vary in direction always provides an underestimate of the true global speed. The HVA, however, provides the correct global speed and direction for an unbiased sample of local velocities with respect to the global motion direction, as is the case for a simple closed contour. The HVA over biased samples provides an aggregate velocity estimate that can still be combined through an IOC computation to give an accurate estimate of the global velocity, which is not true of the vector average. Psychophysical results for type II Gabor arrays show perceived direction and speed falls close to the IOC direction for Gabor arrays having a wide range of orientations but the IOC prediction fails as the mean orientation shifts away from the global motion direction and the orientation range narrows. In this case perceived velocity generally defaults to the HVA.

On flow reversal boundaries and transpolar voltage in average models of high-latitude convection

The implications of polar cap expansions, contractions and movements for empirical models of high-latitude plasma convection are examined. Some of these models have been generated by directly averaging flow measurements from large numbers of satellite passes or radar scans; others have employed more complex means to combine data taken at different times into large-scale patterns of flow. In all cases, the models have implicitly adopted the assumption that the polar cap is in steady state: they have all characterized the ionospheric flow in terms of the prevailing conditions (e.g. the interplanetary magnetic field and/or some index of terrestrial magnetic activity) without allowance for their history. On long enough time scales, the polar cap is indeed in steady state but on time scales shorter than a few hours it is not and can oscillate in size and position. As a result, the method used to combine the data can influence the nature of the convection reversal boundary and the transpolar voltage in the derived model. This paper discusses a variety of effects due to time-dependence in relation to some ionospheric convection models which are widely applied. The effects are shown to be varied and to depend upon the procedure adopted to compile the model.

Low rank representation on Riemannian manifold of symmetric positive definite matrices

Sparse coding aims to find a more compact representation based on a set of dictionary atoms. A well-known technique looking at 2D sparsity is the low rank representation (LRR). However, in many computer vision applications, data often originate from a manifold, which is equipped with some Riemannian geometry. In this case, the existing LRR becomes inappropriate for modeling and incorporating the intrinsic geometry of the manifold that is potentially important and critical to applications. In this paper, we generalize the LRR over the Euclidean space to the LRR model over a specific Rimannian manifold—the manifold of symmetric positive matrices (SPD). Experiments on several computer vision datasets showcase its noise robustness and superior performance on classification and segmentation compared with state-of-the-art approaches.

Genetic algorithm inversion of the average 1D crustal structure using local and regional earthquakes

Knowing the best 1D model of the crustal and upper mantle structure is useful not only for routine hypocenter determination, but also for linearized joint inversions of hypocenters and 3D crustal structure, where a good choice of the initial model can be very important. Here, we tested the combination of a simple GA inversion with the widely used HYPO71 program to find the best three-layer model (upper crust, lower crust, and upper mantle) by minimizing the overall P- and S-arrival residuals, using local and regional earthquakes in two areas of the Brazilian shield. Results from the Tocantins Province (Central Brazil) and the southern border of the Sao Francisco craton (SE Brazil) indicated an average crustal thickness of 38 and 43 km, respectively, consistent with previous estimates from receiver functions and seismic refraction lines. The GA + HYPO71 inversion produced correct Vp/Vs ratios (1.73 and 1.71, respectively), as expected from Wadati diagrams. Tests with synthetic data showed that the method is robust for the crustal thickness, Pn velocity, and Vp/Vs ratio when using events with distance up to about 400 km, despite the small number of events available (7 and 22, respectively). The velocities of the upper and lower crusts, however, are less well constrained. Interestingly, in the Tocantins Province, the GA + HYPO71 inversion showed a secondary solution (local minimum) for the average crustal thickness, besides the global minimum solution, which was caused by the existence of two distinct domains in the Central Brazil with very different crustal thicknesses. (C) 2010 Elsevier Ltd. All rights reserved.

Global analytic regularity for structures of co-rank one

We consider real analytic involutive structures V, of co-rank one, defined on a real analytic paracompact orientable manifold M. To each such structure we associate certain connected subsets of M which we call the level sets of V. We prove that analytic regularity propagates along them. With a further assumption on the level sets of V we characterize the global analytic hypoellipticity of a differential operator naturally associated to V. As an application we study a case of tube structures.

Influence of quantum-dots density on average in-plane strain of optoelectronic devices investigated by high-resolution X-ray diffraction

High-resolution X-ray diffractometry is used to probe the nature of a diffraction-peak broadening previously noticed in quantum dots (QDs) systems with freestanding InAs islands on top of GaAs (001) substrates [Freitas et al., Phys. Status Solidi (A) 204, 2548 (2007)]. The procedure is hence extended to further investigate the capping process of InAs/GaAs QDs. A direct correlation is established between QDs growth rates and misorientation of lattice-planes at the samples surfaces. This effect provides an alternative too] for studying average strain fields on QDs systems in standard triple axis diffractometers running on X-ray tube sources, which are much more common than synchrotron facilities. (C) 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Beyond the average: Detecting global singular nodes from local features in complex networks

Deviations from the average can provide valuable insights about the organization of natural systems. The present article extends this important principle to the systematic identification and analysis of singular motifs in complex networks. Six measurements quantifying different and complementary features of the connectivity around each node of a network were calculated, and multivariate statistical methods applied to identify singular nodes. The potential of the presented concepts and methodology was illustrated with respect to different types of complex real-world networks, namely the US air transportation network, the protein-protein interactions of the yeast Saccharomyces cerevisiae and the Roget thesaurus networks. The obtained singular motifs possessed unique functional roles in the networks. Three classic theoretical network models were also investigated, with the Barabasi-Albert model resulting in singular motifs corresponding to hubs, confirming the potential of the approach. Interestingly, the number of different types of singular node motifs as well as the number of their instances were found to be considerably higher in the real-world networks than in any of the benchmark networks. Copyright (C) EPLA, 2009

Average Annual Wind Resource Potential in Maine

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Educational Opportunities and Average Income in Maine Towns

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Average Annual Precipitation in Maine

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Determinação da dose eritematosa mínima como marcador de risco e sensibilidade à radiação ultravioleta

Objetivos: Determinar a dose eritematosa mínima (DEM) medida por exposição controlada à radiação ultravioleta-B (RUV-B), como limiar para dano solar agudo nos diversos fototipos, e medir a cor da pele constitucional pelo sistema colorimétrico CIELAB. Pacientes e Métodos: Um total de 194 voluntários, sadios, com idades acima de 18 anos, distribuídos em um mínimo de 30 participantes por fototipo. Todos foram classificados por fototipos segundo os critérios de Fitzpatrick. As regiões infra-axilar torácica e nádega foram irradiadas em 4 áreas de 1 cm2, assim como foi registrada a cor da pele desses locais pelo sistema CIELAB. Delineamento: Estudo transversal. Resultados: A média de idade dos participantes foi de 38 anos, sendo 68% do sexo feminino. A avaliação da associação entre as medidas das DEMs e dos valores colorimétricos da coordenada L*, mostrou uma correlação de Pearson negativa com r = -0,91 para um valor p<0,05. Para os valores das DEMs e os escores da classificação dos voluntários por fototipos, obteve-se correlação de Spearman (rs) de +0,95 para p<0,05 e, correlacionando os valores colorimétricos com os escores dos fototipos, encontrou-se em tórax um rs de -0,93 e em nádega -0,92 para um p < 0,05. Conclusões – Concluiu-se que: 1)- a mensuração dos valores colorimétricos da coordenada L* nas regiões infra-axilar torácica e nádega mostraram uma forte correlação com os valores das DEMs, sendo de menor poder invasivo e de maior praticidade para mensuração de sensibilidade à radiação ultravioleta; 2)- apesar de os escores de Fitzpatrick terem alta correlação com os valores das DEMs, mostraram superposição de valores nos fototipos adjacentes; 3)- o grau de associação das classes dos fototipos com a cor da pele permite dizer que a categoria numérica do fototipo aumenta à medida que a pele fica mais escura.

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise based upon data from a well known survey is also presented. Overall, theoretical and empirical results show promise for the feasible bias-corrected average forecast.

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular it delivers a zero-limiting mean-squared error if the number of forecasts and the number of post-sample time periods is sufficiently large. We also develop a zero-mean test for the average bias. Monte-Carlo simulations are conducted to evaluate the performance of this new technique in finite samples. An empirical exercise, based upon data from well known surveys is also presented. Overall, these results show promise for the bias-corrected average forecast.