Importance of intraspecifically gregarious species in a tropical bird community

In both single- and mixed-species social groups, certain participants are known to play important roles in providing benefits. Identifying these participants is critical for understanding group dynamics, but is often difficult with large roving social groups in the wild. Here, we develop a new approach to characterize roles in social groups and apply it to mixed-species bird flocks (flocks hereafter) in an Indian tropical evergreen forest. Two types of species, namely intraspecifically gregarious and sallying species, are thought to play important roles in flocks because studies have shown they attract other flock participants. However, it is unclear why these types are attractive and whether they are essential for flock formation. We address these questions by focusing on the composition of the subset of flocks containing only two species each. In two-species flocks, it is reasonable to assume that at least one species obtains some kind of benefit. Therefore, only those species combinations that result in benefit to at least one species should occur as two-species flocks. Using data from 540 flocks overall, of which 158 were two-species flocks, we find that intraspecifically gregarious species are disproportionately represented in two-species flocks and always lead flocks when present, and that flocks containing them are joined significantly more by other species. Our results suggest that intraspecifically gregarious species are likely to be the primary benefit providers in flocks and are important for tropical flock formation. Our study also provides a new approach to understanding importance in other mixed-species and single-species social groups.

Effect of viscosity and surface tension on breakup and coalescence of bicomponent sprays

This work deals with an experimental study of the breakup characteristics of liquids with different surface tension and viscosity from a hollow cone hydraulic injector nozzle induced by pressure-swirl. The experiments were conducted at Reynolds numbers Re-p=9500-23,000. The surface tension and viscosity of the surrogate fuels were altered from 72 to 30 mN/m and 1.1 to 1.6 mN s/m(2), respectively. High speed photography and Phase Doppler Particle Anemometry were utilized to study the atomization process. Velocity and drop size measurements of the spray using PDPA in both axial and radial directions indicate a dependency on surface tension. However, these effects are dominant only at low Reynolds numbers and are negligible at high Reynolds number. Downstream of the nozzle, coalescence of droplets due to collision was also found to be significant and the diameters were compared for different liquids. For viscous fluids up to 1.6 cP, the independent effects of viscosity and injection pressure are studied. In general, the spray cone angle increases with increase in pressure. At high pressures, an increase in viscosity leads to higher drop sizes following primary and secondary breakup compared to water. This study will extend our understanding of surrogate fuel film breakup and highlight the importance of long and short wavelength instabilities. (C) 2013 Elsevier Ltd. All rights reserved

FAST AND ACCURATE BILATERAL FILTERING USING GAUSS-POLYNOMIAL DECOMPOSITION

The bilateral filter is a versatile non-linear filter that has found diverse applications in image processing, computer vision, computer graphics, and computational photography. A common form of the filter is the Gaussian bilateral filter in which both the spatial and range kernels are Gaussian. A direct implementation of this filter requires O(sigma(2)) operations per pixel, where sigma is the standard deviation of the spatial Gaussian. In this paper, we propose an accurate approximation algorithm that can cut down the computational complexity to O(1) per pixel for any arbitrary sigma (constant-time implementation). This is based on the observation that the range kernel operates via the translations of a fixed Gaussian over the range space, and that these translated Gaussians can be accurately approximated using the so-called Gauss-polynomials. The overall algorithm emerging from this approximation involves a series of spatial Gaussian filtering, which can be efficiently implemented (in parallel) using separability and recursion. We present some preliminary results to demonstrate that the proposed algorithm compares favorably with some of the existing fast algorithms in terms of speed and accuracy.