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Distance Relationships (distance + relationships)

Distribution by Scientific Domains

Life Sciences	50%

Selected Abstracts

The size,distance relationship in the wood ant Formica rufa

ECOLOGICAL ENTOMOLOGY, Issue 2 2000
Philip J. Wright
Summary 1. The size,distance relationship among honeydew-collecting foragers of the red wood ant Formica rufa was investigated. Within the colony territory, the size (as measured by head width) and fresh weight of samples of foragers were determined for ants ascending and descending trees near, and farther from, the central nest mound. 2. The mean size of the ants was significantly higher at far trees than at near trees in six out of the seven colonies investigated, confirming the general presence of the size,distance relationship. 3. In three colonies, a load,distance relationship was also found. For a given head width, honeydew-carrying ants descending far trees were significantly heavier than those descending near trees (i.e. they were carrying heavier loads from trees farther away from the central nest mound). 4. This is the first time that both load,distance and size,distance relationships have been reported in foraging workers from the same ant colony. 5. The combined effects of these characteristics suggest that colony foraging efficiency is enhanced by far trees being visited by the larger workers that then return with heavier loads of honeydew. [source]

Conoscopic holograms analysis using variations of the Hough transform

INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Issue 1 2009
Julius Butime
Abstract The analysis of holograms obtained using a Conoscopic setup is a very complex subject, given their nature. Holograms contain the 3D depth information about an object whose surface is to be measured and later reconstructed. The recovery of depth information has so far been carried out using mathematical transforms in combination with linear regression techniques. Here the Hough transform, a useful Computer Vision technique for detecting features in images is adapted to the analysis of holograms in order to establish distance relationships for a given object. The captured images of holograms are pre-processed and subsequently analyzed for characteristic patterns that are later used in finding the distance to an object. © 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 10,13, 2009 [source]

Accessing Time,Varying Forces on the Vibrating Tip of the Dynamic Atomic Force Microscope to Map Material Composition

ISRAEL JOURNAL OF CHEMISTRY, Issue 2 2008
Ozgur Sahin
In dynamic atomic force microscopes the primary physical quantities being measured are the amplitude/phase or amplitude/frequency of the vibrating force probe. Topographic images with spatial resolutions down to the atomic scale can be obtained by mapping these measurements across the sample surface under feedback control. During the imaging process the vibrating tip is observing tip,sample interaction potentials (force,distance relationships) at every point on the surface. The interaction potential is a superposition of short- and long,distance interactions of various origins determined by the material compositions of the tip, sample, and the medium of imaging. In principle, measurement of tip,sample interaction potential should allow determination and mapping of material composition of the sample. However, a single measurement of amplitude/phase or amplitude/frequency in dynamic atomic force microscopes is not enough to characterize a complicated tip,sample interaction potential. Recent developments in the understanding of dynamics of the vibrating force probe (cantilever), together with specially designed cantilevers that utilize torsional vibrations in addition to conventional vertical vibrations, enable the recovery of tip,sample interaction potentials at a timescale less than a millisecond. Here, with theory and experiments, we discuss how these cantilevers recover the information about the tip,sample interaction forces and give an example of compositional mapping on a polymeric material system. [source]

Linking movement behaviour, dispersal and population processes: is individual variation a key?

JOURNAL OF ANIMAL ECOLOGY, Issue 5 2009
Colin Hawkes
Summary 1Movement behaviour has become increasingly important in dispersal ecology and dispersal is central to the development of spatially explicit population ecology. The ways in which the elements have been brought together are reviewed with particular emphasis on dispersal distance distributions and the value of mechanistic models. 2There is a continuous range of movement behaviours and in some species, dispersal is a clearly delineated event but not in others. The biological complexities restrict conclusions to high-level generalizations but there may be principles that are common to dispersal and other movements. 3Random walk and diffusion models when appropriately elaborated can provide an understanding of dispersal distance relationships on spatial and temporal scales relevant to dispersal. Leptokurtosis in the relationships may be the result of a combination of factors including population heterogeneity, correlation, landscape features, time integration and density dependence. The inclusion in diffusion models of individual variation appears to be a useful elaboration. The limitations of the negative exponential and other phenomenological models are discussed. 4The dynamics of metapopulation models are sensitive to what appears to be small differences in the assumptions about dispersal. In order to represent dispersal realistically in population models, it is suggested that phenomenological models should be replaced by those based on movement behaviour incorporating individual variation. 5The conclusions are presented as a set of candidate principles for evaluation. The main features of the principles are that uncorrelated or correlated random walk, not linear movement, is expected where the directions of habitat patches are unpredictable and more complex behaviour when organisms have the ability to orientate or navigate. Individuals within populations vary in their movement behaviour and dispersal; part of this variation is a product of random elements in movement behaviour and some of it is heritable. Local and metapopulation dynamics are influenced by population heterogeneity in dispersal characteristics and heritable changes in dispersal propensity occur on time-scales short enough to impact population dynamics. [source]