We use the multi-epoch radial velocities acquired by the Apache Point Observatory Galactic Evolution Experiment (APOGEE) survey to perform a large-scale statistical study of stellar multiplicity for ...field stars in the Milky Way, spanning the evolutionary phases between the main sequence (MS) and the red clump. We show that the distribution of maximum radial velocity shifts (Delta RVmax) for APOGEE targets is a strong function of log g, with MS stars showing Delta RVmax as high as similar to 300 km s(-1), and steadily dropping down to similar to 30 km s(-1) for log g similar to 0, as stars climb up the red giant branch (RGB). Red clump stars show a distribution of Delta RVmax values comparable to that of stars at the tip of the RGB, implying they have similar multiplicity characteristics. The observed attrition of high Delta RVmax systems in the RGB is consistent with a lognormal period distribution in the MS and a multiplicity fraction of 0.35, which is truncated at an increasing period as stars become physically larger and undergo mass transfer after Roche Lobe overflow during H-shell burning. The Delta RVmax distributions also show that the multiplicity characteristics of field stars are metallicity-dependent, with metal-poor (Fe/H less than or similar to -0.5) stars having a multiplicity fraction a factor of 2-3 higher than metal-rich (Fe/H less than or similar to 0.0) stars. This has profound implications for the formation rates of interacting binaries observed by astronomical transient surveys and gravitational wave detectors, as well as the habitability of circumbinary planets.
We report the results of a population-genetic study of the short-nosed fruit bat, Cynopterus sphinx (Pteropodidae). The purpose of our study was to assess the relative importance of drift, gene flow, ...and spatially varying selection in shaping patterns of genetic and phenotypic variation across a latitudinal climatic gradient in peninsular India. At a microgeographic scale, polygynous mating resulted in a substantial reduction of effective population size. However, at a macrogeographic scale, rates of migration were sufficiently high to prevent a pronounced degree of stochastic differentiation via drift. Spatial analysis of genetic and phenotypic differentiation revealed that clinal variation in body size of C. sphinx cannot be explained by a neutral model of isolation by distance. The geographic patterning of morphometric variation is most likely attributable to spatially varying selection and/or the direct influence of latitudinally ordered environmental effects. The combined analysis of genetic and phenotypic variation indicates that recognized subspecies of C. sphinx in peninsular India represent arbitrary subdivisions of a continuous spectrum of clinal size variation.
The goal of our project is to develop and evaluate image analysis methodologies for use on the ground or on-board spacecraft particularly spacecraft constellations. Our focus is on developing methods ...to perform automatic registration and fusion of multisensor data representing multiple spatial, spectral and temporal resolutions, as well as dimension reduction of hyperspectral data. Feature extraction methods such as wavelet decomposition, edge detection and mutual information are combined with feature matching methods such as cross-correlation, optimization, and statistically robust techniques to perform image registration. The approach to image fusion is application-based and involves wavelet decomposition, dimension reduction, and classification methods. Dimension reduction is approached through novel methods based on principal component analysis and wavelet decomposition, and implemented on Beowulf-type parallel architectures. Registration algorithms are tested and compared on several multi-sensor datasets, including one of the EOS Core Sites, the Konza Prairie in Kansas, utilizing four different sensors: IKONOS, Landsat-7/ETM+, MODIS, and SeaWIFS. Fusion methods are tested using Landsat, MODIS and SAR or JERS data. Dimension reduction is demonstrated on A VIRIS hyperspectral data.
While automatic image registration algorithms are usually being evaluated with regards to their accuracy, it is often useful to relate this accuracy to the "initial conditions", i.e., the distance ...between the initial navigation geolocation and the correct result. This paper describes a modular framework that was built to describe registration algorithms, and utilize this framework to attempt to classify different registration components and algorithms in terms of their responses to the initial conditions. Performances would be evaluated on synthetic data, multitemporal and multisensor data. All results of the study would be presented at the conference and would be useful for two different purposes: (1) provide automatic quality assessment of the geolocation of remote sensing data by performing interalgorithm consistency studies; and (2) be the foundations for the design of future on-board applications including planetary exploration.
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