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F. Yang

Publications and source records attributed to F. Yang.

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Chromosome painting among Proboscidea, Hyracoidea and Sirenia: Support for Paenungulata (Afrotheria, Mammalia) but not Tethytheria

Despite marked improvements in the interpretation of systematic relationships within Eutheria, particular nodes, including Paenungulata (Hyracoidea, Sirenia and Proboscidea), remain ambiguous. The combination of a rapid radiation, a deep divergence and an extensive morphological diversification has resulted in a limited phylogenetic signal confounding resolution within this clade both at the morphological and nucleotide levels. Cross-species chromosome painting was used to delineate regions of homology between Loxodonta africana (2n = 56), Procavia capensis (2n=54), Trichechus manatus latirostris (2n = 48) and an outgroup taxon, the aardvark (Orycteropus afer, 2n = 20). Changes specific to each lineage were identified and although the presence of a minimum of 11 synapomorphies confirmed the monophyly of Paenungulata, no change characterizing intrapaenungulate relationships was evident. The reconstruction of an ancestral paenungulate karyotype and the estimation of rates of chromosomal evolution indicate a reduced rate of genomic repatterning following the paenungulate radiation. In comparison to data available for other mammalian taxa, the paenungulate rate of chromosomal evolution is slow to moderate. As a consequence, the absence of a chromosomal character uniting two paenungulates (at the level of resolution characterized in this study) may be due to a reduced rate of chromosomal change relative to the length of time separating successive divergence events. ?? 2007 The Royal Society.

Proceedings of the Royal Society B: Biological Sci

Gaussian-based filters for detecting Martian dust devils

The ability to automatically detect dust devils in the Martian atmosphere from orbital imagery is becoming important both for scientific studies of the planet and for the planning of future robotic and manned missions. This paper describes our approach for the unsupervised detection of dust devils and the preliminary results achieved to date. The algorithm centers upon the use of a filter constructed from Gaussian profiles to match dust devil characteristics over a range of scale and orientation. The classification step is designed to reduce false positive errors caused by static surface features such as craters. A brief discussion of planned future work is included. ?? 2006 IEEE.

Conference Paper