The Pleistocene archaeology and environments of the Wasiriya Beds, Rusinga Island, Kenya.

Western Kenya is well known for abundant early Miocene hominoid fossils. However, the Wasiriya Beds of Rusinga Island, Kenya, preserve a Pleistocene sedimentary archive with radiocarbon age estimates of >33-45 ka that contains Middle Stone Age artifacts and abundant, well-preserved fossil fauna: a co-occurrence rare in eastern Africa, particularly in the region bounding Lake Victoria. Artifacts and fossils are associated with distal volcanic ash deposits that occur at multiple localities in the Wasiriya Beds, correlated on the basis of geochemical composition as determined by electron probe microanalysis. Sediment lithology and the fossil ungulates suggest a local fluvial system and associated riparian wooded habitat within a predominantly arid grassland setting that differs substantially from the modern environment, where local climate is strongly affected by moisture availability from Lake Victoria. In particular, the presence of oryx (Oryx gazella) and Grevy's zebra (Equus grevyi) suggest a pre-Last Glacial Maximum expansion of arid grasslands, an environmental reconstruction further supported by the presence of several extinct specialized grazers (Pelorovis antiquus, Megalotragus sp., and a small alcelaphine) that are unknown from Holocene deposits in eastern Africa. The combination of artifacts, a rich fossil fauna, and volcaniclastic sediments makes the Wasiriya Beds a key site for examining the Lake Victoria basin, a biogeographically important area for understanding the diversification and dispersal of Homo sapiens from Africa, whose pre-Last Glacial Maximum history remains poorly understood.

Exploration of shape variation using localized components analysis.

Localized Components Analysis (LoCA) is a new method for describing surface shape variation in an ensemble of objects using a linear subspace of spatially localized shape components. In contrast to earlier methods, LoCA optimizes explicitly for localized components and allows a flexible trade-off between localized and concise representations, and the formulation of locality is flexible enough to incorporate properties such as symmetry. This paper demonstrates that LoCA can provide intuitive presentations of shape differences associated with sex, disease state, and species in a broad range of biomedical specimens, including human brain regions and monkey crania.

Localized components analysis.

We introduce Localized Components Analysis (LoCA) for describing surface shape variation in an ensemble of biomedical objects using a linear subspace of spatially localized shape components. In contrast to earlier methods, LoCA optimizes explicitly for localized components and allows a flexible trade-off between localized and concise representations. Experiments comparing LoCA to a variety of competing shape representation methods on 2D and 3D shape ensembles establish the superior ability of LoCA to modulate the locality-conciseness tradeoff and generate shape components corresponding to intuitive modes of shape variation. Our formulation of locality in terms of compatibility between pairs of surface points is shown to be flexible enough to enable spatially-localized shape descriptions with attractive higher-order properties such as spatial symmetry.