Macrofossil evidence for a rapid and severe Cretaceous–Paleogene mass extinction in Antarctica

Debate continues about the nature of the Cretaceous–Paleogene (K–Pg) mass extinction event. An abrupt crisis triggered by a bolide impact contrasts with ideas of a more gradual extinction involving flood volcanism or climatic changes. Evidence from high latitudes has also been used to suggest that the severity of the extinction decreased from low latitudes towards the poles. Here we present a record of the K–Pg extinction based on extensive assemblages of marine macrofossils (primarily new data from benthic molluscs) from a highly expanded Cretaceous–Paleogene succession: the López de Bertodano Formation of Seymour Island, Antarctica. We show that the extinction was rapid and severe in Antarctica, with no significant biotic decline during the latest Cretaceous, contrary to previous studies. These data are consistent with a catastrophic driver for the extinction, such as bolide impact, rather than a significant contribution from Deccan Traps volcanism during the late Maastrichtian

The macroscopic yield behaviour of polymers

A yield criterion, not previously compared with the actual macroscopic behaviour of polymers, is herein compared with the pressure-modified octahedral shear stress criterion earlier suggested by others. This new relation, which is a version of the von Mises criterion, accommodates differences in tensile and compressive yield strengths and accounts for any dependence of yielding on the hydrostatic component of the applied stress state.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44784/1/10853_2004_Article_BF00550671.pd

Shear wave velocity prediction using seismic attributes and well log data

Formation’s properties can be estimated indirectly using joint analysis of compressional and shear wave velocities. Shear wave data isnot usually acquired during well logging, which is most likely for costsaving purposes. Even if shear data is available, the logging programs provide only sparsely sampled one-dimensional measurements: this informationis inadequate to estimate reservoir rock properties. Thus, if the shear wave data can be obtained using seismic methods, the results can be used across the field to estimate reservoir properties. The aim of this paper is to use seismic attributes for prediction of shear wave velocity in a field located in southern part of Iran. Independent component analysis(ICA) was used to select the most relevant attributes to shear velocity data. Considering the nonlinear relationship between seismic attributes and shear wave velocity, multi-layer feed forward neural network was used for prediction of shear wave velocity and promising results were presented