Simplifying the mosaic description of DNA sequences

By using the Jensen-Shannon divergence, genomic DNA can be divided into compositionally distinct domains through a standard recursive segmentation procedure. Each domain, while significantly different from its neighbours, may however share compositional similarity with one or more distant (non--neighbouring) domains. We thus obtain a coarse--grained description of the given DNA string in terms of a smaller set of distinct domain labels. This yields a minimal domain description of a given DNA sequence, significantly reducing its organizational complexity. This procedure gives a new means of evaluating genomic complexity as one examines organisms ranging from bacteria to human. The mosaic organization of DNA sequences could have originated from the insertion of fragments of one genome (the parasite) inside another (the host), and we present numerical experiments that are suggestive of this scenario.Comment: 16 pages, 1 figure, Accepted for publication in Phys. Rev.

Earthquake source parameters of the 2009 Mw 7.8 Fiordland (New Zealand) earthquake from L-band InSAR observations

The 2009 MW7.8 Fiordland (New Zealand) earthquake is the largest to have occurred in New Zealand since the 1931 Mw 7.8 Hawke’s Bay earthquake, 1 000 km to the northwest. In this paper two tracks of ALOS PALSAR interferograms (one ascending and one descending) are used to determine fault geometry and slip distribution of this large earthquake. Modeling the event as dislocation in an elastic half-space suggests that the earthquake resulted from slip on a SSW-NNE orientated thrust fault that is associated with the subduction between the Pacific and Australian Plates, with oblique displacement of up to 6.3 m. This finding is consistent with the preliminary studies undertaken by the USGS using seismic data

Estimation and Testing for Unit Root Processes with GARCH(1,1) Errors: Theory and Monte Carlo Evidence,

Least squares (LS) and maximum likelihood (ML) estimation are considered for unit root processes with GARCH (1, 1) errors. The asymptotic distributions of LS and ML estimators are derived under the condition alpha + beta

"Estimation and Testing for Unit Root Processes with GARCH (1, 1) Errors: Theory and Monte Carlo Evidence"

Least squares (LS) and maximum likelihood (ML) estimation are con-sidered for unit root processes with GARCH (1, 1) errors. The asymp-totic distributions of LS and ML estimators are derived under the con-dition ƒ¿ + ƒÀ