4,479 research outputs found
VIDA: a virus database system for the organization of animal virus genome open reading frames
VIDA is a new virus database that organizes open reading frames (ORFs) from partial and complete genomic sequences from animal viruses. Currently VIDA includes all sequences from GenBank for Herpesviridae, Coronaviridae and Arteriviridae. The ORFs are organized into homologous protein families, which are identified on the basis of sequence similarity relationships, Conserved sequence regions of potential functional importance are identified and can be retrieved as sequence alignments. We use a controlled taxonomical and functional classification for all the proteins and protein families in the database. When available, protein structures that are related to the families have also been included. The database is available for online search and sequence information retrieval at http://www.biochem.ucl.ac.uk/bsm/virus-database/ VIDA.html
On the Josephson Coupling between a disk of one superconductor and a surrounding superconducting film of a different symmetry
A cylindrical Josephson junction with a spatially dependent Josephson
coupling which averages to zero is studied in order to model the physics of a
disk of d-wave superconductor embedded in a superconducting film of a different
symmetry. It is found that the system always introduces Josepshon vortices in
order to gain energy at the junction. The critical current is calculated. It is
argued that a recent experiment claimed to provide evidence for s-wave
superconductivity in may also be consistent with d-wave
superconductivity. Figures available from the author on request.Comment: 10 pages, revtex3.0, TM-11111-940321-1
Superconducting film with randomly magnetized dots: A realization of the 2D XY model with random phase shifts
We consider a thin superconducting film with randomly magnetized dots on top
of it. The dots produce a disordered pinning potential for vortices in the
film. We show that for dots with permanent and random magnetization normal or
parallel to the film surface, our system is an experimental realization of the
two-dimensional XY model with random phase shifts. The low-temperature
superconducting phase, that exists without magnetic dots, survives in the
presence of magnetic dots for sufficiently small disorder.Comment: 5 pages, 1 figur
Dispersion control for matter waves and gap solitons in optical superlattices
We present a numerical study of dispersion manipulation and formation of
matter-wave gap solitons in a Bose-Einstein condensate trapped in an optical
superlattice. We demonstrate a method for controlled generation of matter-wave
gap solitons in a stationary lattice by using an interference pattern of two
condensate wavepackets, which mimics the structure of the gap soliton near the
edge of a spectral band. The efficiency of this method is compared with that of
gap soliton generation in a moving lattice recently demonstrated experimentally
by Eiermann et al. [Phys. Rev. Lett. 92, 230401 (2004)]. We show that, by
changing the relative depths of the superlattice wells, one can fine-tune the
effective dispersion of the matter waves at the edges of the mini-gaps of the
superlattice Bloch-wave spectrum and therefore effectively control both the
peak density and the spatial width of the emerging gap solitons.Comment: 8 pages, 9 figures; modified references in Section 2; minor content
changes in Sections 1 and 2 and Fig. 9 captio
RankPL: A Qualitative Probabilistic Programming Language
In this paper we introduce RankPL, a modeling language that can be thought of
as a qualitative variant of a probabilistic programming language with a
semantics based on Spohn's ranking theory. Broadly speaking, RankPL can be used
to represent and reason about processes that exhibit uncertainty expressible by
distinguishing "normal" from" surprising" events. RankPL allows (iterated)
revision of rankings over alternative program states and supports various types
of reasoning, including abduction and causal inference. We present the
language, its denotational semantics, and a number of practical examples. We
also discuss an implementation of RankPL that is available for download
Hierarchical Models for Independence Structures of Networks
We introduce a new family of network models, called hierarchical network
models, that allow us to represent in an explicit manner the stochastic
dependence among the dyads (random ties) of the network. In particular, each
member of this family can be associated with a graphical model defining
conditional independence clauses among the dyads of the network, called the
dependency graph. Every network model with dyadic independence assumption can
be generalized to construct members of this new family. Using this new
framework, we generalize the Erd\"os-R\'enyi and beta-models to create
hierarchical Erd\"os-R\'enyi and beta-models. We describe various methods for
parameter estimation as well as simulation studies for models with sparse
dependency graphs.Comment: 19 pages, 7 figure
Gaussian Belief with dynamic data and in dynamic network
In this paper we analyse Belief Propagation over a Gaussian model in a
dynamic environment. Recently, this has been proposed as a method to average
local measurement values by a distributed protocol ("Consensus Propagation",
Moallemi & Van Roy, 2006), where the average is available for read-out at every
single node. In the case that the underlying network is constant but the values
to be averaged fluctuate ("dynamic data"), convergence and accuracy are
determined by the spectral properties of an associated Ruelle-Perron-Frobenius
operator. For Gaussian models on Erdos-Renyi graphs, numerical computation
points to a spectral gap remaining in the large-size limit, implying
exceptionally good scalability. In a model where the underlying network also
fluctuates ("dynamic network"), averaging is more effective than in the dynamic
data case. Altogether, this implies very good performance of these methods in
very large systems, and opens a new field of statistical physics of large (and
dynamic) information systems.Comment: 5 pages, 7 figure
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