1,072 research outputs found
NASA space station automation: AI-based technology review. Executive summary
Research and Development projects in automation technology for the Space Station are described. Artificial Intelligence (AI) based technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics
Extremal Optimization at the Phase Transition of the 3-Coloring Problem
We investigate the phase transition of the 3-coloring problem on random
graphs, using the extremal optimization heuristic. 3-coloring is among the
hardest combinatorial optimization problems and is closely related to a 3-state
anti-ferromagnetic Potts model. Like many other such optimization problems, it
has been shown to exhibit a phase transition in its ground state behavior under
variation of a system parameter: the graph's mean vertex degree. This phase
transition is often associated with the instances of highest complexity. We use
extremal optimization to measure the ground state cost and the ``backbone'', an
order parameter related to ground state overlap, averaged over a large number
of instances near the transition for random graphs of size up to 512. For
graphs up to this size, benchmarks show that extremal optimization reaches
ground states and explores a sufficient number of them to give the correct
backbone value after about update steps. Finite size scaling gives
a critical mean degree value . Furthermore, the
exploration of the degenerate ground states indicates that the backbone order
parameter, measuring the constrainedness of the problem, exhibits a first-order
phase transition.Comment: RevTex4, 8 pages, 4 postscript figures, related information available
at http://www.physics.emory.edu/faculty/boettcher
Gene copy number variation throughout the Plasmodium falciparum genome
BACKGROUND: Gene copy number variation (CNV) is responsible for several important phenotypes of the malaria parasite Plasmodium falciparum, including drug resistance, loss of infected erythrocyte cytoadherence and alteration of receptor usage for erythrocyte invasion. Despite the known effects of CNV, little is known about its extent throughout the genome. RESULTS: We performed a whole-genome survey of CNV genes in P. falciparum using comparative genome hybridisation of a diverse set of 16 laboratory culture-adapted isolates to a custom designed high density Affymetrix GeneChip array. Overall, 186 genes showed hybridisation signals consistent with deletion or amplification in one or more isolate. There is a strong association of CNV with gene length, genomic location, and low orthology to genes in other Plasmodium species. Sub-telomeric regions of all chromosomes are strongly associated with CNV genes independent from members of previously described multigene families. However, approximately 40% of CNV genes were located in more central regions of the chromosomes. Among the previously undescribed CNV genes, several that are of potential phenotypic relevance are identified. CONCLUSION: CNV represents a major form of genetic variation within the P. falciparum genome; the distribution of gene features indicates the involvement of highly non-random mutational and selective processes. Additional studies should be directed at examining CNV in natural parasite populations to extend conclusions to clinical settings
Extremal Optimization of Graph Partitioning at the Percolation Threshold
The benefits of a recently proposed method to approximate hard optimization
problems are demonstrated on the graph partitioning problem. The performance of
this new method, called Extremal Optimization, is compared to Simulated
Annealing in extensive numerical simulations. While generally a complex
(NP-hard) problem, the optimization of the graph partitions is particularly
difficult for sparse graphs with average connectivities near the percolation
threshold. At this threshold, the relative error of Simulated Annealing for
large graphs is found to diverge relative to Extremal Optimization at equalized
runtime. On the other hand, Extremal Optimization, based on the extremal
dynamics of self-organized critical systems, reproduces known results about
optimal partitions at this critical point quite well.Comment: 7 pages, RevTex, 9 ps-figures included, as to appear in Journal of
Physics
Phase Transitions and Computational Difficulty in Random Constraint Satisfaction Problems
We review the understanding of the random constraint satisfaction problems,
focusing on the q-coloring of large random graphs, that has been achieved using
the cavity method of the physicists. We also discuss the properties of the
phase diagram in temperature, the connections with the glass transition
phenomenology in physics, and the related algorithmic issues.Comment: 10 pages, Proceedings of the International Workshop on
Statistical-Mechanical Informatics 2007, Kyoto (Japan) September 16-19, 200
Free-radical generation by copper ions and hydrogen peroxide. Stimulation by Hepes buffer
Separation and characterization of the aldehydic products of lipid peroxidation stimulated by carbon tetrachloride or ADP-iron in isolated rat hepatocytes and rat liver microsomal suspensions
Coupling models of cattle and farms with models of badgers for predicting the dynamics of bovine tuberculosis (TB)
Bovine TB is a major problem for the agricultural industry in several
countries. TB can be contracted and spread by species other than cattle and
this can cause a problem for disease control. In the UK and Ireland, badgers
are a recognised reservoir of infection and there has been substantial
discussion about potential control strategies. We present a coupling of
individual based models of bovine TB in badgers and cattle, which aims to
capture the key details of the natural history of the disease and of both
species at approximately county scale. The model is spatially explicit it
follows a very large number of cattle and badgers on a different grid size for
each species and includes also winter housing. We show that the model can
replicate the reported dynamics of both cattle and badger populations as well
as the increasing prevalence of the disease in cattle. Parameter space used as
input in simulations was swept out using Latin hypercube sampling and
sensitivity analysis to model outputs was conducted using mixed effect models.
By exploring a large and computationally intensive parameter space we show that
of the available control strategies it is the frequency of TB testing and
whether or not winter housing is practised that have the most significant
effects on the number of infected cattle, with the effect of winter housing
becoming stronger as farm size increases. Whether badgers were culled or not
explained about 5%, while the accuracy of the test employed to detect infected
cattle explained less than 3% of the variance in the number of infected cattle
Extremal Optimization for Graph Partitioning
Extremal optimization is a new general-purpose method for approximating
solutions to hard optimization problems. We study the method in detail by way
of the NP-hard graph partitioning problem. We discuss the scaling behavior of
extremal optimization, focusing on the convergence of the average run as a
function of runtime and system size. The method has a single free parameter,
which we determine numerically and justify using a simple argument. Our
numerical results demonstrate that on random graphs, extremal optimization
maintains consistent accuracy for increasing system sizes, with an
approximation error decreasing over runtime roughly as a power law t^(-0.4). On
geometrically structured graphs, the scaling of results from the average run
suggests that these are far from optimal, with large fluctuations between
individual trials. But when only the best runs are considered, results
consistent with theoretical arguments are recovered.Comment: 34 pages, RevTex4, 1 table and 20 ps-figures included, related papers
available at http://www.physics.emory.edu/faculty/boettcher
- …