Regulatory motif discovery using a population clustering evolutionary algorithm

This paper describes a novel evolutionary algorithm for regulatory motif discovery in DNA promoter sequences. The algorithm uses data clustering to logically distribute the evolving population across the search space. Mating then takes place within local regions of the population, promoting overall solution diversity and encouraging discovery of multiple solutions. Experiments using synthetic data sets have demonstrated the algorithm's capacity to find position frequency matrix models of known regulatory motifs in relatively long promoter sequences. These experiments have also shown the algorithm's ability to maintain diversity during search and discover multiple motifs within a single population. The utility of the algorithm for discovering motifs in real biological data is demonstrated by its ability to find meaningful motifs within muscle-specific regulatory sequences

Image processing applications using a novel parallel computing machine based on reconfigurable logic

Zelig is a 32 physical node fine-grained computer employing field-programmable gate arrays. Its application to the high speed implementation of various image pre-processing operations (in particular binary morphology) is described together with typical speed-up result

Hierarchical strategies for efficient fault recovery on the reconfigurable PAnDA device

A novel hierarchical fault-tolerance methodology for reconfigurable devices is presented. A bespoke multi-reconfigurable FPGA architecture, the programmable analogue and digital array (PAnDA), is introduced allowing fine-grained reconfiguration beyond any other FPGA architecture currently in existence. Fault blind circuit repair strategies, which require no specific information of the nature or location of faults, are developed, exploiting architectural features of PAnDA. Two fault recovery techniques, stochastic and deterministic strategies, are proposed and results of each, as well as a comparison of the two, are presented. Both approaches are based on creating algorithms performing fine-grained hierarchical partial reconfiguration on faulty circuits in order to repair them. While the stochastic approach provides insights into feasibility of the method, the deterministic approach aims to generate optimal repair strategies for generic faults induced into a specific circuit. It is shown that both techniques successfully repair the benchmark circuits used after random faults are induced in random circuit locations, and the deterministic strategies are shown to operate efficiently and effectively after optimisation for a specific use case. The methods are shown to be generally applicable to any circuit on PAnDA, and to be straightforwardly customisable for any FPGA fabric providing some regularity and symmetry in its structure

THE INFLUENCE OF SALT MARSH FUCOID ALGAE (ECADS) ON SEDIMENT DYNAMICS OF NORTHWEST ATLANTIC MARSHES

Resilience is currently a key theme within salt marsh ecological studies. Understanding the factors that affect salt marsh accretion and elevation gains are of paramount importance if management of these ecosystems is to be successful under increasing synergistic stresses of storm surge, inundation period, and eutrophication. We present the results of salt marsh fucoid algae (ecads) removal experiments on Spartina alterniflora abundance, production and decomposition and the sedimentary dynamics of two marshes on Cape Cod, Massachusetts. The presence of the thick layer of marsh fucoids had a significant and positive influence on sediment deposition, accretion, concentration of water column particulates, while it inhibited water flow. Decomposition rates of Spartina alterniflora in the field were significantly higher under the fucoid macroalgae layer, and, in lab experiments, S. alterniflora seedlings added more leaves when the marsh fucoids were present. In contrast, fucoids caused a significant decrease in S. alterniflora seedlings’ survival in the field. We found that marsh fucoids are stable despite not being attached to any substrate, and field surveys revealed a relatively widespread, but not ubiquitous, distribution along outer Cape Cod. Salt marsh fucoid algae directly and substantially contribute to salt marsh sediment elevation gain, yet their potential inhibitory effects on colonizing S. alterniflora may counteract some of their overall contributions to salt marsh persistence and resilience

Variation in hospital caesarean section rates for preterm births

Background: Evidence about optimal mode of delivery for preterm birth is lacking and there is thought to be considerable variation in practice. Objective: To assess whether variation in hospital preterm caesarean section rates (Robson Classification Group 10) and outcomes are explained by casemix, labour or hospital characteristics. Materials and Methods: Population-based cohort study in NSW, 2007-2011. Births were categorised according to degree of prematurity and hospital service capability: 26-31 weeks, 32-33 weeks and 34-36 weeks. Hospital preterm caesarean rates were investigated using multilevel logistic regression models, progressively adjusting for casemix, labour and hospital factors. The association between hospital caesarean rates, and severe maternal and neonatal morbidity rates was assessed. Results: At 26-31 weeks the caesarean rate was 55.2% (7 hospitals, range 43.4-58.4%); 50.9% at 32-33 weeks (12 hospitals, 43.4- 58.1%); and 36.4% at 34-36 weeks (51 hospitals, 17.4-48.3%). At 26-31 weeks and 32-33 weeks, 81% and 59% of the variation between hospitals was explained with no hospital significantly different from the state average after adjustment. At 34-36 weeks, although 59% of the variation was explained, substantial unexplained variation persisted. Hospital caesarean rates were not associated with severe maternal morbidity rates at any gestational age. At 26-31 weeks medium and high caesarean rates were associated with higher severe neonatal morbidity rates, but there was no evidence of this association ≥32 weeks. 3 Conclusion: Both casemix and practice differences contributed to the variation in hospital caesarean rates. Low preterm caesarean rates were not associated with worse outcomes.Australian National Health and Medical Research Council; Australian Research Counci

Pearling: stroke segmentation with crusted pearl strings

We introduce a novel segmentation technique, called Pearling, for the semi-automatic extraction of idealized models of networks of strokes (variable width curves) in images. These networks may for example represent roads in an aerial photograph, vessels in a medical scan, or strokes in a drawing. The operator seeds the process by selecting representative areas of good (stroke interior) and bad colors. Then, the operator may either provide a rough trace through a particular path in the stroke graph or simply pick a starting point (seed) on a stroke and a direction of growth. Pearling computes in realtime the centerlines of the strokes, the bifurcations, and the thickness function along each stroke, hence producing a purified medial axis transform of a desired portion of the stroke graph. No prior segmentation or thresholding is required. Simple gestures may be used to trim or extend the selection or to add branches. The realtime performance and reliability of Pearling results from a novel disk-sampling approach, which traces the strokes by optimizing the positions and radii of a discrete series of disks (pearls) along the stroke. A continuous model is defined through subdivision. By design, the idealized pearl string model is slightly wider than necessary to ensure that it contains the stroke boundary. A narrower core model that fits inside the stroke is computed simultaneously. The difference between the pearl string and its core contains the boundary of the stroke and may be used to capture, compress, visualize, or analyze the raw image data along the stroke boundary