Multiparameter estimation along quantum trajectories with sequential Monte Carlo methods

This paper proposes an efficient method for the simultaneous estimation of the state of a quantum system and the classical parameters that govern its evolution. This hybrid approach benefits from efficient numerical methods for the integration of stochastic master equations for the quantum system, and efficient parameter estimation methods from classical signal processing. The classical techniques use sequential Monte Carlo (SMC) methods, which aim to optimize the selection of points within the parameter space, conditioned by the measurement data obtained. We illustrate these methods using a specific example, an SMC sampler applied to a nonlinear system, the Duffing oscillator, where the evolution of the quantum state of the oscillator and three Hamiltonian parameters are estimated simultaneously

Vegetation database of Great Britain: Countryside Survey

This paper describes the vegetation database created as part of the Countryside Survey (CS) of Great Britain (GIVD ID EU-GB-003) which was established to monitor ecological and land use change in 1978 (http://www.countrysidesurvey.org.uk). The sample design is based on a series of stratified, randomly selected 1 km squares, which numbered 256 in the 1978 survey, 500 in the 1990 survey, 569 in the 1998 survey and 591 in the 2007 survey. Stratification of sample squares was based on predefined strata (called land classes) which have been derived from a classification of all 1 km squares in Britain based on their topographic, climatic and geological attributes obtained from published maps. A series of vegetation plots were located within each 1 km square using a restricted randomisation procedure designed to reduce aggregation. Linear features (road verges, watercourse banks, hedges, arable margins and field boundaries) and areal features (fields, unenclosed land and small semi-natural biotope patches) were sampled. Linear plots were 1 x 10 m laid out along a feature whilst unenclosed land and small biotopes were sampled using 2 m x 2 m plots. Larger randomly-placed plots were nested 14 m² plots with an inner nest of 2 m x 2 m. Within each 1 km Countryside Survey sample square the land cover and all landscape features were mapped and each parcel of land (and vegetation plot) has been assigned to a Broad Habitat/EUNIS habitat type. This database of vegetation plots is a very useful resource. The data is freely available from the website, however, there are restrictions on the release of the spatial location of the plots. There is now a considerable time-series of plots within the database going back to 1978 representing different habitat types and landscape features that can be analysed to determine changes in vegetation metrics (e.g. Ellenberg scores) and individual species. Vegetation changes can be linked to environmental drivers and the spatial scale (across GB) is sufficiently large to analyse gradients in most driving variables

PinR mediates the generation of reversible population diversity in Streptococcus zooepidemicus

Opportunistic pathogens must adapt to and survive in a wide range of complex ecosystems. Streptococcus zooepidemicus is an opportunistic pathogen of horses and many other animals, including humans. The assembly of different surface architecture phenotypes from one genotype is likely to be crucial to the successful exploitation of such an opportunistic lifestyle. Construction of a series of mutants revealed that a serine recombinase, PinR, inverts 114 bp of the promoter of SZO_08560, which is bordered by GTAGACTTTA and TAAAGTCTAC inverted repeats. Inversion acts as a switch, controlling the transcription of this sortase-processed protein, which may enhance the attachment of S. zooepidemicus to equine trachea. The genome of a recently sequenced strain of S. zooepidemicus, 2329 (Sz2329), was found to contain a disruptive internal inversion of 7 kb of the FimIV pilus locus, which is bordered by TAGAAA and TTTCTA inverted repeats. This strain lacks pinR and this inversion may have become irreversible following the loss of this recombinase. Active inversion of FimIV was detected in three strains of S. zooepidemicus, 1770 (Sz1770), B260863 (SzB260863) and H050840501 (SzH050840501), all of which encoded pinR. A deletion mutant of Sz1770 that lacked pinR was no longer capable of inverting its internal region of FimIV. The data highlight redundancy in the PinR sequence recognition motif around a short TAGA consensus and suggest that PinR can reversibly influence the wider surface architecture of S. zooepidemicus, providing this organism with a bet-hedging solution to survival in fluctuating environments

Efficient estimation of probability of conflict between air traffic using Subset Simulation

This paper presents an efficient method for estimating the probability of conflict between air traffic within a block of airspace. Autonomous Sense-and-Avoid is an essential safety feature to enable Unmanned Air Systems to operate alongside other (manned or unmanned) air traffic. The ability to estimate probability of conflict between traffic is an essential part of Sense-and-Avoid. Such probabilities are typically very low. Evaluating low probabilities using naive Direct Monte Carlo generates a significant computational load. This paper applies a technique called Subset Simulation. The small failure probabilities are computed as a product of larger conditional failure probabilities, reducing the computational load whilst improving the accuracy of the probability estimates. The reduction in the number of samples required can be one or more orders of magnitude. The utility of the approach is demonstrated by modeling a series of conflicting and potentially conflicting scenarios based on the standard Rules of the Air

Stochastic Particle Flow for Nonlinear High-Dimensional Filtering Problems

A series of novel filters for probabilistic inference that propose an alternative way of performing Bayesian updates, called particle flow filters, have been attracting recent interest. These filters provide approximate solutions to nonlinear filtering problems. They do so by defining a continuum of densities between the prior probability density and the posterior, i.e. the filtering density. Building on these methods' successes, we propose a novel filter. The new filter aims to address the shortcomings of sequential Monte Carlo methods when applied to important nonlinear high-dimensional filtering problems. The novel filter uses equally weighted samples, each of which is associated with a local solution of the Fokker-Planck equation. This hybrid of Monte Carlo and local parametric approximation gives rise to a global approximation of the filtering density of interest. We show that, when compared with state-of-the-art methods, the Gaussian-mixture implementation of the new filtering technique, which we call Stochastic Particle Flow, has utility in the context of benchmark nonlinear high-dimensional filtering problems. In addition, we extend the original particle flow filters for tackling multi-target multi-sensor tracking problems to enable a comparison with the new filter

Multi-target out-of-sequence data association

In data fusion systems, one often encounters measurements of past target locations and then wishes to deduce where the targets are currently located. Recent research on the processing of such out-of-sequence data has culminated in the development of a number of algorithms for solving the associated tracking problem. This paper reviews these different approaches in a common Bayesian framework and proposes an architecture that orthogonalises the data association and out-of-sequence problems such that any combination of solutions to these two problems can be used together. The emphasis is not on advocating one approach over another on the basis of computational expense, but rather on understanding the relationships between the algorithms so that any approximations made are explicit

The status of Habitats Directive Annex I saltmarsh habitats, transition zones and spartina species in England

On unmodified soft sediment coastlines, of which there are long lengths especially on the English east and south coasts, there should be a wide transitional zone between tidal areas and full terrestrial land. The conditions in this zone result in a rich and distinctive range of habitats. There are two saltmarsh habitats listed in Annex I of the Habitats Directive within this zone (H1420 Mediterranean and thermo-Atlantic halophilous scrubs and H1320 Spartina swards,Spartinion maritimae) reflecting its importance for nature conservation. At the time work for this project was started in 2012, the conservation status of these habitats was reported as ‘unfavourable, bad and deteriorating’. Due to construction of artificial sea defences, these zones are now much reduced in extent and distribution and are under threat from a range of factors. This project aims to provide an inventory and description of Annex I saltmarsh habitats and transitional vegetation in England. This will help to update future reporting on conservation status. The outcomes will also help improve understanding of the underpinning processes which can be used in design to improve the potential for recreating these elements of saltmarshes as part of intertidal restoration schemes. The project also provides an up to date assessment of Spartina alterniflora stands in the Solent SAC through review and field survey for 2012