Mutations affecting the Rossman fold of isoleucyl-tRNA synthetase are correlated with low-level mupirocin resistance in Staphylococcus aureus.

The isoleucyl-tRNA synthetase (ileS) gene was sequenced in toto from 9 and in part from 31 Staphylococcus aureus strains with various degrees of susceptibility to mupirocin. All strains for which the mupirocin MIC was greater than 8 µg/ml contained point mutations affecting the Rossman fold via Val-to-Phe changes at either residue 588 (V588F) or residue 631 (V631F). The importance of the V588F mutation was confirmed by an allele-specific PCR survey of 32 additional strains. Additional mutations of uncertain significance were found in residues clustered on the surface of the IleS protein.

Mineralogy of selected geological deposits from the United Kingdom and the Republic of Ireland as possible capping materials for low-level radioactive waste disposal facilities

Solid low-level radioactive waste (LLW) is currently being disposed at a number of facilities in the United Kingdom (UK). The safety of these facilities relies to some extent on the use of engineered barriers, such as a cap, to isolate the waste and protect the environment. Generally, the material used as the barrier layer within such a cap should be of low permeability and it should retain this property over long timescales (beyond a few decades normally required for facilities containing non-radioactive wastes). The objective of this research is to determine the mineralogy of selected geological deposits from the UK and Ireland as part of a larger project to examine their suitability as a capping material, particularly on LLW sites. Mineral transformations, as a result of future climate change, may impact on the long-term performance of the cap and even the disposal facility. X-ray diffraction (XRD) was carried-out on the sand, silt and clay fractions of the London Clay, Belfast Upper Boulder Clay, Irish Glacial Till, Belfast Sleech, and Ampthill Clay geological deposits. Minerals were present that could pose both positive and negative effects on the long-term performance of the cap. Smectite, which has a high shrink swell potential, may produce cracks in London Clay, Belfast Upper Boulder Clay and Ampthill Clay capping material during dry, hotter periods as a possible consequence of future climate change; thus, resulting in higher permeability. Ampthill Clay and Belfast Sleech had elevated amounts of organic matter (OM) at 5.93% and 5.88%, respectively, which may also contribute to cracking. Over time, this OM may decompose and result in increased permeability. Gypsum (CaSO4) in the silt and sand fractions of Ampthill Clay may reduce the impact of erosion during wetter periods if it is incorporated into the upper portion of the cap. There are potential negative effects from the acidity created by the weathering of pyrite (FeS2) present in the silt and sand fractions of Belfast Sleech and Ampthill Clay that could impede the growth of grasses used to stabilize the surface of the capping material if this material is used as part of the vegetative soil layer. Additionally, acidic waters generated from pyrite weathering could negatively impact the lower lying capping layers and the disposal facility in general. However, the calcium carbonate (CaCO3) present in the silt and sand fractions of these deposits, and dolomite (CaMg(CO3)2) in Belfast Sleech, may counter act the acidity.

Herd-level bovine tuberculosis risk factors: assessing the role of low-level badger population disturbance

Bovine TB (bTB) is endemic in Irish cattle and has eluded eradication despite considerable expenditure, amid debate over the relative roles of badgers and cattle in disease transmission. Using a comprehensive dataset from Northern Ireland (>10,000 km²; 29,513 cattle herds), we investigated interactions between host populations in one of the first large-scale risk factor analyses for new herd breakdowns to combine data on both species. Cattle risk factors (movements, international imports, bTB history, neighbours with bTB) were more strongly associated with herd risk than area-level measures of badger social group density, habitat suitability or persecution (sett disturbance). Highest risks were in areas of high badger social group density and high rates of persecution, potentially representing both responsive persecution of badgers in high cattle risk areas and effects of persecution on cattle bTB risk through badger social group disruption. Average badger persecution was associated with reduced cattle bTB risk (compared with high persecution areas), so persecution may contribute towards sustaining bTB hotspots; findings with important implications for existing and planned disease control programmes.

Evidential event inference in transport video surveillance

This paper presents a new framework for multi-subject event inference in surveillance video, where measurements produced by low-level vision analytics usually are noisy, incomplete or incorrect. Our goal is to infer the composite events undertaken by each subject from noise observations. To achieve this, we consider the temporal characteristics of event relations and propose a method to correctly associate the detected events with individual subjects. The Dempster–Shafer (DS) theory of belief functions is used to infer events of interest from the results of our vision analytics and to measure conflicts occurring during the event association. Our system is evaluated against a number of videos that present passenger behaviours on a public transport platform namely buses at different levels of complexity. The experimental results demonstrate that by reasoning with spatio-temporal correlations, the proposed method achieves a satisfying performance when associating atomic events and recognising composite events involving multiple subjects in dynamic environments.

An optimized stereo vision implementation for embedded systems: application to RGB and Infra-Red images

The aim of this paper is to demonstrate the applicability and the effectiveness of a computationally demanding stereo matching algorithm in different lowcost and low-complexity embedded devices, by focusing on the analysis of timing and image quality performances. Various optimizations have been implemented to allow its deployment on specific hardware architectures while decreasing memory and processing time requirements: (1) reduction of color channel information and resolution for input images, (2) low-level software optimizations such as parallel computation, replacement of function calls or loop unrolling, (3) reduction of redundant data structures and internal data representation. The feasibility of a stereovision system on a low cost platform is evaluated by using standard datasets and images taken from Infra-Red (IR) cameras. Analysis of the resulting disparity map accuracy with respect to a full-size dataset is performed as well as the testing of suboptimal solutions

Evidence reasoning for event inference in smart transport video surveillance

In this paper we present a new event recognition framework, based on the Dempster-Shafer theory of evidence, which combines the evidence from multiple atomic events detected by low-level computer vision analytics. The proposed framework employs evidential network modelling of composite events. This approach can effectively handle the uncertainty of the detected events, whilst inferring high-level events that have semantic meaning with high degrees of belief. Our scheme has been comprehensively evaluated against various scenarios that simulate passenger behaviour on public transport platforms such as buses and trains. The average accuracy rate of our method is 81% in comparison to 76% by a standard rule-based method.

Video Event Recognition by Dempster-Shafer Theory

This paper presents an event recognition framework, based on Dempster-Shafer theory, that combines evidence of events from low-level computer vision analytics. The proposed method employing evidential network modelling of composite events, is able to represent uncertainty of event output from low level video analysis and infer high level events with semantic meaning along with degrees of belief. The method has been evaluated on videos taken of subjects entering and leaving a seated area. This has relevance to a number of transport scenarios, such as onboard buses and trains, and also in train stations and airports. Recognition results of 78% and 100% for four composite events are encouraging.

Semantic feature-based visual attention model for pedestrian detection

Objective
Pedestrian detection under video surveillance systems has always been a hot topic in computer vision research. These systems are widely used in train stations, airports, large commercial plazas, and other public places. However, pedestrian detection remains difficult because of complex backgrounds. Given its development in recent years, the visual attention mechanism has attracted increasing attention in object detection and tracking research, and previous studies have achieved substantial progress and breakthroughs. We propose a novel pedestrian detection method based on the semantic features under the visual attention mechanism.
Method
The proposed semantic feature-based visual attention model is a spatial-temporal model that consists of two parts: the static visual attention model and the motion visual attention model. The static visual attention model in the spatial domain is constructed by combining bottom-up with top-down attention guidance. Based on the characteristics of pedestrians, the bottom-up visual attention model of Itti is improved by intensifying the orientation vectors of elementary visual features to make the visual saliency map suitable for pedestrian detection. In terms of pedestrian attributes, skin color is selected as a semantic feature for pedestrian detection. The regional and Gaussian models are adopted to construct the skin color model. Skin feature-based visual attention guidance is then proposed to complete the top-down process. The bottom-up and top-down visual attentions are linearly combined using the proper weights obtained from experiments to construct the static visual attention model in the spatial domain. The spatial-temporal visual attention model is then constructed via the motion features in the temporal domain. Based on the static visual attention model in the spatial domain, the frame difference method is combined with optical flowing to detect motion vectors. Filtering is applied to process the field of motion vectors. The saliency of motion vectors can be evaluated via motion entropy to make the selected motion feature more suitable for the spatial-temporal visual attention model.
Result
Standard datasets and practical videos are selected for the experiments. The experiments are performed on a MATLAB R2012a platform. The experimental results show that our spatial-temporal visual attention model demonstrates favorable robustness under various scenes, including indoor train station surveillance videos and outdoor scenes with swaying leaves. Our proposed model outperforms the visual attention model of Itti, the graph-based visual saliency model, the phase spectrum of quaternion Fourier transform model, and the motion channel model of Liu in terms of pedestrian detection. The proposed model achieves a 93% accuracy rate on the test video.
Conclusion
This paper proposes a novel pedestrian method based on the visual attention mechanism. A spatial-temporal visual attention model that uses low-level and semantic features is proposed to calculate the saliency map. Based on this model, the pedestrian targets can be detected through focus of attention shifts. The experimental results verify the effectiveness of the proposed attention model for detecting pedestrians.

Chloroplast microsatellites: new tools for studies in plant ecology and systematics

The nonrecombinant, uniparentally inherited nature of organelle genomes
makes them useful tools for evolutionary studies. However, in plants, detecting
useful polymorphism at the population level is often difficult because of the
low level of substitutions in the chloroplast genome, and because of the slow
substitution rates and intramolecular recombination of mtDNA. Chloroplast
microsatellites represent potentially useful markers to circumvent this problem
and, to date, studies have demonstrated high levels of intraspecific variability.
Here,we discuss the use of these markers in ecological and evolutionary
studies of plants, as well as highlighting some of the potential problems
associated with such use.

Reproductive isolation and genetic differentiation of ferox trout from sympatric brown trout in Loch Aweand Loch Laggan, Scotland

Molecular marker studies reported here, involving allozymes, mitochondrial DNA and microsatellites, demonstrate that ferox brown trout Salmo trutta in Lochs Awe and Laggan, Scotland, are reproductively isolated and genetically distinct from co-occurring brown trout. Ferox were shown to spawn primarily, and possibly solely, in a single large river in each lake system making them particularly vulnerable to environmental changes. Although a low level of introgression seems to have occurred with sympatric brown trout, possibly as a result of human-induced habitat alterations and stocking, ferox trout in these two lakes meet the requirements for classification as a distinct biological, phylogenetic and morphological species. It is proposed that the scientific name Salmo ferox Jardine, 1835, as already applied to Lough Melvin (Ireland) ferox, should be extended to Awe and Laggan ferox.