Model-based vehicle detection and classification using orthographic approximations

This paper reports the current state of work to simplify our previous model-based methods for visual tracking of vehicles for use in a real-time system intended to provide continuous monitoring and classification of traffic from a fixed camera on a busy multi-lane motorway. The main constraints of the system design were: (i) all low level processing to be carried out by low-cost auxiliary hardware, (ii) all 3-D reasoning to be carried out automatically off-line, at set-up time. The system developed uses three main stages: (i) pose and model hypothesis using 1-D templates, (ii) hypothesis tracking, and (iii) hypothesis verification, using 2-D templates. Stages (i) & (iii) have radically different computing performance and computational costs, and need to be carefully balanced for efficiency. Together, they provide an effective way to locate, track and classify vehicles.

Detection of flood extent in urban areas using high resolution TerraSAR-X data

Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. An investigation of the ability of high resolution TerraSAR-X data to detect flooded regions in urban areas is described. An important application for this would be the calibration and validation of the flood extent predicted by an urban flood inundation model. To date, research on such models has been hampered by lack of suitable distributed validation data. The study uses a 3m resolution TerraSAR-X image of a 1-in-150 year flood near Tewkesbury, UK, in 2007, for which contemporaneous aerial photography exists for validation. The DLR SETES SAR simulator was used in conjunction with airborne LiDAR data to estimate regions of the TerraSAR-X image in which water would not be visible due to radar shadow or layover caused by buildings and taller vegetation, and these regions were masked out in the flood detection process. A semi-automatic algorithm for the detection of floodwater was developed, based on a hybrid approach. Flooding in rural areas adjacent to the urban areas was detected using an active contour model (snake) region-growing algorithm seeded using the un-flooded river channel network, which was applied to the TerraSAR-X image fused with the LiDAR DTM to ensure the smooth variation of heights along the reach. A simpler region-growing approach was used in the urban areas, which was initialized using knowledge of the flood waterline in the rural areas. Seed pixels having low backscatter were identified in the urban areas using supervised classification based on training areas for water taken from the rural flood, and non-water taken from the higher urban areas. Seed pixels were required to have heights less than a spatially-varying height threshold determined from nearby rural waterline heights. Seed pixels were clustered into urban flood regions based on their close proximity, rather than requiring that all pixels in the region should have low backscatter. This approach was taken because it appeared that urban water backscatter values were corrupted in some pixels, perhaps due to contributions from side-lobes of strong reflectors nearby. The TerraSAR-X urban flood extent was validated using the flood extent visible in the aerial photos. It turned out that 76% of the urban water pixels visible to TerraSAR-X were correctly detected, with an associated false positive rate of 25%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 58% and 19% respectively. These findings indicate that TerraSAR-X is capable of providing useful data for the calibration and validation of urban flood inundation models.

Identifying management zones in agricultural fields using spatially constrained classification of soil and ancillary data

Site-specific management requires accurate knowledge of the spatial variation in a range of soil properties within fields. This involves considerable sampling effort, which is costly. Ancillary data, such as crop yield, elevation and apparent electrical conductivity (ECa) of the soil, can provide insight into the spatial variation of some soil properties. A multivariate classification with spatial constraint imposed by the variogram was used to classify data from two arable crop fields. The yield data comprised 5 years of crop yield, and the ancillary data 3 years of yield data, elevation and ECa. Information on soil chemical and physical properties was provided by intensive surveys of the soil. Multivariate variograms computed from these data were used to constrain sites spatially within classes to increase their contiguity. The constrained classifications resulted in coherent classes, and those based on the ancillary data were similar to those from the soil properties. The ancillary data seemed to identify areas in the field where the soil is reasonably homogeneous. The results of targeted sampling showed that these classes could be used as a basis for management and to guide future sampling of the soil.

A review and classification of the existing models of cyanobacteria

Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting bloom occurrence in lakes and rivers. In this paper existing key models of cyanobacteria are reviewed, evaluated and classified. Two major groups emerge: deterministic mathematical and artificial neural network models. Mathematical models can be further subcategorized into those models concerned with impounded water bodies and those concerned with rivers. Most existing models focus on a single aspect such as the growth of transport mechanisms, but there are a few models which couple both.

Independent evaluation of the ability of spaceborne radar and lidar to retrieve the microphysical and radiative properties of ice clouds

The combination of radar and lidar in space offers the unique potential to retrieve vertical profiles of ice water content and particle size globally, and two algorithms developed recently claim to have overcome the principal difficulty with this approach-that of correcting the lidar signal for extinction. In this paper "blind tests" of these algorithms are carried out, using realistic 94-GHz radar and 355-nm lidar backscatter profiles simulated from aircraft-measured size spectra, and including the effects of molecular scattering, multiple scattering, and instrument noise. Radiation calculations are performed on the true and retrieved microphysical profiles to estimate the accuracy with which radiative flux profiles could be inferred remotely. It is found that the visible extinction profile can be retrieved independent of assumptions on the nature of the size distribution, the habit of the particles, the mean extinction-to-backscatter ratio, or errors in instrument calibration. Local errors in retrieved extinction can occur in proportion to local fluctuations in the extinction-to-backscatter ratio, but down to 400 m above the height of the lowest lidar return, optical depth is typically retrieved to better than 0.2. Retrieval uncertainties are greater at the far end of the profile, and errors in total optical depth can exceed 1, which changes the shortwave radiative effect of the cloud by around 20%. Longwave fluxes are much less sensitive to errors in total optical depth, and may generally be calculated to better than 2 W m(-2) throughout the profile. It is important for retrieval algorithms to account for the effects of lidar multiple scattering, because if this is neglected, then optical depth is underestimated by approximately 35%, resulting in cloud radiative effects being underestimated by around 30% in the shortwave and 15% in the longwave. Unlike the extinction coefficient, the inferred ice water content and particle size can vary by 30%, depending on the assumed mass-size relationship (a problem common to all remote retrieval algorithms). However, radiative fluxes are almost completely determined by the extinction profile, and if this is correct, then errors in these other parameters have only a small effect in the shortwave (around 6%, compared to that of clear sky) and a negligible effect in the longwave.

Soft topographic map for clustering and classification of bacteria

In this work a new method for clustering and building a topographic representation of a bacteria taxonomy is presented. The method is based on the analysis of stable parts of the genome, the so-called “housekeeping genes”. The proposed method generates topographic maps of the bacteria taxonomy, where relations among different type strains can be visually inspected and verified. Two well known DNA alignement algorithms are applied to the genomic sequences. Topographic maps are optimized to represent the similarity among the sequences according to their evolutionary distances. The experimental analysis is carried out on 147 type strains of the Gammaprotebacteria class by means of the 16S rRNA housekeeping gene. Complete sequences of the gene have been retrieved from the NCBI public database. In the experimental tests the maps show clusters of homologous type strains and present some singular cases potentially due to incorrect classification or erroneous annotations in the database.

Foods derived from animals: the impact of animal nutrition on their nutritive value and ability to sustain long-term health

Foods derived from domestic animals are a significant source of nutrients in the UK diet. However, certain aspects of some animal-derived foods, notably levels of saturated fatty acids, have given rise to concerns that these foods may contribute to the risk of cardiovascular disease, the metabolic syndrome and other conditions. However, the composition of the many animal-derived foods is not constant and can often be enhanced by manipulating the nutrition of the animal. This paper reviews these possibilities with particular attention to lipids, and draws attention to the fact that milk in particular, contains a number of compounds which may, for example, exert anti-carcinogenic effects. It is clear that the role of animal nutrition in creating foods closer to the optimum composition for long-term human health will not only be more relevant in the future, but will be vital in attempts to improve the health of the human population.

Successful long-term ultra dry storage of seed of 15 species of Brassicaceae in a genebank: variation in ability to germinate over 40 years and dormancy

Seed of 15 species of Brassicaceae were stored hermetically in a genebank (at -5 degrees C to -10 degrees C with c. 3% moisture content) for 40 years. Samples were withdrawn at intervals for germination tests. Many accessions showed an increase in ability to germinate over this period. due to loss in dormancy. Nevertheless, some dormancy remained after 40 years' storage and was broken by pre-applied gibberellic acid. The poorest seed survival occurred in Hormatophylla spinosa. Even in this accession the ability to germinate declined by only 7% between 1966 and 2006. Comparison of seeds from 1966 stored for 40 years with those collected anew in 2006 from the original sampling sites, where possible, showed few differences, other than a tendency (7 of 9 accessions) for the latter to show greater dormancy. These results for hermetic storage at sub-zero temperatures and low moisture contents confirm that long-term seed storage can provide a successful technology for ex situ plant biodiversity conservation.

Macrophyte community structure and species occurrence in relation to environmental determinants in the ephemeral aquatic habitats of Gavdos, Greece

The aims of this study were to explore the environmental factors that determine the distribution of plant communities in temporary rock pools and provide a quantitative analysis of vegetation-environment relationships for five study sites on the island of Gavdos, southwest of Crete, Greece. Data from 99 rock pools were collected and analysed using Two-Way Indicator Species Analysis (TWINSPAN), Detrended Correspondence Analysis (DCA) and Canonical Correspondence Analysis (CCA) to identify the principal communities and environmental gradients that are linked to community distribution. A total of 46 species belonging to 21 families were recorded within the study area. The dominant families were Labiatae, Gramineae and Compositae while therophytes and chamaephytes were the most frequent life forms. The samples were classified into six community types using TWINSPAN, which were also corroborated by CCA analysis. The principal gradients for vegetation distribution, identified by CCA, were associated with water storage and water retention ability, as expressed by pool perimeter and water depth. Generalised Additive Models (GAMs) were employed to identify responses of four dominant rock pool species to water depth. The resulting species response curves showed niche differentiation in the cases of Callitriche pulchra and Tillaea vaillantii and revealed competition between Zannichellia pedunculata and Chara vulgaris. The use of classification in combination with ordination techniques resulted in a good discrimination between plant communities. Generalised Additive Models are a powerful tool in investigating species response curves to environmental gradients. The methodology adopted can be employed for improving baseline information on plant community ecology and distribution in Mediterranean ephemeral pools.

Common variants of apolipoprotein A-IV differ in their ability to inhibit low density lipoprotein oxidation

Apolipoprotein A-IV (apoA-IV) inhibits lipid peroxidation, thus demonstrating potential anti-atherogenic properties. The aim of this study was to investigate how the inhibition of low density lipoprotein (LDL) oxidation was influenced by common apoA-IV isoforms. Recombinant wild type apoA-IV (100 mu g/ml) significantly inhibited the oxidation of LDL (50 mu g protein/ml) by 5 mu M CuSO4 (P < 0.005), but not by 100 mu M CuSO4, suggesting that it may act by binding copper ions. ApoA-IV also inhibited the oxidation of LDL by the water-soluble free-radical generator 2,2'-azobis(amidinopropane) dihydrochloride (AAPH; I mM), as shown by the two-fold increase in the time for half maximal conjugated diene formation (T-1/2; P < 0.05) suggesting it can also scavenge free radicals in the aqueous phase. Compared to wild type apoA-IV, apoA-IV-S347 decreased T-1/2 by 15% (P = 0.036) and apoA-IV-H360 increased T-1/2 by 18% (P = 0.046). All apoA-IV isoforms increased the relative electrophoretic mobility of native LDL, suggesting apoA-IV can bind to LDL and acts as a site-specific antioxidant. The reduced inhibition of LDL oxidation by apoA-IV-S347 compared to wild type apoA-IV may account for the previous association of the APOA4 S347 variant with increased CHD risk and oxidative stress. (c) 2006 Elsevier Ireland Ltd. All rights reserved.