Multiresolution semantic activity characterisation and abnormality discovery in videos

This paper addresses the issue of activity understanding from video and its semantics-rich description. A novel approach is presented where activities are characterised and analysed at different resolutions. Semantic information is delivered according to the resolution at which the activity is observed. Furthermore, the multiresolution activity characterisation is exploited to detect abnormal activity. To achieve these system capabilities, the focus is given on context modelling by employing a soft computing-based algorithm which automatically enables the determination of the main activity zones of the observed scene by taking as input the trajectories of detected mobiles. Such areas are learnt at different resolutions (or granularities). In a second stage, learned zones are employed to extract people activities by relating mobile trajectories to the learned zones. In this way, the activity of a person can be summarised as the series of zones that the person has visited. Employing the inherent soft relation properties, the reported activities can be labelled with meaningful semantics. Depending on the granularity at which activity zones and mobile trajectories are considered, the semantic meaning of the activity shifts from broad interpretation to detailed description.Activity information at different resolutions is also employed to perform abnormal activity detection.

Simulation of long-term thermal characteristics of three Estonian lakes

A one-dimensional surface energy-balance lake model, coupled to a thermodynamic model of lake ice, is used to simulate variations in the temperature of and evaporation from three Estonian lakes: Karujärv, Viljandi and Kirjaku. The model is driven by daily climate data, derived by cubic-spline interpolation from monthly mean data, and was run for periods of 8 years (Kirjaku) up to 30 years (Viljandi). Simulated surface water temperature is in good agreement with observations: mean differences between simulated and observed temperatures are from −0.8°C to +0.1°C. The simulated duration of snow and ice cover is comparable with observed. However, the model generally underpredicts ice thickness and overpredicts snow depth. Sensitivity analyses suggest that the model results are robust across a wide range (0.1–2.0 m−1) of lake extinction coefficient: surface temperature differs by less than 0.5°C between extreme values of the extinction coefficient. The model results are more sensitive to snow and ice albedos. However, changing the snow (0.2–0.9) and ice (0.15–0.55) albedos within realistic ranges does not improve the simulations of snow depth and ice thickness. The underestimation of ice thickness is correlated with the overestimation of snow cover, since a thick snow layer insulates the ice and limits ice formation. The overestimation of snow cover results from the assumption that all the simulated winter precipitation occurs as snow, a direct consequence of using daily climate data derived by interpolation from mean monthly data.

Supramolecular materials for inkjet printing: self-assembling polymer networks

Electronically complementary, low molecular weight polymers that self-assemble through tuneable π-π stacking interactions to form extended supramolecular polymer networks have been developed for inkjet printing applications and successfully deposited using three different printing techniques. Sequential overprinting of the complementary components results in supramolecular network formation through complexation of π-electron rich pyrenyl or perylenyl chain-ends in one component with π-electron deficient naphthalene diimide residues in a chain-folding polyimide. The complementary π-π stacked polymer blends generate strongly coloured materials as a result of charge-transfer absorptions in the visible spectrum, potentially negating the need for pigments or dyes in the ink formulation. Indeed, the final colour of the deposited material can be tailored by changing varying the end-groups of the π electron rich polymer component. Piezoelectric printing techniques were employed in a proof of concept study to allow characterisation of the materials deposited, and a thermal inkjet printer adapted with imaging software enabled a detailed analysis of the ink-drops as they formed, and of their physical properties. Finally, continuous inkjet printing allowed greater volumes of material to be deposited, on a variety of different substrate surfaces, and demonstrated the utility and versatility of this novel type of ink for industrial applications.

Experimental evolution for generalists and specialists reveals multivariate genetic constraints on thermal reaction norms

Theory predicts the emergence of generalists in variable environments and antagonistic pleiotropy to favour specialists in constant environments, but empirical data seldom support such generalist–specialist trade-offs. We selected for generalists and specialists in the dung fly Sepsis punctum (Diptera: Sepsidae) under conditions that we predicted would reveal antagonistic pleiotropy and multivariate trade-offs underlying thermal reaction norms for juvenile development. We performed replicated laboratory evolution using four treatments: adaptation at a hot (31 °C) or a cold (15 °C) temperature, or under regimes fluctuating between these temperatures, either within or between generations. After 20 generations, we assessed parental effects and genetic responses of thermal reaction norms for three correlated life-history traits: size at maturity, juvenile growth rate and juvenile survival. We find evidence for antagonistic pleiotropy for performance at hot and cold temperatures, and a temperature-mediated trade-off between juvenile survival and size at maturity, suggesting that trade-offs associated with environmental tolerance can arise via intensified evolutionary compromises between genetically correlated traits. However, despite this antagonistic pleiotropy, we found no support for the evolution of increased thermal tolerance breadth at the expense of reduced maximal performance, suggesting low genetic variance in the generalist–specialist dimension.

A critical evaluation of the ability of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) thermal infrared red-green-blue rendering to identify dust events: theoretical analysis

Using a combination of idealized radiative transfer simulations and a case study from the first field campaign of the Saharan Mineral Dust Experiment (SAMUM) in southern Morocco, this paper provides a systematic assessment of the limitations of the widely used Spinning Enhanced Visible and Infrared Imager (SEVIRI) red-green-blue (RGB) thermal infrared dust product. Both analyses indicate that the ability of the product to identify dust, via its characteristic pink coloring, is strongly dependent on the column water vapor, the lower tropospheric lapse rate, and dust altitude. In particular, when column water vapor exceeds ∼20–25 mm, dust presence, even for visible optical depths of the order 0.8, is effectively masked. Variability in dust optical properties also has a marked impact on the imagery, primarily as a result of variability in dust composition. There is a moderate sensitivity to the satellite viewing geometry, particularly in moist conditions. The underlying surface can act to confound the signal seen through variations in spectral emissivity, which are predominantly manifested in the 8.7μm SEVIRI channel. In addition, if a temperature inversion is present, typical of early morning conditions over the Sahara and Sahel, an increased dust loading can actually reduce the pink coloring of the RGB image compared to pristine conditions. Attempts to match specific SEVIRI observations to simulations using SAMUM measurements are challenging because of high uncertainties in surface skin temperature and emissivity. Recommendations concerning the use and interpretation of the SEVIRI RGB imagery are provided on the basis of these findings.

Synthesis, characterisation and magnetic properties of a one-dimensional Iron(II) coordination polymer

A new iron(II) coordination polymer, [FeCl2(NC7H9)2(N2C12H12)], has been synthesized under solvothermal conditions and structurally characterized by single-crystal X-ray diffraction. This material crystallizes in the monoclinic space group C2/c, with a = 11.2850(6), b = 13.8925(7), c = 17.0988(9) Å and β = 94.300(3)º (Z = 4). The crystal structure consists of neutral zig-zag chains, in which the iron(II) ions are octahedrally coordinated. The infinite polymer chains are packed into a three-dimensional structure through C–H···Cl interactions. Magnetic susceptibility measurements reveal the existence of weak antiferromagnetic interactions between the iron(II) ions. The effective magnetic moment, μ eff = 5.33 μ B , is consistent with a high-spin iron(II) configuration.

Thermal and pressure stability of myrosinase enzymes from black mustard (Brassica nigra L. W.D.J Koch. var. nigra), brown mustard (Brassica juncea L. Czern. var. juncea) and yellow mustard (Sinapsis alba L. Subsp Maire) seeds

This study investigates the effects of temperature and pressure on inactivation of myrosinase extracted from black, brown and yellow mustard seeds. Brown mustard had higher myrosinase activity (2.75 un/mL) than black (1.50 un/mL) and yellow mustard (0.63 un/mL). The extent of enzyme inactivation increased with pressure (600-800 MPa) and temperature (30-70 °C) for all the mustard seeds. However, at combinations of lower pressures (200-400 MPa) and high temperatures (60-80 °C), there was less inactivation. For example, application of 300 MPa and 70 °C for 10 minutes retained 20%, 80% and 65% activity in yellow, black and brown mustard, respectively, whereas the corresponding activity retentions when applying only heat (70 °C, 10min) were 0%, 59% and 35%. Thus, application of moderate pressures (200-400 MPa) can potentially be used to retain myrosinase activity needed for subsequent glucosinolate hydrolysis.