The FunFOLD2 server for the prediction of protein-ligand interactions

The FunFOLD2 server is a new independent server that integrates our novel protein–ligand binding site and quality assessment protocols for the prediction of protein function (FN) from sequence via structure. Our guiding principles were, first, to provide a simple unified resource to make our function prediction software easily accessible to all via a simple web interface and, second, to produce integrated output for predictions that can be easily interpreted. The server provides a clean web interface so that results can be viewed on a single page and interpreted by non-experts at a glance. The output for the prediction is an image of the top predicted tertiary structure annotated to indicate putative ligand-binding site residues. The results page also includes a list of the most likely binding site residues and the types of predicted ligands and their frequencies in similar structures. The protein–ligand interactions can also be interactively visualized in 3D using the Jmol plug-in. The raw machine readable data are provided for developers, which comply with the Critical Assessment of Techniques for Protein Structure Prediction data standards for FN predictions. The FunFOLD2 webserver is freely available to all at the following web site: http://www.reading.ac.uk/bioinf/FunFOLD/FunFOLD_form_2_0.html.

Detection of flooded urban areas in high resolution Synthetic Aperture Radar images using double scattering

Flooding is a particular hazard in urban areas worldwide due to the increased risks to life and property in these regions. Synthetic Aperture Radar (SAR) sensors are often used to image flooding because of their all-weather day-night capability, and now possess sufficient resolution to image urban flooding. The flood extents extracted from the images may be used for flood relief management and improved urban flood inundation modelling. A difficulty with using SAR for urban flood detection is that, due to its side-looking nature, substantial areas of urban ground surface may not be visible to the SAR due to radar layover and shadow caused by buildings and taller vegetation. This paper investigates whether urban flooding can be detected in layover regions (where flooding may not normally be apparent) using double scattering between the (possibly flooded) ground surface and the walls of adjacent buildings. The method estimates double scattering strengths using a SAR image in conjunction with a high resolution LiDAR (Light Detection and Ranging) height map of the urban area. A SAR simulator is applied to the LiDAR data to generate maps of layover and shadow, and estimate the positions of double scattering curves in the SAR image. Observations of double scattering strengths were compared to the predictions from an electromagnetic scattering model, for both the case of a single image containing flooding, and a change detection case in which the flooded image was compared to an un-flooded image of the same area acquired with the same radar parameters. The method proved successful in detecting double scattering due to flooding in the single-image case, for which flooded double scattering curves were detected with 100% classification accuracy (albeit using a small sample set) and un-flooded curves with 91% classification accuracy. The same measures of success were achieved using change detection between flooded and un-flooded images. Depending on the particular flooding situation, the method could lead to improved detection of flooding in urban areas.

Progress report on longitudinal and cross-sectional study of carbon disclosure strategies: evidence from UK listed companies

Global warming has attracted attention from all over the world and led to the concern about carbon emission. Kyoto Protocol, as the first major international regulatory emission trading scheme, was introduced in 1997 and outlined the strategies for reducing carbon emission (Ratnatunga et al., 2011). As the increased interest in carbon reduction the Protocol came into force in 2005, currently there are already 191 nations ratifying the Protocol(UNFCCC, 2012). Under the cap-and-trade schemes, each company has its carbon emission target. When company’s carbon emission exceeds the target the company will either face fines or buy emission allowance from other companies. Thus unlike most of the other social and environmental issues carbon emission could trigger cost for companies in introducing low-emission equipment and systems and also emission allowance cost when they emit more than their targets. Despite the importance of carbon emission to companies, carbon emission reporting is still operating under unregulated environment and companies are only required to disclose when it is material either in value or in substances (Miller, 2005, Deegan and Rankin, 1997). Even though there is still an increase in the volume of carbon emission disclosures in company’s financial reports and stand-alone social and environmental reports to show their concern of the environment and also their social responsibility (Peters and Romi, 2009), the motivations behind corporate carbon emission disclosures and whether carbon disclosures have impact on corporate environmental reputation and financial performance have not yet to explore. The problems with carbon emission lie on both the financial side and non-financial side of corporate governance. On one hand corporate needs to spend money in reducing carbon emission or paying penalties when they emit more than allowed. On the other hand as the public are more interested in environmental issues than before carbon emission could also impact on the image of corporate regarding to its environmental performance. The importance of carbon emission issue are beginning to be recognized by companies from different industries as one of the critical issues in supply chain management (Lee, 2011) and 80% of companies analysed are facing carbon risks resulting from emissions in the companies’ supply chain as shown in a study conducted by the Investor Responsibility Research Centre Institute for Corporate Responsibility (IRRCI) and over 80% of the companies analysed found that the majority of greenhouse gas (GHG) emission are from electricity and other direct suppliers (Trucost, 2009). The review of extant literature shows the increased importance of carbon emission issues and the gap in the study of carbon reporting and disclosures and also the study which links corporate environmental reputation and corporate financial performance with carbon reporting (Lohmann, 2009a, Ratnatunga and Balachandran, 2009, Bebbington and Larrinaga-Gonzalez, 2008). This study would focus on investigating the current status of UK carbon emission disclosures, the determinant factors of corporate carbon disclosure, and the relationship between carbon emission disclosures and corporate environmental reputation and financial performance of UK listed companies from 2004-2012 and explore the explanatory power of classical disclosure theories.

Global climatology of surface water temperatures of large lakes by remote sensing

Lake surface water temperatures (LSWTs) of 246 globally distributed large lakes were derived from Along-Track Scanning Radiometers (ATSR) for the period 1991–2011. The climatological cycles of mean LSWT derived from these data quantify on a global scale the responses of large lakes' surface temperatures to the annual cycle of forcing by solar radiation and the ambient meteorological conditions. LSWT cycles reflect the twice annual peak in net solar radiation for lakes between 1°S to 12°N. For lakes without a lake-mean seasonal ice cover, LSWT extremes exceed air temperatures by 0.5–1.7 °C for maximum and 0.7–1.9 °C for minimum temperature. The summer maximum LSWTs of lakes from 25°S to 35°N show a linear decrease with increasing altitude; −3.76 ± 0.17 °C km−1 (inline image = 0.95), marginally lower than the corresponding air temperature decrease with altitude −4.15 ± 0.24 °C km−1 (inline image = 0.95). Lake altitude of tropical lakes account for 0.78–0.83 (inline image) of the variation in the March to June LSWT–air temperature differences, with differences decreasing by 1.9 °C as the altitude increases from 500 to 1800 m above sea level (a.s.l.) We define an ‘open water phase’ as the length of time the lake-mean LSWT remains above 4 °C. There is a strong global correlation between the start and end of the lake-mean open water phase and the spring and fall 0 °C air temperature transition days, (inline image = 0.74 and 0.80, respectively), allowing for a good estimation of timing and length of the open water phase of lakes without LSWT observations. Lake depth, lake altitude and distance from coast further explain some of the inter-lake variation in the start and end of the open water phase.