Adapting to climate change impacts on water resources in England - an assessment of draft Water Resources Management Plans

Climate change is expected to produce reductions in water availability in England, potentially necessitating adaptive action by the water industry to maintain supplies. As part of Ofwat's fifth Periodic Review (PR09), water companies recently released their draft Water Resources Management Plans, setting out how each company intends to maintain the balance between the supply and demand for water over the next 25 years, following Environment Agency guidelines. This paper reviews these plans to determine company estimates of the impact of climate change on water supply relative to other resource pressures. The approaches adopted for incorporating the impact in the plans and the proposed management solutions are also identified. Climate change impacts for individual resource zones range from no reductions in deployable output to greater than 50% over the planning period. The estimated national aggregated loss of deployable output under a “core” climate scenario is ~520 Ml/d (3% of deployable output) by 2034/35, the equivalent of the supply of one entire water company (South West Water). Climate change is the largest single driver of change in water supplies over the planning period. Over half of the climate change impact is concentrated in southern England. In extreme cases, climate change uncertainty is of the same magnitude as the change under the core scenario (up to a loss of ~475 Ml/d). 44 of the 68 resource zones with available data are estimated to have a climate change impact. In 35 of these climate change has the greatest impact although in 10 zones sustainability reductions have a greater impact. Of the overall change in downward pressure on the supply-demand balance over the planning period, ~56% is accounted for by increased demand (620 Ml/d) and supply side climate change accounts for ~37% (407 Ml/d). Climate change impacts have a cumulative impact in concert with other changing supply side reducing components increasing the national pressure on the supply-demand balance. Whilst the magnitude of climate change appears to justify its explicit consideration, it is rare that adaptation options are planned solely in response to climate change but as a suite of options to provide a resilient supply to a range of pressures (including significant demand side pressures). Supply-side measures still tend to be considered by water companies to be more reliable than demand-side measures.

Amyloid formation: interface influence

The causes of pathological conditions such as Alzheimer’s and Parkinson’s diseases are becoming better understood. Proteins that misfold from their native structure to form aggregates of β-sheet fibrils — termed amyloid — are known1,2 to be implicated in these ‘amyloid diseases’. Understanding the early steps of fibril formation is critical, and the conditions, mechanism and kinetics of protein and peptide aggregation are being widely investigated through a variety of in vitro studies. Kinetic aspects of the dispersion of the protein or peptide in solution are thought to influence the fibrillization process by mass-transfer effects. In addition, mixing also leads to shear forces, which can influence fibril growth by perturbing the equilibrium between the isolated and aggregated proteins, causing existing fibrils to fragment and create new nuclei3. Writing in the Journal of the American Chemical Society, David Talaga and co-workers have now highlighted4 an additional factor that can influence the fibrillization of amyloid-forming proteins — the presence of hydrophobic interfaces.

Video activity extraction and reporting with incremental unsupervised learning

The present work presents a new method for activity extraction and reporting from video based on the aggregation of fuzzy relations. Trajectory clustering is first employed mainly to discover the points of entry and exit of mobiles appearing in the scene. In a second step, proximity relations between resulting clusters of detected mobiles and contextual elements from the scene are modeled employing fuzzy relations. These can then be aggregated employing typical soft-computing algebra. A clustering algorithm based on the transitive closure calculation of the fuzzy relations allows building the structure of the scene and characterises the ongoing different activities of the scene. Discovered activity zones can be reported as activity maps with different granularities thanks to the analysis of the transitive closure matrix. Taking advantage of the soft relation properties, activity zones and related activities can be labeled in a more human-like language. We present results obtained on real videos corresponding to apron monitoring in the Toulouse airport in France.

Individual assets, market structure and the drivers of return

Much prior research on the structure and performance of UK real estate portfolios has relied on aggregated measures for sector and region. For these groupings to have validity, the performance of individual properties within each group should be similar. This paper analyses a sample of 1,200 properties using multiple discriminant analysis and cluster analysis techniques. It is shown that conventional property type and spatial classifications do not capture the variation in return behaviour at the individual building level. The major feature is heterogeneity - but there may be distinctions between growth and income properties and between single and multi-let properties that could help refine portfolio structures.

Energy at work: a measurement validation and linkage to unit effectiveness

We introduce the notion that the energy of individuals can manifest as a higher-level, collective construct. To this end, we conducted four independent studies to investigate the viability and importance of the collective energy construct as assessed by a new survey instrument—the productive energy measure (PEM). Study 1 (n = 2208) included exploratory and confirmatory factor analyses to explore the underlying factor structure of PEM. Study 2 (n = 660) cross-validated the same factor structure in an independent sample. In study 3, we administered the PEM to more than 5000 employees from 145 departments located in five countries. Results from measurement invariance, statistical aggregation, convergent, and discriminant-validity assessments offered additional support for the construct validity of PEM. In terms of predictive and incremental validity, the PEM was positively associated with three collective attitudes—units' commitment to goals, the organization, and overall satisfaction. In study 4, we explored the relationship between the productive energy of firms and their overall performance. Using data from 92 firms (n = 5939employees), we found a positive relationship between the PEM (aggregated to the firm level) and the performance of those firms. Copyright © 2011 John Wiley & Sons, Ltd.

Precisely wrong or roughly right? An evaluation of development viability appraisal modelling

Purpose – The purpose of this paper is to investigate the effect of choices of model structure and scale in development viability appraisal. The paper addresses two questions concerning the application of development appraisal techniques to viability modelling within the UK planning system. The first relates to the extent to which, given intrinsic input uncertainty, the choice of model structure significantly affects model outputs. The second concerns the extent to which, given intrinsic input uncertainty, the level of model complexity significantly affects model outputs. Design/methodology/approach – Monte Carlo simulation procedures are applied to a hypothetical development scheme in order to measure the effects of model aggregation and structure on model output variance. Findings – It is concluded that, given the particular scheme modelled and unavoidably subjective assumptions of input variance, that simple and simplistic models may produce similar outputs to more robust and disaggregated models. Evidence is found of equifinality in the outputs of a simple, aggregated model of development viability relative to more complex, disaggregated models. Originality/value – Development viability appraisal has become increasingly important in the planning system. Consequently, the theory, application and outputs from development appraisal are under intense scrutiny from a wide range of users. However, there has been very little published evaluation of viability models. This paper contributes to the limited literature in this area.

Determination of turbulent heat fluxes using a large aperture scintillometer over undulating mixed agricultural terrain

Scintillometry is an established technique for determining large areal average sensible heat fluxes. The scintillometer measurement is related to sensible heat flux via Monin–Obukhov similarity theory, which was developed for ideal homogeneous land surfaces. In this study it is shown that judicious application of scintillometry over heterogeneous mixed agriculture on undulating topography yields valid results when compared to eddy covariance (EC). A large aperture scintillometer (LAS) over a 2.4 km path was compared with four EC stations measuring sensible (H) and latent (LvE) heat fluxes over different vegetation (cereals and grass) which when aggregated were representative of the LAS source area. The partitioning of available energy into H and LvE varied strongly for different vegetation types, with H varying by a factor of three between senesced winter wheat and grass pasture. The LAS derived H agrees (one-to-one within the experimental uncertainty) with H aggregated from EC with a high coefficient of determination of 0.94. Chronological analysis shows individual fields may have a varying contribution to the areal average sensible heat flux on short (weekly) time scales due to phenological development and changing soil moisture conditions. Using spatially aggregated measurements of net radiation and soil heat flux with H from the LAS, the areal averaged latent heat flux (LvELAS) was calculated as the residual of the surface energy balance. The regression of LvELAS against aggregated LvE from the EC stations has a slope of 0.94, close to ideal, and demonstrates that this is an accurate method for the landscape-scale estimation of evaporation over heterogeneous complex topography.

Epidemic K-Means clustering

The K-Means algorithm for cluster analysis is one of the most influential and popular data mining methods. Its straightforward parallel formulation is well suited for distributed memory systems with reliable interconnection networks. However, in large-scale geographically distributed systems the straightforward parallel algorithm can be rendered useless by a single communication failure or high latency in communication paths. This work proposes a fully decentralised algorithm (Epidemic K-Means) which does not require global communication and is intrinsically fault tolerant. The proposed distributed K-Means algorithm provides a clustering solution which can approximate the solution of an ideal centralised algorithm over the aggregated data as closely as desired. A comparative performance analysis is carried out against the state of the art distributed K-Means algorithms based on sampling methods. The experimental analysis confirms that the proposed algorithm is a practical and accurate distributed K-Means implementation for networked systems of very large and extreme scale.

Oxidation of low density lipoprotein by iron at lysosomal pH: implications for atherosclerosis

Low density lipoprotein (LDL) has recently been shown to be oxidised by iron within the lysosomes of macrophages and this is a novel potential mechanism for LDL oxidation in atherosclerosis. Our aim was to characterise the chemical and physical changes induced in LDL by iron at lysosomal pH and to investigate the effects of iron chelators and α-tocopherol on this process. LDL was oxidised by iron at pH 4.5 and 37°C and its oxidation monitored by spectrophotometry and HPLC. LDL was oxidised effectively by FeSO4 (5-50 µM) and became highly aggregated at pH 4.5, but not at pH 7.4. Cholesteryl esters decreased and after a pronounced lag 7-ketocholesterol increased greatly. Total hydroperoxides (measured by tri-iodide assay) increased up to 24 h and then decreased only slowly. The lipid composition after 12 h at pH 4.5 and 37°C was similar to that of LDL oxidised by copper at pH 7.4 and 4°C, i.e. rich in hydroperoxides but low in oxysterols. Previously oxidised LDL aggregated rapidly and spontaneously at pH 4.5, but not at pH 7.4. Ferrous was much more effective than ferric iron at oxidising LDL when added after the oxidation was already underway. The iron chelators diethylenetriaminepentaacetic acid and, to a lesser extent, desferrioxamine inhibited LDL oxidation when added during its initial stages, but were unable to prevent LDL aggregating after it had been partially oxidised. Surprisingly, desferrioxamine increased the rate of LDL modification when added late in the oxidation process. α-Tocopherol enrichment of LDL initially increased the oxidation of LDL, but inhibited it later. The presence of oxidised and highly aggregated lipid within lysosomes has the potential to perturb the function of these organelles and to promote atherosclerosis.

Risk reduction and diversification in UK commercial property portfolios

The issue of diversification in direct real estate investment portfolios has been widely studied in academic and practitioner literature. Most work, however, has been done using either partially aggregated data or data for small samples of individual properties. This paper reports results from tests of both risk reduction and diversification that use the records of 10,000+ UK properties tracked by Investment Property Databank. It provides, for the first time, robust estimates of the diversification gains attainable given the returns, risks and cross‐correlations across the individual properties available to fund managers. The results quantify the number of assets and amount of money needed to construct both ‘balanced’ and ‘specialist’ property portfolios by direct investment. Target numbers will vary according to the objectives of investors and the degree to which tracking error is tolerated. The top‐level results are consistent with previous work, showing that a large measure of risk reduction can be achieved with portfolios of 30–50 properties, but full diversification of specific risk can only be achieved in very large portfolios. However, the paper extends previous work by demonstrating on a single, large dataset the implications of different methods of calculating risk reduction, and also by showing more disaggregated results relevant to the construction of specialist, sector‐focussed funds.

Fault tolerant decentralised K-Means clustering for asynchronous large-scale networks

The K-Means algorithm for cluster analysis is one of the most influential and popular data mining methods. Its straightforward parallel formulation is well suited for distributed memory systems with reliable interconnection networks, such as massively parallel processors and clusters of workstations. However, in large-scale geographically distributed systems the straightforward parallel algorithm can be rendered useless by a single communication failure or high latency in communication paths. The lack of scalable and fault tolerant global communication and synchronisation methods in large-scale systems has hindered the adoption of the K-Means algorithm for applications in large networked systems such as wireless sensor networks, peer-to-peer systems and mobile ad hoc networks. This work proposes a fully distributed K-Means algorithm (EpidemicK-Means) which does not require global communication and is intrinsically fault tolerant. The proposed distributed K-Means algorithm provides a clustering solution which can approximate the solution of an ideal centralised algorithm over the aggregated data as closely as desired. A comparative performance analysis is carried out against the state of the art sampling methods and shows that the proposed method overcomes the limitations of the sampling-based approaches for skewed clusters distributions. The experimental analysis confirms that the proposed algorithm is very accurate and fault tolerant under unreliable network conditions (message loss and node failures) and is suitable for asynchronous networks of very large and extreme scale.

Genetic relatedness and phenotypic characteristics of Treponema associated with human periodontal tissues and ruminant foot disease

Treponema have been implicated recently in the pathogenesis of digital dermatitis (DID) and contagious ovine digital dermatitis (CODD) that are infectious diseases of bovine and ovine foot tissues, respectively. Previous analyses of treponemal 16S rDNA sequences, PCR-amplified directly from DID or CODD lesions, have suggested relatedness of animal Treponema to some human oral Treponema species isolated from periodontal tissues. In this study a range of adhesion and virulence-related properties of three animal Treponema isolates have been compared with representative human oral strains of Treponema denticola and Treponema vincentii. In adhesion assays using biotinylated treponemal cells, T denticola cells bound in consistently higher numbers to fibronectin, laminin, collagen type 1, gelatin, keratin and lactoferrin than did T. vincentii or animal Treponema isolates. However, animal DID strains adhered to fibrinogen at equivalent or greater levels than T denticola. All Treponema strains bound to the amino-terminal heparin l/fibrin I domain of fibronectin. 16S rDNA sequence analyses placed ovine strain UB1090 and bovine strain UB1467 within a cluster that was phylogenetically related to T vincentii, while ovine strain UB1466 appeared more closely related to T denticola. These observations correlated with phenotypic properties. Thus, T denticola ATCC 35405, GM-1, and Treponema UB1466 had similar outer-membrane protein profiles, produced chymotrypsin-like protease (CTLP), trypsin-like protease and high levels of proline iminopeptidase, and co-aggregated with human oral bacteria Porphyromonas gingivalis and Streptococcus crista. Conversely, T vincentii ATCC 35580, D2A-2, and animal strains UB1090 and UB1467 did not express CTLP or trypsin-like protease and did not co-aggregate with P. gingivalis or S. crista. Taken collectively, these results suggest that human oral-related Treponema have broad host specificity and that similar control or preventive strategies might be developed for human and animal Treponema-associated infections.

Peaceful coexistence? The role of religious schools and NGOs in the growth of female secondary schooling in Bangladesh

Bangladesh Rural Advancement Committee (BRAC), a non-governmental organisation (NGO), runs a large number of non-formal primary schools in Bangladesh which target out-of-school children from poor families. These schools are well-known for their effectiveness in closing the gender gap in primary school enrolment. On the other hand, registered non-government secondary madrasas (or Islamic schools) today enrol one girl against every boy student. In this article, we document a positive spillover effect of BRAC schools on female secondary enrolment in registered madrasas. Drawing upon school enrolment data aggregated at the region level, we first show that regions that had more registered madrasas experienced greater secondary female enrolment growth during 1999–2003, holding the number of secular secondary schools constant. In this context we test the impact of BRAC-run primary schools on female enrolment in registered madrasas. We deal with the potential endogeneity of placement of BRAC schools using an instrumental variable approach. Controlling for factors such as local-level poverty, road access and distance from major cities, we show that regions with a greater presence of BRAC schools have higher female enrolment growth in secondary madrasas. The effect is much bigger when compared to that on secondary schools.

Very high resolution bioclimatic zoning of Portuguese wine regions: present and future scenarios

Wine production is strongly affected by weather and climate and thus highly vulnerable to climate change. In Portugal, viticulture and wine production are an important economic activity. In the present study, current bioclimatic zoning in Portugal (1950–2000) and its projected changes under future climate conditions (2041–2070) are assessed through the analysis of an aggregated, categorized bioclimatic index (CatI) at a very high spatial resolution (near 1 km). CatI incorporates the most relevant bioclimatic characteristics of a given region, thus allowing the direct comparison between different regions. Future viticultural zoning is achieved using data from 13 climate model transient experiments following the A1B emission scenario. These data are downscaled using a two-step method of spatial pattern downscaling. This downscaling approach allows characterizing mesoclimatic influences on viticulture throughout Portugal. Results for the recent past depict the current spatial variability of Portuguese viticultural regions. Under future climate conditions, the current viticultural zoning is projected to undergo significant changes, which may represent important challenges for the Portuguese winemaking sector. The changes are quite robust across the different climate models. A lower bioclimatic diversity is also projected, resulting from a more homogeneous warm and dry climate in most of the wine regions. This will lead to changes in varietal suitability and wine characteristics of each region.

Forecasting VaR using analytic higher moments for GARCH processes

It is widely accepted that some of the most accurate Value-at-Risk (VaR) estimates are based on an appropriately specified GARCH process. But when the forecast horizon is greater than the frequency of the GARCH model, such predictions have typically required time-consuming simulations of the aggregated returns distributions. This paper shows that fast, quasi-analytic GARCH VaR calculations can be based on new formulae for the first four moments of aggregated GARCH returns. Our extensive empirical study compares the Cornish–Fisher expansion with the Johnson SU distribution for fitting distributions to analytic moments of normal and Student t, symmetric and asymmetric (GJR) GARCH processes to returns data on different financial assets, for the purpose of deriving accurate GARCH VaR forecasts over multiple horizons and significance levels.