Risk under performance-based contracting in the UK construction sector

As a method of procuring the services of the built environment, performance-based contracting (PBC) seeks to link the building supplier to longer term commitments than has traditionally been the case in the construction sector. By rewarding the building producer according to the way that building or structure delivers the users' requirements, rather than according to a list of assembled parts, a number of additional risks are taken by contractors, including fitness for purpose, costs and briefing. The extent to which contractors recognize these risks and their methods of dealing with them vary considerably and are influenced by their attitudes towards risk. As the risks associated with PBC are seen as large, uninsurable, and vulnerable to changing client requirements, the majority of respondents would reject the use of PBC as a method of contracting. Nevertheless, PBC may be used under particular conditions, where rewards are deemed sufficient to compensate for the additional risk to the contractor of undertaking work on the basis of a stream of payments paid over the life of a structure depending on the satisfactory performance of the building or as part of a private finance initiative.

Effects of chronic and acute consumption of fruit- and vegetable-puree-based drinks on vasodilation, risk factors for CVD and the response as a result of the eNOS G298T polymorphism

The average UK adult consumes less than three portions of fruit and vegetables daily, despite evidence to suggest that consuming five portions daily could help prevent chronic diseases. It is recommended that fruit juice should only count as one of these portions, as juicing removes fibre and releases sugars. However, fruit juices contain beneficial compounds such as vitamin C and flavonoids and could be a useful source of dietary phytochemicals. Two randomised controlled cross-over intervention studies investigating the effects of chronic and acute consumption of commercially-available fruit- and vegetable-puree-based drinks (FVPD) on bioavailability, antioxidant status and CVD risk factors are described. Blood and urine samples were collected during both studies and vascular tone was measured using laser Doppler imaging. In the chronic intervention study FVPD consumption was found to significantly increase dietary carotenoids (P = 0.001) and vitamin C (P = 0.003). Plasma carotenoids were increased (P = 0.001), but the increase in plasma vitamin C was not significant. There were no significant effects on oxidative stress, antioxidant status and other CVD risk factors. In the acute intervention study FVPD were found to increase total plasma nitrate and nitrite (P = 0.001) and plasma vitamin C (P = 0.002). There was no effect on plasma lipids or uric acid, but there was a lower glucose and insulin peak concentration after consumption of the FVPD compared with the sugar-matched control. There was a trend towards increased vasodilation following both chronic and acute FVPD consumption. All volunteers were retrospectively genotyped for the eNOS G298T polymorphism and the effect of genotype on the measurements is discussed. Overall, there was a non-significant trend towards increased endothelium-dependent vasodilation following both acute and chronic FVPD consumption. However, there was a significant time x treatment effect (P < 0.05) of acute FVPD consumption in individuals with the GG variant of the eNOS gene.

Risk assessment of UK skylark populations using life-history and individual-based landscape models

Abstract: Following a workshop exercise, two models, an individual-based landscape model (IBLM) and a non-spatial life-history model were used to assess the impact of a fictitious insecticide on populations of skylarks in the UK. The chosen population endpoints were abundance, population growth rate, and the chances of population persistence. Both models used the same life-history descriptors and toxicity profiles as the basis for their parameter inputs. The models differed in that exposure was a pre-determined parameter in the life-history model, but an emergent property of the IBLM, and the IBLM required a landscape structure as an input. The model outputs were qualitatively similar between the two models. Under conditions dominated by winter wheat, both models predicted a population decline that was worsened by the use of the insecticide. Under broader habitat conditions, population declines were only predicted for the scenarios where the insecticide was added. Inputs to the models are very different, with the IBLM requiring a large volume of data in order to achieve the flexibility of being able to integrate a range of environmental and behavioural factors. The life-history model has very few explicit data inputs, but some of these relied on extensive prior modelling needing additional data as described in Roelofs et al.(2005, this volume). Both models have strengths and weaknesses; hence the ideal approach is that of combining the use of both simple and comprehensive modeling tools.

A word of caution on calculating market-based minimum capital risk requirements

This paper demonstrates that the use of GARCH-type models for the calculation of minimum capital risk requirements (MCRRs) may lead to the production of inaccurate and therefore inefficient capital requirements. We show that this inaccuracy stems from the fact that GARCH models typically overstate the degree of persistence in return volatility. A simple modification to the model is found to improve the accuracy of MCRR estimates in both back- and out-of-sample tests. Given that internal risk management models are currently in widespread usage in some parts of the world (most notably the USA), and will soon be permitted for EC banks and investment firms, we believe that our paper should serve as a valuable caution to risk management practitioners who are using, or intend to use this popular class of models.

An energy budget agent-based model of earthworm populations and its application to study the effects of pesticides

Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species.

Case study on the maintenance of a construction monitoring using USN-based data acquisition

In recent years, there has been an increasing interest in the adoption of emerging ubiquitous sensor network (USN) technologies for instrumentation within a variety of sustainability systems. USN is emerging as a sensing paradigm that is being newly considered by the sustainability management field as an alternative to traditional tethered monitoring systems. Researchers have been discovering that USN is an exciting technology that should not be viewed simply as a substitute for traditional tethered monitoring systems. In this study, we investigate how a movement monitoring measurement system of a complex building is developed as a research environment for USN and related decision-supportive technologies. To address the apparent danger of building movement, agent-mediated communication concepts have been designed to autonomously manage large volumes of exchanged information. In this study, we additionally detail the design of the proposed system, including its principles, data processing algorithms, system architecture, and user interface specifics. Results of the test and case study demonstrate the effectiveness of the USN-based data acquisition system for real-time monitoring of movement operations.

Equations to predict methane emissions from cows fed at maintenance energy level in pasture-based systems

Ruminant production is a vital part of food industry but it raises environmental concerns, partly due to the associated methane outputs. Efficient methane mitigation and estimation of emissions from ruminants requires accurate prediction tools. Equations recommended by international organizations or scientific studies have been developed with animals fed conserved forages and concentrates and may be used with caution for grazing cattle. The aim of the current study was to develop prediction equations with animals fed fresh grass in order to be more suitable to pasture-based systems and for animals at lower feeding levels. A study with 25 nonpregnant nonlactating cows fed solely fresh-cut grass at maintenance energy level was performed over two consecutive grazing seasons. Grass of broad feeding quality, due to contrasting harvest dates, maturity, fertilisation and grass varieties, from eight swards was offered. Cows were offered the experimental diets for at least 2 weeks before housed in calorimetric chambers over 3 consecutive days with feed intake measurements and total urine and faeces collections performed daily. Methane emissions were measured over the last 2 days. Prediction models were developed from 100 3-day averaged records. Internal validation of these equations, and those recommended in literature, was performed. The existing in greenhouse gas inventories models under-estimated methane emissions from animals fed fresh-cut grass at maintenance while the new models, using the same predictors, improved prediction accuracy. Error in methane outputs prediction was decreased when grass nutrient, metabolisable energy and digestible organic matter concentrations were added as predictors to equations already containing dry matter or energy intakes, possibly because they explain feed digestibility and the type of energy-supplying nutrients more efficiently. Predictions based on readily available farm-level data, such as liveweight and grass nutrient concentrations were also generated and performed satisfactorily. New models may be recommended for predictions of methane emissions from grazing cattle at maintenance or low feeding levels.

Population-Based Multicentric Survey of Hepatitis B Infection and Risk Factor Differences among Three Regions in Brazil

This multicentric population-based study in Brazil is the first national effort to estimate the prevalence of hepatitis B (HBV) and risk factors in the capital cities of the Northeast. Central-West, and Federal Districts (2004-2005). Random multistage cluster sampling was used to select persons 13-69 years of age. Markers for HBV were tested by enzyme-linked immunosorbent assay. The HBV genotypes were determined by sequencing hepatitis B surface antigen (HBsAg). Multivariate analyses and simple catalytic model were performed. Overall. 7,881 persons were inculded < 70% were not vaccinated. Positivity for HBsAg was less than 1% among non-vaccinated persons and genotypes A, D, and F co-circulated. The incidence of infection increased with age with similar force of infection in all regions. Males and persons having initiated sexual activity were associated with HBV infection in the two settings: healthcare jobs and prior hospitalization were risk factors in the Federal District. Our survey classified these regions as areas with HBV endemicity and highlighted the risk factors differences among the settings.

Flood Risk Assessment in Coastal Drainage Basins through a Multivariate Analysis within a GIS-Based Model

This paper presents a GIS-based multicriteria flood risk assessment and mapping approach applied to coastal drainage basins where hydrological data are not available. It involves risk to different types of possible processes: coastal inundation (storm surge), river, estuarine and flash flood, either at urban or natural areas, and fords. Based on the causes of these processes, several environmental indicators were taken to build-up the risk assessment. Geoindicators include geological-geomorphologic proprieties of Quaternary sedimentary units, water table, drainage basin morphometry, coastal dynamics, beach morphodynamics and microclimatic characteristics. Bioindicators involve coastal plain and low slope native vegetation categories and two alteration states. Anthropogenic indicators encompass land use categories properties such as: type, occupation density, urban structure type and occupation consolidation degree. The selected indicators were stored within an expert Geoenvironmental Information System developed for the State of Sao Paulo Coastal Zone (SIIGAL), which attributes were mathematically classified through deterministic approaches, in order to estimate natural susceptibilities (Sn), human-induced susceptibilities (Sa), return period of rain events (Ri), potential damages (Dp) and the risk classification (R), according to the equation R=(Sn.Sa.Ri).Dp. Thematic maps were automatically processed within the SIIGAL, in which automata cells (""geoenvironmental management units"") aggregating geological-geomorphologic and land use/native vegetation categories were the units of classification. The method has been applied to the Northern Littoral of the State of Sao Paulo (Brazil) in 32 small drainage basins, demonstrating to be very useful for coastal zone public politics, civil defense programs and flood management.

Risk factors for dengue virus infection in rural Amazonia: Population-based cross-sectional surveys

A comparison of dengue virus (DENV) antibody levels in paired serum samples collected from predominantly DENV-naive residents in an agricultural settlement in Brazilian Amazonia (baseline seroprevalence, 18.3%) showed a seroconversion rate of 3.67 episodes/100 person-years at risk during 12 months of follow-up. Multivariate analysis identified male sex, poverty, and migration from extra-Amazonian states as significant predictors of baseline DENY seropositivity, whereas male sex, a history of clinical diagnosis of dengue fever, and travel to an urban area predicted subsequent seroconversion. The laboratory surveillance of acute febrile illnesses implemented at the study site and in a nearby town between 2004 and 2006 confirmed 11. DENV infections among 102 episodes studied with DENV IgM detection, reverse transcriptase-polymerise chain reaction, and virus isolation; DENV-3 was isolated. Because DENV exposure is associated with migration or travel, personal protection measures when visiting high-risk urban areas may reduce the incidence of DENV infection in this rural population.

A Community-based Survey of Human Toxoplasmosis in Rural Amazonia: Seroprevalence, Seroconversion Rate, and Associated Risk Factors

IgG antibodies to Toxoplasma gondii were detected in, March-April 2004, in 65.8% (95% confidence interval, 60.8-70.8%) of 342 systematically sampled subjects 5-90 years of age (87.5% of the eligible) living in a rural settlement in Amazonia, with a seroconversion rate of 9% over I year of follow-up of 99 seronegative subjects. Multiple logistic regression analysis identified age as the only significant independent predictor of seropositivity at the baseline. Each additional year of age increases the odds of being seropositive by 6%, and 76.8% of the subjects are expected to be seropositive at 30 years of age. A single high-prevalence spatial cluster, comprising 11.9% of the seropositive subjects, was detected in the area; households in the cluster were less likely to have dogs as pets and their heads had a lower education level, when compared with households located outside the cluster. The challenges for preventing human toxoplasmosis in tropical rural settings are discussed.

Software maintenance project delays prediction using Bayesian Networks

Managing software maintenance is rarely a precise task due to uncertainties concerned with resources and services descriptions. Even when a well-established maintenance process is followed, the risk of delaying tasks remains if the new services are not precisely described or when resources change during process execution. Also, the delay of a task at an early process stage may represent a different delay at the end of the process, depending on complexity or services reliability requirements. This paper presents a knowledge-based representation (Bayesian Networks) for maintenance project delays based on specialists experience and a corresponding tool to help in managing software maintenance projects. (c) 2006 Elsevier Ltd. All rights reserved.