Criteria for validation and selection of cognitive tests for investigating the effects of foods and nutrients.

This review is an output of the International Life Sciences Institute (ILSI) Europe Marker Initiative, which aims to identify evidence-based criteria for selecting adequate measures of nutrient effects on health through comprehensive literature review. Experts in cognitive and nutrition sciences examined the applicability of these proposed criteria to the field of cognition with respect to the various cognitive domains usually assessed to reflect brain or neurological function. This review covers cognitive domains important in the assessment of neuronal integrity and function, commonly used tests and their state of validation, and the application of the measures to studies of nutrition and nutritional intervention trials. The aim is to identify domain-specific cognitive tests that are sensitive to nutrient interventions and from which guidance can be provided to aid the application of selection criteria for choosing the most suitable tests for proposed nutritional intervention studies using cognitive outcomes. The material in this review serves as a background and guidance document for nutritionists, neuropsychologists, psychiatrists, and neurologists interested in assessing mental health in terms of cognitive test performance and for scientists intending to test the effects of food or food components on cognitive function.

Biosensor-based diagnostics of contaminated groundwater: assessment and remediation strategy

Shallow groundwater beneath a former airfield site in southern England has been heavily contaminated with a wide range of chlorinated solvents. The feasibility of using bacterial biosensors to complement chemical analysis and enable cost-effective, and focussed sampling has been assessed as part of a site evaluation programme. Five different biosensors, three metabolic (Vibrio fischeri, Pseudomonas fluorescens 10568 and Escherichia coli HB101) and two catabolic (Pseudomonas putida TVA8 and E. coli DH5alpha), were employed to identify areas where the availability and toxicity of pollutants is of most immediate environmental concern. The biosensors used showed different sensitivities to each other and to the groundwater samples tested. There was generally a good agreement with chemical analyses. The potential efficacy of remediation strategies was explored by coupling sample manipulation to biosensor tests. Manipulation involved sparging and charcoal treatment procedures to simulate remediative engineering solutions. Sparging was sufficient at most locations. (C) 2004 Elsevier Ltd. All rights reserved.

Environmental assessment and the built environment : a highway engineer's perspective

This paper is an engineer's appreciation of environmental assessment with particular reference to highway development. While scheme-related Environmental Assessment for individual development may identify particular potential impacts, and may avoid or minimise some of the problems, in many cases it may be too late to take such actions. Ideally, Environmental Assessment should commence at the Strategic Level to cover policies, plan and programmes, and the scheme-related Environmental Assessments for individual projects should supplement those in the framework of Strategic Level. The utimate target is to assess the policy for their contribution to effecting sustainable development. Whole Life Environmental Impacts should be considered. These are the full impact consideration from planning, design and choice of materials, construction, operation and finally decommission. Most of the Environmental Assessments have not included the Whole Life Environmental Impacts. There is only limited monitoring in the operation stage after the construction of the scheme is complete, therefore, subsequent Environmental Assessments cannot benefit from the feedback of the scheme. No development should cost the Earth, hence Environmental Assessments have to be carried out thoroughly to serve as one of the instruments to meet the need of sustainable development.

Bayesian estimation and selection of nonlinear vector error correction models: The case of the sugar-ethanol-oil nexus in Brazil

Nonlinear adjustment toward long-run price equilibrium relationships in the sugar-ethanol-oil nexus in Brazil is examined. We develop generalized bivariate error correction models that allow for cointegration between sugar, ethanol, and oil prices, where dynamic adjustments are potentially nonlinear functions of the disequilibrium errors. A range of models are estimated using Bayesian Monte Carlo Markov Chain algorithms and compared using Bayesian model selection methods. The results suggest that the long-run drivers of Brazilian sugar prices are oil prices and that there are nonlinearities in the adjustment processes of sugar and ethanol prices to oil price but linear adjustment between ethanol and sugar prices.

Bayesian ranking and selection of fishing boat efficiencies

The steadily accumulating literature on technical efficiency in fisheries attests to the importance of efficiency as an indicator of fleet condition and as an object of management concern. In this paper, we extend previous work by presenting a Bayesian hierarchical approach that yields both efficiency estimates and, as a byproduct of the estimation algorithm, probabilistic rankings of the relative technical efficiencies of fishing boats. The estimation algorithm is based on recent advances in Markov Chain Monte Carlo (MCMC) methods—Gibbs sampling, in particular—which have not been widely used in fisheries economics. We apply the method to a sample of 10,865 boat trips in the US Pacific hake (or whiting) fishery during 1987–2003. We uncover systematic differences between efficiency rankings based on sample mean efficiency estimates and those that exploit the full posterior distributions of boat efficiencies to estimate the probability that a given boat has the highest true mean efficiency.

Gene flow, risk assessment and the environmental release of transgenic plants

The release of genetically modified plants is governed by regulations that aim to provide an assessment of potential impact on the environment. One of the most important components of this risk assessment is an evaluation of the probability of gene flow. In this review, we provide an overview of the current literature on gene flow from transgenic plants, providing a framework of issues for those considering the release of a transgenic plant into the environment. For some plants gene flow from transgenic crops is well documented, and this information is discussed in detail in this review. Mechanisms of gene flow vary from plant species to plant species and range from the possibility of asexual propagation, short- or long-distance pollen dispersal mediated by insects or wind and seed dispersal. Volunteer populations of transgenic plants may occur where seed is inadvertently spread during harvest or commercial distribution. If there are wild populations related to the transgenic crop then hybridization and eventually introgression in the wild may occur, as it has for herbicide resistant transgenic oilseed rape (Brassica napus). Tools to measure the amount of gene flow, experimental data measuring the distance of pollen dispersal, and experiments measuring hybridization and seed survivability are discussed in this review. The various methods that have been proposed to prevent gene flow from genetically modified plants are also described. The current "transgenic traits'! in the major crops confer resistance to herbicides and certain insects. Such traits could confer a selective advantage (an increase in fitness) in wild plant populations in some circumstances, were gene flow to occur. However, there is ample evidence that gene flow from crops to related wild species occurred before the development of transgenic crops and this should be taken into account in the risk assessment process.

Facial feature extraction and selection by Gabor wavelets and boosting

In this paper, we present a feature selection approach based on Gabor wavelet feature and boosting for face verification. By convolution with a group of Gabor wavelets, the original images are transformed into vectors of Gabor wavelet features. Then for individual person, a small set of significant features are selected by the boosting algorithm from a large set of Gabor wavelet features. The experiment results have shown that the approach successfully selects meaningful and explainable features for face verification. The experiments also suggest that for the common characteristics such as eyes, noses, mouths may not be as important as some unique characteristic when training set is small. When training set is large, the unique characteristics and the common characteristics are both important.