Application of the entropy technique and genetic algorithms to construction site layout planning of medium-size projects

Genetic algorithms (GAs) have been introduced into site layout planning as reported in a number of studies. In these studies, the objective functions were defined so as to employ the GAs in searching for the optimal site layout. However, few studies have been carried out to investigate the actual closeness of relationships between site facilities; it is these relationships that ultimately govern the site layout. This study has determined that the underlying factors of site layout planning for medium-size projects include work flow, personnel flow, safety and environment, and personal preferences. By finding the weightings on these factors and the corresponding closeness indices between each facility, a closeness relationship has been deduced. Two contemporary mathematical approaches - fuzzy logic theory and an entropy measure - were adopted in finding these results in order to minimize the uncertainty and vagueness of the collected data and improve the quality of the information. GAs were then applied to searching for the optimal site layout in a medium-size government project using the GeneHunter software. The objective function involved minimizing the total travel distance. An optimal layout was obtained within a short time. This reveals that the application of GA to site layout planning is highly promising and efficient.

Quantifying uncertainty in critical loads: (B) acidity mass balance critical loads on a sensitive site

This paper reports an uncertainty analysis of critical loads for acid deposition for a site in southern England, using the Steady State Mass Balance Model. The uncertainty bounds, distribution type and correlation structure for each of the 18 input parameters was considered explicitly, and overall uncertainty estimated by Monte Carlo methods. Estimates of deposition uncertainty were made from measured data and an atmospheric dispersion model, and hence the uncertainty in exceedance could also be calculated. The uncertainties of the calculated critical loads were generally much lower than those of the input parameters due to a "compensation of errors" mechanism - coefficients of variation ranged from 13% for CLmaxN to 37% for CL(A). With 1990 deposition, the probability that the critical load was exceeded was > 0.99; to reduce this probability to 0.50, a 63% reduction in deposition is required; to 0.05, an 82% reduction. With 1997 deposition, which was lower than that in 1990, exceedance probabilities declined and uncertainties in exceedance narrowed as deposition uncertainty had less effect. The parameters contributing most to the uncertainty in critical loads were weathering rates, base cation uptake rates, and choice of critical chemical value, indicating possible research priorities. However, the different critical load parameters were to some extent sensitive to different input parameters. The application of such probabilistic results to environmental regulation is discussed.

Establishment of a Cross-European Field Site Network in the ALARM Project for Assessing Large-Scale Changes in Biodiversity

The field site network (FSN) plays a central role in conducting joint research within all Assessing Large-scale Risks for biodiversity with tested Methods (ALARM) modules and provides a mechanism for integrating research on different topics in ALARM on the same site for measuring multiple impacts on biodiversity. The network covers most European climates and biogeographic regions, from Mediterranean through central European and boreal to subarctic. The project links databases with the European-wide field site network FSN, including geographic information system (GIS)-based information to characterise the test location for ALARM researchers for joint on-site research. Maps are provided in a standardised way and merged with other site-specific information. The application of GIS for these field sites and the information management promotes the use of the FSN for research and to disseminate the results. We conclude that ALARM FSN sites together with other research sites in Europe jointly could be used as a future backbone for research proposals

Analysis of the antigen combining site: Correlations between length and sequence composition of the hypervariable loops and the nature of the antigen

It has long been suggested that the overall shape of the antigen combining site (ACS) of antibodies is correlated with the nature of the antigen. For example, deep pockets are characteristic of antibodies that bind haptens, grooves indicate peptide binders, while antibodies that bind to proteins have relatively flat combining sites. In. 1996, MacCallum, Martin and Thornton used a fractal shape descriptor and showed a strong correlation of the shape of the binding region with the general nature of the antigen. However, the shape of the ACS is determined primarily by the lengths of the six complementarity-determining regions (CDRs). Here, we make a direct correlation between the lengths of the CDRs and the nature of the antigen. In addition, we show significant differences in the residue composition of the CDRs of antibodies that bind to different antigen classes. As well as helping us to understand the process of antigen recognition, autoimmune disease and cross-reactivity these results are of direct application in the design of antibody phage libraries and modification of affinity. (C) 2003 Elsevier Science Ltd. All rights reserved.

Multi-site evaluation of an urban land-surface model: intra-urban heterogeneity, seasonality and parameter complexity requirements

An extensive off-line evaluation of the Noah/Single Layer Urban Canopy Model (Noah/SLUCM) urban land-surface model is presented using data from 15 sites to assess (1) the ability of the scheme to reproduce the surface energy balance observed in a range of urban environments, including seasonal changes, and (2) the impact of increasing complexity of input parameter information. Model performance is found to be most dependent on representation of vegetated surface area cover; refinement of other parameter values leads to smaller improvements. Model biases in net all-wave radiation and trade-offs between turbulent heat fluxes are highlighted using an optimization algorithm. Here we use the Urban Zones to characterize Energy partitioning (UZE) as the basis to assign default SLUCM parameter values. A methodology (FRAISE) to assign sites (or areas) to one of these categories based on surface characteristics is evaluated. Using three urban sites from the Basel Urban Boundary Layer Experiment (BUBBLE) dataset, an independent evaluation of the model performance with the parameter values representative of each class is performed. The scheme copes well with both seasonal changes in the surface characteristics and intra-urban heterogeneities in energy flux partitioning, with RMSE performance comparable to similar state-of-the-art models for all fluxes, sites and seasons. The potential of the methodology for high-resolution atmospheric modelling application using the Weather Research and Forecasting (WRF) model is highlighted. This analysis supports the recommendations that (1) three classes are appropriate to characterize the urban environment, and (2) that the parameter values identified should be adopted as default values in WRF.

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.

Financial viability appraisals for site-specific planning decisions in England

In England, appraisals of the financial viability of development schemes have become an integral part of planning policy-making, initially in determining the amount of planning obligations that might be obtained via legal agreements (known as Section 106 agreements) and latterly as a basis for establishing charging schedules for the Community Infrastructure Levy (CIL). Local planning authorities set these policies on an area-wide basis but ultimately development proposals require consent on a site-by-site basis. It is at this site-specific level that issues of viability are hotly contested. This paper examines case documents, proofs of evidence and decisions from a sample of planning disputes in order to address major issues within development viability, the application of the models and the distribution of the development gain between the developer, landowner and community. The results have specific application to viability assessment in England and should impact on future policy and practice guidance in this field. They also have relevance to other countries that incorporate assessments of economic viability in their planning systems.

Effects of agricultural management practices on earthworm populations and crop yield: validation and application of a mechanistic modelling approach

There is little consensus on how agriculture will meet future food demands sustainably. Soils and their biota play a crucial role by mediating ecosystem services that support agricultural productivity. However, a multitude of site-specific environmental factors and management practices interact to affect the ability of soil biota to perform vital functions, confounding the interpretation of results from experimental approaches. Insights can be gained through models, which integrate the physiological, biological and ecological mechanisms underpinning soil functions. We present a powerful modelling approach for predicting how agricultural management practices (pesticide applications and tillage) affect soil functioning through earthworm populations. By combining energy budgets and individual-based simulation models, and integrating key behavioural and ecological drivers, we accurately predict population responses to pesticide applications in different climatic conditions. We use the model to analyse the ecological consequences of different weed management practices. Our results demonstrate that an important link between agricultural management (herbicide applications and zero, reduced and conventional tillage) and earthworms is the maintenance of soil organic matter (SOM). We show how zero and reduced tillage practices can increase crop yields while preserving natural ecosystem functions. This demonstrates how management practices which aim to sustain agricultural productivity should account for their effects on earthworm populations, as their proliferation stimulates agricultural productivity. Synthesis and applications. Our results indicate that conventional tillage practices have longer term effects on soil biota than pesticide control, if the pesticide has a short dissipation time. The risk of earthworm populations becoming exposed to toxic pesticides will be reduced under dry soil conditions. Similarly, an increase in soil organic matter could increase the recovery rate of earthworm populations. However, effects are not necessarily additive and the impact of different management practices on earthworms depends on their timing and the prevailing environmental conditions. Our model can be used to determine which combinations of crop management practices and climatic conditions pose least overall risk to earthworm populations. Linking our model mechanistically to crop yield models would aid the optimization of crop management systems by exploring the trade-off between different ecosystem services.