An application of the GLUE methodology for estimating the parameters of the INCA-N model

The conceptual and parameter uncertainty of the semi-distributed INCA-N (Integrated Nutrients in Catchments-Nitrogen) model was studied using the GLUE (Generalized Likelihood Uncertainty Estimation) methodology combined with quantitative experimental knowledge, the concept known as 'soft data'. Cumulative inorganic N leaching, annual plant N uptake and annual mineralization proved to be useful soft data to constrain the parameter space. The INCA-N model was able to simulate the seasonal and inter-annual variations in the stream-water nitrate concentrations, although the lowest concentrations during the growing season were not reproduced. This suggested that there were some retention processes or losses either in peatland/wetland areas or in the river which were not included in the INCA-N model. The results of the study suggested that soft data was a way to reduce parameter equifinality, and that the calibration and testing of distributed hydrological and nutrient leaching models should be based both on runoff and/or nutrient concentration data and the qualitative knowledge of experimentalist. (c) 2006 Elsevier B.V. All rights reserved.

Analysis and application of ichnofabrics

Bioturbation at all scales, which tends to replace the primary fabric of a sediment by the ichnofabric (the overall fabric of a sediment that has been bioturbated), is now recognised as playing a major role in facies interpretation. The manner in which the substrate may be colonized, and the physical, chemical and ecological controls (grainsize, sedimentation rate, oxygenation, nutrition, salinity, ethology, community structure and succession), together with the several ways in which the substrate is tiered by bioturbators, are the factors and processes that determine the nature of the ichnofabric. Eleven main styles of substrate tiering are described, ranging from single, pioneer colonization to complex tiering under equilibria, their modification under environmental deterioration and amelioration, and diagenetic enhancement or obscuration. Ichnofabrics may be assessed by four attributes: primary sedimentary factors, Bioturbation Index (BI), burrow size and frequency, and ichnological diversity. Construction of tier and ichnofabric constituent diagrams aid visualization and comparison. The breaks or changes in colonization and style of tiering at key stratal surfaces accentuate the surfaces, and many reflect a major environmental shift of the trace-forming biota. due to change in hydrodynamic regime (leading to non-deposition and/or erosion and/or lithification), change in salinity regime, or subaerial exposure. The succession of gradational or abrupt changes in ichnofabric through genetically related successions, together with changes in colonization and tiering across event beds, may also be interpreted in terms of changes in environmental parameters. It is not the ichnotaxa per se that are important in discriminating between ichnofabrics, but rather the environmental conditions that determine the overall style of colonization. Fabrics composed of different ichnotaxa (and different taphonomies) but similar tier structure and ichnoguild may form in similar environments of different age or different latitude. Appreciation of colonization and tiering styles places ancient ichnofabrics on a sound processrelated basis for environmental interpretation. (C) 2002 Elsevier Science B.V. All rights reserved.

The combined effect of the application of a biocontrol agent Paecilomyces lilacinus, with various practices for the control of root-knot nematodes

The effectiveness of a formulated product containing spores of the naturally occurring fungus Paecilomyces lilacinus, strain 251, was evaluated against root-knot nematodes in pot and greenhouse experiments. Decrease of second-stage juveniles hatching from eggs was recorded by using the bio-nematicide at a dose of 4 kg ha(-1), while a further decrease was recorded by doubling the dose. However, the mortality rate decreased by increasing the inoculum level. Application of P. lilacinus and Bacillus firmus, singly or together in pot experiments, provided effective control of second-stage juveniles, eggs or egg masses of root-knot nematodes. In a greenhouse experiment, the bio-nematicide was evaluated for its potential to control root-knot nematodes either as a stand-alone method or in combination with soil solarization. Soil was solarized for 15 d and the bio-nematicide was applied just after the removal of the plastic sheet. Soil solarization for 15 d either alone or combined with the use of P. lilacinus did not provide satisfactory control of root-knot nematodes. The use of oxamyl, which was applied 2 weeks before and during transplanting, gave results similar to the commercial product containing P. lilacinus but superior to soil solarization. (C) 2007 Elsevier Ltd. All rights reserved.

Typification of farming systems for constructing representative farm models: two illustrations of the application of multi-variate analyses in Chile and Pakistan

If the fundamental precepts of Farming Systems Research were to be taken literally then it would imply that for each farm 'unique' solutions should be sought. This is an unrealistic expectation, but it has led to the idea of a recommendation domain, implying creating a taxonomy of farms, in order to increase the general applicability of recommendations. Mathematical programming models are an established means of generating recommended solutions, but for such models to be effective they have to be constructed for 'truly' typical or representative situations. The multi-variate statistical techniques provide a means of creating the required typologies, particularly when an exhaustive database is available. This paper illustrates the application of this methodology in two different studies that shared the common purpose of identifying types of farming systems in their respective study areas. The issues related with the use of factor and cluster analyses for farm typification prior to building representative mathematical programming models for Chile and Pakistan are highlighted. (C) 2003 Elsevier Science Ltd. All rights reserved.

Time patterns in UK demand for alcohol and tobacco: an application of the EM algorithm

Capturing the pattern of structural change is a relevant task in applied demand analysis, as consumer preferences may vary significantly over time. Filtering and smoothing techniques have recently played an increasingly relevant role. A dynamic Almost Ideal Demand System with random walk parameters is estimated in order to detect modifications in consumer habits and preferences, as well as changes in the behavioural response to prices and income. Systemwise estimation, consistent with the underlying constraints from economic theory, is achieved through the EM algorithm. The proposed model is applied to UK aggregate consumption of alcohol and tobacco, using quarterly data from 1963 to 2003. Increased alcohol consumption is explained by a preference shift, addictive behaviour and a lower price elasticity. The dynamic and time-varying specification is consistent with the theoretical requirements imposed at each sample point. (c) 2005 Elsevier B.V. All rights reserved.

Application of one-list capture-recapture models to scrapie surveillance data in Great Britain

In this paper, we apply one-list capture-recapture models to estimate the number of scrapie-affected holdings in Great Britain. We applied this technique to the Compulsory Scrapie Flocks Scheme dataset where cases from all the surveillance sources monitoring the presence of scrapie in Great Britain, the abattoir survey, the fallen stock survey and the statutory reporting of clinical cases, are gathered. Consequently, the estimates of prevalence obtained from this scheme should be comprehensive and cover all the different presentations of the disease captured individually by the surveillance sources. Two estimators were applied under the one-list approach: the Zelterman estimator and Chao's lower bound estimator. Our results could only inform with confidence the scrapie-affected holding population with clinical disease; this moved around the figure of 350 holdings in Great Britain for the period under study, April 2005-April 2006. Our models allowed the stratification by surveillance source and the input of covariate information, holding size and country of origin. None of the covariates appear to inform the model significantly. Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

Application of constrained predictive control on a 3D crane system

This paper describes the SIMULINK implementation of a constrained predictive control algorithm based on quadratic programming and linear state space models, and its application to a laboratory-scale 3D crane system. The algorithm is compatible with Real Time. Windows Target and, in the case of the crane system, it can be executed with a sampling period of 0.01 s and a prediction horizon of up to 300 samples, using a linear state space model with 3 inputs, 5 outputs and 13 states.

Application of a novel optimal control algorithm to a benchmark fed-batch fermentation process

A novel algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimisation and Parameter Estimation (DISOPE) which has been designed to achieve the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimisation procedure. A method based on Broyden's ideas is used for approximating some derivative trajectories required. Ways for handling con straints on both manipulated and state variables are described. Further, a method for coping with batch-to- batch dynamic variations in the process, which are common in practice, is introduced. It is shown that the iterative procedure associated with the algorithm naturally suits applications to batch processes. The algorithm is success fully applied to a benchmark problem consisting of the input profile optimisation of a fed-batch fermentation process.

Development and application of a novel algorithm for steady-state optimising control using dynamic information

A novel optimising controller is designed that leads a slow process from a sub-optimal operational condition to the steady-state optimum in a continuous way based on dynamic information. Using standard results from optimisation theory and discrete optimal control, the solution of a steady-state optimisation problem is achieved by solving a receding-horizon optimal control problem which uses derivative and state information from the plant via a shadow model and a state-space identifier. The paper analyzes the steady-state optimality of the procedure, develops algorithms with and without control rate constraints and applies the procedure to a high fidelity simulation study of a distillation column optimisation.

Application of interpolymer complexation to coat solid and soft surfaces

Water-soluble polymers are often capable of forming interpolymer complexes in solutions and at interfaces, which offers an excellent opportunity for surface modification. The complex formation may be driven by H-bonding between poly(carboxylic acids) and non-ionic polymers or by electrostatic attraction between oppositely-charged polyelectrolytes. In the present communication the following applications of interpolymer complexation in coating technologies will be considered: (1) Complexation between poly(acrylic acid) and non-ionic polymers via H-bonding was used to coat glass surfaces. It was realised using layer-by-layer deposition of IPC on glass surfaces with subsequent cross-linking of dry multilayers by thermal treatment. Depending on the glass surface functionality this complexation resulted in detachable and non-detachable hydrogel films; (2) Electrostatic layer-by-layer self-assembly between glycol chitosan and bovine serum albumin (BSA) was used to coat magnetic nanoparticles. It was demonstrated that the native structure of BSA remains unaffected by the self-assembling process.

Application of mid-infrared spectroscopy to the prediction of maturity and sensory texture attributes of cheddar cheese

The objective of this study was to determine the potential of mid-infrared spectroscopy in conjunction with partial least squares (PLS) regression to predict various quality parameters in cheddar cheese. Cheddar cheeses (n = 24) were manufactured and stored at 8 degrees C for 12 mo. Mid-infrared spectra (640 to 4000/cm) were recorded after 4, 6, 9, and 12 mo storage. At 4, 6, and 9 mo, the water-soluble nitrogen (WSN) content of the samples was determined and the samples were also evaluated for 11 sensory texture attributes using descriptive sensory analysis. The mid-infrared spectra were subjected to a number of pretreatments, and predictive models were developed for all parameters. Age was predicted using scatter-corrected, 1st derivative spectra with a root mean square error of cross-validation (RMSECV) of 1 mo, while WSN was predicted using 1st derivative spectra (RMSECV = 2.6%). The sensory texture attributes most successfully predicted were rubbery, crumbly, chewy, and massforming. These attributes were modeled using 2nd derivative spectra and had, corresponding RMSECV values in the range of 2.5 to 4.2 on a scale of 0 to 100. It was concluded that mid-infrared spectroscopy has the potential to predict age, WSN, and several sensory texture attributes of cheddar cheese..