Changes in selected biochemical and sensory parameters as affected by the superficial inoculation of Penicillium camemberti on dry fermented sausages

An atoxigenic strain of Penicillium camemberti was superficially inoculated on fermented sausages in an attempt to improve their sensory properties. The growth of this mould on the surface of the sausages resulted in an intense proteolysis and lipolysis, which caused an increase in the concentration of free amino acids, free fatty acids (FFA) and volatile compounds. Many of these were derived from amino acid catabolism and were responsible for the "ripened flavour", i.e. branched aldehydes and the corresponding alcohols, acids and esters. The development of the fungal mycelia on the surface of the sausages also protected lipids from oxidation, resulting in both lower 2-thiobarbituric acid (TBARS) values and lipid oxidation-derived compounds, such as aliphatic aldehydes and alcohols. The sensory analysis of superficially inoculated sausages showed clear improvements in odour and flavour and, as a consequence, in the overall quality of the sausages. Therefore, this strain is proposed as a potential starter culture for dry fermented sausage production. (C) 2002 Elsevier Science B.V All rights reserved.

Robust identification for linear-in-the-parameters models

In this paper new robust nonlinear model construction algorithms for a large class of linear-in-the-parameters models are introduced to enhance model robustness, including three algorithms using combined A- or D-optimality or PRESS statistic (Predicted REsidual Sum of Squares) with regularised orthogonal least squares algorithm respectively. A common characteristic of these algorithms is that the inherent computation efficiency associated with the orthogonalisation scheme in orthogonal least squares or regularised orthogonal least squares has been extended such that the new algorithms are computationally efficient. A numerical example is included to demonstrate effectiveness of the algorithms. Copyright (C) 2003 IFAC.

Estimation of Hidden Markov Models parameters using differential evolution

Hidden Markov Models (HMMs) have been successfully applied to different modelling and classification problems from different areas over the recent years. An important step in using HMMs is the initialisation of the parameters of the model as the subsequent learning of HMM’s parameters will be dependent on these values. This initialisation should take into account the knowledge about the addressed problem and also optimisation techniques to estimate the best initial parameters given a cost function, and consequently, to estimate the best log-likelihood. This paper proposes the initialisation of Hidden Markov Models parameters using the optimisation algorithm Differential Evolution with the aim to obtain the best log-likelihood.

A fast linear-in-the-parameters classifier construction algorithm using orthogonal forward selection to minimize leave-one-out misclassification rate

We propose a simple and computationally efficient construction algorithm for two class linear-in-the-parameters classifiers. In order to optimize model generalization, a forward orthogonal selection (OFS) procedure is used for minimizing the leave-one-out (LOO) misclassification rate directly. An analytic formula and a set of forward recursive updating formula of the LOO misclassification rate are developed and applied in the proposed algorithm. Numerical examples are used to demonstrate that the proposed algorithm is an excellent alternative approach to construct sparse two class classifiers in terms of performance and computational efficiency.

Are differences in life history parameters of the pine beauty moth Panolis flammea modified by host plant quality or gender?

Pine beauty moth (Panolis flammea D&S, Lepidoptera: Noctuidae) were reared individually from egg hatch to pupation on one of three host plants, Pinus sylvestris (native host plant), Pinus contorta (Central Interior seed origin - good quality introduced host) and P. contorta (Alaskan seed origin - poor quality introduced host). After emerging from the pupae the adult moths were confined to a Skeena River seed origin of P. contorta. Female pupal weight and adult life span were significantly higher on P. sylvestris than on the two lodgepole pine seed origins. Development time was, however, not significantly different between treatments, but larval mean relative growth rate was found to be negatively correlated with birth weight and positively correlated with pupal weight. The time to emerge from the pupa was also not significantly different between treatments. However, there were marked differences between the genders. Male moths lost a significantly greater proportion of their weight over the pupal stage but lived significantly longer as adults than the females. Female moths emerged from the pupal stage significantly sooner than male moths. There was no apparent advantage of lai-ge birth size when looked at in terms of subsequent performance. These results are discussed in light of current life history theory.

Using continuous ground-based radar and lidar measurements for evaluating the representation of clouds in four operational models

The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the present paper using a two-year time series of observations collected by profiling ground-based active remote sensors (cloud radar and lidar) located at three different sites in western Europe (Cabauw. Netherlands; Chilbolton, United Kingdom; and Palaiseau, France). Particular attention is given to potential biases that may arise from instrumentation differences (especially sensitivity) from one site to another and intermittent sampling. In a second step the statistical properties of the cloud variables involved in most advanced cloud schemes of numerical weather forecast models (ice water content and cloud fraction) are characterized and compared with their counterparts in the models. The two years of observations are first considered as a whole in order to evaluate the accuracy of the statistical representation of the cloud variables in each model. It is shown that all models tend to produce too many high-level clouds, with too-high cloud fraction and ice water content. The midlevel and low-level cloud occurrence is also generally overestimated, with too-low cloud fraction but a correct ice water content. The dataset is then divided into seasons to evaluate the potential of the models to generate different cloud situations in response to different large-scale forcings. Strong variations in cloud occurrence are found in the observations from one season to the same season the following year as well as in the seasonal cycle. Overall, the model biases observed using the whole dataset are still found at seasonal scale, but the models generally manage to well reproduce the observed seasonal variations in cloud occurrence. Overall, models do not generate the same cloud fraction distributions and these distributions do not agree with the observations. Another general conclusion is that the use of continuous ground-based radar and lidar observations is definitely a powerful tool for evaluating model cloud schemes and for a responsive assessment of the benefit achieved by changing or tuning a model cloud

A framework for comparing pollinator performance: effectiveness and efficiency

Measuring pollinator performance has become increasingly important with emerging needs for risk assessment in conservation and sustainable agriculture that require multi-year and multi-site comparisons across studies. However, comparing pollinator performance across studies is difficult because of the diversity of concepts and disparate methods in use. Our review of the literature shows many unresolved ambiguities. Two different assessment concepts predominate: the first estimates stigmatic pollen deposition and the underlying pollinator behaviour parameters, while the second estimates the pollinator’s contribution to plant reproductive success, for example in terms of seed set. Both concepts include a number of parameters combined in diverse ways and named under a diversity of synonyms and homonyms. However, these concepts are overlapping because pollen deposition success is the most frequently used proxy for assessing the pollinator’s contribution to plant reproductive success. We analyse the diverse concepts and methods in the context of a new proposed conceptual framework with a modular approach based on pollen deposition, visit frequency, and contribution to seed set relative to the plant’s maximum female reproductive potential. A system of equations is proposed to optimize the balance between idealised theoretical concepts and practical operational methods. Our framework permits comparisons over a range of floral phenotypes, and spatial and temporal scales, because scaling up is based on the same fundamental unit of analysis, the single visit.

Transport impacts on atmosphere and climate: metrics

The transport sector emits a wide variety of gases and aerosols, with distinctly different characteristics which influence climate directly and indirectly via chemical and physical processes. Tools that allow these emissions to be placed on some kind of common scale in terms of their impact on climate have a number of possible uses such as: in agreements and emission trading schemes; when considering potential trade-offs between changes in emissions resulting from technological or operational developments; and/or for comparing the impact of different environmental impacts of transport activities. Many of the non-CO2 emissions from the transport sector are short-lived substances, not currently covered by the Kyoto Protocol. There are formidable difficulties in developing metrics and these are particularly acute for such short-lived species. One difficulty concerns the choice of an appropriate structure for the metric (which may depend on, for example, the design of any climate policy it is intended to serve) and the associated value judgements on the appropriate time periods to consider; these choices affect the perception of the relative importance of short- and long-lived species. A second difficulty is the quantification of input parameters (due to underlying uncertainty in atmospheric processes). In addition, for some transport-related emissions, the values of metrics (unlike the gases included in the Kyoto Protocol) depend on where and when the emissions are introduced into the atmosphere – both the regional distribution and, for aircraft, the distribution as a function of altitude, are important. In this assessment of such metrics, we present Global Warming Potentials (GWPs) as these have traditionally been used in the implementation of climate policy. We also present Global Temperature Change Potentials (GTPs) as an alternative metric, as this, or a similar metric may be more appropriate for use in some circumstances. We use radiative forcings and lifetimes from the literature to derive GWPs and GTPs for the main transport-related emissions, and discuss the uncertainties in these estimates. We find large variations in metric (GWP and GTP) values for NOx, mainly due to the dependence on location of emissions but also because of inter-model differences and differences in experimental design. For aerosols we give only global-mean values due to an inconsistent picture amongst available studies regarding regional dependence. The uncertainty in the presented metric values reflects the current state of understanding; the ranking of the various components with respect to our confidence in the given metric values is also given. While the focus is mostly on metrics for comparing the climate impact of emissions, many of the issues are equally relevant for stratospheric ozone depletion metrics, which are also discussed.

Single trial BCI operation via Wackermann parameters

Accurate single trial P300 classification lends itself to fast and accurate control of Brain Computer Interfaces (BCIs). Highly accurate classification of single trial P300 ERPs is achieved by characterizing the EEG via corresponding stationary and time-varying Wackermann parameters. Subsets of maximally discriminating parameters are then selected using the Network Clustering feature selection algorithm and classified with Naive-Bayes and Linear Discriminant Analysis classifiers. Hence the method is assessed on two different data-sets from BCI competitions and is shown to produce accuracies of between approximately 70% and 85%. This is promising for the use of Wackermann parameters as features in the classification of single-trial ERP responses.

Using modelling tools to optimise the calculation and subsequent reduction of cable distortion parameters with application to oil well logging systems

This paper discusses how the use of computer-based modelling tools has aided the design of a telemetry unit for use with oil well logging. With the aid of modern computer-based simulation techniques, the new design is capable of operating at data rates of 2.5 times faster than previous designs.

Effects of inulin on lipid parameters in humans

Convincing lipid-lowering effects of the fructooligosaccharide inulin have been demonstrated in animals, yet attempts to reproduce similar effects in humans have generated conflicting results. This may be because of the much lower doses used in humans as a result of the adverse gastrointestinal symptoms exhibited by most subjects consuming daily doses in excess of 30 g. Two studies that fed either oligofructose (20 g/d) or inulin (14 g/d) observed no effect on fasting total, LDL or HDL cholesterol, or serum triglycerides. Two other studies that fed inulin either in a breakfast cereal (9 g/d) or as a powdered addition to beverages and meals (10 g/d) reported similar reductions in fasting triglycerides (227 and 219%, respectively). In one of these studies, total and LDL cholesterol concentrations were also modestly reduced (5 and 7%, respectively). Because animal studies have identified inhibition of hepatic fatty acid synthesis as the major site of action for the triglyceride-lowering effects of inulin, and because this pathway is relatively inactive in humans unless a high carbohydrate diet is fed, future attempts to demonstrate lipid-lowering effects of inulin should consider the nature of the background diet as a determinant of response.

The influence of carbon surface oxygen groups on Dubinin–Astakhov equation parameters calculated from CO2 adsorption isotherm

We present the results of a systematic study of the influence of carbon surface oxidation on Dubinin–Astakhov isotherm parameters obtained from the fitting of CO2 adsorption data. Using GCMC simulations of adsorption on realistic VPC models differing in porosity and containing the most frequently occurring carbon surface functionalities (carboxyls, hydroxyls and carbonyls) and their mixtures, it is concluded that the maximum adsorption calculated from the DA model is not strongly affected by the presence of oxygen groups. Unfortunately, the same cannot be said of the remaining two parameters of this model i.e. the heterogeneity parameter (n) and the characteristic energy of adsorption (E0). Since from the latter the pore diameters of carbons are usually calculated, by inverse-type relationships, it is concluded that they are questionable for carbons containing surface oxides, especially carboxyls.