Automatic artefact removal from event-related potentials via clustering

This paper outlines a method for automatic artefact removal from multichannel recordings of event-related potentials (ERPs). The proposed method is based on, firstly, separation of the ERP recordings into independent components using the method of temporal decorrelation source separation (TDSEP). Secondly, the novel lagged auto-mutual information clustering (LAMIC) algorithm is used to cluster the estimated components, together with ocular reference signals, into clusters corresponding to cerebral and non-cerebral activity. Thirdly, the components in the cluster which contains the ocular reference signals are discarded. The remaining components are then recombined to reconstruct the clean ERPs.

Effect of incremental levels of fish oil in the diet on ruminal lipid metabolism in growing steers

Based on the potential benefits to human health, there is interest in developing sustainable nutritional strategies to enhance the concentration of long-chain n-3 fatty acids in ruminant-derived foods. Four Aberdeen Angus steers fitted with rumen and duodenal cannulae were used in a 4 × 4 Latin square experiment with 21 d experimental periods to examine the potential of fish oil (FO) in the diet to enhance the supply of 20 : 5n-3 and 22 : 6n-3 available for absorption in growing cattle. Treatments consisted of total mixed rations based on maize silage fed at a rate of 85 g DM/kg live weight0·75/d containing 0, 8, 16 and 24 g FO/kg diet DM. Supplements of FO reduced linearly (P < 0·01) DM intake and shifted (P < 0·01) rumen fermentation towards propionate at the expense of acetate and butyrate. FO in the diet enhanced linearly (P < 0·05) the flow of trans-16 : 1, trans-18 : 1, trans-18 : 2, 20 : 5n-3 and 22 : 6n-3, and decreased linearly (P < 0·05) 18 : 0 and 18 : 3n-3 at the duodenum. Increases in the flow of trans-18 : 1 were isomer dependent and were determined primarily by higher amounts of trans-11 reaching the duodenum. In conclusion, FO alters ruminal lipid metabolism of growing cattle in a dose-dependent manner consistent with an inhibition of ruminal biohydrogenation, and enhances the amount of long-chain n-3 fatty acids at the duodenum, but the increases are marginal due to extensive biohydrogenation in the rumen.

Quasi-optimal assimilation of satellite retrievals for incremental 4D-Var

An interface between satellite retrievals and the incremental version of the four-dimensional variational assimilation scheme is developed, making full use of the information content of satellite measurements. In this paper, expressions for the function that calculates simulated observations from model states (called “observation operator”), together with its tangent linear version and adjoint, are derived. Results from our work can be used for implementing a quasi-optimal assimilation of satellite retrievals (e.g., of atmospheric trace gases) in operational meteorological centres.

Mean-tracking clustering algorithm for radial basis function centre selection

Radial basis functions can be combined into a network structure that has several advantages over conventional neural network solutions. However, to operate effectively the number and positions of the basis function centres must be carefully selected. Although no rigorous algorithm exists for this purpose, several heuristic methods have been suggested. In this paper a new method is proposed in which radial basis function centres are selected by the mean-tracking clustering algorithm. The mean-tracking algorithm is compared with k means clustering and it is shown that it achieves significantly better results in terms of radial basis function performance. As well as being computationally simpler, the mean-tracking algorithm in general selects better centre positions, thus providing the radial basis functions with better modelling accuracy

Robust initialisation of Gaussian radial basis function networks using partitioned k-means clustering

Radial basis function networks can be trained quickly using linear optimisation once centres and other associated parameters have been initialised. The authors propose a small adjustment to a well accepted initialisation algorithm which improves the network accuracy over a range of problems. The algorithm is described and results are presented.

Modelling niches of arbitrary shape in genetic algorithms using Niche Linkage in the Dynamic Niche Clustering framework

We present some additions to a fuzzy variable radius niche technique called Dynamic Niche Clustering (DNC) (Gan and Warwick, 1999; 2000; 2001) that enable the identification and creation of niches of arbitrary shape through a mechanism called Niche Linkage. We show that by using this mechanism it is possible to attain better feature extraction from the underlying population.

Dynamic Niche Clustering: a fuzzy variable radius niching technique for multimodal optimisation in GAs

This paper describes the recent developments and improvements made to the variable radius niching technique called Dynamic Niche Clustering (DNC). DNC is fitness sharing based technique that employs a separate population of overlapping fuzzy niches with independent radii which operate in the decoded parameter space, and are maintained alongside the normal GA population. We describe a speedup process that can be applied to the initial generation which greatly reduces the complexity of the initial stages. A split operator is also introduced that is designed to counteract the excessive growth of niches, and it is shown that this improves the overall robustness of the technique. Finally, the effect of local elitism is documented and compared to the performance of the basic DNC technique on a selection of 2D test functions. The paper is concluded with a view to future work to be undertaken on the technique.

In vitro gas production and nitrogen degradability of tannin-containing tree fruits in response to incremental levels of polyethylene glycol

This study was designed to determine the response of in vitro fermentation parameters to incremental levels of polyethylene glycol (PEG) when tanniniferous tree fruits (Dichrostachys cinerea, Acacia erioloba, A. erubiscens, A. nilotica and Piliostigma thonningii) were fermented using the Reading Pressure Technique. The trivalent ytterbium precipitable phenolics content of fruit substrates ranged from 175 g/kg DM in A. erubiscens to 607 g/kg DM in A. nilotica, while the soluble condensed tannin content ranged from 0.09 AU550nm/40mg in A. erioloba to 0.52 AU550nm/40 mg in D. cinerea. The ADF was highest in P. thonningii fruits (402 g/kg DM) and lowest in A. nilotica fruits (165 g/kg DM). Increasing the level of PEG caused an exponential rise to a maximum (asymptotic) for cumulative gas production, rate of gas production and nitrogen degradability in all substrates except P. thonningii fruits. Dry matter degradability for fruits containing higher levels of soluble condensed tannins (D. cinerea and P. thonningii), showed little response to incremental levels of PEG after incubation for 24 h. The minimum levels of PEG required to maximize in vitro fermentation of tree fruits was found to be 200 mg PEG/g DM of sample for all tree species except A. erubiscens fruits, which required 100 mg PEG/g DM sample. The study provides evidence that PEG levels lower than 1 g/g DM sample can be used for in vitro tannin bioassays to reduce the cost of evaluating non-conventional tanniniferous feedstuffs used in developing countries in the tropics and subtopics. The use of in vitro nitrogen degradability in place of the favoured dry matter degradability improved the accuracy of PEG as a diagnostic tool for tannins in in vitro fermentation systems.

Conditioning of incremental variational data assimilation, with application to the Met Office system

Implementations of incremental variational data assimilation require the iterative minimization of a series of linear least-squares cost functions. The accuracy and speed with which these linear minimization problems can be solved is determined by the condition number of the Hessian of the problem. In this study, we examine how different components of the assimilation system influence this condition number. Theoretical bounds on the condition number for a single parameter system are presented and used to predict how the condition number is affected by the observation distribution and accuracy and by the specified lengthscales in the background error covariance matrix. The theoretical results are verified in the Met Office variational data assimilation system, using both pseudo-observations and real data.