Stranding events provide indirect insights into the seasonality and persistence of jellyfish medusae (Cnidaria : Scyphozoa)

It is becoming increasingly evident that jellyfish (Cnidaria: Scyphozoa) play an important role within marine ecosystems, yet our knowledge of their seasonality and reproductive strategies is far from complete. Here, we explore a number of life history hypotheses for three common, yet poorly understood scyphozoan jellyfish (Rhizostoma octopus; Chrysaora hysoscella; Cyanea capillata) found throughout the Irish and Celtic Seas. Specifically, we tested whether (1) the bell diameter/wet weight of stranded medusae increased over time in a manner that suggested a single synchronised reproductive cohort; or (2) whether the range of sizes/weights remained broad throughout the stranding period suggesting the protracted release of ephyrae over many months. Stranding data were collected at five sites between 2003 and 2006 (n = 431 surveys; n = 2401 jellyfish). The relationship between bell diameter and wet weight was determined for each species (using fresh specimens collected at sea) so that estimates of wet weight could also be made for stranded individuals. For each species, the broad size and weight ranges of stranded jellyfish implied that the release of ephyrae may be protracted (albeit to different extents) in each species, with individuals of all sizes present in the water column during the summer months. For R. octopus, there was a general increase in both mean bell diameter and wet weight from January through to June which was driven by an increase in the variance and overall range of both variables during the summer. Lastly, we provide further evidence that rhizostome jellyfish may over-wintering as pelagic medusa which we hypothesise may enable them to capitalise on prey available earlier in the year.

Locally regularised two-stage learning algorithm for RBF network centre selection

Nonlinear models constructed from radial basis function (RBF) networks can easily be over-fitted due to the noise on the data. While information criteria, such as the final prediction error (FPE), can provide a trade-off between training error and network complexity, the tunable parameters that penalise a large size of network model are hard to determine and are usually network dependent. This article introduces a new locally regularised, two-stage stepwise construction algorithm for RBF networks. The main objective is to produce a parsomous network that generalises well over unseen data. This is achieved by utilising Bayesian learning within a two-stage stepwise construction procedure to penalise centres that are mainly interpreted by the noise.

Safe Therapeutic Economic Pharmaceutical Selection (STEPS): development, introduction and use in Northern Ireland

A number of medicine selection methods have been used worldwide for formulary purposes. In Northern Ireland, integrated medicines management is being developed, and related projects have been carried out. This paper deals with the description of the STEPS (Safe Therapeutic Economic Pharmaceutical Selection) programme. The paper outlines the development of STEPS and its application as an element of a cost-effective medicines-management process in Northern Ireland.

An efficient feature selection method for mobile devices with application to activity recognition

This paper presents a feature selection method for data classification, which combines a model-based variable selection technique and a fast two-stage subset selection algorithm. The relationship between a specified (and complete) set of candidate features and the class label is modelled using a non-linear full regression model which is linear-in-the-parameters. The performance of a sub-model measured by the sum of the squared-errors (SSE) is used to score the informativeness of the subset of features involved in the sub-model. The two-stage subset selection algorithm approaches a solution sub-model with the SSE being locally minimized. The features involved in the solution sub-model are selected as inputs to support vector machines (SVMs) for classification. The memory requirement of this algorithm is independent of the number of training patterns. This property makes this method suitable for applications executed in mobile devices where physical RAM memory is very limited. An application was developed for activity recognition, which implements the proposed feature selection algorithm and an SVM training procedure. Experiments are carried out with the application running on a PDA for human activity recognition using accelerometer data. A comparison with an information gain based feature selection method demonstrates the effectiveness and efficiency of the proposed algorithm.

Indirect comparisons of treatments based on systematic reviews of randomised controlled trials

Randomised controlled trials are the most effective way to differentiate between the effects of competing interventions. However, head-to-head studies are unlikely to have been conducted for all competing interventions.

The potential for human exposure, direct and indirect, to the suspected carcinogenic triphenylmethane dye Brilliant Green from green paper towels

Triphenylmethanes - Malachite Green (MG), Crystal Violet (CV) and Brilliant Green (BC) are dyes with known genotoxic and carcinogenic properties. Apart from being illegally used in aquaculture for treatment of fish diseases they are also applied in industry such as paper production to colour paper towels widely used in hospitals, factories and other locations for hand drying after washing. The present study provides evidence that the triphenylmethane dye (BC) present in green paper towels can migrate through the skin even when the exposure time is short (30-300 s). The transfer of the dye from the towel to food (fish) was also studied and a high amount of colour was found to migrate during overnight exposure. The risk to humans associated with these two dye transfer studies was assessed using a 'margin of exposure approach' on the basis of the toxicological data available for the closely related dye MG and its metabolite Leucomalachite Green. The data indicated that the risk associated with the use of triphenylmethane containing paper towels is of a similar proportion to the risk associated with consumption of fish contaminated with these dyes due to the illegal application in aquaculture. (C) 2011 Elsevier Ltd. All rights reserved.