Mark Baillie

The efficacy of emamectin benzoate against infestations of Lepeophtheirus salmonis on farmed Atlantic salmon (Salmo salar L) in Scotland, 2002-2006

Background Infestations of the parasitic copepod Lepeophtheirus salmonis, commonly referred to as sea lice, represent a major challenge to commercial salmon aquaculture. Dependence on a limited number of theraputants to control such infestations has led to concerns of reduced sensitivity in some sea lice populations. This study investigates trends in the efficacy of the in-feed treatment emamectin benzoate in Scotland, the active ingredient most widely used across all salmon producing regions. Methodology/Principal Findings Study data were drawn from over 50 commercial Atlantic salmon farms on the west coast of Scotland between 2002 and 2006. An epi-informatics approach was adopted whereby available farm records, descriptive epidemiological summaries and statistical linear modelling methods were used to identify factors that significantly affect sea lice abundance following treatment with emamectin benzoate (SLICE®, Schering Plough Animal Health). The results show that although sea lice infestations are reduced following the application of emamectin benzoate, not all treatments are effective. Specifically there is evidence of variation across geographical regions and a reduction in efficacy over time. Conclusions/Significance Reduced sensitivity and potential resistance to currently available medicines are constant threats to maintaining control of sea lice populations on Atlantic salmon farms. There is a need for on-going monitoring of emamectin benzoate treatment efficacy together with reasons for any apparent reduction in performance. In addition, strategic rotation of medicines should be encouraged and empirical evidence for the benefit of such strategies more fully evaluated.

Factors associated with changing efficacy of emamectin benzoate against infestations of Lepeophtheirus salmonis on Scottish salmon farms

The availability and use of medicines to control infestations of sea lice on Atlantic salmon, Salmosalar L., farms in Scotland has changed considerably in the last decade (Lees, Gettinby & Revie 2008b). Whereas hydrogen peroxide and organophosphate compounds were used widely throughout the 1990s and in the early 2000s, only two therapeutants have remained in common use since 2005: topical cypermethrin (Excis; Novartis Animal Health, Camberley, UK) and an oral formulation of emamectin benzoate (SLICE; Schering Plough Animal Health, Uxbridge, UK).

Exploring memory in email refinding

Human memory plays an important role in personal information management (PIM). Several scholars have noted that people refind information based on what they remember and it has been shown that people adapt their management strategies to compensate for the limitations of memory. Nevertheless, little is known about what people tend to remember about their personal information and how they use their memories to refind. The aim of this article is to increase our understanding of the role that memory plays in the process of refinding personal information. Concentrating on email re-finding, we report on a user study that investigates what attributes of email messages participants remember when trying to refind. We look at how the attributes change in different scenarios and examine the factors which impact on what is remembered.

A statistical comparison of tag and query logs

We investigate tag and query logs to see if the terms people use to annotate websites are similar to the ones they use to query for them. Over a set of URLs, we compare the distribution of tags used to annotate each URL with the distribution of query terms for clicks on the same URL. Understanding the relationship between the distributions is important to determine how useful tag data may be for improving search results and conversely, query data for improving tag prediction. In our study, we compare both term frequency distributions using vocabulary overlap and relative entropy. We also test statistically whether the term counts come from the same underlying distribution. Our results indicate that the vocabulary used for tagging and searching for content are similar but not identical. We further investigate the content of the websites to see which of the two distributions (tag or query) is most similar to the content of the annotated/searched URL. Finally, we analyze the similarity for different categories of URLs in our sample to see if the similarity between distributions is dependent on the topic of the website or the popularity of the URL.

Towards query log based personalization using topic models

We investigate the utility of topic models for the task of personalizing search results based on information present in a large query log. We define generative models that take both the user and the clicked document into account when estimating the probability of query terms. These models can then be used to rank documents by their likelihood given a particular query and user pair.

Adaptive query-based sampling of distributed collections

As part of a Distributed Information Retrieval system a description of each remote information resource, archive or repository is usually stored centrally in order to facilitate resource selection. The acquisition of precise resource descriptions is therefore an important phase in Distributed Information Retrieval, as the quality of such representations will impact on selection accuracy, and ultimately retrieval performance. While Query-Based Sampling is currently used for content discovery of uncooperative resources, the application of this technique is dependent upon heuristic guidelines to determine when a sufficiently accurate representation of each remote resource has been obtained. In this paper we address this shortcoming by using the Predictive Likelihood to provide both an indication of the quality of an acquired resource description estimate, and when a sufficiently good representation of a resource has been obtained during Query-Based Sampling.

Temporal and spatial variations in lice numbers on salmon farms in the Hardanger fjord 2004–06

The long and narrow Hardanger fjord in western Norway has a high density of salmon farms and has had severe salmon lice, Lepeophtheirus salmonis, problems. In the years 2004-06, salmon lice numbers were recorded in selected salmon farms in the fjord as part of a larger research project. Most farm sites participated in a strategic control programme and were deloused between November and January in each year. The aim of the programme was to achieve a mean abundance of <0.3 adult female lice at this time and to minimize the infection pressure on wild smolts in the spring. Dedicated teams carried out detailed counting of lice on farmed fish in April-September each year. Temperature conditions were fairly similar throughout the fjord and amongst years, but wide variations in salinities were observed. The two innermost zones, B and C, had the lowest lice mean abundances, whereas the outermost zones, D and E, consistently had more lice. General linear model analyses showed that differences in adult female lice abundance between the zones were associated with differing levels of salinity and emamectin benzoate treatments strategically administered. Mean fish weight was significantly positively correlated with mean abundance of adult female lice.

Updating collection representations for federated search

To facilitate the search for relevant information across a setof online distributed collections, a federated information retrieval system typically represents each collection, centrally, by a set of vocabularies or sampled documents. Accurate retrieval is therefore related to how precise each representation reflects the underlying content stored in that collection. As collections evolve over time, collection representations should also be updated to reflect any change, however, a current solution has not yet been proposed. In this study we examine both the implications of out-of-date representation sets on retrieval accuracy, as well as proposing three different policies for managing necessary updates. Each policyis evaluated on a testbed of forty-four dynamic collections over an eight-week period. Our findings show that out-of-date representations significantly degrade performance overtime, however, adopting a suitable update policy can minimise this problem.

Tripartite hidden topic models for personalised tag suggestion

Social tagging systems provide methods for users to categorise resources using their own choice of keywords (or “tags”) without being bound to a restrictive set of predefined terms. Such systems typically provide simple tag recommendations to increase the number of tags assigned to resources. In this paper we extend the latent Dirichlet allocation topic model to include user data and use the estimated probability distributions in order to provide personalised tag suggestions to users. We describe the resulting tripartite topic model in detail and show how it can be utilised to make personalised tag suggestions. Then, using data from a large-scale, real life tagging system, test our system against several baseline methods. Our experiments show a statistically significant increase in performance of our model over all key metrics, indicating that the model could be successfully used to provide further social tagging tools such as resource suggestion and collaborative filtering.

The use of prevalence as a measure of lice burden: a case study of Lepeophtheirus salmonis on Scottish Atlantic salmon, Salmo salar L., farms

This study investigates the benefits of using prevalence as a summary measure of sea lice infestation on farmed Atlantic salmon, Salmo salar L. Aspects such as sampling effort, the relationship between abundance and prevalence arising from the negative binomial distribution, and how this relationship can be used to indicate the degree of aggregation of lice on a site at a given time point are discussed. As a case study, data were drawn from over 50 commercial Atlantic salmon farms on the west coast of Scotland between 2002 and 2006. Descriptive statistics and formal analysis using a linear modelling technique identified significant variations in sea lice prevalence across year class, region and season. Supporting evidence of a functional relationship between prevalence and abundance of sea lice is provided, which is explained through the negative binomial distribution.