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

Racial and Ethnic Differences in Chronic Pain

Chronic pain literature consistently shows differences in the prevalence of chronic pain by race and ethnicity. However, these studies primarily focus on White, African American, and Hispanic respondents. This paper aims to examine differences in pain by race and ethnicity including most major racial categories as well as Asian, Native American, and multiple-race respondents. This study uses data from the 2017 and 2018 National Health Interview Survey (n=33,161). To determine the relationship between race and ethnicity and chronic pain, we conducted multiple nested logistic regression. The analysis found that African Americans [OR= 0.67, p\u3c0.001], Hispanic [OR= 0.61, p\u3c0.001], and Asian [OR= 0.42, p\u3c0.001] respondents have lower odds of pain when compared to White participants while multiracial respondents have higher odds of chronic pain [OR = 1.28, p\u3c0.05]. This study is important for future research as it shows the need for other scholars, as well as policymakers, to focus on expanding racial and ethnic categories commonly studied in chronic pain literature

Time series semi-Markov decision process with variable costs for maintenance planning

Deciding when and how to maintain offshore wind turbines is becoming even more complex as the size of wind farms increases, while accessibility is challenging compared to onshore wind farms. Planning future maintenance actions requires the wind farm operator to consider factors such as the current condition of the turbine, the cost of a given maintenance action, revenue generated by the asset, weather factors and vessel availability. Rather than making case-by-case decisions for each turbine, the approach described in this paper allows the wind farm operators to automate the process of short to-medium term maintenance planning through application of a Semi-Markov Decision Process (SMDP). The model proposed here is capable of suggesting the cost-optimal maintenance policy given weather forecast, future vessel costs and availability and the current condition of the turbine. Using the semi-Markov approach, allows the user to implement time varying failure rate. As the model is capable of utilising time-series data, future weather and vessel constraints can be applied depending on the information available to the user at the time, which will be reflected in the optimal policy suggested by the model. The model proposed here facilitates maintenance decision making in wind farms and will lead to cost reduction through more efficient planning. In addition to that, the model can be used to carry out a cost-benefit analysis of using vessels with different properties

Semigroup analysis of structured parasite populations

Motivated by structured parasite populations in aquaculture we consider a class of size-structured population models, where individuals may be recruited into the population with distributed states at birth. The mathematical model which describes the evolution of such a population is a first-order nonlinear partial integro-differential equation of hyperbolic type. First, we use positive perturbation arguments and utilise results from the spectral theory of semigroups to establish conditions for the existence of a positive equilibrium solution of our model. Then, we formulate conditions that guarantee that the linearised system is governed by a positive quasicontraction semigroup on the biologically relevant state space. We also show that the governing linear semigroup is eventually compact, hence growth properties of the semigroup are determined by the spectrum of its generator. In the case of a separable fertility function, we deduce a characteristic equation, and investigate the stability of equilibrium solutions in the general case using positive perturbation arguments.Comment: to appear in Mathematical Modelling of Natural Phenomen

What is the value of a standard?

Standards play a critical role in the procurement of defence, and other, systems. Choosing the most appropriate standard is important but has become more topical given the UK Ministry of Defence policy of “as civilian as possible, as military as necessary”. Whereas historically managers might have selected from classes of defence standards, this choice set is now increased to include civil standards. We develop a model that has been commissioned by the UK Defence Standardisation whose responsibilities include supporting project teams on the selection of standards. Our model is based on an extension of Bayesian Belief Networks, called an Influence Diagram, which allows decisions and consequences to be represented as well as uncertain-ties. We have developed an initial model for a real case to assess the feasibility and use. We outline the con-text of the defence procurement project in our case study and describe the reasoning underpinning the model structure. We have found that it is possible to develop a simple model that captures the views of multiple stakeholders and informs a reasoned choice about the value of alternative standards

On modeling player fitness in training for team sports with application to professional rugby

It is increasingly important for professional sports teams to monitor player fitness in order to optimize performance. Models have been put forward linking fitness in training to performance in competition but rely on regular measurements of player fitness. As formal tests for measuring player fitness are typically time-consuming and inconvenient, measurements are taken infrequently. As such, it may be challenging to accurately predict performance in competition as player fitness is unknown.Alternatively, other data, such as how the players are feeling, may be measured more regularly. This data, however, may be biased as players may answer the questions differently and these differences may dominate the data. Linear Mixed Methods and Support Vector Machines were used to estimate player fitness from available covariates at times when explicit measures of fitness are unavailable. Using data provided by Glasgow Warriors Rugby Club, a case study was used to illustrate the application and value of these models. Both models performed well with R2 values ranging from 60% to 85%, demonstrating that the models largely captured the biases introduced by individual players

Changes in epidemiological patterns of sea lice infestation on farmed Atlantic salmon, Salmo salar L., in Scotland between 1996 and 2006

Analyses of a unique database containing sea lice records over an 11 year period provide evidence of changing infestation patterns in Scotland. The data, collected from more than 50 commercial Atlantic salmon farms, indicate that both species of sea lice commonly found in Scotland, Lepeophtheirus salmonis and Caligus elongatus, have declined on farms over the past decade. Reductions for both species have been particularly marked since 2001 when more effective veterinary medicines became available. Treatment data were also available in the database and these show a growing trend towards the use of the in feed medication emamectin benzoate (Slice), particularly in the first year of the salmon production cycle. However, this trend to wards single product use has not been sustained in 2006, the latest year for which data are available. There is some evidence of region to region variation within Scotland with the Western Isles experiencing higher levels of infestation. However, compared to the levels observed between 1996 and 2000, all regions have benefited from reduced lice infestation, with the overall pattern showing a particular reduction in the second and third quarters of the second year of production

Intelligent integrated maintenance for wind power generation

A novel architecture and system for the provision of Reliability Centred Maintenance (RCM) for offshore wind power generation is presented. The architecture was developed by conducting a bottom-up analysis of the data required to support RCM within this specific industry, combined with a top-down analysis of the required maintenance functionality. The architecture and system consists of three integrated modules for Intelligent Condition Monitoring, Reliability and Maintenance Modelling, and Maintenance Scheduling that provide a scalable solution for performing dynamic, efficient and cost effective preventative maintenance management within this extremely demanding renewable energy generation sector. The system demonstrates for the first time, the integration of state-of-the-art advanced mathematical techniques: Random Forests, Dynamic Bayesian Networks, and Memetic Algorithms in the development of an intelligent autonomous solution. The results from the application of the intelligent integrated system illustrated the automated detection of faults within a wind farm consisting of over 100 turbines, the modelling and updating of the turbines’ survivability and creation of a hierarchy of maintenance actions, and the optimising of the maintenance schedule with a view to maximising the availability and revenue generation of the turbines

Robust Rolling Horizon Optimisation Model for Offshore Wind Farm Installation Logistics

Our approach can be considered as both proactive and reactive, since uncertainty is considered both in creating the initial schedule and the schedule can be updated in real-time