Epidemics and control strategies for diseases of farmed salmonids: A parameter study

AbstractThe susceptibility of the English and Welsh fish farming and fisheries industry to emergent diseases is assessed using a stochastic simulation model. The model dynamics operate on a network comprising directed transport and river contacts, as well as undirected local and fomite transmissions. The directed connections cause outward transmission risk to be geographically more confined than inward risk. We consider reactive, proactive, and hybrid methods of control which correspond to a mixture of policy and the ease of disease detection. An explicit investigation of the impact of laboratory capacity is made. General quantified guidelines are derived to mitigate future epidemics

Final Technical Report: Integrated Restoration Strategies Towards Weed Control on Western Rangelands

Invasive species are having severe ecological (Mack et al. 2000) and economic (Pimentel et al. 2005) impacts on ecosystems around the world. Invasive species can alter many ecosystem processes (Crooks 2002, Walker & Smith 1997) including: water and nutrient availability, such as form and amount of N if the soil (Evans et al. 2001, Sperry et al. 2006); primary productivity, through shifts in growth rates or efficiency of resource use; disturbance regimes, including the type, frequency, and severity of disturbances such as fire (D’Antonio 2002); and community dynamics, such as species replacements (Alvarez & Cushman 2002). The economic losses and damages by invasive plants are estimated to be ~$34 billion in the US and ~$95 billion worldwide (Pimental et al. 2005). Although trade and human migrations are among the most important vectors for introducing invasive plants (Mack et al. 2000), similar consensus on the causal mechanism for invasiveness is lacking (Dietz & Edwards 2006). Many different hypotheses have been proposed to explain why species are invasive. Some hypotheses, such as the vacant niche hypothesis, are conceptually appealing but lack concrete evidence to support them (Mack et al. 2000). Others, such as the allelopathy hypothesis (Callaway & Aschehoug 2000, Bais et al. 2003), have strong evidence to support them for some specific cases, but are unlikely to be important for most plants. Understanding why a species is invasive is important because it provides insight into how to control the invasion. Because a causal mechanism that is universally applicable to all plants has not been identified to date, careful attention must be made to biological and ecological characteristics of the plants and communities of interest if control strategies are to be implemented

Third ERTS Symposium: Abstracts

Abstracts are provided for the 112 papers presented at the Earth Resources Program Symposium held at Washington, D.C., 10-14 December, 1973

Improvement of lake water quality by paying farmers to abate nonpoint source pollution

To mitigate damages caused by agricultural runoff, private lake owners' associations are paying for inlake and instream pollution abatement measures and onland conservation practices. This phenomenon supports the notion that individuals who benefit from improved water quality should be willing to pay part of the abatement costs. Our research suggests that onland conservation measures can substantially reduce sediment delivery at low cost. The Sediment Economics (SEDEC) model was modified and then used to select and to site management systems that achieved stated sediment goals at least cost. Other resource policies such as T value, no-till, and contouring were compared with the least-cost frontier and shown to be more costly. Abatement costs decreased substantially and sediment delivery increased only slightly when the same resource policies were applied to cropland areas closest to water channels. The research also pointed out the importance of noncropland areas adjacent to water channels. The noncropland areas substantially reduced sediment delivery to water channels and lowered abatement costs. Further research is needed for long-range watershed planning models such as SEDEC. More work is needed on the modelling of physical processes, particularly sediment delivery. The model also needs to be repackaged into a user-friendly format.U.S. Department of the Interior || U.S. Geological SurveyU.S. Geological SurveyOpe

Proceedings, High Altitude Revegetation Workshop no. 5: Colorado State University, Fort Collins, Colorado, March 8-9, 1982

Includes bibliographies.High Altitude Revegetation Workshop (5th : 1982 : Fort Collins, Colo.

Towards an Unsupervised Bayesian Network Pipeline for Explainable Prediction, Decision Making and Discovery

An unsupervised learning pipeline for discrete Bayesian networks is proposed to facilitate prediction, decision making, discovery of patterns, and transparency in challenging real-world AI applications, and contend with data limitations. We explore methods for discretizing data, and notably apply the pipeline to prediction and prevention of preterm birth

A teachable semi-automatic web information extraction system based on evolved regular expression patterns

This thesis explores Web Information Extraction (WIE) and how it has been used in decision making and to support businesses in their daily operations. The research focuses on a WIE system based on Genetic Programming (GP) with an extensible model to enhance the automatic extractor. This uses a human as a teacher to identify and extract relevant information from the semi-structured HTML webpages. Regular expressions, which have been chosen as the pattern matching tool, are automatically generated based on the training data to provide an improved grammar and lexicon. This particularly benefits the GP system which may need to extend its lexicon in the presence of new tokens in the web pages. These tokens allow the GP method to produce new extraction patterns for new requirements

On microelectronic self-learning cognitive chip systems

After a brief review of machine learning techniques and applications, this Ph.D. thesis examines several approaches for implementing machine learning architectures and algorithms into hardware within our laboratory. From this interdisciplinary background support, we have motivations for novel approaches that we intend to follow as an objective of innovative hardware implementations of dynamically self-reconfigurable logic for enhanced self-adaptive, self-(re)organizing and eventually self-assembling machine learning systems, while developing this new particular area of research. And after reviewing some relevant background of robotic control methods followed by most recent advanced cognitive controllers, this Ph.D. thesis suggests that amongst many well-known ways of designing operational technologies, the design methodologies of those leading-edge high-tech devices such as cognitive chips that may well lead to intelligent machines exhibiting conscious phenomena should crucially be restricted to extremely well defined constraints. Roboticists also need those as specifications to help decide upfront on otherwise infinitely free hardware/software design details. In addition and most importantly, we propose these specifications as methodological guidelines tightly related to ethics and the nowadays well-identified workings of the human body and of its psyche

Weed/Plant Classification Using Evolutionary Optimised Ensemble Based On Local Binary Patterns

This thesis presents a novel pixel-level weed classification through rotation-invariant uniform local binary pattern (LBP) features for precision weed control. Based on two-level optimisation structure; First, Genetic Algorithm (GA) optimisation to select the best rotation-invariant uniform LBP configurations; Second, Covariance Matrix Adaptation Evolution Strategy (CMA-ES) in the Neural Network (NN) ensemble to select the best combinations of voting weights of the predicted outcome for each classifier. The model obtained 87.9% accuracy in CWFID public benchmark