The economic viability and potential of a novel poultry agroforestry system

Investigating agroforestry systems that incorporate poultry is warranted in Northern Europe as they may offer benefits including: improved welfare and use of range; reduced feed costs; price premia on products; reduced payback periods for forests; and, greater returns on investment. Free-range egg production accounts for 27% of the United Kingdom egg market and demand for outdoor broilers is increasing. No research has been conducted recently on the economic viability of agroforestry systems with poultry. An economic model was constructed to: assess economic viability of a broiler agroforestry system; and, investigate the sensitivity of economic performance to key factors and interactions, and identify those which warrant attention in research and management. The system modelled is a commercial trial established in Southern England in 2002 where deciduous trees were planted and broilers reared in six- or nine-week periods. The model uses Monte Carlo simulation and financial performance analyses run for a 120-year period. An Internal Rate of Return (IRR) of 15.5% is predicted for the six-week system which remains viable under a 'worst case' scenario (IRR of 12.6%). Factors which affect financial performance most (decreasing in magnitude) are prices achieved for broilers, costs of brooding houses, chicks, arks, feed and timber prices. The main anticipated effects of biological interactions on financial performance (increased ranging on feed conversion and excess nutrient supply on tree health) were not supported by analysis. Further research is particularly warranted on the welfare benefits offered by the tree component and its relation to price premia.

Soil disturbed using a strip tillage implement on a range of soil types and the effects on sugar beet establishment

The area of soil disturbed using a single tine is well documented. However, modern strip tillage implements using a tine and disc design have not been assessed in the UK or in mainland Europe. Using a strip tillage implement has potential benefits for European agriculture where economic returns and sustainability are key issues. Using a strip tillage system a narrow zone is cultivated leaving most of the straw residue on the soil surface. Small field plot experiments were undertaken on three soil types and the operating parameters of forward speed, tine depth and tine design were investigated together with measurements of seedbed tilth and crop emergence. The type of tine used was found to be the primary factor in achieving the required volume of disturbance within a narrow zone whilst maintaining an area of undisturbed soil with straw residue on the surface. The winged tine produced greater disturbance at a given depth compared with the knife tine. Increasing forward speed did not consistently increase the volume of disturbance. In a sandy clay loam the tilth created and emergence of sugar beet by strip tillage and ploughing were similar but on a sandy loam the strip tillage treatments generally gave a finer tilth but poorer emergence particularly at greater working depth.

Collaborative tele-rehabilitation: A strategy for increasing engagement

This paper examines the influence of a collaborative rehabilitation environment that encourages a long-distance collaborative "play" using two robot-mediated environments. This study presents a strategy for increasing motivation on able-bodied persons, applicable to impaired persons, to engage, sustain play and relate during a shared task. The study consisted of a series of eighteen single case studies, each involved in two distinct phases and assessed using a multidimensional measurement intended to assess participant' subjective experience. The results showed a clear positive trend in favour of the robot-mediated game environment. Subjects found the collaborative environment more valuable and more interesting and enjoyable. As a consequence, it appears subjects were willing to spend more time at a task.

Increasing detection rate of user-to-root attacks using genetic algorithms

An extensive set of machine learning and pattern classification techniques trained and tested on KDD dataset failed in detecting most of the user-to-root attacks. This paper aims to provide an approach for mitigating negative aspects of the mentioned dataset, which led to low detection rates. Genetic algorithm is employed to implement rules for detecting various types of attacks. Rules are formed of the features of the dataset identified as the most important ones for each attack type. In this way we introduce high level of generality and thus achieve high detection rates, but also gain high reduction of the system training time. Thenceforth we re-check the decision of the user-to- root rules with the rules that detect other types of attacks. In this way we decrease the false-positive rate. The model was verified on KDD 99, demonstrating higher detection rates than those reported by the state- of-the-art while maintaining low false-positive rate.