Relationships between lameness and feeding behaviour in cubicle-housed Holstein-Friesian dairy cows

The relationship between lameness and feeding behaviour in dairy cows is not yet fully understood. This study examined the effect of lameness on feeding behaviour at two points during lactation. Forty-five Holstein–Friesian dairy cows (average parity 3.3) were housed in cubicle accommodation after calving and fed a total mixed ration (TMR). At approximately 60 and 120 days post partum, 48 h of information on feeding behaviour (including number of meals eaten, meal duration, meal size and feeding rate) was collected for each animal using feed boxes fitted to a data recording system. At the same time points, locomotion scores were recorded for each cow as a measure of lameness (1.0-sound to 4.5-severely lame). Relationships between feeding behaviour and locomotion score were analysed using Residual Maximum Likelihood (REML) analysis. At both time points, cows with higher locomotion scores ate fewer (P < 0.001), larger meals (P < 0.001) and had a shorter total feeding time (P < 0.001). At day 60 post partum, an increase in locomotion score was associated with a decrease in dry matter intake (P < 0.05), but at day 120 post partum no relationship was found between locomotion score and DMI. No relationship was found at either time point between locomotion score and mean meal duration or rate of feeding. The results of this study suggest that the effect of lameness on feeding behaviour in dairy cows does not remain constant across lactation.

Guidelines and considerations for conducting experiments using tissue microarrays

Tissue microarrays (TMAs) represent a powerful method for undertaking large-scale tissue-based biomarker studies. While TMAs offer several advantages, there are a number of issues specific to their use which need to be considered when employing this method. Given the investment in TMA-based research, guidance on design and execution of experiments will be of benefit and should help researchers new to TMA-based studies to avoid known pitfalls. Furthermore, a consensus on quality standards for TMA-based experiments should improve the robustness and reproducibility of studies, thereby increasing the likelihood of identifying clinically useful biomarkers. In order to address these issues, the National Cancer Research Institute Biomarker and Imaging Clinical Studies Group organized a 1-day TMA workshop held in Nottingham in May 2012. The document herein summarizes the conclusions from the workshop. It includes guidance and considerations on all aspects of TMA-based research, including the pre-analytical stages of experimental design, the analytical stages of data acquisition, and the postanalytical stages of data analysis. A checklist is presented which can be used both for planning a TMA experiment and interpreting the results of such an experiment. For studies of cancer biomarkers, this checklist could be used as a supplement to the REMARK guidelines.

Man-in-the-Middle Attack Test-bed Investigating Cyber-security Vulnerabilities in Smart Grid SCADA Systems

The increased complexity and interconnectivity of Supervisory Control and Data Acquisition (SCADA) systems in the Smart Grid has exposed them to a wide range of cyber-security issues, and there are a multitude of potential access points for cyber attackers. This paper presents a SCADA-specific cyber-security test-bed which contains SCADA software and communication infrastructure. This test-bed is used to investigate an Address Resolution Protocol (ARP) spoofing based man-in-the-middle attack. Finally, the paper proposes a future work plan which focuses on applying intrusion detection and prevention technology to address cyber-security issues in SCADA systems.

A Study of Tower Shadow Effect on Fixed-Speed Wind Turbines

This paper studies the impact of tower shadow effect on the power output of a fixed-speed wind farm. A data acquisition unit was placed at a wind farm in Northern Ireland which consists of ten fixed-speed wind turbines. The recording equipment logged the wind farmpsilas electrical data, which was time stamped using the global positioning network. Video footage of the wind farm was recorded and from it the blade angle of each turbine was determined with respect to time. Using the blade angle data and the wind farmpsilas power output, studies where performed to ascertain the extent of tower shadow effect on power fluctuation. This paper presents evidence that suggests that tower shadow effect has a significant impact on power fluctuation and that this effect is increased due to the synchronising of turbine blades around the tower region.

Overcoming the Scalability Challenges of Epidemic Simulations on Blue Waters

Modeling dynamical systems represents an important application class covering a wide range of disciplines including but not limited to biology, chemistry, finance, national security, and health care. Such applications typically involve large-scale, irregular graph processing, which makes them difficult to scale due to the evolutionary nature of their workload, irregular communication and load imbalance. EpiSimdemics is such an application simulating epidemic diffusion in extremely large and realistic social contact networks. It implements a graph-based system that captures dynamics among co-evolving entities. This paper presents an implementation of EpiSimdemics in Charm++ that enables future research by social, biological and computational scientists at unprecedented data and system scales. We present new methods for application-specific processing of graph data and demonstrate the effectiveness of these methods on a Cray XE6, specifically NCSA's Blue Waters system.

Incorporating PGMs into a BDI Architecture

In this paper, we present a hybrid BDI-PGM framework, in which PGMs (Probabilistic Graphical Models) are incorporated into a BDI (belief-desire-intention) architecture. This work is motivated by the need to address the scalability and noisy sensing issues in SCADA (Supervisory Control And Data Acquisition) systems. Our approach uses the incorporated PGMs to model the uncertainty reasoning and decision making processes of agents situated in a stochastic environment. In particular, we use Bayesian networks to reason about an agent’s beliefs about the environment based on its sensory observations, and select optimal plans according to the utilities of actions defined in influence diagrams. This approach takes the advantage of the scalability of the BDI architecture and the uncertainty reasoning capability of PGMs. We present a prototype of the proposed approach using a transit scenario to validate its effectiveness.

Can(Plan)+: Extending the Operational Semantics of the BDI Architecture to deal with Uncertain Information

The BDI architecture, where agents are modelled based on their beliefs, desires and intentions, provides a practical approach to develop large scale systems. However, it is not well suited to model complex Supervisory Control And Data Acquisition (SCADA) systems pervaded by uncertainty. In this paper we address this issue by extending the operational semantics of Can(Plan) into Can(Plan)+. We start by modelling the beliefs of an agent as a set of epistemic states where each state, possibly using a different representation, models part of the agent's beliefs. These epistemic states are stratified to make them commensurable and to reason about the uncertain beliefs of the agent. The syntax and semantics of a BDI agent are extended accordingly and we identify fragments with computationally efficient semantics. Finally, we examine how primitive actions are affected by uncertainty and we define an appropriate form of lookahead planning.

Monitoring Bridge Dynamic Behaviour using an Instrumented Two Axle Vehicle

Highway structures such as bridges are subject to continuous degradation primarily due to ageing, loading and environmental factors. A rational transport policy must monitor and provide adequate maintenance to this infrastructure to guarantee the required levels of transport service and safety. Increasingly in recent years, bridges are being instrumented and monitored on an ongoing basis due to the implementation of Bridge Management Systems. This is very effective and provides a high level of protection to the public and early warning if the bridge becomes unsafe. However, the process can be expensive and time consuming, requiring the installation of sensors and data acquisition electronics on the bridge. This paper investigates the use of an instrumented 2-axle vehicle fitted with accelerometers to monitor the dynamic behaviour of a bridge network in a simple and cost-effective manner. A simplified half car-beam interaction model is used to simulate the passage of a vehicle over a bridge. This investigation involves the frequency domain analysis of the axle accelerations as the vehicle crosses the bridge. The spectrum of the acceleration record contains noise, vehicle, bridge and road frequency components. Therefore, the bridge dynamic behaviour is monitored in simulations for both smooth and rough road surfaces. The vehicle mass and axle spacing are varied in simulations along with bridge structural damping in order to analyse the sensitivity of the vehicle accelerations to a change in bridge properties. These vehicle accelerations can be obtained for different periods of time and serve as a useful tool to monitor the variation of bridge frequency and damping with time.

Cybersecurity Test-Bed for IEC 61850 based Smart Substations

With the development and deployment of IEC 61850 based smart substations, cybersecurity vulnerabilities of supervisory control and data acquisition (SCADA) systems are increasingly emerging. In response to the emergence of cybersecurity vulnerabilities in smart substations, a test-bed is indispensable to enable cybersecurity experimentation. In this paper, a comprehensive and realistic cyber-physical test-bed has been built to investigate potential cybersecurity vulnerabilities and the impact of cyber-attacks on IEC 61850 based smart substations. This test-bed is close to a real production type environment, and has the ability to carry out end-to-end testing of cyber-attacks and physical consequences. A fuzz testing approach is proposed for detecting IEC 61850 based intelligent electronic devices (IEDs) and validated in the proposed test-bed.

Electron impact fragmentation of thymine:partial ionization cross sections for positive fragments

We have measured mass spectra for positive ions for low-energy electron impact on thymine using a reflectron time-of-flight mass spectrometer. Using computer controlled data acquisition, mass spectra have been acquired for electron impact energies up to 100 eV in steps of 0.5 eV. Ion yield curves for most of the fragment ions have been determined by fitting groups of adjacent peaks in the mass spectra with sequences of normalized Gaussians. The ion yield curves have been normalized by comparing the sum of the ion yields to the average of calculated total ionization cross sections. Appearance energies have been determined. The nearly equal appearance energies of 83 u and 55 u observed in the present work strongly indicate that near threshold the 55 u ion is formed directly by the breakage of two bonds in the ring, rather than from a successive loss of HNCO and CO from the parent ion. Likewise 54 u is not formed by CO loss from 82 u. The appearance energies are in a number of cases consistent with the loss of one or more hydrogen atoms from a heavier fragment, but 70 u is not formed by hydrogen loss from 71 u.