Using accelerometer, high sample rate GPS and magnetometer data to develop a cattle movement and behaviour model

The study described in this paper developed a model of animal movement, which explicitly recognised each individual as the central unit of measure. The model was developed by learning from a real dataset that measured and calculated, for individual cows in a herd, their linear and angular positions and directional and angular speeds. Two learning algorithms were implemented: a Hidden Markov model (HMM) and a long-term prediction algorithm. It is shown that a HMM can be used to describe the animal's movement and state transition behaviour within several “stay” areas where cows remained for long periods. Model parameters were estimated for hidden behaviour states such as relocating, foraging and bedding. For cows’ movement between the “stay” areas a long-term prediction algorithm was implemented. By combining these two algorithms it was possible to develop a successful model, which achieved similar results to the animal behaviour data collected. This modelling methodology could easily be applied to interactions of other animal specie

Growth of pasture plants (2012)

"Agriculture.""Dairy grazing.""Dairy grazing publication series: This publication is one in a series about operating and managing a pasture-based dairy. Although these publications often refer to conditions in Missouri, many of the principles and concepts described may apply to operations throughout the United States.""Revised by Robert L. Kallenbach, Forages State Specialist, Division of Plant Sciences.""This publication replaces Chapter 3, Growth of Forage Plants, in MU Extension publication M168, Dairy Grazing Manual. Original author: Greg J. Bishop-Hurley, University of Missouri."New 2/12/Web

Development of anti-infectives using phage display: biological agents against bacteria, viruses, and parasites

The vast majority of anti-infective therapeutics on the market or in development are small molecules; however, there is now a nascent pipeline of biological agents in development. Until recently, phage display technologies were used mainly to produce monoclonal antibodies (MAbs) targeted against cancer or inflammatory disease targets. Patent disputes impeded broad use of these methods and contributed to the dearth of candidates in the clinic during the 1990s. Today, however, phage display is recognized as a powerful tool for selecting novel peptides and antibodies that can bind to a wide range of antigens, ranging from whole cells to proteins and lipid targets. In this review, we highlight research that exploits phage display technology as a means of discovering novel therapeutics against infectious diseases, with a focus on antimicrobial peptides and antibodies in clinical or preclinical development. We discuss the different strategies and methods used to derive, select, and develop anti-infectives from phage display libraries and then highlight case studies of drug candidates in the process of development and commercialization. Advances in screening, manufacturing, and humanization technologies now mean that phage display can make a significant contribution in the fight against clinically important pathogens

Mapping Through Memory: The location and nature of Mass paths in Ireland.

Methodologies that capture the ways in which individuals and communities value places are becoming increasingly attractive to policymakers and authors highlight the need for additional tools and archival material concerning how people engage with landscapes on an everyday basis. This paper addresses that need and argues that oral history and personal memory can be used as effective tools for geographical mapping and analysis, both physical and virtual. Religion involves the collective identity of a people and has strong affinities with the traditions and knowledge handed down from generation to generation. Such traditions and knowledge are often handed down orally and offer potential for geographical enquiry. Oral history can provide unique insights into the history of place, often providing narratives about the recollection of self, relationships with others and place, insights rarely provided in such depth by other methods. Place memory has become an important theme in recent geographical research and landscape can be mapped through memories and stories to create a virtual cartography of place. Using a case study approach in Lackagh, County Galway, the authors use an innovative assemblage of methods to produce one of the most thorough syntheses of information available in respect to the location, history and heritage of Mass paths in Ireland at a parish level

The cost of breast cancer recurrences.

Information about the costs of recurrent breast cancer is potentially important for targeting cost containment strategies and analysing the cost-effectiveness of breast cancer control programmes. We estimated these costs by abstracting health service and consumable usage data from the medical histories of 128 patients, and valuing each of the resources used. Resource usage and costs were summarised by regarding the recurrence as a series of episodes which were categorised into five anatomical site-based groups according to the following hierarchy: visceral, central nervous system (CNS), bone, local and other. Hospital visits and investigations comprised 78% of total costs for all episodes combined, and there were significant differences between the site-based groups in the frequency of hospital visits and most investigations. Total costs were most accurately described by separate linear regression models for each group, with the natural logarithm of the cost of the episode as the dependent variable, and predictor variables including the duration of the episode, duration squared, duration cubed and a variable indicating whether the episode was fatal. Visceral and CNS episodes were associated with higher costs than the other groups and were more likely to be shorter and fatal. A fatal recurrence of duration 15.7 months (the median for our sample) was predicted to cost $10,575 (Aus + 1988; or 4,877 pounds). Reduction of the substantial costs of recurrent breast cancer is likely to be a sizable economic benefit of adjuvant systemic therapy and mammographic screening. We did not identify any major opportunities for cost containment during the management of recurrences

Opportunities for Improving Livestock Production with e-Management Systems

There is increased interest in hardware and software that can support e-Management for grassland-based livestock industries. Managers of grazing livestock were early adopters of radio frequency identification (RFID) technologies automatically monitoring individual animal performance. Recent developments of remote sensing, automated individual recording and management, location based systems, improved data transfer and technologies that can be used in more extensive grazing systems are providing new opportunities for the development of e-Management systems. There is a need for better data integration and systems that can provide the best available information to enable better decision-making. For greater industry adoption of more integrated e-Management systems, there needs to be a clear economic value. With increased on farm monitoring and the expansion of digital data sources, grazing livestock production systems have the opportunity to expand production efficiency through the implementation of e-Management

Economics of pasture-based dairies (2012)

"Agriculture.""Dairy grazing.""Dairy grazing publication series: This publication is one in a series about operating and managing a pasture-based dairy. Although these publications often refer to conditions in Missouri, many of the principles and concepts described may apply to operations throughout the United States. A list of the publications in this series is available online at http://extension.missouri.edu/m168.""Revised from M168, Dairy Grazing Manual, by Joe Horner, Dairy Economist, Commercial Agriculture Program, Ryan Milhollin, Project Manager, Commercial Agriculture Program, Wayne Prewitt, West Central Region Agriculture Business Specialist.""This publication replaces Chapter 14, Economics of a Pasture-Based Dairy, in MU Extension publication M168, Dairy Grazing Manual. Original authors: Stacey A. Hamilton, Greg J. Bishop-Hurley and Ron Young, University of Missouri."New 2/12/Web

A noise robust automatic radiolocation animal tracking system

Agriculture is becoming increasingly reliant upon accurate data from sensor arrays, with localization an emerging application in the livestock industry. Ground-based time difference of arrival (TDoA) radio location methods have the advantage of being lightweight and exhibit higher energy efficiency than methods reliant upon Global Navigation Satellite Systems (GNSS). Such methods can employ small primary battery cells, rather than rechargeable cells, and still deliver a multi-year deployment. In this paper, we present a novel deep learning algorithm adapted from a one-dimensional U-Net implementing a convolutional neural network (CNN) model, originally developed for the task of semantic segmentation. The presented model (ResUnet-1d) both converts TDoA sequences directly to positions and reduces positional errors introduced by sources such as multipathing. We have evaluated the model using simulated animal movements in the form of TDoA position sequences in combination with real-world distributions of TDoA error. These animal tracks were simulated at various step intervals to mimic potential TDoA transmission intervals. We compare ResUnet-1d to a Kalman filter to evaluate the performance of our algorithm to a more traditional noise reduction approach. On average, for simulated tracks having added noise with a standard deviation of 50 m, the described approach was able to reduce localization error by between 66.3% and 73.6%. The Kalman filter only achieved a reduction of between 8.0% and 22.5%. For a scenario with larger added noise having a standard deviation of 100 m, the described approach was able to reduce average localization error by between 76.2% and 81.9%. The Kalman filter only achieved a reduction of between 31.0% and 39.1%. Results indicate that this novel 1D CNN U-Net like encoder/decoder for TDoA location error correction outperforms the Kalman filter. It is able to reduce average localization errors to between 16 and 34 m across all simulated experimental treatments while the uncorrected average TDoA error ranged from 55 to 188 m

Monitoring Animal Behaviour and Environmental Interactions Using Wireless Sensor Networks, GPS Collars and Satellite Remote Sensing

Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle

Energy-efficient Localization for Virtual Fencing

International audienceThis poster addresses the tradeoff between energy consumption and localization performance in a mobile sensor network application. It focuses on combining GPS location with more energy-efficient location sensors to bound position estimate uncertainty in order to prolong node lifetime. The focus is on an outdoor location monitoring application for tracking cattle using smart collars that contain wireless sensor nodes and GPS modules. We use empirically-derived models to explore duty cycling strategies for maintaining position uncertainty within specified bounds. Specifically we explore the benefits of using short-range radio contact logging alongside GPS as an energy-inexpensive means of lowering uncertainty while the GPS is off. Results show that GPS combined with radio-contact logging is effective in extending node lifetime while meeting application-specific positioning criteria