New frontiers in biologging science

The term ‘biologging’ refers to the use of miniaturized animal-attached tags for logging and/or relaying of data about an animal's movements, behaviour, physiology and/or environment. Biologging technology substantially extends our abilities to observe, and take measurements from, free-ranging, undisturbed subjects, providing much scope for advancing both basic and applied biological research. Here, we review highlights from the third international conference on biologging science, which was held in California, USA, from 1 to 5 September 2008. Over the last few years, considerable progress has been made with a range of recording technologies as well as with the management, visualization, integration and analysis of increasingly large and complex biologging datasets. Researchers use these techniques to study animal biology with an unprecedented level of detail and across the full range of ecological scales—from the split-second decision making of individuals to the long-term dynamics of populations, and even entire communities. We conclude our report by suggesting some directions for future research.

The accuracy of Fastloc-GPS locations and implications for animal tracking

Over recent years, a major breakthrough in marine animal tracking has occurred with the advent of Fastloc-GPS that provides highly accurate location data even for animals that only surface briefly such as sea turtles, marine mammals and penguins. We assessed the accuracy of Fastloc-GPS locations using fixed trials of tags in which >45 000 locations were obtained. Procedures for determining the speed of travel and heading were developed by simulating tracks and then adding Fastloc-GPS location errors. The levels of detail achievable for speed and heading estimates were illustrated by using empirical Fastloc-GPS data for a green turtle (Chelonia mydas, Linnaeus, 1758) travelling over 3000 km across the Indian Ocean. The accuracy of Fastloc-GPS locations varied as a function of the number of GPS satellites used in the location calculation. For example, when Fastloc-GPS locations were calculated using 4 GPS satellites, 50% of locations were within 36 m and 95% within 724 m of the true position. These values improved to 18 and 70 m, respectively, when 6 satellites were used. Simulations indicated that for animals travelling around 2·5 km h-1 (e.g. turtles, penguins and seals) and depending on the number of satellites used in the location calculation, robust speed and heading estimates would usually be obtained for locations only 1-6 h apart. Fastloc-GPS accuracy is several orders of magnitude better that conventional Argos tracking or light-based geolocation and consequently will allow new insights into small-scale movement patterns of marine animals.

Movement patterns of green turtles in Brazilian coastal waters described by satellite tracking and flipper tagging

The movements of 8 green turtles Chelonia mydas in Brazilian coastal waters were tracked using transmitters linked to the Argos system for periods of between 1 and 197 d. These were the first tracking data gathered on juveniles of this species in this important foraging ground. Information was integrated with that collected over a decade using traditional flipper-tagging methods at the same site. Both satellite telemetry and flipper tagging suggested that turtles undertook 1 of 3 general patterns of behaviour: pronounced long range movements (>100 km), moderate range movements (<100 km) or extended residence very close to the capture/release site. There seemed to be a general tendency for the turtles recaptured/tracked further afield to have been among the larger turtles captured. Satellite tracking of 5 turtles which moved from the release site showed that they moved through coastal waters; a factor which is likely to predispose migrating turtles to incidental capture as a result of the prevailing fishing methods in the region. The movements of the 3 turtles who travelled less than 100 km from the release site challenge previous ideas relating to home range in green turtles feeding in sea grass pastures. We hypothesise that there may be a fundamental difference in the pattern of habitat utilisation by larger green turtles depending on whether they are feeding on seagrass or macroalgae. Extended tracking of 2 small turtles which stayed near the release point showed that small juvenile turtles, whilst in residence in a particular feeding ground, can also exhibit high levels of site-fidelity with home ranges of the order of several square kilometers.

Tracking and tracing applications of 3G for SMEs

With dynamic growth and acceptance of mobile devices, many innovative business applications are beginning to emerge. Tracking and tracing seems to be one of the popular applications which many organisations have initiated, often facilitated by location based services provided by mobile network operators. However, there are many issues associated with the provisioning of this application with current technologies and business models. Small and Medium-size Enterprises (SMEs) that make up a significant segment of businesses worldwide do not yet seem able to benefit widely from these services. In this chapter, we initially review current technologies/ applications and the issues associated with them, drawing from research and the experiences of a long term ongoing action research project with SMEs in the trade sector. Subsequently, we explore the opportunities offered by 3G services/business applications to SMEs, and provide a broad critical outlook on future opportunities for SMEs to benefit from 3G services.

Robust extended kalman filter applied to location tracking and trajectory prediction for PCS networks

Provisioning of real-time multimedia sessions over wireless cellular network poses unique challenges due to frequent handoff and rerouting of a connection. For this reason, the wireless networks with cellular architecture require efficient user mobility estimation and prediction. This paper proposes using robust extended Kalman filter (REKF) as a location heading altitude estimator of mobile user for next cell prediction in order to improve the connection reliability and bandwidth efficiency of the underlying system. Through analysis we demonstrate that our algorithm reduces the system complexity (compared to existing approach using pattern matching and Kalman filter) as it requires only two base station measurements or only the measurement from the closest base station. Further, the technique is robust against system uncertainties due to inherent deterministic nature in the mobility model and more effective in comparison with the standard Kalman filter.

On the geometry of localization, tracking and navigation

The thesis characterizes the geometry of certain localization, tracking and navigation problems. For instance, the potential localization performance of certain multi-sensor systems is measurably linked to the relative sensor-target geometry. Additionally, several optimal and robust algorithms for localization and tracking are designed which exploit the underlying geometry of the problem considered.

Companion animal visitation and its effectiveness with stroke patients

The study employed a randomised controlled trial design to determine whether a companion animal intervention had any effect on wellbeing and quality of life in patients who were admitted to hospital after suffering a stroke. The study found significant benefits for their wellbeing and improvements in quality of life.

Variation of mohair staple length across Angora goat fleeces : implications for animal selection and fleece evaluation

The present study aimed to determine how the average mohair staple length (SL) differences between nine sampling sites vary between sex and flock, to identify differences in SL variability between sampling sites as a result of between-animal and between-sire variability and to determine SL correlations between sampling sites in between-animal and between-sire variability. Australian Angora goats (n=301) from two farms in southern Australia were sampled at 12 and 18 months of age at nine sites (mid side, belly, brisket, hind flank, hip, hock, mid back, neck and shoulder). Staples were taken prior to shearing at skin level and stretched SL determined. For each shearing, differences in SL between sampling sites, how these differences were affected by farm, sex and sire, and the covariance between sites for sire and individual animal effects were investigated by restricted maximum likelihood (REML) analyses. The median mid-side SL at 12 and 18 months of age was 110 and 130 mm, respectively, but the actual range in mid-side SL was 65–165 mm. There was an anterior–posterior decline in SL with the hock being particularly short. There was no evidence that the between-site correlation of the sire effects differed from 1, indicating that genetic selection for SL at one site will be reflected in SL over the whole fleece. However, low heritabilities of SL at the hock, belly and brisket or at any site at 12 months of age were obtained. There was more variability between sites than between sires, but the between-animal variation was greater. The hip and mid-back sites can be recommended for within-flock (culling) and genetic selection for SL due to their low sampling variability, moderate heritability and ease of location.

Vision-based target tracking and surveillance with robust set-valued state estimation

Tracking a target from a video stream (or a sequence of image frames) involves nonlinear measurements in Cartesian coordinates. However, the target dynamics, modeled in Cartesian coordinates, result in a linear system. We present a robust linear filter based on an analytical nonlinear to linear measurement conversion algorithm. Using ideas from robust control theory, a rigorous theoretical analysis is given which guarantees that the state estimation error for the filter is bounded, i.e., a measure against filter divergence is obtained. In fact, an ellipsoidal set-valued estimate is obtained which is guaranteed to contain the true target location with an arbitrarily high probability. The algorithm is particularly suited to visual surveillance and tracking applications involving targets moving on a plane.

A role for glutathione in the pathophysiology of bipolar disorder and schizophrenia? Animal models and relevance to clinical practice.

The tripeptide, glutathione (glutamylcysteinylglycine) is the primary endogenous free radical scavenger in the human body. When glutathione (GSH) levels are reduced there is an increased potential for cellular oxidative stress, characterised by an increase and accruement of reactive oxygen species (ROS). Oxidative stress has been implicated in the pathology of schizophrenia and bipolar disorder. This could partly be caused by alterations in dopaminergic and glutamatergic activity that are implicated in these illnesses. Glutamate and dopamine are highly redox reactive molecules and produce ROS during normal neurotransmission. Alterations to these neurotransmitter pathways may therefore increase the oxidative burden in the brain. Furthermore, mitochondrial dysfunction, as a source of oxidative stress, has been documented in both schizophrenia and bipolar disorder. The combination of altered neurotransmission and this mitochondrial dysfunction leading to oxidative damage may ultimately contribute to illness symptoms. Animal models have been established to investigate the involvement of glutathione depletion in aspects of schizophrenia and bipolar disorder to further characterise the role of oxidative stress in psychopathology. Stemming from preclinical evidence, clinical studies have recently shown antioxidant precursor treatment to be effective in schizophrenia and bipolar disorder, providing a novel clinical angle to augment often suboptimal conventional treatments.

Tracking and surveillance in wide-area spatial environments using the abstract hidden markov model.

In this paper, we consider the problem of tracking an object and predicting the object's future trajectory in a wide-area environment, with complex spatial layout and the use of multiple sensors/cameras. To solve this problem, there is a need for representing the dynamic and noisy data in the tracking tasks, and dealing with them at different levels of detail. We employ the Abstract Hidden Markov Models (AHMM), an extension of the well-known Hidden Markov Model (HMM) and a special type of Dynamic Probabilistic Network (DPN), as our underlying representation framework. The AHMM allows us to explicitly encode the hierarchy of connected spatial locations, making it scalable to the size of the environment being modeled. We describe an application for tracking human movement in an office-like spatial layout where the AHMM is used to track and predict the evolution of object trajectories at different levels of detail.

Model-based combined tracking and resolution enhancement

Wide area surveillance requires high-resolution images of the object of interest derived possibly from only low-resolution video of the whole scene. We propose a combined tracking and resolution enhancement approach that increases the resolution of the object of interest during tracking. The key idea is the use of an object-specific 3D mesh model with which we are able to track non-planar objects across a large number of frames. This model is subdivided such that every triangle is smaller than a pixel when projected into the image to facilitate super-resolution on the model rather than on the image. We apply our approach to faces and show that it outperforms interpolation methods by achieving resolution enhancement, while being less blurred.