Computational challenges in deriving dairy cows' action patterns from accelerometer data

We describe an attempt to build a computational model for deriving dairy cows' action patterns automatically from accelerometer data

An example of a method to wirelessly transfer measurement data from cows in a free stall barn

Here we describe a wireless data measurement and transfer system that operates within a free stall barn. We report also the reliability of the system. This system was designed and built in Very Intelligent Cow Barn project in 2006-2007

Policy prescriptions to address energy and transport poverty in the United Kingdom

Tens of millions of households across Europe struggle to afford adequate electricity and heating services and reliable transportation, while recent high fuel prices could lead to an increase in excess winter deaths. Tackling energy and transport poverty is thus of paramount policy importance. Here we document the drivers and lived experiences of energy and transport poverty in the United Kingdom, based on public focus groups and expert interviews. We find a set of policies that resonate with both expert planners and members of the public, implying they have a level of political and social acceptability that other measures may be lacking, notably: mandatory landlord energy efficiency upgrades, increasing the extent of financial assistance to households, cheaper (or even free) bus and train fares and restarting and expanding bus services. We buttress these findings with further suggestions for energy and transport system redesign that better meets emerging principles of energy and social justice

Smart homes and their users:a systematic analysis and key challenges

Published research on smart homes and their users is growing exponentially, yet a clear understanding of who these users are and how they might use smart home technologies is missing from a field being overwhelmingly pushed by technology developers. Through a systematic analysis of peer-reviewed literature on smart homes and their users, this paper takes stock of the dominant research themes and the linkages and disconnects between them. Key findings within each of nine themes are analysed, grouped into three: (1) views of the smart home-functional, instrumental, socio-technical; (2) users and the use of the smart home-prospective users, interactions and decisions, using technologies in the home; and (3) challenges for realising the smart home-hardware and software, design, domestication. These themes are integrated into an organising framework for future research that identifies the presence or absence of cross-cutting relationships between different understandings of smart homes and their users. The usefulness of the organising framework is illustrated in relation to two major concerns-privacy and control-that have been narrowly interpreted to date, precluding deeper insights and potential solutions. Future research on smart homes and their users can benefit by exploring and developing cross-cutting relationships between the research themes identified

Sensor data classification for the indication of lameness in sheep

Lameness is a vital welfare issue in most sheep farming countries, including the UK. The pre-detection at the farm level could prevent the disease from becoming chronic. The development of wearable sensor technologies enables the idea of remotely monitoring the changes in animal movements which relate to lameness. In this study, 3D-acceleration, 3D-orientation, and 3D-linear acceleration sensor data were recorded at ten samples per second via the sensor attached to sheep neck collar. This research aimed to determine the best accuracy among various supervised machine learning techniques which can predict the early signs of lameness while the sheep are walking on a flat field. The most influencing predictors for lameness indication were also addressed here. The experimental results revealed that the Decision Tree classifier has the highest accuracy of 75.46%, and the orientation sensor data (angles) around the neck are the strongest predictors to differentiate among severely lame, mildly lame and sound classes of sheep

Thrombus Aspirates From Patients With Acute Ischemic Stroke Are Infiltrated by Viridans Streptococci

BACKGROUND: Acute ischemic stroke may be due to embolism from ruptured atherosclerotic carotid arteries. DNA of oral bacteria, mainly the viridans streptococci group, has been detected in thrombus aspirates of patients with ischemic stroke as well as in carotid endarterectomy samples. Because viridans streptococci are known to possess thrombogenic properties, we studied whether their presence in thrombus aspirates and in carotid artery specimens can be confirmed using bacterial immunohistochemistry. METHODS AND RESULTS: Thrombus aspirates from 61 patients with ischemic stroke (70.5% men; mean age, 66.8 years) treated with mechanical thrombectomy, as well as carotid endarterectomy samples from 20 symptomatic patients (65.0% men; mean age, 66.2 years) and 48 carotid artery samples from nonstroke autopsy cases (62.5% men; mean age, 66.4 years), were immunostained with an antibody cocktail against 3 species ( Streptococcus sanguinis, Streptococcus mitis, and Streptococcus gordonii) of viridans streptococci. Of the thrombus aspirates, 84.8% were immunopositive for viridans streptococci group bacteria, as were 80.0% of the carotid endarterectomy samples, whereas immunopositivity was observed in 31.3% of the carotid artery samples from nonstroke autopsies. Most streptococci were detected inside neutrophil granulocytes, but there were also remnants of bacterial biofilm as well as free bacterial infiltrates in some samples. CONCLUSIONS: Oral streptococci were found in aspirated thrombi of patients with acute ischemic stroke as well as in carotid artery samples. Our results suggest that viridans streptococci group bacteria may play a role in the pathophysiology of ischemic stroke.Peer reviewe

Classification of behaviour in housed dairy cows using an accelerometer-based activity monitoring system

Background Advances in bio-telemetry technology have made it possible to automatically monitor and classify behavioural activities in many animals, including domesticated species such as dairy cows. Automated behavioural classification has the potential to improve health and welfare monitoring processes as part of a Precision Livestock Farming approach. Recent studies have used accelerometers and pedometers to classify behavioural activities in dairy cows, but such approaches often cannot discriminate accurately between biologically important behaviours such as feeding, lying and standing or transition events between lying and standing. In this study we develop a decision-tree algorithm that uses tri-axial accelerometer data from a neck-mounted sensor to both classify biologically important behaviour in dairy cows and to detect transition events between lying and standing. Results Data were collected from six dairy cows that were monitored continuously for 36 h. Direct visual observations of each cow were used to validate the algorithm. Results show that the decision-tree algorithm is able to accurately classify three types of biologically relevant behaviours: lying (77.42 % sensitivity, 98.63 % precision), standing (88.00 % sensitivity, 55.00 % precision), and feeding (98.78 % sensitivity, 93.10 % precision). Transitions between standing and lying were also detected accurately with an average sensitivity of 96.45 % and an average precision of 87.50 %. The sensitivity and precision of the decision-tree algorithm matches the performance of more computationally intensive algorithms such as hidden Markov models and support vector machines. Conclusions Biologically important behavioural activities in housed dairy cows can be classified accurately using a simple decision-tree algorithm applied to data collected from a neck-mounted tri-axial accelerometer. The algorithm could form part of a real-time behavioural monitoring system in order to automatically detect dairy cow health and welfare status

Prying into the intimate secrets of animal lives; software beyond hardware for comprehensive annotation in ‘Daily Diary’ tags

Smart tags attached to freely-roaming animals recording multiple parameters at infra-second rates are becoming commonplace, and are transforming our understanding of the way wild animals operate. However, interpretation of such data is complex and currently limits the ability of biologists to realise the value of their recorded information. This work presents a single program, FRAMEWORK 4, that uses a particular sensor constellation described in the?Daily Diary? tag (recording tri-axial acceleration, tri-axial magnetic field intensity, pressure and e.g. temperature and light intensity) to determine the 4 key elements considered pivotal within the conception of the tag. These are; animal trajectory, behaviour, energy expenditure and quantification of the environment in which the animal operates. The program takes the original data recorded by the Daily Dairy and transforms it into dead-reckoned movements,template-matched behaviours, dynamic body acceleration-derived energetics and positionlinked environmental data before outputting it all into a single file. Biologists are thus left with a single data set where animal actions and environmental conditions can be linked across time and space.Fil: Walker, James S.. Swansea University. College Of Sciences; Reino UnidoFil: Jones, Mark W.. Swansea University. College Of Sciences; Reino UnidoFil: Laramee, Robert S.. Swansea University. College Of Sciences; Reino UnidoFil: Holton, Mark D.. Swansea University; Reino UnidoFil: Shepard, Emily L. C.. Swansea University. College Of Sciences; Reino UnidoFil: Williams, Hannah J.. Swansea University. College Of Sciences; Reino UnidoFil: Scantlebury, D. Michael. The Queens University Of Belfast; IrlandaFil: Marks, Nikki, J.. The Queens University Of Belfast; IrlandaFil: Magowan, Elizabeth A.. The Queens University Of Belfast; IrlandaFil: Maguire, Iain E.. The Queens University Of Belfast; IrlandaFil: Grundy, Ed. Swansea University. College Of Sciences; Reino UnidoFil: Di Virgilio, Agustina Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Patagonia Norte. Instituto de Investigación En Biodiversidad y Medioambiente; Argentina. Universidad Nacional del Comahue; ArgentinaFil: Wilson, Rory P.. Swansea University. College Of Sciences; Reino Unid

Decarbonisation and its discontents: a critical energy justice perspective on four low-carbon transitions

Low carbon transitions are often assumed as normative goods, because they supposedly reduce carbon emissions, yet without vigilance there is evidence that they can in fact create new injustices and vulnerabilities, while also failing to address pre-existing structural drivers of injustice in energy markets and the wider socio-economy. With this in mind, we examine four European low-carbon transitions from an unusual normative perspective: that of energy justice. Because a multitude of studies looks at the co-benefits renewable energy, low-carbon mobility, or climate change mitigation, we instead ask in this paper: what are the types of injustices associated with low-carbon transitions? Relatedly, in what ways do low-carbon transitions worsen social risks or vulnerabilities? Lastly, what policies might be deployed to make these transitions more just? We answer these questions by first elaborating an “energy justice” framework consisting of four distinct dimensions—distributive justice (costs and benefits), procedural justice (due process), cosmopolitan justice (global externalities), and recognition justice (vulnerable groups). We then examine four European low-carbon transitions—nuclear power in France, smart meters in Great Britain, electric vehicles in Norway, and solar energy in Germany—through this critical justice lens. In doing so, we draw from original data collected from 64 semi-structured interviews with expert partisans as well as five public focus groups and the monitoring of twelve internet forums. We document 120 distinct energy injustices across these four transitions, including 19 commonly recurring injustices. We aim to show how when low-carbon transitions unfold, deeper injustices related to equity, distribution, and fairness invariably arise