Smartphone and GPS technology for freeroaming dog population surveillance -a methodological study (Studio metodologico sull’applicazione di smartphone e tecnologia GPS alla sorveglianza delle popolazioni di cani vaganti)

Free-roaming dogs (FRD) represent a potential threat to the quality of life in cities from an ecological, social and public health point of view. One of the most urgent concerns is the role of uncontrolled dogs as reservoirs of infectious diseases transmittable to humans and, above all, rabies. An estimate of the FRD population size and characteristics in a given area is the first step for any relevant intervention programme. Direct count methods are still prominent because of their non-invasive approach, information technologies can support such methods facilitating data collection and allowing for a more efficient data handling. This paper presents a new framework for data collection using a topological algorithm implemented as ArcScript in ESRI® ArcGIS software, which allows for a random selection of the sampling areas. It also supplies a mobile phone application for Android® operating system devices which integrates Global Positioning System (GPS) and Google Maps™. The potential of such a framework was tested in 2 Italian regions. Coupling technological and innovative solutions associated with common counting methods facilitate data collection and transcription. It also paves the way to future applications, which could support dog population management systems.

Changes in the attitudes of GPs to health screening of patients with learning disabilities

GP's appear reluctant to undertake health screening for people with learning disabilities. This article describes a specialist health screening service delivered mainly by community learning disability nurses to nearly 600 children and adults. Prior to the service being established, 141 GPs within a defined area were surveyed and 51% responded. Although a majority thought the service would be helpful, three-quarters felt it was better provided within the context of specialist services. After screening, 54% of the sample (318 persons) were referred to their GP for further assessment and treatment, nearly all for physoical health needs. A second study investigated the attitudes of 91 GPs who had patients refrrered. Those (45) who reported dealing with a referral were more favourably disposed to undertaking health screening within their practice, whereas those (23) who had been uninvolved continued to opt for specialist provision. Options for encouraging more GPs' to offer preventive health care to theisclient group are discussed, including medical training, extra consulting time and linking community learning disbaility nurses with GP practices.

Post-release GPS tracking of hand-reared Irish hare Lepus timidus hibernicus leverets, Slemish, Co. Antrim, Northern Ireland.

Animal rescue centres release large numbers of captive-bred, rehabilitated or translocated animals into the wild annually but little is known about their post-release survival and behaviour. We developed a novel and innovative coupling of traditional radio-tags with new GPS loggers to track hand-reared Irish hare Lepus timidus hibernicus leverets after release into the wild. Cyanoacrylate SuperGlue® proved a poor fixative with two out of three leverets managing to detach their tags within 24 hours. Nevertheless, a total of 2,505 GPS locations were recorded every 60 seconds for one leveret over three nights (approx. 835 per night). The leveret dispersed

The bird GPS - long-range navigation in migrants

Nowadays few people consider finding their way in unfamiliar areas a problem as a GPS (Global Positioning System) combined with some simple map software can easily tell you how to get from A to B. Although this opportunity has only become available during the last decade, recent experiments show that long-distance migrating animals had already solved this problem. Even after displacement over thousands of kilometres to previously unknown areas, experienced but not first time migrant birds quickly adjust their course toward their destination, proving the existence of an experience-based GPS in these birds. Determining latitude is a relatively simple task, even for humans, whereas longitude poses much larger problems. Birds and other animals however have found a way to achieve this, although we do not yet know how. Possible ways of determining longitude includes using celestial cues in combination with an internal clock, geomagnetic cues such as magnetic intensity or perhaps even olfactory cues. Presently, there is not enough evidence to rule out any of these, and years of studying birds in a laboratory setting have yielded partly contradictory results. We suggest that a concerted effort, where the study of animals in a natural setting goes hand-in-hand with lab-based study, may be necessary to fully understand the mechanism underlying the long-distance navigation system of birds. As such, researchers must remain receptive to alternative interpretations and bear in mind that animal navigation may not necessarily be similar to the human system, and that we know from many years of investigation of long-distance navigation in birds that at least some birds do have a GPS-but we are uncertain how it works.

Might how you look influence how well you are looked after?:A study which demonstrates that GPs perceive socio-economic gradients in attractiveness

To test the hypothesis that more disadvantaged patients are perceived by general practitioners (GPs) as being less attractive than their more affluent peers.

Analysis of Bayesian classification-based approaches for Android malware detection

Mobile malware has been growing in scale and complexity spurred by the unabated uptake of smartphones worldwide. Android is fast becoming the most popular mobile platform resulting in sharp increase in malware targeting the platform. Additionally, Android malware is evolving rapidly to evade detection by traditional signature-based scanning. Despite current detection measures in place, timely discovery of new malware is still a critical issue. This calls for novel approaches to mitigate the growing threat of zero-day Android malware. Hence, the authors develop and analyse proactive machine-learning approaches based on Bayesian classification aimed at uncovering unknown Android malware via static analysis. The study, which is based on a large malware sample set of majority of the existing families, demonstrates detection capabilities with high accuracy. Empirical results and comparative analysis are presented offering useful insight towards development of effective static-analytic Bayesian classification-based solutions for detecting unknown Android malware.