Welfare epidemiology as a tool to assess the welfare impact of inherited defects on the pedigree dog population

The effect that breed standards and selective breeding practices have on the welfare of pedigree dogs has recently come under scrutiny from both the general public and scientific community. Recent research has suggested that breeding for particular aesthetic traits, such as tightly curled tails, highly domed skulls and short muzzles predisposes dogs with these traits to certain inherited defects, such as spina bifida, syringomyelia and brachycephalic airway obstruction syndrome, respectively. Further to this, there is a very large number of inherited diseases that are not related to breed standards, which are thought to be prevalent, partly as a consequence of inbreeding and restricted breeding pools. Inherited diseases, whether linked to conformation or not, have varying impact on the individuals affected by them, and affect varying proportions of the pedigree dog population. Some diseases affect few breeds but are highly prevalent in predisposed breeds. Other diseases affect many breeds, but have low prevalence within each breed. In this paper, we discuss the use of risk analysis and severity diagrams as means of mapping the overall problem of inherited disorders in pedigree dogs and, more specifically, the welfare impact of specific diseases in particular breeds.

Measuring health-related quality of life after stroke: A brief tool.

Routine assessment of health-related quality of life (HRQoL) can be time consuming and burdensome for a person with stroke. Therefore the aim of this study was to develop and test a brief instrument for assessing HRQoL among people with stroke. The Quality of Life after Stroke Scale (QLASS) was constructed from items within the Quality of Life Index-Stroke Version and the Chronic Respiratory Disease Questionnaire. It was administered to 92 people with stroke at three points in time: immediately after discharge from hospital, 6 months and 12 months later. Results suggest that the QLASS has 19 items which represent three factors: emotional functioning, mastery and fatigue which correlate with valid measures of health status and activities of daily living. The QLASS is proposed as a brief, valid HRQoL tool for use among people with stroke.

Dogs as a diagnostic tool for ill-health in humans

Researchers have long reported that dogs and cats improve the physical and psychological health of their human caregivers, and while it is still inconclusive, a substantial amount of research now lends support for the commonly held view that "pets are good for us." Recently, studies have directed attention toward exploring the use of animals, most notably dogs, in the detection of disease and other types of health problems in people. This article reviews the evidence for dogs' ability to detect ill health in humans, focusing specifically on the detection of cancer, epileptic seizures, and hypoglycemia. The author describes the research carried out in this area and evaluates it in an effort to determine whether dogs have a role to play in modern health care as an "alert" tool or screening system for ill health. Where necessary, the author has highlighted weaknesses in the work and proposed directions for future studies.

Assessing quality of life in cardiac rehabilitation: Choosing an appropriate tool

Quality of life is an important outcome for people undergoing cardiac rehabilitation. This paper discusses the difficulties with defining the concept of quality of life and how it might be distinct from the concept of health-related quality of life. Based on a review of the literature, a description is provided of health-related quality of life questionnaires that have been used in cardiac rehabilitation populations. Some criteria for choosing between these questionnaires are then discussed and, finally, a brief discussion is presented of the concept of response shift and how this might influence the assessment of health-related quality of life in a cardiac rehabilitation setting.

Analysis of information leakage from encrypted Skype conversations

Voice over IP (VoIP) has experienced a tremendous growth over the last few years and is now widely used among the population and for business purposes. The security of such VoIP systems is often assumed, creating a false sense of privacy. This paper investigates in detail the leakage of information from Skype, a widely used and protected VoIP application. Experiments have shown that isolated phonemes can be classified and given sentences identified. By using the dynamic time warping (DTW) algorithm, frequently used in speech processing, an accuracy of 60% can be reached. The results can be further improved by choosing specific training data and reach an accuracy of 83% under specific conditions. The initial results being speaker dependent, an approach involving the Kalman filter is proposed to extract the kernel of all training signals.