Percentages of records in the testing dataset correctly and incorrectly assigned to groups <i>G</i>₁, <i>G</i>₂ and <i>G</i>₃ by the pairwise SVM- classifier.

<p>Percentages of records in the testing dataset correctly and incorrectly assigned to groups <i>G</i>₁, <i>G</i>₂ and <i>G</i>₃ by the pairwise SVM- classifier.</p

Percentage of time each day involving baseline, animal motion or human-related motion.

<p>Mean values over the first 11 days are shown as red lines for baseline (<i>m</i>₁) and animal motion (<i>m</i>₂).</p

Minimum (Min.), first quartile (<i>Q</i>₁), median (Med.), third quartile (<i>Q</i>₃) and maximum (Max.) centroid values for the <i>k</i> = 32 clusters computed through <i>k</i>-means algorithm describing motion over 15-second intervals (90 frames) during the pre-infection period.

<p>Percentages refer to the total number of records in each cluster.</p

Domain Γ_g in numerical experiments, extending from latitude 34°N to 44°N and from longitude 10°W to 4.25°E.

<p>Black lines demarcate country boundaries and black dots locate the fixed 2,500 grid points.</p

Averaged <i>Culicoides</i> trapped per capture (blue dots) and polynomial approximation curve (red line), <i>δ</i>(.).

<p>Averaged <i>Culicoides</i> trapped per capture (blue dots) and polynomial approximation curve (red line), <i>δ</i>(.).</p

Timeline showing the four analytical phases of the experiment.

<p>The experiment began on day 1 (kick off), and animals were inoculated with ASF virus on day 11. On day 15, six of eight animals tested positive for the virus by quantitative PCR. On day 18, clinical signs of ASF became evident in five of eight animals. The experiment ended on day 23.</p

Simulated spatial distribution of the number density of <i>Culicoides</i> deposited on the target territory throughout 2004, when the midge source was both Morocco and Algeria (left), Morocco alone (center) or Algeria alone (right).

<p>Number densities were plotted in logarithmic scale, <i>log</i>(<i>C</i> + 1) (log1). Blue dots represent the source of <i>Culicoides</i>, Γ_<i>s</i>.</p

Effect of temperature on air density.

<p>Effect of temperature on air density.</p

Motion-based video monitoring for early detection of livestock diseases: The case of African swine fever

<div><p>Early detection of infectious diseases can substantially reduce the health and economic impacts on livestock production. Here we describe a system for monitoring animal activity based on video and data processing techniques, in order to detect slowdown and weakening due to infection with African swine fever (ASF), one of the most significant threats to the pig industry. The system classifies and quantifies motion-based animal behaviour and daily activity in video sequences, allowing automated and non-intrusive surveillance in real-time. The aim of this system is to evaluate significant changes in animals’ motion after being experimentally infected with ASF virus. Indeed, pig mobility declined progressively and fell significantly below pre-infection levels starting at four days after infection at a confidence level of 95%. Furthermore, daily motion decreased in infected animals by approximately 10% before the detection of the disease by clinical signs. These results show the promise of video processing techniques for real-time early detection of livestock infectious diseases.</p></div

<i>Culicoides</i> lifespan used in the present model according to temperature variations based on field data (blue dots) and cubic Hermite approximation (red line), 1/<i>μ</i>(.).

<p><i>Culicoides</i> lifespan used in the present model according to temperature variations based on field data (blue dots) and cubic Hermite approximation (red line), 1/<i>μ</i>(.).</p