Correlation between steps and percentage of time involved in active behaviour in a given hour.

<p>Scatter plot illustrating the association between the number of steps taken and the proportion of time spent in active behaviour for 40 cattle between December 2006 and January 2007 in the Kasero and Makale veterinary camps of Petauke District in the Eastern Province of Zambia. [A] Scatter plot and fitted linear trend (Pearson’s correlation coefficient = 0.994) based on all 24 hours (<i>n</i> = 12,745). [B] Scatter plots for only those hours where cattle spent 50% or more time in standing (shown in blue circles) or lying (red circles) behaviour. (Note that the scales on the x and y-axis in [B] are halved compared to those in [A] because the maximum proportion of time that can be spent in active behaviour is 50%.)</p

Intraclass correlation coefficients within animal on the first four PCs.

<p>Intraclass correlation coefficients for PC scores over the studied period within individual animal were calculated separately in each of two vet camps. Moderate to high ICC values for the first four PCs indicate that there would be little benefit in employing daily behaviour variables, at the cost of increasing the total variance in the data. All ICC values were significantly different from 0 (<i>p</i> < 0.001).</p><p>Intraclass correlation coefficients within animal on the first four PCs.</p

Loading value for each behaviour across 24 hours.

<p>The loading of each cattle behaviour variable, active (green hollow circles), lying (blue diamonds), and standing (red crosses) across 0:00 to 23:00 hours, on [A] PC1 and [B] PC2. These figures indicate that much of the heterogeneity in cattle behaviour during the night and day time is accounted for by PC1 and PC2, respectively.</p

Scatter plot illustrating the location of each animal in PC1 and PC2 space.

<p>Annotations of plots represent each of 40 individual cattle from the Kasero (blue) and Makale (orange) veterinary camps of Petauke District in the Eastern Province of Zambia. PC1 and PC2 accounted for 51.0% and 14.1% of the total variance in the data.</p

Proportion of unaccounted variance against the number of PC included.

<p>Scree plot showing the proportion of variance that is unaccounted for against the number of Principal Components included. The first four components derived from Principal Component Analysis account for over 80% of the variance in the original data.</p

Scatter plot of animals in PC1 and PC3 space.

<p>Each point located in PC1 and PC3 space, represents individual cattle from the Kasero (blue) and Makale (orange) veterinary camps of Petauke District in the Eastern Province of Zambia. The dotted line represents a classification line predicted from a logistic regression model that best separates the animals from the two vet camps. PC1 and PC3 accounted for 51.0% and 9.0% of the total variance in the data.</p

Prevalence of tested resistance genes among isolated Enterococci.

<p>Prevalence of antimicrobial resistance genes tested among <i>E</i>. <i>faecalis</i> and <i>E</i>. <i>faecium</i> isolated from retail poultry products collected in 5 major Japanese cities between July and August 2012.</p><p>Prevalence of tested resistance genes among isolated Enterococci.</p

Final globally optimal additive Bayesian network model after adjustment for over-fitting.

<p>Final additive Bayesian network model after removing arcs that appeared in <50% of bootstrappings for the interrelationships between selected antimicrobial resistance genes and phenotypes. Solid lines and dashed lines represent positive and negative associations between variables, respectively. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121189#pone.0121189.g002" target="_blank">Fig. 2</a> lists the variable names.</p

Map of Japan showing the study area.

<p>A choropleth map of 46 Japanese administrative areas (prefectures) showing the origin of the purchased domestic chicken products and the quantity of products supplied from each prefecture. The origin of 82 domestic products (52.6%) was unavailable and is not shown. The superimposed points show the locations of the 5 Japanese cities where chicken products were purchased between July and August 2012.</p

Posterior marginal log odds ratios for parameters.

<p>Posterior estimates for remaining arcs obtained from the final ABN model after bootstrapping. The median and 95% credibility intervals for each parameter estimate are shown.</p><p>^aMIC for dihydrostreptomycin: ≥128 μg/mL and ≤512 μg/mL.</p><p>^bMIC for dihydrostreptomycin: >512 μg/mL.</p><p>^cMIC for oxytetracycline: ≥16 μg/mL and ≤64 μg/mL.</p><p>^dMIC for oxytetracycline: >64 μg/mL.</p><p>Posterior marginal log odds ratios for parameters.</p