Likelihood-based approach to discriminate mixtures of network models that vary in time.

Discriminating between competing explanatory models as to which is more likely responsible for the growth of a network is a problem of fundamental importance for network science. The rules governing this growth are attributed to mechanisms such as preferential attachment and triangle closure, with a wealth of explanatory models based on these. These models are deliberately simple, commonly with the network growing according to a constant mechanism for its lifetime, to allow for analytical results. We use a likelihood-based framework on artificial data where the network model changes at a known point in time and demonstrate that we can recover the change point from analysis of the network. We then use real datasets and demonstrate how our framework can show the changing importance of network growth mechanisms over time.

The choice behaviour of pigs in a Y maze: effects of deprivation of feed, social contact and bedding.

We examined effects of deprivation of feed, social contact and bedding on the choice behaviour in Y maze tests. Eighty pigs were used to study two main effects: feed (estimated voluntary feed intake (VFI) vs. 70% VFI) and bedding (presence vs. absence), experiment 1; social contact (full vs. restricted) and bedding (presence vs. absence), experiment 2; and feed (as in experiment 1) and social contact (as in experiment 2), experiment 3. Overall pigs consistently chose feed and social contact over bedding. While social contact was more preferred than feed in experiment 3, there was substantial variation between pigs in their choice behaviour. The overall choice behaviour in experiment 3 contradicts previous research, but differences such as the preference methodology as well as the level of deprivation, level of reward and cost involved in accessing reward, may be responsible. Average daily weight gain (ADG) was affected in experiment 3: both feed and social restriction reduced ADG. While the feed effect is expected, one interpretation of the social effect is that social deprivation, through stress, may have reduced ADG. These results provide limited support for the notion that deprivation of a highly preferred resource may disrupt biological function.