On the application of a nature-inspired stochastic evolutionary algorithm to constrained multi-objective beer fermentation optimisation

Fermentation is an essential step in beer brewing, often acting as the system bottleneck due to the time-consuming nature of the process stage (duration >120 h), where a trade-off exists between attainable ethanol concentration and required batch time. To explore this trade-off we employ a multi-objective plant propagation algorithm (the Strawberry algorithm), for identifying temperature manipulations for improved fermentation performance. The methodology employed successfully produces families of favourable temperature profiles which exist along the Pareto front. A subset of these output profiles can simultaneously reduce batch time and increase product ethanol concentration while satisfying constraints on by-products produced in the fermenters, representing significant improvements in comparison with current industrial practice. A potential batch time reduction of over 12 h has been highlighted, coupled with a moderate improvement in ethanol content

Neural Correlates of Visual Motion Prediction

Predicting the trajectories of moving objects in our surroundings is important for many life scenarios, such as driving, walking, reaching, hunting and combat. We determined human subjects’ performance and task-related brain activity in a motion trajectory prediction task. The task required spatial and motion working memory as well as the ability to extrapolate motion information in time to predict future object locations. We showed that the neural circuits associated with motion prediction included frontal, parietal and insular cortex, as well as the thalamus and the visual cortex. Interestingly, deactivation of many of these regions seemed to be more closely related to task performance. The differential activity during motion prediction vs. direct observation was also correlated with task performance. The neural networks involved in our visual motion prediction task are significantly different from those that underlie visual motion memory and imagery. Our results set the stage for the examination of the effects of deficiencies in these networks, such as those caused by aging and mental disorders, on visual motion prediction and its consequences on mobility related daily activities

Strontium isotope evidence for landscape use by early hominins

Ranging and residence patterns among early hominins have been indirectly inferred from morphology, stone-tool sourcing, referential models and phylogenetic models. However, the highly uncertain nature of such reconstructions limits our understanding of early hominin ecology, biology, social structure and evolution. We investigated landscape use in Australopithecus africanus and Paranthropus robustus from the Sterkfontein and Swartkrans cave sites in South Africa using strontium isotope analysis, a method that can help to identify the geological substrate on which an animal lived during tooth mineralization. Here we show that a higher proportion of small hominins than large hominins had non-local strontium isotope compositions. Given the relatively high levels of sexual dimorphism in early hominins, the smaller teeth are likely to represent female individuals, thus indicating that females were more likely than males to disperse from their natal groups. This is similar to the dispersal pattern found in chimpanzees, bonobos and many human groups, but dissimilar from that of most gorillas and other primates. The small proportion of demonstrably non-local large hominin individuals could indicate that male australopiths had relatively small home ranges, or that they preferred dolomitic landscapes