How a well-adapting immune system remembers

An adaptive agent predicting the future state of an environment must weigh trust in new observations against prior experiences. In this light, we propose a view of the adaptive immune system as a dynamic Bayesian machinery that updates its memory repertoire by balancing evidence from new pathogen encounters against past experience of infection to predict and prepare for future threats. This framework links the observed initial rapid increase of the memory pool early in life followed by a mid-life plateau to the ease of learning salient features of sparse environments. We also derive a modulated memory pool update rule in agreement with current vaccine response experiments. Our results suggest that pathogenic environments are sparse and that memory repertoires significantly decrease infection costs even with moderate sampling. The predicted optimal update scheme maps onto commonly considered competitive dynamics for antigen receptors

Current, emerging and future technologies for sensing the environment

This paper reviews current technologies that are used for environmental monitoring, and presents emerging technologies that will dramatically improve our ability to obtain spatially distributed, real-time data about key indicators of environmental quality at specific locations. Futuristic approaches to environmental monitoring that employ fundamental breakthroughs in materials science to revolutionise the way we monitor our environment will also be considered. In particular, approaches employing biomimetic and 'adaptive'/'stimuli-responsive' materials will be highlighted, as these could play an important role in the realization of small, low power, low cost, autonomous sensing and communications platforms that could form the building blocks of the much vaunted environmental 'sensor web'