Fault Tolerance in Cellular Automata at High Fault Rates

A commonly used model for fault-tolerant computation is that of cellular automata. The essential difficulty of fault-tolerant computation is present in the special case of simply remembering a bit in the presence of faults, and that is the case we treat in this paper. We are concerned with the degree (the number of neighboring cells on which the state transition function depends) needed to achieve fault tolerance when the fault rate is high (nearly 1/2). We consider both the traditional transient fault model (where faults occur independently in time and space) and a recently introduced combined fault model which also includes manufacturing faults (which occur independently in space, but which affect cells for all time). We also consider both a purely probabilistic fault model (in which the states of cells are perturbed at exactly the fault rate) and an adversarial model (in which the occurrence of a fault gives control of the state to an omniscient adversary). We show that there are cellular automata that can tolerate a fault rate $1/2 - \xi$ (with $\xi>0$) with degree $O((1/\xi^2)\log(1/\xi))$, even with adversarial combined faults. The simplest such automata are based on infinite regular trees, but our results also apply to other structures (such as hyperbolic tessellations) that contain infinite regular trees. We also obtain a lower bound of $\Omega(1/\xi^2)$, even with purely probabilistic transient faults only

Activity-dependent release of Adenosine: a critical re-evaluation of mechanism

Adenosine is perhaps the most important and universal modulator in the brain. The current consensus is that it is primarily produced in the extracellular space from the breakdown of previously released ATP. It is also accepted that it can be released directly, as adenosine, during pathological events primarily by equilibrative transport. Nevertheless, there is a growing realization that adenosine can be rapidly released from the nervous system in a manner that is dependent upon the activity of neurons. We consider three competing classes of mechanism that could explain neuronal activity dependent adenosine release (exocytosis of ATP followed by extracellular conversion to adenosine; exocytotic release of an unspecified transmitter followed by direct non-exocytotic adenosine release from an interposed cell; and direct exocytotic release of adenosine) and outline discriminatory experimental tests to decide between them. We review several examples of activity dependent adenosine release and explore their underlying mechanisms where these are known. We discuss the limits of current experimental techniques in definitively discriminating between the competing models of release, and identify key areas where technologies need to advance to enable definitive discriminatory tests. Nevertheless, within the current limits, we conclude that there is evidence for a mechanism that strongly resembles direct exocytosis of adenosine underlying at least some examples of neuronal activity dependent adenosine release

Understanding contextual interactions to design navigational context-aware applications

Context-aware technology has stimulated rigorous research into novel ways to support people in a wide range of tasks and situations. However, the effectiveness of these technologies will ultimately be dependent on the extent to which contextual interactions are understood and accounted for in their design. This study involved an investigation of contextual interactions required for route navigation. The purpose was to illustrate the heterogeneous nature of humans in interaction with their environmental context. Participants were interviewed to determine how each interacts with or use objects/information in the environment in which to navigate/orientate. Results revealed that people vary individually and collectively. Usability implications for the design of navigational context-aware applications are identified and discussed