Titlebook: Bio-Inspired Computing and Communication; First Workshop on Bi Pietro Liò,Eiko Yoneki,Dinesh C. Verma Conference proceedings 2008 Springer-

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Wireless Epidemic Spread in Dynamic Human Networksng epidemic spread in such dynamic human networks, a topic which shares many issues with network-based epidemiology. We explore hub nodes extracted from real world connectivity traces and show their influence on the epidemic to demonstrate the characteristics of information propagation.

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Self-organizing Desynchronization and TDMA on Wireless Sensor Networksronization in a single-hop network. We also describe .-TDMA, a self-adjusting TDMA protocol that addresses two weaknesses of traditional TDMA: it does not require a global clock and it automatically adjusts to the number of participating nodes, so that bandwidth is always fully utilized.

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,T?dtung frei umherlaufender Jagdhunde, examples, the utility of building simplifying neural models. In the first example, we consider the development of neuronal positioning. In the second example, we investigate the stability of a cortical network under control and perturbed conditions.

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Die Gewinnung von Fichtensamen betr,ontact networks such as clustering and variable strengths of interactions are seen to be important factors in the spread of an epidemic. We consider the evolution of a pathogen spreading through a dynamic network and show that the pattern of contacts within a host population determines the evolutionary pressures that a pathogen experiences.

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