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The invention relates to a system for the implementation of chemical, biological or physical reactions, consisting of - one or more magnetic micro-reactors, each comprising a shell made of hydrophobic magnetic nanoparticles encapsulating an aqueous core, - a plane platform comprising a surface to receive the micro-reactors, - a source that generates a magnetic field above or underneath the platform for manipulating the one or more hydrophobic magnetic micro-reactors, or for moving them along the surface of the platform from one position to another position, characterized in that the aqueous core of the one or more magnetic micro-reactors contains a reaction solution or buffer, and wherein the magnetic field generated by the source correlates to a defined position on the surface of the platform.
The network approach towards the analysis of the dynamics of complex systems has been successfully applied in a multitude of studies in the neurosciences and has yielded fascinating insights. With this approach, a complex system is considered to be composed of different constituents which interact with each other. Interaction structures can be compactly represented in interaction networks. In this contribution, we present a brief overview about how interaction networks are derived from multivariate time series, about basic network characteristics, and about challenges associated with this analysis approach.