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Here we propose a class of macroscopic networks of thermal conduction that combine regular networks with macroscopic thermally conductive systems.

One prerequisite for this was shown to be that macroscopic networks of the conducting polymers have to be avoided in the coating in order to avoid predominant and disastrously fast cation incorporation during the corrosion induced reduction of the polymer.

By avoiding continuous macroscopic networks of conducting polymer in composite coatings the latter can be prevented, opening up the application of conducting polymers for secure performance in intelligent corrosion protection.

There is now strong evidence that brain networks, ranging from simple nets of interconnected neurons up to macroscopic networks of brain areas display the typical features of complex systems: high clustering, short path lengths (both typical of 'small-world' networks), skewed degree distributions, presence of hubs, assortative mixing and the presence of modules.

The volume phase transition of the shell was found to be continuous and the degree of shrinking was found to be much less than what is observed for macroscopic networks of a similar degree of crosslinking.

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The improved ductility was attributed to both the strain hardening induced by the coarse-grained structure and the extra strain hardening caused by the peculiar macroscopic network of ultrafine-grained structure.

Hence, the weights on the links of the macroscopic network are of crucial importance, since they define the complete structure of the network.

They can be obtained from quite a broad range of precursors provided that the latter have the ability to form colloid dispersions from solution state (sol) with particles aggregating to macroscopic networks (gel), the voids of which are filled with the respective solvent (hydro- or solvogel).

The mean metapopulation lifetime is expressed as a function of four macroscopic network properties: the ratio of dispersal range and network size, the ratio of range of environmental correlation and network size, and the total number and (geometric mean) size of the patches.

These grains are water insoluble macroscopic complex networks of amylose and amylopectin [ 14], organized in alternating concentric 120 400 nm thick amorphous and semi-crystalline domains, known as growth rings [ 10, 15].

To assess the robustness of the macroscopic network properties versus the variation of the sampled data and the sample size, we have performed a sub-sampling experiment.

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