We consider maximal regularity for the heat equation based on the endpoint function class BMO (the class of bounded mean oscillation). It is well known that BM O(Rn) is the endpoint class for solving the initial value problem for the incompressible Navier-Stokes equations and it is well suitable for solving such a problem ([3]) rather than the end-point homogeneous Besov spaces (cf. [1], [5]). First we recall basic properties of the function space BM O and show maximal regularity for the initial value problem of the Stokes equations ([4]). As an application, we consider the local well-posedness issue for the MHD equations with the Hall effect (cf. [2]). This talk is based on a joint work with Senjo Shimizu (Kyoto University).[-]

The aim of this talk is the rigorous derivation of crossdiffusion systems from stochastic, moderately interacting many-particle systems for multiple species. Applications include animal populations and neuronal ensembles. The mean-field limit leads to nonlocal cross-diffusion systems, while the limit of vanishing interaction radius gives local cross-diffusion equations. This allows for the derivation of fluid-type models that can be found in neuronal networks and of Shigesada-Kawasaki-Teramoto population models. The derivation uses the techniques of Oehlschläger. The entropy structure of the limiting models is discussed and some numerical experiments are presented.[-]