The theory of Markov Processes has become a powerful tool in partial differential equations and potential theory with important applications to physics.

1. Markov processes and related problems of analysis; 2. Martin boundaries and non-negative solutions of a boundary value problem with a directional derivative; 3. Boundary theory of Markov processes (the discrete case); 4. The initial and final behaviour of trajectories of Markov processes; 5. Integral representation of excessive measures and excessive functions; 6. Regular Markov processes; 7 Markov representations of stochastic systems; 8. Sufficient statistics and extreme points; 9. Minimal excessive measures and functions.