Emergence of classical reality from a quantum mechanical background

A model for the process of knowledge acquisition is presented that shows how naive realism emerges from a quantum mechanical background. We formalise this process of emergence and obtain in this way an illustrative insight to some of the most fundamental physical theories: GRW-theory and E^∞-theory.     

Simulations of polyelectrolyte dynamics in an externally applied electric field in confined geometry

We consider the dynamics of charged polymers in free solution in a slit geometry under the influence of an electrical field, applied at an angle to the plane parallel walls of the confinement. The simulations are carried out using the Brownian dynamics method with explicit counterions and implicit hydrodynamics. The hydrodynamic interactions between all the particles and the plane parallel walls are taken into account using a diffusion matrix which depends on slit geometry and the actual polyelectrolyte-solute conformations. We observe a selective transport of the charged polymers, as a function of the degree of polymerization and slit height.     

A Geometric Framework for Stochastic Shape Analysis

We introduce a stochastic model of diffeomorphisms, whose action on a variety of data types descends to stochastic evolution of shapes, images and landmarks. The stochasticity is introduced in the vector field which transports the data in the large deformation diffeomorphic metric mapping framework for shape analysis and image registration. The stochasticity thereby models errors or uncertainties of the flow in following the prescribed deformation velocity. The approach is illustrated in the example of finite-dimensional landmark manifolds, whose stochastic evolution is studied both via the Fokker–Planck equation and by numerical simulations. We derive two approaches for inferring parameters of the stochastic model from landmark configurations observed at discrete time points. The first of the two approaches matches moments of the Fokker–Planck equation to sample moments of the data, while the second approach employs an expectation-maximization based algorithm using a Monte Carlo bridge sampling scheme to optimise the data likelihood. We derive and numerically test the ability of the two approaches to infer the spatial correlation length of the underlying noise.

     

Zur Theorie der analytischen Funktionen mehrerer komplexer Veränderlichen

Ohne Zusammenfassung     

Determination of wear metals in lubrication oils: a comparison study of ICP-OES and FAAS.

Certain wear metals (Fe, Cr, Ni, Cu and Zn) of various lubrication oils were determined by means of ICP-OES and FAAS. The kerosene dilution method, which is used widely together with ICP-OES, was applied with both methods here. Calibration standards were made from a commercial organo-metallic standard. Our aim was to clarify the possibility of using the quick kerosene dilution method together with FAAS for a rapid check for certain indicator metals. Metal determinations with FAAS were accurate enough for quantitative work in machine condition diagnostics and waste oil characterization, when compared with those with ICP-OES.