This doctoral thesis examines organizational development in public management, using the example of a police department as a basis. It follows the theory of autopoietic social systems according to Niklas Luhmann and establishes what can be observed from a social science point of view within two subsystems of this public management organization (police authority and police clients) and what consequences may result from this. The dissertation consistently follows Luhmanns circular way of thinking in which every term used precludes knowledge of the following terms. The author adopts a critical stance towards Luhmann and persists on one central point where everything converges: an autopoietic social system is regarded as a social system which develops new communication elements from the communications of which it already consists.

Pharmaceutical adjuvants or excipients are important ingredients of medicaments. These substances are used as support and for building the matrix for the active ingredients. In this way, the active ingredients will be realised in accurately and defined way at the specific site of action. In this study, the most important pharmaceutical adjuvants are characterised and analysed via near infrared-spectroscopic methods. The powdery samples were measured by means of diffuse reflectance with six NIR-spectrometer. The obtained NIR-spectra were used to build a near infrared spectra library based on SpecInfo systems of the firm Chemical Concepts. Furthermore, discrimination analysis were carried out, while reference spectra were compared with the database for performing an identity control.

Zugl.: Berlin, Humboldt-Univ., Diss., 2005

Universiẗat, Diss., 1969--Bonn.

The phenomenon of friction is on the one hand useful, for example for walking, which would not be so easy without friction, and on the other hand disturbing, for example in wheel bearings, where it slows down desired motion. Therefore, the origin and effect of friction is under intense research. One main point in this work is the analytic investigation of the coupling between friction force and (torsion) friction torque of a sliding and spinning disk. The local friction force at a contact area element was chosen to be an algebraic function of the local relative velocity with an exponent α > 0. It could be shown, that for α < 1 sliding and torsion friction dynamically reduce each other, while for α > 1 they amplify each other. In case of α = 1 sliding and torsion friction are decoupled. With respect to the velocity ratio of sliding and angular velocity, the final motion mode has been investigated, i.e. whether both motions stop together or whether one motion gets dominant. For α < 1 both motions stop together, while for α > 1 it depends on the initial velocity ratio. The mass distribution and contact area radius, which are encoded in the key parameter C of the corresponding differential equation, are the second important influence on the final motion mode. A phase diagram shows for given values C and α the possible final motion modes. The influence of an inhomogenous pressure distribution within the contact area on the coupling was investigated exemplarily for α = 0 with a cylinder as object. In contrast to the disk (homogenous pressure distribution) the cylinder is deflected from its initial sliding direction. In this context the motion of a curling rock on ice is discussed, as it is deflected towards the opposite direction compared to that of the cylinder. Another focal point is the investigation of the role of friction torques (rolling and torsion friction) in the compaction of nano-powders. For this three dimensional contact dynamics simulations with phenomenologically chosen contact laws were performed. With this it could be shown that torsion and rolling friction contribute significantly to the final porosity. Furthermore, these contributions of torsion and rolling friction are independent of each other and can be represented by a sum. In the chapter Conclusions and Outlook a brief introduction on recent research of atomic scale torsion friction is presented.

In this thesis, several stochastic models are investigated, which are subjected to irreversible dynamics. Motivation for the presented work stems, on the one hand, from particular physical systems under consideration, which are modeled by the studied stochastic processes. Besides that, the models discussed in this thesis are, on the other hand, generally interesting from the point of view of statistical physics, since they describe systems far from thermodynamic equilibrium. Interesting properties to be encountered are, e.g., dynamical scaling behavior or continuous phase transitions. The first issue to be addressed, is the investigation of irreversibly aggregating systems, where the main emphasis is laid on aggregation of monopolarly charged clusters suspended in a fluid. For this purpose, rate equations are analyzed and Brownian dynamics simulations are performed. It is shown that the system crosses over from power-law cluster growth to sub-logarithmic cluster growth. Asymptotically, the cluster size distribution evolves towards a universal scaling form, which implies a 'self-focussing' of the size distribution. Another emphasis of this thesis is the investigation of nonequilibrium critical phenomena, in particular, the study of phase transitions into absorbing states (states that may be reached irreversibly). To this end, the continuous nonequilibrium phase transition of directed percolation, which serves as a paradigm for absorbing-state phase transitions, is analyzed by a novel approach. Despite the lack of a partition function for directed percolation, this novel approach follows the ideas of Yang-Lee theory of equilibrium statistical mechanics, by investigating the complex roots of the survival probability. Stochastic models such as directed percolation mimic spreading processes, e.g., the spreading of an infectious disease. The effect of long-time memory, which is not included in directed percolation and which corresponds to immunization in epidemic spreading, is investigated through an appropriate model. This model includes dynamical percolation (perfect immunization) as a special case, as well as directed percolation (no immunization). The critical behavior of this model is studied by means of Monte Carlo simulations, in particular for weak immunization. A further generalization is investigated, which allows spontaneous mutations and different species of spreading agents (pathogens). Restricting the analysis to perfect immunization and two spatial dimensions, it is shown by Monte Carlo simulations, that immunization leads to a crossover from dynamical to directed percolation. Other properties of this model are discussed in detail.

In order to characterize the spin-reorientation transition (SRT), i. e. the change of the easy axis of the magnetization, of ultrathin Ni/Cu(100)- and Fe/Ni/Cu(100)-films the magnetic domain structure was imaged as a function of the Ni and Fe layer thickness, respectively, by using spin-polarized low energy electron microscopy (SPLEEM) during the film growth in ultrahigh vacuum at 300 K. Whereas the size of the domains at the SRT of Ni/Cu(100) is some micrometers, the domain structure of the Fe/Ni-films breaks up into a pattern of 180 nm wide stripe domains. It was shown that the SRT of both Ni/Cu(100) and Fe/Ni/Cu(100) proceeds via a spiral-like rotation of the magnetization within the domains. A discontinuous SRT via coexisting in-plane and out-of-plane magnetized stripe domains is not observed for the film systems.

In recent years a new class of one-dimensional cellular automata (CA) models has attracted much attention. These so-called mass transport models can be characterized as nonequilibrium stochastic processes. In the presented thesis a new model of this class, the Asymmetric Multi Occupation Process (AMOP) is considered. This CA model was first introduced with open boundary conditions to simulate Internet data transport. It is defined on a one-dimensional lattice equipped with buffers of finite size that can be occupied by at most B particles. The local dynamics are implemented by the totally asymmetric shift of discrete mass variables respectively particles under consideration of hard-core repulsion and parallel dynamics. In the first part of this work the AMOP with periodic boundary conditions is investigated by means of numerical as well as analytical considerations. Regarding deterministic model dynamics the influence of finite buffer and system sizes onto the fundamental diagram (FD), i.e., flow-density relation is analyzed. Furthermore, for stochastic movement the FDs obtained by numerical simulations are compared with analytical results derived by Mean-Field (MF) approaches and a 2-cluster approximation. In the second part the AMOP with open boundary conditions is investigated in the context of boundary induced phase transitions. In case of deterministic bulk dynamics an analytical exact representation of the system inflow as well as the outflow is presented in dependence of the buffer size. As a result the deterministic phase diagram derived by numerical simulations could be verified by analytical considerations. Regarding stochastic particle movement the phase diagram is obtained by Monte Carlo simulations. In both cases it is shown that the jammed phase is strongly enlarged for increasing buffer sizes. Finally, in the third part of this thesis the influence of interacting boundaries on the model dynamics is analyzed. Therefore, a new fall back inflow strategy is introduced in order to stabilize high flow states and thus prevent the system from a complete jamming. Precisely, the inflow is determined by the state of the last site of the system. As a result the phase diagrams of the deterministic and the stochastic model obtained by means of numerical simulations are presented. Two new phases could be identified a free-flow as well as a jammed phase both characterized by a striped microscopic pattern. Especially in the arising striped jammed regime system flow and mean velocity are drastically enlarged compared to generic inflow strategies. Here, the fall back strategy is capable to prevent the system from a complete jamming. Thus, the introduced inflow procedure represents an effective strategy for establishing reliable connections.

Probability estimation is important for the application of probabilistic models as well as for any evaluation in IR. We discuss the interdependencies between parameter estimation and certain properties of probabilistic models: dependence assumptions, binary vs. non-binary features, estimation sample selection. Then we define an optimum estimate for binary features which can be applied to various typical estimation problems in IR. A method for computing this estimate using empirical data is described. Some experiments show the applicability of our method, whereas comparable approaches are partially based on false assumptions or yield biased estimates.

Proceedings of the Fourteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval