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Service-oriented modeling employs collaborations to capture the coordination of multiple roles in form of service contracts. In case of dynamic collaborations the roles may join and leave the collaboration at runtime and therefore complex structural dynamics can result, which makes it very hard to ensure their correct and safe operation. We present in this paper our approach for modeling and verifying such dynamic collaborations. Modeling is supported using a well-defined subset of UML class diagrams, behavioral rules for the structural dynamics, and UML state machines for the role behavior. To be also able to verify the resulting service-oriented systems, we extended our former results for the automated verification of systems with structural dynamics [7, 8] and developed a compositional reasoning scheme, which enables the reuse of verification results. We outline our approach using the example of autonomous vehicles that use such dynamic collaborations via ad-hoc networking to coordinate and optimize their joint behavior.
In this thesis, the properties of nonlinear disordered one dimensional lattices is investigated. Part I gives an introduction to the phenomenon of Anderson Localization, the Discrete Nonlinear Schroedinger Equation and its properties as well as the generalization of this model by introducing the nonlinear index α. In Part II, the spreading behavior of initially localized states in large, disordered chains due to nonlinearity is studied. Therefore, different methods to measure localization are discussed and the structural entropy as a measure for the peak structure of probability distributions is introduced. Finally, the spreading exponent for several nonlinear indices is determined numerically and compared with analytical approximations. Part III deals with the thermalization in short disordered chains. First, the term thermalization and its application to the system in use is explained. Then, results of numerical simulations on this topic are presented where the focus lies especially on the energy dependence of the thermalization properties. A connection with so-called breathers is drawn.
Music is a powerful and reliable means to stimulate the percept of both intense pleasantness and unpleasantness in the perceiver. However, everyone’s social experiences with music suggest that the same music piece may elicit a very different valence percept in different individuals. A comparison of music from different historical periods suggests that enculturation modulates the valence percept of intervals and harmonies, and thus possibly also of relatively basic feature extraction processes. Strikingly, it is still largely unknown how much the valence percept is dependent on physical properties of the stimulus and thus mediated by a universal perceptual mechanism, and how much it is dependent on cultural imprinting. The current thesis investigates the neurophysiology of the valence percept, and the modulating influence of culture on several distinguishable sub-processes of music processing, so-called functional modules of music processing, engaged in the mediation of the valence percept.
In my dissertation on 'Security Cooperation as a Way to Stop the Spread of Nu-clear Weapons? Nuclear Nonproliferation Policies of the United States towards the Federal Republic of Germany and Israel, 1945-1968', I study the use of security assistance as nonproliferation policy. I use insights of the Structural Realist and the Rational Institutionalist theories of International Relations to explain, respectively, important foreign policy goals and the basic orientation of policies, on the one hand, and the practical workings and effects of security cooperation on states’ behavior, on the other hand. Moreover, I consider the relations of the United States (US) with the two states in light of bargaining theory to explain the level of US ability to press other states to its preferred courses of action. The study is thus a combination of theory proposing and testing and historic description and explanation. It is also policy-relevant as I seek general lessons regarding the use of security cooperation as nonproliferation policy. I show that the US sought to keep the Federal Republic of Germany (FRG) from acquiring nuclear weapons in order to avoid crises with Moscow and threats to the cohesion of NATO. But the US also saw it as necessary to credibly guarantee the security of the FRG and treat it well in order to ensure that it would remain satisfied as an ally and without own nuclear weapons. Through various institutionalized security cooperation schemes, the US succeeded in this – though the FRG did acquire an option to produce nuclear weapons. The US opposed Israel’s nuclear weapon ambitions in turn because of an expectation that Arab states’ reactions could otherwise result in greater tension and risks of escalation and a worse balance-of-power in the area. But as also a US-Israel alliance could have led to stronger Arab-Soviet ties and thus a worse balance-of-power, and as it was not in US in-terest to be tied to Israel’s side in all regional issues, the US was not prepared to guarantee Israel’s security in a formal, credible way like it did in West Germany’s case. The US failed to persuade Israel to forgo producing nuclear weapons but gradually, an opaque nu-clear status combined with US arms sales that helped Israel to maintain a conventional military advantage over Arabs emerged as a solution to Israel’s security strategy. Because of perceptions that Israel and the FRG had also other options than cooperation with the US, and because the US ability to punish them for unwanted action was limited, these states were able to offer resistance when the US pressed its nonproliferation stance on them.
The fat-soluble vitamin A, which is chemically referred to retinol (ROH), is known to be essential for the process of vision, the immune system but also for cell differentiation and proliferation. Recently, ROH itself has been reported to be involved in adipogenesis and a ROH transport protein, the retinol-binding protein 4 (RBP4), in insulin resistance and type 2 diabetes. However, there is still considerable scientific debate about this relation. With the increasing amount of studies investigating the relation of ROH in obesity and type 2 diabetes, basic research is an essential prerequisite for interpreting these results. This thesis enhances the knowledge on this relation by reviewing ROH metabolism on extra- and intracellular level. Aim 1: In the blood stream ROH is transported in a complex with RBP4 and a second protein, transthyretin (TTR), to the target cells. The levels of RBP4 and TTR are influenced by several factors but mainly by liver and kidney function. The reason for that is that liver and the kidneys are the sites of RBP4 synthesis and catabolism, respectively. Interestingly, obesity and type 2 diabetes involve disorders of the liver and the kidneys. Therefore the aim was to investigate factors that influence RBP4 and TTR levels in relation to obesity and type 2 diabetes (Part 1). Aim 2: Once arrived in the target cell ROH is bound to cellular retinol-binding protein type I (CRBP-I) and metabolised: ROH can either be stored as retinylesters or it can be oxidised to retinoic acid (RA). By acting as a transcription factor in the nucleus RA may influence processes such as adipogenesis. Therefore vitamin A has been postulated to be involved in obesity and type 2 diabetes. CRBP-I is known to mediate the storage of ROH in the liver, but the extra-hepatic metabolism and the functions of CRBP-I are not well known. This has been investigated in Part 2 of this work. Material & Methods: RBP4 and TTR levels were investigated by ELISA in serum samples of human subjects with overweight, type 2 diabetes, kidney or liver dysfunction. Molecular alterations of the RBP4 and TTR protein structure were analysed by MALDI-TOF mass spectrometry. The functions of intracellular CRBP-I were investigated in CRBP-I knock-out mice in liver and extra-hepatic tissues by measuring ROH levels as well as the levels of its storage form, the retinylesters, using reverse phase HPLC. The postprandial uptake of ROH into tissues was analysed using labelled ROH. The mRNA levels of enzymes that metabolize ROH were examined by real-time polymerase chain reaction (RCR). Results: The previous published results showing increased RBP4 levels in type 2 diabetic patients could not be confirmed in this work. However, it could be shown that during kidney dysfunction RBP4 levels are increased and that RBP4 and TTR levels are decreased during liver dysfunction. The important new finding of this work is that increased RBP4 levels in type 2 diabetic mice were increased when kidney function was decreased. Thus an increase in RBP4 levels in type 2 diabetes may be the effect of a reduced kidney function which is common in type 2 diabetes. Interestingly, during severe kidney dysfunction the molecular structure of RBP4 and TTR was altered in a specific manner which was not the case during liver diseases and type 2 diabetes. This underlines the important function of the kidneys in RBP4 metabolism. CRBP-I has been confirmed to be responsible for the ROH storage in the liver since CRBP-I knock-out mice had decreased ROH and retinylesters (the storage form of ROH) levels in the liver. Interestingly, in the adipose tissue (the second largest ROH storage tissue in the body) ROH and retinylesters levels were higher in the CRBP-I knock-out compared to the wild-type mice. It could be shown in this work that a different ROH binding protein, cellular retinol-binding protein type III, is upregulated in CRBP-I knock-out mice. Moreover enzymes were identified which mediate very efficiently ROH esterification in the adipose tissue of the knock-out mice. In the pancreas there was a higher postprandial ROH uptake in the CRBP-I knock-out compard to wild-type mice. Even under a vitamin A deficient diet the knock-out animals had ROH and retinylesters levels which were comparable to wild-type animals. These results underline the important role of ROH for insulin secretion in the pancreas. Summing up, there is evidence that RBP4 levels are more determined by kidney function than by type 2 diabetes and that specific molecular modifications occur during kidney dysfunction. The results in adipose tissue and pancreas of CRBP-I knock-out mice support the hypothesis that ROH plays an important role in glucose and lipid metabolism.
New ABC triblock copolymers were synthesized by controlled free-radical polymerization via Reversible Addition-Fragmentation chain Transfer (RAFT). Compared to amphiphilic diblock copolymers, the prepared materials formed more complex self-assembled structures in water due to three different functional units. Two strategies were followed: The first approach relied on double-thermoresponsive triblock copolymers exhibiting Lower Critical Solution Temperature (LCST) behavior in water. While the first phase transition triggers the self-assembly of triblock copolymers upon heating, the second one allows to modify the self-assembled state. The stepwise self-assembly was followed by turbidimetry, dynamic light scattering (DLS) and 1H NMR spectroscopy as these methods reflect the behavior on the macroscopic, mesoscopic and molecular scale. Although the first phase transition could be easily monitored due to the onset of self-assembly, it was difficult to identify the second phase transition unambiguously as the changes are either marginal or coincide with the slow response of the self-assembled system to relatively fast changes of temperature. The second approach towards advanced polymeric micelles exploited the thermodynamic incompatibility of “triphilic” block copolymers – namely polymers bearing a hydrophilic, a lipophilic and a fluorophilic block – as the driving force for self-assembly in water. The self-assembly of these polymers in water produced polymeric micelles comprising a hydrophilic corona and a microphase-separated micellar core with lipophilic and fluorophilic domains – so called multi-compartment micelles. The association of triblock copolymers in water was studied by 1H NMR spectroscopy, DLS and cryogenic transmission electron microscopy (cryo-TEM). Direct imaging of the polymeric micelles in solution by cryo-TEM revealed different morphologies depending on the block sequence and the preparation conditions. While polymers with the sequence hydrophilic-lipophilic-fluorophilic built core-shell-corona micelles with the core being the fluorinated compartment, block copolymers with the hydrophilic block in the middle formed spherical micelles where single or multiple fluorinated domains “float” as disks on the surface of the lipophilic core. Increasing the temperature during micelle preparation or annealing of the aqueous solutions after preparation at higher temperatures induced occasionally a change of the micelle morphology or the particle size distribution. By RAFT polymerization not only the desired polymeric architectures could be realized, but the technique provided in addition a precious tool for molar mass characterization. The thiocarbonylthio moieties, which are present at the chain ends of polymers prepared by RAFT, absorb light in the UV and visible range and were employed for end-group analysis by UV-vis spectroscopy. A variety of dithiobenzoate and trithiocarbonate RAFT agents with differently substituted initiating R groups were synthesized. The investigation of their absorption characteristics showed that the intensity of the absorptions depends sensitively on the substitution pattern next to the thiocarbonylthio moiety and on the solvent polarity. According to these results, the conditions for a reliable and convenient end-group analysis by UV-vis spectroscopy were optimized. As end-group analysis by UV-vis spectroscopy is insensitive to the potential association of polymers in solution, it was advantageously exploited for the molar mass characterization of the prepared amphiphilic block copolymers.
Since the end of the Apartheid international tourism in South Africa has increasingly gained importance for the national economy. The centre of this PKS issue’s attention is a particular form of tourism: Township tourism, i.e. guided tours to the residential areas of the black population. About 300,000 tourists per year visit the townships of Cape Town. The tours are also called Cultural, Social, or Reality Tours. The different aspects of township tourism in Cape Town were subject of a geographic field study, which was undertaken during a student research project of Potsdam University in 2007. The text at hand presents the empirical results of the field study, and demonstrates how townships are constructed as spaces of tourism.
Model-driven software development requires techniques to consistently propagate modifications between different related models to realize its full potential. For large-scale models, efficiency is essential in this respect. In this paper, we present an improved model synchronization algorithm based on triple graph grammars that is highly efficient and, therefore, can also synchronize large-scale models sufficiently fast. We can show, that the overall algorithm has optimal complexity if it is dominating the rule matching and further present extensive measurements that show the efficiency of the presented model transformation and synchronization technique.
Modern acquisition of seismic data on receiver networks worldwide produces an increasing amount of continuous wavefield recordings. Hence, in addition to manual data inspection, seismogram interpretation requires new processing utilities for event detection, signal classification and data visualization. Various machine learning algorithms, which can be adapted to seismological problems, have been suggested in the field of pattern recognition. This can be done either by means of supervised learning using manually defined training data or by unsupervised clustering and visualization. The latter allows the recognition of wavefield patterns, such as short-term transients and long-term variations, with a minimum of domain knowledge. Besides classical earthquake seismology, investigations of temporal patterns in seismic data also concern novel approaches such as noise cross-correlation or ambient seismic vibration analysis in general, which have moved into focus within the last decade. In order to find records suitable for the respective approach or simply for quality control, unsupervised preprocessing becomes important and valuable for large data sets. Machine learning techniques require the parametrization of the data using feature vectors. Applied to seismic recordings, wavefield properties have to be computed from the raw seismograms. For an unsupervised approach, all potential wavefield features have to be considered to reduce subjectivity to a minimum. Furthermore, automatic dimensionality reduction, i.e. feature selection, is required in order to decrease computational cost, enhance interpretability and improve discriminative power. This study presents an unsupervised feature selection and learning approach for the discovery, imaging and interpretation of significant temporal patterns in seismic single-station or network recordings. In particular, techniques permitting an intuitive, quickly interpretable and concise overview of available records are suggested. For this purpose, the data is parametrized by real-valued feature vectors for short time windows using standard seismic analysis tools as feature generation methods, such as frequency-wavenumber, polarization, and spectral analysis. The choice of the time window length is dependent on the expected durations of patterns to be recognized or discriminated. We use Self-Organizing Maps (SOMs) for a data-driven feature selection, visualization and clustering procedure, which is particularly suitable for high-dimensional data sets. Using synthetics composed of Rayleigh and Love waves and three different types of real-world data sets, we show the robustness and reliability of our unsupervised learning approach with respect to the effect of algorithm parameters and data set properties. Furthermore, we approve the capability of the clustering and imaging techniques. For all data, we find improved discriminative power of our feature selection procedure compared to feature subsets manually selected from individual wavefield parametrization methods. In particular, enhanced performance is observed compared to the most favorable individual feature generation method, which is found to be the frequency spectrum. The method is applied to regional earthquake records at the European Broadband Network with the aim to define suitable features for earthquake detection and seismic phase classification. For the latter, we find that a combination of spectral and polarization features favor S wave detection at a single receiver. However, SOM-based visualization of phase discrimination shows that clustering applied to the records of two stations only allows onset or P wave detection, respectively. In order to improve the discrimination of S waves on receiver networks, we recommend to consider additionally the temporal context of feature vectors. The application to continuous recordings of seismicity close to an active volcano (Mount Merapi, Java, Indonesia) shows that two typical volcano-seismic events (VTB and Guguran) can be detected and distinguished by clustering. In contrast, so-called MP events cannot be discriminated. Comparable results are obtained for selected features and recognition rates regarding a previously implemented supervised classification system. Finally, we test the reliability of wavefield clustering to improve common ambient vibration analysis methods such as estimation of dispersion curves and horizontal to vertical spectral ratios. It is found, that in general, the identified short- and long-term patterns have no significant impact on those estimates. However, for individual sites, effects of local sources can be identified. Leaving out the corresponding clusters, yields reduced uncertainties or allows for improving estimation of dispersion curves.