## Doctoral Thesis

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The provision of electronic participation services (e-participation) is a complex socio-technical undertaking that needs comprehensive design and implementation strategies. E-participation service providers, in the most cases administrations and governments, struggle with changing requirements that demand more transparency, better connectivity and increased collaboration among different actors. At the same time, less staff are available. As a result, recent research assesses only a minority of e-participation services as successful. The challenge is that the e-participation domain lacks comprehensive approaches to design and implement (e-)participation services. Enterprise Architecture (EA) frameworks have evolved in information systems research as an approach to guide the development of complex socio-technical systems. This approach can guide the design and implementation services, if the collection of organisations with the commonly held goal to provide participation services is understood as an E Participation Enterprise (EE). However, research & practice in the e participation domain has not yet exploited EA frameworks. Consequently, the problem scope that motivates this dissertation is the existing gap in research to deploy EA frameworks in e participation design and implementation. The research question that drives this research is: What methodical and technical guides do architecture frameworks provide that can be used to design and implement better and successful e participation?
This dissertation presents a literature study showing that existing approaches have not covered yet the challenges of comprehensive e participation design and implementation. Accordingly, the research moves on to investigate established EA frameworks such as the Zachman Framework, TOGAF, the DoDAF, the FEA, the ARIS, and the ArchiMate for their use. While the application of these frameworks in e participation design and implementation is possible, an integrated approach is lacking so far. The synthesis of literature review and practical insights in design and implementation of e participation services from four projects show the challenges of adapting architecture frameworks for this domain. However, the research shows also the potential of a combination of the different approaches. Consequently, the research moves on to develop the E-Participation Architecture Framework (EPART-Framework). Therefore, the dissertation applies design science research including literature review and action research. Two independent settings test an initial EPART-Framework version. The results yield into the EPART-Framework presented in this dissertation.
The EPART-Framework comprises of the EPART-Metamodel with six EPART-Viewpoints, which frame the stakeholder concerns: the Participation Scope, the Participant Viewpoint, the Participation Viewpoint, the Data & Information Viewpoint, the E-participation Viewpoint, and Implementation & Governance Viewpoint. The EPART-Method supports the stakeholders to design the EE and implement e participation and stores its output in an architecture description and a solution repository. It consists of five consecutive phases accompanied by requirements management: Initiation, Design, Implementation and Preparation, Participation, and Evaluation. The EPART-Framework fills the gap between the e participation domain and the enterprise architecture framework domain. The evaluation gives reasonable evidence that the framework is a valuable addition in academia and in practice to improve e-participation design and implementation. The same time, it shows opportunities for future research to extend and advance the framework.

This thesis presents novel approaches for integrating context information into probabilistic models. Data from social media is typically associated with metadata, which includes context information such as timestamps, geographical coordinates or links to user profiles. Previous studies showed the benefits of using such context information in probabilistic models, e.g.\ improved predictive performance. In practice, probabilistic models which account for context information still play a minor role in data analysis. There are multiple reasons for this. Existing probabilistic models often are complex, the implementation is difficult, implementations are not publicly available, or the parameter estimation is computationally too expensive for large datasets. Additionally, existing models are typically created for a specific type of content and context and lack the flexibility to be applied to other data.
This thesis addresses these problems by introducing a general approach for modelling multiple, arbitrary context variables in probabilistic models and by providing efficient inference schemes and implementations.
In the first half of this thesis, the importance of context and the potential of context information for probabilistic modelling is shown theoretically and in practical examples. In the second half, the example of topic models is employed for introducing a novel approach to context modelling based on document clusters and adjacency relations in the context space. They can cope with areas of sparse observations and These models allow for the first time the efficient, explicit modelling of arbitrary context variables including cyclic and spherical context (such as temporal cycles or geographical coordinates). Using the novel three-level hierarchical multi-Dirichlet process presented in this thesis, the adjacency of ontext clusters can be exploited and multiple contexts can be modelled and weighted at the same time. Efficient inference schemes are derived which yield interpretable model parameters that allow analyse the relation between observations and context.

Die Entstehung von Gründungsteams wird bisher lediglich als Abfolge von Suche, Auswahl und Gewinnung von Gründerpersonen verstanden. In der vorliegenden Arbeit wird auf Basis von 47 interviewten Gründerpersonen ein neues Verständnis für die Entstehung von Gründungsteams geschaffen. Dabei wird im Stil der Grounded Theory das bisher vorherrschende Model der Teamentstehung maßgeblich erweitert. So wird eine neue Art der Unterscheidung von Grünerpersonen entdeckt, welche auf die Intention von Teammitgliedern abzielt. Zudem zeigt sich, dass Teams in einem iterativ-epiodischen Prozess entstehen und Veränderungen von Teamzu-sammmensetzungen Bestandteil der Entstehung sind. Aufgrund der in dieser Arbeit geschaffenen neuen Erkenntnisse zur Teamentstehung können Handlungsempfehlungen für Gründerpersonen und die Gründungsförderung gegeben werden. Zudem werden neue Untersuchungsgebiete für Gründungsteams eröffnet, die das hier entwickelte Modell als Bezugsrahmen für weitere Forschung nehmen können.

Ein zentrales Problem der stationären Behandlung psychischer und psychosomatischer Störungen ist die Nachhaltigkeit von Therapieerfolgen. Im Rahmen einer Pilotstudie wurde ein SMS-basiertes Nachsorgeprogramm zur Modifikation Perfektionismus-bezogener Kognitionen im Anschluss an eine stationäre Behandlung von Burnout-Patienten evaluiert.
Es handelte sich um eine kontrollierte Verlaufsstudie mit vier Messzeitpunkten (Aufnahme, Entlassung, 6 und 10-Wochen-Katamnese). Die Patienten der Versuchsgruppe (n=31) erhielten zusätzlich zur Routine-Behandlung eine 6-wöchige kognitiv ausgerichtete individualisierte SMS-Nachsorge. Als Kontrollgruppe (n=30) diente eine Gruppe von Patienten mit einer stationären Routine-Behandlung. Zur Erfassung der Burnout-Symptomatik wurde das Maslach Burnout Inventory General Survey (MBI-GS-D) eingesetzt, die depressive Symptomatik wurde mit dem Beck-Depressions-Inventar-V (BDI-V) erhoben. Zur Erfassung der Facetten des Perfektionismus dienten Items aus der Multidimensional Perfectionism Scale (FMPS und HMPS) sowie der Almost Perfect Scale (APS-R).
Ein sehr hohes Interesse, eine hohe Inanspruchnahme sowie eine hohe Akzeptanz des Nachsorgeprogramms konnte anhand der Bereitschaft zur Teilnahme und der von den Teilnehmern bewertete Nutzen aufgezeigt werden.
Eine Wirksamkeit der SMS-Nachsorge bzgl. Burnout und depressiver Symptomatik sowie dysfunktionalen Facetten des Perfektionismus konnte mittels zweifaktoriellen Kovarianzanalysen (Gruppe, Zeit, Baseline als Kovariate) nicht nachgewiesen werden. Ein Grund hierfür könnte sein, dass der Interventionszeitraum von 10 Wochen nach der stationären Entlassung für eine effektive Nachsorge zu kurz bemessen wurde. Bzgl. einiger dysfunktionaler Perfektionismusskalen (Concern over Mistakes, Discrepancy, Socially Prescribed Perfectionism) zeigten sich kleinere Interaktionseffekte, die einen ersten Hinweis liefern, dass die eingesetzten SMS-Nachrichten Perfektionismus-bezogene Kognitionen verändern können. Da das vorgestellte Interventionsprogramm ein ökonomisches und niedrigschwelliges ambulantes Nachsorge-Konzept darstellt und sich erste Hinweise auf eine Wirksamkeit ergeben, wären für die Zukunft weitere Studien wünschenswert, die sich über einen längeren Interventionszeitraum erstrecken. Es sollten weitere Messinstrumente einbezogen und die Implementierung eines Feedbackprozesses erwogen werden.

One of the main goals of the artificial intelligence community is to create machines able to reason with dynamically changing knowledge. To achieve this goal, a multitude of different problems have to be solved, of which many have been addressed in the various sub-disciplines of artificial intelligence, like automated reasoning and machine learning. The thesis at hand focuses on the automated reasoning aspects of these problems and address two of the problems which have to be overcome to reach the afore-mentioned goal, namely 1. the fact that reasoning in logical knowledge bases is intractable and 2. the fact that applying changes to formalized knowledge can easily introduce inconsistencies, which leads to unwanted results in most scenarios.
To ease the intractability of logical reasoning, I suggest to adapt a technique called knowledge compilation, known from propositional logic, to description logic knowledge bases. The basic idea of this technique is to compile the given knowledge base into a normal form which allows to answer queries efficiently. This compilation step is very expensive but has to be performed only once and as soon as the result of this step is used to answer many queries, the expensive compilation step gets worthwhile. In the thesis at hand, I develop a normal form, called linkless normal form, suitable for knowledge compilation for description logic knowledge bases. From a computational point of view, the linkless normal form has very nice properties which are introduced in this thesis.
For the second problem, I focus on changes occurring on the instance level of description logic knowledge bases. I introduce three change operators interesting for these knowledge bases, namely deletion and insertion of assertions as well as repair of inconsistent instance bases. These change operators are defined such that in all three cases, the resulting knowledge base is ensured to be consistent and changes performed to the knowledge base are minimal. This allows us to preserve as much of the original knowledge base as possible. Furthermore, I show how these changes can be applied by using a transformation of the knowledge base.
For both issues I suggest to adapt techniques successfully used in other logics to get promising methods for description logic knowledge bases.

Leaf litter breakdown is a fundamental process in aquatic ecosystems, being mainly mediated by decomposer-detritivore systems that are composed of microbial decomposers and leaf-shredding, detritivorous invertebrates. The ecological integrity of these systems can, however, be disturbed, amongst others, by chemical stressors. Fungicides might pose a particular risk as they can have negative effects on the involved microbial decomposers but may also affect shredders via both waterborne toxicity and their diet; the latter by toxic effects due to dietary exposure as a result of fungicides’ accumulation on leaf material and by negatively affecting fungal leaf decomposers, on which shredders’ nutrition heavily relies. The primary aim of this thesis was therefore to provide an in-depth assessment of the ecotoxicological implications of fungicides in a model decomposer-detritivore system using a tiered experimental approach to investigate (1) waterborne toxicity in a model shredder, i.e., Gammarus fossarum, (2) structural and functional implications in leaf-associated microbial communities, and (3) the relative importance of waterborne and diet-related effects for the model shredder.
Additionally, knowledge gaps were tackled that were related to potential differences in the ecotoxicological impact of inorganic (also authorized for organic farming in large parts of the world) and organic fungicides, the mixture toxicity of these substances, the field-relevance of their effects, and the appropriateness of current environmental risk assessment (ERA).
In the course of this thesis, major differences in the effects of inorganic and organic fungicides on the model decomposer-detritivore system were uncovered; e.g., the palatability of leaves for G. fossarum was increased by inorganic fungicides but deteriorated by organic substances. Furthermore, non-additive action of fungicides was observed, rendering mixture effects of these substances hardly predictable. While the relative importance of the waterborne and diet-related effect pathway for the model shredder seems to depend on the fungicide group and the exposure concentration, it was demonstrated that neither path must be ignored due to additive action. Finally, it was shown that effects can be expected at field-relevant fungicide levels and that current ERA may provide insufficient protection for decomposer-detritivore systems. To safeguard aquatic ecosystem functioning, this thesis thus recommends including leaf-associated microbial communities and long-term feeding studies using detritus feeders in ERA testing schemes, and identifies several knowledge gaps whose filling seems mandatory to develop further reasonable refinements for fungicide ERA.

The work presented in this thesis investigated interactions of selected biophysical processes that affect zooplankton ecology at smaller scales. In this endeavour, the extent of changes in swimming behaviour and fluid disturbances produced by swimming Daphnia in response to changing physical environments were quantified. In the first research question addressed within this context, size and energetics of hydrodynamic trails produced by Daphnia swimming in non-stratified still waters were characterized and quantified as a function of organisms’ size and their swimming patterns.
The results revealed that neither size nor the swimming pattern of Daphnia affects the width of induced trails or dissipation rates. Nevertheless, as the size and swimming velocity of the organisms increased, trail volume increased in proportional to the cubic power of Reynolds number, and the biggest trail volume was about 500 times the body volume of the largest daphnids. Larger spatial extent of fluid perturbation and prolonged period to decay caused by bigger trail volumes would play a significant role in zooplankton ecology, e.g. increasing the risk of predation.
The study also found that increased trail volume brought about significantly enhanced total dissipated power at higher Reynolds number, and the magnitudes of total dissipated power observed varied in the range of (1.3-10)X10-9 W.
Furthermore, this study provided strong evidence that swimming speed of Daphnia and total dissipated power in Daphnia trails exceeded those of some other selected zooplankton species.
In recognizing turbulence as an intrinsic environmental perturbation in aquatic habitats, this thesis also examined the response of Daphnia to a range of turbulence flows, which correspond to turbu-lence levels that zooplankton generally encounter in their habitats. Results indicated that within the range of turbulent intensities to which the Daphnia are likely to be exposed in their natural habitats, increasing turbulence compelled the organisms to enhance their swimming activity and swim-ming speed. However, as the turbulence increased to extremely high values (10-4 m2s-3), Daphnia began to withdraw from their active swimming behaviour. Findings of this work also demonstrated that the threshold level of turbulence at which animals start to alleviate from largely active swimming is about 10-6 m2s-3. The study further illustrated that during the intermediate range of turbu-lence; 10-7 - 10-6 m2s-3, kinetic energy dissipation rates in the vicinity of the organisms is consistently one order of magnitude higher than that of the background turbulent flow.
Swarming, a common conspicuous behavioural trait observed in many zooplankton species, is considered to play a significant role in defining freshwater ecology of their habitats from food exploitation, mate encountering to avoiding predators through hydrodynamic flow structures produced by them, therefore, this thesis also investigated implications of Daphnia swarms at varied abundance & swarm densities on their swimming kinematics and induced flow field.
The results showed that Daphnia aggregated in swarms with swarm densities of (1.1-2.3)x103 L-1, which exceeded the abundance densities by two orders of magnitude (i.e. 1.7 - 6.7 L-1). The estimated swarm volume decreased from 52 cm3 to 6.5 cm3, and the mean neighbouring distance dropped from 9.9 to 6.4 body lengths. The findings of this work also showed that mean swimming trajectories were primarily horizontal concentric circles around the light source. Mean flow speeds found to be one order of magnitude lower than the corresponding swimming speeds of Daphnia. Furthermore, this study provided evidences that the flow fields produced by swarming Daphnia differed considerably between unidirectional vortex swarming and bidirectional swimming at low and high abundances respectively.

Reactive local algorithms are distributed algorithms which suit the needs of battery-powered, large-scale wireless ad hoc and sensor networks particularly well. By avoiding both unnecessary wireless transmissions and proactive maintenance of neighborhood tables (i.e., beaconing), such algorithms minimize communication load and overhead, and scale well with increasing network size. This way, resources such as bandwidth and energy are saved, and the probability of message collisions is reduced, which leads to an increase in the packet reception ratio and a decrease of latencies.
Currently, the two main application areas of this algorithm type are geographic routing and topology control, in particular the construction of a node's adjacency in a connected, planar representation of the network graph. Geographic routing enables wireless multi-hop communication in the absence of any network infrastructure, based on geographic node positions. The construction of planar topologies is a requirement for efficient, local solutions for a variety of algorithmic problems.
This thesis contributes to reactive algorithm research in two ways, on an abstract level, as well as by the introduction of novel algorithms:
For the very first time, reactive algorithms are considered as a whole and as an individual research area. A comprehensive survey of the literature is given which lists and classifies known algorithms, techniques, and application domains. Moreover, the mathematical concept of O- and Omega-reactive local topology control is introduced. This concept unambiguously distinguishes reactive from conventional, beacon-based, topology control algorithms, serves as a taxonomy for existing and prospective algorithms of this kind, and facilitates in-depth investigations of the principal power of the reactive approach, beyond analysis of concrete algorithms.
Novel reactive local topology control and geographic routing algorithms are introduced under both the unit disk and quasi unit disk graph model. These algorithms compute a node's local view on connected, planar, constant stretch Euclidean and topological spanners of the underlying network graph and route messages reactively on these spanners while guaranteeing the messages' delivery. All previously known algorithms are either not reactive, or do not provide constant Euclidean and topological stretch properties. A particularly important partial result of this work is that the partial Delaunay triangulation (PDT) is a constant stretch Euclidean spanner for the unit disk graph.
To conclude, this thesis provides a basis for structured and substantial research in this field and shows the reactive approach to be a powerful tool for algorithm design in wireless ad hoc and sensor networking.

In Part I: "The flow-decomposition problem", we introduce and discuss the flow-decomposition problem. Given a flow F, this problem consists of decomposing the flow into a set of paths optimizing specific properties of those paths. We introduce different types of decompositions, such as integer decompositions and alpha-decompositions, and provide two formulations of the set of feasible decompositions.
We show that the problem of minimizing the longest path in a decomposition is NP-hard, even for fractional solutions. Then we develop an algorithm based on column generation which is able to solve the problem.
Tight upper bounds on the optimal objective value help to improve the performance.
To find upper bounds on the optimal solution for the shortest longest path problem, we develop several heuristics and analyze their quality. On pearl graphs we prove a constant approximation ratio of 2 and 3 respectively for all heuristics. A numerical study on random pearl graphs shows that the solutions generated by the heuristics are usually much better than this worst-case bound.
In Part II: "Construction and analysis of evacuation models using flows over time", we consider two optimization models in the context of evacuation planning. The first model is a parameter-based quickest flow model with time-dependent supply values. We give a detailed description of the network construction and of how different scenarios are modeled by scenario parameters. In a second step we analyze the effect of the scenario parameters on the evacuation time. Understanding how the different parameters influence the evacuation time allows us to provide better advice for evacuation planning and allows us to predict evacuation times without solving additional optimization problems. To understand the effect of the time-dependent supply values, we consider the quickest path problem with time-dependent supply values and provide a solution algorithm. The results from this consideration are generalized to approximate the behavior of the evacuation times in the context of quickest flow problems.
The second model we consider is a path-based model for evacuation in the presence of a dynamic cost function. We discuss the challenges of this model and provide ideas for how to approach the problem from different angles. We relate the problem to the flow-decomposition problem and consider the computation of evacuation paths with dynamic costs for large capacities. For the latter method we provide heuristics to find paths and compare them to the optimal solutions by applying the methods to two evacuation scenarios. An analysis shows that the paths generated by the heuristic yield close to optimal solutions and in addition have several desirable properties for evacuation paths which are not given for the optimal solution.

While reading this sentence, you probably gave (more or less deliberately) instructions to approximately 100 to 200 muscles of your body. A sceptical face or a smile, your fingers scrolling through the text or holding a printed version of this work, holding your head, sitting, and much more.
All these processes take place almost automatically, so they seem to be no real achievement. In the age of digitalization it is a defined goal to transfer human (psychological and physiological) behavior to machines (robots). However, it turns out that it is indeed laborious to obtain human facial expression or walking from robots. To optimize this transfer, a deeper understanding of a muscle's operating principle is needed (and of course an understanding of the human brain, which will, however, not be part of this thesis).
A human skeletal muscle can be shortened willingly, but not lengthened, thereto it takes an antagonist. The muscle's change in length is dependent on the incoming stimulus from the central nervous system, the current length of the muscle itself, and certain muscle--specific quantities (parameters) such as the maximum force. Hence, a muscle can be mathematically described by a differential equation (or more exactly a coupled differential--algebraic system, DAE), whose structure will be revealed in the following chapters. The theory of differential equations is well-elaborated. A multitude of applicable methods exist that may not be known by muscle modelers. The purpose of this work is to link the methods from applied mathematics to the actual application in biomechanics.
The first part of this thesis addresses stability theory. Let us remember the prominent example from middle school physics, in which the resting position of a ball was obviously less susceptible towards shoves when lying in a bowl rather than balancing at the tip of a hill. Similarly, a dynamical (musculo-skeletal) system can attain equilibrium states that react differently towards perturbations.
We are going to compute and classify these equilibria.
In the second part, we investigate the influence of individual parameters on model equations or more exactly their solutions. This method is known as sensitivity analysis.
Take for example the system "car" containing a value for the quantity "pressure on the break pedal while approaching a traffic light". A minor deviation of this quantity upward or downward may lead to an uncomfortable, abrupt stop or even to a collision, instead of a smooth stop with a sufficient gap.
The considered muscle model contains over 20 parameters that, if changed slightly, have varying effects on the model equation solutions at different instants of time. We will investigate the sensitivity of those parameters regarding different sub--models, as well as the whole model among different dynamical boundary conditions.
The third and final part addresses the \textit{optimal control} problem (OCP).
The muscle turns a nerve impulse (input or control) into a length change and therefore a force response (output). This forward process is computable by solving the respective DAE. The reverse direction is more difficult to manage. As an everyday example, the OCP is present regarding self-parking cars, where a given path is targeted and the controls are the position of the
steering wheel as well as the gas pedal.
We present two methods of solving OCPs in muscle modeling: the first is a conjunction of variational calculus and optimization in function spaces, the second is a surrogate-based optimization.