Thousands of chemicals from daily use are being discharged from civilization into the water cycle via different pathways. Ingredients of personal care products, detergents, pharmaceuticals, pesticides, and industrial chemicals thus find their way into the aquatic ecosystems and may cause adverse impacts on the ecology. Pharmaceuticals for instance, represent a central group of anthropogenic chemicals, because of their designed potency to interfere with physiological functions in organisms. Ecotoxicological effects from pharmaceutical burden have been verified in the past. Therapeutic groups with pronounced endocrine disrupting potentials such as steroid hormones gain increasing focus in environmental research as it was reported that they cause endocrine disruption in aquatic organisms even when exposed to environmentally relevant concentrations. This thesis considers the comprehensive investigation of the occurrence of corticosteroids and progestogens in wastewater treatment plant (WWTP) effluents and surface waters as well as the elucidation of the fate and biodegradability of these steroid families during activated sludge treatment. For the first goal of the thesis, a robust and highly sensitive analytical method based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed in order to simultaneously determine the occurrence of around 60 mineralocorticoids, glucocorticoids and progestogens in the aquatic environment. A special focus was set to the compound selection due to the diversity of marketed synthetic steroids. Some analytical challenges have been approved by individual approaches regarding sensitivity enhancement and compound stabilities. These results may be important for further research in environmental analysis of steroid hormones. Reliable and low quantification limits are the perquisite for the determination of corticosteroids and progestogens at relevant concentrations due to low consumption volumes and simultaneously low effect-based trigger values. Achieved quantification limits for all target analytes ranged between 0.02 ng/L and 0.5 ng/L in surface water and 0.05 ng/L to 5 ng/L in WWTP effluents. This sensitivity enabled the detection of three mineralocorticoids, 23 glucocorticoids and 10 progestogens within the sampling campaign around Germany. Many of them were detected for the first time in the environment, particularly in Germany and the EU. To the best of our knowledge, this in-depth steroid screening provided a good overview of single steroid burden and allowed for the identification of predominantly steroids of each steroid type analyzed for the first time. The frequent detection of highly potent synthetic steroids (e.g. triamcinolone acetonide, clobetasol propionate, betamethasone valerate, dienogest, cyproterone acetate) highlighted insufficient removal during conventional Summary wastewater treatment and indicated the need for regulation to control their emission since the steroid concentrations were found to be above the reported effect-based trigger values for biota. Overall, the study revealed reliable environmental data of poorly or even not analyzed steroids. The results complement the existing knowledge in this field but also providednew information which can beused particularly for compound prioritization in ecotoxicological research and environmental analysis. Based on the data obtained from the monitoring campaign, incubation experiments were conducted to enable the comparison of the biodegradability and transformation processes in activated sludge treatment for structure-related steroids under aerobic and standardized experimental conditions. The compounds were accurately selected to cover manifold structural moieties of commonly used glucocorticoids, including non-halogenated and halogenated steroids, their mono- and diesters, and several acetonide-type steroids. This approach allowed for a structure-based interpretation of the results. The obtained biodegradation rate constants suggested large variations in the biodegradability (half-lifes ranged from < 0.5 h to > 14 d). An increasing stability was identified in the order from non-halogenated steroids (e.g. hydrocortisone), over 9α-halogenated steroids (e.g. betamethasone), to C17-monoesters (e.g. betamethasone 17-valerate, clobetasol propionate), and finally to acetonides (e.g. triamcinolone acetonide), thus suggesting a strong relationship of the biodegradability with the glucocorticoid structure. Some explanations for this behavior have been received by identifying the transformation products (TPs) and elucidating individual transformation pathways. The results revealed the identification of the likelihood of transformation reactions depending on the chemical steroid structure for the first time. Among the identified TPs, the carboxylates (e.g. TPs of fluticasone propionate, triamcinolone acetonide) have been shown persistency in the subsequent incubation experiments. The newly identified TPs furthermore were frequently detected in the effluents of full-scale wastewater treatment plants. These findings emphasized i) the transferability of the lab-scale degradation experiments to real world and that ii) insufficient removals may cause adverse effects in the aquatic environment due to the ability of the precursor steroids and TPs to interact with the endocrine system in biota. For the last goal, the conceptual study for glucocorticoids was applied to progestogens. Here, two sub-types of the steroid family frequently used for hormonal contraception were selected (17α-hydroxyprogesterone and 19-norstestosterone type). The progestogens showed a fast and complete degradation within six hours, and thus empathizes pronounced biodegradability. However, cyproterone acetate and dienogest Summary have been found to be more recalcitrant in activated sludge treatment. This was consistent with their ubiquitously occurrence during the previous monitoring campaign. The elucidation of TPs again revealed some crucial information regarding the observed behavior and highlighted furthermore the formation of hazardous TPs. It was shown that 19-nortestosterone type steroids are able to undergo aromatization at ring A in contact with activated sludge, leading to the formation of estrogen-like TPs with a phenolic moiety at ring A. In the case of norethisterone the formation of 17α-ethinylestradiol was confirmed, which is a well-known potent synthetic estrogen with elevated ecotoxicological potency. Thus, the results indicated for the very first time an unknown source of estrogenic compounds, particularly for 17α-ethinylestradiol. In conclusion, some steroids were found to be very stable in activated sludge treatment, others degrade well, and others which do degrade but predominantly to active TPs depending on their chemical structure. Fluorinated acetal steroids such as triamcinolone acetonide and fluocinolone acetonide are poorly biodegradable, which is reflected in high concentrations detected ubiquitously in WWTP effluents. Endogenous steroids and their most related synthetic once such as hydrocortisone, prednisolone or 17α-hydroxyprogesterone are readily biodegradable. Regardless their high influent concentrations, they are almost completely removed in conventional WWTPs. Steroids between this range have been found to form elevated quantities of TPs which are partially still active, which particularly the case for betamethasone, fluticasone propionate, cyproterone acetate or dienogest. The thesis illustrates the need for an extensive evaluation of the environmental risks and carried out that corticosteroids and progestogens merit more attention in environmental regulatory and research than it is currently the case

Scientific and public interest in epidemiology and mathematical modelling of disease spread has increased significantly due to the current COVID-19 pandemic. Political action is influenced by forecasts and evaluations of such models and the whole society is affected by the corresponding countermeasures for containment. But how are these models structured? Which methods can be used to apply them to the respective regions, based on real data sets? These questions are certainly not new. Mathematical modelling in epidemiology using differential equations has been researched for quite some time now and can be carried out mainly by means of numerical computer simulations. These models are constantly being refinded and adapted to corresponding diseases. However, it should be noted that the more complex a model is, the more unknown parameters are included. A meaningful data adaptation thus becomes very diffcult. The goal of this thesis is to design applicable models using the examples of COVID-19 and dengue, to adapt them adequately to real data sets and thus to perform numerical simulations. For this purpose, first the mathematical foundations are presented and a theoretical outline of ordinary differential equations and optimization is provided. The parameter estimations shall be performed by means of adjoint functions. This procedure represents a combination of static and dynamical optimization. The objective function corresponds to a least squares method with L2 norm which depends on the searched parameters. This objective function is coupled to constraints in the form of ordinary differential equations and numerically minimized, using Pontryagin's maximum (minimum) principle and optimal control theory. In the case of dengue, due to the transmission path via mosquitoes, a model reduction of an SIRUV model to an SIR model with time-dependent transmission rate is performed by means of time-scale separation. The SIRUV model includes uninfected (U) and infected (V ) mosquito compartments in addition to the susceptible (S), infected (I) and recovered (R) human compartments, known from the SIR model. The unknwon parameters of the reduced SIR model are estimated using data sets from Colombo (Sri Lanka) and Jakarta (Indonesia). Based on this parameter estimation the predictive power of the model is checked and evaluated. In the case of Jakarta, the model is additionally provided with a mobility component between the individual city districts, based on commuter data. The transmission rates of the SIR models are also dependent on meteorological data as correlations between these and dengue outbreaks have been demonstrated in previous data analyses. For the modelling of COVID-19 we use several SEIRD models which in comparison to the SIR model also take into account the latency period and the number of deaths via exposed (E) and deaths (D) compartments. Based on these models a parameter estimation with adjoint functions is performed for the location Germany. This is possible because since the beginning of the pandemic, the cumulative number of infected persons and deaths are published daily by Johns Hopkins University and the Robert-Koch-Institute. Here, a SEIRD model with a time delay regarding the deaths proves to be particularly suitable. In the next step, this model is used to compare the parameter estimation via adjoint functions with a Metropolis algorithm. Analytical effort, accuracy and calculation speed are taken into account. In all data fittings, one parameter each is determined to assess the estimated number of unreported cases.

Habitat loss and fragmentation due to climate and land-use change are among the biggest threats to biodiversity, as the survival of species relies on suitable habitat area and the possibility to disperse between different patches of habitat. To predict and mitigate the effects of habitat loss, a better understanding of species dispersal is needed. Graph theory provides powerful tools to model metapopulations in changing landscapes with the help of habitat networks, where nodes represent habitat patches and links indicate the possible dispersal pathways between patches. This thesis adapts tools from graph theory and optimisation to study species dispersal on habitat networks as well as the structure of habitat networks and the effects of habitat loss. In chapter 1, I will give an introduction to the thesis and the different topics presented in this thesis. Chapter 2 will then give a brief summary of tools used in the thesis. In chapter 3, I present our model on possible range shifts for a generic species. Based on a graph-based dispersal model for a generic aquatic invertebrate with a terrestrial life stage, we developed an optimisation model that models dispersal directed to predefined habitat patches and yields a minimum time until these patches are colonised with respect to the given landscape structure and species dispersal capabilities. We created a time-expanded network based on the original habitat network and solved a mixed integer program to obtain the minimum colonisation time. The results provide maximum possible range shifts, and can be used to estimate how fast newly formed habitat patches can be colonised. Although being specific for this simulation model, the general idea of deriving a surrogate can in principle be adapted to other simulation models. Next, in chapter 4, I present our model to evaluate the robustness of metapopulations. Based on a variety of habitat networks and different generic species characterised by their dispersal traits and habitat demands, we modeled the permanent loss of habitat patches and subsequent metapopulation dynamics. The results show that species with short dispersal ranges and high local-extinction risks are particularly vulnerable to the loss of habitat across all types of networks. On this basis, we then investigated how well different graph-theoretic metrics of habitat networks can serve as indicators of metapopulation robustness against habitat loss. We identified the clustering coefficient of a network as the only good proxy for metapopulation robustness across all types of species, networks, and habitat loss scenarios. Finally, in chapter 5, I utilise the results obtained in chapter 4 to identify the areas in a network that should be improved in terms of restoration to maximise the metapopulation robustness under limited resources. More specifically, we exploit our findings that a network’s clustering coefficient is a good indicator for metapopulation robustness and develop two heuristics, a Greedy algorithm and a deducted Lazy Greedy algorithm, that aim at maximising the clustering coefficient of a network. Both algorithms can be applied to any network and are not specific to habitat networks only. In chapter 6, I will summarize the main findings of this thesis, discuss their limitations and give an outlook of future research topics. Overall this thesis develops frameworks to study the behaviour of habitat networks and introduces mathematical tools to ecology and thus narrows the gap between mathematics and ecology. While all models in this thesis were developed with a focus on aquatic invertebrates, they can easily be adapted to other metapopulations.

Ray tracing acceleration through dedicated data structures has long been an important topic in computer graphics. In general, two different approaches are proposed: spatial and directional acceleration structures. The thesis at hand presents an innovative combined approach of these two areas, which enables a further acceleration of the tracing process of rays. State-of-the-art spatial data structures are used as base structures and enhanced by precomputed directional visibility information based on a sophisticated abstraction concept of shafts within an original structure, the Line Space. In the course of the work, novel approaches for the precomputed visibility information are proposed: a binary value that indicates whether a shaft is empty or non-empty as well as a single candidate approximating the actual surface as a representative candidate. It is shown how the binary value is used in a simple but effective empty space skipping technique, which allows a performance gain in ray tracing of up to 40% compared to the pure base data structure, regardless of the spatial structure that is actually used. In addition, it is shown that this binary visibility information provides a fast technique for calculating soft shadows and ambient occlusion based on blocker approximations. Although the results contain a certain inaccuracy error, which is also presented and discussed, it is shown that a further tracing acceleration of up to 300% compared to the base structure is achieved. As an extension of this approach, the representative candidate precomputation is demonstrated, which is used to accelerate the indirect lighting computation, resulting in a significant performance gain at the expense of image errors. Finally, techniques based on two-stage structures and a usage heuristic are proposed and evaluated. These reduce memory consumption and approximation errors while maintaining the performance gain and also enabling further possibilities with object instancing and rigid transformations. All performance and memory values as well as the approximation errors are measured, presented and discussed. Overall, the Line Space is shown to result in a considerate improvement in ray tracing performance at the cost of higher memory consumption and possible approximation errors. The presented findings thus demonstrate the capability of the combined approach and enable further possibilities for future work.

Enterprise Collaboration Systems (ECS) have become substantial for computer-mediated communication and collaboration among employees in organisations. As ECS combine features from social media and traditional groupware, a growing number of organisations implement ECS to facilitate collaboration among employees. Consequently, ECS form the core of the digital workplace. Thus, the activity logs of ECS are particularly valuable since they provide a unique opportunity for observing and analysing collaboration in the digital workplace. Evidence from academia and practice demonstrates that there is no standardised approach for the analysis of ECS logs and that practitioners struggle with various barriers. Because current ECS analytics tools only provide basic features, academics and practitioners cannot leverage the full potential of the activity logs. As ECS activity logs are a valuable source for understanding collaboration in the digital workplace, new methods and metrics for their analysis are required. This dissertation develops Social Collaboration Analytics (SCA) as a method for measuring and analysing collaboration activities in ECS. To address the existing limitations in academia and practice and to contribute a method and structures for applying SCA in practice, this dissertation aims to answer two main research questions: 1. What are the current practices for measuring collaboration activities in Enterprise Collaboration Systems? 2. How can Social Collaboration Analytics be implemented in practice? By answering the research questions, this dissertation seeks to (1) establish a broad thematic understanding of the research field of SCA and (2) to develop SCA as a structured method for analysing ac-tivity logs of ECS. As part of the first research question, this dissertation documents the status quo of SCA in the academic literature and practice. By answering the second research question, this dissertation contributes the SCA framework (SCAF), which guides the practical application of SCA. SCAF is the main contribution of this dissertation. The framework was developed based on findings from an analysis of 86 SCA studies, results from 6 focus groups and results from a survey among 27 ECS user companies. The phases of SCAF were derived from a comparison of established process models for data mining and business intelligence. The eight phases of the framework contain detailed descriptions, working steps, and guiding questions, which provide a step by step guide for the application of SCA in practice. Thus, academics and practitioners can benefit from using the framework. The constant evaluation of the research outcomes in focus groups ensures both rigour and relevance. This dissertation employs a qualitative-dominant mixed-methods approach. As part of the university-industry collaboration initiative IndustryConnect, this research has access to more than 30 leading ECS user companies. Being built on a key case study and a series of advanced focus groups with representatives of user companies, this dissertation can draw from unique insights from practice as well as rich data with a longitudinal perspective.

We are living in a world where environmental crises come to a head. To curb aggravation of these problems, a socio-ecological transformation within society is needed, going along with human behavior change. How to encourage such behavior changes on an individual level is the core issue of this dissertation. It takes a closer look at the role of individuals as consumers resulting in purchase decisions with more or less harmful impact on the environment. By using the example of plastic pollution, it takes up a current environmental problem and focuses on an understudied behavioral response to this problem, namely reduction behavior. More concrete, this dissertation examines which psychological factors can encourage the mitigation of plastic packaging consumption. Plastic packaging accounts for the biggest amount of current plastic production and is associated with products of daily relevance. Despite growing awareness of plastic pollution in society, behavioral responses do not follow accordingly and plastic consumption is still very high. As habits are often a pitfall when implementing more resource-saving behavior, this dissertation further examines if periods of discontinuity can open a ’window of opportunity’ to break old habits and facilitate behavior change. Four manuscripts approach this matter from the gross to the subtle. Starting with a literature review, a summary of 187 studies addresses the topic of plastic pollution and human behavior from a societal-scientific perspective. Based on this, a cross-sectional study (N = 648) examines the deter-minants of plastic-free behavior intentions in the private-sphere and public-sphere by structural equation modeling. Two experimental studies in pre-post design build upon this, by integrating the determinants in intervention studies. In addition, it was evaluated if the intervention presented during Lent (N = 140) or an action month of ‘Plastic Free July’ (N = 366) can create a ‘window of opportunity’ to mitigate plastic packaging consumption. The literature review emphasized the need for research on behavioral solutions to reduce plastic consumption. The empirical results revealed moral and control beliefs to be the main determinants of reduction behavior. Furthermore, the time point of an intervention influenced the likelihood to try out the new behavior. The studies gave first evidence that a ‘window of opportunity’ can facilitate change towards pro-environmental behavior within the application field of plastic consumption. Theoretical and practical implications of creating the right opportunity for individuals to contribute to a socio-ecological transformation are finally discussed.

Water scarcity is already an omnipresent problem in many parts of the world, especially in sub-Saharan Africa. The dry years 2018 and 2019 showed that also in Germany water resources are finite. Projections and predictions for the next decades indicate that renewal rates of existing water resources will decline due the growing influence of climate change, but that water extraction rates will increase due to population growth. It is therefore important to find alternative and sustainable methods to make optimal use of the water resources currently available. For this reason, the reuse of treated wastewater for irrigation and recharge purposes has become one focus of scientific research in this field. However, it must be taken into account that wastewater contains so-called micropollutants, i.e., substances of anthropogenic origin. These are, e.g., pharmaceuticals, pesticides and industrial chemicals which enter the wastewater, but also metabolites that are formed in the human body from pharmaceuticals or personal care products. Through the treatment in wastewater treatment plants (WWTPs) as well as through chemical, biological and physical processes in the soil passage during the reuse of water, these micropollutants are transformed to new substances, known as transformation products (TPs), which further broaden the number of contaminants that can be detected within the whole water cycle. Despite the fact that the presence of human metabolites and environmental TPs in untreated and treated wastewater has been known for a many years, they are rarely included in common routine analysis methods. Therefore, a first goal of this thesis was the development of an analysis method based on liquid chromatography - tandem mass spectrometry (LC-MS/MS) that contains a broad spectrum of frequently detected micropollutants including their known metabolites and TPs. The developed multi-residue analysis method contained a total of 80 precursor micropollutants and 74 metabolites and TPs of different substance classes. The method was validated for the analysis of different water matrices (WWTP influent and effluent, surface water and groundwater from a bank filtration site). The influence of the MS parameters on the quality of the analysis data was studied. Despite the high number of analytes, a sufficient number of datapoints per peak was maintained, ensuring a high sensitivity and precision as well as a good recovery for all matrices. The selection of the analytes proved to be relevant as 95% of the selected micropollutants were detected in at least one sample. Several micropollutants were quantified that were not in the focus of other current multi-residue analysis methods (e.g. oxypurinol). The relevance of including metabolites and TPs was demonstrated by the frequent detection of, e.g., clopidogrel acid and valsartan acid at higher concentrations than their precursors, the latter even being detected in samples of bank filtrate water. By the integration of metabolites, which are produced in the body by biological processes, and biological and chemical TPs, the multi-residue analysis method is also suitable for elucidating degradation mechanisms in treatment systems for water reuse that, e.g., use a soil passage for further treatment. In the second part of the thesis, samples from two treatment systems based on natural processes were analysed: a pilot-scale above-ground sequential biofiltration system (SBF) and a full-scale soil aquifer treatment (SAT) site. In the SBF system mainly biological degradation was observed, which was clearly demonstrated by the detection of biological TPs after the treatment. The efficiency of the degradation was improved by an intermediate aeration, which created oxic conditions in the upper layer of the following soil passage. In the SAT system a combination of biodegradation and sorption processes occurred. By the different behaviour of some biodegradable micropollutants compared to the SBF system, the influence of redox conditions and microbial community was observed. An advantage of the SAT system over the SBF system was found in the sorption capacity of the natural soil. Especially positively charged micropollutants showed attenuation due to ionic interactions with negatively charged soil particles. Based on the physicochemical properties at ambient pH, the degree of removal in the investigated systems and the occurrence in the source water, a selection of process-based indicator substances was proposed. Within the first two parts of this thesis a micropollutant was frequently detected at elevated concentrations in WWTPs effluents, which was not previously in the focus of environmental research: the antidiabetic drug sitagliptin (STG). STG showed low degradability in biological systems and thus it was investigated to what extend chemical treatment by ozonation can ensure attenuation of it. STG contains an aliphatic primary amine as the principal point of attack for the ozone molecule. There is only limited information about the behaviour of this functional group during ozonation and thus, STG served as an example for other micropollutants containing aliphatic primary amines. A pH-dependent degradation kinetic was observed due to the protonation of the primary amine at lower pH values. At pH values in the range 6 - 8, which is typical for the environment and in WWTPs, STG showed degradation kinetics in the range of 103 M-1s-1 and thus belongs to the group of readily degradable substances. However, complete degradation can only be expected at significantly higher pH values (> 9). The transformation of the primary amine moiety into a nitro group was observed as the major degradation mechanism for STG during ozonation. Other mechanisms involved the formation of a diketone, bond breakages and the formation of trifluoroacetic acid (TFA). Investigations at a pilot-scale ozonation plant using the effluent of a biological degradation of a municipal WWTP as source water confirmed the results of the laboratory studies: STG could not be removed completely even at high ozone doses and the nitro compound was formed as the main TP and remained stable during further ozonation and subsequent biological treatment. It can therefore be assumed that under realistic conditions both a residual concentration of STG and the formed main TP as well as other stable TPs such as TFA can be detected in the effluents of a WWTP consisting of conventional biological treatment followed by ozonation and subsequent biological polishing steps.

Water is used in a way as if it were available infinitely. Droughts, increased rainfall or flooding already lead to water shortages and, thus, deprive entire population groups of the basis of their livelihoods. There is a growing fear that conflicts over water will increase, especially in arid climate zones, because life without water - whether for humans, animals or plants - is not possible. More than 60 % of the African population depend on land and water resources for their livelihoods through pastoralism, fishing and farming. The water levels of rivers and lakes are decreasing. Hence, the rural population which is dependent on land and water move towards water-rich and humid areas. This internal migration increases the pressure on available water resources. Driven by the desire to strengthen the economic development, African governments align their political agendas with the promotion of macro international and national economic projects. This doctoral thesis examines the complex interrelationships between water shortages, governance, vulnerability, adaptive capacity and violent and non-violent conflicts at Lake Naivasha in Kenya and Lake Wamala in Uganda. In order to satisfy the overall complexity, this doctoral thesis combines various theoretical and empirical aspects in which a variety of methods are applied to different geographical regions, across disciplines, and cultural and political boundaries. The investigation reveals that Lake Naivasha is more affected by violent conflicts than Lake Wamala. Reasons for this include population growth, historically grown ethnic conflicts, corruption and the preferential treatment of national and international economic actors. The most common conflict response tools are raiding and the blockage of water access. However, deathly encounters, destruction of property and cattle slaughtering are increasingly used to gain access to water and land. The insufficient implementation of the political system and the governments’ prioritization to foster economic development results, on the one hand, in the commercialization of water resources and increases, on the other hand, non-violent conflict between national and sub-national political actors. While corruption, economic favours and patronage defuse this conflict, resource access becomes more difficult for the local population. Resulting thereof, a final hypothesis is developed which states that the localization of the political conflict aggravates the water situation for the local population and, thereby, favours violent conflicts over water access and water use in water-rich areas.

Rivers play an important role in the global water cycle, support biodiversity and ecological integrity. However, river flow and thermal regimes are heavily altered in dammed rivers. These impacts are being exacerbated and become more apparent in rivers fragmented by multiple dams. Recent studies mainly focused on evaluating the cumulative impact of cascade reservoirs on flow or thermal regimes, but the role of upstream reservoirs in shaping the hydrology and hydrodynamics of downstream reservoirs remains poorly understood. To improve the understanding of the hydrodynamics in cascade reservoirs, long-term observational data are used in combination with numerical modeling to investigate the changes in flow and thermal regime in three cascade reservoirs at the upper reach of the Yangtze River. The three studied reservoirs are Xiluodu (XLD), Xiangjiaba (XJB) and Three Gorges Reservoir (TGR). In addition, the effects of single reservoir operation (at seasonal/daily time scale) on hydrodynamics are examined in a large tributary of TGR. The results show that the inflow of TGR has been substantially altered by the two upstream reservoirs with a higher discharge in spring and winter and a reduced peak flow in summer. XJB had no obvious contribution to the variations in inflow of TGR. The seasonal water temperature of TGR was also widely affected by the upstream two reservoirs, i.e., an increase in winter and decrease in spring, associated with a delay in water temperature rise and fall. These effects will probably be intensified in the coming years due to the construction of new reservoirs. The study also underlines the importance of reservoir operation in shaping the hydrodynamics of TGR. The seasonal dynamics of density currents in a tributary bay of TGR are closely related to seasonal reservoir operations. In addition, high-frequency water level fluctuations and flow velocity variations were observed in response to periodic tributary bay oscillations, which are driven by the diurnal discharge variations caused by the operation of TGR. As another consequence of operation of cascade reservoirs, the changes in TGR inflow weakened spring thermal stratification and caused warming in spring, autumn and winter. In response to this change, the intrusions from TGR occurred more frequently as overflow and earlier in spring, which caused a sharp reduction in biomass and frequency of phytoplankton blooms in tributary bays of TGR. This study suggests that high-frequency bay oscillations can potentially be used as an efficient management strategy for controlling algal blooms, which can be included in future multi-objective ecological conservation strategies.

Real-time operating systems for mixed-criticality systems must support different types of software, such as real-time applications and general purpose applications, and, at the same time, must provide strong spatial and temporal isolation between independent software components. Therefore, state-of-the-art real-time operating systems focus mainly on predictability and bounded worst-case behavior. However, general purpose operating systems such as Linux often feature more efficient---but less deterministic---mechanisms that significantly improve the average execution time. This thesis addresses the combination of the two contradicting requirements and shows thread synchronization mechanisms with efficient average-case behavior, but without sacrificing predictability and worst-case behavior. This thesis explores and evaluates the design space of fast paths in the implementation of typical blocking synchronization mechanisms, such as mutexes, condition variables, counting semaphores, barriers, or message queues. The key technique here is to avoid unnecessary system calls, as system calls have high costs compared to other processor operations available in user space, such as low-level atomic synchronization primitives. In particular, the thesis explores futexes, the state-of-the-art design for blocking synchronization mechanisms in Linux that handles the uncontended case of thread synchronization by using atomic operations in user space and calls into the kernel only to suspend and wake up threads. The thesis also proposes non-preemptive busy-waiting monitors that use an efficient priority ceiling mechanism to prevent the lock holder preemption problem without using system calls, and according low-level kernel primitives to construct efficient wait and notify operations. The evaluation shows that the presented approaches improve the average performance comparable to state-of-the-art approaches in Linux. At the same time, a worst-case timing analysis shows that the approaches only need constant or bounded temporal overheads at the operating system kernel level. Exploiting these fast paths is a worthwhile approach when designing systems that not only have to fulfill real-time requirements, but also best-effort workloads.

Schizophrenia is a chronic mental health disorder, which changes rapidly the life of the persons and their families, who suffer from it. It causes high biological and psychological vulnerability as well as cognitive, emotional and behavioral disorders. Nowadays, evidence-based pharmacotherapy and psychotherapy are available aiming the rehabilitation and recovery of individuals with schizophrenia. A democratic society is obliged to give these people the opportunity to have an access to those treatments. The following three published studies present this dissertation thesis and have a common focus on the implementation of evidence-based psychotherapy in individuals with schizophrenia. The first study evaluates the efficacy of the Integrated Psychological Therapy (IPT) in Greece, one of the most evaluated rehabilitation programs. IPT was compared to Treatment as Usual (TAU) in a randomized controlled trial (RCT) with 48 individuals with schizophrenia. Significant effects favouring IPT were found in working memory, in social perception, in negative symptoms, in general psychopathology and in insight. This study supports evidence for the efficacy of IPT in Greece. The second study evaluates a second hypothesis, when IPT is more and less effective regarding treatment resistant schizophrenia (TRS) and non treatment resistant schizophrenia (NTRS). It is a part of the first paper. Significant effects favouring NTRS were found for verbal memory, for symptoms, for functioning and quality of life. Effect sizes showed superiority of NTRS in comparison to TRS. IPTTRS showed on the other side some significant improvements. This study presents the initial findings of a larger study to be conducted internationally for the first time. The third study is a systematic review, which aims to evaluate the efficacy of Cognitive Behavioral Therapy (CBT), of Meta Cognitive Therapy (MCT), Metacognitive Training (MCTR), Metacognitive Reflection and Insight Therapy (MERIT), of various Rehabilitation Programs and Recovery Programs in individuals with schizophrenia. 41 RCTs and 12 Case Studies were included. The above interventions are efficacious in the improvement of cognitions, symptoms, functional outcome, insight, self-esteem, comorbid disorders and metacognitive capacity. The three studies provide insight regarding the importance of evidence-based psychotherapy in persons with schizophrenia leading to recovery and reintegration into society. Future RCTs with larger samples and long-term follow up, combining evidence-based psychotherapies for individuals with schizophrenia need to be done.

The Material Point Method (MPM) has proven to be a very capable simulation method in computer graphics that is able to model materials that were previously very challenging to animate [1, 2]. Apart from simulating singular materials, the simulation of multiple materials that interact with each other introduces new challenges. This is the focus of this thesis. It will be shown that the self-collision capabilities of the MPM can naturally handle multiple materials interacting in the same scene on a collision basis, even if the materials use distinct constitutive models. This is then extended by porous interaction of materials as in[3], which also integrates easily with MPM.It will furthermore be shown that regular single-grid MPM can be viewed as a subset of this multi-grid approach, meaning that its behavior can also be achieved if multiple grids are used. The porous interaction is generalized to arbitrary materials and freely changeable material interaction terms, yielding a flexible, user-controllable framework that is independent of specific constitutive models. The framework is implemented on the GPU in a straightforward and simple way and takes advantage of the rasterization pipeline to resolve write-conflicts, resulting in a portable implementation with wide hardware support, unlike other approaches such as [4].

In Western personnel psychology, competence- and control beliefs (CCB) are of widespread use to predict typical work-related outcomes such as well-being, achievement motivation and job performance. The predictive value and comprehension of CCB in East Africa is examined, comparing a Kenyan target with a German source sample (N=143). Responses to personality tests included qualitative interviews on items capturing control orientations (self concept of ability, internality, powerful others, and chance). Linear regression analyses, explorative factor analyses, and a procrustean target rotation showed comparable, but not fully congruent predictability for the connection of CCB with outcome variables. Factor structures of control responses did not resemble each other sufficiently. Content analyses including scale intercorrelations, quantitative and qualitative item information served for an explanation of this predictability gap, specifying differences between the German and Kenyan samples that are associated with the social-relational domain of personality. Results fit in the picture depicted by the African Ubuntu philosophy and the South African Personality Inventory project (SAPI), both emphasizing social-relational aspects. In particular, the powerful others control orientation diverges the most between the cultures. Being perceived as a negative and external factor in the German sample with its individualistic culture, powerful others is of mixed emotional quality and just as well internal, when asked for in the Kenyan sample with its Ubuntu-worldview. An uncritical transfer of CCB measures from one culture to another is assumed to be inappropriate. More emic-etic based research is demanded concerning intra- and intercultural variability of CCB to depict a transcultural applicable model.

Interest in crowdfunding has been increasing in recent years, both from the economy and the scientific community. Besides artists and entrepreneurs, researchers are now also funding their projects through many small contributions from the crowd. However, the perceived use in Germany does not reflect the benefits of a crowdfunding campaign, especially in international comparison. This study investigates this issue by identifying the motives and barriers for crowdfunding in order to formulate recommendations for research institutions to encourage the use of crowdfunding. By means of a literature review, first insights are gained which are then used to conduct qualitative interviews with eleven researchers who successfully completed a crowdfunding campaign. The results indicate that researchers in Germany use crowdfunding primarily to raise awareness for the subject and the scientific community in general. The initial assumption of the speed of crowdfunding as a motive was contradicted by the experts. The major barriers are the immense effort involved in a campaign and the lack of reputation for the concept of crowdfunding by German scientists. In addition, only subjects and projects with a high public relevance and funding volume of up to five digits are recommended for crowdfunding. Furthermore, the public exposure of the experts during the campaign was identified as an additional barrier. These findings lead to three recommendations for research institutions to increase the use of crowdfunding: Firstly, universities should raise awareness for the subject of crowdfunding as an additional form of research funding and highlight the benefits of a crowdfunding campaign. Secondly, universities should cooperate with crowdfunding partners and utilize the networking capacities of a university. Lastly, universities should provide support to distribute the workload among interdisciplinary teams in order to enhance the effortreturn ratio of a crowdfunding campaign. The chosen methodology and the scope of the thesis enable further research that might examine the perspective of the universities and the conditions in other countries. In addition, a largescale quantitative survey is required to validate the identified concepts statistically.

Initial goal of the current dissertation was the determination of image-based biomarkers sensitive for neurodegenerative processes in the human brain. One such process is the demyelination of neural cells characteristic for Multiple sclerosis (MS) - the most common neurological disease in young adults for which there is no cure yet. Conventional MRI techniques are very effective in localizing areas of brain tissue damage and are thus a reliable tool for the initial MS diagnosis. However, a mismatch between the clinical fndings and the visualized areas of damage is observed, which renders the use of the standard MRI diffcult for the objective disease monitoring and therapy evaluation. To address this problem, a novel algorithm for the fast mapping of myelin water content using standard multiecho gradient echo acquisitions of the human brain is developed in the current work. The method extents a previously published approach for the simultaneous measurement of brain T1, T∗ 2 and total water content. Employing the multiexponential T∗ 2 decay signal of myelinated tissue, myelin water content is measured based on the quantifcation of two water pools (myelin water and rest) with different relaxation times. Whole brain in vivo myelin water content maps are acquired in 10 healthy controls and one subject with MS. The in vivo results obtained are consistent with previous reports. The acquired quantitative data have a high potential in the context of MS. However, the parameters estimated in a multiparametric acquisition are correlated and constitute therefore an ill-posed, nontrivial data analysis problem. Motivated by this specific problem, a new data clustering approach is developed called Nuclear Potential Clustering, NPC. It is suitable for the explorative analysis of arbitrary dimensional and possibly correlated data without a priori assumptions about its structure. The developed algorithm is based on a concept adapted from nuclear physics. To partition the data, the dynamic behavior of electrically even charged nucleons interacting in a d-dimensional feature space is modeled. An adaptive nuclear potential, comprised of a short-range attractive (Strong interaction) and a long-range repulsive term (Coulomb potential), is assigned to each data point. Thus, nucleons that are densely distributed in space fuse to build nuclei (clusters), whereas single point clusters are repelled (noise). The algorithm is optimized and tested in an extensive study with a series of synthetic datasets as well as the Iris data. The results show that it can robustly identify clusters even when complex configurations and noise are present. Finally, to address the initial goal, quantitative MRI data of 42 patients are analyzed employing NPC. A series of experiments with different sets of image-based features show a consistent grouping tendency: younger patients with low disease grade are recognized as cohesive clusters, while those of higher age and impairment are recognized as outliers. This allows for the definition of a reference region in a feature space associated with phenotypic data. Tracking of the individual's positions therein can disclose patients at risk and be employed for therapy evaluation.

The three biodegradable polymers polylactic acid (PLA), polyhydroxybutyrate (PHB) and polybutylene adipate terephthalate (PBAT) were coated with hydrogenated amorphous carbon layers (a-C:H) in the context of this thesis. A direct alignment of the sample surface to the source was chosen, resulting in the deposition of a robust, r-type a-C:H. At the same time, a partly covered silicon wafer was placed together with the polymers in the coating chamber and was coated. Silicon is a hard material and serves as a reference for the applied layers. Due to the hardness of the material, no mixed phase occurs between the substrate and the applied layer (no interlayer formation). In addition, the thickness of the applied layer can be estimated with the help of the silicon sample. The deposition of the layer was realized by radio frequency plasma enhanced chemical vapor deposition (RF-PECVD). For the coating the samples were pre-treated with an oxygen plasma. Acetylene was used as precursor gas for the plasma coating. Coatings with increasing thickness in 50 nm steps from 0-500 nm were realised. The surface analysis was performed using several techniques: The morphology and layer stability were analyzed with scanning electron microscopy (SEM) measurements. The wettability was determined by contact angle technique. In addition, the contact angles provide macroscopic information about the bond types of the carbon atoms present on the surface. For microscopic analysis of the chemical composition of the sample and layer surfaces, diffuse reflectance Fourier transform infrared spectroscopy (DRIFT) as well as synchrotron based X-ray photon spectroscopy (XPS) and near edge X-ray absorption fine structure spectroscopy (NEXAFS) were used. All coated polymers showed several cases of layer failure due to internal stress in the layers. However, these were at different layer thicknesses, so there was a substrate effect. In addition, it is visible in the SEM images that the coatings of PLA and PHB can cause the applied layer to wave, the so-called cord buckling. This does not occur with polymer PBAT, which indicates a possible better bonding of the layer to the polymer. The chemical analyses of the layer surfaces show for each material a layer thickness dependent ratio of sp² to sp³ bonds of carbon, which alternately dominate the layer. In all polymers, the sp³ bond initially dominates, but the sp² to sp³ ratio changes at different intervals. Although the polymers were coated in the same plasma, i.e. the respective layer thicknesses (50 nm, 100 nm, ...) were applied in the same plasma process, the respective systems differed considerably from each other. A substrate effect is therefore demonstrably present. In addition, it was found that a change in the dominant bond from sp³ to sp² is an indication ofan upcoming layer failure of the a-C:H layer deposited on the polymer. In the case of PLA, this occurs immediately with change to sp² as the dominant bond; in the case of PHB and PBAT, this occurs with different delay to increased layer thicknesses (at PHB 100 nm, at PBAT approx. 200 nm. Overall, this thesis shows that there is a substrate effect in the coating of the biodegradable polymers PLA, PHB and PBAT, since despite the same coating there is a different chemical composition of the surface at the respective layer thicknesses. In addition, a layer failure can be predicted by analyzing the existing bond.

Amphibian populations are declining worldwide for multiple reasons such as habitat destruction and climate change. An example for an endangered European amphibian is the yellow-bellied toad Bombina variegata. Populations have been declining for decades, particularly at the northern and western range margin. One of the extant northern range centres is the Westerwald region in Rhineland-Palatinate, Germany. To implement informed conservation activities on this threatened species, knowledge of its life-history strategy is crucial. This study therefore focused on different developmental stages to test predictions of life-history theory. It addressed (1) developmental, (2) demographic and (3) genetic issues of Bombina variegata as a model organism: (1) Carry-over effects from larval environment to terrestrial stages and associated vulnerability to predators were investigated using mesocosm approaches, fitness tests and predation trials. (2) The dynamics and demography of B. variegata populations were studied applying a capture-mark-recapture analysis and skeletochronology. The study was complemented through (3) an analysis of genetic diversity and structuring of B. variegata populations using 10 microsatellite loci. In order to reveal general patterns and characteristics among B. variegata populations, the study focused on three geographical scales: local (i.e. a former military training area), regional (i.e. the Westerwald region) and continental scale (i.e. the geographical range of B. variegata). The study revealed carry-over effects of larval environment on metamorph phenotype and behaviour causing variation in fitness in the early terrestrial stage of B. variegata. Metamorph size and condition are crucial factors for survival, as small-sized individuals were particularly prone to predator attacks. Yellow-bellied toads show a remarkable fast-slow continuum of the life-history trait longevity. A populations’ position within this continuum may be determined by local environmental stochasticity, i.e. an extrinsic source of variation, and the efficiency of chemical antipredator protection, i.e. an intrinsic source of variation. Extreme longevity seems to be an exception in B. variegata. Senescence was absent in this study. Weather variability affected reproductive success and thus population dynamics. The dispersal potential was low and short-term fragmentation of populations caused significant genetic differentiation at the local scale. Long-term isolation resulted in increased genetic distance at the regional scale. At the continental scale, populations inhabiting the marginal regions were deeply structured with reduced allelic richness. As consequence of environmental changes, short-lived and isolated B. variegata populations at the range margin may face an increased risk of extinction. Conservation measures should thus improve the connectivity among local populations and reinforce annual reproductive success. Further research on the intraspecific variation in B. variegata skin toxins is required to reveal potential effects on palatability and thus longevity.

Railway safety is a topic which gains the public attention only if major railway accidents happen. This is because railway is considered as a safe mode of travel by the public. However, to ensure the safety of the railway system railway companies as well as universities conduct a broad spectrum of research. An overview of this research has not yet been provided in the scholarly literature. Therefore, this thesis follows two objectives. First an overview and ranking of railway safety research universities should be provided. Second, based on these universities, it should be identified which are the most relevant and influential research topics. The ranking is based on the research method “literature review” which forms the methodical basis for this thesis. To evaluate the universities based on a measurable and objective criterion, the number of citations of the researchers from each university is gathered. As a result, the University of Leuven for the civil engineering, Milan Politechnico for mechanical enginering and the University of Loughborough for electrical engineering are identified as the leading university in their field of railway safety research. The top universities for each discipline are distributed all over Europe, North America and Asia. However, a clear focus on the US and British universities is observed. For identification of the most relevant and influential topics the keywords from the publications which are considered in the ranking procedure are analyzed. Focus areas among these keywords are revealed by calculating the count of each keyword. High-speed trains as well as maintenance are recognized as the highly relevant topics in both civil and mechanical engineering. Furthermore, the topic of railway dynamics for mechanical engineering and noise and vibration for civil engineering are identified as the leading topics in the respective discipline. Achieving both research goals required exploratory approaches. Therefore, this thesis leaves open space for future research to deepen the individual topics which are approached in each section. A validation of the results through experts interviews as well as a deepening of the analysis through increasing the number of analyzed universities as well as applying statistical methods is recommended.

The industry standard Decision Model and Notation (DMN) has enabled a new way for the formalization of business rules since 2015. Here, rules are modeled in so-called decision tables, which are defined by input columns and output columns. Furthermore, decisions are arranged in a graph-like structure (DRD level), which creates dependencies between them. With a given input, the decisions now can be requested by appropriate systems. Thereby, activated rules produce output for future use. However, modeling mistakes produces erroneous models, which can occur in the decision tables as well as at the DRD level. According to the Design Science Research Methodology, this thesis introduces an implementation of a verification prototype for the detection and resolution of these errors while the modeling phase. Therefore, presented basics provide the needed theoretical foundation for the development of the tool. This thesis further presents the architecture of the tool and the implemented verification capabilities. Finally, the created prototype is evaluated.

Bio-medical data comes in various shapes and with different representations. Domain experts use such data for analysis or diagnosis, during research or clinical applications. As the opportunities to obtain or to simulate bio-medical data become more complex and productive, the experts face the problem of data overflow. Providing a reduced, uncluttered representation of data, that maintains the data’s features of interest falls into the area of Data Abstraction. Via abstraction, undesired features are filtered out to give space - concerning the cognitive and visual load of the viewer - to more interesting features, which are therefore accentuated. To address this challenge, the dissertation at hand will investigate methods that deal with Data Abstraction in the fields of liver vasculature, molecular and cardiac visualization. Advanced visualization techniques will be applied for this purpose. This usually requires some pre-processing of the data, which will also be covered by this work. Data Abstraction itself can be implemented in various ways. The morphology of a surface may be maintained, while abstracting its visual cues. Alternatively, the morphology may be changed to a more comprehensive and tangible representation. Further, spatial or temporal dimensions of a complex data set may be projected to a lower space in order to facilitate processing of the data. This thesis will tackle these challenges and therefore provide an overview of Data Abstraction in the bio-medical field, and associated challenges, opportunities and solutions.

Molecular dynamics (MD) as a field of molecular modelling has great potential to revolutionize our knowledge and understanding of complex macromolecular structures. Its field of application is huge, reaching from computational chemistry and biology over material sciences to computer-aided drug design. This thesis on one hand provides insights into the underlying physical concepts of molecular dynamics simulations and how they are applied in the MD algorithm, and also briefly illustrates different approaches, as for instance the molecular mechanics and molecular quantum mechanics approaches. On the other hand an own all-atom MD algorithm is implemented utilizing and simplifying a version of the molecular mechanics based AMBER force field published by \big[\cite{cornell1995second}\big]. This simulation algorithm is then used to show by the example of oxytocin how individual energy terms of a force field function. As a result it has been observed, that applying the bond stretch forces alone caused the molecule to be compacted first in certain regions and then as a whole, and that with adding more energy terms the molecule got to move with increasing flexibility.

The European landscape is dominated by intensive agriculture which leads to widespread impact on the environment. The frequent use of agricultural pesticides is one of the major causes of an ongoing decline in flower-visiting insects (FVIs). The conservation of this ecologically diverse assemblage of mobile, flying insect species is required by international and European policy. To counteract the decrease in species numbers and their abundances, FVIs need to be protected from anthropogenic stressors. European pesticide risk assessment was devised to prevent unacceptable adverse consequences of pesticide use on FVIs. However, there is an ongoing discussion by scientists and policy-makers if the current risk assessment actually provides adequate protection for FVI species. The first main objective of this thesis was to investigate pesticide impact on FVI species. The scientific literature was reviewed to identify groups of FVIs, summarize their ecology, and determine their habitat. This was followed by a synthesis of studies about the exposure of FVIs in their habitat and subsequent effects. In addition, the acute sensitivity of one FVI group, bee species, to pesticides was studied in laboratory experiments. The second main objective was to evaluate the European risk assessment for possible deficits and propose improvements to the current framework. Regulatory documents were screened to assess the adequacy of the guidance in place in light of the scientific evidence. The suitability of the honey bee Apis mellifera as the currently only regulatory surrogate species for FVIs was discussed in detail. The available scientific data show that there are far more groups of FVIs than the usually mentioned bees and butterflies. FVIs include many groups of ecologically different species that live in the entire agricultural landscape. Their habitats in crops and adjacent semi-natural areas can be contaminated by pesticides through multiple pathways. Environmentally realistic exposure of these habitats can lead to severe effects on FVI population parameters. The laboratory studies of acute sensitivity in bee species showed that pesticide effects on FVIs can vary greatly between species and pesticides. The follow-up critical evaluation of the European FVI risk assessment revealed major shortcomings in exposure and effect assessment. The honey bee proved to be a sufficient surrogate for bee species in lower tier risk assessment. Additional test species may be chosen for higher tier risk assessment to account for ecological differences. This thesis shows that the ecology of FVIs should generally be considered to a greater extent to improve the regulatory process. Data-driven computational approaches could be used as alternative methods to incorporate ecological trait data in spatio-temporal scenarios. Many open questions need to be answered by further research to better understand FVI species and promote necessary changes to risk assessment. In general, other FVI groups than bees need to be investigated. Furthermore, comprehensive data on FVI groups and their ecology need to be collected. Contamination of FVI habitat needs to be linked to exposure of FVI individuals and ecologically complex effects on FVI populations should receive increased attention. In the long term, European FVI risk assessment would benefit from shifting its general principles towards more scientifically informed regulatory decisions. This would require a paradigm shift from arbitrary assumptions and unnecessarily complicated schemes to a substantiated holistic framework.

Engineered inorganic nanoparticles (EINPs) are produced and utilized on a large scale and will end up in surface waters. Once in surface waters, EINPs are subjected to transformations induced by environmental processes altering the particles’ fate and inherent toxicity. UV irradiation of photoactive EINPs is defined as one effect-inducing pathway, leading to the formation of reactive oxygen species (ROS), increasing EINP toxicity by exerting oxidative stress in aquatic life. Simultaneously, UV irradiation of photoactive EINP alters the toxicity of co-occurring micropollutants (e.g. pesticides) by affecting their degradation. The presence of natural organic matter (NOM) reduces the agglomeration and sedimentation of EINPs, extending the exposure of pelagic species, while delaying the exposure of benthic species living in and on the sediment, which is suggested as final sink for EINPs. However, the joint impact of NOM and UV irradiation on EINP-induced toxicity, but also EINP-induced degradation of micropollutants, and the resulting risk for aquatic biota, is poorly understood. Although potential effects of EINPs on benthic species are increasingly investigated, the importance of exposure pathways (waterborne or dietary) is unclear, along with the reciprocal pathway of EINPs, i.e. the transport back from aquatic to terrestrial ecosystems. Therefore, this thesis investigates: (i) how the presence of NOM affects the UV-induced toxicity of the model EINP titanium dioxide (nTiO2) on the pelagic organism Daphnia magna, (ii) to which extent UV irradiation of nTiO2 in the presence and absence of NOM modifies the toxicity of six selected pesticides in D. magna, (iii) potential exposure pathway dependent effects of nTiO2 and silver (nAg) EINPs on the benthic organism Gammarus fossarum, and (iv) the transport of nTiO2 and gold EINPs (nAu) via the merolimnic aquatic insect Chaetopteryx villosa back to terrestrial ecosystems. nTiO2 toxicity in D. magna increased up to 280-fold in the presence of UV light, and was mitigated by NOM up to 12-fold. Depending on the pesticide, UV irradiation of nTiO2 reduced but also enhanced pesticide toxicity, by (i) more efficient pesticide degradation, and presumably (ii) formation of toxic by-products, respectively. Likewise, NOM reduced and increased pesticide toxicity, induced by (i) protection of D. magna against locally acting ROS, and (ii) mitigation of pesticide degradation, respectively. Gammarus’ energy assimilation was significantly affected by both EINPs, however, with distinct variation in direction and pathway dependence between nTiO2 and nAg. EINP presence delayed C. villosa emergence by up to 30 days, and revealed up to 40% reduced lipid reserves, while the organisms carried substantial amounts of nAu (~1.5 ng/mg), and nTiO2 (up to 2.7 ng/mg). This thesis shows, that moving test conditions of EINPs towards a more field-relevant approach, meaningfully modifies the risk of EINPs for aquatic organisms. Thereby, more efforts need to be made to understand the relative importance of EINP exposure pathways, especially since a transferability between different types of EINPs may not be given. When considering typically applied risk assessment factors, adverse effects on aquatic systems might already be expected at currently predicted environmental EINP concentrations in the low ng-µg/L range.

Nowadays, almost any IT system involves personal data processing. In such systems, many privacy risks arise when privacy concerns are not properly addressed from the early phases of the system design. The General Data Protection Regulation (GDPR) prescribes the Privacy by Design (PbD) principle. As its core, PbD obliges protecting personal data from the onset of the system development, by effectively integrating appropriate privacy controls into the design. To operationalize the concept of PbD, a set of challenges emerges: First, we need a basis to define privacy concerns. Without such a basis, we are not able to verify whether personal data processing is authorized. Second, we need to identify where precisely in a system, the controls have to be applied. This calls for system analysis concerning privacy concerns. Third, with a view to selecting and integrating appropriate controls, based on the results of system analysis, a mechanism to identify the privacy risks is required. Mitigating privacy risks is at the core of the PbD principle. Fourth, choosing and integrating appropriate controls into a system are complex tasks that besides risks, have to consider potential interrelations among privacy controls and the costs of the controls. This thesis introduces a model-based privacy by design methodology to handle the above challenges. Our methodology relies on a precise definition of privacy concerns and comprises three sub-methodologies: model-based privacy analysis, modelbased privacy impact assessment and privacy-enhanced system design modeling. First, we introduce a definition of privacy preferences, which provides a basis to specify privacy concerns and to verify whether personal data processing is authorized. Second, we present a model-based methodology to analyze a system model. The results of this analysis denote a set of privacy design violations. Third, taking into account the results of privacy analysis, we introduce a model-based privacy impact assessment methodology to identify concrete privacy risks in a system model. Fourth, concerning the risks, and taking into account the interrelations and the costs of the controls, we propose a methodology to select appropriate controls and integrate them into a system design. Using various practical case studies, we evaluate our concepts, showing a promising outlook on the applicability of our methodology in real-world settings.

Water uptake, respiration and exudation are some of the biological functions fulfilled by plant roots. They drive plant growth and alter the biogeochemical parameters of soil in the vicinity of roots, the rhizosphere. As a result, soil processes such as water fluxes, carbon and nitrogen exchanges or microbial activity are enhanced in the rhizosphere in comparison to the bulk soil. In particularly, the exudation of mucilage as a gel-like substance by plant roots seems to be a strategy for plants to overcome drought stress by increasing soil water content and soil unsaturated hydraulic conductivity at negative water potentials. Although the variations of soil properties due to mucilage are increasingly understood, a comprehensive understanding of the mechanisms in the pore space leading to such variations is lacking. The aim of this work was to elucidate the gel properties of mucilage in the pore space, i.e. interparticulate mucilage, in order to link changes of the physico-chemical properties in the rhizosphere to mucilage. The fulfilment of this goal was confronted to the three following challenges: The lack of methods for in situ detection of mucilage in soil; The lack of knowledge concerning the properties of interparticulate mucilage; The unknown relationship between the composition and the properties of model substances and root mucilage produced by various species. These challenges are addressed in several chapters. In a first instance, a literature review picked information from various scientific fields about methods enabling the characterization of gels and gel phases in soil. The variation of soil properties resulting from biohydrogel swelling in soil was named the gel effect. The combined study of water entrapment of gels and gel phases in soil and soil structural properties in terms of mechanical stability or visual structures proved promising to disentangle the gel effect in soil. The acquired methodical knowledge was used in the next experiments to detect and characterize the properties of interparticulate gel. 1H NMR relaxometry allows the non-invasive measure of water mobility in porous media. A conceptual model based on the equations describing the relaxation of water protons in porous media was developed to integrate the several gel effects into the NMR parameters and quantify the influence of mucilage on proton relaxation. Rheometry was additionally used to assess mucilage viscosity and soil microstructural stability and ESEM images to visualize the network of interparticulate gel. Combination of the results enabled to identify three main interparticulate gel properties: The spider-web effect restricts the elongation of the polymer chains due to the grip of the polymer network to the surface of soil particles. The polymer network effect illustrates the organization of the polymer network in the pore space according to the environment. The microviscosity effect describes the increased viscosity of interparticulate gel in contrast to free gel. The impact of these properties on soil water mobility and microstructural stability were investigated. Consequences on soil hydraulic and soil mechanical properties found in the literature are further discussed. The influence of the chemical properties of polymers on gel formation mechanism and gel properties was also investigated. For this, model substances with various uronic acid content, degree of esterification and amount of calcium were tested and their amount of high molecular weight substances was measured. The substances investigated included pectic polysaccharides and chia seed mucilage as model polymers and wheat and maize root mucilage. Polygalacturonic acid and low-methoxy pectin proved as non-suitable model polymers for seed and root mucilage as ionic interactions with calcium control their properties. Mucilage properties rather seem to be governed by weak electrostatic interactions between the entangled polymer chains. The amount of high molecular weight material varies considerably depending on mucilage´s origin and seems to be a straight factor for mucilage’s gel effect in soil. Additionally to the chemical characterization of the high molecular weight compounds, determination of their molecular weight and of their conformation in several mucilages types is needed to draw composition-property profiles. The variations measured between the various mucilages also highlight the necessity to study how the specific properties of the various mucilages fulfill the needs of the plant from which they are exuded. Finally, the integration of molecular interactions in gel and interparticulate gel properties to explain the physical properties of the rhizosphere was discussed. This approach offers numerous perspectives to clarify for example how water content or hydraulic conductivity in the rhizosphere vary according to the properties of the exuded mucilage. The hypothesis that the gel effect is general for all soil-born exudates showing gel properties was considered. As a result, a classification of soil-born gel phases including roots, seeds, bacteria, hyphae and earthworm’s exuded gel-like material according to their common gel physico-chemical properties is recommended for future research. An outcome could be that the physico-chemical properties of such gels are linked with the extent of the gel effect, with their impact on soil properties and with the functions of the gels in soil.