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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.
Virtual reality is a growing field of interest as it provides a particular intuitive way of user-interaction. However, there are still open technical issues regarding latency — the delay between interaction and display reaction — and the trade-off between visual quality and frame-rate of real-time graphics, especially when taking visual effects like specular and semi-transparent surfaces and volumes into account. One solution, a distributed rendering setup, is presented in this thesis, in which the image synthesis is divided into an accurate but costly physically based rendering thread with a low refresh rate and a fast reprojection thread to remain a responsive interactivity with a high frame-rate. Two novel reprojection techniques are proposed that cover reflections and refractions produced by surface ray-tracing as well as volumetric light transport generated by volume ray-marching. The introduced setup can enhance the VR experience within several domains. In this thesis, three innovative training applications have been realized to investigate the added value of virtual reality to the three learning stages of observation, interaction and collaboration. For each stage an interdisciplinary curriculum, currently taught with traditional media, was transferred to a VR setting in order to investigate how virtual reality is capable of providing a natural, flexible and efficient learning environment
Graph-based data formats are flexible in representing data. In particular semantic data models, where the schema is part of the data, gained traction and commercial success in recent years. Semantic data models are also the basis for the Semantic Web - a Web of data governed by open standards in which computer programs can freely access the provided data. This thesis is concerned with the correctness of programs that access semantic data. While the flexibility of semantic data models is one of their biggest strengths, it can easily lead to programmers accidentally not accounting for unintuitive edge cases. Often, such exceptions surface during program execution as run-time errors or unintended side-effects. Depending on the exact condition, a program may run for a long time before the error occurs and the program crashes.
This thesis defines type systems that can detect and avoid such run-time errors based on schema languages available for the Semantic Web. In particular, this thesis uses the Web Ontology Language (OWL) and its theoretic underpinnings, i.e., description logics, as well as the Shapes Constraint Language (SHACL) to define type systems that provide type-safe data access to semantic data graphs. Providing a safe type system is an established methodology for proving the absence of run-time errors in programs without requiring execution. Both schema languages are based on possible world semantics but differ in the treatment of incomplete knowledge. While OWL allows for modelling incomplete knowledge through an open-world semantics, SHACL relies on a fixed domain and closed-world semantics. We provide the formal underpinnings for type systems based on each of the two schema languages. In particular, we base our notion of types on sets of values which allows us to specify a subtype relation based on subset semantics. In case of description logics, subsumption is a routine problem. For
the type system based on SHACL, we are able to translate it into a description
logic subsumption problem.
This thesis addresses the reduced basis methods for parametrized quasilinear elliptic and parabolic partial differential equations with strongly monotone differential operator. It presents all of the ingredients of the reduced basis method: basis generation for reduced basis approximation, certification of the approximation error by suitable a-posteriori error control and an Offine-Online decomposition. The methodology is further applied to the magnetostatic and magnetoquasistatic approximations of Maxwell’s equations and its validity is confirmed by numerical examples.
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.
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.
We consider variational discretization of three different optimal control problems.
The first being a parabolic optimal control problem governed by space-time measure controls. This problem has a nice sparsity structure, which motivates our aim to achieve maximal sparsity on the discrete level. Due to the measures on the right hand side of the partial differential equation, we consider a very weak solution theory for the state equation and need an embedding into the continuous functions for the pairings to make sense. Furthermore, we employ Fenchel duality to formulate the predual problem and give results on solution theory of both the predual and the primal problem. Later on, the duality is also helpful for the derivation of algorithms, since the predual problem can be differentiated twice so that we can apply a semismooth Newton method. We then retrieve the optimal control by duality relations.
For the state discretization we use a Petrov-Galerkin method employing piecewise constant states and piecewise linear and continuous test functions in time. For the space discretization we choose piecewise linear and continuous functions. As a result the controls are composed of Dirac measures in space-time, centered at points on the discrete space-time grid. We prove that the optimal discrete states and controls converge strongly in L^q and weakly-* in Μ, respectively, to their smooth counterparts, where q ϵ (1,min{2,1+2/d}] is the spatial dimension. The variational discrete version of the state equation with the above choice of spaces yields a Crank-Nicolson time stepping scheme with half a Rannacher smoothing step.
Furthermore, we compare our approach to a full discretization of the corresponding control problem, precisely a discontinuous Galerkin method for the state discretization, where the discrete controls are piecewise constant in time and Dirac measures in space. Numerical experiments highlight the sparsity features of our discrete approach and verify the convergence results.
The second problem we analyze is a parabolic optimal control problem governed by bounded initial measure controls. Here, the cost functional consists of a tracking term corresponding to the observation of the state at final time. Instead of a regularization term for the control in the cost functional, we consider a bound on the measure norm of the initial control. As in the first problem we observe a sparsity structure, but here the control resides only in space at initial time, so we focus on the space discretization to achieve maximal sparsity of the control. Again, due to the initial measure in the partial differential equation, we rely on a very weak solution theory of the state equation.
We employ a dG(0) approximation of the state equation, i.e. we choose piecewise linear and continuous functions in space, which are piecewise constant in time for our ansatz and test space. Then, the variational discretization of the problem together with the optimality conditions induce maximal discrete sparsity of the initial control, i.e. Dirac measures in space. We present numerical experiments to illustrate our approach and investigate the sparsity structure
As third problem we choose an elliptic optimal control governed by functions of bounded variation (BV) in one space dimension. The cost functional consists of a tracking term for the state and a BV-seminorm in terms of the derivative of the control. We derive a sparsity structure for the derivative of the BV control. Additionally, we utilize the mixed formulation for the state equation.
A variational discretization approach with piecewise constant discretization of the state and piecewise linear and continuous discretization of the adjoint state yields that the derivative of the control is a sum of Dirac measures. Consequently the control is a piecewise constant function. Under a structural assumption we even get that the number of jumps of the control is finite. We prove error estimates for the variational discretization approach in combination with the mixed formulation of the state equation and confirm our findings in numerical experiments that display the convergence rate.
In summary we confirm the use of variational discretization for optimal control problems with measures that inherit a sparsity. We are able to preserve the sparsity on the discrete level without discretizing the control variable.
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.
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.
Mathematical models of species dispersal and the resilience of metapopulations against habitat loss
(2021)
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.
Augmented reality (AR) applications typically extend the user's view of the real world with virtual objects.
In recent years, AR has gained increasing popularity and attention, which has led to improvements in the required technologies. AR has become available to almost everyone.
Researchers have made great progress towards the goal of believable AR, in which the real and virtual worlds are combined seamlessly.
They mainly focus on issues like tracking, display technologies and user interaction, and give little attention to visual and physical coherence when real and virtual objects are combined. For example, virtual objects should not only respond to the user's input; they should also interact with real objects. Generally, AR becomes more believable and realistic if virtual objects appear fixed or anchored in the real scene, appear indistinguishable from the real scene, and response to any changes within it.
This thesis examines on three challenges in the field of computer vision to meet the goal of a believable combined world in which virtual objects appear and behave like real objects.
Firstly, the thesis concentrates on the well-known tracking and registration problem. The tracking and registration challenge is discussed and an approach is presented to estimate the position and viewpoint of the user so that virtual objects appear fixed in the real world. Appearance-based line models, which keep only relevant edges for tracking purposes, enable absolute registration in the real world and provide robust tracking. On the one hand, there is no need to spend much time creating suitable models manually. On the other hand, the tracking can deal with changes within the object or the scene to be tracked. Experiments have shown that the use of appearance-based line models improves the robustness, accuracy and re-initialization speed of the tracking process.
Secondly, the thesis deals with the subject of reconstructing the surface of a real environment and presents an algorithm to optimize an ongoing surface reconstruction. A complete 3D surface reconstruction of the target scene
offers new possibilities for creating more realistic AR applications. Several interactions between real and virtual objects, such as collision and occlusions, can be handled with physical correctness. Whereas previous methods focused on improving surface reconstructions offline after a capturing step, the presented method de-noises, extends and fills holes during the capturing process. Thus, users can explore an unknown environment without any preparation tasks such as moving around and scanning the scene, and without having to deal with the underlying technology in advance. In experiments, the approach provided realistic results where known surfaces were extended and filled in plausibly for different surface types.
Finally, the thesis focuses on handling occlusions between the real and virtual worlds more realistically, by re-interpreting the occlusion challenge as an alpha matting problem. The presented method overcomes limitations in state-of-the-art methods by estimating a blending coefficient per pixel of the rendered virtual scene, instead of calculating only their visibility. In several experiments and comparisons with other methods, occlusion handling through alpha matting worked robustly and overcame limitations of low-cost sensor data; it also outperformed previous work in terms of quality, realism and practical applicability.
The method can deal with noisy depth data and yields realistic results in regions where foreground and background are not strictly separable (e.g. caused by fuzzy objects or motion blur).
Connected vehicles will have a tremendous impact on tomorrow’s mobility solutions. Such systems will heavily rely on information delivery in time to ensure the functional reliability, security and safety. However, the host-centric communication model of today’s networks questions efficient data dissemination in a scale, especially in networks characterized by a high degree of mobility. The Information-Centric Networking (ICN) paradigm has evolved as a promising candidate for the next generation of network architectures. Based on a loosely coupled communication model, the in-network processing and caching capabilities of ICNs are promising to solve the challenges set by connected vehicular systems. In such networks, a special class of caching strategies which take action by placing a consumer’s anticipated content actively at the right network nodes in time are promising to reduce the data delivery time. This thesis contributes to the research in active placement strategies in information-centric and computation-centric vehicle networks for providing dynamic access to content and computation results. By analyzing different vehicular applications and their requirements, novel caching strategies are developed in order to reduce the time of content retrieval. The caching strategies are compared and evaluated against the state-of-the-art in both extensive simulations as well as real world deployments. The results are showing performance improvements by increasing the content retrieval (availability of specific data increased up to 35% compared to state-of-the-art caching strategies), and reducing the delivery times (roughly double the number of data retrieval from neighboring nodes). However, storing content actively in connected vehicle networks raises questions regarding security and privacy. In the second part of the thesis, an access control framework for information-centric connected vehicles is presented. Finally, open security issues and research directions in executing computations at the edge of connected vehicle networks are presented.
Cultural eutrophication due to excessive inputs of nutrients seriously threatens aquatic ecosystems worldwide and is one of the major anthropogenic stressors on aquatic biota in European rivers. In streams and shallow rivers, its effects include excessive periphyton growth, which causes biological clogging and thereby oxygen depletion in the hyporheic zone. The result is a serious degradation of habitat quality for benthic invertebrates as well as for the eggs and larvae of gravel-spawning fish. Unlike in standing waters, efficient tools for controlling eutrophication in rivers are lacking. However, top-down control of the food-web by manipulating fish stocks, similar to the biomanipulation successfully applied in lakes, offers a promising approach to mitigating the effects of eutrophication in shallow rivers, especially those in which major reductions in nutrient inputs are not feasible. The overall aim of this thesis was to assess the potential for top-down control by two large cypriniform fish, the common nase (Chondrostoma nasus), the only obligate herbivorous fish species in European rivers, and the omnivorous European chub (Squalius cephalus), to mitigate the effects of eutrophication in medium-sized rivers. I therefore conducted field experiments on different spatial and temporal scales in the hyporhithral zone of a eutrophic gravel-bed river. Generally, the results of those experiments revealed the crucial role of fish-mediated top-down effects in river food webs. In a 4-year reach-scale experiment, the key contribution of my thesis, the enhancement of fish densities significantly increased both oxygen availability and water exchange in the upper layer of the hyporheic zone, even though the top-down effects of the fish on periphyton biomass were relatively small. These findings were supported by those of a 4-week mesocosm experiment, which also provided insights into the mechanisms underlying the mitigation of eutrophication effects by nase and chub. The top-down effects of both fish species reduced hyporheic oxygen depletion, suggesting a reduction of biological clogging. The positive effects of herbivorous nase on hyporheic oxygen availability could be attributed to benthic grazing, whereas the reduction of hyporheic oxygen depletion in the presence of omnivorous chub was best explained by the enhanced bioturbation induced by the fish’s benthic foraging. Overall, the results of my thesis demonstrate that biomanipulation achieved by enhancing herbivorous and omnivorous fish stocks can mitigate the effects of eutrophication in medium-sized European rivers. The results may be the first step towards the establishment of biomanipulation as a supportive management tool for eutrophication control in running waters and therefore as a strategy to preserve aquatic biodiversity.
The Stereotype Content Modell (SCM; Fiske et al., 2002) proposes two fundamental dimensions of social evaluation: Warmth, or the intentions of the target, and Competence, or the ability to enact these intentions. The practical applications of the SCM are very broad and have led to an assumption of universality of warmth and competence as fundamental dimensions of social evaluation.
This thesis has identified five mainly methodological shortcomings of the current SCM research and literature: (I) An insufficient initial scale development; (II) the usage of varying warmth and competence scales without sufficient scale property assessment in later research; (III) the dominant application of first-generation analytical approaches; (IV) the insufficient definition and empirical proof for the SCM’s assumption of universality; and (V) the limited application of the SCM for some social targets. These shortcomings were addressed in four article manuscripts strictly following open science recommendations.
Manuscript # 1 re-analysed published research using English SCM measures to investigate the measurement properties of the used warmth and competence scales. It reported the scales’ reliability, dimensionality and comparability across targets as well as the indicator-based parameter performance in a (multiple group) confirmatory factor analysis framework. The findings indicate that about two thirds of all re-analysed scales do not show the theoretically expected warmth and competence dimensionality. Moreover, only about eleven per cent allowed meaningful mean value comparisons between targets. Manuscript # 2 presents a replication of Manuscript # 1 in the national and language of German(y) generating virtually identical results as Manuscript # 1 did. Manuscript # 3 investigated the stereotype content of refugee subgroups in Germany. We showed that refugees was generally perceived unfavourably in terms of warmth and competence, but that the stereotype content varied based on the refugees’ geographic origin, religious affiliation, and flight motive. These results were generated using a reliability-corrected approach to compare mean values named alignment optimisation procedure. Manuscript # 4 developed and tested a high-performing SCM scale assessing occupational stereotypes a number of exploratory and confirmatory factor analyses.
Content and Language Integrated Learning (CLIL) has experienced growing importance in the last decades and an increasing number of schools have already implemented CLIL programmes or are planning to do so. Though the potentials of CLIL programmes are widely praised, first research results also raise doubts if CLIL students can live up to these high expectations. Both Fehling (2005) as well as Rumlich (2013; 2016), for example, found that CLIL programmes not inevitably show the expected results but that the CLIL students’ success might also be at least partially explained by other influences, such as the selection process of future CLIL students. Hence, CLIL students apparently fall short of the high expectations that are usually connected to the respective CLIL programmes and as this is mainly based on the unsatisfactory quality of these programmes, Rumlich concludes that “it is now high time to focus on the quality of CLIL provision” (Rumlich 2016: 452). He continues to explain that “the promises of CLIL do not materialise automatically owing to the fact that another language is used for learning in a non-language subject” (Rumlich 2016: 452). It must be assumed that the success of CLIL teaching also highly depends on the quality of the CLIL teachers.
In contrast to the continuously growing number of CLIL schools, however, the number of specifically trained CLIL teachers is comparably small. In Germany, CLIL teachers are not (yet) required to attend any special training in order to teach in a CLIL programme. Notwithstanding, is it sufficient for a CLIL teacher only to be trained in the content subject and the foreign language? Or does CLIL teaching require more than the sum of these two components? Do CLIL teachers need additional teaching competences to the ones of a content and a language teacher? In the light of the recent findings of CLIL programmes falling short of the high expectations, the answer to these questions must clearly be “Yes”. Hence, in order to appropriately train (future) CLIL teachers, special training programmes need to be developed which consider the teachers’ individual educational backgrounds, i.e. their qualifications as language and/or as content teachers and build up on these competences through adding the CLIL-specific teaching competences.
Therefore, this thesis aims at developing a German Framework for CLIL Teacher Education, which considers both the already published, theory-based standards of CLIL teacher education as well as the practical perspective of experienced CLIL teachers in Germany. This German Framework for CLIL Teacher Education classifies the different teaching competences, which are derived from integrating the theoretical and the practical perspective on CLIL teacher education, with regard to the three different competence areas, i.e. the general teaching competence, the language teaching competence and the subject teaching competence and is hence adaptable to different CLIL settings and educational backgrounds. In addition to developing this German Framework for CLIL Teacher Education, which provides the content of future CLIL teacher education programmes, this thesis discusses different forms of structurally implementing CLIL teacher education programmes in the existing structures of teacher education in Germany. This is achieved through analysing the current state of the art of CLIL teacher education at German universities and systematising the different forms of implementing these training programmes in the prevailing educational structures. Building on these first two steps, in the third and final step, this thesis develops a CLIL teacher education programme at a German university that is based on the results and elements of the German Framework for CLIL Teacher Education as well as the state of the art of CLIL teacher education in Germany. Thus, this thesis is allocated at the intersection between foreign language teaching as well as teacher education and is structured in eleven chapters.
Wild bees are essential for the pollination of wild and cultivated plants. However, within the
last decades, the increasing intensification of modern agriculture has led to both a reduction and fragmentation as well as a degradation of the habitats wild bees need. The resulting loss of pollinators and their pollination poses an immense challenge to global food production. To support wild bees, the availability of flowering resources is essential. However, the flowering period of each resource is temporally limited and has different effects on pollinators and their pollination, depending on the time of their flowering.
Therefore, to efficiently promote and manage wild bee pollinators in agricultural landscapes, we identified species-specific key floral resources of three selected wild bee species and their spatial and temporal availability (CHAPTERS 2, 3 & 4). We examined, which habitat types predominantly provide these resources (CHAPTERS 3 & 4). We also investigated whether floral resource maps based on the use of these key resources and their spatial and temporal availability explain the abundance and development of the selected wild bees (CHAPTERS 3 & 4) and pollination (CHAPTER 5) better than habitat maps, that only indirectly account for the availability of floral resources.
For each of the species studied, we were able to identify different key pollen sources, predominantly woody plants in the early season (April/May) and increasingly herbaceous plants in the later season (June/July; CHAPTERS 2, 3 & 4). The open woody semi-natural habitats of our agricultural landscapes provided about 75% of the floral resources for the buff-tailed bumblebees, 60% for the red mason bees, and 55% for the horned mason bees studied, although they accounted for only 3% of the area (CHAPTERS 3 & 4). In addition, fruit orchards provided about 35% of the floral resources for the horned mason bees on 4% of the landscape area (CHAPTER 3). We showed that both mason bee species benefited from the resource availability in the surrounding landscapes (CHAPTER 3). Yet this was not the case for the bumblebees (CHAPTER 4). Instead, the weight gain of their colonies, the number of developed queen cells and their colony survival were higher with increasing proximity to forests. The proximity to forests also had a positive effect on the mason bees studied (CHAPTER 3). In addition, the red mason bees benefited from herbaceous semi-natural habitats. The proportion of built-up areas had a negative effect on the horned mason bees, and the proportion of arable land on the red mason bees. The habitat maps explained horned mason bee abundances equally well as the floral resource maps, but red mason bee abundances were distinctly better explained by key floral resources. The pollination of field bean increased with higher proportions of early floral resources, whereas synchronous floral resources showed no measurable reduction in their pollination (CHAPTER 5). Habitat maps also explained field bean pollination better than floral resource maps. Here, pollination increased with increasing proportions of built-up areas in the landscapes and decreased with increasing proportions of arable land.
Our results highlight the importance of the spatio-temporal availability of certain key species as resource plants of wild bees in agricultural landscapes. They show that habitat maps are ahead of, or at least equal to, spatio-temporally resolved floral resource maps in predicting wild bee development and pollination. Nevertheless, floral resource maps allow us to draw more accurate conclusions between key floral resources and the organisms studied. The proximity to forest edges had a positive effect on each of the three wild bee species studied. However, besides pure food availability, other factors seem to co-determine the occurrence of wild bees in agricultural landscapes.
Within the field of Business Process Management, business rules are commonly used to model company decision logic and govern allowed company behavior. An exemplary business rule in the financial sector could be for example:
”A customer with a mental condition is not creditworthy”. Business rules are
usually created and maintained collaboratively and over time. In this setting,
modelling errors can occur frequently. A challenging problem in this context is
that of inconsistency, i.e., contradictory rules which cannot hold at the same
time. For instance, regarding the exemplary rule above, an inconsistency would
arise if a (second) modeller entered an additional rule: ”A customer with a mental condition is always creditworthy”, as the two rules cannot hold at the same
time. In this thesis, we investigate how to handle such inconsistencies in business
rule bases. In particular, we develop methods and techniques for the detection,
analysis and resolution of inconsistencies in business rule bases
Method development for the quantification of pharmaceuticals in aqueous environmental matrices
(2021)
As a consequence of the world population increase and the resulting water scarcity, water quality is the object of growing attention. In that context, organic anthropogenic molecules — often defined as micropollutants— represent a threat for water resources. Among them, pharmaceuticals are the object of particular concerns due to their permanent discharge, their increasing consumption and their effect-based structures. Pharmaceuticals are mainly introduced in the environment via wastewater treatment plants (WWTPs), along with their metabolites and the on-site formed transformation products (TPs). Once in the aquatic environment, they partition between the different environmental compartments in particular the aqueous phase, suspended particulate matter(SPM) and biota. In the last decades, pharmaceuticals have been widely investigated in the water phase. However, extreme polar pharmaceuticals have rarely been monitored due to the lack of robust analytical methods. Moreover, metabolites and TPs have seldom been included in routine analysis methods although their environmental relevance is proven. Furthermore, pharmaceuticals have been only sporadically investigated in SPM and biota and adequate multi-residue methods are lacking to obtain comprehensive results about their occurrence in these matrices. This thesis endeavors to cover these gaps of knowledge by the development of generic multi-residue methods for pharmaceuticals determination in the water phase, SPM and biota and to evaluate the occurrence and partition of pharmaceuticals into these compartments. For a complete overview, a particular focus was laid on extreme polar pharmaceuticals, pharmaceutical metabolites and TPs. In total, three innovative multi-residue methods were developed, they include analytes covering a broad range of physico-chemical properties. First, a reliable multi-residue method was developed for the analysis of extreme polar pharmaceuticals, metabolites and TPs dissolved in water. The selected analytes covered a significant range of elevated polarity and the method would be easily expendable to further analytes. This versatility could be achieved by the utilization of freeze-drying as sample preparation and zwitterionic hydrophilic interaction liquid chromatography (HILIC) in gradient elution mode. The suitability of HILIC chromatography to simultaneously quantify a large range of micropollutants in aqueous environmental samples was thoroughly studied. Several limitations were pointed out: a very complex and time-consuming method development, a very high sensitivity with regards to modification of the acetonitrile to water ratio in the eluent or the diluent and high positive matrix effects for certain analytes. However, these limitations can be overcome by the utilization of a precise protocol and appropriate labeled internal standards. They are overmatched by the benefits of HILIC which permits the chromatographic separation of extreme polar micropollutants. Investigation of environmental samples showed elevated concentrations of the analytes in the water phase. In particular, gabapentin, metformin, guanylurea and oxypurinol were measured at concentrations in the µg/L range in surface water. Subsequently, a reliable multi-residue method was established for the determination of 57 pharmaceuticals, 47 metabolites and TPs sorbed to SPM down to the low ng/g range. This method was conceived to cover a large range of polarity in particular with the inclusion of extreme polar pharmaceuticals. The extraction procedure was based on pressurized liquid extraction (PLE) followed by a clean-up via solvent exchange and detection via direct injection-reversed-phase LC-MS/MS and freeze-drying HILIC-MS/MS. Pharmaceutical sorption was examined using laboratory experiments. Derived distribution coefficients Kd varied by five orders of magnitude among the analytes and confirmed a high sorption potential for positively charged and nonpolar pharmaceuticals. The occurrence of pharmaceuticals in German rivers SPM was evaluated by the investigation of annual composite SPM samples taken at four sites at the river Rhine and one site at the river Saar between the years 2005 and 2015. It revealed the ubiquitous presence of pharmaceuticals sorbed to SPM in these rivers. In particular, positively charged analytes, even very polar and nonpolar pharmaceuticals showed appreciable concentrations. For many pharmaceuticals, a distinct correlation was observed between the annual quantities consumed in Germany and the concentrations measured in SPM. Studies of composite SPM spatial distribution permitted to get hints about specific industrial discharge by comparing the pollution pattern along the river. For the first time, these results showed the potential of SPM for the monitoring of positively charged and nonpolar pharmaceuticals in surface water. Finally, a reliable and generic multi residue method was developed to investigate 35 pharmaceuticals and 28 metabolites and TPs in fish plasma, fish liver and fish fillet. For this matrix, it was very challenging to develop an adequate clean-up allowing for the sufficient separation of the matrix disturbances from the analytes. In the final method, fish tissue extraction was performed by cell disruption followed by a non-discriminating clean-up based on silica gel solid-phase extraction(SPE) and restrictive access media (RAM) chromatography. Application of the developed method to the measurement of bream and carp tissues from German rivers revealed that even polar micropollutants such as pharmaceuticals are ubiquitously present in fish tissues. In total, 17 analytes were detected for the first time in fish tissues, including 10 metabolites/TPs. The importance of monitoring metabolites and TPs in fish tissues was confirmed with their detection at similar concentrations as their parents. Liver and fillet were shown to be appropriate for the monitoring of pharmaceuticals in fish, whereas plasma is more inconvenient due to very low concentrations and collection difficulties. Elevated concentrations of certain metabolites suggest possible formation of human metabolites in fish. Measured concentrations indicate a low bioaccumulation potential for pharmaceuticals in fish tissues.
Artificial intelligence (AI) is of rising importance in these days. AI is increasingly used in various company fields. Nonetheless, no high-quality scientific sources could be found stating the use of AI in the field of leadership. This research gap is addressed with this elaboration by performing expert interviews with leaders. In total seventeen companies could be questioned. The results indicate that AI is not widely used in leadership yet since only one company uses it currently and just about 10% of the participants plan the implementation in the closer feature. While the following items ex- plain why companies want to use AI in leadership: Chances for automation, time and cost savings, many important disadvantages and issues prevent companies from actively using it now: No areas of application are known, no need justifies the use, human interactions as a key aspect of leadership is reduced and it is hard to collect all necessary data. Beyond that, it was aimed to identify changes in the field of leadership through the use of AI. This objective could not be addressed due to the limited number of participants using AI in leadership.
Keywords: Leadership, artificial intelligence, transformation, state-of-use
SUMMARY
Buildings and infrastructures characterize the appearance of our cultural landscapes and provide essential services for the human society. However, they inevitably impact the natural environment e.g. by the structural change of habitats. Additionally, they potentially cause further negative environmental impacts due to the release of chemical substances from construction materials. Galvanic anodes and organic coatings regularly used for corrosion protection of steel structures are building materials of particular importance for the transport infrastructure. In direct contact with a water body or indirectly via the runoff after rainfall, numerous chemicals can be released into the environment and pose a risk to aquatic organisms. Up to now, there is no uniform investigation and evaluation approach for the assessment of the environmental compatibility of building products. Furthermore, galvanic anodes and organic coatings pose particular challenges for their ecotoxicological characterization due to their composition. Therefore, the objective of the presented thesis was the ecotoxicological assessment of emissions from galvanic anodes and protective coatings as well as the development of standardized assessment procedures for these materials.
The possible environmental hazard posed by the use of anodes on offshore installations was investigated on three trophic levels. To ensure a realistic and reliable evaluation, the experiments were carried out in natural seawater and under natural pH conditions. Moreover, the anode material and its main components zinc and aluminum were exposed while simulating a worst-case scenario. The anode material examined caused a weak inhibition of algae growth; no acute toxicity was observed on the luminescent bacteria and amphipods. However, an increase of aluminum and indium levels in the crustacean species was found. On the basis of these results, no direct threat has been identified for marine organisms from the use of galvanic aluminum anodes. However, an accumulation of metals in crustaceans and a resulting entry into the marine food web cannot be excluded.
The environmental compatibility of organic coating systems was exemplarily evaluated using a selection of relevant products based on epoxy resins (EP) and polyurethanes. For this purpose, coated test plates were dynamically leached over 64 days. The eluates obtained were systematically analyzed for their ecotoxicological effects (acute toxicity to algae and luminescent bacteria, mutagenic and estrogenic effects) and their chemical composition. In particular, the EP-based coatings caused significant bacterial toxicity and estrogen-like effects. The continuously released 4-tert-butylphenol was identified as a main contributor to these effects and was quantified in concentrations exceeding the predicted no effect concentration for freshwater in all samples. Interestingly, the overall toxicity was not governed by the content of 4-tert-butylphenol in the products but rather by the release mechanism of this compound from the investigated polymers. This finding indicates that an optimization of the composition can result in the reduction of emissions and thus of environmental impacts - possibly due to a better polymerization of the compounds.
Coatings for corrosion protection are exposed to rain, changes in temperature and sun light leading to a weathering of the polymer. To determine the influence of light-induced aging on the ecotoxicity of top coatings, the emissions and associated adverse effects of UV-irradiated and untreated EP-based products were compared. To that end, the investigation of static leachates was focused on estrogenicity and bacterial toxicity, which were detected in the classic microtiter plate format and in combination with thin-layer plates. Both materials examined showed a significant decrease of the ecotoxicological effects after irradiation with a simultaneous reduction of the 4-tert-butylphenol emission. However, bisphenol A and various structural analogues were detected as photolytic degradation products of the polymers, which also contributed to the observed effects. In this context, the identification of bioactive compounds was supported by the successful combination of in-vitro bioassays with chemical analysis by means of an effect-directed analysis. The presented findings provide important information to assess the general suitability of top coatings based on epoxy resins.
Within the scope of the present study, an investigation concept was developed and successfully applied to a selection of relevant construction materials. The adaptation of single standard methods allowed an individual evaluation of these products. At the same time, the suitability of the ecotoxicological methods used for the investigation of materials of unknown and complex composition was confirmed and the basis for a systematic assessment of the environmental compatibility of corrosion protection products was created. Against the background of the European Construction Products Regulation, the chosen approach can facilitate the selection of environmentally friendly products and contributes to the optimization of individual formulations by the simple comparison of different building materials e.g. within a product group.