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The ability to sense and respond to different environmental conditions allows living organisms to adapt quickly to their surroundings. In order to use light as a source of information, plants, fungi, and bacteria employ phytochromes. With their ability to detect far-red and red light, phytochromes constitute a major photoreceptor family. Bacterial phytochromes (BphPs) are composed of an apo-phytochrome and an open-chain tetrapyrrole, the chromophore biliverdin IXα, which mediates the photosensory properties. Depending on the photoexcitation and the quality of the incident light, phytochromes interconvert between two photoconvertible parental states: the red light-absorbing Pr-form and the far-red light-absorbing Pfr-form. In contrast to prototypical phytochromes, with a thermal stable Pr ground state, there is a group of bacterial phytochromes that exhibit dark reversion from the Pr- to the Pfr-form. These special proteins are classified as bathy phytochromes and range across different classes of bacteria. Moreover, the majority of BphPs act as sensor histidine kinases in two-component regulatory systems. The light-triggered conformational change results in the autophosphorylation of the histidine kinase domain and the transphosphorylation of an associated response regulator, inducing a cellular response. Spectroscopic analysis utilizing homologously produced protein identified PaBphP, the histidine kinase of the human opportunistic pathogen Pseudomonas aeruginosa, as a bathy phytochrome. Intensive research on PaBphP revealed evidence that the interconversion between its physiological active and inactive states is influenced by light and darkness rather than far-red and red light. In order to conduct a comprehensive systematic analysis, further bacterial phytochromes were investigated regarding their biochemical and spectroscopic behavior, as well as their autokinase activity. In addition to PaBphP, this work employs the bathy phytochromes AtBphP2, AvBphP2, XccBphP from the non-photosynthetic plant pathogens Agrobacterium tumefaciens, Allorhizobium vitis, Xanthomonas campestris, as well as RtBphP2 from the soil bacterium Ramlibacter tataouinensis. All investigated BphPs displayed a bathy-typical behavior by developing a distinct Pr-form under far-red light conditions and undergoing dark reversion to their Pfr-form. Different Pr/Pfr-fractions can be identified among the BphP populations in varying natural light conditions, including red or blue light. The Pr-form is considered as the active form due to autophosphorylation activity in the heterologously produced phytochromes when exposed to light. In the absence of light, associated with the development of the Pfr-form, the phytochromes exhibited disabled or strongly reduced autokinase activity. Additionally, light-triggered phosphorylation was observed for the response regulator PaAlgB, which is linked to the phytochrome of P. aeruginosa. This study presents the first comparative investigation of numerous bathy phytochromes under identical conditions. The work addressed a gap in the literature by providing quantitative correlation between kinase activity and calculated Pr/Pfr-fractions obtained from spectroscopic measurements. The biological role of PaBphP was partially elucidated through phenotypic characterization employing P. aeruginosa mutant and overexpression strains. The generation of a functional model was possible by considering the postulated functions of the other phytochromes found in the literature. In summary, bathy BphPs are hypothesized to modulate bacterial virulence according to the circadian day/night rhythm of their hosts. The pathogens are believed to reduce their virulence during daylight hours to evade immune and defense reactions, while increasing their virulence during the evening and night, enabling more effective infections.
Fused Filament Fabrication (FFF), an extrusion-based additive manufacturing technique, is becoming increasingly popular for polymer processing in academia and industry since it provides several benefits. As an inherent nature of additive structures, the quality of the inter-filament bonding in 3D printed components poses the main challenge in the application to mechanically critical components. Still, the precise placement of the material allows for generating load-path-specific orientations within a volume. In this work, to improve inter-filament bonding, the effects of the processing conditions on the mechanical properties of macroscopically defect-free 3D printed polypropylene (PP) were comprehensively investigated based on an analysis of supermolecular morphology formation in combination with local thermal simulations. Additionally, to exploit the anisotropic properties of the FFF process, specifically the unique fiber orientation, a composite based on PP and poly(ethylene terephthalate) (PET) microfibrils was prepared, and the morphology and the effects of the PET-fiber reinforcement on the mechanical performance were studied. The importance of the fiber orientation on the tribological properties was highlighted by the characterization of two printed fiber-reinforced polyetheretherketone (PEEK)-based compounds sliding against a steel ring. By understanding in-depth the effect of the processing conditions and the anisotropic properties of fiber-reinforced composites, practical insights were gained regarding how the material potential can be exploited via the FFF process.
Temporal Data Management and Incremental Data Recomputation with Wide-column Stores and MapReduce
(2017)
In recent years, ”Big Data” has become an important topic in academia
and industry. To handle the challenges and problems caused by Big Data,
new types of data storage systems called ”NoSQL stores” (means ”Not-only-
SQL”) have emerged.
”Wide-column stores” are one kind of NoSQL stores. Compared to relational database systems, wide-column stores introduce a new data model,
new IRUD (Insert, Retrieve, Update and Delete) semantics with support for
schema-flexibility, single-row transactions and data expiration constraints.
Moreover, each column stores multiple data versions with associated time-
stamps. Well-known examples are Google’s ”Big-table” and its open sourced
counterpart ”HBase”. Recently, such systems are increasingly used in business intelligence and data warehouse environments to provide decision support, controlling and revision capabilities.
Besides managing the current values, data warehouses also require management and processing of historical, time-related data. Data warehouses
frequently employ techniques for processing changes in various data sources
and incrementally applying such changes to the warehouse to keep it up-to-
date. Although both incremental data warehousing maintenance and temporal data management have been the subject of intensive research in the
relational database and finally commercial database products have picked up
the ability for temporal data processing and management, such capabilities
have not been explored systematically for today’s wide-column stores.
This thesis helps to address the shortcomings mentioned above. It care-
fully analyzes the properties of wide-column stores and the applicability
of mechanisms for temporal data management and incremental data ware-
house maintenance known from relational databases, extends well-known approaches and develops new capabilities for providing equivalent support in
wide-column stores.
Research across virtually all subfields of psychology has suffered from construct proliferation, often resulting in redundant constructs that strongly overlap conceptually and/or empirically. Such cases of old wine in new bottles, i.e., established constructs with new labels, are instances of the jangle fallacy and are problematic because they lead to fragmented literatures and thereby considerably impede the accumulation of knowledge.
The present thesis aims at demonstrating how to scrutinize potential jangle fallacies in a theory-driven, deductive, and falsificationist way. Using the example of the common core of aversive traits, D, I discuss the ways one can find and test differences between more or less overlapping, competing constructs. Specifically,the first paper tests the plausibility of a potential jangle fallacy with respect to D and a Fast Life History Strategy, concluding that the latter is unlikely to represent the common core of aversive traits at all. The remaining three papers test the distinctness of D from FFM Agreeableness, HEXACO Honesty-Humility, and a blend of the two, AG+, all of which are conceptually and empirically remarkably similar to, but could nevertheless be dissociated from D, thereby also refuting an instance of the jangle fallacy.
Although research often places emphasis on similarities, it is impossible to conclusively prove the equivalence of constructs. I therefore conclude that a falsificationist approach is more informative in that it allows to test whether any differences identified on a conceptual level can be confirmed empirically. Stated differently, if a new construct is dissociable both theoretically and empirically, one may assume that it is functionally distinct and no instance of the jangle fallacy.
On Gyroscopic Stabilization
(2012)
This thesis deals with systems of the form
\(
M\ddot x+D\dot x+Kx=0\;, \; x \in \mathbb R^n\;,
\)
with a positive definite mass matrix \(M\), a symmetric damping matrix \(D\) and a positive definite stiffness
matrix \(K\).
If the equilibrium in the system is unstable, a small disturbance is enough to set the system in motion again. The motion of the system sustains itself, an effect which is called self-excitation or self-induced vibration. The reason behind this effect is the presence of negative damping, which results for example from dry friction.
Negative damping implies that the damping matrix \(D\) is indefinite or negative definite. Throughout our work, we assume \(D\) to be indefinite, and that the system possesses both stable and unstable modes and thus is unstable.
It is now the idea of gyroscopic stabilization to mix the modes of a system with indefinite damping such
that the system is stabilized without introducing further
dissipation. This is done by adding gyroscopic forces \(G\dot x\) with a suitable
skew-symmetric matrix \(G\) to the left-hand side. We call \(G=-G^T\in\mathbb R^{n\times n}\) a gyroscopic stabilizer for
the unstable system, if
\(
M\ddot x+(D+ G)\dot x+Kx=0
\)
is asymptotically stable. We show the existence of \(G\) in space dimensions three and four.
This thesis deals with the solution of special problems arising in financial engineering or financial mathematics. The main focus lies on commodity indices. Chapter 1 addresses the important issue for the financial engineering practice of developing well-suited models for certain assets (here: commodity indices). Descriptive analysis of the Dow Jones-UBS commodity index compared to the Standard & Poor 500 stock index provides us with first insights of some features of the corresponding distributions. Statistical tests of normality and mean reversion then helps us in setting up a model for commodity indices. Additionally, chapter 1 encompasses a thorough introduction to commodity investment, history of commodities trading and the most important derivatives, namely futures and European options on futures. Chapter 2 proposes a model for commodity indices and derives fair prices for the most important derivatives in the commodity markets. It is a Heston model supplemented with a stochastic convenience yield. The Heston model belongs to the model class of stochastic volatility models and is currently widely used in stock markets. For the application in the commodity markets the stochastic convenience yield is included in the drift of the instantaneous spot return process. Motivated by the results of chapter 1 it seems reasonable to model the convenience yield by a mean reverting Ornstein-Uhlenbeck process. Since trading desks only apply and consider models with closed form solutions for options I derive such formulas for commodity futures by solving the corresponding partial differential equation. Additionally, semi-closed form formulas for European options on futures are determined. The Cauchy problem with respect to these options is more challenging than the first one. A solution can be provided. Unlike equities, which typically entitle the holder to a continuing stake in a corporation, commodity futures contracts normally specify a certain date for the delivery of the underlying physical commodity. In order to avoid the delivery process and maintain a futures position, nearby contracts must be sold and contracts that have not yet reached the delivery period must be purchased (so called rolling). Optimal trading days for selling and buying futures are determined by applying statistical tests for stochastic dominance. Besides the optimization of the rolling procedure for commodity futures we dedicate ourselves in chapter 3 with the optimization of the weightings of the commodity futures that make up the index. To this end, I apply the Markowitz approach or mean-variance optimization. The mean-variance optimization penalizes up-side and down-side risk equally, whereas most investors do not mind up-side risk. To overcome this, I consider in the next step other risk measures, namely Value-at-Risk and Conditional Value-at-Risk. The Conditional Value-at-Risk is generalized to discontinuous cumulative distribution functions of the loss. For continuous loss distributions, the Conditional Value-at-Risk at a given confidence level is defined as the expected loss exceeding the Value-at-Risk. Loss distributions associated with finite sampling or scenario modeling are, however, discontinuous. Various risk measures involving discontinuous loss distributions shall be introduced and compared. I then apply the theoretical results to the field of portfolio optimization with commodity indices. Furthermore, I uncover graphically the behavior of these risk measures. For this purpose, I consider the risk measures as a function of the confidence level. Based on a special discrete loss distribution, the graphs demonstrate the different properties of these risk measures. The goal of the first section of chapter 4 is to apply the mathematical concept of excursions for the creation of optimal highly automated or algorithmic trading strategies. The idea is to consider the gain of the strategy and the excursion time it takes to realize the gain. In this section I calculate formulas for the Ornstein-Uhlenbeck process. I show that the corresponding formulas can be calculated quite fast since the only function appearing in the formulas is the so called imaginary error function. This function is already implemented in many programs, such as in Maple. My main contribution of this topic is the optimization of the trading strategy for Ornstein-Uhlenbeck processes via the Banach fixed-point theorem. The second section of chapter 4 deals with statistical arbitrage strategies, a long horizon trading opportunity that generates a riskless profit. The results of this section provide an investor with a tool to investigate empirically if some strategies (for example momentum strategies) constitute statistical arbitrage opportunities or not.
In a recent paper, G. Malle and G. Robinson proposed a modular anologue to Brauer's famous \( k(B) \)-conjecture. If \( B \) is a \( p \)-block of a finite group with defect group \( D \), then they conjecture that \( l(B) \leq p^r \), where \( r \) is the sectional \( p \)-rank of \( D \). Since this conjecture is relatively new, there is obviously still a lot of work to do. This thesis is concerned with proving their conjecture for the finite groups of exceptional Lie type.
Since the early days of representation theory of finite groups in the 19th century, it was known that complex linear representations of finite groups live over number fields, that is, over finite extensions of the field of rational numbers.
While the related question of integrality of representations was answered negatively by the work of Cliff, Ritter and Weiss as well as by Serre and Feit, it was not known how to decide integrality of a given representation.
In this thesis we show that there exists an algorithm that given a representation of a finite group over a number field decides whether this representation can be made integral.
Moreover, we provide theoretical and numerical evidence for a conjecture, which predicts the existence of splitting fields of irreducible characters with integrality properties.
In the first part, we describe two algorithms for the pseudo-Hermite normal form, which is crucial when handling modules over ring of integers.
Using a newly developed computational model for ideal and element arithmetic in number fields, we show that our pseudo-Hermite normal form algorithms have polynomial running time.
Furthermore, we address a range of algorithmic questions related to orders and lattices over Dedekind domains, including computation of genera, testing local isomorphism, computation of various homomorphism rings and computation of Solomon zeta functions.
In the second part we turn to the integrality of representations of finite groups and show that an important ingredient is a thorough understanding of the reduction of lattices at almost all prime ideals.
By employing class field theory and tools from representation theory we solve this problem and eventually describe an algorithm for testing integrality.
After running the algorithm on a large set of examples we are led to a conjecture on the existence of integral and nonintegral splitting fields of characters.
By extending techniques of Serre we prove the conjecture for characters with rational character field and Schur index two.
A fast numerical method for an advanced electro-chemo-mechanical model is developed which is able to capture phase separation processes in porous materials. This method is applied to simulate lithium-ion battery cells, where the complex microstructure of the electrodes is fully resolved. The intercalation of ions into the popular cathode material LFP leads to a separation into lithium-rich and lithium-poor phases. The large concentration gradients result in high mechanical stresses. A phase-field method applying the Cahn-Hilliard equation is used to describe the diffusion. For the sake of simplicity, the linear elastic case is considered. Numerical tests for fully resolved three-dimensional granular microstructures are discussed in detail.
The iterative development and evaluation of the gamified stress management app “Stress-Mentor”
(2020)
The gamification of mHealth applications is a critically discussed topic. On one hand, studies show that gamification can have positive impact on an app’s usability and user experience. Furthermore, evidence grows that gamification can positively influence the regular usage of health apps. On the other hand it is questioned whether gamification is useful for health apps in all contexts, especially regarding stress management. However, to this point few studies investigated the gamification of stress management apps.
This thesis describes the iterative development of the gamified stress management app “Stress-Mentor” and examines whether the implemented gamification concept results in changes in the app’s usage behavior, as well as in usability and user experience ratings.
The results outline how the users’ involvement in “Stress-Mentor’s” development through different studies influenced the app’s design and helped to identify necessary improvements. The thesis also shows that users who received a gamified app version used the app more frequently than users of a non-gamified control group.
While gamification of stress management is critically discussed, it was positively received by the users of “Stress-Mentor” throughout the app’s development. The results also showed that gamification can have positive effects on the usage behavior of a stress management app and therefore, results in an increased exposure to the app’s content. Moreover, an expert study outlined the applicability of “Stress-Mentor’s” concept for other health contexts.
This thesis addresses several challenges for sustainable logistics operations and investigates (1) the integration of intermediate stops in the route planning of transportation vehicles, which especially becomes relevant when alternative-fuel vehicles with limited driving range or a sparse refueling infrastructure are considered, (2) the combined planning of the battery replacement infrastructure and of the routing for battery electric vehicles, (3) the use of mobile load replenishment or refueling possibilities in environments where the respective infrastructure is not available, and (4) the additional consideration of the flow of goods from the end user in backward direction to the point of origin for the purpose of, e.g., recapturing value or proper disposal. We utilize models and solution methods from the domain of operations research to gain insights into the investigated problems and thus to support managerial decisions with respect to these issues.
Reactive absorption with amines is the most important technique for the removal of CO2
from gas streams, e.g. from flue gas, natural gas or off-gas from the cement industry.
In this work a rigorous simulation model for the absorption and desorption of CO2 with
an amine-containing solvent is validated using data from pilot plants of various sizes.
This model was then coupled with a detailed simulation of a coal-fired power plant.
The power generation efficiency drop with CO2 capture was determined and process
parameters in the power plant and separation process were optimized. It was shown
that the high energy demand of CO2 separation significantly reduces power generation
efficiencies, which underlines the need for improvements. This can be achieved by better
solvents or by advanced process designs. In this work such improved CO2 separation
processes are described and evaluated by detailed simulation studies.
In order to develop detailed rigorous simulation models for reactive absorption with novel
solvent systems, a precise knowledge of the liquid phase reaction kinetics is necessary.
There are well established techniques for measuring species distributions in equilibirated
aqueous amine solutions by NMR spectrosopy. However, the existing NMR techniques
cannot be used for monitoring fast reactions in these solutions. Therefore, in this work
a novel temperature-controlled micro-reactor NMR probe head was developed which
enables studying reaction kinetics with time constants in the range of seconds.
On this basis, modern solvent systems for CO2 absorption can be characterized and
the scale-up of separation process for future plants can be accompanied using rigorous
process simulation.
Photonic crystals are inhomogeneous dielectric media with periodic variation of the refractive index. A photonic crystal gives us new tools for the manipulation of photons and thus has received great interests in a variety of fields. Photonic crystals are expected to be used in novel optical devices such as thresholdless laser diodes, single-mode light emitting diodes, small waveguides with low-loss sharp bends, small prisms, and small integrated optical circuits. They can be operated in some aspects as "left handed materials" which are capable of focusing transmitted waves into a sub-wavelength spot due to negative refraction. The thesis is focused on the applications of photonic crystals in communications and optical imaging: • Photonic crystal structures for potential dispersion management in optical telecommunication systems • 2D non-uniform photonic crystal waveguides with a square lattice for wide-angle beam refocusing using negative refraction • 2D non-uniform photonic crystal slabs with triangular lattice for all-angle beam refocusing • Compact phase-shifted band-pass transmission filter based on photonic crystals
Drought is a significant environmental factor that can impair plant growth and development, leading to reduced crop productivity or even plant death. Maintaining sugar distribution from source to sink is crucial for increasing crop production under water limitation conditions. Numerous studies have suggested that nutrition fertilization, especially potassium (K), can enhance plant growth and yield production. To investigate the mechanism of K in sugar long-distance transportation under drought stress, we established a soil-grow system and a hydroponic-grow system with varying amounts of potassium supplementation and analyzed the biochemical and molecular responses in Arabidopsis and potato plants under drought stress conditions. Our findings showed that excess potassium fertilization limited sucrose metabolism, leading to lower drought tolerance in Arabidopsis in both grow systems. However, higher potassium supplementation altered sugar relocation and potassium movement, resulting in an increase in starch yield production in both potato plants with different sink strength capacities. We also proposed that a low amount of sodium increases Arabidopsis drought tolerance under low potassium conditions since a low amount of sodium can improve the control of osmotic potential, leading to more water being retained in plant cells.
Silicon (Si) has received considerable attention recently for its potential in mitigating drought stress, although the effects vary among different plant species. To investigate the mechanism of Si in drought stress tolerance, we applied monosilicic acid in hydroponic media and then applied PEG8000 to simulate drought stress. Our findings revealed that Si-dependent drought mitigation occurred more in the shoot than in the root of Arabidopsis, and we observed silicon accumulation in the shoot of Arabidopsis. In Si-treated plants, more glucose was accumulated in the vacuole, leading to better osmotic potential control under drought stress. RNA sequencing analysis showed that Si altered the activity of sugar transporters and the sugar metabolism process, and increased photosynthesis. However, Si-dependent regulation in sugar transporter showed different responses in potato. Understanding the mechanism of Si in potato requires further studies. Overall, our dissertation provides important information for clarifying the mechanism of Si in drought stress, which forms the basis for further investigation.
Aim of this work was the extension and development of a coupled Computational Fluid Dynamics (CFD) and population balance model (PBM) solver to enable a simulation aided design of stirred liquid-liquid extraction columns. The principle idea is to develop a new design methodology based on a CFD-PBM approach and verify it with existing data and correlations. On this basis, the separation performance in any apparatus geometry should be possible to predict without any experimental input. Reliable “experiments in silico” (computer calculations) should give the engineer a valuable and user-friendly tool for early design studies at minimal costs.
The layout of extraction columns is currently based on experimental investigations from miniplant to pilot plant and a scale-up to the industrial scale. The hydrodynamic properties can be varied by geometrical adjustments of the stirrer diameter, the stirrer height, the free cross sectional area of the stator, the compartment height as well as the positioning and the size of additional baffles. The key parameter for the liquid–liquid extraction is the yield which is mainly determined at the in- and outlets of the column. Local phenomena as the swirl structure are influenced by geometry changes. However, these local phenomena are generally neglected in state-of-the are design methodologies due to the complex required measurement techniques. A geometrical optimization of the column therefore still results in costs for validation experiments as assembly and operation of the column, which can be reduced by numerical investigations. The still mainly in academics used simulation based layout of counter-current extraction columns is based at the beginning of this work on one dimensional simulations of extraction columns and first three dimensional simulations. The one dimensional simulations are based on experimental derived, geometrical dependent correlations for the axial backmixing (axial dispersion), the hold-up, the phase fraction, the droplet sedimentation and the energy dissipation. A combination of these models with droplet population balance modeling resulted in a description of the complex droplet-droplet interactions (droplet size) along the column height. The three dimensional CFD simulations give local information about the flow field (velocity, swirl structure) based on the used numerical mesh corresponding to the real geometry. A coupling of CFD with population balance modeling further provides information about the local droplet size. A backcoupling of the droplet size with the CFD (drag model) results in an enhancement of the local hydrodynamics (e.g. hold-up, dispersed phase velocity). CFD provided local information about the axial dispersion coefficient of simple geometrical design (e.g. Rotating Disc Contactor (RDC) column). First simulations of the RDC column using a two dimensional rotational geometry combined with population balance modeling were performed and gave local information about the droplet size for different boundary conditions (rotational speed, different column sizes).
In this work, two different column types were simulated using an extended OpenSource CFD code. The first was the RDC column, which were mainly used for code development due to its simple geometry. The Kühni DN32 column is equipped with a six-baffled stirring device and flat baffles for disturbing the flow and requires a full three dimensional description. This column type was mainly used for experimental validation of the simulations due to the low required volumetric flow rate. The Kühni DN60 column is similar to the Kühni DN32 column with slight changes to the stirring device (4-baffles) and was used for scale up investigations. For the experimental validation of the hydrodynamics, laser based measurement techniques as Particle Image Velocimetry (PIV) and Laser Induced Fluorescence (LIF) were used. A good agreement between the experimental derived values for velocity, hold-up and energy dissipation, experimentally derived correlations from literature and the simulations with a modified Euler-Euler based OpenSource CFD code could be found. The experimental derived axial dispersion coefficient was further compared to Euler-Lagrange simulations. The experimental derived correlations for the Kühni DN32 in literature fit to the simulated values. Also the axial dispersion coefficient for the dispersed phase satisfied a correlation from literature. However, due to the complexity of the dispersed phase axial dispersion coefficient measurement, the available correlations gave no distinct agreement to each other.
A coupling of the modified Euler-Euler OpenSource CFD code was done with a one group population balance model. The implementation was validated to the analytical solution of the population balance equation for constant breakage and coalescence kernels. A further validation of the population balance transport equation was done by comparing the results of a five compartment section to the results of the commercial CFD code FLUENT using the Quadrature Method of Moments (QMOM).
For the simulation of the droplet-droplet interactions in liquid-liquid extraction columns, several breakage and coalescence models are available in the literature. The models were compared to each other using the one-group population balance model in Matlab which allows the determination of the minimum stable droplet diameter at a certain energy dissipation. Based on this representation, it was possible to determine the parameters for a specific breakage and coalescence model combination which allowed the simulation of a Kühni miniplant column at different rotational speeds. The resulting simulated droplet size was in very good agreement to the experimental derived droplet size from literature. Several column designs of the DN32 were investigated by changing the compartment height and the axial stirrer position. It could be shown that a decrease of the stirrer position increases the phase fraction inside the compartment. At the same time, the droplet size decreases inside the compartment, which allows a higher mass transfer due to a higher available interfacial area. However, the shifting results in an expected earlier flooding of the column due to a compressed flow structure underneath the stirring device. In a next step, the code was further extended by mass transfer equations based on the two-film theory. Mass transfer coefficient models for the dispersed and continuous phase were investigated for the RDC column design.
A first mass transfer simulation of a full miniplant column was done. The change in concentration was accounted by the mixture density, viscosity and interfacial tension in dependence of the concentration, which affects the calculation of the droplet size. The results of the column simulation were compared to own experimental data of the column. It could be shown that the concentration profile along the column height can be predicted by the presented CFD/population balance/mass transfer code. The droplet size decreases corresponding to the interfacial tension along the column height. Compared to the experimental derived droplet size at the outlet, the simulation is in good agreement.
Besides the occurrence of a mono dispersed droplet size, high breakage may lead to the generation of small satellite droplets and coalescence underneath the stator leads to larger droplets inside the column and hence to a change of the hold-up and of the flooding point. A multi-phase code was extended by the Sectional Quadrature Method of Moment (SQMOM) allowing a modeling of the droplet interactions of bimodal droplet interactions or multimodal distributions. The implementations were in good agreement to the analytical solution. In addition, the simulation of an RDC column section showed the different distribution of the smaller droplets and larger droplets. The smaller droplets tend to follow the continuous phase flow structure and show a higher distribution of inside the column. The larger droplets tend to rise directly through the column and show only a low influence to the continuous phase flow.
The current results strengthen the use of CFD for the layout of liquid-liquid extraction columns in future. The coupling of CFD/PBM and mass transfer using an OpenSource CFD code allows the investigation of computational intensive column designs (e.g. pilot plant columns). Furthermore the coupled code enhances the accuracy of the hydrodynamics simulations and leads to a better understanding of counter-current liquid-liquid extraction columns. The gained correlation were finally used as an input for one dimensional mass transfer simulations, where a perfect fit of the concentration profiles at varied boundary conditions could be obtained. By using the multi-scale approach, the computational time for mass transfer simulations could be reduced to minutes. In future, with increasing computational power, a further extend of the multiphase CFD/SQMOM model including mass transfer equation will provide an efficient tool to model multimodal and multivariate systems as bubble column reactors.
The main goal of this work is to model size effects, as they occur in materials with an intrinsic microstructure at the consideration of specimens that are not by orders larger than this microstructure. The micromorphic continuum theory as a generalized continuum theory is well suited to account for the occuring size effects. Thereby additional degrees of freedoms capture the independent deformations of these microstructures, while they provide additional balance equation. In this thesis, the deformational and configurational mechanics of the micromorphic continuum is exploited in a finite-deformation setting. A constitutive and numerical framework is developed, in which also the material-force method is advanced. Furthermore the multiscale modelling of thin material layers with a heterogeneous substructure is of interest. To this end, a computational homogenization framework is developed, which allows to obtain the constitutive relation between traction and separation based on the properties of the underlying micromorphic mesostructure numerically in a nested solution scheme. Within the context of micromorphic continuum mechanics, concepts of both gradient and micromorphic plasticity are developed by systematically varying key ingredients of the respective formulations.
In this dissertation we apply financial mathematical modelling to electricity markets. Electricity is different from any other underlying of financial contracts: it is not storable. This means that electrical energy in one time point cannot be transferred to another. As a consequence, power contracts with disjoint delivery time spans basically have a different underlying. The main idea throughout this thesis is exactly this two-dimensionality of time: every electricity contract is not only characterized by its trading time but also by its delivery time.
The basis of this dissertation are four scientific papers corresponding to the Chapters 3 to 6, two of which have already been published in peer-reviewed journals. Throughout this thesis two model classes play a significant role: factor models and structural models. All ideas are applied to or supported by these two model classes. All empirical studies in this dissertation are conducted on electricity price data from the German market and Chapter 4 in particular studies an intraday derivative unique to the German market. Therefore, electricity market design is introduced by the example of Germany in Chapter 1. Subsequently, Chapter 2 introduces the general mathematical theory necessary for modelling electricity prices, such as Lévy processes and the Esscher transform. This chapter is the mathematical basis of the Chapters 3 to 6.
Chapter 3 studies factor models applied to the German day-ahead spot prices. We introduce a qualitative measure for seasonality functions based on three requirements. Furthermore, we introduce a relation of factor models to ARMA processes, which induces a new method to estimate the mean reversion speed.
Chapter 4 conducts a theoretical and empirical study of a pricing method for a new electricity derivative: the German intraday cap and floor futures. We introduce the general theory of derivative pricing and propose a method based on the Hull-White model of interest rate modelling, which is a one-factor model. We include week futures prices to generate a price forward curve (PFC), which is then used instead of a fixed deterministic seasonality function. The idea that we can combine all market prices, and in particular futures prices, to improve the model quality also plays the major role in Chapter 5 and Chapter 6.
In Chapter 5 we develop a Heath-Jarrow-Morton (HJM) framework that models intraday, day-ahead, and futures prices. This approach is based on two stochastic processes motivated by economic interpretations and separates the stochastic dynamics in trading and delivery time. Furthermore, this framework allows for the use of classical day-ahead spot price models such as the ones of Schwartz and Smith (2000), Lucia and Schwartz (2002) and includes many model classes such as structural models and factor models.
Chapter 6 unifies the classical theory of storage and the concept of a risk premium through the introduction of an unobservable intrinsic electricity price. Since all tradable electricity contracts are derivatives of this actual intrinsic price, their prices should all be derived as conditional expectation under the risk-neutral measure. Through the intrinsic electricity price we develop a framework, which also includes many existing modelling approaches, such as the HJM framework of Chapter 5.
The main concern of this contribution is the computational modeling of biomechanically relevant phenomena. To minimize resource requirements, living biomaterials commonly adapt to changing demands. One way to do so is the optimization of mass. For the modeling of biomaterials with changing mass, we distinguish between two different approaches: the coupling of mass changes and deformations at the constitutive level and at the kinematic level. Mass change at the constitutive level is typically realized by weighting the free energy function with respect to the density field, as experimentally motivated by Carter and Hayes [1977] and computationally realized by Harrigan and Hamilton [1992]. Such an ansatz enables the simulation of changes in density while the overall volume remains unaffected. In this contribution we call this effect remodeling. Although in principle applicable for small and large strains, this approach is typically adopted for hard tissues, e.g. bone, which usually undergo small strain deformations. Remodeling in anisotropic materials is realized by choosing an appropriate anisotropic free energy function. <br> Within the kinematic coupling, a changing mass is characterized through a multiplicative decomposition of the deformation gradient into a growth part and an elastic part, as first introduced in the context of plasticity by Lee [1969]. In this formulation, which we will refer to as growth in the following, mass changes are attributed to changes in volume while the material density remains constant. This approach has classically been applied to model soft tissues undergoing large strains, e.g. the arterial wall. The first contribution including this ansatz is the work by Rodriguez, Hoger and McCulloch [1994]. To model anisotropic growth, an appropriate anisotropic growth deformation tensor has to be formulated. In this contribution we restrict ourselves to transversely isotropic growth, i.e., growth characterized by one preferred direction. On that account, we define a transversely isotropic growth deformation tensor determined by two variables, namely the stretch ratios parallel and perpendicular to the characteristic direction. <br> Another method of material optimization is the adaption of the inner structure f a material to its loading conditions. In anisotropic materials this can be realized by a suitable orientation of the material directions. For example, the trabeculae in the human femur head are oriented such that they can carry the daily loads with an optimum mass. Such a behavior can also be observed in soft tissues. For instance, the fibers of muscles and the collagen fibers in the arterial wall are oriented along the loading directions to carry a maximum of mechanical load. If the overall loading conditions change, for instance during a balloon angioplasty or a stent implantation, the material orientation readapts, which we call reorientation. The anisotropy type in biomaterials is often characterized by fiber reinforcement. A particular subclass of tissues, which includes muscles, tendons and ligaments, is featured by one family of fibers. More complex microstructures, such as arterial walls, show two fiber families, which do not necessarily have to be perpendicular. Within this contribution we confine ourselves to the first case, i.e., transversely isotropic materials indicated by one characteristic direction. The reorientation of the fiber direction in biomaterials is commonly smooth and continuous. For transverse isotropy it can be described by a rotation of the characteristic direction. Analogous to the theory of shells, we additionally exclude drilling rotations, see also Menzel [2006]. However, the driving force for these reorientation processes is still under discussion. Mathematical considerations promote strain driven reorientations. As discussed, for instance, in Vianello [1996], the free energy reaches a critical state for coaxial stresses and strains. For transverse isotropy, it can be shown that this can be achieved if the characteristic direction is aligned with a principal strain direction. From a biological point of view, depending on the kind of material (i.e. bone, muscle tissue, cartilage tissue, etc.), both strains and stresses can be suggested as stimuli for reorientation. Thus, whithin this contribution both approaches are investigated. <br> In contrast to previous works, in which remodeling, growth and reorientation are discussed separately, the present work provides a framework comprising all of the three mentioned effects at once. This admits a direct comparison how and on which level the individual phenomenon is introduced into the material model, and which influence it has on the material behavior. For a uniform description of the phenomenological quantities an internal variable approach is chosen. Moreover, we particularly focus on the algorithmic implementation of the three effects, each on its own, into a finite element framework. The nonlinear equations on the local and the global level are solved by means of the Newton-Raphson scheme. Accordingly, the local update of the internal variables and the global update of the deformation field are consistently linearized yielding the corresponding tangent moduli. For an efficient implementation into a finite element code, unitized update algorithms are given. The fundamental characteristics of the effects are illustrated by means of some representative numerical simulations. Due to the unified framework, combinations of the individual effects are straightforward.
Extensions of Shallow Water Equations The subject of the thesis of Michael Hilden is the simulation of floods in urban areas. In case of strong rain events, water can flow out of the overloaded sewer system onto the street and damage the connected houses. The dependable simulation of water flow out of a manhole ("manhole") and over a curb ("curb") is crucial for the assessment of the flood risks. The incompressible 3D-Navier-Stokes Equations (3D-NSE) describe the free surface flow of water accurately, but require expensive computations. Therefore, the less CPU-intensive (factor ca.1/100) Shallow Water Equations (SWE) are usually applied in hydrology. They can be derived from 3D-NSE under the assumption of a hydrostatic pressure distribution via depth-integration and are applied successfully in particular to simulations of river flow processes. The SWE-computations of the flow problems "manhole" and "curb" differ to the 3D-NSE results. Thus, SWE need to be extended appropriately to give reliable forecasts for flood risks in urban areas within reduced computational efforts. These extensions are developed based on physical considerations not considered in the classical SWE. In one extension, a vortex layer on the ground is separated from the main flow representing its new bottom. In a further extension, the hydrostatic pressure distribution is corrected by additional terms due to approximations of vertical velocities and their interaction with the flow. These extensions increase the quality of the SWE results for these flow problems up to the quality level of the NSE results within a moderate increase of the CPU efforts.
Feature Based Visualization
(2007)
In this thesis we apply powerful mathematical tools such as interval arithmetic for applications in computational geometry, visualization and computer graphics, leading to robust, general and efficient algorithms. We present a completely novel approach for computing the arrangement of arbitrary implicit planar curves and perform ray casting of arbitrary implicit functions by jointly achieving, for the first time, robustness, efficiency and flexibility. Indeed we are able to render even the most difficult implicits in real-time with guaranteed topology and at high resolution. We use subdivision and interval arithmetic as key-ingredients to guarantee robustness. The presented framework is also well-suited for applications to large and unstructured data sets due to the inherent adaptivity of the techniques that are used. We also approach the topic of tensors by collaborating with mechanical engineers on comparative tensor visualization and provide them with helpful visualization paradigms to interpret the data.
Magnetic and Structural Characterization of Isolated Gaseous Ions by XMCD and IRMPD Spectroscopy
(2017)
This thesis comprises four independent research studies on the magnetic and structural characterization of isolated ions in the gas phase. The electrospray ionization (ESI) technique is used for the transfer of (multi-)metallic complexes and organic molecules from solution into the gas phase. The subsequent storage of molecular ions in ion traps allows for a variety of spectroscopic methods in order to investigate the intrinsic properties of the isolated species void of solvent, crystal lattice, bulk or supporting surface effects. The magnetic properties of metal complexes are elucidated by gas phase X-ray magnetic circular dichroism (XMCD) spectroscopy. The element selective technique in combination with sum rule analysis allows for a separate determination of spin and orbital magnetic moments at different metal centers. Structural investigations on isolated molecular ions in terms of coordination sphere, binding motifs and hydrogen bonds are conducted using infrared multiple photon dissociation (IRMPD) spectroscopy. A resonant two color IRMPD technique serves to increase fragmentation yields, overcome dissociation bottlenecks and reveal otherwise dark bands. Comparison of experimental IRMPD spectra with calculated harmonic absorption spectra by density functional theory (DFT) provides structural assignments for a profound understanding of intra- and intermolecular interactions.
A building-block model reveals new insights into the biogenesis of yeast mitochondrial ribosomes
(2020)
Most of the mitochondrial proteins in yeast are encoded in the nuclear genome, get synthesized by cytosolic ribosomes and are imported via TOM and TIM23 into the matrix or other subcompartments of mitochondria. The mitochondrial DNA in yeast however also encodes a small set of 8 proteins from which most are hydrophobic membrane proteins and build core components of the OXPHOS complexes. They get synthesized by mitochondrial ribosomes which are descendants of bacterial ribosomes and still have some similarities to them. On the other hand, mitochondrial ribosomes experienced various structural and functional changes during evolution that specialized them for the synthesis of the mitochondrial encoded membrane proteins. The mitoribosome contains mitochondria-specific ribosomal proteins and replaced the bacterial 5S rRNA by mitochondria-specific proteins and rRNA extensions. Furthermore, the mitoribosome is tethered to the inner mitochondrial membrane to facilitate a co-translational insertion of newly synthesized proteins. Thus, also the assembly process of mitoribosomes differs from that of bacteria and is to date not well understood.
Therefore, the biogenesis of mitochondrial ribosomes in yeast should be investigated. To this end, a strain was generated in which the gene of the mitochondrial RNA-polymerase RPO41 is under control of an inducible GAL10-promoter. Since the scaffold of ribosomes is built by ribosomal RNAs, the depletion of the RNA-polymerase subsequently leads to a loss of mitochondrial ribosomes. Reinduction of Rpo41 initiates the assembly of new mitoribosomes, which makes this strain an attractive model to study mitoribosome biogenesis.
Initially, the effects of Rpo41 depletion on cellular and mitochondrial physiology was investigated. Upon Rpo41 depletion, growth on respiratory glycerol medium was inhibited. Furthermore, mitochondrial ribosomal 21S and 15S rRNA was diminished and mitochondrial translation was almost completely absent. Also, mitochondrial DNA was strongly reduced due to the fact that mtDNA replication requires RNA primers that get synthesized by Rpo41.
Next, the effect of reinduction of Rpo41 on mitochondria was tested. Time course experiments showed that mitochondrial translation can partially recover from 48h Rpo41 depletion within a timeframe of 4.5h. Sucrose gradient sedimentation experiments further showed that the mitoribosomal constitution was comparable to wildtype control samples during the time course of 4.5h of reinduction, suggesting that the ribosome assembly is not fundamentally altered in Gal-Rpo41 mitochondria. In addition, the depletion time was found to be critical for recovery of mitochondrial translation and mitochondrial RNA levels. It was observed that after 36h of Rpo41 depletion, the rRNA levels and mitochondrial translation recovered to almost 100%, but only within a time course of 10h.
Finally, mitochondria from Gal-Rpo41 cells isolated after different timepoints of reinduction were used to perform complexome profiling and the assembly of mitochondrial protein complexes was investigated. First, the steady state conditions and the assembly process of mitochondrial respiratory chain complexes were monitored. The individual respiratory chain complexes and the super-complexes of complex III, complex IV and complex V were observed. Furthermore, it was seen that they recovered from Rpo41 depletion within 4.5h of reinduction. Complexome profiles of the mitoribosomal small and large subunit discovered subcomplexes of mitoribosomal proteins that were assumed to form prior to their incorporation into assembly intermediates. The complexome profiles after reinduction indeed showed the formation of these subcomplexes before formation of the fully assembled subunit. In the mitochondrial LSU one subcomplex builds the membrane facing protuberance and a second subcomplex forms the central protuberance. In contrast to the preassembled subcomplexes, proteins that were involved in early assembly steps were exclusively found in the fully assembled subunit. Proteins that assemble at the periphery of the mitoribosome during intermediate and late assembly steps where found in soluble form suggesting a pool of unassembled proteins that supply assembly intermediates with proteins.
Taken together, the findings of this thesis suggest a so far unknow building-block model for mitoribosome assembly in which characteristic structures of the yeast mitochondrial ribosome form preassembled subcomplexes prior to their incorporation into the mitoribosome.
About 2.4 Ga ago the Great Oxygenation Event (GOE) started the permanent oxygenation of Earth’s anoxic atmosphere. The oxygen was most likely produced by oxygenic photosynthesis in Cyanobacteria. However, hints for local occurrences of Cyanobacterial life and free oxygen exists for at least 300 Ma prior to the GOE. Different hypotheses were proposed to explain this delay between the evolution of oxygen producers and the start of the GOE. For this thesis, theoretic predictions made by two of those hypotheses were tested in laboratory experiments using ancestral, basal clade Cyanobacteria grown under simulated Archean like conditions.
Cyanobacteria might have evolved in freshwater environments and subsequently had to adapt to the higher salinity of the Archean ocean. In turn, this would have delayed their global expansion required for the GOE. Experiments with the most primitive freshwater Cyanobacterium Gloeobacter violaceus PCC 7421, showed its ability to tolerate and slowly grow in brackish water, thereby providing a route for the evolution of open ocean dwelling, salt tolerant species. The Archean ocean may have presented another hurdle to Cyanobacterial expansion as it contained large amounts of Fe(II), which is presumed to be toxic to Cyanobacteria. This thesis shows that the localised activity of Cyanobacteria could have formed marine oxygen oases in shallow coastal regions. This would have negated the toxicity of Fe(II) and could have produced more net O2 then modern oxic systems. Additionally, the formation of green rust was observed, which seemed to have a toxic effect on Cyanobacterial growth and could be an important factor for the genesis of banded iron formations.
In conclusion, this thesis could show the viability of both, the “freshwater-origin” and “Fe(II)-toxicity”, hypothesis. Nevertheless, how long it took for Cyanobacteria to overcome the restrictions described above to expand into the open ocean is uncertain and needs to be further studied.
A main result of this thesis is a conceptual proof of the fact that the weighted number of tropical curves of given degree and genus, which pass through the right number of general points in the plane (resp., which pass through general points in R^r and represent a given point in the moduli space of genus g curves) is independent of the choices of points. Another main result is a new correspondence theorem between plane tropical cycles and plane elliptic algebraic curves.
This thesis shows an approach to combine the advantages of MBS tyre models and FEM models for the use in full vehicle simulations. The procedure proposed in this thesis aims to describe a nonlinear structure with a Finite Element approach combined with nonlinear model reduction methods. Unlike most model reduction methods - as the frequently used Craig-Bampton approach - the method of Proper Orthogonal Decomposition (POD) offers a projection basis suitable for nonlinear models. For the linear wave equation, the POD method is studied comparing two different choices of snapshot sets. Set 1 consists of deformation snapshots, and set 2 additionally contains velocities and accelerations. An error analysis proves no convergence guarantee for deformations only. For inclusion of derivatives it yields an error bound diminishing for small time steps. The numerical results show a better behaviour for the derivative snapshot method, as long as the sum of the left-over eigenvalues is significant. For the reduction of nonlinear systems - especially when using commercial software - it is necessary to decouple the reduced surrogate system from the full model. To achieve this, a lookup table approach is presented. It makes use of the preceding computation step with the full model necessary to set up the POD basis (training step). The nonlinear term of inner forces and the stiffness matrix are output and stored in a lookup table for the reduced system. Numerical examples include a nonlinear string in Matlab and an airspring computed in Abaqus. Both examples show that effort reductions of two orders of magnitude are possible within a reasonable error tolerance. The lookup approaches perform faster than the Trajectory Piecewise Linear (TPWL) method and produce comparable errors. Furthermore, the Abaqus example shows the influence of training excitation on the quality of the reduced model.
Virtual Possibilities: Exploring the Role of Emerging Technologies in Work and Learning Environments
(2024)
The present work aims to investigate whether virtual reality can support learning as well as vocational work environments. To this end, four studies were conducted, with the first set investigating the demands for vocational workers and the impact of input methods on participant performance. These studies laid the foundation needed to create studies incorporating virtual reality research. The second set of studies was concerned with the impact of virtual reality on learning performance as well as the influence of binaural stimuli presentation on task performance. Results of each study are discussed individually and in conjunction with one another. The four studies are further supplemented with further research conducted by the author as well as an analysis of the growing field of virtual reality-based research. The thesis closes by embedding the discussed work into the scientific landscape and tries to give an outlook for virtual reality-based use cases in the future.
In the last few years a lot of work has been done in the investigation of Brownian motion with point interaction(s) in one and higher dimensions. Roughly speaking a Brownian motion with point interaction is nothing else than a Brownian motion whose generator is disturbed by a measure supported in just one point.
The purpose of the present work is the introducing of curve interactions of the two dimensional Brownian motion for a closed curve \(\mathcal{C}\). We will understand a curve interaction as a self-adjoint extension of the restriction of the Laplacian to the set of infinitely often continuously differentiable functions with compact support in \(\mathbb{R}^{2}\) which are constantly 0 at the closed curve. We will give a full description of all these self-adjoint extensions.
In the second chapter we will prove a generalization of Tanaka's formula to \(\mathbb{R}^{2}\). We define \(g\) to be a so-called harmonic single layer with continuous layer function \(\eta\) in \(\mathbb{R}^{2}\). For such a function \(g\) we prove
\begin{align}
g\left(B_{t}\right)=g\left(B_{0}\right)+\int\limits_{0}^{t}{\nabla g\left(B_{s}\right)\mathrm{d}B_{s}}+\int\limits_{0}^{t}\eta\left(B_{s}\right)\mathrm{d}L\left(s,\mathcal{C}\right)
\end{align}
where \(B_{t}\) is just the usual Brownian motion in \(\mathbb{R}^{2}\) and \(L\left(t,\mathcal{C}\right)\) is the connected unique local time process of \(B_{t}\) on the closed curve \(\mathcal{C}\).
We will use the generalized Tanaka formula in the following chapter to construct classes of processes related to curve interactions. In a first step we get the generalization of point interactions in a second step we get processes which behaves like a Brownian motion in the complement of \(\mathcal{C}\) and has an additional movement along the curve in the time- scale of \(L\left(t,\mathcal{C}\right)\). Such processes do not exist in the one point case since there we cannot move when the Brownian motion is in the point.
By establishing an approximation of a curve interaction by operators of the form Laplacian \(+V_{n}\) with "nice" potentials \(V_{n}\) we are able to deduce the existence of superprocesses related to curve interactions.
The last step is to give an approximation of these superprocesses by a sytem of branching particles. This approximation gives a better understanding of the related mass creation.
The main topic of this thesis is to define and analyze a multilevel Monte Carlo algorithm for path-dependent functionals of the solution of a stochastic differential equation (SDE) which is driven by a square integrable, \(d_X\)-dimensional Lévy process \(X\). We work with standard Lipschitz assumptions and denote by \(Y=(Y_t)_{t\in[0,1]}\) the \(d_Y\)-dimensional strong solution of the SDE.
We investigate the computation of expectations \(S(f) = \mathrm{E}[f(Y)]\) using randomized algorithms \(\widehat S\). Thereby, we are interested in the relation of the error and the computational cost of \(\widehat S\), where \(f:D[0,1] \to \mathbb{R}\) ranges in the class \(F\) of measurable functionals on the space of càdlàg functions on \([0,1]\), that are Lipschitz continuous with respect to the supremum norm.
We consider as error \(e(\widehat S)\) the worst case of the root mean square error over the class of functionals \(F\). The computational cost of an algorithm \(\widehat S\), denoted \(\mathrm{cost}(\widehat S)\), should represent the runtime of the algorithm on a computer. We work in the real number model of computation and further suppose that evaluations of \(f\) are possible for piecewise constant functions in time units according to its number of breakpoints.
We state strong error estimates for an approximate Euler scheme on a random time discretization. With this strong error estimates, the multilevel algorithm leads to upper bounds for the convergence order of the error with respect to the computational cost. The main results can be summarized in terms of the Blumenthal-Getoor index of the driving Lévy process, denoted by \(\beta\in[0,2]\). For \(\beta <1\) and no Brownian component present, we almost reach convergence order \(1/2\), which means, that there exists a sequence of multilevel algorithms \((\widehat S_n)_{n\in \mathbb{N}}\) with \(\mathrm{cost}(\widehat S_n) \leq n\) such that \( e(\widehat S_n) \precsim n^{-1/2}\). Here, by \( \precsim\), we denote a weak asymptotic upper bound, i.e. the inequality holds up to an unspecified positive constant. If \(X\) has a Brownian component, the order has an additional logarithmic term, in which case, we reach \( e(\widehat S_n) \precsim n^{-1/2} \, (\log(n))^{3/2}\).
For the special subclass of $Y$ being the Lévy process itself, we also provide a lower bound, which, up to a logarithmic term, recovers the order \(1/2\), i.e., neglecting logarithmic terms, the multilevel algorithm is order optimal for \( \beta <1\).
An empirical error analysis via numerical experiments matches the theoretical results and completes the analysis.
In recent years, enormous progress has been made in the field of Artificial Intelligence (AI). Especially the introduction of Deep Learning and end-to-end learning, the availability of large datasets and the necessary computational power in form of specialised hardware allowed researchers to build systems with previously unseen performance in areas such as computer vision, machine translation and machine gaming. In parallel, the Semantic Web and its Linked Data movement have published many interlinked RDF datasets, forming the world’s largest, decentralised and publicly available knowledge base.
Despite these scientific successes, all current systems are still narrow AI systems. Each of them is specialised to a specific task and cannot easily be adapted to all other human intelligence tasks, as would be necessary for Artificial General Intelligence (AGI). Furthermore, most of the currently developed systems are not able to learn by making use of freely available knowledge such as provided by the Semantic Web. Autonomous incorporation of new knowledge is however one of the pre-conditions for human-like problem solving.
This work provides a small step towards teaching machines such human-like reasoning on freely available knowledge from the Semantic Web. We investigate how human associations, one of the building blocks of our thinking, can be simulated with Linked Data. The two main results of these investigations are a ground truth dataset of semantic associations and a machine learning algorithm that is able to identify patterns for them in huge knowledge bases.
The ground truth dataset of semantic associations consists of DBpedia entities that are known to be strongly associated by humans. The dataset is published as RDF and can be used for future research.
The developed machine learning algorithm is an evolutionary algorithm that can learn SPARQL queries from a given SPARQL endpoint based on a given list of exemplary source-target entity pairs. The algorithm operates in an end-to-end learning fashion, extracting features in form of graph patterns without the need for human intervention. The learned patterns form a feature space adapted to the given list of examples and can be used to predict target candidates from the SPARQL endpoint for new source nodes. On our semantic association ground truth dataset, our evolutionary graph pattern learner reaches a Recall@10 of > 63 % and an MRR (& MAP) > 43 %, outperforming all baselines. With an achieved Recall@1 of > 34% it even reaches average human top response prediction performance. We also demonstrate how the graph pattern learner can be applied to other interesting areas without modification.
There are a lot of photonic micro- and nano-structures in nature that consist of materials with a low refractive index and that can keep up with artificial structures concerning optical properties like scattering or coloration. This work aims to understand the photonic structures in the silver ant Cataglyphis bombycina, the blue butterfly of genus Morpho, the beetle Entimus imperialis, which shows polarization-dependent reflection, and the white beetle Cyphochilus insulanus. Furthermore, corresponding micro- and nano-structures are fabricated.
Bioinspired models with the same optical properties as the investigated structures are developed and analyzed using geometric optics and finite-difference time-domain calculations. These models are qualitatively and quantitatively compared regarding their optical properties with the original structures and fabricated by direct laser writing. To mimic potential effects of material-based disorder of the natural photonic structures, a cellulose-based resist for direct laser writing is developed and examined.
Conventional resists in direct laser writing can be replaced by a resist containing cellulose derivatives. Here, different combinations of cellulose derivatives, initiators, and solvents are examined. The best performance is observed for a combination of methacrylated cellulose acetate (MACA500), 2-Isopropyl-9H-thioxanthen-9-one (ITX), and dimethyl sulfoxide (DMSO). These resists allow for direction is attained. The achieved cross-linking enables stable three-dimensional structures and, together with the possible resolution, allows to fabricate the model inspired by the white beetle Cyphochilus insulanus in the cellulose-based resist.
The silver appearance of the Cataglyphis bombycina can be completely explained with geometric optics in the prism-shaped hairs that cover its body. The more complex structures of the other three insects use photonic crystal-like material arrangements with a varying amount of disorder. The polarization dependence of the Entimus imperialis arises from a diamond structure inside the scales of the beetle and can be mimicked with a photonic woodpile crystal. The blue butterfly of the genus Morpho and the white beetle Cyphochilus insulanus both can be reduced to disordered Bragg stacks, in which the exact properties are achieved by introducing different amounts of disorder. For Cataglyphis bombycina, Entimus imperialis, and Cyphochilus insulanus, the developed bioinspired models are fabricated using conventional resists in direct laser writing. All models show a qualitative correspondence to the optical properties of the original structures.
The cellulose-based resists enable the use of polysaccharides in direct laser writing and the concepts can be transferred to other polysaccharides, like chitin. The analysis of the different natural photonic structures and the developed bioinspired models reveal a material independence of the structures that allows the fabrication of these models in different transparent materials.
Grey-box modelling deals with models which are able to integrate the following two kinds of information: qualitative (expert) knowledge and quantitative (data) knowledge, with equal importance. The doctoral thesis has two aims: the improvement of an existing neuro-fuzzy approach (LOLIMOT algorithm), and the development of a new model class with corresponding identification algorithm, based on multiresolution analysis (wavelets) and statistical methods. The identification algorithm is able to identify both hidden differential dynamics and hysteretic components. After the presentation of some improvements of the LOLIMOT algorithm based on readily normalized weight functions derived from decision trees, we investigate several mathematical theories, i.e. the theory of nonlinear dynamical systems and hysteresis, statistical decision theory, and approximation theory, in view of their applicability for grey-box modelling. These theories show us directly the way onto a new model class and its identification algorithm. The new model class will be derived from the local model networks through the following modifications: Inclusion of non-Gaussian noise sources; allowance of internal nonlinear differential dynamics represented by multi-dimensional real functions; introduction of internal hysteresis models through two-dimensional "primitive functions"; replacement respectively approximation of the weight functions and of the mentioned multi-dimensional functions by wavelets; usage of the sparseness of the matrix of the wavelet coefficients; and identification of the wavelet coefficients with Sequential Monte Carlo methods. We also apply this modelling scheme to the identification of a shock absorber.
We encounter directional data in numerous application areas such as astronomy, biology or engineering. Examples include the direction of arrival of cosmic rays, the direction of flight of migratory birds or the orientation of steel fibres in fibre-reinforced concrete.
In part I, we define and apply morphological operators, quantiles and depths for directional data. The morphological operators are defined for \(\mathcal{S}^{d−1}\)-valued images with \(\mathcal{S}^{d−1} = \{x \in \mathbb{R}^d :\sqrt{x^T x} = 1\}\) , \(d \geq 2\). Since an ordered structure is necessary for a definition of these operators, which is not naturally given between vectors, an order is determined with the help of the theory of statistical depth functionals.
This allows for defining the basic operators erosion and dilation as well as morphological (multi-scale) operators for \(\mathcal{S}^{d−1}\)-valued images based on them. The operators introduced are related to their grey value counterparts. Furthermore, quantiles and the "angular Mahalanobis" depth for directional data introduced by Ley
et al. (2014) are extended. The concept of Ley et al. (2014) provides useful geometric properties of the depth contours (such as convexity and rotational equivariance) and a Bahadur-type representation of the quantiles. Their concept is canonical for rotationally symmetric depth contours. However, it also produces rotationally symmetric depth contours when the underlying distribution is not rotationally
symmetric. We solve this lack of flexibility for distributions with elliptical depth contours. The basic idea is to deform the elliptic contours by a diffeomorphic mapping to rotationally symmetric contours, thus reverting to the canonical case in Ley et al. (2014). Our results are confirmed by a Monte Carlo simulation study and applied to the analysis of fibre directions in fibre-reinforced concrete. In Part II, we elaborate interdisciplinary results of statistical analysis and stochastic modelling in civil
engineering. Our statistical analysis of the correlation between production parameters (fibre length, fibre diameter, fibre volume fraction as well as casting method, superplasticiser content and specimen size) of ultra-high performance fibre reinforced concrete and the fibre system (spatial arrangement and orientation of the fibres) provides users with a better understanding of this relatively new composite material. The fibre system is modelled by a Boolean model and the fibre orientation by a one-parameter distribution. In addition, the behaviour under tensile loading is modelled.
Ambulatory assessment (AA) is becoming an increasingly popular research method in the fields of psychology and life science. Nevertheless, knowledge about the effects that design choices, such as questionnaire length (i.e., number of items per questionnaire), have on AA participants’ perceived burden, data quantity (i.e., compliance with the AA protocol), and data quality is still surprisingly restricted. The aims of this dissertation were to experimentally manipulate aspects of an AA study’s sampling strategy - sampling frequency (Study 1) and questionnaire length (Study 2) - and to investigate their impact on perceived burden, data quantity, and aspects of data quality in three papers. In Study 1, students (n = 313) received either 3 or 9 questionnaires per day for the first 7 days of the study. In Study 2, students (n = 282) received either a 33- or 82-item questionnaire 3 times a day for 14 days.
Paper 1 described that a higher sampling frequency (Study 1) led to a higher perceived participant burden, but did not affect other aspects of data quantity and quality. Furthermore, a longer questionnaire (Study 2) did not affect perceived participant burden or data quantity, but did lead to a lower within-person variability, and a lower within-person relationship between time-varying variables. Paper 2 investigated the effects of the sampling frequency (Study 1) on careless responding by identifying careless responding indices that could be applied to AA data and by extending the multilevel latent class analysis model to a multigroup multilevel latent class analysis model. Results indicated that a higher sampling frequency did not affect careless responding. Paper 3 investigated the effects of questionnaire length (Study 2) on (the relative impact of) response styles by extending the item response tree (IRTree) modeling approach to a multilevel data structure. Results indicated that a longer questionnaire led to a greater relative impact of RS.
Although further validation of the results is essential, I hope that future researchers will integrate the results of this dissertation when designing an AA study.
Magnetoelastic coupling describes the mutual dependence of the elastic and magnetic fields and can be observed in certain types of materials, among which are the so-called "magnetostrictive materials". They belong to the large class of "smart materials", which change their shape, dimensions or material properties under the influence of an external field. The mechanical strain or deformation a material experiences due to an externally applied magnetic field is referred to as magnetostriction; the reciprocal effect, i.e. the change of the magnetization of a body subjected to mechanical stress is called inverse magnetostriction. The coupling of mechanical and electromagnetic fields is particularly observed in "giant magnetostrictive materials", alloys of ferromagnetic materials that can exhibit several thousand times greater magnitudes of magnetostriction (measured as the ratio of the change in length of the material to its original length) than the common magnetostrictive materials. These materials have wide applications areas: They are used as variable-stiffness devices, as sensors and actuators in mechanical systems or as artificial muscles. Possible application fields also include robotics, vibration control, hydraulics and sonar systems.
Although the computational treatment of coupled problems has seen great advances over the last decade, the underlying problem structure is often not fully understood nor taken into account when using black box simulation codes. A thorough analysis of the properties of coupled systems is thus an important task.
The thesis focuses on the mathematical modeling and analysis of the coupling effects in magnetostrictive materials. Under the assumption of linear and reversible material behavior with no magnetic hysteresis effects, a coupled magnetoelastic problem is set up using two different approaches: the magnetic scalar potential and vector potential formulations. On the basis of a minimum energy principle, a system of partial differential equations is derived and analyzed for both approaches. While the scalar potential model involves only stationary elastic and magnetic fields, the model using the magnetic vector potential accounts for different settings such as the eddy current approximation or the full Maxwell system in the frequency domain.
The distinctive feature of this work is the analysis of the obtained coupled magnetoelastic problems with regard to their structure, strong and weak formulations, the corresponding function spaces and the existence and uniqueness of the solutions. We show that the model based on the magnetic scalar potential constitutes a coupled saddle point problem with a penalty term. The main focus in proving the unique solvability of this problem lies on the verification of an inf-sup condition in the continuous and discrete cases. Furthermore, we discuss the impact of the reformulation of the coupled constitutive equations on the structure of the coupled problem and show that in contrast to the scalar potential approach, the vector potential formulation yields a symmetric system of PDEs. The dependence of the problem structure on the chosen formulation of the constitutive equations arises from the distinction of the energy and coenergy terms in the Lagrangian of the system. While certain combinations of the elastic and magnetic variables lead to a coupled magnetoelastic energy function yielding a symmetric problem, the use of their dual variables results in a coupled coenergy function for which a mixed problem is obtained.
The presented models are supplemented with numerical simulations carried out with MATLAB for different examples including a 1D Euler-Bernoulli beam under magnetic influence and a 2D magnetostrictive plate in the state of plane stress. The simulations are based on material data of Terfenol-D, a giant magnetostrictive materials used in many industrial applications.
The fact that long fibre reinforced thermoplastic composites (LFT) have higher tensile
strength, modulus and even toughness, compared to short fibre reinforced
thermoplastics with the same fibre loading has been well documented in literature.
These are the underlying factors that have made LFT materials one of the most
rapidly growing sectors of plastics industry. New developments in manufacturing of
LFT composites have led to improvements in mechanical properties and price
reduction, which has made these materials an attractive choice as a replacement for
metals in automobile parts and other similar applications. However, there are still
several open scientific questions concerning the material selection leading to the
optimal property combinations. The present work is an attempt to clarify some of
these questions. The target was to develop tools that can be used to modify, or to
“tailor”, the properties of LFT composite materials, according to the requirements of
automobile and other applications.
The present study consisted of three separate case studies, focusing on the current
scientific issues on LFT material systems. The first part of this work was focused on
LGF reinforced thermoplastic styrenic resins. The target was to find suitable maleic
acid anhydride (MAH) based coupling agents in order to improve the fibre-matrix
interfacial strength, and, in this way, to develop an LGF concentrate suitable for
thermoplastic styrenic resins. It was shown that the mechanical properties of LGF
reinforced “styrenics” were considerably improved when a small amount of MAH
functionalised polymer was added to the matrix. This could be explained by the better fibre-matrix adhesion, revealed by scanning electron microscopy of fracture surfaces.
A novel LGF concentrate concept showed that one particular base material can be
used to produce parts with different mechanical and thermal properties by diluting the
fibre content with different types of thermoplastic styrenic resins. Therefore, this
concept allows a flexible production of parts, and it can be used in the manufacturing
of interior parts for automobile components.The second material system dealt with so called hybrid composites, consisting of
long glass fibre reinforced polypropylene (LGF-PP) and mineral fillers like calcium
carbonate and talcum. The aim was to get more information about the fracture
behaviour of such hybrid composites under tensile and impact loading, and to
observe the influence of the fillers on properties. It was found that, in general, the
addition of fillers in LGF-PP, increased stiffness but the strength and fracture
toughness were decreased. However, calcium carbonate and talcum fillers resulted
in different mechanical properties, when added to LGF-PP: better mechanical
properties were achieved by using talcum, compared to calcium carbonate. This
phenomenon could be explained by the different nucleation effect of these fillers,
which resulted in a different crystalline morphology of polypropylene, and by the
particle orientation during the processing when talc was used. Furthermore, the
acoustic emission study revealed that the fracture mode of LGF-PP changed when
calcium carbonate was added. The characteristic acoustic signals revealed that the
addition of filler led to the fibre debonding at an earlier stage of fracture sequence
when compared to unfilled LGF-PP.
In the third material system, the target was to develop a novel long glass fibre
reinforced composite material based on the blend of polyamide with thermoset
resins. In this study a blend of polyamide-66 (PA66) and phenol formaldehyde resin
(PFR) was used. The chemical structure of the PA66-PFR resin was analysed by
using small molecular weight analogues corresponding to PA66 and PFR
components, as well as by carrying out experiments using the macromolecular
system. Theoretical calculations and experiments showed that there exists a strong
hydrogen bonding between the carboxylic groups of PA66 and the hydroxylic groups
of PFR, exceeding even the strength of amide-water hydrogen bonds. This was
shown to lead to the miscible blends, when PFR was not crosslinked. It was also
found that the morphology of such thermoplastic-thermoset blends can be controlled
by altering ratio of blend components (PA66, PFR and crosslinking agent). In the
next phase, PA66-PFR blends were reinforced by long glass fibres. The studies
showed that the water absorption of the blend samples was considerably decreased,
which was also reflected in higher mechanical properties at equilibrium state.
Wie man aus zahlreichen Untersuchungen und Anwendungsbeispielen entnehmen
kann, besitzen langfaserverstärkte Thermoplaste (LFT) eine bessere Zugfestigkeit,
Biege- und Schlagzähigkeit im Vergleich zu kurzfaserverstärkten Thermoplasten. Die
Vorteile in den mechanischen Eigenschaften haben die LFT zu einem
schnellwachsenden Bereich in der Kunststoffindustrie gemacht. Neue Entwicklungen
in Bereich der Herstellung von LFT haben für zusätzliche Verbesserungen der
mechanischen Eigenschaften sowie eine Preisreduzierung der Materialien in den
vergangenen Jahren gesorgt, was die LFT zu einer attraktiven Wahl u.a. als Ersatz
von Metallen in Automobilteilen macht. Es stellen sich allerdings immer noch einige
offene wissenschaftliche Fragen in Bezug auf z.B. die Materialbeschaffenheit, um
optimale Eigenschaftskombinationen zu erreichen. Die vorliegende Arbeit versucht,
einige dieser Fragen zu beantworten. Ziel war es, Vorgehensweisen zu entwickeln,
mit denen man die Eigenschaften von LFT gezielt beeinflussen und so den
Anforderungen von Automobilen oder anderen Anwendungen anpassen oder
„maßschneidern“ kann.
Die vorliegende Arbeit besteht aus drei Teilen, welche sich auf unterschiedliche
Materialsysteme, angepasst an den aktuellen Bedarf und das Interesse der Industrie,
konzentrieren.
Der erste Teil der Arbeit richtet sich auf die Eigenschaftsoptimierung von
langglasfaserverstärkten (LGF) thermoplastischen Styrolcopolymeren und von
Blends aus diesen Materialien. Es wurden passende, auf Maleinsäureanhydride
(MAH) basierende Kopplungsmittel gefunden, um die Faser-Matrix-Haftung zu
optimieren. Weiterhin wurde ein LGF Konzentrat entwickelt, welches mit
verschiedenen thermoplastischen Styrolcopolymeren kompatibel ist und somit als
„Verstärkungsadditiv“ eingesetzt werden kann.Das Konzept für ein neues LGF-Konzentrat auf Basis des kompatiblen
Materialsystems konzentriert sich insbesondere darauf, dass ein Basismaterial für
die Herstellung von Bauteilen bereit gestellt werden kann, mit dessen Hilfe gezielt
verschiedene mechanische und thermomechanischen Eigenschaften durch das
Zumischen von verschiedenen Styrolcopoylmeren und Blends verbessert werden
können. Dieses Konzept ermöglicht eine sehr flexible Produktion von Bauteilen und
wird seine Anwendung bei der Herstellung von Bauteilen u.a. im Interieur von Autos
finden.
Das zweite Materialsystem basiert auf sogenannten hybriden Verbundwerkstoffen,
welche aus Langglasfasern und mineralischen Füllstoffen wie Kalziumkarbonat und
Talkum in einer Polypropylen (PP) - Matrix zusammengesetzt sind. Ziel war es, durch
detaillierte bruchmechanische Analysen genaue Informationen über das
Bruchverhalten dieser hybriden Verbundwerkstoffe bei Zug- und Schlagbelastung zu
bekommen, um dann die Unterschiede zwischen den verschiedenen Füllstoffen in
Bezug auf ihre Eigenschaften zu dokumentieren. Es konnte beobachtet werden, dass
bei Zugabe der Füllstoffe zum LGF-PP normalerweise die Steifigkeit weiter
verbessert wurde, jedoch die Festigkeit und Schlagzähigkeit abnahmen. Weiterhin
zeigten die verschiedenen Füllstoffe wie Kalziumkarbonat und Talkum
unterschiedliche mechanische Eigenschaften auf, wenn sie zusammen mit LGF
Verstärkung eingesetzt wurden: Bei der Zugabe von Talkum wurde u.a. eine deutlich
bessere Schlagzähigkeit als bei der Zugabe von Kalziumkarbonat festgestellt. Dieses
Phänomen konnte durch das unterschiedliche Nukleierungsverhalten des PPs erklärt
werden, welches in einer unterschiedlichen Kristallmorphologie von Polypropylen
resultierte. Weiterhin konnte man durch Messungen der akustischen Emmissionen
während der Zugbelastung eines bruchmechanischen Versuchskörpers aufzeigen,
dass die höhere Bruchzähigkeit von LGF-PP ohne Füllstoffe daraus resultiert, dass
Faser-Pullout schon bei geringeren Kräften vorhanden war.
Due to their superior weight-specific mechanical properties, carbon fibre epoxy composites (CFRP) are commonly used in aviation industry. However, their brittle failure behaviour limits the structural integrity and damage tolerance in case of impact (e.g. tool drop, bird strike, hail strike, ramp collision) or crash events. To ensure sufficient robustness, a minimum skin thickness is therefore prescribed for the fuselage, partially exceeding typical service load requirements from ground or flight manoeuvre load cases. A minimum skin thickness is also required for lightning strike protection purposes and to enable state-of-the-art bolted repair technology. Furthermore, the electrical conductivity of CFRP aircraft structures is insufficient for certain applications; additional metal components are necessary to provide electrical functionality (e.g. metal meshes on the outer skin for lightning strike protection, wires for electrical bonding and grounding, overbraiding of cables to provide electromagnetic shielding). The corresponding penalty weights compromise the lightweight potential that is actually given by the structural performance of CFRP over aluminium alloys.
Former research attempts tried to overcome these deficits by modifying the resin system (e.g. by addition of conductive particles or toughening agents) but could not prove sufficient enhancements. A novel holistic approach is the incorporation of highly conductive and ductile continuous metal fibres into CFRP. The basic idea of this hybrid material concept is to take advantage of both the electrical and mechanical capabilities of the integrated metal fibres in order to simultaneously improve the electrical conductivity and the damage tolerance of the composite. The increased density of the hybrid material is over-compensated by omitting the need for additional electrical system installation items and by the enhanced structural performance, enabling a reduction of the prescribed minimum skin thickness. Advantages over state-of-the-art fibre metal laminates mainly arise from design and processing technology aspects.
In this context, the present work focuses on analysing and optimising the structural and electrical performance of such hybrid composites with shares of metal fibres up to 20 vol.%. Bundles of soft-annealed austenitic steel or copper cladded low carbon steel fibres with filament diameters of 60 or 63 µm are considered. The fibre bundles are distinguished by high elongation at break (32 %) and ultimate tensile strength (900 MPa) or high electrical conductivity (2.4 × 10^7 S/m). Comprehensive researches are carried out on the fibre bundles as well as on unidirectional and multiaxial laminates. Both hybrid composites with homogeneous and accumulated steel fibre arrangement are taken into account. Electrical in-plane conductivity, plain tensile behaviour, suitability for bolted joints as well as impact and perforation performance of the composite are analysed. Additionally, a novel non-destructive testing method based on measurement of deformation-induced phase transformation of the metastable austenitic steel fibres is discussed.
The outcome of the conductivity measurements verifies a correlation of the volume conductivity of the composite with the volume share and the specific electrical resistance of the incorporated metal fibres. Compared to conventional CFRP, the electrical conductivity in parallel to the fibre orientation can be increased by one to two orders of magnitude even for minor percentages of steel fibres. The analysis, however, also discloses the challenge of establishing a sufficient connection to the hybrid composite in order to entirely exploit its electrical conductivity.
In case of plain tensile load, the performance of the hybrid composite is essentially affected by the steel fibre-resin-adhesion as well as the laminate structure. Uniaxial hybrid laminates show brittle, singular failure behaviour. Exhaustive yielding of the embedded steel fibres is confined to the arising fracture gap. The high transverse stiffness of the isotropic metal fibres additionally intensifies strain magnification within the resin under transverse tensile load. This promotes (intralaminar) inter-fibre-failure at minor composite deformation. By contrast, multiaxial hybrid laminates exhibit distinctive damage evolution. After failure initiation, the steel fibres extensively yield and sustain the load-carrying capacity of angularly (e.g. ±45°) aligned CFRP plies. The overall material response is thus not only a simple superimposition but a complex interaction of the mechanical behaviour of the composite’s constituents. As a result of this post-damage performance, an ultimate elongation of over 11 % can be proven for the hybrid laminates analysed in this work. In this context, the influence of the steel fibre-resin adhesion on the failure behaviour of the hybrid composite is explicated by means of an analytical model. Long term exposure to corrosive media has no detrimental effect on the mechanical performance of stainless steel fibre reinforced composites. By trend, water uptake increases the maximum elongation at break of the hybrid laminate.
Moreover, the suitability of CFRP for bolted joints can partially be improved by the integration of steel fibres. While the bearing strength basically remains nearly unaffected, the bypass failure behaviour (ε_{max}: +363 %) as well as the head pull-through resistance (E_{a,BPT}: +81 %) can be enhanced. The improvements primarily concern the load-carrying capacity after failure initiation. Additionally, the integrated ductile steel fibres significantly increase the energy absorption capacity of the laminate in case of progressive bearing failure by up to 63 %.
However, the hybrid composite exhibits a sensitive low velocity/low mass impact behaviour. Compared to conventional CFRP, the damage threshold load of very thin hybrid laminates is lower, making them prone for delamination at minor, non-critical impact energies. At higher energy levels, however, the impact-induced delamination spreads less since most of the impact energy is absorbed by yielding of the ductile metal fibres instead of crack propagation. This structural advantage compared to CFRP gains in importance with increasing impact energy. The plastic deformation of the metastable austenitic steel fibres is accompanied by a phase transformation from paramagnetic γ-austenite to ferromagnetic α’-martensite. This change of the magnetic behaviour can be used to detect and evaluate impacts on the surface of the hybrid composite, which provides a simple non-destructive testing method. In case of low velocity/high mass impact, integration of ductile metal fibres into CFRP enables to address spacious areas of the laminate for energy absorption purposes. As a consequence, the perforation resistance of the hybrid composite is significantly enhanced; by addition of approximately 20 vol.% of stainless steel fibres, the perforation strength can be increased by 61 %, while the maximum energy absorption capacity rises by 194 %.
In the first part of this thesis we study algorithmic aspects of tropical intersection theory. We analyse how divisors and intersection products on tropical cycles can actually be computed using polyhedral geometry. The main focus is the study of moduli spaces, where the underlying combinatorics of the varieties involved allow a much more efficient way of computing certain tropical cycles. The algorithms discussed here have been implemented in an extension for polymake, a software for polyhedral computations.
In the second part we apply the algorithmic toolkit developed in the first part to the study of tropical double Hurwitz cycles. Hurwitz cycles are a higher-dimensional generalization of Hurwitz numbers, which count covers of \(\mathbb{P}^1\) by smooth curves of a given genus with a certain fixed ramification behaviour. Double Hurwitz numbers provide a strong connection between various mathematical disciplines, including algebraic geometry, representation theory and combinatorics. The tropical cycles have a rather complex combinatorial nature, so it is very difficult to study them purely "by hand". Being able to compute examples has been very helpful
in coming up with theoretical results. Our main result states that all marked and unmarked Hurwitz cycles are connected in codimension one and that for a generic choice of simple ramification points the marked cycle is a multiple of an irreducible cycle. In addition we provide computational examples to show that this is the strongest possible statement.
Glycine constitutes the major neurotransmitter at inhibitory synapses of lower brain regions.
A rapid removal of glycine from the synaptic cleft and consequent recycling is crucial for
synaptic transmission in systems with high effort on temporal precision. This is mainly
achieved by glycine translocation via two glycine transporters (GlyTs), namely GlyT1 and
GlyT2. At inhibitory synapses, GlyT2 was found to be specifically expressed by neurons,
supplying the presynapse with glycine needed for vesicle filling. In contrast, GlyT1 is attributed
to astrocytes and primarily mediates the termination of synaptic transmission by glycine
removal from the synaptic cleft. Employing patch-clamp recordings from principal neurons of
the lateral superior olive (LSO) in acute brainstem slices of GlyT1b/c knockout (KO) mice and
wildtype (WT) littermates at postnatal day 20, I analyzed how postsynaptic responses are
changed in a GlyT1-depleted environment. During spontaneous vesicle release I found no
change of postsynaptic responses, contradicting my initial hypothesis of prolonged decay
times. Electrical stimulation of fibers of the medial nucleus of the trapezoid body (MNTB),
which are known to form fast, reliable and highly precise synapses with LSO principal neurons,
revealed that GlyT1 is involved in proper synaptic function during sustained, high frequent
synaptic transmission. Stimulation with 50 Hz led to a stronger decay time and latency
prolongation in GlyT1b/c KO, accelerating to 60% longer decay times and 30% longer latencies.
Additionally, a more pronounced frequency-dependent depression and fidelity decrease was
observed during stimulation with 200 Hz in GlyT1b/c KO, resulting in 67% smaller amplitudes
and only 25% of WT fidelity at the end of the challenge. Basic properties like readily releasable
pool, release probability, and quantal size (q) were not altered in GlyT1b/c KO, but
interestingly q decreased during 50 Hz and 100 Hz challenges to about 84%, which was not
observed in WT. I conclude that stronger accumulation of extracellular glycine due to GlyT1
loss leads to prolonged activation of postsynaptic glycine receptors (GlyRs). As a further
consequence, activation of presynaptic GlyRs in the vicinity of the synaptic cleft might be
enhanced, accompanied by a stronger occurrence of shunting inhibition. Furthermore, I
assume a GlyT1-dependent glycine shuttle, which is absent at GlyT1b/c KO synapses. This
could result in a diminished glycine supply to GlyT2 located at more distant sites, causing a
disturbed replenishment during periods with excess release of glycine. Conclusively, my study
reveals a contribution of astrocytes in fast and reliable synaptic transmission at the MNTB-LSO
synapse, which in turn is crucial for proper sound source localization.
In modern textile manufacturing industries, the function of human eyes to detect disturbances in the production processes which yield defective products is switched to cameras. The camera images are analyzed with various methods to detect these disturbances automatically. There are, however, still problems with in particular semi-regular textures which are typical for weaving patterns. We study three parts of that problem of automatic texture analysis: image smoothing, texture synthesis and defect detection. In image smoothing, we develop a two dimensional kernel smoothing method with locally and directionally adaptive bandwidths allowing correlation in the errors. Two approaches are used in synthesising texture. The first is based on constructing a generalized Ising energy function in the Markov Random Field setup, and for the second, we use two-dimensional periodic bootstrap methods for semi-regular texture synthesis. We treat defect detection as multihypothesis testing problem with the null hypothesis representing the absence of defects and the other hypotheses representing various types of defects. We develop a test based on a nonparametric regression setup, and we use the bootstrap for approximating the distribution of our test statistic.
Prostate cancer preferentially metastasizes to the skeleton and abundant evidence exists that osteoblasts specifically support the metastatic process, including cancer stem cell niche formation. At early stages of bone metastasis, crosstalk of prostate cancer cells and osteoblasts through soluble molecules results in a decrease of cancer cell proliferation, accompanied by altered adhesive properties and increased expression of bone-specific genes, or osteomimicry. Osteoblasts synthesize a plethora of biologically active factors, which comprise the unique bone microenvironment. By means of quantitative real-time RT-PCR it was determined that exposure to the osteoblast secretome induced gene expression changes in prostate cancer cells, including the upregulation of osteomimetic genes such as BMP2, AP, COL1A1, OPG and RANKL. IL6 and TGFbeta1 signaling pathway components also became upregulated at early time points. Moreover, osteoblast-released IL6 and TGFbeta1 contributed to the upregulation of OPG mRNA in LNCaP. Thus, the earliest response of prostate cancer cells to osteoblast-released factors, which ultimately cause metastatic cells to assume an osteomimetic phenotype, involved activation of paracrine and autocrine IL6 and TGFbeta signaling. On the other hand, a microarray analysis showed that osteoblasts exposed to the secretome of prostate cancer cells exhibited gene expression alterations suggestive of repressed proliferation, decreased matrix synthesis and inhibited immune response, which together indicate enhanced preosteocytic differentiation. TGFbeta signaling, known to inhibit osteoblast maturation, was strongly suppressed, as shown by elevated expression of negative regulators, downregulation of pathway components and of numerous target genes. Transcriptional downregulation of osteoblast inhibitory molecules such as DKK1 and FST also occurred, with concomitant upregulation of the osteoinductive molecules ADM, STC1 and BMP2, and of the transcription factors CBFA1 and HES1, which promote osteoblast differentiation. Finally, the mRNA encoding NPPB, the precursor of a molecule implicated in the inhibition of TGFbetaeffects, in bone formation and in stem cell maintenance, became upregulated after coculture both in osteoblasts and in prostate cancer cells. These results provide an insight into potential mechanisms of dysregulated bone formation in metastatic prostate cancer, as well as mechanisms by which osteoblasts might enhance the invasive, osteomimetic and stem cell-like properties of the tumor cells. In particular, the differential modulation of TGFbetasignaling in prostate cancer cells and osteoblasts appears to merit further research.
In this dissertation, I will present the studies conducted during my doctoral studies. In spite of a lot of research in the last decades, the complex cognitive processes underlying human memory are not fully unraveled. Furthermore, the development of neuroscientific methods like functional mag-netic resonance imaging (fMRI) and event-related potentials (ERPs) have further build a founda-tion for new insights. Naturally, the utilization of these techniques led to further adaptation of both these techniques and the paradigms in which they have been employed. This can be observed in the research literature on episodic memory retrieval. Familiarity and recollection, have been found to be the chief factors at play during memory retrieval. The two processes have been thoroughly characterized in several studies and reviews (e.g., Mecklinger, 2000; Rugg & Curran, 2007; Yonelinas, 2002; Zimmer & Ecker, 2010), yet there are still open questions that have to be ad-dressed by researchers in this field (c.f., Leynes, Bruett, Krizan, & Veloso, 2017; MacLeod & Donaldson, 2017).
In order to answer these questions, we conducted several studies during my doctoral studies. In Study 1, we developed a paradigm to investigated episodic memory using ERPs. In the study phase, pictorial stimuli were presented which at test were either perceptually identical, perceptually changed, or entirely new. Data collected from a sample of young adults revealed that the paradigm was suitable to elicit ERP correlates of both familiarity and recollection. As the newly developed paradigm yielded similar results as existing literature, we then applied this paradigm in two devel-opmental populations, second-graders and fifth-graders. According to the ERPs, the younger chil-dren seemed to rely on recollection alone, whereas ERPs of older children suggested the use of familiarity for perceptually identical items and only after intentional encoding. In a follow-up study two years later, we used the results from both studies to only slightly refine the paradigm, again administering it to young adults. In this study, Study 3, we found that ERP correlates were much smaller than in the earlier studies, hence we used a data-driven approach to detect time windows of interest. In spite of the large body of research on episodic memory, these studies serve to demon-strate that episodic memory is a complex interplay of several contributing cognitive processes which need to assessed carefully in order to unravel the key factors at play during familiarity and recollection.
Enhanced information processing of phobic natural images in participants with specific phobias
(2014)
From an evolutionary point of view, it can be assumed that visual processing and rapid detection of potentially dangerous stimuli in the environment (e.g., perilous animals) is highly adaptive for all humans. In the present dissertation, I address three research questions; (1) Is information processing of threatening stimuli enhanced in individuals with specific phobias? (2) Are there any differences between the different types of phobia (e.g., spider phobia vs. snake phobia)? (3) Is the frequently reported attentional bias of individuals with specific phobias - which may contribute to an enhancement in information processing – also detectable in a prior entry paradigm? In Experiments 1 to 3 of the present thesis non-anxious control, spider-fearful, snake-fearful, and blood-injection-injury-fearful participants took part in the study. We applied in each experiment a response priming paradigm which has a strong theoretical (cf. rapid-chase theory; Schmidt, Niehaus, & Nagel, 2006; Schmidt, Haberkamp, Veltkamp et al., 2011) as well as empirical background (cf. Schmidt, 2002). We show that information processing in fearful individuals is indeed enhanced for phobic images (i.e., spiders for spider-fearful participants; injuries for blood-injury-injection(BII)-fearful individuals). However, we found marked differences between the different types of phobia. In Experiment 1 and 2 (Chapter 2 and 3), spiders had a strong and specific influence in the group of spider-fearful individuals: Phobic primes entailed the largest priming effects, and phobic targets accelerated responses, both effects indicating speeded response activation by phobic images. In snake-fearful participants (Experiment 1, Chapter 2), this processing enhancement for phobic material was less pronounced and extended to both snake and spider images. In Experiment 3 (Chapter 4), we demonstrated that early information processing for pictures of small injuries is also enhanced in BII-fearful participants, even though BII fear is unique in that BII-fearful individuals show opposite physiological reactions when confronted with the phobic stimulus compared to individuals with animal phobias. These results show that already fast visuomotor responses are further enhanced in spider- and BII-fearful participants. Results give evidence that responses are based on the first feedforward sweep of neuronal activation proceeding through the visuomotor system. I propose that the additional enhancement in spider- and BII-fearful individuals depend on a specific hardwired binding of elementary features belonging to the phobic object in fearful individuals (i.e., effortless recognition of the respective phobic object via hardwired neuronal conjunctions). I suggest that these hardwired conjunctions developed due to long-term perceptual learning processes. We also investigate the frequently reported attentional bias of phobic individuals and showed that this bias is detectable in temporal order judgments using a prior entry paradigm. I assume that perceptual learning processes might also strengthen the attentional bias, for example, by providing a more salient bottom-up signal that draws attention involuntarily. In sum, I conclude that (1) early information processing of threatening stimuli is indeed enhanced in individuals with specific phobias but that (2) differences between divers types of phobia exist (i.e., spider- and BII-fearful participants show enhanced information of the respective phobic object; though, snake-fearful participants show no specific information processing enhancement of snakes); (3) the frequently reported attentional bias of spider-fearful individuals is also detectable in a prior entry paradigm.
In the context of inverse optimization, inverse versions of maximum flow and minimum cost flow problems have thoroughly been investigated. In these network flow problems there are two important problem parameters: flow capacities of the arcs and costs incurred by sending a unit flow on these arcs. Capacity changes for maximum flow problems and cost changes for minimum cost flow problems have been studied under several distance measures such as rectilinear, Chebyshev, and Hamming distances. This thesis also deals with inverse network flow problems and their counterparts tension problems under the aforementioned distance measures. The major goals are to enrich the inverse optimization theory by introducing new inverse network problems that have not yet been treated in the literature, and to extend the well-known combinatorial results of inverse network flows for more general classes of problems with inherent combinatorial properties such as matroid flows on regular matroids and monotropic programming. To accomplish the first objective, the inverse maximum flow problem under Chebyshev norm is analyzed and the capacity inverse minimum cost flow problem, in which only arc capacities are perturbed, is introduced. In this way, it is attempted to close the gap between the capacity perturbing inverse network problems and the cost perturbing ones. The foremost purpose of studying inverse tension problems on networks is to achieve a well-established generalization of the inverse network problems. Since tensions are duals of network flows, carrying the theoretical results of network flows over to tensions follows quite intuitively. Using this intuitive link between network flows and tensions, a generalization to matroid flows and monotropic programs is built gradually up.
2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a highly toxic and persistent organic pollutant, which is ubiquitously found in the environment. The prototype dioxin compound was classified as a human carcinogen by the International Agency for Research on Cancer. TCDD acts as a potent liver tumor promoter in rats, which is one of the major concerns related to TCDD exposure. There is extensive evidence, that TCDD exerts anti-estrogenic effects via arylhydrocarbon receptor (AhR)-mediated induction of cytochromes P450 and interferes with the estrogen receptor alpha (ERalpha)-mediated signaling pathway. The present work was conducted to shed light on the hypothesis that enhanced activation of estradiol metabolism by TCDD-induced enzymes, mainly CYP1A1 and CYP1B1, leads to oxidative DNA damage in liver cells. Furthermore, the possible modulation by 17beta-estradiol (E2) was investigated. The effects were examined using four different AhR-responsive species- and sex-specific liver cell models, rat H4II2 and human HepG2 hepatoma cell lines as well as rat primary hepatocytes from male and female Wistar rats. The effective induction of CYP1A1 and CYP1B1 by TCDD was demonstrated in all liver cell models. Basal and TCDD-induced expression of CYP1B1, which is a key enzyme in stimulating E2 metabolism via the more reactive formation of the genotoxic 4-hydroxyestradiol, was most pronounced in rat primary hepatocytes. CYP-dependent induction of reactive oxygen species (ROS) was only observed in rodent cells. E2 induced ROS only in primary rat hepatocytes, which was associated with a weak CYP1B1 mRNA induction. Thus, E2 itself was suggested to induce its own metabolism in primary rat hepatocytes, resulting in the redox cycling of catechol estradiol metabolites leading to ROS formation. In this study the role of TCDD and E2 on oxidative DNA damage was investigated for the first time in vitro in the comet assay using liver cells. Both TCDD and E2 were shown to induce oxidative DNA base modifications only in rat hepatocytes. Additionally, direct oxidative DNA-damaging effects of the two main E2 metabolites, 4-hydroxyestradiol and 2-hydroxyestradiol, were only observed in rat hepatocytes and revealed that E2 damaged the DNA to the same extent. However, the induction of oxidative DNA damage by E2 could not completely be explained by the metabolic conversion of E2 via CYP1A1 and CYP1B1 and has to be further investigated. The expression of low levels of endogenous ERalpha mRNA in primary rat hepatocytes and the lack of ERalpha in hepatoma cell lines were identified as crucial. Therefore, the effects of interference of ERalpha with AhR were examined in HepG2 cells, which were transiently transfected with ERalpha. The over-expression of ERalpha led to enhanced AhR-mediated transcriptional activity by E2, suggesting a possible regulation of E2 levels. In turn, TCDD reduced E2-mediated ERalpha signaling, confirming the anti-estrogenic action of TCDD. Such a modulation of the combined effects of TCDD with E2 was not observed in any of the other experiments. Thus, the role of low endogenous ERalpha levels has to be further investigated in transfection experiments using rat primary hepatocytes. Overall, rat primary hepatocyte culture turned out to be the more adaptive cell model to investigate metabolism in the liver, reflecting a more realistic situation of the liver tissue. Nevertheless, during this work a crosstalk between ERalpha and AhR was shown for the first time using human hepatoma cell line HepG2 by transiently transfecting ERalpha.
In this thesis we propose an efficient method to compute the automorphism group of an arbitrary hyperelliptic function field over a given constant field of odd characteristic as well as over its algebraic extensions. Beside theoretical applications, knowing the automorphism group also is useful in cryptography: The Jacobians of hyperelliptic curves have been suggested by Koblitz as groups for cryptographic purposes, because the discrete logarithm is believed to be hard in this kind of groups. In order to obtain "secure" Jacobians, it is necessary to prevent attacks like Pohlig/Hellman's and Duursma/Gaudry/Morain's. The latter is only feasible, if the corresponding function field has an automorphism of large order. According to a theorem by Madan, automorphisms seem to allow the Pohlig/Hellman attack, too. Hence, the function field of a secure Jacobian will most likely have trivial automorphism group. In other words: Computing the automorphism group of a hyperelliptic function field promises to be a quick test for insecure Jacobians. Let us outline our algorithm for computing the automorphism group Aut(F/k) of a hyperelliptic function field F/k. It is well known that Aut(F/k) is finite. For each possible subgroup U of Aut(F/k), Rolf Brandt has given a normal form for F if k is algebraically closed. Hence our problem reduces to deciding, whether a given hyperelliptic function field F=k(x,y), y^2=D_x has a defining equation of the form given by Brandt. This question can be answered using theorem III.18: We have F=k(t,u), u^2=D_t iff x is a fraction of linear polynomials in t and y=pu, where the factor p is a rational function w.r.t. t which can be determined explicitly from the coefficients of x. This condition can be checked efficiently using Gröbner basis techniques. With additional effort, it is also possible to compute Aut(F/k) if k is not algebraically closed. Investigating a huge number of examples one gets the impression that the above motivation of getting a quick test for insecure Jacobians is partially fulfilled: The computation of automorphism groups is quite fast using the suggested algorithm. Furthermore, fields with nontrivial automorphism groups seem to have insecure Jacobians. Only fields of small characteristic seem to have a reasonable chance of having nontrivial automorphisms. Hence, from a cryptographic point of view, computing Aut(F/k) seems to make sense whenever k has small characteristic.
In recent years the consumption of polymer based composites in many engineering
fields where friction and wear are critical issues has increased enormously. Satisfying
the growing industrial needs can be successful only if the costly, labor-intensive and
time-consuming cycle of manufacturing, followed by testing, and additionally followed
by further trial-and-error compounding is reduced or even avoided. Therefore, the
objective is to get in advance as much fundamental understanding as possible of the
interaction between various composite components and that of the composite against
its counterface. Sliding wear of polymers and polymer composites involves very
complex and highly nonlinear processes. Consequently, to develop analytical models
for the simulation of the sliding wear behavior of these materials is extremely difficult
or even impossible. It necessitates simplifying hypotheses and thus compromising
accuracy. An alternative way, discussed in this work, is an artificial neural network
based modeling. The principal benefit of artificial neural networks (ANNs) is their ability
to learn patterns through a training experience from experimentally generated data
using self-organizing capabilities.
Initially, the potential of using ANNs for the prediction of friction and wear properties
of polymers and polymer composites was explored using already published friction
and wear data of 101 independent fretting wear tests of polyamide 46 (PA 46) composites.
For comparison, ANNs were also applied to model the mechanical properties
of polymer composites using a commercial data bank of 93 pairs of independent Izod
impact, tension and bending tests of polyamide 66 (PA 66) composites. Different
stages in the development of ANN models such as selection of optimum network
configuration, multi-dimensional modeling, training and testing of the network were
addressed at length. The results of neural network predictions appeared viable and
very promising for their application in the field of tribology.
A case example was subsequently presented to model the sliding friction and wear
properties of polymer composites by using newly measured datasets of polyphenylene
sulfide (PPS) matrix composites. The composites were prepared by twinscrew
extrusion and injection molding. The dataset investigated was generated from
pin-on-disc testing in dry sliding conditions under various contact pressures and sliding speeds. Initially the focus was placed on exploring the possible synergistic effects
between traditional reinforcements and particulate fillers, with special emphasis on
sub-micro TiO2 particles (300 nm average diameter) and short carbon fibers (SCFs).
Subsequently, the lubricating contributions of graphite (Gr) and polytetrafluoroethylene
(PTFE) in these multiphase materials were also studied. ANNs were trained
using a conjugate gradient with Powell/Beale restarts (CGB) algorithm as well as a
variable learning rate backpropagation (GDX) algorithm in order to learn compositionproperty
relationships between the inputs and outputs of the system. Likewise, the
influence of the operating parameters (contact pressure (p) and sliding speed (v))
was also examined. The incorporation of short carbon fibers and sub-micro TiO2
particles resulted in both a lower friction and a great improvement in the wear resistance
of the PPS composites within the low and medium pv-range. The mechanical
characterization and surface analysis after wear testing revealed that this beneficial
tribological performance could be explained by the following phenomena: (i)
enhanced mechanical properties through the inclusion of short carbon fibers, (ii)
favorable protection of the short carbon fibers by the sub-micro particles diminishing
fiber breakage and removal, (iii) self-repairing effects with the sub-micro particles, (iv)
formation of quasi-spherical transfer particles free to roll at the tribological contact.
Still, in the high pv-range stick-slip sliding motion was observed with these hybrid
materials. The adverse stick-slip behavior could be effectively eliminated through the
additional inclusion of solid lubricant reservoirs (Gr and PTFE), analogous to the
lubricants used in real ball bearings. Likewise, solid lubricants improved the wear resistance
of the multiphase system PPS/SCF/TiO2 in the high pv-range (≥ 9 MPa·m/s).
Yet, their positive effect, especially that of graphite, was limited up to certain volume
fraction and loading conditions. The optimum results were obtained by blending
comparatively low amounts of Gr and PTFE (≈ 5 vol.% from each additive). An introduction
of softer sub-micro particles did not bring the desired ball bearing effect and
fiber protection. The ANN prediction profiles for PPS tribo-compounds exhibited very
good or even perfect agreement with the measured results demonstrating that the
target of achieving a well trained network was reached. The results of employing a
validation test dataset indicated that the trained neural network acquired enough
generalization capability to extend what it has learned about the training patterns to
data that it has not seen before from the same knowledge domain. Optimal brain surgeon (OBS) algorithm was employed to perform pruning of the network
topology by eliminating non-useful weights and bias in order to determine if the
performance of the pruned network was better than the fully-connected network.
Pruning resulted in accuracy gains over the fully-connected network, but induced
higher computational cost in coding the data in the required format. Within an importance
analysis, the sensitivity of the network response variable (frictional coefficient
or specific wear rate) to characteristic mechanical and thermo-mechanical input variables
was examined. The goal was to study the relationships between the diverse
input variables and the characteristic tribological parameters for a better understanding
of the sliding wear process with these materials. Finally, it was demonstrated that
the well-trained networks might be applied for visualization what will happen if a certain
filler is introduced into a composite, or what the impacts of the testing conditions
on the frictional coefficient and specific wear rate are. In this way, they might be a
helpful tool for design engineers and materials experts to explore materials and to
make reasoned selection and substitution decisions early in the design phase, when
they incur least cost.
The thesis deals with the subgradient optimization methods which are serving to solve nonsmooth optimization problems. We are particularly concerned with solving large-scale integer programming problems using the methodology of Lagrangian relaxation and dualization. The goal is to employ the subgradient optimization techniques to solve large-scale optimization problems that originated from radiation therapy planning problem. In the thesis, different kinds of zigzagging phenomena which hamper the speed of the subgradient procedures have been investigated and identified. Moreover, we have established a new procedure which can completely eliminate the zigzagging phenomena of subgradient methods. Procedures used to construct both primal and dual solutions within the subgradient schemes have been also described. We applied the subgradient optimization methods to solve the problem of minimizing total treatment time of radiation therapy. The problem is NP-hard and thus far there exists no method for solving the problem to optimality. We present a new, efficient, and fast algorithm which combines exact and heuristic procedures to solve the problem.
This thesis has the goal to propose measures which allow an increase of the power efficiency of OFDM transmission systems. As compared to OFDM transmission over AWGN channels, OFDM transmission over frequency selective radio channels requires a significantly larger transmit power in order to achieve a certain transmission quality. It is well known that this detrimental impact of frequency selectivity can be combated by frequency diversity. We revisit and further investigate an approach to frequency diversity based on the spreading of subsets of the data elements over corresponding subsets of the OFDM subcarriers and term this approach Partial Data Spreading (PDS). The size of said subsets, which we designate as spreading factor, is a design parameter of PDS, and by properly choosing , depending on the system designer's requirements, an adequate compromise between a good system performance and a low complexity can be found. We show how PDS can be combined with ML, MMSE and ZF data detection, and it is recognized that MMSE data detection offers a good compromise between performance and complexity. After having presented the utilization of PDS in OFDM transmission without FEC encoding, we also show that PDS readily lends itself for FEC encoded OFDM transmission. We display that in this case the system performance can be significantly enhanced by specific schemes of interleaving and utilization of reliabiliy information developed in the thesis. A severe problem of OFDM transmission is the large Peak-to-Average-Power Ratio (PAPR) of the OFDM symbols, which hampers the application of power efficient transmit amplifiers. Our investigations reveal that PDS inherently reduces the PAPR. Another approch to PAPR reduction is the well known scheme Selective Data Mapping (SDM). In the thesis it is shown that PDS can be beneficially combined with SDM to the scheme PDS-SDM with a view to jointly exploit the PAPR reduction potentials of both schemes. However, even when such a PAPR reduction is achieved, the amplitude maximum of the resulting OFDM symbols is not constant, but depends on the data content. This entails the disadvantage that the power amplifier cannot be designed, with a view to achieve a high power efficiency, for a fixed amplitude maximum, what would be desirable. In order to overcome this problem, we propose the scheme Optimum Clipping (OC), in which we obtain the desired fixed amplitude maximum by a specific combination of the measures clipping, filtering and rescaling. In OFDM transmission a certain number of OFDM subcarriers have to be sacrificed for pilot transmission in order to enable channel estimation in the receiver. For a given energy of the OFDM symbols, the question arises in which way this energy should be subdivided among the pilots and the data carrying OFDM subcarriers. If a large portion of the available transmit energy goes to the pilots, then the quality of channel estimation is good, however, the data detection performs poor. Data detection also performs poor if the energy provided for the pilots is too small, because then the channel estimate indispensable for data detection is not accurate enough. We present a scheme how to assign the energy to pilot and data OFDM subcarriers in an optimum way which minimizes the symbol error probability as the ultimate quality measure of the transmission. The major part of the thesis is dedicated to point-to-point OFDM transmission systems. Towards the end of the thesis we show that the PDS can be also applied to multipoint-to-point OFDM transmission systems encountered for instance in the uplinks of mobile radio systems.
In the context of distributed networked control systems, many issues affect the performance and functionality of the connected subsystems, mainly raised because of the communication medium imposed into the system structure. The communication functionality must generally cope with the data exchange requirements between system entities. Therefore, due to the limited communication resources, especially in wireless networks, an optimal algorithm for the assignment of the communication resources and proper selection of the right Medium Access Control (MAC) protocol are highly needed.
In this dissertation, we studied several problems raised by communication networks in wireless networked control systems, with a particular focus on the effect of standard Medium Access Control (MAC) protocols on the overall control system performance. We examined the effect of both the Time Division Multiple Access (TDMA) and the Orthogonal Frequency Division Multiple Access (OFDMA) protocols and developed a set of distributed algorithms that suit their specification requirements.
As a benchmark, we used a vehicle dynamics optimal control problem where the objective of the optimization problem is to penalize the maximal utilization of the tire's adhesion forces for a given driving maneuver. The problem was decomposed into a distributed form using primal and dual decomposition techniques, and solving algorithms were derived using both primal and dual subgradient methods. The problem solver was tested with respect to a wireless networked system structure and evaluated for different communication typologies, such as uni-directional, bidirectional, and broadcasting topology.
Later, the setup of the solution algorithms was extended concerning the specification of the TDMA and OFDMA protocols, and we introduced an event-triggered scheme into the solver algorithm. The proposed event-triggered scheme is mainly utilized to reduce communication between concurrent computation subsystems, which is primarily intended to facilitate real-time efficiency.
Next, we investigated the effect of the data exchange between subsystems on the overall solver performance and adapted the sensitivity analysis concept within the event-based communication scheme. An adaptive sensitivity-based TDMA algorithm was developed to manage the extensive communication resource requests, and channel utilization was adapted for the optimal solution behavior.
In the last part of the thesis, we extended our research direction to the multi-vehicle concept and investigated the communication resource allocation problem in the context of the OFDMA protocol. We developed an adaptive sensitivity-based OFDMA protocol based on linking the evolution of the application layer to the communication layer and assigning the communication resources concerning the sensitivity analysis of the optimization problem at the application layer.
In the avionics domain, “ultra-reliability” refers to the practice of ensuring quantifiably negligible residual failure rates in the presence of transient and permanent hardware faults. If autonomous Cyber- Physical Systems (CPS) in other domains, e.g., autonomous vehicles, drones, and industrial automation systems, are to permeate our everyday life in the not so distant future, then they also need to become ultra-reliable. However, the rigorous reliability engineering and analysis practices used in the avionics domain are expensive and time consuming, and cannot be transferred to most other CPS domains. The increasing adoption of faster and cheaper, but less reliable, Commercial Off-The-Shelf (COTS) hardware is also an impediment in this regard.
Motivated by the goal of ultra-reliable CPS, this dissertation shows how to soundly analyze the reliability of COTS-based implementations of actively replicated Networked Control Systems (NCSs)—which are key building blocks of modern CPS—in the presence of transient hard- ware faults. When an NCS is deployed over field buses such as the Controller Area Network (CAN), transient faults are known to cause host crashes, network retransmissions, and incorrect computations. In addition, when an NCS is deployed over point-to-point networks such as Ethernet, even Byzantine errors (i.e., inconsistent broadcast transmissions) are possible. The analyses proposed in this dissertation account for NCS failures due to each of these error categories, and consider NCS failures in both time and value domains. The analyses are also provably free of reliability anomalies. Such anomalies are problematic because they can result in unsound failure rate estimates, which might lead us to believe that a system is safer than it actually is.
Specifically, this dissertation makes four main contributions. (1) To reduce the failure rate of NCSs in the presence of Byzantine errors, we present a hard real-time design of a Byzantine Fault Tolerance (BFT) protocol for Ethernet-based systems. (2) We then propose a quantitative reliability analysis of the presented design in the presence of transient faults. (3) Next, we propose a similar analysis to upper-bound the failure probability of an actively replicated CAN-based NCS. (4) Finally, to upper-bound the long-term failure rate of the NCS more accurately, we propose analyses that take into account the temporal robustness properties of an NCS expressed as weakly-hard constraints.
By design, our analyses can be applied in the context of full-system analyses. For instance, to certify a system consisting of multiple actively replicated NCSs deployed over a BFT atomic broadcast layer, the upper bounds on the failure rates of each NCS and the atomic broadcast layer can be composed using the sum-of-failure-rates model.
For many years real-time task models have focused the timing constraints on execution windows defined by earliest start times and deadlines for feasibility.
However, the utility of some application may vary among scenarios which yield correct behavior, and maximizing this utility improves the resource utilization.
For example, target sensitive applications have a target point where execution results in maximized utility, and an execution window for feasibility.
Execution around this point and within the execution window is allowed, albeit at lower utility.
The intensity of the utility decay accounts for the importance of the application.
Examples of such applications include multimedia and control; multimedia application are very popular nowadays and control applications are present in every automated system.
In this thesis, we present a novel real-time task model which provides for easy abstractions to express the timing constraints of target sensitive RT applications: the gravitational task model.
This model uses a simple gravity pendulum (or bob pendulum) system as a visualization model for trade-offs among target sensitive RT applications.
We consider jobs as objects in a pendulum system, and the target points as the central point.
Then, the equilibrium state of the physical problem is equivalent to the best compromise among jobs with conflicting targets.
Analogies with well-known systems are helpful to fill in the gap between application requirements and theoretical abstractions used in task models.
For instance, the so-called nature algorithms use key elements of physical processes to form the basis of an optimization algorithm.
Examples include the knapsack problem, traveling salesman problem, ant colony optimization, and simulated annealing.
We also present a few scheduling algorithms designed for the gravitational task model which fulfill the requirements for on-line adaptivity.
The scheduling of target sensitive RT applications must account for timing constraints, and the trade-off among tasks with conflicting targets.
Our proposed scheduling algorithms use the equilibrium state concept to order the execution sequence of jobs, and compute the deviation of jobs from their target points for increased system utility.
The execution sequence of jobs in the schedule has a significant impact on the equilibrium of jobs, and dominates the complexity of the problem --- the optimum solution is NP-hard.
We show the efficacy of our approach through simulations results and 3 target sensitive RT applications enhanced with the gravitational task model.
Phycobilisomes (PBS) are the major light-harvesting complexes for the majority of cyanobacteria
and allow these organisms to absorb in the so-called green gap. They consist of smaller units called
phycobiliproteins (PBPs), which are composed of an α- and a β-subunit with covalently bound
linear tetrapyrroles (phycobilins). The latter are attached to the apo-PBPs by phycobiliprotein
lyases. Interestingly, cyanobacteria of the genus Prochlorococcus lack complete PBS and instead
use prochlorophyte chlorophyll-binding proteins (Pcbs), which effectively utilize the energy of the
blue light region. The low-light-adapted (LL) strain Prochlorococcus marinus SS120 has a single
PBP, phycoerythrin-III (PE-III). It has been postulated that PE-III is chromophorylated with the
phycobilins phycourobilin (PUB) and phycoerythrobilin (PEB) in a 3:1 ratio. Thereby, the function
of PE-III remains unclear so far, so that light-gathering function and also photoreceptor function
are discussed.
The main goal of this work was to characterize the assembly of PE-III and thus the function of the
six putative phycobiliprotein lyases of P. marinus SS120. Previous work found that the individual
lyases could not be produced in soluble form, so we switched to a dual pDuet™ plasmid system in
E. coli, which was successfully established. Investigation of the binding of PEB to Apo-PE
revealed that the CpeS lyase specifically chromophorylated Cys82 with 3Z-PEB. Unfortunately,
additional chromophorylation could not be observed using the pDuet system. Therefore, in a
second part of the work, the entire PE gene cluster from P. marinus SS120 was to be introduced
into E. coli and expressed. Although the gene cluster was successfully transcribed within E. coli,
no translation was observed, possibly due to incompatible translation initiation between
Prochlorococcus and E. coli. The introduction of a mini PE cluster (CpeAB) into the
cyanobacterium Synechococcus sp. PCC 7002 was also successfully performed, in which case
production of CpeB but not CpeA from Prochlorococcus was detected. Recombinant CpeB was
also detected together with intrinsic PBP in Synechococcussp. 7002, indicating structural similarity
and incorporation into PBS in Synechococcus sp. 7002. Overall, the obtained results suggest that a
cyanobacterial host is a good option for the studies on the assembly of PE-III from P. marinus and,
based on this, future work could aim at generating an artificial operon using synthetic biology to
achieve efficient translation of all genes.
Activity recognition has continued to be a large field in computer science over the last two decades. Research questions from 15 years ago have led to solutions that today support our daily lives. Specifically, the success of smartphones or more recent developments of other smart devices (e.g., smart-watches) is rooted in applications that leverage on activity analysis and location tracking (fitness applications and maps). Today we can track our physical health and fitness and support our physical needs by merely owning (and using) a smart-phone. Still, the quality of our lives does not solely rely on fitness and physical health but also more increasingly on our mental well-being. Since we have learned how practical and easy it is to have a lot of functions, including health support on just one device, it would be specifically helpful if we could also use the smart-phone to support our mental and cognitive health if need be.
The ultimate goal of this work is to use sensor-assisted location and motion analysis to support various aspects of medically valid cognitive assessments.
In this regard, this thesis builds on Hypothesis 3: Sensors in our ubiquitous environment can collect information about our cognitive state, and it is possible to extract that information. In addition, these data can be used to derive complex cognitive states and to predict possible pathological changes in humans. After all, not only is it possible to determine the cognitive state through sensors but also to assist people in difficult situations through these sensors.
Thus, in the first part, this thesis focuses on the detection of mental state and state changes.
The primary purpose is to evaluate possible starting points for sensor systems in order to enable a clinically accurate assessment of mental states. These assessments must work on the condition that a developed system must be able to function within the given limits of a real clinical environment.
Despite the limitations and challenges of real-life deployments, it was possible to develop methods for determining the cognitive state and well-being of the residents. The analysis of the location data provides a correct classification of cognitive state with an average accuracy of 70% to 90%.
Methods to determine the state of bipolar patients provide an accuracy of 70-80\% for the detection of different cognitive states (total seven classes) using single sensors and 76% for merging data from different sensors. Methods for detecting the occurrence of state changes, a highlight of this work, even achieved a precision and recall of 95%.
The comparison of these results with currently used standard methods in psychiatric care even shows a clear advantage of the sensor-based method. The accuracy of the sensor-based analysis is 60% higher than the accuracy of the currently used methods.
The second part of this thesis introduces methods to support people’s actions in stressful situations on the one hand and analyzes the interaction between people during high-pressure activities on the other.
A simple, acceleration based, smartwatch instant feedback application was used to help laypeople to learn to perform CPR (cardiopulmonary resuscitation) in an emergency on the fly.
The evaluation of this application in a study with 43 laypersons showed an instant improvement in the CPR performance of 50%. An investigation of whether training with such an instant feedback device can support improved learning and lead to more permanent effects for gaining skills was able to confirm this theory.
Last but not least, with the main interest shifting from the individual to a group of people at the end of this work, the question: how can we determine the interaction between individuals within a group of people? was answered by developing a methodology to detect un-voiced collaboration in random ad-hoc groups. An evaluation with data retrieved from video footage provides an accuracy of up to more than 95%, and even with artificially introduced errors rates of 20%, still an accuracy of 70% precision, and 90% recall can be achieved.
All scenarios in this thesis address different practical issues of today’s health care. The methods developed are based on real-life datasets and real-world studies.
In this thesis we integrate discrete dividends into the stock model, estimate
future outstanding dividend payments and solve different portfolio optimization
problems. Therefore, we discuss three well-known stock models, including
discrete dividend payments and evolve a model, which also takes early
announcement into account.
In order to estimate the future outstanding dividend payments, we develop a
general estimation framework. First, we investigate a model-free, no-arbitrage
methodology, which is based on the put-call parity for European options. Our
approach integrates all available option market data and simultaneously calculates
the market-implied discount curve. We illustrate our method using stocks
of European blue-chip companies and show within a statistical assessment that
the estimate performs well in practice.
As American options are more common, we additionally develop a methodology,
which is based on market prices of American at-the-money options.
This method relies on a linear combination of no-arbitrage bounds of the dividends,
where the corresponding optimal weight is determined via a historical
least squares estimation using realized dividends. We demonstrate our method
using all Dow Jones Industrial Average constituents and provide a robustness
check with respect to the used discount factor. Furthermore, we backtest our
results against the method using European options and against a so called
simple estimate.
In the last part of the thesis we solve the terminal wealth portfolio optimization
problem for a dividend paying stock. In the case of the logarithmic utility
function, we show that the optimal strategy is not a constant anymore but
connected to the Merton strategy. Additionally, we solve a special optimal
consumption problem, where the investor is only allowed to consume dividends.
We show that this problem can be reduced to the before solved terminal wealth
problem.
In this thesis, the enhanced Galerkin (eG) finite element method in time is presented. The eG method leads to higher order accurate energy and momentum conserving time integrators for the underlying finite-dimensional Hamiltonian systems. This thesis is concerned with particle dynamics and semi-discrete nonlinear elastodynamics. The conservation is generally related to the collocation property of the eG method. The momentum conservation renders the Gaussian quadrature and the energy conservation is obtained by using a new projection technique. An objective time discretisation of the used strain measures avoids artificial strains for large superimposed rigid body motions. The numerical examples show the well long term performance in the presence of stiffness as well as for calculating large-strain motions.
Interactive visualization of large structured and unstructured data sets is a permanent challenge for scientific visualization. Large data sets are for example created by magnetic resonance imaging (MRI), computed tomography (CT), Computational fluid dynamics (CFD) finite element method (FEM), and computer aided design (CAD). For visualizing those data sets not only accelerated rasterization by means of using specialized hardware i.e. graphics cards is of interest, but also ray casting, as it is perfectly suited for scientific visualization. Ray casting does not only support many rendering modes (e.g., opaque rendering, semi transparent rendering, iso surface rendering, maximum intensity projection, x-ray, absorption emitter model, ...) for which it allows the creation of high quality images, but it also supports many primitives (e.g., not only triangles but also spheres, curved iso surfaces, NURBS, implicit functions, ...). It furthermore scales basically linear to the amount of processor cores used and - this makes it highly interesting for the visualization of large data sets - it scales for static scenes sublinear to data size. Interactive ray casting is currently not widely used within the scientifc visualization community. This is mainly based on historical reasons, as just a few years ago no applicable interactive ray casters for commodity hardware did exist. Interactive scientific visualization has only been possible by using graphics cards or specialized and/or expensive hardware. The goal of this work is to broaden the possibilies for interactive scientific visualization, by showing that interactive CPU based ray casting is today feasible on commodity hardware and that it may efficiently be used together with GPU based rasterization. In this thesis it is first shown that interactive CPU based ray casters may efficiently be integrated into already existing OpenGL frameworks. This is achieved through an OpenGL friendly interface that supports multiple threads and single instruction multiple data (SIMD) operations. For the visualization of rectilinear (and not necessarily cartesian) grids are new implicit kd-trees introduced. They have fast construction times, low memory requirements, and allow ontoday's commodity desktop machines interactive iso surface ray tracing and maximum intensity projection of large scalar fields. A new interactive SIMD ray tracing technique for large tetrahedral meshes is introduced. It is very portable and general and is therefore suited for portation upon different (future) hardware and for usage upon several applications. The thesis ends with a real life commercial application which shows that CPU-based ray casting has already reached the state where it may outperform GPU-based rasterization for scientific visualization.
The main theme of this thesis is the interplay between algebraic and tropical intersection
theory, especially in the context of enumerative geometry. We begin by exploiting
well-known results about tropicalizations of subvarieties of algebraic tori to give a
simple proof of Nishinou and Siebert’s correspondence theorem for rational curves
through given points in toric varieties. Afterwards, we extend this correspondence
by additionally allowing intersections with psi-classes. We do this by constructing
a tropicalization map for cycle classes on toroidal embeddings. It maps algebraic
cycle classes to elements of the Chow group of the cone complex of the toroidal
embedding, that is to weighted polyhedral complexes, which are balanced with respect
to an appropriate map to a vector space, modulo a naturally defined equivalence relation.
We then show that tropicalization respects basic intersection-theoretic operations like
intersections with boundary divisors and apply this to the appropriate moduli spaces
to obtain our correspondence theorem.
Trying to apply similar methods in higher genera inevitably confronts us with moduli
spaces which are not toroidal. This motivates the last part of this thesis, where we
construct tropicalizations of cycles on fine logarithmic schemes. The logarithmic point of
view also motivates our interpretation of tropical intersection theory as the dualization
of the intersection theory of Kato fans. This duality gives a new perspective on the
tropicalization map; namely, as the dualization of a pull-back via the characteristic
morphism of a logarithmic scheme.
In this dissertation we present analysis of macroscopic models for slow dense granular flow. Models are derived from plasticity theory with yield condition and flow rule. Corner stone equations are conservation of mass and conservation of momentum with special constitutive law. Such models are considered in the class of generalised Newtonian fluids, where viscosity depends on the pressure and modulo of the strain-rate tensor. We showed the hyperbolic nature for the evolutionary model in 1D and ill-posed behaviour for 2D and 3D. The steady state equations are always hyperbolic. In the 2D problem we derived a prototype nonlinear backward parabolic equation for the velocity and the similar equation for the shear-rate. Analysis of derived PDE showed the finite blow up time. Blow up time depends on the initial condition. Full 2D and antiplane 3D model were investigated numerically with finite element method. For 2D model we showed the presence of boundary layers. Antiplane 3D model was investigated with the Runge Kutta Discontinuous Galerkin method with mesh addoption. Numerical results confirmed that such a numerical method can be a good choice for the simulations of the slow dense granular flow.
The German energy mix, which provides an overview of the sources of electricity available in Germany, is changing as a result of the expansion of renewable energy sources. With this shift towards sustainable energy sources such as wind and solar power, the electricity market situation is also in flux. Whereas in the past there were few uncertainties in electricity generation and only demand was subject to stochastic uncertainties, generation is now subject to stochastic fluctuations as well, especially due to weather dependency. To provide a supportive framework for this different situation, the electricity market has introduced, among other things, the intraday market, products with half-hourly and quarter-hourly time slices, and a modified balancing energy market design. As a result, both electricity price forecasting and optimization issues remain topical.
In this thesis, we first address intraday market modeling and intraday index forecasting. To do so, we move to the level of individual bids in the intraday market and use them to model the limit order books of intraday products. Based on statistics of the modeled limit order books, we present a novel estimator for the intraday indices. Especially for less liquid products, the order book statistics contain relevant information that allows for significantly more accurate predictions in comparison to the benchmark estimator.
Unlike the intraday market, the day ahead market allows smaller companies without their own trading department to participate since it is operated as a market with daily auctions. We optimize the flexibility offer of such a small company in the day ahead market and model the prices with a stochastic multi-factor model already used in the industry. To make this model accessible for stochastic optimization, we discretize it in time and space using scenario trees. Here we present existing algorithms for scenario tree generation as well as our own extensions and adaptations. These are based on the nested distance, which measures the distance between two distributions of stochastic processes. Based on the resulting scenario trees, we apply the stochastic optimization methods of stochastic programming, dynamic programming, and reinforcement learning to illustrate in which context the methods are appropriate.
To render membrane proteins amenable to in vitro functional and structural studies, they need to be extracted from cellular membranes and stabilised using membrane-mimetic systems. Amphiphilic copolymers gain considerable interest, because they are able to coextract
membrane proteins and their surrounding lipids from complex cellular membranes to form polymer-bounded nanodiscs. The latter harbour a native-like lipid-bilayer core stabilised by a copolymer rim. Accordingly, these membrane mimics are supposed to provide superior
stability to embedded membrane proteins as compared with conventional detergent micelles.
Herein, the formation of nanodiscs by the most commonly used styrene/maleic acid (SMA)copolymer, termed SMA(2:1), was elucidated in detail. To this end, the equilibrium solubilisation efficiencies towards model and cellular membranes were quantified and
compared with those of the more hydrophobic SMA(3:1) and the more hydrophilic diisobutylene/maleic acid (DIBMA) copolymers. It was shown that, from a thermodynamic viewpoint, SMA(2:1) is the most efficient membrane solubiliser in terms of lipid- and proteinextraction
yields. Solvent properties (pH, ionic strength) or membrane characteristics (lateral pressure, charge, or thickness) can affect the polymers’ solubilisation efficiency to a certain extent. In addition, the lipid transfer behaviour of SMA(2:1) nanodiscs was studied.
Notwithstanding their high effective negative charge, SMA(2:1) nanodiscs exchange phospholipids more rapidly among each other than vesicles or protein-bounded nanodiscs, thus rendering them highly dynamic nano-assemblies. Two alternative electroneutral polymers, namely SMA(2:1)-SB and DIBMA-SB, were introduced in this thesis. They were generated by polymer backbone modifications of SMA(2:1) and DIBMA, respectively. The derivatised polymers were shown to quantitatively solubilise model and biological membranes and, like DIBMA, only had a mild effect on lipidbilayer integrity. Along these lines, DIBMA-SB preserved membrane-protein complexes of distinct structural classes and extracted them from various cellular membranes. Importantly, the electroneutral polymers were amenable to protein/lipid interaction studies otherwise masked by unspecific interactions of their anionic counterparts with target lipids or proteins. Taken together, the in-depth characterisation of nanodiscs formed by anionic and electroneutral polymers allows for adjusting the nanodisc properties to specifically suit experimental requirements or address membrane-protein research questions.
Modelling languages are important in the process of software development. The suitability of a modelling language for a project depends on its applicability to the target domain. Here, domain-specific languages have an advantage over more general modelling languages. On the other hand, modelling languages like the Unified Modeling Language can be used in a wide range of domains, which supports the reuse of development knowledge between projects. This thesis treats the syntactical and semantical harmonisation of modelling languages and their combined use, and the handling of complexity of modelling languages by providing language subsets - called language profiles - with tailor-made formal semantics definitions, generated by a profile tool. We focus on the widely-used modelling languages SDL and UML, and formal semantics definitions specified using Abstract State Machines.
Grape powdery mildew, Erysiphe necator, is one of the most significant plant pathogens, which affects grape growing regions world-wide. Because of its short generation time and the production of large amounts of conidia throughout the season, E. necator is classified as a moderate to high risk pathogen with respect to the development of fungicide resistance. The number of fungicidal mode of actions available to control powdery mildew is limited and for some of them resistances are already known. Aryl-phenyl-ketones (APKs), represented by metrafenone and pyriofenone, and succinate-dehydrogenase inhibitors (SDHIs), composed of numerous active ingredients, are two important fungicide classes used for the control of E. necator. Over the period 2014 to 2016, the emergence and development of metrafenone and SDHI resistant E. necator isolates in Europe was followed and evaluated. The distribution of resistant isolates was thereby strongly dependent on the European region. Whereas the north-western part is still predominantly sensitive, samples from east European countries showed higher resistance frequencies.
Classical sensitivity tests with obligate biotrophs can be challenging regarding sampling, transport and especially the maintenance of the living strains. Whenever possible, molecular genetic methods are preferred for a more efficient monitoring. Such methods require the knowledge of the resistance mechanisms. The exact molecular target and the resistance mechanism of metrafenone is still unknown. Whole genome sequencing of metrafenone sensitive and resistant wheat powdery mildew isolates, as well as adapted laboratory mutants of Aspergillus nidulans, where performed with the aim to identify proteins potentially linked to the mode of action or which contribute to metrafenone resistance. Based on comparative SNP analysis, four proteins potentially associated with metrafenone resistance were identified, but validation studies could not confirm their role in metrafenone resistance. In contrast to APKs, the mode of action of SDHIs is well understood. Sequencing of the sdh-genes of less sensitive E. necator isolates identified four different target-site mutations, the B-H242R, B-I244V, C-G169D and C-G169S, in sdhB and sdhC, respectively. Based on this information it was possible to develop molecular genetic monitoring methods for the mutations B-H242R and C-G169D. In 2016, the B-H242R was thereby identified as by far the most frequent mutation. Depending on the analysed SDH compound and the sdh-genotype, different sensitivities were observed and revealed a complex cross-resistance pattern.
Growth competition assays without selection pressure, with mixtures of sensitive and resistant E. necator isolates, were performed to determine potential fitness costs associated with fungicide resistance. With the experimental setups used, a clear fitness disadvantage associated with metrafenone resistance was not identified, although a strong variability of fitness was observed among the tested resistant E. necator isolates. For isolates with a reduced sensitivity towards SDHIs, associated fitness costs were dependent on the sdh-genotype analysed. Competition tests with the B-H242R genotypes gave evidence that there are no fitness costs associated with this mutation. In contrast, the C-G169D genotypes were less competitive, indicating a restricted fitness compared to the tested sensitive partners. Competition assays of field isolates, which exhibited several resistances towards different fungicide classes, indicated that there are no fitness costs associated with a multiple resistant phenotype in E. necator. Overall, these results clearly indicate the importance to analyse a representative number of isolates with sensitive and resistant phenotypes.
This work is concerned with two often separated disciplines. First, experimental studies in which the effect of cooling rate on martensite transformation and the resulting microstructure in a low-alloy steel is investigated. From this, a possible transformation mechanism is derived. Second, the development of a simulation model which describes the martensitic morphology and its evolution. In this context, a phase field model is presented introducing order parameters to simulate the material state, namely austenite and martensite. The evolution of the order parameters is assumed to follow the time-dependent Ginzburg-Landau equation. A major extension to previous models is the consideration of twelve crystallographic martensite variants corresponding to the Nishiyama-Wassermann orientation relationship. To describe the ordered displacement of atoms during transformation and to account for the martensitic substructure, the well-known phenomenological theory of martensite crystallography is employed. The presented experiments as well as thermodynamic calculations are used as a basis in the identification of model parameters. With the presented model, basic features of the martensitic transformation can be reproduced. These include the martensite start temperature and the hierarchical microstructure consisting of blocks and packets. The sizes of the blocks are in good agreement with the real sizes of the experimental database.
This work aims at including nonlinear elastic shell models in a multibody framework. We focus our attention to Kirchhoff-Love shells and explore the benefits of an isogeometric approach, the latest development in finite element methods, within a multibody system. Isogeometric analysis extends isoparametric finite elements to more general functions such as B-Splines and Non-Uniform Rational B-Splines (NURBS) and works on exact geometry representations even at the coarsest level of discretizations. Using NURBS as basis functions, high regularity requirements of the shell model, which are difficult to achieve with standard finite elements, are easily fulfilled. A particular advantage is the promise of simplifying the mesh generation step, and mesh refinement is easily performed by eliminating the need for communication with the geometry representation in a Computer-Aided Design (CAD) tool.
Quite often the domain consists of several patches where each patch is parametrized by means of NURBS, and these patches are then glued together by means of continuity conditions. Although the techniques known from domain decomposition can be carried over to this situation, the analysis of shell structures is substantially more involved as additional angle preservation constraints between the patches might arise. In this work, we address this issue in the stationary and transient case and make use of the analogy to constrained mechanical systems with joints and springs as interconnection elements. Starting point of our work is the bending strip method which is a penalty approach that adds extra stiffness to the interface between adjacent patches and which is found to lead to a so-called stiff mechanical system that might suffer from ill-conditioning and severe stepsize restrictions during time integration. As a remedy, an alternative formulation is developed that improves the condition number of the system and removes the penalty parameter dependence. Moreover, we study another alternative formulation with continuity constraints applied to triples of control points at the interface. The approach presented here to tackle stiff systems is quite general and can be applied to all penalty problems fulfilling some regularity requirements.
The numerical examples demonstrate an impressive convergence behavior of the isogeometric approach even for a coarse mesh, while offering substantial savings with respect to the number of degrees of freedom. We show a comparison between the different multipatch approaches and observe that the alternative formulations are well conditioned, independent of any penalty parameter and give the correct results. We also present a technique to couple the isogeometric shells with multibody systems using a pointwise interaction.
Point defects in piezoelectric materials – continuum mechanical modelling and numerical simulation
(2010)
The topic of this work is the continuum mechanic modelling of point defects in piezoelectric materials. Devices containing piezoelectric material and especially ferroelectrics require a high precision and are exposed to a high number of electrical and mechanical load cycles. As a result, the relevant material properties may decrease with increasing load cycles. This phenomenon is called electric fatigue. The transported ionic and electric charge carriers can interact with each other, as well as with structural elements (grain boundaries, inhomogeneities) or with material interfaces (domain walls). A reduced domain wall mobility also reduces the electromechanical coupling effect, which leads to the electric fatigue effect. The materials considered here are barium titanate and lead zirconate titanate (PZT), in which oxygen vacancies is the most mobile and most frequently appearing defect species. Intentionally introduced foreign atoms (dopants) can adjust the material properties according to their field of application by generating electric dipoles with the vacancies. Agglomerations of point defects can strongly influence the domain wall motion. The domain wall can be slowed down or even be stopped by the locally varying fields in the vicinity of the clusters. Accumulations of point defects can be detected at electrodes, pores or in the bulk of fatigued samples. The present thesis concentrates focuses on the self interaction behaviour of point defects in the bulk. A micro mechanical continuum model is used to show the qualitative and the quantitative interaction behaviour of defects in a static setup and during drift processes. The modelling neglects the ferroelectric switching mechanisms, but is applicable to every piezoelectric material. The underlying differential equations are solved by means of analytical (Green's functions) and numerical (Finite Differences with discrete Fourier Transform) methods, depending on the boundary conditions. The defects are introduced as localised Eigenstrains, as electric charges and as electric dipoles. The required defect parameters are obtained by comparisons with atomistic methods (lattice statics). There are no standardised procedures available for the parameter identification. In this thesis, the mechanical parameter is obtained by a comparison of relaxation volumes of the atomic lattice and the continuum solution. Parameters for isotropic and anisotropic defect descriptions are identified. The strength of the electric defect is obtained by a comparison of the electric internal energies of atomistics and continuum. The appearing singularities are eliminated by taking only the energy difference of a infinite crystal and a periodic cell into account. Both identification processes are carried out for the cubic structure of barium titanate, which decouples the mechanical and the electrical problem. The defect interaction is analysed by means of configurational forces. The mechanical defect parameter generates a directional short-range attraction between defects. An electrical defect parameter produces the long-range Coulomb interaction, which predicts a repulsion of two similar charges. Additionally, an interaction with defect dipoles is taken into account. It is shown that a defect agglomeration is possible for any static defect configuration. Finally, defect drift is simulated using a thermodynamically motivated migration law based on configurational forces. In this context, the migration of point defects due to self interaction, and the influence of external fields is investigated.
Safety analysis is of ultimate importance for operating Nuclear Power Plants (NPP). The overall
modeling and simulation of physical and chemical processes occuring in the course of an accident
is an interdisciplinary problem and has origins in fluid dynamics, numerical analysis, reactor tech-
nology and computer programming. The aim of the study is therefore to create the foundations
of a multi-dimensional non-isothermal fluid model for a NPP containment and software tool based
on it. The numerical simulations allow to analyze and predict the behavior of NPP systems under
different working and accident conditions, and to develop proper action plans for minimizing the
risks of accidents, and/or minimizing the consequences of possible accidents. A very large number
of scenarios have to be simulated, and at the same time acceptable accuracy for the critical param-
eters, such as radioactive pollution, temperature, etc., have to be achieved. The existing software
tools are either too slow, or not accurate enough. This thesis deals with developing customized al-
gorithm and software tools for simulation of isothermal and non-isothermal flows in a containment
pool of NPP. Requirements to such a software are formulated, and proper algorithms are presented.
The goal of the work is to achieve a balance between accuracy and speed of calculation, and to
develop customized algorithm for this special case. Different discretization and solution approaches
are studied and those which correspond best to the formulated goal are selected, adjusted, and when
possible, analysed. Fast directional splitting algorithm for Navier-Stokes equations in complicated
geometries, in presence of solid and porous obstales, is in the core of the algorithm. Developing
suitable pre-processor and customized domain decomposition algorithms are essential part of the
overall algorithm amd software. Results from numerical simulations in test geometries and in real
geometries are presented and discussed.
The dissertation is concerned with the numerical solution of Fokker-Planck equations in high dimensions arising in the study of dynamics of polymeric liquids. Traditional methods based on tensor product structure are not applicable in high dimensions for the number of nodes required to yield a fixed accuracy increases exponentially with the dimension; a phenomenon often referred to as the curse of dimension. Particle methods or finite point set methods are known to break the curse of dimension. The Monte Carlo method (MCM) applied to such problems are 1/sqrt(N) accurate, where N is the cardinality of the point set considered, independent of the dimension. Deterministic version of the Monte Carlo method called the quasi Monte Carlo method (QMC) are quite effective in integration problems and accuracy of the order of 1/N can be achieved, up to a logarithmic factor. However, such a replacement cannot be carried over to particle simulations due to the correlation among the quasi-random points. The method proposed by Lecot (C.Lecot and F.E.Khettabi, Quasi-Monte Carlo simulation of diffusion, Journal of Complexity, 15 (1999), pp.342-359) is the only known QMC approach, but it not only leads to large particle numbers but also the proven order of convergence is 1/N^(2s) in dimension s. We modify the method presented there, in such a way that the new method works with reasonable particle numbers even in high dimensions and has better order of convergence. Though the provable order of convergence is 1/sqrt(N), the results show less variance and thus the proposed method still slightly outperforms standard MCM.
With the expansion of the electromobility and wind energy, the number of frequency inverter-controlled electric motors and generators is increasing. In parallel, the number of the rolling bearing failures caused by inverter-induced parasitic currents also shows an increasing trend. In order to determine the electrical state of the rolling bearing, to develop preventive measures against damages caused by parasitic currents and to support system-level calculations, electrical rolling bearing models have been developed. The models are based on the electrical insulating ability of the lubricant film that develops in the rolling contacts. For the capacitance calculation of the rolling contacts, different correction factors were developed to simplify the complex tribological and electrical interactions of this region. The state-of-the-art correction factors vary widely, and their validity range also differ significantly, which leads to uncertainty in their general application and to the demand for further investigations of this field. In the present work, a combined simulation method is developed that can determine the rolling bearing capacitance of axially loaded rolling bearings. The simulation consists of an electrically extended EHL simulation for calculating the capacitance of the rolling contact, and an electrical FEM simulation for the capacitance calculation of the non-contact regions. With the combination of the resulted capacitance values of the two simulation methods, the total rolling bearing capacitance can be determined with high accuracy and without using correction factors. In addition, due to experimental investigations, the different capacitance sources of the rolling bearing are identified. After the validation of the combined simulation method, it can be applied for the investigation of the different capacitance sources, i.e., to determine their significance compared to the total rolling bearing capacitance. The developed simulation method allows a detailed analysis of the rolling bearing capacitances, taking into account influencing factors that could not be considered before (e.g., oil quantity in the environment of the rolling bearing). As a result, the accurate calculation of the rolling bearing capacitance can improve the prediction of the harmful parasitic currents and help to develop preventive measures against them.
In this work we study and investigate the minimum width annulus problem (MWAP), the circle center location or circle location problem (CLP) and the point center location or point location problem (PLP) on Rectilinear and Chebyshev planes as well as in networks. The relations between the problems have served as a basis for finding of elegant solution, algorithms for both new and well known problems. So, MWAP was formulated and investigated in Rectilinear space. In contrast to Euclidean metric, MWAP and PLP have at least one common optimal point. Therefore, MWAP on Rectilinear plane was solved in linear time with the help of PLP. Hence, the solution sequence was PLP-->MWAP. It was shown, that MWAP and CLP are equivalent. Thus, CLP can be also solved in linear time. The obtained results were analysed and transfered to Chebyshev metric. After that, the notions of circle, sphere and annulus in networks were introduced. It should be noted that the notion of a circle in a network is different from the notion of a cycle. An O(mn) time algorithm for solution of MWAP was constructed and implemented. The algorithm is based on the fact that the middle point of an edge represents an optimal solution of a local minimum width annulus on this edge. The resulting complexity is better than the complexity O(mn+n^2logn) in unweighted case of the fastest known algorithm for minimizing of the range function, which is mathematically equivalent to MWAP. MWAP in unweighted undirected networks was extended to the MWAP on subsets and to the restricted MWAP. Resulting problems were analysed and solved. Also the p–minimum width annulus problem was formulated and explored. This problem is NP–hard. However, the p–MWAP has been solved in polynomial O(m^2n^3p) time with a natural assumption, that each minimum width annulus covers all vertexes of a network having distances to the central point of annulus less than or equal to the radius of its outer circle. In contrast to the planar case MWAP in undirected unweighted networks have appeared to be a root problem among considered problems. During investigation of properties of circles in networks it was shown that the difference between planar and network circles is significant. This leads to the nonequivalence of CLP and MWAP in the general case. However, MWAP was effectively used in solution procedures for CLP giving the sequence MWAP-->CLP. The complexity of the developed and implemented algorithm is of order O(m^2n^2). It is important to mention that CLP in networks has been formulated for the first time in this work and differs from the well–studied location of cycles in networks. We have constructed an O(mn+n^2logn) algorithm for well–known PLP. The complexity of this algorithm is not worse than the complexity of the currently best algorithms. But the concept of the solution procedure is new – we use MWAP in order to solve PLP building the opposite to the planar case solution sequence MWAP-->PLP and this method has the following advantages: First, the lower bounds LB obtained in the solution procedure are proved to be in any case better than the strongest Halpern’s lower bound. Second, the developed algorithm is so simple that it can be easily applied to complex networks manually. Third, the empirical complexity of the algorithm is equal to O(mn). MWAP was extended to and explored in directed unweighted and weighted networks. The complexity bound O(n^2) of the developed algorithm for finding of the center of a minimum width annulus in the unweighted case does not depend on the number of edges in a network, because the problems can be solved in the order PLP-->MWAP. In the weighted case computational time is of order O(mn^2).
Genome-based Approaches for Understanding Nutritional Iron Homeostasis in Chlamydomonas reinhardtii
(2021)
Iron is an essential nutrient for all life forms, including plants, but of limiting availability in many environments, affecting productivity of both food production and carbon capturing. Iron is essential because of its broad function as a catalyst of redox reactions and processes involving O2 chemistry in the catalytic centers of enzymes. Because of the nature of these reactions, excess amounts of the nutrient can be toxic, requiring a fine tuning of the cellular iron content, to both accommodate the essential demand and avoid detrimental effects simultaneously. A question of this project is how plant metabolism is modified in iron-deficient conditions, for which the green alga Chlamydomonas reinhardtii as a microbe is an excellent reference organism. The metabolic flexibility of C. reinhardtii, specifically the capacity for both heterotrophic (on acetate) and autotrophic (on CO2) growth, offers a unique opportunity to distinguish the impact of iron nutrition on photosynthetic versus respiratory metabolism. During steady-state photoheterotrophic Fe-limited growth, where the cells are provided with light, CO2, and acetate, but lack extracellular iron, cells maintain respiration while decreasing photosynthetic contribution to the energetics of the cell. This thesis analyzes the transition from photoautotrophic (light and CO2) to photoheterotrophic cultures in the context of Fe-nutrition by adding a reduced carbon source to phototrophic cultures and assessing the developing changes to the metabolism time-dependently, in various levels of readouts. Based on the transcriptome analysis, all major cellular processes and pathways respond to the availability of acetate, but Fe-limited cells specifically sacrifice photosynthetic capacity towards respiratory activity in the first 12h after the additional carbon source becomes available, allowing to gain mechanistic insights of transitioning between different ways of life, dependent on the nutritional makeup of the environment. Secondly, exposure to high extracellular iron amounts, its opportunities, and the mechanisms of avoiding deleterious effects as a result from it, had been under-investigated before the beginning of this thesis. Physiological and photosynthetic parameters, elemental analysis, transcriptomics, and a mutant depleted of functional acidic vacuoles, proposed to be involved in the storage for transition metals, were utilized to further the understanding of the processes. Altogether, the results presented in this thesis illustrate how C. reinhardtii can be successfully used as a model organism to study a large variety of aspects of cell and molecular biology, including dynamic acclimations to changing environments.
Membrane proteins are generally soluble only in the presence of detergent micelles or other membrane-mimetic systems, which renders the determination of the protein’s molar mass or oligomeric state difficult. Moreover, the amount of bound detergent varies drastically among different proteins and detergents. However, the type of detergent and its concentration have a great influence on the protein’s structure, stability, and functionality and the success of structural and functional investigations and crystallographic trials. Size-exclusion chromatography, which is commonly used to determine the molar mass of water-soluble proteins, is not suitable for detergent-solubilised proteins because
the protein–detergent complex has a different conformation and, thus, commonly exhibits
a different migration behaviour than globular standard proteins. Thus, calibration curves obtained with standard proteins are not useful for membrane-protein analysis. However,
the combination of size-exclusion chromatography with ultraviolet absorbance, static light scattering, and refractive index detection provides a tool to determine the molar mass of protein–detergent complexes in an absolute manner and allows for distinguishing the contributions of detergent and protein to the complex.
The goal of this thesis was to refine the standard triple-detection size-exclusion chromatography measurement and data analysis procedure for challenging membrane-protein samples, non-standard detergents, and difficult solvents such as concentrated denaturant solutions that were thought to elude routine approaches. To this end, the influence of urea on the performance of the method beyond direct influences on detergents and proteins was investigated with the help of the water-soluble bovine serum albumin. On the basis of
the obtained results, measurement and data analysis procedures were refined for different detergents and protein–detergent complexes comprising the membrane proteins OmpLA and Mistic from Escherichia coli and Bacillus subtilis, respectively.
The investigations on mass and shape of different detergent micelles and the compositions of protein–detergent complexes in aqueous buffer and concentrated urea solutions
showed that triple-detection size-exclusion chromatography provides valuable information
about micelle masses and shapes under various conditions. Moreover, it is perfectly suited for the straightforward analysis of detergent-suspended proteins in terms of composition and oligomeric state not only under native but, more importantly, also under denaturing conditions.
Novel image processing techniques have been in development for decades, but most
of these techniques are barely used in real world applications. This results in a gap
between image processing research and real-world applications; this thesis aims to
close this gap. In an initial study, the quantification, propagation, and communication
of uncertainty were determined to be key features in gaining acceptance for
new image processing techniques in applications.
This thesis presents a holistic approach based on a novel image processing pipeline,
capable of quantifying, propagating, and communicating image uncertainty. This
work provides an improved image data transformation paradigm, extending image
data using a flexible, high-dimensional uncertainty model. Based on this, a completely
redesigned image processing pipeline is presented. In this pipeline, each
step respects and preserves the underlying image uncertainty, allowing image uncertainty
quantification, image pre-processing, image segmentation, and geometry
extraction. This is communicated by utilizing meaningful visualization methodologies
throughout each computational step.
The presented methods are examined qualitatively by comparing to the Stateof-
the-Art, in addition to user evaluation in different domains. To show the applicability
of the presented approach to real world scenarios, this thesis demonstrates
domain-specific problems and the successful implementation of the presented techniques
in these domains.
In many medical, financial, industrial, e.t.c. applications of statistics, the model parameters may undergo changes at unknown moment of time. In this thesis, we consider change point analysis in a regression setting for dichotomous responses, i.e. they can be modeled as Bernoulli or 0-1 variables. Applications are widespread including credit scoring in financial statistics and dose-response relations in biometry. The model parameters are estimated using neural network method. We show that the parameter estimates are identifiable up to a given family of transformations and derive the consistency and asymptotic normality of the network parameter estimates using the results in Franke and Neumann Franke Neumann (2000). We use a neural network based likelihood ratio test statistic to detect a change point in a given set of data and derive the limit distribution of the estimator using the results in Gombay and Horvath (1994,1996) under the assumption that the model is properly specified. For the misspecified case, we develop a scaled test statistic for the case of one-dimensional parameter. Through simulation, we show that the sample size, change point location and the size of change influence change point detection. In this work, the maximum likelihood estimation method is used to estimate a change point when it has been detected. Through simulation, we show that change point estimation is influenced by the sample size, change point location and the size of change. We present two methods for determining the change point confidence intervals: Profile log-likelihood ratio and Percentile bootstrap methods. Through simulation, the Percentile bootstrap method is shown to be superior to profile log-likelihood ratio method.
1,3-Diynes are frequently found as an important structural motif in natural products, pharmaceuticals and bioactive compounds, electronic and optical materials and supramolecular molecules. Copper and palladium complexes are widely used to prepare 1,3-diynes by homocoupling of terminal alkynes; albeit the potential of nickel complexes towards the same is essentially unexplored. Although a detailed study on the reported nickel-acetylene chemistry has not been carried out, a generalized mechanism featuring a nickel(II)/nickel(0) catalytic cycle has been proposed. In the present work, a detailed mechanistic aspect of the nickel-mediated homocoupling reaction of terminal alkynes is investigated through the isolation and/or characterization of key intermediates from both the stoichiometric and the catalytic reactions. A nickel(II) complex [Ni(L-N4Me2)(MeCN)2](ClO4)2 (1) containing a tetradentate N,N′-dimethyl-2,11-diaza[3.3](2,6)pyridinophane (L-N4Me2) as ligand was used as catalyst for homocoupling of terminal alkynes by employing oxygen as oxidant at room temperature. A series of dinuclear nickel(I) complexes bridged by a 1,3-diyne ligand have been isolated from stoichiometric reaction between [Ni(L-N4Me2)(MeCN)2](ClO4)2 (1) and lithium acetylides. The dinuclear nickel(I)-diyne complexes [{Ni(L-N4Me2)}2(RC4R)](ClO4)2 (2) were well characterized by X-ray crystal structures, various spectroscopic methods, SQUID and DFT calculation. The complexes not only represent as a key intermediate in aforesaid catalytic reaction, but also describe the first structurally characterized dinuclear nickel(I)-diyne complexes. In addition, radical trapping and low temperature UV-Vis-NIR experiments in the formation of the dinuclear nickel(I)-diyne confirm that the reactions occurring during the reduction of nickel(II) to nickel(I) and C-C bond formation of 1,3-diyne follow non-radical concerted mechanism. Furthermore, spectroscopic investigation on the reactivity of the dinuclear nickel(I)-diyne complex towards molecular oxygen confirmed the formation of a mononuclear nickel(I)-diyne species [Ni(L-N4Me2)(RC4R)]+ (4) and a mononuclear nickel(III)-peroxo species [Ni(L-N4Me2)(O2)]+ (5) which were converted to free 1,3-diyne and an unstable dinuclear nickel(II) species [{Ni(L-N4Me2)}2(O2)]2+ (6). A mononuclear nickel(I)-alkyne complex [Ni(L-N4Me2)(PhC2Ph)](ClO4).MeOH (3) and the mononuclear nickel(III)-peroxo species [Ni(L-N4Me2)(O2)]+ (5) were isolated/generated and characterized to confirm the formulation of aforementioned mononuclear nickel(I)-diyne and mononuclear nickel(III)-peroxo species. Spectroscopic experiments on the catalytic reaction mixture also confirm the presence of aforesaid intermediates. Results of both stoichiometric and catalytic reactions suggested an intriguing mechanism involving nickel(II)/nickel(I)/nickel(III) oxidation states in contrast to the reported nickel(II)/nickel(0) catalytic cycle. These findings are expected to open a new paradigm towards nickel-catalyzed organic transformations.
The research problem is that the land-use (re-)planning process in the existing Egyptian cities
does not attain sustainability. This is because of the unfulfillment of essential principles within
their land-use structures, lack of harmony between the added and old parts in the cities, and
other reasons. This leads to the need for developing an assessment system, which is a
computational spatial planning support system-SPSS. This SPSS is used for identifying the
degree of sustainability attainment in land-uses plans, predicting probable problems, and
suggesting modifications in the evaluated plans.
The main goal is to design the SPSS for supporting sustainability in the Egyptian cities. The
secondary goals are: studying the Egyptian planning and administrative systems for designing
the technical and administrative frameworks for the SPSS, the development of an assessment
model from the SPSS for assessing sustainability in land-use structures of urban areas, as well
as the identification of the improvements required in the model and the recommendations for
developing the SPSS.
The theoretical part aims to design each of the administrative and technical frameworks of the
SPSS. This requires studying each of the main planning approaches, the sustainability in urban
land-use planning, and the significance of using efficient assessment tools for evaluating the
sustainability in this process. The added value of the planning support systems-PSSs for
planning and their role in supporting sustainability attainment in urban land-use planning are
discussed. Then, a group of previous examples in the sustainability assessment from various
countries (developed and developing countries) are selected, which have used various
assessment tools. This is to extract some learned lessons to be guides for the SPSS. And so,
the comprehensive technical framework for the SPSS is designed, which includes the suggested
methods and techniques that perform various stages of the assessment process.
The Egyptian context is studied regarding the planning and administration systems within the
Egyptian cities, as well as the spatial and administrative problems facing the sustainable
development. And so, the administrative framework for the SPSS is identified, which includes
the entities that should be involved in the assessment process.
The empirical part focuses on the design of a selected assessment model from the
comprehensive technical framework of the SPSS to be established as a minimized version from
it. This model is programmed in the form of a new toolbox within the ArcGIS™ software through
geoscripting using Python programming language to be applied for assessing the sustainability
attainment in the land-use structure of urban areas. The required assessing criteria for the model
specialized for the Egyptian and German cities are identified, for applying it on German and
Egyptian study areas.
The conclusions regarding each of PSSs, the Egyptian local administration and planning
systems, sustainability attainment in the land-use planning process in Egyptian Cities, as well as
the proposed SPSS and the developed toolbox are drawn. The recommendations are regarding
each of challenges facing the development and application of PSSs, the Egyptian local
administration and planning systems, the spatial problems in Egyptian cities, the establishment
of the SPSS, and the application of the toolbox. The future agenda is in the fields of sustainable urban land-use planning, planning support science, and the development process in the
Egyptian cities.
Machine Learning (ML) is expected to become an integrated part of future mobile networks due to its capacity for solving complex problems. During inference, ML algorithms extract the hidden knowledge of their input data which is delivered to them through wireless links in many scenarios. Transmission of a massive amount of such input data can impose a huge burden on the mobile network. On the other hand, it is known that ML algorithms can tolerate different levels of distortion on their input components, while the quality of their predictions remains unaffected. Therefore, utilization of the conventional approaches
implies a waste of radio resources, since they target an exact reconstruction of transmitted data, i.e., the input of ML algorithms. In this thesis, we propose a novel relevance based framework that focuses on the quality of final ML outputs instead of such syntax based reconstruction of transmitted inputs. To this end, we quantify the semantics or relevancy of input components in terms of the bit allocation aspect of data compression, where a higher tolerance for distortion implies less relevancy. A lower relevance level is translated into the allocation of less radio resources, e.g., bandwidth. The introduced formulation provides the foundations for the efficient support of ML models with their required data in the inference phase, while wireless resources are employed efficiently.
In this dissertation, a generic relevance based framework utilizing the Kullback-Leibler Divergence (KLD) is developed that is applicable to many realistic scenarios. The system model under study contains multiple sources transmitting correlated multivariate input components of a ML algorithm. The ML model is seen as a black box, which is trained and has fixed parameters while operating in the inference phase. Our proposed bit allocation accounts for the rate-distortion tradeoff. Hence, it is simply adjustable for application to
other problems. Here, an extended version of the proposed bit allocation strategy is introduced for signaling overhead reduction, in which the relevancy level of each input attribute changes instantaneously. In another expansion, to take the effect of dynamic channel states into account, a resource allocation approach for ML based centralized control systems is proposed. The novel quality of service metric takes outputs of ML algorithms into consideration,
and in combination with the designed greedy algorithm, provides significantly
improved end-to-end performance for a network of cart inverted pendulums.
The introduced relevance based framework is comprehensively investigated by considering various case studies, real and synthetic data, regression and classification, different estimators for the KLD, various ML models and codebook designs. Furthermore, the reliability of this proposed solution is explored in presence of packet drops, indicating robustness of the relevance based compression. In all of the simulations, the relevance based solutions deliver the best outcome in terms of the carefully chosen key performance indicators. In most of them, significantly high gains are also achieved compared to the conventional techniques, motivating further research on the subject.
Cloud Computing, or the Cloud, became one of the most used technologies in today's world, right after its possibilities had been figured out. It is a renowned technology that enables ubiquitous access to tasks that need collaboration or remote monitoring. It is widely used in daily lives as well as the industry. The paradigm uses Internet Technologies which rely on best-effort communication. Best-effort communication limits the applicability of the technology in the domains where the timing is critical. Edge Computing is a paradigm that is seen as a complementary technology to the Cloud. It is expected to solve the Quality of Service (QoS) and latency problems that are raised due to the increased count of connected devices, and the physical distance between the infrastructure and devices. The Edge Computing adds a new tier between Information Technology (IT) and Operational Technology (OT) and brings the computing power close to the source of the data. Computing power near devices reduces the dependency to the Internet; hence, in case of a network failure, the computation can still continue. Close proximity deployments also enable the application of Edge Computing in the areas where real-timeliness is necessary. Computation and communication in Edge Computing are performed via Edge Servers. This thesis suggests a standardized and hardware-independent software reference architecture for Edge Servers that can be realized as a framework on servers, to be used on domains where the timing is critical. The suggested architecture is scalable, extensible, modular, multi-user supported, and decentralized. In decentralized systems, several precautions must be taken into consideration, such as latencies, delays, and available resources of the neighbouring servers. The resulting architecture evaluates these factors and enables real-time execution. It also hides the complexity of low-level communication and automates the collaboration between Edge Servers to enable seamless offloading in case of a need due to lack of resources. The thesis also validates an exemplary instance of the architecture with at framework, called Real-Time Execution Framework (RTEF), with multiple scenarios. The tasks used are resource-demanding and requested to be executed on an Edge Server in an Edge Network comprising multiple Edge Servers. The servers can make decisions by evaluating their availabilities, and determine the optimal location to execute the task, without causing deadline misses. Even under a heavy load, the decisions made by the servers to execute the tasks on time were correct, and the concept is proven.
Embedded systems, ranging from very simple systems up to complex controllers, may
nowadays have quite challenging real-time requirements. Many embedded systems are reactive
systems that have to respond to environmental events and have to guarantee certain real-time
constrain. Their execution is usually divided into reaction steps, where in each step, the
system reads inputs from the environment and reacts to these by computing corresponding
outputs.
The synchronous Model of Computation (MoC) has proven to be well-suited for the
development of reactive real-time embedded systems whose paradigm directly reflects the
reactive nature of the systems it describes. Another advantage is the availability of formal
verification by model checking as a result of the deterministic execution based on a formal
semantics. Nevertheless, the increasing complexity of embedded systems requires to compensate
the natural disadvantages of model checking that suffers from the well-known state-space
explosion problem. It is therefore natural to try to integrate other verification methods with
the already established techniques. Hence, improvements to encounter these problems are
required, e.g., appropriate decomposition techniques, which encounter the disadvantages
of the model checking approach naturally. But defining decomposition techniques for synchronous
language is a difficult task, as a result of the inherent parallelism emerging from
the synchronous broadcast communication.
Inspired by the progress in the field of desynchronization of synchronous systems by
representing them in other MoCs, this work will investigate the possibility of adapting and use
methods and tools designed for other MoC for the verification of systems represented in the
synchronous MoC. Therefore, this work introduces the interactive verification of synchronous
systems based on the basic foundation of formal verification for sequential programs – the
Hoare calculus. Due to the different models of computation several problems have to be
solved. In particular due to the large amount of concurrency, several parts of the program
are active at the same point of time. In contrast to sequential programs, a decomposition
in the Hoare-logic style that is in some sense a symbolic execution from one control flow
location to another one requires the consideration of several flows here. Therefore, different
approaches for the interactive verification of synchronous systems are presented.
Additionally, the representation of synchronous systems by other MoCs and the influence
of the representation on the verification task by differently embedding synchronous system
in a single verification tool are elaborated.
The feasibility is shown by integration of the presented approach with the established
model checking methods by implementing the AIFProver on top of the Averest system.
Like many other bacteria, the opportunistic pathogen P. aeruginosa encodes a broad network of enzymes that regulate the intracellular concentration of the second messenger c-di-GMP. One of these enzymes is the phosphodiesterase NbdA that consists of three domains: a membrane anchored, putative sensory MHYT domain, a non-functional diguanylate cyclase domain with degenerated GGDEF motif and an active PDE domain with EAL motif. Analysis of the nbdA open reading frame by 5’-RACE PCR revealed an erroneous annotation of nbdA in the Pseudomonas database with the ORF 170 bp shorter than previously predicted. The newly defined promoter region of nbdA contains recognition sites for the alternative sigma-factor RpoS as well as the transcription factor AmrZ. Promoter analysis within PAO1 wt as well as rpoS and amrZ mutant strains utilizing transcriptional fusions of the nbdA promoter to the reporter gene lacZ revealed transcriptional activation of nbdA by RpoS in stationary growth phase and transcriptional repression by AmrZ. Additionally, no influence of nitrite and neither exogenous nor endogenous NO on nbdA transcription could be shown in this study. However, deletion of the nitrite reductase gene nirS led to a strong increase of nbdA promoter activity which needs to be characterized further. Predicted secondary structures of the 5’-UTR of the nbdA mRNA indicated either an RNA thermometer function of the mRNA or post-transcriptional regulation of nbdA by the RNA binding proteins RsmA and RsmF. Nevertheless, translational studies using fusions of the 5’ UTR of nbdA to the reporter gene bgaB did not verify either of these hypotheses. In general, nbdA translational levels were very low and neither the production of the reporter BgaB nor genomically encoded NbdA could be detected on a western blot. Overproduction of NbdA variants induced many phenotypic changes in motility and biofilm formation. But strains overproducing variants containing the MHYT domain revealed greatly elongated cells and were impaired in surface growth, indicating a misbalance in the membrane protein homeostasis. Therefore, these phenotypes have to be interpreted very critically. Microscopic studies with fluorescently tagged NbdA revealed either a diffuse fluorescent signal of NbdA or the formation of fluorescent foci which were located mainly at the cell poles. Co-localization studies with the polar flagellum and the chemotaxis protein CheA showed that NbdA is not generally localizing to the flagellated cell pole. NbdA localization indicates the control of a specific local c-di-GMP pool in the cell which is most likely involved in MapZ mediated chemotactic flagellar motor switching.
An huge amount of computational models and programming languages have been proposed
for the description of embedded systems. In contrast to traditional sequential programming
languages, they cope directly with the requirements for embedded systems: direct support for
concurrent computations and periodic interaction with the environment are only some of the
features they offer. Synchronous languages are one class of languages for the development of
embedded systems and they follow the fundamental principle that the execution is divided into
a sequence of logical steps. Thereby, each step follows the simplification that the computation
of the outputs is finished directly when the inputs are available. This rigorous abstraction leads
to well-defined deterministic parallel composition in general, and to deterministic abortion
and suspension in imperative synchronous languages in particular. These key features also
allow to translate programs to hardware and software, and also formal verification techniques
like model checking can be easily applied.
Besides the advantages of imperative synchronous languages, also some drawbacks can
be listed. Over-synchronization is an effect being caused by parallel threads which have to
synchronize for each execution step, even if they do not communicate, since the synchronization
is implicitly forced by the control-flow. This thesis considers the idea of clock refinement to
introduce several abstraction layers for communication and synchronization in addition to the
existing single-clock abstraction. Thereby, clocks can be refined by several independent clocks
so that a controlled amount of asynchrony between subsequent synchronization points can be
exploited by compilers. The declarations of clocks form a tree, and clocks can be defined within
the threads of the parallel statement, which allows one to do independent computations based
on these clocks without synchronizing the threads. However, the synchronous abstraction is
kept at each level of the abstraction.
Clock refinement is introduced in this thesis as an extension to the imperative synchronous
language Quartz. Therefore, new program statements are introduced which allow to define
a new clock as a refinement of an existing one and to finish a step based on a certain clock.
Examples are considered to show the impact of the behavior of the new statements to
the already existing statements, before the semantics of this extension is formally defined.
Furthermore, the thesis presents a compile algorithm to translate programs to an intermediate
format, and to translate the intermediate format to a hardware description. The advantages
obtained by the new modeling feature are finally evaluated based on examples.
The dissertation deals with the application of Hub Location models in public transport planning. The author proposes new mathematical models along with different solution approaches to solve the instances. Moreover, a novel multi-period formulation is proposed as an extension to the general model. Due to its high complexity heuristic approaches are formulated to find a good solution within a reasonable amount of time.
This thesis deals with risk measures based on utility functions and time consistency of dynamic risk measures. It is therefore aimed at readers interested in both, the theory of static and dynamic financial risk measures in the sense of Artzner, Delbaen, Eber and Heath [7], [8] and the theory of preferences in the tradition of von Neumann and Morgenstern [134].
A main contribution of this thesis is the introduction of optimal expected utility (OEU) risk measures as a new class of utility-based risk measures. We introduce OEU, investigate its main properties, and its applicability to risk measurement and put it in perspective to alternative risk measures and notions of certainty equivalents. To the best of our knowledge, OEU is the only existing utility-based risk measure that is (non-trivial and) coherent if the utility function u has constant relative risk aversion. We present several different risk measures that can be derived with special choices of u and illustrate that OEU reacts in a more sensitive way to slight changes of the probability of a financial loss than value at risk (V@R) and average value at risk.
Further, we propose implied risk aversion as a coherent rating methodology for retail structured products (RSPs). Implied risk aversion is based on optimal expected utility risk measures and, in contrast to standard V@R-based ratings, takes into account both the upside potential and the downside risks of such products. In addition, implied risk aversion is easily interpreted in terms of an individual investor's risk aversion: A product is attractive (unattractive) for an investor if its implied risk aversion is higher (lower) than his individual risk aversion. We illustrate this approach in a case study with more than 15,000 warrants on DAX ® and find that implied risk aversion is able to identify favorable products; in particular, implied risk aversion is not necessarily increasing with respect to the strikes of call warrants.
Another main focus of this thesis is on consistency of dynamic risk measures. To this end, we study risk measures on the space of distributions, discuss concavity on the level of distributions and slightly generalize Weber's [137] findings on the relation of time consistent dynamic risk measures to static risk measures to the case of dynamic risk measures with time-dependent parameters. Finally, this thesis investigates how recursively composed dynamic risk measures in discrete time, which are time consistent by construction, can be related to corresponding dynamic risk measures in continuous time. We present different approaches to establish this link and outline the theoretical basis and the practical benefits of this relation. The thesis concludes with a numerical implementation of this theory.
In tribology laboratories, the management of material samples and test specimens, the planning and execution of experiments, the evaluation of test data and the longterm storage of results are critical processes. However, despite their criticality, they are carried out manually and typically at a low level of computerization and standardization. Therefore, formats for primary data and aggregated results are wildly different between laboratories, and the interoperability of research data is low. Even within laboratories, low levels of standardization, in combination with ambiguous or non-unique identifiers for data files, test specimens and analysis results greatly reduce data integrity and quality. As a consequence, productivity is low, error rates are high, and the lack or low quality of metadata causes the value of produced data to deteriorate very quickly, which makes the re-use of data, e.g. for data mining and meta studies, practically impossible.
In other fields of science, these are mitigated by the use of Laboratory Information Management Systems (LIMS). However, at the moment, such systems do not exist
in tribological research. The main challenge for the implementation of such a system is that it requires extensive interdisciplinary knowledge from otherwise very
disparate fields: tribology, data and process modelling, quality management, databases and programming. So far, existing solutions are either proprietary, very limited
in their scope or focused on merely storing aggregated results without any support for laboratory operations.
Therefore, this thesis describes fundamentals of information technology, data modelling and programming that are required to build a LIMS for tribology laboratories.
Based on an analysis of a typical workflow of a tribology laboratory, a data model for all relevant entities and processes is designed using object-relational data modelling and object-oriented programming and a relational database is used to provide a reference implementation of such a LIMS. It provides critical functionalities
like a materials database, test specimen management, the planning, execution and evaluation of friction and wear tests, automated procedures for tribometer
parameterization and data transmission, storage and evaluation and for aggregating individual tests into test sets and projects. It improves the quality and long-term usability of data by replacing error-prone human processes by automated variants, e.g. automated collection of metadata and data file transmission, homogenization and storage. The usefulness of the developed LIMS is demonstrated by applying it to Transfer Film Luminance Analysis (TLA), which is a newly developed advanced method for the analysis of the formation and stability of transfer films and their impact on friction and wear, but which produces so much data and requires such a large amount of metadata during evaluation that it can only be performed safely, quickly and reliably by integration into the presented LIMS.
Most software systems are described in high-level model or programming languages. Their runtime behavior, however, is determined by the compiled code. For uncritical software, it may be sufficient to test the runtime behavior of the code. For safety-critical software, there is an additional aggravating factor resulting from the fact that the code must satisfy the formal specification which reflects the safety policy of the software consumer and that the software producer is obliged to demonstrate that the code is correct with respect to the specification using formal verification techniques. In this scenario, it is of great importance that static analyses and formal methods can be applied on the source code level, because this level is more abstract and better suited for such techniques. However, the results of the analyses and the verification can only be carried over to the machine code level, if we can establish the correctness of the translation. Thus, compilation is a crucial step in the development of software systems and formally verified translation correctness is essential to close the formalization chain from high-level formal methods to the machine-code level. In this thesis, I propose an approach to certifying compilers which achieves the aim of closing the formalization chain from high-level formal methods to the machine-code level by applying techniques from mathematical logic and programming language semantics. I propose an approach called foundational translation validation (FTV) in which the software producer implements an FTV system comprising a compiler and a specification and verification framework (SVF) which is implemented in higher-order logic (HOL). The most important part of the SVF is an explicit translation contract which comprises the formalizations of the source and the target languages of the compiler and the formalization of a binary translation correctness predicate corrTrans(S,T) for source programs S and target programs T. The formalizations of the languages are realized as deep embeddings in HOL. This enables one to declare the whole program in a formalized language as a HOL constant. The predicate formally specifies when T is considered to be a correct translation of S. Its definition is explicitly based on the program semantics definitions provided by the translation contract. Subsequent to the translation, the compiler translates the source and the target programs into their syntactic representations as HOL constants, S and T, and generates a proof of corrTrans(S,T). We call a compiler which follows the FTV approach a proof generating compiler. Our approach borrows the idea of representing programs in correctness proofs as logic constants from the foundational proof-carrying code (FPCC) approach. Novel features that distinquish our approach from further approaches to certifying compilers, such as proof-carrying code (PCC) and translation validation (TV) are the following: Firstly, the presence of an explicit translation contract formalized in HOL: The approaches PCC and TV do not formalize a translation contract explicitly. Instead of this, they incorporate operational semantics and translation correctness criterion in translation validation tools on the programming language level. Secondly, representation of programs in correctness proofs as logic constants: The approaches PCC and the TV translate programs into their representations as semantic abstractions that serve as inputs for translation validation tools. Thirdly, certification of program transformation chains: Unlike the TV approach, which certifies single program transformations, the FTV approach achieves the aim of certifying whole chains of program transformations. This is possible due to the fact that the translation contract provides, for all programming languages involved in the program transformation chain, definitions of program semantics functions which map programs to mathematical objects that are elements of a set with an (at least) partial order "<=". Then, the proof makes use of the fact that the relation "<=" is transitive. In this thesis, the feasibility of the FTV approach is exemplified by the implementation of an FTV system. The system comprises a compiler front-end that certifies its optimization phase and an accompanying SVF that is implemented in the theorem prover Isabelle/HOL. The compiler front-end translates programs in a small C-like programming language, performs three optimizations: constant folding, dead assignment elimination, and loop invariant hoisting, and generates translation certificates in the form of Isabelle/HOL theories. The main focus of the thesis is on the description of the SVF and its translation verification techniques.
Robotic systems are entering the stage. Enabled by advances in both hardware components and software techniques, robots are increasingly able to operate outside of factories, assist humans, and work alongside them. The limiting factor of robots’ expansion remains the programming of robotic systems. Due to the many diverse skills necessary to build a multi-robot system, only the biggest organizations are able to innovate in the space of services provided by robots.
To make developing new robotic services easier, in this dissertation I propose a program- ming model in which users (programmers) give a declarative specification of what needs to be accomplished, and then a backend system makes sure that the specification is safely and reliably executed. I present Antlab, one such backend system. Antlab accepts Linear Temporal Logic (LTL) specifications from multiple users and executes them using a set of robots of different capabilities.
Building on the experience acquired implementing Antlab, I identify problems arising from the proposed programming model. These problems fall into two broad categories, specification and planning.
In the category of specification problems, I solve the problem of inferring an LTL formula from sets of positive and negative example traces, as well as from a set of positive examples only. Building on top of these solutions, I develop a method to help users transfer their intent into a formal specification. The approach taken in this dissertation is combining the intent signals from a single demonstration and a natural language description given by a user. A set of candidate specifications is inferred by encoding the problem as a satisfiability problem for propositional logic. This set is narrowed down to a single specification through interaction with the user; the user approves or declines generated simulations of the robot’s behavior in different situations.
In the category of planning problems, I first solve the problem of planning for robots that are currently executing their tasks. In such a situation, it is unclear what to take as the initial state for planning. I solve the problem by considering multiple, speculative initial states. The paths from those states are explored based on a quality function that repeatedly estimates the planning time. The second problem is a problem of reinforcement learning when the reward function is non-Markovian. The proposed solution consists of iteratively learning an automaton representing the reward function and using it to guide the exploration.
The scientific and industrial interest devoted to polymer/layered silicate
nanocomposites due to their outstanding properties and novel applications resulted
in numerous studies in the last decade. They cover mostly thermoplastic- and
thermoset-based systems. Recently, studies in rubber/layered silicate
nanocomposites were started, as well. It was presented how complex maybe the
nanocomposite formation for the related systems. Therefore the rules governing their
structure-property relationships have to be clarified. In this Thesis, the related
aspects were addressed.
For the investigations several ethylene propylene diene rubbers (EPDM) of polar and
non-polar origin were selected, as well as, the more polar hydrogenated acrylonitrile
butadiene rubber (HNBR). The polarity was found to be beneficial on the
nanocomposite formation as it assisted to the intercalation of the polymer chains
within the clay galleries. This favored the development of exfoliated structures.
Finding an appropriate processing procedure, i.e. compounding in a kneader instead
of on an open mill, the mechanical performance of the nanocomposites was
significantly improved. The complexity of the nanocomposite formation in
rubber/organoclay system was demonstrated. The deintercalation of the organoclay
observed, was traced to the vulcanization system used. It was evidenced by an
indirect way that during sulfur curing, the primary amine clay intercalant leaves the
silicate surface and migrates in the rubber matrix. This was explained by its
participation in the sulfur-rich Zn-complexes created. Thus, by using quaternary
amine clay intercalants (as it was presented for EPDM or HNBR compounds) the
deintercalation was eliminated. The organoclay intercalation/deintercalation detected
for the primary amine clay intercalants, were controlled by means of peroxide curing
(as it was presented for HNBR compounds), where the vulcanization mechanism
differs from that of the sulfur curing.
The current analysis showed that by selecting the appropriate organoclay type the
properties of the nanocomposites can be tailored. This occurs via generating different
nanostructures (i.e. exfoliated, intercalated or deintercalated). In all cases, the
rubber/organoclay nanocomposites exhibited better performance than vulcanizates
with traditional fillers, like silica or unmodified (pristine) layered silicates.The mechanical and gas permeation behavior of the respective nanocomposites
were modelled. It was shown that models (e.g. Guth’s or Nielsen’s equations)
developed for “traditional” vulcanizates can be used when specific aspects are taken
into consideration. These involve characteristics related to the platy structure of the
silicates, i.e. their aspect ratio after compounding (appearance of platelet stacks), or
their orientation in the rubber matrix (order parameter).
The visualization of numerical fluid flow datasets is essential to the engineering processes that motivate their computational simulation. To address the need for visual representations that convey meaningful relations and enable a deep understanding of flow structures, the discipline of Flow Visualization has produced many methods and schemes that are tailored to a variety of visualization tasks. The ever increasing complexity of modern flow simulations, however, puts an enormous demand on these methods. The study of vortex breakdown, for example, which is a highly transient and inherently three-dimensional flow pattern with substantial impact wherever it appears, has driven current techniques to their limits. In this thesis, we propose several novel visualization methods that significantly advance the state of the art in the visualization of complex flow structures. First, we propose a novel scheme for the construction of stream surfaces from the trajectories of particles embedded in a flow. These surfaces are extremely useful since they naturally exploit coherence between neighboring trajectories and are highly illustrative in nature. We overcome the limitations of existing stream surface algorithms that yield poor results in complex flows, and show how the resulting surfaces can be used a building blocks for advanced flow visualization techniques. Moreover, we present a visualization method that is based on moving section planes that travel through a dataset and sample the flow. By considering the changes to the flow topology on the plane as it moves, we obtain a method of visualizing topological structures in three-dimensional flows that are not accessible by conventional topological methods. On the same algorithmic basis, we construct an algorithm for the tracking of critical points in such flows, thereby enabling the treatment of time-dependent datasets. Last, we address some problems with the recently introduced Lagrangian techniques. While conceptually elegant and generally applicable, they suffer from an enormous computational cost that we significantly use by developing an adaptive approximation algorithm. This allows the application of such methods on very large and complex numerical simulations. Throughout this thesis, we will be concerned with flow visualization aspect of general practical significance but we will particularly emphasize the remarkably challenging visualization of the vortex breakdown phenomenon.
The research deals with a question about Architecture and its design strategies, combining historical information and digital tools. Design strategies are historically defined, they rely on geometry, context, building technologies and other factors. The study of Architecture´s own history, particularly in the verge of technological advancements, like the introduction of new materials or tools may shed some light on how to internalize digital tools like parametric design and digital fabrication.
Pyrrolizidine alkaloids are naturally occurring secondary plant metabolites mainly found in plant families of Asteraceae, Boraginaceae, and Fabaceae. Chemically, PAs consist of a pyrrolizidine core bearing hydroxyl groups, the so-called necine base, and mono- or dicarboxylic necine acids bound to the pyrrolizidine core via ester linkages. 1,2-unsaturated PAs are hepatotoxic, genotoxic, and carcinogenic due to the highly reactive pyrrolic metabolites formed by cytochrome P450 monooxygenases (CYPs) primarily in the liver. The presence of PAs as frequent contaminants in the wide variety of food and feed products would be a concern for public health.
Due to the inadequate data, the risk assessment of PAs was mainly approached using the two most toxic potent congeners, i.e., lasiocarpine and riddelliine. However, the toxic potencies of individual PA congeners differentiated widely between the congeners probably related to their structural features. The risk of PA-containing products is indeed overestimated, and a comprehensive risk assessment should take these differences into account.
After analyzing the data of many PAs, Merz and Schrenk derived interim Relative Potency (iREP) factors to present the differences in their toxicity between the sub-groups concerning their structural features. But since this concept was derived from an inadequate database, it was found that the relative toxicity of individual congeners cannot be entirely reliably evaluated. My work aimed to achieve more comprehensive congener-specific in vitro toxicological data and estimate the structure-related characteristics for refining this concept. For this purpose, ten congeners, lasiocarpine, monocrotaline, retrorsine, senecionine, seneciphylline, echimidine, europine, heliotrine, indicine, and lycopsamine, were determined in a series of in vitro test systems with different endpoints to quantify their cytotoxicity, genotoxicity, and mutagenicity.
Cytotoxicity was assessed using the Alamar blue assay. A clear structure dependence could be demonstrated in primary rat hepatocytes and HepG2 (CYP3A4) cells. On the contrary, in HepG2 cells, none of the selected PAs exhibited cytotoxic effects, probably due to the lack of CYPs. The role of CYP450 enzymes in metabolic activation was further confirmed using an inhibition assay and the activity of CYP450 enzymes was measured by a kinetic assay analyzing 7-benzyloxyresorufin-O-dealkylation (BROD). Furthermore, utilizing a glutathione-reductase-DTNB recycling assay indicated that glutathione might not play a critical role in PA-induced cytotoxicity. A micronucleus test was used for determining the PA-induced clastogenic genotoxicity. All selected PA congeners exhibited a concentration-dependent manner in the HepG2 (CYP3A4) cells. The relative potencies of PA congeners estimated from Alamar blue assay and micronucleus assay are generally consistent with the following ranking: lasiocarpine > senecionine > seneciphylline ≥ retrorsine > heliotrine (?) echimidine ≥ europine ≈ indicine ≈ lycopsamine ≈ monocrotaline. Compared to the iREP reported by Merz and Schrenk, monocrotaline exhibited considerably lower toxic potency. However, echimidine was more toxic than expected. On the other hand, mutagenicity was measured in Ames fluctuation assay with Salmonella typhimurium strains TA98 and TA100. None of the selected PA congeners up to 300 µM showed mutagenic effects despite metabolic activation with S9-mix.
More than 2.4 % of the continental surface area is covered by shallow aquatic systems such as ponds. Despite occupying only a tiny fraction of the earth's surface area, ponds are globally significant sites of carbon cycling. They receive carbon, process it and emit large amounts of greenhouse gases into the atmosphere, the most potent among others are carbon dioxide (CO2) and methane (CH4). Tube-dwelling macroinvertebrates, such as chironomid larvae (Diptera: Chironomidae) change biogeochemical functions, particularly in shallow aquatic systems. Through bioturbation involving burrow ventilation and sediment particle reworking, tube-dwelling macroinvertebrates enhance solute exchange between sediment and water. Stimulate the benthic microbial community, and regulate organic matter decomposition. This doctoral project integrates aquatic carbon biogeochemical processes with the research field of ecology to relate knowledge of biogeochemical reaction dynamics upon application of the mosquito control biocide Bacillus thuringiensis israelensis (Bti), which is an entomopathogen that kills mosquitos larvae, but also reduces the abundance of chironomids. The interdisciplinary approach combines field measurements and laboratory experiments. First, an experiment was conducted in 12 outdoor floodplain ponds mesocosms (FPMs), where the effect of Bti application on carbon transformations, carbon pools, and carbon fluxes was monitored for one year. Half of the FPMs were Bti-treated and the remaining half were controls. The study revealed that seasonal variations governed changes in transformations, pools, and fluxes on the carbon components. Treated FPMs, for which a 26 % and 41% reduction in emerging merolimnic insects and macroinvertebrates abundance, respectively was reported (in companion studies) were higher CH4emitters (137% higher than in control mesocosms). The higher CH4 emissions occurred specifically in the shallow zone where the macroinvertebrate reduction was also significant. In the same treated FPMs, a tendency towards less dissolved organic carbon in porewater (33% lower than in control mesocosms), was potentially caused by the reduction in bioturbation activities of chironomids, whereas the remaining measured components of the carbon budget were not affected by the treatment with Bti. Second, laboratory microcosm (LMs) experiments that excluded environmental constraints were developed, to clarify the findings of the FPMs experiment. Out of the 15 microcosms, 3 were treated (each set) with standard Bti dose, 5 times standard Bti dose, chironomid larvae with low and high areal density, and control. The findings demonstrated that bioturbation increased CH4 and CO2 efflux and sediment oxygen (O2) consumption, while it did not affect the net production of CH4 and CO2. The negligible effect on net production rates in treatments with chironomids indicates that the increase in emissions rate was predominantly caused by bioturbation, which reduced the gas accumulation in the sediment. In the absence of chironomids, the application of any dose of Bti led to a three-fold higher net production rate of CH4 and CO2 (by up to 2.7 times than in control), due to the high addition of bioavailable carbon through the Bti excipients. However, the sole addition of carbon through the Bti excipients could not justify the high net production rate suggesting that the addition of Bti triggered a more robust carbon metabolism process. Both FPMs and LMs results suggested that the application of Bti may have functional implications on carbon biogeochemistry in affected aquatic systems beyond those mediated by changes in macroinvertebrate communities.
Index Insurance for Farmers
(2021)
In this thesis we focus on weather index insurance for agriculture risk. Even though such an index insurance is easily applicable and reduces information asymmetries, the demand for it is quite low. This is in particular due to the basis risk and the lack of knowledge about it’s effectiveness. The basis risk is the difference between the index insurance payout and the actual loss of the insured. We evaluate the performance of weather index insurance in different contexts, because proper knowledge about index insurance will help to use it as a successful alternative for traditional crop insurance. In addition to that, we also propose and discuss methods to reduce the basis risk.
We also analyze the performance of an agriculture loan which is interlinked with a weather index insurance. We show that an index insurance with actuarial fair or subsidized premium helps to reduce the loan default probability. While we first consider an index insurance with a commonly used linear payout function for this analysis, we later design an index insurance payout function which maximizes the expected utility of the insured. Then we show that, an index insurance with that optimal payout function is more appropriate for bundling with an agriculture loan. The optimal payout function also helps to reduce the basis risk. In addition, we show that a lender who issues agriculture loans can be better off by purchasing a weather index insurance in some circumstances.
We investigate the market equilibrium for weather index insurance by assuming risk averse farmers and a risk averse insurer. When we consider two groups of farmers with different risks, we show that the low risk group subsidizes the high risk group when both should pay the same premium for the index insurance. Further, according to the analysis of an index insurance in an informal risk sharing environment, we observe that the demand of the index insurance can be increased by selling it to a group of farmers who informally share the risk based on the insurance payout, because it reduces the adverse effect of the basis risk. Besides of that we analyze the combination of an index insurance with a gap insurance. Such a combination can increase the demand and reduce the basis risk of the index insurance if we choose the correct levels of premium and of gap insurance cover. Moreover our work shows that index insurance can be a good alternative to proportional and excess loss reinsurance when it is issued at a low enough price.
Multicore processors and Multiprocessor System-on-Chip (MPSoC) have become essential in Real-Time Systems (RTS) and Mixed-Criticality Systems (MCS) because of their additional computing capabilities that help reduce Size, Weight, and Power (SWaP), required wiring, and associated costs. In distributed systems, a single shared multicore or MPSoC node executes several applications, possibly of different criticality levels. However, there is interference between applications due to contention in shared resources such as CPU core, cache, memory, and network.
Existing allocation and scheduling methods for RTS and MCS often rely on implicit assumptions of the constant availability of individual resources, especially the CPU, to provide guaranteed progress of tasks. Most existing approaches aim to resolve contention in only a specific shared resource or a set of specific shared resources. Moreover, they handle a limited number of events such as task arrivals and task completions.
In distributed RTS and MCS with several nodes, each having multiple resources, if the applications, resource availability, or system configurations change, obtaining assumptions about resources becomes complicated. Thus, it is challenging to meet end-to-end constraints by considering each node, resource, or application individually.
Such RTS and MCS need global resource management to coordinate and dynamically adapt system-wide allocation of resources. In addition, the resource management can dynamically adapt applications to changing availability of resources and maintains a system-wide (global) view of resources and applications.
The overall aim of global resource management is twofold.
Firstly, it must ensure real-time applications meet their end-to-end deadlines even in the presence of faults and changing environmental conditions. Secondly, it must provide efficient resource utilization to improve the Quality of Service (QoS) of co-executing Best-Effort (BE) (or non-critical) applications.
A single fault in global resource management can render it useless. In the worst case, the resource management can make faulty decisions leading to a deadline miss in real-time applications. With the advent of Industry 4.0, cloud computing, and Internet-of-Things (IoT), it has become essential to combine stringent real-time constraints and reliability requirements with the need for an open-world assumption and ensure that the global resource management does not become an inviting target for attackers.
In this dissertation, we propose a domain-independent global resource management framework for distributed RTS and MCS consisting of heterogeneous nodes based on multicore processors or MPSoC. We initially developed the framework with the French Aerospace Lab -- ONERA and Thales Research & Technology during the DREAMS project and later extended it during SECREDAS and other internal projects. Unlike previous resource management frameworks RTS and MCS, we consider both safety and security for the framework itself.
To enable real-time industries to use cloud computing and enter a new market segment -- real-time operation as a cloud-based service, we propose a Real-Time-Cloud (RT-Cloud) based on global resource management for hosting RTS and MCS.
Finally, we present a mixed-criticality avionics use case for evaluating the capabilities of the global resource management framework in handling permanent core failures and temporal overload condition, and a railway use case to motivate the use of RT-Cloud with global resource management.
In this thesis, collision-induced dissociation (CID) studies serve to elucidate relative stabilities and to determine bond strengths within a given structure type of transition metal complexes. The infrared multi photon dissociation (IRMPD) spectroscopy combined with density functional theory (DFT) allow for structural analysis and provide insights into the coordination sphere of transition metal centers. The used combination of CID and IRMPD experiments is a powerful tool to obtain a detailed and comprehensive characterization and understanding of interactions between transition metals and organic ligands. The compounds’ spectrum comprises mono- or oligonuclear transition metal complexes containing iron, palladium, and ruthenium as well as lanthanide containing single molecule magnets (SMM). The presented investigations on the different transition metal complexes reveal manifold effects for each species leading to valuable results. A fundamental understanding of metal to ligand interactions is mandatory for the development of new and better organometallic complexes with catalytic, optical or magnetic properties.
In computer graphics, realistic rendering of virtual scenes is a computationally complex problem. State-of-the-art rendering technology must become more scalable to
meet the performance requirements for demanding real-time applications.
This dissertation is concerned with core algorithms for rendering, focusing on the
ray tracing method in particular, to support and saturate recent massively parallel computer systems, i.e., to distribute the complex computations very efficiently
among a large number of processing elements. More specifically, the three targeted
main contributions are:
1. Collaboration framework for large-scale distributed memory computers
The purpose of the collaboration framework is to enable scalable rendering
in real-time on a distributed memory computer. As an infrastructure layer it
manages the explicit communication within a network of distributed memory
nodes transparently for the rendering application. The research is focused on
designing a communication protocol resilient against delays and negligible in
overhead, relying exclusively on one-sided and asynchronous data transfers.
The hypothesis is that a loosely coupled system like this is able to scale linearly
with the number of nodes, which is tested by directly measuring all possible
communication-induced delays as well as the overall rendering throughput.
2. Ray tracing algorithms designed for vector processing
Vector processors are to be efficiently utilized for improved ray tracing performance. This requires the basic, scalar traversal algorithm to be reformulated
in order to expose a high degree of fine-grained data parallelism. Two approaches are investigated: traversing multiple rays simultaneously, and performing
multiple traversal steps at once. Efficiently establishing coherence in a group
of rays as well as avoiding sorting of the nodes in a multi-traversal step are the
defining research goals.
3. Multi-threaded schedule and memory management for the ray tracing acceleration structure
Construction times of high-quality acceleration structures are to be reduced by
improvements to multi-threaded scalability and utilization of vector processors. Research is directed at eliminating the following scalability bottlenecks:
dynamic memory growth caused by the primitive splits required for high-
quality structures, and top-level hierarchy construction where simple task par-
allelism is not readily available. Additional research addresses how to expose
scatter/gather-free data-parallelism for efficient vector processing.
Together, these contributions form a scalable, high-performance basis for real-time,
ray tracing-based rendering, and a prototype path tracing application implemented
on top of this basis serves as a demonstration.
The key insight driving this dissertation is that the computational power necessary
for realistic light transport for real-time rendering applications demands massively
parallel computers, which in turn require highly scalable algorithms. Therefore this
dissertation provides important research along the path towards virtual reality.
Destructive diseases of the lung like lung cancer or fibrosis are still often lethal. Also in case of fibrosis in the liver, the only possible cure is transplantation.
In this thesis, we investigate 3D micro computed synchrotron radiation (SR\( \mu \)CT) images of capillary blood vessels in mouse lungs and livers. The specimen show so-called compensatory lung growth as well as different states of pulmonary and hepatic fibrosis.
During compensatory lung growth, after resecting part of the lung, the remaining part compensates for this loss by extending into the empty space. This process is accompanied by an active vessel growing.
In general, the human lung can not compensate for such a loss. Thus, understanding this process in mice is important to improve treatment options in case of diseases like lung cancer.
In case of fibrosis, the formation of scars within the organ's tissue forces the capillary vessels to grow to ensure blood supply.
Thus, the process of fibrosis as well as compensatory lung growth can be accessed by considering the capillary architecture.
As preparation of 2D microscopic images is faster, easier, and cheaper compared to SR\( \mu \)CT images, they currently form the basis of medical investigation. Yet, characteristics like direction and shape of objects can only properly be analyzed using 3D imaging techniques. Hence, analyzing SR\( \mu \)CT data provides valuable additional information.
For the fibrotic specimen, we apply image analysis methods well-known from material science. We measure the vessel diameter using the granulometry distribution function and describe the inter-vessel distance by the spherical contact distribution. Moreover, we estimate the directional distribution of the capillary structure. All features turn out to be useful to characterize fibrosis based on the deformation of capillary vessels.
It is already known that the most efficient mechanism of vessel growing forms small torus-shaped holes within the capillary structure, so-called intussusceptive pillars. Analyzing their location and number strongly contributes to the characterization of vessel growing. Hence, for all three applications, this is of great interest. This thesis provides the first algorithm to detect intussusceptive pillars in SR\( \mu \)CT images. After segmentation of raw image data, our algorithm works automatically and allows for a quantitative evaluation of a large amount of data.
The analysis of SR\( \mu \)CT data using our pillar algorithm as well as the granulometry, spherical contact distribution, and directional analysis extends the current state-of-the-art in medical studies. Although it is not possible to replace certain 3D features by 2D features without losing information, our results could be used to examine 2D features approximating the 3D findings reasonably well.
In this thesis we develop a shape optimization framework for isogeometric analysis in the optimize first–discretize then setting. For the discretization we use
isogeometric analysis (iga) to solve the state equation, and search optimal designs in a space of admissible b-spline or nurbs combinations. Thus a quite
general class of functions for representing optimal shapes is available. For the
gradient-descent method, the shape derivatives indicate both stopping criteria and search directions and are determined isogeometrically. The numerical treatment requires solvers for partial differential equations and optimization methods, which introduces numerical errors. The tight connection between iga and geometry representation offers new ways of refining the geometry and analysis discretization by the same means. Therefore, our main concern is to develop the optimize first framework for isogeometric shape optimization as ground work for both implementation and an error analysis. Numerical examples show that this ansatz is practical and case studies indicate that it allows local refinement.
To improve efficiency of memory accesses, modern multiprocessor architectures implement a whole range of different weak memory models. The behavior of performance-critical code depends on the underlying hardware. There is a rising demand for verification tools that take the underlying memory model into account. This work examines a variety of prevalent problems in the field of program verification of increasing complexities: testing, reachability, portability and memory model synthesis.
We give efficient tools to solve these problems. What sets the presented methods apart is that they are not limited to some few given architectures. They are universal: The memory model is given as part of the input. We make use of the CAT language to succinctly describe axiomatic memory models. CAT has been used to define the semantics of assembly for x86/TSO, ARMv7, ARMv8, and POWER but also the semantics of programming languages such as C/C++, including the Linux kernel concurrency primitives.
This work shows that even the simple testing problem is NP-hard for most memory models. It does so using a general reduction technique that applies to a range of models. It examines the more difficult program verification under a memory model and introduces Dartagnan, a bounded model checker (BMC) that encodes the problem as an SMT-query and makes use of advanced encoding techniques. The program portability problem is shown to be even harder. Despite this, it is solved efficiently by the tool Porthos which uses a guided search to produce fast results for most practical instances. A memory model is synthesized by Aramis for a given set of reachability results. Concurrent program verification is generally undecidable even for sequential consistency. As an alternative to BMC, we propose a new CEGAR method for Petri net invariant synthesis. We again use SMT-queries as a back-end.
Human interferences within the Earth System are accelerating, leading to major impacts and feedback that we are just beginning to understand. Summarized under the term 'global change' these impacts put human and natural systems under ever-increasing stress and impose a threat to human well-being, particularly in the Global South. Global governance bodies have acknowledged that decisive measures have to be taken to mitigate the causes and to adapt to these new conditions. Nevertheless, neither current international nor national pledges and measures reach the effectiveness needed to sustain global human well-being under accelerating global change. On the contrary, competing interests are not only paralyzing the international debate but also playing an increasingly important role in debates over social fragmentation and societal polarization on national and local scales. This interconnectedness of the natural and the social system and its impact on social phenomena such as cooperation and conflicts need to be understood better, to strengthen social resilience to future disturbances, drive societal transformation towards socially desirable futures while at the same time avoiding path dependencies along continuing colonial continuities. As a case example, this thesis provides insights into southwestern Amazonia, where the intertwined challenges of human contribution to global change in all its dimensions, as well as human adaptation and mitigation attempts to the imposed changes become exaggeratedly visible. As such, southwestern Amazonia with its high social, economic, and biological diversity is a good example to study the deep interrelations of humans with nature and the consequences these relations have on social cohesion amid an ecological crisis.
Therefore, this thesis takes a social-ecological perspective on conflicts and social cohesion. Social cohesion is in a wider sense understood as the way "how members of a society, group, or organization relate to each other and work together" (Dany and Dijkzeul 2022, p. 12). In particular in contexts of violence, conflicts, and fragility, little has been investigated on the role of social cohesion to govern public goods and build resilience for (future) environmental crises. At the same time, governments and international decision-makers more and more acknowledge the role of social cohesion _ comprising both relations between social groups and between groups and the state _ to build upon resilience against crises. Facing uncertainty in how natural and social systems react to certain disturbances and shocks, the governance of potential tipping points, is an additional challenge for the governance of social-ecological systems (SES). Therefore, this thesis asks: "How does governance shape pathways towards cooperative or conflictive social-ecological tipping points?" The results of this thesis can be distinguished into theoretical/conceptual results and empirical results. Initial systematic literature research on the nexus of climate change, land use, and conflict revealed, an extensive body of literature on direct effects, for example, drought-related land use conflicts, with diverging opinions on whether global warming increases the risk for conflicts or not. Adding the perspective of indirect implications, we further identified research gaps, and also a lack of policy recognition, concerning the negative externalities on land use and conflict through climate mitigation and adaptation measures. On a conceptual note, taking a social cohesion perspective into the analysis is beneficial to shift the focus from the problem-oriented perspective of vulnerabilities and conflicts to global change and potential resulting conflicts to a solution-oriented perspective of enhancing agency and resilience to strengthen collaboration. The developed Social Cohesion Conceptual Model and the related analytical framework facilitate the incorporation of societal dynamics into the analysis of SES dynamics. In addition, the elaborated Tipping Multiverse Framework took up this idea and enhanced it with a more detailed perspective on the soil ecosystem and the household livelihood system to identify entry points to potential social-ecological tipping cascades. As such, the Tipping Multiverse Framework offered two matrices that can advance the understanding of regional SES by identifying core processes, functioning, and links in each TE and thus provide entry points to identify potential tipping cascades across SES sub-systems. The exemplified application of these two frameworks on southwestern Amazonia shows the analytical potential of both proposed frameworks in advancing the understanding of social-ecological tipping points and potential tipping cascades in a regional SES.
On an empirical note, zooming in on questions of governance by applying a political ecology lens to human security, we find that 'glocal' resource governance often reproduces, amplifies, or creates power imbalances and divisions on and between different scales. Our results show that the winners of resource extraction are mostly found at the national and international scale while local communities receive little benefit and are left vulnerable to externalities. Hence, our study contributes to the existing research by stressing the importance of one underlying question: "governance by whom and for whom?" This question raised the demand to understand the underlying dynamics of resource governance and resulting conflicts. Therefore, we aimed at analyzing how (environmental) institutions influence the major drivers of social-ecological conflicts over land in and around three protected areas, Tambopata (Peru), the Extractive Reserve Chico Mendes (Brazil), and Manuripi (Bolivia). We found that state institutions, in particular, have the following effects on key conflict drivers: Overlapping responsibilities of governance institutions and limited enforcement of regulations protecting and empowering rural and disadvantaged populations, enabling external actors to (illegally) access and control resources in the protected areas. Consequently, the already fragile social contract between the residents of the protected area and its surrounding areas and the central state is further weakened by the expanding influence of criminal organizations that oppose the state's authority. For state institutions to avoid aggravating these conflict drivers but instead better manage them or even contribute to conflict prevention and mitigation, a transformation from reactive to reflexive institutions and the development of new reflexive governance competencies is needed.
This need for reflexive governance becomes particularly visible when sudden disturbances or shocks impact the SES. Our analysis of the impacts of the COVID-19 pandemic on the interconnections of land use change, ecosystem services, human agency, conflict, and cooperation that the pandemic has had a severe influence on the human security of marginalized social groups in southwestern Amazonia. Civil society actions have been an essential strategy in the fight against COVID-19, not just in the health sector but also in the economic, political, social, and cultural realms. However, our research also showed that the pandemic has consolidated and partly renewed criminal structures, while the already weak state has fallen further behind due to additional tasks managing the pandemic and other disasters such as floods.
In conclusion, it can be said that the reflexivity of governance is crucial to foster cooperation and preventing conflicts in the realm of social-ecological systems. By not only reacting to already occurring changes but also reflecting upon potential future changes, governance can shape transformation pathways away from the detrimental and towards life-sustaining pathways. It can do so, by exercising agency across scales to avoid the crossing of detrimental social-ecological tipping points but rather to trigger life-sustaining tipping points that contribute to global social-ecological well-being.
The present thesis reports on studies of atomically precise, size-selected tantalum
cluster ions \(Ta_n^±\) under cryogenic conditions in a FT-ICR mass spectrometer with respect to surface adsorbate interactions at the fundamental level, focusing on \(N_2\) and \(H_2\) adsorption and activation. The wealth of results presented here is the result of systematic studies that have revealed valuable kinetic, spectroscopic, and quantum chemical information, which together paint a comprehensive picture of the elementary adsorption steps and mechanisms in detail.
The \(N_2\) and \(H_2\) adsorption processes to \(Ta_n^+\) clusters exhibit dependencies on cluster size n and on adsorbate load. In terms of \(N_2\) adsorption, there is evidence for spontaneous \(N_2\) activation and cleavage by \(Ta_2^+\) - \(Ta_4^+\), while it appears to be suppressedby \(Ta_5^+\) - \(Ta_8^+\). The activation and cleavage of \(N_2\) molecules proceeds across
surmountable barriers and along much-involved multidimensional reaction paths.
Underlying reaction processes and involved intermediates are elucidated. Two different processes are characteristic of \(H_2\) adsorption: There are fast adsoprtion processes without competing desorption reactions at low \(H_2\) loadings, indicating dissociative adsorption processes, followed by slow adsorption reactions accompanied by multiple desorption reactions at high \(H_2\) loadings, indicating molecular \(H_2\) adsorption. The threshold is the completion of the first adsorbate shell. The \(N_2\) adsorption study of \(Ta_n^-\) clusters revealed that the \(N_2\) adsorption ability of anionic tantalum clusters depends strongly on cluster size n. The cluster size n = 9 is the minimum size for \(N_2\) adsorption onto \(Ta_n^-\) clusters to yield stable and detectable cluster adsorbate species \([Ta_n(N_2)_m]^-\).