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Noise is ubiquitous in nature and usually results in rich dynamics in stochastic systems such as oscillatory systems, which exist in such various fields as physics, biology and complex networks. The correlation and synchronization of two or many oscillators are widely studied topics in recent years.
In this thesis, we mainly investigate two problems, i.e., the stochastic bursting phenomenon in noisy excitable systems and synchronization in a three-dimensional Kuramoto model with noise. Stochastic bursting here refers to a sequence of coherent spike train, where each spike has random number of followers due to the combined effects of both time delay and noise. Synchronization, as a universal phenomenon in nonlinear dynamical systems, is well illustrated in the Kuramoto model, a prominent model in the description of collective motion.
In the first part of this thesis, an idealized point process, valid if the characteristic timescales in the problem are well separated, is used to describe statistical properties such as the power spectral density and the interspike interval distribution. We show how the main parameters of the point process, the spontaneous excitation rate, and the probability to induce a spike during the delay action can be calculated from the solutions of a stationary and a forced Fokker-Planck equation. We extend it to the delay-coupled case and derive analytically the statistics of the spikes in each neuron, the pairwise correlations between any two neurons, and the spectrum of the total output from the network.
In the second part, we investigate the three-dimensional noisy Kuramoto model, which can be used to describe the synchronization in a swarming model with helical trajectory. In the case without natural frequency, the Kuramoto model can be connected with the Vicsek model, which is widely studied in collective motion and swarming of active matter. We analyze the linear stability of the incoherent state and derive the critical coupling strength above which the incoherent state loses stability. In the limit of no natural frequency, an exact self-consistent equation of the mean field is derived and extended straightforward to any high-dimensional case.
This thesis focuses on the synthesis of novel functional materials based on plasmonic nanoparticles. Three systems with targeted surface modification and functionalization have been designed and synthesized, involving modified perylenediimide doped silica-coated silver nanowires, polydopamine or TiO2 coated gold-palladium nanorods and thiolated poly(ethylene glycol) (PEG-SH)/dodecanethiol (DDT) modified silver nanospheres. Their possible applications as plasmonic resonators, chiral sensors as well as photo-catalysts have been studied. In addition, the interaction between silver nanospheres and 2,3,5,6-Tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4TCNQ) molecules has also been investigated in detail.
In the first part of the thesis, surface modification on Ag nanowires (NWs) with optimized silica coating through a modified Stöber method has been firstly conducted, employing sodium hydroxide (NaOH) to replace ammonia solution (NH4OH). The coated silver nanowires with a smooth silica shell have been investigated by single-particle dark-field scattering spectroscopy, transmission electron microscopy and electron-energy loss spectroscopy to characterize the morphologies and structural components. The silica-coated silver nanowires can be further functionalized with fluorescent molecules in the silica shell via a facile one-step coating method. The as-synthesized nanowire is further coupled with a gold nanosphere by spin-coating for the application of the sub-diffractional chiral sensor for the first time. The exciton-plasmon-photon interconversion in the system eases the signal detection in the perfectly matched 1D nanostructure and contributes to the high contrast of the subwavelength chiral sensing for the polarized light.
In the second part of the thesis, dumbbell-shaped Au-Pd nanorods coated with a layer of polydopamine (PDA) or titanium dioxide (TiO2) have been constructed. The PDA- and TiO2- coated Au-Pd nanorods show a strong photothermal conversion performance under NIR illumination. Moreover, the catalytic performance of the particles has been investigated using the reduction of 4-nitrophenol (4-NP) as the model reaction. Under light irradiation, the PDA-coated Au-Pd nanorods exhibit a superior catalytic activity by increasing the reaction rate constant of 3 times. The Arrhenius-like behavior of the reaction with similar activation energies in the presence and absence of light irradiation indicates the photoheating effect to be the dominant mechanism of the reaction acceleration. Thus, we attribute the enhanced performance of the catalysis to the strong photothermal effect that is driven by the optical excitation of the gold surface plasmon as well as the synergy with the PDA layer.
In the third part, the kinetic study on the adsorption of 2,3,5,6-Tetrafluoro-7,7,8,8-tetracyanoquino-dimethane (F4TCNQ) on the surface of Ag nanoparticles (Ag NPs) in chloroform has been reported in detail. Based on the results obtained from the UV-vis-NIR absorption spectroscopy, cryogenic transmission electron microscopy (cryo-TEM), scanning nano-beam electron diffraction (NBED) and electron energy loss spectroscopy (EELS), a two-step interaction kinetics has been proposed for the Ag NPs and F4TCNQ molecules. It includes the first step of electron transfer from Ag NPs to F4TCNQ indicated by the ionization of F4TCNQ, and the second step of the formation of Ag-F4TCNQ complex. The whole process has been followed via UV-vis-NIR absorption spectroscopy, which reveals distinct kinetics at two stages: the instantaneous ionization and the long-term complex formation. The kinetics and the influence of the molar ratio of Ag NPs/F4TCNQ molecules on the interaction between Ag NPs and F4TCNQ molecules in the organic solution are reported herein for the first time. Furthermore, the control experiment with silica-coated Ag NPs indicates that the charge transfer at the surface between Ag NPs and F4TCNQ molecules has been prohibited by a silica layer of 18 nm.
The galactic interstellar medium is magnetized and turbulent. The magnetic field and turbulence play important roles in many astrophysical mechanisms, including cosmic ray transport, star formation, etc. Therefore, measurements of magnetic field and turbulence information are crucial for the proper interpretation of astronomical observations. Nonetheless, the magnetic field observation is quite challenging, especially, there is not universal magnetic tracer for diffuse medium. Moreover, the modelling of turbulence can be oversimplified due to the lack of observational tools to diagnose the plasma properties of the turbulence in the galactic interstellar medium. The studies presented in this thesis have addressed these challenges by bridging the theoretical studies of magnetic field and turbulence with numerical simulations and observations.
The following research are presented in this thesis. The first observational evidence of the novel magnetic tracer, ground state alignment (GSA), is discovered, revealing the three-dimensional magnetic field as well as 2 orders of magnitude higher precision comparing to previous observational study in the stellar atmosphere of the post-AGB 89 Herculis. Moreover, the application of GSA in the sub-millimeter fine-structure lines is comprehensively studied for different elements and with magnetohydrodynamic simulations. Furthermore, the influence of GSA effect on the spectroscopy is analyzed and it is found that measurable variation will be produced on the spectral line intensity and the line ratio without accounting for the optical pumping process or magnetic field.
Additionally, a novel method to measure plasma modes in the interstellar medium, Signatures from Polarization Analysis (SPA), is proposed and applied to real observations. Magneto-sonic modes are discovered in different types of interstellar medium. An explanation is provided for the long-standing mystery, the origin of γ-ray enhanced emission “Cygnus Cocoon”, based on the comparison between the outcome of SPA and multi-waveband observational data. These novel methods have strong potentials for broader observational applications and will play crucial roles in future multi-wavelength astronomy.
This thesis focuses on the study of marked Gibbs point processes, in particular presenting some results on their existence and uniqueness, with ideas and techniques drawn from different areas of statistical mechanics: the entropy method from large deviations theory, cluster expansion and the Kirkwood--Salsburg equations, the Dobrushin contraction principle and disagreement percolation.
We first present an existence result for infinite-volume marked Gibbs point processes. More precisely, we use the so-called entropy method (and large-deviation tools) to construct marked Gibbs point processes in R^d under quite general assumptions. In particular, the random marks belong to a general normed space S and are not bounded. Moreover, we allow for interaction functionals that may be unbounded and whose range is finite but random. The entropy method relies on showing that a family of finite-volume Gibbs point processes belongs to sequentially compact entropy level sets, and is therefore tight.
We then present infinite-dimensional Langevin diffusions, that we put in interaction via a Gibbsian description. In this setting, we are able to adapt the general result above to show the existence of the associated infinite-volume measure. We also study its correlation functions via cluster expansion techniques, and obtain the uniqueness of the Gibbs process for all inverse temperatures β and activities z below a certain threshold. This method relies in first showing that the correlation functions of the process satisfy a so-called Ruelle bound, and then using it to solve a fixed point problem in an appropriate Banach space. The uniqueness domain we obtain consists then of the model parameters z and β for which such a problem has exactly one solution.
Finally, we explore further the question of uniqueness of infinite-volume Gibbs point processes on R^d, in the unmarked setting. We present, in the context of repulsive interactions with a hard-core component, a novel approach to uniqueness by applying the discrete Dobrushin criterion to the continuum framework. We first fix a discretisation parameter a>0 and then study the behaviour of the uniqueness domain as a goes to 0. With this technique we are able to obtain explicit thresholds for the parameters z and β, which we then compare to existing results coming from the different methods of cluster expansion and disagreement percolation.
Throughout this thesis, we illustrate our theoretical results with various examples both from classical statistical mechanics and stochastic geometry.
Contributions to the theoretical analysis of the algorithms with adversarial and dependent data
(2021)
In this work I present the concentration inequalities of Bernstein's type for the norms of Banach-valued random sums under a general functional weak-dependency assumption (the so-called $\cC-$mixing). The latter is then used to prove, in the asymptotic framework, excess risk upper bounds of the regularised Hilbert valued statistical learning rules under the τ-mixing assumption on the underlying training sample. These results (of the batch statistical setting) are then supplemented with the regret analysis over the classes of Sobolev balls of the type of kernel ridge regression algorithm in the setting of online nonparametric regression with arbitrary data sequences. Here, in particular, a question of robustness of the kernel-based forecaster is investigated. Afterwards, in the framework of sequential learning, the multi-armed bandit problem under $\cC-$mixing assumption on the arm's outputs is considered and the complete regret analysis of a version of Improved UCB algorithm is given. Lastly, probabilistic inequalities of the first part are extended to the case of deviations (both of Azuma-Hoeffding's and of Burkholder's type) to the partial sums of real-valued weakly dependent random fields (under the type of projective dependence condition).
Shape-Memory effects of thermoplatic multiblock copolymers with overlapping thermal transitions
(2021)
With ongoing anthropogenic global warming, some of the most vulnerable components of the Earth system might become unstable and undergo a critical transition. These subsystems are the so-called tipping elements. They are believed to exhibit threshold behaviour and would, if triggered, result in severe consequences for the biosphere and human societies. Furthermore, it has been shown that climate tipping elements are not isolated entities, but interact across the entire Earth system. Therefore, this thesis aims at mapping out the potential for tipping events and feedbacks in the Earth system mainly by the use of complex dynamical systems and network science approaches, but partially also by more detailed process-based models of the Earth system.
In the first part of this thesis, the theoretical foundations are laid by the investigation of networks of interacting tipping elements. For this purpose, the conditions for the emergence of global cascades are analysed against the structure of paradigmatic network types such as Erdös-Rényi, Barabási-Albert, Watts-Strogatz and explicitly spatially embedded networks. Furthermore, micro-scale structures are detected that are decisive for the transition of local to global cascades. These so-called motifs link the micro- to the macro-scale in the network of tipping elements. Alongside a model description paper, all these results are entered into the Python software package PyCascades, which is publicly available on github.
In the second part of this dissertation, the tipping element framework is first applied to components of the Earth system such as the cryosphere and to parts of the biosphere. Afterwards it is applied to a set of interacting climate tipping elements on a global scale. Using the Earth system Model of Intermediate Complexity (EMIC) CLIMBER-2, the temperature feedbacks are quantified, which would arise if some of the large cryosphere elements disintegrate over a long span of time. The cryosphere components that are investigated are the Arctic summer sea ice, the mountain glaciers, the Greenland and the West Antarctic Ice Sheets. The committed temperature increase, in case the ice masses disintegrate, is on the order of an additional half a degree on a global average (0.39-0.46 °C), while local to regional additional temperature increases can exceed 5 °C. This means that, once tipping has begun, additional reinforcing feedbacks are able to increase global warming and with that the risk of further tipping events.
This is also the case in the Amazon rainforest, whose parts are dependent on each other via the so-called moisture-recycling feedback. In this thesis, the importance of drought-induced tipping events in the Amazon rainforest is investigated in detail. Despite the Amazon rainforest is assumed to be adapted to past environmental conditions, it is found that tipping events sharply increase if the drought conditions become too intense in a too short amount of time, outpacing the adaptive capacity of the Amazon rainforest. In these cases, the frequency of tipping cascades also increases to 50% (or above) of all tipping events. In the model that was developed in this study, the southeastern region of the Amazon basin is hit hardest by the simulated drought patterns. This is also the region that already nowadays suffers a lot from extensive human-induced changes due to large-scale deforestation, cattle ranching or infrastructure projects.
Moreover, on the larger Earth system wide scale, a network of conceptualised climate tipping elements is constructed in this dissertation making use of a large literature review, expert knowledge and topological properties of the tipping elements. In global warming scenarios, tipping cascades are detected even under modest scenarios of climate change, limiting global warming to 2 °C above pre-industrial levels. In addition, the structural roles of the climate tipping elements in the network are revealed. While the large ice sheets on Greenland and Antarctica are the initiators of tipping cascades, the Atlantic Meridional Overturning Circulation (AMOC) acts as the transmitter of cascades. Furthermore, in our conceptual climate tipping element model, it is found that the ice sheets are of particular importance for the stability of the entire system of investigated climate tipping elements.
In the last part of this thesis, the results from the temperature feedback study with the EMIC CLIMBER-2 are combined with the conceptual model of climate tipping elements. There, it is observed that the likelihood of further tipping events slightly increases due to the temperature feedbacks even if no further CO$_2$ would be added to the atmosphere.
Although the developed network model is of conceptual nature, it is possible with this work for the first time to quantify the risk of tipping events between interacting components of the Earth system under global warming scenarios, by allowing for dynamic temperature feedbacks at the same time.
3D point clouds are a universal and discrete digital representation of three-dimensional objects and environments. For geospatial applications, 3D point clouds have become a fundamental type of raw data acquired and generated using various methods and techniques. In particular, 3D point clouds serve as raw data for creating digital twins of the built environment.
This thesis concentrates on the research and development of concepts, methods, and techniques for preprocessing, semantically enriching, analyzing, and visualizing 3D point clouds for applications around transport infrastructure. It introduces a collection of preprocessing techniques that aim to harmonize raw 3D point cloud data, such as point density reduction and scan profile detection. Metrics such as, e.g., local density, verticality, and planarity are calculated for later use. One of the key contributions tackles the problem of analyzing and deriving semantic information in 3D point clouds. Three different approaches are investigated: a geometric analysis, a machine learning approach operating on synthetically generated 2D images, and a machine learning approach operating on 3D point clouds without intermediate representation.
In the first application case, 2D image classification is applied and evaluated for mobile mapping data focusing on road networks to derive road marking vector data. The second application case investigates how 3D point clouds can be merged with ground-penetrating radar data for a combined visualization and to automatically identify atypical areas in the data. For example, the approach detects pavement regions with developing potholes. The third application case explores the combination of a 3D environment based on 3D point clouds with panoramic imagery to improve visual representation and the detection of 3D objects such as traffic signs.
The presented methods were implemented and tested based on software frameworks for 3D point clouds and 3D visualization. In particular, modules for metric computation, classification procedures, and visualization techniques were integrated into a modular pipeline-based C++ research framework for geospatial data processing, extended by Python machine learning scripts. All visualization and analysis techniques scale to large real-world datasets such as road networks of entire cities or railroad networks.
The thesis shows that some use cases allow taking advantage of established image vision methods to analyze images rendered from mobile mapping data efficiently. The two presented semantic classification methods working directly on 3D point clouds are use case independent and show similar overall accuracy when compared to each other. While the geometry-based method requires less computation time, the machine learning-based method supports arbitrary semantic classes but requires training the network with ground truth data. Both methods can be used in combination to gradually build this ground truth with manual corrections via a respective annotation tool.
This thesis contributes results for IT system engineering of applications, systems, and services that require spatial digital twins of transport infrastructure such as road networks and railroad networks based on 3D point clouds as raw data. It demonstrates the feasibility of fully automated data flows that map captured 3D point clouds to semantically classified models. This provides a key component for seamlessly integrated spatial digital twins in IT solutions that require up-to-date, object-based, and semantically enriched information about the built environment.
The scapula plays a significant role in efficient shoulder movement. Thus, alterations from typical scapular motion during upper limb movements are thought to be associated with shoulder pathologies. However, a clear understanding of the relationship is not yet obtained.. Scapular alterations may only represent physiological variability as their occurrence can appear equally as frequent in individuals with and without shoulder disorders. Evaluation of scapular motion during increased load might be a beneficial approach to detect clinically relevant alterations. However, functional motion adaptations in response to maximum effort upper extremity loading has not been established yet. Therefore, the overall purpose of this research project was to give further insight in physiological adaptations of scapular kinematics and their underlying scapular muscle activity in response to high demanding shoulder movements in healthy asymptomatic individuals. Prior to the investigation of the effect of various load situation, the reproducibility of scapular kinematics and scapular muscle activity were evaluated under maximum effort arm movements. Healthy asymptomatic adults performed unloaded and maximal loaded concentric and eccentric isokinetic shoulder flexion and extension movements in the scapular plane while scapular kinematics and scapular muscle activity were simultaneously assessed. A 3D motion capture system (infra-red cameras & reflective markers) was utilized to track scapular and humerus motion in relation to the thorax. 3D scapular position angles were given for arm raising and lowering between humerus positions of 20° and 120° flexion. To further characterize the scapular pattern, the scapular motion extent and scapulohumeral rhythm (ratio of scapular and humerus motion extent) were determined. Muscle activity of the upper and lower trapezius and the serratus anterior were assessed with surface electromyography. Amplitudes were calculated for the whole ROM and four equidistant movement phases. Reliability was characterized by overall moderate to good reproducibility across the load conditions. Irrespective of applied load, scapular kinematics followed a motion pattern of continuous upward rotation, posterior tilt and external rotation during arm elevation and a continuous downward rotation, anterior tilt and internal rotation during arm lowering. However, kinematics were altered between maximal loaded and unloaded conditions showing increased upward rotation, reduced posterior tilt and external rotation. Further, the scapulohumeral rhythm was decreased and scapular motion extent increased under maximal loaded movements. Muscle activity during maximum effort were of greater magnitude and differed in their pattern in comparison to the continuous increase and decrease of activity during unloaded shoulder flexion and extension. Relationships between scapular kinematics and their underlying scapular muscle activity could only be identified for a few isolated combinations, whereas the majority showed no associations. Scapular kinematics and scapular muscle activity pattern alter according to the applied load. Alterations between the load conditions comply in magnitude and partially in direction with differences seen between symptomatic and asymptomatic individuals. Even though long-term effects of identified adaptations in response to maximum load are so far unclear, deviations from typical scapular motion or muscle activation should not per se be seen as indicators of shoulder impairment. However, evaluation of alterations in scapular motion and activation in response to maximum effort may have the potential to identify individuals that are unable to cope with increased upper limb demands. Findings further challenge the understanding of scapular motion and stabilization by the trapezius and serratus anterior muscles, as clear relationships between the underlying scapular muscle activity and scapular kinematics were neither observed during unloaded nor maximal loaded shoulder movements.
Supernova remnants (SNRs) are discussed as the most promising sources of galactic cosmic rays (CR). The diffusive shock acceleration (DSA) theory predicts particle spectra in a rough agreement with observations. Upon closer inspection, however, the photon spectra of observed SNRs indicate that the particle spectra produced at SNRs shocks deviate from the standard expectation. This work suggests a viable explanation for a softening of the particle spectra in SNRs. The basic idea is the re-acceleration of particles in the turbulent region immediately downstream of the shock. This thesis shows that at the re-acceleration of particles by the fast-mode waves in the downstream region can be efficient enough to impact particle spectra over several decades in energy. To demonstrate this, a generic SNR model is presented, where the evolution of particles is described by the reduced transport equation for CR. It is shown that the resulting particle and the corresponding synchrotron spectra are significantly softer compared to the standard case. Next, this work outlines RATPaC, a code developed to model particle acceleration and corresponding photon emissions in SNRs. RATPaC solves the particle transport equation in test-particle mode using hydrodynamic simulations of the SNR plasma flow. The background magnetic field can be either computed from the induction equation or follows analytic profiles. This work presents an extended version of RATPaC that accounts for stochastic re-acceleration by fast-mode waves that provide diffusion of particles in momentum space. This version is then applied to model the young historical SNR Tycho. According to radio observations, Tycho’s SNR features the radio spectral index of approximately −0.65. In previous modeling approaches, this fact has been attributed to the strongly distinctive Alfvénic drift, which is assumed to operate in the shock vicinity. In this work, the problems and inconsistencies of this scenario are discussed. Instead, stochastic re-acceleration of electrons in the immediate downstream region of Tycho’s SNR is suggested as a cause for the soft radio spectrum. Furthermore, this work investigates two different scenarios for magnetic-field distributions inside Tycho’s SNR. It is concluded that magnetic-field damping is needed to account for the observed filaments in the radio range. Two models are presented for Tycho’s SNR, both of them feature strong hadronic contribution. Thus, a purely leptonic model is considered as very unlikely. Additionally, to the detailed modeling of Tycho’s SNR, this dissertation presents a relatively simple one-zone model for the young SNR Cassiopeia A and an interpretation for the recently analyzed VERITAS and Fermi-LAT data. It shows that the γ-ray emission of Cassiopeia A cannot be explained without a hadronic contribution and that the remnant accelerates protons up to TeV energies. Thus, Cassiopeia A is found to be unlikely a PeVatron.
Geochemical processes such as mineral dissolution and precipitation alter the microstructure of rocks, and thereby affect their hydraulic and mechanical behaviour. Quantifying these property changes and considering them in reservoir simulations is essential for a sustainable utilisation of the geological subsurface. Due to the lack of alternatives, analytical methods and empirical relations are currently applied to estimate evolving hydraulic and mechanical rock properties associated with chemical reactions. However, the predictive capabilities of analytical approaches remain limited, since they assume idealised microstructures, and thus are not able to reflect property evolution for dynamic processes. Hence, aim of the present thesis is to improve the prediction of permeability and stiffness changes resulting from pore space alterations of reservoir sandstones.
A detailed representation of rock microstructure, including the morphology and connectivity of pores, is essential to accurately determine physical rock properties. For that purpose, three-dimensional pore-scale models of typical reservoir sandstones, obtained from highly resolved micro-computed tomography (micro-CT), are used to numerically calculate permeability and stiffness. In order to adequately depict characteristic distributions of secondary minerals, the virtual samples are systematically altered and resulting trends among the geometric, hydraulic, and mechanical rock properties are quantified. It is demonstrated that the geochemical reaction regime controls the location of mineral precipitation within the pore space, and thereby crucially affects the permeability evolution. This emphasises the requirement of determining distinctive porosity-permeability relationships
by means of digital pore-scale models. By contrast, a substantial impact of spatial alterations patterns on the stiffness evolution of reservoir sandstones are only observed in case of certain microstructures, such as highly porous granular rocks or sandstones comprising framework-supporting cementations. In order to construct synthetic granular samples a process-based approach is proposed including grain deposition and diagenetic cementation. It is demonstrated that the generated samples reliably represent the microstructural complexity of natural sandstones. Thereby, general limitations of imaging techniques can be overcome and various realisations of granular rocks can be flexibly produced. These can be further altered by virtual experiments, offering a fast and cost-effective way to examine the impact of precipitation, dissolution or fracturing on various petrophysical correlations.
The presented research work provides methodological principles to quantify trends in permeability and stiffness resulting from geochemical processes. The calculated physical property relations are directly linked to pore-scale alterations, and thus have a higher accuracy than commonly applied analytical approaches. This will considerably improve the predictive capabilities of reservoir models, and is further relevant to assess and reduce potential risks, such as productivity or injectivity losses as well as reservoir compaction or fault reactivation. Hence, the proposed method is of paramount importance for a wide range of natural and engineered subsurface applications, including geothermal energy systems, hydrocarbon reservoirs, CO2 and energy storage as well as hydrothermal deposit exploration.
Energy is at the heart of the climate crisis—but also at the heart of any efforts for climate change mitigation. Energy consumption is namely responsible for approximately three quarters of global anthropogenic greenhouse gas (GHG) emissions. Therefore, central to any serious plans to stave off a climate catastrophe is a major transformation of the world's energy system, which would move society away from fossil fuels and towards a net-zero energy future. Considering that fossil fuels are also a major source of air pollutant emissions, the energy transition has important implications for air quality as well, and thus also for human and environmental health. Both Europe and Germany have set the goal of becoming GHG neutral by 2050, and moreover have demonstrated their deep commitment to a comprehensive energy transition. Two of the most significant developments in energy policy over the past decade have been the interest in expansion of shale gas and hydrogen, which accordingly have garnered great interest and debate among public, private and political actors.
In this context, sound scientific information can play an important role by informing stakeholder dialogue and future research investments, and by supporting evidence-based decision-making. This thesis examines anticipated environmental impacts from possible, relevant changes in the European energy system, in order to impart valuable insight and fill critical gaps in knowledge. Specifically, it investigates possible future shale gas development in Germany and the United Kingdom (UK), as well as a hypothetical, complete transition to hydrogen mobility in Germany. Moreover, it assesses the impacts on GHG and air pollutant emissions, and on tropospheric ozone (O3) air quality. The analysis is facilitated by constructing emission scenarios and performing air quality modeling via the Weather Research and Forecasting model coupled with chemistry (WRF-Chem). The work of this thesis is presented in three research papers.
The first paper finds that methane (CH4) leakage rates from upstream shale gas development in Germany and the UK would range between 0.35% and 1.36% in a realistic, business-as-usual case, while they would be significantly lower - between 0.08% and 0.15% - in an optimistic, strict regulation and high compliance case, thus demonstrating the value and potential of measures to substantially reduce emissions. Yet, while the optimistic case is technically feasible, it is unlikely that the practices and technologies assumed would be applied and accomplished on a systematic, regular basis, owing to economics and limited monitoring resources. The realistic CH4 leakage rates estimated in this study are comparable to values reported by studies carried out in the US and elsewhere. In contrast, the optimistic rates are similar to official CH4 leakage data from upstream gas production in Germany and in the UK. Considering that there is a lack of systematic, transparent and independent reports supporting the official values, this study further highlights the need for more research efforts in this direction. Compared with national energy sector emissions, this study suggests that shale gas emissions of volatile organic compounds (VOCs) could be significant, though relatively insignificant for other air pollutants. Similar to CH4, measures could be effective for reducing VOCs emissions.
The second paper shows that VOC and nitrogen oxides (NOx) emissions from a future shale gas industry in Germany and the UK have potentially harmful consequences for European O3 air quality on both the local and regional scale. The results indicate a peak increase in maximum daily 8-hour average O3 (MDA8) ranging from 3.7 µg m-3 to 28.3 µg m-3. Findings suggest that shale gas activities could result in additional exceedances of MDA8 at a substantial percentage of regulatory measurement stations both locally and in neighboring and distant countries, with up to circa one third of stations in the UK and one fifth of stations in Germany experiencing additional exceedances. Moreover, the results reveal that the shale gas impact on the cumulative health-related metric SOMO35 (annual Sum of Ozone Means Over 35 ppb) could be substantial, with a maximum increase of circa 28%. Overall, the findings suggest that shale gas VOC emissions could play a critical role in O3 enhancement, while NOx emissions would contribute to a lesser extent. Thus, the results indicate that stringent regulation of VOC emissions would be important in the event of future European shale gas development to minimize deleterious health outcomes.
The third paper demonstrates that a hypothetical, complete transition of the German vehicle fleet to hydrogen fuel cell technology could contribute substantially to Germany's climate and air quality goals. The results indicate that if the hydrogen were to be produced via renewable-powered water electrolysis (green hydrogen), German carbon dioxide equivalent (CO2eq) emissions would decrease by 179 MtCO2eq annually, though if electrolysis were powered by the current electricity mix, emissions would instead increase by 95 MtCO2eq annually. The findings generally reveal a notable anticipated decrease in German energy emissions of regulated air pollutants. The results suggest that vehicular hydrogen demand is 1000 PJ annually, which would require between 446 TWh and 525 TWh for electrolysis, hydrogen transport and storage. When only the heavy duty vehicle segment (HDVs) is shifted to green hydrogen, the results of this thesis show that vehicular hydrogen demand drops to 371 PJ, while a deep emissions cut is still realized (-57 MtCO2eq), suggesting that HDVs are a low-hanging fruit for contributing to decarbonization of the German road transport sector with hydrogen energy.
Magnetic strain contributions in laser-excited metals studied by time-resolved X-ray diffraction
(2021)
In this work I explore the impact of magnetic order on the laser-induced ultrafast strain response of metals. Few experiments with femto- or picosecond time-resolution have so far investigated magnetic stresses. This is contrasted by the industrial usage of magnetic invar materials or magnetostrictive transducers for ultrasound generation, which already utilize magnetostrictive stresses in the low frequency regime.
In the reported experiments I investigate how the energy deposition by the absorption of femtosecond laser pulses in thin metal films leads to an ultrafast stress generation. I utilize that this stress drives an expansion that emits nanoscopic strain pulses, so called hypersound, into adjacent layers. Both the expansion and the strain pulses change the average inter-atomic distance in the sample, which can be tracked with sub-picosecond time resolution using an X-ray diffraction setup at a laser-driven Plasma X-ray source. Ultrafast X-ray diffraction can also be applied to buried layers within heterostructures that cannot be accessed by optical methods, which exhibit a limited penetration into metals. The reconstruction of the initial energy transfer processes from the shape of the strain pulse in buried detection layers represents a contribution of this work to the field of picosecond ultrasonics.
A central point for the analysis of the experiments is the direct link between the deposited energy density in the nano-structures and the resulting stress on the crystal lattice. The underlying thermodynamical concept of a Grüneisen parameter provides the theoretical framework for my work. I demonstrate how the Grüneisen principle can be used for the interpretation of the strain response on ultrafast timescales in various materials and that it can be extended to describe magnetic stresses. The class of heavy rare-earth elements exhibits especially large magnetostriction effects, which can even lead to an unconventional contraction of the laser-excited transducer material. Such a dominant contribution of the magnetic stress to the motion of atoms has not been demonstrated previously. The observed rise time of the magnetic stress contribution in Dysprosium is identical to the decrease in the helical spin-order, that has been found previously using time-resolved resonant X-ray diffraction. This indicates that the strength of the magnetic stress can be used as a proxy of the underlying magnetic order. Such magnetostriction measurements are applicable even in case of antiparallel or non-collinear alignment of the magnetic moments and a vanishing magnetization.
The strain response of metal films is usually determined by the pressure of electrons and lattice vibrations. I have developed a versatile two-pulse excitation routine that can be used to extract the magnetic contribution to the strain response even if systematic measurements above and below the magnetic ordering temperature are not feasible. A first laser pulse leads to a partial ultrafast demagnetization so that the amplitude and shape of the strain response triggered by the second pulse depends on the remaining magnetic order. With this method I could identify a strongly anisotropic magnetic stress contribution in the magnetic data storage material iron-platinum and identify the recovery of the magnetic order by the variation of the pulse-to-pulse delay. The stark contrast of the expansion of iron-platinum nanograins and thin films shows that the different constraints for the in-plane expansion have a strong influence on the out-of-plane expansion, due to the Poisson effect. I show how such transverse strain contributions need to be accounted for when interpreting the ultrafast out-of-plane strain response using thermal expansion coefficients obtained in near equilibrium conditions.
This work contributes an investigation of magnetostriction on ultrafast timescales to the literature of magnetic effects in materials. It develops a method to extract spatial and temporal varying stress contributions based on a model for the amplitude and shape of the emitted strain pulses. Energy transfer processes result in a change of the stress profile with respect to the initial absorption of the laser pulses. One interesting example occurs in nanoscopic gold-nickel heterostructures, where excited electrons rapidly transport energy into a distant nickel layer, that takes up much more energy and expands faster and stronger than the laser-excited gold capping layer. Magnetic excitations in rare earth materials represent a large energy reservoir that delays the energy transfer into adjacent layers. Such magneto-caloric effects are known in thermodynamics but not extensively covered on ultrafast timescales. The combination of ultrafast X-ray diffraction and time-resolved techniques with direct access to the magnetization has a large potential to uncover and quantify such energy transfer processes.
Cellulose is the most abundant biopolymer on Earth and cell wall (CW) synthesis is one of the major carbon consumers in the plant cell. Structure and several interaction partners of plasma membrane (PM)-bound cellulose synthase (CESA) complexes, CSCs, have been studied extensively, but much less is understood about the signals that activate and translocate CESAs to the PM and how exactly cellulose synthesis is being regulated during the diel cycle. The literature describes CSC regulation possibilities through interactions with accessory proteins upon stress conditions (e.g. CC1), post-translational modifications that regulate CSC speed and their possible anchoring in the PM (e.g. with phosphorylation and S-acylation, respectively). In this thesis, 13CO2 labeling and imaging techniques were employed in the same Arabidopsis seedling growth system to elucidate how and when new carbon is incorporated into cell wall (CW) sugars and UDP-glucose, and to follow CSC behavior during the diel cycle. Additionally, an ubiquitination analysis was performed to investigate a possible mechanism to affect CSC trafficking to and/or from the PM. Carbon is being incorporated into CW glucose at a 3-fold higher rate during the light period in comparison to the night in wild-type seedlings. Furthermore, CSC density at the PM, as an indication of active cellulose synthesizing machinery, is increasing in the light and falling during the night, showing that CW biosynthesis is more active in the light. Therefore, CW synthesis might be regulated by the carbon status of the cell. This regulation is broken in the starchless pgm mutant where light and dark carbon incorporation rates into CW glucose are similar, possibly due to the high soluble sugar content in pgm during the first part of the night. Strikingly, pgm CSC abundance at the PM is constantly low during the whole diel cycle, indicating little or no cellulose synthesis, but can be restored with exogenous sucrose or a longer photoperiod. Ubiquitination was explored as a possible regulating mechanism for translocation of primary CW CSCs from the PM and several potential ubiquitination sites have been identified.. The approach in this thesis enabled to study cellulose/CW synthesis from different angles but in the same growth system, allowing direct comparison of those methodologies, which could help understand the relationship between the amount of available carbon in a plant cell and the cells capacity to synthesize cellulose/CW. Understanding which factors contribute to cellulose synthesis regulation and addressing those fundamental questions can provide essential knowledge to manage the need for increased crop production.
Anthropogenic climate change alters the hydrological cycle. While certain areas experience more intense precipitation events, others will experience droughts and increased evaporation, affecting water storage in long-term reservoirs, groundwater, snow, and glaciers. High elevation environments are especially vulnerable to climate change, which will impact the water supply for people living downstream. The Himalaya has been identified as a particularly vulnerable system, with nearly one billion people depending on the runoff in this system as their main water resource. As such, a more refined understanding of spatial and temporal changes in the water cycle in high altitude systems is essential to assess variations in water budgets under different climate change scenarios.
However, not only anthropogenic influences have an impact on the hydrological cycle, but changes to the hydrological cycle can occur over geological timescales, which are connected to the interplay between orogenic uplift and climate change. However, their temporal evolution and causes are often difficult to constrain. Using proxies that reflect hydrological changes with an increase in elevation, we can unravel the history of orogenic uplift in mountain ranges and its effect on the climate.
In this thesis, stable isotope ratios (expressed as δ2H and δ18O values) of meteoric waters and organic material are combined as tracers of atmospheric and hydrologic processes with remote sensing products to better understand water sources in the Himalayas. In addition, the record of modern climatological conditions based on the compound specific stable isotopes of leaf waxes (δ2Hwax) and brGDGTs (branched Glycerol dialkyl glycerol tetraethers) in modern soils in four Himalayan river catchments was assessed as proxies of the paleoclimate and (paleo-) elevation. Ultimately, hydrological variations over geological timescales were examined using δ13C and δ18O values of soil carbonates and bulk organic matter originating from sedimentological sections from the pre-Siwalik and Siwalik groups to track the response of vegetation and monsoon intensity and seasonality on a timescale of 20 Myr.
I find that Rayleigh distillation, with an ISM moisture source, mainly controls the isotopic composition of surface waters in the studied Himalayan catchments. An increase in d-excess in the spring, verified by remote sensing data products, shows the significant impact of runoff from snow-covered and glaciated areas on the surface water isotopic values in the timeseries.
In addition, I show that biomarker records such as brGDGTs and δ2Hwax have the potential to record (paleo-) elevation by yielding a significant correlation with the temperature and surface water δ2H values, respectively, as well as with elevation. Comparing the elevation inferred from both brGDGT and δ2Hwax, large differences were found in arid sections of the elevation transects due to an additional effect of evapotranspiration on δ2Hwax. A combined study of these proxies can improve paleoelevation estimates and provide recommendations based on the results found in this study.
Ultimately, I infer that the expansion of C4 vegetation between 20 and 1 Myr was not solely dependent on atmospheric pCO2, but also on regional changes in aridity and seasonality from to the stable isotopic signature of the two sedimentary sections in the Himalaya (east and west).
This thesis shows that the stable isotope chemistry of surface waters can be applied as a tool to monitor the changing Himalayan water budget under projected increasing temperatures. Minimizing the uncertainties associated with the paleo-elevation reconstructions were assessed by the combination of organic proxies (δ2Hwax and brGDGTs) in Himalayan soil. Stable isotope ratios in bulk soil and soil carbonates showed the evolution of vegetation influenced by the monsoon during the late Miocene, proving that these proxies can be used to record monsoon intensity, seasonality, and the response of vegetation. In conclusion, the use of organic proxies and stable isotope chemistry in the Himalayas has proven to successfully record changes in climate with increasing elevation. The combination of δ2Hwax and brGDGTs as a new proxy provides a more refined understanding of (paleo-)elevation and the influence of climate.
The energy required to drive photochemical reactions is derived from charge separation across the thylakoid membrane. As the consequence of difference in proton concentration between chloroplasts stroma and thylakoid lumen, a proton motive force (pmf) is generated. The pmf is composed out of the proton gradient (ΔpH) and membrane potential (ΔΨ), and together they drive the ATP synthesis. In nature, the amount of energy fueling photosynthesis varies due to frequent changes in the light intensity. Thylakoid ion transport can adapt the energy flow through a photosynthetic apparatus to the light availability by adjusting the pmf composition. Dissipation of ΔΨ reduces the charge recombination at the photosystem II, allowing for an increase in ΔpH component to trigger a feedback downregulation of photosynthesis. K+ Exchange Antiporter 3 (KEA3) driven K+/H+ antiport reduces the ΔpH fraction of pmf, thereby dampening a non-photochemical quenching (NPQ). As a result, it increases the photosynthesis efficiency during the transition to lower light intensity. This thesis aimed to find the answers for questions concerning KEA3 activity regulation and its role in plant development. Presented data shows that in plants lacking chloroplast ATP synthase assembly factor CGL160 with decreased ATP synthase activity, KEA3 has a pivotal role in photosynthesis regulation and plant growth during steady-state conditions. Lack of KEA3 in cgl160 mutant results in a strong growth impairment, as photosynthesis is limited due to increased pH-dependent NPQ and decreased electron flow through cytochrome b6f complex. Overexpression of KEA3 in cgl160 mutant increases charge recombination at photosystem II, promoting photosynthesis. Thus, during periods of low ATP synthase activity, plants benefit from KEA3 activity. The KEA3 undergoes dimerization via its regulatory C-terminus (RCT). The RCT responds to changes in light intensity as the plants expressing KEA3 without this domain show reduced photo-protective mechanism in light intensity transients. However, those plants fix more carbon during the photosynthesis induction phase as a trade-off for a long-term photoprotection, showing KEA3 regulatory role in plant development. The KEA3 RCT is facing thylakoid stroma, thus its regulation depends on light-induced changes in the stromal environment. KEA3 activity regulation overlaps with the stromal pH changes occurring during light fluctuations. The ATP and ADP has shown to have an affinity towards heterologously expressed KEA3 RCT. Such interaction causes conformational changes in RCT structure. The fold change of RCT-ligand interaction depends on the environmental pH value. With a combination of bioinformatics and in vitro approach, the ATP binding site at RCT was located. Introduction of binding site point mutation in planta KEA3 RCT resulted in antiporter activity deregulation during transition to low light. Together, the data presented in this thesis allowed us to assess more broadly a KEA3 role in photosynthesis adjustment and propose the models of KEA3 activity regulation throughout transition in light intensity.
Generative adversarial networks (GANs) have been broadly applied to a wide range of application domains since their proposal. In this thesis, we propose several methods that aim to tackle different existing problems in GANs. Particularly, even though GANs are generally able to generate high-quality samples, the diversity of the generated set is often sub-optimal. Moreover, the common increase of the number of models in the original GANs framework, as well as their architectural sizes, introduces additional costs. Additionally, even though challenging, the proper evaluation of a generated set is an important direction to ultimately improve the generation process in GANs. We start by introducing two diversification methods that extend the original GANs framework to multiple adversaries to stimulate sample diversity in a generated set. Then, we introduce a new post-training compression method based on Monte Carlo methods and importance sampling to quantize and prune the weights and activations of pre-trained neural networks without any additional training. The previous method may be used to reduce the memory and computational costs introduced by increasing the number of models in the original GANs framework. Moreover, we use a similar procedure to quantize and prune gradients during training, which also reduces the communication costs between different workers in a distributed training setting. We introduce several topology-based evaluation methods to assess data generation in different settings, namely image generation and language generation. Our methods retrieve both single-valued and double-valued metrics, which, given a real set, may be used to broadly assess a generated set or separately evaluate sample quality and sample diversity, respectively. Moreover, two of our metrics use locality-sensitive hashing to accurately assess the generated sets of highly compressed GANs. The analysis of the compression effects in GANs paves the way for their efficient employment in real-world applications. Given their general applicability, the methods proposed in this thesis may be extended beyond the context of GANs. Hence, they may be generally applied to enhance existing neural networks and, in particular, generative frameworks.
Massive Open Online Courses (MOOCs) open up new opportunities to learn a wide variety of skills online and are thus well suited for individual education, especially where proffcient teachers are not available locally. At the same time, modern society is undergoing a digital transformation, requiring the training of large numbers of current and future employees. Abstract thinking, logical reasoning, and the need to formulate instructions for computers are becoming increasingly relevant. A holistic way to train these skills is to learn how to program. Programming, in addition to being a mental discipline, is also considered a craft, and practical training is required to achieve mastery. In order to effectively convey programming skills in MOOCs, practical exercises are incorporated into the course curriculum to offer students the necessary hands-on experience to reach an in-depth understanding of the programming concepts presented. Our preliminary analysis showed that while being an integral and rewarding part of courses, practical exercises bear the risk of overburdening students who are struggling with conceptual misunderstandings and unknown syntax. In this thesis, we develop, implement, and evaluate different interventions with the aim to improve the learning experience, sustainability, and success of online programming courses. Data from four programming MOOCs, with a total of over 60,000 participants, are employed to determine criteria for practical programming exercises best suited for a given audience.
Based on over five million executions and scoring runs from students' task submissions, we deduce exercise difficulties, students' patterns in approaching the exercises, and potential flaws in exercise descriptions as well as preparatory videos. The primary issue in online learning is that students face a social gap caused by their isolated physical situation. Each individual student usually learns alone in front of a computer and suffers from the absence of a pre-determined time structure as provided in traditional school classes. Furthermore, online learning usually presses students into a one-size-fits-all curriculum, which presents the same content to all students, regardless of their individual needs and learning styles. Any means of a personalization of content or individual feedback regarding problems they encounter are mostly ruled out by the discrepancy between the number of learners and the number of instructors. This results in a high demand for self-motivation and determination of MOOC participants. Social distance exists between individual students as well as between students and course instructors. It decreases engagement and poses a threat to learning success. Within this research, we approach the identified issues within MOOCs and suggest scalable technical solutions, improving social interaction and balancing content difficulty.
Our contributions include situational interventions, approaches for personalizing educational content as well as concepts for fostering collaborative problem-solving. With these approaches, we reduce counterproductive struggles and create a universal improvement for future programming MOOCs. We evaluate our approaches and methods in detail to improve programming courses for students as well as instructors and to advance the state of knowledge in online education.
Data gathered from our experiments show that receiving peer feedback on one's programming problems improves overall course scores by up to 17%. Merely the act of phrasing a question about one's problem improved overall scores by about 14%. The rate of students reaching out for help was significantly improved by situational just-in-time interventions. Request for Comment interventions increased the share of students asking for help by up to 158%. Data from our four MOOCs further provide detailed insight into the learning behavior of students. We outline additional significant findings with regard to student behavior and demographic factors. Our approaches, the technical infrastructure, the numerous educational resources developed, and the data collected provide a solid foundation for future research.
Partial synchronous states exist in systems of coupled oscillators between full synchrony and asynchrony. They are an important research topic because of their variety of different dynamical states. Frequently, they are studied using phase dynamics. This is a caveat, as phase dynamics are generally obtained in the weak coupling limit of a first-order approximation in the coupling strength. The generalization to higher orders in the coupling strength is an open problem. Of particular interest in the research of partial synchrony are systems containing both attractive and repulsive coupling between the units. Such a mix of coupling yields very specific dynamical states that may help understand the transition between full synchrony and asynchrony. This thesis investigates partial synchronous states in mixed-coupling systems. First, a method for higher-order phase reduction is introduced to observe interactions beyond the pairwise one in the first-order phase description, hoping that these may apply to mixed-coupling systems. This new method for coupled systems with known phase dynamics of the units gives correct results but, like most comparable methods, is computationally expensive. It is applied to three Stuart-Landau oscillators coupled in a line with a uniform coupling strength. A numerical method is derived to verify the analytical results. These results are interesting but give importance to simpler phase models that still exhibit exotic states. Such simple models that are rarely considered are Kuramoto oscillators with attractive and repulsive interactions. Depending on how the units are coupled and the frequency difference between the units, it is possible to achieve many different states. Rich synchronization dynamics, such as a Bellerophon state, are observed when considering a Kuramoto model with attractive interaction in two subpopulations (groups) and repulsive interactions between groups. In two groups, one attractive and one repulsive, of identical oscillators with a frequency difference, an interesting solitary state appears directly between full and partial synchrony. This system can be described very well analytically.
The spread of shrubs in Namibian savannas raises questions about the resilience of these ecosystems to global change. This makes it necessary to understand the past dynamics of the vegetation, since there is no consensus on whether shrub encroachment is a new phenomenon, nor on its main drivers. However, a lack of long-term vegetation datasets for the region and the scarcity of suitable palaeoecological archives, makes reconstructing past vegetation and land cover of the savannas a challenge.
To help meet this challenge, this study addresses three main research questions: 1) is pollen analysis a suitable tool to reflect the vegetation change associated with shrub encroachment in savanna environments? 2) Does the current encroached landscape correspond to an alternative stable state of savanna vegetation? 3) To what extent do pollen-based quantitative vegetation reconstructions reflect changes in past land cover?
The research focuses on north-central Namibia, where despite being the region most affected by shrub invasion, particularly since the 21st century, little is known about the dynamics of this phenomenon.
Field-based vegetation data were compared with modern pollen data to assess their correspondence in terms of composition and diversity along precipitation and grazing intensity gradients. In addition, two sediment cores from Lake Otjikoto were analysed to reveal changes in vegetation composition that have occurred in the region over the past 170 years and their possible drivers. For this, a multiproxy approach (fossil pollen, sedimentary ancient DNA (sedaDNA), biomarkers, compound specific carbon (δ13C) and deuterium (δD) isotopes, bulk carbon isotopes (δ13Corg), grain size, geochemical properties) was applied at high taxonomic and temporal resolution. REVEALS modelling of the fossil pollen record from Lake Otjikoto was run to quantitatively reconstruct past vegetation cover. For this, we first made pollen productivity estimates (PPE) of the most relevant savanna taxa in the region using the extended R-value model and two pollen dispersal options (Gaussian plume model and Lagrangian stochastic model). The REVEALS-based vegetation reconstruction was then validated using remote sensing-based regional vegetation data.
The results show that modern pollen reflects the composition of the vegetation well, but diversity less well. Interestingly, precipitation and grazing explain a significant amount of the compositional change in the pollen and vegetation spectra. The multiproxy record shows that a state change from open Combretum woodland to encroached Terminalia shrubland can occur over a century, and that the transition between states spans around 80 years and is characterized by a unique vegetation composition. This transition is supported by gradual environmental changes induced by management (i.e. broad-scale logging for the mining industry, selective grazing and reduced fire activity associated with intensified farming) and related land-use change. Derived environmental changes (i.e. reduced soil moisture, reduced grass cover, changes in species composition and competitiveness, reduced fire intensity) may have affected the resilience of Combretum open woodlands, making them more susceptible to change to an encroached state by stochastic events such as consecutive years of precipitation and drought, and by high concentrations of pCO2. We assume that the resulting encroached state was further stabilized by feedback mechanisms that favour the establishment and competitiveness of woody vegetation.
The REVEALS-based quantitative estimates of plant taxa indicate the predominance of a semi-open landscape throughout the 20th century and a reduction in grass cover below 50% since the 21st century associated with the spread of encroacher woody taxa. Cover estimates show a close match with regional vegetation data, providing support for the vegetation dynamics inferred from multiproxy analyses. Reasonable PPEs were made for all woody taxa, but not for Poaceae.
In conclusion, pollen analysis is a suitable tool to reconstruct past vegetation dynamics in savannas. However, because pollen cannot identify grasses beyond family level, a multiproxy approach, particularly the use of sedaDNA, is required. I was able to separate stable encroached states from mere woodland phases, and could identify drivers and speculate about related feedbacks. In addition, the REVEALS-based quantitative vegetation reconstruction clearly reflects the magnitude of the changes in the vegetation cover that occurred during the last 130 years, despite the limitations of some PPEs.
This research provides new insights into pollen-vegetation relationships in savannas and highlights the importance of multiproxy approaches when reconstructing past vegetation dynamics in semi-arid environments. It also provides the first time series with sufficient taxonomic resolution to show changes in vegetation composition during shrub encroachment, as well as the first quantitative reconstruction of past land cover in the region. These results help to identify the different stages in savanna dynamics and can be used to calibrate predictive models of vegetation change, which are highly relevant to land management.
Carbonatite magmatism is a highly efficient transport mechanism from Earth’s mantle to the crust, thus providing insights into the chemistry and dynamics of the Earth’s mantle. One evolving and promising tool for tracing magma interaction are stable iron isotopes, particularly because iron isotope fractionation is controlled by oxidation state and bonding environment. Meanwhile, a large data set on iron isotope fractionation in igneous rocks exists comprising bulk rock compositions and fractionation between mineral groups. Iron isotope data from natural carbonatite rocks are extremely light and of remarkably high variability. This resembles iron isotope data from mantle xenoliths, which are characterized by a variability in δ56Fe spanning three times the range found in basalts, and by the extremely light values of some whole rock samples, reaching δ56Fe as low as -0.69 ‰ in a spinel lherzolite. Cause to this large range of variations may be metasomatic processes, involving metasomatic agents like volatile bearing high-alkaline silicate melts or carbonate melts. The expected effects of metasomatism on iron isotope fractionation vary with parameters like melt/rock-ratio, reaction time, and the nature of metasomatic agents and mineral reactions involved. An alternative or additional way to enrich light isotopes in the mantle could be multiple phases of melt extraction. To interpret the existing data sets more knowledge on iron isotope fractionation factors is needed.
To investigate the behavior of iron isotopes in the carbonatite systems, kinetic and equilibration experiments in natro-carbonatite systems between immiscible silicate and carbonate melts were performed in an internally heated gas pressure vessel at intrinsic redox conditions at temperatures between 900 and 1200 °C and pressures of 0.5 and 0.7 GPa. The iron isotope compositions of coexisting silicate melt and carbonate melt were analyzed by solution MC-ICP-MS. The kinetic experiments employing a Fe-58 spiked starting material show that isotopic equilibrium is obtained after 48 hours. The experimental studies of equilibrium iron isotope fractionation between immiscible silicate and carbonate melts have shown that light isotopes are enriched in the carbonatite melt. The highest Δ56Fesil.m.-carb.melt (mean) of 0.13 ‰ was determined in a system with a strongly peralkaline silicate melt composition (ASI ≥ 0.21, Na/Al ≤ 2.7). In three systems with extremely peralkaline silicate melt compositions (ASI between 0.11 and 0.14) iron isotope fractionation could analytically not be resolved. The lowest Δ56Fesil.m.-carb.melt (mean) of 0.02 ‰ was determined in a system with an extremely peralkaline silicate melt composition (ASI ≤ 0.11 , Na/Al ≥ 6.1). The observed iron isotope fractionation is most likely governed by the redox conditions of the system. Yet, in the systems, where no fractionation occurred, structural changes induced by compositional changes possibly overrule the influence of redox conditions. This interpretation implicates, that the iron isotope system holds the potential to be useful not only for exploring redox conditions in magmatic systems, but also for discovering structural changes in a melt.
In situ iron isotope analyses by femtosecond laser ablation coupled to MC-ICP-MS on magnetite and olivine grains were performed to reveal variations in iron isotope composition on the micro scale. The investigated sample is a melilitite bomb from the Salt Lake Crater group at Honolulu (Oahu, Hawaii), showing strong evidence for interaction with a carbonatite melt. While magnetite grains are rather homogeneous in their iron isotope compositions, olivine grains span a far larger range in iron isotope ratios. The variability of δ56Fe in magnetite is limited from - 0.17 ‰ (± 0.11 ‰, 2SE) to +0.08 ‰ (± 0.09 ‰, 2SE). δ56Fe in olivine range from -0.66‰ (± 0.11 ‰, 2SE) to +0.10 ‰ (± 0.13 ‰, 2SE). Olivine and magnetite grains hold different informations regarding kinetic and equilibrium fractionation due to their different Fe diffusion coefficients. The observations made in the experiments and in the in situ iron isotope analyses suggest that the extremely light iron isotope signatures found in carbonatites are generated by several steps of isotope fractionation during carbonatite genesis. These may involve equilibrium and kinetic fractionation. Since iron isotopic signatures in natural systems are generated by a combination of multiple factors (pressure, temperature, redox conditions, phase composition and structure, time scale), multi tracer approaches are needed to explain signatures found in natural rocks.
One of the key challenges in modern Facility Management (FM) is to digitally reflect the current state of the built environment, referred to as-is or as-built versus as-designed representation. While the use of Building Information Modeling (BIM) can address the issue of digital representation, the generation and maintenance of BIM data requires a considerable amount of manual work and domain expertise. Another key challenge is being able to monitor the current state of the built environment, which is used to provide feedback and enhance decision making. The need for an integrated solution for all data associated with the operational life cycle of a building is becoming more pronounced as practices from Industry 4.0 are currently being evaluated and adopted for FM use. This research presents an approach for digital representation of indoor environments in their current state within the life cycle of a given building. Such an approach requires the fusion of various sources of digital data. The key to solving such a complex issue of digital data integration, processing and representation is with the use of a Digital Twin (DT). A DT is a digital duplicate of the physical environment, states, and processes. A DT fuses as-designed and as-built digital representations of built environment with as-is data, typically in the form of floorplans, point clouds and BIMs, with additional information layers pertaining to the current and predicted states of an indoor environment or a complete building (e.g., sensor data). The design, implementation and initial testing of prototypical DT software services for indoor environments is presented and described. These DT software services are implemented within a service-oriented paradigm, and their feasibility is presented through functioning and tested key software components within prototypical Service-Oriented System (SOS) implementations. The main outcome of this research shows that key data related to the built environment can be semantically enriched and combined to enable digital representations of indoor environments, based on the concept of a DT. Furthermore, the outcomes of this research show that digital data, related to FM and Architecture, Construction, Engineering, Owner and Occupant (AECOO) activity, can be combined, analyzed and visualized in real-time using a service-oriented approach. This has great potential to benefit decision making related to Operation and Maintenance (O&M) procedures within the scope of the post-construction life cycle stages of typical office buildings.
Anthropogenic activities such as continuous landscape changes threaten biodiversity at both local and regional scales. Metacommunity models attempt to combine these two scales and continuously contribute to a better mechanistic understanding of how spatial processes and constraints, such as fragmentation, affect biodiversity. There is a strong consensus that such structural changes of the landscape tend to negatively effect the stability of metacommunities. However, in particular the interplay of complex trophic communities and landscape structure is not yet fully understood.
In this present dissertation, a metacommunity approach is used based on a dynamic and spatially explicit model that integrates population dynamics at the local scale and dispersal dynamics at the regional scale. This approach allows the assessment of complex spatial landscape components such as habitat clustering on complex species communities, as well as the analysis of population dynamics of a single species. In addition to the impact of a fixed landscape structure, periodic environmental disturbances are also considered, where a periodical change of habitat availability, temporally alters landscape structure, such as the seasonal drying of a water body.
On the local scale, the model results suggest that large-bodied animal species, such as predator species at high trophic positions, are more prone to extinction in a state of large patch isolation than smaller species at lower trophic levels.
Increased metabolic losses for species with a lower body mass lead to increased energy limitation for species on higher trophic levels and serves as an explanation for a predominant loss of these species. This effect is particularly pronounced for food webs, where species are more sensitive to increased metabolic losses through dispersal and a change in landscape structure.
In addition to the impact of species composition in a food web for diversity, the strength of local foraging interactions likewise affect the synchronization of population dynamics. A reduced predation pressure leads to more asynchronous population dynamics, beneficial for the stability of population dynamics as it reduces the risk of correlated extinction events among habitats. On the regional scale, two landscape aspects, which are the mean patch isolation and the formation of local clusters of two patches, promote an increase in $\beta$-diversity. Yet, the individual composition and robustness of the local species community equally explain a large proportion of the observed diversity patterns.
A combination of periodic environmental disturbance and patch isolation has a particular impact on population dynamics of a species. While the periodic disturbance has a synchronizing effect, it can even superimpose emerging asynchronous dynamics in a state of large patch isolation and unifies trends in synchronization between different species communities.
In summary, the findings underline a large local impact of species composition and interactions on local diversity patterns of a metacommunity. In comparison, landscape structures such as fragmentation have a negligible effect on local diversity patterns, but increase their impact for regional diversity patterns. In contrast, at the level of population dynamics, regional characteristics such as periodic environmental disturbance and patch isolation have a particularly strong impact and contribute substantially to the understanding of the stability of population dynamics in a metacommunity. These studies demonstrate once again the complexity of our ecosystems and the need for further analysis for a better understanding of our surrounding environment and more targeted conservation of biodiversity.
Kenya and Uganda are amongst the countries that, for different historical, political, and economic reasons, have embarked on law reform processes as regards to citizenship. In 2009, Uganda made provisions in its laws to allow citizens to have dual citizenship while Kenya’s 2010 constitution similarly introduced it, and at the same time, a general prohibition on dual citizenship was lifted, that is, a ban on state officers, including the President and Deputy President, being dual nationals (Manby, 2018).
Against this background, I analysed the reasons for which these countries that previously held stringent laws and policies against dual citizenship, made a shift in a close time proximity. Given their geo-political roles, location, regional, continental, and international obligations, I conducted a comparative study on the processes, actors, impact, and effect. A specific period of 2000 to 2010 was researched, that is, from when the debates for law reforms emerged, to the processes being implemented, the actors, and the implications.
According to Rubenstein (2000, p. 520), citizenship is observed in terms of “political institutions” that are free to act according to the will of, in the interests of, or with authority over, their citizenry. Institutions are emergent national or international, higher-order factors above the individual spectrum, having the interests and political involvement of their actors without requiring recurring collective mobilisation or imposing intervention to realise these regularities. Transnational institutions are organisations with authority beyond single governments. Given their International obligations, I analysed the role of the UN, AU, and EAC in influencing the citizenship debates and reforms in Kenya and Uganda. Further, non-state actors, such as civil society, were considered.
Veblen, (1899) describes institutions as a set of settled habits of thought common to the generality of men. Institutions function only because the rules involved are rooted in shared habits of thought and behaviour although there is some ambiguity in the definition of the term “habit”. Whereas abstracts and definitions depend on different analytical procedures, institutions restrain some forms of action and facilitate others. Transnational institutions both restrict and aid behaviour. The famous “invisible hand” is nothing else but transnational institutions. Transnational theories, as applied to politics, posit two distinct forms that are of influence over policy and political action (Veblen, 1899). This influence and durability of institutions is “a function of the degree to which they are instilled in political actors at the individual or organisational level, and the extent to which they thereby “tie up” material resources and networks. Against this background, transitional networks with connection to Kenya and Uganda were considered alongside the diaspora from these two countries and their role in the debate and reforms on Dual citizenship.
Sterian (2013, p. 310) notes that Nation states may be vulnerable to institutional influence and this vulnerability can pose a threat to a nation’s autonomy, political legitimacy, and to the democratic public law. Transnational institutions sometimes “collide with the sovereignty of the state when they create new structures for regulating cross-border relationships”. However, Griffin (2003) disagrees that transnational institutional behaviour is premised on the principles of neutrality, impartiality, and independence. Transnational institutions have become the main target of the lobby groups and civil society, consequently leading to excessive politicisation. Kenya and Uganda are member states not only of the broader African union but also of the E.A.C which has adopted elements of socio-economic uniformity. Therefore, in the comparative analysis, I examine the role of the East African Community and its partners in the dual citizenship debate on the two countries.
I argue in the analysis that it is not only important to be a citizen within Kenya or Uganda but also important to discover how the issue of dual citizenship is legally interpreted within the borders of each individual nation-state. In light of this discussion, I agree with Mamdani’s definition of the nation-state as a unique form of power introduced in Africa by colonial powers between 1880 and 1940 whose outcomes can be viewed as “debris of a modernist postcolonial project, an attempt to create a centralised modern state as the bearer of Westphalia sovereignty against the background of indirect rule” (Mamdani, 1996, p. xxii). I argue that this project has impacted the citizenship debate through the adopted legal framework of post colonialism, built partly on a class system, ethnic definitions, and political affiliation. I, however, insist that the nation-state should still be a vital custodian of the citizenship debate, not in any way denying the individual the rights to identity and belonging. The question then that arises is which type of nation-state? Mamdani (1996, p. 298) asserts that the core agenda that African states faced at independence was threefold: deracialising civil society; detribalising the native authority; and developing the economy in the context of unequal international relations. Post-independence governments grappled with overcoming the citizen and subject dichotomy through either preserving the customary in the name of “defending tradition against alien encroachment or abolishing it in the name of overcoming backwardness and embracing triumphant modernism”. Kenya and Uganda are among countries that have reformed their citizenship laws attesting to Mamdani’s latter assertion.
Mamdani’s (1996) assertions on how African states continue to deal with the issue of citizenship through either the defence of tradition against subjects or abolishing it in the name of overcoming backwardness and acceptance of triumphant modernism are based on the colonial legal theory and the citizen-subject dichotomy within Africa communities. To further create a wider perspective on legal theory, I argue that those assertions above, point to the historical divergence between the republican model of citizenship, which places emphasis on political agency as envisioned in Rousseau´s social contract, as opposed to the liberal model of citizenship, which stresses the legal status and protection (Pocock, 1995).
I, therefore, compare the contexts of both Kenya and Uganda, the actors, the implications of transnationalism and post-nationalism, on the citizens, the nation-state and the region. I conclude by highlighting the shortcomings in the law reforms that allowed for dual citizenship, further demonstrating an urgent need to address issues, such as child statelessness, gender nationality laws, and the rights of dual citizens. Ethnicity, a weak nation state, and inconsistent citizenship legal reforms are closely linked to the historical factors of both countries. I further indicate the economic and political incentives that influenced the reform.
Keywords: Citizenship, dual citizenship, nation state, republicanism, liberalism, transnationalism, post-nationalism
Forming as a result of the collision between the Adriatic and European plates, the Alpine orogen exhibits significant lithospheric heterogeneity due to the long history of interplay between these plates, other continental and oceanic blocks in the region, and inherited features from preceeding orogenies. This implies that the thermal and rheological configuration of the lithosphere also varies significantly throughout the region. Lithology and temperature/pressure conditions exert a first order control on rock strength, principally via thermally activated creep deformation and on the distribution at depth of the brittle-ductile transition zone, which can be regarded as the lower bound to the seismogenic zone. Therefore, they influence the spatial distribution of seismicity within a lithospheric plate. In light of this, accurately constrained geophysical models of the heterogeneous Alpine lithospheric configuration, are crucial in describing regional deformation patterns. However, despite the amount of research focussing on the area, different hypotheses still exist regarding the present-day lithospheric state and how it might relate to the present-day seismicity distribution.
This dissertaion seeks to constrain the Alpine lithospheric configuration through a fully 3D integrated modelling workflow, that utilises multiple geophysical techniques and integrates from all available data sources. The aim is therefore to shed light on how lithospheric heterogeneity may play a role in influencing the heterogeneous patterns of seismicity distribution observed within the region. This was accomplished through the generation of: (i) 3D seismically constrained, structural and density models of the lithosphere, that were adjusted to match the observed gravity field; (ii) 3D models of the lithospheric steady state thermal field, that were adjusted to match observed wellbore temperatures; and (iii) 3D rheological models of long term lithospheric strength, with the results of each step used as input for the following steps.
Results indicate that the highest strength within the crust (~ 1 GPa) and upper mantle (> 2 GPa), are shown to occur at temperatures characteristic for specific phase transitions (more felsic crust: 200 – 400 °C; more mafic crust and upper lithospheric mantle: ~600 °C) with almost all seismicity occurring in these regions. However, inherited lithospheric heterogeneity was found to significantly influence this, with seismicity in the thinner and more mafic Adriatic crust (~22.5 km, 2800 kg m−3, 1.30E-06 W m-3) occuring to higher temperatures (~600 °C) than in the thicker and more felsic European crust (~27.5 km, 2750 kg m−3, 1.3–2.6E-06 W m-3, ~450 °C). Correlation between seismicity in the orogen forelands and lithospheric strength, also show different trends, reflecting their different tectonic settings. As such, events in the plate boundary setting of the southern foreland correlate with the integrated lithospheric strength, occurring mainly in the weaker lithosphere surrounding the strong Adriatic indenter. Events in the intraplate setting of the northern foreland, instead correlate with crustal strength, mainly occurring in the weaker and warmer crust beneath the Upper Rhine Graben.
Therefore, not only do the findings presented in this work represent a state of the art understanding of the lithospheric configuration beneath the Alps and their forelands, but also a significant improvement on the features known to significantly influence the occurrence of seismicity within the region. This highlights the importance of considering lithospheric state in regards to explaining observed patterns of deformation.
The ubiquitin-proteasome-system (UPS) is a cellular cascade involving three enzymatic steps for protein ubiquitination to target them to the 26S proteasome for proteolytic degradation. Several components of the UPS have been shown to be central for regulation of defense responses during infections with phytopathogenic bacteria. Upon recognition of the pathogen, local defense is induced which also primes the plant to acquire systemic resistance (SAR) for enhanced immune responses upon challenging infections. Here, ubiquitinated proteins were shown to accumulate locally and systemically during infections with Psm and after treatment with the SAR-inducing metabolites salicylic acid (SA) and pipecolic acid (Pip). The role of the 26S proteasome in local defense has been described in several studies, but the potential role during SAR remains elusive and was therefore investigated in this project by characterizing the Arabidopsis proteasome mutants rpt2a-2 and rpn12a-1 during priming and infections with Pseudomonas. Bacterial replication assays reveal decreased basal and systemic immunity in both mutants which was verified on molecular level showing impaired activation of defense- and SAR-genes. rpt2a-2 and rpn12a-1 accumulate wild type like levels of camalexin but less SA. Endogenous SA treatment restores local PR gene expression but does not rescue the SAR-phenotype. An RNAseq experiment of Col-0 and rpt2a-2 reveal weak or absent induction of defense genes in the proteasome mutant during priming. Thus, a functional 26S proteasome was found to be required for induction of SAR while compensatory mechanisms can still be initiated.
E3-ubiquitin ligases conduct the last step of substrate ubiquitination and thereby convey specificity to proteasomal protein turnover. Using RNAseq, 11 E3-ligases were found to be differentially expressed during priming in Col-0 of which plant U-box 54 (PUB54) and ariadne 12 (ARI12) were further investigated to gain deeper understanding of their potential role during priming.
PUB54 was shown to be expressed during priming and /or triggering with virulent Pseudomonas. pub54 I and pub54-II mutants display local and systemic defense comparable to Col-0. The heavy-metal associated protein 35 (HMP35) was identified as potential substrate of PUB54 in yeast which was verified in vitro and in vivo. PUB54 was shown to be an active E3-ligase exhibiting auto-ubiquitination activity and performing ubiquitination of HMP35. Proteasomal turnover of HMP35 was observed indicating that PUB54 targets HMP35 for ubiquitination and subsequent proteasomal degradation. Furthermore, hmp35-I benefits from increased resistance in bacterial replication assays. Thus, HMP35 is potentially a negative regulator of defense which is targeted and ubiquitinated by PUB54 to regulate downstream defense signaling. ARI12 is transcriptionally activated during priming or triggering and hyperinduced during priming and triggering. Gene expression is not inducible by the defense related hormone salicylic acid (SA) and is dampened in npr1 and fmo1 mutants consequently depending on functional SA- and Pip-pathways, respectively. ARI12 accumulates systemically after priming with SA, Pip or Pseudomonas. ari12 mutants are not altered in resistance but stable overexpression leads to increased resistance in local and systemic tissue. During priming and triggering, unbalanced ARI12 levels (i.e. knock out or overexpression) leads to enhanced FMO1 activation indicating a role of ARI12 in Pip-mediated SAR. ARI12 was shown to be an active E3-ligase with auto-ubiquitination activity likely required for activation with an identified ubiquitination site at K474. Mass spectrometrically identified potential substrates were not verified by additional experiments yet but suggest involvement of ARI12 in regulation of ROS in turn regulating Pip-dependent SAR pathways.
Thus, data from this project provide strong indications about the involvement of the 26S proteasome in SAR and identified a central role of the two so far barely described E3-ubiquitin ligases PUB54 and ARI12 as novel components of plant defense.
Background: A growing body of research has documented negative effects of sexualization in the media on individuals’ self-objectification. This research is predominantly built on studies examining traditional media, such as magazines and television, and young female samples. Furthermore, longitudinal studies are scarce, and research is missing studying mediators of the relationship. The first aim of the present PhD thesis was to investigate the relations between the use of sexualized interactive media and social media and self-objectification. The second aim of this work was to examine the presumed processes within understudied samples, such as males and females beyond college age, thus investigating the moderating roles of age and gender. The third aim was to shed light on possible mediators of the relation between sexualized media and self-objectification.
Method: The research aims were addressed within the scope of four studies. In an experiment, women’s self-objectification and body satisfaction was measured after playing a video game with a sexualized vs. a nonsexualized character that was either personalized or generic. The second study investigated the cross-sectional link between sexualized television use and self-objectification and consideration of cosmetic surgery in a sample of women across a broad age spectrum, examining the role of age in the relations. The third study looked at the cross-sectional link between male and female sexualized images on Instagram and their associations with self-objectification among a sample of male and female adolescents. Using a two-wave longitudinal design, the fourth study examined sexualized video game and Instagram use as predictors of adolescents’ self-objectification. Path models were conceptualized for the second, third and fourth study, in which media use predicted body surveillance via appearance comparisons (Study 4), thin-ideal internalization (Study 2, 3, 4), muscular-ideal internalization (Study 3, 4), and valuing appearance (all studies).
Results: The results of the experimental study revealed no effect of sexualized video game characters on women’s self-objectification and body satisfaction. No moderating effect of personalization emerged. Sexualized television use was associated to consideration of cosmetic surgery via body surveillance and valuing appearance for women of all ages in Study 2, while no moderating effect of age was found. Study 3 revealed that seeing sexualized male images on Instagram was indirectly associated with higher body surveillance via muscular-ideal internalization for boys and girls. Sexualized female images were indirectly linked to higher body surveillance via thin-ideal internalization and valuing appearance over competence only for girls. The longitudinal analysis of Study 4 showed no moderating effect of gender: For boys and girls, sexualized video game use at T1 predicted body surveillance at T2 via appearance comparisons, thin-ideal internalization and valuing appearance over competence. Furthermore, the use of sexualized Instagram images at T1 predicted body surveillance at T2 via valuing appearance.
Conclusion: The findings show that sexualization in the media is linked to self-objectification among a variety of media formats and within diverse groups of people. While the longitudinal study indicates that sexualized media predict self-objectification over time, the experimental null findings warrant caution regarding this temporal order. The results demonstrate that several mediating variables might be involved in this link. Possible implications for research and practice, such as intervention programs and policy-making, are discussed.
Media artists have been struggling for financial survival ever since media art came into being. The non-material value of the artwork, a provocative attitude towards the traditional arts world and originally anti-capitalist mindset of the movement makes it particularly difficult to provide a constructive solution. However, a cultural entrepreneurial approach can be used to build a framework in order to find a balance between culture and business while ensuring that the cultural mission remains the top priority.
We investigate models for incremental binary classification, an example for supervised online learning. Our starting point is a model for human and machine learning suggested by E.M.Gold.
In the first part, we consider incremental learning algorithms that use all of the available binary labeled training data in order to compute the current hypothesis. For this model, we observe that the algorithm can be assumed to always terminate and that the distribution of the training data does not influence learnability. This is still true if we pose additional delayable requirements that remain valid despite a hypothesis output delayed in time. Additionally, we consider the non-delayable requirement of consistent learning. Our corresponding results underpin the claim for delayability being a suitable structural property to describe and collectively investigate a major part of learning success criteria. Our first theorem states the pairwise implications or incomparabilities between an established collection of delayable learning success criteria, the so-called complete map. Especially, the learning algorithm can be assumed to only change its last hypothesis in case it is inconsistent with the current training data. Such a learning behaviour is called conservative.
By referring to learning functions, we obtain a hierarchy of approximative learning success criteria. Hereby we allow an increasing finite number of errors of the hypothesized concept by the learning algorithm compared with the concept to be learned. Moreover, we observe a duality depending on whether vacillations between infinitely many different correct hypotheses are still considered a successful learning behaviour. This contrasts the vacillatory hierarchy for learning from solely positive information.
We also consider a hypothesis space located between the two most common hypothesis space types in the nearby relevant literature and provide the complete map.
In the second part, we model more efficient learning algorithms. These update their hypothesis referring to the current datum and without direct regress to past training data. We focus on iterative (hypothesis based) and BMS (state based) learning algorithms. Iterative learning algorithms use the last hypothesis and the current datum in order to infer the new hypothesis.
Past research analyzed, for example, the above mentioned pairwise relations between delayable learning success criteria when learning from purely positive training data. We compare delayable learning success criteria with respect to iterative learning algorithms, as well as learning from either exclusively positive or binary labeled data. The existence of concept classes that can be learned by an iterative learning algorithm but not in a conservative way had already been observed, showing that conservativeness is restrictive. An additional requirement arising from cognitive science research %and also observed when training neural networks is U-shapedness, stating that the learning algorithm does diverge from a correct hypothesis. We show that forbidding U-shapes also restricts iterative learners from binary labeled data.
In order to compute the next hypothesis, BMS learning algorithms refer to the currently observed datum and the actual state of the learning algorithm. For learning algorithms equipped with an infinite amount of states, we provide the complete map. A learning success criterion is semantic if it still holds, when the learning algorithm outputs other parameters standing for the same classifier. Syntactic (non-semantic) learning success criteria, for example conservativeness and syntactic non-U-shapedness, restrict BMS learning algorithms. For proving the equivalence of the syntactic requirements, we refer to witness-based learning processes. In these, every change of the hypothesis is justified by a later on correctly classified witness from the training data. Moreover, for every semantic delayable learning requirement, iterative and BMS learning algorithms are equivalent. In case the considered learning success criterion incorporates syntactic non-U-shapedness, BMS learning algorithms can learn more concept classes than iterative learning algorithms.
The proofs are combinatorial, inspired by investigating formal languages or employ results from computability theory, such as infinite recursion theorems (fixed point theorems).
Intentionality in Sellars
(2021)
This book argues that Sellars’ theory of intentionality can be understood as an advancement of a transcendental philosophical approach. It shows how Sellars develops his theory of intentionality through his engagement with the theoretical philosophy of Immanuel Kant.
The book delivers a provocative reinterpretation of one of the most problematic and controversial concepts of Sellars' philosophy: the picturing-relation. Sellars' theory of intentionality addresses the question of how to reconcile two aspects that seem opposed: the non-relational theory of intellectual and linguistic content and a causal-transcendental theory of representation inspired by the philosophy of the early Wittgenstein. The author explains how both parts cohere in a transcendental account of finite knowledge. He claims that this can only be achieved by reading Sellars as committed to a transcendental methodology inspired by Kant. In a final step, he brings his interpretation to bear on the contemporary metaphilosophical debate on pragmatism and expressivism.
Intentionality in Sellars will be of interest to scholars of Sellars and Kant, as well as researchers working in philosophy of mind, epistemology, and the history of nineteenth- and twentieth-century philosophy.
During sentence reading the eyes quickly jump from word to word to sample visual information with the high acuity of the fovea. Lexical properties of the currently fixated word are known to affect the duration of the fixation, reflecting an interaction of word processing with oculomotor planning. While low level properties of words in the parafovea can likewise affect the current fixation duration, results concerning the influence of lexical properties have been ambiguous (Drieghe, Rayner, & Pollatsek, 2008; Kliegl, Nuthmann, & Engbert, 2006). Experimental investigations of such lexical parafoveal-on-foveal effects using the boundary paradigm have instead shown, that lexical properties of parafoveal previews affect fixation durations on the upcoming target words (Risse & Kliegl, 2014). However, the results were potentially confounded with effects of preview validity.
The notion of parafoveal processing of lexical information challenges extant models of eye movements during reading. Models containing serial word processing assumptions have trouble explaining such effects, as they usually couple successful word processing to saccade planning, resulting in skipping of the parafoveal word. Although models with parallel word processing are less restricted, in the SWIFT model (Engbert, Longtin, & Kliegl, 2002) only processing of the foveal word can directly influence the saccade latency.
Here we combine the results of a boundary experiment (Chapter 2) with a predictive modeling approach using the SWIFT model, where we explore mechanisms of parafoveal inhibition in a simulation study (Chapter 4). We construct a likelihood function for the SWIFT model (Chapter 3) and utilize the experimental data in a Bayesian approach to parameter estimation (Chapter 3 & 4).
The experimental results show a substantial effect of parafoveal preview frequency on fixation durations on the target word, which can be clearly distinguished from the effect of preview validity. Using the eye movement data from the participants, we demonstrate the feasibility of the Bayesian approach even for a small set of estimated parameters, by comparing summary statistics of experimental and simulated data. Finally, we can show that the SWIFT model can account for the lexical preview effects, when a mechanism for parafoveal inhibition is added. The effects of preview validity were modeled best, when processing dependent saccade cancellation was added for invalid trials. In the simulation study only the control condition of the experiment was used for parameter estimation, allowing for cross validation. Simultaneously the number of free parameters was increased. High correlations of summary statistics demonstrate the capabilities of the parameter estimation approach. Taken together, the results advocate for a better integration of experimental data into computational modeling via parameter estimation.
To achieve a sustainable energy economy, it is necessary to turn back on the combustion of fossil fuels as a means of energy production and switch to renewable sources. However, their temporal availability does not match societal consumption needs, meaning that renewably generated energy must be stored in its main generation times and allocated during peak consumption periods. Electrochemical energy storage (EES) in general is well suited due to its infrastructural independence and scalability. The lithium ion battery (LIB) takes a special place, among EES systems due to its energy density and efficiency, but the scarcity and uneven geological occurrence of minerals and ores vital for many cell components, and hence the high and fluctuating costs will decelerate its further distribution.
The sodium ion battery (SIB) is a promising successor to LIB technology, as the fundamental setup and cell chemistry is similar in the two systems. Yet, the most widespread negative electrode material in LIBs, graphite, cannot be used in SIBs, as it cannot store sufficient amounts of sodium at reasonable potentials. Hence, another carbon allotrope, non-graphitizing or hard carbon (HC) is used in SIBs. This material consists of turbostratically disordered, curved graphene layers, forming regions of graphitic stacking and zones of deviating layers, so-called internal or closed pores.
The structural features of HC have a substantial impact of the charge-potential curve exhibited by the carbon when it is used as the negative electrode in an SIB. At defects and edges an adsorption-like mechanism of sodium storage is prevalent, causing a sloping voltage curve, ill-suited for the practical application in SIBs, whereas a constant voltage plateau of relatively high capacities is found immediately after the sloping region, which recent research attributed to the deposition of quasimetallic sodium into the closed pores of HC.
Literature on the general mechanism of sodium storage in HCs and especially the role of the closed pore is abundant, but the influence of the pore geometry and chemical nature of the HC on the low-potential sodium deposition is yet in an early stage. Therefore, the scope of this thesis is to investigate these relationships using suitable synthetic and characterization methods. Materials of precisely known morphology, porosity, and chemical structure are prepared in clear distinction to commonly obtained ones and their impact on the sodium storage characteristics is observed. Electrochemical impedance spectroscopy in combination with distribution of relaxation times analysis is further established as a technique to study the sodium storage process, in addition to classical direct current techniques, and an equivalent circuit model is proposed to qualitatively describe the HC sodiation mechanism, based on the recorded data. The obtained knowledge is used to develop a method for the preparation of closed porous and non-porous materials from open porous ones, proving not only the necessity of closed pores for efficient sodium storage, but also providing a method for effective pore closure and hence the increase of the sodium storage capacity and efficiency of carbon materials.
The insights obtained and methods developed within this work hence not only contribute to the better understanding of the sodium storage mechanism in carbon materials of SIBs, but can also serve as guidance for the design of efficient electrode materials.
Detecting and categorizing particular entities in the environment are important visual tasks that humans have had to solve at various points in our evolutionary time. The question arises whether characteristics of entities that were of ecological significance for humans play a particular role during the development of visual categorization.
The current project addressed this question by investigating the effects of developing visual abilities, visual properties and ecological significance on categorization early in life. Our stimuli were monochromatic photographs of structure-like assemblies and surfaces taken from three categories: vegetation, non-living natural elements, and artifacts. A set of computational and rated visual properties were assessed for these stimuli. Three empirical studies applied coherent research concepts and methods in young children and adults, comprising (a) two card-sorting tasks with preschool children (age: 4.1-6.1 years) and adults (age: 18-50 years) which assessed classification and similarity judgments, (b) a gaze contingent eye-tracking search task which investigated the impact of visual properties and category membership on 8-month-olds' ability to segregate visual structure. Because eye-tracking with infants still provides challenges, a methodological study (c) assessed the effect of infant eye-tracking procedures on data quality with 8- to 12-month-old infants and adults.
In the categorization tasks we found that category membership and visual properties impacted the performance of all participant groups. Sensitivity to the respective categories varied between tasks and over the age groups. For example, artifact images hindered infants' visual search but were classified best by adults, whereas sensitivity to vegetation was highest during similarity judgments. Overall, preschool children relied less on visual properties than adults, but some properties (e.g., rated depth, shading) were drawn upon similarly strong. In children and infants, depth predicted task performance stronger than shape-related properties. Moreover, children and infants were sensitive to variations in the complexity of low-level visual statistics. These results suggest that classification of visual structures, and attention to particular visual properties is affected by the functional or ecological significance these categories and properties may have for each of the respective age groups.
Based on this, the project highlights the importance of further developmental research on visual categorization with naturalistic, structure-like stimuli. As intended with the current work, this would allow important links between developmental and adult research.
Botulinum neurotoxin (BoNT) is produced by the anaerobic bacterium Clostridium botulinum. It is one of the most potent toxins found in nature and can enter motor neurons (MN) to cleave proteins necessary for neurotransmission, resulting in flaccid paralysis. The toxin has applications in both traditional and esthetic medicine. Since BoNT activity varies between batches despite identical protein concentrations, the activity of each lot must be assessed. The gold standard method is the mouse lethality assay, in which mice are injected with a BoNT dilution series to determine the dose at which half of the animals suffer death from peripheral asphyxia. Ethical concerns surrounding the use of animals in toxicity testing necessitate the creation of alternative model systems to measure the potency of BoNT.
Prerequisites of a successful model are that it is human specific; it monitors the complete toxic pathway of BoNT; and it is highly sensitive, at least in the range of the mouse lethality assay. One model system was developed by our group, in which human SIMA neuroblastoma cells were genetically modified to express a reporter protein (GLuc), which is packaged into neurosecretory vesicles, and which, upon cellular depolarization, can be released – or inhibited by BoNT – simultaneously with neurotransmitters. This assay has great potential, but includes the inherent disadvantages that the GLuc sequence was randomly inserted into the genome and the tumor cells only have limited sensitivity and specificity to BoNT. This project aims to improve these deficits, whereby induced pluripotent stem cells (iPSCs) were genetically modified by the CRISPR/Cas9 method to insert the GLuc sequence into the AAVS1 genomic safe harbor locus, precluding genetic disruption through non-specific integrations. Furthermore, GLuc was modified to associate with signal peptides that direct to the lumen of both large dense core vesicles (LDCV), which transport neuropeptides, and synaptic vesicles (SV), which package neurotransmitters. Finally, the modified iPSCs were differentiated into motor neurons (MNs), the true physiological target of BoNT, and hypothetically the most sensitive and specific cells available for the MoN-Light BoNT assay.
iPSCs were transfected to incorporate one of three constructs to direct GLuc into LDCVs, one construct to direct GLuc into SVs, and one “no tag” GLuc control construct. The LDCV constructs fused GLuc with the signal peptides for proopiomelanocortin (hPOMC-GLuc), chromogranin-A (CgA-GLuc), and secretogranin II (SgII-GLuc), which are all proteins found in the LDCV lumen. The SV construct comprises a VAMP2-GLuc fusion sequence, exploiting the SV membrane-associated protein synaptobrevin (VAMP2). The no tag GLuc expresses GLuc non-specifically throughout the cell and was created to compare the localization of vesicle-directed GLuc.
The clones were characterized to ensure that the GLuc sequence was only incorporated into the AAVS1 safe harbor locus and that the signal peptides directed GLuc to the correct vesicles. The accurate insertion of GLuc was confirmed by PCR with primers flanking the AAVS1 safe harbor locus, capable of simultaneously amplifying wildtype and modified alleles. The PCR amplicons, along with an insert-specific amplicon from candidate clones were Sanger sequenced to confirm the correct genomic region and sequence of the inserted DNA. Off-target integrations were analyzed with the newly developed dc-qcnPCR method, whereby the insert DNA was quantified by qPCR against autosomal and sex-chromosome encoded genes. While the majority of clones had off-target inserts, at least one on-target clone was identified for each construct.
Finally, immunofluorescence was utilized to localize GLuc in the selected clones. In iPSCs, the vesicle-directed GLuc should travel through the Golgi apparatus along the neurosecretory pathway, while the no tag GLuc should not follow this pathway. Initial analyses excluded the CgA-GLuc and SgII-GLuc clones due to poor quality protein visualization. The colocalization of GLuc with the Golgi was analyzed by confocal microscopy and quantified. GLuc was strongly colocalized with the Golgi in the hPOMC-GLuc clone (r = 0.85±0.09), moderately in the VAMP2-GLuc clone (r = 0.65±0.01), and, as expected, only weakly in the no tag GLuc clone (r = 0.44±0.10). Confocal microscopy of differentiated MNs was used to analyze the colocalization of GLuc with proteins associated with LDCVs and SVs, SgII in the hPOMC-GLuc clone (r = 0.85±0.08) and synaptophysin in the VAMP2-GLuc clone (r = 0.65±0.07). GLuc was also expressed in the same cells as the MN-associated protein, Islet1.
A significant portion of GLuc was found in the correct cell type and compartment. However, in the MoN-Light BoNT assay, the hPOMC-GLuc clone could not be provoked to reliably release GLuc upon cellular depolarization. The depolarization protocol for hPOMC-GLuc must be further optimized to produce reliable and specific release of GLuc upon exposure to a stimulus. On the other hand, the VAMP2-GLuc clone could be provoked to release GLuc upon exposure to the muscarinic and nicotinic agonist carbachol. Furthermore, upon simultaneous exposure to the calcium chelator EGTA, the carbachol-provoked release of GLuc could be significantly repressed, indicating the detection of GLuc was likely associated with vesicular fusion at the presynaptic terminal. The application of the VAMP2-GLuc clone in the MoN-Light BoNT assay must still be verified, but the results thus far indicate that this clone could be appropriate for the application of BoNT toxicity assessment.
Participation has become an orthodoxy in the field of development, an essential element of projects and programmes. This book analyses participation in development interventions as an institutionalised expectation – a rationalized myth – and examines how organisations on different levels of government process it. At least two different objectives of participation are appropriate and legitimate for international organisations in the field: the empowerment of local beneficiaries and the achievement of programme goals. Both integrate participatory forums into the organisational logic of development interventions. Local administrations react to the institutionalised expectation with means-ends decoupling, where participatory forums are implemented superficially but de facto remain marginalised in local administrative processes and activities. The book furthermore provides a thick description of the organisationality of participation in development interventions. Participatory forums are shown to be a form of partial organisation. They establish an order in the relationship between administrations and citizens through the introduction of rules and the creation of a defined membership. At the same time, this order is found to be fragile and subject to criticism and negotiation.
Due to global climate change providing food security for an increasing world population is a big challenge. Especially abiotic stressors have a strong negative effect on crop yield. To develop climate-adapted crops a comprehensive understanding of molecular alterations in the response of varying levels of environmental stresses is required. High throughput or ‘omics’ technologies can help to identify key-regulators and pathways of abiotic stress responses. In addition to obtain omics data also tools and statistical analyses need to be designed and evaluated to get reliable biological results.
To address these issues, I have conducted three different studies covering two omics technologies. In the first study, I used transcriptomic data from the two polymorphic Arabidopsis thaliana accessions, namely Col-0 and N14, to evaluate seven computational tools for their ability to map and quantify Illumina single-end reads. Between 92% and 99% of the reads were mapped against the reference sequence. The raw count distributions obtained from the different tools were highly correlated. Performing a differential gene expression analysis between plants exposed to 20 °C or 4°C (cold acclimation), a large pairwise overlap between the mappers was obtained. In the second study, I obtained transcript data from ten different Oryza sativa (rice) cultivars by PacBio Isoform sequencing that can capture full-length transcripts. De novo reference transcriptomes were reconstructed resulting in 38,900 to 54,500 high-quality isoforms per cultivar. Isoforms were collapsed to reduce sequence redundancy and evaluated, e.g. for protein completeness level (BUSCO), transcript length, and number of unique transcripts per gene loci. For the heat and drought tolerant aus cultivar N22, I identified around 650 unique and novel transcripts of which 56 were significantly differentially expressed in developing seeds during combined drought and heat stress. In the last study, I measured and analyzed the changes in metabolite profiles of eight rice cultivars exposed to high night temperature (HNT) stress and grown during the dry and wet season on the field in the Philippines. Season-specific changes in metabolite levels, as well as for agronomic parameters, were identified and metabolic pathways causing a yield decline at HNT conditions suggested.
In conclusion, the comparison of mapper performances can help plant scientists to decide on the right tool for their data. The de novo reconstruction of rice cultivars without a genome sequence provides a targeted, cost-efficient approach to identify novel genes responding to stress conditions for any organism. With the metabolomics approach for HNT stress in rice, I identified stress and season-specific metabolites which might be used as molecular markers for crop improvement in the future.
The development of type 2 diabetes (T2D) is driven by genetic as well as life style factors. However, even genetically identical female NZO mice on a high-fat diet show a broad variation in T2D onset. The main objective of this study was to elucidate and investigate early epigenetic determinants of type 2 diabetes. Prior to other experiments, early fat content of the liver (<55.2 HU) in combination with blood glucose concentrations (>8.8 mM) were evaluated as best predictors of diabetes in NZO females. Then, DNA methylome and transcriptome were profiled to identify molecular pathophysiological changes in the liver before diabetes onset. The major finding of this thesis is that alterations in the hepatic DNA methylome precede diabetes onset. Of particular interest were 702 differentially methylated regions (DMRs), of which 506 DMRs had genic localization. These inter-individual DMRs were enriched by fivefold in the KEGG pathway type 2 diabetes mellitus, independent of the level of gene expression, demonstrating an epigenetic predisposition toward diabetes. Interestingly, among the list of hepatic DMRs, eleven DMRs were associated with known imprinted genes in the mouse genome. Thereby, six DMRs (Nap1l5, Mest, Plagl1, Gnas, Grb10 and Slc38a4) localized to imprinting control regions, including five iDMRs that exhibited hypermethylation in livers of diabetes-prone mice. This suggests that gain of DNA methylation in multiple loci of the paternal alleles has unfavourable metabolic consequences for the offspring. Further, the comparative liver transcriptome analysis demonstrated differences in expression levels of 1492 genes related to metabolically relevant pathways, such as citrate cycle and fatty acid metabolism. The integration of hepatic transcriptome and DNA methylome indicated that 449 differentially expressed genes were potentially regulated by DNA methylation, including genes implicated in insulin signaling. In addition, liver transcriptomic profiling of diabetes-resistant and diabetes-prone mice revealed a potential transcriptional dysregulation of 17 hepatokines, in particular Hamp. The hepatic expression of Hamp was decreased by 52% in diabetes-prone mice, on account of an increase in DNA methylation of promoter CpG-118. Hence, HAMP protein levels were lower in mice prone to develop diabetes, which correlated to higher liver triglyceride levels.. In sum, the identified DNA methylation changes appear to collectively favor the initiation and progression of diabetes in female NZO mice. In near future, epigenetic biomarkers are likely to contribute to improved diagnosis for T2D.
Polymeric films and coatings derived from semi-crystalline oligomers are of relevance for medical and pharmaceutical applications. In this context, the material surface is of particular importance, as it mediates the interaction with the biological system. Two dimensional (2D) systems and ultrathin films are used to model this interface. However, conventional techniques for their preparation, such as spin coating or dip coating, have disadvantages, since the morphology and chain packing of the generated films can only be controlled to a limited extent and adsorption on the substrate used affects the behavior of the films. Detaching and transferring the films prepared by such techniques requires additional sacrificial or supporting layers, and free-standing or self supporting domains are usually of very limited lateral extension. The aim of this thesis is to study and modulate crystallization, melting, degradation and chemical reactions in ultrathin films of oligo(ε-caprolactone)s (OCL)s with different end-groups under ambient conditions. Here, oligomeric ultrathin films are assembled at the air-water interface using the Langmuir technique. The water surface allows lateral movement and aggregation of the oligomers, which, unlike solid substrates, enables dynamic physical and chemical interaction of the molecules. Parameters like surface pressure (π), temperature and mean molecular area (MMA) allow controlled assembly and manipulation of oligomer molecules when using the Langmuir technique. The π-MMA isotherms, Brewster angle microscopy (BAM), and interfacial infrared spectroscopy assist in detecting morphological and physicochemical changes in the film. Ultrathin films can be easily transferred to the solid silicon surface via Langmuir Schaefer (LS) method (horizontal substrate dipping). Here, the films transferred on silicon are investigated using atomic force microscopy (AFM) and optical microscopy and are compared to the films on the water surface.
The semi-crystalline morphology (lamellar thicknesses, crystal number densities, and lateral crystal dimensions) is tuned by the chemical structure of the OCL end-groups (hydroxy or methacrylate) and by the crystallization temperature (Tc; 12 or 21 °C) or MMAs. Compression to lower MMA of ~2 Å2, results in the formation of a highly crystalline film, which consists of tightly packed single crystals. Preparation of tightly packed single crystals on a cm2 scale is not possible by conventional techniques. Upon transfer to a solid surface, these films retain their crystalline morphology whereas amorphous films undergo dewetting.
The melting temperature (Tm) of OCL single crystals at the water and the solid surface is found proportional to the inverse crystal thickness and is generally lower than the Tm of bulk PCL. The impact of OCL end-groups on melting behavior is most noticeable at the air-solid interface, where the methacrylate end-capped OCL (OCDME) melted at lower temperatures than the hydroxy end-capped OCL (OCDOL). When comparing the underlying substrate, melting/recrystallization of OCL ultrathin films is possible at lower temperatures at the air water interface than at the air-solid interface, where recrystallization is not visible. Recrystallization at the air-water interface usually occurs at a higher temperature than the initial Tc.
Controlled degradation is crucial for the predictable performance of degradable polymeric biomaterials. Degradation of ultrathin films is carried out under acidic (pH ~ 1) or enzymatic catalysis (lipase from Pseudomonas cepcia) on the water surface or on a silicon surface as transferred films. A high crystallinity strongly reduces the hydrolytic but not the enzymatic degradation rate. As an influence of end-groups, the methacrylate end-capped linear oligomer, OCDME (~85 ± 2 % end-group functionalization) hydrolytically degrades faster than the hydroxy end capped linear oligomer, OCDOL (~95 ± 3 % end-group functionalization) at different temperatures. Differences in the acceleration of hydrolytic degradation of semi-crystalline films were observed upon complete melting, partial melting of the crystals, or by heating to temperatures close to Tm. Therefore, films of densely packed single crystals are suitable as barrier layers with thermally switchable degradation rates.
Chemical modification in ultrathin films is an intricate process applicable to connect functionalized molecules, impart stability or create stimuli-sensitive cross-links. The reaction of end-groups is explored for transferred single crystals on a solid surface or amorphous monolayer at the air-water interface. Bulky methacrylate end-groups are expelled to the crystal surface during chain-folded crystallization. The density of end-groups is inversely proportional to molecular weight and hence very pronounced for oligomers. The methacrylate end-groups at the crystal surface, which are present at high concentration, can be used for further chemical functionalization. This is demonstrated by fluorescence microscopy after reaction with fluorescein dimethacrylate. The thermoswitching behavior (melting and recrystallization) of fluorescein functionalized single crystals shows the temperature-dependent distribution of the chemically linked fluorescein moieties, which are accumulated on the surfaces of crystals, and homogeneously dispersed when the crystals are molten. In amorphous monolayers at the air-water interface, reversible cross-linking of hydroxy-terminated oligo(ε-caprolactone) monolayers using dialdehyde (glyoxal) lead to the formation of 2D networks. Pronounced contraction in the area occurred for 2D OCL films in dependence of surface pressure and time indicating the reaction progress. Cross linking inhibited crystallization and retarded enzymatic degradation of the OCL film. Altering the subphase pH to ~2 led to cleavage of the covalent acetal cross-links. Besides as model systems, these reversibly cross-linked films are applicable for drug delivery systems or cell substrates modulating adhesion at biointerfaces.
The present work focuses on minimising the usage of toxic chemicals by integration of the biobased monomers, derived from fatty acid esters, to photopolymerization processes, which are known to be nature friendly. Internal double bond present in the oleic acid was converted to more reactive (meth)acrylate or epoxy group. Biobased starting materials, functionalized by different pendant groups, were used for photopolymerizing formulations to design of new polymeric structures by using ultraviolet light emitting diode (UV-LED) (395 nm) via free radical polymerization or cationic polymerization.
New (meth)acrylates (2,3 and 4) consisting of two isomers, methyl 9-((meth)acryloyloxy)-10-hydroxyoctadecanoate / methyl 9-hydroxy-10-((meth)acryloyloxy)octadecanoate (2 and 3) and methyl 9-(1H-imidazol-1-yl)-10-(methacryloyloxy)octadecanoate / methyl 9-(methacryloyloxy)-10-(1H-imidazol-1-yl)octadecanoate (4), modified from oleic acid mix, and ionic liquid monomers (1a and 1b) bearing long alkyl chain were polymerized photochemically. New (meth)acrylates are based on vegetable oil, and ionic liquids (ILs) have nonvolatile behaviour. Therefore, both monomer types have green approach. Photoinitiated polymerization of new (meth)acrylates and ionic liquids was investigated in the presence of ethyl (2,4,6-trimethylbenzoyl) phenylphosphinate (Irgacure® TPO−L) or di(4-methoxybenzoyl)diethylgermane (Ivocerin®) as photoinitiator (PI). Additionally, the results were discussed in comparison with those obtained from commercial 1,6-hexanediol di(meth)acrylate (5 and 6) for deeper investigation of biobased monomer’s potential to substitute petroleum derived materials with renewable resources for possible coating applications. Kinetic study shows that methyl 9-(1H-imidazol-1-yl)-10-(methacryloyloxy)octadecanoate / methyl 9-(methacryloyloxy)-10-(1H-imidazol-1-yl)octadecanoate (4) and ionic liquids (1a and 1b) have quantitative conversion after irradiation process which is important for practical applications. On the other hand, heat generation occurs in a longer time during the polymerization of biobased systems or ILs.
The poly(meth)acrylates modified from (meth)acrylated fatty acid methyl ester monomers generally show a low glass transition temperature because of the presence of long aliphatic chain in the polymer structure. However, poly(meth)acrylates containing aromatic group have higher glass transition temperature. Therefore, new 4-(4-methacryloyloxyphenyl)-butan-2-one (7) was synthesized which can be a promising candidate for the green techniques, such as light induced polymerization. Photokinetic investigation of the new monomer, 4-(4-methacryloyloxyphenyl)-butan-2-one (7), was discussed using Irgacure® TPO−L or Ivocerin® as photoinitiator. The reactivity of that monomer was compared to commercial 2-phenoxyethyl methacrylate (8) and phenyl methacrylate (9) basis of the differences on monomer structures. The photopolymer of 4-(4-methacryloyloxyphenyl)-butan-2-one (7) might be an interesting candidate for the coating application with the properties of quantitative conversion and high molecular weight. It also shows higher glass transition temperature.
In addition to the linear systems based on renewable materials, new crosslinked polymers were also designed in this thesis. Therefore, isomer mixture consisting of ethane-1,2-diyl bis(9-methacryloyloxy-10-hydroxy octadecanoate), ethane-1,2-diyl 9-hydroxy-10-methacryloyloxy-9’-methacryloyloxy10’-hydroxy octadecanoate and ethane-1,2-diyl bis(9-hydroxy-10-methacryloyloxy octadecanoate) (10) was synthesized by derivation of the oleic acid which has not been previously described in the literature. Crosslinked material based on this biobased monomer was produced by photoinitiated free radical polymerization using Irgacure® TPO−L or Ivocerin® as photoinitiator. Furthermore, material properties were diversified by copolymerization of 10 with 4-(4-methacryloyloxyphenyl)-butan-2-one (7) or methyl 9-(1H-imidazol-1-yl)-10-(methacryloyloxy)octadecanoate / methyl 9-(methacryloyloxy)-10-(1H-imidazol-1-yl)octadecanoate (4). In addition to this, influence of comonomer with different chemical structure on the network system was investigated by analysis of thermo-mechanical properties, crosslink density and molecular weight between two crosslink junctions. An increase in the glass transition temperature caused by copolymerization of biobased monomer 10 with the excess amount of 4-(4-methacryloyloxyphenyl)-butan-2-one (7) was confirmed by both techniques, differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA). On the other hand, crosslink density decreased as a result of copolymerization reactions due to the reduction in the mean functionality of the system. Furthermore, surface characterization has been tested by contact angle measurements using solvents with different polarity.
This work also contributes to the limited data reported about cationic photopolymerization of the epoxidized vegetable oils in the literature in contrast to the widely investigation of thermal curing of the biorenewable epoxy monomers. In addition to the 9,10-epoxystearic acid methyl ester (11), a new monomer of bis-(9,10-epoxystearic acid) 1,2-ethanediyl ester (12) has been synthesized from oleic acid. These two biobased epoxies have been polymerized via cationic photoinitiated polymerization in the presence of bis(t-butyl)-iodonium-tetrakis(perfluoro-t-butoxy)aluminate ([Al(O-t-C4F9)4]-) and isopropylthioxanthone (ITX) as photinitiating system. Polymerization kinetic of 9,10-epoxystearic acid methyl ester (11) and bis-(9,10-epoxystearic acid) 1,2-ethanediyl ester (12) was investigated and compared with the kinetic of commercial monomers being 3,4-epoxycyclohexylmethyl-3’,4’-epoxycyclohexane carboxylate (13), 1,4-butanediol diglycidyl ether (14), and diglycidylether of bisphenol-A (15). Both biobased epoxies (11 and 12) showed higher conversion than cycloaliphatic epoxy (13), and lower reactivity than 1,4-butanediol diglycidyl ether (14). Additional network systems were designed by copolymerization of bis-(9,10-epoxystearic acid) 1,2-ethanediyl ester (12) and diglycidylether of bisphenol-A (15) in different molar ratios (1:1; 1:5; 1:9). It addresses that, final conversion is dependent on polymerization rate as well as physical processes such as vitrification during polymerization. Moreover, low glass transition temperature of homopolymer derived from bis-(9,10-epoxystearic acid) 1,2-ethanediyl ester (12) was successfully increased by copolymerization with diglycidylether bisphenol-A (15). On the other hand, the surface produced from bis-(9,10-epoxystearic acid) 1,2-ethanediyl ester (12) shows hydrophobic character. Higher concentration of biobased diepoxy (12) in the copolymerizing mixture decreases surface free energy. Network systems were also investigated according to the rubber elasticity theory. Crosslinked polymer derived from the mixture of bis-(9,10-epoxystearic acid) 1,2-ethanediyl ester (12) and diglycidylether of bisphenol-A (15) (molar ratio=1:5) exhibits almost ideal polymer network.
The objective of this book is to provide ICAO, States, competent authorities and aerodrome operators with a comprehensive overview of legal challenges related to international aerodrome planning. Answers to derived legal questions as well as recommendations thereafter shall help to enhance regulatory systems and to establish a safer aerodrome environment worldwide. Compliant aerodrome planning has an immense impact on the safety of passengers, personnel, aircraft – and of course the airport. Achieving a high safety standard is crucial, as many incidents and accidents in aviation happen at or in the vicinity of airports. Currently, more than 40% of the ICAO Member States do not fully comply with international legal requirements for aerodrome planning. Representatives of ICAO and States, as well as aerodrome and authority personnel, will understand why compliance with the different legal facets of aerodrome planning is challenging and learn how shortcomings can be solved.
The Internet of Things (IoT) is a system of physical objects that can be discovered, monitored, controlled, or interacted with by electronic devices that communicate over various networking interfaces and eventually can be connected to the wider Internet. [Guinard and Trifa, 2016]. IoT devices are equipped with sensors and/or actuators and may be constrained in terms of memory, computational power, network bandwidth, and energy. Interoperability can help to manage such heterogeneous devices. Interoperability is the ability of different types of systems to work together smoothly. There are four levels of interoperability: physical, network and transport, integration, and data. The data interoperability is subdivided into syntactic and semantic data. Semantic data describes the meaning of data and the common understanding of vocabulary e.g. with the help of dictionaries, taxonomies, ontologies. To achieve interoperability, semantic interoperability is necessary.
Many organizations and companies are working on standards and solutions for interoperability in the IoT. However, the commercial solutions produce a vendor lock-in. They focus on centralized approaches such as cloud-based solutions. This thesis proposes a decentralized approach namely Edge Computing. Edge Computing is based on the concepts of mesh networking and distributed processing. This approach has an advantage that information collection and processing are placed closer to the sources of this information. The goals are to reduce traffic, latency, and to be robust against a lossy or failed Internet connection.
We see management of IoT devices from the network configuration management perspective. This thesis proposes a framework for network configuration management of heterogeneous, constrained IoT devices by using semantic descriptions for interoperability. The MYNO framework is an acronym for MQTT, YANG, NETCONF and Ontology. The NETCONF protocol is the IETF standard for network configuration management. The MQTT protocol is the de-facto standard in the IoT. We picked up the idea of the NETCONF-MQTT bridge, originally proposed by Scheffler and Bonneß[2017], and extended it with semantic device descriptions. These device descriptions provide a description of the device capabilities. They are based on the oneM2M Base ontology and formalized by the Semantic Web Standards.
The novel approach is using a ontology-based device description directly on a constrained device in combination with the MQTT protocol. The bridge was extended in order to query such descriptions. Using a semantic annotation, we achieved that the device capabilities are self-descriptive, machine readable and re-usable.
The concept of a Virtual Device was introduced and implemented, based on semantic device descriptions. A Virtual Device aggregates the capabilities of all devices at the edge network and contributes therefore to the scalability. Thus, it is possible to control all devices via a single RPC call.
The model-driven NETCONF Web-Client is generated automatically from this YANG model which is generated by the bridge based on the semantic device description. The Web-Client provides a user-friendly interface, offers RPC calls and displays sensor values. We demonstrate the feasibility of this approach in different use cases: sensor and actuator scenarios, as well as event configuration and triggering.
The semantic approach results in increased memory overhead. Therefore, we evaluated CBOR and RDF HDT for optimization of ontology-based device descriptions for use on constrained devices. The evaluation shows that CBOR is not suitable for long strings and RDF HDT is a promising candidate but is still a W3C Member Submission. Finally, we used an optimized JSON-LD format for the syntax of the device descriptions.
One of the security tasks of network management is the distribution of firmware updates. The MYNO Update Protocol (MUP) was developed and evaluated on constrained devices CC2538dk and 6LoWPAN. The MYNO update process is focused on freshness and authenticity of the firmware. The evaluation shows that it is challenging but feasible to bring the firmware updates to constrained devices using MQTT. As a new requirement for the next MQTT version, we propose to add a slicing feature for the better support of constrained devices. The MQTT broker should slice data to the maximum packet size specified by the device and transfer it slice-by-slice.
For the performance and scalability evaluation of MYNO framework, we setup the High Precision Agriculture demonstrator with 10 ESP-32 NodeMCU boards at the edge of the network. The ESP-32 NodeMCU boards, connected by WLAN, were equipped with six sensors and two actuators. The performance evaluation shows that the processing of ontology-based descriptions on a Raspberry Pi 3B with the RDFLib is a challenging task regarding computational power. Nevertheless, it is feasible because it must be done only once per device during the discovery process.
The MYNO framework was tested with heterogeneous devices such as CC2538dk from Texas Instruments, Arduino Yún Rev 3, and ESP-32 NodeMCU, and IP-based networks such as 6LoWPAN and WLAN.
Summarizing, with the MYNO framework we could show that the semantic approach on constrained devices is feasible in the IoT.
Permafrost is warming globally, which leads to widespread permafrost thaw and impacts the surrounding landscapes, ecosystems and infrastructure. Especially ice-rich permafrost is vulnerable to rapid and abrupt thaw, resulting from the melting of excess ground ice. Local remote sensing studies have detected increasing rates of abrupt permafrost disturbances, such as thermokarst lake change and drainage, coastal erosion and RTS in the last two decades. All of which indicate an acceleration of permafrost degradation.
In particular retrogressive thaw slumps (RTS) are abrupt disturbances that expand by up to several meters each year and impact local and regional topographic gradients, hydrological pathways, sediment and nutrient mobilisation into aquatic systems, and increased permafrost carbon mobilisation. The feedback between abrupt permafrost thaw and the carbon cycle is a crucial component of the Earth system and a relevant driver in global climate models. However, an assessment of RTS at high temporal resolution to determine the dynamic thaw processes and identify the main thaw drivers as well as a continental-scale assessment across diverse permafrost regions are still lacking.
In northern high latitudes optical remote sensing is restricted by environmental factors and frequent cloud coverage. This decreases image availability and thus constrains the application of automated algorithms for time series disturbance detection for large-scale abrupt permafrost disturbances at high temporal resolution. Since models and observations suggest that abrupt permafrost disturbances will intensify, we require disturbance products at continental-scale, which allow for meaningful integration into Earth system models.
The main aim of this dissertation therefore, is to enhance our knowledge on the spatial extent and temporal dynamics of abrupt permafrost disturbances in a large-scale assessment. To address this, three research objectives were posed:
1. Assess the comparability and compatibility of Landsat-8 and Sentinel-2 data for a combined use in multi-spectral analysis in northern high latitudes.
2. Adapt an image mosaicking method for Landsat and Sentinel-2 data to create combined mosaics of high quality as input for high temporal disturbance assessments in northern high latitudes.
3. Automatically map retrogressive thaw slumps on the landscape-scale and assess their high temporal thaw dynamics.
We assessed the comparability of Landsat-8 and Sentinel-2 imagery by spectral comparison of corresponding bands. Based on overlapping same-day acquisitions of Landsat-8 and Sentinel-2 we derived spectral bandpass adjustment coefficients for North Siberia to adjust Sentinel-2 reflectance values to resemble Landsat-8 and harmonise the two data sets. Furthermore, we adapted a workflow to combine Landsat and Sentinel-2 images to create homogeneous and gap-free annual mosaics. We determined the number of images and cloud-free pixels, the spatial coverage and the quality of the mosaic with spectral comparisons to demonstrate the relevance of the Landsat+Sentinel-2 mosaics. Lastly, we adapted the automatic disturbance detection algorithm LandTrendr for large-scale RTS identification and mapping at high temporal resolution. For this, we modified the temporal segmentation algorithm for annual gradual and abrupt disturbance detection to incorporate the annual Landsat+Sentinel-2 mosaics. We further parametrised the temporal segmentation and spectral filtering for optimised RTS detection, conducted further spatial masking and filtering, and implemented a binary object classification algorithm with machine-learning to derive RTS from the LandTrendr disturbance output. We applied the algorithm to North Siberia, covering an area of 8.1 x 106 km2.
The spectral band comparison between same-day Landsat-8 and Sentinel-2 acquisitions already showed an overall good fit between both satellite products. However, applying the acquired spectral bandpass coefficients for adjustment of Sentinel-2 reflectance values, resulted in a near-perfect alignment between the same-day images. It can therefore be concluded that the spectral band adjustment succeeds in adjusting Sentinel-2 spectral values to those of Landsat-8 in North Siberia.
The number of available cloud-free images increased steadily between 1999 and 2019, especially intensified after 2016 with the addition of Sentinel-2 images. This signifies a highly improved input database for the mosaicking workflow. In a comparison of annual mosaics, the Landsat+Sentinel-2 mosaics always fully covered the study areas, while Landsat-only mosaics contained data-gaps for the same years. The spectral comparison of input images and Landsat+Sentinel-2 mosaic showed a high correlation between the input images and the mosaic bands, testifying mosaicking results of high quality. Our results show that especially the mosaic coverage for northern, coastal areas was substantially improved with the Landsat+Sentinel-2 mosaics. By combining data from both Landsat and Sentinel-2 sensors we reliably created input mosaics at high spatial resolution for comprehensive time series analyses.
This research presents the first automatically derived assessment of RTS distribution and temporal dynamics at continental-scale. In total, we identified 50,895 RTS, primarily located in ice-rich permafrost regions, as well as a steady increase in RTS-affected areas between 2001 and 2019 across North Siberia. From 2016 onward the RTS area increased more abruptly, indicating heightened thaw slump dynamics in this period. Overall, the RTS-affected area increased by 331 % within the observation period. Contrary to this, five focus sites show spatiotemporal variability in their annual RTS dynamics, alternating between periods of increased and decreased RTS development. This suggests a close relationship to varying thaw drivers. The majority of identified RTS was active from 2000 onward and only a small proportion initiated during the assessment period. This highlights that the increase in RTS-affected area was mainly caused by enlarging existing RTS and not by newly initiated RTS.
Overall, this research showed the advantages of combining Landsat and Sentinel-2 data in northern high latitudes and the improvements in spatial and temporal coverage of combined annual mosaics. The mosaics build the database for automated disturbance detection to reliably map RTS and other abrupt permafrost disturbances at continental-scale. The assessment at high temporal resolution further testifies the increasing impact of abrupt permafrost disturbances and likewise emphasises the spatio-temporal variability of thaw dynamics across landscapes. Obtaining such consistent disturbance products is necessary to parametrise regional and global climate change models, for enabling an improved representation of the permafrost thaw feedback.
This dissertation was carried out as part of the international and interdisciplinary graduate school StRATEGy. This group has set itself the goal of investigating geological processes that take place on different temporal and spatial scales and have shaped the southern central Andes. This study focuses on claystones and carbonates of the Yacoraite Fm. that were deposited between Maastricht and Dan in the Cretaceous Salta Rift Basin. The former rift basin is located in northwest Argentina and is divided into the sub-basins Tres Cruces, Metán-Alemanía and Lomas de Olmedo. The overall motivation for this study was to gain new knowledge about the evolution of marine and lacustrine conditions during the Yacoraite Fm. Deposit in the Tres Cruces and Metán-Alemanía sub-basins. Other important aspects that were examined within the scope of this dissertation are the conversion of organic matter from Yacoraite Fm. into oil and its genetic relationship to selected oils produced and natural oil spills. The results of my study show that the Yacoraite Fm. began to be deposited under marine conditions and that a lacustrine environment developed by the end of the deposition in the Tres Cruces and Metán-Alemanía Basins. In general, the kerogen of Yacoraite Fm. consists mainly of the kerogen types II, III and II / III mixtures. Kerogen type III is mainly found in samples from the Yacoraite Fm., whose TOC values are low. Due to the adsorption of hydrocarbons on the mineral surfaces (mineral matrix effect), the content of type III kerogen with Rock-Eval pyrolysis in these samples could be overestimated. Investigations using organic petrography show that the organic particles of Yacoraite Fm. mainly consist of alginites and some vitrinite-like particles. The pyrolysis GC of the rock samples showed that the Yacoraite Fm. generates low-sulfur oils with a predominantly low-wax, paraffinic-naphthenic-aromatic composition and paraffinic wax-rich oils. Small proportions of paraffinic, low-wax oils and a gas condensate-generating facies are also predicted. Here, too, mineral matrix effects were taken into account, which can lead to a quantitative overestimation of the gas-forming character.
The results of an additional 1D tank modeling carried out show that the beginning (10% TR) of the oil genesis took place between ≈10 Ma and ≈4 Ma. Most of the oil (from ≈50% to 65%) was generated prior to the development of structural traps formed during the Plio-Pleistocene Diaguita deformation phase. Only ≈10% of the total oil generated was formed and potentially trapped after the formation of structural traps. Important factors in the risk assessment of this petroleum system, which can determine the small amounts of generated and migrated oil, are the generally low TOC contents and the variable thickness of the Yacoraite Fm. Additional risks are associated with a low density of information about potentially existing reservoir structures and the quality of the overburden.
River flooding poses a threat to numerous cities and communities all over the world. The detection, quantification and attribution of changes in flood characteristics is key to assess changes in flood hazard and help affected societies to timely mitigate and adapt to emerging risks. The Rhine River is one of the major European rivers and numerous large cities reside at its shores. Runoff from several large tributaries superimposes in the main channel shaping the complex from regime. Rainfall, snowmelt as well as ice-melt are important runoff components. The main objective of this thesis is the investigation of a possible transient merging of nival and pluvial Rhine flood regimes under global warming. Rising temperatures cause snowmelt to occur earlier in the year and rainfall to be more intense. The superposition of snowmelt-induced floods originating from the Alps with more intense rainfall-induced runoff from pluvial-type tributaries might create a new flood type with potentially disastrous consequences.
To introduce the topic of changing hydrological flow regimes, an interactive web application that enables the investigation of runoff timing and runoff season- ality observed at river gauges all over the world is presented. The exploration and comparison of a great diversity of river gauges in the Rhine River Basin and beyond indicates that river systems around the world undergo fundamental changes. In hazard and risk research, the provision of background as well as real-time information to residents and decision-makers in an easy accessible way is of great importance. Future studies need to further harness the potential of scientifically engineered online tools to improve the communication of information related to hazards and risks.
A next step is the development of a cascading sequence of analytical tools to investigate long-term changes in hydro-climatic time series. The combination of quantile sampling with moving average trend statistics and empirical mode decomposition allows for the extraction of high resolution signals and the identification of mechanisms driving changes in river runoff. Results point out that the construction and operation of large reservoirs in the Alps is an important factor redistributing runoff from summer to winter and hint at more (intense) rainfall in recent decades, particularly during winter, in turn increasing high runoff quantiles. The development and application of the analytical sequence represents a further step in the scientific quest to disentangling natural variability, climate change signals and direct human impacts.
The in-depth analysis of in situ snow measurements and the simulations of the Alpine snow cover using a physically-based snow model enable the quantification of changes in snowmelt in the sub-basin upstream gauge Basel. Results confirm previous investigations indicating that rising temperatures result in a decrease in maximum melt rates. Extending these findings to a catchment perspective, a threefold effect of rising temperatures can be identified: snowmelt becomes weaker, occurs earlier and forms at higher elevations. Furthermore, results indicate that due to the wide range of elevations in the basin, snowmelt does not occur simultaneously at all elevation, but elevation bands melt together in blocks. The beginning and end of the release of meltwater seem to be determined by the passage of warm air masses, and the respective elevation range affected by accompanying temperatures and snow availability. Following those findings, a hypothesis describing elevation-dependent compensation effects in snowmelt is introduced: In a warmer world with similar sequences of weather conditions, snowmelt is moved upward to higher elevations, i.e., the block of elevation bands providing most water to the snowmelt-induced runoff is located at higher elevations. The movement upward the elevation range makes snowmelt in individual elevation bands occur earlier. The timing of the snowmelt-induced runoff, however, stays the same. Meltwater from higher elevations, at least partly, replaces meltwater from elevations below.
The insights on past and present changes in river runoff, snow covers and underlying mechanisms form the basis of investigations of potential future changes in Rhine River runoff. The mesoscale Hydrological Model (mHM) forced with an ensemble of climate projection scenarios is used to analyse future changes in streamflow, snowmelt, precipitation and evapotranspiration at 1.5, 2.0 and
3.0 ◦ C global warming. Simulation results suggest that future changes in flood characteristics in the Rhine River Basin are controlled by increased precipitation amounts on the one hand, and reduced snowmelt on the other hand. Rising temperatures deplete seasonal snowpacks. At no time during the year, a warming climate results in an increase in the risk of snowmelt-driven flooding. Counterbalancing effects between snowmelt and precipitation often result in only little and transient changes in streamflow peaks. Although, investigations point at changes in both rainfall and snowmelt-driven runoff, there are no indications of a transient merging of nival and pluvial Rhine flood regimes due to climate warming. Flooding in the main tributaries of the Rhine, such as the Moselle River, as well as the High Rhine is controlled by both precipitation and snowmelt. Caution has to be exercised labelling sub-basins such as the Moselle catchment as purely pluvial-type or the Rhine River Basin at Basel as purely nival-type. Results indicate that this (over-) simplifications can entail misleading assumptions with regard to flood-generating mechanisms and changes in flood hazard. In the framework of this thesis, some progress has been made in detecting, quantifying and attributing past, present and future changes in Rhine flow/flood characteristics. However, further studies are necessary to pin down future changes in the flood genesis of Rhine floods, particularly very rare events.
Learning analytics at scale
(2021)
Digital technologies are paving the way for innovative educational approaches. The learning format of Massive Open Online Courses (MOOCs) provides a highly accessible path to lifelong learning while being more affordable and flexible than face-to-face courses. Thereby, thousands of learners can enroll in courses mostly without admission restrictions, but this also raises challenges. Individual supervision by teachers is barely feasible, and learning persistence and success depend on students' self-regulatory skills. Here, technology provides the means for support. The use of data for decision-making is already transforming many fields, whereas in education, it is still a young research discipline. Learning Analytics (LA) is defined as the measurement, collection, analysis, and reporting of data about learners and their learning contexts with the purpose of understanding and improving learning and learning environments. The vast amount of data that MOOCs produce on the learning behavior and success of thousands of students provides the opportunity to study human learning and develop approaches addressing the demands of learners and teachers.
The overall purpose of this dissertation is to investigate the implementation of LA at the scale of MOOCs and to explore how data-driven technology can support learning and teaching in this context. To this end, several research prototypes have been iteratively developed for the HPI MOOC Platform. Hence, they were tested and evaluated in an authentic real-world learning environment. Most of the results can be applied on a conceptual level to other MOOC platforms as well. The research contribution of this thesis thus provides practical insights beyond what is theoretically possible. In total, four system components were developed and extended:
(1) The Learning Analytics Architecture: A technical infrastructure to collect, process, and analyze event-driven learning data based on schema-agnostic pipelining in a service-oriented MOOC platform. (2) The Learning Analytics Dashboard for Learners: A tool for data-driven support of self-regulated learning, in particular to enable learners to evaluate and plan their learning activities, progress, and success by themselves. (3) Personalized Learning Objectives: A set of features to better connect learners' success to their personal intentions based on selected learning objectives to offer guidance and align the provided data-driven insights about their learning progress. (4) The Learning Analytics Dashboard for Teachers: A tool supporting teachers with data-driven insights to enable the monitoring of their courses with thousands of learners, identify potential issues, and take informed action.
For all aspects examined in this dissertation, related research is presented, development processes and implementation concepts are explained, and evaluations are conducted in case studies. Among other findings, the usage of the learner dashboard in combination with personalized learning objectives demonstrated improved certification rates of 11.62% to 12.63%. Furthermore, it was observed that the teacher dashboard is a key tool and an integral part for teaching in MOOCs. In addition to the results and contributions, general limitations of the work are discussed—which altogether provide a solid foundation for practical implications and future research.
Magmatic continental rifts often constitute the earliest stage of nascent plate boundaries. These extensional tectonic provinces are characterized by ubiquitous normal faulting and volcanic activity; the spatial pattern, the geometry, and the age of these normal faults can help to unravel the spatiotemporal relationships between extensional deformation, magmatism, and long-wavelength crustal deformation of continental rift provinces. This study focuses on the active faulting in the Kenya Rift of the Cenozoic East African Rift System (EARS) with a focus on the mid-Pleistocene to the present-day.
To examine the early stages of continental break-up in the EARS, this thesis presents a time-averaged minimum extension rate for the inner graben of the Northern Kenya Rift (NKR) for the last 0.5 m.y. Using the TanDEM-X digital elevation model, fault-scarp geometries and associated throws are determined across the volcano-tectonic axis of the inner graben of the NKR. By integrating existing geochronology of faulted units with new ⁴⁰Ar/³⁹Ar radioisotopic dates, time-averaged extension rates are calculated. This study reveals that in the inner graben of the NKR, the long-term extension rate based on mid-Pleistocene to recent brittle deformation has minimum values of 1.0 to 1.6 mm yr⁻¹, locally with values up to 2.0 mm yr⁻¹. In light of virtually inactive border faults of the NKR, we show that extension is focused in the region of the active volcano-tectonic axis in the inner graben, thus highlighting the maturing of continental rifting in the NKR.
The phenomenon of focused extension is further investigated with a structural analysis of the youngest volcanic manifestations of the Kenya Rift, their relationship with extensional structures, and their overprint by Holocene faulting. In this context I analyzed the fault characteristics at the ~36 ka old Menengai Caldera and adjacent areas in the Central Kenya Rift using detailed field mapping and a structure-from-motion-based DEM generated from UAV data. In general, the Holocene intra-rift normal faults are dip-slip faults which strike NNE and thus reflect the present-day tectonic stress field; however, inside Menengai caldera persistent magmatic activity and magmatic resurgence overprints these young structures significantly. The caldera is located at the center of an actively extending rift segment and this and the other volcanic edifices of the Kenya Rift may constitute nucleation points of faulting an magmatic extensional processes that ultimately lead into a future stage of magma-assisted rifting.
When viewed at the scale of the entire Kenya Rift the protracted normal faulting in this region compartmentalizes the larger rift depressions, and influences the sedimentology and the hydrology of the intra-rift basins at a scale of less than 100 km. In the present day, most of the fault-bounded sub-basins of the Kenya Rift are hydrologically isolated due to this combination of faulting and magmatic activity that has generated efficient hydrological barriers that maintain these basins as semi-independent geomorphic entities. This isolation, however, was overcome during wetter climatic conditions during the past when the basins were transiently connected. I therefore also investigated the hydrological connectivity of the rift basins during the African Humid Period of the early Holocene, when climate was wetter. With the help of DEM analysis, lake-highstand indicators, radiocarbon dating, and a review of the fossil record, two lake-river-cascades could be identified: one directed southward, and one directed northward. Both cascades connected presently isolated rift basins during the early Holocene via spillovers of lakes and incised river gorges. This hydrological connection fostered the dispersal of aquatic faunas along the rift, and in addition, the water divide between the two river systems represented the only terrestrial dispersal corridor across the Kenya Rift. The reconstruction explains isolated distributions of Nilotic fish species in Kenya Rift lakes and of Guineo-Congolian mammal species in forests east of the Kenya Rift. On longer timescales, repeated episodes of connectivity and isolation must have occurred. To address this problem I participated in research to analyze a sediment drill core from the Koora basin of the Southern Kenya Rift, which provides a paleo-environmental record of the last 1 Ma. Based on this record it can be concluded that at ~400 ka relatively stable environmental conditions were disrupted by tectonic, hydrological, and ecological changes, resulting in increasingly large and frequent fluctuations in water availability, grassland communities, and woody plant cover. The major environmental shifts reflected in the drill core data coincide with phases where volcano-tectonic activity affected the basin. This thesis therefore shows how protracted extensional tectonic processes and the resulting geomorphologic conditions can affect the hydrology, the paleo-environment and the biodiversity of extensional zones in Kenya and elsewhere.
Learning to read in German
(2021)
In the present dissertation, the development of eye movement behavior and the perceptual span of German beginning readers was investigated in Grades 1 to 3 (Study 1) and longitudinally within a one-year time interval (Study 2), as well as in relation to intrinsic and extrinsic reading motivation (Study 3). The presented results are intended to fill the gap of only sparse information on young readers’ eye movements and completely missing information on German young readers’ perceptual span and its development. On the other hand, reading motivation data have been scrutinized with respect to reciprocal effects on reading comprehension but not with respect to more immediate, basic cognitive processing (e.g., word decoding) that is indicated by different eye movement measures. Based on a longitudinal study design, children in Grades 1–3 participated in a moving window reading experiment with eye movement recordings in two successive years. All children were participants of a larger longitudinal study on intrapersonal developmental risk factors in childhood and adolescence (PIER study). Motivation data and other psychometric reading data were collected during individual inquiries and tests at school. Data analyses were realized in three separate studies that focused on different but related aspects of reading and perceptual span development. Study 1 presents the first cross-sectional report on the perceptual span of beginning German readers. The focus was on reading rate changes in Grades 1 to 3 and on the issue of the onset of the perceptual span development and its dependence on basic foveal reading processes. Study 2 presents a successor of Study 1 providing first longitudinal data of the perceptual span in elementary school children. It also includes information on the stability of observed and predicted reading rates and perceptual span sizes and introduces a new measure of the perceptual span based on nonlinear mixed-effects models. Another issue addressed in this study is the longitudinal between-group comparison of slower and faster readers which refers to the detection of developmental patterns. Study 3 includes longitudinal reading motivation data and investigates the relation between different eye movement measures including perceptual span and intrinsic as well as extrinsic reading motivation. In Study 1, a decelerated increase in reading rate was observed between Grades 1 to 3. Grade effects were also reported for saccade length, refixation probability, and different fixation duration measures. With higher grade, mean saccade length increased, whereas refixation probability, first-fixation duration, gaze duration, and total reading time decreased. Perceptual span development was indicated by an increase in window size effects with grade level. Grade level differences with respect to window size effects were stronger between Grades 2 and 3 than between Grades 1 and 2. These results were replicated longitudinally in Study 2. Again, perceptual span size significantly changed between Grades 2 and 3, but not between Grades 1 and 2 or Grades 3 and 4. Observed and predicted reading rates were found to be highly stable after first grade, whereas stability of perceptual span was only moderate for all grade levels. Group differences between slower and faster readers in Year 1 remained observable in Year 2 showing a pattern of stable achievement differences rather than a compensatory pattern. Between Grades 2 and 3, between-group differences in reading rate even increased resulting in a Matthew effect. A similar effect was observed for perceptual span development between Grades 3 and 4. Finally, in Study 3, significant relations between beginning readers’ eye movements and their reading motivation were observed. In both years of measurement, higher intrinsic reading motivation was related to more skilled eye movement patterns as indicated by short fixations, longer saccades, and higher reading rates. In Year 2, intrinsic reading motivation was also significantly and negatively correlated with refixation probability. These correlational patterns were confirmed in cross-sectional linear models controlling for grade level and reading amount and including both reading motivation measures, extrinsic and intrinsic motivation. While there were significant positive relations between intrinsic reading motivation and word decoding as indicated by the above stated eye movement measures, extrinsic reading motivation only predicted variance in eye movements in Year 2 (significant for fixation durations and reading rate), with a consistently opposite pattern of effects as compared to intrinsic reading motivation. Finally, longitudinal effects of Year 1 intrinsic reading motivation on Year 2 word decoding were observed for gaze duration, total reading time, refixation probability, and perceptual span within cross-lagged panel models. These effects were reciprocal because all eye movement measures significantly predicted variance in intrinsic reading motivation. Extrinsic reading motivation in Year 1 did not affect any eye movement measure in Year 2, and vice versa, except for a significant, negative relation with perceptual span. Concluding, the present dissertation demonstrates that largest gains in reading development in terms of eye movement changes are observable between Grades 1 and 2. Together with the observed pattern of stable differences between slower and faster readers and a widening achievement gap between Grades 2 and 3 for reading rate, these results underline the importance of the first year(s) of formal reading instruction. The development of the perceptual span lags behind as it is most apparent between Grades 2 and 3. This suggests that efficient parafoveal processing presupposes a certain degree of foveal reading proficiency (e.g., word decoding). Finally, this dissertation demonstrates that intrinsic reading motivation—but not extrinsic motivation—effectively supports the development of skilled reading.
By regulating the concentration of carbon in our atmosphere, the global carbon cycle drives changes in our planet’s climate and habitability. Earth surface processes play a central, yet insufficiently constrained role in regulating fluxes of carbon between terrestrial reservoirs and the atmosphere. River systems drive global biogeochemical cycles by redistributing significant masses of carbon across the landscape. During fluvial transit, the balance between carbon oxidation and preservation determines whether this mass redistribution is a net atmospheric CO2 source or sink. Existing models for fluvial carbon transport fail to integrate the effects of sediment routing processes, resulting in large uncertainties in fluvial carbon fluxes to the oceans.
In this Ph.D. dissertation, I address this knowledge gap through three studies that focus on the timescale and routing pathways of fluvial mass transfer and show their effect on the composition and fluxes of organic carbon exported by rivers. The hypotheses posed in these three studies were tested in an analog lowland alluvial river system – the Rio Bermejo in Argentina. The Rio Bermejo annually exports more than 100 Mt of sediment and organic matter from the central Andes, and transports this material nearly 1300 km downstream across the lowland basin without influence from tributaries, allowing me to isolate the effects of geomorphic processes on fluvial organic carbon cycling. These studies focus primarily on the geochemical composition of suspended sediment collected from river depth profiles along the length of the Rio Bermejo.
In Chapter 3, I aimed to determine the mean fluvial sediment transit time for the Rio Bermejo and evaluate the geomorphic processes that regulate the rate of downstream sediment transfer. I developed a framework to use meteoric cosmogenic 10Be (10Bem) as a chronometer to track the duration of sediment transit from the mountain front downstream along the ~1300 km channel of the Rio Bermejo. I measured 10Bem concentrations in suspended sediment sampled from depth profiles, and found a 230% increase along the fluvial transit pathway. I applied a simple model for the time-dependent accumulation of 10Bem on the floodplain to estimate a mean sediment transit time of 8.5±2.2 kyr. Furthermore, I show that sediment transit velocity is influenced by lateral migration rate and channel morphodynamics. This approach to measuring sediment transit time is much more precise than other methods previously used and shows promise for future applications.
In Chapter 4, I aimed to quantify the effects of hydrodynamic sorting on the composition and quantity of particulate organic carbon (POC) export transported by lowland rivers. I first used scanning electron miscroscopy (SEM) coupled with nanoscale secondary ion mass spectrometry (NanoSIMS) analyses to show that the Bermejo transports two principal types of POC: 1) mineral-bound organic carbon associated with <4 µm, platy grains, and 2) coarse discrete organic particles. Using n-alkane stable isotope data and particle shape analysis, I showed that these two carbon pools are vertically sorted in the water column, due to differences in particle settling velocity. This vertical sorting may drive modern POC to be transported efficiently from source-to-sink, driving efficient CO2 drawdown. Simultaneously, vertical sorting may drive degraded, mineral-bound POC to be deposited overbank and stored on the floodplain for centuries to millennia, resulting in enhanced POC remineralization. In the Rio Bermejo, selective deposition of coarse material causes the proportion of mineral-bound POC to increase with distance downstream, but the majority of exported POC is composed of discrete organic particles, suggesting that the river is a net carbon sink. In summary, this study shows that selective deposition and hydraulic sorting control the composition and fate of fluvial POC during fluvial transit.
In Chapter 5, I characterized and quantified POC transformation and oxidation during fluvial transit. I analyzed the radiocarbon content and stable carbon isotopic composition of Rio Bermejo suspended sediment and found that POC ages during fluvial transit, but is also degraded and oxidized during transient floodplain storage. Using these data, I developed a conceptual model for fluvial POC cycling that allows the estimation of POC oxidation relative to POC export, and ultimately reveals whether a river is a net source or sink of CO2 to the atmosphere. Through this study, I found that the Rio Bermejo annually exports more POC than is oxidized during transit, largely due to high rates of lateral migration that cause erosion of floodplain vegetation and soil into the river. These results imply that human engineering of rivers could alter the fluvial carbon balance, by reducing lateral POC inputs and increasing the mean sediment transit time.
Together, these three studies quantitatively link geomorphic processes to rates of POC transport and degradation across sub-annual to millennial time scales and nanoscale to 103 km spatial scales, laying the groundwork for a global-scale fluvial organic carbon cycling model.
Mycotoxins are secondary metabolites produced by several filamentous fungal species, thus occurring ubiquitously in the environment and food. While the heterogeneous group shows differences in their bioavailability and toxicity, the low-molecular-weight xenobiotics are capable of impacting human and animal health acutely and chronically. Therefore, maximum levels for the major mycotoxins in food and feed are regulated in the current European legislation. Besides free mycotoxins, naturally occurring modified mycotoxins are gaining more attention in recent years. Modified mycotoxins constitute toxins altered by plants, microorganisms, and living organisms in different metabolic pathways or food processing steps. The toxicological relevant compounds often co-occur with their free forms in infested food and feed. Thus, the toxins may contribute to the overall toxicity of mycotoxins, wherefore their presence and toxicity should be considered in risk assessment. Until now, however, there are no regulated limits for modified mycotoxins within the European Union. In this thesis, rapid, sensitive, and robust methods for the analysis of mycotoxins and their modified forms were developed and validated using state-of-the-art high performance liquid chromatography tandem mass spectrometry (LC-MS/MS) systems. Firstly, two analytical methods for determining 38 mycotoxins in cereals and 41 mycotoxins in beer were established since agricultural products count as the primary source of mycotoxin contamination. For the analysis of cereal samples, a QuEChERS- based extraction approach was pursued, while analytes from beer samples were extracted using an acetonitrile precipitation scheme. Validation in cereals, namely wheat, corn, rice, and barley, as well as in beer, demonstrated satisfactory results. To obtain information regarding the natural occurrence of mycotoxins in food products, the developed methods were applied to the analysis of several commercial samples partly produced worldwide. The Fusarium toxins deoxynivalenol and its conjugated metabolite deoxynivalenol-3-glucoside turned out to be the most abundant toxins. None of the other modified mycotoxins were quantified in the samples. However, one cereal sample showed traces of zearalenone- 14-sulfate below the limit of quantification. Moreover, pesticides, plant growth regulators, and tropane alkaloids were investigated in this thesis. Pesticides present biologically highly effective compounds applied in the environment to protect humans from the hazardous effects of pests. While plant growth regulators show similar functions, mainly improving agricultural production, tropane alkaloids are naturally occurring secondary metabolites mainly in the species of Solanaceae that may pose unintended poisoning of humans. The third part of the present thesis aimed to analyze cereal-relevant compounds simultaneously, wherefore a multi-method for the analysis of (modified) mycotoxins, pesticides, plant growth regulators, and tropane alkaloids was established. After processing the samples, this should be done in a single extraction step with subsequent one-time measurements. Various sample preparation procedures were compared, whereby an approach based on an acidified acetonitrile/water extraction, followed by an online clean-up, was finally chosen. The simultaneous determination of more than 350 analytes required an analytical tool that offered an increased resolving power, represented as an enhanced peak capacity, and the possibility of analyzing a broad polarity range. Thus, a two-dimensional LC-MS/MS system based on two different separation mechanisms that performed orthogonal to one another was used for the analysis. Validation of the developed method revealed good performance characteristics for most analytes, while subsequent application showed that 86% of the samples were contaminated with at least one compound. In summary, this thesis provides novel insights into the analysis of food-relevant (modified) mycotoxins. Different sample preparation and LC-MS/MS approaches were introduced, resulting in the development of three new analytical methods. For the first time, such a high number of modified mycotoxins was included in multi-mycotoxin methods and a multi-method ranging both contaminants and residues. Although first steps towards the analysis of modified mycotoxins have been made, further research is needed to elucidate their (co-) occurrence and toxicological behavior in order to understand their relevance to human health in the future.
‘Smart’ Janus emulsions
(2021)
Emulsions constitute one of the most prominent and continuously evolving research areas in Colloid Chemistry, which involves the preparation of mixtures or dispersions of immiscible components in a continuous medium. Besides conventional oil-in-water or water-in-oil emulsions, other emulsions of complex droplet morphologies have recently attracted significant research interests. Especially Janus emulsions, in which each droplet is comprised of two distinct sub-regions, have shown versatile potential applications. One of their advantages is the possibility of compartmentalization, which enables to play with two different chemistries in a single droplet. Though microfluidic methods are conventionally used to prepare Janus emulsions, their industrial applications are largely hindered by low throughput and extensive instrumentations. Recently, it has been discovered that simply one-pot moderate/high energy emulsification is also capable of developing Janus morphology, although their preparation and stabilization remain rather substantially challenging. This cumulative doctoral thesis focuses on the preparation and characterization of ‘smart’ Janus emulsions, i.e. Janus emulsions with special stimuli-responsive features. One-step moderate/high energy emulsification of olive and silicone oil in an aqueous medium was carried out. Special consideration was devoted to the interfacial tensions among the components to maintain the criteria of forming characteristic droplet architectures, in addition to avoiding multiple emulsion destabilization phenomena like imminent phase separation or even separated droplet formation. A series of investigations were conducted related to the formation of complexes of charged macromolecules and role of them as stabilizers to achieve stable Janus emulsions for a realistic timeframe (more than 3 months). The correlation between the size of the stabilizer particles and the droplet size of emulsion was established. Furthermore, it was observed that Janus emulsion gels with interesting rheological properties can be fabricated in the presence of suitable polyelectrolyte complexes. Janus emulsions that could be influenced by pH, temperature or magnetic field were successfully produced in presence of characteristic stimuli-responsive stabilizers. Afterwards, the effect of these changes was studied by different characterization techniques. The size and morphology could be tuned easily by changing the pH. The incorporation of iron oxide magnetic nanoparticles (synthesized separately by a co-precipitation method) to one component of the Janus emulsion was carried out so that the movement and orientation of the complex droplets in aqueous media could be controlled by an external magnetic field. Additionally, temperature-triggered instantaneous reversible breakdown of Janus droplets was also accomplished. The responses of the Janus droplets by the stimuli were well-documented and explained. Another goal of the present contribution was to exploit this special morphological feature of emulsions as a template for producing porous materials. This was demonstrated by the preparation of ultralight magnetic responsive aerogels, utilizing Janus emulsion gels. The produced aerogels also showed the capacity to separate toxic dye from water. To the best of our knowledge, this is the first example of investigation towards batch scale production of Janus emulsion with such special stimuli-responsive properties by a simple bulk emulsification method.
Boon and bane
(2021)
Semi-natural habitats (SNHs) in agricultural landscapes represent important refugia for biodiversity including organisms providing ecosystem services. Their spill-over into agricultural fields may lead to the provision of regulating ecosystem services such as biological pest control ultimately affecting agricultural yield. Still, it remains largely unexplored, how different habitat types and their distributions in the surrounding landscape shape this provision of ecosystem services within arable fields. Hence, in this thesis I investigated the effect of SNHs on biodiversity-driven ecosystem services and disservices affecting wheat production with an emphasis on the role and interplay of habitat type, distance to the habitat and landscape complexity.
I established transects from the field border into the wheat field, starting either from a field-to-field border, a hedgerow, or a kettle hole, and assessed beneficial and detrimental organisms and their ecosystem functions as well as wheat yield at several in-field distances. Using this study design, I conducted three studies where I aimed to relate the impacts of SNHs at the field and at the landscape scale on ecosystem service providers to crop production.
In the first study, I observed yield losses close to SNHs for all transect types. Woody habitats, such as hedgerows, reduced yields stronger than kettle holes, most likely due to shading from the tall vegetation structure. In order to find the biotic drivers of these yield losses close to SNHs, I measured pest infestation by selected wheat pests as potential ecosystem disservices to crop production in the second study. Besides relating their damage rates to wheat yield of experimental plots, I studied the effect of SNHs on these pest rates at the field and at the landscape scale. Only weed cover could be associated to yield losses, having their strongest impact on wheat yield close to the SNH. While fungal seed infection rates did not respond to SNHs, fungal leaf infection and herbivory rates of cereal leaf beetle larvae were positively influenced by kettle holes. The latter even increased at kettle holes with increasing landscape complexity suggesting a release of natural enemies at isolated habitats within the field interior.
In the third study, I found that also ecosystem service providers benefit from the presence of kettle holes. The distance to a SNH decreased species richness of ecosystem service providers, whereby the spatial range depended on species mobility, i.e. arable weeds diminished rapidly while carabids were less affected by the distance to a SNH. Contrarily, weed seed predation increased with distance suggesting that a higher food availability at field borders might have diluted the predation on experimental seeds. Intriguingly, responses to landscape complexity were rather mixed: While weed species richness was generally elevated with increasing landscape complexity, carabids followed a hump-shaped curve with highest species numbers and activity-density in simple landscapes. The latter might give a hint that carabids profit from a minimum endowment of SNHs, while a further increase impedes their mobility. Weed seed predation was affected differently by landscape complexity depending on weed species displayed. However, in habitat-rich landscapes seed predation of the different weed species converged to similar rates, emphasising that landscape complexity can stabilize the provision of ecosystem services. Lastly, I could relate a higher weed seed predation to an increase in wheat yield even though seed predation did not diminish weed cover. The exact mechanisms of the provision of weed control to crop production remain to be investigated in future studies.
In conclusion, I found habitat-specific responses of ecosystem (dis)service providers and their functions emphasizing the need to evaluate the effect of different habitat types on the provision of ecosystem services not only at the field scale, but also at the landscape scale. My findings confirm that besides identifying species richness of ecosystem (dis)service providers the assessment of their functions is indispensable to relate the actual delivery of ecosystem (dis)services to crop production.
In modern times of evolving globalization and continuous technological developments, organizations are required to respond to ever-changing demands. Therefore, to be successful in today’s highly uncertain environments, organizations need employees to actively search for opportunities, anticipate challenges, and act ahead. In other words, employee proactivity in the workplace represents a highly valuable resource in nowadays organizations. Empirical studies conducted as part of this thesis advance the research on the outcomes of proactivity from the individual perspective. The main contribution of this thesis pertains to revealing several important individual and contextual conditions under which engaging in proactivity will have negative and positive effects on employees’ well-being and their consequent behaviours, as well as shedding light on the unique psychological mechanisms through which these effects unfold. From a practical standpoint, this research underscores the importance of creating work environments that support employees’ autonomous motivation for proactivity and urge organizations and managers to be mindful about the pressures they place on employees to be proactive at work. Besides, this thesis stimulates research efforts aimed at further extending our knowledge of when and how individual proactive behaviours at work will do more good than harm for those who enact them.
Halide perovskites are a class of novel photovoltaic materials that have recently attracted much attention in the photovoltaics research community due to their highly promising optoelectronic properties, including large absorption coefficients and long carrier lifetimes. The charge carrier mobility of halide perovskites is investigated in this thesis by THz spectroscopy, which is a contact-free technique that yields the intra-grain sum mobility of electrons and holes
in a thin film.
The polycrystalline halide perovskite thin films, provided from Potsdam University, show moderate mobilities in the range from 21.5 to 33.5 cm2V-1s-1. It is shown in this work that the room temperature mobility is limited by charge carrier scattering at polar optical phonons. The mobility at low temperature is likely to be limited by scattering at charged and neutral impurities at impurity concentration N=1017-1018 cm-3. Furthermore, it is shown that exciton formation
may decrease the mobility at low temperatures. Scattering at acoustic phonons can be neglected at both low and room temperatures. The analysis of mobility spectra over a broad range of temperatures for perovskites with various cation compounds shows that cations have a minor impact on charge carrier mobility.
The low-dimensional thin films of quasi-2D perovskite with different numbers of [PbI6]4−sheets (n=2-4) alternating with long organic spacer molecules were provided by S. Zhang from Potsdam University. They exhibit mobilities in the range from 3.7 to 8 cm2V-1s-1. A clear
decrease of mobility is observed with decrease in number of metal-halide sheets n, which likely arises from charge carrier confinement within metal-halide layers. Modelling the measured THz mobility with the modified Drude-Smith model yields localization length from 0.9 to 3.7 nm, which agrees well on the thicknesses of the metal-halide layers. Additionally, the mobilities are found to be dependent on the orientation of the layers. The charge carrier dynamics is also
dependent on the number of metal-halide sheets n. For the thin films with n =3-4 the dynamics is similar to the 3D MHPs. However, the thin film with n = 2 shows clearly different dynamics, where the signs of exciton formation are observed within 390 fs timeframe after
photoexcitation.
Also, the charge carrier dynamics of CsPbI3 perovskite nanocrystals was investigated, in particular the effect of post treatments on the charge carrier transport.
Centroid moment tensor inversion can provide insight into ongoing tectonic processes and active faults. In the Alpine mountains (central Europe), challenges result from low signal-to-noise ratios of earthquakes with small to moderate magnitudes and complex wave propagation effects through the heterogeneous crustal structure of the mountain belt. In this thesis, I make use of the temporary installation of the dense AlpArray seismic network (AASN) to establish a work flow to study seismic source processes and enhance the knowledge of the Alpine seismicity. The cumulative thesis comprises four publications on the topics of large seismic networks, seismic source processes in the Alps, their link to tectonics and stress field, and the inclusion of small magnitude earthquakes into studies of active faults.
Dealing with hundreds of stations of the dense AASN requires the automated assessment of data and metadata quality. I developed the open source toolbox AutoStatsQ to perform an automated data quality control. Its first application to the AlpArray seismic network has revealed significant errors of amplitude gains and sensor orientations. A second application of the orientation test to the Turkish KOERI network, based on Rayleigh wave polarization, further illustrated the potential in comparison to a P wave polarization method. Taking advantage of the gain and orientation results of the AASN, I tested different inversion settings and input data types to approach the specific challenges of centroid moment tensor (CMT) inversions in the Alps. A comparative study was carried out to define the best fitting procedures.
The application to 4 years of seismicity in the Alps (2016-2019) substantially enhanced the amount of moment tensor solutions in the region. We provide a list of moment tensors solutions down to magnitude Mw 3.1. Spatial patterns of typical focal mechanisms were analyzed in the seismotectonic context, by comparing them to long-term seismicity, historical earthquakes and observations of strain rates. Additionally, we use our MT solutions to investigate stress regimes and orientations along the Alpine chain. Finally, I addressed the challenge of including smaller magnitude events into the study of active faults and source processes. The open-source toolbox Clusty was developed for the clustering of earthquakes based on waveforms recorded across a network of seismic stations. The similarity of waveforms reflects both, the location and the similarity of source mechanisms. Therefore the clustering bears the opportunity to identify earthquakes of similar faulting styles, even when centroid moment tensor inversion is not possible due to low signal-to-noise ratios of surface waves or oversimplified velocity models. The toolbox is described through an application to the Zakynthos 2018 aftershock sequence and I subsequently discuss its potential application to weak earthquakes (Mw<3.1) in the Alps.
Lie group method in combination with Magnus expansion is utilized to develop a universal method applicable to solving a Sturm–Liouville Problem (SLP) of any order with arbitrary boundary conditions. It is shown that the method has ability to solve direct regular and some singular SLPs of even orders (tested up to order eight), with a mix of boundary conditions (including non-separable and finite singular endpoints), accurately and efficiently.
The present technique is successfully applied to overcome the difficulties in finding suitable sets of eigenvalues so that the inverse SLP problem can be effectively solved.
Next, a concrete implementation to the inverse Sturm–Liouville problem
algorithm proposed by Barcilon (1974) is provided. Furthermore, computational feasibility and applicability of this algorithm to solve inverse Sturm–Liouville problems of order n=2,4 is verified successfully. It is observed that the method is successful even in the presence of significant noise, provided that the assumptions of the algorithm are satisfied.
In conclusion, this work provides methods that can be adapted successfully for solving a direct (regular/singular) or inverse SLP of an arbitrary order with arbitrary boundary conditions.
The aim of the doctoral project was to answer the question of whether the structural word-initial noun capitalization, as it can otherwise only be found in Luxembourgish alongside German, has a function that is advantageous for the reader. The overriding hypothesis was that an advantage is achieved by activating a syntactic category, namely the core of a noun phrase, through the parafoveal perception of the capital letters. This perception from the corner of the eye should make it possible to preprocess the following noun. As a result, sentence processing should be facilitated, which should ultimately be reflected in overall faster reading times and fixation durations.
The structure of the project includes three studies, some of which included different participant groups:
Study 1:
Study design: Semantic priming using garden-path sentences should bring out the functionality of noun capitalization for the reader
Participant groups: German natives reading German
Study 2:
Study design: same design as study 1, but in English
Participant groups:
English natives without any knowledge of German reading English
English natives who regularly read German reading English
German with high proficiency in English reading English
Study 3:
Study design:
Influence of the noun frequency on a potential preprocessing using the boundary paradigm; Study languages: German and English
Participant groups:
German natives reading German
English natives without any knowledge of German reading English
German with high proficiency in English reading English
Brief summary: The noun capitalization clearly has an impact on sentence processing in both German and English. It cannot be confirmed that this has a substantial, decisive advantage.
Compound values are not universally supported in virtual machine (VM)-based programming systems and languages. However, providing data structures with value characteristics can be beneficial. On one hand, programming systems and languages can adequately represent physical quantities with compound values and avoid inconsistencies, for example, in representation of large numbers. On the other hand, just-in-time (JIT) compilers, which are often found in VMs, can rely on the fact that compound values are immutable, which is an important property in optimizing programs. Considering this, compound values have an optimization potential that can be put to use by implementing them in VMs in a way that is efficient in memory usage and execution time. Yet, optimized compound values in VMs face certain challenges: to maintain consistency, it should not be observable by the program whether compound values are represented in an optimized way by a VM; an optimization should take into account, that the usage of compound values can exhibit certain patterns at run-time; and that necessary value-incompatible properties due to implementation restrictions should be reduced.
We propose a technique to detect and compress common patterns of compound value usage at run-time to improve memory usage and execution speed. Our approach identifies patterns of frequent compound value references and introduces abbreviated forms for them. Thus, it is possible to store multiple inter-referenced compound values in an inlined memory representation, reducing the overhead of metadata and object references. We extend our approach by a notion of limited mutability, using cells that act as barriers for our approach and provide a location for shared, mutable access with the possibility of type specialization. We devise an extension to our approach that allows us to express automatic unboxing of boxed primitive data types in terms of our initial technique. We show that our approach is versatile enough to express another optimization technique that relies on values, such as Booleans, that are unique throughout a programming system. Furthermore, we demonstrate how to re-use learned usage patterns and optimizations across program runs, thus reducing the performance impact of pattern recognition.
We show in a best-case prototype that the implementation of our approach is feasible and can also be applied to general purpose programming systems, namely implementations of the Racket language and Squeak/Smalltalk. In several micro-benchmarks, we found that our approach can effectively reduce memory consumption and improve execution speed.
The propagation of test fields, such as electromagnetic, Dirac or linearized gravity, on a fixed spacetime manifold is often studied by using the geometrical optics approximation. In the limit of infinitely high frequencies, the geometrical optics approximation provides a conceptual transition between the test field and an effective point-particle description. The corresponding point-particles, or wave rays, coincide with the geodesics of the underlying spacetime. For most astrophysical applications of interest, such as the observation of celestial bodies, gravitational lensing, or the observation of cosmic rays, the geometrical optics approximation and the effective point-particle description represent a satisfactory theoretical model. However, the geometrical optics approximation gradually breaks down as test fields of finite frequency are considered.
In this thesis, we consider the propagation of test fields on spacetime, beyond the leading-order geometrical optics approximation. By performing a covariant Wentzel-Kramers-Brillouin analysis for test fields, we show how higher-order corrections to the geometrical optics approximation can be considered. The higher-order corrections are related to the dynamics of the spin internal degree of freedom of the considered test field. We obtain an effective point-particle description, which contains spin-dependent corrections to the geodesic motion obtained using geometrical optics. This represents a covariant generalization of the well-known spin Hall effect, usually encountered in condensed matter physics and in optics. Our analysis is applied to electromagnetic and massive Dirac test fields, but it can easily be extended to other fields, such as linearized gravity. In the electromagnetic case, we present several examples where the gravitational spin Hall effect of light plays an important role. These include the propagation of polarized light rays on black hole spacetimes and cosmological spacetimes, as well as polarization-dependent effects on the shape of black hole shadows. Furthermore, we show that our effective point-particle equations for polarized light rays reproduce well-known results, such as the spin Hall effect of light in an inhomogeneous medium, and the relativistic Hall effect of polarized electromagnetic wave packets encountered in Minkowski spacetime.
Plants possess cell wall, a polysaccharide exoskeleton which encompasses all plant cells. Cell wall gives plant cells mechanical support, defines their shape, enables growth and water transport through a plant. It also has important role in communication with the external environment. Regulation of plant cell wall biosynthesis and cell and organ morphogenesis depends on cell’s ability to detect mechanical signals originating both from the external environment and from internal plant tissues. Thanks to the presence of the cell wall, all living plant cells develop constant internal pressure generated by the active water uptake, known as turgor pressure, which enables them to grow. Thus, actively growing cells in the tissue are exerting mechanical stress to each other. In order to properly coordinate cell growth, tissue morphogenesis and maintain cell-to-cell adhesion, plant cell have to detect these mechanical signals. That is performed by a group of still not well enough characterized plant mechanosensitive proteins. Mechanosensors are proteins capable of detecting changes in mechanical stress patterns and translating them into physiological and developmental outputs. One of plant mechanosensitive proteins, DEFECTIVE KERNEL1 (DEK1) has shown to be a very important in proper plant development. DEK1 bears similarity with animal cysteine proteases of Calpain superfamily. DEK1 is very important for plant development since all null alleles are embryo lethal. During the last 20 years of DEK1 studies, this protein has proven to be a very difficult for different molecular and biochemical manipulations. As a consequence, very little is known about its direct target proteins. Wang and co-workers (2003) and Johnson and co-workers (2008) have given a valuable contribution to biochemical understanding of DEK1 by determining that it functions as Cys-protease in similar way as animal calpains. However, a lot of indirect knowledge was gathered about the effects of disruption and modulation of DEK1 activity. DEK1 is important for proper organ development, epidermal specification, and maintenance. However, some studies have inferred that DEK1 affects expression of different cell wall related genes, and it regulates cell-to-cell adhesion in epidermal cells. This led to two extensive studies (Amanda et al., 2016, 2017) which demonstrated importance of DEK1 in regulation leaf epidermal cell walls in A. thaliana mature leaves and inflorescence stems. These studies demonstrated that DEK1 also influences cell wall thickness and cell-to-cell adhesion and that it could potentially regulate cell growth and expansion. Building up on this research, we decided to try to further characterize molecular and biomechanical aspects of DEK1 mediated cell wall regulation, with special emphasis on regulation of cellulose synthesis. We used two mutant lines, with modulated DEK1 activity, a constitutive overexpressor for DEK1 CALPAIN domain and a point mutant in CALPAIN domain, dek1-4. In Chapter 3 we demonstrated that DEK1 regulates dynamics of Cellulose Synthase Complexes (CSCs). Both lines showed decreased crystalline cellulose contents. This led us to investigate if velocity of CSCs in cotyledons, was affected, since it is known that changes in cellulose contents are often caused by defects in CSC. We found that bothDEK1 modulated lines we used have significantly decreased velocity of CSCs. We have also examined plasma membrane turnover rates of CSCs and found out that after photo-bleaching OE CALPAIN has much faster recovery rates compared to Col-0 wild type, while dek1-4 has lower exocytotic rates of CSCs, and much longer life-time of CSCs inserted into the plasma membrane. These results suggested that DEK1 regulates different aspects of CSC dynamics, possibly through interaction with different regulatory proteins. Decrease in cellulose contents we observed in DEK1 modulated lines, prompted us to investigate how this reflects biomechanics and structural properties of epidermal cotyledon cell walls of DEK1 modulated lines, which is described in Chapter 4. To achieve this, we developed a novel microdissection method for isolation and mechanical and structural characterization of native epidermal cell wall monolayers using atomic force microscopy (AFM). AFM force spectroscopy assays showed that both DEK1 modulated lines had stiffer cell walls compared to Col-0. This was awkward since we initially detected decrease in crystalline cellulose which implied decrease in cell wall stiffness. However, subsequent high-resolution AFM imaging has revealed that DEK1 modulate lines cells walls have their cellulose microfibrils organized in thicker bundles than Col-0. Also, polysaccharide composition analysis has revealed that DEK1 modulated lines have increased abundance of pectins, which could also be responsible for the observed increase in cell wall stiffness. Previous work has shown that different dek1 mutants and modulated lines have defects in cell-to-cell adhesion. This implied that DEK1 may be involved in sensing and/or maintaining cell wall integrity (CWI). We performed several growth assays to determine role of DEK1 in CWI, which is described in Chapter 5. We performed cellulose synthesis perturbation assays with cellulose synthesis inhibitor Isoxaben and obtained very interesting results. While OE CALPAIN plants were hypersensitive to Isoxaben, dek1-4 has shown complete insensitivity. Furthermore, a regular CWI maintenance response, reported in A. thaliana as result of compromised CWI, ectopic lignification in seedlings’ roots was absent in both DEK1 modulated lines we examined. We detected interesting growth response of DEK1 lines to NaCl and mannitol treatments as well. Although these findings are pointing out that DEK1 could be part of CWI signalling pathways, more experiments are necessary to fully elucidate possible role of DEK1 in CWI sensing and/or maintenance pathways, especially to check if DEK1 is interacting with Catharanthus roseus Receptor Like Kinase group of CWI sensors. Studies on 4-month old short day grown DEK1 modulated lines, have shown defects in branching, with development of fasciated stem branches in a DEK1 modulated line overexpressing CALPAIN domain (Amanda et al., 2017). This result pointed out to a possibility that DEK1 may regulate organ morphogenesis and patterning at the level of shoot apical meristem (SAM). Work towards elucidating role of DEK1 in SAM maintenance and organ patterning is detailed in Chapter 6. We determined that OE CALPAIN had significantly larger central zone of SAM as well as larger individual SAM cells in central zone, as well as higher distribution of cell sizes, implying possible cell expansion defects. dek1-4 did not exhibited changes in SAM central zone size or individual stem cell size, but it seemed that it had increased number of stem cells in SAM central zone. Both DEK1 lines had perturbation of phyllotaxis on SAM level, with disturbed divergence angles between floral primordia. Disturbed phyllotaxis was also observed between siliques, in mature plants. In addition to this, OE CALPAIN has exhibited occurrence of multiple (up to four) siliques growing from a single stem node. All this is pointing out that DEK1 might participate in hormone-signalling in the SAM.. DEK1 is a highly intriguing protein. However, since it is a unigene, and in addition to that, a regulatory protease, it probably participates in multiple signalling pathways, which makes understanding its function much more complicated.
Today, the Mekong Delta in the southern of Vietnam is home for 18 million people. The delta also accounts for more than half of the country’s food production and 80% of the exported rice. Due to the low elevation, it is highly susceptible to the risk of fluvial and coastal flooding. Although extreme floods often result in excessive damages and economic losses, the annual flood pulse from the Mekong is vital to sustain agricultural cultivation and livelihoods of million delta inhabitants.
Delta-wise risk management and adaptation strategies are required to mitigate the adverse impacts from extreme events while capitalising benefits from floods. However, a proper flood risk management has not been implemented in the VMD, because the quantification of flood damage is often overlooked and the risks are thus not quantified. So far, flood management has been exclusively focused on engineering measures, i.e. high- and low- dyke systems, aiming at flood-free or partial inundation control without any consideration of the actual risks or a cost-benefit analysis. Therefore, an analysis of future delta flood dynamics driven these stressors is valuable to facilitate the transition from sole hazard control towards a risk management approach, which is more cost-effective and also robust against future changes in risk.
Built on these research gaps, this thesis investigates the current state and future projections of flood hazard, damage and risk to rice cultivation, the most important economic activity in the VMD. The study quantifies the changes in risk and hazard brought by the development of delta-based flood control measures in the last decades, and analyses the expected changes in risk driven by the changing climate, rising sea-level and deltaic land subsidence, and finally the development of hydropower projects in the Mekong Basin. For this purpose, flood trend analyses and comprehensive hydraulic modelling were performed, together with the development of a concept to quantify flood damage and risk to rice plantation.
The analysis of observed flood levels revealed strong and robust increasing trends of peak and duration downstream of the high-dyke areas with a step change in 2000/2001, i.e. after the disastrous flood which initiated the high-dyke development. These changes were in contrast to the negative trends detected upstream, suggested that high-dyke development has shifted flood hazard downstream. Findings of the trend’s analysis were later confirmed by hydraulic simulations of the two recent extreme floods in 2000 and 2011, where the hydrological boundaries and dyke system settings were interchanged.
However, the high-dyke system was not the only and often not the main cause for a shift of flood hazard, as a comparative analysis of these two extreme floods proved. The high-dyke development was responsible for 20–90% of the observed changes in flood level between 2000 and 2011, with large spatial variances. The particular flood hydrograph of the two events had the highest contribution in the northern part of the delta, while the tidal level had 2–3 times higher influence than the high-dyke in the lower-central and coastal areas downstream of high-dyke areas. The impact of the high-dyke development was highest in the areas closely downstream of the high-dyke area just south of the Cambodia-Vietnam border. The hydraulic simulations also validated that the concurrence of the flood peak with spring tides, i.e. high sea level along the coast, amplified the flood level and inundation in the central and coastal regions substantially.
The risk assessment quantified the economic losses of rice cultivation to USD 25.0 and 115 million (0.02–0.1% of the total GDP of Vietnam in 2011) corresponding to the 10-year and the 100-year floods, with an expected annual damage of about USD 4.5 million. A particular finding is that the flood damage was highly sensitive to flood timing. Here, a 10-year event with an early peak, i.e. late August-September, could cause as much damage as a 100-year event that peaked in October. This finding underlines the importance of a reliable early flood warning, which could substantially reduce the damage to rice crops and thus the risk.
The developed risk assessment concept was furthermore applied to investigate two high-dyke development alternatives, which are currently under discussion among the administrative bodies in Vietnam, but also in the public. The first option favouring the utilization of the current high-dyke compartments as flood retention areas instead for rice cropping during the flood season could reduce flood hazard and expected losses by 5–40%, depending on the region of the delta. On the contrary, the second option promoting the further extension of the areas protected by high-dyke to facilitate third rice crop planting on a larger area, tripled the current expected annual flood damage. This finding challenges the expected economic benefit of triple rice cultivation, in addition to the already known reducing of nutrient supply by floodplain sedimentation and thus higher costs for fertilizers.
The economic benefits of the high-dyke and triple rice cropping system is further challenged by the changes in the flood dynamics to be expected in future. For the middle of the 21st century (2036-2065) the effective sea-level rise an increase of the inundation extent by 20–27% was projected. This corresponds to an increase of flood damage to rice crops in dry, normal and wet year by USD 26.0, 40.0 and 82.0 million in dry, normal and wet year compared to the baseline period 1971-2000.
Hydraulic simulations indicated that the planned massive development of hydropower dams in the Mekong Basin could potentially compensate the increase in flood hazard and agriculture losses stemming from climate change. However, the benefits of dams as mitigation of flood losses are highly uncertain, because a) the actual development of the dams is highly disputed, b) the operation of the dams is primarily targeted at power generation, not flood control, and c) this would require international agreements and cooperation, which is difficult to achieve in South-East Asia. The theoretical flood mitigation benefit is additionally challenged by a number of negative impacts of the dam development, e.g. disruption of floodplain inundation in normal, non-extreme flood years. Adding to the certain reduction of sediment and nutrient load to the floodplains, hydropower dams will drastically impair rice and agriculture production, the basis livelihoods of million delta inhabitants.
In conclusion, the VMD is expected to face increasing threats of tidal induced floods in the coming decades. Protection of the entire delta coastline solely with “hard” engineering flood protection structures is neither technically nor economically feasible, adaptation and mitigation actions are urgently required. Better control and reduction of groundwater abstraction is thus strongly recommended as an immediate and high priority action to reduce the land subsidence and thus tidal flooding and salinity intrusion in the delta. Hydropower development in the Mekong basin might offer some theoretical flood protection for the Mekong delta, but due to uncertainties in the operation of the dams and a number of negative effects, the dam development cannot be recommended as a strategy for flood management. For the Vietnamese authorities, it is advisable to properly maintain the existing flood protection structures and to develop flexible risk-based flood management plans. In this context the study showed that the high-dyke compartments can be utilized for emergency flood management in extreme events. For this purpose, a reliable flood forecast is essential, and the action plan should be materialised in official documents and legislation to assure commitment and consistency in the implementation and operation.
Over the last decades, the rate of near-surface warming in the Arctic is at least double than elsewhere on our planet (Arctic amplification). However, the relative contribution of different feedback processes to Arctic amplification is a topic of ongoing research, including the role of aerosol and clouds. Lidar systems are well-suited for the investigation of aerosol and optically-thin clouds as they provide vertically-resolved information on fine temporal scales. Global aerosol models fail to converge on the sign of the Arctic aerosol radiative effect (ARE). In the first part of this work, the optical and microphysical properties of Arctic aerosol were characterized at case study level in order to assess the short-wave (SW) ARE. A long-range transport episode was first investigated. Geometrically similar aerosol layers were captured over three locations. Although the aerosol size distribution was different between Fram Strait(bi-modal) and Ny-Ålesund (fine mono-modal), the atmospheric column ARE was similar. The latter was related to the domination of accumulation mode aerosol. Over both locations top of the atmosphere (TOA) warming was accompanied by surface cooling.
Subsequently, the sensitivity of ARE was investigated with respect to different aerosol and spring-time ambient conditions. A 10% change in the single-scattering albedo (SSA) induced higher ARE perturbations compared to a 30% change in the aerosol extinction coefficient. With respect to ambient conditions, the ARETOA was more sensitive to solar elevation changes compared to AREsur f ace. Over dark surfaces the ARE profile was exclusively negative, while over bright surfaces a negative to positive shift occurred above the aerosol layers. Consequently, the sign of ARE can be highly sensitive in spring since this season is characterized by transitional surface albedo conditions.
As the inversion of the aerosol microphysics is an ill-posed problem, the inferred aerosol size distribution of a low-tropospheric event was compared to the in-situ measured distribution. Both techniques revealed a bi-modal distribution, with good agreement in the total volume concentration. However, in terms of SSA a disagreement was found, with the lidar inversion indicating highly scattering particles and the in-situ measurements pointing to absorbing particles. The discrepancies could stem from assumptions in the inversion (e.g. wavelength-independent refractive index) and errors in the conversion of the in-situ measured light attenuation into absorption. Another source of discrepancy might be related to an incomplete capture of fine particles in the in-situ sensors. The disagreement in the most critical parameter for the Arctic ARE necessitates further exploration in the frame of aerosol closure experiments. Care must be taken in ARE modelling studies, which may use either the in-situ or lidar-derived SSA as input.
Reliable characterization of cirrus geometrical and optical properties is necessary for improving their radiative estimates. In this respect, the detection of sub-visible cirrus is of special importance. The total cloud radiative effect (CRE) can be negatively biased, should only the optically-thin and opaque cirrus contributions are considered. To this end, a cirrus retrieval scheme was developed aiming at increased sensitivity to thin clouds. The cirrus detection was based on the wavelet covariance transform (WCT) method, extended by dynamic thresholds. The dynamic WCT exhibited high sensitivity to faint and thin cirrus layers (less than 200 m) that were partly or completely undetected by the existing static method. The optical characterization scheme extended the Klett–Fernald retrieval by an iterative lidar ratio (LR) determination (constrained Klett). The iterative process was constrained by a reference value, which indicated the aerosol concentration beneath the cirrus cloud. Contrary to existing approaches, the aerosol-free assumption was not adopted, but the aerosol conditions were approximated by an initial guess. The inherent uncertainties of the constrained Klett were higher for optically-thinner cirrus, but an overall good agreement was found with two established retrievals. Additionally, existing approaches, which rely on aerosol-free assumptions, presented increased accuracy when the proposed reference value was adopted. The constrained Klett retrieved reliably the optical properties in all cirrus regimes, including upper sub-visible cirrus with COD down to 0.02.
Cirrus is the only cloud type capable of inducing TOA cooling or heating at daytime. Over the Arctic, however, the properties and CRE of cirrus are under-explored. In the final part of this work, long-term cirrus geometrical and optical properties were investigated for the first time over an Arctic site (Ny-Ålesund). To this end, the newly developed retrieval scheme was employed. Cirrus layers over Ny-Ålesund seemed to be more absorbing in the visible spectral region compared to lower latitudes and comprise relatively more spherical ice particles. Such meridional differences could be related to discrepancies in absolute humidity and ice nucleation mechanisms. The COD tended to decline for less spherical and smaller ice particles probably due to reduced water vapor deposition on the particle surface. The cirrus optical properties presented weak dependence on ambient temperature and wind conditions.
Over the 10 years of the analysis, no clear temporal trend was found and the seasonal cycle was not pronounced. However, winter cirrus appeared under colder conditions and stronger winds. Moreover, they were optically-thicker, less absorbing and consisted of relatively more spherical ice particles. A positive CREnet was primarily revealed for a broad range of representative cloud properties and ambient conditions. Only for high COD (above 10) and over tundra a negative CREnet was estimated, which did not hold true over snow/ice surfaces. Consequently, the COD in combination with the surface albedo seem to play the most critical role in determining the CRE sign over the high European Arctic.
Synthesis and Characterization of Upconversion Nanaparticles for Applications in Life Sciences
(2021)
The spread of antibiotic-resistant bacteria poses a globally increasing threat to public health care. The excessive use of antibiotics in animal husbandry can develop resistances in the stables. Transmission through direct contact with animals and contamination of food has already been proven. The excrements of the animals combined with a binding material enable a further potential path of spread into the environment, if they are used as organic manure in agricultural landscapes. As most of the airborne bacteria are attached to particulate matter, the focus of the work will be the atmospheric dispersal via the dust fraction.
Field measurements on arable lands in Brandenburg, Germany and wind erosion studies in a wind tunnel were conducted to investigate the risk of a potential atmospheric dust-associated spread of antibiotic-resistant bacteria from poultry manure fertilized agricultural soils. The focus was to (i) characterize the conditions for aerosolization and (ii) qualify and quantify dust emissions during agricultural operations and wind erosion.
PM10 (PM, particulate matter with an aerodynamic diameter smaller than 10 µm) emission factors and bacterial fluxes for poultry manure application and incorporation have not been previously reported before. The contribution to dust emissions depends on the water content of the manure, which is affected by the manure pretreatment (fresh, composted, stored, dried), as well as by the intensity of manure spreading from the manure spreader. During poultry manure application, PM10 emission ranged between 0.05 kg ha-1 and 8.37 kg ha-1. For comparison, the subsequent land preparation contributes to 0.35 – 1.15 kg ha-1 of PM10 emissions. Manure particles were still part of dust emissions but they were accounted to be less than 1% of total PM10 emissions due to the dilution of poultry manure in the soil after manure incorporation. Bacterial emissions of fecal origin were more relevant during manure application than during the subsequent manure incorporation, although PM10 emissions of manure incorporation were larger than PM10 emissions of manure application for the non-dried manure variants.
Wind erosion leads to preferred detachment of manure particles from sandy soils, when poultry manure has been recently incorporated. Sorting effects were determined between the low-density organic particles of manure origin and the soil particles of mineral origin close above the threshold of 7 m s-1. In dependence to the wind speed, potential erosion rates between 101 and 854 kg ha-1 were identified, if 6 t ha-1 of poultry manure were applied. Microbial investigation showed that manure bacteria got detached more easily from the soil surface during wind erosion, due to their attachment on manure particles.
Although antibiotic-resistant bacteria (ESBL-producing E. coli) were still found in the poultry barns, no further contamination could be detected with them in the manure, fertilized soils or in the dust generated by manure application, land preparation or wind erosion. Parallel studies of this project showed that storage of poultry manure for a few days (36 – 72 h) is sufficient to inactivate ESBL-producing E. coli. Further antibiotic-resistant bacteria, i.e. MRSA and VRE, were only found sporadically in the stables and not at all in the dust. Therefore, based on the results of this work, the risk of a potential infection by dust-associated antibiotic-resistant bacteria can be considered as low.
Deoxyribonucleic acid (DNA) nanostructures enable the attachment of functional molecules to nearly any unique location on their underlying structure. Due to their single-base-pair structural resolution, several ligands can be spatially arranged and closely controlled according to the geometry of their desired target, resulting in optimized binding and/or signaling interactions.
This dissertation covers three main projects. All of them use variations of functionalized DNA nanostructures that act as platform for oligovalent presentation of ligands. The purpose of this work was to evaluate the ability of DNA nanostructures to precisely display different types of functional molecules and to consequently enhance their efficacy according to the concept of multivalency. Moreover, functionalized DNA structures were examined for their suitability in functional screening assays. The developed DNA-based compound ligands were used to target structures in different biological systems.
One part of this dissertation attempted to bind pathogens with small modified DNA nanostructures. Pathogens like viruses and bacteria are known for their multivalent attachment to host cells membranes. By blocking their receptors for recognition and/or fusion with their targeted host in an oligovalent manner, the objective was to impede their ability to adhere to and invade cells. For influenza A, only enhanced binding of oligovalent peptide-DNA constructs compared to the monovalent peptide could be observed, whereas in the case of respiratory syncytial virus (RSV), binding as well as blocking of the target receptors led to an increased inhibition of infection in vitro.
In the final part, the ability of chimeric DNA-peptide constructs to bind to and activate signaling receptors on the surface of cells was investigated. Specific binding of DNA trimers, conjugated with up to three peptides, to EphA2 receptor expressing cells was evaluated in flow cytometry experiments. Subsequently, their ability to activate these receptors via phosphorylation was assessed. EphA2 phosphorylation was significantly increased by DNA trimers carrying three peptides compared to monovalent peptide. As a result of activation, cells underwent characteristic morphological changes, where they "round up" and retract their periphery.
The results obtained in this work comprehensively prove the capability of DNA nanostructures to serve as stable, biocompatible, controllable platforms for the oligovalent presentation of functional ligands. Functionalized DNA nanostructures were used to enhance biological effects and as tool for functional screening of bio-activity. This work demonstrates that modified DNA structures have the potential to improve drug development and to unravel the activation of signaling pathways.
Elucidating the molecular basis of enhanced growth in the Arabidopsis thaliana accession Bur-0
(2021)
The life cycle of flowering plants is a dynamic process that involves successful passing through several developmental phases and tremendous progress has been made to reveal cellular and molecular regulatory mechanisms underlying these phases, morphogenesis, and growth. Although several key regulators of plant growth or developmental phase transitions have been identified in Arabidopsis, little is known about factors that become active during embryogenesis, seed development and also during further postembryonic growth. Much less is known about accession-specific factors that determine plant architecture and organ size. Bur-0 has been reported as a natural Arabidopsis thaliana accession with exceptionally big seeds and a large rosette; its phenotype makes it an interesting candidate to study growth and developmental aspects in plants, however, the molecular basis underlying this big phenotype remains to be elucidated. Thus, the general aim of this PhD project was to investigate and unravel the molecular mechanisms underlying the big phenotype in Bur-0.
Several natural Arabidopsis accessions and late flowering mutant lines were analysed in this study, including Bur-0. Phenotypes were characterized by determining rosette size, seed size, flowering time, SAM size and growth in different photoperiods, during embryonic and postembryonic development. Our results demonstrate that Bur-0 stands out as an interesting accession with simultaneously larger rosettes, larger SAM, later flowering phenotype and larger seeds, but also larger embryos. Interestingly, inter-accession crosses (F1) resulted in bigger seeds than the parental self-crossed accessions, particularly when Bur-0 was used as the female parental genotype, suggesting parental effects on seed size that might be maternally controlled. Furthermore, developmental stage-based comparisons revealed that the large embryo size of Bur-0 is achieved during late embryogenesis and the large rosette size is achieved during late postembryonic growth. Interestingly, developmental phase progression analyses revealed that from germination onwards, the length of developmental phases during postembryonic growth is delayed in Bur-0, suggesting that in general, the mechanisms that regulate developmental phase progression are shared across developmental phases.
On the other hand, a detailed physiological characterization in different tissues at different developmental stages revealed accession-specific physiological and metabolic traits that underlie accession-specific phenotypes and in particular, more carbon resources during embryonic and postembryonic development were found in Bur-0, suggesting an important role of carbohydrates in determination of the bigger Bur-0 phenotype. Additionally, differences in the cellular organization, nuclei DNA content, as well as ploidy level were analyzed in different tissues/cell types and we found that the large organ size in Bur-0 can be mainly attributed to its larger cells and also to higher cell proliferation in the SAM, but not to a different ploidy level.
Furthermore, RNA-seq analysis of embryos at torpedo and mature stage, as well as SAMs at vegetative and floral transition stage from Bur-0 and Col-0 was conducted to identify accession-specific genetic determinants of plant phenotypes, shared across tissues and developmental stages during embryonic and postembryonic growth. Potential candidate genes were identified and further validation of transcriptome data by expression analyses of candidate genes as well as known key regulators of organ size and growth during embryonic and postembryonic development confirmed that the high confidence transcriptome datasets generated in this study are reliable for elucidation of molecular mechanisms regulating plant growth and accession-specific phenotypes in Arabidopsis.
Taken together, this PhD project contributes to the plant development research field providing a detailed analysis of mechanisms underlying plant growth and development at different levels of biological organization, focusing on Arabidopsis accessions with remarkable phenotypical differences. For this, the natural accession Bur-0 was an ideal outlier candidate and different mechanisms at organ and tissue level, cell level, metabolism, transcript and gene expression level were identified, providing a better understanding of different factors involved in plant growth regulation and mechanisms underlying different growth patterns in nature.
The Arctic environments constitute rich and dynamic ecosystems, dominated by microorganisms extremely well adapted to survive and function under severe conditions. A range of physiological adaptations allow the microbiota in these habitats to withstand low temperatures, low water and nutrient availability, high levels of UV radiation, etc. In addition, other adaptations of clear competitive nature are directed at not only surviving but thriving in these environments, by disrupting the metabolism of neighboring cells and affecting intermicrobial communication. Since Arctic microbes are bioindicators which amplify climate alterations in the environment, the Arctic region presents the opportunity to study local microbiota and carry out research about interesting, potentially virulent phenotypes that could be dispersed into other habitats around the globe as a consequence of accelerating climate change. In this context, exploration of Arctic habitats as well as descriptions of the microbes inhabiting them are abundant but microbial competitive strategies commonly associated with virulence and pathogens are rarely reported. In this project, environmental samples from the Arctic region were collected and microorganisms (bacteria and fungi) were isolated. The clinical relevance of these microorganisms was assessed by observing the following virulence markers: ability to grow at a range of temperatures, expression of antimicrobial resistance and production of hemolysins. The aim of this project is to determine the frequency and relevance of these characteristics in an effort to understand microbial adaptations in habitats threatened by climate change. The isolates obtained and described here were able to grow at a range of temperatures, in some cases more than 30 °C higher than their original isolation temperature. A considerable number of them consistently expressed compounds capable of lysing sheep and bovine erythrocytes on blood agar at different incubation temperatures. Ethanolic extracts of these bacteria were able to cause rapid and complete lysis of erythrocyte suspensions and might even be hemolytic when assayed on human blood. In silico analyses showed a variety of resistance elements, some of them novel, against natural and synthetic antimicrobial compounds. In vitro experiments against a number of antimicrobial compounds showed resistance phenotypes belonging to wild-type populations and some non-wild type which clearly denote human influence in the acquisition of antimicrobial resistance. The results of this project demonstrate the presence of virulence-associated factors expressed by microorganisms of natural, non-clinical environments. This study contains some of the first reports, to the best of our knowledge, of hemolytic microbes isolated from the Arctic region. In addition, it provides additional information about the presence and expression of intrinsic and acquired antimicrobial resistance in environmental isolates, contributing to the understanding of the evolution of relevant pathogenic species and opportunistic pathogens. Finally, this study highlights some of the potential risks associated with changes in the polar regions (habitat melting and destruction, ecosystem transition and re-colonization) as important indirect consequences of global warming and altered climatic conditions around the planet.
Bottom-up synthetic biology is used for the understanding of how a cell works. It is achieved through developing techniques to produce lipid-based vesicular structures as cellular mimics. The most common techniques used to produce cellular mimics or synthetic cells is through electroformation and swelling method. However, the abovementioned techniques cannot efficiently encapsulate macromolecules such as proteins, enzymes, DNA and even liposomes as synthetic organelles. This urges the need to develop new techniques that can circumvent this issue and make the artificial cell a reality where it is possible to imitate a eukaryotic cell through encapsulating macromolecules. In this thesis, the aim to construct a cell system using giant unilamellar vesicles (GUVs) to reconstitute the mitochondrial molybdenum cofactor biosynthetic pathway. This pathway is highly conserved among all life forms, and therefore is known for its biological significance in disorders induced through its malfunctioning. Furthermore, the pathway itself is a multi-step enzymatic reaction that takes place in different compartments. Initially, GTP in the mitochondrial matrix is converted to cPMP in the presence of cPMP synthase. Further, produced cPMP is transported across the membrane to the cytosol, to be converted by MPT synthase into MPT. This pathway provides a possibility to address the general challenges faced in the development of a synthetic cell, to encapsulate large biomolecules with good efficiency and greater control and to evaluate the enzymatic reactions involved in the process.
For this purpose, the emulsion-based technique was developed and optimised to allow rapid production of GUVs (~18 min) with high encapsulation efficiency (80%). This was made possible by optimizing various parameters such as density, type of oil, the impact of centrifugation speed/time, lipid concentration, pH, temperature, and emulsion droplet volume. Furthermore, the method was optimised in microtiter plates for direct experimentation and visualization after the GUV formation. Using this technique, the two steps - formation of cPMP from GTP and the formation of MPT from cPMP were encapsulated in different sets of GUVs to mimic the two compartments. Two independent fluorescence-based detection systems were established to confirm the successful encapsulation and conversion of the reactants. Alternatively, the enzymes produced using bacterial expression and measured. Following the successful encapsulation and evaluation of enzymatic reactions, cPMP transport across mitochondrial membrane has been mimicked using GUVs using a complex mitochondrial lipid composition. It was found that the cPMP interaction with the lipid bilayer results in transient pore-formation and leakage of internal contents.
Overall, it can be concluded that in this thesis a novel technique has been optimised for fast production of functional synthetic cells. The individual enzymatic steps of the Moco biosynthetic pathway have successfully implemented and quantified within these cellular mimics.
Flooding is a vast problem in many parts of the world, including Europe. It occurs mainly due to extreme weather conditions (e.g. heavy rainfall and snowmelt) and the consequences of flood events can be devastating. Flood risk is mainly defined as a combination of the probability of an event and its potential adverse impacts. Therefore, it covers three major dynamic components: hazard (physical characteristics of a flood event), exposure (people and their physical environment that being exposed to flood), and vulnerability (the elements at risk). Floods are natural phenomena and cannot be fully prevented. However, their risk can be managed and mitigated. For a sound flood risk management and mitigation, a proper risk assessment is needed. First of all, this is attained by a clear understanding of the flood risk dynamics. For instance, human activity may contribute to an increase in flood risk. Anthropogenic climate change causes higher intensity of rainfall and sea level rise and therefore an increase in scale and frequency of the flood events. On the other hand, inappropriate management of risk and structural protection measures may not be very effective for risk reduction. Additionally, due to the growth of number of assets and people within the flood-prone areas, risk increases. To address these issues, the first objective of this thesis is to perform a sensitivity analysis to understand the impacts of changes in each flood risk component on overall risk and further their mutual interactions. A multitude of changes along the risk chain are simulated by regional flood model (RFM) where all processes from atmosphere through catchment and river system to damage mechanisms are taken into consideration. The impacts of changes in risk components are explored by plausible change scenarios for the mesoscale Mulde catchment (sub-basin of the Elbe) in Germany.
A proper risk assessment is ensured by the reasonable representation of the real-world flood event. Traditionally, flood risk is assessed by assuming homogeneous return periods of flood peaks throughout the considered catchment. However, in reality, flood events are spatially heterogeneous and therefore traditional assumption misestimates flood risk especially for large regions. In this thesis, two different studies investigate the importance of spatial dependence in large scale flood risk assessment for different spatial scales. In the first one, the “real” spatial dependence of return period of flood damages is represented by continuous risk modelling approach where spatially coherent patterns of hydrological and meteorological controls (i.e. soil moisture and weather patterns) are included. Further the risk estimations under this modelled dependence assumption are compared with two other assumptions on the spatial dependence of return periods of flood damages: complete dependence (homogeneous return periods) and independence (randomly generated heterogeneous return periods) for the Elbe catchment in Germany. The second study represents the “real” spatial dependence by multivariate dependence models. Similar to the first study, the three different assumptions on the spatial dependence of return periods of flood damages are compared, but at national (United Kingdom and Germany) and continental (Europe) scales. Furthermore, the impacts of the different models, tail dependence, and the structural flood protection level on the flood risk under different spatial dependence assumptions are investigated.
The outcomes of the sensitivity analysis framework suggest that flood risk can vary dramatically as a result of possible change scenarios. The risk components that have not received much attention (e.g. changes in dike systems and in vulnerability) may mask the influence of climate change that is often investigated component.
The results of the spatial dependence research in this thesis further show that the damage under the false assumption of complete dependence is 100 % larger than the damage under the modelled dependence assumption, for the events with return periods greater than approximately 200 years in the Elbe catchment. The complete dependence assumption overestimates the 200-year flood damage, a benchmark indicator for the insurance industry, by 139 %, 188 % and 246 % for the UK, Germany and Europe, respectively. The misestimation of risk under different assumptions can vary from upstream to downstream of the catchment. Besides, tail dependence in the model and flood protection level in the catchments can affect the risk estimation and the differences between different spatial dependence assumptions.
In conclusion, the broader consideration of the risk components, which possibly affect the flood risk in a comprehensive way, and the consideration of the spatial dependence of flood return periods are strongly recommended for a better understanding of flood risk and consequently for a sound flood risk management and mitigation.
The incorporation of proteins in artificial materials such as membranes offers great opportunities to avail oneself the miscellaneous qualities of proteins and enzymes perfected by nature over millions of years. One possibility to leverage proteins is the modification with artificial polymers. To obtain such protein-polymer conjugates, either a polymer can be grown from the protein surface (grafting-from) or a pre-synthesized polymer attached to the protein (grafting-to). Both techniques were used to synthesize conjugates of different proteins with thermo-responsive polymers in this thesis.
First, conjugates were analyzed by protein NMR spectroscopy. Typical characterization techniques for conjugates can verify the successful conjugation and give hints on the secondary structure of the protein. However, the 3-dimensional structure, being highly important for the protein function, cannot be probed by standard techniques. NMR spectroscopy is a unique method allowing to follow even small alterations in the protein structure. A mutant of the carbohydrate binding module 3b (CBM3bN126W) was used as model protein and functionalized with poly(N-isopropylacrylamide). Analysis of conjugates prepared by grafting-to or grafting-from revealed a strong impact of conjugation type on protein folding. Whereas conjugates prepared by grafting a pre-formed polymer to the protein resulted in complete preservation of protein folding, grafting the polymer from the protein surface led to (partial) disruption of the protein structure.
Next, conjugates of bovine serum albumin (BSA) as cheap and easily accessible protein were synthesized with PNIPAm and different oligoethylene glycol (meth)acrylates. The obtained protein-polymer conjugates were analyzed by an in-line combination of size exclusion chromatography and multi-angle laser light scattering (SEC-MALS). This technique is particular advantageous to determine molar masses, as no external calibration of the system is needed. Different SEC column materials and operation conditions were tested to evaluate the applicability of this system to determine absolute molar masses and hydrodynamic properties of heterogeneous conjugates prepared by grafting-from and grafting-to. Hydrophobic and non-covalent interactions of conjugates lead to error-prone values not in accordance to expected molar masses based on conversions and extents of modifications.
As alternative to this method, conjugates were analyzed by sedimentation velocity analytical ultracentrifugation (SV-AUC) to gain insights in the hydrodynamic properties and how they change after conjugation. Within a centrifugal field, a sample moves and fractionates according to the mass, density, and shape of its individual components. Conjugates of BSA with PNIPAm were analyzed below and above the cloud point temperature of the thermo-responsive polymer component. It was identified that the polymer characteristics were transferred to the conjugate molecule which than showed a decreased ideality – defined as increased deviation from a perfect sphere model – below and increased ideality above the cloud point temperature. This effect can be attributed to an arrangement of the polymer chain pointing towards the solvent (expanded state) or snuggling around the protein surface depending on the applied temperature.
The last project dealt with the synthesis of ferric hydroxamate uptake protein component A (FhuA)-polymer conjugates as building blocks for novel membrane materials. The shape of FhuA can be described as barrel and removal of a cork domain inside the protein results in a passive channel aimed to be utilized as pores in the membrane system. The polymer matrix surrounding the membrane protein is composed of a thermo-responsive and a UV-crosslinkable part. Therefore, an external trigger for covalent immobilization of these building blocks in the membrane and switchability of the membrane between different states was incorporated. The overall performance of membranes prepared by a drying-mediated self-assembly approach was evaluated by permeability and size exclusion experiments. The obtained membranes displayed an insufficiency in interchain crosslinking and therefore a lack in performance. Furthermore, the aimed switch between a hydrophilic and hydrophobic state of the polymer matrix did not occur. Correspondingly, size exclusion experiments did not result in a retention of analytes larger than the pores defined by the dimension of the used FhuA variant.
Overall, different paths to generate protein-polymer conjugates by either grafting-from or grafting-to the protein surface were presented paving the way to the generation of new hybrid materials. Different analytical methods were utilized to describe the folding and hydrodynamic properties of conjugates providing a deeper insight in the overall characteristics of these seminal building blocks.
Virtualizing physical space
(2021)
The true cost for virtual reality is not the hardware, but the physical space it requires, as a one-to-one mapping of physical space to virtual space allows for the most immersive way of navigating in virtual reality. Such “real-walking” requires physical space to be of the same size and the same shape of the virtual world represented. This generally prevents real-walking applications from running on any space that they were not designed for.
To reduce virtual reality’s demand for physical space, creators of such applications let users navigate virtual space by means of a treadmill, altered mappings of physical to virtual space, hand-held controllers, or gesture-based techniques. While all of these solutions succeed at reducing virtual reality’s demand for physical space, none of them reach the same level of immersion that real-walking provides.
Our approach is to virtualize physical space: instead of accessing physical space directly, we allow applications to express their need for space in an abstract way, which our software systems then map to the physical space available. We allow real-walking applications to run in spaces of different size, different shape, and in spaces containing different physical objects. We also allow users immersed in different virtual environments to share the same space.
Our systems achieve this by using a tracking volume-independent representation of real-walking experiences — a graph structure that expresses the spatial and logical relationships between virtual locations, virtual elements contained within those locations, and user interactions with those elements. When run in a specific physical space, this graph representation is used to define a custom mapping of the elements of the virtual reality application and the physical space by parsing the graph using a constraint solver. To re-use space, our system splits virtual scenes and overlap virtual geometry. The system derives this split by means of hierarchically clustering of our virtual objects as nodes of our bi-partite directed graph that represents the logical ordering of events of the experience. We let applications express their demands for physical space and use pre-emptive scheduling between applications to have them share space. We present several application examples enabled by our system. They all enable real-walking, despite being mapped to physical spaces of different size and shape, containing different physical objects or other users.
We see substantial real-world impact in our systems. Today’s commercial virtual reality applications are generally designing to be navigated using less immersive solutions, as this allows them to be operated on any tracking volume. While this is a commercial necessity for the developers, it misses out on the higher immersion offered by real-walking. We let developers overcome this hurdle by allowing experiences to bring real-walking to any tracking volume, thus potentially bringing real-walking to consumers.
Die eigentlichen Kosten für Virtual Reality Anwendungen entstehen nicht primär durch die erforderliche Hardware, sondern durch die Nutzung von physischem Raum, da die eins-zu-eins Abbildung von physischem auf virtuellem Raum die immersivste Art von Navigation ermöglicht. Dieses als „Real-Walking“ bezeichnete Erlebnis erfordert hinsichtlich Größe und Form eine Entsprechung von physischem Raum und virtueller Welt. Resultierend daraus können Real-Walking-Anwendungen nicht an Orten angewandt werden, für die sie nicht entwickelt wurden.
Um den Bedarf an physischem Raum zu reduzieren, lassen Entwickler von Virtual Reality-Anwendungen ihre Nutzer auf verschiedene Arten navigieren, etwa mit Hilfe eines Laufbandes, verfälschten Abbildungen von physischem zu virtuellem Raum, Handheld-Controllern oder gestenbasierten Techniken. All diese Lösungen reduzieren zwar den Bedarf an physischem Raum, erreichen jedoch nicht denselben Grad an Immersion, den Real-Walking bietet.
Unser Ansatz zielt darauf, physischen Raum zu virtualisieren: Anstatt auf den physischen Raum direkt zuzugreifen, lassen wir Anwendungen ihren Raumbedarf auf abstrakte Weise formulieren, den unsere Softwaresysteme anschließend auf den verfügbaren physischen Raum abbilden. Dadurch ermöglichen wir Real-Walking-Anwendungen Räume mit unterschiedlichen Größen und Formen und Räume, die unterschiedliche physische Objekte enthalten, zu nutzen. Wir ermöglichen auch die zeitgleiche Nutzung desselben Raums durch mehrere Nutzer verschiedener Real-Walking-Anwendungen.
Unsere Systeme erreichen dieses Resultat durch eine Repräsentation von Real-Walking-Erfahrungen, die unabhängig sind vom gegebenen Trackingvolumen – eine Graphenstruktur, die die räumlichen und logischen Beziehungen zwischen virtuellen Orten, den virtuellen Elementen innerhalb dieser Orte, und Benutzerinteraktionen mit diesen Elementen, ausdrückt. Bei der Instanziierung der Anwendung in einem bestimmten physischen Raum wird diese Graphenstruktur und ein Constraint Solver verwendet, um eine individuelle Abbildung der virtuellen Elemente auf den physischen Raum zu erreichen. Zur mehrmaligen Verwendung des Raumes teilt unser System virtuelle Szenen und überlagert virtuelle Geometrie. Das System leitet diese Aufteilung anhand eines hierarchischen Clusterings unserer virtuellen Objekte ab, die als Knoten unseres bi-partiten, gerichteten Graphen die logische Reihenfolge aller Ereignisse repräsentieren. Wir verwenden präemptives Scheduling zwischen den Anwendungen für die zeitgleiche Nutzung von physischem Raum. Wir stellen mehrere Anwendungsbeispiele vor, die Real-Walking ermöglichen – in physischen Räumen mit unterschiedlicher Größe und Form, die verschiedene physische Objekte oder weitere Nutzer enthalten.
Wir sehen in unseren Systemen substantielles Potential. Heutige Virtual Reality-Anwendungen sind bisher zwar so konzipiert, dass sie auf einem beliebigen Trackingvolumen betrieben werden können, aber aus kommerzieller Notwendigkeit kein Real-Walking beinhalten. Damit entgeht Entwicklern die Gelegenheit eine höhere Immersion herzustellen. Indem wir es ermöglichen, Real-Walking auf jedes Trackingvolumen zu bringen, geben wir Entwicklern die Möglichkeit Real-Walking zu ihren Nutzern zu bringen.
Brown adipose tissue (BAT) is responsible for non-shivering thermogenesis, thereby allowing mammals to maintain a constant body temperature in a cold environment. Thermogenic capacity of this tissue is due to a high mitochondrial density and expression of uncoupling protein 1 (UCP1), a unique brown adipocyte marker which dissipates the mitochondrial proton gradient to produce heat instead of ATP. BAT is actively involved in whole-body metabolic homeostasis and during aging there is a loss of classical brown adipose tissue with concomitantly reduced browning capacity of white adipose tissue. Therefore, an age-dependent decrease of BAT-related energy expenditure capacity may exacerbate the development of metabolic diseases, including obesity and type 2 diabetes mellitus. Given that direct effects of age-related changes of BAT-metabolic flux have yet to be unraveled, the aim of the current thesis is to investigate potential metabolic mechanisms involved in BAT-dysfunction during aging and to identify suitable metabolic candidates as functional biomarkers of BAT-aging. To this aim, integration of transcriptomic, metabolomic and proteomic data analyses of BAT from young and aged mice was performed, and a group of candidates with age-related changes was revealed. Metabolomic analysis showed age-dependent alterations of metabolic intermediates involved in energy, nucleotide and vitamin metabolism, with major alterations regarding the purine nucleotide pool. These data suggest a potential role of nucleotide intermediates in age-related BAT defects. In addition, the screening of transcriptomic and proteomic data sets from BAT of young and aged mice allowed identification of a 60-kDa lysophospholipase, also known as L-asparaginase (Aspg), whose expression declines during BAT-aging. Involvement of Aspg in brown adipocyte thermogenic function was subsequently analyzed at the molecular level using in vitro approaches and animal models. The findings revealed sensitivity of Aspg expression to β3-adrenergic activation via different metabolic cues, including cold exposure and treatment with β3-adrenergic agonist CL. To further examine ASPG function in BAT, an over-expression model of Aspg in a brown adipocyte cell line was established and showed that these cells were metabolically more active compared to controls, revealing increased expression of the main brown-adipocyte specific marker UCP1, as well as higher lipolysis rates. An in vitro loss-of-function model of Aspg was also functionally analyzed, revealing reduced brown adipogenic characteristics and an impaired lipolysis, thus confirming physiological relevance of Aspg in brown adipocyte function. Characterization of a transgenic mouse model with whole-body inactivation of the Aspg gene (Aspg-KO) allowed investigation of the role of ASPG under in vivo conditions, indicating a mild obesogenic phenotype, hypertrophic white adipocytes, impairment of the early thermogenic response upon cold-stimulation and dysfunctional insulin sensitivity. Taken together, these data show that ASPG may represent a new functional biomarker of BAT-aging that regulates thermogenesis and therefore a potential target for the treatment of age-related metabolic disease.
Discriminative Models for Biometric Identification using Micro- and Macro-Movements of the Eyes
(2021)
Human visual perception is an active process. Eye movements either alternate between fixations and saccades or follow a smooth pursuit movement in case of moving targets. Besides these macroscopic gaze patterns, the eyes perform involuntary micro-movements during fixations which are commonly categorized into micro-saccades, drift and tremor. Eye movements are frequently studied in cognitive psychology, because they reflect a complex interplay of perception, attention and oculomotor control.
A common insight of psychological research is that macro-movements are highly individual. Inspired by this finding, there has been a considerable amount of prior research on oculomotoric biometric identification. However, the accuracy of known approaches is too low and the time needed for identification is too long for any practical application. This thesis explores discriminative models for the task of biometric identification.
Discriminative models optimize a quality measure of the predictions and are usually superior to generative approaches in discriminative tasks. However, using discriminative models requires to select a suitable form of data representation for sequential eye gaze data; i.e., by engineering features or constructing a sequence kernel and the performance of the classification model strongly depends on the data representation. We study two fundamentally different ways of representing eye gaze within a discriminative framework. In the first part of this thesis, we explore the integration of data and psychological background knowledge in the form of generative models to construct representations. To this end, we first develop generative statistical models of gaze behavior during reading and scene viewing that account for viewer-specific distributional properties of gaze patterns. In a second step, we develop a discriminative identification model by deriving Fisher kernel functions from these and several baseline models. We find that an SVM with Fisher kernel is able to reliably identify users based on their eye gaze during reading and scene viewing. However, since the generative models are constrained to use low-frequency macro-movements, they discard a significant amount of information contained in the raw eye tracking signal at a high cost: identification requires about one minute of input recording, which makes it inapplicable for real world biometric systems. In the second part of this thesis, we study a purely data-driven modeling approach. Here, we aim at automatically discovering the individual pattern hidden in the raw eye tracking signal. To this end, we develop a deep convolutional neural network DeepEyedentification that processes yaw and pitch gaze velocities and learns a representation end-to-end. Compared to prior work, this model increases the identification accuracy by one order of magnitude and the time to identification decreases to only seconds. The DeepEyedentificationLive model further improves upon the identification performance by processing binocular input and it also detects presentation-attacks.
We find that by learning a representation, the performance of oculomotoric identification and presentation-attack detection can be driven close to practical relevance for biometric applications. Eye tracking devices with high sampling frequency and precision are expensive and the applicability of eye movement as a biometric feature heavily depends on cost of recording devices.
In the last part of this thesis, we therefore study the requirements on data quality by evaluating the performance of the DeepEyedentificationLive network under reduced spatial and temporal resolution. We find that the method still attains a high identification accuracy at a temporal resolution of only 250 Hz and a precision of 0.03 degrees. Reducing both does not have an additive deteriorating effect.
While patients are known to respond differently to drug therapies, current clinical practice often still follows a standardized dosage regimen for all patients. For drugs with a narrow range of both effective and safe concentrations, this approach may lead to a high incidence of adverse events or subtherapeutic dosing in the presence of high patient variability. Model-informedprecision dosing (MIPD) is a quantitative approach towards dose individualization based on mathematical modeling of dose-response relationships integrating therapeutic drug/biomarker monitoring (TDM) data. MIPD may considerably improve the efficacy and safety of many drug therapies. Current MIPD approaches, however, rely either on pre-calculated dosing tables or on simple point predictions of the therapy outcome. These
approaches lack a quantification of uncertainties and the ability to account for effects that are delayed. In addition, the underlying models are not improved while applied to patient data. Therefore, current approaches are not well suited for informed clinical decision-making based on a differentiated understanding of the individually predicted therapy outcome.
The objective of this thesis is to develop mathematical approaches for MIPD, which (i) provide efficient fully Bayesian forecasting of the individual therapy outcome including associated uncertainties, (ii) integrate Markov decision processes via reinforcement learning (RL) for a comprehensive decision framework for dose individualization, (iii) allow for continuous learning across patients and hospitals. Cytotoxic anticancer chemotherapy with its major dose-limiting toxicity, neutropenia, serves as a therapeutically relevant application example.
For more comprehensive therapy forecasting, we apply Bayesian data assimilation (DA) approaches, integrating patient-specific TDM data into mathematical models of chemotherapy-induced neutropenia that build on prior population analyses. The value of uncertainty quantification is demonstrated as it allows reliable computation of the patient-specific probabilities of relevant clinical quantities, e.g., the neutropenia grade. In view of novel home monitoring devices that increase the amount of TDM data available, the data processing of
sequential DA methods proves to be more efficient and facilitates handling of the variability between dosing events.
By transferring concepts from DA and RL we develop novel approaches for MIPD. While DA-guided dosing integrates individualized uncertainties into dose selection, RL-guided dosing provides a framework to consider delayed effects of dose selections. The combined
DA-RL approach takes into account both aspects simultaneously and thus represents a holistic approach towards MIPD. Additionally, we show that RL can be used to gain insights into important patient characteristics for dose selection. The novel dosing strategies substantially reduce the occurrence of both subtherapeutic and life-threatening neutropenia grades in a simulation study based on a recent clinical study (CEPAC-TDM trial) compared to currently used MIPD approaches.
If MIPD is to be implemented in routine clinical practice, a certain model bias with respect to the underlying model is inevitable, as the models are typically based on data from comparably small clinical trials that reflect only to a limited extent the diversity in real-world patient populations. We propose a sequential hierarchical Bayesian inference framework that enables continuous cross-patient learning to learn the underlying model parameters of the target patient population. It is important to note that the approach only requires summary information of the individual patient data to update the model. This separation of the individual inference from population inference enables implementation across different centers of care.
The proposed approaches substantially improve current MIPD approaches, taking into account new trends in health care and aspects of practical applicability. They enable progress towards more informed clinical decision-making, ultimately increasing patient benefits beyond the current practice.
Spatiotemporal variations of key air pollutants and greenhouse gases in the Himalayan foothills
(2021)
South Asia is a rapidly developing, densely populated and highly polluted region that is facing the impacts of increasing air pollution and climate change, and yet it remains one of the least studied regions of the world scientifically. In recognition of this situation, this thesis focuses on studying (i) the spatial and temporal variation of key greenhouse gases (CO2 and CH4) and air pollutants (CO and O3) and (ii) the vertical distribution of air pollutants (PM, BC) in the foothills of the Himalaya. Five sites were selected in the Kathmandu Valley, the capital region of Nepal, along with two sites outside of the valley in the Makawanpur and Kaski districts, and conducted measurements during the period of 2013-2014 and 2016. These measurements are analyzed in this thesis.
The CO measurements at multiple sites in the Kathmandu Valley showed a clear diurnal cycle: morning and evening levels were high, with an afternoon dip. There are slight differences in the diurnal cycles of CO2 and CH4, with the CO2 and CH4 mixing ratios increasing after the afternoon dip, until the morning peak the next day. The mixing layer height (MLH) of the nocturnal stable layer is relatively constant (~ 200 m) during the night, after which it transitions to a convective mixing layer during the day and the MLH increases up to 1200 m in the afternoon. Pollutants are thus largely trapped in the valley from the evening until sunrise the following day, and the concentration of pollutants increases due to emissions during the night. During afternoon, the pollutants are diluted due to the circulation by the valley winds after the break-up of the mixing layer. The major emission sources of GHGs and air pollutants in the valley are transport sector, residential cooking, brick kilns, trash burning, and agro-residue burning. Brick industries are influential in the winter and pre-monsoon season. The contribution of regional forest fires and agro-residue burning are seen during the pre-monsoon season. In addition, relatively higher CO values were also observed at the valley outskirts (Bhimdhunga and Naikhandi), which indicates the contribution of regional emission sources. This was also supported by the presence of higher concentrations of O3 during the pre-monsoon season.
The mixing ratios of CO2 (419.3 ±6.0 ppm) and CH4 (2.192 ±0.066 ppm) in the valley were much higher than at background sites, including the Mauna Loa observatory (CO2: 396.8 ± 2.0 ppm, CH4:1.831 ± 0.110 ppm) and Waligaun (CO2: 397.7 ± 3.6 ppm, CH4: 1.879 ± 0.009 ppm), China, as well as at an urban site Shadnagar (CH4: 1.92 ± 0.07 ppm) in India.
The daily 8 hour maximum O3 average in the Kathmandu Valley exceeds the WHO recommended value during more than 80% of the days during the pre-monsoon period, which represents a significant risk for human health and ecosystems in the region. Moreover, in the measurements of the vertical distribution of particulate matter, which were made using an ultralight aircraft, and are the first of their kind in the region, an elevated polluted layer at around ca. 3000 m asl. was detected over the Pokhara Valley. The layer could be associated with the large-scale regional transport of pollution. These contributions towards understanding the distributions of key air pollutants and their main sources will provide helpful information for developing management plans and policies to help reduce the risks for the millions of people living in the region.
The High Energy Stereoscopic System (H.E.S.S.) is an array of five imaging atmospheric Cherenkov telescopes located in the Khomas Highland of Namibia. H.E.S.S. operates in a wide energy range from several tens of GeV to several tens of TeV, reaching the best sensitivity around 1 TeV or at lower energies. However, there are many important topics – such as the search for Galactic PeVatrons, the study of gamma-ray production scenarios for sources (hadronic vs. leptonic), EBL absorption studies – which require good sensitivity at energies above 10 TeV. This work aims at improving the sensitivity of H.E.S.S. and increasing the gamma-ray statistics at high energies. The study investigates an enlargement of the H.E.S.S. effective field of view using events with larger offset angles in the analysis. The greatest challenges in the analysis of large-offset events are a degradation of the reconstruction accuracy and a rise of the background rate as the offset angle increases. The more sophisticated direction reconstruction method (DISP) and improvements to the standard background rejection technique, which by themselves are effective ways to increase the gamma-ray statistics and improve the sensitivity of the analysis, are implemented to overcome the above-mentioned issues. As a result, the angular resolution at the preselection level is improved by 5 - 10% for events at 0.5◦ offset angle and by 20 - 30% for events at 2◦ offset angle. The background rate at large offset angles is decreased nearly to a level typical for offset angles below 2.5◦. Thereby, sensitivity improvements of 10 - 20% are achieved for the proposed analysis compared to the standard analysis at small offset angles. Developed analysis also allows for the usage of events at large offset angles up to approximately 4◦, which was not possible before. This analysis method is applied to the analysis of the Galactic plane data above 10 TeV. As a result, 40 sources out of the 78 presented in the H.E.S.S. Galactic plane survey (HGPS) are detected above 10 TeV. Among them are representatives of all source classes that are present in the HGPS catalogue; namely, binary systems, supernova remnants, pulsar wind nebulae and composite objects. The potential of the improved analysis method is demonstrated by investigating the more than 10 TeV emission for two objects: the region associated with the shell-type SNR HESS J1731−347 and the PWN candidate associated with PSR J0855−4644 that is coincident with Vela Junior (HESS J0852−463).
Modern knowledge bases contain and organize knowledge from many different topic areas. Apart from specific entity information, they also store information about their relationships amongst each other. Combining this information results in a knowledge graph that can be particularly helpful in cases where relationships are of central importance. Among other applications, modern risk assessment in the financial sector can benefit from the inherent network structure of such knowledge graphs by assessing the consequences and risks of certain events, such as corporate insolvencies or fraudulent behavior, based on the underlying network structure. As public knowledge bases often do not contain the necessary information for the analysis of such scenarios, the need arises to create and maintain dedicated domain-specific knowledge bases.
This thesis investigates the process of creating domain-specific knowledge bases from structured and unstructured data sources. In particular, it addresses the topics of named entity recognition (NER), duplicate detection, and knowledge validation, which represent essential steps in the construction of knowledge bases.
As such, we present a novel method for duplicate detection based on a Siamese neural network that is able to learn a dataset-specific similarity measure which is used to identify duplicates. Using the specialized network architecture, we design and implement a knowledge transfer between two deduplication networks, which leads to significant performance improvements and a reduction of required training data.
Furthermore, we propose a named entity recognition approach that is able to identify company names by integrating external knowledge in the form of dictionaries into the training process of a conditional random field classifier. In this context, we study the effects of different dictionaries on the performance of the NER classifier. We show that both the inclusion of domain knowledge as well as the generation and use of alias names results in significant performance improvements.
For the validation of knowledge represented in a knowledge base, we introduce Colt, a framework for knowledge validation based on the interactive quality assessment of logical rules. In its most expressive implementation, we combine Gaussian processes with neural networks to create Colt-GP, an interactive algorithm for learning rule models. Unlike other approaches, Colt-GP uses knowledge graph embeddings and user feedback to cope with data quality issues of knowledge bases. The learned rule model can be used to conditionally apply a rule and assess its quality.
Finally, we present CurEx, a prototypical system for building domain-specific knowledge bases from structured and unstructured data sources. Its modular design is based on scalable technologies, which, in addition to processing large datasets, ensures that the modules can be easily exchanged or extended. CurEx offers multiple user interfaces, each tailored to the individual needs of a specific user group and is fully compatible with the Colt framework, which can be used as part of the system.
We conduct a wide range of experiments with different datasets to determine the strengths and weaknesses of the proposed methods. To ensure the validity of our results, we compare the proposed methods with competing approaches.
Natural products have proved to be a major resource in the discovery and development of many pharmaceuticals that are in use today. There is a wide variety of biologically active natural products that contain conjugated polyenes or benzofuran structures. Therefore, new synthetic methods for the construction of such building blocks are of great interest to synthetic chemists. The recently developed one-pot tethered ring-closing metathesis approach allows for the formation of Z,E-dienoates in high stereoselectivity. The extension of this method with a Julia-Kocienski olefination protocol would allow for the formation of conjugated trienes in a stereoselective manner. This strategy was applied in the total synthesis of conjugated triene containing (+)-bretonin B. Additionally, investigations of cross metathesis using methyl substituted olefins were pursued. This methodology was applied, as a one-pot cross metathesis/ring-closing metathesis sequence, in the total synthesis of benzofuran containing 7-methoxywutaifuranal. Finally, the design and synthesis of a catalyst for stereoretentive metathesis in aqueous media was investigated.
As the ongoing trend of developing smart materials that can reversibly switch geometry stimulated by environmental control addressed increasing attention in many research fields, especially for biomedical or soft robotic applications. Shape-memory polymers (SMPs), which can change shape, stiffness, size, and structure when exposed to an external stimulus, are intensively explored as encouraging material candidates for achieving multifunctionality, and for miniaturizing into micro-components to expand the applications. Besides, the geometrical design has gained growing attention for creating engineering applications, such as bi-stable mechanisms, and has the potential to be explored by implementing SMP for new functions. In this context, this thesis aimed to develop smart micro-/nano-objects based on SMP and explore new functions by geometrical design using SMP. Here, two types of stimuli-responsive objects capable of one-way temperature-memory effect (TME) or free-standing reversible actuation e.g., micro/nanofibers (i) and microcuboids (ii) at different aspects were explored. At first, it was hypothesized that the advanced atomic force microscopy (AFM) platform can be established to study individual polymeric micro-/nanofibers (i) in terms of incorporation and characterization of a reversible shape-memory actuation capability. Crystallizable material was chosen for preparing the fibers and the molecular alignment within the fibers among different diameters will influence the crystallization-induced elongation during cooling that determined the reversible effect. For the second type, microcuboids (ii), it was hypothesized that a programming and quantification approach can be developed to enable the realization and characterization of a one-way micro-TME and micro-shape-memory polymer actuation (SMPA) in microcuboids. The responsive temperature of one-way shape transformation can be tuned by programming temperature (Tp) and the separation temperature (Tsep) for post-programming can influence the actuation. Finally, a geometrical design with bi-stability was combined with SME to create new functions of shape actuation. It was hypothesized that the predicted bi-stable or mono-stable structures can be achieved with the aid of digital fabrication methods. Using shape-memory effect (SME), the alteration of bi-stable and mono-stable can initiate shape transformation with a larger magnitude and higher energy output.
In the first part, the method to quantify the reversible SMPA of a single micro/nano crystallizable fiber with geometry change during the actuation was explored. Electrospinning was used to prepare poly (ε-caprolactone) (PCL) micro/nanofiber with different diameters, which were fixed by UV glue and crosslinked on the structured silicon wafer. Using AFM, the programming, as well as the observation of recovery and reversible displacement of the fiber, were performed by vertical three-point bending at the free suspended part. A plateau tip was chosen to achieve stable contact and longer working distance for performing larger deformation, enabling intensified reversible SMPA of single fibers. In this way, programming strains of 39 ± 1% or 46 ± 1% were realized for fiber with a diameter of 1 ± 0.2 µm and 300 ± 50 nm, which were bent at 80 °C and fixed at 10 °C. Values for the reversible elongation of εrev = 3.4 ± 0.1% and 10.5 ± 0.1% were obtained for a single micro and nanofiber respectively between 10 and 60 °C. The higher actuation effect observed for nanofiber demonstrated that the highly compact and oriented crystallites in nanofibers, which determined the pronounced εrev compared to the thick microfibers. Besides, a stable reversible actuation of a nanofiber can be tracked by AFM tip up to 10 cycles, indicating a sustainable application can be achieved on the fiber actuators. The findings obtained for cPCL micro-/nano-fibers will help design and evaluate the next generation polymeric microactuators or micromanipulators.
The second part of the thesis studies the shape-memory effect (SME) of a single individual SMP micro-object by controlling deformation temperatures during programming and actuation temperatures during reversible change. In this work, microcuboids of crosslinked poly[ethylene-co-(vinyl acetate)] (cPEVA) elastomers with 18 wt% vinyl acetate (VA) contents were successfully prepared by template-based replication from polydimethylsiloxane (PDMS) mold. The micro-TME and micro-SMPA were observed and studied based on micro-geometry change using optical microscopy (OM) and AFM. Different switching temperatures of shape recovery were achieved from 55 °C to 86 °C by tuning Tp from 55 °C to 100 °C, indicating a successful implementation of micro-TME on individual microcuboid. For micro-SMPA functionalization, microcuboids were deformed by compression at 100 °C and the change in single particle height was monitored during cyclic heating and cooling between various Tseps from 60 °C to 85 °C and 20 °C. The micro-SMPA on a single microcuboid was achieved with a reversible strain in the range of 2 to 7%, whereby higher compression ratio CR and Tsep induced prominent reversible strain. The results achieved in this work demonstrated the successful functionalization of microcuboids with different SMEs by controlling temperatures during programming and actuation processes. Based on these achievements, such micro-objects can be further designed as on demand switchable microactuators or release systems with adjustable working temperatures.
In the last part of the work, a new function of shape-memory polymeric bi-stable 3D structured film was designed and fabricated. The SME and geometrical design of compliant mechanics were merged to enable switching between bi-stable and mono-stable states, which generate snap movement that mimics the Venus flytrap. A truncated tetrahedron structure with a slope angle as a tunable parameter to alter the bi-stability was chosen for the study to combine with
SME. It was anticipated that the structured film designed with a slope angle of 30° exhibited mono-stable behavior, and such a structure with a slope angle of 45° exhibited bi-stable behavior. Then the structured SMP film of designed mono-stable shape was successfully fabricated using soft lithography based on 3D printed master molds supported from digital manufacturing. The structured mold was also used in programming the SMP film into the structure with a higher slope angle to attain bi-stability. Finally, the switching between bi-stable and mono-stable states was successfully realized using SME, which introduces snapping movement triggered by heat. The implementation of compliant mechanisms by the SME increased the magnitude of thermally induced reconfiguration without additional external force.
To sum up, the results of the thesis support the development of smart objects capable of one-way micro-TME, free-standing reversible actuation, or bi-stability mediated shape-memory reconfiguration. Electrospinning and template-based method were used for fabrication with good control of geometry and low size dispersity. Microscopy methods especially the AFM platform with decent sensitivity was developed for implementation as well as characterization of SME on individual micro-/nanoobjects. Implementation of bi-stability improves the shape transformation amplitude of thermally triggered SMP. These findings can give novel insights for designing polymer-based actuators or soft robotics.
The survey of the prevalence of chronic ankle instability in elite Taiwanese basketball athletes
(2021)
BACKGROUND: Ankle sprains are common in basketball. It could develop into Chronic Ankle Instability (CAI) causing decreased quality of life, functional performance, early osteoarthritis, and increased risk of other injuries. To develop a strategy of CAI prevention, localized epidemiology data and a valid/reliable tool are essential. However, the epidemiological data of CAI is not conclusive from previous studies and the prevalence of CAI in Taiwanese basketball athletes are not clear. In addition, a valid and reliable tool among the Taiwan-Chinese version to evaluate ankle instability is missing.
PURPOSE: The aims were to have an overview of the prevalence of CAI in sports population using a systematic review, to develop a valid and reliable cross-cultural adapted Cumberland Ankle Instability Tool Questionnaire (CAIT) in Taiwan-Chinese (CAIT-TW), and to survey the prevalence of CAI in elite basketball athletes in Taiwan using CAIT-TW.
METHODS: Firstly, a systematic search was conducted. Research articles applying CAI related questionnaires in order to survey the prevalence of CAI were included in the review. Second, the English version of CAIT was translated and cross-culturally adapted into the CAIT-TW. The construct validity, test-retest reliability, internal consistency, and cutoff score of CAIT-TW were evaluated in an athletic population (N=135). Finally, the cross-sectional data of CAI prevalence in 388 elite Taiwanese basketball athletes were presented. Demographics, presence of CAI, and difference of prevalence between gender, different competitive levels and play positions were evaluated.
RESULTS: The prevalence of CAI was 25%, ranging between 7% and 53%. The prevalence of CAI among participants with a history of ankle sprains was 46%, ranging between 9% and 76%. In addition, the cross-cultural adapted CAIT-TW showed a moderate to strong construct validity, an excellent test-retest reliability, a good internal consistency, and a cutoff score of 21.5 for the Taiwanese athletic population. Finally, 26% of Taiwanese basketball athletes had unilateral CAI while 50% of them had bilateral CAI. In addition, women athletes in the investigated cohort had a higher prevalence of CAI than men. There was no difference in prevalence between competitive levels and among play positions.
CONCLUSION: The systematic review shows that the prevalence of CAI has a wide range among included studies. This could be due to the different exclusion criteria, age, sports discipline, or other factors among the included studies. For future studies, standardized criteria to investigate the epidemiology of CAI are required. The CAI epidemiological study should be prospective. Factors affecting the prevalence of CAI ability should be investigated and described. The translated CAIT-TW is a valid and reliable tool to differentiate between stable and unstable ankles in athletes and may further apply for research or daily practice in Taiwan. In the Taiwanese basketball population, CAI is highly prevalent. This might relate to the research method, preexisting ankle instability, and training-related issues. Women showed a higher prevalence of CAI than men. When applying the preventive measure, gender should be taken into consideration.
As society paves its way towards device miniaturization and precision medicine, micro-scale actuation and guided transport become increasingly prominent research fields, with high potential impact in both technological and clinical contexts. In order to accomplish directed motion of micron-sized objects, as biosensors and drug-releasing microparticles, towards specific target sites, a promising strategy is the use of living cells as smart biochemically-powered carriers, building the so-called bio-hybrid systems. Inspired by leukocytes, native cells of living organisms efficiently migrating to critical targets as tumor tissue, an emerging concept is to exploit the amoeboid crawling motility of such cells as mean of transport for drug delivery applications.
In the research work described in this thesis, I synergistically applied experimental, computational and theoretical modeling approaches to investigate the behaviour and transport mechanism of a novel kind of bio-hybrid system for active transport at the micro-scale, referred to as cellular truck. This system consists of an amoeboid crawling cell, the carrier, attached to a microparticle, the cargo, which may ideally be drug-loaded for specific therapeutic treatments.
For the purposes of experimental investigation, I employed the amoeba Dictyostelium discoideum as crawling cellular carrier, being a renowned model organism for leukocyte migration and, in general, for eukaryotic cell motility. The performed experiments revealed a complex recurrent cell-cargo relative motion, together with an intermittent motility of the cellular truck as a whole. The evidence suggests the presence of cargoes on amoeboid cells to act as mechanical stimulus leading cell polarization, thus promoting cell motility and giving rise to the observed intermittent dynamics of the truck. Particularly, bursts in cytoskeletal polarity along the cell-cargo axis have been
found to occur in time with a rate dependent on cargo geometrical features, as particle diameter. Overall, the collected experimental evidence pointed out a pivotal role of cell-cargo interactions in the emergent cellular truck motion dynamics. Especially, they can determine the transport capabilities of amoeboid cells, as the cargo size significantly impacts the cytoskeletal activity and repolarization dynamics along the cell-cargo axis, the latter responsible for truck displacement and reorientation.
Furthermore, I developed a modeling framework, built upon the experimental evidence on cellular truck behaviour, that connects the relative dynamics and interactions arising at the truck scale with the actual particle transport dynamics. In fact, numerical simulations of the proposed model successfully reproduced the phenomenology of the cell-cargo system, while enabling the prediction of the transport properties of cellular trucks over larger spatial and temporal scales. The theoretical analysis provided a deeper understanding of the role of cell-cargo interaction on mass transport, unveiling in particular how the long-time transport efficiency is governed by the interplay between the persistence time of cell polarity and time scales of the relative dynamics stemming from cell-cargo interaction. Interestingly, the model predicts the existence of an optimal cargo size, enhancing the diffusivity of cellular trucks; this is in line with previous independent experimental data, which appeared rather counterintuitive and had no explanation prior to this study.
In conclusion, my research work shed light on the importance of cargo-carrier interactions in the context of crawling cell-mediated particle transport, and provides a prototypical, multifaceted framework for the analysis and modelling of such complex bio-hybrid systems and their perspective optimization.
The presented study investigated the influence of microbial and biogeochemical processes on the physical transport related properties and the fate of microplastics in freshwater reservoirs. The overarching goal was to elucidate the mechanisms leading to sedimentation and deposition of microplastics in such environments. This is of importance, as large amounts of initially buoyant microplastics are found in reservoir sediments worldwide. However, the transport processes which lead to microplastics accumulation in sediments, were up to now understudied.
The impact of biofilm formation on the density and subsequent sedimentation of microplastics was investigated in the eutrophic Bautzen reservoirs (Chapter 2). Biofilms are complex microbial communities fixed to submerged surfaces through a slimy organic film. The mineral calcite was detected in the biofilms, which led to the
sinking of the overgrown microplastic particles. The calcite was of biogenic origin, most likely precipitated by sessile cyanobacteria within the biofilms.
Biofilm formation was also studied in the mesotrophic Malter reservoir. Unlike in Bautzen reservoir, biofilm formation did not govern the sedimentation of different microplastics in Malter reservoir (Chapter 3). Instead autumnal lake mixing led to
the formation of sinking aggregates of microplastics and iron colloids. Such colloids form when anoxic, iron-rich water from the hypolimnion mixes with the oxygenated epilimnetic waters. The colloids bind organic material from the lake water, which leads to the formation of large and sinking iron-organo flocs.
Hence, iron-organo floc formation and their influence on the buoyancy or burial of microplastics into sediments of Bautzen reservoir was studied in laboratory experiments (Chapter 4). Microplastics of different shapes (fiber, fragment, sphere) and sizes were readily incorporated into sinking iron-organo flocs. By this initially buoyant polyethylene microplastics were transported on top of sediments from Bautzen reservoir. Shortly after deposition, the microplastic bearing flocs started to subside and transported the pollutants into deeper sediment layers. The microplastics were not released from the sediments within two months of laboratory incubation.
The stability of floc microplastic deposition was further investigated employing experiments with the iron reducing model organism Shewanella oneidensis (Chapter 5). It was shown, that reduction or re-mineralization of the iron minerals did not affect the integrity of the iron-organo flocs. The organic matrix was stable under iron reducing conditions. Hence, no incorporated microplastics were released from the flocs. As similar processes are likely to take place in natural sediments, this might explain the previous described low microplastic release from the sediments.
This thesis introduced different mechanisms leading to the sedimentation of initially buoyant microplastics and to their subsequent deposition in freshwater reservoirs. Novel processes such as the aggregation with iron-organo flocs were identified and the understudied issue of biofilm densification through biogenic mineral formation was further investigated. The findings might have implications for the fate of microplastics within the river-reservoir system and outline the role of freshwater reservoirs as important accumulation zone for microplastics. Microplastics deposited in the sediments of reservoirs might not be transported further by through flowing river. Hence the study might contribute to better risk assessment and transport balances of these anthropogenic contaminants.
As part of our everyday life we consume breaking news and interpret it based on our own viewpoints and beliefs. We have easy access to online social networking platforms and news media websites, where we inform ourselves about current affairs and often post about our own views, such as in news comments or social media posts. The media ecosystem enables opinions and facts to travel from news sources to news readers, from news article commenters to other readers, from social network users to their followers, etc. The views of the world many of us have depend on the information we receive via online news and social media. Hence, it is essential to maintain accurate, reliable and objective online content to ensure democracy and verity on the Web. To this end, we contribute to a trustworthy media ecosystem by analyzing news and social media in the context of politics to ensure that media serves the public interest. In this thesis, we use text mining, natural language processing and machine learning techniques to reveal underlying patterns in political news articles and political discourse in social networks.
Mainstream news sources typically cover a great amount of the same news stories every day, but they often place them in a different context or report them from different perspectives. In this thesis, we are interested in how distinct and predictable newspaper journalists are, in the way they report the news, as a means to understand and identify their different political beliefs. To this end, we propose two models that classify text from news articles to their respective original news source, i.e., reported speech and also news comments. Our goal is to capture systematic quoting and commenting patterns by journalists and news commenters respectively, which can lead us to the newspaper where the quotes and comments are originally published. Predicting news sources can help us understand the potential subjective nature behind news storytelling and the magnitude of this phenomenon. Revealing this hidden knowledge can restore our trust in media by advancing transparency and diversity in the news.
Media bias can be expressed in various subtle ways in the text and it is often challenging to identify these bias manifestations correctly, even for humans. However, media experts, e.g., journalists, are a powerful resource that can help us overcome the vague definition of political media bias and they can also assist automatic learners to find the hidden bias in the text. Due to the enormous technological advances in artificial intelligence, we hypothesize that identifying political bias in the news could be achieved through the combination of sophisticated deep learning modelsxi and domain expertise. Therefore, our second contribution is a high-quality and reliable news dataset annotated by journalists for political bias and a state-of-the-art solution for this task based on curriculum learning. Our aim is to discover whether domain expertise is necessary for this task and to provide an automatic solution for this traditionally manually-solved problem. User generated content is fundamentally different from news articles, e.g., messages are shorter, they are often personal and opinionated, they refer to specific topics and persons, etc. Regarding political and socio-economic news, individuals in online communities make use of social networks to keep their peers up-to-date and to share their own views on ongoing affairs. We believe that social media is also an as powerful instrument for information flow as the news sources are, and we use its unique characteristic of rapid news coverage for two applications. We analyze Twitter messages and debate transcripts during live political presidential debates to automatically predict the topics that Twitter users discuss. Our goal is to discover the favoured topics in online communities on the dates of political events as a way to understand the political subjects of public interest. With the up-to-dateness of microblogs, an additional opportunity emerges, namely to use social media posts and leverage the real-time verity about discussed individuals to find their locations.
That is, given a person of interest that is mentioned in online discussions, we use the wisdom of the crowd to automatically track her physical locations over time. We evaluate our approach in the context of politics, i.e., we predict the locations of US politicians as a proof of concept for important use cases, such as to track people that
are national risks, e.g., warlords and wanted criminals.
The goal of this dissertation is to empirically evaluate the predictions of two classes of models applied to language processing: the similarity-based interference models (Lewis & Vasishth, 2005; McElree, 2000) and the group of smaller-scale accounts that we will refer to as faulty encoding accounts (Eberhard, Cutting, & Bock, 2005; Bock & Eberhard, 1993). Both types of accounts make predictions with regard to processing the same class of structures: sentences containing a non-subject (interfering) noun in addition to a subject noun and a verb. Both accounts make the same predictions for processing ungrammatical sentences with a number-mismatching interfering noun, and this prediction finds consistent support in the data. However, the similarity-based interference accounts predict similar effects not only for morphosyntactic, but also for the semantic level of language organization. We verified this prediction in three single-trial online experiments, where we found consistent support for the predictions of the similarity-based interference account. In addition, we report computational simulations further supporting the similarity-based interference accounts. The combined evidence suggests that the faulty encoding accounts are not required to explain comprehension of ill-formed sentences.
For the processing of grammatical sentences, the accounts make conflicting predictions, and neither the slowdown predicted by the similarity-based interference account, nor the complementary slowdown predicted by the faulty encoding accounts were systematically observed. The majority of studies found no difference between the compared configurations. We tested one possible explanation for the lack of predicted difference, namely, that both slowdowns are present simultaneously and thus conceal each other. We decreased the amount of similarity-based interference: if the effects were concealing each other, decreasing one of them should allow the other to surface. Surprisingly, throughout three larger-sample single-trial online experiments, we consistently found the slowdown predicted by the faulty encoding accounts, but no effects consistent with the presence of inhibitory interference.
The overall pattern of the results observed across all the experiments reported in this dissertation is consistent with previous findings: predictions of the interference accounts for the processing of ungrammatical sentences receive consistent support, but the predictions for the processing of grammatical sentences are not always met. Recent proposals by Nicenboim et al. (2016) and Mertzen et al. (2020) suggest that interference might arise only in people with high working memory capacity or under deep processing mode. Following these proposals, we tested whether interference effects might depend on the depth of processing: we manipulated the complexity of the training materials preceding the grammatical experimental sentences while making no changes to the experimental materials themselves. We found that the slowdown predicted by the faulty encoding accounts disappears in the deep processing mode, but the effects consistent with the predictions of the similarity-based interference account do not arise.
Independently of whether similarity-based interference arises under deep processing mode or not, our results suggest that the faulty encoding accounts cannot be dismissed since they make unique predictions with regard to processing grammatical sentences, which are supported by data. At the same time, the support is not unequivocal: the slowdowns are present only in the superficial processing mode, which is not predicted by the faulty encoding accounts. Our results might therefore favor a much simpler system that superficially tracks number features and is distracted by every plural feature.
Smart contracts promise to reform the legal domain by automating clerical and procedural work, and minimizing the risk of fraud and manipulation. Their core idea is to draft contract documents in a way which allows machines to process them, to grasp the operational and non-operational parts of the underlying legal agreements, and to use tamper-proof code execution alongside established judicial systems to enforce their terms. The implementation of smart contracts has been largely limited by the lack of an adequate technological foundation which does not place an undue amount of trust in any contract party or external entity. Only recently did the emergence of Decentralized Applications (DApps) change this: Stored and executed via transactions on novel distributed ledger and blockchain networks, powered by complex integrity and consensus protocols, DApps grant secure computation and immutable data storage while at the same time eliminating virtually all assumptions of trust.
However, research on how to effectively capture, deploy, and most of all enforce smart contracts with DApps in mind is still in its infancy. Starting from the initial expression of a smart contract's intent and logic, to the operation of concrete instances in practical environments, to the limits of automatic enforcement---many challenges remain to be solved before a widespread use and acceptance of smart contracts can be achieved.
This thesis proposes a model-driven smart contract management approach to tackle some of these issues. A metamodel and semantics of smart contracts are presented, containing concepts such as legal relations, autonomous and non-autonomous actions, and their interplay. Guided by the metamodel, the notion and a system architecture of a Smart Contract Management System (SCMS) is introduced, which facilitates smart contracts in all phases of their lifecycle. Relying on DApps in heterogeneous multi-chain environments, the SCMS approach is evaluated by a proof-of-concept implementation showing both its feasibility and its limitations.
Further, two specific enforceability issues are explored in detail: The performance of fully autonomous tamper-proof behavior with external off-chain dependencies and the evaluation of temporal constraints within DApps, both of which are essential for smart contracts but challenging to support in the restricted transaction-driven and closed environment of blockchain networks. Various strategies of implementing or emulating these capabilities, which are ultimately applicable to all kinds of DApp projects independent of smart contracts, are presented and evaluated.
Conceptual knowledge about objects, people and events in the world is central to human cognition, underlying core cognitive abilities such as object recognition and use, and word comprehension. Previous research indicates that concepts consist of perceptual and motor features represented in modality-specific perceptual-motor brain regions. In addition, cross-modal convergence zones integrate modality-specific features into more abstract conceptual representations.
However, several questions remain open: First, to what extent does the retrieval of perceptual-motor features depend on the concurrent task? Second, how do modality-specific and cross-modal regions interact during conceptual knowledge retrieval? Third, which brain regions are causally relevant for conceptually-guided behavior? This thesis addresses these three key issues using functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS) in the healthy human brain.
Study 1 - an fMRI activation study - tested to what extent the retrieval of sound and action features of concepts, and the resulting engagement of auditory and somatomotor brain regions depend on the concurrent task. 40 healthy human participants performed three different tasks - lexical decision, sound judgment, and action judgment - on words with a high or low association to sounds and actions. We found that modality-specific regions selectively respond to task-relevant features: Auditory regions selectively responded to sound features during sound judgments, and somatomotor regions selectively responded to action features during action judgments. Unexpectedly, several regions (e.g. the left posterior parietal cortex; PPC) exhibited a task-dependent response to both sound and action features. We propose these regions to be "multimodal", and not "amodal", convergence zones which retain modality-specific information.
Study 2 - an fMRI connectivity study - investigated the functional interaction between modality-specific and multimodal areas during conceptual knowledge retrieval. Using the above fMRI data, we asked (1) whether modality-specific and multimodal regions are functionally coupled during sound and action feature retrieval, (2) whether their coupling depends on the task, (3) whether information flows bottom-up, top-down, or bidirectionally, and (4) whether their coupling is behaviorally relevant. We found that functional coupling between multimodal and modality-specific areas is task-dependent, bidirectional, and relevant for conceptually-guided behavior. Left PPC acted as a connectivity "switchboard" that flexibly adapted its coupling to task-relevant modality-specific nodes.
Hence, neuroimaging studies 1 and 2 suggested a key role of left PPC as a multimodal convergence zone for conceptual knowledge. However, as neuroimaging is correlational, it remained unknown whether left PPC plays a causal role as a multimodal conceptual hub. Therefore, study 3 - a TMS study - tested the causal relevance of left PPC for sound and action feature retrieval. We found that TMS over left PPC selectively impaired action judgments on low sound-low action words, as compared to sham stimulation. Computational simulations of the TMS-induced electrical field revealed that stronger stimulation of left PPC was associated with worse performance on action, but not sound, judgments. These results indicate that left PPC causally supports conceptual processing when action knowledge is task-relevant and cannot be compensated by sound knowledge. Our findings suggest that left PPC is specialized for action knowledge, challenging the view of left PPC as a multimodal conceptual hub.
Overall, our studies support "hybrid theories" which posit that conceptual processing involves both modality-specific perceptual-motor regions and cross-modal convergence zones. In our new model of the conceptual system, we propose conceptual processing to rely on a representational hierarchy from modality-specific to multimodal up to amodal brain regions. Crucially, this hierarchical system is flexible, with different regions and connections being engaged in a task-dependent fashion. Our model not only reconciles the seemingly opposing grounded cognition and amodal theories, it also incorporates task dependency of conceptually-related brain activity and connectivity, thereby resolving several current issues on the neural basis of conceptual knowledge retrieval.
In our daily life, recurrence plays an important role on many spatial and temporal scales and in different contexts. It is the foundation of learning, be it in an evolutionary or in a neural context. It therefore seems natural that recurrence is also a fundamental concept in theoretical dynamical systems science. The way in which states of a system recur or develop in a similar way from similar initial states makes it possible to infer information about the underlying dynamics of the system. The mathematical space in which we define the state of a system (state space) is often high dimensional, especially in complex systems that can also exhibit chaotic dynamics. The recurrence plot (RP) enables us to visualize the recurrences of any high-dimensional systems in a two-dimensional, binary representation. Certain patterns in RPs can be related to physical properties of the underlying system, making the qualitative and quantitative analysis of RPs an integral part of nonlinear systems science. The presented work has a methodological focus and further develops recurrence analysis (RA) by addressing current research questions related to an increasing amount of available data and advances in machine learning techniques. By automatizing a central step in RA, namely the reconstruction of the state space from measured experimental time series, and by investigating the impact of important free parameters this thesis aims to make RA more accessible to researchers outside of physics.
The first part of this dissertation is concerned with the reconstruction of the state space from time series. To this end, a novel idea is proposed which automates the reconstruction problem in the sense that there is no need to preprocesse the data or estimate parameters a priori. The key idea is that the goodness of a reconstruction can be evaluated by a suitable objective function and that this function is minimized in the embedding process. In addition, the new method can process multivariate time series input data. This is particularly important because multi-channel sensor-based observations are ubiquitous in many research areas and continue to increase. Building on this, the described minimization problem of the objective function is then processed using a machine learning approach.
In the second part technical and methodological aspects of RA are discussed. First, we mathematically justify the idea of setting the most influential free parameter in RA, the recurrence threshold ε, in relation to the distribution of all pairwise distances in the data. This is especially important when comparing different RPs and their quantification statistics and is fundamental to any comparative study. Second, some aspects of recurrence quantification analysis (RQA) are examined. As correction schemes for biased RQA statistics, which are based on diagonal lines, we propose a simple method for dealing with border effects of an RP in RQA and a skeletonization algorithm for RPs. This results in less biased (diagonal line based) RQA statistics for flow-like data. Third, a novel type of RQA characteristic is developed, which can be viewed as a generalized non-linear powerspectrum of high dimensional systems. The spike powerspectrum transforms a spike-train like signal into its frequency domain. When transforming the diagonal line-dependent recurrence rate (τ-RR) of a RP in this way, characteristic periods, which can be seen in the state space representation of the system can be unraveled. This is not the case, when Fourier transforming τ-RR.
Finally, RA and RQA are applied to climate science in the third part and neuroscience in the fourth part. To the best of our knowledge, this is the first time RPs and RQA have been used to analyze lake sediment data in a paleoclimate context. Therefore, we first elaborate on the basic formalism and the interpretation of visually visible patterns in RPs in relation to the underlying proxy data. We show that these patterns can be used to classify certain types of variability and transitions in the Potassium record from six short (< 17m) sediment cores collected during the Chew Bahir Drilling Project. Building on this, the long core (∼ m composite) from the same site is analyzed and two types of variability and transitions are
identified and compared with ODP Site wetness index from the eastern Mediterranean. Type variability likely reflects the influence of precessional forcing in the lower latitudes at times of maximum values of the long eccentricity cycle ( kyr) of the earth’s orbit around the sun, with a tendency towards extreme events. Type variability appears to be related to the minimum values of this cycle and corresponds to fairly rapid transitions between relatively dry and relatively wet conditions.
In contrast, RQA has been applied in the neuroscientific context for almost two decades. In the final part, RQA statistics are used to quantify the complexity in a specific frequency band of multivariate EEG (electroencephalography) data. By analyzing experimental data, it can be shown that the complexity of the signal measured in this way across the sensorimotor cortex decreases as motor tasks are performed. The results are consistent with and comple- ment the well known concepts of motor-related brain processes. We assume that the thus discovered features of neuronal dynamics in the sensorimotor cortex together with the robust RQA methods for identifying and classifying these contribute to the non-invasive EEG-based development of brain-computer interfaces (BCI) for motor control and rehabilitation.
The present work is an important step towards a robust analysis of complex systems based on recurrence.
Identification of chemical mediators that regulate the specialized metabolism in Nostoc punctiforme
(2021)
Specialized metabolites, so-called natural products, are produced by a variety of different organisms, including bacteria and fungi. Due to their wide range of different biological activities, including pharmaceutical relevant properties, microbial natural products are an important source for drug development. They are encoded by biosynthetic gene clusters (BGCs), which are a group of locally clustered genes. By screening genomic data for genes encoding typical core biosynthetic enzymes, modern bioinformatical approaches are able to predict a wide range of BGCs. To date, only a small fraction of the predicted BGCs have their associated products identified.
The phylum of the cyanobacteria has been shown to be a prolific, but largely untapped source for natural products. Especially multicellular cyanobacterial genera, like Nostoc, harbor a high amount of BGCs in their genomes.
A main goal of this study was to develop new concepts for the discovery of natural products in cyanobacteria. Due to its diverse setup of orphan BGCs and its amenability to genetic manipulation, Nostoc punctiforme PCC 73102 (N. punctiforme) appeared to be a promising candidate to be established as a model organism for natural product discovery in cyanobacteria. By utilizing a combination of genome-mining, bioactivity-screening, variations of culture conditions, as well as metabolic engineering, not only two new polyketides were discovered, but also first-time insights into the regulation of the specialized metabolism in N. punctiforme were gained during this study.
The cultivation of N. punctiforme to very high densities by utilizing increasing light intensities and CO2 levels, led to an enhanced metabolite production, causing rather complex metabolite extracts. By utilizing a library of CFP reporter mutant strains, each strain reporting for one of the predicted BGCs, it was shown that eight out of 15 BGCs were upregulated under high density (HD) cultivation conditions. Furthermore, it could be demonstrated that the supernatant of an HD culture can increase the expression of four of the influenced BGCs, even under conventional cultivation conditions. This led to the hypothesis that a chemical mediator encoded by one of the affected BGCs is accumulating in the HD supernatant and is able to increase the expression of other BGCs as part of a cell-density dependent regulatory circuit. To identify which of the BGCs could be a main trigger of the presumed regulatory circuit, it was tried to activate four BGCs (pks1, pks2, ripp3, ripp4) selectively by overexpression of putative pathway-specific regulatory genes that were found inside the gene clusters. Transcriptional analysis of the mutants revealed that only the mutant strain targeting the pks1 BGC, called AraC_PKS1, was able to upregulate the expression of its associated BGC. From an RNA sequencing study of the AraC_PKS1 mutant strain, it was discovered that beside pks1, the orphan BGCs ripp3 and ripp4 were also upregulated in the mutant strain. Furthermore, it was observed that secondary metabolite production in the AraC_PKS1 mutant strain is further enhanced under high-light and high-CO2 cultivation conditions. The increased production of the pks1 regulator NvlA also had an impact on other regulatory factors, including sigma factors and the RNA chaperone Hfq. Analysis of the AraC_PKS1 cell and supernatant extracts led to the discovery of two novel polyketides, nostoclide and nostovalerolactone, both encoded by the pks1 BGC. Addition of the polyketides to N. punctiforme WT demonstrated that the pks1-derived compounds are able to partly reproduce the effects on secondary metabolite production found in the AraC_PKS1 mutant strain. This indicates that both compounds are acting as extracellular signaling factors as part of a regulatory network. Since not all transcriptional effects that were found in the AraC_PKS1 mutant strain could be reproduced by the pks1 products, it can be assumed that the regulator NvlA has a global effect and is not exclusively specific to the pks1 pathway.
This study was the first to use a putative pathway specific regulator for the specific activation of BGC expression in cyanobacteria. This strategy did not only lead to the detection of two novel polyketides, it also gave first-time insights into the regulatory mechanism of the specialized metabolism in N. punctiforme. This study illustrates that understanding regulatory pathways can aid in the discovery of novel natural products. The findings of this study can guide the design of new screening strategies for bioactive compounds in cyanobacteria and help to develop high-titer production platforms for cyanobacterial natural products.
Silicate melts are major components of the Earth’s interior and as such they make an essential contribution in igneous processes, in the dynamics of the solid Earth and the chemical development of the entire Earth. Macroscopic physical and chemical properties such as density, compressibility, viscosity, degree of polymerization etc. are determined by the atomic structure of the melt. Depending on the pressure, but also on the temperature and the chemical composition, silicate melts show different structural properties. These properties are best described by the local coordination environment, i.e. symmetry and number of neighbors (coordination number) of an atom, as well as the distance between the central atom and its neighbors (inter-atomic distance). With increasing pressure and temperature, i.e. with increasing depth in the Earth, the density of the melt increases, which can lead to changes in coordination number and distances. If the coordination number remains the same, the distance usually decreases. If the coordination number increases, the distance can increase. These general trends can, however, vary greatly, which can be attributed in particular to the chemical composition.
Due to the fact that natural melts of the deep earth are not accessible to direct investigations, in order to understand their properties under the relevant conditions, extensive experimental and theoretical investigations have been carried out so far. This has often been studied using the example of amorphous samples of the end-members SiO2 and GeO2 , with the latter serving as a structural and chemical analog model to SiO2. Commonly, the experiments were carried out at high pressure and at room temperature. Natural melts are chemically much more complex than the simple end-member SiO2 and GeO2, so that observations made on them may lead to incorrect compression models. Furthermore, the investigations on glasses at room temperature can show potentially strong deviations from the properties of melts under natural thermodynamic conditions.
The aim of this thesis was to explain the influence of the composition and the temperature on the structural properties of the melts at high pressures. To understand this, we studied complex alumino-germanate and alumino-silicate glasses. More precisely, we studied synthetic glasses that have a composition like the mineral albite and like a mixture of albite-diopside at the eutectic point. The albite glass is structurally similar to a simplified granitic melt, while the albite-diopside glass simulates a simplified basaltic melt. To study the local coordination environment of the elements, we used X-ray absorption spectroscopy in combination with a diamond anvil cell. Because the diamonds have a high absorbance for X-rays with energies below 10 keV, the direct investigation of the geologically relevant elements such as Si, Al, Ca, Mg etc. with this spectroscopic probe technique in combination with a diamond anvil cell is not possible. Therefore the glasses were doped with Ge and Sr. These elements serve partially or fully as substitutes for important major elements. In this sense, Ge serves as an a substitute for Si and other network formers, while Sr replaces network modifiers such as Ca, Na, Mg etc.,
as well as other cations with a large ionic radius.
In the first step we studied the Ge K-edge in Ge-Albit-glass, NaAlGe3O8, at room temperature up to 131 GPa. This glass has a higher chemical complexity than SiO2 and GeO2, but it is still fully polymerized. The differences in the compression mechanism between this glass and the simple oxides can clearly be attributed to higher chemical complexity. The albite and albite-diopside compositions partially doped with Ge and Sr were probed at room temperature for Ge up to 164 GPa and for Sr up to 42 GPa. While the albite glass is nominally fully polymerized like NaAlGe3O8, the albite-diopside glass is partially depolymerized. The results show that structural changes take place in all three glasses in the first 25 to a maximum of 30 GPa, with both Ge and Sr reaching the maximum coordination number 6 and ∼9, respectively. At higher pressures, only isostructural shrinkage of the coordination polyhedra takes place in the glasses. The most important finding of the high pressure studies on the alumino-silicate and alumino-germanate glasses is that in these complex glasses the polyhedra show a much higher compressibility than what can be observed in the end-members. This is shown in particular by the strong shortening of the Ge-O distances in the amorphous NaAlGe3O8 and albite-diopside glass at pressures above 30 GPa.
In addition to the effects of the composition on the compaction process, we investigated the influence of temperature on the structural changes. To do this, we probed the albite-diopside glass, as it is chemically most similar to the melts in the lower mantle. We studied the Ge K edge of the sample with a resistively heated and a laser-heated diamond anvil cell, for a pressure range of up to 48 GPa and a temperature range of up to 5000 K. High temperatures at which the sample is liquid and that are relevant for the Earth mantle, have a significant impact on the structural transformation, with a shift of approx. 30% to significantly lower pressures, compared to the glasses at room temperature and below 1000 K.
The results of this thesis represent an important contribution to the understanding of the properties of melts at conditions of the lower mantle. In the context of the discussion about the existence and origin of ultra-dense silicate melts at the core-mantle boundary, these investigations show that the higher density compared to the surrounding material cannot be explained by only structural features, but by a distinct chemical composition. The results also suggest that only very low solubilities of noble gases are to be expected for melts in the lower mantle, so that the structural properties clearly influence the overall budget and transport of noble gases in the Earth’s mantle.
Digital surveillance fiction
(2021)